Study of Profile, Knowledge and Problems of Anganwadi Workers in ICDS Blocks: A Cross Sectional Study

Objectives: To study the profile of Anganwadi Workers (AWWs). To assess knowledge of AWWs & problems faced by them while working. Study Design: Cross sectional study. Methods: Anganwadi centres were selected by stratified sampling technique. From each block 10% AWWs were enrolled into study. The functioning of AWWs was assessed by interviewing Anganwadi workers for their literacy status, years of experience, their knowledge about the services rendered by them and problems faced by them. Result: Most of AWWs were from the age group of between 41-50 years; more than half of them were matriculate and 34(69.38%) workers had an experience of more than 10 years. Majority (81.63 %) of AWWs had a knowledge assessment score of above 50%. They had best knowledge about nutrition and health education (70%). Of the workers 87.7% complained of inadequate honorarium, 28.5% complained of lack of help from community and other problems reported were infrastructure related supply, excessive work overload and record maintenance. Conclusions: Majority of AWWs were beyond 40 years of age, matriculate, experienced, having more than 50% of knowledge related to their job. Complaints mentioned by them were chiefly honorarium related and excessive workload

Effects of administration of oral n-acetylcysteine on oxidative stress in chronic obstructive pulmonary disease patients in rural population

Background: Chronic obstructive pulmonary disease (COPD) is a common pulmonary disease and the fourth leading cause of death globally. Oxidative stress is an important attribute in the pathogenesis of COPD.  Targeting oxidative stress would be a logical therapeutic approach for COPD and glutathione precursors like N-acetylcysteine (NAC) have shown therapeutic promise in the treatment of this chronic pathology. This study attempts to determine the dose related effects of NAC on the oxidative stress, its safety and efficacy in COPD patients.Methods: A randomized, double blind, placebo controlled, parallel group, single centred study, and was carried out in rural set-up. Sixty eight diagnosed cases of COPD according to GOLD criteria (global initiative for chronic obstructive lung disease), were recruited in the study, following approval from the ethics committee. The patients were randomized to three treatment arms (placebo, NAC 600 mg once a day (OD) and NAC 600 mg bis a day (BID). The patients were monitored for incidence and severity of adverse effects as a measure of safety. Efficacy of NAC was determined based on symptom improvement, pulmonary function, oxygen saturation and serum malondialdehyde (MDA) concentration.Results: Results indicate a significant improvement in the efficacy parameters in the group that received higher dose of NAC. NAC was well tolerated by all the study subjects. Addition of NAC to the standard treatment of COPD exhibits beneficial effects in disease exacerbations, symptom improvement and a decline in oxidative stress parameters, reinforcing the antioxidant, anti-inflammatory and mucolytic properties of NAC.Conclusions: This approach opens possibilities for a novel therapeutic approach in COPD

Massive Assymetrical Virginal Breast Hypertrophy: A Case Report

Virginal breast hypertrophy (VHB) is a rare , distinct disorder of unknown etiology with the rapid onset of macromastia at the onset of puberty.We reported a 12 year old, peripubertal girl presented to us with abnormal assymetrical growth of her breasts in 10 months. Due to the enormous breast volume, which caused her physical and psychological problems, she curtailed her social life. On examination, left breast was enlarged more in comparision to right, with associated skin changes. Endocrinological investigations were normal. A bilateral reduction mammaplasty with free nipple graft was performed. Histological analysis of the breast tissue revealed the diagnosis of virginal hypertrophy. During the follow-up period of 13 months, no recurrence was noted and patient is physically and psychologically satisfied

Confound-leakage: confound removal in machine learning leads to leakage

BACKGROUND: Machine learning (ML) approaches are a crucial component of modern data analysis in many fields, including epidemiology and medicine. Nonlinear ML methods often achieve accurate predictions, for instance, in personalized medicine, as they are capable of modeling complex relationships between features and the target. Problematically, ML models and their predictions can be biased by confounding information present in the features. To remove this spurious signal, researchers often employ featurewise linear confound regression (CR). While this is considered a standard approach for dealing with confounding, possible pitfalls of using CR in ML pipelines are not fully understood. RESULTS: We provide new evidence that, contrary to general expectations, linear confound regression can increase the risk of confounding when combined with nonlinear ML approaches. Using a simple framework that uses the target as a confound, we show that information leaked via CR can increase null or moderate effects to near-perfect prediction. By shuffling the features, we provide evidence that this increase is indeed due to confound-leakage and not due to revealing of information. We then demonstrate the danger of confound-leakage in a real-world clinical application where the accuracy of predicting attention-deficit/hyperactivity disorder is overestimated using speech-derived features when using depression as a confound. CONCLUSIONS: Mishandling or even amplifying confounding effects when building ML models due to confound-leakage, as shown, can lead to untrustworthy, biased, and unfair predictions. Our expose of the confound-leakage pitfall and provided guidelines for dealing with it can help create more robust and trustworthy ML models

Decoupling competing surface binding kinetics and reconfiguration of receptor footprint for ultrasensitive stress assays

Cantilever arrays have been used to monitor biochemical interactions and their associated stress. However, it is often necessary to passivate the underside of the cantilever to prevent unwanted ligand adsorption, and this process requires tedious optimization. Here, we show a way to immobilize membrane receptors on nanomechanical cantilevers so that they can function without passivating the underlying surface. Using equilibrium theory, we quantitatively describe the mechanical responses of vancomycin, human immunodeficiency virus type 1 antigens and coagulation factor VIII captured on the cantilever in the presence of competing stresses from the top and bottom cantilever surfaces. We show that the area per receptor molecule on the cantilever surface influences ligand-receptor binding and plays an important role on stress. Our results offer a new way to sense biomolecules and will aid in the creation of ultrasensitive biosensors

Surface mediated cooperative interactions of drugs enhance mechanical forces for antibiotic action

The alarming increase of pathogenic bacteria that are resistant to multiple antibiotics is now recognized as a major health issue fuelling demand for new drugs. Bacterial resistance is often caused by molecular changes at the bacterial surface, which alter the nature of specific drug-target interactions. Here, we identify a novel mechanism by which drug-target interactions in resistant bacteria can be enhanced. We examined the surface forces generated by four antibiotics; vancomycin, ristomycin, chloroeremomycin and oritavancin against drug-susceptible and drug-resistant targets on a cantilever and demonstrated significant differences in mechanical response when drug-resistant targets are challenged with different antibiotics although no significant differences were observed when using susceptible targets. Remarkably, the binding affinity for oritavancin against drug-resistant targets (70 nM) was found to be 11,000 times stronger than for vancomycin (800 μM), a powerful antibiotic used as the last resort treatment for streptococcal and staphylococcal bacteria including methicillin-resistant Staphylococcus aureus (MRSA). Using an exactly solvable model, which takes into account the solvent and membrane effects, we demonstrate that drug-target interactions are strengthened by pronounced polyvalent interactions catalyzed by the surface itself. These findings further enhance our understanding of antibiotic mode of action and will enable development of more effective therapies.We thank the EPSRC Interdisciplinary Research Centre in Nanotechnology (Cambridge, UCL, Bristol (GR/R45680/01), the EPSRC Grand Challenge in Nanotechnology for Healthcare (EP/G0620064/1), I-sense EPSRC IRC in Early Warning Sensing Systems for Infectious Diseases (EP/G062064/1), the EPSRC Speculative Engineering Program (EP/D50925/1), Royal Society (RS), Medicine Company Inc., USA, NHMRC Australia Fellowship (AF511105), UCL Graduate School Scholarship, UCL COMPLEX, Bio Nano Consulting (BNC), European Union FP7 Project VSMMART Nano (managed by BNC) and NHS Trusts Biomedical Research Centre (BRC) for funding

White rice consumption and risk of esophageal cancer in Xinjiang Uyghur Autonomous Region, northwest China: a case-control study

This study investigated the association between white rice consumption and the risk of esophageal cancer in remote northwest China, where the cancer incidence is known to be high. A case-control study was conducted during 2008-2009 in Urumqi and Shihezi, Xinjiang Uyghur Autonomous Region of China. Participants were 359 incident esophageal cancer patients and 380 hospital-based controls. Information on habitual white rice consumption was obtained by personal interview using a validated semi-quantitative food frequency questionnaire. Logistic regression analyses were performed to assess the association between white rice consumption and the esophageal cancer risk. Confounding variables including socio-demographics, family history, dietary and lifestyle factors were adjusted in the multivariate model. The esophageal cancer patients reported lower consumption levels of white rice-based products, including cooked white rice and porridge, when compared to the control group. Overall, regular consumption of white rice foods was inversely associated with the esophageal cancer risk, the adjusted OR being 0.34 (95 % CI 0.23 to 0.52) for the highest (>250 g) versus the lowest (<92 g) tertile of daily intake. Similar reductions in risk were also apparent for high consumption levels of cooked white rice and porridge. In conclusion, habitual white rice consumption was associated with a reduced risk of esophageal cancer for adults residing in northwest China. Our findings provide evidence to support the continued consumption of white rice

Massless D-strings and moduli stabilization in type I cosmology

We consider the cosmological evolution induced by the free energy F of a gas of maximally supersymmetric heterotic strings at finite temperature and weak coupling in dimension D>=4. We show that F, which plays the role of an effective potential, has minima associated to enhanced gauge symmetries, where all internal moduli can be attracted and dynamically stabilized. Using the fact that the heterotic/type I S-duality remains valid at finite temperature and can be applied at each instant of a quasi-static evolution, we find in the dual type I cosmology that all internal NS-NS and RR moduli in the closed string sector and the Wilson lines in the open string sector can be stabilized. For the special case of D=6, the internal volume modulus remains a flat direction, while the dilaton is stabilized. An essential role is played by light D-string modes wrapping the internal manifold and whose contribution to the free energy cannot be omitted, even when the type I string is at weak coupling. As a result, the order of magnitude of the internal radii expectation values on the type I side is (lambda_I alpha')^{1/2}, where lambda_I is the ten-dimensional string coupling. The non-perturbative corrections to the type I free energy can alternatively be described as effects of "thermal E1-instantons", whose worldsheets wrap the compact Euclidean time cycle.Comment: 39 pages, 1 figur

FastTagger: an efficient algorithm for genome-wide tag SNP selection using multi-marker linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Human genome contains millions of common single nucleotide polymorphisms (SNPs) and these SNPs play an important role in understanding the association between genetic variations and human diseases. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), thus it is not necessary to genotype all SNPs for association study. Many algorithms have been developed to find a small subset of SNPs called tag SNPs that are sufficient to infer all the other SNPs. Algorithms based on the <it>r</it>²LD statistic have gained popularity because <it>r</it>²is directly related to statistical power to detect disease associations. Most of existing <it>r</it>²based algorithms use pairwise LD. Recent studies show that multi-marker LD can help further reduce the number of tag SNPs. However, existing tag SNP selection algorithms based on multi-marker LD are both time-consuming and memory-consuming. They cannot work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.</p> <p>Results</p> <p>We propose an efficient algorithm called FastTagger to calculate multi-marker tagging rules and select tag SNPs based on multi-marker LD. FastTagger uses several techniques to reduce running time and memory consumption. Our experiment results show that FastTagger is several times faster than existing multi-marker based tag SNP selection algorithms, and it consumes much less memory at the same time. As a result, FastTagger can work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.</p> <p>FastTagger also produces smaller sets of tag SNPs than existing multi-marker based algorithms, and the reduction ratio ranges from 3%-9% when length-3 tagging rules are used. The generated tagging rules can also be used for genotype imputation. We studied the prediction accuracy of individual rules, and the average accuracy is above 96% when <it>r</it>²≥ 0.9.</p> <p>Conclusions</p> <p>Generating multi-marker tagging rules is a computation intensive task, and it is the bottleneck of existing multi-marker based tag SNP selection methods. FastTagger is a practical and scalable algorithm to solve this problem.</p

A statistical framework for genetic association studies of power curves in bird flight

How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maximum likelihood context, implemented with the EM algorithm for estimating the population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameters of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution