Physical disuse is a major risk factor for complex regional pain syndrome type I. Using a rat chronic post-cast pain model, we investigated how oxidative stress modulates pain processing across the neuraxis and evaluated sex as a biological variable. Following immobilization, both sexes developed widespread mechanical hyperalgesia, which was markedly attenuated by the antioxidant Tempol. However, we uncovered a striking phenotypic dissociation: whereas male rats also developed tactile and cold allodynia, female rats completely lacked tactile allodynia. Peripherally, Tempol reduced neurogenic inflammation and suppressed p38 MAPK phosphorylation in peptidergic and nonpeptidergic dorsal root ganglion nociceptors, demonstrating a conserved reactive oxygen species-dependent "hardware" for mechanical pain. Centrally, Tempol inhibited plasticity-related pERK expression in neurokinin1 receptor-positive projection neurons and stimulus-evoked c-Fos in the lumbar (L5) and sacral (S2) dorsal horn. Crucially, the sex-specific behavioral divergence correlated with distinct neuroimmune profiles. Quantitative polymerase chain reaction revealed that while male rats exhibited a robust pro-inflammatory cytokine upregulation (C-C motif chemokine ligand 2, interleukin-1beta, interleukin-6) in the soleus muscle, this inflammatory cascade was markedly blunted in female rats. Consistent with this lack of peripheral inflammatory amplification, optogenetic stimulation of nonnociceptive Aβ fibers failed to induce c-Fos in the female spinal cord and central amygdala-a maladaptive sensory processing shift that Tempol successfully reversed in male rats. These findings demonstrate that disuse-induced oxidative stress initiates sensitization across the neuraxis. Importantly, our study reveals that while reactive oxygen species drives mechanical pain uniformly, the development of tactile allodynia requires a sexually dimorphic inflammatory amplification, underscoring the critical need for personalized, sex-specific therapeutic strategies in pain management.

Cold plasma has emerged as a promising non-thermal technology for modifying hydrocolloid gums owing to its ability to induce targeted physicochemical and structural changes under mild processing conditions. This review comprehensively summarizes the recent advances in CP-induced modification of food hydrocolloids, including xanthan gum, guar gum, gum Arabic, κ-carrageenan, agar, alginate, konjac glucomannan, basil seed gum, fenugreek gum, locust bean gum, and Lepidium perfoliatum seed gum. The effects of CP treatment on physicochemical, structural, rheological, and functional properties are critically discussed with emphasis on the influence of processing parameters such as plasma type, applied voltage, power, gas composition, and treatment duration. The reviewed studies demonstrate that CP modifies gum properties primarily through reactive species, leading to surface etching, depolymerization, oxidation, and changes in functional groups. These modifications influence moisture content, color, molecular weight, crystallinity, surface morphology, wettability, solubility, water-binding capacity, viscosity, and interfacial properties. However, the extent of modification differs among gums depending on their molecular architecture and treatment conditions. Overall, CP has shown considerable potential to improve the functional performance of gums while providing an environmentally friendly alternative to conventional thermal and chemical modification methods. This review further summarizes the potential applications of plasma-modified gums in food systems and discusses the current research gaps and future perspectives to facilitate their industrial utilization.

Enteroviruses are among the most common viral pathogens in humans, causing illnesses ranging from the common cold to severe and sometimes life-threatening diseases such as acute haemorrhagic conjunctivitis or poliomyelitis. To replicate efficiently within host cells, enteroviruses hijack several host factors, including the lipid kinase PI4KB and the adaptor protein ACBD3. During infection, ACBD3 is recruited to viral replication sites through a direct interaction between its C-terminal GOLD domain and viral non-structural 3A proteins. Here, we identify exportin 1 (XPO1) as a host factor involved in enteroviral replication. We demonstrate that 3A proteins of various enteroviruses recruit the host proteins ACBD3 and XPO1 to form a stable ternary complex. Chemical inhibition of XPO1 with selinexor, (originally developed as an anti-cancer medication), significantly attenuates coxsackievirus B3 replication in human cells. Consequently, our study identifies XPO1 as a host target for potential anti-enteroviral interventions, highlighting an immediate opportunity for drug repurposing.

Abnormal interoception may be a hallmark of medically-unexplained symptoms (MUS), although its underlying mechanisms remain unclear. We investigated whether MUS are associated with enhanced interoceptive learning, potentially facilitated by post-learning stress. From 177 volunteers providing self-reports on MUS, 22 individuals were recruited from the upper and 26 from the lower quartile (high/HSR and low symptom reporters/LSR) and randomly assigned to a stress or a control condition (LSR-stress/n = 12; LSR + stress/n = 14; HSR-stress/n = 11; HSR + stress/n = 11). Participants underwent a heartbeat perception training as interoceptive perceptual learning task, followed by a socially-evaluated cold pressor stress or a control intervention. Interoceptive accuracy was measured using the heartbeat counting and discrimination task at baseline (T₁), 30 min. (T₂) and 24 h (T₃) after the stress/control intervention. Sympatho-adreno-medullary (SAM) and hypothalamic-pituitary-adrenal (HPA) axes were measured in terms of heart rate, blood pressure (SBP/DBP) and salivary cortisol reflected reactivity. The stress test induced a robust increase of SBP/DBP in both stress groups, and a cortisol increase in the LSR + stress group only. Post-learning stress induced an increase of interoceptive accuracy (heartbeat discrimination) the HSR + stress group only. Correlation/regression analyses showed a positive association between changes in interoceptive accuracy (heartbeat discrimination) from T1 to T2 with MUS, and changes from T2 to T3 with SAM and HPA axis responsiveness. Post-learning stress may enhance interoceptive learning in MUS, which may explain why benign body sensations are perceived as symptoms. While MUS-specific heightened attention to body sensations may be responsible for early effects, physiological stress axes may explain late effects of interoceptive learning, including overnight consolidation.

Urban forests modify near-surface air quality; however, the vertical distribution of air pollutants within winter canopies remains poorly understood. This is especially true in cold-climate cities, where heating emissions and stable atmospheric conditions intensify pollution. To address this, we established a multi-level monitoring system in an urban forest in Shenyang, Northeast China, to measure the concentrations of PM2.5, PM10, O3, NO2, SO2, CO, and meteorological variables at 1.5, 10, and 20 m. The observations showed a pronounced height-dependent stratification during winter. PM2.5 and PM10 concentrations were generally higher at 10 and 20 m than at 1.5 m, whereas O3 and CO concentrations were relatively higher at the pedestrian level. NO2 and SO2 exhibited mid-canopy concentration maxima. Statistical and machine learning analyses revealed that meteorological factors, particularly relative humidity and wind speed, were associated with pollutant variability, although these associations were highly dependent on canopy height and pollutant type. These findings provide field evidence of the distinct vertical distributions of air pollutants within a northern urban forest during winter and demonstrate the importance of considering vertical heterogeneity when assessing air quality within urban forest canopies.

Temperature is a biologically active physical variable in skeletal tissues, but apparently contradictory findings often arise because thermal magnitude is reported without the accompanying time, spatial, mechanical, and pathological context. This critical review synthesizes evidence on temperature-dependent regulation of bone and cartilage using a thermal-dose framework that distinguishes local mild hypothermia, chronic systemic cold exposure, adaptive mild heating, and hyperthermic injury. Representative studies indicate that no universal boundary temperature exists: transient exposures of approximately 39-41 °C can support heat-shock-protein-dependent osteogenic or chondrogenic adaptation, whereas longer exposures at the same or slightly higher temperatures may inhibit proliferation; cartilage injury increases steeply around 50-55 °C, while sustained culture at 34-35.5 °C suppresses osteoblast differentiation and promotes osteoclastogenesis. We therefore interpret biological outcome as a function of temperature-time history, spatial gradients, delivery modality, tissue depth, mechanical/osmotic co-stimulation, and disease state rather than nominal temperature alone. At the molecular level, mild heat can be buffered by proteostasis networks and polymodal TRPV4-Ca2+ signaling, whereas excessive thermal load increases protein unfolding/aggregation, oxidative and mitochondrial stress, and remodeling signals from osteocytes and other microenvironmental cells. Evidence is strongest for cell- and tissue-specific response windows, but clinical dose-response relationships remain incompletely validated. We propose a testable multiscale framework that links bioheat transfer, molecular damage-versus-adaptation, and multicellular remodeling, together with a minimum reporting set for thermal interventions. NIR photothermal and magnetothermal biomaterials illustrate the promise of spatially controlled heating, but their translation requires direct target-tissue thermometry, modality-specific dosimetry, and patient-stratified validation.

A dual-crosslinked gelatin-hyaluronic acid (HA) film loaded with perilla essential oil was developed for Actinidia arguta preservation. Ca2+ and gallic acid reinforced the film network, giving GH/Ca/A₃ high tensile strength (40.39 MPa), low water vapor permeability (3.34 g/m2·day), improved hydrophobicity, and enhanced thermal stability. During 12 days of storage, the essential oil-free gelatin-HA film (GH-K) reduced fruit weight loss from 40.01% to 17.98%, confirming its physical barrier-based preservation effect under ambient storage conditions. Perilla essential oil further enhanced preservation, reducing weight loss to 10.00%, maintaining firmness at 27.6 N, and lowering total colony and yeast/mold counts to 4.26 and 2.19 log CFU/g, respectively. Proteomics showed that GH/P-K modulated antioxidant defense, glutathione metabolism, phenylpropanoid biosynthesis, redox regulation, and cell wall-related pathways, linking film performance with delayed kiwiberry deterioration.

Driven by consumer demand for healthier foods, starch-lipid complexes have gained prominence for their enhanced resistance to enzymatic digestion. Microwave-assisted processing offers a highly efficient strategy to fabricate these complexes, utilizing electromagnetic effects to drive starch and lipid molecular reorganization. To elucidate the underlying mechanisms, this review establishes quantitative relationships between microwave processing parameters and the resulting structural and functional evolution. Furthermore, by integrating macroscopic experimental observations with molecular dynamics (MD) simulations, this work reveals atomic-scale interaction mechanisms, such as conformational changes, hydrogen bonding, and interfacial dynamics, that remain inaccessible to conventional experiments. Bridging experimental evidence with computational insights provides a robust theoretical basis for tailoring these assemblies and advancing the rational design of functional starchy foods with improved nutritional performance. Ultimately, this review emphasizes that future research should focus on deciphering competitive molecular interactions within intricate real-food matrices and establishing machine learning-driven predictive models to autonomously optimize processing parameters for scalable commercial applications.

Post-slaughter handling plays a critical role in determining the quality, microbial safety, and shelf life of poultry meat, yet spoilage and contamination remain persistent challenges for the poultry industry, contributing to food loss and reduced sustainability across the food supply chain. This review synthesizes current knowledge on post-slaughter factors influencing poultry meat deterioration, with emphasis on microbial ecology, spoilage mechanisms, and preservation strategies that enhance food safety and support sustainable food systems. Key processing steps, including scalding, defeathering, evisceration, chilling, packaging, and transport, are identified as major contamination points, where cold-chain integrity strongly governs microbial growth and quality loss. Major spoilage organisms, including Pseudomonas spp., lactic acid bacteria, Enterobacteriaceae, Brochothrix thermosphacta, Campylobacter, and Salmonella, are discussed in relation to psychrotrophic growth, enzymatic degradation, lipid oxidation, biofilm formation, and volatile compound production. Shelf-life assessment is evaluated using integrated microbiological, chemical (TBARS, TVB-N, VOCs), and sensory indicators, each with inherent limitations, to support effective quality management and minimize product losses. Preservation strategies are categorized into conventional (refrigeration, freezing), biological (lactic acid bacteria, bacteriocins, plant extracts), and advanced systems such as modified atmosphere packaging, vacuum packaging, active and intelligent packaging, and nanotechnology-based approaches. Evidence indicates that multi-hurdle strategies combining complementary interventions provide superior shelf-life extension through synergistic effects on microbial and oxidative stability. Collectively, these preservation strategies have the potential to reduce food loss and waste, improve resource efficiency, and enhance the sustainability of poultry production and food systems while maintaining product quality and safety.

Side effects caused by drug combinations pose a major challenge in healthcare. Knowledge of these side effects is limited because often they are not detected in clinical trials, which typically involve a restricted number of participants and tested drug combinations. We introduce DCSE (Drug Combinations Side Effects), a novel machine learning method for predicting polypharmacy side effects. DCSE learns latent signatures for drugs, drug pairs, and side effects to predict the probability that a side effect occurs in a given drug combination. We first evaluate its performance in the commonly adopted experimental settings in the literature. However, these rely on balanced testing datasets and sampled negative examples, which do not capture the highly imbalanced and structured set of unknown side effects encountered in practice. Therefore, a key contribution of this paper is the introduction of more realistic experimental settings under prospective evaluations. Here, we attempt to predict side effects reported between 2009 and 2014 after training only on data available prior to that period. These evaluations include warm-start scenarios, in which some side effects are already known for a drug pair, and cold-start scenarios, in which the model predicts side effects for previously uncharacterized drug pairs. Our results indicate that DCSE consistently outperforms state-of-the-art methods, demonstrating its robustness and efficacy in real-world applications.

Antarctic deep-sea ecosystems harboured unique and metabolically versatile micro-organisms that sustained key biogeochemical processes under extreme polar conditions. However, the genomic diversity and ecological functions of these sedimentary or deep-sea microbial communities remained largely unexplored. Here, we constructed a comprehensive deep-sea microbial dataset of the Antarctic Ocean (dsMDAO) by integrating three newly sequenced Prydz Bay sediment metagenomes with 22 publicly available datasets (9 seawater and 13 sediment samples), spanning water depths of ~300-3500 m. Genome binning yielded 186 metagenome-assembled genomes spanning 19 phyla, including 175 bacteria and 11 archaea, a substantial proportion of which represent previously uncharacterized species. Meanwhile, reads mapping with the available standard Kraken2 database (k2_standard) enabled the expansion of species richness of the dsMDAO database. Furthermore, functional annotation revealed diverse metabolic and ecological potentials, including carbon, nitrogen and sulphur cycling, as well as secondary metabolite biosynthesis, virulence-associated defence and cold-adaptation mechanisms. Sediment microbiomes exhibited higher phylogenetic and functional diversity, enriched in Thaumarchaeota and Chloroflexi, whereas seawater communities were dominated by Proteobacteria with more competitive biosynthetic and interaction potentials. Co-occurrence analyses further indicated complex and competitive networks in seawater versus modular and cooperative assemblages in sediments, reflecting distinct ecological strategies. Collectively, dsMDAO provides the first genome-resolved dataset of Antarctic deep-sea microbiota, revealing the hidden taxonomic and functional diversity that underpins ecosystem resilience in polar oceans. This resource lays a foundation for future ecological, evolutionary and biotechnological exploration of Antarctic microbial dark matter.

Emerging contaminants (EC) pose a major challenge to sustainable water and wastewater treatment because of their persistence, continuous release, biological activity, and resistance to conventional remediation. This review provides a critical assessment of EC occurrence, environmental fate, analytical detection, conventional treatment technologies, and cold plasma technology (CPT). Comparative analysis demonstrates that the principal challenge in EC remediation lies not in the absence of effective technologies but in the mismatch between contaminant properties and treatment mechanisms. Adsorption and membrane processes efficiently separate EC but generate secondary waste streams, biological treatment is constrained by microbial selectivity and slow degradation kinetics, and advanced oxidation processes achieve rapid oxidation but remain limited by energy demand, incomplete mineralization, transformation-product formation, and operational complexity. Hybrid systems improve treatment performance by integrating complementary mechanisms but increase process complexity and cost. CPT is critically evaluated as an emerging process-intensification platform capable of generating diverse reactive oxygen and nitrogen species in situ for broad-spectrum EC degradation. Current advances in plasma chemistry, reactor engineering, plasma-liquid interaction, and hybrid plasma systems are assessed alongside challenges related to energy efficiency, reactor scalability, standardized performance metrics, and real wastewater validation. The review identifies key mechanistic framework for developing efficient, scalable, and sustainable EC remediation technologies.

Copper is an essential yet potentially toxic biological trace element, whose functions in cells arise from its unique redox and coordination chemistry. The same chemical properties that make copper indispensable for a variety of fundamental biological processes, including respiration and antioxidant defense, also render it highly toxic when intracellular concentrations exceed homeostatic levels. Recently, a copper-dependent form of regulated cell death (RCD) termed cuproptosis has been identified, in which excess copper triggers cytotoxicity by directly binding the metabolic machinery of mitochondria to induce proteotoxic stress. Hallmark features of cuproptosis include the high-affinity coordination of copper with lipoylated proteins and the destabilization of iron-sulfur (Fe-S) cluster enzymes within the mitochondrial matrix, which together trigger metabolic dysfunction and protein aggregation that ultimately lead to cell death. Cuproptosis thus represents the first RCD pathway whose execution depends directly on metal-protein coordination chemistry. Emerging evidence indicates that cuproptosis may contribute to the pathogenesis of a variety of human diseases including cancer, neurodegeneration, and genetic disorders of copper metabolism. A precise mechanistic understanding of this form of RCD therefore has the potential to reveal new opportunities for therapeutic intervention. Here, we examine the bioinorganic basis of cuproptosis, its intersections with cellular copper handling systems, its role in disease processes, and the potential therapeutic strategies that aim to exploit this pathway for clinical benefit.