ObjectiveTo investigate the effect and mechanism of transplantation of human umbilical cord mesenchymal stem cell （hUC-MSC） with overexpression of the Numb gene in the treatment of cholestatic liver fibrosis （CLF）. MethodsThe technique of lentiviral transfection was used to induce the overexpression of the Numb gene in hUC-MSC （hUC-MSC^Numb-OE）， and hUC-MSC transfected with empty vector （hUC-MSC^OE-EV） was used as negative control. Bile duct ligation （BDL） was performed to establish a rat model of CLF， and then the rats were randomly divided into BDL group， hUC-MSC group， hUC-MSC^OE-EV group， and hUC-MSC^Numb-OE group， while a sham-operation group was also established. The rats in the intervention groups were given a single splenic injection of the corresponding cells after BDL， and samples were collected at the end of week 4. Related indicators were measured， including serum biochemistry， liver histopathology， the content of hydroxyproline （Hyp） in the liver， hepatic stellate cell activation， ductular reaction， liver regeneration， and the expression levels of key molecules in the Numb-p53 signaling axis. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups. ResultsCompared with the BDL group， the hUC-MSC group and the hUC-MSC^OE-EV group had significant reductions in the levels of serum biochemical parameters （aspartate aminotransferase， gamma-glutamyl transpeptidase， total bile acid， total bilirubin， and direct bilirubin）， liver fibrosis markers （the content of Hyp and the expression levels of alpha-smooth muscle actin， tumor necrosis factor-α， and transforming growth factor-beta 1）， and ductular reaction markers （the expression levels of CK7 and CK19） （all P <0.05）， and compared with the hUC-MSC^OE-EV group， the hUC-MSC^Numb-OE group had significantly greater improvements in the above indicators （all P <0.05）. In addition， compared with the hUC-MSC^OE-EV group， the hUC-MSC^Numb-OE group had significant improvements in the expression levels of liver regeneration-related markers （albumin and hepatocyte nuclear factor 4α） and the molecules associated with the Numb-p53 signaling axis （Numb， pNumb， Mdm2， and p53） （all P <0.05）. ConclusionOverexpression of the Numb gene can enhance the therapeutic effect of hUC-MSC on CLF， possibly by activating the Numb-PTB^L-p53-HNF4α axis， promoting the hepatic differentiation of hUC-MSCs and subsequently enhancing liver regeneration.

AIM: To explore the effect of dihydroquercetin on visual function in mice with form deprivation myopia based on the NOD-like receptor thermoprotein domain-related protein 3(NLRP3)inflammasome pathway.METHODS: The C57BL/6 mice were randomly divided into control group and form deprivation myopia model group, and the form deprivation myopia model group was constructed by covering the right eye with a translucent eye patch. After successful modeling, the mice in the model group of form deprivation myopia were randomly divided into model group, low-, medium- and high-dose dihydroquercetin groups, and high-dose dihydroquercetin + NLRP3 agonist group. The diopter and axial length of mice in each group were detected. The kit was used to detect the levels of superoxide dismutase(SOD)and malondialdehyde(MDA)in retinal tissue. RT-qPCR was used to detect the mRNA expressions of NLRP3, apoptosis-associated spot-like protein(ASC), Caspase-1, IL-1β and IL-18 in retinal tissues. Western blot was used to detect the expression of NLRP3, ASC, cleaved Caspase-1, IL-1β and IL-18 proteins in retinal tissues. TUNEL staining was used to detect apoptosis in retinal tissue.RESULTS: Compared with the control group, the diopter of the mice in the model group decreased, and axial length increased, and the SOD decreased whereas MDA, NLRP3, ASC, Caspase-1, IL-1β, IL-18 increased, and the rate of apoptosis in retinal tissue increased(all P<0.05). Compared with the model group, the diopter of mice in the low-, medium- and high-dose dihydroquercetin groups increased, axial length shortened, the SOD increased, whereas MDA, NLRP3, ASC, Caspase-1, IL-1β, IL-18 decreased, and the rate of apoptosis in retinal tissue decreased(all P<0.05). Compared with the high-dose dihydroquercetin group, the high-dose dihydroquercetin+NLRP3 agonist group had reduced diopter, increased axial length, decreased SOD levels, elevated MDA, NLRP3, ASC, Caspase-1, IL-1β, and IL-18 levels, as well as increased apoptosis rate in retinal tissue(all P<0.05).CONCLUSION: Dihydroquercetin can improve visual function in mice with form deprivation myopia by inhibiting pyroptosis and oxidative stress responses, which may be related to the suppression of NLRP3 inflammasome. NLRP3 agonists can partially mitigate the effects of high-dose dihydroquercetin on form deprivation myopia in mice.

To thoroughly implement the strategic deployment outlined in the Opinions of the Central Committee of the Communist Party of China and the State Council on Promoting the Inheritance and Innovative Development of Traditional Chinese Medicine regarding research on dominant diseases of traditional Chinese medicine and to uphold the development philosophy of equal emphasis on traditional Chinese medicine and western medicine，the China Association of Chinese Medicine has fully played a leading academic role by systematically organizing and conducting a series of academic youth salons on clinical dominant diseases of traditional Chinese medicine. On September 13，2024，the 36^th Youth Salon on Clinical Dominant Diseases was successfully held in Nanjing，focusing on the advantages of traditional Chinese medicine and the integrative traditional Chinese medicine and western medicine in the diagnosis and treatment of erectile dysfunction （ED）. The conference brought together leading experts from traditional Chinese medicine，western medicine，and interdisciplinary fields，facilitating in-depth multidisciplinary discussions that led to key consensus on optimizing traditional Chinese medicine treatment protocols for ED，researching and developing new drugs of traditional Chinese medicine，and advancing interdisciplinary development in traditional Chinese medicine. This salon systematically sorted out the clinical strengths and distinctive features of traditional Chinese medicine in the diagnosis and treatment of ED. Based on current research foundations and clinical needs，it identified key directions for future scientific layout and scientific research tackling： （1） Standardization of syndrome differentiation system of traditional Chinese medicine for ED. （2） Optimization and standardization of intervention methods of integrated traditional Chinese medicine and western medicine. （3） High-quality clinical research guided by evidence-based medicine. （4） In-depth analysis of the pharmacological mechanisms of traditional Chinese medicine in the treatment of ED. （5） Clinical translation and application promotion of new drugs of traditional Chinese medicine. （6） Interdisciplinary integration and innovation in traditional Chinese medicine. For each research direction，key focus areas，expected objectives，and clinical value were further refined，along with the establishment of a scientifically sound priority funding level evaluation system. Therefore，building on the series of salons on the ED-focused dominant diseases of traditional Chinese medicine，this paper provides standardized guidance for clinical practice of traditional Chinese medicine in ED management，effectively contributing to the high-quality development of traditional Chinese medicine. It serves as a valuable reference for national scientific and technological strategic layout， research and development decision-making in new drugs of traditional Chinese medicine，research topic planning，and clinical guideline formulation.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

In this study, lipopolysaccharide(LPS), ovalbumin(OVA), and compound 48/80(C48/80) were administered to establish non-infectious pneumonia models under simulated clinical conditions, and the correlation between their pathological characteristics and traditional Chinese medicine(TCM) syndromes was compared, providing the basis for the selection of appropriate animal models for TCM efficacy evaluation. An acute pneumonia model was established by nasal instillation of LPS combined with intraperitoneal injection for intensive stimulation. Three doses of OVA mixed with aluminum hydroxide adjuvant were injected intraperitoneally on days one, three, and five and OVA was administered via endotracheal drip for excitation on days 14-18 to establish an OVA-induced allergic pneumonia model. A single intravenous injection of three doses of C48/80 was adopted to establish a C48/80-induced pneumonia model. By detecting the changes in peripheral blood leukocyte classification, lung tissue and plasma cytokines, immunoglobulins(Ig), histamine levels, and arachidonic acid metabolites, the multi-dimensional analysis was carried out based on pathological evaluation. The results showed that the three models could cause pulmonary edema, increased wet weight in the lung, and obvious exudative inflammation in lung tissue pathology, especially for LPS. A number of pyrogenic cytokines, inclading interleukin(IL)-6, interferon(IFN)-γ, IL-1β, and IL-4 were significantly elevated in the LPS pneumonia model. Significantly increased levels of prostacyclin analogs such as prostaglandin E2(PGE2) and PGD2, which cause increased vascular permeability, and neutrophils in peripheral blood were significantly elevated. The model could partly reflect the clinical characteristics of phlegm heat accumulating in the lung or dampness toxin obstructing the lung. The OVA model showed that the sensitization mediators IgE and leukotriene E4(LTE4) were increased, and the anti-inflammatory prostacyclin 6-keto-PGF2α was decreased. Immune cells(lymphocytes and monocytes) were decreased, and inflammatory cells(neutrophils and basophils) were increased, reflecting the characteristics of "deficiency", "phlegm", or "dampness". Lymphocytes, monocytes, and basophils were significantly increased in the C48/80 model. The phenotype of the model was that the content of histamine, a large number of prostacyclins(6-keto-PGE1, PGF2α, 15-keto-PGF2α, 6-keto-PGF1α, 13,14-D-15-keto-PGE2, PGD2, PGE2, and PGH2), LTE4, and 5-hydroxyeicosatetraenoic acid(5S-HETE) was significantly increased, and these indicators were associated with vascular expansion and increased vascular permeability. The pyrogenic inflammatory cytokines were not increased. The C48/80 model reflected the characteristics of cold and damp accumulation. In the study, three non-infectious pneumonia models were constructed. The LPS model exhibited neutrophil infiltration and elevated inflammatory factors, which was suitable for the efficacy study of TCM for clearing heat, detoxifying, removing dampness, and eliminating phlegm. The OVA model, which took allergic inflammation as an index, was suitable for the efficacy study of Yiqi Gubiao formulas. The C48/80 model exhibited increased vasoactive substances(histamine, PGs, and LTE4), which was suitable for the efficacy study and evaluation of TCM for warming the lung, dispersing cold, drying dampness, and resolving phlegm. The study provides a theoretical basis for model selection for the efficacy evaluation of TCM in the treatment of pneumonia.
Animals ; Disease Models, Animal ; Mice ; Pneumonia/genetics* ; Medicine, Chinese Traditional ; Male ; Humans ; Cytokines/immunology* ; Female ; Lipopolysaccharides/adverse effects* ; Lung/drug effects* ; Drugs, Chinese Herbal ; Ovalbumin ; Mice, Inbred BALB C

BACKGROUND:Exercise as a form of active rehabilitation can improve the dysfunction caused by peripheral nerve injury,and different exercise modalities target different lesion sites and recovery mechanisms. OBJECTIVE:To comprehensively analyze the application and mechanisms of different exercise modalities in functional recovery from peripheral nerve injury. METHODS:A computerized search was conducted in PubMed and CNKI databases for relevant literature published before January 2024.The search terms used were"peripheral nerve injury,spinal cord,exercise,cerebral cortex,muscle atrophy,mirror therapy,blood flow restriction training"in both English and Chinese.Finally,77 articles were included for review. RESULTS AND CONCLUSION:Peripheral nerve injury can cause systemic pathological changes such as skeletal muscle atrophy,corresponding spinal cord segmental lesions,and sensorimotor cortex remodeling.Aerobic exercise can improve dysfunction by enhancing the immune response,promoting glial cell polarization,and promoting the release of nerve growth factor.Blood flow restriction exercise can regulate the secretion of muscle growth factor,promote muscle growth and enhance muscle strength.Mirror movement has a good effect in activating the cerebral cortex and reducing cortical remodeling.Different exercise modalities have potential benefits in functional recovery after peripheral nerve injury;however,there are still some problems and challenges,such as the choice of exercise modalities,the control of exercise intensity and frequency,and the detailed analysis of mechanisms.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.