PUBLICATION TRENDS IN GLOBAL OUTPUT OF RFID: A BIBLIOMETRIC PROFILE

The paper presents an analysis of 2735 global publications in RFID(Radio Frequency Identification), indexed in Web of science database during 2014-2018. The collected records were analyzed with the help of ‘Histcite tool’.The present study attempted to reveal the year, country and institution, formwise distribution, authorship pattern, degree of collaboration, relative growth rate and doubling time of publications. The findings of this showed that degree of Collaboration was high at 2017 (0.96).The relative growth rates (RGR) has increased and the doubling time (DT) has rapidly decreased while calculated year wise i.e.2014 to 2018

RESEARCH OUTPUT ON MYOPIA DURING THE PERIOD 2016-2018: A SCIENTOMETRIC ANALYSIS

The article covers 3092 publications on myopia research in global level from the period of 2016-2018.Web of science database has been used to retrieve the scientometric records for the study period.The trends within the most influential publications and authors were analyzed. The aim of this study was to analyze the year wise distribution of articles & citations, authorship pattern of articles, most productive countries and institutions and type of document published. From the analysis, it has been observed that in the year 2016, the highest number of 1085(35.1%) articles were published out of 3092 articles in three years. Multiple author contributions were more dominant with 2879(93.11%) articles. In geographical distribution articles, United States of America have contributed the highest number of 769 articles with 24.9%.The study discloses that the Degree of Collaboration was low at 2017 (0.91), regarding collaborators contribution. The study analyzes the Relative Growth Rate (RGR) has increased from 2016 to 2018 in the span of three years. Doubling time (DT) has rapidly decreased when calculated year wise, i.e.2016 to 2018

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection ar

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

PUBLICATION TRENDS IN GLOBAL OUTPUT OF RFID: A BIBLIOMETRIC PROFILE

The paper presents an analysis of 2735 global publications in RFID(Radio Frequency Identification), indexed in Web of science database during 2014-2018. The collected records were analyzed with the help of ‘Histcite tool’.The present study attempted to reveal the year, country and institution, formwise distribution, authorship pattern, degree of collaboration, relative growth rate and doubling time of publications. The findings of this showed that degree of Collaboration was high at 2017 (0.96).The relative growth rates (RGR) has increased and the doubling time (DT) has rapidly decreased while calculated year wise i.e.2014 to 2018

Fungal infections in the soft tissue: A study from a tertiary care center

Isolated fungal soft-tissue infections are uncommon but may cause severe morbidity or mortality, especially among immunosuppressed patients. In this study, a total of 56 soft-tissue specimens from patients with clinical suspicion of fungal infection collected at a tertiary care centre in Chennai during the period December 2005 to May 2007 were evaluated. Among the culture positives, majority were from diabetic patients. Among the 34 culture positives, the isolates consisted of Candida 12, Fusarium 4, Rhizopus 1 and Aspergillus 3 one each of Absidia corymbifera and Apophysomyces elegans . Treatment of fungal soft-tissue infection requires a team approach of surgeons, pathologists and microbiologists

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease