IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide and a major cause of chronic kidney disease and kidney failure. IgAN exhibits marked heterogeneity in clinical presentation, histopathology, and pathogenic mechanisms, contributing to variable treatment responses and prognosisamong patients. Precise risk assessment and individualized intervention are therefore of critical importance. This review systematically traces the evolution of IgAN management from traditional risk stratification toward biomarker-driven precision medicine. We first review the clinical utility and limitations of established risk stratification tools, including the KDIGO guidelines, the Oxford MEST-C classification, and the International IgAN Prediction Tool. We then discuss emerging biomarkers closely linked to disease pathogenesis, including galactose-deficient IgA1 (Gd-IgA1), anti-Gd-IgA1 autoantibodies, B cell activating factor (BAFF), a proliferation-inducing ligand (APRIL), and complement components, as well as the targeted therapies they have informed. In addition, urinary biomarkers and multi-omics approaches show promise for dynamic disease monitoring and individualized risk stratification.

Elderly patients with primary membranous nephropathy (PMN) exhibit significant prognostic heterogeneity and poor tolerance to immunotherapy. However, there is a lack of early prognostic prediction tools specifically for this population. This study aimed to develop a prognostic prediction model applicable to elderly PMN patients.

Infection-related glomerulonephritis (IRGN) is an immune-mediated glomerular injury triggered by infectious agents. This article reports a case of immune complex-mediated glomerulonephritis following acute hepatitis B virus infection, which continued to progress despite standard antiviral and immunosuppressive therapy. Given the significant elevation of soluble complement membrane attack complex (sC5b-9), an indicator of terminal complement pathway activation, the patient was treated with eculizumab. Following treatment, the patient's urine protein-to-creatinine ratio significantly decreased, hypoalbuminemia and hematuria markedly improved, and sC5b-9 levels declined. This case suggests that abnormal complement system activation may be a key mechanism driving disease persistence in some patients with IRGN. For those unresponsive to conventional therapy, complement function screening and targeted terminal complement pathway inhibition may represent an effective salvage strategy.

Immune checkpoint inhibitors (ICIs) are widely used in the treatment of malignant tumors, and their related immune-related adverse events (irAEs) have attracted increasing attention. This study reports the diagnosis and treatment process of a case of immune cystitis in a patient with hepatobiliary tract malignant tumor after treatment with pembrolizumab. The patient was admitted to the hospital due to frequent urination, urgency of urination and dysuria for 1 month. Previous repeated anti-infection treatments were ineffective. Combined with medical history, laboratory tests, imaging findings, cystoscopy and pathological results, the patient was clinically diagnosed with ICIs-associated immune cystitis (Pembrolizumab) ultimately. The patient's symptoms significantly improved after treatment with glucocorticoids. This case reindicates that clinicians need to improve awareness of ICI-related urinary system irAEs. Early identification and timely intervention can significantly improve patient prognosis.

Oral squamous cell carcinoma (OSCC) is a common head and neck malignancy. Approximately 50% to 60% of patients with OSCC are diagnosed at a locally advanced stage (clinical staging III-IVa). Even with comprehensive and sequential treatment primarily based on surgery, the 5-year overall survival rate remains below 50%, and patients often suffer from postoperative functional impairments such as difficulties with speaking and swallowing. Programmed death receptor-1 (PD-1) inhibitors are increasingly used in the neoadjuvant treatment of locally advanced OSCC and have shown encouraging efficacy. However, clinical practice still faces key challenges, including the definition of indications, optimization of combination regimens, and standards for efficacy evaluation. Based on the latest research advances worldwide and the clinical experience of the expert group, this expert consensus systematically evaluates the application of PD-1 inhibitors in the neoadjuvant treatment of locally advanced OSCC, covering combination strategies, treatment cycles and surgical timing, efficacy assessment, use of biomarkers, management of special populations and immune related adverse events, principles for immunotherapy rechallenge, and function preservation strategies. After multiple rounds of panel discussion and through anonymous voting using the Delphi method, the following consensus statements have been formulated: 1) Neoadjuvant therapy with PD-1 inhibitors can be used preoperatively in patients with locally advanced OSCC. The preferred regimen is a PD-1 inhibitor combined with platinum based chemotherapy, administered for 2-3 cycles. 2) During the efficacy evaluation of neoadjuvant therapy, radiographic assessment should follow the dual criteria of Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 and immune RECIST (iRECIST). After surgery, systematic pathological evaluation of both the primary lesion and regional lymph nodes is required. For combination chemotherapy regimens, PD-L1 expression and combined positive score need not be used as mandatory inclusion or exclusion criteria. 3) For special populations such as the elderly (≥ 70 years), individuals with stable HIV viral load, and carriers of chronic HBV/HCV, PD-1 inhibitors may be used cautiously under the guidance of a multidisciplinary team (MDT), with close monitoring for adverse events. 4) For patients with a poor response to neoadjuvant therapy, continuation of the original treatment regimen is not recommended; the subsequent treatment plan should be adjusted promptly after MDT assessment. Organ transplant recipients and patients with active autoimmune diseases are not recommended to receive neoadjuvant PD-1 inhibitor therapy due to the high risk of immune related activation. Rechallenge is generally not advised for patients who have experienced high risk immune related adverse events such as immune mediated myocarditis, neurotoxicity, or pneumonitis. 5) For patients with a good pathological response, individualized de escalation surgery and function preservation strategies can be explored. This consensus aims to promote the standardized, safe, and precise application of neoadjuvant PD-1 inhibitor strategies in the management of locally advanced OSCC patients.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

ObjectiveDiscriminating atypical hepatocellular carcinoma (HCC) from other malignancies in liver nodules classified as Liver Imaging Reporting and Data System category M (LR-M) remains a significant diagnostic challenge on conventional ultrasound examination. The LR-M category, originally intended to capture non-HCC malignancies, paradoxically contains up to 63% of atypical HCCs that deviate from classic enhancement patterns, leading to potential misdiagnosis and suboptimal treatment planning. While deep learning has shown promise in HCC diagnosis, most existing models rely exclusively on single-modality ultrasound, overlooking the diagnostic benefits of integrating complementary information from multiple imaging sources. To address this gap, we propose a novel attention-weighted tri-modal ultrasound network (TUS-Net) that integrates contrast-enhanced ultrasound (CEUS), B-mode ultrasound (BUS), and time-intensity curves (TICs) to improve diagnostic accuracy for these clinically challenging lesions. MethodsOur framework incorporates a three-dimensional convolutional neural network (C3D) backbone to extract spatiotemporal features from CEUS videos, capturing dynamic vascular patterns critical for lesion characterization. To effectively fuse complementary modalities, we introduce a dual-channel feature fusion module (DCFFM) that adaptively combines features from CEUS and BUS through channel-wise attention mechanisms, allowing the model to dynamically weigh the contribution of each modality based on diagnostic relevance. Additionally, we propose a temporal intensity feature fusion module (TIFFM) that leverages quantitative hemodynamic information from TICs to guide the model’s attention toward diagnostically critical temporal phases, such as arterial wash-in and portal venous washout. The model is further enhanced by automated lesion localization using YOLOX and class activation mapping for interpretability, ensuring that predictions align with clinically meaningful imaging features. ResultsEvaluated on a tri-modal ultrasound dataset comprising 161 patients with pathologically confirmed LR-M nodules (131 atypical HCC and 30 non-HCC malignancies), our model achieved an accuracy of 86.83%, a sensitivity of 92.50%, a specificity of 75.50%, and an AUC of 89.32% in screening atypical HCC. Compared to single-modality baselines, TUS-Net demonstrated superior specificity, a clinically critical metric given the higher risk associated with misclassifying non-HCC malignancies. Ablation studies confirmed the contribution of each module, with the full model outperforming both standard C3D and 3D ResNet backbones integrated with attention mechanisms. A reader study involving junior and senior radiologists further validated the clinical utility of AI assistance, showing consistent improvements in specificity and inter-reader consistency, particularly for less experienced clinicians. ConclusionThese results surpass existing benchmark models and demonstrate the potential of our approach to enhance diagnostic precision in clinically specific cases. By intelligently fusing multi-modal ultrasound data with attention-guided mechanisms, TUS-Net offers a reliable and interpretable tool that holds promise for improving the non-invasive diagnosis of atypical HCC in challenging LR-M liver nodules.

Objective To establish a chronic rejection (CR) model of mouse heart transplantation and analyze its characteristics. Methods Allogeneic BALB/c and C57BL/6 mice were used as donor and recipient for heart transplantation, and intraperitoneal injection of cytotoxic T lymphocyte-associated antigen 4-immunoglobulin (CTLA4-Ig) was given 1 and 2 days after surgery. Graft survival time, donor specific antibody (DSA) level, graft pathology and inflammatory cell infiltration were observed. Results In allogeneic transplantation model, graft survival time was prolonged after CTLA4-Ig treatment [(28.2±4.1) d vs. (7.0±0.7) d, P < 0.01]. The level of serum DSA-IgG increased at 2, 3 and 4 weeks after surgery, while the level of DSA-IgM remained unchanged. Myocardial cell injury, inflammatory cell infiltration, interstitial fibrosis and C4d deposition in capillaries were aggravated 3 weeks after operation and worsened 4 weeks after operation. The infiltrated immune cells were mainly macrophages, T cells and plasma cells. Conclusions Mouse allogeneic heart transplantation combined with CTLA4-Ig successfully establishes a CR model, which provides a basis for subsequent studies on the pathogenesis and intervention of CR.

In order to achieve the quality homogenization of medical services among regions,Chi-na actively explores and promotes the construction of regional national medical centers.This paper illustrates the substantive cooperation during the integration period of the establishment of the re-gional center between output hospital(Sun Yat-Sen University Cancer Center)and the input hospi-tal(Gansu Cancer Hospital).During the integration period a collaborative management model with vertical and horizontal linkages was formed,and the cross-regional long-distance cooperation bar-riers were effectively overcome.Based on the patients-oriented medical service,the two hospitals have achieved remarkable results in the construction and development of clinical service,teach-ing,research and management of Gansu Hospital,which would provide a practical reference for the construction and management of regional national medical center.

Objective To establish the phylogenic relationships among genus Botrychium,and to develop better molecular markers,along with to gain better understanding of cytonuclear coordination patterns of RuBisCO enzyme,the current article sampled two species(e.g.Botrychium ternatum(Thunb.)Sw.and Botrychium virginianum(L.)Sw.),and applied sequencing approaches for the data mining.Methods The assembly results of chloroplast(cp)genomes from B.ternatum and B.virginianum were determined via de novo hybrid assemble approach with the help of short reads(Illumina)and long reads(PacBio and Nanopore).Then the phylogenic relationships of 18 fern species were reconstructed based on the protein coding sequences from the cp genome and the rbcS gene,which were fished out of the RNA-seq data from SRA database,respectively.Then the adaptive selection and co-evolutionary analysis were employed to investigate the evolutionary trajectories of rbcL(cp genome)and rbcS(nuclear genome)genes.Results The full length of cp genome in the two genus Botrychium species were determined as 139 063 bp(NC_060644)and 139 372 bp(OR609363).Then 92 SSR sites and 78 SSR sites were identified in the current two cp genomes,respectively.The collinearity analysis showed high relevant relationship between the current two species,and significant relationship within both species among the inverted repeats regions.The adaptation and coevolution investigations illustrated the following results:①Coevolution network exists between RBCL and RBCS subunits from the fern RuBisCO enzyme.②Positively selected sites were significantly detected among both rbcL and rbcS genes.③Two coevolutionary pair sites from the two genes(e.g.site 11 in RBCL and site 106 in RBCS)were significantly positively selected,which may demonstrate a molecular pattern for the fern species fine-tuning the RuBisCO enzyme during the long earth history via the cytonuclear coordination.Conclusion Our current research shed a new light on the phylogenetic relationship of the genus Botrychium among the fern backbone-tree and provided amount of cpSSR sites with the potential as molecular markers for further population study on B.ternatum and B.virginianum.Moreover,our adaptation and coevolution investigations on rbcL and rbcS genes might indicate that the underlying cytonuclear coordination between the organelle and nuclear in cell of fern species for fine-tuning the key photosynthesis enzyme RuBisCO to gain better fitness according to the changing environment of earth during the geologic time-scale.