Clinicopathological Profile and Surgical Treatment of Abdominal Tuberculosis: A Single Centre Experience in Northwestern Tanzania.

Abdominal tuberculosis continues to be a major public health problem worldwide and poses diagnostic and therapeutic challenges to general surgeons practicing in resource-limited countries. This study was conducted to describe the clinicopathological profile and outcome of surgical treatment of abdominal tuberculosis in our setting and compare with what is described in literature. A prospective descriptive study of patients who presented with abdominal tuberculosis was conducted at Bugando Medical Centre (BMC) in northwestern Tanzania from January 2006 to February 2012. Ethical approval to conduct the study was obtained from relevant authorities. Statistical data analysis was performed using SPSS version 17.0. Out of 256 patients enrolled in the study, males outnumbered females. The median age was 28 years (range = 16-68 years). The majority of patients (77.3%) had primary abdominal tuberculosis. A total of 127 (49.6%) patients presented with intestinal obstruction, 106 (41.4%) with peritonitis, 17 (6.6%) with abdominal masses and 6 (2.3%) patients with multiple fistulae in ano. Forty-eight (18.8%) patients were HIV positive. A total of 212 (82.8%) patients underwent surgical treatment for abdominal tuberculosis. Bands /adhesions (58.5%) were the most common operative findings. Ileo-caecal region was the most common bowel involved in 122 (57.5%) patients. Release of adhesions and bands was the most frequent surgical procedure performed in 58.5% of cases. Complication and mortality rates were 29.7% and 18.8% respectively. The overall median length of hospital stay was 32 days and was significantly longer in patients with complications (p < 0.001). Advanced age (age ≥ 65 years), co-morbid illness, late presentation, HIV positivity and CD4+ count < 200 cells/μl were statistically significantly associated with mortality (p < 0.0001). The follow up of patients were generally poor as only 37.5% of patients were available for follow up at twelve months after discharge. Abdominal tuberculosis constitutes a major public health problem in our environment and presents a diagnostic challenge requiring a high index of clinical suspicion. Early diagnosis, early anti-tuberculous therapy and surgical treatment of the associated complications are essential for survival

Sexual selection protects against extinction

Reproduction through sex carries substantial costs, mainly because only half of sexual adults produce offspring. It has been theorised that these costs could be countered if sex allows sexual selection to clear the universal fitness constraint of mutation load. Under sexual selection, competition between (usually) males, and mate choice by (usually) females create important intraspecific filters for reproductive success, so that only a subset of males gains paternity. If reproductive success under sexual selection is dependent on individual condition, which depends on mutation load, then sexually selected filtering through ‘genic capture’ could offset the costs of sex because it provides genetic benefits to populations. Here, we test this theory experimentally by comparing whether populations with histories of strong versus weak sexual selection purge mutation load and resist extinction differently. After evolving replicate populations of the flour beetle Tribolium castaneum for ~7 years under conditions that differed solely in the strengths of sexual selection, we revealed mutation load using inbreeding. Lineages from populations that had previously experienced strong sexual selection were resilient to extinction and maintained fitness under inbreeding, with some families continuing to survive after 20 generations of sib × sib mating. By contrast, lineages derived from populations that experienced weak or non-existent sexual selection showed rapid fitness declines under inbreeding, and all were extinct after generation 10. Multiple mutations across the genome with individually small effects can be difficult to clear, yet sum to a significant fitness load; our findings reveal that sexual selection reduces this load, improving population viability in the face of genetic stress

CYP17 genetic polymorphism, breast cancer, and breast cancer risk factors: Australian Breast Cancer Family Study

INTRODUCTION: Because CYP17 can influence the degree of exposure of breast tissues to oestrogen, the interaction between polymorphisms in this gene and hormonal risk factors is of particular interest. We attempted to replicate the findings of studies assessing such interactions with the -34T→C polymorphism. METHODS: Risk factor and CYP17 genotyping data were derived from a large Australian population-based case-control-family study of 1,284 breast cancer cases and 679 controls. Crude and adjusted odds ratio (OR) estimates and 95% confidence intervals (CIs) were calculated by unconditional logistic regression analyses. RESULTS: We found no associations between the CYP17 genotype and breast cancer overall. Premenopausal controls with A(2)/A(2 )genotype had a later age at menarche (P < 0.01). The only associations near statistical significance were that postmenopausal women with A(1)/A(1 )(wild-type) genotype had an increased risk of breast cancer if they had ever used hormone replacement therapy (OR 2.40, 95% CI 1.0 to 5.7; P = 0.05) and if they had menopause after age 47 years (OR 2.59, 95% CI 1.0 to 7.0; P = 0.06). We found no associations in common with any other studies, and no evidence for interactions. CONCLUSION: We observed no evidence of effect modification of reproductive risk factors by CYP17 genotype, although the experiment did not have sufficient statistical power to detect small main effects and modest effects in subgroups. Associations found only in subgroup analyses based on relatively small numbers require cautious interpretation without confirmation by other studies. This emphasizes the need for replication in multiple and large population-based studies to provide convincing evidence for gene–environment interactions

Effect of Material Stiffness Variation on Shakedown Solutions of Soils Under Moving Loads

Shakedown limits of pavements and railway foundations can be calculated based on shakedown theorems. These values can be used to guide the thickness designs of pavement and railway constructions considering material plastic properties. However, most existing shakedown analyses were carried out by assuming a unique stiffness value for each material. This paper mainly concentrates on the influence of stiffness variation on the shakedown limits of pavements and railway foundations under moving loads. Finite element models as well as a user-defined material subroutine UMAT are first developed to obtain the elastic responses of soils considering a linearly increasing stiffness modulus with depth. Then, based on the lower-bound shakedown theorem, shakedown solutions are obtained by searching for the most critical self-equilibrated residual stress field. It is found that for a single-layered structure, the rise of a stiffness changing ratio will give a larger shakedown limit; and the increase is more pronounced when the friction angle is relatively high. For multi-layered pavement and railway systems, neglecting the stiffness variation may overestimate the capacity of the structures

Quantification of codon selection for comparative bacterial genomics

<p>Abstract</p> <p>Background</p> <p>Statistics measuring codon selection seek to compare genes by their sensitivity to selection for translational efficiency, but existing statistics lack a model for testing the significance of differences between genes. Here, we introduce a new statistic for measuring codon selection, the Adaptive Codon Enrichment (ACE).</p> <p>Results</p> <p>This statistic represents codon usage bias in terms of a probabilistic distribution, quantifying the extent that preferred codons are over-represented in the gene of interest relative to the mean and variance that would result from stochastic sampling of codons. Expected codon frequencies are derived from the observed codon usage frequencies of a broad set of genes, such that they are likely to reflect nonselective, genome wide influences on codon usage (<it>e.g</it>. mutational biases). The relative adaptiveness of synonymous codons is deduced from the frequency of codon usage in a pre-selected set of genes relative to the expected frequency. The ACE can predict both transcript abundance during rapid growth and the rate of synonymous substitutions, with accuracy comparable to or greater than existing metrics. We further examine how the composition of reference gene sets affects the accuracy of the statistic, and suggest methods for selecting appropriate reference sets for any genome, including bacteriophages. Finally, we demonstrate that the ACE may naturally be extended to quantify the genome-wide influence of codon selection in a manner that is sensitive to a large fraction of codons in the genome. This reveals substantial variation among genomes, correlated with the tRNA gene number, even among groups of bacteria where previously proposed whole-genome measures show little variation.</p> <p>Conclusions</p> <p>The statistical framework of the ACE allows rigorous comparison of the level of codon selection acting on genes, both within a genome and between genomes.</p

Accurate path integration in continuous attractor network models of grid cells

Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of ~10–100 meters and ~1–10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other

Role of C677T and A1298C MTHFR, A2756G MTR and -786 C/T eNOS Gene Polymorphisms in Atrial Fibrillation Susceptibility

Hyperhomocysteinemia has been suggested to play a role in the NonValvular Atrial Fibrillation (NVAF) pathogenesis. Polymorphisms in genes coding for homocysteine (Hcy) metabolism enzymes may be associated with hyperhomocysteinemia and NVAF.456 NVAF patients and 912 matched controls were genotyped by an electronic microchip technology for C677T and A1298C MTHFR, A2756G MTR, and -786C/T eNOS gene polymorphisms. Hcy was determined by an immunoassay method.The genotype distribution of the four polymorphisms as well as genotype combinations did not differ in patients and controls. Hcy was higher in patients than in controls (15.2, 95%CI 14.7–15.7 vs 11.3, 95%CI 11.0–11.6 µmol/L; p<0.0001). In both populations, a genotype-phenotype association (p<0.0001) between Hcy and C677T MTHFR polymorphism was observed; in controls a significant (p = 0.029) association between tHcy and −786C/T eNOS polymorphism was also observed. At the multivariate analysis the NVAF risk significantly increased in the upper quartiles of Hcy compared to the lowest: OR from 2.8 (1.68–4.54 95%CI) in Q2 to 12.9 (7.96–21.06 95%CI) in Q4. or in combination

Population based allele frequencies of disease associated polymorphisms in the Personalized Medicine Research Project

<p>Abstract</p> <p>Background</p> <p>There is a lack of knowledge regarding the frequency of disease associated polymorphisms in populations and population attributable risk for many populations remains unknown. Factors that could affect the association of the allele with disease, either positively or negatively, such as race, ethnicity, and gender, may not be possible to determine without population based allele frequencies.</p> <p>Here we used a panel of 51 polymorphisms previously associated with at least one disease and determined the allele frequencies within the entire Personalized Medicine Research Project population based cohort. We compared these allele frequencies to those in dbSNP and other data sources stratified by race. Differences in allele frequencies between self reported race, region of origin, and sex were determined.</p> <p>Results</p> <p>There were 19544 individuals who self reported a single racial category, 19027 or (97.4%) self reported white Caucasian, and 11205 (57.3%) individuals were female. Of the 11,208 (57%) individuals with an identifiable region of origin 8337 or (74.4%) were German.</p> <p>41 polymorphisms were significantly different between self reported race at the 0.05 level. Stratification of our Caucasian population by self reported region of origin revealed 19 polymorphisms that were significantly different (p = 0.05) between individuals of different origins. Further stratification of the population by gender revealed few significant differences in allele frequencies between the genders.</p> <p>Conclusions</p> <p>This represents one of the largest population based allele frequency studies to date. Stratification by self reported race and region of origin revealed wide differences in allele frequencies not only by race but also by region of origin within a single racial group. We report allele frequencies for our Asian/Hmong and American Indian populations; these two minority groups are not typically selected for population allele frequency detection. Population wide allele frequencies are important for the design and implementation of studies and for determining the relevance of a disease associated polymorphism for a given population.</p