Search Results (5,518)

Drought stress significantly constrains crop productivity and yield stability. Sorghum (Sorghum bicolor L. Moench), a C4 cereal widely cultivated in arid and semi-arid regions, exhibits high water-use efficiency and remarkable drought tolerance. Understanding both the impacts of drought and the plant’s response mechanisms is essential for enhancing drought resilience in this crop. In this study, physiological changes and differential protein accumulation were analyzed in leaves of the sorghum inbred line BT × 623 under 10% PEG-6000-induced drought stress. The physiological adaptation to drought was characterized by improved water retention and mitigation of oxidative damage through the synergistic action of antioxidant enzymes. Using two-dimensional electrophoresis (2-DE) and MALDI-TOF-TOF mass spectrometry, 43 protein spots were successfully identified, corresponding to 38 unique proteins differentially expressed under osmotic stress. These proteins function in diverse biological processes, including protein synthesis, processing, and degradation; photosynthesis; carbohydrate and energy metabolism; transcriptional regulation; stress and defense; lipid and membrane metabolism; and amino acid metabolism. Proteomic profiling revealed that the coordinated modulation of multiple functional groups, such as those involved in photosynthesis, energy metabolism, transcriptional adjustment, ROS scavenging, and protein turnover, underpins sorghum’s osmotic stress adaptation. These findings provide key insights into the drought resistance mechanisms of sorghum at both physiological and proteomic levels. Full article

Background: Fundamental movement skills (FMS) underpin lifelong physical activity (PA) and health, yet many children are failing to meet age-appropriate standards. Caregivers hold a critical influence over children’s motor development, but little is known about what helps or hinders family participation, including messaging. This study explored the determinants of family FMS engagement in the United Kingdom (UK) during early childhood, addressing unexplored gaps in how guidance reaches families and the role of grandparents in supporting children’s motor development. Methods: Twenty-three semi-structured interviews were conducted with 15 caregivers and 8 educators, including 4 grandparents and 2 family hub practitioners who offered original insights. Eleven children aged 3–5 years completed a flexible draw-and-tell task, enabling inclusion of rarely represented 3-year-olds. Thematic analysis was deployed. Results: Families and outdoor spaces were pivotal to children’s movement opportunities. However, awareness and understanding of FMS and UK PA guidance were poor, even among educators, disrupting dissemination of information to families. Greater emphasis on PA and FMS concepts within professional development, alongside clearer signposting to resources, more visible public-facing campaigns, and digital formats, could improve how families receive these messages. Tensions emerged between parents’ concerns about grandparents’ physical capability and grandparents’ belief that they could adapt to support children’s development. Unexpectedly, no children drew technology despite screen time frequently displacing active play, hinting at its normalisation and regulatory role in children’s lives. Conclusions: To enhance family understanding, value, and participation in FMS, UK policy must evolve to become more visible, relatable, and responsive to diverse family needs. Full article

Opioid analgesics are essential in the management of severe and chronic pain; however, their prolonged use is limited by the onset of analgesic tolerance and opioid-induced hyperalgesia (OIH). Recent studies increasingly implicate both synaptic functional and structural plasticity within nociceptive pathways as crucial mechanisms in OIH and tolerance. This review integrates current mechanistic understanding of how opioids alter synaptic transmission throughout the dorsal root ganglia (DRG), spinal dorsal horn, and supraspinal nociceptive networks. Peripherally, μ-opioid receptor (MOR) activation on TRPV1-positive nociceptors initiates presynaptic long-term potentiation (LTP), forming an early substrate for central sensitization. In the spinal dorsal horn, chronic opioid exposure drives NMDAR-dependent LTP, TRPC-mediated calcium influx, and actin cytoskeleton remodeling, leading to persistent increases in synaptic strength and excitatory connectivity. In supraspinal regions—including the ventral hippocampus, prefrontal cortex, and amygdala—opioids promote experience-dependent plasticity and predictive coding, which link environmental cues to reduced analgesic effectiveness. In addition to synaptic functional plasticity, opioid-induced synaptic structural plasticity within nociceptive pathways has been shown to underlie the long-term nature of opioid analgesic tolerance. Collectively, these data define a distributed network of opioid-responsive synapses whose pathological potentiation underpins the development of tolerance and hyperalgesia. Elucidating these mechanisms underlying OIH and tolerance paves the way for targeted therapeutic strategies that maintain analgesic efficacy while minimizing adverse synaptic remodeling and negative outcomes. Full article

Multiple myeloma (MM) and osteosarcoma (OS) are two biologically distinct osseous malignancies with similar molecular networks that present translational challenges for their computational modeling. This comparative research analyzes MM and OS biology relevant to in silico approaches, focusing on PI3K-AKT-mTOR signaling, the RANK-RANKL-OPG axis, angiogenic factors (VEGF, TGFs), and immune mediators in MM, alongside the transcription factors (SOX9, RUNX2), signaling pathways (PI3K-AKT-mTOR, NOTCH), immune cell state (TAM2), and interleukins in OS. Based on this pathophysiologic foundation, the review outlines five computational paradigms: (i) mechanistic models; (ii) data-driven/machine learning schemes; (iii) hybrid mechanistic approaches; (iv) digital twins/virtual cohorts, and (v) MIDD/PBPK models for real-world applications. A cross-cancer comparison section summarizes common and distinct biological axes and their computational translation as well as the overlapping features from the bone microenvironment. For both MM and OS, the research assesses strengths, limitations, and data needs of current models, outlining the strategic objectives for next-generation multiscale, AI-enabled models providing a roadmap for tissue engineers, oncology scientists, and translational researchers to design clinically relevant preclinical tests and accelerate safer, more effective strategies for tumor-affected bones. The differences between MM and OS impose distinct biological constraints, so their comparisons are rare. Combining all these features with artificial intelligence capabilities will underpin a promising transition in the development of in silico adaptive and learning models. Full article

This is a study of the nun as a queer archetype of femininity across Kate O’Brien’s fiction and non-fiction. Alongside characters who are actual nuns, the fiction includes characters who can be described as ‘nun-like,’ especially in their renunciation of sexual desire. In the fiction, this secular renunciation is aligned with religious celibacy as actively chosen and ethically purposeful and situated as similar to artistic creativity. The study argues that O’Brien’s nuns are paradoxical and queer figures, undermining the temporality, class politics and models of human subjectivity central to O’Brien’s own ideological commitments. Attending to these nun figures prompts significant questions about the liberal feminist politics underpinning contemporary O’Brien studies and the prevailing critical reception of O’Brien as an exemplary Irish woman writer. Full article

Forest structural complexity underpins habitat quality, microclimate buffering, and resilience, yet it remains poorly characterized across the Hindu Kush Himalaya (HKH) where field inventories and airborne LiDAR are difficult to scale across rugged terrain. Conservation planning and protected-area evaluation in the HKH therefore often rely on canopy height or cover proxies that do not directly represent vertical structural organization. Here we develop a repeatable, uncertainty-aware indicator of forest structural complexity from GEDI waveform LiDAR using the Waveform Structural Complexity Index (WSCI) and its prediction intervals. We first define a conservative analysis footprint (“trustable pixels”) by combining a woody-vegetation screen with minimum GEDI sampling support and canopy-stature plausibility, and by excluding the highest-uncertainty tail using a relative prediction-interval criterion. To separate complexity from canopy height, we model the HKH-wide expected WSCI–RH98 relationship and map height-normalized excess complexity (observed minus expected), identifying structural complexity hotspots and coldspots as the upper and lower tails of the excess distribution. Anomaly patterns are strongly organized along elevation and treeline-relevant belts and show coherent departures among ecoregions that persist after stratified adjustment for elevation and mean annual precipitation, indicating additional controls beyond broad environmental gradients. Protected areas exhibit systematically lower hotspot prevalence than surrounding landscapes, and within-elevation comparisons suggest this association is not explained by elevation alone, highlighting the need to interpret protected-area signals in the context of placement and land-use pressure. Overall, the anomaly atlas provides an operational indicator framework to stratify monitoring, prioritize field validation, and support the landscape-scale assessment of structural conditions beyond canopy height across one of the world’s most critical mountain forest systems. Full article

Gallium-based liquid metals have garnered significant attention due to their distinct combination of metallic and liquid behavior at room temperature. This review systematically examines the fundamental properties and advanced multifunctional applications of this class of materials. Key characteristics such as low melting point, excellent fluidity, high electrical and thermal conductivity, and biocompatibility are first highlighted. Subsequently, progress in four major application areas is discussed. In sensing, these materials enable the fabrication of highly compliant and responsive devices capable of monitoring strain, temperature, and electromagnetic fields. Within biomedical engineering, their inherent low toxicity and biocompatibility underpin advances in biosensing platforms, precision drug delivery, and engineered tissue scaffolds. For energy-related applications, they are utilized in batteries and high-efficiency thermoelectric systems for converting heat into electricity. In catalysis, their dynamic and tunable interfaces facilitate efficient carbon dioxide conversion and selective thermocatalytic reactions. This review summarizes current advances in the application of gallium-based liquid metals and provides critical perspectives on future developments and opportunities in this technology. Full article

Functional pet food has grown rapidly, in line with the accelerated humanization of pets, growing attention to relations between diet and health, and mounting sustainability awareness. The article provides a critical overview of recent developments and new trends in functional pet food, combining data from published works, patents and market-driven innovative companies. The current trends depict a transition from single-nutrient fortification to integrated nutrition interventions through modulation of gastrointestinal health, immunity, metabolism, cognition and age-associated conditions. Special attention is dedicated to probiotics, prebiotics, postbiotics, polyphenols and novel protein sources, as well as innovations in processing and delivery technologies. The review highlights ongoing issues on the relevance of study design, available long-term safety information and our capacity to mechanistically underpin claims with respect to function. Because this review maps clusters of innovation and clusters of underdeveloped knowledge, it offers a roadmap for the translational pathway from scientific discovery to commercialization. The results highlight a call for harmonized methods, longer duration studies and integrative omics-based approaches in order to improve the evidence basis formulation and responsible marketing of future functional pet food products following credible, safe and sustainable strategies. Full article

Neuropsychiatric diseases are characterized by complex molecular underpinnings that remain challenging to fully elucidate. Molecular dynamics (MD) simulations have emerged as a powerful computational tool, providing a crucial bridge between static genetic data and the dynamic functional consequences of molecular alterations. This review offers a comprehensive overview of the application of MD simulations in studying the molecular basis of neuropsychiatric disorders. We highlight key applications, including the assessment of mutation pathogenicity in disease-associated proteins, the influence of post-translational modifications on protein function, folding, misfolding, and aggregation, and the characterization of psychopharmacological drug–target interactions at atomic resolution. Through relevant examples from research on psychiatric and neurodegenerative diseases, we illustrate how these computational methods are implemented to gain mechanistic insights. Importantly, this review traces the historical development of MD simulations in biological applications, critically examines the method’s limitations, and outlines future perspectives for simulating long-timescale physiological processes, large molecular ensembles, and even whole-cell environments. Ultimately, this work highlights MD simulations as a useful and complementary tool for modern neuropsychiatry research, capable of revealing disease mechanisms and guiding the development of novel therapeutic strategies. Full article

The growing prevalence of home education necessitates exploration of parental involvement outside traditional schooling environments. This paper conceptualises parental involvement within home education decision-making. Core elements of decision making, including Choices, Contexts, Challenges and Changes, are integrated with Bronfenbrenner’s bioecological systems theory to create the 4Cs model of parental decision-making in home education. The 4Cs model is developed from integrating findings from the literature with previous empirical work on how parents make and explain decisions in home education. The present paper uses this model to organise and explain parental decision-making in a structured way. Building on critiques of school-centric parental involvement models, the 4Cs model steps away from assumptions that position parents as passive participants in schools’ agendas to instead illustrate parents’ active collaboration and involvement in their children’s education. The paper goes on to use the 4Cs model to help reframe Epstein’s typology of parental involvement to bridge home education research and broader scholarship on parental involvement. It provides a structured lens to analyse the decision-making processes that underpin why families choose home education and how it is enacted in practice. Central to this framework is the concept of parental agency, which is decoupled from school-based imperatives and positioned as the driving force in constructing tailored learning environments. This theorisation offers a critical lens for examining how parents navigate educational trade-offs, socioecological constraints, and adaptive strategies. We reframe parental involvement as deliberative, context-responsive praxis, creating potential for the 4Cs framework to act as a transferable model for analysing agency-driven parental engagement across diverse educational settings. Full article

Elaeocarpus sylvestris (Lour.) Poir., an evergreen tree native to East and Southeast Asia, has gained increasing scientific attention owing to its broad pharmacological properties. Traditionally used in East Asian medicine to treat inflammation, fever, and infectious diseases, modern research has revealed diverse bioactivities, including potent antioxidant, anti-inflammatory, antiviral, anticancer, antidiabetic, and immunomodulatory effects. This therapeutic potential is primarily attributed to its rich phytochemical composition, particularly polyphenols such as geraniin, 1,2,3,4,6-penta-O-galloyl-β-D-glucose and quercetin. This review particularly focuses on the chemistry of E. sylvestris, summarizing structurally elucidated compounds, including hydrolysable tannins, flavonoids, and triterpenoids, along with recent insights into the structure–activity relationships that underpin these antiviral, antioxidant, and anticancer activities. Recent studies have demonstrated substantial antiviral efficacy of E. sylvestris extracts and isolated compounds against major human pathogens, including herpesviruses, influenza A virus, and SARS-CoV-2, supported by in silico, in vitro, in vivo, and early-phase clinical evaluations. Its cosmeceutical applications, including antioxidant, skin-whitening, and blue-light protective effects, further highlight its multifunctional potential. To our knowledge, this is the first comprehensive review summarizing the phytochemistry, pharmacological activities, therapeutic potential, and cosmeceutical applications of E. sylvestris. Despite these promising findings, challenges remain in elucidating precise molecular mechanisms, pharmacokinetics, and clinical validation. This review identifies current research gaps and future directions necessary to advance E. sylvestris as a scientifically validated natural therapeutic resource. Full article

Background/Objectives: Autophagy plays a role in systemic lupus erythematosus (SLE) pathogenesis. Nevertheless, the specific genetic determinants underpinning this process remain poorly characterized. Summary data-based Mendelian randomization (SMR) analysis was therefore utilized to pinpoint autophagy-related genes associated with SLE risk. Methods: We analyzed 700 autophagy-related genes, integrating methylation quantitative trait loci (mQTL), expression QTL (eQTL) from blood and relevant tissue, and protein QTL (pQTL) data with genome-wide association studies (GWAS) data on SLE from the IEU dataset (discovery). GWAS data from FinnGen and the GWAS Catalog were used as replication datasets. Colocalization analysis identified shared genetic variants. Blood samples from 10 healthy control and 20 SLE patients were collected and analyzed for the expression of candidate genes. Results: Our SMR analysis identified suggestive associations between NLRP6 expression (OR = 0.528, 95%CI = 0.291–0.96) and p27Kip1 protein abundance (OR = 0.269, 95%CI = 0.08–0.904) with SLE susceptibility in the discovery cohort, supported by colocalization evidence. Additionally, we found that the methylation of the NLRP6 promoter (cg06432119) was significantly increased, while NLRP6 expression and p27Kip1 level were significantly decreased in SLE patients compared to controls. Furthermore, NLRP6 mRNA expression was significantly negatively correlated with the SLE severity (SLEDAI-2000). Conclusions: These findings not only prioritized candidate genes via SMR analysis but also provided evidence of epigenetic dysregulation of NLRP6 and its correlation with disease activity in SLE, thereby offering novel insights into the underlying mechanisms. Full article

Spinocerebellar Ataxia type 2 (SCA2) and Amyotrophic Lateral Sclerosis type 13 (ALS13) are triggered by polyglutamine expansion in Ataxin-2 (ATXN2). To understand these neurodegenerative disorders at the molecular level, the brains of 10-month-old Atxn2-CAG100-knockin mice were analyzed as microglial, astroglial and neuronal fractions via global RNA sequencing. Data were validated by comparison with the spinal cord oligonucleotide microarray profile or filtered by RNA-seq consistency. Here, we show that the mutation causes a massive inflammatory response in microglia and a reciprocal loss of neuronal transcripts in glial fractions, suggesting severe synapse loss. Beyond these general neurodegenerative signs, we identify pathognomonic changes in the machinery for protein translation and RNA splicing. Glial fractions showed upregulation of Gpnmb (to 2082%), Cst7, Clec7a, Axl, Csf1, Lgals3, Lgals3bp, Slc11a1, and Usp18 as an unspecific neuroinflammatory signature, versus downregulation of axonal Nefh (to <19%), and synaptic Scn4b, Camk2b, Rab15, and Grin1 mRNAs correlating with circuit disconnection. In all fractions, reductions in Kif5a, Rph3a, and Cplx1 were noted versus disease-specific inductions of ribosomal subunits, presumably mirroring the partial loss-of-function of ATXN2 as RNA translation modulator. Selective accumulations of embryonic factors Rnu1b2 and Eef1a1 versus downregulation of adult Eef1a2 specify the mutation impact on splicing and translation elongation. As a potential underpinning of toxic gain-of-function, the proteostasis transcript Rnf213 appeared increased in astroglial and microglial fractions. These transcriptome data suggest altered ribosomal and spliceosome machinery, with massive microgliosis versus mild astrogliosis, at the core of SCA2 and ALS13. Full article

The development of high-performance electrochemical sensors requires precise integration of electrode active materials that provide both superior electrocatalytic activity and long-term structural stability. Herein, we report a systematically optimized, one-pot electrochemical deposition approach for the fabrication of nanographenide-based nanoarchitectures, incorporating either a conducting polymer (PEDOT-NG) or Prussian blue (PB-NG). Derived from optimization-driven structural refinement—including applied potential, electrodeposition time, and precursor concentration—the robust nanoarchitecture exhibits a hierarchical morphology that provides an expanded electroactive surface area, accelerating charge transfer and enhancing electrochemical catalytic activity. The optimized PEDOT-NG exhibits exceptional sensitivity for the simultaneous determination of ascorbic acid (AA), dopamine (DA), and uric acid (UA), achieving wide linear ranges with low detection limits of 4.1, 0.12, and 0.18 μM, respectively. The PB-NG achieves a limit of detection of 4.39 μM, driven by highly reversible and stable redox kinetics. This performance is underpinned by narrowed peak-to-peak separations (ΔE) and reduced redox potentials. These results underscore the pivotal role of precise parametric control in developing high-performance electrochemical sensors. Furthermore, this work establishes a comprehensive strategy for designing resilient electrode active materials, thereby paving the way for next-generation electrochemical platforms tailored for diverse and robust sensing environments. Full article

In the extraction of shale gas and oil, the vibration characteristics of the drill string significantly influence wellbore quality, potentially leading to wellbore instability, excessive tool wear, and diminished drilling efficiency. This study tackles the challenges associated with drill string vibrations by developing an integrated technical framework of multi-field coupled dynamic modeling, Sobol-based key parameter identification, and NSGA-II-driven multi-objective structural optimization, and proposes a synergistic vibration suppression strategy combining structural parameter adjustment and hydraulic damper configuration based on multibody dynamics and finite element analysis. Initially, a dynamic model that accounts for the coupling between the wellbore and the drill string is developed to scrutinize the impact of various vibration modes on wellbore quality. Subsequently, detrimental vibrations are mitigated through the optimization of structural parameters, including but not limited to stiffness distribution and the strategic placement of vibration absorbers. Finally, the efficacy of the optimized design is substantiated through numerical simulations and field experiments. The results demonstrate that the optimized drill string achieves a simulation average reduction of 30% in lateral vibration amplitude across the rotational speed range of 60–120 RPM and a simulation average improvement of 25% in the attenuation of axial vibration energy. These enhancements notably bolster drilling stability and elevate wellbore quality. This research furnishes both theoretical and technical underpinnings for the efficient development of shale gas and oil resources. Full article