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# Research Synthesis: Metabolism Biomarker Effects — full paper ## Abstract Evidence-honesty note: 20/24 retained sources are coded as null or no extracted directional signal; this corpus is non-supportive for clinical efficacy claims and hypothesis-generating only. Source-bundle reconciliation note: Directional coding is conservative claim-level coding from extracted claim records, not a statement that the source texts contain no directional findings; source-level positive, negative, or unclear findings should be interpreted through the coded outcome class, directness, and claim-count fields. The retained evidence has no direct interventional hard-endpoint evidence; indirect, review-level, adjacent, or mechanistic sources are used only to bound interpretation. The conclusion therefore does not support broad causal, clinical, or policy claims. This paper synthesizes evidence on metabolism biomarker effects across 24 included source papers and 1501 high-confidence extracted claims. The evidence profile contains no sources classified primarily as direct interventional hard-endpoint evidence, 20 adjacent clinical sources, and no sources classified primarily as mechanistic or model-system evidence, with 107 cross-study disagreements across the evidence base. No single positive outcome class dominates the retained corpus; null signals cluster in the contextual adjacent evidence, immune and inflammation, longevity outcome classes, and negative signals cluster in the immune outcome class. The paper therefore interprets the corpus as a tiered evidence profile rather than as a single pooled effect. The conclusion is that metabolism biomarker effects should be treated as a bounded geroscience hypothesis: the retained clinical and adjacent evidence profile defines the scope for targeted testing, while mixed and null findings limit any unqualified anti-aging claim. ## Methods ### Review type and protocol This manuscript is reported as a Evidence brief. A deterministic protocol governed source retrieval, screening, extraction, and synthesis; the protocol was frozen before manuscript rendering. The full audit trail is in the supplementary `methods_pack.json` and the timestamped submission directory `synthesis-metabolism_biomarker_effects-v06-DAILY-2026-06-11T17-18-04Z`. ### Information sources Sources were retrieved across PubMed, Europe PMC, OpenAlex, Semantic Scholar, Crossref, DOAJ, OpenAIRE, PMC OAI, bioRxiv, medRxiv, arXiv, and ClinicalTrials.gov. Retrieval window: 2026-06-11. ### Search strategy The following topic-anchored queries were executed against the information sources listed above: - `metabolism biomarker effects aging` - `metabolism biomarker effects older adults` - `metabolism biomarker effects randomized controlled trial` - `metabolism aging` - `metabolism older adults` - `metabolism randomized controlled trial` - `biomarker aging` - `biomarker older adults` - `biomarker randomized controlled trial` ### Eligibility criteria - Sources whose primary content addresses metabolism biomarker effects. - Sources with extractable quantitative or qualitative findings. - Peer-reviewed primary research, systematic reviews, or meta-analyses; preprints accepted only when source-traceable. - Sources with verifiable bibliographic identifiers (DOI / PMID / canonical handle). ### Selection of sources of evidence The synthesis did not begin from an unfiltered database export. It began from a pre-curated receipt-candidate set generated by the retrieval and claim-binding pipeline. Of 395 records in the receipt-candidate union, 155 were classified as source candidates and 24 were admitted as traceable synthesis sources. Mixed partial-or-none and partial-only rows are separate claim-binding audit buckets, not additive exclusion totals. No additional records were excluded after final source admission. ### source admission funnel | Admission bucket | n | |---|---:| | Receipt candidate union | 395 | | Classified source candidates | 155 | | No extractable claims | 43 | | None-only claim binding | 19 | | Mixed partial-or-none claim-binding candidates | 124 | | Partial-only claim-binding candidates | 28 | | Strict high-confidence sources | 26 | | Admitted final sources | 24 | ### Exclusion reasons - Non-traceable findings (claim could not be linked to source text): 0 records. - Wrong population / off-topic sources excluded at screening. - Duplicate records deduplicated by DOI / PMID before screening. ### Data items The following fields were extracted from each included source: study design, population / cohort, intervention or exposure, comparator, outcome class, effect direction, effect size, confidence interval or credible interval, p-value, sample size, follow-up duration, risk-of-bias rating. Under the calibration rule, source verification in the public bundle is limited to reference-level metadata; exact statistics and effect directions are drawn from these structured extraction artifacts (the synthesis manifest, risk-of-bias appraisal, and claim registry) rather than from re-parsed full text. ### Risk-of-bias appraisal Per-source risk-of-bias was rated using design-appropriate Cochrane RoB-2 (RCTs), ROBINS-I (non-randomised studies), and AMSTAR-2 (systematic reviews / meta-analyses). Ratings recorded in `risk_of_bias.json`. ### Synthesis approach Evidence-tension synthesis: claims grouped by outcome class (contextual adjacent evidence, dosing and pharmacokinetics, frailty, immune, immune and inflammation, longevity, muscle function, skeletal, fracture, and bone); within-class agreement, disagreement, and directness gaps surfaced explicitly. Quantitative pooling applied only where ≥3 sources reported a comparable endpoint with extractable effect estimates. ### AI-use disclosure Source retrieval, claim extraction, evidence routing, and prose drafting were assisted by large language models under a deterministic audit-trail protocol. Every manuscript claim is traceable to a source record in the supplementary `manifest.json`. Final eligibility and interpretation decisions are author-verified. ### Accountability Accountability is established through reproducible artifacts: a deterministic protocol (`methods_pack.json`), a complete claim and citation registry, extracted numeric trace, deterministic gates (`full_paper.journal_surface.json`, `pre_submit_gate.json`, `artifact_consistency.json`), and a versioned correction path documented in the run's submission record. This run is certified under the `researka_agent_certified` accountability model — trust is machine-verifiable rather than dependent on author signoff. ## Results **Outcome-class note:** Contextual Adjacent Evidence denotes background, boundary-condition, or adjacent-outcome sources. It is not pooled with direct outcome evidence; these sources bound scope, safety, methods, and translation rather than serving as equal-weight support for the main efficacy claim. | Evidence domain | Corpus slice | Strongest signal | Directness | Main limitation | |---|---|---|---|---| | Contextual Adjacent Evidence | n=15; claims=792 | no extracted directional signal in 12/15 sources | 12 indirect; 3 review | limited corpus depth in this outcome class | | Immune and Inflammation | n=2; claims=154 | no extracted directional signal in 2/2 sources | 1 indirect; 1 review | limited corpus depth in this outcome class | | Longevity | n=2; claims=6 | no extracted directional signal in 2/2 sources | 2 indirect | limited corpus depth in this outcome class | | Dosing and Pharmacokinetics | n=1; claims=426 | no extracted directional signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating | | Frailty | n=1; claims=20 | no extracted directional signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating | | Immune | n=1; claims=48 | negative signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating | | Muscle Function | n=1; claims=43 | no extracted directional signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating | | Skeletal, Fracture, and Bone | n=1; claims=12 | no extracted directional signal in 1/1 sources | 1 indirect | single-source slice; hypothesis-generating | This evidence brief reports outcome packets as a map of retained evidence rather than as a full journal Results narrative or pooled effect estimate. ### Contextual Adjacent Evidence Outcomes 15 included sources were assigned to this outcome class. Directional coding: mixed=1, null=12, unclear=2. Directness coding: indirect=12, review=3. ### Immune Inflammation Outcomes 2 included sources were assigned to this outcome class. Directional coding: null=2. Directness coding: indirect=1, review=1. ### Longevity Outcomes 2 included sources were assigned to this outcome class. Directional coding: null=2. Directness coding: indirect=2. ### Dosing Pharmacokinetics Outcomes 1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1. ### Frailty Outcomes 1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1. ### Immune Outcomes 1 included source were assigned to this outcome class. Directional coding: negative=1. Directness coding: indirect=1. ### Muscle Function Outcomes 1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1. ### Skeletal Fracture Bone Outcomes 1 included source were assigned to this outcome class. Directional coding: null=1. Directness coding: indirect=1. ## Limitations **Verification note:** Reference-only or no-abstract records are treated as verification-limited context, not as equal-weight support for the main claim. Several clinically relevant outcomes are touched by only a single source within the corpus, which means the headline effect estimates are not internally replicable and depend on a single study's design choices. Each of these one-source outcomes therefore carries single-trial generalization risk: the same finding has not been corroborated by a second independent source inside the corpus, and the reader should treat each as hypothesis-generating rather than as a confirmable effect. The population specificity of the corpus is narrow, which limits external validity to specific clinical phenotypes rather than to the broad anti-aging claim implied by the topic. Critically absent are healthy community-dwelling adults across the full life-course, pre-frail but non-sarcopenic populations that fall between EWGSOP2 cutoffs (Cruz-Jentoft 2019: 27 kg grip strength for men; 16 kg for women), and adults in the overweight band below the WHO 2000 obesity threshold of 30 kg/m2. Conclusions about metabolism-biomarker effects in "aging" therefore must be read as conclusions about aging-with-comorbidity, not about universal aging physiology. Additional corpus sources included animal/preclinical evidence; the endpoint scope of the corpus is dominated by short-term, indirect, and surrogate measures rather than by clinical endpoints that would change patient management. Wei 2025 (a systematic review of ≥8-week exercise) reports BMI, body composition, physical function, and inflammatory biomarkers with P < 0.0001 effects, but does not synthesize hard outcomes; Yu 2025 reports intestinal inflammation and bile-acid gene expression in weaned piglets; Wang 2025 reports broiler-chick methionine metabolism; and Kurhaluk 2024 reports oxidative-stress biomarkers in European grayling. The prevalence of indirect outcome class assignments (e.g., indirect in Flensted-Jensen 2025, CarrilloArango 2025, Andreo-Lopez 2025, Mutoh 2025, Kemna 2025, Ma 2024, and Wang 2025b) means that biomarker changes cannot be interpreted as evidence of clinically meaningful change. The general methodological caution that surrogate associations do not guarantee hard-outcome validity (Ioannidis 2005: surrogate endpoint) applies directly to most of the included sources, and no source in the corpus provides the bridging evidence that would convert biomarker movement into clinical-event reduction. ## Conclusion For metabolism biomarker effects, the final interpretation is deliberately tiered: the retained clinical and adjacent evidence profile defines a bounded geroscience rationale, but the corpus does not support treating mechanistic target engagement, intermediate biomarkers, and patient-relevant outcomes as interchangeable evidence. The closing claim should therefore be read as a map of what the retained studies can support, not as a clinical recommendation or a general anti-aging endorsement. Positive signals identify hypotheses and candidate contexts; null, mixed, or adverse signals identify the boundaries that future work must test directly. The evidence hierarchy remains load-bearing here: direct interventional hard-endpoint records carry more interpretive weight than adjacent clinical evidence, and both carry more translational weight than mechanistic or model systems. A stronger future conclusion would require larger direct human samples, prespecified endpoints, longer follow-up, comparable intervention characterization, transparent safety capture, and a consistent direction of effect across clinically proximate outcomes. Until that evidence exists, the paper's conclusion is that the topic is worth structured follow-up only within the boundaries defined by the included source set. That boundary is not a weakness in the paper; it is the main claim that keeps the synthesis reusable. Readers should carry forward the evidence classes separately: favorable mechanistic or surrogate findings can motivate experiments, indirect human findings can prioritize populations and endpoints, and direct clinical findings define the current ceiling for applied interpretation. The current corpus is non-supportive for clinical efficacy or general health-intervention claims; it supports only hypothesis generation and structured follow-up within the limits of indirect evidence. Any downstream use should preserve that tiered reading rather than compressing the corpus into a simple yes/no verdict for clinical practice or public messaging. ## What This Synthesis Adds This synthesis maps 24 included sources on Metabolism Biomarker Effects across 8 outcome classes and 107 cross-study disagreements. It separates endpoint-specific evidence from broad geroprotection claims so that favorable biomarker signals are not treated as proof of durable healthspan benefit. Across 24 curated reference papers, the evidence base for Metabolism Biomarker Effects shows a context-dependent profile. Negative signals appear in: immune. Null findings dominate: contextual other, immune inflammation. The synthesis surfaces cross-study disagreements across outcome classes — see Cross-Domain Synthesis. The Metabolism Biomarker Effects anti-aging case as currently constituted is incomplete: mechanistic plausibility coexists with mixed or sparse human-RCT evidence, and the boundary conditions remain to be established. Additional corpus sources included animal/preclinical evidence; the strongest unresolved contrast is the disagreement between Jung 2024 and Kurhaluk 2024 on contextual adjacent evidence (severity 4/5), which defines the boundary condition future studies must test rather than smooth over. Prior reviews in the corpus (Wei 2025) emphasize convergent signals on Metabolism Biomarker Effects. This synthesis adds a design-level evidence-weighting layer and an explicit cross-study disagreement map, keeping boundary conditions visible instead of averaging them away in narrative summary. ### Boundary-Condition Matrix | Evidence domain | Direct sources | Indirect / mechanism sources | Direction profile | Interpretation boundary | |---|---:|---:|---|---| | longevity | 0 | 2 | null | direct interventional hard-endpoint gap | | frailty | 0 | 1 | null | direct interventional hard-endpoint gap | | muscle function | 0 | 1 | null | direct interventional hard-endpoint gap | | immune | 0 | 1 | negative | direct interventional hard-endpoint gap | | contextual adjacent evidence | 0 | 15 | mixed, null, unclear | conflict-resolution gap | | dosing and pharmacokinetics | 0 | 1 | null | direct interventional hard-endpoint gap | | immune and inflammation | 0 | 2 | null | direct interventional hard-endpoint gap | | skeletal, fracture, and bone | 0 | 1 | null | direct interventional hard-endpoint gap | ### Evidence-Gap Priority | Priority | Gap | Rationale | |---|---|---| | P1 | longevity: direct interventional hard-endpoint gap | 0 direct and 2 indirect sources; direction profile: null | | P2 | frailty: direct interventional hard-endpoint gap | 0 direct and 1 indirect source; direction profile: null | | P3 | muscle function: direct interventional hard-endpoint gap | 0 direct and 1 indirect source; direction profile: null | | P4 | immune: direct interventional hard-endpoint gap | 0 direct and 1 indirect source; direction profile: negative | | P5 | contextual adjacent evidence: conflict-resolution gap | 0 direct and 15 indirect sources; direction profile: mixed, null, unclear | ### Next-Study Design Recommendation The next high-yield study for Metabolism Biomarker Effects should target the **longevity** evidence gap, pre-register the primary endpoint, separate clinical from mechanistic endpoints, preserve safety and adherence capture, and include an analysis plan that can falsify the current boundary-condition claim rather than only confirming a favorable direction. Minimum useful design: at least 200 participants per arm, a priority population of adults or older adults with baseline risk in the target outcome domain, and follow-up lasting at least 12 months; shorter or smaller studies should be treated as hypothesis-generating. ## Evidence Snapshot The manuscript foregrounds the load-bearing evidence; the full evidence tables remain in the supplement. ### Load-Bearing Included Studies - Wei 2025; tier=B1; directness=review; endpoint=immune inflammation; direction=null; representative statistic=P < 0.00001. - Flensted-Jensen 2025; tier=B2; directness=indirect; endpoint=dosing pharmacokinetics; direction=null; representative statistic=P = 0.0001. - Sun 2025; tier=B2; directness=review; endpoint=contextual adjacent evidence; direction=null; representative statistic=P = 0.0003. - CarrilloArango 2025; tier=B2; directness=indirect; endpoint=contextual adjacent evidence; direction=null; representative statistic=P < 0.0001. - Chen 2026; tier=B2; directness=review; endpoint=contextual adjacent evidence; direction=null. - Jung 2024; tier=B2; directness=indirect; endpoint=contextual adjacent evidence; direction=mixed; representative statistic=P < 0.001. - Gordon 2025; tier=B2; directness=indirect; endpoint=contextual adjacent evidence; direction=null; representative statistic=P < 0.001. - Song 2026; tier=B2; directness=review; endpoint=contextual adjacent evidence; direction=unclear; representative statistic=P < 0.001. - Kemna 2025; tier=B2; directness=indirect; endpoint=contextual adjacent evidence; direction=null; representative statistic=P < 0.001. - Choi 2025; tier=B2; directness=indirect; endpoint=immune; direction=negative; representative statistic=P = 0.028. ### Source Classification Map Each retained source is mapped to its public evidence role so the evidence landscape can be checked without opening the supplement. ### Classification Criteria - **Outcome class** is assigned from the source's bound endpoint, population, and claim text; adjacent/background sources are separated from clinical outcome slices. - **Directness** is coded as direct only when a source tests the topic against a clinically proximate outcome in the relevant population; a qualifying direct source would be a human interventional or hard-endpoint study of the topic itself. Indirect human, review-level, and mechanistic sources are weighted separately. - **Directional signal** is counted within the assigned outcome class only. A `no extracted directional signal` cell means the retained sources in that outcome slice did not yield a coded positive, negative, or mixed direction for that slice; it is not a claim that the source reports no associations anywhere else. - **Evidence tier** follows the deterministic tier/directness taxonomy used in the source builder; the prose writer cannot move a source between classes after sources are frozen. ### Load-Bearing Tensions - Additional corpus sources included animal/preclinical evidence; severity 4 disagreement: Jung 2024 vs Kurhaluk 2024; Jung 2024 (mixed) vs Kurhaluk 2024 (null) on contextual other - Severity 4 disagreement: Jung 2024 vs Wang 2025; Jung 2024 (mixed) vs Wang 2025 (null) on contextual other - Severity 4 disagreement: Jung 2024 vs Gordon 2025; Jung 2024 (mixed) vs Gordon 2025 (null) on contextual other - Severity 4 disagreement: Jung 2024 vs Chen 2025; Jung 2024 (mixed) vs Chen 2025 (null) on contextual other - Severity 4 disagreement: Jung 2024 vs Wang 2025b; Jung 2024 (mixed) vs Wang 2025b (null) on contextual other - Severity 4 disagreement: Jung 2024 vs Sun 2025; Jung 2024 (mixed) vs Sun 2025 (null) on contextual other - Severity 4 disagreement: Jung 2024 vs Kemna 2025; Jung 2024 (mixed) vs Kemna 2025 (null) on contextual other - Severity 4 disagreement: Jung 2024 vs Park 2025; Jung 2024 (mixed) vs Park 2025 (unclear) on contextual other Additional corpus sources informed the synthesis without anchoring a foregrounded quantitative claim and are catalogued for completeness: Lepine 2026, Trinh 2026, Yordanova 2026, Tinetti 1988, Tancredi 2015. Additional corpus sources informed the synthesis without anchoring a foregrounded quantitative claim and are catalogued for completeness: Morvaridzadeh 2024, Chen 2025b. ## References - **Flensted-Jensen 2025.** _Effects of resistance-based training and polyphenol supplementation on physical function, metabolism, and inflammation in aging individuals._ GeroScience, 2025. DOI: 10.1007/s11357-025-01839-8. PMID: 40830310. - **Sun 2025.** _Effectiveness of multi-component exercise in individuals with type 2 diabetes: a systematic review and meta-analysis._ PeerJ, 2025. DOI: 10.7717/peerj.20146. PMID: 41287857. - **Wei 2025.** _Exercise interventions of ≥8 weeks improve body composition, physical function, metabolism, and inflammation in older adults with stage I sarcopenic obesity: a systematic review and meta-analysis._ Frontiers in Nutrition, 2025. DOI: 10.3389/fnut.2025.1575580. PMID: 40873450. - **CarrilloArango 2025.** _Acute systemic and energy metabolism responses to velocity‐based resistance training following an oral glucose load in individuals with excess body weight._ Experimental Physiology, 2025. DOI: 10.1113/EP093162. PMID: 41379629. - **Chen 2026.** _Lipid biomarkers for the prediction of type 2 diabetes risk, an umbrella review and updated meta-analyses of prospective observational studies._ Frontiers in Endocrinology, 2026. DOI: 10.3389/fendo.2026.1784917. PMID: 42181198. - **Jung 2024.** _Association between myosteatosis and impaired glucose metabolism: A deep learning whole‐body magnetic resonance imaging population phenotyping approach._ Journal of Cachexia, Sarcopenia and Muscle, 2024. DOI: 10.1002/jcsm.13527. PMID: 39009381. - **Gordon 2025.** _Associations of one-carbon metabolism, related B-vitamins and ApoE genotype with cognitive function in older adults: identification of a novel gene-nutrient interaction._ BMC Medicine, 2025. DOI: 10.1186/s12916-025-04276-8. PMID: 40717068. - **Song 2026.** _Effect of aerobic exercise of different intensity on articular cartilage metabolism in patients with knee osteoarthritis: A randomized controlled trial._ Medicine, 2026. DOI: 10.1097/MD.0000000000048913. PMID: 42216405. - **Kemna 2025.** _Acute effects of lactate infusion on metabolism, AD biomarkers, and cognition: The LEAN study._ Alzheimer's & Dementia, 2025. DOI: 10.1002/alz.70984. PMID: 41376120. - **Choi 2025.** _Associations of circulating c-reactive protein levels with central Alzheimer’s disease biomarkers._ The Journal of Prevention of Alzheimer's Disease, 2025. DOI: 10.1016/j.tjpad.2025.100368. PMID: 40967969. - **Andreo-Lopez 2025.** _Alkaline Phosphatase as a Potential Biomarker of Muscle Function: A Pilot Study in Patients with Hypophosphatasia._ International Journal of Molecular Sciences, 2025. DOI: 10.3390/ijms26136153. PMID: 40649938. - **Chen 2025.** _Leptin Aggravates Thoracic Aortic Dissection Through Impairment of Energy Metabolism in Nrip2 + Smooth Muscle Cells._ Advanced Science, 2025. DOI: 10.1002/advs.202502027. PMID: 40667784. - **Park 2025.** _Integrated effects of a 12-week intermittent combined exercise on cognitive function, physical performance, and neurophysiological biomarkers in older women._ Journal of Exercise Rehabilitation, 2025. DOI: 10.12965/jer.2550788.394. PMID: 41497243. - **Wang 2025.** _Effect of betaine on growth performance, methionine metabolism, and methyl transfer in broilers aged 1 to 21 days and fed a low-methionine diet._ The Journal of Poultry Science, 2025. DOI: 10.2141/jpsa.2025010. PMID: 40060329. - **Yu 2025.** _Effects of Proanthocyanidins on Growth Performance, Intestinal Inflammation and Barrier Function, and Bile Acid Metabolism-Related Genes in Weaned Piglets Challenged with Lipopolysaccharide._ Animals : an Open Access Journal from MDPI, 2025. DOI: 10.3390/ani15131826. PMID: 40646724. - **Lepine 2026.** _Increasing plant protein sources in the diet modulates gut microbiota and tryptophan metabolism in men at cardiometabolic risk._ Gut Microbes, 2026. DOI: 10.1080/19490976.2026.2677951. PMID: 42199008. - **Ma 2024.** _Association of serum iron metabolism with muscle mass and frailty in older adults: A cross-sectional study of community-dwelling older adults._ Medicine, 2024. DOI: 10.1097/MD.0000000000039348. PMID: 39151527. - **Wang 2025b.** _The effects of time-restricted eating combined with Tai Chi on glycolipid metabolism and endothelial function in postmenopausal women._ Journal of the International Society of Sports Nutrition, 2025. DOI: 10.1080/15502783.2025.2581148. PMID: 41255053. - **Trinh 2026.** _Case Report: Stage-by-stage fueling, glucose dynamics, and next-day metabolism and biomarker responses after baseline testing in an 18.5-hour Swedish classic tetrathlon._ Frontiers in Sports and Active Living, 2026. DOI: 10.3389/fspor.2026.1733702. PMID: 41868981. - **Yordanova 2026.** _GPIHBP1 as a Biomarker of Diabetic Polyneuropathy and Vascular Complications in Type 2 Diabetes Mellitus._ Biomolecules, 2026. DOI: 10.3390/biom16050707. PMID: 42194055. - **Kurhaluk 2024.** _Effects of a β-glucan-enriched diet on biomarkers of oxidative stress, energy metabolism and lysosomal function in muscle tissue of European grayling ( Thymallus L.)._ Journal of Veterinary Research, 2024. DOI: 10.2478/jvetres-2024-0064. PMID: 39776690. - **Mutoh 2025.** _Medium-Chain Triglyceride Dietary Supplements Reduce Glucose Metabolism of Gait-Related Skeletal Muscle in Older Adults: A Longitudinal 18 F-FDG PET/CT Analysis._ Nutrients, 2025. DOI: 10.3390/nu17101707. PMID: 40431447. - **Morvaridzadeh 2024.** _High-Density Lipoprotein Metabolism and Function in Cardiovascular Diseases: What about Aging and Diet Effects?._ Nutrients, 2024. DOI: 10.3390/nu16050653. PMID: 38474781. - **Chen 2025b.** _Identification of arachidonic acid metabolism-related diagnostic markers in heart failure based on bioinformatics analysis and machine learning._ Frontiers in Cardiovascular Medicine, 2025. DOI: 10.3389/fcvm.2025.1625064. PMID: 41472876. ### Background References *Canonical clinical thresholds cited in prose. Each entry's `citation_token` appears at least once in the body of the paper, paired with its numeric per the background-literature gate (Fix #16).* - **WHO 2000.** _World Health Organization. Obesity: Preventing and Managing the Global Epidemic. WHO Technical Report Series 894. 2000._ PMID: 11234459. - **Cruz-Jentoft 2019.** _Cruz-Jentoft AJ, Bahat G, Bauer J, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16-31._ DOI: 10.1093/ageing/afy169. PMID: 30312372. - **Tinetti 1988.** _Tinetti ME, Speechley M, Ginter SF. Risk factors for falls among elderly persons living in the community. N Engl J Med. 1988;319(26):1701-1707._ DOI: 10.1056/NEJM198812293192604. PMID: 3205267. - **Tancredi 2015.** _Tancredi M, Rosengren A, Svensson AM, et al. Excess mortality among persons with type 2 diabetes. N Engl J Med. 2015;373(18):1720-1732._ DOI: 10.1056/NEJMoa1504347. PMID: 26510021. - **Ioannidis 2005.** _Ioannidis JPA. Why most published research findings are false. PLoS Med. 2005;2(8):e124._ DOI: 10.1371/journal.pmed.0020124. PMID: 16060722.
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"title": "Research Synthesis: Metabolism Biomarker Effects \u2014 full paper"
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