Gene Co-expression Network Characterizing Microenvironmental Heterogeneity and Intercellular Communication in Pancreatic Ductal Adenocarcinoma: Implications of Prognostic Significance and Therapeutic Target

Background Pancreatic ductal adenocarcinoma (PDAC) is characterized by intensive stroma involvement and heterogeneity. Pancreatic cancer cells interplay with surrounding tumor micro-environment (TME), leading to exacerbated tumorigenesis, dismal prognosis and tenacious therapy resistance. Herein, we aim to ascertain a gene-network indicative of vicious features of TME, then find a vulnerability for pancreatic cancer. Methods Single cell RNA sequencing data was processed by Seurat package, retrieving the cell component marker genes (CCMGs). Correlation networks/modules of CCMGs were determined by WGCNA algorithm in a combined PDAC mRNA expression dataset. The gene modules that statistically associate with prognosis were chosen for classifying TME subgroups, constructing neural network and designing the risk score system. Cell-cell communication analysis was achieved by NATMI software. The tumor suppressive effect of ITGA2 inhibitor was evaluated in vivo by using a Kras G12D -driven murine pancreatic cancer model.Results WGCNA analysis categorized cell component marker genes into eight co-expression networks. From gene modules with the maximum and minimum hazard ratio, we stratify PDAC samples based on TME gene patterns, resulting in two main TME subclasses with contrasting survival periods. Furthermore, we generated a neural network model and a risk score model which robustly predict prognosis and therapeutic outcomes. The hub genes in both gene modules were also gathered for functional enrichment analysis, elucidating a crucial role of cell communication-mediating integrins in TME associated PDAC malignancy. To perform a confirmatory experiment underpinning the significance of hub gene targeting, the mice with spontaneously developed pancreatic cancer were orally treated with an integrin inhibitor. The in vivo assays unraveled that pharmacologically inhibiting ITGA2 counteracts cancer-promoting micro-environment, and ameliorates pancreatic lesions. Conclusions By recapitulating gene-network across various cell types, we exploited novel PDAC prognosis-predicting strategies. Medically interfering ITGA2, a key factor guiding cellular reciprocal interaction, attenuated tumor development. These findings may open new avenue about PDAC targeting therapy.

Assessment of Human Islet Composition and Acinar Cell Component by Immunofluorescence Staining v2

This Standard Operating Procedure (SOP) is based on the Human Islet Phenotyping Program of the IIDP Immunofluorescence Staining Procedure. This SOP provides the HIPP procedure for immunofluorescent staining, imaging, and analysis of islet preparations. This SOP defines the assay method used by the Human Islet Phenotyping Program (HIPP) for quantitative and qualitative determination of the Purified Human Pancreatic Islet product, post-shipment, manufactured for use in the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)-sponsored research in the Integrated Islet Distribution Program (IIDP).

Identification of Hub Genes Associated With Tuberculous Pleurisy by Integrated Bioinformatics Analysis

Improving the understanding of the molecular mechanism of tuberculous pleurisy is required to develop diagnosis and new therapy strategies of targeted genes. The purpose of this study is to identify important genes related to tuberculous pleurisy. In this study, the expression profile obtained by sequencing the surgically resected pleural tissue was used to explore the differentially co-expressed genes between tuberculous pleurisy tissue and normal tissue. 29 differentially co-expressed genes were screened by weighted gene co-expression network analysis (WGCNA) and differential gene expression analysis methods. According to the functional annotation analysis of R clusterProfiler software package, these genes are mainly enriched in nucleotide−sugar biosynthetic process (biological process), ficolin−1−rich granule lumen (cell component), and electron transfer activity (molecular function). In addition, in the protein-protein interaction (PPI) network, 20 hub genes of DEGs and WCGNA genes were identified using the CytoHubba plug-in of Cytoscape. In the end, RPL17 was identified as a gene that can be the biomarker of tuberculous pleurisy. At the same time, there are seven genes that may have relationship with the disease (UBA7, NDUFB8, UQCRFS1, JUNB, PSMC4, PHPT1, and MAPK11).

Research on Online Defect Detection Method of Solar Cell Component Based on Lightweight Convolutional Neural Network

The defects of solar cell component (SCC) will affect the service life and power generation efficiency. In this paper, the defect images of SCC were taken by the photoluminescence (PL) method and processed by an advanced lightweight convolutional neural network (CNN). Firstly, in order to solve the high pixel SCC image detection, each silicon wafer image was segmented based on local difference extremum of edge projection (LDEEP). Secondly, in order to detect the defects with small size or weak edges in the silicon wafer, an improved lightweight CNN model with deep backbone feature extraction network structure was proposed, as the enhancing feature fusion layer and the three-scale feature prediction layer; the model provided more feature detail. The final experimental results showed that the improved model achieves a good balance between the detection accuracy and detection speed, with the mean average precision (mAP) reaching 87.55%, which was 6.78% higher than the original algorithm. Moreover, the detection speed reached 40 frames per second (fps), which meets requirements of precision and real-time detection. The detection method can better complete the defect detection task of SCC, which lays the foundation for automatic detection of SCC defects.

Parameters of the gelatinase B activity in the integument epithelium and the lamina propria of the gastric mucosa in experimental acetate ulcer in rats

Objective: to determine the specifi c number and expression intensity of gelatinase B-positive cells in the gastric surface epithelium and lamina propria (cell component) in the area of the ulcerous defect in rats with experimental acetate ulcer of the stomach.Materials and methods: 18 white Wistar rats were divided into three groups: initial (intact), experimental (modeling of an acetate ulcer) and control (falsely operated) in the experiment. Tissues were obtained from the ulceration zone or the presumed ulceration zone (in the initial and control groups) to asses morphological changes and also indicators, characterizing the activity of gelatinase B 7 days after the simulation of the experiment.Results and Discussion. It was revealed some increase in the specifi c number of gelatinase B-positive cells against the background of moderate accumulation of lymphocytes in the integument epithelium of the gastric mucosa. A signifi cant increase in the specifi c number of gelatinase B-positive cells at the maximum intensity of its expression and a moderate accumulation of eff ector cells of tissue alterations was determined in the cellular component of the lamina propria of the gastric mucosa at the same time.

Succinylation profiles of brain injury after intracerebral hemorrhage

Protein posttranslational modifications (PTMs) regulate the biological processes of human diseases by genetic code expansion and cellular pathophysiology regulation; however, system-wide changes in PTM levels in the intracerebral hemorrhage (ICH) brain remain poorly understood. Succinylation refers to a major PTM during the regulation of multiple biological processes. In this study, according to the methods of quantitative succinyllysine proteomics based on high-resolution mass spectrometry, we investigated ICH-associated brain protein succinyllysine modifications and obtained 3,680 succinylated sites and quantified around 3,530 sites. Among them, 25 succinyllysine sites on 23 proteins were upregulated (hypersuccinylated), whereas 13 succinyllysine sites on 12 proteins were downregulated (hyposuccinylated) following ICH. The cell component enrichment analysis of these succinylproteins with significant changes showed that 58.3% of the hyposuccinylated proteins were observed in the mitochondria, while the hyper-succinylproteins located in mitochondria decreased in the percentage to about 35% in ICH brains with a concomitant increase in the percentage of cytoplasm to 30.4%. Further bioinformatic analysis showed that the succinylproteins were mostly mitochondria and synapse-related subcellular located and involved in many pathophysiological processes, like metabolism, synapse working, and ferroptosis. Moreover, the integrative analysis of our succinylproteomics data and previously published transcriptome data showed that the mRNAs matched by most differentially succinylated proteins were especially highly expressed in neurons, endothelial cells, and astrocytes. Our study uncovers some succinylation-affected processes and pathways in response to ICH brains and gives us novel insights into understanding pathophysiological processes of brain injury caused by ICH.

Gastrointestinal Goblet Cell Adenocarcinomas Harbor Distinctive Clinicopathological, Immune, and Genomic Landscape

Goblet cell adenocarcinoma (GCA) is a rare amphicrine tumor and difficult to diagnose. GCA is traditionally found in the appendix, but extra-appendiceal GCA may be underestimated. Intestinal adenocarcinoma with signet ring cell component is also very rare, and some signet ring cell carcinomas are well cohesive, having some similar morphological features to GCAs. It is necessary to differentiate GCA from intestinal adenocarcinomas with cohesive signet ring cell component (IACSRCC). The goal of this study is to find occurrence of extra-appendiceal GCA and characterize the histological, immunohistochemical, transcriptional, and immune landscape of GCA. We collected 12 cases of GCAs and 10 IACSRCCs and reviewed the clinicopathologic characters of these cases. Immunohistochemical stains were performed with synaptophysin, chromogranin A, CD56, somatostatin receptor (SSTR) 2, and Ki-67. Whole transcriptome RNA-sequencing was performed, and data were used to analyze differential gene expression and predict immune cell infiltration levels in GCA and IACSRCC. RNA-sequencing data for colorectal adenocarcinoma were gathered from TCGA data portal. Of the 12 patients with GCA, there were 4 women and 8 men. There were three appendiceal cases and nine extra-appendiceal cases. GCAs were immunohistochemically different from IACSRCC. GCA also had different levels of B-cell and CD8+ T-cell infiltration compared to both colorectal adenocarcinoma and cohesive IACSRCCs. Differential gene expression analysis showed distinct gene expression patterns in GCA compared to colorectal adenocarcinoma, with a number of cancer-related differentially expressed genes, including upregulation of TMEM14A, GOLT1A, DSCC1, and HSD17B8, and downregulation of KCNQ1OT1 and MXRA5. GCA also had several differentially expressed genes compared to IACSRCCs, including upregulation of PRSS21, EPPIN, RPRM, TNFRSF12A, and BZRAP1, and downregulation of HIST1H2BE, TCN1, AC069363.1, RP11-538I12.2, and REG4. In summary, the number of extra-appendiceal GCA was underestimated in Chinese patients. GCA can be seen as a distinct morphological, immunohistochemical, transcriptomic, and immunological entity. The classic low-grade component of GCA and the immunoreactivity for neuroendocrine markers are the key points to diagnosing GCA.