Objective To summarize and analyze the efficacy and influencing factors of second allogeneic hematopoietic stem cell transplantation (allo-HSCT) for acute leukemia relapsing after the first allo-HSCT. Methods Clinical data of 17 patients with acute leukemia who underwent second allo-HSCT at Peking University First Hospital from January 2005 to December 2024 were retrospectively analyzed. Results Among the 17 patients, 7 achieved long-term disease-free survival after second transplantation. The median progression-free survival after successful second transplantation was 7 months (range 8 days to 69 months). The relapse fatality was 24%, and the transplant-related fatality was 35%. Conclusions Second transplantation is an effective treatment for relapsed and refractory acute leukemia, but the relapse fatality and transplant-related fatality remain high. Patient age, time of relapse after the first transplantation and disease status before second transplantation are all factors that affect the efficacy of second transplantation. Younger age, late relapse and complete remission of disease before second transplantation are all beneficial for long-term disease-free survival after second transplantation.

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male

Nutritional support therapy is one of the extremely important treatment methods for patients in the intensive care unit. Timely and effective nutritional support regimens can improve patients' immune function, reduce complications, and optimize clinical outcomes. Energy expenditure is influenced by multiple factors, including patients' baseline characteristics (such as physical condition, gender, age) and dynamic changes in indicators (such as body temperature, nutritional support regimens, and therapeutic interventions). The currently recognized "gold standard" for accurately assessing energy metabolism in clinical practice is the indirect calorimetry system, also known as the metabolic cart. This device monitors carbon dioxide production and oxygen consumption in real time and uses specific algorithms to estimate the metabolic proportions of the three major nutrients (carbohydrates, fats, and proteins) in energy expenditure. An appropriate nutrient ratio helps maintain the balance between supply and demand in the body's nutritional metabolism. In the management of critically ill patients, the application of the metabolic cart enables personalized nutritional therapy, avoiding over- or under-supply of energy and optimizing the use of medical resources. Furthermore, with real-time, quantitative data support from the energy metabolism monitoring system, clinicians can develop more precise nutritional intervention strategies, thereby improving patient prognosis. This article provides a systematic review of the technical features of the metabolic cart and its application value in various critical care scenarios, aiming to offer a reference for indirect calorimetry in clinical practice.
Humans ; Critical Illness/therapy* ; Nutritional Support ; Energy Metabolism ; Calorimetry, Indirect

OBJECTIVES: This study aimed to investigate the association between temporomandibular disorder (TMD) and insomnia using a two-sample Mendelian randomization (MR) approach. METHODS: Bidirectional MR analyses of two samples, TMD (n=377 277) and insomnia (n=375 359), were performed using genome-wide association study statistics published in the FinnGen database. Instrumental variables were first screened, and then inverse variance weighting (IVW) and MR-Egger were used as the main-effect assessment methods. Weighted median, weighted mode, and simple mode served as supplementary methods. We used IVW and MR-Egger to test for heterogeneity, as well as MR-Egger intercepts to assess the single nucleotide polymorphism (SNP) potential level of multiplicity effects. Sensitivity analyses were conducted based on leave-one-out to identify potentially influential SNPs. All analyses were conducted by using the two-sample MR R package and were considered statistically significant when P<0.05. RESULTS: MR analysis showed the presence of TMD on insomnia (OR=1.089, 95%CI: 1.017-1.166, P=0.014). Meanwhile, no effect of insomnia on TMD (OR=0.996, 95%CI: 0.964-1.029, P=0.816) was found. The sensitivity-analysis showed that no heterogeneity existed (P>0.05), and the presence of horizontal pleiotropy was not detected (P>0.05). Leave-one-out sensitivity analysis showed no single SNP, which may affect the causal relation. All findings indicated that the causal relationship between TMD and insomnia was not significantly affected by any individual SNP and that IV did not bias the results. CONCLUSIONS Results of MR analyses showed that TMD is a risk factor for insomnia, whereas insomnia is not a risk factor for TMD.
Humans ; Sleep Initiation and Maintenance Disorders/genetics* ; Mendelian Randomization Analysis ; Polymorphism, Single Nucleotide ; Temporomandibular Joint Disorders/complications* ; Genome-Wide Association Study

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

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 describe the clinical and pathological features of patients with myofasciitis.Methods:The clinical manifestations and auxiliary examination (laboratory, electromyogram, imaging and muscle biopsy) results of 52 patients with myofasciitis diagnosed by pathology at Peking University First Hospital from August 2002 to December 2024 were collected and analyzed.Results:Among the 52 patients (33 males and 19 females), the age of disease onset was (34.4±16.4) years (6.0-73.0 years) and the disease duration was 17.7 (0.3, 120.0) months; the main symptoms included myalgia in the distal limbs (28 cases, 53.8%), diffuse cutaneous or muscle sclerosis (21 cases, 40.4%), muscle weakness (22 cases, 42.3%) and limited joint activity (23 cases, 44.2%); 12 patients (23.1%) were combined with other diseases. All patients had no history of vaccination. Laboratory examinations showed that 80.8% (21/26) of patients had elevated C-reactive protein, 80.0% (20/25) had elevated erythrocyte sedimentation rate, and 26.5% (9/34) had elevated creatine kinase. Among 19 patients undergoing electromyography, 6 cases showed myogenic changes, 4 cases showed neurogenic changes, 1 case showed both myogenic and neurogenic changes, and 8 cases showed no obvious abnormality. Myofascial edema was observed in all 15 patients who underwent muscle magnetic resonance imaging, with partial involvement of adjacent muscles in some cases. According to myopathological changes, the 52 patients were divided into macrophagic myofasciitis in 41 cases (78.8%), lymphocytic myofasciitis in 7 cases (13.5%), and eosinophilic fasciitis in 4 cases (7.7%). Among the 52 patients, fibroblast proliferation in the myofascia was present in 39 cases (75.0%), subfascial muscle fiber atrophy in 28 cases (53.8%), and scattered muscle fiber necrosis and regeneration in 15 cases (28.8%). Major histocompatibility complex class Ⅰexpression on muscle fibers was positive in 89.5% (34/38) of patients, and membrane attack complex deposition on muscle fibers and/or capillary walls was present in 39.5% (15/38) of patients. Among 25 patients with follow-up, all received low-dose oral glucocorticoids, and 7 additionally received methotrexate, intravenous immunoglobulin, or hydroxychloroquine. During follow-up, 22 patients showed clinical improvement, 1 patient remained stable, and 2 patients died.Conclusions:Non-vaccine-associated macrophagic myofasciitis is the most common pathological subtype of myofasciitis. A few patients are concomitant with other diseases. Muscle magnetic resonance imaging is helpful in the diagnosis of the disease. Most patients respond to immunosuppressive treatment.

[This corrects the article DOI: 10.1016/j.jpha.2023.08.006.].

Objective To develop an automated system that can accurately determine the relationship between the mandibular third molar and the mandibular nerve canal from panoramic images.Methods A dataset consisting of 600 panoramic images of the oral cavi-ty was selected,and the positions of the mandibular third molar and the mandibular nerve canal were accurately labeled.We compared the research designed TI-YOLOv5 with PANet,Faster R-CNN,Mask R-CNN,ResNeSt-101,and the original YOLOv5 in image seg-mentation tasks,with evaluation metrics of AP and AP50.Results TI-YOLOv5 achieved AP(average precision)54.0％and AP5094.9％,an increase of 4.9 and 6.7 percentage points respectively compared to the original YOLOv5(AP 49.1％,AP50 88.2％),and surpassed other SOTA methods such as Mask R-CNN(AP 45.1％,AP50 84.2％).Conclusion TI-YOLOv5 is significantly superior to mainstream networks in automatic positioning and relationship classification of mandibular wisdom teeth and neural tubes,with high de-tection accuracy and discrimination accuracy,and can provide reliable technical support for preoperative risk assessment of mandibular wisdom tooth extraction.