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At least 127 records · Page 7Linked to original sources

PubMed2026

Crosstalk mediators implicated in the Stevens-Johnson Syndrome through gene regulatory network analysis.

Stevens-Johnson syndrome (SJS) is a rare and severe mucocutaneous disorder often triggered by medications or infections. Our previous research identified that four key genes, Ikzf1, Ptger3, Mavs, and Tlr3 are involved in SJS susceptibility and the conjunctival epithelial innate immune response, demonstrating their role in regulating interferon-stimulated genes. However, the interplay among these regulatory factors remains unclear. This study aimed to elucidate the crosstalk mechanisms between the pathways regulated by these four genes in conjunctival epithelial cells. We constructed a comprehensive gene regulatory network using transcriptomic data from murine conjunctival epithelial cells under 16 distinct conditions, including polyI:C stimulation across wild-type, knockout, and transgenic backgrounds for the key genes. A targeted network analysis systematically identified numerous candidate genes mediating the crosstalk between the regulatory pathways initiated by Ikzf1, Ptger3, Mavs, and Tlr3. The identified candidates suggest the involvement of diverse signaling pathways previously unlinked to SJS pathology. Our findings suggest that the pathogenesis of SJS may arise not from the dysfunction of isolated genes but from the disruption of a balance maintained by intricate pathway crosstalk.

Animals↗

PubMed2026

Functional and Nutritional Potential of Chickpea Protein Hydrolysates: A Systematic Review and Plant-protein Network Analysis.

Chickpea is a protein-rich legume increasingly explored as a substrate for functional plant-based ingredients. Chickpea protein hydrolysates (CPHs) and chickpea-derived peptides (CPs), obtained through enzymatic hydrolysis or simulated gastrointestinal digestion, may provide technological and biological properties while supporting the valorization of chickpea fractions and by-products. This review integrates a network analysis of title-abstract terms from 5,728 unique Scopus and PubMed records on plant protein hydrolysates with a systematic review of 72 studies focused on CPH production, peptide characterization, bioactivity, and translational gaps. The evidence indicates that CPHs and CPs show promising antioxidant, antihypertensive, antidiabetic, anti-inflammatory, lipid-lowering, immunomodulatory, antimicrobial, and anticancer-related activities, mainly supported by biochemical assays, cell models, and animal studies. However, heterogeneous hydrolysis protocols, incomplete peptide characterization, inconsistent bioactivity methods, limited scale-up evidence, and the absence of human intervention trials restrict translation. Future studies should prioritize standardized protocols, mechanistic validation, bioavailability, sensory and regulatory assessment, food-matrix validation, and clinical trials.

Cicer↗

PubMed1995

Neural network analysis of quantitative histological factors to predict pathological stage in clinical stage I nonseminomatous testicular cancer.

A great deal of controversy exists in staging clinical stage I (CSI) nonseminomatous testicular germ cell tumors (NSGCT) because of the difficulty of distinguishing true stage I patients from those with occult retroperitoneal or distant metastases. The goal of this study was to quantitate primary tumor histologic factors and to apply these in a neural network computer analysis to determine if more accurate staging could be achieved. All available primary tumor histological slides from 93 CSI NSGCT patients were analyzed for vascular invasion (VI), lymphatic invasion (LI), tunical invasion (TI) and quantitative determination of percentage of the primary tumor composed of embryonal carcinoma (%EMB), yolk sac carcinoma (%YS), teratoma (%TER) and seminoma (%SEM). These patients had undergone retroperitoneal lymphadenectomy or follow-up such that final stage included 55 pathologic stage I and 38 stage II or higher lesions. Two investigators were provided identical datasets for neural network analysis; one experienced researcher used custom Kohonen and back propagation programs and one less experienced researcher used a commercially available program. For each experiment, a subset of data was used for training, and subsets were blindly used to test the accuracy of the networks. In the custom back propagation network, 86 of 93 patients were correctly staged for an overall accuracy of 92% (sensitivity 88%, specificity 96%). Using Neural Ware commercial software 74 of 93 (79.6%) were accurately staged when all 7 input variables were used; however, accuracy improved from 84.9 to 87.1% when 2, 4 and 5 of the variables were used. Quantitative histologic assessment of the primary tumor and neural network processing of data may provide clinically useful information in the CSI NSGCT population; however, the expertise of the network researcher appears to be important, and commercial software in general use may not be superior to standard regression analysis. Prospective testing of expert methodology should be instituted to confirm its utility.

Germinoma↗

PubMed2003

Social-network analysis of Mycobacterium bovis transmission among captive brushtail possums (Trichosurus vulpecula).

Wild brushtail possums (Trichosurus vulpecula) are the main source of Mycobacterium bovis infection for New Zealand livestock. The disease is spread principally by infectious aerosol; therefore, social interactions determine disease transmission. In captive possums, den-sharing behaviour provided the greatest risk of tuberculosis transmission between animals. Den sharing between individual possums was used as the basic measurement for quantifying close proximity between animals over extended periods. Social-network analysis (SNA) was used to model patterns of social behaviour and to predict tuberculosis transmission. There was great diversity between groups in their social behaviour-but there were consistent trends in the SNA measures (closeness and flow-betweenness). With time, the social distance between possums in the same group increased, the social network became more homogeneous and the possums less differentiated from each other. Alteration of the physical environment of the pens (such as changing the number of dens or relocating the group to a new pen) had an inconsistent effect on social structure when comparing different groups. During the infection-transmission study, the possums that became infected had greater closeness and flow-betweenness scores than those that remained free of infection. Although standard statistical descriptive measures (such as the number of partners and the frequency of den-sharing events) were greater for the infected than the infection-free possums, the SNA-specific measures were more precise and could be compared across time and between groups.

Animal Husbandry↗

PubMed1998

A hybrid neural network analysis of subtle brain volume differences in children surviving brain tumors.

In the treatment of children with brain tumors, balancing the efficacy of treatment against commonly observed side effects is difficult because of a lack of quantitative measures of brain damage that can be correlated with the intensity of treatment. We quantitatively assessed volumes of brain parenchyma on magnetic resonance (MR) images using a hybrid combination of the Kohonen self-organizing map for segmentation and a multilayer backpropagation neural network for tissue classification. Initially, we analyzed the relationship between volumetric differences and radiologists' grading of atrophy in 80 subjects. This investigation revealed that brain parenchyma and white matter volumes significantly decreased as atrophy increased, whereas gray matter volumes had no relationship with atrophy. Next, we compared 37 medulloblastoma patients treated with surgery, irradiation, and chemotherapy to 19 patients treated with surgery and irradiation alone. This study demonstrated that, in these patients, chemotherapy had no significant effect on brain parenchyma, white matter, or gray matter volumes. We then investigated volumetric differences due to cranial irradiation in 15 medulloblastoma patients treated with surgery and radiation therapy, and compared these with a group of 15 age-matched patients with low-grade astrocytoma treated with surgery alone. With a minimum follow-up of one year after irradiation, all radiation-treated patients demonstrated significantly reduced white matter volumes, whereas gray matter volumes were relatively unchanged compared with those of age-matched patients treated with surgery alone. These results indicate that reductions in cerebral white matter: 1) are correlated significantly with atrophy; 2) are not related to chemotherapy; and 3) are correlated significantly with irradiation. This hybrid neural network analysis of subtle brain volume differences with magnetic resonance may constitute a direct measure of treatment-induced brain damage.

Adolescent↗

PubMed2026

Genetic dissection of cardiac iron regulation using transcriptome network analysis and systems genetics in BXD mice.

Cardiac iron homeostasis is essential for myocardial energy metabolism and contractile function, yet the genetic and molecular mechanisms governing iron levels within the heart remain poorly understood. We used a systems genetics approach to dissect the transcriptional regulation of cardiac iron homeostasis. Myocardial iron level varies substantially across BXD strains (40-112 μg/g) and is under heritable genetic control (H2 = 0.38). Elevated cardiac iron is associated with reduced ventricular mass, increased ventricular ectopy, and prolonged atrioventricular conduction in the BXD population. Weighted gene co-expression network analysis of the BXD heart transcriptome identified a co-expression module that was significantly and negatively correlated with cardiac iron levels in both young and old BXD mice and enriched for pathways related to metabolic regulation, cyclic AMP (cAMP) signaling, circadian entrainment, and cardiovascular physiology. The module showed substantial overlap with a curated cardiac iron gene set, and cross-species enrichment analysis confirmed its conservation in human cardiomyopathy differentially expressed genes (enrichment ratio = 1.49; false discovery rate [FDR] = 0.0342). Quantitative trait locus (QTL) mapping of the first principal component of the overlapping module iron genes (n = 38), corroborated by individual gene mapping, identified trans-eQTL hotspots on multiple chromosomes, implicating Fcho2, Gcc2, and Rmdn1 as candidate upstream regulators operating through sequential steps of intracellular iron trafficking. Together, these findings establish a systems-level map of cardiac iron gene regulation, identify candidate genetic regulators, and provide a molecular framework linking disruption of iron-related transcriptional networks to structural and electrical cardiac dysfunction with implications for iron-related heart diseases.

BXD mouse population↗

PubMed2003

A social network analysis of communication about hereditary nonpolyposis colorectal cancer genetic testing and family functioning.

Hereditary cancers are relational diseases. A primary focus of research in the past has been the biological relations that exist within the families and how genes are passed along family lines. However, hereditary cancers are relational in a psychosocial sense, as well. They can impact communication relationships within a family, as well as support relationships among family members. Furthermore, the familial culture can affect an individual's participation in genetic counseling and testing endeavors. Our aims are (a) to describe the composition of familial networks, (b) to characterize the patterns of family functioning within families, (c) to analyze how these patterns relate to communications about genetic counseling and testing among family members, and (d) to identify influential family members. Specifically, we asked how the relationship between mutation status, kinship ties, and family functioning constructs, e.g., communication, cohesion, affective involvement, leadership, and conflict, was associated with discussions about genetic counseling and testing. We used social network analysis and random graph techniques to examine 783 dyadic relationships in 36 members of 5 hereditary nonpolyposis colorectal cancer (HNPCC) families interviewed from 1999-2000. Results suggest that in these five HNPCC families, two family members are more likely to discuss genetic counseling and testing if either one carries the mutation, if either one is a spouse or a first-degree relative of the other, or if the relationship is defined by positive cohesion, leadership, or lack of conflict. Furthermore, the family functioning patterns suggest that mothers tend to be the most influential persons in the family network. Results of this study suggest encouraging family members who act in the mother role to take a "team approach" with the family proband when discussing HNPCC risks and management with family members.

Adult↗

PubMed2005

The causes of low back pain: a network analysis.

Beliefs regarding the cause of low back pain differ between individual sufferers and health care professionals. One consequence of this is the potential acquisition of maladaptive attitudes and behaviour in relation to pain, and increases in the utilisation of primary care services (Health Expect.3(3) (2000) 161). Methods that have been used to elicit the causal interpretation of social phenomena are varied yet they are unable to categorically demonstrate the different weightings or levels of importance that individuals may assign. The diagram method of network analysis allows individuals to spontaneously consider pathways they believe to be critical to a target event and to determine the strength of those pathways. Seventy-one completed diagrams indicating the causes that sufferers perceived to be related to low back pain were analysed. The mean number of direct causal paths was 5.61 (SD=3.25) and mean number of indirect causal links was 1.16 (SD=2.34). A significant correlation between path frequency and path strength was also found (r=0.76, p=0.001). Sufferers do not have an overtly complex view of the causative factors of low back pain but were able to define four core contributory causes (disc, sciatica, lifting, and injury) and one indirect pathway between lifting and injury. There was a clear delineation between external (biomedical) and internal (person-related) factors that were attributed to low back pain acquisition. By determining these causal attributions it is proposed that treatment packages could be tailored to address biases in thinking. This may be particularly useful for those individuals who attribute their pain as a consequence of external (or biomedical) causes.

Adaptation, Psychological↗

PubMed2004

Dynamic actor network analysis for diffuse pollution in the province of North-Holland.

Diffuse pollution problems involve numerous different organizations and this requires decision makers to involve different actors if they want to develop policies that have a chance of being implemented effectively. A first step in such interactive policy development would be to gain an overview of the different actors involved in diffuse pollution problems, as well as their views on the problem, their interests and their means to influence policy development and implementation. Dynamic Actor Network Analysis (DANA) offers a method that helps analysts in providing such an overview, and the use of this method is explored through its application to a case in the Dutch province of North Holland. The described case specifically focuses on the use of herbicides in public space and involves actors from regional water management authorities, municipalities and private sector users. An important finding is that there is an imbalance in the perceptions of actors that needs to be addressed by water management authorities. The paper concludes that DANA is a promising tool for offering new and useful insights to decision makers, although more practical experience is needed to better assess the utility of this analysis tool.

Diffusion↗

PubMed2002

Metabolic network analysis of Bacillus clausii on minimal and semirich medium using (13)C-labeled glucose.

Using (13)C-labeled glucose fed to the facultative alkalophilic Bacillus clausii producing the alkaline serine protease Savinase, the intracellular fluxes were quantified in continuous cultivation and in batch cultivation on a minimal medium. The flux through the pentose phosphate pathway was found to increase with increasing specific growth rate but at a much lower level than previously reported for Bacillus subtilis. Two futile cycles in the pyruvate metabolism were included in the metabolic network. A substantial flux in the futile cycle involving malic enzyme was estimated, whereas only a very small or zero flux through PEP carboxykinase was estimated, indicating that the latter enzyme was not active during growth on glucose. The uptake of the amino acids in a semirich medium containing 15 of the 20 amino acids normally present in proteins was estimated using fully labeled glucose in batch cultivations. It was found that leucine, isoleucine, and phenylalanine were taken up from the medium and not synthesized de novo from glucose. In contrast, serine and threonine were completely synthesized from other metabolites and not taken up from the medium. Valine, proline, and lysine were partly taken up from the medium and partly synthesized from glucose. The metabolic network analysis was extended to include analysis of growth on the semirich medium containing amino acids, and the metabolic flux distribution on this medium was estimated and compared with growth on minimal medium.

Amino Acids↗

PubMed1996

Network analysis of human Y microsatellite haplotypes.

To investigate the utility of Y chromosome microsatellites for studying human male-lineage evolution, we typed samples from three populations for five tetranucleotide repeats and an Alu insertion polymorphism. We found very high levels of haplotype diversity and evidence that most mutations involve the gain or loss of only one repeat unit, implying that any given microsatellite haplotype may have arisen independently on two or more Y-chromosome lineages. Together, these factors suggest that interpretation of small sample sizes (< 30) will be problematic. By typing a large sample of individuals (n = 174) from one population, East Anglia, we were able to construct a haplotype network. The network exhibits a well-connected core structure of commoner haplotypes. Computer simulations based on this network estimate the convergence time for African and Caucasian groups may be between 1.4 and 1.8 times as long as the convergence of the East Anglian population. Based on our comparison between large and small sample sizes, we suggest that large sample sizes are necessary in order to interpret Y-microsatellite haplotypes, and that a network analysis of the type we describe may prove informative in future studies.

Base Sequence↗

PubMed2005

Comparative metabolic network analysis of two xylose fermenting recombinant Saccharomyces cerevisiae strains.

The recombinant xylose fermenting strain Saccharomyces cerevisiae TMB3001 can grow on xylose, but the xylose utilisation rate is low. One important reason for the inefficient fermentation of xylose to ethanol is believed to be the imbalance of redox co-factors. In the present study, a metabolic flux model was constructed for two recombinant S. cerevisiae strains: TMB3001 and CPB.CR4 which in addition to xylose metabolism have a modulated redox metabolism, i.e. ammonia assimilation was shifted from being NADPH to NADH dependent by deletion of gdh1 and over-expression of GDH2. The intracellular fluxes were estimated for both strains in anaerobic continuous cultivations when the growth limiting feed consisted of glucose (2.5 g L-1) and xylose (13 g L-1). The metabolic network analysis with 13C labelled glucose showed that there was a shift in the specific xylose reductase activity towards use of NADH as co-factor rather than NADPH. This shift is beneficial for solving the redox imbalance and it can therefore partly explain the 25% increase in the ethanol yield observed for CPB.CR4. Furthermore, the analysis indicated that the glyoxylate cycle was activated in CPB.CR4.

Computer Simulation↗

PubMed2006

Effects of antipsychotic drugs on I(to), I (Na), I (sus), I (K1), and hERG: QT prolongation, structure activity relationship, and network analysis.

PURPOSE: To evaluate in vitro and computationally model the effects of selected antipsychotic drugs on several ionic currents that contribute to changes in the action potential in cardiac tissue. METHODS: Fourteen antipsychotic drugs or metabolites were examined to determine whether QT interval prolongation could be accounted for by an effect on one or more myocardial ion channels [I(to), I(Na), I(sus), I(K1), and human ether-a-go-go related gene (hERG)]. Using the patch clamp technique, drug effects on these human cardiac currents were tested. RESULTS: All molecules had little inhibitory effect on ion channels (blocking at concentrations >5 microM) other than hERG. A significant correlation was observed between the estimated hERG blockade and the increase in corrected QT for five of the antipsychotics. Molecular modeling identified hydrophobic features related to the interaction with hERG and correctly rank-ordered the test set molecules olanzapine and its metabolites. A network analysis of ligand and protein interactions around hERG using MetaCore (GeneGo Inc., St. Joseph, MI, USA) was used to visualize antipsychotics with affinity for this channel and their interactions with other proteins in this database. CONCLUSION: The antipsychotics do not inhibit the ion channels I(to), I(Na), I(sus), I(K1) to any appreciable extent; however, blockade of hERG is a likely mechanism for the prolongation of the QT interval.

Action Potentials↗

PubMed1995

Quantification of biomedical NMR data using artificial neural network analysis: lipoprotein lipid profiles from 1H NMR data of human plasma.

Artificial neural network (ANN) analysis is a new technique in NMR spectroscopy. It is very often considered only as an efficient "black-box' tool for data classification, but we emphasize here that ANN analysis is also powerful for data quantification. The possibility of finding out the biochemical rationale controlling the ANN outputs is presented and discussed. Furthermore, the characteristics of ANN analysis, as applied to plasma lipoprotein lipid quantification, are compared to those of sophisticated lineshape fitting (LF) analysis. The performance of LF in this particular application is shown to be less satisfactory when compared to neural networks. The lipoprotein lipid quantification represents a regular clinical need and serves as a good example of an NMR spectroscopic case of extreme signal overlap. The ANN analysis enables quantification of lipids in very low, intermediate, low and high density lipoprotein (VLDL, IDL, LDL and HDL, respectively) fractions directly from a 1H NMR spectrum of a plasma sample in < 1 h. The ANN extension presented is believed to increase the value of the 1H NMR based lipoprotein quantification to the point that it could be the method of choice in some advanced research settings. Furthermore, the excellent quantification performance of the ANN analysis, demonstrated in this study, serves as an indication of the broad potential of neural networks in biomedical NMR.

Humans↗

PubMed2006

High-density oligonucleotide microarrays and functional network analysis reveal extended lung carcinogenesis pathway maps and multiple interacting genes in NNK [4-(methylnitrosamino)-1-(3-pyridyle)-1-butanone] induced CD1 mouse lung tumor.

PURPOSE: NNK [4-(methylnitrosamino)-1-(3-pyridyle)-1-butanone] is a nicotine-derived nitrosaminoketone contained in tobacco smoke used as a powerful chemical carcinogen for rodent experimental models of pulmonary carcinogenesis. To clarify its carcinogenetic mechanisms, we examined the expression status of 22,625 mouse genes. METHODS: The affymetrix GeneChip mouse expression 430 A arrays have been used in CD1-induced mouse lung tumor. The affected genes were analyzed by Ingenuity pathway analysis to investigate functional network and gene ontology. RESULTS: A total of 876 genes were found to be differentially expressed at least twofold between NNK-induced tumors and normal lung tissues, 390 up-regulated and 486 down-regulated in these lesions. The functions with the highest P values were related to cellular growth and proliferation (P = 1.71 x 10(-4) to 4.10 x 10(-2)). In addition, we identified canonical pathways for Wnt/beta-catenin signaling (P = 0.0338). CONCLUSIONS: These results suggest that application of gene expression profiling may provide an improved strategy for therapeutic targeting of tobacco smoking-induced lung cancer.

Animals↗

PubMed2006

Gene interaction network analysis suggests differences between high and low doses of acetaminophen.

Bayesian networks for quantifying linkages between genes were applied to detect differences in gene expression interaction networks between multiple doses of acetaminophen at multiple time points. Seventeen (17) genes were selected from the gene expression profiles from livers of rats orally exposed to 50, 150 and 1500 mg/kg acetaminophen (APAP) at 6, 24 and 48 h after exposure using a variety of statistical and bioinformatics approaches. The selected genes are related to three biological categories: apoptosis, oxidative stress and other. Gene interaction networks between all 17 genes were identified for the nine dose-time observation points by the TAO-Gen algorithm. Using k-means clustering analysis, the estimated nine networks could be clustered into two consensus networks, the first consisting of the low and middle dose groups, and the second consisting of the high dose. The analysis suggests that the networks could be segregated by doses and were consistent in structure over time of observation within grouped doses. The consensus networks were quantified to calculate the probability distribution for the strength of the linkage between genes connected in the networks. The quantifying analysis showed that, at lower doses, the genes related to the oxidative stress signaling pathway did not interact with the apoptosis-related genes. In contrast, the high-dose network demonstrated significant interactions between the oxidative stress genes and the apoptosis genes and also demonstrated a different network between genes in the oxidative stress pathway. The approaches shown here could provide predictive information to understand high- versus low-dose mechanisms of toxicity.

Acetaminophen↗

PubMed2000

[Improvement of transrectal ultrasound. Artificial neural network analysis (ANNA) in detection and staging of prostatic carcinoma].

As a result of the enhanced clinical application of prostate specific antigen (PSA), an increasing number of men are becoming candidates for prostate cancer work-up. A high PSA value over 20 ng/ml is a good indicator of the presence of prostate cancer, but within the range of 4-10 ng/ml, it is rather unreliable. Even more alarming is the fact that prostate cancer has been found in 12-37% of patients with a "normal" PSA value of under 4 ng/ml (Hybritech). While PSA is capable of indicating a statistical risk of prostate cancer in a defined patient population, it is not able to localize cancer within the prostate gland or guide a biopsy needle to a suspicious area. This necessitates an additional effective diagnostic technique that is able to localize or rule out a malignant growth within the prostate. The methods available for the detection of these prostate cancers are digital rectal examination (DRE) and Transrectal ultrasound (TRUS). DRE is not suitable for early detection, as about 70% of the palpable malignancies have already spread beyond the prostate. The classic problem of visual interpretation of TRUS images is that hypoechoic areas suspicious for cancer may be either normal or cancerous histologically. Moreover, about 25% of all cancers have been found to be isoechoic and therefore not distinguishable from normal-appearing areas. None of the current biopsy or imaging techniques are able to cope with this dilemma. Artificial neural networks (ANN) are complex nonlinear computational models, designed much like the neuronal organization of a brain. These networks are able to model complicated biologic relationships without making assumptions based on conventional statistical distributions. Applications in Medicine and Urology have been promising. One example of such an application will be discussed in detail: A new method of Artificial Neural Network Analysis (ANNA) was employed in an attempt to obtain existing subvisual information, other than the gray scale, from conventional TRUS and to improve the accuracy of prostate cancer identification.

Adult↗

PubMed2005

A network analysis of committees in the U.S. House of Representatives.

Network theory provides a powerful tool for the representation and analysis of complex systems of interacting agents. Here, we investigate the U.S. House of Representatives network of committees and subcommittees, with committees connected according to "interlocks," or common membership. Analysis of this network reveals clearly the strong links between different committees, as well as the intrinsic hierarchical structure within the House as a whole. We show that network theory, combined with the analysis of roll-call votes using singular value decomposition, successfully uncovers political and organizational correlations between committees in the House without the need to incorporate other political information.

Journal Article↗