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Results for “network physiology”

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At least 271 records · Page 15Linked to original sources
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↗
PubMed2002

Modeling fatigue.

The American Board of Family Practice is developing a patient simulation program to evaluate diagnostic and management skills. The simulator must give temporally and physiologically reasonable answers to symptom questions such as "Have you been tired?" A three-step process generates symptom histories. In the first step, the simulator determines points in time where it should calculate instantaneous symptom status. In the second step, a Bayesian network implementing a roughly physiologic model of the symptom generates a value on a severity scale at each sampling time. Positive, zero, and negative values represent increased, normal, and decreased status, as applicable. The simulator plots these values over time. In the third step, another Bayesian network inspects this plot and reports how the symptom changed over time. This mechanism handles major trends, multiple and concurrent symptom causes, and gradually effective treatments. Other temporal insights, such as observations about short-term symptom relief, require complimentary mechanisms.

Artificial Intelligence↗
PubMed2001

Simultaneous multi-site recordings of neural activity with an inline multi-electrode array and optical measurement in rat hippocampal slices.

Understanding neuronal network function requires multi-site recording. An optical imaging method using voltage-sensitive dyes (VSD) is one such suitable method. It is also important to complement this technique with methods that measure other physiological parameters of neuronal network activity. We aimed to develop a multi-channel electrode method that would easily permit the simultaneous optical imaging of neural activity in vitro. There are several multi-electrode systems; some of these are commercially available, but they are not easy to use and are also expensive. We developed a novel, less expensive, stainless steel inline electrode array that utilizes the standard etching method of circuit board manufacturing. This method, along with widely available computer drawing software, allowed us to produce electrode arrays with uniform quality in electrical characteristics and shapes. The electrode array was designed so that it could easily substitute for single electrode systems without modifying the conventional set-up used for electrophysiological measurements and optical recordings. Simultaneous measurement of evoked neural activities in area CA1 of the rat hippocampal slice with our optical imaging method using the VSD Di-4-ANEPPS is demonstrated in this paper. The electrode array was also used as a stimulating electrode, and the evoked response was measured by the optical recording method. The results demonstrate the advantages of simultaneous recordings obtained by these complementary multi-site recording methods in vitro.

Animals↗
PubMedDate not supplied

Polylactones 57. Biodegradable networks based on A-B-A triblock segments containing poly(ethylene glycol)s-syntheses and drug release properties.

Condensation of Bu(2)Sn(OMe)(2) with poly(ethylene glycol)s yielded macrocyclic tin alkoxides which were, in turn, used as cyclic initiators for the ring-expansion polymerization of epsilon-caprolactone, D,L-lactide, or trimethylene carbonate. The resulting cyclic triblock copolymers were in situ cross-linked with trimesoyl chloride. The lengths of the A-B-A triblock segments were varied via the monomer-initiator ratio (M/I) or via the lengths of the poly(ethylene glycol)s. After extraction with CH(2)Cl(2), the isolated networks were characterized by (1)H NMR spectroscopy, DSC measurements, and swelling experiments. The release of dexamethasone and 5-fluorouracil from two triblock networks was studied in physiological buffer solutions at 37 degrees C over a period of several weeks. A strong initial burst was found in all cases. Only a weak initial burst and a more continuous release was observed when networks of random L-lactide/epsilon-caprolactone copolymers were studied under the same conditions.

Absorbable Implants↗
PubMed2004

The Era-like GTPase TrmE conditionally activates gadE and glutamate-dependent acid resistance in Escherichia coli.

Escherichia coli survives pH 2 acid stress at a level rivalling Helicobacter pylori. Of the three E. coli acid resistance systems involved, the one most efficient and most studied uses isozymes of glutamate decarboxylase (GadA/GadB) to consume intracellular protons, and a glutamate:gamma-amino butyric acid (GABA) anti-porter (GadC) to expel GABA in exchange for extracellular glutamate. Because acid resistance is a critical factor in resisting stomach acidity, mechanisms that control this system are extremely important. Here we show that an Era-like, molecular switch GTPase called TrmE regulates glutamate-dependent acid resistance. Western blot analysis revealed a TrmE-dependent, glucose-induced system and a TrmE-independent, glucose-repressed pathway. Gene fusion studies indicated that the TrmE requirement for GadA/B production takes place at both the transcriptional and translational levels. TrmE controls GAD transcription by affecting the expression of GadE, the essential activator of the gadA and gadBC genes. TrmE most probably controls gadE expression indirectly by influencing the synthesis or activity of an unknown regulator that binds the gadE control region. Translational control of GAD production by TrmE appears to be more direct, affecting synthesis of the decarboxylase and the anti-porter proteins. TrmE GTPase activity was critical for both the transcriptional and translational effects. Thus, TrmE is part of an increasingly complex control network designed to integrate diverse physiological signals and forecast future exposures to extreme acid. The significance of this network extends beyond acid resistance as the target of this control, GadE, regulates numerous genes in addition to gadA/BC.

Escherichia coli↗
PubMed1997

Ventilation mode recognition using artificial neural networks.

This study investigated the capabilities of artificial neural networks to identify spontaneous and pressure support ventilation modes from gas flow and airway pressure signals. After receiving written informed consent, flow and pressure waveforms were recorded from 13 patients undergoing general anesthesia. During analysis, the inspiratory phase of each breath was extracted and normalized in amplitude and wavelength. Neural networks were configured to input flow, pressure, or both waveforms and to output the ventilatory mode. Neural network training was accomplished with data from 500 breaths obtained from 7 patients. Neural network performance was tested with 433 breaths from the remaining 6 patients. Networks using flow, pressure, and both waveforms recognized correctly 78% (337), 97% (423), and 100% (433) of the test waveforms, respectively. Results indicate that neural networks can be used effectively for breathing pattern recognition and encourage the application of neural networks in other types of respiratory pattern recognition problems.

Aged↗
PubMed1978

Command neurons in Pleurobranchaea receive synaptic feedback from the motor network they excite.

Command neurons that cause rhythmic feeding behavior in the marine mollusc Pleurobranchaea californica have been identified in the cerebropleural ganglion (brain). Intracellular stimulation of single command neurons in isolated nervous systems, semi-intact prepartions, and restrained whole animals causes the same rhythmic motor output pattern as occurs during feeding. During this motor output pattern, action potentials recorded intracellularly from the command neurons occur in cyclic bursts that are phase-locked with the feeding rhythm. This modulation results from repetitive, alternating bursts of excitatory and inhibitory postsynaptic potentials, which are caused at least in part by synaptic feedback to the command neurons from identified classes of neurons in the feeding network. Central feedback to command neurons from the motor network they excite provides a possible general physiological mechanism for the sustained oscillation of neural networks controlling cyclic behavior.

Action Potentials↗
PubMed1992

[Aging of the arterial system].

The high-pressure systemic arterial network plays a major physiological role as it buffers the impact of the blood flow wave generated by the left ventricle and transforms it into a more continuous flow in the peripheral arterioles. In ageing processes unrelated to hypertensive or vascular disease the structural properties of the arterial network are significantly altered. The collagen, elastin and smooth muscle contents of the tunica media and the geometrical arrangement of arterial wall components are constantly modified according to the subject's age. These morphometric changes are responsible for changes in the mechanical properties of the arterial walls leading to rigidity. An increase in caliber of the arterial lumen has been found in all studies; it partially compensates for the effects of arterial wall rigidity on vascular compliance, thereby limiting the haemodynamic and functional changes that occur in blood circulation.

Adult↗
PubMed2006

An integrated biological approach to nuclear receptor signaling in physiological control and disease.

The nuclear receptors (NRs)--vitamin D receptor (VDR); peroxisome proliferator-activated receptor (PPAR) alpha, delta, gamma; and pregnane X receptor (PXR)--act as sensors for various molecules encountered by the body on a daily basis. The effects of these ligands can be understood by the fact that numerous genes involved in the cellular processes, such as general homeostasis, growth, and defense against microbes, are under the control of these five NRs. The target gene and protein expression patterns of VDR, PPARs, and PXR; the resulting changes in metabolite levels; and their physiological consequences create a network that can be monitored by high-throughput methods and analyzed by multimodal approaches, such as systems biology. We suggest that the fine regulation of this NR network is specific to each human individual and depends, in part, on the constellation of regulatory small nucleotide polymorphisms (SNPs) in his or her genome. When regulatory SNPs affect NRs response elements, lifetime exposure to food components will have different accumulative consequences on the expression of the respective NR target genes. These differences will influence the individual's susceptibility to aging-related diseases, such as type 2 diabetes, atherosclerosis, cancer, and osteoporosis. Furthermore, it is anticipated that systems biology methods will also help to identify the most critical genes, proteins, or metabolites in the NR network that will serve as biomarkers for the early detection of these diseases.

Computational Biology↗
PubMed2006

Anatomical profiling of nuclear receptor expression reveals a hierarchical transcriptional network.

In multicellular organisms, the ability to regulate reproduction, development, and nutrient utilization coincided with the evolution of nuclear receptors (NRs), transcription factors that utilize lipophilic ligands to mediate their function. Studying the expression profile of NRs offers a simple, powerful way to obtain highly relational information about their physiologic functions as individual proteins and as a superfamily. We surveyed the expression of all 49 mouse NR mRNAs in 39 tissues, representing diverse anatomical systems. The resulting data set uncovers several NR clades whose patterns of expression indicate their ability to coordinate the transcriptional programs necessary to affect distinct physiologic pathways. Remarkably, this regulatory network divides along the following two physiologic paradigms: (1) reproduction, development, and growth and (2) nutrient uptake, metabolism, and excretion. These data reveal a hierarchical transcriptional circuitry that extends beyond individual tissues to form a meganetwork governing physiology on an organismal scale.

Animals↗
PubMed2005

Regulatory networks of the phytohormone abscisic acid.

Structurally similar to retinoic acid (RA), the phytohormone abscisic acid (ABA) controls many developmental and physiological processes via complicated signaling networks that are composed of receptors, secondary messengers, protein kinase/phosphatase cascades, transcription factors, and chromatin-remodeling factors. In addition, ABA signaling is further modulated by mRNA maturation and stability, microRNA (miRNA) levels, nuclear speckling, and protein degradation. This chapter highlights the identified regulators of ABA signaling and reports their homologues in dicotyledonous and monocotyledonous plants.

Abscisic Acid↗
PubMed1999

Classification of asthmatic breath sounds: preliminary results of the classifying capacity of human examiners versus artificial neural networks.

For continuous monitoring of the respiratory condition of patients, e.g., at the intensive care unit, computer assistance is required. Existing mechanical devices, such as the peak expiratory flow meter, provide only with incidental measurements. Moreover, such methods require cooperation of the patient, which at, e.g., the ICU is usually not possible. The evaluation of complicated phenomena such as asthmatic respiratory sounds may be accomplished by use of artificial neural networks. To investigate the merit of artificial neural networks, the capacities of neural networks and human examiners to classify breath sounds were compared in this study. Breath sounds were in vivo recorded from 50 school-age children with asthma and from 10 controls. Sound intervals with a duration of 20 seconds were randomly sampled from asthmatics during exacerbation, asthmatics in remission, and controls. The samples were digitized and related to peak expiratory flow. From each interval, two full breath cycles were selected. Of each selected breath cycle, a Fourier power spectrum was calculated. The so-obtained set of spectral vectors was classified by means of artificial neural networks. Humans evaluated graphic displays of the spectra. Human examiners could not clearly discriminate between the three groups by inspecting the spectrograms. Classification by self-classifying neural networks confirmed the existence of at least three classes; however, discrimination of 11 classes seemed more appropriate. Good results were obtained with supervised networks: as much as 95% of the training vectors could be classified correctly, and 43% of the test vectors. The three patient groups, as discriminated in advance, do not correspond with three sharply separated sets of spectrograms. More than three classes seem to be present. Humans cannot take up the spectral complexity and showed negative classification results. Artificial neural networks, however, are able to handle classification tasks and show positive results.

Acoustics↗
PubMed2003

Neural network for photoplethysmographic respiratory rate monitoring.

The reflection mode photoplethysmographic (PPG) signal was studied with the aim of determining respiratory rate. The PPG signal includes respiratory synchronous components, seen as frequency modulation of the heart rate (respiratory sinus arrhythmia), amplitude modulation of the cardiac pulse and respiratory-induced intensity variations (RIIVs) in the PPG baseline. PPG signals were recorded from the foreheads of 15 healthy subjects. From these signals, the systolic wave-form, diastolic waveform, respiratory sinus arrhythmia, pulse amplitude and RIIVs were extracted. Using basic algorithms, the rates of false positive and false negative detection of breaths were calculated separately for each of the five components. Furthermore, a neural network was assessed in a combined pattern recognition approach. The error rates (sum of false positive and false negative breath detections) for the basic algorithms ranged from 9.7% (pulse amplitude) to 14.5% (systolic waveform). The corresponding values for the neural network analysis were 9.5-9.6%. These results suggest the use of a combined PPG system for simultaneous monitoring of respiratory rate and arterial oxygen saturation (pulse oximetry).

Adult↗
PubMed1997

Acetylcholine and associative memory in the piriform cortex.

The significance of cholinergic modulation for associative memory performance in the piriform cortex was examined in a study combining cellular neurophysiology in brain slices with realistic biophysical network simulations. Three different physiological effects of acetylcholine were identified at the single-cell level: suppression of neuronal adaptation, suppression of synaptic transmission in the intrinsic fibers layer, and activity-dependent increase in synaptic strength. Biophysical simulations show how these three effects are joined together to enhance learning and recall performance of the cortical network. Furthermore, our data suggest that activity-dependent synaptic decay during learning is a crucial factor in determining learning capability of the cortical network. Accordingly, it is predicted that acetylcholine should also enhance long-term depression in the piriform cortex.

Acetylcholine↗
PubMed2004

Functionally and structurally integrated computational modeling of ventricular physiology.

Computational biology is integrative in several ways. Functionally, computational models are valuable for integrating the many interacting processes within biochemical networks and the many interacting physiological subsystems within the cell. Structurally detailed models provide a way of integrating across scales of biological organization from molecule to organism. Data integration across diverse laboratory and clinical measurements is another unique strength of computational biology. We describe examples of all three categories of integration by using recent advances in modeling cardiac excitation-contraction coupling and whole-heart electromechanics in health and disease.

Animals↗
PubMed2005

Neural network adaptive control for nonlinear nonnegative dynamical systems.

Nonnegative and compartmental dynamical system models are derived from mass and energy balance considerations that involve dynamic states whose values are nonnegative. These models are widespread in engineering and life sciences and typically involve the exchange of nonnegative quantities between subsystems or compartments wherein each compartment is assumed to be kinetically homogeneous. In this paper, we develop a full-state feedback neural adaptive control framework for adaptive set-point regulation of nonlinear uncertain nonnegative and compartmental systems. The proposed framework is Lyapunov-based and guarantees ultimate boundedness of the error signals corresponding to the physical system states and the neural network weighting gains. In addition, the neural adaptive controller guarantees that the physical system states remain in the nonnegative orthant of the state-space for nonnegative initial conditions.

Adaptation, Physiological↗
PubMed2001

Ontologies of developmental anatomy: their current and future roles.

A central problem in current biology is elucidating the molecular networks that drive developmental change and physiological function. Such knowledge is needed partly to understand these networks, partly to be able to manipulate them, and partly to understand and help treat those human congenital abnormalities that arise as a result of mutation. Thus far, bioinformatics technology has been of limited use in this enterprise, mainly because its core focus has been on sequence technology and data archiving. For bioinformatics to be of use in this next tier of investigations, genetic and protein data need to be both archived and searchable by tissue since this is the level at which these networks operate. The resulting databases in turn require ontologies of developmental anatomy that can provide the formal infrastructure for handling gene expression, microarray and other tissue-based data. Here, the progress in making such ontologies, particularly for the developing mouse, is reported and the uses to which they are and will be put, together with the resources and tools currently available for investigating molecular networks and the genetic basis of congenital abnormalities, are considered.

Anatomy↗