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At least 685 records · Page 38Linked to original sources
PubMed1995

Ovarian dysplasia in epithelial inclusion cysts. A morphometric approach using neural networks.

BACKGROUND: Ovarian dysplasia has been described in the ovarian surface epithelium by histologic and morphometric studies. This study evaluates ovarian dysplasia in epithelial inclusion cysts adjacent to overt carcinoma and also incidentally found in ovaries removed for nonneoplastic diseases, including oophorectomies for family history of ovarian cancer, using an artificial neural network. METHODS: Histologic sections from 37 ovaries of which 26 were diagnosed with dysplasia in epithelial inclusion cysts (10 adjacent to carcinoma and 16 incidental) and 11 with benign epithelial inclusion cysts were evaluated by tracing nuclear profiles and assessing measures of nuclear area, shape, and texture. These sections were analyzed using artificial neural networks and also statistically using the Kruskal-Wallis test with the Dunn procedure to compare the morphologic similarity of dysplasia found incidentally in inclusion cysts unrelated to carcinoma from that in inclusion cysts adjacent to carcinoma. RESULTS: Neither statistical nor artificial neural network analysis was able to distinguish between incidental and adjacent dysplasia. Both types differed significantly from the control cases. CONCLUSIONS: Neural networks are powerful classification tools when applied to multiple variables extracted from individual cases. In this study, they helped to substantiate the similarity between dysplasia found incidentally and that adjacent to ovarian carcinoma. Because dysplasia represents a potential precancerous lesion, its incidental finding may help identify patients at risk for developing ovarian carcinoma.

Female↗
PubMed1983

The role of physician networks in the diffusion of clinical applications of computers.

This study utilizes network analysis to examine the process by which physicians adopt and utilize computers in providing patient care. It also demonstrates how network techniques can be used to determine the role and position of individual physicians in their professional network and to develop educational programs designed to increase the clinical use of computers.

Communication↗
PubMed2001

Sexual networks and sexually transmitted infections: a tale of two cities.

Research on risk behaviors for sexually transmitted infections (STIs) has revealed that they seldom correspond with actual risk of infection. Core groups of people with high-risk behavior who form networks of people linked by sexual contact are essential for STI transmission, but have been overlooked in epidemiological studies. Social network analysis, a subdiscipline of sociology, provides both the methods and analytical techniques to describe and illustrate the effects of sexual networks on STI transmission. Sexual networks of people from Colorado Springs, Colorado, and from Winnipeg, Manitoba, Canada, infected with chlamydia during a 6-month period were compared. In Winnipeg, 442 networks were identified, comprising 571 cases and 663 contacts, ranging in size from 2 to 20 individuals; Colorado Springs data yielded 401 networks, comprising 468 cases and 700 contacts, ranging in size from 2 to 12 individuals. Taking differing partner notification methods and the slightly smaller population size in Colorado Springs into account, the networks from both places were similar in both size and structure. These smaller, sparsely linked networks, peripheral to the core, may form the mechanism by which chlamydia can remain endemic, in contrast with larger, more densely connected networks, closer to the core, which are associated with steep rises in incidence.

Adolescent↗
PubMed2006

Network-based predictions of retail store commercial categories and optimal locations.

I study the spatial organization of retail commercial activities. These are organized in a network comprising "antilinks," i.e., links of negative weight. From pure location data, network analysis leads to a community structure that closely follows the commercial classification of the U.S. Department of Labor. The interaction network allows one to build a "quality" index of optimal location niches for stores, which has been empirically tested.

Journal Article↗
PubMed1988

[Social networks and mental disease].

This is a three-purpose study: (a) Furthering a definition of social network analysis since such a theoretical and methodological approach is of great interest to studying social interaction, (b) Analyzing the social networks within one psychiatric case study in order to build up a network interaction model aiming at fostering future research, this interaction model being used as a concept framework, and (c) Discussing how fruitful research on social networks can prove to be in connection with the treatment of the mentally ill, as well as considering the protective and supportive functions of these networks.

Humans↗
PubMedDate not supplied

Information technologies within the cancer information service: factors related to innovation adoption.

CONCLUSIONS: This collaborative study, conducted by members of the Cancer Information Service Research Consortium Team for Evaluation and Audit Methods and the Network Analysis Advisory Board, is part of a larger project that evaluates the impact of communication structure on innovation within the contractual network of the Cancer Information Service (CIS). This study examines four different technological innovations with respect to the characteristics of relative advantage, compatibility, observability, complexity, trialability, adaptability, riskiness, disadvantage, computer knowledge, and acceptance. METHODS: Data were gathered from self-report questionnaires completed in May 1995 by organizational members (n = 82) within the National Cancer Institute's CIS, a geographically dispersed federal government health information program. RESULTS: Paired comparison t tests found that organizational members rate contrasting dimensions of an innovation differentially, depending on the nature of the specific technology. For example, significantly lower levels of riskiness were reported for computerization for communication (e.g., e-mail) than for computerization for telephone service or outreach. In addition, computerization for office management had significantly lower levels of riskiness than computerization for telephone service or outreach. With respect to complexity, computerization for communication had significantly lower ratings than did outreach. In terms of observability and trialability, computerization for communication had significantly lower ratings than for telephone service. With respect to relative advantage, computerization for office management had significantly lower ratings than all other areas of computerization. In terms of computer knowledge, ratings were significantly higher for communication than for all other areas of computerization. No significant differences were found between contrasting innovations for adaptability or acceptance. CONCLUSIONS: Results suggest that organizational members rate contrasting dimensions of an innovation differentially, depending on the nature of the specific innovation. Managers can employ this information as a diagnostic tool to evaluate the fit of an innovation, anticipate problems arising as a result of innovation, and modify innovations to reflect the changes that stakeholders deem necessary. Computerization efforts such as this one are at the cutting edge of efforts to improve the dissemination of information to the public. These efforts can result in considerable improvements in public health.

Automation↗
PubMed1990

Social networks and health: impact on returning home after entry into residential care homes.

This research extends the study of social network analysis and labeling theories into the context of residential care homes (RCHs). Findings suggest that: (1) when members of intense social networks decide to move elderly persons into RCHs, placement is truly needed and (2) although the likelihood of returning home from RCHs is affected by sociocultural characteristics, the functional and cognitive status of the resident are of primary importance.

Aged↗
PubMed2005

Generating uniformly distributed random networks.

The analysis of real networks taken from the biological, social, and physical sciences often requires a carefully posed statistical null-hypothesis approach. One common method requires comparing real networks to an ensemble of random matrices that satisfy realistic constraints in which each different matrix member is equiprobable. We discuss existing methods for generating uniformly distributed (constrained) random matrices, describe their shortcomings, and present an efficient technique that should have many practical applications.

Journal Article↗
PubMed2002

Peripheral inflammation increases the functional coherency of spinal responses to tactile but not nociceptive stimulation.

Reorganization of central networks and plasticity of neuronal representations have been implicated in recent years in the dynamic expression of somatosensory responses. The functional properties of spinal cells were shown to change in the scale of minutes after peripheral high-intensity stimulations and to undergo profound alterations in their responses in experimental models of chronic pain. These observations, however, are restricted to recordings from individual cells, and no information exists on how these changes may be reflected on the activity of somatosensory neuronal networks involved in pain processing. To understand how spinal cord networks may be altered after the onset of hyperalgesia, we extracellularly recorded from groups of five to nine neighboring neurons in the hindlimb representation area of the dorsal horn. The multineuronal activity evoked by cutaneous innocuous and noxious stimulation was compared before and for 3 h after the subcutaneous injection of diluted formalin. Formalin caused immediate changes in response properties and mechanical threshold of activation for the majority of the neurons and induced the incorporation of previously unresponsive neighboring neurons to the functional network. Analysis of the temporal correlation within the neuronal population revealed that formalin-induced inflammation increased the functional coherence of the network to the nonnociceptive stimulation but not to the painful stimuli. This increase in the tactile acuity of populations of nociceptive neurons may be a basis for the emergence of touch-evoked pain.

Animals↗
PubMed2000

Metabolic flux distributions in Corynebacterium glutamicum during growth and lysine overproduction. Reprinted from Biotechnology and Bioengineering, Vol. 41, Pp 633-646 (1993).

The two main contributions of this article are the solidification of Corynebacterium glutamicum biochemistry guided by bioreaction network analysis, and the determination of basal metabolic flux distributions during growth and lysine synthesis. Employed methodology makes use of stoichiometrically based mass balances to determine flux distributions in the C. glutamicum metabolic network. Presented are a brief description of the methodology, a thorough literature review of glutamic acid bacteria biochemistry, and specific results obtained through a combination of fermentation studies and analysis-directed intracellular assays. The latter include the findings of the lack of activity of glyoxylate shunt, and that phosphoenolpyruvate carboxylase (PPC) is the only anaplerotic reaction expressed in C. glutamicum cultivated on glucose minimal media. Network simplifications afforded by the above findings facilitated the determination of metabolic flux distributions under a variety of culture conditions and led to the following conclusions. Both the pentose phosphate pathway and PPC support significant fluxes during growth and lysine overproduction, and that flux partitioning at the glucosa-6-phosphate branch point does not appear to limit lysine synthesis.

Corynebacterium↗
PubMed2026

Lymphangiogenesis-related gene signature-based risk model for prognostic assessment of cervical cancer: immune-metabolic characterization and molecular subtype analysis.

BACKGROUND: Lymphangiogenesis promotes tumor dissemination and may shape the immune contexture of cervical cancer, yet lymphangiogenesis-related prognostic stratification and its immunometabolic implications remain insufficiently defined in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). METHODS: TCGA-CESC transcriptomes and clinical data were obtained from UCSC Xena and integrated with normal cervix tissues from the Genotype-Tissue Expression Project after batch correction. Prognostic LYMRGs were first identified from the differentially expressed set using univariable Cox proportional hazards analysis. Candidate genes were then reduced using an L1-regularized Cox model (Least Absolute Shrinkage and Selection Operator), and the remaining markers were entered into a multivariable Cox regression to obtain the final coefficients and compute an individualized risk score. The model's prognostic value was further assessed in an independent Gene Expression Omnibus dataset. In addition, expression patterns of the signature genes were leveraged for molecular subtyping of TCGA samples via non-negative matrix factorization (NMF). Immune infiltration and immunotherapy-associated characteristics were interrogated through a multi-algorithm strategy (single-sample gene set enrichment analysis, CIBERSORT, ESTIMATE, Tumor Immune Dysfunction and Exclusion (TIDE), and Immunophenoscore . Additional analyses included pathway enrichment (GSEA/GO/KEGG), drug sensitivity prediction (pRRophetic/CellMiner), and ceRNA network analysis. RESULTS: A six-gene LYMRG signature robustly stratified survival. High-risk patients had significantly worse overall survival in The Cancer Genome Atlas with AUCs of 0.819/0.801/0.801 at 1/3/5 years, and in GSE52903 (P = 0.001) with AUCs of 0.733/0.719/0.725. NMF identified two subtypes with distinct prognosis (P = 0.01) and divergent immune landscapes. Risk groups and subtypes exhibited consistent differences in immune infiltration, checkpoint expression, TIDE/IPS patterns, and pathway enrichment. Predicted chemosensitivity differed by risk group, and the ceRNA network suggested candidate upstream lncRNA regulators of the signature. CONCLUSION: A lymphangiogenesis-related six-gene model enables clinically meaningful prognostic stratification of CESC and links lymphangiogenesis programs to distinct tumor immune phenotypes and therapeutic vulnerabilities.

cancer↗
PubMed2006

Proteome analysis of Halobacterium sp. NRC-1 facilitated by the biomodule analysis tool BMSorter.

To better understand the extremely halophilic archaeon Halobacterium species NRC-1, we analyzed its soluble proteome by two-dimensional liquid chromatography coupled to electrospray ionization tandem mass spectrometry. A total of 888 unique proteins were identified with a ProteinProphet probability (P) between 0.9 and 1.0. To evaluate the biochemical activities of the organism, the proteomic data were subjected to a biological network analysis using our BMSorter software. This allowed us to examine the proteins expressed in different biomodules and study the interactions between pertinent biomodules. Interestingly an integrated analysis of the enzymes in the amino acid metabolism and citrate cycle networks suggested that up to eight amino acids may be converted to oxaloacetate, fumarate, or oxoglutarate in the citrate cycle for energy production. In addition, glutamate and aspartate may be interconverted from other amino acids or synthesized from citrate cycle intermediates to meet the high demand for the acidic amino acids that are required to build the highly acidic proteome of the organism. Thus this study demonstrated that proteome analysis can provide useful information and help systems analyses of organisms.

Amino Acids↗
PubMed2026

Dissecting genetic architecture and improving machine learning‑based genomic prediction of flowering time in Osmanthus fragrans by integrating structural variants.

Sweet osmanthus (Osmanthus fragrans), a traditional ornamental plant in China, exhibits substantial variation in autumn flowering time, which significantly affects landscape application and cultivation efficiency. Here, we performed a genome-wide association study on 127 resequenced accessions classified into early, intermediate, and late flowering types, using a set of 2,325,410 single-nucleotide polymorphisms (SNPs) and 246,824 structural variants (SVs). By integrating SNP/insertion and deletion (Indel) and SV data with weighted gene co-expression network analysis, machine learning, and genomic prediction, we dissected the genetic architecture of flowering time. We identified 24 associated SNP/Indels and six SVs, mapping to 30 candidate genes, including known flowering regulators FLK, LOS1, Y14, MIF2, and GID1B. These genes showed tissue-specific expression, with some responding to low temperature. The two hub genes, GUX1 and LYG027904, were located within modules of the co-expression network associated with low-temperature treatment. Haplotype analysis revealed a specific three-SNP haplotype associated with late flowering and linked to LOS1, and epistatic interactions among combined genotypes contributed to phenotypic variation. Notably, integrating SVs with SNP/Indels improved genomic prediction accuracy; the gradient boosting decision tree model outperformed other machine learning algorithms, achieving a mean accuracy of 0.859 and an AUC > 0.8 (where AUC is area under receiver operating characteristic curve) for all flowering types. These findings provide insights into the genetic mechanisms underlying flowering time variation in O. fragrans, offer candidate genes and haplotypes for molecular breeding, and highlight the value of integrating SVs with machine learning for genomic prediction in woody ornamentals.

Machine Learning↗
PubMed2025

Circulating microRNA panels for multi-cancer detection and gastric cancer screening: leveraging a network biology approach.

BACKGROUND: Screening tests, particularly liquid biopsy with circulating miRNAs, hold significant potential for non-invasive cancer detection before symptoms manifest. METHODS: This study aimed to identify biomarkers with high sensitivity and specificity for multiple and specific cancer screening. 972 Serum miRNA profiles were compared across thirteen cancer types and healthy individuals using weighted miRNA co-expression network analysis. To prioritize miRNAs, module membership measure and miRNA trait significance were employed. Subsequently, for specific cancer screening, gastric cancer was focused on, using a similar strategy and a further step of preservation analysis. Machine learning techniques were then applied to evaluate two distinct miRNA panels: one for multi-cancer screening and another for gastric cancer classification. RESULTS: The first panel (hsa-miR-8073, hsa-miR-614, hsa-miR-548ah-5p, hsa-miR-1258) achieved 96.1% accuracy, 96% specificity, and 98.6% sensitivity in multi-cancer screening. The second panel (hsa-miR-1228-5p, hsa-miR-1343-3p, hsa-miR-6765-5p, hsa-miR-6787-5p) showed promise in detecting gastric cancer with 87% accuracy, 90% specificity, and 89% sensitivity. CONCLUSIONS: Both panels exhibit potential for patient classification in diagnostic and prognostic applications, highlighting the significance of liquid biopsy in advancing cancer screening methodologies.

Neoplasms↗
PubMed2006

Design, construction and performance of the most efficient biomass producing E. coli bacterium.

Inverse metabolic engineering based on elementary mode analysis was applied to maximize the biomass yield of Escherchia coli MG1655. Elementary mode analysis was previously employed to identify among 1691 possible pathways for cell growth the most efficient pathway with maximum biomass yield. The metabolic network analysis predicted that deletion of only 6 genes reduces the number of possible elementary modes to the most efficient pathway. We have constructed a strain containing these gene deletions and we evaluated its properties in batch and in chemostat growth experiments. The results show that the theoretical predictions are closely matched by the properties of the designed strain.

Biomass↗
PubMed1999

FLR1 gene (ORF YBR008c) is required for benomyl and methotrexate resistance in Saccharomyces cerevisiae and its benomyl-induced expression is dependent on pdr3 transcriptional regulator.

In this work we report the disruption of a Saccharomyces cerevisiae ORF YBR008c (FLR1 gene) within the context of EUROFAN (EUROpean Functional Analysis Network) six-pack programme, using a PCR-mediated gene replacement protocol as well as the results of the basic phenotypic analysis of a deletant strain and the construction of a disruption cassette for inactivation of this gene in any yeast strain. We also show results extending the knowledge of the range of compounds to which FLR1 gene confers resistance to the antimitotic systemic benzimidazole fungicide benomyl and the antitumor agent methotrexate, reinforcing the concept that the FLR1 gene is a multidrug resistance (MDR) determinant. Our conclusions were based on the higher susceptibility to these compounds of flr1Delta compared with wild-type and on the increased resistance of both flr1Delta and wild-type strains upon increased expression of FLR1 gene from a centromeric plasmid clone. The present study also provides, for the first time, evidence that the adaptation of yeast cells to growth in the presence of benomyl involves the dramatic activation of FLR1 gene expression during benomyl-induced latency (up to 400-fold). Results obtained using a FLR1-lacZ fusion in a plasmid indicate that the activation of FLR1 expression in benomyl-stressed cells is under the control of the transcriptional regulator Pdr3p. Indeed, PDR3 deletion severely reduces benomyl-induced activation of FLR1 gene expression (by 85%), while the homologous Pdr1p transcription factor is apparently not involved in this activation.

4-Nitroquinoline-1-oxide↗
PubMed2026

Identification of NLRP3 and TIPE2 as asthma biomarkers via integrative bioinformatics and Mendelian randomization.

Asthma is a chronic inflammatory airway disease imposing a substantial global health burden. NLRP3 is an immune sensor involved in infection and cellular stress responses. Recent studies suggest that NLRP3 may be involved in the pathogenesis of asthma. We hypothesized that genetic variation in NLRP3 may contribute to asthma susceptibility. However, the causal relationship between NLRP3 and asthma still remains unclear. In this study, bioinformatics analysis using asthma data and R software was performed to identify NLRP3-related genes. We performed weighted gene co-expression network analysis to identify co-expressed genes, resulting in 12 candidate genes. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses were used to identify the functions of these candidate genes, revealing their involvement in cellular metabolism. Mendelian randomization analysis of the 12 candidate genes identified 2 biomarkers: NLRP3 and TNFAIP8L2 (TIPE2). We validated their diagnostic value for asthma using the GSE182503 dataset, with area under the curve values of 0.83 and 0.66 for NLRP3 and TIPE2, respectively. This project discusses how NLRP3 promotes asthma pathogenesis, whereas TIPE2 may alleviate it, and explores the potential interplay between them. NLRP3 and TIPE2 may serve as diagnostic biomarkers for asthma: NLRP3 may promote, whereas TIPE2 may alleviate asthma development. Both genes represent potential diagnostic biomarkers and therapeutic targets that warrant further functional investigation.

Asthma↗
PubMed2025

Integrated 16 S rRNA and transcriptome analysis reveal molecular and microbial mechanisms of cold-tolerant germination in hulless barley.

BACKGROUND: Elucidating the mechanisms underlying cold-tolerant germination is crucial for enhancing crop resilience to low temperatures. Hulless barley (Hordeum vulgare var. coeleste L.), with remarkable natural cold adaptation, serves as an ideal model to study cold stress tolerance mechanisms in gramineous crops. In this study, cold-tolerant variety 37 and cold-sensitive variety 44 were screened and used to investigate the molecular mechanisms of cold-tolerant germination, via seed germination assays, combined with phytohormone determination, transcriptome sequencing and 16 S rRNA amplicon sequencing. RESULTS: Low temperature significantly inhibited hulless barley seed germination: the germination rate of cold-sensitive variety 44 decreased by 69%, while that of cold-tolerant variety 37 only decreased by 2%. Transcriptome analysis identified 2,647 and 2,392 differentially expressed genes (DEGs) in variety 37 and 44, respectively. Weighted gene co-expression network analysis (WGCNA) revealed a green module significantly positively correlated with gibberellic acid (GA) content, containing 10 core genes such as late embryogenesis abundant protein (LEA) and Homeobox genes. 16 S rRNA sequencing showed that the cold-tolerant variety 37 had enriched abundances of dominant endophytes including Sphingomonas and Pelomonas, with correlation coefficients of 0.70 and 0.87 with GA content, respectively. Additionally, exogenous GA treatment significantly increased germination rates under cold stress by 176.67% in cold-sensitive variety 44. CONCLUSIONS: This study confirms that the enhanced cold tolerance of hulless barley during seed germination originates from the synergistic interaction between beneficial endophytes (Sphingomonas, Pelomonas), GA, and core genes (e.g., LEA, Homeobox). Exogenous GA application can significantly restore the germination ability of cold-sensitive varieties. These findings provide a critical theoretical basis for improving cold tolerance in hulless barley germplasm.

Hordeum↗