This study addresses the resource waste and environmental pollution resulting from the conventional disposal of waste Chinese medicine residues (WCMRs) and examines the feasibility of high-value resource recovery using pyrolysis technology. Products obtained through oxygen-constrained pyrolysis of underground (UM) and above-ground (GM) biomass were compared systematically, and a catalyst, CaO, was added to enhance the production of syngas. Several characterization methods and batch adsorption experiments were used to comprehensively assess the performance and composition of the three-phase products. The results revealed that biochar produced at 700 °C (UMB-700 °C) had a high specific surface area of 184.78 m[2]·g[-1] and an ammonium nitrogen theoretical maximum adsorption capacity of 38.93 mg·g[-1], and that the predominant adsorption pathway was physical adsorption, which indicates its potential as a slow nitrogen fertilizer carrier. The bio-oils of both kinds of WCMRs contained high-value products, including levoglucosan, phenols, and fatty acids, with UM-based bio-oil having a higher suitability for use as a biodiesel precursor, and GM-based bio-oil having fine chemical extraction advantages. The catalysis process of CaO greatly enhanced the level of light gas constituents in the UM-derived syngas, enhancing the quality of the gas produced. This study demonstrates the regulatory impacts of various components of WCMRs on the characteristics of pyrolysis products, which offers a "one-stone, three-birds" green technology pathway to the high-value use of WCMRs and potential agricultural applications.

In many plant species, guard cells retain their distinctive morphology and physiological function for extended periods after differentiation and maturation. How this terminally differentiated state is actively maintained over time is not fully understood, but recent studies have begun to reveal the underlying mechanisms. Elucidating the underlying mechanisms in Arabidopsis guard cells may provide valuable insights into the maintenance of differentiated identities in other plant cell types. In this review, we synthesize recent findings showing that guard cell identity is secured by two interconnected layers: PRC2-mediated H3K27me3 deposition silences stomatal stem cell genes, while sustained expression of FAMA, supported by SWI/SNF and HAC1-dependent chromatin remodeling, reinforces the mature transcriptional program. Permanent cell cycle exit may serve as an additional safeguard against dedifferentiation, as aberrant cell cycle reactivation triggers fate resetting. This framework highlights the combined action of two interconnected layers: repression of stomatal stem cell genes, coupled with sustained expression of the mature transcriptional program, with cell cycle exit providing additional protection. Such a framework may serve as a useful reference for studying terminal differentiation maintenance in guard cells and other post-mitotic cell types.

Fasting-induced molting is widely employed in the poultry industry to rejuvenate the reproductive system of aging laying hens, thereby improving post-molt laying performance and extending productive lifespan. However, substantial individual variation in post-molt reproductive recovery may compromise the overall effectiveness of molting programs. Elucidating the molecular basis underlying this variation is therefore important for poultry production and genetic improvement. In this study, laying hens were classified into high-recovery (HR) and low-recovery (LR) groups according to their egg production recovery following fasting-induced molting. Transcriptomic profiling of the hypothalamus, pituitary, ovary, and liver was performed using RNA sequencing (RNA-seq). A total of 271, 435, 3,425, and 289 differentially expressed genes (DEGs) were identified between the HR and LR groups in the hypothalamus, pituitary, ovary, and liver, respectively. Functional enrichment analysis showed that these DEGs were primarily associated with protein homeostasis, hormone response, ribosome function, and immune regulation, indicating distinct tissue-specific biological functions during post-molt recovery. Integration of weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis further identified HSP90AA1, GDF7, CTSS, and STS as candidate hub genes associated with post-molt reproductive recovery. Collectively, this study provides a comprehensive multi-tissue transcriptomic landscape of post-molt egg production recovery and identifies key biological processes and candidate genes potentially involved in this process. These findings improve our understanding of the molecular mechanisms underlying post-molt reproductive recovery and provide valuable genetic resources for the genetic improvement of laying hens with superior post-molt performance.

Plants must continuously adapt to complex dynamic environmental conditions throughout their entire life cycle. Abiotic stresses, such as drought, salinity, heavy metal toxicity, extreme temperatures significantly impair plant growth and cause substantial reductions in crop yield. Iron (Fe), an essential micronutrient, serves as a cofactor for numerous metalloenzymes and a critical component of the mitochondrial and chloroplast electron transport chains. It plays an indispensable role in fundamental physiological processes such as photosynthesis, respiration, antioxidant defense, and nitrogen metabolism. However, abiotic stress frequently disrupts iron homeostasis in plants, resulting in either iron deficiency or toxic accumulation, a dual imbalance that compromises cellular function. Such dysregulation exacerbates oxidative damage via Fenton chemistry and severely inhibits growth and development by impairing photosynthetic efficiency and enzymatic activity. Emerging evidence indicates that iron acts not merely as a nutritional element but also as a key modulator of intracellular signaling, metabolic reprogramming, and ion homeostasis, thereby contributing critically to abiotic stress resilience. This review comprehensively synthesizes current understanding of iron's regulatory roles in plant responses to major abiotic stresses, with particular emphasis on the crosstalk between iron homeostasis networks and stress activated signaling pathways. We further elucidate how perturbations in iron homeostasis exert bidirectional effects on stress tolerance, both sensitizing and, under certain contexts, potentiating adaptive responses, thereby offering conceptual and mechanistic insights to advance research on the integration of iron nutrition and stress adaptation, and to inform strategies for enhancing crop resilience.

The aquatic products industry has experienced rapid development due to the growing global demand for high-quality proteins. However, conventional production models remain constrained by multifaceted impediments, including disease outbreaks, environmental stressors, microbial contamination, and operational inefficiencies in processing, quality control, and logistics. Artificial intelligence (AI) offers targeted methodological solutions to these challenges. From a functional perspective, this review categorizes artificial intelligence into four major types: perception, prediction, control, and generation, and systematically evaluates its application progress in aquaculture, processing, quality inspection, and traceability fields. Perception AI constitutes the data acquisition and digitization layer, utilizing computer vision, sonar, and multimodal fusion technologies to establish digital mappings from environmental parameters to biological indicators. Prediction AI employs machine learning and deep learning algorithms to transform historical datasets into quantitative forecasts regarding water quality dynamics, disease risks, and production trends. Control AI translates decision-making protocols into precise, autonomous regulatory actions for aquaculture environments and processing workflows through fuzzy logic and model-based predictive control. Generation AI leverages large language models and generative adversarial networks to demonstrate innovative capabilities in data augmentation, solution optimization, and virtual simulation. Collectively, these applications optimize core production processes while significantly enhancing product quality, processing efficiency, safety management, and traceability systems. Future research directions will prioritize the development of robust, interdisciplinary AI technologies with superior integration capabilities.

Diapause serves as an adaptive dormancy strategy in freshwater, hypersaline, and marine crustaceans, allowing them to survive harsh conditions like temperature extremes, salinity fluctuations, hypoxia, and food scarcity. This review focuses on diapause across major crustacean taxa, with particular emphasis on branchiopods and copepods. However, detailed mechanistic evidence is more prevalent in well-studied species like Artemia, Daphnia, and calanoid copepods, leading to an uneven distribution of evidence across these taxa. Thus, the molecular and physiological mechanisms discussed in this review should not be assumed to be universally conserved across Crustacea, and taxon-specific differences and current knowledge gaps are highlighted where appropriate. The review consolidates the current understanding of crustacean diapause, focusing on environmental cues, gene-regulatory networks, hormonal and epigenetic control, metabolic suppression, and stress resilience. In the best-studied taxa, diapause has been associated with changes in the expression and/or activity of antioxidant defenses, small RNAs, energy-storage pathways, heat shock proteins, and FoxO-associated signaling components; however, the evidence for these mechanisms varies among taxa, and their conservation across Crustacea, remains uncertain. The functions of these responses include developmental arrest, energy conservation, cellular protection, and maintaining viability during dormancy. Their significance varies among different groups of organisms and remains incompletely understood in many cases. Diapause also contributes to the persistence of populations by forming dormant propagule banks, coordinating seasonal processes, linking trophic levels, and increasing resilience to environmental changes. The ecological effects of diapause depend on the life stage and habitat. Recent progress in transcriptomics, epigenomics, long-read sequencing, single-cell methodologies, and multi-omics integration present new opportunities for comparing regulatory responses across species. Molecular data primarily focuses on Artemia, Daphnia, and a limited number of copepod species, posing challenges in generalizing to less represented lineages. Previous syntheses have concentrated on individual taxa, physiological dormancy, or specific molecular mechanisms. This review aims to fill this gap by integrating environmental regulation, taxonomic and life-stage contexts, molecular and physiological mechanisms, and ecological and evolutionary implications systematically. This comparative approach distinguishes between shared regulatory features across species and lineage-specific characteristics, while considering variations in the strength of supporting evidence. Future research should prioritize functional validation, broader taxonomic inclusivity, comparative multi-species analyses, multifactorial experiments, and long-term ecological investigations to enhance understanding of crustacean diapause evolution and refine predictions amidst climate-induced environmental shifts.

To investigate the age-related anatomical, structural, and functional changes occurring in the human nose, and to evaluate the most effective surgical techniques utilized for structural rejuvenation and airway restoration in older patients. A comprehensive narrative literature review was conducted utilizing established scientific databases, including PubMed/Medline, Scopus, Web of Science, and Embase, covering articles published up to 2024. A structured search strategy was applied using keywords such as "aging nose," "rhinoplasty," "tip ptosis," "nasal valve collapse," and "nasal cartilages." Peer-reviewed clinical trials, anatomical evaluations, and authoritative surgical guidelines were included to synthesize the current evidence regarding morphological age-related changes and the efficacy of structural surgical techniques in older patients. The aging process fundamentally alters nasal morphology, primarily resulting in tip ptosis, dorsal pseudohump formation, and nasal valve collapse. These changes are driven by diminished skin elasticity, soft-tissue atrophy, and the weakening of cartilaginous suspensory ligaments. Because standard septoplasty often fails to resolve airway obstruction in older adults, robust structural modifications are required. Techniques utilizing septal extension grafts, columellar struts, and tongue-in-groove positioning successfully restore tip rotation and projection. Concurrently, the application of spreader grafts and alar strut grafts effectively counteracts dynamic internal and external nasal valve collapse, thereby significantly improving nasal airflow. The aging nose presents intertwined aesthetic and functional challenges caused by progressive tissue and cartilage degradation. Surgical management must move beyond simple resection and prioritize strong cartilaginous reinforcement and valve stabilization to achieve durable cosmetic outcomes and optimal functional breathing in older patients.

Rice panicle blast detection is an important task in plant disease phenotyping. Field-based detection remains challenging because infected spike regions are often small, sparse, elongated, and affected by overlapping panicles, complex backgrounds, and variable illumination. In this study, we propose RPB-YOLO11, a lightweight YOLO11-based detector designed for rice panicle blast detection. The model uses a Lightweight Ghost Backbone (LGB) to reduce redundant computation. It uses Anisotropic Axial Stripe Attention (A2SA) to represent elongated panicle structures. It also uses Focal Multi-Scale Attention (FMSA) for multi-scale feature refinement and Adaptive Geometric Shape IoU (AGS-IoU) for geometry-aware localization. The model was trained and evaluated on a rice panicle image dataset containing 1,055 training images, 69 validation images, and 169 test images. On the test set, RPB-YOLO11 achieved 76.09% mAP50, 45.44% mAP50-95, 73.98% precision, and 72.75% recall with 6.21 GFLOPs. Compared with the YOLO11n baseline, it improved mAP50, mAP50-95, precision, and recall by 2.73, 2.12, 1.64, and 2.11 percentage points, respectively. An Android-oriented inference application supports local image inference, detection visualization, class counting, and diseased-panicle incidence estimation. These results suggest that RPB-YOLO11 provides a practical approach for image-based rice panicle blast survey.

This study focuses on the walnut cultivar 'Wen 185' in the arid region of southern Xinjiang. Addressing the limitation that traditional vegetation indices often experience saturation during peak growth periods, which restricts inversion accuracy in complex orchard environments, we obtained full-growth period images using a multispectral unmanned aerial vehicle platform. We incorporated the blue (450 nm) and red-edge (750 nm) bands to develop enhanced spectral index schemes. By integrating machine learning algorithms, we achieved improved estimation of SPAD values. The results indicate that the multiplicative improved spectral index scheme using the blue band (Scheme c), which multiplies and recombines the traditional index with the blue light band, significantly improves sensitivity to chlorophyll variations and effectively mitigates the spectral saturation phenomenon. In algorithm evaluations, the Convolutional Neural Network (CNN) model achieved the highest individual validation predictive accuracy under Scheme c (validation R[2] = 0.814, RPD = 2.359). However, its performance varied across different index combinations. In contrast, the Random Forest (RF) model demonstrated consistent cross-scheme stability and generalization capability across all spectral enhancement formulations (validation R[2] ≥ 0.70). Therefore, while CNN provides peak performance under specific optimal feature configurations, RF offers a more stable and robust alternative for practical applications involving diverse spectral inputs. While the spatial distribution map, generated by integrating geographical coordinates, visually illustrates the dynamic evolution of walnut SPAD-characterized by an initial increase followed by a decrease during the growth period-subsequent multi-stage variance analysis revealed that the superiority of the W1F1 water and fertilizer coupling treatment is stage-dependent. Specifically, W1F1 achieved significantly higher SPAD values than other combinations during the oil transformation stage (p < 0.05), whereas differences across other growth periods were not statistically significant. The findings provide a scientific foundation for precise nitrogen diagnosis and informed decision-making in the smart fruit and forestry sector in arid regions.

The global agri-food system is navigating an era of unprecedented complexity and urgency [...].

This study systematically investigated the modulation effects of heating duration (0-60 min) on the structure, functional properties, and Pickering emulsion performance of chickpea protein aggregates (CPAs). CPAs heated for 30 min (CPAs-30) exhibited favorable properties: the smallest particle size (534.67 nm) and zeta potential (-26.6 mV), and enhanced colloidal stability compared to other heating durations. Further mechanistic analysis revealed that a synergistic stabilization mechanism involving enhanced hydrophobic interactions (contact angle increased from 71.75° to 77.8°, surface hydrophobicity rose 10.47-fold, β-sheet content increased from 36.9% to 46.7%), disulfide cross-linking, and hydrogen bonding. Consequently, emulsifying activity and stability increased by 1.42-fold and 3.79-fold, respectively, while interfacial adsorption capacity improved 1.07-fold, forming an elastic network (G' > G″). In vitro digestion assays further confirmed that CPAs-30 exhibited enhanced gastrointestinal resistance. This work establishes a structure-function framework for the rational design of high-performance plant protein colloids through controlled thermal aggregation.

Water-soluble oyster mushroom polysaccharides (OMPs) are multifunctional biopolymers with growing relevance in food and health-related applications. This review summarizes recent progress in the extraction, purification, structural features, biological activities, and food applications of OMPs, with particular emphasis on tentative structure-activity relationships constrained by heterogeneous experimental evidence. Conventional and emerging extraction approaches, including hot water, enzyme-assisted, ultrasound-assisted, and microwave-assisted methods, are compared in terms of yield and structural integrity. The monosaccharide profiles of OMP fractions vary considerably across different preparation conditions: glucose is universally the dominant component (17.78%-100%), followed by mannose (3.60%-40.34%) and galactose (3.09%-100%), with this compositional variation largely driven by extraction approaches, purification procedures, and fractionation strategies. Water-soluble OMPs are mainly β-glucans with β-(1→3)(1→6)-linked glucose backbones, while small amounts of galactans occur in certain fractions. A wide range of in vitro and animal assays report antioxidant, antitumor, anti-obesity, immunoregulatory, and gastrointestinal protective capacities of OMPs, yet these biological outcomes are dependent on OMP purity, molecular weight range, experimental dosage, and cell/animal model systems. Substantial in vitro and in vivo evidence confirms that OMP bioactive potency closely correlates with monosaccharide composition, molecular weight profile, and functional group distribution. Chemical modifications (e.g., sulfation, phosphorylation, selenization) can further boost OMP bioactivities. In food systems, β-(1→3)/(1→6)-glucan-rich OMPs have been used as stabilizers and texture modifiers. Despite progress, challenges remain in large-scale production, structural standardization, and mechanistic elucidation. Future studies should integrate advanced analytical techniques, multiomics strategies, and artificial intelligence (AI)-assisted modeling to facilitate rational design and industrial application of OMP-based functional materials.

Accurate assessment of animal semen quality is essential for artificial insemination efficiency, genetic resource conservation, and sustainable development of animal husbandry. Although conventional semen evaluation methods (e.g., microscopic morphological observation, flow cytometry, and hypo-osmotic swelling test) have been standardized, they generally suffer from long processing times, dependence on laboratory equipment, and the need for professional operation, making them inadequate for rapid-response scenarios such as on-farm breeding guidance and real-time semen viability monitoring. This review provides a critical, systematic synthesis of the latest advances from 2020 to 2026 in rapid animal semen quality detection technologies, with particular focus on field validation status and practical implementation feasibility. It focuses on comparing two branches of computer-assisted sperm analysis (CASA) traditional image-based processing systems and emerging deep learning approaches in terms of analytical sensitivity, portability, and field-deployability. Furthermore, this article reports on the application of microfluidic chip technology and smartphone-based imaging systems as next-generation point-of-care tools, enabling multiparameter analysis at the single-sperm level. The potential of portable biosensors (e.g., impedance sensors and lateral flow strips) for rapid detection of oxidative stress and DNA fragmentation in semen is also reviewed, along with the growing role of artificial intelligence in automated sperm morphology classification and motility trajectory prediction. Building on a unified biological framework linking molecular targets to fertility outcomes, this review systematically evaluates emerging fertility-associated biomarkers including proteomic signatures, extracellular vesicles, non-coding RNAs, and epigenetic markers, and critically assesses their predictive value for field reproductive performance. A modified QUADAS-2 framework tailored for veterinary diagnostics is applied to grade the strength of evidence for all included technologies, distinguishing high-quality multi-center validated methods from proof-of-concept prototypes, and systematically identifying sources of bias such as spectrum bias, operator blinding deficits, and developer-led validation studies. Quantitative analysis shows that only 7.1% of included studies meet high-quality evidence standards, while 82.5% of emerging technology evaluations carry performance overestimation bias due to developer-led trial design. A three-tiered technology maturity classification is established to distinguish established laboratory standards, field-validated developing tools, and proof-of-concept emerging technologies, clarifying the practical readiness of each method. Advanced rapid detection methods have reduced total assay time from 30 to 60 min (conventional manual microscopy) to 5-15 min; however, challenges remain regarding standardization of sample pretreatment and interference caused by semen heterogeneity. A structured, scenario-based technology selection framework with fully quantitative comparisons of capital equipment cost, per-test reagent cost, training investment, and cost-effectiveness across deployment scales, with benchmarking against conventional manual microscopy and laboratory gold-standard methods to clarify incremental cost-effectiveness ratios for each deployment scenario, is proposed to assist researchers and practitioners in selecting appropriate detection methods according to specific needs, including sensitivity, cost, throughput, and deployment scenarios. A multidimensional comparative analysis across 12 standardized performance criteria demonstrates that deep learning-assisted imaging based on microfluidic chips achieves the best balance among detection speed, accuracy, and field deployability, whereas flow cytometry remains the quantitative gold standard for laboratory semen quality assessment. This review also provides an in-depth analysis of current standardization gaps and regulatory frameworks for veterinary semen diagnostic devices across major global jurisdictions, identifying key barriers to commercial translation including lack of certified reference materials, underdeveloped inter-laboratory proficiency testing schemes, and fragmented regulatory pathways for point-of-care products. Finally, a phased 10-year translational roadmap is proposed, highlighting priority directions including multi-omics integration, multiplex point-of-care platform development, cross-species diagnostic standardization, and commercial translation of laboratory prototypes.

Drought stress severely limits grapevine productivity and compromises fruit quality, with its adverse effects expected to intensify under ongoing climate change. This review synthesizes recent advances in elucidating the molecular and physiological mechanisms underlying drought tolerance in Vitis vinifera. Key physiological responses include abscisic acid (ABA)-mediated amplification of stomatal closure, osmotic adjustment, activation of antioxidant defense systems, and hydraulic vulnerability segmentation-a protective strategy involving the targeted sacrifice of petioles and basal leaves to maintain hydraulic integrity in stems and roots. These coordinated responses are regulated by a complex transcriptional network centered on NAC, WRKY, MYB, and bZIP transcription factors, and further modulated by hormone metabolism, potassium channel activity, aquaporin-facilitated water transport, and both enzymatic and non-enzymatic antioxidant pathways. We also identify critical knowledge gaps requiring urgent attention: (First) field-scale validation of transgenic or CRISPR-edited grapevine lines; (Second) the molecular basis of rootstock-scion signaling during drought stress; and (Third) the integration of multi-omics data with high-resolution phenotyping to accelerate precision breeding. Collectively, this review provides an integrative conceptual framework to support sustainable viticulture in water-limited environments.