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PubMed2026

Translating single-cell RNA sequencing into monocyte direct leukocyte subpopulation-transcript abundance assay ratio-based biomarkers (IFI27/PSAP or IFI27/CTSS) for clinical detection of viral infection.

A rapid method for triaging febrile patients by aetiology (e.g., viral or bacterial infection) using gene expression in peripheral blood (PB) is an intensively researched area. However, gene expression in blood represents a composite sum of gene expression of all the component cell types present in the sample. As a result, numerous genes are measured in most proposed signatures. Herein, we propose a simple ratio-based biomarker (RBB) called direct leukocyte subpopulation-transcript abundance assay (DIRECT LS-TA) that recapitulates gene expressions of a single cell type in PB (i.e., monocytes). Based on single-cell RNA sequencing (scRNAseq) data and bulk expression data, IFI27 and SIGLEC1 are found as interferon-stimulated genes (ISGs) predominantly expressed by monocytes. The DIRECT LS-TA method can use a simple ratio of two genes measured in PB as an RBB to represent the target gene expression in monocytes without the need for monocyte purification. Both scRNAseq and bulk RNA sequencing datasets were used to evaluate the correlation between ISG expression in monocytes and PB, with a particular focus on monocyte expression of IFI27. An iceberg plot of bulk transcriptome data was used to identify genes that were predominantly expressed by monocytes in PB. DIRECT LS-TA RBBs of the three genes (IFI27, IFI44L and SIGLEC1) were evaluated by group-wise comparison, receiver operating characteristic and meta-analysis. In addition, the conventional interferon (IFN) score was evaluated for comparison of diagnostic performance. In viral infection datasets, DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) was most intensely activated (p value by t test <1e-9) and had the best area under the curve (0.94) among the three potential monocyte ISGs analysed. DIRECT LS-TA SIGLEC1 was also another monocyte biomarker but showed a lower activation (p<9e-5). IFI27/PSAP showed better diagnostic performance than the conventional IFN score. On the other hand, IFI44L was not a predominant monocyte expression gene. DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) measured in PB was the best biomarker of viral infection and IFN activation among ISGs predominantly expressed by monocytes. It performed even better than the conventional IFN score which required quantification of eight genes. The results suggest that DIRECT LS-TA of IFI27 is a monocyte-informative biomarker which is easy to determine in PB without the need for cell sorting.

Humans↗

PubMed2026

A randomized trial of viral vector and adjuvanted protein HBV therapeutic vaccine in people with chronic hepatitis B on nucleos(t)ide analogs.

BACKGROUND: This study assessed the safety, efficacy, and immunogenicity of a therapeutic immunization strategy aimed at reaching a functional cure for chronic hepatitis B (CHB), relying on a heterologous prime-boost with viral vectors ChAd155-hIi-HBV and MVA-HBV, combined with sequential or concomitant administration of adjuvanted recombinant HBV proteins (HBc-HBs/AS01B). METHODS: This single-blind, randomized, controlled, first-in-human, phase 1/2 trial enrolled adults aged 18-65 years with HBeAg-negative CHB, virally suppressed on nucleos(t)ide analogs (NAs), with HBsAg >50 IU/mL. Participants received NAs and the following regimens of 4 doses (8-week intervals): sequential administration of ChAd155-hIi-HBV, MVA-HBV, and 2 HBc-HBs/AS01B doses; co-administration of ChAd155-hIi-HBV+HBc-HBs/AS01B, followed by 3 co-administered MVA-HBV+HBc-HBs/AS01B doses; 4 HBc-HBs/AS01B doses; 2 placebo doses followed by ChAd155-hIi-HBV and MVA-HBV administered alone or with HBc-HBs/AS01B; or 4 placebo doses. Safety, efficacy (≥1-log decrease in quantitative (q)HBsAg or HBsAg loss 24 weeks post-dose 4 [day (D)337]), antibody, and T-cell responses were evaluated. RESULTS: In all, 134 participants were vaccinated. Grade 3 solicited adverse events (AEs) (median duration: 2-3 days) were more frequent after co-administration (systemic: 59.3%; administration-site: 33.3%) than sequential administration (systemic: 10.3%; administration-site: 12.8%) of high-dose viral vectors and proteins. No vaccine-related or fatal serious AEs were reported. After 4 doses, no participant had HBsAg loss or ≥1-log decrease in qHBsAg (D337 vs. D1). Co-administration induced the strongest anti-HBs response (73.7% achieved anti-HBs ≥10 mIU/mL 2 weeks post-dose 4 vs. 40.0% after sequential administration). Both sequential and co-administration induced HBc-specific CD4+ and CD8+ T-cell responses, with a prime-boost effect of the viral vectors. CONCLUSIONS: Heterologous prime-boost with ChAd155-hIi-HBV and MVA-HBV, combined with sequential or co-administration of HBc-HBs/AS01B, had an acceptable safety profile, were moderately immunogenic, but no participants showed the expected efficacy outcome.

Humans↗

PubMed2026

Genome mining of alkaliphilic cyanobacterial consortia: identification of biosynthetic gene clusters in Sodalinema and associated heterotrophs.

Alkaline soda lakes are high-pH environments that host specialized microbial communities with potential for biotechnology and natural product discovery. We characterized three Sodalinema-dominated cyanobacterial consortia enriched from Canadian soda lakes over 510 days. Using hybrid metagenomic sequencing and metatranscriptomics across pH, alkalinity, and temperature gradients, we reconstructed high-quality metagenome-assembled genomes and assessed functional activity. All consortia converged toward cyanobacteria dominance and exhibited temperature optima between 21°C and 30°C. Phylogenetic analysis placed Sodalinema genomes within a distinct clade affiliated with Candidatus Sodalinema alkaliphilum. Genomic analysis indicated complete biosynthetic pathways for vitamin B5, vitamin B7, and the molybdenum cofactor, but incomplete pathways for vitamins B1, B9, and B12, consistent with patterns observed in Sodalinema yuhuli. Metatranscriptomic profiles showed increased expression of genes involved in phycocyanin and carotenoid biosynthesis at pH 10.2 relative to pH 8.5. Biosynthetic gene cluster analysis revealed that most secondary metabolic potential resided in heterotrophic community members. Roseinatronobacter encoded pathways for N-acyl homoserine lactones, osmoprotectants, betalactones, and prodigiosin, while Alkalimonas, Wenzhouxiangella, and members of the Kiloniellales encoded clusters for lanthipeptides, cyclodipeptides, hydrogen cyanide, and pyrroloquinoline quinone. These findings indicate functional partitioning within the consortia and highlight the contribution of heterotrophs to secondary metabolism.IMPORTANCEAlkaline soda lakes contain microbial communities adapted to high pH that remain underexplored for biotechnology. This study focuses on Sodalinema, a filamentous cyanobacterium that dominates enriched consortia from Canadian soda lakes, and its associated heterotrophic partners. We show that while Sodalinema drives primary productivity, heterotrophic bacteria encode most of the pathways for antimicrobial and signaling compounds. These interactions may support community stability and defense against competing microorganisms. By linking genomic potential with gene expression, this work identifies alkaline cyanobacterial consortia as a source of bioactive compounds and provides a framework for exploring extremophilic microbial communities for natural product discovery.

Sodalinema↗

PubMed2026

Origins and timing of somatic variants in the brain.

Somatic variants accumulate in human brain cells throughout the lifespan. Variant allele fraction has traditionally been used as a proxy for both the developmental timing of somatic variants and their functional effect, based on the assumption that earlier mutations are shared by larger cell populations and therefore have greater potential for severe phenotypes. However, recent discoveries challenge this simplified model. Variables such as developmental bottlenecks, lineage restriction, and cellular and molecular context play critical roles in shaping the distribution and functional impact of somatic variants in the brain. These insights support a shift toward a context-dependent framework for interpreting somatic mosaicism.

Humans↗

PubMed2026

PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.

BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.

Humans↗

PubMed2026

Preoperative Olanzapine and Quality of Recovery after Ambulatory Surgery: A Randomized Clinical Trial.

BACKGROUND: Postdischarge nausea and vomiting negatively impact recovery after surgery. Preoperative administration of 10 mg olanzapine decreases postdischarge nausea and vomiting but increases sedation. No data are available on the impact of olanzapine on global quality of recovery. METHODS: This was a single-center, randomized, double-blind, placebo-controlled trial in female patients 18 to 50 yr old undergoing ambulatory surgery during general anesthesia. Participants received 5 mg oral olanzapine or placebo in addition to antiemetic prophylaxis with dexamethasone and ondansetron. The primary outcome was Quality of Recovery-40 (QoR-40) on postoperative day (POD) 1. Secondary outcomes included QoR-40 on POD 2, postdischarge nausea (any and severe) through POD 2, and postanesthesia care unit length of stay. QoR-40 analyses used mixed-effects models adjusted for baseline preoperative QoR-40 scores. The group differences and corresponding 95% CI are reported. RESULTS: A total of 384 participants received olanzapine (n = 191) or placebo (n = 193). Compared with placebo, olanzapine was associated with higher QoR-40 scores on POD 1 (difference, 9.0 points; 95% CI, 6.1 to 11.8; P < 0.001). The POD 2 difference was 4.8 points (95% CI, 2.0 to 7.6; nominal P = 0.001), and this secondary outcome remained significant after false discovery rate correction. Olanzapine was associated with lower odds of any nausea (odds ratio [OR], 0.43; 95% CI, 0.28 to 0.66) and severe nausea (OR, 0.26; 95% CI, 0.14 to 0.48) on POD 1. On POD 2, olanzapine was associated with lower odds of any nausea (OR, 0.48; 95% CI, 0.30 to 0.76), but not severe nausea (OR, 0.65; 95% CI, 0.30 to 1.40). Postanesthesia care unit length of stay did not differ between groups. The significance of these prespecified secondary outcomes was unchanged after false discovery rate correction. CONCLUSIONS: When combined with dexamethasone and ondansetron, a single preoperative dose of 5 mg olanzapine improved global quality of recovery after discharge from ambulatory surgery.

Humans↗

PubMed2026

Multi-omics panorama of glaucoma: Pathogenesis, biomarkers, and novel therapeutic strategies.

Glaucoma is a group of irreversible, blinding eye diseases characterized by progressive loss of retinal ganglion cells, leading to gradual visual field defects that severely impact patients' quality of life. Its complex pathophysiological mechanisms remain incompletely understood, limiting the development of early diagnostic and effective therapeutic strategies. Advances in omics technologies have provided new insights into elucidating the pathophysiology of glaucoma. We summarize specific alterations in genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics associated with glaucoma. We emphasize the systematic analysis of disease mechanisms, identification of clinically applicable biomarkers, and discovery of novel therapeutic targets through the integration of these data. This approach paves new pathways for glaucoma subtype diagnosis and personalized treatment, while also outlining future research directions and challenges.

Humans↗

PubMed2026

Assessing the threat of Bacillus cereus: From toxin characterization to modern detection strategies.

Bacillus cereus is a spore-forming pathogen responsible for both diarrheal and emetic foodborne illnesses worldwide. Its significance in food safety has received growing attention. Recent advances, including the discovery of novel virulence factors and the development of emerging detection technologies, have provided new insights into its pathogenic mechanisms and surveillance strategies. This review critically examines the global burden of B. cereus infections, and molecular mechanisms of its major virulence factors, and the performance characteristics of current detection knowledge gaps such as the viable-but-non-culturable state and regulatory blind spots for emetic toxins, and discuss unresolved challenges in clinical management. By integrating epidemiological, microbiological, and technological perspectives with critical lens, this review aims to provide a valuable reference for future research and food safety practices.

Bacillus cereus↗

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

Genetic overlap between estimated glomerular filtration rate and cardiovascular disease identifies potential targets for cardiorenal syndrome.

Heart and kidney diseases frequently coexist, but the genetic basis of this relationship remains unclear. We analyzed genetic data from large-scale studies to investigate how kidney function (estimated glomerular filtration rate, eGFR) and six common cardiovascular diseases share genetic risk factors. Using MiXeR method, and conjunctional false discovery rate (conjFDR) to identify overlapping genetic regions, we found 478 shared genomic loci between eGFR and cardiovascular diseases. These shared genes are involved in tissue development and structure. We also identified 29 genes that could be targeted by existing medications approved by the US Food and Drug Administration, such as PRKAG2, PDE1A, and IGF1R. Among these, genetically predicted higher level of IGF1R expression is associated with a higher eGFR, which reflects good kidney function and is protective against cardiorenal diseases, such as atrial fibrillation, and myocardial infarction. These findings reveal genetic overlap between kidney function and cardiovascular diseases, highlighting potential targets for understanding and treating cardiorenal syndrome.

Humans↗

PubMed2026

Human-Centered Workspace Optimization: A 2 × 2 Factorial Study of Adjustable Furniture and Indoor Environmental Quality.

Small workspaces function as integrated systems, yet ergonomic furniture and indoor environmental conditions are usually evaluated separately. A six-site, assessor-blinded, randomized 2 × 2 factorial controlled study was conducted of two multicomponent packages-adjustable furniture and optimized indoor environmental quality (IEQ)-among 240 office workers for four weeks. Each group included 60 participants. Overall comfort in week 4 was highest for both packages (5.62 ± 0.53 versus 3.99 ± 0.60 with fixed furniture and basic IEQ). In a site-adjusted factorial model with HC3 robust standard errors, the adjustable-furniture effect was 0.86 points (95% confidence interval [CI], 0.62-1.09), the optimized-IEQ effect was 0.34 points (95% CI, 0.12-0.55), and their interaction was 0.44 points (95% CI, 0.14-0.74). Adjustable furniture improved postural comfort and reduced neck and lower back discomfort; optimized IEQ improved environmental comfort; both packages improved perceived productivity, satisfaction, and fatigue. The task-accuracy interaction did not remain significant after false-discovery-rate adjustment, and exploratory mediation and spline analyses did not support indirect or nonlinear effects. These results support coordinated ergonomic and environmental implementation while preserving distinct outcome pathways.

Interior Design and Furnishings↗

PubMed2026

Gastrointestinal digestion governs insect protein hydrolysis and predicted bioactive peptide release: Species-dependent implications for functional food applications.

This study investigates the digestion of insect proteins and the release of predicted bioactive peptides during human gastrointestinal digestion. Using the Infogest in vitro model, mealworm, cricket, and black soldier fly larvae (BSFL) proteins were digested and analyzed through discovery proteomics and bioinformatics to identify predicted bioactive peptides. Sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) quantified insect proteins including predicted bioactive peptide precursor proteins, the precursors of predicted bioactive peptides. Results indicated that gastrointestinal digestion strongly influences peptide release, with the gastric phase exhibiting a richer predicted bioactive peptide profile than the small intestinal phase. Many predicted bioactive peptides were rapidly hydrolysed under small intestine conditions, which may lead to reduced stability or diminished activity in vivo, potentially explaining why certain peptides show strong bioactivity in vitro but limited effects in vivo. Additionally, predicted bioactive peptide release varied by insect species, influenced by genetic factors and peptide abundance. These findings highlight the importance of species selection and consideration of proteolytic digestion patterns in optimizing insect-derived bioactive peptides for functional foods and nutraceutical applications.

Animals↗

PubMed2026

Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence↗

PubMed2026

Divergent evolutionary strategies in spider venoms: A comparative proteomic profiling of four sympatric species from Yunnan.

Spider venoms comprise complex cocktails of bioactive molecules evolved for predation and defense, representing a valuable resource for biological research and pharmaceutical discovery. In this study, we performed a systematic analysis of venom gland extracts from four common spider species indigenous to Yunnan, China: Agelena limbata, Hippasa lycosina, Lycosa grahami, and Sinopoda pengi. Using an integrated transcriptomic and proteomic targeted profiling approach, we successfully annotated 141 distinct toxins. Comparative analysis revealed significant interspecific heterogeneity, suggesting distinct evolutionary trajectories and "weapon system economics." Both A. limbata and L. grahami exhibited a "peptide-dominant" profile anchored by neurotoxic peptides and isomerases, optimized for rapid chemical paralysis. In contrast, S. pengi displayed a distinct "protein-dominant" signature enriched with high-molecular-weight enzymes and CAP superfamily proteins, likely functioning to facilitate tissue degradation and toxin diffusion. Occupying an intermediate position, H. lycosina demonstrated a hybrid composition. These findings suggest that although these species share the same geographical range, their venom systems have undergone divergent evolutionary adaptations driven by specific ecological niches and hunting strategies. This study represents the first systematic proteomic characterization of these venom components, providing a valuable reservoir of molecular candidates while highlighting the bioinformatic nuances of analyzing whole-gland homogenates.

Animals↗

PubMed2026

Implicit and explicit statistical learning in reading: Evidence from a randomized controlled-learning study and computational modeling.

A key challenge in reading acquisition is understanding how learners extract the complex probabilistic mappings between print, meaning, and sound. Statistical learning (SL) theory offers a mechanistic account of how such mappings are acquired, whether implicitly through exposure or explicitly through instruction. We conducted a randomized controlled-learning study in Chinese, a writing system characterized by multiple sub-lexical regularities linking orthography, semantics, and phonology. Ninety-five 2nd-3rd graders with or at risk for dyslexia were randomly assigned to one of three groups: an implicit-SL training group exposed to repeated lexical and sublexical orthography-semantics-phonology associations, an explicit-SL training group receiving the same input plus explicit instruction on the sublexical print-sound mapping, and a no-SL control group. Both SL groups outperformed controls on the characters they were trained on, as well as on untrained characters that required generalization. However, only the explicit group demonstrated abstraction of print-sound mapping to novel items. Neural network simulations further revealed distinct mechanisms supporting implicit and explicit SL, consistent with a dual-system account of reading acquisition. Together, these findings (1) clarify how implicit and explicit learning distinctly support the discovery of statistical structure in written language and (2) underscore the implicit-explicit dual learning mechanism underlying reading acquisition.

Humans↗

PubMed2026

The combination of morphogenic regulators BABY BOOM and GRF-GIF improves maize transformation efficiency and promotes leaf regeneration.

Transformation is an indispensable tool for plant genetics and functional genomics. Although stable transformation in maize is no longer a major obstacle, there remains a need for accessible and efficient methods for academic laboratories. Here, we present the GGB system, a rapid and efficient approach optimized for immature embryo transformation in B104 and other maize lines. This system combines two distinct morphogenetic regulators, the wheat GRF4-GIF1 chimera and the maize BABY BOOM (BBM) transcription factor (hence the name "GGB") with a modified QuickCorn protocol, enabling regeneration of transformed maize plantlets in c. 2 months with an efficiency 7-fold higher than when compared to either morphogenic factor used in isolation. Expression of both regulators did not significantly affect development, eliminating the need to excise them after regeneration. However, transmission of the transgenic GGB construct through pollen was significantly reduced, potentially aiding transgenic line containment. We show that the GGB system is adaptable for CRISPR-Cas9 editing and reporter line generation. Furthermore, stable GGB transformants exhibited high leaf regeneration capacity via somatic embryogenesis. RNA-seq time-course profiling of GGB leaf cultures identified additional factors that could promote regeneration and led to the discovery of asparagine and trehalose as additional media components that significantly enhanced leaf regeneration.

Zea mays↗

PubMed2026

An Update on Inborn Errors of V(D)J Recombination.

V(D)J recombination is the fundamental process by which developing T and B lymphocytes generate diverse antigen receptors, enabling adaptive immunity. This tightly regulated program operates exclusively in lymphoid precursors during G1 phase and depends on the lymphocyte-specific RAG1-RAG2 recombinase to introduce programmed DNA double-strand breaks at recombination signal sequences, followed by repair through the classical nonhomologous end joining (c-NHEJ) pathway. Disruption of any step in this molecular choreography compromises antigen receptor diversity and underlies a spectrum of inborn errors of immunity (IEIs), ranging from severe combined immunodeficiency (SCID) to immune dysregulation with autoimmunity and granulomatous disease. In this review, we place disorders of V(D)J recombination within the broader framework of T-cell development, detailing the temporal waves of recombinase activity, chromatin accessibility, and DNA damage responses that guide thymocyte differentiation. We discuss pathogenic variants affecting the cleavage phase [RAG1, RAG2, and the recently identified RAG cochaperone NudC domain-containing 3 (NUDCD3)], end processing (ARTEMIS), ligation and repair (LIG4, XLF, XRCC4, PRKDC), and genome surveillance pathways (ATM, MRN complex, RNF168), highlighting genotype-phenotype correlations and mechanisms driving immune deficiency and dysregulation. We briefly review recent diagnostic advances, including newborn screening using T-cell receptor excision circles, repertoire sequencing, and functional assays, alongside current therapeutic strategies. Finally, we outline key unanswered questions and argue that continued integration of clinical observation with molecular discovery is essential to improve outcomes and deepen understanding of adaptive immune development.

Humans↗

PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗