ArticleJournal of applied physiology (Bethesda, Md. : 1985)2012
Functional classification of skeletal muscle networks. II. Applications to pathophysiology.
Article in Journal of applied physiology (Bethesda, Md. : 1985), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Skeletal muscle: A review of molecular structure and function, in health and disease.Wiley interdisciplinary reviews. Systems biology and medicine · 2020Review
- Article
- Co-expression Network Approach Reveals Functional Similarities among Diseases Affecting Human Skeletal Muscle.Frontiers in physiology · 2017Article
- Statistical insights into major human muscular diseases.Human molecular genetics · 2014Article
- Community Structure Analysis of Gene Interaction Networks in Duchenne Muscular Dystrophy.PloS one · 2013Article
- Functional classification of skeletal muscle networks. I. Normal physiology.Journal of applied physiology (Bethesda, Md. : 1985) · 2012Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
In our preceding companion paper (Wang Y, Winters J, Subramaniam S. J Appl Physiol. doi: 10.1152/japplphysiol.01514.2011), we used extensive expression profile data on normal human subjects, in combination with legacy knowledge to classify skeletal muscle function into four models, namely excitation-activation, mechanical, metabolic, and signaling-production model families. In this paper, we demonstrate how this classification can be applied to study two well-characterized myopathies: amyotrophic lateral sclerosis (ALS) and Duchenne muscular dystrophy (DMD). Using skeletal muscle profile data from ALS and DMD patients compared with that from normal subjects, normal young in the case of DMD, we delineate molecular mechanisms that are causative and consequential to skeletal muscle dysfunction. In ALS, our analysis establishes the metabolic role and specifically identifies the mechanisms of calcium dysregulation and defects in mitochondrial transport of materials as important for muscle dysfunction. In DMD, we illustrate how impaired mechanical function is strongly coordinated with other three functional networks, resulting in transformation of the skeletal muscle into hybrid forms as a compensatory mechanism. Our functional models also provide, in exquisite detail, the mechanistic role of myriad proteins in these four families in normal and disease function.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.