Anesthetic Management of Moyamoya Syndrome Secondary to Sickle Cell Anemia

Moyamoya disease (MMD) is caused by stenosis or occlusion of internal carotid artery in brain, thereby reducing its blood supply. To augment blood flow, brain develops abnormal anastomotic vessels with deranged carbon dioxide reactivity and tendency to bleed. Moyamoya syndrome (MMS) is the name given to MMD when the latter results from secondary to some associated disease. Occurrence of MMS secondary to sickle cell anemia (SCA) presents unique challenges to neuroanesthesiologists. Management of various physiological parameters for cerebral revascularization surgery for MMD under general anesthesia necessitates vigilant and balanced control of various physiological variables, as the manipulation of a particular physiological variable for one pathology may adversely impact the same physiological variable for the associated disease, which will result in poor outcome of the patient. Therefore, optimum outcome of MMS is determined by a watchful balancing of various physiological parameters under anesthesia.

Estimation of biometric, physiological, and nutritional variables in lettuce seedlings using multispectral images

ABSTRACT The formation of seedlings is one of the most important phases of lettuce cultivation. Therefore, any strategy that aims to obtain high-quality seedlings can increase productivity. One of these strategies is the prediction of morphophysiological attributes based on optical properties. The objective of this study was to quantitatively estimate the biometric variables of lettuce from parametric and non-parametric models based on the response of multispectral camera images. The experiment was conducted in a greenhouse in the municipality of Uberaba, Minas Gerais State, Brazil. Twenty days after sowing, multispectral images of the plants were captured using a MAPIR Survey 3 camera. To compose the estimation models, along with the original bands of the camera, the multispectral vegetation indices were calculated using the calibrated original camera bands. Bands B550, B660, and B850 and the near-infrared indices contributed significantly to estimating the physiological variable models, with B850 contributing the most to the biometric and nutritional variables. From the near-infrared band (B850) and derived indices, it was possible to estimate all the agronomic variables from the models generated by the M5 algorithm, with an accuracy of up to 1.6% for the maximum quantum yield. Thus, it is possible to quantify the biometric, physiological, and nutritional variables of lettuce using a multispectral camera. Among the Mapir camera bands, B660 exhibited the greatest variability, showing that the red range was the most sensitive.

Pace Controlled by a Steady-State Physiological Variable Is Associated with Better Performance in a 3000 M Run

This paper aims to test the hypothesis whereby freely chosen running pace is less effective than pace controlled by a steady-state physiological variable. Methods Eight runners performed four maximum-effort 3000 m time trials on a running track. The first time trial (TT1) was freely paced. In the following 3000 m time trials, the pace was controlled so that the average speed (TT2), average V˙O2 (TT3) or average HR (TT4) recorded in TT1 was maintained throughout the time trial. Results: Physiologically controlled pace was associated with a faster time (mean ± standard deviation: 740 ± 34 s for TT3 and 748 ± 33 s for TT4, vs. 854 ± 53 s for TT1; p < 0.01), a lower oxygen cost of running (200 ± 5 and 220 ± 3 vs. 310 ± 5 mLO2·kg−1·km−1, respectively; p < 0.02), a lower cardiac cost (0.69 ± 0.08 and 0.69 ± 0.04 vs. 0.86 ± 0.09 beat·m−1, respectively; p < 0.01), and a more positively skewed speed distribution (skewness: 1.7 ± 0.9 and 1.3 ± 0.6 vs. 0.2 ± 0.4, p < 0.05). Conclusion: Physiologically controlled pace (at the average V˙O2 or HR recorded in a freely paced run) was associated with a faster time, a more favorable speed distribution and lower levels of physiological strain, relative to freely chosen pace. This finding suggests that non-elite runners do not spontaneously choose the best pace strategy.

Physical and Physiological Demands During Handball Matches in Male Adolescent Players

This study aimed to describe the physical and physiological demands of adolescent handball players and compare movement analysis and exercise intensities between the first and second halves and between the different periods of the match. Fourteen adolescent handball players (age 15.7 ± 0.8 years, body mass: 65.6 ± 3.4 kg, body height: 169.5 ± 3.9 cm), played two friendly matches, in which no substitutions were made. The analysis was carried out with a Global Positioning System technology. The following physical variables were analyzed: Total distance covered (TD); distance covered at faster velocities than 18 km·h-1 (TDC>18km·h-1); number of accelerations (Accel) and decelerations (Decel); number of accelerations and decelerations higher than 2.78 m·s-2 (Accel>2.78 m·s-2 and Decel>2.78 m·s-2); number of sprints (Sprints); accelerations interspersed with a maximum of 30 s between them (RAS≤30s) and as a physiological variable the heart rate (HR) was examined. Significant differences (p < 0.01 –p < 0.001) between the first and the second half in all variables mentioned were observed, except in Accel>2.78 m·s-2 and Decel>2.78 m·s-2. This trend was also observed when comparing performance between the different 10-min periods. The 5th period (period 40-50 min) was the one that showed differences with respect to the previous ones. Adolescent handball players showed lower levels of exercise intensity, assessed by both time-motion and HR data, in the second half of matches, especially in the middle of this period.