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Science Advances Jun 2024Functional deficits in basal ganglia (BG) circuits contribute to cognitive and motor dysfunctions in alcohol use disorder. Chronic alcohol exposure alters synaptic...
Functional deficits in basal ganglia (BG) circuits contribute to cognitive and motor dysfunctions in alcohol use disorder. Chronic alcohol exposure alters synaptic function and neuronal excitability in the dorsal striatum, but it remains unclear how it affects BG output that is mediated by the substantia nigra pars reticulata (SNr). Here, we describe a neuronal subpopulation-specific synaptic organization of striatal and subthalamic (STN) inputs to the medial and lateral SNr. Chronic alcohol exposure (CIE) potentiated dorsolateral striatum (DLS) inputs but did not change dorsomedial striatum and STN inputs to the SNr. Chemogenetic inhibition of DLS direct pathway neurons revealed an enhanced role for DLS direct pathway neurons in execution of an instrumental lever-pressing task. Overall, we reveal a subregion-specific organization of striatal and subthalamic inputs onto the medial and lateral SNr and find that potentiated DLS-SNr inputs are accompanied by altered BG control of action execution following CIE.
Topics: Animals; Neuronal Plasticity; Basal Ganglia; Substantia Nigra; Ethanol; Corpus Striatum; Male; Mice; Neurons; Alcoholism; Neural Pathways
PubMed: 38941461
DOI: 10.1126/sciadv.adm6951 -
Journal of Addiction Medicine Jun 2024To prospectively assess rates of QT prolongation, arrhythmia, syncope, and sudden cardiac death (SCD) in a cohort of people with heroin dependence.
OBJECTIVES
To prospectively assess rates of QT prolongation, arrhythmia, syncope, and sudden cardiac death (SCD) in a cohort of people with heroin dependence.
METHODS
To estimate rates of QT prolongation, arrhythmia, and syncope, a subcohort (n = 130) from the Australian Treatment Outcomes Study, a prospective longitudinal cohort study of 615 people with heroin dependence, underwent medical history, venepuncture, and ECG at the 18- to 20-year follow-up.To estimate rates of SCD, probabilistic matching for the entire cohort was undertaken with the Australian Institute of Health and Welfare National Death Index. Deaths were classified into suicide, accidental overdose, trauma, unknown, and disease, which were then further subclassified by probability of SCD. SCD rate was the number of possible or probable SCDs divided by total patient years from the cohort.
RESULTS
From the subcohort, 4 participants (3%) met the criteria for QT prolongation; 3 were prescribed methadone. Seven participants (5%) reported history of arrhythmia, including 2 transferred from methadone to buprenorphine. Thirty participants (23%) reported a previous syncopal event-14 diagnosed as nonarrhythmic syncope and 13 not investigated. In the previous 12 months, 66 participants (51%) reported heroin use; 55 participants (42%) were prescribed methadone. No participant had QTc greater than 500 milliseconds.There were 3 possible SCDs, translating to an estimated SCD rate of 0.29 (CI: 0.05, 0.8) events per 1000 patient years. More cohort members died of overdose (n = 50), suicide (n = 11), and hepatitis C (n = 4).
CONCLUSIONS
Low rates of QT prolongation, arrhythmia, syncope, and SCD in the cohort despite high rates of heroin use and methadone treatment.
PubMed: 38941157
DOI: 10.1097/ADM.0000000000001317 -
JMIR Medical Informatics Jun 2024The pursuit of groundbreaking health care innovations has led to the convergence of artificial intelligence (AI) and traditional Chinese medicine (TCM), thus marking a...
The pursuit of groundbreaking health care innovations has led to the convergence of artificial intelligence (AI) and traditional Chinese medicine (TCM), thus marking a new frontier that demonstrates the promise of combining the advantages of ancient healing practices with cutting-edge advancements in modern technology. TCM, which is a holistic medical system with >2000 years of empirical support, uses unique diagnostic methods such as inspection, auscultation and olfaction, inquiry, and palpation. AI is the simulation of human intelligence processes by machines, especially via computer systems. TCM is experience oriented, holistic, and subjective, and its combination with AI has beneficial effects, which presumably arises from the perspectives of diagnostic accuracy, treatment efficacy, and prognostic veracity. The role of AI in TCM is highlighted by its use in diagnostics, with machine learning enhancing the precision of treatment through complex pattern recognition. This is exemplified by the greater accuracy of TCM syndrome differentiation via tongue images that are analyzed by AI. However, integrating AI into TCM also presents multifaceted challenges, such as data quality and ethical issues; thus, a unified strategy, such as the use of standardized data sets, is required to improve AI understanding and application of TCM principles. The evolution of TCM through the integration of AI is a key factor for elucidating new horizons in health care. As research continues to evolve, it is imperative that technologists and TCM practitioners collaborate to drive innovative solutions that push the boundaries of medical science and honor the profound legacy of TCM. We can chart a future course wherein AI-augmented TCM practices contribute to more systematic, effective, and accessible health care systems for all individuals.
PubMed: 38941141
DOI: 10.2196/58491 -
JAMA Network Open Jun 2024
Topics: Humans; Opioid-Related Disorders; Primary Health Care; Health Knowledge, Attitudes, Practice; Female; Male; Adult; Middle Aged; Analgesics, Opioid; Cross-Sectional Studies; Surveys and Questionnaires
PubMed: 38941101
DOI: 10.1001/jamanetworkopen.2024.19094 -
The International Journal of Eating... Jun 2024Pediatric loss-of-control (LOC) eating is associated with high BMI and predicts binge-eating disorder and obesity onset with age. Research on the etiology of this common...
OBJECTIVE
Pediatric loss-of-control (LOC) eating is associated with high BMI and predicts binge-eating disorder and obesity onset with age. Research on the etiology of this common comorbidity has not explored the potential for shared genetic risk. This study examined genetic and environmental influences on LOC eating and its shared influence with BMI.
METHOD
Participants were 499 monozygotic and 398 same-sex dizygotic twins (age = 17.38 years ± 0.67, BMIz = 0.03 ± 1.03, 54% female) from the Colorado Center for Antisocial Drug Dependence Study. LOC eating was assessed dichotomously. Self-reported height and weight were converted to BMIz. Univariate and bivariate twin models estimated genetic and environmental influences on LOC eating and BMIz.
RESULTS
More girls (21%) than boys (9%, p < 0.001) reported LOC eating. The phenotypic correlation with BMIz was 0.03 in girls and 0.18 in boys. Due to the nonsignificant phenotypic correlation in girls, bivariate twin models were fit in boys only. Across all models, the best-fitting model included genetic and unique environmental effects. Genetic factors accounted for 0.51 (95% CI: 0.23, 0.73) of the variance of LOC eating in girls and 0.54 (0.18, 0.90) in boys. The genetic correlation between LOC eating and BMIz in boys was 0.45 (0.15, 0.75).
DISCUSSION
Findings indicate moderate heritability of LOC eating in adolescence, while emphasizing the role of unique environmental factors. In boys, LOC eating and BMIz share a proportion of their genetic influences.
PubMed: 38940253
DOI: 10.1002/eat.24245 -
Bioinformatics (Oxford, England) Jun 2024In drug discovery, it is crucial to assess the drug-target binding affinity (DTA). Although molecular docking is widely used, computational efficiency limits its...
MOTIVATION
In drug discovery, it is crucial to assess the drug-target binding affinity (DTA). Although molecular docking is widely used, computational efficiency limits its application in large-scale virtual screening. Deep learning-based methods learn virtual scoring functions from labeled datasets and can quickly predict affinity. However, there are three limitations. First, existing methods only consider the atom-bond graph or one-dimensional sequence representations of compounds, ignoring the information about functional groups (pharmacophores) with specific biological activities. Second, relying on limited labeled datasets fails to learn comprehensive embedding representations of compounds and proteins, resulting in poor generalization performance in complex scenarios. Third, existing feature fusion methods cannot adequately capture contextual interaction information.
RESULTS
Therefore, we propose a novel DTA prediction method named HeteroDTA. Specifically, a multi-view compound feature extraction module is constructed to model the atom-bond graph and pharmacophore graph. The residue concat graph and protein sequence are also utilized to model protein structure and function. Moreover, to enhance the generalization capability and reduce the dependence on task-specific labeled data, pre-trained models are utilized to initialize the atomic features of the compounds and the embedding representations of the protein sequence. A context-aware nonlinear feature fusion method is also proposed to learn interaction patterns between compounds and proteins. Experimental results on public benchmark datasets show that HeteroDTA significantly outperforms existing methods. In addition, HeteroDTA shows excellent generalization performance in cold-start experiments and superiority in the representation learning ability of drug-target pairs. Finally, the effectiveness of HeteroDTA is demonstrated in a real-world drug discovery study.
AVAILABILITY AND IMPLEMENTATION
The source code and data are available at https://github.com/daydayupzzl/HeteroDTA.
Topics: Drug Discovery; Molecular Docking Simulation; Proteins; Deep Learning; Pharmacophore
PubMed: 38940179
DOI: 10.1093/bioinformatics/btae240 -
Frontiers in Bioscience (Landmark... Jun 2024
Review
Topics: Humans; Cocaine-Related Disorders; Gastrointestinal Microbiome; Cocaine; Animals; Yin-Yang
PubMed: 38940056
DOI: 10.31083/j.fbl2906215 -
Alcohol and Alcoholism (Oxford,... May 2024Alcohol use disorder poses a significant global health threat, with profound consequences for individuals, families, and communities, necessitating continued exploration...
Alcohol use disorder poses a significant global health threat, with profound consequences for individuals, families, and communities, necessitating continued exploration of novel treatment approaches. Acceptance and Commitment Therapy, an evidence-based approach for various mental health disorders, offers promise in addressing alcohol use disorder as well, but controlled trials are lacking, highlighting a crucial gap in research.
Topics: Humans; Acceptance and Commitment Therapy; Alcoholism
PubMed: 38938218
DOI: 10.1093/alcalc/agae042 -
The American Journal of Case Reports Jun 2024BACKGROUND Ethanol intoxication is very common, and several forms of alcohol intoxication can lead to emergency department visits. Excessive alcohol users, when in...
BACKGROUND Ethanol intoxication is very common, and several forms of alcohol intoxication can lead to emergency department visits. Excessive alcohol users, when in withdrawal, might seek replacement alcoholic beverages; one of the common sources of ethanol is hand sanitizer, which contains 45-95% alcohol. It becomes even more challenging to deal with alcohol use disorder patients when they seek these replacement products inside hospital premises, and medical clinics and hospitals have increased their use of ethanol-based hand sanitizer since the start of the COVID-19 pandemic. CASE REPORT We report the case of a 26-year-old man with alcohol dependence presenting with a fictitious illness leading to hospital admission and consumption of ethanol-based hand sanitizer in the emergency department (ED). The patient initially presented reporting severe abdominal pain that persisted despite medications. The initial laboratory tests and imaging were non-significant. The patient was later caught stealing hand sanitizer bottles, consuming them within 4-6 h. The COVID-19 pandemic has increased alcohol intoxication, especially in EDs. Hand sanitizers, including ethanol, are toxic and hazardous when misused, mostly by adolescents and young adults. Treatments include glucose determination, dextrose infusion, and thiamine perfusion. Strategies to reduce ethanol intoxication include eliminating hand sanitizers, using wall-fixed sanitizers, and using sanitizer wipes. CONCLUSIONS Patients with alcohol use disorder are known to develop alcohol-seeking behaviors. This report has highlighted that healthcare professionals should be aware that the increased availability of ethanol-based hand sanitizers, some of which contain toxic antiviral chemical agents, may be targeted by individuals with alcohol dependency.
Topics: Humans; Male; Adult; Hand Sanitizers; Alcoholic Intoxication; COVID-19; Ethanol; Alcoholism; Emergency Service, Hospital; SARS-CoV-2
PubMed: 38937952
DOI: 10.12659/AJCR.943318 -
Systematic Reviews Jun 2024The steep rise in substance use and substance use disorder (SUD) shows an urgency to assess its prevalence using valid measures. This systematic review summarizes the... (Review)
Review
BACKGROUND
The steep rise in substance use and substance use disorder (SUD) shows an urgency to assess its prevalence using valid measures. This systematic review summarizes the validity of measures to assess the prevalence of substance use and SUD in the US estimated in population and sub-population-based surveys.
METHODS
A literature search was performed using nine online databases. Studies were included in the review if they were published in English and tested the validity of substance use and SUD measures among US adults at the general or sub-population level. Independent reviews were conducted by the authors to complete data synthesis and assess the risk of bias.
RESULTS
Overall, 46 studies validating substance use/SUD (n = 46) measures were included in this review, in which 63% were conducted in clinical settings and 89% assessed the validity of SUD measures. Among the studies that assessed SUD screening measures, 78% examined a generic SUD measure, and the rest screened for specific disorders. Almost every study used a different survey measure. Overall, sensitivity and specificity tests were conducted in over a third of the studies for validation, and 10 studies used receiver operating characteristics curve.
CONCLUSION
Findings suggest a lack of standardized methods in surveys measuring and reporting prevalence of substance use/SUD among US adults. It highlights a critical need to develop short measures for assessing SUD that do not require lengthy, time-consuming data collection that would be difficult to incorporate into population-based surveys assessing a multitude of health dimensions.
SYSTEMATIC REVIEW REGISTRATION
PROSPERO CRD42022298280.
Topics: Humans; Substance-Related Disorders; United States; Reproducibility of Results; Prevalence; Health Surveys; Surveys and Questionnaires; Sensitivity and Specificity
PubMed: 38937847
DOI: 10.1186/s13643-024-02536-x