Novel mechanisms of dietary folic acid in improving hepatopancreas health of grass carp (Ctenopharyngodon idellus): The perspectives of autophagy and DNA methylation.

Tailoring and characterization of chitosan with well-defined pattern of acetylation.

Cognitive-behavioral treatment of gender dysphoria in youth: Opportunities, challenges, and responsibilities.

Sustainable phosphorus recovery and starch-protein-rich biomass generation from wastewater via duckweed.

Settling behaviour of pristine, UV-weathered, and biofouled particles from organic corrosion protection coatings under varying environmental conditions.

In this study, we present the first comprehensive description of the skeletal morphology of the freshwater-tolerant ray †Myledaphus bipartitus, a Late Cretaceous batomorph known from North America. These new data are based on an exceptionally well-preserved specimen from the Campanian of the Dinosaur Park Formation in Alberta, Canada, which provides valuable morphological details previously lacking for this taxon. A detailed morphological analysis was conducted, which revealed a unique combination of plesiomorphic and derived characters. Phylogenetic analyses provide support for the placement of †M. bipartitus within the order Rhinopristiformes, a group that includes modern guitarfishes and sawfishes. As the oldest known freshwater-tolerant representative of Rhinopristiformes, †M. bipartitus thus offers novel insights into the early ecological diversification of this group. The present study underscores the broader necessity for comprehensive morphological and systematic research on Late Cretaceous batomorphs. Nevertheless, the obtained results demonstrate the value of combining detailed morphological data with rigorous phylogenetic methods to elucidate the evolutionary history of extinct and extant batomorph lineages.

Reptiles are currently represented by turtles, archosaurs (crocodylians and birds), and lepidosaurs (lizards, snakes and the tuatara). However, these groups represent only a fraction of the known diversity of crown reptiles throughout geological time, and the evolutionary origin of modern reptiles remains a major outstanding topic in vertebrate systematics. The molecular consensus is that turtles are more closely related to archosaurs than to lepidosaurs, but this does not consider the many extinct neodiapsids that also have their origin close to the base of the reptile crown. Great progress has been made on this subject in recent decades through the detailed study of the anatomy and systematics of Permian and Triassic reptile fossils. Nevertheless, there is still no consensus on reptile interrelationships near the origin of the three major modern reptile clades. Here, we review the current state of systematic research for Permo-Triassic lepidosauromorphs, archosauromorphs, pantestudines, sauropterygomorphs, ichthyosauromorphs, thalattosaurs, choristoderes, weigeltisaurids, drepanosauromorphs, and ‘younginiforms’, and provide an outlook for future efforts for these groups. Addressing this systematic question is complicated by the rarity of relevant fossils for some groups and the inherent challenges of studying the phylogenetic relationships of evolutionary radiations. However, increased research efforts, including continuous new fossil discoveries and detailed morphological studies, especially those aided by micro-computed tomography, are likely to help resolve some of these issues. Furthermore, there is a desire for comprehensive morphological character-taxon matrices focusing on this part of the reptile tree, resembling in scope and approach those already available for other major lineages, such as Archosauromorpha and Lepidosauromorpha.

Cyanobacteria, among the most ancient and versatile microorganisms on Earth, thrive across different aquatic ecosystems, ranging from freshwater to marine environments. In addition to being important producers of structurally diverse secondary metabolites, these photosynthetic prokaryotes are crucial to the global cycling of carbon and nitrogen. With their wide range of biological activities, such as antibacterial, antiviral, anticancer, and anti-inflammatory properties, cyanobacterial metabolites are attractive options for use in biotechnology and medicine. In addition, some cyanometabolites have toxic properties that affect aquatic ecosystems and present problems for human health and water quality. This dual significance for ecology and biomedicine emphasizes how crucial it is to do systematic research on cyanobacterial metabolites. The chemical diversity, biological roles, and biosynthetic origins of cyanobacterial secondary metabolites are summarized in this review, with a focus on their translational potential and ecological responsibilities. Innovative approaches for accelerating metabolite discovery and characterization are also covered, including recent developments in metabolite profiling, genome mining, and artificial intelligence (AI)-assisted biosynthetic gene cluster prediction. The present review integrate ecological, biochemical, and computational perspectives emphasizes the cyanobacteria is ongoing significance as sources of bioactive chemicals for environmental sustainability, pharmaceutical research, and biotechnology.

In recent years, Shallow water Christmas trees have made a significant breakthrough internationally. It fills technological gaps, alleviates energy shortages, and offers innovative solutions for global shallow - water oil and gas development. However, this development faces challenges like special wellbore structures, complex temperature - pressure systems, and downhole operation uncertainties. These issues lead to poor wellbore pressure control and high well - control risks. Traditional steady - state models assume constant flow parameters. They fail to accurately depict wellbore dynamics, ignoring gas - liquid slippage and transient effects. As result, conventional commercial well control software exhibits significant calculation discrepancies, which hinders the design of effective well kill operations. This study introduces a semi-discrete relaxation strategy to address simulation challenges in shallow water environments. By reformulating gas-liquid two-phase flow equations into a semi-linear model with relaxation coefficients, numerical stability is enhanced. The system's dynamic evolution is analyzed using the Chapman-Enskog asymptotic expansion, while the FVS algorithm decomposes source terms to improve accuracy. Flow directions and boundary conditions are determined by solving the characteristic lines of the Jacobian matrix, enabling precise parameter calculation for the Driller’s Method. Practical applications confirm that this method significantly improves the stability and accuracy of transient wellbore simulations, offering an optimized strategy for well control operations. • Algorithmic Integration Innovation For the first time, the semi-discrete method is integrated with the FVS algorithm for solving gas-liquid two-phase flow models. The semi-discrete method transforms the nonlinear hyperbolic system into a semi-linear model, after which the FVS algorithm decomposes the source terms. This integration enables precise capture of the complex dynamic behaviors of fluid flow within the wellbore, significantly enhancing computational accuracy and numerical stability. It breaks through the limitations of traditional algorithms in resolving small-scale flow features. • Engineering Research Innovation This study conducts the first systematic research on well-killing operations in the development mode of shallow-water Christmas tree equipment, filling a gap in both theoretical and engineering practice. By thoroughly analyzing the unique wellbore structures, complex temperature-pressure systems, and operational uncertainties in shallow water, it proposes targeted well-killing strategies, providing a new technical approach and practical guidance for global shallow-water oil and gas development. • Boundary Condition Solution Innovation Through solving the characteristic lines of the Jacobian matrix to analyze the propagation of boundary physical quantities, this research achieves precise solutions for the boundary conditions during well-killing operations in shallow-water wellbores. Compared with the traditional first-order extrapolation method, which often causes numerical oscillations, this approach accurately determines the inflow and outflow directions of fluids and precisely calculates key parameters such as pressure and velocity. As a result, it significantly improves the reliability and engineering practicability of well-killing operation simulations.

Dreaming during anesthesia is common and may have mental health benefits. However, systematic research on its incidence and outcomes in clinical settings remains limited. This study implemented a standardized propofol-based, electroencephalography (EEG)-guided emergence bundle to facilitate a preemergence state conducive to dreaming, integrating it into routine care to assess adherence, dream recall, patient experience, and safety. In this prospective quality improvement feasibility study, 474 patients undergoing elective surgeries were anesthetized according to a five-element protocol: (1) preinduction verbal priming about dreaming; (2) propofol as emergence anesthetic; (3) EEG (SedLine, Masimo Corporation, USA) monitoring to guide emergence; (4) 10 min or longer of minimized stimulation before emergence; and (5) immediate postemergence interviews regarding dream recall, valence, and subjective sleep quality. In a subset of breast cancer patients (N = 106), preregistered analyses examined postanesthesia recovery unit outcomes. Of 452 patients interviewed, 69% reported dreaming. Among 57 patients with full adherence to all protocol elements, 93% reported dreaming. Most dreams were positive (86%), with no very negative dreams. Dreamers (mean ± SD, 9.16 ± 1.57) reported higher sleep quality than nondreamers (7.65 ± 2.86; P < 0.001). The protocol was safe, with no intraoperative awareness. Recovery times and analgesic and antiemetic use did not differ between groups. Feasibility was supported by high adherence to most elements (100% for verbal priming and propofol use, greater than or equal to 90% for EEG monitoring, and 95% for immediate interviews), although adherence to the no-stimulation emergence period was low (14%). This study demonstrates the feasibility of using a standardized anesthetic protocol in real-world clinical setting to facilitate anesthesia dreaming. With full adherence, dream recall rates approached experimental studies. The protocol was safe and linked to positive patient experiences, although dream recall was unrelated to postanesthesia care unit outcomes. These findings align with Enhanced Recovery After Surgery principles and provide a foundation for exploring potential therapeutic applications of anesthesia dreaming.

Cortical reorganization and listening effort in sound localization with left- vs. right-sided deafness.

The natural protection offered by saltmarsh and mangrove wetlands is increasingly recognised and there is widespread interest in understanding this phenomenon to assist nature-based coastal interventions. Roughness plays a fundamental role in shallow-water hydrodynamic process and hence is a critical parameter for simulating flow over coastal vegetation and the resulting dynamics of surge and wave attenuation. This study provides a comprehensive review of our understanding of the Manning’s coefficient (T/L 1/3 ) in saltmarsh and mangroves. The literature was screened using a rigorous selection procedure to identify studies relevant to saltmarsh and mangrove hydrodynamics and bed roughness. Considering all the numerical, laboratory and field studies that used Manning’s coefficient in saltmarsh and mangrove ecosystems, 36 papers were identified and assessed. The results indicate an interquartile range of Manning’s coefficient (s/m 1/3 ) from 0.04 to 0.08 for saltmarshes and 0.10 to 0.14 for mangroves, providing indicative ‘global’ estimates for these two coastal wetland types. Geographic location, tidal range and temperature showed no statistical relationship, supporting the use of global indicative values. However, statistical testing reveals that the Manning’s coefficient for saltmarshes and mangroves do show significant cross-shore variability with increasing values from the seaward to landward direction. This should be considered and further assessed, especially in more detailed studies. Hence, this analysis provides an indicative ‘global’ constant estimate of Manning’s coefficient for saltmarshes and mangroves, as well as suggestions for more systematic future research on wetland roughness. • A global review of Manning’s number in saltmarsh and mangrove wetlands is presented. • Global assessment of supporting nature based solutions restoring coastal wetlands • Indicative Manning’s values: 0.04–0.08 for saltmarsh and 0.10–0.14 for mangroves. • No statistical link found between Manning’s number and location, tide or temperature. • Cross-shore variability of roughness is significant and needs further investigation.

Performance assessment of groundwater circulation well coupled with surfactant-enhanced flushing in low-permeability zones.

Efficient capture of Cs+ ions by two supertetrahedral cluster-based microporous metal chalcogenides in neutral and alkaline environments.

Ambulatory surgery centers now perform more than 60% of the 60 million elective surgical procedures in the United States, yet artificial intelligence research in surgery has focused almost exclusively on hospital-based implementations. This evidence gap has implications for technology validation, investment decisions, and patient safety as ASCs adopt hospital-validated systems without setting-specific evidence. We conducted a scoping literature review searching PubMed, Scopus, Web of Science, and Cochrane Library from January 2020 through September 2025 for studies explicitly examining AI or machine learning applications in ASCs with quantitative outcomes. A parallel search using hospital-related terminology enabled direct comparison of research volume. After screening 847 potentially relevant articles, fewer than 10 studies specifically examined AI in ASC settings, while more than 500 hospital-based studies were identified during the same period. Existing ASC research focused on predictive analytics for workflow optimization; no studies examined intraoperative AI applications. The limited amount of ASC-specific research makes it unclear if hospital-validated benefits translate across settings to ASCs. A profound evidence gap exists between ASC surgical volume and ASC-focused AI research. The operational characteristics that distinguish ASCs from hospitals position them as ideal research settings for rigorous AI validation. Systematic ASC research is urgently needed to inform implementation decisions and establish data-standardization, technical, and economic frameworks required for the setting where most surgical patients receive care.

We report the development of a sensitive biosensing platform based on a shear-horizontal surface acoustic wave (SH-SAW) device and paper fluidics, with the potential to be used outside centralized laboratory settings. Systematic research on the biorecognition surface, blocking agent, fluidics and measuring unit allowed us to transform a laboratory-based method into a field-deployable device. As a proof-of-concept, the platform was used for the detection of SARS-CoV-2 anti-spike antibodies on a surface-immobilized spike protein, tested in both simulated and human blood serum samples. A poly-L-lysine (PLL) layer was selected as a biocompatible surface for spike protein immobilization; the polymer layer can be easily removed through gentle mechanical rubbing, allowing regeneration and multiple uses of the sensing device. This surface, combined with novel paper-based capillary fluidics, enabled real-time monitoring of spike antibody binding via acoustic wave phase measurements in the range of 1-100 nM antibodies in 1% v/v serum. Further acoustic wave amplitude amplification and a tenfold improvement in the detection limit (0.1 nM) were achieved by the use of gold nanoparticles conjugated with a secondary antibody. This optimized assay was successfully evaluated in a small pilot clinical study of 20 patient samples. Our new SH-SAW immunosensor exhibited sensitivity and specificity comparable to commercial systems with standard fluidics and instrumentation; importantly, its limit of detection is better than the clinically relevant value of ∼11 RU mL-1. This portable, low-cost platform, combining a pocket-size network analyzer with disposable paper fluidics and a regenerable sensing surface, offers a promising solution for quantitative antibody detection near or at the point-of-care.

Artemisia annua L., is the primary natural source of the antimalarial drug artemisinin. In nature, fluctuating light is a major environmental stress that affects plant growth and artemisinin biosynthesis. Although the light-harvesting chlorophyll a/b-binding (LHC) superfamily plays a key role in mediating plant responses to fluctuating light, systematic research of this gene family in A. annua has not yet been conducted, limiting our understanding of light adaptation in this medicinally important species. This study investigated the evolutionary dynamics and functional adaptation of the light-harvesting chlorophyll a/b-binding (LHC) superfamily in A. annua, with a focus on the early light‑induced protein (ELIP) subfamily. Comparative genomics of 24 plant species showed that the LHC superfamily recently expanded in the examined Asteraceae lineages through duplication events. In A. annua, 229 LHC genes identified from four haplotype genomes comprised 205 allelic and 24 haplotype-specific loci, with the ELIP subfamily expanding significantly via tandem duplication. Notably, compared to non-Asteraceae plants, ELIPs exhibited a uniform single-exon architecture, indicating it is a genomic feature unique to Asteraceae plants. Population genomics of 41 individuals showed dynamic copy number variations ranging from 1 to 4 copies per locus. Interestingly, a structurally disrupted ELIP allele remained transcriptionally active and produced long aberrant transcripts, showing that this subfamily is still actively evolving. Under UV-B stress, AaELIP loci showed synchronized induction trend but differed in expression levels, suggesting a division into major and auxiliary roles within the expanded tandem cluster. Overall, while the response of ELIPs to light stress is evolutionarily conserved, this dramatic expansion and structural streamlining of AaELIPs may represent a key evolutionary adaptation that enhances the plant's ability to cope with intense light and radiation stress. Collectively, this study demonstrates a significant expansion of the LHC superfamily in A. annua, especially within the ELIP subfamily, as well as its robust response to UV-B treatment, underscoring the essential role of ELIPs in mediating light stress responses. These findings provide a valuable foundation for future research to uncover the molecular mechanisms underlying A. annua's adaptation to complex light environments.

In diverse societies, music education is becoming a means of dialogue between generations and cultures and an effective tool for preserving cultural identity. Today, performance pedagogy is entrusted with not only developing the musician's technical skills but also transmitting cultural memory. In the context of this study, the phenomenon of cultural memory is understood as a set of values, traditions, intonation codes, and historical experiences accumulated through music. The main objective of the study was to analyze how music education curricula can include performance to promote cultural understanding. The current study conceptualizes music performance pedagogy as the primary medium through which cultural memory is encoded, shaped, and transformed. Adopting a qualitative approach based on an interpretivist epistemology, the study draws on systematic secondary research in musicology, performance studies, cultural memory theory, and the digital humanities. Through thematic and comparative analyses, it consolidates understanding of embodiment, repetition, canonical structures, and digital mediation in music performance pedagogy. The study emphasizes the role of music performance educators as curators of cultural memory and the need to tap into the potential of hybrid live-digital spaces as new archival environments. These findings have implications for contemporary pedagogical practice, demonstrating that performance not only preserves but also actively reshapes cultural memory in both the physical and digital spheres.

Systematic research on the ligand effects of atomically precise metal nanoclusters toward enzyme-mimicking activity remains elusive. Herein, a series of Au25(SR)18 nanoclusters capped with six types of thiolate ligands (varying in aliphatic chain length, backbone type, and functional groups) were employed as model catalysts for catalase-like (CAT-like) activity. Moderately increasing the chain length of carboxyl-terminated aliphatic thiolate ligands enhanced CAT-like activity. Au25(MHA)18 (MHA = 6-mercaptohexanoic acid) exhibited satisfactory structural stability and superior CAT-like activity against external environmental variations, with an elevated electron density of Au accounting for its enhanced activity. Urate oxidase (UOx) and Au25(MHA)18 were coencapsulated in zeolitic imidazolate framework-8 (ZIF-8) to construct a self-cascade system. This composite degrades uric acid (UA) via UOx, while generated hydrogen peroxide (H2O2) is converted to oxygen (O2) by Au25(MHA)18, replenishing O2 for UA degradation. Due to the cascade system and the protective effect of ZIF-8, UOx-Au25(MHA)18@ZIF-8 degraded 2.6 times as much UA as free UOx and inhibited UA crystallization. Moreover, the composite exhibits rapid, acid-responsive cargo release yet remains functional under neutral and weakly alkaline conditions. The ligand-engineering approach and self-cascade design provide a foundation for the molecular-level modulation of enzymatic activity in biomedicine.

Semiconductor-based gas sensors offer a promising approach for monitoring and early warning of combustible gases in the petrochemical industry, owing to their low detection limits, high cost-effectiveness, and suitability for large-scale deployment. However, compared with established mainstream technologies, such as catalytic combustion and optical approaches, semiconductor-based combustible gas sensors still require more systematic and deeper research to become a leading solution in practical engineering applications. In this review of semiconductor-based combustible gas sensors, we first outline the main sensing materials used in these gas sensors, including metal oxide semiconductors (MOS), two-dimensional (2D) semiconductors, and carbon nanotubes (CNTs), and then describe their sensing mechanisms, including the surface-adsorbed oxygen ion mechanism and the charge transfer mechanism. Subsequently, we discuss key gas sensing performance parameters, including sensitivity, selectivity, response and recovery times, linear detection range, and stability. Furthermore, based on these parameters, we systematically summarize the main strategies and recent advances aimed at overcoming current performance limitations. They are categorized into nine types, namely, morphology engineering, defect engineering, composite materials, heterojunctions, noble metal modification, gas identification algorithms, molecular sieves, gas sensor arrays, and light illumination. Finally, in view of the current research landscape, we highlight perspectives on future research for semiconductor-based combustible gas sensors in the petrochemical industry.