Objective To systematically review the studies on predictive models for delayed graft function (DGF) after kidney transplantation. Methods Databases including China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Web of Science and CINAHL were searched to collect studies on predictive models for DGF after kidney transplantation published from the establishment of each database to June 29, 2025. Two researchers screened the literatures according to the inclusion and exclusion criteria, evaluated the quality of the literatures using the prediction model risk of bias assessment tool (PROBAST), and conducted a meta-analysis of the common predictors of the models using R software. Results A total of 12 literatures were included, involving 14 predictive models with sample sizes ranging from 103 to 24 653 cases. Donor serum creatinine level, cold ischemia time, donor age and donor body mass index were the top four common predictors. All the predictive models were at high risk of bias and low in applicability. The results of meta-analysis showed that abnormal donor body mass index, advanced donor age, prolonged cold ischemia time and elevated donor serum creatinine level were all associated with an increased risk of DGF after transplantation (all P<0.01), but there was high heterogeneity among the studies. Fixed-effect model and random-effect model were used to re-pool the effect sizes separately. The results indicated that the fixed-effect model and random-effect model had good consistency in terms of donor body mass index, donor age and cold ischemia time, while there was a significant difference in the effect sizes of the two models for donor serum creatinine level. Conclusions The predictive models for DGF risk after kidney transplantation have good predictive performance, but the overall risk of bias is high. In the future, large-sample, multicenter and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Pancreatic cancer is a kind of highly malignant tumor with a low survival rate and poor prognosis. The effectiveness of gemcitabine as a first-line chemotherapy drug is limited; however, it can activate dendritic cells and improve antigen presentation which increase the sensitivity of tumor cell to immunotherapy. Although immunotherapy has made some advancements in cancer treatment, the therapeutic benefit of programmed cell death receptor 1/programmed death receptor-ligand 1 (PD-1/PD-L1) blockade therapy remains relatively low. The chemokine C-X-C chemokine ligand 12 (CXCL12) contributes to an immunosuppressive tumor microenvironment by recruiting immunosuppressive cells. The receptor C-X-C motif chemokine receptor 4 (CXCR4), highly expressed in various tumors including pancreatic cancer, plays a crucial role in tumor development and progression. In this study, the anti-tumor immune response of human peripheral blood mononuclear cell (hPBMC) was enhanced using the combination of BsNb PX4 (anti-PD-L1&CXCR4 bispecific nanobody) and gemcitabine. In a co-culture system of gemcitabine-pretreated hPBMCs with tumor cells, the BsNb PX4 synergized gemcitabine to improve the cytotoxic activity of hPBMCs against tumor cells. Flow cytometry analysis confirmed increased ratio of CD8⁺ to CD4⁺ T cells in combination treatment. In NOD/SCID mice bearing pancreatic cancer, the combination treatment exhibited more infiltration of CD8⁺ T cells into tumor tissues, contributing to an effective anti-tumor response. This study presents potential new therapies for the treatment of pancreatic cancer. Ethical approval was obtained for collection of hPBMC samples from the Local Ethics Committee of Shanghai Jiao Tong University. All animal experiments were approved by the Animal Ethic Committee of Shanghai Jiao Tong University (authorizing number: A2024246).

Objective To analyze the diversity and composition of gut microbiota in individuals with circadian rhythm disruption and their correlation with cognition.Methods Night shift workers and regular shift workers were subjected from our hospital during August 2022 and October 2024.The participants with circadian rhythm disorders were assigned into an experimental group(n=24),and those with normal circadian rhythms were into a control group(n=24).Their height,weight,age,gender,body mass index(BMI)and fresh fecal samples were collected,and Montreal Cognitive Assessment(MoCA)and Mini-Mental State Examination(MMSE)were used to evaluate their mental status.Metagenomics,Alpha and Beta diversity analyses,Linear Discriminant Analysis Effect Size(LEfSe),and Kyoto Encyclopedia of Genes and Genomes(KEGG)analysis were employed to investigate the diversity and function characteristics of gut microbiota in the participants.Results There were no statistical differences between the 2 groups in baseline data,such as height,weight,gender,age,and BMI(P>0.05).Alpha diversity analysis indicated that no statistical differences were observed in the ACE,Chao1,Shannon,or Simpson indices between the 2 groups,while beta diversity analysis revealed significant differences(P<0.01),suggesting different structure of gut microbiota between them.In the experimental group,the abundance of Faecalibacterium prausnitzii and Agathobacter rectalis was decreased,while that of Escherichia coli and Phocaeicola vulgaratus was increased,with significant differences when compared with the control group(P<0.05).Additionally,KEGG functional analysis showed that the experimental group had obviously higher expression levels in Th17 cell differentiation and the IL-17 signaling pathway than the control group(P<0.05).Agathobacter rectalis and Faecalibacterium prausnitzii were positively correlated with MoCA score and MMSE score(P<0.05,P<0.01).Agathobacter rectalis was negatively correlated with the IL-17 signaling pathway and Th17 cell differentiation.Conclusion Individuals with circadian rhythm disorders have significant changes in the structure and function of gut microbiota when compared to those with normal circadian rhythms.Agathobacter rectalis may be involved in the regulation of the IL-17 signaling pathway and differentiation of Th17 cells,thereby possibly impacting the increases of cognitive score related to circadian rhythm disorders.

As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

This study aims to establish the S_(180) tumor-bearing mice model, and to investigate the influence of Shenqi Erpi Granules(SQEPG) on immune function, as well as the drug's tumor-suppressive effect and mechanism. SPF grade KM mice(half male and half female) were randomly divided into 6 groups: a control group, a model group, a cyclophosphamide group(50 mg·kg~(-1)), as well as SQEPG groups in low-, medium-, and high-dose(5.25, 10.5, 21 g·kg~(-1)). The control group and the model group were given distilled water, and the other 4 groups were given the corresponding drugs by gavage. The administration continued for 10 days before the mice were sacrificed. The antitumor and immune regulation effects of SQEPG were evaluated. The effect of SQEPG on delayed type hypersensitivity reaction(DTH), carbon clearance index, and serum hemolysin antibody level was observed to reflect the effect on the immune function of tumor-bearing mice. Tumor weight was recorded to calculate the tumor suppression rate and the immune organ index. Hematoxylin-eosin(HE) staining was used to detect morphological changes in tumor tissues. Flow cytometry was employed to detect the percentage of CD4~+ and CD8~+ T-cells in the spleen tissues and the tumor tissue apoptosis levels. Immunohistochemistry was conducted to detect the KI67 protein expression level of tumor tissues. ELISA resorted to the detection of the following expression levels in tumor tissues: tumor necrosis factor-α(TNF-α), interleukin-2(IL-2), interferon-γ(IFN-γ). Western blot was performed to detect the expression levels of caspase-3, B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), cyclin-dependent kinases 4(CDK4), G_1/S-specific cyclin D1(cyclin D1), and vascular endothelial growth factor A(VEGFA). The results showed that, compared with the model group, the SQEPG could increase the swelling of the auricle of the tumor-bearing mice; significantly increase the phagocytic index of carbon granule contour(P<0.05 or P<0.01), and the middle dose of SQEPG could significantly increase the antibody level of hemolysin(P<0.05); different doses of SQEPG significantly inhibit the growth of the tumor, and decrease the mass of the tumor tissues(P<0.05 or P<0.01); the low dose of SQEPG significantly decreased spleen index(P<0.05), low and high doses of SQEPG increased thymus index, while medium doses of SQEPG decreased thymus index. High doses of SQEPG significantly elevated the levels of CD4~+ and CD8~+ T-cells in the spleens of the homozygous mice(P<0.01 or P<0.001), and increased the apoptosis rate of the cells of the tumor tissues(P<0.05); Meanwhile, high-dose SQEPG elevated the levels of immunity factors such as IL-2, IFN-γ and TNF-α in the serum of tumor-bearing mice(P<0.01); medium-and high-dose SQEPG significantly lowered the rate of positive expression of KI67 protein in tumor tissues(P<0.01). Compared with the model group, high-dose SQEPG significantly up-regulated the expression of caspase-3 and Bax proteins in tumor tissues(P<0.05), and significantly down-regulated the expression of CDK4, cyclin D1, and VEGFA proteins(P<0.05 or P<0.01). In conclusion, SQEPG has the effect of improving immune function and inhibiting tumor growth in tumor-bearing mice. Its mechanism of tumor-suppressive effects may be related to apoptosis promotion, cell cycle progression block, and tumor cell proliferation inhibition.
Animals ; Mice ; Drugs, Chinese Herbal/pharmacology* ; Male ; Female ; Apoptosis/drug effects* ; Sarcoma 180/genetics* ; Humans

Poor water solubility is the primary obstacle preventing the development of many pharmacologically active compounds into oral preparations. Self-nanoemulsifying drug delivery systems(SNEDDS) have become a widely used strategy to enhance the oral bioavailability of poorly soluble drugs by inducing a supersaturated state, thereby improving their apparent solubility and dissolution rate. However, the supersaturated solutions formed in SNEDDS are thermodynamically unstable systems with solubility levels exceeding the crystalline equilibrium solubility, making them prone to drug precipitation in the gastrointestinal tract and ultimately hindering drug absorption. Therefore, maintaining a stable supersaturated state is crucial for the effective delivery of poorly soluble drugs. Incorporating polymers as precipitation inhibitors(PPIs) into the formulation of supersaturated self-nanoemulsifying drug delivery systems(S-SNEDDS) can inhibit drug aggregation and crystallization, thus maintaining a stable supersaturated state. This has emerged as a novel preparation strategy and a key focus in SNEDDS research. This review explores the preparation design of SNEDDS and the technical challenges involved, with a particular focus on polymer-based S-SNEDDS for enhancing the solubility and oral bioavailability of poorly soluble drugs. It further elucidates the mechanisms by which polymers participate in transmembrane transport, summarizes the principles by which polymers sustain a supersaturated state, and discusses strategies for enhancing drug absorption. Altogether, this review provides a structured framework for the development of S-SNEDDS preparations with stable quality and reduced development risk, and offers a theoretical reference for the application of S-SNEDDS technology in improving the oral bioavailability of poorly soluble drugs.
Solubility ; Administration, Oral ; Polymers/chemistry* ; Drug Delivery Systems/methods* ; Humans ; Emulsions/chemistry* ; Biological Availability ; Animals ; Pharmaceutical Preparations/administration & dosage*

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Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

AIM:To determine the concentration of ARV-471(a representative PROTAC drug)in mice plasma by establishing an HPLC-MS/MS method and to apply this method in pharmacokinetic studies in mice.METHODS:Verapamil was taken as the inter-nal standard,the mice plasma samples were extract-ed by methanol.After centrifugation,the superna-tant was analyzed by liquid chromatography-mass spectroscopy(LC-MS/MS).Chromatographic col-umn:ACQUITY UPLC HSS T3(1.8 μm,2.1 mm × 50 mm);The mobile phase consists of acetonitrile(containing 0.1％formic acid)and 2 mmol/L ammoni-um formate aqueous solution(containing 0.1％for-mic acid)for gradient elution;flow-rate of 0.6 mL/min;injection volume:2 μL.The electrospray ioniza-tion(ESI)is employed,operating in positive ion scan-ning mode with multiple reaction monitoring(MRM)detection.The specificity,standard curve and quanti-fication limit,precision and accuracy,recovery rate and matrix effect,stability and dilution reliability of this method were examined.Furthermore,the plas-ma concentration and pharmacokinetic parameters of ARV-471 in mice after intravenous injection of 5 mg/kg and oral gavage of 30 mg/kg were deter-mined and calculated.RESULTS:The results dem-onstrate that ARV-471 exhibits a good linear rela-tionship within the concentration range of 2.0 to 2 000.0 ng/mL.The intra-and inter-accuracy were between 80.0％and 120.0％,with the intra-and in-ter-precision less than 15％.The results of method-ological study of specificity,matrix effect,stability conformed to the requirements of the guideline.Pharmacokinetic parameters reveal that after oral administration of 30 mg/kg ARV-471 to male and fe-male mice,Cmax were(2 947.19±454.77)and(2 682.02±342.23)ng·mL-1;AUC0-twere(23 357.37±3 488.00)and(20 161.23±1 871.32)ng·h·mL-1;T1/2were(3.11±0.18)and(2.93±0.62)h.Tmax were(1.83±0.41)and(2.00±0.00)h for male and fe-male mice,respectively.After intravenous adminis-tration of 5 mg/kg ARV-471 to male and female mice,the AUC0-t values were found to be(18 219.07±2 059.41)and(17 238.01±2 380.55)ng·h·mL-1;T1/2 values were(2.76±0.23)and(2.73±0.20)h;The absolute bio-availability of ARV-471 were deter-mined to be(19.49±1.81)％and(21.37±3.19)％for male and female mice,respectively.CONCLU-SION:This study establishes a rapid and effective method for the pharmacokinetic research of ARV-471,laying the foundation for the pharmacokinetic studies of PROTAC drugs.