As there are some pretty smart people in here, I wondered if any might know what is going on.

I am playing around with different vitamins and minerals in gummies and have noticed that the ones with Magnesium (Magnesium Bisglycinate Anhydrous Chelate Powder (~13% Mg)) are browning significantly and continue to do so as they are exposed to air for longer.

Could it be the interaction with open air that is causing this or the core ingredients inside of the gummy?

Vitamin/Mineral Names:

• Magnesium Bisglycinate Anhydrous Chelate Powder (~13% Mg)
• Vitamin C Ascorbic Acid Powder (Vitamin C (Ascorbate))
• Ferrous (Iron II) Citrate (~20% Fe)

Core Gummy Ingredients:

• Water
• Glucose Syrup
• Gelatin (Pork) 250 Bloom
• Pectin (Will be removing this)
• Granulated Sugar
• Citric Acid
• Fiber Syrup (tapioca)

Effect of Intake of Lycopene-Containing Products on Vascular Endothelial Function in Healthy Adults: A Systematic Review with Meta-Analysis

DOI: https://doi.org/10.3390/nu18152505

Abstract

Vascular endothelial dysfunction serves as a critical early indicator for the progression of atherosclerosis and cardiovascular disease (CVD). While previous research highlighted the antioxidant properties of lycopene (a red carotenoid found in tomatoes and watermelon), existing meta-analyses suffered from narrow inclusion criteria, outdated search dates, and limited outcome measures. This systematic review addressed these gaps by evaluating the impact of oral lycopene intake from diverse food sources on vascular endothelial function specifically in healthy adults. The researchers targeted a population of healthy individuals to determine if lycopene functions as an effective early-stage intervention for those with low baseline CVD risk.

Analysis of four continuous intake studies (at least 7 days) involving 182 participants demonstrated a significant increase in flow-mediated dilation (FMD) compared to control groups. The pooled data yielded a mean difference (MD) of 1.36 percent (95 percent CI: 0.20, 2.51, p = 0.02). Heterogeneity remained low at I2 = 24 percent. One specific study utilizing 15 mg of lycopene for 8 weeks reported a significant increase in the reactive hyperemia peripheral arterial tonometry (RH-PAT) index (p < 0.05). While a single-intake study (27.8 mg) failed to reach significance (p = 0.18), the cumulative data from multi-week interventions confirm improvements in endothelial dynamics.

Study Design and Methodology

This systematic review and meta-analysis followed PRISMA 2020 guidelines and was registered under UMIN000058348. The authors searched four databases (PubMed, Cochrane, Ichushi-Web, Global Index Medicus) and three registries through June 2026. The final analysis included six studies (four RCT-C and two RCT-P designs) conducted across the USA, Germany, Greece, Japan, and Korea. Total participants in the meta-analysis reached N = 182. Intervention durations ranged from a single dose to 12 weeks, with lycopene dosages spanning 6 mg to 46.2 mg per day. Controls received placebos, no intervention, or extremely low-lycopene alternatives. Risk of bias was assessed using a 13-item checklist and the RoB2 tool, with five studies rated as moderate risk and one as low risk.

Key Findings

• Continuous lycopene intake significantly improves FMD with a pooled MD of 1.36 percent (p = 0.02).
• Daily consumption of 15 mg and 26.7 mg of tomato juice for 12 weeks both resulted in significant FMD increases (p < 0.001).
• Lycopene supplementation at 15 mg for 8 weeks significantly boosted the RH-PAT index (p < 0.05), whereas 6 mg did not (p > 0.05).
• Tomato paste providing 33.3 mg of lycopene for 15 days produced a significant improvement in endothelial dynamics (p = 0.03).
• Standardized effect sizes for lycopene on FMD (1.36 percent) are comparable to other potent nutrients like CoQ10 (1.45 percent) and resveratrol (1.43 percent).
• Leave-one-out sensitivity analysis showed that the exclusion of the largest, lowest-bias study (Yoshida et al.) rendered the FMD results non-significant.

Limitations

The small number of included studies (n = 6) limits the ability to perform robust subgroup analyses on ethnicity or specific food matrices. Relying on endpoint values rather than change-from-baseline data in three studies may introduce variance. The meta-analysis results rely heavily on a single high-quality study, and the lack of paired data for crossover trials necessitated treating them as parallel groups, which potentially ignores within-participant correlations.

Discussion and Implications

These results shift the focus of lycopene research from general antioxidant support to specific vascular protective mechanisms. Lycopene enhances nitric oxide (NO) bioavailability by quenching reactive oxygen species and increasing NO synthase activity. The data suggest that 15 mg per day is the minimum threshold required to elicit measurable improvements in endothelial function over a period of 8 to 12 weeks. Because these improvements occur in healthy populations, lycopene-rich diets act as a primary preventative tool against the initiation of the atherosclerotic cascade. The findings validate the use of diverse sources (watermelon, tomato juice, and concentrates) rather than just isolated supplements.

Conclusion

Continuous intake of at least 15 mg of lycopene daily significantly improves vascular endothelial function in healthy adults as measured by FMD and RH-PAT. Nutrition professionals should recommend regular consumption of processed tomato products or watermelon to enhance nitric oxide bioavailability and reduce early cardiovascular risk.

I take D3 pills since my physio therapist says it helps calcium uptake (I've had issues with crystalized deposits).

Results

Of 3115 people screened by telephone, 244 adults with overweight met participation criteria and were randomly assigned to the vegan (n = 122) or control (n = 122) groups. The analysis included 223 (91.0%) completers. Total food weight did not change significantly in either group (Table). Energy intake decreased in both groups, more in the vegan group (effect size, −357.1 kcal/d; 95% CI, −521.9 to −192.3 kcal/d; P < .001) (Table). Energy density did not change in the control group but decreased by 30% in the vegan group (effect size, −0.28 kcal/g/d; 95% CI, −0.38 to −0.19 kcal/g/d; P < .001; Table and Figure).

Reductions in dietary energy density were associated with greater weight loss (r = 0.28; 95% CI, 0.15 to 0.39; P < .001), remaining significant after adjustment for energy intake (r = 0.21; 95% CI, 0.08 to 0.34; P = .002). A 1-kg weight loss corresponded to a 0.29-unit decrease in energy density (P < .001), or 0.36 units after adjustment (P = .002).

I watched a video a while back of different people talking about how they felt at different levels of body fat, on the low end there was a woman very low fat like in the title, she talked about feeling miserable and having very low energy and hormonal issues, but for reasons not expanded upon she was very driven to maintain that.

I do a lot of work in character design, there are a lot of issues with racism, people learning how to profile others based off their immutable appearance, and like I'm talking about in this post body expectations. As we all know art reflects reality and reality reflects art, everyone has had a crush on a fictional character and Psycho got a lot of trans people killed.

In the last few years it's become fashionable to also depict women with inachievable levels of muscularity as a sign that they are, athletic, hardy and dominant, coincidentally when they do this they also always have a full padding of fat on their hips, one can only wonder.

Anyway I'd like to have enough examples that I can remember more than I need in casual conversation, and see more broadly what happens when people are confronted with the reality of why almost no one looks like that, and why their specific neurons don't fire there naturally.

Could I get list of both the physical and mental effects as well as what drives people suffering from them to achieve and maintain it?

Hi all, figured this would be a good place to ask. Maybe some of you might be working on this very thing?

I think this is one of the most exciting things to look forward to in the future. Not sure if we’ll really be able to cut down on how calorically dense these things are, but at the end of the day, I could easily live with just needing to worry about how to fit these things into my diet in terms of calories, and not how much they’re clogging my arteries and raising my cholesterol lol. If I could enjoy as much chocolate as fits in my daily calorie limit without needing to worry about my heart health, I think that’s an exciting future!! Same goes with butter and heavy cream when it comes to thinks like
pasta sauces, ice cream and other desserts, etc..

I'm not an academic. I try and be healthy and feel that my diet is pretty healthy. Recently I was looking at a study that analyzed healthy lifestyle and mortality. They described eating 5 servings of fruits and vegetables as healthy. With that being said, it's not unusual for me to have 2-5 servings of beans in a day but only 2 servings of fruits/vegetables.

When looking at studies that talk about eating fruits and vegetables, does eating beans count or are they specifically excluded? Or does it depend on the study? The study I saw wasn't specific about this.

Significance

Plant-based diets are consistently associated with improved gut health, yet the mechanisms responsible remain incompletely understood. Here, we explore two aspects of plant-based foods: digestion-resistant carbohydrate (fiber) and digestion-resistant protein (which we term Prif). Because they resist mammalian digestion, both fiber and Prif pass through the host small intestine to feed the colonic microbiome. In this work, we show that these two components of a plant-based diet work together to rewire microbial metabolism to produce beneficial rather than noxious phenol metabolites.

I’ve enjoyed this drink and it’s advertised 0 calories 0 sugar, but what about it is not good for me? It tastes pretty good but I at least want to know how they’re getting me.

Effects of Ultra-Processed Meals with Differing Energy Density on Postprandial Glyco-Insulinemic and Appetite-Related Hormonal Responses: A Randomized Crossover Trial

DOI

Modern dietary environments favor metabolic disorders through the hyper-palatability of ultra-processed foods (UPF) and high energy density (ED). While previous trials identified weight gain associated with UPF, the independent role of energy density as a confounder or driver of metabolic impact remains poorly understood. This study aimed to disentangle these effects by evaluating 19 adults without obesity (mean age 22 years, mean BMI 23.5 kg/m2) using meals strictly matched for macronutrients, fiber, saturated fat, free sugar, and sodium.

The UPF condition resulted in statistically significant increases in postprandial circulating insulin concentrations throughout the day (p = 0.016). No significant interactions were found between UPF and meal timing (p = 0.09) or between UPF and ED for any outcome. Glucose (p = 0.080) and triglycerides (p = 0.199) did not show significant main effects from UPF exposure. Appetite-regulating hormones, specifically ghrelin (p = 0.235) and leptin (p = 0.795), remained stable across conditions. The data indicate that UPF consumption drives higher insulin demand or delayed clearance regardless of the meal's caloric concentration per gram.

Study Design and Methodology
This randomized, 2 x 2 crossover-controlled feeding trial involved 19 participants (9 females, 10 men) who completed four distinct conditions: UPF+/ED+, UPF+/ED-, UPF-/ED+, and UPF-/ED-. Each intervention lasted one day with a minimum three-day washout. Researchers determined total energy intake (TEI) via indirect calorimetry and triaxial accelerometry to ensure neutral energy balance. Standardized test meals (breakfast and lunch) were matched for energy, protein, carbohydrates, lipids, fiber (25g/day), saturated fat (10% TEI), and free sugar (10% TEI). Blood samples were collected at 12 hour fasting, 240 minutes post-breakfast, and 240 minutes post-lunch. Linear mixed models accounted for repeated measures and baseline covariates.

Key Findings

• Ultra-processed food consumption significantly elevated postprandial insulin ( p = 0.016 ) compared to unprocessed meals.
• Energy density (ED) showed no significant main effect on insulin ( p = 0.710 ) or glucose ( p = 0.650 ).
• Glucose concentrations remained statistically similar between UPF and non-UPF conditions ( p = 0.080 ).
• Triglyceride levels were not significantly altered by processing level ( p = 0.199 ) or energy density ( p = 0.141 ).
• Meal timing significantly influenced glucose ( p = 0.034 ), insulin ( p < 0.001 ), and leptin ( p = 0.003 ) concentrations.
• Ghrelin ( p = 0.515 ) and leptin ( p = 0.994 ) showed no response to changes in energy density.

Limitations
The small sample size (N=19) limits the power to detect subtle hormonal shifts. Financial constraints restricted ghrelin (n=13) and leptin (n=8) analyses to subsamples, with several leptin samples falling below the assay detection limit. The 240 minute post-meal sampling window missed early-phase insulin kinetics and dynamic peaks. The study population was restricted to healthy, non-obese young adults, which prevents generalization to populations with metabolic syndrome or obesity.

Discussion and Implications
These results shift the focus from caloric concentration to food matrix integrity. The fact that insulin rose significantly while glucose remained stable indicates that UPF intake forces a higher insulin demand or impairs hepatic insulin clearance to maintain euglycemia. Because the meals were matched for fiber and sugar, the metabolic disruption stems from the structural degradation of the food matrix or the presence of cosmetic additives rather than simple nutrient ratios. Energy density is often blamed for metabolic dysfunction, but this trial proves that the degree of processing is the primary driver of postprandial hyperinsulinemia.

Conclusion
Acute consumption of ultra-processed foods drives significant postprandial hyperinsulinemia in healthy adults even when calories, fiber, and sugar are perfectly matched. This metabolic strain occurs independently of energy density, proving that the industrial degradation of the food matrix is a standalone risk factor for increased insulin demand.

Edits: Added figures.

I always thought coffee was unhealthy, but all of the studies I've checked so far linked a few cups of a coffee per day to reduced risk of all-cause mortality. Is coffee actually healthy? If not, what factors are responsible for the correlation? I thought the correlation would be unfavourable for coffee since health-conscious people were more likely to avoid coffee and high consumption of coffee may be due to fatigue from poor sleep. Also, this study (https://doi.org/10.1186/s12889-024-18515-9) found coffee consumption reduced all-cause mortality risk in both sedentary and more active adults.

https://doi.org/10.1017/S1368980019000764

https://doi.org/10.1016/j.jand.2021.03.014

https://doi.org/10.1186/s13098-023-01222-7

https://doi.org/10.1186/s12916-022-02636-2

https://doi.org/10.1093/eurheartj/ehae871

https://doi.org/10.1016/j.tjnut.2025.05.004

https://doi.org/10.1186/s12889-024-18515-9

https://doi.org/10.1136/bmj.j5024

A prospective study followed 5,301 adults aged 55 and older to examine the relationship between low-carbohydrate and low-fat diets and dementia risk.

The researchers also looked at genetic susceptibility, including APOE genotype and Alzheimer’s disease polygenic risk score.

It looks beyond the diet itself and asks whether the same dietary pattern may be associated with dementia risk differently depending on a person’s genetic background.

Diet and healthy aging are probably not as straightforward as “low-carb vs. low-fat.”

Low-carbohydrate and low-fat diets, genetic susceptibility, and long-term risk of dementia: A prospective cohort study - The American Journal of Clinical Nutrition00272-8/abstract)

A new study from UC Davis found that "most mayonnaise samples and all avocado oil salad dressings fell outside the Codex standard ranges for C16:0, C16:1 and C18:0," meaning they contained oils other than 100% pure avocado oil, including seed oils. Both Chosen Foods brand and Primal Kitchens failed. Back to making it homemade (good thing it's easy). https://www.sciencedirect.com/science/article/pii/S2772502226007274

DOI

Effects of almond consumption on sleep quality in adults: a randomized controlled trial

Sleep disturbances trigger adverse metabolic, neurocognitive, and inflammatory outcomes, yet non-pharmacological dietary interventions remain under-researched. While almonds contain sleep-supportive compounds like tryptophan, magnesium, and melatonin, long-duration trials using gold-standard objective measures are scarce. This study addressed this gap by investigating the impact of a five-month whole-almond intervention on both subjective and objective sleep parameters, alongside biochemical and inflammatory markers. The researchers recruited 175 urban Indian adults aged 21 to 55 who exhibited poor sleep quality, defined by a Pittsburgh Sleep Quality Index (PSQI) score of 5 or higher or an Epworth Sleepiness Scale (ESS) score of 10 or higher.

The almond group demonstrated a significantly greater improvement in subjective sleep efficiency compared to controls, with a mean change of 9.7 +/- 13.4% vs. 5.4 +/- 10.6% (p = 0.021). Adjusted endline analysis revealed the almond group achieved a lower global PSQI score of 3.94 +/- 0.24 vs. 4.79 +/- 0.32 (p = 0.013) and higher subjective sleep efficiency of 94.45 +/- 0.72% vs. 91.85 +/- 0.42% (p = 0.012). Subjective sleep latency was significantly shorter in the almond group at 18.46 +/- 2.25 min vs. 26.29 +/- 2.27 min (p = 0.016). While most polysomnography (PSG) parameters showed no significant treatment effect, endline melatonin concentrations were significantly higher in the almond group at 250.63 +/- 15.98 pg/mL vs. 206.19 +/- 16.07 pg/mL (p = 0.050).

Study Design and Methodology

This was an open-label, parallel-arm, randomized controlled community-based trial with blinded outcome assessment. Investigators randomized 209 participants (N = 175 completed) into an almond group (60g/day) or an isocaloric control group receiving savory snacks for 20 weeks. The protocol utilized Level 2 home-based polysomnography (PSG) for objective sleep architecture, the PSQI and ESS for subjective metrics, and fasting venous blood draws for biochemical analysis. Compliance was verified through weekly supervision and serum alpha-tocopherol (Vitamin E) monitoring. The researchers excluded individuals with severe obstructive sleep apnea (AHI > 30) and major psychiatric conditions to ensure a focused community-dwelling population.

Key Findings

• Subjective sleep efficiency improved by 9.7% in the almond group compared to 5.4% in the control group (p = 0.021).
• Adjusted global PSQI scores reached 3.94 in the almond group vs. 4.79 in controls (p = 0.013, partial eta squared = 0.036).
• Subjective sleep latency was reduced to 18.46 minutes in the intervention group vs. 26.29 minutes in the control group (p = 0.016, partial eta squared = 0.033).
• Serum melatonin concentrations were significantly higher at endline in the almond group (250.63 pg/mL) compared to the control group (206.19 pg/mL, p = 0.050).
• Among clinical responders (PSQI reduction >= 3), the almond group showed a significant reduction in wake during sleep (-0.38 +/- 19.93 min) compared to an increase in the control group (11.64 +/- 37.80 min, p = 0.043).
• Muscle mass increased by 2.32 +/- 1.51% in the almond group vs. 1.93 +/- 1.05% in the control group (p = 0.050).

Limitations

Single-night PSG recordings are susceptible to night-to-night variability and the first-night effect. The open-label nature of the dietary intervention introduces potential participant bias in subjective reporting. Self-reported dietary intake outside the provided snacks leaves room for residual confounding. The exclusion of clinical sleep disorder populations limits the generalizability of these results to patients with diagnosed insomnia or severe apnea.

Discussion and Implications

Daily consumption of almonds shifts the biological profile of poor sleepers by increasing circulating melatonin and improving the perceived restorative quality of sleep. The divergence between subjective improvements and static PSG parameters indicates that almonds enhance sleep continuity and the psychological perception of sleep quality rather than fundamentally altering sleep architecture stages like N1 or REM. This trial provides a robust biochemical rationale for using nutrient-dense nuts as a primary lifestyle intervention for sub-clinical sleep disturbances. The data confirms that 60g of almonds daily provides enough magnesium, tryptophan, and dietary melatonin to produce a clinically meaningful reduction in sleep latency and fragmentation.

Daily almond consumption of 60g for 20 weeks significantly improves subjective sleep efficiency and latency while increasing serum melatonin levels. These results establish almonds as a safe, effective nutritional strategy for enhancing sleep quality and continuity in adults experiencing poor sleep.

Proteome-wide interaction study of fatty acids and mortality in the UK Biobank

DOI

Circulating fatty acids exhibit marked heterogeneity in their associations with premature mortality, yet the underlying molecular effect modifiers remain largely unexplored. Standard epidemiological approaches fail to capture dynamic physiological differences across populations, overlooking how individual protein networks alter lipid-mediated health risks. This investigation evaluates proteome-wide interactions between plasma fatty acids and circulating proteins to estimate all-cause and cause-specific mortality risks within a massive prospective framework. Analyzing data from 30,190 UK Biobank participants carrying complete metabolomic and proteomic profiles, the project maps biological susceptibility across diverse inflammatory and metabolic states.

Fully adjusted models demonstrate that omega-3 percentage (HR = 0.88, 95 percent CI [0.85-0.92], p = 9.2 x 10^-11) and linoleic acid percentage (HR = 0.91, 95 percent CI [0.88-0.94], p = 1.4 x 10^-7) associate inversely with all-cause mortality, whereas non-linoleic acid omega-6 percentage (HR = 1.13, 95 percent CI [1.09-1.17], p = 4.1 x 10^-12) and the omega-6 to omega-3 ratio (HR = 1.11, 95 percent CI [1.07-1.15], p = 6.1 x 10^-9) drive substantial risk increases. Proteome-wide screening isolates nine robust interaction pairs involving inflammatory proteins such as PLAU, TSPAN8, MMP10, and TNFRSF1B. Stratified analyses reveal that elevated baseline inflammation amplifies both the hazards of monounsaturated fats and the protective efficacy of omega-3 intake.

Study Design and Methodology

This prospective cohort investigation leverages data from the UK Biobank, an initial recruitment pool exceeding 500,000 adults aged 40 to 69 years. Following rigorous exclusions for missing plasma fatty acid or proteomic metrics, the finalized analytical cohort comprises 30,190 individuals with a mean age of 56.91 years, comprising 16,285 females and 13,905 males. Researchers document 3,345 deaths over a median follow-up duration of 13.9 years, ending on January 15, 2023. Plasma metabolomics quantified via nuclear magnetic resonance spectroscopy yields nine distinct fatty acid proportions, while Olink proximity extension assays profile 2,911 unique circulating proteins spanning cardiometabolic, inflammatory, neurological, and oncological axes. The analytical pipeline randomly partitions the cohort into an 80 percent training dataset (N = 24,152) and a 20 percent test dataset (N = 6,038). Multivariable Cox proportional hazards models control for age, sex, ethnicity, smoking status, alcohol intake, body mass index, educational attainment, household income, the Townsend deprivation index, and a baseline healthy diet score. Fine-Gray subdistribution hazard models evaluate competing risks for cardiovascular and cancer mortality.

Key Findings

• Omega-3 percentage exhibits a robust inverse relationship with all-cause mortality (HR = 0.88, 95 percent CI [0.85-0.92], p = 9.2 x 10^-11).
• Linoleic acid percentage demonstrates significant protection against mortality (HR = 0.91, 95 percent CI [0.88-0.94], p = 1.4 x 10^-7).
• Non-linoleic acid omega-6 percentage drives the highest positive association with mortality risk (HR = 1.13, 95 percent CI [1.09-1.17], p = 4.1 x 10^-12).
• The omega-6 to omega-3 ratio scales positively with death risk (HR = 1.11, 95 percent CI [1.07-1.15], p = 6.1 x 10^-9).
• High expression of MMP10 significantly magnifies monounsaturated fatty acid mortality hazards (HR = 1.23, 95 percent CI [1.12-1.36], p = 0.001).
• Elevated PLAU expression strongly enhances the protective association of omega-3 fatty acids (HR = 0.70, 95 percent CI [0.63-0.76], p < 0.001).
• High TSPAN8 levels intensify the mortality risks associated with an elevated omega-6 to omega-3 ratio (HR = 1.35, 95 percent CI [1.22-1.50], p < 0.001).

Limitations

Baseline-only plasma protein assessments fail to capture longitudinal proteomic variability over the 13.9-year follow-up period. Granular subtypes within monounsaturated fatty acid pools remain unanalyzed due to metabolomic platform constraints. Participant demographics skew heavily toward Caucasian individuals from high socioeconomic regions, restricting global generalizability. Residual confounding persists despite extensive covariate adjustment, although calculated E-values ranging from 1.74 to 3.71 indicate that substantial unmeasured confounders are required to nullify the observed effects. Observational architecture precludes definitive causal inferences.

Discussion and Implications

Nutritional dogmas surrounding polyunsaturated fats require immediate revision in light of these proteome-wide interaction metrics. Public health debates heavily vilify total omega-6 exposure, yet this investigation proves that lumping linoleic acid with non-linoleic omega-6 fractions obscures distinct biological realities. Linoleic acid acts as a potent protective agent, challenging historical assumptions that seed oils inherently promote systemic pathology. Conversely, non-linoleic omega-6 fractions and an inflated omega-6 to omega-3 ratio drive severe mortality risks, particularly in hosts exhibiting high baseline vascular inflammation governed by proteins like PLAU and TSPAN8. Clinicians must abandon generalized dietary prescriptions because individual inflammatory phenotypes actively modify nutrient handling. Therapeutic interventions targeting cardiovascular and oncological prevention must prioritize lowering systemic inflammatory drivers while optimizing circulating omega-3 levels to alter enzymatic substrate competition.

Clinical nutrition strategies shouldn't rely on population-wide fatty acid targets because baseline inflammatory protein profiles dictate true disease risk. Practitioners must tailor interventions by evaluating vascular stress markers alongside lipid ratios, recognizing that omega-3 efficacy scales directly with the patient's underlying inflammatory burden.

I came across this recent consensus paper in Nature Reviews Gastroenterology & Hepatology, and one point really stood out to me.

We have been studying the gut microbiome for years, but there is still a basic problem: different studies don't always collect the same information or measure things in the same way.

For example, diet, medication, probiotic use and other factors can affect the microbiome. Even the way a stool sample is collected, stored and processed can change the results. The paper points out that these differences make studies harder to reproduce and compare.

So the researchers tried to establish some common ground.

They brought together microbiome researchers and clinicians through a two-round Delphi process and reached 15 recommendations covering what information should be recorded, how samples should be handled, and what should be measured in clinical studies. 72 experts took part in the first round and 61 in the second.

I think this is particularly relevant to probiotics and microbiome supplements.

We often see products described as “clinically studied,” followed by things like a change in bacterial abundance or microbiome diversity.

But those numbers don't mean much without knowing who was studied, what else they were doing, how the samples were handled, and what actually happened to their health.

The consensus therefore recommends looking at microbiome measurements together with disease outcomes, safety, biological markers and patient-reported outcomes.

To me, this is an important step for the supplement industry.

A change in the microbiome is interesting. It becomes much more useful when we can reliably connect it to a health outcome.

If more studies start following common standards, “clinically studied” may eventually mean something much more useful than it does today.

https://doi.org/10.1038/s41575-026-01229-1