Objective To investigate the current situation of off-label use of immune checkpoint inhibitors(ICIs)in China and the cognition of medical staff.Methods From August 31 to September 9,2022,a nationwide survey questionnaire was sent to medical staff in the form of electronic questionnaire.The questionnaire included 13 questions,covering four dimensions:Drug allocation,current situation of medication beyond the instructions,cognition of medication beyond the instructions and current situation of medication beyond the instructions.Results A total of 745 questionnaires were collected.75.70％of respondents reported off-label use of ICIs in their hospitals,with the most common type being off-label indications.The primary reasons for such practices included support from authoritative domestic and international guidelines,clinical research data validation,and approved indications in foreign regulatory documents.85.37％of respondents believed off-label use could offer new hope for patients,while 68.86％considered it unlikely to increase adverse reactions.44.97％of respondents' hospitals had not established off-label use registration systems for ICIs.88.86％of respondents emphasized the need for stricter regulations governing off-label use of immunotherapeutic agents.Conclusion Off-label use of ICIs is common,and there is a lack of unified guidance in clinical practice.It is urgent to form norms and consensus on the management of off-label use of ICIs.

Objective:To investigate the clinical characteristics and hormonal changes in patients with adrenocorticotropic hormone(ACTH)-suppressed and non-suppressed subclinical Cushing′s syndrome(SCS), to evaluate the influencing factors of ACTH suppression, and to assess the diagnostic efficiency of serum dehydroepiandrosterone sulfate(DHEAS) levels in distinguishing these two groups of SCS patients.Methods:Clinical data of patients diagnosed with SCS in the Department of Endocrinology, Drum Tower Hospital Affiliated to Nanjing University Medical College, between June 2014 and October 2023 were retrospectively collected. A total of 194 cases were included. According to morning(8: 00 AM) plasma ACTH levels, patients were divided into an ACTH-suppressed group(ACTH<2.2 pmol/L) and a non-suppressed group(ACTH≥2.2 pmol/L). Additionally, 194 gender-, age-, and BMI-matched patients with non-functional adrenal tumors(NFA) were enrolled as controls. Clinical characteristics and hormone levels were compared between groups. Logistic regression analysis was performed to identify factors influencing ACTH suppression in SCS patients. Furthermore, receiver operating characteristic(ROC) curve analysis was conducted to evaluate the diagnostic performance of serum DHEAS levels in distinguishing ACTH-suppressed and non-suppressed SCS patients. Results:There were no significant differences in the prevalence of overweight/obesity, hypertension, abnormal glucose metabolism, or bone metabolism disorders between the ACTH-suppressed and non-suppressed groups. The serum cortisol level after the 1 mg-dexamethasone suppression test(DST) was significantly lower in the ACTH non-suppressed group than that in the suppressed group, while the serum DHEAS level was significantly higher in the non-suppressed group(both P<0.01). The area under the curve(AUCs) of serum DHEAS for diagnosing ACTH non-suppressed SCS patients and ACTH-suppressed SCS patients was 0.779(95% CI 0.721-0.837) and 0.874(95% CI 0.831-0.918), respectively. Using a serum DHEAS cutoff of 60.0 μg/dL, the sensitivity and specificity for diagnosing ACTH non-suppressed SCS patients were 66.7% and 76.1%, respectively, while for ACTH-suppressed SCS patients, the sensitivity and specificity were 84.9% and 75.5%, respectively. Conclusion:There were no significant differences in metabolic characteristics between ACTH-suppressed and non-suppressed SCS patients. Serum cortisol level after 1 mg-DST is an independent influencing factor for ACTH suppression status. Low serum DHEAS level serves as a sensitive diagnostic marker for SCS and also demonstrates diagnostic value in ACTH non-suppressed SCS patients.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To construct a predictive model for high-grade pathological components of early invasive lung adenocarcinoma(ILAC)based on radiomics.Methods Collecting information on total 495 patients who underwent radical operation and were pathologically diagnosed as stage Ⅰ in the cardiothoracic surgery of Zhoushan Hospital from January 2015 to December 2019,including gender,age,pathological findings,tumor markers and preoperative chest CT images.The micropapillary and solid components in postoperative pathology were defined as"high-grade pathological components",while those without high-grade pathological components were classified into the low-grade group and those with high-grade pathological components were classified into the high-grade group.And patients were randomly divided into the training set(343 cases)and the validation set(152 cases)with a ratio of 7∶3 using the simple randomization grouping method.The region of interest of nodules on CT images were delineated layer by layer by scientific research platform and 1950 radiomics features were extracted.And then those features were filtrated by F-test,Pearson correlation coefficient,and L1 based feature selection.A model was built by using Logistic regression machine learning classifier,named mod 2,and radscore was also obtained.Differences between general information and CT features were analyzed.Binary Logistic regression analysis was used to construct a model for statistically significant variables,named mod 1.At the same time,Radscore was added to build the mod and named comb mod.The area under the curve(AUC),sensitivity and specificity of the three models were calculated.A nomogram was also drawn.Results A total of 495 patients were divided into the training set(n=343)and the validation set(n=152).Gender,carcinoma embryonic antigen(CEA),nodule,and maximum diameter were screened out in clinical features and involved in constructing the mod 1.Twelve features were selected from the radiomics features to build mod 2.Comb mod performed best,training set AUC:0.887,validation set AUC:0.875,and had good clinical practicability.Conclusion The model composed of general feature,CT feature and radiomics features could accurately predict high-grade pathological components in early ILAC,and provide references for clinicians to choose surgical method for patients.

Objective:To explore the features of levels of lung cancer biomarkers in peripheral blood of adults in Beijing and surrounding areas, and establish personalized reference intervals for these biomarkers.Methods:A cross sectional study was conducted. The lung cancer biomarker data, including carcinoembryonic antigen (CEA), cytokeratin 19 fragment antigen 21-1 (CYFRA21-1), neuron specific enolase (NSE), progastrin-releasing peptide (ProGRP), and squamous cell carcinoma antigen (SCC-Ag), collected from adults who underwent cancer prevention examinations at the Cancer Hospital of the Chinese Academy of Medical Sciences from July 2021 to July 2022 were retrospectively analyzed. The interquartile range method was used to eliminate outliers, and the P95 value was calculated. Upper limit of 5 lung cancer biomarkers in different gender and age groups were obtained by referring to the reference intervals of quantitative analytes in the clinical laboratory (WS/T 402-2024). By analyzing the data of 208 adults who underwent cancer prevention physical examinations at the same center in June 2021 and 140 patients with benign lung masses confirmed by surgical resection pathology from January 2016 to June 2022, the established reference intervals for biomarkers were validated. Results:Two thousand six hundred and twenty-six cases of apparently healthy physical examiners were included for constructing reference intervals, including 1 456 males (55.4%) and 1 170 females (44.6%); the age range was 20-88 years old. The serum levels [ M ( Q1, Q3)] of CEA, NSE, ProGRP, SCC-Ag and CYFRA21-1 in 2 626 cases were 1.63 (1.07, 2.43) ng/ml, 13.08 (11.44, 14.77) ng/ml, 34.93 (29.02, 42.19) pg/ml, 0.80 (0.60, 1.00) ng/ml and 1.96 (1.48, 2.63) ng/ml, respectively. The serum levels of CEA [1.88 (1.22, 2.76) ng/ml vs. 1.41 (0.93, 2.02) ng/ml], NSE [13.31 (11.87, 15.00) ng/ml vs. 12.69 (10.96, 14.53) ng/ml], SCC-Ag [0.9 (0.7, 1.1) ng/ml vs. 0.7 (0.6, 0.9) ng/ml], and CYFRA21-1 [2.02 (1.53, 2.71) ng/ml vs. 1.87 (1.40, 2.51) ng/ml] in males were higher than those in females, and ProGRP [34.00 (28.25, 41.55) pg/ml vs. 36.12 (29.97, 42.98) pg/ml] was lower than that in females, and the differences were statistically significant (all P < 0.001). There were statistically significant differences in serum CEA levels between the groups of ≤ 40 years old (458 cases), >40-50 years old (827 cases), >50-60 years old (783 cases), >60-70 years old (412 cases), and >70 years old (146 cases) in pairwise comparison (all P < 0.05). Except for the age groups of ≤ 40 years old and >40-50 years old and the age groups of >60-70 years old and >70 years old, there were statistically significant differences in serum NSE levels among the other age groups in pairwise comparison (all P < 0.05). There were statistically significant differences in serum ProGRP levels between the 5 age groups (all P < 0.05). There were statistically significant differences when comparing the serum SCC-Ag level in the >40-50 age group, >50-60 age group and >60-70 age group with that in the ≤40 age group and >70 age group, respectively (all P < 0.05). However, there was no statistically significant difference between the other age groups in pairwise comparison (all P > 0.05). There were statistically significant differences in serum CYFRA21-1 levels between the 5 age groups (all P < 0.05). When gender and age were not distinguished, the P95 values of serum CEA, NSE, ProGRP, SCC-Ag and CYFRA21-1 levels were 4.44 ng/ml, 16.61 ng/ml, 57.65 pg/ml, 1.50 ng/ml, and 4.21 ng/ml, respectively. Considering gender and age, except for the >70 age group with no statistically significant difference in the P95 value of serum CEA level between males and females ( P > 0.05), the P95 value of serum CEA level in males was higher than that in females in all other age groups (all P < 0.001); the P95 values of serum CEA level in both males and females increased with age, but showed a decreasing trend in males over the age of 70. The P95 value of serum NSE level in males was higher than that in females in the age groups of ≤ 40 years and >40-50 years (both P < 0.05), while there was no statistically significant difference in the P95 value of serum NSE level between males and females in other age groups (all P > 0.05). The P95 values of serum NSE level in both males and females decreased firstly and increased later with age, reaching their highest levels at the age of >70. The P95 values of serum ProGRP level in females aged ≤ 40 and >50-60 were higher than those in males (both P < 0.05), while there was no statistically significant difference in the P95 value of serum ProGRP level between genders in other age groups (all P > 0.05); the P95 values of serum ProGRP level in both males and females increased with age. There was no statistically significant difference in the P95 value of serum SCC-Ag level between males and females in the ≤ 40 age group ( P > 0.05), while the P95 value of serum SCC-Ag level in males was higher than that in females in all other age groups (all P < 0.05). The P95 values of serum SCC-Ag level in males increased with age, while they were stable in females. There was no statistically significant difference in the P95 value of serum CYFRA21-1 level between males and females in the >60-70 age group ( P > 0.05), while the P95 value of serum CYFRA21-1 level in males was higher than those in females in all other age groups (all P < 0.05); the P95 values of serum CYFRA21-1 level in both males and females increased with age. Based on data from 2 626 apparently healthy physical examiners, reference intervals for the levels of 5 lung cancer biomarkers were constructed in different age groups of different genders. Validation was conducted on 208 physical examiners and 140 patients with benign lung lesions, and it was found that the compliance rate of using newly created reference intervals for different gender and age groups to interpret detection results was >90%, and the validation was passed. Conclusions:There are gender and age differences in the reference intervals of CEA, CYFRA21-1, NSE, ProGRP, and SCC-Ag in peripheral blood of adults in Beijing and surrounding areas. The constructed reference intervals of gender and age for biomarkers have been validated and shown good results, providing reference for optimizing the clinical application of lung cancer-related biomarkers.

Objective To explore the effects of physical activity(PA)on carotid intima-media thickness(CIMT)thickening in patients with type 2 diabetes mellitus(T2DM)with poor HbA1c control.Methods A total of 2505 T2DM inpatients with poor HbA1c control who visited the Endocrinology Department of the Integrated Traditional Chinese and Western Medicine Hospital Affiliated with Nanjing University of Traditional Chinese Medicine and Changzhou Second People's Hospital Affiliated with Nanjing Medical University from January 2019 to February 2022 were enrolled in this study.The patients were categorized into the mild-intensity PA(1～599 MET-min/w,n=795),moderate-intensity PA(600～1499 MET-min/w,n=1107)and high-intensity PA(≥1500 MET-min/w,n=603)based on the metabolic equivalence level(MET).Logistic regression was performed to analyze the relationship between PA and CIMT thickening.Statified analysis was used to investigate the effects of blood pressure(BP)and low-density lipoprotein cholesterol(LDL-C)target status on CIMT thickness in different PA groups.Results Restricted cubic spline plots showed a nonlinear relationship between PA levels and the risk of CIMT thickening(P<0.05).Logistic regression showed that with moderate-intensity PA as the control,while high-intensity PA was the influence factor of CIMT thickening(OR 1.581,95%CI 1.244～2.010,P<0.05).Statified analyses showed that under mild-intensity PA,using neither BP nor LDL-C on target as reference,achievement of either index and both were the influence factor of CIMT thickening.Using BP on target as reference,achievements of both indexes,achievements of neither of both indexes,and achievement of LDL-C only were the influence factor of CIMT thickening.Using LDL-C on target as reference,achievement of neither of them and achievement of BP only were the influence factor of CIMT thickening.Under high-intensity PA,achievement of both indexes was negatively associated with CIMT thickening.Conclusions Moderate-intensity PA is the recommended scheme to prevent CIMT thickening in T2DM patients whose HbA1c is not up to standard.Mild-intensity PA is not related to the risk of CIMT thickening,while high-intensity PA is positively related to the risk of CIMT thickening,and focusing on LDL-C compliance is particularly important to avoid CIMT thickening.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective·To investigate the role of caspase recruitment domain-containing protein 9(CARD9)in regulating macrophage polarization in a rat model of severe acute pancreatitis(SAP).Methods·SD rats were divided into 4 groups:Control group,SAP group,SAP+CARD9 shRNA group,and SAP+Control shRNA group with six rats in each group.The SAP rats transfected with CARD9 shRNA were established by injecting CARD9 shRNA adenovirus 48 hours before the SAP model was induced.The pancreatic tissues,peripheral blood,and peritoneal macrophages were collected 12 hours after the model was established.The expressions of CARD9 gene and CARD9 protein in peritoneal macrophages and pancreatic tissues were measured by real-time PCR and Western blotting.The expressions of TNF-α,IL-6,IL-10 and Arg-1 mRNA were detected by real-time PCR and the polarization types of peritoneal macrophages were detected by flow cytometry.Results·The expressions of CARD9 gene and CARD9 protein in peritoneal macrophages in CARD9 shRNA rats were significantly lower than those in SAP rats and interference control rats,which confirmed the success of CARD9 interference model.Compared with SAP rats,CARD9 shRNA rats had significantly reduced degree of inflammation and pathological scores;the mRNA levels of TNF-α,and IL-6 in peritoneal macrophages were significantly decreased;meanwhile,the mRNA levels of IL-10 and Arg-1 were increased,and the changes in TNF-α and IL-6 were significantly higher than those of IL-10 and Arg-1.The proportion of M1 macrophages was significantly reduced,and the ratio of M1/M2 was significantly decreased.The expression level of CARD9 mRNA in peritoneal macrophages was positively correlated with the proportion of M1 macrophages and the mRNA levels of TNF-α and IL-6.Conclusion·CARD9 is involved in regulating macrophage polarization in SAP rats,and it mainly regulates M1 polarization.Inhibition of CARD9 expression can reduce M1 macrophage polarization and reduce the inflammatory response in SAP rats.

Objective:To investigate the relationship between nerve growth factor (NGF) concentration in follicular fluid and abnormal menstrual cycle in infertile patients with polycystic ovary syndrome (PCOS).Methods:A retrospective cohort study was conducted on 100 infertile patients with PCOS who underwent in vitro fertilization and embryo transfer (IVF-ET) at Department of Obstetrics and Gynecology, Peking University Third Hospital from March 2017 to June 2019. For comparison, the 100 patients with PCOS were divided into low NGF group ( n=50) and high NGF group ( n=50) based on the median NGF concentration (1 644.03 ng/L) in follicular fluid. Baseline characteristics, menstrual status and clinical outcomes of assisted reproductive technology were compared. We performed multiple linear regression analysis to examine the effect of NGF in follicular fluid on menstrual cycle length for multivariate analysis. Results:1) PCOS patients in the low NGF group had significantly higher body mass index [(27.24±5.17) kg/m 2] and white blood cell count [7.31(5.99, 8.43)×10 9/L ] than those in the high NGF group [(25.03±4.46) kg/m 2, P=0.024; 5.95(5.08,7.01)×10 9/L, P=0.001], while high-density lipoprotein cholesterol [1.15 (0.98, 1.36) mmol/L] and basic follicle-stimulating hormone level [6.51 (5.10,7.95) U/L] in the low NGF group were significantly lower than those in the high NGF group [1.36 (1.09,1.52) mmol/L, P=0.039;6.51 (5.10,7.95)U/L, P=0.040]. 2) PCOS patients in the low NGF group had significantly higher menstrual cycle length [60.00 (35.00, 180.00) d] than the high NGF group [32.50 (27.00,67.50) d, P=0.001]. 3) Multiple linear regression analysis revealed that after adjustment for body mass index, age, infertility duration, infertility type, and glucose and lipid metabolic parameters, the NGF concentration in the follicular fluid independently and negatively correlated with menstrual cycle length ( P<0.05). 4) The NGF concentration in follicular fluid was not correlated with assisted reproductive outcomes. Conclusion:NGF concentration in follicular fluid is closely related to the degree of menstrual cycle abnormalities in patients with PCOS.