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PGPR inoculation and growth enhancement of crops cultivated in hydroponic systems.

Plant growth-promoting rhizobacteria (PGPR) are ubiquitous rhizosphere microorganisms that promote plant health through various mechanisms. Although the study of PGPR inoculants in soil has been done for ages, their application in hydroponic systems has received relatively limited attention. This review identifies PGPR inoculants that are commonly used in hydroponics, methods of application, and their effects on plant growth and nutrient use efficiency. Literature shows that PGPR inoculants improve plant performance in controlled hydroponic systems through the production of growth-stimulating substances, nitrogen fixation, and improved nutrient acquisition. However, the plant growth responses are highly variable depending on the composition of nutrient solutions, environmental factors, crop and microbe species, and the type of hydroponic system. The review identifies various challenges of PGPR inoculation in hydroponic systems and future research directions to address the current gaps. Generally, the productivity of hydroponic systems can be enhanced through advanced inoculation strategies and the development of suitable carrier materials to improve inoculant survival, viability, and functions. Emphasis should also be placed on designing system-specific microbial consortia and Synthetic communities that are tailored to the unique ecological conditions of hydroponic systems.

Hydroponics

A smartphone-integrated Pt@Cu-HCF nanozyme-based paper sensor for on-site determination of total antioxidant capacity in marine oils.

Total antioxidant capacity (TAC) serves as a key indicator for evaluating the nutritional quality of foods. In this study, we designed a platinum-embedded copper hexacyanoferrate (denoted as Pt@Cu-HCF) nanozyme that exhibits high oxidase-like activity, efficiently catalyzing the oxidation of chromogenic substrates to generate robust colorimetric signals. Antioxidants quench hydroxyl radicals (∙OH) produced during the catalytic process, leading to a concentration-dependent suppression of the color signal. Leveraging this mechanism, a smartphone-integrated, colorimetric paper sensor for on-site TAC quantification was developed, using vitamin E as the calibration standard. The sensor was applied to determine TAC in fish oil, algal oil, and krill oil, demonstrating a linear response range of 9.78-312.5 μM and a limit of detection (LOD) of 6.41 μM. Validation using real-world marine oil samples showed excellent agreement with a commercial assay kit, confirming the reliability and practical applicability of this portable sensor for TAC measurement in complex biological matrices.

Antioxidants

A MIL-88@Ru-based molecularly imprinted electrochemiluminescence sensor for highly selective and sensitive detection of enrofloxacin residues in animal-derived foods.

Using a metal-organic framework (MOF) - supported Ru(bpy)32+ (MIL-88@Ru) composite luminescent material, this study innovatively adopted electropolymerization to fabricate a molecularly imprinted polymer-based electrochemiluminescent (MIP-ECL) sensor for enrofloxacin (ENR) detection in animal-derived foods. Systematic investigation of the ECL luminescence and ENR's quenching mechanism confirmed that the sensor integrates ECL's high sensitivity and MIP's high specificity, enabling rapid and accurate recognition of ENR. Experimental results show a good linear response in the range of 1 nmol/L-20 μmol/L (R2 = 0.99), a limit of detection (LOD) as low as 0.28 nmol/L, as well as excellent selectivity and stability. Recoveries of ENR in all investigated matrices ranged from 97.7% to 106.4%, confirming the reliability of the established method. This ECL-MIP coupling strategy provides a new technical approach and application references for the efficient detection of trace pollutants in food safety and environmental monitoring fields.

Enrofloxacin

Deciphering CD8+ T cell exhaustion in human cancers through single-cell and spatial transcriptomics.

Exhausted CD8+ T cells (Tex) within the tumor microenvironment (TME) represents a critical barrier limiting anti-tumor immune responses. Tex cells are characterized by upregulated inhibitory immune checkpoint receptors, reduced cytotoxicity, and functional heterogeneity. Their genomic features and regulatory networks remain poorly defined, and only a minority of patients respond to immune checkpoint blockade (ICB) therapy. Single-cell RNA sequencing (scRNA-seq), through high-resolution transcriptomic profiling, has revealed diverse Tex subpopulations, identified subpopulation-specific marker genes and regulatory pathways. Spatial transcriptomics has further mapped the spatial distribution of Tex and their interaction networks with immune cells, tumor cells, and stromal cells, elucidating the impact of spatial heterogeneity on Tex functionality. Current studies indicate that the exhausted state of Tex is dynamic and modifiable, with functional differences among subpopulations closely associated with tumor progression and therapeutic response. However, the genomic characteristics, epigenetic regulation, and spatial interaction mechanisms of Tex require further exploration. This review summarizes recent advances in high-resolution omics technologies for precisely dissecting Tex heterogeneity, functional features, and interactions with other cells. It emphasizes the central value of optimizing Tex-targeted tumor immunotherapy strategies, providing theoretical foundations and directional guidance for developing more effective anti-tumor immunotherapies.

Humans

Morphology-Encoded Colorimetric Hydrogen Sensing Using Embedded Reactive Pd Absorbers in Fabry-Perot Cavities.

Chemical reactions offer a powerful strategy for generating visible optical responses through localized changes in absorption, dielectric environment, and interfacial wetting. A palladium (Pd)-embedded Fabry-Perot cavity is introduced as a reaction-active optical platform in which structural color is governed by intracavity absorption coupled with reaction-induced dielectric perturbation. Positioning Pd within the dielectric spacer creates a spatially controllable reactive absorber whose vertical location relative to the standing-wave field dictates wavelength-selective absorption within the cavity. The morphology of the embedded Pd layer provides an additional design parameter by modulating both optical loss and interfacial wetting. Under hydrogen exposure in the presence of oxygen, catalytic water formation at the Pd/polymer interface generates localized dielectric heterogeneity and interfacial water droplets, thereby perturbing the optical path length and amplifying the visible response. As a result, the cavity exhibits pronounced, morphology-dependent color transitions that are inaccessible through dielectric-layer engineering or Pd/PdH refractive-index changes alone, enabling direct visual hydrogen sensing under ambient light, as well as flexible optical devices capable of large-area patterning. These findings establish a design framework for reaction-active optical cavities that translate localized chemistry into a colorimetric hydrogen sensing mechanism.

Fabry–Perot resonator

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics

Mitochondrial translocation of DNMT3L suppresses oxidative phosphorylation and restrains megakaryopoiesis.

DNMT3L, a catalytically inactive member of the DNA methyltransferase family, is identified here as a negative regulator of megakaryopoiesis. In K562 cells undergoing PMA-induced megakaryocytic differentiation, DNMT3L protein levels declined progressively, and shRNA-mediated depletion enhanced differentiation, whereas overexpression attenuated it. Consistent with these findings, Dnmt3l-knockout mice exhibited elevated peripheral blood platelet counts and expanded bone marrow megakaryocytes. Mechanistically, megakaryocytic differentiation triggered rapid mitochondrial translocation of DNMT3L within 6 h; mitochondrial DNMT3L suppressed oxidative phosphorylation (OXPHOS) capacity and ATP production and downregulated mitochondrial-encoded genes spanning Complex I, III, IV, and ATP synthase, without altering mitochondrial DNA copy number. This metabolic suppression was mediated through compartment-specific remodeling of DNMT3L-containing protein complexes: upon differentiation, DNMT3L selectively dissociated from DNMT1 and DNMT3B in mitochondria, relieving the repressive constraint on OXPHOS, whereas in the nucleus DNMT3L remained associated with DNMT3A, which concomitantly accumulated during differentiation. These findings reveal a previously unrecognized mechanism by which a catalytically inactive epigenetic co-regulator spatially redistributes to coordinate mitochondrial metabolic output with nuclear epigenetic control, thereby facilitating terminal megakaryocytic maturation.

Animals

Colchicine attenuates cardiac hypertrophy by targeting the macrophage-driven Interleukin-6 suppression.

Hypertrophic cardiomyopathy (HCM), the most prevalent inherited cardiovascular disease, is strongly linked to progressive heart failure and sudden cardiac death (SCD). However, its underlying pathogenic mechanisms remain incompletely understood, and effective therapeutic strategies are still lacking. Here, we established two murine HCM models harboring high SCD risk-associated mutations. Single-cell RNA sequencing revealed immune activation and enhanced fibrotic remodeling in the myocardium of these models. Therefore, we hypothesized that colchicine, a widely used anti-inflammatory drug known to reduce cardiovascular events in multiple cardiac disorders, may also represent a promising therapeutic candidate for HCM. As we expected, colchicine treatment attenuated pathological remodeling in our study, as evidenced by reduced cardiomyocyte hypertrophy, decreased fibrosis, and downregulation of cardiac stress markers (Anp, Bnp) and fibrotic mediators (Ctgf, Col1a1, Col3a1). In addition, colchicine attenuated pro-inflammatory macrophage populations and suppressed IL-6 expression, thereby contributing to the preservation of cardiac function. These findings provide the first preclinical evidence that colchicine alleviates myocardial inflammation and fibrosis in HCM, underscoring its potential as a novel therapeutic strategy to reduce fibrosis, lower SCD risk, and improve patient outcomes.

Animals

Review: The African turquoise killifish as a model for the integrative physiology of vertebrate aging.

With increasing emphasis on extending healthy lifespan, aging research requires vertebrate models that permit efficient mechanistic investigation and intervention testing within practical time and cost constraints. The African turquoise killifish (Nothobranchius furzeri) has attracted growing attention because it combines an exceptionally short life cycle with an intact vertebrate physiological context and an expanding genetic toolkit, enabling relatively rapid evaluation of candidate aging interventions and mechanistic analysis across molecular, tissue, and organismal levels. This review assesses N. furzeri from an integrative-physiology perspective, focusing on germline-soma interactions, gut microbiota-host crosstalk, nutrient sensing and metabolic remodeling, temperature responsiveness, and AMPK-mTOR-linked programs. It also examines expanding genome-engineering and reporter approaches that support mechanistic and tissue-resolved investigation of these physiological processes. Building on recent reviews of killifish biology, disease modeling, regeneration, and the hallmarks of aging, we synthesize evidence across major intervention domains, distinguish established phenotypic effects from incompletely resolved mechanisms, and highlight functional endpoints, methodological standardization, and the appropriate interpretation of the model's translational relevance. Together, these features position N. furzeri as a strategically useful vertebrate platform for rapid mechanistic testing, intervention evaluation, and prioritization of aging-related pathways. Future progress will require improved methodological standardization, tissue-resolved causal studies, and question-driven cross-species validation where appropriate.

Animals

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype

Advanced mitigation strategies for acrylamide formation in foods: Mechanistic insights, emerging innovations, and future perspectives.

Acrylamide is a heat-induced contaminant formed predominantly in carbohydrate-rich foods during high-temperature processing, posing significant concerns due to its potential carcinogenic, neurotoxic, and genotoxic effects. This review critically examines the mechanisms of acrylamide formation, emphasizing the role of the Maillard reaction and key precursors such as asparagine and reducing sugars, along with the influence of processing conditions including temperature, time, pH, and moisture. Various mitigation strategies are comprehensively discussed, ranging from raw material selection and genetic approaches to enzymatic treatments such as asparaginase and the application of natural and chemical inhibitors. Advances in processing technologies, including optimization of conventional thermal methods and emerging non-thermal techniques such as cold plasma and ultrasound, are evaluated for their effectiveness. The review also highlights the role of food additives, functional ingredients, and fermentation in reducing acrylamide formation. Furthermore, recent developments in analytical techniques, including chromatographic methods, biosensors, and artificial intelligence-based predictive models, are explored for improved detection and control. Risk assessment, toxicological implications, and global regulatory frameworks are also examined. Finally, future perspectives focusing on genetic engineering, personalized nutrition, and digital technologies such as AI and blockchain are discussed to support sustainable and industry-applicable mitigation strategies.

Acrylamide

Electroencephalographic evidence of cortical network disruption preceding overt cardioinhibition during tilt-induced reflex syncope.

OBJECTIVE: Reflex syncope is a common cause of transient loss of consciousness. However, the early cerebral mechanisms underlying cardiovascular changes remain poorly understood. Our objective was to investigate early cerebral changes by quantitatively analyzing EEG activity preceding overt cardioinhibition during tilt-induced reflex syncope. METHODS: EEG recordings from patients undergoing tilt testing were retrospectively analyzed. Patients who experienced reflex syncope were compared to those who did not. Spectral and functional connectivity analyses were performed across baseline, pre-cardioinhibition, and syncopal phases. RESULTS: Prior to the onset of cardioinhibitory pathological reflex, a significant increase in theta-band spectral power was observed in the right temporal region, accompanied by a widespread increase in functional connectivity within the same frequency band. These findings suggest the involvement of brain networks before cardioinhibition. CONCLUSIONS: EEG changes in the theta band (power and functional connectivity) were observed before overt cardioinhibition during tilt-induced reflex syncope. SIGNIFICANCE: Our findings support the hypothesis of cortical processing preceding cardioinhibition in reflex syncope. EEG may represent a valuable complementary tool for improving the understanding and diagnosis of these events.

Humans

Ramu stunt virus genome reveals previously unreported segments and nucleocapsid domain duplication in Mechlorovirus.

Ramu stunt virus (RmSV), a member of the genus Mechlorovirus within the family Phenuiviridae, was previously described as a six-segmented RNA virus infecting sugarcane. In this study, we re-examined type material and additional isolates using high-throughput sequencing and RT-PCR validation, revealing that RmSV possesses a nine-segmented genome, making it the largest reported in the Phenuiviridae. This expanded architecture includes duplicated RNA segments (RNA 2a and RNA 2b) encoding nucleocapsid-like proteins and two novel segments (RNA 7 and RNA 8). Comparative analysis showed that RNA 2a and 2b share about 84% amino acid identity, while RNA 5 encodes a third nucleocapsid homolog, indicating unprecedented domain redundancy. Structural modeling confirmed that all three nucleocapsid proteins maintain a conserved fold despite low sequence identity, with electrostatic mapping suggesting differential RNA-binding potential. Additionally, RNA 6 encodes a hypothetical protein structurally similar to the rice stripe virus disease-specific S-protein, implicating a role in symptom development. Transcript abundance analysis revealed RNA 6 as the most highly expressed segment across isolates. These findings revise the genomic composition of RmSV, highlight mechanisms of genome plasticity and adaptive evolution in plant-infecting bunyaviruses, and underscore practical implications for diagnostic assay design, resistance breeding, and biosecurity surveillance.

Genome, Viral

Recent advances in electrode materials for electrochemical detection of zearalenone.

Zearalenone (ZEN) is an estrogenic mycotoxin commonly found in cereals, animal feed, and processed foods, making it an important concern for food safety and public health. Conventional chromatographic and immunological methods can detect ZEN; however, they often require expensive instruments, lengthy sample preparation, and skilled personnel, which restrict their use for rapid and on-site testing. Electrochemical sensors have attracted enormous interest of the scientific community because of their high sensitivity, rapid response, low cost, miniaturization potential, and compatibility with portable systems. The analytical performance of the electrochemical sensors is strongly influenced by electrode materials, morphology, conductivity, porosity, surface functionality, and the efficiency of bioreceptor immobilization. Despite several reviews on mycotoxin detection, a systematic assessment connecting electrode-material design, modification strategies, sensing mechanisms, and electroanalytical performance specifically for ZEN sensing remain limited. This review critically evaluates recent advances in metal oxides, carbon-based materials, metal-organic- and covalent organic frameworks, MXenes, polymers, and hybrid composites for electrochemical ZEN detection. Particular attention has been given to their roles in electron transfer, analyte enrichment, selectivity, and real-sample analysis. The review also compares the major limitations of current sensing systems, including complex fabrication, matrix interference, insufficient long-term stability, poor inter-electrode reproducibility, and limited scalability. Finally, future directions for developing robust, cost-effective, portable, and commercially viable ZEN sensors are discussed.

Journal Article

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans

CNNM2 in schizophrenia: multilevel evidence of genetic susceptibility, magnesium homeostasis, neurodevelopment and cognitive dysfunction.

Schizophrenia (SCZ) is a common psychiatric disorder with a complex, genetically and environmentally influenced etiology, but the specific pathogenesis remains unclear. In recent years, the SCZ susceptibility gene CNNM2 (encoding cyclin M2) located at the 10q24.32-33 locus has received widespread attention. The well-validated SCZ risk interval 10q24.32-33 harbors two independent risk variants: rs11191580 in NT5C2 (significantly associated with CNNM2 mRNA and protein levels) and rs7914558 in CNNM2. Results from functional genomic analyses indicate that lower CNNM2 expression is significantly associated with SCZ. Imaging genetics studies have demonstrated that carriers of risk alleles of CNNM2 SNPs exhibit alterations in brain structure. Animal model studies have revealed that Cnnm2 downregulation in mice leads to impairments in sensorimotor gating and cognitive function. As an Mg2+ transporter, CNNM2 primarily maintains systemic Mg2+ homeostasis. According to clinical studies, a proportion of patients with SCZ exhibit reduced Mg2+ concentrations in plasma and cerebrospinal fluid. CNNM2 dysfunction may contribute to the pathology of SCZ by disrupting Mg2+ homeostasis, thereby affecting neurodevelopment and synaptic plasticity. A systematic consolidation of current evidence supporting the involvement of CNNM2 in SCZ pathogenesis provides a direction for further investigation of the pathological mechanisms underlying this disease, and for identification of novel targets for clinical intervention..

Schizophrenia

All-inside repair is an effective treatment for medial meniscus posterior root tears: a systematic review and meta-analysis of biomechanical and clinical evidence.

BACKGROUND: Medial meniscus posterior root tears (MMPRTs) reproduce the biomechanics of subtotal meniscectomy. Repair is favored, but the role of all-inside repair (AR) remains unclear relative to transtibial pull-out (TP). This study aimed to review the biomechanical and clinical evidence on AR for MMPRTs. METHODS: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and registered in the International Prospective Register of Systematic Reviews (PROSPERO). MEDLINE, Embase, Scopus, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched. Outcomes included patient-reported outcome measures (PROMs), magnetic resonance imaging (MRI), and biomechanical performance. When available, random-effects meta-analysis was performed. RESULTS: Thirteen studies were included. AR restored contact mechanics and showed load to failure comparable to TP, with lower stiffness. Meta-analysis showed lower conversion to total knee arthroplasty with AR versus non-repair (RR 0.18, 95% CI 0.05-0.58), and no significant PROM differences between AR and TP. CONCLUSIONS: AR showed favorable biomechanical properties and improved outcomes versus non-repair. Compared with TP, no significant clinical differences were observed. AR may represent a reasonable option in selected scenarios.

Humans

CNOT1 is a potential YTHDF2 target that orchestrates maternal mRNA decay and zygotic genome activation during goat embryogenesis.

Timely and efficient degradation of maternal mRNA is essential for early embryonic development, which occurs from fertilization through the initiation of zygotic genome activation (ZGA). Yet, the regulatory mechanisms governing this process remain poorly characterized. In the present study, we investigated the function of CCR4-NOT transcription complex subunit 1 (CNOT1) during goat embryogenesis. We found that CNOT1 was upregulated during mammalian ZGA, and that its knockdown led to developmental arrest and a marked reduction in blastocyst formation. Moreover, CNOT1 knockdown impaired nascent RNA activity, resulting in 814 upregulated and 1014 downregulated genes, which were enriched for RNA splicing, regulation of chromosome organization, and RNA localization. RNA splicing analysis revealed differential splicing events in 2959 genes, of which 259 were downregulated following CNOT1 knockdown. Notably, CNOT1 was predicted to crosstalk with the m6A reader YTHDF2. Knockdown of YTHDF2 resulted in CNOT1 downregulation at the 8-cell stage in goats and increased transcription levels around polyadenylation sites during ZGA in mice. Together, these findings indicate that CNOT1 is a potential YTHDF2 target that orchestrates maternal mRNA decay and ZGA during goat embryogenesis. Our work provides new insight into the complex regulatory landscape underlying ZGA and may inform strategies to improve the efficiency of goat embryogenesis.

Animals