Histogenetic insights and genetic landscape of fibromatosis-like undifferentiated gastric carcinoma: a focused study.

BACKGROUND: The aim of this study was to elucidate the histogenesis and genetic underpinnings of fibromatosis-like undifferentiated gastric carcinoma (FLUGC), a rare pathological entity. METHOD: Through a detailed analysis of seven cases, including histopathological evaluation, CTNNB1 gene mutation screening, human epidermal growth factor receptor 2 (HER2) protein level quantification, and HER2 gene amplification assessment to identify the pathological and molecular characteristics of FLUGC. RESULTS: Of the seven patients in this study, five were male and two were female (age: 39-73 years). Four patients presented with lesions in the gastric antrum and three had lesions in the lateral curvature of the stomach. Histopathologically, over 90% of the tumor consisted of aggressive fibromatosis-like tissue, including proliferating spindle fibroblasts and myofibroblasts and varying amounts of collagenous fibrous tissues. Undifferentiated cancer cells, accounting for less than 10%, were dispersed among the aggressive fibromatosis-like tissues. These cells were characterized by their small size and were relatively sparse without glandular ducts or nested mass-like structures. Immunophenotyping results showed positive expression of CKpan, CDX2, villin, and p53 in undifferentiated cancer cells; positive expression of vimentin in aggressive fibromatosis-like tissue; positive cytoplasmic expression of ß-catenin; and focal cytoplasmic positive expression of smooth muscle actin (SMA). Genetic analysis did not reveal any mutations in the CTNNB1 gene test, nor was there amplification in the HER2 gene fluorescence in situ hybridization (FISH) test. Additionally, the Epstein-Barr encoding region (EBER) of in situ hybridization was negative; and the mismatch repair (MMR) protein was positive. Programmed cell death-1 (PD-1) was < 1-5%; programmed cell death ligand 1 (PD-L1): TPS = 1-4%, CPS = 3-8. CONCLUSION: The study highlights the significance of CTNNB1, HER2, EBER, and MMR as pivotal genetic markers in FLUGC, underscoring their relevance for diagnosis and clinical management. The rarity and distinct pathological features of FLUGC emphasize the importance of accurate diagnosis to prevent underdiagnosis or misdiagnosis and to raise awareness within the medical community.

Endothelial CXCR2 deficiency attenuates renal inflammation and glycocalyx shedding through NF-κB signaling in diabetic kidney disease.

BACKGROUND: The incidence of diabetic kidney disease (DKD) continues to rapidly increase, with limited available treatment options. One of the hallmarks of DKD is persistent inflammation, but the underlying molecular mechanisms of early diabetic kidney injury remain poorly understood. C-X-C chemokine receptor 2 (CXCR2), plays an important role in the progression of inflammation-related vascular diseases and may bridge between glomerular endothelium and persistent inflammation in DKD. METHODS: Multiple methods were employed to assess the expression levels of CXCR2 and its ligands, as well as renal inflammatory response and endothelial glycocalyx shedding in patients with DKD. The effects of CXCR2 on glycocalyx shedding, and persistent renal inflammation was examined in a type 2 diabetic mouse model with Cxcr2 knockout specifically in endothelial cells (DKD-Cxcr2 eCKO mice), as well as in glomerular endothelial cells (GECs), cultured in high glucose conditions. RESULTS: CXCR2 was associated with early renal decline in DKD patients, and endothelial-specific knockout of CXCR2 significantly improved renal function in DKD mice, reduced inflammatory cell infiltration, and simultaneously decreased the expression of proinflammatory factors and chemokines in renal tissue. In DKD conditions, glycocalyx shedding was suppressed in endothelial Cxcr2 knockout mice compared to Cxcr2 L/L mice. Modulating CXCR2 expression also affected high glucose-induced inflammation and glycocalyx shedding in GECs. Mechanistically, CXCR2 deficiency inhibited the activation of NF-κB signaling, thereby regulating inflammation, restoring the endothelial glycocalyx, and alleviating DKD. CONCLUSIONS: Taken together, under DKD conditions, activation of CXCR2 exacerbates inflammation through regulation of the NF-κB pathway, leading to endothelial glycocalyx shedding and deteriorating renal function. Endothelial CXCR2 deficiency has a protective role in inflammation and glycocalyx dysfunction, suggesting its potential as a promising therapeutic target for DKD treatment.

Interpretation for Individual Brain Age Prediction Based on Gray Matter Volume.

The relationship between age and the central nervous system (CNS) in humans has been a classical issue that has aroused extensive attention. Especially for individuals, it is of far greater importance to clarify the mechanisms between CNS and age. The primary goal of existing methods is to use MR images to derive high-accuracy predictions for age or degenerative diseases. However, the associated mechanisms between the images and the age have rarely been investigated. In this paper, we address the correlation between gray matter volume (GMV) and age, both in terms of gray matter themselves and their interaction network, using interpretable machine learning models for individuals. Our goal is not only to predict age accurately but more importantly, to explore the relationship between GMV and age. In addition to targeting each individual, we also investigate the dynamic properties of gray matter and their interaction network with individual age. The results show that the mean absolute error (MAE) of age prediction is 7.95 years. More notably, specific locations of gray matter and their interactions play different roles in age, and these roles change dynamically with age. The proposed method is a data-driven approach, which provides a new way to study aging mechanisms and even to diagnose degenerative brain diseases.