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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.

The macrophage is a prominent inflammatory cell in wounds, but its role in healing remains incompletely understood. Macrophages have many functions in wounds, including host defence, the promotion and resolution of inflammation, the removal of apoptotic cells, and the support of cell proliferation and tissue restoration following injury. Recent studies suggest that macrophages exist in several different phenotypic states within the healing wound and that the influence of these cells on each stage of repair varies with the specific phenotype. Although the macrophage is beneficial to the repair of normally healing wounds, this pleotropic cell type may promote excessive inflammation or fibrosis under certain circumstances. Emerging evidence suggests that macrophage dysfunction is a component of the pathogenesis of nonhealing and poorly healing wounds. As a result of advances in the understanding of this multifunctional cell, the macrophage continues to be an attractive therapeutic target, both to reduce fibrosis and scarring, and to improve healing of chronic wounds.

Information about the frequency and intensity of extreme precipitation is generally derived from fitting extreme value models using point‐observations, but the regionalization of these models is challenging. Here we propose using high‐resolution convection‐permitting climate model output as covariates for the estimation of observation‐based spatial rainfall return levels. We apply the Weather and Forecasting Research (WRF) model at a 1.5 km resolution driven by ERA5 reanalysis data over southern Germany, where 1,132 rain gauges provide observations of daily rainfall. For this complex topography, we build three different smooth spatial Generalized Extreme Value (GEV) models: (a) a reference model using latitude, longitude and elevation as covariates; (b) a model adding mean annual precipitation from the WRF; (c) a model adding extreme value statistical model estimates using WRF output. We show that the additional information provided by the WRF model can improve the representation of 10‐year and 100‐year return levels of daily rainfall by lowering the percentage bias, mean absolute error, and root‐mean‐square error. Furthermore, we conduct an extensive cross‐validation, where only 5%, 10%, 20%, 50%, 80%, 90%, and 95% of all rain gauges are considered when building spatial GEV models. Again, the additional information provided by the WRF model can improve results here. This cross‐validation study also highlights the robustness of our approach, showing great potential for use in data‐scarce regions. Plain Language Summary Heavy rainfall can trigger floods or landslides. In order to estimate the occurrence probability of these events, statistical models can be built using rainfall observations. However, these measurements are mostly point measurements and hence, one needs to interpolate in space when performing regional analyses. Often, topographical features such as elevation, latitude, and longitude are chosen as auxiliary variables to facilitate this interpolation. Here, we propose to add high‐resolution climate simulations as covariates. We compare three different setups which use data over southern Germany, where a dense rain gauge coverage is available: (a) a reference model using latitude, longitude, and elevation as covariates; (b) a model adding mean annual precipitation from the climate simulation; (c) a model adding extreme value statistical model estimates using data from the climate simulation. We show that the additional information provided by the climate model can improve the spatial representation of extreme daily rainfall. In most parts of the world, the rain gauge density is less than in the study area. Therefore, we test our three approaches with smaller subsets of the observational data. Our approach shows robustness under these conditions, highlighting potential for regions where observational coverage is scarcer but high‐resolution climate simulations are available. Key Points We utilize high‐resolution climate model data as covariates in spatial Generalized Extreme Value models to assess extreme precipitation Compared to using only topographical information, adding climate model data can improve the representation of 10‐ and 100‐year return levels An extensive cross‐validation study shows great potential of our approach for data‐scarce regions

In the era of big data, developing next-generation self-powered continuous energy harvesting systems is of great importance. Taking advantage of fallen leaves’ specific structural advantage gifted by nature, we propose a facile approach to convert fallen leaves into energy harvesters from ubiquitous moisture, based on surface treatments and asymmetric coating of hygroscopic iron hydrogels. Upon moisture absorption, a water gradient is established between areas with/without hydrogel coating, and maintained due to gel-like behaviors and leaf veins for water retention and diffusion restriction, thus forming electrical double layers over the leaf surface and showing capacitance-like behavior for energy charging and discharging. Besides, the specific leaf cell structures with small grooves enabled uniform carbon coatings instead of aggregations, and high electrical conductivity, resulting in 49 μA/cm 2 and 497 μW/cm 3 electrical output, achieving competitive performance with the state-of-art and potential for lower environmental impact compared to other types of energy harvesters. In this work, authors convert fallen leaves into energy harvesters using hygroscopic iron hydrogel, achieving continuous power generation from moisture. The device delivers high current density and power output with potential for lower environmental impact compared to alternative harvesters.

Chronic wounds are a common complication in patients with diabetes that often lead to amputation. These non-healing wounds are described as being stuck in a persistent inflammatory state characterized by accumulation of pro-inflammatory macrophages, cytokines and proteases. Some medications approved for management of type 2 diabetes have demonstrated anti-inflammatory properties independent of their marketed insulinotropic effects and thus have underappreciated potential to promote wound healing. In this review, the potential for insulin, metformin, specific sulfonylureas, thiazolidinediones, and dipeptidyl peptidase-4 inhibitors to promote healing is evaluated by reviewing human and animal studies on inflammation and wound healing. The available evidence indicates that diabetic medications have potential to prevent wounds from becoming arrested in the inflammatory stage of healing and to promote wound healing by downregulating pro-inflammatory cytokines, upregulating growth factors, lowering matrix metalloproteinases, stimulating angiogenesis, and increasing epithelization. However, no clinical recommendations currently exist on the potential for specific diabetic medications to impact healing of chronic wounds. Thus, we encourage further research that may guide physicians on providing personalized diabetes treatments that achieve glycemic goals while promoting healing in patients with chronic wounds.

Monocytes (Mo) and macrophages (Mϕ) play important roles in normal skin wound healing, and dysregulation of wound Mo/Mϕ leads to impaired wound healing in diabetes. Although skin wound Mϕ originate both from tissue resident Mϕ and infiltrating bone marrow-derived Mo, the latter play dominant roles during the inflammatory phase of wound repair. Increased production of bone marrow Mo caused by alterations of hematopoietic stem and progenitor cell (HSPC) niche and epigenetic modifications of HSPCs likely contributes to the enhanced number of wound Mϕ in diabetes. In addition, an impaired transition of diabetic wound Mϕ from \"pro-inflammatory\" to \"pro-healing\" phenotypes driven by the local wound environment as well as intrinsic changes in bone marrow Mo is also thought to be partly responsible for impaired diabetic wound healing. The current brief review describes the origin, heterogeneity and function of wound Mϕ during normal skin wound healing followed by discussion of how dysregulated wound Mϕ numbers and phenotype are associated with impaired diabetic wound healing. The review also highlights the possible links between altered bone marrow myelopoiesis and increased Mo production as well as extrinsic and intrinsic factors that drive wound macrophage dysregulation leading to impaired wound healing in diabetes.

Elucidation of the chain of disease transmission and identification of the source of coronavirus disease 2019 (COVID-19) infections are crucial for effective disease containment. We describe an epidemiological investigation that, with use of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serological assays, established links between three clusters of COVID-19. In Singapore, active case-finding and contact tracing were undertaken for all COVID-19 cases. Diagnosis for acute disease was confirmed with RT-PCR testing. When epidemiological information suggested that people might have been nodes of disease transmission but had recovered from illness, SARS-CoV-2 IgG serology testing was used to establish past infection. Three clusters of COVID-19, comprising 28 locally transmitted cases, were identified in Singapore; these clusters were from two churches (Church A and Church B) and a family gathering. The clusters in Church A and Church B were linked by an individual from Church A (A2), who transmitted SARS-CoV-2 infection to the primary case from Church B (F1) at a family gathering they both attended on Jan 25, 2020. All cases were confirmed by RT-PCR testing because they had active disease, except for A2, who at the time of testing had recovered from their illness and tested negative. This individual was eventually diagnosed with past infection by serological testing. ELISA assays showed an optical density of more than 1·4 for SARS-CoV-2 nucleoprotein and receptor binding domain antigens in titres up to 1/400, and viral neutralisation was noted in titres up to 1/320. Development and application of a serological assay has helped to establish connections between COVID-19 clusters in Singapore. Serological testing can have a crucial role in identifying convalescent cases or people with milder disease who might have been missed by other surveillance methods. National Research Foundation (Singapore), National Natural Science Foundation (China), and National Medical Research Council (Singapore).

Inflammation in the central nervous system (CNS) and disruption of its immune privilege are major contributors to the pathogenesis of multiple sclerosis (MS) and of its rodent counterpart, experimental autoimmune encephalomyelitis (EAE). We have previously identified developmental endothelial locus-1 (Del-1) as an endogenous anti-inflammatory factor, which inhibits integrin-dependent leukocyte adhesion. Here we show that Del-1 contributes to the immune privilege status of the CNS. Intriguingly, Del-1 expression decreased in chronic-active MS lesions and in the inflamed CNS in the course of EAE. Del-1-deficiency was associated with increased EAE severity, accompanied by increased demyelination and axonal loss. As compared with control mice, Del-1 −/− mice displayed enhanced disruption of the blood–brain barrier and increased infiltration of neutrophil granulocytes in the spinal cord in the course of EAE, accompanied by elevated levels of inflammatory cytokines, including interleukin-17 (IL-17). The augmented levels of IL-17 in Del-1-deficiency derived predominantly from infiltrated CD8 + T cells. Increased EAE severity and neutrophil infiltration because of Del-1-deficiency was reversed in mice lacking both Del-1 and IL-17 receptor, indicating a crucial role for the IL-17/neutrophil inflammatory axis in EAE pathogenesis in Del-1 −/− mice. Strikingly, systemic administration of Del-1-Fc ameliorated clinical relapse in relapsing–remitting EAE. Therefore, Del-1 is an endogenous homeostatic factor in the CNS protecting from neuroinflammation and demyelination. Our findings provide mechanistic underpinnings for the previous implication of Del-1 as a candidate MS susceptibility gene and suggest that Del-1-centered therapeutic approaches may be beneficial in neuroinflammatory and demyelinating disorders.

The Nod-like receptor protein (NLRP)-3 inflammasome/IL-1β pathway is involved in the pathogenesis of various inflammatory skin diseases, but its biological role in wound healing remains to be elucidated. Since inflammation is typically thought to impede healing, we hypothesized that loss of NLRP-3 activity would result in a downregulated inflammatory response and accelerated wound healing. NLRP-3 null mice, caspase-1 null mice and C57Bl/6 wild type control mice (WT) received four 8 mm excisional cutaneous wounds; inflammation and healing were assessed during the early stage of wound healing. Consistent with our hypothesis, wounds from NLRP-3 null and caspase-1 null mice contained lower levels of the pro-inflammatory cytokines IL-1β and TNF-α compared to WT mice and had reduced neutrophil and macrophage accumulation. Contrary to our hypothesis, re-epithelialization, granulation tissue formation, and angiogenesis were delayed in NLRP-3 null mice and caspase-1 null mice compared to WT mice, indicating that NLRP-3 signaling is important for early events in wound healing. Topical treatment of excisional wounds with recombinant IL-1β partially restored granulation tissue formation in wounds of NLRP-3 null mice, confirming the importance of NLRP-3-dependent IL-1β production during early wound healing. Despite the improvement in healing, angiogenesis and levels of the pro-angiogenic growth factor VEGF were further reduced in IL-1β treated wounds, suggesting that IL-1β has a negative effect on angiogenesis and that NLRP-3 promotes angiogenesis in an IL-1β-independent manner. These findings indicate that the NLRP-3 inflammasome contributes to the early inflammatory phase following skin wounding and is important for efficient healing.

SummaryComorbidity and hip fracture independently increased mortality risk for 9 years in both sexes, with a significant additive interaction in the first year among women and through 6 years among men.IntroductionHip fracture is associated with a persistently elevated mortality risk, but it is unknown whether the elevated risk is due to the fracture or to pre-fracture comorbidity.MethodsIn a population-based study in Singapore with 9 years of follow-up, patients age > 50 with first hip fracture from 2008 to 2017 were pair-matched to a cohort without hip fracture by age, sex, ethnicity, and pre-fracture Charlson Comorbidity Index (CCI). We investigated additive interaction using the relative excess risk due to interaction (RERI) and multiplicative interaction using the ratio of relative risks.ResultsTwenty-two thousand five hundred ninety of 22,826 patients with a first hip fracture in 2008–2017 were successfully matched. Hip fracture and comorbidity independently increased mortality risk for 9 years in both sexes. After adjustment for comorbidity, excess mortality risk continued to persist for 9 years post-fracture in both men and women. Women with a hip fracture and pre-fracture CCI > 4 had a higher relative risk (RR) of mortality at 9 years of 3.29 [95% confidence interval (CI) 3.01, 3.59] than those without comorbidity (RR 1.51, 95%CI 1.36, 1.68) compared to the referent without hip fracture or comorbidity. An additive interaction between hip fracture and pre-fracture CCI > 4 was observed in the first post-fracture year` [relative excess risk due to interaction (RERI) 1.99, 95%CI 0.97, 3.01]. For men with CCI ≥ 4, the positive additive interaction was observed through 6 years.ConclusionsExcess mortality risks post-fracture are attributable to both the fracture and pre-fracture comorbidity. Early interventions in hip fracture patients with high comorbidity could reduce their excess mortality.