Decreased resting-state functional connectivity and brain network abnormalities in the prefrontal cortex of elderly patients with Parkinson's disease accompanied by depressive symptoms.

This study aimed to explore the brain network characteristics in elderly patients with Parkinson's disease (PD) with depressive symptoms. Thirty elderly PD patients with depressive symptoms (PD-D) and 26 matched PD patients without depressive symptoms (PD-NOD) were recruited based on HAMD-24 with a cut-off of 7. The resting-state functional connectivity (RSFC) was conducted by 53-channel functional near-infrared spectroscopy (fNIRS). There were no statistically significant differences in MMSE scores, disease duration, Hoehn-Yahr stage, daily levodopa equivalent dose, and MDS-UPDRS III between the two groups. However, compared to the PD-NOD group, the PD-D group showed significantly higher MDS-UPDRS II, HAMA-14, and HAMD-24. The interhemispheric FC strength and the FC strength between the left dorsolateral prefrontal cortex (DLPFC-L) and the left frontal polar area (FPA-L) was significantly lower in the PD-D group (FDR p < 0.05). As for graph theoretic metrics, the PD-D group had significantly lower degree centrality (aDc) and node efficiency (aNe) in the DLPFC-L and the FPA-L (FDR, p < 0.05), as well as decreased global efficiency (aEg). Pearson correlation analysis indicated moderate negative correlations between HAMD-24 scores and the interhemispheric FC strength, FC between DLPFC-L and FPA-L, aEg, aDc in FPA-L, aNe in DLPFC-L and FPA-L. In conclusion, PD-D patients show decreased integration and efficiency in their brain networks. Furthermore, RSFC between DLPFC-L and FPA-L regions is negatively correlated with depressive symptoms. These findings propose that targeting DLPFC-L and FPA-L regions via non-invasive brain stimulation may be a potential intervention for alleviating depressive symptoms in elderly PD patients.

Association of dietary selenium intake and all-cause mortality of Parkinson's disease and its interaction with blood cadmium level: a retrospective cohort study.

BACKGROUND: Parkinson's disease (PD) is a slowly progressive neurodegenerating disease that may eventually lead to disabling condition and pose a threat to the health of aging populations. This study aimed to explore the association of two potential risk factors, selenium and cadmium, with the prognosis of Parkinson's disease as well as their interaction effect. METHODS: Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2005-2006 to 2015-2016 and National Death Index (NDI). Participants were classified as Parkinson's patients by self-reported anti-Parkinson medications usage. Cox regression models and restricted cubic spline models were applied to evaluate the association between PD mortality and selenium intake level as well as blood cadmium level. Subgroup analysis was also conducted to explore the interaction between them. RESULTS: A total of 184 individuals were included. In full adjusted cox regression model (adjusted for age, gender, race, hypertension, pesticide exposure, smoking status and caffeine intake), compared with participants with low selenium intake, those with normal selenium intake level were significantly associated with less risk of death (95%CI: 0.18-0.76, P = 0.005) while no significant association was found between low selenium intake group and high selenium group (95%CI: 0.16-1.20, P = 0.112). Restricted cubic spline model indicated a nonlinear relationship between selenium intake and PD mortality (P for nonlinearity = 0.050). The association between PD mortality and blood cadmium level was not significant (95%CI: 0.19-5.57, P = 0.112). However, the interaction term of selenium intake and blood cadmium showed significance in the cox model (P for interaction = 0.048). Subgroup analysis showed that the significant protective effect of selenium intake existed in populations with high blood cadmium but not in populations with low blood cadmium. CONCLUSION: Moderate increase of selenium intake had a protective effect on PD mortality especially in high blood cadmium populations.

GLP-1 receptor agonists and myocardial metabolism in atrial fibrillation.

Atrial fibrillation (AF) is the most common cardiac arrhythmia. Many medical conditions, including hypertension, diabetes, obesity, sleep apnea, and heart failure (HF), increase the risk for AF. Cardiomyocytes have unique metabolic characteristics to maintain adenosine triphosphate production. Significant changes occur in myocardial metabolism in AF. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have been used to control blood glucose fluctuations and weight in the treatment of type 2 diabetes mellitus (T2DM) and obesity. GLP-1RAs have also been shown to reduce oxidative stress, inflammation, autonomic nervous system modulation, and mitochondrial function. This article reviews the changes in metabolic characteristics in cardiomyocytes in AF. Although the clinical trial outcomes are unsatisfactory, the findings demonstrate that GLP-1 RAs can improve myocardial metabolism in the presence of various risk factors, lowering the incidence of AF.

Effects of abamectin nanocapsules on bees through host physiology, immune function, and gut microbiome.

Pesticide usage is a common practice to increase crop yields. Nevertheless, the existence of pesticide residues in the surrounding environment presents a significant hazard to pollinators, specifically the potential undisclosed dangers related to emerging nanopesticides. This study examines the impact of abamectin nanocapsules (AbaNCs), created through electrostatic self-assembly, as an insecticide on honey bees. It was determined that AbaNCs upregulated detoxification genes, including CYP450, as well as antioxidant and immune genes in honey bees. Furthermore, AbaNCs affected the activity of crucial enzymes such as superoxide dismutase (SOD). Although no apparent damage was observed in bee gut tissue, AbaNCs significantly decreased digestive enzyme activity. Microbiome sequencing revealed that AbaNCs disrupted gut microbiome, resulting in a reduction of beneficial bacteria such as Bifidobacterium and Lactobacillus. Additionally, these changes in the gut microbiome were associated with decreased activity of digestive enzymes, including lipase. This study enhances our understanding of the impact of nanopesticides on pollinating insects. Through the revelation of the consequences arising from the utilization of abamectin nanocapsules, we have identified potential stress factors faced by these pollinators, enabling the implementation of improved protective measures.

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.

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.

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.

Oxidative Stress, Endothelial Dysfunction, and N-Acetylcysteine in Type 2 Diabetes Mellitus.

Significance: 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 (T2DM) exhibit a significant endothelial cell (EC) dysfunction with substantially increased risk for CVDs. Recent Advances: Excessive reactive oxygen species (ROS) and oxidative stress are important contributing factors to EC 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 this 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 T2DM. Critical Issues: 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. Future Directions: 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.

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.

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.

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.

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.

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.

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.

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.

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.