Are the health care workers geared to prevent H1N1 in the future?

Objective: Our aim was to assess the knowledge on transmission and prevention of H1N1 influenza among health care workers who play a fundamental role in the community. Methods: We selected Colombo South Teaching Hospital as the study setting to conduct a descriptive cross sectional study. The expected proportion of adequate knowledge was taken as 50% and at 0.05 precision with a non-respondent rate of 10% a study sample of 406 nurses was obtained. A self-administered questionnaire aided in seeking information on socio-demographic details, knowledge and attitude regarding H1N1. Significance level was set at p < 0.05 and tested using Chi-square. Results: Majority knew nasal secretions 338(83.3%) and infective saliva 308(75.9%) as modes of transmission of H1N1 and their mean score was 8.37(S.D±1.53) out of 10. Higher percentages of the study sample knew about hand hygiene 375(92.4%), facial masks 391(96.3%), and patient isolation 344(84.5%) as effective means of prevention. A proportion of 80.5% (n=327) also knew that vaccine is a preventive method and their knowledge on its efficacy had a significant association with vaccination (p= 0.001). However 55.9% (n=227) have not been vaccinated due to side effects of the vaccine. The practices on both transmission of H1N1 (p=0.171) and prevention of H1N1 had no significant association with their actual knowledge (p=0.268). Conclusion: Despite the knowledge their practice of prevention as health care workers was inadequate. Therefore the necessity arises to identify areas in which improvement can be made with the purpose of getting them efficiently and confidently involved in disease prevention

Source Localization by Multidimensional Steered Response Power Mapping with Sparse Bayesian Learning

We propose a method that combines Steered Response Power SRP with sparse optimization for localizing multiple sources While conventional SRP is robust under adverse conditions it struggles with scenarios involving neighboring sources often resulting in ambiguous SRP maps The current state of the art approach optimizes observed SRP maps through group sparse modeling but its performance degrades in reverberant scenarios To address this issue we extend the framework by modeling SRP functions as a multidimensional matrix thereby preserving time frequency information Additionally we employ multi dictionary sparse Bayesian learning as the sparse optimization method to identify source positions without prior knowledge of their quantity We validate our method through practical experiments using a 16 channel planar microphone array and compare it against three other localization methods Results demonstrate that our proposed method outperforms other methods including the current state of the art in localizing closely spaced sources in reverberant environment

Novel and de novo mutations in pediatric refractory epilepsy

Abstract Pediatric refractory epilepsy is a broad phenotypic spectrum with great genetic heterogeneity. Next-generation sequencing (NGS) combined with Sanger sequencing could help to understand the genetic diversity and underlying disease mechanisms in pediatric epilepsy. Here, we report sequencing results from a cohort of 172 refractory epilepsy patients aged 0–14 years. The pathogenicity of identified variants was evaluated in accordance with the American College of Medical Genetics and Genomics (ACMG) criteria. We identified 43 pathogenic or likely pathogenic variants in 40 patients (23.3%). Among these variants, 74.4% mutations (32/43) were de novo and 60.5% mutations (26/43) were novel. Patients with onset age of seizures ≤12 months had higher yields of deleterious variants compared to those with onset age of seizures > 12 months (P = 0.006). Variants in ion channel genes accounted for the greatest functional gene category (55.8%), with SCN1A coming first (16/43). 81.25% (13/16) of SCN1A mutations were de novo and 68.8% (11/16) were novel in Dravet syndrome. Pathogenic or likely pathogenic variants were found in the KCNQ2, STXBP1, SCN2A genes in Ohtahara syndrome. Novel deleterious variants were also found in West syndrome, Doose syndrome and glucose transporter type 1 deficiency syndrome patients. One de novo MECP2 mutation were found in a Rett syndrome patient. TSC1/TSC2 variants were found in 60% patients with tuberous sclerosis complex patients. Other novel mutations detected in unclassified epilepsy patients involve the SCN8A, CACNA1A, GABRB3, GABRA1, IQSEC2, TSC1, VRK2, ATP1A2, PCDH19, SLC9A6 and CHD2 genes. Our study provides novel insights into the genetic origins of pediatric epilepsy and represents a starting-point for further investigations into the molecular pathophysiology of pediatric epilepsy that could eventually lead to better treatments

Correction to: Novel and de novo mutations in pediatric refractory epilepsy

Following publication of the original article [1], the authors reported that one of the authors’ names is spelled incorrectly