Teachers\u27 Motivational Responses to New Teacher Performance Management Systems: An Evaluation of the Pilot of Aldine ISD\u27s inVEST System

Research has shown that some teachers are dramatically more effective than others and further, that these differences are among the most important schooling factors affecting student learning. Accordingly, shifts in policy have resulted in the development of new performance management systems with the goal of improving teacher effectiveness. Although a growing body of research has begun to examine the impact of recent systems, we have very limited knowledge on how these systems influence teachers\u27 motivation and improvement. This dissertation moves the body of research forward by using expectancy-value theory and mixed-methods analysis to examine the impact of INVEST, a new teacher evaluation system in Aldine ISD in Houston, Texas, on teacher motivation, effectiveness, and retention. It also explores how individual personality characteristics, school organizational factors, and evaluation system features influence these outcomes. It employs a mixed methods design, utilizing the strengths of both methodological approaches. The quantitative research captures broad-based results from a teacher survey given to the population of teachers pre- and post- pilot and uses difference-in-differences analysis to examine the impact of the pilot on key outcomes (i.e., motivation, effectiveness, and retention) and multiple regression analysis to examine which predictors (at the individual, school, and system level) influenced outcomes. This analysis is supplemented by the qualitative research which draws from a small purposive sample of teachers to gain an in- depth understanding of how the policy influenced teachers\u27 experiences. Analyses revealed that overall INVEST had a negative impact on teachers\u27 belief in their abilities (expectancy) and no significant impact on the importance they placed on their work (value), their effectiveness, or their decision to remain in teaching. However, teachers\u27 responses varied considerably based on their individual characteristics (e.g., teachers\u27 grit), their school\u27s conditions (e.g., leadership), and their system perceptions (e.g., understanding, accuracy of measures, quality of feedback). The extensive data collected in this analysis offer a rich picture of the implementation of new performance management systems. Thus, it provides both policymakers and researchers with a better understanding of how new policies impact teacher\u27s behavior and the influence of various characteristics (at the individual, school, and system level)

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Stem Cell Research

Book description: More than 150 key social issues confronting the United States today are covered in this eight-volume set, in an A to Z format: from abortion and adoption to capital punishment and corporate crime; from obesity and organized crime to sweatshops and xenophobia. Each includes historical background on the issue; a discussion of current problems, debates, and possible future developments; a chronology; fairly extensive lists of references and Web sites to consult for further information; a glossary; and, in most cases, one or more selected primary documents

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease

Genetic studies of body mass index yield new insights for obesity biology

Note: A full list of authors and affiliations appears at the end of the article. Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P 20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.</p

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease