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Eun Hyung Yoo,1 Hyo-Lim Hong,2 Eun Jin Kim2 1Department of Laboratory Medicine, Daegu Catholic University School of Medicine, Daegu, Korea; 2Department of Internal Medicine, Daegu Catholic University School of Medicine, Daegu, KoreaCorrespondence: Eun Jin Kim, Department of Internal Medicine, Daegu Catholic University School of Medicine, 33, Duryugongwon-ro 17gil, Namgu, Daegu, 42472, Korea, Tel +82-53-650-4274, Fax +82-53-650-4942, Email ejkim77@cu.ac.krPurpose: The prevalence of carbapenem-resistant Enterobacterales (CRE) is rapidly increasing worldwide. Patients in the intensive care unit (ICU) are susceptible to CRE infections, and the related mortality rate is increased. It is necessary to understand CRE strains and risk factors for CRE infection in the ICU, to facilitate development of effective prophylactic strategies and treatments for ICU patients.Patients and Methods: This observational study was conducted in a tertiary hospital between 2016 and 2021. The subjects were patients with CRE cultured from specimens obtained after ICU admission. Genotypes of strains of CRE and carbapenemase-producing Enterobacterales (CPE) were identified, CRE infection was distinguished from mere colonization, and the clinical course of these patients was investigated.Results: Among 327 CRE cases, 84 (25.7%) showed infection and 243 (74.3%) showed colonization. Of these patients, 138 (42.2%) died. The CRE strains were Klebsiella pneumoniae (253 cases, 77.4%), Enterobacter cloacae (44 cases, 13.5%), and Escherichia coli (15 cases, 4.6%). Among CRE cases, CPE was found in 249 (76.1%), including Klebsiella pneumoniae carbapenemase (KPC) in 164 (65.9%), and Guiana extended-spectrum (GES) in 64 (25.7%). A bedridden state, longer ICU stay, chronic kidney disease, malignancy, connective tissue disease, ICU admission for cardiac arrest, and CRE infection were associated with higher mortality, but cerebrovascular disease and ICU admission for trauma were associated with lower mortality. GES outbreak was caused by person-to-person transmission and was controlled through active surveillance.Conclusion: The frequency of K. pneumoniae and KPC was the highest, but E. cloacae and GES was characteristically high in this study. Active CRE surveillance can be helpful for controlling outbreak.Keywords: carbapenemase-producing Enterobacterales, genotypes, intensive care unit, Klebsiella pneumoniae carbapenemase, Guiana extended spectrum

Growing evidence suggests that ambient air pollution has adverse effects on mental health, yet our understanding of its unequal impact remains limited, especially in areas with historical redlining practices. This study investigates whether the impact of daily fluctuations in ambient air pollutant levels on emergency room (ER) visits for mental disorders (MDs) varies across neighborhoods affected by redlining. Furthermore, we explored how demographic characteristics and ambient temperature may modify the effects of air pollution. To assess the disproportional short-term effects of PM 2.5 , NO 2 , and O 3 on ER visits across redlining neighborhoods, we used a symmetric bidirectional case-crossover design with a conditional logistic regression model. We analyzed data from 2 million ER visits for MDs between 2005 and 2016 across 17 cities in New York State, where redlining policies were historically implemented. A stratified analysis was performed to examine potential effect modification by individuals' demographic characteristics (sex, age, and race/ethnicity) and ambient temperature. We found that both PM 2.5 and NO 2 were significantly associated with MD-related ER visits primarily in redlined neighborhoods. Per 10μgm -3 increase in daily PM 2.5 and per 10 ppb increase in NO 2 concentration were associated with 1.04 % (95 % Confidence Interval (CI): 0.57 %, 1.50 %) and 0.44 % (95 % CI: 0.21 %, 0.67 %) increase in MD-related ER visits in redlined neighborhoods, respectively. We also found significantly greater susceptibility among younger persons (below 18 years old) and adults aged 35-64 among residents in grade C or D, but not in A or B. Furthermore, we found that positive and statistically significant associations between increases in air pollutants (PM 2.5 and NO 2 ) and MD-related ER visits exist during medium temperatures (4.90 °C to 21.11 °C), but not in low or high temperature. Exposures to both PM 2.5 and NO 2 were significantly associated with MD-related ER visits, but these adverse effects were disproportionately pronounced in redlined neighborhoods., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: A number of studies based on young to middle aged adult and child samples have found that exposure to greenspace and bluespace can have a positive impact on mental health and well-being. However, there is limited research among older adults and the extant studies have provided mixed results. The present study was designed to examine how the association between these forms of exposure and depressive symptoms among older adults varies as a function of different spatially and temporally resolved exposure metrics., Methods: The sample consisted of 617 individuals (46.19% female) aged ≥ 60 years of age. Depressive symptoms were measured using the 10-item Center for Epidemiological Studies Depression Scale (CES-D). Individuals' greenspace exposure was quantified using spatially and temporally resolved metrics, including monthly and annual averaged satellite-derived normalized difference vegetation index (NDVI) across multiple buffer distances (250 m to 2,000 m) centered at participants' home address. We also quantified exposure to blue-greenspace from a highly detailed land use and land cover dataset. A multivariable logistic regression model assessed the association between greenspace and blue-greenspace exposure and depressive symptoms, adjusting for age, sex, income, education, marital status, current smoking, alcohol status, medical conditions, temperature, crime rate, population density, and per capita park area., Results: We found a significant association between exposures to greenspace and blue-greenspace and depressive symptoms (CES-D cutoff ≥ 4) among older adults. After adjusting for confounding variables, the odds of depressive symptoms were significantly decreased by an IQR increment in residential exposure to greenspace [odds ratio (OR) = 0.67; 95% confidence interval (95% CI), 0.49 ~ 0.91] and blue-greenspace (OR = 0.59; 95% CI, 0.41 ~ 0.84) measured nearby their home address (i.e., as close as 250 m). When stratified by household income level, the association was only significant among low-income individuals. We also found temporal variation in the association between depressive symptoms and monthly NDVI-based greenspace exposure, in which the odds of depressive symptoms were the lowest for greenspace in cold months (i.e., January, February, and March)., Conclusions: Our findings suggest that neighborhood greenspace may serve as a protective factor against depression among older adults, but the benefits may depend on the spatial and temporal context. More investigation is needed to replicate our findings on the spatial and temporal variations of greenspace exposure metrics and their effects on depressive symptoms., (© 2024. The Author(s).)

Background: As a complementary means to urban public transit systems, public bike-sharing provides a green and active mode of sustainable mobility, while reducing carbon-dioxide emissions and promoting health. There has been increasing interest in factors affecting bike-sharing usage, but little is known about the effect of ambient air pollution., Method: To assess the short-term impact of daily exposure to multiple air pollutants (PM 2.5 , PM 10 , NO 2 , and O 3 ) on the public bike-sharing system (PBS) usage in Seoul, South Korea (2018-2021), we applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM). The model was adjusted for day of the week, holiday, temperature, relative humidity, and long-term trend. We also conducted stratification analyses to examine the potential effect modification by age group, seasonality, and COVID-19., Results: We found that there was a negative association between daily ambient air pollution and the PBS usage level at a single lag day 1 (i.e., air quality a day before the event) across all four pollutants. Our results suggest that days with high levels of air pollutants (at 95th percentile) are associated with a 0.91% (0.86% to 0.96%) for PM 2.5 , 0.89% (0.85% to 0.94%) for PM 10 , 0.87% (0.82% to 0.91%) for O 3 , and 0.92% (0.87% to 0.98%) for NO 2 , reduction in cycling behavior in the next day compared to days with low levels of pollutants (at 25th percentile). No evidence of effect modification was found by seasonality, age nor the COVID-19 pandemic for any of the four pollutants., Conclusions: Our findings suggest that high concentrations of ambient air pollution are associated with decreased rates of PBS usage on the subsequent day regardless of the type of air pollutant measured., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The therapeutic application of cannabinoids has gained traction in recent years. Cannabinoids interact with the human endocannabinoid system in the skin. A large body of research indicates that cannabinoids could hold promise for the treatment of eczema, psoriasis, acne, pruritus, hair disorders, and skin cancer. However, most of the available data are at the preclinical stage. Comprehensive, large-scale, randomized, controlled clinical trials have not yet been fully conducted. In this article, we describe new findings in cannabinoid research and point out promising future research areas.

Background: Identification of high-risk areas of cancer, referred to as spatial clusters, can inform targeted policies for cancer control. Although cancer cluster detection could be affected by various geographic characteristics including sociodemographic and environmental factors which impacts could also vary over time, studies accounting for such influence remain limited. This study aims to assess the role of geographic characteristics in the spatial cluster detection for lung and stomach cancer over an extended period., Methods: We obtained sex-specific age-standardized incidence and mortality rates of lung and stomach cancer as well as geographic characteristics across 233 districts in South Korea for three five-year periods between 1999 and 2013. We classified geographic characteristics of each district into four categories: demography, socioeconomic status, behaviors, and physical environments. Specifically, we quantified physical environments using measures of greenness, concentrations of particulate matter and nitrogen dioxide, and air pollution emissions. Finally, we conducted cluster detection analyses using weighted normal spatial scan statistics with the residuals from multiple regression analyses performed with the four progressive sets of geographic attributes., Results: We found that the size of clusters reduced as we progressively adjusted for geographic covariates. Among the four categories, physical environments had the greatest impact on the reduction or disappearance of clusters particularly for lung cancer consistently over time. Whereas older population affected a decrease of lung cancer clusters in the early period, the contribution of education was large in the recent period. The impact was less clear in stomach cancer than lung cancer., Conclusion: Our findings highlight the importance of geographic characteristics in explaining the existing cancer clusters and identifying new clusters, which jointly provides practical guidance to cancer control., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Background: Most previous studies on air pollution exposure disparities among racial and ethnic groups in the US have been limited to residence-based exposure and have given little consideration to population mobility and spatial patterns of residences, workplaces, and air pollution. This study aimed to examine air pollution exposure disparities by racial and ethnic groups while explicitly accounting for both the work-related activity of the population and localized spatial patterns of residential segregation, clustering of workplaces, and variability of air pollutant concentration., Method: In the present study, we assessed population-level exposure to air pollution using tabulated residence and workplace addresses of formally employed workers from LEHD Origin-Destination Employment Statistics (LODES) data at the census tract level across eight Metropolitan Statistical Areas (MSAs). Combined with annual-averaged predictions for three air pollutants (PM 2.5 , NO 2 , O 3 ), we investigated racial and ethnic disparities in air pollution exposures at home and workplaces using pooled (i.e., across eight MSAs) and regional (i.e., with each MSA) data., Results: We found that non-White groups consistently had the highest levels of exposure to all three air pollutants, at both their residential and workplace locations. Narrower exposure disparities were found at workplaces than residences across all three air pollutants in the pooled estimates, due to substantially lower workplace segregation than residential segregation. We also observed that racial disparities in air pollution exposure and the effect of considering work-related activity in the exposure assessment varied by region, due to both the levels and patterns of segregation in the environments where people spend their time and the local heterogeneity of air pollutants., Conclusions: The results indicated that accounting for workplace activity illuminates important variation between home- and workplace-based air pollution exposure among racial and ethnic groups, especially in the case of NO 2 . Our findings suggest that consideration of both activity patterns and place-based exposure is important to improve our understanding of population-level air pollution exposure disparities, and consequently to health disparities that are closely linked to air pollution exposure., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The quantification of PM 2.5 concentrations solely stemming from both wildfire and prescribed burns (hereafter referred to as 'fire') is viable using the Community Multiscale Air Quality (CMAQ), although CMAQ outputs are subject to biases and uncertainties. To reduce the biases in CMAQ-based outputs, we propose a two-stage calibration strategy that improves the accuracy of CMAQ-based fire PM 2.5 estimates. First, we calibrated CMAQ-based non-fire PM 2.5 to ground PM 2.5 observations retrieved during non-fire days using an ensemble-based model. We estimated fire PM 2.5 concentrations in the second stage by multiplying the calibrated non-fire PM 2.5 obtained from the first stage by location- and time-specific conversion ratios. In a case study, we estimated fire PM 2.5 during the Washington 2016 fire season using the proposed calibration approach. The calibrated PM 2.5 better agreed with ground PM 2.5 observations with a 10-fold cross-validated (CV) R 2 of 0.79 compared to CMAQ-based PM 2.5 estimates with R 2 of 0.12. In the health effect analysis, we found significant associations between calibrated fire PM 2.5 and cardio-respiratory hospitalizations across the fire season: relative risk (RR) for cardiovascular disease = 1.074, 95% confidence interval (CI) = 1.021-1.130 in October; RR = 1.191, 95% CI = 1.099-1.291 in November; RR for respiratory disease = 1.078, 95% CI = 1.005-1.157 in October; RR = 1.153, 95% CI = 1.045-1.272 in November. However, the results were inconsistent when non-calibrated PM 2.5 was used in the analysis. We found that calibration affected health effect assessments in the present study, but further research is needed to confirm our findings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Despite a growing interest in the satellite derived estimation of ground-level PM 2.5 concentrations, modeling hourly PM 2.5 levels at high spatial resolution with complete coverage for a large study domain remains a challenge. The primary modeling challenges lie in the presence of missing data in aerosol optical depth (AOD) and the limited data resolution for a single-platformed satellite AOD product. To address these issues, we developed a gap-filling hybrid approach to estimate full coverage hourly ground-level PM 2.5 concentrations at a high spatial resolution of 1 km using multi-platformed and multi-scale satellite derived AOD products. Specifically, we filled the gaps and downscaled the multi-sourced AOD from Geostationary Ocean Color Imager (GOCI), Multi-Angle Implementation of Atmospheric Correction (MAIAC), and Modern-Era Retrospective Analysis for Research and Applications - version 2 (MERRA-2), using a hybrid data fusion approach. The fused hourly AOD with full coverage was then used for hourly PM 2.5 predictions at a high spatial resolution of 1 km. We demonstrated the application of the proposed approach and assessed its performance using the data collected from northeastern Asia from 2015 to 2019. Our fused hourly AOD data showed high accuracy with the mean absolute error of 0.14 and correlation coefficient of 0.94, in validation against Aerosol Robotic Network (AERONET) AOD. Our AOD-based PM 2.5 prediction model showed a good prediction accuracy with cross-validated R 2 of 0.85 and root mean squared error of 12.40 μg/m 3 , respectively. Given that the highly resolved PM 2.5 predictions captured both the temporal trend and the peak of PM 2.5 pollution scenarios, we concluded that the proposed hybrid approach can effectively combine multi-sourced satellite AOD and derive subsequent PM 2.5 distributions at high spatial and temporal resolutions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

The impacts of dynamic high-pressure (DHP) pretreatment and post-treatment (100 MPa) on the physicochemical and functional properties of whey protein isolate (WPI) aggregates formed by thermal treatment were investigated in this study. When WPI aggregates were formed by thermal treatment, the size of the aggregates formed with the DHP pretreated WPI was smaller than that of the aggregates formed with the original WPI. The size of the WPI aggregates formed by thermal treatment decreased with DHP post-treatment. The conformational parameters (ζ-potential, surface hydrophobicity, and intrinsic fluorescence intensity) of the WPI subjected to DHP pretreatment were not significantly influenced by thermal treatment. However, DHP post-treatment affected these parameters for the WPI aggregates formed during thermal treatment because of dissociation caused by intense shear and cavitation forces during DHP treatment. The emulsifying activity index (EAI) of the WPI aggregates slightly improved with DHP treatment, but its order had little effect on the magnitude of the EAI increase. DHP pretreatment or post-treatment can modulate the conformational structures and the physicochemical properties of protein aggregates.

Background: Urinary crystals are the most diverse forms of urine sediments. Reference images for typical urinary crystals are common, however, but images for interpreting atypical urinary crystals are very rare. The authors reviewed various forms and solubility tests of urine crystals to interpret atypical crystals found in clinical specimens., Methods: We reviewed textbooks on urinary crystals and articles published in PubMed. Some atypical crystals were confirmed using a solubility test., Results: The classification, shape, chemical structure, and solubility of the crystals were summarized. In the solubility test, some crystals showed different results; therefore, a new solubility test was proposed based on the literature review. We presented various types of calcium oxalates., Conclusions: These review articles will be helpful in the examination of atypical crystals found in clinical specimens. The solubility test requires additional studies to discriminate the inconsistent results between the authors., (© 2022 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC.)

Understanding the differences in the approaches used to assess household air pollution (HAP) is crucial for evaluating HAP-related health effects and interpreting the effectiveness of stove-fuel interventions. Our review aims to understand how exposure to HAP from solid fuels was measured in epidemiological studies in children under five. We conducted a search of PubMed, EMBASE, Cochrane Central Register of Controlled Trials, Global Health Library, Web of Science, and CINAHL to identify English-language research articles published between January 1, 2000 and April 30, 2022. Two researchers applied the inclusion and exclusion criteria independently. Study region, type of measurement, study design, health outcomes, and other key characteristics were extracted from each article and analyzed descriptively. Our search strategy yielded 2229 records, of which 185 articles were included. A large proportion was published between 2018 and 2022 (42.1%), applied a cross-sectional study design (47.6%), and took place in low- or lower middle-income countries. Most studies (130/185, 70.3%) assessed HAP using questionnaires/interviews, most frequently posing questions on cooking fuel type, followed by household ventilation and cooking location. Cooking frequency/duration and children's location while cooking was less commonly considered. About 28.6% (53/185) used monitors, but the application of personal portable samplers was limited (particulate matter [PM]: 12/40, 30.0%; carbon monoxide [CO]: 13/34, 38.2%). Few studies used biomarkers or modeling approaches to estimate HAP exposure among children under five. More studies that report household and behavioral characteristics and children's location while cooking, apply personal exposure samplers, and perform biomarker analysis are needed to advance our understandings of HAP exposure among infants and young children, who are particularly susceptible to HAP-related health effects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Despite the increasing availability and spatial granularity of individuals' time-activity (TA) data, the missing data problem, particularly long-term gaps, remains as a major limitation of TA data as a primary source of human mobility studies. In the present study, we propose a two-step imputation method to address the missing TA data with long-term gaps, based on both efficient representation of TA patterns and high regularity in TA data. The method consists of two steps: (1) the continuous bag-of-words word2vec model to convert daily TA sequences into a low-dimensional numerical representation to reduce complexity; (2) a multi-scale residual Convolutional Neural Network (CNN)-stacked Long Short-Term Memory (LSTM) model to capture multi-scale temporal dependencies across historical observations and to predict the missing TAs. We evaluated the performance of the proposed imputation method using the mobile phone-based TA data collected from 180 individuals in western New York, USA, from October 2016 to May 2017, with a 10-fold out-of-sample cross-validation method. We found that the proposed imputation method achieved excellent performance with 84% prediction accuracy, which led us to conclude that the proposed imputation method was successful at reconstructing the sequence, duration, and spatial extent of activities from incomplete TA data. We believe that the proposed imputation method can be applied to impute incomplete TA data with relatively long-term gaps with high accuracy.

Background: There is growing evidence that exposure to green space can impact mental health, but these effects may be context dependent. We hypothesized that associations between residential green space and mental health can be modified by social vulnerability., Method: We conducted an ecological cross-sectional analysis to evaluate the effects of green space exposure on mental disorder related emergency room (ER) visits in New York City at the level of census tract. To objectively represent green space exposure at the neighborhood scale, we calculated three green space exposure metrics, namely proximity to the nearest park, percentage of green space, and visibility of greenness. Using Bayesian hierarchical spatial Poisson regression models, we evaluated neighborhood social vulnerability as a potential modifier of greenness-mental disorder associations, while accounting for the spatially correlated structures., Results: We found significant associations between green space exposure (involving both proximity and visibility) and total ER visits for mental disorders in neighborhoods with high social vulnerability, but no significant associations in neighborhoods with low social vulnerability. We also identified specific neighborhoods with particularly high ER utilization for mental disorders., Conclusions: Our findings suggest that exposure to green space is associated with ER visits for mental disorders, but that neighborhood social vulnerability can modify this association. Future research is needed to confirm our finding with longitudinal designs at the level of individuals., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Due to the challenges in data collection, there are few studies examining how individuals' routine mobility patterns change when they experience influenza-like symptoms (ILS). In the present study, we aimed to assess the association between changes in routine mobility and ILS using mobile phone-based GPS traces and self-reported surveys from 1,155 participants over the 2016-2017 influenza season. We used a set of mobility metrics to capture individuals' routine mobility patterns and matched their weekly ILS survey responses. For a statistical analysis, we used a time-stratified case-crossover analysis and conducted a stratified analysis to examine if such associations are moderated by demographic and socioeconomic factors, such as age, gender, occupational status, neighborhood poverty and education levels, and work type. We found that statistically significant associations existed between reduced routine mobility patterns and the experience of ILS. Results also indicated that the association between reduced mobility and ILS was significant only for female and for participants with high socioeconomic status. Our findings offered an improved understanding of ILS-associated mobility changes at the individual level and suggest the potential of individual mobility data for influenza surveillance., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: Laboratory parameter abnormalities are commonly observed in COVID-19 patients; however, their clinical significance remains controversial. We assessed the prevalence, characteristics, and clinical impact of laboratory parameters in COVID-19 patients hospitalized in Daegu, Korea., Methods: We investigated the clinical and laboratory parameters of 1,952 COVID-19 patients on admission in nine hospitals in Daegu, Korea. The average patient age was 58.1 years, and 700 (35.9%) patients were men. The patients were classified into mild (N=1,612), moderate (N=294), and severe (N=46) disease groups based on clinical severity scores. We used chi-square test, multiple comparison analysis, and multinomial logistic regression to evaluate the correlation between laboratory parameters and disease severity., Results: Laboratory parameters on admission in the three disease groups were significantly different in terms of hematologic (Hb, Hct, white blood cell count, lymphocyte%, and platelet count), coagulation (prothrombin time and activated partial thromboplastin time), biochemical (albumin, aspartate aminotransferase, alanine aminotransferase, lactate, blood urea nitrogen, creatinine, and electrolytes), inflammatory (C-reactive protein and procalcitonin), cardiac (creatinine kinase MB isoenzyme and troponin I), and molecular virologic (Ct value of SARS-CoV-2 RdRP gene) parameters. Relative lymphopenia, prothrombin time prolongation, and hypoalbuminemia were significant indicators of COVID-19 severity. Patients with both hypoalbuminemia and lymphopenia had a higher risk of severe COVID-19., Conclusions: Laboratory parameter abnormalities on admission are common, are significantly associated with clinical severity, and can serve as independent predictors of COVID-19 severity. Monitoring the laboratory parameters, including albumin and lymphocyte count, is crucial for timely treatment of COVID-19.

Background: Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) started to spread in Daegu beginning at the end of February 2020. IgG and IgM antibodies against SARS-CoV-2 were measured in hospitalized patients with COVID-19 with moderate to severe symptoms to improve the understanding of antibody responses., Methods: We enrolled 312 patients with COVID-19 admitted to seven hospitals located in Daegu. Using serum (or plasma) samples from patients with polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infections, both IgG and IgM antibodies were measured using commercial enzyme-linked immunosorbent assay (R-FIND CO¬VID-19 ELISA, SG medical, Seoul, Korea)., Results: The median value from the initial diagnosis, confirmed by SARS-CoV-2 PCR, to the sampling date was 24 days (day 1 to 88). The total positive rate of IgG was 93.9% and the positive IgM rate was 39.4%, without considering the elapsed period after diagnosis. Positive IgG and IgM rates were highest at 100.0% and 59.0%, respectively, at 3 weeks (15 - 21 days). IgG showed a high positive rate of 79.3% even within 7 days after the initial diag-nosis of the disease and maintained a positive rate of 97.8% until after 8 weeks., Conclusions: Among hospitalized patients with COVID-19, IgG was detected from the beginning of the diagnosis and persisted for an extended time period.

Background: Organizing pneumonia (OP) can be diagnosed pathologically, and cryptogenic OP (COP) and secondary OP (SOP) have been classified by cause and particular underlying context. Because it is clinically difficult to differentiate between COP and SOP, this study investigated characteristics that could distinguish between COP and SOP., Methods: The medical records of patients who underwent lung biopsy for a diagnosis of OP at a single tertiary hospital from January 2016 to December 2018 were retrospectively reviewed., Results: Eighty-five patients had pathologically proven OP, including 16 diagnosed with COP and 69 diagnosed with SOP. The most common cause of SOP was infectious pneumonia, observed in 57 (82.6%) of the 69 patients, followed by cancer and radiation pneumonitis. The pathogens causing infectious pneumonia were identified in 45 (65.2%) patients. There were no differences in age, sex, and lung function between the COP and SOP groups. Median body mass index was significantly lower (P = 0.030), and median time from symptom onset to hospital admission significantly shorter (P = 0.006), in the SOP than in the COP group. Fever was more common in the SOP group (P = 0.024), and CURB 65, an index of pneumonia severity, tended to be higher in the SOP group (P = 0.017). Some laboratory results differed significantly between the two groups. Lymphocyte counts in bronchoalveolar lavage (BAL) fluid were significantly higher in the COP than in the SOP group (P = 0.012). Radiologic findings showed that effusion was more common in the SOP group (P = 0.036). There were no between-group differences in steroid use, 30 day and in-hospital mortality rates, and rates of OP outcomes and recurrences. Pneumonia recurrence rate was significantly higher in SOP patients who were than were not treated with steroids (P = 0.035)., Conclusions: Infection is the main cause of SOP. Symptom onset is more rapid in patients with SOP than with COP. Some blood and BAL fluid test results differed significantly in the COP and SOP groups. Pleural effusion was more common in the SOP group but there were no differences in clinical course. Recurrence in patients with SOP was more common in those who were than were not treated with steroids., (© 2021. The Author(s).)

Background: When Service Provision Assessment (SPA) surveys on primary health service delivery are combined with the nationally representative household survey-Demographic and Health Survey (DHS), they can provide key information on the access, utilization, and equity of health service availability in low- and middle-income countries. However, existing linkage methods have been established only at aggregate levels due to known limitations of the survey datasets., Methods: For the linkage of two data sets at a disaggregated level, we developed a geostatistical approach where SPA limitations are explicitly accounted for by identifying the sites where health facilities might be present but not included in SPA surveys. Using the knowledge gained from SPA surveys related to the contextual information around facilities and their spatial structure, we made an inference on the service environment of unsampled health facilities. The geostatistical linkage results on the availability of health service were validated using two criteria-prediction accuracy and classification error. We also assessed the effect of displacement of DHS clusters on the linkage results using simulation., Results: The performance evaluation of the geostatistical linkage method, demonstrated using information on the general service readiness of sampled health facilities in Tanzania, showed that the proposed methods exceeded the performance of the existing methods in terms of both prediction accuracy and classification error. We also found that the geostatistical linkage methods are more robust than existing methods with respect to the displacement of DHS clusters., Conclusions: The proposed geospatial approach minimizes the methodological issues and has potential to be used in various public health research applications where facility and population-based data need to be combined at fine spatial scale., (© 2021. The Author(s).)

Background: There is growing evidence suggesting that extreme temperatures have an impact on mental disorders. We aimed to explore the effect of extreme temperatures on emergency room (ER) visits for mental health disorders using 2.8 million records from New York State, USA (2009-2016), and to examine potential effect modifications by individuals' age, sex, and race/ethnicity through a stratified analysis to determine if certain populations are more susceptible., Method: To assess the short-term impact of daily average temperature on ER visits related to mental disorders, we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, as well as long-term and seasonal time trends. We also conducted a meta-analysis to pool the region-specific risk estimates and construct the overall cumulative exposure-response curves for all regions., Results: We found positive associations between short-term exposure to extreme heat (27.07 ∘ C) and increased ER visits for total mental disorders, as well as substance abuse, mood and anxiety disorders, schizophrenia, and dementia. We did not find any statistically significant difference among any subgroups of the population being more susceptible to extreme heat than any other., Conclusions: Our findings suggest that there is a positive association between short-term exposure to extreme heat and increased ER visits for total mental disorders. This extreme effect was also found across all sub-categories of mental disease, although further research is needed to confirm our finding for specific mental disorders, such as dementia, which accounted for less than 1% of the total mental disorders in this sample., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The response rate to treatment with trastuzumab (Tz), a recombinant humanized anti-HER2 monoclonal antibody, is only 12-34% despite demonstrated effectiveness on improving the survival of patients with HER2-positive breast cancers. Selenium has an antitumor effect against cancer cells and can play a cytoprotective role on normal cells. This study investigated the effect of selenium on HER2-positive breast cancer cells and the mechanism in relation to the response of the cells to Tz. HER2-positive breast cancer cell lines, SK-BR-3 as trastuzumab-sensitive cells, and JIMT-1 as Tz-resistant cells were treated with Tz and sodium selenite (selenite). Cell survival rates and expression of Her2, Akt, and autophagy-related proteins, including LC3B and beclin 1, in both cell lines 72 h after treatment were evaluated. Significant cell death was induced at different concentrations of selenite in both cell lines. A combined effect of selenite and Tz at 72 h was similar to or significantly greater than each drug alone. The expression of phosphorylated Akt (p-Akt) was decreased in JIMT-1 after combination treatment compared to that after only Tz treatment, while p-Akt expression was increased in SK-BR-3. The expression of beclin1 increased particularly in JIMT-1 after only Tz treatment and was downregulated by combination treatment. These results showed that combination of Tz and selenite had an antitumor effect in Tz-resistant breast cancer cells through downregulation of phosphorylated Akt and beclin1-related autophagy. Selenite might be a potent drug to treat Tz-resistant breast cancer by several mechanisms., Competing Interests: The authors have declared that no competing interests exist.

Relatively few studies investigated the effects of extreme temperatures (both heat and cold) on mental health (ICD-9: 290-319; ICD-10: F00-F99) and the potential effect modifications by individuals' age, sex, and race. We aimed to explore the effect of extreme temperatures of both heat and cold on the emergency room (ER) visits for mental health disorders, and conducted a stratified analysis to identify possible susceptible population in Erie and Niagara counties, NY, USA. To assess the short-term impacts of daily maximum temperature on ER visits related to mental disorders (2009-2015), we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, long-term time trend, and seasonality. We found that there were positive associations between short-term exposure to extreme ambient temperatures and increased ER visits for mental disorders, and the effects can vary by individual factors. We found heat effect (relative risk (RR) = 1.16; 95% confidence intervals (CI), 1.06-1.27) on exacerbated mental disorders became intense in the study region and subgroup of population (the elderly) being more susceptible to extreme heat than any other age group. For extreme cold, we found that there is a substantial delay effect of 14 days (RR = 1.25; 95% CI = 1.08-1.45), which is particularly burdensome to the age group of 50-64 years old and African-Americans. Our findings suggest that there is a positive association between short-term exposure to extreme ambient temperature (heat and cold) and increased ER visits for mental disorders, and the effects vary as a function of individual factors, such as age and race., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature.)

We evaluated the benefits of the MotionFree algorithm through phantom and patient studies. The various sizes of phantom and vacuum vials were linked to RPM moving with or without MotionFree application. A total of 600 patients were divided into six groups by breathing protocols and CT scanning time. Breathing protocols were applied as follows: (a) patients who underwent scanning without any breathing instructions; (b) patients who were instructed to hold their breath after expiration during CT scan; and (c) patients who were instructed to breathe naturally. The length of PET/CT misregistration was measured and we defined the misregistration when it exceeded 10 mm. In the phantom tests, the images produced by the MotionFree algorithm were observed to have excellent agreement with static images. There were significant differences in PET/CT misregistration according to CT scanning time and each breathing protocol. When applying the type (c) protocol, decreasing the CT scanning time significantly reduced the frequency and length of misregistrations ( p < 0.05). The MotionFree application is able to correct respiratory motion artifacts and to accurately quantify lesions. The shorter time of CT scan can reduce the frequency, and the natural breathing protocol also decreases the lengths of misregistrations.

Introduction and Hypothesis: The aim of this study was to report the long-term outcomes after sacrocolpopexy (SCP) with or without transobturator tape (TOT)., Methods: We conducted a planned secondary analysis of a prospective, observational study comparing urinary outcomes in women who underwent SCP with or without TOT based on the results of a prolapse-reduction stress test. Patients were enrolled between November 2008 and December 2011 and were followed up 5 years after surgery. The primary outcomes were 5-year success rates for stress urinary incontinence (SUI) and pelvic organ prolapse (POP) estimated using the Kaplan-Meier method. SUI success was defined as a negative cough stress test, no bothersome SUI symptoms, and no additional anti-incontinence surgery. POP success was defined as no vaginal bulge symptoms, no apical descent greater than one-third of the total vaginal length or anterior or posterior vaginal wall prolapse beyond the hymen, and no retreatment for prolapse., Results: Of 240 women enrolled, 175 (73%) completed 5 years of follow-up. The estimated SUI success rate was 91.1% in the TOT group and 56.5% in the no TOT group (difference, 34.6%; 95% confidence interval, 24.1 to 45.1). The estimated POP success rate was 90.0% in the TOT group and 92.9% in the no TOT group (difference, -2.9%; 95% confidence interval, -10.7 to 4.9)., Conclusions: The advantage of concomitant TOT for SUI after SCP that was seen at 2 years remained at 5 years. Long-term POP failure rates after SCP are low and not affected by concomitant TOT.

Satellite-derived aerosol optical depth (AOD) has been widely used to predict ground-level fine particulate matter (PM 2.5 ) concentrations, although its utility can be limited due to missing values. Despite recent attempts to address this issue by imputing missing satellite AOD values, the uncertainty associated with the AOD imputation and its impacts on PM 2.5 predictions have been understudied. To fill this gap, we developed a missing data imputation model for the AOD derived from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) and PM 2.5 prediction models using several machine learning methods. We also examined how the uncertainty associated with the imputed AOD and a choice of machine learning algorithm were propagated to PM 2.5 predictions. The application of the proposed imputation model to the data from New York State in the U.S. achieved a superior performance than those related studies, with a cross-validated R 2 of 0.94 and a Root Mean Square Error of 0.017. We also found that there was considerable uncertainty in PM 2.5 predictions associated with the use of imputed AOD values, although it was not as high as the uncertainty from the machine learning algorithms used in PM 2.5 prediction models. We concluded that the quantification of uncertainties for both AOD imputation and its propagation to AOD-based PM 2.5 prediction is necessary for accurate and reliable PM 2.5 predictions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The impact of individuals' mobility on the degree of error in estimates of exposure to ambient PM2.5 concentrations is increasingly reported in the literature. However, the degree to which accounting for mobility reduces error likely varies as a function of two related factors-individuals' routine travel patterns and the local variations of air pollution fields. We investigated whether individuals' routine travel patterns moderate the impact of mobility on individual long-term exposure assessment. Here, we have used real-world time-activity data collected from 2013 participants in Erie/Niagara counties, New York, USA, matched with daily PM2.5 predictions obtained from two spatial exposure models. We further examined the role of the spatiotemporal representation of ambient PM2.5 as a second moderator in the relationship between an individual's mobility and the exposure measurement error using a random effect model. We found that the effect of mobility on the long-term exposure estimates was significant, but that this effect was modified by individuals' routine travel patterns. Further, this effect modification was pronounced when the local variations of ambient PM2.5 concentrations were captured from multiple sources of air pollution data ('a multi-sourced exposure model'). In contrast, the mobility effect and its modification were not detected when ambient PM2.5 concentration was estimated solely from sparse monitoring data ('a single-sourced exposure model'). This study showed that there was a significant association between individuals' mobility and the long-term exposure measurement error. However, the effect could be modified by individuals' routine travel patterns and the error-prone representation of spatiotemporal variability of PM2.5.

Predicting spatial behaviors of an individual (e.g., frequent visits to specific locations) is important to improve our understanding of the complexity of human mobility patterns, and to capture anomalous behaviors in an individual's spatial movements, which can be particularly useful in situations such as those induced by the COVID-19 pandemic. We propose a system called Deep Spatio-Temporal Predictor (DST-Predict), that can predict the future visit frequency of an individual based on one's past mobility behaviour patterns using GPS trace data collected from mobile phones. Predicting such spatial behavior is challenging, primarily because individuals' patterns of location visits for each individual consists of both systematic and random components, which vary across the spatial and temporal scales of analysis. To address these issues, we propose a novel multi-view sequence-to-sequence model that uses Convolutional Long-short term memory (ConvLSTM) where the past history of frequent visit patterns features is used to predict individuals' future visit patterns in a multi-step manner. Using the GPS survey data obtained from 1,464 participants in western New York, US, we demonstrated that the proposed system is capable of predicting individuals' frequency of visits to common places in an urban setting, with high accuracy.

Background: Coronavirus disease 2019 (COVID-19) is a highly contagious disease that causes respiratory failure. Tracheostomy is an essential procedure in critically ill COVID-19 patients; however, it is an aerosol-generating technique and thus carries the risk of infection transmission. We report our experience with percutaneous tracheostomy and its safety in a real medical setting., Methods: During the COVID-19 outbreak, 13 critically ill patients were admitted to the intensive care unit (ICU) at Daegu Catholic University Medical Center between February 24 and April 30, 2020. Seven of these patients underwent percutaneous tracheostomy using Ciaglia Blue Rhino. The medical environment, percutaneous tracheostomy method, and COVID-19 reverse transcriptase-polymerase chain reaction (RT-PCR) results were retrospectively reviewed. After treatment, the COVID-19 infection status of healthcare personnel was investigated by RT-PCR., Results: The ICU contained negative pressure cohort areas and isolation rooms, and healthcare personnel wore a powered air-purifying respirator system. We performed seven cases of percutaneous tracheostomy in the same way as in patients without COVID-19. Five patients (71.4%) tested positive for COVID-19 by RT-PCR at the time of tracheostomy. The median cycle threshold value for the RNA-dependent RNA polymerase was 30.60 (interquartile range [IQR], 25.50-36.56) in the upper respiratory tract and 35.04 (IQR, 28.40-36.74) in the lower respiratory tract. All healthcare personnel tested negative for COVID-19 by RT-PCR., Conclusions: Percutaneous tracheostomy was performed with conventional methods in the negative pressure cohort area. It was safe to perform percutaneous tracheostomy in an environment of COVID-19 infection.

Background: Based on the metabolic effect of exogenous ATPase inhibitory factor 1 (IF1) on glucose metabolism, we tested whether IF1 treatment is effective in ameliorating weight gain and whether its effects are sex specific., Methods: HFD-fed C57BL/6 mice were treated with IF1 (5 mg/kg body weight, injected intraperitoneally). The underlying mechanisms of effect of IF1 on body weight were investigated in vitro and in vivo. Associations between genotypes of IF1 and obesity and relevant phenotype were further tested at the population level., Results: Chronic treatment with IF1 significantly decreased body weight gain by regulating food intake of HFD-fed male mice. IF1 activated the AKT/mTORC pathway and modulated the expression of appetite genes in the hypothalamus of HFD-fed male mice and its effect was confirmed in hypothalamic cell lines as well as hypothalamic primary cells. This required the interaction of IF1 with β-F1-ATPase on the plasma membrane of hypothalamic cells, which led to an increase in extracellular ATP production. In addition, IF1 treatment showed sympathetic nerve activation as measured by serum norepinephrine levels and UCP-1 expression in the subcutaneous fat of HFD-fed male mice. Notably, administration of recombinant IF1 to HFD-fed ovariectomized female mice showed remarkable reductions in food intake as well as body weight, which was not observed in wild-type 5-week female mice. Lastly, sex-specific genotype associations of IF1 with obesity prevalence and metabolic traits were demonstrated at the population level in humans. IF1 genetic variant (rs3767303) was significantly associated with lower prevalence of obesity and lower levels of body mass index, waist circumference, hemoglobin A 1c , and glucose response area only in male participants., Conclusion: IF1 is involved in weight regulation by controlling food intake and potentially sympathetic nerve activation in a sex-specific manner., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Despite their increasing popularity in human mobility studies, few studies have investigated the geo-spatial quality of GPS-enabled mobile phone data in which phone location is determined by special queries designed to collect location data with predetermined sampling intervals (hereafter "active mobile phone data"). We focus on two key issues in active mobile phone data-systematic gaps in tracking records and positioning uncertainty-and investigate their effects on human mobility pattern analyses. To address gaps in records, we develop an imputation strategy that utilizes local environment information, such as parcel boundaries, and recording time intervals. We evaluate the performance of the proposed imputation strategy by comparing raw versus imputed data with participants' online survey responses. The results indicate that imputed data are superior to raw data in identifying individuals' frequently visited places on a weekly basis. To assess the location accuracy of active mobile phone data, we investigate the spatial and temporal patterns of the positional uncertainty of each record and examine via Monte Carlo simulation how inaccurate location information might affect human mobility pattern indicators. Results suggest that the level of uncertainty varies as a function of time of day and the type of land use at which the position was determined, both of which are closely related to the location technology used to determine the location. Our study highlights the importance of understanding and addressing limitations of mobile phone derived positioning data prior to their use in human mobility studies.

Since arginase has been shown to compete with nitric oxide (NO) synthase, emerging evidence has reported that arginase inhibition improves obesity by increasing NO production. Semen cuscutae (SC), which is a well-known Chinese medicine, has multiple biological functions such as anti-oxidant function and immune regulation. In this study, we investigated whether the SC as a natural arginase inhibitor influences hepatic lipid abnormalities and whole-body adiposity in high-fat diet (HFD)-induced obese mice. The lipid accumulation was significantly reduced by SC treatment in oleic acid-induced hepatic steatosis in vitro. Additionally, SC supplementation substantially lowered HFD-induced increases in arginase activity and weights of liver and visceral fat tissue, while increasing hepatic NO. Furthermore, elevated mRNA expressions of sterol regulatory element-binding transcription factor 1 (SREBP-1c), fatty-acid synthase (FAS), peroxisome proliferator-activated receptor-gamma (PPAR-γ)1, and PPAR-γ2 in HFD-fed mice were significantly attenuated by SC supplementation. Taken together, SC, as a novel natural arginase inhibitor, showed anti-obesity properties by modulating hepatic arginase and NO production and metabolic pathways related to hepatic triglyceride (TG) metabolism.

ATPase inhibitory factor 1 (IF1) is an ATP synthase-interacting protein that suppresses the hydrolysis activity of ATP synthase. In this study, we observed that the expression of IF1 was up-regulated in response to electrical pulse stimulation of skeletal muscle cells and in exercized mice and healthy men. IF1 stimulates glucose uptake via AMPK in skeletal muscle cells and primary cultured myoblasts. Reactive oxygen species and Rac family small GTPase 1 (Rac1) function in the upstream and downstream of AMPK, respectively, in IF1-mediated glucose uptake. In diabetic animal models, the administration of recombinant IF1 improved glucose tolerance and down-regulated blood glucose level. In addition, IF1 inhibits ATP hydrolysis by β-F1-ATPase in plasma membrane, thereby increasing extracellular ATP and activating the protein kinase B (Akt) pathway, ultimately leading to glucose uptake. Thus, we suggest that IF1 is a novel myokine and propose a mechanism by which AMPK and Akt contribute independently to IF1-mediated improvement of glucose tolerance impairment. These results demonstrate the importance of IF1 as a potential antidiabetic agent.-Lee, H. J., Moon, J., Chung, I., Chung, J. H., Park, C., Lee, J. O., Han, J. A., Kang, M. J., Yoo, E. H., Kwak, S.-Y., Jo, G., Park, W., Park, J., Kim, K. M., Lim, S., Ngoei, K. R. W., Ling, N. X. Y., Oakhill, J. S., Galic, S., Murray-Segal, L., Kemp, B. E., Mantzoros, C. S., Krauss, R. M., Shin, M.-J., Kim, H. S. ATP synthase inhibitory factor 1 (IF1), a novel myokine, regulates glucose metabolism by AMPK and Akt dual pathways.

Wildland fire is a major emission source of fine particulate matter (PM 2.5 ), which has serious adverse health effects. Most fire-related health studies have estimated human exposures to PM 2.5 using ground observations, which have limited spatial/temporal coverage and could not separate PM 2.5 emanating from wildland fires from other sources. The Community Multiscale Air Quality (CMAQ) model has the potential to fill the gaps left by ground observations and estimate wildland fire-specific PM 2.5 concentrations, although the issues around systematic bias in CMAQ models remain to be resolved. To address these problems, we developed a two-step calibration strategy under the consideration of prediction uncertainties. In a case study of the eastern U.S. in 2014, we evaluated the calibration performance using three cross-validation methods, which consistently indicated that the prediction accuracy was improved with an R 2 of 0.47-0.64. In a health impact study based on the wildland fire-specific PM 2.5 predictions, we identified regions with excess respiratory hospital admissions due to wildland fire events and quantified the estimation uncertainty propagated from multiple components in health impact function. We concluded that the proposed calibration strategy could provide reliable wildland fire-specific PM 2.5 predictions and health burden estimates to support policy development for reducing fire-related risks.

Background: Indoor air pollution, including fine particulate matter (PM 2.5 ) and carbon monoxide (CO), is a major risk factor for pneumonia and other respiratory diseases. Biomass-burning cookstoves are major contributors to PM 2.5 and CO concentrations. However, high concentrations of PM 2.5 (> 1000 μg/m 3 ) have been observed in homes in Dhaka, Bangladesh that do not burn biomass. We described dispersion of PM 2.5 and CO from biomass burning into nearby homes in a low-income urban area of Dhaka, Bangladesh., Methods: We recruited 10 clusters of homes, each with one biomass-burning (index) home, and 3-4 neighboring homes that used cleaner fuels with no other major sources of PM 2.5 or CO. We administered a questionnaire and recorded physical features of all homes. Over 24 h, we recorded PM 2.5 and CO concentrations inside each home, near each stove, and outside one neighbor home per cluster. During 8 of these 24 h, we conducted observations for pollutant-generating activities such as cooking. For each monitor, we calculated geometric mean PM 2.5 concentrations at 5-6 am (baseline), during biomass burning times, during non-cooking times, and over 24 h. We used linear regressions to describe associations between monitor location and PM 2.5 and CO concentrations., Results: We recruited a total of 44 homes across the 10 clusters. Geometric mean PM 2.5 and CO concentrations for all monitors were lowest at baseline and highest during biomass burning. During biomass burning, linear regression showed a decreasing trend of geometric mean PM 2.5 and CO concentrations from the biomass stove (326.3 μg/m 3 , 12.3 ppm), to index home (322.7 μg/m 3 , 11.2 ppm), neighbor homes sharing a wall with the index home (278.4 μg/m 3 , 3.6 ppm), outdoors (154.2 μg/m 3 , 0.7 ppm), then neighbor homes that do not share a wall with the index home (83.1 μg/m 3 ,0.2 ppm) (p = 0.03 for PM 2.5 , p = 0.006 for CO)., Conclusion: Biomass burning in one home can be a source of indoor air pollution for several homes. The impact of biomass burning on PM 2.5 or CO is greatest in homes that share a wall with the biomass-burning home. Eliminating biomass burning in one home may improve air quality for several households in a community.

Objective: Women with pelvic floor disorders and urinary incontinence (UI) are at an increased risk of sexual dysfunction. The purpose of this study was to investigate the effect of surgery for UI on sexual function., Methods: We retrospectively reviewed the charts of 82 women who underwent mid-urethral transobturator tape (TOT) surgery between March 2010 and December 2014. The Pelvic Floor Distress Inventory-20 (PFDI-20) and the Pelvic Organ Prolapse/Urinary Incontinence Sexual Function Questionnaire-12 (PISQ-12) were administered pre- and postoperatively., Results: We observed a significant increase in the total postoperative PISQ-12 scores compared to the preoperative scores (from 27.1±7.3 to 30.5±6.8, P <0.001). Improved sexual function was confirmed in the physical (13.3±4.5 vs. 15.8±3.5, P <0.001) and partner-related domains (6.7±2.6 vs. 7.4±2.4, P =0.001). Coital incontinence and preoperative urinary distress inventory score were significant factors influencing postoperative sexual function in women undergoing TOT surgery for UI after adjusting for age, body mass index, menopause, and preoperative PISQ-12 score in multivariate regression analysis., Conclusion: TOT surgery for UI correction resulted in significant improvement in sexual function., Competing Interests: Conflict of Interest: No potential conflict of interest relevant to this article was reported.

Time-location data collected from location-sensing technologies have the potential to advance our understanding of human mobility. Existing human activity studies tend to ignore a critical issue in data collection-the time period for which the activity data will be collected. Our study investigated this significant gap in the literature on temporal aspects of human mobility behavior-how many days constitute a period long enough to capture individuals' highly organized activity episodes and how they vary among individuals with heterogeneous demographic and social-economic characteristics. To determine a minimum number of days to capture individuals' highly organized activity episodes in activity space, we examined a distribution of Kullback-Leibler divergence indexes. To evaluate the differences in the minimal number of observation days per subgroup whose demographic and economic characteristics are heterogenous, we used a Bayesian profile regression model. Our study showed that the estimated minimum number of days required to capture routine activity patterns was 13.5 days with a standard deviation of 6.64. We found that participant's age, employment status, size of household, and accessibility to downtown, food, and physical activity, as well as economic status of residential environment, are important factors that affect temporal aspects of mobility behavior.

Objectives: To investigate the rate of postoperative urinary retention (POUR) and identify the risk factors for this complication in women who underwent transvaginal uterosacral suspension surgery., Methods: A retrospective chart review was conducted for 75 women who underwent transvaginal uterosacral suspension surgery with vaginal hysterectomy, repair of cystocele, and levator myorrhaphy with/without transobturator anti-incontinence surgery. POUR was defined as a need for continuous intermittent catheterization on the third day subsequent to removal of the urethral indwelling catheter., Results: Acute POUR was reported in 18 women (24.0%). Thirty-six of the 75 patients (48.0%) had undergone anti-incontinence surgery. Crude analysis revealed significant association between the following variables and the risk of POUR: hypertension, the lower average flow rate in the pressure-flow study (PFS), greater post-void residual (PVR) urine volume in PFS, and PVR >30% of the total bladder capacity (TBC) in PFS. In the logistic regression analysis, PVR >30% of the TBC in PFS was identified as the only significant predictor of POUR (odds ratio, 15.4; 95% confidence interval, 2.5-90.9; P = 0.003)., Conclusions: The PVR >30% of the TBC in PFS was identified as the only predictive factor of acute POUR in women who underwent transvaginal uterosacral suspension surgery.

Objectives: To improve public health surveillance and response by using spatial optimization., Methods: We identified cases of suspected nonfatal opioid overdose events in which naloxone was administered from April 2013 through December 2016 treated by the city of Pittsburgh, Pennsylvania, Bureau of Emergency Medical Services. We used spatial modeling to identify areas hardest hit to spatially optimize naloxone distribution among pharmacies in Pittsburgh., Results: We identified 3182 opioid overdose events with our classification approach, which generated spatial patterns of opioid overdoses within Pittsburgh. We then used overdose location to spatially optimize accessibility to naloxone via pharmacies in the city. Only 24 pharmacies offered naloxone at the time, and only 3 matched with our optimized solution., Conclusions: Our methodology rapidly identified communities hardest hit by the opioid epidemic with standard public health data. Naloxone accessibility can be optimized with established location-allocation approaches. Public Health Implications. Our methodology can be easily implemented by public health departments for automated surveillance of the opioid epidemic and has the flexibility to optimize a variety of intervention strategies.

We used the Community Multiscale Air Quality (CMAQ) simulation model to predict daily average of fine particulate matter (PM 2.5 ) concentrations. The primary focus of our study was to investigate the sensitivity of CMAQ prediction accuracy associated with the horizontal grid resolutions and assess its impact on human health studies. To illustrate our point we ran CMAQ model at 4 km and 12 km resolutions over New York State for the year 2011, and systematically assessed the differences between two modeled PM 2.5 concentrations. Model performance was evaluated against PM 2.5 measured values at monitoring stations. The results indicated that simulations at both 4 km and 12 km resolutions reproduced measured PM 2.5 values with fractional error (54.41% for 4 km and 52.28% for 12 km) that are within the recommend performance criteria except for summer seasons and rural areas. Additionally, model results at 12 km compared to 4 km resolution generally performed better and had substantially lower computational burden. In our health impact assessment study, we found that estimated adverse health outcomes associated with PM 2.5 exposure derived from the two CMAQ models were compatible, especially in rural areas. Based on our findings, we conclude that the CMAQ simulation at 12 km resolution with further calibration and/or downscaling is a viable option than 4 km simulation to estimate small-scale within-city variations of air pollution concentrations., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: Air pollutants have been associated with various adverse health effects, including increased rates of hospital admissions and emergency room visits. Although numerous time-series studies and case-crossover studies have estimated associations between day-to-day variation in pollutant levels and mortality/morbidity records, studies on geographic variations in emergency department use and the spatial effects in their associations with air pollution exposure are rare., Methods: We focused on the elderly who visited emergency room for cardiovascular related disease (CVD) in 2011. Using spatially and temporally resolved multi-pollutant exposures, we investigated the effect of short-term exposures to ambient air pollution on emergency department utilization. We developed two statistical models with and without spatial random effects within a hierarchical Bayesian framework to capture the spatial heterogeneity and spatial autocorrelation remaining in emergency department utilization., Results: Although the cardiovascular effect of spatially homogeneous pollutants, such as PM2.5 and ozone, was unchanged, we found the cardiovascular effect of NO[Formula: see text] was pronounced after accounting for the spatially correlated structure in emergency department utilization. We also identified areas with high ED utilization for CVD among the elderly and assessed the uncertainty associated with risk estimates., Conclusions: We assessed the short-term effect of multi-pollutants on cardiovascular risk of the elderly and demonstrated the use of community multiscale air quality model-derived spatially and temporally resolved multi-pollutant exposures to an epidemiological study. Our results indicate that NO[Formula: see text] was significantly associated with the elevated ED utilization for CVD among the elderly.

Objective: To investigate the prevalence, risk factors of overactive bladder (OAB) and the factors affecting the severity of OAB symptoms., Methods: A total 822 interviews with women aged 18-80 years who visited public health centers were conducted between April 2014 and April 2015. The questionnaire was composed of 16 questions about urinary symptoms, 14 questions about self-treatment and the use of complementary and alternative medicine, and 21 questions about socio-demographic characteristics. The diagnostic criterion for OAB is a total OAB symptom score of 3 and more, with an urgency score of 2 or more. To know the risk factors and factors affecting the severity of OAB, the multivariate logistic regression analysis was performed., Results: One hundred fifty-seven participants (19.3%) were diagnosed with OAB, of whom 10.7%, 8.1%, and 0.7% had mild, moderate, and severe OAB symptoms, respectively. In addition, the prevalence of OAB increased with age. Among all the participants, 39.1% had stress incontinence, among them 32.7% had OAB as well. The significant risk factors of OAB were identified as age, current smoking, hyperlipidemia, cardiovascular and renal disease, whereas, the factors affecting the severity of OAB were age, current smoking, and hyperlipidemia., Conclusion: Those who have risk factors and factors affecting severity of OAB should be educated to increase OAB awareness and act of urinary health promotion., Competing Interests: Conflict of interest: No potential conflict of interest relevant to this article was reported.

Background: Recently, despite the high prevalence of fatigue in patients, there is a lack of research on the quality of life (QoL) in unexplained fatigue patients, indicating that they are not properly diagnosed and treated. The aim of this study was to compare fatigue severity and QoL between patients with explained and unexplained fatigue., Methods: The study consisted of 200 Korean adults who complained of fatigue without underlying disease. Fatigue Severity Scale, Short Form Health Survey-36 version 2 (SF-36v2), and Beck Depression Inventory-II (BDI-II) self-questionnaires were administered. Participants were dichotomized to two groups, namely, patients with unexplained or explained fatigue, sorted according to laboratory examination results. The chi-square test, t-test, and Wilcoxon rank-sum test were used, and analysis of covariance was calculated after adjusting for age, sex, body mass index, smoking status, and physical component summary (PCS) of SF-36v2 or BDI-II., Results: PCS of SF-36v2 between the two groups showed significant difference. Compared to patients with explained fatigue, those with unexplained fatigue showed lower physical component scores of QoL., Conclusion: QoL of patients with unexplained fatigue could largely diminish than those with explained fatigue. The primary clinician should be aware of poor QoL in patients with unexplained fatigue to identify who is in need of more attention and intervention.

Wedding mobile phone sensor technology and human spatial behaviour has great potential. The ubiquity of Global Positioning Systems (GPS) technology has made gathering data about human mobility simpler, more precise, and with higher fidelity, providing minute-by-minute records of the locations of cohorts from dozens of participants. While this data provides a strong basis for Geographic Information Science research, it also constitutes an invasion of the participants' privacy and can provide more information than researchers require to answer their questions. As an ethical and practical consideration, researchers should gather only as much data as they need. In this paper, we take three weeks of GPS traces from over a hundred student participants in mobile phone-based tracking studies and show that fewer than 14 days of data is necessary to establish complete activity spaces. We define 'complete' as the point at which marginal information gains become negligible according to a pairwise temporal analysis of the Kullback-Leibler (KL) divergence of the spatial (bivariate) histogram through time. For the fixed level of information difference, observable in the data, impacts due to individual variability, population composition, and spatial resolution are evident. However, all populations at each level of resolution examined in the paper demonstrated convergence to low divergence levels occurred within a matter of days, and to negligible information gain in less than two weeks. The methods described in the paper represent a novel metric useful to understand the interaction between measurements and information in human mobility., Competing Interests: Disclosure statement No potential conflict of interest was reported by the authors.

Myelofibrosis (MF) is often accompanied by chronic myeloid leukemia, hairy cell leukemia, or certain primary myeloproliferative neoplasms, but is rarely associated with lymphoid neoplasms. We herein describe a case of intravascular large B-cell lymphoma (IVLBCL) with MF. IVLBCL is a rare, aggressive type of extranodal B-cell lymphoma, defined by proliferation of lymphomatous cells within small-to medium-sized vessels. A 60-year-old woman was admitted to the hospital with anemia, thrombocytopenia and fever. Bone marrow biopsy findings included trilineage hematopoiesis, increased numbers of immature cells, markedly abnormal and enlarged megakaryocytes, and diffuse fibrosis in multiple focal areas throughout the entire bone marrow space. When the patient was first hospitalized, hepatosplenomegaly was not present. Although initially considered during differential diagnosis, an aggressive lymphoma could not be diagnosed prior to colonoscopy, which was conducted 4 weeks after admission. A biopsy of the terminal ileum revealed IVLBCL with cells with atypical nuclei. Immunophenotyping of the atypical large cells yielded a positive result for CD79a and negative results for terminal deoxynucleotidyl transferase, myeloperoxidase, CD3, CD10, CD20, B-cell lymphoma (Bcl)-2, Bcl-6 and cytomegalovirus. The patient was diagnosed with IVLBCL complicated by MF. This case may serve as a reminder that IVLBCL may be the cause of secondary MF.

Objective: To determine whether late preterm twin neonates have a more favorable perinatal outcome than singleton late preterm neonates., Methods: We studied 401 late preterm births between 34+0 and 36+6 weeks of gestation, from January 2011 to December 2014 in our institution. We compared the maternal and neonatal characteristics and perinatal outcomes between singleton and twin pregnancies. Perinatal outcomes included Apgar score, admission to the neonatal intensive care unit (NICU) or special care nursery, duration of NICU stay, and the rate of composite morbidity (antibiotic use, hypoglycemia, hypocalcemia, hyperbilirubinemia requiring phototherapy, respiratory support, and respiratory distress syndrome)., Results: A total of 289 neonates were in the singleton group and 112 in the twin group. The twin group showed smaller mean birth weight despite of longer gestational age at delivery. In addition, there were significant differences in the indication of delivery and cesarean section rate between the 2 groups. Overall, the risk of composite morbidity was similar between 2 groups (odds ratio, 1.4; 95% confidence interval, 0.8 to 2.4)., Conclusion: Our findings suggest that late preterm twins do not show a more favorable outcome than singleton late preterm births., Competing Interests: Conflict of interest: No potential conflict of interest relevant to this article was reported.

Background: Tenofovir disoproxil fumarate (TDF) is a potent nucleotide analogue recommended as first-line monotherapy for chronic hepatitis B (CHB). We investigated the clinical response to TDF monotherapy in Korean CHB patients., Methods: A total of 90 CHB patients [55 hepatitis B e antigen (HBeAg)-positive and 35 HBeAg-negative] who received TDF monotherapy for >2year, were enrolled. Quantitative hepatitis B surface antigen (qHBsAg) levels, serum alanine aminotransferase (ALT), HBeAg, anti-HBe and HBV DNA levels were measured during treatment. Virologic response (VR) was defined as undetectable HBV DNA level., Results: The cumulative incidences of complete virologic response (CVR) were 75.6% and 89.9% at months 12 and 24, respectively. The cumulative CVR rates were significantly higher in HBeAg-negative than HBeAg-positive group (P<0.001). HBeAg loss/seroconversion was observed in 21 (38.2%) out of 55 HBeAg-positive patients. One HBeAg-positive and 1 HBeAg-negative patients (2.2%) achieved HBsAg loss at months 6 and 8 of TDF therapy, respectively. Baseline HBV DNA level and qHBsAg were significant predictive factors for a CVR (P=0.001 and P<0.001, respectively)., Conclusions: Virologic, serologic, biochemical responses were achieved in both HBeAg-positive and HBeAg-negative patients under 24-month TDF therapy. Monitoring using baseline HBV DNA and qHBsAg levels would be helpful to predict CVR., (Copyright © 2017. Published by Elsevier B.V.)

Objective: Meningioma is the most common brain tumor. Genetic mutations in meningioma that include deletion of the neurofibromatosis type 2 gene, (NF2), offer diagnostic information on tumor behavior, recurrence and potential response to treatment. Obtaining high-grade genetic material is critical for accurate, sensitive and robust molecular testing. Currently, no standardized procedure exists for extracting gDNA from meningioma, and this problem was addressed in this report., Method: This study compared the yield and quality of extracted gDNA from patient meningioma specimens using an optimized phenol chloroform method and two commercial silica column-based extractions kits and tested respective performances as template in qPCR tests and multiplex ligation-dependent probe amplification (MLPA) NF2 screening., Results: Mean gDNA yields were comparable for each method tested; however, phenol chloroform extraction outperformed column-based kits in all other quality assurance metrics examined. Phenol chloroform extracted gDNA was highly pure, and of a higher fragment size species when compared to column prepared gDNA. qPCR of GAPDH, B2MG, and RPL37A housekeeping genes demonstrated variance in cycle thresholds between patient samples was much lower in the phenol chloroform group. Similarly, primer efficiencies were significantly improved in this sample group which translated to a broader qPCR linear dynamic range and much improved qPCR performance at low concentrations of template. MLPA screening identified NF2 gene deletions in 6 of 12 meningioma samples. Inconsistencies in copy number data for NF2 and reference regions of the genome were observed between gDNA sample extraction groups that included both false negative and positive errors in silica column derived gDNA samples., Conclusions: This study outlines a highly robust phenol chloroform extraction method for obtaining high-quality gDNA from frozen meningioma tissue and highlights the significance of performing adequate quality assurance when using gDNA for downstream genetic analysis. Most importantly, we demonstrate using gDNA extracted with silica column based kits can lead to diagnostic errors when screening NF2 deletions in meningiomas with MLPA., (Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.)