More Guidance, Better Results? Three-Year Effects of an Enhanced Student Services Program at Two Community Colleges

In a program at Lorain County Community College and Owens Community College in Ohio, low-income students received enhanced counseling and advising services and were eligible to receive a modest stipend for two semesters. The program improved academic outcomes during the second semester and continued to have a positive effect on registration rates in the semester that followed, but it did not have any meaningful effects on academic outcomes in subsequent semesters

Testing the Integrated Theory of Health Behaviour Change for Postpartum Weight Management

Aim.  This is a report of a correlational study to test the Integrated Theory of Health Behaviour Change within the context of postpartum weight self‐management including the impact of race/ethnicity and weight classification. Background.  Women experiencing childbirth face increasing challenges to manage their weight postpartum. Little is known about women’s weight self‐management during the complex physiological and psychosocial transition of the postpartum period. Methods.  Data were collected during the birth hospitalization and 4 months postbirth during 2005 and 2006. A quota sample of 250 postpartum women using two strata, race/ethnicity and prepregnant weight classification, were enrolled; 179 women completed the follow‐up survey. A survey questionnaire measured concepts from the Integrated Theory of Health Behaviour Change concepts, including knowledge and beliefs (self‐efficacy, outcome expectancy and goal congruence), self‐regulation skills and abilities, and social facilitation (social support and social influence) and the proximal outcome of weight retention. Factor analysis identified 5 factors consistent with the theoretical concepts that accounted for 47·1% of total survey variance. Results.  Model testing using path analysis explored the relationship among factors. The final model explained 25·7% of the variance in self regulation at 4 months, but did not explain weight retention. The contribution of select concepts to total variance was different for Caucasian and African American women, but not by weight classification. Conclusions.  Findings support use of theoretical concepts and relationships to understand postpartum weight self‐management. The different relationships among concepts in Caucasian and African American women should be considered in planning targeted postpartum weight self‐management interventions

Leadership considerations for executive vice chairs, new chairs, and chairs in the 21st century.

The need to fulfill academic goals in the context of significant economic challenges, new regulatory requirements, and ever-changing expectations for leadership requires continuous adaptation. This paper serves as an educational resource for emerging leaders from the literature, national leaders, and other “best practices” in the following domains: 1. Mentorship; 2. Faculty Development; 3. Promotion; 4. Demonstrating value in each of the academic missions; 5. Marketing and communications; and 6. Barrier

A Policy Analysis of the Federal Growth Model Pilot Program\u27s Measures of School Performance: The Florida Case

As test-based educational accountability has moved to the forefront of national and state education policy, so has the desire for better measures of school performance. No Child Left Behind\u27s (NCLB) status and safe harbor measures have been criticized for being unfair and unreliable, respectively. In response to such criticism, in 2005 the federal government announced the Growth Model Pilot Program, which permits states to use projection models (a type of growth model) in their accountability systems. This article uses historical longitudinal data from a large school district to empirically show the inaccuracy of one state\u27s projection model, to demonstrate how projection models are very similar to NCLB\u27s original status measure, and to contrast projection models with value-added models. As policy makers debate the reauthorization of NCLB, this research can provide guidance on ways to improve the current measurement of school performance

Development, Survival and Phenology of the Sweetclover Weevil Parasitoid, \u3ci\u3ePygostolus Falcatus\u3c/i\u3e (Hymenoptera: Braconidae)

Biennial sweetclovers were widely used for soil improvement and as for- ages in the first half of the 1900s. The introduction of the sweetclover weevil, Sitona cylindricollis, caused a drastic decline in sweetclover acreage. In North Dakota, yellow sweetclover, Melilotus officinalis, is still the legume of choice on organic farms. In an effort to control the weevil, the thelyotokous parasitoid Pygostolus falcatus was imported. Parasitoids were studied for temperature-dependent development, and adult longevity as influenced by temperature and availability of provisions. Development from egg to adult at 15, 20, 25 and 30°C was 58, 28, 22 and 21 d, respectively. No parasitoids were reared out at 10°C, although diapausing first instars were present. Longevity of adult parasitoids provided honey, water, sweetclover and sweet- clover weevils at 15, 20, 25 and 30°C was 29, 22, 12 and 6 d, respectively. Adults provided the following combinations of provisions at 25°C survived for: nothing-2 d; water-2 d; honey-4 d; honey and water - 6 d; honey, water and sweetclover - 11 d; honey, water, sweetclover and hosts - 12 d. Field cage releases and a degree-day model developed for the parasitoid demonstrated that poor synchrony between P. falcatus and the sweetclover weevil hinders its usefulness as a biological control agent

Therapeutic targeting of ALS pathways: refocusing an incomplete picture

© 2023 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.Numerous potential amyotrophic lateral sclerosis (ALS)-relevant pathways have been hypothesized and studied preclinically, with subsequent translation to clinical trial. However, few successes have been observed with only modest effects. Along with an improved but incomplete understanding of ALS as a neurodegenerative disease is the evolution of more sophisticated and diverse in vitro and in vivo preclinical modeling platforms, as well as clinical trial designs. We highlight proposed pathological pathways that have been major therapeutic targets for investigational compounds. It is likely that the failures of so many of these therapeutic compounds may not have occurred because of lack of efficacy but rather because of a lack of preclinical modeling that would help define an appropriate disease pathway, as well as a failure to establish target engagement. These challenges are compounded by shortcomings in clinical trial design, including lack of biomarkers that could predict clinical success and studies that are underpowered. Although research investments have provided abundant insights into new ALS-relevant pathways, most have not yet been developed more fully to result in clinical study. In this review, we detail some of the important, well-established pathways, the therapeutics targeting them, and the subsequent clinical design. With an understanding of some of the shortcomings in translational efforts over the last three decades of ALS investigation, we propose that scientists and clinicians may choose to revisit some of these therapeutic pathways reviewed here with an eye toward improving preclinical modeling, biomarker development, and the investment in more sophisticated clinical trial designs.Research funding: Cytokinetics National Institutes of Health, USA. Grant Number: 5R01NS117604-03info:eu-repo/semantics/publishedVersio

CGBayesNets: Conditional Gaussian Bayesian Network Learning and Inference with Mixed Discrete and Continuous Data

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com