ObjectiveTo construct a standardized diagnostic scale for Qi-Yin deficiency with blood stasis syndrome in diabetic macrovascular disease. MethodsLiterature related to Qi-Yin deficiency with blood stasis syndrome in diabetic macrovascular disease was retrieved from CNKI， VIP， and Wanfang databases. Diagnostic information from four diagnostic methods was extracted and standardized， with items having a frequency of ≥15 included in the item pool. A three-round Delphi expert consultation was conducted， screening items using support degree， mean score， rank sum， and coefficient of variation. Item weights were determined using analytic hierarchy process （AHP）， gactor analysis （FA）， and combined weighting method （CWM）. The optimal weighting method was selected by comparing the area under the receiver operating characteristic （ROC） curve （AUC）. The Youden index was calculated to establish the diagnostic cutoff value， which was proportionally scaled. ResultsA total of 102 studies were included. Thirty-five items were incorporated into the item pool. The authority coefficients for the three Delphi rounds were 0.82， 0.85， and 0.86， with coordination coefficients of 0.648， 0.538， and 0.506， respectively. Fifteen items were retained after screening. ROC curve analysis showed the AUC ranking as FA > CWM > AHP. The maximum Youden index was 0.814， corresponding to a diagnostic cutoff of 8.361 （scaled to 40 points）. The final scale adopted a structured diagnostic framework： the symptom dimension requires at least 2 items， and the tongue or pulse dimension requires at least 1 category. ConclusionThis study developed a standardized diagnostic scale for Qi-Yin deficiency with blood stasis syndrome in diabetic macrovascular disease. Core items were screened via the Delphi method， with factor analysis identified as the optimal weighting method through AUC comparison. The diagnostic threshold （40 points） and structured diagnostic framework provide a quantitatively clear， clinically practical tool.

Background/Aims: Natural killer (NK) cell function is generally considered dampened in chronic hepatitis B virus (HBV) infection; however, the NK cell pool exhibits phenotypic and functional heterogeneity, and the antibody--mediated effect of NK cells remains less characterized. This study evaluated the dynamic changes in antibody-mediated NK cell responses and the involvement of distinct NK subsets across disease stages and during antiviral treatment. Methods: A T-cell receptor-like antibody specific for the HBV core 18–27 peptide (cTCRL-Ab) was used to determine the antibody-mediated effect of NK cells, and an array of NK cell surface markers were analyzed in cross-sectional and longitudinal cohorts of patients with chronic HBV infection. Single-cell RNA sequencing (scRNA-seq) was performed to identify the heterogeneity of NK subsets. Results: The cTCRL-Ab enabled the detection of NK cell cytolytic activity and IFNγ production. Notably, cTCRL-Ab-mediated NK cell responses were compromised in chronically HBV-infected patients, particularly in those receiving pegylated interferon-α (Peg-IFNα), which was associated with the downregulation of CD16 expression. Correspondingly, Peg-IFNα inhibited cTCRL-Ab-mediated NK cell function by reducing CD16 expression in vitro. scRNA-seq revealed that CD16 downregulation occurred mainly within a dysfunctional CD16hi NK subset exhibiting exhaustion properties. In contrast, an activated CD16hiNK subpopulation (CX3CR1⁺KLRC2–CD16hi) with high cytotoxicity was enriched in patients who experienced favorable treatment responses. Furthermore, the intrahepatic CX3CR1+KLRC2–CD16hi subset tended to exhibit functional restoration in HBsAg-loss individuals. Conclusions Our data contribute to the understanding of antibody-mediated responses of NK cells in chronic HBV infection, and highlight a previously unappreciated functional CX3CR1+KLRC2–CD16hiNK subset as a potential therapeutic target.

Obesity has become one of the important factors affecting the entire management process of liver transplantation. Its impact is not only reflected in the increased risk of liver steatosis and ischemia-reperfusion injury in the donor, but also involves the increased technical difficulty during the perioperative period for the recipient, the increase in postoperative metabolic complications and poorer long-term prognosis. This article, based on recent relevant studies, reviews aspects such as the utilization of obese donors, the characteristics of adult and pediatric recipients, pre-transplant risk assessment and weight loss intervention, and post-transplant weight and metabolic management. Current evidence suggests that simply judging transplantation risks based on body mass index has limitations. Analysis of body composition, assessment of cardiovascular function and identification of sarcopenic obesity are more clinically valuable. For obese liver transplant recipients, in a multidisciplinary collaboration framework, emphasis should be placed on individualized screening, perioperative optimization and long-term follow-up management to improve the outcomes of the graft and the recipient.

ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

Objective To develop models for predicting response to chemotherapy combined with immunotherapy in patients with esophageal squamous carcinoma with various machine learning algorithms,and then select the optimal model.Methods A retrospective study was performed for 174 patients with esophageal squamous cell carcinoma undergoing chemotherapy combined with immunotherapy admitted in Department of Thoracic Surgery of the First Affiliated Hospital of Army Medical University from January 2022 to December 2023.The CT scans and clinical information were collected before treatment.They were randomly divided into a training set(n=122)and a testing set(n=52)in a ratio of 7∶3.CT radiomic features were extracted and selected,and then 5 machine-learning algorithms were employed to establish the prediction models,including radiomics model and clinical-radiomics model.Five-fold cross-validation was conducted on the training set,and the performance of the prediction models was evaluated on the testing set using receiver operating characteristic(ROC)curve and the F1 score.The best-performing model was further explained using local interpretable model-agnostic explanations(LIME)algorithm.Results Among the 174 patients,115(66.1%)achieved clinical remission.From the clinical information and CT images,1 clinical features and 10 radiomic features were identified.The area under of ROC curve(AUC)for the radiomics and clinical-radiomics models was 0.750(95%CI:0.616～0.883),and 0.766(95%CI:0.637～0.895),respectively.The F1 score of the optimal clinical-radiomics model was 0.829.LIME algorithm indicated that this best model demonstrated reliability in predicting individual samples.Conclusion The clinical-radiomics prediction model based on machine learning algorithm performs well,and can provide a reference for doctors'clinical decision-making by predicting the response to chemotherapy combined with immunotherapy in patients with esophageal squamous cell carcinoma.

Objective To construct an automatic segmentation model to segment female urine control anatomy on MRI images based on deep learning methods in order to improve the segmentation efficiency and accuracy.Methods A dataset comprising 49 female pelvic floor muscle MRI images[30 women with varying degrees of pelvic organ prolapse(POP)and 19 healthy individuals],obtained from Faculty of Biomedical Engineering and Medical Imaging in Army Medical University,was used for model training and testing.The dataset was split into a training set(17 normal cases and 22 POP cases)and a testing set(4 normal cases and 6 POP cases)in a ratio of 8∶2.The training set was used to train UNet,UNet+++,Dense UNet,and UNet++models separately,and then input into each network.The model achieving the highest testing accuracy was selected as the backbone network.Results Under the training of UNet,UNet+++,Dense UNet,and UNet++,the 4 models achieved average Dice similarity coefficients of 61.82%,57.94%,57.63%,and 62.76%,respectively,for the segmentation of 5 anatomical structures(compressor urethrae,urethra sphincter body,bladder wall,bladder cavity and urethra submucosa).The corresponding Intersection over Union(IoU)score was 49.74%,46.59%,46.07%,and 49.44%,while the accuracy rate was 61.74%,55.03%,59.23%,and 61.91%,respectively for the 4 models.Notably,UNet++consistently outperformed UNet,UNet+++,and Dense UNet across the 3 metrics,indicating that UNet++achieved the highest overall segmentation accuracy.Conclusion In UNet,UNet++,Dense UNet and UNet++for automatic segmentation of 5 female urine control anatomical elements,UNet++achieves the best overall segmentation accuracy.

Humanistic caring for patients in the operating room refers to providing the whole process of caring medical services for patients in the operating room. In order to standardize humanistic caring services for patients in the operating room of medical institutions, improve the comprehensive service level of the operating room, and enhance the surgical experience of patients, the Chinese Association for Life Care released the group standard " Humanistic Caring Management Standards for Patients in the Operating Room" in December 2023. This article interpreted the basic requirements for humanistic caring of patients in the operating room, the environment and facilities for humanistic caring, the procedures and measures for humanistic caring, and the quality management framework, aiming to assist administrators and clinical practitioners across various levels of medical institutions in accurately understanding and effectively implementing the standard, and to provide essential textual reference and practical guidance for promoting the application of the standard.

Objective:To understand the mental problem in elderly male prisoners and its related factors.Methods:A total of 289 elderly male prisoners from five prisons in Sichuan Province were selected.They were assessed with the self-compiled general situation questionnaire,12-item General Health Questionnaire(GHQ-12,with a total score ≥ 3 indicating a tendency towards mental problem),short-form UCLA Loneliness Scale(ULS-8)and Insomnia Severity Index-Chinese Version(ISI-C).Results:The detection rate of mental problem was 41.52％.Multiple factor logistic regression analysis indicated that having a remaining sentence of≥5 years,educa-tional levels of primary school and below,high school or technical secondary school and above,involvement in drug-related crimes,property crimes,violent crimes,good and poor relationships with spouses,average relationships with fellow inmates,self-assessed blood pressure levels that were low and high,and having insomnia were risk fac-tors for mental problem(OR=9.55,11.75,13.88,82.24,33.96,363.52,5.77,113.27,2.33,1.87,3.80,42.89).Conclusion:The mental problem among elderly male prisoners are related to their sentence,education lev-el,crime type,relationship with spouse and cellmates,self-rated blood pressure and sleep status.

OBJECTIVE To analyze the status of targeted monitoring of the health care-associated infections in in-tensive care unit(ICU)of a three-A hospital of northwest China in recent 7 years so as to provide bases for formu-lating effective prevention and control measures for the health care-associated infections.METHODS The related data were successively collected from the ICU hospitalized patients of the Second Affiliated Hospital of Air Force Medical University who were under the targeted monitoring by nosocomial infection real-time monitoring system from Jan.2017 to Dec.2023.The data included the incidence of infections,infection sites,use of catheters,inci-dence of catheter-related infections,and distribution and prevalence trend of pathogens.RESULTS A total of 49,137 hospitalized patients from five ICU wards of respiratory medicine department,neurosurgery department,neurology department,thoracic surgery department and critical care medicine department were under the monito-ring,1446(1681 case-times)of whom had health care-associated infections,with the infection rate 2.94％,the case-time infection rate 3.42％.The respiratory system was the major infection site of the patients with the health care-associated infections.Among the patients with instrument-associated infections,20.70％had ventilator-asso-ciated pneumonia(VAP),5.71％had urinary catheter-associated urinary tract infection(CAUTI),and 1.96％had catheter-related bloodstream infection(CRBSI).Totally 405 strains of non-repetitive pathogens were isolated from 477 patients with instruments-associated infections,78.77％of which were gram-negative bacteria.The iso-lation rate of multidrug-resistant organisms(MDROs)was 44.12％,and Acinetobacter baumannii was the pre-dominant species of pathogen isolated from the patients with VAP.CONCLUSIONS The targeted monitoring of health care-associated infections may facilitate the awareness of dynamic changes of the infections in a accurate and timely manner so as to provide bases for developing effective prevention and control measures for the health care-associated infection.It is necessary to strengthen the prevention and control of the infections in critical care medi-cine department,neurosurgery department as well as the lower respiratory tract infections and prevent the MDROs infection in the meantime.

OBJECTIVE To explore the risk factors for polymyxin-and carbapenem-resistant Klebsiella pneumoni-ae(PR-CRKP)infection and establish the prediction model.METHODS The clinical data were retrospectively col-lected from the patients with CRKP infection who were treated in the First Affiliated Hospital of Xi'an Jiaotong University from Jan.2023 to Mar.2024.The enrolled patients were divided into the CRKP group and the PR-CRKP group according to the result of drug susceptibility testing for polymyxin B.Totally 203 patients who were treated from Jan.2023 to Dec.2023 were assigned as the modeling group,and 91 patients who were treated from Jan.2024 to Mar.2024 were assigned as the validation group.Multivariate logistic regression analysis was per-formed for the risk factors for PR-CRKP infection,nomogram was built up for prediction of PR-CRKP infection by R software,and the predictive efficacy of the model was evaluated by means of receiver operating characteristic(ROC)curves.RESULTS The result of univariate analysis showed that the proportions of patients who received fi-berobronchoscopy,endotracheal intubation/tracheotomy,were complicated with other carbapenem-resistant or-ganisms(CROs)infections,bloodstream infections,were treated in intensive care unit(ICU)and had the history of exposure to polymyxins and carbapenems 3 months before the admission were higher in the PR-CRKP group than in the CRKP group(P＜0.05);the length of hospital stay and duration of use of polymyxins and carbapene-ms were longer in the PR-CRKP group than in the CRKP group(P＜0.05).Multivariate logistic regression analy-sis indicated that complication with other CROs infections,history of exposure to polymyxins and carbapenems 3 months before the admission,duration of use of polymyxins and ICU stay were the risk factors for the PR-CRKP infection(P＜0.05).The area under the curve(AUC)of the predictive model was 0.898 in the modeling group,with the sensitivity 80.33％,the specificity 84.51％.ROC curve analysis showed that the AUC was 0.901 in the validation group,with the sensitivity 75.00％,the specificity 92.73％.CONCLUSION The prediction model that is established based on the result of multivariate analysis has high value in prediction of PR-CRKP infection.