Background. Body fat percentage is considered in sports science as a stable, comparable, and interpretable measure. Athletes are compared to sport-specific reference ranges, values from different instruments are directly compared, and differences between sports are attributed to contact demands. None of these assumptions have been systematically tested, and the reference tables most widely used have not been verified against the primary literature they are thought to be based on. Objectives. To assess whether body fat percentage supports the comparisons typically made with it. Specifically: whether values obtained by different measurement methods are comparable; whether the conventional sport-specific reference ranges originate from primary sources; whether a single percentage has a consistent physiological meaning across the competitive spectrum; and whether contact classification accounts for differences in body composition between sports. Methods. A narrative review was conducted. Sources were identified through PubMed, publisher databases, and references from recent reviews. Each data point was categorized as Tier 1 (traceable to a primary peer-reviewed source with details on sample size, measurement method, and dispersion) or Tier 2 (common practitioner ranges without primary source attribution). Sports were organized using the American Academy of Pediatrics contact taxonomy, which served as the main stratification criterion and was evaluated against alternative classifications. Competitive level was determined using the Participant Classification Framework. Results. Tier 1 data included 5,144 athletes and 228 controls with reported sample sizes, along with 232 data points from a review of 90 studies [1]. Elite male athletes had a mean body fat of 14.1 ± 5.4% (range: 8.7–19.5%), and elite females averaged 21.8 ± 4.1% (17.7–25.9%). Contact level did not align with body type clustering; instead, body mass demand—which is a new classification introduced here—accounted for 68.6% of differences between sports, compared to 17.4% for contact level (permutation p = 0.0017). Measurement method influenced variance more than sex: in basketball, values ranged from 12.4% (skinfold) to 21.4% (DXA), a 9-point difference that exceeds the 7.6-point difference between males and females within the same sport. Combat sports (boxing, taekwondo) clustered at 9.8 ± 2.2%, the leanest group, similar to endurance sports. Collision team sports without weight classes (American football, rugby) averaged 15.9 ± 2.6%. Within collision team sports, positional differences exceeded differences between sports: NFL rosters averaged 17.9 ± 6.9%, with defensive backs around 12% and linemen over 25%. Of 32 ranges examined, none were identified within the search described in Section 2.2 as tracing to primary sources. Decomposition of the gradient at each end of the competitive range revealed two opposing mechanisms: below Tier 2, fat mass index decreased by 29.1% while fat-free mass index was unchanged (−1.2%); between Tier 0–1 and Tier 4–5, lean mass was 52.9% greater while fat mass was 10.8% greater in absolute terms. Coefficient of variation was approximately half as large in sports with low mass demand (20.1%) compared to capped (38.8%) or high (38.7%) mass demand sports. Conclusions. Body fat percentage combines two physiologically opposite processes and thus provides no clear information about which process is dominant: below Tier 2, a decreasing percentage indicates fat loss with stable lean mass, while at Tier 4–5, a lower percentage reflects lean mass gain against increasing fat mass. This offers a mechanistic explanation for why lean mass more reliably indicates training status than adiposity. It also suggests that fat mass index and fat-free mass index should be reported alongside, or instead of, body fat percentage. Contact level is not related to body composition. One possible explanation, proposed here as a hypothesis, is body mass demand—what the sport's mechanics and rules require in total mass—leading to low, high, or capped categories. Methodologically, body composition should not be used as a proxy or covariate for head-impact exposure in neurotrauma risk models, as these are independent factors. Standard sport-specific ranges generally align with Tier 1 data but should be viewed as heuristic rather than definitive values. Two additional analyses (by competitive tier and age) and an applied reference are included. All data are cross-sectional and only show associations. Data for female non-athletes and female sub-elite athletes could not be sourced.

Background: A person with depression, unresolved trauma, a substance problem, and cognitive complaints is treated differently depending on which practitioner they consult. A psychiatrist draws on the monoaminergic and glutamatergic literature. A licensed facilitator draws on the session literature. A naturopath draws on the botanical and nutritional literature. Each draws on a defensible evidence base, and none of the three literatures routinely cites the other two. No single reference covers the agents acting on these conditions across the disciplines that use them, with the evidentiary standing of each claim visible and the boundary of each practitioner’s authority stated. Objective: To organize that agent population by mechanism of action rather than by regulatory status or professional tradition, assign an explicit evidence tier to every claim, characterize the route and bioavailability for every agent, and derive an operational logic for safety gating, interaction adjudication, and protocol construction that practitioners from differing disciplines and with varying prescribing authority can apply within their own scope. Methods: A structured review was conducted with framework development, defining fifteen mechanism classes based on receptor pharmacology and downstream signalling. Each agent was characterized by its mechanism, dose range, route, established bioavailability, onset, duration, evidence tier, contraindications, and potential interactions. The evidence was evaluated through an international literature review and categorized into a single standardized tier system, regardless of jurisdiction: T1 for randomized controlled trials, T2 for controlled studies with limitations, T3 for observational or open-label studies, T4 for mechanistic evidence only, and T5 for traditional use. Results: Fifteen classes are outlined across 154 subsections, covering areas like glutamatergic modulation, serotonergic psychedelics, entactogens, non-5-HT2A psychoactives, monoaminergic and inhibitory modulation, neurotrophic and neuroimmune agents, adaptogenic and mitochondrial support, pharmacokinetic modification, potentiation, cholinergic modulation, and circadian phase. Seventy-six agents are individually characterized. A condition matrix links them to sixty-eight indications, including cluster headache, tic disorders, traumatic brain injury, chronic pain, burnout, and insomnia, which are often missing from reviews despite substantial supporting data. The safety measures include six safety gates, eighteen interaction rules with specified severity, a seven-step construction process, and a role-scope matrix. Route and bioavailability are detailed for each agent: five deliver about the administered dose; several widely used agents reach systemic circulation at one to ten percent; and four are pharmacologically inert via their primary route. Conclusions: A mechanism-first organization enables the evaluation of agents with varying evidentiary credibility and regulatory statuses within a single framework, without undervaluing weaker evidence or overestimating stronger cases. Three key points follow. The evidence tier pertains to the agent-indication-dose triplet, not the agent itself: for example, piracetam shows T1 evidence for myoclonus at 24 g daily and T4 for cognition at any dose. An additional axis, circadian phase, runs alongside dose, mechanism, and route; a shifted rhythm indicates deficiency and calls for the opposite intervention. When absorption or first-pass metabolism limits a compound rather than receptor pharmacology, the issue is a formulation problem and should be labelled as such. This framework is designed for complementary and adjunctive practices, highlights sections needing prescribing authority, and does not replace personalized clinical judgment.

Background: Pharmacological glucagon-like peptide-1 receptor agonists (GLP-1RAs) such as semaglutide and dual glucose-dependent insulinotropic polypeptide (GIP)/GLP-1 receptor agonists such as tirzepatide produce clinically meaningful weight reduction in adults with overweight or obesity. However, gastrointestinal and serious adverse events affect a substantial proportion of treated patients, contributing to discontinuation and limiting long-term adherence. Nutraceutical compositions designed to stimulate endogenous GLP-1 and GIP secretion may offer a tolerability advantage. Objective: To describe weight change and adverse event rates in a real-world cohort of overweight adults using a nutraceutical endogenous incretin secretagogue composition (Trimsulin Weight Loss Program) and to compare these outcomes with publicly available outcome data for semaglutide and tirzepatide. Methods: Observational cohort analysis of 503 overweight adults enrolled in the Trimsulin Weight Loss Program, comprising two nutraceutical products (Control, a powdered drink mix; Thermo, a capsule formulation) taken twice daily before meals, plus a structured dietary protocol and a moderate-exercise recommendation. Body weight, BMI, and participant-reported adverse events were tracked at 12 weeks and 24 weeks. Comparative weight-loss outcomes for semaglutide and tirzepatide were drawn from the on-treatment estimand of the published Truveta-derived real-world cohort analysis by Rodriguez et al. (n = 18,386; mean baseline BMI 39.0). Comparative adverse event rates were drawn from a separate body of clinical trial and pharmacovigilance evidence. Outcomes are reported descriptively; no inferential statistical testing was performed between cohorts. Results: Of more than 1,000 enrolled program participants, 503 completed six months of program participation with protocol-conformant follow-up measurements and constitute the analysis cohort. Mean baseline weight was 201.2 lb (range 130–360); mean BMI was 27.5 (range 20.0–50.1). At 3 months, mean weight reduction was 7.3% in the Trimsulin cohort, compared with 3.6% (semaglutide) and 5.9% (tirzepatide) reported in published comparator data. At 6 months, mean reductions were 14.1%, 5.8%, and 10.1%, respectively. Any adverse event was reported by 4.8% of Trimsulin participants, compared with 89.7% (semaglutide) and 81.0% (tirzepatide) in published trial cohorts. No serious adverse events were reported in the Trimsulin cohort, compared with approximately 3.0% for semaglutide and 5–7% for tirzepatide. These hypothesis-generating findings support further controlled investigation of endogenous incretin secretagogue compositions as a class. The present cohort study evaluated one licensed implementation of the BSM platform framework. Future research directions of highest priority include prospective randomized controlled trials of BSM-framework compositions — including next-generation formulations incorporating more advanced ingredient systems and delivery architectures — compared against placebo and against active pharmacological incretin comparators. Secondary endpoints of particular mechanistic value include changes in plasma active GLP-1 and GIP concentrations, DPP-4 activity, fasting and post-prandial glycemic response, UCP-1 induction, and patient-reported tolerability. A factorial design apportioning the contribution of the BSM supplement components versus the dietary and behavioral program elements would clarify the mechanistic contribution of each. Adjunctive use of BSM-framework compositions in patients who discontinue pharmacological incretin therapy due to intolerance represents a clinically meaningful research direction, given the established real-world discontinuation burden of pharmacological GLP-1 receptor agonists. [11–14] Beyond supplement formats, investigation of BSM-framework ingredient systems in functional food and food-additive delivery formats represents a translational research direction of broader public health relevance, given the potential for population-scale access that food-category routes offer relative to pharmaceutical channels.

Background. Repetitive head impacts in contact sports create a cumulative, mostly subconcussive mechanical burden now linked to long-term neurodegeneration, including chronic traumatic encephalopathy (CTE). The harmful factor seems to be cumulative exposure rather than occasional diagnosed concussions. However, the current evidence base is mostly retrospective and biased by selection — derived from autopsy and brain-bank studies — or limited to diagnosed concussions. Each sport measures exposure in different, incompatible units such as heading frequency, punches received, tackles, or impact counts from instruments. No tool exists to convert a living athlete's participation into a forward-looking, comparative estimate of lifetime brain-injury risk. Methods. We developed a transparent, reproducible computational model that standardizes head-impact exposure across six contact sports—boxing, mixed martial arts, kickboxing/Muay Thai, American football, rugby, and soccer—into a single measure called the Normalized Head-Impact Dose (HID). This metric weights each impact by its head-acceleration magnitude, with rotational acceleration given more emphasis than linear acceleration, reflecting the established finding that diffuse brain injury is mainly driven by rotational acceleration. The cumulative burden is modeled as an increasing function of total exposure, incorporating a vulnerability multiplier (the core parameter), while a bounded resilience term is included only in sensitivity analyses. Sport-specific rotational fractions are based on each sport's mechanism of play; for football, the data is further broken down by player position. Parameters were derived through systematic review of existing literature; every estimate is provided with a 95% uncertainty interval. Burden is expressed relative to a low-exposure reference, and the strength of evidence for each sport is graded accordingly. The model parameters in this version are set as default values pending systematic extraction, and sensitivity analyses are used to test all major assumptions. Reporting follows the TRIPOD guidelines, adapted for a model based on literature data. Results. Based on literature-supported initial parameters, the model produces (i) a ranked comparison of lifetime burden where the most significant burdens are seen in combat sports — Muay Thai/kickboxing and boxing — with soccer having the least, and MMA, American football, and rugby occupying an indeterminate middle with overlapping uncertainty intervals; (ii) sport-specific dose-response curves that increase with years of participation; (iii) higher burden associated with earlier age at first exposure; and (iv) a ranked set of modifiable factors, with reducing exposure volume being most prominent. A sub-analysis within football reveals that linemen's cumulative burden is comparable to that of higher-magnitude skill positions, and a comparison to a reference athlete shows that while the ranking remains consistent in shape, it scales steeply with the level of engagement. All values are preliminary, reported as medians with 95% uncertainty intervals, and will change as systematic parameter extraction progresses; the orderings and curve shapes, rather than the exact point values, constitute the current findings. Conclusions. A normalized, mechanism-derived burden model offers a forward-looking, comparative framework to assess lifetime brain-injury burden across contact sports — providing decision-relevant estimates with clear uncertainty, unlike the current literature, which mostly provides retrospective, selection-biased, or sport-specific data. The framework aims to generate solid comparative estimates rather than make categorical claims that one sport is most dangerous. Since there is no external standard for cross-sport burden yet, a prospective validation protocol is pre-specified (Appendix A), framing this work as the first stage of a two-stage development-and-validation process.