SEARCH · PubMed Health

Results for “regularized model”

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 145 records · Page 8Linked to original sources

PubMed2005

[Application of O-PLS in fundamental study of non-invasive measurement of human blood glucose concentration with near infrared spectroscopy].

Near-infrared diffuse reflectance spectroscopy is a promising approach to the non-invasive prediction of blood glucose levels. However, because the measured object is human body whose physiological structures are so complicated that it is very difficult to separate the information of glucose from the overlapped spectra using the traditional modeling method. A new regression method called orthogonal projections to latent structures (O-PLS), which integrated the orthogonal signal correction (OSC) preprocessing into the regular PLS modeling, was applied to the optimization and interpretation of the glucose near-infrared spectroscopy model. Applying O-PLS resulted in removal of non-correlated variation in spectra and reduced model complexity with preserved prediction ability, improved interpretative ability of variation in spectra.

Blood Glucose↗

PubMed2006

Regularized estimation in the accelerated failure time model with high-dimensional covariates.

We consider two regularization approaches, the LASSO and the threshold-gradient-directed regularization, for estimation and variable selection in the accelerated failure time model with multiple covariates based on Stute's weighted least squares method. The Stute estimator uses Kaplan-Meier weights to account for censoring in the least squares criterion. The weighted least squares objective function makes the adaptation of this approach to multiple covariate settings computationally feasible. We use V-fold cross-validation and a modified Akaike's Information Criterion for tuning parameter selection, and a bootstrap approach for variance estimation. The proposed method is evaluated using simulations and demonstrated on a real data example.

Algorithms↗

PubMed2003

First year of practice visits for the Rural Depression Anxiety Research and Treatment General Practice program.

OBJECTIVE: To describe the first 12 months activities of a key component of a General Practice Psychiatry program - the GP practice visit. DESIGN: Questionnaire to evaluate effects on participating general practitioners practice. SETTING: Rural group general practices. SUBJECTS: Thirty-two general practitioners in the Loddon Campaspe Southern Mallee region in Victoria. INTERVENTIONS: Practice visits involved a combination of each of three key activities: primary consultation, secondary consultation and/or case discussion and formal teaching. RESULTS: General practitioners reported a variety of changes in their practice as a result of the visits. CONCLUSION: Practice visits appear to be a useful means of influencing GP's practice. Further work is required to determine whether such changes are accompanied by demonstrable benefits in patient outcome. WHAT IS ALREADY KNOWN: Several models to assist GPs effectively manage mental health problems have been described. These models require regular contact and so have had limited utility in rural settings. WHAT THIS STUDY ADDS: This study suggests that infrequent contact or input, based on well established models, can alter GP's clinical behaviour.

Anxiety↗

PubMed2004

Transplantation for stroke.

Stroke is the most common cause of disability in the United States, and one of the leading causes of mortality and disability in the world. The hope that damage to the CNS can be reversed or at least ameliorated is the central idea behind the research into neural repair. The ultimate repair for the brain should restore the entire lost structure and it's function. However, partial benefit is possible from addressing some of the needs of the injured brain. These partial solutions are the basis of current research into brain repair after stroke. An opportunity arises for two kinds of intervention: (1) replacement of neurons; (2) support of existing neurons, to prevent excessive degeneration and promote rewiring and plasticity. Transplantation for stroke in the rat model was regularly reported starting in 1992, demonstrating graft survival and even evidence of connection with the host brain. These studies determined several parameters for future work in stroke models, but ultimately had limited efficacy and did not progress to clinical experiments. A variety of cell types have been tried for restoration of brain function after stroke, mostly in rodent models. Human fetal cells had shown some promise in clinical studies for the treatment of Parkinson's disease. The technical and ethical difficulties associated with these cells promoted a search for alternatives. These include porcine fetal cells, human cultured stem cells, immortalized cell lines, marrow stromal cells, Sertoli cells pineal cells, and other sources. Human clonal cell lines have few ethical limitations, but some questions remain regarding their safety and efficacy. Autologous somatic stem cells are a very attractive source--there are no ethical concerns and graft rejection is not an issue. However, it is not clear that somatic cells can are plastic enough and can be safely induced to a neural fate. Restorative treatment for stroke is a new field of study. Naturally, new ideas abound and many strategies have been suggested and tried. Methods and controversies abound, and include: local delivery of cells to the area of the stroke versus grafting to an area of the brain far removed form the stroke; cell therapy for reconstitution of structure and function versus use of cell grafts to support intrinsic repair and recovery mechanisms; intravascular administration of bone marrow or other stem cells; and combination grafts, or co-grafting of several cell types or cells and other substances. The various strategies address the issue of restorative treatments form different perspectives. Some interventions occur early after stroke, or are intended to preserve existing neural structures. For example, treatment strategies that aim to provide trophic support may demonstrate early beneficial results. Other strategies aim for growth and integration of new neurons to replace those lost after stroke. In this case, early beneficial results are not likely. Functional integration of grafted neurons, if it can ever happen, is likely to require training and exercise of the appropriate capacities. Further advances in preclinical studies of neural transplantation will require improved animal models with increased sensitivity to subtle behavioral and imaging changes. Non-human primate models have been established and may increase in importance as a phase before clinical trials. The future of brain repair for stroke is likely to require some form of combination therapy designed to replace the lost cells and supporting structure, attract new blood supply, support and enhance intrinsic repair and plasticity mechanisms.

Animals↗

PubMed1996

Thermodynamics of transfer of cholesterol from gel to fluid phases of phospholipid bilayers.

The partitioning of cholesterol between gel and fluid phases of model membrane bilayers has been studied by differential scanning calorimetry. The partition coefficients and thermodynamics of transfer between phases of dimyristoyl-, dipalmitoyl-, distearoyl- and diarachidoylphosphatidylcholines were determined using a regular solution model for the partitioning process. The partition coefficient, which is the ratio of cholesterol in fluid to gel phase lipid, varies from 2.3 to 8.4 as the acyl chain length increases from the C14 to the C20 bilayer and determined at the phase transition temperature. The enthalpies of transfer increase from -46 to +32 kcal/mol as the chain length increases, and there is a compensating increase in the entropy of transfer. The results are interpreted in terms of a disruption of gel phase lipid by the cholesterol, which for the thinner bilayers is increased because the cholesterol molecule spans across the two leafs of the bilayer. At bilayer thicknesses between 18 and 19 carbons, the cholesterol can fit into one-half of the gel phase bilayer, and the enthalpy becomes positive, suggesting less disruption in the gel phase relative to the thinner bilayers. The data support the interpretation that cholesterol does mediate fluidity by acting to disrupt gel domains of lipid.

Calorimetry, Differential Scanning↗

PubMed2005

Modeling of adsorption in nanopores.

Adsorption in nonporous materials has been studied using Grand Canonical Monte Carlo simulations. We discuss three types of materials: (a) a model of cylindrical pores with smooth walls, representing MCM-41 like materials, (b) a model of cylindrical pores with regular structured walls (model of carbon nanotubes) and (c) a material with crystalline wall structure (zeolites). Typical problems related to the stability of adsorbed layers have been analyzed. We have shown that the mechanism of adsorption is strongly dependent on the structure of the pore walls. In the case of amorphous walls it may lead to metastable configurations. In nanotubes, the ordered corrugation structure of walls determines the low temperature structure of the adsorbed system. In 3D ordered porous system, such as zeolites, the mechanism of adsorption is mostly determined by characteristic sites of adsorption. [Figure: see text]. Adsorbed atoms and energy fluctuations at the pressure of the first layer formation of krypton atoms: (a) instantaneous numbers of adsorbed atoms (per nm2 of the pore wall) as a function of the time of simulation (Monte Carlo steps) observed in a relatively long run, (b) the bimodal distribution of the energy fluctuations is a consequence of the behavior of the systems as shown in (a).

Adsorption↗

PubMed1992

Collective behaviors in coupled map lattices with local and nonlocal connections.

After having recalled the basic properties of the nontrivial collective dynamics exhibited by lattices of maps with local coupling and synchronous updating, we present the behavior of the same models in which all the connections are random. The mean-field, synchronized limit is shown to be reached only for large enough connectivities and sufficiently strong local chaos. Intermediate models, in which only a few of the connections of each site are taken at random, are then considered. Preliminary results indicate that the nontrivial collective behaviors shown by the regularly connected models may be robust to a small proportion of nonlocal, random connections.

Journal Article↗

PubMed2005

Adaptive exponential integrate-and-fire model as an effective description of neuronal activity.

We introduce a two-dimensional integrate-and-fire model that combines an exponential spike mechanism with an adaptation equation, based on recent theoretical findings. We describe a systematic method to estimate its parameters with simple electrophysiological protocols (current-clamp injection of pulses and ramps) and apply it to a detailed conductance-based model of a regular spiking neuron. Our simple model predicts correctly the timing of 96% of the spikes (+/-2 ms) of the detailed model in response to injection of noisy synaptic conductances. The model is especially reliable in high-conductance states, typical of cortical activity in vivo, in which intrinsic conductances were found to have a reduced role in shaping spike trains. These results are promising because this simple model has enough expressive power to reproduce qualitatively several electrophysiological classes described in vitro.

Action Potentials↗

PubMed2025

AWGE-ESPCA: An edge sparse PCA model based on adaptive noise elimination regularization and weighted gene network for Hermetia illucens genomic data analysis.

Hermetia illucens is an important insect resource. Studies have shown that exploring the effects of Cu2+-stressed on the growth and development of the Hermetia illucens genome holds significant scientific importance. There are three major challenges in the current studies of Hermetia illucens genomic data analysis: firstly, the lack of available genomic data which limits researchers in Hermetia illucens genomic data analysis. Secondly, to the best of our knowledge, there are no Artificial Intelligence (AI) feature selection models designed specifically for Hermetia illucens genome. Unlike human genomic data, noise in Hermetia illucens data is a more serious problem. Third, how to choose those genes located in the pathway enrichment region. Existing models assume that each gene probe has the same priori weight. However, researchers usually pay more attention to gene probes which are in the pathway enrichment region. Based on the above challenges, we initially construct experiments and establish a new Cu2+-stressed Hermetia illucens growth genome dataset. Subsequently, we propose AWGE-ESPCA: an edge Sparse PCA model based on adaptive noise elimination regularization and weighted gene network. The AWGE-ESPCA model innovatively proposes an adaptive noise elimination regularization method, effectively addressing the noise challenge in Hermetia illucens genomic data. We also integrate the known gene-pathway quantitative information into the Sparse PCA(SPCA) framework as a priori knowledge, which allows the model to filter out the gene probes in pathway-rich regions as much as possible. Ultimately, this study conducts five independent experiments and compared four latest Sparse PCA models as well as representative supervised and unsupervised baseline models to validate the model performance. The experimental results demonstrate the superior pathway and gene selection capabilities of the AWGE-ESPCA model. Ablation experiments validate the role of the adaptive regularizer and network weighting module. To summarize, this paper presents an innovative unsupervised model for Hermetia illucens genome analysis, which can effectively help researchers identify potential biomarkers. In addition, we also provide a working AWGE - ESPCA model code in the address: https://github.com/yhyresearcher/AWGE_ESPCA.

Animals↗

PubMed2006

Singularities affect dynamics of learning in neuromanifolds.

The parameter spaces of hierarchical systems such as multilayer perceptrons include singularities due to the symmetry and degeneration of hidden units. A parameter space forms a geometrical manifold, called the neuromanifold in the case of neural networks. Such a model is identified with a statistical model, and a Riemannian metric is given by the Fisher information matrix. However, the matrix degenerates at singularities. Such a singular structure is ubiquitous not only in multilayer perceptrons but also in the gaussian mixture probability densities, ARMA time-series model, and many other cases. The standard statistical paradigm of the Cramér-Rao theorem does not hold, and the singularity gives rise to strange behaviors in parameter estimation, hypothesis testing, Bayesian inference, model selection, and in particular, the dynamics of learning from examples. Prevailing theories so far have not paid much attention to the problem caused by singularity, relying only on ordinary statistical theories developed for regular (nonsingular) models. Only recently have researchers remarked on the effects of singularity, and theories are now being developed. This article gives an overview of the phenomena caused by the singularities of statistical manifolds related to multilayer perceptrons and gaussian mixtures. We demonstrate our recent results on these problems. Simple toy models are also used to show explicit solutions. We explain that the maximum likelihood estimator is no longer subject to the gaussian distribution even asymptotically, because the Fisher information matrix degenerates, that the model selection criteria such as AIC, BIC, and MDL fail to hold in these models, that a smooth Bayesian prior becomes singular in such models, and that the trajectories of dynamics of learning are strongly affected by the singularity, causing plateaus or slow manifolds in the parameter space. The natural gradient method is shown to perform well because it takes the singular geometrical structure into account. The generalization error and the training error are studied in some examples.

Journal Article↗

PubMed2006

An integrate-and-fire model for synchronized bursting in a network of cultured cortical neurons.

It has been suggested that spontaneous synchronous neuronal activity is an essential step in the formation of functional networks in the central nervous system. The key features of this type of activity consist of bursts of action potentials with associated spikes of elevated cytoplasmic calcium. These features are also observed in networks of rat cortical neurons that have been formed in culture. Experimental studies of these cultured networks have led to several hypotheses for the mechanisms underlying the observed synchronized oscillations. In this paper, bursting integrate-and-fire type mathematical models for regular spiking (RS) and intrinsic bursting (IB) neurons are introduced and incorporated through a small-world connection scheme into a two-dimensional excitatory network similar to those in the cultured network. This computer model exhibits spontaneous synchronous activity through mechanisms similar to those hypothesized for the cultured experimental networks. Traces of the membrane potential and cytoplasmic calcium from the model closely match those obtained from experiments. We also consider the impact on network behavior of the IB neurons, the geometry and the small world connection scheme.

Action Potentials↗

PubMed1998

Role of the sterol superlattice in the partitioning of the antifungal drug nystatin into lipid membranes.

Nystatin isolated from Streptomyces is a polyene antibiotic that is frequently used in the treatment and prophylaxis of fungal infections. Here, the fractional sterol concentration dependencies of the partition coefficient for partitioning of nystatin into ergosterol/dimyristoyl-L-alpha-phosphatidylcholine (DMPC), cholesterol/DMPC, ergosterol/1-palmitoyl-2-oleoyl-L-alpha-phosphatidylcholine (POPC), and ergosterol/POPC/1-palmitoyl-2-oleoyl-L-alpha-phosphatidylethano lam ine (POPE) multilamellar vesicles have been determined fluorometrically at 37 degrees C using approximately 0.3-1.0 mol % sterol concentration increments over a wide concentration range (e.g., 18-54 mol % sterol). This unconventional approach of varying membrane sterol content, in contrast to previous studies using large sterol concentration increments (e.g., 10 mol %), leads to a striking observation. The partition coefficient of nystatin changes dramatically with membrane sterol content in a well-defined alternating manner, displaying a local minimum at or very close to the critical sterol mole fractions (e.g., 20.0, 22.2, 25.0, 33.3, 40.0, and 50.0 mol % sterol) predicted for sterols regularly distributed in either hexagonal or centered rectangular superlattices. In ergosterol/DMPC bilayers, for example, there is a >3-fold increase in nystatin partitioning with a minute change (approximately 1 mol %) in sterol content on either side of the critical sterol mole fraction, 25.0 mol %. These results provide semifunctional evidence supporting the sterol regular distribution model [Chong, P. L.-G. (1994) Proc. Natl. Acad. Sci. U.S.A. 91, 10069-10073]. More importantly, these results reveal a new membrane phenomenon, that is, that nystatin partitioning is affected by the extent of sterol regular distribution in the plane of the membrane. This phenomenon occurs not only in saturated (e.g., DMPC) but also in unsaturated (e.g., POPC) lipid membranes, and persists in the presence of polar headgroup heterogeneity (e.g., POPC/POPE). This membrane property points to a new method for studying the interactions of polyene antibiotics with sterol-containing membranes, and the need to consider the membrane sterol content of the target cells when administering nystatin or other polyene antibiotics.

Anti-Bacterial Agents↗

PubMed2003

3DNA: a software package for the analysis, rebuilding and visualization of three-dimensional nucleic acid structures.

We present a comprehensive software package, 3DNA, for the analysis, reconstruction and visualization of three-dimensional nucleic acid structures. Starting from a coordinate file in Protein Data Bank (PDB) format, 3DNA can handle antiparallel and parallel double helices, single-stranded structures, triplexes, quadruplexes and other complex tertiary folding motifs found in both DNA and RNA structures. The analysis routines identify and categorize all base interactions and classify the double helical character of appropriate base pair steps. The program makes use of a recently recommended reference frame for the description of nucleic acid base pair geometry and a rigorous matrix-based scheme to calculate local conformational parameters and rebuild the structure from these parameters. The rebuilding routines produce rectangular block representations of nucleic acids as well as full atomic models with the sugar-phosphate backbone and publication quality 'standardized' base stacking diagrams. Utilities are provided to locate the base pairs and helical regions in a structure and to reorient structures for effective visualization. Regular helical models based on X-ray diffraction measurements of various repeating sequences can also be generated within the program.

Base Pairing↗

PubMed2004

A finite state model for respiratory motion analysis in image guided radiation therapy.

Effective image guided radiation treatment of a moving tumour requires adequate information on respiratory motion characteristics. For margin expansion, beam tracking and respiratory gating, the tumour motion must be quantified for pretreatment planning and monitored on-line. We propose a finite state model for respiratory motion analysis that captures our natural understanding of breathing stages. In this model, a regular breathing cycle is represented by three line segments, exhale, end-of-exhale and inhale, while abnormal breathing is represented by an irregular breathing state. In addition, we describe an on-line implementation of this model in one dimension. We found this model can accurately characterize a wide variety of patient breathing patterns. This model was used to describe the respiratory motion for 23 patients with peak-to-peak motion greater than 7 mm. The average root mean square error over all patients was less than 1 mm and no patient has an error worse than 1.5 mm. Our model provides a convenient tool to quantify respiratory motion characteristics, such as patterns of frequency changes and amplitude changes, and can be applied to internal or external motion, including internal tumour position, abdominal surface, diaphragm, spirometry and other surrogates.

Algorithms↗

PubMed1988

Exploring Filipino American drinking behavior.

The purpose of this article was to explore characteristics distinguishing levels of drinking by Filipino Americans. A sample of 298 adult Filipinos was interviewed using a schedule based on a national study of drinking behavior and attitudes. Approximately 50% of the female sample were abstainers while 80% of the men were drinkers. Heavy drinking was almost exclusively a male activity. Thus, two models of Filipino drinking were examined. Logistic regression was used to identify social factors distinguishing female drinkers from abstainers. A second model clarified the influence of similar characteristics on male Filipinos who drank limited amounts of alcohol and those who drank heavily. The only variable significant in both models was regular participation in religious service.

Adult↗

PubMed2005

Smooth bistable S-systems.

S-systems have been used as models of biochemical systems for over 30 years. One of their hallmarks is that, although they are highly non-linear, their steady states are characterised by linear equations. This allows streamlined analyses of stability, sensitivities and gains as well as objective, mathematically controlled comparisons of similar model designs. Regular S-systems have a unique steady state at which none of the system variables is zero. This makes it difficult to represent switching phenomena, as they occur, for instance, in the expression of genes, cell cycle phenomena and signal transduction. Previously, two strategies were proposed to account for switches. One was based on a technique called recasting, which permits the modelling of any differentiable non-linearities, including bistability, but typically does not allow steady-state analyses based on linear equations. The second strategy formulated the switching system in a piece-wise fashion, where each piece consisted of a regular S-system. A representation gleaned from a simplified form of recasting is proposed and it is possible to divide the characterisation of the steady states into two phases, the first of which is linear, whereas the other is non-linear, but easy to execute. The article discusses a representative pathway with two stable states and one unstable state. The pathway model exhibits strong separation between the stable states as well as hysteresis.

Cell Physiological Phenomena↗

PubMed1997

Development of an ear edema model of contact hypersensitivity to avoid false-positive results due to interactions between hapten and test agents.

Ear edema models are regularly used for topical testing of antiinflammatory compounds. However, test compounds are usually applied simultaneously with proinflammatory agents at the same site which may result in mutual interactions. In order to avoid the occurrence of false antiinflammatory effects, a model of oxazolone-induced contact hypersensitivity has been described in which the hapten and test compound are each applied separately to only one side of the ear. By splitting and weighing the dorsal and ventral cutis of the ears, it was shown that the edemateous response of the control nonhapten side was comparable with the hapten-treated side. Some agents with antiinflammatory properties, as for example, dapsone, cimetidine, cyclosporine A, and budesonide, were tested simultaneously with oxazolone on both sides of the ear or applied separately on the dorsal and ventral ear sides, respectively. When dissolving the compounds in solutions of oxazolone, marked colorations of the test solutions were noted, indicating the occurrence of a chemical interaction. On simultaneous application at the same area, almost complete inhibition of the edemateous response was obtained for all compounds tested. In contrast, when applied separately, only budesonide appeared to exhibit antiinflammatory activity. The results indicate that the proposed model can be used to avoid the occurrence of interactions between oxazolone, and possibly other sensitizers, and substances that are being evaluated for topical antiinflammatory activity. By use of this model spurious antiinflammatory activity can be detected.

Adjuvants, Immunologic↗

PubMed2026

Penalized Cumulative Probability Model for a Continuous Outcome Subject to Detection Limits.

Mixed-type outcome data occur when the outcome variable's distribution is a mixture of both continuous and discrete ordinal variables. Such mixed-type outcomes are common in biomedical, psychological, and the health sciences, particularly for variables having either a detection or quantitation limit. When interest lies in identifying a combination of genomic features associated with a mixed-type outcome, any method used would require a variable selection strategy for high-dimensional data. Unfortunately, few variable selection methods exist for modeling a mixed-type outcome when the covariate space is high dimensional. This study develops a high-dimensional penalized cumulative probability model (CPM), to allow for the identification of genomic features associated with mixed-type outcome of interest. We demonstrated how such model may be estimated using the iterative penalization procedure-the generalized monotone incremental forward stagewise (GMIFS) algorithm. The Model-X knockoffs procedure was combined with the estimation algorithm to control the false discovery rates (FDR) when performing variable selection. Through extensive simulation studies, our penalized CPM was shown to outperform alternative methods in terms of controlled variable selection performance by achieving high statistical power with the FDR being controlled at the target level. We demonstrate the utility of our method by applying it to predict estimated glomeruli filtration rate (eGFR) in kidney transplant recipients at 24 months post-transplant using baseline gene expression data as predictors. Our CPM model identified five genes associated with this mixed-type outcome which have important links to renal disease, which may provide prognostic guidance for kidney transplantation recipients.

Models, Statistical↗