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PubMed2026

Metabolomic and structural signatures of pigmented and non-pigmented Himalayan rice landraces.

BACKGROUND: This study investigated the anti-oxidant properties, starch composition, pasting behavior, structural properties, textural properties and non-targeted metabolomic profiles of pigmented and non-pigmented rice landraces as potential next-generation functional food ingredients. RESULTS: Pigmented rice demonstrated 1.34 times more anti-oxidant activity as compared to non-pigmented rice. Pigmented landraces showcased superior nutritional and functional attributes, including higher total dietary fiber and starch content. Fourier-transform infrared (FTIR) analysis revealed distinct molecular signatures with enhanced peak transmittance, while X-ray diffraction (XRD) indicated greater crystallinity ranging from 36-44.3% in pigmented rice compared with 30-40% in non-pigmented rice, suggesting improved digestibility and processing versatility. Pigmented rice recorded less amylose content hence tended to possess increased adhesiveness values whereas non-pigmented rice revealed greater amylose content hence was coupled with greater hardness values. Field-emission scanning electron microscopy (FE-SEM) images revealed that pigmented rice had densely packed and polygonal starch granules whereas non-pigmented rice had loosely packed starch granules with intergranular voids. Untargeted gas chromatography-mass spectrometry (GC-MS) profiling identified 84 metabolites, including unique compounds such as 3,3-dimethylbutanol and ethanoic acid, along with shared metabolites such as sucrose and linoleic acid, highlighting notable biochemical diversity. Multivariate statistical analyses using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway mapping further differentiated the metabolomic landscapes, with variable importance in the projection (VIP) scores identifying key bioactive contributors. CONCLUSION: Pigmented rice landraces exhibited significant functional and nutritional advantages, making them promising candidates for functional food development and nutritional improvement programs. These findings support their potential role in advancing sustainable and health-oriented food systems. © 2026 Society of Chemical Industry.

Oryza↗

PubMed2026

Genomic insights into end-use grain quality and nutritional traits of an ancient Indian dwarf wheat ( Triticum sphaerococcum Percival) population using a multi-locus genome-wide association study.

BACKGROUND: Triticum sphaerococcum, an ancient hexaploid wheat species, is renowned for its stress resilience and superior nutritional quality. A panel of 116 T. sphaerococcum accessions (the largest known collection at a single site globally), with six bread wheat released varieties, was evaluated for its potential for genetic quality improvement. Field experiments were conducted under standard, heat and moisture-deficit conditions across two cropping seasons for ten grain end-use quality and nutritional traits. RESULTS: Genotypes showed highly significant differences (P ≤ 0.001) for measured traits, with high broad-sense heritability resulting from substantial genotypic variance contributions. Triticum sphaerococcum consistently outperformed T. aestivum across environments, with moisture-deficit stress proving more detrimental to quality parameters than heat stress, while micronutrient content increased under stressed conditions. Trait correlations revealed that the gluten index (GI) correlated negatively with the grain hardness index (GHI), wet gluten (WG), and water-binding capacity (WB), while positively correlating with dry gluten (DG) and protein content (PRO), whereas grain iron (GFE), zinc (GZN), and protein showed consistent positive interrelationships. Two superior accessions, PAUTS10 (WG 35.13%, DG 13.71%, PRO 16.42%, GZN 50.89 ppm) and Sonamoti (WG 33.33%, DG 12.92%, PRO 16.27%, GZN 56.03 ppm), were identified, surpassing the best check variety HD3226 for quality and nutritional parameters. Multi-locus genome-wide association studies identified 30 stable quantitative trait nucleotides across environments, with candidate gene analysis revealing genes involved in transcription regulation, biosynthetic processes, metal ion homeostasis, and transport. CONCLUSIONS: Triticum sphaerococcum demonstrated superior grain quality and micronutrient potential compared with modern wheat, highlighting its value as a genetic resource for biofortification. The identification of elite accessions and stable quantitative trait nucleotides (QTNs) provides useful targets for breeding programs aimed at improving protein and micronutrient content. Integrating ancient germplasm with modern genomic tools can accelerate the development of nutritionally enhanced wheat varieties. © 2026 Society of Chemical Industry.

Triticum↗

PubMed2026

Temporal proteomic analysis reveals a three-phase adaptation strategy in Phytophthora cinnamomi during salinity stress.

Phytophthora cinnamomi, a highly invasive hemibiotrophic oomycete, threatens global agriculture, forestry, and native ecosystems. Although drought and temperature effects on P. cinnamomi-host interactions are well studied, current knowledge of abiotic stress responses in P. cinnamomi remains largely centered on infection and phytopathology, with limited molecular insight into the pathogen's direct response to salinity independent of its host. To address this gap, we combined growth assays, time-resolved proteomics, and network analysis to define how P. cinnamomi responds and adapts to salinity exposure. Growth assays showed that NaCl-modified agar enhanced mycelial expansion in a concentration-dependent manner, with 100 mM NaCl significantly increasing growth at 48, 72, and 96 h compared with controls, while 50 mM NaCl remained comparable to control conditions. Temporal proteomic analysis of 100 mM NaCl treatment at 0, 1, 6, 12, and 24 h post treatment revealed dynamic shifts in protein abundance. Early induction of ROS (Reactive Oxygen Species)-detoxifying enzymes, including glutathione S-transferases and peroxidases, was consistent with ROS-specific staining assays. Network analysis identified modules enriched for redox regulation, ATP generation, ion transport, and translational control, highlighting multi-layered adaptation to elevated NaCl levels. Notably, clusters of conserved hypothetical proteins were strongly upregulated, indicating unexplored stress tolerance components in Phytophthora species. Here, we propose that P. cinnamomi rapidly activates a three-phase strategy involving metabolism readjustments, redox defenses, and cellular structure alterations under salinity conditions. With increasing soil salinization due to climate change, our study provides first mechanistic insights into P. cinnamomi's adaptive plasticity and ecological resilience to abiotic stress. SIGNIFICANCE: This study represents the first temporal proteomic analysis of salinity stress adaptation in Phytophthora cinnamomi, revealing a sophisticated three-phase adaptation strategy. This research fundamentally advances our understanding of how this globally destructive plant pathogen, P. cinnamomi, maintains environmental resilience. Our findings reveal proteome remodelling as a mechanistic framework for understanding stress tolerance in oomycetes, a group of microorganisms responsible for some of the world's most destructive agricultural and forest diseases. Our results show proteins involved in emergency damage control through metabolic recalibration to sustained adaptation. These findings have relevance for predicting pathogen behavior under climate change scenarios, where increasing soil salinity threatens agricultural productivity while simultaneously enhancing pathogen survival and virulence. Understanding how P. cinnamomi responds to prolonged salinity exposure may inform targeted biocontrol strategies and improve predictive models of disease pressure in salt-affected agricultural regions. The temporal analysis framework we present offers a broadly applicable approach for understanding microbial stress adaptation, with implications extending beyond plant pathology to environmental microbiology and biotechnology applications where stress tolerance is paramount.

Phytophthora↗

PubMed2026

Inactivation of Aspergillus flavus spores by dielectric barrier discharge cold plasma: Kinetics, physiological properties and proteomic analysis.

A. flavus, as a pathogen, poses a grave threat to both human and livestock health, significantly influencing agricultural production as well. This study aimed to investigate the inactivation effect and mechanism of dielectric barrier discharge cold plasma (DBD-CP) on A. flavus spores. The results exhibited that DBD-CP effectively inactivated A. flavus spores by the Weibull + Tail model. Furthermore, the physiological and proteomic analysis revealed that DBD-CP destructed cell wall and membrane integrity, causing cellular protein leakage and increasing membrane penetration of ROS generated from DBD-CP. Although intracellular ROS was excessively accumulated, the protein levels and activities of SOD and CAT were decreased, indicating that intracellular redox homeostasis was disrupted by DBD-CP. Subsequently, DBD-CP treatment induced cellular protein oxidation and changed protein structures, resulting in unstable protein structures. Meanwhile, protein synthesis and degradation in A. flavus spores were disturbed by inhibiting ribosome biogenesis, initiation process and NEDD8-mediated UPS, which did not compensate for the loss of protein caused by oxidative damage and leakage, leading to A. flavus spore inactivation. Besides, DBD-CP could attenuate A. flavus virulence by downregulating hydrolytic enzymes and CFEM-related proteins. This study provides novel insight into the inactivation mechanism of DBD-CP against A. flavus spores, which establishes a basis for the application of DBD-CP in controlling pathogenic fungi contamination in grains and crops, promoting the development of DBD-CP in food and agricultural decontamination.

Spores, Fungal↗

PubMed2026

Chlorfenapyr-pyrethroid nets for pyrethroid-resistant malaria vectors: efficacy, resistance risks, and policy implications.

The Global Technical Strategy for Malaria 2016-2030 aims to reduce malaria incidence and mortality by 90%, yet widespread pyrethroid resistance among major malaria vectors in sub-Saharan Africa threatens this goal. Thus, the World Health Organization recommends chlorfenapyr-pyrethroid combination nets as a priority intervention where pyrethroid resistance undermines vector control. This systematic review synthesizes evidence on the performance, emerging resistance risks, and policy implications of these next-generation insecticide-treated nets. A structured search of literature from 2010 to 2024 across PubMed, Embase, WHO IRIS, and Google Scholar identified 31 eligible studies from 113 records. Evidence shows that chlorfenapyr-pyrethroid nets consistently outperform pyrethroid-only nets against resistant Anopheles populations, demonstrating a 1.8-fold increase in mosquito mortality (95% CI: 1.5-2.1). Community trials report 40-60% reductions in malaria infection incidence and entomological inoculation rates following deployment. However, early signs of chlorfenapyr resistance have emerged in Anopheles gambiae populations in Central Africa (RR: 2.4, p = 0.01), linked to CYP6P4 metabolic overexpression. A significant correlation was also observed between agricultural pesticide use and vector resistance patterns (r = 0.62, p < 0.05). Although chlorfenapyr-pyrethroid nets provide an important short-term tool for managing pyrethroid resistance, their long-term effectiveness depends on integrated resistance management. Rotational deployment with other insecticide classes, strengthened genetic and phenotypic surveillance, and a coordinated 'One Health' approach involving both public health and agriculture are essential to sustain gains and advance progress toward the 2030 malaria targets.

Pyrethrins↗

PubMed2026

Nourishing collaboration: interdisciplinary nutrition education for health care professionals.

Nutrition education remains insufficient in many health care professional training programs despite the central role of diet in the prevention and management of chronic disease. Contemporary nutrition science increasingly recognizes that dietary behaviors and health outcomes are shaped by complex interactions among biological, behavioral, environmental, and food system factors. This perspective proposes an interdisciplinary framework for nutrition education that integrates the complementary expertise of physicians, dietitians, chefs, and farmers. By bridging clinical care, nutrition science, culinary practice, and agricultural systems, such an approach may strengthen the translation of evidence into practice, improve nutrition-related competencies among health care professionals, and ultimately enhance population health outcomes.

Humans↗

PubMed2026

ZrO₂@C-based colorimetric/photothermal dual-mode immunosensor coupled with a novel monoclonal antibody for quantification of Aspergillus ochraceus biomass.

Aspergillus ochraceus contaminates agricultural products and produces nephrotoxic, carcinogenic ochratoxin A (OTA), posing severe food safety hazards. A dual-signal lateral flow immunochromatographic assay (dLFIA) based on ZrO₂@C nanoprobes was established for quantitative detection of A. ochraceus biomass. A novel monoclonal antibody (mAb 4B4) was prepared as the capture antibody to immobilize A. ochraceus mycelial lysate antigen on the test line, and a rabbit polyclonal antibody (pAb G2801) as the detection antibody to modify ZrO₂@C composites (synthesized via UiO-66 pyrolysis) into 200 nm colorimetric/photothermal nanoprobes. This dLFIA achieved limits of detection of 0.164 μg/mL (colorimetric) and 0.517 μg/mL (photothermal). This efficient and reliable method allows quantitative analysis of A. ochraceus biomass, which is suitable for routine monitoring of fungal contamination in agro-food matrices.

Antibodies, Monoclonal↗

PubMed2026

New World screwworm: a re-emerging parasitic threat.

PURPOSE OF REVIEW: New World screwworm (NWS) is an emerging parasitic threat in Central America and Mexico, which is spreading northward into the southern United States. Here we highlight the changing epidemiology, lifecycle of the NWS fly, clinical presentation, identification, treatment, and potential complications of NWS myiasis. RECENT FINDINGS: Despite decades of successfully containing NWS flies south of the Darien Gap in southern Panama, NWS flies reemerged in the Central America region in 2023 and have continued to spread northward ever since. On 3 June 2026, United States Department of Agriculture (USDA) confirmed the identification of an NWS infestation in a young calf in southern Texas. In addition to describing the current epidemiology of the NWS outbreak, we present information about clinical presentation and management of NWS myiasis in patients and include representative cases of patients who experienced NWS myiasis. SUMMARY: This review provides important epidemiologic and clinical updates to an emerging parasitic threat so clinicians can understand the risks and clinical management for patients with suspected NWS myiasis.

Animals↗

PubMed2026

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves↗

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

Bacterially produced dsRNA targeting SePGRP-LB reduces population fitness of Spodoptera exigua (Lepidoptera: Noctuidae) and increases its susceptibility to SeMNPV.

The beet armyworm, Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae), is an important agricultural pest, and S. exigua multiple nucleopolyhedrovirus (SeMNPV) is a host-specific biological control agent. However, baculovirus efficacy can be limited by host antiviral responses. S. exigua peptidoglycan recognition protein LB (SePGRP-LB) has been identified as an antiviral immune factor, suggesting that its suppression may increase larval susceptibility to SeMNPV. In this study, bacterially produced double-stranded RNA targeting SePGRP-LB (bac-dsPGRP-LB) was orally delivered to larvae to induce RNA interference. Feeding bac-dsPGRP-LB reduced SePGRP-LB transcript levels by 24.0% to 65.7% over 7 d. SePGRP-LB knockdown prolonged fifth-instar larval development, reduced female pupal weight, shortened male adult longevity and the oviposition period, and decreased fecundity by approximately 51%. Life table analysis further showed significant reductions in the intrinsic rate of increase (r), finite rate of increase (λ), and net reproductive rate (R0) following bac-dsPGRP-LB treatment. During SeMNPV infection, co-feeding with bac-dsPGRP-LB significantly suppressed SePGRP-LB expression, increased the SeMNPV genomic load, and reduced larval survival compared with the SeMNPV + bac-dsGFP treatment. These findings identify SePGRP-LB as a promising RNAi target for simultaneously reducing S. exigua fitness and enhancing its susceptibility to SeMNPV under laboratory conditions.

SePGRP-LB↗

PubMed2026

Genome-wide identification and expression profiling of CSP and OBP genes in Stictocephala bisonia reveals candidate genes potentially associated with insecticide response.

Stictocephala bisonia is an important invasive agricultural pest. Due to the frequent application of insecticides in its habitat, this species is under intense selection pressure. Chemosensory proteins (CSPs) and odorant-binding proteins (OBPs) are known to play key roles in insecticide resistance, but their specific functions in S. bisonia remain unclear. In this study, we identified a total of 22 SbisCSPs and 16 SbisOBPs based on the S. bisonia genome. To screen for candidate genes potentially linked to insecticide resistance, we adopted a multi-criteria screening strategy that integrated phylogenetic analysis, molecular docking with three insecticides, and tissue-specific expression profiling. Phylogenetic analysis identified several SbisCSPs and SbisOBPs clustering with genes known to be involved in insecticide resistance, serving as an initial evolutionary filter. Molecular docking results indicated that λ-Cyhalothrin exhibited the strong predicted binding affinity with most of SbisCSPs and SbisOBPs. Subsequent qPCR validation of seven prioritized candidates revealed distinct expression patterns: SbisCSP22 was highly expressed in adults and demonstrated strong binding affinity to all three insecticides tested, suggesting a potential role in mediating multi-insecticide response. Conversely, SbisCSP17 was significantly upregulated in larvae, clustered with genes known to mediate imidacloprid resistance, and exhibited strong binding affinity to imidacloprid. Given its larval-specific expression and the soil-dwelling behavior of larvae, we hypothesize that SbisCSP17 is a key candidate gene for larvae coping with soil-treated insecticides.

Animals↗

PubMed2026

Sex- and development-specific transcriptomic profiling of venom and silk genes in the wolf spider Pardosa astrigera provides insights into ecological adaptation and predatory strategies.

Spider venom and silk glands are two major secretory systems that contribute to prey capture, defense, and reproduction, but their sex- and development-specific molecular regulation in wandering wolf spiders remains poorly understood. Here, the transcriptome of Pardosa astrigera, an important agricultural natural enemy in China, revealed significant sex- and development-associated molecular differentiation among adult females, adult males, and spiderlings. A total of 100,025 unigenes were obtained, of which 23,852 were functionally annotated, providing a comprehensive transcriptomic resource for this species. Differential expression patterns showed marked variation among groups, with 531, 1792, and 832 DEGs detected in PAF vs PAS, PAM vs PAS, and PAF vs PAM, respectively. These genes were mainly associated with metabolic, oxidation-reduction, cuticle development, MAPK signaling, and lysosome pathways. Fifteen co-expression modules revealed distinct expression patterns. The turquoise, pink, yellow, and red modules were development-related, whereas the blue module was male-biased. Venom- and spidroin-related genes were distributed across multiple modules, suggesting coordinated regulation. Overall, 42 venom peptides, 21 venom proteins, and 11 spidroins were identified. Representative genes showed strongly biased expression, including spiderling-biased U3_Pp1a and U5_Pp1e, female-biased U4_Pp1a, and male-biased SMase D_108750 and PaTuSp_108466. These findings reveal sex- and development-biased expression patterns of venom- and silk-related candidate genes in P. astrigera and may provide molecular insights into ecological adaptation and predatory strategies in wandering wolf spiders.

Animals↗

PubMed2026

Comprehensive source-risk assessment of organophosphate esters in surface water of the Dianchi Lake Basin, Yunnan, China.

Organophosphate esters (OPEs), widely used as flame retardants and plasticizers, have been increasingly detected in aquatic environments. However, investigations of their distribution in high-altitude plateau lakes remain scarce. Identifying and quantifying the sources and associated risks of OPEs are crucial for subsequent water environment management. In this study, an integrated source-risk analysis approach was employed by combining the Positive Matrix Factorization (PMF) model, the Geodetector (GD) model, and risk quotient (RQ). Analysis of 14 OPEs in surface waters of the Dianchi Lake Basin (DLB) revealed 12 detectable compounds, with total OPEs concentrations (ΣOPEs) ranging from not detected (ND)-64.6 ng/L during the wet season and ND-35.8 ng/L during the dry season. Elevated ΣOPEs were primarily observed at inflow sites in the northern part of the lake and in urban rivers. Source apportionment indicated four major contributing sources: agricultural films containing flame-retardant and plasticizer additives, traffic-related particulate emissions, releases from household and personal care products, and industrial production and applications of flame retardants in plastics, electronics, and related products (the predominant source). The ecological impact caused by OPEs ranges from no risk to low risk, with tris(2-chloroethyl) phosphate emitted from industrial source being the primary driver of potential environmental risk. These findings highlight the necessity of prioritizing industrial sources in future management strategies. Overall, this study provides a methodological framework for source apportionment and risk assessment of OPEs and offers scientific evidence to support environmental management of OPEs in the DLB.

Environmental Monitoring↗

PubMed2025

Influence of soil types with different soil-forming process on the qualitative and quantitative detection of microplastics by near-infrared spectroscopy.

Microplastics (MPs) have become a pressing global environmental threat, with soils-acting as sinks for MPs from multiple sources-gaining increasing attention. Near-infrared (NIR) spectroscopy offers a promising tool for MPs detection due to its rapid, non-destructive, and field-applicable features. Although previous studies have focused on the effects of individual soil components on the NIR detection performance of MPs, there is still a lack of systematic research on how the complex background-formed by the coupling of multiple physicochemical properties in natural soils-affects detection performance. This study focuses on soil types with different soil-forming processes, selected five representative agricultural soils to systematically evaluate how the combinations of physicochemical properties they represented affect the performance of NIR-based qualitative and quantitative analysis of MPs in soils. The results demonstrated that soil type significantly affected both the spectral response and detection performance of MPs. Brown Pedocals and Brown Earth exhibited clearer characteristic absorption and stronger linear responses, achieving higher identification accuracy under low (<1.5 %) or zero MPs concentrations and the best quantitative performance (R2 ≥ 0.988, prediction set root mean square error (RMSEP) ≤ 0.110 %). In contrast, Phaeozem and Red Soil were more prone to misclassification at low concentrations, while Fluvo-aquic Soil showed the poorest quantitative performance. This study is the first to reveal, at a holistic level, the critical constraints posed by natural soil complexity on the NIR detection of MPs, offering targeted empirical evidence to support the application of NIR technology in real-world soil environments.

Soil↗

PubMed2026

Global Patterns of Net Ecosystem Exchange in peatlands: A Systematic Review and Meta-analysis of Drivers Across Land Use and Environmental Gradients.

Peatlands play an essential role in the global carbon cycle, storing approximately one-third of the world's soil carbon despite covering less than 3% of the land surface. Peatland degradation from anthropogenic activities and climate change can convert peatlands from net carbon sinks to sources by altering carbon cycling. Net Ecosystem Exchange (NEE), the balance between CO2 uptake and emission, is a critical indicator for assessing peatland condition and restoration efforts. We conducted a systematic quantitative literature review to investigate global patterns of NEE in peatlands and identify key environmental and anthropogenic drivers of CO2 flux variability. Annual NEE values from 120 globally distributed sites reported in peer-reviewed literature were analyzed in relation to climatic zone, land use, vegetation type, peatland condition, and water table depth. Our synthesis revealed significant geographic gaps, with peatland NEE studies substantially underrepresented in the Tropics, Africa, and Oceania. Agricultural peatlands emitted significantly more CO2 than sites under natural land uses or peat extraction, while degraded peatlands were significantly greater net CO2 sources than intact and restored systems. Restored peatlands remained net CO2 sources on average, emphasizing the importance of long-term monitoring and adaptive management following restoration interventions. Water table depth significantly affected NEE variability, with CO2 emissions increasing approximately 7.2 gCO2-C m-2yr-1 for every centimeter of water table drawdown. A substantial variability in measurement methods, data processing software, and protocols highlighted the critical need for methodological standardization. Our findings provide evidence-based targets for peatland conservation and restoration monitoring as nature-based climate solutions.

Ecosystem↗

PubMed2026

Genomic and Molecular Interaction Analysis of NodD1 in a Novel Bradyrhizobium yuanmingense sp. B64 Isolate for Nodulation and Symbiosis of Legume Plants.

Rhizobial bacteria are known for their ability to fix nitrogen for leguminous plants and their essential function for sustainable agriculture. This study characterizes the taxonomic status and functional potential of the Bradyrhizobium B64 isolate using integrated genomic and molecular approaches. The whole genome of the B64 isolate was sequenced via Illumina paired-end technology. Species delimitation was performed using average nucleotide identity (ANI) and digital DNA-DNA Hybridization (dDDH). The NodD1 protein structure was modeled using AlphaFold3 and validated by Ramachandran plot analysis. Molecular docking was then conducted to evaluate interactions between NodD1 and four signaling flavonoids: Apigenin, Daidzein, Genistein, and Naringenin. Genomic analysis revealed a maximum ANI of 94.4% and dDDH values between 51.4 and 62.4%. Since these values fall below the standard prokaryotic thresholds (ANI < 95%; dDDH < 70%), the B64 isolate is identified as a novel species. Physiological assays confirmed nitrogen fixation (1.97 ppm), IAA production (3.67 ppm), and phosphate solubilization (26.10 ppm). Structural validation showed 100% of NodD1 residues in allowed regions, ensuring high model reliability. Docking simulations demonstrated strong binding affinities across all flavonoids, with binding free energies ranging from - 8.8 to - 9.0 kcal/mol. Daidzein exhibited the highest thermodynamic stability (- 9.0 kcal/mol), whereas apigenin showed the most extensive residue interaction network. The B64 isolate is a novel Bradyrhizobium species with a high symbiotic capacity. The stable NodD1-flavonoid interactions provide a molecular basis for efficient nodulation, positioning B64 as a promising candidate for developing lipo-chitooligosaccharide (LCO)-based biofertilizers.

Bradyrhizobium↗

PubMed2026

Occupationally relevant vibrations and the brain: frequency-dependent proteomics signatures in a rat model.

INTRODUCTION: Occupational exposure to whole-body vibration (WBV), particularly in agricultural environments, has been associated with adverse cognitive and physiological effects. This study examined the neurophysiological impact of WBV in a rat model at 4 Hz and 30 Hz, frequencies representative of off-road and on-road vehicle operation. METHODOLOGY: Forty-four Sprague-Dawley rats were assigned to control (0 Hz), low-frequency (4 Hz), or high-frequency (30 Hz) vibration conditions. After three days of exposure, brain tissues were collected and analyzed using mass spectrometry-based proteomics to identify differentially expressed proteins. RESULTS: Proteomic profiling revealed distinct, frequency-dependent alterations in brain protein expression. Compared with controls, 32 cognition-related proteins were differentially regulated at 4 Hz and 29 at 30 Hz, with 13 differing between the two vibration conditions. Principal component analysis showed clear separation among groups, indicating unique proteomic signatures for each exposure frequency. Functional enrichment and protein-protein interaction analyses demonstrated involvement of synaptic plasticity, cytoskeletal organization, calcium regulation, and neurotransmitter release. Exposure to 4 Hz was associated with the upregulation of proteins involved in calcium homeostasis and synaptic integrity, suggesting potential disruption of cognitive processes. In contrast, 30 Hz increased the expression of proteins related to axonal guidance and neuroprotection, indicating a less clearly adverse response that may reflect adaptive or potentially beneficial effects. DISCUSSION: These findings provide new insight into biological mechanisms underlying WBV-induced cognitive changes and underscore the importance of vibration frequency in shaping neurophysiological outcomes. They also establish a foundation for future studies integrating proteomics with behavioural assessments in animals and humans.

Animals↗