Cervical Cancer Tissue Analysis Using Photothermal Midinfrared Spectroscopic Imaging.

Hyperspectral photothermal mid-infrared spectroscopic imaging (HP-MIRSI) is an emerging technology with promising applications in cervical cancer diagnosis and quantitative, label-free histopathology. This study pioneers the application of HP-MIRSI to the evaluation of clinical cervical cancer tissues, achieving excellent tissue type segmentation accuracy of over 95%. This achievement stems from an integrated approach of optimized data acquisition, computational data reconstruction, and the application of machine learning algorithms. The results are statistically robust, drawing from tissue samples of 98 cervical cancer patients and incorporating over 40 million data points. Traditional cervical cancer diagnosis methods entail biopsy, staining, and visual evaluation by a pathologist. This process is qualitative, subject to variations in staining and subjective interpretations, and requires extensive tissue processing, making it costly and time-consuming. In contrast, our proposed alternative can produce images comparable to those from histological analyses without the need for staining or complex sample preparation. This label-free, quantitative method utilizes biochemical data from HP-MIRSI and employs machine-learning algorithms for the rapid and precise segmentation of cervical tissue subtypes. This approach can potentially transform histopathological analysis by offering a more accurate and label-free alternative to conventional diagnostic processes.

iP3T: an interpretable multimodal time-series model for enhanced gait phase prediction in wearable exoskeletons.

Introduction: Wearable exoskeletons assist individuals with mobility impairments, enhancing their gait and quality of life. This study presents the iP3T model, designed to optimize gait phase prediction through the fusion of multimodal time-series data. Methods: The iP3T model integrates data from stretch sensors, inertial measurement units (IMUs), and surface electromyography (sEMG) to capture comprehensive biomechanical and neuromuscular signals. The model's architecture leverages transformer-based attention mechanisms to prioritize crucial data points. A series of experiments were conducted on a treadmill with five participants to validate the model's performance. Results: The iP3T model consistently outperformed traditional single-modality approaches. In the post-stance phase, the model achieved an RMSE of 1.073 and an R2 of 0.985. The integration of multimodal data enhanced prediction accuracy and reduced metabolic cost during assisted treadmill walking. Discussion: The study highlights the critical role of each sensor type in providing a holistic understanding of the gait cycle. The attention mechanisms within the iP3T model contribute to its interpretability, allowing for effective optimization of sensor configurations and ultimately improving mobility and quality of life for individuals with gait impairments.

A Novel Personalized Strategy for Hip Joint Flexion Assistance Based on Human Physiological State.

Soft exosuits have emerged as potent assistive tools for walking support and rehabilitation training. However, most existing soft exosuit systems rely on preset assistance modes, which may not accurately align with individual physiological states and movement requirements, leading to variable user experiences and efficacy. While existing human-in-the-loop (HIL) research predominantly focuses on optimizing metabolic cost and torque difference parameters, there is a notable absence of real-time monitoring methods that closely reflect the human body's physiological state and strategies that dynamically indicate walking efficiency. Motivated by this, we developed a novel personalized power-assist system. This system optimizes the power-assist output of the hip joint by monitoring the user's physiological and motion signals in real time, including heart rate (HR), blood oxygen saturation (SpO2), and inertial measurement unit (IMU) data, to assist hip flexion based on feedback. The findings from a metabolic expenditure trial demonstrate that the innovative soft exosuit, which is based on a Physiological State Monitoring Control (PSMC) system, achieves a reduction of 7.81% in metabolic expenditure during treadmill walking at a speed of 3.5 km/h compared to walking without the assistance of the exosuit. Additionally, during continuous exercise with varying intensities, the metabolic consumption level is reduced by 5.1%, 5.8%, and 8.2% at speeds of 2, 4, and 6 km per hour, respectively. These results support the design of a novel hip flexion-assisting soft exosuit, demonstrating that applying different assistance forces in consideration of different physiological states is a reasonable approach to reducing metabolic consumption.

Rapid Hyperspectral Photothermal Mid-Infrared Spectroscopic Imaging from Sparse Data for Gynecologic Cancer Tissue Subtyping.

Ovarian cancer detection has traditionally relied on a multistep process that includes biopsy, tissue staining, and morphological analysis by experienced pathologists. While widely practiced, this conventional approach suffers from several drawbacks: it is qualitative, time-intensive, and heavily dependent on the quality of staining. Mid-infrared (MIR) hyperspectral photothermal imaging is a label-free, biochemically quantitative technology that, when combined with machine learning algorithms, can eliminate the need for staining and provide quantitative results comparable to traditional histology. However, this technology is slow. This work presents a novel approach to MIR photothermal imaging that enhances its speed by an order of magnitude. This method resolves the longstanding trade-off between imaging resolution and data collection speed, enabling the reconstruction of high-quality, high-resolution images from undersampled data sets and achieving a 10X improvement in data acquisition time. We assessed the performance of our sparse imaging methodology using a variety of quantitative metrics, including mean squared error (MSE), structural similarity index (SSIM), and tissue subtype classification accuracies, employing both random forest and convolutional neural network (CNN) models, accompanied by Receiver Operating Characteristic (ROC) curves. Our statistically robust analysis, based on data from 100 ovarian cancer patient samples and over 65 million data points, demonstrates the method's capability to produce superior image quality and accurately distinguish between different gynecological tissue types with segmentation accuracy exceeding 95%. Our work demonstrates the feasibility of integrating rapid MIR hyperspectral photothermal imaging with machine learning in enhancing ovarian cancer tissue characterization, paving the way for quantitative, label-free, automated histopathology.

A framework for drought monitoring and assessment from a drought propagation perspective under non-stationary environments.

According to the coupled influence of climate variation and anthropogenic activities, hydro-meteorological variables are hard to keep stationary in a changing environment. Consequently, the efficacy of traditional standardized drought indices, predicated upon the assumption of stationarity, has been called into question. In China, the challenge of drought monitoring and declaration is exacerbated by the need for multiple drought indices covering meteorological, agricultural, hydrological, and groundwater aspects, often lacking real-time availability. To address these challenges, we developed a framework for drought monitoring and assessment from a drought propagation perspective. Central to this is the Nonstationary Integrated Drought Index (NIDI), which integrates responses from meteorological, agricultural, hydrological, and groundwater droughts, accounting for climate change and anthropogenic influences. First, we analyse the process of drought propagation to select the suitable time scale standardized drought index. Subsequently, significant large-scale climatic indices are selected through linear and nonlinear correlation analyses to identify climate anomalies. Anthropogenic influences are assessed using indicators such as the Normalized Difference Vegetation Index (NDVI), Impervious Surface Ratio (ISR), and population density (POP). Nonstationary probability models are then developed for precipitation, soil moisture, runoff, and groundwater series, incorporating climatic and human-induced factors. Finally, the NIDI is calculated using a D-vine copula model, with parameter estimation and updating facilitated by a genetic algorithm, representing the temporal dependence structure among the variables. A case study in the Hulu River Basin of western China validated the NIDI. Results showed that the NIDI effectively accounts for nonstationary hydro-meteorological variables due to climate change and human activities, accurately reproducing their time-dependent structure. Compared to conventional indices like SPI, SSI, SRI, and SGI, the NIDI identifies more extreme drought events. In conclusion, the presented NIDI offers a more comprehensive approach to drought identification, providing valuable insights for accurate drought detection and effective drought-related policy-making.

Multifunctional pressure and humidity sensor modulated by electrostatic interactions and hydrogen bonds for wearable health monitoring.

Breathing and urination, are vital physiological activities of the human body, continuous real-time monitoring of these physiological behaviors could offer timely feedback on an individual's health status. However, current monitoring techniques predominantly rely on cumbersome and intricate medical apparatuses, posing challenges in adapting to the diverse requirements of multi-scenario detection. Consequently, there is a growing interest in developing wearable devices capable of monitoring breathing and urination. In this work, we developed a multifunctional sensor integrating humidity and pressure sensing modes using a simple dip-coating process. By introducing sodium carboxymethyl cellulose and conductive polyaniline hybrid intercalation between MXene layers, a stable conductive network is established through hydrogen bonds and electrostatic interactions among materials. The overall electromechanical properties of the composites will be well improved. And, the effects of different conductive filler ratios and the number of dipping times on the construction of conductive networks are investigated. The multifunctional sensor exhibited improved sensing characteristics, including detecting pressures up to 532 kPa and a sensitivity of 19.58 kPa-1. Furthermore, it also demonstrates good humidity-sensing capabilities. Tests on volunteers demonstrated the potential in the detection of breathing and urination. In addition, the sensors are capable of transmitting Morse code. This interesting application will offer the possibility of normal communication for people with speech impairments. Given its utility and sustainability, the sensor has potential for applications in wearable health monitoring, intelligent life and telemedicine.

Mechanistic insights and applications of lignin-based ultraviolet shielding composites: A comprehensive review.

Lignin is a green aromatic polymer constructed from repeating phenylpropane units, incorporating features such as phenolic hydroxyl groups, carbonyl groups, and conjugated double bonds that serve as chromophores. These structural attributes enable it to absorb a wide spectrum of ultraviolet radiation within the 250-400 nm range. The resulting properties make lignin a material of considerable interest for its potential applications in polymers, packaging, architectural decoration, and beyond. By examining the structure of lignin, this research delves into the structural influence on its UV-shielding capabilities. Through a comparative analysis of lignin's use in various UV-shielding applications, the study explores the interplay between lignin's structure and its interactions with other materials. This investigation aims to elucidate the UV-shielding mechanism, thereby offering insights that could inform the development of high-value applications for lignin in UV-shielding composite materials.

Life history parameters of Ectropis grisescens (Lepidoptera: Geometridae) in different Wolbachia infection states.

Wolbachia, a prevalent intracellular symbiotic bacterium in insects, plays a significant role in insect biology. Ectropis grisescens (Warren; Lepidoptera: Geometridae) is a devastating chewing pest distributed in tea plantations throughout China. However, it is unclear how Wolbachia titers affect the fitness and reproduction of E. grisescens. In this study, the impacts of 3 different infection lines, naturally Wolbachia-infected, Wolbachia-uninfected, and Wolbachia transinfected, regarding the life history traits of E. grisescens, were evaluated using the age-stage, 2-sex life table. Wolbachia infection significantly shortened preadult duration and preoviposition periods and notably increased the fecundity, net reproductive rate, and finite rate of increase. Meanwhile, population projection indicated that E. grisescens population size with Wolbachia infection can increase faster than without. These results indicate that Wolbachia plays a regulatory role in the fitness of E. grisescens. It is also noted that the life history parameters of E. grisescens may positively correlate with Wolbachia titers. These findings could aid in pest management in tea gardens.

A lightweight grape detection model in natural environments based on an enhanced YOLOv8 framework.

Grapefruit and stem detection play a crucial role in automated grape harvesting. However, the dense arrangement of fruits in vineyards and the similarity in color between grape stems and branches pose challenges, often leading to missed or false detections in most existing models. Furthermore, these models' substantial parameters and computational demands result in slow detection speeds and difficulty deploying them on mobile devices. Therefore, we propose a lightweight TiGra-YOLOv8 model based on YOLOv8n. Initially, we integrated the Attentional Scale Fusion (ASF) module into the Neck, enhancing the network's ability to extract grape features in dense orchards. Subsequently, we employed Adaptive Training Sample Selection (ATSS) as the label-matching strategy to improve the quality of positive samples and address the challenge of detecting grape stems with similar colors. We then utilized the Weighted Interpolation of Sequential Evidence for Intersection over Union (Wise-IoU) loss function to overcome the limitations of CIoU, which does not consider the geometric attributes of targets, thereby enhancing detection efficiency. Finally, the model's size was reduced through channel pruning. The results indicate that the TiGra-YOLOv8 model's mAP(0.5) increased by 3.33% compared to YOLOv8n, with a 7.49% improvement in detection speed (FPS), a 52.19% reduction in parameter count, and a 51.72% decrease in computational demand, while also reducing the model size by 45.76%. The TiGra-YOLOv8 model not only improves the detection accuracy for dense and challenging targets but also reduces model parameters and speeds up detection, offering significant benefits for grape detection.

Integrative genomics reveals the polygenic basis of seedlessness in grapevine.

Seedlessness is a crucial quality trait in table grape (Vitis vinifera L.) breeding. However, the development of seeds involved intricate regulations, and the polygenic basis of seed abortion remains unclear. Here, we combine comparative genomics, population genetics, quantitative genetics, and integrative genomics to unravel the evolution and polygenic basis of seedlessness in grapes. We generated the haplotype-resolved genomes for two seedless grape cultivars, "Thompson Seedless" (TS, syn. "Sultania") and "Black Monukka" (BM). Comparative genomics identified a ∼4.25 Mb hemizygous inversion on Chr10 specific in seedless cultivars, with seedless-associated genes VvTT16 and VvSUS2 located at breakpoints. Population genomic analyses of 548 grapevine accessions revealed two distinct clusters of seedless cultivars, and the identity-by-descent (IBD) results indicated that the origin of the seedlessness trait could be traced back to "Sultania." Introgression, rather than convergent selection, shaped the evolutionary history of seedlessness in grape improvement. Genome-wide association study (GWAS) analysis identified 110 quantitative trait loci (QTLs) associated with 634 candidate genes, including previously unidentified candidate genes, such as three 11S GLOBULIN SEED STORAGE PROTEIN and two CYTOCHROME P450 genes, and well-known genes like VviAGL11. Integrative genomic analyses resulted in 339 core candidate genes categorized into 13 functional categories related to seed development. Machine learning-based genomic selection achieved a remarkable prediction accuracy of 97% for seedlessness in grapevines. Our findings highlight the polygenic nature of seedlessness and provide candidate genes for molecular genetics and an effective prediction for seedlessness in grape genomic breeding.

Visual observation of polystyrene nano-plastics in grape seedlings of Thompson Seedless and assessing their effects via transcriptomics and metabolomics.

Micro/nano-plastics (MNPs) are emerging non-point source pollutants that have garnered increasing attention owing to their threat to ecosystems. Studies on the effects of MNPs on horticultural crops are scarce. Specifically, whether MNPs can be absorbed and transported by grapevines have not been reported. To fill this gap, we added polystyrene nanoplastics (PS-NPs, 100 nm) to a hydroponic environment and observed their distribution in grape seedlings of Thompson Seedless (TS, Vitis vinifera L.). After 15 d of exposure, plastic nanospheres were detected on the cell walls of the roots, stems, and leaves using confocal microscopy and scanning electron microscopy. This indicated that PS-NPs can also be absorbed by the root system through the epidermis-cortex interface in grapevines and transported upward along the xylem conduit. Furthermore, we analyzed the molecular response mechanisms of TS grapes to the PS-NPs. Through the measurement of relevant indicators and combined omics analysis, we found that plant hormone signal transduction, flavonoid and flavonol biosynthesis, phenylpropanoid biosynthesis, and MAPK signaling pathway biosynthesis played crucial roles in its response to PS-NPs. The results not only revealed the potential risk of MNPs being absorbed by grapevines and eventually entering the food chain but also provided valuable scientific evidence and data for the assessment of plant health and ecological risk.

High-speed forward-viewing optical coherence tomography probe based on Lissajous sampling and sparse reconstruction.

We present a novel endoscopy probe using optical coherence tomography (OCT) that combines sparse Lissajous scanning and compressed sensing (CS) for faster data collection. This compact probe is only 4 mm in diameter and achieves a large field of view (FOV) of 2.25 mm2 and a 10 mm working distance. Unlike traditional OCT systems that use bulky raster scanning, our design features a dual-axis piezoelectric mechanism for efficient Lissajous pattern scanning. It employs compressive data reconstruction algorithms that minimize data collection requirements for efficient, high-speed imaging. This approach significantly enhances imaging speed by over 40%, substantially improving miniaturization and performance for endoscopic applications.

Heritability of functional gradients in the human subcortico-cortical connectivity.

The human subcortex plays a pivotal role in cognition and is widely implicated in the pathophysiology of many psychiatric disorders. However, the heritability of functional gradients based on subcortico-cortical functional connectivity remains elusive. Here, leveraging twin functional MRI (fMRI) data from both the Human Connectome Project (n = 1023) and the Adolescent Brain Cognitive Development study (n = 936) datasets, we construct large-scale subcortical functional gradients and delineate an increased principal functional gradient pattern from unimodal sensory/motor networks to transmodal association networks. We observed that this principal functional gradient is heritable, and the strength of heritability exhibits a heterogeneous pattern along a hierarchical unimodal-transmodal axis in subcortex for both young adults and children. Furthermore, employing a machine learning framework, we show that this heterogeneous pattern of the principal functional gradient in subcortex can accurately discern the relationship between monozygotic twin pairs and dizygotic twin pairs with an accuracy of 76.2% (P < 0.001). The heritability of functional gradients is associated with the anatomical myelin proxied by MRI-derived T1-weighted/T2-weighted (T1w/T2w) ratio mapping in subcortex. This study provides new insights into the biological basis of subcortical functional hierarchy by revealing the structural and genetic properties of the subcortical functional gradients.

The RhoB p.S73F mutation leads to cerebral palsy through dysregulation of lipid homeostasis.

Cerebral palsy (CP) is a prevalent neurological disorder that imposes a significant burden on children, families, and society worldwide. Recently, the RhoB p.S73F mutation was identified as a de novo mutation associated with CP. However, the mechanism by which the RhoB p.S73F mutation causes CP is currently unclear. In this study, rabbit models were generated to mimic the human RhoB p.S73F mutation using the SpG-BE4max system, and exhibited the typical symptoms of human CP, such as periventricular leukomalacia and spastic-dystonic diplegia. Further investigation revealed that the RhoB p.S73F mutation could activate ACAT1 through the LYN pathway, and the subsequently altered lipid levels may lead to neuronal and white matter damage resulting in the development of CP. This study presented the first mammalian model of genetic CP that accurately replicates the RhoB p.S73F mutation in humans, provided further insights between RhoB and lipid metabolism, and novel therapeutic targets for human CP.

Gene editing therapy for cardiovascular diseases.

The development of gene editing tools has been a significant area of research in the life sciences for nearly 30 years. These tools have been widely utilized in disease detection and mechanism research. In the new century, they have shown potential in addressing various scientific challenges and saving lives through gene editing therapies, particularly in combating cardiovascular disease (CVD). The rapid advancement of gene editing therapies has provided optimism for CVD patients. The progress of gene editing therapy for CVDs is a comprehensive reflection of the practical implementation of gene editing technology in both clinical and basic research settings, as well as the steady advancement of research and treatment of CVDs. This article provides an overview of the commonly utilized DNA-targeted gene editing tools developed thus far, with a specific focus on the application of these tools, particularly the clustered regularly interspaced short palindromic repeat/CRISPR-associated genes (Cas) (CRISPR/Cas) system, in CVD gene editing therapy. It also delves into the challenges and limitations of current gene editing therapies, while summarizing ongoing research and clinical trials related to CVD. The aim is to facilitate further exploration by relevant researchers by summarizing the successful applications of gene editing tools in the field of CVD.

Ferroptosis and Lipid Metabolism in Acute Myocardial Infarction.

Acute myocardial infarction (AMI) is triggered by the blockage of coronary arteries, leading to restricted blood flow to the myocardium, which results in damage and cell death. While the traditional understanding of cell death primarily revolves around apoptosis, a new player in the game has emerged: ferroptosis. This novel form of cell death relies on iron and is propelled by reactive oxygen species (ROS). Lipid metabolism, an indispensable physiological process, plays a vital role in preserving cellular homeostasis. However, when this metabolic pathway is disrupted, the accumulation of excess waste increases, specifically lipid peroxides, which are strongly linked to the occurrence and progression of AMI. As a result, comprehending this complex interaction between ferroptosis and lipid metabolism could pave the way for new therapeutic approaches in tackling AMI.

Mutational profiling of SARS-CoV-2 papain-like protease reveals requirements for function, structure, and drug escape.

Papain-like protease (PLpro) is an attractive drug target for SARS-CoV-2 because it is essential for viral replication, cleaving viral poly-proteins pp1a and pp1ab, and has de-ubiquitylation and de-ISGylation activities, affecting innate immune responses. We employ Deep Mutational Scanning to evaluate the mutational effects on PLpro enzymatic activity and protein stability in mammalian cells. We confirm features of the active site and identify mutations in neighboring residues that alter activity. We characterize residues responsible for substrate binding and demonstrate that although residues in the blocking loop are remarkably tolerant to mutation, blocking loop flexibility is important for function. We additionally find a connected network of mutations affecting activity that extends far from the active site. We leverage our library to identify drug-escape variants to a common PLpro inhibitor scaffold and predict that plasticity in both the S4 pocket and blocking loop sequence should be considered during the drug design process.

A comprehensive exploration of astrocytes in migraine: a bibliometric and visual analysis.

BACKGROUND: Migraine, as a prevalent neurologic disorder, involves intricate and yet incompletely elucidated pathophysiological mechanisms. A plethora of research findings underscores the pivotal role played by astrocytes in the progression of migraines. In order to elucidate the current advances and directions in research pertaining to astrocytes in migraines, we conducted bibliometric analysis of relevant literature and visualized the results. Subsequently, we expound upon these findings to contribute to the evolving understanding of the role of astrocytes in migraine pathophysiology. METHODS: On November 21, 2023, we conducted a search on Web of Science (WOS), restricting the document type to articles or reviews and language to English. Following a meticulous selection process involving three researchers, we identified the literature to be included in our analysis. Subsequently, we employed Microsoft Office Excel programs, R, VOSviewer, Scimago Graphica, and CiteSpace software to conduct visualization analysis of basic information and trends regarding journals, countries/regions, and influential authors, institutions, keywords, and papers. RESULTS: As of November 21, 2023, relevant literature has been published in 71 journals across 27 countries/regions. This corpus comprises contributions from 576 authors affiliated with 220 institutions, encompassing 865 keywords and referencing 6065 scholarly articles. CEPHALALGIA stands out as the most influential journal in this field, while authors PIETROBON D and DALKARA T have significant impact. The United States is highly influential, with CNR and UNIV PADUA emerging as highly influential institutions. The predominant category is Neurosciences. CONCLUSIONS: Future investigators may continue to focus on migraines with aura, familial hemiplegic migraine (FHM), and the crucial calcitonin gene-related peptide (CGRP) system. Employing advanced observational techniques, such as imaging, researchers should pay attention to cellular and tissue structures, such as microglia and the trigeminal ganglion, as well as mechanisms involving inflammation and central sensitization. Moreover, animal models are paramount in obtaining high-quality evidence.

Airway epithelial-derived exosomes induce acute asthma exacerbation after respiratory syncytial virus infection.

Acute asthma exacerbation refers to the progressive deterioration of asthma symptoms that is always triggered by virus infection represented by respiratory syncytial virus (RSV). After RSV infection, exaggerated Th2-mediated pulmonary inflammation is the critical pathological response of asthmatic patients with acute exacerbation. Significantly, airway epithelial cells, being the primary targets of RSV infection, play a crucial role in controlling the pulmonary inflammatory response by releasing airway epithelial cell-derived exosomes (AEC-Exos), which potentially influence the development of asthma. However, the specific role of AEC-Exos in acute asthma exacerbation after RSV infection remains obscure. The purpose of this study was to determine the distinct function of AEC-Exos in exacerbating acute asthma following RSV infection. Blockade of exosomes by GW reduce the enhanced pulmonary inflammation significantly. Specifically, the enhanced Th2 inflammation was induced by AEC-Exos thorough transportation of hsa-miR-155-5p-Sirtuin 1 (SIRT1) pathway during acute asthma exacerbation. Targeted inhibition of hsa-miR-155-5p blocks the exaggerated Th2 inflammation effectively in mice with acute asthma exacerbation. In summary, our study showed that during acute asthma exacerbation after RSV infection, AEC-Exos promote the enhanced Th2 inflammation through transportation of increased hsa-miR-155-5p, which was mediated partly through SIRT1-mediated pathway. hsa-miR-155-5p is a potential biomarker for early prediction of acute asthma exacerbation.

Silybin mitigated liver and brain damage after difenoconazole exposure: Crosstalk between oxidative stress, inflammation, ferroptosis and apoptosis.

Long-term residue of difenoconazole (DFZ) in the environment caused multiple organ damage to aquatic organisms. Due to the potential hepatoprotective and neuroprotective properties of silybin (SIL), we hypothesized that SIL could alleviate growth inhibition, liver, and brain damage in carp induced by DFZ exposure. The in vivo experiments were divided into the Control group, the SIL group, the DFZ group and the DFZ + SIL group. The exposure concentration of DFZ was 0.39 mg/L, and the therapeutic dose of SIL was 400 mg/kg. The whole experiment lasted for 30 days. SIL was also found to reduce hepatic injury and lipid metabolism based on H&E staining, oil red O staining, and measurement of serum and liver tissue levels of ALT, AST, LDH, TG, and TC. Similarly, SIL reduced brain damage after DFZ exposure, according to H&E staining and detection transcription level of the ZO-1, ZO-2, occludin, and Claudin7 in carp brain. In terms of mechanism, the results showed that SIL inhibited the excessive production of ROS in liver and brain tissues, increased the activity of antioxidant enzymes (T-AOC, SOD, CAT) and resist oxidative stress. Also, SIL promoted the production of anti-inflammatory factors (TGF-ß1 and IL-10) and inhibited the expression of pro-inflammatory factors (TNF-α and IL-6) to reduce the inflammatory response in liver and brain tissues caused by DFZ. ln terms of ferroptosis, by lowering iron levels, upregulating ferroptosis-related genes (GPX4, SIC7A11, GCLC), and downregulating the expression of NCOA4, STEAP3, COX2, and P53, SIL was able to inhibit ferroptosis of liver and brain tissues of carp. In addition, SIL restored the reduced mitochondrial membrane potential (MMP) level and inhibited apoptosis as measured by MMP level detection, TUNEL staining, and apoptosis gene transcript levels. In this study, we analyzed the interactions between genes and proteins associated with oxidative stress, inflammation, ferroptosis and apoptosis using the String database and ranked the nodes in the network using the Cytoscape plugin Cytohubba, and found that P53, Caspase3, TNF-α, IL-6 and Bcl-2 were the key hub genes. Our study not only revealed the multiple pharmacological activities of SIL, but also provided a reference for the prevention and reduction pesticide hazards to aquatic organisms.