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.

Metabolic dysfunction-associated fatty liver disease （MAFLD） has become one of the most prevalent chronic liver diseases worldwide， posing a serious challenge to public health. In this context， the integration of artificial intelligence （AI）， especially intelligent diagnosis and treatment and digital health interventions based on machine learning， can break through the limitations of traditional methods， realize efficient screening of multi-dimensional data such as key genes， biomarkers， and biochemical metabolites， and achieve revolutionary breakthroughs in risk prediction， subtype identification， and therapeutic effect assessment for MAFLD. This article systematically reviews the ground-breaking application of machine learning models in driving the innovation of clinical diagnosis and precise risk prediction of MAFLD， conducts a comprehensive comparative analysis of digital health practice cases of MAFLD in China and globally， and deeply analyzes their advantages and limitations in terms of research subjects， interventions， and management team. Studies have shown that the deep integration of digital health and long-term management of MAFLD is becoming the key engine driving the transformation of disease management modes towards an intelligent， individualized， and precise era， but there are various ethical and technical issues that need to be addressed urgently.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

BACKGROUND:Degenerative scoliosis is defined as a condition that occurs in adulthood with a coronal cobb angle of the spine>10° accompanied by sagittal deformity and rotational subluxation,which often produces symptoms of spinal cord and nerve compression,such as lumbar pain,lower limb pain,numbness,weakness,and neurogenic claudication.The finite element method is a mechanical analysis technique for computer modelling,which can be used for spinal mechanics research by building digital models that can realistically restore the human spine model and design modifications. OBJECTIVE:To review the application of finite element method in the etiology and treatment of degenerative scoliosis. METHODS:The literature databases CNKI,PubMed,and Web of Science were searched for articles on the application of finite element method in degenerative scoliosis published before October 2023.Search terms were"finite element analysis,biomechanics,stress analysis,degenerative scoliosis,adult spinal deformity"in Chinese and English.Fifty-four papers were finally included. RESULTS AND CONCLUSION:(1)The biomechanical findings from the degenerative scoliosis model constructed using the finite element method were identical to those from the in vivo experimental studies,which proves that the finite element method has a high practical value in degenerative scoliosis.(2)The study of the etiology and treatment of degenerative scoliosis by the finite element method is conducive to the prevention of the occurrence of the scoliosis,slowing down the progress of the scoliosis,the development of a more appropriate treatment plan,the reduction of complications,and the promotion of the patients'surgical operation.(3)The finite element method has gradually evolved from a single bony structure to the inclusion of soft tissues such as muscle ligaments,and the small sample content is increasingly unable to meet the research needs.(4)The finite element method has much room for exploration in degenerative scoliosis.

[Objective] To validate and optimize the platelet transfusion refractoriness (PTR) prediction model for patients with hematological disorders established by our center. [Methods] The data of patients with hematological diseases who received platelet transfusions from December 2021 to December 2022 were used as the training set, and data from January 2023 to December 2023 as the validation set. The validation set data was used to validate the predictive model constructed on the training set. Relevant risk factors for PTR were collected through literature review and preliminary studies。 The patients were divided into effective and ineffective groups according to the corrected count increment (CCI) of platelet counts. Predictive factors were screened using univariate and multivariate logistic regression. The calibration of the model were assessed via calibration curves, while discrimination, accuracy, sensitivity, and specificity were evaluated using receiver operating characteristic (ROC) curves Clinical utility was further analyzed with decision curve analysis (DCA). [Results] The Hosmer-Lemeshow (H-L) goodness-of-fit test for the validation set yielded S: P=0.000, indicating that the original model needs optimization. Baseline comparisons and logistic regression identified the number of red blood cell units (RBCU) and platelet units (PLT-U) transfused as key predictors for the optimized model. The H-L goodness-of-fit test S: P values for the training and validation sets were 0.930 and 0.056, respectively; the ROC areas were 0.793 5 and 0.809 4, specificities 90.95% and 84.21%, sensitivities 59.26% and 70.04%, and accuracies 78.14% and 74.10%, respectively. DCA demonstrated clinical net benefit within a prediction probability threshold range of 0.2-0.8. [Conclusion] Transfusion volumes of RBC-U and PLT-U were inversely associated with PTR in hematological patients. The resulting PTR prediction model exhibits moderate predictive efficacy and clinical benefit.

INTRODUCTION: Lecanemab has shown promise in treating early Alzheimer's disease (AD), but its safety and efficacy in Chinese populations remain unexplored. This study aimed to evaluate the safety and 6-month clinical outcomes of lecanemab in Chinese patients with mild cognitive impairment (MCI) or mild AD. METHODS: In this single-arm, real-world study, participants with MCI due to AD or mild AD received biweekly intravenous lecanemab (10 mg/kg). The study was conducted at Hainan Branch, Ruijin Hospital Shanghai Jiao Tong University School of Medicine. Patient enrollment and baseline assessments commenced in November 2023. Safety assessments included monitoring for amyloid-related imaging abnormalities (ARIA) and other adverse events. Clinical and biomarker changes from baseline to 6 months were evaluated using cognitive scales (mini-mental state examination [MMSE], montreal cognitive assessment [MoCA], clinical dementia rating-sum of boxes [CDR-SB]), plasma biomarker analysis, and advanced neuroimaging. RESULTS: A total of 64 patients were enrolled in this ongoing real-world study. Safety analysis revealed predominantly mild adverse events, with infusion-related reactions (20.3%, 13/64) being the most common. Of these, 69.2% (9/13) occurred during the initial infusion and 84.6% (11/13) did not recur. ARIA-H (microhemorrhages/superficial siderosis) and ARIA-E (edema/effusion) were observed in 9.4% (6/64) and 3.1% (2/64) of participants, respectively, with only two symptomatic cases (one ARIA-E presenting with headache and one ARIA-H with visual disturbances). After 6 months of treatment, cognitive scores remained stable compared to baseline (MMSE: 22.33 ± 5.58 vs . 21.27 ± 4.30, P = 0.733; MoCA: 16.38 ± 6.67 vs . 15.90 ± 4.78, P = 0.785; CDR-SB: 2.30 ± 1.65 vs . 3.16 ± 1.72, P = 0.357), while significantly increasing plasma amyloid-β 42 (Aβ42) (+21.42%) and Aβ40 (+23.53%) levels compared to baseline. CONCLUSIONS: Lecanemab demonstrated a favorable safety profile in Chinese patients with early AD. Cognitive stability and biomarker changes over 6 months suggest potential efficacy, though high dropout rates and absence of a control group warrant cautious interpretation. These findings provide preliminary real-world evidence for lecanemab's use in China, supporting further investigation in larger controlled studies. REGISTRATION ClinicalTrials.gov , NCT07034222.
Humans ; Alzheimer Disease/drug therapy* ; Male ; Female ; Aged ; Middle Aged ; Cognitive Dysfunction/drug therapy* ; Aged, 80 and over ; Amyloid beta-Peptides/metabolism* ; Biomarkers ; East Asian People

This study identified blood-entering components of Anshen Dropping Pills and explored their anti-insomnia effects and mechanisms. The main blood-entering components of Anshen Dropping Pills were detected and identified by UPLC-Q-TOF-MS/MS. The rationality of the formula was assessed by using enrichment analysis based on the relationship between drugs and symptoms, and core targets of its active components were selected as the the potential anti-insomnia targets of Anshen Dropping Pills through network pharmacology analysis. Furthermore, protein-protein interaction(PPI) network, Gene Ontology(GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were performed on the core targets. An active component-core target network for Anshen Dropping Pills was constructed. Finally, the effects of low-, medium-, and high-dose groups of Anshen Dropping Pills on sleep episodes, sleep duration, and sleep latency in mice were measured by supraliminal and subliminal pentobarbital sodium experiments. Moreover, total scores of the Pittsburgh sleep quality index(PSQI) scale was used to evaluate the changes before and after the treatment with Anshen Dropping Pills in a clinical study. The enrichment analysis based on the relationship between drugs and symptoms verified the rationality of the Anshen Dropping Pills formula, and nine blood-entering components of Anshen Dropping Pills were identified by UPLC-Q-TOF-MS/MS. The network proximity revealed a significant correlation between eight components and insomnia, including magnoflorine, liquiritin, spinosin, quercitrin, jujuboside A, ginsenoside Rb_3, glycyrrhizic acid, and glycyrrhetinic acid. Network pharmacology analysis indicated that the major anti-insomnia pathways of Anshen Dropping Pills involved substance and energy metabolism, neuroprotection, immune system regulation, and endocrine regulation. Seven core genes related to insomnia were identified: APOE, ALB, BDNF, PPARG, INS, TP53, and TNF. In summary, Anshen Dropping Pills could increase sleep episodes, prolong sleep duration, and reduce sleep latency in mice. Clinical study results demonstrated that Anshen Dropping Pills could decrease total scores of PSQI scale. This study reveals the pharmacodynamic basis and potential multi-component, multi-target, and multi-pathway effects of Anshen Dropping Pills, suggesting that its anti-insomnia mechanisms may be associated with the regulation of insomnia-related signaling pathways. These findings offer a theoretical foundation for the clinical application of Anshen Dropping Pills.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Tandem Mass Spectrometry/methods* ; Sleep Initiation and Maintenance Disorders/metabolism* ; Mice ; Network Pharmacology ; Male ; Chromatography, High Pressure Liquid ; Humans ; Protein Interaction Maps/drug effects* ; Sleep/drug effects* ; Female ; Adult

This study investigated the effects and underlying mechanisms of vanillic acid(VA) against cardiac fibrosis(CF) induced by isoproterenol(ISO) in mice. Male C57BL/6J mice were randomly divided into control group, VA group(100 mg·kg~(-1), ig), ISO group(10 mg·kg~(-1), sc), ISO + VA group(10 mg·kg~(-1), sc + 100 mg·kg~(-1), ig), ISO + dynamin-related protein 1(Drp1) inhibitor(Mdivi-1) group(10 mg·kg~(-1), sc + 50 mg·kg~(-1), ip), and ISO + VA + Mdivi-1 group(10 mg·kg~(-1), sc + 100 mg·kg~(-1), ig + 50 mg·kg~(-1), ip). The treatment groups received the corresponding medications once daily for 14 consecutive days. On the day after the last administration, cardiac functions were evaluated, and serum and cardiac tissue samples were collected. These samples were analyzed for serum aspartate aminotransferase(AST), lactate dehydrogenase(LDH), creatine kinase-MB(CK-MB), cardiac troponin I(cTnI), reactive oxygen species(ROS), interleukin(IL)-1β, IL-4, IL-6, IL-10, IL-18, and tumor necrosis factor-α(TNF-α) levels, as well as cardiac tissue catalase(CAT), glutathione(GSH), malondialdehyde(MDA), myeloperoxidase(MPO), superoxide dismutase(SOD), total antioxidant capacity(T-AOC) activities, and cytochrome C levels in mitochondria and cytoplasm. Hematoxylin-eosin, Masson, uranium acetate and lead citrate staining were used to observe morphological and mitochondrial ultrastructural changes in the cardiac tissues, and myocardial injury area and collagen volume fraction were calculated. Flow cytometry was applied to detect the relative content and M1/M2 polarization of cardiac macrophages. The mRNA expression levels of macrophage polarization markers [CD86, CD206, arginase 1(Arg-1), inducible nitric oxide synthase(iNOS)], CF markers [type Ⅰ collagen(Coll Ⅰ), Coll Ⅲ, α-smooth muscle actin(α-SMA)], and cytokines(IL-1β, IL-4, IL-6, IL-10, IL-18, TNF-α) in cardiac tissues were determined by quantitative real-time PCR. Western blot was used to detect the protein expression levels of Coll Ⅰ, Coll Ⅲ, α-SMA, Drp1, p-Drp1, voltage-dependent anion channel(VDAC), hexokinase 1(HK1), NOD-like receptor protein 3(NLRP3), apoptosis-associated speck-like protein(ASC), caspase-1, cleaved-caspase-1, gasdermin D(GSDMD), cleaved N-terminal gasdermin D(GSDMD-N), IL-1β, IL-18, B-cell lymphoma-2(Bcl-2), B-cell lymphoma-xl(Bcl-xl), Bcl-2-associated death promoter(Bad), Bcl-2-associated X protein(Bax), apoptotic protease activating factor-1(Apaf-1), pro-caspase-3, cleaved-caspase-3, pro-caspase-9, cleaved-caspase-9, poly(ADP-ribose) polymerase-1(PARP-1), and cleaved-PARP-1 in cardiac tissues. The results showed that VA significantly improved cardiac function in mice with CF, reduced myocardial injury area and cardiac index, and decreased serum levels of AST, CK-MB, cTnI, LDH, ROS, IL-1β, IL-6, IL-18, and TNF-α. VA also lowered MDA and MPO levels, mRNA expressions of IL-1β, IL-6, IL-18, and TNF-α, and mRNA and protein expressions of Coll Ⅰ, Coll Ⅲ, and α-SMA in cardiac tissues, and increased serum levels of IL-4 and IL-10, cardiac tissue levels of CAT, GSH, SOD, and T-AOC, and mRNA expressions of IL-4 and IL-10. Additionally, VA ameliorated cardiac pathological damage, inhibited myocardial cell apoptosis, inflammatory infiltration, and collagen fiber deposition, reduced collagen volume fraction, and alleviated mitochondrial damage. VA decreased the ratio of F4/80~+CD86~+ M1 cells and the mRNA expressions of CD86 and iNOS in cardiac tissue, and increased the ratio of F4/80~+CD206~+ M2 cells and the mRNA expressions of CD206 and Arg-1. VA also reduced protein expressions of p-Drp1, VDAC, NLRP3, ASC, caspase-1, cleaved-caspase-1, GSDMD, GSDMD-N, IL-1β, IL-18, Bad, Bax, Apaf-1, cleaved-caspase-3, cleaved-caspase-9, cleaved-PARP-1, and cytoplasmic cytochrome C, and increased the expressions of HK1, Bcl-2, Bcl-xl, pro-caspase-3, pro-caspase-9 proteins, as well as the Bcl-2/Bax and Bcl-xl/Bad ratios and mitochondrial cytochrome C content. These results indicate that VA has a significant ameliorative effect on ISO-induced CF in mice, alleviates ISO-induced oxidative damage and inflammatory response, and its mechanism may be closely related to the inhibition of Drp1/HK1/NLRP3 and mitochondrial apoptosis signaling pathways, suppression of myocardial cell inflammatory infiltration and collagen fiber deposition, reduction of collagen volume fraction and CollⅠ, Coll Ⅲ, and α-SMA expressions, thus mitigating CF.
Animals ; Isoproterenol/adverse effects* ; Male ; Mice ; Signal Transduction/drug effects* ; Vanillic Acid/administration & dosage* ; Dynamins/genetics* ; Mice, Inbred C57BL ; Fibrosis/genetics* ; Apoptosis/drug effects* ; Mitochondria/metabolism* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Myocardium/metabolism* ; Humans

The AP2/ERF transcription factor family is a class of transcription factors widely present in plants, playing a crucial role in regulating flowering, flower development, flower opening, and flower senescence. Based on transcriptome data from flower, leaf, and stem samples of two Lonicera macranthoides varieties, 117 L. macranthoides AP2/ERF family members were identified, including 14 AP2 subfamily members, 61 ERF subfamily members, 40 DREB subfamily members, and 2 RAV subfamily members. Bioinformatics and differential gene expression analyses were performed using NCBI, ExPASy, SOMPA, and other platforms, and the expression patterns of L. macranthoides AP2/ERF transcription factors were validated via qRT-PCR. The results indicated that the 117 LmAP2/ERF members exhibited both similarities and variations in protein physicochemical properties, AP2 domains, family evolution, and protein functions. Differential gene expression analysis revealed that AP2/ERF transcription factors were primarily differentially expressed in the flowers of the two L. macranthoides varieties, with the differentially expressed genes mainly belonging to the ERF and DREB subfamilies. Further analysis identified three AP2 subfamily genes and two ERF subfamily genes as potential regulators of flower development, two ERF subfamily genes involved in flower opening, and two ERF subfamily genes along with one DREB subfamily gene involved in flower senescence. Based on family evolution and expression analyses, it is speculated that AP2/ERF transcription factors can regulate flower development, opening, and senescence in L. macranthoides, with ERF subfamily genes potentially serving as key regulators of flowering duration. These findings provide a theoretical foundation for further research into the specific functions of the AP2/ERF transcription factor family in L. macranthoides and offer important theoretical insights into the molecular mechanisms underlying floral phenotypic differences among its varieties.
Plant Proteins/chemistry* ; Gene Expression Regulation, Plant ; Transcription Factors/chemistry* ; Lonicera/classification* ; Flowers/metabolism* ; Phylogeny ; Gene Expression Profiling ; Multigene Family

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.