P < 0.001) and 1 − 100 , but not in those with baseline CACS > 100 . After adjusting for traditional risk factors, the AIP was significantly associated with CAC progression in those with baseline CACS ≤ 100. The AIP has value for predicting CAC progression in asymptomatic adults without heavy baseline CAC.This study aimed to evaluate the association between the atherogenic index of plasma (AIP), which has been suggested as a novel marker for atherosclerosis, and coronary artery calcification (CAC) progression according to the baseline coronary artery calcium score (CACS). We included 12,326 asymptomatic Korean adults who underwent at least two CAC evaluations from December 2012 to August 2016. Participants were stratified into four groups according to AIP quartiles, which were determined by the log of (triglyceride/high-density lipoprotein cholesterol). Baseline CACSs were divided into three groups: 0, 1 − 100, and > 100. CAC progression was defined as a difference ≥ 2.5 between the square roots (√) of the baseline and follow-up CACSs (Δ√transformed CACS). Annualized Δ√transformed CACS was defined as Δ√transformed CACS divided by the inter-scan period. During a mean 3.3-year follow-up period, the overall incidence of CAC progression was 30.6%. The incidences of CAC progression and annualized Δ√transformed CACS were markedly elevated with increasing AIP quartile in participants with baseline CACSs of 0 and 1 − 100, but not in those with a baseline CACS > 100. The AIP level was associated with the annualized Δ√transformed CACS in participants with baseline CACSs of 0 (β = 0.016;  Furthermore, CAC progression is a powerful predictor of mortality beyond traditional CV risk factors4. Recently, the Heinz Nixdorf Recall (HNR) study suggested that CAC progression may only offer additional prognostic benefit in the asymptomatic adult population, and that what counts is the baseline coronary artery calcium score (CACS) and risk factor assessment5. In particular, additional CAC evaluation was not recommended in cases of heavy baseline CAC, although a high CV risk was present in the HNR study5. This result suggests that early detection of the presence and progression of subclinical atherosclerosis is important in conditions with low to intermediate CV risk burden.Coronary artery calcification (CAC) is associated with atherosclerotic burden and adverse cardiovascular (CV) clinical outcomes8. Notably, evidence suggests that the AIP may be more closely related to CV risk than are other atherogenic indices or individual lipoprotein cholesterol concentrations alone11. However, there is a paucity of data on the association between the AIP and CAC progression according to the baseline CACS. Thus, the present study aimed to evaluate the association between the AIP and CAC progression, focusing on the baseline CACS.The atherogenic lipoprotein profile of plasma is a substantial risk factor for atherosclerosis. The atherogenic index of plasma (AIP) has been considered a marker of plasma atherogenicity based on its strong and positive association with lipoprotein particle size, cholesterol esterification rates, and remnant lipoproteinemia13. Briefly, the present study included 12,326 participants who underwent at least two CAC scan examinations, with available data on the AIP and diabetic status, from December 2012 to August 2016. All data were obtained during visits to each healthcare center. Self-reported medical questionnaires were used to obtain information on the participant’s medical history. Blood pressure of the right arm was measured using an automatic manometer, after resting for at least 5 min. Weight and height were measured with the participants wearing light clothing without shoes. The body mass index (BMI) was calculated as the weight in kilograms divided by the square of the height in meters. All blood samples were obtained after at least 8 h of fasting and analyzed for total cholesterol, triglyceride, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), creatinine, glucose, and glycated hemoglobin A1C (HbA1C) levels. Hypertension was defined as systolic blood pressure (BP) ≥ 140 mmHg or diastolic BP ≥ 90 mmHg, a previous diagnosis of hypertension, or use of anti-hypertensive medication. Diabetes was defined as either a fasting glucose level ≥ 126 mg/dL, HbA1C level ≥ 6.5%, a referral diagnosis of diabetes, or use of anti-diabetic treatment. Hyperlipidemia was defined as a total cholesterol level ≥ 240 mg/dL or anti-hyperlipidemic treatment. Obesity was defined as BMI ≥ 25.0 kg/m2 using cut-offs for the Asian population. Current smoking history was considered present if participants currently smoked or smoked until 1 month before the study. Hypertension, diabetes, hyperlipidemia, obesity, and current smoking status were considered as traditional risk factors. The AIP was defined as the base 10 logarithm of the ratio of the concentration of triglycerides to HDL-C6. All participants were categorized into four-groups based on AIP quartiles.Data from the Korea Initiatives on Coronary Artery Calcification (KOICA) registry were analyzed in this study. The KOICA registry is a retrospective, observational, and multicenter registry of self-referred asymptomatic adults who underwent a general health examination at six healthcare centers in South Korea14. CAC progression was defined using the SQRT method; specifically, as a difference ≥ 2.5 between the square roots (√) of the baseline and follow-up CACSs (Δ√transformed CACS), with consideration of the inter-scan variability15. Annualized Δ√transformed CACS was defined as Δ√transformed CACS divided by the inter-scan period. All computed tomography (CT) scans used to assess CAC were obtained from a > 16-slice multi-detector CT scanner . Standard prospective or retrospective methods were used in all centers. All methods were performed in accordance with the relevant guidelines and regulations. The appropriate institutional review board committees of Severance Cardiovascular Hospital approved the protocol of the present study.CACS was measured using the scoring system described by Agatston et al.P value < 0.05 was considered significant in all analyses.Continuous variables are expressed as the mean ± standard deviation. Categorical variables are expressed as absolute values and percentage. The one-way analysis of variance was used to analyze continuous variables. The χ2 or Fisher’s exact test was used to analyze categorical variables, as appropriate. Univariate linear regression analysis was used to assess the association of clinical variables with the annualized Δ√transformed CACS in each categorical CACS group. Multiple logistic regression models were used to identify the independent predictive value of the AIP for CAC progression beyond that for traditional risk factors according to the baseline CACS status, using the forced entry method. Relative risk was estimated by a log-binomial regression analysis for generalized linear models. All statistical analyses were performed using the Statistical Package for the Social Sciences version 19  and SAS version 9.1.3 . A The protocol of the present study was approved by the institutional review board of each institution, and written informed consent was obtained from each participant.Clinical characteristics of the 12,326 participants  are presented in Table P < 0.001), Δ√transformed CACS , and annualized Δ√transformed CACS  were elevated with increasing AIP quartile  and 1–100 , but not in those with baseline CACS > 100 . The annualized Δ√transformed CACS was significantly different among AIP quartiles in those with baseline CACSs of 0  and 1–100 , but not in those with baseline CACS > 100   and 1–100 . However, no significant association between the AIP and annualized Δ√transformed CACS was observed in those with baseline CACS > 100  (Table The AIP (per 0.1-unit increase) was associated with the annualized Δ√transformed CACS in those with baseline CACSs of 0  trial found only a modest association between CAC progression and CV outcomes, although additional prognostic information was not provided in comparison with that for the latest single CAC value, during the mean 3.5-year period16. Lehmann et al. recently reported that CAC progression may only add prognostic benefit for participants without CV disease, based on the HNR study data , during a mean 5.1-year follow-up5. This previous study emphasized the significance of the most recent CAC value and risk factor assessment. Additional CAC examination is not required in cases of heavy CAC at baseline, which implies the presence of a high CV risk. Considering that atherosclerosis-related adverse events commonly occur, even in populations with low CV risk burden19, these results strongly suggest that early detection of the presence and progression of subclinical atherosclerosis is an important issue in clinical practice.Budoff et al. previously reported that CAC progression had additive value in predicting all-cause mortality, beyond that for the baseline score and CV risk factors, in 4,609 asymptomatic participants who underwent repeat screening during a mean 3.1-year period21. In addition, a number of cross-sectional studies demonstrated that the AIP had predictive value for coronary artery disease in various clinical conditions24. However, earlier studies did not address the relationship between the AIP and CAC progression, especially in terms of the baseline CACS. In the present study, we considered a CACS > 100 as indicating heavy CAC status based on the following facts: (1) Nasir et al.25 reported that the frequency of CACS > 100 in the Asian population is significantly lower than that in western populations; and (2) the overall proportion of baseline CACS > 100 was 10.6% in our participants. The presence of CAC at baseline and CAC progression during follow-up were more frequently observed with increasing AIP quartile. However, the AIP was associated with the risk of CAC progression, over that for traditional CV risk factors, in participants without heavy CAC at baseline. This finding suggests that the AIP is a useful marker for the stratification of CV risk, in addition to the baseline CAC status, in conditions with low to intermediate CV risk.Previous studies revealed that the AIP is significantly related to diverse metabolic disorders, such as fatty liver disease, hypertension, and diabetes26. However, a recent CONFIRM  sub-study found that further prognostic benefit was not offered by coronary computed tomographic angiography (CCTA) findings when added to traditional risk factors and CACS in 1,226 asymptomatic participants, during a mean 5.9 ± 1.2 years of follow-up27. This finding suggests that CCTA may have a limited role in future CV risk stratification in the asymptomatic population, until further proven.Because the present study only evaluated the change in CACS in the asymptomatic adult population, data on changes in the regional distribution or pattern of CAC were unavailable. In addition, the effect of medications such as statins, which could influence the changes in plaque sub-types, was not consideredWe should acknowledge some limitations of the present study. First, this study included participants from the KOICA registry who underwent at least two CAC scans with available data on the AIP and diabetic status. Thus, a potential selection bias might be present. Second, we only identified the association between the baseline AIP level and CAC progression, focusing on the baseline CACS; consecutive changes in AIP during the follow-up period were not confirmed. However, the mean change in the AIP between the initial and follow-up CAC scan was very small: − 0.02 ± 0.23. Third, the use of medications for hypertension, diabetes, and hyperlipidemia was not controlled during the follow-up period because this study had an observational design. Fourth, although we evaluated the predictive value of the AIP for CAC progression after adjusting for sex, the predominance of male sex in this cohort registry could have impacted the results. Thus, it might be hard to apply the results of present study to the female population. Fifth, although this study was performed in an asymptomatic and relatively healthy population, there was a paucity of data on environmental risk factors, such as physical activity, exercise, and diet, which could influence CAC progression. Sixth, different CT scanners were used among the participating centers because the KOICA registry was a retrospective, observational, and multicenter registry. However, all participants were examined using the identical CT scanner at both the initial and follow-up image acquisitions. Finally, the generalizability of our results may be limited considering that all participants were Korean. Despite these limitations, we firstly identified the predictive value of the AIP for CAC progression according to the baseline CACS in a large sample of the asymptomatic adult population.In summary, the present study demonstrates that the AIP is independently associated with CAC progression, especially in the absence of heavy CAC at baseline. This result suggests that the AIP has the potential to predict early coronary atherosclerotic changes and to stratify CV risk in asymptomatic adults with low to intermediate CV risk. Further large-scale prospective studies are necessary to confirm the significance of the AIP in primary prevention.Supplementary Information 1.


However, the prognostic value of TyG index in patients with type 2 diabetes mellitus  was recorded. The TyG index was calculated as the ln [fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2].A total of 1932 consecutive patients with Tp < 0.001], non-fatal MI , cardiac rehospitalization , revascularization  and composite MACCEs . The area under ROC curve of the TyG index for predicting the occurrence of MACCEs was 0.604 , with the cut-off value of 9.30. The addition of TyG index to a baseline risk model had an incremental effect on the predictive value for MACCEs .Competing risk regression revealed that the TyG index was positively associated with CV death [2.71(1.92 to 3.83), 2DM and AMI.The TyG index was significantly associated with MACCEs, suggesting that the TyG index may be a valid marker for risk stratification and prognosis in patients with TTrial registration Retrospectively registered. Finally, 1932 patients were included in this analysis. The patients were divided into 2 groups according to the occurrence of MACCEs during the follow-up: the MACCEs group (n = 735) and the No-MACCEs group (n = 1197). In addition, the patients were also divided into tertiles according to their TyG index levels . All patients were followed up till October 31, 2020 with a median follow up of 26.8  months.Study subjects were identified from the Cardiovascular Center of Beijing Friendship Hospital Database (CBD) Bank. A total of 5169 consecutive patients were diagnosed with AMI and underwent coronary angiography from January 2013 to August 2020. Of the 5169 patients, 3237 were excluded according to the exclusion criteria, which were (1) without TThe data collection process was approved by the Institutional Review Board of Beijing Friendship Hospital affiliated to Capital Medical University and was in accordance with the Declaration of Helsinki.0.185/(TGs0.2 × body mass index(BMI)1.338)  . The SinI)1.338) , with fa2DM include: (1) previously diagnosed T2DM under treatment of antidiabetic medication; (2) the typical symptoms of DM with a FPG ≥ 7.0 mmol/L, and/or random blood glucose (RBG) ≥ 11.1 mmol/L, and/or 2-h plasma glucose level after oral glucose tolerance test (OGTT) ≥ 11.1 mmol/L . Figure 5.1%; CV p < 0.001)  of the TyG index for predicting the occurrence of MACCEs was 0.604  Fig. . The cutp < 0.001). In addition, the C-index of the baseline risk model  changed after addition of the TyG-index .Table 2.Subgroup analysis was performed according to age, sex, BMI, smoker, HT, eGFR, LVEF and AMI type Fig. . We foun2DM. Our main findings include: (1) the incidences of MACCEs significantly increased with the increase of TyG index, and (2) the TyG index was an independent predictor of MACCEs The AUC of the TyG index for predicting the occurrence of MACCEs was 0.604 with a cut-off value of 9.30, and (4) The addition of TyG index to a baseline risk model had an incremental effect on the predictive value for MACCEs, and (5) the predictive effect of TyG index on MACCEs is ineffective in patients with eGFR < 60 ml/min/1.73 m2. According to this study, we confirmed that the TyG index was positively associated with increased MACCEs. Most importantly, this study suggested that a simple method of estimating IR may optimize the risk stratification of recurrent cardiovascular risk in AMI patients with T2DM.To the best of our knowledge, this is the first study to explore the association between the TyG index and MACCEs in AMI patients with TIR is defined as a decrease in the efficiency of insulin in promoting glucose uptake and utilization, which is an indicator of abnormal metabolism. IR promotes the progression of CVDs by inducing glucose metabolism imbalance, altering systemic lipid metabolism, and causing endothelial dysfunction . Severalp = 0 003] , and the addition of TyG index to a baseline risk model had an incremental effect on the predictive value for adverse prognosis   . Consideas 9.323 . A study< 0.001] . However2DM for the first time. To better understand the predictive power of TyG index for different CVEs, we analyzed the correlation between TyG index and each type of MACCEs , which other studies have not tried. The conclusions drawn by this research have important guiding role for clinicians to predict the occurrence of future clinical events in patients with AMI and T2DM. In addition, we also found that adding TyG index to the baseline risk model had a significantly incremental effect on the predictive value for MACCEs, which is consistent with the conclusions of Zhao et al. [2. For this result, the mechanism is still unclear. There are relatively few studies on TyG index and kidney disease. Zhao et al. [2). Maybe we need to do some work on that.In this study, we investigated the prognostic value of the TyG index in patients with AMI combined with To et al. . Anothero et al.  found tho et al.  showed tOur study had several limitations. First, this was a single-center study although including a large sample size; thus, generalization of the findings should be cautious. Second, laboratory parameters were only measured once after hospital admission, which could cause potential bias due to measurement error. Third, conventional laboratory testing methods for IR, such as HOMA-IR, has not been tested, the relationship between TyG index and IR cannot be verified directly in this study. In addition, prospective cohort studies are required to confirm our findings.2DM. In addition, adding the TyG index to a baseline risk model had an incremental effect on the predictive value for MACCEs.In conclusion, the current study firstly demonstrated that elevated TyG index level was a strong independent predictor of MACCEs in patients with AMI and T


Mammalian heart valves are soft tissue assemblies with multi-scale material properties. This is because they are constructs comprising both muscle and non-contractile extracellular matrix proteins (such as collagens and proteoglycans) and transition regions where one form of tissue structure becomes another, significantly different form. The leaflets of the mitral and tricuspid valves are connected to chordae tendinae which, in turn, bind through papillary muscles to the cardiac wall of the ventricle. The transition regions between these tissue subsets are complex and diffuse. Their material composition and mechanical properties have not been previously described with both micro and nanoscopic data recorded simultaneously, as reported here. Annotating the mechanical characteristics of these tissue transitions will be of great value in developing novel implants, improving the state of the surgical simulators and advancing robot-assisted surgery. We present here developments in multi-scale methodology that produce data that can relate mechanical properties to molecular structure using scanning X-ray diffraction. We correlate these data to corresponding tissue level (macro and microscopic) stress and strain, with particular emphasis on the transition regions and present analyses to indicate points of possible failure in these tissues. It is estimated that ∼11.7 million people in the United State of America suffer from heart disease . A majorHuman heart valves act as gatekeepers to help ensure unidirectional flow of blood under physiological conditions. Because of their different placements, they control blood flow in the pulmonary and systemic circuits and between the atria and ventricles. The four main valves experience significantly different blood pressures and rates of activation. Blood flow/pressure activates the valves to allow the flow of blood away from a chamber of the heart and they close to prevent blood flow in the wrong direction. The aortic valve (AV) allows the outflow of blood from the left ventricle to the aorta and the pulmonary valve (PV) controls the outflow of blood from the right ventricle to the pulmonary artery . These vAs is clear from visual inspection, the MV and TV have two distinct tissue transitions, where one specialized tissue organizational domain becomes another with a different organization, even though they are principally made of the same materials; namely (i) LL to CT (one type of fibrillar collagen and proteoglycan (PG) arrangement to another; see One may expect, a priori, some manner of muscle-to-tendon transition in cardiac valves, analogous to that found in skeletal tissues. So, the mechanism of injury to the latter may be beneficial for determining similar responses in the former. Previous studies have demonstrated that injury to tissues that possess muscle-to-tendon transitions originates in those transition regions ,11,12. RImportantly, these data are needed to develop high definition computational models of the heart that are intended to closely reflect physiological function. With the development of high-speed computing and modeling techniques, cardiac flow simulations have made it possible to establish potential cardiac injury mechanisms in simulations. These simulations can aid in predicting cardiac damage, particularly chordal tear and valvular defects ,18,19,20A major hurdle in improving the quality and reliability of simulations focused on the function and injury in heart valves is the lack of relatively high-resolution data  concerning tissue composition, tissue boundaries, and elastic properties of heart valves. Several modeling efforts have been focused on developing the elastic contributions of the various elements of a tissue assembly ,29,30,31We present here expanded methods and analyses to establish material and mechanical properties of cardiac tissues, mitral and tricuspid valve transition regions. These methods are an advancement of those described in Madhurapantula et al. (2017)  that werXRD scanning was performed along the samples dissected from pig valves. Diffraction patterns were analyzed to identify and measure the collagen fifth-order meridional and muscle  equatorial peaks. The relative intensity of these peaks was used to calculate the relative percentage composition of muscle and collagen along the transition regions , as per MV and TV have clear differences in mechanical properties, evident also from consideration that one is a bi-part and the other a tri-part valve. However, the material composition from the respective muscle to collagenous tissue transitions are similar. As noted in the study of skeletal muscle to tendon molecular composition transition is not a ‘step-change’, but is diffuse or gradual over a section of the fibrous tissue. XRD data shows a near-linear decrease in collagen percentage is observed in the PM to CT transition, going into the belly of CT (no muscle detected), the length of this transition spanning a few millimeters.The transition between CT–LL, as determined by XRD, appears to be somewhat more homogeneous than the PM–CT transition. This is due to fact that the LL and CT are both primarily constituted of fibrillar collagen , unlike The AV is distinctly different from the MV and TV, consisting of three cusps attaching to the wall of the aorta see . ComposiMV and TV samples were cut and separated, halfway along the CT (‘bisected’) to capture stress vs. strain properties of these segments. XRD scans along these ‘bisected’ samples were used to determine changes in the molecular packing structures of muscle and collagen along the tissues .Molecular strain was calculated as the change in the length of the collagen D-period from that point recorded at ‘Resting’  state as described in Madhurapantula et al. (2017) . Ten datThe PM region is most compliant and the greatest strain can be observed in this element in the PM–CT transition in both MV and TV. The molecular strain is highest at around the PM–CT transition, where the corresponding composition scan shows a steep increase in collagen content in the tissue see . This stA similar trend of localization of molecular strain is observed in the CT–LL transition of the MV and TV. Strain is localized at the point in the transition where there appears to be a muscle-like diffraction series. This can be observed using the corresponding composition scans.2D XRD scans were performed on ‘bisected’ CT–LL samples from MV and TV. Local collagen fiber orientations are reported as aligned ellipses with the direction of the major axis pointed along the fiber direction . See MusIndividual sample elements, i.e., PM, CT and LL, were stretched continuously until breakage. The stress vs. strain was calculated and is reported as below. The CT assumes most stress and the least amount of strain. This is in line with the functional aspects of the highly tensile tendons. PM assumes most strain for the least stress, with LL lying between the two other elements. The PM to CT mechanical differences are relatively comparable to data from skeletal muscle–junction tissues examined previously Madhurapantula et al. (2017) , althougWhile application of stretch on individual tissue elements is important to understand material and mechanical properties, transitions may be understood by performing similar stretch experiments on ‘bisected’ samples that leaves these regions (and surrounding structures) intact. As observed in As a crude test of valve material vulnerability in the transition regions, sample failure pulls were performed for the MV and TV. Since the CT possesses the ultimate strength of the assembly, it was bisected and the PM–CT and CT–LL assembles tested. Ultimate strength (stress before the sample is permanently deformed) can be determined from As is evident from the data presented, the PM–CT and the CT–LL transitions present different stress–strain properties in comparison to the ‘pure’ LL, CT and PM sections of the sample . PM is tThe ultimate strength (point on the stress–strain curve marked by permanent deformation) of each region is markedly different . This maFor both the TV and MV, the ultimate stresses within the transition regions (PM–CT and CT–LL) are not much greater than the PM or LL regions  even witCumulatively, this indicates a mechanical vulnerability to failure relative to those more compliant but thick (PM) or compliant due to fibrillar re-arrangement (LL) or materially durable due to dense construction of relativity non-compliant but strong material (CT and LL). Additional materials and methods are located within the Whole, snap-frozen porcine hearts were procured from Carolina Biological Supply . The mitral (MV), tricuspid (TV) and the aortic (AV) valves were carefully dissected en bloc to preserve underlying structures . Valves were dissected with enough clearance to ensure that the samples of interest were not damaged during dissection. The dissected valves were then stored at −20 °C. Samples were thawed overnight at 4 °C before experiments.Clear sections of these valves that consisted of a portion of the leaflet with a singular connection to a CT leading into a PM were identified and dissected. Any branches of the CT were severed, to ensure that there was one main connection between the three tissue elements. The samples were dissected under 1X phosphate buffered saline (PBS) to keep them hydrated during the course of dissection and were stored at room temperature under a paper towel soaked in PBS before experiments. Samples were not stored in PBS buffer longer than 6 h.Samples were evaluated in three modes: (i) full valve samples (LL to CT to PM); (ii) samples ‘bisected’ by cutting the full valve assembly at the middle of the CT, to evaluate the properties of LL to CT and CT to PM transitions, and; (iii) ‘trisected’ samples, i.e., valve elements separated to evaluate the properties of the LL, CT and PM individually.It was determined at an early stage of investigation that a more direct comparison of structure and physiological roles of the MV and TV would be the study priority. Due to the anatomical placement of the aortic and pulmonary valves, dissecting both valves from the same heart may compromise one or both of these valves. Moreover, MV and TV present higher complexity in valve architecture than the pulmonary and aortic valves. The pulmonary valve was excluded due to its relatively low-pressure function and because it is rarely reported to fail. Given these priorities, in a number of instances it was viable to retrieve the aortic valve, hence allowing some limited study of these samples also, reported in the A strain apparatus was constructed based on that previously described in Madhurapantula et al. (2017) . BrieflySamples were mounted between the top and the bottom sample brackets. The stage on the actuator is moved by the stepper motor. An Arduino based program was used to issue commands to stretch the sample. The Arduino also mediates the collection of displacement (mm) vs. load (g) information into text files, which were used for analyses presented here .See Molecular strain, is defined after Madhurapantula et al. (2017) : for colFor muscle, it is the increase in sarcomere length which is directly related to lengthening of the muscle fibers due to myosin and actin fiber sliding in response to an application of stretch . Muscle 2D scans were performed on bisected samples to determine changes in alignment of collagen fibers in the PM–CT and the CT–LL junctions with application of stretch. The initial sample measurements were noted and stretch was applied to the samples at increments of 2% engineering strain. The sample was allowed to relax for 2 min before 10 XRD patterns were collected along the central sections of the LL–CT and CT-PM samples.‘Bisected’ valve samples  were loaded on to the strain rig described herein. Visual markers (‘dots’) were placed on the sample using a marking pen (Sharpie™). These dots were used as fiducial markers. These markers were placed so there was at least one each in the PM or LL and a pair of dots on either side of the transition region . The eloThe video was then used to generate still frames at 5 fps. These frames were imported into ImageJ  for analAlthough it is often reported that CT is the point of valve failure, our data indicate that the definition of which portion of the valve is CT is highly relevant to the material outcomes of the tissue. Although the CT tissue is present through transition regions from the PM to CT and from the CT to LL, its durability through these material regions is different from that of the CT main section. The significance of tissue transition regions have often been overlooked, when studying mechanical behaviors of soft tissues. Emphasis is usually laid on understanding the individual tissue components. However, as is evident from earlier surgical observations ,43 and dThe methods and data presented here allow attribution of material properties to these regions and their behavior under strain. XRD scans enable determination of high-resolution tissue composition in transition regions in their native state (ex vivo) without introducing possible artifacts due to sample preparation  or in downstream data preparation where 2D sample image sections need to be reconstructed into a 3D volume before detailed analysis is performed. The molecular strain analyses in the context of engineering strain, in relation to the tissue composition, provide insights into changes in the molecular packing of materials in samples that lead to strain distribution in these regions in relation to its change in material composition as it transitions from one tissue into another. No other technique, to our knowledge, allows similar static and dynamic analyses of the simultaneously multi-scale properties  collected from a native untreated sample while it is stretched.Studies have shown that virtual reality-based technique used to train surgeons are highly beneficial ,47. The


High strain rate biaxial forging (HSRBF) was performed on AZ31 magnesium alloy to an accumulated strain of ΣΔε = 1.32, the related microstructure, texture and mechanical properties were investigated. It was found that the microstructure evolution can be divided into two steps during HSRBF. In the early forging processes, the refinement of the grain is obvious, the size of ~10 μm can be achieved; this can be attributed to the unique mechanisms including the formation of high density twins ({10 Magnesium alloys are potential materials in airplanes and automobiles, they have good machinability, excellent damping capacity and favorable recycling capability, besides which, the advantage of light weight can save energy and reduce emissions ,2. HowevIt is well known that, different strain paths during forging lead to different metal plastic flows, which consequently results in different shapes and properties . For exaI(0002):I(10:I(10 = 1:0.83:2.21) were comparable to those of a completely random Mg powder (I(0002):I(10:I(10 = 1:0.85:2.44).A commercial AZ31 magnesium alloy with the chemical composition of Mg-3%A1-1%Zn-0.3%Mn was selected in the present study. The as-cast billets were homogenized at 400 °C for 12 h followed by water quenching. The homogenized material was characteristic of coarse grains with grain size of ~400 μm, and few twins were detected . X-ray dRectangular samples for HSRBF were machined from the homogenized ingot, and the height, width and length for the sample was 40, 35 and 35 mm, respectively. The samples were heated in a muffle furnace before forging, and the hold temperature was 350 °C for 5 min. An air hammer was used to conduct biaxial forging along two orthogonal directions in turn as illustrated in λ), and HSRBF was carried out to an accumulated strain of ΣΔε = 1.32, i.e., 6 passes of forging. The billets stretched along the rolling direction (RD) after HSRBF, and no obvious crack was observed.A pass strain of Δε = 0.22 was obtained by accurate controlling of the pass reduction  was selected to make different microstructure characterizations. Optic microstructures were observed using an optical microscope  after etched with a solution of 1 g oxalic acid, 1 mL nitric acid and 98 mL water. Electron back-scatter diffraction (EBSD) observation was conducted on a scanning electron microscope  at 20 kV, and 1.5 mm was selected as a step size in the measure of the orientation imaging. The Schultz reflection method was carried out on X-ray diffraction  to analysis texture. Dog-bone like tensile specimens were machined with a gauge length of 10 mm, and abrasive papers were utilized to polish the surfaces of tensile specimens. A tensile test was conducted under a constant tensile rate of 0.5 mm/min at room temperature, and the tensile direction was parallel to RD. In order to make sure of the repeatability, three experiments for each condition were conducted. The fracture characters of the tensile samples were observed on SEM.Shown in 1,a2,b1,b2) was similar to that observed by OM, in the twinned regions and at grain boundaries some DRX grains were detected, and the fraction of DRX increased significantly with the increase of accumulated strain. Moreover there are two peaks around 38°and 86° in the misorientation distribution map , indicating that {10Shown in tion map a3,b3, inu et al.  and Li eu et al.  have repThe IPF maps and grain size distribution maps of AZ31 alloys HSRBFed with accumulated strain of ΣΔε = 0.88 and 1.32 are shown in As mentioned above, the microstructure evolution of the AZ31 alloy during HSRBF can lead to the refinement and growth of the grain, which was different from alloys forged at low strain rates as reported in references ,21,22,23w strain ,26. As sw strain ,21,22,23w strain .1,b1) also confirms the strong basal texture as the alloys HSRBFed to the accumulated strain of ΣΔε = 0.22 and 0.44. With further increase of accumulated strain, DRX developed fast at twins and the fraction of the DRX grain increased. It was reported that during the hot deformation of magnesium alloys TDRX was of great importance in texture weakening [During uniaxial compression, magnesium tends to form a basal texture with the c-axis parallel to the loading direction, and the (0002) pole rotates towards the compression direction owing to the development of the {10 strains . It is oeakening ; therefoeakening  have reveakening . TherefoIt is acknowledged that a magnesium alloy with tiled texture displays excellent formability; therefore, basal pole inclining is widely used in tailing the texture of a magnesium alloy. Shear deformation is one of the effective methods to achieve tilted-basal texture, which is commonly seen in processes such as equal channel angular pressing (ECAP), differential speed rolling (DSR) and friction stir processing (FSP), and it is reported that the inclinations were 20–45°, 5–15° and up to 55° in ECAP, DSR and FSP alloys, respectively . It was s, ultimate tensile strength (UTS) σb and elongation δ. The alloy in its initial state exhibits poor mechanical properties. However, it is obvious from The microstructure, texture and mechanical properties of the AZ31 alloy during high strain rate biaxial forging (HSRBF) were investigated. The main conclusions were listed as below.The microstructure evolution during HSRBF can be divided into two steps, i.e., grain refinement in the early stage and grain growth with further increase of accumulated strain. A homogeneous fine DRX structure with the average grain size of 9.2 μm was obtained as accumulated strain was 0.88, implying that DRX developed at lower strain during HSRBF.The formation of high density twins, and subsequently twining induced DRX, leads to the grain refinement, and {10The main texture in the HSRBFed alloys is a typical hot-rolled texture, and the intensity of the texture decreases with increasing of the accumulated strain. Moreover, the basal pole rotates towards the direction of forging direction (FD) after each pass, and a basal texture with a basal pole inclining at 15–20° form the rolling direction (RD) formed in the full recrystallized HSRBFed alloy.The strength and elongation increase with the strain as the accumulated strain is lower than 0.88, but decrease slightly with further forging, and an excellent combination of mechanical property with UTS of 331.2 MPa and elongation of 25.1% was achieved at ΣΔε = 0.88, which resulted from the combined effects of grain refinement and weakened basal texture. Therefore, HSRMF is an efficient way to produce strong and ductile wrought AZ31 alloy.


Passive acoustic monitoring systems allow for non-invasive monitoring of underwater species and anthropogenic noise. One of these systems has been developed keeping in mind the need to create a user-friendly tool to obtain the ambient noise indicators, while at the same time providing a powerful tool for marine scientists and biologists to progress in studying the effect of human activities on species and ecosystems. The device is based on a low-power processor with ad-hoc electronics, ensuring that the system has efficient energy management, and that the storage capacity is large enough to allow deployments for long periods. An application is presented using data from an acoustic campaign done in 2018 at El Gorguel . The results show a good agreement between theoretical maps created using AIS data and the ambient noise level indicators measured in the frequency bands of 63 Hz and 125 Hz specified in the directive 11 of the EU Marine Strategy Framework Directive. Using a 2D representation, these ambient noise indicators have enabled repetitive events and daily variations in boat traffic to be identified. The ship noise registered can also be used to track ships by using the acoustic signatures of the engine propellers’ noise. Assessment of good environmental status (GES) in European seas is at the heart of the Monitoring Guidance for Underwater Noise in European Seas: Monitoring Guidance Specifications . It is eIt is not easy to monitor Directive 11 on environmental noise in the various marine areas. Indeed, it is essential not only to monitor underwater noise in specific locations, but also to use models that enable noise maps to be estimated. To create these models, many variables need to be known: water column salinity and temperature, marine traffic location, vessel type, speed, etc. The simulations carried out by the models must be checked and corrected using the experimental data obtained with PAM acoustic recorders, and complemented with the information regarding the sources of noise (mostly ships) that it is possible to obtain by analyzing real data.This manuscript is an extended version of the work published in . In thisWorking with an autonomous PAM recorder such as the SAMARUC involves several steps: first, the device is deployed for several months in a desired location where it registers acoustic information about the species and anthropogenic noises; after that, the system is recovered, the data extracted from device’s memory and saved as wav files in a local server. Finally, the data is analyzed offline by means of specific software (SAMARUC software is registered by UPV ). The SAThe system’s main component is a general-purpose, ultra-low power consumption digital signal processor (DSP) from Texas Instruments, the TMS320C5535. The selection of the DSP is made as a trade-off among price, low-power consumption, flexibility, and reliability. An adequate selection of the DSP and peripherals allows the time between service intervals to be increased and the battery life extended.The AIC3204 has been set up to perform a BIQUAD filter to establish 192 kHz as a sampling frequency, and it is able to add a gain in order to amplify the signal if it is necessary to increase the sensitivity of the selected hydrophone depending on the marine strategy deployment category. In any case, a system sensitivity (hydrophone + AIC3204 gain) of between −165 and −185 dB re 1 V/uPa is recommended [Data transmission is set up in DMA Ping-Pong mode, so the system records acoustic data without sample loss while storing that data in the microSD cards. The Ping-Pong settings allow a buffer (PING_PONG buffer) to be used, which is internally divided into two subbuffers , allowing the status of each subbuffer to be checked for the tasks to be carried out in parallel. Thanks to the integration of the two DMAs, simultaneous transmission between memory and peripherals is available. A dedicated electronic board was designed whose functions include, among others, adding a second microSD card to double the available storage capacity. This electronic design  and gain. All this information is loaded on powering up the device. The Block-File allocation table stores information about the block start and block end of each of the files, as well as the time stamp of the first sample. Finally, the data section stores the samples of the recording in the different blocks of the uSD card. The system is put into sleep mode during the OFF cycle to preserve battery life.A pressure case was built from a tube of 6082 aluminum anodized with NITUFF, measuring 12 × 70 cm (diameter × length). This material was chosen according to relevant factors such as its durability (the anodized NITUFF is used in military marine applications) and light weight. Pressure tests were performed to guarantee that the housing can withstand a pressure of 50 atmospheres, corresponding to a depth of 500 m.Moreover, to maximize the energy density in the cylindrical housing, a hexagonal layout of D-cell batteries was created. The battery block to supply power to the electronic components is composed of 7 × 4 D-type batteries  on the south-east coast of the Mediterranean Sea . This location allows the existing marine traffic in the Port of Cartagena to be monitored.The seabed in this area is not uniform and consists basically of mud. As described above, the system is prepared for 500 m depth deployments, but in this case, a depth of 60 m was chosen given the bathymetric profile of the exploration area. The device was placed 10 m from the seabed (reducing its acoustic influence) at a depth of 50 m using a 70 kg anchoring weight. The minimum distance between the device and the vessels’ permitted transit area was approximately 150 m  was choUsing the temperature, salinity, and depth/pressure data from the Argo profiler available on the EMODNET website , the souOne of the most important uncertainties in noise modelling is the source level assigned to each vessel, considered to be a noise emitter in the marine zone under study. Ships as an underwater acoustic source are a widely studied problem that remains open due to the complexity of the sound field emitted by each part of the ship at a given frequency. Several kinds of experimental models have been developed in recent decades, from the Ross model  that preSince the frequencies studied in this work are 63 Hz and 125 Hz, we chose the RANDI model to parameterize the source level of each ship considered in the computed AIS data. This method is validated for frequencies between 28.4 Hz–191.6 Hz. The mean value of the Sound Pressure Level (SPL) over the location was calculated considering the AIS data from vessels that have non-zero speed over ground.v), closest point of approach (CPA), and draft can be estimated using a PAM system equipped with a single broadband hydrophone [Acoustic signatures of ship engine propeller noise can be used for noise characterization as well as for target tracking. Engine harmonics can be examined for full awareness of the effect of the different ships in the 1/3 octave ambient noise indicators. Additionally, vessel speed 2πfnt was obtained in Equation f(t)The results obtained considering ray theory approximation are summarized in the sound maps of daily SPL dB re 1 uPa at a depth of 50 m. Daily sound maps of Going back to real data obtained by SAMARUC, we calculated the average one-third-octave band  for an integration interval of one hour at the same timestamp times of the modelling calculations. As The results show a good agreement between experimental and theoretical calculations, verifying not only that the device worked properly and the numerical simulations were valid, but also that the calibration of the system performed well at IEO-UPV’s facilities, an aspect not easy to achieve due to the low frequency range considered.In addition to the aforementioned results, the computed 1/3 octave indicators can be conveniently structured in hours and days, and represented as a 2D color map to provide an acoustic panorama and identify seasonal events . This reLet us now select one of the recordings containing a ship passing within the range of the SAMARUC system. The spectrogram for these real signals is shown in the left panel of v, and The U-shaped structure and Doppler shift can be used to estimate the values for quations  and  as an example, we have illustrated how the theoretical sound maps can be created using marine traffic information, and how the real data can be used to experimentally validate the estimated sound pressure levels associated with continuous noise coming from anthropogenic activities. The system designed efficiently managed the power consumption and thus it is appropriate for long deployments. This fact allowed 2D ambient noise maps to be created, which could be used to identify seasonal events and to characterize ships by means of their acoustic signatures.