OBJECTIVE To study the pharmacokinetic characteristics of antidepressant active components from Jiaotai pills in healthy subjects. METHODS Eight healthy subjects （3 males and 5 females） were recruited and given a single oral dose of 8.55 g of Jiaotai pills. Venous blood samples were collected before administration （0 h） and at intervals from 0.25 to 36.0 hours post- administration. After treating the plasma samples with protein precipitation， the blood concentrations of the antidepressant active ingredients （coptisine， berberine， magnoflorine， and palmatine） in Jiaotai pills were determined using liquid chromatography- tandem mass spectrometry （LC-MS/MS） method. DAS 2.0 software was employed to calculate the pharmacokinetic parameters of healthy subjects [half-life （t1/2）， peak concentration （cmax）， time to peak concentration （tmax）， area under the concentration-time curve （AUC）， and mean residence time （MRT）] using a non-compartmental model. RESULTS After healthy subjects took Jiaotai pills， the drug-time curve of the four antidepressant active ingredients conforms to a two-compartment model and tmax values were similar， with all reaching peak blood concentrations within 2.00 to 4.00 hours post-administration. However， the t1/2 and MRT of coptisine and berberine were significantly longer than that of magnoflorine and palmatine. There were also significant differences in the AUC and cmax among the four antidepressant active ingredients， with magnoflorine exhibiting markedly higher AUC0-t and cmax compared to the other three components. CONCLUSIONS In this study，LC-MS/MS is used to analyze the pharmacokinetic characteristics of the antidepressant active ingredients from Jiaotai pills in healthy subjects， can provide valuable references for the clinical application of Jiaotai pills.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

OBJECTIVE:Based on different algorithms of machine learning,the prediction model of lumbar disc herniation has become a trend and hot spot in the development of precision medicine.However,there is limited evidence on the reporting quality and methodological quality of prediction models of lumbar disc herniation outcomes using machine learning.This article is aimed to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation by comprehensively analyzing the report quality and risk of bias of previous studies that developed and validated prognosis prediction models based on machine learning through a comprehensive literature search,in order to explore the performance of machine learning algorithms in predicting the prognosis of lumbar disc herniation.METHODS:The databases of CNKI,WanFang,VIP,SinOMED,PubMed,Web of Science,Embase,and The Cochrane Library were searched by computer.Studies on the use of machine learning to develop(and/or validate)prognostic prediction models for lumbar disc herniation were collected from the inception of the database to December 31,2023.Two researchers independently screened the literature,extracted data,and assessed the risk of bias of the included studies.The reporting quality and risk of bias of the included studies were assessed by the Multivariable Transparent Reporting of Predictive Models(TRIPOD)statement and the Predictive Model Risk of Bias Assessment Tool(PROBAST).The results of the evaluation were analyzed using descriptive statistics and visual charts.RESULTS:(1)A total of 23 articles were included,and the TRIPOD compliance of each study ranged from 11％to 87％,with a median compliance of 54％.The quality of reporting of titles,detailed descriptions of treatment measures,blinding of predictors,handling of missing data,details of risk stratification,specific procedures for enrollment,model interpretation,and model performance was mostly poor,with TRIPOD adherence rates ranging from 4％to 35％.(2)Of all included studies,61％had a high risk of bias and 39％had an unclear overall risk of bias.The area under the curve,accuracy,sensitivity and specificity were used to evaluate the performance of the model.The areas under the curve of 20 models were reported,ranging from 0.561 to 0.999.Three models reported the accuracy of the model,ranging from 82.07％to 89.65％.(3)Among all included studies,the statistical analysis domain was most often assessed as having a high risk of bias,mainly due to the small number of valid samples,the selection of predictors based on univariate analysis and the lack of calibration and discrimination assessment of the model in the study.CONCLUSION:These results indicate that machine learning can achieve good predictive ability in the development and validation of prognostic models for lumbar disc herniation.The commonly used algorithms include regression algorithm,support vector machine,decision tree,random forest,artificial neural network,naive Bayes and other algorithms.Reasonable algorithms combined with clinical practice can improve the accuracy of prognosis prediction of lumbar disc herniation.However,the reporting and methodological quality of prognosis prediction models based on machine learning are poor,the prediction performance of different models varies greatly,and the generalization and extrapolation of research models are unclear.There is an urgent need to improve the design,implementation and reporting of such studies.To promote the application of machine learning in the clinical practice of lumbar disc herniation prediction models,it is necessary to comprehensively consider various predictors related to the prognosis of the disease before modeling,and strictly follow the relevant standards of PROBAST tool during modeling.

Objective To investigate the causes and management strategies for lower limb ischemic necrosis following xenogeneic heterotopic heart transplantation from a multigene-edited pig to a rhesus monkey. Methods A xenogeneic heterotopic heart transplantation was performed on December 16, 2023, at the Institute of Experimental Animals of Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, using a quintuple-gene-edited pig as the donor and a rhesus monkey as the recipient. On postoperative day (POD) 9, the recipient monkey underwent left lower limb amputation due to ischemic necrosis. Blood samples were collected at various time points after transplantation for analysis of hematologic parameters, liver and renal function, myocardial enzymes, and coagulation profiles. Ultrasound and computed tomography (CT) were used to evaluate anastomotic patency and cardiac structure. Immunological assays, including complement-dependent cytotoxicity (CDC) and IgG/IgM antibody detection, combined with clinical observations, were employed to assess rejection type and therapeutic response. Results The recipient monkey survived for 46 days after transplantation. Echocardiography demonstrated preserved biventricular systolic function in the recipient’s native heart, with left ventricular ejection fraction (LVEF) consistently exceeding 50%. In the donor pig heart, left ventricular endocardial thickening was noted on POD 9, followed by right ventricular endocardial thickening on POD 24, while LVEF remained around 35%. No hyperacute or acute rejection was detected immunologically. CDC positivity ranged between 3.4% and 5.1%, with IgG/IgM antibody binding trends consistent with CDC results. Following amputation, the recipient exhibited elevated inflammatory markers, coagulopathy, and reactive thrombocytosis, which later normalized. Immunohistochemical staining of the necrotic limb revealed arterial and venous thrombosis; however, no T-cell or B-cell infiltration was observed in vascular structures, thrombi, nerves, muscles, fascia, or skin tissues, with CD3 and CD20 staining both negative. Conclusion Limb ischemia after xenogeneic heart transplantation may be associated with lower extremity vascular thrombosis triggered by local trauma in the context of transplantation-induced inflammatory activation and coagulation dysfunction. While no clear lymphocyte-mediated rejection was observed, further studies are needed to explore the potential role of non-lymphocyte-mediated immune mechanisms.

Hepatic encephalopathy is a difficult and critical disease with rapid progression and limited treatment methods in the field of liver disease， and it is urgently needed to make breakthroughs in its pathogenesis. Selection of appropriate prevention and treatment strategies is of great importance in delaying disease progression and reducing the incidence and mortality rates. This article reviews the theory of “turbid toxin pathogenesis” and related prevention and treatment strategies for hepatic encephalopathy in traditional Chinese medicine/Zhuang medicine， proposes a new theory of “turbid toxin pathogenesis”， analyzes the scientific connotations of “turbid”， “toxin”， and the theory of “turbid toxin pathogenesis”， and constructs the “four-step” prevention and treatment strategies for hepatic encephalopathy， thereby establishing the new clinical prevention and treatment regimen for hepatic encephalopathy represented by “four prescriptions and two techniques” and clarifying the effect mechanism and biological basis of core prescriptions and techniques in the prevention and treatment of hepatic encephalopathy， in order to provide a reference for the prevention and treatment of hepatic encephalopathy.

ObjectiveTo explore the mechanism of Hei Xiaoyaosan in improving the cognitive function in Alzheimer's disease （AD） from cell apoptosis mediated by the phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/nuclear factor kappa B （NF-κB） signaling pathway. MethodsFour-month-old SD male rats were randomly assigned into a blank group， a sham group， a model group， a donepezil hydrochloride （0.45 mg·kg^-1） group， and high-， medium-， and low-dose （15.30， 7.65， and 3.82 g·kg^-1， respectively） Hei Xiaoyaosan groups， with 10 rats in each group. The sham group received bilateral hippocampal injection of 1 μL normal saline， while the other groups received bilateral hippocampal injection of 1 μL beta-amyloid 1-42 （Aβ_1-42） solution for the modeling of AD. Rats were administrated with corresponding agents once a day for 42 consecutive days. The Morris water maze test was carried out to assess the learning and memory abilities of rats. Hematoxylin-eosin staining was employed to observe pathological changes in the hippocampus of rats. Enzyme-linked immunosorbent assay was employed to measure the levels of cysteinyl aspartate-specific proteinase-3 （Caspase-3）， B-cell lymphoma-2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. Western blot was employed to determine the protein levels of PI3K， Akt， and NF-κB. A cell model of AD was established by co-culturing Aβ_1-42 and PC12 cells in vitro. Cell viability and apoptosis were detected by the cell-counting kit 8 （CCK-8） assay and flow cytometry （FC）， respectively. ResultsAnimal experiments showed that compared with the blank group， the model group had a prolonged escape latency （P<0.01）， a reduced number of crossing platforms （P<0.01）， disarrangement and a reduced number of hippocampal neurons， up-regulated expression of Bax and Caspase-3， down-regulated expression of Bcl-2 （P<0.01）， decreased p-PI3K/PI3K and p-Akt/Akt levels， and an increased p-NF-κB/NF-κB level （P<0.01）. Compared with the model group， donepezil hydrochloride and high- and medium-dose Hei Xiaoyaosan shortened the escape latency and increased the number of crossing platforms （P<0.05， P<0.01）， improved the arrangement and increased the number of hippocampal neurons， down-regulated the expression levels of Bax and Caspase-3， up-reguated the expression level of Bcl-2 （P<0.05， P<0.01）， increased the p-PI3K/PI3K and p-Akt/Akt levels （P<0.05， P<0.01）， and reduced the p-NF-κB/NF-κB level （P<0.05， P<0.01）. Cell experiments showed that compared with the blank group， the model group exhibited an increased apoptosis rate （P<0.01）. Compared with the model group， the serum containing Hei Xiaoyaosan at various doses improved the cell viability （P<0.01）， and the serum containing Hei Xiaoyaosan at the high dose decreased the cell apoptosis （P<0.01）. ConclusionHei Xiaoyaosan may improve the learning and memory abilities of AD model rats by regulating cell apoptosis， while increasing the vitality and reducing the apoptosis rate of AD model cells via the PI3K/Akt/NF-κB signaling pathway.

ObjectiveTo observe the effects of Hei Xiaoyaosan on the learning and memory abilities of Alzheimer's disease model mice （APP/PS1 mice）， and to explore its mechanism through the inflammatory cascade mediated by nucleotide-binding oligomerization domain-like receptor family pyrin domain-containing 3 （NLRP3）/cysteine aspartate-specific protease （Caspase-1）/gasdermin D （GSDMD） signaling pathway. MethodsSPF-grade 4-month-old APP/PS1 mice were randomly divided into the model group， MCC950 group， and Hei Xiaoyaosan high-， medium-， and low-dose groups. C57BL/6J mice were used as the blank group. After 7 days of adaptive feeding， mice in each group were intervened. The Hei Xiaoyaosan high-， medium-， and low-dose groups were given corresponding doses by gavage （25.79， 12.90， 6.45 g·kg^-1·d^-1）， the MCC950 group was intraperitoneally injected with 10 mg·kg^-1·2 d^-1， and the blank group received the same volume of physiological saline by gavage. After 90 days of intervention， the learning and memory abilities were assessed using the Y maze and Morris water maze tests. The structural changes of hippocampal neurons were observed by hematoxylin-eosin （HE） staining. The expression of amyloid precursor protein （APP） in the hippocampal CA3 region was detected by immunohistochemistry. Enzyme-linked immunosorbent assay （ELISA） was used to measure the levels of interleukin （IL）-10， IL-18， and IL-1β in the hippocampus. Western blot was applied to detect the protein expression of NLRP3， Caspase-1， GSDMD， and GSDMD-N in the hippocampus. Immunofluorescence was used to detect the co-localization of GSDMD-N and ionized calcium-binding adapter molecule-1 （Iba-1） in the hippocampus. Results① In the Y maze test， compared with the blank group， the spontaneous alternation rate of the model group was significantly reduced （P<0.01）. Compared with the model group， the spontaneous alternation rate in the Hei Xiaoyaosan high- and low-dose groups was significantly increased （P<0.01）. ② In the Morris water maze test， during the 1-4 days of the location navigation test， the escape latency time of mice decreased with the extension of training time. On day 4， compared with the blank group， the model group showed a significantly increased escape latency （P<0.05）. Compared with the model group， the MCC950 group and the Hei Xiaoyaosan low-dose group showed significantly reduced escape latency （P<0.05）. In the spatial exploration experiment， compared with the blank group， the number of platform crossings in the model group was significantly reduced （P<0.01）. Compared with the model group， the Hei Xiaoyaosan low-dose group showed significantly increased platform crossings （P<0.05）. ③ HE staining showed that， compared with the blank group， the hippocampal CA3 cells of the model group were damaged， arranged loosely and irregularly， swollen， with unclear boundaries， and the nuclei were pyknotic and deeply stained. MCC950 and all doses of Hei Xiaoyaosan improved the hippocampal CA3 cell damage in APP/PS1 mice to varying degrees. ④ Immunohistochemical results indicated that， compared with the blank group， the expression of APP in the hippocampal CA3 region was significantly increased in the model group （P<0.01）. MCC950 and all doses of Hei Xiaoyaosan could reduce the expression of APP in the hippocampal CA3 region of APP/PS1 mice （P<0.01）. ⑤ ELISA results showed that the levels of IL-18 and IL-1β in the hippocampus of mice in the model group were significantly increased， and IL-10 levels were significantly reduced （P<0.01）. Compared with the model group， the IL-18 levels in the MCC950 group and the Hei Xiaoyaosan medium- and low-dose groups were significantly reduced （P<0.01）. IL-1β levels in the hippocampus of the MCC950 group and Hei Xiaoyaosan high-， medium-， and low-dose groups were significantly decreased （P<0.01）. The IL-10 levels in the hippocampus of the MCC950 group and the Hei Xiaoyaosan medium- and low-dose groups were increased （P<0.05， P<0.01）. ⑥ Western blot results showed that compared with the blank group， the protein levels of NLRP3， Caspase-1， GSDMD， and GSDMD-N in the hippocampus of the model group were significantly elevated （P<0.01）. Compared with the model group， the content of NLRP3 and Caspase-1 in the hippocampus of the treated groups was decreased （P<0.05， P<0.01）. The content of GSDMD in the hippocampus of the Hei Xiaoyaosan high-， medium-， and low-dose groups was reduced （P<0.05， P<0.01）， and the content of GSDMD-N in the hippocampus of the Hei Xiaoyaosan medium- and low-dose groups was decreased （P<0.05， P<0.01）. ⑦ Immunofluorescence results showed that， compared with the blank group， the co-expression of GSDMD-N and Iba-1 in the hippocampus of the model group was significantly increased （P<0.01）. Compared with the model group， the co-expression of GSDMD-N and Iba-1 in the treated groups was significantly reduced （P<0.01）. ConclusionHei Xiaoyaosan may regulate the NLRP3/Caspase-1/GSDMD signaling pathway to affect the release of inflammatory factors， alleviate neuroinflammation，improve hippocampal histopathological changes，and improve learning and memory deficits，thus providing potential therapeutic benefits for Alzheimer's disease.

Objective To analyze the current status and influencing factors of occupational stress, job burnout and sleep quality among workers in the secondary industry in Jinshan District, Shanghai City. Methods A total of 1 418 workers from six key industries in Jinshan District, Shanghai City were selected as the study subjects by the stratified cluster sampling method. The Occupational Stress Core Scale, Maslash Burnout Inventory General Survey and Pittsburgh Sleep Quality Index were used to investigate occupational stress, job burnout and sleep quality of the workers. Results The detection rates of occupational stress, job burnout and sleep disturbance among the study subjects were 33.6%, 65.4% and 23.3%, respectively. Multivariate logistic regression analysis showed that the workers with a monthly income <5 000 yuan had a higher risk of occupational stress than those with a monthly income ≥5 000 yuan (P<0.01). The workers with ≥5.0 years of service had a higher risk than those with <1.0 year (P<0.05). Lack of physical exercise, employment in medium- and large-sized enterprises, and shift work were risk factors of occupational stress in the workers (all P<0.01). The workers aged 18-<30 years had a higher risk of job burnout than those aged 45-<60 years (P<0.05). The workers monthly income <5 000 yuan was associated with a higher risk of job burnout than those with ≥9 000 yuan (P<0.05). The workers with 1.0-<10.0 years or ≥15.0 years of service had higher job burnout risks than those with <1.0 year (all P<0.05). Being unmarried, lack of physical exercise, and employment in medium- and large-sized enterprises were risk factor of job burnout in the workers (all P<0.05). The workers with an educational level of high school or above had a higher risk of sleep disturbance than those with junior school or below (P<0.05). The workers who work >56 hours per week had a higher risk than those working ≤40 hours per week (P<0.01). Conclusion There is a high detection rate of occupational stress, job burnout, and sleep disturbance in the secondary industry workers in Jinshan District, Shanghai City. Special attention should be given to workers with low income, lack of physical exercise, employment in medium- and large-sized enterprises, shift work, long service duration, and long weekly working hours to protect their physical and mental health.

Objective:To identify the key epithelial cell characteristics that can accurately diagnose eosinophilic chronic sinusitis with nasal polyps（ECRSwNP） through nasal brush sampling and comparing with the pathological results of nasal polyp tissue sections. Methods:Ninety-one patients underwent surgery in the Ophthalmology and ENT Department of the Second People's Hospital of Longgang District, Shenzhen, from January 2022 to July 2024 were selected. The cohort comprised 58 males and 33 females（mean age: 41.4 years; range: 12.0-71.0）. The clinical characteristics of the patients, including gender, age, disease duration, smoking and drinking history, asthma history, subjective symptoms, sinus CT, and nasal endoscopy scores, were recorded. Nasal brush sampling of nasal polyps and inferior turbinate mucosa was performed before surgery to obtain cytological specimens, and nasal polyp tissues were collected during surgery. The demographic and clinical characteristics of patients with eosinophilic and non-eosinophilic nasal polyps were compared, as well as the relationship between nasal brush cytology of nasal polyps and inferior turbinate and nasal polyp histopathology. Statistical analysis was performed using SPSS 23.0 software. Results:Among the 91 patients, no significant differences were observed between ECRSwNP and NECRSwNP patients in terms of age, gender, smoking status, alcohol consumption, and disease duration. The nasal brush cell population in ECRSwNP patients was more likely to contain eosinophils（P<0.001） and less likely to contain lymphocytes and plasma cells（P<0.001）. Additionally, the ciliated cells in ECRSwNP patients exhibited larger widths（P=0.036）, shorter cilium lengths（P<0.001）, and more disordered arrangements（P<0.001） compared to NECRSwNP patients. In nasal brush cells from the inferior turbinate, ECRSwNP patients also showed shorter cilium lengths（P<0.001） and shorter cilia（P=0.024） compared to NECRSwNP patients. Conclusion:There are significant differences in obtaining epithelial cytological information from nasal polyps or inferior turbinates through nasal brush sampling between ECRSwNP and NECRSwNP patients.
Humans ; Male ; Female ; Middle Aged ; Adult ; Nasal Polyps/complications* ; Sinusitis/complications* ; Aged ; Chronic Disease ; Adolescent ; Nasal Mucosa/pathology* ; Young Adult ; Rhinitis/complications* ; Eosinophilia/pathology* ; Child ; Eosinophils/pathology* ; Rhinosinusitis

Stearoyl-coenzyme A desaturase 1 (SCD1) catalyzes the rate-limiting step of de novo lipogenesis and modulates lipid homeostasis. Although numerous SCD1 inhibitors were tested for treating metabolic disorders both in preclinical and clinic studies, the tissue-specific roles of SCD1 in modulating obesity-associated metabolic disorders and determining the pharmacological effect of chemical SCD1 inhibition remain unclear. Here a novel role for intestinal SCD1 in obesity-associated metabolic disorders was uncovered. Intestinal SCD1 was found to be induced during obesity progression both in humans and mice. Intestine-specific, but not liver-specific, SCD1 deficiency reduced obesity and hepatic steatosis. A939572, an SCD1-specific inhibitor, ameliorated obesity and hepatic steatosis dependent on intestinal, but not hepatic, SCD1. Mechanistically, intestinal SCD1 deficiency impeded obesity-induced oxidative stress through its novel function of inducing metallothionein 1 in intestinal epithelial cells. These results suggest that intestinal SCD1 could be a viable target that underlies the pharmacological effect of chemical SCD1 inhibition in the treatment of obesity-associated metabolic disorders.