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1.
Res. Biomed. Eng. (Online) ; 32(3): 293-300, July-Sept. 2016. graf
Article in English | LILACS | ID: biblio-829489

ABSTRACT

Abstract Introduction Fourier-transform infrared (FT-IR) spectroscopy is a technique with great potential for body fluids analyses. The aim of this study was to examine the impact of session training on cortisol concentrations in rugby players by means of infrared analysis of serum. Methods Blood collections were performed pre, post and 24 hours after of rugby training sessions. Serum cortisol was analyzed by FT-IR spectroscopy and chemiluminescent immunoassay. Results There was a significant difference between the integrated area, in the region of 1180-1102 cm-1, of the spectra for pre, post and post 24 h serums. The cortisol concentration obtained by chemiluminescent immunoassay showed no significant difference between pre, post and post 24 h. Positive correlations were obtained between the techniques (r = 0.75), post (r = 0.83) and post 24 h (r = 0.73). Conclusion The results showed no increase in cortisol levels of the players after the training sessions, as well as positive correlations indicating that FT-IR spectroscopy have produced promising results for the analysis of serum for diagnosis of stress.

2.
Res. Biomed. Eng. (Online) ; 32(2): 123-128, Apr.-June 2016. graf
Article in English | LILACS | ID: biblio-829476

ABSTRACT

AbstractIntroduction: The diagnosis based on salivary biomarkers provides information about the physiological condition. However, the clinical trials used to analyze these biomarkers are relatively expensive and laborious. Thus, the purpose of this study was to identify the physiological stress in players using Fourier transform infrared spectroscopy (FT-IR). Methods Thirteen male rugby players were submitted to the treadmill fatigue test and saliva collections were performed before and immediately after test. The FT-IR spectra of saliva samples were analyzed by the second derivative and cluster analysis. Results From the results of cluster analysis were possible to discriminate the spectra of saliva before and after physical effort using the spectral region between 1490 to 1420 cm–1. Only the saliva spectra from two players were not discriminated in pre-exercise group and post-exercise group, which are in agreement with lowest value of heart rates. Conclusion The second derivative showed differences between the average spectra of saliva samples collected pre and post-test, which explain the spectra discrimination by the cluster analysis using a specific infrared region for the identification of physiological stress.

3.
Res. Biomed. Eng. (Online) ; 31(2): 116-124, Apr-Jun/2015. tab, graf
Article in English | LILACS | ID: biblio-829429

ABSTRACT

Introduction Saliva is the most promising biofluid to monitor the physiological state of athletes, because this method is not invasive and has low contamination risks. The characterization of saliva by Fourier transform infrared spectroscopy (FT-IR) has been studied as an alternative technique to the standard clinical analysis. However, methodological procedures for saliva analysis are not completely clear, especially in terms of influence of storage conditions and sample preparations for infrared analysis. Thawed saliva includes a precipitate, which may influence the infrared spectral analysis. Thus, the purpose of this study was to show the spectral differences of the precipitate, supernatant, and a combo, as well as the best way to classify the physiological state of the athletes by FT-IR. Methods The saliva collection was performed before, immediately after, and two hours after a handball match. After the storage of samples at –20 ○C, it was possible to identify two phases (precipitate and supernatant) and to determine the biochemical differences between the spectra of each phase, which were distinctly analyzed by the second derivative and deconvolution bands. Results The precipitate and supernatant results showed characteristic bands, especially in the protein regions. All FT-IR spectra were also statistically classified by linear discriminant analysis (LDA), using principal component analysis (PCA). The LDA precipitate and supernatant had lower value when compared to combo spectra (Combination of precipitate and supernatant) with 82%, showing that this combination is the best way to discriminate spectra of saliva samples collected before, immediately after, and 2 h after physical effort. Discussion The results showed that it is possible to differentiate biochemically the two salivary phases, as well as the importance of the homogenization process of saliva samples to classify the physiological status of athletes using FT-IR.

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