A Comparison of Outflow Properties in AGN Dwarfs vs. Star Forming Dwarfs

Feedback likely plays a crucial role in resolving discrepancies between observed and theoretical predictions of dwarf galaxy properties. Stellar feedback was once believed to be sufficient to explain these discrepancies, but it has thus far failed to fully reconcile theory and observations. The recent discovery of energetic galaxy-wide outflows in dwarf galaxies hosting Active Galactic Nuclei (AGN) suggests that AGN feedback may have a larger role in the evolution of dwarf galaxies than previously suspected. In order to assess the relative importance of stellar versus AGN feedback in these galaxies, we perform a detailed Keck/KCWI optical integral field spectroscopic study of a sample of low-redshift star-forming (SF) dwarf galaxies that show outflows in ionized gas in their SDSS spectra. We characterize the outflows and compare them to observations of AGN-driven outflows in dwarfs. We find that SF dwarfs have outflow components that have comparable widths (W$_{80}$) to those of outflows in AGN dwarfs, but are much less blue-shifted, indicating that SF dwarfs have significantly slower outflows than their AGN counterparts. The outflows in SF dwarfs are spatially resolved and significantly more extended than those in AGN dwarfs. The mass loss rates, momentum and energy rates of SF-driven outflows are much lower than those of AGN-driven outflows. Our results indicate that AGN feedback in the form of gas outflows may play an important role in dwarf galaxies and should be considered along with SF feedback in models of dwarf galaxy evolution.Comment: 27 pages, 25 figures, Accepted for publication in Ap

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background: Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods: The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results: A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P < 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion: Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)

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 hospitalization2–4 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

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

Оцінка статури за вимірюванням нижньої кінцівки шляхом регресійного аналізу населення північно-західної Індії

The aim of the study was to estimate the stature from lower limb parameters in the north-west population of India and to know whether a significant correlation exists between the stature and various lower limb dimensions and to further derive regression formulae for estimation of stature from various lower limb segments. Materials and methods: the study was conducted on medical students age ranged between 18 to 28 years, which comes chiefly from north-west part of India. Only the subjects willing to participate in the study and given their written informed consent were included in the study group. The students having any obvious physical deformity were excluded from the study. Correlations between various lower limb parameters and stature were determined by using the Pearson’s correlation test. Sex-specific linear regression equations for stature estimation were developed using the lower limb measurements. The multiple regressions equations were produced based on various combinations of the parameters by stepwise regression analysis. Results: the Pearson’s correlation in combined group showed good correlations between lower limb parameters and stature. There was no statistically significant difference between known stature and estimated stature by using paired T-test for both right and left side in a group consisting of both sexes and in males (p>0.05). Conclusion: from the parameters, lower limb length and foot length had shown strong positive correlations with stature in the north-west Indian populationЦелью исследования было оценить телосложение по параметрам нижних конечностей в северо-западной популяции Индии и узнать, существует ли значительная корреляция между телосложением и разными размерами нижних конечностей, а также получить дальнейшие формулы регрессии для оценки телосложения с разными размерами нижних конечностей. Материалы и способы. Исследование проводилось на студентах-медиках в возрасте от 18 до 28 лет, приезжающих преимущественно из северо-западной части Индии. В исследовательскую группу были включены только субъекты, желающие участвовать в исследовании и предоставившие письменное информированное согласие. Студенты, имеющие какие-либо явные физические деформации, были исключены из исследования. Корреляцию между разными параметрами нижних конечностей и телосложением определяли с помощью теста на корреляцию Пирсона. Специфические для пола уравнения линейной регрессии для оценки телосложения были разработаны с использованием измерений нижних конечностей. Уравнения множественных регрессий были созданы на основе разных комбинаций параметров путём поэтапного регрессионного анализа. Результаты: корреляция Пирсона в группе, состоящей из обоих полов показала хорошие корреляции между параметрами нижних конечностей и телосложением. Не было статистически значимой разницы между известным и рассчитанным телосложением с помощью парного Т-теста как для правой, так и для левой стороны в группе, состоящей из обоих полов и у мужчин (p>0,05). Вывод: исходя из параметров, длина нижних конечностей и длина стопы показали сильную положительную корреляцию со телосложением населения северо-западной ИндииМетою дослідження було оцінити статуру за параметрами нижніх кінцівок у північно-західній популяції Індії та дізнатися, чи існує значна кореляція між статурою і різними розмірами нижніх кінцівок, а також отримати подальші формули регресії для оцінки статури з різними розмірами нижніх кінцівок. Матеріали та методи. Дослідження проводилося на студентах-медиках віком від 18 до 28 років, які приїжджають переважно з північно-західної частини Індії. У дослідницьку групу були включені лише суб’єкти, які хотіли брати участь у дослідженні та надали письмову інформовану згоду. Студенти, які мають будь-які явні фізичні деформації, були виключені з дослідження. Кореляцію між різними параметрами нижніх кінцівок і статурою визначали за допомогою тесту на кореляцію Пірсона. Специфічні для статі рівняння лінійної регресії для оцінки статури були розроблені з використанням вимірювань нижніх кінцівок. Рівняння множинних регресій були створені на основі різних комбінацій параметрів шляхом поетапного регресійного аналізу. Результати: кореляція Пірсона у групі, що складалась з обох статей показала хороші кореляції між параметрами нижніх кінцівок і статурою. Не було статистично значущої різниці між відомим і розрахованою статурою за допомогою парного Т-тесту як для правого, так і для лівого боку у групі, що складалась з обох статей та у чоловіків (p>0,05). Висновок: виходячи з параметрів, довжина нижніх кінцівок і довжина стопи показали сильну позитивну кореляцію зі статурою населення північно-західної Інді

Estimation of stature from lower limb measurements by regression analysis in north-west Indian population

The aim of the study was to estimate the stature from lower limb parameters in the north-west population of India and to know whether a significant correlation exists between the stature and various lower limb dimensions and to further derive regression formulae for estimation of stature from various lower limb segments. Materials and methods: the study was conducted on medical students age ranged between 18 to 28 years, which comes chiefly from north-west part of India. Only the subjects willing to participate in the study and given their written informed consent were included in the study group. The students having any obvious physical deformity were excluded from the study. Correlations between various lower limb parameters and stature were determined by using the Pearson’s correlation test. Sex-specific linear regression equations for stature estimation were developed using the lower limb measurements. The multiple regressions equations were produced based on various combinations of the parameters by stepwise regression analysis. Results: the Pearson’s correlation in combined group showed good correlations between lower limb parameters and stature. There was no statistically significant difference between known stature and estimated stature by using paired T-test for both right and left side in a group consisting of both sexes and in males (p&gt;0.05). Conclusion: from the parameters, lower limb length and foot length had shown strong positive correlations with stature in the north-west Indian population</jats:p

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Epigenetic Biomarkers Driven by Environmental Toxins Associated with Alzheimer&rsquo;s Disease, Parkinson&rsquo;s Disease, and Amyotrophic Lateral Sclerosis in the United States: A Systematic Review

Environmental toxins and epigenetic changes have been linked to neurodegenerative diseases, including Alzheimer&rsquo;s Disease (AD), Parkinson&rsquo;s Disease (PD), and amyotrophic lateral sclerosis (ALS). This paper aimed to (i) identify environmental toxins associated with AD, PD, and ALS, (ii) locate potential industrial sources of toxins in the United States (U.S.), and (iii) assess epigenetic changes driven by exposure to toxins reported by patients. Environmental factors and epigenetic biomarkers of neurodegeneration were compiled from 69 studies in the literature using Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) and geographic information system approaches. Some 127 environmental toxins have been associated or putatively associated with AD, PD, or ALS, with four toxic metals (As, Cd, Mn, and Hg) common to all three of these neurodegenerative diseases. Environmental toxins associated with epigenetic changes (e.g., DNA methylation) in patients include air pollutants, metals, and organic chemicals (e.g., pesticides, mycotoxins, and cyanotoxins). Geographic analysis showed that study locations (e.g., U.S., Europe, and East Asia) were selected by researchers based on convenience of access rather than exposure risk and disease prevalence. We conclude that several toxins and epigenetic markers shared among neurodegenerative diseases could serve as attractive future targets guiding environmental quality improvements and aiding in early disease detection