Alpha-GPC Lab Test

Today I had some free time in my physiology lab so I decided to hook myself up to an EMG to test out Alpha-GPC. I used a hand dynamometer (basically a tube you squeeze which measures force in newtons) and did 4 max output squeezes.

The results were 343.7N, 361.9N, 359.1N and 307.3N. After, I took 900mg of Alpha-GPC and waited 90 minutes. After the 90 minutes were up I tested again and the results were 413.9N, 440.6N, 414.5N and 381.7N. I did statistical analysis on the data and T=4.003 and P=.0035! Thought this was pretty cool and worth sharing with everyone

Interesting… If you have time, would you try setting up a double blind placebo test? I would suggest doing it with a couple buddies (haha) and get them to do two trials, one with Alpha-GPC and one with sugar pills. Have them do two trials, one with and one without. Set it up so that they take the Alpha-GPC at different times (one guys take it for the first trial, and the other guy takes the placebo for the first trial, then reverse it for the second trial).

yeah I’m hoping to do something similar to that sometime soon. This was just kinda made up on the spot since I happened to have Alpha-GPC in my bag with me and the EMG available. Hopefully I’ll be able to do something a little more structured soon.

I agree. These are very cool results and if you do any further testing, I hope you will share the results. Were there any other variables that could affect the results, such as food, caffeine, hot science babes stroking the test tubes, etc.?

Very interesting thanks. I hope to be working with groups of athletes soon and will be experimenting with various WADA-legal noops to investigate CNS/strength improvments.

BBB

Wait, what was the EMG used for in this experiment?

BBB

Your test/experiment is worthless. Like Bulletproof Tiger said, you’d need at least 20-30 people doing a double blind placebo test to have any statistical meaning to your results.

Pity you didn’t repeat after 90mins without the supp. BTW 'placebo effect is very powerful… what were you expecting to get

[quote]JN7844 wrote:
I agree. These are very cool results and if you do any further testing, I hope you will share the results. Were there any other variables that could affect the results, such as food, caffeine, hot science babes stroking the test tubes, etc.?[/quote]

I ate a small meal about an hour before the baseline test and didn’t eat again until after the test with alpha-GPC. No caffeine and unfortunately no hot science babes

the hand dynamometer was run through the EMG.

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at the risk of sounding stupid could you put that in laymens terms?

Thanks

[quote]Josh Rider wrote:
Your test/experiment is worthless. Like Bulletproof Tiger said, you’d need at least 20-30 people doing a double blind placebo test to have any statistical meaning to your results.[/quote]

While a double blind placebo induced study is the best and most reliable setup it is in no way necessary for the results to have statistical meaning.

Wow, some of you are ridiculous.

The guy did this on a whim. It’s not like Biotest wrote an article stating this was their testing to prove the supplement works.

He just wanted to try it out. OP, how dare you share your experiences with us while being honest with your testing procedures, lol

[quote]MattyXL wrote:
at the risk of sounding stupid could you put that in laymens terms?

Thanks[/quote]

basically I hooked myself up to a machine that measured the amount of force I could produce (while squeezing my hand) I did for “reps” of this and my force output was 343.7N, 361.9N, 359.1N and 307.3N. N stands for Newtons which is just a way of measuring force. After I did this I took 900mg of Alpha-GPC and waited 90 minutes for it to kick in, then repeated the experiment.

After taking Alpha-GPC my results were 413.9N, 440.6N, 414.5N and 381.7N, as you can see, they were higher than without it. I ran statistical tests on the data and got a P value of .0035. The P-value is amount of evidence required to accept that an event is unlikely to have arisen by chance. A P-value of .01 means there is a 1% chance that you would get this data if the null hypothesis was true (null hypothesis being Alpha-GPC doesnt work) Since the P-value I received was .0035 there is less than a 1% chance of this being true.

[quote]Josh Rider wrote:
Your test/experiment is worthless. Like Bulletproof Tiger said, you’d need at least 20-30 people doing a double blind placebo test to have any statistical meaning to your results.[/quote]

‘Of limited use’ perhaps, but far from “worthless”.

He experimented and noticed a result. Kudos to him for actually getting off his arse and doing something positive.

BBB

Very interesting thnks for sharing.

[quote]Josh Rider wrote:
Your test/experiment is worthless. Like Bulletproof Tiger said, you’d need at least 20-30 people doing a double blind placebo test to have any statistical meaning to your results.[/quote]
Are you kidding? He said he did this for fun, it’s not like he’s about to publish this in a scientific journal. Kudos to him indeed.

[quote]Josh Rider wrote:
Your test/experiment is worthless. Like Bulletproof Tiger said, you’d need at least 20-30 people doing a double blind placebo test to have any statistical meaning to your results.[/quote]

Whoah now. This is not what I said. Limited use (a.k.a. interesting), as BBB2 said is what I was suggesting… I suggested (if he had time and resources) he re-perform it with a couple buddies. How on earth would he get 20-30 ppl?

have Biotest fund it and give you money and unlimited Alpha-GPC.

[quote]Josh Rider wrote:
Your test/experiment is worthless. Like Bulletproof Tiger said, you’d need at least 20-30 people doing a double blind placebo test to have any statistical meaning to your results.[/quote]

That is not true. There are lots of statistically rigorous studies (neuroscience, mathematical behavioral sciences) with very few subjects.

n=1 studies are what you want to determine an effect something has on an individual. For this one, he just needs to repeat it multiple times, with placebo controls mixed in.

And statistical tests are not necessary. It’s clear that the variability between trials is tiny compared to the effect. Distributions don’t overlap at all.