Trypanosoma brucei rhodesiense in tsetse populations is essential for understanding transmission dynamics, assessing human disease risk and monitoring spatio-temporal trends and the impact of control interventions. Although an important epidemiological variable, identifying flies which carry transmissible infections is difficult, with challenges including low prevalence, presence of other trypanosome species in the same fly, and concurrent detection of immature non-transmissible infections. Diagnostic tests to measure the prevalence of T. b. rhodesiense in tsetse are applied and interpreted inconsistently, and discrepancies between studies suggest this value is not consistently estimated even to within an order of magnitude.Measuring the prevalence of transmissible Trypanosoma brucei s.l. and T. b. rhodesiense in Glossina swynnertoni and G. pallidipes in Serengeti National Park, Tanzania: (i) dissection/microscopy; (ii) PCR on infected tsetse midguts; and (iii) inference from a mathematical model. Using dissection/microscopy the prevalence of transmissible T. brucei s.l. was 0% (95% CI 0–0.085) for G. swynnertoni and 0% (0–0.18) G. pallidipes; using PCR the prevalence of transmissible T. b. rhodesiense was 0.010% (0–0.054) and 0.0089% (0–0.059) respectively, and by model inference 0.0064% and 0.00085% respectively.Three approaches were used to estimate the prevalence of transmissible T. brucei suggesting the zero prevalence result was attributable to insufficient sample size (despite examination of 6000 tsetse). Given the prohibitively high sample sizes required to obtain meaningful results by dissection/microscopy, PCR-based approaches offer the current best option for assessing trypanosome prevalence in tsetse but inconsistencies in relating PCR results to transmissibility highlight the need for a consensus approach to generate meaningful and comparable data.The zero prevalence result by dissection/microscopy  is not unusual by this technique, often ascribed to poor sensitivity. The application of additional techniques confirmed the very low prevalence of  Human African trypanosomiasis is a fatal disease that is carried by a tsetse vector. Assessing the proportion of tsetse which carries human-infective trypanosomes is important in assessing human disease risk and understanding disease transmission dynamics. However, identifying flies which carry transmissible infections is difficult, due to potential presence of other trypanosome species in the same fly, and concurrent detection of immature infections which are not transmissible. We used three methods to estimate the proportion of flies carrying human-infective trypanosomes: dissection and microscopic examination of flies to visualise trypanosomes directly in the fly; PCR of fly midguts in which trypanosomes were observed by microscopy; and theoretical analysis using a mathematical model of disease transmission. All three methods found the prevalence to be extremely low. Given the low prevalence, dissection/microscopy requires prohibitively large sample sizes and therefore PCR-based approaches are likely to be of most value. However, interpretation of PCR data is not straightforward; whilst PCR identifies flies carrying pathogen genetic material it does not directly identify flies with transmissible infections. This study highlights the need for a consensus approach on the analysis and interpretation of PCR data to generate reliable and comparable measures of the proportion of flies which carry transmissible human-infective trypanosomes. Plasmodium spp Oncocerca volvulusLeishmania spp. Wuchereria bancrofti, Brugia malaya and Brugia timoriFor the vector-borne diseases, pathogen prevalence in a vector population is an indicator of disease risk, and accurate measures of the proportion of vectors carrying infections are needed for (i) guiding allocation of resources or targeting intervention programs Trypanosoma brucei rhodesiense and transmitted by tsetse flies (Glossina spp). Measuring the prevalence of T. b. rhodesiense in the tsetse vector is of particular importance as HAT occurs in developing countries where resources for surveillance and disease control are limited Human African trypanosomiasis (HAT) is caused in East Africa by Duttonella or vivax-like, trypanosomes located in the mouthparts and midguts are classified as Nannamonas or congolense-type, and trypanosomes found in the midgut and salivary glands are Trypanozoon or brucei-like. When trypanosomes are found only in the midgut, the infection is assumed to be immature. This dissection/microscopy technique has several disadvantages for use in field studies: it is not possible to differentiate below the level of subgenus ; mature and immature infections cannot always be differentiated; and mixed infections cannot be identified or discriminated. Dissection and trypanosome identification are highly dependent on operator skill, and there exist variations in protocols, with some authors only examining the midgut and salivary glands if trypanosomes are found within the mouthparts Assessment of the prevalence of trypanosomes within tsetse populations has traditionally comprised dissection and microscopic examination of the mouthparts, midguts and salivary glands of the fly, relying on the differing development and maturation sites of the trypanosome subgenera to identify trypanosome species T. b. rhodesiense and its morphologically-identical subspecies Trypanosoma brucei brucei (not pathogenic to man) can be accurately differentiated A suite of molecular tools has been developed for the trypanosomatids Nannomonas or T. congolense-like and Duttonella or T. vivax-like infections are classified as the same species by both techniques). For T. brucei sensu lato, with its potential for human infection, this presents a particular problem. In areas where T. b. rhodesiense is known to occur in wildlife and livestock hosts, and human cases are reported, the majority of studies of T. brucei s.l. in tsetse by dissection/microscopy show prevalence of zero, even when thousands of flies are examined T. brucei s.l. DNA has been found, with 2% of G. palpalis and 18% of G. pallidipes testing positive However, when it comes to assessing the prevalence of trypanosome infections in tsetse it is clear that the results generated by dissection/microscopy do not correlate well with data generated by PCR , Tanzania. Whilst cases of HAT have been reported in this area for over one hundred years G. swynnertoni flies (0.08%) infected with T. brucei s.l. T. brucei s.l. in G. swynnertoniPrevious studies carried out in SNP have relied on dissection/microscopy to determine tsetse prevalence . Large sT. brucei s.l. and T. b. rhodesiense in the two main tsetse species in SNP, G. swynnertoni and G. pallidipes, using (i) dissection/microscopy and (ii) PCR analysis of infected midguts and salivary glands. A third approach was applied to infer the prevalence of T. b. rhodesiense in tsetse from a mathematical model of disease transmission, to examine whether previously reported low prevalences were consistent with other parameters that have been estimated for this system.This study assessed the prevalence of All field work was conducted in SNP, Tanzania, between October and November 2005 and August and October 2006. Tsetse sampling was carried out with the Tsetse and Trypanosomiasis Research Institute, Tanga, Tanzania. Seven sites were randomly selected for tsetse trapping in savannah and open woodland areas, within 1 km of roads and within a 40 km radius of park headquarters at Seronera, where tsetse dissection was conducted (coordinates UTM 36M (i) 711676, 9731432; (ii) 706816, 9733868; (iii) 710747, 9733536; (iv) 695691, 9727934; (v) 700825, 9746320; (vi) 693961, 9733122; (vii) 695278, 9741360). In each study site, three Epsilon traps All live non-teneral flies were dissected and labrum, hypopharynx, salivary glands and midgut examined for trypanosomes under 400× magnification All trypanosome-positive midguts and salivary glands were macerated in phosphate buffered saline and applied to FTA Classic cards  for further analysis. A subset of trypanosome-negative midguts was also preserved on FTA cards. FTA cards were allowed to dry for two hours and stored in foil envelopes with dessicant at ambient temperature prior to processing. For each sample, one disc of diameter 2 mm was cut out from the FTA card using a Harris Micro Punch™ tool. Between cutting of the sample discs, 10 punches were taken from clean FTA paper, to prevent contamination between samples. Discs were washed for two washes of 15 minutes each with FTA purification reagent , followed by two washes of 15 minutes each with 1X TE buffer . Each disc was dried at room temperature for 90 minutes, and then used to seed a PCR reaction. After every seven sample discs, a negative disc was included and the punch tool and mat cleaned, to reduce the risk of contamination between discs, and ensure that any potential contamination would be detected. No evidence of contamination was seen in the sequence of dissection or PCR results.T. b. brucei, T. b. rhodesiense and T. b. gambienseT. brucei s.l., T. b. rhodesiense was differentiated from T. b. brucei by detection of the serum-resistance associated (SRA) gene. Simultaneous amplification of another single copy gene, a phospholipase C (PLC) sequence found in T. brucei s.l., confirmed that there was sufficient T. brucei s.l. material present in the sample to detect the presence of T. b. rhodesienseTBR primers were used to detect a 177 bp satellite repeat sequence common to For all PCRs, one negative control (water) and one positive control (genomic DNA) were run for every 16 samples, in addition to negative control blank discs. PCR products were run on a 1.5% (w/v) agarose gel at 100 V, stained with ethidium bromide and visualised under an ultraviolet transilluminator.T. b. rhodesiense in a tsetse midgut does not indicate a mature infection as only a small proportion of midgut infections will develop to mature infections in the salivary glands. The following calculation was used to predict the prevalence of mature transmissible T. b. rhodesiense infections, where posDis is the proportion of flies with midguts which were positive by dissection/microscopy, posPCR is the proportion of these which tested positive by PCR, Tbr/TbbP is the proportion of T. brucei s.l. positive flies with sufficient genetic material present (ie give positive results with PLC PCR) which test positive for T. b. rhodesiense (as determined by SRA PCR) and matP is the proportion of immature T. b. rhodesiense infections which develop to maturity in the salivary glands, estimated to be 0.12 (CI 0.10–0.14), T. brucei s.l. will have midgut infectons; (ii) that TBR PCR has 100% sensitivity and specificity for detection of T. brucei s.l. in tsetse midguts; (iii) that SRA PCR has 100% sensitivity and specificity for detection of T. b. rhodesiense, if the sample is positive on PLC PCR. The implications of potential assumption violations on the prevalence estimate are addressed in the discussion.Detection of matP was taken from Milligan et al. (1995) the distribution of the original data was used, where Y is the number of flies with midgut infections and matP is the proportion of these which developed mature salivary gland infections . Potential values were generated by sampling from the following nested distributions with 10 000 iterations, and ninety five percent confidence intervals calculated by taking the 2.5% and 97.5% quantiles of the values obtained: 1∼binom, n2∼binom, n3∼binom, p1∼binom, n4∼binomn.Confidence intervals were calculated by repeat sampling from nested distributions of the data. Since the value for x) and two vector populations . Although occasional cases of human African trypanosomiasis do occur, the rate of human feeding by tsetse is very low , so the human population was not included in the model. The model is described by the following equations:http://www.r-project.org/) to give equilibrium conditions for the prevalence of T. b. rhodesiense in wildlife hosts, G. swynnertoni and G. pallidipes and which could be compared to empirically derived estimates of prevalence.Rogers' T. b. rhodesiense, and to G. swynnertoni and G. pallidipes, were used where possible. The proportion of tsetse developing salivary gland infection after feeding on an infected cow is 16% for G. morsitans (closely related to G. swynnertoni) and 2.1% for G. pallidipesT. brucei s.l., either proving uninfectible in experimental infections eg baboons et al.T. b. rhodesiense in G. morsitans flies; no specific data were available for G. pallidipes so the same value was used. Wildlife host parameters have been chosen to represent all wildlife species. Duration of incubation period and duration of infection are therefore estimated mean values from experimental infections of wildlife T. brucei s.l. in lions Parameters were based on those described by Rogers http://www.r-project.org).All statistical analyses and model solving were carried out using R 2.12.1  and 2099 G. pallidipes . Overall, trypanosomes were observed  in 9.2% of G. swynnertoni , and 3.7% of G. pallidipes  examined. No salivary gland infections were observed. Using the classical trypanosome species identification based on the location of parasites within the fly, the prevalence of T. vivax-like, T. congolense-like and T. brucei-like trypanosomes is shown in In total, 6455 tsetse were dissected and examined, comprising 4356 posDis×posPCR, assumed to represent T. brucei s.l. immature infections) was 0.83% in G. swynnertoni and 0.71% in G. pallidipes. All midguts that tested positive for T. brucei s.l. were further analysed with SRA PCR, with 10 out of 43 PLC positive and 1 of these SRA positive, therefore the proportion of T. brucei s.l. testing positive for T. b. rhodesiense was 0.1. Using the expression in Eq. 1, this gives a predicted prevalence of transmissible T. b. rhodesiense infections of 0.010% for G. swynnertoni and 0.0085% for G. pallidipes  and 0.0035% for females (20/2289), and in G. pallidipes was 0.019% for males (5/541) and 0.0024% for females (7/1151).For 5428 flies , all midguts where trypanosomes were observed (n = 133) were analysed by PCR . No fliellidipes . The preT. brucei s.l.. None of these tested positive with PLC or SRA.Midguts from 78 flies with no trypanosomes observed on microscopy were also analysed by PCR. Of these, 3.8% (n = 3) tested positive for T. b. rhodesiense of 0.0064% in G. swynnertoni and 0.00085% for G. pallidipes. The model predicted the prevalence of T. b. rhodesiense in wildlife hosts to be 2.5%, which is within the range of reported prevalences in wildlife in SNP of 1.8% and 4.3% Assuming equilibrium, the model yielded prevalences of The results of all three approaches are presented in T. b. rhodesiense infections in tsetse populations in Serengeti National Park. Fundamental difficulties have been identified associated with the detection of trypanosome infections in tsetse, requiring new approaches to move beyond generation of infection prevalence data to make inferences about transmissibility. The three approaches used in this study confirmed the prevalence of T. b. rhodesiense in SNP to be very low. The prevalence of T. brucei s.l. measured by dissection/microscopy was zero, despite confirmation by the other techniques that T. brucei s.l. was circulating in the area, and evidence of infection in wildlife and human hosts, highlighting a common problem with this technique. The results from PCR analysis of tsetse midguts were used to generate a measure of transmissible infections. In addition, a mathematical model of disease transmission used to predict the prevalence of transmissible infections based on other parameters for this system, confirmed the low prevalence gained by other approaches was compatible with the prevalence of T. b. rhodesiense in wildlife hosts reported in SNP. This study highlights specific challenges in measuring transmissible T. b. rhodesiense infections in tsetse, which have important implications for assessing this variable, and interpreting temporal and spatial patterns of infection in affected areas of Africa.In this study we present data obtained from three different approaches to measuring the prevalence of transmissible T. brucei s.l. in tsetse populations as zero, despite strong evidence to indicate the presence of infection in tsetse using other techniques, and evidence for circulation of T. b. rhodesiense in vertebrate hosts in the same area T. brucei s.l. infections in mice, both in laboratory and field studies T. brucei s.l. infected flies in Glossina palpalis palpalis in Cote d'Ivoire These results illustrate the difficulties of dissection/microscopy techniques, which in this study estimated the prevalence of T. b. brucei and T. b. rhodesiense. The dissection/microscopy technique was first discussed in detail by Lloyd and Johnson in 1924 as an alternative to cumbersome rodent inoculation studies. However, Lloyd and Johnson relied principally on morphology of the developmental and infective forms, using the location within the fly only as an additional aid. It is clear that in areas where the prevalence is very low, dissection is less than ideal. However, since the majority of historical studies have relied on dissection/microscopy it is important to understand how these data compare to those generated by other techniques if we want to be able to detect temporal trends.Dissection/microscopy has a number of other disadvantages: it is time consuming and requires skilled technicians, and whilst it does not require substantial investment in technology, this may be outweighed by high staff costs. Identification of species, mixed infections and immature infections is unreliable, particularly if other trypanosome species are also of interest. Furthermore dissection/microscopy alone cannot differentiate between T. b. rhodesiense. We found that 30% of microscopy-positive midguts tested positive for T. brucei s.l. by PCR in G. swynnertoni and 41% in G. pallidipes. It is difficult to compare these directly with other studies as protocols vary widely, but between 7.9% and 19% of microscopy-positive midguts have been reported testing positive for T. brucei s.l. in these tsetse species T. b. rhodesiense infections which mature to the salivary glands to estimate the prevalence of mature transmissible infections. The prevalence was within the confidence limits of dissection/microscopy and similar to the predictions of the model. Prevalence was higher in males than females, reflecting the increased probability of maturation in males T. brucei s.l. in midguts by PCR means the sample size can be lower for the equivalent precision, reducing field costs and time compared to the substantial sample sizes needed for dissection/microscopy only.PCR-based techniques have the potential to provide a sensitive and specific tool to identify flies carrying T. b. rhodesiense infections by incorporating dissection/microscopy and PCR data relied on assumptions regarding the sensitivity of dissection/microscopy for detecting midgut trypanosome infections, and the diagnostic sensitivity and specificity of TBR and SRA PCRs when used on tsetse midgut samples. Whilst identification of trypanosomes in the midgut is widely used in the laboratory there is little data available on the sensitivity of this technique in the field. There is however no evidence to suggest that flies can carry T. brucei s.l. without trypanosomes being present in the midgut. TBR and SRA PCRs have high specificity The calculation used to predict the prevalence of mature Imperfect test sensitivity and specificity can significantly affect prevalence estimates, particularly when the prevalence is very low T. brucei s.l. infections were identified as T. b. rhodesiense. Whilst this is not outside the range of values found in previous studies T. b. rhodesiense, so our estimate of the proportion of T. brucei s.l. which are T. b. rhodesiense is not very precise . Using the value of 33% resulted in a prevalence of T. b. rhodesiense in G. swynnertoni of 0.03% and in G. pallidipes of 0.028%.In this study, 10% T. brucei s.l. by PCR. Previous authors have found high prevalences of T. brucei s.l. by PCR . In this study we relied on experimental measures of the proportion of midgut T. b. rhodesiense infections which mature to the salivary glands to estimate the prevalence of transmissible infections. However there are two areas for concern with this assumption: (i) laboratory studies may not accurately reflect the situation in the field; and (ii) this proportion is known to vary with factors such as sex, levels of certain antioxidants, mating in female flies, and environmental factors such as temperature To interpret data from PCR analysis it is important to be clear what PCR results do or do not represent. For example, identification of The second concern is with respect to comparative data analysis, in that the variety of techniques used means it is difficult to assess trends in prevalence. This is a significant problem – prevalences measured in different ways cannot be compared between different areas or times, making it impossible to detect changing disease dynamics and human disease risk, and hindering our understanding of the complex relationships between trypanosomes, hosts and vectors. Agreement on an optimal protocol for the collection and interpretation of data on trypanosome prevalence in tsetse populations would be helpful in generating more comparable data.T. b. rhodesiense in G. swynnertoni and G. pallidipes in SNP can be sustained at very low levels. Both the PCR data and the model suggest that G. pallidipes may play a role, albeit a lesser one, in T. b. rhodesiense transmission as well as G. swynnertoni, which has always been regarded as the important vector species in Serengeti. The two species differ in both feeding preferences and vector competence; while both species include suids and bovids in their diet, G. swynnertoni feeds predominantly on warthog while G. pallidipes feeds predominantly on buffalo G. swynnertoni and G. pallidipes are known to avoid feeding on man, this effect is particularly evident for G. pallidipesThis study shows that the prevalence of T. b. rhodesiense in tsetse found in this study suggests that the risk of HAT to tourists is low. Odour-baited tsetse traps are known to target older flies The low prevalence of the prevalence of transmissible human infective trypanosomes in tsetse populations is an important parameter but there is no ideal diagnostic test to measure it. While new molecular diagnostic tools offer great potential for epidemiological studies, many challenges remain in the interpretation of field data generated from these tools, and these need to be recognised and addressed. Development of protocols that directly measure the prevalence of transmissible infections, and the consistent application of such protocols, would aid our knowledge of human disease risk, allow detection of spatial and temporal trends in disease transmission and add to our understanding of complex disease systems.In conclusion


Living systems are often maintained by information flows and, as such, they present interesting mathematical problems for example, in the modeling and analysis of spatial structures, self-organization, environmental interaction, behavior, and development. Biomedical signals extract information from the complex phenomena being measured, which are typically a time series having both a regular and random components. Solutions attempt to map general principles, which are used to model how the living systems work. Many researchers have been studying these problems because of their interesting mathematical features and because of their scientific importance. The focus of this special issue is the mathematical analysis and modeling of time series in living systems and biomedical signals. It is mostly interested in the related new development of both theoretical study and practical implementation, either with modeling, complexity, statistics, or signal transformation in living systems.The papers selected for this special issue represent a good panel in recent challenges. The topics of the research papers and review papers are connected with the living systems and biomedical signals, including modeling dynamical complexity in living systems, for example, network dynamics, mass action, dynamical systems theory, methods for analysis and characterization of dynamical complexity, biomedical signal analysis such as mathematical pattern analysis of biological signals, generative mechanisms of biological signal patterning, implementation of signal analysis algorithms, linking biological structure to biological signal generation, and intracellular signal processing, as well as related models and applications, such as systems theory, biological organization, and biomedical information processing.This special issue contains 31 papers. In the category of modeling dynamical complexity, L. Sena et al. present a fuzzy model to interpret data of drive performances from patients with sleep deprivation. S. Chen et al. review the modeling of biological intelligence for supply chain management system optimization. M. Li presents approximating ideal filters by systems of fractional order. L. T. Ko et al. present nested quantization index modulation for reversible watermarking and its application to healthcare information management systems. C. Cattani studies on the existence of wavelet symmetries in Archaea DNA. A. Ciancio and C. Cattani present separable transition density in the hybrid model for tumor-immune competition. Q. Guan et al. present solid dynamic models for analysis of stress and strain in human hearts. G. Xiong et al. present theorems and application of local activity of CNN with five state variables and one port. L. Fanea et al. present theoretical compartment modeling of DCE-MRI data based on the transport across physiological barriers in the brain. M. Crisan et al. present a multicriteria optimization model for the study of the efficacy of skin antiaging therapy.In the category of methods for analysis of dynamical complexity, L. Xu et al. present high resolution remotely sensed small target detection by imitating fly visual perception mechanism. J. Zhang et al. present target contour recovering for tracking people in complex environments. M. Li and W. Zhao present a report on CPNs for asymptotic identity in min-plus algebra. M. Xu and C. Wei present remotely sensed image classification by complex network eigenvalue and connected-degree. J. Wen et al. present a batch rival penalized expectation-maximization algorithm for Gaussian mixture clustering with automatic model selection. M. Štrbac and D. Popovic show a software tool for the prosthetic foot modeling and stiffness optimization. T. Carletti and A. Filisetti present the stochastic evolution of a protocell: the Gillespie algorithm in a dynamically varying volume. In the category of biomedical signal analysis, S. Chen and X. Li review the annual progress of functional magnetic resonance imaging for imaging neural activity in the human brain. H. C. Hsin et al. present an adaptive coding pass scanning algorithm for optimal rate control in biomedical images. I. Chiorean et al. present a medicoeconomic index for photo-induced skin cancers. C. Vicas et al. present the influence of expert dependent variability over the performance of noninvasive fibrosis assessment at patients with chronic hepatitis C, by the means of texture analysis. G. Nut et al. present a finite element method applied to a problem of blood flow in vessels. S. Chen et al. summarize recent advances in morphological cell image analysis. C. Yao et al. present motion analysis of live objects by super-resolution fluorescence microscopy. H. Castillejos et al. present wavelet transform fuzzy algorithms for dermoscopic image segmentation. D. A. Mitrea et al. present abdominal tumor characterization and recognition using superior order cooccurrence matrices, based on ultrasound images. Q. Guan et al. present a method for modeling and representation of human hearts for volumetric measurement. X. Li et al. present characteristics of evoked potential multiple EEG recordings in patients with chronic pain by means of parallel factor analysis. A. I. Mitrea et al. present iterative methods for obtaining energy-minimizing parametric snakes, with application to medical imaging. K. Lu et al. present nonlocal means based denoising for medical images. K. T. Q. Dang et al. present detecting epileptic seizure from scalp EEG using Lyapunov spectrum.Of 67 submissions, 31 papers are selected in this special issue. Of course, the topics and papers are not an exhaustive representation of the area of biomedical signal processing and modeling complexity of living systems. It can be seen that although some solutions and models become available, most problems remain open and research is highly active in this field. In the near future, we expect more contributions that will address all of the key aspects raised above. Nonetheless, the special issue represents the recent concerns in the community and we have the pleasure of sharing them with the readers.


The authors would like to provide a clarification in relation to several aspects of the article: While the article cites heat maps in several occasions, we appreciate that it could have been made clearer that the article is not describing a new tool for visualization of data but rather a simpler application of an existing one; we would thus like to make the following changes to the Abstract and Introduction sections: Abstract, first sentence of Method section should read: Method: We propose a simple use of an existing tool for visualization of data, known as a ''quilt plot'' , that provides an alternative to presenting large volumes of data as frequency tables. Introduction  should read: In the statistical literature, ''quilt plots'' , have been underutilised for the display of categorical data . We would also like to clarify that the term 'quilt plot' was originally developed by Douglas Nychka -reference 5 in the article. In addition, in compliance with the journal's policy, we are providing the codes for the R functions described in the article:http://www.plosone.org/attachments/pone.0085047.comment1.rhttp://www.plosone.org/attachments/pone.0085047.comment2.rhttp://www.plosone.org/attachments/pone.0085047.comment3.rhttp://www.plosone.org/attachments/pone.0085047.comment5.r


Mycobacterium tuberculosis and Mycobacterium leprae are the most notable mycobacterial human pathogens, Mycobacterium bovis, Mycobacterium avium subsp. avium, Mycobacterium avium subsp. paratuberculosis, Mycobacterium ulcerans, and other mycobacteria are the etiology of important diseases in humans and a wide range of animal species including, cattle, sheep, goats, deer, possums, badgers, elephants, dogs, cats, birds, amphibians, and fish. Moreover, species such as M. bovis represent serious zoonotic pathogens and have become important agents at the interface of humans, domestic livestock, and wildlife. Although M. bovis. Accordingly, M.V. Cunha et al. describe the current status of bovine tuberculosis in Portugal, discussing interspecies transmission and the impact of infected wildlife on the status of tuberculosis in cattle. Many mycobacterioses occur in nonmammalian hosts and K. Dhama et al. provide an in-depth review of avian mycobacterioses.This special issue on mycobacterial diseases of animals contains 26 papers comprising 6 reviews, 3 case reports, and 17 original research papers on various topics including animal models, immunology, epidemiology, microbiology, pathology, environment, and history. Authors from 13 different countries provide a diverse examination of mixed topics. The first 6 papers are reviews; M. Munyeme and H. M. Munang'andu discuss numerous anthropogenic factors that impact wildlife, livestock, and humans in the habitat of the endangered lechwe antelope. Bovine tuberculosis eradication efforts are impeded by the presence of an established wildlife reservoir of  In many species, pathogenic mycobacteria undergo a prolonged asymptomatic, or latent period, after which disease is reactivated in a subset of infected hosts. Containment of disease and latency likely coincide with shifts in host immune response. Accordingly, B. L. Plattner and J. M. Hostetter thoroughly review the role of gamma/delta T-lymphocytes in mycobacterial diseases of humans, cattle, and mice.The last 2 reviews are historical in nature. First, M. Good and A. Duignan discuss tuberculin, the mainstay of TB testing. Their review emphasizes the origins, properties, limitations, and use of tuberculin in control programs, leading to the final review in which M. V. Palmer and W. R. Waters describe the genesis of the US bovine tuberculosis eradication effort in 1917. The authors describe laudable research conducted by veterinarians and other scientists, decades before an eradication program existed. Mycobacterium celatum-induced disease in heretofore-unrecognized hosts in Slovenia. W. R. Waters and colleagues describe herds of fallow deer and elk with unusually high disease prevalence. The authors demonstrate the apparent misdiagnosis of numerous M. bovis-infected deer and elk and show the usefulness of novel serology based diagnostic tests. M. Carstensen and M. W. DonCarlos detail the uncovering of M. bovis in deer and cattle in Minnesota and their efforts to identify deer to cattle transmission, determine the prevalence of disease in free-ranging deer, and methods used to prevent the establishment of a persistent wildlife reservoir. The next 3 papers are best described as case reports, discussing mycobacterioses in wildlife. M. Pate et al. provide the first description of M. bovis via aerosol as a model for evaluation of tuberculosis vaccines. Research papers continue with a focus on epidemiology. S. Barandiaran et al. reminds us of often-overlooked hosts of bovine tuberculosis such as swine, examining transmission of M. bovis from cattle to swine using spoligotyping. Disease transmission between livestock and wildlife is of great interest. The next 2 papers focus on that interface. C. C. Okafor et al. examine deer to cattle transmission of M. bovis in northern Michigan. From Canada, T. K. Shury and D. Bergeson describe the use of various diagnostic strategies, as well as lesion distribution, and epidemiology of tuberculosis in elk and white-tailed deer in southwestern Manitoba. Animal models of tuberculosis are extremely useful, particularly when conservation or ethics prevent experimental infection of the host of interest. This special issue's original research papers begin with L. McCallan et al.'s thorough description of ferrets infected with Mycobacterium avium subsp. paratuberculosis (Map) and Crohn's disease raises questions of public health significance. To that end, H. Okura and colleagues document a low prevalence of Map in muscle from Map-infected cattle, suggesting a bacteremic phase in bovine paratuberculosis. Emphasizing the broad host range of the myriad mycobacterial species, L. Durnez and colleagues discuss the presence of various mycobacteria in insectivores and rodents on cattle farms in Tanzania and compare findings to mycobacteria isolated from cattle. Switching pathogens, host, and geography, A. A. Rita et al. examine the prevalence of ovine paratuberculosis in Italy using both serology and fecal culture. The suggested link between M. bovis and Map are known to persist in the environment, which facilitates interspecies and intraspecies transmission. As a result, A. E. Fine et al. detail the survivability of M. bovis on various feedstuffs and organic matter. Prolonged survival in soil is a feature of Map. However, E. A. Raizman and collaborators show that not only can Map survive in soil, but also can pass through soil to ground water potentially finding its way to local watersheds. For researchers of paratuberculosis, the survivability of samples in the laboratory is important. E. A. Raizman et al. examine the effect of prolonged frozen storage on Map viability. Both Map and Mycobacterium avium subsp. avium. It is believed that exposure to nontuberculosis mycobacteria, such as Map, can result in falsely positive tuberculin skin test reactions. Consequently, S. D. Fitzgerald et al. document a low number of false-positive tuberculin test reactors in Michigan among cattle with confirmed Map infection. J. A. Fernández-Silva et al. use molecular epidemiological tools to characterize Map isolates from cattle in Colombia, while F. Delgado et al. describe the use of in situ PCR for detection of Map in formalin-fixed samples.Great effort and immense resources have been expended to study the diagnosis of mycobacterial diseases. Further complicating diagnosis can be concurrent infection by multiple mycobacteria in the same host. Using a gamma interferon release assay, C. Barry et al. examine the cell-mediated immune response of cattle experimentally infected with both M. bovis includes most mammals including wild species such as African Cape Buffalo. Tuberculosis in buffalo on public and private lands is of concern not only from an animal health and conservation perspective, but also from an economic perspective due to the negative impact on ecotourism. Consequently, H. M. Munang'andu et al. describe the use of tuberculin testing in the formation of a tuberculosis-free herd of buffalo in Zambia's Kafue Basin.The host range of Map, on phagocytosis and pathogen survival in bovine macrophages.Diagnosis of mycobacteriosis is accomplished either by confirming the pathogen's presence or examination of host immune response to the pathogen. Investigation of host immune response is foundational to the development of novel diagnostics. A. Jolly et al. examine the effects of antibodies, induced by the highly immunogenic lipoarabinomannan of M. tuberculosis are of serious concern. Emphasizing the zoonotic nature of M. bovis, S. D. Fitzgerald and colleagues examine M. bovis isolates from deer in the endemic region of Michigan for evidence of drug resistance similar to MDR and XDR patterns seen in M. tuberculosis. In humans, (multidrug resistant) MDR and (extensively drug resistant) XDR strains of


Anopheles coastalis, now known as Anopheles gambiae, was first discovered as the vector of malaria, in 1899. That discovery led to a pioneering vector research in Sierra Leone and neighbouring Liberia, where mosquito species were extensively characterized. Unfortunately, the decade long civil conflicts of the 1990s, in both countries, resulted in a stagnation of the once vibrant research on disease vectors. This paper attempts to fill in some of the gaps on what is now known of the distribution of the sibling species of the An. gambiae complex, and especially the An. coluzzii and An. gambiae s.s, formerly known as the An. gambiae molecular M and S forms respectively, in the cities of Freetown and Monrovia.It was in Freetown, Sierra Leone, that the malaria mosquito  Anopheles gambiae  was first incriminated as a vector of malaria by Sir Ronald Ross in Freetown, Sierra Leone in 1899 Anopheles gambiae complex are the major vectors of malaria in West Africa. As such studying their distribution, ecology and population structure is essential for effective malaria control programs. In the majority of West African countries, various studies on these important vectors have been undertaken in details. However, there is a gap in knowledge of these vectors in post conflict countries such as Sierra Leone and Liberia where ecological studies could not be undertaken in the 1990s and early 2000s because of the civil war that engulfed both countries for more than a decade.An. gambiae and An. funestus, in 1899 Prior to the civil unrest in these countries, the mosquito species and their distribution were largely documented. Sierra Leone primarily served as the centre of malaria vector research and control, being the place where human malarial parasites were first observed in wild-caught An. gambiae vectors of malaria in West Africa had evolved from morphometric to cytotaxonomic studies An. gambiae complex An. gambiae s.s. An. gambiae molecular M form has subsequently been renamed An. coluzzii, whiles the An. gambiae molecular S form retained the name An. gambiae s.s An. gambiae complex had been undertaken/published in Sierra Leone, and in Liberia only one study An. gambiae s.s and their kdr frequencies in the Bomi County. In this short communication, we report the distribution of the An. coluzzii and the An. gambiae s.s., in Freetown and Monrovia the capital cities of Sierra Leone and Liberia respectively.By the 1980s the study of In Sierra Leone, samples were collected in November-December 2009, from 89 households in 5 communities around Freetown. In Liberia, samples were collected in July 2011, from 100 households in 4 communities in Monrovia  Approval for this study was obtained from the IRB of the Liverpool School of Tropical Medicine and the Ethics and Scientific Review Committees of the Ministries of Health in Sierra Leone and Liberia. The communities, where sampling was done, were informed on the project and consent sought from the local authorities within each community. Consent was also sought from the households where mosquito sampling was carried out.An. gambiae and 749 Culex species were collected. In Monrovia, 161 and 381 An. gambiae and Culex species were collected respectively. Culex was the most common mosquito species collected, due to the polluted breeding waters found in the areas where the collections were made. An. funestus and Aedes spp. were also collected, but in very low numbers. The distribution of the mosquito species collected in Freetown and Monrovia is shown in The number of collections from each community in Freetown is shown in An. gambiae complex in Freetown. 182 (93.8%) were successfully identified as either An. coluzzii or An. gambiae s.s. The remaining 12 samples failed to amplify. Further differentiation revealed 63.2% of the samples analyzed to be An. gambiae s.s., while the remaining 36.8% were An. coluzzii. The distribution of An. gambiae s.s. and An. coluzzii is shown in An. gambiae s.s. and An. coluzzii in Freetown, Sierra Leone. Sierra Leone is a mountainous, forested region and this may explain the high proportion of An. gambiae s.s. compared to An. coluzzii, and is in accordance with a study An. gambiae molecular S form was dominant in mountainous, forested areas.194 samples were analyzed for the molecular identification of the members of the An. gambiae were analyzed. Out of these, 90.5% were identified as An. coluzzii, and the remaining 9.5% as An. gambiae s.s. These results are consistent with the results of Temu and colleagues An. gambiae molecular M form in the Bomi County. An. gambiae s.s. and An. coluzzii in the collection sites in Monrovia.In Monrovia, 105 mosquitoes morphologically identified as kdr mutations (96.2%) were detected in the An. gambiae populations  for malaria control activities in Sierra Leone, with possible cross resistance to pyrethroids. Studies conducted in the late 1950’s, on the development of insecticide resistance in the An. gambiae in Freetown, showed the factor conferring resistance to BHC in 66% of the population An. gambiae populations in neighboring Liberia in 1957 kdr only to insecticide use in the 1950’s and further studies will be required to assess this.The very high levels of kdr mutations were not determined for the Monrovia samples, it is believed that the situation may not be much different from Freetown, considering the mosquito control activities that were in place in the 1950s kdr frequencies of over 90% kdr allele and ability to survive exposure to pyrethroid While the frequencies of An. coluzzii and An. gambiae s.s and prevalence of the kdr gene are described here for the first time in Sierra Leone, nearly 115 years after the incrimination of the Anopheles mosquito as the vector of malaria. This study showed that the An. gambiae s.s is the most dominant sibling species of An. gambiae complex in Freetown, while the An. coluzzii is the dominant species in Monrovia. A high prevalence of kdr mutation has been observed in both An. coluzzii and An. gambiae s.s in Freetown. There is however a limitation to these results, in that the determination of the kdr frequencies was not undertaken on surviving or dead mosquitoes exposed to pyrethroids through insecticide susceptibility testing. However, due to the high levels of kdr mutation in the An. coluzzii and An. gambiae s.s populations, it is recommended that insecticide susceptibility testing be done on non-pyrethroids insecticides (organophosphates and carbamates) in order to determine the insecticide of choice for future vector control activities.The distribution of the


The name of the 11th author was incorrectly given. The correct name is: Gerard T. Berry. The correct abbreviation in Contributions is: GTB. In addition, an affiliation is missing for the 11th author. In addition to that affiliation already indicated for Gerard T. Berry, this author is affiliated with the following institution: Harvard Medical School, Boston, Massachusetts, United States of America.


Mycobacterium tuberculosis, the causative agent of TB, and annually there are 10 million new cases of clinical TB and approximately 2 million deaths [Mycobacterium bovis bacille Calmette-Guérin (BCG), has been unable to limit the transmission of the disease, and the problem is compounded by the HIV/AIDS pandemic and the emergence of multidrug resistant strains of M. tuberculosis including extensively drug-resistant strains in multiple countries [M. tuberculosis and develop more effective strategies to control TB. Tuberculosis (TB) remains a major cause of mortality and morbidity worldwide. Currently, a third of the world's population is infected with M. tuberculosis in humans. These studies range from the expression of cytolytic mediators following BCG vaccination in children , control of antigen presentation function , changes in cellular makeup during postprimary TB , and treatment of disseminated infection in immuno-compromised individuals . The reviews of S. Meraviglia et al. and H. Saiga et al. describe the role of immune effectors in mycobacterial infection, while articles describing M. tuberculosis strain diversity , TB in myelitis , and humans T- and B- cell responses to immunodominant mycobacterial antigens  also form part of this special issue.This special issue contains original research reports and review articles covering a number of aspects of TB immunity. The first series of articles focuses on immune response to M. tuberculosis with the host are also provided in this special issue. The reviews of M. Abebe et al., S. L. Sampson et al., and S. Ahmad describe pathogenic mechanisms and virulence factors expressed by M. tuberculosis, while the research articles of N. Sanarico et al. and E. Giacomini et al. investigate the transcriptional and cytokine response of host cells to M. tuberculosis infection. Reviews on TB transcriptomics  and granuloma liquefaction (P.-J. Cardona) provide further insight into the disease process during M. tuberculosis infection.  New insights on the interaction of M. tuberculosis lipoproteins is described in the article of C. Palma et al., and the use of cattle as a model to study TB immunity is the focus of the review article of W. R. Waters et al. The special issue closes with an overview of biosensing technologies for detection of M. tuberculosis by Z. Zhou et al. The development of new vaccines is a major goal of TB research programs, and this special issue contains a number of articles investigating vaccine design and testing in animal models. G. G. Guerrero and C. Locht report on the use of recombinant antigens to boost BCG-induced immunity, while C. Wang et al. and M. Okada et al. similarly investigate prime-boost approaches to develop more effective TB vaccine regimens. The immune response following vaccination with M. tuberculosis infection, host-pathogen interaction and vaccine development covered in this special issue may lead to future advances in the treatment and control of TB. In conclusion, the aspects of immunity to James A. TriccasNathalie WinterCarl G. FengNicholas P. West


You can use the questions to test your own understanding; we hope that you will also discuss them with your colleagues and other members of the eye care team. The questions have been developed in association with the International Council of Ophthalmology (ICO) and are based on the style of the ICO Advanced Examination: a. False. Type 1 diabetes is caused by auto-immune destruction of the insulin secreting cells in the pancreas and cannot be prevented, b. True. c. True. d. False. There is no evidence that any drug is superior to any other. The important thing is to lower the blood pressure.a. False. Perfect control is unobtainable. Good control reduces the risk of DR and delays it, but most people with diabetes will eventually get some DR. b. False. Very few people will go blind from DR if they are treated. It is important to inform them of the risks, but not to frighten them away. They need to know that effective treatments are available, c. True. d. False. People with diabetes have lives, families, and jobs. We need to ensure that detecting and treating retinopathy is simple, quick, and inexpensive.a. True. b. True. c. False. Patients who have oedema near the fovea may still have normal vision, although they need treatment, d. False. A clinical trial showed that intravitreal steroid was not as good as laser, and may cause glaucoma.a. True. b. True. c. False. Non-ophthalmologists may be trained to detect retinopathy in photographs, d. False. Diabetes is more common in urban populations, but it is becoming much more common everywhere, including poor and rural communities.Classify these photographs according to the table on page 12 and say which patients must be referred to a retinal clinic.Moderate non-proliterative retinopathy, and maculopathy with exudates close to fovea. Should be referred for treatment of maculopathy.Severe NPDR and maculopathy. Should be referred for treatment of maculopathy and watched closely for development of new vessels.Mild non-proliferative retinopathy; pictures shows microaneurysms only. Should be examined again in 12 months.Proliferative diabetic retinopathy; picture shows disc new vessels. Requires urgent referral for pan-retinal laser.


The International Association for Radiation Research established in 1985 the Henry S. Kaplan Distinguished Scientist Award. The award, which is presented every four years at the International Congress of Radiation Research, consists of a medal, a certificate and a cash prize. A plenary session is designated for the award ceremony, including a lecture by the awardee. Previous recipients of this award were Professors Mortimer M. Elkind (1987), H. Rodney Withers (1991), Gerald Edward Adams (1995), John B. Little (1999), Eric J. Hall (2003), J. Martin Brown (2007) and P. Richard Hill (2011).The purpose of the award is to honour outstanding contributions to the field of radiation research. Any scientist who has made superior contributions to the field through investigations in physics, chemistry, biology or medicine is eligible.(e.g. 3-page) narrative describing the accomplishments of the nominee. Additional letters of support, up to a maximum of two, may be included with the nomination papers.Nominations may be submitted either by an individual or by a society. Each nomination should include a current curriculum vitae, bibliography and a brief st May 2014 to Professor Gianfranco Grossi, Secretary-Treasurer IARR, Department of Physics, University Federico II, Complesso Universitario Monte Sant'Angelo, Via Cinthia, I-80126 Napoli, Italy (gianfranco.grossi@unina.it). All nomination packages will be forwarded to the Selection Committee, comprising Professors Marco Durante, Mary Helen Barcellos-Hoff and Ohtsura Niwa. The recipient of the Kaplan award will be notified before the end of October 2014.Nominations for the 2015 award are now invited, and should be submitted by 1


Despite progress in malaria control, malaria remains an important public health concern in Cambodia, mostly linked to forested areas. Large-scale vector control interventions in Cambodia are based on the free distribution of long-lasting insecticidal nets (LLINs), targeting indoor- and late-biting malaria vectors only. The present study evaluated the vector density, early biting activity and malaria transmission of outdoor-biting malaria vectors in two forested regions in Cambodia.Plasmodium sporozoites after morphological identification. Blood samples were collected in the same villages for serological analyses. Collected data were analysed by the classification and regression tree (CART) method and linear regression analysis.In 2005 two entomological surveys were conducted in 12 villages and their related forest plots in the east and west of Cambodia. Mosquitoes were collected outdoors by human landing collections and subjected to enzyme-linked immunosorbent assay (ELISA) to detect Plasmodium-positive bites occurred before sleeping time, and 65% in the forest plots. The entomological inoculation rates of survey 1 were important predictors of the respective seroconversion rates in survey 2, whereas the mosquito densities were not.A total of 11,826 anophelines were recorded landing in 787 man-night collections. The majority (82.9%) were the known primary and secondary vectors. Most of the variability in vector densities and early biting rates was explained by geographical factors, mainly at village level. Vector densities were similar between forest and village sites. Based on ELISA results, 29% out of 17 In Cambodia, outdoor malaria transmission in villages and forest plots is important. In this context, deforestation might result in lower densities of the primary vectors, but also in higher densities of secondary vectors invading deforested areas. Moreover, higher accessibility of the forest could result in a higher man-vector contact. Therefore, additional vector control measures should be developed to target outdoor- and early-biting vectors. Anopheles dirus s.s. and Anopheles minimus s.s. [Within the Greater Mekong Region, progress in malaria control has been substantial over the last ten years. However malaria remains an important public health concern in some provinces of each country . In 2010mus s.s. -9. Becaumus s.s. .An. dirus s.s. and An. minimus s.s. are exophagic and exophilic, jeopardizing the impact of LLINs [Anopheles dirus s.l. and Anopheles minimus s.l. are outdoor and early biters [Plasmodium-infected mosquito during the early evening as compared to the rest of the night [An. dirus s.s. and An. minimus s.s., a large number of other anopheline species occur in the vicinity of human dwellings. Transmission by ‘secondary’ vectors that have outdoor or early biting behaviour might become more important than transmission by primary vectors in the context of high coverage of insecticide-treated nets (ITNs) [Plasmodium vivax as compared to Plasmodium falciparum, as the extrinsic incubation period of P. vivax is shorter. In Vietnam, Anopheles sawadwongporni, a very early biting secondary vector, was found positive for P. vivax[Large-scale vector control interventions occurred during the last years in Cambodia, particularly based on the free distribution of long-lasting insecticidal nets (LLINs) . This haof LLINs . Severaly biters -13. In Vhe night . Also, ihe night , meanings (ITNs) . As secos (ITNs) , seconda P. vivax.Recently, Cambodia has declared its intention to eliminate malaria by 2025 . It is tIn the framework of a larger study on the force of malaria infection in the forested environment in Cambodia the results of an entomological survey designed to have a better understanding of early and outdoor malaria transmission by primary and secondary vectors in forested areas in the eastern and western part of Cambodia, are presented here. Vector abundance, malaria transmission, and early biting rates in forest camps were compared to the situation in the nearby village. Results obtained from the entomological survey are analysed in relation to the serological data obtained in the same localities during the same time frame . The stuAn. minimus s.s. and An. dirus s.s. [The study sites were located over five districts in forested areas of Cambodia: two in the north-east (O’Chum and Borkeo in Rattanakiri Province) and three in the north-west . In each of the districts  three villages were selected Figure . The domrus s.s. . A more In 2005 the meteorological data  were conducted in the 12 forest villages. For each entomological survey, outdoor human landing collections were carried out for six successive nights. Human landing collections lasted from 18.00 until 06.00. Each collector collected mosquitoes for four hours per night. A rotation of collectors was conducted every two days for the different collection points and collection hours. In the village, at the edge, two collection points were selected in the front of two houses, making a collection effort of 12 man-nights per survey. In the forest, two collection points were chosen in forest camps where people of the village have their forest plot or stay temporarily for hunting or logging. The collection effort was 12 to 14 man-nights per survey (in some plots collections were carried out during seven successive nights instead of six). The forest plots were between 0.1 and 4.5 km from the village. The same collection points were maintained throughout the study. For one site, mosquitoes were collected only in the forest camp where people lived permanently (BZ).Two additional collection sites per village were selected on the way from the village to the forest camp (between 0.5 and 1 km from the village edge). In these sites mosquitoes were collected in the evening (from 18.00 to 22.00) and in the early morning (from 04.00 to 08.00).Mosquitoes were stored by collection hour and morphologically identified in the field by use of a standardized key for medically important anophelines of Southeast Asia . MosquitP. falciparum, P. vivax 210 and P. vivax 247 circumsporozoite proteins (CSP) in the head-thoracic portion of individual mosquitoes. Details of this procedure and the numbers of mosquitoes tested were published earlier [Most of the collected mosquitoes were subjected to enzyme-linked immunosorbent assay (ELISA) to detect An. minimus complex [An. dirus complex [Anopheles barbirostris s.s. was confirmed by sequencing  the ITS2 rDNA region using primers ITS2A and ITS2B as described in [An. dirus complex and 351 randomly chosen specimens of the An. minimus complex as described above. A random sample of the mosquitoes morphologically identified as An. maculatus (535 specimens) were identified using a PCR-RFLP, based on the amplification of ITS2 rDNA region using primers ITS2A and ITS2B as described in [The morphological identification of the mosquitoes found positive for ELISA was confirmed by PCR using the PCR-RFLP for  complex , and the complex . The ideribed in . The seqribed in . In addiribed in  followedP. falciparum and P. vivax parasite rate (PR). The samples were stored desiccated at 4°C. Plasmodium falciparum GLURP antibodies and P. vivax MSP-119 antibodies were detected using ELISA. ELISA optical densities were converted to percentage positivity. A mixture model was used to generate a cut-off for positivity. Seroconversion rates (SCR) were estimated by using a simple reversible catalytic conversion model to fit the dichotomised serological results, using maximum likelihood methods [Collection of blood samples was carried out as described in . In shorThe study was approved by the ethical committees of the National Centre of Malariology CNM in Phnom Penh (Cambodia) and of the Institute of Tropical Medicine of Antwerp (Belgium). The mosquito collectors and householders were informed about the objectives, process and procedures of the study and oral informed consent was sought from them. Collector candidates were invited among the adult village population and if individuals wanted to withdraw they were allowed to do so at any time without prejudice. Access to malaria diagnosis and treatment was guaranteed throughout the study. Informed consent was received from all people who agreed to give blood samples after being given information about the objectives, process and procedures of the study.The non-parametric classification and regression tree (CART) models  wereP. falciparum and P. vivax, and the parasite rate for P. falciparum and P. vivax. The dependent variables were transformed first using an arcsine transformation of the square root. The independent variables were the MBR expressed by the number of bites/man/night (B/M/N) of the different vector species of survey 1 and survey 2, the EBP calculated as the percentage of vectors biting before 22.00 of the different vector species of survey 1 and survey 2, and the entomological inoculation rate (EIR) for the respective parasite . Because of the high number of variables, univariate analyses were used to determine the significant variables. Variables with a P-value ≤0.10 were incorporated in a multivariate model. The final linear regression model was obtained by backward selection using a P-value ≤ 0.05 as the criterion and was checked for multicollinearity (by using the vif command in STATA 12.0).To identify entomological predictors for the epidemiological outcome, linear regression analysis was carried out using STATA 12.0 . The dependent variables for which the analyses were carried out separately were the seroconversion rate for A summary of the census results of importance for the interpretation of the presented data is available in Table Anopheles maculatus sensu lato (33.1%), An. minimus s.l. (24.8%), An. barbirostris s.l. (14.7%), and An. dirus s.l. . Other anopheline species collected (17.1%) were morphologically identified as Anopheles philippinensis, Anopheles jamesii, Anopheles hyrcanus, Anopheles karwari, Anopheles tessellatus, Ano-pheles umbrosis, Anopheles kochi, Anopheles culicifacies s.l., Anopheles vagus, Anopheles aconitus, Anopheles annan-dalei, and Anopheles willmori.In a total of 787 man-night collections , 11,826 anophelines were recorded landing, of which 52.8% were collected in the forest camps, 46.3% in the villages and 1% on the way. The majority of the anophelines (82.9%) were morphologically identified as the known  primary An. dirus complex members analysed, 99% were molecularly confirmed as An. dirus s.s.. Table An. minimus complex and the An. maculatus complex. The majority of An. minimus complex members collected in the west were molecularly identified as An. minimus s.s., the specimens morphologically identified as belonging to the An. minimus complex in the east comprised mainly of An. aconitus, mixed with An. minimus s.s. and few other species. The specimens morphologically identified as belonging to the An. maculatus complex, comprised in the west mainly of An. sawadwongporni and in the east mainly of a mix of An. maculatus s.s. and An. sawad-wongporni. As not all specimens collected could be molecularly identified, further analysis will be presented at complex level, based on the morphological identification. Note that in the following, the term An. minimus s.l./An. aconitus will be used to account for the mix of species in the mosquitoes that were morphologically identified as An. minimus s.l.Of the 440 An. maculatus s.l. (74.8%), and An. minimus s.l./An. aconitus (19.1%). Anopheles dirus s.l. represented 5.2%. Because of these low numbers of specimens collected on the way, further analysis will only focus on the anophelines collected in the forest camps and the villages. Further analyses will be concentrated on the four known malaria vector complexes that were most abundant in this study.In general, mosquito densities per vector complex were similar between forest and village sites. On the way to the forest camps only 115 anophelines were collected, and only during survey 2 in village PY (three bites/night) and in village PZ (6.1 bite/night) of which 77% in the evening and 23% in the early morning. Most of them were An. minimus s.l./An. aconitus were observed in the district of Pailin and Borkeo. Highest densities of An. barbirostris s.l. were observed in O’chum. Densities of each vector complex were similar between village and the corresponding forest sites.Man-biting rates per district, survey and collection site show a high variability between the districts Figure . The higAn. dirus s.l. (RI: 29) and An. minimus s.l./An. aconitus (RI: 33) but not An. maculatus s.l. (RI: 2) and An.barbirostris s.l. (RI: 0) and this differently according to the district. The relative importance of the sites of collection  was limited (RI ranging from 0 to 8). All CART trees are shown in Additional file Analysis by CART Table  shows thAn. dirus s.l., besides village (RI: 100) and district (RI: 48), region (RI: 43) and survey (RI: 29) were also important predictors. Only in the villages with highest densities (with on average 3.4 B/M/N compared to 0.435 B/M/N in low density villages), a difference was observed between surveys, which was not consistent for all villages: in some villages , higher densities were observed in the second survey, whereas in other villages , higher densities were observed in the first survey. The highest An. dirus s.l. density was observed in the village site of VZ in survey 2 (10.4 B/M/N).For An. minimus s.l./An. aconitus, CART shows that the highest densities were observed in the district of Pailin  and Borkeo , with a maximum of 28 B/M/N in the forest camps of PY in survey 2. In those villages with high densities, the density was higher in the second survey as compared to the first survey.For An. maculatus s.l. highest densities were observed in Pailin (PY and PZ), with a maximum of 24 B/M/N in the village site of PY in survey 1.For An. barbirostris s.l. were observed in all three villages of the O’Chum district, with a maximum of 21 B/M/N in the forest site of OZ in survey 1. In the O’Chum district, a higher density was observed in the forest sites as compared to the village sites.The highest densities of An. philippinensis, An. jamesii, An karwari, An. tessellatus, An. kochi. Species occasionally found are An. hyrcanus , An. umbrosus , An. culicifacies s.l. , An. vagus , An. annandalei (PZ), and An. willmori (VY).Other less abundant species present in all districts were The EBP, calculated as the percentage of vectors biting before 22.00, varied according to district and less according to site (forest or village) Figure .An. barbirostris s.l. . Region and districts are also important determinants, except for the EBP of l. Table .An. dirus s.l. . The lowest EBP was seen in Pailin  were located in Borkeo and O’Chum (east), whereas most villages with a lower EBP (26.9 and 32.9% for An. minimus s.l./An. aconitus and An. maculatus s.l. respectively) were located in Pailin and Pursat (west). For An. barbirostris s.l., in general an EBP of 45.8% was observed, with almost no difference between districts. A higher EBP (60.4%) was observed in four villages  as compared to the others (38.3%).The CART trees for An. philippinensis and 21 specimens of other anopheline species  were tested. Only 17 specimens were confirmed to be positive for sporozoites . No mixed infections were observed. Only An. dirus s.s. was found positive for P. falciparum (11 specimens) and only during survey 1. Most of P. falciparum positives (9/11) were collected in the forest camps (BY and BZ). The five P. vivax- infected mosquitoes (four An. dirus s.s. and one An. minimus s.s.) were only found during survey 2, of which four in the villages. One specimen of An. barbirostris s.s. was found positive for P. malariae (forest camp of OZ).Some 10,080 specimens were tested for detection of sporozoites. The details of 9,233 of these specimens can be found in . In addiBased on all positive bites, the proportion of positive bites before sleeping time (22.00) was 29% (5/17) Figure .The EIR was calculated per week Table . MalariaP. falciparum EIR in Survey 1 is linked to a higher P. falciparum seroconversion rate in survey 2, and a higher P. falciparum parasite rate in survey 1. A similar trend was observed for the P. vivax EIR in survey 1, which was positively linked with the P. vivax seroconversion rate in survey 2. The densities and early biting rates of the different vector species were either not or negatively correlated to the seroconversion rate or parasite rate, showing that vector density is not a good proxy of transmission.The results of the multivariate linear regression analyses are shown in Table Vector control has always been one of the cornerstones of malaria control . Howeveret al. [An. dirus s.l. and An. maculatus s.l. densities were observed in survey 1 as compared to survey 2, whereas in the west, higher densities were observed in survey 2. However, in the east, the amount of rain is almost double compared to the west, with the main rain peak occurring in July and August. In the west, the rain peak occurs in September and October. This difference in rain pattern might explain these general differences observed in vector densities between both regions. The surveys were carried out at approximately the same moment in time in the east and the west. Therefore, survey 1 fell just after the rain peak in the east, and before the rain peak in the west  as compared to the nearby villages (4.23 BMN), but only in the first survey. The latter three villages are situated in areas with the highest degree of conserved forest as compared to the other villages in the study , and indistrict ). In thedistrict  than theAn. minimus s.l./An. aconitus, An. barbirostris s.l. and An. maculatus s.l. between forest plots and villages. These malaria vector complexes do not require the forest for breeding sites; An. minimus s.l. is more associated with mosaic vegetation and crop [An. maculatus s.l. is a widespread species [An. barbirostris s.l. and An. aconitus[In the present study, in general, no difference was observed in the densities of the other vectors and crop , and An. species  preferri aconitus.An. dirus s.l. is able to adapt to peripheral areas where natural forests are replaced with orchards, and tea, coffee, and rubber plantations [An. dirus s.l. is able to overcome larger distances than the 1.5 up to 3 km in [Although the densities of the malaria vectors differed between villages, all vector complexes were found in all villages and forest plots, regardless if the villages were surrounded by deforested areas or by forest (evergreen or deciduous), or plantations. The forest in the region where this study took place was in most cases scattered and fragmented. It has been reported that ntations . It is nntations ,29, from 3 km in , even inAlthough densities were almost similar between villages and nearby forest plots, 11 (65%) out of 17 infective bites were found in the forest plots of BY, BZ and OZ, which are the villages with the highest degree of conserved forest, being in line with previous observations of forest-related transmission ,35. HoweIn the study regions, people combine living in the villages with a second house near to their farm plot in the forest. In 2005, a great proportion of people sleeping in the forest slept unprotected (17 to 31%) particularly in Borkeo, the district with the highest transmission rate. It is clear that both human behaviour   and vectP. vivax, occurred later in the night and was only observed inside the villages and not in the forest plot. It has been observed that the use of LLINs can alter the biting behaviour of the vector species to earlier biting [versus 37 and 38%, respectively for the present study). Interestingly, in some villages located in O’Chum and Pursat districts, a higher proportion of early biting An. dirus s.l. was observed in the villages (39%) as compared to the forest plots (26%). In these districts, people reported a high use of bed nets (treated and untreated) in the village, but not in the forest. An increasing trend of early biting due to increasing LLIN use cannot be excluded. The current study took place in 2005, when LLIN coverage and use was much lower than presently observed. The Cambodia Malaria Survey shows a national increase in LLIN use from 29 and 25% in 2004 and 2007, respectively, until more than 50% in 2010, both in the east and the west [The data from the current study show that LLINs provide useful although only partial protection against malaria: 71% of the infectious bites occurred after 22.00, when people are expected to be sleeping under a net. All infective bites before 22.00 (29%) occurred in the forest plots, underlining the importance of additional protective methods in such environments , their densities vary according to villages, rather than region, without major differences between the sites of collections (inside the village or in the nearby forest plot). The consequences of forest fragmentation and deforestation on malaria transmission in Southeast Asia are difficult to predict as a wide diversity of forest, near-forest and non-forest malaria vectors occurred. A suboptimal habitat in the forest fragments might result in lower densities and survival of the main forest vectors, with a reduction of malaria transmission as a consequence. However, higher accessibility of forest fragments can result in a higher contact rate between man and vector. Additionally, in the long run, deforested areas or areas with fragmented forest might be invaded by other efficient malaria vectors which are now considered secondary vectors. Therefore, although the capacity of secondary vectors of Cambodia in maintaining malaria transmission in the absence of the primary vectors is not known, their behaviour should also be taken into account when applying vector control measures. Because of outdoor and early biting by primary and secondary vectors in Cambodia, a behavioural trait that can be selected in vectors by a higher use of LLINs, additional measures should be explored. Personal protection using LLIHs, or topical and spatial repellents can have added value in tackling residual malaria transmission.The authors declare that they have no competing interests.MC and TS designed the study. LDu and MC carried out the data analysis and drafted the manuscript. TS and SM facilitated and supervised the field work, and critically reviewed the manuscript. LDe and PR carried out the ELISA assays and molecular identification of the collected mosquitoes and critically reviewed the manuscript. MC critically reviewed the manuscript. All authors read and approved the final manuscript.Regression trees for densities of Anopheles dirus s.l., Anopheles minimus s.l./Anopheles aconitus, Anopheles maculatus s.l., and Anopheles barbirostris s.l. The data provided represent the result of the CART analysis for man biting rates of Anopheles dirus s.l., Anopheles minimus s.l./Anopheles aconitus, Anopheles maculatus s.l., and Anopheles barbirostris s.l.Click here for fileRegression trees for early biting rates of Anopheles minimus s.l./Anopheles aconitus, Anopheles maculatus s.l. and Anopheles barbirostris s.l. The data provided represent the result of the CART analysis for early biting rates of Anopheles minimus s.l./Anopheles aconitus, Anopheles maculatus s.l., and Anopheles barbirostris s.l.Click here for fileResults of univariate and multivariate analysis for seroconversion rate and parasite rate. This table shows the coefficients and the p-values of the univariate and multivariate regression analysis for each of the dependent and independent variables assessed.Click here for file