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.

The crosstalk between macrophages and bone marrow mesen chymal stem cells （BMSCs） plays a vital role in regulating tendon-bone healing. Based on the traditional Chinese medicine （TCM） theory that the kidney governs the bones and generates marrow， yin-nourishing and kidney-tonifying Chinese medicines can promote the osteogenic differentiation of BMSCs and the M1-to-M2 polarization of macrophages， thereby facilitating tendon-bone healing. A variety of related medicinal monomers （such as diosgenin and oleanolic acid）， extracts and effective fractions （such as artificial tiger bone powder and total flavonoids of Drynaria fortunei ）， as well as compound prescriptions （such as Liuwei dihuang pill， Xujin jiegu decoction and Duhuo jisheng decoction）， can modulate the crosstalk between macrophages and BMSCs by regulating the Wnt/β-catenin， nuclear factor kappa-B， phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin and transforming growth factor-β/Smad signaling pathways. They further exert anti-inflammatory， antioxidant and osteogenic effects to effectively accelerate tendon-bone healing. However， current evidence was limited to animal experiments exhibiting such as limitations insufficent alignment between animal models and clinical injury types， research focusing mostly on single signaling pathways， and unclear core active ingredients. Future studies shall optimize animal models and carry out large-sample randomized controlled trials， clarify the interactive networks of multiple signaling pathways， and isolate the core active substances of yin-nourishing and kidney-tonifying Chinese medicines， so as to advance the precise application of traditional Chinese medicines.

BACKGROUND:Type 2 diabetes mellitus is a secondary causative factor for osteoporosis.As highly heterogeneous innate immune cells,macrophages may be polarized in a hyperglycemic environment,which affects osteogenesis-angiogenesis coupling.This may be a research target for improving bone quality in patients with type 2 diabetic osteoporosis.OBJECTIVE:To explore the role of modulating macrophage M1/M2 polarization to influence osteogenesis-angiogenesis coupling in type 2 diabetic osteoporosis and to summarize the effects of commonly used anti-glucose and anti-osteoporosis drugs and bone biorepair materials on bone osteogenesis-angiogenesis coupling by regulating macrophage M1/M2 polarization.METHODS:The keywords of"macrophage polarization,type 2 diabetes,osteoporosis,osteogenesis-angiogenesis coupling"in Chinese and"macrophages,macrophage polarization,osteogenesis-angiogenesis coupling"in English were used to search for relevant literature in CNKI and PubMed,respectively.Seventy-nine pieces of literature were screened and analyzed.RESULTS AND CONCLUSION:(1)Type 2 diabetes mellitus causes the body to be in a hyperglycemic environment and increases the secretion of inflammatory-related factors in the body,which promotes macrophage polarization towards M1 and decreases the number of M2 macrophages.(2)In type 2 diabetes,promoting M2 macrophage polarization is beneficial for osteogenesis-angiogenesis coupling.(3)Some anti-glycemic drugs,active ingredients in traditional Chinese medicine and bone biorepair materials can improve type 2 diabetic osteoporosis by regulating macrophage M1/M2 polarization,reducing M1/M2 ratio,and promoting osteogenesis-angiogenesis coupling.

BACKGROUND:Ankylosing spondylitis is closely related to the occurrence and development of psoriasis,but the key genes and regulatory mechanisms are still unclear.OBJECTIVE:To establish an artificial neural network model of genes shared by ankylosing spondylitis and psoriasis based on the GEO database and evaluate its effect,and also to determine whether there is a causal relationship between the expression of key genes and the two diseases using Mendelian randomization.METHODS:Datasets GSE25101(816 ankylosing spondylitis samples and 816 healthy control samples),GSE30999(85 psoriasis samples and 85 healthy control samples),GSE73754(52 ankylosing spondylitis samples and 20 healthy control samples),and GSE14905(33 psoriasis samples and 49 healthy control samples)were downloaded from the GEO database.GSE25101 and GSE30999 were used as the training datasets of ankylosing spondylitis and psoriasis,respectively,and their respective differentially expressed genes were identified through difference analysis to obtain the common driver genes of the two diseases,and the key core genes were further screened out based on Mendelian randomization.The key core genes were further screened out,and artificial neural network models were constructed based on the key core genes and validated in external datasets GSE73754 and GSE14905,followed by the construction of the corresponding nomogram to predict the incidence rates of the diseases.Also,the results of immune infiltration in ankylosing spondylitis and psoriasis were analyzed.Finally,Mendelian randomization was used to assess causal relationships between key genes and diseases,and drug-gene interactions were analyzed using the Dgidb database to predict drug targets.RESULTS AND CONCLUSION:(1)A total of 61 differential genes were obtained in ankylosing spondylitis and 4 309 differential genes were obtained in psoriasis.Eight shared differential genes were obtained after intersection,and five key genes(DNMT1,GNG11,CDC25B,S100A8,and S100A12)were further screened by machine learning.The key genes were utilized to build artificial neural network models of ankylosing spondylitis and psoriasis,with the area under curve values of 0.979 and 0.989 in the training sets GSE25101 and GSE30999,respectively,and 0.818 and 0.874 in the external validation datasets GSE73754 and GSE14905,respectively.(2)Nomogram was constructed based on the five core genes,and the calibration curves showed that the predicted probabilities of the nomogram models were almost the same as that of the ideal model.Immune cell infiltration showed that the key genes were associated with activated B cells,natural killer cells,γδ T cells,follicular helper T cells,monocytes,plasma cell-like dendritic cells,and neutrophils.Mendelian randomization showed that S100A8 was a risk factor for the occurrence of ankylosing spondylitis and psoriasis.Finally,DGldb screening was utilized to obtain 81 targeted drugs,only 16 of which,including methotrexate,atogepant,ubrogepant,rimegepant,eptinezumab,azacitidine,selenium,hydroxyurea,ifosfamide,floxuridine,curcumin,mitoxantrone,cisplatin,arsenic trioxide,diethylstilbestrol,and decitabine,were approved by the U.S.Food and Drug Administration.(3)A large number of successful cases have been accumulated in international databases,research results and data analysis of European groups,especially in genomics and disease phenotyping studies.These experiences provide valuable references for the epidemiological characterization of diseases in China,genetic diversity and their response to the environment and lifestyle.(4)An artificial neural network model of the common driver genes of ankylosing spondylitis and psoriasis was constructed and validated,the causal relationship between the key genes and the pathogenesis of the two diseases was discovered,and the targeted drugs for potential treatments were predicted,which hopefully provides a new perspective for exploring their pathogenesis and therapeutic directions.

Objective To explore the risk factors for mineral and bone disorder in maintenance hemodialysis patients, and to construct and validate a nomogram prediction model. Methods A total of 306 patients undergoing maintenance hemodialysis at Shanghai Eighth People’s Hospital from January 2021 to May 2025 were selected as study subjects and randomly divided into a training set (n＝214) and a validation set (n＝92) in a 7∶3 ratio. In the training set, patients were divided into a normal bone mineral metabolism group and an abnormal bone mineral metabolism group, and related factors were compared between the two groups. The multivariate logistic regression analysis was used to identify the influencing factors of mineral and bone disorder in maintenance hemodialysis patients in the training set, and a nomogram prediction model was constructed. ROC curves were drawn to evaluate the ability of the nomogram model for predicting mineral and bone disorder in these patients. Calibration curves and Hosmer-Lemeshow goodness-of-fit test were used to analyze the consistency of the predictive probability of nomogram model and actual probability of mineral and bone disorder in these patients. The decision curve was used to assess the clinical benefit using nomogram prediction model. Results Among the 306 hemodialysis patients, 254 patients had mineral and bone disorder, accounting for 83.01%. Among the 214 patients in the training set, 177 had mineral and bone disorder, accounting for 82.71%. In the training set, age, gender, body mass index (BMI), hypertension rate, dialysis age, blood urea nitrogen (BUN), hemoglobin (Hb), albumin (ALB), alkaline phosphatase (ALP), serum creatinine (SCr), uric acid (UA), estimated glomerular filtration rate (eGFR), and rate of taking phosphate binders were statistically significant different between the two groups (P＜0.05). The multivariate logistic regression analysis showed higher age, female, hypertension, longer dialysis duration, decreased eGFR, and not taking phosphate binders were identified as risk factors for mineral and bone disorder in maintenance hemodialysis patients (P＜0.01). The nomogram prediction model was constructed. The area under the ROC curve of the model for mineral and bone disorder in the training set and validation set was 0.895 (95%CI 0.850-0.941) and 0.881 (95%CI 0.830-0.932), respectively, with maximum Youden indice of 0.650 and 0.600, sensitivity of 0.856 and 0.849, and specificity of 0.794 and 0.751. The Hosmer-Lemeshow test showed the nomogram prediction model had good consistency in predictive probabilities with actual probabilities in training set and validation set. The decision curve showed the nomogram model could bring clinical net benefits when the threshold probabilities in the training set and validation set were less than 0.96 and 0.91. Conclusions The nomogram prediction model constructed based on six independent risk factors including age, gender, hypertension, dialysis duration, eGFR, and using phosphate binders or not, shows good discrimination and calibration, with good clinical predictive ability, which could provide guidance for the management of maintenance hemodialysis patients.

OBJECTIVE To investigate the mechanism by which Qiaobai cold compress solution （QBCS） improves acne vulgaris （AV） based on transcriptomics and animal experiments. METHODS Rats were randomly divided into a blank control group （ n ＝6） and a modeling group （ n ＝30）. AV models were established in the modeling group by topical application of oleic acid to the inner surface of both ears， combined with subcutaneous injection of Cutibacterium acnes suspension into the auricle. Successfully modeled rats were further divided into the model group， positive control group （Tretinoin cream， 0.045 g/kg）， and QBCS low-， medium-， high-dose groups [3.55， 7.11， 14.22 g/kg （calculated by the amount of crude drug） ] ， with 6 rats in each group. Rats in each d rug group were treated with the corresponding drugs once daily for 14 consecutive days. After the final administration， changes in the appearance of the ears and histopathological changes in the ear tissues were observed， and serum levels of inflammatory factors， including tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6） and IL-1β， were measured. Auricular tissues from the blank control group， model group and QBCS medium-dose group were collected for transcriptome sequencing. Differential expressed genes （DEGs） were screened and subjected to Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis， followed by validation using real-time quantitative polymerase chain reaction and Western blot assay. RESULTS Compared with the model group， rats in all QBCS groups showed alleviated auricular acne symptoms， with reduced epidermal thickening， sebaceous gland hyperplasia， and inflammatory cell infiltration. Serum levels of TNF-α （except for the QBCS low-dose group）， IL-6 （except for the QBCS low-dose group） and IL-1β were significantly decreased （ P ＜0.05）. A total of 590 DEGs were identified （blank control group vs. model group）， and 596 DEGs were identified （model group vs. QBCS medium-dose group）. Above DEGs （blank control group vs. model group） were mainly enriched in Toll-like receptor （TLR） and nuclear factor-kappa B （NF-κB） signaling pathways， etc. Validation experiments showed that， compared with model group， low-， medium- and high-dose of QBCS reduced， to varying degrees， the mRNA expression of TNF-α， TLR2， interferon-γ and CXC chemokine ligand 8 in the auricular tissues of AV rats， increased the mRNA expression of peroxisome-proliferator-activated receptor gamma and tumor protein 53， and inhibited the phosphorylation of NF-κB p65 protein as well as the expressions of TLR2 and myeloid differentiation primary response protein 88（MyD88） （ P ＜0.05）. CONCLUSIONS QBCS can alleviate auricular inflammation and skin lesions in AV rats. This effect may be related to inhibition of the TLR/MyD88/NF-κB signaling pathway， thereby suppressing the expression of downstream inflammatory factors such as TNF-α.

[摘 要] 目的：探讨核仁小RNA（snoRNA）71A通过TLR3/PD-L1通路对食管鳞状细胞癌（ESCC）细胞增殖、迁移及侵袭能力的影响。方法：qPCR检测52例ESCC患者的配对肿瘤组织、癌旁组织，以及人ESCC细胞中SNORA71A的表达情况。将反义寡核苷酸（SNORA71A-ASO-29、SNORA71A-ASO-102和NC-ASO）或小干扰RNA（siTLR3、siTLR3-NC）分别转染至人ESCC TE-1细胞，分别记为SNORA71A-ASO1组、SNORA71A-ASO2组、NC-ASO组及siTLR3组、siNC组。另外将过表达质粒pcDNA3.1-SNORA71A和pcDNA3.1空载体质粒分别转染至TE-1细胞，分别记为SNORA71A组和Vector组。细胞功能学实验（MTS实验、划痕愈合实验，以及Transwell侵袭实验）评估各组细胞在敲低或过表达SNORA71A后增殖、迁移和侵袭能力的变化。高通量转录组测序筛选SNORA71A下游作用靶基因，基因本体论（GO）和京都基因与基因组百科全书（KEGG）功能富集分析预测SNORA71A下游作用靶基因可能参与的生物学过程和信号通路。qPCR检测测序筛选出的下游作用靶基因TLR3在ESCC组织以及细胞中的表达。同时，qPCR和WB检测TE-1细胞在敲低或过表达TLR3后PD-L1 mRNA和蛋白质表达变化。细胞功能学实验检测TLR3敲低对SNORA71A所促进的TE-1细胞恶性生物行为（增殖、迁移、侵袭）的影响。结果：在52例ESCC患者的肿瘤组织以及ESCC细胞中SNORA71A表达均呈高水平（P < 0.01或P < 0.05）。敲低SNORA71A抑制TE-1细胞增殖、迁移和侵袭（P < 0.01或P < 0.05），过表达SNORA71A则促进TE-1细胞增殖、迁移和侵袭（P < 0.01或P < 0.05）。高通量转录组测序筛选到TLR3为SNORA71A下游作用靶基因。TLR3在ESCC组织以及TE-1细胞中呈低表达（P < 0.01或P < 0.05）。TLR3正向调控PD-L1 mRNA和蛋白质表达（P < 0.01或P < 0.05）。细胞功能学实验中，TLR3可以部分削弱SNORA71A对PD-L1表达的调控（P < 0.01）。结论：SNORA71A通过调控TLR3/PD-L1通路调节TE-1细胞增殖、迁移和侵袭。

Objective: To explore the relationship between non suicidal self injury (NSSI) behavior and serum lipid levels as well as thyroid function among college students with depression. Methods: A total of 169 college students with depression in the psychiatry departments of tertiary hospitals (grade 3A and 3B) in Ningbo from December 2023 to April 2025 were selected. The Adolescent Self injury Scale (ASIS) was used to assess the presence of NSSI, and participants were accordingly divided into a NSSI group ( n =51) and a non NSSI group ( n =118). General demographic data (including gender, age, and family situation) were collected from both groups. Blood tests were performed to measure lipid profiles [triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C)] and thyroid hormones [triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4), thyroid stimulating hormone (TSH)]. Multivariate Logistic regression was employed to analyze risk factors for NSSI, and receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of serum lipid and thyroid hormone levels for NSSI occurrence in college students with depression. Results: The levels of TC, LDL-C, and TSH in the NSSI group were (4.02±0.73) mmol/L, (2.32±0.36) mmol/L, and (6.57±1.95) mU/L , which were significantly higher than those in the non NSSI group [(3.41±0.56) mmol/L, (2.00±0.27) mmol/L, and ( 4.48± 1.09) mU/L, respectively] ( t =5.32, 5.60, 7.20, all P <0.05). Logistic regression analysis revealed that college students from single parent/reconstituted families, those who had experienced school bullying, and those with higher levels of TC, LDL-C, and TSH had a significantly increased risk of engaging in NSSI ( OR =5.22, 6.12, 5.90, 83.64, 3.64, all P <0.05). ROC curve analysis demonstrated that the combined detection of TC, LDL-C, and TSH had high diagnostic efficacy for predicting NSSI in college students with depression, with a sensitivity of 86.3% and a specificity of 94.9%. Conclusions NSSI behavior in college students with depression is associated with serum lipid levels and thyroid function. These biomarkers may serve as useful reference indicators for assessing the conditions of these patients.

In the era of evidence-based medicine， the progress of medical science and technology has enriched medical diagnostic tools and treatment methods， but it has also led to the loss of medical warmth and the alienation of the doctor-patient relationships. William Osler emphasized that while medical technology advances， attention should also be paid to the practice of narrative medicine and the development of physician’s narrative literacy. The view of the physician he advocated reminds us that the core of medicine still lies in the narrative connection between doctors and patients， as well as a deep understanding of human nature. By exploring the relationship between Osler’s view of the physician and narrative medicine as well as physician’s narrative literacy， this paper analyzed the methods of cultivating physician’s narrative literacy， providing references for modern medical education and practice， and assisting in the harmony and unity of science and technology and humanity.

Rheumatoid arthritis （RA） is a common autoimmune disease characterised clinically by symmetrical joint pain， swelling， and stiffness. Long-term chronic synovial inflammation can lead to severe joint damage and even disability， thereby affecting quality of life for patients. Current clinical treatment of RA emphasises an integrated approach combining traditional Chinese and Western medicine， with traditional Chinese medicine offering certain advantages in reducing disease activity of RA， preventing relapses， and other aspects. Modern clinical evidence confirms that Guizhi Shaoyao Zhimutang （GSZT） is effective in improving symptoms such as immune metabolism， joint stiffness， and joint pain in RA patients. Pharmacological studies have revealed that GSZT primarily contains components such as cinnamaldehyde， total glucosides of paeony， total alkaloids of Aconiti Lateralis Radix Praeparata， glycyrrhetinic acid， zingiberone， isoimperatorin， ephedra polysaccharides， and cedrol. It improves RA symptoms via multiple mechanisms and targets， including enhancing immune responses， exerting anti-inflammatory and analgesic effects， regulating relevant signalling pathways， inhibiting cell apoptosis， and suppressing bone destruction. This paper reviewed the syndrome patterns and pharmacological basis of GSZT in the treatment of RA， as well as its clinical applications and related mechanisms， thereby providing a theoretical basis and reference for the further development and utilisation of GSZT in the treatment of RA.