Search Results (415)

The nutritional value of beef is highly influenced by its fatty acid composition. This study evaluated whether diet proximate analyses or plasma fatty acid profiles could predict the meat fatty acid composition in young beef cattle finished at pasture or with hay- and concentrate-based diets in stalls. Eighteen crossbred animals (Limousine × Sardo-Bruna) were analyzed for plasma and the intramuscular fat composition of Longissimus thoracis (LT) and Musculus gluteus maximus (MGM). A canonical correlation analysis revealed strong relationships between the dietary antioxidant capacity and meat lipid profiles, particularly for α-linolenic acid and conjugated linoleic acid. The redundancy index indicated that diet explained 38% of the variance in LT fatty acids and 20% in MGM. Partial least squares regression achieved a high precision and accuracy (R² up to 0.94), with a low root mean square error of prediction and high predictive ability (Q² > 0.85), in predicting the intramuscular fatty acid composition from plasma samples. Overall, (i) animals consuming diets with a higher antioxidant capacity and rich in n-3 precursors (ether extract) have healthier fat profiles, and (ii) plasma fatty acid profiling can be a powerful method for monitoring meat quality. This approach provides farmers with a non-invasive tool to improve meat quality management and promote healthier beef products. Full article

The Mediterranean fig (Ficus carica L.) is a dioecious fruit tree of high nutritional and economic value in the Mediterranean basin. In northern Morocco, phenological desynchronization between male and female fig trees limits pollination and production. This study aimed to characterize the phenological stages of indigenous fig and caprifig varieties using the BBCH scale and to evaluate the predictive capacity of artificial neural networks (ANNs). This study was conducted in the Bni Ahmed region over two consecutive years (2021 and 2022) at two sites. At each site, a total of 80 female fig trees were selected. Caprifig trees were selected in accordance with their availability (37 trees/site 1; 24 trees/site 2). Local meteorological data were incorporated into the analysis to evaluate the influence of climatic conditions on phenological stages. Our results revealed significant effects of temperature, humidity, and rainfall on phenological dynamics, along with a clear inter-varietal variability and pronounced desynchronization between male and female fig trees. Early-ripening caprifig varieties showed limited pollination efficiency, whereas late-ripening varieties were better synchronized with the longer receptivity period of female fig trees. Importantly, the ANN model demonstrated exceptional predictive performance (R² up to 0.985, RMSE < 1 day), serving as a robust and practical tool for forecasting key phenological stages and minimizing potential yield losses. These findings demonstrate the value of combining phenological monitoring with AI-based modeling to improve adaptive management of fig orchards under Mediterranean climate change. This is the first study in Morocco to implement such an integrated approach to fig and caprifig trees. Full article

Background: Artificial Intelligence (AI) is increasingly applied in endurance sports to optimize performance, enhance recovery, and personalize nutrition and supplementation. This review synthesizes current knowledge on AI applications in endurance sports, emphasizing implications for metabolic health, nutritional strategies, and recovery optimization, while also addressing ethical considerations and future directions. Methods: A narrative review was conducted using targeted searches of PubMed, Scopus, and Web of Science with cross-referencing. Extracted items included sport/context, data sources, AI methods including machine learning (ML), validation type (internal vs. external/field), performance metrics, comparators, and key limitations to support a structured synthesis; no formal risk-of-bias assessment or meta-analysis was undertaken due to heterogeneity. Results: AI systems effectively integrate multimodal physiological, environmental, and behavioral data to enhance metabolic health monitoring, predict recovery states, and personalize nutrition. Continuous glucose monitoring combined with AI algorithms allows precise carbohydrate management during prolonged events, improving performance outcomes. AI-driven supplementation strategies, informed by genetic polymorphisms and individual metabolic responses, have demonstrated enhanced ergogenic effectiveness. However, significant challenges persist, including measurement validity and reliability of sensor-derived signals and overall dataset quality (e.g., noise, missingness, labeling error), model performance and generalizability, algorithmic transparency, and equitable access. Furthermore, limited generalizability due to homogenous training datasets restricts widespread applicability across diverse athletic populations. Conclusions: The integration of AI in endurance sports offers substantial promise for improving performance, recovery, and nutritional strategies through personalized approaches. Realizing this potential requires addressing existing limitations in model performance and generalizability, ethical transparency, and equitable accessibility. Future research should prioritize diverse, representative, multi-site data collection across sex/gender, age, and race/ethnicity. Coverage should include performance level (elite to recreational), sport discipline, environmental conditions (e.g., heat, altitude), and device platforms (multi-vendor/multi-sensor). Equally important are rigorous external and field validation, transparent and explainable deployment with appropriate governance, and equitable access to ensure scientifically robust, ethically sound, and practically relevant AI solutions. Full article

As a staple cereal worldwide, winter wheat plays a pivotal role in food security. Leaf chlorophyll serves as a direct indicator of photosynthetic performance and nitrogen nutrition, making it critical for precision management and yield gains. Consequently, rapid, nondestructive, and high-accuracy remote-sensing retrievals are urgently needed to underpin field operations and precision fertilization. In this study, canopy hyperspectral reflectance together with destructive chlorophyll assays were systematically acquired from Yangling field trials conducted during 2018–2020. Three families of spectral indices were devised: classical empirical indices; two-dimensional optimal spectral indices (2D OSI) selected by correlation-matrix screening; and novel three-dimensional optimal spectral indices (3D OSI). The main contribution lies in devising novel 3D OSIs that combine three spectral bands and demonstrating how their fusion with classic two-band indices can improve chlorophyll quantification. Correlation analysis showed that most empirical vegetation indices were significantly associated with chlorophyll (p < 0.05), with the new double difference index (NDDI) giving the strongest relationship (R = 0.637). Within the optimal-index sets, the difference three-dimensional spectral index (DTSI; 680, 807, and 1822 nm) achieved a correlation coefficient of 0.703 (p < 0.05). Among all multi-input fusion schemes, fusing empirical indices with 3D OSI and training with RF delivered the best validation performance (R² = 0.816, RMSE = 0.307 mg g⁻¹, MRE = 11.472%), and external data further corroborated its feasibility. Altogether, integrating 3D spectral indices with classical vegetation indices and deploying RF enabled accurate, nondestructive estimation of winter wheat chlorophyll, offering a new hyperspectral pathway for monitoring crop physiological status and advancing precision agricultural management and fertilization, can guide in-season fertilization to optimize nitrogen use, thereby advancing precision agriculture. Full article

Introduction: After total pancreatectomy, patients inevitably develop pancreatogenic diabetes with marked glycemic variability and high risk of malnutrition due to both endocrine and exocrine insufficiency. Weight loss and malnutrition can occur even in those with adequate dietary intake and plausible pancreatic enzyme replacement. We hypothesized that glycemic variability is associated with nutritional decline. Methods: We retrospectively analyzed 14 patients who underwent continuous glucose monitoring (CGM) after total pancreatectomy. Nutritional status was assessed using the Geriatric Nutritional Risk Index (GNRI), and patients were classified into malnutrition-risk progression or nutrition-maintaining groups. Then, we evaluated glycemic indices, dietary intake, anthropometry, and pancreatic enzyme replacement therapy (PERT). Results: Insulin use, PERT dose, and dietary intake were approximately comparable between groups. In contrast, the malnutrition-risk progression group showed significantly higher mean glucose and time above range, and lower time in range (TIR). Importantly, TIR consistently showed an inverse association with malnutrition-risk progression across models adjusted for clinical covariates, including time since pancreatectomy, primary diagnosis, insulin regimen, and pancrelipase dose. These findings indicate that the observed relationship between lower TIR and worsening GNRI was independent of dietary intake and adequacy of enzyme replacement therapy, underscoring TIR as a clinically meaningful indicator of nutritional decline in this population. Conclusions: Hyperglycemia and reduced TIR were significantly associated with worsening GNRI after total pancreatectomy, independent of dietary intake or PERT. CGM-based glycemic metrics may help identify patients at risk of malnutrition and guide postoperative management. Full article

Background and Clinical Significance: Roux-en-Y gastric bypass (RYGB) significantly alters glucose metabolism, yet managing glucose variability in patients undergoing bariatric surgery remains challenging. Continuous Glucose Monitoring (CGM) offers real-time insights into glucose fluctuations and may support long-term metabolic management in this population. This case highlights the utility of CGM in identifying postprandial glycemic variability and guiding dietary adjustments. Case Presentation: A 45-year-old female, 14 years post-RYGB, presented with symptoms including postprandial fatigue, nocturnal cravings, and unexplained weight gain, despite adherence to nutritional guidelines. Her BMI had decreased from 52 kg/m² (pre-surgery) to 29 kg/m². She was provided with a CGM device (FreeStyle Libre 3) by the clinical team and instructed to monitor glucose without modifying her routine initially. Data revealed significant glycemic variability, with peaks up to 220 mg/dL and hypoglycemic dips to 45 mg/dL. Based on this, she adjusted her diet by reducing non-complex carbohydrates and increasing vegetables, proteins, and complex carbohydrates. Within two weeks, her symptoms improved, including better sleep and energy levels, accompanied by a 3 kg weight loss following dietary adjustments informed by CGM feedback. Conclusions: This case suggests how CGM can empower patients having undergone bariatric surgery to manage glucose fluctuations through informed self-management. The patient’s ability to identify and address glucose variability without formal intervention highlights CGM’s potential as a supportive tool in long-term care. While further studies are needed, this case suggests CGM may benefit similar patients experiencing postprandial symptoms or weight regain after bariatric surgery. Full article

Background and Objectives: Iron deficiency anemia (IDA) is the most common cause of anemia in pregnant women and can adversely affect both maternal and fetal health. This study aimed to compare pregnancy outcomes between women with and without IDA in Northern Thailand, a region with a high prevalence of anemia. Methods: A retrospective cohort study was conducted on all singleton pregnancies attending antenatal care (ANC) and/or delivering at Maharaj Nakorn Chiang Mai Hospital between 2003 and 2024. The study group consisted of women diagnosed with IDA in the first half of pregnancy, while the control group comprised women with low-risk pregnancies during the same study period. Results: Of the 38,979 pregnancies, after applying exclusion criteria, 634 pregnancies (2.2%) with laboratory-confirmed IDA and 28,132 controls remained available for analysis. Women with IDA had significantly higher parity, lower socioeconomic status, and lower hemoglobin levels throughout pregnancy. Multivariate regression analysis revealed that IDA was significantly associated with increased risks of preterm birth (adjusted odds ratio; aOR 1.04; 95% CI: 1.01–1.07), fetal growth restriction (FGR) (aOR 1.02; 95% CI: 1.00–1.04), and low birth weight (aOR 1.05; 95% CI: 1.03–1.08). Conclusions: IDA, even with treatment, may still slightly increase the risk of adverse pregnancy outcomes, particularly preterm birth, fetal growth restriction, and low birth weight. The residual risk likely reflects incomplete correction of anemia. Optimizing management requires strict compliance, judicious use of parenteral iron, and attention to coexisting nutritional deficiencies, underscoring the need for closer monitoring and improved care strategies. Full article

Corn stunt complex, transmitted by the corn leafhopper (Dalbulus maidis), poses significant yield risks to corn production. This study evaluated the effects of two corn hybrids and top-dressed nitrogen (N) and potassium (K) fertilization on D. maidis incidence and corn stunt symptom expression under field conditions. Eighteen treatments were tested in a randomized complete block design with six replications over two seasons. Leafhopper populations were monitored using yellow sticky traps, and symptom incidence and severity were assessed at R₁ and R₃ stages, respectively. While D. maidis populations varied substantially between seasons, neither N nor K fertilization, nor hybrid selection, significantly affected vector abundance. Importantly, symptom frequency and severity were not directly proportional to leafhopper density. Top-dressed fertilization, particularly with K, reduced the visual expression of corn stunt symptoms although it did not prevent infection. Hybrid responses to fertilization varied, with a genotype exhibiting greater symptom mitigation. Grain yield was not significantly influenced by nutrient rates or hybrid choice. These findings suggest that balanced N and K fertilization enhances crop resilience to corn stunt disease without directly suppressing vector populations. Integrating nutritional management with hybrid selection presents a promising strategy to add in corn stunt control and deepens our understanding of the environmental factors that mitigate severe symptoms. Full article

Advances in geroscience suggest that aging is modulated by molecular pathways that are amenable to dietary and pharmacological intervention. We conducted an integrative critical review of caloric restriction (CR), intermittent fasting (IF), and caloric restriction mimetics (CR-mimetics) to compare shared mechanisms, clinical evidence, limitations, and translational potential. Across modalities, CR and IF consistently activate AMP-activated protein kinase and sirtuins, inhibit mTOR (mechanistic target of rapamycin) signaling, and enhance autophagy, aligning with improvements in insulin sensitivity, lipid profile, low-grade inflammation, and selected epigenetic aging measures in humans. CR-mimetics, such as metformin, resveratrol, rapamycin, and spermidine, partially reproduce these effects; however, long-term safety and efficacy in healthy populations remain incompletely defined. Methodological constraints—short trial duration, selective samples, intermediate (nonclinical) endpoints, and limited adherence monitoring—impede definitive conclusions on hard outcomes (frailty, disability, hospitalization, mortality). We propose the Active Management of Aging and Longevity (AMAL) model, a three-level biomarker-guided framework that integrates personalized diet, chrono-nutrition, exercise, and the selective use of CR-mimetics, along with digital monitoring and decision support. AMAL emphasizes epigenetic clocks, multi-omics profiling, inflammatory and microbiome metrics, and adaptive protocols to enhance adherence and clinical relevance. Overall, CR, IF, and CR mimetics constitute promising, complementary strategies to modulate biological aging; rigorous long-term trials with standardized biomarkers and clinically meaningful endpoints are needed to enable their scalable implementation. Full article

The green macroalgae Ulva Linnaeus, 1753, also known as sea lettuce, is one of the most ecologically and economically significant algal genera. Its representatives occur in marine, brackish, and freshwater environments worldwide and show high adaptability, rapid growth, and marked biochemical diversity. These traits support their ecological roles in nutrient cycling, primary productivity, and habitat provision, and they also explain their growing relevance to the blue bioeconomy. This review summarizes current knowledge of Ulva biodiversity, taxonomy, and physiology, and evaluates applications in food, feed, bioremediation, biofuel, pharmaceuticals, and biomaterials. Particular attention is given to molecular approaches that resolve taxonomic difficulties and to biochemical profiles that determine nutritional value and industrial potential. This review also considers risks and limitations. Ulva species can act as hyperaccumulators of heavy metals, microplastics, and organic pollutants, which creates safety concerns for food and feed uses and highlights the necessity of strict monitoring and quality control. Technical and economic barriers restrict large-scale use in energy and material production. By presenting both opportunities and constraints, this review stresses the dual role of Ulva as a promising bioresource and a potential ecological risk. Future research must integrate molecular genetics, physiology, and applied studies to support sustainable utilization and ensure safe contributions of Ulva to biodiversity assessment, environmental management, and bioeconomic development. Full article

Crops nitrogen supply through the in situ mineralization of soil organic matter is a critical process for plant nutrition. However, accurately estimating the contribution of mineralization remains challenging. The complexity of biological, chemical, and physical processes in the soil, influenced by environmental conditions, makes it difficult to precisely quantify the amount of nitrogen available for crops. In this study, we created a database by collecting results from 121 mineralization monitoring experiments carried out between 2015 and 2021 on different experimental plots across Wallonia, Southern Belgium, and assessed the efficiency of predictive mineralization methods. The most impactful analytical parameters on in situ mineralization (ISM), determined using LIXIM program, appeared to be potentially mineralizable nitrogen (PMN) (r = 0.79). PMN, estimated by anaerobic soil incubation, also allowed the effective consideration of the after-effects of grassland termination and manure inputs. A multiple linear regression (MLR) combining PMN, POxC, pH, TOC:N, and TOC:clay significantly improved the prediction of soil nitrogen mineralization available for crops, achieving r = 0.87 (vs. r = 0.58 for the current method), while reducing dispersion by 41% (RMSE 56.35 → 33.13 kg N·ha⁻¹). The use of a more flexible Bootstrap Forest model (BFM) further enhanced performance, reaching r = 0.92 and a 50.8% reduction in dispersion compared to the current method (RMSE 56.35 → 27.76 kg N·ha⁻¹), i.e., about 16% lower RMSE than the MLR. Those models provided practical and efficient tools to better manage nitrogen resources in temperate agricultural systems. Full article

Vasconcellea pubescens (mountain papaya) is an underutilized Andean fruit with distinctive nutritional and functional properties, yet its rapid softening and short shelf-life result in significant postharvest losses. This review summarizes current knowledge on the physiology of fruit development and ripening, with emphasis on cell wall disassembly, color changes, and ethylene regulation as determinants of postharvest quality. Advances in postharvest management strategies, including temperature control, packaging, and ethylene-modulating treatments (such as 1-MCP), are discussed in the context of preserving fruit firmness, extending shelf life, and reducing food waste. Furthermore, the high content of bioactive compounds—such as papain, phenolics, and flavonoids—underscores the potential of valorizing by-products through sustainable biotechnological applications. Despite recent progress, critical gaps remain in genomic resources, predictive quality monitoring, and large-scale implementation of preservation techniques. Addressing these challenges could enhance the economic and ecological value of V. pubescens, positioning it as both a model species for postharvest research and a promising fruit for reducing food losses in horticultural supply chains. Full article

Bananas (Musa AAA) can be affected by maturity bronzing, a physiological disorder that appears in the form of bronzing on the fruit’s epidermis, compromising its quality and generating economic losses due to commercial rejection. Since the symptoms are only evidenced at harvest, it is necessary to identify the associated factors in order to develop preventive strategies. This research analyzed morphometric and nutritional characteristics potentially related to the formation of stains on two banana-exporting farms in Antioquia and Magdalena (Colombia). Monitoring plots were established, in which 310 productive units with the banana Cavendish cv. Williams subgroup were evaluated over 52 weeks. In all units, the height, the pseudostem perimeter, the weight and number of hands of the bunch, and the weight of the affected fruit were recorded. In addition, foliar and soil analyses were conducted in each production unit, and some climatic components were characterized. Through a multiple logistic regression model, it was observed that a pseudostem perimeter smaller than 70 cm (measured 50 cm from the base), together with foliar B and Zn concentrations below 100 and 25 mg/kg, respectively, was associated with a higher probability of bronzing formation. These values should be interpreted as preliminary associations derived under specific conditions, and therefore as requiring validation across different contexts and management systems, before being considered as reference parameters. These findings provide new factors associated with maturity bronzing and open opportunities for future research aimed at its prevention. Full article

Background: Disease-related malnutrition (DRM) remains an underdiagnosed condition in Latin American hospitals, with substantial clinical and economic consequences. The global nutritionDay initiative, promoted by ESPEN, provides a standardized audit to evaluate and improve hospital nutritional care. This study aimed to develop expert consensus recommendations to optimize the nutritional care process in Guatemalan hospitals, based on the findings from nutritionDay 2022. Methods: A modified Delphi study was conducted, including three meetings held before and after each round to discuss the results. Sixteen clinical nutrition professionals from eleven hospitals participated. A total of 89 items were assessed, with a predefined consensus threshold of 70%. Data were analyzed using R software (version 4.5.0) and Kendall’s W coefficient was applied to evaluate inter-round agreement. Results: Consensus was achieved for 51 key recommendations covering nutritional screening, clinical assessment, anthropometry, body composition, functional assessment, biochemical monitoring, dietary intervention, and post-discharge follow-up. The proposed actions are aligned with international guidelines (ESPEN, ASPEN, GLIM) and adapted to the Guatemalan healthcare context. Conclusions: This consensus provides a comprehensive and context-specific framework for standardizing and improving hospital nutritional care in Guatemala and similar settings. Its implementation could help reduce DRM prevalence and foster the development of quality indicators and digital tools for clinical nutrition management. Full article

Background: Adherence to Medical Nutrition Therapy (MNT) is a key determinant of therapy success, particularly in chronic diseases like chronic kidney disease (CKD). MNT in CKD requires significant changes in patient’s dietary habits, which can affect long-term adherence. This study aims to evaluate the adherence to MNT in stage 5 CKD patients undergoing conservative kidney management (CKM), identifying potential challenges and strengths of nutritional intervention. Methods: We enrolled in 94 stage 5 CKD patients undergoing CKM at the University Hospital of Modena, Italy. We collect clinical data from medical and nutrition records. The inclusion criteria comprised patients of all genders, ages, and ethnicity with stage 5 chronic kidney disease (CKD), in pre-dialysis, enrolled in the nephrology and dietetics program, who had access to 24-h urine tests, anthropometric measurements, and dietary history records. Exclusion criteria included patients with CKD stages lower than 5, those who had not undergone at least one nutritional assessment, or lacked accessible 24-h urine data. The study utilized medical and dietary records from September 2017 to March 2025. The primary outcome was the assessment of adherence to medical nutrition therapy (MNT), comparing prescribed protein intake with actual intake, estimated from dietary history (DH). Protein intake was compared with normalized protein nitrogen appearance (nPNA) as stated by recent guidelines. Additional factors influencing adherence, such as age, gender, comorbidities, physical activity, and prior dietary interventions, were also evaluated. Anthropometric measurements and biochemical tests were collected, and dietary intake was assessed using a seven-day DH. Results: Data were analyzed using descriptive statistics, linear correlation models, univariate logistic regression, t-tests, paired t-tests, and chi-square tests, with significance set at p < 0.05. Most of the patients follow suggested energy and protein intakes limits; however, substantial individual variability emerged Bland–Altman analysis indicated a moderate bias and wide limits of agreement for energy intake (+116 kcal; limits of agreement –518.8 to +751.3 kcal), revealing frequent overestimation in self-reports. Protein intake showed less systematic error, but discrepancies between dietary recall and biochemical markers persisted. Protein intake decreased significantly over time (p < 0.001), while correlation with nPNA did not reach statistical significance (ρ = 0.224, p = 0.051). No significant associations were identified between adherence and most clinical or lifestyle factors, although diabetes was significantly associated with lower adherence to protein intake (p = 0.042) and a predominantly sedentary lifestyle showed a borderline association with energy intake adherence (p = 0.076), warranting further investigation. Longitudinal analysis found stable BMI and body weight, alongside notable reductions in sodium (p = 0.018), potassium (p = 0.045), and phosphorus intake (p < 0.001) over time. Conclusions: Assessing dietary adherence in CKD remains complex due to inconsistencies between self-reported and biochemical estimates. These findings highlight the need for more objective dietary assessment tools and ongoing, tailored nutritional support. Multifaceted interventions—combining education, personalized planning, regular monitoring, and promotion of physical activity—are recommended to enhance adherence and improve clinical outcomes in this vulnerable population. Full article