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.

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.

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.

This paper summarizes Professor LIU Fengbin's clinical experience in treating autoimmune liver disease （AILD） using the method of nourishing yin and removing stasis based on stage differentiation. He believes that the pathogenesis of AILD generally involves both deficiency in essence and excess in manifestation， with essence deficiency often presenting as liver and kidney yin deficiency， which may progress to spleen deficiency and yang deficiency over time. The excess manifestation commonly includes qi stagnation， blood stasis， damp-heat， and phlegm toxicity. Clinically， he advocates for the treatment principle of nourishing yin and removing stasis. On the foundation of nourishing liver and kidney yin， different pathological factors causing stasis are eliminated according to their nature. Treatment is also tailored to different stages of AILD. In the early and asymptomatic stages， liver qi stagnation and spleen deficiency are prominent， warranting a therapeutic approach of soothing the liver， regulating qi and strengthening the spleen. The modified Chaishao Qizhi Decoction （柴芍气滞汤） is used. During the symptomatic stage， pathogenic factors become more pronounced， often accompanied by a significant deficiency of vital qi， with damp-heat， water retention， and phlegm toxicity as key pathological features. The treatment should focus on strengthening the spleen and dispelling dampness， using modified Sijunzi Decoction （四君子汤） combined with Yinchen Wuling Powder （茵陈五苓散）. In the liver function decompensation stage， vital qi is severely deficient while pathogenic factors persist， with damp-heat， phlegm toxicity， and blood stasis obstructing the liver collaterals. Treatment should focus on nourishing blood， softening the liver， strengthening the spleen， and resolving stasis， using the modified Ruangan Yangxue Decoction （软肝养血汤）. Throughout the treatment process， emphasis is placed on tonifying the liver and kidneys while protecting yin fluids.

AIM: To explore the relationship between hyperopia reserve and ocular biometric parameters in 4-14 year-old Uyghur students from Hotan County, Xinjiang, and to provide scientific evidence for myopia prevention.METHODS: From September 1 to October 31, 2023, a stratified random cluster sampling method was used to select 3 264 students(3 264 eyes)from 6 schools in Hotan County. Participants underwent uncorrected distance visual acuity testing, cycloplegic refraction, and ocular biometric measurements. The correlation between spherical equivalent(SE)and ocular biometric parameters was analyzed by multiple linear regression.RESULTS: A total of 1 998 non-myopic students(1 998 eyes)were included in the study, with 1 354 students(67.77%)showing insufficient hyperopia reserve. The detection rate of insufficient hyperopia reserve decreased with age, from 94.12% at age 4 to 18.13% at age 14(P<0.001). Multiple linear regression analysis showed that in the group with sufficient hyperopia reserve, age, gender, uncorrected distance visual acuity, axial length(AL), and keratometry(K)explained 66.5% of the variance in SE; while in the group with insufficient hyperopia reserve, these factors explained only 28.0% of the SE variance.CONCLUSION: In non-myopic Uyghur students aged 4-14 in Hotan County, Xinjiang, the detection rate of insufficient hyperopia reserve was 67.77%. In the group with insufficient hyperopia reserve, age, gender, AL, and K explained only a small portion of the SE variance, suggesting that the refractive status of this population may be influenced by more complex factors.

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

Intervertebral disc degeneration (IDD) is the main cause of low back pain. Immune cells play an extremely important role in regulating the progression of IDD by interacting with nucleus pulposus (NP) cells and the extracellular matrix (ECM). Healthy NP tissue is a vascular-free and immune-privileged tissue that does not normally interact with macrophages. However, the establishment of neovascularization channels in damaged intervertebral discs has led to extensive cross-talk between NP and macrophages, with different results depending on microenvironmental stimuli. Based on this, this review reviewed the correlation between IDD and low back pain, summarized the source and function of macrophages, and discussed the possible regulatory mechanism between macrophages and discogenic pain. Finally, potential therapies targeting macrophages to delay IDD in recent years were also discussed, aiming to emphasize the important role of immunology in IDD and provide a new direction for the prevention and treatment of IDD.
Humans ; Intervertebral Disc Degeneration/complications* ; Macrophages/immunology* ; Low Back Pain/immunology* ; Nucleus Pulposus ; Animals ; Extracellular Matrix

To clarify the species, pathogenicity, and distribution of the pathogens causing the root rot of Atractylodes lancea in Hubei province, the tissue separation method was used to isolate the pathogens from root rot samples in the main planting areas of A. lancea in Hubei. Based on the preliminary identification of the Fusarium genus by the internal transcribed spacer(ITS) sequence, three housekeeping genes, EF1/EF2, Btu-F-FO1/Btu-F-RO1, and FF1/FR1, were amplified and sequenced. Subsequently, a phylogenetic tree was constructed based on these TEF gene sequences to classify the pathogens. The pathogenicity of these strains was determined using the root irrigation method. A total of 194 pathogen strains were isolated using the tissue separation method. Molecular identification using the three housekeeping genes identified the pathogens as F. solani, F. oxysporum, F. commune, F. equiseti, F. tricinctum, F. redolens, F. fujikuroi, F. avenaceum, F. acuminatum, and F. incarnatum. Among them, F. solani and F. oxysporum were the dominant strains, widely distributed in multiple regions, with F. solani accounting for approximately 54% of the total isolated strains and F. oxysporum accounting for approximately 34%. Other strains accounted for a relatively small proportion, totaling approximately 12%. The results of pathogenicity determination showed that there were certain differences in pathogenicity among strains. The analysis of the pathogenicity differentiation of the widely distributed F. solani and F. oxysporum strains revealed that these dominant strains in Hubei were mainly highly pathogenic. This study determined the species, pathogenicity, and distribution of the pathogens causing the root rot of A. lancea in Hubei province. The results provide a scientific basis for further understanding the root rot of A. lancea and its epidemic occurrence and scientifically preventing and controlling this disease.
Plant Diseases/microbiology* ; Atractylodes/microbiology* ; Phylogeny ; Plant Roots/microbiology* ; Fusarium/classification* ; China ; Virulence ; Fungal Proteins/genetics*