Impact of greening trends on biogenic volatile organic compound emissions in China from 1985 to 2022: Contributions of afforestation projects.

The rapid expansion of green areas in China has enhanced carbon sinks, but it also presents challenges regarding increased biogenic volatile organic compound (BVOC) emissions. This study examines the impact of greening trends on BVOC emissions in China from 1985 to 2001 and from 2001 to 2022, focusing on evaluating long-term trends in BVOC emissions within eight afforestation project areas during these two periods. Emission factors for 62 dominant tree species and provincial Plant Functional Types were updated. The BVOC emission inventories were developed for China at a spatial resolution of 27 km × 27 km using the Model of Emissions of Gases and Aerosols from Nature. The national BVOC emissions in 2018 were estimated at 54.24 Tg, with isoprene, monoterpenes, sesquiterpenes, and other BVOC contributing 26.94 Tg, 2.29 Tg, 0.44 Tg, and 24.57 Tg, respectively. Over the past 37 years, BVOC emissions experienced a slow growth rate of 1.7 % (0.79 Tg) during 1985-2001, followed by a significant increase of 12 % (6 Tg) from 2001 to 2022. BVOC emissions in the eight afforestation project areas increased by 2 % and 20 % during the two periods. From 2001 to 2022, at the regional scale, the Shelterbelt program for the middle reaches of the Yellow River area exhibited the largest rate of increase (43 %) in BVOC emissions. The Shelterbelt program for the upper and middle reaches of the Yangtze River made the most largest contribution (45 %) to the national increase in BVOC emissions. Afforestation projects have shifted towards planting more broadleaf trees than needleleaf trees from 2001 to 2022, and there also showed a change from herbaceous plants to broadleaf trees. These trends have led to higher average emission factors for vegetation, resulting in increased BVOC emissions. It underscores the importance of considering BVOC emissions when evaluating afforestation initiatives, emphasizing the need to balancing ecological benefits with potential atmospheric consequences.

Predicting Microbe-Disease Associations Based on a Linear Neighborhood Label Propagation Method with Multi-order Similarity Fusion Learning.

Computational approaches employed for predicting potential microbe-disease associations often rely on similarity information between microbes and diseases. Therefore, it is important to obtain reliable similarity information by integrating multiple types of similarity information. However, existing similarity fusion methods do not consider multi-order fusion of similarity networks. To address this problem, a novel method of linear neighborhood label propagation with multi-order similarity fusion learning (MOSFL-LNP) is proposed to predict potential microbe-disease associations. Multi-order fusion learning comprises two parts: low-order global learning and high-order feature learning. Low-order global learning is used to obtain common latent features from multiple similarity sources. High-order feature learning relies on the interactions between neighboring nodes to identify high-order similarities and learn deeper interactive network structures. Coefficients are assigned to different high-order feature learning modules to balance the similarities learned from different orders and enhance the robustness of the fusion network. Overall, by combining low-order global learning with high-order feature learning, multi-order fusion learning can capture both the shared and unique features of different similarity networks, leading to more accurate predictions of microbe-disease associations. In comparison to six other advanced methods, MOSFL-LNP exhibits superior prediction performance in the leave-one-out cross-validation and 5-fold validation frameworks. In the case study, the predicted 10 microbes associated with asthma and type 1 diabetes have an accuracy rate of up to 90% and 100%, respectively.

Queen bee gut microbiota extends honeybee lifespan by inhibiting insulin signaling.

Queen and worker bees are natural models for aging research, as their lifespans vary considerably independent of genetic variation. Investigating the reasons why queens live longer than workers is of great significance for research on the universal processes of aging in animals. The gut microbiome has received attention as a vital regulator of host health, while its precise role in honeybee aging needs further investigation. The effects and mechanisms behind the relationship between gut microbiota and worker lifespan were measured by transplanting queen bee gut bacteria (QG) and worker bee gut bacteria (WG) into microbiota-free (MF) workers. The transplantation of QG to MF bees significantly extended the workers' lifespans compared with MF and WG bees. Untargeted metabolomics identified 49 lifespan-related differential metabolites, and Kyoto Encyclopedia of Genes and Genomes analysis of these revealed three lifespan-related metabolic pathways: insulin/insulin-like growth factor signaling, immune, and ketone body metabolism pathways. Further verification showed that QG inhibited the expression of insulin-like peptides (ILPs), and the expression of ILPs was lower in natural queens than in natural workers. QG transplantation also stimulated the expression of antioxidant genes and lowered oxidative damage products in natural queen bees. However, gut microbiota transplantation failed to mimic the immune properties and ketone body metabolism profiles of natural queens and workers. Concisely, QG could increase the antioxidant capacity to extend lifespan by inhibiting insulin signaling. These findings may help determine the mechanisms behind queen longevity and provide further insights into the role of gut symbionts. IMPORTANCE: Queen and worker bees share the same genetic background but have vastly different lifespans. The gut microbiome regulates host health, suggesting that differences in lifespan between queen and worker bees could be related to gut bacteria. Herein, we used an innovative method to transplant gut microbiota from adult queen or worker bees to microbiota-free bees. The transplantation of queen gut microbiota to microbiota-free bees extended their lifespan. Insulin/insulin-like growth factor signaling, a highly conserved metabolic pathway related to lifespan, displayed identical expression profiles in natural queen bees and microbiota-free bees transplanted with queen microbiota. This finding significantly expands our understanding of the relationships between intestinal bacteria, host health, and the biology of aging.

4 mC site recognition algorithm based on pruned pre-trained DNABert-Pruning model and fused artificial feature encoding.

DNA 4 mC plays a crucial role in the genetic expression process of organisms. However, existing deep learning algorithms have shortcomings in the ability to represent DNA sequence features. In this paper, we propose a 4 mC site identification algorithm, DNABert-4mC, based on a fusion of the pruned pre-training DNABert-Pruning model and artificial feature encoding to identify 4 mC sites. The algorithm prunes and compresses the DNABert model, resulting in the pruned pre-training model DNABert-Pruning. This model reduces the number of parameters and removes redundancy from output features, yielding more precise feature representations while upholding accuracy.Simultaneously, the algorithm constructs an artificial feature encoding module to assist the DNABert-Pruning model in feature representation, effectively supplementing the information that is missing from the pre-trained features. The algorithm also introduces the AFF-4mC fusion strategy, which combines artificial feature encoding with the DNABert-Pruning model, to improve the feature representation capability of DNA sequences in multi-semantic spaces and better extract 4 mC sites and the distribution of nucleotide importance within the sequence. In experiments on six independent test sets, the DNABert-4mC algorithm achieved an average AUC value of 93.81%, outperforming seven other advanced algorithms with improvements of 2.05%, 5.02%, 11.32%, 5.90%, 12.02%, 2.42% and 2.34%, respectively.

Oxidative stress, endothelial dysfunction, and N-acetylcysteine in type-2 diabetes mellitus.

Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality globally. Endothelial dysfunction is closely associated with the development and progression of CVDs. Patients with diabetes mellitus (DM) especially type-2 DM exhibit a significant endothelial cell dysfunction with substantially increased risk for CVDs. Excessive reactive oxygen species (ROS) and oxidative stress are important contributing factors to endothelial cell dysfunction and subsequent CVDs. ROS production is significantly increased in DM and is critically involved in the development of endothelial dysfunction in diabetic patients. In the present review, efforts are made to discuss the role of excessive ROS and oxidative stress in the pathogenesis of endothelial dysfunction and the mechanisms for excessive ROS production and oxidative stress in type-2 DM. Although studies with diabetic animal models have shown that targeting ROS with traditional antioxidant vitamins C and E or other antioxidant supplements provides promising beneficial effects on endothelial function, the cardiovascular outcomes of clinical studies with these antioxidant supplements have been inconsistent in diabetic patients. Preclinical and limited clinical data suggest that N-acetylcysteine (NAC) treatment may improve endothelial function in diabetic patients. However, well designed clinical studies are needed to determine if NAC supplementation would effectively preserve endothelial function and improve the clinical outcomes of diabetic patients with reduced cardiovascular morbidity and mortality. With better understanding on the mechanisms of ROS generation and ROS-mediated endothelial damages/dysfunction, it is anticipated that new selective ROS-modulating agents, and effective personalized strategies will be developed for the management of endothelial dysfunction in DM.

Elucidating the crosstalk between endothelial-to-mesenchymal transition (EndoMT) and endothelial autophagy in the pathogenesis of atherosclerosis.

Atherosclerosis, a chronic systemic inflammatory condition, is implicated in most cardiovascular ischemic events. The pathophysiology of atherosclerosis involves various cell types and associated processes, including endothelial cell activation, monocyte recruitment, smooth muscle cell migration, involvement of macrophages and foam cells, and instability of the extracellular matrix. The process of endothelial-to-mesenchymal transition (EndoMT) has recently emerged as a pivotal process in mediating vascular inflammation associated with atherosclerosis. This transition occurs gradually, with a significant portion of endothelial cells adopting an intermediate state, characterized by a partial loss of endothelial-specific gene expression and the acquisition of "mesenchymal" traits. Consequently, this shift disrupts endothelial cell junctions, increases vascular permeability, and exacerbates inflammation, creating a self-perpetuating cycle that drives atherosclerotic progression. While endothelial cell dysfunction initiates the development of atherosclerosis, autophagy, a cellular catabolic process designed to safeguard cells by recycling intracellular molecules, is believed to exert a significant role in plaque development. Identifying the pathological mechanisms and molecular mediators of EndoMT underpinning endothelial autophagy, may be of clinical relevance. Here, we offer new insights into the underlying biology of atherosclerosis and present potential molecular mechanisms of atherosclerotic resistance and highlight potential therapeutic targets.

The simultaneous presence of demoralization, apathy, and depression has a detrimental impact on both cognitive function and motor symptoms in Parkinson's disease patients.

Objective: Parkinson's disease (PD) is marked not only by motor symptoms but also by neuropsychiatric manifestations, including demoralization, apathy, and depression. Understanding the clinical distribution and characteristics of these co-occurring symptoms is crucial for improving quality of life of PD patients. Methods: This study enrolled 195 Chinese PD patients from Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine. The study involved analyzing the clinical characteristics related to the simultaneous presence of demoralization, apathy, and depression in PD patients. Linear regression was employed to elucidate the linear trend between the quantity of negative neuropsychiatric symptoms and cognitive function, as well as motor symptoms and motor complications. SPSS mediation models were utilized to investigate whether the severity of cognitive function mediated the connection between multiple negative neuropsychiatric symptoms and motor symptoms. Results: Among PD patients, a notable 57.5% experience the presence of multiple concurrent negative neuropsychiatric symptoms. Our investigation unveiled a correlation where patients with more negative neuropsychiatric symptoms displayed heightened cognitive impairment (P=0.048) and more severe motor symptoms (P=0.024), following a linear trend with increasing symptom numbers. Additionally, cognitive impairment played a partial mediating role in the impact of multiple negative neuropsychiatric symptoms on motor symptoms (ß=0.747; 95% bootstrap confidence interval: 0.195 to 1.532). Conclusions: The co-occurrence of these negative neuropsychiatric symptoms has the potential to worsen cognitive function and motor symptoms in PD patients. Moreover, cognitive impairment was identified as playing a partial mediating role in the relationship between multiple negative neuropsychiatric symptoms and motor symptoms.

CircDCBLD2 alleviates liver fibrosis by regulating ferroptosis via facilitating STUB1-mediated PARK7 ubiquitination degradation.

BACKGROUND: Liver fibrosis can progress to cirrhosis and hepatic carcinoma without treatment. CircDCBLD2 was found to be downregulated in liver fibrosis. However, the precise underlying mechanism requires further investigation. METHODS: qRT-PCR, Western blot, and immunohistochemistry assays were used to detect the related molecule levels. HE, Masson's trichrome, and Sirius Red staining were used to assess the pathological changes in mice's liver tissues. Flow cytometric analysis and commercial kit were used to assess the levels of lipid reactive oxygen species (ROS), malonaldehyde (MDA), glutathione (GSH), and iron. Cell viability was assessed by MTT. Immunoprecipitation was used to study the ubiquitination of PARK7. Mitophagy was determined by immunostaining and confocal imaging. RIP and Co-IP assays were used to assess the interactions of circDCBLD2/HuR, HuR/STUB1, and STUB1/PARK7. Fluorescence in situ hybridization and immunofluorescence staining were used to assess the co-localization of circDCBLD2 and HuR. RESULTS: CircDCBLD2 was downregulated, whereas PARK7 was upregulated in liver fibrosis. Ferroptosis activators increased circDCBLD2 while decreasing PARK7 in hepatic stellate cells (HSCs) and mice with liver fibrosis. CircDCBLD2 overexpression reduced cell viability and GSH, PARK7, and GPX4 expression in erastin-treated HSCs while increasing MDA and iron levels, whereas circDCBLD2 knockdown had the opposite effect. CircDCBLD2 overexpression increased STUB1-mediated PARK7 ubiquitination by promoting HuR-STUB1 binding and thus increasing STUB1 mRNA stability. PARK7 overexpression or HuR knockdown reversed the effects of circDCBLD2 overexpression on HSC activation and ferroptosis. CircDCBLD2 reduced liver fibrosis in mice by inhibiting PARK7. CONCLUSION: CircDCBLD2 overexpression increased PARK7 ubiquitination degradation by upregulating STUB1 through its interaction with HuR, inhibiting HSC activation and promoting HSC ferroptosis, ultimately enhancing liver fibrosis.

Impulse control behaviors and apathy commonly co-occur in de novo Parkinson's disease and predict the incidence of levodopa-induced dyskinesia.

OBJECTIVE: Impulse control behaviors (ICBs) and apathy are believed to represent opposite motivational expressions of the same behavioral spectrum involving hypo- and hyperdopaminergic status, but this has been recently debated. Our study aims to estimate the co-occurrence of ICBs and apathy in early Parkinson's disease (PD) and to determine whether this complex neuropsychiatric condition is an important marker of PD prognoses. METHODS: Neuropsychiatric symptoms, clinical data, neuroimaging results, and demographic data from de novo PD patients were obtained from the Parkinson's Progression Markers Initiative, a prospective, multicenter, observational cohort. The clinical characteristics of ICBs co-occurring with apathy and their prevalence were analyzed. We compared the prognoses of the different groups during the 8-year follow-up. Multivariate Cox regression analysis was conducted to predict the development of levodopa-induced dyskinesia (LID) using baseline neuropsychiatric symptoms. RESULTS: A total of 422 PD patients and 195 healthy controls (HCs) were included. In brief, 87 (20.6 %) de novo PD patients and 37 (19.0 %) HCs had ICBs at baseline. Among them, 23 (26.4 %) de novo PD patients and 3 (8.1 %) HCs had clinical symptoms of both ICBs and apathy. The ICBs and apathy group had more severe non-motor symptoms than the isolated ICBs group. Cox regression analysis demonstrated that the co-occurrence of ICBs and apathy was a risk factor for LID development (HR 2.229, 95 % CI 1.209 to 4.110, p = 0.010). CONCLUSIONS: Co-occurrence of ICBs and apathy is common in patients with early PD and may help to identify the risk of LID development.

Wearable All-Fabric Hybrid Energy Harvester to Simultaneously Harvest Radiofrequency and Triboelectric Energy.

Distributed micro-energy harvesting devices offer the flexibility, sustainability, and multi-scenario applicability that will be critical to wearable electronic products in the Internet of Things. The radiofrequency and triboelectric (RF-TE) hybrid energy harvester (HEH) concept and prototype is presented for the first time, to simultaneously capture the energy from ambient electromagnetic waves and biological motions. The proposed hybrid energy harvesting system consists of a wearable rectenna, a triboelectric nanogenerator (TENG), and a power management circuit (PMC). Among them, the all-fabric rectenna exhibits good impedance matching characteristics in the ISM frequency. The flexible TENG unit can generate a maximum power density of 0.024 µW cm-2 . The designed multifunctional fabric-based PMC can considerably enhance the controllability of harvested hybrid energy. Additionally, a normalizable fabric circuit board quasi surface mount technology (FCB-SMT) is proposed to integrate all modules on the same fabric substrate in one step, making the entire system superior mechanical robustness. The proposed wearable fabric-based RF-TE hybrid energy harvester is capable of successfully driving consumer electronics (such as sensors, watches, etc.). It provides a new energy solution strategy for self-powered wearable electronic devices and is anticipated to encourage the efficient utilization of renewable energy.

Short sleep duration is associated with worse quality of life in Parkinson's disease: A multicenter cross-sectional study.

OBJECTIVE: To characterize sleep duration and investigate its association with quality of life among Parkinson's Disease (PD) patients. METHODS: In this multicenter cross-sectional study, 970 PD patients were divided into five groups based on self-reported sleep duration: <5, ≥5 to <6, ≥6 to <7, ≥7 to ≤8, and >8 h. The quality of life was evaluated using the 39-Item Parkinson's Disease Questionnaire (PDQ-39). Multivariable linear regression analysis, subgroup analysis, and mediation analysis were conducted to examine the association between sleep duration and quality of life. RESULTS: In multivariable linear regression model, patients with sleep duration (<5 h) had significantly higher PDQ-39 scores (ß = 8.132, 95 % CI: 3.99 to 12.266), especially in mobility, activities of daily living, emotional well-being, stigma, social support, cognition, communication, and bodily discomfort (p < 0.05). The association between sleep duration (<5 h) and worse quality of life was more pronounced in patients with higher HY stage, longer disease duration, and sleep disorders. Moreover, a significant indirect effect of sleep duration (<5 h) on quality of life was observed, with UPDRS I, UPDRS II, and UPDRS IV scores acting as mediators. CONCLUSIONS: Short sleep duration (<5 h) is associated with worse quality of life among PD patients. This association was stronger among patients with advanced PD and sleep disorders, while non-motor symptoms and motor complications were identified as significant mediators in this association. These findings highlight the significance of adequate sleep duration and suitable interventions for sleep may help improve quality of life.

Isolation of the AccCDK8 gene of Apis cerana cerana and its functional analysis under pesticide and heavy metal stress.

Environmental pollution has gained negative attention in recent years. The pesticides and heavy metals are top list of environmental toxicants directly endangering the survival and development of Apis cerana cerana. Cyclin-dependent kinases (CDKs) are heteromeric serine/threonine kinases that participate in cell cycle regulation and have a vital role in pesticide and heavy metal stress in Apis cerana cerana. In this experiment, we filtered out CDK8 gene from Apis cerana cerana (AccCDK8) and investigated its functions of pesticide and heavy metals resistance. Sequence analysis indicated that AccCDK8 is highly homologous to multiple CDK8s and contains a highly conserved CDK active site sequence. Phylogenetic analysis showed that AmCDK8 and AccCDK8 were closely related evolutionarily in Apis mellifera. Transcriptome analysis revealed that AccCDK8 expression was differentially affected after exposure to pesticide and heavy metal stresses. This indicates that AccCDK8 has a significant role in the resistance of Apis cerana cerana to pesticide and heavy metal stresses. It has implications for studying the function of CDK in other insects in response to stress.

Prediction of miRNA-disease associations based on strengthened hypergraph convolutional autoencoder.

Most existing graph neural network-based methods for predicting miRNA-disease associations rely on initial association matrices to pass messages, but the sparsity of these matrices greatly limits performance. To address this issue and predict potential associations between miRNAs and diseases, we propose a method called strengthened hypergraph convolutional autoencoder (SHGAE). SHGAE leverages multiple layers of strengthened hypergraph neural networks (SHGNN) to obtain robust node embeddings. Within SHGNN, we design a strengthened hypergraph convolutional network module (SHGCN) that enhances original graph associations and reduces matrix sparsity. Additionally, SHGCN expands node receptive fields by utilizing hyperedge features as intermediaries to obtain high-order neighbor embeddings. To improve performance, we also incorporate attention-based fusion of self-embeddings and SHGCN embeddings. SHGAE predicts potential miRNA-disease associations using a multilayer perceptron as the decoder. Across multiple metrics, SHGAE outperforms other state-of-the-art methods in five-fold cross-validation. Furthermore, we evaluate SHGAE on colon and lung neoplasms cases to demonstrate its ability to predict potential associations. Notably, SHGAE also performs well in the analysis of gastric neoplasms without miRNA associations.

Direct Fuzzy Adaptive Regulation for High-Order Delayed Systems: A Lyapunov-Razumikhin Function Method.

A slow time-delay assumption restricts the application of control approaches for numerous systems which are constantly affected by multiple uncertainties, including parameters, control coefficients, and the asymmetric dead-zone input. This work presents a new adaptive method for a class of high-order nonlinear delayed systems by removing the so-called slow time-delay assumption and multiple uncertainties. Remarkably, with a novel Lyapunov-Razumikhin (L-R) function and a direct fuzzy adaptive regulation scheme, a memoryless adaptive feedback controller is skillfully constructed to guarantee that the output tracks the given reference signal while keeping the boundedness of all closed-system signals. Finally, the presented scheme is applied to control a single-link robot system.

Comparison of the somatic genomic landscape between central- and peripheral-type non-small cell lung cancer.

OBJECTIVE: Lung cancer is classified into central and peripheral types based on the anatomic location. The present study aimed to explore the distinct patterns of genomic alterations between central- and peripheral-type non-small cell lung cancers (NSCLCs) with negative driver genes and identify potential driver genes and biomarkers to improve therapy strategies for NSCLC. METHODS: Whole-exome sequencing (WES) was performed with 182 tumor/control pairs of samples from 145 Chinese NSCLC patients without EGFR, ALK, or ROS1 alterations. Significantly mutated genes (SMGs) and somatic copy number alterations (SCNAs) were identified. Subsequently, tumor mutation burden (TMB), weighted genome integrity index (wGII), copy number alteration (CNA) burden, Shannon diversity index (SDI), intratumor heterogeneity (ITH), neoantigen load (NAL), and clonal variations were evaluated in central- and peripheral-type NSCLCs. Furthermore, mutational signature analysis and survival analysis were performed. RESULTS: TP53 was the most frequently mutated gene in NSCLC and more frequently mutated in central-type NSCLC. Higher wGII, ITH, and SDI were found in central-type lung adenocarcinoma (LUAD) than in peripheral-type LUAD. The NAL of central-type lung squamous cell carcinoma (LUSC) with stage III/IV was significantly higher than that of peripheral-type LUSC. Mutational signature analysis revealed that SBS10b, SBS24, and ID7 were significantly different in central- and peripheral-type NSCLCs. Furthermore, central-type NSCLC was found to evolve at a higher level with fewer clones and more subclones, particularly in central-type LUSC. Survival analysis revealed that TMB, CNA burden, NAL, subclonal driver mutations, and subclonal mutations were negatively related to the overall survival (OS) and the progression-free survival (PFS) of central-type LUAD. CONCLUSIONS: Central-type NSCLC tended to evolve at a higher level and might suggest a favorable response to immunotherapy. Our study also identified several potential driver genes and promising biomarkers for the prognosis and prediction of chemotherapy responses in NSCLC.

Toxic effects of the heavy metal Cd on Apis cerana cerana (Hymenoptera: Apidae): Oxidative stress, immune disorders and disturbance of gut microbiota.

Cadmium (Cd) is a toxic non-essential metal element that can enter the honey bee body through air, water and soil. Currently, there is a lack of sufficient research on the effects of Cd on A. cerana cerana, especially the potential risks of long-term exposure to sublethal concentrations. In order to ascertain the toxicological effects of the heavy metal Cd on bees, we performed laboratory-based toxicity experiments on worker bees and conducted analyses from three distinctive facets: antioxidative, immunological, and gut microbiota. The results showed that exposure of bees to high concentrations of Cd resulted in acute mortality, and the increase in mortality was concentration dependent. In long-term exposure to sublethal concentrations, Cd reduced the number of transcripts of antioxidant genes (AccSOD1, AccTPx3 and AccTPx4) and superoxide dismutase activity, causing an increase in malondialdehyde content. Simultaneously, the transcription of immune-related genes (AccAbaecin and AccApidaecin) and acetylcholinesterase activities was inhibited. Furthermore, Cd changes the structural characteristics of bacterial and fungal communities in the gut, disrupting the balance of microbial communities. In conclusion, the health and survival of honey bees are affected by Cd. This study provides a scientific basis for investigating the toxicological mechanisms and control strategies of the heavy metal Cd on honey bees, while facilitating a better understanding and protection of these valuable honey bees.

The gene AccCyclin H mitigates oxidative stress by influencing trehalose metabolism in Apis cerana cerana.

BACKGROUND: Environmental stress can induce oxidative stress in Apis cerana cerana, leading to cellular oxidative damage, reduced vitality, and even death. Currently, owing to an incomplete understanding of the molecular mechanisms by which A. cerana cerana resists oxidative damage, there is no available method to mitigate the risk of this type of damage. Cyclin plays an important role in cell stress resistance. The aim of this study was to explore the in vivo protection of cyclin H against oxidative damage induced by abiotic stress in A. cerana cerana and clarify the mechanism of action. We isolated and identified the AccCyclin H gene in A. cerana cerana and analysed its responses to different exogenous stresses. RESULTS: The results showed that different oxidative stressors can induce or inhibit the expression of AccCyclin H. After RNA-interference-mediated AccCyclin H silencing, the activity of antioxidant-related genes and related enzymes was inhibited, and trehalose metabolism was reduced. AccCyclin H gene silencing reduced A. cerana cerana high-temperature tolerance. Exogenous trehalose supplementation enhanced the total antioxidant capacity of A. cerana cerana, reduced the accumulation of oxidants, and improved the viability of A. cerana cerana under high-temperature stress. CONCLUSION: Our findings suggest that trehalose can alleviate adverse stress and that AccCyclin H may participate in oxidative stress reactions by regulating trehalose metabolism. © 2023 Society of Chemical Industry.