Objective. Autophagy has been reported to be involved in the development of various disorders such as neurodegenerative and metabolic diseases and tumors. Autophagy activators and inhibitors are also potential therapeutics for these diseases. However, the mechanism of autophagic involvement in different diseases is not the same, and the role of autophagy in endometriosis (EM) has not yet been elucidated. This research investigated the mechanism by which autophagy acts in EM, with the aim of establishing a theoretical basis for its prevention and treatment through the targeted interference with autophagy. Methods. We used an RNA interference fragment targeting ATG5, the autophagy activator rapamycin, and the autophagy inhibitor 3-MA or overexpression of filopodia-related protein fascin-1, in conjunction with clonogenic assays, growth curves, and scratch assay to investigate the influence of autophagy on cellular growth, proliferation, and invasiveness. We collected specimens from 20 clinical cases of EM and investigated the protein expression of the autophagic marker LC3-II, the autophagic substrate p62, and fascin-1. Results. Rapamycin was able to inhibit the proliferation and colony formation of the endometriotic cell line CRL-7566, whereas the autophagy inhibitor 3-MA as well as the interference with the autophagy-related gene ATG5 had the opposite effect. More importantly, the autophagy activator rapamycin was able to inhibit the growth of filopodia in the endometriotic cells, and the overexpression of the fascin-1 restored the rapamycin-induced decrease of invasiveness. We found that the expression of the autophagy marker LC3-II was significantly reduced among the clinical EM specimens compared to the control group, while the expressions of fascin-1 and autophagic substrate p62 were increased. Conclusion. Our results indicate that the inhibition of autophagy and exogenous expression of fascin-1 may promote the invasiveness of endometrial cells. As a corollary, autophagy represents a potential target for the treatment of EM.

Background: Epstein-Barr virus-positive inflammatory follicular dendritic cell sarcoma (EBV+IFDCS) is a rare disease characterized by mild clinical symptoms and non-specific imaging findings. The diagnosis of the disease depends on pathological diagnosis. However, EBV+IFDCS has a very broad spectrum of histological morphology and immune phenotypes, and its histopathological features have not been fully described by pathologists. Case presentation: A 59-year-old female, with no significant discomfort, was found to have a splenic mass during a routine physical examination. Microscopic examination at low magnification revealed numerous epithelioid granulomas, amidst which a substantial inflammatory response was observed. Interspersed among the dense inflammatory cells were spindle or oval-shaped cells, distributed sporadically with indistinct boundaries. Under high magnification, these spindle cells had subtle features: smooth and clear nuclear membranes, inconspicuous small nucleoli, and infrequent mitotic figures. Immunophenotypically, the spindle cells expressed CD21 and CD23, and Epstein-Barr encoding region (EBER) in situ hybridization yielded positive results. The inflammatory milieu predominantly consisted of T cells, with a minority of plasma cells expressing IgG4. The confluence of morphological and immunohistochemical findings led to the final pathological diagnosis of EBV+IFDCS in this case. Conclusions: The presentation of EBV+IFDCS with pronounced granulomatous changes is rare. This morphological variant poses a high risk of misdiagnosis, frequently leading to confusion with other granulomatous diseases. Accurate diagnosis necessitates a comprehensive analysis, integrating immunohistochemistry and in situ hybridization. The case presented here is instrumental in raising awareness and understanding of EBV+IFDCS, with the goal of reducing misdiagnoses and unrecognized cases.

The canonical Wnt signalling pathway is a critical pathway involved in the proliferation of cells. It has been well‐established that it plays the central role during colorectal carcinogenesis and development. Yet the exact molecular mechanism of how the canonical Wnt pathway is fine‐tuned remains elusive. We found that SLC35C1, a GDP‐fucose transporter, negatively regulates the Wnt signalling pathway. We show here that SLC35C1 is reduced in all colon cancer by both immunohistochemistry images and TCGA data, whereas β‐catenin is increased. Down‐regulation of SLC35C1 is also detected by real‐time PCR in stage 3 and stage 4 colorectal cancer tissues. Moreover, analysing the TCGA database with cBioPortal reveals the negative correlation of SLC35C1 mRNA level to the expression of β‐catenin. Reduced SLC35C1 significantly promotes cell proliferation and colony formation of HEK293 cells. Meanwhile, in HEK293 cells silencing SLC35C1 activates canonical Wnt pathway, whereas overexpressing SLC35C1 inhibits it. Consistently, the reduction of SLC35C1 in HEK293 cells also elevated the mRNA level of Wnt target genes C‐myc , Axin2 and Cyclin D1 , as well as the secretion of Wnt3a. In conclusion, we identified SLC35C1 as a negative regulator of the Wnt signalling pathway in colon cancer. Decreased SLC35C1 may cause over‐activation of Wnt signalling in colorectal cancer.

This study focuses on the pathological subtype classification of lung adenocarcinoma (LUAD) in frozen sections and is the first to apply the state space model Vision Mamba to this task. We developed a fine-tuned multimodal MedMamba model that integrates histopathological images with non-image data. Through architectural optimization and multimodal fusion–including clinical variables and structured CT reports–the model achieved a well-balanced performance in classification accuracy, computational efficiency, and interpretability. In five-fold cross-validation, it achieved a recall of 92.0% and an F1-score of 91.6% for invasive adenocarcinoma (IAC) classification, as well as an accuracy of 89.7% and specificity of 92.0% for adenocarcinoma in situ (AIS) classification. On an external test set, the model maintained an accuracy of 84.2%, outperforming mainstream models such as InceptionV3, EfficientNetV2, and ResNet50. Further analysis revealed significant associations between tumor volume, radiologic appearance, and patient age with subtype classification, highlighting the potential of non-image modalities in diagnostic support. These findings demonstrate the practical value of the fine-tuned multimodal MedMamba model for intraoperative rapid pathology interpretation and clinical risk control.