Objective To investigate the trends in the global burden due to cystic echinococcosis from 1990 to 2021, and to predict the global burden of cystic echinococcosis from 2022 to 2035, so as to provide insights into formulation of the cystic echinococcosis control strategy. Methods The global age-standardized prevalence, mortality, disability-adjusted life years (DALYs) rates and their 95% uncertainty intervals (UI) of cystic echinococcosis from 1990 to 2021 were captured from the Global Burden of Disease Study 2021 (GBD 2021) database, and the trends in the global burden of cystic echinococcosis from 1990 to 2021 were analyzed using the Joinpoint regression model. The associations between the global burden of cystic echinococcosis and socio-demographic index (SDI) were examined using a smoothing spline model and frontier analysis, and the global burden of cystic echinococcosis was projected from 2022 to 2035 using the Bayesian age-period-cohort (BAPC) model. Results The global agestandardized prevalence, mortality and DALYs rates of cystic echinococcosis were 7.69/10⁵ [95% UI: (6.27/10⁵, 9.51/10⁵)], 0.02/10⁵ [95% UI: (0.01/10⁵, 0.02/10⁵)], and 1.32/10⁵ [95% UI: (0.99/10⁵, 1.69/10⁵)] in 2021. The global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a rise by 0.14% per year from 1990 to 2021, and the global age-standardized mortality and DALYs rates of cystic echinococcosis appeared a tendency towards a decline by 4.68% and 4.01% per year from 1990 to 2021, respectively. Joinpoint regression analysis showed that global age-standardized prevalence of cystic echinococcosis appeared a tendency towards a decline from 1990 to 2000 [annual percent change (APC) = −0.66%, 95% confidence interval (CI): (−0.70%, −0.61%)] and from 2005 to 2015 [APC = −0.88%, 95% CI: (−0.93%, −0.82%)], and towards a rise from 2000 to 2005 [APC = 3.68%, 95% CI: (3.49%, 3.87%)] and from 2015 to 2021 [APC=0.30%, 95%CI: (0.19%, 0.40%)].Theagestandardized prevalence (r = −0.17, P < 0.05), mortality (r = −0.67, P < 0.05) and DALYs rates of cystic echinococcosis (r = −0.60, P < 0.05) all correlated negatively with SDI across 21 geographical regions from 1990 to 2021, and the age-standardized mortality (r = −0.61, P < 0.05) and DALYs rates (r = −0.44, P < 0.05) both correlated negatively with SDI across 204 countries and territories in 2021. Frontier analysis revealed that the age-standardized DALYs rate of cystic echinococcosis was still not in line with the frontier in some high-SDI countries or territories. In addition, the global age-standardized prevalence was projected with the BAPC model to appear a tendency towards a rise among both men [estimated annual percent change (EAPC) = 0.18%, 95% CI: (0.13%, 0.23%)] and women [EAPC = 0.29%, 95% CI: (0.24%, 0.34%)] from 2022 to 2035, and the global age-standardized mortality [men: EAPC = −4.71%, 95% CI: (−4.71%, −4.37%); women: EAPC = −4.74%, 95% CI: (−4.74%, −4.74%)] and DALYs rates [men: EAPC = −3.35%, 95% CI: (−3.36%, −3.34%); women: EAPC = −3.17%, 95% CI: (−3.18%, −3.16%)] were projected to appear a tendency towards a decline among both men and women. Conclusions The global burden of cystic echinococcosis appeared an overall tendency towards a decline from 1990 to 2021; however, the global prevalence of cystic echinococcosis is projected to appear a tendency towards a rise from 2022 to 2035. Intensified cystic echinococcosis control programmes are recommended.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Objective:To discuss the effect of royal jelly acid(10-HDA)on the proliferation and migration of the human colon cancer SW620 cells based on the network pharmacology,and to clarify its related molecular mechanism.Methods:The active ingredients such as 10-HDA and their corresponding targets were retrieved by using the keyword"royal jelly"from the Traditiomal Chinese Medicine Systems Pharmacology(TMSCP)Database and the Traditiomal Chinese Medicine Integrated Database(TCMID);the small molecule targets were predicted by the Swiss Target Prediction Database.The GeneCards Database and the Online Mendelian Inheritance in Man(OMIM)Database were used to obtain the targets with the keyword"Colon Cancer";the protein-protein interaction(PPI)network was constructed by using the String Database and Cytoscape 3.8.0 Software to screen the core targets;the Gene Ontology(GO)function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analysis were analyzed by Metascape Database;the specific ingredient 10-HDA was screened for the in vitro activity experiments.The human colon cancer SW620 cells with good growth status were divided into control group and different doses(1,5,10,15,and 20 mmol·L-1)of 10-HDA groups.The viabilities of the cells in various groups were detected by MTT method and the survival rates of the cells were calculated.The SW620 cells were divided into control group,low dose(5 mmol·L-1)of 10-HDA group,middle dose(10 mmol·L-1)of 10-HDA group,and high dose(15 mmol·L-1)of 10-HDA group;Hoechst33342 staining method was used to observe the morphology of the cells in various groups;cell scratch test was used to detect the scratch healing rates of the cells in various groups;flow cytometry was used to detect the percentages of the cells at different cell cycles in various groups;biochemical method was used to detect the activities of total antioxidant capacity(T-AOC)and superoxide dismutase(SOD)in the cells in various groups;Western blotting method was used to detect the expression levels of B-cell lymphoma 2(Bcl-2),Bcl-2-associated X protein(Bax),cysteine-containing aspartate proteolytic enzyme-3(Caspase-3),cysteine-containing aspartate proteolytic enzyme-9(Caspase-9),glycogen synthase kinase 3β(GSK3β),β-catenin,and cyclin D1 proteins in the cells in various groups.Results:Six active ingredients of royal jelly were screened out by the TCMSP Database,and 28 core targets of 10-HDA in the treatment of colon cancer were obtained.The GO function enrichment analysis mainly included the signaling pathways such as cell proliferation and apoptosis.The KEGG signaling pathway enrichment analysis included the cell cycle,prostate cancer,cell senescence,and p53 signaling pathways;the GSK3β/β-catenin signaling pathway was closely related to the cell cycle.Compared with control group,the viabilities of the cells in 5,10,15,and 20 mmol·L-110-HDA groups were decreased in a dose-dependent manner(P<0.05 or P<0.01),the numbers of apoptotic cells in different doses of 10-HDA groups were significantly increased,and the scratch healing rates of the cells were significantly decreased(P<0.05 or P<0.01);the percentages of the cells at S phase in middle and high doses of 10-HDA groups were significantly increased(P<0.05 or P<0.01),the activities of T-AOC and SOD in the cells in different doses of 10-HDA groups were significantly decreased(P<0.05 or P<0.01).Compared with control group,the expression level of Bcl-2 protein in the cells in low dose of 10-HDA group was significantly decreased(P<0.01),and the expression level of GSK3β protein was significantly increased(P<0.05);compared with control group,the expression levels of Bax,Caspase-3,Caspase-9,and GSK3β proteins in the cells in middle and high doses of 10-HDA groups were significantly increased(P<0.05 or P<0.01),and the expression levels of Bcl-2,β-catenin,and CyclinD1 proteins were significantly decreased(P<0.01).Conclusion:10-HDA can significantly inhibit the proliferation and migration of the colon cancer cells and promote the apoptosis and oxidation levels of the colon cancer cells,and its mechanism may be related to the activation of the GSK3β/β-catenin signaling pathway.

Objective To conduct an epidemiological survey of common congenital heart disease(CHD)among children in ethnic minority areas in southeastern Guizhou and to explore the influencing factors of delayed medical treatment.Methods From January 2019 to July 2022,18 850 children aged 3 months to 14 years in Qiandongnan Miao and Dong Autonomous Prefecture were selected;105 children with CHD were included in the training set,and they were divided into delayed group(80 cases)and non-delayed group(25 cases)according to whether or not to delay medical treatment.In addition,children with CHD(35 cases)from July 2022 to December 2022 were included in the validation set.The general data of the subjects in the two groups were compared and ana-lyzed.Multivariate logistic regression was performed and risk scoring model was constructed.Results The preva-lence of CHD in 18 850 children was 5.57‰(105/18 850),with the highest prevalence in Liping County,and the lowest in Huangping County.The proportion of children with secondary atrial septal defect was the highest,and that of the aortic valve malformation was the lowest.Among the complex cases of CHD,the proportion of children with single type was the highest,and that of children with three or more types were the lowest.Among children with CHD,the rate of delayed medical treatment was 76.19% (80/105).The median delay in medical treatment was 12 months,with an average of(18.78±4.77)months.Multifactor logistic regression analysis showed that heart murmur(level 2～3),less-educated(primary and secondary school)guardian,family per capita income<2 000 yuan,and frequent drinking of the guardian were independent risk factors for delayed medical treatment(P<0.05),and commercial settlement of medical expenses was independent protective factor(P<0.05).Risk scoring model divided the children into three groups:low risk(≤80 points),medium risk(>80 points and≤134 points)and high(>134 points)risk group.The evaluation of the model show that it was accurate,effective,safe,and reliable.Conclusion The highest prevalence is observed in Liping County.The proportion of children with secondary atrial septal defect and the proportion of children with single type are the highest.Delayed medical treat-ment is found in most of the children with CHD.Cardiac murmur,education background of the guardian,per capita family income,guardian alcohol consumption,and medical expense settlement method are all independent influencing factors for delayed medical treatment.

The growth of three plague phages from Qinghai Plateau in two Yersinia pestis strains(plague vaccine strains EV76 and 614F)and four non-Yersinia pestis strains(Yersinia pseudotuberculosis PTB3,PTB5,Escherichia coli V517,and Yersinia enterocolitica 52302-2)were detected through a micromethod based on the OmniLogTM microbial identification system and by the drop method,to provide a scientific basis for future ecological studies and classification based on the host range.For plague vaccine strains EV76 and 614F,successful phage infection and subsequent phage growth were observed in the host bacte-rium.Diminished bacterial growth and respiration and a concomitant decrease in color were observed with the OmniLogTM mi-crobial identification system at 33 ℃ for 48 h.Yersinia pseudotuberculosis PTB5 was sensitive to Yersinia pestis phage 476,but Yersinia pseudotuberculosis PST5 was insensitive to phage 087 and 072204.Three strains of non-Yersinia pestis(Yersinia pseudotuberculosis PTB3,Escherichia coli V517,and Yersinia enterocolitica 52302-2)were insensitive to Yersinia pestis pha-ges 087,072204,and 476 showed similar growth curves.The growth of phages 476 and 087,as determined with the drop method,in two Yersinia pestis strains(plague vaccine strains EV76 and 614F)and four non-Yersinia pestis strains(Yersinia pseudotuberculosis PTB3,Escherichia coli V517,and Yersin-ia enterocolitica 52302-2)showed the same results at 37 ℃,on the basis of comparisons with the OmniLogTM microbial i-dentification system;in contrast,phages 072204 did not show plaques on solid medium at 37 ℃ with plague vaccine strains EV76 and 614F.Determination based on the OmniLogTM detection system can be used as an alternative to the traditional determination of the host range,thus providing favorable application val-ue for determining the interaction between the phage and host bacteria.

Objective To analyze the factors affecting the prognosis of patients with knee osteoarthritis,and to construct a nomogram prediction model in conjunction with multi-dimensional clinical indicators.Methods The clinical data of 234 pa-tients with knee osteoarthritis who were treated in our hospital from January 2015 to June 2021 were retrospectively analyzed,including 126 males and 108 females;age more than 60 years old for 135 cases,age less than 60 years old for 99 cases.Lysholm knee function score was used to evaluate the prognosis of the patients,and the patients were divided into good progno-sis group for 155 patients and poor prognosis group for 79 patients according to the prognosis.The clinical data of the subjects in the experimental cohort were analyzed by single factor and multiple factors.The patients were divided into experimental co-hort and verification cohort,the results of the multiple factor analysis were visualized to obtain a nomogram prediction model,the receiver operating characteristic curve(ROC),calibration curve and decision curve were used to evaluate the model's dis-crimination,accuracy and clinical benefit rate.Results The results of multivariate analysis showed that smoking,pre-treatment K-L grades of Ⅲto Ⅳ,and high levels of interleukin 6(IL-6)and matrix metallo proteinase-3(MMP-3)were risk factors for the prognosis of patients with knee osteoarthritis.ROC test results showed that the area under the curve of the nomogram model in the experimental cohort and validation cohort was 0.806[95％CI(0.742,0.866)]and 0.786[(95％CI(0.678,0.893)],re-spectively.The results of the calibration curve showed that the Brier values of the experimental cohort and verification cohort were 0.151 points and 0.134 points,respectively.When the threshold probability value in the decision curve was set to 31％,the clinical benefit rates of the experimental cohort and validation cohort were 51％and 56％,respectively.Conclusion The prognostic model of patients with knee osteoarthritis constructed based on multi-dimensional clinical data has both theoretical and practical significance,and can provide a reference for taking targeted measures to improve the prognosis of patients.

Objective To investigate the status of application of the central venous access in the departments of hematology to develop targeted administrative strategies and provide evidence for management.Methods A self-de-signed questionnaire was applied and convenience sampling was adopted in 93 hematology departments from 48 hospitals in 19 provinces(autonomous regions,municipalities).Results A total of 91 valid questionnaires were col-lected,with a valid questionnaire response rate of 97.85％.Among the 91 hematology departments,91(100％),73(80.22％),and 68(74.73％)carried out PICC,central venous catheter,and totally implantable access port catheteriza-tion,respectively.In the evaluation of blood test indicators before central venous access,the items with a higher e-valuation proportion were platelet count(100％)and D-dimer concentration(87.91％),while the evaluation proportion of other items was＜85％.When PICC catheterization,97.80％of hematology departments prefer basilic vein;83.52％of hematology departments used zone insertion method;95.60％of hematology departments had a skin disinfection range of ≥20 cm;98.90％of hematology departments had catheterization under ultrasound guidance;67.03％and 96.70％of hematology departments used the intracardiac electrocardiogram method or ultrasound assisted localiza-tion,postoperative X-ray localization;12.09％and 53.85％of hematology departments carried out tunnel catheteriza-tion and blunt separation expansion techniques,respectively.In terms of maintenance of central venous access de-vices,82.42％of hematology departments used disposable specialized maintenance kits;61.54％of hematology de-partments used transparent patches to fix PICC;45.21％of hematology departments used suture to fix central venous catheters;24.18％of hematology departments used cotton swabs to disinfect infusion joints;60.44％of hematology departments did not use disposable infusion joint disinfection cap;74.73％of hematology departments used gauze compression to prevent puncture site bleeding;only 6.59％hematology departments used antibacterial dressings con-taining chlorhexidine to prevent puncture site infections.In terms of quality management of central venous access devices,94.51％and 86.81％of hematology departments regularly conducted quality inspections of central venous access,and collected,calculated and analyzed relevant data.50.55％of hematology departments conducted complica-tion risk assessments,and 10.99％of hematology departments had established information management systems for venous therapy.Conclusion The implementation rate of PICC catheterization in the hematology department was relatively high,and the insertion operation basically meets the standard requirements.The evaluation before central venous access catheterization was relatively completed,and the maintenance and management are relatively stan-dardized.However,the evaluation of blood test indicators before the placement of central venous access urgently needs to be standardized and unified.When PICC catheterization,attention should be paid to the application of new technologies,and the information management of venous therapy needs to be improved.

The advent of gene editing represents one of the most transformative breakthroughs in life science, making genome manipulation more accessible than ever before. While traditional CRISPR/Cas-based gene editing, which involves double-strand DNA breaks (DSBs), excels at gene disruption, it is less effective for accurate gene modification. The limitation arises because DSBs are primarily repaired via non-homologous end joining (NHEJ), which tends to introduce indels at the break site. While homology-directed repair (HDR) can achieve precise editing when a donor DNA template is provided, the reliance on DSBs often results in unintended genome damage. HDR is restricted to specific cell cycle phases, limiting its application. Currently, gene editing has evolved to unprecedented levels of precision without relying on DSB and HDR. The development of innovative systems, such as base editing, prime editing, and CRISPR-associated transposases (CASTs), now allow for precise editing ranging from single nucleotides to large DNA fragments. Base editors (BEs) enable the direct conversion of one nucleotide to another, and prime editors (PEs) further expand gene editing capabilities by allowing for the insertion, deletion, or alteration of small DNA fragments. The CAST system, a recent innovation, allows for the precise insertion of large DNA fragments at specific genomic locations. In recent years, the optimization of these precise gene editing tools has led to significant improvements in editing efficiency, specificity, and versatility, with advancements such as the creation of base editors for nucleotide transversions, enhanced prime editing systems for more efficient and precise modifications, and refined CAST systems for targeted large DNA insertions, expanding the range of applications for these tools. Concurrently, these advances are complemented by significant improvements in in vivo delivery methods, which have paved the way for therapeutic application of precise gene editing tools. Effective delivery systems are critical for the success of gene therapies, and recent developments in both viral and non-viral vectors have improved the efficiency and safety of gene editing. For instance, adeno-associated viruses (AAVs) are widely used due to their high transfection efficiency and low immunogenicity, though challenges such as limited cargo capacity and potential for immune responses remain. Non-viral delivery systems, including lipid nanoparticles (LNPs), offer an alternative with lower immunogenicity and higher payload capacity, although their transfection efficiency can be lower. The therapeutic potential of these precise gene editing technologies is vast, particularly in treating genetic disorders. Preclinical studies have demonstrated the effectiveness of base editing in correcting genetic mutations responsible for diseases such as cardiomyopathy, liver disease, and hereditary hearing loss. These technologies promise to treat symptoms and potentially cure the underlying genetic causes of these conditions. Meanwhile, challenges remain, such as optimizing the safety and specificity of gene editing tools, improving delivery systems, and overcoming off-target effects, all of which are critical for their successful application in clinical settings. In summary, the continuous evolution of precise gene editing technologies, combined with advancements in delivery systems, is driving the field toward new therapeutic applications that can potentially transform the treatment of genetic disorders by targeting their root causes.

Through a compound induction method, combined with neurobehavioral, macroscopic characterization and objective pathological evaluation indicators, a murine depression model of liver depression transforming into fire syndrome was constructed and confirmed. The model was constructed using a combination of sleep deprivation, light exposure, and alternate-day food deprivation. Evaluation was conducted at three levels: face validity, constructs validity, and predictive validity. The establishment of the liver depression transforming into fire syndrome depression model was further validated through the counterproof of traditional Chinese medicine formulas. In terms of face validity, compared to the control group, mice in the model group exhibited typical depressive symptoms in neurobehavioral assessments; the general observation of the model group mice reveals disheveled and lackluster fur, along with delayed and easily agitated responses. Additionally, there is a substantial increase in water consumption. In the sleep phase detection of mouse, the model group showed a significant increase in the proportion of time spent in the wake phase during sleep, accompanied by a significant decrease in the proportions of time spent in both non-rapid eye movement (NREM) and rapid eye movement (REM) sleep phases. There are significant differences in physiological indicators such as average blood flow velocity, blood flow rate, tongue, urine, and claw color (r values) in the internal carotid artery. Structural validity demonstrated that levels of 5-hydroxytryptamine (5-HT), dopamine (DA), and γ-aminobutyric acid (GABA) in the hippocampus of model mice decreased significantly, while acetylcholine (ACh), tryptophan (Try), and glutamic acid (Glu) levels increased significantly. Treatment with Danzhi Xiaoyao San led to varying degrees of restoration in the aforementioned neurotransmitters. In terms of predictive validity, the antidepressant paroxetine effectively ameliorated depressive behaviors in the model mice, and the classic formula Danzhi Xiaoyao San demonstrated varying degrees of improvement in depression-related indicators. In conclusion, this study has established a novel animal model of liver-stagnation with the fire depression, thereby expanding the repertoire of traditional Chinese medicine depression models. This development contributes to the diversification of melancholic syndrome models in Chinese medicine, offering a broader spectrum of options for scientific exploration, efficacy evaluation, and drug screening in the future prevention and treatment of depression with traditional Chinese medicine. Animal experiments were conducted with the approval and supervision of the Animal Ethics Committee of Jiangxi University of Traditional Chinese Medicine (ethics number: 20230313040).

Objective The purpose of this study was to investigate the bacterial communities of biting midges and ticks collected from three sites in the Poyang Lake area,namely,Qunlu Practice Base,Peach Blossom Garden,and Huangtong Animal Husbandry,and whether vectors carry any bacterial pathogens that may cause diseases to humans,to provide scientific basis for prospective pathogen discovery and disease prevention and control. Methods Using a metataxonomics approach in concert with full-length 16S rRNA gene sequencing and operational phylogenetic unit(OPU)analysis,we characterized the species-level microbial community structure of two important vector species,biting midges and ticks,including 33 arthropod samples comprising 3,885 individuals,collected around Poyang Lake. Results A total of 662 OPUs were classified in biting midges,including 195 known species and 373 potentially new species,and 618 OPUs were classified in ticks,including 217 known species and 326 potentially new species.Surprisingly,OPUs with potentially pathogenicity were detected in both arthropod vectors,with 66 known species of biting midges reported to carry potential pathogens,including Asaia lannensis and Rickettsia bellii,compared to 50 in ticks,such as Acinetobacter lwoffii and Staphylococcus sciuri.We found that Proteobacteria was the most dominant group in both midges and ticks.Furthermore,the outcomes demonstrated that the microbiota of midges and ticks tend to be governed by a few highly abundant bacteria.Pantoea sp7 was predominant in biting midges,while Coxiella sp1 was enriched in ticks.Meanwhile,Coxiella spp.,which may be essential for the survival of Haemaphysalis longicornis Neumann,were detected in all tick samples.The identification of dominant species and pathogens of biting midges and ticks in this study serves to broaden our knowledge associated to microbes of arthropod vectors. Conclusion Biting midges and ticks carry large numbers of known and potentially novel bacteria,and carry a wide range of potentially pathogenic bacteria,which may pose a risk of infection to humans and animals.The microbial communities of midges and ticks tend to be dominated by a few highly abundant bacteria.