High cardiovascular mortality risk among older merkel cell carcinoma patients.

OBJECTIVE: Previous research has primarily focused on the incidence and mortality rates of Merkel cell carcinoma (MCC), neglecting the examination of cardiovascular mortality (CVM) risk among survivors, particularly older patients. This study aims to assess the risk of CVM in older individuals diagnosed with MCC. METHODS: Data pertaining to older MCC patients were obtained from the Surveillance, Epidemiology, and End Results database (SEER). CVM risk was measured using standardized mortality ratio (SMR) and cumulative mortality. Multivariate Fine-Gray's competing risk model was utilized to evaluate the risk factors contributing to CVM. RESULTS: Among the study population of 2,899 MCC patients, 465 (16.0%) experienced CVM during the follow-up period. With the prolongation of the follow-up duration, the cumulative mortality rate for CVM reached 27.36%, indicating that cardiovascular disease (CVD) became the second most common cause of death. MCC patients exhibited a higher CVM risk compared to the general population (SMR: 1.69; 95% CI: 1.54-1.86, p < 0.05). Notably, the SMR for other diseases of arteries, arterioles, and capillaries displayed the most significant elevation (SMR: 2.69; 95% CI: 1.16-5.29, p < 0.05). Furthermore, age at diagnosis and disease stage were identified as primary risk factors for CVM, whereas undergoing chemotherapy or radiation demonstrated a protective effect. CONCLUSION: This study emphasizes the significance of CVM as a competing cause of death in older individuals with MCC. MCC patients face a heightened risk of CVM compared to the general population. It is crucial to prioritize cardiovascular health starting from the time of diagnosis and implement personalized CVD monitoring and supportive interventions for MCC patients at high risk. These measures are essential for enhancing survival outcomes.

Effects of Deep Tillage on Wheat Regarding Soil Fertility and Rhizosphere Microbial Community.

Wheat production is intrinsically linked to global food security. However, wheat cultivation is constrained by the progressive degradation of soil conditions resulting from the continuous application of fertilizers. This study aimed to examine the effects of deep tillage on rhizosphere soil microbial communities and their potential role in improving soil quality, given that the specific mechanisms driving these observed benefits remain unclear. Soil fertility in this research was evaluated through the analysis of various soil parameters, including total nitrogen, total phosphorus, total potassium, available phosphorus, and available potassium, among others. The high-throughput sequencing technique was utilized to examine the rhizosphere microbial community associated with deep tillage wheat. The findings indicated that deep tillage cultivation of wheat led to reduced fertility levels in the 0-20 cm soil layer in comparison with non-deep tillage cultivation. A sequencing analysis indicated that Acidobacteria and Proteobacteria are the dominant bacterial phyla, with Proteobacteria being significantly more abundant in the deep tillage group. The dominant fungal phyla identified were Ascomycota, Mortierellomycota, and Basidiomycota. Among bacterial genera, Arthrobacter, Bacillus, and Nocardioides were predominant, with Arthrobacter showing a significantly higher presence in the deep tillage group. The predominant fungal genera included Mortierella, Alternaria, Schizothecium, and Cladosporium. Deep tillage cultivation has the potential to enhance soil quality and boost crop productivity through the modulation of soil microbial community structure.

Comparative Transcriptome Analysis Unveils Regulatory Factors Influencing Fatty Liver Development in Lion-Head Geese under High-Intake Feeding Compared to Normal Feeding.

The lion-head goose is the only large goose species in China, and it is one of the largest goose species in the world. Lion-head geese have a strong tolerance for massive energy intake and show a priority of fat accumulation in liver tissue through special feeding. Therefore, the aim of this study was to investigate the impact of high feed intake compared to normal feeding conditions on the transcriptome changes associated with fatty liver development in lion-head geese. In this study, 20 healthy adult lion-head geese were randomly assigned to a control group (CONTROL, n = 10) and high-intake-fed group (CASE, n = 10). After 38 d of treatment, all geese were sacrificed, and liver samples were collected. Three geese were randomly selected from the CONTROL and CASE groups, respectively, to perform whole-transcriptome analysis to analyze the key regulatory genes. We identified 716 differentially expressed mRNAs, 145 differentially expressed circRNAs, and 39 differentially expressed lncRNAs, including upregulated and downregulated genes. GO enrichment analysis showed that these genes were significantly enriched in molecular function. The node degree analysis and centrality metrics of the mRNA-lncRNA-circRNA triple regulatory network indicate the presence of crucial functional nodes in the network. We identified differentially expressed genes, including HSPB9, Pgk1, Hsp70, ME2, malic enzyme, HSP90, FADS1, transferrin, FABP, PKM2, Serpin2, and PKS, and we additionally confirmed the accuracy of sequencing at the RNA level. In this study, we studied for the first time the important differential genes that regulate fatty liver in high-intake feeding of the lion-head goose. In summary, these differentially expressed genes may play important roles in fatty liver development in the lion-head goose, and the functions and mechanisms should be investigated in future studies.

Efficacy and mechanism of the Ermiao San series of formulas for rheumatoid arthritis based on Chinmedomics strategy.

BACKGROUND: The Ermiao San Series of Formulas (ESSF) refers to Ermiao San (TS), Sanmiao Wan (TW), and Simiao Wan (FW), which are widely used traditional Chinese medicine (TCM) formulas for treating rheumatoid arthritis (RA). However, the therapeutic advantages and underlying mechanisms of ESSF treatment are unclear, especially regarding the improper selection of these three formulas when treating RA. PURPOSE: To explore the efficacy and mechanisms of ESSF treatment for RA. METHODS: Complete Freund's adjuvant was used to induce RA in rats. Chinmedomics strategy, which included metabolomics, serum pharmacochemistry of TCM, molecular docking, western blotting and qPCR, was applied to reveal the therapeutic advantages, pathways, and targets of ESSF. RESULTS: In the early stages of treatment, TS quickly reduced joint swelling and the arthritis score index and regulated pathways such as arachidonic acid metabolism and purine metabolism. TW increases the regulation of tryptophan metabolism and pyrimidine metabolism pathways, promoting the recovery of the thymus and spleen. FW increases the regulation of linoleic acid metabolism and has the greatest effect on immune organ and bone recovery. In addition, 54, 67, and 86 bioactive compounds were detected in the serum from TS, TW, and FW, respectively. Berberine, phellodendrine, atractylolide III, limonin, 25R-inokosterone, coixol, and stigmasterol were found to act on the key enzymes COX-2, mPGES-1, ALOX5, and XDH in arachidonic acid metabolism and purine metabolism pathways. Western blot and qPCR results showed that ESSF can reduce the activity of these targets, thereby inhibiting the expression of the inflammatory factors IL-1ß, IL-6, IL-17, and TNF-α; the tissue injury factors MMP-3 and CRP; and the rheumatoid factors CCP Ab and RF, thereby achieving anti-RA efficacy. CONCLUSION: ESSF has a good therapeutic effect on RA. TS focus on rapid swelling reduction in the early stages of RA, TW focus on the recovery of immune organ function, and FW can be used for bone recovery in the later stage of RA treatment. The key mechanism of treating RA is that ESSF reduces the activity of COX-2, mPGES-1, ALOX5, and XDH. These findings provide valuable guidance for targeted therapy for RA and for the clinical application of ESSF.

The communication mechanism of the gut-brain axis and its effect on central nervous system diseases: A systematic review.

Gut microbiota is involved in intricate and active metabolic processes the host's brain function, especially its role in immune responses, secondary metabolism, and symbiotic connections with the host. Gut microbiota can promote the production of essential metabolites, neurotransmitters, and other neuroactive chemicals that affect the development and treatment of central nervous system diseases. This article introduces the relevant pathways and manners of the communication between the brain and gut, summarizes a comprehensive overview of the current research status of key gut microbiota metabolites that affect the functions of the nervous system, revealing those adverse factors that affect typical communication between the brain-gut axis, and outlining the efforts made by researchers to alleviate these neurological diseases through targeted microbial interventions. The relevant pathways and manners of communication between the brain and gut contribute to the experimental design of new treatment plans and drug development. The factors that may cause changes in gut microbiota and affect metabolites, as well as current intervention methods are summarized, which helps improve gut microbiota brain dialogue, prevent adverse triggering factors from interfering with the gut microbiota system, and minimize neuropathological changes.

Social media and social impact assessment: Evolving methods in a shifting context.

Among many by-products of Web 2.0 come the wide range of potential image and text datasets within social media and content sharing platforms that speak of how people live, what they do, and what they care about. These datasets are imperfect and biased in many ways, but those flaws make them complementary to data derived from conventional social science methods and thus potentially useful for triangulation in complex decision-making contexts. Yet the online environment is highly mutable, and so the datasets are less reliable than censuses or other standard data types leveraged in social impact assessment. Over the past decade, we have innovated numerous methods for deploying Instagram datasets in investigating management or development alternatives. This article synthesizes work from three Canadian decision contexts - hydroelectric dam construction or removal; dyke realignment or wetland restoration; and integrating renewable energy into vineyard landscapes - to illustrate some of the methods we have applied to social impact assessment questions using Instagram that may be transferrable to other social media platforms and contexts: thematic (manual coding, machine vision, natural language processing/sentiment analysis, statistical analysis), spatial (hotspot mapping, cultural ecosystem modeling), and visual (word clouds, saliency mapping, collage). We conclude with a set of cautions and next steps for the domain.

Parmi les nombreux sous-produits du Web 2.0 figure un large éventail de données provenant d'images et de textes, de contenus de médias sociaux et de plateformes numériques, qui révèlent comment les gens vivent, ce qu'ils font et les questions qui les préoccupent. Ces ensembles de données sont imparfaits et biaisés à bien des égards, mais nombre de leurs lacunes les rendent complémentaires des informations collectées par les sciences sociales à l'aide de méthodes conventionnelles. D'où leur utilité potentielle pour la triangulation dans des contextes décisionnels complexes. Cet article synthétise le travail de trois études de cas menées au Canada pour illustrer certaines des méthodes que nous avons développées et qui pourraient être utiles à d'autres chercheurs en EIS: thématiques (codage, apprentissage automatique, analyse sémantique, association statistique), spatiales (cartographie des points chauds, modélisation du transfert des bénéfices) et visuelles (cartes de saillance, collage).

Entre los muchos subproductos de la Web 2.0 se encuentra una amplia gama de datos de imágenes y texto, contenidos en redes sociales y plataformas digitales, que hablan de cómo vive, qué hace y por qué cuestiones se preocupa la gente. Estos conjuntos de datos son imperfectos y sesgados en muchos sentidos, pero muchos de sus defectos los hacen complementarios a la información recogida por las ciencias sociales con métodos convencionales. De ahí su potencial utilidad para la triangulación en contextos complejos de toma de decisiones. Este artículo sintetiza el trabajo de tres estudios de caso llevados a cabo en Canadá para ilustrar algunos de los métodos que hemos desarrollado y pueden resultar útiles para otros investigadores en EIS: temáticos (codificación, machine learning, análisis semántico, asociación estadística), espaciales (mapeo de puntos críticos, modelización de transferencia de beneficios) y visuales (mapas de saliencia, collage).

The Role of Cuproptosis Key Factor FDX1 in Gastric Cancer.

BACKGROUND: Gastric cancer is a common malignant tumor of the digestive tract, both domestically and internationally. It has high incidence and mortality rates, posing a significant threat to human health. The levels of blood copper are elevated in patients with gastric cancer. However, the exact relationship between copper overload and the malignant phenotype of gastric cancer is still unclear. This study aims to investigate the role of the Cuproptosis-related factor FDX1 in the conversion of gastric cancer to a malignant phenotype. METHODS: Firstly, the relative mRNA and protein expression levels of FDX1 in gastric cancer were detected. Secondly, lentiviral transfection of gastric cancer cell lines was performed, and the effects of FDX1 functional intervention on the proliferation, invasion and migration of gastric cancer cells were assessed by CCK-8, colony formation, EdU proliferation, cell scratch and Transwell assays. Thirdly, the differential alteration of genes after overexpression of FDX1 was also analyzed by transcriptome sequencing. Finally, we assessed the tumour-forming capacity in vivo by the xenograft model. RESULTS: FDX1 is significantly upregulated in gastric cancer. The inhibition of FDX1 function results in the suppression of malignant phenotypic transformation in gastric cancer cells. Conversely, overexpression of FDX1 function leads to alterations in tumor-related signaling pathways and the tumor microenvironment. CONCLUSION: FDX1 plays a significant role in the malignant phenotypic transformation of gastric cancer cells. Further investigation into the regulatory mechanism of FDX1 in the malignant transformation of gastric cancer will enhance our understanding of the involvement of Cuproptosis in gastric cancer.

TET2-STAT3-CXCL5 nexus promotes neutrophil lipid transfer to fuel lung adeno-to-squamous transition.

Phenotypic plasticity is a rising cancer hallmark, and lung adeno-to-squamous transition (AST) triggered by LKB1 inactivation is significantly associated with drug resistance. Mechanistic insights into AST are urgently needed to identify therapeutic vulnerability in LKB1-deficient lung cancer. Here, we find that ten-eleven translocation (TET)-mediated DNA demethylation is elevated during AST in KrasLSL-G12D/+; Lkb1L/L (KL) mice, and knockout of individual Tet genes reveals that Tet2 is required for squamous transition. TET2 promotes neutrophil infiltration through STAT3-mediated CXCL5 expression. Targeting the STAT3-CXCL5 nexus effectively inhibits squamous transition through reducing neutrophil infiltration. Interestingly, tumor-infiltrating neutrophils are laden with triglycerides and can transfer the lipid to tumor cells to promote cell proliferation and squamous transition. Pharmacological inhibition of macropinocytosis dramatically inhibits neutrophil-to-cancer cell lipid transfer and blocks squamous transition. These data uncover an epigenetic mechanism orchestrating phenotypic plasticity through regulating immune microenvironment and metabolic communication, and identify therapeutic strategies to inhibit AST.

Tumor-derived extracellular vesicle proteins as new biomarkers and targets in precision oncology.

Extracellular vesicles (EVs) are important carriers of signaling molecules, such as nucleic acids, proteins, and lipids, and have become a focus of increasing interest due to their numerous physiological and pathological functions. For a long time, most studies on EV components focused on noncoding RNAs; however, in recent years, extracellular vesicle proteins (EVPs) have been found to play important roles in diagnosis, treatment, and drug resistance and thus have been considered favorable biomarkers and therapeutic targets for various tumors. In this review, we describe the general protocols of research on EVPs and summarize their multifaceted roles in precision medicine applications, including cancer diagnosis, dynamic monitoring of therapeutic efficacy, drug resistance research, tumor microenvironment interaction research, and anticancer drug delivery.

Sub-high amylose maize starch: an ideal substrate to generate starch with lower digestibility by fermentation of Qu.

BACKGROUND: The fermentation of Qu (FQ) is a novel method to modify the properties of starch to expand its application and especially to increase the resistant starch (RS) content. Using waxy maize starch (WMS) as a fermentation substrate can increase the RS content significantly but it may be time consuming and not cost effective due to the almost negligible RS content of WMS. To solve this problem, we hypothesized that sub-high amylose starch (s-HAMS), with an amylose content close to 50% could be an ideal substrate for FQ. RESULTS: The results showed that FQ did not change the shape and the particle size of starch granules, the gelatinization peak (Tp), or the conclusion temperature (Tc), but the slowly digested starch content declined. Rapidly digested starch content fluctuated during FQ and the amylose content decreased within 36 h and then increased. Within 24h, FQ significanlty increased these values: the RS content, relative crystallinity (RC), the ratio of FTIR absorbances at 1047/1022cm-1, the diffraction peak at 19.8° in X-ray diffraction (XRD), and the gelatinization onset temperature (To) increased significantly, within 24 h of FQ. However, after 24 h of fermentation, the RS content, RC, the ratio of FTIR absorbances at 1047/1022 cm-1, and gelatinization enthalpy (ΔH) decreased significantly. CONCLUSION: Sub-high amylose starch is more suitable for FQ to produce low digestibility starch, and the increase in RS may be due to the formation of 'amylose-lipid' complexes (RS5). © 2024 Society of Chemical Industry.

Evaluation of the key ingredient from the main production areas of Phellodendri Amurensis Cortex using ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry and ultra-high-performance liquid chromatography coupled to triple-quadrupole mass spectrometry.

Phellodendri Amurensis Cortex (PAC) is a medicinal herb that has been generally used to treat diarrhea and jaundice. In order to comprehensively evaluate the PAC in the main production areas quality, a qualitative and quantitative method with highly effective, sensitive, and reliable was developed. The chemical compositions of PAC were analyzed, and fingerprints were established by ultra-high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS). Then, the determination of berberine, canthin-6-one, dictamnine, γ-fagarine, and magnoflorine from PAC samples was simultaneously performed using UPLC-QQQ-MS. Furthermore, the chemical components of PAC from different regions were compared and analyzed by combining hierarchical cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis. A total of 58 compounds were identified, including 36 alkaloids, four phenylpropanoids, seven terpenoids, four flavonoids and their glycosides, an organic acid compound, and six other components. The fingerprint results show that samples have good similarity. Meanwhile, the content of the five ingredients in different habitats is quite different. By multivariate statistical analysis, 18 batches of PAC could be divided into three categories, and 20 components were identified as differential markers of various origins. A comprehensive method of PAC quality evaluation and chemical composition difference analysis was established, which provided the scientific basis for quality evaluation and further pharmacological mechanism research.

[Identification of banana ADA1 gene family members and their expression profiles under biotic and abiotic stresses].

The Spt-Ada-Gcn5-acetyltransferase (SAGA) is an ancillary transcription initiation complex which is highly conserved. The ADA1 (alteration/deficiency in activation 1, also called histone H2A functional interactor 1, HFI1) is a subunit in the core module of the SAGA protein complex. ADA1 plays an important role in plant growth and development as well as stress resistance. In this paper, we performed genome-wide identification of banana ADA1 gene family members based on banana genomic data, and analyzed the basic physicochemical properties, evolutionary relationships, selection pressure, promoter cis-acting elements, and its expression profiles under biotic and abiotic stresses. The results showed that there were 10, 6, and 7 family members in Musa acuminata, Musa balbisiana and Musa itinerans. The members were all unstable and hydrophilic proteins, and only contained the conservative SAGA-Tad1 domain. Both MaADA1 and MbADA1 have interactive relationship with Sgf11 (SAGA-associated factor 11) of core module in SAGA. Phylogenetic analysis revealed that banana ADA1 gene family members could be divided into 3 classes. The evolution of ADA1 gene family members was mostly influenced by purifying selection. There were large differences among the gene structure of banana ADA1 gene family members. ADA1 gene family members contained plenty of hormonal elements. MaADA1-1 may play a prominent role in the resistance of banana to cold stress, while MaADA1 may respond to the Panama disease of banana. In conclusion, this study suggested ADA1 gene family members are highly conserved in banana, and may respond to biotic and abiotic stress.

Emotion Recognition From Multimodal Physiological Signals via Discriminative Correlation Fusion With a Temporal Alignment Mechanism.

Modeling correlations between multimodal physiological signals [e.g., canonical correlation analysis (CCA)] for emotion recognition has attracted much attention. However, existing studies rarely consider the neural nature of emotional responses within physiological signals. Furthermore, during fusion space construction, the CCA method maximizes only the correlations between different modalities and neglects the discriminative information of different emotional states. Most importantly, temporal mismatches between different neural activities are often ignored; therefore, the theoretical assumptions that multimodal data should be aligned in time and space before fusion are not fulfilled. To address these issues, we propose a discriminative correlation fusion method coupled with a temporal alignment mechanism for multimodal physiological signals. We first use neural signal analysis techniques to construct neural representations of the central nervous system (CNS) and autonomic nervous system (ANS). respectively. Then, emotion class labels are introduced in CCA to obtain more discriminative fusion representations from multimodal neural responses, and the temporal alignment between the CNS and ANS is jointly optimized with a fusion procedure that applies the Bayesian algorithm. The experimental results demonstrate that our method significantly improves the emotion recognition performance. Additionally, we show that this fusion method can model the underlying mechanisms in human nervous systems during emotional responses, and our results are consistent with prior findings. This study may guide a new approach for exploring human cognitive function based on physiological signals at different time scales and promote the development of computational intelligence and harmonious human-computer interactions.

Correction to: Identification of TAZ as the essential molecular switch in orchestrating SCLC phenotypic transition and metastasis.

[This corrects the article DOI: 10.1093/nsr/nwab232.].

The diagnostic or prognostic values of FADD in cancers based on pan­cancer analysis.

Previous studies have determined that aberrant expression of the fas-associated death domain (FADD) contributes to the development of cancer. However, no pan-cancer analysis has been reported to explore the relationship between FADD and various cancers. Multiple databases were screened to identify cancer datasets for the present study and to validate the expression of FADD in various tumors. The association of FADD alteration with cancer prognosis, clinical features and tumor immunity was also evaluated. Reverse transcription-quantitative PCR (RT-qPCR) was utilized to confirm the expression of FADD in breast, colon, liver and gastric cancer cells. Analysis of Gene Expression Omnibus database and The Cancer Genome Atlas database indicated that FADD was highly expressed in breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma, cholangiocarcinoma, colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD) and prostate adenocarcinoma, whereas RT-qPCR results revealed that FADD was highly expressed in breast cancer and colon cancer. Further analyses demonstrated that FADD expression was significantly altered in ESCA, head and neck squamous cell carcinoma (HNSC), lung squamous cell carcinoma and BRCA. FADD expression was observed to be a risk factor of the overall survival in patients with HNSC, LIHC and LUAD as demonstrated by Kaplan-Meier and Cox regression analyses. The results of the present study demonstrated that FADD is highly expressed in numerous malignancies and can be utilized as a biomarker for the diagnosis of BRCA, COAD, LIHC and stomach adenocarcinoma. Moreover, FADD expression is a predictive risk factor for the development of HNSC, LIHC and LUAD and can potentially be used as a prognostic marker for these cancers.

The Functions and Mechanisms of Long Non-coding RNA SNHGs in Gastric Cancer.

Gastric cancer is one of the most common malignancies worldwide. Despite significant advancements in surgical and adjuvant treatments, patient prognosis remains unsatisfactory. Long non-coding RNAs (lncRNAs) are a class of RNA molecules that lack protein-coding capacity but can participate in various mechanisms of tumor malignancy. Among them, small nucleolar host genes (SNHGs) represent a subgroup of lncRNAs. Studies have revealed their involvement not only in gastric cancer cell proliferation, invasion, migration, epithelialmesenchymal transition (EMT), and apoptosis but also in chemotherapy resistance and tumor stemness. This review comprehensively summarizes the biological functions, molecular mechanisms, and clinical significance of SNHGs in gastric cancer. It provides novel insights into potential biomarkers and therapeutic targets for the exploration of gastric cancer.

STSNet: a novel spatio-temporal-spectral network for subject-independent EEG-based emotion recognition.

How to use the characteristics of EEG signals to obtain more complementary and discriminative data representation is an issue in EEG-based emotion recognition. Many studies have tried spatio-temporal or spatio-spectral feature fusion to obtain higher-level representations of EEG data. However, these studies ignored the complementarity between spatial, temporal and spectral domains of EEG signals, thus limiting the classification ability of models. This study proposed an end-to-end network based on ManifoldNet and BiLSTM networks, named STSNet. The STSNet first constructed a 4-D spatio-temporal-spectral data representation and a spatio-temporal data representation based on EEG signals in manifold space. After that, they were fed into the ManifoldNet network and the BiLSTM network respectively to calculate higher-level features and achieve spatio-temporal-spectral feature fusion. Finally, extensive comparative experiments were performed on two public datasets, DEAP and DREAMER, using the subject-independent leave-one-subject-out cross-validation strategy. On the DEAP dataset, the average accuracy of the valence and arousal are 69.38% and 71.88%, respectively; on the DREAMER dataset, the average accuracy of the valence and arousal are 78.26% and 82.37%, respectively. Experimental results show that the STSNet model has good emotion recognition performance.

Transcriptome and Metabolomics Integrated Analysis Reveals MdMYB94 Associated with Esters Biosynthesis in Apple (Malus × domestica).

Volatile esters are major aromas contributing to the organoleptic quality of apple fruit. However, the molecular mechanisms underlying the regulation of volatile ester biosynthesis in apple remain elusive. This study investigated the volatile profiles and transcriptomes of 'Qinguan' (QG) apple fruit during development and/or postharvest storage. Although the constitution of volatiles varied widely between the peel and flesh, the volatile profiles of the peel and flesh of ripening QG fruit were dominated by volatile esters. WGCNA results suggested that 19 genes belonging to ester biosynthesis pathways and 11 hub transcription factor genes potentially participated in the biosynthesis and regulation of esters. To figure out key regulators of ester biosynthesis, correlation network analysis, dual-luciferase assays, and yeast one-hybrid assay were conducted and suggested that MdMYB94 trans-activated the MdAAT2 promoter and participated in the regulation of ester biosynthesis. This study provides a framework for understanding ester biosynthesis and regulation in apple.