Search Results (140)

This study aimed to determine the net energy (NE) values of common energy-supplying nutrients, including starch, protein, and fat, to investigate their influence on energetic efficiency and NE partition patterns in growing pigs, and to develop prediction equations for the protein deposition (PD) and lipid deposition (LD) based on nutrient characteristics of ingredients. Two experiments were conducted. In Experiment 1, 36 growing barrows (Duroc × Landrace × Yorkshire, initial body weight = 28.1 ± 0.8 kg) were randomly allotted to six treatments, with six replicated pigs per treatment. The diets were formulated as follows: a corn–soybean meal basal diet (T1), and five experimental diets containing of 27% corn starch (T2), 27% tapioca starch (T3), 27% pea starch (T4), 5% soybean oil (T5), and 11.8% casein (T6), respectively. In Experiment 2, PD and LD data of 47 ingredients were collected. Subsequently, the nutrient characteristics of ingredients were used as input variables, and PD and LD were used as output variables to establish the prediction equations. Results exhibited that pigs fed the T2, T3, and T4 diets showed increased digestibility of gross energy (GE) and organic matter (OM) compared to those fed the T1 diet (p < 0.01). For various kind of starches, a greater efficiency of using metabolizable energy (ME) for net energy not deposited as protein (PD-free NE, efficiency denoted as kj) was observed when pigs were fed the T2 or T3 diets compared to the T4 diet. Moreover, the kj of soybean oil was 11% and 27% greater than that of starch and casein, respectively, while casein demonstrated 46% and 39% greater efficiency of using ME for PD (efficiency denoted as pj) compared to starch and soybean oil, respectively. Finally, the best-fitted prediction equations for PD and LD were PD = 364.36 − 18.44 × GE + 29.10 × CP − 3.79 × EE − 21.37 × ADF (R² = 0.96; RMSE = 105.15) and LD = −1503.50 + 21.58 × CP + 51.98 × EE + 26.30 × Starch + 26.81 × NDF − 23.87 × ADF (R² = 0.98; RMSE = 172.85), respectively. In summary, there are considerable differences in energetic efficiency and NE partition patterns among various nutrients. In addition, PD and LD can be predicted through nutrient characteristics of ingredients, presenting an innovative approach and methodological framework for the precision nutrition of pigs. Full article

Soft gels, such as hydrogels, organogels, aerogels, and bigels, represent versatile materials that are increasingly utilized within food systems to modify texture, regulate nutrient delivery, serve as fat substitutes, and enhance product shelf life. Their structural diversity and tunable properties enable targeted solutions for healthier, more sustainable, and consumer-centric products. This review provides a critical overview of recent advances in soft gel science, emphasizing industrial feasibility, regulatory compliance, and strategies to overcome commercialization barriers such as cost, scalability, and consumer acceptance. For each gel type, we compare functional performance with conventional structuring and encapsulation systems, highlighting cases where soft gels offer superior stability, bioactive protection, or caloric reduction. We also examine emerging applications, including gel-based frying media, 3D printing, and nano-enabled formulations, alongside potential risks related to long-term exposure and bioaccumulation. Regulatory frameworks across major jurisdictions are summarized, and sustainability considerations, from sourcing to life cycle impact, are discussed. By integrating technological innovation with safety, regulatory, and market perspectives, this review identifies key research priorities and practical pathways for translating soft gel technologies from laboratory concepts into commercially viable, health-driven food solutions. Full article

Background: This network meta-analysis aimed to assess the relative efficacy of macronutrient dietary groups with varying carbohydrate, fat, and protein ratios on weight control and cardiovascular risk factors improvement in adults. Methods: We searched PubMed, the Cochrane Central Register of Controlled Trials (CENTRAL), Embase, Web of Science Core Collection, and ClinicalTrials.gov from inception to 30 November 2024, as well as reference lists of related systematic reviews. Eligible randomized controlled trials (RCTs) were included. Literature screening, data extraction, and risk of bias assessment were conducted independently by two reviewers. The changes in body weight, blood glucose, systolic blood pressure, diastolic blood pressure, high density lipoprotein (HDL) cholesterol, low density lipoprotein (LDL) cholesterol, triglycerides, and total cholesterol were the study outcomes. Utilizing a Bayesian framework, a series of random-effects network meta-analyses were conducted to estimate mean difference (MD) with 95% credible interval (CrI) and determine the relative effectiveness of the macronutrient dietary groups. The quality of evidence for each pair of dietary groups was assessed based on the online tool called confidence in network meta-analysis (CINeMA). Results: This study initially identified 14,988 studies and ultimately included 66 eligible RCTs involving 4301 participants in the analysis. The very low carbohydrate–low protein (VLCLP, MD −4.10 kg, 95% CrI −6.70 to −1.54), the moderate carbohydrate–high protein (MCHP, MD −1.51 kg, 95% CrI −2.90 to −0.20), the very low carbohydrate–high protein (VLCHP, MD −1.35 kg, 95% CrI −2.52 to −0.26) dietary groups might lead to weight loss compared with the moderate fat–low protein (MFLP) dietary group. Among the dietary groups relative to the MFLP dietary group, the moderate carbohydrate–low protein (MCLP, MD 0.09 mmol/L, 95% CrI 0.02 to 0.16) and VLCHP (MD 0.16 mmol/L, 95% CrI 0.08 to 0.24) dietary groups were less effective in lowering HDL cholesterol, and the VLCHP (MD 0.50 mmol/L, 95% CrI 0.26 to 0.75) dietary group was less effective in lowering LDL cholesterol. In terms of triglyceride reduction, the MCLP (MD −0.33 mmol/L, 95% CrI −0.44 to −0.22), VLCHP (MD −0.31 mmol/L, 95% CrI −0.42 to −0.18), VLCLP (MD −0.14 mmol/L, 95% CrI −0.25 to −0.02), and moderate fat–high protein (MFHP, MD −0.13 mmol/L, 95% CrI −0.21 to −0.06) dietary groups were more efficacious than the MFLP dietary group, while any pair of dietary group interventions showed minimal to no difference in the effects on blood glucose, blood pressure, and total cholesterol. Conclusions: High or moderate certainty evidence reveals that the VLCLP dietary group is the most appropriate for weight loss, while the MCLP dietary group is best for reducing triglycerides. For control of blood glucose, blood pressure, and cholesterol levels, there is little to no difference between macronutrient dietary groups. Additionally, future studies in normal-weight populations are needed to verify the applicability of our findings. Full article

Type 2 diabetes mellitus (T2DM) is a multifactorial disorder defined by insulin resistance, β-cell dysfunction, and chronic hyperglycemia. Although peripheral mechanisms have been extensively studied, increasing evidence implicates the gastrointestinal tract in disease onset. Insights from bariatric surgery, gut hormone signaling, and incretin-based therapies suggest that the gut contributes actively beyond nutrient absorption. Yet, a cohesive framework integrating these observations remains absent, leaving a critical gap in our understanding of T2DM’s upstream pathophysiology. This work builds upon the anti-incretin theory, which posits that nutrient-stimulated neurohormonal signals—termed “anti-incretins”—arise from the proximal intestine to counteract incretin effects and regulate glycemic homeostasis. The excess of anti-incretin signals, perhaps stimulated by macronutrient composition or chemical additives of modern diets, disrupts this balance and may cause insulin resistance and β-cell depletion, leading to T2D. We hypothesize that the neuroendocrine signals produced by cholecystokinin (CCK)-I and secretin-S cells, both located in the proximal intestine, function as endogenous anti-incretins. In this context, we hypothesize a novel model centered on the chronic overstimulation of I and S cells by high-fat, high glycemic index modern diets. This drives what we term “amplified digestion”—a state marked by heightened vagal and hormonal stimulation of biliary and pancreatic secretions, increased enzymatic and bile acid activity, and alterations in bile acid composition. This condition leads to an extended breakdown of carbohydrates, lipids, and proteins into absorbable units, thereby promoting excessive nutrient absorption and ultimately contributing to insulin resistance and progressive β-cell failure. Multiple lines of clinical, surgical, and experimental evidence converge to support our model, rooted in the physiology of digestion and absorption. Western dietary patterns appear to induce an over-digestive adaptation—marked by excessive vagal and hormonal stimulation of biliary and pancreatic secretion—which amplifies digestive signaling. This heightened state correlates with increased nutrient absorption, insulin resistance, and β-cell dysfunction. Interventions that disrupt this maladaptive signaling—such as truncal vagotomy combined with duodenal bypass—may offer novel, physiology-based strategies for T2DM treatment. This hypothesis outlines a potential upstream contributor to insulin resistance and T2DM, grounded in digestive tract-derived neurohormonal dysregulation. This gut-centered model may provide insight into early, potentially reversible stages of the disease and identify a conceptual therapeutic target. Nonetheless, both the hypothesis and the accompanying surgical strategy—truncal vagotomy combined with proximal intestinal bypass—remain highly exploratory and require systematic validation through mechanistic and clinical studies. Further investigation is warranted to clarify the molecular regulation of I and S enteroendocrine cells, including the genetic and epigenetic factors that may drive hypersecretion. While speculative, interventions—surgical or pharmacologic—designed to modulate these digestive signals could represent a future avenue for research into T2DM prevention or remission, pending rigorous evidence. Full article

This study investigated the anti-obesity effects of a homogenized, viscous vegetable (VV) mixture prepared from mucilaginous vegetables, with a focus on modulating hepatic lipid metabolism and gut microbiota composition in mice fed with a high-fat (HF) diet. The VV mixture was formulated by blending freeze-dried powders of ten mucilaginous vegetables, classified as moderately thick using a line-spread test and extremely thick according to the IDDSI framework in a 1:9 ratio (VV mixture: water, w/w). Six-week-old male C57BL/6 mice were fed control or HF diets, with or without 10% VV mixture for 8 weeks (n = 7 per group). The HF diet induced significant weight gain, adipose tissue accumulation, hepatic steatosis, and inflammation. The HF diet also significantly reduced hepatic ACO1, CPT1 mRNA expression, and α-diversity with distinct fecal microbiota profiles. On the other hand, VV mixture supplementation reduced serum TC, LDL-C levels and NAFLD scores. VV mixture supplementation also increased hepatic ACO1 and CPT1 mRNA expression, enhanced α-diversity, and enriched SCFA-producing bacteria, particularly the Lachnospiraceae NK4A136 group. In conclusion, the VV mixture attenuated HF diet-induced obesity, possibly through its high viscosity–mediated effects on hepatic fatty acid oxidation and gut microbiota modulation. Full article

This review synthesizes advances in livestock genomics by examining the interplay between candidate genes, molecular markers (MMs), signatures of selection (SSs), and quantitative trait loci (QTLs) in shaping economically vital traits across livestock species. By integrating advances in genomics, bioinformatics, and precision breeding, the study elucidates genetic mechanisms underlying productivity, reproduction, meat quality, milk yield, fibre characteristics, disease resistance, and climate resilience traits pivotal to meeting the projected 70% surge in global animal product demand by 2050. A critical synthesis of 1455 peer-reviewed studies reveals that targeted genetic markers (e.g., SNPs, Indels) and QTL regions (e.g., IGF2 for muscle development, DGAT1 for milk composition) enable precise selection for superior phenotypes. SSs, identified through genome-wide scans and haplotype-based analyses, provide insights into domestication history, adaptive evolution, and breed-specific traits, such as heat tolerance in tropical cattle or parasite resistance in sheep. Functional candidate genes, including leptin (LEP) for feed efficiency and myostatin (MSTN) for double-muscling, are highlighted as drivers of genetic gain in breeding programs. The review underscores the transformative role of high-throughput sequencing, genome-wide association studies (GWASs), and CRISPR-based editing in accelerating trait discovery and validation. However, challenges persist, such as gene interactions, genotype–environment interactions, and ethical concerns over genetic diversity loss. By advocating for a multidisciplinary framework that merges genomic data with phenomics, metabolomics, and advanced biostatistics, this work serves as a guide for researchers, breeders, and policymakers. For example, incorporating DGAT1 markers into dairy cattle programs could elevate milk fat content by 15-20%, directly improving farm profitability. The current analysis underscores the need to harmonize high-yield breeding with ethical practices, such as conserving heat-tolerant cattle breeds, like Sahiwal. Full article

Forensic entomotoxicology is a subdiscipline that utilizes necrophagous insects as bioindicators for detecting drugs and toxicants in decomposed remains, particularly in cases where conventional biological matrices are no longer available. Toxic substances can profoundly alter insect development, physiology, and community succession, potentially impacting the accuracy of postmortem interval (PMI) estimation. This review systematically summarizes the effects of various xenobiotics, including pesticides, illicit drugs, sedatives, heavy metals, and antibiotics on larval growth, physiological traits, and gut microbial composition in forensically relevant flies. However, most studies to date have relied primarily on phenotypic observations, with limited insight into underlying molecular mechanisms. Significant interspecies and dose-dependent variability also exists in the absorption, metabolism, and physiological responses to xenobiotics. We highlight recent advances in multi-omics technologies that facilitate the identification of molecular biomarkers associated with xenobiotic exposure, particularly within the insect detoxification system. Key components such as cytochrome P450 monooxygenases (P450s), glutathione S-transferases (GSTs), and ATP-binding cassette (ABC) transporters play essential roles in xenobiotic metabolism and insecticide resistance. Additionally, the insect fat body serves as a central hub for detoxification, hormonal regulation, and energy metabolism. It integrates signals related to xenobiotic exposure and modulates larval development, making it a promising model for future mechanistic studies in insect toxicology. Altogether, this review offers a comprehensive and reliable framework for understanding the complex interactions between toxic substance exposure, insect ecology, and decomposition in forensic investigations. Full article

Common carp (Cyprinus carpio) is one of the most significant fish species worldwide, with its natural distribution spanning Europe and Asia. To conduct a genome-wide association study (GWAS) and compare the prediction accuracy of genomic selection (GS) models for the growth traits of common carp in spring and autumn at 2 years of age, a total of 325 carp individuals were re-sequenced and phenotypic measurements were taken. Three GWAS methods (FarmCPU, GEMMA, and GLM) were applied and their performance was evaluated in conjunction with various GS models, using significance levels based on p-values. GWAS analyses were performed on eight traits (including the body length, body weight, fat content of fillet, and condition factor) for both spring and autumn seasons. Eleven different GS models (such as Bayes A, Bayes B, and SVR-linear) were combined to evaluate their performance in genomic selection. The results demonstrate that the FarmCPU method consistently exhibits superior stability and predictive accuracy across most traits, particularly under higher SNP densities (e.g., 5K), where prediction accuracies frequently exceed 0.8. Notably, when integrated with Bayesian approaches, FarmCPU achieves a substantial performance boost, with the prediction accuracy reaching as high as 0.95 for the autumn body weight, highlighting its potential for high-resolution genomic prediction. In contrast, GEMMA and GLM exhibited a more variable performance at lower SNP densities. Overall, the integration of FarmCPU with genomic selection (GS) models offers one of the most reliable and efficient frameworks for trait prediction, particularly for complex traits with substantial genetic variation. This approach proves especially powerful when coupled with Bayesian methodologies, further enhancing its applicability in advanced breeding programs. Full article

Background: Pre-season training is pivotal for optimizing athletic performance in collegiate basketball, yet the effectiveness of such programs in improving body composition (BC) under NCAA-mandated hourly restrictions remains underexplored. The aim of this study was to evaluate the impact of a four-week, NCAA Division II-compliant strength and conditioning (SC) program on BC in women’s basketball. Methods: Sixteen student athletes (20.6 ± 1.8 y; 173.9 ± 6.5 cm; 76.2 ± 20.2 kg) completed an eight-hour-per-week micro-cycle incorporating functional conditioning, Olympic-lift-centric resistance, and on-court skill development. Lean body mass (LBM) and body-fat percentage (BF%) were assessed using multi-frequency bioelectrical impedance on Day 1 and Day 28. Linear mixed-effects models were used to evaluate the fixed effect of Time (Pre, Post), including random intercepts for each athlete and covariate adjustment for age and height (α = 0.05). Results The LBM significantly increased by 1.49 kg (β = +1.49 ± 0.23 kg, t = 6.52, p < 0.001; 95% CI [1.02, 1.96]; R² semi-partial = 0.55), while BF% decreased by 1.27 percentage points (β = −1.27 ± 0.58%, t = −2.20, p = 0.044; 95% CI [−2.45, −0.08]; R² = 0.24). Height positively predicted LBM (β = +1.02 kg/cm, p < 0.001), whereas age showed no association (p > 0.64). Conclusions: A time-constrained, NCAA-compliant SC program meaningfully enhances lean mass and moderately reduces adiposity in collegiate women’s basketball athletes. These findings advocate for structured, high-intensity, mixed-modality training to maximize physiological readiness within existing regulatory frameworks. Future research should validate these results in larger cohorts and integrate performance metrics to further elucidate functional outcomes. Full article

This review examines human digestive physiology and metabolic adaptations in the context of evolutionary dietary patterns, particularly those emphasizing carnivorous and scavenging behaviors. By integrating metabolomic data with archaeological, anatomical, and microbiological evidence, the study explores how early hominins adapted to intermittent but energy-dense animal-based diets. The analysis highlights the development of hepatic insulin resistance, enhanced fat and protein metabolism, and shifts in gut microbiota diversity as physiological signatures of meat consumption. Comparative evaluations of digestive enzyme profiles, intestinal morphology, and salivary composition underscore humans’ omnivorous flexibility and partial carnivorous specialization. Additionally, biomarkers such as ketone bodies, branched-chain amino acids, and trimethylamine-N-oxide are identified as metabolic indicators of habitual meat intake. These adaptations, though once evolutionarily advantageous, are discussed in relation to current metabolic disorders in modern nutritional contexts. Overall, this review presents a metabolomic framework for understanding the evolutionary trajectory of human digestion and its implications for health and dietary recommendations. Full article

Trans fats are linked to numerous chronic diseases and cellular dysfunction; however, Spain has not implemented effective regulatory measures to restrict their presence in food products. This study addressed these gaps by analyzing trans fat content in commercial pastries sold in Spain and their biological impacts on mesenchymal stem cells, further examining its compliance with international guidelines. Also, a novel and scalable method for extracting fatty acids from pastry samples was developed and applied, enabling precise analysis using gas chromatography alongside sensory property assessments. The findings revealed significant variability in TFA levels across samples. To assess the biological implications of these TFAs, mesenchymal stem cells (MSCs) were cultured to perform dose–response experiments using two selected pastry samples with the highest TFA content. Cellular adhesion, cytotoxicity, and proliferation were evaluated through MTT assays, bright-field, and fluorescence staining using FITC and DAPI markers. Results demonstrated dose-dependent impacts of TFAs on MSC viability, including reduced adhesion and proliferation alongside increased cytotoxicity. This study underlines the need for stricter regulatory frameworks to monitor TFA levels worldwide, including in Spain’s food industry. Additionally, it highlights the potential health risks associated with excessive TFA consumption, particularly concerning cellular health and growth mechanisms, which provide insights into its potential bioaccumulation implications. These findings provide a foundation for further research into dietary guidelines and industrial practices aimed at minimizing TFA exposure while promoting public health safety. Full article

Obesity and low back pain (LBP) are major contributors to global disability and healthcare burden in both adults and children. Although a growing body of research supports a bidirectional relationship between these conditions, the underlying mechanisms remain poorly integrated in the current literature. While mechanical overload has traditionally been viewed as the principal link, emerging evidence points to additional roles for metabolic dysregulation, chronic low-grade inflammation, and adipokine activity in the development and persistence of LBP. This review addresses the need for a comprehensive synthesis of how obesity affects spinal structures, including the intervertebral discs, paraspinal muscles, facet joints, and epidural fat, through both biomechanical and systemic biological pathways. We specifically highlight key mechanisms such as oxidative stress, adipokine signalling, and neuroinflammation that may accelerate spinal degeneration and promote chronic pain. In doing so, we aim to bridge gaps between anatomical, biochemical, and clinical perspectives. Additionally, we assess current clinical evidence on weight loss as a potential strategy for alleviating LBP symptoms. By consolidating diverse lines of evidence, this review provides a clearer framework for understanding obesity-related spinal pathology and outlines priorities for future research and targeted interventions. Full article

Background/Objectives: Gestational diabetes mellitus (GDM) is a major pregnancy complication with rising global prevalence. The Mediterranean Diet (MD) has shown metabolic benefits, but total adherence scores may obscure meaningful variation in dietary quality. This study aimed to investigate whether specific dietary patterns, identified within the MD framework, and their glycemic load (GL) are associated with GDM risk. Methods: This prospective cohort is part of the BORN2020 longitudinal study on pregnant women in Greece; dietary intake was assessed using a validated food frequency questionnaire (FFQ) at two time points (pre-pregnancy and during pregnancy). MD adherence was categorized by Trichopoulou score tertiles. GL was calculated for food groups using glycemic index (GI) reference values and carbohydrate content. Dietary patterns were identified using factor analysis. Logistic regression models estimated adjusted odds ratios (aORs) for GDM risk, stratified by MD adherence and time period, controlling for maternal, lifestyle, and clinical confounders. Results: In total, 797 pregnant women were included. Total MD adherence was not significantly associated with GDM risk. However, both food-specific GLs and dietary patterns with distinct dominant foods were predictive. GL from boiled greens/salads was consistently protective (aOR range: 0.09–0.19, p < 0.05). Patterns high in tea, coffee, and herbal infusions before pregnancy were linked to increased GDM risk (aOR = 1.96, 95% CI: 1.31–3.02, p = 0.001), as were patterns rich in fresh juice, vegetables, fruits, legumes, and olive oil during pregnancy (aOR = 2.91, 95% CI: 1.50–6.24, p = 0.003). A pattern dominated by sugary sweets, cold cuts, animal fats, and refined products was inversely associated with GDM (aOR = 0.34, 95% CI: 0.17–0.64, p = 0.001). A pattern characterized by sugar alternatives was associated with higher risk for GDM (aOR = 4.94, 95% CI: 1.48–19.36, p = 0.014). These associations were supported by high statistical power (power = 1). Conclusions: Within the context of the MD, evaluating both the glycemic impact of specific food groups and identifying risk-associated dietary patterns provides greater insight into GDM risk than overall MD adherence scores alone. Full article

This study examines the impact that fat-tailed distributions of the spread residuals have on the optimal orders for pairs trading of stocks and cryptocurrencies. Using daily data from selected pairs, the spread dynamics has been modeled through a mean-reverting Ornstein–Uhlenbeck process and investigates how deviations from normality affect strategy design and profitability. Specifically, we compared four fat-tailed distributions—Lévy stable, generalized hyperbolic, Johnson’s S_U, and non-centered Student’s t—and showed how they modify optimal entry and exit thresholds, and performance metrics. The main findings reveal that the proposed pairs trading strategy correctly captures some key stylized facts of residual spreads such as large jumps, skewness, and excess Kurtosis. Interestingly, we considered regime-switching behaviors to account for structural changes in market dynamics, providing empirical evidence that optimal trading rules are regime-dependent and significantly influenced by the residual distribution’s tail behavior. Unlike conventional approaches, we optimized the entry signal and link heavy tails not only to volatility clustering but also to the nonlinearity in switching regimes. These findings suggest the need to account for distributional properties and dynamic regimes when designing robust pairs trading strategies, providing a more realistic and effective framework of these strategies in highly volatile and non-normal markets. Full article

Landslide hazard chains pose significant threats in mountainous areas worldwide, yet their cascading effects remain insufficiently studied. This study proposes an integrated framework to systematically assess the landslide-landslide dam-outburst flood hazard chain in mountainous river systems. First, landslide susceptibility is assessed through a random forest model incorporating 11 static environmental and geological factors. The surface deformation rate derived from SABS-InSAR technology is incorporated as a dynamic factor to improve classification accuracy. Second, motion trajectories of rock masses in high-risk zones are identified by Rockfall Analyst model to predict potential river blockages by landslide dams, and key geometric parameters of the landslide dams are predicted using a predictive model. Third, the 2D HEC-RAS model is used to simulate outburst flood evolution. Results reveal that: (1) incorporating surface deformation rate as a dynamic factor significantly improves the predictive accuracy of landslide susceptibility assessment; (2) landslide-induced outburst floods exhibit greater destructive potential and more complex inundation dynamics than conventional mountain flash floods; and (3) the outburst flood propagation process exhibits three sequential phases defined by the Outburst Flood Arrival Time (FAT): initial rapid advancement phase, intermediate lateral diffusion phase, and mature floodplain development phase. These phases represent critical temporal thresholds for initiating timely downstream evacuation. This study contributes to the advancement of early warning systems aimed at protecting downstream communities from outburst floods triggered by landslide hazard chains. It enables researchers to better analyze the complex dynamics of such cascading events and to develop effective risk reduction strategies applicable in vulnerable regions. Full article