Allergens induce upregulated IL-18 and IL-18Rα expression in blood Th2 and Th17 cells of patients with allergic asthma.

Allergic asthma (AA) is closely associated with the polarization of T helper (Th)2 and Th17 cells. Interleukin (IL)-18 acts as an inducer of Th2 and Th17 cell responses. However, expressions of IL-18 and IL-18 receptor alpha (IL-18Rα) in blood Th2 and Th17 cells of patients with AA remain unclear. We therefore investigated their expressions in Th2 and Th17 cells using flow cytometric analysis, qPCR and murine AA model. We observed increased proportions of Th2, Th17, IL-18+, IL-18+ Th2 and IL-18+ Th17 cells in blood CD4+ T cells of patients with AA. Additionally, house dust mite seemed to upregulate further IL-18 expression in Th2 and Th17, and upregulate IL-18Rα expression in CD4+ T, Th2 and Th17 cells of AA patients. It was also found that the plasma levels of IL-4, IL-17A and IL-18 in AA patients were elevated, and they were correlated between each other. In OVA-induced asthma mouse (AM), we observed that the percentages of blood CD4+ T, Th2 and Th17 cells were increased. Moreover, OVA-induced AM expressed higher level of IL-18Rα in blood Th2 cells, which was downregulated by IL-18. Increased IL-18Rα expression was also observed in blood Th2 cells of OVA-induced FcεRIα-/-mice. Collectively, our findings suggest the involvement of Th2 cells in AA by expressing excessive IL-18 and IL-18Rα in response to allergen, and that IL-18 and IL-18Rα expressing Th2 cells are likely to be the potential targets for AA therapy.

Gentulizumab, a novel anti-CD47 antibody with potent antitumor activity and demonstrates a favorable safety profile.

BACKGROUND: Targeting CD47/SIRPα axis has emerged as a promising strategy in cancer immunotherapy. Despite the encouraging clinical efficacy observed in hematologic malignancies through CD47-SIRPα blockade, there are safety concerns related to the binding of anti-CD47 antibodies to CD47 on the membrane of peripheral blood cells. METHODS: In order to enhance the selectivity and therapeutic efficacy of the antibody, we developed a humanized anti-CD47 monoclonal antibody called Gentulizumab (GenSci059). The binding capacity of GenSci059 to CD47 was evaluated using flow cytometry and surface plasmon resonance (SPR) methods, the inhibitory effect of GenSci059 on the CD47-SIRPα interaction was evaluated through competitive ELISA assays. The anti-tumor activity of GenSci059 was assessed using in vitro macrophage models and in vivo patient-derived xenograft (PDX) models. To evaluate the safety profile of GenSci059, binding assays were conducted using blood cells. Additionally, we investigated the underlying mechanisms contributing to the weaker binding of GenSci059 to erythrocytes. Finally, toxicity studies were performed in non-human primates to assess the potential risks associated with GenSci059. RESULTS: GenSci059 displayed strong binding to CD47 in both human and monkey, and effectively inhibited the CD47-SIRPα interaction. With doses ranging from 5 to 20 mg/kg, GenSci059 demonstrated potent inhibition of the growth of subcutaneous tumor with the inhibition rates ranged from 30.3% to complete regression. Combination of GenSci059 with 2.5 mg/kg Rituximab at a dose of 2.5 mg/kg showed enhanced tumor inhibition compared to monotherapy, exhibiting synergistic effects. GenSci059 exhibited minimal binding to hRBCs compared to Hu5F9-G4. The binding of GenSci059 to CD47 depended on the cyclization of N-terminal pyroglutamic acid and the spatial conformation of CD47, but was not affected by its glycosylation modifications. A maximum tolerated dose (MTD) of 450 mg/kg was observed for GenSci059, and no significant adverse effects were observed in repeated dosages up to 10 + 300 mg/kg, indicating a favorable safety profile. CONCLUSION: GenSci059 selectively binds to CD47, effectively blocks the CD47/SIRPα axis signaling pathway and enhances the phagocytosis effects of macrophages toward tumor cells. This monoclonal antibody demonstrates potent antitumor activity and exhibits a favorable safety profile, positioning it as a promising and effective therapeutic option for cancer.

Developing and validating clinical models to identify candidates for allergic rhinitis pre-exposure prophylaxis.

PURPOSE: Few risk-forecasting models of allergic rhinitis (AR) exist that may aid AR pre-exposure prophylaxis (PrEP) in clinical practice. Therefore, this study aimed to develop and validate an effective clinical model for identifying candidates for AR PrEP using a routine medical questionnaire. METHODS: This study was conducted in 10 Chinese provinces with 13 medical centers (n = 877) between 2019 and 2021. Clinical characteristics and exposure history were collected via face-to-face interviews. Well-trained physicians diagnosed patients with AR based on skin prick test results and clinical performance. The least absolute shrinkage and selection operator model was used to identify potential risk factors for AR, and the logistic regression model was used to construct the risk-forecasting model. Predictive power and model reliability were assessed using area under the receiver operating characteristic curve and calibration curves, respectively. RESULTS: This study diagnosed 625 patients with AR who had positive responses to at least one indoor or outdoor allergen and 460 to at least one outdoor pollen allergen. Two nomograms were established to identify two types of AR with various sensitization patterns. Both models had an area under curve of approximately 0.7 in the development and internal validation datasets. Additionally, our findings found good agreement for the calibration curves of both models. CONCLUSION: Early identification of candidates for AR PrEP using routine medical information may improve the deployment of limited resources and effective health management. Our models showed good performance in predicting AR; therefore, they can serve as potential automatic screening tools to identify AR PrEP candidates.

Patterns of aeroallergen sensitization in asthma patients identified by latent class analysis: A cross-sectional study in China.

BACKGROUND: This cross-sectional study aimed to identify latent sensitization profiles of asthma patients in mainland China, unveiling the association between regional differences and sensitization patterns. METHODS: 1056 asthma participants from 10 medical centers divided into eastern and western cohorts were clustered into four individual sensitization patterns, respectively, by using an unsupervised statistical modeling method, latent class analysis (LCA), based on the levels of 12 aeroallergens specific IgE reactivities. Moreover, differences in clinical characteristics and environmental exposures were compared in different sensitization patterns. RESULTS: Four distinct sensitization patterns in the two cohorts were defined as follows, respectively. Eastern cohort: Class 1: "High weed pollen and house dust mites (HDMs) sensitization" (8.87%), Class 2: "HDMs dominated sensitization" (38.38%), Class 3: "High HDMs and animal dander sensitization" (6.95%), Class 4: "Low/no aeroallergen sensitization" (45.80%). Western cohort: Class 1: "High weed pollen sensitization" (26.14%), Class 2: "High multi-pollen sensitization" (15.02%), Class 3: "HDMs-dominated sensitization" (10.33%), Class 4: "Low/no aeroallergen sensitization" (48.51%). Of note, the significant statistical difference in age, asthma control test score (ACT) and comorbidities were observed within or between different sensitization patterns. Exposure factors in different sensitization patterns were pointed out. CONCLUSIONS: Asthmatic patients with distinct sensitization patterns were clustered and identified through the LCA method, disclosing the relationship between sensitization profiles of multiple aeroallergens and geographical differences, providing novel insights and potential strategies for atopic disease monitoring, management and prevention in clinical practice.

Public Surveillance of Social Media for Suicide Using Advanced Deep Learning Models in Japan: Time Series Study From 2012 to 2022.

BACKGROUND: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people's expressions on social media. However, there is not enough evidence to conclude that social media provides public surveillance for suicide without aligning suicide risks detected on social media with actual suicidal behaviors. Corroborating this alignment is a crucial foundation for suicide prevention and intervention through social media and for estimating and predicting suicide in countries with no reliable suicide statistics. OBJECTIVE: This study aimed to corroborate whether the suicide risks identified on social media align with actual suicidal behaviors. This aim was achieved by tracking suicide risks detected by 62 million tweets posted in Japan over a 10-year period and assessing the locational and temporal alignment of such suicide risks with actual suicide behaviors recorded in national suicide statistics. METHODS: This study used a human-in-the-loop approach to identify suicide-risk tweets posted in Japan from January 2013 to December 2022. This approach involved keyword-filtered data mining, data scanning by human efforts, and data refinement via an advanced natural language processing model termed Bidirectional Encoder Representations from Transformers. The tweet-identified suicide risks were then compared with actual suicide records in both temporal and spatial dimensions to validate if they were statistically correlated. RESULTS: Twitter-identified suicide risks and actual suicide records were temporally correlated by month in the 10 years from 2013 to 2022 (correlation coefficient=0.533; P<.001); this correlation coefficient is higher at 0.652 when we advanced the Twitter-identified suicide risks 1 month earlier to compare with the actual suicide records. These 2 indicators were also spatially correlated by city with a correlation coefficient of 0.699 (P<.001) for the 10-year period. Among the 267 cities with the top quintile of suicide risks identified from both tweets and actual suicide records, 73.5% (n=196) of cities overlapped. In addition, Twitter-identified suicide risks were at a relatively lower level after midnight compared to a higher level in the afternoon, as well as a higher level on Sundays and Saturdays compared to weekdays. CONCLUSIONS: Social media platforms provide an anonymous space where people express their suicidal thoughts, ideation, and acts. Such expressions can serve as an alternative source to estimating and predicting suicide in countries without reliable suicide statistics. It can also provide real-time tracking of suicide risks, serving as an early warning for suicide. The identification of areas where suicide risks are highly concentrated is crucial for location-based mental health planning, enabling suicide prevention and intervention through social media in a spatially and temporally explicit manner.

Diverged landscape of restaurant recovery from the COVID-19 pandemic in the United States.

The COVID-19 pandemic has imposed catastrophic impacts on the restaurant industry as a crucial socioeconomic sector that contributes to the global economy. However, the understanding of how the restaurant industry was recovered from COVID-19 remains underexplored. This study constructs a spatially explicit evaluation of the effect of COVID-19 on the restaurant industry in the US, drawing on the attributes of +200,000 restaurants from Yelp and +600 million individual-level restaurant visitations provided by SafeGraph from 1st January 2019 to 31st December 2021. We produce quantitative evidence of lost restaurant visitations and revenue amid the pandemic, the changes in the customers' origins, and the retained visitation law of human mobility-the number of restaurant visitations decreases as the inverse square of their travel distances-though such a distance-decay effect becomes marginal at the later pandemic. Our findings support policy makers to monitor economic relief and design place-based policies for economic recovery.

Unpacking the inter- and intra-urban differences of the association between health and exposure to heat and air quality in Australia using global and local machine learning models.

Environmental stressors including high temperature and air pollution cause health problems. However, understanding how the combined exposure to heat and air pollution affects both physical and mental health remains insufficient due to the complexity of such effects mingling with human society, urban and natural environments. Our study roots in the Social Ecological Theory and employs a tri-environmental conceptual framework (i.e., across social, built and natural environment) to examine how the combined exposure to heat and air pollution affect self-reported physical and mental health via, for the first time, the fine-grained nationwide investigation in Australia and highlight how such effects vary across inter- and intra-urban areas. We conducted an ecological study to explore the importance of heat and air quality to physical and mental health by considering 48 tri-environmental confounders through the global and local random forest regression models, as advanced machine learning methods with the advantage of revealing the spatial heterogeneity of variables. Our key findings are threefold. First, the social and built environmental factors are important to physical and mental health in both urban and rural areas, and even more important than exposure to heat and air pollution. Second, the relationship between temperature and air quality and health follows a V-shape, reflecting people's different adaptation and tolerance to temperature and air quality. Third, the important roles that heat and air pollution play in physical and mental health are most obvious in the inner-city and near inner-city areas of the major capital cities, as well as in the industrial zones in peri-urban regions and in Darwin city with a low-latitude. We draw several policy implications to minimise the inter- and intra-urban differences in healthcare access and service distribution to populations with different sensitivity to heat and air quality across urban and rural areas. Our conceptual framework can also be applied to examine the relationship between other environmental problems and health outcomes in the era of a warming climate.

A global portrait of expressed mental health signals towards COVID-19 in social media space.

Globally, the COVID-19 pandemic has induced a mental health crisis. Social media data offer a unique opportunity to track the mental health signals of a given population and quantify their negativity towards COVID-19. To date, however, we know little about how negative sentiments differ across countries and how these relate to the shifting policy landscape experienced through the pandemic. Using 2.1 billion individual-level geotagged tweets posted between 1 February 2020 and 31 March 2021, we track, monitor and map the shifts in negativity across 217 countries and unpack its relationship with COVID-19 policies. Findings reveal that there are important geographic, demographic, and socioeconomic disparities of negativity across continents, different levels of a nation's income, population density, and the level of COVID-19 infection. Countries with more stringent policies were associated with lower levels of negativity, a relationship that weakened in later phases of the pandemic. This study provides the first global and multilingual evaluation of the public's real-time mental health signals to COVID-19 at a large spatial and temporal scale. We offer an empirical framework to monitor mental health signals globally, helping international authorizations, including the United Nations and World Health Organization, to design smart country-specific mental health initiatives in response to the ongoing pandemic and future public emergencies.

Nexus of heat-vulnerable chronic diseases and heatwave mediated through tri-environmental interactions: A nationwide fine-grained study in Australia.

The warming trend over recent decades has already contributed to the increased prevalence of heat-vulnerable chronic diseases in many regions of the world. However, understanding the relationship between heat-vulnerable chronic diseases and heatwaves remains incomplete due to the complexity of such a relationship mingling with human society, urban and natural environments. Our study extends the Social Ecological Theory by constructing a tri-environmental conceptual framework (i.e., across social, built, and natural environments) and contributes to the first nationwide study of the relationship between heat-vulnerable chronic diseases and heatwaves in Australia. We utilize the random forest regression model to explore the importance of heatwaves and 48 tri-environmental variables that contribute to the prevalence of six types of heat-vulnerable diseases. We further apply the local interpretable model-agnostic explanations and the accumulated local effects analysis to interpret how the heat-disease nexus is mediated through tri-environments and varied across urban and rural space. The overall effect of heatwaves on diseases varies across disease types and geographical contexts (latitudes; inland versus coast). The local heat-disease nexus follows a J-shape function-becoming sharply positive after a certain threshold of heatwaves-reflecting that people with the onset of different diseases have various sensitivity and tolerance to heatwaves. However, such effects are relatively marginal compared to tri-environmental variables. We propose a number of policy implications on reducing urban-rural disparity in healthcare access and service distribution, delineating areas, and identifying the variations of sensitivity to heatwaves across urban/rural space and disease types. Our conceptual framework can be further applied to examine the relationship between other environmental problems and health outcomes.

COVID-19 Infection and Contact Tracing Among Refugees in the United States, 2020-2021.

Refugees in the United States are believed to be at high risk of COVID-19. A cross-sectional study design was utilized to collect anonymous, online surveys from refugee communities in the United States during December 2020 to January 2021. We invited bilingual community leaders to share the survey link with other refugees aged ≥18 years. We identified factors associated with COVID-19 infection and measured the distribution of contact tracing among those who tested positive. Of 435 refugees who completed the survey, 26.4% reported testing positive for COVID-19. COVID-19 infection was associated with having an infected family member and knowing people in one's immediate social environment who were infected. Among respondents who tested positive, 84.4% reported that they had been contacted for contact tracing. To prepare for future pandemics, public health authorities should continue partner with refugee community leaders and organizations to ensure efficient programs are inclusive of refugee communities.

RAMP2-AS1 stabilized RAPM2 mRNA through TIA1 to inhibit the progression of non-small cell lung cancer.

As the most common subtype of lung cancer, non-small cell lung cancer (NSCLC)is responsible for a large proportion of global cancer-caused deaths. The implication of long non-coding RNAs (lncRNAs) as tumor-suppressor or carcinogenic genes in NSCLC has been widely documented. Our study sought to investigate the performance of lncRNA RAMP2 antisense RNA1 (RAMP2-AS1) in NSCLC. GEPIA bioinformatics tool and RT-qPCR were applied for assessing the expression of RAMP2-AS1 and its neighboring gene receptor activity-modifying protein 2 (RAMP2) in NSCLC. Functional assays including CCK-8 assay, colony formation assay as well as caspase-3 activity analysis and Transwell invasion assays were applied for detecting the biological phenotypes of NSCLC cells. Interaction among RAMP2-AS1, RAMP2 and T-cell intracellular antigen 1cytotoxic granule associated RNA binding protein (TIA1) was evaluated by RNA immunoprecipitation and pulldown assays. We found that RAMP2-AS1 and RAMP2 were downregulated in NSCLC. Overexpression of RAMP2-AS1 hampered proliferation and invasion, whereas induced apoptosis of NSCLC cells. Mechanistically, RAMP2-AS1 interacted with TIA1 to stabilize the mRNA of RAMP2. In conclusion, we first uncovered that RAMP2-AS1 stabilized RAPM2 mRNA through TIA1 to inhibit the progression of NSCLC, providing new insight to improve the treatment efficacy of NSCLC.

A colorimetric sensing platform for the determination of H2O2 using 2D-1D MoS2-CNT nanozymes.

A novel colorimetric platform based on nano-composites of two-dimensional (2D) molybdenum disulfide nanosheets (MoS2 NSs) and one-dimensional (1D) carbon nanotubes (CNTs), called 2D-1D MoS2-CNT nanozyme, was fabricated for the selective and sensitive determination of hydrogen peroxide (H2O2) in soda water. The MoS2-CNT nanozyme was synthesized through a one-step solvothermal reduction method. The introduced CNTs could effectively prevent the stacking of MoS2 nanosheets (NSs) and not only expanded the interlayer distance of MoS2 NSs from 0.620 nm to 0.710 nm but also improved their specific surface. Under acidic conditions, the as-prepared 2D-1D MoS2-CNT nanozymes could oxidize the colorless 3,3',5,5'-tetramethylbenzidine (TMB) to blue-oxidized TMB (oxTMB) in the presence of H2O2, resulting in enhanced peroxidase-like (POD-like) activity. The kinetic study showed that MoS2-CNT nanozyme had stronger catalytic activity than natural horseradish peroxidase (HRP). The linear range for H2O2 colorimetric determination was 5.00-500 µmol L-1 with a limit of detection (LOD) of 1.40 µmol L-1. Furthermore, the established determination method was applied to actual samples and the recoveries of H2O2 spiked in soda water were in the range of 92.3-107%, showing feasibility for the analysis of food.

Novel Insights into Floral Thermogenesis: In Vivo Analyses of Mitochondrial Dynamics in Nelumbo nucifera Flowers.

Animal-like thermogenic (TM) activities in flowers have been reported in several families of seed plants. While an association of mitochondria with floral thermogenesis has been described, how mitochondrial dynamics are involved in the regulation of floral thermogenesis is unclear. In this study, the morphological and functional dynamics of mitochondria in vivo were assessed in Nelumbo nucifera Gaertn. flowers during floral thermogenesis. The results showed that mitochondrial biogenesis increased considerably in N. nucifera flowers during thermogenesis, accompanied by notable morphological changes in the mitochondria, including long elliptical, rod-shaped, and dumbbell-shaped morphologies, as well as increased mitochondrial reactive oxygen species (ROS) levels in TM cells. An increase in the expression of alternative oxidase (AOX) during the thermogenesis of N. nucifera flowers was also observed. These observations suggested the rapid change in mitochondrial morphology and increased density during thermogenesis implied activation of mitochondrial fission, which combined with elevated levels of mitochondrial ROS trigger a substantial increase in AOX within the respiratory pathway of TM N. nucifera.

Urban-rural disparity of social vulnerability to natural hazards in Australia.

Assessing vulnerability to natural hazards is at the heart of hazard risk reduction. However, many countries such as Australia lack measuring systems to quantity vulnerability for hazard risk evaluation. Drawing on 41 indicators from multiple data sources at the finest spatial unit of the Australian census, we re-forged the Cutter's classic vulnerability measuring framework by involving the '4D' quantification of built environment (diversity, design, density and distance), and constructed the first nationwide fine-grained measures of vulnerability for urban and rural locales, respectively. Our measures of vulnerability include five themes-(1) socioeconomic status; (2) demographics and disability; (3) minority and languages; (4) housing characteristics; and (5) built environment-that were further used to assess the inequality of vulnerability to three widely affected natural hazards in Australia (wildfires, floods, and earthquakes). We found the inequality of vulnerability in the affected areas of the three hazards in eight capital cities are more significant than that of their rural counterparts. The most vulnerable areas in capital cities were peri-urban locales which must be prioritised for hazard adaptation. Our findings contribute to the risk profiling and sustainable urban-rural development in Australia, and the broad understanding of place-based risk reduction in South Hemisphere.

Social media mining under the COVID-19 context: Progress, challenges, and opportunities.

Social media platforms allow users worldwide to create and share information, forging vast sensing networks that allow information on certain topics to be collected, stored, mined, and analyzed in a rapid manner. During the COVID-19 pandemic, extensive social media mining efforts have been undertaken to tackle COVID-19 challenges from various perspectives. This review summarizes the progress of social media data mining studies in the COVID-19 contexts and categorizes them into six major domains, including early warning and detection, human mobility monitoring, communication and information conveying, public attitudes and emotions, infodemic and misinformation, and hatred and violence. We further document essential features of publicly available COVID-19 related social media data archives that will benefit research communities in conducting replicable and reproducible studies. In addition, we discuss seven challenges in social media analytics associated with their potential impacts on derived COVID-19 findings, followed by our visions for the possible paths forward in regard to social media-based COVID-19 investigations. This review serves as a valuable reference that recaps social media mining efforts in COVID-19 related studies and provides future directions along which the information harnessed from social media can be used to address public health emergencies.

Built Environment and Loneliness Among Older Adults in South East Queensland, Australia.

Objective: To examine characteristics of the built environment and investigate associations with loneliness among older adults. Methods: Drawing on geocoded data from the Household, Income and Labour Dynamics in Australia Survey and measures of neighborhood features retrieved from multiple publicly available sources, we conducted principal component and regression analyses to examine the associations between characteristics of the built environment and loneliness among older adults in South East Queensland, Australia. Results: Older adults living in compact neighborhoods with higher population and housing density, smaller land parcels, and more access to green space reported lower levels of loneliness. Compact and mixed land-use neighborhoods may increase people's exposure to and social interactions with surrounding people and the environment. Conclusion: The built environment provides the context for social interactions. Our study and findings inform research and suggest the development of interventions surrounding the built environment that could potentially help tackle loneliness in older adults.

Exploring the spatial disparity of home-dwelling time patterns in the USA during the COVID-19 pandemic via Bayesian inference.

In this study, we aim to reveal hidden patterns and confounders associated with policy implementation and adherence by investigating the home-dwelling stages from a data-driven perspective via Bayesian inference with weakly informative priors and by examining how home-dwelling stages in the USA varied geographically, using fine-grained, spatial-explicit home-dwelling time records from a multi-scale perspective. At the U.S. national level, two changepoints are identified, with the former corresponding to March 22, 2020 (9 days after the White House declared the National Emergency on March 13) and the latter corresponding to May 17, 2020. Inspections at U.S. state and county level reveal notable spatial disparity in home-dwelling stage-related variables. A pilot study in the Atlanta Metropolitan area at the Census Tract level reveals that the self-quarantine duration and increase in home-dwelling time are strongly correlated with the median household income, echoing existing efforts that document the economic inequity exposed by the U.S. stay-at-home orders. To our best knowledge, our work marks a pioneering effort to explore multi-scale home-dwelling patterns in the USA from a purely data-driven perspective and in a statistically robust manner.

A community-level study on COVID-19 transmission and policy interventions in Wuhan, China.

The specific factors and response strategies that affect COVID-19 transmission in local communities remain under-explored in the current literature due to a lack of data. Based on primary COVID-19 data collected at the community level in Wuhan, China, our study contributes a community-level investigation on COVID-19 transmission and response strategies by addressing two research questions: 1) What community factors are associated with viral transmission? and 2) What are the key mechanisms behind policy interventions towards controlling viral transmission within local communities? We conducted two sets of analyses to address these two questions-quantitative analyses of the relationship between community factors and viral transmission and qualitative analyses of policy interventions on community transmission. Our findings show that the viral spread in local communities is irrelevant to the built environment of a community and its socioeconomic position but is related to its demographic composition. Specifically, groups under the age of 18 play an important role in viral transmission. Moreover, a series of community shutdown management initiatives (e.g., group buying, delivering supplies, and self-reporting of health conditions) play an important role in curbing viral transmission at the local level that can be applied to other geographic contexts.

Exploring the Effect of Health on Migrants' Social Integration in China.

There are 376 million migrants, which account for more than 25% of the population in China according to the newest national demographic census, most of whom are from undeveloped areas to developed urban regions. Migrants' social integration was one of the most important issues when the country aimed to build an inclusive society. As a form of human capital, the effect of migrants' health status on social integration has rarely been explored until now, especially empirically. Previous studies have usually ignored health indicators when discussing the determinants of migrants' social integration, and understanding the role of migrants' physical health and mental health on their social integration is significant for efforts to ensure inclusive urbanization. For filling this research gap, the China Migrants Dynamic Survey dataset was used to uncover the role of migrants' health status, including physical health and mental health, in their degree of social integration, and a further comparison of impact was conducted among rural-urban and urban-urban migrants. Through the empirical analysis, our results indicated the following. First, both better physical and mental health lead to higher social integration levels, and a one-point increase in physical and mental health improves the odds of good social integration by 33.27% and 5.98% for belonging and 66.05% and 6.35% for harmony, respectively. Second, health status is equally important for rural-urban and urban-urban migrants' social integration, and the significant positive effect was consistent across groups, although some other impact factors may exhibit differences. Third, the effect of health status on social integration was moderated by social participation, which was more obvious for mental health than physical health. According to our findings, we discuss the measures to promote migrants' health status and additional countermeasures to improve their social integration level.