Objective To explore the feasibility and reference value of allogeneic lung transplantation and postoperative monitoring in miniature pigs for lung transplantation research. Methods Two miniature pigs (R1 and R2) underwent left lung allogeneic transplantation. Complement-dependent cytotoxicity tests and blood cross-matching were performed before surgery. The main operative times and partial pressure of arterial oxygen (PaO₂) after opening the pulmonary artery were recorded during surgery. Postoperatively, routine blood tests, biochemical blood indicators and inflammatory factors were detected, and pathological examinations of multiple organs were conducted. Results The complement-dependent cytotoxicity test showed that the survival rate of lymphocytes between donors and recipients was 42.5%-47.3%, and no agglutination reaction occurred in the cross-matching. The first warm ischemia times of D1 and D2 were 17 min and 10 min, respectively, and the cold ischemia times were 246 min and 216 min, respectively. Ultimately, R1 and R2 survived for 1.5 h and 104 h, respectively. Postoperatively, in R1, albumin (ALB) and globulin (GLB) decreased, and alanine aminotransferase increased; in R2, ALB, GLB and aspartate aminotransferase all increased. Urea nitrogen and serum creatinine increased in both recipients. Pathological results showed that in R1, the transplanted lung had partial consolidation with inflammatory cell infiltration, and multiple organs were congested and damaged. In R2, the transplanted lung had severe necrosis with fibrosis, and multiple organs had mild to moderate damage. The expression levels of interleukin-1β and interleukin-6 increased in the transplanted lungs. Conclusions The allogeneic lung transplantation model in miniature pigs may systematically evaluate immunological compatibility, intraoperative function and postoperative organ damage. The data obtained may provide technical references for subsequent lung transplantation research.

OBJECTIVE To formulate Guidelines for the standardized implementation of pharmacist-managed clinics （ 2026 edition ） in response to the challenges faced by such clinics in China， including uneven development， large discrepancies in service specifications， insufficient patient awareness， and limited medical insurance coverage. METHODS Led by the Pharmaceutical Affairs Professional Committee of the Chinese Hospital Association， the Evidence-based Pharmacy Professional Committee of the Chinese Pharmaceutical Association， and the Hospital Pharmacy Professional Committee of the Cross-strait Medical and Health Exchange Association， a total of 19 domestic hospital pharmacy experts were organized. Through a systematic review of national policies and literature research， current practical experience was summarized. Consensus on the contents of the guidelines was reached after in-depth discussions. RESULTS &CONCLUSIONS The guidelines covered five sections： definition and connotation of pharmacist-managed clinics， establishment requirements， implementation and management， post competency， and practical research. Firstly， the definition and connotation included three operational forms of pharmacist-managed clinics （independent mode， physician-pharmacist joint mode， and online pharmacist-managed clinic mode） and classified service modes （specialty-specific， drug-specific， and disease-specific pharmacist-managed clinics）. The establishment requirements were further refined， covering system construction （pharmaceutical service management system， quality control and assessment mechanism）， personnel qualifications （professional credentials， continuing education and professional training， etc）， service recipients， as well as service venues and facilities. Subsequently， the implementation and management of pharmacist-managed clinics were proposed， involving service procedures， intervention measures， documentation and records， patient education and follow-up， humanistic care， as well as risk management and quality control. Finally， post competency encompassed the competency requirements for pharmacists providing services in pharmacist-managed clinics， as well as the suggestions on teaching methods； practical research encouraged the conduct of high-quality pharmaceutical practice in the setting of pharmacist-managed clinics. The guidelines provide valuable guidance for the standardized implementation of pharmacist-managed clinics in China in terms of establishment， management， teaching， and research， fill the guideline gap in this field， and can promote the high-quality development of pharmacist-managed clinics.

Background: and Purpose Vertebrobasilar fusiform aneurysms (VBFAs) carry substantial morbidity and mortality, but optimal management for unruptured VBFAs remains unclear. We compared the safety and efficacy of conservative management (CM), stent-assisted coiling (SAC), and flow diverters (FDs) in patients with unruptured VBFAs, focusing on long-term prognosis. Methods: This study included data from a nationwide Chinese cohort of patients with vertebrobasilar dissecting aneurysms. Inverse probability of treatment weighting (IPTW) balanced confounders across groups. The primary outcome was poor prognosis (modified Rankin Scale score >2). Secondary outcomes included aneurysm rupture, ischemic stroke, compression symptoms, and VBFA-related deaths. Logistic regression estimated odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup and sensitivity analyses were performed. Results: Among 1,115 patients with unruptured VBFAs, 838 (median age, 54 years; 655 men) were included. After IPTW, baseline characteristics were balanced. Median follow-up was 54 months. FD was associated with a lower risk of poor prognosis than CM (OR, 0.48 [95% CI, 0.30 to 0.77]; p=0.002), with no difference between CM and SAC. FD also reduced aneurysm rupture (OR, 0.20 [95% CI, 0.07 to 0.60]; p=0.004) and compression symptoms (OR, 0.30 [95% CI, 0.13 to 0.68]; p=0.004) versus CM. Time-to-event analyses further revealed significant differences in vertebral artery lesions and Type I–II VBFAs, whereas no significant differences were observed in basilar or vertebrobasilar junction lesions or in Type III–IV VBFAs. Conclusions Compared with CM, FD was associated with improved long-term outcomes in unruptured VBFAs, particularly in vertebral artery lesions and Type I–II VBFAs, although residual confounding cannot be excluded.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Definitive chemoradiotherapy (dCRT) has become a cornerstone in the treatment of locally advanced esophageal cancer; however, local control remains suboptimal, and persistent lesions or locoregional recurrences after treatment are not uncommon. For patients without distant metastases but with local failure, whether surgical intervention can still offer curative potential remains a major clinical dilemma. Salvage esophagectomy (SE) offers potential long-term survival for selected patients, but this procedure is performed in the context of severe fibrosis, impaired local blood supply, and obscured anatomical planes following chemoradiotherapy, resulting in significantly higher perioperative risk compared to primary esophagectomy. Consequently, controversies exist regarding patient selection, preoperative restaging, choice of surgical approach, extent of lymphadenectomy, gastrointestinal reconstruction, and perioperative management. In recent years, with the refinement of restaging modalities such as PET/CT, the accumulation of experience in high-volume centers, and emerging evidence from clinical studies, the clinical role of SE has gradually shifted from a "high-risk salvage measure" to a "selective curative strategy aimed at achieving long-term survival in carefully selected patients". Nevertheless, standardized guidelines for patient selection, technical approaches, and perioperative management are still lacking. Based on current evidence and clinical experience, experts organized by the Integrated Esophageal Cancer Committee of Chinese Anti-Cancer Association systematically reviewed key issues regarding SE, including its definition, indications, preoperative evaluation, choice of surgical approach, lymphadenectomy, gastrointestinal reconstruction, and perioperative management, and formulated a Chinese expert consensus. This consensus aims to provide guidance for standardized assessment, appropriate referral, individualized surgical decision-making, and optimized perioperative management of patients with locoregional failure after dCRT. Ultimately, this will increase the likelihood of R0 resection, reduce the risk of severe complications, and promote the safer, more judicious, and standardized implementation of SE in high-risk scenarios.

BACKGROUND:Human periodontal ligament stem cells are potential functional cells for periodontal tissue engineering.However,long-term in vitro culture may lead to reduced stemness and replicative senescence of periodontal ligament stem cells,which may impair the therapeutic effect of human periodontal ligament stem cells. OBJECTIVE:To investigate the effect of oxymatrine on the stemness maintenance and osteogenic differentiation of periodontal ligament stem cells in vitro,and to explore the potential mechanism. METHODS:Periodontal ligament stem cells were isolated from human periodontal ligament tissues by tissue explant enzyme digestion and cultured.The surface markers of mesenchymal cells were identified by flow cytometry.Periodontal ligament stem cells were incubated with 0,2.5,5,and 10 μg/mL oxymatrine.The effect of oxymatrine on the proliferation activity of periodontal ligament stem cells was detected by CCK8 assay.The appropriate drug concentration for subsequent experiments was screened.Western blot assay was used to detect the expression of stem cell non-specific proteins SOX2 and OCT4 in periodontal ligament stem cells.qRT-PCR and western blot assay were used to detect the expression levels of related osteogenic genes and proteins in periodontal ligament stem cells. RESULTS AND CONCLUSION:(1)The results of CCK8 assay showed that 2.5 μg/mL oxymatrine significantly enhanced the proliferative activity of periodontal stem cells,and the subsequent experiment selected 2.5 μg/mL oxymatrine to intervene.(2)Compared with the blank control group,the protein expression level of SOX2,a stem marker of periodontal ligament stem cells in the oxymatrine group did not change significantly(P>0.05),and the expression of OCT4 was significantly up-regulated(P<0.05).(3)Compared with the osteogenic induction group,the osteogenic genes ALP,RUNX2 mRNA expression and their osteogenic associated protein ALP protein expression of periodontal ligament stem cells were significantly down-regulated in the oxymatrine+osteogenic induction group(P<0.05).(4)The oxymatrine up-regulated the expression of stemness markers of periodontal ligament stem cells and inhibited the bone differentiation of periodontal ligament stem cells,and the results of high-throughput sequencing showed that it may be associated with WNT2,WNT16,COMP,and BMP6.

BACKGROUND:Previous studies have confirmed that Wen-Shen-Tong-Du Decoction can promote the recovery of spinal cord injury by inhibiting pyroptosis of splenic B cells,promoting the phagocytosis of myelin debris by microvascular endothelial cells,affecting the migration and infiltration of microglia,promoting the recovery of damaged neurons,and decreasing neuronal apoptosis after spinal cord injury,but the mechanism of this is still not clear. OBJECTIVE:To investigate the effect of Wen-Shen-Tong-Du Decoction on the triggering receptor expressed on myeloid cells 2(TREM2)and PI3K/Akt signaling pathways in mice following spinal cord injury. METHODS:Thirty-six C57BL/6 mice were selected and randomly divided into a sham-operation group,a model group and a Wen-Shen-Tong-Du Decoction group,with 12 mice in each group.In the model and Wen-Shen-Tong-Du Decoction groups,mouse models of T10 spinal cord injury were prepared by the modified Allen's method.On the 1st day after modeling,the Wen-Shen-Tong-Du Decoction group was given Wen-Shen-Tong-Du Decoction by gavage,and the sham-operation group and the model group were given saline by gavage once a day for 28 days.During the drug administration period,mouse motor function was evaluated by Basso Mouse Scale score and inclined plane test.On the 7th and 28th days after modeling,hematoxylin-eosin staining was used to observe the histopathological changes in the spinal cord tissue of the mice;immunofluorescence double staining was used to detect the protein expression of ionized calcium binding adaptor molecule 1(IBA1)and TREM2;and western blot assay was used to detect the expression of TREM2,PI3K,p-PI3K,Akt,p-Akt,Bcl2,Bax and Caspase3 in spinal cord tissue. RESULTS AND CONCLUSION:Basso Mouse Scale scores and inclined plane test results indicated that the motor function of the mouse hindlimbs was declined after spinal cord injury,and Wen-Shen-Tong-Du Decoction significantly improved motor function in mice with spinal cord injury.Hematoxylin-eosin staining results revealed that Wen-Shen-Tong-Du Decoction significantly ameliorated the pathological structure of spinal cord tissue compared with the model group,manifesting as reduced degrees of dorsal white matter and neuronal atrophy,decreased cytoplasmic vacuolization,and reduced inflammatory cell infiltration.Immunofluorescence double staining results showed that on the 7th day after modeling,the protein expression of IBA1 and TREM2 in the model group was lower than that in the sham-operation group(P＜0.05),and the protein expression of IBA1 and TREM2 in the Wen-Shen-Tong-Du Decoction group was higher than that in the model group(P＜0.05);on the 28th day after modeling,the protein expression of TREM2 in the model group was lower than that in the sham-operation group(P＜0.05),and the protein expression of TREM2 in the spinal cord tissue of the mice in the Wen-Shen-Tong-Du Decoction group was higher than that in the model group(P＜0.05).Western blot results analysis demonstrated that on the 7th day after modeling,compared with the sham-operation group,the model group exhibited a significant reduction in TREM2,PI3K,and Bcl2/Bax(P＜0.05),as well as a significant increase in p-Akt,Bax and p-Akt/Aktp-PI3K(P＜0.05);compared with the model group,the Wen-Shen-Tong-Du Decoction group showed a significant increase in TREM2,PI3K,p-PI3K,Akt,p-Akt,Bcl2,p-PI3K/PI3K,p-Akt/Ak,and Bcl2/Bax(P＜0.05),as well as a significant decrease in Bax and Caspase3 protein expression(P＜0.05).On the 28th day after modeling,compared with the sham-operation group,the model group exhibited a significant reduction in TREM2,PI3K,p-PI3K,Akt,p-Akt,Bcl2 and Bcl2/Bax(P＜0.05),as well as a significant increase in Bax protein expression(P＜0.05);compared with the model group,the Wen-Shen-Tong-Du Decoction group showed a significant increase in TREM2,PI3K,Akt,p-Akt,Bcl2,and Bcl2/Bax(P＜0.05),as well as a significant decrease in Bax protein expression(P＜0.05).To conclude,Wen-Shen-Tong-Du Decoction may activate the PI3K/Akt signaling pathway by up-regulating the expression of TREM2 protein in microglia,and then inhibit neuronal apoptosis,thus exerting neuroprotective effects and promoting the repair of spinal cord injury.

ObjectiveAutoimmune thyroiditis （AIT） is a complex and immune-mediated disorder， with no established treatment protocol. Both Western and traditional Chinese medicine （TCM） focus on the pathogenesis and treatment of AIT. This study evaluated the clinical consistency of existing AIT animal models based on the diagnostic criteria of both Western and TCM， using a novel evaluation method. Additionally， it proposed recommendations and future prospects for improving these models. MethodsA comprehensive literature review was conducted on existing AIT animal models， using databases and the diagnostic criteria of both Western and TCM. Core and accompanying symptoms of these models were scored based on the diagnostic criteria of both Western and TCM， and clinical consistency was assessed. ResultsMice are the primary experimental animals used in AIT modeling. Modeling methods include vaccine immunization， iodine induction， heterologous thyroid antigen immunization， and a combination of high iodine water and antigen immunization. The average consistency of clinical syndromes based on TCM and Western medicine is 40%， 60%， 54%， and 63%， with the highest consistency observed in the combined high iodine water and antigen immunization model. Pathological models based on TCM are less common， with the liver-stagnation-spleen-deficiency rat model showing high clinical consistency. While most models are designed according to Western medical theory， meeting the surface and structural effectiveness criteria of Western medicine. However， there is a lack of fine-tuning and clear differentiation of TCM syndromes. ConclusionCurrent AIT syndrome-disease combination animal models primarily reflect the pathological features of Western medicine， with limited integration of TCM syndromes. Future research should aim to combine the syndrome characteristics of TCM with the pathological features of Western medicine， creating multi-factor and dynamic syndrome-disease models. Such models would better facilitate an experimental platform that conforms to the theories of TCM， providing more comprehensive support and guidance for the pathogenesis and treatment strategies of AIT.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results. Building on their image-recognition abilities, multimodal LLMs (MLLMs) show promising potential for diagnosis based on radiography, chest computed tomography (CT), electrocardiography (ECG), and common pathological images. These models can also assist in treatment planning by suggesting evidence-based interventions and improving clinical decision support systems through integrated analysis of patient records. Despite these promising developments, significant challenges persist regarding the use of LLMs in medicine, including concerns regarding algorithmic bias, the potential for hallucinations, and the need for rigorous clinical validation. Ethical considerations also underscore the importance of maintaining the function of supervision in clinical practice. This paper highlights the rapid advancements in research on the diagnostic and therapeutic applications of LLMs across different medical disciplines and emphasizes the importance of policymaking, ethical supervision, and multidisciplinary collaboration in promoting more effective and safer clinical applications of LLMs. Future directions include the integration of proprietary clinical knowledge, the investigation of open-source and customized models, and the evaluation of real-time effects in clinical diagnosis and treatment practices.
Humans ; Large Language Models ; Tomography, X-Ray Computed