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Behavior Therapy Jul 2024Prior research has demonstrated that conducting acquisition in multiple contexts results in more responding to the point that it can even nullify the benefit of...
Prior research has demonstrated that conducting acquisition in multiple contexts results in more responding to the point that it can even nullify the benefit of subsequent extinction in multiple contexts on reducing renewal of excitatory responding. The underlying mechanism to explain why this happens has not been systematically examined. Using self-reported expectancy of the outcome, the current study investigates three mechanisms that potentially explain why acquisition in multiple contexts results in more responding-greater generalization, stronger acquisition learning, or slower extinction learning. Participants (N = 180) received discriminative training with a conditioned stimulus (CS+) and outcome pairing and a CS- → noOutcome pairing in either one or three contexts. This was followed by either extinction treatment in a novel context or no extinction. Finally, testing occurred in the acquisition context, the extinction context, or a novel context. Stronger renewal of extinguished conditioned expectation was observed for participants who received CS+ → Outcome pairings in three contexts relative to one context. There was no effect of the number of contexts on the strength of the excitatory CS+ → Outcome association or degree of inhibitory learning that occurred during extinction. This suggests that generalization is the mechanism responsible for the adverse impact to extinction learning when acquisition is conducted in multiple contexts.
Topics: Humans; Extinction, Psychological; Generalization, Psychological; Male; Female; Young Adult; Conditioning, Classical; Adult; Adolescent; Discrimination Learning
PubMed: 38937046
DOI: 10.1016/j.beth.2023.10.004 -
Diabetes Research and Clinical Practice Jun 2024Type 2 diabetes mellitus (T2DM) is a growing chronic disease that can lead to disability and early death. This study aimed to establish a predictive model for the...
BACKGROUND
Type 2 diabetes mellitus (T2DM) is a growing chronic disease that can lead to disability and early death. This study aimed to establish a predictive model for the 10-year incidence of T2DM based on novel anthropometric indices METHODS: This was a prospective cohort study comparing people with (n = 1256) and without (n = 5193) diabetes mellitus in phase II of the Mashhad Stroke and Heart Atherosclerotic Disorder (MASHAD) study. The association of several anthropometric indices in phase I, including Body Mass Index (BMI), Body Adiposity Index (BAI), Abdominal Volume Index (AVI), Visceral Adiposity Index (VAI), Weight-Adjusted-Waist Index (WWI), Body Roundness Index (BRI), Body Surface Area (BSA), Conicity Index (C-Index) and Lipid Accumulation Product (LAP) with T2DM incidence (in phase II) were examined; using Logistic Regression (LR) and Decision Tree (DT) analysis.
RESULTS
BMI followed by VAI and LAP were the best predictors of T2DM incidence. Participants with BMI < 21.25 kg/m and VAI ≤ 5.9 had a lower chance of diabetes than those with higher BMI and VAI levels (0.033 vs. 0.967 incident rate). For BMI > 25 kg/m, the chance of diabetes rapidly increased (OR = 2.27).
CONCLUSIONS
BMI, VAI, and LAP were the best predictors of T2DM incidence.
PubMed: 38936481
DOI: 10.1016/j.diabres.2024.111755 -
Nurse Education in Practice Jun 2024This study explores and describes the second victim phenomenon in nursing students in association with the characteristics of the clinical learning environment and the...
AIM
This study explores and describes the second victim phenomenon in nursing students in association with the characteristics of the clinical learning environment and the clinical supervision process.
DESIGN
Qualitative design using conventional content analysis and summative content analysis approaches.
METHODS
From September 2022 to July 2023, in-depth semi-structured individual interviews were conducted with a purposive sample of 10 undergraduate nursing students.
RESULTS
Six main themes were developed: 'defining the physical and psychological responses after the most significant patient safety incident', 'analyzing the characteristics of patient safety incidents', 'creating a safe learning environment to provide the best care for patients', 'developing mentorship capabilities and qualities for an ideal follow up of students as a second victim', 'providing resources and integrating support structures to second victim nursing students during their clinical learning', and 'considering the cooperation and coordination between the health institution and the higher education institutions.'
CONCLUSION
Nursing students become second victims during their clinical placement. The clinical learning environment and mentoring characteristics influence the second victim experience.
PubMed: 38936299
DOI: 10.1016/j.nepr.2024.104038 -
Computers in Biology and Medicine Jun 2024Biomedical knowledge graphs (KGs) serve as comprehensive data repositories that contain rich information about nodes and edges, providing modeling capabilities for...
Biomedical knowledge graphs (KGs) serve as comprehensive data repositories that contain rich information about nodes and edges, providing modeling capabilities for complex relationships among biological entities. Many approaches either learn node features through traditional machine learning methods, or leverage graph neural networks (GNNs) to directly learn features of target nodes in the biomedical KGs and utilize them for downstream tasks. Motivated by the pre-training technique in natural language processing (NLP), we propose a framework named PT-KGNN (Pre-Training the biomedical KG with GNNs) to learn embeddings of nodes in a broader context by applying GNNs on the biomedical KG. We design several experiments to evaluate the effectivity of our proposed framework and the impact of the scale of KGs. The results of tasks consistently improve as the scale of the biomedical KG used for pre-training increases. Pre-training on large-scale biomedical KGs significantly enhances the drug-drug interaction (DDI) and drug-disease association (DDA) prediction performance on the independent dataset. The embeddings derived from a larger biomedical KG have demonstrated superior performance compared to those obtained from a smaller KG. By applying pre-training techniques on biomedical KGs, rich semantic and structural information can be learned, leading to enhanced performance on downstream tasks. it is evident that pre-training techniques hold tremendous potential and wide-ranging applications in bioinformatics.
PubMed: 38936076
DOI: 10.1016/j.compbiomed.2024.108768 -
Journal of American College Health : J... Jun 2024The COVID-19 pandemic caused severe disruptions in living and learning to millions of college students. Here we investigated using mediation analysis two dimensions of...
The COVID-19 pandemic caused severe disruptions in living and learning to millions of college students. Here we investigated using mediation analysis two dimensions of anxiety that were specific to the pandemic - COVID-19 related anxiety and COVID-19 vaccine anxiety - to evaluate their relationship to college adjustment during the pandemic. Using cross-sectional survey data across three semester waves (Spring 2021, Fall 2021, and Spring 2022) we probed whether anxiety functioned as a challenge or hindrance stressor on adjustment. We found that although anxiety decreased in both COVID-19 dimensions across semesters, student adjustment to college remained consistently low. Our mediation analysis revealed that both COVID-19 related anxiety and COVID-19 vaccine-related anxiety functioned as challenge stressors, elevating academic, social, personal-emotional, and institutional adjustment during the pandemic. We discuss the role of positive COVID impacts on college adjustment, including enhanced social support.
PubMed: 38935576
DOI: 10.1080/07448481.2024.2362322 -
Optometry and Vision Science : Official... Jun 2024Our retinal image-based deep learning (DL) cardiac biological age (BioAge) model could facilitate fast, accurate, noninvasive screening for cardiovascular disease (CVD)...
SIGNIFICANCE
Our retinal image-based deep learning (DL) cardiac biological age (BioAge) model could facilitate fast, accurate, noninvasive screening for cardiovascular disease (CVD) in novel community settings and thus improve outcome with those with limited access to health care services.
PURPOSE
This study aimed to determine whether the results issued by our DL cardiac BioAge model are consistent with the known trends of CVD risk and the biomarker leukocyte telomere length (LTL), in a cohort of individuals from the UK Biobank.
METHODS
A cross-sectional cohort study was conducted using those individuals in the UK Biobank who had LTL data. These individuals were divided by sex, ranked by LTL, and then grouped into deciles. The retinal images were then presented to the DL model, and individual's cardiac BioAge was determined. Individuals within each LTL decile were then ranked by cardiac BioAge, and the mean of the CVD risk biomarkers in the top and bottom quartiles was compared. The relationship between an individual's cardiac BioAge, the CVD biomarkers, and LTL was determined using traditional correlation statistics.
RESULTS
The DL cardiac BioAge model was able to accurately stratify individuals by the traditional CVD risk biomarkers, and for both males and females, those issued with a cardiac BioAge in the top quartile of their chronological peer group had a significantly higher mean systolic blood pressure, hemoglobin A1c, and 10-year Pooled Cohort Equation CVD risk scores compared with those individuals in the bottom quartile (p<0.001). Cardiac BioAge was associated with LTL shortening for both males and females (males: -0.22, r2 = 0.04; females: -0.18, r2 = 0.03).
CONCLUSIONS
In this cross-sectional cohort study, increasing CVD risk whether assessed by traditional biomarkers, CVD risk scoring, or our DL cardiac BioAge, CVD risk model, was inversely related to LTL. At a population level, our data support the growing body of evidence that suggests LTL shortening is a surrogate marker for increasing CVD risk and that this risk can be captured by our novel DL cardiac BioAge model.
PubMed: 38935034
DOI: 10.1097/OPX.0000000000002158 -
Behavioral Neuroscience Jun 2024In recent years, there have been significant advances in our understanding of the positive symptoms of schizophrenia, such as hallucinations and delusions. This progress... (Review)
Review
In recent years, there have been significant advances in our understanding of the positive symptoms of schizophrenia, such as hallucinations and delusions. This progress has been significantly aided by the use of associative learning-based approaches in human subjects and preclinical animal models. Here, we first review experimental research focusing on the abnormal processing of absent stimuli using three different conditioning phenomena: conditioned hallucinations, mediated conditioning, and trace conditioning. We then review studies investigating the ability to reduce focal processing of physically present but informationally redundant stimuli using habituation, latent inhibition, and blocking. The results of these different lines of research are then summarized within the framework of Wagner's (1981) standard operating procedures model, an associative learning model with explicit reference to the internal representations of both present and absent stimuli. Within this framework, the central deficit associated with positive symptoms can be described as a failure to suppress the focal processing of both absent stimuli and present but irrelevant stimuli. This can explain the wide range of results obtained in different experimental settings. Finally, we briefly discuss the role of the hippocampus and its interaction with dopaminergic transmission in the emergence of such abnormal stimulus representations and learning. Overall, we hope that the theoretical framework and empirical findings offered by the associative learning approach will continue to facilitate and integrate analyses of schizophrenia conducted at the psychological and behavioral levels on the one hand, and at the neural and molecular levels on the other, by serving as a useful interface between them. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Topics: Humans; Association Learning; Schizophrenia; Animals; Psychotic Disorders; Hallucinations; Schizophrenic Psychology; Conditioning, Classical; Hippocampus; Perception
PubMed: 38934921
DOI: 10.1037/bne0000599 -
Journal of Gerontological Social Work Jun 2024This study examined the benefits of an intergenerational home-based service learning program to reduce psychological distress for homebound older adults. Multivariate...
This study examined the benefits of an intergenerational home-based service learning program to reduce psychological distress for homebound older adults. Multivariate regression analyses were conducted with a sample of 182 to examine the association of length of service from the program and presence of caregivers with psychological distress. Findings indicated length of service (β = -0.15, < .05) and having a child as a caregiver (β = -0.14, < .05) were associated with a reduction in psychological distress. Policies and practice can support a pipeline of geriatric health professionals through innovative service learning models to benefit older adults, caregivers, and students.
PubMed: 38934724
DOI: 10.1080/01634372.2024.2373290 -
Telemedicine Journal and E-health : the... Jun 2024Investigate the association between Telemental Health (TMH) uptake and sociodemographic characteristics, and how TMH uptake relates to health care resource utilization...
Investigate the association between Telemental Health (TMH) uptake and sociodemographic characteristics, and how TMH uptake relates to health care resource utilization and Medicaid expenditures among Mississippi Medicaid enrollees with major depression. A retrospective cohort study was conducted (2019-2020), comparing those who utilized TMH and those who did not. Among the 21,239 identified enrollees, 806 (3.79%) utilized TMH. The TMH cohort was more likely to be of older age, non-Hispanic White, comprehensive managed care organization enrollees, rural residents, and from areas with a higher area deprivation index, and have higher Charlson comorbidity index scores. The TMH cohort also exhibited higher mental health-related and all-cause outpatient and emergency department utilization, along with higher Medicaid expenditures. As the first study investigating telehealth utilization among Mississippi Medicaid enrollees, this study highlights sociodemographic disparities in telehealth adoption. Addressing barriers hindering telehealth adoption among vulnerable populations and ensuring the availability of quality data are vital for future research.
PubMed: 38934133
DOI: 10.1089/tmj.2024.0112 -
Alzheimer's & Dementia : the Journal of... Jun 2024Impaired brain protein synthesis, synaptic plasticity, and memory are major hallmarks of Alzheimer's disease (AD). The ketamine metabolite (2R,6R)-hydroxynorketamine...
INTRODUCTION
Impaired brain protein synthesis, synaptic plasticity, and memory are major hallmarks of Alzheimer's disease (AD). The ketamine metabolite (2R,6R)-hydroxynorketamine (HNK) has been shown to modulate protein synthesis, but its effects on memory in AD models remain elusive.
METHODS
We investigated the effects of HNK on hippocampal protein synthesis, long-term potentiation (LTP), and memory in AD mouse models.
RESULTS
HNK activated extracellular signal-regulated kinase 1/2 (ERK1/2), mechanistic target of rapamycin (mTOR), and p70S6 kinase 1 (S6K1)/ribosomal protein S6 signaling pathways. Treatment with HNK rescued hippocampal LTP and memory deficits in amyloid-β oligomers (AβO)-infused mice in an ERK1/2-dependent manner. Treatment with HNK further corrected aberrant transcription, LTP and memory in aged APP/PS1 mice.
DISCUSSION
Our findings demonstrate that HNK induces signaling and transcriptional responses that correct synaptic and memory deficits in AD mice. These results raise the prospect that HNK could serve as a therapeutic approach in AD.
HIGHLIGHTS
The ketamine metabolite HNK activates hippocampal ERK/mTOR/S6 signaling pathways. HNK corrects hippocampal synaptic and memory defects in two mouse models of AD. Rescue of synaptic and memory impairments by HNK depends on ERK signaling. HNK corrects aberrant transcriptional signatures in APP/PS1 mice.
PubMed: 38934107
DOI: 10.1002/alz.14034