Biology subjects

Espindola, F. S.

Publications and source records attributed to Espindola, F. S..

2 recordsLinked to original sources

bioRxiv2023

Not only age affects cardiovascular parameters, salivary biomarkers, and their correlation, but the level of physical conditioning changes this behavior in the elderly

To compare the physical conditioning, hemodynamic, and salivary biomarkers between elderly athletes and the physically active elderly. 14 men: EA (n = 8) and PAE (n = 6). Collection times (T0; TE; T5; T15). A negative correlation was found between SF and cardiovascular parameters, BL, and STP in both groups, but this was almost double among PAE. For HR and SBP, there was a faster recovery in EA. The EA increase was correlated with SBP, while for PAE it was correlated with HR. BL showed an increase in TE, reaching 481% in EA and 639% in PAE. SNO showed a similar increase for the groups at the TE, but at T5, while EA already showed a reduction, PAE saw a 94% increase, with a slower decay for this group at T15. The SF presented the negative {Delta}% was almost double in PAE, with a quick recovery already at T5 for EA and levels still negative at all times for PAE. For SIgA-s, there was an increase of 37% in EA and only 7% at the TE in PAE; 41% in EA and 15% in PAE for T5; and 26% in EA and 14% in PAE at T15. SA showed a higher peak in EA (TE) and less acute in PAE (T5) but there was a decrease among both at T15. STP increased by 126% in EA and 438% in PAE, already showing a return at T5 for EA, but increasing by 213% in PAE. Negative levels were reached at T15 for EA but levels remained high in PAE. Levels of physical conditioning affect cardiovascular parameters, salivary biomarkers, and their correlation within the over-60s.

physiology↗

bioRxiv2019

Salivary molecular spectroscopy: a rapid and non-invasive monitoring tool for diabetes mellitus during insulin treatment

Monitoring of blood glucose is an invasive, painful and costly practice in diabetes. Consequently, the search for a more cost-effective (reagent-free), non-invasive and specific diabetes monitoring method is of great interest. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy has been used in diagnosis of several diseases, however, applications in the monitoring of diabetic treatment are just beginning to emerge. Here, we used ATR-FTIR spectroscopy to evaluate saliva of non-diabetic (ND), diabetic (D) and diabetic 6U-treated of insulin (D6U) rats to identify potential salivary biomarkers related to glucose monitoring. The spectrum of saliva of ND, D and D6U rats displayed several unique vibrational modes and from these, two vibrational modes were pre-validated as potential diagnostic biomarkers by ROC curve analysis with significant correlation with glycemia. Compared to the ND and D6U rats, classification of D rats was achieved with a sensitivity of 100%, and an average specificity of 93.33% and 100% using bands 1452 cm-1 and 836 cm-1, respectively. Moreover, 1452 cm-1 and 836 cm-1 spectral bands proved to be robust spectral biomarkers and highly correlated with glycemia (R2 of 0.801 and 0.788, P < 0.01, respectively). Both PCA-LDA and HCA classifications achieved an accuracy of 95.2%. Spectral salivary biomarkers discovered using univariate and multivariate analysis may provide a novel robust alternative for diabetes monitoring using a non-invasive and green technology.

bioinformatics↗