Search Results (6,483)

Gestational diabetes mellitus (GDM), as one of the most common metabolic disorders occurring during pregnancy, represents a significant public health concern due to its rising prevalence and the numerous complications that can affect both the mother and the foetus. In recent years, there has been growing interest in the use of omics technologies, such as metabolomics and proteomics, in research on the pathogenesis and early detection of GDM. The aim of this paper was to summarise the current knowledge on metabolomic and proteomic changes observed in women with GDM and to assess the potential usefulness of these methods in identifying biomarkers of the disease. The narrative review was conducted in accordance with the PRISMA 2020 statement, using PubMed and Web of Science until 23 December 2025. The studies analysed show that GDM is associated with abnormalities in the metabolism of lipids, amino acids, carbohydrates and metabolites associated with the gut microbiota. The most commonly observed changes included: elevated levels of branched-chain amino acids, free fatty acids and purine metabolites, as well as changes in the metabolism of phospholipids and acylcarnitines. Multi-omics studies also indicate significant changes in plasma protein and lipid profiles. The data collected suggest that omics technologies may be a promising tool for identifying early biomarkers of GDM and for developing our understanding of the pathophysiological mechanisms of this condition. Nevertheless, further studies involving larger and more diverse patient populations are needed to confirm their diagnostic and clinical value. Full article

Neurodegenerative disorders and epilepsy remain major clinical challenges, due to complex etiologies involving protein misfolding, excitotoxicity, metabolic dysregulation, and impaired cellular resilience. These unmet medical needs have stimulated interest in small-molecule modulators capable of targeting multiple pathogenic pathways. Cyclitols, a diverse family of inositol stereoisomers, play essential roles in cellular signaling and brain metabolism; among them, scyllo-inositol (SCI) has gained attention due to its distinct stereochemistry, capacity to cross the blood–brain barrier, and emerging neuroactive properties. Current pharmacokinetic data indicate that SCI exhibits dose-dependent systemic exposure, and good penetration into the central nervous system. Moreover, its supplementation seems to be well-tolerated. In experimental studies both on animals and humans, SCI has been shown to modulate amyloid-β aggregation, stabilize neuronal homeostatic pathways, and reduce network hyperexcitability, suggesting relevance for both neurodegenerative and epileptic phenotypes. Despite promising results, there is still a need for further analyses to define dosing, transporter involvement, and brain exposure thresholds. Collectively, the available data position SCI as a compelling candidate for translational development, warranting further investigation into its therapeutic window and disease-modifying potential across neurological disorders. Full article

Opportunistic infections are a growing concern in medical mycology. In that context, Mucor circinelloides is recognized as an etiological agent of emerging life-threatening infections in humans. Furthermore, this biomass-degrading species is important in the biotechnological context due to its potential for enzyme discovery. In this work, we describe an in silico pipeline for the comprehensive characterization of the secretome of this species. Our analyses suggest that M. circinelloides encodes a diverse enzymatic repertoire, including multiple carbohydrate-active enzymes (CAZymes). Functional characterization of this secreted protein set identified candidate proteins with potential relevance for industrial application and virulence-related processes. Importantly, we extended this framework by integrating a sequence-based machine-learning (ML) approach for the prediction of extracellular vesicle (EV)-associated proteins. Using a Random Forest model trained on high-confidence EV datasets, we predicted a subset of candidate proteins in M. circinelloides and explored their functional distribution. The predicted EV proteome displayed a degree of similarity to experimentally characterized human EV proteomes, suggesting that the model is able to capture sequence-derived predictive signals. Overall, our results support the potential of ML as a scalable strategy to be integrated into the study of fungal EVs. This approach provided a foundation for research aimed at experimentally validating EV cargo and refining predictive models. Beyond M. circinelloides, we provide a framework that may be useful for future studies on EV biology across diverse fungi of medical and biotechnological interest. Full article

Several strategies can be employed for the identification of novel microbial lipases. Despite the increasing importance of metagenomics in bioprospecting, significant limitations in the expression of recombinant proteins, and lipases in particular, remain. Culture-based bioprospecting approaches are, therefore, still valuable. In this work, a collection of bacterial isolates, mainly of marine origin, was screened for lipase activity through a culture-based approach. Screening for lipolytic bacteria was performed in solid media containing olive oil emulsions and rhodamine B. Positive isolates were subsequently grown in liquid media, to confirm lipase production. Significant hydrolytic activity towards the triglyceride substrates tributyrin and triolein could be observed with the biomass produced, although no lipase activity could be detected in the culture supernatants. Six isolates presenting high activity were characterized as whole-cell biocatalysts, and all were found to be active at temperatures ranging between 25 and 65 °C, and at pH values between 6 and 10.5. Genomic analyses of two of these Gram-negative lipase-producing isolates revealed the presence of several hypothetical genes encoding for lipolytic enzymes, including outer cell-bound enzymes, predicted through the application of machine-learning tools. These natural isolates, containing cell-associated lipases, may therefore be of special interest for application as whole-cell biocatalysts. Full article

Changes in consumer behavior have intensified the demand for alternative protein sources, driving changes in food consumption patterns. At the same time, the increasing consumer awareness considering the health and environmental impacts in food systems, has stimulated interest in more functional and sustainable products. In this context, plant-based beverages (PBBs) have gained attention as potential alternatives to milk. This study was aimed at evaluating plant-based beverages as alternatives to cow’s milk, focusing on their nutritional composition, environmental impact, and technological challenges. Although cow’s milk has a high biological value and nutritional density, plant-based beverages present variable compositions, generally with lower levels of protein and minerals. However, they stand out for the presence of bioactive compounds and have a nutritional quality which can be improved through fortification strategies. From an environmental perspective, their production is associated with a substantially lower carbon footprint compared to dairy farming. Despite these advantages, the sector still faces technological challenges related to physicochemical stability and sensory acceptance due to complex residual flavors. This review highlights the need for improvements in terms of manufacturing processes and regulatory frameworks to establish these beverages as safe, nutritious, and sustainable options in the global market. Full article

Fungi of the genus Pleurotus are increasingly studied not only for their ecological versatility and saprotrophic capabilities but also for their potential in biotechnological applications such as nutrient bioaccumulation. As sustainable alternatives to animal protein sources, Pleurotus species combine high nutritional value with the ability to grow on agro-industrial residues. This review explores the bioaccumulation potential of Pleurotus species of essential compounds of biotechnological interest, particularly selenium and iron, focusing on applications in sustainable nutrition and functional ingredient development. Notably, the substrate composition can nearly double protein content, and selenium-enriched mushrooms can reach up to 858 µg/g without compromising biological efficiency, depending on the dose and chemical form. Similarly, iron biofortification achieved up to 4176 µg/g in P. pulmonarius with minimal productivity loss. Among the species analysed, P. ostreatus and P. eryngii stood out for their productivity and nutritional quality, while P. citrinopileatus recorded the highest protein content at 34.7% dry weight. Overall, mineral biofortification of Pleurotus spp. emerges as a promising strategy to support sustainable food systems, address global micronutrient deficiencies, and expand the biotechnological use of edible fungi. Full article

Research on the cataloging of microstructures and chemical compound localization in peanut hulls in relation to fungal tolerance remains limited. The hull (pericarp) is the first physical interface with the soil environment and may contribute to defense against fungal invasion. Here, hull microstructure and histochemical localization of alkaloid-like compounds, cellulose, lignin, starch, and total proteins were characterized across reproductive developmental stages R3–R6 in three commercially grown cultivars (Georgia-06G, Georgia-12Y, and Georgia-18RU). Stained sections were examined by light and fluorescence microscopy, and images were quantified in Fiji-ImageJ as stained area percentage. Among the compounds studied, the highest area percentages were observed at later stages (R5 and R6). Alkaloid-like compounds, cellulose, and starch were higher at the R5 stages of G-18 (9.61 ± 0.75), G-12Y (22.96 ± 5.84), and G-06 (6.31 ± 1.13) respectively, while lignin and total proteins were highest at the R6 stage of G-18 (respectively, 14.49 ± 1.43 and 13.90 ± 1.45). The lowest histochemical presence for most metabolites occurred in the early stages (R3–R4). This indicates that hull maturation is accompanied by increased physical (sclerenchyma and lignified cells) and biochemical (alkaloid-like compounds, proteins) features consistent with protective roles. As the analysis was based on representative sections and regions of interest (ROI)-level quantification, the results are intended to guide future studies on hull-mediated defense and breeding for Aspergillus tolerance. Full article

Root-knot nematodes (Meloidogyne javanica and M. incognita) constrain olive (Olea europaea L.) production and require safer alternatives to chemical nematicides. Despite the growing interest in microbial biocontrol agents, limited information is available on how application timing and microbial consortia influence nematode suppression and host biochemical responses in olive. This greenhouse study evaluated endophytic Trichoderma (T. harzianum) and Bacillus (B. subtilis), applied alone or in combination, either before or after nematode inoculation, to determine how biocontrol treatment timing influences nematode suppression, plant performance, and host biochemical responses. Across both nematode species, preventive application consistently outperformed curative application, and the combined treatment delivered the strongest overall protection. Preventive co-application reduced nematode infection, improved root and shoot growth, attenuated oxidative damage, and preserved chlorophyll more effectively than single-agent or post-inoculation treatments. Spectroscopic (Fourier Transform Infrared (FTIR)) and multivariate analyses further showed that effective treatments were associated with lower nematode-associated protein and lipid signals and stronger signatures of structural defense in root tissues. Although M. javanica caused greater physiological disruption than M. incognita, both species responded to the same general treatment pattern. These findings show that early establishment of microbial biocontrol agents is critical for durable suppression of root-knot nematodes in olive and supports preventive microbial consortia as a promising strategy for integrated nematode management. Full article

Background/Objectives: Diuretic resistance is a recognized complication in patients with heart failure (HF) and is associated with worse clinical outcomes; however, information regarding its frequency and associated factors in hospitalized patients in Mexico is limited. This study aimed to describe the frequency of diuretic resistance in patients hospitalized with HF in a hospital unit in western Mexico and to identify factors associated with diuretic resistance. Methods: This retrospective study used data obtained from clinical records. Patients older than 18 years with decompensated HF whose complete clinical records included the variables of interest were included. Patients were classified according to the presence or absence of diuretic resistance. Bivariate and multivariate analyses were performed to evaluate factors associated with diuretic resistance. Results: A total of 76 patients were analyzed, and the frequency of diuretic resistance was 35.5% (n = 27). In bivariate analysis, type 2 diabetes mellitus, chronic kidney disease, elevated creatinine, urea, blood urea nitrogen (BUN), and urine protein levels, decreased glomerular filtration rate (GFR) and serum albumin, and prior treatment with nonsteroidal anti-inflammatory drugs (NSAIDs) and angiotensin-converting enzyme inhibitors/angiotensin II receptor antagonists (ACEI/AARII) were significantly associated with diuretic resistance. In the multivariate logistic regression model, prior ACEI/AARII treatment, history of type 2 diabetes mellitus, BUN levels, and serum albumin levels remained independently associated with diuretic resistance classification. Conclusions: Diuretic resistance was frequent in this cohort of patients hospitalized with decompensated heart failure, and several clinical and biochemical factors were independently associated with its occurrence. These findings may help identify patients at higher risk of diuretic resistance, although they should be confirmed in future prospective studies. Full article

Binding affinity prediction is about estimating the degree to which a drug binds to a protein. Predicting the binding affinity between a drug and a protein in a computational process helps researchers filter huge libraries of compounds before performing expensive biochemical lab experiments. Currently, there is interest in predicting binding affinity through computational pattern recognition or machine learning methods instead of the classical physics-inspired methods, which are computationally intractable except for tiny chemical compounds. In the last five years, several machine learning-based methods have been presented, whose experimental validations have achieved increasing Pearson coefficients while trained and tested in the PDBBind 2016 and CASF 2016 databases, respectively. These methods have an important diversity of architectures that provide different properties. The aim of this paper is to discern which binary properties (existence or absence) of these methods make them return higher Pearson coefficients. Basically, the properties introduced are related to the level of structural knowledge, the presence of 3D information, and the introduction of the relationship between the drug and the protein in the input of the model. The t-test confirms that the important binary properties for having a high Pearson coefficient are the protein (or part of the protein) being represented and introduced into the computational model as a graph, the pocket and the drug–protein interaction being part of the input, and incorporating the distance between atoms and the type of chemical bonds into the model. Full article

Background/Objectives: Animal-source protein consumption in Saudi Arabia has increased substantially over the last two decades, raising concerns regarding its environmental impact in a country with among the highest per capita carbon emissions globally. Despite growing interest in sustainable diets, empirical evidence on dietary carbon footprint (CF) in Gulf Cooperation Council countries remains limited. This study aimed to quantify the CF associated with the consumption of animal- and plant-based protein foods among Saudi adults and to identify sociodemographic and lifestyle predictors of dietary CF, with attention to sex differences. Methods: A cross-sectional study was conducted among 1624 Saudi adults (47.1% males; 52.9% females). A newly developed, expert-reviewed, and pilot-tested food frequency questionnaire covering 21 protein-containing food items (13 animal-based; 8 plant-based) was used to estimate daily intake. CF values were calculated using Life Cycle Assessment-derived greenhouse gas emission factors (kgCO₂e/kg food) obtained from peer-reviewed sources. Sex-stratified multiple linear regression models and a pooled sex × animal-source protein food interaction model was used to identify independent predictors of daily CF. Results: Animal-source protein foods contributed 45,641.8 kgCO₂e/week to cumulative CF—a 64-fold excess over plant-based sources (708.33 kgCO₂e/week). Mean individual protein-food CF was 4.07 kgCO₂e/day, of which 98.5% derived from animal sources. Lamb and beef carried the highest emission intensities; nuts the lowest. Animal-source intake was the strongest independent predictor of CF in both sexes, with a significantly stronger association in males than females. High consumers substantially exceeded EAT–Lancet red meat targets across all consumption strata. Conclusions: Red meat dominates protein-food-related GHG emissions among Saudi adults. Even a partial dietary shift toward plant-based proteins, embedded within a coordinated food-system transformation framework, could substantially reduce per capita emissions in alignment with Saudi Vision 2030 and One Health targets. Full article

The application of silk sericin as a polymeric biomaterial has recently gained interest, although its film was found to be fragile, exhibiting brittleness when subjected to relatively slight stress, and it also displayed higher water solubility. This study focused on the enhanced physico-mechanical properties of the three films obtained by the crosslinking of sericin protein from three silkworm cocoons with poly (vinyl alcohol) (PVA) to reduce phase separation and solubilization of the films by promoting miscibility between sericin and PVA. The findings demonstrated how crosslinking with glutaraldehyde enhanced thermal stability and tensile strength and controlled the solubility of the three sericin–PVA films. The sericin from G. postica, G. rufobrunnea, and Argema mimosae is composed of serine, aspartic acid, and glutamic acid, which make up 80% of the total polar amino acids. X-ray diffraction (XRD) patterns showed that sericin–PVA films have semicrystalline features, representing amorphous and crystalline regions. The XRD results also indicated that the Saturniidae sericin–PVA film (Sat-SPF), Gonometa postica sericin–PVA film (GP-SPF), and Gonometa rufobrunnea sericin–PVA film (GR-SPF) have crystallinity percentages of 66.4%, 55.9%, and 17.7%, respectively. The moisture vapor transmission rate (MVTR) values observed in this study ranged from 991.2 to 5160 g/m²/24 h, indicating that these films can effectively regulate moisture levels in wounds. The swelling capacity of the three sericin–PVA composite films depends on the crosslinking density of their structures and was also found to be sensitive to the pH of the aqueous media, demonstrating their hydrophilic nature and potential use in drug delivery systems. The water vapor permeability of sericin–PVA films increased with higher environmental relative humidity (RH) and moisture content within the films. The elongation at break for GP-SPF (107.2% ± 3.1) and Sat-SPF (73.0% ± 4.1) was significantly higher than in GR-SPF (29.3% ± 2.3). However, their tensile strength and elastic modulus were lower than those of GR-SPF. These results show that the number of polar groups (amino and hydroxyl groups) from both sericin and PVA influences all the properties of the sericin–PVA composite films. The three sericin–PVA solutions were found to have antibacterial efficacy against three Gram-positive and one Gram-negative bacteria over 24 h. Scanning electron microscopy (SEM) images revealed a rough surface with a granular network pattern, which supports the potential use of sericin–PVA films for cell adhesion and proliferation, which are essential for biomedical wound dressing applications. Full article

Extracellular vesicles (EVs) have emerged as key mediators of intercellular communication in the brain, with glial cell-derived EVs increasingly recognized for their roles in maintaining brain homeostasis and contributing to the progression of neurodegenerative diseases. By transferring a diverse cargo of bioactive molecules, including proteins, RNAs, and organelles, EVs influence recipient cell behavior and overall brain function. In neurodegenerative conditions, glial EVs can either propagate pathogenic signals or deliver neuroprotective and regenerative cues, depending on their cellular origin and molecular composition. This context-dependent heterogeneity highlights the need for physiologically relevant human models to investigate EVs biology. Human induced pluripotent stem cell (iPSC)-derived glial models provide a disease-relevant platform, as they recapitulate key pathological features of Alzheimer’s disease (AD), Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS). When further integrated with brain organoid platforms, these iPSC-based systems enable the generation of three-dimensional environments that closely resemble in vivo EVs dynamics. Importantly, glial EVs can modulate cellular pathways involved in neuronal survival and function. Indeed, their potential to interact with and, under specific experimental conditions, traverse the blood–brain barrier (BBB) has contributed to growing interest in their application for biomarker discovery and therapeutic development. Engineered and patient-specific EVs derived from iPSCs are emerging as promising tools for targeted, cell type-specific, therapeutic approaches, although their clinical applicability still requires further validation. This review discusses the emerging evidence supporting the dual role of iPSC-derived glial EVs in health and disease, underscores the translational potential of iPSC-based platforms for mechanistic studies, and outlines their promise as precision medicine tools for diagnostics and therapy. Full article

Sarcopenia is a progressive, age-related musculoskeletal disorder characterized by the loss of skeletal muscle mass, strength, and physical performance, which contributes to frailty, disability, and mortality in older adults. Although resistance exercise and optimized protein intake remain first-line interventions, effective pharmacological therapies are limited, highlighting the need for novel adjunctive strategies. Increasing interest has focused on phytochemicals, plant-derived bioactive compounds with antioxidant, anti-inflammatory, and metabolic regulatory properties that may target multiple mechanisms underlying muscle aging. This review summarizes the molecular and translational potential of phytochemicals in sarcopenia management. Experimental and emerging clinical evidence indicates that flavonoids, polyphenols, alkaloids, and terpenoids modulate key pathways involved in sarcopenia pathogenesis, including PI3K/Akt/mTOR-mediated anabolic signaling, AMPK–SIRT3–PGC-1α-dependent mitochondrial biogenesis, NF-κB-driven inflammation, oxidative stress responses, autophagy, and satellite cell function. Through these pleiotropic effects, phytochemicals may attenuate the anabolic resistance, mitochondrial dysfunction, chronic inflammation, and impaired muscle regeneration associated with aging. Despite promising mechanistic evidence, clinical translation remains limited by poor bioavailability, variability in formulation and dosing, a lack of long-term randomized trials, and inconsistent functional outcome measures. Current evidence suggests that phytochemicals are most effective when integrated with resistance exercise and nutritional support rather than used as stand-alone therapies. Overall, phytochemicals represent promising complementary candidates for sarcopenia prevention and management. Future studies should prioritize standardized formulations, biomarker-guided approaches, and rigorously designed clinical trials focused on clinically meaningful functional outcomes to establish their efficacy, safety, and translational relevance in aging populations. Full article

The increasing demand for sustainable and health-oriented dairy and alternative products has enhanced interest in reducing or modifying fat in cheese systems. However, such modifications often lead to undesirable changes in texture and flavor, highlighting the multifunctional roles of milk fat within the cheese matrix. Rather than serving solely as a compositional component, milk fat contributes fundamentally to structure organization and flavor development through its physicochemical properties, interactions with the protein network, and lipid-derived pathways. This review examines these roles from a mechanistic perspective and evaluates emerging lipid structuring approaches for texture modulation, while also discussing complementary approaches with potential to address flavor attributes. Collectively, it provides insights for rational formulation and guides future research toward the design of improved dairy and alternative cheese products. Full article