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At least 109 records · Page 6Linked to original sources
PubMed1994

Neural network analysis of flow cytometric data for 40 marine phytoplankton species.

Flow cytometry data (time of flight, horizontal and vertical forward light scatter, 90 degrees light scatter, and "red" and "orange" integral fluorescence) were collected for laboratory cultures of 40 species of marine phytoplankton, from the following taxonomic classes, the Dinophyceae, Bacillariophyceae, Prymnesiophyceae, Cryptophyceae, and other flagellates. Single-hidden-layer "back-propagation" neural networks were trained to discriminate between species by recognising patterns in their flow cytometric signatures, and network performance was assessed using an independent test data set. Two approaches were adopted employing: (1) a hierarchy of small networks, the first identifying to which major taxonomic group a cell belonged, and then a network for that taxonomic group identified to species, and (2) a single large network. Discriminating some of the major taxonomic groups was successful but others less so. With networks for specific groups, cryptophyte species were all identified reliably (probability of correct classification always being > 0.75); in the other groups half of the species were identified reliably. With the large network, dinoflagellates, cryptomonads, and flagellates were identified almost as well as by networks specific for these groups. The application of neural computing techniques to identification of such a large number of species represents a significant advance from earlier studies, although further development is required.

Flow Cytometry↗
PubMed1996

Positron emission tomography of 5-HT reuptake sites in the human brain with C-11 McN5652 extraction of characteristic images by artificial neural network analysis.

The goal of this work was to identify the distribution of serotonin transporters in the human brain with [11C](+)McN5652/PET. Four healthy volunteers were studied. To determine non-specific binding, a PET study was also performed with the inactive enantiomer [11C](-)McN5652 as well as with [11C](+)McN5652 after pretreatment with fluoxetine. For pattern extraction the PET data sets were analyzed by a back-propagation neural network. Two pharmacokinetic patterns and two characteristic images were separated; one representing specific binding, the other representing non-specific binding. The specific binding image showed characteristic distribution of serotonin transporters with [11C](+)McN5652. The pattern images demonstrated an improvement in image quality compared to the original PET images (reduced variance, higher region-to-cerebellum ratio, good correlation with known density of serotonin transporters). The non-specific binding images extracted from [11C](-)McN5652/PET were similar to those of [11C](-)McN5652 and [11C](-)McN5652 with fluoxetine. Thus, PET studies obtained with [11C](+)McN5652 largely represent the regional distribution of the serotonin transporters and the inactive enantiomer [11C](-)McN5652 shows the distribution of its nonspecific binding.

Adult↗
PubMed1995

Network analysis of brain cognitive function using metabolic and blood flow data.

Functional neuroimaging has become a powerful tool for investigating the neurobiological foundations of cognition. An overview is presented of the two major strategies by which such data are currently analyzed. One strategy compares the pattern of activity between two (or more) tasks, looking for those brain areas that show significant changes. The second investigates the functional relationships between regional activities in an attempt to determine the systems-level neural networks mediating the tasks. Object and spatial visual processing tasks are used to illustrate each of these strategies.

Animals↗
PubMed1996

Multi-layer neural network analysis of cerebrospinal fluid pressure patterns in idiopathic normal-pressure hydrocephalus.

The cerebrospinal fluid (CSF) pressure patterns have been reported as one of the most relevant indexes for the diagnosis and treatment of idiopathic normal-pressure hydrocephalus (INPH). Forty consecutive patients coming from our observations with the classic Hakim's triad underwent continuous CSF pressure monitoring via lumbar puncture for at least 12 hours. Twenty-eight patients were diagnosed as having INPH and underwent CSF shunt. A multi-layer neural network (perceptron) was employed to study the pressure patterns in order to try an alternative classification to the "expert" neurosurgeon one. Differences between expert and neural network classifications were indeed observed. Such differences may depend on the small group studied or on the inadequacy of CFS pressure patterns in correctly individuating those INPH patients who benefit from shunt surgery. The authors think that neural network processing of INPH could add relevant information to select the "responder" patients to surgery: in fact neural networks represent a powerful methodology for aiding the expert to select the proper choice on the basis of "what learnt" by the networks themselves.

Cerebrospinal Fluid↗
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↗
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↗
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↗
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↗
PubMed1984

Shunt haemodynamics and extracorporeal dialysis: an electrical resistance network analysis.

A time-dependent resistance model is used to study haemodynamic aspects of haemodialysis treatment. In the first part of the paper one model circuit, consisting of a pressure source, upstream and downstream resistances and a branching resistance, is shown to represent the haemodynamics of any type of arteriovenous fistula (AVF). Simple algebraic relations are derived for the haemodynamic determinants of AVFS, including finger ischaemia and AVF-maturation. The second part of the paper analyses the influences of a two-needle extracorporeal dialysis (ECD) circuit on the systemic vascular haemodynamics. The main result of the analysis is that the ECD-circuit can be considered as virtually independent of the systemic circulation. Consequently the dialysis flow does not depend on systemic vascular determinants and there are no instantaneous changes in the systemic circulation after switching on the ECD circuit. The ECD flow at onset of AVF collapse is shown to be (slightly) larger than the undisturbed AVF flow. Hence, onset of collapse strongly depends on the systemic blood pressure and vascular resistances. It can be used diagnostically to assess AVF capacities. Optimisation of haemodialysis through the ECD circuit is predicted to be inefficient.

Arm↗