Search Results (2,923)

How ordered and mutually independent are semiflexible ring polymers (RPs) confined to a spherical cavity of variable radius? By varying the cavity radius, we systematically investigate the effect of the confinement size on the conformations of RPs using the coarse-grained molecular dynamics simulations. The results reveal that as the bending energy increases, the RPs exhibit a transition from a purely flexible coil to an elongated oblate-shaped object and, eventually, to a disk-like conformation. Simultaneously, the stacked aggregates composed of adjacent, mutually nearly parallel, semiflexible RPs emerge for stiffer chains. We find that the structural modulation of the stacked aggregates is regulated by the confinement size. For the conditions of strong confinement ($R<2R_g$, where $R_g$ is the radius of gyration of an RP), the semiflexible RPs undergo peculiar deformations and twisting that lead to disruption of the stacked aggregates. At $R\approx 2R_g$, the average number of the RPs per stack reaches a maximum. Concurrently, the order of spatial alignment of all semiflexible RPs is maximized with the global orientational-order parameter reaching the value $S\approx 0.79$. As the cavity radius further increases, at $R>3R_g$, the semiflexible RPs gain greater mobility resulting in diverse orientations of the aggregates being formed, with the order parameter dropping to $S\approx 0.05$. These findings provide important quantitative insights for future applications of the RPs, i.e., in micro- and nanodevice assembly. Full article

To enhance access to efficient and low-carbon public transportation, the city of Alexandria, Egypt, has introduced a fleet of electric buses. Additionally, an ongoing project aims to upgrade and electrify the existing urban railway system, which is expected to alleviate traffic congestion in this densely populated city. The implementation of electric vehicle (EV) parking facilities is also under consideration. This paper investigates the integration of photovoltaic (PV) systems and green hydrogen-powered gas turbines as components of the integrated energy system (IES). An optimal energy management strategy is proposed to maximize the benefits of incorporating renewable energy sources into the urban transportation system (UTS). The proposed energy management algorithm incorporates demand-side management (DSM) for UTS loads and EVs, increasing the complexity of the decision-making process due to the high uncertainty of decision variables. To address this challenge, a modified multi-agent reinforcement learning (MRL) approach is employed, in which uncertainty is incorporated through stochastic environment sampling. Simulation results demonstrate the economic potential of integrating renewable and sustainable energy resources into the IES of the electrified urban transportation system, achieving a 40.2% reduction in the average daily energy consumption cost. Full article

Objectives: To determine whether caffeine supplementation and its expectancy influence muscle strength (ST) and muscle endurance (ME) using a balanced-placebo design. Methods: Using a randomized, double-blind, balanced-placebo design, resistance-trained men (18–30 years; n = 16) participated in two assessment/familiarization visits (demographics; one repetition maximum (1RM) followed by four counterbalanced sessions: C/C (informed caffeine/used caffeine), P/C (informed placebo/used caffeine), C/P (informed caffeine/used placebo), P/P (informed placebo/used placebo). Caffeine dose was 5 mg/kg. Peak torque (PT) and maximum work (MW) were measured in the knee extensors at 0, 60, 180, and 300°/s, which was followed by ME testing (three sets of maximal repetitions using 60%1RM). Capillary blood lactate was measured after ME testing. Results: Caffeine increased PT only during static and 60°/s contractions (4%; p ≤ 0.003; d = 0.3 for both speeds), while MW increased across all speeds (4%; p < 0.001; d = 0.2). Caffeine did not increase ME (3%; p = 0.184; d = 0.1), but it did increase blood lactate levels (1.2 mmol/L; p < 0.001; d = 0.7). Caffeine expectation did not improve ST or ME, but increased blood lactate levels (0.7 mmol/L; p = 0.003; d = 0.4). Across ST and ME, responses to caffeine were markedly heterogeneous, with 50–88% of individuals considered responders (∆ > 0), and improvements in responders ranged from 1–16%. Conclusions: Caffeine significantly increased ST, despite ME increasing in 50% of participants, this was not significant. No placebo effect was observed in ST or ME, but it significantly increased lactate. Further research is necessary to elucidate the mechanisms behind this variability in the ME response, especially the role of fiber-type predominance. Full article

Background/Objectives: Indoor air pollution is an increasingly recognized cause of lung cancer, yet evidence remains fragmented across exposure categories. This systematic review aimed to consolidate epidemiological findings on the relationship between household pollutants and lung cancer risk across diverse settings. Methods: A systematic search of PubMed, Web of Science, Scopus, and Cochrane was conducted to identify observational studies published between 2015 and 2025. Eligible articles evaluated indoor exposure in relation to primary lung cancer. Maximally adjusted effect estimates were extracted. Random effects models were used to calculate pooled odds ratios (ORs) and hazard ratios (HRs) when appropriate. Study quality was assessed using the Newcastle–Ottawa Scale. Results: Thirty-eight studies comprising 475,565 participants were included. Environmental tobacco smoke (ETS) was associated with lung cancer risk (pooled OR 1.97, 95% CI 1.63–2.37; pooled HR 1.44, 95% CI 1.19–1.74). Cooking oil fumes showed a pooled OR of 1.83 (95% CI 1.53–2.21). Solid fuel and biomass combustion were also associated with increased lung cancer risk, with pooled estimates indicating elevated odds and hazard ratios (pooled OR 2.26, 95% CI 1.36–3.77; pooled HR 1.66, 95% CI 1.37–2.02). Incense burning was evaluated in a single study (OR 3.05, 95% CI 1.06–8.84), with wide confidence intervals. Two studies explored gene–environment interactions, suggesting possible variability in susceptibility, although statistical robustness was limited. Conclusions: Across multiple exposure categories, indoor air pollution was consistently associated with lung cancer risk, although the effect magnitude and precision varied between studies. Given the observational nature of the evidence and methodological heterogeneity, further prospective research with standardized exposure assessment is needed to clarify the strength and consistency of these associations. Full article

Untargeted metabolomics faces significant challenges in standardization due to variability introduced by sample preparation and analytical workflows. We systematically evaluated the impact of biological matrices, extraction protocols, and chromatographic configurations to establish a mechanism-informed framework aimed at improving reproducibility in large-scale clinical and epidemiological studies. Three extraction protocols were compared using an in-house pooled heparin plasma: monophasic protein precipitation with isopropanol (IPA), methanol:acetonitrile (MeOH:ACN), and a modified Matyash biphasic method. The most reproducible protocol was then applied to four blood matrices. Samples were analysed using untargeted metabolomics on hydrophilic interaction liquid chromatography (HILIC) and reversed-phase (RP) HPLC columns, with mass spectrometry data processed using Compound Discoverer. Both IPA and MeOH:ACN extractions achieved over 80% of features with coefficient of variation (CV%) ≤ 30% for both RP and HILIC, whereas the Matyash method showed higher variability, with a larger proportion of metabolites exhibiting CV% > 30%. Across matrices, RP chromatography detected over 80% of metabolites with CV% < 30%, while HILIC showed higher variability, with at least 20% of metabolites above this threshold. Among matrices, serum and heparin plasma outperformed EDTA and citrate in reproducibility. We propose a standardized workflow in which monophasic extractions combined with RP chromatography maximize reproducibility and metabolite coverage, minimizing methodological artefacts and providing a reliable framework for robust biological discovery in large-scale untargeted metabolomics studies. Full article

Cachichín (Oecopetalum mexicanum) is a tropical fruit tree native to Mexico and Central America, whose fruit contains an edible seed with potential nutraceutical properties. Empirical toasting of the cachichín seed often compromises the quality of its bioactive compounds. In a first experiment, this study evaluated the effects of time (25, 35, and 45 min) and temperature (115, 134, and 148 °C) to establish a controlled toasting process. The colorimetric properties were evaluated using a HunterLab colorimeter. The stability and structural integrity of fatty acids were assessed through the iodine value and Fourier Transform Infrared Spectroscopy (FTIR) in oils extracted by two methods: extrusion and Soxhlet. The most intense thermal treatments caused progressive darkening and significant lipid degradation. Although chemical variability was observed among treatments, the main functional groups of both saturated and unsaturated fatty acids remained structurally stable. The treatment at 134 °C for 25 min mitigated excessive degradation, achieving a better balance among color preservation, physicochemical properties, and lipid stability. Furthermore, Soxhlet extraction resulted in better preservation of unsaturated fatty acids under these controlled toasting conditions. In a second experiment, this controlled method outperformed traditional treatments (boiling and commercial toasting), preserving a desirable color and low water activity (a_w). Fatty acid analysis confirmed that this treatment maintained lipid stability, notably preserving unsaturated fatty acids (oleic, linoleic and linolenic acids) regardless of the extraction method. These results demonstrate that optimizing thermal processing is fundamental for maximizing the nutritional value of the cachichín seed, enhancing its potential in the food industry. Full article

The Transactional Asset Pricing Approach (TAPA) is able to handle asset valuations on a portfolio level of size constrained markets against the backdrop of low liquidity hindering the estimation of the variance of returns. Prompted by a numerical simulation of the TAPA algorithm, we develop stability conditions associated with the valuation convergence for any maximal positive time period and positive number of assets. We present stability conditions at the local level, both in continuous and discrete algorithmic time, and we develop them by means of log-linearisation about the steady state of its equations’ variables. We conclude on the analytical existence of stability conditions at the local level up to four assets and any positive time period. We adduce analytical applications within such a region and present a solution for a benchmark calibration of the steady state parameters given two time periods and a single asset. Full article

Maximizing the expected value of a concave and strictly increasing utility function defines a fundamental class of discrete optimization problems. Among them, coverage decision problems with diminishing marginal returns under uncertainty, typically modeled via a set-union operator, have been extensively studied. In the classical framework, an item becomes active once it is covered by at least one chosen meta-item. Motivated by increasing robustness requirements in applications such as automated systems, social networks, and emergency response planning, we extend this setting by introducing threshold-based activation. The resulting generalized problem can be formulated as a mixed-integer nonlinear programming problem, for which we further propose three exact algorithms. The first two methods linearize the utility function using submodular cuts (SC) and outer-approximation (OA) techniques, respectively, resulting in formulations that can be solved exactly by off-the-shelf mixed-integer linear programming solvers. The third method builds upon the OA framework and further employs Benders decomposition (BD) to project out the item-related variables, which enables superior performance on ultra-large-scale instances. Extensive computational experiments show that, compared with the SC and BD methods, the OA method exhibits a substantial speed advantage on instances with a size of around 40,000, which can be solved within 100 s. In contrast, for ultra-large-scale instances with more than 100,000 items, the BD method demonstrates superior computational efficiency. These results provide practical guidance for algorithmic strategy selection and further demonstrate the computational tractability of this broader class of utility maximization problems under threshold-based activation. Full article

Background: This systematic review examined the relationship between horizontal multi-step jumps and sprint performance, and whether training interventions including these exercises improve sprinting. Methods: A systematic literature search was conducted in SPORTDiscus and PubMed (MEDLINE) and included English-language studies of athletes aged ≥14–15 years that assessed at least one horizontal multi-step jump and reported sprint outcomes over distances up to 100 m. Methodological quality and risk of bias were assessed using design-appropriate critical appraisal tools. Of 316 records identified, 19 studies met the inclusion criteria (10 intervention studies and 9 correlational studies). Results: Across correlational studies, horizontal multi-step jump performance showed associations ranging from weak to very large with sprint performance, with the strongest relationships typically observed during acceleration (≤20–30 m). In trained sprinters, correlations were often large to very large (r ≈ −0.65 to −0.88), whereas team-sport athletes showed more moderate associations, and younger or less specialized populations showed weak or non-significant relationships. Across intervention studies, horizontal multi-step jump training generally improved short-distance sprint performance, with the largest improvements reported for acceleration (up to ~7–12% in some studies), while effects at longer sprint distances and maximal-speed performance were smaller, inconsistent, or not different from comparison training. Conclusions: Overall, the evidence suggests that the association between horizontal multi-step jumps and sprint performance is strongest during the acceleration phase and is influenced by athlete population and training status. Horizontal multi-step jumps appear to be useful for assessing and potentially developing sprint acceleration. However, the findings should be interpreted with caution due to heterogeneity in study design and variable methodological quality, and associations with maximal sprint speed are less consistent across studies. Full article

Distant metastasis is the main cause of breast cancer (BC) mortality, yet current prognostic models remain largely tumor-centric and underutilize stromal biology. In this study, we quantified reactive stroma, a collagen-rich and fibrotic fraction of the stromal compartment, as a subtype-independent biomarker of metastatic risk. A retrospective cohort of 182 FFPE primary BC biopsies (2006–2020) was analyzed. Total stroma was quantified on H&E-stained sections and reactive stroma on Masson’s trichrome using QuPath with pathologist validation. Cutoffs were defined using maximally selected rank statistics, and overall survival (OS) and metastasis-free survival (MFS) were evaluated by Kaplan–Meier analysis and multivariable Cox regression. RNA sequencing was performed in a subset of cases to characterize associated transcriptomic programs. While total stromal content showed univariate associations with OS and MFS, it was not independently prognostic after adjustment. In contrast, high reactive stroma (cutoff 53.2%) independently predicted shorter MFS (HR = 3.76; p < 0.001), irrespective of molecular subtype and clinicopathological variables. Tumors with high reactive stroma exhibited upregulation of extracellular matrix and profibrotic genes (including FN1, OLR1, and EDN2), enrichment of collagen remodeling and TGF-β signaling pathways, and reduced T-cell activation signatures. These findings demonstrate that quantitative assessment of reactive stroma from standard histological stains is a reproducible, subtype-independent biomarker of metastatic risk in BC and can be readily integrated into routine pathology workflows to improve risk stratification. Full article

Neoantigen vaccines have revitalized cancer vaccination by targeting tumor-specific mutant epitopes largely absent from central tolerance. Yet, clinical benefits remain inconsistent, in part because conventional vaccine platforms often do not reliably deliver antigens within an inflammatory tumor context, struggle to overcome immunosuppressive tumor microenvironments, and may not rapidly adapt to tumor heterogeneity and evolution. Oncolytic viruses (OVs) provide a mechanistically distinct route to “vaccinate in situ” by coupling tumor-selective infection and immunogenic cancer cell death with local innate immune activation, antigen release, and remodeling of the tumor microenvironment. In parallel, advances in sequencing, neoantigen prediction (e.g., updated NetMHCpan and MHCflurry tools as of 2025), and antigen presentation validation have enabled rational selection of patient-specific targets. At the same time, modern OV engineering supports insertion of neoantigen payloads and immune-modulatory transgenes. Here, we summarized principles that underpin neoantigen-encoded OVs as personalized cancer vaccines, emphasizing how OV adjuvanticity and antigenicity interact to drive priming, epitope spreading, and durable systemic immunity. We discussed major OV platforms with respect to payload capacity, expression control, manufacturability, and clinical track records, including lessons learned from approved or late-stage OVs such as talimogene laherparepvec (T-VEC) and teserpaturev/G47Δ. We also discussed design choices for encoding neoantigens (polyepitope strings, minigenes, long peptides; class I/II balancing), prioritizing translational biomarkers and immune-monitoring strategies, and outlining regulatory and GMP considerations for “platform-plus-variable insert” products. Finally, we propose a pragmatic clinical workflow for rapid personalization to maximize therapeutic index. Tightly integrating neoantigen science with immunovirotherapy, including recent 2025 preclinical advances like oncolytic adenovirus neoantigen delivery sensitizing low-TMB tumors to PD-1 blockade, could enable next-generation personalized cancer vaccines capable of converting “cold” tumors into responsive, systemically controlled disease. Full article

Viticulture faces increasing challenges due to the susceptibility of Vitis vinifera L. to biotic and abiotic stresses, which trigger defense responses involving the synthesis of secondary metabolites. Untargeted metabolomics has become a powerful tool to explore these metabolic changes; however, the efficiency and reproducibility of metabolomic studies strongly depend on the extraction protocol used. Current literature shows variability in sample handling, solvent composition, and extraction conditions. This study aimed to optimize an extraction protocol for secondary metabolites in grapevine leaves to ensure high recovery of compounds relevant to untargeted metabolomics. Leaves of Vitis vinifera L. cv. Tempranillo were collected, pooled, frozen, and ground under liquid nitrogen. A factorial design was used to evaluate the effects of sample mass, sample-to-solvent ratio, and solvent type on extraction efficiency. Extracts were analyzed using UHPLC-QTOF-MS in both positive and negative ionization modes, and multivariate statistical tools (PCA and OPLS-DA) were used to identify discriminant metabolites. Optimal extraction was achieved using 750 mg of leaf powder, a sample-to-solvent ratio of 100 mg/Ml, and methanol 80% acidified with 0.1% of formic acid. This protocol maximizes the recovery of metabolites and provides a robust basis for future untargeted metabolomics studies of grapevine responses. Full article

Background/Objectives: While traditional sports nutrition emphasizes high carbohydrate intake for endurance athletes, trained athletes may achieve metabolic adaptation to low-carbohydrate and ketogenic diets with maintained or improved performance outcomes. This systematic review and meta-analysis synthesize evidence on the effects of low-carbohydrate (≤130 g·day⁻¹ or ≤25% total energy) and ketogenic (<50 g·day⁻¹ or <10% total energy) diets on aerobic performance variables in trained athletes. Methods: A comprehensive search of five electronic databases (PubMed, SCOPUS, Web of Science, SPORTDiscus, and Cochrane Central Register of Controlled Trials) identified 33 aerobic-focused studies meeting comprehensive inclusion criteria. Selected studies examined trained athletes (≥6 months structured training, age 18–45 years) randomized to low-carbohydrate, ketogenic, or high-carbohydrate control conditions with outcome data on aerobic performance variables (VO₂max, time trial performance, time to exhaustion, and exercise economy) and metabolic markers (fat oxidation and substrate utilization). Quality assessment employed Newcastle-Ottawa Scale methodology. Results: Maximal aerobic capacity (VO₂max) was preserved in 50.0% of studies, with 11.1% documenting improvements. Submaximal exercise economy showed the greatest sensitivity, with 50.0% documenting impaired efficiency. Time to exhaustion demonstrated context-dependent effects, with 69.2% maintaining performance. All 30 studies measuring fat oxidation demonstrated consistent increases (+28% to +200%). Critically, temporal analysis identified a 1-week adaptation threshold: studies measuring outcomes within ≤7 days documented performance impairment, while studies measuring at >1 week consistently demonstrated maintained or improved performance. Conclusions: Low-carbohydrate diets reliably induce metabolic adaptation characterized by dramatically increased fat oxidative capacity. However, aerobic performance responses are nuanced, with preserved maximal aerobic power, transient submaximal efficiency impairments, and context-dependent endurance effects. Adaptation involves initial acute-phase decrements (≤7 days) followed by recovery. Evidence supports periodized carbohydrate strategies balancing metabolic adaptation benefits from low-carbohydrate training phases with carbohydrate requirements during competition. Full article

We study strong laws of large numbers in a non-linear framework based on conditional sub-additive expectations and conditional sub-additive capacities. Using an axiomatic approach to conditional sub-additive expectation, we establish a conditional Hájek–Rényi-type maximal inequality assuming a general conditional Kolmogorov-type maximal inequality but without imposing any weak dependence structure on the underlying sequence. As a consequence, we derive a general conditional strong law of large numbers. Finally, we introduce a notion of conditional negative dependence under sub-additive expectations and obtain the corresponding conditional Kolmogorov-type maximal inequality, leading to a conditional strong law of large numbers for conditionally negatively dependent random variables. Full article

Reservoir operation under climate change poses significant challenges for hydropower-dependent countries, particularly in cascade reservoir systems. This study aims to derive optimal future operating rule curves for the Nam Khan 2 and Nam Khan 3 cascade reservoirs in Lao PDR to maximize hydropower generation under climate change. Genetic Algorithm (GA), Invasive Weed Optimization (IWO), and Harmony Search (HS) were integrated with a reservoir simulation model to optimize monthly upper and lower rule curves. Future reservoir inflows were generated using climate projections from the INM-CM5-0 climate model’s SSP245 scenario for 2025–2050. The aim was to maximize average annual electricity generation for the entire cascade system while ensuring practicable reservoir operation. The optimized rule curves obtained from all three algorithms exhibited similar seasonal patterns, reflecting regional hydrological characteristics. The proposed rule curves significantly improved hydropower performance compared to the existing operating policies. For Nam Khan 2, average annual electricity generation increased from 324.089 GWh under current operations to 788.246, 787.100, and 786.561 GWh using GA, IWO, and HS. Similarly, Nam Khan 3 achieved substantial improvements, with average annual generation increasing from 156.029 GWh to 270.049, 266.840, and 266.547 GWh. The optimized rule curves also contributed to better storage regulation and reduced variability in energy production. The findings demonstrate that integrating metaheuristic optimization techniques with reservoir simulation models provides an effective framework for adaptive hydropower-oriented reservoir operation under future climate uncertainty. Full article