Search Results (14,081)

Background: Cardiolipin (CL) is a phospholipid composed of a glycerol linked with two phosphatidate moieties that constitutes an integral part of the human inner mitochondrial membrane under physiological conditions. It is also vital for bacterial membrane transport and key bacterial functions associated with cell division and infection. CL is released in the cytosol or into the extracellular milieu upon cell death and during inflammation. We therefore tested the ability of CL to activate and expand tumor infiltrating lymphocytes (TIL) from patients with epithelial cancer. Methods: TIL were isolated from gastrointestinal tumor tissues and expanded in vitro in the presence of CL. The role of the NLRP3 inflammasome was evaluated using the specific inhibitor MCC950 and siRNA-mediated silencing of NLRP3. Phenotypic changes and T-cell potency were assessed via CXCL9/10 expression levels. To characterize the immune repertoire, deep TCR sequencing was performed to compare the TCR Vα and Vβ CDR3 regions between TIL and the corresponding tumor tissue. Recognition of autologous tumor cells and tumor-specific mutations, including mutations in KRAS and mitochondrial UQCRFS1 (D145V), was assessed using MHC class I and II restriction assays. Results: CL-expanded TIL exhibited increased CXCL9/10 expression, which is associated with increased potency of tissue invasion. CL-TIL exhibited broader recognition of frequently occurring KRAS mutations, and this effect could be blocked with an inhibitor (MCC950) of the NLRP3 pathway, a multiprotein inflammatory complex associated with danger signaling. TIL exhibited an enriched TCR Vα and Vβ CDR3 repertoire compared to tumor tissue, as defined by deep TCR sequencing. TCR αβ+ TIL recognized autologous tumor tissue in an MHC class I– and class II–restricted fashion, including the mutant HLA-DP–restricted mitochondrial protein associated with the electron respiratory chain complex III (UQCRFS1 D145V) presented by autologous tumor cells. Conclusions: CL activates the NLRP3 inflammasome pathway in TIL from patients with GI cancer and increases CXCL9/CXCL10 expression in TIL, resulting in enhanced recognition of mutant cancer–associated target epitopes, including a mitochondrial protein. CL may provide a danger signal: that facilitates TIL expansion via CL-activated pathways. Full article

The Beijing–Tianjin–Hebei (BTH) coordinated-development strategy provides a county-level setting for examining how transport-led regional restructuring reshaped the relationship between human activity and land–environment conditions. Using a balanced panel of 200 county-level units from 2010 to 2020, we work with two linked subsystems: the human-activity subsystem (H), which combines transport integration and economic upgrading, and the land–environment subsystem (L), which combines land-use transition and ecological response. Pooled entropy weighting, a coupling-coordination index, spatial autocorrelation analysis, and fixed-effects differential-response models are used to trace temporal change, spatial clustering, and post-2014 heterogeneity within BTH. Mean coupling coordination (D) rose from 0.5430 to 0.6012, but the increase came mainly from the rise of H, while L changed only slightly. Positive spatial autocorrelation persisted throughout the period. Counties in the Beijing–Tianjin ring kept higher absolute coordination levels, yet after 2014, they improved more slowly than non-ring counties because land–environment adjustment lagged behind changes within H. Relative to key ecological function zones, agricultural counties—and to a lesser extent urbanized counties—posted faster gains in D, again mainly through H. The results show that in BTH, regional integration did not move the two subsystems in lockstep: transport reorganization and economic upgrading advanced faster than land–environment adjustment, so durable county coordination still depended on land governance, ecological regulation, and policies matched to territorial functions. Full article

Abundant non-medicinal byproducts of Polygonatum sibiricum and Gentiana scabra are severely underutilized, resulting in resource waste and environmental burden. A previous study confirmed that triple-microbial co-fermentation enhances their antibacterial activity, yet the temporal metabolic mechanism and optimal process parameters remain unclear due to endpoint-only metabolomics limitations. This study aimed to optimize the staged solid-state fermentation (SSF) system for maximum antibacterial activity, verify the triple-microbial consortium’s synergistic enhancement effect, and elucidate the dynamic metabolic mechanism via time-series metabolomics. A staged SSF strategy was established: Aspergillus niger monoculture (0–48 h) followed by Bacillus subtilis and Saccharomyces cerevisiae co-culture (48–72 h). Key parameters were optimized via single-factor experiments and a Box–Behnken design. Under optimal conditions, inhibition zones against Staphylococcus aureus and Escherichia coli reached 20.8 ± 0.3 mm and 17.6 ± 0.2 mm, respectively, with a 17.5% increase in S. aureus inhibition and markedly improved E. coli inter-batch consistency. Time-series untargeted LC-MS/MS metabolomics (2681 identified metabolites) revealed a three-stage metabolic relay model driving antibacterial enhancement: 0–48 h shikimate pathway activation for phenolic precursor accumulation; 48–60 h dipeptide conversion and ABC transporter enrichment initiating antibacterial synthesis; 60–72 h metabolic flux redirected to indole alkaloid biosynthesis for complex antibacterial compound accumulation. This work provides a mechanistic paradigm for the high-value valorization of herbal byproducts, with applications in natural antibacterial agents and functional feed additives. Full article

This study aimed to optimize the ultrasonic-assisted extraction of polyphenols from Archidendron clypearia and to evaluate their anti-hyperuricemic effects. Polyphenols from medicinal plants have attracted increasing attention due to their potential roles in regulating uric acid metabolism. In this study, single-factor experiments combined with Box–Behnken response surface methodology were employed to optimize extraction conditions, and an entropy weighting method was applied to integrate total polyphenols and Archidendrin I into a comprehensive evaluation index. The bioactivity of the obtained extract was further assessed through in vitro assays and a hyperuricemic mouse model. The optimal extraction conditions were determined to be 50% ethanol, a liquid-to-material ratio of 30, and 31 min of sonication, yielding 175 mg GAE/g DW of total polyphenols and 80.34 mg/g DW of Archidendrin I. The extract exhibited significant xanthine oxidase inhibitory activity, reduced serum uric acid levels, regulated urate transporters (URAT1, GLUT9, and ABCG2), and alleviated renal and hepatic injury in hyperuricemic mice. These findings indicate that the optimized process enables efficient extraction of polyphenols from Archidendron clypearia, and the resulting extract exerts beneficial regulatory effects on uric acid metabolism, highlighting its potential as a natural agent for hyperuricemia management. Full article

Offshore industries depend solely on diesel-based power generation systems or mainland grids, which are expensive and carbon-intensive. The demand for renewable energy-based offshore DC microgrids (MGs) has significantly increased due to rising fuel prices, high costs of fuel transportation and storage, extreme operation and maintenance expenses, and associated carbon emissions. This research study optimises the size of an offshore DC MG that integrates wave, solar, energy storage, and diesel, utilising real-world data from a specific geographical location (latitude −33.525587 and longitude 114.772211), thereby accurately representing the availability of renewable energy sources. An algorithm is designed to optimise the utilisation of highly variable renewable sources via battery-based energy management, resulting in optimal energy dispatch. Utilising economic performance metrics, such as levelised cost of energy (LCoE) and net present value (NPV), this research aims to minimise the energy, operating, and greenhouse gas emission costs while maximising the economic feasibility of the system. A sensitivity analysis is performed to determine the impact of fuel prices, discount rates, and system lifespans on the feasibility of the system. The findings demonstrate that the proposed renewable-based offshore DC MG can substantially reduce fuel consumption (93%), operational expenses (77.56%), and carbon emissions (89.50%) compared with a diesel-only system for offshore platforms, while improving the sustainability and reliability of power supply for aquaculture and marine activities. In addition, the proposed renewable-energy-based offshore DC MG achieves a lower LCoE (0.5649 $/kWh) and a higher NPV (2.987 × ${10}^4$ $) than a conventional diesel-based power generation system for offshore industries. The results provide a decision-making framework for the design and implementation of renewable energy-based offshore DC MGs. Full article

Modern cattle comprise two major evolutionary lineages: intensively selected commercial breeds and locally adapted native populations. To investigate their genomic divergence, we performed a comparative population genomic analysis by integrating whole-genome resequencing (WGS) data from multiple representative native breeds and major European commercial breeds. Population genetic analyses showed clear phylogenetic separation between the two groups, with distinct patterns of genetic diversity. Chinese native cattle exhibited generally higher nucleotide diversity (π), lower inbreeding levels, and geographically structured admixed ancestry. Comparative analyses of selection signatures identified 886 candidate selected genes in European commercial breeds, which were primarily enriched in pathways related to production traits, including protein turnover, reproductive regulation, lipid metabolism, and neuro-regulation. In contrast, 50 candidate selected genes in Chinese native cattle were significantly enriched in nervous system functions, particularly ligand-gated ion channel activity and chloride transport (e.g., GRID2, GLRA2/4, GABRD), suggesting neural/ionic regulation may contribute to local adaptation alongside other polygenic mechanisms. Additionally, the two groups also differed in patterns of deleterious mutation load. These findings indicate partially distinct evolutionary trajectories between “production-optimized” and “environment-adapted” cattle and highlight the value of conserving the genetic diversity and adaptive alleles of Chinese native cattle. Full article

Obesity represents a multifactorial health condition influenced by complex interactions among behavioral, environmental, and physiological factors, yet the relative predictive importance of lifestyle behaviors versus medical history indicators remains incompletely characterized. This investigation employed a three-phase machine learning approach to systematically compare the predictive power of behavioral lifestyle factors, medical history variables, and their integration for obesity classification. Phase A utilized a dedicated obesity dataset containing demographic, dietary, and lifestyle predictors to perform seven-category obesity classification, achieving 81.65% test accuracy with an optimized Random Forest ensemble and macro-averaged F1-score of 0.82. Phase B addressed binary obesity classification using health indicators from diabetes screening data, where a Gradient Boosting model with optimized decision threshold achieved 67.84% accuracy and AUC of 0.735, demonstrating substantially lower performance than behavioral predictors. Phase C integrated both feature sets into a unified model, where Gradient Boosting achieved 68.31% accuracy and AUC of 0.747, representing marginal improvement over medical history alone. Cross-validated performance comparisons revealed that behavioral lifestyle factors provided superior discriminative power compared to medical history indicators, with dedicated lifestyle predictors achieving 13.81 percentage points higher accuracy than medical indicators. Feature importance analysis confirmed that transportation mode, physical activity patterns, and dietary behaviors ranked among the most influential predictors in the combined model. These findings demonstrate that behavioral lifestyle factors constitute stronger obesity predictors than medical history variables, with implications for clinical screening strategies and public health intervention targeting that prioritize lifestyle assessment and modification programs. Full article

Muco-obstructive lung diseases, such as chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF), and bronchiectasis, are characterized by the accumulation of highly viscoelastic mucus that compromises mucociliary clearance and fosters infection and inflammation. Mucoactive therapy, encompassing both true mucolytics and non-cleaving agents, seeks to restore airway patency by altering mucus structure, hydration, and transport properties, yet its clinical impact remains variable. This narrative review provides a critical reappraisal of the pharmacological actions and therapeutic outcomes of the main mucolytic agents: N-acetylcysteine (NAC), erdosteine, carbocisteine, bromhexine, ambroxol, and dornase alfa. Beyond their classical role in reducing mucus viscosity, these drugs exhibit pleiotropic effects, including antioxidant, anti-inflammatory, and immunomodulatory activities. Specifically, for thiol-based compounds, the action consists of breaking the disulfide bonds that stabilize the mucin network; for carbocisteine, it lies in modulating mucin glycosylation and chloride transport. Ambroxol and bromhexine act by stimulating surfactant secretion and enhancing mucociliary clearance. Finally, dornase alfa exerts an enzymatic effect on extracellular DNA, a key contributor to the tenacity of mucus in cystic fibrosis. Clinical evidence indicates that NAC and erdosteine can reduce exacerbation rates in COPD, carbocisteine shows benefit with prolonged administration, and dornase alfa remains a cornerstone in CF management. However, therapeutic efficacy is constrained by heterogeneous mucus composition, pharmacokinetic limitations, and disease-specific variability. A key interpretative message is that clinical benefit appears greatest when the dominant biophysical determinant of mucus pathology is specifically targeted, supporting a transition from broad disease-label prescribing to mechanism-informed, phenotype-aware mucolytic therapy. Emerging strategies, such as agents targeting mucin–DNA interactions and advanced inhalation delivery systems, promise improved specificity and durability. By integrating mechanistic insights with clinical data, this review underscores the need for personalized mucolytic therapy and innovative approaches to overcome current challenges in managing muco-obstructive lung diseases. Full article

Arsenic-contaminated groundwater is a major environmental concern, particularly in northern Argentina. Here, Microbacterium oxydans AE038-20, isolated from arsenic-rich groundwater, was investigated to elucidate its tolerance and transformation capacity. Growth assays showed that the strain tolerates inorganic arsenic [As(III), As(V)] and methylarsenite [MAs(III)] without significant inhibition. Speciation analyses revealed progressive oxidation of As(III) to As(V), reaching near-complete conversion after 10 days. Similarly, MAs(III) was fully oxidized to MAs(V). Genome sequencing identified ars-related determinants, including arsR, arsC, putative arsenite efflux systems, and arsP, supporting detoxification via arsenate reduction and arsenite efflux. Proteomic analyses confirmed the expression of proteins related to arsenic resistance, oxidative stress response, and metal transport. However, no canonical arsenite oxidases were detected at either the genomic or proteomic level. Despite this, M. oxydans AE038-20 exhibited clear arsenic oxidation activity. The detection of pigment-associated proteins and in vitro oxidation assays suggest an alternative mechanism potentially mediated by redox-active pigments. These findings highlight an alternative pathway for arsenic transformation in environmental bacteria. Full article

Fermented dairy products with probiotic and functional properties are a promising matrix for modulation of the human microbiome. The functionality of such products will depend not only on the technological properties of the lactic acid bacteria included in the starter culture but also on the combined effects of metabolites, enzymatic activity, stress tolerance, and strain-specific adaptation mechanisms. The aim of this work was to conduct a comprehensive analysis of Lactobacillus strains to facilitate the design of microbial consortia for the development of fermented products with diverse functional properties. Twenty Lactobacillus strains from different species were investigated using microbiological, physicochemical, and biochemical methods to evaluate antagonistic activity against opportunistic microorganisms and to assess changes in amino acid and organic acid profiles, vitamin content, fatty acid composition, and enzymatic activity. Additionally, proteomic analysis was performed to create a matrix of functional complementarity of the studied strains, representing proteins associated with antimicrobial activity, bacteriocin transport, resistance to oxidative stress, surface structure formation, and adhesion. It was shown that the studied strains exhibit pronounced functional heterogeneity, demonstrating the feasibility of scientifically based selection of strains to create next-generation fermented dairy products with predictable properties. Full article

Efficient simulation of geochemical reactions is critical for predicting the long-term chemical evolution of geological disposal repositories for radioactive waste. In large-scale reactive transport simulations, geochemical equilibrium calculations often represent a major computational bottleneck because they must be repeatedly solved for many spatial cells and time steps. This study investigates the development of machine-learning-based surrogate models that are designed to approximate geochemical equilibrium calculations and thereby significantly accelerate reactive transport simulations while reducing computational resource requirements. Calcite dissolution induced by magnesium-rich fluid inflow is used as a representative test case to evaluate the feasibility and performance of such surrogate models. Training and validation datasets were generated using the IPhreeqc C++ API, enabling the automated execution of a large number of PHREEQC equilibrium simulations across a chemically relevant parameter space. The resulting dataset captures nonlinear relationships between initial aqueous composition and outputs of interest after chemical equilibration, including aqueous species concentrations and amounts of minerals. Fully connected feed-forward neural networks were designed and implemented in TensorFlow to reproduce PHREEQC results, and the influence of key hyperparameters—such as network depth, width, activation functions, learning rate, and batch size—was systematically investigated. The results demonstrate that surrogate model accuracy and training stability are sensitive to hyperparameter selection, even for a relatively simple chemical system. Properly configured neural network architectures reproduce equilibrium geochemical responses with high accuracy and provide a computationally efficient alternative to repeated PHREEQC calculations, highlighting their potential for accelerating large-scale reactive transport modelling workflows. Full article

In the context of escalating global warming and the urban heat island effects, recurrent extreme heat events will increase the exposure risk of cyclists, which will have a detrimental effect on both health and the sustainability of active mobility. Nevertheless, this risk has not been given sufficient attention. To accurately quantify the levels of solar radiation exposure experienced by cyclists in high-temperature conditions and the impact of the built environment on these levels, this study focuses on central Shanghai as a case study. The integration of Mobike trajectories, street view imagery, and solar radiation data sets enabled the quantification of trip-level cumulative radiation exposure and per-minute exposure levels. Subsequently, the XGBoost–SHAP interpretability framework was employed to decipher the mechanisms of the built environment. The following key findings have been identified: (1) Spatiotemporally, the radiation exposure level of cyclists exhibited an inverted U-shaped pattern, peaking at midday (10:00–15:00), with per-minute values of 862–943 W/m². This intensity significantly exceeded that observed during the morning (407 W/m²) and evening (253 W/m²). (2) It was determined that geometric factors dominated the radiative exposure level. The shading index demonstrated a critical influence (57% contribution), with exposure reduction intensifying beyond 0.41 yet exhibiting diminishing marginal effects after 0.6. The sky view factor and building height elevated exposure risk by amplifying direct solar radiation. (3) Socioeconomic factors had divergent effects on the radiation exposure level of cyclists: commercial/business densities reduced exposure through continuous building shade, whereas transportation facility density increased exposure due to low-shaded layouts. Consequently, this study proposes “shaded corridors” as a core mitigation strategy, establishing a tripartite intervention framework (spatial-facility-governance) for radiation exposure reduction. The present study provides scientific foundations for the targeted enhancement of heat resilience in active mobility. Full article

The rapid demand for sustainable and efficient energy storage solutions has prompted the pursuit of eco-friendly electrode materials. Biomass-derived carbons from food waste offer a promising pathway to meet this need by combining waste valorization, environmental benefits, and high electrochemical performance. This review highlights that food waste biomass is an effective and inexpensive source of precursors for producing high-performance carbon materials for supercapacitors. Food waste, which includes fruit peels and vegetable residues, cereal husks, and oilseed residues, is a good source of lignocellulosic components, heteroatoms, and structural features that determine the electrochemical characteristics of the derived carbons. These wastes produce hierarchically porous carbons with high surface areas (>1500 m² g⁻¹) on pyrolysis and activation that provide superior ion transport, wettability and pseudocapacitive behaviour. Their electrochemical performance includes capacitances up to 520 F g⁻¹ and energy densities of 35–70 Wh kg⁻¹ in optimized systems, particularly under extended voltage windows or in hybrid supercapacitor configurations, and high cycling stability is equal to or even better than traditional carbons such as activated carbon and graphene. Additionally, biomass valorization contributes to a high level of greenhouse gas capture, decreases landfill, and correlates with the idea of a circular economy. The commercialization potential of biomass-based supercapacitors is supported by recent developments in AI-based optimization, combined with scalable synthesis methods, which would support ecologically, economically, and technologically sustainable energy storage on a large scale. Full article

Background:Pinellia ternata is a major medicinal herb widely utilized in traditional medicine, but is sensitive to high temperature, which often triggers a severe “sprout tumble” phenomenon. Methods: To elucidate the molecular mechanisms of heat tolerance in P. ternata, we screened two contrasting germplasms: the heat-tolerant JBX1 and the heat-sensitive XBX4. In the present study, a combined analysis of physiology, transcriptome, and metabolome was performed on JBX1 and XBX4 under heat stress at 40 °C. Results: JBX1 exhibited significantly greater leaf thickness, higher basal chlorophyll content, more stable antioxidant enzyme activities, and lower oxidative damage than XBX4 under heat stress. Transcriptomically, JBX1 maintained elevated basal expression of genes encoding key enzymes in carbon fixation, amino acid metabolism, and phenylpropanoid biosynthesis, as well as those encoding heat shock transcription factors (HSFs), heat shock proteins (HSPs), and the thermosensor Thermo-With ABA-Response 1 (TWA1). Metabolomically, JBX1 accumulated higher levels of key primary metabolites, antioxidants, and protective phenylpropanoids under both control and heat conditions. Notably, a “polarity reversal” emerged in nitrogen metabolism, where core amino acids accumulated in JBX1 but were depleted in XBX4. Integrated analysis revealed a more coordinated gene–metabolite network in JBX1 involving the phenylpropanoid, ATP-binding cassette (ABC) transporter, and glutathione pathways. Conclusions: Our findings demonstrate that JBX1 possessed stronger basal thermotolerance, which is derived from coordinated establishment of higher constitutive metabolic reserves and efficient dynamic metabolic reprogramming. This study provides insights into the molecular mechanisms of heat stress in P. ternata. Full article

The plasma membrane plays essential roles in cellular transport and signaling. One of its fundamental structural features is the asymmetric distribution of lipids between the inner and outer leaflets. This asymmetry is actively maintained by lipid transport systems, including flippases, floppases, and scramblases, and is critical for membrane integrity and signaling regulation. Accumulating evidence indicates that membrane lipid asymmetry is frequently altered in cancer cells, leading to the externalization of normally inner-leaflet phospholipids such as phosphatidylserine and phosphatidylethanolamine. These alterations can influence tumor signaling, immune interactions, and membrane-associated biological processes. Recent studies further suggest that metabolic reprogramming in cancer may play an important role in regulating membrane lipid asymmetry. Changes in cellular energy status, oxidative stress, calcium signaling, and lipid metabolism can modulate lipid transport systems and membrane organization. In addition, tumor metabolism generates diverse circulating metabolites, including lactate, lysophospholipids, and acylcarnitines, which may influence membrane properties and lipid redistribution. These observations raise the possibility that membrane lipid asymmetry functions as a metabolically responsive interface linking intracellular metabolic state to cell surface signaling and tumor–microenvironment interactions. In this review, we propose a conceptual framework in which cancer-associated metabolic reprogramming influences lipid transport systems and membrane organization, thereby reshaping phospholipid distribution across the plasma membrane. We discuss how metabolic perturbations—including changes in energy metabolism, redox balance, calcium signaling, and lipid remodeling—may regulate membrane lipid asymmetry and explore the implications of these processes for tumor signaling, immune interactions, and emerging membrane-targeted therapeutic strategies. Full article