Risk factors associated with development of senile cataract

Background: Cataract is the most common cause of reversible blindness worldwide, which has been associated with various causative risk factors. Hence, we aim to study the factors that might play a role in cataractogenesis. Material and methods: A total of 240 eyes of 240 subjects were included for the study, which consisted of 120 cases with age-related cataract and 120 age-matched controls, and in them various factors like blood pressure, body mass index (BMI), smoking, sun exposure, and serum cholesterol were studied. Results: A statistically significant difference between the two groups was found with respect to smoking profile (p = 0.007), sun exposure (p = 0.001), and serum cholesterol (p < 0.001). Subjects who were smokers, had a longer exposure to sun, and had higher serum cholesterol level were found to be positively associated with development of cataract. No significant association between BMI (p = 0.384) and blood pressure (p > 0.05) was observed. Conclusion: Higher cholesterol levels, increased sun exposure, and smoking habit play a role in the development of senile cataract, and these are modifiable risk factors. Hence, control of these might help in delaying formation and progression of cataract

Synergistic drug combinations from electronic health records and gene expression.

ObjectiveUsing electronic health records (EHRs) and biomolecular data, we sought to discover drug pairs with synergistic repurposing potential. EHRs provide real-world treatment and outcome patterns, while complementary biomolecular data, including disease-specific gene expression and drug-protein interactions, provide mechanistic understanding.MethodWe applied Group Lasso INTERaction NETwork (glinternet), an overlap group lasso penalty on a logistic regression model, with pairwise interactions to identify variables and interacting drug pairs associated with reduced 5-year mortality using EHRs of 9945 breast cancer patients. We identified differentially expressed genes from 14 case-control human breast cancer gene expression datasets and integrated them with drug-protein networks. Drugs in the network were scored according to their association with breast cancer individually or in pairs. Lastly, we determined whether synergistic drug pairs found in the EHRs were enriched among synergistic drug pairs from gene-expression data using a method similar to gene set enrichment analysis.ResultsFrom EHRs, we discovered 3 drug-class pairs associated with lower mortality: anti-inflammatories and hormone antagonists, anti-inflammatories and lipid modifiers, and lipid modifiers and obstructive airway drugs. The first 2 pairs were also enriched among pairs discovered using gene expression data and are supported by molecular interactions in drug-protein networks and preclinical and epidemiologic evidence.ConclusionsThis is a proof-of-concept study demonstrating that a combination of complementary data sources, such as EHRs and gene expression, can corroborate discoveries and provide mechanistic insight into drug synergism for repurposing

A General Class of Dual to Ratio Estimator

In this paper we have considered the problem of estimating the population mean using auxiliary information in sample surveys. A class of dual to ratio estimators has been defined. Exact expressions for bias and mean squared error of the suggested class of dual to ratio estimator have been obtained. In particular, properties of some members of the proposed class of dual to ratio estimators have been discussed. It has been shown that the proposed class of estimators is more efficient than the sample mean, ratio estimator, dual to ratio estimator and some members of the suggested class of estimators in some realistic conditions. Some numerical illustrations are given in support of the present study

A Two Parameter Ratio-Product-Ratio Estimator in Post Stratification

In this paper we consider a two parameter ratio-product-ratio estimator for estimating population mean in case of post stratification following the estimator due to Chami et al (2012). The bias and mean squared error of proposed estimator are obtained to the first degree of approximation. We derive conditions under which the proposed estimator has smaller mean squared error than the sample mean , ratio estimator and product estimators . Empirical studies gives insight on the magnitude of the efficiency of the estimator developed

OCT based macular thickness in a normal Indian pediatric population

Purpose: Cirrus optical coherence tomography (OCT) provides high resolution cross-sectional images of the retina, vitreous humor, and optic nerve head with an axial resolution of 5 μm and a reproducibility of 1.6 μm. An integrated normative database is available only for adult subjects ≥18 years of age; the normal reference ranges of the macular thicknesses of pediatric subjects are not available. The purpose of this study was to determine the normal reference range of macular thickness of pediatric. Methods: A total of 340 eyes of 170 children 5-17 years of age were recruited for this study. Participants received a full ophthalmic examination including a vision assessment, cycloplegic refraction, fundus examination, intraocular pressure measurement, assessment of ocular motility, and alignment. Macular thickness measurements were obtained through dilated pupils using Cirrus HD-OCT. Results: The mean macular thickness was 114.88 ± 14.74 in the right eye and 113.99 ± 15.62 in the left eye (P = 0.589). On further evaluation, macular thickness was highest in the inner macula, followed by the outer macula and central fovea (P < 0.001). Conclusion: The normative data of macular thickness in pediatric subjects 5-17 years of age will help diagnose macular disorders

Long-Lived Poxvirus Immunity, Robust CD4 Help, and Better Persistence of CD4 than CD8 T Cells

The currently used smallpox vaccine is associated with a high incidence of adverse events, and there is a serious need for a safe and effective alternative vaccine. Here, we carried out a longitudinal evaluation of vaccinia virus-specific CD4 and CD8 T cells in smallpox-vaccinated individuals by using a highly sensitive intracellular cytokine staining assay. Our results demonstrate that, in addition to the CD8 response, the smallpox vaccinations raised a robust CD4 response with a Th1-dominant cytokine profile. These CD4 T cells were stable and exhibited only a twofold contraction between peak effector and memory phases compared with an approximate sevenfold contraction for CD8 cells. A significant proportion of vaccinated individuals lost detectable CD8 memory while maintaining CD4 memory. After a booster immunization, these individuals generated a robust CD8 response, which some of them rapidly lost. Thus, the current smallpox vaccine provides long-lasting CD4 help that may be critical for long-lived B-cell memory. We suggest that the provision of adequate CD4 help for CD8 and humoral effector functions will be critical to the success of the next generation of smallpox vaccines

NLP and deep learning methods for curbing the spread of misinformation in India

The current fight against COVID-19 is not only around its prevention and cure but it is also about mitigating the negative impact resulting from misinformation around it. The pervasiveness of social media and access to smartphones has propelled the spread of misinformation on such a large scale that it is considered as one of the main threats to our society by the World Economic Forum. This ‘Infodemic’ has caused widespread rumors, fueled practices that can jeopardize one’s health, and has even resulted in hate violence in certain parts of the world. We built an engine that has the ability to match incoming text, which may contain correct or incorrect information, with a known repository of misinformation. By matching texts on embeddings generated using BERT, we evaluated paraphrased texts to see if they matched texts previously labeled as misinformation. Further, we augmented an existing data corpus of texts by tagging each misinformation with one or more impact categories. We may be able to take specific actions to avert the consequence of misinformation if we can predict the particular ramification of a certain type of misinformation