Search Results (253)

Background and Objectives: The management of type 2 diabetes (T2D) extends beyond glycemic control, requiring a more global strategy that includes optimization of body composition, even more so in the context of sarcopenia and visceral adiposity, as they contribute to poor outcomes. Past reviews have typically been focused on weight reduction or glycemic effectiveness, with limited inclusion of new therapies’ effects on muscle and fat distribution. In addition, the emergence of incretin-based therapies and dual agonists such as tirzepatide requires an updated synthesis of their impacts on body composition. This review attempts to bridge the gap by taking a systematic approach to how current blood-glucose lowering therapies affect lean body mass, fat mass, and the risk of sarcopenia in T2D patients. Materials and Methods: Between January 2015 and March 2025, we conducted a narrative review by searching the PubMed, Scopus, and Web of Science databases for English-language articles. The keywords were combinations of the following: “type 2 diabetes,” “lean body mass,” “fat mass,” “body composition,” “sarcopenia,” “GLP-1 receptor agonists,” “SGLT2 inhibitors,” “tirzepatide,” and “antidiabetic pharmacotherapy.” Reference lists were searched manually as well. The highest precedence was assigned to studies that aimed at adult type 2 diabetic subjects and reported body composition results. Inclusion criteria for studies were: (1) type 2 diabetic mellitus adult patients and (2) reporting measures of body composition (e.g., lean body mass, fat mass, or muscle function). We prioritized randomized controlled trials and large observational studies and excluded mixed diabetic populations, non-pharmacological interventions only, and poor reporting of body composition. Results: Metformin was widely found to be weight-neutral with minimal effects on muscle mass. Insulin therapy, being an anabolic hormone, often leads to fat mass accumulation and increases the risk of sarcopenic obesity. Incretin-based therapies induced substantial weight loss, mostly from fat mass. Notable results were observed in studies with tirzepatide, demonstrating superior reduction not only in fat mass, but also in visceral fat. Sodium-glucose cotransporter 2 inhibitors (SGLT2 inhibitors) promote fat loss but are associated with a small yet significant decrease in lean muscle mass. Conclusions: Blood-glucose lowering therapies demonstrated clinically relevant effects on body composition. Treatment should be personalized, balancing glycemic control, cardiovascular, and renal benefits, together with optimal impact on muscle mass along with glycemic, cardiovascular, and renal benefits. Full article

The depletion of water resources caused by climate change and human activities is a pressing global issue. Lake Ereen is one of the ten natural landmarks of the Gobi-Altai of western Mongolia is included in the list of “important areas for birds” recognized by the international organization Birdlife. However, the construction of the Taishir Hydroelectric Power Station, aimed at supplying electricity to the western provinces of Mongolia, had a detrimental effect on the flow of the Zavkhan River, resulting in a drying-up and pollution of Lake Ereen, which relies on the river as its water source. This study assesses the pollution levels in Ereen Lake and determines the feasibility of its rehabilitation by redirecting the flow of the Zavkhan River. Field studies included the analysis of water quality, sediment contamination, and the composition of flora. The results show that the concentrations of ammonium, chlorine, fluorine, and sulfate in the lake water exceed the permissible levels set by the Mongolian standard. Analyses of elements from sediments revealed elevated levels of arsenic, chromium, and copper, exceeding international sediment quality guidelines and posing risks to biological organisms. Furthermore, several species of diatoms indicative of polluted water were discovered. Lake Ereen is currently in a eutrophic state and, based on a water quality index (WQI) of 49.4, also in a “polluted” state. Mass balance calculations and box model analysis determined the period of pollutant replacement for two restoration options: drying-up and complete removal of contaminated sediments and plants vs. dilution-flushing without direct interventions in the lake. We recommend the latter being the most efficient, eco-friendly, and cost-effective approach to rehabilitate Lake Ereen. Full article

Background: The gut microbiota is increasingly recognized as a key modulator in obesity management, influencing host energy balance, lipid metabolism, and inflammatory pathways. With obesity prevalence continuing to rise globally, dietary interventions that promote beneficial microbial shifts are essential for enhancing weight loss outcomes and long-term health. Objective: This study investigated the effects of the multicomponent Weight Loss Maintenance 3 Phases Program (WLM3P), which integrates caloric restriction, a high-protein low-carbohydrate diet, time-restricted eating (10h TRE), dietary supplementation (prebiotics and phytochemicals), and digital app-based support on gut microbiota composition compared to a standard low-carbohydrate diet (LCD) in adults with obesity. The analysis focused exclusively on the 6-month weight loss period corresponding to Phases 1 and 2 of the WLM3P intervention. Methods: In this sub-analysis of a randomized controlled trial (ClinicalTrials.gov Identifier: NCT04192357), 58 adults with obesity (BMI 30.0–39.9 kg/m²) were randomized to the WLM3P (n = 29) or LCD (n = 29) groups. Stool samples were collected at baseline and 6 months for 16S rRNA sequencing. Alpha and beta diversity were assessed, and genus-level differential abundance was determined using EdgeR and LEfSe. Associations between microbial taxa and clinical outcomes were evaluated using regression models. Results: After 6-month, the WLM3P group showed a significant increase in alpha diversity (p = 0.03) and a significant change in beta diversity (p < 0.01), while no significant changes were observed in the LCD group. Differential abundance analysis revealed specific microbial signatures in WLM3P participants, including increased levels of Faecalibacterium. Notably, higher Faecalibacterium abundance was associated with greater reductions in fat mass (kg, %) and visceral adiposity (cm²) in the WLM3P group compared to LCD (p < 0.01). Conclusions: These findings suggest a potential microbiota-mediated mechanism in weight loss, where Faecalibacterium may enhance fat reduction effectiveness in the context of the WLM3P intervention. Full article

Driven by the urgent demand for low-frequency vibration and noise control in engineering scenarios such as automobiles, acoustic metamaterials (AMs), as a new class of functional materials, have demonstrated significant application potential. This paper proposes a low-frequency band gap optimization design method for local resonance acoustic metamaterials (LRAMs) based on a multi-objective genetic algorithm. Within a COMSOL Multiphysics 6.2 with MATLAB R2024b co-simulation framework, a parameterized unit cell model of the metamaterial is constructed. The optimization process targets two objectives: minimizing the band gap’s deviation from the target and reducing the structural mass. A multi-objective fitness function is formulated by incorporating the band gap deviation and structural mass constraints, and non-dominated sorting genetic algorithm II (NSGA-II) is employed to perform a global search over the geometric parameters of the resonant unit. The resulting Pareto-optimal solution set achieves a unit cell mass as low as 26.49 g under the constraint that the band gap deviation does not exceed 2 Hz. The results of experimental validation show that the optimized metamaterial configuration reduces the peak of the low-frequency frequency response function (FRF) at 63 Hz by up to 75% in a car door structure. Furthermore, the simulation predictions exhibit good agreement with the experimental measurements, confirming the effectiveness and reliability of the proposed method in engineering applications. The proposed multi-objective optimization framework is highly general and extensible and capable of effectively balancing between the acoustic performance and structural mass, thus providing an efficient engineering solution for low-frequency noise control problems. Full article

Background: Transthoracic echocardiography (TTE) is the primary imaging modality to assess cardiac morphology and function. In athletes, distinguishing physiological adaptations from pathological changes is essential. This study aimed to evaluate long-term cardiac structural and functional changes in professional soccer players. Methods: This retrospective study included 20 healthy male professional soccer players (mean age 21.2 ± 3.4 years) from the German first division, examined annually from 2016 to 2024 (mean follow-up 5.6 ± 2.0 years). TTE parameters associated with the “athlete’s heart” were assessed, including left ventricular end-diastolic diameter (LVEDD), interventricular septal thickness (IVSD), relative wall thickness (RWT), indexed LV mass (LVMi), and left atrial volume index (LAVi), along with 3D-derived LV and RV volumes. Advanced deformation imaging included global longitudinal strain (GLS), right ventricular strain (RVS), and left/right atrial reservoir strain (LASr and RASr, respectively). Baseline and final follow-up values were compared. Results: No significant changes were observed over time in conventional or advanced echocardiographic parameters (e.g., LVEDD: 54.5 ± 3.1 mm vs. 54.6 ± 3.9 mm; p = 0.868; GLS: −18.7% ± 2.2% vs. −18.4% ± 1.9%; p = 0.670). Ventricular volumes and strain values also remained stable throughout follow-up. Conclusions: Over a mean follow-up of more than five years, professional soccer players showed stable cardiac morphology and function without evidence of pathological remodeling. These findings support the concept that long-term high-level training in mixed-discipline sports leads to balanced, physiological cardiac adaptation. Full article

Background/Objectives: Trace minerals (TMs), both essential and toxic, are integral to human physiology, participating in enzymatic reactions, oxidative balance, immune function, and the modulation of chronic disease risk. Despite their importance, imbalances due to deficiencies or toxic exposures are widespread globally. While low-income countries often face overt deficiencies and environmental contamination, middle- and high-income populations increasingly deal with subclinical deficits and chronic toxic metal exposure. This review aims to explore the relevance of serum as a matrix for evaluating TM status across diverse clinical and epidemiological, geographic, and demographic settings. Methods: A narrative literature review was conducted focusing on the physiological roles, health impacts, and current biomarker approaches for key essential (e.g., zinc, copper, selenium) and toxic (e.g., lead, mercury, cadmium, arsenic) trace elements. Particular emphasis was placed on studies utilizing serum analysis and on recent advances in multi-element detection using inductively coupled plasma mass spectrometry (ICP-MS). Results: Serum was identified as a versatile and informative matrix for TM assessment, offering advantages in terms of clinical accessibility, biomarker reliability, and capacity for the simultaneous quantification of multiple elements. For essential TMs, serum levels reflect nutritional status with reasonable accuracy. For toxic elements, detection depends on instrument sensitivity, but serum can still provide valuable exposure data. The method’s scalability supports applications ranging from public health surveillance to individualized patient care. Conclusions: Serum trace mineral analysis is a practical and scalable approach for nutritional assessment and exposure monitoring. Integrating it into clinical practice and public health strategies can improve the early detection of imbalances, guide interventions such as nutritional supplementation, dietary modifications, and exposure mitigation efforts. This approach also supports advanced personalized nutrition and preventive care. Full article

Groundwater storage refers to the water stored in the pore spaces of underground aquifers, which has been increasingly affected by both climate change and anthropogenic activities in recent decades. Therefore, monitoring their changes and the factors that affect it is of great importance. Although the influence of natural factors on groundwater is well-recognized, the impact of human activities, despite being a major contributor to its change, has been less explored due to the challenges in measuring such effects. To address this gap, our study employed an integrated approach using remote sensing and the Google Earth Engine (GEE) cloud-free platform to analyze the effects of various anthropogenic factors such as built-up areas, cropland, and surface water on groundwater storage in the Lake Urmia Basin (LUB), Iran. Key anthropogenic variables and groundwater data were pre-processed and analyzed in GEE for the period from 2000 to 2022. The processes linking these variables to groundwater storage were considered. Built-up area expansion often increases groundwater extraction and reduces recharge due to impervious surfaces. Cropland growth raises irrigation demand, especially in semi-arid areas like the LUB, leading to higher groundwater use. In contrast, surface water bodies can supplement water supply or enhance recharge. The results were then exported to XLSTAT software2019, and statistical analysis was conducted using the Mann–Kendall (MK) non-parametric trend test on the variables to investigate their potential relationships with groundwater storage. In this study, groundwater storage refers to variations in groundwater storage anomalies, estimated using outputs from the Global Land Data Assimilation System (GLDAS) model. Specifically, these anomalies are derived as the residual component of the terrestrial water budget, after accounting for soil moisture, snow water equivalent, and canopy water storage. The results revealed a strong negative correlation between built-up areas and groundwater storage, with a correlation coefficient of −1.00. Similarly, a notable negative correlation was found between the cropland area and groundwater storage (correlation coefficient: −0.85). Conversely, surface water availability showed a strong positive correlation with groundwater storage, with a correlation coefficient of 0.87, highlighting the direct impact of surface water reduction on groundwater storage. Furthermore, our findings demonstrated a reduction of 168.21 mm (millimeters) in groundwater storage from 2003 to 2022. GLDAS represents storage components, including groundwater storage, in units of water depth (mm) over each grid cell, employing a unit-area, mass balance approach. Although storage is conceptually a volumetric quantity, expressing it as depth allows for spatial comparison and enables conversion to volume by multiplying by the corresponding surface area. Full article

This study proposes an RBF-PSO hybrid framework for efficient inversion analysis of hydration heat parameters in mass concrete temperature fields, addressing the computational inefficiency and accuracy limitations of traditional methods. By integrating a Radial Basis Function (RBF) surrogate model with Particle Swarm Optimization (PSO), the method reduces reliance on costly finite element simulations while maintaining global search capabilities. Three objective functions—integral-type (F₁), feature-driven (F₂), and hybrid (F₃)—were systematically compared using experimental data from a C40 concrete specimen under controlled curing. The hybrid F₃, incorporating Dynamic Time Warping (DTW) for elastic time alignment and feature penalties for engineering-critical metrics, achieved superior performance with a 74% reduction in the prediction error (mean MAE = 1.0 °C) and <2% parameter identification errors, resolving the phase mismatches inherent in F₂ and avoiding F₁’s prohibitive computational costs (498 FEM calls). Comparative benchmarking against non-surrogate optimizers (PSO, CMA-ES) confirmed a 2.8–4.6× acceleration while maintaining accuracy. Sensitivity analysis identified the ultimate adiabatic temperature rise as the dominant parameter (78% variance contribution), followed by synergistic interactions between hydration rate parameters, and indirect coupling effects of boundary correction coefficients. These findings guided a phased optimization strategy, as follows: prioritizing high-precision calibration of dominant parameters while relaxing constraints on low-sensitivity variables, thereby balancing accuracy and computational efficiency. The framework establishes a closed-loop “monitoring-simulation-optimization” system, enabling real-time temperature prediction and dynamic curing strategy adjustments for heat stress mitigation. Robustness analysis under simulated sensor noise (σ ≤ 2.0 °C) validated operational reliability in field conditions. Validated through multi-sensor field data, this work advances computational intelligence applications in thermomechanical systems, offering a robust paradigm for parameter inversion in large-scale concrete structures and multi-physics coupling problems. Full article

This study systematically investigates the utilization of marble industry waste—waste marble powder (WMP) as partial cement replacement and waste marble aggregates (WMA) as partial fine aggregate replacement—in self-compacting concrete (SCC). A detailed experimental program evaluated the effects of various replacement levels (5%, 10%, and 20% for WMP; 20%, 30%, and 40% for WMA) on compressive strength and durability, particularly resistance to aggressive sulfuric acid environments. Results indicated that a 5% WMP replacement increased compressive strength by 4.9%, attributed primarily to the filler effect, whereas higher levels (10–20%) led to strength reductions due to limited pozzolanic activity and cement dilution. In contrast, WMA replacement consistently enhanced strength (maximum increase of 11.5% at 30% substitution) due to improved particle packing and aggregate-paste interface densification. Durability tests revealed significantly reduced compressive strength losses and mass loss in marble-containing mixtures compared to control samples, with optimal acid resistance observed at 20% WMP and 40% WMA replacements. A comprehensive life cycle assessment demonstrated notable reductions in environmental impacts, including up to 20% decreases in Global Warming Potential (GWP) at 20% WMP replacement. A desirability-based eco-cost-mechanical optimization—simultaneously integrating mechanical strength, environmental indicators, and production cost—identified the 10% WMP substitution mix as the most sustainable option, achieving optimal balance among key performance criteria. These findings underscore the significant potential for marble waste reuse in SCC, promoting environmental sustainability, resource efficiency, and improved concrete durability in chemically aggressive environments. Full article

Staphylococcus aureus is a leading cause of foodborne intoxication globally, driven by its heat-stable enterotoxins (SEs), which pose significant public health risks. This review critically evaluates modern and traditional methodologies for detecting S. aureus and its enterotoxins in food matrices, emphasizing their principles, applications, and limitations. The review includes a dedicated section on sample preparation and pretreatment methods for diverse food substrates, addressing a critical gap in practical applications. Immunological techniques, including ELISA and lateral flow assays, offer rapid on-site screening but face matrix interference and variable sensitivity challenges. Molecular methods, such as PCR and isothermal amplification, provide high specificity and speed for bacterial and toxin gene detection but cannot confirm functional toxin production. Sequencing-based approaches (e.g., WGS and MLST) deliver unparalleled genetic resolution for outbreak tracing but require advanced infrastructure. Emerging biosensor technologies leverage nanomaterials and biorecognition elements for ultra-sensitive real-time detection, although scalability and matrix effects remain hurdles. Mass spectrometry (MALDI-TOF MS) ensures rapid species identification but depends on pre-isolated colonies. Traditional microbiological methods, while foundational, lack the precision and speed of molecular alternatives. The review underscores the necessity of context-driven method selection, balancing speed, sensitivity, and resource availability. Innovations in multiplexing, automation, AI-based methods, and integration of complementary techniques are highlighted as pivotal for advancing food safety surveillance. Standardized validation protocols and improved reporting of performance metrics are urgently needed to enhance cross-method comparability and reliability in outbreak settings. Full article

Background: Obesity is a major global public health issue with no fully satisfactory solutions. Most nutritional interventions rely on caloric restriction, with varying degrees of success. Very low-calorie ketogenic diets (VLCKD) have demonstrated rapid and sustained weight loss by inducing ketone bodies through lipolysis, reducing appetite, and preserving lean mass while maintaining metabolic health. Methods: A prospective clinical study analyzed sociodemographic, anthropometric, and adherence data from 7775 patients undergoing a multidisciplinary nutritional single-arm intervention based on a commercial weight-loss program. This method, using protein preparations with a specific balanced nutritional profile, aimed to identify key predictors of weight-loss success and classify population phenotypes with shared baseline characteristics and weight-loss patterns to optimize treatment personalization. Results: Statistical and machine learning analyses revealed that male gender (−9.2 kg vs. −5.9 kg) and higher initial body weight (−8.9 kg vs. −4.0 kg) strongly predict greater weight loss on a VLCKD, while age has a lesser impact. Two distinct population clusters emerged, differing in age, sex, follow-up duration, and medical visits, demonstrating unique weight-loss success patterns. These clusters help define individualized strategies for optimizing outcomes. Conclusions: These findings translationally support associations with the efficacy of a multidisciplinary VLCK weight-loss program and highlight predictors of success. Recognizing variables such as sex, age, and initial weight enhances the potential for a precision-based approach in obesity management, enabling more tailored and effective treatments for diverse patient profiles and prescribe weight loss personalized recommendations. Full article

Creole avocado is the second most widely produced and consumed variety of avocado globally. Due to its commercialization, limited studies have explored its potential for sustainable applications in biorefinery, particularly focusing on reusing the significant amount of waste generated during its consumption. This research evaluates thermodynamic energy losses of a Creole avocado extractive-based biorefinery, which are of critical importance during the fruit valorization process to determine the efficiency and possibilities of optimization, as well as sustainability impacts, through an exergy balance using computer-aided process engineering. The proposed method utilizes the whole fruit to produce three primary bioproducts, with a focus on implementation in the Montes de María region of Colombia. Following the extended mass and energy balance, an in-depth exergetic analysis was conducted, revealing that all process stages exhibited an exergetic efficiency exceeding 50%. The irreversibilities of the process were calculated as 7763.74 MJ/h, the total waste exergy was 2924.42 MJ/h, and the exergy from industrial waste amounted to 7800.42 MJ/h. These findings highlight the potential for optimizing the sustainability of avocado-based production systems through computer-aided analysis as an effective method. This approach accurately identifies exergy losses at each stage, providing precise numerical data and graphical representations. Additionally, it underscores not only the environmental benefits but also the contribution of these systems to enhancing energy efficiency in agro-industrial applications. Full article

In response to the growing demand for sustainable and performance-driven building design, this study proposes an integrated digital methodology that combines Building Information Modeling (BIM), parametric scripting, and multi-criteria decision-making (MCDM) to optimize external wall assemblies. The approach leverages Autodesk Revit and Dynamo to automate the parametrization of insulation thickness while ensuring compliance with regulatory thresholds for thermal transmittance and surface mass. Acoustic performance is estimated using ECHO software, and a Weighted Sum Model (WSM) is applied to evaluate and rank configurations based on four criteria: economic cost, Global Warming Potential (GWP), embodied energy, and acoustic insulation. A case study involving 24 wall assemblies—generated from eight base stratigraphies and three insulation materials—demonstrates the method’s ability to balance environmental impact, occupant comfort, and construction feasibility. The results indicate that natural and bio-based materials, such as rammed earth and cork, offer the best overall performance, while conventional systems remain competitive in terms of cost. The proposed workflow reduces design time, increases transparency, and supports informed decision-making during early design stages. This research contributes to the digitalization of sustainability assessment in architecture by promoting integrative, replicable, and regulation-aligned practices for low-impact building envelopes. Full article

Bone remodeling is a dynamic biological process that preserves bone strength and structure through the coordinated actions of osteoblasts, osteoclasts, osteocytes, and bone mass density. Traditional models based on ordinary differential equations often fail to capture the memory-dependent nature of these interactions. In this study, we propose a novel mathematical model of bone remodeling using the Atangana–Baleanu–Caputo fractional derivative, which accounts for the non-local and hereditary characteristics of biological systems. The model introduces fractional-order dynamics into a previously established ODE framework while maintaining the intrinsic symmetry between bone-forming and bone-resorbing mechanisms, as well as the balance mediated by porosity-related feedback. We establish the existence, uniqueness, and positivity of solutions, and analyze the equilibrium points and their global stability using a Lyapunov function. Numerical simulations under various fractional orders demonstrate symmetric convergence toward equilibrium across all biological variables. The results confirm that fractional-order modeling provides a more accurate and balanced representation of bone remodeling and reveal the underlying symmetry in the regulation of bone tissue. This work contributes to the growing use of fractional calculus in modeling physiological processes and highlights the importance of symmetry in both mathematical structure and biological behavior. Full article

In the context of global population aging, identifying reliable, objective tools to assess physical function and postural stability in older adults is increasingly important to mitigate fall risk. This study presents a non-contact platform that uses a Microsoft Azure Kinect depth camera to evaluate functional performance related to lower-limb muscular capacity and static balance through self-selected depth squats and four progressively challenging stances (feet apart, feet together, semitandem, and tandem). By applying markerless motion capture algorithms, the system provides key biomechanical parameters such as center of mass displacement, knee angles, and sway trajectories. A comparison of older and younger individuals showed that the older group tended to perform shallower squats and exhibit greater mediolateral and anteroposterior sway, aligning with age-related declines in strength and postural control. Longitudinal tracking also illustrated how performance varied following a fall, indicating potential for ongoing risk assessment. Notably, in 30 s balance trials, the first 10 s often captured meaningful differences in stability, suggesting that short-duration stance tests can reliably detect early signs of imbalance. These findings highlight the feasibility of low-cost, user-friendly depth-camera technologies to complement traditional clinical measures and guide targeted fall-prevention strategies in older populations. Full article