Georges Cazorla

Secular trends in the performance of children and adolescents (1980-2000): an analysis of 55 studies of the 20m shuttle run test in 11 countries.

It is widely believed that the performance of children and adolescents on aerobic fitness tests is declining. To test this hypothesis, this meta-analysis compared the results of 55 reports of the performance of children and adolescents aged 6–19 years who have used the 20m shuttle run test (20mSRT). All data were collected in the period 1981–2000.Following corrections for methodological variation, the results of all studies were expressed using the common metric of running speed (km/h) at the last completed stage. Raw data were combined with pseudodata generated from reported means and standard deviations using Monte Carlo simulation. Where data were available on children and adolescents from the same country of the same age and sex, but tested at different times, linear regression was used to calculate rates of change. This was possible for 11 (mainly developed) countries, representing a total of 129 882 children and adolescents in 151 age × sex × country slices.There has been a significant decline in performance in the 11 countries where data were available, and in most age × sex groups, with a sample-weighted mean decline of 0.43% of mean values per year. The decline was most marked in older age groups and the rate of decline was similar for boys and girls.There has been a very rapid secular decline in the 20mSRT performance of children and adolescents over the last 20 years, at least in developed countries. The rate of decline is not related to the change in the country’s relative wealth, as quantified by per capita gross domestic product (GDP).

Worldwide variation in the performance of children and adolescents: An analysis of 109 studies of the 20-m shuttle run test in 37 countries

Abstract This study is a meta-analysis of 109 reports of the performance of children and adolescents on the 20-m shuttle run test (20-mSRT). The studies were performed in 37 countries and included data on 418,026 children, tested between 1981 and 2003. Results were expressed as running speed (km · h−1) at the final completed stage of the 20-mSRT. Raw data were combined with pseudodata using Monte Carlo simulation. The 20-mSRT performances were expressed as z-scores relative to all children of the same age and sex from all countries. An overall “performance index” was derived for each country as the average of the age- and sex-specific z-scores for all children from that country. Factorial analysis of variance was used to compare scores among countries and regions, and between boys and girls of the same age. There was wide and significant (P < 0.0001) global variability in the performance of children. The best performing children were from the Northern European countries Estonia, Iceland, Lithuania, and Finland (0.6 – 0.9 standard deviations above the global average). The worst performing children were from Singapore, Brazil, USA, Italy, Portugal, and Greece (0.4 – 0.9 standard deviations below the global average). There is evidence that performance was negatively related to being overweight, as well as to a countrys average temperature.

Biochemical aspects of overtraining in endurance sports: a review.

AbstractTop-level performances in endurance sports require several years of hard training loads. A major objective of this endurance training is to reach the most elevated metabolic adaptations the athlete will be able to support. As a consequence, overtraining is a recurrent problem that highly-trained athletes may experience during their career. Many studies have revealed that overtraining could be highlighted by various biochemical markers but a principal discrepancy in the diagnosis of overtraining stems from the fact that none of these markers may be considered as universal. In endurance sports, the metabolic aspects of training fatigue appear to be the most relevant parameters that may characterise overtraining when recovery is not sufficient, or when dietary habits do not allow an optimal replenishment of substrate stores. From the skeletal muscle functions to the overall energetic substrate availability during exercise, six metabolic schemes have been studied in relation to overtraining, each one related to a central parameter, i.e. carbohydrates, branched-chain amino acids, glutamine, polyunsaturated fatty acids, leptin, and proteins.

Biochemical aspects of overtraining in endurance sports: The metabolism alteration process syndrome

AbstractRecent studies have shown that endurance overtraining could result from successive and cumulative alterations in metabolism, which become chronic during training. The onset of this process is a biochemical alteration in carbohydrate (saccharide) metabolism. During endurance exercises, the amount of saccharide chains from two blood glycoproteins (α2-macroglobulin and α1-acid glycoprotein) was found to have decreased, i.e. concentrations of these proteins remained unchanged but their quality changed. These saccharide chains were probably used for burning liver glycogen stores during exercise. This step was followed by alterations in lipid metabolism. The most relevant aspect of this step was that the mean chain length of blood fatty acids decreased, i.e. the same amount of fatty acids were found within the blood, but overtrained individuals presented shorter fatty acids than well-trained individuals. This suggests that alterations appeared in the liver synthesis of long-chain fatty acids or that higher peroxidation of blood lipoparticles occurred. For the final step of this overtraining process, it was found that these dysfunctions in carbohydrate/lipid metabolism led to the higher use of amino acids, which probably resulted from protein catabolism. The evolution of three protein concentrations (α1-acid glycoprotein, α2-macroglobulin and IgG3) correlated with this amino acid concentration increase, suggesting a specific catabolism of these proteins. At this time only, overtraining was clinically diagnosed through conventional symptoms. Therefore, this process described successive alterations in exercise metabolism that shifted from the main energetic stores of exercise (carbohydrates and lipids) towards molecular pools (proteins) normally not substantially used for the energetic supply of skeletal muscles. Now, a general biochemical model of the overtraining process may be proposed which includes most of the previously identified metabolic hypotheses.

Triglycerides and Glycerol Concentration Determinations Using Plasma FT-IR Spectra

FT-IR spectrometry was used for plasma triglyceride and glycerol concentration measurements, based on their most characteristic IR absorbances within the 1200–800 cm−1 interval. Plasma samples from 68 sportsmen were taken at rest and after an endurance exercise that induced important lipolysis. After subtraction of glucose and lactate absorbances from exercise plasma FT-IR spectra, triglyceride concentration was accurately determined using the spectral window centered at 1106 cm−1 (0.86 ± 0.19 vs. 0.84 ± 0.17 mMol/L; r = 0.97, P < 0.01; SEP = 0.14 mMol/L). Total glycerol concentration (sum of glycerol and glyceryl residue concentrations) was determined using the spectral window centered at 926 cm−1, which was found common to triglycerides and glycerol (0.306 ± 0.057 vs. 0.326 ± 0.051 mMol/L; r = 0.98, P < 0.01; SEP = 0.02 mMol/L). Glycerol concentration could be determined using the spectral window centered at 852 cm−1 (0.216 ± 0.039 vs. 0.231 ± 0.048 mMol/L; r = 0.95, P < 0.01; SEP = 0.03 mMol/L). However, weak glycerol concentration could be only indirectly determined by subtracting glyceryl residue concentration from total glycerol concentration that had been determined using the spectral window centered at 926 cm−1 (0.191 ± 0.061 vs. 0.176 ± 0.051 mMol/L; r = 0.90, P < 0.05; SEP = 0.02 mMol/L). Indeed, FT-IR spectrometry appears to be an accurate method for multiple biomolecular concentration determination on plasma samples.

Validation for quantification of immunoglobulins by Fourier transform infrared spectrometry

Abstract Background: The objective of this study was to develop a robust quantification method for simultaneously analyzing molecules in human plasma using the Fourier transform infrared (FT-IR) system with a partial least square (PLS) regression. Methods: Plasma spectra were analyzed from 4000 to 500 cm−1 (with 2.0 cm−1 of resolution and 32 scans), and the molecule concentrations (IgA, IgG, IgM) were measured blindly by using a cross-validation model prepared by PLS analysis of data from 135 samples. Results: There was a significant correlation between the FT-IR predicted concentration and the concentration obtained with the clinical reference method: R2=0.98 (IgA), R2=0.98 (IgG), and R2=0.97 (IgM). The root mean square error of prediction (RMSEP) was 0.05 g·L−1 (IgA), 0.4 g·L−1 (IgG), and 0.03 g·L−1 (IgM). Variability of inter-experimenter reproducibility was less than 2%. The interchangeability of the two methods was studied by using the Bland-Altman method. Conclusions: Together with PLS analysis, FT-IR spectrometry appears to be an easy-to-use and accurate method to determine multianalyte concentrations in dried human plasma. It could be an alternative tool for rapidly quantifying many molecules after developing a specific predictive model. Clin Chem Lab Med 2009;47:83–90.

Application of FT-IR Spectrometry to Determine the Global Metabolic Adaptations to Physical Conditioning in Sportsmen

Global metabolic adaptations to physical conditioning were described in 15 subjects by FT-IR spectrometry as the method allowed determination of glucose (Glc), lactate (La), glycerol, triglycerides (TG), fatty acyl moieties (FAM), and total amino acids plasma concentrations. Subtraction of plasma FT-IR spectra obtained at resting state from the exercise spectra also allowed determination of the biomolecular response to exercise. On week 1, exercise induced a transient hypoglycemia, a lactatemia increase of 153%, a FAM depletion of 27%, and a TG concentration decrease of 28%. Protein contents increased by 2%, but these were partly catabolized for amino acid supply (+27%), suggesting an important metabolic stress during exercise. On week 3, exercise hypoglycemia had disappeared, lactate increase was diminished by 91%, TG contents were decreased by 14%, and proteins and amino acids exhibited higher absorption increases. On week 5, TG and FAM concentrations were markedly increased during exercise, protein absorption was still increased (+9%), but amino acid blood release was diminished by 81%. These results described positive adaptations to training. Furthermore, FAM concentration could be determined from plasma FT-IR spectra by using the 2996–2819 cm−1 spectral area [νas(CH3), νas(CH2), νs(CH3), and νs(CH2) absorbance; 0.82 mMol·L−1, a.u. cm−1], as well as for amino acid concentration by using the ν(COO−) spectral area (1430–1360 cm−1; 0.062 g·L−1, a.u. × cm−1). FT-IR spectrometry was useful to determine simultaneously various plasma concentrations and most of the biomolecular changes through successive samples.