搜索结果：Evolution & development

Despite the phenotypic diversity of animal species, the basic anatomical features, or body plan, of each animal phylum have been strictly conserved since their initial establishment in the early Cambrian. While this remarkable conservation could be explained by the conservation of the mid-embryonic phase (the developmental hourglass model) when the body plan is established, the underlying evolutionary mechanisms remained largely unclear. In this respect, recent studies have highlighted intrinsic properties in development, such as robustness, stability, and pleiotropic constraints, as potential contributors to its limitation of phenotypic diversifications. These findings suggest a potential mechanism of how phenotypic evolution is intrinsically limited or biased. In this review, potential developmental factors that contributed to the intrinsic limiting effects of animal embryogenesis against phenotypic diversification will be overviewed, with a particular focus on the general relationship between evolution and developmental processes.

The harmonious development of healthcare, medical insurance, and pharmaceutical systems is crucial for advancing healthcare reform in China. This study evaluates the coordination level of China's three medical systems and examines their dynamic evolution trajectories and spatial effects from 2013 to 2023. Data from 31 provinces were analyzed using a coupling coordination degree (CCD) model to assess spatiotemporal evolution. Kernel density estimation and Markov chain models were applied to explore dynamic characteristics, while spatial Durbin models were employed to evaluate interregional spillover effects and influencing factors. From 2013 to 2023, the CCD of China's three medical systems exhibited a steady upward trend. Eastern regions consistently sustained higher levels of coordination, while central and western regions achieved notable improvements. Some provinces transitioned from disequilibrium to preliminary coordination; Dynamic evolution revealed diminishing absolute disparities but widening relative differences, with intensified multipolarization in eastern and western regions and significant internal variation in central provinces; Spatial analysis identified pronounced spatial autocorrelation and spillover effects, with high-high clustering zones expanding into the Yangtze River Delta, while low-low clustering zones remained concentrated in the northwest. Economic development, urbanization, and human capital contributed significantly to coordination, while government healthcare expenditure exerted a negative impact, and aging effect exhibits a significant threshold effect. The level of coordination among China's three major medical systems show sustained improvement, yet significant regional disparities persist, primarily due to uneven pharmaceutical development. Coordination follows a path-dependent trajectory, limiting rapid advancement. Positive spatial spillover effects generate economic influence on neighboring regions. Policies should focus on balancing regional coordination with differentiated strategies, enhancing interdepartmental and interregional mechanisms, and optimizing resource allocation.

Revealing the nanoscale structural evolution of electrocatalysts under realistic acidic oxygen evolution reaction (OER) conditions remains a major challenge. Here, we report the tracking of the evolution of the same individual iridium (Ir) nanocatalysts during prolonged acidic OER by developing identical-location transmission electron microscopy (IL‑TEM). The Ir nanocatalysts dispersed on a TEM grid serving as a working electrode are examined before and after OER operation. We find that the deposition of Au nanoparticles and the formation of SnO2 nanoclusters occur when a conventional holey carbon-film-supported gold (Au) grid is used at 1.7 V versus the reversible hydrogen electrode (VRHE), which obscure the identification of genuine Ir reconstruction. By coating the Au grid with Pt to form a stabilized working electrode, these artifacts are effectively suppressed for up to 2.5 h, enabling direct visualization of the nanoscale evolution of Ir nanocatalysts. Control measurements further confirm that the electrochemical response of Ir nanocatalysts on Pt-coated grids is dominated by the Ir catalysts rather than the Pt support. This study demonstrates that IL-TEM provides a practical approach for probing catalyst evolution in harsh, prolonged acidic environments by tracking the same nanocatalysts over extended reaction times, complementing in situ and operando TEM techniques.

Directed evolution methods face trade-offs between the control of discrete approaches and the throughput of modern continuous systems. Here, we engineered a method called lytic selection and evolution (LySE) for near-continuous evolution of bacterial gene clusters while maintaining discrete checkpoints. We developed a hypermutagenic T7 DNA polymerase variant fused to a dual adenine-cytosine deaminase to install all possible transition mutations at similar frequencies. By relieving pressure from maintaining genome fidelity, we obtained mutation rates of 3.82 × 10-5 substitutions per base. For biocontainment, the T7 DNA polymerase was encoded on an accessory plasmid, while the target gene cluster was encoded on a T7 DNA polymerase-lacking T7 phagemid. Alternating cycles of lysis and transduction enable selective replication and mutagenesis of target genes, while off-target genomic mutations are discarded. LySE evolved a 25-fold increase in tetA-encoded tigecycline resistance in 5 cycles, and a 50.9% increase in endpoint biomass of a bacterial strain that uses the polyethylene terephthalate monomer, ethylene glycol, as its sole carbon source. Our method balances speed and control for directed bacterial evolution.

Branching regulation and biomass accumulation are key determinants of tobacco productivity and bioenergy potential, yet the molecular mechanisms underlying branching control in tobacco remain poorly understood. Here, we characterize the ntmbd1 mutant derived from EMS mutagenesis, which exhibits excessive basal branching and altered plant architecture. SSR mapping and whole-genome sequencing identify a nonsense mutation in ntmbd1 leading to truncation of the encoded P450 protein. NtMBD1 is predominantly expressed in the shoot apical meristem, flower, and root, where its localization to the endoplasmic reticulum suggests a role in ER-associated regulatory processes. Phylogenetic analysis reveals that NtMBD1 in cultivated tobacco originates from its ancestral species Nicotiana. sylvestris, while its homolog from N. tomentosiformis is likely lost during evolution. Functional validation shows that NtMBD1 is required for axillary bud suppression, as CRISPR disruption in N. tabacum and Nicotiana. benthamiana phenocopies the branching defect, while heterologous complementation of the Arabidopsis max1 mutant confirms its conserved function; moreover, complementation of the ntmbd1 mutant restores normal architecture and biomass traits. Collectively, these findings reveal NtMBD1 as a key regulator of branching and plant architecture, providing new insights into its molecular and evolutionary roles and offering potential applications in crop improvement and sustainable bioenergy development.

The Zingiberaceae (ginger family) comprises economically and medicinally important plants, yet mitochondrial genome evolution within this family remains poorly understood. Curcuma longa and Curcuma kwangsiensis are widely used medicinal species whose mitogenomic architectures, gene content, and evolutionary trajectories have not been fully characterized. Understanding these features is essential to resolve phylogenetic relationships and elucidate mechanisms of mitochondrial genome plasticity. We sequenced and assembled the complete mitochondrial genomes of C. longa and C. kwangsiensis, revealing highly expanded and fragmented architectures of 7.66 Mb and 7.96 Mb, respectively. Both genomes exhibited conserved GC content (43.7-43.9%) and retained 39 core protein-coding genes, while showing species-specific variation in gene duplication, rRNA/tRNA copy numbers, and the pseudogenization of sdh3 and rpl10. Codon usage analysis indicated a strong A/U bias in synonymous positions, reflecting translational optimization. Extensive RNA editing, predominantly C-to-U conversions, increased hydrophobic residues in membrane-associated proteins, likely enhancing respiratory efficiency. Repeat analysis identified a significantly more robust repeat landscape in C. kwangsiensis, which featured 3,059 dispersed repeats in the 300 to 349 bp range and large repeats exceeding 700 bp, whereas repetitive elements in C. longa were fewer and predominantly restricted to the first molecule. Sequence divergence analysis revealed that most genes are under strong purifying selection, whereas a limited subset including atp8, ccmFn, cox2, matR, nad4, nad7, and rpl5 showed episodic positive selection. Whole-genome synteny comparisons indicated profound structural rearrangements and low collinearity, despite high sequence identity within conserved blocks (97.7%). Moreover, both species incorporated 25 plastid-derived fragments, with differences in gene completeness, highlighting ongoing cross-organelle gene transfer. Phylogenetic reconstruction placed both species within a well-supported monophyletic clade with maximum bootstrap support of 100, revealing a sister-taxa relationship between C. longa and C. amarissima while exhibiting a low substitution rate of 0.004 per site. Our study demonstrated that Curcuma mitogenomes combine remarkable structural plasticity with functional conservation. Conserved core genes, codon usage bias, and extensive RNA editing maintained mitochondrial function, while repetitive sequence proliferation, repeat-mediated recombination, and plastid-derived sequences facilitated lineage-specific diversification despite stable phylogenetic relationships. These findings provide essential genomic resources for the genus Curcuma and offer insights into mitochondrial genome evolution and species-specific diversification in Zingiberaceae.

Visual impairment affects over 2.2 billion people worldwide and the major causes include age-related macular degeneration (AMD), glaucoma, and diabetic retinopathy. For research in these areas, although animal models offer a more physiologically complex system than in vitro approaches, their use raises ethical considerations, and species-specific differences such as variations in protein sequences and signaling pathways. This can limit the direct translatability of the outcomes. Traditional 2-D cell cultures, in contrast, lack the multicellular organization and dynamic microenvironment necessary to replicate human retinal complexity. Retinal organoids (ROs), three-dimensional tissue constructs derived from pluripotent stem cells, have emerged as a promising model due to their human origin and complex cellular interactions that cannot be achieved in conventional 2-D/3-D co-culture models. In this review, we provide a brief overview of the evolution from 2-D to 3-D retinal models, highlight the structural and functional features of ROs including the presence of layered retinal architecture, photoreceptor outer segment formation, and light-responsive electrophysiological activity and summarize their applications in disease modeling, drug discovery, and gene and cell therapy. ROs represent a significant advancement over traditional models by enabling the recapitulation of human-specific retinal development, facilitating the study of patient-derived disease phenotypes, and providing a platform for personalized therapeutic screening. Their development has deepened understanding of pathological mechanisms in conditions such as retinitis pigmentosa and AMD, while enabling preclinical testing of targeted interventions like CRISPR-based gene editing and photoreceptor cell replacement. Nonetheless, challenges remain in fully replicating retinal vascularization, long-term functional maturation, and synaptic connectivity, underscoring the need for continued refinement and integration with complementary model systems.

Triphala, a traditional Ayurvedic formulation, has garnered significant research interest for its diverse therapeutic potential. However, a comprehensive analysis of its research landscape remains limited. To conduct a comprehensive bibliometric analysis of Triphala research from 2000 to 2024, examining publication trends, research hotspots, and evolving research themes. Publications related to Triphala were retrieved from the Web of Science core collection database (2000-2024). Bibliometric analysis utilized CiteSpace and VOSviewer to analyze publication trends, collaboration networks, and research hotspots. Visualization tools mapped the temporal evolution of research themes and collaboration patterns. The analysis of 417 publications unveiled a complex landscape of research development, identifying 5 major research themes that progressively evolved from 2006 to 2024, including apoptosis, radiation effects, oxidative stress, oral therapeutics, and molecular docking studies. Each theme demonstrated varying research strengths, with oral therapeutics showing the highest research intensity at strength = 3.1. Geographically, the research was predominantly concentrated in India, which produced 271 publications, significantly outpacing the United States (34 publications) and China (33 publications). The research was primarily disseminated through specialized journals, with the International Journal of Ayurvedic Medicine, Journal of Ayurveda and Integrative Medicine, and Indian Journal of Traditional Knowledge emerging as the most influential publication platforms. Key research institutions, including the Bhabha Atomic Research Centre, Chiang Mai University, and Mahidol University, played pivotal roles in advancing Triphala research. This bibliometric analysis demonstrates the progressive evolution of Triphala research from traditional applications to sophisticated scientific investigations. The study reveals a significant transformation in research focus, transitioning from basic mechanistic studies to advanced molecular investigations and clinical applications, particularly in oral health.

Ethanol is a non-food carbon source that is derived from syngas fermentation and has the potential to serve as a raw material for microbial processes that produce various value-added chemicals. Vibrio natriegens is a new type of chassis cell that has been developed in recent years for use in biotechnology and synthetic biology. It has a very fast growth rate and a broad substrate spectrum, but its ability to utilize ethanol is limited and its tolerance is poor. Adaptive Laboratory Evolution (ALE) provides a powerful tool for studying the resistance phenotype, production activity, and genetic stability of industrial strains, and is widely used to screen engineered strains with further improved characteristics. In this study, we developed a Vibrio natriegens that evolved in ethanol to produce 3-hydroxypropionic acid (3-HP). Firstly, strains capable of producing 3-HP from ethanol were obtained through adaptive laboratory evolutionary screening. Subsequently, by optimization of promoters in the 3-HP biosynthetic pathways, rational design of background strain, and adding appropriate concentrations of cerulenin, the 3-HP biosynthesis of engineered strain was significantly improved. Finally, the maximum concentration of 3-HP in shake flask culture reached 3.10 g/L, with a yield of 0.382 g/g. The concentration of 3-HP in 1 L bioreactor fermentation reached 9.94 g/L, achieving a yield of 0.258 g/g. The findings suggest that ethanol derived from synthesis gas shows tremendous promise as an excellent carbon feedstock for producing high-value biochemicals using engineered Vibrio natriegens in integrated carbon-based industrial biotechnology.

Bryophytes are the earliest known plant lineage that switched to invade land from their aquatic predecessors. Therefore, they might have evolved with cytoskeleton modifications to cope with adverse environmental stress. Microtubule dynamics/modifications have often been shown to be correlated with stress. Here, using Physcomitrium patens as a model, we tried to evaluate (i) the occurrence of tubulin post-translational modifications (PTMs) in the earliest known land plant lineage and (ii) the impact of different light, phytohormones, temperature and exogenous calcium (Ca2+). Here, we (i) use in silico analysis to show that the key enzymes responsible for tubulin PTMs are conserved in various mosses, (ii) perform microscopy to detect the modified protein, and (iii) assess the abundance of tyrosinated, acetylated and polyglutamylated α-tubulin under different environmental stresses. We also visualise the calcium dynamics in moss using a GCaMP6f P. patens line. Notably, we demonstrate for the first time that red and far-red light increase the levels of polyglutamylated tubulin in protonemal cells. Additionally, the exogenous application of auxin and cytokinin significantly affects the abundance of tyrosinated and polyglutamylated tubulin, respectively. Furthermore, we demonstrate the trends in the abundance of modified tubulin under different temperatures and Ca2+-treatment. We also show that the flux of intracellular Ca2+ is influenced by auxin and cytokinin, temperature, and exogenously applied Ca2+. The current work demonstrates unequivocally the PTMs of tubulin during land plant evolution and its possible role in stress adaptation. The dynamic accumulation of modified tubulin in P. patens is differentially regulated in response to abiotic factors. This study is relevant in the context of global warming, temperature-induced cell damage as observed in different crops, and the development of improved modern agricultural practices.

Adult T-cell leukaemia/lymphoma (ATL) is an aggressive CD4 +T-cell malignancy caused by the human T-cell leukaemia virus type 1 (HTLV-1). Approximately 3%-5% of infected individuals develop ATL after a prolonged latency of 30-50 years, during which a complex interplay between viral oncoproteins and host genomic alterations drives the transition from viral persistence to overt malignancy. This transformation is orchestrated by the viral transactivator Tax, which initiates cellular transformation, and the HTLV-1 basic leucine zipper factor (HBZ), which maintains the malignant phenotype and promotes survival through immune evasion. Genomic profiling has revealed that over 90% of ATL cases harbour activating mutations in the T-cell receptor (TCR)-NF-κB signalling pathway, enabling the malignant clone to bypass viral dependency. Furthermore, ATL cells survive host immunosurveillance through sophisticated escape mechanisms, including the loss of MHC class I presentation and programed death-ligand 1 (PD-L1) overexpression via 3'-untranslated region (UTR) disruption. Despite the use of antiviral therapies and targeted monoclonal antibodies, therapeutic failure is common due to genomic instability-specifically TP53 mutations compromising Zidovudine/Interferon efficacy and CCR4 antigenic variations leading to mogamulizumab resistance. This review delineates the multi-step journey of HTLV-1-driven clonal evolution and evaluates the molecular barriers to effective clinical management.

Developing low-cost acidic oxygen evolution reaction (OER) catalysts is essential to scale proton exchange membrane water electrolysis (PEMWE). Ruthenium-based high-entropy oxides (Ru-HEOs) hold promise, yet the vast compositional space renders trial-and-error approaches inefficient. Here, we propose a data-driven, high-throughput strategy that accelerates the discovery of stable acidic OER Ru-HEO catalysts. First, literature mining with a large language model (LLM) identifies non-noble metal combinations with potential synergy with Ru. We then integrate automated powder synthesis and catalyst array fabrication to build a 60-member library. Screening using dual activity-stability metrics pinpoints the optimal composition, (RuNiFeMoCr)3O4. Subsequent in situ characterization and theoretical calculations show that the high-entropy environment effectively suppresses Ru dissolution and, by optimizing local coordination and electronic structure, synergistically enhances reaction kinetics and structural stability. Last, in PEMWE device tests, an electrolyzer based on this catalyst operates stably for over 150 hour at 1 A cm-2, validating the data-driven strategy for accelerated screening and proof-of-concept demonstration of Ir-free anode candidates.

Accurate detection and segmentation of moving objects constitute a fundamental challenge in computer vision, particularly for intelligent video surveillance systems operating under variable illumination, dynamic backgrounds, and environmental noise. This paper presents a fully unsupervised dual-phase motion analysis framework that effectively combines statistical independence modeling and geometric contour evolution to achieve high-precision motion detection and segmentation. In the first phase, an enhanced Fast Independent Component Analysis (Fast-ICA) algorithm is employed to perform statistical decomposition of video sequences, exploiting temporal independence to distinguish moving foregrounds from static backgrounds. This process generates an initial motion mask with strong robustness to illumination variation and noise artifacts. In the second phase, a hybrid level set segmentation model integrating the global Chan-Vese formulation and a locally adaptive Yezzi-based energy function refines object boundaries through an adaptive energy minimization process. A stabilization term and a self-regulating convergence criterion are further incorporated to ensure contour smoothness, numerical stability, and resilience to topological changes. Comprehensive experiments conducted on the CDNet-2014 benchmark dataset demonstrate that the proposed method achieves an average recall of 0.9613, precision of 0.9089, and F-measure of 0.9310, outperforming several state-of-the-art supervised, semi-supervised and unsupervised background subtraction algorithms. The proposed Fast-ICA-Level Set fusion framework thus provides a robust, adaptive, and computationally efficient solution for real-world intelligent surveillance and autonomous visual monitoring applications.

The plastic pollution crisis urges innovative recycling solutions. Promising approaches especially for polyester-containing wastes include enzymatic hydrolysis and microbial upcycling. For efficient enzymatic hydrolysis of polyesters, elevated temperatures (70-80 °C) are required, necessitating thermophilic microbial chassis for consolidated bioprocessing (CBP). In this study, we engineered Geobacillus thermoleovorans through adaptive laboratory evolution (ALE) for robust growth on adipic acid (AA) and 1,4-butanediol (BDO), two relevant monomers for example derived from poly(butylene adipate-co-terephthalate) (PBAT), enabling growth rates of up to 0.10 h-1 on AA and 0.13 h-1 on BDO. Based on a high-quality annotated genome sequence of the wild type, genomic mutations and gene expression levels were characterized in mutants grown on the respective substrates compared to glucose. For BDO, an alcohol dehydrogenase (Gth_001044) and an aldehyde dehydrogenase (Gth_001082) were identified to be likely responsible for its oxidative degradation. AA uptake appears to be mediated by a dicarboxylate transporter (Gth_003270), followed by CoA activation and β-oxidation involving a CoA transferase (Gth_003192) and several upregulated CoA-family dehydrogenases. To demonstrate applicability of these strains in plastic upcycling, they were co-cultivated with PBAT as the sole carbon source in combination with the cutinase HiC for PBAT hydrolysis. This resulted in growth on the released AA and BDO. Given the potential to purify the remaining terephthalate (TA), this approach highlights the feasibility of selective monomer valorization in bioprocesses. Additional ALE enabled co-utilization of AA and BDO by a single strain and improved AA consumption at lower concentrations, underscoring the strains' adaptability and high potential for plastic upcycling applications. KEY POINTS: • G. thermoleovorans evolved for robust growth on adipate and 1,4-butanediol at 60 °C. • Genome and transcriptome analyses revealed underlying pathways and enzymes involved. • Co-cultivation of the evolved strains on PBAT with HiC as the sole carbon source.

Extracellular vesicles (EVs) are nanoscale, membrane-bound particles that play pivotal roles in intercellular communication as well as modulate diverse physiological and pathological processes. As a classical EV surface marker, the tetraspanin CD9 is critically involved in vesicle biogenesis, membrane fusion, and cell-to-cell signaling. While antibodies remain the conventional tool for CD9 detection, their utility in biosensing is constrained by inherent limitations. Aptamers offer a compelling alternative as synthetic single-stranded nucleic acids with high target affinity and specificity. In this study, a novel epitope-specific DNA aptamer, CD9 A3-A, targeting the extracellular domain of CD9 was developed using a peptide-directed Systematic Evolution of Ligands by Exponential Enrichment (SELEX) approach. The aptamer's specificity and binding efficacy toward recombinant CD9 protein, CD9-positive cells, and CD9-enriched EVs, including those from human serum, were validated using ELISA and flow cytometry. Furthermore, this epitope-specific CD9 aptamer enabled the detection and differentiation of EVs from distinct cancer cell origins in a fluorescence polarization-based aptamer detection method for extracellular nanovesicles. Notably, a flow cytometric assay based on a HER2 aptamer successfully detected one HER2-povitive EV amongst 499 HER2-negative sEVs, with sEVs defined by the CD9 A3-A aptamer. These findings suggest that the CD9 aptamer-based biosensing platforms represent a promising next-generation tool for liquid biopsy-based precision medicine.

Developing highly efficient and stable electrocatalysts for hydrogen evolution reaction (HER) is critical for sustainable hydrogen production through water electrolysis. The existing limitations in comprehending the intermediate behavior during the alkaline HER obstruct the systematic design of effective catalysts. Herein, we introduce an interfacial engineering approach that employs gold‑nickel phosphide (Au-Ni2P) heterostructures to tackle this challenge by precisely tailoring metal-support interaction (SMSI). By implementing systematic annealing protocols, three distinct interfacial architectures: Yolk-shell (Au@Ni2P YSNs), alloyed (Au-Ni2P), and Janus-type (Ni2P-Au) structures are achieved and confirmed by in situ transmission electron microscopy. Density functional theory (DFT) calculations reveal that the alloyed interface enables optimal water dissociation kinetics through Au-induced 3d orbital modulation of Ni sites, supported by spectroscopic evidence of strong Au-P interfacial bonding. In situ Raman spectroscopy demonstrates the accelerated proton generation via enhanced water dissociation can create localized acidic microenvironments and improve HER activity. As a result, the HER activity sequence is Au-Ni2P > Au@Ni2P YSNs> Ni2P-Au. This work establishes a novel methodology for interfacial engineering through thermal-driven SMSI manipulation, providing new insights into microenvironment modulation for advanced electrocatalysis.

Respiratory syncytial virus (RSV) infections have a high prevalence in young children, immunocompromised adults, and elderly, raising global concerns. Global RSV surveillance infers an 8%-27% mortality rate in preterm-born children, with 2.8 million/year. Continuous surveillance studies, coupled with molecular epidemiological investigations, are essential to comprehend the virus's evolutionary dynamics and devise effective preventive strategies. The study investigates the evolutionary dynamics and molecular characterization of the RSV F-protein using bioinformatic pipelines on NCBI and GISAID data sets and molecular analysis of clinical specimens collected from children. We found S255N/G, N262S, N268I, K272M/N, and S275F/A mutations in the heptad repeat region "A" that were associated with inducing resistance toward palivizumab from bioinformatics analysis of surveillance data sets. Molecular characterization of RSV F protein from clinical specimens found L45F mutations responsible for forming new clades, L172Q and S173L substitutions for suptavumab resistance, and N276S mutations for potentially impacting palivizumab resistance. Six N-glycosylation sites are found at 27, 70, 116, 120, 126, and 500 in all RSV strains. Purifying selection, maintaining fusion protein stability, was observed. Phylogenetic analysis reveals genetic variability, with RSV B showing higher diversity than RSV A, forming distinctive clades belonging to B.D (BA9) and A.D (ON1) strains of RSV B and A, respectively. The phylodynamics of RSV indicate a uniform increase in effective population size. Understanding the F protein's structure and dynamics is essential for elucidating the virus's pathogenic mechanisms and developing effective vaccines and antiviral therapies. Respiratory syncytial virus remains a major cause of severe respiratory disease in infants, the elderly, and immunocompromised populations worldwide. Despite recent advances in monoclonal antibodies and vaccines, the virus continues to evolve, posing challenges for long-term control. The RSV fusion (F) protein is central to viral entry and the primary target for neutralizing antibodies, yet little is known about its global evolutionary dynamics and drug-resistance associated changes. By integrating large-scale surveillance data with clinical isolates, our study identifies critical mutations, glycosylation patterns, and evolutionary pressures that shape the diversity of the F protein. These findings provide mechanistic insight into how RSV adapts under immune and therapeutic pressure, highlighting both vulnerabilities and conserved features of the F protein. Continuous monitoring of these evolutionary patterns will be crucial for maintaining vaccine effectiveness and informing the development of next-generation therapeutics to reduce RSV-associated morbidity and mortality.

The functional properties of protein fibrils are governed by structural transitions and conversion efficiency, highlighting the need to regulate fibrillation. In this study, a combined ultrasound and Zn2+ treatment was developed to promote the formation of pea protein fibrils and enhance their delivery performance. The results showed that this treatment accelerated pea protein hydrolysis during the lag phase, promoted polypeptide chain folding during the growth and plateau phases, and produced short fibrils enriched in β-sheets (38.9%). This effect was associated with greater exposure of hydrophobic groups (H0 = 25,408.3), which made hydrophobic interactions the dominant driving force for fibrillation while suppressing disulfide bond formation. In addition, CO bond transformation and protein backbone reorganization were involved in fibril formation. Fibrils formed under synergistic treatment were found to further enhance the antioxidant capacity, digestive stability, and bio-accessibility of AST (38.19%), whereas the bio-accessibility of free AST was only 9.37%.

We study the behavior of an institution that broadcasts reputational signals to facilitate trust in a population. Using an online marketplace as a motivating example, we develop a theoretical model in which buyers and sellers are matched on a platform to engage in transactions involving moral hazard: After receiving payment, sellers may either faithfully deliver goods or renege. Although buyers do not observe a seller's true strategy-good-faith or bad-faith-the platform broadcasts binary reputation signals about sellers. Buyers condition their purchase decisions on these signals, sellers adapt their strategies over time, and the resulting market composition determines the platform's commission revenue and players' welfare. Our analysis reveals a second layer of moral hazard at the institutional level. Because revenue depends on transaction volume, the platform has an incentive to inflate ratings, making good-faith and bad-faith sellers more difficult to distinguish. This distortion is self-limiting, however: Excessive inaccuracy erodes buyer trust and collapses trade. When signal accuracy is costless, the platform maximizes profit by perfectly identifying good sellers while tolerating some false positives. When accuracy is costly, the platform has an incentive to actively erode signal quality, even at a cost. If the platform can also set commission fees, higher fees are accompanied by stronger incentives to maintain accuracy. These results clarify when institutional incentives align with, or diverge from, the welfare of buyers and good-faith sellers who rely on reputational information.