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At least 271 records · Page 15Linked to original sources
PubMed1995

Evaluation of muscle diseases using artificial neural network analysis of 31P MR spectroscopy data.

Dermatomyositis is an autoimmune disease characterized by an erythematous rash and severe muscle weakness. 31P Magnetic resonance spectroscopy (MRS) provides quantitative data for longitudinal monitoring of disease status and responses to immunosuppressive therapy. A disease variant, amyopathic dermatomyositis, presents with a typical rash but no clinical muscle weakness. However, metabolic abnormalities in the oxidative capacity of muscles of amyopathic patients during exercise were detected with 31P MRS. Because MRS provided the best quantitative data for evaluating dermatomyositis, the 31P metabolic parameters derived from the MR spectra were further processed using an artificial neural network (XERION). The neural network analyses provided additional clinical information from the weighted correlations of multiple 31P parameters, namely, inorganic phosphate, phosphocreatine, ATP, phosphodiesters, and selected ratios. This investigation analyzes the relative importance of the various metabolic parameters for accurate patient characterization and provides insights into the pathogenesis of the disease.

Adenosine Triphosphate↗
PubMed2001

Neural network analysis of EUS images to differentiate between pancreatic malignancy and pancreatitis.

BACKGROUND: The differentiation of focal pancreatitis and pancreatic adenocarcinoma is problematic and often resolved only by pancreaticoduodenectomy. EUS is the most sensitive imaging modality for both conditions, yet ultrasonic criteria for distinguishing the two have not been described and differentiation remains difficult. The aims of this study were to develop a self-learning computer program that can analyze EUS images and differentiate malignancy from pancreatitis, and to compare results obtained with this system with EUS interpretation by experienced endosonographers. METHODS: Twenty-one patients with pancreatic cancer and 14 with focal pancreatitis were included. The diagnosis was confirmed histologically in all cases and each patient had undergone EUS. A single EUS image from each procedure was used for computer analysis. The results were compared with the EUS diagnosis reported at the actual procedure as well that of an endosonographer who reviewed videotapes of the procedures. RESULTS: The software program differentiated focal pancreatitis from malignancy with a maximal 89% accuracy. With sensitivity set at 100% for malignancy, the program was 50% specific and accuracy was 80%. Sensitivity and accuracy of the endosonographer's impression at the time of EUS were, respectively, 89% and 85%. A sensitivity of 73% and accuracy of 83% were achieved with blinded interpretation of EUS videotapes. CONCLUSIONS: Analysis of EUS images with computer software programs is feasible and compares favorably with human interpretation. The application of this technology to EUS and other imaging scenarios could be a useful adjunct to diagnostic endoscopy and warrants further investigation.

Adenocarcinoma↗
PubMed2005

Determination of phenolic compounds by a polyphenol oxidase amperometric biosensor and artificial neural network analysis.

The determination of phenolic compounds is significant given its toxicity, even at very low concentration levels. Amperometric determination of phenols is a simple technique available. Direct oxidation of phenols can be used, but another possibility is the use of polyphenol oxidase (tyrosinase) enzyme biosensors that oxidises the phenolic compounds into their corresponding quinones. Reduction of the resulting quinones accomplishes the amplification of the amperometric signal, as long as the result of the reduction process is the corresponding cathecol, this being able to be oxidised again by the polyphenol oxidase immobilized on the surface of the biosensor. In this communication, simultaneous determination of different phenols was carried out combining biosensor measurements with chemometric tools, in what is known as electronic tongue. The departure information used was the overlapped reduction voltammogram generated with the amperometric biosensor based on polyphenol oxidase. Artificial Neural Networks (ANN) were used for extraction and quantification of each compound. Phenol, cathecol and m-cresol formed the three-analyte study case resolved in this work. Good prediction ability was attained, and so, the separate quantification of these three phenols was accomplished.

Algorithms↗
PubMed1999

Network analysis in episodic encoding and retrieval of word-pair associates: a PET study.

The involvement of distributed brain regions in declarative memory has been hypothesized based on studies with verbal memory tasks. To characterize episodic declarative memory function further, 14 right-handed volunteers performed a visual verbal learning task using paired word associates. The volunteers underwent positron emission tomography. 15O-butanol was used as a tracer of regional cerebral blood flow (rCBF). Inter-regional functional interactions were assessed based on within-task, across-subject inter-regional rCBF correlations. Anatomical connections between brain areas were based on known anatomy. Structural equation modelling was used to calculate the path coefficients representing the magnitudes of the functional influences of each area on the ones to which it is connected by anatomical pathways. The encoding and the retrieval network elicit similarities in a general manner but also differences. Strong functional linkages involving visual integration areas, parahippocampal regions, left precuneus and cingulate gyrus were found in both encoding and retrieval; the functional linkages between posterior regions and prefrontal regions were more closely linked during encoding, whereas functional linkages between the left parahippocampal region and posterior cingulate as well as extrastriate areas and posterior cingulate gyrus were stronger during retrieval. In conclusion, these findings support the idea of a global bihemispheric, asymmetric encoding/retrieval network subserving episodic declarative memory. Our results further underline the role of the precuneus in episodic memory, not only during retrieval but also during encoding.

Adult↗
PubMed1996

Neural network analysis of flow cytometry immunophenotype data.

Acute leukemia is one of the leading malignancies in the United States with a mortality rate strongly influenced by the phenotype. This phenotype is based on detection of cell associated antigens normally expressed during leucopoietic differentiation. In this regard, leukemia classified as lymphoid or myeloid by phenotype is also classified as a candidate for the corresponding chemotherapy protocol. Additionally, the subtype of leukemia based on the degree of differentiation and cell maturity influence prognosis, response to treatment, and median survival times. In this paper, we analyze immunophenotype flow cytometry data toward categorization of leukemia into subcategories based on lineage and differentiation antigen expression. Twenty-eight inputs (derived from the mean fluorescence intensity of up to 27 antibodies, and an additional binary input denoting the past diagnosis of leukemia) are used as input to a neural classifier to categorize a total of 170 cases into the lineage and differentiation categories of leukemia. The neural classifier consisted of a feed forward network trained using back propagation. A complexity regulation term (weight decay) was used to improve the generalization performance of the neural classifier. A training error of 0.0% and a generalization error of 10.3% was obtained for categorization based on lineage, while a training error of 0.0% and a generalization error of 10.0% was obtained for categorization based on differentiation. These results indicate that objective classification of multifaceted phenotypes in leukemia can be achieved for analyzing multiparameter data in flow cytometry and further categorization into the prognostic subtypes.

Adult↗
PubMed2005

Using proteomics and network analysis to elucidate the consequences of synaptic protein oxidation in a PS1 + AbetaPP mouse model of Alzheimer's disease.

Increasing evidence suggests that oxidative injury is involved in the pathogenesis of many age-related neurodegenerative disorders, including Alzheimer's disease (AD). Identifying the protein targets of oxidative stress is critical to determine which proteins may be responsible for the neuronal impairments and subsequent cell death that occurs in AD. In this study, we have applied a high-throughput shotgun proteomic approach to identify the targets of protein carbonylation in both aged and PS1 + AbetaPP transgenic mice. However, because of the inherent difficulties associated with proteomic database searching algorithms, several newly developed bioinformatic tools were implemented to ascertain a probability-based discernment between correct protein assignments and false identifications to improve the accuracy of protein identification. Assigning a probability to each identified peptide/protein allows one to objectively monitor the expression and relative abundance of particular proteins from diverse samples, including tissue from transgenic mice of mixed genetic backgrounds. This robust bioinformatic approach also permits the comparison of proteomic data generated by different laboratories since it is instrument- and database-independent. Applying these statistical models to our initial studies, we detected a total of 117 oxidatively modified (carbonylated) proteins, 59 of which were specifically associated with PS1 + AbetaPP mice. Pathways and network component analyses suggest that there are three major protein networks that could be potentially altered in PS1 + AbetaPP mice as a result of oxidative modifications. These pathways are 1) iNOS-integrin signaling pathway, 2) CRE/CBP transcription regulation and 3) rab-lyst vesicular trafficking. We believe the results of these studies will help establish an initial AD database of oxidatively modified proteins and provide a foundation for the design of future hypothesis driven research in the areas of aging and neurodegeneration.

Activating Transcription Factor 2↗
PubMed1984

Glomerular hemodynamics and vascular structure in uremia: a network analysis of glomerular path lengths and maximal blood transit times computed for a microvascular model reconstructed from subserial ultrathin sections.

The dimensions of individual capillary segments were determined from a glomerular model constructed on the basis of electron micrographs of subserial ultrathin sections of kidney tissue from a rat made chronically uremic by subtotal nephrectomy. Hemodynamic calculations used computer programs for node pressure analysis and for the determination of path lengths and transit times from afferent to efferent arteriole. The afferent arteriole divided into five primary capillary segments. Three of these carried 84% of the flow through 632 paths, which accounted for 54% of the capillary endothelial area. Their mean path length was 520.97 micron, mean of segment numbers per path 17.66, and mean transit time 0.50 sec. The remaining two capillary segments carried 16% of the flow and led to paths accounting for the remaining 46% of the capillary area. The number of paths from the afferent arteriole through these two segments was 21,244. Mean path length from the initial node through these two segments was 852.18 micron, mean of segment numbers per path 29.62, and mean transit time 20.76 sec. The most striking difference between the two sets of paths was in transit time. This asymmetry would tend to reduce the filtration surface and the Kf (hydraulic conductance x filtering surface area) by causing early filtration pressure equilibrium in much of the capillary network, and suggests an intrinsic glomerular aspect of chronic renal insufficiency.

Animals↗
PubMed1995

Cartilage matrix protein forms a type II collagen-independent filamentous network: analysis in primary cell cultures with a retrovirus expression system.

Cartilage matrix protein (CMP) is expressed specifically in mature cartilage and consists of two von Willebrand factor A domains (CMP-A1 and CMP-A2) that are separated by an epidermal growth factor-like domain, and a coiled-coil tail domain at the carboxyl terminal end. We have shown previously that CMP interacts with type II collagen-containing fibrils in cartilage. In this study, we describe a type II collagen-independent CMP filament and we analyze the structural requirement for the formation of this type of filament. Recombinant wild-type CMP and two mutant forms were expressed in chick primary cell cultures using a retrovirus expression system. In chondrocytes, the wild-type virally encoded CMP is able to form disulfide bonded trimers and to assemble into filaments. Filaments also form with CMP whose Cys455 and Cys457 in the tail domain were mutagenized to prevent interchain disulfide bond formation. Therefore, intermolecular disulfide bonds are not necessary for the assembly of CMP into filaments. Both the wild-type and the double cysteine mutant also form filaments in fibroblasts, indicating that chondrocyte-specific factors are not required for filament formation. A truncated form of CMP that consists only of the CMP-A2 domain and the tail domain can form trimers but fails to form filaments, indicating that the deleted CMP-A1 domain and/or the epidermal growth factor domain are necessary for filament assembly but not for trimer formation. Furthermore, the expression of the virally encoded truncated CMP in chondrocyte culture disrupts endogenous CMP filament formation. Together these data suggest a role for CMP in cartilage matrix assembly by forming filamentous networks that require participation and coordination of individual domains of CMP.

Amino Acid Sequence↗
PubMed2026

Enzyme-Metabolite Network Analysis of Endometrial Cancer-Derived Extracellular Vesicles Through Integrated Proteomics and Metabolomics.

Endometrial cancer (EC) is the most common gynecological malignancy in high-income countries. Extracellular vesicles (EVs) are key mediators of intercellular communication and metabolic reprogramming, but their molecular cargo in EC remains poorly characterized. EVs were isolated from four EC cell lines representing Type I and Type II subtypes (AN3CA, ISHIKAWA, HEC1A, and KLE). Untargeted metabolomics was performed by HILIC-LC-MS/MS, proteomics by data-independent acquisition (DIA) mass spectrometry, and multi-omics integration using MetaboAnalyst and OmicsNet. Metabolomic profiling identified 1463 annotated features and revealed significant differences among EC cell lines (PERMANOVA, p = 0.002). Twenty-eight differentially abundant metabolites, including lactic acid, succinic acid, and uric acid, were identified. Proteomic analysis quantified 8513 proteins with subtype-specific expression patterns. Integrated analysis revealed seven significantly enriched pathways, including glycolysis/gluconeogenesis, central carbon metabolism in cancer, and the pentose phosphate pathway. Increased LDHA abundance in metastatic AN3CA-derived EVs was confirmed by Western blot (p = 0.047). EC-derived EVs display subtype- and metastatic-status-specific metabolo-proteomic signatures, with glycolysis, TCA cycle remodeling, and central carbon metabolism as convergent pathway signatures of molecular reprogramming. These findings establish a multi-omics framework for characterizing EV cargo in EC and identify candidate enzyme-metabolite nodes for future biomarker validation in patient-derived specimens.

Female↗
PubMed2000

Network analysis of brain activations in working memory: behavior and age relationships.

Forty-six middle-aged female subjects were scanned using functional Magnetic Resonance Imaging (fMRI) during performance of three distinct stages of a working memory task-encoding, rehearsal, and recognition-for both printed pseudowords and visual forms. An expanse of areas, involving the inferior frontal, parietal, and extrastriate cortex, was active in response to stimuli during both the encoding and recognition periods. Additional increases during memory recognition were seen in right prefrontal regions, replicating a now-common finding [for reviews, see Fletcher et al. (1997) Trends Neurosci 20:213-218; MacLeod et al. (1998) NeuroImage 7:41-48], and broadly supporting the Hemispheric Encoding/Retrieval Asymmetry hypothesis [Tulving et al. (1994) Proc Natl Acad Sci USA 91:2016-2020]. Notably, this asymmetry was not qualified by the type of material being processed. A few sites demonstrated higher activity levels during the rehearsal period, in the absence of any new stimuli, including the medial extrastriate, precuneus, and the medial temporal lobe. Further analyses examined relationships among subjects' brain activations, age, and behavioral scores on working memory tests, acquired outside the scanner. Correlations between brain scores and behavior scores indicated that activations in a number of areas, mainly frontal, were associated with performance. A multivariate analysis, Partial Least Squares [McIntosh et al. (1996) NeuroImage 3:143-157, (1997) Hum Brain Map 5:323-327], was then used to extract component effects from this large set of univariate correlations. Results indicated that better memory performance outside the scanner was associated with higher activity at specific sites within the frontal and, additionally, the medial temporal lobes. Analysis of age effects revealed that younger subjects tended to activate more than older subjects in areas of extrastriate cortex, medial frontal cortex, and the right medial temporal lobe; older subjects tended to activate more than younger subjects in the insular cortex, right inferior temporal lobe, and right inferior frontal gyrus. These results extend recent reports indicating that these regions are specifically involved in the memory impairments seen with aging.

Adult↗
PubMed1995

Pharmacologic modification of tumor blood flow and interstitial fluid pressure in a human tumor xenograft: network analysis and mechanistic interpretation.

Various vasoactive agents have been used to modify tumor blood flow with the ultimate goal of improving cancer detection and treatment, with widely disparate results. Furthermore, the lack of mechanistic interpretations has hindered understanding of how these agents affect the different physiological parameters involved in perfusion. Thus, there is a need to develop a unified framework for understanding the interrelated physiological effects of pharmacological and physical agents. The goals of this study were (1) to develop a mathematical model which helps determine the location and magnitude of changes in the vascular resistance of tumor and normal tissues and (2) to test the model with our experimental studies and by comparison with results from the literature. The systemic and interstitial pressures and relative tumor blood flow were measured before and after administration of angiotensin II, epinephrine, norepinephrine, nitroglycerin, and hydralazine in SCID mice bearing LS174T human colon adenocarcinoma xenografts. A mathematical model was developed in analogy to electrical circuits which examined the pressure, flow, and resistance relationships for arterial and venous segments of the vasculature of a tumor and surrounding normal tissue. Vasoconstrictor-induced increases in the mean arterial blood pressure led to increases in tumor blood flow and interstitial pressure with the magnitude of change dependent on the agent (percentage change in blood flow: angiotensin > epinephrine > norepinephrine). The vasodilating agents induced decreases in tumor blood flow in parallel to the induced decreases in the systemic pressure, but only the long-acting arterial vasodilator hydralazine was capable of effecting a decrease in tumor interstitial pressure. The model was also found to be consistent with other data available in the literature on norepinephrine, pentoxifylline, nicotinamide, and hemodilution, and was useful in providing input as to the location and degree of the physiological effects of these agents. The results of the data and model show that the steal phenomenon is the dominant mechanism for redistribution of host blood flow to the tumor. However, some degree of arterial control was found to be present in the tumors. Moreover, the parallel increases in tumor interstitial pressure and blood flow contradict any hypothesis suggesting that elevated interstitial fluid pressure precipitates chronic vascular collapse, thus decreasing blood flow.

Angiotensin II↗
PubMed1985

Modeling the electrical behavior of anatomically complex neurons using a network analysis program: passive membrane.

We describe the application of a popular and widely available electrical circuit simulation program called SPICE to modeling the electrical behavior of neurons with passive membrane properties and arbitrarily complex dendritic trees. Transient responses may be calculated at any location in the cell model following current, voltage or conductance perturbations at any point. A numbering method is described for binary trees which is helpful in transforming complex dendritic structures into a coded list of short cylindrical dendritic segments suitable for input to SPICE. Individual segments are modeled as isopotential compartments comprised of a parallel resistor and capacitor, representing the transmembrane impedance, in series with one or two core resistors. Synaptic current is modeled by a current source controlled by the local membrane potential and an "alpha-shaped" voltage, thus simulating a conductance change in series with a driving potential. Extensively branched test cell circuits were constructed which satisfied the equivalent cylinder constraints (Rall 1959). These model neurons were perturbed by independent current sources and by synaptic currents. Responses calculated by SPICE are compared with analytical results. With appropriately chosen model parameters, extremely accurate transient calculations may be obtained. Details of the SPICE circuit elements are presented, along with illustrative examples sufficient to allow implementation of passive nerve cell models on a number of common computers. Methods for modeling excitable membrane are presented in the companion paper (Bunow et al. 1985).

Animals↗
PubMed2004

Network analysis of protein structures identifies functional residues.

Identifying active site residues strictly from protein three-dimensional structure is a difficult task, especially for proteins that have few or no homologues. We transformed protein structures into residue interaction graphs (RIGs), where amino acid residues are graph nodes and their interactions with each other are the graph edges. We found that active site, ligand-binding and evolutionary conserved residues, typically have high closeness values. Residues with high closeness values interact directly or by a few intermediates with all other residues of the protein. Combining closeness and surface accessibility identified active site residues in 70% of 178 representative structures. Detailed structural analysis of specific enzymes also located other types of functional residues. These include the substrate binding sites of acetylcholinesterases and subtilisin, and the regions whose structural changes activate MAP kinase and glycogen phosphorylase. Our approach uses single protein structures, and does not rely on sequence conservation, comparison to other similar structures or any prior knowledge. Residue closeness is distinct from various sequence and structure measures and can thus complement them in identifying key protein residues. Closeness integrates the effect of the entire protein on single residues. Such natural structural design may be evolutionary maintained to preserve interaction redundancy and contribute to optimal setting of functional sites.

Allosteric Site↗
PubMed2004

Gene regulatory network analysis in sea urchin embryos.

It may safely be predicted that GRN analysis will become increasingly important. It will come to underlie the causal study of development, the major effort underway to understand the regulatory code built into animal genomes and also the evolution of these genomes. Partly by serendipity, sea urchin embryos turn out to be a superb experimental material for GRN analysis. Their natural properties have, in turn, influenced the predilections of those who work on them, and between them and us, so to speak, this is now a developmental system of which we are rapidly gaining an unusually complete understanding. The causal linkages that control development of the whole embryo will be revealed, leading all the way from the heritable genomic regulatory code to the events of embryology. The fundamental experimental operation is the perturbation analysis: Here is where causality permeates the exploration. We have in this chapter summarized in some detail the requirements for perturbation GRN analysis in sea urchin embryos. But that is not all, nor is it enough to enable the assembly of a GRN: What is required is the combined application of elegant computational methods, of gene regulation molecular biology, of genomic sequence data, and of experimental embryology. As the results crystallize together, we can begin to see how far this powerful combination of methods and ideas is going to carry us.

Animals↗