22 research outputs found
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The Effects of Oat Fiber and Corn Bran on Blood Serum Cholesterol and Triglyceride Levels
Forty Sprague Dawley rats were randomly placed in five groups with eight rats per group. Each group varied in dietary composition for fiber type and carbohydrate source. Groups one and two received oat fiber and either sucrose or corn starch as the carbohydrate source. Groups three and four received corn bran as the fiber source and either sucrose or corn starch as the carbohydrate source. Group five (considered the control group), received Purina standard rat chow. Analysis of variance showed only significant differences for food intake, and the control group had a significantly higher food intake. Weight gain, serum cholesterol and triglyceride levels showed no significant differences
Effect of Deer Antler Velvet on Aerobic, Anaerobic and Strength Performance
Deer antler velvet (DAV) supplementation purportedly increases athletic performance; however, little data support this claim. The primary aim of our study is to examine DAV and exercise performance. We randomized 32 men (18–35 y) participating exclusively in resistance training (>4 y) to 10-weeks of randomly assigned, double blind, DAV (1350 mg, 2×/day) or placebo treatments. Primary outcomes included maximal aerobic capacity (VO2max), maximal strength (1RM; bench press and squat) and anaerobic cycling power. Secondary outcomes included comprehensive blood profiles and body composition. We used general linear models to determine changes following treatment. Eighteen participants (n = 9) completed the study with DAV participants showing significant improvements in VO2max (4.30 ±0.45 to 4.72 ±0.60 L/min, P < 0.04). The placebo and DAV groups increased bench press and squat 1RM (both, P < 0.04); yet, when expressed relative to body mass, only the DAV group showed significant bench press (4%) and squat (10%; both, P < 0.02). Neither group improved cycling performance or showed adverse changes in blood chemistries. We did observe a significant reduction in LDL-C (12%) accompanying DAV supplementation and both groups significantly reduced percent body fat (P < 0.05). Our results suggest that DAV may have ergogenic effects in men participating solely in resistance training
Estimating the Lactate Threshold Using Wireless Near-Infrared Spectroscopy and Threshold Detection Analyses
International Journal of Exercise Science 14(4): 284-294, 2021. The present investigation examined the ability of two threshold detection analyses (maximum distance, Dmax; modified maximum distance, mDmax) in identifying the near-infrared spectroscopy (NIRS) threshold, a lactate threshold (LT) estimate, from exercising tissue oxygen saturation (StO2) responses. Additionally, the test-retest reliability of exercising StO2 and total hemoglobin concentration (THC) responses were examined at moderate and peak cycling intensities. Fourteen healthy, recreationally active participants performed maximal incremental step cycling tests (+25 W / 3 minutes) to volitional fatigue on two separate occasions while StO2 and THC of the vastus lateralis were monitored. Exercising blood [lactate] was collected during Session One. LT and NIRS thresholds (NIRS1, NIRS2) were then determined using Dmax and mDmax threshold analyses. Significant (p \u3c 0.05), moderate correlations were detected between LT and NIRS1 when using Dmax (LT = 130 ± 49 W, NIRS1 = 136 ± 34 W, r = 0.690), but not for mDmax (r = 0.487). No significant test-retest reliability for the NIRS thresholds were observed for Dmax (ICC = 0.351) or mDmax (ICC = 0.385). Exercising StO2 responses demonstrated good reliability (ICC = 0.841-0.873) while exercising THC responses demonstrated moderate-good reliability (ICC = 0.720-0.873) at moderate and peak exercise intensities. The results of this study suggest that neither the Dmax nor mDmax threshold analyses should be used to estimate the LT due to the unreliable detection of the NIRS threshold from session to session
Oral andro-related prohormone supplementation : do the potential risks outweigh the benefits ?
Les fabriquants des prohormones andro prétendent que les andro augmentent la concentration sérique de testostérone, la masse et la force musculaires, contribuent à la réduction des graisses corporelles, améliorent l'humeur et la performance sexuelle. Pourtant la majorité des études contredisent ces effets et certaines montrent les risques accrus de cancer de la prostate ou du pancréas et de maladie cardiovasculaire
Oral andro-related prohormone supplementation : do the potential risks outweigh the benefits ?
Les fabriquants des prohormones andro prétendent que les andro augmentent la concentration sérique de testostérone, la masse et la force musculaires, contribuent à la réduction des graisses corporelles, améliorent l'humeur et la performance sexuelle. Pourtant la majorité des études contredisent ces effets et certaines montrent les risques accrus de cancer de la prostate ou du pancréas et de maladie cardiovasculaire
Collaborative Commentary: Opening Up Spoken Language Databases
We define collaborative commentary as the involvement of a research community in the interpretive annotation of electronic records. The goal of this process is the evaluation of competing theoretical claims. The process requires commentators to link their comments and related evidentiary materials to specific segments of either transcripts or electronic media. Here, we examine current work in the construction of technical methods for facilitating collaborative commentary through browser technology. To illustrate the relevance of this approach, we examine seven spoken language database projects that have reached a level of web-based publication that makes them good candidates as targets of collaborative commentary technology. For each database, we show how collaborative commentary can advance the relevant research agendas
Effects of Hydration Changes on Bioelectrical Impedance in Endurance Trained Individuals
Purpose: The purpose of this study was to determine how differences in hydration states and ion content of hydrating fluids affected bioelectrical impedance (BI) and hydrostatic weighing (HW) measurements. Methods: Fifteen athletic subjects aged 19-56 yr were recruited. Relative body fat (%), fat- weight (FW), and fat-free weight (FW) were assessed using BI and HW under normal conditions (N), hypohydration (HPO), rehydration (RHY), and superhydration (SHY) states. During the RHY and SHY trial periods, subjects were hydrated with either distilled water or an electrolyte solution (ELS). HPO and SHY levels were set at 3% of each person\u27s normally hydrated body weight. Results: Comparison between the distilled water and the ELS trials indicated that hydration solution had no effect on BI or HW. Thus, the results presented are the trial means of both hydration solutions combined. Both BI and HW were shown to be highly test-retest reliable (r-values: 0.96 and 0.99, respectively). The effects of exercise induced HPO followed by RHY on body composition values indicated that HW was very stable across measurement periods while BI was not. From N to the HPO state, BI %BF declined from 14.4 ± 5.3% to 12.3 ± 5.3%, respectively. After RHY, BIA %BF increased to 15.5 ± 5.8%. Similar findings occurred when subjects were superhydrated (N-BI = 13.2 ± 5.3%; SHY-BI = 15.4 ± 5.6%). With a comparison of the intercepts and slopes of HW and BIA for the N and SHY states, it was clear hydration status significantly affected the intercepts (HW: 0.37 vs. BI: 1.85) and not the slopes (HW: 1.00 vs BI: 0.99). As a result, a majority of all fluid changes were interpreted as FW by BI. During HPO, 82% of the weight loss was considered FW while during RHY or SHY, 128% and 85% of the water weight regain/gain was considered FW. Conclusion: These results indicate that BI is not a valid technique in athletes, especially when wanting to determine body composition effects of training/detraining. This study indicates that even small fluid changes such as those that occur with endurance training may be interpreted incorrectly as changes in an athlete\u27s body fat content
The effects of acute exercise on neutrophils and plasma oxidative stress
Purpose: To investigate the influence of intensity versus total energy expenditure on neutrophilia and blood oxidative stress to acute exercise. Methods: Nine males (18-30 yr) completed one maximal (Max) and three submaximal exercise sessions: 1) 45 min at 10% above (LT+) lactate threshold (LT), 2) 45 min at 10% below (LT-) LT, and 3) 10% below LT until caloric expenditure equaled the 10%+ trial (LT-kcal). Blood was sampled before (PRE), immediately (POST), 1 h, and 2 h after exercise to measure neutrophils, myeloperoxidase, superoxide (O2-), neutrophil activation (O2-/neutrophils), ascorbic acid, uric acid, malondialdehyde, and lipid hydroperoxides. Results: Intensity-dependent neutrophilia occurred POST exercise with significant increases (P ≤ 0.05) after Max and LT+. A second neutrophilia wave occurred 2 h postexercise. Superoxide was elevated POST (Max) and 2 h post (Max and LT+). In contrast, O2-/neutrophils was increased at 2 h only (Max and LT +). These data indicate that immediately postexercise, total neutrophil number rather than activation best represents neutrophil-generated reactive species within blood. POST Max, ascorbic acid and uric acid were decreased indicating a blood oxidative stress occurred. Alternately, total energy expenditure was not related to any marker of neutrophilia or oxidative stress. Conclusion: Exercise intensity plays a major role in postexercise blood oxidative stress, whereas total exercise energy expenditure does not. Further, neutrophils recruited into circulation during exercise may impose a threshold dependent oxidative stress in blood plasma after exercise
Effect of Cardiac Autonomic Balance During Sleep on Elite Cycling Performance Following Fatiguing Exercise
Heart-rate variability characterizes cardiac autonomic balance, and provides a useful index of training load exposure, and hence an estimate of cumulative physical fatigue. However, the interaction between HRV and performance is less understood.
Purpose: To determine the predictive value of the Root Mean Square of Successive Differences (RMSSD) and Low to High Frequency Ratio (LF/HF) on cycling 4km TT performance following high-intensity (HI) exercise.
Methods: Four elite cyclists (mountain bike (F), cyclocross (M), triathlon (M), BMX (M)) performed three successive days of 4x5 min HI cycling bouts at 260W (F), and 375 ± 21.8W (M) separated by 5-7 min of recovery between each bout. Following completion of the HI protocol, athletes rested for 30 min and then performed a 4km TT on a Cyclus 2 ergometer. HRV was recorded the evening before the TT’s between 22:00h and 23:59h using a HealthPatch (Vital Connect, Campbell CA), and areas under the curve were computed for RMSSD and LF/HF ratio. Linear regression was performed to determine the relationship between RMSSD, LF/HF ratio and TT time.
Results: 4x5 min HI exercise bouts were sustained in all athletes except BMX where workload was reduced by 14% from day 1 to day 2. Progressive fatigue was evidenced by RPE’s increasing from 1km to 4km by 12.5±3.6% (Day 1) to 20.6±4.5% (Day 3). Day 1 to Day 3 data is shown in the table below;
TT time
TT Power
RMSSD area
LF/HF area
Mountain bike
+2.8%
-9.8%
-25%
+46%
Cyclocross
+5.2%
-2.4%
-11%
-50%
Triathlon
-2.9%
+6.6%
+29%
-16%
BMX
-0.5%
+6.5%
-4%
+3%
RMSSD v. TT time R2 for day 1-3 respectively was, -0.39, -0.29, and -0.60 (p=0.03 for grouped days). LF/HF v. TT time R2 for day 1-3 respectively was, 0.09, 0.59, and 0.18 (p=0.06 for grouped days).
Conclusion: Early sleep cycle HRV data prior to HI fatiguing cycling explains partially TT cycling performance in elite athletes
Validation of submaximal prediction equations for the 1 repetition maximum bench press test on a group of collegiate football players
The purpose of the study was to determine the accuracy of 11 prediction equations in estimating the 1 repetition maximum (1RM) bench press from repetitions completed by collegiate football players (N = 69) using 225 lb. The demographic variables race, age, height, weight, fat-free weight, and percent body fat were measured to determine whether these variables increased the accuracy of the prediction equations; race was the most frequently selected variable in the regression analyses. The validity of the prediction equations was dependent upon the number of repetitions performed, i.e., validity was higher when fewer repetitions were completed. Explained variability of 1RM was slightly higher for all 11 equations when demographic variables were included. A new prediction equation was also developed using the number of repetitions performed and the demographic variables height and fat-free weight