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.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

OBJECTIVE: To investigate the clinical features and prognosis of central nervous system (CNS) invasion in peripheral T-cell lymphoma (PTCL) and construct a risk prediction model for CNS invasion. METHODS: Clinical data of 395 patients with PTCL diagnosed and treated in the First Affiliated Hospital of Zhengzhou University from 1st January 2013 to 31st December 2022 were analyzed retrospectively. RESULTS: The median follow-up time of 395 PTCL patients was 24(1-143) months. There were 13 patients diagnosed CNS invasion, and the incidence was 3.3%. The risk of CNS invasion varied according to pathological subtype. The incidence of CNS invasion in patients with anaplastic large cell lymphoma (ALCL) was significantly higher than in patients with angioimmunoblastic T-cell lymphoma (AITL) (P <0.05). The median overall survival was significantly shorter in patients with CNS invasion than in those without CNS involvement, with a median survival time of 2.4(0.6-127) months after diagnosis of CNS invasion. The results of univariate and multivariate analysis showed that more than 1 extranodal involvement (HR=4.486, 95%CI : 1.166-17.264, P =0.029), ALCL subtype (HR=9.022, 95%CI : 2.289-35.557, P =0.002) and ECOG PS >1 (HR=15.890, 95%CI : 4.409-57.262, P <0.001) were independent risk factors for CNS invasion in PTCL patients. Each of these risk factors was assigned a value of 1 point and a new prediction model was constructed. It could stratify the patients into three distinct groups: low-risk group (0-1 point), intermediate-risk group (2 points) and high-risk group (3 points). The 1-year cumulative incidence of CNS invasion in the high-risk group was as high as 50.0%. Further evaluation of the model showed good discrimination and accuracy, and the consistency index was 0.913 (95%CI : 0.843-0.984). CONCLUSION The new model shows a precise risk assessment for CNS invasion prediction, while its specificity and sensitivity need further data validation.
Humans ; Lymphoma, T-Cell, Peripheral/pathology* ; Prognosis ; Retrospective Studies ; Central Nervous System Neoplasms/pathology* ; Neoplasm Invasiveness ; Male ; Female ; Central Nervous System/pathology* ; Middle Aged ; Adult

BACKGROUND: The clinical impact of post-percutaneous coronary intervention (PCI) quantitative flow ratio (QFR) in patients treated with PCI for chronic total occlusion (CTO) was still undetermined. METHODS: All CTO vessels treated with successful anatomical PCI in patients from PANDA III trial were retrospectively measured for post-PCI QFR. The primary outcome was 2-year vessel-oriented composite endpoints (VOCEs, composite of target vessel-related cardiac death, target vessel-related myocardial infarction, and ischemia-driven target vessel revascularization). Receiver operator characteristic curve analysis was conducted to identify optimal cutoff value of post-PCI QFR for predicting the 2-year VOCEs, and all vessels were stratified by this optimal cutoff value. Cox proportional hazards models were employed to calculate the hazard ratio (HR) with 95% CI. RESULTS: Among 428 CTO vessels treated with PCI, 353 vessels (82.5%) were analyzable for post-PCI QFR. 31 VOCEs (8.7%) occurred at 2 years. Mean value of post-PCI QFR was 0.92 ± 0.13. Receiver operator characteristic curve analysis shown the optimal cutoff value of post-PCI QFR for predicting 2-year VOCEs was 0.91. The incidence of 2-year VOCEs in the vessel with post-PCI QFR < 0.91 (n = 91) was significantly higher compared with the vessels with post-PCI QFR ≥ 0.91 (n = 262) (22.0% vs. 4.2%, HR = 4.98, 95% CI: 2.32-10.70). CONCLUSIONS Higher post-PCI QFR values were associated with improved prognosis in the PCI practice for coronary CTO. Achieving functionally optimal PCI results (post-PCI QFR value ≥ 0.91) tends to get better prognosis for patients with CTO lesions.

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

OBJECTIVE To investigate the impact of Tongxinluo capsules on the pharmacokinetics of rivaroxaban in rats. METHODS Rats were randomly divided into rivaroxaban alone group （2.70 mg/kg）， low-dose Tongxinluo capsules combined with rivaroxaban group （Tongxinluo capsules 0.28 g/kg+rivaroxaban 2.70 mg/kg）， and high-dose Tongxinluo capsules combined with rivaroxaban group （Tongxinluo capsules 0.84 g/kg+rivaroxaban 2.70 mg/kg）， with five rats in each group. Following seven consecutive days of gavage with normal saline or the corresponding doses of Tongxinluo capsules， the rats were subjected to a final gavage administration of rivaroxaban. Blood samples were collected at 0 h prior to the final administration and at 0.16， 0.33， 0.50， 0.75， 1， 1.5， 2， 4， 8， 12 and 24 h post-final administration. The plasma concentration of rivaroxaban in rats was determined by high-performance liquid chromatography-tandem mass spectrometry. The pharmacokinetic parameters [peak concentration （cmax）， half-life （t1/2）， area under the drug concentration time curve （AUC）， mean residence time （MRT）， clearance （CL）， apparent volume of distribution （Vd） and peak time （tmax）] of each group were calculated using a non-compartmental model of MonolixSuite 2023R1 pharmacokinetic software. RESULTS Compared with rivaroxaban alone group， AUC₀₋ₜ and AUC0-∞ of rivaroxaban in rats were increased significantly in high-dose Tongxinluo capsules+rivaroxaban group （P＜0.05）， while CL was decreased significantly （P＜0.05）； t1/2 and MRT were shortened， tmax was extended， cmax was increased， while Vd was decreased， but there was no statistical significance （P＞0.05）. CONCLUSIONS Rivaroxaban combined with Tongxinluo capsules significantly increases the plasma exposure of rivaroxaban in rats. Potential drug-drug interactions should be considered in clinical practice based on the co-administration conditions.

Glaucoma is a group of optic nerve disorders characterized by progressive optic nerve atrophy and visual field defects, which can lead to irreversible blindness. Early diagnosis of glaucoma is essential for preventing visual loss. However, due to the absence of obvious early symptoms, the diagnosis of glaucoma remains challenging. Visual electrophysiological examinations, an objective approach for evaluating visual function, have the potential to be used in the early diagnosis of glaucoma. This review integrates the latest publications to introduce visual electrophysiological examination techniques, including electroretinography(ERG)and visual evoked potential(VEP). It also explores the mechanisms underlying these techniques and their application value in the early diagnosis of glaucoma. In addition, this review summarizes the advantages, limitations, and applicable scenarios of different visual electrophysiological techniques. Finally, the review provides an outlook on the development prospects of visual electrophysiological techniques in the early diagnosis of glaucoma. The findings of this review can assist clinicians in selecting appropriate diagnostic methods, promote the innovation and development of early visual electrophysiological diagnostic techniques for glaucoma, and contribute to reducing the risk of blindness caused by glaucoma.

High mobility group box protein 1(HMGB1)is one of the most widely expressed protein member in the HMGs family,which is well known for its involvement in the body inflammatory response.Previous researches have found that it plays a significant role in cell migration,immune identification and neuroprotection.Spinal cord injury is a disease that causes severe damage to the nervous system,and neural circuits are disrupted after a spinal cord injury,which leads to many conditions including ischemia and hypoxia,inflammatory responses,demyelinating lesions,and glial scar formation that are detrimental to nerve regeneration and repair,making it one of the most difficult diseases to treat in the modern spinal surgery field.HMGB1 is upregulated after spinal cord injury,thereby regulating neuroinflam-matory responses,and participating in the neuronal apoptosis,promoting neuronal regeneration,and inducing neural stem cell differentiation and migration,which plays an important role in the process of neural function recovery.This paper summarizes the structure and function of HMGB1,as well as its role in spinal cord injury,in order to provide direction for founding therapeutic target for neurological function recovery after spinal cord injury.

To investigate the transcriptionally regulatory mechanism of the senp8 promoter in yellow cat-fish(Pelteobagrus fulvidraco);this study used P.fulvidraco as the research subject.Dual-luciferase re-porter assay and electrophoretic mobility shift assay were employed to analyze the functional activity of the promoter;coupled with in vivo experiments.The results indicated that the 2 045 bp senp8 promoter se-quence contained key transcription factor binding sites such as SP1;TATA-Box;CCAAT-Box;SREBP1;PPARα;and PPARγ.The binding sites of SREBP1(-901/-910 bp);PPARα(-1 291/-1 308 bp);and PPARγ(-1 292/-1 306 bp)in the senp8 promoter positively regulate its activity;and oleic acid or palmitic acid promote this binding.Furthermore;high-fat feeding promoted the expression of the senp8 gene and its protein in the liver of P.fulvidraco;oleic acid or palmitic acid treatment significantly en-hanced the activity of the senp8 promoter;and this enhancement could be achieved through the regulatory effects of SREBP1;PPARα;and PPARγ response elements.Additionally;high-fat feeding influenced the mRNA and protein expression levels of genes related to deSUMOylation modification in the liver of P.fulvidraco.This study provides new insights into the relationship between deSUMOylation modification and the regulation of lipid metabolism in the vertebrates.

Lung cancer poses a serious threat to global public health security.Chemotherapy,as the main strategy for cancer treatment,faces challenges such as high toxicity and drug resistance.Anticancer peptides have the potential of being developed into new anticancer drugs due to their advantages of broad-spectrum anticancer activity,rapid action,and difficulty in generating drug resistance,but they also face shortcomings such as weak activity and strong toxic side effects.The weakly acidic microenvironment of tumors(pH 6.5-6.8)provides a good idea for the design of anticancer peptides of high-efficiency and low-toxicity.Previously,we designed the acid-sensitive antibacterial peptide pHly-1 using the wolf spider(Lycosa singoriensis)toxin Lycosin-Ⅰ as a template.In this study,we found that pHly-1 also had acid-sensitive anticancer activity.Further alanine scanning analysis of pHly-1 was carried out,and we ob-tained a mutant pHTP-2 with better acid sensitivity,whose IC50(half maximal inhibitory concentration)against A549 cells was 15.68 μmol/L at pH 6.6 and was greater than 100 μmol/L at pH 7.4.At pH 6.6,pHTP-2 could act on various lung cancer cell lines and induce the death of A549 cells by rapid ly-sis;at pH 7.4,500 μmol/L pHTP-2 had weak toxicity to red blood cells(the hemolysis rate was ap-proximately 38％)and primary myocardial cells(the inhibition rate was 49.7％,with P＜0.05).Analy-sis of its charge,particle size,morphology,and secondary structure showed that at pH 6.6,the histidine in the sequence of pHTP-2 was protonated,increasing the positive charge(P＜0.01),decreasing the hy-drated particle size(P＜0.05)and forming an α-helical structure to induce membrane lysis of A549 cells.At pH 7.4,it was deprotonated,the positive charge decreases,a β-sheet structure was formed and self-aggregation occurred,limiting its effect on the A549 cell membrane and showing weak activity.In summary,pHTP-2 could respond to the weakly acidic microenvironment of tumors to exert selective cyto-toxic activity,effectively overcoming the shortcomings of anticancer peptides such as low efficiency and high toxicity.Our findings suggest that it is a high-quality lead molecule for anticancer drugs.