Datasets:

taln-ls2n

/

pubmed

like 2

Eur_Radiol-2-2-1705545

Accuracy of dual-source CT coronary angiography: first experience in a high pre-test probability population without heart rate control

The aim of this study was to assess the diagnostic accuracy of dual-source computed tomography (DSCT) for evaluation of coronary artery disease (CAD) in a population with extensive coronary calcifications without heart rate control. Thirty patients (24 male, 6 female, mean age 63.1±11.3 years) with a high pre-test probability of CAD underwent DSCT coronary angiography and invasive coronary angiography (ICA) within 14±9 days. No beta-blockers were administered prior to the scan. Two readers independently assessed image quality of all coronary segments with a diameter ≥1.5 mm using a four-point score (1: excellent to 4: not assessable) and qualitatively assessed significant stenoses as narrowing of the luminal diameter >50%. Causes of false-positive (FP) and false-negative (FN) ratings were assigned to calcifications or motion artifacts. ICA was considered the standard of reference. Mean body mass index was 28.3±3.9 kg/m2 (range 22.4–36.3 kg/m2), mean heart rate during CT was 70.3±14.2 bpm (range 47–102 bpm), and mean Agatston score was 821±904 (range 0–3,110). Image quality was diagnostic (scores 1–3) in 98.6% (414/420) of segments (mean image quality score 1.68±0.75); six segments in three patients were considered not assessable (1.4%). DSCT correctly identified 54 of 56 significant coronary stenoses. Severe calcifications accounted for false ratings in nine segments (eight FP/one FN) and motion artifacts in two segments (one FP/one FN). Overall sensitivity, specificity, positive and negative predictive value for evaluating CAD were 96.4, 97.5, 85.7, and 99.4%, respectively. First experience indicates that DSCT coronary angiography provides high diagnostic accuracy for assessment of CAD in a high pre-test probability population with extensive coronary calcifications and without heart rate control. Introduction Recent advances in multi-detector-row computed tomography (CT) technology have continuously improved the quality of non-invasive coronary artery imaging. As a result, various studies have demonstrated a high accuracy of coronary angiography with 64-slice CT for the diagnosis of coronary artery disease (CAD) [1–8]. In particular, the high negative predictive value has made non-invasive coronary angiography using 64-slice CT a modality that allows significant coronary stenoses to be reliably excluded. Consequently, the Task Force on the Management of Stable Angina Pectoris of the European Society of Cardiology has recently recommended in their guidelines that CT coronary angiography be performed in patients with stable angina who have a low pre-test probability of CAD, and an inconclusive exercise electrocardiogram (ECG) or stress imaging test [9]. To date, many studies have been published assessing the diagnostic performance of CT coronary angiography with different generations of scanners. Four-slice CT coronary angiography showed limited resolution and required long breath-hold times of nearly 40 s, resulting in a high number of vessel segments that could not be assessed [10]. Sixteen-slice CT coronary angiography showed improved diagnostic accuracy because of reduced breath-hold times and an increased temporal and spatial resolution [11, 12]. Sixty-four-slice CT scanners were the first to allow highly accurate identification of significant coronary artery stenoses [1–8]. However, data analysis in several of these studies could not be performed in all coronary artery segments, with a percentage of non-assessable segments of up to 12% [2]. The main reasons were severe coronary artery wall calcifications and motion artifacts, the latter occurring especially with higher heart rates. Calcifications are known to complicate the assessment of coronary arteries [10], however, some authors have suggested that substantial coronary calcification should not be used as a reason to defer CT coronary angiography [13]. In order to reduce motion artifacts, the administration of either intravenous or oral beta-blocker medication for heart rate control has been proposed even for 64-slice CT systems [2–6, 8, 11, 14]. In most studies, target heart rates for scanning were below 60–65 beats per minute (bpm). Another concept to comply with higher coronary velocities at higher heart rates is the use of multi-segment reconstruction algorithms that combine data from two or more consecutive cardiac cycles to improve temporal resolution at certain heart rates [15]. However, the latter approach relies on a complete periodicity of heart motion, limiting its use in patients with variable heart rates; does not take into account the inter-heartbeat variability of coronary artery position; and requires low pitch factors, prolonging data acquisition times [16]. In line with this, a recent 64-slice CT study demonstrated no significant overall benefit of multi-segment reconstruction with regard to image quality of coronary arteries [17]. The recently introduced dual-source CT (DSCT) scanner is characterized by two x-ray tubes and two corresponding detectors mounted onto the rotating gantry with an angular offset of 90° [18]. Regarding cardiac imaging capabilities, the new scanner system offers a high temporal resolution of 83 ms in a mono-segment reconstruction mode. Temporal resolution is independent of the heart rate, which is a major difference from single-source CT systems that rely on multi-segment reconstruction techniques. The first feasibility studies have shown promising results with DSCT coronary angiography regarding image quality of coronary arteries, cardiac valves, and left ventricular myocardium independent of the actual heart rate of the patient [19, 20]. However, to date no study has investigated the diagnostic accuracy of DSCT coronary angiography for the diagnosis of CAD. The purpose of our study was to determine the performance of DSCT coronary angiography in diagnosing significant stenoses in comparison to invasive coronary angiography (ICA) in a high pre-test probability patient population without heart rate control. Materials and methods Patients In 30 patients (6 women, 24 men; mean age 63.1±11.3 years; age range 35–86 years) who had undergone ICA for evaluation of suspected CAD, CT coronary angiography was performed within 30 days of catheterization (mean 14±9 days). Exclusion criteria for DSCT were allergy to iodine-containing contrast medium, renal insufficiency (creatinine level>120 μmol/L), pregnancy, hemodynamic instability, and previous stent graft placement or bypass surgery. Symptoms and cardiovascular risk factors of all patients are reported in Table 1. Based on a previously published clinical pre-test score [21], each patient in this population had a high pre-test probability of CAD. Patients with elevated or irregular heart rates were not excluded from the study. The study protocol was approved by our local ethics committee and all participating patients gave written informed consent. Table 1Synopsis of cardiovascular risk factors and symptomsFrequency (%)Risk factorsFamily history16 (53%)Obesity23 (77%)Dyslipidemia18 (60%)Diabetes19 (63%)Smoking25 (83%)Hypertension23 (77%)SymptomsAngina pectoris21 (70%)Probable angina pectoris7 (23%)Atypical chest pain2 (7%) Dual-source CT scan protocol All CT examinations were performed on a DSCT scanner (Somatom Definition, Siemens Medical Solutions, Forchheim, Germany). The patients were centrally placed in the scanner to ensure that the entire heart was covered with the smaller field-of-view of the second tube detector array. Irrespective of the individual heart rate and the heart rate variability, no beta-blockers were given prior to the scan. Three patients took oral beta-blockers as part of their baseline medication. Nonenhanced DSCT for calcium scoring was performed from 1 cm below the level of the tracheal bifurcation to the diaphragm in a cranio-caudal direction using the following scanning parameters: detector collimation 32×0.6 mm, slice acquisition 64×0.6 mm by means of a z-flying focal spot, gantry rotation time 330 ms, pitch of 0.2–0.39 adapted to the heart rate, tube current 80 mAs per rotation, and tube potential 120 kV. Thereafter, all patients received a single dose of 2.5 mg isosorbiddinitrate s. l. (Isoket, Schwarz Pharma, Monheim, Germany) [22]. After 2 min, the coronary angiography scan was started by continuously injecting a bolus of 80 ml of iodixanol (Visipaque 320, 320 mg/mL, GE Healthcare, Buckinghamshire, UK) followed by 30 ml saline solution into an antecubital vein via an 18-gauge catheter (injection rate 5 mL/s). Contrast agent application was controlled by bolus tracking. A region of interest (ROI; mean diameter 10.1±5.6 mm, range 7.5–17.0 mm) was placed into the aortic root, and image acquisition started 5 s after the signal attenuation reached the predefined threshold of 100 Hounsfield units (HU). Data acquisition was performed from 1 cm below the level of the tracheal bifurcation to the diaphragm in a cranio-caudal direction with a detector collimation of 32×0.6 mm, slice acquisition 64×0.6 mm by means of a z-flying focal spot, gantry rotation time 330 ms, pitch of 0.2–0.43 adapted to the heart rate, tube current 400 mAs per rotation, and tube potential 120 kV. ECG-pulsing for radiation dose reduction was applied in all patients. At mean heart rates below 60 bpm, full tube current was applied from 60 to 70%, at 61–70 bpm from 50 to 80%, and at heart rates above 70 from 30 to 80% of the RR-interval. The electrocardiogram (ECG) was digitally recorded during data acquisition and was stored with the unprocessed CT dataset. Dual-source CT image reconstruction A retrospective gating technique was used to synchronize the data reconstruction with the ECG signal. A mono-segment reconstruction algorithm that uses the data from a quarter rotation of both detectors was used for image reconstruction [18]. In each patient, images were first reconstructed at 60 and 70% of the RR-interval. If considered necessary, additional images were reconstructed in 5% steps of the RR interval within the full tube current window. In case of irregular heart rates, the temporal variability in the reconstruction phase was compensated by manual ECG editing. In case of premature heart beats, the temporal window past the premature heart beat was deleted, and the next diastolic window was filled with one to three temporal windows to avoid data gaps. All ECG editing was performed by one experienced cardiovascular radiologist not involved in data read-out. For calcium scoring, non-overlapping images with a slice width of 3 mm were reconstructed using a medium-sharp convolution kernel (B35f). For DSCT coronary angiography, images were reconstructed from the contrast-enhanced DSCT scan with a slice thickness of 0.75 mm, a reconstruction increment of 0.5 mm, and using a medium soft-tissue convolution kernel (B26f). Depending on the individual anatomy, the reconstructed field-of-view (FoV) was adjusted to encompass the heart exactly (mean FoV 167±19 mm; range 131–187 mm; image matrix 512×512 pixels). After removing patient and ECG information, all reconstructed images were transferred to a dedicated workstation (Wizard, Siemens Medical Solutions) equipped with dedicated cardiac post-processing software (Syngo Circulation, Siemens Medical Solutions). Dual-source CT data analysis The mean Agatston score was calculated for each patient from the non-enhanced DSCT data with a detection threshold of 130 HU by using semi-automated software (Syngo Calcium Scoring, Siemens Medical Solutions). For analysis of DSCT coronary angiography data, coronary arteries were segmented according to the guidelines of the American Heart Association [23]. The right coronary artery (RCA) was defined to include segments 1–4, the left main and left anterior descending artery (LM-LAD) to include segments 5–10, and the left circumflex artery (LCX) to include segments 11–15. The intermedial artery was designated as segment 16, if present. All segments with a diameter of at least 1.5 mm at their origin were included. Diameter measurements were performed with an electronic caliper tool. Segments distal to an occluded vessel were excluded from analysis. All reconstructed images were evaluated and classified by two independent readers using axial source images, multi-planar reformations (MPR), and thin-slab maximum intensity projections (MIP) on a per-segment basis. Both readers semi-quantitatively assessed the image quality of each coronary segment on a four-point ranking scale as previously published [1]: 1, excellent (no artifacts, unrestricted evaluation); 2, good (minor artifacts, good diagnostic quality); 3, adequate (moderate artifacts, still acceptable and diagnostic), and 4, not assessable (severe artifacts impairing accurate evaluation). Causes of image degradation were noted by both observers as arterial wall calcifications, motion artifacts, or others. Motion artifacts were defined as any impairment of image quality caused by vessel movement resulting in blurred or doubled vessel contours. Other reasons included low vessel opacification, low signal-to-noise ratio, and disturbing adjacent structures such as contrast-enhanced cardiac veins. In addition, both readers assessed all coronary artery segments for the presence of hemodynamically significant stenoses. Significant stenosis was defined as narrowing of the coronary luminal diameter exceeding 50%. The vessel diameters were measured on reconstructions perpendicularly oriented to the vessel course. For any disagreement in data analysis, consensus agreement was achieved. Invasive coronary angiography ICA was performed according to standard techniques, and multiple views were stored on a CD-ROM. The angiograms were evaluated by one experienced observer who was blinded to the results of the DSCT coronary angiography. Coronary artery segments were defined according to the same guidelines mentioned above [23]. Each vessel segment was scored as being significantly stenosed, defined as a diameter reduction of >50% or not. Coronary artery analysis was performed in all vessels with a luminal diameter of at least 1.5 mm, excluding those vessels distal to complete occlusions. Statistical analysis Statistical analysis was performed using commercially available software (SPSS 12.0, SPSS, Chicago, IL, USA). Quantitative variables were expressed as mean±SD and categorical variables as frequencies or percentages. In a subanalysis, patients were subdivided into mean heart rates of <70 bpm and ≥70 bpm and into Agatston scores of <400 and ≥400. We took into account the clustered nature of the data (i.e., the fact that there were not 420 independent vessel segments but instead clusters of segments in 30 patients). Inter-observer agreements for image quality read-out and assessment of significant coronary artery stenoses were interpreted according to the guidelines of Landis and Koch [24] using the clustered data. Sensitivity, specificity, positive predictive value, and negative predictive value were calculated from chi-squared tests of contingency, and the 95% confidence intervals (CI) were calculated from binomial expression on a per-segment basis. Because of the interdependencies between different segments, the statistics were also calculated on a per-patient basis (presence of at least one significant coronary artery stenosis or absence of any significant stenosis in each patient). ICA was considered the standard of reference. Results DSCT and ICA were successfully performed in all patients without complications. The DSCT protocol was well tolerated by all patients, and all were able to hold their breath during data acquisition. The average HR during scanning was 70.3±14.2 bpm (range 47–102 bpm). Seventeen patients (56.7%) had a heart rate below 70 bpm (mean 59.7±5.9 bpm, range 47–66 bpm), while 13 patients (43.3%) had a heart rate of ≥70 bpm (mean 84.2±8.4 bpm, range 72–102 bpm). Prevalance of coronary artery stenosis and calcium score A total of 56 coronary artery stenoses with a luminal narrowing of more than 50% in diameter were identified in 15 patients (50.0%) using ICA. Single-vessel disease was present in 13.3% (4/30), two-vessel disease in 10.0% (3/30), and three-vessel disease in 26.7% (8/30). Significant coronary artery stenoses could be excluded in 15 patients (50.0%). Calcified vessel wall deposits were present in 24 patients (80%). Fourteen of these patients (58.3%) had significant coronary artery stenoses, while 10 patients (41.7%) had calcifications without significant stenoses. The mean Agatston score was 821±904 (range 0–3,110). Agatston score was <400 in 15 patients (50%, mean score 85±118) and ≥400 in the other 15 patients (50%, mean score 1,483±893). Image quality and image reconstruction intervals with DSCT A total of 420 coronary artery segments with a diameter ≥1.5 mm were evaluated (11 segments were missing because of anatomical variants, 26 segments had a diameter less than 1.5 mm at their origin, and 9 segments were distal to an occluding stenosis). An intermedial artery was present in 16 patients (53.3%). Inter-observer agreement for image quality rating using clustered data was moderate (kappa=0.68). The initially used reconstruction time-points of 60 and 70% provided excellent image quality (score 1) in 21.9% (92/420) and 60.2% (253/420), respectively, while additional reconstructions were necessary in 17.9% (75/420) to improve image quality. Whereas in the subgroup of patients with heart rates ≥70 bpm additional reconstructions at 30 to 50% were considered necessary in 27.4% (48/175), in patients with heart rates <70 bpm, the 60 and 70% interval provided excellent image quality (score 1) in 90.2% of the segments [30.2% (74/245) and 60.0% (147/245), respectively]. Using the individual reconstruction interval with best image quality for each segment, image quality was excellent (score 1) in 47.4% of the coronary segments (199/420), good (score 2) in 37.9% (159/420), adequate (score 3) in 13.3% (56/420), and poor/not assessable in 1.4% (6/420). Non-assessable (score 4) coronary artery segments (segment 4, n=2; segment 8, n=1; segment 10, n=2; and segment 14, n=1) were present in three patients with heart rates of 72, 77, and 86 bpm, and Agatston scores of 30, 616, and 0, respectively. In the 221 segments with image quality rated other than excellent (score 1), reasons for impaired image quality were arterial wall calcifications in 48.9% (108/221), motion artifacts in 46.6% (103/221), or other in 4.5% of segments (10/221; low signal-to-noise ratio, n=5; low vessel opacification, n=4; overlaying adjacent structures, n=1). At heart rates ≥70 bpm, minor to moderate motion artifacts accounted for 68.2% (73/107) of image quality impairment, while in patients with an Agatston score ≥400, severe arterial wall calcifications were mainly responsible for decreased image quality [76.4% (94/123)]. Diagnostic accuracy of DSCT in comparison to ICA The kappa value for coronary artery stenosis detection with DSCT was 0.83 indicating a good inter-observer agreement. DSCT coronary angiography correctly recognized 54 of the 56 significant stenoses (96.4%) detected with ICA. For both readers, nine false-positive (FP) and two false-negative (FN) ratings occurred with DSCT coronary angiography. Causes of FP and FN ratings were massive calcifications in nine segments (eight FP, one FN) and motion artifacts in two segments (one FP, one FN). The two FN ratings occurred in segments 8 and 9. Examples of three patients with suspicion of CAD who underwent DSCT coronary angiography are provided in Figs. 1, 2, and 3. Fig. 1a, bDual-source CT coronary angiography in a 62-year-old woman with suspected coronary artery disease (mean heart rate during scanning 76 bpm, Agatston score 0). a Curved thin-slab maximum-intensity projections through the centerline of the right coronary (RCA), left anterior descending (LAD), and left circumflex artery (LCX). Slight blurring of the mid-RCA and mid-LAD rendered image quality as good (score 2) in these segments, while image quality was rated excellent (score 1) in all other segments. Coronary artery disease could be reliably excluded in this patient. b Volume-rendered image of the left coronary arteries and of the proximal RCA (insert) demonstrates accurate depiction of the coronary artery treeFig. 2a, bDual-source CT coronary angiography in a 69-year-old man with suspected coronary artery disease (mean heart rate during scanning 77 bpm, Agatston score 1,316). a Curved-planar reconstruction of the right coronary artery demonstrates high-grade coronary artery stenosis of the proximal segment (arrow) and non-significant stenoses of the mid and distal segments (arrowheads). b Invasive coronary angiography in a left anterior oblique projection (45°) confirms significant stenosis of the proximal segment of the right coronary artery (arrow) and non-significant stenoses of the mid and distal segments (arrowheads)Fig. 3a, bDual-source CT scan in a 73-year-old man with suspected coronary artery disease (mean heart rate during scanning 86 bpm, Agatston score 259). a Thin-slab maximum-intensity projection shows stenosis of the distal right coronary artery near the origin of the posterior descending artery. This stenosis was rated significant (i.e., >50% luminal diameter narrowing) by both readers. b Invasive coronary angiography in a right anterior oblique projection shows irregular luminal narrowing in the distal right coronary artery that was qualitatively graded as less than 50% luminal diameter narrowing, resulting in a false positive diagnosis in DSCT coronary angiography On a per-segment analysis, overall sensitivity was 96.4% (54/56; 95% CI: 87.7–99.6), specificity was 97.5% (355/364; 95% CI: 95.4–98.9), positive predictive value was 85.7% (54/63; 95% CI: 74.6–93.3), and negative predictive value was 99.4% (355/357; 95% CI: 98.0–99.9). Table 2 summarizes demographic data, overall image quality, and diagnostic accuracy of DSCT. Table 2Demographic data, overall image quality, and diagnostic accuracy  Mean heart rateAgatston score Total<70 bpm≥70 bpm<400≥400No. of patients3017131515Age (years)63.1±11.363.2±10.162.9±13.362.8±13.763.4±8.9Male/female24/615/29/410/514/1BMI (kg/m2)28.3±3.928.9±4.327.6±3.528.1±3.528.5±4.4Mean heart rate (bpm)70.3±14.259.7±5.984.2±8.470.6±13.770.0±15.1Agatston score821±904901±991674±78085±1181,483±893Overall image qualitya1.68±0.751.60±0.731.81±0.771.59±0.751.79±0.75 Score 147.4% (199/420)51.8% (131/245)38.9% (68/175)54.2% (116/214)40.3% (83/206) Score 237.9% (159/420)32.4% (82/245)44.0% (77/175)35.5% (76/214)40.3% (83/206) Score 313.3% (56/420)11.9% (30/245)14.9% (26/175)7.5% (16/214)19.4% (40/206) Score 41.4% (6/420)0.8% (2/245)2.2% (4/175)2.8% (6/214)–Sensitivity96.4% (54/56)97.2% (35/36)95.0% (19/20)100% (5/5)96.1% (49/51)  95% CI87.7–99.685.5–99.975.1–99.947.8–10086.5–99.5Specificity97.5% (355/364)97.1% (203/209)98.0% (152/155)99.5% (208/209)94.8% (147/155) 95% CI95.4–98.994.2–98.894.5–99.697.4–10090.1–97.8PPV85.7% (54/63)85.4% (35/41)86.4% (19/22)83.3% (5/6)86.0% (49/57) 95% CI74.6–93.370.8–94.465.1–97.135.9–99.674.2–93.7NPV99.4% (355/357)99.5% (203/204)98.8% (152/153)100% (208/208)98.7% (147/149) 95% CI98.0–99.997.3–10096.4–10098.2–10095.2–99.8aApplied scores were 1 excellent (no artifacts), 2 good (minor artifacts, good image quality), 3 adequate (moderate artifacts, acceptable image quality), and 4 not assessable (severe artifacts impairing image evaluation). A score of 1–3 was considered acceptable for diagnosis.BMI Body mass index, CI confidence interval, PPV positive predictive value, NPV negative predictive value On a per-patient analysis, sensitivity was 93.3% (14/15; 95% CI: 68.1–99.8), specificity was 100% (15/15; 95% CI: 78.2–100), positive predictive value was 100% (14/14; 95% CI: 76.8–100), and negative predictive value was 93.8% (15/16; 95% CI: 69.8–99.8). In both heart-rate subgroups, diagnostic accuracy for the assessment of coronary artery stenosis was similar and the rate of false ratings was comparable (one FN and six FP at heart rates <70 bpm; one FN and three FP at heart rates ≥70 bpm). In contrast, the subgroup of patients with an Agatston score ≥400 included more false ratings (two FN and eight FP) than the subgroup of patients with an Agatston score <400 (zero FN and one FP). Consequently, sensitivity and specificity were worse in severely calcified vessels (see Table 2). Discussion Four main conclusions can be drawn from this study. First, DSCT coronary angiography provides a high diagnostic accuracy for the evaluation of CAD. Second, this high diagnostic performance of DSCT could be achieved in a patient population with extensive calcifications and in whom no heart rate control using beta blocker medication prior to CT was performed. Third, taking into account these circumstances, only six (1.4%) segments had to be excluded from data analysis, all in the distal part of the coronary artery tree with small vessel diameters. Fourth, false ratings were primarily due to severe vessel wall calcifications rather than motion artifacts. Temporal resolution better than 100 ms in combination with submillimeter isotropic spatial resolution and examination times no longer than 10 s are considered prerequisites for successful implementation of cardiac CT into routine clinical algorithms [18]. DSCT scanners with 0.33-s gantry rotation time and 32×0.6 mm collimation in combination with double z-sampling (i.e., simultaneous acquisition of 64 overlapping 0.6-mm slices) fulfill these requirements. Early feasibility studies confirmed the technical capacity of DSCT to provide diagnostic image quality of coronary arteries in patients with high heart rates [19, 20]. This study is, to the best of our knowledge, the first to demonstrate a high diagnostic accuracy of DSCT coronary angiography for the diagnosis of CAD in comparison to ICA. By including a patient population with a high prevalence of coronary calcification and without heart rate control during scanning, we found an overall sensitivity of 96.4% and specificity of 97.5% for the detection of significant coronary stenoses. These results are comparable to those previously reported with 64-slice CT; however, beta-blocker administration for strict heart rate control was needed in those studies to compensate for motion artifacts. By including patients with heart rates up to 102 bpm, we found minor to moderate vessel wall blurring due to motion artifacts to be present at high heart rates; however, only 1.4% of all segments had to be excluded from analysis because they were non-diagnostic. Further confirmation of our preliminary results in larger patient populations may broaden the clinical indications for CT coronary angiography from a modality that is recommended for ruling-out CAD in patients with a low pre-test probability [9] to use in populations with intermediate- or even high pre-test probabilities of the disease. This might also include the implementation of CT coronary angiography as a tool for preoperative planning before cardiac bypass surgery [25] and as a gatekeeper for invasive angiography in patients referred for cardiac valve surgery [26]. Our patient population had a high prevalence of coronary wall calcification, with a mean Agatston score of 821—being higher than the 75% percentile in an age- and gender-matched control population [27]. With 64-slice CT, Raff et al. [2] reported a considerable decline in diagnostic accuracy in patients with Agatston scores >400 with a sensitivity of 93%, a specificity of 67%, and positive and negative predictive values of 93 and 67%, respectively. Using the same cut-off Agatston score, we found a sensitivity of 96%, a specificity of 95%, and positive and negative predictive values of 86 and 99%, respectively. Considering that the spatial resolution of DSCT is the same as that of the single-source 64-slice CT scanner, this apparent difference in calcification-dependency could indicate that the blooming artifact of severely calcified vessel walls may be sometimes superimposed by additional motion artifacts. We acknowledge the following study limitations. First, we included a relatively small group of only 30 patients. Certainly, future studies with larger patient populations are needed to confirm our first experience. Second, our study patients were a high pre-test probability population, which may have resulted in an overestimation of the ability of DSCT to detect and to rule-out stenoses. In particular the predictive value of positive and negative diagnostic tests is known to be strongly influenced by disease prevalence and pre-test probability. Third, we did not apply the multi-segment reconstruction mode, which possibly may further improve the image quality at elevated heart rates. Fourth, CT coronary angiography is associated with substantial irradiation to the patient. However, using the DSCT system allowed the variable use of ECG-pulsing for dose-saving purposes [28] in all of our patients. In the protocol applied in this study, the ECG-pulsing window width was chosen according to the mean heart rate during scanning, i.e., a relatively narrow window width at low and a larger window width at higher heart rates. As previously performed for 64-slice CT [17, 29], studies analyzing optimum reconstruction intervals for DSCT coronary angiography are mandatory to reduce the width of the pulsing window and the applied radiation dose further. Finally, the ability to use the two x-ray tubes simultaneously with different voltages to improve plaque composition characterization [30] and thus potentially to improve the accuracy of stenosis detection has not been investigated. Conclusion First experience indicates that DSCT coronary angiography provides high diagnostic accuracy for assessment of CAD in a high pre-test probability population with extensive coronary calcifications and without heart rate control. Further studies are needed to confirm our results in appropriate clinical settings with larger patient populations.

J_Antimicrob_Chemother-1-1-2386081

Microbiological evaluation of a new growth-based approach for rapid detection of methicillin-resistant Staphylococcus aureus

Objectives Recently, a rapid screening tool for methicillin-resistant Staphylococcus aureus (MRSA) has been introduced that applies a novel detection technology allowing the rapid presence or absence of MRSA to be determined from an enrichment broth after only a few hours of incubation. To evaluate the reliability of this new assay to successfully detect MRSA strains of different origin and clonality, well-characterized S. aureus strains were tested in this study. Introduction The increasing numbers of multidrug-resistant Gram-positive pathogens have generated worldwide concern in the medical community. In particular, methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of disease and healthcare expenditures in almost every continent. The emergence and spread of MRSA has been shown to be associated with both hospital- and community-acquired infections. Effective treatment options for these infections are limited and the situation may become more severe soon. For these reasons, a proactive management of MRSA in healthcare facilities is needed.1,2 Active screening and compliance to appropriate infection control activities have been shown to play an important role in the control of MRSA.1 Rapid diagnostic tests have the potential to make efforts even more effective. Thus, infection prevention has taken a step forward with the introduction of various tests for rapid identification of MRSA carriers.1,2 In 2006, a new rapid method based on a novel bioluminescence detection technology for the rapid detection of MRSA directly from specimens was published.3 An improved version of this assay, the 3M™ BacLite™ Rapid MRSA Test (3M Company, Maplewood, MN, USA), was recently introduced, which allows the presence or absence of MRSA to be determined within 5 h. Although the clinical performance has been previously analysed,4,5 so far no data are available on the detection of MRSA strains with highly diverse genetic backgrounds. The aim of this study was to assess the reliability of this assay to successfully detect MRSA strains circulating currently in Germany and other parts of Europe on the basis of several well-characterized S. aureus strain collections. For this purpose, S. aureus strains of different origin and clonality comprising 724 methicillin-susceptible and methicillin-resistant strains comprising >90% of all registered European MRSA spa types within the SeqNet network (www.SeqNet.org) were tested in this study. Materials and methods All staphylococcal strains were freshly isolated from clinical material at the University of Münster or during the course of various multicenter studies. One hundred and sixty-four strains isolated from patients with S. aureus bacteraemia (including 12 MRSA strains) as well as 50 isolates from the anterior nares of patients who did not subsequently develop S. aureus bacteraemia in a subsequent observation period (4 MRSA strains), were included into this study. Apart from 28 isolates from 14 patients (S. aureus first recovered from the anterior nares and subsequently from blood, one infected with MRSA), only one isolate per patient was tested. In addition, 96 MRSA strains, each presenting a unique spa type, were selected from our institutional collection (Table 1). Furthermore, four hundred MRSA isolates were collected during the course of a recent multicenter study, also including community-acquired MRSA. In total, the 724 S. aureus strains tested comprised 211 methicillin-susceptible S. aureus (MSSA) and 513 MRSA strains. Table 1 Grouping of spa types tested in this study into spa clonal complexes (spa-CCs) spa-CCa spa typesb Putative MLST typesc 001 t001, t002, t003, t010, t035, t039, t041, t045, t055, t057, t066, t105, t106, t109, t110, t143, t149, t151, t264, t265, t422, t820, t892, t1018 ST-5, ST-45, ST-46, ST-222, ST-225, ST-228, ST-231, ST-111, ST-228 004 t004, t028, t029, t033, t040, t043, t061, t065, t141, t142, t266, t911 ST-45, ST-45, ST-46 015 t015, t031, t069, t073, t102, t116, t133 ST-45 024 t008, t009, t024, t036, t051, t052, t068, t113, t115, t139, t146, t243, t305 ST-8, ST-235, ST-247, ST-250, ST-254, ST-247, ST-250 032 t005, t022, t032, t107, t290, t379, t432, t794 ST-22, ST-23, ST-60 037 t011, t030, t037, t047, t108, t135, t137, t138 ST-30, ST-239, ST-240, ST-241, ST-246 038 t038, t161, t247 ST-45 044 t042, t044, t131 ST-80 Singletons t012, t091, t101, t104, t163, t321, t372, t417, t431, t907 ST-7, ST-30, ST-22 aNaming of spa-CC was derived from the group founder. bt026, t103, t111, t132, t145, t282, t322 and t1007 were excluded from determination of the spa-CCs due to low number of repeats. cPutative MLST types were taken from the public SeqNet.org spa server database. If the biochemical identification of staphylococcal isolates using the ATB 32 Staph gallery (bioMérieux, Marcy l’Étoile, France) was ambiguous or categorized as unacceptable, partial 16S rRNA gene and RNA polymerase B (rpoB) gene sequencing was performed as described previously.6 Isolates were confirmed to be methicillin-resistant by detection of the mecA gene. To determine the clonal lineages of MRSA strains, the x region of the spa gene was amplified by PCR with primers 1095F (5′-AGACGATCCTTCGGTGAGC-3′) and 1517R (5′-GCTTTTGCAATGTCATTTACTG-3′). DNA sequences were obtained with an ABI 377 sequencer (Applied Biosystems, Foster City, CA, USA). spa types were determined using the Ridom StaphType software version 1.3 (Ridom GmbH, Würzburg, Germany), and spa clonal complexes (spa-CCs) were assigned by using the BURP algorithm.7 The 3M™ BacLite™ Rapid MRSA Test is a novel culture-based test for the detection of MRSA performed on a semi-automated system comprising a sample processor and a luminometer. The assay consists of three successive selectivity steps: selective enrichment in a proprietary broth containing cefoxitin (2 mg/L) and colistin (50 mg/L), immuno-magnetic extraction using a highly specific anti-S. aureus monoclonal antibody and selective lysis using lysostaphin. The selectivity steps are followed by a detection step using a highly sensitive cell marker, adenylate kinase (AK). AK is an essential enzyme found in all living cells, which regulates energy provision by catalysing the equilibrium reaction ATP + AMP = 2 ADP. By supplying a continual source of purified ADP, this assay drives the AK reaction to generate up to 40 000 ATP molecules per min. These amplified levels of ATP are measured using the luminometer supplied with the system. For the present study, test isolates were streaked on sheep blood agar plates and grown at 37°C to confirm purity. For each isolate, one to three colonies were picked and suspended in sterile saline (0.9%) to achieve a turbidity equivalent to that of a 0.5 McFarland standard. Usually, 43 isolates were processed in each run. The 3M™ BacLite™ Rapid MRSA Test was performed according to the instructions of the manufacturer. In brief, 10 µL of each prepared bacterial suspension was transferred into a vial containing 1 mL of selective enrichment broth. Vials were incubated at 37°C for 2 h before 150 µL aliquots of each test sample were transferred into two adjacent wells of a 96-well assay plate, each containing 20 µL of capture reagent. MRSA cells bound to the monoclonal antibody on the capture reagent were then extracted from the sample matrix using the sample processor and concentrated in 100 µL of broth. One well for each sample was processed automatically for a baseline signal (T0) in the BacLite luminometer. After a further incubation period of 2 h at 37°C, the second well for each sample was processed in the same way (T2 reading). Results are expressed in relative light units and interpreted as either a positive or negative screen result by a software embedded algorithm. Positive and negative controls as well as reagent and broth controls were included in each test run. A run took ∼5 h with a total hands-on time of 45–50 min (<1.5 min per tested isolate). Results and discussion Analysing a total of 724 S. aureus strains, all 513 MRSA strains tested were recognized as MRSA, whereas none of the 211 MSSA strains was detected positive by the 3M™ BacLite™ Rapid MRSA Test. These results are particularly impressive as the institutional MRSA strain collection used in this study represents more than 90 different spa types covering >90% of all registered European MRSA spa types within the SeqNet network (Table 1). Beside several singletons, the MRSA enrolled in this study were grouped into eight spa clonal complexes (Table 1). Thus, a very large number of MRSA strains with different genetic backgrounds were recognized as MRSA using this novel method. Hospitals and other healthcare facilities across the world are faced with alarming rates of infections caused by MRSA. Continuous spread of these pathogens requires efficient strategies for infection control. Early identification of MRSA carriers among hospitalized patients is crucial to prevent its spread.1 Therefore, rapid availability of laboratory results is of utmost importance. However, conventional screening methods require prolonged incubation and confirmatory testing. During this time, MRSA-negative patients may be held in unnecessary isolation, whereas unidentified MRSA-positive individuals remain a hidden reservoir for cross-infection. A rapid negative result should allow more effective use of hospital isolation resources, whereas a rapid positive result should help reduce the spread of the infection and MRSA infection rates.2 In the past few years, several in-house and commercial rapid MRSA assays based on molecular techniques have been introduced for the detection of this pathogen directly from the specimen, mostly from the anterior nares. The first molecular assays developed were based on the detection of an S. aureus-specific sequence and the mecA gene, which encodes methicillin resistance.8 These tests are difficult to use for the direct detection of MRSA from non-sterile specimens, such as nasal samples, because of the likely co-presence of MSSA and methicillin-resistant coagulase-negative staphylococci.9 In a setting of low prevalence of MRSA, a molecular test targeting the mecA and an S. aureus-specific gene in parallel applied directly to clinical specimens would result in a high number of false positives and unacceptable performance.9 This technical limitation has been overcome in some assays, by linking detection of the presence of the mecA gene with detection of the neighbouring chromosome-borne orfX gene.10,11 In that approach, regions near the integration site of SCCmec were targeted as surrogate markers instead of the mecA gene itself. However, these flanking regions are known to be more heterogeneous than assumed so far.10 Thus, false-negative results due to variations within the primer binding sites may occur. Moreover, false-positive results due to the detection of DNA from non-viable MRSA, deletions or replacement of the mec region in vivo or ‘ghost sequences’ such as partial SCCmec sequences in MSSA can occur, albeit their incidence in the routine clinical setting is as yet unclear.12 Despite the technical improvements in recent molecular-based assays, their high costs and relatively high operator skill requirement remain obstacles to their widespread routine use. The ability of a test to detect a broad range of MRSA clones is particularly important for an assay that may be used across a wide geographic region as tests with gaps in detection could potentially ‘select out’ strains whose spread would be uncontrolled. Beside a variety of method-inherent limitations, rapid DNA-based methods amplify the nucleic acid and not the organism, which means the MRSA strain is unavailable for further characterization, such as determination of the resistance profile and strain typing. In contrast, applying the rapid growth-based assay tested here, any further examinations to characterize the respective strains will be possible from the enrichment broth. For the 3M™ BacLite™ Rapid MRSA Test, a diagnostic sensitivity of 94.6% and diagnostic specificity of 96.9% for nasal screening swabs and 95.9% sensitivity and 88.8% specificity for groin screening swabs, respectively, have been reported.4,5 The analytical limit of detection of the assay was shown to be ≤94 cfu (3M™ BacLite™ Rapid MRSA Test, Instructions for Use).4,5 Here, the new growth-based rapid MRSA assay was shown to detect without exception all MRSA strains of large collections of strains comprising highly diverse genetic backgrounds. Such a phenotypic test might be potentially more likely to cope with new strains. Further studies are warranted to evaluate this method using clinical specimens. Funding This work was supported in part by a grant from the Bundesministerium für Bildung und Forschung (BMBF), Germany (Pathogenomic Plus Network PTJ-BIO/0313801B). The device and the respective assay consumables were given to us by 3M for this study. Transparency declarations Two of the authors (A. W. F. and K. B.) delivered independent scientific presentations at 3M-supported symposia. C. v. E. is a member of 3M’s Scientific Advisory Board. All other authors: none to declare.

Bioprocess_Biosyst_Eng-2-2-1705473

On-line optimization of glutamate production based on balanced metabolic control by RQ

In glutamate fermentations by Corynebacterium glutamicum, higher glutamate concentration could be achieved by constantly controlling dissolved oxygen concentration (DO) at a lower level; however, by-product lactate also severely accumulated. The results of analyzing activities changes of the two key enzymes, glutamate and lactate dehydrogenases involved with the fermentation, and the entire metabolic network flux analysis showed that the lactate overproduction was because the metabolic flux in TCA cycle was too low to balance the glucose glycolysis rate. As a result, the respiratory quotient (RQ) adaptive control based “balanced metabolic control” (BMC) strategy was proposed and used to regulate the TCA metabolic flux rate at an appropriate level to achieve the metabolic balance among glycolysis, glutamate synthesis, and TCA metabolic flux. Compared with the best results of various DO constant controls, the BMC strategy increased the maximal glutamate concentration by about 15% and almost completely repressed the lactate accumulation with competitively high glutamate productivity. Introduction For more than a few decades, the Corynebacterium spp. bacteria have been used for amino acids productions, including the commercially important products of glutamate, glutamine, and lysine. Among the amino acids mentioned earlier, L-glutamate is the largest fermentative product, which occupies about 53% of the world’s amino acids market [1]. It is also particularly important in food industries and widely used as an important starting substance for the synthesis of various and useful pharmaceutical and healthy products. The previous research works [2–4] have revealed that primary by-products, such as lactate, accumulated during L-glutamate fermentation if the operating condition was improperly controlled, which in turn deteriorated the fermentation performance in terms of both glutamate productivity and yield. To cope with the problem, the metabolic reaction network (flux) model (MR model) or technique, as its appearance in the early 1990s, has been recognized as an useful system analysis tool and thus widely used in those areas such as metabolic flux distribution analysis [2, 5], determination of the bottleneck controlling the targeted metabolic product formation [6, 7], recognition of fermentation phases [8], and calculation of theoretical or maximum yields [9, 10], etc. However, the research reports of using MR model for on-line physiological state prediction or process control are very limited [3, 11, 12], and the study stayed on on-line recognition of different fermentation phases or physiological states so as to provide information for the subsequent process control, such as whether substrate should be added or whether the fermentation should be terminated [11], determination of glucose feeding rate to avoid the acetate or ethanol overproduction in Escherichia coli or Saccharomyces cerevisiae fed-batch cultivation [12], etc. Optimization of fermentation processes by MR model was mostly limited on using the feed-forward type’s off-line control strategy with the MR model as the constraint conditions [13–14]. On the other hand, analysis of key enzymes in metabolic network of cells was also very important, as those key enzyme generally play important roles in regulating and overproducing the targeted metabolic products. As a result, extensive research works with regard to the enzymes activities under different operating conditions have been carried out. Among them, the enzymes activities in fermentation by Corynebacterium glutamicum such as the influence of NH4+ concentration on C. glutamicum growth and glutamate dehydrogenase (GDH) [15], activity of phosphoenolpyruvate carboxylase responsible for the anaplerotic reactions in lysine continuous production by C. glutamicum under different dilution rates [16, 17], as well as lactate dehydrogenase (LDH) for pyruvate overproduction under different dilution rates with lactate as the sole carbon source [18], were investigated. The metabolic network models were also built for C. glutamicum under different operating conditions, aiming at achieving metabolic flux distribution information concerning the overproduction of targeted metabolites or substrate utilization [17–19], as well as on-line prediction of the targeted products formation and analysis of the entire metabolic fluxes [3]. In our previous study [3], we found that dissolved oxygen (DO) largely affected the metabolic flux distribution and the glutamate fermentation performance. The comprehensive analysis or evaluation of a fermentation process by the MR model-based metabolic flux analysis integrated with the intracellular enzymes activities monitoring, might gain a deeper insight into the entire fermentation process and the metabolic regulation mechanisms, so as to supply a more comprehensive and accurate information base for the subsequent process control and optimization of the fermentation process. In this study, combining our previous study on on-line metabolic flux analysis of the glutamate fermentation by C. glutamicum, the two major enzymes (GDH and LDH), which possibly dominated the overall glutamate metabolism, were carefully investigated. Then, based on the comprehensive evaluation results of both the metabolic flux analysis and intracellular enzymes activities monitoring, a new optimization strategy of “balanced metabolic control (BMC)” was proposed and verified experimentally, aiming to increase the glutamate production yield, while completely repressing the by-product overproduction simultaneously. Materials and methods Microorganism and fermentation conditions Corynebacterium glutamicum S9114, kept by the laboratory was used throughout this study. The same medium and seed culture conditions described in our previous study [3] were used. Corynebacterium glutamicum S9114 was cultured for glutamate production at 32°C in a 5 L fermentor (BIOTECH-5BG, Baoxing Co., China) containing about 3.4 L medium. Concentrated glucose was fed based on requirement to ensure the substrate concentration above a suitable level (15 g/L) throughout the fermentation period. pH was controlled at 7.1 ± 0.1 by automatic addition of 25% (w/w) ammonia water which also supplied the nitrogen source required for glutamate synthesis. DO was controlled at various levels by automatically or manually controlling the agitation speed based on particular requirements. The air aeration rate and fermentor pressure were kept constantly at 1.60 vvm and 0.07 MPa, respectively. Analytical methods The concentrations of cells, glucose, glutamate, and lactate were measured with the same methods as reported in our previous study [3]. The CO2 and O2 concentrations (partial pressure) in the inlet and exhaust gas were on-line measured by a gas analyzer (LKM2000A, Lokas Co. Ltd, Korea). The collected on-line data were smoothly filtered, and then oxygen uptake rate (OUR) and CO2 evolution rate (CER) were on-line calculated based on the literature reported method [20]. Respiratory quotient (RQ) was determined by its definition (RQ = CER/OUR) using the on-line measured OUR and CER data. Extraction and assay of the GDH and LDH The two key enzymes dominating glutamate fermentation and metabolism, the NADPH and NADH dependent GDH and LDH were detected by spectrophotometric method, and the relevant stoichiometric reactions could be written as follows: The enzymes in the reverse direction of glutamate and lactate consumption were not considered and assayed in this case. Cells were collected by centrifugation and then suspended in 25 mmol/L Tris–HCl buffer, pH 7.5. The suspension was sonicated by a sonifier (JY92-II, Scientz Biotechnology Co., China) at 0°C for a total period of 10 min (pulse on, 1 s; pulse off, 3 s). Cell debris was removed by centrifugation at 9,400g, 4°C, for 20 min, the supernatant was then used as the cell-free crude enzyme. GDH was assayed with a spectrophotometer (UV-2100, Unico, Shanghai, China) at 340 nm by measuring the optical variation within 1 min, with 0.05 mL supernatant and 2.95 ml GDH reaction mixture consisting of 13.3 mmol/L α-ketoglutaric acid, 15 mmol/L NH4Cl, and 1.67 mmol/L NADPH (Sigma Chemical Co., St Louis, MO, USA) in phosphate buffer (pH 7.5) at 37°C. LDH was assayed in the same condition but with the LDH reaction mixture containing 0.757 mmol/L pyruvic acid and 1.67 mmol/L NADH (Sigma Chemical Co., St Louis, MO, USA). Protein was measured by Bradford method with bovine serum albumin as the standard. Enzyme-specific activity (GDH or LDH) was expressed as units/mg-protein, where 1 U was defined as the quantity of enzyme that converted 1 μmol of NAD(P)H per minute. On-line control system The on-line measured RQ data were sent to a PC in which a control program written with Visual-Basic (Microsoft Inc., USA) was embedded. Based on the RQ set-points and the measured RQ, the PC on-line regulated the agitation rate of the fermentor (AGT) with a discrete PI control manner described by Eq. 3 , which renewed the agitation rate at an interval of 5 min. In Eq. 3, k represented the current control instant; RQset was the RQ set-point which might be subject to changes during the control; KC and τI were proportional and integral constants of the feedback controller, respectively. KC and τI were determined by Coon–Cohen method by observing the RQ response to a step change in the input (agitation rate) during a certain period of the glutamate production phase. Results and discussion The changing patterns of glutamate and lactate production, as well as the GDH and LDH activities at different DO control levels Constant control of DO is generally considered as the simplest optimization control method for the aerobic fermentations with aeration. Fig. 1a, c, d showed the time courses of glutamate, lactate, cells, and residual glucose concentrations when DO was constantly controlled at 10 and 50% (saturation level), respectively. The results showed that, glutamate and lactate formation pattern strongly depended on the DO control level. A higher glutamate production rate could be achieved when the DO was controlled at a lower level of 10% and the final glutamate concentration reached about 91.5 g/L at 34 h, while the final glutamate concentration stopped at a lower level of 72.7 g/L (30 h) when controlling DO at 50%. On the other hand, lactate severely accumulated up to 28 g/L when DO was controlled at a lower level of 10%, while almost no lactate accumulation occurred when controlling DO at 50%. These results suggested that the enzymatic activities of GDH and LDH under lower and higher DO level might be quite different.Fig. 1Time courses of glutamate, lactate, cells and glucose concentrations, as well as the key enzymes activities at different DO control levels. a Glutamate concentration: (filled circle) DO 10%, (filled triangle) DO 50%; lactate concentration: (open circle) DO 10%, (open triangle) DO 50%. b GDH activity: (filled circle) DO 10%, (open circle) DO 50%; LDH activity: (filled triangle) DO 10%, (open triangle) DO 50%. c Cells concentration: (filled circle) DO 10%, (filled triangle) DO 50%. d Glucose concentration: (filled circle) DO 10%, (filled triangle) DO 50% Figure 1b indicated the changing pattern of the GDH and LDH activities under the same DO control levels. The GDH activity for the lower DO case (10%) was much higher and declined slower than that of the higher DO case (50%) after experiencing the enzymatic activity peak of about 1.8 U/mg-protein around 12–13 h. This result could at least explain or account for the fact that, higher glutamate production rate and accumulation occurred at lower DO control level in the initial and middle production phases of 8–20 h. The slow down of glutamate production rate in the late production stage (20–30 h) and the final stoppage of glutamate production were due to the reduction of the co-enzyme NADPH regeneration rate, which will be further discussed in the following section. As for the LDH activities, from the result of severe lactate’s accumulation at lower DO level, it was speculated that the LDH activity under lower DO level (10%) should also be much higher than that of the higher DO case. However, the result did not agree with the expectation. Although the LDH activity under lower DO level was slightly higher than that of the higher DO for the majority of the fermentation period, this result could not stand for the large difference in the lactate accumulation under different DO levels. It should be noted that the cell concentration could reach a constant and stabilized level of about 20 g/L prior to production phase (Fig. 1c) for all of the constant DO control cases, therefore using the unit of “U/mg-protein” could actually reflect the total enzyme activity. The changing patterns of glutamate and lactate production, as well as the GDH and LDH activities at anaerobic fermentation condition Generally, it is considered that the anaerobic condition is extremely harmful to glutamate production. To verify the above speculation, an experiment under extremely low DO level was conducted. In the fermentation, DO was initially controlled at 30%, and the agitation rate was manually reduced to bring DO down to 0% instantly at 12 h. Then, the same agitation rate was kept for the next 6 h. During this period, the fermentation could be considered as implemented under anaerobic condition, glutamate production stopped and lactate overflowed as shown in Fig. 2a. At 18 h, the automatic control of DO was resumed to quickly bring DO back to 30%, a partial recovery of glutamate production was observed. However, the final glutamate concentration ended at a very low level of about 45 g/L. As shown in Fig. 2b, during the anaerobic period, GDH activity sharply dropped to a level of 0.87 U/mg from the original 1.86 U/mg, and could not be recovered again even when DO was resumed back to 30% level. The results indicated that the occurrence of anaerobic condition even for a short period would be both fatal and irretrievable to glutamate fermentation.Fig. 2The changing pattern of the products formation and the key enzymes activities when DO control level was subject to a sudden change during 12–18 h, and maintained at extremely low level during the period. a The changing patterns of glutamate and lactate concentrations, as well as the DO control level, filled circle: glutamate concentration, open triangle: lactate concentration, solid line: DO. b The changing patterns of the key enzyme activities, filled circle: GDH activity, open triangle: LDH activity The glucose consumption rates (glycolysis rates) at different DO control levels Figure 3 showed the average glucose consumption rates under different DO control levels during the production phase. Apparently, under regular (aerobic) fermentation, the glycolysis rate did not depend on the DO control level, and the changing patterns of glycolysis rate at different DO levels were basically the same.Fig. 3The time courses of glucose consumption rate at different DO levels. Open circle: DO = 10%, batch no. 050331; open triangle: DO = 50%, batch no. 050407 The mechanism analysis of lactate overflow and the control strategy of BMC For the purpose of easily interpreting the experimental results, the metabolic flow chart of glutamate fermentation by C. glutamicum as shown in our previous study [3] was simplified and re-depicted in Fig. 4. The metabolic fluxes changes at 10, 20, and 30 h of the fermentations with the DO constant controls (10, 50%) and BMC were also depicted. As shown in the map, glucose was converted into pyruvate through EMP pathway, and supplemented with PP pathway to produce NADPH for structuring glutamate synthesis precursors by cells. The pyruvate formed either entered TCA cycle via pyruvate dehydrogenase, generating the energy as well as co-enzyme substances such as ATP, NADH, etc. for the entire metabolic network operations, or was converted into lactate with LDH as the enzymatic catalyst (r5, Eq. 2). At α-KG (α-ketoglutaric acid) node of TCA cycle, the glutamate synthesis reaction (r6) with GDH as the enzymatic catalyst (Eq. 1) occurred. As shown in Fig. 4, with the constant DO control strategy, the decrease of the DO control level enhanced the metabolic fluxes of both glutamate and lactate formation; while the metabolic flux of TCA after the α-KG node (r4) sharply decreased, and the TCA cycle was almost completely shut down when controlling DO at 10% level (also refer to Fig. 5).Fig. 4Simplified metabolic flow chart and the relevant metabolic fluxes changes during the fermentations. Broken line: very low metabolic flux or channels shut down; solid line: moderate metabolic flux; bold solid line: enhanced metabolic flux. a: at 10 h; b: at 20 h; c: at 30 hFig. 5Comparison of RQ and calculated TCA metabolic flux rate at different DO control levels A higher enzyme activity in vivo reflects a higher potential in reaction rate catalyzed by the enzyme. However, it never means that the relevant reaction rate must be high, as the reaction rate also depends on other factors, such as the coenzyme (NADPH, NADH) activity as well as the reactant concentration. As shown in Fig. 1a, b, at the end of the fermentation, the glutamate synthesis completely stopped even though GDH activity still remained at a higher level. The calculation results in our previous report [3] showed that at the end of the fermentation, the coenzyme NADPH regeneration rate had decreased to 5–20% of its peak level (figure not presented). Therefore, it could be concluded that, the glutamate synthesis stoppage was due to the significant reduction of NADPH regeneration rate instead of the reduction in GDH activity. In general, the enzymes catalyzing interaction assures an intracellular carbon fluxes balance. This means that in glutamate fermentation, glycolysis rate (r1) should balance with glutamate synthesis (r6), lactate formation (r5), as well as the TCA metabolic flux (r4) that was involved with CO2 release. As a result, from Figs. 1, 4, and 5, we could speculate that the severe lactate accumulation at lower DO control (DO = 10%) was due to the carbon metabolic balance rather than the higher LDH activity by the following facts. First, the changing patterns of glycolysis rate (r1) at different DO levels were almost the same; second, no significant differences in LDH activities were shown under different DO level; Third, the metabolic flux of TCA significantly decreased with the decrease in DO control level. Under the lower DO level, even though GDH activity was higher, the higher glutamate synthesis rate (r6) still could not completely balance with the glycolysis rate (r1), as TCA cycle was almost closed completely and the TCA metabolic flux (r4) was very low. Under this circumstance, lactate had to be overflowed or excreted (r5) into the broth to achieve the entire intracellular carbon balance. On the other hand, under the higher DO level, GDH activity was relatively low, but the TCA cycle was nearly open for a complete oxidation. Under this condition, lactate was not necessarily overflowed, as the glutamate synthesis rate (r6) plus the higher TCA metabolic flux (r4) were big enough to balance with the glycolysis rate (r1), even though LDH exhibited almost equivalent activity as compared with that of the lower DO case. Is there an effective way to solve the problem of simultaneous accumulation of the main product (glutamate) and by-product (lactate)? Two ways of using genetic engineering technique could be considered as the solution: (1) to use genetic engineering technique to knock-out the genes coding for LDH; (2) to use certain LDH inhibitors to eliminate the LDH action without affecting GDH and entire fermentation activities at the same time. These are direct and straightforward solutions, but might be very complicated and difficult to realize. Based on the metabolic analysis mentioned earlier, an alternative solution, the “BMC” strategy as shown in Fig. 4, which is adaptively regulating of the TCA metabolic fluxes at an appropriate level to achieve the metabolic balance among glycolysis, glutamate synthesis, and TCA metabolic flux for enhancement of the glutamate synthesis and repression of lactate overflow, seemed to be easier to implement and more realistic. Possibility of using and realizing the BMC strategy The necessary conditions for realization of BMC existed in the following two aspects: (1) the rates of the glutamate synthesis (r6) plus the TCA metabolic flux (r4) should just balance with the glycolysis rate (r1); (2) DO should be controlled at a reasonably lower level to assure a higher GDH activity. To achieve the target, an on-line measurable or predictable state variable that could actually reflect the TCA metabolic flux changes, must be available. Based on our experimental results and the on-line metabolic flux calculation in the previous study, we found RQ are related with the TCA metabolic flux (r4) closely, and could be considered as the on-line feedback index for realization of BMC. Figure 5 depicted the time course of RQ and the TCA metabolic flux (r4) for the cases of constantly controlling DO at 10 and 50%, respectively. For both cases, RQ almost followed the same changing patterns during the growth phase. However, during the glutamate production phase, the changing patterns of RQ and TCA metabolic flux under different DO levels were apparently different. RQ almost stayed constantly around 0.80 in the case of controlling DO at 50%, while RQ gradually declined into the range of 0.5–0.6 for the case of controlling DO at 10%. Theoretically, RQ = 1.0 means that TCA cycle is fully opened and glucose is completely converted into CO2 and H2O via TCA cycle. In glutamate fermentation, a lower RQ (for example, RQ = 0.5–0.6) reflected the fact that, TCA cycle was almost completely shut down in order to direct the carbon flux to the glutamate synthesis at α-KG node. On the other hand, a higher RQ meant that the TCA metabolic flux was too high that a large portion of carbon was oxidased into CO2 and H2O accompanyied with large quantities of NADH and ATP formation, which actually caused the “inefficient carbon cycle‘’. Based on Fig. 5, If we could carefully and adaptively control RQ at a suitable level, maintaining the TCA metabolic flux at a moderate level in between the fluxes of lower and higher DO levels, while still directing major carbon flux to the glutamate synthesis, then the BMC might be realized and lactate overflow be relieved. The performance and experimental result of the BMC strategy Figure 6 showed one complete data set of the BMC control results. The BMC was activated at 11 h after the fermentation entered into production phase, where the two controller parameters, KC and τI were set at 20 and 3, respectively. As shown in Fig. 6, the set-point of RQ was changed three times during the fermentation (RQset: 0.80, 11–15 h, initial stage of production phase; 0.70, 15–28 h, middle stage; 0.60, 28–35 h, final stage). The principle of changing RQset was to assure that DO does not subject to either a higher (≥40%) or a very low level (≤5%) for a relatively longer time (1 h) in order to keep a higher GDH activity: if DO stayed at higher level for relatively long time, then it initiatively reduced the RQset down; if DO stayed at very low level for relatively long time, then it initiatively brings the RQset up. By using DO as the complementary indicator in this way, RQ could be controlled around its set-point, with the agitation rate stably staying in the range of 450–750 rpm without reaching its upper limit (950 rpm) or low limit (450 rpm) even for a short time. With this control strategy, DO fluctuated at a lower range of 5–40% so that a higher GDH activity could be maintained. The BMC control led to an excellent fermentation performance as compared with those of the DO constant controls: the maximal glutamate concentration reached 101.6 g/L at 34 h which was about an 11% increase over the best result of the DO constant controls (91.5 g/L, DO = 10%); the lactate concentration at the corresponding time was only 0.11 g/L which was only 14% of the best result of the DO constant controls (0.8 g/L, DO = 50%). To verify the repeatability of BMC control’s performance, the same experiment was repeated once. Again, a maximal glutamate concentration of 98.8 g/L was obtained at 38 h, with the lactate accumulation of only 1.04 g/L at the same time.Fig. 6The experimental results and control performance using the BMC optimization strategy. Filled circle: glutamate concentration; open triangle: lactate concentration; open circle: cells concentration; filled square: glucose concentration It should be noted that constant RQ control strategy could not lead to a good fermentation performance. We did three constant RQ control experiments setting RQ at 0.6, 0.7, and 0.8, respectively. The glutamate production stopped at very low level (40–60 g/L) for all of the three cases. In the first two cases, constantly controlling RQ at 0.6 and 0.7 caused DO to drop to zero level, or the anaerobic environmental condition in other word, in the initial production stage. The cells metabolic and GDH activities were largely damaged as suggested by Fig. 2 and relevant discussion. In the third case, the high RQ set-point (RQ = 0.8) caused a continuous rise-up and high level of DO (from 20 to 70%), which reduced the GDH activity and deteriorated glutamate production in turn. As a result, the adaptive RQ control (step-wise changing RQ set-points) in simultaneous consideration of DO change has to be adopted to satisfy the two conditions of obtaining an appropriate r4 flux and a reasonable lower DO level for realizing the BMC, as described in the previous section. Figure 7 showed the changing patterns of the TCA metabolic flux (r4) when using the BMC control and the DO constant controls. Apparently, the BMC strategy controlled the TCA metabolic flux at an appropriate level just in between those of higher and lower DO levels. This realized the target of “balanced metabolism”, which led to a higher glutamate production and almost completely repressed the lactate accumulation.Fig. 7The calculated TCA metabolic fluxes of the BMC strategy and the DO constant controls Table 1 indicated that CO2 yield (total CO2 released quantity versus total glucose consumed quantity) of the BMC was also just in between those of higher and lower DO constant control cases, which supported the BMC idea from the other side. However, it should be noted that, besides channel r4, the CO2 release also occurred at the other routes in the entire metabolic network, the shutdown of TCA cycle never meant the total CO2 production would cease. The effectiveness of the BMC strategy was also supported by the metabolic fluxes changes results shown in Fig. 4. The moderate TCA metabolic flux (r4) simultaneously ensured a higher glutamate synthetic flux and an almost nil lactate formation flux.Table 1The materials and carbon balances of the balanced metabolic control (BMC) and dissolved oxygen (DO) constant controlsBatch no.Glucose consumed (g)Glutamate produced (g)Lactate produced (g)Cellsa (g)CO2 released (g)Carbon balanceb (%)CO2/Glucose (−) (%)DO = 10%839.2384.0102.090.8352.9C-content335.6156.740.846.996.2101.528.6DO = 50%530.2265.23.277.1262.9C-content212.1108.21.339.871.7104.233.9RQ-BMC716.7406.40.460.7335.9C-content286.7165.90.1831.491.6100.831.9aThe dry cell weight, using the composition of strain C. glutamicum AJ-3462 (C4.71H8.02O1.92N, Ref.#11) as the calculation referencebRatio of the total production (glutamate, lactate, cell, and CO2) to total consumption (glucose) Table 2 summarized the results and performance of the BMC and the DO constant controls. In consideration of the repeatability of the different control strategies, the experiments of constantly controlling DO at 10 and 50%, as well as BMC were repeated at least twice and then the averaged values were calculated for performance evaluation. The table evaluated the two different control strategies in terms of the four major fermentation performance index: maximal glutamate concentration, lactate accumulation quantity, glutamate productivity, and conversion rate from glucose to glutamate. The BMC showed an equivalent performance in the terms of productivity and conversion rate as compared with the best results of the DO constant controls. However, BMC strategy greatly improved the other two performance index: maximal glutamate concentration was increased by about 15% (with respect to DO = 10% case) and lactate accumulation was decreased by about 36% (with respect to DO = 50% case).Table 2The summarized results of the BMC and DO constant controlBatch no.Conversion rate (%)Glutamate concentration (g/L)Lactate concentration (g/L)Productivity (g/L/h)Constant DO controls 050331 (DO = 10%)49.3883.0027.902.86 050526 (DO = 10%)43.6291.5025.502.69 DO = 10%, average46.5087.2526.452.77 050407 (DO = 50%)44.5174.201.002.56 050512 (DO = 50%)53.4072.800.802.43 DO = 50%, average48.9673.500.902.49 050427 (DO = 30%)55.5583.2018.602.19Balanced metabolic control by RQ (RQ-BMC) 050509 (RQ-BMC)56.71101.600.112.99 050516 (RQ-BMC)49.8098.801.042.60 RQ-BMC, average53.26100.200.582.80 Summary A novel fermentation optimization method—the “balanced metabolic control” (BMC) strategy was proposed and successfully used by feedback controlling RQ to regulate the TCA metabolic flux rate at an appropriate level to achieve the metabolic balance among glycolysis, glutamate synthesis, and TCA metabolic flux for glutamate fermentation. The proposed BMC strategy greatly improved the fermentation performance in the two terms of maximal glutamate concentration and the lactate overflow repression. The maximal glutamate concentration increased by about 15% compared with the best results of the DO constant controls, and furthermore, the lactate overproduction occurred in the DO constant control cases could be completely relieved when using the BMC strategy. As a result, the proposed BMC strategy is expected to be applicable for optimization of other aerobic amino acids fermentations in potential.

J_Mol_Med-4-1-2374882

Involvement of (pro)renin receptor in the glomerular filtration barrier

(Pro)renin receptor-bound prorenin not only causes the generation of angiotensin II via the nonproteolytic activation of prorenin, it also activates the receptor’s own intracellular signaling pathways independent of the generated angiotensin II. Within the kidneys, the (pro)renin receptor is not only present in the glomerular mesangium, it is also abundant in podocytes, which play an important role in the maintenance of the glomerular filtration barrier. Recent in vivo studies have demonstrated that the overexpression of the (pro)renin receptor to a degree similar to that observed in hypertensive rat kidneys leads to slowly progressive nephropathy with proteinuria. In addition, the handle region peptide, which acts as a decoy peptide and competitively inhibits the binding of prorenin to the receptor, is more beneficial than an angiotensin-converting enzyme inhibitor with regard to alleviating proteinuria and glomerulosclerosis in experimental animal models of diabetes and essential hypertension. Thus, the (pro)renin receptor may be upregulated in podocytes under hypertensive conditions and may contribute to the breakdown of the glomerular filtration barrier. Introduction When the (pro)renin receptor binds to the “handle” region of inactive prorenin, the receptor-bound prorenin gains its enzyme activity (ability to generate angiotensin I) without the proteolytic cleavage of the prosegment of prorenin in COS-7 cells [1, 2], presumably as a result of a conformational change. On the other hand, receptor-bound prorenin also triggers its own intracellular signaling pathways independent of the generated angiotensin II. Studies have shown that the stimulation of the (pro)renin receptor by renin/prorenin activates tyrosine phosphorylation leading to the activation of extracellular signal-related protein kinases (ERK) [3] and upregulates transforming growth factor-β1 (TGF-β1) and matrix proteins without involving angiotensin II generation in human and rat mesangial cells [4]. In this review, we focus on the latest progress in elucidating the localization, regulation, and pathophysiological roles of the (pro)renin receptor in the kidneys. Localization in the kidney Studies have demonstrated that the (pro)renin receptor protein and messenger ribonucleic acid (mRNA) are expressed in the mesangium cells of human kidneys [3, 4]. However, double immunohistochemical analyses using a polyclonal antirat (pro)renin receptor antibody demonstrated that the (pro)renin receptor was colocalized with a podocyte marker, podocalyxin, but not with a mesangium marker, Thy1.1, in rat kidneys [5] and electron microscopic analyses appeared to indicate the predominant presence of the rat (pro)renin receptor in podocytes, excluding the foot processes, and its absence in mesangial cells [5]. In addition, we recently detected (pro)renin receptor mRNA in cultured human podocytes (unpublished data). Within the glomerulus, podocytes play an important role in the maintenance of the glomerular filtration barrier and podocyte injury leads to proteinuria and initiates glomerulosclerosis resulting in the progressive loss of renal function [6]. Therefore, (pro)renin receptor in the podocytes may contribute to proteinuria and renal injury through an angiotensin-II-dependent pathway, an angiotensin-II-independent pathway, or both pathways in chronic kidney diseases. Possible upregulation of (pro)renin receptor expression under hypertensive conditions In the kidneys of young hypertensive stroke-prone spontaneously hypertensive rats (SHRsp), an increase by two- or threefold in the mRNA expression of the (pro)renin receptor has been observed [7]. However, the kidneys of older hypertensive SHRsp did not show an elevation in (pro)renin receptor mRNA expression. Because the binding of renin to the (pro)renin receptor lowers the (pro)renin receptor mRNA level through a promyelocytic zinc-finger-protein-mediated negative feedback mechanism [8], a further increase in the plasma renin levels in old hypertensive SHRsp might inhibit the increase in (pro)renin receptor mRNA levels through a negative feedback loop. More recently, enhanced mRNA expression of the (pro)renin receptor was also observed in the clipped kidneys of Goldblatt hypertensive rats [9]. These results seem to provide evidence of the importance of hypertensive conditions in the regulation of (pro)renin receptor expression in the kidneys. Effects of (pro)renin receptor overexpression on the kidney Recent studies in transgenic rats overexpressing the human (pro)renin receptor gene nonspecifically by three to seven times demonstrated that glomerulosclerosis with proteinuria developed at 5–6months of age even in the absence of an elevation in blood pressure [10]. In the kidneys of 5- to 6-month-old transgenic rats, mitogen-activated protein kinase(s) (MAPK(s)) were activated without recognizable tyrosine phosphorylation of the epidermal growth factor receptor and the expression of TGF-β1 was enhanced. The in vivo administration of angiotensin-converting enzyme (ACE) inhibitor did not inhibit the development of glomerulosclerosis, proteinuria, MAPK activation, or TGF-β1 expression in the kidneys despite a significant decrease in the renal angiotensin II level. As shown in Fig. 1, recombinant rat prorenin stimulated MAPK activation in human-receptor-expressed cultured cells but human receptor was unable to evoke the enzyme activity of rat prorenin. Thus, the overexpression of the human (pro)renin receptor elicits slowly progressive nephropathy via angiotensin-II-independent MAPK activation but not through the stimulation of angiotensin II generation. However, hypertension developed at 7months of age in transgenic rats overexpressing the human (pro)renin receptor gene exclusively in smooth muscle cells [11]. Because young transgenic rats of this strain show an enhanced expression of macula densa cyclooxygenase-2 that suppresses the tubuloglomerular feedback system and contributes to the inhibition of hypertension development [12], hypertension may not yet have developed at 6months of age or earlier. Therefore, we can interpret these observations as indicating that the hypertension may have occurred as a result of the nephropathy. However, further studies are needed to elucidate the involvement of the (pro)renin receptor in the development of hypertension. Fig. 1Both rat and human prorenin stimulate human (pro)renin receptor (h(P)RR)-dependent intracellular signals, but the h(P)RR activates human prorenin but does not activate rat prorenin Receptor-bound prorenin in diabetic kidneys Recombinant prorenin binds to recombinant (pro)renin receptor expressed compulsorily on the cell surfaces of COS-7 cells and prorenin bound to the receptor on the cell surfaces exerts renin activity without undergoing any change in its molecular weight. However, synthetic peptides containing the amino acid sequence corresponding to the “handle” region of the prorenin prosegment competitively inhibit prorenin from binding to cell membrane receptors [13]. In the absence of experimental data showing the blockade of renin signaling by the handle region peptide, we believe that the possible inhibition of receptor signals and angiotensin II generation by the handle region peptide should be interpreted as indicating the blockade of prorenin binding. Diabetic animals or patients have lower renin levels and higher prorenin levels than normal healthy controls [14, 15]. The handle region peptide was administered to rats with streptozotosin-induced type I diabetes and the tissue angiotensin I and II levels in their kidneys, and the development of nephropathy were followed [16]. The administration of the handle region peptide for 6months significantly inhibited the increase in renal angiotensin II levels and the development of proteinuria and glomerulosclerosis, suggesting that the nonproteolytic activation of prorenin bound to the (pro)renin receptor plays an important role in the development of nephropathy. Although renal mRNA expression of the (pro)renin receptor was similar in the control and diabetic rats [17], nonproteolytically activated prorenin increased in the kidneys of the diabetic rats, and this increase was inhibited by the handle region peptide. In addition, the renal total renin content remained unchanged during the treatment with the handle region peptide. These results suggested that the handle region peptide inhibits the conformational change in prorenin that leads to prorenin’s enzymatic activation but does not alter the prorenin levels. Because the mRNA expression of cathepsin B, which processes the conversion of prorenin to renin, simultaneously decreased in the kidneys of the diabetic rats, prorenin may have accumulated in their kidneys. Also, the amount of prorenin released to the circulatory system may be elevated in diabetes leading to an elevation in receptor-bound prorenin as a result of the increased prorenin levels with no change in (pro)renin receptor expression. To investigate the contribution of angiotensin-II-independent, (pro)renin-receptor-dependent signal pathways to diabetic end-organ damage, the therapeutic effects of infusion were compared with the effect of the deletion of angiotensin II type 1a receptor (ATKO) and ACE inhibition on streptozotosin-induced type I diabetes [18]. Deletion of the angiotensin II type 1 gene attenuated the development of glomerulosclerosis and proteinuria but did not prevent these developments. ACE inhibitor also failed to prevent diabetic nephropathy despite the normalization of renal angiotensin II. On the other hand, the handle region peptide almost completely prevented the development of these conditions despite the absence of an increase in renal angiotensin levels. Of note, MAPKs were markedly activated in diabetic ATKO animals and, while the handle region peptide almost completely inhibited the activation, ACE inhibition failed to even ameliorate it. These results indicate that inhibition of the angiotensin-II-mediated pathway had a little therapeutic effect on nephropathy in the diabetic rats, whereas the blockade of receptor-bound prorenin seemed to suppress the two major pathways for diabetic nephropathy: excessive production of angiotensin II in the kidneys and renal MAPK activation. In this experiment, the renal angiotensin II levels of diabetic mice treated with the handle region peptide were similar to those of untreated wild-type mice. Because the handle region peptide did not seem to inhibit the binding of renin to the (pro)renin receptor, the physiological production of renal angiotensin II induced by renin or receptor-bound renin was probably unaffected by the handle-region-peptide-induced inhibition of receptor-bound prorenin. In addition, the handle region peptide did not influence the plasma levels of renin and prorenin (receptor-unbound free renin and receptor-unbound free prorenin) or blood pressure. Thus, the handle region peptide also had no effect on the physiology of the circulating renin–angiotensin system. We recently found that the handle region peptide also leads to the regression of nephropathy in rats with streptozotosin-induced type I diabetes [17]. Diabetes was induced by streptozotosin injection in 4-week-old rats. Increased urinary protein excretion and glomerulosclerosis were observed 12weeks later and the administration of the handle region peptide or vehicle was started. While urinary protein excretion and glomerulosclerosis had progressed in vehicle-treated 28-week-old diabetic rats, treatment with the handle region peptide significantly reduced the proteinuria and glomerulosclerosis from the levels observed at the start of treatment. This reversal of the glomerulosclerosis that had already developed in the diabetic rats suggested that receptor-bound prorenin contributes not only to the onset of nephropathy but also to its progression. The increased plasma prorenin level might be supplied by the kidneys in which high glucose levels might inhibit the processing of prorenin to renin as described above. In addition, extrarenal tissues might also be sources of the increased prorenin level under high glucose conditions because plasma prorenin is detectable even after a bilateral nephrectomy [15]. Thus, high glucose levels may contribute to an increase in the plasma prorenin level via both renal and extrarenal mechanisms, and the elevated plasma prorenin level might trigger an increase in receptor-bound prorenin leading to nephropathy. These mechanisms may explain why the handle region peptide inhibited the development and progression of nephropathy in animal models of diabetes without affecting the high blood glucose level. Further study is needed to clarify these points. Receptor-bound prorenin in hypertensive kidneys SHRsp rats have high plasma levels of prorenin and renin and are used as a model of primary hypertension [19]. In addition to the increased mRNA expression of the (pro)renin receptor as described above, elevated angiotensin I and II levels and glomerulosclerosis with proteinuria have been observed in the kidneys of young hypertensive SHRsp; administration of the handle region peptide significantly suppressed these changes without affecting the development of hypertension [7]. In addition, profibrotic changes in morphology were observed in the clipped kidneys of Goldblatt hypertensive rats with enhanced mRNA expression of the (pro)renin receptor [9]. Therefore, the increased expression of the (pro)renin receptor may play an important role in the development of renal tissues showing characteristic signs of hypertensive damage. Because recent studies have demonstrated the presence of angiotensin-II-independent, (pro)renin-receptor-dependent MAPK pathways in mesangial cells [20] and vascular smooth muscle cells [21], the beneficial effects of the handle region peptide may be mediated by both of these two major pathways that are stimulated by receptor-bound prorenin. Thus, receptor-bound prorenin also contributes to the development of hypertensive end-organ damage. This was recently supported, in part, by Susic et al., who reported that the handle region peptide significantly reduced the left ventricular mass even though the myocardial collagen content remained unchanged [22]. Possible inhibition of receptor-bound prorenin by high levels of renin Figure 2 shows the binding of renin and prorenin to the (pro)renin receptor. Because both renin and prorenin bind to the (pro)renin receptor [3], increased renin levels may increase the amount of renin and decrease the amount of prorenin that binds to the receptor. A recent review reported that the handle region peptide offered no benefit to renin-transgenic models or to a model with renovascular hypertension [23]. Because the ratio of renin to prorenin must be higher in these models than in control models, renin—but not prorenin—that has bound to the receptor must contribute to the pathogenesis that occurs in these models. Because no data showed the blockade of renin signaling by the handle region peptide, the handle region peptide did not benefit the renin-transgenic models or the model with renovascular hypertension [23]. In contrast, the handle region peptide greatly benefited diabetic animals [16–18]. Because diabetic animals are known to have a low ratio of renin to prorenin [15], they have increased levels of prorenin bound to the receptor and decreased levels of renin bound to the receptor. Thus, the handle region peptide was thought to benefit in vivo diabetic animals by reducing the amount of prorenin that bound to the receptor. In addition, the handle region peptide had a partial benefit on SHRsp [7, 24] and SHR [22] animals fed a high-salt diet. This benefit was reduced by changing from a high-salt diet to a low-salt diet (unpublished preliminary data), suggesting that dietary salt might alter the levels of prorenin bound to the receptor by regulating the renin levels. Thus, the efficiency of the handle region peptide may depend on the ratio of renin to prorenin. Fig. 2Renin and prorenin competitively bind to the (pro)renin receptor in vivo and to the (pro)renin receptor expressed on the cell surfaces of COS-7 cells (Pro)renin receptors in cultured cells Using vascular smooth muscle cells (VSMC) harvested from human-(pro)renin-receptor-transgenic rats, Batenburg et al. recently demonstrated that prorenin binds to the (pro)renin receptor and that receptor-bound prorenin exerts a catalytic activity but that renin does not bind to the receptor or increase its own catalytic activity [25], consistent with the results of a previous study using human VSMC [21]. The structural difference between renin and prorenin arises from 43 amino acids in the prorenin prosegment and prorenin acquires its catalytic activity without changing its molecular weight when a specific protein binds to the “handle” region of the prorenin prosegment [1]. Nevertheless, the handle region decoy peptide, which inhibited the binding of prorenin to the receptor in a test tube and to receptors expressed on the cell surfaces of COS-7 cells [13], failed to inhibit prorenin’s acquisition of catalytic activity by binding to the receptor [25]. A recent study using a human cultured cell line clearly demonstrated that the 39-kDa full-length (pro)renin receptor was predominantly present in the intracellular endoplasmic reticulum [8]. Because both renin and prorenin can permeate the cell membrane [8] but the handle region peptide cannot, the handle region peptide might be incapable of inhibiting intracellular binding between the (pro)renin receptor and its ligands (Fig. 3). Fig. 3Possible fragmentation of (pro)renin receptor in cultured cells Although (pro)renin receptors of VSMC harvested from human-(pro)renin-receptor-transgenic rats were not bound to renin [25], the same authors also showed that both renin and prorenin bind to the (pro)renin receptor and stimulate receptor-dependent ERK pathways in U937 monocytes [26]. In addition, a renin-stimulated, (pro)renin-receptor-dependent ERK pathway was observed in rat and human mesangial cells [4, 20], whereas the stimulation of the receptor by prorenin in cultured cardiomyocytes resulted in the activation of p-38 MAPK, but not ERK [27], and renin stimulation caused the interaction between the receptor and the transcription factor promyelocytic zinc finger protein in HeLa-S3 cells and HEK293 cells [8]. These results suggest that the ability to bind renin and prorenin and the intracellular pathways involving these proteins may be influenced by the species and condition of the cultured cells. In addition, the presence of (pro)renin receptors with molecular weights smaller than the 39kDa of the full-length receptor in cultured cells has been reported in abstracts presented at several meetings. Based on the results of all these studies regarding the (pro)renin receptor in cultured cells, we propose the possible fragmentation of the (pro)renin receptor (Fig. 3). Namely, when the 39-kDa full-length (pro)renin receptor in the endoplasmic reticulum is released to the cytoplasm, it may divide into a renin-binding part and a remnant part. In the cytoplasm of VSMC and cardiomyocytes, the remaining smaller (pro)renin receptor without the renin-binding part would be capable of binding prorenin but would be incapable of binding renin. However, in the cytoplasm of the mesangium and monocytes, the smaller receptor might readhere to the renin-binding part and resume its ability to bind renin. When the smaller receptor in the cytoplasm reaches the cell membrane, it might further divide into the prorenin-binding part, recognizing the “handle” region, and a remnant part. The prorenin-binding part would be released to the extracellular area and the smallest remnant receptor would remain at the cell membrane. Because the smallest receptor does not contain either the renin-binding part or the prorenin-binding part, it would no longer be capable of binding renin or prorenin. When the prorenin bound to the smaller receptor also reaches the cell membrane, it would divide into three parts: the prorenin prosegment adhered to the prorenin-binding part, renin, and the remaining smallest receptor. Because the former two proteins are released to the extracellular area, angiotensin I generation from external angiotensinogen would occur there. Thus, under cultured cell conditions, the (pro)renin receptor may be fragmented depending on the cell species. Further studies are needed to verify the possible fragmentation of the (pro)renin receptor. Conclusion In the glomerulus of the kidneys, the (pro)renin receptor is not only present in the mesangium but is also abundant in the podocytes and its expression was increased by two- to threefold in the kidneys of some animal models of hypertension. A transgene-induced overexpression of human (pro)renin receptor in rats resulted in the development of slowly progressive nephropathy with proteinuria. In addition, the handle-region-peptide-induced inhibition of receptor-bound prorenin significantly inhibited the development and progression of proteinuria in experimental diabetic and hypertensive animal models. Thus, the glomerular (pro)renin receptor appears to play an important role in the regulation of the glomerular filtration barrier.

Graefes_Arch_Clin_Exp_Ophthalmol-3-1-2082068

Ocular blood flow in patients with obstructive sleep apnea syndrome (OSAS)

Background Sleep-related disorders are among the important risk factors for neurovascular diseases. Obstructive sleep apnea syndrome (OSAS) is characterized by snoring, excessive daytime sleepiness, and insomnia. Our aim was to investigate the presence of glaucoma in patients with OSAS and to reveal vascular pathology related to the pathogenesis of glaucoma in those patients. Obstructive sleep apnea syndrome (OSAS) is characterized by snoring, excessive daytime sleepiness, and insomnia. Epidemiological studies revealed a prevalence between 2 and 20%. Among the risk factors, obesity, male gender, upper respiratory tract abnormality, consumption of alcohol, snoring, and thick neck are worth mentioning [5, 11, 12]. In previous studies, retinal vascular tortuosity and congestion [7], floppy eyelid syndrome [3, 18, 22, 27], keratoconus [22], papilledema, and optic neuropathy [2, 14, 20] have been described in patients with OSAS. It has been stressed that OSAS may be a predisposing condition for anterior optic neuropathy [14]. In a study, Mojon et al., investigating 69 patients with OSAS, found the incidence of glaucoma to be 7.2% [21]. Onen et al. found a high incidence (14.6–47.6%) of primary open-angle glaucoma (POAG) in patients with sleep-disordered breathing [24]. Similarly, in another study by Mojon et al., the prevalence of low-tension glaucoma (LTG) in patients with OSAS was found to be 50% [23]. Recently, in a study from Turkey, it was stated that OSAS is correlated with a proportional decrease in retinal nerve fiber layer (NFL) [15]. The study’s aim was to investigate the ocular blood flow in patients with OSAS since pathological ocular blood flow has been suggested as a major mechanism in the etiology of glaucoma and also to detect the glaucoma prevalence in the study group. Patients and methods Patients were recruited from those who were referred for suspected OSAS to the “Sleep Unit” of the Neurology Clinic (Erciyes University Faculty of Medicine, Kayseri, Turkey) between December 2003 and July 2004. These were consecutively all patients referred to the Sleep Unit during the 7-month period. A total of 42 patients were evaluated during this period. Among these, 31 patients fulfilled the inclusion criteria. The remaining 11 patients were excluded from the study because they had at least one of the exclusion criteria (such as those who had previous eye surgery or laser treatment, who had any anterior or posterior segment disease or a history of ocular trauma, those with secondary glaucoma, history of chronic steroid use, history of shock, and diabetes mellitus). The study included 31 patients with OSAS and 25 healthy controls. Diagnosis of OSAS was made by the Sleep Unit of the Neurology Clinic. Atherosclerotic risk factors likely to affect ocular blood flow such as hypertension, cigarette smoking, and high blood cholesterol level were investigated in all subjects; since it was impossible to completely eliminate these factors in both groups, the distribution of these risk factors was investigated and it was found to be similar between the groups (chi-square: 1.97; p = 0.16). Criteria for the diagnosis of POAG were as follows (all four of the criteria listed had to be present for inclusion in the study): A cup to disc ratio (c/d) over 0.5 or difference of c/d between two eyes >0.2 with thinning of the neuroretinal rim; a careful search was made to detect the presence of any disc hemorrhages to strongly support the diagnosis. The c/d ratio and the optic disc evaluation were derived with a +90 diopter aspherical Volk lens by two independent examiners who were masked to the condition of the patient.Any of the detected visual field defects such as localized defects, paracentral scotoma, Bjerrum scotoma, nasal step, temporal sector defect, and diffuse defect which cannot be explained by any neurologic or fundus lesion.Open iridocorneal angle.An intraocular pressure (IOP) >21 mmHg without treatment. Diagnosis of normotensive glaucoma was made with criteria similar to those stated for POAG except for the fact that IOP was <21 mmHg without treatment. The control group consisted of 25 age- and sex-matched healthy subjects who were recruited from those attending the eye clinic for conditions such as refractive errors, etc. Control subjects had to meet all of the following ophthalmological criteria for inclusion in the study: No IOP elevation over 21 mmHgNo evidence of glaucomatous optic nerve appearance (no disc hemorrhages) and a c/d ratio less than 0.5Normal anterior chamber angle on slit lamp and gonioscopic examinationNormal visual field test resultsNo previous history of antiglaucomatous drug usage, ocular trauma, ocular surgery, or laser therapy Patients underwent orbital color Doppler ultrasonography (Toshiba Power Vision 6000, Osaka, Japan) at the Radiology Unit of the University. An 11-MHz linear surface probe was used and the measurements were performed between 12:00 a.m. and 13:00 p.m. The patient was supine; eyes were closed and aimed at the ceiling under the closed eyelids. Systolic blood velocity (PSV) and end-diastolic blood velocity (EDV) were calculated in the ophthalmic artery and central retinal artery; resistivity index (RI) was calculated for the central retinal artery (CRARI) and ophthalmic artery (OARI; RI=PSV-EDV/PSV). Polysomnography was performed at the Sleep Research Unit of the University; it was constituted by two EEG channels, two EOG channels, one EMG channel recording from the submental muscle, one nasal current channel, one thoracic motion channel, one abdominal motion channel, one oximeter channel, a microphone, two leg movement channels from the right and left anterior tibialis muscles, and video recordings made between 2300 and 0700 hours. The parameter used was the apnea-hypopnea index (AHI). Diagnosis of OSAS was made when the AHI was over 5. When the AHI was between 5 and 15, OSAS was regarded as “mild,” between 16 and 30 as “moderate,” and when it was over 30, it was regarded as “severe.” All the subjects in the study underwent a complete ophthalmological examination including visual acuity, slit lamp biomicroscopy, IOP measurement, gonioscopy, and fundus examination. Perimetric examination was made with the Octopus 500 EZ perimeter (Interzeag AG, Schlieren, Switzerland); stimulus size: white, III, full threshold strategy was used. Only phases 1 and phase 3 of the G1 program were used. The Octopus perimeter has a prior education (preparation) program for possibly naive patients, which was used for all patients who were naive to the examination. A factor based on the number of false-positive and false-negative replies to the stimuli, and their ratio (<13%), was used to determine reliability. Unreliable results were retested on another day. Disc analysis was made with the Heidelberg Retinal Tomograph II (Heidelberg Engineering GmbH 2001, software version 3.0, Heidelberg, Germany). Mean nerve fiber layer thickness, rim area, rim volume, and linear c/d ratio were noted. All statistical analyses were carried out using statistical software (SPSS, version 10.0 for Windows, SPSS Inc., Chicago, IL, USA). Differences were considered significant at p < 0.05. Student’s t-test was used for intergroup analysis; chi-square, and Kruskal-Wallis, and Mann-Whitney U tests for nonparametric tests; analysis of variance (ANOVA) was used for the correlation analysis. The study was conducted in accordance with the Declaration of Helsinki and was approved by an Institutional Ethics Committee. Results This study included 31 patients (7 female, 24 male) and 25 controls (7 female, 18 male). There was no significant difference among the groups in terms of sex distribution (Yates corrected chi-square = 0.02; p = 0.88). While the mean age of the patient group was 52.07 ± 9.35 years, it was 50.44 ± 6.38 years in the control group; there was no statistically significant difference between age distributions among the groups (p = 0.13, unpaired Student’s t-test). There was no statistically significant difference between the two groups with respect to the distribution of arteriosclerotic risk factors and hypertension (Yates corrected chi-square = 1.97; p = 0.16). The prevalence of glaucoma was 4 of 31 OSAS patients (12.9%). In two of these four patients, both eyes were affected. One of these patients had normotensive glaucoma and one had POAG. The other two patients had normotensive glaucoma only in one eye. The other eyes had large cupping without any visual field defect. All of these four patients belonged to the severe OSAS group (AHI > 30). There was no significant difference between mild, moderate, or severe OSAS patients in terms of OARI or CRARI values (Kruskal-Wallis test p = 0.961, p = 0.774). The patient and control groups did not differ significantly in terms of CRARI and OARI or IOP (p > 0.05; Table 1). Table 1Comparison of patients and controls with respect to intraocular pressure (IOP), ophthalmic artery resistivity index (OARI), and central retinal artery resistivity index (CRARI)ParametersPatient eyes (mean ± SD) (n = 62)Control eyes (mean ± SD) (n = 50)tpIOP (mmHg)13.37 ± 4.3714.00 ± 4.31−1.000.32OARI0.72 ± 0.060.71 ± 0.060.7690.44CRARI0.69 ± 0.060.70 ± 0.05−0.8030.42 There was a statistically significant difference between median IOP values of mild (10.5 mmHg; range: 9–18 mmHg) and severe (14.5 mm Hg; range: 9–27 mmHg) OSAS patients (p = 0.031; Mann-Whitney U test). When correlation was analyzed between variables, a statistically significant correlation was found between OARI and MD values (r = 0.339, p = 0.007, Fig. 1), CRARI and MD values (r = 0.246, p = 0.05, Fig. 2), CRARI and LV values (r = 0.253, p = 0.048, Fig. 3), and AHI and IOP values (r = 0.426, p = 0.001, Fig. 4). Fig. 1The positive correlation between ophthalmic artery resistivity index (OARI) and mean defect (MD) in the patient group is statistically significant (r = 0.339, p = 0.007)Fig. 2The positive correlation between central retinal artery resistivity index (CRARI) and mean defect (MD) in the patient group is statistically significant (r = 0.246, p = 0.05)Fig. 3The positive correlation between central retinal artery resistivity index (CRARI) and loss variance (LV) in the patient group is statistically significant (r = 0.253, p = 0.048)Fig. 4The positive correlation between apnea-hypopnea index (AHI) and intraocular pressure (IOP) in the patient group is statistically significant (r = 0.426, p = 0.001) Discussion This study aimed to investigate the prevalence of glaucoma in patients with OSAS and also to investigate the association of ocular blood flow with OSAS and glaucoma. In previous studies, while the prevalence of glaucoma was found to be 2% [8], no correlation was obtained between respiratory disturbance index (RDI) and IOP. However, many other studies found higher incidences and a positive correlation between IOP and RDI. For instance, Mojon et al. stated that there was a positive correlation between IOP and RDI in 114 glaucoma suspects [21]. In our study, similar to Mojon et al.’s study, there was a significantly positive correlation between IOP and AHI (r = 0.426, p = 0.001). In another study by Robert et al., which was carried out with 69 patients with OSAS, prevalence was found to be 7.2% [27]. At the same time, a strong positive correlation was found between OSAS and lid hyperlaxity [27]. In that study, incidence was 8.7% and six patients were referred for glaucoma treatment [27]. In the study of McNab et al. in which 8 patients with floppy eyelid syndrome were investigated for OSAS and 20 other patients with known OSAS were examined for floppy eyelid syndrome and other possibly associated ocular features, it was found that 1 of 8 patients with floppy eyelids had normotensive glaucoma [18]. Onen et al. found a high prevalence of sleep-disordered breathing (SDB) in POAG patients [24]. When only snoring was taken into consideration, the incidence of “only snoring” was 47.6%, “snoring and excessive daytime sleeping” was 27.3%, and “snoring, daytime sleepiness, and insomnia” was 14.6% [24]. Marcus et al. also stressed that SDB may be a risk factor for low-tension glaucoma (LTG) [17]. Mojon et al. found that the prevalence of OSAS was 50% in LTG patients aged between 45 and 64 years and 63% in those over 64 years of age [23]. However, Girkin et al. [9] reported an odds ratio of 2.02 for OSAS patients to develop glaucoma. Similar to most of the above-mentioned studies, the authors of the present study also found a high prevalence of glaucoma (12.9%) in the study group of 31 patients suggesting that OSAS in conjunction with a vessel disease is an important risk factor for glaucoma. The correlation between RDI and IOP was also investigated by Geyer et al. [8]; the authors stated that there was no statistically significant correlation [8]. On the contrary, Mojon et al. found a positive correlation between two variables [21]. We found a statistically significant difference between AHI and IOP in mild and severe OSAS patients. In our study, all four glaucomatous patients were in the severe OSAS group with an AHI > 30. In the patient group, there was a positive correlation between OARI and MD as well as CRARI and MD, and LV. Tsang et al. also found that moderate to severe OSAS patients were associated with a higher incidence of visual field defects [29]. These results suggest that visual field defects may be caused by optic nerve perfusion insufficiency and that when RI increases, field defects also increase. However, there was no significant difference between OARI and CRARI values of patients and healthy subjects. This may suggest that the effects of OSAS on body systems are seen not only during sleep but also during daytime; pathological changes may be more clearly documented if recordings and ultrasonography can be made during the sleeping period with a suitable technique to be developed in the future. Hypoxia in OSAS is of intermittent character and the thinning may occur in the progression of the disease in such patients. Long-term follow-up of these patients in terms of NFL thickness changes over time may clarify this issue. Purvin et al. suggested that intracranial pressure increases as a result of episodic nocturnal hypoxemia and hypercapnia, thereby leading to papilledema and increasing the risk of visual loss [25]. Since intracranial pressure increase in these patients is of intermittent character, cerebrospinal fluid pressure may be normal. In our group of patients, visual field defects were detected in ten patients despite normal ophthalmological examination. This may be due to optic nerve damage caused by cerebral ischemia and intermittent intracranial pressure increase in such patients. Low diastolic pressure and systemic hypertension are reported to be strongly associated with glaucoma [4, 6, 25, 26]. Some authors suggested that physiological nocturnal hypotension, in the presence of other vascular risk factors, can bring the optic nerve head circulation under the critical levels and thus play a role in the pathogenesis of anterior ischemic neuropathy and glaucoma [1, 10, 16, 28]. The pathogenesis of LTG is not clear; however, optic nerve head hypoperfusion has been suggested as the cause [30]. Hayreh stated that many systemic and ocular paralyses occur at nighttime and may be realized when the patients awaken early in the morning [13]. Furthermore, Hayreh [13] and Meyer [19] suggested that nocturnal hypotension might play a role in the pathogenesis of LTG. In conclusion, in our group of patients with OSAS, a high prevalence was found (12.9% = 4 glaucoma patients of 31 OSAS patients) and it is interesting to note that all four of the glaucoma patients were in the severe OSAS group. The positive correlation detected between OARI and MD, and also between CRARI and MD as well as LV, suggests that visual field defects may be due to optic nerve perfusion defects and that these field defects also increase as the RI increases. The presence and progression of glaucoma should be investigated particularly in patients with severe OSAS in the long-term follow-up, and changes in retinal nerve fiber layer thickness and ocular Doppler ultrasonographic findings should also be monitored in such patients.

Antonie_Van_Leeuwenhoek-3-1-2140096

Comparative genomics of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens using a Streptomyces coelicolor microarray system

DNA/DNA microarray hybridization was used to compare the genome content of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens with that of Streptomyces coelicolor A3(2). The array data showed an about 93% agreement with the genome sequence data available for S. avermitilis and also showed a number of trends in the genome structure for Streptomyces and closely related Kitasatospora. A core central region was well conserved, which might be predicted from previous research and this was linked to a low degree of gene conservation in the terminal regions of the linear chromosome across all four species. Between these regions there are two areas of intermediate gene conservation by microarray analysis where gene synteny is still detectable in S. avermitilis. Nonetheless, a range of conserved genes could be identified within the terminal regions. Variation in the genes involved in differentiation, transcription, DNA replication, etc. provides interesting insights into which genes in these categories are generally conserved and which are not. The results also provide target priorities for possible gene knockouts in a group of bacteria with a very large numbers of genes with unknown functions compared to most bacterial species. Introduction Streptomyces are a group of aerobic high %G+C Gram positive bacteria that undergo complex differentiation to form filamentous mycelium, aerial hyphae and spores. In addition, they produce a broad range of secondary metabolites including antibiotics, antiparasitic agents, herbicides, anti-cancer drugs and various enzymes of industrial importance. Two Streptomyces species have had their complete genome sequences published, namely the model organism Streptomyces coelicolor (%G+C = 72.1) and avermictin producer Streptomyces avermitilis (%G+C = 70.7) (Bentley et al. 2002; Ikeda et al. 2003). Two important aspects of the genomes structures of Streptomyces were supported by sequence data. Firstly, that the genome size of Streptomyces is large compared to other bacteria; 8,667,507 basepairs for S. coelicolor (7,825 protein coding genes) and 9,025,608 bp (7,577 protein coding genes) for S. avermitilis. Secondly, that the genomes of these two species are linear and both ends contain unique terminal inverted repeats that probably covalently bind a terminal protein. Terminal inverted repeats and covalently bound terminal proteins are not found in the limited number of other bacteria that have linear chromosomes such as Borrelia burgdorferi and Agrobacterium tumefaciens and, up to the present, seem to be unique to the Streptomyces and perhaps other Actinobacteria (Lin et al. 1993; Chen et al. 2002; Goodner et al. 1999; Huang et al. 2004). Over 2,500 Streptomyces strains are present in the Ribosomal Database Project (http://www.rdp.cme.msu.edu), over 1,500 are available at the American Type Culture Collection (http://www.atcc.org/) and many more are held in both public and private culture collections throughout the world. Analysis of the small subunit ribosomal RNA gene sequences of Streptomyces confirms that they form a monophyletic clade, but one with considerable diversity. In addition, there is significant gene diversity at the interspecies level across the genomes of both completely sequenced Streptomyces with 2,291 gene unique to S. avermitilis and 2,307 genes unique to S. coelicolor.. This makes them particularly interesting targets for comparative genomic studies. In this study we chose four species to begin an analysis of the genomic diversity of the Streptomyces. S. avermitilis was chosen because of the availability of the complete genome sequence of this species, while Streptomyces maritimus was chosen because of its intermediate position in terms of phylogeny within the Streptomyces. Streptomyces cattleya was chosen because, based on small subunit ribosomal RNA sequence, this species is phylogenetically quite divergent from S. coelicolor and branches near the root of the Streptomyces clade. Streptomyces cattleya is a β-lactam producing species. Finally, Kitasatospora aureofaciens was chosen as this genus is very closely related to the Streptomyces. The availability of two microarrays for S. coelicolor (Lum et al. 2004; Huang et al. 2001; Vinciotti et al. 2005; http://www.surrey.ac.uk/SBMS/Fgenomics/Microarrays/index.html) makes possible a comparative genomic analysis of Streptomyces species. The genes that make up the genome of S. coelicolor have been classified based on scheme of Riley and colleagues for E. coli and modified for S. coelicolor (http://www.sanger.ac.uk/Projects/S_coelicolor/scheme.shtml). A microarray analysis of the genomes of these Streptomyces using the S. coelicolor microarray is able to provide a wide ranging comparative analysis of the conserved genome content of these Streptomyces. This type of approach, where a heterologous microarray is used to analyze the genome content of a range of strains or species, has been successfully used in a wide range of organisms (Akman and Aksoy 2001; Akman et al. 2001; Behr et al. 1999; Chan et al. 2003; Cho and Tiedje 2001; Dorrell et al. 2001; Dziejman et al. 2002; Fitzgerald et al. 2001; Gill et al. 2002; Leonard et al. 2003; Murray et al. 2001; Porwollik et al. 2002; Salama et al. 2000; Israel et al. 2001; Rajashekara et al. 2004). The strains analyzed using this approach range from intraspecies comparisons such as Campylobacter jejuni, Vibrio cholerae and Staphylococcus aureus (Dorrell et al. 2001; Dziejman et al. 2002; Fitzgerald et al. 2001) to interspecies comparisons such as Sodalis glossinidiusversus an Escherichia coli array, Salmonella bongori versus a Salmonella enterica array, Shewanella species versus Shewanella oneidensis and E. coli arrays and Brucella species versus a Brucella melitensis array (Akman et al. 2001; Chan et al. 2003; Murray et al. 2001; Rajashekara et al. 2004). In this study, we used both versions of the S. coelicolor genome microarrays to compare the gene complements of the three Streptomyces species and one Kitasatospora species. The genus Kitasatospora is closely related to the genus Streptomyces in terms of morphology, chemical taxonomy and small subunit ribosomal RNA sequence analysis. Thus, the choice of a species from this genus acts as potential outgroup in terms of overall genome structure. In terms of genes that are conserved, the types of genes of particular interest include genes involved in secondary metabolism, genes involved in chromosome replication, genes in the terminal regions of the chromosome, sigma factors, genes involved in differentiation and hypothetical genes. In terms of gene absence, the distribution of such genes along the chromosome and the apparent absence of any major housekeeping genes in a specific species are of interest. This information provides insights into genes that make up the core complement for a member of the Streptomyces and into which genes are central to defining a Streptomyces species. Materials and methods 16S phylogeny This was carried out on selected small subunit 16S ribosomal RNA gene sequences obtained from Ribosomal Database Project-II Release 9 (http://www.rdp.cme.msu.edu/index.jsp) and aligned using CLUSTALX (Thompson et al. 1997). The analysis was carried out using Neighbor-Joining algorithm from the same program. In the case of S. maritimus, the taxonomy of the strain was confirmed by DNA sequencing of the 16S ribosomal RNA gene. Arrays Two series of arrays that cover about 97% of the complete genome of Streptomyces coelicolor A3(2) (Lum et al. 2004; http://www.surrey.ac.uk/SBMS/Fgenomics/Microarrays/index.html) were used in this study. Both arrays are PCR arrays, but from different sources, namely Stanford University, USA and the University of Surrey, UK and made up of different PCR products. The Stanford array as used in this study contained sequences covering 7603 open reading frames. The Surrey microarray is made up of 7,758 unique PCR amplified sequences, 7,563 from the chromosome and 195 from SCP1. There are an additional 376 non-unique, alternative and cross-hybridizing sequences that are also spotted on to the array together with no probe spots and control spots. The two types of arrays were used to improve validation with a system using heterologous hybridization; however, only the University of Surrey array was hybridized and analyzed in duplicate. The major difference between the two arrays was that the Surrey array did not include a number of transposition element related genes, although there were other overlap differences. The sequences of the PCR products are not available for either array due to intellectual property protection requirements. Strains and growth conditions S. coelicolor A3(2) (SCP1+) 104, S. avermitilis ATCC 31267, S. cattleya ATCC 35852, S. maritimus Yang-Ming and K. aureofaciens ATCC 10762 were used in these studies. Fresh spores were collected and mycelium cultured in TSB liquid medium with 0.5% glycine at 30°C overnight. Preparation of labeled DNA Genomic DNA from a stationary phase culture was purified by the salting out procedure (Pospiech and Neumann, 1995) and had been sonicated to < 2 Kb. Four to six micrograms of sonicated genomic DNA were used as template and this was denatured in the presence of 12 μg of 72%-GC-content random hexamers in a total volume of 25 μl at 100°C for 10 min. The mixture was then snap-cooled on ice before adding the remaining reaction components: 1.5 μl of Cy3-dCTP or Cy5-dCTP (Amersham Pharmacia Biotech), 4μl Klenow fragment (NEB #212), 5μl Klenow buffer, 0.5 μl dNTP (4 mM dATP, 4 mM dTTP, 10 mM dGTP, and 0.2 mM dCTP), and 14 μl ddH2O. The random primed labeling reaction was carried out for 2–3 h at 37°C. Buffer exchange, purification and concentration of the DNA products was accomplished by three cycles of diluting the reaction mixture in 0.5 ml TE buffer (10 mM Tris and 1 mM EDTA pH 8.0) and filtering though a Microcon-30 microconcentrators (Millipore). Microarray hybridization and data analysis The two DNA pools to be compared were mixed and applied to an array in a hybridization mixture that contained 3.68 × SSC, 0.18% SDS, and 1 μg yeast tRNA (total 16.3 μl), which had been heated at 100°C for 5 min before being applied to array. Hybridization took place under a glass coverslip sealed by glue in a humidified Omnislide (Thermo Hybaid) at 60°C for 12–14 h. The slides were washed, dried and scanned for fluorescence using a GenePix TM 4000B scanner (Axon instruments). Average signal intensity and local background measurements were obtained for each spot on each array using GenePixPro software. The dataset was screened for aberrant spots and these were eliminated from the analysis after manual checking. Most genes are present in duplicate on the two arrays and the signal from each pair of spots was inputted into the computer program available from ScanAlyze (Eisen et al. 1998; Gollub et al. 2003). The data was then processed into a mean log2 Cy3/Cy5 ratio format. The dataset was normalized for each array separately and outputted to Excel where after checking the alignment of the datasets from each array, a mean signal for each common gene was calculated. Genes that were absent from either array, mostly transposon related genes in the University of Surrey array, were not included in the analysis. Based on Bentley et al. 2002, the mean signal and standard deviation for the core region of genes from SCO2050 to SCO5800 was calculated. The standard deviation was used to set a cut-off for gene absence at 2SD below the core mean. The microarray data is presented relative to the S. coelicolor standard in two ways. This is either as a color plot of the genes where green presents a negative hybridization signal, black represents an equal hybridization signal and red indicates a positive hybridization signal using the program Treeview (Eisen et al. 1998) or as numeric values for the signal from each gene. The microarray data for the four species described here and additional unpublished species can be accessed via rkirby@ym.edu.tw. Comparison of the microarray dataset for S. avermitilis with the complete genome sequence The nucleotide sequences for all the identified open reading frame from the S. avermitilis genome sequence (Ikeda et al. 2003) were compared with the genome sequence of S. coelicolor using blastn limiting the output to the best match. This E value dataset for the genes was then aligned with the S. avermitilis microarray dataset and a comparison plotted as a scatterplot. Genes showing disagreement between the two datasets were identified based on a 2 Standard Deviation (SD) cutoff for the microarray dataset and a E-10 cutoff for the blast value. Analysis of gene presence across the chromosome A graphical display was created by counting the number of gene detected as present from the signal based on the 2SD cutoff from each normalized microarray dataset using a moving window of 10 genes in steps of one. Results and discussion Comparison of S. avermitilis, S. cattleya, S. maritimus and K. aureofaciens with the S. coelicolor genome In total, after spot and data validation, a total of 7,083 open reading frames were included in this analysis as presence on both types of array and giving analyzable signal on all three arrays. Validity in this study was initially obtained by using microarrays from two sources that presumably use different PCR products to create the arrays. In addition, the University of Surrey array was hybridized and analyzed in duplicate. In terms of gene absence based on two standard deviations as described in the “Materials and methods" section, the agreement between the Stanford array and the duplicated University of Surrey array was about 95%, while the agreement between the two University of Surrey arrays was about 98%. In order to minimize the effect of divergent individual array spots, the signal mean for each gene from the three arrays was used throughout this study. In this study, the genomic content of three Streptomyces species and one Kitasatospora species with divergent taxonomy, antibiotic production and SSU rRNA sequence are compared using two different S. coelicolor microarrays. It is clear that there are inherent limitations to this approach. Firstly, only gene absence or divergence rather than the presence of new genes can be identified. Secondly, it is not possible to clearly separate the absence of a gene from the presence of a divergent homologue of the same gene. Finally, although the order of the genes in S. coelicolor and S. avermitilis are known from their complete genome sequences and are well conserved, this does not mean that the synteny of most of them is conserved in other Streptomyces species. However, the detection of synteny across Actinobacteria including Mycobacterium tuberculosis, Corynebacteriun glutamicum and other species (Bentley et al. 2002 and unpublished data) supports a conserved central core structure to the genomes of the Actinomycetes and a priori most Streptomyces. Thus, although major chromosomal reorganizations in the central core region cannot be detected by microarray data, a basic chromosomal structure can be assumed as a first approximation; namely, a linear chromosome with variable terminal regions and a relatively well conserved core region. When the pooled data from the two arrays for the four species was analyzed using Cy-3 labeled S. coelicolor A(3)2 chromosomal DNA compared to heterologous Cy-5 labeled chromosomal DNA, a wide range of signal variation could be noted and this is shown in Supplementary Fig. 1. The SSU rRNA tree places the divergence of these four strains from S. coelicolor as S. cattleya > K. aureofaciens > S. maritimus > S.avermitilis (Fig. 1). Gene differences were present in the order S. cattleya > K. aureofaciens > S. avermitilis > S. maritimus based on −2SD cutoff below the mean signal for the core region genes. The microarray data thus shows general agreement with S. cattleya and K aureofaciens being more divergent and the other two species being relatively closer. It is interesting to note that the Kitasatospora species used in this study, K. aureofaciens, shows the same general structure as the Streptomyces species. This is not unexpected and confirms the close relationship between Kitasatospora and Streptomyces and agrees with the SSU rRNA tree data.Fig. 1SSU rRNA phylogenetic tree of selected Streptomyces species and other Actinomycetes that have known complete genome sequences. The species analyzed by microarray are indicated in bold Further support of the reliability of the data comes from a comparison of the blastn E values for all genes and the microarray data as shown in the Fig. 2 scatterplot. This indicated 232 out of 6,832 genes show gene absence by microarray when they seem to be present by blastn and 268 out of 6,832 gene show gene presence by microarray when they seem to be absent by blastn; these results are both based on cutoffs of −2SD for the microarray data and −10 for the E value. This gives an overall reliability for S. coelicolor compared to S. avermitilis of 93%. Potential errors factors include in the case of the former type of error, poor spotting of the array at that point and choice of the PCR product sequence (the comparison is with the whole gene, as the PCR products are not available) and in the latter case cross-hybridization between multiple gene copies or a unreliable hybridization signal due to poor washing in that area. However, the results for S. avermitilis clearly support the reliability of the genome comparisons produced by this study.Fig. 2Scatterplot comparing gene presence/absence based on the microarray data and gene presence/absence based in blastn between Streptomyces coelicolor and Streptomyces avermitilis. See “Material and methods" for details. Box A and Box C includes genes identified as absent in S. avermitilis by the microarray dataset but present using blastn and genes present in S. avermitilis using blastn, but identified as absent by the microarray dataset. Box B includes genes that are correctly identified as absent by the microarray dataset Distribution of gene differences across the complete chromosome of S. coelicolor for all four other Streptomyces species The whole chromosome microarray dataset supports the following structure for the Streptomyces chromosome. Based on Fig. 3 and Supplementary Fig. 1, there is a central core of conserved probably syntenous genes that can be found across many Actinomycetes and in the S. coelicolor genome this reach from about SCO2050 to SCO5800 (Bentley et al. 2002). The regions between SCO1100 and SCO2050 and between SCO5800 and SCO7600 are also quite well conserved between the Streptomyces studied here as well as being syntenous between the S. coelicolor and S. avermitilis genome sequences. However they are not present when the genomes of these two species are compared bioinformatically to other divergent Actinomycetes. These two regions seem to be two genus specific areas. Figure 3 also clearly shows that gene conservation drops off dramatically in the terminal region. The regions from the left terminus to SCO1100 and from SCO7600 to the right terminus show much higher gene divergence that the rest of the chromosome. This agrees with the results for the S. ambofaciens sequencing studies of that species’ terminal regions (Choulet et al. 2006a, b). The gene conservation levels averaged across the four species are as follows: left terminal region (SCO0001–SCO1100) 40.9%; left genus specific region (SCO1101–SCO2050) 84.8%; core region (SCO2050–SCO5800) 79.4%; right genus specific region (SCO5801–SCO7600) 69.6% and right terminal region (SCO7601–SCO7845) 50.3%. It is noticeable that neither the size nor the distribution of conserved genes is symmetrical between the two terminal regions or the two genus specific regions. Notably, the genus specific region actually has a higher frequency of gene conservation than the core regions as a whole and that the left terminal region is much larger than the right terminal region. This possibly represents horizontal exchange of terminal regions by recombination between strains/species that involves only one terminal region. Such an event would give rise to asymmetric gene conservation similar to that detected here.Fig. 3Analysis of “gene presence” across the four species. Created using a moving window of 10 genes and counting the number of genes with a microarray signal >2SD below the mean for the core region genes. The Y axis is the count for “gene presence” In the Karoonuthaisiri et al. (2005) study of regional gene expression in S. coelicolor, the boundaries for higher transcript levels during vegetative growth were placed at 1.5 Mb for the left arm and 2.3 Mb for the right arm. The former is midway across the left genus specific region and the latter approximately agrees with the boundary between the core and the right genus specific region. As the core region boundaries are also defined in terms of synteny with the Mycobacterium and Corynebacterium genomes as well as the data presented here, this supports the idea that the S. coelicolor chromosome structure is asymmetrical with respect to both gene conservation and gene function. It should be noted that because we are using only S. coelicolor as the source of the array data, the results do not imply that the genomes of S. cattleya, S. maritimus and K. aurefaciens are asymmetric. However, it should be noted that the S. avermitilis genome is also asymmetric (Ikeda et al. 2003). Notably, there are 22 identifiable regions where all four species show a significant degree of concurrent gene absence outside of the terminal regions (Table 1). The regions of high gene divergence are shown in Supplementary Fig. 2 in detail. Previously, Bentley et al. identified 14 regions in the S. coelicolor chromosome that were potentially laterally acquired regions. This analysis pinpoints all of these regions and quite accurately, usually to within one or two open reading frames. This suggests that other eight regions are probably quite robust when designated as potential lateral transfer regions. It also supports the usefulness of the microarray approach. All 22 regions were analyzed using Frame Plot (Artemis v7.1) and except for region B, they show abnormalities for at least some of the open reading frames compared to the G+C bias expected for the 1st, 2nd and 3rd codon positions of Streptomyces genes. Eight regions, A, B, F, I, M, O, Q and T contain transposon related genes near to or within the region. Four regions, H, N, P and R are flanked by highly conserved genes such as a ribosomal protein or sigma factor genes, which could encourage interspecific recombination. Finally, five regions consist largely of hypothetical proteins with no known similarity to any known protein as yet; these regions are G, J, L, S and W. Region L is particularly interesting as there is a central core of conserved gene flanked by two subregions that are highly not conserved. One of these genes is a putative spore septum determining protein, while the rest have unknown functions. Taken as a whole, the results suggests that S. coelicolor may have recently acquired all these regions either by transposition or by interspecific/intraspecific recombination (Wolf et al. 2002; Zhang et al. 2002). It is also unlikely that they were acquired from any of the four species studied here. There are other regions that could potentially be identified as lateral transfer positions using less stringent criteria and a wider screening of genomes might help to support these additional regions as being involved in hotizontal transfer. In addition, such a wider screen might allow the identification of possible origins of these regions in other species.Table 1Areas of the Streptomyces coelicolor genome identified as potentially horizontally transferred regions based on microarray parallel gene absence in all four speciesRegionArea of chromosomeGenes missinga%aSignificant featuresRegion ASCO0996–SCO101017/2959Integrase, insertion sequenceRegion BSCO2860–SCO287953/7669Rifampin ribosyl transferaseRegion CSCO3249–SCO328894/15660Integrase, excisionaseRegion DSCO3471–SCO3538198/26873AgaraseRegion ESCO3584–SCO359930/6050Region FSCO3929–SCO393722/3268Integrase/recombinase, fstK-likeRegion GSCO3980–SCO400156/6488Hypothetical proteinsRegion HSCO4052–SCO4066132/14492Boundary dnaZ geneRegion ISCO4210–SCO422337/5469Region JSCO4247–SCO425721/3658Hypothetical proteinsRegion KSCO4340–SCO435434/4085Integrase, DNA invertaseRegion LSCO4509–SCO4547106/14474Hypothetical proteinsRegion MSCO4613–SCO463140/6859Integrase, excisionaseRegion NSCO4686–SCO470024/4455Boundary ribosomal proteins operonRegion OSCO5323–SCO535157/8071Integrase, excisionaseRegion PSCO5605–SCO562046/6472Boundary sigma factor whiGRegion QSCO5632–SCO564440/4491Integrase, korSARegion RSCO5715–SCO573557/7279Boundary ribosomal protein, bldBRegion SSCO5906–SCO592428/5650Hypothetical proteins, xylanaseRegion TSCO6372–SCO640682/10082RecombinaseRegion VSCO6607–SCO664862/12052HelicaseRegion WSCO6806–SCO695373/13355Hypothetical proteinsaThis is calculated from the available normalized gene dataset from the two microarrays Gene conservation in the terminal regions of the four Streptomyces species As has been mentioned earlier, the two regions at either terminus are much less well conserved than the central core region; these extend from SCO0001 to about SCO1100 on the left arm of the chromosome and from about SC7600 to SCO7845 on the right arm. The boundaries of these regions are not absolutely clear-cut, but what is clear is that as one moves towards the centre of the genome, gene conservation increases beyond these points. This can be clearly seen in Fig. 3 where the gene conservation is plotted using a moving window for the four species, but it is also clear that the lack of conservation is not uniform across the terminal regions and that areas of higher gene conservation can be identified. The significant interest in the terminal regions arises because the genomes of all Streptomyces that have been examined are linear and the problem of how the termini of such a molecule replicate is of particularly importance. Recent studies have indicated that two genes in particular, tpgA (SCO7734) and tapA (SCO7733), are involved in this process (Yang et al. 2002; Bao and Cohen 2001). tpgA encoding the terminal protein that covalently binds to the termini of many linear Streptomyces replicons is conserved across all four species. In S. avermitilis this is also true based on sequence data and, further more, there are multiple copies of tpgA unlike S. coelicolor. The signal level of the S. avermitilis gene at +1.2 supports the presence of these multiple copies. The signal levels for the other three species are between about −0.3 and −0.1, which supports a single slightly diverging copy of this gene in these species. However, if two copies are present then the sequence divergence may be higher. Furthermore, tapA is also conserved except for S. maritimus, which seems to be more divergent at −0.8. It should be noted that the presence of these two genes is not a criteria for defining a genome with a linear topology, but the presence of one or both is certainly suggestive (Dary et al. 2000; Wang et al. 1999; Huang et al. 1998; Lin and Chen 1997). Finally, ttrA is known to be involved in chromosomal transfer and is found very close to the telomere of S. coelicolor and S. avermitilis. This is also conserved in all four species suggesting the genetic exchange is highly important in Streptomyces and related species. The two terminal regions encompass the major areas that are prone to deletion in many Streptomyces species and are therefore not essential except for linear terminal replication and genetic exchange. Given the relatively high lack of conservation of genes in this region, genes that are present in all four species represent an interesting class. A full list of all genes conserved in all four species in the terminal regions is provided in Tables 2a and 2b. There are 36 hypothetical genes that show high similarity in the two terminal regions. Analysis of these groups of conserved genes using Artemis v7 (The Sanger Institute) identifies a total of five groups of genes that may make up possible single transcriptional units. These are SCO0551–SCO0552, SCO0705–SCO0710, SCO1021–SCO1024, SCO7677–SCO7680 and SCO7682–SCO7688. In addition to TpgA and TapA, it is possible that there are other genes involved in terminal replication and these may be among the conserved genes present in the terminal regions. Although possible candidates can be deduced from a direct comparison of the two known Streptomyces genome sequences, they are many in number. Using the microarray analysis of the Actinomycetes in this study, the candidates can be reduced significantly. From candidates in Tables 2a and 2b, two possible transcriptional units seem to be potential candidates for involvement in terminal replication; these are SCO1021–SCO1024 (hypothetical proteins), and SCO7677–SCO7689 (including hypothetical proteins, an AMP-binding ligase and membrane proteins). Gene knockout studies may be able to identify possible functions for these and other gene candidates, especially the other hypothetical proteins that are conserved in these four species.Table 2Genes from the (a) left terminal, (b) right terminal region of Streptomyces coelicolor showing microarray conservation in all four species(a)SCO0002 ttrASCO0800 putative TetR-family transcriptional regulatory proteinSCO0142 hypothetical proteinSCO0802 hypothetical proteinSCO0150 hypothetical proteinSCO0810 putative ABC transporter permeaseSCO0201 putative integral membrane proteinSCO0830 putative penicillin-binding proteinSCO0232 hypothetical proteinSCO0839 putative transmembrane transport proteinSCO0415 hypothetical proteinSCO0840 putative marR-family transcriptional regulatorSCO0443 hypothetical proteinSCO0854 hypothetical proteinSCO0452 putative SIR2-like regulatory proteinSCO0883 polypeptide deformylaseSCO0466 araC family transcriptional regulatorSCO0887 putative TetR-family transcriptional regulatorSCO0471 putative araC family transcriptional regulatorSCO0894 putative membrane proteinSCO0496 putative iron-siderophore permease transmembrane proteinSCO0895 RNA polymerase principal sigma factor HrdCSCO0536 hypothetical proteinSCO0900 putative transmembrane efflux proteinSCO0538 probable sugar transporter sugar binding lipoproteinSCO0905 putative membrane proteinSCO0544 hypothetical secreted proteinSCO0907 putative dehydrogenaseSCO0546 pyruvate carboxylaseSCO0925 putative lysR-family transcriptional regulatorSCO0551 putative histidine kinase proteinSCO0926 hypothetical proteinSCO0552 putative response regulatorSCO0931 putative secreted proline-rich proteinSCO0565 putative polyprenyl synthetaseSCO0942 putative RNA polymerase sigma factorSCO0584 putative cytochromeSCO0943 hypothetical proteinSCO0591 putative lysozyme precursorSCO0947 putative integral membrane proteinSCO0592 hypothetical proteinSCO0949 hypothetical proteinSCO0614 hypothetical proteinSCO1011 conserved hypothetical proteinSCO0619 putative membrane proteinSCO1015 hypothetical proteinSCO0637 hypothetical proteinSCO1018 putative isomeraseSCO0690 possible oxidoreductaseSCO1021 hypothetical proteinSCO0695 hypothetical proteinSCO1022 hypothetical proteinSCO0701 hypothetical proteinSCO1024 hypothetical proteinSCO0707 putative branched-chain amino acid ABC transport permeaseSCO1034 putative tetR-family regulatory proteinSCO0708 putative branched-chain amino acid ABC transport proteinSCO1036 putative phosphotriesterase-family proteinSCO0709 putative branched-chain amino acid transport ATP-binding proteinSCO1040 putative DNA repair proteinSCO0710 putative branched-chain amino acid transport ATP-binding proteinSCO1041 hypothetical proteinSCO0765 secreted endoglucanaseSCO1043 putative transcriptional regulatory proteinSCO0779 conserved hypothetical proteinSCO1044 putative secreted proteinSCO0788 hypothetical proteinSCO1046 putative metal transporter ATPaseSCO0790 putative hydrolase(b)SCO7649 putative two-component system sensor kinaseSCO7677 putative secreted solute-binding proteinSCO7678 putative metal transport integral membrane proteinSCO7679 putative transport system integral membrane proteinSCO7680 putative ABC transporter ATP-binding proteinSCO7681 putative AMP-binding ligaseSCO7682 putative non-ribosomal peptide synthaseSCO7684 conserved hypothetical proteinSCO7685 conserved hypothetical proteinSCO7687 putative thioesteraseSCO7688 hypothetical proteinSCO7689 putative ABC transporter ATP-binding proteinSCO7718 hypothetical proteinSCO7720 hypothetical proteinSCO7724 hypothetical proteinSCO7734 Tpg proteinBold indicates groups of consecutive genes that may form a single transcriptional unit Conservation of functional groups of genes across the four Streptomyces species One approach to analyzing genetic variation across these four Streptomyces species is to look at the functional groupings of genes. Such an approach should allow the identification of strain versus genus specific genes especially when there are large numbers of genes with related functions such as sigma factors or where there are two copies of a gene, such as ftsK. However, because microarray data paints a broad picture across a whole genome, it is essential that once a gene or genes has been targeted based on microarray data, that experimental verification by other means is carried out. However, it is hoped that this dataset will be able to help researchers prioritize their gene targets better. The genes of the S. coelicolor chromosome have been grouped based on the scheme of M. Riley and colleagues for E. coli (ecocyc.org) modified for S. coelicolor (http://www.sanger.ac.uk/Projects/S_coelicolor/scheme.shtml) and we used this classification. The genes involved in ribosomal proteins synthesis and modification should be highly conserved and the results indicate that almost all of them are present in all four species (Table 3; Supplementary Fig. 4). The only exceptions are SCO0436, SCO0509 SCO3430 and SCO3909 in S. avermitilis and SCO4716 and SCO5514 in K. aureofaciens. Of these genes, SCO0436, SCO0509 and SCO5514 represent duplicate genes in the S. coelicolor genome and therefore the choice of the microarray sequence will have had a significant effect on the heterologous hybridization. There is no obvious explanation for the failure to hybridize of the other two genes, but as a whole, this dataset supports the integrity of the array system for analysis of genome content as these genes are scattered across the whole Streptomyces genome.Table 3Microarray data for ribosomal proteins from the four species S. avermitilisS. cattleyaS. maritimusK. aureofaciensSCO0436 probable 50S ribosomal protein−0.35−0.130.44−0.29SCO0569 putative 50S ribsomomal protein fragment−0.750.63−0.420.27SCO1150 50S ribosomal protein L310.56−0.47−0.240.14SCO1505 30S ribosomal protein S40.36−0.350.76−0.31SCO1598 50S ribosomal protein L201.500.630.890.34SCO1599 50S ribosomal protein L350.230.410.49−0.51SCO1998 30S ribosomal protein S11.390.770.990.91SCO2563 30s ribosomal protein S20−0.34−0.340.770.33SCO2596 50S ribosomal protein L271.010.590.080.82SCO2597 ribosomal protein L210.270.080.64−0.18SCO3124 ribosomal L25p family protein0.390.31−0.23−0.89SCO3427 putative 50S ribosomal protein L310.240.370.220.60SCO3428 putative 50S ribosomal protein L330.150.280.540.09SCO3429 putative 50S ribosomal protein L280.680.160.550.45SCO3430 putative 30S ribosomal protein S14−0.800.10−0.17−0.19SCO3880 putative 50S ribosomal protein L341.020.130.240.71SCO3906 putative 30S ribosomal protein S60.700.941.11−0.18SCO3909 putative 50S ribosomal protein L91.300.010.87−1.27SCO4648 50S ribosomal protein L111.670.430.900.47SCO4649 50S ribosomal protein L10.620.53−0.250.92SCO4652 50S ribosomal protein L100.42−0.430.64−0.35SCO4653 50S ribosomal protein L7/L121.221.030.790.45SCO4659 30S ribosomal protein S120.740.650.70−0.53SCO4660 30S ribosomal protein S70.57−0.230.680.12SCO4701 30S ribosomal protein S101.191.171.16−0.21SCO4702 50S ribosomal protein L30.920.020.840.49SCO4703 50S ribosomal protein L41.160.910.590.23SCO4704 50S ribosomal protein L230.851.441.240.36SCO4705 50S ribosomal protein L20.85−0.120.840.22SCO4706 30S ribosomal protein S190.060.240.32−0.26SCO4707 50S ribosomal protein L220.960.690.640.15SCO4708 30S ribosomal protein S31.150.380.781.07SCO4709 50S ribosomal protein L160.520.671.091.26SCO4710 50S ribosomal protein L290.33−0.06−0.190.41SCO4711 30S ribosomal protein S170.590.920.51−0.13SCO4712 50S ribosomal protein L141.050.350.480.82SCO4713 50S ribosomal protein L241.090.880.630.64SCO4714 50S ribosomal protein L51.240.780.771.03SCO4715 30S ribosomal protein S140.390.030.190.12SCO4716 30S ribosomal protein S81.18−0.110.64−0.76SCO4717 50S ribosomal protein L60.960.820.79−0.02SCO4718 50S ribosomal protein L180.090.300.570.74SCO4719 30S ribosomal protein S51.560.661.02−0.09SCO4720 50S ribosomal protein L300.130.390.640.26SCO4721 50S ribosomal protein L151.790.420.800.84SCO4726 50S ribosomal protein L360.46−0.130.35−0.10SCO4727 30S ribosomal protein S130.63−0.230.62−0.17SCO4728 30S ribosomal protein S111.120.550.870.27SCO4730 50S ribosomal protein L170.690.270.860.51SCO4734 50S ribosomal protein L13−0.270.450.500.40SCO4735 30S ribosomal protein S90.36−0.020.00−0.01SCO5359 50S ribosomal protein L310.860.221.400.46SCO5564 putative 50S ribosomal protein L280.600.280.210.51SCO5591 30S ribosomal protein S160.440.030.57−0.60SCO5595 50S ribosomal protein L190.770.781.54−0.03SCO5624 30S ribosomal protein S21.160.481.520.30SCO5736 30S ribosomal protein S150.700.410.79−0.46Mean hybridization score for ribosomal protein genes0.670.350.610.18Bold values indicate that the signal for that gene is more than 2SD below the mean core signal for that species and such a value is suggestive of either gene absence or very low similarity Table 4 shows genes identified as possible sigma factors, anti-sigma factors and ant-sigma factor antagonists. The genes found in the central core region are more conserved. As would be expected, the major sigma factors such as hrdA, hrdB, hrdC and hrdD are conserved as well as many of the other studied sigma factors of S. coelicolor such as are sigA, sigE, sigF, sigG, sigR, sigT and whiG. Overall, fewer regulation genes from this group (anti-sigma factors and anti-anti-sigma factors) are conserved than sigma factors themselves. This analysis allows the identification of new candidate sigma factors for further study outside of the well studied ones, but within S. coelicolor and in other species. Overall, the results support the hypothesis that there is a core of sigma factors essential to keeping protein synthesis in Streptomyces running smoothly. The functionality of the rest may vary and include complete silence of some gene fragments, duplication of function, involvement in specific secondary metabolic activities and species/genus specific functions.Table 4Conservation across the four species of genes annotated as sigma factors or related proteins in Streptomyces coelicolor S.avermitilisS.cattleyaS. maritimusK. aureofaciens SCO0037 putative sigma factor−1.04−0.90−0.88−1.49SCO0159 putative ECF sigma factor−1.26−0.652.05−0.60SCO0194 putative sigma factor−0.87−0.35−0.61−0.52SCO0255 putative transcriptional regulator−0.64−0.37−0.99−0.46SCO0414 putative RNA polymerase sigma factor−0.05−0.28−0.15−0.22ConservedSCO0598 putative anti anti sigma factor0.110.50−0.080.57ConservedSCO0599 putative regulator of sig8−1.41−1.07−0.84−1.08SCO0632 putative RNA polymerase sigma factor−0.140.19−0.820.11SCO0672 putative anti-sigma factor antagonist−0.10−0.40−0.190.12SCO0781 putative anti sigma factor antagonist−0.79−0.86−1.06−0.83SCO0803 putative RNA polymerase sigma factor−0.25−0.09−0.51−0.01SCO0864 probable ECF-family sigma factor−0.74−0.86−1.04−0.50SCO0866 probable ECF-family sigma factor−0.130.19−0.280.23ConservedSCO0869 putative anti-sigma factor antagonist−0.59−0.90−1.23−0.90SCO0895 RNA polymerase principal sigma factor HrdC0.520.431.120.34ConservedSCO0942 putative RNA polymerase sigma factor0.340.810.610.45ConservedSCO1263 putative ECF-sigma factor−0.17−0.260.080.35ConservedSCO1276 RNA polymerase ECF sigma factor−1.22−0.550.60−0.88SCO1564 putative RNA polymerase sigma factor1.04−0.331.34−0.47SCO1723 putative RNA polymerase sigma factor0.19−0.39−0.150.52ConservedSCO1876 putative RNA polymerase sigma factor−1.01−0.93−0.77−0.50SCO2465 RNA polymerase principal sigma factor0.760.740.970.64ConservedSCO2639 putative RNA polymerase sigma factor0.740.220.010.27ConservedSCO2954 putative RNA polymerase sigma factor1.12−0.510.94−0.46SCO3066 putative regulator of Sig150.530.290.880.31ConservedSCO3067 putative anti anti sigma factor−0.74−1.250.89−0.42SCO3068 putative RNA polymerase sigma factor0.33−0.061.07−0.41ConservedSCO3202 RNA polymerase principal sigma factor0.980.291.400.19ConservedSCO3323 putative RNA polymerase sigma factor0.760.491.080.27ConservedSCO3356 ECF sigma factor 37−0.050.110.730.46ConservedSCO3450 putative RNA polymerase sigma factor (ECF subfamily)0.16−0.09−0.79−0.23SCO3548 putative anti-sigma factor−0.570.500.49−0.06SCO3549 bldG putative anti-sigma factor antagonist−0.03−0.160.21−0.20ConservedSCO3613 putative RNA polymerase sigma factor0.570.150.080.46ConservedSCO3692 putative anti-sigma factor antagonist0.140.64−0.270.13ConservedSCO3709 putative ECF sigma factor0.020.06−0.210.61ConservedSCO3715 putative ECF sigma factor0.450.92−0.28−0.27ConservedSCO3736 putative RNA polymerase ECF sigma factor−0.06−0.290.28−0.09ConservedSCO3892 putative RNA polymerase sigma factor0.680.210.80−0.27ConservedSCO4027 putative anti sigma factor antagonist−0.041.11−0.590.58SCO4034 putative RNA polymerase sigma factor0.981.271.260.22ConservedSCO4035 RNA polymerase sigma factor (fragment)1.041.270.880.45ConservedSCO4146 putative ECF subfamily sigma factor−0.230.530.580.16ConservedSCO4409 putative RNA polymerase sigma factor−0.100.120.100.64ConservedSCO4410 putative anti anti sigma factor−0.890.070.16−0.81SCO4452 putative sigma factor−0.17−0.21−0.080.27ConservedSCO4769 ECF sigma factor0.09−0.380.680.61SCO4864 putative ECF sigma factor0.02−0.34−0.12−0.73SCO4866 putative ECF sigma factor0.120.190.090.38ConservedSCO4895 putative ECF sigma factor−0.32−1.15−0.11−0.56SCO4938 putative ECF-sigma factor0.170.430.240.64ConservedSCO4960 possible sigma factor−0.040.05−0.660.60SCO4996 putative RNA polymerase ECF sigma factor−0.54−0.040.580.48SCO5147 putative ECF-subfamily sigma factor−0.390.350.790.59SCO5217 anti-sigma factor−0.47−0.050.28−0.80SCO5244 anti-sigma factor−0.32−0.54−0.37−0.29SCO5386 putative anti-sigma factor antagonist0.150.370.00-0.07ConservedSCO5621 RNA polymerase sigma factor WhiG0.790.920.64−0.27ConservedSCO5820 hrdB, major vegetative sigma factor1.361.061.531.09ConservedSCO5934 putative sigma factor0.070.25-0.580.17SCO6239 putative sigma factor−0.92−1.27−1.84−0.74SCO6996 putative RNA polymerase sigma factor-0.340.290.00−0.04ConservedSCO7099 putative RNA polymerase sigma factor−0.20−0.380.380.29SCO7104 putative RNA polymerase sigma factor−0.70−0.02−0.790.56SCO7112 putative ECF-family RNA polymerase sigma factor−0.35−0.25−1.65−0.38SCO7144 putative ECF sigma factor−0.620.13−0.910.34SCO7314 probable RNA polymerase sigma factor−0.25−0.110.230.46ConservedSCO7323 anti-sigma factor antagonist0.30−0.010.230.31ConservedSCO7325 anti-sigma factor antagonist-0.37-0.68−0.23−1.15SCO7341 putative RNA polymerase secondary sigma factor−0.090.540.290.44ConservedSCO7573 putative anti-sigma factor antagonist−0.180.03−1.690.21SCO7619 putative anti sigma factor antagonist−0.280.37−0.97−0.64SCO7754 putative anti-sigma factor antagonist−1.20−0.51−1.890.02Mean hybridization score for ribosomal protein genes0.010.060.100.05NABold values indicate that the signal for that gene is more than 2SD below the mean core signal for that species and such a value is suggestive of either gene absence or very low similarity. A conserved gene is one that seems to be present in all four species. NA, Not applicable All four species studied here undergo differentiation and spore formation and as such would be expected to retain most genes involved in cell division/sporulation/differentiation. This is supported by Table 5. K. aureofaciens shows greater gene divergence for certain genes when compared to the three Streptomyces species and these are specifically ftsI (SCO2090) and a putative cell division protein (SCO2968). However, in general, the same genes in all four species show a higher divergence, for example sapA, which is a protein associated with the spore surface hydrophobicity. As spore morphology varies a lot in the Streptomyces, high variability/gene loss in such a gene is not unexpected. Other genes that show higher divergence are those involved in partitioning and cell division. This suggests that the genes and thus the proteins involved in these functions may differ from species to species in order to create the variation seen in aerial mycelium and spore structure across Streptomyces species. Specifically, SCO3934, an ftsK family protein gene is less well conserved than its homologue. This suggests that SCO5750 may produce the major ftsK protein. Other Fts proteins show a similar pattern with at least one homologue being well conserved. This may well help an understanding of the relationships between the genes involved in cell division and will allow better identification of specific targets for further study. One anomaly that stands out is bldB. This gene consistently shows a low level of hybridization. A comparison of the bldB gene sequence between S. coelicolor and S. avermitilis shows a nucleotide identity of about 87%, which ought to give a signal in the region of 0.0 or better. As two different arrays are used in this study, mechanical problems with this spot can probably be eliminated as the source of the anomaly. We suggest that because this is a relatively small gene, the PCR product chosen for both arrays may be the reason for this result. This emphasizes that array data should be used with a degree of caution and needs to be backed up by other experimental evidence when specific genes are being investigated.Table 5Conservation across the four species of genes in Streptomyces coelicolor annotated as involved in cell division, sporulation and differentiation S. avermitilisS. cattleyaS. maritimus K. aureofaciensSCO0409 sapA spore-associated protein precursor−1.99−1.39−0.59−0.67SCO1454 putative amino oxidase1.000.451.18−0.17SCO1489 bldD putative DNA binding protein0.990.761.020.58SCO1772 putative partitioning or sporulation protein0.690.350.390.54SCO2082 ftsZ cell division protein1.440.890.970.95SCO2083 ftsQ sporulation protein0.320.740.060.26SCO2084 murG0.86−0.010.490.32SCO2085 fts W putative cell division protein0.820.810.590.50SCO2086 murD0.580.230.350.45SCO2087 murX0.410.050.51−0.30SCO2088 murF1.180.730.670.01SCO2089 murE0.730.470.360.31SCO2090 ftsl cell division protein0.800.010.45−0.50SCO2607 Sfr protein0.730.730.91−0.01SCO2608 penicillin binding protein−0.04−0.250.45−0.92SCO2609 mreD rod shape-determining protein0.090.070.660.43SCO2610 mreC rod shape-determining protein−0.42−0.160.17−0.52SCO2611 mreB rod shape-determining protein0.980.800.680.19SCO2620 putative cell division trigger factor0.81−0.120.500.25SCO2968 putative cell division protein0.35−0.170.34−0.39SCO2969 ftsE cell division ATP-binding protein0.37−0.430.00−0.51SCO3034 whiB sporulation regulatory protein0.230.500.810.26SCO3323 bldB putative RNA polymerase sigma factor0.760.491.080.27SCO3404 ftsH2 cell division protein ftsH homolog1.110.511.070.15SCO3549 bldG putative anti-sigma factor antagonist−0.03−0.160.21−0.20SCO3557 putative septum site determining protein0.310.45−0.190.92SCO3558 putative morphological differentiation-associated protein0.69−0.261.62−0.20SCO3846 putative FtsW/RodA/SpoVE family cell cycle protein1.110.311.070.61SCO3886 putative partitioning or sporulation protein0.00−0.83−0.43−0.98SCO3887 putative partitioning or sporulation protein−0.19−0.190.24−1.04SCO3934 ftsK/spoIIIE family protein−0.560.39−1.18−0.53SCO4014 sporulation associated protein−0.87−0.93−0.81−1.17SCO4184 mfC aerial mycelium formation0.120.170.01−0.05SCO4508 putative cell division-related protein−0.62−0.270.070.59SCO4531 putative septum determining protein−0.56−0.880.12−0.09SCO4620 traB1 putative sporulation-related protein−0.49−0.680.19−0.34SCO4621 traA1 putative sporulation-related protein−0.03−0.511.33−0.38SCO4767 putative regulatory protein0.140.001.67−0.01SCO4768 bldM putative two-component regulator1.061.000.920.61SCO5006 minD1 putative septum site-determining protein−0.31−0.040.58−0.28SCO5008 minD3 putative septum site-determining protein0.04−0.21−0.11−0.07SCO5112 BldKA−0.420.92−0.750.51SCO5114 BldKC−0.39−0.08−1.23−0.23SCO5115 BldKD0.01−0.18−0.89−0.15SCO5116 bldKE putative peptide transport system ATP-binding protein−0.04−0.22−0.70−0.03SCO5314 whiE protein VII−1.24−0.230.03−0.67SCO5315 polyketide cyclase−0.39−0.82−0.31−0.25SCO5316 acyl carrier protein−0.42−0.290.750.03SCO5318 polyketide beta-ketoacyl synthase alpha−0.03−0.130.860.43SCO5321 polyketide hydroxylase0.12−0.091.500.27SCO5587 ftsH cell division protein FtsH homolog−0.050.310.230.21SCO5621 whiG RNA polymerase sigma factor WhiG0.790.920.64−0.27SCO5723 bldB putative regulator, BldB−1.47−0.76−1.27−1.05SCO5750 ftsK homolog0.670.160.652.52SCO5819 whiH, sporulation transcription factor0.680.120.160.13SCO6029 whiI two-component regulator0.14−0.260.770.92Mean hybridization score for ribosomal protein genes0.05−0.050.27−0.02Bold values indicate that the signal for that gene is more than 2SD below the mean core signal for that species and such a value is suggestive of either gene absence or very low similarity The genes involved in DNA replication, repair, restriction/modification are shown in Table 6 and only about 20% of these genes are not conserved relatively well across all four species. This is to be expected as DNA replication and repair are core functions. Most of the genes that show higher levels of gene divergence are found in the terminal regions of the linear chromosome and probably are genes that perform functions that are not essential to cell survival because the terminal regions of Streptomyces chromosomes are unstable and liable to deletion without lethality. Of particular interest are SCO0183 and SCO0842 (deoxiribopyrmidine photolyases); these repair system would seem to be absent in S. lividans and S. maritimus, but a homologue is present in S. avermitilis (confirmed by the genome sequence) and in S. cattleya. This confirms the high variability found for this repair function across the Streptomyces (Kobayashi et al. 1989). A similar situation of high variability is found for the mutT homologues, potential 8 hydroxy-dGTP hydrolases. Knockout of this gene has been shown to increase the A:T to G:T mutation rate and thus it has a possible repair function (Kamiya et al. 2004). The genes for recA (SCO5769), recF (SCO3876) and recR (SCO3618) are present in all four species; however, the recX (SCO5770), is more divergent and gives a low signal for S. cattleya and S. maritimus. SCO6405, a putative DNA recombinase, is scored as absent in all four species suggesting that there is redundancy in the Streptomyces genes concerned with recombination or that this gene is transposon related. The latter is supported by low homology to S. avermitilis putative integrases/recombinases. There are four genes encoding DNA gyrases on the microarray, namely, gyrA DNA gyrase subunit A (SCO3873) and gyrB DNA gyrase subunit B (SCO3874) together with SCO5836 and SCO5822 and these may be TopIV homologues involved in resolving chromosome concatenates. All are conserved although the conservation of SCO5822 gyrB2 is lower. Thus both sets of gyrase genes would seem to be important. As expected, SCO1518, a ruvB Holliday junction protein gene and SCO1520, a ruvC crossover junction endonuclease are conserved across all the species. Unexpectedly, although probably present in all species, SCO1519 ruvA is much more divergent that the other two gene in this Holliday junction complex. This diversity is unexpected and not easily explicable except by the fact that recombination in Streptomyces may occur via a more variable mechanism than in other groups of bacteria and this is then reflected in the greater divergence of SCO1519 ruvA. All three genes annotated as a DNA polymerase 1 homologue are conserved as are four out of the five DNA polymerase III homologues, suggesting that there are roles for all of these conserved genes in Streptomyces. Two other unclassified DNA polymerase type genes, SCO4495 and SCO6084 are also conserved and thus may have important functions. There is, however, more diversity among the helicases and methylases/methyltransferases. With the helicases, three out of 14 show significant divergence and therefore most of the helicases probably have important cellular roles. Four out of nine methylases/methyltransferases show divergence. As some of these genes may be involved in the DNA modification part of restriction/modification, such diversity across strains in not unexpected. Finally, four out of six ligases show divergence, perhaps reflecting the fact that the origin of a number of these ligases might be from bacteriophages.Table 6Conservation across the four species of genes in Streptomyces coelicolor annotated as involved in DNA replication, repair, restriction and modification S. avermitilisS. cattleyaS. maritimusK. aureofaciensSCO0183 putative deoxyribodipyrimidine photolyase−1.38331−0.76404−1.15786−0.78973SCO0760 putative methyltransferase−0.23598−0.176030.079613−0.16712SCO0842 putative deoxyribodipyrimidine photolyase0.0024750.167429−0.051980.35453SCO0918 putative excinuclease ABC subunit A−0.28707−0.348130.010852−0.46861SCO0945 putative formamidopyrimidine-DNA glycosylase−0.34857−0.60698−0.4371−0.38083SCO1040 putative DNA repair protein0.0473150.5687230.4561680.367071SCO1050 putative DNA protection protein−0.474790.0932990.451487−0.92697SCO1114 uracil DNA glycosylase−0.345730.3571820.4339020.950894SCO1167 putative helicase (fragment)0.6048130.072648−0.40455−0.25074SCO1180 putative DNA polymerase III beta chain−0.347−0.21511−0.42838−0.20922SCO1202 putative DNA ligase0.3084970.202188−0.155240.096586SCO1203 putative MutT-like protein−0.17791−0.37050.324233−0.28871SCO1255 G/U mismatch-specific DNA glycosylase0.5216790.419040.3212080.429148SCO1343 uracil-DNA glycosylase0.612940.003390.3114780.036821SCO1380 putative DNA damage inducible protein0.7630640.3139480.2149310.677262SCO1395 mutT-like protein0.0682150.5725270.170710.414092SCO1475 putative primosomal protein0.0488920.6892320.535450.457655SCO1518 ruvB holliday junction DNA helicase1.1364890.6388030.9300671.045593SCO1519 ruvA holliday junction DNA helicase−0.57721−0.23275−0.153740.008274SCO1520 ruvC crossover junction endodeoxyribonuclease1.0797860.7081310.8863630.979821SCO1534 putative DNA polymerase III0.32960.371242−0.100250.090739SCO1739 putative DNA polymerase III1.1280490.4231581.1119640.326701SCO1780 putative DNA repair protein−0.14578−0.091750.258713−0.32746SCO1792 putative 3-methyladenine DNA glycosylase−0.20485−0.077550.083499−0.2824SCO1827 putative DNA polymerase III0.5597150.7112650.5128730.343849SCO1966 ABC excision nuclease subunit B0.0473820.068961.085903−0.05934SCO1969 putative DNA-methyltransferase−0.19025−0.121840.1433670.56545SCO2003 DNA polymerase I1.1721760.1884930.4981260.201411SCO2468 DNA primase0.827150.5205521.256130.69797SCO2626 putative DNA repair hydrolase (fragment)0.2899160.3373650.5677830.326821SCO2863 putative helicase−0.47935−0.68124−1.92881−0.81052SCO2952 putative helicase protein0.5139520.388640.7505170.379556SCO3109 putative transcriptional-repair coupling factor−0.87255−0.296110.759684−0.33637SCO3351 putative DNA repair protein−0.95043−0.685210.24637−0.48466SCO3352 putative DNA-binding protein0.090569−0.096020.536392−0.2275SCO3434 putative DNA polymerase I0.85541.6517680.8742461.328528SCO3510 putative DNA methylase0.402433−1.11393−2.15274−2.07607SCO3541 putative DNA polymerase0.003597−0.402890.297076−0.75003SCO3543 probable DNA topoisomerase I0.7987051.334770.878841.226661SCO3550 putative helicase0.2636440.139350.5598720.216127SCO3618 putative recomination protein0.5334040.0526230.511469−0.36893SCO3873 DNA gyrase subunit A1.293458−0.208510.985546−1.2494SCO3874 DNA gyrase subunit B0.993330.9582471.2506690.37466SCO3878 DNA polymerase III0.053750.0260530.328502−0.62343SCO3879 chromosomal replication initiator protein (fragment)1.259831.5725310.731065−0.12482SCO4092 ATP-dependent helicase−0.007520.0551940.978098−0.21188SCO4143 putative mutT-like protein0.0210350.4354710.479161−0.28423SCO4272 putative mutT-like protein−0.13520.016206−0.329680.527274SCO4351 putative DNA invertase−1.26688−0.78144−1.29284−0.68489SCO4495 putative DNA polymerase related protein−0.09624−0.759370.5824190.316259SCO4577 putative helicase0.7269620.0531961.044155−0.09189SCO4797 putative ATP-dependent DNA helicase II0.3233660.2864210.7498680.026912SCO5064 putative bifunctional protein−0.20262−0.49259−1.90763−0.29433SCO5143 DNA-3-methyladenine glycosylase I−0.865940.3424890.2766110.981316SCO5183 putative ATP-dependent DNA helicase0.2356330.1207650.7675040.591935SCO5184 putative ATP-dependent DNA helicase0.180638−0.175870.2088390.666073SCO5188 putative ATP-dependent DNA helicase0.204048−0.360050.808168−0.04087SCO5331 putative DNA methylase−1.52864−2.37483−3.76436−2.18209SCO5494 putative DNA ligase0.1247810.2884290.215946−0.0149SCO5566 putative ATP-dependent DNA helicase0.4089951.1867140.4281830.825946SCO5567 putative methylase0.338198−0.822070.596196−0.83241SCO5573 formamidopyrimidine-DNA glycosylase0.387552−0.083530.6015850.435209SCO5760 DNA glycosylase0.8469850.022350.6758760.46121SCO5770 RecX protein−0.1193−0.72104−0.580750.079675SCO5802 putative ATP-dependent helicase0.823429−0.104330.5115950.058287SCO5803 SOS regulatory protein LexA0.143322−0.78751−0.0905−0.16946SCO5805 ribonucleotide reductase0.2351820.2715140.98906−0.06823SCO5815 probable ATP-dependent DNA helicase−0.52023−0.31138−0.75254−0.71096SCO5822 gyrB2, probable DNA gyrase0.1672750.2234730.4268490.393883SCO5836 DNA gyrase-like protein0.7257080.5074980.9375310.073608SCO6084 putative DNA polymerase−0.053810.1656340.084564−0.16407SCO6151 putative methylated-DNA-protein-cysteine methyltransferase−0.88705−0.081120.3752140.207725SCO6262 putative helicase 6884138:6887071 forward MW:1039120.260624−0.288360.753508−0.08897SCO6405 putative DNA recombinase−0.16958−0.65562−1.15936−0.30768SCO6462 putative methylated-DNA-protein-cysteine methyltransferase−0.09961−0.002850.2318360.026866SCO6640 putative ATP-dependent helicase−0.56659−0.52367−1.18266−0.38994SCO6707 putative DNA ligase−0.254090.618121−0.0252−0.3333SCO6844 putative DNA methylase.0.4878060.475711−0.593870.230037SCO6907 putative DNA ligase.−0.714910.181384−0.67564−0.69734SCO7345 probable ATP-dependent DNA ligase0.1766920.2076060.3402550.085159SCO7522 putative DNA ligase−0.31874−0.0533−0.637010.470458Mean hybridization score0.1136330.0074410.153752−0.04491Bold values indicate that the signal for that gene is more than 2SD below the mean core signal for that species and such a value is suggestive of either gene absence or very low similarity Table 7 shows the genes involved in peptidoglycan and teichoic acid synthesis. In this area of metabolism, there is also a relatively high level of conservation of genes, particularly the murA, murA2, murB, murD, murE, murF,murG and murX genes. Also conserved are the shape-determining genes SCO2609, SCO2610 and SCO2611, which may form an operon. This probably represent a core of genes together with the genes involved in biosynthesis of the cell wall that are needed to give a basic structure to the cells of any Streptomyces species. The penicillin binding proteins show a higher degree of variability, except for SCO2897, SCO4013 and SCO5301. The peptidases SCO3580, SCO3596, SCO3011 and SCO4439 and the D-alanine:D-lactate ligase SCO3595 all show a low level of gene conservation, perhaps because they are involved in relatively broad cellular functions and not under a great deal of selective pressure.Table 7Conservation across the four species of genes in Streptomyces coelicolor annotated as involved in peptidoglycan biosynthesis S. avermitilisS.cattleyaS. maritimusK. aureofaciensSCO0237 putative oxidoreductase−0.07526−1.14854−0.09821−0.57347SCO0286 putative peptidoglycan binding protein−0.9459−0.93949−1.83967−1.02755SCO0830 putative penicillin-binding protein0.2434580.0813410.5560960.08585SCO0936 putative oligosaccharide deacetylase−0.78759−1.38608−0.58892−1.00821SCO1018 putative isomerase0.3905340.5192040.3926050.600019SCO1875 putative secreted penicillin binding protein−0.448310.0395980.3203560.256976SCO2084 murG0.85602−0.006770.4859890.319639SCO2085 putative cell division protein0.8166240.807420.5922140.502565SCO2086 murD0.5805060.2253480.3476740.449973SCO2087 murX0.4057310.0496450.509959−0.3047SCO2088 murF1.1750780.7309250.6673830.006107SCO2089 murE0.7340680.4708690.3634580.308295SCO2345 putative peptidodoglycan-binding membrane protein−0.03290.0163380.1333550.069404SCO2451 putative rod shape-determining protein0.6043270.1800280.6122430.205981SCO2589 putative glycosyl transferase0.093285−0.412170.478809−0.09528SCO2590 putative glycosyltransferase0.069933−0.52938−1.18523−0.89326SCO2608 penicillin binding protein−0.0413−0.246810.445143−0.92429SCO2609 rod shape-determining protein0.0858790.067210.6636090.427758SCO2610 rod shape-determining protein−0.41695−0.157980.168038−0.52083SCO2611 rod shape-determining protein0.9798840.7964030.6752040.186331SCO2706 putative transferase0.2334230.505652−0.555440.407847SCO2707 putative transferase0.014126−0.372250.088105−0.12772SCO2897 probable penicillin-binding protein0.5766460.4093880.6932370.120551SCO2949 murA0.4183630.2090240.3351590.062475SCO3580 putative transpeptidase−0.09884−0.76666−1.133470.212152SCO3595 putative D-alanine:D-lactate ligase−0.77707−1.21402−1.61266−1.31715SCO3596 putative D-alanine:D-alanine dipeptidase−1.47294−0.65926−1.4814−0.85496SCO3811 putative D-alanyl-D-alanine carboxypeptidase−0.50714−0.586170.155077−0.78413SCO3847 putative penicillin-binding protein0.128622−0.436430.640849−0.18456SCO3901 putative penicillin-binding protein−0.59684−0.78306−0.26692−0.39905SCO4013 putative penicillin binding protein−0.09095−0.01844−0.047970.164779SCO4132 putative secreted transglycosylase0.237226−0.17562−0.03522−0.2261SCO4439 putative D-alanyl-D-alanine carboxypeptidase−0.74865−0.930490.177585−1.21329SCO4643 murB−0.01505−0.206590.197283−0.35551SCO5039 putative penicillin-binding protein0.590106−0.709260.8918190.313533SCO5301 putative penicillin-binding protein−0.19347−0.131310.547233−0.22028SCO5365 putative transferase1.11236−0.273340.569152−1.16844SCO5467 muramoyl-pentapeptide carboxypeptidase−0.154480.387477−0.49044−0.02243SCO5560 D-alanine-D-alanine ligase0.7281120.2096020.1677690.330255SCO5998 murA20.8007260.7929751.2913680.051102SCO6060 putative UDP-N-acetylmuramoyl-L-alanine ligase0.199410.3770040.8173290.527531SCO7050 putative D-alanyl-D-alanine carboxypeptidase0.6059490.702030.3438270.524521Mean hybridization score0.125637−0.107440.118866−0.14494Bold values indicate that the signal for that gene is more than 2SD below the mean core signal for that species and such a value is suggestive of either gene absence or very low similarity Conserved genes with no known function Genes with no known function and no homologue outside of S. avermitilis that are conserved across the other three Streptomyces species should represent genes important to specifically being a myceliate Actinobacteria and the phenotype of gene knockout strains for these genes will be particularly interesting in terms of Streptomyces biology. Based on the dataset here, 936 genes can be identified as annotated as either conserved hypothetical genes or non-conserved hypothetical genes and these are shown in Supplementary Table 1. The proportion of these genes that are conserved across all four species are 9%, 20%, 13%, 16% and 12% for the left terminal region, left Streptomyces specific region, core region, right Streptomyces specific region and right terminal region, respectively. There is also a low frequency of conserved hypothetical genes in the left terminal region and right Streptomyces specific region, 0.78% and 0.96%, respectively compared to 3.4% for the left Streptomyces specific region, 1.80% for the core region and 2.11% for the right terminal region. It is clear that there is a need to further screen these genes by increasing the range of Streptomyces species analyzed by microarray hybridization. This will reduce the number to a manageable number and will allow prioritization of genes for knockout and detailed phenotypic analysis. Another approach to the problem of identifying functionally important genes is by the pinpointing of functional groups of such genes that may form a transcriptional unit. Blocks of three or more hypothetical genes that are conserved across all species were identified and are shown in Table 8. It is possible that these groups represent conserved functional groups of genes essential to core functions that make Streptomyces different from other bacteria. They are found mostly in the area between the Streptomyces terminal regions and the central core region. There are seven groups of conserved hypothetical genes larger than five genes (SCO1407–SCO1413, SCO2362–SCO2370, SCO2911–SCO2919, SCO3846–SCO3854, SCO5536–SCO5543, SCO5762–SCO5767 and SCO6522–6528). It is likely, due to the proximity of various genes around SCO3846–SCO3854, that this complex is involved in cell division, development and DNA partitioning. The function of the others groups is unknown. Interestingly, none of these gene groups are upregulated shifting from exponential phase to stationary phase or under stress shift as indicated by Karoonuthaisiri et al. (2005).Table 8Hypothetical genes in S. coelicolor conserved as a group in the four species analyzedGenes (SCO)Operon structureaLinked function if anyb0614, 0616, 0617, 0618None–1317, 1318, 1319, 1320None–1521, 1522, 1523, 1524Possible operonRecombination1634, 1635, 1636Possible operon–1650, 1651, 1652, 1653Possible operonProteosome1788, 1789, 1790, 1791, 1794, 1795, 1796Possible operonBoth flanks of rRNA gene homologues2030, 2031, 2032Possible operon–2124, 2125, 2127, 2129, 2130Possible operonGlucose kinase2268, 2269, 2270Possible operonClose to heme oxygenase2913, 2915, 2916, 2917None–3115, 3117, 3118, 3119None–3150, 3151, 3152, 3153None–3406, 3407, 3408Possible operonPenicillin binding protein3950, 3951, 3952Possible operonOxidoreductase4028, 4029, 4030None–4801, 4803, 4804, 4805None–5307, 5308, 5309, 5310, 5312None–5600, 5601, 5602, 5603, 5604Possible operonHomology to Mycobacterium tuberculosis5762, 5763, 5764, 5765Possible operonDNA helicase6413, 6415, 6416, 6417, 6419, 6420, 6421, 6422None–6574, 6575, 6576, 6577, 6578, 6579, 6580Possible operonPossible DNA binding protein6671, 6672, 6674, 6675, 6676Possible operon–7070, 7071, 7072None–a Gene structure from Artemis v7 is compatible with an operon type structure with possible appropriate ribosome binding sitesb Inside or linked to the conserved genes is a gene(s) of known function Conservation of genes involved in secondary metabolism and similar functions Genes that are involved in secondary metabolism and antibiotic production are widely distributed in the Streptomyces and many if not most may have been involved in horizontal transfer. However, there is significant similarity between genes involved in similar pathways and thus significant cross-hybridization may occur between similar metabolic pathways. A large number of genes are also involved in secondary metabolism (165) and polyketide synthesis (102) in the S. coelicolor genome. These are grouped together in 23 pathway groups and are displayed in Supplementary Fig. 3. Genes identified as secondary metabolic genes but existing on their own and not in a group of secondary metabolic genes have been eliminated to simplify the analysis leaving only genes involved in these functions with two or more genes together in a group. These include specific pathways producing secondary metabolic products such as melanin, actinorhodin, CDA and Red pathway. Many of the other potential pathways have not been studied in detail and the functions of these genes are unknown. Because of evolutionary similarity, the presence of genes hybridizing to a particular pathway does not mean that the specific pathway is present, but possibly that a related one is may be present. Similarly, a high level of hybridization can mean either a very close relationship between the pathways in the two species or the presence of multiple copies of related pathways. In general terms S. maritimus shows the greatest absence of secondary metabolic pathways that are present in S. coelicolor. Interesting, S. cattleya and K. aureofaciens seems to have pathways related to many of the S. coelicolor secondary metabolic pathways present in their genomes, although they are phylogenetically more distant than S. maritimus. The actinorhodin pathway would seem to be absent from S. avermitilis (as expected from the genome data), S. cattleya and S. maritimus although some related genes do seem to be present in K. aureofaciens. The WhiE pathway is conserved in all species, but with some genes showing a very low level of hybridization in certain cases and these include whiE protein VII and the acyl carrier protein. Genes from the Red pathway show varying levels of hybridization suggesting that distantly related pathways may be present in these species. The CDA pathway is conserved in all four species and in certain cases the genes seem to be over represented suggesting multiple examples of the same type of pathway in S. cattleya and S. maritimus. The presence of similar pathways at a level of about 50% for K. aureofaciens supports the well established idea that horizontal gene transfer of secondary metabolic pathways may have played a significant role in the evolution of the Streptomyces and any related genus. Because the natural environment of Streptomyces is the soil, they are thought to play an important role in the recycling of lignocellulose material. However, there is relatively little information on what genes are involved in this process. Interestingly, melC1 and melC2, which encode tyrosinase (monophenol monooxygenase, SCO2700) and its cofactor (SCO2701) (Leu et al. 1992) are conserved across the three Streptomyces species and probably also Kitasatospora (SCO2700 −0.76, SCO2701 0.08). On the other hand, the duplicate MelD1 (SCO2701) and MelD2 (SCO2700) genes found in S. coelicolor are not conserved and are phylogenetically distinct from MelC1 and MelC2 found in other Streptomyces (unpublished results). This perhaps represents a divergence of function between this two gene pairs. S. coelicolor does not produce a detectable amount of black melanin pigment and these results suggest that these enzymes may be involved in the metabolic conversion of lignocellulose byproducts rather than pigment formation. Evolutionary conservation of these genes to serve this function under particular conditions of induction would make more sense than retention of inducible black pigment formation. Other enzymes with a possible role in the lignocellulose cycle that are conserved across the species are shown in Table 9. These include many oxygenases that may have a role in producing oxygen radicals capable of attacking lignin, genes involved in the sensing and breaking down hydrogen peroxide, cellulose metabolism genes, cellobiose metabolism genes, etc. Those found in the terminal regions may represent gene groups that are not conserved in a syntenous manner and subject to horizontal gene transfer, while those within the core and intermediate regions may be part of the basic group of genes essential to Streptomyces in the soil environment. Lignocellulose degradation is a difficult topic to study in the Actinomycetales and therefore these candidate genes may help to solve some of the problems associated with this.Table 9Genes conserved in the four Streptomyces species that are potentially involved in lignocellulose cyclingSCO0333DioxygenaseSCO0560Catalase/PeroxidaseSCO0765EndoglucanaseSCO1187CellulaseSCO1188Cellulose binding proteinSCO1338MonooxygenaseSCO1451EndoglucanaseSCO1923DioxygenaseSCO2016MonooxygenaseSCO2267Heme oxygenaseSCO2700Tyrosinase (monophenol monooxygenase)SCO2701Tyrosinase cofactorSCO2783MonooxygenaseSCO2798Cellobiose hydrolaseSCO2838EndoglucanaseSCO3172MonooxygenaseSCO3236OxygenaseSCO4416MonooxygenaseSCO4870MonooxygenaseSCO5033Hydrogen peroxide sensing regulatorSCO5293OxygenaseSCO5390Alkanal monoxygenaseSCO5773MonooxygenaseSCO6545CellulaseSCO7223MonooxygenaseSCO7637EndoglucanaseNote that the oxygeneases included as possible enzymes that make be able to attack lignin are all unclassified yet as to their real function. The core region is in bold Conclusions This study confirms that within the Streptomyces analyzed here there is conservation of a core set of genes in the middle of the linear S. coelicolor/S. avermitilis chromosome structure. This is associated with a much higher diversity of gene in the terminal regions of the linear chromosome. Linking these regions are two intermediate regions where there seems to be conservation of genus specific genes and gene clusters. This study also identifies candidate genes that may be possibly involved in terminal replication and other myceliate growth related functions based on a classification of genes into conserved and none conserved groups. This study also provides insights into which genes in Streptomyces play a more significant role in the biochemical network of S. coelicolor, Streptomyces and myceliate Actinobacteria in general. Finally, the degree of gene conserved detected between the four species implies that that genome model of S. coelicolor may extent well beyond the borders of the Streptomyces. It includes at least one Kitasatospora species; furthermore, a similar structure by microarray analysis has been found for Saccharomonospora viridis and Streptosporangium roseum, but not Streptomyces rimosus ATCC10970 (unpublished data). Thus, the microarray approach to genome content analysis and exploration of genome evolution may be fairly widely applicable in the various Actinomycete genus close to Streptomyces that undergo complex morphogenesis. Electronic supplementary material Below is the link to the electronic supplementary material ESM (PDF 938 kb)

Int_J_Colorectal_Dis-4-1-2225995

Certolizumab pegol, a monthly subcutaneously administered Fc-free anti-TNFα, improves health-related quality of life in patients with moderate to severe Crohn’s disease

Background and aims Certolizumab pegol, a polyethylene glycolated Fc-free Fab’ was efficacious and well tolerated in patients with moderate-to-severe Crohn’s disease in a previously reported randomized, placebo-controlled study. In this paper, we report the effect of certolizumab pegol on health-related quality of life (HRQoL). Introduction Crohn’s disease is a chronic relapsing and remitting, inflammatory bowel disease (IBD) that has a significant impact on health-related quality of life (HRQoL) [1, 2]. HRQoL has been recognized as an important health outcome and has been defined in the medical setting as “a concept encompassing a broad range of physical and psychological characteristics and limitations which describe an individual’s ability to function and derive satisfaction from doing so” [3]. Crohn’s disease frequently begins in early adulthood, causing a heavy disease burden in a relatively young patient population. Consequently, many patients will be affected for most of their adult life. In Crohn’s disease, health status is affected as much by psychosocial factors and functional status as by disease activity [4]. For example, the need to wear an ostomy bag may adversely affect self-image, and this has been reported to be a common worry for patients with Crohn’s disease [5]. Moreover, previous studies have demonstrated a high correlation between disease severity, as measured by the Crohn’s Disease Activity Index (CDAI) [6], and HRQoL, as assessed using the Inflammatory Bowel Disease Questionnaire (IBDQ) [7, 8]. A large longitudinal study prospectively assessed the HRQoL of patients with Crohn’s disease over 1 year and determined influencing factors [9]. The following factors were associated with a negative impact on overall HRQoL: female gender, tobacco use, active Crohn’s disease, involvement of the colon, hospitalization, corticosteroid treatment, and surgery in the past 3 months (order does not indicate priority). These findings were reflected in a survey of patients with a long-term diagnosis of Crohn’s disease [10]. It is therefore important to include improvement in HRQoL as a key therapeutic goal in the treatment of patients with Crohn’s disease. Conventional treatment options for Crohn’s disease include aminosalicylates, antibiotics, corticosteroids, immunomodulators, and surgery. However, in some patients, the disease can be refractory or unresponsive to certain pharmacologic treatments. Furthermore, corticosteroids are associated with a risk of dependency and potentially serious side effects (e.g., diabetes, osteoporosis, moon face, and acne), which are detrimental to a patient’s HRQoL and may negatively affect self-esteem [11–13]. Such treatments therefore require careful management. Additionally, it is rarely possible to achieve long-term relief from Crohn’s disease with a single surgical procedure, and as a result, patients with Crohn’s disease fear surgery so much that their HRQoL is reduced [14]. It is now well accepted that tumor necrosis factor α (TNFα) plays a pivotal role in the underlying inflammatory pathophysiology of Crohn’s disease [15]. Furthermore, neutralization of TNFα has been shown to improve the symptoms of this debilitating illness [13, 16]. Infliximab has been shown to improve HRQoL, as measured by the IBDQ and the Short-Form Health Survey (SF-36) [8, 17], but the occurrence of infusion reactions along with the risk of developing anti-infliximab antibodies, which can reduce long-term efficacy [18], could negatively impact HRQoL over time. Patients may feel that subcutaneous treatment has advantages over treatments requiring infusion; a long stay at the clinic may negatively impact a patient’s daily life. This increased freedom in patient treatment management may lead to improved treatment compliance with a consequent impact on therapeutic outcomes. Thus, there is a need for alternative long-term therapies for moderate-to-severe Crohn’s disease that have minimal negative impact on patients’ everyday life while also reducing the impact of the disease on patients’ HRQoL [19]. Certolizumab pegol is the first polyethylene glycolated (PEGylated) anti-TNFα antibody fragment (Fab’) to be studied in Crohn’s disease. Unlike conventional anti-TNF agents, certolizumab pegol lacks the crystallizable fragment (Fc) region, thus potentially avoiding unwanted effects [20]. PEGylation increases the plasma half-life and reduces the frequency of dosing required. Certolizumab pegol is administered by subcutaneous injection once every 4 weeks (more frequent dosing may be used during an induction phase). Certolizumab pegol 400 mg administered subcutaneously demonstrated efficacy and was well tolerated in patients with moderate-to-severe active Crohn’s disease in phases II [21] and III (PRECiSE 1 and PRECiSE 2 [22, 23]) studies. Certolizumab pegol has also demonstrated clinical efficacy and good tolerability in patients with rheumatoid arthritis [24, 25]. This is the first paper to report the effect of certolizumab pegol, a monthly subcutaneous treatment, on the HRQoL of patients with moderate-to-severe active Crohn’s disease in a phase II placebo-controlled study [18]. HRQoL was assessed using the IBDQ. Materials and methods Ethical conduct This study was approved by the Independent Ethics Committee/Institutional Review Board for each center before initiation. It was conducted in accordance with the International Conference for Harmonization Guidelines for Good Clinical Practice and the declaration of Helsinki (revised 1996). Written informed consent was obtained from each patient at screening before any study procedures were performed. Patients Adult patients (age ≥18 years) with moderate-to-severe active Crohn’s disease, as defined by a CDAI score of 220–450 points during the week before the administration of the first dose of study drug, were eligible for the study. Exclusion criteria included suspected or diagnosed abscess, a bowel perforation or evidence of non-inflammatory obstruction in 6 months before screening, extensive bowel resection, a functional colostomy or ileostomy, or a known history of tuberculosis. Concomitant medication was allowed, provided that doses were stable and could be continued for the 12-week double-blind period and the 8-week follow-up. Study design This was a multicenter, randomized, double-blind, placebo-controlled, 12-week study conducted at 58 international centers between February 2001 and March 2002. An 8-week follow-up period allowed collection of additional safety data. At screening, patients with moderate-to-severe active Crohn’s disease were stratified according to concomitant steroids, immunosuppressants, or long-term anti-infectives. Eligible patients were randomized (1:1:1:1) to receive certolizumab pegol (100, 200, or 400 mg) or placebo (0.9% w/v saline) by subcutaneous injection at weeks 0, 4, and 8 (Fig. 1). Before dosing, patients’ demography, medical history, and concomitant diseases were recorded. Fig. 1Study design (showing the total numbers of patients recruited into each treatment group) Outcomes The primary endpoint of the study was the proportion of patients achieving a clinical response [≥100-point decrease in CDAI score or CDAI score ≤150 points (remission)] at week 12. HRQoL was a secondary endpoint evaluated at baseline (week 0, pre-injection) and at weeks 2, 4, 6, 8, 10, and 12 using the 32-item self-administered IBDQ. The IBDQ is a disease-specific HRQoL measure. The questionnaire assesses the four aspects of a patient’s life that are affected by IBD: symptoms directly related to the primary bowel symptoms, systemic symptoms, emotional function, and social function [26]. The reliability, validity, and responsiveness of the IBDQ have been demonstrated by Guyatt et al. [26, 27] and Irvine et al. [7, 28]. The IBDQ is completed using a 7-point Likert response for each question. Total IBDQ scores range from 32 to 224, with a higher score indicating better HRQoL. Remission is generally indicated by a score of at least 170 points, and a change of 16 points is regarded as clinically meaningful [7]. In addition to a total score, domain scores can be calculated for the Bowel Symptoms, Systemic Symptoms, Emotional Function, and Social Function domains. IBDQ measurements were performed in parallel with determination of CDAI score and serum concentrations of C-reactive protein (CRP). Official IBDQ versions translated into Danish, French, German, and Swedish were used. Our own translations were used for Russian, Serbian, and Afrikaans. To assess whether our own translated versions of the IBDQ provided a valid measure of HRQoL, we compared scores of the translated versions with those of the official translated versions and evaluated those scores in relation to the patient’s CDAI scores. A sensitivity analysis was also carried out to check for influence of specific item scores on the resulting total scores. The results of these analyses demonstrated that our own translated versions of the IBDQ provided a valid measure of HRQoL, comparable to the official, translated versions. Statistical analysis A sample size of 260 patients was calculated to give approximately 83% power to detect a true difference between treatment groups of 23% for the primary endpoint of the study, based on a placebo response rate of 12%. After screening, patients were to be randomized in a 1:1:1:1 ratio (65 patients to each of the four treatment groups). Therefore, 195 patients were to receive certolizumab pegol and 65 were to receive placebo. Efficacy was assessed for the intent-to-treat (ITT) population, which included all patients who received at least one injection and had at least one efficacy measurement after the first injection. Patients who terminated the trial prematurely were advanced to the end-of-study visit. The last observation carried forward method was used in cases where data were missing. Post hoc analyses of IBDQ total score and individual domain scores were performed. These were purely exploratory in nature. Relationships between CDAI and IBDQ global scores at week 12 were assessed for the ITT population using Kendall’s tau coefficient, a measure of the strength of dependence showing to what extent these two variables move in the same direction. Changes from baseline in IBDQ total score and individual domain scores for each treatment group were formally compared with the placebo group. Least-squares means, adjusted for stratum, pooled country, and baseline IBDQ score, were compared across treatment groups. Fisher’s exact test was used to compare the proportion of patients who achieved remission (defined as an IBDQ total score of ≥170 points) in each active treatment group with that for the placebo group at each week. The analyses were performed based on both the overall ITT population and in the subgroup of patients with elevated baseline CRP (≥10 mg/l). P values ≤0.05 were considered to be statistically significant. Results The clinical efficacy and safety assessments of this phase II dose-finding study have been reported in detail elsewhere [21]. Because the 400 mg dose was identified as being the most appropriate dose, this paper focuses on data for patients receiving certolizumab pegol 400 mg. Patients In total, 372 patients were screened of whom 292 patients were enrolled (CDAI score <220 points was the most common reason for screening failure). Of these 292 patients, 291 were included in the ITT population used to measure the efficacy endpoints according to CDAI scores [1 patient (400 mg group) was excluded because of missing efficacy data]. Baseline IBDQ scores were not obtained for one patient in the certolizumab pegol 100 mg treatment group. The ITT analyses for the HRQoL evaluations therefore included data for 290 patients. Seventy-five patients (25.7%) withdrew from the study by week 12. The majority of withdrawals were a consequence of lack of improvement/disease progression. Baseline CRP measurements were obtained for 290 of the 291 patients in the ITT population. Elevated baseline CRP levels (≥10 mg/l) were recorded for 119 patients (41.0%). One of these patients was the patient in the certolizumab pegol 100 mg treatment group who was excluded from analyses as a result of baseline IBDQ scores not being obtained. The subgroup analyses of IBDQ by baseline CRP status were therefore performed on data from 118 patients with an elevated baseline CRP concentration. The four treatment groups were generally well matched in terms of demographic and clinical characteristics (including baseline IBDQ total score and concomitant medication profile; Table 1). In the ITT population, 21.6% of patients had received previous anti-TNFα therapy, and 15.5% had concomitant medication with both immunomodulators and steroids. Table 1Baseline demographic and clinical characteristics (intent to treat population used to measure efficacy endpoints according to Crohn’s Disease Activity Index scores) Placebo(n = 73)Certolizumab pegol100 mg (n = 74)200 mg (n = 72)400 mg (n = 72)Mean CDAI score (range)291.5 (206–448)299.2 (194–520)310.7 (184–446)304.5 (204–461)Mean IBDQ score (range)a122.9 (61–190)132.2 (66–189)b122.9 (74–189)126.5 (71–177)Geometric mean plasma CRP, mg/l (range)7.268 (0.27–86.10)6.231 (0.15–141.00)b6.475 (0.17–127.00)7.738 (0.35–128.28)CRP ≥ 10 mg/l, n (%)28 (38.4)31 (42.5)b28 (38.9)32 (44.4)Concomitant medications, n (%)  Aminosalicylates29 (39.7)37 (50.0)32 (44.4)28 (38.9)  Anti-infectives7 (9.6)6 (8.1)7 (9.7)6 (8.3)  Antidiarrheals10 (13.7)19 (25.7)16 (22.2)12 (16.7)  Steroids29 (39.7)24 (32.4)29 (40.3)22 (30.6)  Codeine and derivatives6 (8.2)5 (6.8)5 (6.9)2 (2.8)Immunomodulators  Azathioprine17 (23.3)13 (17.6)23 (31.9)22 (30.6)  6-Mercaptopurine4 (5.5)9 (12.2)2 (2.8)2 (2.8)  Methotrexate5 (6.8)4 (5.4)4 (5.6)3 (4.2)CDAI Crohn’s Disease Activity Index; CRP C-reactive protein; IBDQ Inflammatory Bowel Disease Questionnaire; n number of patientsaMaximum score is 224 points.bData missing for one patient. Clinical response The onset of effect (clinical response) of certolizumab pegol was evident at week 2, when certolizumab pegol treatment produced a statistically significant improvement in CDAI score compared with placebo (certolizumab pegol 400 mg 33.3% vs placebo 15.1%; P = 0.010). Clinical response rates were highest in the certolizumab pegol 400 mg group at all time points, with maximal response at week 10 (certolizumab pegol 400 mg 52.8% vs placebo 30.1%; P = 0.006) [21]. Lower CDAI score (representing lower disease severity) was associated with a higher IBDQ global score (representing better HRQoL), as reflected by a high negative Kendall’s tau value (−0.48; P < 0.0001) Clinical response was observed irrespective of baseline CRP level. Improvement in HRQoL Patients demonstrated HRQoL improvements from baseline, as measured by change in IBDQ total score, by the first assessment point, week 2 [certolizumab pegol 100 mg, 16.6 points; certolizumab pegol 200 mg, 21.8 points (P ≤ 0.05 vs placebo); certolizumab pegol 400 mg, 22.8 points (P ≤ 0.05 vs placebo); placebo, 10.6 points] (Fig. 2). Patients receiving certolizumab pegol 400 mg experienced statistically significantly greater improvements from baseline in IBDQ total score at all time points (P ≤ 0.05) compared with those receiving placebo. The greatest increase in IBDQ total score was recorded at week 10 (certolizumab pegol 400 mg 32.2 points vs 18.6 points for placebo; P ≤ 0.05). Approximately half of the patients treated with certolizumab pegol 400 mg demonstrated clinically meaningful improvements in IBDQ total score (≥16-point increase) at week 2 (52.8%) and at week 12 (66.7%). Fig. 2Mean change from baseline in Inflammatory Bowel Disease Questionnaire (IBDQ) total score during 12 weeks’ subcutaneous treatment with either certolizumab pegol or placebo in patients with moderate-to-severe Crohn’s disease (intent-to-treat population); least-squares means (adjusted for stratum, pooled country, and baseline score) As early as week 2, patients receiving certolizumab pegol 400 mg demonstrated statistically significant improvements in the Bowel Symptoms and Emotional Function domains of the IBDQ relative to placebo (Fig. 3). Improvement in the Systemic Symptoms domain score approached statistical significance at week 2 (P = 0.054). These improvements were generally dose-related (Figs. 3a−d). Interestingly, patients in the certolizumab pegol 200 mg group achieved statistically significantly greater improvements than those receiving placebo in IBDQ total score and all four IBDQ domains at week 2 (Figs. 2 and 3a–d). Fig. 3Mean change from baseline in Inflammatory Bowel Disease Questionnaire (IBDQ) domain scores during 12 weeks subcutaneous treatment with either certolizumab pegol or placebo in patients with moderate-to-severe Crohn’s disease (intent-to-treat population); least-squares means (adjusted for stratum, pooled country, and baseline score): a Bowel Symptoms domain, b Systemic Symptoms domain, c Emotional Function domain, and d Social Function domain Emotional Function and Systemic Symptoms were the domains that patients reported as being most improved by certolizumab pegol treatment. At every assessment, patients receiving certolizumab pegol 400 mg showed statistically significantly (P ≤ 0.05) greater improvements in Emotional Function domain scores than those receiving placebo (Fig. 3c). They also demonstrated statistically significantly greater improvements in Systemic Symptoms domain scores than those receiving placebo at weeks 4, 8, 10, and 12 (Fig. 3b). The improvements patients experienced in Social Function domain scores approached statistical significance (P = 0.054) at week 4 (Fig. 3d). The remission rate in the certolizumab pegol 400 mg group was highest at week 10. This was statistically significantly greater than in the placebo group (Table 2). The proportion of patients achieving remission in the certolizumab pegol 400 mg group was also statistically significantly greater than in the placebo group at weeks 6, 8, and 12. The subgroup of patients with elevated CRP showed similar improvements in IBDQ scores to those observed in the ITT population. Table 2Proportion of patients achieving remission defined by Inflammatory Bowel Disease Questionnaire total score (≥170 points)Patients (%), intent-to-treat population (n = 290)WeekPlacebo (n = 73)Certolizumab pegol100 mg (n = 73)200 mg (n = 72)400 mg (n = 72)217.832.919.427.8419.237.0a*26.433.3617.835.6*30.638.9*821.935.629.238.9*1027.443.836.147.2*1223.338.423.638.9*aThe higher remission rate at week 2 in the certolizumab pegol 100 mg group compared with higher-dose groups may reflect the slightly higher mean Inflammatory Bowel Disease Questionnaire (IBDQ) score at baseline in this group. However, certolizumab pegol 400 mg resulted in the greatest mean change in IBDQ at all time points.*p ≤ 0.05 vs placebo Discussion Patients with Crohn’s disease often have poor HRQoL [29], with disease-related concerns, such as worry about needing surgery, being the main causal factor [10]. It therefore follows that treatments relieving the symptoms of Crohn’s disease and/or reducing the risk of surgery should improve HRQoL in patients with Crohn’s disease. Certolizumab pegol administered subcutaneously every 4 weeks is a rapid and clinically effective treatment of moderate-to-severe Crohn’s disease with the 400 mg dose (highest dose tested) inducing the highest response rates [21, 22, 23]. This analysis indicates that such clinical findings are accompanied by improvements in HRQoL. Certolizumab pegol 400 mg appears to exert a rapid, consistently positive effect on HRQoL in patients with moderate-to-severe Crohn’s disease. Patients who received certolizumab pegol 400 mg demonstrated statistically significantly greater improvements in IBDQ total score than those in the placebo group as early as week 2 and at all subsequent time points. As a reflection of the lower baseline IBDQ scores in the 400 mg group, patients in this group experienced the greatest improvement, despite the remission rate (which is the proportion of patients reaching a pre-defined score) being higher in the 100 mg group. Improvements in HRQoL were not dependent on baseline CRP level. Higher baseline CRP concentration was associated with greater improvement in clinical variables in this phase II study [21], but such a relationship has not been evident in phase III studies [30]. In addition, patients receiving certolizumab pegol 200 mg showed a statistically significantly greater change from baseline in IBDQ total score than those receiving placebo at weeks 2 and 4. Collectively, these findings suggest that certolizumab pegol has an early treatment effect in patients with moderate-to-severe Crohn’s disease. The benefits of certolizumab pegol on HRQoL were also apparent in the phase III studies [22, 23, 31, 32]. Improvements in emotional well-being (e.g. depression, anxiety, irritability, and anger resulting from bowel problems) and systemic symptom domains were particularly marked with certolizumab pegol treatment. It appears that the improvements in these two domains of the IBDQ are largely responsible for the reported beneficial effect of certolizumab pegol on HRQoL. Overall, these findings suggest that certolizumab pegol alleviates the psychological symptoms associated with Crohn’s disease and improves a patient’s general well-being, in addition to providing clinical benefits in terms of CDAI response. HRQoL provides an integral picture of the interactions between a patient’s disease, their treatment, and quality of life—positive effects resulting from the efficacy of a treatment and negative effects caused by adverse events are evaluated. Few trials have examined the effects of conventional agents upon HRQoL in patients with Crohn’s disease. While corticosteroids are effective in controlling acute Crohn’s disease and are reported to improve IBDQ scores [33], the potentially serious adverse events associated with corticosteroids may negate any positive effects on HRQoL gained through control of symptoms. Additionally, corticosteroids are not suitable for maintenance treatment. Improvements in HRQoL have been observed with methotrexate treatment in a large, randomized, double-blind, placebo-controlled study [34]. However, 17% of patients (16/94) receiving methotrexate were withdrawn from the study because of adverse events compared with 2% of placebo-treated patients (1/47). The improvements in HRQoL observed with certolizumab pegol in this study appear to be similar to those reported in patients with Crohn’s disease after treatment with infliximab [8, 17, 35]. Similarly, natalizumab has been shown to improve HRQoL in patients with Crohn’s disease [36]. Given the detrimental effects of Crohn’s disease on physical and psychosocial functioning, additional research is needed to assess the impact of currently available and newer therapies on HRQoL. Although HRQoL was evaluated using the self-administered IBDQ, which has proved to be a valid and reliable disease-specific instrument for determining health status in patients with Crohn’s disease [7], the analyses presented in this paper were purely exploratory in nature, and firm conclusions cannot be drawn from the results described. However, clinical benefit was also accompanied by improved HRQoL in the phase III studies [22, 23, 31, 32]. Further benefits may be gained through the good tolerability of certolizumab pegol [37] and convenience of subcutaneous dosing with certolizumab pegol once every 4 weeks. Conclusions This study demonstrates that the clinical efficacy of certolizumab pegol in patients with moderate-to-severe Crohn’s disease, which is evident within 2 weeks of injection, is paralleled by improvements in HRQoL. The benefits of certolizumab pegol were most pronounced at the highest dose tested (400 g). Improvements in emotional well-being and systemic symptoms appear to be largely responsible for the observed beneficial effect of certolizumab pegol on HRQoL.

Virchows_Arch-3-1-1888722

Search for residual prostate cancer on pT0 radical prostatectomy after positive biopsy

Reported incidence of no residual prostate cancer (i.e. pathological stage pT0) on radical prostatectomy ranges from 0.07 to 4.2%. The incidence is higher after neoadjuvant endocrine treatment. The aim of this study was to search for residual cancer on radical prostatectomy (RP) specimens when an initial sampling failed to find the cancer in patients with positive biopsy. Our database of 1,328 consecutive patients whose biopsies and RP specimen were both examined at the Polytechnic University-United Hospitals of the Marche Region between March 1995 and June 2006 was reviewed. The radical prostatectomies were grossly completely sampled and examined with the whole mount technique. We identified eight patients (i.e. 0.6%; three untreated and five hormonally treated preoperatively, i.e. 0.3 and 0.8%, respectively, of the total number of RPs included in the study) with positive biopsy and with no residual cancer in the initial routine histological examination of the RP. The RP of this group of eight was subjected to additional sectioning and evaluation of the paraffin blocks of the prostatectomy, also after block-flipping, immunostaining with an antibody against CAM 5.2, p63, PSA, and alpha-methylacyl-CoA racemase, and DNA specimen identity analysis. There were no cases with a false positive biopsy diagnosis, and cancer was not overlooked or missed in the initial routine histological examination of any of the 8 pT0 RPs. A minute focus of cancer (the diameter was always below 2.0 mm) was found on the additional sections in five. In particular, cancer was found after block-flipping in one of them. In an additional case, cancer was eventually discovered after immunostaining tissue sections for cytokeratin CAM 5.2, for p63 and PSA. In the remaining two cases (one untreated and the other hormonally treated), cancer was not found (0.15% of the 1,328 RPs included in the study); the review of the description of the macroscopic appearance of the RP and of its slides revealed that part of the peripheral zone corresponding to the site of the positive biopsy was missing, i.e. not removed from the patient at the time of the operation at least in one of the two. DNA specimen analysis confirmed the identity of the biopsy and prostatectomy in both. An extensive search for residual cancer reduces the number of pT0 RPs after a positive biopsy from 0.6 to 0.15%. It is recommended to have the needle biopsy reviewed, carefully look again at the radical prostatectomy, do deeper sections and then flip certain paraffin blocks. In addition, atypical foci should be stained for basal cell markers and often AMACR, especially in hormone-treated cases. If a block is missing part of the peripheral zone (capsular incision), this should be commented on. DNA analysis for tissue identity should be performed when the other steps have been taken without finding cancer. Introduction In 1995, Goldstein et al. [9] introduced the term vanishing cancer phenomenon referring to cases with minute or no cancer on radical prostatectomy after a positive biopsy. They reported 13 patients with minimal (11 patients) or no (two patients) cancer in prostatectomy specimens. In two cases with no residual cancer on RP, they confirmed the identity of the biopsy and the prostatectomy tissue by DNA matching. The Johns Hopkins Hospital group documented a fivefold increase in the incidence of no residual cancer on prostatectomy in patients in whom both biopsies and prostatectomies were performed at that institution between 1997 and 2005 (0.07% in 1997, 0.13% in 2004 and 0.34% in 2005) [5, 7, 30]. In their first study, they also documented two cases, one in which the biopsy review revealed only high-grade PIN and in which a diagnosis of cancer had been established in another institution, and a second case in which the possibility of specimen switching could not be ruled out due to DNA mismatch between the biopsy and the prostatectomy. Most recently, they have reported a series of 46 patients, 11 with no residual cancer on prostatectomy and 35 with minute cancer, and in 40 cases, they documented specimen identity [5]. In five of the six remaining cases, the results could not be interpreted due to technical problems, and in one case, the tissue from the biopsy with cancer did not match the tissue from the radical prostatectomy. Bostwick and Bostwick [4] found that 38 patients with no cancer on prostatectomy, identified among 6,843 radical prostatectomies performed at Mayo Clinic during a 30-year period, showed no disease recurrence or progression after a mean follow-up of 10 years. In their experience, the incidence of vanishing cancer declined tenfold, comparing prostatectomies performed before 1980 (2.1% incidence) to a more recent time interval from 1993 to 1995 (0.2% incidence). They have estimated the current incidence of vanishing cancer at 2 per 1,000 radical prostatectomies [4]. Recently, Trpkov et al. [28] found an incidence of no residual cancer on prostatectomy of 0.67% after ten-core positive biopsy. They concluded that in most cases, finding no residual cancer on prostatectomy after additional sectioning and evaluation may indicate minimal patient disease. Very recently Zynger et al. [32] reported that their frequency of finding no residual cancer in RP specimens has increased from 0% in 2002 to 4.2% in 2006. In Canada, Srigley [25] has estimated the incidence of no residual cancer after positive biopsy in his practice at less than 0.5%. In Germany, the incidence of pT0 in patients with prostate cancer without neoadjuvant treatment was analysed by Herkommer et al. [13]. Based on a database of 3,609 patients, no residual prostate cancer was found in 0.8% after RP. Most men in this pT0 series had previous TURP or open prostatectomy, which may have eliminated prostate cancer, whereas in two patients, cytology was used for primary diagnosis. Only in 0.3% of men with positive prostate needle biopsies was no residual tumour detected in the prostatectomy specimen [13]. The incidence of pT0 patients in a very recent French study was reported to be 0.5% [6]. No residual cancer may also result from preoperative endocrine therapy [11, 12, 15, 16, 19, 24, 26]. The incidence of pT0 after neoadjuvant endocrine therapy for prostate cancer is reported to be higher than in untreated patients [11]. Kollermann et al. [16] analysed a group of 174 men who underwent prolonged androgen deprivation therapy and observed a pT0 in 36 of 174 men (21%). Several questions are addressed to explain why cancer is not present in a small proportions of prostatectomies. Cancer is missed during the examination of the RP, all prostatectomy tissue is not sampled, and the cancer is overdiagnosed in the biopsy. Pathologists face additional challenges in eliminating the possibility of laboratory error resulting in specimen (blocks, slides) mislabelling or switching and excluding an information system error resulting in specimen mix-up [28]. The aim of this paper was to report the results of a search for residual cancer on RP after an initial stage pT0 evaluation in eight patients with positive biopsy. Materials and methods We reviewed our database of 1,328 consecutive patients whose biopsies and RP specimen were examined between March 1995 and June 2006 at the five Pathological Anatomy Services associated with the Polytechnic University-United Hospitals of the Marche Region, Ancona, Italy. Most of the biopsies and all the RPs of this series of 1,328 patients were reported by the same pathologist (RM). Seven hundred patients were untreated before the operation, whereas 628 had received neoadjuvant endocrine treatment for approximately 3 to 6 months. The biopsies and RPs were routinely processed as follows. The core biopsies from each site were submitted in separate containers. In brief, during biopsy processing, no more than two biopsy cores were embedded in paraffin blocks, and all blocks were sectioned at 3 μm and were stained with haematoxylin–eosin (HE). All cores were sectioned in two separate levels represented on separate slides, with each slide containing three additional sections [28]. All radical prostatectomy specimens (tissue was not harvested for research) were fixed en bloc in 10% buffered formalin for at least 24 h and were grossly completely sampled using a standard protocol [17, 18, 28]. In particular, each specimen was painted over the surface with India ink. The seminal vesicles were amputated at the prostate junction and were grossly completely sampled. The remainder of the specimen was serially cut with a domestic electric food slicer calibrated and set to deliver slices which are 3–4 mm in thickness, representing transverse planes parallel to the initial apical and basal sections. Each prostate slide was processed into complete whole mount section, and one HE slide was routinely sectioned per block. The apical and basal transverse 2- to 3-mm margins were sectioned perpendicularly to assess the prostatic apical and basal margins. Prostatectomies were grossly sectioned in 8.5 slices (mean; range, 6–16), and 15.3 slides (mean; range, 10 to 20) were generated per prostatectomy. Slides from pelvic lymph nodes were not included in the reported number of examined slides. We identified eight patients with positive 6- to 12-core biopsy and with no residual cancer (pathological stage pT0) in the initial routine histological examination of the RP and successively subjected to additional sectioning and evaluation. Search for residual cancer Since 1995, a special cancer searching protocol has been applied to those RPs in which an initial routine-based examination does not show residual cancer [18]. As mentioned earlier, this is basically done in those cases whose biopsies and RP specimen are both examined at the Ancona institution. The following successive steps were undertaken by two pathologists (RM and RMa). The procedure was usually stopped at the step where cancer is found. The diagnostic needle biopsies were reviewed to exclude the possibility of a false positive biopsy diagnosis and to assess the approximate location of the biopsy with tumour, such as apex, mid-zone and base, both left and right.The slides of the surgical specimens were reviewed for residual cancer that was initially overlooked or missed.If the prostate was not totally embedded, the remaining prostate tissue was processed in toto. If the prostate was completely sampled, then this step was skipped. This type of information was usually contained in the pathology form where the all the steps of the processing procedure were recorded. The information was further confirmed by searching the specimen’s container for residual pieces. As we routinely sample completely all prostatectomies, this step was skipped.Additional deeper sections (i.e. three to five sections) of the prostatectomy area (paraffin block) corresponding to the location of the core with cancer were re-cut. Further sections were also obtained from all the other paraffin blocks.Additional deeper sections (i.e. three to five sections) of the area corresponding to the location of the positive core as well as of all the remaining blocks were re-cut after block-flipping.Immunostains for p63 and alpha-methylacyl-CoA racemase (AMACR) were performed to evaluate suspicious foci (When these two were not yet available, we used 34betaE12 immunostaining).Immunostain for cytokeratin CAM 5.2, for p63 and for PSA (prostate specific antigen) was performed to identify the so-called “minimal residual cancer” especially in patients receiving neoadjuvant hormonal therapy [17].Review the description of the macroscopic appearance of external and cut surfaces of the surgical specimen as well as inspect the contour of the tissue sections on the slides for hint or clues that might indicate that part of the tissue was missing either due to the surgical procedure or for technical reasons.DNA specimen analysis was performed on formalin-fixed tissue to confirm the identity of the biopsies and prostatectomies whenever necessary. DNA specimen identity analysis Tested samples in an individual case included the biopsy core with cancer and a random block for the corresponding RP. The tissue was obtained as a direct section from formalin-fixed and paraffin-embedded blocks. DNA was extracted from paraffin-embedded tissue using the QIAmp DNA mini kit (Qiagen) according to manufacturer’s protocol (Promega, Madison, WI, USA). Fifteen microsatellites and amelogenin locus were co-amplified by the AmpFlSTR identifiler kit (Applied Biosystems, Foster City, CA), and the amplified fragments were electrophorized on an ABIPrism3130 genetic analyzer (Applied Biosystems). Fragment sizing and allele designation were established by GeneMapperID v3.2 software (Applied Biosystems), and genetic profiles from both biopsy and prostatectomy samples were compared. Results Residual cancer was not found in eight RPs after an initial routine examination. They represent 0.6% of the 1,328 consecutive patients. Three (0.2%) of them were from the group of untreated patients, whereas five (0.4%) were from those who had received neoadjuvant treatment. The latter figure represents 0.8% of the treated patients. Patients’ clinical data are summarised in Table 1. The mean age of the patients was 65 years (range, 58–71 years). Mean serum PSA pre-biopsy was 5.1 ng/ml (range, 1.25–9.0 ng/ml). Mean gland volume was 43.9 ml (range, 28.1–93.5 ml). Digital rectal examination was abnormal in 37% of patients, and 25% of patients had abnormal transrectal ultrasound. Table 1Patients’ clinical dataPatient no.Age (years)PSA Prebiopsy (ng/ml)Digital rectal examinationTRUSGland volume (cc)1689.0AbnormalNormal47.92715.4NormalAbnormal31.43646.1NormalNormal28.14671.25AbnormalNormal93.55605.9NormalNormal36.66663.0AbnormalNormal47.97583.9NormalAbnormal29.38666.5NormalNormal36.6Mean (range)65 (58–71)5.1 (1.25–9.0)43.9 (28.1–93.5)PSA Prostate-specific antigen; TRUS transrectal ultrasound Patients’ biopsy findings are shown in Table 2. In all patients, carcinoma was found in one core. Seven patients demonstrated biopsy Gleason score of 6 (3 + 3), whereas in one, it was 7 (3 + 4). Cancer occupied approximately 5% of the core length (Fig. 1) in 6 and 10% of the core in two. The positive biopsy location was variable, and there was no side predilection. Table 2Biopsy findingsPatient no.No. of positive coresGleason scoreCancer length (% of involvement)Positive core location11/123 + 3 = 65Right apex21/103 + 4 = 710Right apex31/63 + 3 = 65Left mid-zone41/63 + 3 = 65Right mid-zone51/63 + 3 = 65Right mid-zone61/123 + 3 = 610Left mid-zone71/103 + 3 = 65Right mid-zone81/123 + 3 = 65Left baseFig. 1Biopsy finding of a small groups of atypical acini (a) devoid of basal cells (b). Section immunostained for p63 (case no. 5). The diagnosis is acinar adenocarcinoma, Gleason score 3 + 3 = 6. (The prostatectomy findings are those seen in Fig. 2) Search for residual cancer There were no cases with a false positive biopsy diagnosis (step 1). Cancer was not overlooked or missed in any of the eight prostatectomies (step 2). Each prostate had been totally embedded (step 3). Cancer was found on deeper sections (steps 4 and 5) in five cases. Cancer was in the right and left apex, respectively, in two of them. Cancer was in the mid-zone in another two, one in the left and the other in the right. The fifth was in the left base. In particular, the cancer found in the right apex was discovered after block-flipping (i.e. step 5; Fig. 2). The location corresponded to site of the positive biopsy in four cases. Two out of five cases were from the untreated group and showed a Gleason score of 3 + 3 = 6. Three cases had the morphologic appearance of cancer with evident regressive changes due to endocrine therapy. The diameter of the tumour, measured on the slides, was always below 2.0 mm. In one of the three treated cases, an additional focus of cancer was seen at a distance from to that of the positive biopsy. Fig. 2Paraffin blocks, original sections and additional sections before and after block-flipping in case no. 1. a Is the right apex. b Is the left apex. c Includes the whole mount sections of the body of the prostate. d Is the right and left base. e Includes the seminal vesicles and deferens. A1 is the paraffin block. A2 is the original H-E-stained section. A3 includes the additional sections before block-flipping. A4 refers to the additional sections after block-flipping (Block-flipping was done only for a and b). The dotted area (see also the red arrow) on the A4 slides is that of the cancer. It corresponds to the lesion of the biopsy seen in Fig. 1. The same identification procedure applies to b. Concerning c and d the paraffin blocks, the original sections and the additional sections (block-flipping was not done) are shown. For e the paraffin blocks and the original sections are shown. (Other slides contain some annotations and abbreviations to indicate additional findings, slide orientation, and section order, etc.) The definitive diagnosis was established on steps 6 and 7 in an additional case (the patient was hormonally treated before RP) where cancer was not seen in the additional sections even after block-flipping. Immunohistochemistry for p63 and AMACR was applied to a small suspicious focus of crowded acini. There were a few scattered p63 positive (basal) cells, whereas AMACR was negative. The focus was considered to be benign (i.e. atrophy). Cancer was discovered after immunostaining for cytokeratin CAM 5.2, for p63 and PSA. It was represented by scattered isolated cells positively immunostained with the antibody against CAM 5.2 (Fig. 3) and with PSA and negative for p63 (Fig. 3). The diameter of the focus was 1.0 mm. The block selected for immunohistochemistry corresponded to an H&E-stained slide with hypercellular stroma. There was no exact correspondence with the site of the positive biopsy. Fig. 3Cancer is discovered after immunostaining for cytokeratin CAM 5.2 (case no. 6). It is represented by scattered isolated cells. The same cells are negative for the basal cell marker p63 and positive for PSA. Part of an atrophic duct is also present In the remaining two cases (one untreated and the other treated preoperatively), cancer was not found on steps 4 through 7. The review of the description of the macroscopic appearance and the inspection of the contour of the tissue sections on the slides revealed that part of the peripheral zone of the prostate was missing (Fig. 4). This corresponded to the location of the positive biopsy (step 8). DNA specimen analysis confirmed the identity of the biopsy and prostatectomy in both cases (step 9; Table 3). Incidentally, prostate tissue was documented clinically in one of the two patients (patient no. 7, hormonally treated before operation; the same patient whose prostate is shown in Fig. 4). In particular, a biopsy of the residual fragment showed normal prostate tissue and adenocarcinoma with features identical to those seen in the preoperative biopsy. Fig. 4Whole mount section (case no 7). Part of the peripheral zone, posteriorly, is missingTable 3Results of the search for residual cancerPatient no.Neoadjuvant treatmentCancer foundID test done1NoIn recutNo2NoIn recutNo3YesIn recutNo4YesIn recutNo5YesIn recut after block-flippingNo6YesAfter cytokeratin stainNo7YesNot in RPaYes, identical8NoNoYes, identicalaA post-operative biopsy of the residual prostate fragment in the patient showed normal prostate tissue and adenocarcinoma with features identical to those seen in the preoperative biopsy. Discussion Reported incidence of no residual cancer on RPs ranges from 0.07 to 4.2% (1–11, 20). It is higher after neoadjuvant hormonal treatment [16]. There are multiple reasons why cancer may not be found on RP after a positive biopsy. In some cases, the cancer may be minute and completely removed by the initial procedure, either needle biopsy or transurethral resection of prostate. Small cancers may be removed from the RP during the technical preparation of the specimen, such as leveling of the paraffin blocks. Small cancer foci can also be completely obscured if the patient has undergone antiandrogen therapy or the RP shows extensive inflammation or granulomatous inflammation. Other reasons include false-positive diagnosis on the initial biopsy, resulting in cancer overdiagnosis, or false-negative diagnosis rendered on the RP. Review of the material by a second pathologist or a specialist in urological pathology can often resolve the latter scenario. Lastly, errors may occur either before a specimen is submitted for pathological assessment or in the pathology laboratory. These errors include switching of patients’ requisitions, mislabelling or switching of specimen containers, mislabelling or switching slides or blocks and information system errors (e.g. incorrect case entry in the information system or mixed accession numbers) [28]. In our study, the incidence of RPs with no residual cancer after an initial routine examination of the 1,328 specimens was 0.6%. This figure includes both untreated and hormonally treated patients. The incidence was 0.2 and 0.4%, respectively, of the total number of RPs included in the study, or 0.4% (3 out 700 untreated patients) and 0.8% (5 out 628 treated patients) when the two groups were considered separately. The former is well in the range of values reported in the literature for untreated patients and very close to the figure published by Herkommer et al. [11, 13]. The latter value seen in our treated patients is much lower than that observed by Kollermann et al. [16]. Additional sectioning and evaluation of the cases can reduce the number of pT0 RPs after a positive biopsy. In particular, the current study showed that the final incidence was 0.15% and included only two RPs with missing parts, probably due to incomplete removal of the prostate. One of these two patients was hormonally treated preoperatively. Our findings on the role of immunohistochemistry to detect residual PCa cells are in agreement with previous studies. Gleave et al. [8] found that 50% of the cases that exhibited no residual cancer on routine pathologic assessment had remaining foci of cancer discovered by immunostaining. Without the aid of additional step sections and immunostaining for cytokeratin, these cases would have been reported as being stage pT0 [2]. DNA identity on formalin-fixed tissue from the paraffin blocks is a useful test to establish specimen identity and to exclude the possibility of laboratory error when no residual cancer is found on RP after a positive biopsy. In particular, DNA analysis is a useful test that eliminates the possibility of specimen mishandling or switching by establishing the identity of the tissue from the positive biopsy and the RP. It can be performed in the formalin-fixed tissue from the paraffin blocks. Different methods are used to investigate tissue specimen identity. These include immunolabeling of blood group antigens [22], sex chromosome targeting using fluorescence in situ hybridization [21] and microsatellite analysis. According to some authors, microsatellite analysis is the gold standard for investigating tissue identity [1, 10, 23, 28, 31]. In our study, the clinical and the biopsy data in patients with no initial residual cancer on radical prostatectomy after positive biopsy are similar to the findings from a recent study in patients with single-core positive biopsies and minimal cancer on biopsy [28, 29]. The majority of patients with no residual cancer on prostatectomy demonstrated minute cancer foci in one or two biopsy cores with Gleason score of 6, which, in many cases, may reflect minimal disease [28]. Rare small-volume cancers of higher grade may also be encountered [28]. Follow-up investigations have, in general, shown that no pT0 patient has clinical or biologic evidence of prostate cancer recurrence or progression [6, 14, 20, 27]. There are four aspects that we have not explored in our study. One is that the carcinoma could be lost in facing off of the paraffin blocks. We are fully aware of this potential problem. Our technicians are instructed so that they have to collect tissue sections and not waste material when the paraffin blocks are levelled off. The second is whether the time, effort and expense of the sampling described in this paper are warranted on a routine basis for all pT0 cases. We have not done any analysis in these respects due to the fact that the number of cases is very small and that time and expense do not represent an issue of concern in our institution. The third is what degree of sampling would be necessary to serially section through the entire prostate. Probably thousands of sections would be required, and we were prepared to cut as many sections as needed to find cancer. The fourth is whether there is an outcome difference when the initial pT0 carcinomas are detected after more thorough sampling vs pT0 cases without additional sampling. This was not addressed in our study because the basic aim was to avoid that a pT0 report is rendered to the clinician and to the patient, thus triggering a potential legal issue with all the problems related to it. There are few observations in the literature on pT0 cases and preoperative diagnosis of cancer made in TURP specimens. The real incidence of no residual cancer after cancer detected by TURP material is not known and is reported to be seen in 6 to 39% of cases [9], presumably due to tumour ablation during the initial resection. However, studies of this phenomenon are limited by variations in the number of tissue sections submitted for histological evaluation and by the small number of cases [3]. Conclusions and recommendations The current study showed that an extensive search for residual cancer reduces the number of pT0 RPs after a positive biopsy. To achieve this, it is recommended to have the needle biopsy reviewed, carefully look again at the radical prostatectomy, do deeper sections and then flip certain paraffin blocks. In addition, atypical foci should be stained for basal cell markers and often AMACR, especially in hormone-treated cases. If a block is missing part of the peripheral zone (capsular incision), this should be commented on. DNA analysis for tissue identity should be performed when the other steps have been taken without finding cancer.

Breast_Cancer_Res_Treat-3-1-2001222

Safety of aromatase inhibitors in the adjuvant setting

The third-generation aromatase inhibitors (AIs) letrozole, anastrozole, and exemestane are replacing tamoxifen as adjuvant therapy in most postmenopausal women with early breast cancer. Although AIs have demonstrated superior efficacy and better overall safety compared with tamoxifen in randomized controlled trials, they may not provide the cardioprotective effects of tamoxifen, and bone loss may be a concern with their long-term adjuvant use. Patients require regular bone mineral density monitoring, and prophylactic bisphosphonates are being evaluated to determine whether they may protect long-term bone health. AIs decrease the risks of thromboembolic and cerebrovascular events compared with tamoxifen, and the overall rate of cardiovascular events in patients treated with AIs is within the range seen in age-matched, non-breast-cancer populations. AIs are also associated with a lower incidence of endometrial cancer and fewer vaginal bleeding/discharge events than tamoxifen. Compared with tamoxifen, the incidence of hot flashes is lower with anastrozole and letrozole but may be higher with exemestane. Generally, adverse events with AIs are predictable and manageable, whereas tamoxifen may be associated with life-threatening events in a minority of patients. Overall, the benefits of AIs over tamoxifen are achieved without compromising overall quality of life. Introduction Tamoxifen became the standard adjuvant therapy for women with early breast cancer following the first demonstration of efficacy more than 20 years ago [1]. Administration of tamoxifen for 5 years has been shown to reduce breast cancer recurrence by 41% and mortality by 34% in women with hormone-responsive tumors [2]. Nevertheless, many limitations of tamoxifen have emerged with widespread use. In the landmark National Surgical Adjuvant Breast and Bowel Project B-14 trial, 66% of tamoxifen-treated patients experienced side effects compared with 58% of patients given placebo [3]. Severe, potentially life-threatening events such as thrombosis were more likely to occur in patients aged >60 years [3]. Long-term adverse effects associated with 5 years’ adjuvant tamoxifen include venous thromboembolic events, vaginal bleeding, vaginal discharge, ischemic cerebrovascular events, endometrial and uterine cancer, and hysterectomy [3, 4]. Experiencing side effects significantly increases the likelihood of patients discontinuing tamoxifen therapy (odds ratio 4.0; 95% confidence interval [CI] 1.1, 13.9 in women aged ≥ 55 years) [5]. Over time, resistance to tamoxifen may develop [6], and therapy beyond 5 years is not recommended because neither further disease-free survival nor survival benefit is gained [7]. The third-generation aromatase inhibitors (AIs) letrozole, anastrozole, and exemestane are rapidly replacing tamoxifen as initial adjuvant therapy [8, 9] or sequential adjuvant therapy after 2–5 years of tamoxifen [10–13]. By potently inhibiting the aromatase enzyme, which converts androgens to estrogen [14, 15], AIs achieve almost total suppression of total body aromatization and dramatic reductions in estrogen concentrations in postmenopausal women [16–18]. AIs are now recommended in international guidelines for the management of breast cancer [19–21]. In addition, guidance is being developed for the management of common co-morbidities such as osteoporosis in postmenopausal women with hormone-sensitive breast cancer receiving AIs [20, 22]. This review examines the safety of AIs and assesses their advantages and disadvantages compared with tamoxifen. It also considers the impact of treatment on co-morbidities commonly encountered in this population. Possible impact of treatment on common co-morbidities Adjuvant therapy should be individualized on the basis of clinical and biologic risk factors [21], including the presence of co-morbidities [23–26]. The most prevalent co-morbidities in the postmenopausal patient population are hypertension, arthritis, heart disease, diabetes, chronic obstructive pulmonary disease, eye problems, anemia, depression, fractures, hearing problems, osteoporosis, Parkinson’s disease, renal failure, and urinary tract problems [25]. Understanding the long-term effects of aromatase inhibition on bone and cardiovascular health are particularly important to consider because of the potential effects of altering estrogen concentrations. Bone disease Bone health typically may deteriorate as women age, particularly after reaching menopause [27, 28]. A decline in estrogen concentrations accelerates postmenopausal bone loss [29–31] while vitamin D deficiency also increases bone turnover and the risk of fracture [32, 33]. It is important to note that bone health is compromised in women with breast cancer compared with the general population [34]. In the Women’s Health Initiative Observational Study, breast cancer survivors had significantly lower total body bone mineral density (BMD) and total hip BMD [34] and a significantly higher risk of clinical fractures [35]. Of concern, osteoporosis was undiagnosed in more than three quarters of breast cancer survivors and the reference population [34]. Multiple factors contribute to the increased risk of osteoporosis and fractures in postmenopausal women with breast cancer [34]. Furthermore, tumor cells can have a direct effect on bone remodeling [36], and breast cancer therapy can lead to cancer treatment-induced bone loss (CTIBL) [37–39]. In a large cohort study, patients with early breast cancer who received anticancer therapy had a 30% higher risk for osteoporosis/osteopenia (odds ratio 1.29; 95% CI 1.13, 1.46) [38]. The study also showed that other factors such as poor health status, history of smoking, and alcohol abuse can contribute to CTIBL. The most serious consequence of CTIBL is an increased risk of fractures (Fig. 1) [35], which increase morbidity and healthcare costs [40]. The presence of bone metastases can contribute to CTIBL and lead to serious complications, including fractures, spinal compression, bone pain, and hypercalcemia of malignancy [41]. Fig. 1Age-standardized fracture incident rates by survivor status. Standardized rates were calculated using the age distribution of the entire Women’s Health Initiative Observational Study cohort. Excess numbers of fractures per 10,000 person-years are above each set of bars [35]. ©2005 American Medical Association. Reproduced with permission Aromatase inhibitors and bone disease In a recent study, the bone health of 1,354 patients with breast cancer receiving an AI (anastrozole, exemestane, or letrozole) was compared with 11,014 controls [39]. Treatment with an AI increased the risk of bone loss (relative risk 1.3; 95% CI 1.1, 1.6; P = 0.01) and bone fracture (relative risk 1.4; 95% CI 1.2, 1.6; P = 0.001). The risks remained significantly higher for AI therapy after adjustment for age and co-morbidities [39]. An increase in the incidence of arthralgia is noted with all three AIs, when compared with tamoxifen. Anastrozole Howell and colleagues reported fracture rates after a median follow-up of 68 months in the Arimidex, Tamoxifen, Alone or in Combination (ATAC) trial [42]. Fractures were reported in 577 (9.3%) of the 6,186 patients and were more common with anastrozole than with tamoxifen (11 vs. 8%, respectively; P < 0.0001). The incidence of hip fractures was 1% in both groups. The rate of fractures was low at approximately 2% per year and decreased to baseline levels after completion of 5 years of treatment. The effects of anastrozole and tamoxifen on BMD were assessed in a sub-analysis of 167 patients from the ATAC trial [43]. Anastrozole-treated patients had significant decreases in lumbar spine BMD (−8.1%; 95% CI −10.1, −6.1; P < 0.0001) and total hip BMD (−7.4%; 95% CI −9.6, −5.3; P < 0.0001) relative to tamoxifen-treated patients, in whom small increases were observed. Bone loss was greatest in the first 2 years of anastrozole treatment, as reported previously [44], but the rate of loss appeared to slow down from years 2 to 5. In the updated analysis after a median follow-up of 68 months, osteopenia or osteoporosis was reported in 11% of patients receiving anastrozole compared with 7% receiving tamoxifen (P < 0.0001) [42, 45]. Another sub-analysis of the ATAC trial showed that the majority of joint symptoms occur within 24 months of initiating treatment [46]. After 68 months’ median follow-up, joint symptoms were reported in 35.6 and 29.4% of patients in the anastrozole and tamoxifen arms, respectively. Most symptoms were mild in intensity, and 46% were reported as an exacerbation of a pre-existing condition. The incidence of serious joint symptoms was similar for anastrozole and tamoxifen (10.6 vs. 10.4%, respectively) and only 2.1 and 0.9%, respectively, discontinued treatment because of joint symptoms. After a median follow-up of 68 months, muscle cramps were less common with anastrozole than tamoxifen (4 vs. 8%, respectively; P < 0.0001), whereas carpal-tunnel syndrome was more common with anastrozole (3 vs. 1%, respectively; P < 0.0001) [42]. These updated results from the ATAC trial confirm that AIs are a well-tolerated initial treatment option in terms of bone health [43, 45, 46]. Although anastrozole is associated with BMD loss, no patient with normal bone at baseline became osteoporotic after 5 years of treatment, and the rate of bone loss in the lumbar spine region slowed down in years 2–5. The ARNO/ABCSG8 trials investigated the efficacy and safety of switching to anastrozole after 2 years of tamoxifen [12]. Although there were significantly more fractures in patients switching to anastrozole (2.1%) than in those continuing on tamoxifen (1.0%) [12], the rate was lower than that seen at a similar point in the ATAC trial [12]. In the Italian Tamoxifen Anastrozole (ITA) trial, switching to anastrozole after 2–3 years of tamoxifen was not associated with an increase in fracture rate, although differences may emerge with longer follow-up [13]. Letrozole In the Breast International Group (BIG) 1–98 trial of initial adjuvant therapy, there was a slight yet significant difference in the incidence of fractures (5.7% with letrozole vs. 4.0% with tamoxifen; P < 0.001) [8]. The MA.17 trial of extended adjuvant therapy showed that when compared with placebo, letrozole had no significant impact on fractures [10]. There was a small but significant difference in patient-reported diagnoses of new-onset osteoporosis (8% letrozole vs. 6% placebo, P = 0.003), and arthralgia and myalgia were significantly more common with letrozole than placebo [10]. A companion study to MA.17 demonstrated a significant decrease in lumbar spine BMD (−5.35 vs. −0.70%; P = 0.008) and total hip BMD (−3.6 vs. −0.71%; P = 0.044) over 2 years in patients treated with letrozole compared with placebo, although no patient went below the threshold for osteoporosis in total hip BMD [47]. Data from this companion study suggest that women with a BMD score of −1.0 or greater when starting letrozole after tamoxifen are less vulnerable to enhanced bone resorption and may not require prophylactic bisphosphonate therapy. Exemestane In a model of ovariectomized rats, the steroidal AI exemestane was shown to prevent bone loss, presumably via its androgenic properties (both exemestane and its metabolite 17-hydro-exemestane demonstrate affinity for the androgen receptor) [48]. However, a randomized study to compare the effects of progestins and AIs on bone remodeling markers in patients with metastatic breast cancer found that exemestane increased osteoclast activity [49]. In the adjuvant treatment setting, a randomized trial involving 147 patients with early breast cancer demonstrated a non-significant effect of exemestane compared with placebo on the annual rate of BMD loss in the lumbar spine (2.17 vs. 1.84%; P = 0.568) and a small but significant effect in the femoral neck (2.72 vs. 1.48%; P = 0.024) [50]. Of note was the finding that BMD may rapidly improve following AI discontinuation: this trial showed that bone resorption markers returned to or below baseline values, and bone formation markers remained moderately increased within 6 months of stopping exemestane [51]. In the Intergroup Exemestane Study (IES) of exemestane following 2–3 years of tamoxifen, fractures were reported more frequently with exemestane than with tamoxifen after a median follow-up of 30.6 months, although this difference was not statistically significant (3.1 vs. 2.3%; P = 0.08) [52]. However, the difference in incidence of fractures was statistically significant (7.0% with exemestane vs. 4.9% with tamoxifen; P = 0.003) after a median follow-up of 55.7 months [11]. The incidence of osteoporosis was also significantly higher with exemestane than with tamoxifen (9.2 vs. 7.2%, respectively; P = 0.01). Recent results from a 1-year sub-study revealed that patients on exemestane experienced a significant decrease in hip BMD, while patients on tamoxifen did not [53]. These results were confirmed by another recent study, which evaluated the effects of exemestane on bone turnover markers and BMD in 70 postmenopausal women (62.0 ± 8.9 years) with early breast cancer who were switched to exemestane after 2–3 years on tamoxifen [54]. Patients in the exemestane group had a significant decrease in BMD and early parathyroid hormone (at month 6) and an increase in bone alkaline phosphatase (B-ALP) and the carboxy-terminal telopeptide of type I collagen after 24 months. These studies suggest that switching postmenopausal women from tamoxifen to exemestane causes a marked increase in bone turnover markers with a consequent reduction in BMD. Arthralgia was also significantly more common with exemestane than with tamoxifen (5.4 vs. 3.6%, P = 0.01) in the IES [52]. A study by Lønning et al. discovered a high prevalence of vitamin D deficiency in postmenopausal women treated with exemestane (52 of 59 patients) or placebo (56 of 62 patients), and this could be the most important factor causing bone loss in both groups [55]. Vitamin D substitution is therefore recommended for postmenopausal women, particularly those with breast cancer receiving an AI. The incidence of carpal-tunnel syndrome in the IES was higher in the exemestane arm (2.8%) than in the tamoxifen arm (0.4%; P < 0.001) [11]. Comparative studies of aromatase inhibitors A randomized trial (Letrozole, Exemestane, and Anastrozole Pharmacodynamics [LEAP]) of healthy volunteers demonstrated that letrozole, exemestane, and anastrozole have similar effects on bone biochemical measurements and all result in increases in bone turnover [56]. There were no statistically significant differences between the AIs in changes from baseline to 24 weeks for B-ALP, serum C-telopeptide crosslinks, and propeptide of type I procollagen. The only difference in the bone remodeling markers was a greater decrease in parathyroid hormone with exemestane than with anastrozole (P = 0.04). Thus, all AIs seem to have similar effects on bone health. The ATAC bone sub-study results are reassuring for the entire AI class, and women with breast cancer who have normal BMD measurements at the onset of AI treatment may be able to undergo 5 years of therapy without the risk of developing osteoporosis. Patients at risk of clinically relevant BMD loss during treatment should be identified and managed according to evolving clinical guidelines [20, 57]. Bisphosphonates In the American Society of Clinical Oncology (ASCO) guidelines postmenopausal patients with breast cancer who receive AIs are identified as being at high risk for osteoporosis, and it is recommended that they have baseline BMD evaluation and regular monitoring to guide subsequent therapeutic interventions such as bisphosphonates [20, 58]. Preliminary results have been reported from a small number of clinical trials of bisphosphonates in women receiving adjuvant AI therapy. In one trial, premenopausal breast cancer patients receiving goserelin plus anastrozole or goserelin plus tamoxifen were randomly assigned to the bisphosphonate zoledronic acid (ZA) (4 mg IV every 6 months) or placebo. After 36 months, it was shown that ZA given every 6 months helped prevent bone loss in these premenopausal patients in both the lumbar spine and hip regardless of endocrine therapy [59]. Two randomized trials have shown that bisphosphonates may be beneficial in postmenopausal patients at a higher risk of osteoporosis [60, 61]. In the Zometa-Femara Adjuvant Synergy Trial (Z-FAST) (North American) trial, 602 postmenopausal women with hormone-responsive breast cancer starting adjuvant therapy with letrozole were randomized to receive upfront ZA (4 mg IV infusion every 6 months) or delayed ZA when indicated (either post-baseline T-score decreases < −2 SD or occurrence of fracture) [60, 62]. Preliminary results after 12 months’ follow-up indicate that initial treatment with ZA may be used to prevent CTIBL, and results at 24 months confirm these initial findings [62, 63] although the rate of clinical fractures was not changed. In addition, the small proportion of patients (8%) requiring ZA in the first year highlights the short-term bone tolerability of letrozole [62]. Results from the similarly designed ZO-FAST (European; N = 1,065) trial also support the use of ZA to potentially manage CTIBL in postmenopausal women with early breast cancer receiving adjuvant letrozole [61]. Lipid metabolism: A cohort study demonstrated that total and low-density lipoprotein (LDL) cholesterol concentrations are positively correlated with years since diagnosis of breast cancer [64]. In addition, during menopause, women experience adverse changes in cardiovascular risk factors, including declines in concentrations of high-density lipoprotein (HDL) cholesterol and increases in concentrations of total cholesterol, LDL cholesterol, HDL3 cholesterol, and triglycerides [65, 66]. These changes are independent of age and body mass index. Assessing the impact of AIs on lipid profiles is difficult in trials where tamoxifen is the comparator. The selective estrogen-receptor modulators (SERMs) such as tamoxifen are known to have lipid-lowering properties [67, 68]. What is clear is that the studies comparing AIs with tamoxifen indicate only that the AIs lack the lipid-lowering effects of tamoxifen. Aromatase inhibitors and lipid metabolism Anastrozole In the ATAC trial, the incidence of hypercholesterolemia was higher in patients receiving anastrozole than tamoxifen (9 vs. 3%, respectively; P < 0.0001) [42]. In the ITA trial, lipid metabolism disorders were reported in 9.3% of patients treated with anastrozole and 4.0% receiving tamoxifen (P = 0.04) [13]. A recent multicenter study in patients with estrogen-receptor positive breast cancer investigated the effects of adjuvant anastrozole and toremifene, a SERM, on serum lipids [68]. Results showed that only toremifene had a beneficial effect on lipid profile, indicated by a decrease in total cholesterol, LDL cholesterol, triglycerides, and apolipoprotein B, and an increase in HDL cholesterol and apolipoprotein A1. Changes in total cholesterol, HDL, LDL, and apolipoproteins were significantly different between toremifene and anastrozole at 6 and 12 months (P < 0.05). Letrozole In the BIG 1–98 trial, according to the protocol, cholesterol concentrations (fasting or non-fasting) were collected systematically in the case-report forms every 6 months and even patients with only a single measurement above the upper limit of normal were defined as hypercholesterolemic [8]. Hypercholesterolemia was reported in 5.4% of the letrozole arm compared with 1.2% of the tamoxifen arm in patients with baseline values within normal limits, who then had an increase of 1.5 times the upper limit of normal [69]. Hypercholesterolemia was typically a single event and in the majority of these patients (80%) occurred at only grade 1 intensity (meaning a slight numerical increase above normal, not requiring medications). Moreover, the majority of cases were single measurements collected in non-fasting patients. Furthermore, when looking at total serum cholesterol levels, there was a 12% median decrease from baseline in total cholesterol in the tamoxifen arm after 6 months, consistent with previous reports demonstrating the lipid-lowering effect of tamoxifen [67], while in the letrozole group total cholesterol values remained stable [8]. Hypercholesterolemia was not predefined as an adverse event in the ATAC trial, and lipid concentrations were not routinely assessed [42]. Exemestane Hypercholesterolemia was not reported in the IES trial of sequential exemestane after tamoxifen [11, 52]. Another study examined the longitudinal changes in body composition and lipid profiles in 55 postmenopausal women with early breast cancer switched to exemestane after at least 2 years of tamoxifen treatment [70]. Fat mass significantly decreased (P < 0.01) while the fat-free mass to fat mass ratio significantly increased (P < 0.05) by month 12 in the exemestane but not in the tamoxifen group. In addition, triglycerides and HDL cholesterol significantly decreased (P < 0.01 and P < 0.05, respectively) in the exemestane group, while LDL cholesterol significantly increased (P < 0.01) at the end of the 1-year study period. Aromatase inhibitors versus placebo When compared with placebo (the most accurate way to assess the true impact of AIs on serum lipids), the final analysis of the MA.17 trial demonstrated the incidence of hypercholesterolemia was 16% in the letrozole and the placebo arms [10]. Results from an MA.17 lipid sub-study showed that in 347 postmenopausal women with primary breast cancer treated for up to 36 months, letrozole (n = 183) does not significantly alter lipid profile (samples drawn under fasting conditions) compared with placebo (n = 164) [71]. In a placebo-controlled study involving 147 postmenopausal women with early breast cancer, exemestane had no major effect on lipid profile except for a modest but significant decrease from baseline in HDL cholesterol (P < 0.001) and apolipoprotein A1 (P = 0.004) [50]. On the basis of these results, it is clear that when compared with placebo, AIs do not have a detrimental effect on lipid profile. However, it should be noted that there have been no placebo-controlled trials of adjuvant anastrozole in women with breast cancer. Comparative studies of aromatase inhibitors The LEAP trial directly compared safety parameters between the steroidal AI exemestane and the non-steroidal AIs anastrozole and letrozole in 90 healthy postmenopausal women (Table 1) [72]. Initial results from the trial showed that there were no significant differences between anastrozole and letrozole in effects on LDL:HDL ratios, triglyceride concentrations, and non-HDL concentrations. Exemestane was associated with an increase in LDL:HDL ratio (+17) (P = 0.047) compared with anastrozole. There was no median change from baseline in total serum cholesterol for letrozole, a slight increase for anastrozole (+0.4), and a non-significant decrease for exemestane (−3.9) (P = 0.164 vs. anastrozole) [72]. Table 1Comparative effects of third-generation aromatase inhibitors on lipids [72]Percentage change from baselineAnastrozole (n = 29)Letrozole (n = 29)P value vs. anastrozoleExemestane (n = 32)P value vs. anastrozoleTotal cholesterol Week 12−2.3−3.80.617−5.50.262 Week 24+0.4−0.00.900−3.90.164 Triglycerides Week 12−2.9+9.60.037−7.70.417 Week 24+0.3+5.40.550+2.10.827Ratio of LDL-C:HDL-C Week 12−0.0−3.10.486+8.80.048 Week 24+4.6+3.40.847+17.00.047 Non-HDL-C Week 12−2.7−4.20.667−3.50.820 Week 24+1.3+1.20.975−0.60.630Ratio of apo B:apo A1 Week 12−1.0−3.30.452+4.40.069 Week 24+0.0−0.80.842+9.00.023LDL-C low-density lipoprotein cholesterol, HDL-C high-density lipoprotein, apo B apolipoprotein B, apo A1 apolipoprotein A1 Cardiovascular disease Cardiovascular risk increases substantially and progressively in women aged ≥65 years [73–77]. Isolated systolic hypertension, associated with arterial stiffening, is predominant in middle- and older-aged hypertensives [75] and predisposes individuals to coronary heart disease, heart failure, stroke, vascular dementia, and chronic kidney disease [73]. The risk of cardiac disease is also influenced by ethnicity, smoking, obesity, physical inactivity, alcohol abuse, and the presence of co-morbid diseases such as diabetes. In patients with breast cancer the presence of co-morbidities, including cardiovascular disease and diabetes, is associated with a poorer prognosis than when co-morbid disease is absent [78] and may explain disparities in outcome between different ethnic groups [79]. There is also evidence that breast cancer is associated with a higher prevalence of hypertension compared with other tumor types [80] and a significantly increased risk of stroke compared with the general population (relative risk 1.12; 95% CI 1.07, 1.17) [81]. Many breast cancer therapies increase the risk of cardiovascular events [82–88]; tamoxifen, however, may have some cardio-protective effects [89, 90]. Tamoxifen and cardiovascular disease Several studies have demonstrated the potential cardioprotective properties of tamoxifen, including a reduction in hospital admissions due to cardiac disease [89–91] and decreased mortality from cardiac disease [92]. In a meta-analysis, tamoxifen was associated with a significantly decreased incidence of myocardial infarction (relative risk 0.90) and death from myocardial infarction (relative risk 0.62) [93]. This finding is consistent with results from an earlier cohort study [94] and the Early Breast Cancer Trialists’ Collaborative Group (EBCTCG) meta-analysis, which demonstrated decreases in the risk of cardiac death and overall mortality from vascular disease in patients receiving tamoxifen compared with those receiving placebo [2]. Aromatase inhibitors and cardiovascular disease Assessing the impact of different AIs on cardiovascular disease in postmenopausal women with breast cancer is difficult and inter-trial comparisons are confounded by differences in data collection and end points; for example, in the BIG 1–98 trial all potential adverse events were predefined in the case-report forms whereas the ATAC trial used non-specific case-report forms to report adverse events [8, 95]. Furthermore, comparisons with tamoxifen are complicated by its cardioprotective properties. Placebo-controlled trials thus provide the best source of data to delineate the effects of AIs in a patient population with an inherently elevated risk of cardiac events. Anastrozole The ATAC trial provided data on the cardiovascular effects of anastrozole as initial adjuvant therapy compared with tamoxifen. The incidence of ischemic cardiovascular disease was higher (but not significantly) with anastrozole than placebo (127/3092, 4.1% vs. 104/3094, 3.4%; P = 0.1). The incidence of angina was also higher with anastrozole (71/3092, 2.3% vs. 51/3094, 1.6%; P = 0.07), while myocardial infarction occurred with similar frequency (37/3092, 1.2% vs. 34/3094, 1.1%; P = 0.7 [42]. Hypertension was statistically significantly more common with anastrozole than with tamoxifen (13 vs. 11%, respectively; P = 0.04) [42]. In the ARNO95 trial vascular events, including hot flashes, ischemic cardiovascular events, deep vein thrombosis, and ischemic cerebrovascular events, occurred in 9.2% of the anastrozole arm compared with 8.8% of the tamoxifen arm [96]. Letrozole The BIG 1–98 trial demonstrated a similar incidence of cardiac events in the letrozole and tamoxifen groups (4.1 vs. 3.8%, respectively; not significant). However, more women in the letrozole group had grade 3, 4, or 5 cardiac events (2.1 vs. 1.1%, respectively; P < 0.001), but these events remain rare [8]. Of note, a recent update of the monotherapy arms of BIG 1–98 after a longer median follow-up of 51 months showed that the overall incidence of cardiac events was comparable in the two groups (134 events [5.5%] in the letrozole group vs. 122 [5.0%] in the tamoxifen arm), thus confirming the safe cardiac profile of letrozole reported at 26 months [97]. Exemestane In the IES, there was no significant difference between exemestane and tamoxifen in the incidence of combined cardiovascular disease/thromboembolic events (22.1 vs. 20.9%, respectively; P = 0.34) after a median follow-up of 55.7 months [11]. The incidence of myocardial infarction was higher with exemestane than with tamoxifen, although the difference between treatment groups was not significant (1.3 vs. 0.8%, respectively; P = 0.08) [11]. Overall, the rate of cardiovascular events in patients treated with AIs is well within the range seen in age-matched, non-breast-cancer populations; for example, for women 57–65 years of age, the rates of fatal myocardial infarction and other fatal coronary artery disease are 1.1 and 0.81 per 1,000 patient-years, respectively [98]. Similar rates were recorded in the UK General Practice Research Database and Swedish MI register [99]. Currently, there is insufficient information to fully determine the effect of AIs on cardiovascular disease, especially coronary heart disease. Aromatase inhibitors versus placebo Cardiovascular events occurred with similar frequency in the letrozole and placebo arms in the MA.17 trial (5.8 vs. 5.6%, respectively; P = 0.76) [10]. Similar incidences were reported in the letrozole and placebo arms for stroke/transient ischemic attack (0.7 vs. 0.6%, respectively), myocardial infarction (0.3 vs. 0.4%, respectively), new or worsening angina (1.2 vs. 0.9%), angina requiring coronary artery bypass graft (0.2 vs. 0.5%), and thromboembolic events (0.4 vs. 0.2%, respectively) [10]. These results clearly indicate that when compared with placebo, AIs do not have a detrimental effect on cardiovascular safety. Gynecologic health The onset of menopause is characterized by numerous adverse events associated with a decline in estrogen concentrations [100–102]. Early symptoms include abnormal vaginal bleeding, hot flashes, and mood changes, while vaginal dryness and irritation, osteoporosis, and heart disease are late symptoms [29, 103, 104]. Vasomotor symptoms, particularly hot flashes, are common during transition to menopause [105–109] and may lead to disturbed sleep, depressive symptoms, and significant reductions in quality of life [110–115]. Cigarette smoking may be associated with increased risk of hot flashes in menopausal women [116]. Sexual dysfunction is also prevalent in menopausal women and is associated with vaginal atrophy, vaginal/genital dryness, dyspareunia (pain during sexual intercourse), vaginitis, cystitis, and urinary tract infections [117]. Aromatase inhibitors and gynecologic health Anastrozole In the ATAC trial, the incidence of hot flashes was significantly lower with anastrozole than with tamoxifen (36 vs. 41%; P < 0.0001) [9]. In the latest analysis, anastrozole was associated with a significantly lower incidence of gynecologic events (endometrial hyperplasia, endometrial neoplasia, cervical neoplasm, and enlarged uterine fibroids: 3 vs. 10% with tamoxifen; P < 0.0001) [42]. A quality-of-life (QOL) analysis confirmed that vaginal discharge, vaginal itching/irritation, and vaginal bleeding were less common with anastrozole but found that vaginal dryness, pain during intercourse, and loss of interest in sex were more common [118]. After 2 years of treatment there was a non-significant trend towards a lower incidence of endometrial abnormalities with anastrozole than tamoxifen (odds ratio 0.44; 95% CI 0.146, 1.314; P = 0.14) [119]. The latest update of the ATAC trial revealed reduced libido in significantly more patients receiving anastrozole (1%) than tamoxifen (<1%; P = 0.0001) [42]. Patients receiving anastrozole also experienced a significantly higher incidence of dyspareunia than those receiving tamoxifen (1 vs. < 1%, respectively; P = 0.002), whereas urinary incontinence and urinary tract infection were significantly less common among patients receiving anastrozole (urinary incontinence: 2 vs. 4%, respectively, P < 0.0001; urinary tract infection: 8 vs. 10%, respectively, P = 0.002). In a randomized study of postmenopausal women in whom abnormal vaginal bleeding and/or asymptomatic endometrial thickening occurred during treatment with tamoxifen, switching to anastrozole was associated with a significant reduction in mean endometrial thickness compared with continuation of tamoxifen (P < 0.0001) [120]. Significantly fewer anastrozole patients required a repeat hysteroscopy and dilation and curettage compared with those taking tamoxifen (4.8 vs. 33.0%, respectively; P < 0.0001). Letrozole In the BIG 1–98 trial [8], endometrial biopsies were significantly less common in patients receiving letrozole than tamoxifen (2.3 vs. 9.1%, respectively; P < 0.001), and there was a trend towards fewer invasive endometrial cancers (0.1 vs. 0.3%, respectively; not significant). There was a significantly lower incidence of vaginal bleeding with letrozole than with tamoxifen (3.3 vs. 6.6%, respectively; P < 0.001), and the incidence of hot flashes was also significantly lower (33.5 vs. 38.0%, respectively; P < 0.001). In another study in patients intolerant of tamoxifen, switching to letrozole for 6 weeks was associated with a 53.7% decrease in hot flashes (hot-flash score 97.0–52.1; P = 0.001) [121]. In the MA.17 trial, letrozole was associated with less vaginal bleeding than placebo (6 vs. 8%, respectively; P = 0.005) but a greater incidence of hot flashes (58 vs. 54%, respectively; P = 0.003) [10]. There was no significant difference in the incidence of vaginal dryness between letrozole and placebo. Exemestane In the IES, there were no significant differences between the exemestane and tamoxifen treatment arms in the incidence of endometrial cancer (0.4 vs. 0.7%, respectively; P = 0.17) [11], or the incidence of hot flashes (42 vs. 40%, respectively; P = 0.28) [52]. Overall, gynecologic symptoms were lower with exemestane than with tamoxifen (6 vs. 9%; P < 0.001) [52]; however, vaginal dryness was significantly more common among women taking exemestane than those taking tamoxifen, while vaginal discharge was significantly more common with tamoxifen [122]. Vaginal bleeding was significantly more common in the tamoxifen arm (7.1%) than in the exemestane group (4.8%; P = 0.001) [11]. Other adverse events Secondary cancer The association between tamoxifen and endometrial and uterine cancers is well-established [4] and is not observed with AIs. However, a safety analysis of the ATAC trial [42] showed a surprisingly higher incidence of head and neck cancer with anastrozole compared with tamoxifen (10/3092 vs. 3/3094, respectively). Similarly, there was an excess of lung cancer (25/3092 vs. 16/3094) and lung cancer deaths with anastrozole; however, further analyses are required to confirm these findings. Of note, a higher incidence of secondary cancer was not noted in the IES (72 events exemestane vs. 107 tamoxifen) or in the BIG 1–98 trial (69 letrozole vs. 82 tamoxifen) [8, 11]. A meta-analysis showed that tamoxifen is associated with a modest but statistically significant increase in the risk of developing gastrointestinal cancer (relative risk 1.31; 95% CI 1.01, 1.69), particularly for postmenopausal women (relative risk 1.77) [93]. Gastrointestinal health Diarrhea was significantly more common among patients receiving the steroidal AI exemestane than in those taking tamoxifen (4.2 vs. 2.2%, respectively) [123] but is not a typical side effect of the non-steroidal AIs letrozole and anastrozole. However, an updated safety analysis of the ATAC trial showed that anastrozole was associated with an increased incidence of diarrhea compared with tamoxifen (9 vs. 7%; P = 0.02) [42]. Neurologic effects and visual disturbance It has been suggested that endocrine therapy may affect cognitive function in patients with breast cancer [124]. In a study comparing patients from the ATAC trial with healthy controls, anastrozole was associated with significant impairments in a processing speed task and on a measure of immediate verbal memory [125]. Another study conducted in healthy, estrogen-treated postmenopausal women treated with testosterone did not reveal any effects of aromatase inhibition on cognition [126]. The impact of adjuvant AI therapy on cognition and other neurologic processes is clearly an important issue that will require further studies in the future. Neurologic effects reported with exemestane, including dizziness and vertigo [127] and significantly more visual disturbances compared with tamoxifen [52], are not characteristic of non-steroidal AIs. Dry mouth The latest analysis of the ATAC trial demonstrated a significantly greater incidence of dry mouth in patients receiving anastrozole (4%) compared with tamoxifen (2%; P = 0.003) [42]. Cosmetic effects Weight gain is common after breast cancer therapy and increases the risk of recurrence, cardiovascular disease, and diabetes [64]. A study of Japanese patients showed that more women reported weight gain in the anastrozole group than in the tamoxifen group (35.8 vs. 12.5%, respectively; P ≤ 0.0036) [128], but no difference was seen among patients from the ATAC trial included in a QOL sub-analysis [118]. The androgen structure of exemestane may lead to androgenic side effects. Hypertrichosis, hair loss, hoarseness, and acne were reported in about 10% of patients treated with daily exemestane doses of 200 mg or more in dose-finding studies [129, 130], but have not emerged as a significant issue in phase II or phase III trials with this agent. Anastrozole treatment was associated with a lower incidence of nail disorders (2 vs. 3%; P = 0.002) and fungal infection (1 vs. 1%; p = 0.01) compared with tamoxifen [42]. Quality of life and patient preference Anastrozole The QOL of patients treated in the ATAC trial was studied during a 5-year follow-up period [118, 131]. Anastrozole and tamoxifen had similar overall effects on QOL (Functional Assessment of Cancer Therapy-Breast [FACT-B] trial outcome index plus endocrine sub-scale) in the first 2 years of treatment [118], and an initial worsening of endocrine symptoms gradually improved over time [131]. The authors concluded that the benefits of anastrozole are achieved without detrimental effects on QOL. However, another study conducted in Japanese patients demonstrated that FACT-G, FACT-B, and FACT-ES scores were significantly better with tamoxifen than with anastrozole (P = 0.012, P = 0.010, and P = 0.015, respectively) [132]. Letrozole The MA.17 and BIG 1–98 trials have demonstrated that adjuvant letrozole is well-tolerated compared with placebo [10] and better tolerated than tamoxifen [8]. In another study of postmenopausal women who were experiencing distressing side effects while taking adjuvant tamoxifen and were switched to letrozole, after 6 weeks 66% of patients preferred to remain on letrozole, 24% preferred to go back to tamoxifen, and 10% stopped all therapy [121]. In the placebo-controlled MA.17 trial, letrozole significantly improved outcomes and did not impair overall QOL [133] (Fig. 2). Minor differences seen in some domains (physical functioning, bodily pain, vitality, vasomotor, and sexual) were consistent with a minority of patients experiencing changes in QOL compatible with a reduction in estrogen synthesis. A sub-analysis of US subjects in MA.17 demonstrated no significant differences between letrozole and placebo in overall QOL summary scores (mental and physical) and five of eight sub-domains of SF-36 [134]. There were no differences in SF-36 mental and physical QOL scores and MENQOL (menopause symptom scale) psychosocial and physical domains [134]. Fig. 2Mean change score in Short Form 36-item Health Survey. A positive score indicates a favorable change in quality of life. (A) Physical component summary; P = not significant for all time points. (B) Mental component summary; P = not significant for all time points. [133]. ©2005 American Society of Clinical Oncology. Reproduced with permission Exemestane Results from the IES QOL sub-protocol indicate that switching to exemestane from tamoxifen improves outcome without a significant detrimental impact upon QOL [135]. At entry, there was a high prevalence of severe endocrine symptoms (vasomotor complaints and sexual problems), and these persisted with exemestane and tamoxifen during the study. No significant differences between groups were seen for any endocrine symptoms apart from vaginal discharge, which was more pronounced with tamoxifen (P < 0.001). Conclusions Clinical trials show that the third-generation AIs lack the serious risks of thromboembolism and endometrial cancers associated with tamoxifen and are generally well tolerated, with the majority of adverse events occurring at mild to moderate intensity [8–11]. AIs are associated with a mild to modest increased risk of osteoporosis compared with tamoxifen, and it is therefore essential that patients have regular BMD assessments and be monitored proactively to minimize the risk of clinical fractures [20, 57]. The increased risk of fractures with an AI compared with tamoxifen needs to be balanced against the increased risk of endometrial and cerebrovascular/thromboembolic morbidity with tamoxifen [136]. Of note, the updated ATAC analysis shows that the majority of excess adverse events associated with tamoxifen occurred during the first 2.5 years of treatment; there were 142 (8%) fewer predefined adverse events in the anastrozole arm [137]. Thus, it appears that many excess gynecologic, thromboembolic, and cerebrovascular adverse effects occurring in tamoxifen-treated patients could be avoided if patients were treated initially with an AI [136]. Although AIs do not have the cholesterol-lowering and potential cardioprotective properties of tamoxifen, they do not significantly worsen total cholesterol concentrations and do not appear to increase cardiovascular risk when compared with placebo. Nevertheless, it is prudent to recommend that all patients at risk of cardiovascular effects are properly monitored and managed, and all breast cancer patients should be routinely monitored for cardiovascular disease. It is difficult to draw meaningful conclusions from comparisons of randomized trials of tamoxifen versus anastrozole, letrozole, or exemestane because of differences in assessing and reporting risk of cardiovascular disease [8, 52, 95, 138]. Current information is insufficient to determine the effects of AIs on cardiovascular disease and coronary heart disease risk [20]. Similarly, further follow-up is required to determine the late consequences of AI therapy [20]. Despite these provisos, ASCO now recommends that optimal adjuvant hormonal therapy for a postmenopausal woman with receptor-positive breast cancer includes an AI as initial therapy or after treatment with tamoxifen. Results from several ongoing trials, including the Femara versus Anastrozole Clinical Evaluation, MA.27, the National Surgical Adjuvant Breast and Bowel Project, LATER, and MILER, should provide more information on the long-term tolerance and the optimal duration of adjuvant AI therapy and help determine which strategy has the best ratio of efficacy to tolerance. In conclusion, the efficacy benefits of AIs outweigh the risks when AIs are used as adjuvant therapy in postmenopausal women with early breast cancer. Safety, QOL, and patient preference must all be considered in the determination of the optimal strategy for long-term endocrine therapy, bearing in mind that patients may require treatment for 10 years or more. Every patient is unique, and endocrine therapy must be individualized according to clinical, biologic, and patient factors such as lifestyle, the presence of significant co-morbidities, and use of concomitant medications. Tolerability should no longer be an obstacle to effective, long-term endocrine therapy.

J_Gastrointest_Surg-3-1-1852390

The Extended Learning Curve for Laparoscopic Fundoplication: A Cohort Analysis Of 400 Consecutive Cases

Many studies have looked at the learning curve associated with laparoscopic Nissen fundoplication (LNF) in a given institution. This study looks at the learning curve of a single surgeon with a large cohort of patients over a 10-year period. Prospective data were collected on 400 patients undergoing laparoscopic fundoplication for over 10 years. The patients were grouped consecutively into cohorts of 50 patients. The operating time, the length of postoperative hospital stay, the conversion rate to open operation, the postoperative dilatation rate, and the reoperation rate were analyzed. Results showed that the mean length of operative time decreased from 143 min in the first 50 patients to 86 min in the last 50 patients. The mean postoperative length of hospital stay decreased from 3.7 days initially to 1.2 days latterly. There was a 14% conversion to open operation rate in the first cohort compared with a 2% rate in the last cohort. Fourteen percent of patients required reoperation in the first cohort and 6% in the last cohort. Sixteen percent required postoperative dilatation in the first cohort. None of the last 150 patients required dilatation. In conclusion, laparoscopic fundoplication is a safe and effective operation for patients with gastroesophageal reflux disease. New techniques and better instrumentation were introduced in the early era of LNF. The learning curve, however, continues well beyond the first 20 patients. Introduction It is well known that there is a learning curve associated with laparoscopic Nissen fundoplication (LNF) for gastroesophageal reflux disease (GERD).1,2 A number of studies have shown a decrease in the number of complications with surgical experience and with modifications to the surgical technique of fundoplication over time. Watson et al.2 showed that the individual surgeon’s complication rate and conversion rate were highest in the first five procedures and stabilized after the first 20 operations. There are, however, few studies with large patient numbers showing the learning curve of a single surgeon and his/her trainees. We have evaluated this learning curve in our series of 400 consecutive patients undergoing laparoscopic fundoplication. Materials and Methods Between January 1993 and August 2002, 400 patients (262 males, 138 females) [mean age: 42.9 years (range 9–86)] underwent laparoscopic fundoplication in a District General Hospital. All procedures were performed or supervised by a dedicated upper gastrointestinal surgeon. Several trainees became the primary surgeons later in the series under direct supervision once they were deemed to have the appropriate laparoscopic skills. The indications for operation were: symptomatic GERD despite prolonged medical therapy; intolerance of medical therapy due to side effects; and volume regurgitation or patient preference for surgery. Data were collected prospectively on a handheld computer database (Psion, Psion Ltd., England). All patients underwent preoperative endoscopy and 24 h ambulatory esophageal pH monitoring. After the first 75 cases, all patients also underwent stationary esophageal manometry using a standardized technique. The operative technique was modified during the course of the study as new equipment became available. Initially, five 10-mm abdominal ports were used: toward the latter half of the study, two 5-mm and three 10-mm ports were used. For the first 35 patients, a 0° laparoscope was used: all subsequent operations were carried out using a 30° laparoscope. The lower esophagus was mobilized from the crural arch. All patients underwent division of the short gastric vessels initially using individually applied ligaclips: after case 215, a harmonic scalpel (Ethicon, Endosurgery, UK) was used. In the first 40 patients, the crura were repaired (using 2/0 silk) only if a hiatal defect and a hernia were present. After this, all patients underwent crural approximation. A loose wrap of 1–2 cm length was constructed over a 56 French gauge bougie using nonabsorbable sutures (initially silk; later “0” Ethibond) incorporating the anterior esophagus. During the period of the study, 63 patients, who were included in the fourth to seventh cohorts, underwent a laparoscopic partial posterior fundoplication as part of a randomized trial.3 These patients were included in this study, as there was no difference in symptomatic outcome, complication rate, or operative time between this group and those undergoing a 360° fundoplication. Fourteen pediatric patients underwent an LNF throughout the series. The surgical technique used was the same in adult and pediatric populations. Patients were encouraged to mobilize immediately and commenced on oral fluids, followed by a light diet, as soon as tolerated. The overall patient group was divided into eight cohorts of 50 consecutive patients. These cohorts were analyzed separately to compare the following: (1) patient demographics, (2) preoperative symptom length, (3) operative time, (4) length of postoperative hospital stay, (5) conversion to open operation, (6) reoperation rate, (7) postoperative dilatation rate, and (8) perioperative mortality or other early (within 6 months) postoperative complications. Results The mean age, weight, and length of preoperative symptoms for each group was similar (see Table 1). This table also shows an overall decrease in the amount of time to accrue each cohort throughout the study period. There was a steady decrease in the mean operative time throughout the study period from 143 min in the first cohort to 86 min in the last cohort (Fig. 1). The mean postoperative hospital stay was reduced from 3.7 days (range 2–25) to 1.2  days (range 1–5) from the first to the last cohort. There were no perioperative deaths. Table 1Demographics and Length of Preoperative Symptoms in Patients Undergoing Fundoplication for GERD Patient Numbers1–5051–100101–150151–200201–250251–300301–350351–400Time period to accrue cohort (months)2921121111121110Mean age (years) (range)36.3 (13–70)41.6 (9–82)43.9 (13–64)44.5 (12–86)44.3 (15–66)43.9 (17–66)45.4 (18–74)45.1 (15–81)Sex (M:F)34:1638:1228:2232:1829:2129:2134:1635:15Mean weight (kg) (range)71.1 (44–102)75.7 (29–98)76.1 (49–104)74.3 (30–102)79.5 (51–120)79.3 (44–103)78 (48–103)80.4 (53–100)Mean preoperative symptomatic period (months) (range)91 (8–420)85 (6–540)106 (3–480)92 (4–516)106 (4–430)96 (12–360)141 (6–1,152)140 (4–1,152)Figure 1Showing operative conversions to open procedure, rates of reoperation, and rates of dilatation in patients undergoing laparoscopic fundoplication for GERD. Figure 1 also shows the rate of conversion from laparoscopic to open fundoplication, the reoperation rate, and the postoperative dilatation rate. Conversions to Open Operation The conversion rate in the first cohort of 50 patients was 14%. Compared to this, only one conversion was required in the last 250 patients in the series, and this was necessitated by equipment failure rather than surgical difficulties. Other conversions were undertaken for hemorrhage from short gastric vessels (seven patients), port-site bleeding (one patient), splenic bleeding (one patient), difficult access (two patient), instrumental esophageal perforation (one patient), and adhesions from previous surgery (two patients). Patients Needing Postoperative Dilatations In the first 50 patients, 8 of them (16%) needed endoscopic balloon dilatation for persistent dysphagia or gas bloat syndrome between 10 days and 3 months postoperatively. They were dilated between one and three times. Nine patients (18%) were dilated in the second cohort between 9 days and 10 months postoperatively on one to four occasions. In the third cohort, six patients (12%) underwent dilatation between 1 week and 7 months, whereas in the fourth cohort, five patients (10%) were dilated between 3 weeks and 2 months postoperatively. They were all dilated once or twice. Two patients (4%) had two dilatations each between 2 and 9 months in the fifth cohort. No dilatations were needed by the last 150 patients to undergo laparoscopic fundoplication. Patients Needing Reoperation Figure 1 illustrates a decline in the number of patients requiring reoperation from seven patients (14%) in the first 50 to three patients (6%) in the last 50 patients. Table 2 shows the number of reoperations that took place for any given reason in our overall patient group. It also highlights the number of reoperations that occurred within 3 months of the original fundoplication. Table 2Total Number and Timing of Patients Undergoing Reoperation after Laparoscopic FundoplicationCause of ReoperationTotal Number of patientsEarly (within 3 months)Late (after 3 months)Mediastinal wrap herniation16115Persistent reflux11Dysphagia despite dilatation211Gas bloat33Perforation of wrap11Port-site hernia11 In the first cohort, five patients underwent reoperation for mediastinal “wrap” herniation between 9 and 80 months postoperatively. Two patients required revisional surgery; one underwent a Watson fundoplication, whereas the other undertook a redo Nissen fundoplication at 2 and 6 months, respectively, for persistent dysphagia failing to respond to endoscopic dilatations. One reoperation for “wrap” herniation was attempted laparoscopically but was converted to an open procedure. All other reoperations were carried out as open procedures. In the second cohort, three patients were reoperated on "for mediastinal “wrap” herniation and wrap disruption at 2, 30, and 47 months postoperatively: one by open surgery and two laparoscopically. One patient underwent laparoscopic conversion of a 360° to 270° “wrap” for “gas bloat” at 11 months despite two endoscopic “wrap” dilatations. There was one reoperation in the third cohort of patients for gas bloat 92 months later. The wrap was found to be mildly attenuated and was taken down laparoscopically. In the fourth cohort, one patient underwent laparoscopic conversion to a 270° “wrap” for “gas bloat” syndrome 12 months later, and one patient was converted from a 270° to a 360° wrap for a persistent reflux. Two patients underwent open reoperations in the fifth cohort: one for a perforation of the “wrap” at 4 days, the other for a port-site hernia repair at 9 months. In the sixth cohort, two patients underwent a redo LNF for wrap herniation and disruption at 23 and 36 months postoperatively. In the seventh cohort, two patients were found to have a wrap herniation, and one patient was found to have a large crural defect with wrap herniation at 18, 19, and 23 months, respectively. All underwent redo LNF; the patient with the large crural defect had a hiatal mesh placed. In the last cohort, three patients underwent redo LNF (two with hiatal mesh placement) for wrap herniation at 20, 27, and 36 months postoperatively. Discussion The postoperative complications most commonly associated with open fundoplication are dysphagia and gas bloat syndrome. The advent of the laparoscopic approach to fundoplication, first described in 1991,4 has introduced a number of procedure-specific complications, including pneumothorax, pneumomediastinum, major-vessel injury, mesenteric thrombosis, and gastrointestinal perforation.5 The first prospective randomized study comparing laparoscopic and open Nissen fundoplication6 showed similar complication rates and a better symptom outcome in those who had undergone laparoscopic surgery. There has, however, been a concern as to the severity of the reported complications in the laparoscopic approach.7 Before the commencement of this study, the surgeon had a 6-year experience with open fundoplications. In the early 1990s, formal courses were not available to learn laparoscopic fundoplication: consequently, the surgeons pioneering this procedure were mentored for the first few cases. After this, the surgeon would operate independently. Our study shows that as the surgeon’s experience of laparoscopic fundoplication increases, the mean operating time becomes comparable to that of an open operation. The mean postoperative length of stay in hospital was 1.2 days in the last 50 patients compared with an average stay of 7 days in those having an open fundoplication.8 The decrease in postoperative length of stay in hospital, which was seen throughout this series, can be partly attributed to increased knowledge of recovery from laparoscopic procedures and from patient feedback of their postoperative recovery. The high conversion rate to an open operation in our first 50 patients (14%) can be attributed to the surgical learning curve and poorer quality equipment leading to reduced quality of vision and the reduced ability to secure bleeding. Similarly, high conversion rates were seen in other early laparoscopic series.9,2 Only 1 of the last 150 patients needed conversion to an open procedure, and this was due to equipment failure. One patient underwent a splenectomy (0.3% of all patients) due to splenic bleeding, which is comparable to other studies.10 This compares with a splenectomy rate of 3.6% in open Nissen fundoplications in one study.6 Of the 15 patients requiring conversion throughout the series, 14 were in the preharmonic scalpel era. Nine of these were converted due to bleeding. The harmonic scalpel has greatly enhanced the ease of fundal mobilization in comparison to the application of individual ligaclips to the short gastric arteries. A decreasing trend in conversion rate can, however, be seen within the first four cohorts before the introduction of the harmonic scalpel. The number of patients undergoing endoscopic dilatation decreased significantly from 17% in the first 100 patients to none in the last 150 patients. This was probably due to a number of factors. First, none of the last 250 patients had symptomatic “wrap” disruptions/slippages causing dysphagia. The patients who were found to have wrap herniation presented with heartburn and not dysphagia. Secondly, it is now recognized that early dysphagia (less than 2 months postoperatively) is present in a significant proportion of patients but settles with time without the need for intervention.11 The exception to this is in children who are less tolerant of dysphagia after laparoscopic fundoplication and hence are more likely to require early endoscopic dilatation.12 Two studies12,13 have shown dilatation success rates of 56 and 67%, respectively, in resolving postfundoplication dysphagia. The study by Malhi-Chowla et al.13 also found that the only symptom that responded to dilatation was dysphagia. Throughout the series, two patients had been reoperated on for persistent dysphagia beyond 2 months. Both were in the first 25 cases, and both were found to have bowstringing of the wrap due to lack of division of the posterior gastric bands. One was converted to a Watson fundoplication, whereas the other underwent a redo Nissen fundoplication. Our low incidence of dysphagia may be in part due to the laparoscopic operation used. Hunter et al.14 showed that the incidence of early and late persistent dysphagia is significantly lower in both LFNs and Toupet fundoplications than in Rosetti–Nissen fundoplications. Two patients had undergone reoperation for gas bloat syndrome: both were converted to a 270° posterior wrap and are now either asymptomatic or mildly symptomatic. All patients in this study had been followed up for a minimum of 4 years. Overall, 6% of our patients required reoperation because principally of wrap herniation. After the first 40 operations, a routine posterior crural approximation was carried out with nonabsorbable sutures to reduce the incidence of thoracic “wrap” migration. Two studies15,16 have emphasized the importance of a crural repair in reducing the incidence of postoperative paraesophageal hiatus hernia. Basso et al.17 have proposed a mesh repair of the hiatus to prevent “wrap” migration after finding that in several reoperations, the sutures approximating the crura had cut out with consequent wrap herniation. Paraesophageal wrap herniation is more common in laparoscopic than in open fundoplication.16 Several reasons have been proposed for this: (1) the tendency to extend esophageal dissection further into the thorax,18 (2) the increased risk of breaching the left pleural membrane during dissection,19 and (3) the reduced postoperative pain allowing increased abdominal pressure when vomiting/coughing in the laparoscopic procedure.16 Wu et al.20 found that routine division of the short gastric arteries and posterior closure of the crura during LNF significantly reduced wrap slippage/migration. This is the procedure that we have undertaken since the 40th patient. Despite of this, 5% of the last 150 patients underwent reoperation (all for heartburn due to wrap herniation). Smith et al.21 have also concluded that wrap herniation is now the most common mechanism of failure requiring a redo fundoplication. Of the eight patients reoperated on in the first cohort, only one procedure was attempted laparoscopically. All reoperations are now attempted laparoscopically where possible. This change in approach has occurred with increasing laparoscopic experience. Several studies22,23 have shown that laparoscopic reoperations are not only possible and safe but also produce good results. Several studies24,25,26 have now shown a 90% satisfaction rate at 5-year follow-up after LNF. Our own study25 on patient satisfaction 2–8 years postlaparoscopic fundoplication revealed that once over the initial problem of early postoperative dysphagia, the satisfaction rate was 91%. Furthermore, 90% remained free of significant reflux symptoms, and only 14% were subsequently taking regular antireflux medication. This has changed little throughout the course of the series. Our results show a decreasing trend in operative time, postoperative hospital stay, conversion rate, postoperative dilatation rate, and reoperation rate with increasing surgical experience and improved technology. Another factor in this improvement may be due to the increased frequency with which this procedure was performed with time. Conclusion Dysphagia is the Achilles’ heel of laparoscopic antireflux surgery. To avoid this, the authors have routinely divided the short gastric vessels. This has led to an increased rate of conversion owing to hemorrhage especially during the period when individual ligaclips were used. Short gastric vessel division may, in addition, increase the rate of wrap herniation and clip or thermal injury to the gastric fundus leading to perforation. The high rate of reintervention in the first two cohorts would not be acceptable a decade later. It must be recognized that at the start of this series, the visual acuity of the optical systems and the quality of the instrumentation were both substantially inferior to those of today. Furthermore, there were no formal training courses available. The pioneers of advanced laparoscopic surgery had to suffer high conversion and complication rates in laparoscopic cholecystectomy,27 antireflux,2 and groin hernia surgery.28,29 When introducing complex techniques, surgeons tend to underestimate the learning curve: both of themselves and of their institution. Only by maintaining prospective data can these problems be identified and recognized.

Neuroimage-2-1-2387200

Abnormal brain connectivity in first-episode psychosis: A diffusion MRI tractography study of the corpus callosum

A model of disconnectivity involving abnormalities in the cortex and connecting white matter pathways may explain the clinical manifestations of schizophrenia. Recently, diffusion imaging tractography has made it possible to study white matter pathways in detail and we present here a study of patients with first-episode psychosis using this technique. We selected the corpus callosum for this study because there is evidence that it is abnormal in schizophrenia. In addition, the topographical organization of its fibers makes it possible to relate focal abnormalities to specific cortical regions. Eighteen patients with first-episode psychosis and 21 healthy subjects took part in the study. A probabilistic tractography algorithm (PICo) was used to study fractional anisotropy (FA). Seed regions were placed in the genu and splenium to track fiber tracts traversing these regions, and a multi-threshold approach to study the probability of connection was used. Multiple linear regressions were used to explore group differences. FA, a measure of tract coherence, was reduced in tracts crossing the genu, and to a lesser degree the splenium, in patients compared with controls. FA was also lower in the genu in females across both groups, but there was no gender-by-group interaction. The FA reduction in patients may be due to aberrant myelination or axonal abnormalities, but the similar tract volumes in the two groups suggest that severe axonal loss is unlikely at this stage of the illness. Introduction Altered connectivity is likely to account for the symptoms and cognitive changes of schizophrenia (Friston and Frith, 1995). A disconnectivity model involving both loss of specialized cortical function and damage to connecting pathways is likely to apply to schizophrenia (Catani and ffytche, 2005). Imaging studies have repeatedly confirmed the presence of cortical abnormalities, especially in prefrontal and temporal heteromodal cortex (Shenton et al., 2001; Bagary et al., 2003; Foong et al., 2001), and synaptic pathology leading to aberrant cortical circuitry has been well documented in neuropathological studies (Harrison and Weinberger, 2005). By comparison, the study of abnormalities in intra- and interhemispheric pathways has received much less attention, although the occurrence of schizophrenia-like symptoms has been documented in diseases involving the white matter (Walterfang et al., 2006). Among these connecting pathways the corpus callosum is of special interest in schizophrenia. The corpus callosum develops into the third decade of life (Pujol et al., 1993) and the topographical organization of its fibers makes it possible to relate its abnormalities to specific cortical regions. Fibers of small diameter from heteromodal cortex traverse the genu (connecting prefrontal cortex) or the splenium (connecting superior temporal cortex), and larger diameter fibers connecting unimodal motor and sensory cortex traverse the body. A model by Crow (1998), based on the evolutionary aspects of language and the emergence of psychosis in man, postulated that abnormalities in callosal pathways connecting areas of the cortex asymmetrically distributed between the two hemispheres were central to schizophrenia. Since then, conventional MRI studies (Shenton et al., 2001), including those in drug-naive patients with their first episode of schizophrenia (Keshavan et al., 2002), have reported reduction in the size of the corpus callosum, more marked anteriorly, but shape differences in the rostral and mid area of the body containing motor and sensory fibers have also been reported (Goghari et al., 2005). Similar findings have been reported by Bachmann et al. (2003) in a first-episode cohort that included patients with schizophreniform and schizoaffective psychoses. In addition, a longitudinal study of patients with childhood-onset schizophrenia (Keller et al., 2003) has suggested that a failure of normal callosal growth may result in area reductions, particularly in the splenium, by early adulthood. Other imaging studies using voxel-based analysis (Hulshoff Pol et al., 2004) or magnetization transfer imaging (Foong et al., 2001) have also reported abnormalities, predominantly in the genu. In addition Highley et al. (1999a), in a detailed neuropathological study, reported a decrease in axon density in all, but the rostral region of the corpus callosum in female schizophrenics compared to controls. The functional significance of the corpus callosum in schizophrenia has been well documented by studies of interhemispheric transfer of information (Innocenti et al., 2003). Diffusion tensor imaging (DTI) (Basser et al., 1994) has made it possible to study in vivo the integrity and orientation of neural tissue by measuring water diffusion in the brain. DTI studies have used a region-of-interest (ROI) methodology and have measured the apparent diffusion coefficient (ADC) and/or fractional anisotropy (FA), indices of white matter integrity. An early study from our group (Foong et al., 2000) reported reduced FA in the splenium of the corpus callosum in patients with chronic schizophrenia and similar findings have been reported by others in the splenium (Agartz et al., 2001), or in the structure as a whole (Brambilla et al., 2005; Ardekani et al., 2003; Kubicki et al., 2005). Kumra et al. (2004), on the other hand, failed to find such abnormalities in a small group of patients with early-onset psychosis and the same was the case in the only available study in first-episode patients, also from our group (Price et al., 2005). The clinical correlations of these corpus callosum abnormalities remain uncertain. Brambilla et al. (2005) reported a correlation between DTI changes in the anterior part of the corpus callosum and severity of positive symptoms, but these findings have not been confirmed in other studies. The information about the direction of diffusion encoded by the eigenvalues and eigenvectors of the diffusion tensor has been used in DTI tractography (Mori et al., 1999) to investigate the continuity of axonal orientation between voxels and thus to infer the paths of fiber tracts in 3 dimensions. DTI tractography has been used in studies of normal subjects (Toosy et al., 2004; Parker and Alexander, 2005; Parker et al., 2005), in patients with multiple sclerosis (Wilson et al., 2003), callosal dysgenesis (Lee et al., 2004) and stroke (Huang et al., 2005). To date only one study (Kanaan et al., 2006) has used tractography to study the corpus callosum in patients with chronic schizophrenia, reporting reduced FA in the genu and it also demonstrated the superiority of this method, over ROI studies, in detecting subtle abnormalities across the whole of a white matter tract. Here we present, to our knowledge, the first study of the corpus callosum (or indeed any white matter pathway) in patients with first-episode schizophrenia spectrum disorders using diffusion imaging tractography. The main aim of the study was to determine whether subtle abnormalities of interhemispheric connections could be detected using this new technique in a group of patients during the first-episode of psychosis, in whom chronicity-related factors could be excluded. We hypothesized that measures of tract coherence (FA), in white matter traversing the genu and splenium of the corpus callosum, would be significantly reduced in the patient group compared to controls. Materials and methods The patients were recruited as part of a prospective, longitudinal study of first-episode psychosis in West London. Patients were eligible to be recruited into the study if they fulfilled the following criteria; age between 16 and 50 years presenting with a psychotic illness for the first time and less than 12 weeks on antipsychotic medication. Patients eligible for the study were screened using the WHO Psychosis Screen (Jablensky et al., 1992). The diagnosis was established using a structured interview, the diagnostic module of the Diagnostic Interview for Psychosis (DIP, Jablensky et al., 2000), which includes items from the Operational Criteria Checklist for Psychosis (OPCRIT, McGuffin et al., 1991) and the World Health Organization Schedules for Clinical Assessment in Neuropsychiatry (SCAN, Wing et al., 1990). Using these data, a computerized algorithm generates diagnoses under several classification systems including DSM-IIIR and ICD-10. DSM-IIIR diagnoses were subsequently checked against DSM-IV criteria by separately entering OPCRIT items into OPCRIT for Windows (http://sgdp.iop.kcl.ac.uk/opcrit/). Exclusion criteria were the presence of a medical or neurological illness that might impair cognitive function including head injury and alcohol or drug dependency. Eighteen patients with an initial diagnosis of schizophrenia, schizophreniform or schizoaffective disorder took part in this study. Fifteen of these patients were interviewed again a year later to review the diagnosis, and for the remaining three, who could not be interviewed, a final diagnosis was established also a year later by compiling information from clinicians looking after the patients and by reviewing the clinical notes. Thirteen patients received a final diagnosis of schizophrenia and the remaining five received a diagnosis of schizoaffective disorder (one bipolar, two manic and two depressed subtype). The patients had been ill for a mean of 12.6 months (SD = 19.3 months, range 0–72 months) at entry into the study. The range and severity of symptoms were assessed at each time point with the Scales for the Assessment of Positive Symptoms (Andreasen, 1983) and Negative Symptoms (Andreasen, 1981), The Young Mania Scale (Young et al., 1978) and the Hamilton Rating Scale for Depression (Hamilton, 1960). The onset of psychosis was established using the Symptom Onset in Schizophrenia inventory (Perkins et al., 2000). Alcohol and drug use was assessed as part of the Diagnostic Interview for Psychosis (see above) and criteria for abuse and dependence were established using the Alcohol Use Scale and the Drug Use Scale (Drake et al., 1990). The mean age of the patient group was 23.6 years (SD = 6.3; range = 17–38 years), composed of 8 males and 10 females. All patients were receiving antipsychotic medication at the time of scanning. Twenty-one healthy subjects with a mean age of 29.4 years (SD = 7.1; range = 16–42 years) with a gender composition of 6 males and 15 females served as controls. Handedness for all subjects was assessed using the Annett scale (Annett, 1970) as it may be associated with DTI findings in the corpus callosum (Westerhausen et al., 2003). Exclusion criteria were the same as in the patient group as well as history of psychiatric illness in themselves or their first-degree relatives. See Table 1 for a description of study subjects. Permission to conduct the study was obtained from Merton, Sutton and Wandsworth, Riverside and Ealing Research Ethics Committees. All participants gave written informed consent and were paid an honorarium for their time. MRI data acquisition MRI for all subjects was obtained using a GE Signa 1.5 T scanner (General Electric, Milwaukee, WI, USA), which underwent regular quality-control checks, using a standard quadrature head coil. Each subject had a dual-echo fast spin echo scan (TR = 2000 ms, TE1/TE2 = 19/95 ms, matrix = 256 × 192, field of view [FoV] = 24 × 18 cm2), which provides both proton density and T2-weighted images. Twenty-eight 5-mm slices were collected, in an oblique-axial plane (parallel to the AC/PC line). An axial plane, IR-SPGR sequence was also performed which obtained a series of 156 contiguous axial slices with the following parameters TE = 5.1 ms, matrix = 256 × 128, field of view = 31 × 16 cm2, slice thickness = 1.2 mm, TR = 14.3 ms, flip angle 20°, TI = 450 ms. Diffusion-weighted single-shot echo planar images (DW-EPI) were acquired in the axial plane (TE = 96 ms, FoV = 22 × 22 cm2, matrix = 96 × 96, slice thickness = 2.3 mm, Δ = 40 ms, δ = 34 ms, resulting in a maximum b factor of 1000 s/mm2). The acquisition of diffusion-weighted images was gated to the cardiac cycle using a pulse oximeter with a gating scheme optimized for diffusion imaging. Gradients for diffusion sensitization were applied in 54 non-collinear directions. Six images with no diffusion weighting (b ≈ 0 s/mm2) were also collected for each slice, giving a total of 60 images per slice. Images were interpolated to a 128 × 128 matrix during reconstruction, yielding a final in-plane resolution of 1.72 mm. Diffusion processing and analysis The diffusion tensor was estimated for each voxel according to the method of Basser et al. (1994) and used to compute FA. We also used a model-selection algorithm based on the fit of spherical harmonic series to the diffusion profile (Alexander et al., 2002) to detect the most parsimonious description of diffusion in every voxel. Diffusion within each voxel was classified as isotropic, anisotropic with a single principal direction of diffusion, or anisotropic with more than one direction of diffusion (as in the white matter of the centrum semiovale). The single tensor model was subsequently used for voxels characterized by isotropic diffusion or a single direction of diffusion population. The two-tensor model of diffusion, as described by Parker and Alexander (2003), was used for the remaining voxels. We used a probabilistic tractography algorithm (PICo or ‘probabilistic index of connectivity’) which considers multiple pathways emanating from a seed point or region (i.e. a group of voxels in a region of interest) (Parker and Alexander, 2003, 2005). Due to the presence of noise in the data, there is some uncertainty associated with the determination of the principal direction of diffusion. The algorithm accounts for this uncertainty by generating a probability density function (PDF) of fiber alignment from the diffusion model of each voxel (which in this case is either the single or the two-tensor model). This provides voxel-wise estimates of confidence in fiber tract alignment, which are then used in the probabilistic tract-tracing procedure. Using the PDFs from a chosen seed point, streamline-based tracking is performed and repeated 10,000 times in a Monte Carlo fashion (sampling each PDF at random on each repeat) to produce tract maps that estimate the probability of connection of every voxel in the brain to a given seed point or region (Parker and Alexander, 2005). Streamlines were propagated using trilinear interpolation of PDFs, as suggested by Behrens et al. (2003), and were terminated if curvature over the scale of a single voxel exceeded 180° or if the path left the brain. Seed regions were placed in the genu and splenium of the corpus callosum. The genu was defined as the most anterior point of the corpus callosum before it bends downwards and backwards in front of the septum pellucidum, and the splenium as the posterior end of the corpus callosum at its thickest part. Each seed region consisted of a six voxel rectangular shape on a single axial slice. This region size ensured that partial volume effects were completely avoided. Seed regions were placed by displaying the FA maps in three mutually orthogonal orientations using MRIcro (http://www.sph.sc.edu/comd/rorden/) and identifying the sagittal and coronal planes in which the volumes of the genu and splenium were largest. The seed regions were placed on the axial view corresponding to the intersection of these sagittal and coronal planes. The seed region placement was the only operator-dependent step in the diffusion processing. To assess the inter-rater reliability of the method, a second, independent rater performed the seed region placement in 8 cases, using the same procedure. The voxel values of the PICo output maps for the corpus callosum range from 0 (no probability of connection) to 1 (certainty of connection) with an intensity resolution step of 0.001 representing the ratio of the number of times that voxel was reached by a streamline originating from the seed point to the total number of iterations in the Monte Carlo process. Each PICo map was thresholded at five probability values ranging from 0.001 (the lowest recorded value of probability of connection) to 0.03, at logarithmically spaced intervals, to generate five objective binary masks (thresholded at 0.001, 0.002, 0.006, 0.013 and 0.03). This multi-threshold approach, previously used in the study of visual pathways (Toosy et al., 2004), allows with increasing degrees of certainty the reconstruction of the core of the tract, where fiber alignment should be greatest, and the exploration of the probability of connection of distant voxels to the seed point. For each threshold the mean tract volume and the mean FA were calculated for each subject. The spatial variability of the tract across each subject group was characterized as previously described (Toosy et al., 2004; Parker et al., 2005). Firstly the non-diffusion-weighted (b = 0) images (inherently co-registered with PICo output images) were normalized to a stereotactic space (Montréal Neurological Institute, MNI) using the standard echo planar image template in SPM2 (Wellcome Department of Cognitive Neurology, Institute of Neurology, London, UK) running in MATLAB (MathWorks, MA). The normalization parameters thus obtained were then applied to the binary images of the tract obtained by thresholding the probability images at the level that maximized the difference in FA between patients and controls (see below). After normalization, these images were averaged on a voxel-by-voxel basis, producing a map used to display the degree of tract overlap between subjects within each group. In order to detect the presence of ventricular enlargement in the patient group, which might affect tractography, we performed a voxel-based comparison of CSF maps between the two groups using SPM2 (Wellcome Department of Cognitive Neurology, Institute of Neurology, London, UK). The IR-SPGR images were segmented and normalized using the iterative procedure described in Good et al. (2001), thus performing first a segmentation in native space, next normalizing gray matter images using the standard a priori gray matter template available in SPM2 and applying the same normalization parameters to the whole volume. The normalized volume was then segmented again yielding white matter, gray matter and CSF probability images. Voxel values in segmented images were multiplied by the Jacobian determinants derived from spatial normalization (modulation) to provide intensity correction for induced regional volumetric changes, thus preserving within-voxel volumes that may have been altered during non-linear normalization (Ashburner and Friston, 2000). CSF images were also smoothed to 6 mm (Full-Width-Half-Maximum) Gaussian filter. Smoothing is required to accommodate anatomical variation between subjects and therefore results in more normally distributed data. Global CSF volumes in cm3 were also obtained by integrating the CSF image signal intensity over the whole volume for each subject. Statistical analysis Age, gender and handedness distributions in the two groups were compared using t-tests and χ2 tests. The inter-rater reproducibility of the method was tested by comparing the tract volumes obtained by the two raters. Inter-rater reliability was assessed using the coefficient of variation (CoV), CoV = (σ / μ) × 100%, where σ is the standard deviation and μ is the mean, with lower values indicating better reproducibility. Multiple linear regressions of mean FA were carried out to compare tract coherence in patients and controls, with gender, age and tract volume as covariates, to control for between-group differences in these covariates. To avoid spurious positive results due to multiple comparisons, the multiple regressions were carried out simultaneously for each of the five thresholds in the genu and the splenium (ten regressions) using Zellner’s seemingly unrelated regression method (Zellner, 1962), which yields a single significance value (from the F-statistic) of the difference between patients and controls across all ten regressions, in addition to individual values for each regression. The F-statistic is obtained by comparing the ten regressions obtained including or excluding group membership and taking into account the correlations between the residuals from all ten equations. This method also allows a test of whether region (genu or splenium) or probability thresholds modify the differences in FA between patients and controls. Similar multiple linear regressions were performed to explore gender differences in FA (when adjusting for group membership, age and tract volume) as well as age differences in FA (adjusting for group membership, gender and tract volume). A voxel-based statistical comparison between CSF maps from patients and controls was performed in SPM2 based on the General Linear Model and Gaussian random field theory incorporating subject age and gender into this model. Results Patients were significantly younger than controls. The mean age for patients was 23.6 years and 29.4 years for controls (t = − 2.7, df = 37, P = 0.011). However, there was an age overlap between the two groups, allowing the results to be adjusted for age. There were no significant differences in gender distribution (χ2 = 0.62, df = 1, P = 0.43) or handedness (χ2 = 1.81, df = 1, P = 0.18) between the groups. All patients were receiving antipsychotic medication and two were on mood stabilizers at the time of the study (see Table 1). The average duration of treatment prior to scanning was 61 days (range 8–153 days). The coefficient of variation for the tract volume for the 8 repeated measurements performed by two raters was 1.36%, indicating a very high inter-rater reproducibility. The tract overlap maps for the genu and splenium in patients and controls (Figs. 1 and 2) were compared with reference maps of the corpus callosum to ascertain their anatomical validity. The estimated tract volumes in patients and controls decreased at higher connection probability thresholds as the core of the tract was progressively isolated. Conversely, FA increased with higher thresholds (Figs. 3A–D). The results of the multiple regression analysis comparing FA in patients and controls are shown in Table 2. The single test of significance considering both regions of the corpus callosum at all thresholds was P ≤ 0.02, indicating a significant difference in FA between the two groups in either region, over all thresholds. Inspection of the differences in FA at the individual thresholds indicated that the differences in FA between the groups are due to lower FA in the patient group in the genu at probability thresholds 0.006 and 0.013, and to a lesser extent in the splenium at thresholds 0.013 and 0.03 (see Table 2). To examine subgroup differences in FA, we performed a regression analysis to compare the 13 schizophrenic and 5 schizoaffective patients. Both subgroups had a lower FA than controls. Results from the regression analysis revealed that in the genu, the schizoaffective group had a lower FA than the schizophrenia group (P = 0.0806), whereas in the splenium, the schizoaffective group had higher FA values than the schizophrenia group (P = 0.0295). This suggests that, although there may be subtle differences between subgroups, they differed from controls in the same direction and amalgamating the subgroups does not obscure the differences between patients and controls. We performed a separate analysis looking for gender and age differences in FA by considering patients and controls together. In the analysis of gender, a single test of significance considering all thresholds and both regions of the corpus callosum gave a P = 0.0001. This result indicates that there are gender differences in FA irrespective of subject status. Thus FA, adjusted for group membership, was lower in females than males in the genu at thresholds 0.001 and 0.002, but not in the splenium. There was no significant group membership-by-gender interaction (P = 0.2). With respect to the effects of age, there was no evidence that the difference between patients and controls in FA varied with age (P = 0.791) for the global test over both regions (i.e. the ten equations), after adjusting for gender and tract volume. Finally, the SPM analysis using a voxel-based comparison of CSF maps between the two groups revealed no differences between patients and controls using a family wise error correction for multiple comparisons, with f = 34.42 and no voxels as an extent threshold. This indicates that no ventricular enlargement was present in the patient group relative to controls. There was no significant difference between the global CSF volumes of patients (287 cm3, SD = 33.6) and controls (283 cm3, SD = 51.6) (t = − 0.85, P = 0.40, CI = [− 41.7–17.2]). Discussion Our findings provide evidence of altered interhemispheric connectivity in patients with first-episode schizophrenia spectrum disorders. In the patient group, abnormal tract coherence, as measured by reduction in FA, was present in tracts traversing the genu and, to a lesser extent, in those traversing the splenium. Tract coherence, as measured by FA, was lower in females, both in patients and controls, but we failed to find a gender-by-group interaction. The genu and the anterior part of the body of the corpus callosum contain mainly connections from prefrontal cortex, cingulate and insula, and pathology in these cortical regions could result in the abnormalities of the corpus callosum described here. Similarly, a decreased thalamic input to the frontal and temporal cortex, perhaps due to excessive synaptic pruning, could also result in decreased cortical connections and hence in abnormalities in the corpus callosum (Innocenti et al., 2003), but it is also possible that primary white matter abnormalities could contribute to our findings (Walterfang et al., 2006). The corpus callosum develops alongside other midline structures, namely the fornix, hippocampus, septum and cingulate cortex, and developmental or maturational abnormalities involving the corpus callosum are also likely to affect these structures known to play a role in schizophrenia. Our diffusion-MRI-based tractography (PICo) used a probabilistic approach that takes into account branching, crossing and merging of tract fibers and this represents an advantage over previous deterministic approaches that do not take these anatomical features into consideration (Kanaan et al., 2006). In addition the use of different probability thresholds and simultaneous multiple regression analysis (Zellner, 1962) has allowed us to demonstrate evidence, from a single statistical test, that there is some difference in tract coherence between patients and controls and to explore the characteristics of the core of the tract in the genu and the splenium. The group differences in FA become more apparent at intermediate probability thresholds in the genu when fiber alignment in the core of the corpus callosum is greatest and aberrant branching that could have artificially reduced FA (Jones et al., 2005) less likely. The high inter-rater reliability in the placement of the seed points also suggests that the differences in FA between patients and controls are likely to be illness-related rather than artifactual. The same applies to the effects of gender and age, known to affect FA (Price et al., 2005; Jones et al., 2005), that were statistically controlled for in our study as our groups were not closely age matched. Antipsychotic medication may have played a role in reducing FA, although it seems unlikely that medication effects could fully account for the differences between the groups in first-episode patients who had been exposed to medication for short periods. Moreover, others (Flynn et al., 2003) have found no correlation between the presence of white matter abnormalities in first-episode psychosis and exposure to antipsychotic medication. The possible effect of mood stabilizers in explaining our results is likely to be negligible as they were used in only 2 patients. The gender difference in tract coherence that we found in our subjects, particularly in the genu, supports our previous results in a different sample of first-episode patients and controls using a region-of-interest methodology (Price et al., 2005) and is in keeping with the lower anisotropy in normal females than males reported by Westerhausen et al. (2003). Gender dimorphism and maturational differences are likely to be relevant in explaining this finding. Dubb et al. (2003), in an MRI study of normal subjects, found a larger genu and smaller splenium in men compared with women and attributed the differences to different hormonal influences, to enhanced motor coordination in men (interhemispheric connections crossing the genu) and to greater bihemispheric representation of language in women (tracts crossing the splenium). Adult maturational changes in the corpus callosum, with a peak in the third decade of life, would further accentuate these differences. The differences in age between the two groups are a limitation of the study, although we tried to circumvent the problem using age as a covariate. The precise neuropathological correlates of FA abnormalities remain to be fully elucidated. Axonal membranes are considered to be the main determinant of anisotropy in neural tissue, and pathological or experimental models of axonal degeneration have lead to reductions in FA. Myelin abnormalities are also responsible for changes in FA, although their contribution may be less important than those of axons or axonal membranes (Beaulieu, 2002). In our study the lower FA in the white matter tracts traversing the corpus callosum may be due, in addition to myelin abnormalities, to differences in axonal membranes, alterations in axonal packing density, mean axonal diameter (for example due to a bias towards axons of greater or lesser diameter in one or other group) or a less coherent fiber alignment in the patient group. The similar tract volumes we found in patients and controls may suggest that severe axonal loss is unlikely at this early stage of the illness. On the other hand, the greater variance in genu tract volumes in the patient group suggests that there may be more branching (i.e. less coherence or alignment) in the core of the tract. We have also excluded the possibility that our findings could be related to ventricular enlargement in the patient group. The study of patients with first-episode psychosis has the advantage of minimizing the effects of chronicity and lengthy exposure to medication, on the other hand, such patients are diagnostically heterogeneous and this is one of the shortcomings of our study and it remains uncertain whether the changes in corpus callosum described here are a core neuropathological abnormality common to all psychosis or are only present in a subgroup of patients. Support for the former accrues from the study of Bachmann et al. (2003) who reported similar findings in a heterogeneous group of patients with first-episode psychosis. In addition, there is evidence to suggest that corpus callosum abnormalities are also present in patients with bipolar disorder (Brambilla et al., 2003, 2004) and other DTI studies looking at ROIs in frontal white matter, although not specifically at the corpus callosum, have reported low FA in a mixed group of patients with first-episode psychosis (Szeszko et al., 2005) and in those with first-episode mania (Adler et al., 2006). There is also evidence that oligodendrocyte and myelination genes may be downregulated both in schizophrenic and affective psychosis (Tkachev et al., 2003; Iwamoto et al., 2005). It is also likely that the abnormalities described here may also be present in other connecting tracts, as suggested by the neuropathological findings of Highley et al. (1999b) in the anterior commissure, and the results of DTI imaging studies (Kubicki et al., 2005). Our study suggests that the schizophrenia and schizoaffective subgroups may be heterogeneous based on FA, but both these groups differ from controls in the same direction of FA change. An intriguing possibility, in need of further study, is that genetic variability within schizophrenia may be associated with specific patterns of brain morphology including variations in the size and structure of the corpus callosum (Agartz et al., 2006). Our findings also demonstrate that tractography is capable of detecting subtle pathological abnormalities in patients with psychosis early in the disease that may go undetected using other DTI methods (Price et al., 2005; Kanaan et al., 2006). Tractography is likely to have a role in future psychosis research, in elucidating connections between relevant cortical regions and in giving specific information about white matter abnormalities and their evolution over time.

Eur_Radiol-3-1-2077908

Bone marrow edema-like lesions change in volume in the majority of patients with osteoarthritis; associations with clinical features

It has been suggested that bone marrow edema-like (BME) lesions in the knee are associated with progression of osteoarthritis (OA). The purpose of our study in patients with OA was to evaluate prospectively changes of BME lesions over 2 years and their relationship with clinical features. Magnetic resonance (MR) images of the knee were obtained from 182 patients (20% male; aged 43–76 years; mean age 59 years) who had been diagnosed with familial symptomatic OA at multiple joint sites. MR images were made at baseline and at 2 years follow-up. BME lesions in 2 years were associated with clinical features assessed by Western Ontario and McMaster Universities Osteoarthritis (WOMAC) scores. A total of 327 BME lesions were recorded. Total size of BME lesions changed in 90 patients (66%). Size of individual lesions changed in 147 foci (45%): new lesions appeared in 69 (21%), existing lesions disappeared in 32 (10%), increased in size in 26 (8%) and decreased in size in 20 (6%) lesions. Increase or decrease of BME lesions, over a 2-year time period, was not associated with severity of WOMAC scores. BME lesions fluctuated in the majority of patients with OA over a 2-year time period. These changes were not associated with severity of WOMAC scores at the study end point. Introduction Knee osteoarthritis (OA) is a chronic, progressive joint disease, leading to pain and loss of function in a considerable proportion of patients, with great impact and consequences in the ageing population of the industrialized world. Disease markers need to be identified in order to predict and quantify progression. One possible marker in OA is the so-called bone marrow edema-like (BME) lesions [1]. Unfortunately, the role of BME in OA remains controversial, as contradictory results have been reported. BME detected with magnetic resonance (MR) imaging has been associated with clinical symptoms in patients with OA [2, 3]. However, other studies reported no association between BME lesions and clinical symptoms [4–6]. Further, the role of BME as a marker for progression of OA is open to discussion. In a study by Felson et al. [7], BME was associated with progression of OA as assessed by joint space narrowing on conventional radiographs. On the other hand, in a study by Phan et al. [5], changes in BME did not significantly change with progression of disease assessed by Western Ontario and McMaster Universities Osteoarthritis (WOMAC) scores. Since these contradictory results regarding the association between BME and clinical features have been reported, the purpose of our study was to evaluate changes in BME lesions over a 2-year period, and associate them with clinical features. Patients and methods Patients The present prospective study is part of the ongoing GARP (Genetics, Osteoarthritis and Progression) study [8]. The primary goal of the GARP study is the identification of genetic susceptibility determinants to OA and disease progression in middle-aged sibling pairs with OA at multiple joint sites. MR image sets of the knee were obtained in 182 patients at study entry and after 2 years [6]. Only one knee, the most symptomatic, was imaged per patient. In the present, study 39% (71/182) of the patients had symptomatic knee OA in their imaged knee, defined as pain or stiffness on most days in the month prior to study entry, and osteophytes on radiographs. As the purpose of the MR study was to assess progression of OA, no images were made of a knee that already had a maximum Kellgren and Lawrence score of grade 4 [9]. Clinical assessment Clinical data were assessed by WOMAC to assess pain, stiffness and functional impairment of the imaged knee at the 2-year time point, not at baseline [10]. MR acquisition Knees were imaged using a transmit-receive four-channel knee coil in a 1.5-T superconducting magnet (Philips Medical Systems, Best, the Netherlands). Each examination consisted of: coronal proton density and T2-weighted dual spin echo (SE) images (with repetition time (TR) of 2,200 ms; echo time (TE) of 20/80 ms; number of excitations per data line (NEX) 2; 5 mm slice thickness; 0.5 mm intersection gap; 160 mm field of view (FOV); 256 × 205 acquisition matrix, 18 slices); sagittal proton density and T2-weighted dual SE images (TR 2,200 ms; TE 20/80 ms; NEX 2; 4 mm slice thickness; 0.4 mm intersection gap; 160 mm (FOV); 256 × 205 acquisition matrix, 20 slices); sagittal 3D T1-weighted spoiled gradient echo (GE) frequency selective fat suppressed images (TR 46 ms; TE 2.5 ms; NEX 1; flip angle 40°; 3.0 mm slice thickness; slice overlap 1.5 mm; no gap; 180 mm (FOV); 256 acquisition matrix, 80 slices); and axial proton density and T2-weighted turbo spin echo (TSE) fat suppressed images (TR 2,500 ms; TE 7.1/40 ms; NEX 2; 2 mm slice thickness; no gap; 180 mm (FOV); 256 acquisition matrix, 62 slices). Total acquisition time (including the initial survey sequence) was 30 min. MR interpretation All MR images were analyzed in known chronological order by means of consensus between three experienced readers, using a comprehensive score form [11]. During the assessment, the readers were blinded to radiographic results, patient symptoms and patient age. In cases of disagreement between the readers the more conservative, less severe score was recorded. BME or cysic lesions was assigned to any one or more of the following anatomic locations: the crista patellae, medial or lateral patellar facets, the medial or lateral trochlear articular facets, the medial or lateral femoral condyles, the medial or lateral tibial plateaux. BME lesions were defined as an ill-defined area of increased signal intensity on T2-weighted images in the subchondral bone, extending away from the articular surface over a variable distance [12]. The lesions were graded as follows: grade 0, absent; grade 1, minimal (diameter <5 mm); grade 2, moderate (diameter 5 mm–20 mm); grade 3, severe (diameter >20 mm). The maximum two-dimensional diameter was measured to grade the lesion. A total BME score of the knee was calculated by adding all grades of each BME lesion in the knee. Maximum possible knee score was 27 (grade 3 times nine anatomic locations). In the total study a maximum of 1,638 BME lesions (182 patients times nine anatomic locations) could be scored. Subchondral cysts were defined as well-defined foci of high signal intensity, with low signal intensity margins, on T2-weighted images, in the bone underlying the joint cartilage. Their greatest dimension was measured and they were graded as follows: grade 0, absent; grade 1, minimal (<3 mm); grade 2, moderate (3–5 mm); grade 3, severe (>5 mm). A total score of the knee was calculated by adding all grades of each cystic lesion in the knee. Maximum possible knee score was 27 (grade 3 times nine anatomic locations). In the total study a maximum of 1638 cystic lesions (182 patients times nine anatomic locations) could be scored. Statistical analysis Odds ratios (ORs) with 99% confidence intervals (CIs) were used to show any association between BME size changes with cystic size changes. The difference in WOMAC scores between patients without BME lesions (group A) and patients with BME lesions (group B: unchanged BME lesions over 2 years; group C: increasing size of BME lesions over 2 years; group D: decreasing size of BME lesions over 2 years) was calculated by linear mixed models in SPSS for Windows, version 12.0 (SPSS, Chicago, Ill.) with a random intercept to adjust for the familial effect within sib pairs. Adjustments were made for age, sex and body mass index (BMI). Estimates of fixed effects were reported with 95% CIs. Results In total 182 patients were monitored over a period of 2 years (Table 1). Forty-six (25%) patients did not have BME lesions; thus, 136 patients (75%) had one or more BME lesions at any time point. In 46 (34%) of patients, BME scores did not fluctuate, whereas they changed in the other 90 (66%) patients. The total BME score per individual patient increased in 54 (40%) patients. It decreased in 27 patients (20%), and total BME score remained unchanged in nine (7%) patients. Individual BME scores did change in this last group without resulting in a change of the total BME score. A total of 327 BME lesions were detected from a possible total of 1,638 lesions (Table 2). One hundred and forty-seven (45%) BME lesions changed: 69 new lesions appeared on the second MR (21%), 26 (8%) increased, 20 (6%) decreased in size, and 32 (10%) were no longer visible on the second MR scan (Fig. 1). It was noted that more lesions appeared or increased than decreased or disappeared. Table 1Patient characteristics (n = 182) At baselineAge years, median (range)59 (43–76)Female sex, (%)157 (80%)Body mass index (kg/m2), median (range)25.7 (20.2–40.0)Symptomatic knee OA, n (%)a71 (39%)Kellgren & Lawrence Score 0/1/2/3/4, No.59/53/60/10/0Over 2 yearsBone marrow edema-like lesions, n (%)b128 (70%)Grade 0/1/2/3c54/56/62/10Cysts, n (%)b100 (55%)Grade 0/1/2/3c82/60/37/3At 2 yearsWOMAC Pain scores, median (range)d13 (0–99)WOMAC Stiffness scores, median (range)d18 (0–99)WOMAC Function scores, median (range)d14 (0–98)aDefined as pain or stiffness on most days of the month prior to study entry, in combination with osteophytes on radiographsbDuring 2 yearscMaximal grade per patientdn = 157Table 2Cystic and BME lesions per patient changing over 2 years in 182 patients (n = 1,638) BME lesionsNo BMENo changeIncreaseDecreaseTotalCystsNo cyst1,2807738211,416No change24872417152Increase21130346Decrease5531124Totals1,31118095521,638Fig. 1a–d Axial T2-weighted turbo spin echo fat suppressed images. Increase (a at baseline, b after two years) in size of bone marrow edema-like lesions over 2 years at the crista patella (arrow) and at the medial femoral condyle (arrowhead). Decrease (c at baseline, d after two years) in size of bone marrow edema-like lesions over 2 years at the crista and medial part of the patella (open arrowhead) One hundred (55%) patients had one or more cystic lesions at any time. In 44 patients (44%), total cystic score did not fluctuate over time, whereas in the other 56 patients (56%) the total cystic score changed in size. In 36 of these 56 patients (64%) the cystic score increased, it decreased in 18 patients (32%), and the total cystic score remained unchanged irrespective of changes on the level of individual cysts in two patients (4%). A total of 222 cystic lesions were detected from a possible total of 1,638 sites (Table 2). Seventy cystic lesions (32%) changed: 32 new cysts appeared on the second MR (46%), 14 (20%) increased, six (8%) decreased in size, and 18 (26%) were no longer visible on the second MR (Fig. 2). Fig. 2a, bAxial T2-weighted turbo spin echo fat suppressed images. Disappearing cyst at the lateral femoral condyle (arrow). a At baseline, b after 2 years Cystic and BME lesions were both present in the same anatomic location (associated lesions) in 191 cases. A change of BME lesions or cystic lesions was associated with a change in size of an adjacent cystic or BME lesion (OR: 6.2; 95% CI: 3.2–12.3). In 47 cases both BME lesions and cystic lesions changed. When cystic and BME lesions were both present in the same anatomic location, size changes (increase or decrease) were in same direction (OR: 37; 95% CI: 6–210) (Table 2). One hundred and fifty-seven (86%) patients completed a WOMAC questionnaire of the imaged knee at 2 years. The WOMAC pain and function scores for patients without and with BME lesions over 2 years are shown in Fig. 3a and b, respectively. The mean WOMAC scores did not differ between the different patient groups; even when BME lesions completely disappeared, lower WOMAC scores were not recorded. The mean difference in WOMAC pain scores between patients with unchanged BME lesions, with increasing BME lesions and with decreasing BME lesions compared with patients without BME lesions were 2 (95% CI-8 to 12), 2 (95% CI-8 to 11) and 1 (95% CI-11 to 12) respectively (Fig. 3a). The mean difference in WOMAC function scores between patients with unchanged BME lesions, with increasing BME lesions and with decreasing BME lesions compared to patients without BME lesions were −2 (95CI-12 to 8), −4 (95CI-13 to 6) and −4 (95CI-15 to 8) respectively (Fig. 3b). Fig. 3Association between WOMAC pain (a) or function (b) scores and bone marrow edema-like lesions. Group A: patients with no bone marrow edema-like lesions; Group B: patients in whom bone marrow edema-like lesions did not change over 2 years; Group C: patients in whom bone marrow edema-like lesions increased in size over 2 years; Group D: patients in whom bone marrow edema-like lesions decreased in size over 2 years. Box plots show the median, interquartile range, minimum and maximum values Discussion The majority (75%) of patients with familial OA at multiple sites have BME lesions visualized when two sequential MR scans are made with a 2-year time interval. In the majority (66%) of these patients with BME lesions, the total size of BME changed over this 2-year time period. Our study also demonstrates that cysts and BME fluctuations are associated. However, no association existed between changes in BME lesions and severity of WOMAC scores after 2 years. The finding, that BME lesions fluctuate in 66% of the patients, indicates that BME is part of a dynamic process in OA. BME is not a constant finding, as opposed to hyaline cartilage loss for example. Thus, it is important to realize that the finding of BME lesions in patients with OA represents only a single snapshot in time. The variability of BME lesions has been noted before [5]. It is also interesting and important to note that 10% of BME lesions disappear completely. This is particularly noteworthy if BME is to be used as an inclusion criterion, outcome parameter or surrogate endpoint in drug trials or clinical outcome studies. The second finding of the present study is that when cystic lesions and BME lesions are in close proximity; the direction in which they change is identical. This is an interesting finding as the role of cysts in OA is unclear. Their exact pathophysiology is uncertain, as is their prognostic significance. A recent study by Carrino et al. [13] also showed a change in cyst size was accompanied by a change in oedema-like signal size. That study also showed subchondral cysts developing in pre-existing regions of subchondral bone marrow oedema-like signal. The third finding is that changes in BME lesions did not correlate with severity of WOMAC scores. Patients in whom BME increased did not have a higher WOMAC score than patients with a decrease in BME size. Even when BME completely disappeared, lower WOMAC scores were not recorded. Previous work has demonstrated that pain, as assessed by WOMAC scores, was not related significantly to changes in BME lesions [5]. However, in the studies by Felson et al. [2, 7], BME was associated with progressive radiographic knee OA and pain. Cross sectional associations between BME lesions and clinical findings remain controversial [2–6]. Hence, a lack of clarity about the relationship between changes in BME lesions and WOMAC scores is not surprising. Phan et al. [5] have suggested that the complexity of pain physiology and the difficulty of pain evaluation may explain these findings, as well as the fact that patients experience pain differently. Another important factor might be the stage of OA in the patients being studied. For instance, pain might be associated with BME lesions in a more developed stage of the disease and less so earlier on. Knee OA studied in the population by Felson [2] was more advanced than the GARP population [8]. Also Felson’s population consisted of patients with knee OA only, whereas the GARP population is focused on patients with familial OA at multiple sites. A considerable proportion of patients in the present study did not have symptomatic radiographic knee OA in the imaged knee, and consequently average WOMAC scores in the present population were low (Table 1). Nevertheless, associations between BME lesions and clinical findings are controversial and BME lesions may be excluded ultimately as a factor in pain sensation. The present study has a number of limitations. Firstly, not all patients with a complete MRI follow-up completed the WOMAC signal knee. Secondly, the inclusion of patients who were first-degree relatives may have introduced an artefact. However, linear regression analysis, with robust standard errors that clustered on pairs, excluded this possibility. Thirdly, although referred pain from the hip may have been a confounder, hip OA occurred in only 7% of the patients and was not thought a contributory factor. Fourthly, 2 years of follow-up may be too short for an early OA population. However, we did find a considerable change in size of both cystic and BME lesions. Finally, the term BME used in this article probably should be described more properly as “ill defined signal intensity abnormalities”, as the so-called BME pattern in OA knees represents on histological examination nonspecific abnormalities such as bone marrow necrosis, bone marrow fibrosis, trabecular abnormalities and only a small amount of bone marrow oedema [1]. Nevertheless, the term BME is a commonly accepted identity and widely used in the OA literature [2]. In conclusion, BME lesions are shown to be a variable parameter when followed over time in patients with knee OA and are not predictive of pain.

Ann_Surg_Oncol-4-1-2277451

Does Practice Make Perfect?

Extensive literature supports the correlation between surgical volume and improved clinical outcome in the management of various cancers. It is this evidence that has catalysed the creation of centres of excellence. However, on closer inspection, many of these studies are poor quality, low weight and use vastly heterogenous end points in assessment of both volume and outcome. We critically appraise the English language literature published over the last ten years pertaining to the volume outcome relationship in the context of cancer care. Future balanced unbiased studies may enable equipoise in planning international cancer management strategies. No longer is there room for eminence-based complacency or misguided arrogance in healthcare delivery. The day of the autonomous clinician is gone with a vogue towards standardised, evidence-based clinical excellence. Cynics would erroneously attribute this to a parallel increase in litigation but increasing patient knowledge and expectations with a move toward subspecialisation are the main catalysts driving change. When offered operative intervention, the question frequently asked by the patient is “How many of these have you done before?” This article aims to critically analyse recent literature and explore the correlation between volume and clinical outcome in the context of cancer care. Background Mortality rates are reported to be influenced by the number of particular operations performed in a given hospital or by a specific surgeon (i.e. outcomes are better in high-volume centres). In 1999, the US National Cancer Policy Board recommended that patients requiring complex procedures be transferred from low- to high-volume hospitals in its report entitled “Ensuring Quality Cancer Care”.1 The following year, the Institute of Medicine held a workshop to discuss cancer care, publishing a document (“Interpreting the Volume-Outcome Relationship in the Context of Cancer Care”2) which concluded that existing evidence was strong enough to recommend the regionalisation of high-risk operations. Hence, the impact of volume on outcome has been assessed in several tumour types but the majority of data relates to gastrointestinal, hepatobiliary, urological, and breast cancers. The literature Patients undergoing pancreatic and oesophageal procedures have lower operative mortality and shorter hospital stay in the hands of experienced surgeons in high-volume units.3 With regard to gastric cancer, the findings are less consistent. Some suggest that high-volume centres have lower in-house mortality4 but no change in long-term survival.5 Various end points have been examined in colorectal cancer (Table 1). Schrang and Billingsley both showed that it was surgeon-specific experience combined with multidisciplinary support rather than centre experience that afforded significant survival advantage.6,7Table 1.Colorectal cancer outcome: high- and low-volume unitsHigh volumeLow volumeRef.APR versus LAR↓ APR↑ APRMeyerhardt et al. 19↑ LAR↓ LARSphincter preservation↑ ↑↓Purves et al.2030-day postoperative mortality↔↔Schrag et al.21Survival (overall and cancer specific)↑↓Schrag et al.21Permanent stoma formation↓↑McGrath et al.22Colonic pouch formation↑↓McGrath et al.22APR, abdominoperineal resection; LAR, low anterior resection.↑ increased, ↓ decreased, ↔ no variation. Comprehensive albeit retrospective studies unequivocally state that patients who undergo radical prostatectomy at lower-volume institutions are at significant risk of requiring adjuvant therapy due to adverse surgical factors, prolonged hospital admission, increased hospital charges and postoperative complications.8 The hospital structure of high-volume units, including easy availability of consultative, diagnostic and ancillary services, were cited as likely contributors to the association between procedure volume and short-term cystectomy outcomes.9 A minimum case load of only 11 radical cystectomies per year was cited to be associated with the lowest mortality rate.10 Less certainty exists in relation to breast cancer but a variety of end points have been examined, including number of visits required to obtain a nonoperative diagnosis, mastectomy rates for <15 mm tumours and rate of referral for adjuvant radiotherapy.11 Skinner et al. were adamant that volume alone could not be used as a surrogate for expertise but, like most studies, conceded that patients with breast cancer operated on in high-volume units compared to very low-volume units had better survival. However there is ambiguity surrounding the exact causal relationship: volume effect alone versus surgical skill versus appropriate use of adjuvant therapy.12 The Flaws The majority of studies are poor quality, heterogenous and potentially flawed. Even the best literature stems from retrospective review of large databases which are up to 40% inaccurate13 and pertain to selected patient groups. Most papers are published from a few very high-volume US centres, thus introducing immediate potential for bias. No consistent end point is used and, incredibly, few studies explore cancer-specific outcomes. Mortality rates, when not corrected for comorbidities or stage at diagnosis, are poor surrogates for more robust comparators of volume–outcome analysis such as cancer-specific survival, patient satisfaction and quality of life. American data cannot be used as a basis for the formation of European cancer strategies because so many inherent differences exist. These include earlier disease stage at time of operation (a function of screening),14 wide variance in population15 and socioeconomic status16 as well as insured versus noninsured outcomes.17 Comparison of very high-volume centres and very low-volume centres is as redundant as measuring revenue from a supermarket versus a corner store. Is it not intuitive that analysis of such extremes will yield vastly different results? Looking at the structure–process–outcome model, structure is relatively fixed (health service, institution) but process is entirely variable and volume is but one component of it. Therefore, in the absence of multivariable data, subgroup analysis is entirely inappropriate, rendering the aforementioned studies at best biased, at worst invalid. The Surgeon To identify procedure volume in a single institution is easy but not so for quantifying specific operations done by a single surgeon, many of whom practise in several centres. Without asking individuals to record caseload prospectively, obtaining accurate figures may be very difficult. Surely significant bias could occur in that those willing to share details of operations may be confident of their own justification in performing such procedures. Furthermore, who counts as more experienced: a mature surgeon who has performed two colonic resections a week for 20 years but now does only two a month or a younger, specialist trained surgeon who performs three a week? How do you weight lifetime experience against current volume? Should a centralised database of surgeons’ logbooks exist, and should permission to operate be granted or denied based on this? What governing body should be afforded such a task? Should operating surgeons be ranked in their ability or would this border on defamation for the less fortunate ones? Regarding referral pattern, does volume attract quantity or do excellent clinicians attract patients? Many studies have compared the significance of surgeon experience to unit volume with varied conclusions as to which has more impact. Do excellent surgeons naturally aggregate in excellent high-volume units, thus giving a self-propagating explanation for improved outcome? The Institution Many papers allude to the importance of the multidisciplinary approach in cancer care. Higher-volume units are far more likely to have subspecialised radiologists, radiation and medical oncologists, high dependency and intensive care units, cancer specialist nurses, dedicated psychologists and palliative care support. Anecdotally, the involvement of such services translates into better patient outcome regardless of unit volume, thus confounding results. The resounding evidence in favour of the volume–outcome relationship pertains to those cancers requiring adjuvant therapy: oesophagus, pancreas and advanced colorectal. It seems, therefore, that good surgical technique or individual surgeon experience do not exclusively guarantee positive outcomes and that much depends on availability of radiation and medical oncology. More often than not, within a short period of the introduction of a new service, its resources are saturated. At what point does a dedicated unit declare that available services can no longer provide for patient throughput? The worry is that potential exists for patients to receive suboptimal care just before this saturation point is reached (Fig. 1). Surely stretched resources in a high-volume centre are just as dangerous as absence of resources in smaller institution. A study on the difference in time lapse between diagnosis and intervention between institutions with different volumes would be welcome. Would prognosis be improved if a patient with aggressive disease underwent early intervention at a lower-volume centre rather than late intervention at a higher-volume centre? As cancer management is a dynamic process, the question of safety in transferring postoperative follow-up of a patient operated on in a high-volume unit to a less experienced lower-volume local centre is a pertinent one. On the other hand, should surgery be performed in low-volume units and adjuvant therapies in specialist centres? Without a doubt, the idea of hospital units functioning as a syncitium rather than single buildings must be engendered and skill-appropriate tasks assigned to each component, as recommended in breast cancer management by the Clinical Oncology Information Network (COIN) group.18Fig. 1.Volume–outcome relationship. The Patient Quality of life and patient satisfaction, apart from in colorectal and prostate cancers, are largely ignored when assessing impact of volume on clinical outcome. Is it preferential for elderly patients to travel long distances for management of a low-grade tumour or would they be better served by treatment in a lower-volume local centre where follow-up will be on their doorstep? Decisions like this are made on a daily basis in the context of primary care and so this begs the question of higher-volume specialist centres receiving selected patient cohorts, thus falsely improving outcome. This is confirmed by Morris et al. who showed that patients treated in the Australian private sector were likely to be younger, male and to have an earlier disease stage.17 The Future The literature supports a correlation between surgical volume and improved clinical outcome in cancer care. However, a rather simplistic approach is evident in many studies and much potential remains for unbiased, prospective, statistically sound investigations with the aim of numerically stratifying appropriate volume and its impact on disease specific cancer outcomes. While traditionally graph 1 in Fig. 1 has been used to represent the volume–outcome relationship, it seems probable that it is more accurately represented by graph 2 in Fig. 1, and can be interpreted as an area under a curve rather than a strictly linear relationship.

Pflugers_Arch-3-1-1915585

The endothelial glycocalyx: composition, functions, and visualization

This review aims at presenting state-of-the-art knowledge on the composition and functions of the endothelial glycocalyx. The endothelial glycocalyx is a network of membrane-bound proteoglycans and glycoproteins, covering the endothelium luminally. Both endothelium- and plasma-derived soluble molecules integrate into this mesh. Over the past decade, insight has been gained into the role of the glycocalyx in vascular physiology and pathology, including mechanotransduction, hemostasis, signaling, and blood cell–vessel wall interactions. The contribution of the glycocalyx to diabetes, ischemia/reperfusion, and atherosclerosis is also reviewed. Experimental data from the micro- and macrocirculation alludes at a vasculoprotective role for the glycocalyx. Assessing this possible role of the endothelial glycocalyx requires reliable visualization of this delicate layer, which is a great challenge. An overview is given of the various ways in which the endothelial glycocalyx has been visualized up to now, including first data from two-photon microscopic imaging. Introduction The endothelial glycocalyx was already visualized some 40 years ago by Luft using electron microscopy [66]. Still, relatively little is known of the composition and function of this layer. Over the past decades, it has been increasingly appreciated as an important factor in vascular physiology and pathology, as described in 2000 in a review by Pries et al. [86] and in other, more recent reviews [4, 74]. The interest in the (patho)physiological role of the glycocalyx started with the observation of low and variable capillary tube hematocrit, which depended on the level of metabolic and pharmacological activation of the vascular system [51, 52, 63, 83, 101]. The relation between metabolic and agonist-induced increases in red blood cell velocity on the one hand and tube hematocrit on the other could partly be explained by plasma skimming as direct continuation of the Fåhraeus effect [83]. However, this relation dissociated upon local treatment of the microvessels with heparinase, an enzyme which breaks down heparan sulfates in the glycocalyx [17]. This finding was in agreement with theoretical estimates predicting a 1.2-μm thick slow-moving plasma layer over the endothelium [51]. In vivo studies have revealed the glycocalyx in muscle capillaries to be a layer of about 0.5 μm thick, covering endothelial cells and determining luminal domains for macromolecules, red and white blood cells [129]. More recent studies indicate that glycocalyx thickness increases with vascular diameter, at least in the arterial system, ranging from 2 to 3 μm in small arteries [125] to 4.5 μm in carotid arteries [67]. To date, many studies indicate a variety of (patho)physiological roles for the endothelial glycocalyx; in addition to modulating capillary red blood cell filling, the glycocalyx may affect many other (dys)functions of the vascular system. Whereas the vascular endothelium is currently believed to be actively involved “in every pathology presenting vascular projections” [28], the same saying might well prove true for the glycocalyx. Assessing this possible involvement of the endothelial glycocalyx requires reliable visualization of this delicate layer, which is a great challenge. This review provides basic insight into the present knowledge of composition and functions of the endothelial glycocalyx and gives an overview of the various ways in which it has been visualized up to now. Composition The endothelial glycocalyx is a carbohydrate-rich layer lining the vascular endothelium. It is considered to be connected to the endothelium through several “backbone” molecules, mainly proteoglycans and also glycoproteins. These form a network in which soluble molecules, either plasma- or endothelium-derived, are incorporated. More luminally, the glycocalyx is formed by soluble plasma components, linked to each other in a direct way or via soluble proteoglycans and/or glycosaminoglycans (which will be discussed below). A dynamic equilibrium exists between this layer of soluble components and the flowing blood, continuously affecting composition and thickness of the glycocalyx. Furthermore, the glycocalyx suffers from enzymatic or shear-induced shedding. The dynamic balance between biosynthesis and shedding makes it hard to define the glycocalyx geometrically [62]. The composition of the membrane-bound mesh of proteoglycans, glycoproteins, and glycosaminoglycans and the composition of associated plasma proteins and soluble glycosaminoglycans cannot be viewed as a static picture. Instead, the layer as a whole—also known as endothelial surface layer (ESL) [86]—is very dynamic, with membrane-bound molecules being constantly replaced and no distinct boundary between locally synthesized and associated elements; membrane-bound hyaluronan may reach lengths of >1 μm. Direct visualization techniques (see section on Visualization techniques) fail to demonstrate clear compositional differences within the glycocalyx, from endothelial membrane towards vascular lumen, but rather indicate that the endothelial glycocalyx resembles an intricate, self-assembling 3D mesh of various polysaccharides. Enzymatic removal of any of its constituents dramatically affects glycocalyx properties, which exemplifies the importance of considering the synergetic interaction of all glycocalyx constituents as a whole. In this review we will, therefore, use the term (endothelial) glycocalyx for the total layer (Fig. 1) and be as specific as possible when addressing its various elements. Fig. 1Schematic representation of the endothelial glycocalyx, showing its main components. Left: The endothelial glycocalyx can be observed in vivo as a red blood cell exclusion zone, located on the luminal side of the vascular endothelium. It consists of membrane-bound and soluble molecules. Right: Components of the endothelial glycocalyx. Bound to the endothelial membrane are proteoglycans, with long unbranched glycosaminoglycan side-chains (GAG-chain) and glycoproteins, with short branched carbohydrate side-chains. Incorporated in and on top of this grid are plasma and endothelium-derived soluble components, including hyaluronic acid and other soluble proteoglycans (e.g., thrombomodulin) and various proteins, such as extracellular superoxide dismutase (ec-SOD) and antithrombin III (AT III). Together, these components form the endothelial glycocalyx that functions as a barrier between blood plasma and the endothelium and exerts various roles in plasma and vessel wall homeostasis. Note that this figure is not drawn to scale; its purpose is to illustrate glycocalyx composition Below, state-of-the-art knowledge on the various components of the endothelial glycocalyx will be provided. Although many molecules have been identified as being part of the glycocalyx, information on their distribution is still scarce; if present, such knowledge was mostly obtained indirectly and nonquantitatively. Proteoglycans Proteoglycans are generally considered to function as the most important “backbone” molecules of the glycocalyx. They consist of a core protein to which one or more glycosaminoglycan chains are linked. There is a notable variation among the proteoglycan core proteins with regard to their size, number of attached glycosaminoglycan chains, and whether or not they are bound to the cell membrane (Table 1). The core protein groups of syndecans (n = 4) and glypicans (n = 6) have a firm connection to the cell membrane via a membrane-spanning domain (syndecans) or a glycosylphosphatidylinositol anchor (glypicans) [12, 25]. The other proteoglycans, such as mimecan, perlecan, and biglycan, are secreted after their assembly and glycosaminoglycan chain modification [44, 50]. This leads to production of soluble proteoglycans, which reside in the glycocalyx or diffuse into the blood stream. Table 1Characteristics of proteoglycan core proteins in the vascular endothelial glycocalyxCore protein groupCore protein size (kDa)Number of subtypesNumber of GAG-chains linkedType of GAG-chains linkedStructural relation to cell membraneSyndecan19–3545HS/CSMembrane-spanningGlypican57–6963HS/CSGPI-anchorPerlecan40013HS/CSSecretedVersican370110–30CS/DSSecretedDecorin4011CS/DSSecretedBiglycan4012CS/DSSecretedMimecan3512–3KSSecretedGAG Glycosaminoglycan, HS heparan sulfate, CS chondroitin sulfate, DS dermatan sulfate, KS keratan sulfate, GPI glycosylphosphatidylinositol Proteoglycans are promiscuous in their binding of glycosaminoglycan chains, meaning that one core protein can contain different types of glycosaminoglycan chains. The proportion of the various chains may change under different circumstances and stimuli [89]. Therefore, naming of proteoglycans after one type of glycosaminoglycan is somewhat deluding. For example, syndecan-1 proteoglycan is often addressed as a heparan sulfate proteoglycan, while in fact, it usually contains similar numbers of heparan sulfate and chondroitin sulfate chains [70]. There are five types of glycosaminoglycan chains: heparan sulfate, chondroitin sulfate, dermatan sulfate, keratan sulfate, and hyaluronan (or hyaluronic acid). They are linear polymers of disaccharides with variable lengths that are modified by sulfation and/or (de)acetylation to a variable extent. The disaccharides are each composed of a uronic acid and a hexosamine; classification of the glycosaminoglycans depends on which uronic acid or hexosamine is incorporated and on the pattern of sulfation (Table 2). Each of the five glycosaminoglycans has been investigated and reviewed extensively [22, 27, 57, 58, 114]. Dermatan sulfate is often regarded as a separate class of glycosaminoglycans, although it actually is type B chondroitin sulfate. The difference between the two is possible epimerization of the glucuronic acids into iduronic acids in dermatan sulfate, which has important consequences for functionality. Whenever possible, we will try to separate the two as precisely as possible; elsewhere, they will be referred to as chondroitin sulfate/dermatan sulfate. Table 2Composition of the disaccharides of various glycosaminoglycan chains Heparan sulfateChondroitin sulfateDermatan sulfateaHyaluronanKeratan sulfateUronic acidGlcA(2S) IdoA(2S)GlcAGlcA IdoA(2S)GlcAGal(6S)Disaccharide link1β41β31β31β31β4HexosamineGlcNAc(NS)(3S)(6S)GalNAc4Sa GalNAc6SaGalNAc(4S)(6S)GlcNAcGlcNAc(6S)Polymerization link1β41β41β41β41β3Note the various possibilities of sulfation in heparan sulfate. These may coincide (e.g., in heparan sulfate the hexosamine GlcNS3S). A rare but possible hexosamine in heparan sulfate is the N-unsubstituted glucosamine which has been left out of the table for convenient reading. Also note the presence of IdoA in dermatan sulfate, in contrast to the other chondroitin sulfates, making it more alike to heparan sulfate.GlcA Glucuronic acid, IdoA iduronic acid, Gal galacturonic acid, GlcNAc N-acetyl-glucosamine, GalNAc N-acetyl-galactosamine, 2S 2-O-sulfated, 3S 3-O-sulfated, 4S 4-O-sulfated, 6S 6-O-sulfated, NS N-sulfatedaThere are three types of chondroitin sulfate. Type A only has 4-O-sulfated N-acetyl-galactosamines, type B is known as dermatan sulfate and type C only has 6-O-sulfated N-acetyl-galactosamines. In vasculature, heparan sulfate proteoglycans represent roughly 50–90% of the total amount of proteoglycans present in the glycocalyx [43, 86]. However, this figure is variable, as the expression of proteoglycans by endothelial cells depends on various stimuli. Syndecans, for example, have a tightly regulated expression pattern which varies with endothelial cell activation or stimulation with different chemokines [119]. The second most common glycosaminoglycan in the endothelial cell glycocalyx is chondroitin sulfate/dermatan sulfate. The presence of heparan sulfate and chondroitin sulfate is reported to have a typical ratio of 4:1 for the vascular endothelium [70, 90]. Expression of keratan sulfate glycosaminoglycans in vasculature and its importance in (patho)physiology is less well understood. Another important glycosaminoglycan in the glycocalyx is hyaluronan. This long polymeric molecule (up to 104 kDa) differs from other glycosaminoglycans in that it is not linked to a core protein. Its exact link to the cell membrane is unknown, but it can be bound to the receptor CD44 [72]. Alternatively, hyaluronan may be attached to its assembly proteins, the hyaluronan synthases [135], which are located at the cytosolic side of the cell membrane. Another possibility is that hyaluronan is (in part) not directly bound to the membrane at all. It is capable of forming strikingly viscous solutions [57]. More recently, intracellular hyaluronan binding proteins such as cdc37 [31] and P32 [15] have been identified, suggesting a role for this glycosaminoglycan within the cell [23, 58]. Heparan sulfate and chondroitin sulfate/dermatan sulfate containing proteoglycans are produced in the endoplasmic reticulum and Golgi apparatus of the endothelial cell. After the ribosomal translation of the core protein, a xylosyltransferase will transfer xylose (Xyl) from uracildiphosphate xylose to specific serine residues (Ser) in the core protein. The xylose-enriched core protein is transported to the cis-Golgi, and galactosyltransferases types I and II will add two galactose-groups (Gal) to the xylose, after which glucuronosyltransferase type I adds glucuronic acid, thus, completing the primary linker for glycosaminoglycan chains: –GlcA–β3–Gal–β3–Gal–β4–Xylβ3–[Ser]. After formation of the primary linker, the following step determines the type of glycosaminoglycan chain that will be formed. In the case of heparan sulfate, an α4-glucosamine is added; in the case of chondroitin sulfate and dermatan sulfate, a β4-galactosamine is added, and both galactose-residues from the linker may be sulfated. From this point onward, glucuronic acids and glucosamines are linked to the core protein. After chain polymerization, the growing glycosaminoglycan chain will undergo modifications including N-sulfation, O-sulfation, and epimerization. The latter changes glucuronic acid residues into iduronic acid residues and will change any chondroitin sulfate chain into its type B dermatan sulfate. These chain modifications take place in both the cis- and the trans-Golgi, determining the final type and functionality of the proteoglycan and each of its side chains. In contrast, hyaluronan is assembled at the cytosolic side of the cell membrane, and it is not modified afterwards. As a consequence, it has no sulfate groups or modification pattern. As glycosaminoglycan chains contain numerous specific binding sites for plasma-derived proteins, small chain modifications can have great functional consequences. Sequential enzymatic modifications of the individual saccharide units within glycosaminoglycan chains endow proteoglycans with unique functions. Typically 16–48 different sulfation patterns may exist per disaccharide and as functional domains are assumed to be usually penta- to deca-saccharide long, at least 163 = 4,096 different sulfation patterns on a hexasaccharide backbone are theoretically possible, and such a structural diversity corresponds to diversified biological functions of glycosaminoglycans. Indeed, it has been shown that modification patterns vary in time and under different (patho)physiological stimuli [4, 131]. The diversity of glycosaminoglycan sulfation patterns and its effect on specific protein binding and modulation of protein function suggest that conditions that diminish glycocalyx thickness or modulate protein specific glycosaminoglycan sulfation patterns and charge are likely to modulate vascular permeability and alter specific protein binding and activity. Glycoproteins Besides the proteoglycans with their long linear side chains, certain glycoproteins are also regarded as “backbone” molecules, connecting the glycocalyx to the endothelial cell membrane. This group of endothelial glycoproteins, characterized by relatively small (2–15 sugar residues) and branched carbohydrate side chains, comprises a number of molecules that all have been studied intensively; major classes that will be discussed in more detail below are the endothelial cell adhesion molecules and components of the coagulation and fibrinolysis system. It is beyond the scope of this review to categorically discuss all glycoproteins that can be expressed by endothelial cells. Furthermore, one should realize that the level of glycoprotein expression on the endothelial cell membrane varies considerably with cell activation or stimulation. The endothelial cell adhesion molecules are well-defined glycoproteins that play a major role in cell recruitment from the bloodstream and in cell signaling. The three families of cell adhesion molecules present in the endothelial glycocalyx are the selectin family, the integrin family, and the immunoglobulin superfamily. Glycoproteins from the selectin family contain a cytoplasmic tail, a transmembrane domain, several consensus repeats, an epidermal growth factor-like domain, and a terminal lectin domain, which is primarily responsible for binding of carbohydrate groups on glycosylated proteins or lipids. However, the epidermal growth factor-like domain is involved in selectin-ligand recognition as well [29, 48]. Selectins found on the vascular endothelium are E-selectin and P-selectin, both involved in leukocyte–endothelial cell interactions [108]. P-selectin is constitutively produced and subsequently stored in the Weibel–Palade bodies of the endothelial cells. Exocytosis of Weibel–Palade bodies as induced by stimuli such as thrombin and histamine allows a rapid translocation of P-selectin to the cell surface [19, 53]. However, this expression is short-lived due to P-selectin internalization and redirection to lysosomal granules or the Golgi apparatus, where it is restored in newly formed Weibel–Palade bodies [109]. E-selectin is not stored in granules, but requires de novo mRNA and protein synthesis to be expressed on the cell surface. Stimulation of endothelial cells by cytokines such as interleukin-1, tumor necrosis factor α, and lipopolysaccharide upregulates E-selectin expression; this typically requires 2–6 h [47]. In some tissues like the skin, P- and E-selectin appear to be constitutively expressed on endothelial cells [78, 139]. Integrins are heterodimeric molecules, composed of non-covalently bound α and β subunits. Both subunits have a cytoplasmic tail and a transmembrane domain, and together, they constitute an integral membrane protein. To date, 18 different α-subunits and 8 β-subunits have been identified, which means that each integrin is characterized by the specific combination of its subunits [142]. Integrins are found on many cell types, including endothelial cells, leukocytes, and platelets. In their luminal membrane, endothelial cells express integrin αVβ3, which is an important mediator of platelet–endothelial cell interactions [11]. Most other endothelial cell integrins are involved in binding to the basement membrane. These integrins, such as α2β1, α5β1, and α6β1, bind to multiple extracellular matrix ligands, and are as such, responsible for interactions with laminin, fibronectin, and collagen. Many studies have focused and still focus on the interactions between these integrins and the subendothelial matrix during angiogenesis [98]. The immunoglobulin superfamily of glycoproteins is characterized by a cytoplasmic tail, a transmembrane domain, and a variable number of immunoglobulin-like domains that protrude luminally. Best known examples are intercellular adhesion molecule 1 and 2 (ICAM-1 and -2), vascular cell adhesion molecule 1 (VCAM-1), and platelet/endothelial cell adhesion molecule 1 (PECAM-1), which act as ligand for integrins on leukocytes and platelets and are crucial mediators of leukocyte homing to the endothelium and subsequent diapedesis. ICAM-1 and -2 and PECAM-1 have a baseline expression, whereas VCAM-1 is only present after endothelial cell stimulation by cytokines, which also upregulates ICAM-1 expression [71]. Paradoxically, the constitutive expression of PECAM-1 is decreased after cytokine treatment [113]. The role of ICAM-2 in inflammation is still unclear, as it is also downregulated by inflammatory stimuli. Recently, it was shown that ICAM-2 is involved in regulation of angiogenesis [41]. Besides the cell adhesion molecules, the endothelial glycocalyx harbors glycoproteins with functionality in coagulation, fibrinolysis, and hemostasis. A good example is the glycoprotein Ib-IX–V complex, which is expressed on endothelial cells and also on platelets. It consists of four glycoproteins: Ibα, Ibβ, IX, and V, that are each membrane-spanning polypeptides. Glycoprotein Ibα and Ibβ are covalently linked via a disulfide group, whereas IX and V are non-covalently attached to the Ib heterodimer. The Ib-IX–V complex binds von Willebrand factor (vWf) and is primarily known as the platelet vWf-receptor [65, 99]. Furthermore, the complex also binds P-selectin, mediating the interaction of platelets with activated endothelial cells [7]. Like platelets, endothelial cells express all components of the Ib-IX–V complex [115, 141], which on one hand, allows binding to the vWf substrate of the subendothelium, and on the other, binds Weibel–Palade body derived vWf, secreted luminally by activated endothelial cells. Soluble components Embedded within and layered on top of the mesh of proteoglycans and glycoproteins are soluble components of various types such as proteins and soluble proteoglycans. These components are either derived from the endothelium or from the bloodstream, such as albumin and orosomucoid, which are pivotal in preserving the (charge-)selectivity of the permeability barrier [42]. The soluble components of the glycocalyx contribute greatly to the functional importance of the glycocalyx, as will be described below. The structural attribution of these soluble components is less well established. At least some of the soluble components may contribute to the structural organization of the luminal glycocalyx, although this is hard to prove. There are indications that proteoglycans bind to each other and to proteins [54, 88]. Protein–glycosaminoglycan–protein complexes have been identified, although not in the glycocalyx in particular [145]. Still, it is presumable that interactions between membrane-bound proteoglycans, soluble proteins, and soluble proteoglycans create a cross-linked mesh and provide some stability to the luminal glycocalyx. Hyaluronan might play an important role in this respect, being a very large linear molecule and possibly unbound to the endothelial cell membrane (Fig. 1). It has been shown to interact with itself, forming stable hyaluronan–hyaluronan complexes [103, 104]. Still, the glycocalyx is a delicate layer, and removal of one specific component may result in loss of function of the total [117]. Functional importance The endothelial glycocalyx as the endothelial gatekeeper Located between the blood stream and the endothelium, the endothelial glycocalyx is an important determinant of vascular permeability [35, 130]. It is able to limit access of certain molecules to the endothelial cell membrane, as has been demonstrated in small rat mesenteric arteries with the use of fluorescently labeled dextrans of various molecular weights, showing increasing permeability for smaller molecules [125]. Enzymatic (partial) removal and subsequent loss of permeability barrier function of the glycocalyx in rat myocardial capillaries leads to myocardial edema [124]. Not only size and steric hindrance play a role in glycocalyx dependent permeability, but also, electrostatic charges of the glycocalyx and the permeating substance. With many of the glycosaminoglycan chains being highly sulfated, the glycocalyx presents a net negatively charged surface to the bloodstream. Accordingly, neutralization of the glycocalyx induces an increase in albumin uptake by cultured endothelial cells [121] and an increased permeability for fluorescently labeled dextrans in rat mesenteric arteries [126]. The classical model used to describe microvascular fluid exchange is that of Starling [112], stating that fluid filtration rate across capillary endothelium is determined by the hydraulic and colloid osmotic pressures in the vascular lumen and in the surrounding tissue. This balance has been applied across the entire transendothelial barrier, with the different pressures being assessed globally. The discovery of a relatively thick endothelial glycocalyx and its influence on, e.g., edema formation has led to a major revision of the Starling principle by Weinbaum [137] and Michel [68], who proposed to apply the pressure gradients to the endothelial glycocalyx only. Hu and Weinbaum used this idea to generate a 3-D model of permeability over different regions of the endothelial layer, such as the glycocalyx, the endothelial clefts, and the tight junctions [40]. Recently, this model was simplified into a 1-D description of the varying tissue concentration gradients and subsequent permeability of the endothelium [144]. Another model, known as the glycocalyx-junction-break model, applies the Starling mechanism over the glycocalyx and describes its effects on solute and water transport over the endothelium, based on theoretical “pores” in the endothelium [79]. Recently, Curry has written a review on this model and the influences of phenotypical changes on microvascular permeability [14]. The importance of the endothelial glycocalyx in controlling extravasation of colloids and fluids is also stressed by studies of Rehm et al. [91] and Jacob et al. [45], who show impaired endothelial barrier function after glycocalyx degradation in an isolated, perfused heart model. Infusion of 5% albumin or 6% hydroxethyl starch, a natural and an artificial colloid, led to decreased fluid extravasation. However, after 20 mins of warm ischemia, only albumin infusion prevented vascular leakage. This underscores the importance of an intact glycocalyx and the role of plasma-derived proteins for competent glycocalyx functioning. The revised Starling principle has provided more detailed insight into vascular permeability and stresses the importance of the endothelial glycocalyx as a major determinant. Besides its capacity to restrict molecules from reaching the endothelium, the glycocalyx also influences blood cell–vessel wall interactions. It repulses red blood cells from the endothelium. In the microcirculation, a red blood cell exclusion zone flanking the endothelium can be observed in vivo, which is decreased upon light dye-induced breakdown of the glycocalyx [129]. Similarly, platelets are not often observed interacting with the endothelium in control conditions, whereas partial glycocalyx removal by infusion with oxidized low-density lipoprotein (ox-LDL) is accompanied by an increase in platelet–vessel wall interactions [128]. The role of the glycocalyx in leukocyte–vessel wall interactions seems dual: on the one hand, it harbors the endothelial cell adhesion molecules, such as P-selectin, ICAM-1, and VCAM-1; on the other hand, it attenuates adhesion of leukocytes to these molecules. In healthy mouse cremaster muscle venules, breakdown of heparan sulfate side chains through heparitinase leads to an increase in leukocyte adhesion to the endothelium in a dose-dependent manner [13]. Administration of ox-LDL or TNFα also induces leukocyte rolling and adhesion [13, 36]. Steric hindrance seems to play a role in this process. The endothelial glycocalyx is much thicker (ranging from 0.2–0.5 μm in capillaries [124] to 2–3 μm in small arteries [125] and 4.5 μm in carotid arteries [67]) than the length of the various cell adhesion molecules. P-selectin, for example, the molecule initiating leukocyte rolling, only extends about 38 nm from the endothelial surface [111]. On cultured cells transfected with P-selectin constructs with two to six consensus repeats that are consequently shorter than normal P-selectin (nine consensus repeats), the number of attaching neutrophils decreased with decreasing P-selectin length. Cells defective of glycosylation, having a thinner glycocalyx, showed increased attachment of neutrophils [81]. Hence, in normal conditions, the glycosaminoglycan chains and soluble components of the glycocalyx seem to shield adhesion molecules, thereby, preventing interaction. Stimuli which degrade the glycocalyx or induce a more open mesh, such as enzymes, cytokines, or ischemia and reperfusion, appear to uncover the adhesion molecules, which in turn, allows blood cells to interact with the endothelium [13, 36, 70, 128]. One should realize that ligands for endothelial adhesion molecules are not uniformly distributed over the cell membrane of leukocytes, but show association with microvilli and membrane ruffles [102]. As the glycocalyx is estimated to have a low stiffness [33, 106, 138], it is likely that the ligand bearing leukocyte membrane extensions protrude relatively easily into the glycocalyx to reach their receptor and enable leukocyte–vessel wall interaction. In contrast to other tissues, leukocyte–vessel wall interactions occur spontaneously in venules in the skin, even in normal conditions without preceding trauma or inflammation [46, 78]. Whether this is associated with a deviating glycocalyx structure and/or composition in skin microvessels remains to be elucidated. The presence of a relatively thick endothelial glycocalyx in vivo has great consequences for rheology, especially in the microvasculature [62, 84]. In this part of the circulation, local blood viscosity and hematocrit appear to be modulated by the glycocalyx. Using a physical model, based on hemodynamic and hematocrit measurements in microvascular networks in vivo, Pries and Secomb recently demonstrated that incorporation of realistic estimates of glycocalyx dimensions in reconstructed mesenteric microvascular networks introduces about a twofold increase in the apparent viscosity of blood. These changes are sufficient to minimize discrepancies between experimentally determined and theoretically predicted microvascular network resistances in previous studies, which were based on the apparent viscosity of blood in glycocalyx-devoid glass capillaries [85]. The endothelial glycocalyx as mechanotransducer The endothelium is exposed to mechanical forces induced by blood flow. It has long been recognized that these forces, in particular, shear stress, determine endothelial cell morphology and function [16, 18]. Endothelial cells exposed to shear stress produce nitric oxide (NO) [96], which is an important determinant of vascular tone. However, the molecule(s) responsible for the translation of biomechanical forces into biochemical signals (mechanotransduction) have not been identified as yet. Recently, the glycocalyx has been added to the list of possible candidates. In studies with cultured endothelial cells, Florian and colleagues [24] showed that treatment with heparitinase to specifically break down heparan sulfate glycosaminoglycans results in inadequate responses to shear variations and impaired NO production. Similarly, ex vivo experiments on canine femoral arteries conducted by Mochizuki and coworkers exhibited reduced shear-induced NO production after infusion with hyaluronidase, which degrades the hyaluronan glycosaminoglycans in the glycocalyx [69]. Thus, both heparan sulfate and hyaluronan appear to play a role in detecting and amplifying flow-induced shear forces [69]. Interestingly, exposure of human umbilical vein endothelial cells to shear stress was found to increase the amount of hyaluronan in the glycocalyx approximately twofold, which may represent a positive feedback for shear stress sensing by endothelial cells [30]. Another recent study showed a correlation between shear stress profile and glycocalyx dimensions in the mouse carotid artery; the laminar flow profiles in the common carotid were found to coincide with a glycocalyx thickness of 399 ± 174 nm, whereas disturbed laminar flow in the sinus region of the carotid bifurcation coincided with a thinner glycocalyx of 73 ± 36 nm [123]. Moreover, the flow divider region of the carotid bifurcation, supposedly having an undisturbed high laminar flow profile, was covered with a glycocalyx of 308 ± 185 nm, comparable to the common carotid glycocalyx thickness. From these data, it seems likely that the glycocalyx plays an important role in mechanotransduction and that its composition is, in turn (at least partly), shear-dependent. The different components of the glycocalyx probably operate together, which means that the glycocalyx, as a whole, is responsible for its role as mechanotransducer. This idea is confirmed by theoretical models based on a regular hexagonal distribution of core proteins over the endothelial cell membrane [138]. Recently, Tarbell and Pahakis reviewed the current concepts on mechanotransduction by the (membrane-bound) glycocalyx [116]. They conclude that the glycocalyx core proteins are responsible for transmission of shear stress signals into specific cell signaling processes, e.g., NO production and cytoskeletal reorganization. At the same time, shear stress is transmitted to other regions of the endothelial cell as well, such as intercellular junctions and basal adhesion plaques, which are responsible for additional shear sensing even in the absence of a glycocalyx. The endothelial glycocalyx as control center for the microenvironment The proteoglycans in the glycocalyx contribute greatly to its functional importance. The glycosaminoglycan chain variety arising from chain epimerization, elongation, and most notably, chain sulfation, gives rise to a heterogeneous surface to which a lot of plasma-derived molecules can dock. Table 3 lists a number of molecules, which depend on interaction with the glycocalyx for their functionality. Table 3Molecules dependent on interaction with the endothelial glycocalyx for proper functioningInteracting moleculePrimary function in vasculatureReference numberAntithrombin IIIPotent inactivator of pro-coagulant proteases such as thrombin, factor Xa and factor IXa; activity enhanced by heparin or heparan sulfate107Heparin cofactor IIInactivator of the procoagulant protease thrombin; activated by dermatan sulfate in the endothelial glycocalyx120TFPIAnticoagulant protein blocking activated factor VII and X38, 49LPLEnzyme involved in breakdown of low density lipoproteins133LDLTransports cholesterol and triglycerides through the circulation140VEGFPotent stimulator of angiogenesis, production of which is triggered by hypoxia92TGFβ1/2Growth factor known to mediate in a lot of signaling pathways, including smooth muscle cell differentiation and vascular tone and reactivity64FGF(r)Growth factor (receptor) involved in endothelial cell proliferation and angiogenesis3, 26Ec-SODExtracellular quencher of reactive oxygen species11IL 2, 3, 4, 5, 7, 8, 12, RANTESChemotaxis of leukocytes to the subendothelium; involved in arrest and diapedesis2, 39, 100, 110, 143TFPI Tissue factor pathway inhibitor, LPL lipoprotein lipase, LDL low density lipoprotein, VEGF vascular endothelial growth factor, TGFβ1/2 transforming growth factor β1 or β2, FGF(r) fibroblast growth factor (receptor), ec-SOD extracellular superoxide dismutase, IL interleukin, RANTES Regulated on Activation, Normal T Expressed and Secreted—also known as chemokine CCL5 Docking of plasma-derived molecules can influence the local environment in several ways: (1) Binding of receptors or enzymes and their ligands to the endothelial glycocalyx causes a localized rise in concentration of these substances, which enables proper signaling or enzymatic modification. Fibroblast growth factor (FGF) signaling is mediated in this way and is known to depend completely on the interaction of both ligand and receptor with the glycocalyx [3, 26]. Similarly, the glycocalyx is involved in the lipolytic system, binding both lipoprotein lipase and its ligand low-density lipoprotein (LDL) [133, 140]. (2) Binding of plasma-derived molecules to the glycocalyx can lead to a local concentration gradient, which is often seen in growth factor-regulated gene transcription and developmental processes [61, 82]. (3) Docking of enzymes and their agonists or inhibitors to the glycocalyx adds a vasculoprotective role to glycocalyx functionality. Several important anticoagulant mediators can bind to the glycocalyx, such as antithrombin III, heparin cofactor II, thrombomodulin, and tissue factor pathway inhibitor (TFPI). Antithrombin III is a strong inhibitor of procoagulant enzymes like thrombin and activated factors X and IX (FXa and FIXa) [87]. It is known to bind to specific regions in heparan sulfate, which enhances its anticoagulant activity [107]. Heparin cofactor II is a thrombin-specific protease inhibitor [80], which is activated by dermatan sulfate in the glycocalyx [120]. Thrombomodulin is a chondroitin sulfate containing protein expressed by endothelial cells and is able to convert thrombin from a procoagulant enzyme to an activator of the protein C pathway, thus, becoming anticoagulant [136]. TFPI is a potent inhibitor of FVIIa and FXa. TFPI is believed to bind to the glycocalyx via heparan sulfates, but other proteins could be involved as well [49]. Furthermore, uptake and degradation of TFPI–FXa complexes depends on heparan sulfates in the glycocalyx [38]. All these anticoagulant molecules present in the glycocalyx contribute to the thromboresistant nature of healthy endothelium [21]. The endothelial glycocalyx also modulates inflammatory responses by binding cytokines and attenuating binding of cytokines to cell surface receptors. Shedding of heparan sulfate from the glycocalyx results in increased endothelial cell sensitivity to activation by cytokines [9, 10]. Another aspect of the vasculoprotective role of the endothelial glycocalyx is its capacity to bind quenchers of oxygen radicals, such as extracellular superoxide dismutase (SOD) [59]. These enzymes help to reduce the oxidative stress and keep up NO bioavailability, thus, preventing the endothelium from becoming dysfunctional. The endothelial glycocalyx in pathophysiology In healthy vessels, the endothelial glycocalyx determines vascular permeability, attenuates blood cell–vessel wall interactions, mediates shear stress sensing, enables balanced signaling, and fulfills a vasculoprotective role. But when it is disrupted or modified, these properties are lost, as has been shown through direct targeting of the glycocalyx in experimental settings. In the last few years, evidence is emerging that (damage to) the glycocalyx plays a pivotal role in several vascular pathologies. Here, we will discuss its suspected roles in diabetes, ischemia/reperfusion, and atherosclerosis. Diabetes Diabetes is a clinically well-known disease with far-reaching complications, such as retino- and nephropathy, and elevated risks for atherothrombotic cardiovascular events. One of the hallmarks of diabetes is insulin absence or resistance and subsequent hyperglycemia, impairing the protective capacity of the vessel wall [73], and resulting in enhanced endothelial permeability [1] and impaired NO synthase function [20]. However, a common pathway leading to these vascular dysfunctions has not been identified. Recently, it was shown that the systemic glycocalyx volume of healthy volunteers, as assessed by comparing the intravascular distribution volume of a glycocalyx-permeable and a glycocalyx-impermeable tracer, was halved within 6 h after induction of acute hyperglycemia [76]. Using the same methodology, the systemic glycocalyx volume in type 1 diabetics was found to be about half of that of healthy controls; it was further reduced in diabetics with microalbuminuria [75]. In the same study, plasma levels of hyaluronan and hyaluronidase were found to be elevated in patients with diabetes, reflecting increased synthesis and shedding of hyaluronan under hyperglycemic conditions. Both studies show that acute and long-standing hyperglycemia is associated with profound reduction of glycocalyx dimensions. It is tempting to speculate that this damage to the glycocalyx contributes to endothelial dysfunction in hyperglycemic conditions, which can be measured in nondiabetic subjects as well [118]. Further studies are needed to investigate whether glycocalyx perturbation is responsible for the (micro)vascular complications in diabetes. Ischemia/reperfusion Damage to tissues during a period of absent or decreased flow (total or partial ischemia) can paradoxically be exaggerated by restoration of blood flow (reperfusion). Although the severity of damage resulting from ischemia/reperfusion varies between tissues, a common component of this pathologic process for all organs is microvascular dysfunction [32, 105]. Endothelial cells play a central role and exhibit swelling and detachment from the basement membrane after ischemia/reperfusion [77]. Especially in postcapillary venules, endothelial cells suffer from increased oxidative stress [56], leukocytes adhere and transmigrate [8, 132], and vascular permeability increases [55]. These endothelial consequences of ischemia/reperfusion allude at involvement of the endothelial glycocalyx. Indeed, it was recently shown by Mulivor and Lipowsky [70] that intestinal ischemia/reperfusion led to significant reduction of glycocalyx thickness in rat mesenteric venules, most likely due to shedding of glycosaminoglycan chains. The effects of ischemia/reperfusion on the glycocalyx could be attenuated by blockade of xanthine-oxidoreductase, which is an endogenous reactive oxygen species (ROS) producing enzyme bound to heparan sulfate domains in the glycocalyx. This way, a central role for ROS in disruption and shedding of the glycocalyx in ischemia/reperfusion was established [97]. Infusion of exogenous hyaluronan to restore the glycocalyx or administration of pertussis toxin, which inhibits G-protein-mediated shedding of glycosaminoglycan chains, also reduced ischemia-/reperfusion-induced damage [70]. Together, these data hint at a role for the endothelial glycocalyx in the pathophysiology of ischemia-/reperfusion-induced tissue damage. However, its relative contribution to this process and the impact of possible therapeutical interventions are yet to be established [6, 122, 134]. Atherosclerosis Atherosclerosis is a large artery disease and typically requires high plasma levels of LDL to develop at predilection sites [34] that are marked by disturbed flow profiles. Subendothelial retention of atherogenic lipoproteins and subsequent inflammatory responses lead to the formation of subendothelial plaques [60, 93]. The role of the endothelial glycocalyx in atherogenesis is, as yet, not well-established, but there are some interesting observations which point at its involvement. In 2000, Vink and colleagues [128] showed that administration of clinically relevant doses of ox-LDL leads to a disruption of the glycocalyx in hamster cremaster muscle microcirculation and evokes local platelet adhesion. Co-infusion with SOD and catalase, enzymes catalyzing the dismutation of superoxide anion and the decomposition of hydrogen peroxide, abolished this effect of ox-LDL, implicating a role for oxygen-derived free radicals. Indeed, loss of glycocalyx results in shedding of endogenous protective enzymes, such as extracellular SOD, and increases the oxidative stress on endothelial cells. This was further illustrated by a recent study by van den Berg et al. [123], showing a reduction in glycocalyx dimensions due to a high-fat, high-cholesterol diet. Furthermore, an inverse relation between glycocalyx thickness and intima–media ratio was found, reflecting a reduction of vasculoprotective capacity of the endothelial glycocalyx at sites with higher atherogenic risk. In healthy mice, regional variations were found showing a thinner glycocalyx in the internal carotid sinus region compared to the common carotid artery. Together, these data suggest that the endothelial glycocalyx is involved in the initiation and progression of the atherosclerotic process [74]. In summary, the endothelial glycocalyx appears to be perturbed in several vascular diseases. It remains to be elucidated whether glycocalyx perturbation is causally involved in the pathophysiology of these diseases. If so, restoration of the glycocalyx may be a therapeutic target of interest. Furthermore, identification of specific glycosaminoglycan domains involved in these diseases, as a platform for other substances or signaling pathways, might also prove to be of therapeutic value [4]. Visualization techniques Because of the functional importance of the endothelial glycocalyx, development of direct visualization techniques is crucial to establish its exact role. The glycocalyx can be labeled by administration of specific markers that attach to one or more of its components, making them fluorescent or detectable. Preparation of (parts of) the vessel would then allow specific microscopic imaging of the endothelial glycocalyx. Regretfully, the glycocalyx is very vulnerable and easily disturbed or dehydrated during vessel handling and preparation protocols. As a result, glycocalyx dimensions are easily underestimated, which is illustrated by the first images of the glycocalyx, made by transmission electron microscopy (TEM) in 1966 with the use of the probe ruthenium red; glycocalyx thickness measured this way approximated 20 nm in capillaries [66]. Since then, many other attempts were made to image the glycocalyx using TEM. On bovine aorta endothelial cells under shear stress conditions of 3.0 Pa, the glycocalyx was reported to be 40 nm thick [121]. These dimensions did not comply with theoretical estimates predicting the glycocalyx to be up to 1 μm thick [51]. Using a new staining protocol with Alcian blue 8GX, van den Berg et al. [124] recently applied TEM to measure endothelial glycocalyx dimensions in rat myocardial capillaries, which revealed that endothelial cells are covered by a 200- to 500-nm thick glycocalyx (Fig. 2a). Hyaluronidase treatment before fixation and staining resulted in significant reduction of this layer to 100–200 nm. The groups of Haraldsson [37] and of Rostgaard and Qvortrup [94, 95] improved the TEM staining protocol using fluorocarbon-based oxygen carrying fixatives, revealing glycocalyces as thick as 60–200 nm in glomerular capillaries, and 50–100 nm in intestinal fenestrated capillaries. Apparently, the new staining and preparation protocols improved glycocalyx conservation in TEM experiments. However, TEM cannot be used in the in vivo situation. Fig. 2Visualization of the endothelial glycocalyx with different microscopic techniques. a Endothelial glycocalyx of a rat left ventricular myocardial capillary stained with Alcian blue 8GX and visualized using electron microscopy. Bar represents 1 μm. Reproduced with permission from reference number [124]. b Intravital microscopic recording of the endothelial glycocalyx of a hamster cremaster muscle capillary. The anatomical diameter of 5.4 μm is larger than the red blood cell column width (left pane) or the plasma column width (right pane) labeled with fluorescent dextran (70 kD). This difference is caused by the presence of the endothelial glycocalyx. The bar in the left pane represents 5 μm. Reproduced with permission from reference number [129]. c Endothelial glycocalyx of a mouse common carotid artery. 3D-reconstruction of a series of optical slices obtained with two-photon laser scanning microscopy showing part of the vessel wall. The intact vessel was perfused with FITC-labeled lectin (WGA) to stain the endothelial glycocalyx (green) and SYTO 41 to label cell nuclei (blue). The arrows indicate the direction of the X, Y, and Z axis. The scanned volume approximates 200 × 200 × 60 μm3. For details on methodology see also reference number [67] Some 30 years after the first TEM images were made, Vink et al. [129] used intravital microscopy to visualize the endothelial glycocalyx in hamster cremaster muscle capillaries in vivo using indirect approaches. The glycocalyx was recognized as a red blood cell “exclusion zone” or “gap” between the flowing red blood cells and the endothelium. In addition, the plasma was labeled by a fluorescent dextran, and the glycocalyx then appeared as a plasma exclusion zone (Fig. 2b). Interestingly, no exclusion zone was found for rolling white blood cells, suggesting that they have the ability to compress the glycocalyx in these vessels, which complies with the estimated low stiffness of the glycocalyx [33, 106, 138]. Subtraction of the diameter of the plasma column from the anatomical internal diameter revealed the dimensions of the glycocalyx, which appeared to be 0.4–0.5 μm thick [129]. This method has been used in many studies since, primarily in the cremaster muscle microcirculation of hamsters [35, 36, 130] or mice [13, 97]. This tissue is suited for intravital microscopy because it is thin and translucent, allowing clear visualization of microvascular endothelial cells and flowing blood cells, with low or absent vessel wall motion (Fig. 2b). In addition, local flow velocities can be measured. However, the estimation of the glycocalyx thickness using intravital microscopy-based methods is indirect. Furthermore, intravital microscopy cannot be applied to image the endothelial glycocalyx in larger vessels. Direct visualization of the glycocalyx has been performed via several approaches, mostly using lectins which are proteins that bind specific disaccharide moieties of glycosaminoglycan chains [5, 24, 70]. Other labels include antibodies for heparan sulfate, syndecan-1 or hyaluronan [24, 70]. When attaching these markers to a fluorescent probe, advanced microscopic techniques can be applied to visualize the glycocalyx. Confocal laser scanning microscopy (CLSM) enables optical sectioning with good optical resolution, allowing 3D reconstructions of the specimen. Lectin labeling of the glycocalyx of cultured human umbilical vein endothelial cells and subsequent CLSM imaging revealed a surface layer as thick as 2.5 ± 0.5 μm [5]. CLSM has also been used to detect concentration changes of fluorescently labeled lectins in the glycocalyx of fixated rat mesentery postcapillary venules in case of ischemia/reperfusion and inflammation [70]. Because larger vessels have thicker walls, which results in lower light penetration depths with significant loss of resolution at higher depths (>40 μm) [127] due to increased scattering of signal, CLSM is less suitable for imaging of the glycocalyx in arteries. A promising technique to directly visualize the glycocalyx in larger vessels, both ex vivo and in vivo, is two-photon laser scanning microscopy (TPLSM). TPLSM depends on excitation of a fluorophore by simultaneous uptake (i.e., within 10−18 s) of two red photons, instead of one blue photon as in conventional fluorescence excitation. The use of long wavelength red photons reduces scattering, and hence, increases penetration depth into tissue. Excitation of the fluorophore and consequent fluorescence only occurs at the focal point of the illumination cone, as the probability of two-photon excitation depends on the squared intensity of the excitatory photons. Any light received by the photomultipliers has to originate from the focal position, so scattering of the emitted photons does not influence resolution and no pinholes are required. As a consequence, TPLSM offers good resolution and optical sectioning at reasonable acquisition speed, while bleaching and phototoxicity of the dyes is limited to the focal position. The combination of enhanced penetration depth, good resolution, optical sectioning, and low phototoxicity makes TPLSM a suitable technique to visualize the delicate endothelial glycocalyx in larger vessels. This idea was confirmed by a recent study by Megens and colleagues [67] in which the endothelial glycocalyx was imaged with TPLSM in intact mouse carotid arteries (Fig. 2c); the glycocalyx thickness was found to be 4.5 ± 1.0 μm. As TPLSM is also applicable in vivo in rodents [127], it might prove to be a good approach of in vivo visualization of the glycocalyx in the macrocirculation of these animals. Conclusions Overlying the vascular endothelium, the glycocalyx is a membrane-bound mesh in which plasma-derived molecules integrate. It exerts a variety of functions, important in normal vascular physiology and also in vascular disease. Although data from experiments in microcirculation, and more recently, in macrocirculation strongly suggests a vasculoprotective role for the glycocalyx, research on this subject is hampered by lack of a good visualization technique. Two-photon laser scanning microscopy may prove to be a successful tool in achieving direct visualization of the glycocalyx in larger arteries in rodents, both ex vivo and in vivo, with the possibility to analyze focal variations in the composition or integrity of this layer.

Pediatr_Nephrol-3-1-1784542

Therapeutic approach to FSGS in children

Therapy of primary focal segmental glomerulosclerosis (FSGS) in children incorporates conservative management and immunosuppression regimens to control proteinuria and preserve kidney function. In long-term cohort studies in adults and children with primary FSGS, renal survival has been directly associated with degree of proteinuria control. This educational article reviews the current therapeutic approach toward children with primary FSGS. Introduction Focal segmental glomerulosclerosis (FSGS) is a histologic finding that may result from a variety of insults to the kidney. FSGS typically presents with proteinuria and has a high risk of progressive loss of renal function [1]. Treatment of secondary forms of FSGS targets control of the underlying condition. Therapy of primary FSGS incorporates conservative management and immunosuppression regimens to control proteinuria and preserve kidney function. In long-term cohort studies in adults and children with primary FSGS, renal survival has been directly associated with degree of proteinuria control (Fig. 1) [2, 3]. Patients who are resistant to therapies have a significant likelihood of progressing to end-stage renal disease (ESRD) and are a group in need of novel therapies to delay or prevent this outcome [4]. Fig. 1a Kaplan–Meyer analysis of the risk of end-stage renal disease (ESRD) by proteinuria remission status in children with primary focal segmental glomerulosclerosis (FSGS). b Kidney survival by proteinuria remission status in adults with primary FSGS. CR complete remission, PR partial remission, NR no remission Genetic considerations An undefined proportion of patients with classically defined primary FSGS harbor genetic mutations in podocyte-specific genes such as nephrin, podocin, α-actinin-4, and CD2AP [5, 6]. There are conflicting reports about the effectiveness of immune-based therapy in the setting of these mutations, but the likelihood of a positive response may be low [7]. Although mutation-linked cases of FSGS may have a lower response rate to conventional immunomodulatory treatment, these patients still manifest the progressive fibrosis that is observed in nongenetic FSGS. Nonimmunosuppressive therapy Diuretic therapy Control of edema in nephrotic syndrome allows not only cosmetic improvement but is expected to decrease pulmonary effusions, decrease ascites, and lower the risk of peritonitis and skin-related problems from edema. Overaggressive diuresis in patients with intravascular depletion may be a risk factor, however, in developing thrombotic complications and acute renal insufficiency. Loop diuretics are often required for control of edema in patients with proteinuria in the nephrotic range. Delivery of the diuretic to the site of action (lumen of the tubule) is often impaired in nephrotic syndrome due to decreased glomerular filtration rate (GFR), increased binding of the diuretic to intraluminal albumin, and/or decreased delivery of sodium to sites of diuretic activity. An increase of sodium reabsorption in the distal tubule in response to loop diuretic activity may add to resistance to loop diuretics. This distal compensatory mechanism may be diminished by the use of a combination of loop and distal diuretics (thiazides) [8]. Though the addition of aldosterone inhibitors (spironolactone) is theoretically attractive under the theory that edema is in part driven by aldosterone, it is unclear whether spironolactone or other similar medications are clinically helpful to control edema [9–11] An additional advantage to the use of aldosterone inhibitors such as spironolactone is suggested by the antifibrotic properties of these agents, which will be discussed below [12]. Combined albumin and furosemide therapy for anasarca has been studied, as well. Na et al. showed evidence for a mild increase in water diuresis but little evidence that the concomitant use of albumin adds to the natruretic effect of furosemide [13, 14]. Fliser et al. [15] showed a moderate (20%) increase in water and salt excretion when comparing albumin and furosemide to furosemide alone. Haws et al. [16] also showed a mild but transient benefit of albumin and furosemide therapy but commented on the potential serious complications of hypertension, respiratory distress, congestive heart failure, and electrolyte disturbances. Thus, the combination of albumin and furosemide infusions, whether in combination or sequential, may provide a small transient benefit in the therapy of children with severe edema [17]. Treatment of hyperlipidemia For patients who become nephrotic from the progression of FSGS, hyperlipidemia is an almost universal finding. Whether the hyperlipidemia associated with nephrotic syndrome should be specifically targeted for treatment in children separately from nephrotic syndrome treatment itself has been a question for more than 20 years. The childhood origin of atherosclerotic disease and increased risk for cardiovascular disease secondary to chronic kidney disease supports an interventional approach. The report of the expert panel on blood cholesterol levels in children and adolescents [18] from the National Cholesterol Education Program (NCEP) defined categories of hypercholesterolemia in children for total cholesterol and low-density lipoprotein (LDL) cholesterol levels. High levels for total cholesterol were defined as ≥200 mg/dl and for LDL cholesterol as ≥130 mg/dl. Dietary treatment of hyperlipidemia is the first-line intervention. In adults with nephrotic syndrome, soy-based vegetarian diets and supplemented low protein diets have been shown to have potential benefits, decreasing both proteinuria and cholesterol, but have not been shown to slow the decline in GFR [19, 20]. Dietary therapy for dyslipidemia has been effective in reducing lipid levels in children with primary lipid disorders [21]. Based on the report from the NCEP, pharmacologic therapy for children ages 10 years and older should be considered after an adequate trial of diet therapy if LDL cholesterol remains ≥160 mg/dl in children with significant risk for cardiovascular disease, as is seen in children with FSGS. Recommendations for pharmacologic therapy for hyperlipidemia in children from the report suggested that bile acid sequestrants cholestyramine and colestipol should be the first-line agents for treating children with lipid disorders [18]. This was due mainly to concerns about the safety of 3-hydroxy-3-methylglutaryl coenzyme A (HMG CoA) reductase inhibitors (statins) in children. While they are effective in lowering cholesterol and are relatively safe, bile acid sequestrants pose particular problems in children. They are not very palatable, and they may affect absorption of other medications being used, including thiazide diuretics, propranolol, corticosteroids, thyroid hormones, and loop diuretics. A new medication in this category, colesevelam, apparently does not have these problems but is not approved for use in children. Since the NCEP report in 1992, several studies have been published suggesting that statins are safe in children as young as 4 years of age with familial hypercholesterolemia and do not adversely affect growth, hormone levels, or sexual development [21–23]. Statins are effective in treating the hypercholesterolemia of nephrotic syndrome, with decreases in total cholesterol levels up to 45% [24]. The long-term benefit of statins on renal function may be positive. Down stream from glomerular injury, high levels of urinary protein pass to the renal tubule and are reabsorbed. Protein reabsorption may injure the renal tubule. Statins may inhibit this tubular protein reabsorption and thereby protect from additional renal injury. Whether statins provide renoprotective effects in children has not been well studied, but there are several studies in adults with nondiabetic proteinuria that indicate that statins may slow GFR decline [25]. In these studies, the greatest benefit seemed to accrue in patients with the greatest amount of proteinuria and renal insufficiency. The side effects of statins have mainly been limited to myopathy and hepatotoxicity [26, 27]. Drugs in the fibrate class have also been used alone and in combination to treat hypercholesterolemia in children with nephrotic syndrome [28]. The use of gemfibrozil with a statin may increase the incidence of myopathy. Fenofibrate, approved for adult use in January 2006, may have less interaction due different hepatic metabolism [29]. The long-term safety of fibrates in children has not been well established. Alteration of the renin-angiotensin-aldosterone axis Blood pressure control for children with FSGS targets values less than or equal to the 90th percentile for age, gender, and height and is consistent with recommendations for all children with kidney disease. Evidence from many trials using angiotensin-converting enzyme inhibitor (ACE-I) and/or angiotensin receptor blocker (ARB) therapy in patients with proteinuria indicate that, beyond their antihypertensive effect, both are effective in reducing proteinuria in a wide variety of renal diseases. Few studies have had significant numbers of patients with FSGS specifically, and fewer still have included children with FSGS. In 1988, Trachtman and Gauthier reported a 50–70% reduction in proteinuria in children with steroid-resistant nephrotic syndrome (SRNS) using ACE-I therapy [30]. Bagga et al. [31], in a randomized, crossover trial of low-dose (0.2 mg/kg) vs. high-dose (0.6 mg/kg) enalapril in 25 patients with SRNS showed dose related responses, with average urine albumin/creatinine ratio reductions of 33% and 52%, respectively. Blood pressure control was similar between the two groups. Several other studies of enalapril and ramipril in children with a variety of proteinuric renal diseases have confirmed the efficacy of these drugs in reducing proteinuria in many, but not all, treated children [32–35]. In the Ramipril Efficacy in Nephropathy (REIN) study, a double-blind study in adults with nondiabetic nephropathy, treatment with ramipril seemed to reduce both proteinuria and the rate of GFR decline more than could be attributed to blood pressure control alone [36]. Wühl et al., in a similar trial in almost 400 children with hypoplasia/dysplasia (70%) and glomerulopathies (13%), had similar findings [37]. There have been many studies in adults with renal disease comparing combined ACE-I/angiotensin receptor blocker (ARB) therapy with monotherapy alone [38, 39]. Though differing in design and findings, overall, the studies seem to indicate greater reduction in proteinuria without a greater frequency of side effects [39–41]. Yang et al. [41] reported greater reduction in proteinuria with combined therapy in a small group of five children with immunoglobulin (Ig)A nephropathy and heavy proteinuria, with no significant side effects noted. The most concerning side effect of ACE-I and ARB therapy is in females of childbearing years, with significant risk of fetal abnormalities reported with in utero exposure [42]. Other side effects of ACE-I therapy were noted in 2.4% of children in one large series with ramipril in children with chronic renal failure [37]. These side effects included decreases in GFR and hemoglobin and increases in serum potassium levels. Acute renal failure, often associated with hypovolemia, has been noted and seems to respond to discontinuation of the medicine until the acute illness resolves. Angioedema and nonproductive cough have been encountered with the use of ACE-I therapy in adults and are less frequently reported in children. ARBs seem to have a lower incidence of angioedema and cough [43, 44]. The incidence of recurrent angioedema in those who experience ACE-I-associated angioedema and are switched to ARB therapy appears to be low [45]. Aldosterone inhibitors have shown potential for alteration of the fibrotic mechanisms in animal models of kidney fibrosis, in the reduction of proteinuria in diabetic nephropathy, and in proteinuric chronic kidney diseases [12, 46, 47]. In the later study of 40 patients with a variety of proteinuric kidney diseases, the combination of ACE-I and aldosterone inhibitor therapy led to a decrease in mean urinary protein excretion in the ten patients assigned to this study arm [48]. Studies in humans with FSGS have not been published. Antioxidants The potential for antioxidant therapy in FSGS stems from experimental data that supports a role for excessive free radicals in multiple disease states, including chronic kidney disease. Based on antioxidant properties, vitamin E has been evaluated as a potential therapy for FSGS in one small study by Tahzib et al. In this open-label study, 11 children with FSGS were treated with vitamin E for approximately 3 months. A reduction in protein excretion was noted [49]. The antioxidant properties of vitamin E and the relatively low risk for adverse effects of this agent make this an interesting, if unproven, therapeutic option. The combined conservative management approach may control morbidity but leave the majority of patients with uncontrolled urinary protein excretion and risk for progression of disease. The typical approach to FSGS therapy in children is to add immunosuppression at the onset of therapy. Immunosuppression Corticosteroids Corticosteroids have long been the mainstay of treatment for childhood nephrotic syndrome, regardless of its etiology. The huge role that these agents play is evident in the way this disease is classified: steroid responsive, steroid dependent, and steroid resistant. The International Study of Kidney Disease in Children (ISKDC) standard dosing has been, and generally continues to be, applied. That is, an 8-week course of oral prednisone at 60 mg/m2/day for 4 weeks, followed by 40 mg/m2 on alternate days for 4 weeks [50]. Initial ISKDC data showed a corticosteroid response rate of approximately 30% of the 37 children with FSGS studied, and subsequent studies have been consistent in showing a response to oral corticosteroids in a minority of FSGS patients [51]. However, a response to corticosteroids is generally consistent with a more favorable prognosis, even when an initial response is followed by resistance after a subsequent relapse. There are also reported population differences in the response to steroid treatment, such as decreased response in African Americans and Hispanics [52]. Some literature is emerging that shows a lower response rate for patients with the nephrosis 2 homolog, podocin (human) (NPHS2) mutation [53]. The more recent debate has been about what steroid, how much steroid, and for how long, before a patient can be definitely declared unresponsive. Certainly, data in adult patients advocate prolonged oral corticosteroid administration, in some cases >6 months [54]. There have been no pediatric trials of prolonged oral corticosteroid use in patients with FSGS. The regimens used vary tremendously, with the most dramatic differences occurring between pediatric nephrologists and internist nephrologists. Due to the generally poor response to the standard oral dosing, some pediatric protocols have advocated high doses of intravenous methylprednisolone, with varying degrees of success [54, 55]. Corticosteroids remain a key component of many therapeutic regimens for FSGS, usually in combination with the various other drugs used to treat this disease, such as alkylating agents or calcineurin inhibitors. Of course, corticosteroid therapy is not without side effects. These include hypertension, growth impairment with prolonged therapy, susceptibility to infection, diabetes mellitus, and osteoporosis [55]. These side effects have led to the tendency toward lower corticosteroid doses and shorter, rather than prolonged, courses. Calcineurin inhibitors Cyclosporine A The rationale behind the initial use of cyclosporine A (CsA) in FSGS and other forms of nephrotic syndrome is the evidence in animal models that the disease may be mediated by lymphokines that mediate glomerular basement membrane damage although it is unclear that this is actually the case. CsA acts on T-helper cells to inhibit interleukin-2 (IL-2) production, cytotoxic T-cell proliferation, and activation of B-cell responses by helper T-cells. However, CsA likely induces remission in proteinuria by two other mechanisms: induction of vasoconstriction of the glomerular afferent arteriole and interference with glomerular basement membrane permselectivity to proteins [56]. It has been two decades since CsA was first reported to show some benefit for patients with idiopathic nephrotic syndrome, especially for patients with steroid-responsive disease who had frequent relapses. One randomized trial of 49 steroid-resistant patients assigned to either CsA or placebo for 6 months showed a benefit in the CsA arm, with a response rate of 70% (complete or partial remission). This is the only medication with documented efficacy for steroid-resistant FSGS in controlled clinical trials in both adults and children [57, 58]. A major concern of long-term CsA treatment is the well-documented potential for nephrotoxicity. Another is the high relapse rate after drug withdrawal. In the Cattran study [57], 60% of the patients who responded to treatment had relapsed by week 78. There is also now concern being raised about secondary resistance developing in patients treated with CsA: an initial induction of remission, relapse when the drug is withdrawn, and resistance on reinstitution of the drug [59]. In this study of 32 children, the diagnosis of FSGS and the presence of C4 or C1q during immunofluorescence staining of kidney tissue appear to correlate with an increased risk of secondary resistance. There are still no guidelines for standardized dosing or duration of treatment of children with steroid-resistant nephrotic syndrome, which probably accounts for the variability in reported response to treatment in the literature. Side effects of CsA treatment include hypertension, hirsutism, and gingival hyperplasia. As a result of these and the risk for nephrotoxicity, treatment with cyclosporine has not been without controversy in terms of perceived optimal daily dosing, blood level to be maintained, and duration of treatment. A recent Egyptian study in 117 children with nephrotic syndrome, which included 79 patients with FSGS, used low-dose, long-term CsA (more than 2 years of treatment) [60]. The starting dose of 4–5 mg/kg per day was adjusted to maintain a whole-blood trough level of 100–150 ng/ml during the first 2 months and 50–100 ng/ml thereafter. In these subjects with steroid-resistant FSGS, the investigators were able to achieve an almost 70% complete remission rate during the 6 months of therapy. Unfortunately, the relapse rate was substantial upon withdrawal of CsA. Overall, it appears that, as with corticosteroids, a positive response to CsA, even if followed by a relapse, is a good prognostic indicator with regard to the risk for progression to ESRD [57]. Tacrolimus This newer and more potent calcineurin inhibitor has not undergone a controlled clinical trial for the treatment of FSGS, but there are anecdotal reports of responses in patients with nephrotic syndrome, some of whom had FSGS [61]. One retrospective study of 16 children with treatment-resistant nephrotic syndrome, including 13 with FSGS, documented reduction in urinary protein excretion in 13 while on therapy and subsequent relapse in three of the 13 [62]. There are also two small prospective studies in adults that showed a positive response [63, 64]. In these small studies, tacrolimus appeared to present a problem similar to that of CsA, with a majority of patients relapsing on drug withdrawal [63]. Alkylating agents DNA alkylating agents such as cyclophosphamide and chlorambucil have been in use since the 1980s for several glomerular diseases, including FSGS. The use of these agents has been limited due to potential side effects, including bone marrow suppression, infertility, hemorrhagic cystitis, and possible future malignancy risk. A retrospective cohort of 29 patients suggested that cyclophosphamide may have some survival benefit in those with at least a partial response measured by impact on proteinuria and progression of chronic kidney disease [65]. A randomized trial in 1996 from the ISKDC evaluated 60 children with FSGS and their response to daily oral cyclophosphamide and alternate day prednisone vs. alternate day prednisone alone. There was no difference in renal survival or proteinuria between the two groups [66]. Due to unfavorable toxic side effects and variable reported efficacy in the literature, alkylating agents are falling out of favor for primary therapy in FSGS. Mycophenolate mofetil Mycophenolate mofetil (MMF) was introduced in the mid-1990s as an immunosuppressive agent for organ transplantation. Due to its steroid-sparing effect, efforts have been made to expand its clinical application to several glomerular diseases, including FSGS. MMF blocks de novo synthesis of T- and B-cell lymphocytes through noncompetitive, reversible inhibition of inosine monophosphate dehydrogenase. Data on the use of MMF in FSGS has been limited to a few uncontrolled trials with small numbers of patients, but it shows early promise. Choi et al. reported 46 patients with primary glomerulopathies, including 18 patients with FSGS. They found a statistically significant decrease in proteinuria in patients receiving MMF as adjunctive therapy [67]. Cattran et al. reported an open-label, 6-month trial of MMF in 18 patients with steroid-resistant FSGS, 12 of whom were also resistant to alkylating agents and/or calcineurin inhibitors. Although patients did not achieve complete remission, four of 18 had a reduction in proteinuria during therapy [68]. A similar decrease in proteinuria was documented in a series of nine children and young adults with steroid-resistant FSGS who were treated with pulse steroids and MMF [69]. Overall, MMF is showing early promise as a steroid-sparing therapy in FSGS, but questions remain about length of therapy, escalation of dosing, and long-term malignancy risks. Sirolimus The utility of sirolimus in the treatment of FSGS has been entertained in patients with intolerance or resistance to corticosteroid therapy. One prospective nonrandomized study documented a reduction of proteinuria in 12 of 21 patients treated with 6 months of sirolimus [70]. Conversely, a study of six FSGS patients treated with sirolimus documented a decline in kidney function in five patients. None had a complete remission [71]. In transplant recipients, the use of sirolimus in conjunction with calcineurin inhibitors has also been associated with acute renal failure [72]. Consequently, sirolimus is not recommended for the treatment of FSGS due to the associated renal toxicity. Plasmapheresis In multiple-drug-resistant primary FSGS, the use of plasmapheresis has been considered a rescue option. The generally accepted rationale is for the removal of a circulating factor from the plasma that alters glomerular barrier function [73]. In primary FSGS in the native kidneys, two small studies encompassing 19 patients reported a response rate between 12% and 55% [74, 75]. The best response was seen using a protocol of plasmapheresis, corticosteroids, and cyclophosphamide, making it difficult to attribute the full response to plasmapheresis alone [75]. A single case report of a child with resistant disease demonstrated improved proteinuria and serum creatinine [76]. At present, plasmapheresis is considered a rescue therapy and is an invasive procedure with significant risks of infection, hypocalcemia, and bleeding. Plasmapheresis is considered an option for prevention or treatment of recurrent FSGS in the transplant recipient based on uncontrolled studies [77, 78]. Antifibrotic therapy There are a large number of patients with multiple-drug-resistant FSGS who are at substantial risk of progression to ESRD and for whom there are no proven therapeutic options. The past decade has witnessed striking advances in understanding the cellular and molecular basis of renal fibrosis and its contribution to progressive kidney failure. Several therapeutic targets have been identified in animal models of fibrosis in the kidney, including molecules involved in the recruitment and activation of mononuclear cells (e.g., chemokines, lymphokines, adhesion molecules), recruitment and activation of interstitial myofibroblasts, fibrogenic molecules [e.g., transforming growth factor (TGF)-β, endothelin-1, angiotensin II, tumor necrosis factor (TNF)-α, and platelet-derived growth factor (PDGF)-β], angiogenic factors [e.g., vascular endothelial growth factor (VEGF)], antiapoptotic molecules, inhibitors of matrix synthesis, and molecules that enhance matrix degradation (matrix-degrading proteases, blockers of protease inhibitors) [79–83]. Crossing many of these mechanisms, peroxisome proliferator activator receptor-γ (PPARγ) agonists alter regulation of renal cell differentiation and proliferation [84–87], extracellular matrix production, macrophage accumulation, tissue inflammation, and apoptosis [88]. The most effective treatment to prevent progression of fibrosis and kidney failure in FSGS is likely to entail a combination of drugs that modulate mediators of fibrosis. The progression of kidney fibrosis is interrupted in part by the use of ACE-I and ARB agents in FSGS therapy. Future therapeutic options are likely to emanate from this area of research. Conclusions Current strategies for control of FSGS use a stepwise approach with a goal of normalization of urinary protein excretion and the prevention of kidney failure. Progress in this field remains a priority in order to prevent the trajectory toward renal failure for patients proven to be resistant to treatment and to identify therapeutic regimens with minimal toxicity. CME questions (Answers appear following the reference list) A 14-year-old boy presents with nephrotic syndrome, normal serum creatinine, and normal blood pressure. He is diagnosed with FSGS by kidney biopsy and treated with corticosteroids. What is the most likely response to corticosteroids in this setting? Complete remission with corticosteroid therapyDependence on corticosteroidsFailure to respond to corticosteroids but improves with cyclosporineFailure to control proteinuria and progression to kidney failureFactors that seem to confer an unfavorable prognosis in children with nephrotic syndrome are: Primary resistance to corticosteroidsResistance to cyclosporinePresence of NPHS2 podocin mutationAfrican American or Hispanic ethnicityAll of the aboveIn the management of FSGS, progressive kidney fibrosis may be slowed by: FurosemideAngiotensin receptor blockadeCholestyraminePrednisoneBoth b and dFSGS patients with NPHS2 podocin mutation are more likely to respond to corticosteroids than patients without a podocin mutation (T/F).Cyclophosphamide is considered a mainstay in therapy for FSGS to prevent progression to end-stage renal failure (T/F).

Pharm_World_Sci-3-1-2082655

Understanding the meaning of medications for patients: The medication experience

Objective: To understand and describe the meaning of medications for patients. Methods: A metasynthesis of three different, yet complementary qualitative research studies, was conducted by two researchers. The first study was a phenomenological study of patients’ medication experiences that used unstructured interviews. The second study was an ethnographic study of pharmaceutical care practice, which included participant observation, in-depth interviews and focus groups with patients of pharmaceutical care. The third was a phenomenological study of the chronic illness experience of medically uninsured individuals in the United States and included an explicit aim to understand the medication experience within that context. The two researchers who conducted these three qualitative studies that examined the medication experience performed the meta-synthesis. The process began with the researchers reviewing the themes of the medication experience for each study. The researchers then aggregated the themes to identify the overlapping and similar themes of the medication experience and which themes are sub-themes within another theme versus a unique theme of the medication experience. The researchers then used the analytic technique, “free imaginative variation” to determine the essential, structural themes of the medication experience. Results: The meaning of medications for patients was captured as four themes of the medication experience: a meaningful encounter; bodily effects; unremitting nature; and exerting control. The medication experience is an individual’s subjective experience of taking a medication in his daily life. It begins as an encounter with a medication. It is an encounter that is given meaning before it occurs. The experience may include positive or negative bodily effects. The unremitting nature of a chronic medication often causes an individual to question the need for the medication. Subsequently, the individual may exert control by altering the way he takes the medication and often in part because of the gained expertise with the medication in his own body. Conclusion: The medication experience is a practice concept that serves to understand patients’ experiences and to understand an individual patient’s medication experience and medication-taking behaviors in order to meet his or her medication-related needs. Introduction Medications are one of the main options in the cure, treatment, and prevention of numerous medical conditions. However, there is still a gap in society regarding who must be held accountable for the outcomes of pharmacotherapy. Pharmacists have recently recognized the societal need to take responsibility for drug therapy outcomes [1]. However, if a health care practitioner strives to meet a patient’s drug-related needs then that practitioner must understand the meaning of medications for that patient [1–3]. However, the medication experience as a practice concept has not been comprehensively researched in pharmacy. Medical and social scientists have examined the subjective experience of medications for patients, typically within the illness experience. Studies have been conducted on the meaning of medications for patients with specific medical conditions including: asthma [4]; hypertension [5]; and schizophrenia [6]. Moreover, studies have explored the meaning of therapeutic classes including: selective serotonin reuptake inhibitors [7]; hormone-replacement therapy [8, 9]; and antipsychotic medications [10]. Studies have also focused on patients’ medication practices or medication-taking behaviors [10, 11]; decision-making [8]; and cultural ideas of drug use [12]. Conrad [13] introduced the concept of medication practices or how patients manage their medications. He found that patients with epilepsy interpret the prescribed regimen and create medication practices that may vary from the prescribed one. Though many studies have examined the meaning of medications, most have focused on specific diseases or classes of drugs. The authors surmise that there could be a common experience of taking medications chronically that transcends the specificity of diseases and medications. Additionally, most studies on the meaning of medications have focused on patients’ decision-making, medication-taking behaviors, or compliance. Synthesizing the findings from three studies that investigate the meaning of taking medications for patients with many chronic conditions could provide a deeper level of understanding about a concept of importance to pharmacy practitioners. These three studies focused on understanding how patients experience taking medications on a daily basis; meaning how they feel, react and think about medications. This understanding may help pharmacists to better comprehend how and why patients make the decisions and take the actions they do. It is the goal of this article to present an understanding of the meaning of medications for patients, introduced here as the medication experience. Methods This paper is the result of a meta-synthesis of three different yet complementary qualitative studies that included aims to understand the medication experience. These three studies were conducted by the two authors. Table 1 describes each study’s method and participants’ demographics. Table 1Studies’ methods and participant attributesStudyMedication experiencePharmaceutical care practiceIllness experience of medically uninsuredMethodologyPhenomenologyEthnographyInterpretive phenomenologyMethods InterviewsInterviews, focus groups, participant observationInterviewsSetting of interviewsUniversity conference rooms and officesParticipants’ homes and clinic exam roomsParticipants’ homes, public library rooms, & university roomsParticipantsStaff and faculty at public universityPatients of pharmaceutical care (PC)Medically uninsured individualsSelection criteria6+ months taking a chronic medication (actual 3–15 years)2+ years experience with PC1+ year uninsured, 2+ medical conditions, prescribed medsNumber of participants52511Age range24–6036–7427–64Gender of participants4 women, 1 man17 women, 8 men8 women, 3 menAverage number of medical conditions per participant2.844.5 The first study was a phenomenological study of individuals’ experiences taking at least two prescription medications. The methods were guided by Van Manen’s [14] insights using in-depth interviews, which were audio-taped and transcribed. The analysis involved reading and coding each interview transcript for the meaning units of each participant’s experience. Meaning units are phrases or text sections that illustrate a segment of the meaning distinct from the adjacent text. Then the codes were reviewed to identify the common themes of the medication experience for all participants. The second study was an ethnography that used a triangulation of methods to reach a comprehensive understanding of pharmaceutical care practice [3]. The study revealed patients’ medication experiences as a significant part of patients’ experiences with pharmaceutical care. The study was conducted over a period of eight months in six clinics and one community pharmacy. The sampling was theoretical sampling, which involved selecting participants who would yield information that was relevant to the understanding of experiences of those in the pharmaceutical care practices. The data analysis was conducted following the techniques of Wolcott [15]. The third study was an interpretive phenomenological study that used in-depth interviews to understand medically uninsured individuals’ (in the United States) chronic illness experiences, including the medication experience [16]. The interviews were audiotaped and transcribed. The interview transcripts and field notes were segmented and labeled for one of the three experiential units - the illness, medication, and uninsured experience. A thematic analysis of the lived experience of each segment of text was conducted coding each segment with a descriptive code that captured the meaning conveyed. The codes were iteratively refined, and removed as appropriate. This was in part conducted using an analytic method called free imaginative variation. Free imaginative variation involves removing a theme, then asking if the essence of the phenomenon withstands [14]. The resultant essential codes became the themes of the illness and medication experience of medically uninsured individuals. The researchers used meta-synthesis of the three studies to reach a greater breadth of understanding about individuals’ medication experiences. Meta-synthesis is an analytic method that facilitates a fuller understanding of a phenomenon by providing an interpretive integration of qualitative findings. The meta-synthesis of qualitative findings is increasingly seen as essential to enhance the generalizability of qualitative research [17]. The two researchers who conducted these three qualitative studies performed the meta-synthesis. The process began with the researchers reviewing the themes of the medication experience for each study. The researchers then aggregated the themes to identify the overlapping and similar themes of the medication experience. The researchers used free imaginative variation to determine the essential themes of the medication experience and from these the prevailing themes were identified. The findings from the meta-synthesis of the three studies informed the meaning of medications (i.e., the medication experience) that is presented in this paper. Results The meaning of medications for participants was revealed as the following themes: a meaningful encounter, bodily effects, unremitting nature, and exerting control. A meaningful encounter The medication experience is first revealed as an encounter with a medication. It is an encounter that is embedded with meaning long before it occurs. The meaningful encounter can be revealed as a sense of losing control, a sign of getting older, cause questioning, and a meeting with stigma. Each of these sub-themes of the meaningful encounter is described below. The encounter with a chronic medication for the first time can be experienced as a sense of losing control, as one participant states: I used to think I was immune to disease. This body is so tremendous that it will never let me down, but here I was—I had to start taking medication. One participant explicitly characterized her medical need for chronic medications as a loss of control:I lost control of my health. I wish I could handle it myself. Another participant describes a similar desire to treat her condition without medication:I felt like if I took lorazepam that I’m failing. If I could fight it myself, get over it myself without the drug then I’m getting better. Participants commonly ascribed a negative meaning to medications when they first encountered them or when they began taking an increasing number of medications chronically. Another study found loss of control as part of the meaning of medications for patients [18]. Many participants described medications as signifying aging. One participant characterized starting a medication as depressing because it indicated he was “getting older.” However, for a participant in her mid-twenties using several medications, the significance was even greater:I feel like a 90-year-old woman. Like my grandpa, he’s on all these pills. If you’re an old person that’s okay, but if you’re young it’s really odd. Medications distinguish the healthy from the sick and the young from the old. Taking chronic medications often made participants feel that they were now part of that group of people who take medications because they are getting older. As part of the initial encounter with a chronic medication, many participants question the actual need for the medication they are prescribed.I’m not sure what I’ll get from these medications. Uncertainty arises when participants realize they are supposed to take a medication chronically.I thought about what would happen to me if I just decided not to take it. Questioning the need for a medication when it is first prescribed can be interpreted as resistance by health care professionals, whereas for participants it is a way to reclaim a degree of control. Participants sensed that their individual autonomy was undermined when taking chronic medications until the point they questioned the taken-for-granted notion that medications are the right option. The first reactions to initiating a medication can also be shaped by the social views of the medical condition. For example, the reaction of individuals to initiating psychotropic medications can be a response to the stigma of mental illness. As expressed by participants in these studies, taking an antidepressant carries the shame associated with mental illness.Maybe I’m just embarrassed, even if nobody would know. I think people would see me as weak. When initiating a chronic medication, participants encountered different meanings that shaped their initial experience of the medication. Participants experienced the meaningful encounter with a chronic medication as a sense of losing control, a sign of getting older, causing them to question, and a meeting with stigma. Bodily effects Medications have expected pharmacological benefits as well as anticipated side effects and unanticipated adverse events, all of which are bodily experiences. When a patient’s experience of their body in illness is debilitating, a medication can provide relief and allow the patient to regain their “healthy” body. However, medications also can cause negative bodily sequelae that are part of a patient’s medication experience. The bodily effects of medications theme was revealed as the experience of a magic elixir and trade-offs. The medication can “normalize” the patient or bring her body as a whole together: At first I was very grateful that insulin existed—it saved my life. I am grateful that I’m alive. It is scary that you’re reliant on this magic elixir to be alive. Participants who characterized their medications as “magic elixirs” often had medical conditions that incapacitated them.I’ve struggled with depression all my life. My psychiatrist started me on antidepressants. I’m very grateful for these drugs. I wouldn’t be able to work if it wasn’t for them. Sometimes the body, disrupted by a disease, can be brought back into balance with medications. Conrad [13] found that epileptic patients perceived taking their anticonvulsants as a ‘ticket’ to normality. An important component of the bodily effects stemmed from what the medications did to improve their lives. In contrast, other participants experienced the negative sequelae of a medication. However, if the benefit experienced was sufficiently good they would be willing to accept the side effects as a trade-off. One participant indicates:You learn to decide if you’re gonna take the side effect over how well it helps with your depression. Citalopram worked so well for me that I didn’t care that I was peeing my pants. Another participant describes:I’m not worried about taking them, mostly because if they’re going to kill me earlier I don’t care because I just want the problem to go away. Another study identified that patients are aware of the trade-offs that must be made while trying to maximize their well-being [10]. Participants also expressed concern about taking a medication until they experienced the benefits.Even though I was hesitant at the beginning, after seeing the benefits and realizing how life can be with “just a medication” and feel good… This theme illustrates how patients may rationally approach the decision to take or continue a medication and that they are willing to take a medication once they believe that the medication’s benefits outweigh its risks. Unremitting nature The unremitting nature of a chronic medication, like a chronic condition, is a burden.The first time somebody told me I would have to take that for the rest of my life I got mad. Another participant states: I feel that part of my life now is going to be me taking more and more medicine and relying on medications to continue living. The expectation of taking a medication regularly positions the patient as a passive agent, and the medication then becomes a symbol of dependence.I think, what if I went a couple months without taking anything? But I don’t feel I have that choice. Those pills keep you prisoner. If you go on a trip, that’s one of the major factors - it’s more important than packing enough underclothes. This participant has lost autonomy and in her words she is held captive by her medications. Additionally, due to the chronicity of medications participants have to take responsibility.It’s this constant thing you wish you could have a break from, but you can’t. In order to achieve normal function some participants have to take medications indefinitely, yet they still wish that wasn’t the case.You feel sorry for yourself because you’re still on these pills. I don’t want to think - it’s been this long and I’m still on them. Exerting control The last theme of the medication experience was revealed as participants exerting control over their medications. After encountering the meaning of a medication, questioning it, realizing the bodily effects and the continuous nature of medications, participants experimented with becoming the managers of their treatment regimens. After taking chronic medications for a period of time participants became familiar with the effects of medications on their bodies. They discovered creative ways to manage their medications and exert control over them; in part because they were now knowledgeable.I don’t think people understand how much you have to think about it. I call it thinking like a pancreas. You have to do all the work. You have to determine how much you take [insulin] and that changes from day to day and from hour to hour... Participants have their own method of learning pharmacology–through experience. They know their bodies and perceive the changes produced by medications. As a result, exerting control is a common practice in individuals taking medications chronically.I know how to go off of it, decrease it very slowly or you get sick. Health care professionals rarely acknowledge this practice as a form of exerting control; instead it is labeled as noncompliance. Another participant offers a description of being attuned to her body and taking control: As the doctor upped the dose I felt like I was high … I started getting a really weird feeling in my head, I even had pains in my chest. I thought to myself, I’m just gonna quit taking this. So I quit, and then as the week went on I was slowly getting better. Participants also self manage their medications by reducing the dose particularly when they are uncertain about the effects or concerned about becoming “dependent.” I like being able to adjust my sertraline as I find necessary. I like to have that control. As the participants in these studies convey and Carrick et al. [10] also observed, patients are the ultimate managers of their treatments and create their own medication practices. From the patient’s perspective, such behaviors are rational and help them preserve control. Ramalho de Oliveira and Shoemaker [2] argued that pharmacists typically take a paternalistic perspective, viewing patients’ non-compliant behavior as an irrational act. The understanding of patients exerting control over their medications provides a context in which to challenge the notion that patients’ medication practices are illogical. Discussion The authors define the medication experience as an individual’s subjective experience of taking a medication in his daily life. It begins as an encounter with a chronic medication. It is an encounter that is given meaning before it happens and is often a reaction to the symbol that medication holds. The experience may include positive or negative bodily effects. The unremitting nature of a chronic medication often causes an individual to question the need for the medication. Subsequently, the individual may exert control by altering the way he takes the medication and often in part because of the gained expertise with the medication in his own body. In this paper, the themes of the medication experience are described as being essentially independent of one another; however there was a temporal location in which the meanings seemed to arise in the participants’ stories. It appeared that the four themes are essentially stages of the medication experience or the experience of taking a chronic medication has a natural progression from a meaningful encounter to participants exerting control. Other scholars have recognized a pattern or stages that patients go through with specific medications. A study of young women using selective-serotonin reuptake inhibitors (SSRIs) for depression revealed that SSRI users passed through stages corresponding to how they felt about themselves [7]. Further research is needed to explore the validity of patients’ medication experiences as a progression through stages or a journey. Since medications are among the most common options in the treatment and mitigation of diseases, it is essential for health care practitioners to acknowledge an individual’s medication experience in order to positively influence patients’ medication-taking behaviors. Patients’ decisions, which at first appear irrational, might be seen as intelligent when a practitioner understands a patient’s unique medication experience. Cipolle et al. [1] state “a practitioner cannot make sound clinical decisions without a good understanding of the patient’s medication experience” and urge practitioners to take responsibility for improving each patient’s medication experience. The findings of this study provide pharmacists insights on the meanings that medications can have for patients, which may explain and certainly impact their medication-taking behavior. For example, understanding the potential meaning of initiating a chronic medication (e.g., losing control) may help explain a patient’s reticence to taking the medication. A limitation of this study is that the synthesis of findings was from studies that explored the medication experience across multiple chronic conditions, which makes it difficult to discern the aspects of participants’ experiences related to the unique illness experience of a specific disease. Additionally, the participants were all in the U.S. (though not all native born) and the medication experiences may vary in different cultures. Even though meta-synthesis addresses the issue of small sample sizes in qualitative research, this study still has a relatively small sample size (n = 41), which limits the applicability of these findings to others’ experiences. Lastly, the authors re-analyzed their own work, which could have led to bias and reinforcement of the original findings. Conclusions The medication experience is a practice concept that serves to understand patients’ experiences and to understand an individual patient’s medication experience in order to meet his or her medication-related needs. The understanding of the medication experience presented in this paper can serve as a guide for health care practitioners who are interested in meeting a patient’s medication-related needs and provide a foundation from which to interpret each individual’s unique medication experience. Additional research is needed to further understand the medication experience and examine how it can be used to optimize patients’ medication-taking behaviors as well as if there are stages of the medication experience that patients pass through.

Childs_Nerv_Syst-2-2-1705512

Genome-wide microRNA profiling in human fetal nervous tissues by oligonucleotide microarray

Objects Our objective was to develop an oligonucleotide DNA microarray (OMA) for genome-wide microRNA profiling and use this method to find miRNAs, which control organic development especially for nervous system. Introduction To date, 326 microRNAs (miRNAs), a ubiquitous family of about 22-nt noncoding regulatory RNAs, have been identified in the human genome and published in a database (http://www.sanger.ac.uk/Software/Rfam/mirna/index.shtml) [1]. Although more than 200 distinct miRNAs are predicted in the human genome, little is known about their biological functions, especially during embryonic development. MiRNAs regulate target genes at the post-transcriptional level and play important roles in development and cell lineage decisions. However, in vertebrates, neither the targets of miRNAs nor their expression profiles during development are well understood. Some miRNAs are specifically expressed in individual tissues and at particular developmental stages. The developmental or tissue-specific patterns of miRNA expression observed may suggest analogous roles in regulating human development or cellular differentiation [2–4]. A major obstacle in the study of miRNA function is the lack of methods for quantitative expression profiling. The miRNA microarray method, a powerful tool for global analysis of miRNA expression first reported by Krichevsky et al. [5], is based on a membrane array spotted with specific antisense mature miRNA oligonucleotides. Since then, other types of oligonucleotide array methods have been published, including arrays on glass slides and on beads [6–9]. In this study, a robust microarray-based technique was established and used to identify the expression of 158 miRNAs in human fetal organs. The oligonucleotide microarray (OMA) was designed according to the method of Liu [7], with modifications. We used miRNA microarrays to study the profiles of miRNA expression in nervous tissue samples and other organic samples from two fetuses. Some clusters of miRNA families were co-expressed, providing clues about the maturation processes of miRNAs. At the same time, we found a high concordance between our array results and those from Northern blots. The microarray described here offers more comprehensive coverage and higher throughput than other methods, represents a powerful tool to better understand miRNA expression profiles in human tissues, and provides clues to the mechanisms for regulating protein translation. Materials and methods Samples and RNA extraction Two fetal abortuses [12 weeks (G12w) and 24 weeks (G24w) gestational age] tissues were obtained from the National Infrastructure Program of the Chinese Genetic Resources after obtaining informed consent. The G12w tissues were liver, kidney, cerebrum, lung, and heart, and the G24w tissues were the same, plus ovary, spleen, hypothalamus, pancreas, and cervical, thoracic, lumbar, and sacral spinal cord. Total RNA was isolated using TRIZOL reagent (Invitrogen) according to the manufacturer’s standard protocol, and mRNA was purified by oligotex (Qiagen). Microarray design The miRNA oligonucleotide microarray design was based on that of spotted OMAs by Liu et al. [7], with significant modifications. The mature miRNA sequences, which ranged from 19 to 24 nt, were too short, so two probes were designed for several miRNAs, one containing active sites that detected both the mature and the precursor forms (probe a), while the other did not contain the active sites located in the precursor (probe b). An oligo probe was designed that was not homologous to any human sequence and was used as normalization control (control oligo); the sequence was 5′ ATGTCATCTTGCGCGGCAGCTCGTCGACCGTGGCGAGAGT GTCTCGTCGATCATC 3′. All oligos were 40 nt long. In theory, the mature miRNA expression level can be determined by subtracting the (a) signal from the (b) signal. Nine probes for nine tRNA genes were used as positive controls and six probes for six types of miRNA genes from Arabidopsis thaliana were used as negative controls. Microarray fabrication All probes were dissolved in 150 mM phosphate acid buffer (pH 7.5–8.0) to a final concentration of 25 pmol/μl. Then the control oligo was added to each miRNA probe at 2 pmol/μl. The OMAs were spotted by a GeneMachine OmniGrid 100 Microarrayer in a 1×4 pin and 9×8 spot configuration for each subarray with triplicates. The spotting conditions were 75% humidity and 20°C. After spotting, slides were hydrated overnight in saturated salt solution and then crosslinked with UV light at 600 mJ/cm2 (UVP CL1000). Sample labeling The cDNA was labeled during first strand synthesis by using a fluorescence-tagged (Cy5) random octameric primer. Briefly, 10 μg total RNA and 1 μg random primer were mixed and incubated at 70°C for 10 min, then 5 × first-strand buffer, 0.1 M DTT, 5 mM unlabeled dNTP mix, Cy5-dCTP, RNA inhibitor, and Superscript II (200 U/μl) were added and incubated at 42°C for 2 h, then denatured at 70°C for 10 min. NaOH was added to hydrolyze RNA to stop the reaction of reverse transcription, and then HEPES was added to neutralize it. The labeled cDNA was purified by using the QIAquick Nucleotide Removal Kit (Qiagene). Microarray hybridization The labeled cDNAs and Cy3-tagged oligonucleotides complementary to the control probes were dissolved in 6 × SSPE/5 × Denhardt hybridization buffer and were hybridized with the miRNA oligonucleotide microarray for 16 h at 42°C. Then the slides were washed with buffer I (2 × SSC/0.5% SDS) for 15 min at 42°C, buffer II (1 × SSC/0.1% SDS) for 10 min at 42°C, buffer III (0.1 × SSC) for 5 min at room temperature, dipped in double-distilled water for 1 min at room temperature, and then dried. The slides were scanned by an Agilent scanner (G2565AA) at 535 and 635 nm. Statistical analysis The images were split into two, Cy3 and Cy5 channels, and each channel was imported into the Imagene Software 7.0 to read the signal value. The Cy3 signal was used as reference for the spot size of each miRNA oligo on the slides. The expression level of each miRNA in the sample labeled by Cy5 was normalized by a median method according to the Cy3 signal between two microarrays. So, the Cy5 signal, after normalization, gave the expression level of each miRNA. Clustering was carried out by Genespring Software 8.0 according to Cy5 intensity. Northern blot analysis Forty micrograms of total RNA from each sample was separated on 15% acrylamide denaturing gels (8 M urea) and then transferred to Hybond N+ membranes (Amersham) by electrophoresis for Northern blots. The filters were crosslinked with 150 mJ of UV (Bio-Rad) and baked at 80°C for 1 h. The specific oligo probes complementary to the corresponding miRNAs were labeled at the 5′ end by using T4 polynucleotide kinase with 32P-γ-ATP (Amersham). The sequence list of probes for Northern blots were: miR-92-2: 5′- CAGGCCGGGACAAGTGCAATA-3′; miR-9: 5′- TCATACAGCTAGATAACCAAAGA-3′; miR-9*: 5′-ACTTTCGGTTATCTAGCTTTA-3′; miR-15a: 5′- CACAAACCATTATGTGCTGCTA-3′; miR-17: 5′- ACAAGTGCCTTCACTGCAGT-3′; miR-20: 5′-CTACCTGCACTATAAGCACTTTA-3′; miR-106a: 5′- GCTACCTGCACTGTAAGCACTTTT-3′, and U6: 5′-CGTTCCAATTTTAGTATATGTGCTGCCGAAGCGA-3′ [10]. U6 on the membrane served as loading control. Prehybridization and hybridization were carried out using ExpressHyb Hybridization Solution (Clontech) according to the manufacturer’s instructions. Membranes were washed at room temperature, twice with 2 × SSC, 0.1% SDS and twice with 0.5 × SSC, 0.1% SDS. The blots were exposed on Molecular Dynamics Phosphorimager screens and signals were quantified using ImageQuant (Molecular Dynamics). For reuse, blots were stripped by boiling in 0.5% SDS for 20 min and scanned on Phosphorimager screens. Blots without radioactive signals were re-hybridized and re-used up to six times without influencing the quality of radioactive signals. Results MiRNA oligo nucleotide microarray construction We designed 243 oligonucleotide probes and covered 158 human miRNAs from http://microrna.sanger.ac.uk/cgi-bin/sequences/browse.pl and from publications. Nine tRNAs served as positive controls. The oligonucleotide probes were 40 nt in length. For 67 miRNAs, two different probes were designed, one containing the active site and the other specific for the precursor. Using this strategy, we were able to analyze the miRNA and pre-miRNA in the same experiment. A control oligo probe, which was not homologous to any human gene sequence, was designed for spotting and quality control. All miRNA probes were dissolved in phosphate buffer at 25 μmol/ml and the control probe was mixed with each miRNA probe at 2 μmol/ml. The microarray slides were printed on an Ominigride 100 machine (Gene Machine). Each oligo probe was spotted in triplicate. To develop the optimal conditions for the OMA, we compared mRNA and total RNA as the starting sample. Two micrograms of mRNA and 10 μg of total RNA were separately labeled during the reverse transcription reaction and hybridized to the OMA. The results indicated that mRNA had a relatively low signal compared to the total RNA, suggesting that mRNA had little influence on the results (Fig. 1d), so total RNA could be used for the microarray experiment. The microarray hybridization time was tested at 4, 6, and 16 h. The hybridization signals at 6 h were considerably higher than those at 4 h, while the signals at 16 h were only slightly higher than those at 6 h (Fig. 1a). To test the OMA sensitivity, quantities of total RNA ranging from 5 to 20 μg were labeled and then hybridized to the OMA (Fig. 1c). The strongest signal was obtained at 10 μg total RNA. To find the optimal temperature, we tested hybridization at 42, 50, and 55°C. The signal was very low at 50 and 55°C (Fig. 1b). From the above results, we chose 10 μg total RNA and 42°C hybridization for 16 h in all OMA experiments. Fig. 1miRNA oligonucleotiede microarrary construction. a The signal at hybridization times of 6 and 16 h was much higher than that at 4 h. b A hybridization temperature of 42°C was optimal for the microarray. c On testing quantities of total RNA from 5 to 20 μg, the signal was highest at 10 μg. d Comparison of total RNA and mRNA as the starting sample. The 100 highest signal pairs were chosen, and signal values greater than 3,000 were shown as 3,000. The results indicated that mRNA had little influence on the signal, so total RNA could be used as the starting material Distinct miRNA profiling in different organs during human development Total RNAs of samples from human fetal organs at G12w and G24w were labeled during reverse transcription. The labeled cDNAs hybridized to the OMA. After data processing, we found that 72–83% of the miRNAs were expressed in human fetal organs, in which the most miRNAs were expressed in G24w cerebrum. Distinct miRNA expression patterns were found in different organs at each developmental stage (Fig. 2a). Some miRNAs were seen in all samples from both embryonic stages (e.g., let-7d, miR-193, miR-7-3, miR-185, and miR-328, among others); they represent a type of restricted spatial and temporal expression pattern. These miRNAs were uniformly expressed over time, which suggests more general roles in gene regulation. Fig. 2Profiles of miRNome expression in human G12w and G24w fetal organs. a Distinct patterns of miRNA expression in different human fetal organs (abbreviation listed below). All of the data represent the average of at least three replicates from the same organ. b The same G24w heart sample triplicate chip results showed good reliability. Each result was from three replicates of the array. c Three stage-specific miRNAs, miR-92-2, miR-25, and miR-321, were expressed in G24w and G12w liver and lung. The bar represents the microarray signal intensity from 1,000 to 10,000. The blue line on the left indicates that the four miRNAs were clustered by cluster software analysis. C cerebrum, Hr heart, K kidney, Li liver, Lu lung, O ovary, P pancreas, S spleen, Vc cervical spinal cord, Vl lumbar spinal cord, Vs sacral spinal cord, Vt thoracic spinal cord To test the replicability of the microarray, the G24w heart sample was labeled and hybridized in triplicate. The results from different detection batches were highly reproducible (Fig. 2b). Similar miRNA expression patterns were seen in samples from developmentally proximal organs, indicating that a miRNA expression profile can be a marker of developmental stage in organs originating from the same endodermal layer. Three different miRNAs, miR-92-2, miR-25, and mirR-321, were predominantly expressed in liver and lung at G24w compared with the same organs at G12w (Fig. 2c). As an indicator of miRNA expression level, the color of samples from G24w organs was brighter than those from G12w organs. So, the miRNA expression profile can be used as a biomarker of developmental stage. CNS specifically and higher expressed microRNAs In our study, we found four CNS specifically expressed microRNAs, miR-9, miR-9*, miR-124a, and miR-125b, in which miR-124a and miR-125b are expressed higher in G24w cerebrum than in G12w. At the same time, miR-15a, miR-106a, and miR-17–92 cluster members were found expressed relatively higher in CNS tissues than other tissues. To validate the reliability of the microarray data, we selected seven CNS specifically and higher expressed miRNAs and designed specific probes for Northern blot analysis. The miRNAs were: miR-9, miR-9*, miR-15a, miR-106a, and miR-17–92 cluster members including miR-17, miR-20 and miR-92-1, which are located in the genomic site of both terminals and in the middle of the cluster. We found good consistency between the Northern blot and microarray data, as shown by the results from the selected miR-15a and miR-106a (Fig. 3). Fig. 3Expression of miR-15a and miR-106a, detected by Northern blot. were in accord with the signals detected by microarray. The abbreviations are as in the legend of Fig. 2. The miR-15a and miR-106a are shown on the left, indicating the corresponding expression detected by Northern blot. The microarray results are presented numerically, indicated by Oligo. U6 snRNA detected by Northern blot was used as detection control MiR-9, miR-9*, miR-124a, and miR-125b known to be specifically expressed in rat nervous system, are also only expressed in the human fetal nervous system found by microarray and Northern blot at the same time (Fig. 4). Analysis of the array results indicated that miR-9 and miR-9* probably originated from the expressed pre-mi-RNA of chromosome 5 and may play key roles in human nervous system development. So it can be concluded that miRNA microarrays can identify different pre-miRNA origins by using different oligo probes. Fig. 4miR-9 and miR-9* were expressed specifically in the human nervous system. a miR-9 and miR-9* can be expressed from human chromosomes 1, 5, and 15 and form three types of pre-miRNA. The secondary structures of pre-miRNAs from the Sanger miRNA register website were predicted with mfold software. The pre-miRNAs can be excised by Dicer into the same mature miRNAs—miR-9 and miR-9*. b Northern blot results probed with miR-9 and miR-9*. The abbreviations are as in the legend of Fig. 2. The microarray results are presented numerically, indicated by Oligo. U6 snRNA detected by Northern blot was used as detection control Members of the miR-17–92 cluster, which contains six pre-miRNAs within about 1 kb on human chromosome 13, share the same expression profile [11]. The microarray and Northern blot results showed that these six miRNAs had the same expression pattern (Fig. 5), suggesting that clustered miRNAs have the same transcript and share the same promoter element. Fig. 5Co-expressed miR-17-92 cluster miRNAs. a The three known human miRNA clusters. The miR-17–92 cluster contains six pre-miRNAs within about 1 kb on chromosome 13. b The miR-17, miR-20, and miR-92-1 expression profiles detected by Northern blot (the name of the miRNA and pre-miRNA are given on the left and the abbreviations are as in the legend of Fig. 2.) and microarray (results given numerically and marked as miR-17-oligo, miR-20-oligo, and miR-92-1-oligo). U6 snRNA detected by Northern blot was used as detection control Discussion The small size of miRNAs requires more sensitive tools for quantitative analysis. Although the optimized method of RT-Q-PCR can indirectly detect mature miRNAs [12], the efficiency of detection is relatively low. Currently, the most reliable method for the study of miRNA expression is Northern blot analysis with polyacrylamide gels. This method can distinguish pre-miRNA and miRNA at the same time, although the technique is relatively insensitive owing to the large total RNA volume needed, and it is labor-intensive. The miRNA oligonucleotide microarray provides a novel method to carry out genome-wide microRNA profiling in human samples. We used total RNA as the sample for the microarray test, not just labeling filtered low molecular weight RNA, which could change the ratio of pre-miRNA to miRNA. So the profile we generated was that of pre-miRNAs and miRNAs. Owing to its high throughput and small sample requirement, the miRNA OMA can be used as screening method in miRNA research. Some microRNAs are within the introns of host genes. Intronic miRNAs are usually expressed in coordination with their host gene mRNA, suggesting that they are generally derived from a common transcript [13]. Some human microRNAs are even processed from capped, polyadenylated transcripts and can function as mRNAs [14]. Therefore, recognition of these miRNA gene families should help in the identification of putative mRNA targets and in understanding the pathways of miRNA biogenesis. Through GeneCluster software analysis, we found that miR-17, miR-18, miR-19a, miR-19b, miR-20, and miR-92-1 form a cluster. Based on the bioinformatics study and previous work, we attempted to verify the hypothesis that the miR-17–92 cluster may share the same expression unit. We searched for the genome location and possible co-expressed mRNA and found the six pre-miRNAs within about 1 kb on human chromosome 13; the possible co-expressed mRNA is human chromosome 13 open reading frame 25 (C13 orf25), transcript variant 2 mRNA, indicating that the miR-17–92 cluster members are intronic miRNAs. Analysis of clustered miRNA expression profiles suggested that the six clustered miRNAs may have the same promoter element. In our study, we found that four miRNAs were only expressed in the human fetal nervous system, indicating that they may play important roles in human nervous system development. Before our study, Krichevsky et al. found miR-9 and miR-9* specifically expressed in mouse brain, and they were de-regulated in presenilin-1 null mice, which exhibited severe developmental defects of the brain [5]. MiR-9 and miR-9* may modulate critical development processes in human brain development and changes in stage and level of expression may induce major developmental errors. Giraldez et al. showed that miR-430 regulates brain morphogenesis in zebrafish and MZdicer mutants undergo axis formation and differentiate multiple cell types but display abnormal morphogenesis during gastrulation, brain formation, somitogenesis, and heart development. Injection of miR-430 rescues the brain defects in MZdicer mutants, revealing essential roles for miRNAs during morphogenesis [15]. No human miR-430 is registered online at present, but miR-17, miR-20, and miR-106a have the same sequence at nucleotides 2–8. Giraldez thought this is most important for recognition. In our study, members of the miR-17–92 cluster were highly expressed in the nervous system, but no human miRNA expression homologous to miR-430 was detected by Northern blot with a pre-miR-430 probe (data not shown). In humans, it is not miR-430 that plays a critical role in nervous system morphogenesis. So these results indicated that there are differences in the mechanisms of brain morphogenesis between human and zebra fish. This raises the question of whether the specifically expressed miR-9, miR-9*, and higher expressed miR-17–92 cluster are functionally linked, or perhaps this just reflects higher nonspecific Dicer activity. He et al. compared B-cell lymphoma samples and cell lines to normal tissues and found that the levels of the primary or mature miRNAs derived from the miR-17–92 locus are often substantially increased in these cancers, implicating the miR-17–92 cluster as a potential human oncogene [16]. O’Donnell et al. found that c-Myc-regulated miR-17 and miR-20 modulate E2F1 expression [17]. These findings indicate that the miR-17–92 cluster may be a common channel to regulate cell differentiation.

J_Chem_Ecol-4-1-2239250

Performance of Generalist and Specialist Herbivores and their Endoparasitoids Differs on Cultivated and Wild Brassica Populations

Through artificial selection, domesticated plants often contain modified levels of primary and secondary metabolites compared to their wild progenitors. It is hypothesized that the changed chemistry of cultivated plants will affect the performance of insects associated with these plants. In this paper, the development of several specialist and generalist herbivores and their endoparasitoids were compared when reared on a wild and cultivated population of cabbage, Brassica oleracea, and a recently established feral Brassica species. Irrespective of insect species or the degree of dietary specialization, herbivores and parasitoids developed most poorly on the wild population. For the specialists, plant population influenced only development time and adult body mass, whereas for the generalists, plant populations also affected egg-to-adult survival. Two parasitoid species, a generalist (Diadegma fenestrale) and a specialist (D. semiclausum), were reared from the same host (Plutella xylostella). Performance of D. semiclausum was closely linked to that of its host, whereas the correlation between survival of D. fenestrale and host performance was less clear. Plants in the Brassicaceae characteristically produce defense-related glucosinolates (GS). Levels of GS in leaves of undamaged plants were significantly higher in plants from the wild population than from the domesticated populations. Moreover, total GS concentrations increased significantly in wild plants after herbivory, but not in domesticated or feral plants. The results of this study reveal that a cabbage cultivar and plants from a wild cabbage population exhibit significant differences in quality in terms of their effects on the growth and development of insect herbivores and their natural enemies. Although cultivated plants have proved to be model systems in agroecology, we argue that some caution should be applied to evolutionary explanations derived from studies on domesticated plants, unless some knowledge exists on the history of the system under investigation. Introduction The occurrence of pests in agroecosystems has long promoted the study of insect–plant interactions in crop plants, such as cabbage, lima bean, maize, cotton, and tomato (Takabayashi et al. 1994; Turlings et al. 1995; De Moraes et al. 1998; Geervliet et al. 2000; Thaler et al. 2001). Studies with crop plants have generated a wealth of data, highlighting a number of important mechanisms that influence the structure and function of multitrophic interactions and communities (Root 1973; Sheehan 1986; Khan et al. 1997; Gols et al. 2005). However, critics have argued that the biology and ecology of crop plants is often dramatically different from wild populations, thus bringing into some question the evolutionary relevance of the conclusions generated from data that rely on crop plants (Benrey et al. 1998; van der Meijden and Klinkhamer 2000). For instance, plant breeding programs have been reported to disrupt the original plant defense strategies that were present in the wild progenitors of cultivated species (Evans 1993). Artificial selection of some crop plants, aimed at accentuating a specific plant trait or group of traits (e.g., the production of edible structures), has been shown to reduce the level of undesired constituents, such as defense compounds, while enhancing others (such as primary metabolites including proteins and sugars). Many of the undesired secondary plant compounds (SPC) are known to have evolved and function as putative defenses against herbivores, whereas the desired primary plant compounds act as nutrients and thus may actually enhance the performance of herbivores (Schoonhoven et al. 2005). Levels of SPC are dynamic and vary with such factors as season, soil conditions, and leaf age (reviewed by Schoonhoven et al. 2005). Moreover, plants may increase their levels of defenses in response to feeding damage (Karban and Baldwin 1997; Agrawal 1999a), which may reduce the costs of defenses by avoiding the allocation of resources to defense when the attacker is absent. Secondary plant compounds have also been shown to affect negatively the development of higher trophic levels that attack these herbivores, such as predators, parasitoids, and even hyperparasitoids (Barbosa et al. 1986, 1991; Francis et al. 2001; Harvey et al. 2003, 2005, 2007; Ode et al. 2004). Consequently, changes in plant chemistry, mediated by artificial selection, may influence the behavior and development of consumers over several trophic levels, and this may ultimately lead to broader effects on the communities associated with these plants (Harvey et al. 2003; Ode 2006). Most importantly, in wild plants, defense mechanisms have not been constrained by the “directional selection” that characterizes many crop plants. Therefore, to understand the evolution of plant defenses against insect herbivores, multitrophic interactions should also be studied in wild conspecifics of the cultivated plant species where plant defenses are the likely result of a range of biotic and abiotic selection pressures. One appropriate plant family for studying the effects of artificial versus natural selection on multitrophic interactions is the Brassicaceae, which contains such important crops as cabbages and various types of mustard (Gómez-Campo and Prakash 1999). Of all plants that have been domesticated, few have been manipulated to produce so many different cultivars as Brassica oleracea L. (e.g., cabbage, broccoli, cauliflower, and Brussels sprout; Gómez-Campo and Prakash 1999). Wild types of B. oleracea grow naturally along rocky coastlines of Britain and France (Mitchell and Richards 1979). It has been speculated that the wild populations in the UK are derived from plants that were cultivated by the Greeks and Romans in the Mediterranean region between 1,000 and 2,000 BC (Mitchell 1976). These early cultivated forms were introduced to Britain, but have been naturalized for centuries (Mitchell 1976). However, more recent evidence points also at an Atlantic origin of domestication (Song et al. 1990). Plants in the Brassicaceae characteristically produce secondary metabolites called glucosinolates (hereafter GS) (Fahey et al. 2002). After tissue damage, myrosinases catalyze the hydrolysis of GS into (iso)thiocyanates and nitriles (Mithen 2001; Fahey et al. 2002), which play a role in defense against insect herbivores (Rask et al. 2000). Generalist herbivores produce enzymes that can detoxify a wide range of substrates (Krieger et al. 1971), whereas specialists have evolved enzyme systems that can detoxify specific plant compounds that are associated with herbivore diet (e.g., Johnson 1999; Ratzka et al. 2002). Thus, generalist herbivores are usually more sensitive to high levels of specific allelochemicals compared to specialists. (see e.g., Blau et al. 1978; Giamoustaris and Mithen 1995). Specialist feeding on brassicaceous plants are adapted to plants containing GS, and they detoxify, excrete, or even sequester these harmful metabolites (Müller et al. 2001; Ratzka et al. 2002; Wittstock et al. 2004). Moreover, some insects use these compounds as indicators of food plant suitability (Nayar and Thorsteinson 1963; Renwick and Lopez 1999). Not all GS are equally effective as stimulants, and high levels of GS can reduce the performance of herbivores that are specialized on brassicaceous species (Stowe 1998; Li et al. 2000; Traw and Dawson 2002; Agrawal and Kurashige 2003). In addition, GS concentrations can increase in response to herbivore feeding damage (Bodnaryk 1992; Agrawal 1999b) and negatively affect subsequent herbivory by both generalists and specialists (Agrawal 1999b; Bartlet et al. 1999; Traw and Dawson 2002). This study compares the development of several species of herbivores and endoparasitoids when reared on three Brassica populations that differ in their degree of domestication. Insects were reared on a cultivated and a wild population of B. oleracea, and a recently escaped (feral) Brassica species. Levels of GS were measured as indicators of direct plant defense. Initially, the development of two specialists on Brassicaceae, Plutella xylostella L. (Lepidoptera: Plutellidae) and Pieris rapae L. (Lepidoptera: Pieridae), and a generalist herbivore, Mamestra brassicae L. (Lepidoptera: Noctuidae), were examined when reared on the three populations. Finally, the development of a specialist and generalist parasitoid reared on the same host, P. xylostella, were compared. Separate cohorts of P. xylostella were parasitized by two species of endoparasitoids, Diadegma semiclausum Hellén (Hymenoptera: Ichneumonidae) and a related species, D. fenestrale Holmgren (Hymenoptera: Ichneumonidae). These two parasitoids differ in host specialization, with D. semiclausum restricted to P. xylostella and D. fenestrale attacking several other hosts that feed on non-brassicaceous species (Legaspi 1986; Azidah et al. 2000). The following hypothesis was tested: specialist herbivores and parasitoids are less affected than generalists by differences in host plant chemistry between various Brassica populations that differ in their degree of domestication. It is proposed that changes in plant biology via domestication have significant effects on community level interactions and processes. Methods and Materials Plants The B. oleracea variety gemmifera (Brussels sprout) cv. Cyrus was used. Compared to other vegetable crops of B. oleracea, Brussels sprout cultivars contain relatively high levels of GS (Kushad et al. 1999; Rosa 1999), but considerably lower levels than the wild B. oleracea populations in Dorset, Great Britain (Moyes et al. 2000; Gols et al. 2008). Seeds from several plants (>10) were collected from a wild population of B. oleracea growing on chalk cliffs along the south coast of Great Britain, near Swanage, Dorset (“Old Harry,” 50°38′N, 1°55′E). This population contains intermediate levels of GS compared to other Dorset wild populations (Moyes et al. 2000). A feral Brassica population, which was found in a roadside hollow about 15 km east of Wageningen (51°95′N, 5°78′E, The Netherlands), was also included. In addition to comparing the development of different herbivores, we also compared the development of a specialist and generalist parasitoid reared on the same host (see section on Plutella xylostella and Diadegma species). To discriminate between food-plant quality mediated through the host and host quality itself, a second closely related wild brassicaceous plant species, black mustard, Brassica nigra L., was included in one of the experiments. Seeds of B. nigra were collected from a natural population growing in a small patch along the River Rhine, near Wageningen, The Netherlands (51°94′N, 5°62′E). Seeds from the different populations were germinated in the first week of March 2005. Seedlings were transferred to 1.1 l pots filled with potting soil (“Lentse potgrond” no. 4, Lent, The Netherlands). Plants were grown in a greenhouse at 20–30°C, 40–80% r.h, with a photoperiod of at least 16 hr. If the light dropped below 500 μmol photons/m2/sec during the 16-hr photoperiod, supplementary illumination was supplied by high-pressure mercury lamps. Plants were watered daily. After the plants were 4 wk old, they were fertilized once a week with Kristalon Blauw (N–P–K) 19–6–20–3 micro (2.5 mg/l), which was applied to the soil. B. oleracea plants were 7 wk old when they were used in experiments and attained similar amounts of biomass (25–30 g per plant). Plants from all three populations were in the vegetative state and developed new leaves during the experiments. Fertilization and watering continued during the experiments. Brassica nigra plants were 5 wk old and were not fertilized because the soil still contained enough nutrients for optimal growth. B. nigra matures much faster than B. oleracea. Insects All insects used originated from cabbage fields in the vicinity of Wageningen. Cultures of all the herbivores have been maintained in the laboratory on Brussels sprouts cv. Cyrus for many years in climate rooms at 22 ± 2°C, 40–80% r.h, with a light regime of 16:8 L/D. The two parasitoid species were collected in the summer of 2004 and were thereafter reared on plants heavily infested with P. xylostella larvae for several generations. After pupation on the walls of the rearing cage, parasitoid cocoons were carefully removed and transferred to a clean cage. Emerged adult wasps were provided with water and honey ad libitum. For parasitism, we used females that were 5 to 10 d old after adult emergence. Glucosinolate Analyses As an indicator of direct defense, GS concentrations in leaf tissues of B. oleracea were measured. Leaf samples were taken during the performance experiments (see below) from three treatment groups: plants that were undamaged, plants damaged by unparasitized P. xylostella, and plants damaged by larvae that had been parasitized by D. semiclausum. When leaf samples were taken, the damaged plant groups had been exposed to herbivore feeding for 7 d. Undamaged control plants were maintained in the same greenhouse, but were physically separated from the plants with caterpillars. Larvae, feces, and pupae were removed from leaves. All fully developed leaves were harvested with the exception of the oldest leaves, which had turned yellow and did not contain feeding damage. Leaves were removed with a razor blade, pooled per plant, and stored at −80°C. Samples were later freeze-dried and pulverized with a mortar and pestle. Fifty milligram aliquots of freeze-dried material were weighed in 2-ml centrifuge tubes. GS were extracted and purified as described in van Dam et al. (2004) and were separated on a reverse phase C-18 column (Alltima C-18, 3 μm,150 × 4.6 mm, Alltech, Deerfield, IL, USA) on HPLC (Dionex, Sunnyvale, CA, USA) with an acetonitrile water gradient. Detection was performed with a DIONEX PDA-100 Photodiode array detector set to scan from 200 to 350 nm. For quantification, sinigrin (Sigma, St. Louis, MO, USA) was used as an external standard. Peaks were integrated at 229 nm, for which standard response factors have been defined (EC 1990). The different GS were identified based on their retention times, and UV spectra were compared to those of pure compounds (sinigrin, Sigma, St. Louis, MO, USA; glucotropaeolin and glucobrassicin were kindly provided by M. Reichelt, Max Planck Institute for Chemical Ecology, Jena, Germany), or compared to a certified oil seed reference (EC Community Bureau of Reference BCR-367R, Fluka, Buchs, Switzerland). Insect Performance To investigate the effect of domestication on plant direct defenses, the different herbivores and parasitoids (see below) were reared on the three plant populations. For all insects, egg-to-adult development time, adult dry mass, and survival (to adult) were determined when reared on the different populations. Adult dry mass was obtained by weighing adults on a Cahn C-33 microbalance (Cahn Instruments, Cerritos, CA, USA) that had been dried to constant weight at 80°C (3 d). Plants with insects were maintained in a greenhouse under the same conditions as described in the Plant section. Plants of the same population that received the same insect treatment were placed together, and caterpillars were allowed to develop and move around freely on plants until they reached the final instar. Different herbivore treatments were randomly positioned in a greenhouse, but were all placed in a similar position relative to the light sources to minimize microclimatic differences among plant populations and treatments. Plutella xylostella and Diadegma Species To obtain eggs of P. xylostella, more than 150 adult moths were released with a 50:50 sex ratio in a plastic cage (37 × 40 × 30 cm). Folded strips of Parafilm served as substrate for females to lay eggs on. Females were allowed to oviposit on the Parafilm overnight. Subsequently, the strips with eggs were incubated for 4 d at 22°C until the eggs hatched. Pieces of Parafilm with neonate larvae were placed on top of individual plants of each of the three plant populations. Larvae were allowed to feed on these plants until they reached the third instar (L3). For each plant population, one cohort of 60 larvae was transferred to new plants and served as an unparasitized control. A second cohort of 130 larvae was parasitized by D. semiclausum, and a third cohort of 180 larvae was parasitized by D. fenestrale. For parasitism, individual female wasps of both species were presented with a L3 P. xylostella host. A host was considered as parasitized when the female wasp was observed to insert into and remove her ovipositor from the larva. Individual female wasps were allowed to oviposit in up to 10 separate hosts. After this, they were removed. Parasitized larvae were transferred to new plants of the same population on which the larvae had fed previously. Five plants were used for the unparasitized controls and nine for each of the parasitoid treatments. The number of plants provided ample food for all larvae to complete their development. When caterpillars molted into L4, strips of corrugated cardboard were placed on top of the plants, as P. xylostella prefers to pupate in secluded areas. After pupation, cocoons were collected and stored in labeled vials until adult emergence. When the moths or wasps emerged, the time of eclosion and sex were recorded. Individuals were killed by freezing at −20°C and stored for dry mass determination. Vials with cocoons ready to emerge were checked every 2 hr. Development time for P. xylostella was measured in full days, as the exact time of oviposition had not been recorded. In the case of the two Diadegma species, the median time point of the period needed to parasitize the hosts (3–4 hr) was used as the time of oviposition. To further investigate whether food plant quality or host quality was a more important factor in the development of D. fenestrale, the experiments described above with P. xylostella were repeated on a second (and closely related) wild brassicaceous species, B. nigra. A separate study (Gols et al. unpublished) has shown that B. nigra is a qualitatively superior plant for the development of P. xylostella, compared with B. oleracea. We reared 33 unparasitized larvae on three B. nigra plants, and 180 larvae parasitized by D. fenestrale on 10 plants. We recorded egg-to-adult development time, adult biomass, and survival as before. The plants provided ample food for all the larvae to complete their development. Pieris rapae Neonate larvae were obtained from the general culture and transferred to seven plants of each population with a distribution of six larvae per plant. When larvae had developed into L5, they were transferred to plastic containers that contained some leaf material from the plants they had fed on previously. After pupation, pupae were collected and placed in new plastic containers lined with filter paper. At adult emergence, the time of eclosion and sex were recorded, and the individuals were killed by freezing, followed by dry mass determination (as above). Containers with pupae ready to emerge were checked every 2 hr. Development time was measured in full days, as the exact time of oviposition had not been recorded. Mamestra brassicae Like P. xylostella, adult M. brassicae are primarily nocturnal. Females do not need plants as an oviposition substrate and readily lay batches of eggs onto the surface of paper. From the general culture, we obtained paper sheets with M. brassicae eggs that were laid the previous night. These sheets were incubated at 22 ± 2°C (5 d) until the eggs hatched. Neonate larvae were transferred to 10 plants of each population, with a density of five larvae per plant. Once they had reached late L5, M. brassicae larvae were collected from the three populations, counted, and transferred to plastic containers (15 × 12 × 6 cm) that contained 2 cm of potting soil mixed with vermiculite (1:1) and some leaf material from the plant on which they had been feeding previously. After the larvae had pupated, they were collected and placed in new plastic containers filled with a layer of vermiculite. At moth emergence, the date of eclosion was recorded, and the individuals were killed by freezing, followed by dry mass determination. Containers with pupae ready to emerge were checked every 2 h. Development was measured in full days as the exact time of oviposition had not been recorded. Statistical Analysis Data on adult dry mass and development time were analyzed by using ANOVA with plant population and sex and their interaction as factors. All larvae within one plant population were considered as independent samples. The Tukey–Kramer method was used for multiple comparisons of the means. For each insect species, a G test for heterogeneity was performed on survival rates of the three plant populations with H0: survival on each of the three plant populations is equal. Concentrations of individual GS compounds were log(x+1) transformed to meet assumptions of normality. To examine differences in GS content, a Mixed Model was used with plant population and plant treatment (intact, damaged by unparasitized Plutella, damaged by parasitized Plutella) as the fixed factors in the model. There was no random factor in the analysis, and the estimation of effects in the model was based on restricted likelihood maximization. When the main factors or their interactions were significant, specific linear contrasts were applied to separate further factor levels. When necessary, correction for unbalanced sample sizes was carried out by using the Satterthwaite correction. Analysis was carried out with SAS 8.02 (1999–2001 ©SAS Institute, Inc). Results Glucosinolate Analyses GS analyses of leaf tissues revealed considerable quantitative and some qualitative variation among the different Brassica populations (Fig. 1). Three pentyl-derived (C5) GS, glucoalyssin, gluconapoleiferin, and glucobrassicanapin were only detected in the feral population, whereas the other 10 compounds were present in all three populations (Fig. 1). Total GS concentrations in undamaged plants were 3.2 and 1.4 times higher in plants of the wild population than in the cultivated and feral populations, respectively (Fig. 1). Furthermore, concentrations of all individual compounds were significantly different among the three populations (statistics not shown, but all significance levels were lower than 0.05). Fig. 1Glucosinolate (GS) concentrations (mean ± SE) in leaf tissues of a cultivated (a), feral (b), and wild (c) Brassica population. Concentrations were measured in leaf tissue from plants that were undamaged (black bars), damaged by unparasitized P. xylostella larvae (white bars) and damaged by parasitized (D. semiclausum) larvae (gray bars). GS abbreviations and scientific names: TOT total GS concentration, GBC glucobrassicin (= indol-3-ylmethyl GS), IBE glucoiberin (= 3-methylsulfinyl propyl GS), GNA gluconapin (= 3-butenyl GS), NEO neoglucobrassicin (= 1-methoxyindol-3-ylmethyl GS), RAP glucoraphanin (= 4-methylsulfinyl butyl GS), SIN sinigrin (= 2-propenyl GS), PRO progoitrin (= 2(R)-2-hydroxy-3-butenyl GS), GBN glucobrassicanapin (= 4-pentenyl GS), GNL gluconapoleiferin (= 2-hydroxy-4-pentenyl GS), ALY glucoallyssin (= 5-methylsulfinyl pentyl GS), 4OH 4-hydroxyglucobrassicin (= 4-hydoxyindol-3-ylmethyl GS), 4MeOH, 4-methoxyglucobrassicin (= 4-methoxyindol-3-ylmethyl GS), and NAS gluconasturcin (= 2-phenylethyl GS). ND not detectable Differences between the cultivated and feral populations on the one side, and the wild population on the other side, became even more pronounced after the plants were induced by larval P. xylostella feeding (Fig. 1). In the cultivated and feral plants, total levels of GS remained at similar levels before and after induction by P. xylostella feeding (cultivar: t50 = 0.82, P = 0.42; feral population: t50 = 0.39, P = 0.70), whereas in the wild population, concentrations were 1.5–2 times higher after herbivore feeding (t50 = 3.11, P < 0.001). Levels of individual GS changed differentially in response to herbivore feeding. The indole GS, glucobrassicin, was induced by P. xylostella feeding in all the plant populations (t50 = 6.90, P < 0.001). Moreover, glucobrassicin accounted for almost 70% of the GS composition in the wild population after induction, and for only 53% and 35% in the cultivated and feral population, respectively. In contrast, the relative amount of glucobrassicin in undamaged plants was only 21%, 5%, and 25% in the cultivated, feral, and wild populations, respectively. A second indole GS, neoglucobrassicin, was also induced in response to herbivory in the feral (t50 = 2.55, P = 0.01) and the wild population (t50 = 4.76, P < 0.001), but not in the cultivated population (t50 = 0.37, P = 0.71) in which levels of this compound were very low. Not all GS concentrations increased after herbivory. Sinigrin was reduced after P. xylostella larval feeding in the cultivated (t50 = 2.4, P = 0.02) and the wild population (t50 = 3.67, P < 0.001), but not in the feral population (t50 = 0.07, P = 0.95). Similarly, levels of glucoiberin decreased in response to P. xylostella feeding in the cultivar (t50 = 2.79, P = 0.007) and the wild population (t50 = 4.22, P < 0.001), but not in the feral population (t50 = 0.02, P = 0.99). In the feral population, both sinigrin and glucoiberin were present in much lower concentrations than in the other two populations (Fig. 1). In plants damaged by parasitized and unparasitized larvae of P. xylostella, concentrations of individual GS were not significantly different (statistics not shown, but all significance levels were lower than 0.05). Insect Performance: Herbivores In P. xylostella, plant population and sex had an effect on egg-to-adult development time (plant population: F2, 131 = 5.95, P = 0.003; sex: F1, 131 = 5.52, P = 0.02; Fig. 2a). Female P. xylostella developed faster than males; the fastest development time was observed for females reared on the cultivated and the feral population. For adult biomass, the interaction between plant population and sex was significant (F2, 132 = 11.1, P < 0.001). Plant population had a strong effect on female but not on male biomass (Fig. 2b). The heaviest females were recovered from the cultivar, and the lightest from the wild population. In contrast, males were significantly lighter than females (F1, 132 = 317, P < 0.001) and obtained similar biomasses on all three plant populations (Fig. 2b). For P. xylostella, plant population did not affect larval survival to the adult stage (χ2 = 0.96, df = 2, P = 0.62, Fig. 3). Fig. 2Egg-to-adult development time (a) and adult dry mass (b) of P. xylostella males (white bars) and females (gray bars) reared on either a cultivated, a feral, or wild Brassica population. Bars (mean ± SE) with different letters are significantly different from each other (Tukey multiple comparisons, α = 0.05). Numbers of individuals (N) were on the cultivar, escape, and wild population, respectively: males, 21, 22, and 31; females 23, 22, 18Fig. 3Larval to adult survival of two specialist herbivores, P. xylostella and P. rapae, and one generalist, Mamestra brassica, when reared on either a cultivated, feral or wild Brassica population. P. xylostella was also reared on a wild population of B. nigra Development time also varied with the population on which the P. rapae larvae had been reared (F2, 105 = 7.8, P < 0.001, Fig. 4a). Egg-to-adult development time of males was shortest on the cultivar, longer on the feral, and longest on the wild population (Fig. 4a). Males took longer to complete their development than females (F1, 105 = 7.5, P = 0.007). Plant population also had a significant effect on adult biomass (F2, 101 = 17.5, P < 0.001, Fig. 4b). Whereas adult biomass in P. rapae did not differ between the cultivated and the feral line, biomass of butterflies reared on the wild population was lower (Fig. 4b). On average, females were marginally heavier than males (F1, 101 = 3.2, P = 0.08). Irrespective of plant population, more than 92% of all P. rapae larvae successfully developed into adults, and survival rates were not significantly different (χ2 = 0.22, df = 2, P = 0.90, Fig. 3). Fig. 4Egg-to-adult development time (a) and adult dry mass (b) of P. rapae males (white bars) and females (gray bars) reared on either a cultivated, feral, or wild Brassica population. Bars (mean ± SE) with different letters are significantly different from each other (Tukey multiple comparisons, α = 0.05). Numbers of individuals (N) were on the cultivated, feral, and wild population, respectively: males, 22, 10, and 19; females 16, 20, 20 In the case of the generalist herbivore, M. brassicae, the effect of host-plant population on adult biomass was more pronounced compared to the two specialists. It is difficult to determine the sex of adult moths, therefore, the data were pooled. Adult mass on the cultivated line was twice as high, compared to the wild population, and was also significantly higher on the feral population (F2, 49 = 8.28, P < 0.001, Fig. 5b). Plant population did not affect development time (F2, 49 = 0.33, P = 0.72, Fig. 5a). Unlike the two specialists, survival of M. brassicae was affected by plant population (χ2 = 20.4, df = 2, P < 0.001, Fig. 3). The percentage of M. brassicae larvae that developed successfully into adults was highest on the cultivated population (58%), slightly lower on the feral population (42%), and the smallest (4%) on the wild population. Fig. 5Egg-to-adult development time (a) and adult dry mass (b) of M. brassicae reared on either a cultivated, feral, or wild Brassica population. Bars (mean ± SE) with different letters are significantly different from each other (Tukey multiple comparisons, α = 0.05). Numbers of individuals (N) were on the cultivated, feral, and wild population, respectively: 21, 29, and 2 Insect Performance: Parasitoids In the specialist parasitoid, D. semiclausum, plant population had an effect on egg-to-adult development time (F2, 275 = 6.49, P = 0.002, Fig. 6a). The parasitoid developed fastest on the feral population and developed more slowly on the cultivated and wild populations of B. oleracea (Fig. 6a). Egg-to-adult development time was longer in females than in males (F1, 275 = 13.0, P < 0.001). Furthermore, plant population had an effect on adult biomass in D. semiclausum, (F2, 277 = 11.3, P < 0.001, Fig. 6b). The heaviest D. semiclausum wasps emerged from hosts that were reared on the cultivated population, whereas the lightest emerged from host reared on the wild and feral populations. D. semiclausum females were heavier than males (F1, 277 = 57.4, P < 0.001). Between 67 and 80% D. semiclausum successfully completed development to eclosion on the three Brassica populations (Fig. 7). Survival rates were not significantly different on the three plant populations (χ2 = 3.77, df = 2, P = 0.15). Fig. 6Egg-to-adult development time (a) and adult dry mass (b) of D. semiclausum males (white bars) and females (gray bars) reared on P. xylostella feeding on either a cultivated, feral, or wild Brassica population. Bars (mean ± SE) with different letters are significantly different from each other (Tukey multiple comparisons, α = 0.05). Numbers of individuals (N) were on the cultivated, feral, and wild population, respectively: 87, 69, and 81 for males and 11, 12, 10 for femalesFig. 7Egg-to-adult survival of a specialist parasitoid, D. semiclausum, and a generalist parasitoid, D. fenestrale, when reared from the host, P. xylostella, on either a cultivated, feral, or wild Brassica population. D. fenestrale was also reared from P. xylostella on a wild population of B. nigra As with D. semiclausum, egg-to-adult development time in D. fenestrale varied with plant population (F2, 69 = 5.27, P = 0.007, Fig. 8a). However, dry mass in male D. fenestrale wasps did not vary significantly with the population on which the hosts had been reared (F2, 69 = 0.25, P = 0.78, Fig. 8b). As only thirteen D. fenestrale females in total successfully developed, data on females were excluded from the analysis and are not presented in the figures. The most dramatic effect of plant population was on the survival of D. fenestrale (Fig. 7), which was significantly different for the three plant populations (χ2 = 12.2, df = 2, P = 0.002). Only 9% of the parasitized hosts reared on the wild population successfully produced D. fenestrale wasps. By contrast, 33% survived on the cultivar and 16% on the feral population. Moreover, the lowest number of surviving D. fenestrale parasitoids, eight out of 172 (or 4.6%), was obtained on B. nigra. Male wasps (N = 5) developing in hosts reared on B. nigra plants were lighter (0.432 ± 0.033 mg, mean ± SE) and developed slower (17.8 ± 0.37 d) than males reared from hosts on B. oleracea (see Fig. 6). In contrast, healthy P. xylostella moths performed better on B. nigra than on B. oleracea, in terms of survival (97%, Fig. 3) and adult mass, 1.985 ± 0.068 mg (N = 16) and 1.104 ± 0.068 mg (N = 16), for females and males, respectively (see also Fig. 2b). However, development time, 17.8 ± 0.26 d for both female and male moths, was slightly longer (see also Fig. 2a). Fig. 8Egg-to-adult development time (a) and adult dry mass (b) of D. fenestrale males reared on P. xylostella feeding on either a cultivated, feral, or wild Brassica population. Bars (mean ± SE) with different letters are significantly different from each other (Tukey multiple comparisons, α = 0.05). Numbers of individuals (N) were on the cultivar, escape, and wild population, respectively: 44, 18, and 14 Discussion Through artificial selection via domestication, levels of primary and secondary compounds in domesticated plants are often altered compared with their progenitors. The results of this study revealed that GS concentrations in leaf tissue varied significantly among the three different plant populations. Much higher concentrations of GS were recorded in wild B. oleracea than in cultivated and feral population. GS levels in the wild population studied in this paper were similar to concentrations reported earlier in other wild populations of B. oleracea (Mithen et al. 1995; Moyes et al. 2000). The most striking differences in GS concentrations were observed after induction by herbivore feeding, especially in the wild population. In wild plants, total GS concentrations were 1.7 times higher in induced plants than in uninduced conspecific plants, and were 2.7 and 4.9 times higher after herbivory than in induced plants of the cultivated and feral population, respectively. By contrast, the total GS concentrations in induced plants remained at the same level as in undamaged plants in the cultivated and feral populations, although differences were found for levels of individual compounds. The feral population differed from the other two populations with respect to pentyl-derived GS, which were absent in the cultivated and wild population. These C5 GS usually are not found in B. oleracea crops (Rosa 1999), indicating that this population may have crossed with a closely related species such as B. napus or B. rapa, both of which contain pentyl GS (Giamoustaris and Mithen 1995). Moreover, both B. napus and B. rapa are cultivated and grow naturally in the Netherlands. In all plant populations, concentrations of the indole GS, glucobrassicin, increased the most after herbivore feeding, but this compound was dominant only in the wild population, accounting for 70% of the GS content. Several studies have reported on herbivore-induced changes in GS concentrations in both cultivated and wild brassicaceous species. In line with our results, previous studies have shown that levels of indole GS increase in response to insect wounding (Bodnaryk 1992; Agrawal et al. 1999; Bartlet et al. 1999; Gols et al. 2008). We found that concentrations of some of the aliphatic GS were lower in plants that had been damaged by P. xylostella than in undamaged plants. Previous studies that used different herbivores reported that levels of aliphatic GS were either unaffected (Bodnaryk 1992; Bartlet et al. 1999; Traw and Dawson 2002; Gols et al. 2008) or even increased (Traw and Dawson 2002) in response to insect wounding. These results suggest differential induction of aliphatic GS by different herbivores (see also Traw and Dawson 2002). Glucosinolates also play a major role in determining a plant’s nutritional quality, not only for humans and livestock but also for pathogens and insect herbivores (Chew 1988; Mithen 1992). This study shows that plants from a wild population of B. oleracea are less suitable for the development of several herbivores than plants from a cultivated and a feral population. However, the severity of these effects differed between the specialists P. rapae and P. xylostella on one hand, and the generalist M. brassicae on the other. In P. rapae, emerging adult butterflies were smaller and took longer to complete development when reared on wild plants than on the other two populations. These effects were less pronounced in P. xylostella; however, where adult body mass was more negatively affected than development time. Importantly, in both of the specialist herbivores, survival was high, irrespective of the plant population on which the larvae had been reared. By contrast, adult body mass and survival in the generalist herbivore, M. brassicae, were significantly lower when reared on the wild B. oleracea strain. This reveals that costs in terms of reduced fitness are higher for generalist herbivores than for specialists when they feed on the more toxic wild plants. Similarly, Giamoustaris and Mithen (1995) found a negative relationship between GS content in oilseed rape (B. napus) and the amount of leaf damage by generalist herbivores, but a positive relationship for specialists. Levels of GS, especially indole GS, were higher in the wild population of B. oleracea than levels of GS found in B. napus by Giamoustaris and Mithen (1995). These results suggest that indole GS, especially neoglucobrassicin, which is present in very low concentrations in the cultivar, may play a role in reducing the performance of insect herbivores. Specialist insect herbivores, in contrast with generalists, may use GS as indicators of host plant suitability. For example, GS serve as feeding stimulants for insect herbivores specialized on plants belonging to the Brassicaceae (Nayar and Thorsteinson 1963; David and Gardiner 1966; Renwick and Lopez 1999). However, not all GS are equally active as feeding stimulants (e.g., Nayar and Thorsteinson 1963), and high levels of GS can even be toxic for specialists (Agrawal and Kurashige 2003). As such, high levels of specific GS may be responsible for the reduced performance of the specialists P. xylostella and P. rapae when reared on the wild population. Furthermore, levels of the enzyme myrosinase, which catalyzes hydrolysis of GS into the more toxic (iso)thiocyanates and nitriles (Rask et al. 2000; Mithen 2001), may also have differed among the populations. In addition, host plant quality is not determined only by the presence of allelochemicals. Nutrients, such as proteins and carbohydrates, as well as digestibility reducers, also play a role (Slansky 1993). It is possible that levels of limiting nutrients such as nitrogen and other defense-related compounds also vary across the three populations and thus amplify differences in performance caused by GS (Slansky and Feeny 1977). The performance of the two parasitoid species reared on P. xylostella also varied with the plant population on which the host had been reared. However, there were also significant differences in performance between the specialist parasitoid, D. semiclausum, and the congeneric generalist parasitoid, D. fenestrale. The development of D. semiclausum was directly affected by the development of the host. Adult body mass was reduced when developing on wild B. oleracea plants, whereas development time and survival were unaffected, revealing that D. semiclausum ontogeny is affected by quantitative changes in host quality as mediated through the diet of their host. Alternatively, the development of D. fenestrale was characterized less by direct differences in host quality than by indirect population-related variations in plant quality. Although P. xylostella survival was high (>80%) on all B. oleracea populations, as well as on B. nigra plants, mortality in D. fenestrale was much higher on the wild Brassica populations. As in most endoparasitoids, larvae of D. fenestrale primarily consume host hemolymph and fat body during early development. They only begin to indiscriminately attack other tissues later during development (the so-called “destructive feeding phase”). In this way, they do not kill the host until the last possible moment. Larvae of P. xylostella are known to utilize enzymes that convert GS into desulfo-GS in their gut, which are then excreted with their feces (Ratzka et al. 2002). Because of their polarity, GS presumably do not permeate the host-gut membrane but effectively remain in the gut before they are excreted. Consequently, the larvae of D. fenestrale probably ingest little, if any, GS when feeding on hemolymph. However, during the destructive feeding phase, the parasitoid larvae undoubtedly consume the host gut and its contents, and this is when the toxic effects of plant allelochemicals on non-adapted parasitoids may be realized. In hosts parasitized by D. fenestrale, mortality mainly occurred just before the parasitoids would have been expected to pupate (personal observation) supporting this argument. Furthermore, the gut of endoparasitoid larvae is not externally connected until after emergence from the host. The excretion of wastes into internal host tissues would facilitate bacterial infection and precocious death of both the host and the developing parasitoid (Harvey et al. 2003). Thus, low concentrations of allelochemicals that are ingested by parasitoid larvae are stored and presumably accumulate in their tissues. This may account for the high mortality recorded here with D. fenestrale that developed in P. xylostella caterpillars reared on mustard and wild cabbage plants, which contain high levels of GS. All insects used in this study have been reared on the Cyrus cultivar for many generations and may have adapted to this plant population. However, P. xylostella developed more successfully on B. nigra plants than on the cultivar, with moths enjoying higher survival and larger body mass. Furthermore, the performance of Mamestra brassicae and Pieris rapae was almost similar on the feral and the cultivated population. We cannot exclude that the observed differences are the result of rearing history rather than true plant effects, but the fact that the insects have no history with the recently cultivated feral population of B. oleracea and developed with equal success as on the cultivar suggests that plant quality is affected by domestication. Moreover, the development of the insects was more strongly negatively affected on the wild “Old Harry” population than on the feral population. In summary, this study has shown that plant quality in terms of development of herbivores and their natural enemies differs significantly between wild and cultivated populations of B. oleracea. The identity of the food plant and the degree of specialization exhibited by the herbivores and their parasitoids influenced the degree to which plant population affected performance. Most importantly, these results demonstrate that artificial selection in which certain plant traits are accentuated at the expense of others can alter a significant part of a plant’s evolved physiology. This may in turn have large impacts on insect communities that are associated with these plants. In wild plants, defense mechanisms have evolved under natural selection pressures from herbivores and pathogens and by the effects of natural enemies on herbivore populations. The reduction of the levels of direct defenses in cultivated plants could partly explain why these plants have often become more susceptible to attack from a wide range of herbivores and pathogens. To better understand the relative contribution of insect herbivory as a selective agent on the evolution of plant defenses, these traits should be studied in wild populations in which defense mechanisms have not been constrained by the “directional selection” that characterizes many species of crop plants. Future studies should examine insect communities associated with plant populations, including cultivars that differ in resistance against insect herbivores in plots in which the structural heterogeneity is also manipulated. This will facilitate a better understanding of the role that artificial selection has played in shaping the structure of communities associated with cropping systems.

Eur_J_Appl_Physiol-3-1-2039810

The effect of ambient temperature on gross-efficiency in cycling

Time-trial performance deteriorates in the heat. This might potentially be the result of a temperature-induced decrease in gross-efficiency (GE). The effect of high ambient temperature on GE during cycling will be studied, with the intent of determining if a heat-induced change in GE could account for the performance decrements in time trial exercise found in literature. Ten well-trained male cyclists performed 20-min cycle ergometer exercise at 60% (power output at which VO2max was attained) in a thermo-neutral climate (N) of 15.6 ± 0.3°C, 20.0 ± 10.3% RH and a hot climate (H) of 35.5 ± 0.5°C, 15.5 ± 3.2% RH. GE was calculated based on VO2 and RER. Skin temperature (Tsk), rectal temperature (Tre) and muscle temperature (Tm) (only in H) were measured. GE was 0.9% lower in H compared to N (19.6 ± 1.1% vs. 20.5 ± 1.4%) (P < 0.05). Tsk (33.4 ± 0.6°C vs. 27.7 ± 0.7°C) and Tre (37.4 ± 0.6°C vs. 37.0 ± 0.6°C) were significantly higher in H. Tm was 38.7 ± 1.1°C in H. GE was lower in heat. Tm was not high enough to make mitochondrial leakage a likely explanation for the observed reduced GE. Neither was the increased Tre. Increased skin blood flow might have had a stealing effect on muscular blood flow, and thus impacted GE. Cycling model simulations showed, that the decrease in GE could account for half of the performance decrement. GE decreased in heat to a degree that could explain at least part of the well-established performance decrements in the heat. Introduction Performance decrements are widely observed during exercise in the heat compared to thermo-neutral circumstances (Febbraio et al. 1996; Gonzalez Alonso et al. 1999; Parkin et al. 1999; Romer et al. 2003; Tatterson et al. 2000; Tucker et al. 2004). It has been shown that fatigue at exhaustion is related to factors associated with thermoregulation and hyperthermia (Febbraio et al. 1996; Nielsen et al. 1990; Parkin et al. 1999). Time trial performance and fatigue (evidenced by decrements in power output over the race) and finish time have received much less attention in the literature. Accordingly, the present study will focus on the effect of a hot ambient temperature on thermal and cardio respiratory strain during the exercise that might contribute to the well-established decrease in power output. Tatterson et al. (2000) measured time trial performance on a 30 min self-paced cycling time trial in 32°C, 60% RH versus 23°C, 60% RH. They observed that power output was reduced in the heat by 6.5% (345 ± 9 W vs. 323 ± 8 W). Tucker et al. (2004) compared 20 km time trials in 35 and 15°C and found a comparable reduction in average power output in the heat of about 6.3% (255 ± 47 W vs. 272 ± 45 W). This change in average power output led to a difference in final time on a 20 km time trial of about 48 s (29.6 ± 1.9 min vs. 28.8 ± 1.8 min), which equals about 2.8%. Possible causes for this deterioration in performance are associated with elevated body temperature (Tatterson et al. 2000) and anticipatory changes in pacing strategy to avoid hyperthermia (Tucker et al. 2004). Although most research has revolved around neuromuscular function, central drive and fatigue at the point of exhaustion, a plausible explanation for the deterioration in time trial performance in heat may also be found in a temperature-induced change in gross-efficiency (GE). GE is an important variable in cycling performance (Lucia et al. 2002; Moseley et al. 2004) and a linear relationship between body temperature and GE has been observed (Daanen et al. 2006). A possible explanation for the decreased GE in the heat could be mitochondrial leakage. A temperature induced metabolic disruption caused by non-specific proton-leakage across the inner mitochondrial membrane has been shown to occur at high muscle temperatures (Brooks et al. 1971; Willis and Jackman 1994), resulting in a decrease in ADP:O ratio. Further, a heat induced skin vasodilatation could occur in heat. To prevent a resulting decrease in blood flow to exercising and respiratory muscles (Nielsen et al. 1990; Romer et al. 2003; Rowell et al. 1966) a higher cardiac output must exist to continue supplying the muscles with the same blood flow, but still sending extra blood to the skin for cooling. In the present study we sought to determine the effect of heat on GE. GE can be assessed accurately during sub-maximal exercise at intensities as high as 60−80% VO2max by calculating the ratio between mechanical and metabolic (mainly dependent on aerobic energy metabolism) power output, as has been done in Daanen et al. (2006), Foster et al. (2003), Hettinga et al. (2006), Lucia et al. (2002), Moseley et al. (2001, 2004). The presence of a possible effect of ambient temperature on GE can serve as input for an energy flow model (De Koning et al. 1999) to quantify the impact of this effect on time trial performance. Materials and methods Subjects Ten healthy, non-smoking, well-trained male subjects, familiar with cycling exercise at the club-level, participated in this study. They were informed of the nature of the experiment and provided written informed consent. Subject characteristics are presented in Table 1. The study was approved by the Medical Ethical Committee of the University Medical Centre Utrecht (The Netherlands).Table 1Subject characteristicsMean value ± SDAge (years)23.5 ± 4.4Height (cm)179.7 ± 9.1Body mass (kg)72.5 ± 7.2VO2max (l min−1)4.78 ± 0.41(W)354 ± 29Values are mean ± SD Experimental design Incremental test The subjects first performed an incremental bicycle test to determine at which power output VO2max was attained The incremental test was performed in the heat, under similar conditions as the constant intensity bouts, to make sure that would not be overestimated in the hot condition. This incremental test was used solely to determine the relative intensities for the constant intensity cycling bouts. The test began at a power output (PO) of 150 W, after which PO was increased with 15 W every minute. Exercise was performed on an electronically braked cycle ergometer (Lode Excalibur, Lode NV, Groningen, The Netherlands) until exhaustion or until pedal frequency dropped below 80 rpm. Oxygen consumption (VO2) was measured breath by breath, using open circuit spirometry (Oxycon Pro-Delta, Jaeger, Hoechberg, Germany). The gas analyzer was calibrated using a Jaeger 2 l syringe, room air and a calibration gas mixture. Heart rate (HR) was monitored using radiotelemetry (Polar Electro, Kempele, Finland). Constant intensity exercise bouts On separate days, subjects performed a constant-intensity exercise bout at 60% of in a thermo-neutral climate (N) and in a hot, dry climate (H). Temperature in the thermo-neutral climate was 15.6 ± 0.3°C, relative humidity (RH) was 20.0 ± 10.3%. In the hot, dry climate, the temperature was 35.5 ± 0.5°C and RH was 15.5 ± 3.2%. These temperatures were equivalent to the temperatures in the studies of Tatterson et al. (2000) and Tucker et al. (2004). All tests were performed in a climate-controlled room with a continuous airflow of 0.2 m s−1. RH was set low to increase the evaporative capacity of the environment. Further, all trials in the H-climate were performed with a simulated wind velocity of 1.72 m s−1 (6.2 km/h) to further increase evaporative heat loss, which is the most important form of heat loss in cycling in hot conditions (Saunders et al. 2005). Prior to the experiments, the subjects were asked to refrain from vigorous exercise for at least 48 h. They were also asked not to consume coffee, alcohol or drugs after 10 p.m. the day before the exercise and not to eat for two hours prior to the experiments. Subjects drank water ad libitum before the experiment. Before the constant intensity bout in the H-condition, the subject stabilized for 50 min in the 35°C, 20% RH room. For the comfort of the subjects and to prevent them from shivering, the stabilizing period was reduced to 35 min for the N-condition in the 15°C, 20% RH room. During the test, oxygen consumption (VO2), respiratory exchange ratio (RER) and ventilation (VE) were measured breath by breath. Power output (PO) and heart rate were registered continuously. After stabilization, a 5-min warm-up was performed at 100 W with a pedal frequency of ∼100 rpm. After 1 min of rest, the constant intensity bout was started (∼100 rpm). The subjects cycled for 20 min at a constant power output of 60% of the power output at which maximal VO2 was attained at the incremental test in the H condition. Directly after the end of exercise, blood lactate concentration (BLC) was measured (Lactate Pro, Arkray, Kyoto, Japan). Rectal temperature (Tre) was monitored every 5 s during the entire test using a thermistor temperature probe (YSI 701, Yellow Springs Instrument, Dayton, USA) inserted about ten centimeters in the rectum. Skin temperature (Tsk) was measured every 5 s at 14 different skin loci, conform ISO 9886, using thermocouples (YSI 709B, Yellow Springs Instrument, Dayton, USA). Data were recorded with a Data Translation acquisition board (DT2821, Viewdac, Keithley Instruments, Cleveland, USA). Further, muscle temperature (Tm) was measured at a minimum depth of two centimeters and recorded every 5 s. Since this measurement was invasive, measurements were restricted to the constant intensity bout in H (n = 6). Tm was measured with a sterile thermal thermocouple-probe (type MAC08170A275SM, Ellab A/S, Rodovre, Denmark) in the right vastus lateralis muscle, inserted by a physician. One hour before inserting the temperature probe, a lidocaine plaster was attached to the skin, as a local anaesthetic. Calculating gross-efficiency (GE) Metabolic power (Pmet) was calculated by multiplying oxygen consumption with the oxygen equivalent: Pmet (W) = VO2 × [(4,940 × RER + 16,040)/60] according to Garby and Astrup (1987), assuming that respiratory exchange ratio (RER) equaled respiratory quotient (RQ) at sub-maximal intensities. Further, we assumed that respiratory exchange ratios in excess of 1.00 were attributable to buffering of lactate by bicarbonate. Ratios in excess of 1.00 were thus treated as if they equaled 1.00. The measured mechanical power output (PO) divided by the calculated Pmet defined GE. GE was calculated from 90 s after the start of exercise until the end of exercise. Energy flow model The energy flow model as described by De Koning et al. (1999) was used to calculate the effect of changes in GE on performance, by simulating a 20 km time trial as is studied in literature (Tatterson et al. 2000; Tucker et al. 2004). This model is based on power equations and has been reasonably successful in predicting performance in cyclic events as cycling (De Koning et al. 1999) and speed skating (De Koning et al. 2005). The energy flow model, also referred to as power balance model, relates to power production and power dissipation: Pprod = Plost + dE/dt, where Pprod is total power that can be produced, Plost power that is used to overcome frictional losses, and dE/dt rate of change of kinetic energy of the mass centre of the body. These terms can be calculated as described in De Koning et al. (1999), and the influence of changing one single variable, in this case GE, can be predicted. Statistics Paired Student t test’s were performed to test if data were significantly different between the H-condition and N-condition, P values less than 0.05 were accepted as statistically significant. Results Power output at 60% was 211.5 ± 18.6 W. All subjects were able to complete the trials in both H and N. VO2 was significantly higher in H than in N, resulting in GE being significantly lower in H compared to N. Further, HR and VE were higher in H compared to N. For RER and BLC, no main effect of temperature was found. Mean values are shown in Table 2.Table 2Gross-efficiency (GE), VO2, respiratory exchange ratio (RER), respiratory minute volume (VE), heart rate (HR) and blood lactate concentration (BLC) at 60% in the thermo-neutral (N) and in the hot dry (H) climate60% NHGE (%)20.5 ± 1.419.6 ± 1.1*VO2 (ml min−1)3,002.8 ± 290.13,126.5 ± 268.3*RER0.89 ± 0.030.90 ± 0.01VE (l min−1)76.9 ± 7.782.0 ± 9.4*HR (bpm)145.1 ± 6.5155.4 ± 12.0*BLC (mmol l−1)2.6 ± 1.03.9 ± 2.1Values are mean ± SD* Significant differences with N (P < 0.05) Mean GE over time is plotted for both conditions in Fig. 1. The difference in GE between conditions was 0.9% over the entire trial. From minute 5–8, the N − H difference was 0.6% ± 0.7%, from minute 15–18, the difference was 1.1 ± 1.3%, both significant. No significant change in GE within trials was observed comparing GE over the first half (min 5–8) with GE over the second half (min 15–18).Fig. 1Gross-efficiency (GE) plotted over time at 60% in the thermo-neutral (N) climate (dashed line) and in the hot dry (H) climate (solid line) ±SD (dotted lines) Tsk and Tre were significantly higher in H. Rectal and skin temperature changes combined, the difference in body heat content between N and H amounts to ∼138.5 ± 35.1 kJ, calculated assuming that the specific heat of the body tissue was 3.4 kJ kg−1°C−1. Maximal muscle temperature (Tmmax) in H was 38.7 ± 1.1°C. Mean temperature values are shown in Table 3. Figure 2 shows Tre, Tsk and Tm plotted over time for both conditions. Figure 3 shows the correlation between Tre and GE for both conditions. R2 in N was 0.04, R2 in H was 0.36.Table 3Rectal temperature (Tre), skin temperature (Tsk) and maximal muscle temperature (Tmmax) at 60% in the thermo-neutral (N) and in the hot dry (H) climate60% NHTre (°C)37.03 ± 0.5837.35 ± 0.63*Tsk (°C)27.74 ± 0.7133.39 ± 0.57*Tmmax (°C)38.7 ± 1.1 (n = 6)Values are mean ± SD* Significant differences with N (P < 0.05)Fig. 2Top panel Rectal temperature (Tre) plotted over time at 60% in the thermo-neutral (N) climate (dashed line) and in the hot dry (H) climate (solid line) ±SD (dotted lines). Center panel Skin temperature (Tsk) plotted over time at 60% in the thermo-neutral (N) climate (dashed line) and in the hot dry (H) climate (solid line) ±SD (dotted lines). Bottom panel Muscle temperature (Tm) plotted over time at 60% in the hot dry (H) climate (solid line) ±SD (dotted lines)Fig. 3Top panel Correlation between gross-efficiency (GE) and rectal temperature (Tre) for the thermo-neutral (N) climate. Bottom panel Correlation between gross-efficiency (GE) and rectal temperature (Tre) for the hot, dry (H) climate To quantify the effect of the decrease in GE of 0.9%, a simulation with an energy flow model (De Koning et al. 1999) was performed. This simulation showed that a change in GE of 0.9% would result in a difference in final time of 25.6 s over 20 km. Thus, about half of the decrement in performance reported in the literature (a difference in final time of 48 s over 20 km, Tucker et al. 2004) could be accounted for by the measured decrease in GE. To explain the entire deterioration in time trial performance in the heat, the mean decrease in GE had to be 2%. Discussion GE during sub-maximal cycling exercise in the heat was significantly reduced compared to exercise in N by 0.9%. Values for GE corresponded to values found in literature, between 17 and 22% (Foster et al. 2003; Moseley et al. 2001). It has to be kept in mind that in calculating GE at 60% anaerobic contribution was assumed to be negligible. But it might have been influenced by the different climates. Gonzalez-Alonso et al. (1999) reported that exercise in a hot environment results in a higher anaerobic contribution and found an increase in carbohydrate utilization and lactate accumulation during exercise. Though not significant, BLC in the present study was higher in H. According to di Prampero et al. (1999), an increase of BLC of 1 mmol l−1 of blood is equivalent to an O2 consumption of 3 ml kg−1 body weight. Differences in BLC in the present study between climates (2.6 mmol l−1 in N vs. 3.9 mmol l−1 in H) thus correspond with a difference in O2 consumption equivalent of ∼14.1 ml min−1. Accordingly, differences in GE between climates might be even larger then reported in the present study. If one adds this ‘anaerobic O2 equivalent’ to the VO2, then GE decreases about ∼0.19% in N compared to ∼0.27% in H, which means that the difference in GE between N and H increases with ∼0.07%. Mean Tre was about 0.3°C higher in H compared to N. Mean Tsk was about 5.7°C higher in H than in N. Comparable differences of 0.2–0.4°C in Tre (Tatterson et al. 2000; Tucker et al. 2004) and ∼6.0°C in Tsk (Tatterson et al. 2000) were reported during cycling bouts of ∼30 min in climates comparable to the present study. Although the difference in rectal temperature between H and N was significant, it was not a large difference compared to literature. The measured absolute values for Tre were somewhat low, presumably due to the relatively short period of exercise in our protocol and the use of a fan to optimize losing heat to the environment, as was done in the studies of Tatterson et al. (2000) and Tucker et al. (2004). The fan was used to simulate competitive circumstances, and although wind velocity in this study was not as high as the cycling speed, combined with the relatively low RH, the effect would have been considerable (Saunders et al. 2005). The differences in ambient temperature between H and N represent a considerable difference in thermal stress. Thermal strain is mainly visible in the increased skin temperature, but although the difference of 0.3°C in core temperature is small, it is significant. Rectal and skin temperature changes combined, the difference in body heat content between N and H amounts to 138.5 ± 35.1 kJ, which is considerable. Further, the differences between climates have been shown to be large enough to evoke a difference in GE of 0.9%, the main purpose of the present study. A possible explanation for the lower GE in the heat may be the higher core temperature. Daanen et al. (2006) found a strong linear relationship between body temperature, mainly determined by Tre, and GE at 60% in 30°C. Their study showed that our difference in Tre of 0.3°C could account for a reduction in GE of ∼0.2%, and thus was not large enough to explain the entire reduction in GE of 0.9%. In the study of Daanen et al. (2006), the skin temperature however was almost unchanged, while in the present study skin temperature in the H condition was about 5.6°C higher, indicating an increased blood flow to the skin. The present study did not find a strong correlation in heat (r2 = of 0.36) between Tre and GE. Further, remarkably, in the N-condition, no correlation between Tre and GE was found at all, even though Tre reached values which are also observed in the H-condition, only later in time (see Fig. 3). Apparently, Tre does not seem to be the main cause of the reduced GE. This is supported by the observation that even though Tre rose significantly during the time trial with about 1°C, GE did not increase significantly comparing the first half with the second half within the trials. Two other explanations for the reduced GE in heat can be given. Firstly, an explanation for the temperature-induced reduction in GE might be a metabolic disruption that is known to occur at elevated muscle temperatures (Brooks et al. 1971; Willis and Jackman 1994). Though Ferguson et al. (2006) found no effect of increasing muscle temperature on energy turnover in dynamic exercise in a range of 34.2–38.3°C, ADP:O ratio has been shown to decrease at higher muscle temperatures (Brooks et al. 1971; Willis and Jackman 1994). During heavy exercise in the heat, non-specific proton leakage across the inner mitochondrial membrane is increased, resulting in a decrease in the efficiency of oxidative phosphorylation and increasing the resting metabolic rate (Willis and Jackman 1994). This will result in a reduction in GE. Willis and Jackman (1994) found a decrease of 10–20% in ADP:O ratio at muscle temperatures of 40°C and higher compared to 37°C. They found that this decrease resulted in a 400–800 ml min−1 increase in VO2. In the present study, a smaller but significant increase in VO2 of 124 ml min−1 was found. Mean Tmmax in heat was 38.7°C, lower than the 40°C as found in Willis and Jackman (1994), but higher than 34.2–38.3°C, the Tm range in which Ferguson et al. (2006) found no effect of increasing Tm on energy turnover in dynamic exercise. Since Tm was not measured in both climates, it cannot be confirmed if muscle temperature was significantly different. Tsk and Tre were significantly different but did not approach 40°C in either condition. It seems that, as suggested by Brooks (1971), the core of the body functions as a heat sink for the skeletal musculature helping to maintain Tm below the point where significant reductions in the ADP:O ratio occur. Another potential cause for the decrease of GE in a hot ambient temperature was the larger vasodilatation of the skin to lose heat, as was shown by the significantly higher Tsk in H compared to N. The resulting decreased blood flow to exercising and respiratory muscles may be compensated by increasing cardiac output (Nielsen et al. 1990; Rowell et al. 1966), since a significant increase in heart rate was found in heat. The extra VO2 in the H condition is at least partially attributable to the extra myocardial VO2, since a higher cardiac output has to exist to continue supplying the muscles with the same blood flow, but have to send extra blood to the skin for cooling. Additionally, ventilation was increased, which may also lead to a reduction in GE. Assuming that the mechanical work per breath is 80–125 J (Milic-Amili et al. 2001), it can be estimated that the higher VE in this study can account for maximally 10% of the increase in VO2. Lastly, it has to be noticed, that GE decreases if the proportion of energy expenditure that is used to maintain homeostasis is increased. Thus, the lower GE in H could have been solely due to an increase in resting metabolic rate, while net efficiency remained unchanged. This would be consistent with the hypothesis that muscle temperature in the hot conditions was not high enough to make mitochondrial leakage a likely explanation for the observed reduced GE. Unfortunately, resting metabolic rate has not been measured. To determine the potential importance of the measured decrease in GE on time trial performance, a 20-km time trial, which was also studied by Tucker et al. (2004), was modeled by the use of the energy flow model (De Koning et al. 1999). A time trial of this distance can be seen as a mainly aerobic exercise bout. Tucker et al. (2004) found a difference in final time of 48 s between exercise in 35°C compared to 15°C. Using the energy flow model of De Koning et al. (1999), it was calculated that the measured difference in GE of 0.9% would lead to a difference in final time between H and N of 25.6 s. This explains about half of the 48 s found by Tucker et al. (2004). For the entire reduction in final time of 48 s, a decrease in GE of 2% would be necessary, which was not found. It can be concluded that about half of the decrease in time trial performance can be accounted for by the reduction in GE. It has to be noted that in this simulation, it is assumed that the difference in GE between H and N at higher intensities will not change. Although it has been shown that GE increases with exercise intensity, since the relative share of resting metabolism diminishes at higher sub-maximal intensities (Mosely and Jeukendrup 2001), this effect seems to be equal for both conditions and will at most have only a minor effect on the difference between conditions. Conclusion GE was lower in the heat. Tm was not high enough to make mitochondrial leakage a likely explanation for the observed reduced GE. Neither was the increased Tre. The extra VO2 in the H condition seems to be at least partially attributable to the extra myocardial VO2, since a higher cardiac output has to exist to continue supplying the muscles with the same blood flow, but have to send extra blood to the skin for cooling and thus impacted GE. Based on our findings under the current circumstances, it can be concluded that the temperature-induced change in GE could account for about half of the well-established performance decrements found during time trial exercise in the heat.

Eur_Radiol-2-2-1766021

Value of tissue harmonic imaging (THI) and contrast harmonic imaging (CHI) in detection and characterisation of breast tumours

The purpose of this study was to investigate the extent to which tissue harmonic imaging (THI), speckle reduction imaging (SRI), spatial compounding (SC) and contrast can improve detection and differentiation of breast tumours. We examined 38 patients (14 benign, 24 malignant tumours) with different combinations of THI, SRI and SC. The effect on delineation, margin, tissue differentiation and posttumoral phenomena was evaluated with a three-point score. Additionally, 1oo not palpable tumours (diameters: 4–15 mm) were examined by contrast harmonic imaging (CHI) with power Doppler. After bolus injection (0.5 ml Optison), vascularisation and enhancement were observed for 20 min. The best combination for detection of margin, infiltration, echo pattern and posterior lesion boundary was the combination of SRI level 2 with SC low. THI was helpful for lesions OF more than 1 cm depth. In native Power Doppler, vessels were found in 54 of 100 lesions. Within 5 min after contrast medium (CM) injection, marginal and penetrating vessels increased in benign and malignant tumours and central vessels mostly in carcinomas (p<0.05). A diffuse CM accumulation was observed up to 20 min after injection in malignant tumours only (p<0.05). THI, SRI and SC improved delineation and tissue differentiation. Second-generation contrast agent allowed detection of tumour vascularisation with prolonged enhancement. Introduction As a technique complementary to mammography, high-resolution ultrasound (US) is well accepted for differentiating between cystic and noncystic putative tumour lesions [1–11]. New developments such as tissue harmonic imaging (THI) and contrast harmonic imaging (CHI) have enhanced its value, particularly for primary detecting tumours in dense inhomogeneous mammary gland tissue, identifying mammographically occult tumours and appraising abnormalities in tissue architecture [8, 12–22]. Lesions that are only a few millimetres in size become detectable, and tumours can be characterised more precisely. Ultimately, the exact localisation of small tumours is a prerequisite for ultrasound-guided needle biopsy, vacuum biopsy or preoperative wire placement [15, 23–25]. Harmonic imaging allows better visualisation of tissue architecture and facilitates recognition of parenchymal changes with tumour infiltration, making it easier to wire mark small lesions with THI [19, 26, 27]. For tumour characterisation, it is also essential to appraise vascularisation in a manner comparable to that achieved by dynamic contrast-medium-enhanced magnetic resonance imaging (MRI) [4, 12, 16, 17, 28–31]. Even if computed evaluation programmes with pixel analysis facilitate appraisal of tumour blood flow, native vascular US with power Doppler (PD) has proved to be relatively unreliable [4, 9, 13, 17, 18, 23, 24, 29]. Contrast medium enhancement already enables more distinct visualisation of intratumoral and peritumoral vessels. However, the brief diagnostic time window after bolus injection of US contrast medium (CM) is often a limiting factor. The combination of CHI with PD opens up promising vistas for appraisal of vascularisation. Preliminary investigations indicate that tumour detection, characterisation and US-guided intervention can be improved by using a CM of the second generation with modified CHI technique [18, 25, 32]. The aim of our study was to evaluate their potential benefits and limitations for detecting and differentiating breast tumours. Materials and methods Patients and US A total of 138 patients (age: 25–79 years, median 54 years) were investigated in a multicentre trial with complementary mammary diagnostic procedures over a 36-month period (November 2002 to November 2005). All women gave informed written consent for their results to be used for programme research and evaluation. On the basis of US findings, each lesion was evaluated based on size, shape (ellipsoid, round, irregular), margins (smooth, macrolobulated, microlobulated, speculated, angulated, ill-defined), posterior sonographic artefacts (shadowing, through transmission, no posterior artefacts), echogenicity (hyperechogenic, isoechoic, hypoechoic), presence of calcifications and ductal extension. Investigations were supplemented by clinical examination and mammography in two planes. Ultrasound lesions were examined in three planes using PD and digital imaging with the GE Logiq 9 (GE Medical Systems, Milwaukee, WI, USA) US units. All investigations were carried out with a high-resolution multifrequency linear matrix array transducer (Linear Array M10L, 5–10 MHz) with the modalities of THI, spatial compounding (crossbeam), speckle reduction imaging (SRI) and contrast-medium-enhanced PD with CHI and additional three-dimensional (3D) imaging. Imaging documentation of digital raw data in single-image and short sequences was effected using a Picture and Communication System (PACS). Study population The patient population was divided into two groups. In group 1, we focused on the advantage of THI, SC and an adaptive algorithm for SRI. In group 2, we focused on CHI with PD. Group 1 Thirty-eight patients (37–62 years) with 14 benign and 24 malignant tumours were examined in fundamental mode and with harmonic imaging with a high-frequency matrix-array transducer with the modalities of THI, SC and an adaptive algorithm for SRI. Prospectively, fundamental and tissue harmonic mode were used alone and in combination with all available levels of SC (cross beam: low, medium, high, maximum) and five levels of SRI. In patients without tumour lesions, criteria were differentiation of normal fibroglandular tissue from premammary and retromammary fat, including the Cooper’s ligaments and ducts. Criteria that were evaluated for differential diagnosis in patients with lesions were margin, infiltration of malignant tumours, echo pattern with tissue components, calcifications, posterior lesion boundary and posterior acoustic features. After optimising system settings, a three-level score was applied to enable comparison of the quality of scans with fundamental imaging (0=equal, −1=inferior, +1=superior). Group 2 One hundred patients (25–76 years, median 53 years) comprised 29 probably benign [Breast Imaging Reporting and Data System (BI-RADS III)] and 71 malignant (BI-RADS IV–V) tumours confirmed by vacuum-assisted biopsy in 100/100 lesions and 78/100 cases additionally in the course of surgery. Tumour diameters varied between 4 and 15 mm (mean: 9 mm). Histological confirmation was obtained in all cases. All patients were comparatively investigated with fundamental B scan, THI and CHI with PD. After the B scan and evaluation of vascularisation in native PD, we used an echo signal amplifier of the second generation with low mechanical index (MI) technology. A bolus injection of Optison was administered (0.5 ml Optison diluted with 20 ml with NaCl solution and subsequent injection of another 20 ml NaCl). The bolus of CM was injected intravenously, and spreading of the contrast enhancement and washout in the tumours were followed for at least 20 min. A low MI (0.15–0.25) was chosen to avoid early destruction of the microbubbles. CM enhancement was appraised for up to 20 min. Moreover, additional 3D evaluations of the cine sequences were also possible retrospectively in consequence of the archiving of dynamic digital images of up to 180 single images and 10- loop. The images archived in B scan and THI could also be processed retrospectively, with various phases of SRI, which enabled marginal contours of the tumours to be highlighted by homogenising tissue structures. The patients were given detailed information before each injection of CM, particularly with respect to a possible predisposition to allergic reactions. Written consent was obtained. Studies were performed only in patients with normal renal function. Approval had been obtained from the hospital’s ethics committee. Histopathological correlation Histopathological correlation was determined based on surgical and biopsy findings. Tumour size, grade, histological subtype and presence of invasion were documented. Pathological imaging correlation was performed in conjunction with both pathologist and breast imagers with regard to lesion location and size to ensure that the imaged lesions were evaluated histologically. Breast biopsy US-guided biopsies were performed as vacuum-assisted biopsies, mostly with an 11-gauge needle. Up to 12 representative tissue samples were taken. When there were malignant findings, US-guided wire marking was mostly undertaken before surgical excision. Afterwards, follow-up examinations were carried out at 6-month intervals. Statistical analysis We carried out statistical analyses: Elementary statistics were computed.Fisher’s two-tailed exact test was applied for statistical assessment of powers for discriminating different vascularisation and comparison of benign tumours versus carcinomas after the use of Optison. Results Group1 THI has no effect on image quality in the near field. THI needs at least 1 cm of tissue penetration. The effect is best seen in the middle and far field, especially around the focus zone. Cutis and the first 10 mm of fat and Cooper’s ligaments are already seen in fundamental mode, with better visibility and delineation with SC (cross beam: level medium) and SRI. The reflex of the anterior mammary fascia appears thinner and brighter with SC (cross beam: level medium to high) than in fundamental imaging. Ducts in deeper areas are best visualised with a combination of SC and THI. The main disadvantage is a significant reduction of the frame rate caused by SC, especially when THI is possible in addition. The first impression from image analysis of all combinations of SC and SRI was that higher levels of SC could be avoided by using, in addition, an SRI level of 1 or 2, giving the same advantage over the fundamental image with less reduction of frame rate. The best compromise for screening examinations of breast tissue is the combination of SC (level low) and SRI (level 1 or 2) with THI in small breasts. Fat appears slightly more echogenic, which potentially helps to define small tumours. The main limitation of THI was the reduced penetration (16% of our patients). In patients with large breasts and abundant fibrous tissue, fundamental imaging should be preferred. Lesion detection and differentiation In four out of five cysts, THI clears artifactual echoes caused by reverberations, noise and speckle so that even small intracystic lesions could be depicted. Best visibility was achieved with a combination of THI, SC (level low) and SRI 2, giving clear cyst borders and the intracystic lesion. Using SC in two out of five cysts, the typical dorsal enhancement caused by sound transmission is less intense, as expected from the fundamental mode. Fibroadenomas were best detected with a combination of THI with SC (level medium) and SRI (2), showing better margin delineation, even in the edges. Better differentiation of tissue components and tumour infiltration could be achieved by the same combination (Fig. 1). Solid nodules generally appear more hypoechoic compared with surrounding breast tissue, which affords a better chance of detection [33]. Fig. 1Effect on delineation of tumour margin and tissue differentiation. On the left side is fundamental mode without spatial averaging and tissue harmonic imaging (THI). On the right side THI+cross beam level low+speckle reduction imaging (SRI) 2. a Improvement of delineation of tumour margin, especially if the tumour border is perpendicular to the ultrasound beam (fibroadenoma). b Improvement of tissue differentiation (haematoma) Calcifications detected in mammography were seen in US in six out of ten patients. Visibility was increased, especially after using the combination of THI and SRI or SC and SRI (Fig. 2a,b). Results for malignant tumours are summarised in Table 1. Fig. 2a, b Effect on visibility of calcifications and delineation of tumour margin a Fundamental B mode. b Tissue harmonic imaging (THI)+cross beam low+speckle reduction imaging (SRI) level 1. Well-differentiated invasive ductal carcinoma with microcalcification and infiltration better seen in cross beam+SRI 2. There is less attenuation retrotumoral due to spatial compounding (SC)Table 1Results of comparison of fundamental versus combination of tissue harmonic imaging (THI), spatial compounding (SC) (cross beam: level low) and speckle reduction imaging (SRI) level 1Criteria−10+1Margin11112Infiltration (existent in 19/24 malignant cases)1315Echo pattern/tissue components31011Calcifications123Posterior lesion boundary1716Posterior acoustic features996Score : −1=fundamental superior, 0=no difference, +1=combination superior Group 2 Seventy-one cases confirmed by biopsy were classified as malignant (BI-RADS IV–V), and 29 cases were categorised as most likely benign (BI-RADS III). Histological confirmation by vacuum biopsy was also performed at patients’ expressed request and in cases of malignancy or borderline lesions also by surgery (82/100). Histological appraisal Benign lesions Histological finding detected four cases with a scar or intraductal inflammatory origin or ductal lesions, two cases of papillomas, five cases of fibrocystic mastopathy and 18 cases of fibroadenomas. Malignant lesions Histological findings revealed 11 ductal carcinomas in situ (DCIS), two lobular carcinomas in situ (LCIS) and 58 cases of ductal invasive carcinomas. Sonomorphology defined in particular the extent of the tumour, marginal contours, change in tissue architecture, possible infiltration of surrounding tissue, intraductal spreading, altered echogenicity of lesions with possible dorsal sound enhancement or attenuation and unchanged compressibility. In PD, CM enhancement with harmonic imaging additionally enabled detection of peritumoral or intratumoral and irregular vessels penetrating the tumour as well as increased tumour vascularisation in intermittent dynamic appraisal. In particular, irregular penetrating vessels and prolonged enhancement for more than 5 min were found in only malignancies (65/71 cases: Fig. 3a–d, Fig. 4a–d and Fig. 5a–f). In six cases of DCIS with a maximum diameter of 5 mm and low grading (G I), increased vascularisation could not be demonstrated, even after CM enhancement. All were detected as small lesions using a combination of THI with SC. Five out of six showed tiny peritumoral vessels after contrast administration. Proliferating fibroadenomas and scars may show an increased peritumoral vascularisation but did not show prolonged enhancement in harmonic imaging with PD (Table 2). Fig. 3a–d Well-differentiated invasive ductal carcinoma (75-year-old woman, non-palpable mass) a Irregular tumour of 12 mm with hidden distal border in fundamental B scan and tissue harmonic imaging (THI). b, c In combination with cross beam and speckle reduction imaging (SRI), better delineation of the pectoral (distal) aspect , in particular, showing infiltration of the pectoral fascia. d Good visibility of the biopsy needle in THI and THI with crossbeam in three-dimensional (3D) techniqueFig. 4a–d Same patient as Fig. 3 with invasive ductal carcinoma. a Unenhanced power Doppler (PD) shows few peripheral vessels. b–c After administration of 0.5 ml Option, increasing enhancement within the lesion with prolonged persistence of enhancement up to 6 min is seen. d Beginning washout after 8 minFig. 5a, b Ductal carcinoma in situ (DCIS) (35-year-old woman, no palpable mass). Cervical carcinoma, breast cancer in mother and sister. No clinical signs. Tumour proven by vacuum-assisted biopsy (DCIS) a Fundamental (B scan). b Tissue harmonic imaging (THI) showing a small, distinct, irregular mass of 8 mm. c–f Same patient as a, b. c Power Doppler (PD) before administration of contrast. d Pronounced visibility of the feeding vessel in the early phase. e Late and persistent enhancement of the tumour typical for malignant breast tumours. f Better delineation of the tumour even after 14 min in contrast harmonic imaging (CHI) modeTable 2Comparison of benign tumours versus carcinomas. Vascularisation after administration of CM [0.5 ml Optison] Benign tumours (n=29)Carcinomas (n=71)Power DopplerPower Doppler +CMPower DopplerPower Doppler + CMEarly phase (1–5 min)Marginal vessels11/29 (38%)24/29 (83%)43/71 (60%)67/71 (94%)Penetrating vessels4/29 (14%)12/29 (41%)28/71 (39%)65/71 (91%) (p<0.05)Central vessels0/29 (0%)6/29 (20%)21/71 (29%)48/71 (68%) (p<0.05)Late phase (5–20 min)Diffuse enhancement0/290/290/7165/71 (91%) (p<0.01)Marginal vessels are seen in both groups in a high percentage. Most carcinomas show diffuse enhancement through the late phase (statistical evaluation with the Fisher’s exact test, significant differences p<0.05) The results of our own investigations indicate that the tumours can be identified better during biopsy in echo-inhomogeneous tissue using CHI in biopsies of smaller tumours under 10 mm in size. This enables false negative findings to be avoided in the histopathological investigations. After injection of CM, satellite foci and lymph nodes may also show increased vascularisation, which is manifested especially in harmonic imaging with PD. Discussion After clinical examination, breast US is the preferred method in symptomatic patients. In cases without symptoms, breast US is ascribed a higher sensitivity for detecting breast cancer in women with dense breast tissue, women under the age of 50 and high-risk women. Mammographically occult cancers can be detected by US in 10–40% of cases, depending on patients’ breast density and age. For women without symptoms, breast US should be mandatory and complementary to mammography in the case of breast density grade II [American College of Radiology (ACR)] or more [34]. US is now the more accurate imaging test in women 45 years or younger who present with breast symptoms and should be the initial imaging investigation [5, 7, 35]. In preoperative assessment of the local extent of breast cancer, US showed higher sensitivity for invasive cancer than for DCIS [8, 35, 41]. In nonfatty breasts, US and MRI were more sensitive than mammography for detecting invasive cancer, but both MRI and US involved the risk of overestimating tumour extent [4, 7–9, 12, 35]. Mammographic sensitivity decreased from 100% in fatty breasts to 45% in extremely dense breasts. The respective diagnostic accuracy of the different breast imaging modalities, i.e. mammography (Mx), high-resolution breast US, and dynamic contrast-enhanced breast scanning (MRI) regarding early diagnosis of familial (hereditary) breast cancer were investigated. Breast cancer detection rates were: Mx: 42%, US 25% and MRI 83%, and positive predictive values were: Mx 29%, US 30% and MRI 43% [8]. THI in combination with digital encoding of the US beam is an increasingly common option for B-mode imaging. It reduces reverberations, sidelobe effects and speckle. Both image contrast and lateral resolution are improved in harmonic mode compared with conventional fundamental US [36]. First applications are reported for liver disease [37], lymph node enlargement in children [38] and patients with pancreatitis. Benefits of harmonic imaging are more apparent in obese patients, improving accuracy of diagnosis from 60% to 80% [39]. To determine the impact of THI on visualisation of focal breast lesions, Szopinski et al. [21] performed a prospective study on 219 female patients. THI improved the grey scale contrast between fatty tissue and breast lesions in 230 lesions (90.6%; p<0.001) compared with fundamental frequency images. Contrast improvement was greater in breasts with predominantly fatty or mixed (fatty/glandular) composition than in predominantly glandular breasts. Overall conspicuousness, lesion border definition, lesion content definition and acoustic shadow conspicuousness were improved or equal in the harmonic mode for all lesions. After optimising the system settings, our results showed better delineation of tumour borders and infiltration with the combination of SC and SRI. Better differentiation of tissue structure was seen in the combination of THI and SRI; microcalcifications could be depicted best with a combination of harmonic mode, SRI and SC [19, 27, 40]. Retrotumoral tissue and the posterior lesion boundary of tumours are significantly better identified with high values of SC. One must be aware of the potential problem that the typical posterior acoustic enhancement is significantly reduced, with the result that a cyst can be misinterpreted as a solid tumour. THI and CHI can be helpful for detecting tumours less than 10 mm in size in echo-inhomogeneous dense tissue, for characterising tumour morphology with dynamic enhancement studies and for performing a definitive core needle biopsy or vacuum-assisted biopsy in cases of tumour lesions less detectable in fundamental B scan or tumours located in the deep tissue near the intercostal muscles. Harmonic imaging in combination with SRI and cross beam can facilitate detection of intraductal tumours such as papillomas. With 3D imaging, the needle could be more easily placed in the middle of these small intraductal tumours during biopsies [15]. Various criteria of image morphology have proved useful in appraising whether a breast tumour is benign or malignant on the basis of US. Smooth marginal contour, dorsal US amplification, displacement margin, bilateral US extinction and absence of structural discontinuity in that order rather indicate a benign lesion. An echodense border, tumour outliers, jagged marginal contour, dorsal extinction and structural discontinuity point to malignant lesions. In consequence of the increasing improvements in tumour detection and morphological imaging, sensitivity <80% and specificities <95% can be achieved with US in tumour diagnostics [5, 7, 20, 21, 35]. An even higher diagnostic certainty is aspired to. This can already be attained with the combination of mammography and breast US, especially in dense and inhomogeneous glandular tissue [2, 7, 22, 35]. Tumour lesions of BI-RADS IV and V have to be clarified by biopsy, in particular, punch biopsy or vacuum biopsy. Consequently, US-guided biopsy is appropriate when it allows unequivocal lesion identification. US-guided interventions are required for further clarification in mammography occult findings and preoperative wire marking. In our own investigations, harmonic imaging was employed for definitive preoperative wire marking, to carry out a US-guided vacuum biopsy and also with CM enhancement for improved tumour detection. Additional Doppler methods have been used to analyse breast tumour vascularity [42, 43]. Detection of penetrating or central vessels proved to be an accurate sign of malignancy [12, 13, 17, 22, 24, 25, 29, 31]. With the application of CM (Levovist), additional vessels were detected within the lesions, increasing diagnostic accuracy. Sensitivity of colour-coded US was improved from 64% up to 86% using the echo signal amplifier. Specificity was 86% without and 82% with echo signal amplifier. MRI was found to have a sensitivity of 100% and a specificity of up to 82% [12]. Our study with a modified technique of CM-enhanced PD and THI showed better visualisation of tumour vascularisation after bolus application of Optison. Persistent enhancement after 5 min was characteristic for malignant tumours, enabling tumour characterisation as has hitherto only been known from CM-enhanced MRI [4, 12, 16, 18, 24, 29–31, 44]. When using CM containing protein, special attention must be paid to an allergic predisposition and kidney function disorder. The use of second-generation CM necessitates a change in MI and imaging with harmonic imaging. However, the modified technique allows a differentiated diagnosis of tumour morphology and vascularisation [4, 12, 25, 29, 44, 45]. To improve the detection and assessment of intratumoral vessels in malignant breast tumours, techniques to enhance visualisation of vessels within focal lesions have been developed and automated. These techniques focus on the early perfusion phase following CM administration. Contrast-enhanced MRI allowed semiquantitative assessment of the kinetics of contrast media [4, 18, 31]. Artefacts caused by pulsation and patient movement should be avoided. More frequently, 3D postprocessing has become important in assessment of vasculature. CHI US is already used to distinguish scars from recurrent tumours as well as in the optimisation of US-guided biopsies [14, 15, 20, 32]. Conclusion In conclusion, we feel confident that US using THI and CHI technologies is a valuable tool for evaluating focal breast lesions, in particular in mammography-dense breasts. If utilised extensively, it will be a cost-effective tool to facilitate detection and differentiation of malignant breast lesions in early, well-treatable stages and will thus help in reducing breast cancer mortality.