Correlation between immune-related adverse events and efficacy of PD-(L)1 inhibitors in small cell lung cancer: a multi-center retrospective study.

BACKGROUND: Patients receiving PD-(L)1 inhibitors frequently encounter unusual side effects known as immune-related adverse events (irAEs). However, the correlation of irAEs development with clinical response in small cell lung cancer (SCLC) is unknown. METHOD: This retrospective study enrolled 244 stage IV SCLC patients who receiving PD-(L)1 inhibitors from 3 cancer centers. The correlation of irAEs with objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) were evaluated. RESULTS: 140 in 244 (57%) patients experienced irAEs, with 122 (87.1%) experiencing one and 18 (12.9%) experiencing two or more. Compared to patient without irAEs, those developing irAEs had higher ORR (73.6% vs. 52.9%, P < 0.001) and DCR (97.9% vs. 79.8%, P < 0.001), as well as prolonged median PFS (8.8 vs. 4.5 months, P < 0.001) and OS (23.2 vs. 21.6 months, P < 0.05). Among the different spectra of irAEs, thyroid dysfunction, rash, and pneumonitis were the most powerful indicator for improved PFS. When analyzed as a time-dependent covariate, the occurrence of irAEs was associated with significant improvement in PFS rather than in OS. Furthermore, patients experiencing multisystem irAEs displayed a longer PFS and OS compared with single-system irAEs and the irAE-free ones. IrAEs grade and steroid use did not impact the predictive value of irAEs on PFS. CONCLUSION: The presence of irAEs predicts superior clinical benefit in SCLC. Patients who develop multi-system irAEs may have an improved survival than those developed single-system irAEs and no-irAEs. This association persists even when systemic corticosteroids were used for irAEs management.

Generating High Spatial Resolution Exposure Estimates from Sparse Regulatory Monitoring Data.

Random Forest algorithms have extensively been used to estimate ambient air pollutant concentrations. However, the accuracy of model-predicted estimates can suffer from extrapolation problems associated with limited measurement data to train the machine learning algorithms. In this study, we developed and evaluated two approaches, incorporating low-cost sensor data, that enhanced the extrapolating ability of random-forest models in areas with sparse monitoring data. Rochester, NY is the area of a pregnancy-cohort study. Daily PM2.5 concentrations from the NAMS/SLAMS sites were obtained and used as the response variable in the model, with satellite data, meteorological, and land-use variables included as predictors. To improve the base random-forest models, we used PM2.5 measurements from a pre-existing low-cost sensors network, and then conducted a two-step backward selection to gradually eliminate variables with potential emission heterogeneity from the base models. We then introduced the regression-enhanced random forest method into the model development. Finally, contemporaneous urinary 1-hydroxypyrene was used to evaluate the PM2.5 predictions generated from the two approaches. The two-step approach increased the average external validation R2 from 0.49 to 0.65, and decreased the RMSE from 3.56 µg/m3 to 2.96 µg/m3. For the regression-enhanced random forest models, the average R2 of the external validation was 0.54, and the RMSE was 3.40 µg/m3. We also observed significant and comparable relationships between urinary 1-hydroxypyrene levels and PM2.5 predictions from both improved models. This PM2.5 model estimation strategy could improve the extrapolating ability of random forest models in areas with sparse monitoring data.

On-field test and data calibration of a low-cost sensor for fine particles exposure assessment.

BACKGROUND: Accurate individual exposure assessment is crucial for evaluating the health effects of particulate matter (PM). Various portable monitors built upon low-cost optical sensors have emerged. However, the main challenge for their application is to guarantee accuracy of measurements. OBJECTIVE: To assess the performance of a newly developed PM sensor, and to develop methods for post-hoc data calibration to optimize its data quality. METHOD: We conducted a series of laboratory experiments and field evaluations to quantify the reproducibility within Plantower PM sensors 7003 (PMS 7003) and the consistency between sensors and two established PM2.5 measurement methods [tapered element oscillating microbalances (TEOM) and gravimetric method (GM)]. Post-hoc data calibration methods for sensors were based on a multiple linear regression model (MLRM) and a random forest model (RFM). Ratios of raw and calibrated readings over the data of reference methods were calculated to examine the improvement after calibration. RESULTS: Strong correlations (≥0.82) and relatively small relative standard deviations (16-21%) between sensors were found during the laboratory and the field sampling. Compared with the reference methods, moderate to strong coefficients of determination (0.56-0.83) were observed; however, significant deviations were presented. After calibration, the ratios of PMS measurements over that of two reference methods both became convergent. CONCLUSIONS: Our study validated low-cost optical PM sensors under a wide range of PM2.5 concentrations (8-167 µg/m3). Our findings indicated potential applicability of PM sensors in PM2.5 exposure assessment, and confirmed a need of calibration. Linear calibration methods may be sufficient for ambient monitoring using TEOM as a reference, while nonlinear calibration methods may be more appropriate for indoor monitoring using GM as a reference.

Application of land use regression to assess exposure and identify potential sources in PM2.5, BC, NO2 concentrations.

BACKGROUND: Understanding spatial variation of air pollution is critical for public health assessments. Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations. However, they have limited application in China due to the lack of spatially resolved data. OBJECTIVE: Based on purpose-designed monitoring networks, this study developed LUR models to predict fine particulate matter (PM2.5), black carbon (BC) and nitrogen dioxide (NO2) exposure and to identify their potential outdoor-origin sources within an urban/rural region, using Taizhou, China as a case study. METHOD: Two one-week integrated samples were collected at 30 PM2.5 (BC) sites and 45 NO2 sites in each two distinct seasons. Samples of 1/3 of the sites were collected simultaneously. Annual adjusted average was calculated and regressed against pre-selected GIS-derived predictor variables in a multivariate regression model. RESULTS: LUR explained 65% of the spatial variability in PM2.5, 78% in BC and 73% in NO2. Mean (±Standard Deviation) of predicted PM2.5, BC and NO2 exposure levels were 48.3 (±6.3) µg/m3, 7.5 (±1.4) µg/m3 and 27.3 (±8.2) µg/m3, respectively. Weak spatial corrections (Pearson r = 0.05-0.25) among three pollutants were observed, indicating the presence of different sources. Regression results showed that PM2.5, BC and NO2 levels were positively associated with traffic variables. The former two also increased with farm land use; and higher NO2 levels were associated with larger industrial land use. The three pollutants were correlated with sources at a scale of ≤5 km and even smaller scales (100-700m) were found for BC and NO2. CONCLUSION: We concluded that based on a purpose-designed monitoring network, LUR model can be applied to predict PM2.5, NO2 and BC concentrations in urban/rural settings of China. Our findings highlighted important contributors to within-city heterogeneity in outdoor-generated exposure, and indicated traffic, industry and agriculture may significantly contribute to PM2.5, NO2 and BC concentrations.

Nitrogen dioxide air pollution and preterm birth in Shanghai, China.

BACKGROUND: Nitrogen dioxide (NO2) is a typical indicator of traffic-related air pollution, and few studies with exposure assessment of high resolution have been conducted to explore its association with preterm birth in China. OBJECTIVES: To investigate the association between NO2 exposure based on a land use regression (LUR) model and preterm birth in Shanghai, China. METHODS: A retrospective cohort study was performed among 25,493 singleton pregnancies in a major maternity hospital in Shanghai, China, from 2014 to 2015. A temporally adjusted LUR model was used to predict the prenatal exposure to NO2 based on residence address of each gravida. Logistic regression was performed to evaluate the associations of ambient NO2 exposure with preterm birth during six exposure periods, including the entire pregnancy, the first trimester, the second trimester, the third trimester, the last month, and the last week before delivery. Sensitivity analysis with a matched case-control design was conducted to test the robustness of the association between NO2 exposure and preterm birth. RESULTS: The average NO2 concentrations during the entire pregnancy was 48.23 µg/m3 among all participants. A 10 µg/m3 increase in NO2 concentrations was associated with preterm birth, with an adjusted odds ratio of 1.03 (95% confidence interval [CI]: 0.96,1.10) for exposures during the entire pregnancy, 1.00 (95%CI: 0.95,1.06) in the first trimester, 1.01 (95%CI: 0.96,1.07) in the second trimester, 1.07 (95%CI: 1.02,1.13) in the third trimester, 1.10 (95%CI: 1.04,1.15) and 1.05 (95%CI: 1.00,1.09) in the month and week before delivery, respectively. The results of the matched case-control analysis were generally consistent with those of main analyses. CONCLUSION: NO2 may increase the risk of preterm birth, especially for exposures during the third trimester, the month and the week before delivery in Shanghai, China.

Effects of personal nitrogen dioxide exposure on airway inflammation and lung function.

BACKGROUND: Few epidemiological studies have evaluated the respiratory effects of personal exposure to nitrogen dioxide (NO2), a major traffic-related air pollutant. The biological pathway for these effects remains unknown. OBJECTIVES: To evaluate the short-term effects of personal NO2 exposure on lung function, fractional exhaled nitric oxide (FeNO) and DNA methylation of genes involved. METHODS: We conducted a longitudinal panel study among 40 college students with four repeated measurements in Shanghai from May to October in 2016. We measured DNA methylation of the key encoding genes of inducible nitric oxide synthase (NOS2A) and arginase (ARG2). We applied linear mixed-effect models to assess the effects of NO2 on respiratory outcomes. RESULTS: Personal exposure to NO2 was 27.39 ±â€¯23.20 ppb on average. In response to a 10-ppb increase in NO2 exposure, NOS2A methylation (%5 mC) decreased 0.19 at lag 0 d, ARG2 methylation (%5 mC) increased 0.21 and FeNO levels increased 2.82% at lag 1 d; and at lag 2 d the percentage of forced vital capacity, forced expiratory volume in 1 s and peak expiratory flow in predicted values decreased 0.12, 0.37 and 0.67, respectively. The model performance was better compared with those estimated using fixed-site measurements. These effects were robust to the adjustment for co-pollutants and weather conditions. CONCLUSIONS: Our study suggests that short-term personal exposure to NO2 is associated with NOS2A hypomethylation, ARG2 hypermethylation, respiratory inflammation and lung function impairment. The use of personal measurements may better predict the respiratory effects of NO2.

Alleviated systemic oxidative stress effects of combined atmospheric oxidant capacity by fish oil supplementation: A randomized, double-blinded, placebo-controlled trial.

BACKGROUND: Combined atmospheric oxidant capacity (Ox), represented by the sum of nitrogen dioxide (NO2) and ozone (O3), is an important hazardous property of outdoor air pollution mixture. It remains unknown whether its adverse effects can be ameliorated by dietary fish-oil supplementation. OBJECTIVE: To assess the effects of fish-oil supplementation against oxidative stress induced by acute Ox exposure. METHODS: We conducted a randomized, double-blinded and placebo-controlled study among 65 young adults in Shanghai, China between September 2017 and January 2018. We randomly assigned participants to receive either 2.5 g/day of fish oil or placebo, and conducted four repeated physical examinations during the last two months of treatments. Ox concentrations were calculated as the sum of hourly measurements of NO2 and O3. We measured six biomarkers on systemic oxidative stress and antioxidant activity. Linear mixed-effect models were used to assess the short-term effects of Ox on biomarkers in each group. RESULTS: During our study period, the 72-h average Ox concentration was 93.6 µg/m3. Short-term exposure to Ox led to weaker changes in all biomarkers in the fish oil group than in the placebo group. Compared with the placebo group, for a 10-µg/m3 increase in Ox, there were smaller decrements in myeloperoxidase (MPO, difference = 5.92%, lag = 0-2 d, p = 0.03) and malondialdehyde (MDA, difference = 5.00%, lag = 1 d, p = 0.04) in the fish-oil group; there were also larger increments in total antioxidant capacity (TAC, difference = 16.33%, lag = 2 d, p = 0.02) and in glutathione peroxidase (GSH-Px, difference = 8.89%, lag = 0-2 d, p = 0.03) in the fish-oil group. The estimated differences for MPO were robust to adjustment for all co-pollutants and the differences for other biomarkers remained for some co-pollutants. CONCLUSIONS: This trial provides first-hand evidence that dietary fish-oil supplementation may alleviate the systemic oxidative stress induced by Ox.

Associations between ambient temperature and daily hospital admissions for rheumatic heart disease in Shanghai, China.

Rheumatic heart disease (RHD) remains a serious public health burden in developing countries. We conducted a time-series study to explore the association between ambient temperature and daily hospital admissions for RHD in Shanghai, China. We collected data on daily hospital admissions for RHD from 2013 to 2015 from the database of Shanghai Health Insurance System. We applied the generalized additive models together with the distributed lag nonlinear model to estimate the association between temperature and RHD hospital admissions after controlling for relative humidity, time trend, day of the week, and holidays. Stratification analyses by age and gender were performed to evaluate their potential effect modification. A total of 4178 cases of RHD hospitalizations were identified over the study period. There were almost linear, positive, and significant associations between daily mean temperature and RHD hospital admissions with higher risks at hotter days. Compared to reference temperature (0 °C), the cumulative risks of moderate heat (the 90th percentile of temperature, 28.0 °C) and extreme heat (the 99th percentile of temperature, 33.5 °C) over lags 0-5 days were 2.55 (95% confidence interval 1.14, 5.73) and 3.22 (95% confidence interval 1.36, 7.61), respectively. These associations were significantly stronger in older people than in younger people. This study indicated larger risks of RHD hospital admissions associated with higher temperature, especially in older people. Our findings provided first-hand epidemiological evidence regarding the effects of ambient temperature on RHD incidence.

Prognostic value of body mass index for first-line chemoimmunotherapy combinations in advanced non-small cell lung cancer in Chinese population.

Background: Few studies have examined the correlation between body mass index (BMI) and effectiveness of first-line chemoimmunotherapy in patients with advanced non-small cell lung cancer (NSCLC); moreover, the conclusion remains elusive and no such studies have been conducted in the Chinese population. Our study aimed to validate the predictive significance of BMI in Chinese patients with advanced NSCLC receiving first-line chemoimmunotherapy combinations. Methods: Data of patients with advanced NSCLC treated with first-line chemoimmunotherapy between June 2018 and February 2022 at three centers were retrieved retrospectively. The association between baseline BMI with progression-free survival (PFS) and overall survival (OS) was evaluated using the Kaplan-Meier method and Cox regression models. BMI was categorized according to the World Health Organization criteria. Results: Of the included 805 patients, 5.3 % were underweight, 63.4 % had normal weight, 27.8 % were overweight, and 3.5 % were obese. Survival analysis showed that patients in the high BMI group had significantly better PFS (p = 0.012) and OS (p = 0.014) than those in the low BMI group. Further, patients in the overweight subgroup had better PFS (p = 0.036) and OS (p = 0.043) compared to the normal weight population. The results of Cox regression analysis confirmed the correlations between BMI and prognosis of advanced NSCLC patients receiving first-line chemoimmunotherapy combinations. Conclusions: Baseline BMI affected the clinical outcomes of first-line chemoimmunotherapy combinations in patients with advanced NSCLC, and was especially favorable for the overweight subgroup.

PD-(L)1 inhibitors plus bevacizumab and chemotherapy as first-line therapy in PD-L1-negative metastatic lung adenocarcinoma: a real-world data.

BACKGROUND: Chemotherapy combined with immune checkpoint inhibitors (IC), bevacizumab (BC), or both (IBC) is the preferred first-line therapy for PD-L1-negative and oncogenic-driver wild-type metastatic lung adenocarcinoma. However, the optimal strategy is still undetermined. METHODS: This retrospective study enrolled PD-L1-negative metastatic lung adenocarcinoma patients from four cancer centers between January 1, 2018 and June 30, 2022. All the patients received IC, BC, or IBC as the first-line therapies. The efficacy and safety were evaluated. RESULTS: A total of 205 patients were included, with 60, 83, and 62 patients in IC, BC, and IBC groups, respectively. The baseline characteristics among three groups were well balanced. Patients treated with IBC had the highest objective response rate (ORR) (43.5%) and disease control rate (DCR) (100%) relative to those treated with IC (40.4%, 84.2%) or BC (40.5%, 96.2%) (ORR: P = 0.919, DCR: P < 0.01). Compared with the IC (6.74 m) or BC (8.28 m), IBC treatment significantly improved median progression-free survival (mPFS) (9.53 m, P = 0.005). However, no difference in overall survival (OS) was observed. When stratified by different clinical and molecular information, we found that male gender, ever smoking, wild-type genes mutations, and adrenal metastasis predict superior PFS benefit when treated with IBC. In patients with liver metastasis, IBC or BC treatment displayed better PFS compared with IC. No additional adverse reactions were observed in IBC group compared with other two groups. CONCLUSION: Combined IBC treatment achieved superior DCR and PFS compared with IC or BC in patients with PD-L1-negative metastatic lung adenocarcinoma, while did not increase the adverse events.

Arachidonic Acid Metabolites in Self-collected Biospecimens Following Campfire Exposure: Exploring Non-invasive Biomarkers of Wildfire Health Effects.

Climate change has contributed to increased frequency and intensity of wildfire. Studying its acute effects is limited due to unpredictable nature of wildfire occurrence, which necessitates readily deployable techniques to collect biospecimens. To identify biomarkers of wildfire's acute effects, we conducted this exploratory study in eight healthy campers (four men and four women) who self-collected nasal fluid, urine, saliva, and skin wipes at different time points before, during, and after 4-hour exposure to wood smoke in a camping event. Concentrations of black carbon in the air and polycyclic aromatic hydrocarbons in participants' silicone wristbands were significantly elevated during the exposure session. Among 30 arachidonic acid metabolites measured, lipoxygenase metabolites were more abundant in nasal fluid and saliva, whereas cyclooxygenase and non-enzymatic metabolites were more abundant in urine. We observed drastic increases, at 8 hours following the exposure, in urinary levels of PGE2 (398%) and 15-keto-PGF2α (191%) (FDR<10%), with greater increases in men (FDR < 0.01%) than in women. No significant changes were observed for other metabolites in urine or the other biospecimens. Our results suggest urinary PGE2 and 15-keto-PGF2α as promising biomarkers reflecting pathophysiologic (likely sex-dependent) changes induced by short-term exposure to wildfire.

Systemic oxidative stress levels during the course of pregnancy: Associations with exposure to air pollutants.

Increased systemic oxidative stress, implicated in adverse pregnancy outcomes for both mothers and fetuses, has been associated with gestational exposure to air pollutants such as polycyclic aromatic hydrocarbons (PAHs), fine particulate matter (PM2.5), and nitrogen dioxide (NO2). However, it is unclear whether exposure to pollutants at levels below the current air quality standards can increase oxidative stress in pregnant women. In a cohort of 305 pregnant persons residing in western New York, we examined the association between exposure to PM2.5, NO2, and PAHs (measured as urinary 1-hydroxypyrene) and urinary biomarkers of oxidative stress (malondialdehyde [MDA] and 8-hydroxy-2'-deoxyguanosine [8-OHdG]) measured in each trimester. After controlling for gestational stage, maternal age, lifestyles, and socioeconomic factors, each interquartile range (IQR) increase in 1-hydroxypyrene concentration (65.8 pg/ml) was associated with a 7.73% (95%CI: 3.18%,12.3%) higher in MDA levels throughout the pregnancy and in the first and second trimester. An IQR increase in PM2.5 concentration (3.20 µg/m3) was associated with increased MDA levels in the first trimester (8.19%, 95%CI: 0.28%,16.1%), but not the 2nd (-7.99%, 95% CI: 13.8%, -2.23%) or 3rd trimester (-2.81%, 95% CI: 10.0%, 4.38%). The average cumulative PM2.5 exposures in the 3-7 days before urine collection were associated with increased 8-OHdG levels during the second trimester, with the largest difference (22.6%; 95% CI: 3.46%, 41.7%) observed in relation to a one IQR increase in PM2.5 concentration in the previous 7 days. In contrast, neither oxidative stress biomarker was associated with NO2 exposure. Observed in pregnant women exposed to low-level air pollution, these findings expanded previously reported associations between systemic oxidative stress and high-level PM2.5 and PAH concentrations. Further, the first and second trimesters may be a susceptible window during pregnancy for oxidative stress responses to air pollution exposure.

Critical windows of greenness exposure during preconception and gestational periods in association with birthweight outcomes.

Few studies have examined the association between greenness exposure and birth outcomes. This study aims to identify critical exposure time windows during preconception and pregnancy for the association between greenness exposure and birth weight. A cohort of 13 890 pregnant women and newborns in Shanghai, China from 2016-2019 were included in the study. We assessed greenness exposure using Normalized Difference Vegetation Index (NDVI) during the preconception and gestational periods, and evaluated the association with term birthweight, birthweight z-score, small-for-gestational age, and large-for-gestational age using linear and logistic regressions adjusting for key maternal and newborn covariates. Ambient temperature, relative humidity, ambient levels of fine particles (PM2.5) and nitrogen dioxide (NO2) assessed during the same period were adjusted for as sensitivity analyses. Furthermore, we explored the potential different effects by urbanicity and park accessibility through stratified analysis. We found that higher greenness exposure at the second trimester of pregnancy and averaged exposure during the entire pregnancy were associated with higher birthweight and birthweight Z-score. Specifically, a 0.1 unit increase in second trimester averaged NDVI value was associated with an increase in birthweight of 10.2 g (95% CI: 1.8-18.5 g) and in birthweight Z-score of 0.024 (0.003-0.045). A 0.1 unit increase in an averaged NDVI during the entire pregnancy was associated with 10.1 g (95% CI: 1.0-19.2 g) increase in birthweight and 0.025 (0.001-0.048) increase in birthweight Z-score. Moreover, the associations were larger in effect size among urban residents than suburban residents and among residents without park accessibility within 500 m compared to those with park accessibility within 500 m. Our findings suggest that increased greenness exposure, particularly during the second trimester, may be beneficial to birth weight in a metropolitan area.

Efficacy of first-line treatment options beyond RET-TKIs in advanced RET-rearranged non-small cell lung cancer: A multi-center real-world study.

BACKGROUND: Although RET-tyrosine kinase inhibitors (RET-TKIs) are the preferred first-line therapy for advanced RET-arranged NSCLC, most patients cannot afford them. In this population, bevacizumab, immunotherapy, and chemotherapy are the most commonly used regimens. However, the optimal scheme beyond RET-TKIs has not been defined in the first-line setting. METHODS: This retrospective study included 86 stage IV NSCLC patients harboring RET rearrangement from six cancer centers between May 2017 and October 2022. RET-TKIs, chemotherapy, or one of the combination therapies (including immune checkpoint inhibitor (ICI) combined with chemotherapy (I + C), bevacizumab combined with chemotherapy (B + C), ICI and bevacizumab combined with chemotherapy (I + B + C)), were used as the first-line therapeutics. The clinical outcomes and safety were evaluated. RESULTS: Fourteen of the 86 patients received RET-TKIs, 57 received combination therapies, and 15 received chemotherapy alone. Their medium PFS (mPFS) were 16.92 months (95% CI: 5.9-27.9 months), 8.7 months (95% CI: 6.5-11.0 months), and 5.55 months (95% CI: 2.4-8.7 months) respectively. Among all the combination schemes, B + C (p = 0.007) or I + B + C (p = 0.025) gave beneficial PFS compared with chemotherapy, while I + C treatment (p = 0.169) generated comparable PFS with chemotherapy. In addition, I + B + C treatment had a numerically longer mPFS (12.21 months) compared with B + C (8.74 months) or I + C (7.89 months) schemes. In terms of safety, I + B + C treatment led to the highest frequency of hematological toxicity (50%) and vomiting (75%), but no ≥G3 adverse effect was observed. CONCLUSIONS: I + B + C might be a preferred option beyond RET-TKIs in the first-line therapy of RET-arranged NSCLC. Combination with Bevacizumab rather than with ICIs offered favorable survival compared with chemotherapy alone.

Orthodontic treatment improves magnetic resonance imaging features and quality of life in adult patients with temporomandibular disorders.

OBJECTIVE: This research intends to clarify the magnetic resonance imaging (MRI) features as well as changes in symptoms and quality of life (QoL) in adult patients with temporomandibular disorders (TMDs) before and after orthodontic treatment. METHODS: Clinical data of 57 TMD patients before and after orthodontic treatment were collected and analyzed retrospectively. The anterior and posterior regions of the temporomandibular joint (TMJ)'s articular disc were checked before, during and after the treatment by MRI, and the anterior and posterior spaces of TMJ were measured with an electronic measuring ruler. Pre- and post-treatment alterations in the Visual Analogue Scale (VAS) score, TMJ clicking, maximum mouth opening (MMO), and Fricton's indexes (TMJ dysfunction index, DI; palpation index, PI; craniomandibular index, CMI) of the patients were comparatively analyzed. The Oral Health Impact Profile questionnaire was employed for QoL assessment before and after treatment. RESULTS: On MRI, patients with TMDs presented clear changes in TMJ disc position, morphology, thickness and joint effusion, while those with pain symptoms also had condylar degeneration. In addition to a reduced VAS score, the line distance of the TMJ anterior space increased significantly, while the posterior space line distance decreased significantly after treatment, as compared with the baseline (before treatment). Before orthodontic treatment, a total of 46 TMD patients were accompanied by associated TMJ clicking, including 8 severe cases and 38 mild cases. The clicking disappeared in 39 cases after treatment, but mild unilateral clicking, mild bilateral clicking, and severe clicking were still observed in 5, 1, and 1 case(s), respectively. The patients exhibited an increase in MMO and a decrease in Fricton's indexes with significantly enhanced QoL after the orthodontic treatment. CONCLUSIONS: Patients with TMDs exhibit diverse clinical features, and MRI can accurately reflect changes in the position, morphology and thickness of the articular disc as the disease progresses, which can improve the accuracy of clinical diagnosis. In addition, orthodontic treatment for TMD patients can effectively alleviate adverse clinical symptoms and improve their QoL.

Design of a palette of SNAP-tag mimics of fluorescent proteins and their use as cell reporters.

Naturally occurring fluorescent proteins (FPs) are the most widely used tools for tracking cellular proteins and sensing cellular events. Here, we chemically evolved the self-labeling SNAP-tag into a palette of SNAP-tag mimics of fluorescent proteins (SmFPs) that possess bright, rapidly inducible fluorescence ranging from cyan to infrared. SmFPs are integral chemical-genetic entities based on the same fluorogenic principle as FPs, i.e., induction of fluorescence of non-emitting molecular rotors by conformational locking. We demonstrate the usefulness of these SmFPs in real-time tracking of protein expression, degradation, binding interactions, trafficking, and assembly, and show that these optimally designed SmFPs outperform FPs like GFP in many important ways. We further show that the fluorescence of circularly permuted SmFPs is sensitive to the conformational changes of their fusion partners, and that these fusion partners can be used for the development of single SmFP-based genetically encoded calcium sensors for live cell imaging.

Urinary 1-hydroxypyrene in pregnant women in a Northeastern U.S. city: socioeconomic disparity and contributions from air pollution sources.

BACKGROUND: Maternal exposure to polycyclic aromatic hydrocarbons (PAHs), ubiquitous constituents of air pollution, has been associated with adverse birth outcomes. Yet it remains unclear whether and how socioeconomic status (SES) affects gestational PAH exposure. OBJECTIVE: To examine whether there are socioeconomic disparities in PAHs exposure among pregnant women from Rochester, NY, and if so, to what extent disproportionate proximity to air pollution sources, measured by residential distance to transportation-related sources, contributed to the exposure disparity. METHODS: We measured 1-hydroxypyrene concentrations in 726 urine samples collected from 305 pregnant women up to three samples throughout pregnancy. Residential distances to transportation-related sources were calculated based on participants' home addresses. We used linear mixed-effects models with random intercepts of participants to examine associations between 1-hydroxypyrene, SES indicators, and distance to transportation-related sources. We used structural equation modelling to assess to what extent distance to transportation-related sources contributes to the socioeconomic disparity in 1-hydroxypyrene concentrations. RESULTS: Reduced household income and maternal education level were both significant SES predictors of 1-hydroxypyrene concentrations, after the adjustment for other maternal demographic characteristics. Each interquartile range (IQR) increases in residential proximity to the airport (from 14.3 to 6.0 km), the railroad yard (from 22.3 to 6.0 km), and annual average daily traffic within 300 m (from 3796 to 99,933 vehicles/year) were associated with 15.0% (95%CI: 7.0-22.2%), 15.4% (95%CI: 6.5-23.5%), and 13.6% (95%CI: 4.7-23.3%) increases in 1-hydroxypyrene concentrations, respectively. Proximity to these sources jointly explained 10% (95%CI: 1.6-18.4%) of the 1-hydroxypyrene concentration change associated with decreases in SES as a latent variable defined by both household income and education level. IMPACT STATEMENT: Our findings suggest that efforts to address disproportionate residential proximity to transportation-related sources may reduce the socioeconomic disparity in PAH exposure.

Application of land use regression to map environmental noise in Shanghai, China.

BACKGROUND: Urban environment noise has been linked with wide adverse effects on health; however, noise epidemiological researches are hindered by the lack of large-scale population-based exposure assessment. OBJECTIVE: We aimed to measure noise levels over multiple seasons and to establish an LUR model to assess the spatial variability of intra-urban noise and identify its potential sources in Shanghai, China. METHODS: Forty-minute (LAeq, 40 min) measurements of environmental noise were collected at 144 fixed sites, and each was visited three times (morning, afternoon, and evening) in winter, spring, and summer in 2019. Noise measurements were then integrated with land-use types, road networks, socioeconomic variables, and geographic information systems to construct LUR models. Ten-fold cross-validation was used to test the model performance. RESULTS: A total of 1296 measurements and 29 predicting variables were used to estimate the spatial variation in environmental noise. The annual mean (±standard deviation) of LAeq, 40min, was 62 ± 8 dB (A). Significant variations were observed among monitoring sites but not between seasons or time of day. The LUR model explained 79% of the spatial variability of the noise, and the R2 of the ten-fold cross-validation was 0.75. The most contributory predictors of noise level were road-related variables all within the 50-m buffers, followed by urban area within a 50-m buffer, total area of buildings within a 1000-m buffer, and number of restaurant clusters within a 50-m buffer. Farmland area within a 100-m buffer was the only negative variable in the model. A 50-m resolution noise prediction map was produced and suggested high noise level in urban areas and near traffic arteries. CONCLUSION: LUR can be a robust method for reflecting noise variability in megacities such as Shanghai and may provide an efficient solution for noise exposure assessment in areas where noise maps are not available.

High spatial resolution land-use regression model for urban ultrafine particle exposure assessment in Shanghai, China.

BACKGROUND: Little is currently known about long-term health effects of ambient ultrafine particles (UFPs) due to the lack of exposure assessment metrics suitable for use in large population-based studies. Land use regression (LUR) models have been used increasingly for modeling small-scale spatial variation in UFPs concentrations in European and American, but have never been applied in developing countries with heavy air pollution. OBJECTIVE: This study developed a land-use regression (LUR) model for UFP exposure assessment in Shanghai, a typic mega city of China, where dense population resides. METHOD: A 30-minute measurement of particle number concentrations of UFPs was collected at each visit at 144 fixed sites, and each was visited three times in each season of winter, spring, and summer. The annual adjusted average was calculated and regressed against pre-selected geographic information system-derived predictor variables using a stepwise variable selection method. RESULT: The final LUR model explained 69% of the spatial variability in UFP with a root mean square error of 6008 particles cm-3. The 10-fold cross validation R2 reached 0.68, revealing the robustness of the model. The final predictors included traffic-related NOx emissions, number of restaurants, building footprint area, and distance to the nearest national road. These predictors were within a relatively small buffer size, ranging from 50 m to 100 m, indicating great spatial variations of UFP particle number concentration and the need of high-resolution models for UFP exposure assessment in urban areas. CONCLUSION: We concluded that based on a purpose-designed short-term monitoring network, LUR model can be applied to predict UFPs spatial surface in a mega city of China. Majority of the spatial variability in the annual mean of ambient UFP was explained in the model comprised primarily of traffic-, building-, and restaurant-related predictors.

Acute effects of personal exposure to fine particulate matter on salivary and urinary biomarkers of inflammation and oxidative stress in healthy adults.

Non-invasive bio-samples, such as saliva and urine, are promising tools for assessment of inflammation and oxidative stress biomarkers. Few studies have investigated potential responses of those biomarkers towards short-term PM2.5 exposure. We conducted a longitudinal study with 4 repeated examinations among 40 healthy, nonsmoking adults in Shanghai, China. Personal samplings were performed for PM2.5 exposure assessment. Then, five biomarkers, including C-reactive protein (CRP), tumor necrosis factor-α (TNF-α), alpha-1 antitrypsin (A1AT) in saliva and 8-Iso-Prostaglanding F2α (8-iso-PGF2α), total antioxidant capacity (TAC) in urine, were measured. We fitted linear mixed-effect models to evaluate short-term effect of personal PM2.5 exposure on salivary and urinary biomarkers, adjusting for potential confounders of meteorology, sociodemographic characteristics and biomarker detection. We also explored sensitive time windows of exposure for different biomarkers. We found robust associations of salivary CRP, TNF-α, and urinary 8-iso-PGF2α with PM2.5 exposure, and responses of salivary inflammatory markers occurred more acutely than urinary oxidative stress markers. For instance, a 10 µg/m3 increase in PM2.5 was associated with an elevation of 5.49% (95% CI: 1.17%, 9.99%) in CRP and 7.05% (95% CI: 1.29%, 13.13%) in TNF-α both at lag 12 h, and 6.97% (95% CI: 1.33%, 12.92%) in 8-iso-PGF2α at lag 01 d. Based on non-invasive samples, this study provided evidence on effect of PM2.5 exposure on responses of systematic inflammation and oxidative stress. Sub-daily (6-12 h) and daily (≥24 h) period after PM2.5 exposure might be sensitive time window to detect the responses of salivary (i.e. CRP, TNF) and urinary biomarkers (i.e. 8-iso-PGF2α), respectively.