Chronic kidney disease has a graded association with death and cardiovascular outcomes in stable coronary artery disease : An analysis of 21,911 patients from the CLARIFY registry

Chronic kidney disease (CKD) is associated with an increased cardiovascular risk in a broad spectrum of populations. However, the risk associated with a reduced estimated glomerular filtration rate (eGFR) in patients with stable coronary artery disease receiving standard care in the modern era, independently of baseline cardiovascular disease, risk factors, and comorbidities, remains unclear. We analyzed data from 21,911 patients with stable coronary artery disease, enrolled in 45 countries between November 2009 and July 2010 in the CLARIFY registry. Patients with abnormal renal function were older, with more comorbidities, and received slightly lower-although overall high-rates of evidence-based secondary prevention therapies than patients with normal renal function. The event rate of patients with CKD stage 3b or more (eGFR <45 mL/min/1.73 m) was much higher than that associated with any comorbid condition. In a multivariable adjusted Cox proportional hazards model, lower eGFR was independently associated with a graded increased risk of cardiovascular mortality, with adjusted HRs (95% CI) of 0.98 (0.81-1.18), 1.31 (1.05-1.63), 1.77 (1.38-2.27), and 3.12 (2.25-4.33) for eGFR 60-89, 45-59, 30-44, and <30 mL/min/1.73 m, compared with eGFR ≥90 mL/min/1.73 m. A strong graded independent relationship exists between the degree of CKD and cardiovascular mortality in this large cohort of patients with chronic coronary artery disease, despite high rates of secondary prevention therapies. Among clinical risk factors and comorbid conditions, CKD stage 3b or more is associated with the highest cardiovascular mortality

Chronic kidney disease has a graded association with death and cardiovascular outcomes in stable coronary artery disease: an analysis of 21,911 patients from the CLARIFY registry

Chronic kidney disease (CKD) is associated with an increased cardiovascular risk in a broad spectrum of populations. However, the risk associated with a reduced estimated glomerular filtration rate (eGFR) in patients with stable coronary artery disease receiving standard care in the modern era, independently of baseline cardiovascular disease, risk factors, and comorbidities, remains unclear. We analyzed data from 21,911 patients with stable coronary artery disease, enrolled in 45 countries between November 2009 and July 2010 in the CLARIFY registry. Patients with abnormal renal function were older, with more comorbidities, and received slightly lower—although overall high—rates of evidence-based secondary prevention therapies than patients with normal renal function. The event rate of patients with CKD stage 3b or more (eGFR &lt;45 mL/min/1.73 m2) was much higher than that associated with any comorbid condition. In a multivariable adjusted Cox proportional hazards model, lower eGFR was independently associated with a graded increased risk of cardiovascular mortality, with adjusted HRs (95% CI) of 0.98 (0.81–1.18), 1.31 (1.05–1.63), 1.77 (1.38–2.27), and 3.12 (2.25–4.33) for eGFR 60–89, 45–59, 30–44, and &lt;30 mL/min/1.73 m2, compared with eGFR ≥90 mL/min/1.73 m2. A strong graded independent relationship exists between the degree of CKD and cardiovascular mortality in this large cohort of patients with chronic coronary artery disease, despite high rates of secondary prevention therapies. Among clinical risk factors and comorbid conditions, CKD stage 3b or more is associated with the highest cardiovascular mortality

HCV Causes Chronic Endoplasmic Reticulum Stress Leading to Adaptation and Interference with the Unfolded Protein Response

BACKGROUND: The endoplasmic reticulum (ER) is the cellular site for protein folding. ER stress occurs when protein folding capacity is exceeded. This stress induces a cyto-protective signaling cascades termed the unfolded protein response (UPR) aimed at restoring homeostasis. While acute ER stress is lethal, chronic sub-lethal ER stress causes cells to adapt by attenuation of UPR activation. Hepatitis C virus (HCV), a major human pathogen, was shown to cause ER stress, however it is unclear whether HCV induces chronic ER stress, and if so whether adaptation mechanisms are initiated. We wanted to characterize the kinetics of HCV-induced ER stress during infection and assess adaptation mechanisms and their significance. METHODS AND FINDINGS: The HuH7.5.1 cellular system and HCV-transgenic (HCV-Tg) mice were used to characterize HCV-induced ER stress/UPR pathway activation and adaptation. HCV induced a wave of acute ER stress peaking 2-5 days post-infection, which rapidly subsided thereafter. UPR pathways were activated including IRE1 and EIF2α phosphorylation, ATF6 cleavage and XBP-1 splicing. Downstream target genes including GADD34, ERdj4, p58ipk, ATF3 and ATF4 were upregulated. CHOP, a UPR regulated protein was activated and translocated to the nucleus. Remarkably, UPR activity did not return to baseline but remained elevated for up to 14 days post infection suggesting that chronic ER stress is induced. At this time, cells adapted to ER stress and were less responsive to further drug-induced ER stress. Similar results were obtained in HCV-Tg mice. Suppression of HCV by Interferon-α 2a treatment, restored UPR responsiveness to ER stress tolerant cells. CONCLUSIONS: Our study shows, for the first time, that HCV induces adaptation to chronic ER stress which was reversed upon viral suppression. These finding represent a novel viral mechanism to manipulate cellular response pathways

Label-Free Optical Single-Molecule Micro- and Nanosensors

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this recordLabel-free optical sensor systems have emerged that exhibit extraordinary sensitivity for detecting physical, chemical, and biological entities at the micro/nanoscale. Particularly exciting is the detection and analysis of molecules, on miniature optical devices that have many possible applications in health, environment, and security. These micro- and nanosensors have now reached a sensitivity level that allows for the detection and analysis of even single molecules. Their small size enables an exceedingly high sensitivity, and the application of quantum optical measurement techniques can allow the classical limits of detection to be approached or surpassed. The new class of label-free micro- and nanosensors allows dynamic processes at the single-molecule level to be observed directly with light. By virtue of their small interaction length, these micro- and nanosensors probe light–matter interactions over a dynamic range often inaccessible by other optical techniques. For researchers entering this rapidly advancing field of single-molecule micro- and nanosensors, there is an urgent need for a timely review that covers the most recent developments and that identifies the most exciting opportunities. The focus here is to provide a summary of the recent techniques that have either demonstrated label-free single-molecule detection or claim single-molecule sensitivity.Living Systems Institute, University of Exete

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

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

A disciplina estatística no curso de pedagogia da USP: uma abordagem histórica

Este artigo apresenta uma abordagem histórica acerca da disciplina estatística no curso de pedagogia da Universidade de São Paulo – USP (1939-1999). O objetivo foi investigar as origens da disciplina, os conteúdos e métodos propostos e seu papel na formação do pedagogo. A análise documental e a história oral foram utilizadas como recursos metodológicos. Fundamentando-se na história do currículo, a pesquisa dialogou especialmente com as ideias centrais de Ivor Goodson, ao compreender o currículo como construção social e investigar como e por que certo conhecimento é ensinado (ou não) em determinado contexto histórico. Constatou-se que a estatística foi considerada muito importante para a área educacional na primeira metade do século XX, por contribuir com a produção de diagnósticos para o planejamento de políticas públicas, com os trabalhos de inspeção escolar e com a classificação de alunos. Com origem nos cursos de administradores escolares do Instituto de Educação da Universidade de São Paulo nos anos 1930, a estatística ganhou espaço no curso de pedagogia, criado em 1939, mantendo-se presente no currículo, ainda que tenha passado por várias reformulações curriculares. A partir dos anos 1980, começou a sofrer limitações no campo educacional, seja pelo enfoque das pesquisas educacionais, que perderam gradualmente o cunho quantitativo, seja pela redefinição do curso de pedagogia, que passou a defender a docência como a base da formação do pedagogo

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

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