This study aimed to investigate the correlation between changes in intestinal toxicity and compositional alterations of Euphorbiae Ebracteolatae Radix(commonly known as Langdu) before and after milk processing, and to explore the detoxification mechanism of milk processing. Mice were intragastrically administered the 95% ethanol extract of raw Euphorbiae Ebracteolatae Radix, milk-decocted(milk-processed), and water-decocted(water-processed) Euphorbiae Ebracteolatae Radix. Fecal morphology, fecal water content, and the release levels of inflammatory cytokines tumor necrosis factor-α(TNF-α) and interleukin-1β(IL-1β) in different intestinal segments were used as indicators to evaluate the effects of different processing methods on the cathartic effect and intestinal inflammatory toxicity of Euphorbiae Ebracteolatae Radix. LC-MS/MS was employed to analyze the small-molecule components in the raw product, the 95% ethanol extract of the milk-processed product, and the milky waste(precipitate) formed during milk processing, to assess the impact of milk processing on the chemical composition of Euphorbiae Ebracteolatae Radix. The results showed that compared with the blank group, both the raw and water-processed Euphorbiae Ebracteolatae Radix significantly increased the fecal morphology score, fecal water content, and the release levels of TNF-α and IL-1β in various intestinal segments(P<0.05). Compared with the raw group, all indicators in the milk-processed group significantly decreased(P<0.05), while no significant differences were observed in the water-processed group, indicating that milk, as an adjuvant in processing, plays a key role in reducing the intestinal toxicity of Euphorbiae Ebracteolatae Radix. Mass spectrometry results revealed that 29 components were identified in the raw product, including 28 terpenoids and 1 acetophenone. The content of these components decreased to varying extents after milk processing. A total of 28 components derived from Euphorbiae Ebracteolatae Radix were identified in the milky precipitate, of which 27 were terpenoids, suggesting that milk processing promotes the transfer of toxic components from Euphorbiae Ebracteolatae Radix into milk. To further investigate the effect of milk adjuvant processing on the toxic terpenoid components of Euphorbiae Ebracteolatae Radix, transmission electron microscopy(TEM) was used to observe the morphology of self-assembled casein micelles(the main protein in milk) in the milky precipitate. The micelles formed in casein-terpenoid solutions were characterized using particle size analysis, fluorescence spectroscopy, ultraviolet spectroscopy, and Fourier-transform infrared(FTIR) spectroscopy. TEM observations confirmed the presence of casein micelles in the milky precipitate. Characterization results showed that with increasing concentrations of toxic terpenoids, the average particle size of casein micelles increased, fluorescence intensity of the solution decreased, the maximum absorption wavelength in the UV spectrum shifted, and significant changes occurred in the infrared spectrum, indicating that interactions occurred between casein micelles and toxic terpenoid components. These findings indicate that the cathartic effect of Euphorbiae Ebracteolatae Radix becomes milder and its intestinal inflammatory toxicity is reduced after milk processing. The detoxification mechanism is that terpenoid components in Euphorbiae Ebracteolatae Radix reassemble with casein in milk to form micelles, promoting the transfer of some terpenoids into the milky precipitate.
Animals ; Mice ; Milk/chemistry* ; Drugs, Chinese Herbal/chemistry* ; Male ; Tumor Necrosis Factor-alpha/immunology* ; Intestines/drug effects* ; Interleukin-1beta/immunology* ; Tandem Mass Spectrometry ; Female

Acute pancreatitis (AP) is a severe inflammatory disease characterized by self-digestion of pancreatic tissue and inflammatory responses. Recent studies have revealed a close connection between gut microbiota and AP. The gut microbiota community, a complex ecosystem composed of trillions of microorganisms, is closely associated with various physiological activities of the host, including metabolic processes, immune system regulation, and intestinal structure maintenance. However, in patients with AP, dysbiosis of the gut microbiota are believed to play a key role in the occurrence and progression of the disease. This dysbiosis not only impairs the integrity of the intestinal barrier, but may also exacerbate inflammatory responses through multiple mechanisms, thereby affecting the severity of the disease and patient' clinical prognosis. This article reviews the mechanisms of action of gut microbiota in AP, explores how gut microbiota dysbiosis affects disease progression, and evaluates current clinical treatment methods to regulate intestinal flora, including probiotic supplementation, fecal microbiota transplantation, antibiotic therapy, and early enteral nutrition. In addition, this article discusses the efficacy and safety of the aforementioned therapeutic approaches, and outlines future research directions, aiming to provide novel perspectives and strategies for the diagnosis, treatment and prognostic evaluation of AP. Through in-depth understanding the interaction between gut microbiota and AP, it is expected that more precise and personalized therapeutic regimens will be developed to improve patients' quality of life and clinical outcomes.
Humans ; Gastrointestinal Microbiome ; Dysbiosis ; Pancreatitis/microbiology* ; Fecal Microbiota Transplantation ; Probiotics/therapeutic use* ; Acute Disease ; Anti-Bacterial Agents/therapeutic use* ; Enteral Nutrition

We have isolated an intestinal probiotic strain, Pediococcus acidilactici HRQ-1. To improve its gastrointestinal fluid tolerance, transportation and storage stability, and slow-release properties, we employed the extrusion method to prepare the microcapsules with P. acidilactici HRQ-1 as the core material and sodium alginate and chitosan as the wall material. The optimal conditions for preparing the microcapsules were determined by single factor and orthogonal tests, and the optimal ratio was determined by taking the embedding rate, survival rate, storage stability, gastrointestinal fluid tolerance, and release rate as the evaluation indexes. The results showed that under the optimal embedding conditions, the embedding rate reached (89.60±0.02)%. Under the optimal formula of freeze-drying protective agent, the freeze-drying survival rate reached (76.42±0.13)%, and the average size of the microcapsules produced was (1.16±0.03) mm. The continuous gastrointestinal fluid simulation experiments confirmed that the microcapsules ensured the viable bacterial count and can slowly release bacteria in the intestinal fluid. The curve of the viable bacterial count during storage at 4 ℃ and room temperature indicated that the prepared microcapsules achieved strains' live number protection. The formula and preparation process of P. acidilactici microcapsules may provide a technological reserve for the preparation of more live bacterial drugs in the future.
Pediococcus acidilactici/chemistry* ; Probiotics/chemistry* ; Capsules/chemistry* ; Alginates/chemistry* ; Chitosan/chemistry* ; Drug Compounding/methods* ; Glucuronic Acid/chemistry* ; Hexuronic Acids/chemistry* ; Freeze Drying

Uric acid (UA) is the final metabolite of purines in the human body. An imbalance in UA production and excretion that disrupts homeostasis leads to elevated blood UA levels and the development of hyperuricemia (HUA). Approximately one-third of UA is excreted through the intestinal tract. As a crucial component of the intestinal microenvironment, the gut microbiota plays a pivotal role in regulating blood UA levels. Alterations or imbalances in gut microbiota composition are linked to the onset of HUA, which implies the potential of gut microbiota as a novel target for the prevention and treatment of HUA. This review introduces the occurrence mechanism and damage of hyperuricemia, examines the association between HUA and the gut microbiota and their metabolites, and explores the molecular mechanisms underlying gut microbiota-targeted therapies for HUA. Furthermore, it discusses the potential applications of probiotics, prebiotics, and traditional Chinese medicine (including both single herbs and compound formulas) with UA-lowering effects, along with cutting-edge technologies such as fecal microbiota transplantation and machine learning in HUA treatment. This review provides valuable perspectives and strategies for improving the prevention and treatment of HUA.
Hyperuricemia/microbiology* ; Humans ; Gastrointestinal Microbiome/physiology* ; Probiotics/therapeutic use* ; Uric Acid/blood* ; Fecal Microbiota Transplantation ; Prebiotics ; Medicine, Chinese Traditional

Diabetic chronic wounds are characterized by difficult healing, recurrent progression, and high rates of disability and mortality, which make their clinical treatment a medical challenge urgent to be addressed. However, the complex local microenvironment conditions of chronic wounds, such as high protease activity and persistent inflammatory responses, result in low bioavailability of exogenous cytokines (e.g., chemokine CXCL12) at the wound site, limiting their clinical application. In this study, we utilized Lactobacillus plantarum WCFS1 as the chassis to develop an efficient CXCL12 delivery system based on synthetic biology. Subsequently, we evaluated the role of the engineered probiotic strain in promoting the chronic wound healing in diabetic mice. Firstly, we fused the endogenous secretion signal peptide lp_3050 (SP_{lp_3050}) of L. plantarum WCFS1 and the commonly used secretion signal peptide usp45 (SP_usp45) of lactic acid bacteria with the reporter gene gusA and inserted them into the pTRK892-P_32(pgm) plasmid by molecular cloning. Then, we prepared the engineered strains and characterized the efficacy of the two signal peptides in driving the secretion of GusA. The results showed that SP_{lp_3050} efficiently drove the secretion of GusA in L. plantarum WCFS1, increasing the activity of GusA in the culture supernatant by nearly five times compared with that of SP_{lp_3050}. Further, we fused SP_{lp_3050} and codon-optimized CXCL12 gene to construct an engineered probiotic strain Lpw-CXCL12 for CXCL12 delivery. The results demonstrated that the content of CXCL12 in the culture supernatant reached (13.40±0.20) μg/mL. Finally, we found that the engineered probiotic strain Lpw-CXCL12 accelerated chronic wound healing in a diabetic mouse model. In conclusion, these results support an engineered probiotic strain in promoting diabetic chronic wound healing, providing a new strategy and technological foundation for the management of diabetic chronic wounds in the future.
Probiotics ; Animals ; Chemokine CXCL12/biosynthesis* ; Mice ; Wound Healing ; Lactobacillus plantarum/metabolism* ; Diabetes Mellitus, Experimental/complications* ; Male

Agriculture, the strategic cornerstone of national long-term stability, is undergoing a fundamental shift from resource-dependent to technology-driven, driven by global food security and ecological conservation needs. Traditional agriculture can no longer sustain the growing food demand. Scientific and technological advancements are fundamental guarantees for ensuring food supply security and are the primary driver for future agricultural development. This special issue compiles the latest research advancements from diverse experts, covering fields such as microbe-driven green agriculture, pesticide technology innovation, intelligent agricultural machinery, smart manufacturing, and molecular design breeding fundamentals. It aims to inspire researchers to explore cutting-edge directions in future agriculture, promote interdisciplinary collaboration and technological integration, and thereby drive innovative breakthroughs and industrial transformation in agricultural modernization.
Agriculture/methods* ; Crops, Agricultural/genetics* ; Food Supply ; Biotechnology ; Pesticides

To explore the feasibility of using UAV-LiDAR for measuring the leaf area index (LAI) of crop canopies, we employed UAV-LiDAR to scan sugarcane canopies during the tillering and elongation stages, acquiring canopy point cloud data. Subsequently, features such as average row height, projected row area, point cloud density at different canopy layers, and the ratios between these parameters were extracted. Three feature selection methods-partial least squares regression (PLSR), XGBoost feature importance (XGBoost-FI), and random forest-recursive feature elimination (RF-RFE)-were adopted to evaluate and identify the optimal input variables for modeling. With these selected variables, LAI inversion models were developed based on random forest (RF) and adaptive boosting (AdaBoost) algorithms, and their performance was assessed. Among the extracted features, the projected row area S_p and the total row point count C_total exhibited strong correlations with LAI, with correlation coefficients of 0.73 and 0.72, respectively. The AdaBoost-based LAI inversion model, using the projected row area S_p, average height H_avg, mid-layer point cloud density C_m, and total row point count C_total as input variables, achieved the best performance, with a coefficient of determination (R_v²) of 0.713 and a root mean square error (RMSE_v) of 0.25 on the validation set. This study provides an effective method for high-throughput acquisition of LAI in field crops, offering valuable scientific support for sugarcane field management and breeding efforts.
Plant Leaves/growth & development* ; Saccharum/growth & development* ; Algorithms ; Unmanned Aerial Devices ; Remote Sensing Technology/methods* ; Crops, Agricultural/growth & development*

Accurately obtaining the crop quantity and density is not only crucial for the demand-based input of water and fertilizer in the field but also vital for ensuring the yield and quality of crops. Aerial photography by unmanned aerial vehicles (UAVs) can quickly acquire the distribution image information of crops over a large area. However, the accurate recognition of a single type of dense targets is a huge challenge for most recognition algorithms. Taking banana seedlings as an example in this study, we captured the images of banana plantations by UAVs from high altitudes to explore an efficient recognition method for dense targets. We proposed a strategy of "cut-recognition-stitch" and constructed a counting method based on the improved Faster R-CNN algorithm. First, the images containing highly dense targets were cropped into a large number of image tiles according to different sizes (simulating different flight altitudes), and the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm was adopted to improve the image quality. A banana seedling dataset containing 36 000 image tiles was constructed. Then, the Faster R-CNN network with optimized parameters was used to train the banana seedling recognition model. Finally, the recognition results were reversely stitched together, and a boundary deduplication algorithm was designed to correct the final counting results to reduce the repeated recognition caused by image cropping. The results show that the recognition accuracy of the Faster R-CNN with optimized parameters for banana image datasets of different sizes can reach up to 0.99 at most. The deduplication algorithm can reduce the average counting error for the original aerial images from 1.60% to 0.60%, and the average counting accuracy of banana seedlings reaches 99.4%. The proposed method effectively addresses the challenge of recognizing dense small objects in high-resolution aerial images, providing an efficient and reliable technical solution for intelligent crop density monitoring in precision agriculture.
Musa/growth & development* ; Crops, Agricultural/growth & development* ; Algorithms ; Neural Networks, Computer ; Unmanned Aerial Devices ; Seedlings/growth & development* ; Image Processing, Computer-Assisted/methods* ; Photography ; Agriculture/methods*

Genetically modified (GM) crops, as a pivotal innovation in modern agriculture, exhibit significant advantages such as pest and disease resistance, herbicide tolerance, stress tolerance, and yield enhancement. However, their widespread adoption has been associated with potential ecological risks, including weediness of transgenic plants, gene flow, emergence of novel viral strains in virus-resistant crops, impacts on non-target organisms and soil ecosystems, and evolution of target pest resistance. This review focuses on the dual characteristics of GM crops, systematically examining their agronomic benefits and the underlying mechanisms of ecological risks. This review provides a theoretical foundation for optimizing the development of GM crops and ecological risk management, facilitating sustainable agricultural practices.
Plants, Genetically Modified/growth & development* ; Crops, Agricultural/growth & development* ; Ecosystem ; Ecology

Epigenetics refers to a heritable phenomenon that dynamically modulates gene expression without altering the DNA sequence, through molecular mechanisms such as DNA methylation, histone modification, non-coding RNA, chromatin remodeling, and RNA modifications. In plants, these modifications are extensively involved in key biological processes, including flowering time, gametogenesis, stress responses, and immune defenses. Over the past few decades, the research on epigenetics has gradually shifted from fundamental studies primarily conducted in Arabidopsis thaliana to investigations in various crop species such as rice and tomato. This transition has revealed the multifaceted roles of epigenetic regulation in shaping agronomic traits. This review integrates current knowledge of epigenetic regulatory mechanisms and their functions in plant responses to both biotic and abiotic stresses. Epigenetic editing tools such as CRISPR-dCas9 enable targeted DNA methylation or histone acetylation. Emerging transformation technologies, including magnetic nanoparticles and virus-based delivery systems, have the potential to overcome the bottlenecks of plant regeneration, offering new possibilities for precise epigenetic editing. In future agriculture, it is essential to further elucidate multi-layered epigenetic regulatory mechanisms at the single-cell level, develop efficient delivery systems, and leverage artificial intelligence to advance the application of epigenetic breeding for sustainable agricultural development.
Epigenesis, Genetic/genetics* ; Crops, Agricultural/genetics* ; Plant Breeding/methods* ; DNA Methylation/genetics* ; Gene Editing ; Disease Resistance/genetics* ; CRISPR-Cas Systems