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Escherichia coli O157:H7 is estimated to cause [approximately equal to] 63,000 domestically acquired foodborne illnesses and 20 deaths in the United States each year (1). E. coli O157:H7 infections are [...]

A key aim of systems biology is the reconstruction of molecular networks. We do not yet, however, have networks that integrate information from all datasets available for a particular clinical condition. This is in part due to the limited scalability, in terms of required computational time and power, of existing algorithms. Network reconstruction methods should also be scalable in the sense of allowing scientists from different backgrounds to efficiently integrate additional data. We present a network model of acute myeloid leukemia (AML). In the current version (AML 2.1), we have used gene expression data (both microarray and RNA-seq) from 5 different studies comprising a total of 771 AML samples and a protein-protein interactions dataset. Our scalable network reconstruction method is in part based on the well-known property of gene expression correlation among interacting molecules. The difficulty of distinguishing between direct and indirect interactions is addressed by optimizing the coefficient of variation of gene expression, using a validated gold-standard dataset of direct interactions. Computational time is much reduced compared to other network reconstruction methods. A key feature is the study of the reproducibility of interactions found in independent clinical datasets. An analysis of the most significant clusters, and of the network properties (intraset efficiency, degree, betweenness centrality, and PageRank) of common AML mutations demonstrated the biological significance of the network. A statistical analysis of the response of blast cells from 11 AML patients to a library of kinase inhibitors provided an experimental validation of the network. A combination of network and experimental data identified CDK1, CDK2, CDK4, and CDK6 and other kinases as potential therapeutic targets in AML.

This article responds to the need to synthesize theory and research in educational psychology by introducing the Thriving with Social Purpose (TSP) conceptual framework. TSP results when the four components of human motivation--goals, capability beliefs, context beliefs, and emotions--are amplified in dynamic, mutually reinforcing patterns. The centerpiece of the TSP motivational pattern is an active approach goal orientation informed by a fundamental concern for others (social purpose). This orientation is supported and strengthened by a firm belief in one's ability to make progress toward meaningful goals (personal optimism), a persistent tendency to imagine alternative pathways when progress is challenged (mindful tenacity), and intentional efforts to align emotions and circumstances in ways that will best facilitate goal progress (emotional wisdom). The TSP framework also emphasizes positive (discrepancy increasing) feedback cycles that accelerate learning and competence development, facilitate meaningful change, and promote personal and social well-being.

The scale of influence of hydrological and thermal conditions on disease remains uncertain for most wild plant pathosystems, thus restricting our ability to predict the impacts of climate change. Analysis of the spatiotemporal spread of a fungal rust pathogen throughout four naturally occurring flax populations over the course of five growing seasons reveals relationships between epidemic magnitude and snow cover, relative humidity and temperature, as well as an unexpectedly significant effect of severe drought on disease progression. These results indicate that climate change will likely disrupt wild plant epidemics, and points to a need for further epidemiological studies characterizing the effects of environmental conditions on population‐level disease dynamics in natural pathosystems. [ABSTRACT FROM AUTHOR]

Cronobacter sakazakii, a species of gram-negative bacteria belonging to the Enterobacteriaceae family, is known to cause severe and often fatal meningitis and sepsis in young infants. C. sakazakii is ubiquitous in the environment, and most reported infant cases have been attributed to contaminated powdered infant formula (powdered formula) or breast milk that was expressed using contaminated breast pump equipment (1-3). Previous investigations of cases and outbreaks have identified C. sakazakii in opened powdered formula, breast pump parts, environmental surfaces in the home, and, rarely, in unopened powdered formula and formula manufacturing facilities (2,4-6). This report describes two infants with C. sakazakii meningitis reported to CDC in September 2021 and February 2022. CDC used whole genome sequencing (WGS) analysis to link one case to contaminated opened powdered formula from the patient's home and the other to contaminated breast pump equipment. These cases highlight the importance of expanding awareness about C. sakazakii infections in infants, safe preparation and storage of powdered formula, proper cleaning and sanitizing of breast pump equipment, and using WGS as a tool for C. sakazakii investigations., Competing Interests: All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. No potential conflicts of interest were disclosed.