Bayesian Analysis of Count Data with R Using Laplace Approximation and Simulation Tools

The Poisson regression model for count data belongs to the family of “generalized linear models”, and is available in the R system for statistical computing. In this article, the Bayesian methods are applied to fit the Poisson model using analytic and simulation tools. Laplace Approximation is implemented for approximating posterior densities of the parameters. Moreover, parallel simulation tools are implemented using LaplacesDemon and R2jags packages of R. A data set “DoctorVisits” is used for the purpose of illustrations

An intraorbital metallic foreign body

A 30-year-old male presented with diplopia for 20 days post occupational accident involving left side of his nose, while he was working with a nail gun. He was fully conscious and did not have any neurological deficits. Patient narrated the mechanism of injury and was sure that the nail fell down after hitting the left side of his nose. He had normal vision, but extra ocular movements were restricted and painful. Computed tomography (CT) scan revealed a curved metal object lodged in the posterior aspect of the left orbit extending diagonally from medial wall to the anterior-superior aspect of the orbital roof. The object was removed via a small surgical approach, inflicting least possible surgical trauma. Post surgery, the patient recovered with complete resolution of diplopia. The original aspects of this case are the lack of signs of a foreign body entry and its relative harmlessness in spite of its large size

Increased expression levels of Syntaxin 1A and Synaptobrevin 2/Vesicle-Associated Membrane Protein-2 are associated with the progression of bladder cancer

Abstract Gene expression is tightly regulated in time and space through a multitude of factors consisting of signaling molecules. Soluble N-ethylmaleimide-sensitive-factor attachment protein receptors (SNARE) are membrane proteins responsible for the intercellular trafficking of signals through endocytosis and exocytosis of vesicles. Altered expression of SNARE proteins in cellular communication is the major hallmark of cancer phenotypes as indicated in recent studies. SNAREs play an important role in maintaining cell growth and epithelial membrane permeability of the bladder and are not only involved in cancer progression but also metastatic cell invasion through SNARE-mediated trafficking. Synaptobrevin2/Vesicle associated membrane protein-2 (v-SNARE) and Syntaxin (t-SNARE) form a vesicular docking complex during endocytosis. Some earlier studies have shown a critical role of SNARE in colon, lungs, and breast cancer progression and metastasis. In this study, we analyzed the relative expression of the STX1A and VAMP2 (SYB2) for their possible association in the progression and metastasis of bladder cancer. The profiling of the genes showed a significant increase in STX1A and VAMP2 expression (p < 0.001) in high-grade tumor cells compared to normal and low-grade tumors. These findings suggest that elevated expression of STX1A and VAMP2 might have caused the abnormal progression and invasion of cancer cells leading to the transformation of cells into high-grade tumor in bladder cancer

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

Background: Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. Methods: Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. Findings: In 2021, there were 529 million (95% uncertainty interval [UI] 500-564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8-6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7-9·9]) and, at the regional level, in Oceania (12·3% [11·5-13·0]). Nationally, Qatar had the world's highest age-specific prevalence of diabetes, at 76·1% (73·1-79·5) in individuals aged 75-79 years. Total diabetes prevalence-especially among older adults-primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1-96·8) of diabetes cases and 95·4% (94·9-95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5-71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5-30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22-1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1-17·6) in north Africa and the Middle East and 11·3% (10·8-11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. Interpretation: Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers. Funding: Bill & Melinda Gates Foundation