A comprehensive overview of graph neural network-based approaches to clustering for spatial transcriptomics.

Spatial transcriptomics technologies enable researchers to accurately quantify and localize messenger ribonucleic acid (mRNA) transcripts at a high resolution while preserving their spatial context. The identification of spatial domains, or the task of spatial clustering, plays a crucial role in investigating data on spatial transcriptomes. One promising approach for classifying spatial domains involves the use of graph neural networks (GNNs) by leveraging gene expressions, spatial locations, and histological images.

HOXA1 participates in VSMC-to-macrophage-like cell transformation via regulation of NF-κB p65 and KLF4: a potential mechanism of atherosclerosis pathogenesis.

Background: Macrophage-like transformation of vascular smooth muscle cells (VSMCs) is a risk factor of atherosclerosis (AS) progression. Transcription factor homeobox A1 (HOXA1) plays functional roles in differentiation and development. This study aims to explore the role of HOXA1 in VSMC transformation, thereby providing evidence for the potential mechanism of AS pathogenesis.

Graph deep learning enabled spatial domains identification for spatial transcriptomics.

Advancing spatially resolved transcriptomics (ST) technologies help biologists comprehensively understand organ function and tissue microenvironment. Accurate spatial domain identification is the foundation for delineating genome heterogeneity and cellular interaction. Motivated by this perspective, a graph deep learning (GDL) based spatial clustering approach is constructed in this paper.

The locoregional adiponectin and its synergistic antitumor effect with HIF-1α blockade in TSCC.

Adiponectin (APN) is a kind of endogenous anti-tumor adipocytokine, which exerts its function by binding to its receptors (AdipoR1 and AdipoR2). However, hyperadiponectinemia is found in some pathophysiological processes without significant protective effect, which indicates the existence of APN resistance. Here, we aimed to investigate the locoregional expression of APN in tongue squamous cell carcinoma (TSCC) tissues, and to explore the potential regulatory mechanism of APN resistance under hypoxia.

Polyethylene Glycol Ointment Alleviates Psoriasis-Like Inflammation Through Down-Regulating the Function of Th17 Cells and MDSCs.

To explore the possible mechanism of improving the imiquimod (IMQ)-induced psoriasis-like inflammation by using polyethylene glycol (PEG) ointment. We evaluated the appearance of psoriasis lesions by Psoriasis Area and Severity Index (PASI), observed the epidermal proliferation by histopathological staining and immunohistochemical staining, and explored the key molecules and signaling pathways of improving psoriasis-like inflammation treated with PEG ointment by RNA sequencing. Finally, we verified the expression of inflammatory cells and inflammatory factors by flow cytometry, immunohistochemical staining, and Q-PCR.

PySmash: Python package and individual executable program for representative substructure generation and application.

Background: Substructure screening is widely applied to evaluate the molecular potency and ADMET properties of compounds in drug discovery pipelines, and it can also be used to interpret QSAR models for the design of new compounds with desirable physicochemical and biological properties. With the continuous accumulation of more experimental data, data-driven computational systems which can derive representative substructures from large chemical libraries attract more attention. Therefore, the development of an integrated and convenient tool to generate and implement representative substructures is urgently needed.

QSAR-assisted-MMPA to expand chemical transformation space for lead optimization.

Matched molecular pairs analysis (MMPA) has become a powerful tool for automatically and systematically identifying medicinal chemistry transformations from compound/property datasets. However, accurate determination of matched molecular pair (MMP) transformations largely depend on the size and quality of existing experimental data. Lack of high-quality experimental data heavily hampers the extraction of more effective medicinal chemistry knowledge.

RSK2 protects human breast cancer cells under endoplasmic reticulum stress through activating AMPKα2-mediated autophagy.

Autophagy can protect stressed cancer cell by degradation of damaged proteins and organelles. However, the regulatory mechanisms behind this cellular process remain incompletely understood. Here, we demonstrate that RSK2 (p90 ribosomal S6 kinase 2) plays a critical role in ER stress-induced autophagy in breast cancer cells.

UCH-L1-mediated Down-regulation of Estrogen Receptor α Contributes to Insensitivity to Endocrine Therapy for Breast Cancer.

: To determine the role of UCH-L1 in regulating ERα expression, and to evaluate whether therapeutic targeting of UCH-L1 can enhance the efficacy of anti-estrogen therapy against breast cancer with loss or reduction of ERα. : Expressions of UCH-L1 and ERα were examined in breast cancer cells and patient specimens. The associations between UCH-L1 and ERα, therapeutic response and prognosis in breast cancer patients were analyzed using multiple databases.

Identification of phosphatidylcholine and lysophosphatidylcholine as novel biomarkers for cervical cancers in a prospective cohort study.

Metabolites are the end products of cellular regulatory processes. Squamous cervical cancer (SCC) can alter the level of certain small molecular metabolite in plasma through modulating gene expression. In this study, we identified two metabolites, phosphatidylcholine (PC) and lysophosphatidylcholine (LPC), which are significantly down- and upregulated in plasma of SCC as compared to uterine fibroid (UF) patients via ultra-performance liquid chromatographic-mass spectrometry (UPLC-MS).

LAPTM4B-35 overexpression is an independent prognostic marker in endometrial carcinoma.

Background: Lysosomal protein transmembrane 4 β-35 (LAPTM4B-35), a novel oncoprotein that belongs to the mammalian 4-tetratransmembrane spanning protein superfamily, has been implicated in oncogenesis and cancer progression in several solid malignances. However, the expression of LAPTM4B-35 and its role in endometrial cancer progression remain unknown.

Materials And Methods: We investigated the expression of the LAPTM4B-35 protein by immunohistochemistry in 30 normal endometrium specimens and 165 endometrial carcinomas and analyzed its correlation with various clinicopathologic features, including patient outcome.