Duy Tan University

IMPORTANCE: Cancer is the second leading cause of death worldwide. Current estimates on the burden of cancer are needed for cancer control planning. OBJECTIVE: To estimate mortality, incidence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 32 cancers in 195 countries and territories from 1990 to 2015. EVIDENCE REVIEW: Cancer mortality was estimated using vital registration system data, cancer registry incidence data (transformed to mortality estimates using separately estimated mortality to incidence [MI] ratios), and verbal autopsy data. Cancer incidence was calculated by dividing mortality estimates through the modeled MI ratios. To calculate cancer prevalence, MI ratios were used to model survival. To calculate YLDs, prevalence estimates were multiplied by disability weights. The YLLs were estimated by multiplying age-specific cancer deaths by the reference life expectancy. DALYs were estimated as the sum of YLDs and YLLs. A sociodemographic index (SDI) was created for each location based on income per capita, educational attainment, and fertility. Countries were categorized by SDI quintiles to summarize results. FINDINGS: In 2015, there were 17.5 million cancer cases worldwide and 8.7 million deaths. Between 2005 and 2015, cancer cases increased by 33%, with population aging contributing 16%, population growth 13%, and changes in age-specific rates contributing 4%. For men, the most common cancer globally was prostate cancer (1.6 million cases). Tracheal, bronchus, and lung cancer was the leading cause of cancer deaths and DALYs in men (1.2 million deaths and 25.9 million DALYs). For women, the most common cancer was breast cancer (2.4 million cases). Breast cancer was also the leading cause of cancer deaths and DALYs for women (523 000 deaths and 15.1 million DALYs). Overall, cancer caused 208.3 million DALYs worldwide in 2015 for both sexes combined. Between 2005 and 2015, age-standardized incidence rates for all cancers combined increased in 174 of 195 countries or territories. Age-standardized death rates (ASDRs) for all cancers combined decreased within that timeframe in 140 of 195 countries or territories. Countries with an increase in the ASDR due to all cancers were largely located on the African continent. Of all cancers, deaths between 2005 and 2015 decreased significantly for Hodgkin lymphoma (-6.1% [95% uncertainty interval (UI), -10.6% to -1.3%]). The number of deaths also decreased for esophageal cancer, stomach cancer, and chronic myeloid leukemia, although these results were not statistically significant. CONCLUSION AND RELEVANCE: As part of the epidemiological transition, cancer incidence is expected to increase in the future, further straining limited health care resources. Appropriate allocation of resources for cancer prevention, early diagnosis, and curative and palliative care requires detailed knowledge of the local burden of cancer. The GBD 2015 study results demonstrate that progress is possible in the war against cancer. However, the major findings also highlight an unmet need for cancer prevention efforts, including tobacco control, vaccination, and the promotion of physical activity and a healthy diet.

<h3>Importance</h3> Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. <h3>Objective</h3> To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. <h3>Evidence Review</h3> We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. <h3>Findings</h3> In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs). <h3>Conclusions and Relevance</h3> The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care.

The current outbreak of the novel coronavirus SARS-CoV-2 (coronavirus disease 2019; previously 2019-nCoV), epi-centred in Hubei Province of the People's Republic of China, has spread to many other countries. On 30. January 2020, the WHO Emergency Committee declared a global health emergency based on growing case notification rates at Chinese and international locations. The case detection rate is changing daily and can be tracked in almost real time on the website provided by Johns Hopkins University 1 and other forums. As of midst of February 2020, China bears the large burden of morbidity and mortality, whereas the incidence in other Asian countries, in Europe and North America remains low so far. Coronaviruses are enveloped, positive single-stranded large RNA viruses that infect humans, but also a wide range of animals. Coronaviruses were first described in 1966 by Tyrell and Bynoe, who cultivated the viruses from patients with common colds 2. Based on their morphology as spherical virions with a core shell and surface projections resembling a solar corona, they were termed coronaviruses (Latin: corona = crown). Four subfamilies, namely alpha-, beta-, gamma- and delta-coronaviruses exist. While alpha- and beta-coronaviruses apparently originate from mammals, in particular from bats, gamma- and delta-viruses originate from pigs and birds. The genome size varies between 26 kb and 32 kb. Among the seven subtypes of coronaviruses that can infect humans, the beta-coronaviruses may cause severe disease and fatalities, whereas alpha-coronaviruses cause asymptomatic or mildly symptomatic infections. SARS-CoV-2 belongs to the B lineage of the beta-coronaviruses and is closely related to the SARS-CoV virus 3, 4. The major four structural genes encode the nucleocapsid protein (N), the spike protein (S), a small membrane protein (SM) and the membrane glycoprotein (M) with an additional membrane glycoprotein (HE) occurring in the HCoV-OC43 and HKU1 beta-coronaviruses 5. SARS-CoV-2 is 96% identical at the whole-genome level to a bat coronavirus 4. SARS-CoV-2 apparently succeeded in making its transition from animals to humans on the Huanan seafood market in Wuhan, China. However, endeavours to identify potential intermediate hosts seem to have been neglected in Wuhan and the exact route of transmission urgently needs to be clarified. The initial clinical sign of the SARS-CoV-2-related disease COVID-19 which allowed case detection was pneumonia. More recent reports also describe gastrointestinal symptoms and asymptomatic infections, especially among young children 6. Observations so far suggest a mean incubation period of five days 7 and a median incubation period of 3 days (range: 0–24 days) 8. The proportion of individuals infected by SARS-CoV-2 who remain asymptomatic throughout the course of infection has not yet been definitely assessed. In symptomatic patients, the clinical manifestations of the disease usually start after less than a week, consisting of fever, cough, nasal congestion, fatigue and other signs of upper respiratory tract infections. The infection can progress to severe disease with dyspnoea and severe chest symptoms corresponding to pneumonia in approximately 75% of patients, as seen by computed tomography on admission 8. Pneumonia mostly occurs in the second or third week of a symptomatic infection. Prominent signs of viral pneumonia include decreased oxygen saturation, blood gas deviations, changes visible through chest X-rays and other imaging techniques, with ground glass abnormalities, patchy consolidation, alveolar exudates and interlobular involvement, eventually indicating deterioration. Lymphopenia appears to be common, and inflammatory markers (C-reactive protein and proinflammatory cytokines) are elevated. Recent investigations of 425 confirmed cases demonstrate that the current epidemic may double in the number of affected individuals every seven days and that each patient spreads infection to 2.2 other individuals on average (R0) 6. Estimates from the SARS-CoV outbreak in 2003 reported an R0 of 3 9. A recent data-driven analysis from the early phase of the outbreak estimates a mean R0 range from 2.2 to 3.58 10. Dense communities are at particular risk and the most vulnerable region certainly is Africa, due to dense traffic between China and Africa. Very few African countries have sufficient and appropriate diagnostic capacities and obvious challenges exist to handle such outbreaks. Indeed, the virus might soon affect Africa. WHO has identified 13 top-priority countries (Algeria, Angola, Cote d'Ivoire, the Democratic Republic of the Congo, Ethiopia, Ghana, Kenya, Mauritius, Nigeria, South Africa, Tanzania, Uganda, Zambia) which either maintain direct links to China or a high volume of travel to China. Recent studies indicate that patients ≥60 years of age are at higher risk than children who might be less likely to become infected or, if so, may show milder symptoms or even asymptomatic infection 7. As of 13. February 2020, the case fatality rate of COVID-19 infections has been approximately 2.2% (1370/60363; 13. February 2020, 06:53 PM CET); it was 9.6% (774/8096) in the SARS-CoV epidemic 11 and 34.4% (858/2494) in the MERS-CoV outbreak since 2012 12. Like other viruses, SARS-CoV-2 infects lung alveolar epithelial cells using receptor-mediated endocytosis via the angiotensin-converting enzyme II (ACE2) as an entry receptor 4. Artificial intelligence predicts that drugs associated with AP2-associated protein kinase 1 (AAK1) disrupting these proteins may inhibit viral entry into the target cells 13. Baricitinib, used in the treatment of rheumatoid arthritis, is an AAK1 and Janus kinase inhibitor and suggested for controlling viral replication 13. Moreover, one in vitro and a clinical study indicate that remdesivir, an adenosine analogue that acts as a viral protein inhibitor, has improved the condition in one patient 14, 15. Chloroquine, by increasing the endosomal pH required for virus-cell fusion, has the potential of blocking viral infection 15 and was shown to affect activation of p38 mitogen-activated protein kinase (MAPK), which is involved in replication of HCoV-229E 16. A combination of the antiretroviral drugs lopinavir and ritonavir significantly improved the clinical condition of SARS-CoV patients 17 and might be an option in COVID-19 infections. Further possibilities include leronlimab, a humanised monoclonal antibody (CCR5 antagonist), and galidesivir, a nucleoside RNA polymerase inhibitor, both of which have shown survival benefits in several deadly virus infections and are being considered as potential treatment candidates 18. Repurposing these available drugs for immediate use in treatment in SARS-CoV-2 infections could improve the currently available clinical management. Clinical trials presently registered at ClinicalTrials.gov focus on the efficacy of remdesivir, immunoglobulins, arbidol hydrochloride combined with interferon atomisation, ASC09F+Oseltamivir, ritonavir plus oseltamivir, lopinavir plus ritonavir, mesenchymal stem cell treatment, darunavir plus cobicistat, hydroxychloroquine, methylprednisolone and washed microbiota transplantation 19. Given the fragile health systems in most sub-Saharan African countries, new and re-emerging disease outbreaks such as the current COVID-19 epidemic can potentially paralyse health systems at the expense of primary healthcare requirements. The impact of the Ebola epidemic on the economy and healthcare structures is still felt five years later in those countries which were affected. Effective outbreak responses and preparedness during emergencies of such magnitude are challenging across African and other lower-middle-income countries. Such situations can partly only be mitigated by supporting existing regional and sub-Saharan African health structures.

<h3>Importance</h3> Liver cancer is among the leading causes of cancer deaths globally. The most common causes for liver cancer include hepatitis B virus (HBV) and hepatitis C virus (HCV) infection and alcohol use. <h3>Objective</h3> To report results of the Global Burden of Disease (GBD) 2015 study on primary liver cancer incidence, mortality, and disability-adjusted life-years (DALYs) for 195 countries or territories from 1990 to 2015, and present global, regional, and national estimates on the burden of liver cancer attributable to HBV, HCV, alcohol, and an “other” group that encompasses residual causes. <h3>Design, Settings, and Participants</h3> Mortality was estimated using vital registration and cancer registry data in an ensemble modeling approach. Single-cause mortality estimates were adjusted for all-cause mortality. Incidence was derived from mortality estimates and the mortality-to-incidence ratio. Through a systematic literature review, data on the proportions of liver cancer due to HBV, HCV, alcohol, and other causes were identified. Years of life lost were calculated by multiplying each death by a standard life expectancy. Prevalence was estimated using mortality-to-incidence ratio as surrogate for survival. Total prevalence was divided into 4 sequelae that were multiplied by disability weights to derive years lived with disability (YLDs). DALYs were the sum of years of life lost and YLDs. <h3>Main Outcomes and Measures</h3> Liver cancer mortality, incidence, YLDs, years of life lost, DALYs by etiology, age, sex, country, and year. <h3>Results</h3> There were 854 000 incident cases of liver cancer and 810 000 deaths globally in 2015, contributing to 20 578 000 DALYs. Cases of incident liver cancer increased by 75% between 1990 and 2015, of which 47% can be explained by changing population age structures, 35% by population growth, and −8% to changing age-specific incidence rates. The male-to-female ratio for age-standardized liver cancer mortality was 2.8. Globally, HBV accounted for 265 000 liver cancer deaths (33%), alcohol for 245 000 (30%), HCV for 167 000 (21%), and other causes for 133 000 (16%) deaths, with substantial variation between countries in the underlying etiologies. <h3>Conclusions and Relevance</h3> Liver cancer is among the leading causes of cancer deaths in many countries. Causes of liver cancer differ widely among populations. Our results show that most cases of liver cancer can be prevented through vaccination, antiviral treatment, safe blood transfusion and injection practices, as well as interventions to reduce excessive alcohol use. In line with the Sustainable Development Goals, the identification and elimination of risk factors for liver cancer will be required to achieve a sustained reduction in liver cancer burden. The GBD study can be used to guide these prevention efforts.

IMPORTANCE: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019) provided systematic estimates of incidence, morbidity, and mortality to inform local and international efforts toward reducing cancer burden. OBJECTIVE: To estimate cancer burden and trends globally for 204 countries and territories and by Sociodemographic Index (SDI) quintiles from 2010 to 2019. EVIDENCE REVIEW: The GBD 2019 estimation methods were used to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life years (DALYs) in 2019 and over the past decade. Estimates are also provided by quintiles of the SDI, a composite measure of educational attainment, income per capita, and total fertility rate for those younger than 25 years. Estimates include 95% uncertainty intervals (UIs). FINDINGS: In 2019, there were an estimated 23.6 million (95% UI, 22.2-24.9 million) new cancer cases (17.2 million when excluding nonmelanoma skin cancer) and 10.0 million (95% UI, 9.36-10.6 million) cancer deaths globally, with an estimated 250 million (235-264 million) DALYs due to cancer. Since 2010, these represented a 26.3% (95% UI, 20.3%-32.3%) increase in new cases, a 20.9% (95% UI, 14.2%-27.6%) increase in deaths, and a 16.0% (95% UI, 9.3%-22.8%) increase in DALYs. Among 22 groups of diseases and injuries in the GBD 2019 study, cancer was second only to cardiovascular diseases for the number of deaths, years of life lost, and DALYs globally in 2019. Cancer burden differed across SDI quintiles. The proportion of years lived with disability that contributed to DALYs increased with SDI, ranging from 1.4% (1.1%-1.8%) in the low SDI quintile to 5.7% (4.2%-7.1%) in the high SDI quintile. While the high SDI quintile had the highest number of new cases in 2019, the middle SDI quintile had the highest number of cancer deaths and DALYs. From 2010 to 2019, the largest percentage increase in the numbers of cases and deaths occurred in the low and low-middle SDI quintiles. CONCLUSIONS AND RELEVANCE: The results of this systematic analysis suggest that the global burden of cancer is substantial and growing, with burden differing by SDI. These results provide comprehensive and comparable estimates that can potentially inform efforts toward equitable cancer control around the world.

Importance: The increasing burden due to cancer and other noncommunicable diseases poses a threat to human development, which has resulted in global political commitments reflected in the Sustainable Development Goals as well as the World Health Organization (WHO) Global Action Plan on Non-Communicable Diseases. To determine if these commitments have resulted in improved cancer control, quantitative assessments of the cancer burden are required. Objective: To assess the burden for 29 cancer groups over time to provide a framework for policy discussion, resource allocation, and research focus. Evidence Review: Cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs) were evaluated for 195 countries and territories by age and sex using the Global Burden of Disease study estimation methods. Levels and trends were analyzed over time, as well as by the Sociodemographic Index (SDI). Changes in incident cases were categorized by changes due to epidemiological vs demographic transition. Findings: In 2016, there were 17.2 million cancer cases worldwide and 8.9 million deaths. Cancer cases increased by 28% between 2006 and 2016. The smallest increase was seen in high SDI countries. Globally, population aging contributed 17%; population growth, 12%; and changes in age-specific rates, -1% to this change. The most common incident cancer globally for men was prostate cancer (1.4 million cases). The leading cause of cancer deaths and DALYs was tracheal, bronchus, and lung cancer (1.2 million deaths and 25.4 million DALYs). For women, the most common incident cancer and the leading cause of cancer deaths and DALYs was breast cancer (1.7 million incident cases, 535 000 deaths, and 14.9 million DALYs). In 2016, cancer caused 213.2 million DALYs globally for both sexes combined. Between 2006 and 2016, the average annual age-standardized incidence rates for all cancers combined increased in 130 of 195 countries or territories, and the average annual age-standardized death rates decreased within that timeframe in 143 of 195 countries or territories. Conclusions and Relevance: Large disparities exist between countries in cancer incidence, deaths, and associated disability. Scaling up cancer prevention and ensuring universal access to cancer care are required for health equity and to fulfill the global commitments for noncommunicable disease and cancer control.

BACKGROUND: To contribute to the WHO initiative, VISION 2020: The Right to Sight, an assessment of global vision impairment in 2020 and temporal change is needed. We aimed to extensively update estimates of global vision loss burden, presenting estimates for 2020, temporal change over three decades between 1990-2020, and forecasts for 2050. METHODS: We did a systematic review and meta-analysis of population-based surveys of eye disease from January, 1980, to October, 2018. Only studies with samples representative of the population and with clearly defined visual acuity testing protocols were included. We fitted hierarchical models to estimate 2020 prevalence (with 95% uncertainty intervals [UIs]) of mild vision impairment (presenting visual acuity ≥6/18 and <6/12), moderate and severe vision impairment (<6/18 to 3/60), and blindness (<3/60 or less than 10° visual field around central fixation); and vision impairment from uncorrected presbyopia (presenting near vision <N6 or <N8 at 40 cm where best-corrected distance visual acuity is ≥6/12). We forecast estimates of vision loss up to 2050. FINDINGS: In 2020, an estimated 43·3 million (95% UI 37·6-48·4) people were blind, of whom 23·9 million (55%; 20·8-26·8) were estimated to be female. We estimated 295 million (267-325) people to have moderate and severe vision impairment, of whom 163 million (55%; 147-179) were female; 258 million (233-285) to have mild vision impairment, of whom 142 million (55%; 128-157) were female; and 510 million (371-667) to have visual impairment from uncorrected presbyopia, of whom 280 million (55%; 205-365) were female. Globally, between 1990 and 2020, among adults aged 50 years or older, age-standardised prevalence of blindness decreased by 28·5% (-29·4 to -27·7) and prevalence of mild vision impairment decreased slightly (-0·3%, -0·8 to -0·2), whereas prevalence of moderate and severe vision impairment increased slightly (2·5%, 1·9 to 3·2; insufficient data were available to calculate this statistic for vision impairment from uncorrected presbyopia). In this period, the number of people who were blind increased by 50·6% (47·8 to 53·4) and the number with moderate and severe vision impairment increased by 91·7% (87·6 to 95·8). By 2050, we predict 61·0 million (52·9 to 69·3) people will be blind, 474 million (428 to 518) will have moderate and severe vision impairment, 360 million (322 to 400) will have mild vision impairment, and 866 million (629 to 1150) will have uncorrected presbyopia. INTERPRETATION: Age-adjusted prevalence of blindness has reduced over the past three decades, yet due to population growth, progress is not keeping pace with needs. We face enormous challenges in avoiding vision impairment as the global population grows and ages. FUNDING: Brien Holden Vision Institute, Fondation Thea, Fred Hollows Foundation, Bill & Melinda Gates Foundation, Lions Clubs International Foundation, Sightsavers International, and University of Heidelberg.

BACKGROUND: Climate change can directly affect human health by varying exposure to non-optimal outdoor temperature. However, evidence on this direct impact at a global scale is limited, mainly due to issues in modelling and projecting complex and highly heterogeneous epidemiological relationships across different populations and climates. METHODS: We collected observed daily time series of mean temperature and mortality counts for all causes or non-external causes only, in periods ranging from Jan 1, 1984, to Dec 31, 2015, from various locations across the globe through the Multi-Country Multi-City Collaborative Research Network. We estimated temperature-mortality relationships through a two-stage time series design. We generated current and future daily mean temperature series under four scenarios of climate change, determined by varying trajectories of greenhouse gas emissions, using five general circulation models. We projected excess mortality for cold and heat and their net change in 1990-2099 under each scenario of climate change, assuming no adaptation or population changes. FINDINGS: Our dataset comprised 451 locations in 23 countries across nine regions of the world, including 85 879 895 deaths. Results indicate, on average, a net increase in temperature-related excess mortality under high-emission scenarios, although with important geographical differences. In temperate areas such as northern Europe, east Asia, and Australia, the less intense warming and large decrease in cold-related excess would induce a null or marginally negative net effect, with the net change in 2090-99 compared with 2010-19 ranging from -1·2% (empirical 95% CI -3·6 to 1·4) in Australia to -0·1% (-2·1 to 1·6) in east Asia under the highest emission scenario, although the decreasing trends would reverse during the course of the century. Conversely, warmer regions, such as the central and southern parts of America or Europe, and especially southeast Asia, would experience a sharp surge in heat-related impacts and extremely large net increases, with the net change at the end of the century ranging from 3·0% (-3·0 to 9·3) in Central America to 12·7% (-4·7 to 28·1) in southeast Asia under the highest emission scenario. Most of the health effects directly due to temperature increase could be avoided under scenarios involving mitigation strategies to limit emissions and further warming of the planet. INTERPRETATION: This study shows the negative health impacts of climate change that, under high-emission scenarios, would disproportionately affect warmer and poorer regions of the world. Comparison with lower emission scenarios emphasises the importance of mitigation policies for limiting global warming and reducing the associated health risks. FUNDING: UK Medical Research Council.

Microalgae has been consumed in human diet for thousands of years. It is an under-exploited crop for production of dietary foods. Microalgae cultivation does not compete with land and resources required for traditional crops and has a superior yield compared to terrestrial crops. Its high protein content has exhibited a huge potential to meet the dietary requirements of growing population. Apart from being a source of protein, presence of various bio-active components in microalgae provide an added health benefit. This review describes various microalgal sources of proteins and other bio-active components. One of the heavily studied group of bio-active components are pigments due to their anticarcenogenic, antioxidative and antihypertensive properties. Compared to various plant and floral species, microalgae contain higher amounts of pigments. Microalgal derived proteins have complete Essential Amino Acids (EAA) profiles and their protein content is higher than conventional sources such as meat, poultry and dairy products. However, microalgal based functional foods have not flooded the market. The lack of awareness coupled with scarce incentives for producers result in under-exploitation of microalgal potential. Application of microalgal derived components as dietary and nutraceutical supplements is discussed comprehensively. Keywords: Health, Human, Microalgae, Protein, Supplement

Indoor air pollution (IAP) is a serious threat to human health, causing millions of deaths each year. A plethora of pollutants can result in IAP; therefore, it is very important to identify their main sources and concentrations and to devise strategies for the control and enhancement of indoor air quality (IAQ). Herein, we provide a critical review and evaluation of the major sources of major pollutant emissions, their health effects, and issues related to IAP-based illnesses, including sick building syndrome (SBS) and building-related illness (BRI). In addition, the strategies and approaches for control and reduction of pollutant concentrations are pointed out, and the recent trends in efforts to resolve and improve IAQ, with their respective advantages and potentials, are summarized. It is predicted that the development of novel materials for sensors, IAQ-monitoring systems, and smart homes is a promising strategy for control and enhancement of IAQ in the future.

The current SMAC (Social, Mobile, Analytic, Cloud) technology trend paves the way to a future in which intelligent machines, networked processes and big data are brought together. This virtual world has generated vast amount of data which is accelerating the adoption of machine learning solutions & practices. Machine Learning enables computers to imitate and adapt human-like behaviour. Using machine learning, each interaction, each action performed, becomes something the system can learn and use as experience for the next time. This work is an overview of this data analytics method which enables computers to learn and do what comes naturally to humans, i.e. learn from experience. It includes the preliminaries of machine learning, the definition, nomenclature and applications' describing it's what, how and why. The technology roadmap of machine learning is discussed to understand and verify its potential as a market & industry practice. The primary intent of this work is to give insight into why machine learning is the future.

Introduction: Multiple myeloma (MM) is a plasma cell neoplasm with substantial morbidity and mortality. A comprehensive description of the global burden of MM is needed to help direct health policy, resource allocation, research, and patient care. Objective: To describe the burden of MM and the availability of effective therapies for 21 world regions and 195 countries and territories from 1990 to 2016. Design and Setting: We report incidence, mortality, and disability-adjusted life-year (DALY) estimates from the Global Burden of Disease 2016 study. Data sources include vital registration system, cancer registry, drug availability, and survey data for stem cell transplant rates. We analyzed the contribution of aging, population growth, and changes in incidence rates to the overall change in incident cases from 1990 to 2016 globally, by sociodemographic index (SDI) and by region. We collected data on approval of lenalidomide and bortezomib worldwide. Main Outcomes and Measures: Multiple myeloma mortality; incidence; years lived with disabilities; years of life lost; and DALYs by age, sex, country, and year. Results: Worldwide in 2016 there were 138 509 (95% uncertainty interval [UI], 121 000-155 480) incident cases of MM with an age-standardized incidence rate (ASIR) of 2.1 per 100 000 persons (95% UI, 1.8-2.3). Incident cases from 1990 to 2016 increased by 126% globally and by 106% to 192% for all SDI quintiles. The 3 world regions with the highest ASIR of MM were Australasia, North America, and Western Europe. Multiple myeloma caused 2.1 million (95% UI, 1.9-2.3 million) DALYs globally in 2016. Stem cell transplantation is routinely available in higher-income countries but is lacking in sub-Saharan Africa and parts of the Middle East. In 2016, lenalidomide and bortezomib had been approved in 73 and 103 countries, respectively. Conclusions and Relevance: Incidence of MM is highly variable among countries but has increased uniformly since 1990, with the largest increase in middle and low-middle SDI countries. Access to effective care is very limited in many countries of low socioeconomic development, particularly in sub-Saharan Africa. Global health policy priorities for MM are to improve diagnostic and treatment capacity in low and middle income countries and to ensure affordability of effective medications for every patient. Research priorities are to elucidate underlying etiological factors explaining the heterogeneity in myeloma incidence.

ConspectusPhotodynamic therapy (PDT) is a clinically approved therapeutic modality that has shown great potential for the treatment of cancers owing to its excellent spatiotemporal selectivity and inherently noninvasive nature. However, PDT has not reached its full potential, partly due to the lack of ideal photosensitizers. A common molecular design strategy for effective photosensitizers is to incorporate heavy atoms into photosensitizer structures, causing concerns about elevated dark toxicity, short triplet-state lifetimes, poor photostability, and the potentially high cost of heavy metals. To address these drawbacks, a significant advance has been devoted to developing advanced smart photosensitizers without the use of heavy atoms to better fit the clinical requirements of PDT. Over the past few years, heavy-atom-free nonporphyrinoid photosensitizers have emerged as an innovative alternative class of PSs due to their superior photophysical and photochemical properties and lower expense. Heavy-atom-free nonporphyrinoid photosensitizers have been widely explored for PDT purposes and have shown great potential for clinical oncologic applications. Although many review articles about heavy-atom-free photosensitizers based on porphyrinoid structure have been published, no specific review articles have yet focused on the heavy-atom-free nonporphyrinoid photosensitizers.In this account, the specific concept related to heavy-atom-free photosensitizers and the advantageous properties of heavy-atom-free photosensitizers for cancer theranostics will be briefly introduced. In addition, recent progress in the development of heavy-atom-free photosensitizers, ranging from molecular design approaches to recent innovative types of heavy-atom-free nonporphyrinoid photosensitizers, emphasizing our own research, will be presented. The main molecular design approaches to efficient heavy-atom-free PSs can be divided into six groups: (1) the approach based on traditional tetrapyrrole structures, (2) spin–orbit charge-transfer intersystem crossing (SOCT-ISC), (3) reducing the singlet–triplet energy gap (ΔEST), (4) the thionation of carbonyl groups of conventional fluorophores, (5) twisted π-conjugation system-induced intersystem crossing, and (6) radical-enhanced intersystem crossing. The innovative types of heavy-atom-free nonporphyrinoid photosensitizers and their applications in cancer diagnostics and therapeutics will be discussed in detail in the third section. Finally, the challenges that need to be addressed to develop optimal heavy-atom-free photosensitizers for oncologic photodynamic therapy and a perspective in this research field will be provided. We believe that this review will provide general guidance for the future design of innovative photosensitizers and spur preclinical and clinical studies for PDT-mediated cancer treatments.

The number of COVID-19 patients is dramatically increasing worldwide. Treatment in intensive care units (ICU) has become a major challenge; therefore, early recognition of severe forms is absolutely essential for timely triaging of patients. While the clinical status, in particular peripheral oxygen saturation (SpO2) levels, and concurrent comorbidities of COVID-19 patients largely determine the need for their admittance to ICUs, several laboratory parameters may facilitate the assessment of disease severity. Clinicians should consider low lymphocyte count as well as the serum levels of CRP, D-dimers, ferritin, cardiac troponin and IL-6, which may be used in risk stratification to predict severe and fatal COVID-19 in hospitalised patients. It is more likely that the course of the disease will be unfavourable if some or all of these parameters are altered.

The main objective of this study is to evaluate and compare the performance of different machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme Learning Machine (ELM), and Boosting Trees (Boosted) algorithms, considering the influence of various training to testing ratios in predicting the soil shear strength, one of the most critical geotechnical engineering properties in civil engineering design and construction. For this aim, a database of 538 soil samples collected from the Long Phu 1 power plant project, Vietnam, was utilized to generate the datasets for the modeling process. Different ratios (i.e., 10/90, 20/80, 30/70, 40/60, 50/50, 60/40, 70/30, 80/20, and 90/10) were used to divide the datasets into the training and testing datasets for the performance assessment of models. Popular statistical indicators, such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Correlation Coefficient (R), were employed to evaluate the predictive capability of the models under different training and testing ratios. Besides, Monte Carlo simulation was simultaneously carried out to evaluate the performance of the proposed models, taking into account the random sampling effect. The results showed that although all three ML models performed well, the ANN was the most accurate and statistically stable model after 1000 Monte Carlo simulations (Mean R = 0.9348) compared with other models such as Boosted (Mean R = 0.9192) and ELM (Mean R = 0.8703). Investigation on the performance of the models showed that the predictive capability of the ML models was greatly affected by the training/testing ratios, where the 70/30 one presented the best performance of the models. Concisely, the results presented herein showed an effective manner in selecting the appropriate ratios of datasets and the best ML model to predict the soil shear strength accurately, which would be helpful in the design and engineering phases of construction projects.

BACKGROUND: Few studies have examined variation in the associations between heat waves and mortality in an international context. OBJECTIVES: We aimed to systematically examine the impacts of heat waves on mortality with lag effects internationally. METHODS: We collected daily data of temperature and mortality from 400 communities in 18 countries/regions and defined 12 types of heat waves by combining community-specific daily mean temperature ≥90th, 92.5th, 95th, and 97.5th percentiles of temperature with duration ≥2, 3, and 4 d. We used time-series analyses to estimate the community-specific heat wave-mortality relation over lags of 0-10 d. Then, we applied meta-analysis to pool heat wave effects at the country level for cumulative and lag effects for each type of heat wave definition. RESULTS: Heat waves of all definitions had significant cumulative associations with mortality in all countries, but varied by community. The higher the temperature threshold used to define heat waves, the higher heat wave associations on mortality. However, heat wave duration did not modify the impacts. The association between heat waves and mortality appeared acutely and lasted for 3 and 4 d. Heat waves had higher associations with mortality in moderate cold and moderate hot areas than cold and hot areas. There were no added effects of heat waves on mortality in all countries/regions, except for Brazil, Moldova, and Taiwan. Heat waves defined by daily mean and maximum temperatures produced similar heat wave-mortality associations, but not daily minimum temperature. CONCLUSIONS: Results indicate that high temperatures create a substantial health burden, and effects of high temperatures over consecutive days are similar to what would be experienced if high temperature days occurred independently. People living in moderate cold and moderate hot areas are more sensitive to heat waves than those living in cold and hot areas. Daily mean and maximum temperatures had similar ability to define heat waves rather than minimum temperature. https://doi.org/10.1289/EHP1026.

Floods are one of nature's most destructive disasters because of the immense damage to land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods. Therefore, earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood disasters. In this study, we applied and assessed two new hybrid ensemble models, namely Dagging and Random Subspace (RS) coupled with Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Machine (SVM) which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin, the northern region of Bangladesh. The application of these models includes twelve flood influencing factors with 413 current and former flooding points, which were transferred in a GIS environment. The information gain ratio, the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential factors. For the validation and the comparison of these models, for the ability to predict the statistical appraisal measures such as Freidman, Wilcoxon signed-rank, and t-paired tests and Receiver Operating Characteristic Curve (ROC) were employed. The value of the Area Under the Curve (AUC) of ROC was above 0.80 for all models. For flood susceptibility modelling, the Dagging model performs superior, followed by RF, the ANN, the SVM, and the RS, then the several benchmark models. The approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.

absorbent surface chemicals and the addition of modifiers or nano-materials. Hence in the present review, the synthesis methods of GQDs and CQDs has been summarized and their characterization methods also been analyzed. The applications of carbon-based QDs (GQDs and CQDs) in biological and sensing areas, such as biological imaging, drug/gene delivery, antibacterial and antioxidant activity, photoluminescence sensors, electrochemiluminescence sensors and electrochemical sensors, have also been discussed. This study then covers sensing features of key neurotransmitters, including dopamine, tyrosine, epinephrine, norepinephrine, serotonin and acetylcholine. Hence, issues and challenges of the GQDs and CQDs were analyzed for their further development.

Since it was first discovered, thousands of years ago, silkworm silk has been known to be an abundant biopolymer with a vast range of attractive properties. The utilization of silk fibroin (SF), the main protein of silkworm silk, has not been limited to the textile industry but has been further extended to various high-tech application areas, including biomaterials for drug delivery systems and tissue engineering. The outstanding mechanical properties of SF, including its facile processability, superior biocompatibility, controllable biodegradation, and versatile functionalization have allowed its use for innovative applications. In this review, we describe the structure, composition, general properties, and structure-properties relationship of SF. In addition, the methods used for the fabrication and modification of various materials are briefly addressed. Lastly, recent applications of SF-based materials for small molecule drug delivery, biological drug delivery, gene therapy, wound healing, and bone regeneration are reviewed and our perspectives on future development of these favorable materials are also shared.

The coronavirus disease (COVID-19) pandemic has impacted the economy, livelihood, and physical and mental well-being of people worldwide. This study aimed to compare the mental health status during the pandemic in the general population of seven middle income countries (MICs) in Asia (China, Iran, Malaysia, Pakistan, Philippines, Thailand, and Vietnam). All the countries used the Impact of Event Scale-Revised (IES-R) and Depression, Anxiety and Stress Scale (DASS-21) to measure mental health. There were 4479 Asians completed the questionnaire with demographic characteristics, physical symptoms and health service utilization, contact history, knowledge and concern, precautionary measure, and rated their mental health with the IES-R and DASS-21. Descriptive statistics, One-Way analysis of variance (ANOVA), and linear regression were used to identify protective and risk factors associated with mental health parameters. There were significant differences in IES-R and DASS-21 scores between 7 MICs (p<0.05). Thailand had all the highest scores of IES-R, DASS-21 stress, anxiety, and depression scores whereas Vietnam had all the lowest scores. The risk factors for adverse mental health during the COVID-19 pandemic include age <30 years, high education background, single and separated status, discrimination by other countries and contact with people with COVID-19 (p<0.05). The protective factors for mental health include male gender, staying with children or more than 6 people in the same household, employment, confidence in doctors, high perceived likelihood of survival, and spending less time on health information (p<0.05). This comparative study among 7 MICs enhanced the understanding of metal health in the general population during the COVID-19 pandemic.