Age-related changes of dopamine D1 and D2 receptors expression in parvalbumin-positive cells of the orbitofrontal and prelimbic cortices of mice.

Dopamine (DA) plays a pivotal role in reward processing, cognitive functions, and emotional regulation. The prefrontal cortex (PFC) is a critical brain region for these processes. Parvalbumin-positive (PV+) neurons are one of the major classes of inhibitory GABAergic neurons in the cortex, they modulate the activity of neighboring neurons, influencing various brain functions. While DA receptor expression exhibits age-related changes, the age-related changes of these receptors in PV+ neurons, especially in the PFC, remain unclear. To address this, we investigated the expression of DA D1 (D1R) and D2 (D2R) receptors in PV+ neurons within the orbitofrontal (OFC) and prelimbic (PrL) cortices at different postnatal ages (P28, P42, P56, and P365). We found that the expression of D1R and D2R in PV+ neurons showed both age- and region-related changes. PV+ neurons in the OFC expressed a higher abundance of D1 than those in the PrL, and those neurons in the OFC also showed higher co-expression of D1R and D2R than those in the PrL. In the OFC and PrL, D1R in PV+ neurons increased from P28 and reached a plateau at P42, then receded to express at P365. Meanwhile, D2R did not show significant age-related changes between the two regions except at P56. These results showed dopamine receptors in the prefrontal cortex exhibit age- and region-specific changes, which may contribute to the difference of these brain regions in reward-related brain functions.

A disinhibitory microcircuit of the orbitofrontal cortex mediates cocaine preference in mice.

Both clinical and animal studies showed that the impaired functions of the orbitofrontal cortex (OFC) underlie the compulsive drug-seeking behavior of drug addiction. However, the functional changes of the microcircuit in the OFC and the underlying molecular mechanisms in drug addiction remain elusive, and little is known for whether microcircuits in the OFC contributed to drug addiction-related behaviors. Utilizing the cocaine-induced conditioned-place preference model, we found that the malfunction of the microcircuit led to disinhibition in the OFC after cocaine withdrawal. We further showed that enhanced Somatostatin-Parvalbumin (SST-PV) inhibitory synapse strength changed microcircuit function, and SST and PV inhibitory neurons showed opposite contributions to the drug addiction-related behavior of mice. Brevican of the perineuronal nets of PV neurons regulated SST-PV synapse strength, and the knockdown of Brevican alleviated cocaine preference. These results reveal a novel molecular mechanism of the regulation of microcircuit function and a novel circuit mechanism of the OFC in gating cocaine preference.

Development and validation of mathematical nomogram for predicting the risk of poor sleep quality among medical students.

Background: Despite the increasing prevalence of poor sleep quality among medical students, only few studies have identified the factors associated with it sing methods from epidemiological surveys. Predicting poor sleep quality is critical for ensuring medical Students' good physical and mental health. The aim of this study was to develop a comprehensive visual predictive nomogram for predicting the risk of poor sleep quality in medical students. Methods: We investigated medical Students' association with poor sleep quality at JiTang College of North China University of Science and Technology through a cross-sectional study. A total of 5,140 medical students were randomized into a training cohort (75%) and a validation cohort (25%). Univariate and multivariate logistic regression models were used to explore the factors associated with poor sleep quality. A nomogram was constructed to predict the individual risk of poor sleep quality among the medical students studied. Results: 31.9% of medical students in the study reported poor sleep quality. We performed multivariate logistic analysis and obtained the final model, which confirmed the risk and protective factors of poor sleep quality (p < 0.05). Protective factors included the absence of physical discomfort (OR = 0.638, 95% CI: 0.546-0.745). Risk factors included current drinking (OR = 0.638, 95% CI: 0.546∼0.745), heavy study stress (OR = 2.753, 95% CI: 1.456∼5.631), very heavy study stress (OR = 3.182, 95% CI: 1.606∼6.760), depressive symptoms (OR = 4.305, 95% CI: 3.581∼5.180), and anxiety symptoms (OR = 1.808, 95% CI: 1.497∼2.183). The area under the ROC curve for the training set is 0.776 and the area under the ROC curve for the validation set is 0.770, which indicates that our model has good stability and prediction accuracy. Decision curve analysis and calibration curves demonstrate the clinical usefulness of the predictive nomograms. Conclusion: Our nomogram helps predict the risk of poor sleep quality among medical students. The nomogram used includes the five factors of drinking, study stress, recent physical discomfort, depressive symptoms, and anxiety symptoms. The model has good performance and can be used for further research on and the management of the sleep quality of medical students.

Metabolomic Identification of Serum Exosome-Derived Biomarkers for Bipolar Disorder.

BACKGROUND: Exosomes are extracellular vesicles that play important roles in various physiological and pathological functions. Previous studies have demonstrated that exosome-derived contents are promising biomarkers to inform the pathogenesis and diagnosis of major depressive disorder and schizophrenia. METHODS: We used ultraperformance liquid chromatography-tandem mass spectrometry to analyze the differentially expressed metabolites in serum exosomes of patients with bipolar disorder (BD) and evaluated the potential of exosomal metabolites as biomarkers for BD. RESULTS: Our results showed 26 differentially expressed serum exosomal metabolites in patients with BD (n = 32) when compared with healthy control (HC) subjects (n = 40), and these differentially expressed metabolites were enriched in pathways related to sugar metabolism. We then utilized random forest classifier and identified 15 exosomal metabolites that can be used to classify samples from patients with BD and HC subjects with 0.838 accuracy (95% CI, 0.604-1.00) in the training set of participants. These 15 metabolites showed excellent performance in differentiating between patients with BD and HC subjects in the testing set of participants, with 0.971 accuracy (95% CI, 0.865-1.00). Importantly, the 15 exosomal metabolites also showed good to excellent performance in differentiating between BD patients and other major psychiatric diseases (major depressive disorder and schizophrenia). CONCLUSION: Collectively, our findings for the first time revealed a potential role of exosomal metabolite dysregulations in the onset and/or development of BD and suggested that blood exosomal metabolites are strong candidates to inform the diagnosis of BD.

[Multiscale influences of urbanized landscape metrics on the diversity of indigenous plant species: A case study in Shunyi District of Beijing, China.] / åŸŽå¸‚åŒ–æ™¯è§‚æ ¼å±€å¯¹æœ¬åœŸæ¤ç‰©å¤šæ ·æ€§çš„å¤šå°ºåº¦å½±å“­­ä»¥åŒ—京市顺义区为例.

The effects of landscape pattern on plant diversity have been widely reported in literature, with that of urban landscape remaining largely unknown. To explore the impacts of urbanization landscape pattern on plant diversity and its scale effect, 105 plots were investigated in Shunyi District, Beijing. The α and ß diversity of each plot were calculated, and 43 urban landscape indices of 10 scales in the range of 100-1000 m were analyzed with 100 m as the step. The results showed that the urban landscape area metric, core metrics and edge metrics were negatively related with diversity of indigenous plant species at all the examined scales. Shape complexity metrics contributed to plant diversity at small scale, while the area-weighted complexity metrics contributed at large scale. Other metrics, such as connection, proximity, cohesion, fragmentation and interspersion juxtaposition of urban patches showed a slight and unsteady relationship with the diversity of indigenous plant species. The urbanization intensity was negatively related with scales and with plant diversity at all scales. Urban landscape could better conserve indigenous plant diversity by reasonably dividing an urbanized area into many small patches with simple edge. Our results presented suitable urban landscape indicators for preserving plant diversity and suggestions for the construction of ecological cities.