Berberine Before And After

... Taken directly with breakfast. After Day 7 this cap remains... (take min. 3 h after GHK-Cu). MIDDAY (2:00... minimum of 3 hours after the morning GHK-Cu injection.... / electrolyte / food recruitment before altering any medication parameters. 2... Amino Stack, Epitalon, ATRA, Berberine, 5-Loxin AKBA (all caps), EGCG...and anti-inflammatory synergy alongside Bergamot / Berberine. C21 / Buloxibutid: oral AT2R...

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... DHA 500EPA fish oil berberine 400mg acarbose 50mg (before meal) gotu kola... rapa days and the day after) Ergothioneine 30mg (once a week... predisposition? Anything I should add? Before I was hoping to live...

... liquid supplement with raw honey, berberine, bee pollen, and royal jelly... daily (morning + night). Here's the before/after pic and the exact bottle ...

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... chronic inflammaging—likely manifest only after drug cessation, similar to verified... pressure of 125/85 mmHg) before chronic pathology manifests. Ezetimibe Priority... an over-the-counter supplement (e.g., berberine). The Rapamycin Blunting Effect: Stanfield’s... the five fundamental longevity pillars before adding molecular interventions: Sleep optimization...

Bodybuilding is associated with considerable health deterioration marked by infertility, decreased lifespan, and at times failure of vital organs like the liver and heart. On one hand, everyone can appreciate how effective anabolics are at improving physique and athletic ability, but on the other there is a well established danger to this way of life. In this post, I will attempt to construct the most carefully planned list of drugs to satisfy the best of both worlds: anabolism on par with established protocols, and preservation of health. Legacy anabolics The most relevant steroids and SARMs from the time of me writing this post are the following: Testosterone (4,412 human trials, ~2,885 as monotherapy, 4 used 600mg/ week or above) Oxandrolone (106 human trials, 62 as monotherapy) Nandrolone (73 human trials, 51 as monotherapy) LGD-4033 (4 human trials, all monotherapy) RAD-140 (1 human trial, monotherapy) Methenolone (1 human trial, 0 monotherapy) Trenbolone (0 human trials) Visualizing weight gain: For calculating the lean mass gains which each compound, we will have to extrapolate some metrics. To first establish a baseline, the clinical trial wherein LGD-4033 or placebo was given to 76 healthy young men for 21 days will be used for comparison.\1]) After a lot of extrapolation, which will be elaborated on, we get a graph that looks like this: Standardized real and predicted weight gain with anabolics Calculating weight gain: To derive this data, we have done a few things. First of all, weight gain in clinical trials closest in comparison to the study on LGD-4033 (Ligandrol)\1]) were prorated for Oxandrolone (Anavar)\2]), Nandrolone Decanoate (Deca)\3]) and Testosterone Enanthate (Test E)\4]) with the following formula: Prorated 21-day Gain (kg) = Total Clinical Lean Mass Gain x (21 ÷ Trial Duration in Days) Then, additional estimations were made for when the subjects were not young and healthy. In the case of Oxandrolone, a 20% increase was seen when accounting for age-related anabolic disparities.\5]) With Nandrolone Decanoate, there was a huge increase when adjusting for responsiveness between young healthy men and those suffering from HIV. To do this, a 300mg dose of testosterone was evaluated in healthy,\4]) and HIV-suffering patients,\6]) creating a multiplier of 1.49. With this adjustment, we get an estimated 1.45kg per 21 days. That being said, these are just estimations, so it's best interpreted as a range; Oxandrolone under these circumstances could increase weight by 0.75-0.9kg, and Nandrolone could increase weight by 0.97-1.45kg. But it's not known if that is true. Moving on to our preclinical data, which was specific to Methenolone (Primobolan),\8]) RAD-140 (Testolone),\9]) and Trenbolone (Tren).\10]) This is where a ton of speculation happens, so the accuracy of these numbers isn't clear, however an attempt was made to loosely predict their anabolic effect in humans. The highest recorded weight gain, 1.85kg (again, with high dose testosterone, this time with weight training)\7]) was multiplied by the dose divided by the dose added to an estimated dose based on the drug achieving 50% occupation from assay data. The final value is then multiplied again by 0.85 as a penalty if the drug an injectable ester that takes time to build up in the system. When this was conducted with testosterone and LGD-4033, values of 1.18, and 1.23 were achieved, respectively, suggesting this formula could be accurate, as it was close to the actual results from clinical trials. Pharmacodynamic Emax saturation was calculated by using the highest recorded weight gain, 1.85kg (using high dose testosterone, and this time alongside weight training)\7]) and multiplied it by the dose divided by the dose added to an estimated dose based on the drug achieving 50% occupation from assay data. Please note that for the occupation-estimated dose, AI was used, so it may be inaccurate - feel free to check it. The final value is then multiplied again by 0.85 as a penalty if the drug an injectable ester that takes time to build up in the system. 21 day Pharmacodynamic Emax Saturation Model = 1.85 x (Dose + Dose ÷ Affinity-Predicted Dose) x Ester Value Summarizing weight gain findings: In short, 1mg LGD-4033 shows the highest weight gain in clinical trials when the time period is reduced to 21 days, followed by 600mg Testosterone Enanthate, 600mg Nandrolone Decanoate, and 20mg Oxandrolone. This would make LGD-4033 34-60% stronger in terms of muscle growth than Oxandrolone when adjusting for a difference in responsiveness in samples. When trying to compensate for the subjects having HIV-induced muscle wasting, Nandrolone ranks the highest at 1.45kg/ 21 days, followed by Trenbolone at 1.43kg/ 21 days (extrapolated from rodent data) and RAD-140 at 1.33kg/ 21 days (extrapolated from non-human primate data). Under these circumstances, Nandrolone would have 18% greater anabolic effects than LGD-4033. Limitations to lean mass calculations Comparative safety of legacy anabolics In general, targeting the androgen receptor has its consequences across the entire body. However, there are major differences in the relative safety of these compounds. Trenbolone in particular is not only lacking in clinical data entirely, but has evidence strongly linking it to neurotoxicity independent of AR activation.\11]) Nandrolone also displayed neurotoxic symptoms in the same study, albeit to a lesser extent and only through AR-mediated processes. BBB penetration of anabolics Despite likely being CNS-penetrating, LGD-4033 displays the lowest relative CNS MPO Score,\12]) making its profile at least somewhat selective to peripheral tissue. Despite androgen receptor activation itself being at least somewhat neurotoxic,\11]) circumstantial preclinical evidence exists like in the case for Alzheimer's for both RAD-140 and Testosterone.\13]) SARMs vs. Steroids vs. Dirty Steroids: SARMs (Selective Androgen Receptor Modulators) were designed primarily as a class of orally bioavailable, non-aromatizing AR agonists that show less preference towards prostate binding, with the main goal of preserving the anabolic function associated with steroids, while reducing the side effects. Steroids follow a similar concept, although they have decreased selectivity due to being structurally derived from cholesterol. Off-targets ranked by affinity Prostate growth can compress prostatic urethra, causing serious urinary problems. These can be transient, or with continued growth, permanently affected. In addition, prostate cancer may accelerate, which is a concern particularly in older populations who's growth has naturally decelerated due to age. Aromatization of testosterone into estrogen causes a negative feedback loop resulting in the combined inhibition to testosterone synthesis by both (discussed in detail later), as well as estrogenic side effects such as gynecomastia (gyno), the enlargement of glandular breast tissue in males, edema (swelling caused by water retention that can potentially become dangerous), secondary hypertension caused by increased blood volume, and emotional volatility. Nandrolone converts into a weaker estrogen, estradiol-3-methyl ether, and at a reduced rate compared to testosterone; from this list, only Nandrolone and Testosterone aromatize into estrogenic compounds. 5α-reductase metabolizes testosterone into dihydrotestosterone (DHT). In the case of testosterone, DHT acts as a natural aromatase inhibitor, in turn reducing estrogen. However, DHT is the primary androgen driving androgenic alopecia (male pattern baldness). Unlike testosterone, nandrolone's 5α-reduced form is much less active than its parent molecule. Progesterone receptor binding is a particularly dirty effect of both Nandrolone and Trenbolone, because of multiple factors. Firstly, it accelerates breast tissue growth from estrogen and IGF-1,\14]) and amplifies estrogenic signaling.\15]) Second, it triggers the localized release of dynorphin to shut down gonadotrophin-releasing hormone (GnRH), reducing LH and FSH.\16]) Summarizing off-targets in legacy anabolics (1/3): Testosterone possesses the strongest prostate binding, followed by trenbolone, Nandrolone and Methenolone. This can cause temporary or permanent urination obstruction, and accelerate prostate cancer in aging populations. LGD-4033 and RAD-140 performed best in this category. Out of the selected drugs, only Testosterone and Nandrolone aromatized into estrogenic compounds, with greater severity in the case of Testosterone. Following 5α-reductase, testosterone is metabolized into DHT - Nandrolone is also subject to this enzymatic change, however the resulting compound possesses only weak androgenic effects. Lastly, for both Trenbolone and Nandrolone, they acted as potent agonists to the progesterone receptor, which could enhance the development of gynecomastia from estrogen. SHBG suppression with legacy anabolics Above represents the SHBG suppression seen with Oxandrolone,\17]) RAD-140,\18])00240-8/abstract) LGD-4033,\1]) Trenbolone,\19]) Nandrolone,\20]) Testosterone\21]) and Methenolone\22]) when scaling for the same doses used to generate our 21-day lean mass graph. Under normal circumstances, slightly reduced SHBG levels are not a huge concern, as it increases free testosterone. However, SHBG regulates hepatic lipogenesis by reducing acetyl-coenzyme A carboxylase levels. Severely low SHBG is marked by increased LDL and total cholesterol, which may form arterial plaques, representing a significant cardiotoxicity concern outside of cardiac hypertrophy. Agonists at the androgen receptor can reduce SHBG, with estrogen generally exerting the opposite effect, which appears consistent with the results in the graph. Dose-scaled Cardiac Hypertrophy risk The above represents a calculated risk using genomic AR activation in cardiomyocytes, non-genomic calcium-handling disruption factor (CA2 / CaMKII pathways), and hemodynamic fluid retention afterload burden, scaled with dose. Despite having a much higher cardiotoxicity coefficient versus testosterone, the comparatively lower dose of Trenbolone at 10.3mg/ day reduces the risk percentage closer to that of Oxandrolone's in this model. Cardiac risk calculation explained here Summarizing off-targets in legacy anabolics (2/3): Oxandrolone showed the most significant suppression, around twice as strong when compared to Methenolone's predicted suppression. Interestingly, Nandrolone Decanoate's scaled SHBG suppression is significantly lower in clinical practice than the assay data Trenbolone's predictions are based off would suggest. Methenolone's SHBG suppression is based on purely predictive data and thus is the most likely to be inaccurate. Inverse to these findings, one study in mice with metabolic syndrome shows Trenbolone actually being far less cardiotoxic than testosterone and even circumstantially cardioprotective.\23]) Hepatotoxicity risk of legacy anabolics The above attempts to predict risk of hepatotoxicity and nephrotoxicity using the same dosages and routes of administration as in the lean mass graph. Predicted values for hepatotoxicity and nephrotoxicity were derived from a structural understanding of the molecules and their metabolism, and animal data wherever possible. Since these predicted risk values aren't based on real data, they should be taken with a grain of salt. Summarizing off-targets in legacy anabolics (3/3): When comparing Hepatotoxicity and Nephrotoxicity, Oxandrolone\24]) and RAD-140\18])00240-8/abstract) are by far the worst offenders as their predictive hepatoxicity is clinically confirmed. Nephrotoxicity data here is strictly predictive, and highest in Trenbolone, followed by RAD-140 and testosterone. Weighted Risk Assessment of Legacy Anabolics To establish a singular number representing the overall risk of each drug, the data should be weighted and then pooled based on the damage and unpleasantness of the side effect, as well as the strength of the data provided. Since an egregious amount of extrapolation was used here, at times estimation based on chemical structure itself, combining this data with weighted clinical data will likely provide the most accurate result. The side effect priority will first estimate the clinical danger relative to the other side effects, as well as the unpleasantness of the side effect. The unpleasantness value will be divided by 2, then added to the danger value, and then the sum divided by 2. While this step may seem arbitrarily calculated, it's the most convenient way to derive a singular risk value for the anabolics. Side Effect Clinical Danger Unpleasantness Concern Nephrotoxicity 9.5 3 11 Hepatotoxicity 8.5 5 11 Cardiac Hypertrophy 9 5.5 11.75 Estrogenic Edema & Hypertension 5 6 8 Neurotoxicity 7 4 9 SHBG-Suppression Lipid Derangement 6 2 7 Prostate Growth 4.5 7.5 8.25 Progesterone LH/FSH Inhibition 3 8 7 Estrogenic/Progestogenic Gyno 2 9.5 6.75 DHT-related Balding 0 8.5 4.25 Next, risk data for each compound was standardized to a 0-5 baseline scale and multiplied by the concern value. In the case of nephrotoxicity and hepatotoxicity, predicted toxicity was counted as half its value due to lack of evidence. Neurotoxicity was calculated based on brain penetration and direct literature. When tallying everything, this is the result when contrasted against the lean mass gains described earlier. Grand comparison Conclusion to Legacy Anabolics After creating a comprehensive weighting of the overall side effects, and contrasting it with anabolism from our 7 drug candidates, we see a clear trend in the data: the side effects of anabolic-androgenic steroids (AAS) scale with the potency of their anabolic effect, possibly with the exception of Nandrolone if we do not adjust for their disease. SARMs on the other hand did not represent this trend, and performed slightly weaker, or superior to the steroids, while having the lowest total risk, with LGD-4033 having the greatest lean mass-to-risk ratio. From these drugs, Trenbolone was the least studied, and Testosterone the most studied. Limitations to this conclusion Adjunct Therapy Part 1. Appetite Stimulants & Food The most relevant appetite stimulants from the time of me writing this post are the following: Mirtazapine (483 clinical trials, 324 as monotherapy) Ginger extract (162 clinical trials, 126 as monotherapy) THC (118 clinical trials, 54 as monotherapy) MK-677 (14 clinical trials, all monotherapy) ART27.13 (2 clinical trials, all monotherapy) Naturally, with weight training and anabolic drugs, nutritional requirements increase to satisfy an increased muscle protein synthesis rate.\35]) However, a subset of the population cannot naturally obtain this level of appetite, which can greatly contribute to anabolic responsiveness. ART27.13 is a peripherally-selective cannabinoid receptor agonist which I have covered previously,\25]) and like Mirtazapine,\26]) MK-677,\27]) THC,\28]) and Ginger,\29]) acts as an appetite stimulant. Appetite stimulants generally have a strong influence on weight gain, but without concomitant administration of other substances, this preferentially registers as fat mass. This is because anabolic substances typically both reduce fat mass and increase lean mass simultaneously, and eating alone should have a negative effect on body composition, especially in a western environment. Standardized 30 day weight gain and mass distributions against relative risk Calculations and interpretation: The above graph estimates weight gained from clinical trials on the compounds, and makes extrapolations to extend the results to a 30 day time-period, using Emax saturation and prorated adjustments as described earlier. In addition, similar calculations are performed as before to account for disease states skewing results. ART27.13 shows the highest effect when adjusted to match a healthy person, at 3.23kg in weight gain, but matches Mirtazapine's results when using raw clinical data. Ginger extract led to a minor 0.15kg in weight loss, rendering the rest of its results in this graph as null. Lean mass gains are estimated as 15% for Mirtazapine\29]) 20% for both ART27.13 and THC,\30]) and 85% for MK-677,\27]) with the percentages of that mass as water weight being 73% for ART27.13, Mirtazapine, THC and MK-677 based on standard body composition,\31]) and the actual clinical results of MK-677.\27]) Risk was was calculated on the basis of obesity, heart failure and cognitive impairment, with heart failure holding the most weight; ART27.13 due to not penetrating the CNS and thus having less side effects than THC resulted in the lowest risk score, whereas MK-677's was the highest due to evidence of cardiovascular events in previous clinical trials, followed by THC given it's cognition impairment and neurotoxicity.\25]) MK-677's positive effect on lean mass is due to stimulating the release of Ghrelin, which can increase bone density and to an extent muscle tissue through elevated human growth hormone, although it would appear this effect is limited and pure HGH is likely to elicit a stronger response.\32]) Of these drugs, only ART27.13 was intentionally designed to stimulate appetite. Mirtazapine having the lowest lean mass value is likely influenced by it biasing appetite towards unhealthy food,\34]) which is also a trait of CB1 receptor agonists, seemingly to a lesser extent.\25]) Increased calorie demand from anabolics: The six anabolics we discussed prior could increase caloric demand from 1.6% (40kcal, Methenolone's preclinical extrapolation) up to 4.14% (103.6kcal, Nandrolone's healthy extrapolation)\35]) needed for tissue deposition at the doses and days mentioned previously. There is also a needed increase in protein intake of around 5.83% (+9.33g/ day, Methenolone's model), up to 15.11% (+24.17g/ day, Nandrolone's healthy model), based on muscle composition and the efficiency of protein incorporation.\36]) This protein would represent another 1.49-3.87% increase in caloric demand, resulting in a net demand increase of at least 3.09-8.01% more calories. Mirtazapine exceeds this value by increasing caloric consumption by around 26%.\33]) It is already known that supplementation of whey protein increases muscle synthesis, so with that in mind we can calculate a 25% increase in lean mass gains from anabolics if adding an additional 48 grams of protein and 500 calories.\4])\37])\38]) Appetite stimulants combined with anabolics: While both Mirtazapine and ART27.13 at the 650ug dose increased mass by around ~2.5kg in their respective studies, ART27.13 at 130ug increased it by only ~1.5kg and is predicted to have 5% less carbohydrate bias than Mirtazapine in meal selection. Since this weight gain was found in cachexia patients, it's possible that the fat mass gain is worse, however there is insufficient data on appetite stimulants to extrapolate from in comparison to anabolics, so the extrapolation was not done for the sake of accuracy. 130ug ART27.13 with legacy anabolics Calculating the synergy: Factoring in the nutrient demands of muscle growth as previously described, as well as individual fat-suppressing properties of the anabolics (such as with Testosterone,\4]) Oxandrolone,\39]) Trenbolone\40])), or lack thereof like with LGD-4033\1]) and Nandrolone,\41]) and then adding in the lean mass caused by eating alone, we get the above graph demonstrating the relative fat-suppressing and combined anabolic effect of each compound. Trenbolone's preclinical data demonstrated the best fat suppression per lean mass gained, whereas Oxandrolone suppressed fat mass the most. The greatest net weight was achieved using a combination of Nandrolone (extrapolated to represent a healthy population) and ART27.13, at 3.79kg total mass with 2.23kg being lean mass (a 54% increase in lean mass). The fat elephant in the room: While fat mass is generally neglected during "bulking" to achieve maximum lean mass gains, it is generally undesirable and can be perceived as a drawback to this synergy. A lot of this data was extrapolated from western populations and poor diet, and eating better could vastly lower the accumulated fat mass shown in the graph. While not included in this writeup, drugs that lower fat mass while preserving lean mass may also be useful. Limitations to appetite stimulant calculations Countering the contraceptive effects of anabolics The most relevant LHr-promoting drugs from the time of me writing this post are the following: HCG (~1,246 clinical trials, ~398 as monotherapy) Enclomiphene (14 clinical trials, all monotherapy) Kisspeptin-10 (6 clinical trials, all monotherapy) ORG-43902 (1 clinical trial, monotherapy) Hijacking steroidogenesis: In our analysis, LGD-4033 is by far the safest anabolic agent despite still yielding a considerable increase to lean mass. However, the vast majority of anabolics severely impair the biosynthesis of androgens, to the extent that they act like contraceptives, and this too is true for LGD-4033.\4]) This side effect is mediated by the testis, as androgen receptor agonists limit the amount of intratesticular testosterone (ITT) and LH, and prolonged AR agonism can cause testicular atrophy if it's not reversed.\42]) LH being shut down also impairs neurosteroids, which likely caused the cognitive impairment seen with high dose testosterone administration (although the GABAergic effect of testosterone is also plausible). Luckily HCG can reverse this effect, however there are considerable drawbacks in that it upregulates aromatase and can therefore increase the ratio of estrogen to testosterone, causing the aforementioned estrogenic side effects. This led us to looking into ORG-43902 which not only lacked this effect, but was expected to upregulate LH receptors over time. Unfortunately, ORG-43902 turned out to be ineffective as monotherapy when used alongside anabolics in our group (data not shown), as only one person achieved supraphysiological testosterone levels on it, and they were not using an AR agonist, leading us to believe it is a true PAM and its effect is dependent on LH levels. This would mean that a LH promoter like. Kisspeptin-10 would need to be administered twice a week alongside it for it to work properly. Since HCG and Kisspeptin can bypass the LH inhibition by anabolics, they have an edge over Enclomiphene in this regard. However, Enclomiphene can be used to further disinhibit the estrogen-mediated impairment to steroidogenesis caused by either adjunct. While Enclomiphene's effect is lasting, any LH-mediated process will inherently develop tolerance unlike ORG-43902.\42]) On the topic of other steroids produced through steroidogenesis, it's likely they contribute somewhat to anabolism as well, meaning disinhibiting this should make anabolics work more effectively, although to what extent would require its own separate analysis. Enclomiphene's inhibition to IGF-1\43]) does not interfere with androgen receptor-mediated anabolism thus ending a long-standing debate on its implications.\44]) Countering the lipid changes caused by anabolics The most relevant cholesterol modifying drugs from the time of me writing this post are the following: Atorvastatin (~1,842 clinical trials, 718 as monotherapy) Rosuvastatin (~1,154 clinical trials, 392 as monotherapy) Ezetimibe (712 clinical trials, 114 as monotherapy) Pitavastatin (234 clinical trials, 96 as monotherapy) Evolocumab (186 clinical trials, 14 as monotherapy) Berberine (98 clinical trials, 76 as monotherapy) Inclisiran (52 clinical trials, 2 as monotherapy) Lycopene (48 clinical trials, 42 as monotherapy) Red Yeast Extract (22 clinical trials, 19 as monotherapy) Pantethine (14 clinical trials, 12 as monotherapy) Citrus Bergamot (11 clinical trials, 9 as monotherapy) LDL-C changes scaled against relative risk Calculations and interpretation: The above graph was constructed by comparing the side effect profile of various cholesterol modifying drugs, and then scaling them up to match the previously established risk metrics we produced with anabolics. Actual clinical data was available for Oxandrolone,\45]) LGD-4033,\1]) Nandrolone,\46]) and Testosterone.\4]) When clinical data wasn't available, it was predicted based on those four drugs with the following formula: LDL-C Impact = 0.3784 x (SHBG Suppression Percentage) - 14.2297% The resulting numbers are an 18% increase with Oxandrolone, 13.01% increase with RAD-140, 12.2% increase with Nandrolone, 7.71% increase with Trenbolone, 6.6% increase with LGD-4033, 1.66% increase with Methenolone, and a 0% increase with high dose Testosterone. It should be noted that this low value for testosterone was not expected until this portion of the writeup, and likely means that Testosterone's risk value was over-predicted to an unknown extent if using LDL-C increases as the determining factor for SHBG's risk. That being said, the consequences to SHBG suppression are beyond that of just LDL-C, as it causes increased hormone fluctuation and reduces HDL-C, so the value would probably only reduce moderately. In this analysis, the following cholesterol-modifying drugs were used: Evolocumab (140mg Subcutaneous),\47]) Inclisiran (284mg Subcutaneous),\48]) Rosuvastatin (5mg Oral),\49])00530-7) Pitavastatin (2mg Oral),\50]) Atorvastatin (10mg Oral),\51]) Citrus Bergamot (1000mg Oral),\52]) Berberine (1000mg Oral),[53] Ezetimibe (10mg Oral),\54)] Red Yeast Extract (2400mg Oral),\55]) Pantethine (600mg Oral),\56]) and Lycopene (100mg Oral).\57]) The risk was calculated from the clinical data with the following formula: Cholesterol-modifying drug risk = (Myotoxicity + Hepatic burden + systemic load) ÷ 3 The results can be found here. Conclusion: Oxandrolone had the most negative effect on LDL-C, whereas high dose testosterone had the least effect. Evolocumab had the strongest reduction to LDL-C and also showed the most favorable safety profile. Citrus Bergamot reduced LDL-C almost to the same extent as statins, despite having a drastically improved safety profile, and is a supplement that is widely available. Lycopene had the least effect, and Atorvastatin was the most risky of the substances analyzed. Limitations to cholesterol-drug comparisons HGH, Myostatin Inhibitors, and IGF-1 mimetics: The most relevant in this category from the time of me writing this post are the following: HGH, GHr agonist (492 clinical trials, 431 as monotherapy) rIGF-1, IGF-1 mimetic (34 clinical trials, 27 as monotherapy) BVS857, IGF-1 mimetic (3 clinical trials, all monotherapy) ACE-031, myostatin inhibitor (3 clinical trials, 2 as monotherapy) https://preview.redd.it/abb4spttjw3h1.png?width=1600&format=png&auto=webp&s=d0adbc922e442973e3e2f80ab65fa04e27576e1b Calculations and interpretation: AI was used to predict the long-term risk using the occurrence and severity, clinical danger and unpleasantness of side effects, giving side effects with higher severity a greater score. Data was limited to clinical trials. Testosterone was added as a control value, but risk assessment was performed the same way. The following equation was used to calculate risk: Long-term risk score = (Σi(Incidence x Severity)) x 10 Severity was based on the following categories: Category 5 (Catastrophic / Structural Failure / Trial-Halting): Permanent autoimmune destruction, or structural breakdown of vascular systems. Category 4 (Major Morbidity / Irreversible Organ Damage): Conditions requiring lifelong medical management, organ hypertrophy, or permanent nerve destruction. Category 2 (Manageable Systemic Risk / Reversible Strain): Reversible suppression of natural hormone axes, or manageable shifts in lipid/blood viscosity profiles. Category 1 (Mild / Cosmetic Shift): Cosmetic skin changes or localized inflammation. The exact weight gain statistics were then determined (standardized to a 21-day window) for HGH\58]) with +1.57kg (1.42kg as water weight), ACE-031\59]) with +1.482kg (0.37kg as water weight, rhIGF-1\60]) with +0.9kg (0.495 as water weight), BVS857 with +0.5kg (0.275kg as water weight), and high dose testosterone\4]) with +1.18kg (0.354kg as water weight). In the case of BVS857 and rhIGF-1, these trials were conducted in people with diseases and extrapolated to healthy people to give the above numbers, with the actual weight gain being 0.375kg for rhIGF-1 and 0.2kg for BVS857. The problem with HGH, and IGF-1 as anabolics: While there is clearly lean mass gained by these compounds, it is relatively minimal when scaling for water weight and risk. Further, IGF-1 nor HGH influences androgen receptor-mediated anabolism in vivo,\44]) meaning it is not expected that mixing these with an AR agonist would amplify the effects of AR agonists. This is on top of the fact that they are far less selective to muscular tissue than AR agonists, and lean mass gains purely as muscle tissue would make this an even smaller value. In addition to this, HGH, IGF-1 and mTOR are all extremely relevant to lifespan, with HGH restriction resulting in a ~+40-70% extension to lifespan, and IGF-1 ~+5%.\61]) Conclusion: ACE-031 yielded the most lean mass out of any anabolic in this writeup, and simultaneously carried an extreme risk. Unlike HGH, it is expected that the myostatin inhibition of ACE-031 would amplify the anabolic effect of AR agonists. Two drugs in this category were pulled from clinical trials due to severe adverse effects, that being ACE-031 and BVS857. rhIGF-1, HGH and BVS857 all had exceptionally poor muscle-to-risk ratios, whereas high dose testosterone had the best. Limitations to other anabolics calculations Other anabolics and known stressors While we extensively covered 7 anabolic drugs, there are many others in the category. Those include but are not limited to MENT (Trestolone), Ostarine, LGD-3033, S23, YK-11, S4 (Andarine), AC-262, Masteron (Drostanolone), Anadrol (oxymetholone), Methyltren (R1881/Methyltrienolone), Superdrol (Methasterone), DHB (Dihydroboldenone), EQ (Boldenone), Dianabol (methandrostenolone) and Winstrol (Stanozol). When asking AI to compare the structures and binding activities of these drugs to our 6 AAS and SARM-poised anabolics, we get the following chart (not supervised for accuracy): Hierarchical clustering of anabolics compared by similarity to structure and binding profiles Antioxidants: AR-dependent anabolics exacerbate oxidative stress,\62]) which in turn could cause widespread aging and reduced lifespan independent of the aforementioned risks. Many antioxidants promote cancer growth, but this is not the case for at least Astaxanthin and Carnosic Acid, with Carnosic Acid killing cancer cells is nearly every type of cell culture. It is thus recommended that someone on an anabolic cycle uses antioxidants if hoping to maintain their health. Expounding on why I favor these two antioxidants would require a separate post, and is based on literature not provided in this one. Grand conclusion and hypothetical stacks From this analysis, we see a clear division between the relative safety of anabolic substances, as well as approaches that may be used to minimize known side effects. Stigmas and assumptions from the bodybuilding community over the years have proven themselves here to varying degrees, whereas other assumptions turned out to be false. I would add more but it would break the post character limit. Stack 1: Optimizing muscle growth with minimal side effects Anabolic: 1mg/ day LGD-4033 Lipid-protection: 1g/ day Citrus Bergamot Appetite stimulant (optional): 100-200mcg/ day ART27.13 Anti-contraceptive: Either 400iu HCG injected 3x/ week or 50mg/ day ORG-43902 with Kisspeptin-10, with or without 6.25mg/ day Enclomiphene Antioxidant: 12mg Astaxanthin, or 400mg Carnosic Acid Stack 2: Maximizing body composition with maximal side effects Anabolic 1: 10.3/day Trenbolone Anabolic 2: 3mg/kg ACE-031 Anti-contraceptive: 1500iu HCG injected 3x/ week Stack 3: Maximizing muscle growth purely based on the amount of clinical trials Anabolic 1: 600mg/week Testosterone Anabolic 2: 0.4mg/kg/day HGH Lipid-protection: 10mg/ day Atorvastatin Appetite stimulant (optional): 15mg Mirtazapine Anti-contraceptive: 1500iu HCG injected 3x/ week Antioxidant: 12mg Astaxanthin References submitted by /u/sirsadalot to r/NooTopics [link] [comments]

Quick backstory. I'm a refractory SIBO case. 26M, tortuous colon, high E. coli and Proteobacteria on stool testing, plus POIS (post-orgasmic illness syndrome, weird neuro-immune reaction after sex) and these "wired but tired" neuro crashes nobody can explain. Years of rifaximin, allicin, berberine, neem, every protocol you've heard of. Always came back. Nighttime was the worst. Couldn't sleep through the night for years because of the gas pressure and pain. Got desperate enough to do something kind of insane. I scraped about 7 million comments and 670k posts from this sub plus 15 related ones (r/MCAS, r/dysautonomia, r/covidlonghaulers, r/Microbiome, r/ibs, r/FODMAPS, r/HistamineIntolerance, r/LongCovid and others) into a searchable database. Then built an AI layer on top so I could run actual queries against it. Things like "show me everyone who tried X long term and what their outcome was," "what did the responders to Y have in common," "what does the failure mode of Z look like." Turned thousands of people's lived experience into something I could analyze instead of doomscrolling one anecdote at a time. The pattern that fell out of it was so consistent it pissed me off that no GI, naturopath, or functional medicine doctor I've seen in years ever framed it this way. The bacteria aren't actually the problem. The motility is. The MMC (migrating motor complex) is your small intestine's cleaning wave that fires every 90-120 minutes when you're fasted and sweeps bacteria out the door. When it's broken, anything you kill grows back. You're mopping the floor with the faucet still on. The people in the data who got durable results weren't the ones with the most aggressive antimicrobial protocols. They were the ones who fixed motility first, then killed, then maintained. Been seeing 4-5 posts this week from people on their 2nd, 3rd, 4th round of rifaximin watching it relapse again. That's exactly what the data predicts if you don't fix motility. So I flipped the order. Went hard on motility first: Motility Activator by Integrative Therapeutics, 3 caps at bedtime. It's a concentrated ginger + artichoke extract. There's a 2015 clinical trial that tested this exact combination for motility in IBS patients and it actually worked, which is more than you can say for most supplements. About $25 for a bottle on Amazon. LDN (low-dose naltrexone) 3mg at night. I was already on it for the neuro/autoimmune side but it's also a legit prokinetic. Prescription, but cheap and very low side effect profile. Actually fasting between meals. 4+ hours minimum, no snacking, nothing within 3 hours of bed. This is the part everyone skips and then wonders why nothing works. Results so far: Day 1. Huge reduction in nighttime gas pressure. Slept through. Day 2. Ate pizza at a friend's thing, fully expected to pay for it, didn't. Day 3. Zero gas, zero pain, woke up actually rested for the first time I can remember. Day 4. Bit of gas pain when I rolled onto my back but still way reduced from baseline. These are the first pain-free nights I've had in literal years. I know it's only 4 days. I know it could fall apart. But the trajectory matches exactly what the long-term responders in my dataset described in their early weeks, so I'm cautiously optimistic. If you're in the rifaximin loop, before you do another round, seriously ask yourself: Are you actually fasting between meals? Constant snacking destroys the MMC. No prokinetic in the world will work if you're eating every 2 hours. Are you on a prokinetic? If not, you're going to relapse. Period. If gentle stuff like ginger/artichoke doesn't move the needle, prucalopride (Motegrity) is the prescription option that long-term users on this sub describe as a game changer. It's a serotonin receptor drug that directly stimulates the cleaning waves. On the database. If there's interest I'll clean it up and make it publicly available so anyone can query it the way I have been. Drop a comment and let me know. Will report back at Day 14. Fingers crossed it holds. submitted by /u/Toczix to r/SIBO [link] [comments]

Some of you have been following my posts and knew that I was about to start IG treatment. Well, after a lengthy battle with insurance, I finally got my first treatment (IVIG 70G) on April 22. I wanted to wait to see how I reacted over a longer time frame than just a few days or a week or two even. Well, it's been a little more than three weeks and the Garmin data... it doesn't lie. Not only am I feeling better and able to do more, the Garmin data shows a shocking contrast pre/post. As you can see, I'm able to tolerate a lot more activity (7K steps avg per day to 12K a near 50% increase) with significantly reduced stress compared to before treatment. (Body Battery scores much higher highs higher lows, vs lower highs and lower lows pre-treatment.) The first few days of the "loading dose" of IVIG were very hard on me. But after that, things began to improve significantly. A week later I transitioned to weekly SCIG (15G) due to the PE I had in October. I've had 4 total treatments so far including the loading IV dose. The dramatic increase in my exertional tolerance is undeniable. The only other time I experienced a thing close to this was last year when I was on Rapamycin (along with a few other meds and supplements) but that wore off nicotine long after ending the Rapamycin which says to me an overactive immune system is clearly to blame. Meds I'm currently on: LDN 4.5 mg January- Ozempic Dec-Feb .25-.5 Mounjaro .5 March- Fenofibrate 67 mg micronized March- Fisetin (pulse protocol 2 days 1500 per day) Early April, mid April and end of April ~2 weeks apart. Last SGB near end of March. Bisoprolol, Ivabradine (years) and Eliquis since October PE. Lidocaine 5% patch daily since mid March Banana bag IV 2 x weekly (1L saline plus multi since last June) Supplements (note none of these were the cure... but I think some are helpful in Spring recovery once the primary issue is addressed. https://www.reddit.com/r/covidlonghaulers/comments/1ozgdtx/supplement_stack_comparison_who_is_choking_down/ I dropped a couple of those (Dihydro-Berberine, GABA, Tryptophan) and added some more aminos like Proline, LOLA, and Sarcosine. I do think this will ultimately result in sustained improvement as, unlike the Rapamycin trial that lasted only 12 weeks, I'll be on this for at least 6 months but most likely a year or more and that shoild allow my immune system to reset fully. One interesting finding that I am covered a few weeks ago was that I have a genetic homozygous deletion of CFHR1/3 which is not uncommon in Mediterranean and Northern African populations (5-10%) and may possibly be contributing to the problem. As I understand it, it removes the "break" on the alternative pathway of the complement system which has also been implicated in LC. https://insight.jci.org/articles/view/194314 My primary theory on this: https://www.reddit.com/r/covidlonghaulers/comments/1q96kw8/eureka_virusinduced_endothelial_senescence_as_a/ https://www.reddit.com/r/covidlonghaulers/comments/1smknm0/new_research_preprint_from_dr_iwasaki_puts_long/ Edit: for context I am three and a half years in so to have such a dramatic turnaround in such a short amount of time shows how for some of us this could be very quickly reversible, in my opinion. Long haulers should be asking their docs for this test as a positive hit on any one of these ten on the panel likely, get you access to IG to at least try. https://www.labcorp.com/tests/505413/autoimmune-dysautonomia-profile 2nd edit I forgot to include my twice weekly banana bags. submitted by /u/SpaceXCoyote to r/covidlonghaulers [link] [comments]

The attached photos are 3 days apart. I never thought I'd post these anywhere, but here I am. I live by the beach, love biking and exercising, and want to feel good in my skin. This bloating is destroying everything to the point where I can't exercise, I get anxious about going to the beach with people, constantly wondering how my stomach will decide to look that day. I finished Rifaximin 6 days ago. I wasn't formally tested for SIBO (no breath test available locally), but my doctor agreed to prescribe it based on my symptoms. I took 800mg per day for 10 days, which I understand is on the lower end of what's typically used for SIBO. During and right after treatment, I felt about 60% better. The day after I finished was probably my best day in months (almost zero symptoms). But over the past 2-3 days, pretty much all symptoms have returned. Is this normal? Symptoms returning this fast? Do I need another round, probably at a higher dose? Has anyone had a similar experience? How did you move forward? What I've tried so far: Rifaximin 800mg/day for 10 days Ginger extract 1000mg before bed daily Digestive enzymes, probiotics, berberine, peppermint oil, oregano oil Breathing techniques A 36-hour fast submitted by /u/Strange-Comedian-409 to r/SIBO [link] [comments]

I took berberine for about 1-2 months, and I strongly believe it helped me a lot with my PCOS. After taking it, I noticed a drastic difference in my sugar cravings and overall hunger. I was no longer 'always hungry' and felt satisfied after having a meal. I didn't take it consistently/proper dosage, mostly took 500mg whenever I could, at least once a day before a meal. Common side effects were bloating and slight diarrhea, but it stops after the first few weeks. I also started becoming consistent with the gym, 4x/week, which I think is the main reason for my weight loss, but berberine definitely gave me that little push which I needed. I also started getting my period, which may be due to weight loss/increased activity. However, I did stop once I was more confident in going to the gym and had a steady routine and still noticed a difference. I also wouldn't recommend staying on it for long term, and definitely doing blood work if you feel something is wrong. It is no magic pill; you still have to put in all the hard work. Also I know everyone says this already, but walking really is the game-changer when it comes to PCOS. I remember being hesitant before starting it and looking at tons of reddit posts, so hopefully this can help someone out submitted by

To avoid confusion: on a photo is about 30 days of supplements. Are you guys still taking supplements after starting peptides? I just finished about a month on KLOW (prescription from a compounding pharmacy), and the changes were not what I expected ( but much better). Skin looks better, shoulder pain is gone, and my training capacity went up a lot. I can run, swim, and lift longer and at higher intensity. Rough estimate is around 2 to 2.5x more total training volume compared to before. Because of that, I’m starting to question whether my supplement stack still makes sense. Before this, I was pretty consistent with a standard stack like GlyNAC, vitamin D, berberine, magnesium, TMG, creatine, astaxanthin. Not extreme, but definitely not minimal either. Now it feels like peptides are doing most of the heavy lifting, especially for recovery and performance, so I’m trying to understand if the supplements are still adding anything meaningful or just marginal on top. Also trying to sanity check this angle: does this kind of peptide-driven improvement resemble what people describe on TRT, where things feel better and performance goes up, but underlying issues may still be there and you’re just pushing the system harder? Curious how others think about this, especially if you’ve reduced your stack or tracked changes before vs after submitted by /u/Pure_Respond_9765 to r/Biohackers [link] [comments]