When "No Load Training" Builds Muscle and Classic Biceps Curls Diminish Your Triceps Size, Science Must be Involved

When "No Load Training" Builds Muscle and Classic Biceps Curls Diminish Your Triceps Size, Science Must be Involved

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Do not misunderstand the results of the study at hand. It does not "proof that you don't have to use weights to make size gains" and it does not even suggest that "training without load works as effectively as training with loads for every muscle".

I suspect you will remember that I have previously written about the potential muscle building effects of posing. Now, the isometric contractions you perform when you "pose", are not exactly the same, but at least related to the "maximal contractions through a full range of motion" Counts et al. investigated in their latest study. Accordingly, it doesn't seem to be totally far-fetched to assume that (1) increases in muscle size would be similar with this type of NO LOAD compared to HIGH LOAD training and that (2) HIGH LOAD training would still result in a greater strength increases compared to NO LOAD due to the principle of specificity.

To elucidate whether these hypotheses are accurate, Counts et al. recruited fifteen (6 men, 9 women) participants for a 6-week study (see Figure 1) ... untrained subjects.

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Untrained? I know what you're thinking, but you got to start somewhere and to measure significant muscle gains in only 6 weeks, your subjects almost have to be untrained; even if this means that it is neither necessarily nor likely possible to transfer your results to trained individuals. It is thus well possible, that the NO LOAD conditions, the authors describe as follows, ...

"[t]he NO LOAD training condition is defined as voluntarily maximally contracting the muscle through the full range of motion without the use of an external load. During each NO LOAD training session, surface electromyography (EMG) electrodes were applied to the biceps to provide feedback to the participant and to help encourage greater activation during each repetition. The participants completed 4 sets of 20 repetitions with 30 seconds of rest between sets. This protocol was based off of pilot work performed in our laboratory which suggested that 4 sets of 20 repetitions should result in increases in both fatigue and muscle activation" (Counts. 2016).

... will have smaller or even no effect at all on the muscle size of already trained individuals - and that would obviously be much in contrast to the tried-and-proven HIGH LOAD training in which the authors completed 4 sets of 8–12 repetitions with 90 s of rest between sets at 70% of their 1RM (weight was increased if more than 12 reps could be done).

Figure 1: Study design outline. 1RM – one repetition maximum (Counts. 2016).

But enough of the "could"s and "might"s. Let's take a look at what we can says for sure: In the study at hand, where both conditions exercised to a metronome at a cadence of 1.5 s for the concentric and eccentric portion of the lift, totaling a 3 s contraction, the subjects were assigned to the NO or HIGH load condition according to a counterbalanced design and the results were quite intriguing:

• Contracting muscle through a full range of motion with no external load increases muscle size similar to high load training.
• High load training produced larger increases in 1RM strength & muscle endurance compared to contracting with no external load.
• Muscle growth can occur independent of the external load provided sufficient tension is produced by the muscle.
• Muscle strength is proportional to the load being used and the modality of exercise being performed (specificity)

More specifically, the study results show that anterior muscle thickness increased similarly from Pre to Post, with no differences between conditions for the 50% [Pre: 2.7 (0.8) vs. Post: 2.9 (0.7)], 60% [Pre: 2.9 (0.7) vs. Post: 3.1 (0.7)] or 70% [Pre: 3.2 (0.7) vs. Post: 3.5 (0.7)] sites, that there is a significant condition × time interaction for one repetition maximum (p = 0.017), with HIGH LOAD (+2.3 kg) increasing it more than the NO LOAD condition (+1 kg) and thus that it is, as Counts et al. write "generally possible to make gains [at least in untrained individuals] across a vast range of external loads and muscle actions" - even independent of external load "provided there are enough muscle fibers undergoing mechanotransduction" (Counts. 2016).

Figure 2: Mean muscle thickness from pre to post training at 50%,60% and 70% sites of the anterior (biceps) & posterior (triceps) upper arm (left) and individual differences in anterior muscle thickness (right | Counts. 2016).

Before you drop the weights altogether, though, you should know that there are a few other limitations of the study (next to the previously hinted at lack of training experience in the subjects) the scientists discuss: They range from the lack of quantitative data on the volume of work completed in the NO LOAD condition (workload is distance times weight - with no weight, you cannot calculate it), of which the scientists say that it "may explain some of the variability in the growth response following NO LOAD training" to the choice of tests which are "more specific to the HIGH LOAD condition and less specific to the NO LOAD condition[. Consequently] it stands to reason that NO LOAD training's effect on strength may be underestimated" (Counts. 2016).

Eventually, the results of the study at hand, as intriguing as they may be, must thus be considered preliminary evidence in support of the mechanotransduction theory of muscle building and its implications, namely that no external load is necessary to stimulate the transcription factors that will eventually initiate the adaptive response to "no-weight lifting" (see Figure below)

Overview of the main events during signal transduction and gene regulation leading to muscle hypertrophy (my orange emphasis in a figure from Rennie, et al. 2004)

So, yes further research is war-ranted to evaluate whether training w/out load could make sense for trained individuals as well.  I have to admit, though, that the existing evidence on the underlying mechanisms of muscle growth supports the notion that training for size does not necessarily involve high weights or muscle damage. After all, the hypertrophy driving trans-criptional factors (see Figure on the right) can be induced by Ca2+ increa-ses, stretch and hypoxia, which can all be achieved in the absence of high loads or sign. muscle damage (Rennie. 2004)... and still, I have my doubts about the effects on trained individuals.

What? Oh, yes... the hint at the reduced posterior muscle (=tripecs) size from the headline. I almost forgot that. Well, the scientists were probably not less surprised than you were when you looked at Figure 2 and realized that the tried and proven "HIGH LOAD condition decreased posterior upper arm muscle thickness following 6 weeks of bicep curl training" (Counts. 2016). Just like me Counts et al. are "not aware of any studies that investigated HIGH LOAD resistance training that targeted only the biceps and measured muscle size of both the biceps and triceps"; and in contrast to what I previously suggested, this cannot be a methodological artifice, because the ultrasound measures the scientists used could distinguish between muscle and fat. What exactly the reason for the ostensible 'atrophy' of the triceps muscle is, may thus still be called a 'mystery' - one that needs to be addressed in future studies, though... (thx Jeremy for spotting this mistake) | What do you think, any ideas on the mechanism? Comment on Facebook!

References:

• Counts, Brittany R., et al. "The acute and chronic effects of “NO LOAD” resistance training." Physiology & Behavior (2016).
• Rennie, Michael J., et al. "Control of the size of the human muscle mass." Annu. Rev. Physiol. 66 (2004): 799-828.

Training in Line W/ Your Genetic Potential Can Boost Your Performance Gains More Than 600%, DNAFit™ Studies Say

Training in Line W/ Your Genetic Potential Can Boost Your Performance Gains More Than 600%, DNAFit™ Studies Say

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While the study at hand appears to confirm that the DNAFit test can tell you if you're an endurance or strength athlete, it won't help you achieve goals you were not "made for" - it eventually you may thus have to give up your dream of being the fastest, strongest or most chiseled guy / gal on the track, field or in gym.

You probably know that: There's that guy at the gym who has been training only half as long as you and still made twice the gains, ... must be juicing that idiot, right? Well, even if we assume that you're not one of the >50% of trainees who overtrain (and undereat) that's by no means the most likely explanation for the astonishing discrepancies.

A recent study that was conducted by a consortium of European researchers is now the first to impressively demonstrate that "matching the individual’s genotype with the appropriate training modality leads to more effective resistance training" (Jones. 2016) What the scientists some of whom work for a company that offers corresponding DNA tests won't tell you, though is that their test will eventually just help you to select the right sport, not to excel in the one sport you have already chosen.

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Eventually, none of this should surprise you, though. Scientists and practitioners alike have suspected for centuries and known for decades that elite athletes are born, not formed in the gym. Association studies have identified dozens of genetic variants linked to training responses and sport-related traits (Table 1 provides a glimpse at the peak of a hitherto largely unknown iceberg of genetic variants that will influence your adaptation to specific training types).

Table 1: List of known genetic variants that influence your adaptation to specific (resistance) training stimuli that were analyzed with the patented DNAFit Peak Performance Algorithm™ in the study at hand (Jones. 2016).

Yes, the way and consistence with which you train will obviously have an effect on the way your physique, strength, speed, conditioning, etc. develops, but when all is said and done, you are simply lucky if you're not lapped by somebody who has trained just as intense- and persistenly who was gifted with a more appropriate gene set for the sports you love. It is thus no wonder that scientists have been pondering about ways to (a) select the right candidates for the right sports and (b) personalizing athletes' training based on their genetic profiles.

In the previously cited study, Jones et al. proposed to do just that by the means of an algorithm that would allow athletes to achieve "greater results in response to high- or low-intensity resistance training programs by predicting athlete's potential for the development of power and endurance qualities" (Jones. 2016).The DNAFit algorithm which is designed to predict the response to high- or low-intensity resistance training programs invokes the 15 performance-associated gene polymorphisms from Table 1.

Figure 1: Both studies used the same randomized, double-blinded crossover design (based on Jones. 2016).

To validate it, its designers from DNA Sports Performance Ltd. and scientists from the University of Central Lancashire, the Universitat Pompeu Fabra and the Parc Científic i Tecnològic Agroalimentari de LleidaPCiTAL performed two studies in independent cohorts of male athletes using in ...

• study 1: athletes from different sports (n=28) / 55 Caucasian male University athletes, all aged 18-20 years, volunteered for the study, and 28 of them (height 180.7 ± 1.5 cm, weight 77.0 ± 2.1 kg) successfully completed it (27 athletes had not completed all aspects of the study due to either injury or illness); each participant was a member of first or second team, actively competing in British Universities and Colleges Sports (BUCS) leagues. The athletes competed in squash (n = 1), swimming (n = 7), running (n = 1), ski/snowboard (n = 4), soccer (n = 1), lacrosse (n = 2), badminton (n = 1), motorsport (n = 1), cycling (n = 4), cricket (n = 2), volleyball (n = 1), fencing (n = 1) and rugby union (n = 2). and 
• study 2: soccer players (n=39) / 68 male soccer players, all aged 16-19 years, volunteered to participate in the study, and 39 of them (height 176.1 ± 1.0 cm, weight 68.9 ± 1.5 kg) successfully completed it (29 participants were withdrawn from the study due to non-adherence of set training volumes over the 8 weeks, or injury); each subject was a member of college soccer academy who actively competed in British Universities & Colleges Sport (BUCS) league.

In both studies athletes completed an eight-week high- or low-intensity resistance training program, which either matched or mismatched their individual genotype. In that, participants of both studies were initially randomly allocated to an eight-week high- or low-intensity resistance-training program, after undergoing performance tests for both explosive power and endurance. After another set of performance tests, they then transitioned to the respective other 8-week intervention, the results of which were then compared with the previous ones and correlated with the subjects gene types.

No, the muscle or strength gains were not assessed: I am not sure why the scientists decided against measuring the lean / fat mass gains / losses. After all, their gene set included the thyrotropin-releasing hormone (TRH) receptor gene where polymorphisms at rs16892496 A/C that influences the secretion of thyroid-stimulating hormone (TSH) and prolactin (PRL) and has been found to modulate the amount of lean mass by Liu et al. in 2009. My best bets are that the reasons are financial ones (DXA is expensive, everything else inaccurate)strategic ones, with 8-weeks of training being unlikely to produce sufficiently inter-group differences in already trained athletes, given the small sample size(s) and range of sports that were included (esp. in study 1), or a mere consequence of the choice of protocols, which did not include a hypertrophy protocol (thus no measurement of muscle gains) and/or would obviously produce greater strength gains with the high intensity protocol (measuring those would thus be useless, too).

As the authors point out, "[t]he study was double blinded, in that all were unaware of their ‘genetic potential status’, as determined by the DNAFit Peak Performance Algorithm™" (Jones. 2016). Since this also included the lead investigator who coached the participants during the 8 weeks of resistance training, the notion that 'this is the optimal training type for me / my trainee' should not have influenced the study outcomes.

Figure 2: Intergroup comparisons of CMJ increases (%) in response to high- or low-intensity training; the %-ages over the bars indicate the difference to the mean effect (all) - It's easy to see that training 'according to your genotype' makes a 40-80% difference even if you compare the speficic to the average success; >100% for inter-group comparisons (Jones. 2016)

And still, as the data from the explosive power and aerobic fitness tests that involved countermovement jumps (CMJ) and an aerobic 3-min cycle test (Aero3) revelead, training 'according' to your genes (or rather the assessment of the DNAFit test), i.e.

• high-intensity trained with power genotype or 
• low-intensity trained with endurance genotype,

significantly increased results in CMJ (P=0.0005) and Aero3 (P=0.0004). Athletes from the mismatched group (i.e. high-intensity trained with endurance genotype or low intensity trained with power genotype), however, demonstrated non-significant improvements in CMJ (P=0.175) and less prominent results in Aero3 (P=0.0134).

Figure 3: Inter-group comparisons of Aero3 increases (%) in response to high- or low-intensity training; left axes = power and endurance genes groups, right axes = all subjects (data from both cohorts | Jones. 2016).

Similar results were observed in the 2nd study, where  soccer players from the matched groups saw significantly greater (P<0.0001) performance changes in both tests compared to the mismatched group. In that, the following facts are particularly noteworthy:

• the advantage of training 'according to your genotype' ranges from ~40% to ~80% even if you compare it to the average training response (Figure 1, "all");
• comparing training according to training in discordance with your genotype(s) yields differences that range from 55% up to 610% (the latter in the soccer players on the low intensity regimen for CMJ; Figure 1, study 2 / low intensity)

What is maybe even more important than the statistically significant differences in the mean gains is the consistency of failure, i.e. the fact that Among non- or low responders of both studies, 82% of athletes (both for CMJ and Aero3) were from the mismatched group (P<0.0001).

Remember? Your Post-Workout Testosterone Levels Can Predict Your Gains - Study Takes Novel Approach to the T ↔ Muscle Link | Learn more

Bottom line: As the (maybe biased) authors of the study point out, their well-designed and appropriately blinded trial clearly "indicate[s] that matching the individual’s genotype with the appropriate training modality [as determined with 'their' proprietary DNAFit test] leads to more effective resistance training" (Jones. 2016). It does therefore stand to reason that "[t]he developed algorithm may be used to guide individualised resistance-training interventions" (Jones. 2016). Whether that's actually useful for the average gymrat, whose goal may diverge sign. from what he was 'born to achieve', though, is another story... at least until you'll be able to home-brew / -tweak your genes with CRISPER ;-)

Another thing we shouldn't forget is that getting big and buffed, the goal of a majority of male gymgoers, wasn't even investigated in the study at hand... I bet, though, that future studies with different training regimen and study populations (e.g. untrained individuals) will assess and probably find similar results for muscle and strength gains - And you know where you will be able to read about their results, right? | Comment on Facebook!

References:

• Jones, N., et al. "A genetic-based algorithm for personalized resistance training." Biol Sport 33.2 (2016): 117-126.
• Liu, Xiao-Gang, et al. "Genome-wide association and replication studies identified TRHR as an important gene for lean body mass." The American Journal of Human Genetics 84.3 (2009): 418-423.

Your Post-Workout Testosterone Levels Can Predict Your Gains - Study Takes Novel Approach to the T ↔ Muscle Link

Your Post-Workout Testosterone Levels Can Predict Your Gains - Study Takes Novel Approach to the T ↔ Muscle Link

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GainZ - Are they all about T and we just didn't do the right statistical tests in previous studies to realize that?

Only recently one of the longstanding "truths" of protein anabolism has been busted (learn why the acute muscle protein synthesis response matters more than prev. thought). And now, a new paper in the Journal of Strength and Conditioning Research (Mangine. 2016), appears to suggest that the lack of effect of exercise induced hormone elevations may have been misunderstood, too.

In the conclusion of their study, Mangine et al. point out that the previously used "[t]raditional statistical measures do not adequately assess the relationships between multiple variables that exist across time" (Mangine. 2016).

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In order to overcome this problem, their study used what the scientists call a "unique method for analyzing these types of relationships without the need for transforming data"; and - first things first - their the PLS-SEM analysis (details below) shows: "baseline muscle size and the hormonal response to resistance exercise are related to muscle hypertrophy following 8 wks of training  (Mangine. 2016).

Figure 1: The scientists ,odel for the relationship between changes in muscle size and the endocrine response to resistance exercise predicts influence of all hormones on muscle size and vice versa(!); RF_CSA = Rectus femoris cross-sectional area; RF_MT = Rectus femoris muscle thickness; VL_CSA = Vastus lateralis cross-sectional area; VL_MT = Vastus lateralis muscle thickness; WK1 = Week 1; WK8 = Week 8 (Mangine. 2016).

Moreover, the data from the Kennesaw State University, the University of Central Florida and the College of New Years appears to suggest that the often derided exercise-induced post-workout (PWO) increases in testosterone concentrations may be the most important agent in the hormone quintet of testosterone, cortisol, growth hormone, IGF-1, and insulin that is going to react to every intense resistance training study.

Figure 2: Sign. associations between PWO hormone levels and lean mass, as well as fiber size increases (West. 2012).

That's surprising in two ways: (A) the majority of previous studies refuted the existence of a practically relevant link between the amount of muscle you will gain and the change in hormone levels, altogether. And (B) you will remember that my hitherto favorite study on the "[a]sociations of exercise-induced hormone profiles and gains in strength and hypertrophy in a large cohort after weight training" by West and Phillips (2012) showed in a large cohort that - if there is any link between the PWO hormone response to resistance training and the changes in muscle size it would be a link to growth hormone (GH) and cortisol (see Figure 2).

Free testosterone (upper line) and cortisol (lower line) levels before and after exhaustive endurance exercise in trained young men (Anderson. 2016).

Excess cardio cannot, it will ruin your testosterone levels and (surprise) 24h post also your cortisol levels: The data in the figure on the left hand side was recorded in a recent study by Anderson et al. (2016) who observed that the full recovery of free testosterone and cortisol after an exhaustive endurance exercise session (prolonged exercise run on the treadmill until volitional fatigue, running at 100 % of ventilatory threshold (VT), within 3 % - 75 minutes) will take 48h - even in endurance trained fit, young men such as the 12 subjects (VO2max 66.3±4.8 ml/kg/min, age 22.8 ± 3.1 years, body fat 11.0 ± 1.4 %, training 7.1y) Anderson et al recruited.

That's obviously significantly different from what we see in the Magine study, at hand, where the likewise previously trained subjects completed at least 28 resistance training sessions (~90%) of an 8-wk resistance-training program (4 sessions/wk) that included six upper- and lower-body exercises during each session, under supervision of certified strength & conditioning specialists.

With the inclusion of potential influence of the initial muscle mass on the hormonal response to exercise Magine's study does now suggest what many trainees still believed, anyways: "When it comes to making gainz, the testosterone response to workouts counts." Furthermore, the scientists argue that the reason studies like McCall et al. (1999), Ahtianinen et al. (2003), and Walker et al. (2015), which used Pearson’s product moment correlation coefficients or Spearman’s rank correlation coefficients (Walker. 2014) were conflicting and not really reliable, because...

"significant amount of information [that] is lost when using either of these statistical procedures for assessing the relationships between concepts that exist across time (i.e. hypertrophy, multiple endocrine responses) because the statistics can only assess the relationship between two sets of values" (Mangine. 2016). 

With their approach, on the other hand, Mangine et al. (2016) transformed the correlation between hypertrophy and the endocrine response from baseline and post-testing into a single value (i.e. change score, average score). The method to do this is called "partial least squares structural equation modeling" (PLS-SEM) and it allows estimating complex cause-effect relationship models with latent variables. Since it is a component-based estimation approach, it differs from the covariance-based structural equation modeling you'd usually expect to be used and constitutes, as the scientists summarize

"[...] a variance based procedure that utilizes bootstrapping to statistically assess the relationships between multiple latent variables that are developed from several collected indicator variables [which has] been used to assess relationships within the biomedical sciences [already... even though] it has not yet been used to assess the relationships between the post-exercise endocrine response and muscle hypertrophy" (Mangine. 2016).

For it to work, the authors obviously have to assume that "the related variables were collected without systematic or random error" in their experiment that included pre-tests (PRE) of measures of muscle size (thickness and cross-sectional area) of the vastus lateralis and rectus femoris in 26 resistance-trained men who were randomly selected to complete a high-volume (VOL, n=13, 10–12RM, 1-min rest) or high-intensity (INT, n = 13, 3–5RM, 3-min rest) resistance training program while following a food-log controlled diet that was supplemented with a standardized supplement containing ~235 mL of chocolate milk (170 calories; 2.5g Fat; 29g Carbohydrate; 9g protein) or Lactaid® (150 calories; 2.5g Fat; 24g Carbohydrate; 8g protein) to each participant immediately following each workout.

A pre- vs post-workout salivary testosterone test could hold the clue to the perfect workout | more

Another argument that "testosterone may count" comes from a previously discussed, but in my humble opinion largely overlooked study by Beaven et al. (2008) whose study into the correlation between the individual testosterone response to a certain workout style and the subsequent gains subjects in a randomized cross-over design study made also suggests that "testosterone counts". Sounds intruiging? I know, but the corresponding SuppVersityarticle from 2013 went almost as unrecognized as the original paper that was published 5 years before in the Journal of Strength and Conditioning Research - the same journal in which Mangine et al. have now published the results of their study.

Blood samples were collected at baseline, immediately post-exercise, 30-min, and 60-min post-exercise during weeks 1 (WK1) and 8 (WK8) of training and testosterone, growth hormone [22 kD], insulin-like growth factor-1, cortisol, and insulin levels were evaluated using area-under-the-curve (AUC) analyses of the blood values, based on which the scientists were able to identify the relationships between muscle size (PRE), AUC values (WK1 + WK8) for each hormone, and muscle size (POST) "using a consistent PLS-SEM algorithm and tested for statistical significance (p<0.05) using a 1000 samples consistent bootstrapping analysis" (Mangine. 2016).

Figure 3: Actually significant was only the link between the effect of the muscle mass before the study and the testosterone response and the testosterone response on the muscle mass after the 8-wk study (Mangine. 2016).

The model the scientists developed was capable of explaining 73.4% (p<0.001) of variance in muscle size at POST and revealed "[s]ignificant pathways between testosterone and muscle size PRE (p=0.043) and muscle size at POST (p=0.032) were observed.

Table 1: In contrast to what you may have expected, there was no sign difference in the way the hormones effected the outcomes of the 8-wk resistance training study between the high intensity and volume arm (Magine. 2016).

And while the ability to explain muscle size at POST improved when the model was analyzed by group (INT: VOL: p<0.001), the data in Table 1 goes to show you that the researchers found no group differences between the intense low volume and the moderate intensity high volume training. This in turn suggests that the link between muscle size and post-exercise increases in hormone levels - especially the effects on testosterone - are universal and do not dependent on the training type (volume vs. high intensity), as previous studies that argued in favor of volume training based on its more pronounced effects on the hormone response to exercise suggested.

In view of the conflicting evidence and hitherto relatively conclusive evidence that endogenous T & co elevations do not matter, I would not begin to train "for testosterone elevations", now... you may after all still be barking up the wrong tree. Correlations and links are after all no causations | learn more

Bottom line: I would like to point out that the study at hand does not provide sufficiently reliable evidence to say that Mangine, et al. had 'proven that the post-workout testosterone increase had a mechanistic effect on your muscle gains'. What it does show, however, is, just as the scientists say, that "[e]xercise-induced testosterone elevations, independent of the training programs used in this study, appear to be related to muscle growth" (Magine. 2016, my emphasis in the quote).

This is in contrast to previous studies, where the pre-tfiraining correlation between muscle mass and thus testosterone levels had not been accounted for. The scientists' partial least squares regression structural equation modeling (PLS-SEM), however, is eventually just "statistical shenanigan". Therefore, its impressive explanatory power of 73.4% of the variance in muscle size following 8 wks of resistance training is a neat figure, but no proof of a mechanistic link.

Furthermore, one has to be careful to falsely single out testosterone among the five hormones that were assessed. After all, restricting the model to T, which was the only significant hormonal correlate of muscle gains, reduced the explanatory power of the model by only 30.8%. This leaves the rest of the hormones with an explanatory power of 42.6% (all statistics, obviously ;-). To say that GH, IGF-1, insulin and cortisol had 'no say' in skeletal muscle hypertrophy is thus just as unwarranted as the previously hinted at (false) conclusion that the study at hand would provide the long-sought definitive evidence of the muscle building effects of exercise-induced, natural testosterone surges, i.e. the temporary elevation of T-levels after a workout | Comment!

References:

• Ahtiainen, Juha P., et al. "Muscle hypertrophy, hormonal adaptations and strength development during strength training in strength-trained and untrained men." European journal of applied physiology 89.6 (2003): 555-563.
• Beaven CM, Cook CJ, Gill ND. Significant strength gains observed in rugby players after specific resistance exercise protocols based on individual salivary testosterone responses. J Strength Cond Res. 2008 Mar;22(2):419-25.
• Mangine, Gerald T., et al. "Exercise-Induced Hormone Elevations Are Related To Muscle Growth." The Journal of Strength & Conditioning Research (2016).
• McCall, Gary E., et al. "Acute and chronic hormonal responses to resistance training designed to promote muscle hypertrophy." Canadian Journal of Applied Physiology 24.1 (1999): 96-107.
• Walker, Simon, et al. "Effects of prolonged hypertrophic resistance training on acute endocrine responses in young and older men." Journal of Aging & Physical Activity 23.2 (2015).
• West, Daniel WD, and Stuart M. Phillips. "Associations of exercise-induced hormone profiles and gains in strength and hypertrophy in a large cohort after weight training." European journal of applied physiology 112.7 (2012): 2693-2702.

Important Insights into Muscle Growth: Muscle Breakdown & Protein Synthesis Balance Determines Your Muscle Gains

Important Insights into Muscle Growth: Muscle Breakdown & Protein Synthesis Balance Determines Your Muscle Gains

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MyoPS - muscle damage = gainz - It's as easy as that, but this simple equation gets complicated by decreases in both...

You will remember from previous SuppVersity articles that the assumption that an acute increase in myofibrillar protein synthesis (MyoPS) you measure after a workout would necessarily translate into "muscle gains" is oversymplistic. In fact, a correlation between muscle hypertrophy and acute MPS has been shown not to exist (learn more).

In the introduction to their latest paper, Felipe Damas et al. (2016) highlight our lack of understanding of the different mechanisms that eventually determine t he hypertrophy response to resistance training.

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To investigate how muscle hypertrophy is modulated through RT, Damas et al. "measured day-to-day integrated myofibrillar protein synthesis (MyoPS) using deuterium-oxide ingestion and assessed muscle damage at the beginning (T1), at 3wk (T2), and 10wk of RT (T3)" in a study that involved ten young men (27(1) y) who had muscle biopsies (vastus lateralis) taken to measure integrated MyoPS and muscle damage (Z-band streaming and indirect parameters) before and 24h and 48h post-resistance exercise (RE) at T1, T2 and T3.

Figure 1: Experimental design. RE: resistance exercise; D2O: deuterated water; MVC: maximal voluntary isometric torque; SOR: muscle soreness; T1: 1st week of resistance training (RT); T2: 3rd week of RT; T3: last week of RT (Damas. 2016).

The analysis of the data from the subjects who had prior experience in lower limb RT, before they trained their lower limbs (bilateral 45° leg-press exercise and leg extension) for 10 weeks in the study at hand (twice a week, totaling 19 workouts), but who had not engaged in lower limb RT for at least 6 months prior to the study and did not use vitamin supplements or anti-inflammatory medications chronically were recruited, provided some interesting insights.

Figure 2: Fibre cross-sectional area (CSA) at the first week (T1), third week (T2) and tenth week (T3) of resistance training. † Significantly different (P < 0.05) from T1 and T2. Values are means (SEM | Damas. 2016)

Firstly, there's the increase in fibre cross-sectional area, which was observed to be significant only when the scientists compared the fcsa at T3 compared with T1 (P =0.017) and T2 (P = 0.027; see Figure 2) - in other words: Significant gains were made only over the latter part of the training period.

Figure 3: (A) Myofibrillar (Myo) fractional synthetic rate (FSR) at rest, 24h and 48h following a single bout of resistance exercise at the first week (T1), third week (T2) and tenth week (T3) of resistance training. * Significantly different (P < 0.05) from rest at T1. # Main acute time effect (24h significantly different (P = 0.003) from 48h independent of training phase). ‡ Main training phase effect (T1 significantly different (P < 0.03) from T2 and T3). (B) Change from baseline in the percentage of fibres that showed any Zband streaming sign following a single bout of resistance exercise at the T1, T2 and T3. ‡ Significantly different (P < 0.05) from T2 and T3. + Significantly different (P < 0.05) from T3 (Damas. 2016).

These increases in the actual muscle size gains (vs. MyoPS) are the related to the second and most important observation, which is, as the highly significant decrease in Z-Band data in Figure 3.b indicates, a result of the improved difference between muscle protein synthesis, which decreased much less than the protein breakdown the scientists approximated by the means of directly assessed muscle ultrastructure changes (Z-band streaming). In other words: the "net gains" increased over time, as the subjects accommodated to the workouts.

In the previous study by Mitchell et al. (2014) there was no correlation between MyoPS / FSR andn the actual increase in muscle size over 16 weeks.

Bottom line: One thing that is important to highlight is the training status of the subjects of whom I previously pointed out that "had not engaged in lower limb RT for at least 6 months prior to the study" (Damas. 2016). This is important, because it is probably the prerequisite for the time-effect. A time effect which is characterized by (a) slightly decreasing protein synthesis from week one to week three (and following) and highly significantly decreasing muscle damage over the first 3 weeks, over which the muscle damage due to the initially unaccustomed exercise declined progressively.

Accordingly, Damas et al. were able to confirm a correlation between MyoPS, i.e. the myofibrillar protein synthesis, and the actual muscle hypertrophy that had not been observed by Mitchell, et al. (2014 | read up on the study in my previous article) only in the latter ~70% of the study when the net muscle gains increased due to the significant decrease in protein breakdown.

That the results of this study which are in disagreement with a previous studies that found "acute increases in MyoPS aligned qualitatively with hypertrophy-related chronic RT outcomes, such as increases in muscle volume and muscle fibre CSA (fCSA)" would be "due to damage to protein structures that would require repair, and therefore a greater increase in protein synthetic response" was the point of departure for Damas et al. in the study at hand. And it is also what the data the experiment generated confirmed: "Despite the lack of correlation between initial MyoPS and muscle hypertrophy, we observed that early (T2) and later (T3) rates of MyoPS, while attenuated compared to initial (T1), were strongly correlated with muscle hypertrophy" (Damas. 2016).

Another related and likewise important important finding of the study at hand is the observation that the subjects' muscle damage, on the other hand, "which was progressively mitigated throughout RT reaching a minimal magnitude at the end of 10wk of RT, did not correlate with MyoPS or hypertrophy at any time point during RT" (Damas. 2016). Eventually, the exercise induced increase in protein synthesis may thus still be considered the determinant factors underpinning RT-induced muscle hypertrophy in - as long, at least, as we are looking at trained subjects doing exercises they have already accommodated to (within ~3 weeks) | Comment on Facebook!

References:

• Damas, Felipe, et al. "Resistance training‐induced changes in integrated myofibrillar protein synthesis are related to hypertrophy only after attenuation of muscle damage." The Journal of physiology (2016).
• Mitchell, Cameron J., et al. "Acute post-exercise myofibrillar protein synthesis is not correlated with resistance training-induced muscle hypertrophy in young men." PLoS One 9.2 (2014): e89431.

Not Resting Long Enough May Ruin Your Gains! 1 vs. 5 min Cut Post-Workout Increase in Protein Synthesis by 50% !

Not Resting Long Enough May Ruin Your Gains! 1 vs. 5 min Cut Post-Workout Increase in Protein Synthesis by 50% !

build muscle gains gainz hypertrophy inter-set rest muscle protein synthesis protein synthesis rest rest intervals

Rest is not a waste of time ;-)

You may remember Schoenfeld et al's 2015 study with the telling title "Longer inter-set rest periods enhance muscle strength and hypertrophy in resistance-trained men" (Schoenfeld. 2015) and Henselmann's and Schoenfeld's previous review of "The Effect of Inter-Set Rest Intervals on Resistance Exercise-Induced Muscle Hypertrophy" stating that "the literature does not support the hypothesis that training for muscle hypertrophy requires shorter rest intervals than training for strength development or that predetermined rest intervals are preferable to auto-regulated rest periods in this regard" (Henselmann. 2004).

Eventually, it can thus not be surprising that James McKendry and colleagues write in their latest paper that "short rest (1 min) between sets of moderate-intensity, high volume resistance exercise blunts the acute muscle anabolic response compared with a longer rest period (5 min), despite a superior circulating hormonal milieu," and conclude that their "data have important implications for the development of training regimens to maximize muscle hypertrophy" (McKendry).

Want to bump up the volume? Add bicarbonate as a pH-buffer to make that possible!

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HIIT it Hard W/ NaCHO3

Creatine + BA = Perfect Match

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Beta Alanine Fails to HIIT Back

What may be surprising, though, is the extent (see Figure 2) to which the post-exercise protein synthesis the researchers measured in young male subjects who habitually performed lower-limb resistance training at least once per week for ≥1 year prior to study enrollment and were deemed ‘recreationally trained’, when they had them do the same leg workout

• 4 sets of leg press and 4 sets of knee extension exercise at 75% of 1RM
• performed w/ a lifting-lowering cadence of ~1 sec in both concentric & eccentric phases, 
• without pause, until momentary muscular failure (i.e. 9-10 on the Borg CR-10 scale). 

with either five minutes or one minute of passive rest between sets and gave them 25g of whey protein isolate (MyProtein, Cheshire, UK) right after the workout to kickstart the protein synthesis.

Figure 1: Overview of the initial (Trial 1) and next morning procedures (Trial 2 | McKendry. 2016).

After having ingested the whey protein shake, the participants rested in both trials supine for 240 minutes. After those 4h, another muscle biopsy was obtained ~3cm proximal to the second biopsy to determine MPS rates over the ‘early’ phase (0-4 h) of post-exercise recovery. The data from this phase was complemented by data from a last, fourth muscle biopsy on the next morning and after consuming an identical protein shake after 10h of fasting (lunch and dinner on the day before were standardized, so that this would not mess with the results).

Figure 2: Protein synthetic (myofibrillar) and hormone response after working out with 1 vs. 5 min rest (McKendry. 2016).

Whether and to which extent the sign. difference in protein synthesis of which the scientists say that it is an 76% vs. 152% increase in the 0-4h time-window after the workout is related or even triggered by the significantly higher GH response in after the 5-min rest trial is questionable, but if you recall the seminal paper by West et al. (2012), you will certainly remember that GH and cortisol are the only hormones the levels of which after a workout show any correlation with muscle gains (see Figure 3).

Figure 3: Sign. associations between PWO hormone levels and lean mass, as well as fiber size increases (West. 2012).

With that being said, you may consider this odd, because usually the metabolically more demanding short-rest workout will yield greater GH increases (Kraemer. 1990; Goto. 2004; Bottaro. 2009) - this and the fact that the previously hinted at association exists, but the incline or, in other words, the effect on fiber size per unit increase in GH is low (too low to fully explain the 5-minute-advantage) suggest that there must be more to it than the small GH increase with 5 minutes vs. 1 minute rest.

Why do other studies not confirm this finding? I guess that depends on the study. An often-cited paper by Kraemer, et al. for example found 1 minute of rest to outperform 3 minutes hypertrophy-wise - probably because the 1-min rest protocol involved 3 sets of 8 exercises with a 10-RM load, while the 3 minute protocol involved "only" five sets of five exercises, performed with a 5-RM load, so that the two workouts were not volume equated and the study no comparison of workouts with different rest times, but rather one of hypertrophy vs. strength workouts.

Acute effect of different rest intervals between sets over the number of repetitions maximum (RM). Values expressed as RM (de Salles. 2009)

Conflicting results from other studies, e.g. Villanueva, et al. (2015) who found sign. greater muscle gains in with 1 vs. 4 minutes of rest, may be explained by differences in the study population (elderly in Villanueva, et al.) and/or the training protocol, which did not involve training to failure and thus probably didn't produce significant volume advantages for the 4-minute rest group. Eventually, volume appears to be, within sustainable limits, the most sign. determinant of the hypertrophy response to exercise, so if you do something to increase it (e.g. myoreps or real vs. volume- equated drop sets, etc.) you may still benefit. If you simply cut the rest, however, the volume suffers from not resting long enough (cf. table on the left) and this may affect your gains.

The existing differences in  anabolic signaling protein phosphorylation (e.g. p70S6KThr389, rpS6Ser240/244, 4EBP1Thr37/46, etc.) can likewise not serve as a mechanistic explanation. After all, these are the switches that trigger the growth. Saying they are responsible would be tantamount to saying that the light switch is the reason the light went out, when someone actually switched it off.

So, what is it that makes the difference? Well, in view of the results of previous studies that suggest that, ultimately, it's not hormones, not protein phosphorylation, but rather the total volume of weight that is lifted (at least unless that's so much that you do more harm than good) that determines the hypertrophy response to resistance training (Schoenfeld. 2013), we should look at a different study outcome: the total volume in kilograms (see Figure 4):

Figure 4: Set- and total volume when subjects trained with 1 vs. 5 minutes rest (McKendry. 2016).

That the sign. difference in volume on set 3 and 4, and the significant difference in total volume are actually the explanation, is obviously speculative, but at least for me it is the most likely explanation for a difference (see red box, as well).

The ineffectiveness of drop-sets in Fisher's recent study may in fact also have been a result of a lack of difference in training volume | more

Bottom line: Eventually, the study at hand only proves what we already knew - training volume is more important than metabolic stress when it comes to hypertrophy gains.

Any training regimen / modification that reduces the total volume of weight lifted may thus potentially compromise your gains... if the volume is in fact all that is to the effects of shortening rest times will obviously still have to be determined. As of now, volume is yet the best explanation for the differences or lack of differences and effects scientists observed in this and previous studies such as the recently discussed dropset study by Fisher et al. where the set-volume standardization may have blocked any sign. advantage of real-world (=add-on) dropsets | Discuss!.

References:

• Bottaro, Martim, et al. "Effects of rest duration between sets of resistance training on acute hormonal responses in trained women." Journal of science and medicine in sport 12.1 (2009): 73-78.
• de Salles, Belmiro Freitas, et al. "Rest interval between sets in strength training." Sports Medicine 39.9 (2009): 765-777.
• Goto, Kazushige, et al. "Muscular adaptations to combinations of high-and low-intensity resistance exercises." The Journal of Strength & Conditioning Research 18.4 (2004): 730-737.
• Henselmans, Menno, and Brad J. Schoenfeld. "The effect of inter-set rest intervals on resistance exercise-induced muscle hypertrophy." Sports Medicine 44.12 (2014): 1635-1643.
• Kraemer, WJ, Marchitelli, L, Gordon, SE, Harman, E, Dziados, JE, Mello, R, Frykman, P, McCurry, D, and Fleck, SJ. Hormonal and growth factor responses to high intensity resistance exercise protocols. J Appl Physiol 69: 1442-1450, 1990.
• Schoenfeld, Brad J. "Postexercise hypertrophic adaptations: a reexamination of the hormone hypothesis and its applicability to resistance training program design." The Journal of Strength & Conditioning Research 27.6 (2013): 1720-1730.
• Schoenfeld, Brad J., et al. "Longer inter-set rest periods enhance muscle strength and hypertrophy in resistance-trained men." Journal of strength and conditioning research/National Strength & Conditioning Association (2015).
• Villanueva, Matthew G., Christianne Joy Lane, and E. Todd Schroeder. "Short rest interval lengths between sets optimally enhance body composition and performance with 8 weeks of strength resistance training in older men." European journal of applied physiology 115.2 (2015): 295-308.
• West, Daniel WD, and Stuart M. Phillips. "Associations of exercise-induced hormone profiles and gains in strength and hypertrophy in a large cohort after weight training." European journal of applied physiology 112.7 (2012): 2693-2702.
• Willardson, Jeffrey M. "A Brief Review: How Much Rest between Sets?." Strength & Conditioning Journal 30.3 (2008): 44-50.