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It is known that altered amino acid metabolism can influence immunological responses, thus studying the molecular mechanisms underlying these changes requires analytical methods for reliably determining the quantities of individual analytes. To address the ongoing need for quantitative assessment of amino acid composition, a validated method for determining their quantities was proposed. This study presents the development and validation of a novel method for the quantitative analysis of selected amino acids using high-performance liquid chromatography coupled with a quadrupole time-of-flight (Q-TOF) mass spectrometer equipped with an electrospray ionization source. The method has been satisfactorily validated in terms of linearity, range, precision, accuracy, and stability. Its applicability to biological matrices was demonstrated by the successful quantification of amino acids in HaCaT cell lysates. Owing to the use of a robust, state-of-the-art analytical platform based on Q-TOF technology, which enables high-resolution mass detection, the method is readily adaptable for the inclusion of additional analytes and can be extended to other complex biological samples. The applicability of the method for the simultaneous determination of selected amino acids was demonstrated, and the method successfully applied to the HaCaT cell lysates.

Leishmaniasis remains a major public health challenge in many tropical and subtropical regions despite long-standing emphasis on controlling adult sandflies. This commentary highlights an important ecological gap that has received limited attention: the immature stages of sandflies. Unlike mosquitoes, sandflies develop in cryptic terrestrial microhabitats that are rarely detected through routine surveillance. Consequently, most vector control programmes concentrate on suppressing adult populations, while the biological processes that generate new adult vectors remain poorly understood. Recent ecological studies indicate that breeding activity may be spatially structured and biologically detectable. Surveillance approaches that consider oviposition behaviour and breeding ecology may therefore help make vector population dynamics more measurable and support more sustainable, biology-based control strategies.

PIWI-interacting RNAs (piRNAs) are an important class of non-coding RNA molecules in epigenetic regulation. It plays a crucial role in maintaining genomic stability and inhibiting transposable elements, and have been proven to participate in various diseases by regulating gene expression and influencing signaling pathways. Traditional biological experimental methods have limitations such as low throughput, long cycles, and high costs, making them difficult to meet the requirements of large-scale systematic screening. In this study, we develop a predictive framework named PiDA-DVLSA. We integrate autoencoder, dual graph transformer, and multi-head self-attention mechanisms, and construct an end-to-end multimodal deep learning system. We use autoencoder to perform nonlinear dimensionality reduction and denoising on piRNA sequence features and disease phenotype semantic features, and extract potential representations with strong discriminative ability. Then, we use graph transformers to model the high-order topological relationships between nodes in isomorphic similar graphs, and input heterogeneous graph transformers to learn complex cross-entity interaction patterns in heterogeneous networks. Finally, we achieve adaptive fusion of multi-source information through multi-head self-attention mechanisms. PiDA-DVLSA performs excellently on the benchmark dataset, with AUC and AUPR reach 0.9437 and 0.9195, respectively, significantly outperform eight mainstream algorithms. In independent case validations for breast cancer, clioblastoma, and Alzheimer disease, our model successfully predicts multiple biologically significant potential associations, further confirming its practicality and effectiveness in real scientific research scenarios and providing a solid computational basis for future precision diagnostic and therapeutic applications. PiDA-DVLSA is freely available at https://github.com/zhaoqi106/PiDA-DVLSA .

Hair and clothing are among the most frequently recovered evidentiary items at crime scenes. Compared with human soft tissue, they resist environmental degradation and frequently retain perpetrator-derived biological deposits; accurate identification of these traces is therefore pivotal for case qualification and investigation. Microbiome profiling has emerged as a promising forensic tool for body-fluid attribution, yet body fluids like blood and semen contain only a sparse indigenous flora and are highly vulnerable to environmental or substrate-borne microbial overwrite. To date, systematic evaluations of how deposition surface and ambient microbiota influence the reliability of microbe-based fluid identification remain scarce, especially with respect to hair-a substrate that inherently carries the victim's resident microbial community and may obscure fluid-specific markers. In this study, four forensically relevant body fluids (blood, semen, vaginal fluid and saliva) were deposited on hair shafts and cotton fabric and aged for 30 days under indoor conditions. Amplicon sequencing of the V3-V4 hypervariable region of the bacterial 16S rRNA gene revealed that fabric-hosted stains retained a stable, fluid-specific microbiota across all sampling intervals. In contrast, hair-associated traces underwent a rapid and persistent compositional shift toward the native scalp/hair community, resulting in significant loss of fluid-identifying signals. Consequently, the prediction accuracy of our random-forest classifier decreased to 84.2% when hair samples were included. Saliva and vaginal fluid proved exceptional: a subset of oral-associated taxa (Streptococcus, Gemella) and vaginal associated microorganisms (Lactobacillus) remained detectable on both substrates, preserving a degree of fluid specificity. Collectively, these findings demonstrate that substrate-derived microbiota can compromise microbiome-based body-fluid identification, underscoring the necessity of matrix-specific marker panels and cautious extrapolation of signatures derived from pristine laboratory simulations to real-world evidentiary samples.

Intracavitary drug instillation is a crucial therapeutic strategy for treating bladder cancer. However, current methods are limited in efficacy due to insufficient tumour targeting and drug penetration across tissue barriers in pathophysiological conditions. Here we devise biohybrid magnetic algae microrobots with hierarchical nanoporous structure and develop an 'algebot'-mediated, non-contact convective transport strategy to synergistically integrate targeted carrier transport, selective drug release and ultrafast tissue penetration. Our approach leverages machine-intelligent image feedback for autonomous navigation, magnetite-endowed multimodal control for reconfigurable swarming and flow-tuned convective diffusion for on-demand therapeutic delivery. We exemplify this approach with doxorubicin-loaded magnetic Coscinodiscus granii evaluated in a murine model of bladder tumour, demonstrating an over tenfold increase in drug permeation and substantially reduced tumour burden to less than 3% compared with conventional intravesical instillation in a preclinical trial of 1-week therapy without inducing systemic toxicity. Our drug delivery system offers a non-invasive solution to overcome complex biological barriers, advancing the efficacy and safety of intracavitary chemotherapy.

Bacillus thuringiensis (Bt) is widely employed as a biological control agent against pests in tea plantations, yet its impacts on soil health and microbial ecology remain insufficiently understood. This study investigated the effects of two Bt application regimes, namely moderate-frequency conventional Bt application (Bt1, 3 sprays over 21 days) and high-frequency intensive Bt application (Bt2, 6 sprays over 42 days), on soil physicochemical properties, enzyme activities, and microbial community structure and function in tea soils. The moderate-frequency conventional Bt1 significantly improved soil nutrient status by increasing organic matter, available nitrogen, and potassium, and boosted acid protease, sucrase, and cellulase activities, while Bt2 achieved the maximum urease and polyphenol oxidase activities but failed to promote soil available nutrients and organic matter as effectively as Bt1. Although neither Bt treatment induced notable shifts in overall microbial alpha-diversity indices, community composition differed distinctly between the two treatments. Bt1 enriched beneficial taxa related to nitrogen fixation and organic matter degradation including Pseudomonas, Bradyrhizobium, and Sphingomonas, and sharply suppressed pathogenic fungi such as Aspergillus and Curvularia, whereas Bt2 caused an 18.29% reduction in Sphingomonas abundance with limited enrichment of beneficial bacteria. Functional predictions indicated that Bt1 amplified microbial carbon degradation and nitrogen cycling, enriched saprotrophic and symbiotic fungi and reduced plant pathogens by 85.78%, while both Bt treatments elevated saprotrophic fungi yet Bt2 only reduced pathogens by 11.84%. Co-occurrence network analyses revealed enhanced microbial interactions and community stability under Bt1, while excessive high-frequency Bt2 reduced network connectivity and stability compared with CK and Bt1. These results suggest that moderate-frequency conventional Bt application can positively modulate soil microbial communities and ecosystem functions, providing valuable insights for sustainable pest management and soil health maintenance in tea agroecosystems.

Nutrition shapes development, health and risk of disease over the life course and across generations. The predominant approaches to understanding these relationships have either been to consider the effects of single nutrients, one at a time, or to consider associations with food types and dietary patterns. Although, to date, the single-nutrient approach has defined much of the scientific enquiry and public debate on the macronutrients - carbohydrate, fat and protein - there is an emerging appreciation that their proportions and quality matter more than their individual effects. Growing evidence demonstrates that macronutrient interactions operate at multiple biological levels, and research on dietary protein has proven a particularly productive entry point for characterizing these mixture effects. In this narrative Review, we begin by analysing key issues and introducing a framework for navigating the complexity of macronutrient mixtures (nutritional geometry), then consider the role of macronutrient proportions on food intake, systemic physiology, health and the risk of disease across the life course. Finally, we discuss how human nutritional biology has been subverted within the modern, industrialized food environment, contributing to the global burden of obesity and related diseases of unhealthy ageing.

Antisense oligonucleotides (ASOs) represent a promising therapeutic modality for central nervous system (CNS) disorders, offering highly specific modulation of gene expression. However, their clinical utility is severely limited by their inability to cross the blood-brain barrier (BBB), necessitating effective shuttling strategies. While transferrin receptor (TfR1)-mediated shuttling has shown therapeutic promise, the fundamental mechanisms governing the delivery of antibody-ASO conjugates across the BBB remain poorly understood. This study directly addresses this critical knowledge gap by establishing a mechanistic understanding of how the ASO cargo impacts major cellular interactions during the BrainshuttleTM-mediated transport across the BBB. Using a panel of advanced in vitro assays developed specifically for this purpose, including quantitative transcytosis, detailed imaging-based intracellular trafficking, and binding assays with brain endothelial cells (BECs), the shuttling process was systematically investigated. We demonstrate that ASO conjugation profoundly alters the cellular fate of the BrainshuttleTM. Specifically, conjugation increased the binding to BECs of low-affinity TfR1 shuttles via avidity effects while paradoxically reducing the binding strength of high-affinity shuttles. Functional assays confirmed the biological activity of the delivered ASOs; however, transcytosis of high-to-moderate affinity binders across the BBB model was significantly delayed upon ASO conjugation. Building on these mechanistic insights, we engineered TfR1 BrainshuttlesTM with optimized affinity and explored the shuttling potential of an alternative BBB receptor, CD98hc. These efforts culminated in the development of a novel bispecific BrainshuttleTM targeting both CD98hc and TfR1. This dual-targeting strategy exploits distinct and potentially non-competing trafficking pathways to overcome ASO-induced delays and significantly enhance in vitro transcytosis efficiency. The in vitro findings in this study underscore the necessity of mechanism-driven design to overcome ASO-induced limitations in delivery across the BBB. The bispecific CD98/TfR1 approach presented here provides a promising new strategy for maximizing delivery efficiency and enabling more effective therapeutic outcomes for CNS diseases.

Oral cancer is a significant global health challenge, ranking as the sixth most prevalent cancer worldwide, with approximately 377,000 new cases diagnosed annually. The high morbidity and mortality rates are largely attributed to tobacco and alcohol use. While conventional treatments such as surgery, radiation, and chemotherapy have improved survival rates, they often lead to unfavourable aesthetic and functional outcomes. Tissue engineering offers a promising alternative, providing regenerative solutions aimed at restoring both oral function and appearance. By integrating biomaterials, biological systems, and engineering principles, tissue engineering enables the creation of functional tissue replacements. The current review examines different t pathways the potential applications of autologous tissue, oral cancer cell lines, CRISPR, gene-editing technologies, and epigenetic modifications for tissue regeneration. Advanced scaffold technologies that mimic the natural extracellular matrix, along with stem cell-based therapies and bioactive molecules, are employed to support tissue growth and differentiation. Mesenchymal stem cells (MSCs) and induced pluripotent stem cells (iPSCs) show significant potential in regenerating hard and soft oral tissues, while also targeting cancer stem cells (CSCs) to prevent recurrence. Furthermore, innovative technologies like 3D bio printing, combined with vascularization strategies, hold promise for developing patient-specific tissue constructs for reconstructive procedures. In conclusion, tissue engineering offers transformative potential for oral cancer treatment, presenting regenerative therapies that can significantly enhance patient outcomes and quality of life.

To investigate the relationship between the basal metabolic rate (BMR) and subfoveal choroidal thickness (SFCT) and the statistical mediating role of the BMR in age-related changes in SFCT. This cross-sectional study included 119 cataract surgery patients. BMR was calculated by the Mifflin-St Jeor equation, and SFCT was measured via swept-source OCT and its integrated software. Covariates included metabolic indices (e.g., triglyceride-glucose index, hemoglobin level, platelet count, systolic blood pressure, and relevant comorbidities), comorbidities (hypertension, diabetes mellitus, and cardiovascular/cerebrovascular events), and ocular parameters (including intraocular pressure and axial length). Associations were evaluated using linear regression (with nested models for multicollinearity) and bootstrap mediation analysis. BMR was positively correlated with SFCT after adjusting for axial length according to both univariate and multivariate linear regression analyses (all P&#x2009;<&#x2009;0.05), but significance was lost in the nested models including age and sex because of multicollinearity (VIF&#x2009;>&#x2009;5). Mediation analysis revealed that age had a total effect on SFCT of -4.4641 (P&#x2009;<&#x2009;0.01), with BMR mediating 27.71% of this effect (indirect effect: -1.2368, 95% CI: -2.0745 to -0.5340). In this cohort of cataract patients, BMR did not independently biological affect SFCT but served as a statistical mediating variable, partially elucidating the relationship between SFCT thinning and advancing age. A hypothesis was formulated that metabolic pathway regulation as a potential strategy for preserving age-related ocular health.

Vascular diseases, particularly atherosclerosis, represent a leading cause of global morbidity and mortality. Endovascular stenting has emerged as a cornerstone of therapy to restore vessel patency, yet conventional stents remain obstructed by significant clinical limitations, including in-stent restenosis, thrombosis, and mechanical failure. These adverse outcomes are intrinsically linked to their fundamental structural design, which is characterized by a positive Poisson's ratio, leading to foreshortening and a biomechanical mismatch with the native vasculature. This review critically examines auxetic stents as a next-generation solution, engineered with a structure possessing a negative Poisson's ratio. This unique property allows them to expand axially upon radial deployment, thereby eliminating foreshortening, enhancing conformability to tortuous vessels, and distributing mechanical stress more uniformly onto the arterial wall. This paper synthesizes the robust body of in-silico/bench-top evidence from computational modeling and in-vitro experimentation that validates these superior biomechanical characteristics. Furthermore, it explores the profound and favorable biological implications, arguing that the optimized mechanical environment and improved hemodynamics are hypothesized to attenuate the primary triggers for neointimal hyperplasia and foster rapid, complete endothelialization. The review concludes by outlining the translational pathway, including challenges in structure integration and discussing the vast future horizons for auxetic structured stents in complex peripheral, carotid, and non-vascular applications. Auxetic design represents a paradigm shift from material-centric iteration to structure-driven innovation, holding the promise to significantly improve the long-term safety and efficacy of endovascular stent implants.

The sympathetic nervous system (SNS) plays a crucial role in chronic liver diseases, but its function, particularly in terms of the underlying mechanisms of liver metastasis, remains unclear. Here, we reported that hepatic sympathetic nerve activity increases in the early stage of metastasis and was accompanied by a moderate increase in norepinephrine (NE). Unexpectedly, NE had a dose-dependent effect on colorectal liver metastasis. Only daily administration of low-dose NE could maintain NE at a moderate concentration in the liver during this early phase significantly suppressed metastatic tumor growth. Conversely, extremely low NE concentrations (induced by 6-hydroxydopamine, 6-OHDA) or high-dose NE prompted liver metastasis. Single-cell RNA sequencing (scRNA-seq) demonstrated that NE modulated monocyte recruitment and M2 macrophage polarization through the CCL2-CCR2 signaling axis and influenced the immunosuppressive effects of myeloid-derived suppressor cells (MDSCs) on T cells: low-dose NE inhibited monocyte recruitment and M2 macrophage polarization and relieved the immunosuppressive effects of MDSCs on T cells, whereas extremely low- and high-dose NE supplementation had the opposite effects. Further investigations confirmed that these biological effects were closely associated with the NE-mediated expression ratio of &#x3b1;2a-adrenergic receptor to &#x3b2;2-adrenergic receptor (&#x3b1;2a-AR/&#x3b2;2-AR). Specifically, at moderate NE concentrations, a high &#x3b1;2a-AR/&#x3b2;2-AR expression ratio was correlated with antitumor effects. Collectively, these findings reveal that the SNS mediates U-shaped effects on liver metastasis in an &#x3b1;2a-AR/&#x3b2;2-AR ratio-dependent manner, highlighting moderate sympathetic activation as a potential therapeutic strategy to inhibit the progression of liver metastasis.

Vitiligo is a chronic autoimmune depigmenting disorder affecting 0.5%-2% of the global population, characterized by bidirectional interplay between psychological stress and disease progression, with accumulating evidence highlighting the central role and translational relevance of the neuro-endocrine-immune-cutaneous axis in its pathogenesis. Epidemiological data indicate over half of patients experience significant psychological stress prior to disease onset, while visible depigmentation markedly elevates the burden of depression and anxiety, establishing a self-amplifying pathogenic loop. Mechanistically, neural crest-derived melanocytes form functional "neuro-pigment units" with intraepidermal nerve endings, enabling bidirectional communication via neuropeptides including calcitonin gene-related peptide (CGRP) and substance P. Dynamic crosstalk among keratinocytes, sensory neurons, and melanocytes integrates neurotrophic and inflammatory signals to tightly regulate melanocyte survival and biological function. Sympathetic activation drives melanocyte injury via norepinephrine-mediated &#x3b2;2-adrenergic receptor signaling, while dopamine metabolites exacerbate apoptosis via the oxidative stress-Akt-Bad axis; context-dependent hypothalamic-pituitary-adrenal axis effects and light-melatonin-circadian clock disruption further promote immune dysregulation and melanocyte loss. Notably, neuromodulatory approaches like transcutaneous auricular vagus nerve stimulation show therapeutic promise by attenuating oxidative stress and limiting pathogenic CD8&#x207a; T-cell infiltration. These insights have fostered targeted strategies including CGRP receptor antagonists and dual antioxidant-neuroprotective natural compounds. Integrating neuroimmunological modulation with psychological and circadian interventions represents a promising precision medicine framework for vitiligo management.

The natural antifungal peptide Histatin 5 (Hst 5) is a histidine-rich cationic peptide secreted by human salivary glands and a key component of oral innate immunity, but its moderate activity limits clinical use. Hst 5 enters Candida albicans via the membrane receptor Ssa1/2. Here, we integrated artificial intelligence-assisted and computer-aided drug design to rationally modified the sequence structure of Hst 5. Truncated derivatives of Hst5 were screened for antimicrobial potential using ESM2-AFPpred, and high-probability candidates were docked with Ssa1/2. The Hst 5-22 was identified, then redesigned based on alanine scanning to yield the optimized derivative Hst 5-22-RW. Compared with Hst 5, Hst 5-22-RW has a shorter sequence, stronger Ssa1/2 binding, and improved activity against C. albicans. It also shows superior activity against fluconazole-resistant strains. RT-qPCR and transmembrane tracking confirmed higher cellular transport efficiency in C. albicans. The CADD/AIDD-driven optimization successfully generated the highly active antifungal peptide Hst 5-22-RW, providing a novel strategy for rational modification of antimicrobial peptides.

Rangeland degradation is a major ecological problem in Central Asia, where extensive pasture systems support biodiversity, livestock production, and rural livelihoods. This study presents a systematic review of research on ecological monitoring of rangeland degradation in the region, focusing on satellite-based methods and field observations. Publications from 1990 to 2026 were screened using a structured review process, and 44 studies were included in the final analysis. The reviewed studies show that satellite-based methods are used more frequently because they allow monitoring over large areas, while field studies usually provide more detailed ecological information but cover smaller territories. A major contribution of this review is the combined analysis of regional patterns and monitoring methodologies used across Central Asia. The review analyzes monitoring practices across Central Asia and discusses the advantages and limitations of existing approaches. The review shows that the most reliable assessments are produced when satellite observations are supported by field data on vegetation, biomass, and soil condition. The reviewed studies report different degradation patterns depending on ecological conditions, observation periods, and research methods. In most cases, degradation is associated with both climatic factors and human activities. At the same time, such integrated approaches are still not widely applied, and research remains concentrated in a few countries, especially Kazakhstan and Kyrgyzstan. Considerable gaps persist in Uzbekistan, Tajikistan, and Turkmenistan. Overall, the reviewed literature shows the importance of developing more unified monitoring approaches that integrate satellite observations with field-based ecological data in different parts of Central Asia.

The microbiome actively influences antimicrobial resistance (AMR) dynamics by shaping both ecological and evolutionary processes. However, the extent of its role in resistance emergence, transmission and persistence remains unclear. Traditional AMR research has mainly focused on genetic mechanisms and pathogen-level dynamics. In contrast, the intersection of AMR and the microbiome, including resistance-gene reservoirs, microbial competition and community-mediated selection, remains poorly represented, especially in a modelling context. Here we present a structured framework for incorporating microbiome-AMR interactions into predictive models. We identify key microbiome-mediated processes shaping AMR across different levels of complexity, describe how these can be quantitatively integrated into models, and identify critical data gaps that limit current approaches. By bridging microbiome ecology, AMR biology and mathematical modelling, we set out research priorities and strategies to improve resistance prediction and guide microbiome-targeted interventions.

N7-methylguanosine (m7G) modification plays a critical role in RNA metabolism and is increasingly recognized for its implications in cancer biology. It can influence RNA stability, translation efficiency, and gene expression regulation. However, the specific role of m7G modification and its downstream genes in thyroid carcinoma (THCA) is not well understood. To comprehensively explore the impact of m7G methylation modification and the m7G-related gene ZNF831 on THCA, this study aims to identify key genes influencing m7G modification in THCA, with a particular focus on clarifying the role of ZNF831. This study is expected to further elucidate the pathological mechanisms of THCA and fill the current research gap in this field. Weighted gene co-expression network (WGCNA) analysis was used to evaluate the expression of m7G-related genes in the THCA expression data from the GEO (Gene Expression Omnibus) datasets. Machine learning algorithms, including the least absolute shrinkage and selection operator (LASSO), gradient boosting decision tree (XGBoost), and random forest (RF), were used to identify the feature genes, including GPSM3 and ZNF831, in the TCGA-THCA dataset. Immunohistochemistry was used to identify the expression difference of ZNF831 in 3 THCA tissues and 3 normal tissues. Finally, the changes of proliferation and migration of THCA cells after overexpression of ZNF831 were investigated. This study investigated m7G-related genes in THCA, focusing on ZNF831 as a key tumor suppressor. Differential expression analysis revealed significant dysregulation of m7G-related genes in THCA. Functional and bioinformatics analyses, including gene set enrichment analysis and protein-protein interaction network construction, identified ZNF831 as a candidate gene. Experimental validation demonstrated that ZNF831 overexpression significantly reduced the proliferation and migration of THCA cells. Additionally, tumor microenvironment analysis showed a positive correlation between ZNF831 expression and immune cell infiltration, indicating its potential role in enhancing anti-tumor immunity. These findings underscore the importance of m7G modifications and m7G-related gene ZNF831 in THCA pathogenesis, highlighting their potential as therapeutic targets. Further research is needed to elucidate the molecular mechanisms and explore clinical applications of these findings.

The twin-arginine translocation (Tat) system is a mechanistically unique protein transport pathway moving folded proteins across membranes. It is found in all domains of life and is essential for bacterial virulence and plant photosynthesis. The membrane proteins, TatA, TatB and TatC form a core complex to which substrate proteins bind, triggering the recruitment of additional TatA protomers to form the transport site. Here we present cryo-electron microscopy structures of the prototypical TatBC complex from Escherichia coli and the atypical complexes from Nitratifactor salsuginis and Myxococcus xanthus in a resting state, alongside TatAC substrate-bound TatBC and TatABC complexes from E. coli in the early stages of transport. These structures demonstrate that substrate proteins associate with the core complex solely through their N-terminal signal peptides. The Tat targeting sequences of the signal peptides make specific contacts with TatC, and the peptide body is clamped by TatB. The core complex contains highly tilted transmembrane helices that drive extreme local membrane thinning. On the basis of our structures and biochemical and functional analyses, we propose a model for the early steps in Tat transport.

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