Quality of Work Life and Mental Health in Primary Care Physicians

AbstractThe aim of this study was to find the relationship between the perception of Quality of Work Life (QWL) and the mental health of primary care physicians of a public health institution in Guadalajara, Mexico. The study was analytical and was carried out with a universe of 818 doctors from 92 health units and the probability sample of 154 people. In all of them, CVT-GOHISALO and Goldberg GHQ-28 questionnaires were applied in order to measure their perception of QWL and the risk of mental illness respectively. Both instruments were selected because of their high reliability. We measured the satisfaction of the people interviewed for each one of the seven dimensions of CVT-GOHISALO and related to the points assigned to GHQ-28 case or not to consider the case of mental illness. The percentages of dissatisfaction with the QWL were greater than 12% in all dimensions of the instrument, being the highest value of 20.5% dissatisfaction for the job satisfaction dimension. In the classification of the case or not according to the GHQ-28, 22% were considered cases and 78% non-cases. We sought correspondence of satisfaction with the QWL by dimensions and non-case of Goldberg's, as well as dissatisfaction with the QWL and Goldberg's case, finding a clear link between being satisfied and having mental health. All dimensions have a correspondence that goes from 79.7% to 82.3% between satisfaction and non-case, being in all the statistical significance value less than 0.05 For primary care physicians in the studied institution, there is a clear relationship between being satisfied with the QWL and present less risk of mental illness. It is alarming that the medical staff presents high rates of dissatisfaction with the QWL and risk of mental illness. It is necessary to provide preventive programs among health care workers in order to improve their QWL and mental health

Comparative and functional genomics of the protozoan parasite Babesia divergens highlighting the invasion and egress processes

Babesiosis is considered an emerging disease because its incidence has significantly increased in the last 30 years, providing evidence of the expanding range of this rare but potentially life-threatening zoonotic disease. Babesia divergens is a causative agent of babesiosis in humans and cattle in Europe. The recently sequenced genome of B. divergens revealed over 3,741 protein coding-genes and the 10.7-Mb high-quality draft become the first reference tool to study the genome structure of B. divergens. Now, by exploiting this sequence data and using new computational tools and assembly strategies, we have significantly improved the quality of the B. divergens genome. The new assembly shows better continuity and has a higher correspondence to B. bovis chromosomes. Moreover, we present a differential expression analysis using RNA sequencing of the two different stages of the asexual lifecycle of B. divergens: the free merozoite capable of invading erythrocytes and the intraerythrocytic parasite stage that remains within the erythrocyte until egress. Comparison of mRNA levels of both stages identified 1,441 differentially expressed genes. From these, around half were upregulated and the other half downregulated in the intraerythrocytic stage. Orthogonal validation by real-time quantitative reverse transcription PCR confirmed the differential expression. A moderately increased expression level of genes, putatively involved in the invasion and egress processes, were revealed in the intraerythrocytic stage compared with the free merozoite. On the basis of these results and in the absence of molecular models of invasion and egress for B. divergens, we have proposed the identified genes as putative molecular players in the invasion and egress processes. Our results contribute to an understanding of key parasitic strategies and pathogenesis and could be a valuable genomic resource to exploit for the design of diagnostic methods, drugs and vaccines to improve the control of babesiosis.This work was funded by grants from Ministerio de Economía y Competitividad from Spain (AGL2010-21774 and AGL2014-56193 R to EM and LMG). ES was awarded a research fellowship from Plan Estatal de Investigación Científica y Técnica y de Innovación, Ministerio de Economía y Competitividad, Spain (http://www.mineco.gob.es/portal/site/mineco/). Work in CL’s laboratory is funded by a grant from the National Institutes of Health (https://www.nih.gov/) NIH- 1R01HL140625-01. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscriptS

Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort.

Some patients with breast cancer treated by surgery and radiation therapy experience clinically significant toxicity, which may adversely affect cosmesis and quality of life. There is a paucity of validated clinical prediction models for radiation toxicity. We used machine learning (ML) algorithms to develop and optimise a clinical prediction model for acute breast desquamation after whole breast external beam radiation therapy in the prospective multicenter REQUITE cohort study. Using demographic and treatment-related features (m = 122) from patients (n = 2058) at 26 centers, we trained 8 ML algorithms with 10-fold cross-validation in a 50:50 random-split data set with class stratification to predict acute breast desquamation. Based on performance in the validation data set, the logistic model tree, random forest, and naïve Bayes models were taken forward to cost-sensitive learning optimisation. One hundred and ninety-two patients experienced acute desquamation. Resampling and cost-sensitive learning optimisation facilitated an improvement in classification performance. Based on maximising sensitivity (true positives), the "hero" model was the cost-sensitive random forest algorithm with a false-negative: false-positive misclassification penalty of 90:1 containing m = 114 predictive features. Model sensitivity and specificity were 0.77 and 0.66, respectively, with an area under the curve of 0.77 in the validation cohort. ML algorithms with resampling and cost-sensitive learning generated clinically valid prediction models for acute desquamation using patient demographic and treatment features. Further external validation and inclusion of genomic markers in ML prediction models are worthwhile, to identify patients at increased risk of toxicity who may benefit from supportive intervention or even a change in treatment plan. [Abstract copyright: © 2022 The Authors.

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Global variations in diabetes mellitus based on fasting glucose and haemogloblin A1c

Fasting plasma glucose (FPG) and haemoglobin A1c (HbA1c) are both used to diagnose diabetes, but may identify different people as having diabetes. We used data from 117 population-based studies and quantified, in different world regions, the prevalence of diagnosed diabetes, and whether those who were previously undiagnosed and detected as having diabetes in survey screening had elevated FPG, HbA1c, or both. We developed prediction equations for estimating the probability that a person without previously diagnosed diabetes, and at a specific level of FPG, had elevated HbA1c, and vice versa. The age-standardised proportion of diabetes that was previously undiagnosed, and detected in survey screening, ranged from 30% in the high-income western region to 66% in south Asia. Among those with screen-detected diabetes with either test, the agestandardised proportion who had elevated levels of both FPG and HbA1c was 29-39% across regions; the remainder had discordant elevation of FPG or HbA1c. In most low- and middle-income regions, isolated elevated HbA1c more common than isolated elevated FPG. In these regions, the use of FPG alone may delay diabetes diagnosis and underestimate diabetes prevalence. Our prediction equations help allocate finite resources for measuring HbA1c to reduce the global gap in diabetes diagnosis and surveillance.peer-reviewe

Characterization of infiltration capacity of permeable pavements with porous asphalt surface using cantabrian fixed infiltrometer

Porous asphalt is used in Permeable Pavement Systems, but it is sensitive to surface clogging, which leads to a loss in its infiltration capacity. Test methods based on the use of permeable pavement models, which are manufactured in a laboratory and assessed under different clogging conditions, such as slope, rain, and runoff, have been widely applied to the study of permeable pavements with concrete blocks but not to the study of porous bituminous mixtures. The Cantabrian Fixed (CF) Infiltrometer has been used for the study of porous asphalt with void percentages between 20 and 33%. Three clogging scenarios were studied: 1) newly placed surface, 2) surface with an average maintenance level, and 3) clogged surface. Each clogging scenario was tested with five different slopes: 0, 2, 5, 8, and 10% and three repetitions. The direct rainfall simulation was produced by five lines of bubblers over the 0.25 - m 2 piece, and the runoff was simulated by one perforated pipe over a plastic ramp at the beginning of the surface. From the analysis of the results, it was concluded that a suitable design of a porous bituminous mixture, with a void percentage that increases with depth, along with surface brushing are enough to ensure and maintain a good infiltration capacity. Finally, an empirical, conservative model for estimating the porous asphalt infiltration capacity, based on the length, the clogging scenario, and the surface slope, is proposed

. 53 Tomo V (1974-1975) Séptima Época (1967-1976). Anales del Instituto Nacional de Antropología e Historia

Publicación que recopila y difunde cien años de trabajo de la antropología en México (1877-1977), integrada por documentos y manuscritos arqueológicos, antropológicos, históricos, geológicos, botánicos y lingüísticos.- Exploraciones en Palenque durante 1972 por Jorge R. Acosta. - Exploraciones en Palenque, temporada 1973-1974 por Jorge R. Acosta. - Tercera temporada de salvamento arqueológico en la Presa de la Angostura, Chiapas por Jordi Gussinyer. - San Juan Parangaricutiro: Memorias de un campesino por Celedonio Gutiérrez. - El Ixtépete como un ejemplo de desarrollo cultural en el occidente de México por Lorenzo Ochoa S. y Marcia Castro Leal. - El trabajo educativo y su relación con algunos aspectos de la sociolingüística por Antonio García de León. - Cerámica de Uxmal, Yucatán por César A. Sáenz. - La ceiba-cocodrilo por Alfredo Barrera Vázquez. - Artefactos en piedra pulida del México prehispánico por Constanza Vega Sosa. - Relaciones familiares en el pedigree de los lacandones de México por Lourdes Cobo de Gallegos, Alfonso L. de Garay y James E. Bowman