Search Results (895)

Background and Objectives: The “friend or foe” debate in chronic hepatitis B (CHB) with steatotic liver disease (SLD) partly arises from treating hepatic fat, metabolic burden, and steatohepatitis as one exposure and interpreting different outcomes together. Materials and Methods: This narrative review applies an exposure–stage–context framework to literature identified in PubMed and Web of Science through 21 September 2026. We synthesized outcome evidence from 119 reports, including 14 detailed examples, using within-study comparisons of exposures, outcomes, and patient subgroups. Results: Within individual cohorts, associations with the same outcome could diverge: steatosis or an SLD diagnosis was associated with lower hepatocellular carcinoma (HCC) or mortality risk, whereas greater metabolic burden was associated with higher risk. Favorable antigen-related associations also coexisted with adverse fibrosis trajectories. Steatohepatitis was associated with more severe fibrosis and liver-related events, while metabolic abnormalities and prolonged glycemic exposure were associated with adverse hepatic outcomes. Studies of metabolic dysfunction-associated steatotic liver disease (MASLD) reported greater cardiovascular risk, and a study of hepatitis B virus-positive patients with nonalcoholic fatty liver disease (NAFLD) reported more prevalent kidney disease. Baseline fibrosis, patient selection, and antiviral treatment shape these associations; lower relative risks can coexist with a high absolute event burden. Conclusions: Current hepatic fat, cumulative metabolic exposure, and established injury therefore carry different prognostic meanings. Their separate assessment helps explain part of the apparent paradox, while adverse steatosis findings and discrepancies in similar settings remain unresolved. The evidence is predominantly observational. Full article

Objective: The objective of this study is to evaluate county-specific changes in standardized management and glycemic control associated with an integrated county–township–village care model among patients with type 2 diabetes mellitus (T2DM) in resource-constrained areas of China. Methods: Three intervention counties that implemented an integrated county–township–village care model in 2019 were included. County-level quarterly data from 2017 to 2022 were extracted from electronic health record systems. Two outcome measures were assessed: the standardized management rate and the glycemic control rate among patients with T2DM. Synthetic controls were constructed from non-intervention counties within the same prefecture-level city. Sensitivity analyses excluding the highest-weight donor were conducted. Results: The synthetic controls approximated pre-intervention characteristics and outcome trajectories, although fit varied across counties and outcomes. Following implementation, mean standardized management rates exceeded their synthetic counterparts by 4.57, 3.96, and 4.35 percentage points in Counties Q, Y, and F, respectively. Placebo tests provided suggestive evidence for Counties Q and Y (p = 0.100 and p = 0.111) but limited evidence for County F (p = 0.750). Mean glycemic control rates exceeded their synthetic counterparts by 4.61 and 3.81 percentage points in Counties Q and F, respectively, compared with 0.83 percentage points in County Y. Estimated differences remained positive after excluding the highest-weight donor, although their magnitudes were sensitive to donor selection in some models. Conclusions: The integrated county–township–village care model was associated with improvements in selected T2DM management outcomes, with patterns varying across counties. Our findings suggest potential value in strengthening collaboration between county hospitals and primary health care institutions in comparable resource-constrained settings. Full article

Background: Artificial intelligence (AI) is increasingly being integrated into insulin management through decision-support systems, adaptive bolus calculators, conversational platforms, and automated insulin delivery (AID) technologies. However, the clinical effectiveness and safety of AI-assisted insulin management remain uncertain. Objective: To systematically evaluate evidence from randomized controlled trials (RCTs) investigating AI-assisted insulin management systems in individuals with type 1 or type 2 diabetes. Methods: A systematic literature review was conducted following PRISMA guidelines. PubMed/MEDLINE, Embase, and Cochrane CENTRAL were searched for RCTs evaluating AI-enabled insulin management interventions in insulin-treated individuals with diabetes. Eligible studies compared AI-based systems with standard care, clinician-guided insulin titration, conventional bolus calculators, or other AID algorithms. Outcomes included glycemic control, insulin titration, safety, and implementation-related measures. Owing to substantial heterogeneity, findings were synthesized narratively. Results: We included seven RCTs published between 2020 and 2025. Interventions comprised clinical decision-support systems, adaptive bolus calculators, conversational AI platforms, neural-network-based artificial pancreas algorithms, and exercise-aware AID systems. AI-assisted interventions consistently demonstrated favorable safety profiles, with no increase in severe hypoglycemia, diabetic ketoacidosis, or serious adverse events. Some systems, particularly fully automated closed-loop platforms and conversational AI-guided insulin titration, showed improvements in time in range, glucose control, adherence, and insulin optimization. User acceptance and adherence emerged as important determinants of effectiveness. Conclusions: Current randomized evidence suggests that AI-assisted insulin management systems are safe, feasible, and capable of achieving glycemic outcomes comparable to conventional care. Although certain technologies demonstrate promising clinical benefits, the evidence base remains limited by small sample sizes, short follow-up durations, and heterogeneity across interventions. Larger, long-term randomized trials are needed to establish comparative effectiveness, optimize human–AI interaction, and support broader clinical implementation. Full article

Background: Accurate scoring is essential when patient-reported self-management instruments are related to biochemical outcomes. The principal contribution of this study was to reconstruct and audit Diabetes Self-Management Questionnaire (DSMQ) scores from item-level data before reassessing their cross-sectional association with glycemic control. Methods: We performed a cross-sectional secondary analysis of a clinical database of adults with type 2 diabetes. One non-patient header row was removed. Because 12 observation-sheet identifiers occurred twice and visit dates were unavailable, all 24 records carrying repeated identifiers were excluded from the prespecified primary analysis, leaving 238 records. Negatively keyed DSMQ items were reverse-scored, and total and subscale scores were transformed to a 0–10 scale according to the original algorithm. Associations with HbA1c were assessed using Spearman correlation, exploratory ROC analysis, and multivariable linear regression with HC3 robust standard errors. Results: HbA1c was available for 237 records; mean age was 64.18 years (SD 11.14), 56.1% of records with valid sex coding were female, and mean HbA1c was 7.81% (SD 1.94). The corrected DSMQ total score was 5.19 (SD 2.36). DSMQ total score correlated inversely with HbA1c (ρ = −0.467, bootstrap 95% CI −0.572 to −0.350; p < 0.001). In the adjusted model (n = 236), each one-point higher DSMQ total score was associated with a 0.254 percentage-point lower HbA1c (regression coefficient = −0.254, 95% CI −0.344 to −0.163; p < 0.001). Sensitivity analyses using all records or first/last repeated-record rules produced similar estimates. Conclusions: Correctly scored DSMQ results showed a moderate, independent cross-sectional association with HbA1c. The corrected analysis did not demonstrate excellent discrimination, and the cross-sectional data cannot support causal or predictive claims. Prospective studies with verified unique participants and clearly documented data provenance are needed. Full article

Background/Objectives: Patients with type 2 diabetes face heightened risks of lower respiratory tract infections, but whether distinct glucose-lowering drug targets differentially alter pulmonary susceptibility remains unclear. We investigated how genetically proxied perturbations of major antidiabetic targets relate to respiratory infection and sepsis risks. Methods: Using two-sample drug-target Mendelian randomization, we examined genetic instruments proxying six antidiabetic pathways: insulin (INSR), sulfonylureas (KCNJ11/ABCC8), thiazolidinediones (PPARG), GLP-1 receptor agonists (GLP1R), SGLT2 inhibitors (SLC5A2), and metformin (GPD1, GPD2, PRKAG2). Associations were calibrated to standardized glycemic decrements and tested across 13 respiratory infection and sepsis GWAS outcomes. Analyses incorporated functional-variant comparisons, a type 2 diabetes positive control, and linkage disequilibrium adjustment. Results: Genetically proxied glucose lowering through PPARG showed consistent nominal associations with increased respiratory infection risk. Per 0.1 mmol/L lower glucose, the primary proxy and Pro12Ala functional variant were associated with higher odds of influenza and pneumonia (odds ratio [OR] 1.53, 95% CI 1.16–2.02, p = 0.003; and OR 1.53, 95% CI 1.13–2.06, p = 0.006) and other acute lower respiratory infections (OR 1.78, 95% CI 1.14–2.77, p = 0.011; and OR 1.87, 95% CI 1.16–3.01, p = 0.010). PPARG primary and functional proxies agreed in direction for 10/13 outcomes, whereas potassium-channel proxies agreed for only 3/13. Other targets showed distinct, heterogeneous patterns. Crucially, all signals were nominal and none survived false discovery rate correction (q ≥ 0.05). Conclusions: Genetically proxied glucose-lowering pathways exhibit divergent associations with respiratory infection susceptibility. While findings do not support class-wide causal risks, the repeated PPARG pattern highlights target-specific pulmonary immune mechanisms warranting functional and clinical investigation. Full article

The renewed interest in indigenous African foods reflects a shift towards traditional, nutrient-dense alternatives to address the burden of non-communicable diseases and micronutrient deficiencies. This review evaluates the evidence for proposed health benefits of baobab (Adansonia digitata L.) fruit pulp (BFP) across four domains: gut homeostasis, immune modulation, glycemic control, and iron bioavailability. The evidence base is predominantly preclinical. Tier 3 (in vitro) and Tier 2 (animal) studies suggest that BFP fibers (low-methoxylated homogalacturonan, xylogalacturonan, and possibly inulin and fructooligosaccharides) may exert prebiotic-like effects by selectively stimulating Bifidobacteriaceae and Lactobacilli, while BFP polyphenols and organic acids have been associated with enzyme inhibition and enhanced iron bioaccessibility, respectively. The methodological quality of these studies was not assessed. However, human evidence is scarce. Only six human intervention studies were identified, limited to glycemic response in healthy normoglycemic adults and one iron status trial in schoolchildren, which showed increased hemoglobin but no significant improvement in ferritin or soluble transferrin receptor. No human studies have examined gut microbiota modulation, immune outcomes, or effects in diabetic or pre-diabetic populations. Consequently, clinical efficacy has not been established, and BFP cannot currently be characterized as having confirmed prebiotic or therapeutic properties. The current evidence supports potential prebiotic and enzyme-inhibitory activity in preclinical models only. Evidence-based dietary recommendations require high-quality human intervention trials with clinically meaningful endpoints, standardization of BFP preparations, and systematic investigation of real-world dietary contexts. Future research should address these gaps to advance the evidence base for BFP. Practical barriers to translation, including sensory acceptance, product adulteration, and sustainable sourcing, are briefly considered. Full article

Objective: To investigate the association between key components of prenatal nutrition education interventions and the prevention of GDM in pregnant women. Methods: We systematically searched PubMed, Web of Science, Embase, and the Cochrane Central Register of Controlled Trials from database inception to 18 January 2026, using search terms including “gestational diabetes mellitus,” “glycemic control,” “pregnancy,” and “nutrition interventions”; only English-language publications were eligible. Eligible studies were randomized controlled trials (RCTs) assessing prenatal nutrition education interventions and reporting gestational diabetes mellitus (GDM) incidence. Of the initial 4961 retrieved records, 29 RCTs fulfilled the selection criteria. In accordance with PRISMA guidelines, two reviewers independently performed data extraction and risk-of-bias assessment using the Cochrane RoB 2.0 tool. Given expected clinical heterogeneity, pooled risk ratios (RRs) were synthesized via a random-effects model. The primary outcome was GDM incidence, expressed as a pooled RR comparing nutrition education intervention groups with control groups. Results: A total of 29 RCTs comprising 17,937 pregnant women were included. The pooled analysis showed that prenatal nutrition education interventions were associated with a statistically significant reduction in GDM risk (pooled RR, 0.88 [95% CI, 0.79–0.98]; p = 0.02). In absolute terms, the GDM incidence was 16.01% in the intervention group vs. 17.06% in the control group. Moderate between-study heterogeneity was observed (I² = 51.1%; p for heterogeneity < 0.001), largely driven by variations in dietary protocols and intervention fidelity. Conclusions: In this meta-analysis of 29 RCTs, prenatal nutrition education was associated with a significantly lower GDM risk. Interventions grounded in nutritional theory, delivered in hospital settings, and achieving high fidelity were associated with the largest reductions in risk; delivery by healthcare professionals, high individualization, and balanced dietary content showed favorable but statistically nonsignificant trends. These findings support the systematic adoption of these core components in routine antenatal care to mitigate the GDM burden. Full article

Objective: Obesity and type 2 diabetes mellitus frequently coexist and require therapeutic strategies capable of addressing both excess adiposity and cardiometabolic risk. However, real-world evidence on whether improvements in cardiometabolic parameters are accompanied by clinically meaningful weight loss remains limited, particularly in public healthcare settings in the Brazilian Amazon. This study evaluated longitudinal changes in body weight and cardiometabolic parameters among adults with obesity receiving routine outpatient endocrinology care within the Brazilian Unified Health System and investigated the relationship between weight change, glycemic response, and factors associated with therapeutic target achievement. As a complementary metabolic analysis, longitudinal changes in the triglyceride–glucose (TyG) index, as a surrogate marker of insulin resistance, were also evaluated. Methods: This retrospective longitudinal observational study included 90 adults with obesity receiving routine outpatient endocrinology care within the Brazilian Unified Health System in Marabá, Pará, Brazil. Participants had at least six months of follow-up, with a mean follow-up duration of 14.3 ± 4.0 months. Changes in anthropometric, glycemic, blood pressure, and lipid parameters were evaluated between baseline and follow-up. The TyG index was calculated from fasting plasma glucose and triglyceride concentrations, with longitudinal TyG analysis restricted to participants with paired measurements available at baseline and follow-up. Standardized within-participant effect sizes were estimated using Cohen’s dz with bootstrap 95% confidence intervals (CIs). Spearman correlations were used to examine associations between percentage weight change and cardiometabolic changes. Multivariable logistic regression models evaluated factors associated with achieving HbA1c < 7.0% among participants with type 2 diabetes mellitus and ≥5% weight loss in the overall cohort. Results: Body weight changed minimally during follow-up (mean Δ = −0.47 kg; dz = −0.072; 95% CI −0.306 to 0.126), whereas HbA1c decreased by 1.00 percentage point (dz = −0.441; 95% CI −0.751 to −0.219). Small reductions were also observed in fasting plasma glucose (Δ = −31.53 mg/dL), LDL cholesterol (Δ = −15.79 mg/dL), and triglycerides (Δ = −35.30 mg/dL). Among 51 participants with complete paired fasting plasma glucose and triglyceride measurements, mean TyG decreased from 9.68 ± 0.85 to 9.29 ± 0.79 (mean Δ = −0.39; 95% CI −0.58 to −0.20; p < 0.001), with a moderate standardized within-participant effect (dz = −0.569; bootstrap 95% CI −0.881 to −0.301). Only 21/90 participants (23.3%) achieved ≥5% weight loss, while 44/90 (48.9%) gained weight. Among participants with paired HbA1c measurements, the proportion with HbA1c ≥7.0% decreased from 72.9% to 52.9%. Percentage weight change was not significantly correlated with changes in HbA1c (rs = −0.018; p = 0.882), fasting plasma glucose, or lipid parameters, nor with change in TyG (rs = −0.041; p = 0.776). Self-reported medication adherence was associated with a greater median reduction in HbA1c (−1.55 vs. 0.00 percentage points; p = 0.003) and higher adjusted odds of achieving HbA1c < 7.0% (OR = 3.58; 95% CI 1.08–11.86; p = 0.037) but was not associated with weight-loss response. No evaluated baseline characteristic was significantly associated with achieving ≥5% weight loss. Conclusions: In adults with obesity receiving routine outpatient endocrinology care within the Brazilian Unified Health System in the Brazilian Amazon, longitudinal follow-up was accompanied by modest improvements in glycemic and selected lipid parameters but minimal average weight reduction. The TyG index also decreased significantly among participants with paired measurements, consistent with improvement in this surrogate marker of insulin resistance; however, this finding should not be interpreted as direct evidence of improved insulin sensitivity or reduced cardiovascular risk. Clinically meaningful weight loss was achieved by fewer than one quarter of participants, and nearly half gained weight. Medication adherence was associated with better glycemic control but not with weight loss. These findings indicate that improvements in conventional and surrogate metabolic markers were not consistently accompanied by meaningful reductions in body weight and support the incorporation of weight-specific outcomes and comprehensive obesity-directed strategies into chronic disease care. Full article

Pumpkin (Cucurbita spp.) processing generates peels, seeds, seed coats, pomace, and press cakes containing carotenoids, phenolics, proteins, unsaturated lipids, tocopherols, phytosterols, polysaccharides, and dietary fiber. This critical narrative review integrates composition and analytical characterization across anatomical fractions with extraction technologies, processing effects, biological evidence, and application readiness. Conventional extraction, pressing, supercritical carbon dioxide, deep eutectic solvents, enzyme-assisted extraction, ultrasound, microwaves, pulsed electric fields, and high-pressure homogenization differ in selectivity, recovery, and scalability. The reviewed evidence does not establish the environmental superiority of green extraction technologies without full process-level assessment. Processing can improve extractability or simulated bioaccessibility but also cause degradation or losses; concentration following water removal does not establish true retention. Experimental studies support potential antioxidant, anti-inflammatory, glycemia-related, antimicrobial, and antiproliferative activities, but most evidence remains chemical, cellular, or animal-based. Human evidence is preparation-specific and most developed for lower urinary tract symptoms; controlled evidence for glycemic and other systemic outcomes remains limited or inconsistent. Near-term opportunities include food ingredients, oils, protein fractions, pigment delivery, and selected packaging materials. Translation requires authenticated materials, validated analytical fingerprints, standardized preparations, safety and stability testing, adequately powered clinical trials for health-related claims, and mass, energy, economic, and life-cycle assessments. Full article

Cardiometabolic risk changes as metabolic state, vascular injury, behavior and treatment evolve. Multi-omics assays characterize the underlying molecular state, whereas wearable sensors and continuous glucose monitoring capture physiological responses during daily life. This review asks whether combining these measurements improves a defined clinical decision beyond established clinical information in type 2 diabetes, atherosclerotic cardiovascular disease and heart failure. We distinguish biological association, prediction and clinical utility, and define dynamic risk prediction as repeated estimation of future event probability over a specified horizon using only information available at each prediction time. Large cohorts link proteins and metabolites with future disease, and intensive studies connect molecular variation with activity, nutrition and glycemic responses. However, evidence for joint molecular–digital integration remains predominantly observational. Trials of glucose monitoring and structured telemanagement show that monitoring can improve outcomes when it is embedded in an effective care pathway, but they do not establish the incremental value of multi-omics. We therefore organize the evidence around three requirements: temporal alignment of stable genomic information, intermittent molecular assays and dense digital trajectories; validation against a strong clinical comparator; and prospective assessment of patient outcomes, cost and burden. Emerging sensors, dynamical network biomarkers and digital twins may eventually extend this framework, but they remain experimental or conceptual for integrated cardiometabolic event prediction. Full article

Prebiotic supplementation has emerged as a promising strategy to ameliorate metabolic disorders through beneficial reshaping of the gut microbiota. Accumulating evidence suggests that fungi and their polysaccharides (e.g., those from Auricularia auricula-judae, Boletus edulis, Hirsutella sinensis, Isaria cicadae, Ramaria botrytoides, and Wolfiporia cocos) possess considerable potential in this context. The present review summarizes studies providing data relevant to the potential involvement of the gut microbiota in mediating the metabolic benefits of fungal interventions. Observed outcomes, potentially linked to the gut microbiota, included reductions in body, visceral fat, and liver weights, improved lipid and glycemic profiles, enhanced insulin sensitivity, and decreased circulating lipopolysaccharide, leptin, and proinflammatory cytokines (TNF-α, IL-1β, IL-6). Upregulation of tight junction proteins in the colon implied strengthened gut barrier function. Histological analyses revealed smaller adipocytes and attenuation of hepatic steatosis. Additional effects included stimulation of white adipose tissue browning and enhanced hepatic thermogenesis. Alterations in gut microbiota composition were diverse; however, a reduction in the Firmicutes/Bacteroidetes ratio was commonly reported. Furthermore, oral administration of bacterial species enriched by fungal interventions, such as Papillibacter cinnamivorans, Parabacteroides goldsteinii, Bacteroides intestinalis, Lactobacillus johnsonii, and Enterococcus casseliflavus, reproduced the metabolic improvements, supporting their possible mediating role. Collectively, current evidence indicates that fungi and their polysaccharides may exert metabolic benefits, at least in part, through gut microbiota modulation; however, further investigation is needed to determine the extent to which the gut microbiota contributes causally to these benefits. Full article

Background: Doctoral training involves prolonged performance demands, uncertainty, supervisory dependence, and career pressure, yet objective biochemical correlates of academic stress remain incompletely characterized. This study examined academic stress in relation to glycemic, neuroendocrine, inflammatory, and thyroid-related markers, alongside psychological symptoms and sleep quality, in doctoral research scholars. Methods: This cross-sectional study included 203 doctoral research scholars (123 female, 80 male; mean age 27.2 years). Academic stress was assessed using a 34-item doctoral-adapted Academic Stress Scale (AST). Glycated hemoglobin (HbA1c), evening cortisol, C-reactive protein (CRP), and thyroid-stimulating hormone (TSH) were measured as biochemical outcomes. Depression, anxiety, and stress symptoms were assessed using the 21-item Depression Anxiety Stress Scales (DASS-21), and sleep quality using the Pittsburgh Sleep Quality Index (PSQI). Primary associations were examined using linear regression with heteroscedasticity-consistent type 3 (HC3) robust standard errors, adjusted for age, gender, body mass index, and lifestyle activity, with false-discovery-rate (FDR) correction. Results: Mean AST was 109.5 (standard deviation 21.0). Above-normal DASS-21 scores were observed for depression in 64.5%, anxiety in 86.7%, and stress in 49.3%, while 79.3% had poor sleep quality. Higher AST was associated with all four biochemical markers. Per 10-point increase in AST, HbA1c was 0.225 percentage points higher (95% confidence interval 0.158–0.291), evening cortisol 0.502 µg/dL higher (0.299–0.706), CRP 13.9% higher (8.4–19.7%), and TSH 0.125 µIU/mL higher (0.049–0.200); all FDR q ≤ 0.0013. Depression and anxiety severity distributions differed by gender, whereas stress did not. Exploratory analyses showed positive correlations between DASS-21 symptoms and all four biomarkers (Spearman ρ = 0.22–0.58; all FDR q < 0.01). Conclusions: Higher academic stress was associated with variation across glycemic, neuroendocrine, inflammatory, and thyroid-related markers in doctoral scholars, alongside substantial psychological symptom and sleep burden. The cross-sectional design precludes conclusions regarding temporal direction or causality and supports the need for longitudinal research on doctoral health and well-being. Full article

Background: Baseline HbA1c is expected to dominate prediction of subsequent HbA1c status; therefore, the clinically relevant question is whether additional routinely available variables provide reproducible incremental value. Methods: This retrospective longitudinal study used 809 records from adults with type 2 diabetes receiving routine outpatient care. Six-month HbA1c was available for 808 participants. The primary outcome was six-month glycemic status (HbA1c < 7.0%). An HbA1c-only benchmark and three fixed blockwise logistic models were compared in the same complete-case cohort (n = 806). Internal validation used 1000 bootstrap resamples and reported optimism-corrected AUC, Brier score, calibration intercept, and calibration slope. Correlations, variance inflation factors (VIFs), nonlinear effects, decision-curve analysis, and a sensitivity analysis restricted to baseline HbA1c ≥ 7.0% were evaluated. Results: At baseline, 215 participants had HbA1c < 7.0%; 179 maintained this status, 206 newly reached <7.0%, 36 moved above the threshold, and 387 remained ≥7.0%. In complete cases, the optimism-corrected AUC was 0.868 (95% CI 0.844–0.892) for HbA1c alone and 0.870 (95% CI 0.848–0.893) for the full model. The corrected AUC difference between the full and HbA1c-only models was 0.001 (95% CI of −0.011 to 0.011). For the full model, the corrected Brier score was 0.146, the calibration intercept was 0.001, and the calibration slope was 0.925. VIFs were low (maximum of 1.33), although the TyG coefficient reversed direction after adjustment and was not interpreted causally. In participants with baseline HbA1c ≥ 7.0% (n = 592 complete cases), corrected AUCs were 0.850 for HbA1c alone and 0.849 for the full model. Conclusions: Baseline HbA1c accounts for nearly all discriminative performance. Added biomarkers and baseline therapeutic classes provide little internally validated incremental value, and the model should not be used for treatment decisions before external validation and prospective evaluation of clinical impact. Full article

Ketogenic dietary therapies (KDTs) have been used for a century in drug-resistant epilepsy, and β-hydroxybutyrate (BHB), the major ketone body, is recognized as a signaling metabolite. This review examines how KDTs and BHB modulate mitochondrial function and evaluates evidence supporting these mechanisms. BHB is oxidized through D-β-hydroxybutyrate dehydrogenase 1 and succinyl-CoA:3-oxoacid-CoA transferase and alters redox balance and oxidative phosphorylation. It also inhibits class I histone deacetylases, serves as the substrate for lysine β-hydroxybutyrylation, activates hydroxycarboxylic acid receptor 2, and blocks the NLR family pyrin domain-containing 3 inflammasome. These pathways influence redox defense, organelle quality, and inflammation. However, ketogenic feeding suppresses mitochondrial one-carbon metabolism and some signaling effects occur only at BHB concentrations exceeding those typically achieved through dietary ketosis. Clinical benefits are best established in drug-resistant epilepsy and appear genotype-dependent in primary mitochondrial disease, with potential benefit in mitochondrial DNA (mtDNA) variant carriers but possible harm in DNA polymerase gamma-related disease and mtDNA deletion myopathy. Outside neurology, human evidence includes a hemodynamic response to infused 3-hydroxybutyrate in heart failure, sustained glycemic improvement in non-randomized diabetes cohorts, and small trials in psychiatric and oncological populations. Most clinical studies have not directly measured mitochondrial outcomes. Proposed mitochondrial mechanisms of KDTs and BHB remain plausible but are not established explanations for clinical benefit. Genotype-stratified trials, ketone exposure assessment, and direct measurement of mitochondrial variables in patients are needed. Full article

Edible mushroom polysaccharide (EMP) preparations have repeatedly improved glycemic control, adiposity, lipid homeostasis and hepatic lipid accumulation in animal models, and luminal assays and microbiota-perturbation experiments support the routes involved. Selected preparations also thicken, emulsify, retain water and modify food matrices. Yet these findings rarely concern the same material: metabolic, mechanistic and techno-functional studies usually examine different preparations, and retained function is seldom assessed after formulation, processing and digestion. This narrative review uses preparation identity, defined by biological source, processing route and resulting material characteristics, to integrate preparation chemistry, gastrointestinal mechanisms, animal and human outcomes, food-system behavior and food-use considerations. Molecular size, solubility, hydration, binding and fermentability provide a shared physicochemical basis for food-matrix performance and gastrointestinal interactions. Animal doses, human intakes and food-matrix loadings overlap at gram scale, which leaves functional delivery as the unresolved step. Controlled human trials are still few, small and dissimilar in design, so translation remains to be tested. The central question is therefore whether a reproducible EMP preparation can retain its intended function in an acceptable food and produce matched human outcomes. Progress depends on following the same characterized preparation from production and food incorporation through processing, consumption and human evaluation. Full article