Institution Building in Myanmar: The Establishment of Regional and State Assemblies

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Quantitative CMR population imaging on 20,000 subjects of the UK Biobank imaging study: LV/RV quantification pipeline and its evaluation

Population imaging studies generate data for developing and implementing personalised health strategies to prevent, or more effectively treat disease. Large prospective epidemiological studies acquire imaging for pre-symptomatic populations. These studies enable the early discovery of alterations due to impending disease, and enable early identification of individuals at risk. Such studies pose new challenges requiring automatic image analysis. To date, few large-scale population-level cardiac imaging studies have been conducted. One such study stands out for its sheer size, careful implementation, and availability of top quality expert annotation; the UK Biobank (UKB). The resulting massive imaging datasets (targeting ca. 100,000 subjects) has put published approaches for cardiac image quantification to the test. In this paper, we present and evaluate a cardiac magnetic resonance (CMR) image analysis pipeline that properly scales up and can provide a fully automatic analysis of the UKB CMR study. Without manual user interactions, our pipeline performs end-to-end image analytics from multi-view cine CMR images all the way to anatomical and functional bi-ventricular quantification. All this, while maintaining relevant quality controls of the CMR input images, and resulting image segmentations. To the best of our knowledge, this is the first published attempt to fully automate the extraction of global and regional reference ranges of all key functional cardiovascular indexes, from both left and right cardiac ventricles, for a population of 20,000 subjects imaged at 50 time frames per subject, for a total of one million CMR volumes. In addition, our pipeline provides 3D anatomical bi-ventricular models of the heart. These models enable the extraction of detailed information of the morphodynamics of the two ventricles for subsequent association to genetic, omics, lifestyle habits, exposure information, and other information provided in population imaging studies. We validated our proposed CMR analytics pipeline against manual expert readings on a reference cohort of 4620 subjects with contour delineations and corresponding clinical indexes. Our results show broad significant agreement between the manually obtained reference indexes, and those automatically computed via our framework. 80.67% of subjects were processed with mean contour distance of less than 1 pixel, and 17.50% with mean contour distance between 1 and 2 pixels. Finally, we compare our pipeline with a recently published approach reporting on UKB data, and based on deep learning. Our comparison shows similar performance in terms of segmentation accuracy with respect to human experts

EMOPAIN Challenge 2020: Multimodal Pain Evaluation from Facial and Bodily Expressions.

The EmoPain 2020 Challenge is the first international competition aimed at creating a uniform platform for the comparison of machine learning and multimedia processing methods of automatic chronic pain assessment from human expressive behaviour, and also the identification of pain-related behaviours. The objective of the challenge is to promote research in the development of assistive technologies that help improve the quality of life for people with chronic pain via real-time monitoring and feedback to help manage their condition and remain physically active. The challenge also aims to encourage the use of the relatively underutilised, albeit vital bodily expression signals for automatic pain and pain-related emotion recognition. This paper presents a description of the challenge, competition guidelines, bench-marking dataset, and the baseline systems' architecture and performance on the three sub-tasks: pain estimation from facial expressions, pain recognition from multimodal movement, and protective movement behaviour detection.PSRC grant Emotion& Pain Project; NIHR Nottingham Biomedical Research Centr

The emergence and diversification of a zoonotic pathogen from within the microbiota of intensively farmed pigs

The expansion and intensification of livestock production is predicted to promote the emergence of pathogens. As pathogens sometimes jump between species, this can affect the health of humans as well as livestock. Here, we investigate how livestock microbiota can act as a source of these emerging pathogens through analysis of Streptococcus suis, a ubiquitous component of the respiratory microbiota of pigs that is also a major cause of disease on pig farms and an important zoonotic pathogen. Combining molecular dating, phylogeography, and comparative genomic analyses of a large collection of isolates, we find that several pathogenic lineages of S. suis emerged in the 19th and 20th centuries, during an early period of growth in pig farming. These lineages have since spread between countries and continents, mirroring trade in live pigs. They are distinguished by the presence of three genomic islands with putative roles in metabolism and cell adhesion, and an ongoing reduction in genome size, which may reflect their recent shift to a more pathogenic ecology. Reconstructions of the evolutionary histories of these islands reveal constraints on pathogen emergence that could inform control strategies, with pathogenic lineages consistently emerging from one subpopulation of S. suis and acquiring genes through horizontal transfer from other pathogenic lineages. These results shed light on the capacity of the microbiota to rapidly evolve to exploit changes in their host population and suggest that the impact of changes in farming on the pathogenicity and zoonotic potential of S. suis is yet to be fully realized

Histological Evaluation of Diabetic Neurodegeneration in the Retina of Zucker Diabetic Fatty (ZDF) Rats

In diabetes, retinal dysfunctions exist prior to clinically detectable vasculopathy, however the pathology behind these functional deficits is still not fully established. Previously, our group published a detailed study on the retinal histopathology of type 1 diabetic (T1D) rat model, where specific alterations were detected. Although the majority of human diabetic patients have type 2 diabetes (T2D), similar studies on T2D models are practically absent. To fill this gap, we examined Zucker Diabetic Fatty (ZDF) rats - a model for T2D - by immunohistochemistry at the age of 32 weeks. Glial reactivity was observed in all diabetic specimens, accompanied by an increase in the number of microglia cells. Prominent outer segment degeneration was detectable with changes in cone opsin expression pattern, without a decrease in the number of labelled elements. The immunoreactivity of AII amacrine cells was markedly decreased and changes were detectable in the number and staining of some other amacrine cell subtypes, while most other cells examined did not show any major alterations. Overall, the retinal histology of ZDF rats shows a surprising similarity to T1D rats indicating that despite the different evolution of the disease, the neuroretinal cells affected are the same in both subtypes of diabetes

Yeast thioredoxin reductase Trr1p controls TORC1-regulated processes

The thioredoxin system plays a predominant role in the control of cellular redox status. Thioredoxin reductase fuels the system with reducing power in the form of NADPH. The TORC1 complex promotes growth and protein synthesis when nutrients, particularly amino acids, are abundant. It also represses catabolic processes, like autophagy, which are activated during starvation. We analyzed the impact of yeast cytosolic thioredoxin reductase TRR1 deletion under different environmental conditions. It shortens chronological life span and reduces growth in grape juice fermentation. TRR1 deletion has a global impact on metabolism during fermentation. As expected, it reduces oxidative stress tolerance, but a compensatory response is triggered, with catalase and glutathione increasing. Unexpectedly, TRR1 deletion causes sensitivity to the inhibitors of the TORC1 pathway, such as rapamycin. This correlates with low Tor2p kinase levels and indicates a direct role of Trr1p in its stability. Markers of TORC1 activity, however, suggest increased TORC1 activity. The autophagy caused by nitrogen starvation is reduced in the trr1Δ mutant. Ribosomal protein Rsp6p is dephosphorylated in the presence of rapamycin. This dephosphorylation diminishes in the TRR1 deletion strain. These results show a complex network of interactions between thioredoxin reductase Trr1p and the processes controlled by TOR

Heterogeneous contributions of change in population distribution of body mass index to change in obesity and underweight

From 1985 to 2016, the prevalence of underweight decreased, and that of obesity and severe obesity increased, in most regions, with significant variation in the magnitude of these changes across regions. We investigated how much change in mean body mass index (BMI) explains changes in the prevalence of underweight, obesity, and severe obesity in different regions using data from 2896 population-based studies with 187 million participants. Changes in the prevalence of underweight and total obesity, and to a lesser extent severe obesity, are largely driven by shifts in the distribution of BMI, with smaller contributions from changes in the shape of the distribution. In East and Southeast Asia and sub-Saharan Africa, the underweight tail of the BMI distribution was left behind as the distribution shifted. There is a need for policies that address all forms of malnutrition by making healthy foods accessible and affordable, while restricting unhealthy foods through fiscal and regulatory restrictions

Isoniazid resistance levels of Mycobacterium tuberculosis can largely be predicted by high-confidence resistance-conferring mutations.

YesThe majority of Mycobacterium tuberculosis isolates resistant to isoniazid harbour a mutation in katG. Since these mutations cause a wide range of minimum inhibitory concentrations (MICs), largely below the serum level reached with higher dosing (15 mg/L upon 15–20 mg/kg), the drug might still remain partly active in presence of a katG mutation. We therefore investigated which genetic mutations predict the level of phenotypic isoniazid resistance in clinical M. tuberculosis isolates. To this end, the association between known and unknown isoniazid resistance-conferring mutations in whole genome sequences, and the isoniazid MICs of 176 isolates was examined. We found mostly moderate-level resistance characterized by a mode of 6.4 mg/L for the very common katG Ser315Thr mutation, and always very high MICs (≥19.2 mg/L) for the combination of katG Ser315Thr and inhA c-15t. Contrary to common belief, isolates harbouring inhA c-15t alone, partly also showed moderate-level resistance, particularly when combined with inhA Ser94Ala. No overt association between low-confidence or unknown mutations, except in katG, and isoniazid resistance (level) was found. Except for the rare katG deletion, line probe assay is thus not sufficiently accurate to predict the level of isoniazid resistance for a single mutation in katG or inhA.European Research Council (Starting Grant INTERRUPTB 311725 to CM, LR and BdJ), The Damien Foundatio