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yo

i remember reading in an article or post somewhere u wrote that u have figured out and know now exactly what you need to do to increase ur vert, like exactly what works for you individually.  Just wondering what that was

Also i'm looking into buying some fitness books, u got any that u think are must reads whether it's about anatomy, kinesiology, sports training, stretching,  or whatever

Fatigue during the 400-m sprint was studied by measuring muscle ATP, creatine phosphate (CP), lactate (M-La), and blood lactate (B-La) in six male runners before and after four experimental sprints (100, 200, 300, and 400 m). During the first 100 m, muscle CP decreased from 15.8 +/- 1.7 to 8.3 +/- 0.3 mmol/kg while M-La increased to 3.6 +/- 0.4 mmol/kg. After 200 m the CP had decreased to 6.5 +/- 0.5 mmol/kg and M-La had increased to 8.3 +/- 1.1 mmol/kg. At the end of the 400 meters, ATP and CP concentrations had decreased by 27% and 89%, respectively, and M-La had increased to 17.3 +/- 0.9 mmol/kg. It was concluded that after 200 m the speed of running decreased, although CP was not depleted and lactate concentration was not at maximum level. Complete fatigue occurred when CP stores were depleted and B-La and M-La attained an individual maximum.

In summary, world-class runners adopt a more aggressive pacing strategy and demonstrate greater fatigue than the less experienced runners; this might indicate a greater mental commitment and/or a better capacity to run under fatigue.

In an effort to compare the disturbances in leg muscle pH during sprint running, muscle biopsies were obtained from the gastrocnemius and vastus lateralis muscles of six healthy men (three endurance-trained and three nonendurance-trained) before and after a treadmill sprint run (TSR) to fatigue (54-105 s) at roughly 125% of their aerobic capacities. Following the TSR, repeated blood samples were taken from a hand vein and later analyzed for pH, Pco2, and lactic acid (HLa). The muscle specimens were analyzed in duplicate for pH and HLa. Resting-muscle pH was 7.03 +/- 0.02 ([latin capital V with dot above] +/- SE) and 7.04 +/- 0.01 for the gastrocnemius and vastus lateralis muscles, respectively. At the termination of the TSR, the pH in these muscles was 6.88 +/- 0.05 and 6.86 +/- 0.03, respectively. After a 400-m timed run on the track, the pH in the gastrocnemius of four of the subjects averaged 6.63 +/- 0.03, while blood pH and HLa were 7.10 +/- 0.03 and 12.3 mM, respectively. Although no differences in pH and HLa were observed between the vastus lateralis and gastrocnemius muscles at the end of the treadmill trial, it is speculated that the lesser disturbance in acid-base balance seen in endurance performers may have been due to a lesser production of metabolites in their running musculature when compared to nonendurance performers.

Six healthy subjects performed four exercise studies in random order on separate days: a control study, metabolic acidosis induced by ammonium chloride, metabolic alkalosis induced by sodium bicarbonate, and respiratory acidosis induced by 5% CO2 inhalation. The subjects exerted maximal force on the pedals of a constant-velocity cycle ergometer at 100 rpm for 30 s; torque was measured and power calculated. Arterialized venous blood was sampled, and plasma lactate concentrations was measured immediately after and at 2-min intervals for 10 min following exercise. Although maximal peak power and total work, for the 30-s test, were lower in the two acidosis conditions, this effect was not statistically significant. Plasma lactate 30-s postexercise was lower in metabolic acidosis (2.8 +/- 1.6 mmol X 1(-1) (mean +/- SD) and respiratory acidosis (1.5 +/- 0.8 mmol X 1(-1) than in placebo conditions (5.9 +/- 3.3 mmol X 1(-1) and metabolic alkalosis 7.8 +/- 4.2 mmol X 1(-1). These differences were maintained but lessened during 10 min of recovery. In contrast to previous studies, which showed a marked reduction in endurance time during sustained heavy exercise, reductions in blood pH are associated with only small reductions in the total work performed in 30 s of maximal exercise. A delayed and smaller accumulation of lactate in plasma was observed following exercise during acidosis.

Introduction There are not many available research studies dealing with the characteristics of reaction time, or its influence on sprint race performance (Slater-Hammel & Stumpner, 1952 ; Fairclough, 1952 ; Ozolin, 1986 ; Brueggemann & Glad, 1988 ; Mero & Komi, 1990 ; Martin & Buonchristiani, 1995 ; Collet, 2000). Most of them were not able to establish the correlation between the reaction time and the result in sprint. Therefore, the purpose of this research is to examine the relationship between the age of the sprinters and their reaction time as well as between reaction time and the sprint result in every sprint event for male sprinters who performed at the 2004 Olympic Games in Athens. Methods The sample of entities consists of all male athletes (sprinters and decathlon athletes, N=357) who performed at the 2004 Olympic Games in Athens. The recorded values of the attained result at the competition (R), values of reaction time (RT) and values of the age (YRS) of the sprinters accomplished at higher competitive level were taken for the analyses of this research study. The sample of variables is presented by 8 sprint events (100 m flat, 110 m hurdles (110 m H), 200 m flat, 400 m flat, 400 m hurdles (400 m H), 100 m as a decathlon event (100 m D), 110 m hurdles as a decathlon event (110 m H D) and 400 m as a decathlon event (400 m D). All data collected were analyzed by program package Statistica for Windows version 7 ; consequently, general univariate analysis of variance (ANOVA) was used to determine the differences between the arithmetic means of 8 sprint events in the variable reaction time as well as to determine the differences between competitive levels within every sprint event in the variable reaction time. Correlation analysis between reaction time and race result and reaction time and age of sprinters was calculated. Results The results showed existence of statistically significant differences in average reaction time values between longer and shorter sprint events but however, there were no statistically significant differences in reaction time between different competitive levels within analyzed sprint events, except of sprint event 100 m flat. Correlation analysees yielded results that there was a tendency that older sprinters reacted faster at start while statistically significant (positive) correlation between reaction time and sprint result was found for the sprint events 100 m flat and 110 m hurdles. Discussion It can be said that reaction time has significant influence on sprint result but only in short sprint events. When it comes to reaction time, it is interesting how top-level sprinters do not show significantly better values of reaction time than sprinters who managed to perform in qualification and semifinals rounds. It was found that older sprinters tend to react faster at the start. That means that in training preparation with younger sprinters more attention should be devoted to psychological preparation.

INTRODUCTION: The follow-up of performances and the prevention about possible incidents at the athletes make necessary the medical supervision in physical training.The aims of this study are to estimate the effect of a precompetition training program in athletes' body composition, and cardiovascular modifications (in clinical examination and electrocardiogram) MATERIALS ET METHODS: Ten athletes (3 men and 7 women; mean age of 23.6 +/- 3.16 years) of Dakar international Athletics' Center are subjected to a training on a period of 2 months in aerobic dominant followed by a period of 3 months in anaerobic dominant. At the beginning and the end of training program, an electrocardiogram is recorded after blood pressure (BP) measure in lying and standing posture and heart rate (HR) take. The weight, height and cutaneous folds are measured to calculate the body fat percentage, fat body mass, fat-free mass and body mass index. Every athlete has performed the Ruffier test Comparisons are realized by the paired t-test, statistically significant for a p value < 0,05 RESULTS: Significant declines after training interest HR (79.2 +/- 14.7 vs 63.2 +/- 10.25 beat min(-1); p< 0.001), systolic BP in standing posture (11.8 +/- 0.44 vs 10.6 +/- 0.96 mmHg; p= 0.02), and Ruffier index (4.4 +/- 3.28 vs 2.23 +/- 1.62; p= 0.048) whereas the fat-free mass increased (53.14 +/- 8.41 vs 54.16 +/- 9.67 kg; p= 0.046). At the electrocardiogram, the number of athletes having sinusal bradycardia is crossed from 1 to 4; there is no modification as for the two cases of uncomplete right bundle-branch block and the pre-existent left ventricular hypertrophy. Negative T waves in V1 and V2 leads are present in one athlete before training and in two others after. CONCLUSION: The impact of the specific training on body is real, interesting more the cardiovascular system.

Diuretic-induced dehydration impairs prolonged running performance (> 1500 m). Sprinting performance may suffer by similar mechanisms (i.e., altered cardiovascular strain, heat storage, and metabolism) or may improve because of reduced mass to accelerate and carry.

Purpose: To examine sprint and power performance after diuretic-induced dehydration.

Methods: After six sprint practice sessions, nine male former sprinters (mean +/- SD; age, 21 +/- 2 yr; body mass (BM), 80.0 +/- 5.2 kg; height, 1.78 +/- 0.08 m; body fat, 14 +/- 4%) participated in a 50-m race, a 200-m race, a 400-m race, and a vertical jump on an indoor synthetic track, once when dehydrated (40-mg furosemide; DD) and once with no diuretic (CON) using a counter-balanced crossover design. Plasma volume change (%[delta]PV), heart rate (HR), blood pressure, rectal temperature, serum electrolytes, plasma lactate, plasma glucose, rating of perceived exertion, thirst, and thermal sensations were measured before and after each race.

Results: Sprint times (DD vs CON) for the 50 m (6.72 +/- 0.28 vs 6.73 +/- 0.29 s), 200 m (25.95 +/- 1.20 vs 26.21 +/- 1.42 s), and 400 m (59.01 +/- 4.26 vs 58.68 +/- 3.68 s) were similar for both conditions, as was vertical jump height (0.67 +/- 0.10 vs 0.66 +/- 0.11 m). This occurred despite losing 2.2 +/- 0.4% BM and 7.3 +/- 6.7%[delta]PV (50/200 m) or 2.5 +/- 0.4% BM and 7.1 +/- 2.7% [delta]PV (VJ/400 m) in response to DD.

Conclusions: Diuretic-induced dehydration was not detrimental to sprint and power performance. Metabolic, thermoregulatory, and cardiovascular variables were not significantly altered by DD. Furthermore, the theoretical benefit of dehydration on performance (i.e., BM reduction) was not supported in this subject cohort.

In this paper I use a mathematical model to simulate the effect of wind and altitude on men's and women's 400-m race performances. Both wind speed and direction were altered to calculate the effect on the velocity profile and the final time of the sprinter. The simulation shows that for a constant wind velocity, changing the wind direction can produce a large variation in the race time and velocity profile.

The results of our study suggest that supplementation of ?-ala may improve exercise performance in wrestlers during a competitive season. Because of the design of this experiment, it is impossible to identify exactly how much of the positive effects experienced by the subjects was a direct result of the supplementation. However, due to the large increase in performance and the similarity of results in comparison to other ?-ala studies, we feel our study suggests efficacy of ?-ala supplementation. The ergogenic effects of ?-ala supplementation during a competitive wrestling season needs to be confirmed in placebo-controlled trials.

These results suggest that acute exposure to hypoxia causes a greater degree of peripheral muscle deoxygenation during supramaximal exercise, especially in sprint athletes, and this physiological response would be explained mainly by lower arterial oxygen saturation.

The Pearson product - moment correlation coefficients between the variables for the track and treadmill protocols were 0.96 (vmax), 0.82 (v10 mM), 0.70 (v5 mM), and 0.78 (peak blood lactate concentration) (P<0.05). In sprint runners, the velocity of the seasonal best 400-m run correlated positively with vmax in the treadmill (r = 0.90, P<0.001) and track protocols (r = 0.92, P<0.001). In distance runners, a positive correlation was observed between the velocity of the 1000-m time-trial and vmax in the treadmill (r = 0.70, P<0.01) and track protocols (r = 0.63, P<0.05). It is apparent that the results from the track protocol are related to, and in agreement with, the results of the treadmill protocol. In conclusion, the track version of the maximal anaerobic running test is a valid means of measuring different determinants of sprint running performance.

We investigated the effects of program design on 400-m sprint time by applying a Rating of Perceived Exertion (RPE) mathematical model to training performance. The subject was 24 years old and had been training for 9 years. His best performance in 400-m sprint competitions was 45.50 seconds. Body weight, resting heart rate, training time and RPE were monitored daily after training sessions. Similarly, performance in 400-m races was recorded 9 times during 2003. At the World Championships in Athletics in France, the subject's team placed eighth in the 1,600-m relay. The RPE mathematical model was able to predict changes in performance. Rate of matching was statistically significant (r2 = 0.83, F ratio = 34.27, p < 0.001). Application of the RPE mathematical model to the design of a training program specific to the needs of a 400-m sprinter indicates a potentially powerful tool that can be applied to accurately assess the effects of training on athletic performance.

Purpose: We compared incline and level training sessions as usually used in elite 400-m runners through stride kinematics and muscular activity measurements.

Methods: Nine highly trained 400-m runners (international and French national level) performed two maximal velocity sprints: 1) 300-m on level ground (LEV) and 2) 250-m on an incline ground (INC) characterized by a mean +/- SD grade of 5.4 +/- 0.7%. Kinematics (250 Hz) and electromyography parameters (root mean square [RMS] and integrated electromyography [iEMG] measurements) were analyzed (from 40- to 50-m phases).

Results: INC induced a decrease in running velocity compared to LEV (6.28 +/- 0.38 vs 7.56 +/- 0.38 m[middle dot]s-1) explained by a reduction in stride length (-14.2%) and stride rate (-7.4%) and by an increase in push-off time (+26.4%). Kinematics analysis indicated that the lower limbs were more flexed during INC running. Concerning the level of activity of the lower limb muscles, the major findings pointed out the decrease in RMS for semitendinosus and biceps femoris muscles during the contact phase and for vastus lateralis during its concentric phase. However, iEMG of both semitendinosus and biceps femoris muscles remained constant during both contact and push-off phases.

Conclusion: Our results are clearly different from those of previous studies carried out at similar absolute velocities in both LEV and INC conditions, which were not the case in this study. The lower running velocity marking INC running was associated with a decrease in the activation of the hamstrings. Trainers should particularly consider this lower level of activation of the hamstrings muscles during INC maximal sprint.

The purpose of this study was to determine the value of the peak oxygen deficit (POD) as a predictor of sprint and middle-distance track performance. POD, peak blood laclate, [latin capital V with dot above]O2peak, lactate threshold, and running economy at 3.6 m[middle dot]s-1 were measured during horizontal treadmill running in 22 male and 19 female competitive runners of different event specialties. Subjects also completed running performance trials at 100, 200, 400, 800, 1500, and 5000 m. Correlations of track performances with POD (ml[middle dot]kg-1) (-0.66, -0.71, -0.71, -0.62, -0.52, and -0.40) were moderately strong at the sprint and middle distances, accounting for 44-50% of the performance variance at the three shortest distances. Correlations of track performances with peak blood lactate concentration were lower than with POD and accounted for approximately one-half as much of the performance variance (21-26%) at the three shortest distances. Multiple regression analyses indicated that the POD was the strongest metabolic predictor of 100-, 200- and 400-m performance, and that [latin capital V with dot above]O2peak was the strongest metabolic predictor of 800-, 1500-, and 5000-m performance. We conclude that the POD is a moderately strong predictor of sprint and middle-distance track performance.

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