An AI-empowered indoor digital contact tracing system for COVID-19 outbreaks in residential care homes

An AI-empowered indoor digital contact-tracing system was developed using a centralized architecture and advanced low-energy Bluetooth technologies for indoor positioning, with careful preservation of privacy and data security. We analyzed the contact pattern data from two RCHs and investigated a COVID-19 outbreak in one study site. To evaluate the effectiveness of the system in containing outbreaks with minimal contacts under quarantine, a simulation study was conducted to compare the impact of different quarantine strategies on outbreak containment within RCHs. The significant difference in contact hours between weekdays and weekends was observed for some pairs of RCH residents and staff during the two-week data collection period. No significant difference between secondary cases and uninfected contacts was observed in a COVID-19 outbreak in terms of their demographics and contact patterns. Simulation results based on the collected contact data indicated that a threshold of accumulative contact hours one or two days prior to diagnosis of the index case could dramatically increase the efficiency of outbreak containment within RCHs by targeted isolation of the close contacts. This study demonstrated the feasibility and efficiency of employing an AI-empowered system in indoor digital contact tracing of outbreaks in RCHs in the post-pandemic era.

Marine plastic pollution detection and identification by using remote sensing-meta analysis

The persistent plastic litter, originating from different sources and transported from rivers to oceans, has posed serious biological, ecological, and chemical effects on the marine ecosystem, and is considered a global issue. In the past decade, many studies have identified, monitored, and tracked marine plastic debris in coastal and open ocean areas using remote sensing technologies. Compared to traditional surveying methods, high-resolution (spatial and temporal) multispectral or hyperspectral remote sensing data have been substantially used to monitor floating marine macro litter (FMML). In this systematic review, we present an overview of remote sensing data and techniques for detecting FMML, as well as their challenges and opportunities. We reviewed the studies based on different sensors and platforms, spatial and spectral resolution, ground sampling data, plastic detection methods, and accuracy obtained in detecting marine litter. In addition, this study elaborates the usefulness of high-resolution remote sensing data in Visible (VIS), Near-infrared (NIR), and Short-Wave InfraRed (SWIR) range, along with spectral signatures of plastic, in-situ samples, and spectral indices for automatic detection of FMML. Moreover, the Thermal Infrared (TIR), Synthetic aperture radar (SAR), and Light Detection and Ranging (LiDAR) data were introduced and these were demonstrated that could be used as a supplement dataset for the identification and quantification of FMML.

Current methods for evaluating people's exposure to green space: A scoping review

People's exposure to green space is a critical link between urban green space and urban residents' health. Since green space may affect human health through multiple pathways regarding diverse human health outcomes, the measurement of people's exposure to green space must be tailored to concrete study contexts and research questions. In this scoping review, we systematically categorized the available green space representations and metrics in the last two decades that can be used to derive people's exposure to green space regarding different research topics. A three-phase systematic review was conducted after a generalized search of relevant research articles from the three most-used publication databases, namely Scopus, the Web of Science, and PubMed. We identified 260 research articles that particularly discuss green space representations and metrics. We further developed a multi-pathway framework to articulate the complicated context issues in green space studies. We categorized the most relevant green space representations and metrics into five groups, including green space indices, the delineation, inventory, and usage of green space, the spatiotemporal evolution of green space, the attributes and components of green space, and the green space landscape and fragmentation. Finally, we discussed the inter-conversion between different green space representations and metrics, the "mobility-turn" in green space studies and how it may affect the derivation of people's exposure to green space, and other potential methodological issues in measuring people's exposure to green space. Our scoping review provides the most comprehensive framework and categories for deriving people's exposure to green space to date, which may strongly support a broad range of studies that concern green space's health effects.

Smart probes for optical imaging of T cells and screening of anti-cancer immunotherapies

T cells are an essential part of the immune system with crucial roles in adaptive response and the maintenance of tissue homeostasis. Depending on their microenvironment, T cells can be differentiated into multiple states with distinct functions. This myriad of cellular activities have prompted the development of numerous smart probes, ranging from small molecule fluorophores to nanoconstructs with variable molecular architectures and fluorescence emission mechanisms. In this Tutorial Review, we summarize recent efforts in the design, synthesis and application of smart probes for imaging T cells in tumors and inflammation sites by targeting metabolic and enzymatic biomarkers as well as specific surface receptors. Finally, we briefly review current strategies for how smart probes are employed to monitor the response of T cells to anti-cancer immunotherapies. We hope that this Review may help chemists, biologists and immunologists to design the next generation of molecular imaging probes for T cells and anti-cancer immunotherapies.

Multi-spatiotemporal AOD trends and association with land use changes over the Guangdong-Hong Kong-Macao Greater Bay Area during 2001-2021

Analyzing long-term variations of aerosol optical depth (AOD) is beneficial for determining high-pollutant-risk areas and formulating mitigation policies. In this study, multi-spatiotemporal trends and periodicity of AOD, as well as the persistence over the Guangdong-Hong Kong-Macao Greater Bay Area from 2001 to 2021, were investigated by the extreme-point symmetric mode decomposition (ESMD), Theil-Sen Median trend analysis and Hurst exponent. The results elucidate that AOD exhibits fluctuant variations during the 21-year period with the year 2012 as the turning point. There is a slight upward tendency (0.009 year^-1) in the pre-2012 period but a pronounced downward trend (- 0.03 year^-1) in the post-2012 period, suggesting an overall declining trend in the study area. The northern cities in the area present an increasing-stable-decreasing trend of monthly average AOD, whereas other cities have an increasing-fluctuating-decreasing trend over the study period. The decreasing rate in the western parts is higher than that in the eastern parts, like Zhaoqing, Jiangmen and Foshan city. A continuous decline of AOD is dominated over the study area, whereas an anti-persistence tendency is accumulated in the northeastern parts. Additionally, elevated AOD can be observed in unused land, water bodies and construction land, while grassland, cropland and woodland have lower AOD. The decreasing rate is larger when land-use types with high AOD are converted to those with low AOD; otherwise, the decreasing rate is smaller. The results have a great significance for improving the understanding of long-term variations of AOD, as well as providing a scientific basis to formulate environmental protection and mitigation practices.

Impact of the COVID-19 pandemic on travel behavior: A case study of domestic inbound travelers in Jeju, Korea

This study analyzes a large-scale navigation dataset that captures travel activities of domestic inbound visitors in Jeju, Korea in the first nine months of 2020. A collection of regression models are introduced to quantify the dynamic effects of local and national COVID-19 indicators on their travel behavior. Results suggest that behavior of inbound travelers was jointly affected by pandemic severity locally and remotely. The daily number of new cases in Jeju has a greater impact on reducing travel activities than the national-level daily new cases of COVID-19. The impacts of the pandemic did not diminish over time but produced heterogeneous effects on travels with different trip purposes. Our findings reveal the persistence of COVID-19's effects on travel behavior and the variability in travelers' responses across tourism activities with different levels of perceived health risks. The implications for crisis management and recovery strategies are also discussed.

Effects of Urban Green Space on Cardiovascular and Respiratory Biomarkers in Chinese Adults: Panel Study Using Digital Tracking Devices

Background

The health benefits of urban green space have been widely reported in the literature; however, the biological mechanisms remain unexplored, and a causal relationship cannot be established between green space exposure and cardiorespiratory health.

Objective

Our aim was to conduct a panel study using personal tracking devices to continuously collect individual exposure data from healthy Chinese adults aged 50 to 64 years living in Hong Kong.

Methods

A panel of cardiorespiratory biomarkers was tested each week for a period of 5 consecutive weeks. Data on weekly exposure to green space, air pollution, and the physical activities of individual participants were collected by personal tracking devices. The effects of green space exposure measured by the normalized difference vegetation index (NDVI) at buffer zones of 100, 250, and 500 meters on a panel of cardiorespiratory biomarkers were estimated by a generalized linear mixed-effects model, with adjustment for confounding variables of sociodemographic characteristics, exposure to air pollutants and noise, exercise, and nutrient intake.

Results

A total of 39 participants (mean age 56.4 years, range 50-63 years) were recruited and followed up for 5 consecutive weeks. After adjustment for sex, income, occupation, physical activities, dietary intake, noise, and air pollution, significant negative associations with the NDVI for the 250-meter buffer zone were found in total cholesterol (–21.6% per IQR increase in NDVI, 95% CI –32.7% to –10.6%), low-density lipoprotein (–14.9%, 95% CI –23.4% to –6.4%), glucose (–11.2%, 95% CI –21.9% to –0.5%), and high-sensitivity C-reactive protein (–41.3%, 95% CI –81.7% to –0.9%). Similar effect estimates were found for the 100-meter and 250-meter buffer zones. After adjustment for multiple testing, the effect estimates of glucose and high-sensitivity C-reactive protein were no longer significant.

Conclusions

The health benefits of green space can be found in some metabolic and inflammatory biomarkers. Further studies are warranted to establish the causal relationship between green space and cardiorespiratory health.

Sensor technology to monitor health, well-being and movement among healthcare personnel at workplace: a systematic scoping review protocol

INTRODUCTION

The well-being and health of healthcare personnel is becoming increasingly important in the delivery of high-quality healthcare. The recent developments in technology have provided new opportunities for the objective detection of a wide variety of real-world properties and movement. However, technologies that are used to monitor health, well-being and movement among healthcare personnel have not been fully synthesised. The overall aim of this scoping review is to examine what type of sensor technology is available to monitor the health, well-being and movement of healthcare personnel in healthcare settings. More specifically, we want to explore what types of sensor technology applications, for what purposes and how they have been used to monitor health, well-being and movement among healthcare personnel in different workplace settings.

METHODS AND ANALYSIS

This scoping review protocol will follow Arksey and O'Malley's methodology, complemented by the approach of the Joanna Briggs Institute to scoping reviews and guidance for conducting systematic scoping reviews. Peer-reviewed literature will be identified using a search strategy developed by a librarian, and a wide range of electronic datasets of medical, computer and information systems disciplines will be used. Eligibility of the articles will be determined using a two-stage screening process consisting of (1) a title and abstract scan, and (2) a full-text review. Extracted data will be thematically analysed and validated by an expert of sensor technology and a group of nurses as stakeholders. Descriptive statistics will be calculated when necessary.

ETHICS AND DISSEMINATION

The results obtained from the review will inform what technology has been used, how it has been used in healthcare settings and what types of technology might still be needed for future innovations. Findings of the scoping review will be published in a peer-reviewed journal.

REGISTRATION

This review was submitted in Open Science Framework on 12 December 2020.

Performance of the Roche/Snibe electrochemiluminescent anti-SARS-COV-2 spike assays compared to the Roche/Abbott IgG nucleocapsid and Abbott IgM spike assays

Introduction

We evaluated the Roche Elecsys Anti-SARS-CoV-2 and Snibe SARS-CoV-2 S-RBD IgG spike chemiluminescent immunoassays and compared them to existing Roche/Abbott nucleocapsid and Abbott IgM spike assays.

Methods

We enrolled 184 SARS-CoV-2 RT-PCR positive samples and 215 controls (172 pre-pandemic, and 43 cross-reactivity) to evaluate the Roche spike antibody (anti-SARS-CoV-2-S) assay. For the Snibe evaluation, we included 119 RT-PCR positive samples and 249 controls (200 pre-pandemice, 49 cross-reactivity). 98 cases had been tested on three spike assays (Roche total antibody, Snibe IgG and Abbott IgM).

Results

The Roche anti-SARS-CoV-2-S assay had a CV of 0.5% (0.82U/mL) and 2.3% (8.72U/mL) and was linear from 1.16 to 240U/mL. The Snibe assay was linear from 6.43 to 77.7AU/mL, CV of 5.5% (0.43AU/mL) and 8.8% (0.18AU/mL). The Snibe spike assay was significantly more sensitive than the Abbott IgG assay at 0–6 days POS (35.2% vs 3.6%, mean difference 29.6%, 95% CI 17.5 to 41.8, p < 0.0001). Optimized LORs significantly improved the sensitivity of the Roche spike (48.1%–56.7%) and both nucleocapsid assays (Roche 43.3%–65.5%, Abbott 3.6%–18.5%) in early disease.

Conclusion

Although both spike assays showed higher sensitivity than their nucleocapsid counterparts, lower, optimized LORs provided the most significant improvements to sensitivity.

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We report the performance of the Roche and Snibe anti-SARS-CoV-2 spike assays.

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The Snibe spike assay displayed the greatest sensitivity in early disease.

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The Snibe assay showed cross-reactivity with dengue and hepatitis antibodies.

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Optimized limits of reactivity improved the sensitivities of assays.

Reopening International Borders without Quarantine: Contact Tracing Integrated Policy against COVID-19

With the COVID-19 vaccination widely implemented in most countries, propelled by the need to revive the tourism economy, there is a growing prospect for relieving the social distancing regulation and reopening borders in tourism-oriented countries and regions. This need incentivizes stakeholders to develop border control strategies that fully evaluate health risks if mandatory quarantines are lifted. In this study, we have employed a computational approach to investigate the contact tracing integrated policy in different border-reopening scenarios in Hong Kong, China. Explicitly, by reconstructing the COVID-19 transmission from historical data, specific scenarios with joint effects of digital contact tracing and other concurrent measures (i.e., controlling arrival population and community nonpharmacological interventions) are applied to forecast the future development of the pandemic. Built on a modified SEIR epidemic model with a 30% vaccination coverage, the results suggest that scenarios with digital contact tracing and quick isolation intervention can reduce the infectious population by 92.11% compared to those without contact tracing. By further restricting the inbound population with a 10,000 daily quota and applying moderate-to-strong community nonpharmacological interventions (NPIs), the average daily confirmed cases in the forecast period of 60 days can be well controlled at around 9 per day (95% CI: 7–12). Two main policy recommendations are drawn from the study. First, digital contact tracing would be an effective countermeasure for reducing local virus spread, especially when it is applied along with a moderate level of vaccination coverage. Second, implementing a daily quota on inbound travelers and restrictive community NPIs would further keep the local infection under control. This study offers scientific evidence and prospective guidance for developing and instituting plans to lift mandatory border control policies in preparing for the global economic recovery.

A purpose-design computational method for estimation of plane of maximum curvature in Adolescent Idiopathic Scoliosis

Adolescent idiopathic scoliosis (AIS) is a complex three-dimensional (3D) deformity, and the plane of maximum curvature (PMC) is proposed to reflect these clinical features, which refers to a vertical plane presenting the maximum projected spinal curvature and its parameters include the PMC Cobb and orientation (angle between PMC and sagittal planes). This study aimed to develop a computational method (CM) for PMC estimation. Twenty-nine patients with AIS and computed tomography (CT) images were recruited. For CT, PMC was determined by rotating a vertical plane about its vertical axis with 5° increment until the maximum Cobb angle was measured. For CM, PMC was estimated via identifying the eight points (the corner points of the superior and inferior endplates of the upper and lower end-vertebrae respectively) in the coronal and lateral CT images. Two experienced raters repeated the PMC estimation three times with one-week interval. The intra-class correlation coefficient (ICC) and Bland-Altman method were used for statistical analysis. Twenty-seven right thoracic curves (RTs) (mean Cobb: 46.1°±12.4°) and 23 left thoracolumbar/lumbar (LTLs/LLs) (mean Cobb: 30.6°±11.1°) were analysed. The intra- and inter-rater ICC values were >0.91 and 0.84 in RTs and LTLs/LLs, respectively. The PMCs obtained from the CM and CT were showed good agreement was also observed between the PMCs obtained from the two methods according to ICC (>0.90) and Bland-Altman method assessments. This purpose-design computational method could provide reliable and valid estimation of PMCs for AIS, which has potential to be used as an alternative for 3D assessment.

Assessing the Country-Level Excess All-Cause Mortality and the Impacts of Air Pollution and Human Activity during the COVID-19 Epidemic

The impact of Coronavirus Disease 2019 (COVID-19) on cause-specific mortality has been investigated on a global scale. However, less is known about the excess all-cause mortality and air pollution-human activity responses. This study estimated the weekly excess all-cause mortality during COVID-19 and evaluated the impacts of air pollution and human activities on mortality variations during the 10th to 52nd weeks of 2020 among sixteen countries. A SARIMA model was adopted to estimate the mortality benchmark based on short-term mortality during 2015-2019 and calculate excess mortality. A quasi-likelihood Poisson-based GAM model was further applied for air pollution/human activity response evaluation, namely ground-level NO2 and PM2.5 and the visit frequencies of parks and workplaces. The findings showed that, compared with COVID-19 mortality (i.e., cause-specific mortality), excess all-cause mortality changed from -26.52% to 373.60% during the 10th to 52nd weeks across the sixteen countries examined, revealing higher excess all-cause mortality than COVID-19 mortality in most countries. For the impact of air pollution and human activities, the average country-level relative risk showed that one unit increase in weekly NO2, PM2.5, park visits and workplace visits was associated with approximately 1.54% increase and 0.19%, 0.23%, and 0.23% decrease in excess all-cause mortality, respectively. Moreover, compared with the impact on COVID-19 mortality, the relative risks of weekly NO2 and PM2.5 were lower, and the relative risks of weekly park and workplace visits were higher for excess all-cause mortality. These results suggest that the estimation based on excess all-cause mortality reduced the potential impact of air pollution and enhanced the influence of human activities compared with the estimation based on COVID-19 mortality.

Identifying the space-time patterns of COVID-19 risk and their associations with different built environment features in Hong Kong

Identifying the space-time patterns of areas with a higher risk of transmission and the associated built environment and demographic characteristics during the COVID-19 pandemic is critical for developing targeted intervention measures in response to the pandemic. This study aims to identify areas with a higher risk of COVID-19 transmission in different periods in Hong Kong and analyze the associated built environment and demographic factors using data of individual confirmed cases. We detect statistically significant space-time clusters of COVID-19 at the Large Street Block Group (LSBG) level in Hong Kong between January 23 and April 14, 2020. Two types of high-risk areas are identified (residences of and places visited by confirmed cases) and two types of cases (imported and local cases) are considered. The demographic and built environment features for the identified high-risk areas are further examined. The results indicate that high transport accessibility, dense and high-rise buildings, a higher density of commercial land and higher land-use mix are associated with a higher risk for places visited by confirmed cases. More green spaces, higher median household income, lower commercial land density are linked to a higher risk for the residences of confirmed cases. The results in this study not only can inform policymakers to improve resource allocation and intervention strategies but also can provide guidance to the public to avoid conducting high-risk activities and visiting high-risk places.

Effects of urban functional fragmentation on nitrogen dioxide (NO2) variation with anthropogenic-emission restriction in China

Urban functional fragmentation plays an important role in assessing Nitrogen Dioxide (NO2) emissions and variations. While the mediated impact of anthropogenic-emission restriction has not been comprehensively discussed, the lockdown response to the novel coronavirus disease 2019 (COVID-19) provides an unprecedented opportunity to meet this goal. This study proposes a new idea to explore the effects of urban functional fragmentation on NO2 variation with anthropogenic-emission restriction in China. First, NO2 variations are quantified by an Autoregressive Integrated Moving Average with external variables-Dynamic Time Warping (SARIMAX-DTW)-based model. Then, urban functional fragmentation indices including industrial/public Edge Density (ED) and Landscape Shape Index (LSI), urban functional Aggregation Index (AI) and Number of Patches (NP) are developed. Finally, the mediated impacts of anthropogenic-emission restriction are assessed by evaluating the fragmentation-NO2 variation association before and during the lockdown during COVID-19. The findings reveal negative effects of industrial ED, public LSI, urban functional AI and NP and positive effects of public ED and industrial LSI on NO2 variation based on the restricted anthropogenic emissions. By comparing the association analysis before and during lockdown, the mediated impact of anthropogenic-emission restriction is revealed to partially increase the effect of industrial ED, industrial LSI, public LSI, urban functional AI and NP and decrease the effect of public ED on NO2 variation. This study provides scientific findings for redesigning the urban environment in related to the urban functional configuration to mitigating the air pollution, ultimately developing sustainable societies.

Spatial analysis of the impact of urban geometry and socio-demographic characteristics on COVID-19, a study in Hong Kong

The World Health Organization considered the wide spread of COVID-19 over the world as a pandemic. There is still a lack of understanding of its origin, transmission, and treatment methods. Understanding the influencing factors of COVID-19 can help mitigate its spread, but little research on the spatial factors has been conducted. Therefore, this study explores the effects of urban geometry and socio-demographic factors on the COVID-19 cases in Hong Kong. For each patient, the places they visited during the incubation period before going to hospital were identified, and matched with corresponding attributes of urban geometry (i.e., building geometry, road network and greenspace) and socio-demographic factors (i.e., demographic, educational, economic, household and housing characteristics) based on the coordinates. The local cases were then compared with the imported cases using stepwise logistic regression, logistic regression with case-control of time, and least absolute shrinkage and selection operator regression to identify factors influencing local disease transmission. Results show that the building geometry, road network and certain socio-economic characteristics are significantly associated with COVID-19 cases. In addition, the results indicate that urban geometry is playing a more important role than socio-demographic characteristics in affecting COVID-19 incidence. These findings provide a useful reference to the government and the general public as to the spatial vulnerability of COVID-19 transmission and to take appropriate preventive measures in high-risk areas.

Environmental impacts of shifts in energy, emissions, and urban heat island during the COVID-19 lockdown across Pakistan

Restrictions on human and industrial activities due to the coronavirus (COVID-19) pandemic have resulted in an unprecedented reduction in energy consumption and air pollution around the world. Quantifying these changes in environmental conditions due to government-enforced containment measures provides a unique opportunity to understand the patterns, origins and impacts of air pollutants. During the lockdown in Pakistan, a significant reduction in energy demands and a decline of ∼1786 GWh (gigawatt hours) in electricity generation is reported. We used satellite observational data for nitrogen dioxide (NO₂), carbon monoxide (CO), sulphur dioxide (SO₂), aerosol optical depth (AOD) and land surface temperature (LST) to explore the associated environmental impacts of shifts in energy demands and emissions across Pakistan. During the strict lockdown period (March 23 to April 15, 2020), we observed a reduction in NO₂ emissions by 40% from coal-based power plants followed by 30% in major urban areas compared to the same period in 2019. Also, around 25% decrease in AOD (at 550 nm) thickness in industrial and energy sectors was observed although no major decrease was evident in urban areas. Most of the industrial regions resumed emissions during the 3rd quarter of April 2020 while the urban regions maintained reduced emissions for a longer period. Nonetheless, a gradual increase has been observed since April 16 due to relaxations in lockdown implementations. Restrictions on transportation in the cities resulted in an evident drop in the surface urban heat island (SUHI) effect, particularly in megacities. The changes reported as well as the analytical framework provides a baseline benchmark to assess the sectoral pollution contributions to air quality, especially in the scarcity of ground-based monitoring systems across the country.

Spatial and environmental constraints on natural forest regeneration in the degraded landscape of Hong Kong

Tropical forests are the main reservoirs for global biodiversity and climate control. As secondary forests are now more widespread than primary forests, understanding their functioning and role in the biosphere is increasingly important. This includes understanding how they achieve stability, how they accumulate species and build biodiversity and how they cycle nutrients and carbon. This study investigates how we can restore tropical secondary forests to resemble high biomass, highly biodiverse and stable ecosystems seen today only in primary, undisturbed forests. The study used historic aerial photographs and recent high-resolution satellite images from 1945 to 2014 to map forest patches with five age categories, from 14-years to over 70-years, in Hong Kong's degraded tropical landscape. A forest inventory comprising 28 quadrats provided a rare opportunity to relate patterns of species composition at different stages during the succession with topographic and soil characteristics. The topographic variables accounted for 15% of the variance in species abundance, and age of forest stands explained 29%. Species richness rapidly increased after the first 15 years, but was lower in old-growth, than in medium age forest. This is attributed to the inability of late-successional species to disperse into the young forests as the natural dispersal agents (birds, mammals) have been lost. Light-loving pioneers which are unable to tolerate the shade of older forests, cannot regenerate in their own shade, therefore species diversity declines after a few decades. For ecosystem restoration in tropical secondary forests, introduction of late-successional species is necessary to assist natural succession, given the absence of native fauna, seed dispersal agents, and the surrounding altered environment. We also show that remote sensing can play a pivotal role in understanding the recovery and functioning of secondary forest regeneration as its contribution to the biosphere is increasingly important.

Evaluation of an Electrochemiluminescent SARS-CoV-2 Antibody Assay

BACKGROUND

Little is known about the performance of the Roche novel severe acute respiratory syndrome coronavirus 2 antibody (anti-SARS-CoV-2) assay. We provide an extensive evaluation of this fully automated assay on Cobas e801/e602 immunoassay analyzers.

METHODS

We assessed the linearity, precision, and throughput of the Roche anti-SARS-CoV-2 assay. Sensitivity was calculated from 349 SARS-CoV-2 polymerase chain reaction (PCR) positive samples; specificity was determined from 715 coronavirus disease 2019 (COVID-19)-naive samples. We examined cross-reactivity against other antibody positive samples [syphilis, rheumatoid factor (RF), antinuclear antibody (ANA), double-stranded DNA (ds-DNA), influenza, dengue, hepatitis B (HBV), hepatitis C (HCV)] and the anti-SARS-CoV-2 kinetics.

RESULTS

The assay cut-off index (COI) was linear up to 90.8. The interassay precision was 2.9% for a negative control (COI = 0.1) and 5.1% for a positive control (COI = 3.0). Assay time is 18 min and results are available 1 min later; throughput for 300 samples was 76 min. Only 1 case positive for HBsAg tested falsely positive; specificity was 99.9%. The assay has a sensitivity of 97.1% 14 days after PCR positivity (POS) and 100% at ≥21 days POS; 48.2% of cases had anti-SARS-CoV-2 within 6 days POS. In 11 patients in whom serum was available prior to a positive antibody signal (COI ≥1.0) the interval between the last negative and first positive COI (time to "seroconversion") on average is 3 days (range 1-6 days) and 4 more days (range 1-7) for the anti-SARS-CoV-2 to plateau.

CONCLUSION

The Roche anti-SARS-CoV-2 assay shows excellent performance with minimal cross-reactivity from other viral and confounding antibodies. Antibody development and seroconversion appears quite early.

Geospatial context of social and environmental factors associated with health risk during temperature extremes: Review and discussion

This study reviews forty-six publications between 2008 and 2017 dealing with socio-environmental impacts on adverse health effects of temperature extremes, in a geospatial context. The review showed that most studies focus on extremely hot weather but lack analysis of how spatial heterogeneity across a region can influence cold mortality/morbidity. There are limitations regarding the use of temperature datasets for spatial analyses. Only a few studies have applied air temperature datasets with high spatial resolution to health studies, but none of these studies have used anthropogenic heat as a factor for analysis of health risk. In addition, the elderly is generally recognized as a vulnerable group in most studies, but the interaction between old age and temperature risk varies by location. Other socio-demographic factors such as low income, low education and accessibility to community shelters may also need to be considered in the future. There are only a few studies which investigate the interaction between temperature and air pollution in a geospatial context, despite the fact that this is a known interaction that can influence health risk under extreme weather. In conclusions, although investigation of temperature effects on health risk is already at the "mature stage", studies of socio-environmental influences on human health under extreme weather in a geospatial context is still being investigated. A comprehensive assessment is required to analyse how the spatial aspects of the geophysical and social environments can influence human health under extreme weather, in order to develop a better community plan and health protocols for disaster preparedness.

Analysis of accessibility to emergency rooms by dynamic population from mobile phone data: Geography of social inequity in South Korea

Accessibility of emergency medical care is one of the crucial factors in evaluating national primary medical care systems. While many studies have focused on this issue, there was a fundamental limit to the measurement of accessibility of emergency rooms, because the commonly used census-based population data are difficult to provide realistic information in terms of time and space. In this study, we evaluated the geographical accessibility of emergency rooms in South Korea by using dynamic population counts from mobile phone data. Such population counts were more accurate and up-to-date because they are obtained by aggregating the number of mobile phone users in a 50-by-50 m grid of a locational field, weighted by stay time. Considering both supply and demand of emergency rooms, the 2-step floating catchment analysis was implemented. As a result, urban areas, including the capital city Seoul, showed lower accessibility to emergency rooms, whereas rural areas recorded higher accessibility. This result was contrary to the results analyzed by us based on census-based population data: higher accessibility in urban areas and lower in rural. This implies that using solely census data for accessibility analysis could lead to certain errors, and adopting mobile-based population data would represent the real-world situations for solving problems of social inequity in primary medical care.

Urban environmental influences on the temperature-mortality relationship associated mental disorders and cardiorespiratory diseases during normal summer days in a subtropical city

Temperature is associated with mortality risk across cities. However, there is lack of study investigating the summer effect on mortality associated with mental/behavioral disorders, especially in cities with subtropical climate. In addition, summer mortality in subtropical cities is different from tropical cities, and previous studies have not investigated the urban environmental inequality on heat mortality associated with mental/behavioral disorders. A register-based study was developed to estimate the temperature effects on decedents on days with 50^th percentile of average daily temperature between 2007 and 2014 in Hong Kong (n = 133,359). Poisson regression was firstly applied to estimate the incidence rate ratio (IRR) from the summer temperature effects on all-cause mortality, cardiovascular mortality, respiratory mortality, and mortality associated with mental/behavioral disorders. For a 1 °C increase in average temperature on days with temperature ≥ 24.51 °C, IRRs of mortality associated with mental and behavioral disorders on lag 0 and lag 1 days were 1.033 [1.004, 1.062] and 1.030 [1.002, 1.060], while temperature effects on cardiovascular mortality and respiratory mortality during normal summer days (not extreme heat events) were not significant. A further investigation with linear regression has shown that decedents with mental/behavioral disorders on higher temperature days resided in areas with lower percentage of sky view, lower percentage of vegetation cover, higher level of neighborhood-level PM_2.5, higher level of neighborhood-level NO, and higher level of neighborhood-level black carbon (BC). In order to develop protocols for community healthcare based on the "Leaving no one behind" scheme documented in the 2016 Sustainable Development Goals report of the United Nations, it is necessary to include heat effects on mental/behavioral disorders, especially people with dementia, for community planning and healthcare development.

Characterizing spatiotemporal dynamics of anthropogenic heat fluxes: A 20-year case study in Beijing-Tianjin-Hebei region in China

Rapid urbanization, which is closely related to economic growth, human health, and micro-climate, has resulted in a considerable amount of anthropogenic heat emissions. The lack of estimation data on long-term anthropogenic heat emissions is a great concern in climate and urban flux research. This study estimated the annual average anthropogenic heat fluxes (AHFs) in Beijing-Tianjin-Hebei region in China between 1995 and 2015 on the basis of multisource remote sensing images and ancillary data. Anthropogenic heat emissions from different sources (e.g., industries, buildings, transportation, and human metabolism) were also estimated to analyze the composition of AHFs. The spatiotemporal dynamics of long-term AHFs with high spatial resolution (500 m) were estimated by using a refined AHF model and then analyzed using trend and standard deviation ellipse analyses. Results showed that values in the region increased significantly from 0.15 W· m^-2 in 1995 to 1.46 W· m^-2 in 2015. Heat emissions from industries, transportation, buildings, and human metabolism accounted for 64.1%, 17.0%, 15.5%, and 3.4% of the total anthropogenic heat emissions, respectively. Industrial energy consumption was the dominant contributor to the anthropogenic heat emissions in the region. During this period, industrial heat emissions presented an unstable variation but showed a growing trend overall. Heat emissions from buildings increased steadily. Spatial distribution was extended with an increasing tendency of the difference between the maximum and the minimum and was generally dominated by the northeast-southwest directional pattern. The spatiotemporal distribution patterns and trends of AHFs could provide vital support on management decision in city planning and environmental monitoring.

Influence of Urban Green Space and Facility Accessibility on Exercise and Healthy Diet in Hong Kong

Background A cross-sectional study using a convenience sampling method was conducted to understand how green space and accessibility of common public open spaces in compact urban areas affect physical activity and healthy diets of residents. Methods A total of 554 residents completed a structured questionnaire on quality of life, physical activity level and healthy eating practice. Particularly, categories of physical activity and durations were obtained by using the short form Chinese International Physical Activity Questionnaire (IPAQ-C), then the Metabolic Equivalent of Task (MET)-minutes/week was calculated using the formulae (walking minutes × walking days × 3.3) + (moderate-intensity activity minutes × moderate days × 4.0) + (vigorous-intensity activity minutes × vigorous-intensity days × 8.0). The percentage of green space was calculated based on a spatial buffer with a 500 m radius from participants' geocoded addresses using a SPOT ('Satellite Pour l'Observation de la Terre' in French) satellite image-derived vegetation dataset. Parks, promenade and sports facilities were examples of open spaces. Results The sampled population who lived with green space averaged 10.11% ± 7.95% (ranged 1.56-32.90%), with the majority (90%) performing physical activities at medium and high levels. MET-minutes/week was significantly associated (Pearson r = 0.092; p < 0.05) with the green space percentage. Relatively active residents commonly used open spaces within the district for performing exercise, in particular, parks and promenades were mostly used by older residents, while sports facilities by the younger groups at age 25-44 and <25 years. Conclusions Current findings suggested promotion of exercise could be achieved by the design or redesign of built environment to include more parks accessible to the residents with the increase of vegetation.

Neighborhood-based subjective environmental vulnerability index for community health assessment: Development, validation and evaluation

Neighborhood-based environmental vulnerability is significantly associated with long-term community health impacts. Previous studies have quantified environmental vulnerability using objective environmental datasets. However, environmental cognition among a population may influence subjective feelings of environmental vulnerability, and this can be associated with community health risk. In this study, a mixed-methods approach was applied to estimate neighborhood-based environmental vulnerability based on objective environmental measures and subjective environmental understanding from a local population. The synergistic use of both qualitative and quantitative data resulted in a "subjective environmental vulnerability" index which can demonstrate environmental deprivation across Hong Kong. The resultant maps were compared with a mortality dataset between 2007 and 2014, based on a case-series analysis. The case-series analysis indicated that using a subjective environmental vulnerability index as an approach for neighborhood mapping is able to estimate the community health risk across Hong Kong. In particular, the following types of cause-specific mortality have significant association with the subjective environmental vulnerability index: 1) mortality associated with mental and behavioral disorders, 2) cardiovascular mortality, 3) respiratory mortality, and 4) mortality associated with diseases of the digestive system. In conclusion, the use of a subjective environmental vulnerability index can be implemented within a community health planning program, especially to reduce long-term adverse impacts on population with mental impairment.

Spatiotemporal Prediction of Increasing Winter Perceived Temperature across a Sub-Tropical City for Sustainable Planning and Climate Change Mitigation

Climate variability has been documented as being key to influencing human wellbeing across cities as it is linked to mortality and illness due to changes in the perceived weather cycle. Many studies have investigated the impact of summer temperature on human health and have proposed mitigation strategies for summer heat waves. However, sub-tropical cities are still experiencing winter temperature variations. Increasing winter perceived temperature through the decades may soon affect city wellbeing, due to a larger temperature change between normal winter days and extreme cold events, which may cause higher health risk due to lack of adaptation and self-preparedness. Therefore, winter perceived temperature should also be considered and integrated in urban sustainable planning. This study has integrated the increasing winter perceived temperature as a factor for developing spatiotemporal protocols for mitigating the adverse impact of climate change. Land surface temperature (LST) derived from satellite images and building data extracted from aerial photographs were used to simulate the adjusted wind chill equivalent temperature (AWCET) particularly for sub-tropical scenarios between 1990 and 2010 of the Kowloon Peninsula, Hong Kong. Compared with perceived temperature based on the representative station located at the headquarters of the Hong Kong Observatory, the temperature of half the study area in the Kowloon Peninsula has raised by 1.5 °C. The areas with less green space and less public open space in 2010 show higher relative temperatures. Socioeconomically deprived areas (e.g., areas with lower median monthly income) may suffer more from this scenario, but not all types of socioeconomic disparities are associated with poor sustainable planning. Based on our results and the "no-one left behind" guideline from the United Nations, climate change mitigation should be conducted by targeting socioeconomic neighborhoods more than just aging communities.

Risk of needing completion thyroidectomy for low-risk papillary thyroid cancers treated by lobectomy

Background

Low-risk differentiated thyroid cancers may, according to the American Thyroid Association (ATA) 2015 guidelines, be managed initially with lobectomy. However, definitive risk categorization requires pathological assessment of the specimen, resulting in completion thyroidectomy being recommended when discordance between preoperative and postoperative staging occurs. This study sought to establish the expected rate of completion thyroidectomy in patients with papillary thyroid cancer (PTC) treated by lobectomy.

Methods

Patients with PTC treated over 5 years (2013-2017 inclusive) and meeting the ATA criteria for lobectomy were identified from the prospectively developed database of a high-volume, university department of endocrine surgery. Concordance between the ATA initial and final recommendation, and the putative rate of completion thyroidectomy were calculated. Multivariable analysis was used to assess preoperative factors as predictors of the need for total thyroidectomy.

Results

Of 275 patients with PTC who met ATA preoperative criteria for lobectomy there was concordance between this and the final recommendation in 158 (57·5 per cent) and discordance in 117 (43·5 per cent). Most common reasons for discordance were: angioinvasion (30·8 per cent), local invasion (23·9 per cent) or both (20·5 per cent). Four patients (1·5 per cent) had permanent hypoparathyroidism. On multivariable analysis, age, sex, tumour size and family history did not independently predict the final treatment required.

Conclusion

Although many patients may be treated adequately with lobectomy, just under half would require completion thyroidectomy. Further work is needed on preoperative risk stratification but, before this, total thyroidectomy remains the treatment of choice for low-risk 1-4-cm PTC in the hands of high-volume thyroid surgeons who can demonstrate low complication rates.

Evaluation of machine learning techniques with multiple remote sensing datasets in estimating monthly concentrations of ground-level PM2.5

Fine particulate matter (PM_2.5) has been recognized as a key air pollutant that can influence population health risk, especially during extreme cases such as wildfires. Previous studies have applied geospatial techniques such as land use regression to map the ground-level PM_2.5, while some recent studies have found that Aerosol Optical Depth (AOD) derived from satellite images and machine learning techniques may be two elements that can improve spatiotemporal prediction. However, there has been a lack of studies evaluating use of different machine learning techniques with AOD datasets for mapping PM_2.5, especially in areas with high spatiotemporal variability of PM_2.5. In this study, we compared the performance of eight predictive algorithms with the use of multiple remote sensing datasets, including satellite-derived AOD data, for the prediction of ground-level PM2.5 concentration. Based on the results, Cubist, random forest and eXtreme Gradient Boosting were the algorithms with better performance, while Cubist was the best (CV-RMSE = 2.64 μg/m3, CV-R² = 0.48). Variable importance analysis indicated that the predictors with the highest contributions in modelling were monthly AOD and elevation. In conclusion, appropriate selection of machine learning algorithms can improve ground-level PM2.5 estimation, especially for areas with nonlinear relationships between PM2.5 and predictors caused by complex terrain. Satellite-derived data such as AOD and land surface temperature (LST) can also be substitutes for traditional datasets retrieved from weather stations, especially for areas with sparse and uneven distribution of stations.

Influences of socioeconomic vulnerability and intra-urban air pollution exposure on short-term mortality during extreme dust events

Air pollution has been shown to be significantly associated with morbidity and mortality in urban areas, but there is lack of studies focused on extreme pollution events such as extreme dust episodes in high-density Asian cities. However, such cities have had extreme climate episodes that could have adverse health implications for downwind areas. More importantly, few studies have comprehensively investigated the mortality risks of extreme dust events for socioeconomically vulnerable populations. This paper examined the association between air pollutants and mortality risk in Hong Kong from 2006 to 2010, with a case-crossover analysis, to determine the elevated risk after an extreme dust event in a high-density city. The results indicate that PM_10-2.5 dominated the all-cause mortality effect at the lag 0 day (OR: 1.074 [1.051, 1.098]). This study also found that people who were aged ≥ 65, economically inactive, or non-married had higher risks of all-cause mortality and cardiorespiratory mortality during days with extreme dust events. In addition, people who were in areas with higher air pollution had significantly higher risks of all-cause mortality and cardiorespiratory mortality. In conclusion, the results of this study can be used to target the vulnerable among a population or an area and the day(s) at risk to assist in health protocol development and emergency planning, as well as to develop early warnings for the general public in order to mitigate potential mortality risk for vulnerable population groups caused by extreme dust events.

Spatiotemporal influence of temperature, air quality, and urban environment on cause-specific mortality during hazy days

Haze is an extreme weather event that can severely increase air pollution exposure, resulting in higher burdens on human health. Few studies have explored the health effects of haze, and none have investigated the spatiotemporal interaction between temperature, air quality and urban environment that may exacerbate the adverse health effects of haze. We investigated the spatiotemporal pattern of haze effects and explored the additional effects of temperature, air pollution and urban environment on the short-term mortality risk during hazy days. We applied a Poisson regression model to daily mortality data from 2007 through 2014, to analyze the short-term mortality risk during haze events in Hong Kong. We evaluated the adverse effect on five types of cause-specific mortality after four types of haze event. We also analyzed the additional effect contributed by the spatial variability of urban environment on each type of cause-specific mortality during a specific haze event. A regular hazy day (lag 0) has higher all-cause mortality risk than a day without haze (odds ratio: 1.029 [1.009, 1.049]). We have also observed high mortality risks associated with mental disorders and diseases of the nervous system during hazy days. In addition, extreme weather and air quality contributed to haze-related mortality, while cold weather and higher ground-level ozone had stronger influences on mortality risk. Areas with a high-density environment, lower vegetation, higher anthropogenic heat, and higher PM_2.5 featured stronger effects of haze on mortality than the others. A combined influence of haze, extreme weather/air quality, and urban environment can result in extremely high mortality due to mental/behavioral disorders or diseases of the nervous system. In conclusion, we developed a data-driven technique to analyze the effects of haze on mortality. Our results target the specific dates and areas with higher mortality during haze events, which can be used for development of health warning protocols/systems.

Danshen (Salvia miltiorrhiza) protects ovariectomized rats fed with high-saturated fat-sucrose diet from bone loss

Dietary patterns may interfere with the efficacy of herbal intervention. Our results demonstrated the protective effects of Salvia miltiorrhiza aqueous extract (SMA) on bone metabolism were influenced by levels of dietary fat and sucrose in ovariectomized (OVX) rats through its actions on attenuating lipid deposition and oxidative stress in rats.

INTRODUCTION

Salvia miltiorrhiza (SM), also known as Danshen, has been tested as an osteoporosis treatment in a series of small, short human trials that generally report improvements in bone property. However, dietary patterns may interfere with the effects of herbal intervention. We hypothesized that dietary fat and sucrose levels could influence the effects of SM supplementation on bone in estrogen-deficient animals.

METHODS

Six-month-old Sprague-Dawley sham or OVX rats were fed either a low-saturated fat-sucrose (LFS, a diet that was similar in composition to normal rat chow) or a high-fat-sucrose (HFS) diet and OVX rats were treated (8 rats/group) with SM aqueous extract (SMA, 600 mg/kg/day), 17β-estradiol (1 mg/kg/day), or vehicle for 12 weeks.

RESULTS

SMA significantly improved bone properties as revealed by the increase in trabecular bone mineral density and decrease in trabecular separation at proximal metaphysis of the tibia (PT) in HFS-fed OVX rats, but not in LFS-fed OVX rats. SMA greatly reduced lipid deposition and malondialdehyde levels, improved the activities of superoxide dismutase, catalase, and glutathione peroxidase in the livers of HFS-fed OVX rats. SMA could directly improve the proliferation and differentiation in vitro in an H₂O₂-induced preosteoblast cell model by attenuating cellular reactive oxygen species levels.

CONCLUSIONS

The protective effects of SMA on bone metabolism were influenced by dietary fat and sucrose levels in OVX rats. The ability of SMA to reduce bone loss in HFS-fed OVX rats was associated with the attenuation of lipid deposition and oxidative stress levels.

Observational evidence of a long-term increase in precipitation due to urbanization effects and its implications for sustainable urban living

Although projected precipitation increases in East Asia due to future climate change have aroused concern, less attention has been paid by the scientific community and public to the potential long-term increase in precipitation due to rapid urbanization. A ten-year precipitation dataset was analysed for both a rapidly urbanized megacity and nearby suburban/rural stations in southern China. Rapid urbanization in the megacity was evident from satellite observations. A statistically significant, long-term, increasing trend of precipitation existed only at the megacity station (45.6mm per decade) and not at the other stations. The increase was attributed to thermal and dynamical modifications of the tropospheric boundary layer related to urbanization, which was confirmed by the results of our WRF-SLUCM simulations. The results also suggested that a long-term regional increase in precipitation, caused by greenhouse gas-induced climate change, for instance, was not evident within the study period. The urbanization-induced increase was found to be higher than the precipitation increase (18.3mm per decade) expected from future climate change. The direct climate impacts due to rapid urbanization is highlighted with strong implications for urban sustainable development and the planning of effective adaptation strategies for issues such as coastal defenses, mosquito-borne disease spread and heat stress mortality.

A Case-Control Study of Body Composition, Prevalence, and Curve Severity of the Patients With Adolescent Idiopathic Scoliosis in the East Part of China

OBJECTIVE

The purpose of the study is to investigate the characteristics of prevalence and curve severity in patients with adolescent idiopathic scoliosis (AIS) and the body composition alterations between the patients with AIS and healthy controls.

METHODS

Information on the study sample was obtained from a screening database. The AIS cohort was paired with an age- and gender-matched healthy cohort. The stratification of BMI and curve severity was conducted according to the criteria developed by the US Centers for Disease Control and Prevention and the Scoliosis Research Society. The prevalence and curve severity of the patients with AIS were investigated. Multigroup comparison of body composition parameters was conducted according to BMI between the patients with AIS and healthy controls.

RESULTS

A total of 1,202 patients with AIS and an age- and gender-matched cohort were recruited from local schools. The underweight cases had the highest prevalence of AIS and significantly higher Cobb angle compared with the other three BMI subgroups. Although the patients with AIS had lower body weight, body fat mass, percentage of body fat, and fat-free mass compared with healthy controls, converse results were observed in the underweight cases after stratification according to BMI.

CONCLUSION

Based on the sporadic body composition of the patients with AIS observed in the current study, it is predictable that the pathophysiological alterations may be different before and after the onset of scoliosis. Well-designed human or animal studies for underweight patients would be helpful to reveal the mechanisms of pathophysiological alterations and better predict the development of AIS.

Spatial variability of excess mortality during prolonged dust events in a high-density city: a time-stratified spatial regression approach

BACKGROUND

Dust events have long been recognized to be associated with a higher mortality risk. However, no study has investigated how prolonged dust events affect the spatial variability of mortality across districts in a downwind city.

METHODS

In this study, we applied a spatial regression approach to estimate the district-level mortality during two extreme dust events in Hong Kong. We compared spatial and non-spatial models to evaluate the ability of each regression to estimate mortality. We also compared prolonged dust events with non-dust events to determine the influences of community factors on mortality across the city.

RESULTS

The density of a built environment (estimated by the sky view factor) had positive association with excess mortality in each district, while socioeconomic deprivation contributed by lower income and lower education induced higher mortality impact in each territory planning unit during a prolonged dust event. Based on the model comparison, spatial error modelling with the 1st order of queen contiguity consistently outperformed other models. The high-risk areas with higher increase in mortality were located in an urban high-density environment with higher socioeconomic deprivation.

CONCLUSION

Our model design shows the ability to predict spatial variability of mortality risk during an extreme weather event that is not able to be estimated based on traditional time-series analysis or ecological studies. Our spatial protocol can be used for public health surveillance, sustainable planning and disaster preparation when relevant data are available.

A new approach for the estimation of phytoplankton cell counts associated with algal blooms

This study proposes a method for estimating phytoplankton cell counts associated with an algal bloom, using satellite images coincident with in situ and meteorological parameters. Satellite images from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI) and HJ-1 A/B Charge Couple Device (CCD) sensors were integrated with the meteorological observations to provide an estimate of phytoplankton cell counts. All images were atmospherically corrected using the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) atmospheric correction method with a possible error of 1.2%, 2.6%, 1.4% and 2.3% for blue (450-520nm), green (520-600nm), red (630-690nm) and near infrared (NIR 760-900nm) wavelengths, respectively. Results showed that the developed Artificial Neural Network (ANN) model yields a correlation coefficient (R) of 0.95 with the in situ validation data with Sum of Squared Error (SSE) of 0.34cell/ml, Mean Relative Error (MRE) of 0.154cells/ml and a bias of -504.87. The integration of the meteorological parameters with remote sensing observations provided a promising estimation of the algal scum as compared to previous studies. The applicability of the ANN model was tested over Hong Kong as well as over Lake Kasumigaura, Japan and Lake Okeechobee, Florida USA, where algal blooms were also reported. Further, a 40-year (1975-2014) red tide occurrence map was developed and revealed that the eastern and southern waters of Hong Kong are more vulnerable to red tides. Over the 40 years, 66% of red tide incidents were associated with the Dinoflagellates group, while the remainder were associated with the Diatom group (14%) and several other minor groups (20%). The developed technology can be applied to other similar environments in an efficient and cost-saving manner.

Assessment of Urban Environmental Quality in a Subtropical City Using Multispectral Satellite Images

Urban environmental quality (UEQ) is a complex and spatially variable parameter of increasing concern, especially in densely populated cities of the tropics and subtropics where climate, air quality, and the urban infrastructure may interact to produce uncomfortable and hazardous effects. The study investigates the application of multispectral remote sensing from the Landsat ETM+ and IKONOS satellite sensors for the mapping of UEQ in urban Hong Kong at a detailed level, using the measurable, image-based parameters of temperature and biomass, and examines the relationship between these and air quality in selected study districts. Multiple-criteria queries on these two parameters show that spatial variations in UEQ are closely related to natural topographic factors and urban morphology. The amount of biomass, as opposed to total area of vegetation, is also shown to be an important factor in the spatial variation of UEQ. The data permit visualisation of the relationship between the human and natural factors involved in UEQ and generate recommendations for future planning and urban-renewal projects.

Renin inhibitor aliskiren exerts beneficial effect on trabecular bone by regulating skeletal renin-angiotensin system and kallikrein-kinin system in ovariectomized mice

SUMMARY

The skeletal renin-angiotensin system contributes to the development of osteoporosis. The renin inhibitor aliskiren exhibited beneficial effects on trabecular bone of osteoporotic mice, and this action might be mediated through angiotensin and bradykinin receptor pathways. This study implies the potential application of renin inhibitor in the management for postmenopausal osteoporosis.

INTRODUCTION

The skeletal renin-angiotensin system plays key role in the pathological process of osteoporosis. The present study is designed to elucidate the effect of renin inhibitor aliskiren on trabecular bone and its potential action mechanism in ovariectomized (OVX) mice.

METHODS

The OVX mice were treated with low dose (5 mg/kg) or high dose (25 mg/kg) of aliskiren or its vehicle for 8 weeks. The bone turnover markers were measured by ELISA. The structural parameters of trabecular bone at lumbar vertebra (LV) and distal femoral metaphysis were measured by micro-CT. The expression of messenger RNA (mRNA) and protein was studied by RT-PCR and immunoblotting, respectively.

RESULTS

Aliskiren treatment reduced urinary excretion of calcium and serum level of tartrate-resistant acid phosphatase in OVX mice. The treatment with aliskiren significantly increased bone volume (BV/TV) and connectivity density (Conn.D) of trabecular bone at LV-2 and LV-5 as well as dramatically enhanced BV/TV, Conn.D, bone mineral density (BMD/BV) and decreased bone surface (BS/BV) at the distal femoral end. Aliskiren significantly down-regulated the expression of angiotensinogen, angiotensin II (Ang II), Ang II type 1 receptor, bradykinin receptor (BR)-1, and osteocytic-specific gene sclerostin as well as the osteoclast-specific genes, including carbonic anhydrase II, matrix metalloproteinase-9, and cathepsin K.

CONCLUSIONS

This study revealed that renin inhibitor aliskiren exhibited the beneficial effects on trabecular bone of ovariectomy-induced osteoporotic mice, and the underlying mechanism for this action might be mediated through Ang II and BR signaling pathways in bone.

Analysis of airborne particulate matter (PM2.5) over Hong Kong using remote sensing and GIS

Airborne fine particulates (PM_2.5; particulate matter with diameter less than 2.5 μm) are receiving increasing attention for their potential toxicities and roles in visibility and health. In this study, we interpreted the behavior of PM_2.5 and its correlation with meteorological parameters in Hong Kong, during 2007–2008. Significant diurnal variations of PM_2.5 concentrations were observed and showed a distinctive bimodal pattern with two marked peaks during the morning and evening rush hour times, due to dense traffic. The study observed higher PM_2.5 concentrations in winter when the northerly and northeasterly winds bring pollutants from the Chinese mainland, whereas southerly monsoon winds from the sea bring fresh air to the city in summer. In addition, higher concentrations of PM_2.5 were observed in rush hours on weekdays compared to weekends, suggesting the influence of anthropogenic activities on fine particulate levels, e.g., traffic-related local PM_2.5 emissions. To understand the spatial pattern of PM_2.5 concentrations in the context of the built-up environment of Hong Kong, we utilized MODerate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Thickness (AOT) 500 m data and visibility data to derive aerosol extinction profile, then converted to aerosol and PM_2.5 vertical profiles. A Geographic Information Systems (GIS) prototype was developed to integrate atmospheric PM_2.5 vertical profiles with 3D GIS data. An example of the query function in GIS prototype is given. The resulting 3D database of PM_2.5 concentrations provides crucial information to air quality regulators and decision makers to comply with air quality standards and in devising control strategies.

The effect of pressure pad location of spinal orthosis on the treatment of adolescent idiopathic scoliosis (AIS)

Patient with moderate AIS is usually prescribed with spinal orthosis aiming to mechanically support and prevent the spine from further deterioration. In the conventional fitting method, pre-brace X-ray is the main reference, thus, the pressure pad of spinal orthosis may not be accurately located to the strategic areas because the spinal deformities could change 3-dimensionally once pressure pad is applied. A high correlation (r > 0.98) between Cobb's angle and spinous process angle (SPA) was found in the recent studies. With the advancements of 3D clinical ultrasound (3D CUS), tracing SPA along a scoliotic spine becomes possible and this can be used to estimate Cobb's angle. This study aimed to evaluate the effect of pressure pad location of spinal orthosis in the treatment of AIS and 3D CUS was used to trace SPA for estimation of Cobb's angle. The in-brace X-rays were assessed for confirmation of treatment effectiveness. The subjects were divided into ultrasound-guided fitting group A (n=21) and conventional fitting group B (n=22). In the group A, pressure pads were tested at 5 locations - the prescribed location as in the conventional fitting (referred to the pre-brace X-ray), and 1 cm and 2 cm above and below the prescribed location, and 3D CUS was applied to trace the SPA in these 5 pad locations, and the pad location with the lowest estimated Cobb's angle was selected in the final fitting. The assessments of in-brace X-rays showed that the mean Cobb's angle of group A decreased from 28.9° (pre-brace) to 18.6° (immediate in-brace) while the mean Cobb's angle of group B decreased from 27.1° (pre-brace) to 22.5° (immediate in-brace). There was a significant difference (p < 0.05) in the correction of Cobb's angle between the two groups. The results showed that accurate pressure pad location does play an important role in the reduction of Cobb's angle and 3D CUS can be considered as a non-invasive and effective assessment tool to improve orthotic treatment of AIS.

The influence of the precursor and synthesis method on the CO2 capture capacity of carpet waste-based sorbents

Adsorption is one of the most promising technologies for reducing CO(2) emissions and at present several different types of sorbents are being investigated. The use of sorbents obtained from low-cost and abundant precursors (i.e. solid wastes) appears an attractive strategy to adopt because it will contribute to a reduction not only in operational costs but also in the amount of waste that is dumped and burned in landfills every year. Following on from previous studies by the authors, in this work several carbon-based adsorbents were developed from different carpet wastes (pre-consumer and post-consumer wastes) by chemical activation with KOH at various activation temperatures (600-900 °C) and KOH:char impregnation ratios (0.5:1 to 4:1). The prepared materials were characterised by chemical analysis and gas adsorption (N(2), -196 °C; CO(2), 0 °C), and tested for CO(2) adsorption at temperatures of 25 and 100 °C. It was found that both the type of precursor and the conditions of activation (i.e. impregnation ratios, and activation temperatures), had a huge influence on the microporosity of the resultant samples and their CO(2) capture capacities. The carbon-based adsorbent that presented the maximum CO(2) capture capacities at 25 and 100 °C (13.8 wt.% and 3.1 wt.%, respectively), was prepared from a pre-consumer carpet waste and was activated at 700 °C using a KOH:char impregnation ratio of 1:1. This sample showed the highest narrow microporosity volume (0.47 cm(3) g(-1)), thus confirming that only pores of less than 1 nm are effective for CO(2) adsorption at atmospheric pressure.

Size-effect induced short-range magnetic ordering in germanium nanostructures

Formation of ordered magnetic states in germanium nanostructures embedded in SiO2 has been investigated. Samples with the nanostructures were prepared by sputtering deposition on Si(100) substrates, followed by thermal annealing in vacuum. Transmission electron microscopy, energy dispersive X-ray spectrometry, and Raman spectroscopy have been used to characterize the samples. Magnetic measurements were performed using a superconducting quantum interference device. Size-effect induced magnetic orderings in the germanium nanostructures were found to be present at room temperatures and below. Superparamagnetic behavior was observed at temperatures above 230 K, whereas thermal excitation of spin reorientation and magnetic coupling has been revealed at temperatures below 60 K. Inverted hysteresis loops with negative remanences and multiple plateaus revealed the ferri- or antiferromagnetic nature of the coupling. Inter-domain coupling and effect of magnetic anisotropy will be discussed based on the experimental results and simulations with a spin reorientation model.

Application of 3-D ultrasound in assisting the fitting procedure of spinal orthosis to patients with adolescent idiopathic scoliosis

Spinal orthosis is generally applied to the patients with adolescent idiopathic scoliosis (AIS) during puberty to mechanically support the spine and prevent further deterioration. However, the optimum location of pressure is not easy to be determined and the X-ray taken is not a real time presentation of the spinal curvature. With the advancement of clinical ultrasound, tracing spinal processes along a scoliotic spine becomes possible, which means spinous process angle (SPA) can be obtained from ultrasound images. Moreover, SPA is found to be highly correlated with Cobb's angle. Since the outcome of orthotic intervention for AIS is considered to be associated with accurate orthosis fitting, this study seeks to apply three-dimensional (3-D) ultrasound in the fitting procedure of spinal orthosis for patients with AIS. The accuracy of pressure pad location in brace can help to improve the effectiveness of spinal orthosis treatment. By means of the ultrasound assessments, spinous process angle is examined and used as the parameter to evaluate the optimal location for pressure pad. The intra-rater reliability [ICC (1, 3)] for using ultrasound to measure SPA is >0.9 (p<0.05). Furthermore, the correlation between Cobb's angle estimated from the measurement of SPA in 3-D ultrasound images and Cobb's angle measured from X-ray is highly significant (R=0.98, p<0.01). According to these findings, ultrasound can be further developed as a non-invasive real-time assessment tool for spinal curvature especially in fitting stage to improve the treatment effect of the spinal orthosis.