Objective To explore a method for rapid and differential diagnosis of rejection after kidney transplantation through urine hyperspectral imaging technology. Methods Hyperspectral data information from urine samples of 118 recipients after kidney transplantation was collected, and a deep learning model was constructed to diagnose and classify the types of rejection. Results A deep learning diagnostic model based on the 34-layer residual network (ResNet-34) was constructed, and 118 patients were included and divided into the training set and the test set. Based on the pathological results of the transplanted kidney puncture, the urine samples of the patients were classified into five groups: the non-rejection group, the T-cell-mediated rejection group, the antibody-mediated rejection group, the mixed rejection group and the nephropathy recurrence group. The results showed that the diagnostic sensitivities of the model for the above five groups were 0.960, 0.980, 0.930, 0.940 and 0.943 respectively, and the diagnostic specificities were 0.983, 0.993, 0.997, 0.989 and 0.989 respectively. The overall diagnostic accuracy rate reached 95.7%. Conclusions The study provides a non-invasive, rapid and accurate auxiliary diagnostic method for the differential diagnosis of rejection after kidney transplantation.

ObjectiveTo investigate the effects of Huanglian Jiedutang （HLJDT） on cognitive function in mice with ischemic stroke （IS） and to elucidate whether its neuroprotective effects are mediated by inhibition of the nuclear factor-κB （NF-κB） signaling pathway and subsequent suppression of NF-κB-regulated neuronal apoptosis. MethodsAn IS model was established using middle cerebral artery occlusion （MCAO）. Sixty C57BL/6J mice were randomly assigned to five groups （n =12 per group）， i.e.， sham operation， model， HLJDT low-dose （3.9 g·kg^-1·d^-1）， HLJDT high-dose （7.8 g·kg^-1·d^-1）， and Ginkgo biloba extract （GBE， 31.2 mg·kg^-1·d^-1）. Post-operatively， neurological deficit scores （Longa score）， cerebral infarct volume assessed by 2，3，5-triphenyltetrazolium chloride （TTC） staining， and brain water content were evaluated. Learning and memory were assessed using new object recognition （NOR） and fear conditioning （FC） tests. Hippocampal pathology was examined via hematoxylin and eosin （HE） staining. Immunofluorescence detected expression of glial fibrillary acidic protein （GFAP， astrocyte marker）， cellular oncogene Fos （c-Fos， neuronal activation marker）， and glutamate decarboxylase 65 （GAD65）. Western blot measured nuclear factor-κB inhibitor protein α （IκBα）， phosphorylated IκBα （p-IκBα）， NF-κB p65， phosphorylated NF-κB p65 （p-NF-κB p65）， ionic calcium binding adapter molecule 1 （Iba-1）， tumor necrosis factor （TNF）-α， interleukin （IL）-1β， and apoptosis-related proteins， such as cleaved cysteinyl aspartate-specific protease 3 （Caspase-3）， B-cell lymphoma 2 （Bcl-2）， and Bcl-2-associated X protein （Bax）. Real-time quantitative PCR （Real-time PCR） was used to assess mRNA levels of Iba-1， TNF-α， IL-1β， NF-κB p65， cleaved Caspase-3， Bax， and Bcl-2. ResultsCompared with the sham group， the model group exhibited significantly increased neurological deficit scores， brain water content， and cerebral infarct volume （P<0.01）. Hippocampal CA1 neurons were disorganized， showing nuclear pyknosis and karyolysis. NOR exploration time and FC freezing time were significantly reduced （P<0.01）. GFAP and c-Fos expression were increased， while GAD65 expression was decreased （P<0.01）. Cleaved Caspase-3 and Bax were upregulated， Bcl-2 was downregulated， and the Bax/Bcl-2 ratio was elevated （P<0.01）. Expression levels of p-IκBα， p-NF-κB p65， IL-1β， TNF-α， and Iba-1 were significantly increased （P<0.01）. Compared with the model group， HLJDT high-dose， low-dose， and GBE groups showed significant improvements in all parameters （P<0.01）. Among them， the HLJDT high-dose group showed the most pronounced neuronal structural recovery and superior performance in NOR and FC tests （P<0.01）. In this group， GFAP and c-Fos decreased， GAD65 increased （P<0.01）， apoptosis-related protein expression was reversed， and NF-κB signaling and related inflammatory factor expression were suppressed （P<0.01）. ConclusionHLJDT ameliorates cognitive dysfunction in mice after IS， potentially by inhibiting the NF-κB signaling pathway， thereby reducing neuroinflammation and hippocampal neuronal apoptosis.

ObjectiveTo investigate the feasibility and safety of endoscopic retrograde cholangiopancreatography （ERCP） combined with oral cholangiopancreatography in the treatment of major duodenal papilla gallbladder polyps. MethodsA retrospective analysis was performed for the clinical data of eight patients with choledocholithiasis and gallbladder polyps who underwent ERCP and combined with oral cholangiopancreatography for major duodenal papilla cholecystectomy in Center of Digestive Endoscopy， Jilin People’s Hospital， from May 2022 to June 2024， and related data were collected， including the success rate of surgery， the technical success rate of gallbladder polyp removal， the superselective method of cystic duct， the time of operation， the time of gallbladder polyp removal， and surgical complications. ResultsBoth the success rate of surgery and the technical success rate of gallbladder polyp removal reached 100%， and of all eight patients， three patients used guide wire to enter the gallbladder under direct view， while five patients received oral cholangiopancreatography to directly enter the gallbladder. The time of operation was 51.88±12.34 minutes， and the time of gallbladder polyp removal was 23.13±10.94 minutes. The diameter of gallbladder polyp was 2‍ ‍—‍ ‍8 mm， and pathological examination showed inflammatory polyps in three patients， adenomatous polyps in one patient， and cholesterol polyps in four patients. There were no complications during or after surgery. The patients were followed up for 2‍ ‍—‍ ‍27 months after surgery， and no recurrence of gallbladder polyp was observed. ConclusionOral cholangiopancreatography is technically safe and feasible in endoscopic major duodenal papilla cholecystectomy.

Objective: To explore the changes of mechanosensitive channels Piezos (Piezo 1 and Piezo 2) in neurogenic bladder (NB) of young rats and their effects，so as to provide reference for clinical search of new therapeutic targets. Methods: A total of 30 female young SD rats were divided into 5 groups based on random number table method：sham operation group (sham)，2-week nerve transection group (NB-2W)，6-week nerve transection group (NB-6W)，2-week nerve transection + Piezos inhibitor group (NB-P-2W) and 6-week nerve transection + Piezos inhibitor group (NB-P-6W)，with 6 rats in each group.The NB models were constructed by transecting the L6 and S1 spinal nerves of young rats.The NB-2W and NB-6W groups were not intervened after modeling，while the NB-P-2W and NB-P-6W groups were intraperitoneally injected with Piezos inhibitor GsMTx4 (10 mg/kg) every 2 days after modeling.Bladder cystometry and ultrasound were performed after 2 and 6 weeks of transection.The expressions of Piezos and fibrosis-related indexes (Collagen Ⅰ and α-smooth muscle actin) were detected in bladder tissues. Results: The results of bladder cystometry showed that the basal bladder pressure in NB-2W group was significantly increased，while it was slightly decreased but was still higher in NB-6W group than in the sham group (P<0.05).Basal bladder pressure was lower in NB-P-2W group than in NB-2W group，but was higher than that in the sham group; basal bladder pressure was lower in NB-P-6W group than in NB-6W group，but higher than that in the sham group (P<0.05).Compared with the sham group，the NB-2W and NB-6W groups had firstly increased and then decreased maximum cystometric capacity (MCC) (P<0.05).Compared with NB-2W group，NB-P-2W group had lower bladder leakage point pressure (BLPP)，but higher MCC and bladder compliance (BC) (P<0.05).Compared with NB-6W group，NB-P-6W group had significantly lower BLPP but higher MCC and BC (P<0.05).HE and MASSON staining and ultrasound results showed that，with the extension of nerve transection time，bladder fibrosis gradually worsened，the bladder wall became rough and thickened，calculi were visible inside，and hydronephrosis gradually appeared; the degree of fibrosis in NB-P-2W and NB-P-6W groups was less than that in NB-2W and NB-6W groups，and no hydronephrosis was observed in the upper urinary tract.In addition，Western blotting and immunohistochemical results showed that NB-2W and NB-6W groups had significantly higher relative expression levels of Piezos，Collagen Ⅰ and α-SMA than the sham group (P<0.01)，while NB-P-2W and NB-P-6W groups had lower relative expression levels of Piezos,Collagen Ⅰ and α-SMA than NB-2W and NB-6W groups (P<0.01). Conclusion: The increased expressions of mechanosensitive channels Piezos in NB young rats may be involved in the progression of bladder fibrosis，but its mechanism needs further study.

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.

Graves'ophthalmopathy(GO)is a specific autoimmune disease occurring in orbital tissues and is closely related to hyperthyroidism caused by Graves'disease(GD).Its disabling and disfiguring features significantly impact the quality of life of patients.The exact mechanism of GO still remains to be fully elucidated.In recent years,gene sequencing and medical microbiology studies have shown that changes in the gut microbiota may play a role in the development and progression of GO,with gut dysbiosis altering immune system regulatory signals and causing immune damage to organs.Clarifying the correlation between gut microbiota and GO helps to understand the disease's pathogenic mechanism and provides a theoretical basis for the diagnosis and treatment of GO.This review summarizes the impact of gut microbiota dysbiosis in the pathogenesis of GO and promising therapeutic approaches,including research progress in aspects such as gut microbiota experiments,case studies,pathogenesis,and treatment strategies.

Objective To explore the relationship between dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)and clinical pathological features of invasive breast cancer and lymphovascular invasion(LVI).Methods Imaging and clinical pathological data were retrospectively collected from 508 patients with invasive breast cancer who underwent breast DCE-MRI at the First Medical Center of Chinese PLA General Hospital from January 2019 to August 2021.Patients were divided into the LVI-positive(LVI+)group(n=79)and LVI-negative(LVI-)group(n=429)based on postoperative pathological results.Univariate and multivariate logistic regression analyses were used to identify risk factors for LVI.Results Compared with LVI-group,LVI+group had a higher proportion of patients aged<45 years(44.3%vs.27.0%,P=0.002),non-mass-like enhancement(NME)(31.7%vs.17.7%,P=0.004),Ki-67 expression rate(40.0%vs.30.0%,P<0.001),high Ki-67 expression(94.9%vs.78.1%,P=0.001),Luminal B subtype(76.0%vs.60.1%,P=0.008),and positive axillary lymph nodes rate(72.2%vs.31.5%,P<0.001),while the proportion of Luminal A subtype was lower(2.5%vs.21.5%,P<0.001).Univariate and multivariate logistic regression analyses showed that age≥45 years(OR=0.468,95%CI 0.280-0.783,P=0.004)was an independent protective factor for LVI,while NME(OR=1.987,95%CI 1.126-3.444,P=0.016)was an independent risk factor.Compared with Luminal A subtype,patients with Luminal B subtype(OR=10.482,95%CI 3.164-64.923,P=0.001),HER-2 overexpression subtype(OR=11.571,95%CI 2.755-79.341,P=0.003)and triple-negative subtypes(OR=8.433,95%CI 1.985-57.908,P=0.009)had a higher risk of LVI.Conclusions Age≥45 years is an independent protective factor for LVI,while NME is an independent risk factor.Among molecular subtypes,patients with Luminal B,HER-2 overexpression and triple-negative subtypes have a higher risk of LVI compared with the Luminal A subtype.

Objective To investigate the association of insulin resistance(IR)and its related indices,including triacylglycerol-glucose(TyG)index and metabolic score of insulin resistance(Mets-IR),with the occurrence of early neurological deterioration(END)in patients with branch atheromatous disease(BAD),and develop a risk prediction model based on these factors.Methods A total of 189 BAD patients were consecutively recruited from the Department of Neurology of the Second Affiliated Hospital of Zhengzhou University between March 2020 and August 2024.Based on the occurrence of END within 7 d after admission,the participants were stratified into END(75 cases)and non-END(114 cases)groups.Demographic characteristics,clinical parameters,TyG index and Mets-IR values were systematically collected and analyzed.Multivariate logistic regression analysis was performed to identify independent risk factors for END in BAD-related stroke.Receiver operating characteristic curve(ROC)analysis was subsequently conducted to evaluate the predictive performance of significant variables,followed by construction of a nomogram prediction model.Results The END group exhibited significantly elevated fasting blood glucose[6.47(5.74,7.86)mmol/L vs 5.83(5.14,6.70)mmol/L]and triacylglycerol[1.65(1.21,2.04)mmol/L vs 1.27(0.99,1.57)mmol/L]levels,higher body mass index[25.02(23.88,26.67)kg/m2 vs 23.71(22.66,25.27)kg/m2]and TyG index(9.03±0.41 vs 8.71±0.45),and increased Mets-IR(39.98±4.23 vs 36.85±4.38)and NIHSS score[5.00(3.00,7.00)vs 3.00(2.00,5.00)]at admission when compared with the non-END group(P＜0.05).Multivariate logistic regression analysis showed that high TyG index(OR=3.751,95％CI:1.592-9.202,P＜0.01),Mets-IR(OR=1.146,95％CI:1.049-1.252,P＜0.01),and NIHSS score at admission(OR=1.279,95％CI:1.128-1.451,P＜0.01)were risk factors for the occurrence of END in BAD patients(P＜0.05).ROC curve indicated that the AUC value of TyG index,Mets-IR,and NIHSS score at admission in predicting END occurrence was 0.698(95％CI:0.623-0.774,P＜0.01),0.698(95％CI:0.620-0.775,P＜0.01),and 0.666(95％CI:0.586-0.745,P＜0.01),respectively.The nomogram prediction model based on these factors demonstrated significant clinical benefits by decision curve analysis and goodness of fit in internal calibration analysis.Conclusion IR shows significant association with END in BAD patients.The IR related indices,TyG index and Mets-IR,have certain predictive efficiency for occurrence and progression of END.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.