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 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 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 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 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 effect of esketamine on the analgesic efficacy,arterial blood gas indicators and inflammatory factors of patients with severe mechanical ventilation.Methods:A prospective study was conducted on 66 patients with severe mechanical ventilation who were admitted to our hospital from December 2022 to June 2024,and they were divided into control group and study group according to the envelope lottery method,with 33 cases in each group.The control group received remifentanil analgesic treatment,and the study group received esketamine analgesic treatment on the basis of the control group.Critical-care pain observation tool(CPOT)score,blood gas indicators[Partial pressure of arterial oxygen(PaO2)and partial pressure of carbon dioxide(PaCO2)],offline success rate,mechanical ventilation time,maximum remifentanil dosage to achieve analgesic goals,inflammatory factors levels[Interleukin(IL)-6,interleukin(IL)-10,white blood cell count(WBC),procalcitonin(PCT)]and the incidence of adverse reactions were compared between the two groups.Results:PaCO2 and CPOT scores decreased,while PaO2 increased after treatment of both groups(P＜0.05).The CPOT scores of the study group was lower than that of the control group after treatment(P＜0.05).The offline success rate of the study group was higher than that of the control group,the mechanical ventilation time was shorter than that of the control group,and the maximum remifentanil dosage to achieve analgesic goals was lower than that of the control group (P＜0.05).IL-6,WBC and PCT levels of the study group after treatment were lower than those of the control group,while IL-10 was higher than that of the control group(P＜0.05).There was no significant difference in the incidence of adverse reactions between the two groups(P＞0.05).Conclusion:Esketamine in the treatment of patients with severe mechanical ventilation,can effective analgesia,increase offline success rate,shorten mechanical ventilation time,reduce inflammatory factors levels.

Objective:To investigate the effect of esketamine on the analgesic efficacy,arterial blood gas indicators and inflammatory factors of patients with severe mechanical ventilation.Methods:A prospective study was conducted on 66 patients with severe mechanical ventilation who were admitted to our hospital from December 2022 to June 2024,and they were divided into control group and study group according to the envelope lottery method,with 33 cases in each group.The control group received remifentanil analgesic treatment,and the study group received esketamine analgesic treatment on the basis of the control group.Critical-care pain observation tool(CPOT)score,blood gas indicators[Partial pressure of arterial oxygen(PaO2)and partial pressure of carbon dioxide(PaCO2)],offline success rate,mechanical ventilation time,maximum remifentanil dosage to achieve analgesic goals,inflammatory factors levels[Interleukin(IL)-6,interleukin(IL)-10,white blood cell count(WBC),procalcitonin(PCT)]and the incidence of adverse reactions were compared between the two groups.Results:PaCO2 and CPOT scores decreased,while PaO2 increased after treatment of both groups(P＜0.05).The CPOT scores of the study group was lower than that of the control group after treatment(P＜0.05).The offline success rate of the study group was higher than that of the control group,the mechanical ventilation time was shorter than that of the control group,and the maximum remifentanil dosage to achieve analgesic goals was lower than that of the control group (P＜0.05).IL-6,WBC and PCT levels of the study group after treatment were lower than those of the control group,while IL-10 was higher than that of the control group(P＜0.05).There was no significant difference in the incidence of adverse reactions between the two groups(P＞0.05).Conclusion:Esketamine in the treatment of patients with severe mechanical ventilation,can effective analgesia,increase offline success rate,shorten mechanical ventilation time,reduce inflammatory factors levels.