ObjectiveTo explore the mechanism by which Xiaoyaosan regulates HPT axis dysfunction in the rat model with the syndrome of liver depression and spleen deficiency by observing its effect on the glycoprotein hormone α-subunit （CGA）/glutathione peroxidase 2 （GPX2）/thyroid-stimulating hormone β-subunit （TSHβ） pathway for thyroid hormone synthesis. MethodsSeventy-two male SD rats were randomized into six groups： normal， model， high-dose （16.7 g·kg^-1）， medium-dose （8.35 g·kg^-1）， and low-dose （4.175 g·kg^-1） Xiaoyaosan， and fluoxetine （0.001 8 g·kg^-1） groups， with 12 rats in each group. The rat model of liver depression and spleen deficiency was induced by chronic restraint stress for 21 days. The intervention groups were treated with Xiaoyaosan decoctions or fluoxetine suspension， respectively. After modeling， hematoxylin-eosin staining was employed to observe morphological changes in the thyroid and pituitary tissue of the rats. Serum levels of triiodothyronine （T3）， tetraiodothyronine （T4）， and thyroid-stimulating hormone （TSH） were measured by enzyme-linked immunosorbent assay （ELISA）. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the mRNA and protein levels， respectively， of TSH receptor （TSHR） in the thyroid tissue， thyrotropin-releasing hormone receptor （TRHR） and TSHβ in the pituitary tissue， and thyrotropin-releasing hormone （TRH）， CGA， GPX2， and TSHβ in the hypothalamic tissue. ResultsCompared with the normal group， the model group showed significant atrophy and irregularity of thyroid follicles， a marked reduction in colloid secretion， extensive vacuolar degeneration of adenocytes in the anterior pituitary， lowered serum levels of T3， T4， and TSH （P<0.01）， and down-regulated mRNA and protein levels of TSHR in the thyroid tissue， TRHR and TSHβ in the pituitary tissue， and TRH， CGA， GPX2， and TSHβ in the hypothalamic tissue （P<0.01）. Compared with the model group， high- and medium-dose Xiaoyaosan and fluoxetine alleviated the pathological changes in the thyroid and pituitary tissue， outperforming the low-dose Xiaoyaosan group. Moreover， they elevated the serum levels of T3， T4， and TSH （P<0.05， P<0.01）. The serum TSH level was also elevated in the low-dose Xiaoyaosan group （P<0.05）. The mRNA and protein levels of TSHR in the thyroid， TRHR and TSHβ in the pituitary， and TRH， CGA， GPX2， and TSHβ in the hypothalamus were up-regulated in the high- and medium-dose Xiaoyaosan groups （P<0.05， P<0.01）. Additionally， the mRNA and protein levels of TSHβ in the hypothalamus were up-regulated in the low-dose Xiaoyaosan group （P<0.01）. In the fluoxetine group， the mRNA and protein levels of TSHR in the thyroid， TRHR in the pituitary， and TRH， CGA， and GPX2 in the hypothalamus were up-regulated （P<0.05， P<0.01）. ConclusionThe downregulation of CGA/GPX2/TSHβ pathway may be one of the biological mechanisms underlying HPT axis dysfunction in the rat model with the syndrome of liver depression and spleen deficiency. Xiaoyaosan may regulate the HPT axis dysfunction by up-regulating the CGA/GPX2/TSHβ pathway.

Objective: To investigate the mechanism of action of curcumol on mitochondrial autophagy in hepatic stellate cells and its molecular mechanism against liver fibrosis. Methods : Hepatic stellate cells were divided into blank group, model group(lipopolysaccharide 5 mg/L), and low, medium and high curcumol group(12.5, 25 and 50 mg/L); Thiazolyland(MTT) was used to detect the effects of curcumol on the viability of hepatic stellate cells; flow cytometry was used to detect the effects of curcumol on apoptosis of hepatic stellate cells; 5,5′,6,6′-Tetrachloro-1,1′,3,3′-tetraethylimidacarbocyanine iodide(JC-1) was used to detect the mitochondrial membrane potential; effects of curcumol on mitochondrial morphology and autophagosome were detected by transmission electron microscopy; effect of curcumol on mitochondrial localisation were detected by fluorescent probe; Immunoblotting assay was performed to detect the effects of curcumin on PTEN-induced putative kinase 1(PINK1), Parkinson's disease protein(Parkin), microtubule-associated protein light chain 3(LC3), autophagy-associated protein(Beclin1), mitochondrial inner membrane translocase 23(Timm23), mitochondrial outer membrane translocase 20(Tomm20), Bcl-2 associated X protein(Bax), B lymphocytoma-2(Bcl2), cleaved-cysteine protease 3(Caspase3), α-smooth muscle actin(ɑ-SMA), collagen type Ⅰ(Collagen Ⅰ), and collagen type Ⅲ(Collagen Ⅲ) protein expression. Results : Compared with the blank control group, cell proliferation rate, Caspase3, Bcl2, LC3Ⅱ, Beclin1, PINK1, Parkin, ɑ-SMA, CollagenⅠ, CollagenⅢ proteins significantly increased in the model group(P<0.01), co-localisation of mitochondria and lysosomes increased, and the number of mitochondrial autophagosome significantly increased(P<0.01), while Timm23 and Tomm20 proteins, mitochondrial membrane potential decreased significantly(P<0.01), apoptosis rate decreased, and Bax protein expression decreased. Compared with the model group, after curcumol intervention, cell proliferation rate, Bcl2, Timm23, Tomm20, α-SMA, CollagenⅠ and CollagenⅢ protein expression significantly decreased in the curcumol low-, medium-and high-concentration groups(P<0.01), and the mitochondrial membrane potential significantly decreased(P<0.01), whereas apoptosis rate, Caspase3, Bax, LC3Ⅱ, Beclin1, PINK1 and Parkin proteins significantly increased(P<0.05), the co-localisation of mitochondria and lysosomes increased, and the number of mitochondrial autophagosome significantly increased(P<0.01). Conclusion Curcumol exerts ameliorative effects on hepatic fibrosis by modulating mitochondrial hyperautophagy mediated by the PINK1/Parkin signaling pathway, and promoting hepatic stellate cell apoptosis.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Objective To compare the discrepancies among results of three commonly used laboratory direct test methods for maximal oxygen uptake(VO2max),explore their linear regression relationships,mutual predictability and comparability.Methods Using a quasi-experimental design of cluster sampling and within-group interaction design,20 male cross-country skiers were tested for VO2max using the Bruce protocol(Method 1),90-second incremental load exercise on power bicycle(Method 2),and 1-minute incremental load exercise on treadmill(Method 3),with an interval of one week.The indepen-dent and dependent variable were the three VO2max test methods and the VO2max,respectively.Results Significant differences were found in the average VO2max of the three test results,with the value mea-sured by Method 1 ranking the first,followed by that assessed by Method 3 and Method 2(P<0.05).Moreover,the frequency of individual differences in the results of the three methods showed that the VO2max of Method 1 was about 6 and 3 ml/min·kg higher than that measured by Method 2 and 3.However,at the same treadmill speed,the average blood lactate evaluated using Method 3 was higher than Method 1,and the speed reached aerobic and anaerobic thresholds about one speed unit(1 km/h)lower than Method 1.Meanwhile,linear regression analyses of the test results between Method 1 and 2,as well as Method 1 and 3 showed that both the regression models and coefficients were statis-tically significant(P<0.001),with the R-squared values of 9.25 and 9.05,respectively.Conclusion The Bruce protocol performs best in assessing the maximum value of the athlete's VO2max phase,whose results have linear regression relationships with the other two methods,and can be used for pre-dicting their results.Moreover,athletes of different events and levels can choose different VO2max test methods accordingly.Lastly,the speed and heart rate ranges corresponding to the aerobic and anaero-bic thresholds can serve as an effective and convenient method to control the training intensity.

Objective To explore the perioperative safety of video-assisted thoracic surgery (VATS) in Day Care Unit and the risk factors for delayed discharge under centralized management model. Methods The patients with VATS managed by the Day Care Unit of the Drum Tower Hospital Affiliated to Nanjing University Medical School in 2021 were retrospectively collected. The patients’ postoperative data and risk factors for delayed discharge were analyzed. Results A total of 383 patients were enrolled, including 179 males and 204 females with an average age of 46.09±14.82 years. Eleven (2.87%) patients developed grade 3-4 postoperative complications during the hospitalization. Eighteen (4.70%) patients visited unscheduled outpatient clinic within 7 days, and 6 (1.57%) patients were re-hospitalized within 30 days after discharge. The remaining patients had no significant adverse events during the 30-day follow-up. The average length of hospital stay was 2.27±0.35 d. The length of hospital stay was over 48 h in 48 (12.53%) patients. The independent risk factor for delayed discharge was lobectomy or combined resection (OR=3.015, 95%CI 1.174-7.745, P=0.022). Conclusion VATS can be safely conducted under the centralized management in Day Care Unit. The risk factor for delayed discharge is the extent of surgical resection.

Objective To investigate the current status of off-label drug use(OLDU)management in tertiary hospitals of Guizhou province and to provide baseline evidence for developing a unified administration regulation for OLDU in Guizhou province.Methods In line with the relevant policies and regulations,a questionnaire including basic information about the person filling out the form,basic information about the hospitals,and information about OLDU was developed.The questionnaire was sent to 84 tertiary hospitals in Guizhou province through the Wenjuanxing.Results A total of 84 questionnaires were distributed and recovered,with a response rate of 100.00%.Of the 84 hospitals,77 had OLDU,of which 68(88.31%)had established a management system for OLDU.Among the 77 hospitals with OLDU,65(84.42%),42(54.55%),58(75.32%),36(46.75%),15(19.48%),and 21(27.27%)hospitals respectively,required approval from the Committee on Drug Administration and Pharmacotherapy before OLDU,restricted the qualifications of doctors prescribing OLDU,required informed consent from patients or their families before OLDU,recorded the matters and reasons in the medical records of patients treated with OLDU,followed up patients in their files and evaluated the reasonableness of the OLDU,and carried out special reviews for OLDU.Only 30(38.96%)hospitals have set up a catalogue of OLDUs,and 58(75.32%)hospitals have urgent needs to set up a unified provincial catalogue of OLDUs.Conclusion The pharmacy administration level of OLDU in tertiary hospitals of Guizhou province is relatively low,so there is an urgent need to establish a unified OLDU management system and medication catalog.

Auditory neuropathy spectrum disorder (ANSD) represents a variety of sensorineural deafness conditions characterized by abnormal inner hair cells and/or auditory nerve function, but with the preservation of outer hair cell function. ANSD represents up to 15% of individuals with hearing impairments. Through mutation screening, bioinformatic analysis and expression studies, we have previously identified several apoptosis-inducing factor (AIF) mitochondria-associated 1 (AIFM1) variants in ANSD families and in some other sporadic cases. Here, to elucidate the pathogenic mechanisms underlying each AIFM1 variant, we generated AIF-null cells using the clustered regularly interspersed short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system and constructed AIF-wild type (WT) and AIF-mutant (mut) (p.‍T260A, p.‍R422W, and p.‍R451Q) stable transfection cell lines. We then analyzed AIF structure, coenzyme-binding affinity, apoptosis, and other aspects. Results revealed that these variants resulted in impaired dimerization, compromising AIF function. The reduction reaction of AIF variants had proceeded slower than that of AIF-WT. The average levels of AIF dimerization in AIF variant cells were only 34.5%‍‒‍49.7% of that of AIF-WT cells, resulting in caspase-independent apoptosis. The average percentage of apoptotic cells in the variants was 12.3%‍‒‍17.9%, which was significantly higher than that (6.9%‍‒‍7.4%) in controls. However, nicotinamide adenine dinucleotide (NADH) treatment promoted the reduction of apoptosis by rescuing AIF dimerization in AIF variant cells. Our findings show that the impairment of AIF dimerization by AIFM1 variants causes apoptosis contributing to ANSD, and introduce NADH as a potential drug for ANSD treatment. Our results help elucidate the mechanisms of ANSD and may lead to the provision of novel therapies.
Humans ; Apoptosis Inducing Factor/metabolism* ; NAD/metabolism* ; Dimerization ; Apoptosis

Auditory neuropathy spectrum disorder (ANSD) represents a variety of sensorineural deafness conditions characterized by abnormal inner hair cells and/or auditory nerve function, but with the preservation of outer hair cell function. ANSD represents up to 15％ of individuals with hearing impairments. Through mutation screening, bioinformatic analysis and expression studies, we have previously identified several apoptosis-inducing factor (AIF) mitochondria-associated 1 (AIFM1) variants in ANSD families and in some other sporadic cases. Here, to elucidate the pathogenic mechanisms underlying each AIFM1 variant, we generated AIF-null cells using the clustered regularly interspersed short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system and constructed AIF-wild type (WT) and AIF-mutant (mut) (p.T260A, p.R422W, and p.R451Q) stable transfection cell lines. We then analyzed AIF structure, coenzyme-binding affinity, apoptosis, and other aspects. Results revealed that these variants resulted in impaired dimerization, compromising AIF function. The reduction reaction of AIF variants had proceeded slower than that of AIF-WT. The average levels of AIF dimerization in AIF variant cells were only 34.5％?49.7％ of that of AIF-WT cells, resulting in caspase-independent apoptosis. The average percentage of apoptotic cells in the variants was 12.3％?17.9％, which was significantly higher than that (6.9％?7.4％) in controls. However, nicotinamide adenine dinucleotide (NADH) treatment promoted the reduction of apoptosis by rescuing AIF dimerization in AIF variant cells. Our findings show that the impairment of AIF dimerization by AIFM1 variants causes apoptosis contributing to ANSD, and introduce NADH as a potential drug for ANSD treatment. Our results help elucidate the mechanisms of ANSD and may lead to the provision of novel therapies.

Objective To investigate the molecular characteristics of immune response signaling molecules induced by transfection of coxsackievirus B2 ( CVB2 ) structural proteins into epithelial cells. Methods Recombinant eukaryotic expression plasmids containing the coding regions of CVB2 structural proteins VP1-VP4 were constructed and then transfected into 16HBE cells. Culture supernatants and cell ly-sates of the transfected 16HBE cells were collected. Expression of signaling molecules involved in innate im-mune responses in transfected 16HBE cells at mRNA level was detected by RT-Q-PCR. The proliferation of T cells co-cultured with culture supernatants and cell lysates of the transfected 16HBE cells was analyzed by ELISPOT. Results Expression of innate immunity-related signaling molecules such as TGF-β-activated ki-nase ( TAK) , NF-κB-inducing kinase ( NIK) , IκB kinase α ( IKKα) and IFN-β at mRNA level was up-regulated in 16HBE cells transfected with CVB2 structural proteins VP1-VP4. Both culture supernatants and cell lysates of the transfected 16HBE cells enhanced the proliferation of T cells. Conclusions CVB2 struc-tural proteins VP1-VP4 could enhance the expression of innate immunity-related signaling molecules to var-ying degrees and promote the activation of adaptive immunity.