Association of Oral Microbiome Diversity and All-Cause Mortality in the General US Population and in Individuals With Chronic Diseases: A Prospective Cohort Study.

AIM: To investigate whether oral microbiome diversity is associated with all-cause mortality in the general US population and in individuals with chronic diseases. MATERIALS AND METHODS: We included 8224 individuals with oral microbiome diversity data from the National Health and Nutrition Examination Survey (2009-2012), representing 164,000,205 US adults, using a survey-weighted analysis method. Cox regression analyses were performed to identify the association between oral microbiome diversity and all-cause mortality. RESULTS: During a survey-weighted mean follow-up period of 8.86 years, 429 all-cause deaths (survey-weighted number: 7,124,920) occurred in 8224 participants. Cox regression analysis revealed that higher oral microbiome diversity was significantly associated with a lower all-cause mortality risk. Significant differences in all-cause mortality risk were observed among the different clusters based on oral microbiome ß-diversity (log-rank p < 0.001). Subgroup analyses revealed that the oral microbiome diversity was independently associated with all-cause mortality in individuals with diabetes mellitus and hypertension. A multivariate logistic regression model showed that current smoking and antibiotic use were significantly associated with lower oral microbiome α diversity. CONCLUSIONS: Higher oral microbiome diversity was significantly associated with a lower all-cause mortality risk in the general US population and in individuals with diabetes mellitus and hypertension.

BRCA1-mediated inflammation and growth activated & inhibited transition mechanisms between no-tumor hepatitis/cirrhotic tissues and HCC.

To understand breast cancer 1 early onset (BRCA1)-mediated inflammation and growth activated and inhibited transition mechanisms between no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) and human hepatocellular carcinoma (HCC), BRCA1-activated different complete (all no positive correlation, Pearson correlation coefficient <0.25) and uncomplete (partly no positive correlation except BRCA1, Pearson <0.25) networks were identified in higher HCC compared with lower no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) from the corresponding BRCA1-stimulated (Pearson ≥0.25) or inhibited (Pearson ≤-0.25) overlapping molecules of Pearson and GRNInfer, respectively. This result was verified by the corresponding scatter matrix. As visualized by GO, KEGG, GenMAPP, BioCarta, and disease database integration, we proposed mainly that BRCA1-stimulated different complete network was involved in BRCA1 activation with integral to membrane killer cell lectin-like receptor C to nucleus interferon regulatory factor 5-induced inflammation, whereas the corresponding inhibited network participated in BRCA1 repression with matrix roundabout axon guidance receptor homolog 1 to plasma membrane versican-induced growth in lower no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection). However, BRCA1-stimulated network contained BRCA1 activation with endothelium-specific to lysosomal transmembrane and carbamoyl synthetase to tastin, histone cluster and cyclin-induced growth, whereas the corresponding inhibited different complete network included BRCA1 repression with ovalbumin, thyroid stimulating hormone beta and Hu antigen C to cytochrome P450 to transducin-induced inflammation in higher HCC. Our BRCA1 different networks were verified by BRCA1-activated or -inhibited complete and uncomplete networks within and between no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) or (and) HCC.

High EGFR_1 Inside-Out Activated Inflammation-Induced Motility through SLC2A1-CCNB2-HMMR-KIF11-NUSAP1-PRC1-UBE2C.

48 different Pearson mutual-positive-correlation epidermal growth factor receptor (EGFR_1)-activatory molecular feedback, up- and down-stream network was constructed from 171 overlapping of 366 GRNInfer and 223 Pearson under EGFR_1 CC ≥0.25 in high lung adenocarcinoma compared with low human normal adjacent tissues. Our identified EGFR_1 inside-out upstream activated molecular network showed SLC2A1 (solute carrier family 2 (facilitated glucose transporter) member 1), CCNB2 (cyclin B2), HMMR (hyaluronan-mediated motility receptor (RHAMM)), KIF11 (kinesin family member 11), NUSAP1 (nucleolar and spindle associated protein 1), PRC1 (protein regulator of cytokinesis 1), UBE2C (ubiquitin-conjugating enzyme E2C) in high lung adenocarcinoma. EGFR_1 inside-out upstream activated terms network includes intracellular, membrane fraction, cytoplasm, plasma membrane, integral to membrane, basolateral plasma membrane, transmembrane transport, nucleus, cytosol, cell surface; T cell homeostasis, inflammation; microtubule cytoskeleton, embryonic development (sensu Mammalia), cell cycle, mitosis, thymus development, cell division, regulation of cell cycle, Contributed--cellular process--Hs cell cycle KEGG, cytokinesis, M phase, M phase of mitotic cell cycle, estrogen-responsive protein Efp controls cell cycle and breast tumors growth, cell motility, locomotion, locomotory behavior, neoplasm metastasis, spindle pole, spindle microtubule, microtubule motor activity, microtubule-based movement, mitotic spindle organization and biogenesis, mitotic centrosome separation, spindle pole body organization and biogenesis, microtubule-based process, microtubule, cytokinesis after mitosis, mitotic chromosome condensation, establishment of mitotic spindle localization, positive regulation of mitosis, mitotic spindle elongation, spindle organization and biogenesis, positive regulation of exit from mitosis, regulation of cell proliferation, positive regulation of cell proliferation based on integrative GO, KEGG, GenMAPP, BioCarta and disease databases in high lung adenocarcinoma. Therefore, we propose high EGFR_1 inside-out activated inflammation-induced motility through SLC2A1-CCNB2-HMMR-KIF11-NUSAP1-PRC1-UBE2C in lung adenocarcinoma.

Adenosylmethionine decarboxylase 1 (AMD1)-mediated mRNA processing and cell adhesion activated & inhibited transition mechanisms by different comparisons between chimpanzee and human left hemisphere.

To understand adenosylmethionine decarboxylase 1 (AMD1)-mediated mRNA processing and cell adhesion activated & inhibited transition mechanisms between chimpanzee and human left hemisphere, AMD1-activated different complete (all no positive correlation, Pearson correlation coefficient < 0.25) and uncomplete (partly no positive correlation except AMD1, Pearson < 0.25) networks were identified in higher human compared with lower chimpanzee left hemisphere from the corresponding AMD1-stimulated (Pearson ≥ 0.25) or inhibited (Pearson ≤ -0.25) overlapping molecules of Pearson and GRNInfer, respectively. This result was verified by the corresponding scatter matrix. As visualized by GO, KEGG, GenMAPP, BioCarta, and disease database integration, we proposed mainly that AMD1-stimulated different complete network was involved in AMD1 activation with cytoplasm ubiquitin specific peptidase (tRNA-guanine transglycosylase) to nucleus paired box-induced mRNA processing, whereas the corresponding inhibited network participated in AMD1 repression with cytoplasm protocadherin gamma and adaptor-related protein complex 3-induced cell adhesion in lower chimpanzee left hemisphere. However, AMD1-stimulated network contained AMD1 activation with plakophilin and phosphodiesterase to SH3 binding glutamic acid-rich protein to dynein and zinc finger-induced cell adhesion, whereas the corresponding inhibited different complete network included AMD1 repression with mitochondrial denine nucleotide translocator, brain protein, and ADH dehydrogenase to ribonucleoprotein-induced mRNA processing in higher human left hemisphere. Our AMD1 different networks were verified by AMD1-activated or -inhibited complete and uncomplete networks within and between chimpanzee left hemisphere or (and) human left hemisphere.

Activated amelogenin Y-linked (AMELY) regulation and angiogenesis in human hepatocellular carcinoma by biocomputation.

In the present study, a comparison of the biological processes and gene ontology (GO) in human hepatocellular carcinoma (HCC) with high expression (fold change ≥2) of amelogenin Y-linked (AMELY)-activated upstream regulation networks with non-tumor hepatitis/cirrhotic tissues (HBV or HCV infection) with low expression of activated networks was performed. The principle biological processes involved in non-tumor hepatitis/cirrhotic tissues include positive regulation of mismatch repair, regulation of transcription from RNA polymerase II promoters, negative regulation of cell-cell adhesion, protein ubiquitinatin and protein catabolism. The main biological processes involved in the development of HCC include positive regulation of calcium ion transport into the cytosol, cell proliferation, DNA replication, fibroblast proliferation, immune response, microtubule polymerization and protein secretion. Specific transcription from RNA polymerase II promoters, regulation of angiogenesis, cell growth, protein metabolism, Wnt receptor signaling pathways, negative regulation of endothelial cell differentiation, microtubule depolymerization, peptidase activity and progression through the cell cycle are also involved. Positive regulation of transcription is involved in both processes. An activated AMELY-coupled upstream positive regulation of immune response-mediated protein secretion to Wnt signaling and calcium into cytosol-induced regulation of cell growth and angiogenesis in HCC is proposed. The AMELY upstream regulation molecular network model was constructed with BUB1B, CST6, ESM1, HOXA5, LEF1, MAPT, MYBL2, NOTCH3, PLA2G1B, PROK1, ROBO1, SCML2 and UBE2C in HCC from a Gene Expression Omnibus (GEO) dataset by gene regulation network inference methods and our programming methods.

Cartilage oligomeric matrix protein (COMP)-mediated cell differentiation to proteolysis mechanism networks from human normal adjacent tissues to lung adenocarcinoma.

BACKGROUND: To understand cartilage oligomeric matrix protein (COMP) mechanism network from human normal adjacent tissues to lung adenocarcinoma. METHODS: COMP complete different activated (all no positive correlation, Pearson CC < 0.25) and uncomplete (partly no positive correlation except COMP, Pearson CC < 0.25) network were identified in higher lung adenocarcinoma compared with lower human normal adjacent tissues from the corresponding COMP-stimulated (≥0.25) or inhibited (Pearson CC ≤ -0.25) overlapping molecules of Pearson correlation coefficient (CC) and GRNInfer, respectively. COMP complete different activated and inhibited (all no positive correlation, Pearson CC < 0.25) mechanisms networks of higher lung adenocarcinoma and lower human normal adjacent tissues were constructed by integration of Pearson CC, GRNInfer and GO. As visualized by integration of GO, KEGG, GenMAPP, BioCarta and Disease, we deduced COMP complete different activated and inhibited network in higher lung adenocarcinoma and lower human normal adjacent tissues. RESULTS: As visualized by GO, KEGG, GenMAPP, BioCarta and disease database integration, we proposed mainly that the mechanism and function of COMP complete different activated network in higher lung adenocarcinoma was involved in COMP activation with matrix-localized insulin-like factor coupling carboxypeptidase to metallopeptidase-induced proteolysis, whereas the corresponding inhibited network in lower human normal adjacent tissues participated in COMP inhibition with nucleus-localized vasculogenesis, B and T cell differentiation and neural endocrine factors coupling pyrophosphatase-mediated proteolysis. However, COMP complete different inhibited network in higher lung adenocarcinoma included COMP inhibition with nucleus-localized chromatin maintenance, licensing and assembly factors coupling phosphatase-inhibitor to cytokinesis regulators-mediated cell differentiation, whereas the corresponding activated network in lower human normal adjacent tissues contained COMP activation with cytolplasm-localized translation elongation factor coupling fucosyltransferase to ubiquitin-protein ligase-induced cell differentiation. CONCLUSION: COMP different networks were verified not only by complete and uncomplete COMP activated or inhibited networks within human normal adjacent tissues or lung adenocarcinoma, but also by COMP activated and inhibited network between human normal adjacent tissues and lung adenocarcinoma.