Investigating the ID3/SLC22A4 as immune-related signatures in ischemic stroke

BACKGROUND

Ischemic stroke (IS) is a fearful disease that can cause a variety of immune events. Nevertheless, precise immune-related mechanisms have yet to be systematically elucidated. This study aimed to identify immune-related signatures using machine learning and to validate them with animal experiments and single cell analysis.

METHODS

In this study, we screened 24 differentially expressed genes (DEGs) while identifying immune-related signatures that may play a key role in IS development through a comprehensive strategy between least absolute shrinkage and selection operation (LASSO) regression, support vector machine (SVM) and immune-related genes. In addition, we explored immune infiltration using the CIBERSORT algorithm. Finally, we performed validation in mouse brain tissue and single cell analysis.

RESULTS

We identified 24 DEGs for follow-up analysis. ID3 and SLC22A4 were finally identified as the better immune-related signatures through a comprehensive strategy among DEGs, LASSO, SVM and immune-related genes. RT-qPCR, western blot, and immunofluorescence revealed a significant decrease in ID3 and a significant increase in SLC22A4 in the middle cerebral artery occlusion group. Single cell analysis revealed that ID3 was mainly concentrated in endothelial_2 cells and SLC22A4 in astrocytes in the MCAO group. A CIBERSORT finds significantly altered levels of immune infiltration in IS patients.

CONCLUSIONS

This study focused on immune-related signatures after stroke and ID3 and SLC22A4 may be new therapeutic targets to promote functional recovery after stroke. Furthermore, the association of ID3 and SLC22A4 with immune cells may be a new direction for post-stroke immunotherapy.

Phenotypic Analysis and Molecular Characterization of Enlarged Cell Size Mutant in Nannochloropsis oceanica

The cell cycle is the fundamental cellular process of eukaryotes. Although cell-cycle-related genes have been identified in microalgae, their cell cycle progression differs from species to species. Cell enlargement in microalgae is an essential biological trait. At the same time, there are various causes of cell enlargement, such as environmental factors, especially gene mutations. In this study, we first determined the phenotypic and biochemical characteristics of a previously obtained enlarged-cell-size mutant of Nannochloropsis oceanica, which was designated ECS. Whole-genome sequencing analysis of the insertion sites of ECS indicated that the insertion fragment is integrated inside the 5'-UTR of U/P-type cyclin CYCU;1 and significantly decreases the gene expression of this cyclin. In addition, the transcriptome showed that CYCU;1 is a highly expressed cyclin. Furthermore, cell cycle analysis and RT-qPCR of cell-cycle-related genes showed that ECS maintains a high proportion of 4C cells and a low proportion of 1C cells, and the expression level of CYCU;1 in wild-type (WT) cells is significantly increased at the end of the light phase and the beginning of the dark phase. This means that CYCU;1 is involved in cell division in the dark phase. Our results explain the reason for the larger ECS size. Mutation of CYCU;1 leads to the failure of ECS to fully complete cell division in the dark phase, resulting in an enlargement of the cell size and a decrease in cell density, which is helpful to understand the function of CYCU;1 in the Nannochloropsis cell cycle.

The Potential Mechanism of Cannabidiol (CBD) Treatment of Epilepsy in Pentetrazol (PTZ) Kindling Mice Uncovered by Multi-Omics Analysis

Cannabidiol (CBD) is the main active ingredient in the cannabis plant used for treating epilepsy and related diseases. However, how CBD ameliorates epilepsy and its effect on the hippocampus remains unknown. Herein, we evaluated how CBD ameliorates seizure degree in pentylenetetrazol (PTZ) induced epilepsy mice after being exposed to CBD (10 mg/kg p.o). In addition, transcriptome and metabolomic analysis were performed on the hippocampus. Our results suggested that CBD could alleviate PTZ-induced seizure, of which the NPTX2, Gprc5c, Lipg, and Stc2 genes were significantly down-regulated in mice after being exposed to PTZ. Transcriptome analysis showed 97 differently expressed genes (CBD) and the PTZ groups. Metabonomic analysis revealed that compared with the PTZ group, 41 up-regulated and 67 down-regulated metabolites were identified in the hippocampus of epileptic mice exposed to CBD. The correlation analysis for transcriptome and metabolome showed that (±) 15-HETE and carnitine C6:0 were at the core of the network and were involved in the positive or negative regulation of the related genes after being treated with CBD. In conclusion, CBD ameliorates epilepsy by acting on the metabolism, calcium signaling pathway, and tuberculosis pathways in the hippocampus. Our study provided a practical basis for the therapeutic potential of treating epilepsy using CBD.

A Highly Effective Bacteriophage-1252 to Control Multiple Serovars of Salmonella enterica

Salmonella enterica (S. enterica) is the most common foodborne pathogen worldwide, leading to massive economic loss and a significant burden on the healthcare system. The primary source of S. enterica remains contaminated or undercooked poultry products. Considering the number of foodborne illnesses with multiple antibiotic resistant S. enterica, new controlling approaches are necessary. Bacteriophage (phage) therapies have emerged as a promising alternative to controlling bacterial pathogens. However, the limitation on the lysis ability of most phages is their species-specificity to the bacterium. S. enterica has various serovars, and several major serovars are involved in gastrointestinal diseases in the USA. In this study, Salmonella bacteriophage-1252 (phage-1252) was isolated and found to have the highest lytic activity against multiple serovars of S. enterica, including Typhimurium, Enteritidis, Newport, Heidelberg, Kentucky, and Gallinarum. Whole-genome sequencing analysis revealed phage-1252 is a novel phage strain that belongs to the genus Duplodnaviria in the Myoviridae family, and consists of a 244,421 bp dsDNA, with a G + C content of 48.51%. Its plaque diameters are approximately 2.5 mm to 0.5 mm on the agar plate. It inhibited Salmonella Enteritidis growth after 6 h. The growth curve showed that the latent and rise periods were approximately 40 min and 30 min, respectively. The burst size was estimated to be 56 PFU/cell. It can stabilize and maintain original activity between 4 °C and 55 °C for 1 h. These results indicate that phage-1252 is a promising candidate for controlling multiple S. enterica serovars in food production.

Clustering analysis revealed the autophagy classification and potential autophagy regulators' sensitivity of pancreatic cancer based on multi-omics data

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy and is unresponsive to conventional therapeutic modalities due to its high heterogeneity, expounding the necessity, and priority of searching for effective biomarkers and drugs. Autophagy, as an evolutionarily conserved biological process, is upregulated in PDAC and its regulation is linked to a poor prognosis. Increased autophagy sequestered MHC-I on PDAC cells and weaken the antigen presentation and antitumor immune response, indicating the potential therapeutic strategies of autophagy inhibitors.

METHODS

By performing 10 state-of-the-art multi-omics clustering algorithms, we constructed a robust PDAC classification model to reveal the autophagy-related genes among different subgroups.

OUTCOMES

After building a more comprehensive regulating network for potential autophagy regulators exploration, we concluded the top 20 autophagy-related hub genes (GAPDH, MAPK3, RHEB, SQSTM1, EIF2S1, RAB5A, CTSD, MAP1LC3B, RAB7A, RAB11A, FADD, CFKN2A, HSP90AB1, VEGFA, RELA, DDIT3, HSPA5, BCL2L1, BAG3, and ERBB2), six miRNAs, five transcription factors, and five immune infiltrated cells as biomarkers. The drug sensitivity database was screened based on the biomarkers to predict possible drug-targeting signal pathways, hoping to yield novel insights, and promote the progress of the anticancer therapeutic strategy.

CONCLUSION

We succefully constructed an autophagy-related mRNA/miRNA/TF/Immune cells network based on a 10 state-of art algorithm multi-omics analysis, and screened the drug sensitivity dataset for detecting potential signal pathway which might be possible autophagy modulators' targets.

Dental calculus: A repository of bioinformation indicating diseases and human evolution

Dental calculus has long been considered as a vital contributing factor of periodontal diseases. Our review focuses on the role of dental calculus as a repository and discusses the bioinformation recently reported to be concealed in dental calculus from three perspectives: time-varying oral condition, systemic diseases, and anthropology at various times. Molecular information representing an individual's contemporary oral health status could be detected in dental calculus. Additionally, pathogenic factors of systemic diseases were found in dental calculus, including bacteria, viruses and toxic heavy metals. Thus, dental calculus has been proposed to play a role as biological data storage for detection of molecular markers of latent health concerns. Through the study of environmental debris in dental calculus, an overview of an individual's historical dietary habits and information about the environment, individual behaviors and social culture changes can be unveiled. This review summarizes a new role of dental calculus as a repository of bioinformation, with potential use in the prediction of oral diseases, systemic diseases, and even anthropology.

Linking transcriptomes with morphological and functional phenotypes in mammalian retinal ganglion cells

Retinal ganglion cells (RGCs) are the brain's gateway to the visual world. They can be classified into different types on the basis of their electrophysiological, transcriptomic, or morphological characteristics. Here, we characterize the transcriptomic, morphological, and functional features of 472 high-quality RGCs using Patch sequencing (Patch-seq), providing functional and morphological annotation of many transcriptomic-defined cell types of a previously established RGC atlas. We show a convergence of different modalities in defining the RGC identity and reveal the degree of correspondence for well-characterized cell types across multimodal data. Moreover, we complement some RGC types with detailed morphological and functional properties. We also identify differentially expressed genes among ON, OFF, and ON-OFF RGCs such as Vat1l, Slitrk6, and Lmo7, providing candidate marker genes for functional studies. Our research suggests that the molecularly distinct clusters may also differ in their roles of encoding visual information.

Bioinformation and Neutrino Communication

Communications among civilizations may include self-descriptive bioinformation because pathogen dynamics exist in their astrobiology and astrovirology, which could become pathogenic upon actual contact. This information is of mutual benefit, if reciprocated. However, in contrast, the strategic counter-scenario of self-hidden civilizations is also discussed. Civilizations, including extra-terrestrial civilizations have been divided and stratified into three levels, using a wide non-linear logarithmic scale. The levels are based on their energy expenditures: level 1 is at 4x10^19 erg/sec; level 2 is at 4x10^33 erg/sec; and level 3 is at 4x10^44 erg/sec. Terrestrial civilization is currently below the entry level I. Particularly advanced civilizations, which are above the highest level, may engineer interstellar travel and could move their planets across interstellar distances. Communication among civilizations has always been of keen interest. In terms of ability to communicate among advanced civilizations, neutrinos may be used for galactic and inter-galactic communication, in addition to or instead of using electromagnetic radiation. Thus, at this juncture, deliberation and debate are essential to proceed with development of civilization and communication.

Bioinformatics and Experimental Analysis of the Prognostic and Predictive Value of the CHPF Gene on Breast Cancer

Background

Recent studies in the United States have shown that breast cancer accounts for 30% of all new cancer diagnoses in women and has become the leading cause of cancer deaths in women worldwide. Chondroitin Polymerizing Factor (CHPF), is an enzyme involved in chondroitin sulfate (CS) elongation and a novel key molecule in the poor prognosis of many cancers. However, its role in the development and progression of breast cancer remains unclear.

Methods

The transcript expression of CHPF in the Cancer Genome Atlas-Breast Cancer (TCGA-BRCA), Gene Expression Omnibus (GEO) database was analyzed separately using the limma package of R software, and the relationship between CHPF transcriptional expression and CHPF DNA methylation was investigated in TCGA-BRCA. Kaplan-Meier curves were plotted using the Survival package to further assess the prognostic impact of CHPF DNA methylation/expression. The association between CHPF transcript expression/DNA methylation and cancer immune infiltration and immune markers was investigated using the TIMER and TISIDB databases. We also performed gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis with the clusterProfiler package. Western blotting and RT-PCR were used to verify the protein level and mRNA level of CHPF in breast tissue and cell lines, respectively. Small interfering plasmids and lentiviral plasmids were constructed for transient and stable transfection of breast cancer cell lines MCF-7 and SUM1315, respectively, followed by proliferation-related functional assays, such as CCK8, EDU, clone formation assays; migration and invasion-related functional assays, such as wound healing assay and transwell assays. We also conducted a preliminary study of the mechanism.

Results

We observed that CHPF was significantly upregulated in breast cancer tissues and correlated with poor prognosis. CHPF gene transcriptional expression and methylation are associated with immune infiltration immune markers. CHPF promotes proliferation, migration, invasion of the breast cancer cell lines MCF-7 and SUM1315, and is significantly enriched in pathways associated with the ECM-receptor interaction and PI3K-AKT pathway.

Conclusion

CHPF transcriptional expression and DNA methylation correlate with immune infiltration and immune markers. Upregulation of CHPF in breast cancer promotes malignant behavior of cancer cells and is associated with poorer survival in breast cancer, possibly through ECM-receptor interactions and the PI3K-AKT pathway.

Study on Biomarkers Related to the Treatment of Post-Stroke Depression and Alternative Medical Treatment Methods

PURPOSE

PSD is a syndrome that occurs after a stroke, which manifests as a series of depressive symptoms and corresponding physiological symptoms. Relevant studies have shown that the drug therapy is often accompanied by drug side effects and patient resistance. Acupuncture has attracted attention as a treatment method without adverse reactions of patients. The purpose of this study was to investigate the possible mechanism of action of acupuncture in PSD.

PATIENTS AND METHODS

Download depression and stroke datasets from public databases. Bioinformatics methods were used to analyze the key gene targets related to stroke and depression. Functional enrichment analysis assesses important pathways. Further screen PSD-related biological pathways and genes. After the experimental model was established, the expression differences of key genes and related pathways were compared between the model group and the control group through acupuncture treatment and qPCR verification.

RESULTS

Depression and stroke-related genes were obtained by bioinformatics methods, and then important biological processes and biological pathways related to depression and stroke were analyzed by GO and KEGG. And further screen out the disease targets closely related to PSD. In the follow-up animal experiments, we confirmed that acupuncture can intervene on these key pathways and targets, and then play a role in the targeted therapy of diseases.

CONCLUSION

The results of this study show that five genes ("NRBP1", "SIRT1", "BDNF", "MAPK3", "CREB1".) and key biological pathways such as NFkB, PI3K/AKT activation, and MAPK are the keys to the occurrence and development of PSD biomarkers, which can also be therapeutically intervened by acupuncture.

Identification of a Liver Progenitor Cell-Related Genes Signature Predicting Overall Survival for Hepatocellular Carcinoma

Background: Liver progenitor cells (LPCs) play significant roles in the development and progression of hepatocellular carcinoma (HCC). However, no studies on the value of LPC-related genes for evaluating HCC prognosis exist. We developed a gene signature of LPC-related genes for prognostication in HCC. Methods: To identify LPC-related genes, we analyzed mRNA expression arrays from a dataset (GSE57812 & GSE 37071) containing LPCs, mature hepatocytes, and embryonic stem cell samples. HCC RNA-Seq data from The Cancer Genome Atlas (TCGA) were used to explore the differentially expressed genes (DEGs) related to prognosis through DEG analysis and univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed to construct the LPC-related gene prognostic model in the TCGA training dataset. This model was validated in the TCGA testing set and an external dataset (International Cancer Genome Consortium [ICGC] dataset). Finally, we investigated the relationship between this prognostic model with tumor-node-metastasis stage, tumor grade, and vascular invasion of HCC. Results: Overall, 1770 genes were identified as LPC-related genes, of which 92 genes were identified as DEGs in HCC tissues compared with normal tissues. Furthermore, we randomly assigned patients from the TCGA dataset to the training and testing cohorts. Twenty-six DEGs correlated with overall survival (OS) in the univariate Cox regression analysis. Lasso and multivariate Cox regression analyses were performed in the TCGA training set, and a 3-gene signature was constructed to stratify patients into 2 risk groups: high-risk and low-risk. Patients in the high-risk group had significantly lower OS than those in the low-risk group. Receiver operating characteristic curve analysis confirmed the signature's predictive capacity. Moreover, the risk score was confirmed to be an independent predictor for patients with HCC. Conclusion: We demonstrated that the LPC-related gene signature can be used for prognostication in HCC. Thus, targeting LPCs may serve as a therapeutic alternative for HCC.

Identifying the hub genes and immune cell infiltration in synovial tissue between osteoarthritic and rheumatoid arthritic patients by bioinformatic approach

BACKGROUND

Osteoarthritis (OA) and rheumatoid arthritis (RA) are two common diseases that result in limb disability and a decrease in quality of life. The major symptoms of OA and RA are pain, swelling, stiffness, and malformation of joints, and each disease also has unique characteristics.

OBJECTIVE

To compare the pathological mechanisms of OA and RA via weighted correlation network analysis (WGCNA) and immune infiltration analysis and find potential diagnostic and pharmaceutical targets for the treatment of OA and RA.

METHODS

The gene expression profiles of ten OA and ten RA synovial tissue samples were downloaded from the Gene Expression Omnibus (GEO) database (GSE55235). After obtaining differentially expressed genes (DEGs) via GEO2R, WGCNA was conducted using an R package, and modules and genes that were highly correlated with OA and RA were identified. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) network analyses were also conducted. Hub genes were identified using the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape software. Immune infiltration analysis was conducted using the Perl program and CIBERSORT software.

RESULTS

Two hundred ninety-nine DEGs, 24 modules, 16 GO enrichment terms, 6 KEGG pathway enrichment terms, 10 hub genes (CXCL9, CXCL10, CXCR4, CD27, CD69, CD3D, IL7R, STAT1, RGS1, and ISG20), and 8 kinds of different infiltrating immune cells (plasma cells, CD8 T cells, activated memory CD4 T cells, T helper follicular cells, M1 macrophages, Tregs, resting mast cells, and neutrophils) were found to be involved in the different pathological mechanisms of OA and RA.

CONCLUSION

Inflammation-associated genes were the top differentially expressed hub genes between OA and RA, and their expression was downregulated in OA. Genes associated with lipid metabolism may have upregulated expression in OA. In addition, immune cells that participate in the adaptive immune response play an important role in RA. OA mainly involves immune cells that are associated with the innate immune response.

Identification of Prognostic RBPs in Osteosarcoma

Osteosarcoma often occurs in children and adolescents and causes poor prognosis. The role of RNA-binding proteins (RBPs) in malignant tumors has been elucidated in recent years. Our study aims to identify key RBPs in osteosarcoma that could be prognostic factors and treatment targets. GSE33382 dataset was downloaded from Gene Expression Omnibus (GEO) database. RBPs extraction and differential expression analysis was performed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to explore the biological function of differential expression RBPs. Moreover, we constructed Protein-protein interaction (PPI) network and obtained key modules. Key RBPs were identified by univariate Cox regression analysis and multiple stepwise Cox regression analysis combined with the clinical information from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Risk score model was generated and validated by GSE16091 dataset. A total of 38 differential expression RBPs was identified. Go and KEGG results indicated these RBPs were significantly involved in ribosome biogenesis and mRNA surveillance pathway. COX regression analysis showed DDX24, DDX21, WARS and IGF2BP2 could be prognostic factors in osteosarcoma. Spearman's correlation analysis suggested that WARS might be important in osteosarcoma immune infiltration. In conclusion, DDX24, DDX21, WARS and IGF2BP2 might play key role in osteosarcoma, which could be therapuetic targets for osteosarcoma treatment.

Association of Pericardiac Adipose Tissue With Coronary Artery Disease

BACKGROUND AND AIM

Coronary artery disease (CAD) poses a worldwide health threat. Compelling evidence shows that pericardial adipose tissue (PAT), a brown-like adipose adjacent to the external surface of the pericardium, is associated with CAD. However, the specific molecular mechanisms of PAT in CAD are elusive. This study aims to characterize human PAT and explore its association with CAD.

METHODS

We acquired samples of PAT from 31 elective cardiac surgery patients (17 CAD patients and 14 controls). The transcriptome characteristics were assessed in 5 CAD patients and 4 controls via RNA-sequencing. Cluster profile R package, String database, Cytoscape were applied to analyze the potential pathways and PPI-network key to DEGS, whereas the hubgenes were predicted via Metascape, Cytohubba, and MCODE. We use Cibersort, ENCORI, and DGIDB to predict immunoinfiltration, mRNA-miRNA target gene network, and search potential drugs targeting key DEGs. The predictable hubgenes and infiltrating inflammatory cells were validated in 22 patients (12 CAD samples and 10 control samples) through RT-qPCR and immunohistochemistry.

RESULTS

A total of 147 different genes (104 up-regulated genes and 43 down-regulated genes) were identified in CAD patients. These different genes were associated with immunity and inflammatory dysfunction. Cibersort analysis showed monocytes and macrophages were the most common subsets in immune cells, whereas immunohistochemical results revealed there were more macrophages and higher proportion of M1 subtype cells in PAT of CAD patients. The PPI network and module analysis uncovered several crucial genes, defined as candidate genes, including Jun, ATF3, CXCR4, FOSB, CCl4, which were validated through RT-qPCR. The miRNA-mRNA network implicated hsa-miR-185-5p as diagnostic targets and drug-gene network showed colchicine, fenofibrate as potential therapeutic drugs, respectively.

CONCLUSION

This study demonstrates that PAT is mainly associated with the occurrence of CAD following the dysfunction of immune and inflammatory processes. The identified hubgenes, predicted drugs and miRNAs are promising biomarkers and therapeutic targets for CAD.

UBE2C Drives Human Cervical Cancer Progression and Is Positively Modulated by mTOR

Cervical cancer is a common gynecological malignancy, accounting for 10% of all gynecological cancers. Recently, targeted therapy for cervical cancer has shown unprecedented advantages. Several studies have shown that ubiquitin conjugating enzyme E2 (UBE2C) is highly expressed in a series of tumors, and participates in the progression of these tumors. However, the possible impact of UBE2C on the progression of cervical squamous cell carcinoma (CESC) remains unclear. Here, we carried out tissue microarray analysis of paraffin-embedded tissues from 294 cervical cancer patients with FIGO/TNM cancer staging records. The results indicated that UBE2C was highly expressed in human CESC tissues and its expression was related to the clinical characteristics of CESC patients. Overexpression and knockdown of UBE2C enhanced and reduced cervical cancer cell proliferation, respectively, in vitro. Furthermore, in vivo experiments showed that UBE2C regulated the expression and activity of the mTOR/PI3K/AKT pathway. In summary, we confirmed that UBE2C is involved in the process of CESC and that UBE2C may represent a molecular target for CESC treatment.

Bioinformatics analysis of prognostic value of PITX1 gene in breast cancer

BACKGROUND

Paired-like homeodomain transcription factor 1 (PITX1) participates in miscellaneous biological processes including cell growth, development, progression and invasion in various malignant tumors. However, the analysis of the association between PITX1 expression and the survival in breast cancer remains unclear.

METHODS

Clinical prognostic parameters and survival data related to PITX1 in breast cancer patients were performed using the bioinformatic analysis including Oncomine, Bc-GenExMiner v4.3, PrognoScan and UCSC Xena.

RESULTS

We found that PITX1 gene expression was significantly higher in different histological classification of breast cancer. The Scarff-Bloom-Richardson (SBR) grade, Nottingham prognostic index (NPI), estrogen receptor (ER) negative, epidermal growth factor receptor-2 (HER2) positive, lymph node positive, triple-negative status and basal-like status were positively correlated with PITX1 level, except for patients' age and the progesterone receptor (PR) status. We have found that the increased PITX1 expression correlated with worse relapse-free survival, disease specific survival and overall survival. PITX1 was positively correlated with metastatic relapse-free survival and distant metastasis-free survival. We also confirmed positive correlation between PITX1 and the nucleotide-binding oligomerization domain 2 (NOD2).

CONCLUSION

The lower expression of PITX1 was associated with better clinical prognostic parameters and clinical survival in breast cancer according to the bioinformatic analysis.

Identification of lnc RNAs Related to Prognosis of Patients With Colorectal Cancer

The purpose of this study was to identify long noncoding RNAs (lncRNAs) related to prognosis of patients with colorectal cancer (CRC) and develop a prognostic prediction model for CRC. Transcriptome data and survival information of CRC patients were downloaded from The Cancer Genome Atlas. The differentially expressed lncRNAs (DElncRNAs) between CRC and normal colorectal tissues were identified by the edgeR package. The association of DElncRNAs expression with prognosis of CRC patients was analyzed by the survival package. A nomogram predicting 3- and 5- year overall survival of CRC patients was drawn by the rms package. A total of 1046 DElncRNAs were identified, including 271 down-regulated and 775 up-regulated lncRNAs in CRC. Multivariate Cox regression analysis showed 10 lncRNAs related to the prognosis of CRC patients. Thereinto high expression of AC004009.1, LHX1-DT, ELFN1-AS1, AL136307.1, AC087379.2, RBAKDN and AC078820.1 was associated with poorer prognosis of CRC patients. High expression of LINC01055, AL590483.1 and AC008514.1 was associated with better prognosis of CRC patients. Furthermore, the risk score model developed based on the 10 lncRNAs could effectively predict overall survival of CRC patients. In conclusion, 10 prognostic biomarkers for CRC were identified, which would be helpful to understand the role of lncRNAs in CRC progression.

High neuropilin and tolloid-like 1 expression associated with metastasis and poor survival in epithelial ovarian cancer via regulation of actin cytoskeleton

Abnormal expression of neuropilin and tolloid‐like 1 (NETO1) has been detected in some human carcinomas. However, the expression of NETO1 and the underlying mechanism in epithelial ovarian cancer (EOC) remain unknown. In this study, we found that a higher NETO1 expression in EOC tissue samples compared to normal ovarian tissue samples was significantly correlated with worse overall survival. Additionally, Cox regression analysis suggested that NETO 1 was independently associated with overall survival. NETO1 overexpression enhanced the EOC cells’ migration and invasion capability in vitro via regulation of actin cytoskeleton. Mechanistically, silencing NETO1 reduced the expression of β‐tubulin, F‐actin and KIF2A. In conclusion, our results demonstrated the critical role of NETO1 in EOC invasion, and therapies aimed at inhibiting its expression or activity might significantly control EOC growth, invasion and metastatic dissemination.

Combining Bioinformatics and Experiments to Identify CREB1 as a Key Regulator in Senescent Granulosa Cells

Aging of functional ovaries occurs many years before aging of other organs in the female body. In recent years, a greater number of women continue to postpone their pregnancies to later stages in their lives, raising concerns of the effect of ovarian aging. Mitochondria play an important role in the connection between the aging granulosa cells and oocytes. However, the underlying mechanisms of mitochondrial dysfunction in these cells remain poorly understood. Therefore, we evaluated the molecular mechanism of the aging granulosa cells, including aspects such as accumulation of mitochondrial reactive oxygen species, reduction of mtDNA, imbalance of mitochondrial dynamics, and diminished cell proliferation. Here, we applied bioinformatics approaches, and integrated publicly available resources, to investigate the role of CREB1 gene expression in reproduction. Senescence hallmark enrichment and pathway analysis suggested that the downregulation of bioenergetic-related genes in CREB1. Gene expression analyses showed alterations in genes related to energy metabolism and ROS production in ovary tissue. We also demonstrate that the biogenesis of aging granulosa cells is subject to CREB1 binding to the PRKAA1 and PRKAA2 upstream promoters. In addition, cofactors that regulate biogenesis significantly increase the levels of SIRT1 and PPARGC1A mRNA in the aging granulosa cells. These findings demonstrate that CREB1 elevates an oxidative stress-induced senescence in granulosa cells by reducing the mitochondrial function.

Identifying the optimal target genes associated with multiple myeloma by a novel bioinformatical analysis

Multiple myeloma (MM) is one of the most frequent malignant hematopoietic diseases, the pathogenesis of which remains unclear. It is well known that miRNAs are aberrantly expressed in many tumors, thus, investigating the target genes of miRNAs contributes to understanding the functional effect of miRNAs on MM. In this study, plasma samples of 147 patients with MM and 15 normal donors were collected. Using high-throughout microarray and limma package to screen the differentially expressed genes. Furthermore, to accurately predict the optimal target genes of MM, the logFC, targetScanCS and targetScanPCT values of known genes in four miRNAs (i.e. has-miR-21, has-miR-20a, has-miR-148a and has-miR-99b) were used to compute the targetScore values. As a result, 171 genes with larger difference were screened out using t-test, F-test and eBayes statistics analysis. Furthermore, 34 potential target genes associated with MM were selected by integrating the differentially expressed genes (DEGs) and the genes obtained by targetScore algorithm. Additionally, combining with the mutated genes in MM and the obtained DEGs, 41 consistently expressed genes were obtained. Finally, 5 optimal target genes, including SYK, LCP1, HIF1A, ALDH1A1 and MAFB, were screened out by the intersection of 34 DEGs and 41 mutated genes. In a word, this novel target gene prediction algorithm may contribute to improve our understanding on the pathogenesis of miRNAs in MM, which open up a new approach for future study.

Bioinformation Informs the Allostasiome: Translational Environmental Restoration (TER) for the Climate Crisis Medical Emergency

Health care is optimized when the best evidence base (BEB) is translated into policies whose effectiveness can be verified. Bioinformation disseminates BEB and is critical to translational health care. The survival of all prokaryotes and eukaryotes, including mammals, and ultimately our species, depends upon their ability to adapt to changes in their micro-environmental milieu and to the challenges of their surrounding macro-environment. Disturbances in the organism's macro-environment, such as the stressful stimuli derived from environmental changes akin to the current climate crisis, alter its physiological, cytological, biological, epigenetic and molecular microenvironment, and trigger concerted allostatic responses to regain homeostasis. Individual patient data analysis advocates the allostasiome as the specific pattern of biological events and pathways each individual organism undergoes to regain a balanced state of homeostasis following macro-environmental insults. Translational Environmental Restoration (TER) is the translation of BEB in climate change research into effective and efficacious policies for restorative renewal of our macro-environment. Patient-centered translational health care in the current climate crisis depends upon defining and characterizing the allostasiome as a complex systemic process intertwined with TER. Bioinformation is timely and critical to climate crisis research in general and to TER specifically, because it informs and disseminates the best available evidence for each subject's allostasiome. Concerted research must define and characterize BEB of the multi-dimensional medical emergency produced by the current climate crisis. Novel lines of investigation, including allostasione research, increasingly depend on bioinformation for dissemination, and are foundational for TER, one plausible solution to this complex health care crisis.

Artificial Intelligence and Virology - quo vadis

Artificial Intelligence (AI), robotics, co-robotics (cobots), quantum computers (QC), include surges of scientific endeavor to produce machines (mechanical and software) among numerous types and constructions that are accelerating progress to defeat infectious diseases. There is a plethora of additional applications and uses of these methodologies and technologies for the understanding of biomedicine through bioinformation discovery. Therefore, we briefly outline the use of such techniques in virology.

Identification and Comparison of Differentiation-Related Proteins in Hepatocellular Carcinoma Tissues by Proteomics

Histological differentiation is a major pathological criterion indicating the risk of tumor invasion and metastasis in patients with hepatocellular carcinoma. The degree of tumor differentiation is controlled by a complex interacting network of associated proteins. The principal aim of the present study is to identify the possible differentiation-related proteins which may be used for early diagnosis and more effective therapies. We compared poorly differentiated and well-differentiated hepatocellular carcinoma tissues by using 2-dimensional gel electrophoresis and matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Among the 11 identified protein spots, 6 were found to be upregulated in poorly differentiated hepatocellular carcinoma tissues and 5 were correspondingly downregulated. Immunohistochemistry was performed on 106 hepatocellular carcinoma tissues to confirm the results of the proteomic analysis. By using bioinformatic tools GO and STRING, these proteins were found to be related to catalytic activity, binding, and antioxidant activity. In particular, our data suggest that overexpression of peroxiredoxin-2, annexin A2, and heat shock protein β-1 was correlated with tumor invasion, metastasis, and poor prognosis, and therefore, these proteins may serve as potential diagnostic and therapeutic biomarkers.

The highly expressed COL4A1 genes contributes to the proliferation and migration of the invasive ductal carcinomas

BACKGROUND

Invasive ductal carcinoma is a kind of very typical breast cancer. The goal of our research was to figure out the molecular mechanism of Invasive ductal carcinoma and to find out its potential therapy targets.

RESULTS

The total amount of 478 differentially expressed genes in Invasive ductal carcinoma which compared with normal breast epithelial cells were recognized. Functional enrichment analysis proved the most part of differentially expressed genes had connection with ECM-receptor interaction. The two genes lists were contrasted in PPI network, and miRNA regulation networks, The most two crucial genes were identified in our study, which may be helpful to improve Invasive ductal carcinoma treatment. Additionally, experimental results shows that the COL4A1 gene, one of identified genes, played important roles in both of proliferation and colony formation in Invasive ductal carcinoma.

CONCLUSIONS

Invasive ductal carcinoma could have connection with ECM-receptor mutations. These 9 vital genes could be an important part in the progression of Invasive ductal carcinoma and be offered as therapy targets and prognosis indicator. and the experimental results showed that one of the most crucial genes, COL4A1, was the key gene that influence the proliferation and colony formation of the Invasive ductal carcinoma cell.

Identified key genes related to carotid atheroma plaque from gene expression chip

As one of the leading reason in morbidity and death in the world, atherosclerosis is usually associated with vessel stenosis, ulceration, and inflammatory cell infiltration. However, the formation mechanism of atheroma plaque is unknown. In this research, we have used bioinformatics tools to identify 118 differential expression genes from a GEO dataset. Besides, we also revealed KYNU as a crucial gene in atheroma plaque development.

Improving communication skill training in patient centered medical practice for enhancing rational use of laboratory tests: The core of bioinformation for leveraging stakeholder engagement in regulatory science

Requests for laboratory tests are among the most relevant additional tools used by physicians as part of patient's health problemsolving. However, the overestimation of complementary investigation may be linked to less reflective medical practice as a consequence of a poor physician-patient communication, and may impair patient-centered care. This scenario is likely to result from reduced consultation time, and a clinical model focused on the disease. We propose a new medical intervention program that specifically targets improving the patient-centered communication of laboratory tests results, the core of bioinformation in health care. Expectations are that medical students training in communication skills significantly improve physicians-patient relationship, reduce inappropriate use of laboratorial tests, and raise stakeholder engagement.