PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Network inference”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,099 records · Page 61Linked to original sources

Structure of the C-terminal RING finger from a RING-IBR-RING/TRIAD motif reveals a novel zinc-binding domain distinct from a RING.

The really interesting new gene (RING) family of proteins contains over 400 members with diverse physiological functions. A subset of these domains is found in the context of the RING-IBR-RING/TRIAD motifs which function as E3 ubiquitin ligases. Our sequence analysis of the C-terminal RING (RING2) from this motif show that several metal ligating and hydrophobic residues critical for the formation of a classical RING cross-brace structure are not present. Thus, we determined the structure of the RING2 from the RING-IBR-RING motif of HHARI and showed that RING2 has a completely distinct topology from classical RINGs. Notably, RING2 binds only one zinc atom per monomer rather than two and uses a different hydrophobic network to that of classical RINGs. Additionally, this RING2 topology is novel, bearing slight resemblance to zinc-ribbon motifs around the zinc site and is different from the topologies of the zinc binding sites found in RING and PHDs. We demonstrate that RING2 acts as an E3 ligase in vitro and using mutational analysis deduce the structural features required for this activity. Further, mutations in the RING-IBR-RING of Parkin cause a rare form of Parkinsonism and these studies provide an explanation for those mutations that occur in its RING2. From a comparison of the RING2 structure with those reported for RINGs, we infer sequence determinants that allow discrimination between RING2 and RING domains at the sequence analysis level.

Amino Acid Motifs↗

Automatic analysis of signals with symbolic content.

This paper presents a set of methods for helping in the analysis of signals with particular features that admit a symbolic description. The methodology is based on a general discrete model for a symbolic processing subsystem, which is fuzzyfied by means of a fuzzy inference system. In this framework a number of design problems have been approached. The curse of dimensionality problem and the specification of adequate membership functions are the main ones. In addition, other strategies, which make the design process simpler and more robust, are introduced. Their goals are automating the production of the rule base of the fuzzy system and composing complex systems from simpler subsystems under symbolic constrains. These techniques are applied to the analysis of wakefulness episodes in the sleep EEG. In order to solve the practical difficulty of finding remarkable situations from the outputs of the symbolic subsystems an unsupervised adaptive learning technique (FART network) has been applied.

Artificial Intelligence↗

In vitro and in vivo studies on the impact of the familial adenomatous polyposis heterogeneous mutation MUC20-S671C on colorectal carcinogenesis and progression.

BACKGROUND: Familial adenomatous polyposis (FAP) is a hereditary colorectal cancer (CRC). We performed genetic testing on nine FAP patients and identified a recurrent mutation at the 671st site of the MUC20 gene-MUC20-S671C. This mutation has a detection frequency of zero in the 1000 Genomes Project database. Previous studies have demonstrated that MUC20 can promote CRC progression through epithelial-mesenchymal transition (EMT). We conducted a series of experiments to analyze the impact of this mutation on CRC cells, aiming to infer its potential role and significance in CRC patients. METHODS: We introduced the MUC20-S671C mutation into the CRC SW480 cell line using the CRISPR-Cas9 technique and established a stable cell line carrying this mutation. We then conducted various experiments to assess the effects of this mutation. The Transwell assay was used to evaluate cell invasion and migration. We also examined cell proliferation, cell cycle progression, and apoptosis rate. Furthermore, we tested the tumorigenic ability of these cells in NOD-scid IL2Rγ[null] (NSG) mice. Additionally, transcriptome sequencing was performed on both cell lines and mouse tumor tissues to obtain molecular regulatory network data, and key molecules were further validated. RESULTS: The results of Cell Counting Kit-8 (CCK-8), 5-ethynyl-2'-deoxyuridine (EdU), and colony formation assays indicated that the proliferation ability of mutant cells was significantly reduced. The Transwell assay demonstrated a marked decline in the invasion and migration capabilities of mutant cells. Flow cytometry analysis revealed that the mutation increased the apoptosis rate of CRC cells and might have caused S-phase arrest. The tumor formation assay in nude mice showed that the tumorigenic ability of mutant cells was weakened. Transcriptome sequencing of both the cells and tumor tissues suggested that the mutation altered the expression of apoptosis- and cell cycle-related molecules and also affected EMT. Further experiments confirmed that key molecules involved in the EMT process, such as E-cadherin, were upregulated, while Vimentin, MMP9, and MMP14 were significantly downregulated, indicating that the mutation weakened the EMT capability of CRC cells. CONCLUSIONS: We have identified a novel mutation, MUC20-S671C, in patients with FAP. Our study demonstrates that this mutation exerts its tumor-suppressive effect by reversing the EMT process.

MUC20-S671C↗

Functional connectivity of the prefrontal cortex and the amygdala in posttraumatic stress disorder.

BACKGROUND: Persistent, intrusive re-experiencing in posttraumatic stress disorder (PTSD) is commonly construed as a failure of cingulate inhibition (i.e., extinction) over a hyperresponsive amygdala, based primarily on animal research of fear conditioning and the finding of cingulate hypoperfusion in PTSD. METHODS: We examined functional connectivity in patients with PTSD and healthy trauma survivors during repeated symptom provocation using H(2)O(15) positron emission tomography. RESULTS: Memory retrieval networks (right prefrontal cortex, hippocampus, and visual cortex) were common to both groups. Networks supporting autonomic and emotional control and preparatory motor action (amygdala, anterior cingulate, subcallosal gyrus, and premotor cortex) differed between the two groups and became progressively disparate with successive presentations of the traumatic script. Patterns of effective connectivity demonstrated the predominance of direct influences of the amygdala on visual cortex, subcallosal gyrus, and anterior cingulate in PTSD but not in control subjects. There was little evidence for failure of inhibition of cingulate or subcallosal cortex over the amygdala. CONCLUSIONS: These patterns might represent excessive influences of the amygdala over regions involved in autonomic, and higher-order visual memory processing in PTSD. The present data suggest that inferences of direct correspondence between animal studies and pathophysiology of PTSD should be made with caution.

Adult↗

Combining gene expression profiles and protein-protein interaction data to infer gene functions.

The ever-increasing flow of gene expression profiles and protein-protein interactions has catalyzed many computational approaches for inference of gene functions. Despite all the efforts, there is still room for improvement, for the information enriched in each biological data source has not been exploited to its fullness. A composite method is proposed for classifying unannotated genes based on expression data and protein-protein interaction (PPI) data, which extracts information from both data sources in novel ways. With the noise nature of expression data taken into consideration, importance is attached to the consensus expression patterns of gene classes instead of the actual expression profiles of individual genes, thus characterizing the composite method with enhanced robustness against microarray data variation. With regard to the PPI network, the traditional clear-cut binary attitude towards inter- and intra-functional interactions is abandoned, whereas a more objective perspective into the PPI network structure is formed through incorporating the varied function-function interaction probabilities into the algorithm. The composite method was implemented in two numerical experiments, where its improvement over single-data-source based methods was observed and the superiority of the novel data handling operations was discussed.

Algorithms↗

Universality in two-dimensional cellular structures evolving by cell division and disappearance.

The dynamics of two-dimensional cellular networks is written in terms of coupled population equations, which describe how the population of s-sided cells is affected by cell division and disappearance. In these equations the effect of the rest of the foam on the disappearing or dividing cell is treated as a local mean field. Under not too restrictive conditions, the equilibrium distribution P(s) of cells satisfies a linear difference equation of order two or higher. The population equations are asymptotically integrable. The asymptotic integrability implies a "universal" distribution P(s) approximately Cs-kZs for large values of s, which is also the Boltzmann distribution associated with the maximum entropy inference. Asymptotic integrability of the population equations is absent in a global mean-field approximation. The importance of short-range topological information to control the evolution of foams is thus confirmed.

Apoptosis↗

Reconstruction of in vivo time-evolving neuroendocrine dose-response properties unveils admixed deterministic and stochastic elements.

Homeostasis in the intact organism is achieved implicitly by repeated incremental feedback (inhibitory) and feedforward (stimulatory) adjustments enforced via intermittent signal exchange. In separated systems, neurohormone signals act deterministically on target cells via quantifiable effector-response functions. On the other hand, in vivo interglandular signaling dynamics have not been estimable to date. Indeed, experimentally isolating components of an interactive network definitionally disrupts time-sensitive linkages. We implement and validate analytical reconstruction of endogenous effector-response properties via a composite model comprising (i) a deterministic basic feedback and feedforward ensemble structure; (ii) judicious statistical allowance for possible stochastic variability in individual biologically interpretable dose-response properties; and (iii) the sole data requirement of serially observed concentrations of a paired signal (input) and response (output). Application of this analytical strategy to a prototypical neuroendocrine axis in the conscious uninjected horse, sheep, and human (i) illustrates probabilistic estimation of endogenous effector dose-response properties; and (ii) unmasks statistically vivid (2- to 5-fold) random fluctuations in inferred target-gland responsivity within any given pulse train. In conclusion, balanced mathematical formalism allows one to (i) reconstruct deterministic properties of interglandular signaling in the intact mammal and (ii) quantify apparent signal-response variability over short time scales in vivo. The present proof-of-principle experiments introduce a previously undescribed means to estimate time-evolving signal-response relationships without isotope infusion or pathway disruption.

Animals↗

Geographic identification of high gonorrhea transmission areas in Baltimore, Maryland.

Geographic approaches to sexually transmitted infection (STI) research frequently seek to identify areas where outreach STI testing may most effectively interrupt continued transmission of STIs. Many of the studies are limited, however, in that they fail to control for racial/ethnic composition of the high prevalence areas. These studies thus may be merely identifying the broader sexual networks of the high morbidity population and not the high transmission networks within them. Cluster detection analysis may be an appropriate approach to identify critical STI disease transmission locations. This study determined whether statistically significant geographic clusters of high prevalence gonorrhea cases can be located after controlling for race/ethnicity. Using a spatial scan statistic, the authors analyzed reported cases of gonorrhea (n = 32,454) in Baltimore City, Maryland, from 1994 to 1999 geocoded to the primary address and aggregated to census block groups (n = 709). They adjusted for the underlying distribution of the population aged 15-39 years and percent African American per census block group. The results identified eight significant clusters of high STI prevalence areas, reinforcing the inference that risks for gonorrhea are associated with definable sociogeographic spaces. The areas identified may be critical to control STIs and may provide important direction for further study and targeted interventions.

Adolescent↗

Construction of a cDNA microarray derived from the ascidian Ciona intestinalis.

A cDNA microarray was constructed from a basal chordate, the ascidian Ciona intestinalis. The draft genome of Ciona has been read and inferred to contain approximately 16,000 protein-coding genes, and cDNAs for transcripts of 13,464 genes have been characterized and compiled as the "Ciona intestinalis Gene Collection Release I". In the present study, we constructed a cDNA microarray of these 13,464 Ciona genes. A preliminary experiment with Cy3- and Cy5-labeled probes showed extensive differential gene expression between fertilized eggs and larvae. In addition, there was a good correlation between results obtained by the present microarray analysis and those from previous EST analyses. This first microarray of a large collection of Ciona intestinalis cDNA clones should facilitate the analysis of global gene expression and gene networks during the embryogenesis of basal chordates.

Animals↗

Parietal Cortex Transcriptomics Refines Parkinson Disease GWAS Nomination and Highlights STAT3 as a Putative Upstream Glial Regulator.

Parkinson disease (PD) affects more than 1.1 million individuals in the United States and around 12 million worldwide. Although Genome Wide Association Studies (GWAS) have substantially advanced our understanding of PD genetic architecture, the regulatory mechanisms linking PD risk loci to disease-relevant gene expression remain incompletely characterized, limiting our ability to infer disease mechanisms from genetic associations. Here, we integrated disease-state parietal cortex transcriptomics with the International Parkinson's Disease Genomics Consortium (iPDGC) locus prioritization to refine PD gene nomination and identify biologically plausible candidates missed by GWAS-only approaches. Using bulk RNA-seq from 99 neuropathologically confirmed PD cases and 30 neuropathologically confirmed controls, we prioritized candidate genes across 78 loci and classified them according to concordance between genetic evidence and differential expression in diseased cortices. This integrative approach recovered candidate genes not captured by external GWAS-based prioritization methods and highlighted synaptic, lysosomal, and proteostasis pathways as major components of PD risk biology. Network and transcription factor analyses further suggested coordinated regulation of these genes, with STAT3 emerging as a putative upstream glial regulator. Together, these findings suggest that integrating disease-state transcriptomics with genetic prioritization can refine PD risk-gene nomination and uncover regulatory programs that may be missed by GWAS alone.

Journal Article↗

Biomechanical study using fuzzy systems to quantify collagen fiber recruitment and predict creep of the rabbit medial collateral ligament.

In normal daily activities, ligaments are subjected to repeated loads, and respond to this environment with creep and fatigue. While progressive recruitment of the collagen fibers is responsible for the toe region of the ligament stress-strain curve, recruitment also represents an elegant feature to help ligaments resist creep. The use of artificial intelligence techniques in computational modeling allows a large number of parameters and their interactions to be incorporated beyond the capacity of classical mathematical models. The objective of the work described here is to demonstrate a tool for modeling creep of the rabbit medial collateral ligament that can incorporate the different parameters while quantifying the effect of collagen fiber recruitment during creep. An intelligent algorithm was developed to predict ligament creep. The modeling is performed in two steps: first, the ill-defined fiber recruitment is quantified using the fuzzy logic. Second, this fiber recruitment is incorporated along with creep stress and creep time to model creep using an adaptive neurofuzzy inference system. The model was trained and tested using an experimental database including creep tests and crimp image analysis. The model confirms that quantification of fiber recruitment is important for accurate prediction of ligament creep behavior at physiological loads.

Algorithms↗

A framework for the analysis of neuronal networks.

The object of this work is to consider the application of some methods of spike train analysis that are not widely known, and are concerned with the description of the interaction between spike trains and the determination of causal connections between them. The notation and terminology follow conventions established in the statistical literature. The examples given are based on in-continuity recordings of the spontaneous activity of single Ia afferents from the soleus muscle and single motor units from the same muscle. Cumulant densities are shown to be simple extensions of the traditional cross-correlation methods, and are useful in characterizing the pattern of activity in one spike train that influences that in another, and to reveal interactions between spike trains that would not be apparent from the correlation histogram alone. Parameters based on the Fourier transforms of the spike trains are shown to be useful in determining timing relations between them, and in inferring patterns of connectivity not possible by correlation methods alone.

Action Potentials↗

A pooling-deconvolution strategy for biological network elucidation.

The generation of large-scale data sets is a fundamental requirement of systems biology. But despite recent advances, generation of such high-coverage data remains a major challenge. We developed a pooling-deconvolution strategy that can dramatically decrease the effort required. This strategy, pooling with imaginary tags followed by deconvolution (PI-deconvolution), allows the screening of 2(n) probe proteins (baits) in 2 x n pools, with n replicates for each bait. Deconvolution of baits with their binding partners (preys) can be achieved by reading the prey's profile from the 2 x n experiments. We validated this strategy for protein-protein interaction mapping using both proteome microarrays and a yeast two-hybrid array, demonstrating that PI-deconvolution can be used to identify interactions accurately with fewer experiments and better coverage. We also show that PI-deconvolution can be used to identify protein-small molecule interactions inferred from profiling the yeast deletion collection. PI-deconvolution should be applicable to a wide range of library-against-library approaches and can also be used to optimize array designs.

Computational Biology↗

Mental, neuropsychic, and brain patterns of defense. Neuropsychic defense continua from psychopathology to the particularly human parallel networks that are problematic for artificial intelligence.

The synthesis of psychodynamic and neuroscientific data may be advanced by the study of similarly configured specific patterns of defense along continua from the normal and neurotic mental mechanisms of defenses, through what might be termed neuropsychiatric defenses influenced by the neurological state, to the more clearly neurological cortical reactions. These similar patterns and continua are the particularly human way brain adds its flavor of organism to mind, and the way in which all the psychodynamic mechanisms are specifically imbedded in brain. A purely psychological psychodynamics lacking this medical perspective fails to model human mental processes and reflects problems with artificial intelligence models that do not model brain. The pathological reactions that we address in psychiatry and neuropsychiatry interfere with and thereby reveal parallel processing features in (1) analogical and metaphorical thinking; (2) reduplication, redundancy, and repetitiveness; (3) self, person, and environmental recognition, including transference processes; (4) approximation and statistical inference; (5) spatiality and motor control; (6) affectivity, perception of sensations and sexuality; (7) projective mechanisms; and (8) problem solving by optimization, vectorial summation, and the mutual interaction of interconnected agencies. The new concepts in artificial intelligence built upon brainlike structures called neural nets portend great economies, emergent natural features that are more like human processes, and hierarchical and cyclic organizational demands. Medical psychoanalysts who comprehend dynamic and brain mechanisms and can describe them in terms that refer to both domains and their interaction should find increasing theoretical and practical convergence of their work with the emerging study and modeling of these processes by new forms of computers.

Adult↗

Y-chromosome genotyping and genetic structure of Zhuang populations.

Zhuang, the largest ethnic minority population in China, is one of the descendant groups of the ancient Bai-Yue. Linguistically, Zhuang languages are grouped into northern and southern dialects. To characterize its genetic structure, 13 East Asian-specific Y-chromosome biallelic markers and 7 Y-chromosome short tandem repeat (STR) markers were used to infer the haplogroups of Zhuang populations. Our results showed that O*, O2a, and O1 are the predominant haplogroups in Zhuang. Frequency distribution and principal component analysis showed that Zhuang was closely related to groups of Bai-Yue origin and therefore was likely to be the descendant of Bai-Yue. The results of principal component analysis and hierarchical clustering analysis contradicted the linguistically derived north-south division. Interestingly, a west-east clinal trend of haplotype frequency changes was observed, which was supported by AMOVA analysis that showed that between-population variance of east-west division was larger than that of north-south division. O* network suggested that the Hongshuihe branch was the center of Zhuang. Our study suggests that there are three major components in Zhuang. The O* and O2a constituted the original component; later, O1 was brought into Zhuang, especially eastern Zhuang; and finally, northern Han population brought O3 into the Zhuang populations.

Alleles↗

Genetic differentiation of relictual populations of Alsophila spinulosa in southern China inferred from cpDNA trnL-F noncoding sequences.

The genetic differentiation and phylogeographical pattern of 11 relictual populations of Alsophila spinulosa distributed across Hainan, Guangdong, and Guangxi in southern China were inferred from sequence variations of trnL-F noncoding regions of chloroplast DNA (cpDNA). The length of trnL-F noncoding sequences varied from 863 to 940 bp. The A + T content was 62.23-63.36%. Sequences were neutral in terms of evolution (Tajima's criterion D=-0.62417, P>0.10 and Fu and Li's test D*=-1.45455, P>0.10; F*=-1.32798, P>0.10). Thirty-four haplotypes were identified based on nucleotide variation. Relatively high levels of haplotype diversity (h=0.929) and nucleotide diversity (Dij=0.022263) were detected in A. spinulosa, probably associated with its long evolutionary history which allowed the accumulation of genetic variation within lineages. Both the minimum spanning network and the strict consensus tree of the most parsimonious trees generated for haplotypes demonstrated that the investigated populations of A. spinulosa were subdivided into two geographical groups: Hainan and Guangdong-Guangxi. An analysis of molecular variance (AMOVA) indicated that most of the genetic variation (87.48%, P<0.001) was partitioned among regions. Spatial structure measurements revealed that population genetic structure was not related to geographical distance. This research suggests that blocked gene flow by Qiongzhou strait and an inbreeding system might result in the geographical subdivision between Hainan and Guangdong-Guangxi (F(ST)=0.92, Nm=0.09). Within each region, the "star like" pattern of phylogeography of haplotypes implied a population expansion process during evolutionary history. Gene genealogies together with coalescent theory were useful tools for uncovering the phylogeography of A. spinulosa.

China↗

Spatial imagery in deductive reasoning: a functional MRI study.

Various cognitive theories aim to explain human deductive reasoning: (1) mental logic theories claim syntactic language-based proofs of derivation, (2) the mental model theory proposes cognitive processes of constructing and manipulating spatially organized mental models, and (3) imagery theories postulate that such abilities are based on visual mental images. To explore the neural substrates of human deductive reasoning, we examined BOLD (blood oxygen level dependent) contrasts of twelve healthy participants during relational and conditional reasoning with whole-brain functional magnetic resonance imaging (fMRI). The results indicate that, in the absence of any correlated visual input, reasoning activated an occipitoparietal-frontal network, including parts of the prefrontal cortex (Brodmann's area, BA, 6, 9) and the cingulate gyrus (BA 32), the superior and inferior parietal cortex (BA 7, 40), the precuneus (BA 7), and the visual association cortex (BA 19). In the discussion, we first focus on the activated occipito-parietal pathway that is well known to be involved in spatial perception and spatial working memory. Second, we briefly relate the activation in the prefrontal cortical areas and in the anterior cingulate gyrus to other imaging studies on higher cognitive functions. Finally, we draw some general conclusions and argue that reasoners envisage and inspect spatially organized mental models to solve deductive inference problems.

Adult↗

Functional MRI neuroanatomic correlates of the Hooper Visual Organization Test.

The Hooper Visual Organization Test (VOT), a commonly applied neuropsychological test of visual spatial ability, is used for assessing patients with suspected right hemisphere, or parietal lobe involvement. A controversy has developed over whether the inferences of this test metric can be assumed to involve global, lateralized, or regional functionality. In this study, the characteristic visual organization and object naming aspects of the VOT task presentation were adapted to a functional MR imaging (fMRI) paradigm to probe the neuroanatomic correlates of this neuropsychological test. Whole brain fMRI mapping results are reported on a cohort of normal subjects. Bilateral fMRI responses were found predominantly in the posterior brain, in regions of superior parietal lobules, ventral temporal-occipital cortex, and posterior visual association areas, and to a lesser extent, the frontal eye fields bilaterally, and left dorsolateral prefrontal cortex. The results indicate a general brain region or network in which VOT impairment, due to its visuospatial and object identification demands, is possible to be detected. Discussion is made of interpretive limitations when adapting neuropsychological tests to fMRI analysis.

Adult↗