Filling gaps between exposure modeling and the analysis of urinary biomarkers using personal air monitoring: An intervention study of permethrin used in home insecticide spray.

Permethrin is one of the most widely used active ingredients in spray-type home insecticides. However, indoor permethrin exposure resulting from the use of home insecticides is not well-characterized, as measured permethrin concentrations in indoor environmental and biological media with a known application rate are scarce. We conducted an intervention study with four participants for seven days. We conducted personal air monitoring and collected 24-h urine samples in which we quantified time-weighted average (TWA) permethrin concentrations in indoor air (Cair ) and urinary concentrations of two permethrin metabolites, 3-phenoxybenzoic acid (3-PBA) and cis/trans-3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid (cis/trans-DCCA). We also estimated (1) TWA Cair using a simple indoor air model and (2) urinary excreted (UE) mass using a simple excretion model with both estimated and measured TWA Cair . Measurements of TWA Cair from personal air monitoring were lower than those estimated from the indoor model by a factor of 2.9 to 49.4. The ratio of estimated to measured UE mass ranged 3.5-18.2 when using estimated TWA Cair and 1.1-2.9 when using measured TWA Cair . Smaller ratios in estimating internal permethrin exposure from personal air monitoring suggest that personal air monitoring could reduce uncertainties in permethrin exposure assessment resulting from the use of spray-type insecticides.

Development of a personal passive air sampler for estimating exposure to effective chlorine while using chlorine-based disinfectants.

With an increasing use of indoor disinfectants such as chlorine (Cl2 ) and hypochlorous acid, a convenient sampler for estimating exposure to oxidants, such as effective chlorine, is necessary. Here, we developed a personal passive air sampler (PPAS) composed of a redox dye, o-dianisidine, in a polydimethylsiloxane (PDMS) sheet. o-Dianisidine readily reacts with gaseous oxidants generated by bleach usage, and its color changes as the reaction progresses; hence, personal exposure to effective chlorine could be easily detected by the naked eye, while cumulative exposure could be determined by measuring concentrations of o-dianisidine reacting with it. The PPAS was calibrated, and a sampling rate of 0.00253 m3 /h was obtained using a small test chamber. The PPAS was tested with the help of ten volunteers whose personal exposure to Cl2 -equivalent gas was estimated after bathrooms were cleaned using spray and liquid-type household disinfection products, and the accumulated exposure-gas concentrations ranged from 69 to 408 ppbv and 148 to 435 ppbv, respectively. These PPAS-derived exposure concentrations were approximately two orders lower than those estimated using ConsExpo, suggesting a significant overestimation by prevailing screening models, possibly due to the ignorance of transformation reactions.

Smart Sensors and Standard-Based Interoperability in Smart Grids.

Smart grids (SGs) are electrical power grids that apply information, advanced networking, and real-time monitoring and control technologies to lower costs, save energy, and improve security, interoperability, and reliability. Smart sensors (SSs) can provide real-time data and status of the grids for real-time monitoring, protection, and control of grid operations. Sensor data exchange and interoperability are major challenges for the SGs. This paper describes sensing, timing, intelligence, and communication requirements of sensors for the SGs and proposes a general model of the SSs for SGs based on these requirements. Then it illustrates, how the model works with phasor measurement unit (PMU)- and merging unit-based SSs deployed in the SGs with standardized interfaces to support the interoperability of the SSs. Furthermore, to address the interoperability issues, this paper describes sensor interface standards used in the SGs and the need for interoperability testing, and proposes a passive interoperability test method for the SSs to achieve and assure sensor data interoperability. To verify this test method, an interoperability test system for the PMU-based SSs was developed and presented. Interoperability test results of eight commercial PMU-based SSs are provided to show that the proposed interoperability test method works.

Effects of priming self-construals on self-evaluations: Cultural game player perspective.

This study examined the validity of situational view on culture-specific behaviours focusing on self-evaluation. Two experiments with American students as samples were conducted to examine whether priming their self-construals would affect individuals' self-evaluation. In Experiment 1, the participants' self-evaluation was compared across different conditions of primed self-contruals. In Experiment 2, the participants were split into 2 groups based on their initial default self-consturals and, the self-evaluations were compared across the 2 groups after priming self-contruals. The results demonstrated that although the participants' self-evaluation was initially in accord with their default self-construal, it changed into accord with the primed self-construals. The findings supported the proposed cultural game player view. Implications on situational view of self-evaluation are also discussed.

Determining Distinct Suicide Attempts From Recurrent Electronic Health Record Codes: Classification Study.

BACKGROUND: Prior suicide attempts are a relatively strong risk factor for future suicide attempts. There is growing interest in using longitudinal electronic health record (EHR) data to derive statistical risk prediction models for future suicide attempts and other suicidal behavior outcomes. However, model performance may be inflated by a largely unrecognized form of "data leakage" during model training: diagnostic codes for suicide attempt outcomes may refer to prior attempts that are also included in the model as predictors. OBJECTIVE: We aimed to develop an automated rule for determining when documented suicide attempt diagnostic codes identify distinct suicide attempt events. METHODS: From a large health care system's EHR, we randomly sampled suicide attempt codes for 300 patients with at least one pair of suicide attempt codes documented at least one but no more than 90 days apart. Supervised chart reviewers assigned the clinical settings (ie, emergency department [ED] versus non-ED), methods of suicide attempt, and intercode interval (number of days). The probability (or positive predictive value) that the second suicide attempt code in a given pair of codes referred to a distinct suicide attempt event from its preceding suicide attempt code was calculated by clinical setting, method, and intercode interval. RESULTS: Of 1015 code pairs reviewed, 835 (82.3%) were nonindependent (ie, the 2 codes referred to the same suicide attempt event). When the second code in a pair was documented in a clinical setting other than the ED, it represented a distinct suicide attempt 3.3% of the time. The more time elapsed between codes, the more likely the second code in a pair referred to a distinct suicide attempt event from its preceding code. Code pairs in which the second suicide attempt code was assigned in an ED at least 5 days after its preceding suicide attempt code had a positive predictive value of 0.90. CONCLUSIONS: EHR-based suicide risk prediction models that include International Classification of Diseases codes for prior suicide attempts as a predictor may be highly susceptible to bias due to data leakage in model training. We derived a simple rule to distinguish codes that reflect new, independent suicide attempts: suicide attempt codes documented in an ED setting at least 5 days after a preceding suicide attempt code can be confidently treated as new events in EHR-based suicide risk prediction models. This rule has the potential to minimize upward bias in model performance when prior suicide attempts are included as predictors in EHR-based suicide risk prediction models.

Increase of the indoor concentration of volatile organic compounds after the use of incense and scented candle in studio apartments determined using passive sampling.

Burning incenses and scented candles may provide harmful chemicals. Although many studies have evaluated volatile organic chemicals emitted by their use and related health risks, extension of our understanding for guiding appropriate use under various use conditions is necessary. In this study, emission characteristics of commercial incenses and scented candles were evaluated in a laboratory chamber using real-time measurement and the time-weighted average exposure concentrations of monoaromatic compounds and monoterpenes were assessed using passive samplers while volunteers living in a studio apartment use them. After burning incense, the average levels of benzene increased from 1.4 to 100 µg m-3. The presence of a wood core in commercial incense products was the main cause of high benzene emission by burning them although the increase in benzene was also influenced by factors such as the brand of the products, the number of incense sticks burned, the duration of each burning session, and ventilation period. Electrical warming of scented candles increased the levels of monoterpenes by factors of 16-30 on average. Considering the emission characteristics found in this study, exposure to benzene and monoterpenes could be mitigated by cautious use of those products in residential areas.

Validation of an ICD-code-based case definition for psychotic illness across three health systems.

Background and Hypothesis: Early detection of psychosis is critical for improving outcomes. Algorithms to predict or detect psychosis using electronic health record (EHR) data depend on the validity of the case definitions used, typically based on diagnostic codes. Data on the validity of psychosis-related diagnostic codes is limited. We evaluated the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for psychosis. Study Design: Using EHRs at three health systems, ICD codes comprising primary psychotic disorders and mood disorders with psychosis were grouped into five higher-order groups. 1,133 records were sampled for chart review using the full EHR. PPVs (the probability of chart-confirmed psychosis given ICD psychosis codes) were calculated across multiple treatment settings. Study Results: PPVs across all diagnostic groups and hospital systems exceeded 70%: Massachusetts General Brigham 0.72 [95% CI 0.68-0.77], Boston Children's Hospital 0.80 [0.75-0.84], and Boston Medical Center 0.83 [0.79-0.86]. Schizoaffective disorder PPVs were consistently the highest across sites (0.80-0.92) and major depressive disorder with psychosis were the most variable (0.57-0.79). To determine if the first documented code captured first-episode psychosis (FEP), we excluded cases with prior chart evidence of a diagnosis of or treatment for a psychotic illness, yielding substantially lower PPVs (0.08-0.62). Conclusions: We found that the first documented psychosis diagnostic code accurately captured true episodes of psychosis but was a poor index of FEP. These data have important implications for the development of risk prediction models designed to predict or detect undiagnosed psychosis.

Validation of an ICD-Code-Based Case Definition for Psychotic Illness Across Three Health Systems.

BACKGROUND AND HYPOTHESIS: Psychosis-associated diagnostic codes are increasingly being utilized as case definitions for electronic health record (EHR)-based algorithms to predict and detect psychosis. However, data on the validity of psychosis-related diagnostic codes is limited. We evaluated the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for psychosis. STUDY DESIGN: Using EHRs at 3 health systems, ICD codes comprising primary psychotic disorders and mood disorders with psychosis were grouped into 5 higher-order groups. 1133 records were sampled for chart review using the full EHR. PPVs (the probability of chart-confirmed psychosis given ICD psychosis codes) were calculated across multiple treatment settings. STUDY RESULTS: PPVs across all diagnostic groups and hospital systems exceeded 70%: Mass General Brigham 0.72 [95% CI 0.68-0.77], Boston Children's Hospital 0.80 [0.75-0.84], and Boston Medical Center 0.83 [0.79-0.86]. Schizoaffective disorder PPVs were consistently the highest across sites (0.80-0.92) and major depressive disorder with psychosis were the most variable (0.57-0.79). To determine if the first documented code captured first-episode psychosis (FEP), we excluded cases with prior chart evidence of a diagnosis of or treatment for a psychotic illness, yielding substantially lower PPVs (0.08-0.62). CONCLUSIONS: We found that the first documented psychosis diagnostic code accurately captured true episodes of psychosis but was a poor index of FEP. These data have important implications for the case definitions used in the development of risk prediction models designed to predict or detect undiagnosed psychosis.

Determination of terpene levels after the use of essential oil diffusers in vehicles and studio apartments using passive sampling.

The exposure levels of selected terpenes (limonene, α- and ß-pinenes, and γ-terpinene) emitted by essential oil diffusers in vehicles and studio apartments were assessed using a passive sampling method. A previously developed passive sampler composed of an expanded polytetrafluoroethylene membrane and adsorbent (ePTFE PS) was enlarged and made wearable. Before field deployment, the sampling performance of the modified ePTFE PS for selected terpenes was compared with that of active sampling in a lab-scale 5 m3 test chamber under constant exposure conditions, supporting that passive sampling provides reasonable estimates of the time-weighted exposure concentration. Fifty volunteers were recruited and asked to wear the ePTFE PS while using an essential oil diffuser inside their own vehicle while commuting and in their studio apartment while sleeping. Terpene levels without an essential oil diffuser were very low in vehicles and 47, 3.6, 1.6, and 0.62 µg m-3 for average concentrations of limonene, α- and ß-pinenes, and γ-terpinene in studio apartments, respectively, close to those reported in previous studies. The indoor concentrations of all selected terpenes in vehicles and studio apartments were elevated by the use of essential oil diffusers, especially in vehicles. The average concentration of limonene in vehicles after the use of essential oil diffusers was 11 µg m-3, which was greater than that before use by a factor of 30. Therefore, cautious usage of essential oil diffusers indoors where the volume is limited, such as a vehicle, is needed to reduce exposure to terpenes.

An efficient landmark model for prediction of suicide attempts in multiple clinical settings.

Growing evidence has shown that applying machine learning models to large clinical data sources may exceed clinician performance in suicide risk stratification. However, many existing prediction models either suffer from "temporal bias" (a bias that stems from using case-control sampling) or require training on all available patient visit data. Here, we adopt a "landmark model" framework that aligns with clinical practice for prediction of suicide-related behaviors (SRBs) using a large electronic health record database. Using the landmark approach, we developed models for SRB prediction (regularized Cox regression and random survival forest) that establish a time-point (e.g., clinical visit) from which predictions are made over user-specified prediction windows using historical information up to that point. We applied this approach to cohorts from three clinical settings: general outpatient, psychiatric emergency department, and psychiatric inpatients, for varying prediction windows and lengths of historical data. Models achieved high discriminative performance (area under the Receiver Operating Characteristic curve 0.74-0.93 for the Cox model) across different prediction windows and settings, even with relatively short periods of historical data. In short, we developed accurate, dynamic SRB risk prediction models with the landmark approach that reduce bias and enhance the reliability and portability of suicide risk prediction models.

Tetrazolium-Based Visually Indicating Bacteria Sensor for Colorimetric Detection of Point of Contamination.

Protective equipment for detecting bacterial contamination has been in high demand with increasing interest in public health and hygiene. Herein, a fiber-based visually indicating bacteria sensor (VIBS) embedded with iodonitrotetrazolium chloride is developed for the general purpose of detecting live bacteria, and its chromogenic effectiveness is investigated for Gram-negative Escherichia coli and Gram-positive Micrococcus luteus. The developed color intensity is measured by the light absorption coefficient to the scattering coefficient (K/S) based on the Kubelka-Munk equation, and the colorimetric sensitivities of different membranes are examined by calculating the limit of detection (LOD) and the limit of quantification (LOQ). The results demonstrate that the interactions between VIBS and bacteria depend on the wetting properties of membranes. A hydrophobic membrane shows excessive interactions at high concentrations of Gram-negative E. coli bacteria, whose cell membrane is lipophilic. The membrane blended with hydrophobic and hydrophilic polymers displays linear colorimetric responses for both Gram-negative and Gram-positive bacteria strains, demonstrating a reliable sensing capability in the range of the tested bacteria concentration. This study is significant in that explorative experimentations are performed to conceive a proof of concept of a fiber-based bacteria sensor, which is readily applicable in various fields where bacteria pose a threat.

A Methodology for Modeling Interoperability of Smart Sensors in Smart Grids.

Smart sensors in smart grids provide real-time data and status of bidirectional flows of energy for monitoring, protection, and control of grid operations to improve reliability and resilience. Smart sensor data interoperability is a major challenge for smart grids. This paper proposes a methodology for modeling interoperability of smart sensors in terms of interactions using labeled transition systems and finite state processes in order to quantitatively and automatically measure and assess the interoperability, identify and resolve interoperability issues, and improve interoperability. A generic interoperability model of synchronous message passing from a sender to a receiver is built based on the proposed methodology. A case study is provided to apply this methodology for modeling interoperability between the Institute of Electrical and Electronics Engineers C37.118 phasor measurement unit-based smart sensors and phasor data concentrators. The interoperability model can be used for the quantitative and automated measurement and assessment of the interoperability of phasor measurement unit-based smart sensors and phasor data concentrators to address interoperability issues. This methodology can also be applied to modeling interoperability of smart sensors based on other standard communication protocols in order to achieve and assure sensor data interoperability in smart grids.

The evolutionary trajectory of drosophilid walking.

Neural circuits must both execute the behavioral repertoire of individuals and account for behavioral variation across species. Understanding how this variation emerges over evolutionary time requires large-scale phylogenetic comparisons of behavioral repertoires. Here, we describe the evolution of walking in fruit flies by capturing high-resolution, unconstrained movement from 13 species and 15 strains of drosophilids. We find that walking can be captured in a universal behavior space, the structure of which is evolutionarily conserved. However, the occurrence of and transitions between specific movements have evolved rapidly, resulting in repeated convergent evolution in the temporal structure of locomotion. Moreover, a meta-analysis demonstrates that many behaviors evolve more rapidly than other traits. Thus, the architecture and physiology of locomotor circuits can execute precise individual movements in one species and simultaneously support rapid evolutionary changes in the temporal ordering of these modular elements across clades.

Effect of Public Empathy with Infection-Control Guidelines on Infection-Prevention Attitudes and Behaviors: Based on the Case of COVID-19.

Since the outbreak of the novel coronavirus disease (COVID-19), the government has provided infection-control guidelines to prevent the spread of the virus. The authors of this study examined the structure (causal relationship) of factors that influence public behavior toward COVID-19 and verified the effect of public empathy with infection-control guidelines in each structure. Data were collected using a self-administered questionnaire survey from 211 Korean adults. The results showed that (1) the perceived susceptibility and severity of economic damage had a positive effect on infection-prevention attitudes and infection-prevention attitudes had a positive effect on infection-prevention behaviors; (2) the perceived severity of economic damage had a positive effect on infection-prevention attitudes; and (3) public empathy with infection-control guidelines positively moderated the effect of the perceived severity of economic damage on infection-prevention behaviors and that of perceived susceptibility on infection-prevention attitudes. Accordingly, the authors of this study present the following three suggestions to prevent the spread of an infectious disease: engage in risk communication focused on a potential virus infection and cooperation, make multifaceted efforts to increase public empathy with infection-control guidelines, and implement measures to alleviate or reduce economic damage to the public in a viral pandemic.

Exposure to permethrin used as a home insecticide: A case study comparing model predictions and excretion of metabolites.

Pyrethroids have been widely used as an active ingredient in home insecticide products since the 1960 s. Although their occurrence in indoor environments has been studied, the contribution of home insecticide application to the aggregate exposure to pyrethroids is not well known. The objective of this study was to estimate the consumer exposure to permethrin, a representative pyrethroid, via the use of home insecticide spray during the summer season using biomonitoring and personal exposure modeling. Exposure to permethrin was assessed by analyzing its urinary metabolites, 3-phenoxybenzoic acid (3-PBA) and cis/trans-3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropan carboxylic acid (cis/trans-DCCA), for a group of consumers (n = 27). The levels of metabolites were also compared with those predicted by a screening exposure model considering personal exposure parameters. The levels of metabolites in 15 participants increased significantly (p < 0.05) with the application of home insecticide products, thereby suggesting that the heavy use of home insecticides during summer could be an important exposure route of permethrin in addition to other sources, such as food consumption. The total amount of excreted 3-PBA and cis/trans-DCCA was lower than the amount estimated by the exposure model for most participants by a factor of 0.9-861.0. These differences could be attributed to the rapid loss of permethrin after application, including sorption to indoor surfaces, reaction with indoor substances, individual biological variations, and ventilation during application. However, the screening exposure model used for the initial safety assessment of biocidal products generally performed well because it did not underestimate the personal exposure to permethrin during the application of home insecticide spray.

Impact of Social Support and Social Trust on Public Viral Risk Response: A COVID-19 Survey Study.

Public health has been under continuous threat worldwide in recent years. This study examined the impact of social support and social trust on the activities and efficacy of the public's risk response in the case of COVID-19. We conducted an online survey over eight days with 620 Korean adult participants. Data were analyzed using structural equation modelling and K-means cluster analysis. Our results showed that public support had a positive impact on response efficacy, while response efficacy had a positive impact on sanitation, distancing, and purchasing activities. In addition, social support positively moderated the impact of public and individual support on response efficacy, while response efficacy negatively moderated the impact on sanitation activities. These results suggest that, first, amid viral risk, governments should proactively supply tools and information for infection-prevention, and deliver messages that encourage and support infection-prevention activities among the public. Second, when viral risk occurs, governments, along with all other members of society, must engage in aggressive risk response measures. Third, there is a need for risk communication that further emphasizes the importance of personal sanitation activities in the face of viral risk.

Korean Consumers' Recognition of Risks Depending on the Provision of Safety Information for Chemical Products.

After the 2011 "Oxy accident" involving deaths from humidifier disinfectants, Korean consumers' anxiety about chemical products has risen. To provide timely, appropriate information to consumers, we must understand their risk recognition and explore methods of safety information provision. We investigated Korean consumers' level of risk perception for chemical products depending on the provision of safety information and other factors. We conducted an online survey for 10 days with 600 adult Korean consumer participants and analyzed seven factors: catastrophic potential, controllability, familiarity, fear, scientific knowledge, and risk for future generations. Our results showed that married women over 30 perceived chemical products as higher risk, but when information was provided on how to use products safely, catastrophic potential, controllability, fear, scientific knowledge, as well as risk perception, increased significantly. When only risk diagnosis information was provided, catastrophic potential, fear, and risk for future generations remained static, but familiarity had a negative effect (R^2 = 0.586). Age and scientific knowledge affected the recognition of risk when safe risk management methods were provided (R^2 = 0.587). Risk controllability did not have any effect on risk perception. These results suggest that providing information about avoiding or dealing with risks has a positive effect on consumers' risk perception.

Disinfection Treatments of Disposable Respirators Influencing the Bactericidal/Bacteria Removal Efficiency, Filtration Performance, and Structural Integrity.

In the outbreak of COVID-19, the extended wear of single-use, disposable respirators was inevitable due to limited supplies. As a respirator is front-line protection against particulate matter, including bioaerosol and droplets, a comprehensive understanding for the reuse strategy is needed. In this study, eight different disinfection methods commonly applied for the reuse of respirators were compared for their influence on the filtration and bactericidal/bacteria removal performance, with in-depth discussion on the cause of effects. Treatments including oven-dry, ultraviolet irradiation (UV), microwaving, laundering with and without detergent, and immersion in hypochlorite, isopropanol, and ethanol were performed to respirators. Immersion in ethanol or isopropanol was effective for inactivation and removal of bacteria, yet such a treatment significantly deteriorated the filtration efficiency in about 20-28%, dissipating the surface charges. Laundering, while effective in removing the attached bacteria, triggered physical damage, leading to a possible reduction of filtration performance. A short-term oven-dry, UV irradiation, and microwaving mostly preserved the filtration performance, yet the drawback lied in the incomplete bactericidal efficiency. This study would contribute to the public health and safety by providing scientific background on the effect of disinfection treatment methods for respirators.