Real-time observation of two distinctive non-thermalized hot electron dynamics at MXene/molecule interfaces.

The photoinduced non-thermalized hot electrons at an interface play a pivotal role in determining plasmonic driven chemical events. However, understanding non-thermalized electron dynamics, which precedes electron thermalization (~125 fs), remains a grand challenge. Herein, we simultaneously captured the dynamics of both molecules and non-thermalized electrons in the MXene/molecule complexes by femtosecond time-resolved spectroscopy. The real-time observation allows for distinguishing non-thermalized and thermalized electron responses. Differing from the thermalized electron/heat transfer, our results reveal two non-thermalized electron dynamical pathways: (i) the non-thermalized electrons directly transfer to attached molecules at an interface within 50 fs; (ii) the non-thermalized electrons scatter at the interface within 125 fs, inducing adsorbed molecules heating. These two distinctive pathways are dependent on the irradiating wavelength and the energy difference between MXene and adsorbed molecules. This research sheds light on the fundamental mechanism and opens opportunities in photocatalysis and interfacial heat transfer theory.

A Natural Casein-Based Separator with Brick-and-Mortar Structure for Stable, High-Rate Proton Batteries.

Rechargeable aqueous proton batteries with small organic molecule anodes are currently considered promising candidates for large-scale energy storage due to their low cost, stable safety, and environmental friendliness. However, the practical application is limited by the poor cycling stability caused by the shuttling of soluble organic molecules between electrodes. Herein, a cell separator is modified by a GO-casein-Cu2+ layer with a brick-and-mortar structure to inhibit the shuttling of small organic molecules. Experimental and calculation results indicate that, attributed to the synergistic effect of physical blocking of casein molecular chains and electrostatic and coordination interactions of Cu2+, bulk dissolution and shuttling of multiple small molecules can be inhibited simultaneously, while H+ transfer across the separators is not almost affected. With the protection of the GO-casein-Cu2+ separator, soluble small molecules, such as diquinoxalino[2,3-a:2',3'-c]phenazine,2,3,8,9,14,15-hexacyano (6CN-DQPZ) exhibit a high reversible capacity of 262.6 mA h g-1 and amazing stability (capacity retention of 92.9% after 1000 cycles at 1 A g-1). In addition, this strategy is also proved available to other active conjugated small molecules, such as indanthrone (IDT), providing a general green sustainable strategy for advancing the use of small organic molecule electrodes in proton cells.

The construction of a novel prognostic prediction model for glioma based on GWAS-identified prognostic-related risk loci.

Backgrounds: Glioma is a highly malignant brain tumor with a grim prognosis. Genetic factors play a role in glioma development. While some susceptibility loci associated with glioma have been identified, the risk loci associated with prognosis have received less attention. This study aims to identify risk loci associated with glioma prognosis and establish a prognostic prediction model for glioma patients in the Chinese Han population. Methods: A genome-wide association study (GWAS) was conducted to identify risk loci in 484 adult patients with glioma. Cox regression analysis was performed to assess the association between GWAS-risk loci and overall survival as well as progression-free survival in glioma. The prognostic model was constructed using LASSO Cox regression analysis and multivariate Cox regression analysis. The nomogram model was constructed based on the single nucleotide polymorphism (SNP) classifier and clinical indicators, enabling the prediction of survival rates at 1-year, 2-year, and 3-year intervals. Additionally, the receiver operator characteristic (ROC) curve was employed to evaluate the prediction value of the nomogram. Finally, functional enrichment and tumor-infiltrating immune analyses were conducted to examine the biological functions of the associated genes. Results: Our study found suggestive evidence that a total of 57 SNPs were correlated with glioma prognosis (p < 5 × 10-5). Subsequently, we identified 25 SNPs with the most significant impact on glioma prognosis and developed a prognostic model based on these SNPs. The 25 SNP-based classifier and clinical factors (including age, gender, surgery, and chemotherapy) were identified as independent prognostic risk factors. Subsequently, we constructed a prognostic nomogram based on independent prognostic factors to predict individualized survival. ROC analyses further showed that the prediction accuracy of the nomogram (AUC = 0.956) comprising the 25 SNP-based classifier and clinical factors was significantly superior to that of each individual variable. Conclusion: We identified a SNP classifier and clinical indicators that can predict the prognosis of glioma patients and established a prognostic prediction model in the Chinese Han population. This study offers valuable insights for clinical practice, enabling improved evaluation of patients' prognosis and informing treatment options.

Steric hindrance modulation of hexaazatribenzanthraquinone isomers for high-capacity and wide-temperature-range aqueous proton battery.

Organic materials with rich active sites are good candidates of high-capacity anodes in aqueous batteries, but commonly low utilization of active sites limits their capacity. Herein, two isomers, symmetric and asymmetric hexaazatribenzanthraquinone (s-HATBAQ and a-HATBAQ), with rich active sites have been synthesized in a controllable manner. It has been revealed for the first time that a sulfuric acid catalyst can facilitate the stereoselective formation of s-HATBAQ. Attributed to the reduced steric hindrance in favor of proton insertion as well as the amorphous structure conducive to electrochemical dynamics, s-HATBAQ exhibits 1.5 times larger specific capacity than a-HATBAQ. Consequently, the electrode of s-HATBAQ with 50% reduced graphene oxide (s-HATBAQ-50%rGO) delivers a record high specific capacity of 405 mAh g-1 in H2SO4 electrolyte. Moreover, the assembled MnO2//s-HATBAQ-50%rGO aqueous proton full batteries show an exceptional cycling stability at 25°C and can maintain ∼92% capacity after 1000 cycles at 0.5 A g-1 at -80°C. This work demonstrates the controllable synthesis of isomers, showcases a wide-temperature-range prototype proton battery and highlights the significance of precise molecular structure modulation in organic energy storage.

Recent Advances in Flexible Pressure Sensors Based on MXene Materials.

In the past decade, with the rapid development of wearable electronics, medical health monitoring, the Internet of Things, and flexible intelligent robots, flexible pressure sensors have received unprecedented attention. As a very important kind of electronic component for information transmission and collection, flexible pressure sensors have gained a wide application prospect in the fields of aerospace, biomedical and health monitoring, electronic skin, and human-machine interface. In recent years, MXene has attracted extensive attention because of its unique 2D layered structure, high conductivity, rich surface terminal groups, and hydrophilicity, which has brought a new breakthrough for flexible sensing. Thus, it has become a revolutionary pressure-sensitive material with great potential. In this work, the recent advances of MXene-based flexible pressure sensors are reviewed from the aspects of sensing type, sensing mechanism, material selection, structural design, preparation strategy, and sensing application. The methods and strategies to improve the performance of MXene-based flexible pressure sensors are analyzed in details. Finally, the opportunities and challenges faced by MXene-based flexible pressure sensors are discussed. This review will bring the research and development of MXene-based flexible sensors to a new high level, promoting the wider research exploitation and practical application of MXene materials in flexible pressure sensors.

The degree of risk factor and accumulation effect for large niche in individuals after cesarean section.

BACKGROUND: The risk factors associated with niche on the cesarean scar have been reported, however, the degree of these factors associated with large niche and the accumulation effects of these risk factors on the development of large niche are unclear. METHODS: Large niche was evaluated by transvaginal sonography during mid-follicular phase. Logistic regression model was used to assess 32 risk factors by univariate analysis. Then, a scoring model based on the screened risk factors was generated. The performance of this model was evaluated by area under curve (AUC). Finally, the scoring model was applied in 123 women to assess the external validation. RESULT(S): In the training cohort study, 163 women were diagnosed with large niche. The final scoring model involves eight risk factors with the rating scores including age at delivery (30-34 years: 1 point; ≥ 35 years: 4.5 points), retroflexed uterus (8.5 points), meconium-stained amniotic fluid (4.5 points), twice CSs (4.0 points), postpartum endometritis (4.5 points), premature rupture of membranes (2.5 points), intrahepatic cholestasis of pregnancy (mild to moderate: 3 points; severe: 6.5 points), and cervical dilatation (1-3 cm: 2.0 points; 4-10 cm: 4.5 points). The accumulation effect with a cut-off value of 8.0 in the scoring was associated with the large niche after CS. CONCLUSION(S): This is the first scoring model to objectively quantify the risk of a large niche after CS. Optimal risk factors control by avoiding high score factors and multiple factors accumulation may eliminate the risk of large niche development.

Searching High-Potential Dihydroxynaphthalene Cathode for Rocking-Chair All-Organic Aqueous Proton Batteries.

The lack of acid-proof high-potential cathode largely limits the development and competitiveness of proton batteries. Herein, the authors systematically investigated six dihydroxynaphthalenes (DHNs) and found that 2,6-DHN delivered the best cathode performance in proton battery with the highest redox potential (0.84 V, vs SHE) and a specific capacity of 91.6 mAh g-1 at 1 A g-1 . In situ solid-state electropolymerization of DHNs is responsible for the voltage and capacity fading of DHNs, and 2,6-DHN's excellent electrochemical performance is derived from its high polymerization energy barrier. By compounding with rGO, the 2,6-DHN/rGO electrode can maintain a specific capacity of 89 mAh g-1 even after 12 000 cycles at 5 A g-1 . When it is paired with the 2,6-dihydroxyanthraquinone (DHAQ) anode, the assembled rocking-chair all-organic proton battery exhibited a high cell voltage of 0.85 V, and excellent energy/power densities (70.8 Wh kg-1 /850 W kg-1 ). This study showcases a new-type high-potential proton-containing organic cathode and paves the way for constructing a high-voltage rocking-chair proton battery. Also, in situ solid-state electropolymerization will inspire the further study of phenol-based small-molecule electrodes.

Impact of TREM1 Variants on the Risk and Prognosis of Glioma in the Chinese Han Population.

Background: Glioma is the main pathological subtype of brain tumors with high mortality. Objective: This study aimed to elucidate the correlation between TREM1 variants and glioma risk in the Chinese Han population. Methods: Genotyping of six variants of TREM1 was completed by Agena MassARRAY platform in 1061 subjects (503 controls and 558 glioma patients). The relationship between TREM1 polymorphisms and glioma risk was calculated using the logistic regression model, with odds ratio (OR) and 95% confidence intervals (CIs). A multifactor dimensionality reduction (MDR) method was performed to assess SNP-SNP interactions to predict glioma risk. Results: In this research, overall analysis illustrated an association between TREM1 rs9369269 and an increased risk of glioma. Rs9369269 was also related to the risk of glioma in patients aged ≤40 years and females. Subjects with rs9369269 AC genotype were likely to obtain glioma compared to people with CC genotype (patients with astroglioma vs healthy people). Compared to TT genotype carriers, carriers with AT genotype of rs1351835 were significantly associated with overall survival (OS). Conclusion: Taken together, the study identified the association between TREM1 variants and glioma risk and TREM1 variants were significantly associated with the prognosis of glioma. In the future, larger samples are needed to verify the results.

How can blockchain technology promote food safety in agricultural market?-an evolutionary game analysis.

The governance of agricultural food safety issues is closely linked to social interests. To promote food safety supervision in the Chinese agricultural markets under the background of blockchain application, this paper develops a partnership comprising vendors, consumers, and the government. Using the theory of evolutionary game combined with the actual situation of China, the evolutionary process simulations of three participants prove that the tripartite subjects can realize a stable state under the specific relationship. Impact investigation results of typical influential factors indicate the following: (1) The behavior of vendors depends on the government's supervision and consumers' reporting attitude. Limiting the penalty amount for vendors to 66.7% of speculative gains can shorten the processing time for vendors to comply with the law. (2) Consumers play a vital role in food safety supervision of the agricultural market. The penalty for consumers should be limited to 1/3 of the reward amount. (3) The government's incentive-oriented and punishment-inhibited policies can promote blockchain technology in supervision. Punishment-inhibited and key influencing parameters can cooperate in obtaining the maximum regulatory benefits. The results of this study have certain reference values for promoting policy formulation and implementing blockchain technology in agricultural food safety supervision.

Effect of OR51E1 single nucleotide polymorphisms on glioma susceptibility in the Chinese Han population.

BACKGROUND: Glioma is one of the common primary intracranial tumors, which is heterogeneous among individuals with a low cure rate. Our study aimed to investigate the association between single nucleotide polymorphisms (SNPs) of the OR51E1 gene and glioma susceptibility in the Chinese Han population. METHODS: A total of six SNPs on OR51E1 in 1,026 subjects (526 cases and 500 controls) were genotyped by MassARRAY iPLEX GOLD assay. The association between these SNPs and glioma susceptibility was analyzed using logistic regression, and odds ratios (ORs) and 95% confidence intervals (CIs) were also calculated. The multifactor dimensionality reduction (MDR) method was applied to detect "SNP-SNP" interactions. RESULTS: In the overall sample, polymorphisms rs10768148, rs7102992, and rs10500608 were identified to be associated with glioma risk. In the stratified analysis based on gender, only polymorphism rs10768148 was observed to be associated with the risk of glioma. In the age-stratified analysis, rs7102992, rs74052483, and rs10500609 contributed to the risk of glioma in subjects aged > 40 years. And polymorphisms rs10768148 and rs7102992 were associated with the risk of glioma in subjects aged ≤ 40 years and subjects with astrocytoma. In addition, a strong synergistic relationship between rs74052483 and rs10768148, and a strong redundant relationship between rs7102992 and rs10768148 were identified in the study. CONCLUSIONS: This study demonstrated the association of OR51E1 polymorphisms with glioma susceptibility, providing a basis for assessing glioma risk-associated variants in the Chinese Han population.

Fe Powder Catalytically Synthesized C3N3 toward High-Performance Anode Materials of Lithium-Ion Batteries.

Recently, carbon nitrides and their carbon-based derivatives have been widely studied as anode materials of lithium-ion batteries due to their graphite-like structure and abundant nitrogen active sites. In this paper, a layered carbon nitride material C3N3 consisting of triazine rings with an ultrahigh theoretical specific capacity was designed and synthesized by an innovative method based on Fe powder-catalyzed carbon-carbon coupling polymerization of cyanuric chloride at 260 °C, with reference to the Ullmann reaction. The structural characterizations indicated that the as-synthesized material had a C/N ratio close to 1:1 and a layered structure and only contained one type of nitrogen, suggesting the successful synthesis of C3N3. When used as a lithium-ion battery anode, the C3N3 material showed a high reversible specific capacity up to 842.39 mAh g-1 at 0.1 A g-1, good rate capability, and excellent cycling stability attributed to abundant pyridine nitrogen active sites, large specific surface area, and good structure stability. Ex situ XPS results indicated that Li+ storage relies on the reversible transformation of -C=N- and -C-N- groups as well as the formation of bridge-connected -C=C- bonds. To further optimize the performance, the reaction temperature was further increased to synthesize a series of C3N3 derivatives for the enhanced specific surface area and conductivity. The resulting derivative prepared at 550 °C showed the best electrochemical performance, with an initial specific capacity close to 900 mAh g-1 at 0.1 A g-1 and good cycling stability (94.3% capacity retention after 500 cycles at 1 A g-1). This work will undoubtedly inspire the further study of high-capacity carbon nitride-based electrode materials for energy storage.

How does agricultural production agglomeration affect green total factor productivity?: empirical evidence from China.

Economic growth in agriculture is often accompanied by environmental pollution. To overcome this dilemma, agricultural green total factor productivity is essential. The role of agricultural production agglomeration has been studied extensively; however, there is no apparent association between agricultural production agglomeration and agricultural green total factor productivity. We use the non-angular and non-radial super-efficiency slacks-based measure model and the global Malmquist-Luenberger productivity model to assess the agricultural green total factor productivity in 30 Chinese provinces from 2001 to 2019. In addition, we investigate the evolutionary trend, influence relationship, and internal mechanism between agricultural production agglomeration and agricultural green total factor productivity. The results show an inverted U-shaped relationship between agricultural production agglomeration and agricultural green total factor productivity. Heterogeneity analysis finds that this role is more pronounced in provinces located in the Yangtze River economic zone with strong fiscal support for agriculture and high levels of regional economic development. Regarding the mechanism analysis, enhancing green technology progress and the quality of rural human capital leads to an increase in agricultural green total factor productivity. Therefore, this study provides a new perspective on global carbon emission reduction and a theoretical and practical reference for realizing global agricultural green development.

Association Between Night Shift and Hypertension: A Cross-Sectional Study in Chinese Adults.

OBJECTIVE: The purpose of this study was to explore the effect of night-shift work on the risk of hypertension for improving workers' health. METHODS: A total of 10,038 Chinese participants were constituted in the cross-sectional study. Logistic regression and restricted cubic spline were used to estimate the effect of night shift on hypertension. RESULTS: There were higher odds of having hypertension in any night-shift workers (odds ratio [OR], 1.16 [95% confidence interval, 1.03-1.30]) when compared with day workers. Having 5 to 10 night shifts per month were significantly more likely to be hypertensive (OR, 1.19 [95% confidence interval, 1.03-1.38]). The OR for hypertension increased as the number of night shifts increased as the result of the restricted cubic spline. CONCLUSIONS: Our results support the hypothesis that night shift is associated with an elevated risk of hypertension.

Integrated Uniformly Microporous C4 N/Multi-Walled Carbon Nanotubes Composite Toward Ultra-Stable and Ultralow-Temperature Proton Batteries.

Benefiting from the proton's small size and ultrahigh mobility in water, aqueous proton batteries are regarded as an attractive candidate for high-power and ultralow-temperature energy storage devices. Herein, a new-type C4 N polymer with uniform micropores and a large specific surface area is prepared by sulfuric acid-catalyzed ketone amine condensation reaction and employed as the electrode of proton batteries. Multi-walled carbon nanotubes (MWCNT) are introduced to induce the in situ growth of C4 N, and reaped significantly enhanced porosity and conductivity, and thus better both room- and low-temperature performance. When coupled with MnO2 @Carbon fiber (MnO2 @CF) cathode, MnO2 @CF//C4 N-50% MWCNT full battery shows unprecedented cycle stability with a capacity retention of 98% after 11 000 cycles at 10 A g-1 and even 100% after 70 000 cycles at 20 A g-1 . Additionally, a novel anti-freezing electrolyte (5 m H2 SO4  + 0.5 m MnSO4 ) is developed and showed a high ionic conductivity of 123.2 mS cm-1 at -70 °C. The resultant MnO2 @CF//C4 N-50% MWCNT battery delivers a specific capacity of 110.5 mAh g-1 even at -70 °C at 1 A g-1 , the highest in all reported proton batteries under the same conditions. This work is expected to offer a package solution for constructing high-performance ultralow-temperature aqueous proton batteries.

Simultaneous capturing phonon and electron dynamics in MXenes.

Plasmonic MXenes are of particular interest, because of their unique electron and phonon structures and multiple surface plasmon effects, which are different from traditional plasmonic materials. However, to date, how electronic energy damp to lattice vibrations (phonons) in MXenes has not been unraveled. Here, we employed ultrafast broadband impulsive vibrational spectroscopy to identify the energy damping channels in MXenes (Ti3C2Tx and Mo2CTx). Distinctive from the well-known damping pathways, our results demonstrate a different energy damping channel, in which the Ti3C2Tx plasmonic electron energy transfers to coherent phonons by nonthermal electron mediation after Landau damping, without involving electron-electron scattering. Moreover, electrons are observed to strongly couple with A1g mode (~60 fs, 85-100%) and weakly couple with Eg mode (1-2 ps, 0-15%). Our results provide new insight into the electron-phonon interaction in MXenes, which allows the design of materials enabling efficient manipulation of electron transport and energy conversion.

Dynamic feature learning for COVID-19 segmentation and classification.

Since December 2019, coronavirus SARS-CoV-2 (COVID-19) has rapidly developed into a global epidemic, with millions of patients affected worldwide. As part of the diagnostic pathway, computed tomography (CT) scans are used to help patient management. However, parenchymal imaging findings in COVID-19 are non-specific and can be seen in other diseases. In this work, we propose to first segment lesions from CT images, and further, classify COVID-19 patients from healthy persons and common pneumonia patients. In detail, a novel Dynamic Fusion Segmentation Network (DFSN) that automatically segments infection-related pixels is first proposed. Within this network, low-level features are aggregated to high-level ones to effectively capture context characteristics of infection regions, and high-level features are dynamically fused to model multi-scale semantic information of lesions. Based on DFSN, Dynamic Transfer-learning Classification Network (DTCN) is proposed to distinguish COVID-19 patients. Within DTCN, a pre-trained DFSN is transferred and used as the backbone to extract pixel-level information. Then the pixel-level information is dynamically selected and used to make a diagnosis. In this way, the pre-trained DFSN is utilized through transfer learning, and clinical significance of segmentation results is comprehensively considered. Thus DTCN becomes more sensitive to typical signs of COVID-19. Extensive experiments are conducted to demonstrate effectiveness of the proposed DFSN and DTCN frameworks. The corresponding results indicate that these two models achieve state-of-the-art performance in terms of segmentation and classification.

Exposure to multiple trace elements and thyroid cancer risk in Chinese adults: A case-control study.

The incidence of thyroid cancer (TC) has increased rapidly in last decades. Multiple trace elements in the external environment have important effects with thyroid function. However, the evidence for these on TC risk were rarely reported. A total of 585 newly diagnosed TC patients and 585 healthy controls were included in this study, and 14 urinary elements were measured to explain the fixed-exposure effect on TC risk. Conditional logistic regressions were used to reflect the multi-element associations, and Bayesian kernel machine regression (BKMR) was applied to show the tendency of mixed effects. Furthermore, the interaction effects were examined by Generalized linear model (GLM). The levels of lithium (Li), cobalt (Co), strontium (Sr), zinc (Zn) and copper (Cu) had negative effects with TC risk, nevertheless lead (Pb), arsenic (As) and chromide (Cr) showed positive effects. The BKMR and GLM models reflected the effect fluctuations of different elements, and there was a slight interaction effects between Li and Cr, Co, Zn and Pb. Further study is required to confirm these results in the future.

Individual PM2.5 component exposure model, elevated blood pressure and hypertension in middle-aged and older adults: A nationwide cohort study from 125 cities in China.

Recently, elevated blood pressure (BP) and hypertension (HTN) have caused a huge burden of health loss. Previous studies used ambient air pollutants as a proxy for individual exposure, limiting the assessment of its multiple exposure to health effects. For the first time, this study constructed individual PM2.5 component (SO42-, NO3-, NH4+, OM, and BC) exposure model DAG (Directed Acyclic Graph), DAG-oriented generalized linear model and random forest model, and explored the effects of single and multiple exposures to PM2.5 components on BP at different stages by the generalized linear model (GLM) and Quantile g-Computation (QgC) model based on a large cohort study in China. We defined BP in four stages according to the 2017 ACC/AHA guidelines. After excluding the lack of key information, the cohort analyses ultimately included 9031 participants. Our results showed that the individual PM2.5 component exposure model had good efficacy. Single or multiple exposure to PM2.5 components had significant positive effects on normal BP to elevated BP and elevated BP to stage 1 HTN. In addition, males, the elderly and urban residents were more sensitive to PM2.5 components. This study provided implications for environmental exposure assessment and control of particulate pollution in the future.

Short-term exposure to six air pollutants and cause-specific cardiovascular mortality of nine counties or districts in Anhui Province, China.

Recently, the burden of cardiovascular disease (CVD) has attracted global attention. Meanwhile, CVD has become the leading cause of death in China. Some epidemiological studies have indicated that ambient air pollution may contribute to increased mortality from CVD diseases. Many studies have found a strong association between air pollutants and the risk of CVD deaths in some big cities, but few have focused on the effects of six pollutants in rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO2, O3, PM2.5, PM10, and SO2) on CVD deaths of rural areas in Anhui Province and to further clarify which populations were susceptible to air pollution. First, the generalized additive models were combined with the distributed lag nonlinear models to evaluate the individual effects of air pollution on CVD deaths in each area. Then, random-effects models were used to aggregate the associations between air pollutants and CVD mortality risk in nine regions. Overall, all six pollutants had a statistically significant effect on the risk of CVD deaths on the lag 07 days. The associations between PM2.5, PM10, and SO2 and daily CVD deaths were strongest, with maximum cumulative RR (lag 07) of 1.91 (1.64-2.18), 2.27 (1.50-3.05), and 2.13 (1.44-2.82). In general, we found that six air pollutants were the important risk factors for CVD and specific CVD deaths in Anhui Province. The elderly were susceptible to PM2.5, PM10, and SO2.

Outdoor air pollution enhanced the association between indoor air pollution exposure and hypertension in rural areas of eastern China.

Recently, the high prevalence of hypertension (HTN) has caused serious disease burden. Previous studies mostly focused on the separate association between outdoor or indoor air pollution and HTN, and did not explore their possible interaction with HTN. To explore this issue, this study investigated the relationship between indoor and outdoor air pollution and HTN and their possible interactions among adult residents in 14 rural areas in eastern China. The generalized linear model (GLM) and interplot model were used to evaluate the separate effects and potential interaction of outdoor or indoor air pollutants on HTN. In separate analyses, we found a significant positive association between outdoor and indoor air pollution and HTN, and a significant negative association between range hood use and HTN. In the interaction analysis, outdoor air pollution could significantly enhance the positive effects of indoor air pollution on HTN. In addition, PM2.5 and O3 could significantly reduce the protective effect of range hoods use on HTN. Finally, we found that females were more susceptible to both indoor and outdoor air pollution.