Objective To systematically analyze the spatiotemporal distribution characteristics and epidemiological trends of tracheal, bronchus, and lung cancer (TBL) disease burden attributed to air pollution globally and in China and the United States from 1990 to 2021, and to assess the patterns of disease burden changes from 2022 to 2031 based on predictive models, providing a scientific basis for formulating targeted TBL prevention and control strategies. Methods Based on the Global Burden of Disease (GBD) 2021 database, we analyzed the disease burden data of TBL attributed to air pollution globally and in China and the United States from 1990 to 2021. R Studio 4.3.2 software was used to analyze the corresponding trends and the Bayesian age-period-cohort (BAPC) prediction model was used to predict the status of the disease burden of TBL attributed to air pollution in the world and in China and the United States from 2022 to 2031. Results In 2021, China had the highest number of deaths and disability-adjusted life years attributed to air pollution (211 400 patients and 4.8947 million person-years), followed by the United States (6 000 patients and 124 300 person-years). The age-standardized mortality rate (ASMR) and age-standardized disability-adjusted life years rate (ASDR) of TBL due to air pollution in the world and in China and the United States showed a decreasing trend. From 1990 to 2021, the ASMR and ASDR of TBL in China due to air pollution were much higher than those in the United States and the global average. In terms of gender, from 1990 to 2021, the disease burden of male patients with TBL attributed to air pollution was much higher than that of female patients. The BAPC prediction model showed that from 2022 to 2031, the ASMR and ASDR of TBL attributed to air pollution showed an upward trend globally, while they showed a downward trend in China and the United States. Conclusion Over the past 30 years, the air pollution-related TBL disease burden in the world and in China and the United States has continued to decline, but China's disease burden is still significantly higher than the global average. The disease burden in men far exceeds that in women, with men and the population aged ≥50 years being high-risk groups. In the future, the global disease trend may reverse and rise, while China and the United States are expected to continuously decline. However, precise prevention and control for high-risk groups remains a key challenge.

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 explore the role of fibroblast growth factor 21 (FGF21) in rats with severe acute pancreatitis-associated acute lung injury (SAP-ALI) and its related molecular mechanisms.Methods:Twenty-four healthy male SD rats were randomly divided into 4 groups (random number, n=6 per group): Control group, SAP group, FGF21 intervention group (SAP+FGF21 group), and autophagy inhibitor group (SAP+FGF21+3-MA group). The SAP model was established by retrograde injection of 3.5% sodium taurocholate into the pancreatic duct. In SAP+FGF21 group, FGF21 10 mg/kg was intraperitoneally injected at 1 hour before modeling. In SAP+FGF21+3-MA group, FGF21 10 mg/kg and 3-MA 20 mg/kg were intraperitoneally injected at 1 h before modeling. Serum amylase activity was detected by biochemical kit. Plasma levels of tumor necrosis factor alpha (TNF-α) and FGF21 were detected by ELISA. HE staining was used to observe the pathological changes of pancreas and lung tissues. Immunofluorescence was used to detect the protein level of FGF21 in lung tissue. Western blot was used to detect the expression levels of autophagy-related proteins in lung tissue. Autophagosomes in lung tissue were observed by electron microscopy. Results:Compared with the Control group, the plasma and lung tissue FGF21 levels in SAP group were significantly decreased (both P<0.001) , severe pancreatic and lung tissue damage, and elevated plasma TNF-α levels ( P<0.001). Western Blot and transmission electron microscopy showed that: The expression of LC3Ⅱ/Ⅰ in lung tissue of SAP group was down-regulated [(0.912±0.052) vs. (0.700±0.135), P<0.001], and P62 protein level was up-regulated [(0.475±0.068) vs. (0.687±0.070), P<0.001] , and reduced autophagosome counts in the SAP group. In contrast, the SAP+FGF21 group showed elevated FGF21 levels (both P<0.01), attenuated pancreatic and lung injury ( P<0.001), decreased TNF-α levels [(280.10±49.36) pg/mL vs. (86.32±66.00) pg/mL, P<0.001]. Lung tissue of LC3 Ⅱ/Ⅰ levels increase [(0.700±0.135) vs. (0.853±0.073), P<0.01], P62 protein levels cut [(0.687±0.070) vs. (0.538±0.030), P<0.01] ], and increased autophagosomes and autolysosomes under electron microscopy. Compared with SAP+FGF21 group, the expression levels of FGF21 in plasma and lung tissue in SAP+FGF21+3-MA group were not significantly changed, and the level of autophagy was decreased. Pancreas and lung tissue injury was severe ( P<0.001), Plasma TNF-α level obviously higher [(86.32±66.00) pg/mL vs. (212.90±11.56) pg/mL, P<0.05]. Conclusion:FGF21 may play a protective role in SAP-ALI by up-regulating the level of autophagy.

Objective To utilize single-cell and peripheral blood transcriptomic data from 3D brain organoids,combined with machine learning,to analyze the role of mitochondrial autophagy genes in schizophrenia(SCZ).Methods By integrating two machine learning algorithms,we identified differentially expressed mitochondrial autophagy-related genes between schizophrenia patients and healthy controls using peripheral blood RNA sequencing data.The relationship between mitophagy gene,immune cells and inflammatory factors was further explored.Comprehensive single-cell analysis was used to explore the signaling pathways and specific transcription factors based on mitophagy genes.Results Using machine learning,seven key mitophagy genes expressed in schizophrenia patients were identified.Based on Mitoscore analysis,at the single-cell level,neurons with high mitochondrial autophagy activity(Mitohigh_Neuron)formed new interactions with endothelial cells via the SPP1 signaling pathway.Conclusion This study identified two subtypes of mitophagy and seven key mitophagy genes in schizophrenia,providing new insights into the pathogenesis of the disease.

BACKGROUND:Psoralen has a strong anti-osteoporotic activity and may have a restorative effect on chemotherapy-induced osteoporosis. OBJECTIVE:To explore the restorative effect of psoralen on the osteogenic differentiation of bone marrow mesenchymal stem cells in mice inhibited by cyclophosphamide and its mechanism. METHODS:C57BL/6 mouse bone marrow mesenchymal stem cells were isolated and cultured.Effect of psoralen on viability of bone marrow mesenchymal stem cells was detected by MTT assay.Osteogenic induction combined with alkaline phosphatase staining was used to determine the optimal dose of psoralen to restore the osteogenic differentiation of bone marrow mesenchymal stem cells inhibited by cyclophosphamide.The mRNA expression levels of Runx2,alkaline phosphatase,Osteocalcin,osteoprotegerin,and Wnt/β-catenin signaling pathway-related genes Wnt1,Wnt4,Wnt10b,β-catenin,and c-MYC were measured by RT-qPCR at different time points under the intervention with psoralen.The protein expression of osteogenic specific transcription factor Runx2 and Wnt/β-catenin signaling pathway related genes Active β-catenin,DKK1,c-MYC,and Cyclin D1 was determined by western blot assay at different time points under the intervention with psoralen. RESULTS AND CONCLUSION:(1)There was no significant effect of different concentrations of psoralen on the viability of bone marrow mesenchymal stem cells.The best recovery of the inhibition of osteogenic differentiation of bone marrow mesenchymal stem cells caused by cyclophosphamide was under the intervention of psoralen at a concentration of 200 μmol/L.(2)Psoralen reversed the reduction in osteogenic differentiation marker genes Runx2,alkaline phosphatase,Osteocalcin and osteoprotegerin mRNA expression and Runx2 protein expression in bone marrow mesenchymal stem cells caused by cyclophosphamide conditioned medium.(3)Psoralen reversed the decrease in Wnt/β-catenin pathway-related genes Wnt4,β-catenin,c-MYC mRNA and Active β-catenin,c-MYC,and Cyclin D1 protein expression and the increase in DKK1 protein expression in bone marrow mesenchymal stem cells caused by cyclophosphamide conditioned medium.(4)The results showed that cyclophosphamide inhibited osteogenic differentiation of bone marrow mesenchymal stem cells in mice,and psoralen had a restorative effect on it.The best intervention effect was achieved at a concentration of 200 μmol/L psoralen,and this protective effect might be related to the activation of Wnt4/β-catenin signaling pathway by psoralen.

Objective:To investigate altered neurovascular coupling in patients with depression(DEP)using resting-state functional magnetic resonance imaging(MRI)and arterial spin labeling perfusion MRI,as well as its association with depressive symptoms.Methods:Neuropsychological assessment and multimodal MRI scans were performed for 25 DEP patients and 35 healthy controls(HCs).Arterial spin labeling perfusion MRI was used to calculate cerebral blood flow(CBF),and functional MRI was used to calculate regional homogeneity(ReHo).The Pearson correlation coefficient between CBF and ReHo was calculated to obtain neurovascular cou-pling.Results:At the whole-brain level,CBF-ReHo coupling was reduced in DEP patients compared with HCs.At the brain region level,CBF-ReHo coupling was reduced in 26 brain regions in DEP patients,which were mainly located in the visual network,the default network,and the auditory network.The correlation analysis showed that the coupling values of the left suboccipital gyrus,the left angular gyrus,and the left thalamus were negatively correlated with Hamilton Depression Scale score.Conclusion:There is a sig-nificant reduction in neurovascular coupling in DEP patients,which is correlated with the severity of DEP.

Objective To investigate the clinical application of ceftazidime/avibactam(CAZ/AVI)in lung trans-plant recipients with pulmonary infection caused by carbapenem-resistant Gram-negative bacilli(CRGNB),and ana-lyze the factors affecting the prognosis.Methods Lung transplant recipients who had CRGNB pulmonary infection and were treated with CAZ/AVI were included in the analysis.Based on 14-day clinical response,14-day microbial response,and 30-day survival status,the recipients were divided into a clinical response group and a clinical failure group,a microbial response group and a microbial failure group,as well as a survival group and a death group,re-spectively.Univariate analysis was conducted on various data from the two groups.Factors affecting therapeutic ef-ficacy and survival were included in a binary logistic regression model.Independent risk factors for CAZ/AVI anti-infective efficacy and all-cause mortality outcomes were analyzed.Results A total of 43 recipients were included.After 14-day anti-infective treatment,32 recipients(74.42％)achieved clinical response,and 30 recipients(69.77％)achieved microbial response.34 recipients(79.07％)survived 30 days after CAZ/AVI treatment.The Charlson comorbidity index(CCI),proportion of renal dysfunction,and incidence of shock in recipients in the clini-cal response group were all lower than those in the clinical failure group(P＜0.05),while the serum albumin(ALB)level was higher(P＜0.05).The incidence of shock in recipients in the microbial response group was lower than that in the microbial failure group(P＜0.05).CCI,proportion of renal dysfunction,and incidence of shock in recipients in the survival group were all lower than those in the death group(all P＜0.05),while ALB level was higher during treatment period(P＜0.05).Multivariate analysis of 14-day clinical response and 30-day survival showed that higher CCI was an independent risk factor affecting 14-day clinical response of recipients(OR=2.22,95％CI:1.07-4.63),while lower ALB levels(OR=0.72,95％CI:0.54-0.98)and higher CCI(OR=5.27,95％CI:1.18-23.58)were independent risk factors for 30-day all-cause mortality in recipients with pulmonary in-fection after lung transplant.Conclusion CAZ/AVI may be an effective drug for treating pulmonary infection caused by CRGNB in lung transplant recipients.Higher CCI is an independent risk factor for 14-day clinical failure in recipients after CAZ/AVI treatment.Lower ALB level and higher CCI are independent risk factors for increased 30-day mortality in recipients.

Objective:To summarize the characteristics and treatment strategies of tissue expander infections in auricular reconstruction using tissue expansion, providing references for the prevention and treatment of expander infections.Methods:A retrospective analysis was conducted on the data of patients who underwent auricular reconstruction using tissue expansion from January 2018 to January 2024 in the Plastic Surgery Hospital of Chinese Academy of Medical Sciences. Patients meeting the inclusion criteria were included in the study. The causes of expander infections were summarized. Infections were categorized based on time periods (perioperative, inflation period, skin expansion period) and severity (mild, severe). The management and healing outcomes of different types of expander infections were recorded and their incidence rates were calculated. Descriptive statistical method were employed for analysis.Results:A total of 39 patients were included, with 25 males (64.1%) and 14 females (35.9%). The age was (8.2 ±1.9) years (range 5-13 years). Regarding infection causes, folliculitis of the expanded flap was noted in 9 cases (23.1%), inflation procedures in 10 cases (25.6%), insect bites in 2 cases (5.1%), and no obvious cause in 18 cases (46.2%). Perioperative infections occurred in 3 cases (7.7%), inflation period infections in 30 cases (76.9%), and skin expansion period infections in 6 cases (15.4%). Mild infections were present in 21 cases (53.8%) and severe infections in 18 cases (46.2%). After successful treatment of expander infections, 34 patients (87.2%) completed the second stage of reconstruction, while the remaining 5 cases(12.8%) had the expander removed and received ear reconstruction six months later.Conclusion:Infections of expanders during auricular reconstruction using tissue expansion are more common during the inflation period. Early management of potential causes of expander infections can reduce the risk of infection.

BACKGROUND:Previous studies have demonstrated that acupuncture at the governor meridian has precise efficacy in the treatment of ischemic stroke and can improve cerebral ischemia-reperfusion injury by attenuating pyroptosis,but the upstream regulatory mechanisms are not yet fully clarified.OBJECTIVE:To observe the neuroprotective effect of electroacupuncture in model rats of cerebral ischemia-reperfusion injury.METHODS:Twenty-seven Sprague-Dawley rats were randomly divided into sham surgery,model,and electroacupuncture groups,with nine rats in each group.Modified suture method was used to establish cerebral ischemia-reperfusion model rats in the model and electroacupuncture groups.The electroacupuncture group was subjected to electroacupuncture at"Baihui,""Fengfu,"and"Dazhui"acupoints,20 minutes each,once a day,for 7 consecutive days.After treatment,neurological deficit scoring and pole test were performed to assess behavioral changes.Tri-phenyl tetrazolium chloride staining was used to assess cerebral infarction size in rats.Hematoxylin-eosin staining was performed to observe morphological changes in cerebral cortex tissue on the infarcted side of rats.Immunofluorescence analysis was used to determine Iba-1 and reactive oxygen species levels in cerebral cortex tissue on the infarcted side of rats,ELISA method was used for measuring interleukin-1β,interleukin-6 and tumor necrosis factor α levels in cerebral cortex tissue on the infarcted side of rats.Real-time fluorescence quantitative PCR and western blot were used to detect mRNA and protein expression levels of thioredoxin interaction protein,nod-like receptor associated protein 3(NLRP3),Caspase-1 and interleukin-1β in cerebral cortex tissue on the infarcted side of rats respectively,and the interaction between thioredoxin interaction protein and NLRP3 was analyzed by immunoprecipitation.RESULTS AND CONCLUSION:(1)Compared with the sham surgery group,rats in the model group showed an increase in neurological deficit score,pole test score,cerebral infarction volume(P<0.05),the immunofluorescence expression of Iba-1 and reactive oxygen species(P<0.05),the levels of interleukin-1β,interleukin-6 and tumor necrosis factor α(P<0.05),and the mRNA and protein expression of thioredoxin interaction protein,NLRP3,Caspase-1 and interleukin-1β in cerebral cortex tissue(P<0.05).Hematoxylin-eosin staining in the model group showed neuronal degeneration and necrosis,with fragmented and dissolved nuclei and cellular vacuoles.(2)Compared with the model group,rats in the electroacupuncture group showed a reduction in neurological deficit score,pole climbing test score,cerebral infarction volume(P<0.05),the immunofluorescence expression of Iba-1 and reactive oxygen species(P<0.05),the levels of interleukin-1β,interleukin-6 and tumor necrosis factor α(P<0.05),and the mRNA and protein expression of thioredoxin interaction protein,NLRP3,Caspase-1 and interleukin-1β in cerebral cortex tissue(P<0.05).Hematoxylin-eosin staining showed that the pathological damage of neurons in cerebral cortex tissue on the infarcted side of rats in the electroacupuncture group was significantly attenuated,with significantly reduced cell necrosis and vacuolation.(3)Immunoprecipitation assay showed an interaction between thioredoxin interaction proteins and NLRP3 in the cerebral cortical tissues on the infarcted side of rats in the model group.To conclude,electroacupuncture has a significant therapeutic effect against cerebral ischemia-reperfusion injury,possibly by inhibiting the reactive oxygen species/thioredoxin interaction protein/NLRP3 cell pyroptosis signaling pathway and activation of microglia to reduce the release of inflammatory factors.