Objective: To identify the mimicking autoantibodies using papain-enhanced erythrocyte agglutination in a case of repeated red blood cell transfusion refractoriness, aiming to explore the immune hematological methods for identifying mimicking alloantibodies, autoantibodies and alloantibodies, and to develop a safe and effective blood transfusion strategy based on the results. Methods: ABO, RhD and RhEeCc blood groups were detected using routine blood group serological method. The unexpected antibodies in plasma were screened and identified, followed by identification using a two-step papain-treated indirect antiglobulin test (enzyme-IAT). The cause of transfusion refractoriness of red blood cells was analyzed and summarized, and the prognosis was followed up. Results: The patient's blood type was type A, CCDee. The direct antiglobulin test (DAT) was positive. Unexpected antibody screening and identification using saline tube method, polybrene method, IAT were negative, and the release fluid (acid release) IAT identification was negative. Mimicking anti-e antibodies in plasma was identified by enzyme-ITA. The cause of red blood cell transfusion refractoriness in patients was autoimmune hemolysis caused by mimicking anti-e antibodies. After choosing to avoid antibodies corresponding to antigen-positive red blood cells, the patient's hemoglobin (Hb) increase value is in line with theoretical expectations, indicating effective red blood cell transfusion. Conclusion: Mimicking antibodies can cause immune destruction of red blood cells by non-specific binding to their own red blood cells and specific binding to red blood cells, resulting in red blood cell transfusion refractoriness.

To evaluate long-term survival and clinical outcomes of patients with knee osteo-arthritis undergoing total knee arthroplasty (TKA) through long-term follow-up.

To analyze the occurrence of early complications after total hip arthroplasty (THA) in patients with systemic lupus erythematosus (SLE).

Objective:To evaluate the alveolar ridge preservation effect of immediate implantation at extraction site with the im-proved CBCT measuring method.Methods:Eighty patients with extraction site were divided into test group A,B,C and control group.The patients were treated by means of immediate implant placement combined with large flap surgery,guided bone regener-ation(GBR)using mass Bio-Oss bone particles in the group A(the thickness of facial bone wall＜1 mm);The patients were trea-ted by means of immediate implant placement combined without flap surgery and bone graft in the group B(the thickness of facial bone wall ≥1 mm and＜2 mm)and C(the thickness of facial bone wall ≥2 mm),the CGF was implanted in the jumping space only when the thickness of jumping space was＞2 mm.In the control group,the alveolar sockets healed naturally without any in-tervention or treatment.CBCT was taken before surgery,immediately after surgery,and 6 months after surgery to evaluate the height and width of alveolar bone,the thickness of facial bone wall and jumping space.Results:The reduction of alveolar ridge height in group A,B,C and control group was(0.41±0.13,0.94±0.18,0.59±0.12,1.31±0.19)mm,The reduction of alveolar ridge width in group A,B,C and control group was(0.93±0.10,1.48±0.21,1.12±0.17,1.66±0.16)mum.The re-sults of four groups were statistically different(F=177.0,P＜0.001;F=125.3,P＜0.001).The alveolar ridge thickness of facial bone wall in group A,B,C and con-trol group was(0.98±0.25,2.39±0.28)mm,(1.43±0.52,2.10±0.33)mm,(2.17±0.41,2.79±0.27)mm before surgery and six months after immediate implantation.The results of each group were statistically different between before surgery and six months after immediate implantation(t=16.45,P＜0.001;t=7.357,P＜0.001;t=5.488,P＜0.001).Patients in three test groups had the thickness of jumping space＞2 mm and ≤2 mm,and the reduction of alveolar ridge width was(0.78±0.18,0.88±0.17)mm.The results were statistically different(t=17.18,P=0.018).Conclusion:The alveolar ridge preservation was obtained by means of immediate implant placement combined with large flap surgery,guided bone regeneration(GBR)using mass Bio-Oss bone particles at extraction site with the thickness of facial bone wall＜1 mm;The alveolar ridge preservation was obtained without flap surgery and GBR at extraction site with the thickness of facial bone wall≥1 mm.The preservation of soft and hard tissue was better in the axial palatal side of immediate implantation with the thickness of jumping space＞2 mm than that with the thickness of jumping space≤2 mm.

Objective To develop and validate a prediction model for risk of amputation in patients with diabetic foot ulcers(DFU)based on systematic review and meta-analysis.Methods The studies on the risk factors of amputation in DFU patients was retrieved by using subject words+free words.After screening,37 cohort studies were finally included,and the Newcastle-Ottawa scale(NOS)was used for quality evaluation.Meta-analysis was performed on the risk factors of amputation in DFU.Then a prediction model for DFU amputation risk were constructed based on the statistically significant risk factors in the meta-analysis.The corresponding β value was calculated based on the combined odds ratio(OR)value of each risk factor,and each risk factor was scored to establish a scoring system model.The clinical data of 453 DFU patients hospitalized in our department from 2021 to 2023 were collected as a validation cohort.Receiver operating characteristic(ROC)curve analysis was used to evaluate the model performance.The area under the curve(AUC)was calculated,and the optimal cutoff score was determined by calculation of the maximum Youden index through sensitivity and specificity.Results Our meta-analysis showed a cumulative amputation rate of approximately 34.65%in 11 779 DFU patients.The final risk prediction models include gangrene[OR=11.92(5.86～24.24)],ulcer depth[OR=4.93(2.52～9.64)],osteomyelitis[OR=3.19(2.36～4.29)],previous amputation history[OR=3.19(2.00～5.09)]and lower extremity arterial disease[OR=3.10(2.31～4.17)].According to the weights of each risk factor,the total score of the model is 76,and the optimal cut-off score is 36.5.The prediction model performed well,with an AUC value of 0.864(0.824,0.903),a sensitivity of 0.743,a specificity of 0.859,and an accuracy rate of 83.00%.Conclusion A prediction model for DFU amputation risk is developed based on risk factor scoring,and has good discrimination and calibration,providing effective scientific basis for clinical research and clinical decision-making related to DFU amputation.

Smart healthcare plays an important role in easing the strain on medical resources and improving the continuity of chronic disease management. This study analysed the iatrogenic risks from the intrinsic attributes and the external environment of smart healthcare, including doctor-patient conflict risk, technical operation risk, information leakage risk, humanistic absence risk, legal risk, regulatory risk and ethical risk. Based on the " structure process result" model, suggestions were proposed to optimize the construction of a smart healthcare platform for chronic diseases, improve the legal system and industry standards, strengthen talent cultivation and capacity building, establish an integrated regulatory system, and regularly evaluate the effectiveness of chronic disease management. These suggestions provided references for creating a healthy, orderly, and safe smart healthcare environment for chronic disease patients.

Objective:The purpose of this study was to develop a dynamic prediction model for patients with gastric signet ring cell cancer (GSRCC)following laparoscopic radical gastrectomy in order to improve the precision and usefulness of prognoses prediction for overall survival and disease-free survival.Methods:From 2011 to 2018, 914 National Cancer Center patients participated in the study. To find independent prognostic indicators and create a prognostic nomogram model, univariate and multivariate regression analyses were performed. Calibration curves, receiver operating characteristic curves, and consistency indices were used to assess the model's performance. To make clinical application more convenient, two web-based prediction tools were created.Results:A training set of 639 cases and a validation set of 275 instances were randomly selected from among the patients. Important predictive variables such as age, tumor size, location, pN and pT staging, and postoperative chemotherapy were all incorporated in the model (all P<0.05). The model's consistency index and area under the receiver operating characteristic curves were both higher than 0.7, and the calibration curves demonstrated a good fit between the expected and actual values, indicating high accuracy and consistency in postoperative survival prediction for patients with gastric signet ring cell carcinoma. Conclusion:We successfully developed two dynamic prediction models in this study, which improved its clinical practicability using web-based tools and is anticipated to be crucial to clinical practice going forward.

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

Neuropathic pain is frequently comorbidity with cognitive deficits. Neuralized1 (Neurl1)-mediated ubiquitination of CPEB3 in the hippocampus is critical in learning and memory. However, the role of Neurl1 in the cognitive impairment in neuropathic pain remains elusive. Herein, we found that lumbar 5 spinal nerve ligation (SNL) in male rat-induced neuropathic pain was followed by learning and memory deficits and LTP impairment in the hippocampus. The Neurl1 expression in the hippocampal CA1 was decreased after SNL. And this decrease paralleled the reduction of ubiquitinated-CPEB3 level and reduced production of GluA1 and GluA2. Overexpression of Neurl1 in the CA1 rescued cognitive deficits and LTP impairment, and reversed the reduction of ubiquitinated-CPEB3 level and the decrease of GluA1 and GluA2 production following SNL. Specific knockdown of Neurl1 or CPEB3 in bilateral hippocampal CA1 in naïve rats resulted in cognitive deficits and impairment of synaptic plasticity. The rescued cognitive function and synaptic plasticity by the treatment of overexpression of Neurl1 before SNL were counteracted by the knockdown of CPEB3 in the CA1. Collectively, the above results suggest that the downregulation of Neurl1 through reducing CPEB3 ubiquitination and, in turn, repressing GluA1 and GluA2 production and mediating synaptic plasticity impairment in hippocampal CA1 leads to the genesis of cognitive deficits in neuropathic pain.
Animals ; Male ; Neuralgia/metabolism* ; Rats ; Down-Regulation/physiology* ; Ubiquitination/physiology* ; Neuronal Plasticity/physiology* ; Rats, Sprague-Dawley ; CA1 Region, Hippocampal/metabolism* ; Cognitive Dysfunction/metabolism* ; RNA-Binding Proteins/metabolism* ; Receptors, AMPA/metabolism*

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*