Adipose tissue is a critical energy reservoir in animals and humans, with multifaceted roles in endocrine regulation, immune response, and providing mechanical protection. Based on anatomical location and functional characteristics, adipose tissue can be categorized into distinct types, including white adipose tissue (WAT), brown adipose tissue (BAT), beige adipose tissue, and pink adipose tissue. Traditionally, adipose tissue research has centered on its morphological and functional properties as a whole. However, with the advent of single-cell transcriptomics, a new level of complexity in adipose tissue has been unveiled, showing that even under identical conditions, cells of the same type may exhibit significant variation in morphology, structure, function, and gene expression——phenomena collectively referred to as cellular heterogeneity. Single-cell transcriptomics, including techniques like single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq), enables in-depth analysis of the diversity and heterogeneity of adipocytes at the single-cell level. This high-resolution approach has not only deepened our understanding of adipocyte functionality but also facilitated the discovery of previously unidentified cell types and gene expression patterns that may play key roles in adipose tissue function. This review delves into the latest advances in the application of single-cell transcriptomics in elucidating the heterogeneity and diversity within adipose tissue, highlighting how these findings have redefined the understanding of cell subpopulations within different adipose depots. Moreover, the review explores how single-cell transcriptomic technologies have enabled the study of cellular communication pathways and differentiation trajectories among adipose cell subgroups. By mapping these interactions and differentiation processes, researchers gain insights into how distinct cellular subpopulations coordinate within adipose tissues, which is crucial for maintaining tissue homeostasis and function. Understanding these mechanisms is essential, as dysregulation in adipose cell interactions and differentiation underlies a range of metabolic disorders, including obesity and diabetes mellitus type 2. Furthermore, single-cell transcriptomics holds promising implications for identifying therapeutic targets; by pinpointing specific cell types and gene pathways involved in adipose tissue dysfunction, these technologies pave the way for developing targeted interventions aimed at modulating specific adipose subpopulations. In summary, this review provides a comprehensive analysis of the role of single-cell transcriptomic technologies in uncovering the heterogeneity and functional diversity of adipose tissues.

ObjectiveTo develop a nomogram-based risk prediction model for chronic obstructive pulmonary disease (COPD) incidence among the community-dwelling population aged 40 years old and above, so as to provide targeted references for the screening and prevention of COPD. MethodsBased on a natural population cohort in suburban Shanghai, a total of 3 381 randomly selected participants aged ≥40 years underwent pulmonary function tests between July and October 2021. Cox stepwise regression analysis was used to develop overall and gender-specific risk prediction models, along with the construction of corresponding risk nomograms. Model predictive performance was evaluated using the C-indice, area under the curve (AUC) values, and Brier score. Stability was assessed through 10-fold cross-validation and sensitivity analysis. ResultsA total of 3 019 participants were included, with a median follow-up duration of 4.6 years. The COPD incidence density was 17.22 per 1 000 person-years, significantly higher in males (32.04/1 000 person-years) than that in females (7.38/1 000 person-years) (P<0.001). The overall risk prediction model included the variables such as gender, age, education level, BMI, smoking, passive smoking, and respiratory comorbidities. The male-specific model incorporated the variables such as age, BMI, respiratory comorbidities, and smoking, while the female-specific model included age, marital status, respiratory comorbidities, and pulmonary tuberculosis history. The C-indices for the overall, male-specific, and female-specific models were 0.829, 0.749, and 0.807, respectively. The 5-year AUC values were 0.785, 0.658, and 0.811, with Brier scores of 0.103, 0.176, and 0.059, respectively. Both 10-fold cross-validated C-indices and sensitivity analysis (excluding participants with a follow-up duration of <6 months) yielded C-indices were above 0.740. ConclusionThis study developed concise and practical overall and gender-specific COPD risk prediction models and corresponding nomograms. The models demonstrated robust performance in predicting COPD incidence, providing a valuable reference for identifying high-risk populations and formulating targeted screening and personalized management strategies.

OBJECTIVE To construct a risk prediction model for bloodstream infection （BSI） induced by carbapenem-resistant Klebsiella pneumoniae （CRKP）. METHODS Retrospective analysis was conducted for clinical data from 253 patients with BSI induced by K. pneumoniae in the First Hospital of Qinhuangdao from January 2019 to June 2022. Patients admitted from January 2019 to December 2021 were selected as the model group （n＝223）， and patients admitted from January 2022 to June 2022 were selected as the validation group （n＝30）. The model group was divided into the CRKP subgroup （n＝56） and the carbapenem- sensitive K. pneumoniae （CSKP） subgroup （n＝167） based on whether CRKP was detected or not. The univariate and multivariate Logistic analyses were performed on basic information such as gender， age and comorbid underlying diseases in two subgroups of patients； independent risk factors were screened for CRKP-induced BSI， and a risk prediction model was constructed. The established model was verified with patients in the validation group as the target. RESULTS Admissioning to intensive care unit （ICU）， use of immunosuppressants， empirical use of carbapenems and empirical use of antibiotics against Gram-positive coccus were independent risk factors of CRKP-induced BSI （ORs were 3.749， 3.074， 2.909， 9.419， 95%CIs were 1.639-8.572， 1.292- 7.312， 1.180-7.717， 2.877-30.840， P＜0.05）. Based on this， a risk prediction model was established with a P value of 0.365. The AUC of the receiver operating characteristic （ROC） curve of the model was 0.848 [95%CI （0.779， 0.916）， P＜0.001]， and the critical score was 6.5. In the validation group， the overall accuracy of the prediction under the model was 86.67%， and the AUC of ROC curve was 0.926 [95%CI （0.809， 1.000]， P＜0.001]. CONCLUSIONS Admission to ICU， use of immunosuppressants， empirical use of carbapenems and empirical use of antibiotics against Gram-positive coccus are independent risk factors of CRKP- induced BSI. The CRKP-induced BSI risk prediction model based on the above factors has good prediction accuracy.

ObjectiveAngle-closure glaucoma (ACG) is one of the major eye-blinding diseases. To diagnose ACG, it is crucial to examine the anterior chamber angle. Current diagnostic tools include slit lamp gonioscopy, water gonioscopy, ultrasound biomicroscopy (UBM), and anterior segment optical coherence tomography (AS-OCT). Slit lamp and water gonioscopy allow convenient observation of the anterior chamber angle, but pose risks of invasive operation and eye infections. UBM can accurately measure the structure of the anterior chamber angle. However, it is complex to operate and unsuitable for patients, who have undergone trauma or ocular surgery. Although AS-OCT provides detailed images, it is costly. The aim of this study is to explore a non-invasive, non-destructive optical reflection tomography (ORT) technique. This technique can achieve low-cost three-dimensional imaging and full-field anterior chamber angle measurement of the porcine eye. MethodsThe experiment involved assembling an optical reflection tomography system, which included a complementary metal oxide semiconductor (CMOS) camera, a telecentric system, a stepper motor, and a white light source, achieving a spatial resolution of approximately 8.5 μm. The process required positioning the porcine eye at the center of the field of the imaging system and rotating it around its central axis using a stepper motor. Reflection projection images were captured at each angle with an exposure time of 1.0 ms and an interval of 2°. The collected reflection-projection data were processed using a filtered reflection tomography algorithm, generating a series of two-dimensional slice data. These slices essentially represented cross-sectional views of the three-dimensional structural image, and were reconstructed into a complete three-dimensional structural image. Based on the reconstructed three-dimensional structural image of the porcine eye, the anterior chamber angles at different positions were measured, and a distribution map of these angles was drawn. Simultaneously, the ORT measurements were compared with the standard results obtained from optical coherence tomography (OCT) to assess the accuracy of ORT measurements. ResultsIn this study, we successfully obtained the reflection projection data of a porcine eye using ORT technology, reconstructed its three-dimensional structural image, and measured the anterior chamber angle, generating the corresponding distribution map. To better distinguish the different structural parts of porcine eye, the three-dimensional structural image was marked with blue, green, and yellow dashed lines from the outer to the inner layers. The area between the blue and green dashed lines corresponded to the sclera. The area between the green and yellow dashed lines corresponded to the iris. The area inside the yellow dashed line corresponded to the pupil. The three-dimensional structural image clearly revealed the key anatomical features of the porcine eye. It was able to measure the anterior chamber angle at different positions. Additionally, the anterior chamber angle measurements of the porcine eye using ORT were compared with the measurements obtained using a TEL320C1 type OCT system, showing an average deviation of 0.51° and a mean square error MSE of 0.317. ConclusionORT is a non-invasive, non-destructive, low-cost, and high-resolution imaging technique capable of achieving three-dimensional structural imaging and full-field anterior chamber angle measurement of a porcine eye. This technology offers a new perspective for the diagnosis of angle-closure glaucoma and is significant for the screening, diagnosis, and monitoring of eye diseases, potentially benefiting clinics and small hospitals in remote areas in the future.

Brasilicardin A, a diterpene glycoside isolated from pathogenic actinomycete Nocardia brasiliensis IFM 0406, has become a novel immunosuppressant candidate due to its significant immunosuppressive activity, low toxicity and unique mechanism of action. However, brasilicardin A and its analogues have become a research hotspot to the development of this promising immunosuppressant because of the low-yield production in the natural pathogenic producer and the synthetically challenging skeleton. According to the reported biosynthetic pathway of brasilicardin A, the function of involved diterpene synthase was analyzed by bioinformatics. Then the genes bra1-5 that synthesize the brasilicardin A skeleton were directionally amplified from the pathogenic strain N. brasiliensis IFM 0406, and heterologous expression was achieved successfully in Streptomyces albus R1. The compounds were isolated and purified by using various column chromatographies including silica gel column chromatography and semi-preparative HPLC. Six new brasilicardins were established and named brasilicardin H-M. The activity of brasilicardins was screened using lipopolysaccharide (LPS)-activated mouse primary macrophage inflammation model. Brasilicardin H-M exhibited good inhibitory activity on nitric oxide (NO) release with IC₅₀ values of 28.24 ± 3.70, 37.44 ± 2.00, 39.85 ± 4.02, 26.77 ± 4.40, 65.25 ± 1.48 and 15.24 ± 2.72 μmol·L^-1, respectively (indomethacin as the positive control with IC₅₀ value of 34.28 ± 4.10 μmol·L^-1). The results indicated that six compounds had potential anti-inflammatory activity. This study laid a foundation for the elucidation of the brasilicardin A biosynthetic pathway and evaluation of the structure-activity relationship as well as new drug developments.

Objective To establish an early prediction model for the diagnosis of severe acute pancreatitis based on the improved machine learning models,and to analyze its clinical value.Methods A case-control study was conducted on 352 patients with acute pancreatitis admitted to the Gastroenterology and Hepatobiliary Surgery Departments of the Army Medical Center of PLA and Emergency and Critical Care Medicine Department of No.945 Hospital of Joint Logistics Support Force of PLA from January 2014 to August 2023.According to the severity of the disease,the patients were divided into the severe group(n=88)and the non-severe group(n=264).The RUSBoost model and improved Archimead optimization algorithm was used to analyze 39 routine laboratory biochemical indicators within 48 h after admission to construct an early diagnosis and prediction model for severe acute pancreatitis.The task of feature screening and hyperparameter optimization was completed simultaneously.The ReliefF algorithm feature importance rank and multivariate logistic analysis were used to analyze the value of the selected features.Results In the training set,the area under curve(AUC)of the improved machine learning model was 0.922.In the testing set,the AUC of the improved machine learning model reached 0.888.The 4 key features of predicting severe acute pancreatitis based on the improved Archimedes optimization algorithm were C-reactive protein,blood chlorine,blood magnesium and fibrinogen level,which were consistent with the results of ReliefF algorithm feature importance ranking and multivariate logistic analysis.Conclusion The application of improved machine learning model analyzing the laboratory examination results can help to early predict the occurrence of severe acute pancreatitis.

Objective To investigate the effects of Fuzheng Quxie Prescription(mainly with the actions of supporting healthy qi and dispelling pathogens)combined with neoadjuvant chemotherapy on tumor recurrence,serum thymidine kinase 1(TK1)level and immune function in patients with triple-negative breast cancer(TNBC).Methods Eighty patients with TNBC of qi and yin deficiency type were randomly divided into a combination group and a control group,with 40 patients in each group.The control group was treated with AC-T sequential chemotherapy(Doxorubicin combined with Cyclophosphamide plus sequential Docetaxel),and the combination group was treated with Fuzheng Quxie Prescription on the basis of treatment for the control group.One course of treatment covered 21 days,and the two groups were treated for 4 consecutive courses.The changes of traditional Chinese medicine(TCM)syndrome scores,Karnofsky Performance Status(KPS)score,levels of tumor markers of carbohydrate antigen 125(CA125),carbohydrate antigen 153(CA153)and TK1,and T lymphocyte subset levels in the two groups were observed before and after the treatment.Moreover,the clinical efficacy and tumor metastasis and recurrence in the two groups were compared.Results(1)After 4 courses of treatment,the total effective rate of the combination group was 87.50%(35/40),and that of the control group was 67.50%(27/40),and the intergroup comparison(tested by chi-square test)showed that the efficacy of the combination group was significantly superior to that of the control group(P＜0.05).(2)After treatment,the TCM syndrome scores in the two groups were significantly decreased compared with those before treatment(P＜0.05),and the KPS scores were significantly increased compared with those before treatment(P＜0.05),and the decrease of TCM syndrome scores and the increase of KPS scores in the combination group were significantly superior to that in the control group(P＜0.05 or P＜0.01).(3)After treatment,the serum CA125,CA153 and TK1 levels of patients in the two groups were significantly decreased compared with those before treatment(P＜0.05),and the decrease of serum CA125,CA153 and TK1 levels in the combination group was significantly superior to that in the control group(P＜0.01).(4)After treatment,the T lymphocyte subset CD3+,CD4+ levels and CD4+/CD8+ ratio in the two groups were significantly increased compared with those before treatment(P＜0.05),and the CD8+ level was significantly decreased compared with that before treatment(P＜0.05).The post-treatment intergroup comparison showed that the increase of the T lymphocyte subset CD3+,CD4+ levels and CD4+/CD8+ ratio as well as the decrease of the CD8+ level in the combination group was all significantly superior to that in the control group(P＜0.05 or P＜0.01).(5)The one-year follow-up showed that the tumor recurrence rate and tumor metastasis rate in the combination group were 7.50%(3/40)and 12.50%(5/40)respectively,significantly lower than 25.00%(10/40)and 35.00%(14/40)in the control group,and the differences were statistically significant when comparing between the two groups(P＜0.05).Conclusion The combination of neoadjuvant chemotherapy with Fuzheng Quxie Prescription has a better therapeutic effect on TNBC patients with qi and yin deficiency syndrome,which can effectively improve the immune function of the patients,decrease the level of serum tumor markers,improve the quality of life of the patients,and reduce the incidence of tumor recurrence and metastasis.

Objective To investigate the rate of germline variants in patients with pancreatic cancer and clinical characteristics related with germline variants.Methods A total of 271 patients diagnosed with pancreatic cancer were enrolled in this study.Germline variants of 21 tumor susceptibility genes were detected by next-generation sequencing,and the relationship between germline variants and clinical factors such as age of onset,family history and personal history was analyzed.Results The rate of germline P/LP variants was 6.3%in unselected pancreatic cancer patients,but was high as 17.1%in genetic high-risk group patients(those with a family or personal history of cancer,or early-onset).Genes with higher frequency of germline variants in pancreatic cancer patients were PALB2,BRCA2,and ATM.Conclusion The rate of germline variants in overall pancreatic cancer patients is not high,but it increases significantly in genetic high-risk group,proving the importance of clinical factors in the screening of hereditary pancreatic cancer.

ObjectiveTo evaluate the efficacy of three screening questionnaires for COPD in the community residents of Songjiang District， Shanghai， and to provide a basis for selecting COPD screening questionnaire and process that are more suitable. MethodsCommunity residents aged 40 years or over were randomly selected from the Shanghai Suburban Adult Cohort and Biobank for the study with screening questionnaires and spirometry. Questionnaires included the COPD screening questionnaire （COPD-SQ）， the COPD population screener （COPD-PS） and the revised COPD diagnostic questionnaire （revised-CDQ）. Evaluation of the efficacy of these questionnaires was based on the area under the receiver operating characteristic curve （AUC） of the subjects. DeLong test was used to compare the accuracy of different questionnaires； Z test was used to compare the accuracy of different cut-off values for the same questionnaire. ResultsAmong 3 184 community residents， a total of 259 （8.1%） COPD patients were screened by spirometry. AUC values of these 3 screening questionnaires were >0.7 indicating that they were reliable COPD screening tools. The sensitivity and specificity of the questionnaires at the recommended cut-off values were COPD-SQ （63.7% and 72.2%）， COPD-PS （12.0% and 96.1%）， and revised CDQ （78.8% and 52.7%）， with the COPD-SQ having the highest screening accuracy （AUC=0.754）. The optimal and recommended cut-off values for the three questionnaires differed in this population， but the difference in accuracy was statistically significant only for COPD-PS. The optimal cut-off values for the three questionnaires differed between male and female， and the sensitivity and accuracy of COPD-SQ and COPD-PS improved when lower cut-off values were used for women. The AUC was greater when two questionnaires were utilized simultaneously for screening， but the differences were not statistically significant. ConclusionThe COPD-SQ is recommended for primary COPD screening； a lower cut-off value for women should be considered. The COPD screening questionnaire needs to be further improved for the early diagnosis and treatment of COPD patients.

OBJECTIVE To construct a risk prediction model for non-compliance with inhaled medication in patients with chronic obstructive pulmonary disease （COPD）. METHODS A retrospective analysis was conducted on 365 COPD patients admitted to the cough and wheeze pharmaceutical care clinic of the First Hospital of Qinhuangdao from October 2021 to October 2023. The patients admitted from October 2021 to June 2023 were selected as the model group （n＝303）， and the patients admitted from July to October 2023 were selected as the validation group （n＝62）. The model group was divided into compliance subgroup （n＝126） and non-compliance subgroup （n＝177）. Univariate analysis combined with multivariate Logistic regression analysis were used to analyze the risk factors for non-compliance with inhaled formulations in patients； the risk prediction model was established through regression analysis， and the accuracy of the model prediction was evaluated based on the validation group of patients. RESULTS Multivariate Logistic regression analysis showed that simultaneous use of 2 inhaled formulations （OR＝3.730， 95%CI 1.996-6.971， P＜0.001）， the number of acute exacerbations within one year ≥2 （OR＝2.509， 95%CI 1.509-4.173， P＜0.001）， smoking （OR＝2.167， 95%CI 1.309-3.588， P＝0.003）， complicated with anxiety/depression （OR＝2.112， 95%CI 1.257-3.499， P＝0.004） and mMRC grading≥2 levels （OR＝1.701， 95%CI 1.014-2.853， P＝0.044） were risk factors for non-compliance with inhaled preparations. Based on this， a risk prediction model was established and the ROC curve was drawn. The areas under the curve of the model group and validation group were 0.836 and 0.928， and the overall accuracy of the model’s prediction was 88.71%. CONCLUSIONS The predictive model based on the simultaneous use of 2 inhaled formulations， the number of acute exacerbations within one year ≥2， smoking， complicated with anxiety/depression， mMRC grading ≥2 levels has certain predictive value for the risk of non-compliance with inhaled formulations for COPD patients.