Machine learning and genetic algorithm-guided directed evolution for the development of antimicrobial peptides.

INTRODUCTION: Antimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics, possess a variety of potent biological activities and exhibit immunomodulatory effects that alleviate difficult-to-treat infections. Clarifying the structure-activity relationships of AMPs can direct the synthesis of desirable peptide therapeutics. OBJECTIVES: In this study, the lipopolysaccharide-binding domain (LBD) was identified through machine learning-guided directed evolution, which acts as a functional domain of the anti-lipopolysaccharide factor family of AMPs identified from Marsupenaeus japonicus. METHODS: LBDA-D was identified as an output of this algorithm, in which the original LBDMj sequence was the input, and the three-dimensional solution structure of LBDB was determined using nuclear magnetic resonance. Furthermore, our study involved a comprehensive series of experiments, including morphological studies and in vitro and in vivo antibacterial tests. RESULTS: The NMR solution structure showed that LBDB possesses a circular extended structure with a disulfide crosslink at the terminus and two 310-helices and exhibits a broad antimicrobial spectrum. In addition, scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that LBDB induced the formation of a cluster of bacteria wrapped in a flexible coating that ruptured and consequently killed the bacteria. Finally, coinjection of LBDB, Vibrio alginolyticus and Staphylococcus aureus in vivo improved the survival of M. japonicus, demonstrating the promising therapeutic role of LBDB for treating infectious disease. CONCLUSIONS: The findings of this study pave the way for the rational drug design of activity-enhanced peptide antibiotics.

Identification and functional analysis of a serine protease inhibitor using machine learning strategy.

In the intricate realm of animal biology, a multitude of vital processes heavily rely on precisely orchestrated proteinase cascades, but the potential for havoc makes proteinase inhibitors indispensable, with serine proteinase inhibitors (serpins) at the forefront, serving as custodians of homeostasis and participating in various critical biological processes. Importantly, there are still many unexplored facets of serpin functionality. In this study, we focused on the serpin family proteins from Marsupenaeus japonicus, utilizing a fine-tuned pretrained protein language model. This approach led to the identification and evolutionary validation of 28 serpins, one of which, referred to as Mjserpin-1, was both computationally and experimentally demonstrated to show potential as an antiviral and apoptosis inhibitor. Our research unveils exciting prospects for the fusion of state-of-the-art artificial intelligence and rich bioinformatics, holding the promise of significant discoveries that could pave the way for future therapeutic advancements.

Metagenomic exploration of the rhizosphere soil microbial community and their significance in facilitating the development of wild-simulated ginseng.

Panax ginseng, a prized medicinal herb, has faced increasingly challenging field production due to soil degradation and fungal diseases in Northeast China. Wild-simulated cultivation has prevailed because of its sustainable soil management and low disease incidence. Despite the recognized benefits of rhizosphere microorganisms in ginseng cultivation, their genomic and functional diversity remain largely unexplored. In this work, we utilized shotgun metagenomic analysis to reveal that Pseudomonadota, Actinomycetota, and Acidobacteriota were dominant in the ginseng rhizobiome and recovered 14 reliable metagenome-assembled genomes. Functional analysis indicated an enrichment of denitrification-associated genes, potentially contributing to the observed decline in soil fertility, while genes associated with aromatic carbon degradation may be linked to allelochemical degradation. Further analysis demonstrated enrichment of Actinomycetota in 9-year-old wild-simulated ginseng (WSG), suggesting the need for targeted isolation of Actinomycetota bacteria. Among these, at least three different actinomycete strains were found to play a crucial role in fungal disease resistance, with Streptomyces spp. WY144 standing out for its production of actinomycin natural products active against the pathogenic fungus Ilyonectria robusta. These findings not only enhance our understanding of the rhizobiome of WSG but also present promising avenues for combating detrimental fungal pathogens, underscoring the importance of ginseng in both medicinal and agricultural contexts.IMPORTANCEWild-simulated ginseng, growing naturally without human interference, is influenced by its soil microbiome. Using shotgun metagenomics, we analyzed the rhizospheric soil microbiome of 7- and 9-year-old wild-simulated ginseng. The study aimed to reveal its composition and functions, exploring the microbiome's key roles in ginseng growth. Enrichment analysis identified Streptomycetes in ginseng soil, with three strains inhibiting plant pathogenic fungi. Notably, one strain produced actinomycins, suppressing the ginseng pathogenic fungus Ilyonectria robusta. This research accelerates microbiome application in wild-simulated ginseng cultivation, offering insights into pathogen protection and supporting microbiome utilization in agriculture.

A Streptomyces species from the ginseng rhizosphere exhibits biocontrol potential.

Plants and their associated microbes live in complicated, changeable, and unpredictable environments. They usually interact with each other in many ways through multidimensional, multiscale, and multilevel coupling manners, leading to challenges in the coexistence of randomness and determinism or continuity and discreteness. Gaining a deeper understanding of these diverse interaction mechanisms can facilitate the development of data-mining theories and methods for complex systems, coupled modeling for systems with different spatiotemporal scales and functional properties, or even a universal theory of information and information interactions. In this study, we use a "closed-loop" model to present a plant-microbe interaction system and describe the probable functions of microbial natural products. Specifically, we report a rhizosphere species, Streptomyces ginsengnesis G7, which produces polyketide lydicamycins and other active metabolites. Interestingly, these distinct molecules have the potential to function both as antibiotics and as herbicides for crop protection. Detailed laboratory experiments conducted in Arabidopsis (Arabidopsis thaliana), combined with a comprehensive bioinformatics analysis, allow us to rationalize a model for this specific plant-microbe interaction process. Our work reveals the benefits of exploring otherwise neglected resources for the identification of potential functional molecules and provides a reference to better understand the system biology of complex ecosystems.

Comparative transcriptome analysis revealed that auxin and cell wall biosynthesis play important roles in the formation of hollow hearts in cucumber.

BACKGROUND: Hollow heart is a kind of physiological defect that seriously affects the yield, quality, and economic value of cucumber. However, the formation of hollow hearts may relate to multiple factors in cucumber, and it is necessary to conduct analysis. RESULTS: In this study, hollow and non-hollow fruits of cucumber K07 were used for comparative transcriptome sequencing and analysis. 253 differentially expressed genes and 139 transcription factors were identified as being associated with the formation of hollow hearts. Hormone (auxin) signaling and cell wall biosynthesis were mainly enriched in GO and KEGG pathways. Expression levels of key genes involved in indole-3-acetic acid biosynthesis in carpel were lower in the hollow fruits than non-hollow fruits, while there was no difference in the flesh. The concentration of indole-3-acetic also showed lower in the carpel than flesh. The biosynthetic pathway and content analysis of the main components of the cell wall found that lignin biosynthesis had obvious regularity with hollow heart, followed by hemicellulose and cellulose. Correlation analysis showed that there may be an interaction between auxin and cell wall biosynthesis, and they collectively participate in the formation of hollow hearts in cucumber. Among the differentially expressed transcription factors, MYB members were the most abundant, followed by NAC, ERF, and bHLH. CONCLUSIONS: The results and analyses showed that the low content of auxin in the carpel affected the activity of enzymes related to cell wall biosynthesis at the early stage of fruit development, resulting in incomplete development of carpel cells, thus forming a hollow heart in cucumber. Some transcription factors may play regulatory roles in this progress. The results may enrich the theory of the formation of hollow hearts and provide a basis for future research.

Offline Model-Based Adaptable Policy Learning for Decision-Making in Out-of-Support Regions.

In reinforcement learning, a promising direction to avoid online trial-and-error costs is learning from an offline dataset. Current offline reinforcement learning methods commonly learn in the policy space constrained to in-support regions by the offline dataset, in order to ensure the robustness of the outcome policies. Such constraints, however, also limit the potential of the outcome policies. In this paper, to release the potential of offline policy learning, we investigate the decision-making problems in out-of-support regions directly and propose offline Model-based Adaptable Policy LEarning (MAPLE). By this approach, instead of learning in in-support regions, we learn an adaptable policy that can adapt its behavior in out-of-support regions when deployed. We give a practical implementation of MAPLE via meta-learning techniques and ensemble model learning techniques. We conduct experiments on MuJoCo locomotion tasks with offline datasets. The results show that the proposed method can make robust decisions in out-of-support regions and achieve better performance than SOTA algorithms.

[Research on classification method of multimodal magnetic resonance images of Alzheimer's disease based on generalized convolutional neural networks].

Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. Neuroimaging based on magnetic resonance imaging (MRI) is one of the most intuitive and reliable methods to perform AD screening and diagnosis. Clinical head MRI detection generates multimodal image data, and to solve the problem of multimodal MRI processing and information fusion, this paper proposes a structural and functional MRI feature extraction and fusion method based on generalized convolutional neural networks (gCNN). The method includes a three-dimensional residual U-shaped network based on hybrid attention mechanism (3D HA-ResUNet) for feature representation and classification for structural MRI, and a U-shaped graph convolutional neural network (U-GCN) for node feature representation and classification of brain functional networks for functional MRI. Based on the fusion of the two types of image features, the optimal feature subset is selected based on discrete binary particle swarm optimization, and the prediction results are output by a machine learning classifier. The validation results of multimodal dataset from the AD Neuroimaging Initiative (ADNI) open-source database show that the proposed models have superior performance in their respective data domains. The gCNN framework combines the advantages of these two models and further improves the performance of the methods using single-modal MRI, improving the classification accuracy and sensitivity by 5.56% and 11.11%, respectively. In conclusion, the gCNN-based multimodal MRI classification method proposed in this paper can provide a technical basis for the auxiliary diagnosis of Alzheimer's disease.

Transcriptome, intestinal microbiome and histomorphology profiling of differences in the response of Chinese sea bass (Lateolabrax maculatus) to Aeromonas hydrophila infection.

The Chinese sea bass (Lateolabrax maculatus) is an important aquaculture fish, but diseases caused by Aeromonas hydrophila have led to severe economic losses to the aquaculture industry in recent years. To date, only a few studies have focused on the relationship between the intestinal immune response and changes in intestinal microbes by A. hydrophila infection. Here, we report the transcriptome and intestinal changes in infected sea bass. Histopathological results showed that severe steatosis and vacuolation occurred in the liver and that the intestinal villi and mesentery were seriously affected after infection. By extracting total RNA from intestinal tissue and studying the transcriptome profile, 1,678 genes (1,013 upregulated and 665 downregulated) were identified as significantly differentially expressed genes (DEGs). These genes are involved in many immune-related signalling pathways, such as the NOD-like receptor, C-type lectin receptor, and Toll-like receptor signalling pathways. Moreover, the intestinal microbes of sea bass changed significantly after infection. Interestingly, at the genus level, there was an increase in Serratia, Candida arthromitus and Faecalibacterium as well as a decrease in Akkermansia and Parabacteroides after infection. The results also indicated that some of the DEGs involved in the immune response were related to the genus level of intestinal microbiota. Finally, there was a relationship between gene expression patterns and the bacterial structure in the host intestine. Our study provides a reference for the study of the immune response and particular functions of intestinal microbes of sea bass after pathogen infection.

Genome-Wide Identification and Functional Analysis of the Roles of SAUR Gene Family Members in the Promotion of Cucumber Root Expansion.

Auxin serves as an essential regulator of the expression of many different genes in plants, thereby regulating growth and development. The specific functional roles of members of the SAUR (small auxin-up RNA) auxin early response gene family in the development of cucumber plants, however, remain to be fully clarified. Here, 62 SAUR family genes were identified, followed by their classification into 7 groups that included several functionally associated cis-regulatory elements. Phylogenetic tree and chromosomal location-based analyses revealed a high degree of homology between two cucumber gene clusters and other plants in the Cucurbitaceae family. These findings, together with the results of an RNA-seq analysis, revealed high levels of CsSAUR31 expression within the root and male flower tissues. Plants overexpressing CsSAUR31 exhibited longer roots and hypocotyls. Together, these results provide a basis for further efforts to explore the roles that SAUR genes play in cucumber plants, while also expanding the pool of available genetic resources to guide research focused on plant growth and development.

Nano-Polycrystalline Cu Layer Interlaced with Ti3+-Self-Doped TiO2 Nanotube Arrays as an Electrocatalyst for Reduction of Nitrate to Ammonia.

The electrochemical nitrate reduction reaction (NO3RR) is considered as a promising strategy to degrade nitrate-containing wastewater and synthesize recyclable ammonia at atmospheric pressure and room temperature. In this work, the copper oxides-derived nano-polycrystalline Cu (NPC Cu) was integrated with Ti3+-self-doped TiO2 nanotube arrays (NTA) to fabricate the NPC Cu/H-TiO2 NTA. Ti3+-self-doped TiO2 NTAs and the NPC Cu facilitate electron transfer and mass transportation and create abundant active sites. The unique nanostructure in which Cu nano-polycrystals interlace with the TiO2 nanotube accelerates the electron transfer from the substrate to surface NPC Cu. The density functional theory calculations confirm that the built-in electric field between Cu and TiO2 improves the adsorption characteristic of the NPC Cu/H-TiO2 NTA, thereby converting the endothermic NO3- adsorption step into an exothermic process. Therefore, the high NO3- conversion of 98.97%, the Faradic efficiency of 95.59%, and the ammonia production yield of 0.81 mg cm-2 h-1 are achieved at -0.45 V vs reversible hydrogen electrode in 10 mM NaNO3 (140 mg L-1)-0.1 M Na2SO4. This well-designed NPC Cu/H-TiO2 NTA as an effective electrocatalyst for the 8e- NO3RR possesses promising potential in the applications of ammonia production.

Zn and N co-doped three-dimensional honeycomb-like carbon featured with interconnected nano-pools for dendrite-free zinc anode.

The zinc-ion battery (ZIB) has been extensively researched as one of the promising electrochemical power sources. However, the problem of Zn-dendrite formation during repeated plating and stripping process seriously hinders the development of ZIBs. Herein, three-dimensional (3D) honeycomb-like porous carbon (HPC) with co-doping of zinc and nitrogen is prepared through confining growth of nanoscale zeolite imidazole framework-8 (ZIF-8) on the well-designed nano-pools walls of HPC followed by pyrolysis at 600 ℃ to obtain the final product ZnN/HPC-600, which exhibits large surface area and abundant zincophilic interfaces, ensuring homogeneous distribution of electronic field and low polarization during cycling process. Importantly, ZnN/HPC-600 facilitates the uniform distribution and migration of Zn2+ in this nano-pools structure, avoiding the growth of dendritic Zn crystal during charging stage. The symmetric and asymmetric cells with Zn/ZnN/HPC-600 anodes are assembled, demonstrating excellent cycling reversibility, good rate performance and long-term stability. Besides, a Zn||MnO2 full cell with Zn/ZnN/HPC-600 anode also exhibits robust cycling stability, fast reaction kinetics and almost 100 % coulombic efficiency. This work offers a novel and efficient carbonaceous nano-pools strategy to realize dendrite-free zinc anode in ZIBs.

Dietary macrominerals: Updated review of their role and orchestration in human nutrition throughout the life cycle with sex differences.

Macrominerals play vital roles in a multitude of physiologic systems. A myriad of biochemical reactions are dependent on or affected by these electrolytes. The current review attempts to identify the role of macrominerals as calcium, phosphorus, magnesium, sodium, potassium and sulfur in human health, in addition to their absorption and homeostasis inside the body. We also focused on their amount in major food sources and the recommended daily intake of each macromineral. In addition, a deep insight into the orchestration of the 6 different macrominerals' requirements is presented across the human life cycle, beginning from fertility and pregnancy, and reaching adulthood and senility, with insight on interactions among them and underlying action mechanisms. The effect of sex is also presented for each mineral at each life stage to highlight the different daily requirements and/ or effects. The current review identified the role of macrominerals in human health, in addition to their absorption and homeostasis in the body. Based on the in-depth understanding of the factors influencing the metabolism of macrominerals, we could better explore their safety and possible therapeutic potential in specific disorders. There is still a need to precisely demonstrate the bioavailability of macrominerals from various types of functional food.

Industrial application of antimicrobial peptides based on their biological activity and structure-activity relationship.

Last several years, a rapid increase in drug resistance to traditional antibiotics has driven the emergence and development of antimicrobial peptides (AMPs). AMPs have also gained considerable attention from scientists due to their high potency in combatting infectious pathogens. A subset of analogues and their derivatives with specific targets have been successfully designed based on natural peptide patterns. In this review, scientific knowledge on the mechanisms of action related to biological activity and structure-activity relationship (SAR) of AMPs are summarized, and the biological applications in several important fields are critically discussed. SAR shows that the positive charge, secondary structure, special amino acid residues, hydrophobicity, and helicity of AMPs are closely related to their biological activities. The combination of nanotechnology, bioinformatics, and genetic engineering can accelerate to achieve the application of AMPs as effective, safe, economical, and nonresistant antimicrobial agents in medicine, the food and feed industries, and agriculture in coming years. Given the intense interest in AMPs, further investigations are needed in the future to evaluate the specific structure and function that make their use favorable in several industries. This review may provide a comprehensive reference for future studies on chemical modifications, mechanistic exploration, and applications of AMPs.

Current and potential trends in the bioactive properties and health benefits of Prunus mume Sieb. Et Zucc: a comprehensive review for value maximization.

Prunus mume Sieb. Et Zucc (P. mume) is an acidic fruit native to China (named Chinese Mei or greengage plum). It is currently cultivated in several Asian countries, including Japan ("Ume"), Korea (Maesil), and Vietnam (Mai or Mo). Due to its myriad nutritional and functional properties, it is accepted in different countries, and its characteristics account for its commercialization. In this review, we summarize the information on the bioactive compounds from the fruit of P. mume and their structure-activity relationships (SAR); the pulp has the highest enrichment of bioactive chemicals. The nutritional properties of P. mume and the numerous uses of its by-products make it a potential functional food. P. mume extracts exhibit antioxidant, anticancer, antimicrobial, and anti-hyperuricaemic properties, cardiovascular protective effects, and hormone regulatory properties in various in vitro and in vivo assays. SAR shows that the water solubility, molecular weight, and chemical conformation of P. mume extracts are closely related to their biological activity. However, further studies are needed to evaluate the fruit's potential nutritional and functional therapeutic mechanisms. The industrial process of large-scale production of P. mume and its extracts as functional foods or nutraceuticals needs to be further optimized.

Size-dependent toxicological effects of polystyrene microplastics in the shrimp Litopenaeus vannamei using a histomorphology, microbiome, and metabolic approach.

Due to the wide application of plastic products in human life, microplastic pollution in water has recently attracted more attention. Many studies have revealed the size-dependent toxicity of microplastics. Here, we investigated the toxicological effects of polystyrene microplastics (PS-MPs) on the white leg shrimp, Litopenaeus vannamei, a profitable aquaculture species, using a comprehensive histomorphological, microbiome, and metabolomic approach to verify whether smaller particles are more toxic than larger particles. L. vannamei were experimentally exposed to water containing PS-MPs of four sizes (0.1, 1.0, 5.0, and 20.0 µm) for 24 h at 10 mg/L (acute experiment) and 12 d at 1 mg/L (subchronic experiment). After 24 h of acute exposure, PS-MP accumulation in shrimp indicated that the ingestion and egestion of PS-MPs had a size-dependent effect, and smaller particles were more bioavailable. The tissue morphological results of subchronic experiments showed that, for the guts and gills, the smaller sizes of the PS-MPs exhibited greater damage. In addition, 16 S rRNA gene amplicon sequencing showed that the alpha diversity was higher under larger PS-MP exposure. Correlated with changes in intestinal bacteria, we found a greater enrichment of metabolic pathways in hemolymph proteins and metabolites in larger PS-MP groups, such as "arginine and proline metabolism", "protein digestion and absorption", "lysine degradation". Interestingly, the activity or content of biomarkers of oxidative stress showed a peak at 1 µm and 5 µm. Under specific sizes of PS-MPs, the abundance of the pathogen Vibrio and probiotic bacteria Rhodobacter (5-µm) and Bacillus and Halomonas (1-µm) were simultaneously enriched. Our results indicated that PS-MP exposure can cause size-dependent damage to shrimp, yet specific particle size can be influential differently in regard to some research indicators. Therefore, it can enhance our comprehensive understanding of the impacts of microplastics on shrimp health and suggests that specific particle size should be considered when assessing the size-dependent toxicity of microplastics.

Parallel processing of radiation measurements and radiation video optimization.

In this study, we propose a parallel processing method for analyzing video-image radiation-response signals and suppressing radiation noise. We studied the linear-representation law of various image-information components on the radiation dose rate. Subsequently, the simulation images were used to examine the response-signal extract and radiation-noise suppression. The results indicate that the majority of response signals in the global image comprise forward superposition. The peak signal-to-noise ratio of the red channel was significantly improved when the noise signal-substitution algorithm and median filter were applied successively. Real-time radiation dose-rate measurements and clear images under irradiation can be obtained simultaneously.

Grain Boundary Engineering in Ta-Doped Garnet-Type Electrolyte for Lithium Dendrite Suppression.

Solid-state lithium batteries (SSLBs) based on Ta-doped Li6.5La3Zr1.5Ta0.5O12 (LLZTO) suffer from lithium dendrite growth, which hinders their practical application. Herein, first principles simulations indicate that the Ta element prefers to segregate along grain boundaries in the form of Ta2O5 precipitates due to a high energy difference induced by Ta doping. Grain boundary engineering is employed to regulate the distribution of the Ta element and enhance the density of LLZTO by introducing the La2O3 additive. The sufficient La2O3 additive reacts with the Ta2O5 precipitates, while the residual La2O3 nanoparticles fill up void defects, promoting the homogeneous distribution of the Ta element and improving the relative density to ∼98%. Critical current density of the symmetric Li battery reaches 2.12 mA·cm-2 at room temperature with the solid-state electrolyte (LLZTO + 5 wt % La2O3), which increases by 41% compared to pure LLZTO. SSLBs with the LiFePO4 cathode achieve a stable cycling performance with a discharge capacity of 138.6 mA·h·g-1 after 400 cycles at 0.2 C. This work provides theoretical insights into the distribution of Ta-doped LLZTO and inhibits lithium dendrite growth through grain boundary engineering.

Recent two-year advances in anti-dengue small-molecule inhibitors.

Dengue is an acute tropical infectious disease transmitted by mosquitoes, which has posed a major challenge to global public health. Unfortunately, there is a lack of clinically proven dengue-specific drugs for its prevention and treatment. As the pathogenesis of dengue has not been fully elucidated, the development of specific drugs is seriously hindered. This article briefly describes the pathogenesis of dengue fever, the molecular characteristics, and epidemiology of dengue virus, and focuses on the potential small-molecule inhibitors of dengue virus, including on-target and multi-targeted inhibitors, which have been reported in the past two years.

Style transfer in conditional GANs for cross-modality synthesis of brain magnetic resonance images.

Magnetic resonance imaging (MRI) has become one of the most standardized and widely used neuroimaging protocols in the detection and diagnosis of neurodegenerative diseases. In clinical scenarios, multi-modality MR images can provide more comprehensive information than single modality images. However, high-quality multi-modality MR images can be difficult to obtain in the actual diagnostic process due to various uncertainties. Efficient methods of modality complement and synthesis have aroused increasing attention in the research community. In this article, style transfer is introduced into conditional generative adversarial networks (cGAN) architecture. A cGAN model with hierarchical feature mapping and fusion (ST-cGAN) is proposed to address the cross-modality synthesis of MR images. In order to surmount the sole focus on the pixel-wise similarity as most cGAN-based methods do, the proposed ST-cGAN takes advantage of the style information and applies it to the synthetic image's content structure. Taking images of two modalities as conditional input, ST-cGAN extracts different levels of style features and integrates them with the content features to form the style-enhanced synthetic image. Furthermore, the proposed model is made robust to random noise by adding noise input to the generator. A comprehensive analysis is performed by comparing the proposed ST-cGAN with other state-of-the-art baselines based on four representative evaluation metrics. The experimental results on the IXI (Information eXtraction from Images) dataset verify the validity of the ST-cGAN from different evaluation perspectives.

Persistence behavior of chlorpyrifos and biological toxicity mechanism to cucumbers under greenhouse conditions.

Chlorpyrifos, a broadly utilized insecticide, inhibits many cellular and physiological processes in plants. Here, the phyto-toxicity of chlorpyrifos on cucumber plants, as well as the dissipation kinetics of chlorpyrifos in leaves, were investigated. Those results showed that chlorpyrifos accumulated primarily in the leaves under normal agrochemical spraying conditions with the half-lives among 2.48-4.59 days. Residues of the primary metabolite, 3,5,6-trichloro-2-pyridinol (TCP), rapidly accumulated in plant tissues and soil with chlorpyrifos degradation. The application amount of chlorpyrifos had a significant effect on the persistence of chlorpyrifos and TCP in both plant and soil environments. Chlorpyrifos generated excessive reactive oxygen species (ROS) and malondialdehyde (MDA), which led to oxidative damage. High chlorpyrifos stress even inhibited antioxidant enzymes. The photosynthetic system and gas exchange were suppressed, which ultimately lead to inefficient light use under chlorpyrifos stress. Morphological results revealed that chlorpyrifos induced membrane damage and harmed organelles such as mitochondria and chloroplast. Noninvasive micro-test technology (NMT) showed that chlorpyrifos promoted intracellular Ca2+ influx and efflux of H+ and K+. The Ca2+ influx was significantly stimulated after both high and low chlorpyrifos treatment with the minimum value of - 336.33 pmol·cm-2·s-1 at 258 s and - 155.68 pmol·cm-2·s-1 at 288 s, respectively. Chlorpyrifos stress reversed the H+ influx to an efflux in cucumber mesophyll with the mean value of 0.45 ± 0.03 pmol·cm-2·s-1 and 0.19 ± 0.03 pmol·cm-2·s-1 in cucumber plants under low and high chlorpyrifos stress. High chlorpyrifos stress dramatically increase K+ efflux in cucumber leaves by 13.68 times higher than the control. We suggest that ion homeostasis destruction, accompanied by ROS, resulted in oxidative damage to the mesophyll cell of cucumber seedlings.