Estimation of ibuprofen in urine and tablet formulations by transmission Fourier Transform Infrared spectroscopy by partial least square

Khaskheli, Abdul Rauf; Sirajuddin, Sirajuddin; Sherazi, Syed Tufail Hussain; Mahesar, Sarfaraz Ahmed; Kandhro, Aftab Ahmed; Kalwar, Nazar Hussain; Mallah, Muhammad Ali

doi:10.1016/j.saa.2012.10.021

Cited by 28 publications

(11 citation statements)

References 23 publications

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“…Fourier-transform infrared spectroscopy (FT-IR) has also been used to characterize biological samples as an alternative technique for laboratory tests (Ellis and Goodacre, 2006;Khaskheli et al, 2013). Many studies demonstrated high sensitivity of FT-IR to analyze the skeletal muscle (Jerônimo et al, 2012), heart muscle (Cheheltani et al 2012), and some biological fluids, such as serum (Carvalho et al, 2014), urine (Khaskheli et al, 2013), and saliva (Khaustova et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Analysis of saliva by Fourier transform infrared spectroscopy for diagnosis of physiological stress in athletes

2015

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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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Section: Introductionmentioning

confidence: 99%

“…Many studies demonstrated high sensitivity of FT-IR to analyze the skeletal muscle (Jerônimo et al, 2012), heart muscle (Cheheltani et al 2012), and some biological fluids, such as serum (Carvalho et al, 2014), urine (Khaskheli et al, 2013), and saliva (Khaustova et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Analysis of saliva by Fourier transform infrared spectroscopy for diagnosis of physiological stress in athletes

2015

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“…In order to minimize such difficulties, new laboratory tools have been proposed to characterize biological samples as an alternative technique for health monitoring of athletes (Ellis and Goodacre, 2006;Khaskheli et al, 2013;Petibois et al, 2000).…”

Section: Introductionmentioning

confidence: 99%

Analysis of serum cortisol levels by Fourier Transform Infrared Spectroscopy for diagnosis of stress in athletes

et al. 2016

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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.

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“…Fourier-transform infrared spectroscopy (FT-IR) has also been used to characterize biological samples as an alternative technique for laboratory tests (Ellis and Goodacre, 2006;Khaskheli et al, 2013). This technique has great potential for analysis of body fluids (Petibois et al, 2000;Yoshida et al, 2013), allowing quantifying the biochemical components of biological sample.…”

Section: Introductionmentioning

confidence: 99%

Application of FT-IR spectroscopy to assess physiological stress in rugby players during fatigue test

et al. 2016

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Introduction: 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.

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Estimation of ibuprofen in urine and tablet formulations by transmission Fourier Transform Infrared spectroscopy by partial least square

Cited by 28 publications

References 23 publications

Analysis of saliva by Fourier transform infrared spectroscopy for diagnosis of physiological stress in athletes

Analysis of saliva by Fourier transform infrared spectroscopy for diagnosis of physiological stress in athletes

Analysis of serum cortisol levels by Fourier Transform Infrared Spectroscopy for diagnosis of stress in athletes

Application of FT-IR spectroscopy to assess physiological stress in rugby players during fatigue test

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