Factors Influencing the Sharing of Personal Health Data Based on the Integrated Theory of Privacy Calculus and Theory of Planned Behaviors Framework: Results of a Cross-Sectional Study of Chinese Patients in the Yangtze River Delta.

BACKGROUND: The health care system in China is fragmented, and the distribution of high-quality resources remains uneven and irrational. Information sharing is essential to the development of an integrated health care system and maximizing its benefits. Nevertheless, data sharing raises concerns regarding the privacy and confidentiality of personal health information, which affect the willingness of patients to share information. OBJECTIVE: This study aims to investigate patients' willingness to share personal health data at different levels of maternal and child specialized hospitals in China, to propose and test a conceptual model to identify key influencing factors, and to provide countermeasures and suggestions to improve the level of data sharing. METHODS: A research framework based on the Theory of Privacy Calculus and the Theory of Planned Behavior was developed and empirically tested through a cross-sectional field survey from September 2022 to October 2022 in the Yangtze River Delta region, China. A 33-item measurement instrument was developed. Descriptive statistics, chi-square tests, and logistic regression analyses were conducted to characterize the willingness of sharing personal health data and differences by sociodemographic factors. Structural equation modeling was used to assess the reliability and validity of the measurement as well as to test the research hypotheses. The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist for cross-sectional studies was applied for reporting results. RESULTS: The empirical framework had a good fit with the chi-square/degree of freedom (χ2/df)=2.637, root-mean-square residual=0.032, root-mean-square error of approximation=0.048, goodness-of-fit index=0.950, and normed fit index=0.955. A total of 2060 completed questionnaires were received (response rate: 2060/2400, 85.83%). Moral motive (ß=.803, P<.001), perceived benefit (ß=.123, P=.04), and perceived effectiveness of government regulation (ß=.110, P=.001) had a significantly positive association with sharing willingness, while perceived risk (ß=-.143, P<.001) had a significant negative impact, with moral motive having the greatest impact. The estimated model explained 90.5% of the variance in sharing willingness. CONCLUSIONS: This study contributes to the literature on personal health data sharing by integrating the Theory of Privacy Calculus and the Theory of Planned Behavior. Most Chinese patients are willing to share their personal health data, which is primarily motivated by moral concerns to improve public health and assist in the diagnosis and treatment of illnesses. Patients with no prior experience with personal information disclosure and those who have tertiary hospital visits were more likely to share their health data. Practical guidelines are provided to health policy makers and health care practitioners to encourage patients to share their personal health information.

Factors Influencing the Acceptance of Pediatric Telemedicine Services in China: A Cross-Sectional Study.

Background: Pediatrician workforce shortages have aroused great attention from health authorities in China. Telemedicine services have been known to enhance the management of children's health, yet the rate of adoption and usage in Chinese hospitals still at a quite low level, and the factors influencing the acceptance of telemedicine services remains unclear. Objective: The purpose of this empirical study was to evaluate the reliability and validity of a technology acceptance measurement instrument applied in healthcare, to investigate the perception of telemedicine services on the provider-side and demand-side, and to determine the factors that may drive individuals to adopt telemedicine services. Methods: A cross-sectional survey study based at Shanghai Children's Hospital, Shanghai Jiao Tong University, was conducted in March 2020. A total of 456 valid responses were obtained by convenience sampling. The internal consistency of items was assessed by Cronbach's alpha (α), composite reliability (CR) and average variance extracted (AVE) to evaluate both the reliability and validity of the questionnaire. Structural equation modeling analysis was used to test and verify the interrelationships among relevant variables. Results: Price value is the strongest predictor (ß = 0.30, p = 0.02), facilitating conditions (ß = 0.28, p = 0.01) and hedonic motivation (ß = 0.13, p = 0.04) also have significantly positive direct effects on telemedicine acceptance. The results showed the perception of child patients' families were significantly more acceptable to telemedicine services than pediatricians (t = -2.99, p < 0.01). Participants with no prior experience and lower education may be more willing to adopt telemedicine. Conclusion: Telemedicine will likely continue to have an integral role in pediatric health care delivery, and the findings can assist policy makers and hospital administrators in determining the more valued characteristics of telemedicine services from a behavioral perspective. Future attention will be paid to the pricing, training and service quality of telemedicine in China.

Influence of ambient temperature and diurnal temperature variation on the premature rupture of membranes in East China: A distributed lag nonlinear time series analysis.

BACKGROUND: Extreme ambient temperature has an adverse effect on pregnancy outcomes, but the conclusions have been inconsistent. The influence of ambient temperature and diurnal temperature variation on the premature rupture of membranes (PROM) needs further study. METHODS AND FINDINGS: The daily data of PROMs, daily meteorological and air pollutant were obtained. After controlling for potential confounding factors, the quasi-Poisson generalized additive model (GAM) combined with the distributed lag nonlinear model (DLNM) was used to analyze the association between temperature or diurnal temperature variation and PROM, including preterm premature rupture of membranes (PPROM) and term premature rupture of membranes (term PROM). Compared with the median temperature(18.7 °C), the mean temperature of 5-7 days lagging beyond 31.5 °C and below -1.5 °C was positively correlated with PROM; the mean temperature had more sensitive effect on the term PROM. Exposure to extremely high temperatures (97.5th percentile, 32 °C) had a 6-day lagging relative risk (RR) (95% CI: 1.005-1.160) of 1.08 for PROM and a 6-day lagging RR of 1.079 (95% CI: 1.005-1.159) for term PROM; Exposure to a high diurnal temperature variation (diurnal temperature variation greater than 16 °C) was positively correlated with the term PROM. Compared with the 2.5th percentile diurnal temperature variation (2 °C), exposure to the 95th percentile diurnal temperature variation (17 °C) significantly increased the risk of term PROM (RR: 1.229, 95% CI: 1.029-1.467). CONCLUSIONS: Exposure to a high-temperature and a high diurnal temperature variation environment will increase the relative risks of PROM. For pregnant women in the 3rd trimester, it is important to reduce exposure to extremely high-temperatures and greater diurnal temperature changes.

Necessity of personal sampling for exposure assessment on specific constituents of PM2.5: Results of a panel study in Shanghai, China.

Many epidemiological studies have evaluated the health risks of ambient fine particulate matter (PM2.5). However, few studies have investigated the potential exposure misclassification caused by using ambient PM2.5 concentrations as proxy for individual exposure to PM2.5 in regions with high-level of air pollution. This study aimed to compare the differences between personal and ambient PM2.5 constituent concentrations, and to predict the personal exposure of sixteen PM2.5 constituents. We collected 141 72-h personal exposure filter samples from a panel of 36 healthy non-smoking college students in Shanghai, China. We then used the liner mixed effects models to predict personal constituent-specific exposure using ambient observations and several possible influencing factors including time-activity patterns, temporal variables, and meteorological conditions. The final model of each component was further evaluated by determination coefficient (R2) and root mean square error (RMSE) from leave-one-out-cross-validation (LOOCV). We observed ambient concentrations were higher than personal concentrations for all PM2.5 components except for Mn, Fe, Ca, and V. Especially, ambient NH4+, As, and NO3- concentrations were 3.65, 5.65 and 7.33-fold higher than their corresponding personal concentrations, respectively. The ambient level was the strongest predictor of their corresponding personal PM2.5 components with the highest marginal R2 (RM2: 0.081 ~ 0.901), meteorological conditions (RM2: 0.000 ~ 0.357), time-activity pattern (RM2: 0.000 ~ 0.083) and temporal indicators (RM2: 0.031 ~ 0.562) were also important predictors. Our final models predicted at least 50% of the variance of all personal PM2.5 constituents and even over 90% for K, Pb, and SO42-. LOOCV analysis showed that R2 and RMSE ranged from 0.251 to 0.907 and 0.000 to 0.092 µg/m3, respectively. Our results showed that ambient concentration of most PM2.5 constituents along with time-activity patterns, temporal variables, and meteorological conditions, could adequately predict personal exposure concentration. Prediction models of individual PM2.5 constituent may help to improve the accuracy of exposure measurement in future epidemiological studies.

Effects of filtered fresh air ventilation on classroom indoor air and biomarkers in saliva and nasal samples: A randomized crossover intervention study in preschool children.

To evaluate the short-term effects of filtered fresh air ventilation system on classroom indoor air and biomarkers in saliva and nasal samples in preschool children, a randomized crossover study was conducted in a kindergarten in Shanghai, China in 2016. Two classrooms at the same grade (n = 43) were selected and fresh air ventilation systems (FAVS) with high efficiency particulate air filter (HEPA) were installed. In the first week, FAVS-HEPA was run in one classroom for 2 continuous school days and the other classroom was remained as usual with no use of FAVS-HEPA. After one week of wash-out, the ventilation modes exchanged between two classrooms and another 2 days of intervention were repeated. Real-time indoor and outdoor air pollution and climate factors (PM2.5, Temp and relative humidity (R.H.)) were measured. Saliva and nasal internal mucosa samples were collected immediately at the end of each intervention scenario. Linear mixed-effect regression model was applied to evaluate the effects of intervention on children's health indicators controlling for age, gender, height, BMI and temperature. The results showed, with FAVS-HEPA, the classroom indoor fine particulate matter (PM2.5)(29.1 ±â€¯17.9 µg/m3) was on average significantly lower than that without FAVS-HEPA (85.7 ±â€¯43.2 µg/m3). By regression analysis, each 10 µg/m3 decrease of indoor PM2.5 during the 8 school hours in the first intervention day was associated with an average of 1.76% (95% confidence interval (CI) 0.43-3.08%) increase in saliva lysozyme. This percentage increased to 2.41% (95%CI 0.52-4.26%) if related to the PM2.5 level in 16 school hours over 2 days of intervention. A total of 19 nasal bacterial taxa were lower in subjects exposed to FAVS-HEPA, compared to that with no use of FAVS-HEPA, despite the general bacteria diversity levels in nasal samples were not statistically different. Among others, Providencia species showed significant effects in mediating the associations between higher PM2.5 and lower lysozyme. In conclusion, using FAVS-HEPA was effective in decreasing the classroom indoor PM2.5. Saliva lysozyme, as a non-specific immune biomarker, was significantly inversely associated with indoor PM2.5. Certain nasal bacteria might play key roles in mediating PM2.5 exposure and children's lysozyme levels.

Personal Fine Particulate Matter Constituents, Increased Systemic Inflammation, and the Role of DNA Hypomethylation.

Limited evidence is available on the effects of various fine particulate matter (PM2.5) components on inflammatory cytokines and DNA methylation. We examined whether 16 PM2.5 components are associated with changes in four blood biomarkers, that is, tumor necrosis factor-α (TNF-α), soluble cluster of differentiation 40 ligand (sCD40L), soluble intercellular adhesion molecule-1 (sICAM-1), and fibrinogen, as well as their corresponding DNA methylation levels in a panel of 36 healthy college students in Shanghai, China. We used linear mixed-effect models to evaluate the associations, with controls of potential confounders. We further conducted mediation analysis to evaluate the potential mediation effects of components on inflammatory markers through change in DNA methylation. We observed that several components were consistently associated with TNF-α and fibrinogen as well as their DNA hypomethylation. For example, an interquartile range increase in personal exposure to PM2.5-lead (Pb) was associated with 65.20% (95% CI: 37.07, 99.10) increase in TNF-α and 2.66 (95% CI: 37.07, 99.10) decrease in TNF-α methylation, 30.51% (95% CI: 0.72, 69.11) increase in fibrinogen and 1.25 (95% CI: 0.67, 1.83) decrease in F3 methylation. PM2.5 components were significantly associated with sICAM-1 methylation but not with sICAM-1 protein. DNA methylation mediated 19.89%-41.75% of the elevation in TNF-α expression by various PM2.5 constituents. Our findings provide clues that personal PM2.5 constituents exposure may contribute to increased systemic inflammation through DNA hypomethylation.

Estimation of personal PM2.5 and BC exposure by a modeling approach - Results of a panel study in Shanghai, China.

BACKGROUND: Epidemiologic studies of PM2.5 (particulate matter with aerodynamic diameter ≤2.5 µm) and black carbon (BC) typically use ambient measurements as exposure proxies given that individual measurement is infeasible among large populations. Failure to account for variation in exposure will bias epidemiologic study results. The ability of ambient measurement as a proxy of exposure in regions with heavy pollution is untested. OBJECTIVE: We aimed to investigate effects of potential determinants and to estimate PM2.5 and BC exposure by a modeling approach. METHODS: We collected 417 24 h personal PM2.5 and 130 72 h personal BC measurements from a panel of 36 nonsmoking college students in Shanghai, China. Each participant underwent 4 rounds of three consecutive 24-h sampling sessions through December 2014 to July 2015. We applied backwards regression to construct mixed effect models incorporating all accessible variables of ambient pollution, climate and time-location information for exposure prediction. All models were evaluated by marginal R2 and root mean square error (RMSE) from a leave-one-out-cross-validation (LOOCV) and a 10-fold cross-validation (10-fold CV). RESULTS: Personal PM2.5 was 47.6% lower than ambient level, with mean (±Standard Deviation, SD) level of 39.9 (±32.1) µg/m3; whereas personal BC (6.1 (±2.8) µg/m3) was about one-fold higher than the corresponding ambient concentrations. Ambient levels were the most significant determinants of PM2.5 and BC exposure. Meteorological and season indicators were also important predictors. Our final models predicted 75% of the variance in 24 h personal PM2.5 and 72 h personal BC. LOOCV analysis showed an R2 (RMSE) of 0.73 (0.40) for PM2.5 and 0.66 (0.27) for BC. Ten-fold CV analysis showed a R2 (RMSE) of 0.73 (0.41) for PM2.5 and 0.68 (0.26) for BC. CONCLUSION: We used readily accessible data and established intuitive models that can predict PM2.5 and BC exposure. This modeling approach can be a feasible solution for PM exposure estimation in epidemiological studies.

Possible Mediation by Methylation in Acute Inflammation Following Personal Exposure to Fine Particulate Air Pollution.

Air pollution may increase cardiovascular and respiratory risk through inflammatory pathways, but evidence for acute effects has been weak and indirect. Between December 2014 and July 2015, we enrolled 36 healthy, nonsmoking college students for a panel study in Shanghai, China, a city with highly variable levels of air pollution. We measured personal exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) continuously for 72 hours preceding each of 4 clinical visits that included phlebotomy. We measured 4 inflammation proteins and DNA methylation at nearby regulatory cytosine-phosphate-guanine (CpG) loci. We applied linear mixed-effect models to examine associations over various lag times. When results suggested mediation, we evaluated methylation as mediator. Increased PM2.5 concentration was positively associated with all 4 inflammation proteins and negatively associated with DNA methylation at regulatory loci for tumor necrosis factor alpha (TNF-α) and soluble intercellular adhesion molecule-1. A 10-µg/m3 increase in average PM2.5 during the 24 hours preceding blood draw corresponded to a 4.4% increase in TNF-α and a statistically significant decrease in methylation at one of the two studied candidate CpG loci for TNF-α. Epigenetics may play an important role in mediating effects of PM2.5 on inflammatory pathways.

Validation of a light-scattering PM2.5 sensor monitor based on the long-term gravimetric measurements in field tests.

BACKGROUND: Portable direct-reading instruments by light-scattering method are increasingly used in airborne fine particulate matter (PM2.5) monitoring. However, there are limited calibration studies on such instruments by applying the gravimetric method as reference method in field tests. METHODS: An 8-month sampling was performed and 96 pairs of PM2.5 data by both the gravimetric method and the simultaneous light-scattering real-time monitoring (QT-50) were obtained from July, 2015 to February, 2016 in Shanghai. Temperature and relative humidity (RH) were recorded. Mann-Whitney U nonparametric test and Spearman correlation were used to investigate the differences between the two measurements. Multiple linear regression (MLR) model was applied to set up the calibration model for the light-scattering device. RESULTS: The average PM2.5 concentration (median) was 48.1µg/m3 (min-max 10.4-95.8µg/m3) by the gravimetric method and 58.1µg/m3 (19.2-315.9µg/m3) by the light-scattering method, respectively. By time trend analyses, they were significantly correlated with each other (Spearman correlation coefficient 0.889, P<0.01). By MLR, the calibration model for the light-scattering instrument was Y(calibrated) = 57.45 + 0.47 × X(the QT - 50 measurements) - 0.53 × RH - 0.41 × Temp with both RH and temperature adjusted. The 10-fold cross-validation R2 and the root mean squared error of the calibration model were 0.79 and 11.43 µg/m3, respectively. CONCLUSION: Light-scattering measurements of PM2.5 by QT-50 instrument overestimated the concentration levels and were affected by temperature and RH. The calibration model for QT-50 instrument was firstly set up against the gravimetric method with temperature and RH adjusted.

Personal exposure to fine particulate matter, lung function and serum club cell secretory protein (Clara).

BACKGROUND: The underlying mechanisms about the association between ambient fine particulate matter (PM2.5) and lung function were unclear. Few epidemiological studies have evaluated the potential mediating effects of serum club cell secretory protein (Clara) (CC16), a biomarker of pulmonary epithelium integrity. OBJECTIVES: To evaluate the short-term effect of personal PM2.5 exposure on lung function and to explore the potential mediating role of CC16 in this effect. METHODS: We enrolled 36 healthy, nonsmoking college students for a panel study in Shanghai, China from December 17, 2014 to July 11, 2015. We measured personal and real-time exposure to PM2.5 for 72 h preceding each of four rounds of health examinations, including lung function test and serum CC16 measurement. We used linear mixed-effect models to examine the effects of PM2.5 on lung function and CC16 over various lag times. Furthermore, we analyzed the mediating effect of CC16 in the association between PM2.5 and lung function. RESULTS: Average PM2.5 exposure ranged from 36 to 52 µg/m3 across different lag periods. PM2.5 exposure was negatively associated with lung function and positively associated with serum CC16 concentration. The effect of PM2.5 on CC16 occurred earlier than that on lung function. For instance, an interquartile range (IQR) increase in 0-2 h average exposure to PM2.5 was significantly associated with a 4.84% increase in serum CC16; and an IQR increase in 3-6 h average exposure to PM2.5 was significantly associated with a 1.08% decrease in 1-sec forced expiratory volume. These effects lasted up to 24 h after exposure. Increased serum CC16 contributed 3.9%-36.3% of the association between PM2.5 and impaired lung function. CONCLUSIONS: Acute exposure to PM2.5 might induce an immediate decrease in lung function by virtue of the loss of pulmonary epithelium integrity.

Cardiovascular Benefits of Wearing Particulate-Filtering Respirators: A Randomized Crossover Trial.

BACKGROUND: Practical approaches to protect individuals from ambient particulate matter (PM) are urgently needed in developing countries. Evidence on the health benefits of wearing particulate-filtering respirators is limited. OBJECTIVES: We evaluated the short-term cardiovascular health effects of wearing respirators in China. METHODS: A randomized crossover trial was performed in 24 healthy young adults in Shanghai, China in 2014. The subjects were randomized into two groups and wore particulate-filtering respirators for 48 hr alternating with a 3-week washout interval. Heart rate variability (HRV) and ambulatory blood pressure (BP) were continuously monitored during the 2nd 24 hr in each intervention. Circulating biomarkers were measured at the end of each intervention. Linear mixed-effect models were applied to evaluate the effects of wearing respirators on health outcomes. RESULTS: During the intervention periods, the mean daily average concentration of PM with an aerodynamic diameter < 2.5 µm (PM2.5) was 74.2 µg/m3. Compared with the absence of respirators, wearing respirators was associated with a decrease of 2.7 mmHg [95% confidence interval (CI): 0.1, 5.2 mmHg] in systolic BP and increases of HRV parameters, including 12.5% (95% CI: 3.8%, 21.2%) in high frequency (HF) power, 10.9% (95% CI: 1.8%, 20.0%) in the root mean square of the successive differences, and 22.1% (95% CI: 3.6%, 40.7%) in the percentage of normal RR intervals with duration > 50 msec different from the previous normal RR interval (pNN50). The presence of respirators was also associated with a decrease of 7.8% (95% CI: 3.5%, 12.1%) in the ratio of low frequency (LF)/HF power. CONCLUSIONS: Short-term wearing of particulate-filtering respirators may produce cardiovascular benefits by improving autonomic nervous function and reducing BP. Citation: Shi J, Lin Z, Chen R, Wang C, Yang C, Cai J, Lin J, Xu X, Ross JA, Zhao Z, Kan H. 2017. Cardiovascular benefits of wearing particulate-filtering respirators: a randomized crossover trial. Environ Health Perspect 125:175-180; http://dx.doi.org/10.1289/EHP73.

Personal exposure to fine particulate matter and blood pressure: A role of angiotensin converting enzyme and its DNA methylation.

BACKGROUND: The underlying intermediate mechanisms about the association between fine particulate matter (PM2.5) air pollution and blood pressure (BP) were unclear. Few epidemiological studies have explored the potential mediation effects of angiotensin-converting enzyme (ACE) and its DNA methylation. METHODS: We designed a longitudinal panel study with 4 follow-ups among 36 healthy college students in Shanghai, China from December 17, 2014 to July 11, 2015. We measured personal real-time exposure to PM2.5, serum ACE level, and blood methylation of ACE gene and the repetitive elements. We applied linear mixed-effects models to examine the effects of PM2.5 on ACE protein, DNA methylation and BP markers. Furthermore, we conducted mediation analyses to evaluate the potential pathways. RESULTS: An interquartile range increase (26.78µg/m(3)) in 24-h average exposure to PM2.5 was significantly associated with 1.12 decreases in ACE average methylation (%5mC), 13.27% increase in ACE protein, and increments of 1.13mmHg in systolic BP, 0.66mmHg in diastolic BP and 0.82mmHg in mean arterial pressure. ACE hypomethylation mediated 11.78% (P=0.03) of the elevated ACE protein by PM2.5. Increased ACE protein accounted for 3.90~13.44% (P=0.35~0.68) of the elevated BP by PM2.5. Repetitive-element methylation was also decreased but did not significantly mediate the association between PM2.5 and BP. CONCLUSIONS: This investigation provided strong evidence that short-term exposure to PM2.5 was significantly associated with BP, ACE protein and ACE methylation. Our findings highlighted a possible involvement of ACE and ACE methylation in the effects of PM2.5 on elevating BP.

Association between fine particulate matter chemical constituents and airway inflammation: A panel study among healthy adults in China.

BACKGROUND: Ambient fine particulate matter (PM2.5) air pollution has been associated with increased airway inflammation, but the roles of various PM2.5 constituents remain to be determined. OBJECTIVES: To investigate the acute effects of PM2.5 constituents on fractional exhaled nitric oxide (FeNO), a well-established biomarker of respiratory inflammation. METHODS: A longitudinal panel study was performed among 32 healthy young adults in Shanghai, China from January 12th to February 6th, 2015. FeNO was repeatedly measured, 6-8 times per subject. Real-time mass concentration of ambient PM2.5 and chemical constituents were obtained from a nearby monitoring station. Linear mixed-effect models were applied to evaluate the association between FeNO and PM2.5 constituents, with the adjustment of age, gender, body mass index, temperature, relative humidity and day of week. The robustness of constituents' effects was also evaluated. RESULTS: A total of 234 effective measurements of FeNO were obtained with a geometric mean of 13.1 ppb. The PM2.5-FeNO associations were strongest at lags of 0-6h and diminished at lags longer than 12h. An interquartile range increase in PM2.5 constituents (NH4(+), NO3(-), K(+), SO4(2-) and elemental carbon) at lags of 0-6h were significantly associated with increments in FeNO by 12.3%, 11.3%, 11.1%, 9.6% and 10.7%, respectively. After controlling for PM2.5 total mass and the colinearity, only elemental carbon remained significant. CONCLUSION: Several chemical constituents of PM2.5 may impact FeNO following acute exposure. Elemental carbon in particular may be the primary component responsible for increased airway inflammation.

The first 2-year home environment in relation to the new onset and remission of asthmatic and allergic symptoms in 4246 preschool children.

The home environment can influence childhood allergies and respiratory health but there is little information on associations between early life exposure at home and new onset and remission of the asthmatic or allergic symptoms in preschool children. A questionnaire survey was performed in a random cluster sample of 4246 preschool children in Urumqi, China. Information on the home environment (perceptions of odors and indicators of pollution sources) and children's health (wheeze, rhinitis and eczema) was collected for the first 2 years of life and the last year (before answering the questionnaire) from one of the parents or another guardian of the child. Associations between the home environment the first 2 years of life and new onset and remission of childhood symptoms were analyzed by multiple logistic regression. Home environment factors reported for the first 2 years of life were consistently positively associated with new onset of symptoms and negatively associated with remission of symptoms. Visible mold (OR 1.46, 95% CI 1.12-1.90), moldy odor (OR 2.15, 95% CI 1.45-3.18), air dryness (OR 1.31, 95% CI 1.08-1.59), stuffy odor (OR 1.25, 95% CI 1.01-1.54) and parental smoking (OR 1.36, 95% CI 1.13-1.65) were associated with new onset of symptoms. These factors were negatively associated with the remission of symptoms. In conclusion, mold contamination at home (moldy odor/visible mold), poor indoor air quality (stuffy odor, air dryness) and exposure to environmental tobacco smoke (ETS) in the first 2 years of life can increase the incidence of asthmatic and allergic symptoms and decrease the remission from these symptoms in preschool children.

[Effect of combination of sub-MIC sodium houttuyfonate and erythromycin on biofilm of Staphylococcus epidermidis].

OBJECTIVE: To observe the effect of the combination of sub-MIC sodium houttuyfonate and erythromycin on biofilm of Staphylococcus epidermidis. METHOD: The serial dilution method was adopted to determine MIC of the combination of sodium houttuyfonate and erythromycin on S. epidermidis; the checkerboard method was used to evaluate the combination of sodium houttuyfonate and erythromycin on suspended bacteria of S. epidermidis; S. epidermidis biofilm was built in vitro, and XTT reduction assay was used to evaluate the effect of the combination of sub-MIC sodium houttuyfonate and erythromycin on the adhesion of S. epidermidis and bacterial metabolism inside the biofilm. Microscope was applied to observe the impact the single administration and combination of the two medicines under sub-MIC on biofilm morphology of S. epidermidis. RESULT: The MIC of sodium houttuyfonate and erythromycin were 62.5, 7.812 5 mg x L(-1), respectively. The combination of 1/8MIC sodium houttuyfonate and 1/2MIC erythronmycin showed a synergistic effect on S. epidermidis. Sodium houttuyfonate, erythromycin and their combination had an inhibitory effect on the adhesion and metabolism of S. epidermidis biofilm bacteria, and made impact on the morphology of S. epidermidis biofilm. CONCLUSION: The sub-MIC sodium houttuyfonate and erythromycin have an inhibitory effect on S. epidermidis biofilm. The combination of sodium houttuyfonate and erythromycin shows a synergistic effect in inhibiting suspended bacteria and biofilm of S. epidermidis, particularly in inhibiting the metabolism of S. epidermidis biofilm bacteria and impacting the morphology of biofilm.

[Preliminary study of effects of andrographolide on Staphylococcus epidermidis biofilms].

OBJECTIVE: To provide a new therapeutic approach for Staphylococcus epidermidis biofilm-associated infections by the study of inhibitory effect of andrographolide (AG) on S. epidermidis biofilm. METHOD: S. epidermidis biofilms were set up in vitro, erythromycin was acted as the positive control agent, XTT reduction assay was used to evaluate AG on the initial adhesion of S. epidermidis and bacterial metabolism within biofilm, microscope was applied to observe biofilm morphology, and Congo red assay was used to detect polysacchatide interc-ellular adhesion (PIA)formation when exposed to AG. RESULT: AG showed inhibitory effects against the initial adhesion of S. epidermidis at concentrations of 1 000,100, 10 mg x L(-1), respectively,and inhibited metabolism of biofilm bacteria at the concentration of 31.25 mg x L(-1), and exhibited significantly inhibition against the biofilm morphology at the concentration of 250 mg x L(-1), while did not display inhibition against PIA formation at the concentration of 10 mg x L(-1). CONCLUSION: AG could remarkably inhibit biofilm formation of S. epidermidis, although it was less potent than erythromycin.

Carbon dioxide capture by functionalized solid amine sorbents with simulated flue gas conditions.

A novel solid amine sorbent was prepared using KIT-6-type mesoporous silica modified with tetraethylenepentamine (TEPA). Its adsorption behavior toward CO(2) from simulated flue gases is investigated using an adsorption column. The adsorption capacities at temperatures of 303, 313, 333, 343, and 353 K are 2.10, 2.29, 2.58, 2.85, and 2.71 mmol g(-1), respectively. Experimental adsorption isotherms were obtained, and the average isosteric heat of adsorption was 43.8 kJ/mol. The adsorption capacity increases to 3.2 mmol g(-1) when the relative humidity (RH) of the simulated flue gas reaches 37%. The adsorption capacity is inhibited slightly by the presence of SO(2) at concentrations lower than 300 ppm but is not significantly influenced by NO at concentrations up to 400 ppm. The adsorbent is completely regenerated in 10 min at 393 K and a pressure of 5 KPa, with expected consumption energy of about 1.41 MJ kg(-1) CO(2). The adsorption capacity remains almost the same after 10 cycles of adsorption/regeneration with adsorption conditions of 10 vol % CO(2), 100 ppm SO(2), 200 ppm NO, 100% relative humidity, and a temperature of 393 K. The solid amine sorbent, KIT-6(TEPA), performs excellently for CO(2) capture and its separation from flue gas.