School-Based Relationships Among Children with or at Risk for Emotional and Behavioral Disorders

We investigated the influence of a teacher’s perceived emotional state (e.g., feeling emotionally exhausted; feeling accomplished) on the association between parent-teacher relationships and teacher-child conflict among young children. We used pretest data from a pilot study examining the efficacy of a socio-emotional learning intervention for children with or at risk for emotional or behavioral disorders (EBD). Twenty-six teachers and 45 children (Mean age= 7.46 years; SD = 1.21) participated in the intervention. Teachers rated their relationships with children and their parents using the Parent-Teacher Relationship Scale and Student-Teacher Relationship Scale. Multilevel models showed that teachers with a higher sense of personal accomplishment evidenced a negative association between parent-teacher relationships and teacher-child conflict. However, for teachers who felt emotionally exhausted or those who had a lower sense of personal achievement, the association between parent-teacher relationships and teacher-child conflict either remained unchanged or was positive. We conclude by discussing findings in relation to the importance of increasing teacher efficacy, reducing teacher burnout, and strengthening parent-teacher relationships in schools to improve teacher-child relationships and children’s psychosocial outcomes

A high-resolution map of human evolutionary constraint using 29 mammals.

The comparison of related genomes has emerged as a powerful lens for genome interpretation. Here we report the sequencing and comparative analysis of 29 eutherian genomes. We confirm that at least 5.5% of the human genome has undergone purifying selection, and locate constrained elements covering ∼4.2% of the genome. We use evolutionary signatures and comparisons with experimental data sets to suggest candidate functions for ∼60% of constrained bases. These elements reveal a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons. We find 220 candidate RNA structural families, and nearly a million elements overlapping potential promoter, enhancer and insulator regions. We report specific amino acid residues that have undergone positive selection, 280,000 non-coding elements exapted from mobile elements and more than 1,000 primate- and human-accelerated elements. Overlap with disease-associated variants indicates that our findings will be relevant for studies of human biology, health and disease

Climate change mitigation in Zimbabwe and links to sustainable development

In 2021, Zimbabwe updated its Greenhouse Gas (GHG) reduction target from a 33% reduction in per capita energy sector GHG emissions to a 40% reduction from all sectors, compared to 2030 baseline emission scenarios. This work aims to demonstrate how the actions identified in Zimbabwe's Nationally Determined Contribution (NDC) can achieve this updated target, and what development benefits could occur in Zimbabwe through the implementation of these actions. The magnitude of GHG emissions in Zimbabwe are modelled historically and to 2030 to quantify GHG emission reduction potentials, and contributions to selected sustainable development goal targets, from implementation of 28 mitigation measures. The estimated ∼37 million tonnes CO2-equivalent emissions emitted by Zimbabwe in 2017 are projected to increase by 109% to ∼77 million tonnes without implementation of any mitigation measures. The mitigation measures included in the updated NDC could reduce GHG emissions by 40% in 2030 compared to the baseline, while additional measures included in other plans and strategies in Zimbabwe could achieve a further 23% reduction. Implementing Zimbabwe's NDC could also lead to substantial development benefits locally, including to public health, biodiversity, and sustainable energy use. This assessment therefore provides a clear pathway to achieve Zimbabwe's updated climate change mitigation commitment, as the target is linked to the implementation of specific, concrete mitigation actions. It provides a practical example as to how methods to assess climate mitigation and development priorities can be integrated within climate change mitigation target-setting assessments. The more widespread adoption of prospective, quantitative assessment of development benefits from climate change mitigation actions could provide further motivation for more ambitious climate change action

Monitoring soil nutrients using a management unit approach

This publication focuses on how to design a soil nutrient monitoring strategy that fits today’s requirements for record keeping and increased accuracy in managing nitrogen (N), phosphorus (P), and other nutrients. We advocate the use of management units or zones for soil testing and nutrient application. To measure a real change in soil test values over time, you will need to use consistent management units over many growing seasons. In this publication, a management unit is considered an area in a field that is soil sampled and fertilized separately for one or more nutrients. Different management unit delineations may be more appropriate for insect, weed, and disease control; irrigation water management; and other cultural practices.Published October 2003. Reviewed October 2014. Facts and recommendations in this publication may no longer be valid. Please look for up-to-date information in the OSU Extension Catalog: http://extension.oregonstate.edu/catalo

Identification of functional elements and regulatory circuits by Drosophila modENCODE

To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation

Accurate Prediction of Secreted Substrates and Identification of a Conserved Putative Secretion Signal for Type III Secretion Systems

The type III secretion system is an essential component for virulence in many Gram-negative bacteria. Though components of the secretion system apparatus are conserved, its substrates—effector proteins—are not. We have used a novel computational approach to confidently identify new secreted effectors by integrating protein sequence-based features, including evolutionary measures such as the pattern of homologs in a range of other organisms, G+C content, amino acid composition, and the N-terminal 30 residues of the protein sequence. The method was trained on known effectors from the plant pathogen Pseudomonas syringae and validated on a set of effectors from the animal pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium) after eliminating effectors with detectable sequence similarity. We show that this approach can predict known secreted effectors with high specificity and sensitivity. Furthermore, by considering a large set of effectors from multiple organisms, we computationally identify a common putative secretion signal in the N-terminal 20 residues of secreted effectors. This signal can be used to discriminate 46 out of 68 total known effectors from both organisms, suggesting that it is a real, shared signal applicable to many type III secreted effectors. We use the method to make novel predictions of secreted effectors in S. Typhimurium, some of which have been experimentally validated. We also apply the method to predict secreted effectors in the genetically intractable human pathogen Chlamydia trachomatis, identifying the majority of known secreted proteins in addition to providing a number of novel predictions. This approach provides a new way to identify secreted effectors in a broad range of pathogenic bacteria for further experimental characterization and provides insight into the nature of the type III secretion signal

City of Hitchcock Comprehensive Plan 2020-2040

Hitchcock is a small town located in Galveston County (Figure 1.1), nestled up on the Texas Gulf Coast. It lies about 40 miles south-east of Houston. The boundaries of the city encloses an area of land of 60.46 sq. miles, an area of water of 31.64 sq. miles at an elevation just 16 feet above sea level. Hitchcock has more undeveloped land (~90% of total area) than the county combined. Its strategic location gives it a driving force of opportunities in the Houston-Galveston Region.The guiding principles for this planning process were Hitchcock’s vision statement and its corresponding goals, which were crafted by the task force. The goals focus on factors of growth and development including public participation, development considerations, transportation, community facilities, economic development, parks, and housing and social vulnerabilityTexas Target Communitie

A systematic review evaluating the psychometric properties of measures of social inclusion

Introduction: Improving social inclusion opportunities for population health has been identified as a priority area for international policy. There is a need to comprehensively examine and evaluate the quality of psychometric properties of measures of social inclusion that are used to guide social policy and outcomes. Objective: To conduct a systematic review of the literature on all current measures of social inclusion for any population group, to evaluate the quality of the psychometric properties of identified measures, and to evaluate if they capture the construct of social inclusion. Methods: A systematic search was performed using five electronic databases: CINAHL, PsycINFO, Embase, ERIC and Pubmed and grey literature were sourced to identify measures of social inclusion. The psychometric properties of the social inclusion measures were evaluated against the COSMIN taxonomy of measurement properties using pre-set psychometric criteria. Results: Of the 109 measures identified, twenty-five measures, involving twenty-five studies and one manual met the inclusion criteria. The overall quality of the reviewed measures was variable, with the Social and Community Opportunities Profile-Short, Social Connectedness Scale and the Social Inclusion Scale demonstrating the strongest evidence for sound psychometric quality. The most common domain included in the measures was connectedness (21), followed by participation (19); the domain of citizenship was covered by the least number of measures (10). No single instrument measured all aspects within the three domains of social inclusion. Of the measures with sound psychometric evidence, the Social and Community Opportunities Profile-Short captured the construct of social inclusion best. Conclusions: The overall quality of the psychometric properties demonstrate that the current suite of available instruments for the measurement of social inclusion are promising but need further refinement. There is a need for a universal working definition of social inclusion as an overarching construct for ongoing research in the area of the psychometric properties of social inclusion instruments

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas