Bicarbonato ingestion has no ergogenic effect on consecutive all out sprint test in MWX elite cyclists

The aim of the present study was to examine the effect of sodium bicarbonate ingestion on consecutive "all out" sprint tests, analyzing the acid-base status and its influence on performance and perceived effort. Ten elite bicycle motocross (BMX) riders (20.7 ± 1.4 years, training experience 8-12 years) participated in this study which consisted of two trials. Each trial consisted of three consecutive Wingate tests (WTs) separated by 15 min recovery. Ninety minutes prior to exercise subjects ingested either NaHCO(3) (-) (0.3 g kg(-1) body weight) or placebo. Blood samples were collected for the assessment of blood acid-base status: bicarbonate concentration ([HCO(3) (-)]), pH, base excess (BE) and blood lactate concentration ([La(-)]). Performance variables of peak power (PP), mean power (MP), time to peak power and fatigue index were calculated for each sprint. Significant differences (p < 0.05) were observed in acid-base variables [pH before WT1: 7.47 ± 0.05 vs. 7.41 ± 0.03; [HCO(3) (-)] before WT1: 29.08 ± 2.27 vs. 22.85 ± 0.24 mmol L(-1) (bicarbonate vs. placebo conditions, respectively)], but there were not significant differences in performance variables between trials [PP WT1: 1,610 ± 373 vs. 1,599 ± 370 W; PP WT2: 1,548 ± 460 vs. 1,570 ± 428 W; PP WT3: 1,463 ± 361 vs. 1,519 ± 364 W. MP WT1: 809 ± 113 vs. 812 ± 108 W; MP WT2: 799 ± 135 vs. 799 ± 124 W; MP WT3: 762 ± 165 vs. 782 ± 118 W (bicarbonate vs. placebo conditions, respectively)]. Rating of perceived effort (RPE) was not influenced nor ratings of perceived readiness. Sodium bicarbonate ingestion modified significantly the blood acid-base balance, although the induced alkalosis did not improve the Wingate test performance, RPE and perceived readiness across three consecutive WTs in elite BMX cyclists.

Crowdsourcing malaria parasite quantification: an online game for analyzing images of infected thick blood smears

Background: There are 600,000 new malaria cases daily worldwide. The gold standard for estimating the parasite burden and the corresponding severity of the disease consists in manually counting the number of parasites in blood smears through a microscope, a process that can take more than 20 minutes of an expert microscopist’s time. Objective: This research tests the feasibility of a crowdsourced approach to malaria image analysis. In particular, we investigated whether anonymous volunteers with no prior experience would be able to count malaria parasites in digitized images of thick blood smears by playing a Web-based game. Methods: The experimental system consisted of a Web-based game where online volunteers were tasked with detecting parasites in digitized blood sample images coupled with a decision algorithm that combined the analyses from several players to produce an improved collective detection outcome. Data were collected through the MalariaSpot website. Random images of thick blood films containing Plasmodium falciparum at medium to low parasitemias, acquired by conventional optical microscopy, were presented to players. In the game, players had to find and tag as many parasites as possible in 1 minute. In the event that players found all the parasites present in the image, they were presented with a new image. In order to combine the choices of different players into a single crowd decision, we implemented an image processing pipeline and a quorum algorithm that judged a parasite tagged when a group of players agreed on its position. Results: Over 1 month, anonymous players from 95 countries played more than 12,000 games and generated a database of more than 270,000 clicks on the test images. Results revealed that combining 22 games from nonexpert players achieved a parasite counting accuracy higher than 99%. This performance could be obtained also by combining 13 games from players trained for 1 minute. Exhaustive computations measured the parasite counting accuracy for all players as a function of the number of games considered and the experience of the players. In addition, we propose a mathematical equation that accurately models the collective parasite counting performance. Conclusions: This research validates the online gaming approach for crowdsourced counting of malaria parasites in images of thick blood films. The findings support the conclusion that nonexperts are able to rapidly learn how to identify the typical features of malaria parasites in digitized thick blood samples and that combining the analyses of several users provides similar parasite counting accuracy rates as those of expert microscopists. This experiment illustrates the potential of the crowdsourced gaming approach for performing routine malaria parasite quantification, and more generally for solving biomedical image analysis problems, with future potential for telediagnosis related to global health challenges.