ObjectiveTo construct and evaluate various machine learning models for predicting the risk of chronic obstructive pulmonary disease （COPD） in individuals， thereby providing data support for early screening and intervention. MethodsA total of 823 subjects were selected for this study， comprising 142 individuals in the high-risk group for COPD and 681 individuals in the low-risk group. Data collected included demographic characteristics， smoking history， symptoms （such as cough and shortness of breath）， and scores from the Chronic obstructive pulmonary disease screening questionnaire. Four machine learning algorithms—Logistic regression， random forest， support vector machine， and XGBoost—were utilized to construct risk prediction models. The performance of these models was assessed using 5-fold cross-validation， with evaluation metrics including accuracy， precision， recall， F1-score， area under the receiver operating characteristic curve （AUC）， and average precision （AP）. Furthermore， a feature importance analysis was performed. ResultsThe Logistic Regression model exhibited superior performance， achieving an AUC of 0.982 and an AP of 0.939. This was closely followed by the Random Forest model， which recorded an AUC of 0.975 and an AP of 0.890. Feature importance analysis revealed that smoking history， symptoms of shortness of breath， and body weight were significant predictors. All models demonstrated robust performance in identifying low-risk populations； however， variations were observed in their efficacy in identifying high-risk populations. ConclusionMachine learning models have proven effective in identifying individuals at high risk for COPD. Among these， the Logistic regression model exhibits the best overall performance， efficiently identifying high-risk populations and serving as a valuable clinical auxiliary screening tool. Various models， each with distinct performance characteristics， are suited to different clinical screening scenarios， thereby offering targeted decision-making support for the establishment of a hierarchical and intelligent COPD screening pathway.

ObjectiveTo observe the effect of Xiaoke drink on insulin resistance in ob/ob mice and explore the mechanism. MethodEighteen ob/ob mice were randomly assigned into model， Xiaoke drink （17.68 g·kg^-1）， and atorvastatin （0.01 g·kg^-1） groups （n=6）， and six C57BL/6 mice were selected as the normal group. Mice in the normal and model groups were administrated with the same amount of distilled water. Fasting body weight， weekly food intake， and weekly water intake were measured at a fixed time. Fasting plasma glucose （FPG） and 2-hour post-load plasma glucose （2 hPG） were measured before and after 8-week intervention. After intervention， total cholesterol （TC）， triglyceride （TG）， fasting insulin （FINS）， Homeostasis Model Assessment-Insulin Resistance （HOMA-IR）， blood routine， and alkaline phosphatase （ALP） were measured. Western blot was employed to determine the expression levels of ubiquitin-specific protease 20 （USP20） and 3-hydroxy-3-methylglutaryl coenzyme A reductase （HMGCR） in the liver. The pancreas was stained with hematoxylin-eosin for observation. ResultCompared with the model group， the Xiaoke drink group showed decreased body weight of ob/ob mice （P<0.05， P<0.01）， declined growth trend of body weight （P<0.05， P<0.01）， reduced weekly average water intake， lowered levels of FPG， 2 hPG， TC， and HOMA-IR （P<0.05， P<0.01）， and down-regulated expression level of USP20 in the liver （P<0.05）. HMGCR content was positively correlated with USP20 expression. In addition， Xiaoke drink promoted the recovery of islet tissue morphology and function in ob/ob mice. ConclusionXiaoke drink can ameliorate insulin resistance in ob/ob mice by inhibiting USP20/HMGCR expression， reversing cholesterol biosynthesis process， and reducing cholesterol level.

Background/Aims: To evaluate the causal correlation between complement components and non-viral liver diseases and their potential use as druggable targets. Methods: We conducted Mendelian randomization (MR) to assess the causal role of circulating complements in the risk of non-viral liver diseases. A complement-centric protein interaction network was constructed to explore biological functions and identify potential therapeutic options. Results: In the MR analysis, genetically predicted levels of complement C1q C chain (C1QC) were positively associated with the risk of autoimmune hepatitis (odds ratio 1.125, 95% confidence interval 1.018–1.244), while complement factor H-related protein 5 (CFHR5) was positively associated with the risk of primary sclerosing cholangitis (PSC;1.193, 1.048– 1.357). On the other hand, CFHR1 (0.621, 0.497–0.776) and CFHR2 (0.824, 0.703–0.965) were inversely associated with the risk of alcohol-related cirrhosis. There were also significant inverse associations between C8 gamma chain (C8G) and PSC (0.832, 0.707–0.979), as well as the risk of metabolic dysfunction-associated steatotic liver disease (1.167, 1.036–1.314). Additionally, C1S (0.111, 0.018–0.672), C7 (1.631, 1.190–2.236), and CFHR2 (1.279, 1.059–1.546) were significantly associated with the risk of hepatocellular carcinoma. Proteins from the complement regulatory networks and various liver diseaserelated proteins share common biological processes. Furthermore, potential therapeutic drugs for various liver diseases were identified through drug repurposing based on the complement regulatory network. Conclusions Our study suggests that certain complement components, including C1S, C1QC, CFHR1, CFHR2, CFHR5, C7, and C8G, might play a role in non-viral liver diseases and could be potential targets for drug development.

OBJECTIVE: To investigate the efficacy of brain-targeted rapamycin (T-Rap) in treatment of epilepsy in rats. METHODS: Rapamycin nanoparticles targeting brain were prepared. The epilepsy model was induced by injection of pilocarpine in rats. The rats with pilocarpine-induced epilepsy were treated with rapamycin (Rap group) or brain-targeted rapamycin (T-Rap group). Seizure activity was observed by electroencephalography; the effect on mTOR signaling pathway was detected by Western blot; neuronal death and moss fiber sprouting were analyzed by Fluoro-Jade B (FJB) and Timm's staining, respectively. RESULTS: Electroencephalography showed that both preparation of rapamycin significantly reduced the frequency of spontaneous seizures in rats, and the effect of T-Rap was stronger than that of conventional rapamycin (<0.05). Western blot showed that the phosphorylation levels of S6K and S6 in T-Rap group were lower than those in Rap group (all <0.05), indicating that T-Rap had a stronger inhibitory effect on mTOR signaling pathway. FJB staining showed that T-Rap significantly decreased neuronal death, but there was no significant difference as compared with Rap group. Timm's staining showed that both preparations of rapamycin significantly reduced the germination of mossy fibers, while the effect of T-Rap was more pronounced than Rap group (<0.05). The inhibition of body weight gain of T-Rap group was less than that of Rap group (<0.05). CONCLUSIONS T-Rap has a better therapeutic effect on epilepsy than conventional rapamycin with a less adverse effects in rats.
Animals ; Brain ; drug effects ; Disease Models, Animal ; Epilepsy ; chemically induced ; drug therapy ; Neurons ; drug effects ; Pilocarpine ; Rats ; Rats, Sprague-Dawley ; Signal Transduction ; drug effects ; Sirolimus ; pharmacology ; therapeutic use ; Treatment Outcome

T-cell internal antigen-1 (TIA-1) has roles in regulating alternative pre-mRNA splicing, mRNA translation, and stress granule (SG) formation in human cells. As an evolutionarily conserved response to environmental stress, SGs have been reported in various species. However, SG formation in chicken cells and the role of chicken TIA-1 (cTIA-1) in SG assembly has not been elucidated. In the present study, we cloned cTIA-1 and showed that it facilitates the assembly of canonical SGs in both human and chicken cells. Overexpression of the chicken prion-related domain (cPRD) of cTIA-1 that bore an N-terminal green fluorescent protein (GFP) tag (pntGFP-cPRD) or Flag tag (pFlag-cPRD) induced the production of typical SGs. However, C-terminal GFP-tagged cPRD induced notably large cytoplasmic granules that were devoid of endogenous G3BP1 and remained stable when exposed to cycloheximide, indicating that these were not typical SGs, and that the pntGFP tag influences cPRD localization. Finally, endogenous cTIA-1 was recruited to SGs in chicken cells and tissues under environmental stress. Taken together, our study provide evidence that cTIA-1 has a role in canonical SG formation in chicken cells and tissues. Our results also indicate that cPRD is necessary for SG aggregation.
Chickens ; Clone Cells ; Cycloheximide ; Cytoplasmic Granules ; Humans ; Protein Biosynthesis ; RNA Precursors ; RNA-Binding Proteins ; T-Lymphocytes