Global, Regional, and National Burdens of Stroke in Children and Adolescents From 1990 to 2019: A Population-Based Study.

BACKGROUND: Stroke is one of the leading causes of death among children, yet evidence on stroke incidence and prognosis in this population is largely neglected worldwide. The aim of this study was to estimate the latest burden of childhood stroke, as well as trends, risk factors, and inequalities from 1990 to 2019, at the global, regional, and national levels. METHODS: The Global Burden of Disease 2019 study was utilized to evaluate the prevalence, incidence, years lived with disability, years of life lost (YLLs), and average annual percentage changes in stroke among populations aged 0 to 19 years from 1990 to 2019. RESULTS: The global age-standardized incidence of stroke increased (average annual percentage change, 0.15% [95% uncertainty interval, 0.09%-0.21%]), while YLLs decreased substantially (average annual percentage change, -3.33% [95% uncertainty interval, -3.38% to -3.28%]) among children and adolescents between 1990 and 2019. Ischemic stroke accounted for 70% of incident cases, and intracerebral hemorrhage accounted for 63% of YLLs. Children under 5 years of age had the highest incidence of ischemic stroke, while adolescents aged 15 to 19 years had the highest incidence of hemorrhagic stroke. In 2019, low-income and middle-income countries were responsible for 84% of incident cases and 93% of YLLs due to childhood stroke. High-sociodemographic index countries had a reduction in YLLs due to stroke that was more than twice as fast as that of low-income and middle-income. CONCLUSIONS: Globally, the burden of childhood stroke continues to increase, especially among females, children aged <5 years, and low-sociodemographic index countries, such as sub-Saharan Africa. The burden of childhood stroke is likely undergoing a significant transition from being fatal to causing disability. Global public health policies and the deployment of health resources need to respond rapidly and actively to this shift.

CCR7 affects the tumor microenvironment by regulating the activation of naïve CD8+ T cells to promote the proliferation of oral squamous cell carcinoma.

BACKGROUND: Head and neck cancer is the sixth most common malignancy worldwide, and oral squamous cell carcinoma (OSCC) is the most common head and neck cancer, being one of the leading causes of cancer morbidity and mortality worldwide. CC Chemokine receptor 7(CCR7) is a multifunctional G protein-coupled trans-membrane chemokine that affects immune cell chemotaxis, migration, and cancer progression through its interaction with its ligands C-C motif chemokine ligand 19(CCL19) and C-C motif chemokine ligand 21(CCL21). Numerous studies have demonstrated the involvement of CCR7 in the malignant progression of a variety of cancers, reflecting the pro-cancer properties of CCR7. The Cancer Genome Atlas data suggests CCR7 has elevated expression in oral cancer. Specifically, CCR7 expression in tumor microenvironment (TME) may regulate the ability of some immune cells to engage in anti-tumor immune responses. Since CD8+ T cells have become a key immunotherapeutic target, the role of CCR7 in antitumor immune response of naïve CD8+ T cells in TME has not been thoroughly investigated. METHODS: A CCR7 knockout mouse model was constructed, and the mechanism of ccr7 on the regulation of tumor microenvironment by naïve CD8+ T cells was verified under the guidance of single-cell RNA sequencing combined with in vivo animal experiments and in vitro cell experiments. RESULTS: CCR7 is knocked out with impaired tumor growth and altered CD8+ T cell profiles, revealing the importance of this protein in OSCC. CONCLUSIONS: Inhibition of CCR7 enhances CD8+ T cell activation, proliferation, and anti-tumor function, suggesting its potential as a therapeutic target.

Analysis of the effect of CCR7 on the microenvironment of mouse oral squamous cell carcinoma by single-cell RNA sequencing technology.

BACKGROUND: Studies have shown that CCR7, an important inflammatory factor, can promote the proliferation and metastasis of oral squamous cell carcinoma (OSCC), but its role in the tumor microenvironment (TME) remains unclear. This paper explores the role of CCR7 in the TME of OSCC. METHODS: In this work, we constructed CCR7 gene knockout mice and OSCC mouse models. Single-cell RNA sequencing (scRNA-seq) and bioinformatics were used to analyze the differences in the OSCC microenvironment between three CCR7 gene knockout mice (KO) and three wild-type mice (WT). Immunohistochemistry, immunofluorescence staining, and flow cytometry were used to analyze the expression of key genes in significantly different cell types between the KO and WT groups. An in vitro experiment was used to verify the effect of CCR7 on M2 macrophage polarization. RESULTS: In the mouse OSCC models, the tumor growth rate in the KO group was significantly lower than that in the WT group. Eight main cell types (including tumor cells, fibroblasts, macrophages, granulocytes, T cells, endothelial cells, monocytes, and B cells) were identified by Seurat analysis. The scRNA-seq results showed that the proportion of tumor cells was lower, but the proportion of inflammatory cells was significantly higher in the KO group than in the WT group. CellPhoneDB analysis results indicated a strong interaction relationship between tumor cells and macrophages, T cells, fibroblasts, and endothelial cells. Functional enrichment results indicated that the expression level of the Dusp1 gene in the KO group was generally higher than that in the WT group in various cell types. Macrophage subclustering results indicated that the proportion of M2 macrophages in the KO group was lower than that in the WT group. In vitro experimental results showed that CCR7 can promote M2 macrophage polarization, thus promoting the proliferation, invasion and migration of OSCC cells. CONCLUSIONS: CCR7 gene knockout can significantly inhibit the growth of mouse oral squamous cell carcinoma by promoting the polarization of M2 macrophages.

MYCT1 inhibits hematopoiesis in diffuse large B-cell lymphoma by suppressing RUNX1 transcription.

BACKGROUND: The abnormality of chromosomal karyotype is one factor causing poor prognosis of lymphoma. In the analysis of abnormal karyotype of lymphoma patients, three smallest overlap regions were found, in which MYCT1 was located. MYCT1 is the first tumor suppressor gene cloned by our research team, but its studies relating to the occurrence and development of lymphoma have not been reported. METHODS: R banding analyses were employed to screen the abnormality of chromosomal karyotype in clinical specimen and MYCT1 over-expression cell lines. FISH was to monitor MYCT1 copy number aberration. RT-PCR and Western blot were to detect the mRNA and protein levels of the MYCT1 and RUNX1 genes, respectively. The MYCT1 and RUNX1 protein levels in clinical specimen were evaluated by immunohistochemical DAB staining. The interaction between MYCT1 and MAX proteins was identified via Co-IP and IF. The binding of MAX on the promoter of the RUNX1 gene was detected by ChIP and Dual-luciferase reporter assay, respectively. Flow cytometry and CCK-8 assay were to explore the effects of MYCT1 and RUNX1 on the cell cycle and proliferation, respectively. RESULTS: MYCT1 was located in one of three smallest overlap regions of diffuse large B-cell lymphoma, it altered chromosomal instability of diffuse large B-cell lymphoma cells. MYCT1 negatively correlated with RUNX1 in lymphoma tissues of the patients. MAX directly promoted the RUNX1 gene transcription by binding to its promoter region. MYCT1 may represses RUNX1 transcription by binding MAX in diffuse large B-cell lymphoma cells. MYCT1 binding to MAX probably suppressed RUNX1 transcription, leading to the inhibition of proliferation and cell cycle of the diffuse large B-cell lymphoma cells. CONCLUSION: This study finds that there is a MYCT1-MAX-RUNX1 signaling pathway in diffuse large B-cell lymphoma. And the study provides clues and basis for the in-depth studies of MYCT1 in the diagnosis, treatment and prognosis of lymphoma.

The application of radiomics machine learning models based on multimodal MRI with different sequence combinations in predicting cervical lymph node metastasis in oral tongue squamous cell carcinoma patients.

BACKGROUND: The purpose of this study was to explore preliminary the performance of radiomics machine learning models based on multimodal MRI to predict the risk of cervical lymph node metastasis (CLNM) for oral tongue squamous cell carcinoma (OTSCC) patients. METHODS: A total of 400 patients were enrolled in this study and divided into six groups according to the different combinations of MRI sequences. Group I consisted of patients with T1-weighted images (T1WI) and FS-T2WI (fat-suppressed T2-weighted images), group II consisted of patients with T1WI, FS-T2WI, and contrast enhanced MRI (CE-MRI), group III consisted of patients with T1WI, FS-T2WI, and T2-weighted images (T2WI), group IV consisted of patients with T1WI, FS-T2WI, CE-MRI, and T2WI, group V consisted of patients with T1WI, FS-T2WI, T2WI, and apparent diffusion coefficient map (ADC), and group VI consisted of patients with T1WI, FS-T2WI, CE-MRI, T2WI, and ADC. Machine learning models were constructed. The performance of the models was compared in each group. RESULTS: The machine learning model in group IV including T1WI, FS-T2WI, T2WI, and CE-MRI presented best prediction performance, with AUCs of 0.881 and 0.868 in the two sets. The models with CE-MRI performed better than the models without CE-MRI(I vs. II, III vs. IV, V vs. VI). CONCLUSIONS: The radiomics machine learning models based on CE-MRI showed great accuracy and stability in predicting the risk of CLNM for OTSCC patients.

Efficient and robust estimation of single-vehicle crash severity: A mixed logit model with heterogeneity in means and variances.

This study delves into the factors that contribute to the severity of single-vehicle crashes, focusing on enhancing both computational speed and model robustness. Utilizing a mixed logit model with heterogeneity in means and variances, we offer a comprehensive understanding of the complexities surrounding crash severity. The analysis is grounded in a dataset of 39,788 crash records from the UK's STATS19 database, which includes variables such as road type, speed limits, and lighting conditions. A comparative evaluation of estimation methods, including pseudo-random, Halton, and scrambled and randomized Halton sequences, demonstrates the superior performance of the latter. Specifically, our estimation approach excels in goodness-of-fit, as measured by ρ2, and in minimizing the Akaike Information Criterion (AIC), all while optimizing computational resources like run time and memory usage. This strategic efficiency enables more thorough and credible analyses, rendering our model a robust tool for understanding crash severity. Policymakers and researchers will find this study valuable for crafting data-driven interventions aimed at reducing road crash severity.

Global PM2.5 Prediction and Associated Mortality to 2100 under Different Climate Change Scenarios.

Ambient fine particulate matter (PM2.5) has severe adverse health impacts, making it crucial to reduce PM2.5 exposure for public health. Meteorological and emissions factors, which considerably affect the PM2.5 concentrations in the atmosphere, vary substantially under different climate change scenarios. In this work, global PM2.5 concentrations from 2021 to 2100 were generated by combining the deep learning technique, reanalysis data, emission data, and bias-corrected CMIP6 future climate scenario data. Based on the estimated PM2.5 concentrations, the future premature mortality burden was assessed using the Global Exposure Mortality Model. Our results reveal that SSP3-7.0 scenario is associated with the highest PM2.5 exposure, with a global concentration of 34.5 µg/m3 in 2100, while SSP1-2.6 scenario has the lowest exposure, with an estimated of 15.7 µg/m3 in 2100. PM2.5-related deaths for individuals under 75 years will decrease by 16.3 and 10.5% under SSP1-2.6 and SSP5-8.5, respectively, from 2030s to 2090s. However, premature mortality for elderly individuals (>75 years) will increase, causing the contrary trends of improved air quality and increased total PM2.5-related deaths in the four SSPs. Our results emphasize the need for stronger air pollution mitigation measures to offset the future burden posed by population age.

Mitigating the impact of outliers in traffic crash analysis: A robust Bayesian regression approach with application to tunnel crash data.

Traffic crash datasets are often marred by the presence of anomalous data points, commonly referred to as outliers. These outliers can have a profound impact on the results obtained through the application of traditional methods such as logit and probit models, commonly used in the domain of traffic safety analysis, resulting in biased and unreliable estimates. To mitigate this issue, this study introduces a robust Bayesian regression approach, the robit model, which utilizes a heavy-tailed Student's t distribution to replace the link function of these thin-tailed distributions, effectively reducing the influence of outliers on the analysis. Furthermore, a sandwich algorithm based on data augmentation is proposed to enhance the estimation efficiency of posteriors. The proposed model is rigorously tested using a dataset of tunnel crashes, and the results demonstrate its efficiency, robustness, and superior performance compared to traditional methods. The study also reveals that several factors such as night and speeding have a significant impact on the injury severity of tunnel crashes. This research provides a comprehensive understanding of the outliers treatment methods in traffic safety studies and offers valuable recommendations for the development of appropriate countermeasures to effectively prevent severe injuries in tunnel crashes.

A predictable prospect of the South Asian summer monsoon.

Prediction of the South Asian summer monsoon (SASM) has remained a challenge for both scientific research and operational climate prediction for decades. By identifying two dominant modes of the SASM, here we show that the unsatisfactory prediction may be due to the fact that the existing SASM indices are mostly related to the less predictable second mode. The first mode, in fact, is highly predictable. It is physically linked to the variation of the Indian monsoon trough coupled with large rainfall anomalies over core monsoon zone and the northern Bay of Bengal. An index is constructed as a physical proxy of this first mode, which can be well predicted one season in advance, with an overall skill of 0.698 for 1979-2020. This result suggests a predictable prospect of the SASM, and we recommend the new index for real-time monitoring and prediction of the SASM.

Core immune cell infiltration signatures identify molecular subtypes and promote precise checkpoint immunotherapy in cutaneous melanoma.

Yutao Wang, China Medical University, ChinaThe tumor microenvironment (TME) has been shown to impact the prognosis of tumors in patients including cutaneous melanoma (CM); however, not all components of TME are important. Given the aforementioned situation, the functional immune cell contents correlated with CM patient prognosis are needed to optimize present predictive models and reflect the overall situation of TME. We developed a novel risk score named core tumor-infiltrating immune cell score (cTICscore), which showed certain advantages over existing biomarkers or TME-related signatures in predicting the prognosis of CM patients. Furthermore, we explored a new gene signature named cTILscore-related module gene score (cTMGs), based on four identified TME-associated genes (GCH1, GZMA, PSMB8, and PLAAT4) showing a close correlation with the cTICscore, which was generated by weighted gene co-expression network analysis and least absolute shrinkage and selection operator analysis to facilitate clinical application. Patients with low cTMGs had significantly better overall survival (OS, P = 0.002,< 0.001, = 0.002, and = 0.03, respectively) in the training and validating CM datasets. In addition, the area under the curve values used to predict the immune response in four CM cohorts were 0.723, 0.723, 0.754, and 0.792, respectively, and that in one gastric cohort was 0.764. Therefore, the four-gene signature, based on cTICscore, might improve prognostic information, serving as a predictive tool for CM patients receiving immunotherapy.cutaneous melanoma, tumor microenvironment, prognosis, immunotherapy, cTICscore.

Impact of different types of entrepreneurial alertness on entrepreneurial opportunities identification.

In the context of resource constraints, how different dimensions of entrepreneurial alertness affect the entrepreneurial opportunity recognition of new ventures is an important issue worth studying. From entrepreneurial cognition theory and bricolage theory perspectives, we systematically investigate the intrinsic relationships among entrepreneurial alertness, entrepreneurial bricolage, entrepreneurial passion, and entrepreneurial opportunity recognition. Further, it explored the intrinsic mechanism of role in exploring entrepreneurial opportunity recognition. This study applied stepwise regression analyses and the Bootstrap method to test the hypotheses on a sample of 295 questionnaires of the new venture. The findings revealed that entrepreneurial alertness is positively related to entrepreneurial opportunity recognition. Entrepreneurial bricolage is positively related to entrepreneurial opportunity recognition. Entrepreneurial bricolage partially mediates between entrepreneurial alertness and entrepreneurial opportunity recognition. Entrepreneurial passion positively moderates the relationship between entrepreneurial bricolage and entrepreneurial opportunity identification. The study guides new ventures to enhance entrepreneurial alertness and reasonably use entrepreneurial bricolage to explore entrepreneurial opportunities.

Nickel-Catalyzed Decarboxylative Coupling of Redox-Active Esters with Aliphatic Aldehydes.

The addition of alkyl fragments to aliphatic aldehydes is a highly desirable transformation for fragment couplings, yet existing methods come with operational challenges related to the basicity and instability of the nucleophilic reagents commonly employed. We report herein that nickel catalysis using a readily available bioxazoline (BiOx) ligand can catalyze the reductive coupling of redox-active esters with aliphatic aldehydes using zinc metal as the reducing agent to deliver silyl-protected secondary alcohols. This protocol is operationally simple, proceeds under mild conditions, and tolerates a variety of functional groups. Initial mechanistic studies suggest a radical chain pathway. Additionally, alkyl tosylates and epoxides are suitable alkyl precursors to this transformation providing a versatile suite of catalytic reactions for the functionalization of aliphatic aldehydes.

Specificity protein 1/microRNA-92b forms a feedback loop promoting the migration and invasion of head and neck squamous cell carcinoma.

In this study we report a novel specificity protein 1 (SP1)/microRNA-92b (miR-92b) feedback loop regulating the migration and invasion of head and neck squamous cell carcinoma (HNSCC). Microarray and real-time Polymerase Chain Reaction (PCR) were used to detect gene expression in HNSCC tissues and cell lines. Transwell migration, invasion, wound healing and cell counting kit - 8 (CCK-8) cell assays were used to compare cell migration, invasion and proliferation abilities. Chromatin Immunoprecipitation (ChIP) assays were used to detect SP1 binding to the miR-92b promoter. Western blot was used to detect protein levels. An in vivo tumorigenesis experiment was used to evaluate the effect of SP1 knockdown on tumor growth and protein levels were evaluated by immunohistochemistry. We found that the miR-92b expression level was elevated in HNSCC primary focus tissue compared with adjacent normal tissue, and a higher level of miR-92b was related to a higher clinical stage and worse prognosis of HNSCC patients. MiR-92b and SP1 mutually promoted each expression and cooperatively facilitated the migration, invasion and proliferation of HNSCC cells. A decreased level of SP1/miR-92b resulted in a restraint of in vivo tumor growth. In conclusion, our results suggest that the SP1/miR-92b feedback loop generally promotes HNSCC invasion and metastasis, thus presenting a possible therapeutic target in the treatment of HNSCC patients.

MKP-1 is required to limit myeloid-cell mediated oral squamous cell carcinoma progression and regional extension.

Mitogen-activated protein kinases (MAPKs) require MAPK phosphatases (MKPs) for deactivation of MAPK intracellular signaling. MKP-1 (encoded by Dusp1) is a key negative regulator of MAPKs and prior reports have indicated that MKP-1 regulates oral cancer-associated inflammation and leukocyte infiltration. OBJECTIVE: To determine the significance of myeloid-based expression of MKP-1 in oral cancer. METHODS: The Cancer Genome Atlas (TCGA) was used to address DUSP1 expression in oral squamous cell carcinoma (OSCC). Syngeneic and carcinogen-induced mouse models using global and myeloid-specific Dusp-1 deficient mice with immunophenotypic, histologic, and transcriptomic analyses and in vitro migration assays. RESULTS: Data from TCGA indicates the DUSP1 expression is inversely related to oral cancer burden and nodal involvement. Using murine models of OSCC, the role of MKP-1 signaling in tumor associated macrophages (TAMs) was assessed. Dusp1-deficient mice had increased tumor burden and TAM infiltrate with increased M2 macrophage polarization. Transcriptomic signatures of TAMs from Dusp1-deficent mice indicated a pro-metastatic phenotype as well as concomitant differences in myeloid-associated genes, cytokine/chemokine signaling, and Notch signaling consistent with tumor progression. In vitro and in vivo assays revealed mouse OSCC cells had a higher migration rate using TAM cell-free supernatant from Dusp1 deficiency mice compared to controls with enhanced regional cervical lymph node metastasis, respectively. To validate TAM studies using implantable mouse models, an OSCC progression model with conditional myeloid-specific Dusp-1 deficient mice demonstrated enhanced OSCC disease progression, characterized by advanced onset, histological stage, and tumor burden. CONCLUSION: Myeloid-based Dusp1-deficiency increases OSCC burden and metastasis through alteration in TAM recruitment, gene profile, and polarity suggesting that MKP-1 could be a viable target to reprogram TAM to limit local/regional OSCC extension.

Characteristics of boundary layer ozone and its effect on surface ozone concentration in Shenzhen, China: A case study.

In late September 2019, the longest and most extensive ozone (O3) pollution process occurred at Pearl River Delta. Base on the observational data, surface-level O3, vertical distribution characteristics boundary layer O3 as well as its effect on surface-level O3 are thoroughly analyzed. The O3 lidar results showed similar vertical O3 profiles both in pollution episodes and clean periods, from which a high O3 concentration layer between 300 and 500 m and a sub-high O3 concentration layer between 1300 and 1700 m (near the top of the mixing layer) can be found. Besides, the downward O3 transport paths from the high/sub-high O3 concentration layers could be observed along with the boundary layer evolution: At nighttime, large amounts of O3 were effectively stored into the residual layer (RL). Due to the upward development of Mixing layer (ML) in early morning, atmospheric vertical mixing carried the O3 inside the RL down to the surface, which led to a rapid increase in the surface-level O3. The sub-high O3 layer began the downward mixing at noon, and became well-mixed after the boundary layer was fully developed in the afternoon, by which the near surface O3 pollution deteriorated again. Further analysis of the heavy O3 pollution episodes show that, the high O3 concentration inside the RL contributed 54% ± 6% of the surface-level O3 at 9:00 LT and the average contribution of O3 in the sub-high concentration layer to the surface-level O3 at 14:00 LT was 26% ± 9%. Based on the quantitative analysis of the observational data, this paper focus to reveal the importance of the contribution of O3 inside the RL and near the top of the ML to the surface O3.

Hydrogen gas inhalation alleviates myocardial ischemia-reperfusion injury by the inhibition of oxidative stress and NLRP3-mediated pyroptosis in rats.

AIMS: Reperfusion therapy is the most common and effective treatment against ischemic heart disease (IHD), but the process inflicts massive ischemia/reperfusion (I/R) injury for which no treatment exists. Notably, reperfusion after ischemia causes ischemia/reperfusion injury (IR injury) and the "no-reflow" phenomenon seriously affecting the therapeutic effects in clinical practice. The principle purpose of this study is to validate the effect of hydrogen gas on IHD and further explore the mechanism of hydrogen gas in alleviating myocardial I/R injury and no-reflow phenomenon. MATERIALS AND METHODS: The rat model of myocardial ischemia-reperfusion was well established. Myocardial infarct size was evaluated by TTC & Evans blue staining. The no-reflow area and the cardiac function were assessed by thioflavin-S staining and echocardiography respectively. Microstructure and mitochondria of myocardial tissue were assessed by transmission electron microscope. Western blot and immunohistochemistry were used to evaluate the expression of NLRP3 mediated pyroptosis related proteins. The 8-OHdG, MDA and serum total ROS were used to evaluate the degree of oxidative stress. KEY FINDINGS: The myocardial infarct size, no-reflow area, cardiac function, microstructure and mitochondrial morphology of I/R model rats were significantly improved after hydrogen inhalation. In addition, the expression of 8-OHdG, MDA, ROS and NLRP3 mediated pyroptosis related proteins were significantly decreased. SIGNIFICANCE: We found that oxidative stress and NLRP3 mediated pyroptosis are the important mechanisms for hydrogen to alleviate myocardial I/R injury, and we also confirmed that hydrogen can significantly improve no reflow phenomenon caused by ischemia-reperfusion.

Development and application of a hybrid long-short term memory - three dimensional variational technique for the improvement of PM2.5 forecasting.

The current state-of-the-art three-dimensional (3D) numerical model for air quality forecasting is restricted by the uncertainty from the emission inventory, physical/chemical parameterization, and meteorological prediction. Forecasting performance can be improved by using the 3D-variational (3D-VAR) technique for assimilating the observation data, which corrects the initial concentration field. However, errors from the prognostic model cause the correction effects at the first hour to be erased, and the bias of the forecast increases relatively fast as the simulation progresses. As an emerging alternative technique, long short-term memory (LSTM) shows promising performance in air quality forecasting for individual stations and outperforms the traditional persistent statistical models. In this study, a new method was developed to combine a 3D numerical model with 3D-VAR and LSTM techniques. This method integrates the advantage of LSTM, namely its high-accuracy forecasting for a single station and that of the 3D-VAR technique, namely its ability to extend improvement to the whole simulation domain. This hybrid method can effectively improve PM2.5 forecasting for the next 24 h, relative to forecasting with the 3D-VAR technique which uses the initial hour concentration correction. Results showed that the root-mean-square error and normalized mean error were decreased by 29.3% and 33.3% in the validation stations, respectively. The LSTM-3D-VAR method developed in this study can be further applied in other regions to improve the forecasting of PM2.5 and other ambient pollutants.

Effect of bromine and iodine chemistry on tropospheric ozone over Asia-Pacific using the CMAQ model.

Recent studies have focused on the chemistry of tropospheric halogen species which are able to deplete tropospheric ozone (O3). In this study, the effect of bromine and iodine chemistry on tropospheric O3 within the annual cycle in Asia-Pacific is investigated using the CMAQ model with the newly embedded bromine and iodine chemistry and a blended and customized emission inventory considering marine halogen emission. Results indicate that the vertical profiles of bromine and iodine species show distinct features over land/ocean and daytime/nighttime, related to natural and anthropogenic emission distributions and photochemical reactions. The halogen-mediated O3 loss has a strong seasonal cycle, and reaches a maximum of -15.9 ppbv (-44.3%) over the ocean and -13.4 ppbv (-38.9%) over continental Asia among the four seasons. Changes in solar radiation, dominant wind direction, and nearshore chlorophyll-a accumulation all contribute to these seasonal differences. Based on the distances to the nearest coastline, the onshore and offshore features of tropospheric O3 loss caused by bromine and iodine chemistry are studied. Across a coastline-centric 400-km-wide belt from onshore to offshore, averaged maximum gradient of O3 loss reaches 1.1 ppbv/100 km at surface level, while planetary boundary layer (PBL) column mean of O3 loss is more moderate, being approximately 0.7 ppbv/100 km. Relative high halogen can be found over Tibetan Plateau (TP) and the largest O3 loss (approximately 4-5 ppbv) in the PBL can be found between the western boundary of the domain and the TP. Halogens originating from marine sources can potentially affect O3 concentration transported from the stratosphere over the TP region. As part of efforts to improve our understanding of the effect of bromine and iodine chemistry on tropospheric O3, we call for more models and monitoring studies on halogen chemistry and be considered further in air pollution prevention and control policy.