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PubMed2026

Evaluation of three Aspergillus antibody assays for screening of chronic pulmonary aspergillosis: prospective diagnostic accuracy study.

OBJECTIVES: Chronic pulmonary aspergillosis (CPA) is a frequent complication of pulmonary tuberculosis (PTB), particularly in high-burden settings where access to reliable serological diagnostics remains limited. We evaluated the diagnostic performance of two immunochromatographic technology (ICT) lateral flow assays (LFAs) and an ELISA for CPA screening among patients with active or previously treated PTB. METHODS: In this two-year prospective multicentre diagnostic evaluation, serum from adults with prior or active PTB was tested using the Era Biology Aspergillus IgG ICT LFA, LDBio Aspergillus IgG/IgM ICT LFA, and Bordier Aspergillus fumigatus IgG ELISA. CPA diagnosis was established using a consensus composite reference standard incorporating clinical, immunological, radiological, and microbiological criteria. The Bordier ELISA was used as part of the immunological component of the consensus CPA diagnosis, with a cutoff optical density of ≥1.0. Diagnostic accuracy, agreement statistics, receiver operating characteristic analysis, and latent class analysis (LCA) were performed. RESULTS: Among 340 participants, 24 (7.06%) had CPA. Proportion of participants with positive antibody tests among all tested individuals were 6.76% for LDBio ICT LFA, 20.0% for Era Biology ICT LFA, and 11.47% for Bordier ELISA. Against consensus CPA diagnosis, Bordier ELISA showed 87.50% sensitivity and 94.30% specificity, LDBio ICT LFA 58.33% sensitivity and 97.15% specificity, and Era Biology LFA 66.67% sensitivity and 83.54% specificity. LCA estimated CPA prevalence at 7.72%. LCA-derived sensitivities and specificities were 86.58% and 99.92% for LDBio ICT LFA, 83.39% and 85.31% for Era Biology LFA, and 79.10% and 94.19% for Bordier ELISA. CONCLUSIONS: The Bordier ELISA showed high sensitivity and specificity, while the LDBio ICT LFA demonstrated very high specificity with strong LCA-derived performance. These findings support the use of ELISA for laboratory diagnosis and ICT as a point-of-care screening tool for CPA in resource-limited settings. Era Biology Aspergillus IgG LFA demonstrated moderate sensitivity and acceptable diagnostic performance, indicating its potential utility as a supplementary screening assay for CPA in settings where rapid, point-of-care testing is required.

Humans↗

PubMed2026

Multiplexed CRISPR/Cas9 mediated knockdown of BCH gene in potato enhances beta-carotene to combat vitamin A deficiency.

The inadequate amounts of provitamin A carotenoids in crops contribute to the widespread vitamin A deficiency, leading to malnutrition and blindness in humans. Suppression of the β-carotene hydroxylase (BCH) increases β-carotene levels. In the current study, we utilized the multiplexed CRISPR/Cas9 approach by designing three targets against the BCH gene in a local potato cultivar. Transformation efficiency was recorded as 15%, the successful integration of the CRISPR/Cas9-BCH multiplex construct in potatoes was confirmed through PCR. When analysed using TIDE software, Sanger sequencing revealed the highest indel efficacy of 92.1% in plant 7 and 26.6% in plant 1. qRT-PCR (quantitative real-time PCR) analysis indicated a significant 89-fold reduction in BCH transcript levels in genome-edited potato lines compared to control plants. Spectrophotometry demonstrated a notable increase in beta-carotene levels in genome-edited potato plants, ranging from 0.831 µg/mL FW to 4.236 µg/mL FW, compared to the control plant with the lowest beta-carotene concentration (0.344 µg/mL FW). HPLC analysis further confirmed increased beta-carotene levels in genome-edited potato plants, ranging from 0.11 mg/mL FW to 0.36 mg/mL FW, compared to the unmodified control plant with a minimum beta-carotene value of 0.09 mg/mL. Our results revealed that the multiplexed CRISPR-Cas9 approach targeting the BCH gene results in enhanced beta-carotene contents in potato tubers.

Solanum tuberosum↗

PubMed2026

Cis-regulatory variation in the MdCKX6 promoter is associated with allele-specific expression and fruit size in apple.

Fruit size is a key determinant of apple fruit quality and market value and is strongly influenced by phytohormone-regulated cell proliferation and expansion during early fruit development. Cytokinin oxidase/dehydrogenase (CKX) enzymes regulate cytokinin homeostasis by irreversibly degrading active cytokinins, but the contribution of natural variation in CKX genes to fruit size remains poorly understood. Here, we identified MdCKX6 as a candidate regulator of fruit growth in apple (Malus domestica). MdCKX6 exhibited pronounced allele-specific expression during fruit development in the cultivar 'Royal Gala'. Sequence analysis identified a promoter SNP associated with differential promoter activity and allele-specific expression. Genotyping of diverse apple cultivars and wild Malus accessions revealed a significant association between MdCKX6 promoter genotype and fruit size. Cultivars carrying low-expression alleles produced larger fruits, whereas high-expression alleles were associated with smaller fruits. To investigate gene function, MdCKX6 was overexpressed in tomato, resulting in reduced fruit size. Histological analyses of the transgenic tomato fruit revealed smaller pericarp cells. Transcriptome analysis of transgenic fruits revealed widespread changes in genes associated with cell-cycle regulation, cell wall modification, hormone-related processes, and transcriptional regulation. Together, these results identify MdCKX6 as a potential negative regulator of apple fruit growth and reveal an association between cis-regulatory variants, gene expression, and fruit size. This study provides new insights into the role of cytokinin metabolism in fruit development and highlights regulatory variation in MdCKX6 as a potential target for apple breeding.

Malus↗

PubMed2026

Effects of umbilical cord mesenchymal stem cell-derived exosomes on periodontal ligament stem cells: An exploratory study.

OBJECTIVE: To investigate whether exosomes derived from human umbilical cord mesenchymal stem cells (UCMSCs) at two osteogenic induction stages (undifferentiated and late-stage) differentially affect periodontal ligament stem cells (PDLSCs), and to explore the potential molecular basis. DESIGN: UCMSCs and PDLSCs were isolated and cultured. Exosomes were harvested from undifferentiated UCMSCs (Exo-D0) and UCMSCs after 14 days of osteogenic induction (Exo-D14). PDLSCs were treated with both exosome types. Proliferation and migration were analyzed using EdU and scratch assays, the latter under serum-free conditions. Early osteogenic differentiation was assessed by alkaline phosphatase staining and quantitative reverse transcription PCR (qRT-PCR). Differentially expressed miRNAs were identified by high-throughput sequencing and further analyzed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. RESULTS: Both exosome types promoted PDLSC migration. Exo-D0 enhanced early osteogenic differentiation, whereas Exo-D14 enhanced proliferation but reduced early osteogenic marker expression. Sequencing identified 21 differentially expressed miRNAs (13 upregulated, 8 downregulated). Bioinformatic prediction suggested that the putative target genes were enriched in Ras signal transduction, regulation of kinase activity, and focal adhesion, and further predicted significant enrichment in the MAPK, Ras, and PI3K-Akt signaling pathways, which are central to cell proliferation and osteogenic differentiation. CONCLUSIONS: Exosomes from undifferentiated and osteogenically induced UCMSCs exerted distinct effects on PDLSCs, potentially associated with differentially packaged miRNAs. These findings offer a basis for hypotheses about exosome-mediated mechanisms and support matching exosome sources to the intended therapeutic outcome as potential cell-free strategies for periodontal tissue regeneration and alveolar bone repair.

Humans↗

PubMed2026

XsiAMT1.1a was identified as a novel ammonium uptake functional gene and its overexpression combined with GA4 application significantly increased yield in Arabidopsis thaliana.

Nitrogen (N) is a key limiting factor for plant yield. Ammonium is one of the main N forms absorbed by plants. Overexpression of ammonium uptake functional genes, such as ammonium transporter (AMT), can increase yield. However, the AMTs reported to enhance yield significantly is still limited. No researches have focused on the effect of overexpressing AMT combined with hormone application on yield improvement. In this study, we first investigated the role of XsiAMT1.1a, a potential ammonium uptake functional gene in an ammonium preference plant Xanthium sibiricum, in ammonium uptake by the analysis of bioinformatics, gene expression and subcellular localization, and the determination of ammonium uptake rate in endogenous silencing and heterologous overexpression plants. Subsequently, the effect of XsiAMT1.1a overexpression combined with hormone application on yield increase was further investigated in model plant Arabidopsis thaliana. Our results showed that XsiAMT1.1a shared the same conserved domains with AtAMT1 subfamily members and localized on the plasma membrane. XsiAMT1.1a was induced by N deficiency and highly expressed during the reproductive period. XsiAMT1.1a endogenous silencing and heterologous overexpression significantly decreased and increased ammonium uptake rates in X. sibiricum and A. thaliana, respectively. Overexpression of XsiAMT1.1a significantly improved total N accumulation, biomass and yield in A. thaliana, while XsiAMT1.1a overexpression combined with GA4 application had a stronger promoting effect on the above indicators. Our research identified a novel ammonium uptake functional gene, XsiAMT1.1a, and provided a new yield-increasing strategy which was verified in A. thaliana.

Arabidopsis↗

PubMed2026

Artificial intelligence for anticancer drug discovery from natural products of macroalgae and sponges: A systematic review.

Marine natural products (MNPs) from macroalgae and marine sponges have inspired clinically important anticancer agents, including the cytarabine pharmacophore and the eribulin scaffold, while cyanobacterial dolastatin chemistry supplies the auristatin payloads of several marine-inspired antibody-drug conjugates (ADCs) such as brentuximab vedotin. Artificial intelligence (AI) methods, encompassing both classical machine learning (ML) with hand-engineered features and modern deep learning (DL) with many-layered neural networks, are increasingly supporting key decisions in natural-product anticancer drug discovery, including bioactivity prediction, target identification, absorption, distribution, metabolism, excretion and toxicity (ADMET) filtering, generative analogue design, and the selection of preclinical candidates. DL architectures relevant to this field include graph neural networks, transformer-based molecular generators, diffusion models for protein-ligand docking, and convolutional networks for mass spectrometry, while classical ML contributes interpretable fingerprint-based bioactivity models and molecular networking for dereplication. This review follows a systematic literature review methodology to organize the landscape of AI methods now applied to MNP anticancer discovery, distinguishing ML and DL approaches where relevant, situating them within the chemical context of macroalgal and sponge-derived oncology leads, and critically examining published case studies, including validation level (computational, in vitro, in vivo, clinical). The principal bottleneck for medical translation has shifted partly from algorithmic capability toward data infrastructure and experimental validation. Sparse, heterogeneous, and taxonomically biased bioactivity records limit what current models can learn and reduce the reliability of AI-prioritized candidates entering the preclinical pipeline. A roadmap is proposed that prioritizes open MNP-specific benchmarks, symbiont-aware modeling, and active learning loops with synthesizability and ADMET constraints. These AI workflows may accelerate the prioritization of marine-derived anticancer leads and support earlier, more evidence-based translational decisions in oncology drug development.

Biological Products↗

PubMed2026

A review on the environmental distribution, toxic effects, bioaccumulation characteristics and risk assessment of short-chain chlorinated paraffins.

Chlorinated paraffins (CPs) are synthetic chemicals, widely used as flame retardants and plasticizers. As emerging contaminants, short chain chlorinated paraffins (SCCPs) have attracted tremendous attention due to their persistence, chronic toxicity, long-range transport potential and bioaccumulation potential. This review synthesizes global data on SCCPs' environmental occurrence, toxicological impacts, and bioaccumulation characteristics. SCCPs are ubiquitously detected in various environmental media, including water, sediment, air, soil, and biota. Ecotoxicological studies reveal that SCCPs have lethality, carcinogenicity, growth and developmental toxicities, organs toxicities and endocrine-disrupting effects across species, which pose risks to ecological systems and human health. In addition, the bioaccumulation effects of SCCPs in terrestrial and aquatic ecosystems were analyzed, and proposed the key factors affecting the bioaccumulation of SCCPs. Finally, the risk assessment of SCCPs contamination in the surface water and the soil was carried out, and all soil and most water bodies were found to be low risk. The present study could provide scientific basis and reference for environmental management of CPs products.

Paraffin↗

PubMed2026

Genome-wide identification of CXE gene family in soybean and functional characterization of GmCXE31 in lipid biosynthesis and salt tolerance.

GmCXE31 negatively regulates salt tolerance and lipid synthesis in soybean, and the cxe31-edited lines improve soybean yield and seed quality. Carboxylesterases (CXEs), as essential lipid hydrolases of the α/β-hydrolase fold superfamily, are critical for plant stress responses, hormone signaling and secondary metabolism. The key candidate gene GmCXE31 was previously identified in our laboratory through a genome‑wide association study (GWAS) of soybean lipid‑related traits. In the present study, we further identified 60 GmCXE family genes in soybean. Phylogenetic analysis clustered them into 11 conserved subfamilies. Cis-acting element analysis showed their promoters are enriched with elements related to abiotic stress, growth and hormone signaling, suggesting potential roles in soybean development and stress adaptation. GmCXE31 is highly expressed in seedling roots and responsive to strigolactones (SLs) and salt stress. Functional assays revealed that GmCXE31 negatively regulates soybean salt tolerance: its overexpression reduced salt tolerance in Arabidopsis and soybean under 150 mM NaCl stress, while its knockout enhanced this trait. Lipid profiling revealed GmCXE31-edited lines had higher seed oil content, elevated oleic/linoleic acid ratio and lower saturated fatty acid proportion, which was achieved by regulating lipid synthesis-related genes like GmNFYA. Agronomic trait analysis showed GmCXE31-edited lines had increased nodule number, plant height and single-plant yield at maturity, with opposite phenotypes in overexpression lines. In conclusion, this study elucidates the multifaceted roles of GmCXE31 in coordinating soybean salt tolerance, lipid metabolism and agronomic traits, providing theoretical and genetic resources for salt-tolerant and high-quality soybean molecular breeding.

Glycine max↗

PubMed2026

Low Carbohydrate Availability in Energy Balance Alters Bone Turnover and Muscle Proteomic Response With Limited Endocrine Disruption.

Training with low carbohydrate availability (LCA) has been proposed as an independent determinant of physiological perturbations commonly attributed to low energy availability (LEA) and to increase skeletal muscle oxidative machinery, yet the effects of LCA in isolation from LEA remain unclear. We examined whether short-term carbohydrate restriction under energy balance alters endocrine and metabolic markers associated with LEA and skeletal muscle proteomic response. In a randomized crossover design, eight trained males completed 4 days of either a low-carbohydrate high-fat diet (LOW; 12% carbohydrate, 69% fat, 19% protein) or a normal-carbohydrate diet (NORM; 62% carbohydrate, 19% fat, 19% protein), while undertaking daily cycloergometer exercise (15 kcal kg FFM-1 day-1) and maintaining energy availability at 45 kcal kg FFM-1 day-1. LOW induced a clear metabolic shift consistent with LCA, evidenced by elevated circulating free fatty acids, glycerol and β-hydroxybutyrate, in fasting conditions and fat oxidation at rest and during exercise, alongside reduced exercise glucose concentrations. Despite these responses, LOW did not alter insulin, testosterone, triiodothyronine, leptin, hepcidin, or P1NP. In contrast, β-CTX increased and IGF-1 decreased relative to NORM. Muscle glycogen concentration decreased only in LOW (40% ± 14%). Proteomic analysis identified 671 proteins; 57 differentially expressed in LOW relative to NORM were limited to fatty acid metabolism pathways and suppression of ribosomal, sarcomeric, and extracellular matrix proteins. These findings indicate that isolated LCA exerts limited endocrine disruption but may selectively compromise bone turnover and muscle anabolic response, suggesting that without acute LEA, LCA has limited influence on muscle oxidative phenotype.

Male↗

PubMed2026

Comparative phylogenomics and transcriptional regulatory networks of AQPs, HSPs, and LEA proteins in salt-stressed Portulaca oleracea.

Soil salinization severely threatens global food security, necessitating systematic investigations of halophytes like Portulaca oleracea to decode the molecular mechanisms of environmental resilience. Utilizing an integrated framework of deep learning-based genome annotation (58,817 predicted genes; 96.5% BUSCO completeness), multi-tissue RNA-Seq, phylogenomics, and gene regulatory network (GRN) inference, the synergistic orchestration of 78 aquaporins (AQPs), 525 heat shock proteins (HSPs), and 119 late embryogenesis abundant (LEA) proteins was elucidated. The active transcriptome, encompassing 39,065 expressed loci, revealed a systemic growth-defense trade-off. Tissues displayed distinct adaptive mechanisms: leaves modulated intracellular water balance via specialized AQPs, whereas adult roots maintained proteostasis through robust HSP20/HSP70 induction. Phylogenomic clustering across 154 species demonstrated that salinity tolerance constitutes an evolutionary mosaic, identifying 81 halophyte-exclusive orthogroups and 1129 species-specific clusters. Comparative topology across six independent GRNs (4.2M-5.3 M edges) unmasked a highly modular transcriptional reprogramming strategy governed by a core apparatus of 22 stress-exclusive regulators, with functional enrichment heavily prioritizing protein dimerization and chromatin remodeling. Theoretically, the distinct convergence of Trihelix transcription factors with guard cell differentiation pathways offers a candidate transcriptomic framework to explain the plant's characteristic C4-CAM photosynthetic plasticity under severe osmotic pressure. Practically, these evolutionary blueprints and specific master switches transcend single-gene transgenic limitations. Utilizing these root-sustained and stress-inducible targets under localized promoters provides a naturally optimized, network-level precision engineering roadmap to transfer robust, compartmentalized halotolerance to sensitive glycophytic crops.

Gene Regulatory Networks↗

PubMed2026

Community-driven advances in computational mass spectrometry: The perspective of EuBIC-MS members.

Advances in data acquisition, artificial intelligence, and integrative bioinformatics are driving the rapid evolution of computational mass spectrometry, and in turn, transforming modern proteomics, metabolomics, and lipidomics. These developments have greatly increased the scale and complexity of mass spectrometry data, underscoring the importance of evolving accurate, transparent, efficient and reproducible data processing workflows. Addressing these challenges requires collaborative innovation that brings together expertise in software engineering, statistics, and biology. The European Bioinformatics Community for Mass Spectrometry (EuBIC-MS), an initiative of the European Proteomics Association (EuPA), fosters a culture of open, community-driven development through its biennial Developers Meetings and Winter Schools. This commentary summarizes the scientific background and outcomes of the EuBIC-MS Developers Meeting 2025, which took place in Novacella, Italy. Three keynote presentations highlighted major frontiers in the field: deep proteome and phosphoproteome profiling, text mining for protein-protein interaction extraction, and scalable proteomics for AI-driven drug discovery. Seven community-selected hackathons addressed emerging challenges such as single-cell proteomics data analysis, FAIR metadata extraction, deep learning frameworks, R-Python interoperability, and DIA validation. Together, these efforts demonstrate the potential for scientific and technical innovation to arise from open collaboration, and highlight how community-driven initiatives can accelerate progress in computational mass spectrometry. SIGNIFICANCE: Modern proteomics increasingly depends on computational advances to translate complex, high-dimensional data into biological knowledge. The EuBIC-MS Developers Meeting 2025 exemplifies how community-driven collaboration can directly accelerate this process by bringing together experts from bioinformatics, statistics, and experimental proteomics to co-develop open, interoperable, and reproducible analytical tools. By fostering shared software frameworks, transparent benchmarking, and collaborative problem solving, the EuBIC-MS community helps ensure that technological innovation translates into reliable biological insights. This collaborative model strengthens the foundation for quantitative, system-level understanding of proteomes and establishes a sustainable path for integrating artificial intelligence and next-generation data acquisition into routine biological discovery. This commentary shows some current highlights in the field of computational mass spectrometry and community-based approaches undertaken during the most recent Developers Meeting to solve these challenges. The approaches discussed and initiated during the meeting - ranging from deep proteome profiling and phosphosite mapping to text mining, single-cell data analysis, and FAIR metadata extraction - address key bottlenecks that currently limit the biological interpretability and comparability of proteomics data.

Mass Spectrometry↗

PubMed2026

"Clinical efficacy and expression of antimicrobial resistance genes after using a novel herbal mouthwash compared to chlorhexidine: A Randomised controlled trial in generalised gingivitis patients".

OBJECTIVES: Chlorhexidine, the gold-standard mouthwash, has several disadvantages, like promotion of antimicrobial resistance. Herbal mouthwashes are emerging as alternatives to chlorhexidine. However, its impact on antimicrobial resistance remains unclear. The aim of the study was to compare the clinical efficacy and the expression of antimicrobial resistance genes of chlorhexidine with a novel herbal mouthwash. DESIGN: Sixty patients with generalised gingivitis were randomly assigned to two groups using block randomisation. After professional mechanical plaque removal patients were instructed to use either chlorhexidine or a novel herbal mouthwash (patented composition) for two weeks. Tetracycline resistance (tetM) and macrolide efflux (mefI) gene expression in subgingival plaque were analysed using real-time polymerase chain reaction. Intragroup comparisons were performed with a paired t-test and Wilcoxon signed-rank test for parametric and nonparametric data. Intergroup comparisons employed unpaired t-test, chi-square test, and Mann-Whitney test. RESULTS: A significant reduction in bleeding, plaque, pocket depth and and patient reported outcomes were noticed in both groups. But reduction in plaque was more significant in chlorhexidine group. tetM and mefI genes significantly upregulated in the chlorhexidine group, while it was downregulated with herbal mouthwash (fold change 1.79 ± 0.74 and 0.60 ± 0.43 for tetM, and 1.83 ± 0.87 and 0.51 ± 0.44 for mefI). However, patients' perception of taste, freshness, and overall satisfaction was better in the chlorhexidine group. CONCLUSIONS: The increased expression of antimicrobial resistance genes following chlorhexidine use warrants careful consideration. Herbal mouthwash is an effective, safer alternative with comparable clinical benefits and less impact on antimicrobial resistance.

Humans↗

PubMed2026

Comprehensive analysis of mRNA-microRNA-lncRNA expression profiles in post-traumatic elbow heterotopic ossification using RNA sequencing and experimental validation.

BACKGROUND: This study aimed to profile the molecular signatures of post-traumatic elbow heterotopic ossification (HO) to identify key regulators and potential therapeutic targets. METHODS: Total RNA from post-traumatic elbow HO tissues (n=4) and normal bone tissues (n=6) was subjected to high-throughput sequencing to identify differentially expressed mRNAs (DEGs), microRNAs (DEMs), and lncRNAs (DELs). Bioinformatics analyses included Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein-protein interaction network construction, and transcription factor (TF)-microRNA-mRNA network analysis. The expression trends of four most upregulated and four most downregulated DEGs were validated by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). RESULTS: We identified 2,138 DEGs, 40 DEMs, and 905 DELs. DEGs were significantly enriched in biological process "bone mineralization," cellular component "plasma membrane," molecular function "integrin binding," and pathways including PI3K-Akt, NF-κB, JAK-STAT, and TNF signaling pathways. Hub genes with high connectivity included MMP9, IL6, MMP3, CTSK, and BGLAP. Integrated network analysis highlighted the transcription factor JUN and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b). The qRT-PCR results confirmed the expression trends of selected DEGs. CONCLUSIONS: This study, for the first time, profiled the differentially expressed mRNAs, microRNAs, and lncRNAs in post-traumatic elbow HO using high-throughput RNA sequencing. These findings provide valuable insights into the molecular mechanisms of HO following elbow trauma. The identified hub genes (MMP9, IL6, MMP3, CTSK, and BGLAP), key TF (JUN), and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b) may serve as potential therapeutic targets for preventing and treating post-traumatic elbow HO.

Humans↗

PubMed2026

Proteomic characterization of the acquired enamel pellicle under acidic challenges at early and mature formation stages.

OBJECTIVES: This study aimed to characterize acquired enamel pellicle (AEP) proteomic changes after exposure to citric acid (CA) and hydrochloric acid (HCl) under different pellicle formation times (3 and 120 min) in the same volunteers. DESIGN: Nine healthy volunteers participated in this randomized crossover in vivo study. The AEP was allowed to form for 3 or 120 min and subsequently exposed for 10 s to deionized water (control), 1% CA (pH 2.5), or 0.01 M HCl (pH 2.0). Pellicle samples were collected, followed by protein extraction, tryptic digestion, and analysis by nanoliquid chromatography (nanoLC) coupled to mass spectrometry (MS) with MSE (data-independent acquisition; nanoLC-MSᴱ). Label-free quantitative proteomics were performed for relative quantification using t-test (p < 0.05). RESULTS: At 120 min, CA exposure markedly reduced several typical AEP proteins, especially acidic proline-rich proteins (PRPs). Conversely, basic PRPs were upregulated, suggesting acid-resistance protein signature. At 3 min, basal-layer proteins (PRPs, cystatins, histatins and mucins) were more abundant. Hemoglobins increased 6-8-fold (up to 150-fold in 3 min control), suggesting association with early pellicle formation and an acid-resistant protein signature. CA exposures for 120 min also upregulated typical AEP proteins (PRPs, mucins, cystatins, immunoglobulins), while HCl exposure depleted albumins and lactotransferrin. CONCLUSION: Intrinsic and extrinsic acids induce distinct proteomic signatures in the AEP. Hemoglobin and PRPs appear consistently enriched in the early pellicle layer, reflecting an initial acid-resistant protein signature. These findings provide new insights into the molecular remodeling of the AEP following intrinsic and extrinsic acid exposure, highlighting proteins potentially involved in early-stage pellicle formation.

Humans↗

PubMed2026

Reassessment of the effect of oral l-arginine on blood pressure: A systematic review and meta-analysis based on ambulatory blood pressure monitoring.

OBJECTIVE: This meta-analysis aimed to evaluate the effect of oral l-arginine supplementation on ambulatory blood pressure (ABP). METHODS: A systematic search of PubMed, Cochrane Library, Embase, and Web of Science databases was conducted from their inception through March 1, 2026. Randomized controlled trials (RCTs) assessing the effects of oral l-arginine intervention were included. Outcome measures included 24-h systolic blood pressure (24h SBP), 24-h diastolic blood pressure (24h DBP), daytime systolic blood pressure (dSBP), daytime diastolic blood pressure (dDBP), nighttime systolic blood pressure (nSBP), and nighttime diastolic blood pressure (nDBP). Meta-analysis was performed using Stata 17.0. The weighted mean difference (WMD) was used as the effect size, and the results were pooled with 95% confidence intervals (CIs). RESULTS: A total of 5 RCTs comprising 202 participants were included. Meta-analysis results demonstrated that oral l-arginine significantly reduced 24h SBP (WMD = -4.23 mmHg, 95% CI [-5.87, -2.58]; P < 0.01) and 24h DBP (WMD = -3.04 mmHg, 95% CI [-4.48, -1.59]; P < 0.01). Significant reductions were also observed for dSBP (WMD = -4.16 mmHg, 95% CI [-5.90, -2.41]; P < 0.01) and dDBP (WMD = -4.25 mmHg, 95% CI [-5.85, -2.66]; P < 0.01). Furthermore, oral l-arginine significantly lowered nSBP (WMD = -5.70 mmHg, 95% CI [-7.81, -3.58]; P < 0.01) and nDBP (WMD = -4.18 mmHg, 95% CI [-6.27, -2.09]; P < 0.01). CONCLUSION: Oral l-arginine supplementation significantly reduces ABP. However, the number of included studies was limited, and further validation through additional relevant research is warranted.

Arginine↗

PubMed2026

Phenotypic, physiological and transcriptomic analysis of graded salt stress responses in Pyrus betulifolia Bunge and functional characterization of the hub gene PbSTY46.

Pyrus betulifolia Bunge is a salt‑tolerant rootstock for pear, but its salt‑tolerance mechanisms remain largely unknown. In this study, P. betulifolia seedlings were subjected to graded NaCl stress at concentrations of 0 (CK), 50 (T1), 100 (T2), and 200 (T3) mM. We integrated phenotypic observation, physiological assessment, transcriptomic profiling, and functional gene validation to systematically elucidate its salt tolerance mechanisms. Salt stress inhibited seedling growth and root traits in a concentration-dependent manner, and T3 caused the most severe damage. Osmotic solutes responded differentially: soluble sugars peaked under T2, while proline peaked under T3. Antioxidant enzymes showed tissue-specific biphasic responses and declined after prolonged T3 stress. Meanwhile, chlorophyll and photosynthesis decreased, whereas anthocyanin increased, indicating a metabolic shift from photosynthesis to photoprotection. Transcriptome analysis revealed distinct responses depending on stress intensity: mild stress induced membrane lipid remodeling, moderate stress activated circadian rhythm and hormone signaling, and severe stress enhanced phenylpropanoid biosynthesis and thiamine metabolism. Gene Set Enrichment Analysis (GSEA) further highlighted progressive enrichment of phenylpropanoid biosynthesis, heme binding, and oxidoreductase activity. Weighted Gene Co‑expression Network Analysis (WGCNA) identified a blue module significantly positively correlated with root traits, from which the hub gene PbSTY46 was identified. Functional validation via overexpression, loss‑of‑function mutants, and pharmacological interventions (MeJA/DIECA) confirmed that PbSTY46 acts through JA signaling to enhance antioxidant enzyme activities and thereby confer salt tolerance. Collectively, P. betulifolia adopts a "survival‑first" strategy that coordinates growth arrest, osmotic homeostasis, and ROS scavenging. These findings establish PbSTY46 as a key regulator that links JA signaling to antioxidant defense. Thus, PbSTY46 represents a promising candidate for marker‑assisted breeding of salt‑tolerant pear cultivars.

Salt Stress↗

PubMed2026

Protein persulfidation emerges as a conserved component of the redox response to DNA damage.

Genotoxic stress is frequently accompanied by alterations in cellular redox homeostasis; however, the mechanisms linking redox regulation to the DNA damage response (DDR) remain incompletely understood. Here, we investigated the early redox response to DNA damage induced by methyl methanesulfonate (MMS) in Saccharomyces cerevisiae, focusing on cysteine oxidative post-translational modifications (PTM). We show that activation of the DNA damage response is accompanied by rapid redox changes that occur in the absence of a generalized oxidative stress response. MMS exposure promotes selective remodeling of cysteine oxidative modifications, characterized by decreased free thiols, robust induction of protein persulfidation, and comparatively modest changes in sulfenylation. These alterations are accompanied by increased intracellular hydrogen sulfide levels, supporting the involvement of reactive sulfur species in the cellular response to DNA damage. Proteome-wide analyses revealed that cysteine oxidative modifications preferentially target proteins involved in central metabolism, nucleotide biosynthesis, and genome maintenance. Consistent with these observations, MMS-induced genotoxic stress promotes metabolic adaptation characterized by increased mitochondrial respiration, elevated ATP production, and mitochondrial morphological remodeling, linking bioenergetic adaptation to redox regulation. Importantly, perturbation of intracellular redox balance using N-acetylcysteine compromises survival under DNA-damaging conditions, supporting a functional role for redox signaling during the DDR. Finally, MMS treatment also induces protein persulfidation in mammalian cells. Moreover, exposure to etoposide, a mechanistically distinct genotoxic agent that induces DNA double-strand breaks through topoisomerase II inhibition, showed a similar trend, suggesting that protein persulfidation may not be restricted to alkylation-induced DNA damage. Together our findings identify protein persulfidation as a prominent component of the redox response to DNA damage and provide new insight into the functional interplay between mitochondrial metabolism, cysteine-based redox regulation, and genome maintenance.

Oxidation-Reduction↗

PubMed2026

Meta-PseU: A meta-classifier for robust prediction of RNA pseudouridine modification sites from long sequences.

BACKGROUND AND OBJECTIVES: Pseudouridine (Ψ) represents one of the most abundant and conserved RNA modifications. Ψ provides an additional hydrogen-bond donor that enhances RNA structural stability and modulates translation. It participates in diverse biological processes, including RNA-protein interactions, splicing, translational control, and stress responses. Aberrant pseudouridylation is implicated in cancer, neurodegenerative disorders, and autoimmune diseases. Despite its biological importance, experimental identification of Ψ sites remains time-consuming and costly, limiting the feasibility of transcriptome-wide profiling. Computational approaches have therefore become essential complements to experimental techniques. However, state-of-the-art machine-learning and deep-learning predictors often suffer from limited generalizability due to small training datasets. To overcome these issues, we aim at constructing new long-sequence datasets and developing a novel Ψ site predictor. METHODS: New long-sequence datasets were constructed as benchmarks for RNA Ψ-site prediction. The Ψ modification sites in RMBase 3.0 were mapped to the reference genomes across three species of human, mouse, and yeast, and the RNA sequences with a length of 201 were generated by extending the upstream and downstream from the mapped, central sites. To eliminate sequence redundancy, the sequences were clustered using CD-HIT with a 70% sequence identity threshold. We developed Meta-PseU, a logistic regression-based meta-classifier that considered 118 machine learning and deep learning classifiers. The datasets and programs are freely accessible at https://github.com/kuratahiroyuki/MetaPseU. RESULTS: By optimizing model configuration, we proposed the Meta-PseU model stacking 32 machine learning and deep learning classifiers out of 118 classifiers. Meta-PseU substantially improved model generalizability, overcoming a key limitation of existing approaches. It greatly outperformed state-of-the-art predictors and achieved increasing accuracy with increasing sequence length. CONCLUSIONS: Long-sequence datasets were newly constructed as benchmarks for RNA Ψ-site prediction. Meta-PseU offers a new framework for robust Ψ-site identification by using long sequences.

Pseudouridine↗