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Tenderness and nutritional quality are critical determinants of meat value and consumer acceptance. This review discusses applications of plant cysteine proteases primarily for improving meat texture, with emphasis on their effects on myofibrillar, sarcoplasmic, and connective tissue proteins. Factors governing artificial meat tenderization, including enzyme properties, processing conditions, and delivery methods, are evaluated. The review also examines how protease pretreatment influences in vitro protein digestion and the release of bioactive peptides. Controlled application of plant cysteine proteases can improve meat texture and modify digestive and peptide-release characteristics, although enzyme type, dose, treatment conditions, sensory quality, and physiological validation must be considered for practical implementation.
As oxidative processes are increasingly employed for the removal of trace substances in advanced wastewater treatment, as required by, among others, by the EU urban Wastewater treatment directive, disinfection by-products, particularly bromate are becoming increasingly important. This study presents a comprehensive intra- and interlaboratory evaluation of four ion chromatography (IC) based methods for the determination of bromate in wastewater: conductivity detection (IC-CD), post-column reaction with UV/Vis detection (IC-PCR-UV/Vis), high-resolution mass spectrometry (IC-ESI-HRMS), and inductively coupled plasma mass spectrometry (IC-ICP-MS). Performance parameters were assessed in ultrapure water and verified across different wastewater matrices, including influent, secondary clarifier effluent, and final effluent of a municipal wastewater treatment plant. IC-CD achieved a LOQ of 1.4 µg/L in ultrapure water but exhibited strong matrix dependency in untreated wastewater. In treated wastewater, the verified LOQs were sufficiently low to allow quantification below the regulated drinking water limit (10 µg/L). IC-PCR-UV/Vis and IC-ICP-MS demonstrated robust performance across all investigated matrices, with a LOQ of 1.0 µg/L and consistently reliable precision (<5%) and recoveries (90-110%), making these methods suitable for both treated and untreated wastewater. IC-ESI-HRMS provided the lowest LOQ (0.07 µg/L) though requiring dilution in untreated wastewaters due to matrix effects. Interlaboratory validation confirmed that IC-CD is only suitable for treated wastewater, whereas IC-PCR-UV/Vis is broadly applicable across treated and untreated wastewaters. Overall, IC-PCR-UV/Vis represents the most practical method for routine bromate monitoring in wastewaters. Mass spectrometry-based approaches demonstrated enhanced selectivity and lower LODs, while enabling multi- analyte analysis, albeit with higher instrumental complexity. However, their broader applicability for routine wastewater monitoring requires further interlaboratory evaluation.
Plant viruses continue to impose severe constraints on global agriculture, often leading to substantial yield and economic losses. Conventional management strategies such as vector control and resistance breeding frequently fail to provide durable and broad-spectrum protection due to rapid evolution of virus, their dependence on host cellular machinery and the lack of effective antiviral compounds. These shortcomings have led researchers to increasingly explore molecular approaches, with RNA interference (RNAi) emerging as a precise and sustainable strategy for managing plant viral diseases. RNAi operates through endogenous gene regulatory mechanisms and is driven by small RNAs (sRNAs) such as small interfering RNAs (siRNAs) and microRNAs (miRNAs). Through mechanisms such as post-transcriptional gene silencing (PTGS) and transcriptional gene silencing (TGS), sRNAs orchestrate a robust and multilayered immune response against plant viruses. Recent advances have expanded RNAi-based strategies to both transgenic and non-transgenic platforms. Transgenic approaches such as host-induced gene silencing (HIGS), provide stable and long-term resistance, while non-transgenic methods like spray-induced gene silencing (SIGS) and other exogenous nucleic acid delivery systems offer flexible and environmentally safe alternatives without genetic modification. Furthermore, engineered sRNAs such as artificial microRNA (amiRNA) and synthetic trans-acting small interfering RNA (syn-tasiRNA) enhance target specificity, enable multiplex targeting and reduce off-target effects. This review aims to bridge the fundamental concepts of sRNA biology with their application in antiviral crop protection. It provides a comprehensive overview of sRNA biogenesis, antiviral mechanisms and engineered sRNA technologies for plant virus management.
Plant-based vegan diets (PBVDs) improve cardiometabolic risk markers, hence are recommended as an adjunct treatment by some cardiologists. To complete a service evaluation, practical measures of dietary adherence are required, and perceptions of patients need to be considered. A single-arm, mixed-methods design was used to assess the feasibility of using two diet indices to assess adherence to a PBVD and the acceptability of adopting a PBVD in a cardiac outpatient setting. Diet adherence was measured via absence of proscribed foods (APF) and a plant-based vegan diet score (PBVD-S). Acceptability of the PBVD was assessed via individual interviews and a food acceptability questionnaire. Twenty patients completed the dietary assessment. After 8 weeks, 55% (n = 11) were classified as fully adherent to the PBVD. Mean score for the PBVD-S increased from 20.3 ± 8.7 at baseline to 38.9 ± 5.8 at Week 8. Mean total cholesterol (TC), body mass index (BMI), body mass, and waist circumference significantly decreased (p < 0.001) after 8 weeks on the PBVD. The PBVD-S satisfied the feasibility criteria of alignment with diet education and assessment of adherence. The PBVD was rated as either "moderately" or "extremely" acceptable by 80% of patients. The PBVD-S is a feasible option for assessing adherence and diet quality of a PBVD in a cardiology outpatient setting.
Food-based enteral formulas are increasingly being used for children with medical complexity and are associated with improved feeding tolerance. However, feed volumes needed to meet energy needs may not be tolerated. This study monitored short-term gastrointestinal (GI) and weight outcomes after initiating a commercial hypercaloric, plant- and food-based, formula in tube-fed children with medical complexities. In this exploratory study, tube-fed children aged 1-13 years were recruited from outpatient clinics at a tertiary care hospital (May 2023-June 2024). Participants received study formula (1.5 kcal/mL) exclusively for 14 days with additional water to meet total fluid needs. Caregivers recorded data about feed administration, as well as any change to GI symptoms and bowel movements, daily. Weight-for-age and BMI-for-age z-scores were compared at baseline and end-of-study using Wilcoxon signed rank tests. The percentage of energy achieved versus prescribed, as well as protein (g/kg/day) intake compared to Dietary Reference Intakes for sex and age, was assessed. Twenty-six participants (median age 5.5 years, 59% male) completed the study. After two weeks on the study formula, a modest increase in mean weight-for-age and BMI-for-age z-scores was observed (p<0.01). There were no significant changes to GI symptoms or bowel movements reported. Participants achieved 100% of prescribed energy for nearly all study days (13±1.7 days) and exceeded daily protein requirements. Caregivers (84.6%) reported high satisfaction with the study formula. Short-term administration of a commercial hypercaloric, plant- and food-based formula that met prescribed energy and protein needs was associated with modest weight increase and no changes to baseline GI symptoms or bowel movements. These findings suggest that hypercaloric food-based enteral nutrition products are generally tolerated in stable, medically complex, tube-fed children. Larger, prolonged studies are needed to evaluate long-term tolerance and nutritional adequacy.
The eukaryotic genome has been described as a collection of different phylogenetic histories. For most phylogenomic analyses the primary goal is to identify the species tree, the singular history that underlies and shapes the "gene trees" of individual loci. Discordance among gene trees and with the species tree is expected due to deep coalescence/lineage sorting, while also resulting from various technical causes (e.g., long branch attraction, pseudo-orthology), or, of greater interest, by introgression and horizontal transfer. Where do competing phylogenetic signals reside in gene tree topology space-that part of tree space occupied by the gene trees reconstructed for a particular dataset of taxa and genetic loci? We explored this question in the small (~30 species) leguminous plant genus, Glycine, which has extensive genomic resources due to the inclusion of cultivated soybean (G. max). Glycine genomes are highly duplicated due to relatively recent (~10 million years) ancestral polyploidy and have extensive nuclear-cytoplasmic discordance. We explored Glycine gene tree topology space using a set of 2389 nuclear genes and 61 representative accessions selected from a 570-taxon x 100 gene concatenation supergene tree, reconstructing gene trees for all nuclear loci and from complete plastid genomes and partial mitochondrial genomes. Species trees (ASTRAL) and maximum likelihood (ML) concatenation trees were congruent with one another but were discordant with organellar genome trees, which were incongruent with one another. Individual loci all had unique topologies for the 61-taxon dataset and for a reduced dataset of 27 taxa. No locus tracked either the species tree or the plastome topology in the resulting "flat" gene tree topology space of either dataset, nor did clustering identify any regional differentiation of gene tree topology space populated by loci with similar topologies. Only when the dataset was reduced to six Glycine species, chosen because they have complete genome sequences, and an outgroup was a topological landscape produced in which most loci tracked the species tree topology, with secondary peaks that included, most prominently, the discordant plastome topology. There was no evidence of pseudo-orthology in this landscape, and synteny-based assessment of thousands of loci across these six genomes identified few candidate pseudo-orthologs. Thus, while it is true that the Glycine genome is indeed a collection of different historical signals, those signals are complex and exist at the level of clades within trees rather than as entire gene trees. Although phylogenomic methods can reconstruct the species tree from signals scattered among many loci, even loci with very low resolution, other biologically relevant signals are much more difficult to localize without an explicit starting hypothesis.
Caffeine, a safe methylxanthine, has been widely used for the treatment of skin diseases such as cellulite, hair loss, aging, and psoriasis. However, its skin penetration is low. Transcutol is a biocompatible, nonvolatile permeation enhancer which solubilize large number of drugs and does not change the integrity of the skin structure. In this study, the skin permeability of synthetic and natural caffeine gels was compared by ex vivo experiments. Furthermore, Transcutol P was used as a permeation enhancer, and its impact on skin permeation enhancement was determined. The skin penetration of caffeine from the formulation containing coffee extract, a type of natural caffeine, is higher than that of the formulation containing pure synthetic caffeine. This effect is likely due to the presence of coffee, which can act as a skin permeation enhancer. Additionally, the use of Transcutol P in a formulation containing coffee extract at a concentration of 2.5% caused the highest amount of flux. Therefore, the formulation of gel containing natural caffeine along with 2.5% Transcutol is optimal and can be used for further studies. It can be concluded that the addition of 2.5% Transcutol P in the formulation containing coffee extract resulted in the highest skin permeation.
Climate change has increased the incidence of compound stresses, including the co-occurrence of nitrogen deficiency (-N) and high temperature (HT), which severely reduce plant productivity. Studies have primarily focused on single plant tissues to decipher tolerance mechanisms; however, tissue-specific metabolic reprogramming remains poorly examined. This work aimed to examine the distinct metabolic reprogramming in roots and leaves under whole-plant nitrogen deficiency (-N) and high temperature (HT), applied individually or combined. We hypothesized that roots and leaves exhibit complementary metabolic profiles, while combined stress triggers a unique metabolic signature associated with plant growth regulation. Soybean plants were subjected to control, -N, HT, and HT-N conditions, and later whole-plant physiological assessment and untargeted metabolites profiling of roots and leaves were performed and analyzed by machine learning analyses (e.g., t-SNE, UMAP, WGCNA, and random forest regression), qPCR and absolute quantification of identified key metabolites. Combined HT-N stress caused severe growth inhibition, reduced shoot length (67%), root fresh weight (52%), and photosynthetic efficiency (Fv/Fm; by 51%) compared to control. Metabolomic analysis revealed stress specific responses in different tissues, with roots prioritizing N assimilation (accumulating glutamate, proline and aspartate) under -N, while leaves enhanced osmo-protection (accumulating flavonoids) under HT. Under combined HT-N, tissue-specific responses were additive, with roots focusing on amino acid and proline metabolism and leaves on phenylpropanoid and glutathione metabolism. Our machine learning analyses (t-SNE, UMAP), WGCNA and RFR showed distinct tissue-specific metabolic signatures for each stress, and identified glucose, flavonoids, proline, and specific amino acids among key candidate metabolites associated with physiological resilience. Later, exogenous application of proline, quercetin, and L-arginine recovered soybean growth under stress, but in a stress-specific manner. Soybean employs distinct metabolic strategies in roots and leaves to manage multiple stresses. The identified key metabolites represent candidate hubs in the stress response network, offering candidate targets that warrant further investigation for breeding climate-resilient crops.
Low-carbohydrate and low-fat diets (LCDs and LFDs) are promoted for cardiometabolic prevention. This study examined associations of LCDs and LFDs with incident dementia and evaluated modification by genetic susceptibility. We included 5301 dementia-free adults aged ≥55 years from the Health and Retirement Study. Overall LCD and LFD indices were constructed based on macronutrient composition rankings assessed using a food frequency questionnaire in 2013-2014. Plant-based, animal-based, healthy, and unhealthy sub-scores were derived to characterize macronutrient sources and quality. Incident dementia was defined using the Langa-Weir algorithm through 2022. Genetic susceptibility was assessed using APOE genotype and Alzheimer disease polygenic risk score (AD-PRS). Cox models estimated hazard ratios (HRs). During the 9-year follow-up, 506 participants developed dementia. Greater LCD score was associated with lower dementia risk (HR per SD increment 0.90, 95% CI, 0.82, 0.99), whereas an overall LFD was not (1.05, 95% CI, 0.96, 1.15). Plant-based and healthy LCDs showed stronger inverse associations (0.85, 95% CI, 0.78, 0.94 and 0.82, 95% CI, 0.74, 0.90), while higher animal-based (1.10; 95% CI, 1.00, 1.20) and unhealthy LFDs (1.13; 95% CI, 1.04, 1.24) were linked to higher dementia risk. Associations were consistent across APOE genotype and AD-PRS strata. Higher plant-based and healthy LCDs were also associated with better global and domain-specific cognitive performance. Adherence to LCDs, particularly plant-based and higher-quality LCDs, was associated with lower dementia risk, consistently across genetic susceptibility strata. These findings underscored the importance of macronutrient quality, in addition to quantity, in promoting cognitive health.
This study evaluated the impact of hydropriming and gamma rays on morpho-functional attributes of Cannabis sativa L. and identified optimal radiation levels for improvements in local hemp germplasm. Two seed lots, G1 (pre-irradiation hydropriming) and G2 (post-irradiation hydropriming), were subjected to the radiation source cobalt-60 (Co60) at specified doses (150, 300, 450, and 600 Gy) in a completely randomized factorial experiment with 10 treatments and three replications. Key physiomorphic traits, including germination rate, survival percentage, plant height, leaf number, shoot/root dry weight, trichome traits, chlorophyll and metabolite contents (anthocyanin, flavonoids), were measured and statistically analyzed via ANOVA Tukey's HSD. Regression heat maps and dose response curves were drawn to find out optimal dose levels. Gamma irradiation significantly influenced all the parameters across treatments compared to wild-types. Application @150 Gy increased seed germination, survival rate, plant height, biomass, chlorophyll content, and trichome density while high doses (210.16 Gy in G1 and 425.95 Gy in G2) surpassed LD50. Maximum phenotypic variation was observed in G1D1 and G2D3. The trichome density notably increased at low to moderate doses. A significantly positive correlation was observed among parameters in response to gamma irradiation; however, dose response curves showed greater radio-tolerance and growth in G2 than G1 plants. Low-dose gamma irradiation (150 Gy) combined with hydropriming can be an effective mutagenic approach to enhance the growth and biochemical traits of Cannabis sativa. The findings offered a viable mutation protocol to develop improved hemp varieties tailored for fiber and cannabidiol (CBD) production.
Camptothecin (CPT), a potent anticancer quinoline alkaloid derived from plant resources, is conventionally purified through multi-step processes with low selectivity, high solvent consumption and unsatisfactory recovery. In this study, a novel bio-based surface-imprinted adsorbent (CCS-Si&MIP-CPT) was rationally designed and fabricated using porous cellulose-silica hybrid microspheres as the support matrix, with CPT as the template molecule and methacrylic acid as the functional monomer. The physicochemical structure of the as-prepared material was fully characterized, and its adsorption kinetics, isotherms, selective recognition mechanism and reusability were systematically investigated. Furthermore, the material was applied as a solid-phase extraction (SPE) filler for the purification of CPT from crude camptotheca seed extracts, and its performance was benchmarked against established purification methods. The results show that the adsorption behaviour of CCS-Si&MIP-CPT toward CPT is in good agreement with the Langmuir isotherm and the pseudo-second-order kinetic model. Combined with molecular structure comparison of CPT analogs, the selective recognition mechanism was comprehensively elucidated from three perspectives: hydrogen-bonding functional group matching, steric hindrance effect of substituents, and complementarity of molecular size and overall shape. The renewable carrier design and its cyclic stability not only show potential for application in green separation technologies for natural medicine development, but also provide a theoretical foundation for the high-value utilization of plant resources.
Crawling soft robots have attracted widespread attention due to their high adaptability to unstructured environments. However, existing research often focuses on understanding the formation mechanism of their motion capabilities from the perspective of actuation methods or control strategies, resulting in fragmented design logic and a lack of a possible framework. Through comparative analysis across animal, plant, and microbial systems, this paper points out that crawling behavior in different biological systems largely depends on the synergistic effect of morphological deformation and interface friction. Many studies have shown that rectifying periodic, reversible deformation processes into directional net displacement plays a crucial role. Building on this, this paper further analyzes the roles of various actuation technologies in crawling systems, emphasizing that actuation primarily undertakes deformation triggering and modulation functions, and its impact on motion performance is highly dependent on the coupling method with morphological structure and interface conditions. Regarding control and learning methods, this paper discusses the key role of morphological and interface design in reducing control dimensionality and improving system robustness from the perspective of embodied intelligence, pointing out that control strategies are more about compensating for and optimizing the structure-generated motion capabilities. The motion capability of soft crawling robots is not entirely determined by a single actuation performance, but rather stems from the synergistic rectification of periodic deformation by morphological structure, actuation timing, and interface interactions. Finally, this paper summarizes and proposes several future-oriented design languages and research paradigms, providing a unified reference framework for understanding the mechanisms and engineering design of crawling soft robots.
Based on the landscape perception theory and human factors methods, this study adopted eye-tracking and multimodal physiological monitoring to explore the effects of age-friendly rehabilitative landscapes on stress recovery in older adults. A total of 44 healthy older adults were recruited. Fourteen landscape scenes from five types of parks in Xi'an were selected to collect physiological data under visual-only and audio-visual combined conditions. The results showed three key findings. First, the main effect of visual environment was significant (p < 0.05). Landscapes with moderate plant diversity and static water features produced the optimal stress recovery effects. Second, the audio-visual interaction effect was significant (p < 0.05). Auditory stimuli did not universally promote stress recovery, and their effects were regulated by visual landscape types. Third, eye movement data indicated excessive audio-visual stimuli might reduce recovery efficiency. Open spaces and static water features showed strong anti-interference capabilities. Sound cues effectively drew older adults' visual attention to water landscapes. This study suggests prioritizing landscapes with moderate plant complexity and static water features. The sound volume of dynamic water scenes should be controlled, and open spaces can be designed to reduce cognitive load. The findings deepen the understanding of how audio-visual landscapes affect stress recovery in older adults, and provide empirical evidence for the design and optimization of age-friendly landscapes in urban parks and community green spaces.
Coconut oil cake and meal generated during oil and milk processing contain significant quantity of high-quality proteins. Compared to other plant proteins, coconut proteins contain higher ratio of essential amino acids, better digestibility, and demonstrate versatile functionality in food matrices. However, they are seldom extracted at industrial scale and used in food formulations. This study evaluates the critical linkage between the extraction methods, protein structure, nutritional quality, functional properties, allergenicity, and their suitability for food applications. Conventional extraction techniques such as alkaline extraction and isoelectric precipitation are assessed alongside emerging techniques, such as membrane-based separations, enzyme, microwave and ultrasound-assisted extractions, with emphasis on the protein yield, structural integrity, and functional properties. Structure-function relationship governing solubility, thermal stability, gelation, interfacial, rheological, oil and water binding properties are critically analyzed, particularly for the predominant globulin fractions. The generation of bioactive peptides during enzymatic hydrolysis and their relevance in functional food are also examined. Strategies to improve functionality, including deamidation, protein-polysaccharide conjugation and amino acid-mediated modulation of protein-protein interactions, are discussed. Process scale-up and limited knowledge on value chain are the key challenges limiting the commercialization of coconut proteins. The work outlines directions for future research and industrial applications of coconut proteins. Coconut seed cake is an underutilized, sustainable source of plant protein (4–25%).Coconut proteins contain ∼32–38% essential amino acids with high digestibility (>85%).Globulin fractions (7S and 11S) impart strong emulsifying, oil-binding and gelation properties.Green extraction and targeted protein modification enhance yield and functionality.Lower allergenicity prevalence and clean-label potential support diverse food applications.
The tomato plant is considered one of the most important crops in the world, yet it is vulnerable to various diseases that affect crop quality and agricultural productivity. These challenges have driven the need for an efficient and intelligent plant disease detection system. With the development of computer vision and artificial intelligence, this proposed methodology based on deep learning for tomato leaf diseases has been presented. Two public datasets: Taiwan DS with nine classes and Tomato Leaf Diseases Detection Computer Vision Dataset (TLDDCV DS) with seven classes have been used to test this system. This system begins with plant image processing, which includes gamma correction and bilateral filtering, to enhance image quality and clarity while preserving key disease features. Then, a genetic metaheuristic algorithm was used to automatically select the most significant hyperparameters, further optimizing both processing time and accuracy. After that, the tomato leaf disease detection applies the You Only Look Once version 11 Nano (YOLOv11n) model. The YOLOv11n backbone is edited through a Data-efficient Image Transformer (DeiT) to improve the system's capacity for learning global contextual information and long-range dependencies. Experimental results demonstrate that the proposed system outperforms existing methods. It achieved an average mAP@50 of 97.8%, mAP@50-95 of 93.4%, precision of 97.3%, recall of 93.8%, and F1-score of 95.5% on the Taiwan dataset. Additionally, it achieved an average mAP@50 of 87%, mAP@50-95 of 48%, precision of 83.9%, recall of 70.3%, and F1-score of 76.4% on the TLDDCV dataset. These results demonstrate the generalizability and effectiveness of the proposed system in real-world agricultural situations.
Metabolic disorders have grown more common, with obesity representing a significant chronic illness that leads to various severe health complications. The Obesity Atlas 2022 predicts one billion obese people by 2030. Contributors to obesity encompass heightened oxidative stress, hyperlipidemia, hunger enhancement, fat accumulation, insulin resistance, and diminished caloric expenditure. Numerous synthetic interventions for obesity are accessible today ; nonetheless, they frequently entail detrimental side effects. This research aimed to investigate the formulation of a prospective anti-obesity drug derived from plant origins. The anti-obesity effectiveness of a polyherbal formulation, derived from the ethanolic extract of both Hugonia mystax and Blumea lacera in a 1:1 ratio, was assessed in female mice with progesterone-induced obesity. The preliminary phytochemical screening of the formulation specifies the presence of phenolic acids, flavonoids, and tannins. In accordance to OECD recommendations, 200 mg/kg and 400 mg/kg were designated after performing acute oral toxicity assessment as a low dose and high dose. During the study, body weight, BMI, abdomen circumference, glucose levels, lipid profile, SGOT, SGPT, atherogenic index, lipid peroxidation (LPO), and glutathione (GSH) levels were evaluated in all groups. The treatment markedly corrected the abnormal levels of these parameters and dramatically restored GSH levels. Metabolic disorders, especially obesity, are increasing globally. Synthetic therapies have negative consequences; therefore, exploration of plant substitutes is encouraged A polyherbal extract of Hugonia mystax and Blumea lacera has shown significant anti-obesity properties in mice. It restored biochemical parameters, likely due to phytochemicals such as polyphenols. Histological examination validated its therapeutic efficacy. The formulation's efficacy in addressing obesity is likely attributable to the presence of polyphenols, saponins, and terpenoids. Histopathological examination of hepatic and adipose tissues further corroborated the anti-obesity efficacy of the polyherbal formulation. Future research will focus on isolating and identifying the active chemicals in both plants to better understand their composition.
Supramolecular deep eutectic solvents (SUPRADES) have are promising green extraction media for the sustainable extraction of bioactive compounds from plant materials. In this study, a combined strategy of SUPRADES with ultrasound-assisted extraction (UAE) was developed for the efficient extraction and enrichment of isoflavones from the root of Pueraria lobata. The extraction process was systematically optimized using single-factor experiments followed by Box-Behnken design (BBD) response surface methodology. The optimal SUPRADES system consisted of L‑proline and urea at a 1:2 molar ratio, supplemented with 5 wt% β‑cyclodextrin and 30 wt% water. Under these conditions, the yield of puerarin reached 70.4 ± 0.6 mg/g, which is 1.33‑ to 5.33‑fold higher than those obtained with conventional methods. The self‑assembled structure of the SUPRADES and its molecular‑level interaction mechanism with isoflavones were further elucidated by FT‑IR spectroscopy, ¹H NMR spectroscopy, and density functional theory (DFT) calculations. These results confirmed that the extraction process is synergistically driven by hydrogen bonding and β‑cyclodextrin‑mediated host-guest complexation. GAPI evaluation demonstrated the excellent environmental friendliness and sustainability of the established method. Collectively, this study provides a novel and efficient extraction strategy for isoflavones from Pueraria lobata root and offers a theoretical basis for green the extraction of natural products in traditional Chinese medicine.
Glomalin-related soil proteins (GRSP) are operationally defined soil fractions associated with arbuscular mycorrhizal fungi (AMF) and are widely studied for their contributions to soil structure, carbon dynamics, and ecosystem functioning. Since its discovery, GRSP has attracted considerable attention because of its association with soil aggregation, carbon stabilization, and ecosystem sustainability. Glomalin, has been associated with various soil attributes, including the stability of soil aggregates, the size of soil carbon and nitrogen reservoirs, the sequestration of heavy metals, and the mitigation of diverse plant stresses. While GRSP concentrations in soil have often been correlated with AMF biomass measured through alternative (microscopic) methods, the chemical composition of GRSP extracted from soil remains intricate and not fully understood. This complexity arises from the nonspecific nature of its extraction and purification processes, as well as the diverse array of analytical techniques employed thus far to evaluate it. Current evidence suggests that GRSP contributes to soil organic carbon stabilization primarily through its association with soil aggregates. In this review, we endeavor to synthesize and explore various facets of glomalin, encompassing its composition, production mechanisms, soil-related functions, recalcitrant properties, and its potential role in the sequestration and stabilization of soil carbon.
Rapid and reliable detection of activated sludge (AS) is essential for smart wastewater treatment but remains challenged by the interference susceptibility and poor generalization of current methods. Here, a Three-Dimensional Settling Map (3D-SM) was proposed to dynamically encode the complete sludge settling process as a unified spatiotemporal-optical fingerprint. Using a self-developed platform and adaptive image processing, this map was extracted and decoded via a deep learning model to directly quantify key AS parameters-MLSS, SVI30, and SV30-with high accuracy (MLSS: R2=0.957, SV30: R2=0.953, SVI30: R2=0.962). The 3D-SM showed low sensitivity to tested environmental factors (e.g., pH, conductivity, and color) within the evaluated range and enabled short-term state prediction (R2>0.60) under investigated conditions. Furthermore, it supported threshold-based sludge-state assessment and exploratory identification of filamentous bacteria enrichment, achieving>92.7% accuracy in identifying settling dysfunctions and 99.3% accuracy in classifying filamentous levels on the test set. A 71-day cross-site validation at one industrial AO treatment plant confirmed consistent performance (R2>0.801, accuracy>95.2%) within the tested operational range. This work establishes 3D-SM as a foundational, interference-resistant tool that transforms settling dynamics into an AI-parsable digital signature, providing a robust at-line approach for supportive AS intelligent monitoring.
The escalating incidence and severity of wheat crown rot poses a profound threat to global wheat yields and food security. Despite widespread fungicide application, the spatial mismatch between deposition sites and pathogen infection loci limits the precision and sufficiency of delivery, thereby reducing disease control efficacy and utilization efficiency, resulting in resource waste and environmental pollution. This study aimed to develop a multifunctional fungicidal nano-formulation with high leaf deposition and long-distance transport of active ingredients, in order to enhance the utilization efficiency of the active components. A functional difenoconazole Pickering emulsion (DIF-PE) with high deposition and delivery efficacy was successfully developed using mesoporous amphiphilic Janus nanoparticles. These nanoparticles (PEG@PDA@CaP) composed of hydrophobic calcium phosphate (CaP) integrated with hydrophilic polydopamine modified with methoxy poly (ethylene glycol) thiol, served as both solid emulsifiers and functional carriers. Interface behavior and transport performance were characterized using theoretical calculations, HPLC-MS/MS, SEM, TEM, CLMS, and ICP‑OES. Electrostatic interaction (E =  - 64.24 kcal/mol) between PEG@PDA@CaP and wheat leaves imparts DIF-PE with exceptional foliar deposition and adhesion. Compared to commercialized difenoconazole emulsion (DIF-EW), DIF-PE achieved 79.73% greater foliar deposition and 63.84% higher rainfastness. Enhanced deposition and penetration, together with the synergistic transport facilitated by PEG@PDA@CaP, collectively promoted more efficient downward delivery of difenoconazole, root and stem difenoconazole concentrations in treated plants were 6.95-fold and 2.34-fold higher than in controls at 24 h, respectively. Ultimately, DIF-PE improved the control efficacy against wheat crown rot by 19.15% relative to DIF-EW, with no adverse effects on plant growth. This nanocarrier-formulation system significantly improved the efficacy of conventional formulations, and broadened the applicability of nanocarriers, providing a powerful strategy for green management of crop diseases.