Gorham-Stout disease(GSD) is a rare osteolytic disorder characterized by spontaneous and progressive osteolysis, along with abnormal angiogenesis and lymphangiogenesis, with no new bone formation. We present a case of a 15-year-old female admitted due to " recurrent right leg pain for 5 years, 11 months after undergoing right femoral fracture surgery". Through comprehensive integration of the patient's clinical phenotype, laboratory tests, imaging findings, pathological examinations, and molecular biological test results, GSD was considered highly likely. A multidisciplinary treatment approach was conducted, including a combination of zoledronic acid and sirolimus to inhibit osteolysis, along with rehabilitation training and orthopedic intervention, providing a personalized and comprehensive treatment strategy.

Digestive system tumors are the leading cause of cancer incidence and mortality globally， and their occurrence and development generally follow the key pathological process of inflammation-cancer transformation. Therefore， intervening in the precancerous lesion stage is an important strategy to block malignant transformation of the disease and reduce the incidence rate of tumors. Banxia Xiexin Tang-related prescriptions （including Banxia Xiexin Tang， Shengjiang Xiexin Tang， and Gancao Xiexin Tang） originated from the Shanghan Zabinglun They follow the principle of pungent dispersing and bitter descending， combination of cold and warm medicinals， and tonifying deficiency and purging excess， which aligns with the core pathogenesis of digestive system precancerous lesions characterized by cold-heat intermingling and disorder of ascending and descending. These prescriptions are widely used in the clinical treatment of various digestive system inflammatory disorders such as atrophic gastritis， ulcerative colitis， and reflux esophagitis. This review systematically summarizes the theoretical basis， clinical evidence， and therapeutic mechanisms of such prescriptions in preventing and treating the inflammation-cancer transformation process in the digestive system. Clinical studies have shown that whether used alone or in combination with modern therapies， Banxia Xiexin Tang can effectively alleviate symptoms， repair histopathological changes， and improve patients' quality of life. Basic research further reveals that their efficacy stems from multi-target systemic regulatory effects： ameliorating the chronic inflammatory microenvironment， antagonizing oxidative stress， reshaping the gut microbiota， restoring the immune balance， regulating cell proliferation and apoptosis， etc. On the basis of the convergence of traditional Chinese and Western medicine understanding of inflammation-cancer transformation， this article constructs a research framework centered on regulating the inflammatory microenvironment homeostasis to systematically elucidate the mechanism of treating different diseases with the same method （Banxia Xiexin Tang）. In view of the limitations of current research in terms of evidence level， disease-syndrome combination models， and overall mechanism analysis of compound prescriptions， this article proposes future research directions of integrating high-quality clinical research， systems biology， and cutting-edge technologies， providing a new theoretical basis and translational ideas for the precise prevention and control of digestive system tumors with traditional Chinese medicine.

The introduction of national dementia action plans will further drive the development of service systems for the continuum of care for cognitive disorders. However， current healthcare delivery models are often plagued by resource wastage and inefficiency. Grounded in the medical service chain theory， integrating healthcare and social resources through service teams to build a more efficient service system centered on patients' needs holds promise for improving both the quality and efficiency of care. This article reviews the construction of the continuum of care service chain for cognitive disorders， analyzes the potential value of social prescribing as an innovative service model， and explores the role of digital platforms in optimizing care process coordination and enabling information sharing， with the aim of providing a practical reference for the coordinated operation of the continuum of care for cognitive disorders.

Objective:To investigate the characteristics of resting-state mirror homotopic connectivity and the gray matter volume of brain in patients with neuropsychiatric systemic lupus erythematosus (NPSLE).Methods:From June 2020 to March 2023, a total of 35 NPSLE patients (NPSLE group) and 30 non-NPSLE patients (non-NPSLE group) were selected from Taizhou People's Hospital Affiliated to Nanjing Medical University, another 31 healthy volunteers were recruited as the healthy controls(HC group). All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) and mini-mental state examination (MMSE) assessments. The patients in NPSLE and non-NPSLE groups were additionally assessed using the fatigue scale for motor and cognitive functions (FSMC) and the hospital anxiety and depression scale (HADS).The DPABI V7.0 toolkit based on the MATLAB platform was used to preprocess the rs-fMRI data and calculate the voxel-mirrored homotopic connectivity(VMHC) indexes, and the differences in VMHC between groups were evaluated by covariance analysis in SPM12.0 software, and the VMHC values of brain regions with significant differences were extracted for further comparison between the two groups.Partial correlation analysis was performed to investigate the association between VMHC values and clinical parameters in NPSLE patients.The brain regions with significant differences between NPSLE patients and non-NPSLE patients were used as region of interest (ROI), and gray matter volumes within these ROIs were then calculated by VBM8 toolbox.Results:(1)There were statistically significant differences in the VMHC values of bilateral precentral gyrus, bilateral dorsolateral superior frontal gyrus, bilateral medial and paracingulate gyrus, bilateral parahippocampal gyrus, bilateral middle occipital gyrus, bilateral postcentral gyrus, and bilateral superior temporal gyrus among the 3 groups( F=11.246-14.102, all P<0.05). The NPSLE group exhibited significantly lower VMHC values in these regions compared to both the non-NPSLE group and HC group (all P<0.05), but there were no significant differences in these regions between the non-NPSLE group and HC group (all P>0.05).(2) The gray matter volumes of bilateral dorsolateral superior frontal gyrus(right: (0.57±0.11)mm 3, (0.65±0.08)mm 3, t=-3.409, P=0.001; left: (0.53±0.10)mm 3, (0.60±0.07)mm 3, t=-3.082, P=0.003), bilateral precentral gyrus(right: (0.32±0.06)mm 3, (0.35±0.04)mm 3, t=-2.044, P=0.045; left: (0.39±0.06)mm 3, (0.42±0.04)mm 3, t=-2.505, P=0.015), right medial and paracingulate gyrus((0.66±0.08)mm 3, (0.70±0.07)mm 3, t=-2.491, P=0.015) and left superior temporal gyrus((0.57±0.09)mm 3, (0.61±0.06)mm 3, t=- 2.344, P=0.022) in the NPSLE group were smaller than those of non-NPSLE group.(3)Correlation analysis showed that the VMHC value of dorsolateral superior frontal gyrus was positively correlated with IgA level in NPSLE patients ( r=0.353, P=0.047). Conclusion:Patients with NPSLE generally have decreased mirror homotopy functional connectivity in the cerebral hemispheres, accompanied by a decrease in gray matter volume in some brain regions, which can provide a certain neuroimaging basis for the pathogenesis of brain injury.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To understand the changing composition and antibiotic resistance of bacterial species in the clinical isolates from outpatient and emergency department(hereinafter referred to as outpatients)and inpatient children over time in various hospitals,and to provide laboratory evidence for rational antibiotic use.Methods The data on clinically isolated pathogenic bacteria and antimicrobial susceptibility of isolates from outpatients and inpatient children in the CHINET program from 2015 to 2021 were collected and analyzed.Results A total of 278 471 isolates were isolated from pediatric patients in the CHINET program from 2015 to 2021.About 17.1％of the strains were isolated from outpatients,primarily group A β-hemolytic Streptococcus,Escherichia coli,and Staphylococcus aureus.Most of the strains(82.9％)were isolated from inpatients,mainly SS.aureus,E.coli,and H.influenzae.The prevalence of methicillin-resistant S.aureus(MRSA)in outpatients(24.5％)was lower than that in inpatient children(31.5％).The MRSA isolates from outpatients showed lower resistance rates to the antibiotics tested than the strains isolated from inpatient children.The prevalence of vancomycin-resistant Enterococcus faecalis or E.faecium and penicillin-resistant S.pneumoniae was low in either outpatients or inpatient children.S.pneumoniae,β-hemolytic Streptococcus and S.viridans showed high resistance rates to erythromycin.The prevalence of erythromycin-resistant group A β-hemolytic Streptococcus was higher in outpatients than that in inpatient children.The prevalence of β-lactamase-producing H.influenzae showed an overall upward trend in children,but lower in outpatients(45.1％)than in inpatient children(59.4％).The prevalence of carbapenem-resistant Klebsiella pneumoniae(CRKpn),carbapenem-resistant Pseudomonas aeruginosa(CRPae)and carbapenem-resistant Acinetobacter baumannii(CRAba)was 14％,11.7％,47.8％in outpatients,but 24.2％,20.6％,and 52.8％in inpatient children,respectively.The prevalence of multidrug-resistant E.coli,K.pneumoniae,Proteus mirabilis,P.aeruginosa and A.baumannii strains was lower in outpatients than in inpatient children.The prevalence of fluoroquinolone-resistant E.coli,ESBLs-producing K.pneumoniae,ESBLs-producing P.mirabilis,carbapenem-resistant E.coli(CREco),CRKpn,and CRPae was lower in children in outpatients than in inpatient children,but the prevalence of CRAba in 2021 was higher than in inpatient children.Conclusions The distribution of clinical isolates from children is different between outpatients and inpatients.The prevalence of MRSA,ESBL,and CRO was higher in inpatient children than in outpatients.Antibiotics should be used rationally in clinical practice based on etiological diagnosis and antimicrobial susceptibility test results.Ongoing antimicrobial resistance surveillance and prevention and control of hospital infections are crucial to curbing bacterial resistance.

Objective To investigate the changing antibiotic resistance profiles of E.coli isolated from patients in the 52 hospitals participating in the CHINET program from 2015 to 2021.Methods Antimicrobial susceptibility was tested for clinical isolates of E.coli according to the unified protocol of CHINET program.WHONET 5.6 and SPSS 20.0 software were used for data analysis.Results Atotal of 289 760 nonduplicate clinical strains ofE.coli were isolated from 2015 to 2021,mainly from urine samples(44.7±3.2)％.The proportion of E.coli strains isolated from urine samples was higher in females than in males(59.0％vs 29.5％).The proportion of E.coli strains isolated from respiratory tract and cerebrospinal fluid samples was significantly higher in children than in adults(16.7％vs 7.8％,0.8％vs 0.1％,both P＜0.05).The isolates from internal medicine department accounted for the largest proportion(28.9±2.8)％with an increasing trend over years.Overall,the prevalence of ESBLs-producing E.coli and carbapenem resistant E.coli(CREco)was 55.9％and 1.8％,respectively during the 7-year period.The prevalence of ESBLs-producing E.coli was the highest in tertiary hospitals each year from 2015 to 2021 compared to secondary hospitals.The prevalence of CREco was higher in children's hospitals compared to secondary and tertiary hospitals each year from 2015 to 2021.The prevalence of ESBLs-producing E.coli in tertiary hospitals and children's hospitals and the prevalence of CREco in children's hospitals showed a decreasing trend over the 7-year period.The prevalence of CREco in secondary and tertiary hospitals increased slowly.Antibiotic resistance rates changed slowly from 2015 to 2021.Carbapenem drugs(imipenem,meropenem)were the most active drugs amongβ-lactams against E.coli(resistance rate≤2.1％).The resistance rates of E.coli to β-lactam/β-lactam inhibitor combinations(piperacillin-tazobactam,cefoperazone-sulbactam),aminoglycosides(amikacin),nitrofurantoin and fosfomycin(for urinary isolates only)were all less than 10％.The resistance rate of E.coli strains to antibiotics varied with the level of hospitals and the departments where the strains were isolated,especially for cefazolin and ciprofloxacin,to which the resistance rate of E.coli strains from children in non-ICU departments was significantly lower than that of the strains isolated from other departments(P＜0.05).The E.coli isolates from ICU showed higher resistance rate to most antimicrobial agents tested(excluding tigecycline)than the strains isolated from other departments.The E.coli strains isolated from tertiary hospitals showed higher resistance rates to the antimicrobial agents tested(excluding tigecycline,polymyxin B,cefepime and carbapenems)than the strains from secondary hospitals and children's hospitals.Conclusions E.coli is an important pathogen causing clinical infection.More than half of the clinical isolates produced ESBL.The prevalence of CREco is increasing in secondary and tertiary hospitals over the 7-year period even though the overall prevalence is still low.This is an issue of concern.

Objective:To investigate the association between different types of lung nodules and the risk of lung cancer in a population at high risk of lung cancer and to provide an epidemiologic basis for the comprehensive management of lung nodules.Methods:Using the free lung cancer screening program of low-dose CT (LDCT) in Wenling, Zhejiang Province, we collected baseline and imaging information of high-risk groups for lung cancer who underwent LDCT screening from April 2019 to October 2021 and patients with previous history of lung cancer, tuberculosis, pneumoconiosis, and silicosis were excluded. A total of 28 539 study subjects were included in the analysis, and the follow-up ended on 31 December 2023. Based on the characteristics of the detected pulmonary nodules, the study subjects were classified with no nodules, with solid nodules, with pure ground glass nodules, and with part solid nodules groups. The association between different characteristics of lung nodules and the risk of lung cancer development was analyzed using the Cox proportional hazard regression model with a new diagnosis of lung cancer during the follow-up period as the outcome.Results:The overall detection rate of lung nodules with a mean diameter of ≥3 mm was 76.5%, of which 53.7%, 18.2%, and 4.6% were detected in the solid nodule, pure ground glass nodule, and partially solid nodule groups, respectively. There were statistically significant differences between the different nodule groups in terms of age, gender, BMI, history of toxic exposure education level, smoking status, history of lung disease, and family history of lung cancer (all P<0.05). The median follow-up time of the study population was 3.4 years, and 485 new lung cancer cases were diagnosed during the follow-up period. After adjusting for covariates, the results of multifactorial Cox proportional hazard regression model analysis showed that the risk of lung cancer was higher in pure ground glass nodules and part solid nodules compared with solid nodules, with HR values (95% CI) of 1.89 (1.52-2.35) and 6.49 (5.18-8.14), respectively. The results of subgroup analysis showed that patients in the group of part solid nodules had the highest risk of lung cancer in all strata of the population, followed by patients with pure ground glass nodules. Patients in the solid nodule group who were older or had previous lung disease had a higher risk of lung cancer, and the risk of lung cancer in the part solid nodule group differed between genders. Conclusions:The proportion of lung nodules detected is high in the high-risk group of lung cancer, and among them, patients with pure ground glass and part solid nodules have a higher risk of developing lung cancer. Attention should be paid to the annual follow-up management for patients with solid nodules who are older or who have had lung diseases, as well as for female patients with part solid nodules.

Objective To develop and validate a machine learning-based predictive model to assess the in-hospital mortality risk of patients with myocardial infarction(MI)complicated by heart failure(HF)undergoing percutaneous coronary intervention(PCI).Methods This retrospective study analyzed MI patients with HF who underwent PCI at The First Affiliated Hospital of Xinjiang Medical University from January 2019 to January 2023.Patient data,including demographic characteristics,vital signs,laboratory test results,imaging parameters and medication use,were collected and randomly divided into a training set(70％)and a validation set(30％).The extreme gradient boosting(XGBoost)model was used to identify variables significantly associated with in-hospital mortality,and the Shapley additive explanations(SHAP)model was applied to assess feature importance.A predictive model was then constructed using univariate and multivariate Logistic regression analyses.Model performance was evaluated using receiver operating characteristic(ROC)curves,area under the curve(AUC)values,calibration curves,and decision curve analysis.Finally,a nomogram was developed for intuitive risk assessment.Results A total of 1 214 MI patients with HF were included in the study,with a median age of 64 years.The in-hospital mortality rate was 7.41％(90 deaths).XGBoost feature selection identified ten key predictive variables:age,myoglobin,albumin,fasting blood glucose,N-terminal pro-B-type natriuretic peptide(NT-proBNP),diabetes mellitus,creatinine,cystatin C,procalcitonin,and left ventricular ejection fraction.Based on these variables,a Logistic regression model was developed,with seven final predictors:age,diabetes mellitus,creatinine,fasting blood glucose,cystatin C,NT-proBNP,and albumin.The model demonstrated high predictive accuracy,with AUC value of 0.869(95％CI:0.84-0.89)in the training set and 0.827(95％CI:0.79-0.85)in the validation set.The calibration curve indicated that the predicted probabilities were consistent with the actual observed outcomes,and decision curve analysis showed that the model had a high net benefit across various decision thresholds.Conclusion This study developed a machine learning-based predictive model incorporating Logistic regression to assess the in-hospital mortality risk of MI patients with HF undergoing PCI.The model demonstrated high predictive performance and clinical utility.The nomogram derived from this model provides an intuitive tool for individualized risk assessment,aiding clinicians in the early identification of high-risk patients,optimizing intervention strategies,and improving patient outcomes.

Objective To construct and validate machine learning-based models to predict the risk of acute kidney injury(AKI)following percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 2 315 STEMI patients who underwent PCI between January 2020 and June 2023 were included;306(13.2％)of them developed AKI.Baseline variables were screened using LASSO regression,with the optimal λ value selected via 10-fold cross-validation to identify AKI-associated features.Subsequently,eight distinct machine learning models were constructed and evaluated for their predictive performance.SHAP value analysis was employed to assess the impact of key variables on model predictions.Results LASSO regression identified seven variables significantly associated with AKI,including age,multivessel disease,preoperative creatinine,heart failure,white blood cell count,hemoglobin,and albumin levels.Among all the models,the light gradient boosting machine(LGBM)and extreme gradient boosting(XGB)demonstrated the best predictive performance,with training set AUCs being 0.899(95％CI:0.877-0.921)and 0.893(95％CI:0.868-0.918),and validation set AUCs being 0.809(95％CI:0.763-0.856)and 0.871(95％CI:0.833-0.909),respectively.SHAP analysis revealed that albumin,age,preoperative creatinine,and white blood cell count were the primary contributors to AKI risk.Conclusion This study successfully developed and validated machine learning-based predictive models capable of effectively identifying the risk of AKI following PCI in STEMI patients,thus providing valuable support for clinical decision-making.