Biomedical subjects

Marco Toigo

Publications and source records attributed to Marco Toigo.

3 recordsLinked to original sources

PubMed2006

New fundamental resistance exercise determinants of molecular and cellular muscle adaptations.

Abstract Physical activity relies on muscular force. In adult skeletal muscle, force results from the contraction of postmitotic, multinucleated myofibres of different contractile and metabolic properties. Myofibres can adapt to (patho-)physiological conditions of altered functional demand by radial growth, longitudinal growth, and regulation of fibre type functional gene modules. The adaptation's specificity depends on the distinct molecular and cellular events triggered by unique combinations of conditional cues. In order to derive effective and tailored exercise prescriptions, it must be determined (1) which mechano-biological condition leads to what molecular/cellular response, and (2) how this molecular/cellular response relates to the structural, contractile, and metabolic adaptation. It follows that a thorough mechano-biological description of the loading condition is imperative. Unfortunately, the definition of (resistance) exercise conditions in the past and present literature is insufficient. It is classically limited to load magnitude, number of repetitions and sets, rest in-between sets, number of interventions/week, and training period. In this review, we show why the current description is insufficient, and identify new determinants of quantitative and/or qualitative effects on skeletal muscle with respect to resistance exercise in healthy, adult humans. These new mandatory determinants comprise the fractional and temporal distribution of the contraction modes per repetition, duration of one repetition, rest in-between repetitions, time under tension, muscular failure, range of motion, recovery time, and anatomical definition. We strongly recommend to standardise the design and description of all future resistance exercise investigations by using the herein proposed set of 13 mechano-biological determinants (classical and new ones).

Adaptation, Physiological↗

PubMed2005

ICAT-MS-MS time course analysis of atrophying mouse skeletal muscle cytosolic subproteome.

Skeletal muscle atrophy is a process in which protein degradation exceeds protein synthesis, resulting in a decrease of the muscle's physiological cross-sectional area and mass, and is often a serious consequence of numerous health problems. We used the isotope-coded affinity tag (ICAT) labelling approach and MS-MS to protein profile cytosolic subcellular fractions from mouse tibialis anterior skeletal muscle undergoing 0, 4, 8, or 16 days of immobilisation-induced atrophy. For the validation of peptide and protein identifications statistical algorithms were applied to the sequence database search results in order to obtain consistent sensitivity/error rates for protein and peptide identifications at each immobilisation time point. In this study, we identified and quantified a large number of mouse skeletal muscle proteins. At a protein probability (P) of P> or = 0.9 (corresponding to a false positive error rate of less than 1%) 807 proteins were identified (231, 226, 217 for 4, 8, 16 days of immobilisation and 133 for the control sample, respectively), from which 51 displayed altered protein abundance with atrophy. Due to randomness of data acquisition, a full time course could be generated only for 62 proteins, most of which displayed unchanged protein abundance. In spite of this, useful information about dataset characteristics and underlying biological processes could be obtained through gene over-representation analysis. 20 gene categories-mainly but not exclusively encoded by the subset of overlapping proteins--were consistently found to be significantly (p < 0.05) over-represented in all 4 sub-datasets.

Adaptor Proteins, Signal Transducing↗

PubMed2004

Reference genes identified in SH-SY5Y cells using custom-made gene arrays with validation by quantitative polymerase chain reaction.

Transcriptomic methods are widely used as an initial approach to gain a mechanistic insight into physiological and pathological processes. Because differences in gene regulation to be assessed by RNA screening methods (e.g., SAGE, Affymetrix GeneChips) can be very subtle, these techniques require stable reference genes for accurate normalization. It is widely known that housekeeping genes, which are routinely used for normalization, can vary significantly depending on the tissue, and experimental test. In this study, we aimed at identifying stable reference genes for a fibrillar Abeta(42) peptide-treated, human tau-expressing SH-SY5Y neuroblastoma cell line derived to model aspects of Alzheimer's disease in tissue culture. We selected genes exhibiting potential normalization characteristics from public databases to create a custom-made microarray allowing the identification of reference genes for low, intermediate, and abundant mRNAs. A subset of these candidates was subjected to quantitative real-time polymerase chain reaction and was analyzed with geNorm software. By doing so, we were able to identify GAPD, M-RIP, and POLR2F as stable and usable reference genes irrespective of differentiation status and Abeta(42) treatment.

Alzheimer Disease↗