Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A multiple regression model of normal central and peripheral motor conduction times.

ABSTRACT: The effects of age, height, and gender on magnetic central and peripheral motor conduction times (CMCT, PMCT) were analyzed using a multiple regression model.Motor evoked potentials were recorded in 91 healthy volunteers. Magnetic stimulation was performed over the primary motor cortex (cortical latency) and over the cervical and lumbar spines (spinal latency). The spinal latency was taken as an estimate of PMCT and was subtracted from cortical latency to yield CMCT.Lower limb CMCT correlated significantly with height only; there were no significant predictors for upper limb CMCT. Upper and lower limb PMCT correlated with both age and height.This is among the largest studies of CMCT in normal subjects. The multiple regression model unifies previously reported simple regression analyses, reconciles past discrepancies, and allows normal ranges to be individualized.

SUBMITTER: Jaiser SR

PROVIDER: S-EPMC4858813 | biostudies-other | 2015 May

REPOSITORIES: biostudies-other

ACCESS DATA

Json Xml

Publications

A multiple regression model of normal central and peripheral motor conduction times.

Jaiser Stephan R SR Barnes Jonathan D JD Baker Stuart N SN Baker Mark R MR

Muscle & nerve 20150314 5

<h4>Introduction</h4>The effects of age, height, and gender on magnetic central and peripheral motor conduction times (CMCT, PMCT) were analyzed using a multiple regression model.<h4>Methods</h4>Motor evoked potentials were recorded in 91 healthy volunteers. Magnetic stimulation was performed over the primary motor cortex (cortical latency) and over the cervical and lumbar spines (spinal latency). The spinal latency was taken as an estimate of PMCT and was subtracted from cortical latency to yie ...[more]

PMID: 25154476

Similar Datasets

Central motor conduction time may predict response to fampridine in patients with multiple sclerosis.

Project description: Not available

| S-EPMC4033025 | biostudies-literature

Central motor conduction time in spinocerebellar ataxia: a meta-analysis.

Project description:The dominantly inherited spinocerebellar ataxias (SCAs) are a large class of neurodegenerative diseases. Transcranial magnetic stimulation has been used to evaluate the function of the pyramidal tract, and central motor conduction time (CMCT) is one index used to detect pyramidal tract dysfunction. We conducted a comprehensive search of PubMed, Embase and Web of Science. Eight eligible studies were included in the meta-analysis. For upper limb CMCT, the mean difference (95% confidence interval (CI)) between the combined SCA group and the control group was 2.24 [1.76-2.72], while the mean differences (95% CIs) between the subtypes and the control group were as follows: 4.43 [3.58-5.28] for SCA1, 0.25 [-0.15,0.65] for SCA2, 1.04 [-0.37,2.46] for SCA3 and 0.49 [-0.29,1.28] for SCA6. Additionally, SCA1 significantly differed from SCA2 and SCA3 in terms of CMCT (P=0.0006 and P=0.010, respectively). We also compared lower limb CMCT between the SCA2 and control groups. The mean difference (95% CI) was 6.58 [4.49-8.67], which was clearly statistically significant. The differences in CMCT values among different subtypes suggests diverse pathological mechanisms. In general, CMCT is a promising objective index to judge the severity of disease deserving further investigation.

| S-EPMC7803510 | biostudies-literature

Somatosensory Evoked Potentials and Central Motor Conduction Times in children with dystonia and their correlation with outcomes from Deep Brain Stimulation of the Globus pallidus internus.

Project description:OBJECTIVES:To report Somatosensory Evoked Potentials (SEPs) and Central Motor Conduction Times (CMCT) in children with dystonia and to test the hypothesis that these parameters predict outcome from Deep Brain Stimulation (DBS). METHODS:180 children with dystonia underwent assessment for Globus pallidus internus (GPi) DBS, mean age 10 years (range 2.5-19). CMCT to each limb was calculated using Transcranial Magnetic Stimulation. Median and posterior tibial nerve SEPs were recorded over contralateral and midline centro-parietal scalp. Structural abnormalities were assessed with cranial MRI. One-year outcome from DBS was assessed as percentage improvement in Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS-m). RESULTS:Abnormal CMCTs and SEPs were found in 19% and 47% of children respectively and were observed more frequently in secondary than primary dystonia. Of children proceeding to DBS, better outcome was seen in those with normal (n = 78/89) versus abnormal CMCT (n = 11/89) (p = 0.002) and those with normal (n = 35/51) versus abnormal SEPs (n = 16/51) (p = 0.001). These relationships were independent of dystonia aetiology and cranial MRI findings. CONCLUSIONS:CMCTs and SEPs provide objective evidence of motor and sensory pathway dysfunction in children with dystonia and relate to DBS outcome. SIGNIFICANCE:CMCTs and SEPs can contribute to patient selection and counselling of families about potential benefit from neuromodulation for dystonia.

| S-EPMC5786451 | biostudies-literature

A Bayesian Genomic Regression Model with Skew Normal Random Errors.

Project description:Genomic selection (GS) has become a tool for selecting candidates in plant and animal breeding programs. In the case of quantitative traits, it is common to assume that the distribution of the response variable can be approximated by a normal distribution. However, it is known that the selection process leads to skewed distributions. There is vast statistical literature on skewed distributions, but the skew normal distribution is of particular interest in this research. This distribution includes a third parameter that drives the skewness, so that it generalizes the normal distribution. We propose an extension of the Bayesian whole-genome regression to skew normal distribution data in the context of GS applications, where usually the number of predictors vastly exceeds the sample size. However, it can also be applied when the number of predictors is smaller than the sample size. We used a stochastic representation of a skew normal random variable, which allows the implementation of standard Markov Chain Monte Carlo (MCMC) techniques to efficiently fit the proposed model. The predictive ability and goodness of fit of the proposed model were evaluated using simulated and real data, and the results were compared to those obtained by the Bayesian Ridge Regression model. Results indicate that the proposed model has a better fit and is as good as the conventional Bayesian Ridge Regression model for prediction, based on the DIC criterion and cross-validation, respectively. A computing program coded in the R statistical package and C programming language to fit the proposed model is available as supplementary material.

| S-EPMC5940167 | biostudies-literature

Transient peripheral immune response and central nervous system leaky compartmentalization in a viral model for multiple sclerosis.

Project description:Theiler's virus-induced demyelination represents an important animal model to study the chronic-progressive form of multiple sclerosis (MS). The aim of the present study was to identify specific genes and pathways in the deep cervical lymph node (cLN) and spleen of experimentally infected SJL-mice, using DNA microarrays. Analyses identified 387 genes in the deep cLN and only 6 genes in the spleen of infected animals. The lymph node presented 27.4% of genes with fold changes +/-1.5 at 14 days post infection (dpi) and a reduced transcription at later time points. K-means clustering analyses resulted in five clusters. Accordingly, functional annotation revealed that the B-cell immune response pathway was the most up-regulated cluster at the early phase. Additionally, an increase of CD68- and lysozyme-positive cells in the deep cLN was observed by immunohistochemistry. Polioencephalitis was most intense at 14 dpi, and the spinal cord demyelinating leukomyelitis started at 42 dpi. In summary, early gene expression is indicative of virus-trigged immune responses in the central nervous system (CNS)-draining lymph node. The decreased gene transcription in the deep cLN during the chronic phase and the low number of spleen genes supports the hypothesis of a compartmentalized inflammation within the CNS, as described in progressive MS.

| S-EPMC8094647 | biostudies-literature

The Influence of Chronic Inflammation on Peripheral Motor Nerve Conduction Following Spinal Cord Injury: A Randomized Clinical Trial.

Project description:Objective: To examine the potential influence of chronic inflammation on peripheral motor nerve function in vivo following spinal cord injury (SCI). Methods: This study was part of a randomized, parallel-group, controlled clinical trial. The study included 20 participants with varying levels and severities of SCI randomized (3:2) to either a treatment group, consisting of a 12-week anti-inflammatory diet program, or control group. Outcome measures were assessed at baseline, 1 month, and 3 months and consisted of measures of motor nerve conduction velocity (NCV) and amplitude as well as markers of inflammation as assessed by various pro- and anti-inflammatory cytokines. Results: Despite a significant reduction in inflammation in the treatment group, 2-way repeated measures analysis of variance (ANOVA) showed no significant Group × Time interaction for motor NCV (p = .77) or M-wave amplitude (p = .61). Further, the change in motor NCV and M-wave amplitude were not shown to be associated with the change in inflammatory mediators as assessed via a backwards elimination multiple regression analysis. Conclusion: These results suggest that at physiologically relevant concentrations, inflammatory mediators may not have a substantial influence on peripheral motor nerve conduction in vivo following SCI. Future studies may still be warranted to examine the potential for central effects.

| S-EPMC5667434 | biostudies-literature

Evaluation of central and peripheral fatigue in the quadriceps using fractal dimension and conduction velocity in young females.

Project description:PurposeOver the past decade, linear and non-linear surface electromyography descriptors for central and peripheral components of fatigue have been developed. In the current study, we tested fractal dimension (FD) and conduction velocity (CV) as myoelectric descriptors of central and peripheral fatigue, respectively. To this aim, we analyzed FD and CV slopes during sustained fatiguing contractions of the quadriceps femoris in healthy humans.MethodsA total of 29 recreationally active women (mean age±standard deviation: 24±4 years) and two female elite athletes (one power athlete, age 24 and one endurance athlete, age 30 years) performed two knee extensions: (1) at 20% maximal voluntary contraction (MVC) for 30 s, and (2) at 60% MVC held until exhaustion. Surface EMG signals were detected from the vastus lateralis and vastus medialis using bidimensional arrays.ResultsCentral and peripheral fatigue were described as decreases in FD and CV, respectively. A positive correlation between FD and CV (R=0.51, p<0.01) was found during the sustained 60% MVC, probably as a result of simultaneous motor unit synchronization and a decrease in muscle fiber CV during the fatiguing task.ConclusionsCentral and peripheral fatigue can be described as changes in FD and CV, at least in young, healthy women. The significant correlation between FD and CV observed at 60% MVC suggests that a mutual interaction between central and peripheral fatigue can arise during submaximal isometric contractions.

| S-EPMC4400165 | biostudies-literature

A unified censored normal regression model for qPCR differential gene expression analysis.

Project description:Reverse transcription quantitative polymerase chain reaction (RT-qPCR) is considered as the gold standard for accurate, sensitive, and fast measurement of gene expression. Prior to downstream statistical analysis, RT-qPCR fluorescence amplification curves are summarized into one single value, the quantification cycle (Cq). When RT-qPCR does not reach the limit of detection, the Cq is labeled as "undetermined". Current state of the art qPCR data analysis pipelines acknowledge the importance of normalization for removing non-biological sample to sample variation in the Cq values. However, their strategies for handling undetermined Cq values are very ad hoc. We show that popular methods for handling undetermined values can have a severe impact on the downstream differential expression analysis. They introduce a considerable bias and suffer from a lower precision. We propose a novel method that unites preprocessing and differential expression analysis in a single statistical model that provides a rigorous way for handling undetermined Cq values. We compare our method with existing approaches in a simulation study and on published microRNA and mRNA gene expression datasets. We show that our method outperforms traditional RT-qPCR differential expression analysis pipelines in the presence of undetermined values, both in terms of accuracy and precision.

| S-EPMC5560691 | biostudies-literature

A semi-nonparametric Poisson regression model for analyzing motor vehicle crash data.

Project description:This paper develops a semi-nonparametric Poisson regression model to analyze motor vehicle crash frequency data collected from rural multilane highway segments in California, US. Motor vehicle crash frequency on rural highway is a topic of interest in the area of transportation safety due to higher driving speeds and the resultant severity level. Unlike the traditional Negative Binomial (NB) model, the semi-nonparametric Poisson regression model can accommodate an unobserved heterogeneity following a highly flexible semi-nonparametric (SNP) distribution. Simulation experiments are conducted to demonstrate that the SNP distribution can well mimic a large family of distributions, including normal distributions, log-gamma distributions, bimodal and trimodal distributions. Empirical estimation results show that such flexibility offered by the SNP distribution can greatly improve model precision and the overall goodness-of-fit. The semi-nonparametric distribution can provide a better understanding of crash data structure through its ability to capture potential multimodality in the distribution of unobserved heterogeneity. When estimated coefficients in empirical models are compared, SNP and NB models are found to have a substantially different coefficient for the dummy variable indicating the lane width. The SNP model with better statistical performance suggests that the NB model overestimates the effect of lane width on crash frequency reduction by 83.1%.

| S-EPMC5965849 | biostudies-literature

TMS-Induced Central Motor Conduction Time at the Non-Infarcted Hemisphere Is Associated with Spontaneous Motor Recovery of the Paretic Upper Limb after Severe Stroke.

Project description:Stroke affects the neuronal networks of the non-infarcted hemisphere. The central motor conduction time (CMCT) induced by transcranial magnetic stimulation (TMS) could be used to determine the conduction time of the corticospinal tract of the non-infarcted hemisphere after a stroke. Our primary aim was to demonstrate the existence of prolonged CMCT in the non-infarcted hemisphere, measured within the first 48 h when compared to normative data, and secondly, if the severity of motor impairment of the affected upper limb was significantly associated with prolonged CMCTs in the non-infarcted hemisphere when measured within the first 2 weeks post stroke. CMCT in the non-infarcted hemisphere was measured in 50 patients within 48 h and at 11 days after a first-ever ischemic stroke. Patients lacking significant spontaneous motor recovery, so-called non-recoverers, were defined as those who started below 18 points on the FM-UE and showed less than 6 points (10%) improvement within 6 months. CMCT in the non-infarcted hemisphere was prolonged in 30/50 (60%) patients within 48 h and still in 24/49 (49%) patients at 11 days. Sustained prolonged CMCT in the non-infarcted hemisphere was significantly more frequent in non-recoverers following FM-UE. The current study suggests that CMCT in the non-infarcted hemisphere is significantly prolonged in 60% of severely affected, ischemic stroke patients when measured within the first 48 h post stroke. The likelihood of CMCT is significantly higher in non-recoverers when compared to those that show spontaneous motor recovery early post stroke.

| S-EPMC8157217 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data