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Biology subjects

Goncalves, L. C. O.

Publications and source records attributed to Goncalves, L. C. O..

3 recordsLinked to original sources

Machine Learning exploratory technic detected that men might be up to eight times more affected by the control effect and three times more affected by the placebo effect than women

BackgroundThe Placebo effect has been historically described since the beginning of Medicine. When the most skeptical researchers say they do not believe in Noetic Science but use a placebo in their research, they generate an apparent contradiction. The present study aimed to understand the noetic influence on high-level athletes, using a sportomics strategy, statistical exploratory techniques of machine learning and holistic analysis. MethodsThe study included 14 volunteer volleyball athletes. Each volunteer was submitted to four running tests of 3,000 meters, on a 400-meter track, with one test each subsequent day. On the first day, the athletes performed the first test of 3,000, aiming to adapt to the trial (ADAPT 1), and on the second day, the same adaptation (ADAPT 2). On the third and fourth days, the placebos were introduced, and on the third day, the athletes received the information that that would be just a placebo, which was called (CONTROL). On the fourth day, when the identical placebo was given, the athletes received the information that it would be a new cutting-edge nutritional supplement being studied (PLACEBO). ResultsMen might be up to eight times more affected by the control effect and three times more by the placebo effect than women. Regarding performance, there was an antagonistic behavior concerning gender for the control effect and an agonistic effect for the placebo effect, but with less impact on women. Men also showed a faster adaptation to the test. ConclusionNoetic science, always considered but never assumed by researchers, is confirmed when the present study reveals that men are more affected by the control effect and the placebo effect than women, with antagonistic behavior concerning gender for the control effect and an agonist effect for the placebo effect, but with less impact on women about performance.

physiology↗

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↗

Interleukin 12 correlates with performance, metabolism and acid-base balance during physical exercise

Studies involving physical exercise are no longer performed only to evaluate the performance of athletes, but have become an important tool to understand how different forms of stress affect immunometabolism. The present study investigated the acute impact of a treadmill running test on different biomarkers, the acid-base system, glycemia/lactatemia, and the correlation between IL-12 and metabolism/performance. Ten male subjects participated in a cross-sectional study. The treadmill protocol was progressively increased until exhaustion. The IL-12 concentration was measured using the "Cytometric Bead Array" kit (CBA, BD Bioscience, USA) through flow cytometry, and the data were analyzed using FCAP Array software. The test had an average time of 13 minutes and 51 seconds and induced alterations in IL-12 concentration of 160%, lactate of 607%, blood glucose of 58%, blood pH of -3%, BE of -529%, bicarbonate of - 58%, and anion gap of 232%. It was observed that the lower the percentage variation in IL-12, the greater the phase to reach the anaerobic threshold (AT) in Km/h, and the time to reach this same threshold, and the opposite was also true, confirmed by the Spearman test. (-0.900 between IL-12 and the time to reach AT and -0.872 between IL-12 and the phase to reach AT). Other correlations were observed: between post-IL-12 and pre anion gap of 1.0, post-IL-12 and post chloride of 1.0, percentage change in IL-12 and post anion gap of 1.0 and percentage variation in IL-12 and post lactate of 0.943, pre-IL-12 and post anion gap of -1.0, post-IL-12 and pre LDH of -0.943, post-IL-12 and post LDH of -0.943, post-IL -12 and BE post of -9.943, post-IL-12 and post bicarbonate of -0.943, and post-IL-12 and post pH of -0.943. The AT was reached in 7:52 minutes, in the 14.9 km/h phase, with a heart rate of 163 beats per minute, an absolute power of 524 W, and an absolute VO2 of 3.12 l.min. A correlation between IL-12 and performance, metabolism, and blood acid-base balance is suggested. Furthermore, it is expected that approximately 15% of glycemia is formed by the CORI cycle, through the removal of lactate and reestablishment of glycemia, however, this estimate can be exceeded in athletes, according to the level of training.

immunology↗