Objective:To explore the difference of type 2 innate lymphoid cell(ILC2),IL-9 and related cytokines between chronic lymphocytic leukemia(CLL)patients and normal individuals,as well as the correlation between ILC2 and IL-9 and other cytokines in CLL patients.Methods:Flow cytometry was used to detect the expression of ILC2 and regulatory T cells(Tregs)in peripheral blood of 26 CLL patients at initial diagnosis and 10 healthy controls.RT-qPCR was used to detected IFN-γ,TGF-β,IL-9 and IL-10 mRNA in peripheral blood mononuclear cell(PBMC).ELISA was used to detect serum IFN-γ,TNF-α,TGF-β,IL-9,IL-10 and IL-21.ILC2 and IL-9 were observed in the cervical lymph node of 12 CLL patients at initial diagnosis and 12 patients with reactive lymphoid hyperplasias by multiplex indirect immunofluorescence staining.Spearman test was used to analyze the correlation between peripheral blood ILC2 and IL-9,IL-9 and IL-21,IFN-γ mRNA and IL-10 mRNA in CLL patients.Pearson test was used to analyze the correlation between TNF-α and TGF-β in CLL patients.Results:Compared with control group,the proportions of ILC2 and Tregs were significantly increased in CLL group(both P＜0.05).The mRNA expressions of IFN-γ,IL-9,IL-10 and TGF-β in PBMCs of CLL patients were significantly increased(all P＜0.05).In CLL patients,the expressions of IFN-γ,TNF-α,TGF-β,IL-9 and IL-10 in serum were significantly increased(all P＜0.01),while IL-21 slightly increased without statistical difference(P＞0.05).In CLL patients,the peripheral blood ILC2 was positively related to IL-9(r=0.56),IL-9 was positively related to IL-21(r=0.397),IFN-γ mRNA was positively related to IL-10 mRNA(r=0.623),and TNF-α was positively related to TGF-β(r=0.577).Compared with reactive lymphoid hyperplasias patients,the mean fluorescence intensities of GAT A3 and CRTH2 representing ILC2 and IL-9 in cervical lymph nodes were significantly increased in the CLL group(all P＜0.001),and showed colocalization.Conclusion:In CLL patients,the proportions of ILC2 and IL-9 in peripheral blood and lymph nodes increase,and ILC2 and IL-9 show colocalization in lymph nodes.There is a positive correlation between ILC2 and IL-9 in the peripheral blood of CLL patients,the ability of ILC2 to secrete IL-9 is increased,and ILC2 may affect the occurrence and development of CLL through IL-9.

Objective To comprehensively analyze the clinical characteristics and risk factors of children with refractory mycoplasma pneumonia(RMPP),precisely identify the joint predictors in these children,and construct a prediction model.This aims to offer a scientific foundation for the early identification of RMPP and the formulation of accurate treatment and medication strategies.Methods A retrospective analysis was performed on the clinical data of 282 children diagnosed with mycoplasma pneumoniae pneumonia(MPP)who were admitted to the Pediatric Department of the Seventh Medical Center of the Chinese People's Liberation Army General Hospital between August 1,2023,and February 29,2024.Among these children,119 with RMPP were classified into the RMPP group,while the remaining 163 with general MPP(GMPP)were assigned to the GMPP group.The clinical data of both groups,encompassing age,gender,duration of fever,symptoms,laboratory test indices,chest imaging data,complications,etc.,were compared.A logistic probability model(LogP model)for joint application was constructed.The discriminatory ability of the model was evaluated using the area under the receiver operating characteristic(ROC)curve,and the calibration of the model was assessed by means of a calibration curve.Results In comparison with the GMPP group,children in the RMPP group exhibited a significantly longer duration of fever(P=0.002).Moreover,they had a higher incidence of complications,including myocardial damage and coagulation dysfunction(P<0.05).Regarding inflammatory markers,the levels of C-reactive protein(CRP),procalcitonin(PCT),and lactate dehydrogenase(LDH)were notably elevated in the RMPP group(P<0.05),whereas the level of albumin(Alb)was lower(P=0.001).In the RMPP group,the levels of interleukin-2(IL-2),interleukin-5(IL-5),interleukin-8(IL-8),interleukin-1β(IL-1β),and D-Dimer were increased,while the levels of interleukin-6(IL-6)and interleukin-17(IL-17)were decreased(P<0.05).Chest computed tomography(CT)scans revealed a higher proportion of lung consolidation,pleural effusion,and atelectasis in the RMPP group(P<0.05).Multivariate logistic regression analysis demonstrated that CRP,total bilirubin(T-BIL),LDH,IL-17,and prothrombin time(PT)were independent risk factors for RMPP(P<0.05).The receiver operating characteristic(ROC)predictive model established based on these factors had an area under the curve(AUC)of 0.787(95%confidence interval[CI]:0.693～0.880),with a cutoff value of 0.421,a sensitivity of 0.786,and a specificity of 0.660.The calibration curve indicated that the predicted probability matched well with the reference probability,and there was no statistical difference in the results of the Hosmer-Lemeshow test(P>0.05).Conclusions The clinical features of children with RMPP are predominantly characterized by prolonged fever,moderate lung lesions,other organ injuries,and high inflammatory markers.CRP,T-BIL,LDH,IL-17,and PT can act as independent risk factors for RMPP.

AIM To study the chemical constituents from Periploca forrestii Schltr and their antitumor activity in vitro.METHODS Silica gel and Sephadex LH-20 were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The in vitro antitumor activity was evaluated by MTT mothod.RESULTS Twenty-four compounds were isolated and identified as lysidicichin(1),fraxidin(2),methoxylatifolone(3),corilagin(4),ligballinol(5),6-dehydroprogesterone(6),anomallenodiol(7),mustakone(8),eupatoricacid(9),honokiol(10),methyl 4-hydroxybenzoate(11),5,6,7,8-tetramethoxycoumarin(12),6,7-dimethoxycoumarin(13),5,6,7,4'-tetramethoxyflavone(14),2,3,2",3"-tetrahydrospirotaxone(15),sequoiavone(16),isocubebin(17),isoquercitrin(18),mellein(19),pistaciamide(20),suberoyltrigone(21)、daucosterol(22)、berchemol(23)、confluentin(24).The IC50 value of compound 18 for lung cancer cell NCI-H596 was(27.41±3.36)μmol/L.CONCLUSION Compounds 1-24 are isolated from P.forrestii for the first time.Compound 18 has good antitumor activity in vitro.

Objective To design an individually portable oral treatment device to solve the problems of oral diagnosis and treatment under field conditions in alpine regions.Methods The individually portable oral treatment device had a trolley box structure and consisted of an outer box,an inner framework and an operation panel.The outer box was made of low-density polyethylene material and formed by by one-time rotational moulding process;the inner framework integrated a plateau com-pressor,an independent negative-pressure compressor,an integrated control system for programmable logic controller(PLC),an individually portable respiratory synchronized pulsed oxygen supply module for plateau application;there were several curative devices equipped in the operation panel,including a 3-way syringe,a high-speed turbine handpiece,an electric variable-speed handpiece,a water control switch,a light curing machine and an ultrasonic dental cleaning handpiece.Trials were carried out with the test-phase prototype in alpine regions so as to verify the performance of the device.Results Trials proved that the prototype gained advantages in mobility,multifunctionality and pressure supply facilitating continuous operation of power gas source for oral diagnosis and treatment in alpine regions.Conclusion The device developed solves the problems in pressure insufficiency and instability,control system integration,portability and oxygen supply for medical staffs,improves the mobility of oral diagnosis and treatment in alpine regions and enhances the oral support service and equipment effectively.[Chinese Medical Equipment Journal,2025,46(1):108-113]

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

AIM To study the chemical constituents from Periploca forrestii Schltr and their antitumor activity in vitro.METHODS Silica gel and Sephadex LH-20 were used for isolation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The in vitro antitumor activity was evaluated by MTT mothod.RESULTS Twenty-four compounds were isolated and identified as lysidicichin(1),fraxidin(2),methoxylatifolone(3),corilagin(4),ligballinol(5),6-dehydroprogesterone(6),anomallenodiol(7),mustakone(8),eupatoricacid(9),honokiol(10),methyl 4-hydroxybenzoate(11),5,6,7,8-tetramethoxycoumarin(12),6,7-dimethoxycoumarin(13),5,6,7,4'-tetramethoxyflavone(14),2,3,2",3"-tetrahydrospirotaxone(15),sequoiavone(16),isocubebin(17),isoquercitrin(18),mellein(19),pistaciamide(20),suberoyltrigone(21)、daucosterol(22)、berchemol(23)、confluentin(24).The IC50 value of compound 18 for lung cancer cell NCI-H596 was(27.41±3.36)μmol/L.CONCLUSION Compounds 1-24 are isolated from P.forrestii for the first time.Compound 18 has good antitumor activity in vitro.