The influence of therapy quality on outcomes from behavioural activation and guided self-help treatments for depression in adults with intellectual disabilities.

Objectives: We report the effect of quality of therapy delivery on outcomes in a randomized, controlled trial of behavioural activation (BA) and guided self-help (GSH) for depression in adults with intellectual disabilities.

Methods: A study specific measure of quality was used in a linear mixed effect model to determine the effects therapy and therapy quality on therapy outcome.

Results: There was a significant interaction between quality and treatment type, with lower quality therapy associated with better outcome for GSH but poorer outcome for BA, with little difference in outcomes at higher levels of therapy quality.

Vehicle choice modeling for emerging zero-emission light-duty vehicle markets in California.

To predict the market dynamics of various zero-emission vehicle (ZEV) technologies, this study introduces a dynamic discrete vehicle choice model (VCM) that investigates the probabilities associated with 14 decision factors, applying these to the purchase of ZEVs from 2020 to 2040. Market share and penetration results are presented under eight scenarios, that vary by vehicle costs infrastructure development and incentive strategies. The findings suggest that in the early years, incentives alone may not generate significant market penetration of ZEVs before the infrastructure meets the basic convenience for daily use, especially for fuel cell vehicles (FCVs).

The effect of COVID-19 on cancer incidences in the U.S.

Fundamental data analysis assists in the evaluation of critical questions to discern essential facts and elicit formerly invisible evidence. In this article, we provide clarity into a subtle phenomenon observed in cancer incidences throughout the time of the COVID-19 pandemic. We analyzed the cancer incidence data from the American Cancer Society [1].

Effects of Internal and External Factors on Hospital Data Breaches: Quantitative Study.

Background: Health care data breaches are the most rapidly increasing type of cybercrime; however, the predictors of health care data breaches are uncertain.

Objective: This quantitative study aims to develop a predictive model to explain the number of hospital data breaches at the county level.

Methods: This study evaluated data consolidated at the county level from 1032 short-term acute care hospitals.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages.

Breast cancer is a heterogeneous disease, and treatment is guided by biomarker profiles representing distinct molecular subtypes. Breast cancer arises from the breast ductal epithelium, and experimental data suggests breast cancer subtypes have different cells of origin within that lineage. The precise cells of origin for each subtype and the transcriptional networks that characterize these tumor-normal lineages are not established.

The Health Status of the US Veterans: A Longitudinal Analysis of Surveillance Data Prior to and during the COVID-19 Pandemic.

Chronic diseases affect a disproportionate number of United States (US) veterans, causing significant long-term health issues and affecting entitlement spending. This longitudinal study examined the health status of US veterans as compared to non-veterans pre- and post-COVID-19, utilizing the annual Center for Disease Control and Prevention (CDC) behavioral risk factor surveillance system (BRFSS) survey data. Age-adjusted descriptive point estimates were generated independently for 2003 through 2021, while complex weighted panel data were generated from 2011 and onward.

Predictors and moderators of the response of adults with intellectual disabilities and depression to behavioural activation and guided self-help therapies.

Background: No previous studies have reported predictors and moderators of outcome of psychological therapies for depression experienced by adults with intellectual disabilities (IDs). We investigated baseline variables as outcome predictors and moderators based on a randomised controlled trial where behavioural activation was compared with guided self-help.

Methods: This study was an exploratory secondary data analysis of data collected during a randomised clinical trial.

An Exploratory Analysis of the Association Between Hospital Labor Costs and the Quality of Care.

Introduction: The competent healing touch of a caregiver is a critical component to the care patients receive. The more skilled the provider, the higher the likelihood outcomes will be delivered in a safe and effective manner. Unfortunately, in recent years, hospitals in the United States have faced immense financial pressures that are threatening their economic sustainability and patients' access to care in the future.

Understanding the role of coalescence in social justice leadership development.

This article highlights the important role of coalescence in preparing leaders to engage in a diverse society. The authors draw on intersectional and critical frames to understand coalescence. Using supporting data from a study on BIPOC student leaders, the authors demonstrate the ways in which students build capacity for coalescence and recommend strategies to cultivate environments that promote this work.

The Predictive Factors of Hospital Bankruptcy-An Exploratory Study.

The United States healthcare industry has witnessed a number of hospitals declare bankruptcy. This has a meaningful impact on local communities with vast implications on access, cost, and quality of care available. In our research, we seek to determine what contemporary structural and operational factors influence a bankruptcy outcome, and craft predictive models to guide healthcare leaders on how to best avoid bankruptcy in the future.

Semi-automated assembly of high-quality diploid human reference genomes.

The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted society. However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individuals. Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genome.

Spatially restricted drivers and transitional cell populations cooperate with the microenvironment in untreated and chemo-resistant pancreatic cancer.

Pancreatic ductal adenocarcinoma is a lethal disease with limited treatment options and poor survival. We studied 83 spatial samples from 31 patients (11 treatment-naïve and 20 treated) using single-cell/nucleus RNA sequencing, bulk-proteogenomics, spatial transcriptomics and cellular imaging. Subpopulations of tumor cells exhibited signatures of proliferation, KRAS signaling, cell stress and epithelial-to-mesenchymal transition.

Allogeneic peripheral blood haematopoietic stem cell transplantation for the treatment of dogs with high-grade B-cell lymphoma.

Autologous peripheral blood haematopoietic stem cell transplantation (HCT) cures 33%-40% of dogs with high-grade B-cell lymphoma. We hypothesized, based on human allogeneic bone marrow transplantation literature, that transplanting dogs using canine donor leukocyte-matched CD34+ cells would lead to fewer relapses and increased cure rates. We retrospectively reviewed medical records of dogs diagnosed with high-grade B-cell lymphoma who received an identical allogeneic HCT.

Geospatial analysis as a tool to identify target areas for Chagas disease education for healthcare providers.

Chagas Disease (CD) is a neglected zoonotic disease of the Americas. It can be fatal if not diagnosed and treated in its early stages. Using geospatial and sensitivity analysis, this study focuses on understanding how to better allocate resources and educational information to areas in the United States, specifically Texas, that have the potential for increased risk of CD cases and the associated costs of addressing the disease.

Quantification and characterization of plastics in near-shore surface waters of Atlantic Canada.

Plastics are a ubiquitous pollutant in the marine environment. Despite growing concerns, quantitative and qualitative data on microplastics in aquatic and marine environments of Atlantic Canada is just emerging. Surface water plastics were measured and categorized by morphology (thread, microfibre, fragment, foam, film, pellet, and microbead) in two locations in Nova Scotia and one in Newfoundland and Labrador, Canada.

Testing Kissick's Iron Triangle-Structural Equation Modeling Analysis of a Practical Theory.

Background/purpose: The purpose of this research is to determine if the tradeoffs that Kissick proposed among cost containment, quality, and access remain as rigidly interconnected as originally conceived in the contemporary health care context. Although many have relied on the Kissick model to advocate for health policy decisions, to our knowledge the model has never been empirically tested. Some have called for policy makers to come to terms with the premise of the Kissick model tradeoffs, while others have questioned the model, given the proliferation of quality-enhancing initiatives, automation, and information technology in the health care industry.

College students' willingness to accept COVID-19 vaccines.

To assess college students' willingness to accept COVID-19 vaccines and the factors that influence their decisions. Traditional (aged 18-23) undergraduate students at a university in central Texas. An online survey was administered in fall 2020 to 614 students stratified by sex and race/ethnicity.

Deep Vision for Breast Cancer Classification and Segmentation.

(1) Background: Female breast cancer diagnoses odds have increased from 11:1 in 1975 to 8:1 today. Mammography false positive rates (FPR) are associated with overdiagnoses and overtreatment, while false negative rates (FNR) increase morbidity and mortality. (2) Methods: Deep vision supervised learning classifies 299 × 299 pixel de-noised mammography images as negative or non-negative using models built on 55,890 pre-processed training images and applied to 15,364 unseen test images.

Examining Predictors of Myocardial Infarction.

Cardiovascular diseases are the leading cause of death in the United States. This study analyzed predictors of myocardial infarction (MI) for those aged 35 and older based on demographic, socioeconomic, geographic, behavioral, and risk factors, as well as access to healthcare variables using the Center for Disease (CDC) Control Behavioral Risk Factor Surveillance System (BRFSS) survey for the year 2019. Multiple quasibinomial models were generated on an 80% training set hierarchically and then used to forecast the 20% test set.

Search for Lepton Number and Flavor Violation in K^{+} and π^{0} Decays.

Searches for the lepton number violating K^{+}→π^{-}μ^{+}e^{+} decay and the lepton flavor violating K^{+}→π^{+}μ^{-}e^{+} and π^{0}→μ^{-}e^{+} decays are reported using data collected by the NA62 experiment at CERN in 2017-2018. No evidence for these decays is found and upper limits of the branching ratios are obtained at 90% confidence level: B(K^{+}→π^{-}μ^{+}e^{+})<4.2×10^{-11}, B(K^{+}→π^{+}μ^{-}e^{+})<6.

Genomic Profiling of Lung Adenocarcinoma in Never-Smokers.

Purpose: Approximately 10%-40% of patients with lung cancer report no history of tobacco smoking (never-smokers). We analyzed whole-exome and RNA-sequencing data of 160 tumor and normal lung adenocarcinoma (LUAD) samples from never-smokers to identify clinically actionable alterations and gain insight into the environmental and hereditary risk factors for LUAD among never-smokers.

Methods: We performed whole-exome and RNA-sequencing of 88 and 69 never-smoker LUADs.