Search Results (6,279)

The rapid deployment of distributed photovoltaic (PV) systems has increased renewable energy generation while introducing operational challenges for distribution networks, particularly surplus PV export during periods of high solar production. This study proposes a measurement-driven, rule-based smart electric vehicle (EV) charging framework to enhance the local utilization of surplus PV generation using real operational measurements acquired from a Siemens PAC3200T power quality analyzer installed at the point of common coupling (PCC) of the Far’ata–Immatain distribution feeder in Palestine. The proposed framework coordinates EV charging based on representative surplus PV operating states and PCC operating conditions while considering user charging requirements and network operational limits. Four MATLAB-based simulation scenarios representing increasing EV penetration were evaluated. The results demonstrate progressive reductions in reverse active power export together with corresponding improvements in local PV utilization as EV penetration increases. Under the highest investigated charging scenario, up to 200 kW of the investigated surplus PV generation was locally utilized, and reverse active power export was eliminated under the investigated operating conditions. Overall, the proposed framework provides a practical and scalable approach for improving renewable energy utilization in data-limited distribution networks without requiring comprehensive feeder models or immediate network reinforcement. Full article

Background/Objectives: Human physiological evidence for functional clothing is limited, and garment changes may reflect ordinary material or measurement effects. We described surface-temperature and heart rate variability (HRV) observations before and after wearing black-silica-containing clothing and quantified paired changes and between-participant dispersion. Methods: Ten adults enrolled as healthy volunteers completed this single-center, non-randomized, unblinded, uncontrolled, fixed-order, single-group before–after pilot protocol. No physically matched control textile was used. No directional hypothesis or single primary outcome was prospectively specified. Exploratory domains comprised abdominal and leg surface temperature and eight RR interval (RRI)-derived HRV indices. All participants were analyzed; a post hoc n = 9 quality-control sensitivity analysis excluded one participant with a short post-wearing RRI segment. Effect estimates, 95% confidence intervals (CIs), and Holm-adjusted p values were reported. Between-participant dispersion was secondary and exploratory. Results: Leg surface temperature showed a modest increase of 0.668 °C (95% CI −0.001 to 1.336; raw p = 0.050; Holm p = 0.100); abdominal temperature changed by 0.007 °C (95% CI −0.447 to 0.462). No paired HRV outcome retained support after correction (all Holm p ≥ 0.797). In the secondary dispersion analysis, total power had an after/before log-scale SD ratio of 0.612 (bootstrap 95% CI 0.347 to 0.861; Holm p = 0.031); no dispersion outcome retained support in the n = 9 sensitivity analysis. Conclusions: This small uncontrolled pilot provides hypothesis-generating observations but cannot isolate an effect attributable specifically to black silica or demonstrate autonomic benefit, therapeutic action, or product efficacy. Confirmation requires an adequately powered, randomized, participant-blinded crossover study using physically matched garments and standardized measurement conditions. Full article

Under varying demand, pump states, load allocation, speed settings, and supply pressure are strongly coupled in parallel pumping systems. This study develops a steady-state energy-efficiency optimization framework for homogeneous and heterogeneous three-branch systems by integrating continuous pump-performance modeling, hard hydraulic-feasibility handling, mixed-variable optimization, and demand-dependent pressure regulation. An improved snake optimizer (ISO) is constructed through targeted strategies for population initialization, global exploration, and local exploitation. Flow–head and flow–power models established from LVR5-5 and CDL3-50 experimental data achieved a total-power MAPE of 2.36% and R² = 0.9972 over 40 implemented steady-state schemes. Deterministic constrained solutions for all effective pump-state combinations were used as references for the pumping-system optimization. Under the same budget of 21,000 function evaluations, ISO, SO, PSO, DE, and GA completed 1500 independent runs; ISO achieved the best overall search performance, with all 300 runs reaching the 0.1% neighborhood of the reference solution and the lowest mean NAUC and final gaps. Using ISO for both pressure-control modes, variable-pressure operation reduced mean power consumption by 10.92% and 7.51% for the homogeneous and heterogeneous systems, respectively, relative to constant-pressure operation under the same minimum service-pressure requirement. The results demonstrate that combining high-quality mixed-variable optimization with demand-dependent pressure regulation can effectively improve the steady-state energy efficiency of parallel pumping systems. Full article

Background/Objectives: Premium intraocular lens (IOL) implantation after laser vision correction (LVC) is increasingly common among post-refractive patients seeking cataract and presbyopia management. Therefore, this review aimed to provide a comprehensive updated synthesis of the challenges and outcomes of premium IOL implantation in post-refractive eyes, including visual quality, patient satisfaction, complications, and practical management approaches for patient selection, refractive surprises, and dysphotopsias. Methods and Search Strategies: In this narrative review, relevant articles published in English (January 2016–January 2026) were searched for using appropriate keywords and database indexing terms. The databases used in this review were PubMed/MEDLINE, Embase, Web of Science, and Scopus. Results: A total of 127 studies were included. Across post-LVC subgroups, including LASIK, PRK, SMILE, RK, and hyperopic ablation, premium IOL implantation provided good distance and intermediate-range vision, significant spectacle independence, and high patient satisfaction. Modern techniques, including total keratometry, posterior corneal evaluation, swept-source optical coherence tomography biometry, current post-refractive equations, multi-method comparison, and selective intraoperative aberrometry, have enhanced refractive targeting, with ±0.50 D of target refraction commonly used as a key accuracy benchmark, though not all outliers have been eliminated. However, several key challenges persist, including accurate corneal power estimation, personalization, and accurate lens position, which predispose patients to refractive surprises and a high frequency of dysphotopsias. Furthermore, there is heterogeneity in identifying visual outcomes and vision quality across studies. Conclusions: This review suggests that successful premium IOL implantation in patients after LVC requires individualized planning and structured management protocols. Future studies should standardize quality-of-vision outcomes that compare emerging optics, adjustable technologies, and AI-assisted prediction across post-refractive subgroups. Full article

Aging frailty is a multifactorial geriatric syndrome characterized by reduced physiological reserve across multiple interrelated systems, leading to increased vulnerability to adverse health outcomes. Mesenchymal stem cells (MSCs) have emerged as a potential therapeutic intervention due to their immunomodulatory and regenerative properties. This systematic review aimed to evaluate the available clinical evidence regarding the safety and efficacy of MSC administration in individuals with aging frailty. A systematic literature search was conducted in PubMed, Scopus, and the Cochrane Library from database inception to 15 April 2026. Only randomized controlled trials (RCTs) were eligible. Data were extracted according to study design, participants’ characteristics, MSC source and dosing, safety outcomes, functional performance measures, quality of life (QoL) indices, and inflammatory, immune, and vascular biomarkers. Three RCTs met the inclusion criteria, comprising a total of approximately 208 participants. MSC administration was well-tolerated, with no treatment-related serious adverse events reported. Signals of improvement were reported in mobility-related and physical performance outcomes, although the magnitude and consistency of the response varied across studies. A dose-dependent increase in 6 min walk distance was observed at nine months in one trial, while improvements in SPPB, TUG, and grip strength were reported in the other studies. Additionally, MSC therapy was associated with QoL improvement and reduction in circulating pro-inflammatory cytokine concentrations. MSC administration was also associated with changes in immune-cell activation and a dose-dependent reduction in circulating sTIE2. Because of substantial clinical and methodological heterogeneity among the included trials, a quantitative meta-analysis was not performed. Current randomized evidence remains limited but suggests that intravenous MSC therapy is generally well tolerated in older adults with aging frailty and may produce clinically relevant signals of improvement in mobility-related functional outcomes, quality of life, and selected inflammatory, immune, and vascular biomarkers. However, the small number of trials, heterogeneity in MSC source, dose, endpoints, and follow-up duration, and the exploratory nature of much of the evidence preclude definitive conclusions regarding efficacy. Larger, adequately powered trials with standardized frailty endpoints are required, while future trials specifically targeting sarcopenia should apply consensus diagnostic criteria and direct measures of muscle quantity, strength, and physical performance. Full article

Sarcopenia is a progressive skeletal muscle disorder in which clinically relevant muscle failure is expressed primarily as reduced muscle strength, with low muscle quantity or quality used to confirm the diagnosis and impaired physical performance indicating greater severity in the EWGSOP2 (European Working Group on Sarcopenia in Older People 2) framework. This narrative review first defines the clinical phenotype and its current diagnostic operationalization and then uses an author-proposed five-pillar framework: energy, structure, regeneration, neuromuscular control, and systemic communication, to organize the interacting biological mechanisms that may generate that phenotype. The framework is intended as a translational heuristic rather than a validated classification and is positioned within broader geroscience and hallmarks-of-ageing concepts. Particular emphasis is placed on the distinction between muscle mass, strength, power, and physical performance; context-dependent mTORC1 signaling; the limited specificity of candidate biomarkers; and the uncertain causal direction of several mechanistic associations. Resistance exercise and adequate energy and protein intake remain the foundations of management, whereas pharmacological and regenerative strategies have not yet demonstrated sufficiently consistent improvements in patient-relevant functional outcomes to replace these interventions. Linking biological mechanisms to measurable muscle failure may improve interpretation of current evidence and help define priorities for future mechanistic and clinical studies. Full article

Objectives: To assess the clinical viability of compressed sensing magnetization, we prepared a rapid acquisition gradient echo (CS-MPRAGE) for brain volume measurement by comparing its scan time and image quality with standard MPRAGE. Methods: In this retrospective study, we analyzed a total of 40 morphologically normal MRIs from relatively young subjects (mean age 27.03 ± 5.02, range 19~40, F:M = 33:7) who underwent both CS-MPRAGE and standard MPRAGE. MRI was performed with a 3T MR scanner using a 64-channel head coil. Volumetric data analysis was conducted using commercial AI-powered quantification software. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR _{gray matter/white matter}) were measured and compared. Qualitative analysis based on overall image quality, deep gray matter delineation, artifacts, and gray–white matter differentiation was rated on a five-point visual scoring system. Statistical analyses included paired t-tests, intraclass correlation coefficients (ICCs) and Pearson correlation. Results: CS-MPRAGE had a significantly shorter scan time than standard MPRAGE (1:46 vs. 5:20 min; p < 0.001). Whole-brain volume was similar (standard-MPRAGE, 1176.89 ± 105.36; CS-MPRAGE, 1181.14 ± 105.62 mL; r = 0.988; ICC, 0.9754–0.9931). Gray matter and regional lobe volumes were comparable, while the white matter volume was slightly larger with CS-MPRAGE. CNR of the gray–white matter was significantly higher with CS-MPRAGE (left, 30.45 ± 11.21 vs. 49.53 ± 32.71; right, 30.73 ± 11.97 vs. 46.89 ± 30.40; p = 0.0001) while SNR were similar across key brain regions. Conclusions: CS-MPRAGE provides high-quality 3D images and reliable volume data with significantly reduced acquisition time and comparable image quality. Full article

Background: Sarcopenia, systemic inflammation, and malnutrition are established poor prognostic factors in renal cell carcinoma (RCC). This study investigated the utility of a novel preoperative score combining psoas muscle density (PMD)—an imaging-based indicator of muscle quality—and the albumin–bilirubin (ALBI) grade—a blood-based biomarker of liver reserve and systemic nutritional status—for predicting disease-free survival (DFS) and overall survival (OS) in patients undergoing curative surgery for RCC. Methods: This retrospective observational study included 274 patients with non-metastatic RCC treated with radical or partial nephrectomy. Preoperative computed tomography was utilized to measure PMD, defining “low PMD” as a value below the sex-specific median (males: 47.75 Hounsfield Units [HU]; females: 46.25 HU). “Worsened ALBI” was defined as an ALBI grade ≥ 2. Patients were stratified into three risk categories: Score 0 (both normal, n = 122), Score 1 (either abnormal, n = 114), and Score 2 (both abnormal, n = 38). Results: Kaplan–Meier analysis revealed a highly significant, stepwise decline in both DFS and OS as the risk score increased (log–rank p < 0.001 and p = 0.004, respectively). Multivariate Cox regression identified the combined risk score as a robust, independent prognostic factor for DFS (Score 1: HR 1.93, 95% CI 1.11–3.37, p = 0.020; Score 2: HR 3.58, 95% CI 1.82–7.02, p < 0.001). Furthermore, after adjusting for age and comorbidities, the score remained an independent predictor of poor OS (Score 1: HR 2.35, 95% CI 1.08–5.13, p = 0.032; Score 2: HR 3.01, 95% CI 1.16–7.82, p = 0.024). The combined model synergistically enhanced risk stratification accuracy compared to evaluating either factor independently. Conclusions: The concurrent presence of preoperative low PMD and a worsened ALBI grade is a powerful, independent predictor of poor prognosis in localized RCC. Derived solely from routine preoperative imaging and laboratory tests, this straightforward scoring system effectively captures the structural and immunometabolic dimensions of cancer cachexia and host vulnerability. This tool can significantly aid in personalizing postoperative surveillance strategies and identifying high-risk patients who may warrant closer postoperative surveillance or who might be considered as high-risk candidates for adjuvant therapy discussions. Full article

Botrytis cinerea is a major fungal pathogen of grapevine responsible for gray mold, causing significant economic losses worldwide. Under specific environmental conditions, controlled development of Botrytis cinerea may lead to “noble rot,” a quality-enhancing attribute of premium wines; however, the same fungus can rapidly develop into destructive gray mold, causing significant grape losses. Consequently, the challenge is not necessarily the complete eradication of the pathogen, but the regulation of its development to prevent uncontrolled disease progression while preserving grape quality. The present study investigated the potential of using essential oils extracted from selected aromatic plants using ultrasound-assisted hydrodistillation (UAHD) as eco-friendly biocontrol agents against Botrytis cinerea. The extraction process was optimized by evaluating the effects of biomass particle size, ultrasonic power, and distillation time on essential oil yield. Antifungal activity was assessed through in vitro poisoned food and disk diffusion assays and validated in vivo on artificially inoculated grape berries by evaluating disease incidence, disease severity, treatment efficacy, and weight loss. Ultrasound pretreatment increased essential oil yield by up to 29.58% compared with conventional hydrodistillation, with optimal conditions achieved using 1 cm biomass, 150 W ultrasonic power, and 85 min distillation. Oregano, thyme, sage, and lemon balm essential oils achieved 100% inhibition of Botrytis cinerea mycelial growth at the tested concentrations, whereas lavender essential oil showed 95.03% inhibition at 0.125% and complete inhibition at 0.25%. In vivo, essential oil formulations markedly reduced gray mold development, with the 2.0% formulation providing the highest treatment efficacy and the lowest disease severity. These findings show that UAHD-derived essential oils represent promising sustainable alternatives for the management of Botrytis cinerea in viticulture. However, these findings represent preliminary evidence obtained under controlled in vitro conditions, necessitating further validation in real-world applications. Full article

Accurate detection of tomato flowering stages is important for greenhouse crop management and automated pollination, but it remains challenging because tomato flowers are small, densely distributed, frequently occluded, and visually similar across adjacent developmental stages. To address these problems, this study proposes YOLO11-FAL, an improved object detection model based on YOLO11 for tomato flowering stage detection in greenhouse environments. The original C3k2 modules are replaced with C3k2_Faster to reduce redundant spatial computation and enhance local structural feature representation. An Attentional Scale Sequence Fusion (ASF) structure is introduced into the neck network to strengthen multi-scale feature interaction, and a Localization Quality Estimation Head (LQEHead) is incorporated to recalibrate classification confidence using bounding-box distribution information. Experiments were conducted on a self-constructed tomato flower dataset containing Bud, Anthesis, and Post-anthesis stages under varying illumination conditions. YOLO11-FAL achieved 92.00% Precision, 88.88% mAP@0.5, 62.21% mAP@0.75, and 56.72% mAP@0.5:0.95. The model contained 2.384 M parameters and achieved 49.58 FPS on an NVIDIA Jetson AGX Orin (NVIDIA Corporation, Santa Clara, CA, USA) using TensorRT FP16, with a measured onboard power consumption of 11.07 W. These results indicate that YOLO11-FAL provides a practical and efficient visual perception approach for greenhouse tomato flowering stage detection. Full article

A naive Bayesian classifier (NBC) combined with principal component analysis (PCA) effectively differentiates the dose-dependent effects of certain groups of psychoactive drugs based on their impact on the amplitude–spectral characteristics of electrocorticograms (ECoG) in rats. This approach has been shown to be useful for pharmacological screening of agents with unknown or poorly understood activity. Despite previously obtained optimistic results, classification determination for some drugs was inaccurate, necessitating the search for possible ways to improve the predictive effectiveness of the proposed algorithm. One possible approach would be to use as input quantitative data not only the impact of the psychoactive drugs studied on the amplitude–spectral characteristics of ECoG but also connectivity changes, including the average coherence power of different pairs of leads. The aim of this study was to compare the accuracy of NBC in classifying the pharmacological mechanism of action of agents with well-known mechanisms (test set) using pharmaco-EEG data on changes in the amplitude–spectral characteristics of ECoG, coherence, and the combined use of two data sets. Materials and methods. Experiments were performed on Wistar rats with chronically implanted ECoG electrodes. The training set, relative to which the effects of the pharmacological agents from the test set were classified, were the matrices of effects of 12 pharmacological agents: the NMDA antagonist dizocilpine, the D2/D3 antagonists haloperidol and sulpiride, the M-anticholinergic tropicamide, the H1/5HT2A receptor blocker hydroxyzine, the acetylcholinesterase inhibitor galantamine, the alpha-2 adrenergic agonist dexmedetomidine, the alpha-2 adrenergic antagonist atipamezole, the adenosine receptor blocker caffeine and the GABA-mimetics aminophenylbutyric acid (phenibut), bromdihydrochlorophenylbenzodiazepine (phenazepam) and 5-ethyl-5-phenyl-2,4,6(1H,3H,5H)-pyrimidinetrione. The test set included various drugs with tropism for the targets of the training set drugs: dopamine receptor antagonists chlorpromazine, droperidol, tiapride and raclopride, H1-histamine blockers diphenhydramine and promethazine, 5-HT2-receptor blockers ritanserin and glemenserin, acetylcholinesterase inhibitor ipidacrine, alpha2-adrenergic receptor antagonist yohimbine, alpha2-adrenergic agonists medetomidine and xylazine, GABA-mimetics 5-ethyl-5-(1-methylbutyl)-2,4,6(1H,3H,5H)-pyrimidinetrione and chloral hydrate. The analysis of the ECoG signal included the calculation of 132 amplitude–spectral characteristics and 75 coherence indicators, which, using the PCA, led to new integrative indicators used for further classification of the NBC. Results and discussion. For each drug in the test set, the median similarity probability with a particular group from the training set was calculated, which was used to assess the classification quality. It was found that, when using the amplitude–spectral characteristics of ECoG, the proposed methodological approach allows for the identification of the ECoG effects of several groups of psychoactive drugs, including D2/D3-dopamine, M-cholinergic, H1-histamine, and 5-HT2-serotonin receptor blockers, AChE inhibitors, GABA-mimetics, and alpha-2-adrenergic receptor agonists and antagonists. This approach enabled the correct classification of 18 of 24 groups in the test set. When using changes in coherence indices as the initial data, the classification accuracy also amounted to 18 of 24 groups. When combining the two data sets, the number of correctly identified NBC groups was 20 of 24 groups. When comparing the classification during training (confusion matrix), it was found that coherence data or adding coherence data to the data based on changes in amplitude–spectral characteristics leads to a statistically significant (p < 0.01 in both cases) increase in accuracy. Conclusions. The obtained data demonstrated high accuracy in classifying the pharmacological activity of the test sample drugs using any of the three compared approaches. Despite the lack of statistically significant differences between them, classification based on the combined dataset demonstrated a higher number of “correct” similarities. This allows us to recommend the approach based on combined data of drug effects on amplitude–spectral characteristics and coherence as the most promising for further studies using pharmaco-EEG screening. Full article

Reverse osmosis (RO) desalination is a major technology for freshwater production in arid regions, but its energy demand becomes more challenging when the system is supplied by variable renewable energy. This study presents an offline digital-twin-assisted decision-support framework for dynamic RO under Kuwait solar-availability conditions. Within this framework, the predictive models are driven primarily by the dynamic RO process variables, while NASA Prediction Of Worldwide Energy Resources (POWER) data provide the Kuwait solar-availability context, and the PV power margin serves as a scenario-level energy indicator. The purpose is to predict instantaneous permeate flow rate, estimate specific energy consumption, and identify energy-efficient operating conditions using machine learning. Kuwait City was used as the solar case-study location. Hourly solar and meteorological data were obtained from NASA POWER, while dynamic RO membrane data were obtained from the open experimental wave desalination dataset published by the National Renewable Energy Laboratory (NREL) through Data.gov and the Marine and Hydrokinetic Data Repository. The RO dataset includes steady-state, ramp, sinusoidal, and Wave Energy Converter SIMulator (WEC-Sim) pressure/flow experiments. The process-flow image used in the system description was also taken from the same NREL dataset and is cited in the figure caption. The raw RO files were cleaned, harmonized, and transformed into a process-informed modeling dataset. Derived features included pressure rate, recovery ratio, salt rejection, estimated pump power, specific energy consumption (SEC), PV power margin, and rolling pressure/flow features. Three supervised regression models were tested: Gradient Boosting, Random Forest, and XGBoost. A representative subset of 60,000 records was used to preserve the main experimental conditions while reducing redundancy in the densely sampled sequential data. Results show that permeate flow rate can be predicted with high accuracy using Gradient Boosting (R² = 0.981; RMSE = 0.161 L/min). The moderate energy prediction performance yielded an R² of 0.654 and RMSE of 7.570 kWh/m³ for Random Forest. The accuracy of permeate conductivity predictions was lower (R² = 0.257; RMSE = 245.44 µS/cm) because membrane and feed characterizing parameters should be included for an adequate water quality control. The proposed approach is best suited as an offline decision-support framework for dynamic RO process analysis. Full article

The 4 km/15 min downward surface shortwave radiation (DSSR) product from Fengyun-4B (FY-4B)/AGRI shows great potential for solar energy assessment in China, but its applicability requires further validation. This study conducts a comprehensive evaluation of the FY-4B DSSR product over Guangxi for 2025, using ground-observed irradiance from a dense network of 101 photovoltaic (PV) power stations. The overall comparison shows a correlation coefficient (R) of 0.84, a root-mean-square error (RMSE) of 161.78 W/m², a relative prediction error (RPE) of 51.02%, and a mean bias error (MBE) of 56.23 W/m², indicating systematic overestimation. Seasonally, the largest discrepancies occur in spring (MBE = 85.27 W/m², RPE = 53.12%) and summer (R = 0.82, RMSE = 184.10 W/m²). Diurnally, retrievals are most reliable around 09:00–13:00 local time, deteriorating notably in the early morning and, especially, the afternoon and evening. Spatially, errors are larger in the hilly, elevated terrain of northwestern Guangxi (e.g., Hechi) than in flatter southern and coastal cities, with RPE rising from roughly 40–60% at lower elevations to around 80% above 600–700 m. Sky-condition classification confirms that data quality follows clear > cloudy > overcast sky, while AOD-binned analysis shows aerosol loading playing a secondary but non-negligible role, especially under high-AOD pollution events. Solar zenith angle (SZA) also strongly affects accuracy: R peaks around 0.75–0.8 in the 30–50° SZA range and drops below 0.4 beyond about 75°. This study offers the most spatially and dimensionally comprehensive validation of FY-4B DSSR over Guangxi to date, characterizing accuracy across seasonal, diurnal, spatial, cloud, aerosol, solar-geometry, and elevation dimensions using a denser ground-truth network than previously available, with direct implications for photovoltaic resource assessment and power forecasting in subtropical hilly regions. Full article

Woody biomass is often promoted as a low-carbon energy source in global decarbonization efforts. However, LCA (life cycle assessment) evaluations of woody biomass-to-energy systems show very different environmental performance. Variations in technology and methodology across investigations can cause these inconsistencies. This review paper analyzes methodologies of LCAs of woody biomass conversion routes such as combustion, combined heat and power, gasification, pyrolysis, torrefaction-assisted systems, and new bioenergy with carbon capture configurations. A systematic literature review was conducted using Scopus, SpringerLink, and ScienceDirect, identifying 4272 records, of which 98 studies were retained for detailed analysis following the application of defined inclusion and exclusion criteria. Functional unit selection, from biomass mass per unit to power or heat per unit, is highly variable, affecting comparability. Forest carbon stock fluctuations, infrastructure, and end-of-life treatment are inconsistently included in cradle-to-grave system boundaries. Static GWP100 methods are often used in biogenic carbon removal without considering temporal carbon dynamics. The importance of pretreatment steps like drying, pelletizing, and torrefaction cannot be overstated, even though they have a direct impact on the quality of the fuel, the efficiency of transportation, and the effectiveness of the conversion process downstream. The large range of stated emission levels for comparable technologies is further influenced by logistics assumptions, plant scale, and allocation mechanisms in cogeneration systems. The review synthesizes these methodological differences and proposes a harmonization methodology to increase woody biomass LCA transparency and comparability. By identifying important sources of outcome variability, this study helps policymakers, project developers, and industry stakeholders evaluate biomass energy investments and bring clarity to environmental decisions. Full article

Background/Objectives: Obesity is a chronic, progressive, and relapsing disease that requires long-term, multidisciplinary management rather than episodic weight-loss treatment. Although novel incretin-based anti-obesity pharmacotherapies, including GLP-1 receptor agonists and dual GIP/GLP-1 receptor agonists, have markedly improved the clinical management of obesity, weight reduction alone does not fully capture treatment success. Body composition, lean mass preservation, physical function, nutritional adequacy, psychological well-being, adherence, and long-term weight-loss maintenance are increasingly recognized as essential therapeutic outcomes. This narrative review critically examines the role of lifestyle medicine as a co-therapeutic strategy during modern anti-obesity pharmacotherapy, with particular attention to physical activity, nutrition, behavioral support, and individualized monitoring. Methods: A narrative literature search was conducted in PubMed up to June 2026. The review included studies addressing adults with overweight or obesity and evidence related to anti-obesity pharmacotherapy, physical activity, nutrition, body composition, functional outcomes, eating behavior, quality of life, treatment tolerability, adherence, weight regain, and long-term maintenance. Results: Current evidence indicates that incretin-based therapies produce substantial and clinically meaningful weight loss, but pharmacological efficacy may be limited by reductions in lean mass, gastrointestinal adverse events, inadequate nutritional intake, treatment discontinuation, and weight regain after drug withdrawal. Physical activity should be considered a therapeutic component rather than only a tool for increasing energy expenditure, as aerobic exercise supports cardiometabolic health and cardiorespiratory fitness, while resistance training helps preserve muscle strength, bone health, and functional capacity. Nutritional strategies are equally important, particularly during appetite suppression, to maintain adequate protein, fiber, fluids, micronutrients, and diet quality. Behavioral factors, including sleep, stress, mood, stigma, self-regulation, and the food environment, may influence adherence and long-term outcomes. Conclusions: Novel anti-obesity drugs should not be viewed as replacements for lifestyle medicine but as powerful tools within an integrated chronic-care model. The goal of treatment should move beyond maximal body-weight reduction to durable improvements in body composition, metabolic health, physical function, nutritional status, quality of life, and weight-loss maintenance. Full article