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Liza Stathokostas and Gareth R. Jones

A convenience sample of 176 healthy, community-dwelling, inactive older adults (mean age 70 ± 5 years; 62 males, 114 females) were tracked for one year. The purpose was to describe the exercise modality choices older adults make one year following participation in an exercise and education intervention. Telephone follow-up contacted 137 participants (78%, men = 50, women = 87) and 62% of the men and 69% of the women reported to be “currently exercising.” Exercising independently was the most common type of exercise reported by 81% and 64% of men and women, respectively. Walking was the most commonly reported modality by both genders. The setting of exercise was most often reported to be at home or outside for both men and women. The main reason for continued participation at 12 months was for overall health (50% of men and 40% of women). Little variation was observed for exercise modality choice. Future interventions should consider a variety of exercise and physical activity opportunities for older adults.

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Øyvind Sandbakk, Thomas Haugen, and Gertjan Ettema

), intensity, and frequency with subsequent adaptations interplaying with recovery periods, which have been heavily investigated in previous research literature. 2 – 19 In contrast, the influence of exercise modality on training load management remains relatively unexplored. External training load is defined

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Chun-Chih Wang, Brandon Alderman, Chih-Han Wu, Lin Chi, Su-Ru Chen, I-Hua Chu, and Yu-Kai Chang

exercise modality, acute exercise was shown to significantly improve cognitive function across all Stroop task conditions. In addition, although both acute exercise modalities resulted in higher cortisol responses compared with the no exercise control condition, no differences were observed between the two

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Marc Sim, Brian Dawson, Grant Landers, Dorine W. Swinkels, Harold Tjalsma, Debbie Trinder, and Peter Peeling

The effect of exercise modality and intensity on Interleukin-6 (IL-6), iron status, and hepcidin levels was investigated. Ten trained male triathletes performed 4 exercise trials including low-intensity continuous running (L-R), low-intensity continuous cycling (L-C), high-intensity interval running (H-R), and high-intensity interval cycling (H-C). Both L-R and L-C consisted of 40 min continuous exercise performed at 65% of peak running velocity (vVO2peak) and cycling power output (pVO2peak), while H-R and H-C consisted of 8 × 3-min intervals performed at 85% vVO2peak and pVO2peak. Venous blood samples were drawn pre-, post-, and 3 hr postexercise. Significant increases in postexercise IL-6 were seen within each trial (p < .05) and were significantly greater in H-R than L-R (p < .05). Hepcidin levels were significantly elevated at 3 hr postexercise within each trial (p < .05). Serum iron levels were significantly elevated (p < .05) immediately postexercise in all trials except L-C. These results suggest that, regardless of exercise mode or intensity, postexercise increases in IL-6 may be expected, likely influencing a subsequent elevation in hepcidin. Regardless, the lack of change in postexercise serum iron levels in L-C may indicate that reduced hemolysis occurs during weight-supported, low-intensity activity.

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Katja Tomazin, Jean-Benoit Morin, and Guillaume Y. Millet

Purpose:

To compare neuromuscular fatigue induced by repeated-sprint running vs cycling.

Methods:

Eleven active male participants performed 2 repeated-maximal-sprint protocols (5×6 s, 24-s rest periods, 4 sets, 3 min between sets), 1 in running (treadmill) and 1 in cycling (cycle ergometer). Neuromuscular function, evaluated before (PRE); 30 s after the first (S1), the second (S2), and the last set (LAST); and 5 min after the last set (POST5) determined the knee-extensor maximal voluntary torque (MVC); voluntary activation (VA); single-twitch (Tw), high- (Db100), and low- (Db10) frequency torque; and maximal muscle compound action potential (M-wave) amplitude and duration of vastus lateralis.

Results:

Peak power output decreased from 14.6 ± 2.2 to 12.4 ± 2.5 W/kg in cycling (P < .01) and from 21.4 ± 2.6 to 15.2 ± 2.6 W/kg in running (P < .001). MVC declined significantly from S1 in running but only from LAST in cycling. VA decreased after S2 (~–7%, P < .05) and LAST (~–9%, P < .01) set in repeated-sprint running and did not change in cycling. Tw, Db100, and Db10/Db100 decreased to a similar extent in both protocols (all P < .001 post-LAST). Both protocols induced a similar level of peripheral fatigue (ie, low-frequency peripheral fatigue, no changes in M-wave characteristics), while underlying mechanisms probably differed. Central fatigue was found only after running.

Conclusion:

Findings about neuromuscular fatigue resulting from RS cycling cannot be transferred to RS running.

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Marc Sim, Brian Dawson, Grant Landers, Debbie Trinder, and Peter Peeling

The trace element iron plays a number of crucial physiological roles within the body. Despite its importance, iron deficiency remains a common problem among athletes. As an individual’s iron stores become depleted, it can affect their well-being and athletic capacity. Recently, altered iron metabolism in athletes has been attributed to postexercise increases in the iron regulatory hormone hepcidin, which has been reported to be upregulated by exercise-induced increases in the inflammatory cytokine interleukin-6. As such, when hepcidin levels are elevated, iron absorption and recycling may be compromised. To date, however, most studies have explored the acute postexercise hepcidin response, with limited research seeking to minimize/attenuate these increases. This review summarizes the current knowledge regarding the postexercise hepcidin response under a variety of exercise scenarios and highlights potential areas for future research—such as: a) the use of hormones though the female oral contraceptive pill to manipulate the postexercise hepcidin response, b) comparing the use of different exercise modes (e.g., cycling vs. running) on hepcidin regulation.

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Simon Avrillon, Boris Jidovtseff, François Hug, and Gaël Guilhem

Purpose:

Muscle strengthening is commonly based on the use of isoinertial loading, whereas variable resistances such as pneumatic loading may be implemented to optimize training stimulus. The purpose of the current study was to determine the effect of the ratio between pneumatic and isoinertial resistance on the force–velocity relationship during ballistic movements.

Methods:

A total of 15 participants performed 2 concentric repetitions of ballistic bench-press movements with intention to throw the bar at 30%, 45%, 60%, 75%, and 90% of the maximal concentric repetition with 5 resistance ratios including 100%, 75%, 50%, 25%, or 0% of pneumatic resistance, the additional load being isoinertial. Force-, velocity-, and power-time patterns were assessed and averaged over the concentric phase to determine the force–velocity and power–velocity relationships for each resistance ratio.

Results:

Each 25% increase in the pneumatic part in the resistance ratio elicited higher movement velocity (+0.11 ± 0.03 m/s from 0% to 80% of the concentric phase) associated with lower force levels (–43.6 ± 15.2 N). Increased isoinertial part in the resistance ratio resulted in higher velocity toward the end of the movement (+0.23 ± 0.01 m/s from 90% to 100%).

Conclusions:

The findings show that the resistance ratio could be modulated to develop the acceleration phase and force toward the end of the concentric phase (pneumatic-oriented resistance). Inversely, isoinertial-oriented resistance should be used to develop maximal force and maximal power. Resistance modality could, therefore, be considered an innovative variable to modulate the training stimulus according to athletic purposes.

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Andrew N. Bosch, Kirsten C. Flanagan, Maaike M. Eken, Adrian Withers, Jana Burger, and Robert P. Lamberts

( Fredericson, 1996 ). During this time, the use of low-impact exercise modalities, such as the “elliptical trainer” and “stepper,” are often used as alternative training ( Mays et al., 2010 ; Roy et al., 2004 ), modalities commonly used by nonrunners in their training regimens. Furthermore, runners that are

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Raphael M. Cunha, Gisela Arsa, Iransé Oliveira-Silva, Izabela Ferreira Rocha, and Alexandre Machado Lehnen

; GEE = generalized estimating equation. * p  < .05 versus preexercise session of the same group. ** p  < .05 versus CS value at same time. † p  < .05 versus immediately after session. Immediately after the exercise, the SBP increased in all exercise modalities when compared with CS (Figure  2B ), RE

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Patrick P.J.M. Schoenmakers, Florentina J. Hettinga, and Kate E. Reed

performance outcomes were reported across a multitude of exercise modalities when recovery duration was increased between work intervals. 14 , 16 , 17 , 18 McEwan et al 17 compared the acute physiological responses and running performance in 12 × 30-second sprints, wherein the recovery duration was either