Database Retrieval Research Articles

Impactos causados pelo uso de telas durante a pandemia da COVID-19 em crianças e adolescentes: uma revisão integrativa

ABSTRACT Objective: To identify the scientific evidence on the impacts caused by the use of screens during the COVID-19 pandemic in children and adolescents, raising reflections for future interventions with this public. Data source: This is an integrative literature review, conducted in the databases Medical Literature Analysis and Retrieval System Online (MEDLINE), Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS), Cumulative Index to Nursing and Allied Health Literature (CINAHL), United States National Library of Medicine (PubMed), Scopus, Web of Science, and Embase, published from March 2020 to January 2022, in Portuguese, English and Spanish. Data synthesis: The search strategies allowed retrieving 418 articles, of which 218 were duplicates. The analysis of titles and abstracts resulted in the maintenance of 62 studies. Of these, 31 were excluded from the reading of the full text, since they did not clearly present the phenomenon investigated. Thirty-one were eligible, resulting in five categories: eye consequences; increased sedentary behavior and weight; change in eating habits; implications for sleep quality and impacts on mental health. Conclusions: The excessive use of screens during the pandemic led to numerous consequences for children and adolescents, with a higher incidence of visual damage, sedentary lifestyle, inadequate eating habit and increased weight gain, in addition to impaired sleep quality and mental health. This study provides subsidy for health professionals to carry out continuing education focused on this theme, and elaborate effective interventions for this public in this transition to the post-pandemic period.

Network Mathematical Virtual Data Analysis Model Based on Deep Learning Algorithm

In today's era of big data, people need to extract valuable and nutritious information from these data, but for the huge database, manual browsing and manual retrieval by ordinary users are obviously inefficient. Network data analysis can help users to study network data and deeply understand the embedded value of big data, which is popular in both civil and industrial and academic circles. This article aimed to use intelligent mathematical models to assist in the construction of network data analysis models and enabled the model to be repeatedly trained in the training set based on deep learning algorithms, becoming increasingly able to identify patterns between data.

English teaching resource database retrieval based on adaptive differential evolution algorithm

English teaching resource database retrieval based on adaptive differential evolution algorithm

An English teaching resource database retrieval based on adaptive differential evolution algorithm

An English teaching resource database retrieval based on adaptive differential evolution algorithm

Exploring the Role of Lycium barbarum Polysaccharide in Corneal Injury Repair and Investigating the Relevant Mechanisms through In Vivo and In Vitro Experiments.

Lycium barbarum polysaccharide (LBP) is the main active component of Fructus Lycii, exhibiting various biological activities. This study aims to explore the protective effects of LBP on human corneal epithelial cells (HCEC) and a rat corneal injury model. Potential target points for LBP improving corneal injury repair were screened from public databases, and functional and pathway enrichment analyses of core targets were conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Rat corneal alkali burns and HCEC oxidative stress injury models were established, and the results were validated through slit lamp examination, HE staining, TUNEL assay, immunofluorescence, CCK-8 assay, flow cytometry, scratch assay, and qRT-PCR methods. In the context of database retrieval, identification of 10 LBP monosaccharide components and 50 corneal injury repair-related targets was achieved. KEGG pathway analysis suggested that LBP might regulate the IL-17 and TNF signaling pathways through targets such as JUN, CASP3, and MMP9, thereby improving corneal damage. In vivo and in vitro experimental results indicated that LBP could reduce the increase of inflammation index scores (p < 0.05), inflammatory cell density (p < 0.01), TUNEL-positive cells (p < 0.01), corneal opacity scores (p < 0.01), and expression of corneal stromal fibrosis-related proteins α-SMA, FN, and COL (p < 0.01) caused by chemical damage to rat corneas. LBP inhibited oxidative stress-induced decreases in cell viability (p < 0.001) and migration healing ability (p < 0.01) in HCECs, reducing apoptosis rates (p < 0.001), ROS levels (p < 0.001), and the expression of inflammatory factors TNF-α and IL-6 (p < 0.01). qRT-PCR results demonstrated that LBP intervention decreased the mRNA levels of JUN, CASP3, and MMP9 in H2O2-induced alkaline-burned corneas and HCECs (p < 0.01).The integrated results from network pharmacology and validation experiments suggest that the inhibitory effects of LBP on apoptosis, inflammation, and fibrosis after corneal injury may be achieved through the suppression of the TNF and IL-17 signaling pathways mediated by JUN, CASP3, and MMP9.

Possibility of Wild Boar Harm Occurring in Five Provinces of Northwest China.

With the implementation of ecological engineering projects and related policies in China, wild boar (Sus scrofa) populations have surged, leading to increasingly serious conflicts with humans. We evaluated their potential habitat changes from the perspective of environmental suitability. To elucidate the suitable habitat characteristics for wild boars, we obtained data from 79 sites in five provinces in northwest China using database retrieval, human-wildlife conflict (HWC) incident questionnaires, and document retrieval. Thus, 10 environmental variables with lower correlation were selected, and potentially suitable distribution areas for wild boars under the current climate scenario were predicted based on the maximum entropy model. These areas were superimposed with different land use types in different periods to explore habitat selection. Precipitation seasonality (26.40%), human footprint index (16.50%), and elevation (11.90%) were the main environmental factors affecting wild boar distribution. The areas with high potential suitability for wild boars were mainly in the southeast and northwest of the region (total area of 2.63 × 105 km2). The land use types in the high-suitability zones are mainly woodland and grassland with high coverage, canopy density, and cultivated land borders. This study provides a reference for the effective prevention of HWC and management of wild boars.

ANALYZING THE BIBLIOMETRIC LANDSCAPE OF DIGITAL TRANSFORMATION AND PROJECT MANAGEMENT IN ORGANIZATIONAL CONTEXTS

Digital transformation entails technological shifts, cultural shifts, and alterations in the manner organizations operate and deliver value, necessitating a rethink of organizational strategies and the undertaking of new risks. These changes occur and are needed across various sectors of society. Project management assists in altering the dynamics of organizations, enabling the implementation of new technologies, innovations, and transformations. This article aims to analyze the existing relationship between digital transformation and project management, and to identify the trends of this topic in the literature. The study employs bibliometric analysis to verify the existing relationship and to identify the most explored elements within the topic. The research was confined to the utilization of the Scopus database for data retrieval, wherein 245 articles were found, distributed between the years 2008 and 2020. Through bibliometric pairing, eight factors were identified (Change, Technologies, Strategy, Processes, People, Model, Autonomous Systems, and Artificial Intelligence), confirming the breadth of the topic, its relevance, and the main themes addressed. The findings indicate that the fields of engineering, computer science, and business administration encompass the majority of the studies, enabling scholars to comprehend the contemporary nature of the issues discussed and the trends for future studies.

Trends and hotspots in research of traumatic brain injury from 2000 to 2022: A bibliometric study

Traumatic brain injury (TBI) is a major health concern globally, which is characterized by high morbidity and mortality rates. Since the 21st century, TBI has received increasing attention and the number of publications is growing rapidly. This study aimed to characterize the volume and quality of scholarly output on TBI and identify the most impactful literature, research trends, and hotspots from the year 2000–2022. We searched publications on TBI through the Web of Science Core Collection-Science Citation Index Expanded database which were published from 2000 to 2022. Basic information of each paper, including publication year, countries, authors, affiliations, journal, fundings, subject areas, and keywords were collected for further analysis by using Microsoft Excel, VOSviewer, and CiteSpace software. A total of 47231 TBI-related publications were identified through database retrieval. The annual number of publications on TBI has increased steadily over the past twenty years and the number in the year 2022 is sevenfold higher than that in 2000. The United States of America (USA) was the leading country in both numbers of publications and citations, which is consistent with the finding that it had the most funding agencies. Menon DK was the author with the highest influence and the University of California System was the most productive affiliation. Moreover, keywords analysis suggested that the research topics can be mainly divided into six categories: management, rehabilitation, mechanisms, concussion, neuroimaging, and neuroendocrine. This study visualized the trends and focuses of scientific research related to TBI, both quantitatively and qualitatively. The USA had a relatively high academic impact owing to its productive experts and institutions in this field. Neuroinflammation, machine learning, tranexamic acid, and extracellular vesicles are currently hot topics in the field of TBI.

High-tech Advanced Roadside Vehicle Breakdown and Accidental Service System

The High-tech Advanced Roadside Vehicle Breakdown and Accidental Service System is an innovative solution designed to enhance the efficiency and effectiveness of roadside assistance and accident response services. High-tech advanced Roadside Vehicle Breakdown And Accidental service system Application is a mobile app designed to provide quick and efficient roadside assistance to users experiencing vehicle breakdowns. The application will be built using Android Studio with Java as the primary programming language, and it will leverage Firebase Database for real-time data storage and retrieval. Additionally, a user-friendly mobile application allows users to request assistance, track progress, and access relevant information. With a built-in data analytic module, the system collects and analyzes data to optimize performance. the High-tech Advanced Roadside Vehicle Breakdown and Accidental Service System aims to revolutionize the industry by providing faster, more efficient, and customer -centric service

Advanced Metrics and Early Predictors of Cardiogenic Shock.

Cardiogenic shock (CS) can be defined as a range of illnesses that describes a state where cardiac output, which is the blood volume ejected from the left ventricle every minute that leads to tissue perfusion of nutrients, is insufficient in providing adequate oxygenation to the systemic circulation. The incidence of CS on admission has increased in recent years, with the six- and 12-month mortality rates remaining unchanged. The purpose of this literature review is to bring forth several parameters that have been utilized in the past 10 years to predict CS mortality. Further studies to implement these parameters in management algorithms, along with early screenings and advanced treatment options such as mechanical cardiac assist devices, can improve the mortality associated with CS. This literature-based review was conducted by evaluating current research focusing on the clinical presentation of CS and predictors of CS. PubMed served as the primary database for article retrieval due to access. Two searches were conducted: One for clinical presentations and advanced metrics for CS and another for early predictors for CS. Thirteen articles regarding clinical presentation and seven articles regarding early predictors were selected. Three tools/scores and five laboratory tests were identified that allowed clinicians to prognosticate outcomes in patients suffering from CS based on clinical and laboratory presentations. Examining these predictors will allow earlier intervention in the development of CS and potentially help lower the mortality rate of CS. The eventual creation of a scoring system that incorporates multiple metrics discussed in this review can provide the most accurate prognosis of CS, which can lead to more targeted interventions.

Role of inositol polyphosphate-4-phosphatase type II in oncogenesis of digestive system tumors.

Inositol polyphosphate-4-phosphatase type II (INPP4B) is a newly discovered PI(3,4,5)P3 phosphatase. Many studies have revealed that INPP4B is upregulated or downregulated in tumors of the digestive system, and the abnormal expression of INPP4B may be attributed to the occurrence, development, and prognosis of tumors of the digestive system. This paper reviews studies on the correlations between INPP4B and digestive system tumors and the roles of INPP4B in the development of different tumors to provide a theoretical basis for further research on its molecular mechanism and clinical application. "INPP4B" and "tumor" were searched as key words in PubMed and in the CNKI series full text database retrieval system from January 2000 to August 2023. A total of 153 English-language studies and 30 Chinese-language studies were retrieved. The following enrollment criteria were applied: (1) Studies contained information on the biological structure and functions of INPP4B; (2) studies covered the influence of abnormal expression of INPP4B in digestive system tumors; and (3) studies covered the role of INPP4B in the diagnosis, treatment, and prognosis of digestive system tumors. After excluding the literature irrelevant to this study, 61 papers were finally included in the analysis. INPP4B expression is low in gastric cancer, colon cancer, pancreatic cancer, and liver cancer but it has high expression in esophageal cancer, colon cancer, pancreatic cancer, and gallbladder cancer. INPP4B is involved in the occurrence and development of digestive system tumors through the regulation of gene expression and signal transduction. The abnormal expression of INPP4B plays an important role in the development of digestive system tumors. Studies on INPP4B provide new molecular insights for the diagnosis, treatment, and prognosis evaluation of digestive system tumors.

Mechanism of Wuling Capsules against hepatic fibrosis based on network pharmacology and animal experiments

The present study aimed to explore the underlying mechanism of Wuling Capsules in the treatment of hepatic fibrosis(HF) through network pharmacology, molecular docking, and animal experiments. Firstly, the chemical components and targets of Wuling Capsules against HF were searched from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), Traditional Chinese Medicines Integrated Database(TCMID), GeneCards, and literature retrieval. The protein-protein interaction(PPI) network analysis was carried out on the common targets by STRING database and Cytoscape 3.9.1 software, and the core targets were screened, followed by Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses. Enrichment analysis was conducted on the core targets and the &quot;drug-core component-target-pathway-disease&quot; network was further constructed. Subsequently, molecular docking between core components and core targets was conducted using AutoDock Vina software to predict the underlying mechanism of action against HF. Finally, an HF model induced by CCl_4 was constructed in rats, and the general signs and liver tissue morphology were observed. HE and Masson staining were used to analyze the liver tissue sections. The effects of Wuling Capsules on the levels of inflammatory factors, hydroxyproline(HYP) levels, and core targets were analyzed by ELISA, RT-PCR, etc. A total of 445 chemical components of Wuling Capsules were screened, corresponding to 3 882 potential targets, intersecting with 1 240 targets of HF, and 47 core targets such as TNF, IL6, INS, and PIK3CA were screened. GO and KEGG enrichment analysis showed that the core targets mainly affected the process of cell stimulation response and metabolic regulation, involving cancer, PI3K-Akt, MAPK, and other signaling pathways. Molecular docking showed that the core components of Wuling Capsules, such as lucidenic acid K, ganoderic acid B, lucidenic acid N, saikosaponin Q2, and neocryptotanshinone, had high affinities with the core targets, such as TNF, IL6 and PIK3CA. Animal experiments showed that Wuling Capsules could reduce fat vacuole, inflammatory infiltration, and collagen deposition in rat liver, decrease the levels of inflammatory cytokines TNF-α, IL-6, and HYP, and downregulated the expressions of PI3K and Akt mRNA. This study suggests that the anti-HF effect of Wuling Capsules may be achieved by regulating the PI3K-Akt signaling pathway, reducing the levels of TNF-α and IL-6 inflammatory factors, and inhibiting the excessive deposition of collagen.

Secret data sharing through coverless video steganography based on bit plane segmentation

Recently information hiding is acquiring significance with the rising multimedia content over the web. Coverless steganography has been perceived as quite possibly the most solid way to deal with moving classified information and has turned into a research problem area. Considering video as a transporter, coverless steganography is expanding prominently because of its greater number of features than other transporters like text and images. Usually, the existing scheme hides confidential information based on single-frame features in the video. A secret data sharing through coverless video steganography technique based on bit-plane segmentation has been proposed. After extracting frames from the video, each frame is split into multiple bit-planes using BPCS(Bit-plane complexity segmentation). The hash sequences are obtained from these bit-planes by calculating the mean values of corresponding bit-plane sub-blocks. A retrieval database is constructed, including the relation between obtained hash sequences and bit-plane features. To begin with, the sender altered the secret data into a piece stream and divided it into equivalent lengths. The related retrieval information matching the fragmented secret information is transmitted to the recipient over the insecure channel. The experimental results show that the proposed technique achieves better robustness to various attacks, larger capacity, less time cost for extracting hash sequences, and a higher concealing success rate than existing coverless video steganography techniques.

A novel hash based feature descriptors for content based image retrieval in large database

For retrieving the relevant images from the internet, CBIRs (content based image retrievals) techniques are most globally utilized. However, the traditional image retrieval techniques are unable to represent the image features semantically. The CNNs (convolutional neural networks) and DL has made the retrieval task simpler. But, it is not adequate to consider only the finalized aspect vectors from the completely linked layers to fill the semantic gap. In order to alleviate this problem, a novel Hash Based Feature Descriptors (HBFD) method is proposed. In this method, the most significant feature vectors from each block are considered. To reduce the number of descriptors, pyramid pooling is used. To improve the performance in huge databases, the hash code like function is introduced in each block to represent the descriptors. The proposed method has been evaluated in Oxford 5k, Paris 6k, and UKBench datasets with the accuracy level of 80.6%, 83.9% and 92.14% respectively and demonstrated better recall value than the existing methods.

Meta-analysis: reducing the recurrence rate of allergic rhinitis through oral administration of traditional Chinese medicine.

A systematic review and meta-analysis were carried out to investigate the medical evidence of oral Chinese herbal medicine in reducing the recurrence of allergic rhinitis (AR). Through computer retrieval of PubMed, ScienceDirect, WOS, and other databases, relevant randomized controlled literature was obtained based on the inclusion criteria and retrieval strategies. The retrieval time was set from January 1, 2013, to December 31, 2022. The bias of the literature was evaluated using the bias evaluation module in Cochrane Manual Version 5.1.0, and the meta-analysis was conducted using RevMan software to verify the effectiveness of oral administration of traditional Chinese medicine (TCM) and its impact on reducing the recurrence rate. The meta-analysis included 7 articles. In the meta-analysis of all articles, the effective treatment rate of oral administration of TCM reached 97.09%. Additionally, when comparing the recurrence rate of AR between patients taking Chinese medicine orally and other treatment groups, the recurrence rate of patients taking Chinese medicine orally was only 24.46%, which was significantly lower (p<0.05). Furthermore, the quality of life of patients taking Chinese medicine orally after treatment was significantly higher than that of patients in the control group (C), indicating the good safety of oral Chinese medicine. Oral administration of TCM has demonstrated an effective reduction in the recurrence rate of AR, offering patients a good prognosis. This finding holds significant value for the clinical diagnosis and treatment of AR.

Fibroblast growth factor receptor 3 mutation attenuates response to immune checkpoint blockade in metastatic urothelial carcinoma by driving immunosuppressive microenvironment

BackgroundImmune checkpoint blockade (ICB) therapy holds promise in metastatic urothelial carcinoma (UC). Fibroblast growth factor receptor 3 (FGFR3) mutation drives T-cell-depleted microenvironment in UC, which led to the hypothesis that...

Infrastructure tools to support an effective Radiation Oncology Learning Health System.

Radiation Oncology Learning Health System (RO-LHS) is a promising approach to improve the quality of care by integrating clinical, dosimetry, treatment delivery, research data in real-time. This paper describes a novel set of tools to support the development of a RO-LHS and the current challenges they can address. We present a knowledge graph-based approach to map radiotherapy data from clinical databases to an ontology-based data repository using FAIR concepts. This strategy ensures that the data are easily discoverable, accessible, and can be used by other clinical decision support systems. It allows for visualization, presentation, and data analyses of valuable information to identify trends and patterns in patient outcomes. We designed a search engine that utilizes ontology-based keyword searching, synonym-based term matching that leverages the hierarchical nature of ontologies to retrieve patient records based on parent and children classes, connects to the Bioportal database for relevant clinical attributes retrieval. To identify similar patients, a method involving text corpus creation and vector embedding models (Word2Vec, Doc2Vec, GloVe, and FastText) are employed, using cosine similarity and distance metrics. The data pipeline and tool were tested with 1660 patient clinical and dosimetry records resulting in 504180 RDF (Resource Description Framework) tuples and visualized data relationships using graph-based representations. Patient similarity analysis using embedding models showed that the Word2Vec model had the highest mean cosine similarity, while the GloVe model exhibited more compact embeddings with lower Euclidean and Manhattan distances. The framework and tools described support the development of a RO-LHS. By integrating diverse data sources and facilitating data discovery and analysis, they contribute to continuous learning and improvement in patient care. The tools enhance the quality of care by enabling the identification of cohorts, clinical decision support, and the development of clinical studies and machine learning programs in radiation oncology.

Neutrophil extracellular traps-related signature predicts the prognosis and immune infiltration in gastric cancer.

Gastric cancer (GC) is the fifth most prevalent cancer globally, with the third highest case fatality rate. Neutrophil extracellular traps (NETs) are a reticulated structure of DNA, histones, and antimicrobial peptides produced by active neutrophils that trap pathogens. Even though NETs are associated with poorer recurrence-free survival (RFS) and overall survival (OS), the specifics of this interaction between NETs and cancer cells are yet unknown. The keywords "neutrophil extracellular traps and gastric cancer" were used in the GEO database for retrieval, and the GSE188741 dataset was selected to obtain the NETs-related gene. 27 NETs-related genes were screened by univariate Cox regression analysis (p < 0.05). 27 NETs-related genes were employed to identify and categorize NETs-subgroups of GC patients under the Consensus clustering analysis. 808 GC patients in TCGA-STAD combined with GES84437 were randomly divided into a training group (n = 403) and a test group (n = 403) at a ratio of 1:1 to validate the NETs-related signature. Based on Multivariate Cox regression and LASSO regression analysis to develop a NETs-related prognosis model. We developed a very specific nomogram to improve the NETs-clinical score's usefulness. Similarly, we also performed a great result in pan-cancer study with NETs-score. Low NETs scores were linked to higher MSI-H (microsatellite instability-high), mutation load, and immune activity. The cancer stem cell (CSC) index and chemotherapeutic treatment sensitivity were also connected to the NET score. Our comprehensive analysis of NETs in GC suggests that NETs have a role in the tumor microenvironment, clinicopathological features, and prognosis. The NETs-score risk model provides a basis for better prognosis and therapy outcomes in GC patients.

Mechanism of Qilongtian Capsules in treatment of acute lung injury based on network pharmacology prediction and experimental validation

This study aimed to explore the mechanism of Qilongtian Capsules in treating acute lung injury(ALI) based on network pharmacology prediction and in vitro experimental validation. Firstly, UPLC-Q-TOF-MS/MS was used to analyze the main chemical components of Qilongtian Capsules, and related databases were used to obtain its action targets and ALI disease targets. STRING database was used to build a protein-protein interaction(PPI) network. Metascape database was used to conduct enrichment analysis of Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG). AutoDock software was used to perform molecular docking verification on the main active components and key targets. Then, the RAW264.7 cells were stimulated with lipopolysaccharide(LPS) for in vitro experiments. Cell viability was measured by MTT and ROS level was measured by DCFH-DA. NO content was measured by Griess assay, and IL-1β, IL-6, and TNF-α mRNA expression was detected by RT-PCR. The predicted targets were preliminarily verified by investigating the effect of Qilongtian Capsules on downstream cytokines. Eighty-four compounds were identified by UPLC-Q-TOF-MS/MS. Through database retrieval, 44 active components with 589 target genes were screened out. There were 560 ALI disease targets, and 65 intersection targets. PPI network topology analysis revealed 10 core targets related to ALI, including STAT3, JUN, VEGFA, CASP3, and MMP9. KEGG enrichment analysis showed that Qilongtian Capsules mainly exerted an anti-ALI effect by regulating cancer pathway, AGE-RAGE, MAPK, and JAK-STAT signaling pathways. The results of molecular docking showed that the main active components in Qilongtian Capsules, including crenulatin, ginsenoside F_1, ginsenoside Rb_1, ginsenoside Rd, ginsenoside Rg_1, ginsenoside Rg_3, notoginsenoside Fe, notoginsenoside G, notoginsenoside R_1, notoginsenoside R_2, and notoginsenoside R_3, had good binding affinities with the corresponding protein targets STAT3, JUN, VEGFA, CASP3, and MMP9. Cellular experiments showed that Qilongtian Capsules at 0.1, 0.25, and 0.5 mg·mL~(-1) reduced the release of NO, while Qilongtian Capsules at 0.25 and 0.5 mg·mL~(-1) reduced ROS production, down-regulated mRNA expression of IL-1β, IL-6, TNF-α, and inhibited the inflammatory cascade. In summary, Qilongtian Capsules may exert therapeutic effects on ALI through multiple components and targets.

Molecular Mechanism Pathways of Natural Compounds for the Treatment of Non-Alcoholic Fatty Liver Disease.

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in the world, and its incidence continues to increase each year. Yet, there is still no definitive drug that can stop its development. This review focuses mainly on lipotoxicity, oxidative stress, inflammation, and intestinal flora dysbiosis to understand NAFLD's pathogenesis. In this review, we used NCBI's PubMed database for retrieval, integrating in vivo and in vitro experiments to reveal the therapeutic effects of natural compounds on NAFLD. We also reviewed the mechanisms by which the results of these experiments suggest that these compounds can protect the liver from damage by modulating inflammation, reducing oxidative stress, decreasing insulin resistance and lipid accumulation in the liver, and interacting with the intestinal microflora. The natural compounds discussed in these papers target a variety of pathways, such as the AMPK pathway and the TGF-β pathway, and have significant therapeutic effects. This review aims to provide new possible therapeutic lead compounds and references for the development of novel medications and the clinical treatment of NAFLD. It offers fresh perspectives on the development of natural compounds in preventing and treating NAFLD.