Chronic obstructive pulmonary disease （COPD） is a chronic respiratory disease that poses a significant threat to global health， exhibiting high morbidity， disability and mortality rate， with its prevention and treatment situation becoming increasingly critical. The pathogenesis of COPD is complex， and the underlying cellular and molecular biological mechanisms remain incompletely elucidated. Programmed cell death （PCD） is the process wherein cells actively undergo demise to maintain internal environmental stability in response to certain signals or specific stimuli. Contemporary medical research indicates that the dysregulation of PCD patterns such as apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis is closely related to the onset and progression of COPD. Clarifying the molecular mechanisms of PCD in COPD may provide novel perspectives for in-depth understanding and prevention of the disease. Traditional Chinese medicine （TCM） is characterized by holistic regulation. In recent years， extensive research has been conducted in the TCM field focusing on modulating apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis for the treatment of COPD， yielding remarkable achievements. Therefore， this study systematically explored the molecular mechanism of PCD in COPD and reviewed the potential mechanisms and intervention status of TCM targeting PCD in COPD， aiming to provide insights and references for the clinical prevention， treatment and in-depth research of COPD.

Chronic obstructive pulmonary disease （COPD） is a chronic respiratory disease that poses a significant threat to global health， exhibiting high morbidity， disability and mortality rate， with its prevention and treatment situation becoming increasingly critical. The pathogenesis of COPD is complex， and the underlying cellular and molecular biological mechanisms remain incompletely elucidated. Programmed cell death （PCD） is the process wherein cells actively undergo demise to maintain internal environmental stability in response to certain signals or specific stimuli. Contemporary medical research indicates that the dysregulation of PCD patterns such as apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis is closely related to the onset and progression of COPD. Clarifying the molecular mechanisms of PCD in COPD may provide novel perspectives for in-depth understanding and prevention of the disease. Traditional Chinese medicine （TCM） is characterized by holistic regulation. In recent years， extensive research has been conducted in the TCM field focusing on modulating apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis for the treatment of COPD， yielding remarkable achievements. Therefore， this study systematically explored the molecular mechanism of PCD in COPD and reviewed the potential mechanisms and intervention status of TCM targeting PCD in COPD， aiming to provide insights and references for the clinical prevention， treatment and in-depth research of COPD.

Aim Based on coronary CT-fractional flow reserve(CT-FFR)combined with machine learning methods,a nomogram prediction model for coronary in-stent restenosis(ISR)was developed to assess the risk of ISR.Methods Retrospective analysis was performed on patients who underwent re-examination after PCI at our hospital from January 2022 to January 2025.According to the exclusion criteria,a total of 210 patients were enrolled,including 100 cases of ISR and 110 cases of non-ISR.The dataset was randomly divided into training and test sets at a 7∶3 ratio.Af-ter univariate analysis to screen potential predictors,LASSO regression was applied to identify feature variables with non-ze-ro coefficients.Subsequently,three machine learning(ML)algorithms including random forest(RF),support vector machine(SVM),and extreme gradient boosting(XGB)were used to rank the importance of the significant factors.The intersection of the top 10 variables from each algorithm was used as input for bidirectional stepwise multivariate Logistic re-gression.An ISR risk score was then constructed and visualized using a nomogram.Results A total of 14 predictive factors were identified through LASSO regression,including diastolic blood pressure,C-reactive protein,triglycerides(TG),N-terminal pro-brain natriuretic peptide(NT-proBNP),low density lipoprotein cholesterol(LDLC),minimum stent diameter＜3 mm,systolic blood pressure,△CT-FFR,CT-FFR,interleukin-6(IL-6),body mass index,glycosylated hemoglobin(HbA1c),history of hypertension,and high density lipoprotein cholesterol(HDLC).Following stepwise screening using three ML algorithms and Logistic regression,six independent risk factors for ISR were identified:elevated△CT-FFR,IL-6,NT-proBNP,TG and CT-FFR values,and minimum stent diameter＜3 mm.The area under the curve for the training set and test set were 0.995(95％CI:0.989～1.000)and 0.965(95％CI:0.927～1.000),respectively.Decision curve analysis demonstrated high net benefit across threshold probabilities of 0～1.00 in the training set and 0～0.92 in the test set.The nomogram integrating these six predictors exhibited high accuracy and clinical utility.Con-clusion The ISR nomogram prediction model based on LASSO-ML combined with CT-FFR technology has high accuracy and clinical utility for ISR.

Objective To construct a prognostic model of future asthma exacerbation risk in adults by com-bining novel biomarkers of serum chitinase-3-like protein 1(YKL-40),dipeptidyl peptidase-4(DPP4)and conventional predictors.Methods Patients with asthma in the non-acute exacerbation phase were recruited from the People's Hospital of Yubei District of Chongqing,from March 2022 to May 2023.Baseline clinical da-ta collected included medical history,forced expiratory volume in the first second(FEV1)/forced vital capacity(FVC),percentage of predicted forced expiratory volume in the first second(FEV1％pred),blood eosinophil count(EOS),blood neutrophil count(NEU),fractional exhaled nitric oxide(FeNO),serum YKL-40,and ser-um DPP4,etc.The patients were followed for one year to gather data on asthma acute exacerbations and their timings as defined in this study.A COX proportional hazards regression model was used to construct a prog-nostic model for future asthma exacerbations,with internal validation and results presentation.Results A to-tal of 224 patients with asthma completed the study.During the one-year follow-up period,102 patients experi-enced acute exacerbations as defined in this study.Based on univariate COX regression,stepwise regression for variable selection,clinical significance,and model simplicity,asthma control test(ACT)score group,number of asthma exacerbations in the past year group,log10(YKL-40),log10(FeNO),log10(EOS),and FEV1％pred were the following predictors were included in the final model.The overall C-statistic of the model was 0.795(95％CI:0.754-0.836),the area under the curve at the 52-week follow-up was 0.879(95％CI:0.834-0.924),and the Brier score at the 52-week follow-up was 0.142(95％CI:0.117-0.168).The calibration curve was close to a slope of 1,and bootstrap validation suggested good stability of the prediction model.The model was presented using a Nomogram and a dynamic scoring table in a web APP,which can be used to predict the risk of asthma exacerbations within 52 weeks for individual patients.Conclusion The prediction model based on serum YKL-40,EOS,FeNO,the number of asthma exacerbation in the past year group,FEV1％pred and ACT scores group can accurately predict the probability of acute attacks in 52 weeks of asthma patients.

The principle of treating different diseases with the same therapy is the essence of syndrome differentiation and treatment in traditional Chinese medicine （TCM）. It means that when the same pathogenic changes or the same symptoms appear in the development of different diseases， the same principles or methods can be used for treatment. Due to the complexity and high variability of viral pathogenicity， the precise and effective treatment of different types of viral pneumonia （VP） has always been a research focus and difficulty in modern medicine. VP belongs to the category of external-contraction febrile disease， warm disease， and epidemic in TCM. Haoqin Qingdantang （HQQDD） is a representative formula for clearing heat and dispelling dampness in warm diseases， and its intervention in VP caused by various viral infections has significant effects. This study， guided by the theory of treating different diseases with the same therapy， links the related studies on using HQQDD to treat different types of VP and finds that influenza virus pneumonia （IVP）， severe acute respiratory syndrome （SARS）， and COVID-19 all have a common pathogenic mechanism of dampness-heat at different stages of respective diseases. When these diseases are dominated by damp-heat factors， the use of HQQDD yields remarkable therapeutic effects. Modern pharmacological studies have confirmed that HQQDD can inhibit virus replication， reduce fever reactions， inhibit the expression of inflammatory mediators， and regulate immune balance. Moreover， the sovereign medicine in this formula has excellent antiviral activity， and the formula reflects rich scientific connotations of treating VP. According to the theory of treating different diseases with the same therapy and based on the effective treatment practice and modern pharmacological research of HQQDD for different types of VP， this paper mines the underlying TCM theory of treatment with the same therapy， explores the syndrome differentiation and treatment strategy and effect mechanism of this formula for different types of VP， and analyzes the treatment mechanism and characteristics， with the aim of providing evidence and reference for the clinical application and modern research of HQQDD.

Pneumonia is an infectious disease with high morbidity and mortality worldwide， and its damage to the body is not limited to the acute phase. The theory of combination of pathogenic factors emphasizes that the combination of new pathogens and residual pathogens in the body leads to the occurrence of diseases， which generalizes the causes of recurrence during pneumonia recovery. During the recovery stage of pneumonia， pathological changes such as disturbance of immune homeostasis， persistent low-grade inflammation， and microvascular damage continue to affect the body function， impair the health and quality of life of patients， and increase the risk of secondary infection. According to the theory of traditional Chinese medicine （TCM）， pneumonia is caused by deficiency， and Qi deficiency and blood stasis is the core pathogenesis in the recovery stage. At this time， the body is not full of healthy qi and still has residual pathogens， and thus it is susceptible to external pathogenic factors that lead to disease recurrence. As an important part of the TCM philosophy of treating disease before its onset， prevention of recurrence after recovery emphasizes the need for aftercare in the recovery stage to prevent disease recurrence. Based on the pathogenesis theory of combination of pathogenic factors and the pathogenesis of Qi deficiency and blood stasis， this paper discusses the effect and connotation of TCM in regulating immune inflammation and microvascular damage in preventing recurrence of pneumonia during the recovery stage， aiming to develop new ideas for effective prevention and treatment of pneumonia at this stage.

Bone grafting is a primary method for treating bone defects. Among various graft materials, xenogeneic bone substitutes are widely used in clinical practice due to their abundant sources, convenient processing and storage, and avoidance of secondary surgeries. With the advancement of domestic production and the limitations of imported products, an increasing number of bone filling or grafting substitute materials isentering clinical trials. Relevant experts have drafted this consensus to enhance the management of medical device clinical trials, protect the rights of participants, and ensure the scientific and effective execution of trials. It summarizes clinical experience in aspects, such as design principles, participant inclusion/exclusion criteria, observation periods, efficacy evaluation metrics, safety assessment indicators, and quality control, to provide guidance for professionals in the field.
Humans ; Bone Substitutes/therapeutic use* ; Randomized Controlled Trials as Topic/methods* ; Consensus ; Bone Transplantation ; Research Design

Aim Based on coronary CT-fractional flow reserve(CT-FFR)combined with machine learning methods,a nomogram prediction model for coronary in-stent restenosis(ISR)was developed to assess the risk of ISR.Methods Retrospective analysis was performed on patients who underwent re-examination after PCI at our hospital from January 2022 to January 2025.According to the exclusion criteria,a total of 210 patients were enrolled,including 100 cases of ISR and 110 cases of non-ISR.The dataset was randomly divided into training and test sets at a 7∶3 ratio.Af-ter univariate analysis to screen potential predictors,LASSO regression was applied to identify feature variables with non-ze-ro coefficients.Subsequently,three machine learning(ML)algorithms including random forest(RF),support vector machine(SVM),and extreme gradient boosting(XGB)were used to rank the importance of the significant factors.The intersection of the top 10 variables from each algorithm was used as input for bidirectional stepwise multivariate Logistic re-gression.An ISR risk score was then constructed and visualized using a nomogram.Results A total of 14 predictive factors were identified through LASSO regression,including diastolic blood pressure,C-reactive protein,triglycerides(TG),N-terminal pro-brain natriuretic peptide(NT-proBNP),low density lipoprotein cholesterol(LDLC),minimum stent diameter＜3 mm,systolic blood pressure,△CT-FFR,CT-FFR,interleukin-6(IL-6),body mass index,glycosylated hemoglobin(HbA1c),history of hypertension,and high density lipoprotein cholesterol(HDLC).Following stepwise screening using three ML algorithms and Logistic regression,six independent risk factors for ISR were identified:elevated△CT-FFR,IL-6,NT-proBNP,TG and CT-FFR values,and minimum stent diameter＜3 mm.The area under the curve for the training set and test set were 0.995(95％CI:0.989～1.000)and 0.965(95％CI:0.927～1.000),respectively.Decision curve analysis demonstrated high net benefit across threshold probabilities of 0～1.00 in the training set and 0～0.92 in the test set.The nomogram integrating these six predictors exhibited high accuracy and clinical utility.Con-clusion The ISR nomogram prediction model based on LASSO-ML combined with CT-FFR technology has high accuracy and clinical utility for ISR.

Objective:To classify the etiology of secondary hemophagocytic syndrome (sHLH) and explore its clinical, laboratory and therapeutic characteristics in order to deepen the understanding of the disease.Method:A retrospective observational study was conducted on sHLH patients who were treated at Peking University People's Hospital from January 2016 to December 2021. Patients under the age of 18 and those with missing clinical data were excluded. The distribution of departments visited and etiologies of sHLH were analyzed. Baseline data, clinical characteristics, complications, laboratory data, treatment, and in-hospital outcomes of sHLH were collected. The sHLH patients were then divided into 3 groups including malignancy group, macrophage activation syndrome (MAS) group and other etiologies (mainly infection) group. Intergroup comparisons were performed using chi-square tests, analysis of variance, Mann-Whitney tests, and other statistical methods.Results:A total 169 patients were enrolled, among these patients, 27.8% were malignancy-related HLH, 47.9% were MAS, and 24.3% were other etiologies related HLH. Statistical analysis revealed that the clinical characteristics of other etiological group was highly consistent with the malignancy group, including more and severer peripheral blood cell reduction, higher sCD25 levels, more Epstein-Barr virus infection, and the prognosis was similar, both were with more than 50% in-hospital mortality. And the incidence of hemophagocytosis was highest in other etiological groups (65.9%). In contrast, MAS group was with an obviously lower mortality of 17.3% ( P<0.05). Meanwhile, treatments including methylprednisolone pulse, cyclosporine A and interleukin-2 were used frequently in MAS group. Conclusion:Malignancy related HLH and other etiologies related HLH exhibit more similar clinical characteristics and prognosis, while the MAS group, has a milder overall condition and better prognosis.

Objective To investigate the clinical characteristics of Charcot-Marie-Tooth disease(CMT),and conduct genetic analysis.Methods The clinical data of 2 families were retrospectively analyzed.Results The proband of family 1 had atrophy of bilateral thigh and calf muscles,serum creatine kinase(CK)was 292 U/L,and EMG examination showed peripheral nerve damage of upper and lower limbs(mainly axonal).Genetic testing revealed that the proband carried a heterozygous mutation of NEFH:NM＿02107:c.3057dupG:p.K1020Efs*43.According to American College of Medical Genetics and Genomics(ACMG),the variant of NEFH gene was interpreted as likely pathogenic(PS3＿moderate+PM2+PM4+PP1).The proband of family 2 had scoliosis,calf muscle atrophy,flat foot,blood creatine kinase 80 U/L,and EMG examination showed peripheral nerve damage in the upper and lower limbs(mainly axonal).Genetic testing revealed that the proband carried a heterozygous mutation of the MFN2:NM＿014874:c.746C＞G:p.S249C.This mutation had not been reported and included in the relevant literature,and was likely to be pathogenic according to the ACMG regulation rating(Likely Pathogenic:PM1+PM2+PM5+PP3).Conclusions The clinical manifestations of the two families are muscle weakness with muscle atrophy,normal or mild elevation of creatine kinase,disappearance of tendon reflex,arched foot,and electromyography indicating neurogenic damage.Gene testing reveals that the probands carried heterozygous mutations in the NEFH and MFN2 genes,respectively.