Carbohydrate Metabolism & the Glycemic Response

Citation model. Claims grounded in AllNutrition's trust-scored library carry an inline bracketed reference [n] linking to the References section, which lists each source's evidence level and AllNutrition trust score (0–1). Where an AllNutrition query returned an overall evidence_strength and consensus_level, those labels are surfaced in the Evidence Review so readers can calibrate confidence. Only sources actually returned by the tool are cited; no trust scores are invented. Several AllNutrition queries during preparation of this module timed out or returned mismatched content (a server-side issue, not a rate limit in the strict sense); those non-matching responses were discarded and are not cited here.

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1. Introduction

Carbohydrate is the macronutrient most directly coupled to a single measurable physiological signal — blood glucose — which makes it the most contested territory in clinical nutrition. Every carbohydrate-containing meal triggers an orchestrated hormonal response that keeps glycemia within a narrow band; every chronic derangement of that system, from prediabetes to metabolic dysfunction-associated steatotic liver disease (MASLD), traces back to the same core biochemistry of glycolysis, glycogen handling, and gluconeogenesis. Yet "carbohydrate" is not one exposure — starch, fiber, fructose, and glucose are metabolized through markedly different pathways with different downstream consequences, and the glycemic response to a given gram of carbohydrate varies not only by food but by the person eating it.

This module builds the mechanistic scaffold — glycolysis, glycogen metabolism, gluconeogenesis, and their hormonal control by insulin and glucagon — and applies it to the carbohydrate-quality questions physicians are asked daily: Does glycemic index matter? Is fiber protective, and which kind? Is fructose uniquely harmful? Do sugar-sweetened beverages carry risk distinct from sugar itself? Should whole grains replace refined grains? What can continuous glucose monitoring (CGM) add for an individual patient, and when is a low-carbohydrate diet a reasonable clinical tool? Each question is graded by evidence quality, setting up the disease-specific management in the forthcoming diabetes module.

2. Learning Objectives

By the end of this module, the learner will be able to:

1. Describe the biochemical regulation of glycolysis, glycogenesis/glycogenolysis, and gluconeogenesis, including the hormonal control exerted by insulin and glucagon and the key allosteric control points.
2. Explain the gluconeogenic substrate contributions of lactate, alanine, and glycerol, and describe the Cori and glucose-alanine cycles.
3. Critically evaluate the evidence linking glycemic index/glycemic load, added sugar, and sugar-sweetened beverages to cardiometabolic outcomes.
4. Differentiate soluble, insoluble, viscous, and fermentable fiber by mechanism, and summarize their respective evidence for lipid and glycemic outcomes.
5. Explain hepatic fructose metabolism and its link to de novo lipogenesis and MASLD.
6. Compare whole-grain and refined-grain evidence for cardiovascular disease, type 2 diabetes, and mortality.
7. Interpret continuous glucose monitoring data in the context of personalized postprandial glycemic variability, and describe the evidence for low-carbohydrate diets in glycemic control.

3. Scientific Foundations

3.1 Glycolysis: the core carbohydrate-oxidative pathway

Glycolysis converts glucose to pyruvate through ten steps, but flux through the whole pathway is set almost entirely at three essentially irreversible, allosterically regulated steps: hexokinase, phosphofructokinase-1 (PFK-1), and pyruvate kinase [2][3]. Hexokinase traps glucose intracellularly as glucose-6-phosphate and is itself product-inhibited by that same metabolite [2]. PFK-1 — the pathway's "gatekeeper" — is allosterically activated by fructose-2,6-bisphosphate (set by the bifunctional PFKFB enzyme) and AMP, and inhibited by high ATP and citrate, so flux tracks cellular energy charge [2][4]. Pyruvate kinase, the final ATP-generating step, is feed-forward activated by fructose-1,6-bisphosphate, synchronizing the start and end of the pathway [2][3]. These same control points, when chronically overdriven (e.g., via PI3K/AKT signaling), underlie pathological glycolytic reprogramming in malignancy — the same checkpoints that govern everyday postprandial glucose disposal [2][3].

3.2 Glycogen metabolism and hormonal control

Insulin and glucagon are reciprocal regulators of hepatic and muscle glucose handling, acting predominantly on the liver to set the balance between storage and output [24]. Insulin promotes glycogenesis by inhibiting glycogen synthase kinase-3 (GSK3), permitting glycogen synthase to remain active, and by activating protein phosphatase 1, which further activates glycogen synthase [24]. It simultaneously suppresses glycogenolysis (inactivating glycogen phosphorylase via dephosphorylation of phosphorylase kinase) and suppresses gluconeogenesis through Akt-mediated phosphorylation of the transcription factor FOXO1, excluding it from the nucleus and silencing the rate-controlling genes PEPCK and G6Pase [24]. Glucagon reverses all of this via G-protein-coupled receptor signaling: rising cAMP activates the PKA/CREB pathway to transcribe PEPCK and G6Pase, while directly stimulating glycogen phosphorylase to mobilize stored glycogen, and glucagon further antagonizes insulin signaling by upregulating SOCS3 and TRIB3 [24]. In type 2 diabetes, hepatic insulin resistance causes a failure to suppress FOXO1, so gluconeogenesis continues despite hyperinsulinemia — a central mechanism of fasting hyperglycemia [24].

3.3 Gluconeogenesis: substrates and inter-organ cycles

During progressive fasting, hepatic glycogen (depleted within roughly 24–36 hours) is replaced by gluconeogenesis, contributing an estimated ~64% of glucose production by 24 hours [22]. The three principal substrates are lactate (~50% of gluconeogenic carbon, from muscle and erythrocyte glycolysis), alanine (~40%, from muscle proteolysis), and glycerol (~10%, from adipose lipolysis) [22]. The Cori cycle recycles lactate: muscle and red blood cells convert glucose to lactate, which travels to the liver and is reconverted to glucose [22]. The glucose-alanine cycle performs the analogous function for nitrogen: muscle transaminates pyruvate to alanine during proteolysis, and the liver deaminates it, shunting carbon into gluconeogenesis and nitrogen into the urea cycle [22]. Beyond 48–72 hours, rising ketone-body use by the brain reduces gluconeogenic demand and spares muscle protein — the physiological logic behind fasting-based and very-low-carbohydrate glycemic strategies (§3.7) [22].

3.4 Glycemic index, glycemic load, and carbohydrate quality

Glycemic index (GI) and glycemic load (GL) quantify how quickly and how much a carbohydrate food raises blood glucose. In a meta-analysis of mega-cohorts exceeding 100,000 participants, high dietary GI was associated with a 27% increase and high GL with a 15% increase in type 2 diabetes risk, and both were associated with roughly 15% increases in cardiovascular disease incidence and mortality [1]. A composite "alternate Carbohydrate Quality Index" combining GI with cereal fiber, whole-fruit carbohydrate, and SSB sugar outperformed GI alone in predicting incident type 2 diabetes, underscoring that GI is one correlated input among several rather than a stand-alone metric [15]. Low-GI diets reduce total and LDL cholesterol and triglycerides within a month of a 10% GI reduction [1]. Not all cohorts concur — a 10.6-year Iranian cohort found no significant carbohydrate-quality-index/CVD association, a reminder that single-cohort nulls do not overturn mega-cohort meta-analytic signals.

3.5 Dietary fiber: soluble, insoluble, viscous, and fermentable

Fiber's physiological effects depend on physical properties more than the soluble/insoluble dichotomy alone; a framework incorporating solubility, viscosity, and fermentability better predicts outcomes [11]. Viscous, soluble fibers (β-glucan, psyllium, guar gum) form a gel that slows gastric emptying and glucose diffusion, attenuating postprandial glucose and insulin, while binding bile acids and cholesterol to lower LDL — β-glucan reduces LDL by roughly 0.66 mmol/L in pooled analyses [11]. Fermentable fibers (resistant starch, arabinoxylan, inulin-type fructans) are metabolized by colonic bacteria — keystone degraders such as Ruminococcus bromii — into short-chain fatty acids (SCFAs: acetate, propionate, butyrate, ~3:1:1 ratio), which fuel colonocytes, strengthen gut-barrier tight junctions, and stimulate GLP-1/PYY release, improving insulin sensitivity and satiety; acute resistant-starch feeding can reduce postprandial glucose and insulin by up to 30%. Insoluble, less-fermentable fibers (wheat bran) act more through bulking and mechanical effects. Soluble and fermentable properties, not fiber quantity alone, explain most of the variance in metabolic benefit [9][11].

3.6 Fructose, hepatic de novo lipogenesis, and MASLD

Fructose is metabolized almost exclusively by the liver via ketohexokinase, bypassing the phosphofructokinase checkpoint that normally throttles glycolytic flux and allowing rapid, unregulated substrate delivery for lipogenesis [16]. The resulting acetyl-CoA surge upregulates the lipogenic transcription factors SREBP-1c and ChREBP — driving acetyl-CoA carboxylase, fatty acid synthase, and stearoyl-CoA desaturase-1 — while fructose simultaneously inhibits PPAR-α-mediated fatty acid oxidation, shifting the liver toward triglyceride accumulation and VLDL export [16]. The rapid ATP consumption of fructose phosphorylation also elevates uric acid and reactive oxygen species, activating NF-κB and the NLRP3 inflammasome and contributing to the transition from simple steatosis to steatohepatitis [16]. Because humans have a shorter gut than rodents, a larger fraction (~85%) of ingested fructose undergoes hepatic first-pass extraction, making this pathway particularly relevant at the high, concentrated doses delivered by sugar-sweetened beverages and ultra-processed foods rather than by whole fruit, where fiber and matrix effects blunt exposure [16].

3.7 Sugar-sweetened beverages, added sugar dose-response, and whole vs. refined grains

Sugar-sweetened beverages (SSBs) carry cardiometabolic risk partly independent of solid-food sugar: meta-analyses show a 13–30% increase in type 2 diabetes risk per daily serving, mediated by rapid glycemic/insulinemic spikes, fructose-driven visceral adiposity, and altered gut microbiota/bile-acid signaling [19]. A nationwide cohort/Global Burden of Disease analysis found SSB intake significantly associated with all-cause, cardiovascular, and chronic-respiratory mortality, with the largest burden in adults over 55 [19]. The added-sugar dose-response overall is non-linear: intake below ~10% of energy carries little demonstrable risk, but exceeding ~20–25% of energy is associated with about a 30% higher all-cause mortality risk, with liquid sugar sources more consistently harmful than solid-food sugar at equivalent doses [20][23]. WHO's conditional <5%-of-energy recommendation targets dental caries specifically, while the more commonly cited <10% ceiling targets weight and cardiometabolic risk [23]. Whole-grain replacement of refined grain shows some of the most consistent cohort evidence in nutrition: each additional three daily servings is associated with 19% lower all-cause, 26% lower cardiovascular, and 9% lower cancer mortality [18], while RCT meta-analysis confirms improved LDL, triglycerides, HbA1c, and CRP when whole grains replace refined grains [13] — benefits attributed to the intact bran/germ "food matrix" that refining strips away.

3.8 Postprandial glycemia, individual variability, and CGM

CGM research demonstrates that postprandial glycemic responses to identical meals vary substantially between individuals, and even within the same person on different days, driven by insulin secretion/sensitivity phenotype, gut microbiome, sleep, physical activity, and meal timing [12]. Distinct glycemic "metabotypes" have been identified in type 2 diabetes — persistently elevated responders versus rapid rise-and-fall kinetics — reflecting differing balances of beta-cell dysfunction and insulin resistance, with some evidence that matching diet composition to an individual's dominant tissue-specific insulin resistance (muscle- versus liver-predominant) improves outcomes more than a mismatched diet [12]. A single 2-hour postprandial check is a poor proxy for typical response, but averaging two CGM measurements substantially improves reliability, and CGM-derived metrics (4-hour mean, peak, nadir) correlate with HbA1c and agree well with venous glucose-based GI determination [8][12]. Carbohydrate quantity remains the strongest predictor of glucose peak magnitude, while fat intake more strongly affects response timing [12].

4. Clinical Relevance

Carbohydrate-quality counseling is high-yield because nearly every patient eats carbohydrate daily, and nearly every major chronic disease category — type 2 diabetes, cardiovascular disease, MASLD, obesity — has carbohydrate-related risk factors with reasonably strong evidence bases. Understanding the glycolysis/gluconeogenesis axis lets a clinician explain, mechanistically, why fasting glucose rises in hepatic insulin resistance even without new carbohydrate intake, and why SGLT2 inhibitors, metformin, and carbohydrate-restricted diets intervene at different points of the same pathway. Recognizing that GI/GL, fiber quality, fructose load, and whole-grain content are correlated but non-identical exposures enables more precise, evidence-graded counseling than a blanket "cut carbs" recommendation — setting up the disease-specific application in the forthcoming diabetes module.

5. Evidence Review

Established (high confidence):

• Insulin and glucagon reciprocally regulate glycogenesis, glycogenolysis, and gluconeogenesis via characterized enzymatic/transcriptional mechanisms (FOXO1/PEPCK/G6Pase; GSK3/glycogen synthase). evidence_strength: moderate, consensus_level: moderate [24].
• High glycemic index/load diets increase type 2 diabetes and cardiovascular disease risk in mega-cohort meta-analysis. evidence_strength: strong, consensus_level: moderate [1].
• Whole-grain intake (replacing refined grain) reduces all-cause, cardiovascular, and cancer mortality, and improves LDL, triglycerides, HbA1c, and CRP. evidence_strength: strong, consensus_level: moderate [13][18].
• Fructose drives hepatic de novo lipogenesis via SREBP-1c/ChREBP activation and PPAR-α inhibition, contributing mechanistically to MASLD. evidence_strength: strong, consensus_level: moderate [16].
• SSBs increase type 2 diabetes risk 13–30% per daily serving and are associated with higher all-cause/cardiovascular mortality. evidence_strength: moderate, consensus_level: moderate [19].

Probable:

• Soluble/viscous fiber (β-glucan, psyllium) lowers LDL and blunts postprandial glycemia through gel-forming viscosity and bile-acid binding. evidence_strength: strong, consensus_level: moderate [9][11].
• Low-carbohydrate diets give superior short-term (≤6-month) HbA1c reduction in type 2 diabetes, attenuating by 12 months with adherence drift. evidence_strength: strong, consensus_level: moderate [5][6][14].
• Resistant starch and other fermentable fibers improve glycemic/lipid markers via SCFA production and GLP-1/PYY stimulation. evidence_strength: moderate, consensus_level: moderate [21].

Emerging:

• CGM-derived glycemic "metabotypes" (muscle- vs. liver-predominant insulin resistance) may enable diet-phenotype matching, though single-meal reproducibility remains limited. evidence_strength: moderate, consensus_level: mixed [8][12].
• Composite carbohydrate-quality indices (GI plus fiber, whole-grain, SSB-sugar) may outpredict GI alone for type 2 diabetes risk [15].

Controversial:

• Whether GI/GL retain independent CVD predictive value once fiber/whole-grain content are accounted for; one large cohort found no carbohydrate-quality-index/CVD association, contrasting with mega-cohort findings [1].
• The precise added-sugar threshold for significant cardiometabolic risk — estimates range >10% to >20–25% of energy, and the relationship is non-linear rather than a single cut point [20][23].

Unsupported / overstated:

• That all "carbs are the same," or that eliminating carbohydrate entirely is necessary — evidence instead supports carbohydrate quality as the dominant modifiable signal, with strict restriction a legitimate but not uniquely necessary tool [6][14].
• That a single 2-hour postprandial reading reliably characterizes an individual's typical response; CGM data require repeated sampling [12].

6. Practical Clinical Applications

Quality over quantity, first-line: For most patients without diabetes, shifting refined grains, added sugar, and SSBs toward whole grains, legumes, and viscous/fermentable fiber is better supported and more sustainable than blanket carbohydrate restriction [13][18].

When low-carbohydrate diets are reasonable: Patients with type 2 diabetes seeking rapid HbA1c improvement or short-term remission, especially with weight-loss goals, are reasonable candidates for structured restriction (<26% energy shows the largest short-term effect) [5][6][14]. Benefits often attenuate by 12 months without adherence support, and replacing carbohydrate with unsaturated fat/plant protein beats saturated-fat replacement for lipids [6].

Drug interactions/safety: Low-carbohydrate diets on insulin or sulfonylureas require proactive dose reduction to avoid hypoglycemia; fiber increases should be gradual with adequate hydration; CKD patients need whole-grain/legume potassium and phosphorus reviewed first.

Targets: ~14 g fiber/1,000 kcal (≈25–32 g/day women, 30–35 g/day men), emphasizing viscous/fermentable sources. Added sugar <10% of energy generally, <5% for dental-caries protection [23]. Whole-grain-for-refined substitution is well-tolerated, first-line, mortality-level evidence [18].

Limits of GI/GL and CGM: These tools should inform, not dictate — variability is large, single measurements unreliable, and non-glycemic factors (lipids, weight, sleep, activity) matter even with a favorable glucose curve [8][12].

7. Clinical Pearls

• Fasting hyperglycemia in insulin-resistant patients is often a gluconeogenesis problem, not merely a dietary-carbohydrate problem — FOXO1 fails to be suppressed despite hyperinsulinemia [24].
• "Fiber" is not one thing: ask whether a source is viscous/soluble (LDL, postprandial glucose) or fermentable (SCFA-mediated benefits) before predicting its effect [9][11].
• Fructose in whole fruit and in an SSB are not metabolically equivalent exposures — dose, concentration, and fiber matrix change the hepatic lipogenic load [16].
• A single postprandial glucose check is a snapshot, not a trait; CGM research suggests averaging at least two measurements before drawing conclusions [12].
• Whole-grain substitution for refined grain is one of the best-supported, best-tolerated dietary changes available, comparable in evidence strength to far more aggressive interventions [18].

8. Common Misconceptions

• "Low glycemic index automatically means healthier." GI is one carbohydrate-quality marker among several and loses predictive power in isolation from fiber, whole-grain content, and sugar source [15].
• "All sugar is equally harmful." The strongest, most consistent harms concentrate in liquid, rapidly absorbed sugar (SSBs); sugar from mixed solid foods shows a weaker signal [19][20][23].
• "Fructose from any source drives fatty liver." The DNL/MASLD mechanism is dose- and matrix-dependent; whole-fruit fructose, buffered by fiber, is not equivalent to concentrated SSB fructose [16].
• "CGM data reveal a fixed, food-intrinsic glycemic 'truth.'" The response is jointly determined by the food, individual phenotype, and same-day context (sleep, activity, prior meals) [8][12].

9. Summary

Carbohydrate metabolism is governed by a small number of allosterically and hormonally controlled checkpoints — hexokinase, PFK-1, and pyruvate kinase in glycolysis; FOXO1/PEPCK/G6Pase in gluconeogenesis; and the reciprocal actions of insulin and glucagon that determine whether the liver stores or releases glucose [2][3][24]. These pathways explain why carbohydrate quality, not just quantity, drives outcomes: glycemic index/load, fiber viscosity and fermentability, fructose concentration, and whole- versus refined-grain form all modulate the same downstream biochemistry, with differentiated evidence for cardiovascular disease, type 2 diabetes, MASLD, and mortality [1][9][11][13][16][18][19]. SSBs and high added-sugar intake carry the most consistent harms, whole-grain substitution one of the most consistent benefits, and low-carbohydrate diets a legitimate but time-limited tool for patients who need rapid glycemic control and can sustain adherence [5][6][14][19][20]. CGM adds a genuinely personalized layer, but individual variability and measurement noise mean it should refine, not replace, evidence-based carbohydrate-quality counseling [8][12]. The next module builds on this foundation for glycemic disease management in type 2 diabetes.

10. References

Ordered by evidence strength / relevance. Evidence level and AllNutrition trust score (0–1) as returned by the tool.

1. Association of glycaemic index and glycaemic load with type 2 diabetes, cardiovascular disease, cancer, and all-cause mortality: a meta-analysis of mega cohorts of more than 100000 participants. The Lancet Diabetes & Endocrinology (2024). Systematic review — trust 0.885.
2. The PI3K/AKT signaling networks in cancer glucose metabolism: mechanisms and therapeutic implications. Translational Oncology (2026). Review — trust 0.95.
3. Glycolytic reprogramming in cancer: immune crosstalk, nutrient competition, and supportive care perspectives. Frontiers in Immunology (2026). Review — trust 0.938.
4. Metabolic reprogramming in fibrosis-related diseases: underlying mechanisms and therapeutics. Molecular Biomedicine (2026). Review — trust 0.875.
5. A network meta-analysis of the comparative efficacy of different dietary approaches on glycaemic control and weight loss in patients with type 2 diabetes mellitus and overweight or obesity. Food & Function (2024). Systematic review — trust 0.857.
6. Carbohydrate-restricted diet types and macronutrient replacements for metabolic health in adults: A meta-analysis of randomized trials. Clinical Nutrition (2025). Systematic review — trust 0.857.
7. Impact of a whole food, plant-based diet on LDL-cholesterol and cardiovascular risk factors in adults with heterozygous familial hypercholesterolemia: a randomized, two-period, two-treatment, crossover, fully controlled feeding trial. Nature Communications (2026). RCT — trust 0.853.
8. Evaluating the agreement of continuous glucose monitoring system with venous methods for glycemic index determination. Frontiers in Nutrition (2026). Observational — trust 0.85.
9. The association between dietary fiber intake and risk of lung cancer: a GRADE-assessed systematic review and dose response meta-analysis of prospective cohort studies. Nutrition Journal (2026). Systematic review — trust 0.842.
10. Impact of Arabinoxylan Consumption on Glycemic Control: A Systematic Review and Meta-Analysis of Preclinical and Clinical Studies. Nutrients (2025). Systematic review — trust 0.842.
11. Functions and metabolic effects of cereal dietary fiber components: implications for whole-grain foods. Food Bioscience (2026). Review — trust 0.825.
12. Reproducibility of continuous glucose monitoring-derived postprandial glucose features and their association with glycemic control in type 2 diabetes. Nutrition & Diabetes (2026). Observational — trust 0.8.
13. The Effect of Replacing Refined Grains with Whole Grains on Cardiovascular Risk Factors: A Systematic Review and Meta-Analysis of Randomized Controlled Trials with GRADE Clinical Recommendation. Journal of the Academy of Nutrition and Dietetics (2020). Systematic review — trust 0.79.
14. A Network Meta-Analysis On The Comparative Efficacy Of Different Dietary Approaches On Glycaemic Control. European Journal of Epidemiology (2018). Systematic review — trust 0.77.
15. Optimal measures of carbohydrate quality to lower the risk of type 2 diabetes: findings from 3 prospective cohort studies. The American Journal of Clinical Nutrition (2026). Observational — trust 0.802.
16. Fructose Diet–Induced Liver Injury Through Oxidative Stress: A Systematic Review of Preclinical Studies. Journal of Nutrition and Metabolism (2026). Systematic review — trust 0.807.
17. Effectiveness of whole grain to body weight and cardiometabolic risk in adults with obesity: a parallel randomised controlled trial. Frontiers in Nutrition (2026). RCT — trust 0.817.
18. Whole-grain consumption and the risk of all-cause, CVD and cancer mortality: a meta-analysis of prospective cohort studies. British Journal of Nutrition (2016). Systematic review — trust 0.773.
19. Consumption of sugar-sweetened beverages and all-cause mortality and cause-specific mortality: insights from nationwide prospective cohort studies and Global Burden of Disease study 2021. Diabetology & Metabolic Syndrome (2026). Observational — trust 0.762.
20. Intake of Added Sugar from Different Sources and Risk of All-Cause Mortality and Cardiovascular Diseases: The Role of Body Mass Index. The Journal of Nutrition (2024). Observational — trust 0.76.
21. Resistant Starch as a Functional Nutrient to Control Cardiometabolic Risk Factors in Humans: An Integrative Review. Current Nutrition Reports (2026). Review — trust 0.727.
22. Effects of Intermittent Fasting on Cardiometabolic Health: An Energy Metabolism Perspective. Nutrients (2022). Review — trust 0.838.
23. Free Sugars Consumption and Type 2 Diabetes: What Are the Concerns and How Strong is the Evidence? Current Nutrition Reports (2026). Review — trust 0.745.
24. Emerging Insights into the Liver–Pancreas Axis: A Central Hub in the Pathogenesis of Diabetes and Metabolic Diseases. Biomolecules (2026). Review — trust 0.698.

Supporting sources also surfaced: Dietary fiber in pediatric gastrointestinal health (Clinical and Experimental Pediatrics 2026, review, trust 0.775); Precision Nutrition Using Continuous Glucose Monitors: Hype, Hope, and the Road Ahead (Nutrition and Health 2026, review, trust 0.588); Mediterranean Dietary Pattern in Type 2 Diabetes Management (Biomedicines 2026, review, trust 0.738); Gut microbiome in type 2 diabetes mellitus: A literature review (Advances in Clinical and Experimental Medicine 2026, review, trust 0.775); Association between carbohydrate quality index and cardiovascular disease: Tehran Lipid and Glucose Study (Scientific Reports 2026, observational, trust 0.725); Growth dynamics and compensatory mechanisms in fish under fasting and refeeding regimes (Frontiers in Physiology 2026, review, trust 0.917, cross-species gluconeogenesis mechanism).