The Role of the Cerebellum in Drug Reward: A Review.

Drug abuse remains a global problem; nonetheless, its mechanism has not yet been fully understood. Recent studies have reported on the non-motor functions of the cerebellum, and evidence from neuroimaging and behavioral studies has suggested the role of cerebellum in drug reward, which has received increasing attention. Furthermore, emerging technological developments have aided in clarifying the various circuits and functions of the cerebellum. Exploring the role of the cerebellum in drug reward can improve our understanding of the mechanism underlying addiction and facilitate the development of new treatment schemes. This review summarizes the anatomy of the cerebellum and its connections to brain regions considered important in addiction. Subsequently, we investigate the neurological reasons elucidating why the cerebellum is a potential target for drug reward. Additionally, we expound the molecular targets of addictive drugs in the cerebellum, mainly glutamate and endocannabinoids. Unlike previous studies, this article focuses on the influence of alcohol, nicotine, morphine, cannabis, and cocaine on the cerebellum from multiple viewpoints, including imaging and behavioral changes, molecular signals, neurotransmitters, and synaptic transmission. We aim to clarify some drug-induced cerebellar changes to supplement the previous research regarding the relationship between addiction and the cerebellum. Finally, we discuss the limitations and prospects of drug reward research on the cerebellum to provide novel insights into studying the cerebellum and its role in addiction. We recommend that future addiction network models should include the cerebellum to provide new therapeutic targets for treating addiction.

The Application of Computer Technology to Clinical Practice Guideline Implementation: A Scoping Review.

Implementation of clinical practice guidelines (CPG) is a complex and challenging task. Computer technology, including artificial intelligence (AI), has been explored to promote the CPG implementation. This study has reviewed the main domains where computer technology and AI has been applied to CPG implementation. PubMed, Embase, Web of science, the Cochrane Library, China National Knowledge Infrastructure database, WanFang DATA, VIP database, and China Biology Medicine disc database were searched from inception to December 2021. Studies involving the utilization of computer technology and AI to promote the implementation of CPGs were eligible for review. A total of 10429 published articles were identified, 117 met the inclusion criteria. 21 (17.9%) focused on the utilization of AI techniques to classify or extract the relative content of CPGs, such as recommendation sentence, condition-action sentences. 47 (40.2%) focused on the utilization of computer technology to represent guideline knowledge to make it understandable by computer. 15 (12.8%) focused on the utilization of AI techniques to verify the relative content of CPGs, such as conciliation of multiple single-disease guidelines for comorbid patients. 34 (29.1%) focused on the utilization of AI techniques to integrate guideline knowledge into different resources, such as clinical decision support systems. We conclude that the application of computer technology and AI to CPG implementation mainly concentrated on the guideline content classification and extraction, guideline knowledge representation, guideline knowledge verification, and guideline knowledge integration. The AI methods used for guideline content classification and extraction were pattern-based algorithm and machine learning. In guideline knowledge representation, guideline knowledge verification, and guideline knowledge integration, computer techniques of knowledge representation were the most used.

Causal association between major depressive disorder and venous thromboembolism: a bidirectional mendelian randomization study.

Purpose: Major depressive disorder (MDD) and venous thromboembolism (VTE) may be linked in observational studies. However, the causal association remains ambiguous. Therefore, this study investigates the causal associations between them. Methods: We performed a two-sample univariable and multivariable bidirectional Mendelian randomization (MR) analysis to evaluate the associations between MDD and VTE. The summary genetic associations of MDD statistics were obtained from the Psychiatric Genomics Consortium and UK Biobank. Information on VTE, deep vein thrombosis (DVT), and pulmonary embolism (PE) were obtained from the FinnGen Biobank. Inverse-variance weighting was used as the main analysis method. Other methods include weighted median, MR-Egger, Simple mode, and Weighted mode. Results: Univariable MR analysis revealed no significant associations between MDD and VTE risk (odds ratio (OR): 0.936, 95% confidence interval (CI): 0.736-1.190, p = 0.590); however, after adjusting the potential relevant polymorphisms of body mass index and education, the multivariable MR analysis showed suggestive evidence of association between them (OR: 1.163, 95% CI: 1.004-1.346, p = 0.044). Univariable MR analysis also revealed significant associations between MDD and PE risk (OR: 1.310, 95% CI: 1.073-1.598, p = 0.008), but the association between them was no longer significant in MVMR analysis (p = 0.072). We found no significant causal effects between MDD and DVT risk in univariable or multivariable MR analyses. There was also no clear evidence showing the causal effects between VTE, PE, or DVT and MDD risk. Conclusion: We provide suggestive genetic evidence to support the causal association between MDD and VTE risk. No causal associations were observed between VTE, PE, or DVT and MDD risk. Further validation of these associations and investigations of potential mechanisms are required.

N-palmitoylethanolamide attenuates negative emotions induced by morphine withdrawal in mice.

Depression and anxiety are prominent symptoms of withdrawal syndrome, often caused by the abuse of addictive drugs like morphine. N-palmitoylethanolamide (PEA), a biologically active lipid, is utilized as an anti-inflammatory and analgesic medication. Recent studies have highlighted PEA's role in mitigating cognitive decline and easing depression resulting from chronic pain. However, it remains unknown whether PEA can influence negative emotions triggered by morphine withdrawal. This study seeks to explore the impact of PEA on such emotions and investigate the underlying mechanisms. Mice subjected to morphine treatment underwent a 10-day withdrawal period, followed by assessments of the effect of PEA on anxiety- and depression-like behaviors using various tests. Enzyme-linked immunosorbent assay was conducted to measure levels of monoamine neurotransmitters in specific brain regions. The findings indicate that PEA mitigated anxiety and depression symptoms and reduced 5-hydroxytryptamine, noradrenaline, and dopamine levels in the hippocampus and prefrontal cortex. In summary, PEA demonstrates a significant positive effect on negative emotions associated with morphine withdrawal, accompanied with the reduction in levels of monoamine neurotransmitters in key brain regions. These insights could be valuable for managing negative emotions arising from morphine withdrawal.

Clinical biomarker-based biological aging and risk of benign prostatic hyperplasia: A large prospective cohort study.

Objective: Chronological age (CAge), biological age (BAge), and accelerated age (AAge) are all important for aging-related diseases. CAge is a known risk factor for benign prostatic hyperplasia (BPH); However, the evidence of association of BAge and AAge with BPH is limited. This study aimed to evaluate the association of CAge, Bage, and AAge with BPH in a large prospective cohort. Method: A total of 135,933 males without BPH at enrolment were extracted from the UK biobank. We calculated three BAge measures (Klemera-Doubal method, KDM; PhenoAge; homeostatic dysregulation, HD) based on 16 biomarkers. Additionally, we calculated KDM-BAge and PhenoAge-BAge measures based on the Levine method. The KDM-AAge and PhenoAge-AAge were assessed by the difference between CAge and BAge and were standardized (mean = 0 and standard deviation [SD] = 1). Cox proportional hazard models were applied to assess the associations of CAge, Bage, and AAge with incident BPH risk. Results: During a median follow-up of 13.150 years, 11,811 (8.690%) incident BPH were identified. Advanced CAge and BAge measures were associated with an increased risk of BPH, showing threshold effects at a later age (all P for nonlinearity <0.001). Nonlinear relationships between AAge measures and risk of BPH were also found for KDM-AAge (P = 0.041) and PhenoAge-AAge (P = 0.020). Compared to the balance comparison group (-1 SD < AAge < 1 SD), the accelerated aging group (AAge > 2 SD) had a significantly elevated BPH risk with hazard ratio (HR) of 1.115 (95% CI, 1.000-1.223) for KDM-AAge and 1.180 (95% CI, 1.068-1.303) for PhenoAge-AAge, respectively. For PhenoAge-AAge, subgroup analysis of the accelerated aging group showed an increased HR of 1.904 (95% CI, 1.374-2.639) in males with CAge <50 years and 1.233 (95% CI, 1.088-1.397) in those having testosterone levels <12 nmol/L. Moreover, AAge-associated risk of BPH was independent of and additive to genetic risk. Conclusions: Biological aging is an independent and modifiable risk factor for BPH. We suggest performing active health interventions to slow biological aging, which will help mitigate the progression of prostate aging and further reduce the burden of BPH.