42 research outputs found
An epidemiological study of ear morbidities among primary school children in a rural area of Delhi
Background: Globally, more than 360 million population (nearly 5% of worldβs population) have disabling hearing loss and 32 million of them are children. Approximately 0.5-5 of every 1000 infants is born with or develops in early childhood disabling hearing loss. It is estimated that over 60% of the otological (ear) morbidities could be avoided through preventive measures, as stated by World Health Organization (2015). As per World health Organization report 2007, 6% of the population of India suffers with significant otological morbidities. Many ear morbidities have their origin in childhood and they may go unnoticed. Estimates indicate that by the age of 3 years at least half of children have experienced at least one episode of middle ear infection. Because it is a childhood illness, it requires close monitoring of signs and symptoms and it is often co-morbid with other infections of the upper or lower respiratory tract. Method: It was a cross sectional study conducted at a rural area based school of Delhi. A total of 368 primary school students, 5 to 11 years age, were included. Questionnaire was used to take history of ear morbidities, related risk factors and health seeking behaviour. Ear examination was performed using otoscope. Educational status of mother, immunization status, frequent cough-coryza, socio-economic status were found to be significant risk factors [p<0.05]. Results: Around 25 % of students had preventable ear morbidity. Cerumen impaction was the commonest morbidity followed by Chronic Suppurative Otitis Media. Conclusion: Preventable ear morbidities are prevalent among children. Health education pertaining to health seeking behaviour for ear hygiene and regular ear examination in schools can reduce the prevalence of ear morbidities.
Keywords: cerumen, otitis media, otological morbidities, rura
Assessment and performance evaluation of photon optimizer (PO) vs. dose volume optimizer (DVO) for IMRT and progressive resolution optimizer (PRO) for RapidArc planning using a virtual phantom
Purpose: The purpose of the study was to present the quantitative and qualitative evaluation of newly incorporated photon optimizer (PO) versus previously was used independent dose volume optimizer (DVO) for intensity modulated radiation therapy (IMRT) and progressive resolution optimizer (PRO) for Rapid-arc/ volumetric modulated arc therapy (VMAT) in version 13.5 of Eclipse treatment planning system (ETPS).Methods: We accomplished this study with the help of cylindrical virtual phantom created in the ETPS. Six individual phantoms study sets (PSS) were generated and different material density value was assigned in order to evaluate the behavior optimizers in the presence of tissue heterogeneity. Several independent plans were generated for IMRT and Rapid-arc by changing optimizer module PO, DVO, and PRO for 6 MV, 15 MV flattened beam and 6 MV-flattening filter free (FFF) beam.Results: The self-governing evaluations of PO versus DVO for IMRT plan and PO versus PRO for Rapid-arc/VMAT plans were performed. We estimated and compared various distinct parameters such as maximum dose, minimum dose, mean dose, conformity index (CI), quality index (QI), homogeneity index (HI), integral plan monitor unit (MU) and dose volume histogram (DVH). The percentages of the average variation over all PSS and beam energy between PO versus DVO optimized plan quality parameters such as planning target volume (PTV) maximum, minimum, mean doses, CI, QI and HI were 0.23%, 1.67%, 0.09%, 20.4%, 0.77% and 0.52% , respectively, whereas for PO versus PRO were 1.18%, 3.38%, 0.19%, 8.11%, 2.78%, and 1.28%, respectively.Conclusion: The results presented in this study showed that PO generates plans with better quality in shorter time compared to DVO and PRO for both IMRT and Rapid-arc/VMAT, respectively
Gender-Based Comparative Study of Type 2 Diabetes Risk Factors in Kolkata, India: A Machine Learning Approach
Type 2 diabetes mellitus represents a prevalent and widespread global health
concern, necessitating a comprehensive assessment of its risk factors. This
study aimed towards learning whether there is any differential impact of age,
Lifestyle, BMI and Waist to height ratio on the risk of Type 2 diabetes
mellitus in males and females in Kolkata, West Bengal, India based on a sample
observed from the out-patient consultation department of Belle Vue Clinic in
Kolkata. Various machine learning models like Logistic Regression, Random
Forest, and Support Vector Classifier, were used to predict the risk of
diabetes, and performance was compared based on different predictors. Our
findings indicate a significant age-related increase in risk of diabetes for
both males and females. Although exercising and BMI was found to have
significant impact on the risk of Type 2 diabetes in males, in females both
turned out to be statistically insignificant. For both males and females,
predictive models based on WhtR demonstrated superior performance in risk
assessment compared to those based on BMI. This study sheds light on the
gender-specific differences in the risk factors for Type 2 diabetes, offering
valuable insights that can be used towards more targeted healthcare
interventions and public health strategies.Comment: 10 pages, 7 tables,3 figures, submitted to a conferenc
Biofuel production potential from wastewater in India by integrating anaerobic membrane reactor with algal photobioreactor
The authors would like to express sincere gratitude towards the Director, Birla Institute of Technology and Science, Pilani K. K. Birla Goa Campus for the support in using the institutional infrastructure for the development of this paper.Peer reviewedPostprin
Biochemical Characterization of High Mercury Tolerance in a Pseudomonas Spp. Isolated from Industrial Effluent
A mercury resistant Pseudomonas spp. was isolated from industrial effluent that was able to tolerate 200 Β΅M HgCl2. The Hg2+-resistant Pseudomonas spp. exhibited elevated stress-regulatory mechanisms as indicated by its high and inducible mercury reductase activity, high intrinsic catalase activity and enhanced resistance to Hg2+-induced release of protein-bound iron. An enhanced resistance of the bacterium to Hg2+-induced lipid peroxidation was observed as indicated by 40% lower conjugated diene and 60% lower lipid hydroperoxide content compared to a non-mercury resistant strain Pseudomonas aeruginosa (ATCC 27853). Phospholipid (PL) analysis of both the species reveled intrinsic differences in their PL composition. We observed 80% PE, 15% PG and 5% of an unidentified PL (U) in MRP compared to 65% PE, 20% PG and 17% CL in Pseudomonas aeruginosa (ATCC 27853). Mercury toxicity led to significant reorganization of PL in Pseudomonas aeruginosa (ATCC 27853) compared to MRP. While HgCl2 led to 25% increase in PE, 35% depletion in CL and 27% depletion in PG content of Pseudomonas aeruginosa (ATCC 27853), MRP exhibited only 5% enhancement in PE content that was accompanied by 20% depletion in PG content, indicating that MRP resists mercury induced PL organization. Interaction of the MRP with polystyrene surface showed two fold higher Hg2+-induced exopolysaccharide secretion and elevated biofilm forming ability compared to Pseudomonas aeruginosa (ATCC 27853). Our investigation reveals a novel Pseudomonas spp. with high Hg2+-tolerance mechanisms that can be utilized for efficient bioremediation of mercury
Correlation between morphological, chemical and RAPD markers for assessing genetic diversity in Withania somnifera (L.) Dunal
A compendium of molecules involved in vector-pathogen interactions pertaining to malaria
Malaria is a vector-borne disease causing extensive morbidity, debility and mortality. Development of resistance to drugs among parasites and to conventional insecticides among vector-mosquitoes necessitates innovative measures to combat this disease. Identification of molecules involved in the maintenance of complex developmental cycles of the parasites within the vector and the host can provide attractive targets to intervene in the disease transmission. In the last decade, several efforts have been made in identifying such molecules involved in mosquito-parasite interactions and, subsequently, validating their role in the development of parasites within the vector. In this study, a list of mosquito proteins, which facilitate or inhibit the development of malaria parasites in the midgut, haemolymph and salivary glands of mosquitoes, is compiled. A total of 94 molecules have been reported and validated for their role in the development of malaria parasites inside the vector. This compendium of molecules will serve as a centralized resource to biomedical researchers investigating vector-pathogen interactions and malaria transmission. Β© 2013 Sreenivasamurthy et al.; licensee BioMed Central Ltd
Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes
Β© 2017 Wong et al.; Published by Cold Spring Harbor Laboratory Press. Complementing genome sequence with deep transcriptome and proteome data could enable more accurate assembly and annotation of newly sequenced genomes. Here, we provide a proof-of-concept of an integrated approach for analysis of the genome and proteome of Anopheles stephensi, which is one of the most important vectors of the malaria parasite. To achieve broad coverage of genes, we carried out transcriptome sequencing and deep proteome profiling of multiple anatomically distinct sites. Based on transcriptomic data alone, we identified and corrected 535 events of incomplete genome assembly involving 1196 scaffolds and 868 protein-coding gene models. This proteogenomic approach enabled us to add 365 genes that were missed during genome annotation and identify 917 gene correction events through discovery of 151 novel exons, 297 protein extensions, 231 exon extensions, 192 novel protein start sites, 19 novel translational frames, 28 events of joining of exons, and 76 events of joining of adjacent genes as a single gene. Incorporation of proteomic evidence allowed us to change the designation of more than 87 predicted noncoding RNAs to conventional mRNAs coded by protein-coding genes. Importantly, extension of the newly corrected genome assemblies and gene models to 15 other newly assembled Anopheline genomes led to the discovery of a large number of apparent discrepancies in assembly and annotation of these genomes. Our data provide a framework for how future genome sequencing efforts should incorporate transcriptomic and proteomic analysis in combination with simultaneous manual curation to achieve near complete assembly and accurate annotation of genomes
A Systematic Analysis of Eluted Fraction of Plasma Post Immunoaffinity Depletion: Implications in Biomarker Discovery
Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS) has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20) cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house), we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample