Downstream Relationships Research Articles

Construction of an adverse outcome pathway framework for arsenic-induced lung cancer using a network-based approach

Environmental pollutants are considered as a cause of tumorigenesis, but approaches to assess their risk of causing tumors remain insufficient. As an alternative approach, the adverse outcome pathway (AOP) framework is used to assess the risk of tumors caused by environmental pollutants. Arsenic is a pollutant associated with lung cancer, but early assessment of lung cancer risk is lacking. Therefore, we applied the AOP framework to arsenic-induced lung cancer. A systematic review revealed increased risks of lung cancer following exposure to a range of arsenic concentrations in drinking water (OR = 1.83, 95 % CI = 1.46–2.30). We obtained, from public databases, genes related to risk of arsenic-induced lung cancer. Then, Cox and LASSO regressions were used to screen target genes from the risk genes. Subsequently, target genes, phenotypes, and pathways were used to construct the computational AOP network, which was determined by Cytoscape to have 156 edges and 45 nodes. Further, target genes, phenotypes, and pathways were used as molecular initiating events and key events to construct the AOP framework depending on upstream and downstream relationships. In the AOP framework, by Weight of Evidence, arsenic exposure increased levels of EGFR, activated the PI3K/AKT pathway, regulated cell proliferation by promoting the G1/S phase transition, and caused generation of lung cancers. External validation was achieved through arsenite-induced, malignant transformed human bronchial epithelial (HBE) cells. Overall, these results, by integration into existing data to construct an AOP framework, provide insights into the assessment of lung cancer risk for arsenic exposure. Special attention needs to be focused on populations with low-dose arsenic exposure.

Stream sediment geochemical anomaly mapping based on the dynamic enhanced weighted drainage catchment basin method for mineral exploration

Accurately determining the presence of subterranean deposits is challenging due to the intricate geological processes that give rise to these deposits. The use of stream sediment geochemical data to identify and map geochemical anomalies is a widely employed technique in mineral exploration and offers a robust indicator of the possible presence of mineral deposits. This research presents a comparison between the weighted drainage catchment basin (WDCB) technique and its improved version, the dynamic enhanced weighted drainage catchment basin (DE-WDCB) approach, in the context of mineral exploration. We constructed a model of the catchment basin for the study area, clarified the upstream and downstream relationships between the basins, determined the background value in each basin via the trend surface method, and carried out geochemical anomaly mapping based on the DE-WDCB method. Then we conducted two comparative experiments using the WDCB method, employing both dynamic and nondynamic classification methods for anomaly classification. Finally, we compared the mineralization of the three methods and find that the DE-WDCB method exhibited superior performance in identifying sedimentary manganese ore anomalies, followed by the dynamic grading WDCB method and the nondynamic grading WDCB method. These results indicated that the DE-WDCB method revealed excellent performance when applied to stream sediment geochemistry in prospecting, hence enhancing its utility in mineral resource exploration.

A Framework Based on LIDs and Storage Pumping Stations for Urban Waterlogging

Climate change has resulted in an increase in extreme rainstorm events, posing the challenges of urban waterlogging and runoff pollution. Low Impact Development (LID) is widely used to address the issues above, but its effectiveness is unknown in mountainous areas. Due to a flash flood and high flood peak, storage pumping stations are also needed to drain. Thus, a framework composed of storage pumping stations and Low Impact Developments (LIDs) was proposed based on the topography and the regional upstream and downstream relationships. The water quantity in this framework is applied to YI County in Hebei Province, China. The results showed that individual LIDs effectively reduced runoff volume, with the implementation area being more crucial than the location. Combining storage pumping stations with LIDs significantly reduces peak outflow and delays it by 5 to 51 min. The combined downstream implementation of storage pumping stations and LIDs yielded the most effective results. These findings offer important insights and management strategies for controlling waterlogging in mountainous cities of developing countries.

The effect of stability and concentration of upstream and downstream relationships of focal firms on two-level trade credit

The stability and concentration of the buyer–supplier relationships are crucial factors in the realm of supply chain finance. Previous studies have focused on the impact of a single characteristic of the buyer–supplier relationships on the trade credit of focal firms. In this study, we investigated 973 A-share listed firms in China from 2012 to 2021 and adopted ordinary least squares regression to analyze the effects of stability and concentration in both upstream and downstream relationships on two-level trade credit. Our findings indicate that supplier stability has a positive impact, while concentration negatively impacts focal firms’ access to trade credit. Furthermore, customer stability and concentration positively affect the focal firms’ provided trade credit. In addition, focal firms’ market power mitigates the impact of supplier stability and concentration on focal firms receiving trade credit while amplifying the impact of customer concentration on focal firms providing trade credit. A higher supplier concentration is a disadvantage for focal firms, whereas customer stability is an advantage for focal firms to reduce the cost of trade credit. Our study offers comprehensive insights for promoting supply chain financial flows via supply chain relationship management.

Combination of gene/protein and metabolite multiomics to reveal biomarkers of nickel ion cytotoxicity and the underlying mechanism.

Biomarkers have been applied for toxicity assessment of biomaterials due to their advantages. However, research on biomarkers for biomaterials is still in its early stages. There is a lack of integrated analysis in biomarker research based on multiomics studies. Herein, we report a new approach for combining of gene/protein and metabolite multiomics to reveal biomarkers of nickel ion (Ni2+) cytotoxicity and the underlying mechanism. Firstly, differentially expressed genes and proteins were compared to screen gene/protein pairs exhibiting consistent differential expression within the same Ni2+-treated groups. Next, metabolic pathway analysis was carried out to reveal pathways in which gene/protein pairs and metabolites showed upstream and downstream relationships. Important networks composed of gene/protein pairs, metabolites and metabolic pathways and candidate biomarkers were subsequently identified. Through expression level and function validation, the gene/protein/metabolite biomarkers were confirmed, and the underlying mechanism was revealed: Ni2+ influenced the expression of the Rrm2 gene biomarker, which subsequently affected the expression of the RRM2 protein biomarker. These changes in turn impacted the levels of uric acid and uridine metabolite biomarkers, ultimately inhibiting DNA synthesis, suppressing cell proliferation, increasing intracellular ROS levels and reducing ATP content.

Early short-term hypoxia promotes epidermal cell migration by activating the CCL2-ERK1/2 pathway and epithelial-mesenchymal transition during wound healing.

Due to vasculature injury and increased oxygen consumption, the early wound microenvironment is typically in a hypoxic state. We observed enhanced cell migration ability under early short-term hypoxia. CCL2 belongs to the CC chemokine family and was found to be increased in early hypoxic wounds and enriched in the extracellular signal-regulated kinase (ERK)1/2 pathway in our previous study. However, the underlying mechanism through which the CCL2-ERK1/2 pathway regulates wound healing under early short-term hypoxia remains unclear. Activation of epithelial-mesenchymal transition (EMT) is a key process in cancer cell metastasis, during which epithelial cells acquire the characteristics of mesenchymal cells and enhance cell motility and migration ability. However, the relationship between epithelial cell migration and EMT under early short-term hypoxia has yet to be explored. HaCaT cells were cultured to verify the effect of early short-term hypoxia on migration through cell scratch assays. Lentiviruses with silenced or overexpressed CCL2 were used to explore the relationship between CCL2 and migration under short-term hypoxia. An acute full-thickness cutaneous wound rat model was established with the application of an ERK inhibitor to reveal the hidden role of the ERK1/2 pathway in the early stage of wound healing. The EMT process was verified in all the above experiments through western blotting. In our study, we found that short-term hypoxia promoted cell migration. Mechanistically, hypoxia promoted cell migration through mediating CCL2. Overexpression of CCL2 via lentivirus promoted cell migration, while silencing CCL2 via lentivirus inhibited cell migration and the production of related downstream proteins. In addition, we found that CCL2 was enriched in the ERK1/2 pathway, and the application of an ERK inhibitor in vivo and in vitro verified the upstream and downstream relationships between the CCL2 pathway and ERK1/2. Western blot results both in vivo and in vitro demonstrated that early short-term hypoxia promotes epidermal cell migration by activating the CCL2-ERK1/2 pathway and EMT during wound healing. Our work demonstrated that hypoxia in the early stage serves as a stimulus for triggering wound healing through activating the CCL2-ERK1/2 pathway and EMT, which promote epidermal cell migration and accelerate wound closure. These findings provide additional detailed insights into the mechanism of wound healing and new targets for clinical treatment.

Water quality analysis based on LSTM and BP optimization with a transfer learning model.

In the urban water environmental management, a fast and effective method for water quality analysis should be established with the rapid urbanization. In this study, the Beijing's sub-center was chosen as a case study, and long short-term memory (LSTM) and back propagation (BP) models were built, then a transfer learning model was proposed and applied to optimize the two models on the base of the upstream and downstream relationships in the rivers. The results indicated that the proposed deep learning model could improve NSE by 7% and 9% for LSTM and BP at the Dongguan Bridge gauge, respectively. At the Xugezhuang gauge in the Liangshui River, NSE was improved by 11% and 17%, respectively. At the Yulinzhuang gauge, it was improved by 16% and 13%, respectively. Because the upstream and downstream relationships were considered in the learning model, the model performance was obviously better. In brief, this method would provide an idea for the effective water quality model construction in the ungauged basins or regions.

Drainage Pattern Recognition of River Network Based on Graph Convolutional Neural Network

Drainage network pattern recognition is a significant task with wide applications in geographic information mining, map cartography, water resources management, and urban planning. Accurate identification of spatial patterns in river networks can help us understand geographic phenomena, optimize map cartographic quality, assess water resource potential, and provide a scientific basis for urban development planning. However, river network pattern recognition still faces challenges due to the complexity and diversity of river networks. To address this issue, this study proposes a river network pattern recognition method based on graph convolutional networks (GCNs), aiming to achieve accurate classification of different river network patterns. We utilize binary trees to construct a hierarchical tree structure based on river reaches and progressively determine the tree hierarchy by identifying the upstream and downstream relationships among river reaches. Based on this representation, input features for the graph convolutional model are extracted from both spatial and geometric perspectives. The effectiveness of the proposed method is validated through classification experiments on four types of vector river network data (dendritic, fan-shaped, trellis, and fan-shaped). The experimental results demonstrate that the proposed method can effectively classify vector river networks, providing strong support for research and applications in related fields.

Three gorges dam shifts estuarine heavy metal risk through suspended sediment gradation

Damming alters downstream sediment supply relationships and erosion in the estuarine delta. Given that sediment grainsize serves as a key parameter for the ability to adsorb heavy metals from water, the assessment of estuarine heavy metal risk needs to get connected initially. Hence, fine suspended sediment (<63 μm) in the Yangtze River estuary (YRE) was divided into four grainsize fractions to simulate the surface suspended sediment concentration (SSC) and grainsize composition before and after the completion of the Three Gorges Dam (TGD). Representative months were selected for flood peak reduction (October) and runoff compensation in the dry season (March) to maximize the scheduling impact of the TGD on runoff and riverine sediment input to the YRE. An improved Water Quality Index (WQI) approach was proposed to assess the combined risk alteration of five heavy metals in six estuarine sensitive targets due to TGD-induced sediment characteristics. The results demonstrated that TGD significantly but tardily reduced the SSC and the proportion of fine sediment in the YRE, decreasing the risk of heavy metals resuspension. Seasonally, the total SSC became higher in the flood season than in the dry season during post-TGD period. However, the fine SSC in the flood season was averaged only 59.7% of that in the dry season due to the pronounced grainsize coarsening effect. As the significant reduction in fine SSC overcomes the increase in heavy metal content per unit of SS, the integrated resuspension risk declined significantly, particularly for Pb and Cr. Spatially, the risk reduction for sensitive targets near the turbidity maximum zone (TMZ) is 8.4 times greater than for inner river channel. However, undiminished anthropogenic metal inputs to the YRE signified greater pressures on the depositional environment.

Effective oxygen metabolism-based prognostic signature for colorectal cancer.

Oxygen metabolism is an important factor affecting the development of tumors, but its roles and clinical value in Colorectal cancer are not clear. We developed an oxygen metabolism (OM) based prognostic risk model for colorectal cancer and explored the role of OM genes in cancer. Gene expression and clinical data obtained from The Cancer Genome Atlas, Clinical Proteomic Tumor Analysis Consortium databases were consider as discovery and validation cohort, respectively. The prognostic model based on differently expressed OM genes between tumor and GTEx normal colorectal tissues were constructed in discovery cohort and validated in validation cohort. The Cox proportional hazards analysis was used to test clinical independent. Upstream and downstream regulatory relationships and interaction molecules are used to clarify the roles of prognostic OM genes in colorectal cancer. A total of 72 common differently expressed OM genes were detected in the discovery and validation set. A five-OM gene prognostic model including LRT2, ATP6V0E2, ODC1, SEL1L3 and VDR was established and validated. Risk score determined by the model was an independent prognostic according to routine clinical factors. Besides, the role of prognostic OM genes involves transcriptional regulation of MYC and STAT3, and downstream cell stress and inflammatory response pathways. We developed a five-OM gene prognostic model and study the unique roles of oxygen metabolism in of colorectal cancer.

Endoplasmic reticulum stress promotes endometrial fibrosis through the TGF-β/SMAD pathway.

Intrauterine adhesion (IUA) is one of the main causes of female infertility. This study reveals that endoplasmic reticulum stress activation upregulates the TGF-β/SMAD pathway to induce epithelial-mesenchymal transition and promote endometrial fibrosis in an IUA model. IUA is a common gynecological disease and is a leading cause of female infertility. Mechanical or infectious damage to the endometrial basal layer can lead to endometrial fibrosis, which is the most common cause of IUA. Endoplasmic reticulum stress (ERS), the transforming growth factor beta signaling pathway (TGF-β/SMAD) and epithelial-mesenchymal transition (EMT) are important factors promoting endometrial fibrosis. The purpose of this study was to determine the up- and downstream regulatory relationships of the above three in the process of endometrial fibrosis. The rat IUA model was induced by double injury method and prophylactic injection of the ERS inhibitor 4-phenylbutyric acid (4-PBA) was given in vivo. The ERS activator tunicamycin and the TGF-β/SMAD pathway inhibitor A 83-01 were used in human endometrial epithelial cells (HEECs) in vitro. Masson's trichrome, Sirius red staining, immunohistochemistry, immunofluorescence and Western blot analyses were used to determine ERS, TGF-β/SMAD pathway, EMT and fibrosis markers in the uterine tissue and HEECs of the different treatment groups. In animal experiments, ERS and the TGF-β/SMAD pathway had been activated and EMT occurred in an in vivo model of IUA but was suppressed in animals treated with prophylactic 4-PBA. In in vitro experiments, tunicamycin-treated HEECs had increased the activation of ERS, the abundance of TGF-β/SMAD pathway and fibrosis markers while EMT occurred, but the TGF-β/SMAD pathway and EMT were significantly inhibited in the tunicamycin+A 83-01 group. Our data suggest that increased ERS can induce EMT and promote endometrial fibrosis through the TGF-β/SMAD pathway.

Payment for Environmental Services in Indonesia: Mutually Beneficial Watershed Environmental Management Model

Payment for Environmental Services (PES) is an effort and commitment of the world community in tackling the symptoms of global warming and damage to the ozone layer that will affect global climate change. Using field research methods, research data is collected through in-depth interviews with stakeholders in environmental services return programs in this research area. Research data is analyzed and described qualitatively for further conclusions. The concept developed upstream and downstream watershed relationships through the PES mechanism is based on the principle of voluntary agreement and awareness of maintaining the watershed ecosystem. The experience of implementing the PES Program in the Cidanau Watershed of Banten Province of Indonesia, managed by an independent institution. The PES program, in addition to its role as an environmental conservation program in the Cidanau watershed, also has socio-economical benefits for the community, environmental service (ES) users, and providers.

Time evolution of a Supply Chain Network: Kinetic modeling

Resilient supply chains are often inherently dependent on the nature of their complex interconnected networks that are simultaneously multi-dimensional and multi-layered. This article presents a Supply Chain Network (SCN) model that can be used to regulate downstream relationships towards a sustainable SME using a 4-component cost function structure — Environmental (E), Demand (D), Economic (E), and Social (S). As a major generalization to the existing practice of using phenomenological interrelationships between the EDES cost kernels, we propose a complementary time varying model of a cost function, based on Lagrangian mechanics (incorporating SCN constraints through Lagrange multipliers), to analyze the time evolution of the SCN variables to interpret the competition between economic inertia and market potential. Multicriteria decision making, based on an Analytic Hierarchy Process (AHP), ranks performance quality, identifying key business decision makers. The model is first solved numerically and then validated against real data pertaining to two Small and Medium Enterprises (SMEs) from diverse domains, establishing the domain-independent nature of the model. The results quantify how increases in a production line without appropriate consideration of market volatility can lead to bankruptcy, and how high transportation cost together with increased production may lead to a break-even state. The model also predicts the time it takes a policy change to reinvigorate sales, thereby forecasting best practice operational procedure that ensures holistic sustainability on all four sustainability fronts.

Deficiency of the bZIP transcription factors Mafg and Mafk causes misexpression of genes in distinct pathways and results in lens embryonic developmental defects.

Deficiency of the small Maf proteins Mafg and Mafk cause multiple defects, namely, progressive neuronal degeneration, cataract, thrombocytopenia and mid-gestational/perinatal lethality. Previous data shows Mafg −/−:Mafk +/- compound knockout (KO) mice exhibit cataracts age 4-months onward. Strikingly, Mafg −/−:Mafk −/− double KO mice develop lens defects significantly early in life, during embryogenesis, but the pathobiology of these defects is unknown, and is addressed here. At embryonic day (E)16.5, the epithelium of lens in Mafg −/−:Mafk −/− animals appears abnormally multilayered as demonstrated by E-cadherin and nuclear staining. Additionally, Mafg −/−:Mafk −/− lenses exhibit abnormal distribution of F-actin near the “fulcrum” region where epithelial cells undergo apical constriction prior to elongation and reorientation as early differentiating fiber cells. To identify the underlying molecular changes, we performed high-throughput RNA-sequencing of E16.5 Mafg −/−:Mafk −/− lenses and identified a cohort of differentially expressed genes that were further prioritized using stringent filtering criteria and validated by RT-qPCR. Several key factors associated with the cytoskeleton, cell cycle or extracellular matrix (e.g., Cdk1, Cdkn1c, Camsap1, Col3a1, Map3k12, Sipa1l1) were mis-expressed in Mafg −/−:Mafk −/− lenses. Further, the congenital cataract-linked extracellular matrix peroxidase Pxdn was significantly overexpressed in Mafg −/−:Mafk −/− lenses, which may cause abnormal cell morphology. These data also identified the ephrin signaling receptor Epha5 to be reduced in Mafg −/−:Mafk −/− lenses. This likely contributes to the Mafg −/−:Mafk −/− multilayered lens epithelium pathology, as loss of an ephrin ligand, Efna5 (ephrin-A5), causes similar lens defects. Together, these findings uncover a novel early function of Mafg and Mafk in lens development and identify their new downstream regulatory relationships with key cellular factors.

The interaction mechanism of nickel ions with L929 cells based on integrative analysis of proteomics and metabolomics data.

The aim of this article was to study the toxicity mechanism of nickel ions (Ni2+) on L929 cells by combining proteomics and metabolomics. First, iTRAQ-based proteomics and LC/MS metabolomics analyses were used to determine the protein and metabolite expression profiles in L929 cells after treatment with 100 μM Ni2+ for 12, 24 and 48 h. A total of 177, 2191 and 2109 proteins and 40, 60 and 74 metabolites were found to be differentially expressed. Then, the metabolic pathways in which both differentially expressed proteins and metabolites were involved were identified, and three pathways with proteins and metabolites showing upstream and downstream relationships were affected at all three time points. Furthermore, the protein–metabolite–metabolic pathway network was constructed, and two important metabolic pathways involving 4 metabolites and 17 proteins were identified. Finally, the functions of the important screened metabolic pathways, metabolites and proteins were investigated and experimentally verified. Ni2+ mainly affected the expression of upstream proteins in the glutathione metabolic pathway and the arginine and proline metabolic pathway, which further regulated the synthesis of downstream metabolites, reduced the antioxidant capacity of cells, increased the level of superoxide anions and the ratio of GSSG to GSH, led to oxidative stress, affected energy metabolism and induced apoptosis.

Associating diethylhexyl phthalate to gestational diabetes mellitus via adverse outcome pathways using a network-based approach

Gestational diabetes mellitus (GDM) is a common pregnancy complication that is harmful to both the woman and fetus. Several epidemiological studies have found that exposure to diethylhexyl phthalate (DEHP), an endocrine disruptor ubiquitous in the environment, may be associated with GDM. This study aims to investigate the mechanism between DEHP and GDM using the adverse outcome pathway (AOP) framework, which can integrate information from different sources to elucidate the causal pathways between chemicals and adverse outcomes. We applied a network-based workflow to integrate diverse information to generate computational AOPs and accelerate the AOP development. The interactions among DEHP, genes, phenotypes, and GDM were retrieved from several publicly available databases, including the Comparative Toxicogenomics Database (CTD), Computational Toxicology (CompTox) Chemicals Dashboard, DisGeNET, MalaCards, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Based on the above interactions, a DEHP-Gene-Phenotype-GDM network consisting of 52 nodes and 227 edges was formed to support AOP construction. The filtered genes and phenotypes were assembled as molecular initiating events (MIEs) and key events (KEs) according to the upstream and downstream relationships, generating a computational AOP (cAOP) network. Based on the Organization for Economic Co-operation and Development handbook of AOPs, a cAOP was assessed and applied to determine the effects of DEHP on GDM. DEHP could increase TNF-α, downregulate the glucose uptake process, and lead to GDM. Overall, this study revealed the utility of computational methods in integrating a variety of datasets, supporting AOP development, and facilitating a better understanding of the underlying mechanism of exposure to chemicals on human health.

Helping and Hurting on the TV Screen: Bounded Generalized Reciprocity and Interracial Group Expectations

ABSTRACT Two survey studies, one with a college sample (Study 1, n = 245) and one with a national U.S. adult sample (Study 2, n = 590) examined how media messages can influence attitudes toward Black people in the U.S. A novel contribution is the role of Bounded Generalized Reciprocity, or the belief that members of an outgroup are likely to return a favor (positive), or enact retribution for a wrong (negative) as a factor in the relationship between television use and attitudes. Study 1 (college student sample) found support for a relationship between lifetime television exposure and negative attitudes, mediated by negative reciprocity beliefs. Study 2 (U.S. adult sample) found support for an ambivalence effect, where lifetime television exposure was associated with increases in both positive and negative reciprocity beliefs. This indicates that reciprocity beliefs can be cultivated similarly to other kinds of beliefs (e.g., crime frequency, mean world), and that these beliefs have downstream relationships with racial attitudes. The direction in which they are influenced by television use remains an open question, and likely depends on TV content patterns over time.

Examining the impact of upstream and downstream relationship stability and concentration on firms’ financial performance

Maintaining a healthy buyer–supplier relationship enhances the competence of the firm and the entire supply chain. This study examines the stability and concentration of both the upstream and downstream relationships in the focal firms in a supply chain. Using empirical evidence from 2,920 listed firms in China, we find that maintaining higher stability with major suppliers and customers enhances a firm’s financial performance, whereas a higher concentration of major suppliers and customers negatively affects the firm’s financial performance. The positive impact of stability is higher than the negative effect of concentration on firm’s performance. Additionally, geographical distance with the customer amplifies the positive impact of customer stability on a firm’s performance, and the geographical distance with suppliers and customers enlarges the concentration’s negative impact. Firms should build an open, long-term relationship that is stable but not exclusive with their major suppliers and customers to achieve better financial performance.

Application of Fuzzy Matter Element Analysis to the Evaluation of Circulation Efficiency of Agricultural Products

This article builds an evaluation indicator system based on the process of agricultural circulation and the balance of many-sided benefits. A new classification of indicator types was made from the perspective of benefit balance, and gross profit margin and inventory-sales ratio were classified as interval indicators, which enriched the indicator types. The matter-element analysis method is used to measure the circulation efficiency of agricultural product wholesale markets. The study found that in terms of geographical location, in the vertical direction of Aihui-Tengchong Line, the closer to the southeast, the higher the circulation efficiency; Since 2016, the overall circulation efficiency has almost stagnated, mainly because the wholesale industry has strengthened its ability to control upstream and downstream relationships, and the entry barriers of agricultural products have been continuously increased.

The important role of RPS14, RPL5 and MDM2 in TP53-associated ribosome stress in mycophenolic acid-induced microtia

ObjectiveMycophenolate embryopathy (ME) is a congenital malformation induced by mycophenolic acid (MA). Microtia is the most common ME phenotype. This study aimed to identify the key genes in the pathological process of microtia caused by mycophenolate mofetil (MM) through bioinformatics methods, to explore the potential pathogenesis, and to provide a direction for future genetic research on aetiology. MethodsGenes related to MM and microtia were obtained from the GeneCards database for bioinformatics. Metacore was used to identify and visualize the upstream and downstream gene relationships in the protein-protein interaction (PPI) results of these genes. The clusterProfiler R software package was used to simulate and visualize the enrichment results based on data from Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. ResultsFifty-nine genes were associated with microtia and MM/MA. The hub genes with the most significant effects on MM/MA-induced microtia pathogenesis included tumour protein P53 (p53), MDM2 proto-oncogene (MDM2), ribosomal protein L5 (RPL5) and ribosomal protein S14 (RBS14). The GO term with the most enriched genes was peptidyl-tyrosine phosphorylation. For the KEGG terms, there was significant enrichment regarding the haematopoietic cell lineage, apoptosis, p53 signalling, proteasome and necroptosis. ConclusionsWe propose that an axis composed of MA, microtia, TP53 and related genes is involved in ME pathogenesis. The important role of TP53-associated ribosome stress in ME pathogenesis is consistent with our previous findings from MA-induced cleft lip and palate. Deregulation of genes protective against TP53 overexpression, such as MDM2, could be a strategy for constructing a microtia animal model.