Reply to Comment by Velasco on “High-Resolution, Multilayer Modeling of Singapore’s Urban Climate Incorporating Local Climate Zones”

In response to the comment on our paper “High‐resolution, multilayer modeling of Singapore's urban climate incorporating local climate zones,” we provide detailed response to each of the incorrect accusations with scientifically based evidence. We have evaluated our model using all the available observational data, and the results showed good agreement. Our modeling study includes assumptions, as all modeling work does, and we have discussed their rationales and possible implications

Mapping trends in the care workforce using SOC 1990 and SOC 2000

NAT12/NAA30 knockdown resulted in dysregulation of the hypoxia response pathway as shown by microarray analysis. Asterisks signify p values and indicate level of significance. *=(p≈0.01-0.05), **=(p≈0.001-0.01)

Variability in detection of SARS-CoV-2-specific antibody responses following mild infection: a prospective multicentre cross-sectional study, London, United Kingdom, 17 April to 17 July 2020

Introduction Immunoassays targeting different SARS-CoV-2-specific antibodies are employed for seroprevalence studies. The degree of variability between immunoassays targeting anti-nucleocapsid (anti-NP; the majority) vs the potentially neutralising anti-spike antibodies (including anti-receptor-binding domain; anti-RBD), particularly in mild or asymptomatic disease, remains unclear. Aims We aimed to explore variability in anti-NP and anti-RBD antibody detectability following mild symptomatic or asymptomatic SARS-CoV-2 infection and analyse antibody response for correlation with symptomatology. Methods A multicentre prospective cross-sectional study was undertaken (April–July 2020). Paired serum samples were tested for anti-NP and anti-RBD IgG antibodies and reactivity expressed as binding ratios (BR). Multivariate linear regression was performed analysing age, sex, time since onset, symptomatology, anti-NP and anti-RBD antibody BR. Results We included 906 adults. Antibody results (793/906; 87.5%; 95% confidence interval: 85.2–89.6) and BR strongly correlated (ρ = 0.75). PCR-confirmed cases were more frequently identified by anti-RBD (129/130) than anti-NP (123/130). Anti-RBD testing identified 83 of 325 (25.5%) cases otherwise reported as negative for anti-NP. Anti-NP presence (+1.75/unit increase; p < 0.001), fever (≥ 38°C; +1.81; p < 0.001) or anosmia (+1.91; p < 0.001) were significantly associated with increased anti-RBD BR. Age (p = 0.85), sex (p = 0.28) and cough (p = 0.35) were not. When time since symptom onset was considered, we did not observe a significant change in anti-RBD BR (p = 0.95) but did note decreasing anti-NP BR (p < 0.001). Conclusion SARS-CoV-2 anti-RBD IgG showed significant correlation with anti-NP IgG for absolute seroconversion and BR. Higher BR were seen in symptomatic individuals, particularly those with fever. Inter-assay variability (12.5%) was evident and raises considerations for optimising seroprevalence testing strategies/studies

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children &lt;18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p&lt;0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p&lt;0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p&lt;0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

Urban heat island mitigation in Singapore: Evaluation using WRF/multilayer urban canopy model and local climate zones

© 2020 Elsevier B.V. Mitigation and adaption measures must be designed strategically by urban planners, designers, and decision-makers to reduce urban heat island (UHI) related risks. We employed the Weather Research and Forecasting (WRF) model to assess UHI mitigation scenarios for the tropical city of Singapore during April 2016, including two heat wave periods. The local climate zones for Singapore were used as the land use/land cover data to account for the intra-urban variability. The simulations show that the canopy layer UHI intensity in Singapore can reach up to 5 °C in compact areas during nighttime. The results reveal that city-scale deployment of cool roofs can provide an overall reduction of 1.3 °C in the near-surface daytime air temperature in large low-rise areas. Increasing the thermostat set temperature to 25 °C from 21 °C in city-wide buildings can potentially reduce the air temperature due to less (~20%) waste heat discharge from air-conditioning units. A densification scenario considering an increase from approximately 7 841 people/km2 (2016) to 9040-9,600 people/km2 (2030) under the current climate leads to air temperature increase of 1.4 °C, which demonstrates the importance of limiting the densification of less compact areas in maintaining thermal comfort in the future

Knockdown of NAT12/NAA30 reduces tumorigenic features of glioblastoma-initiating cells

Background Glioblastoma (GBM) is the most common primary brain malignancy and confers a dismal prognosis. GBMs harbor glioblastoma-initiating cells (GICs) that drive tumorigenesis and contribute to therapeutic resistance and tumor recurrence. Consequently, there is a strong rationale to target this cell population in order to develop new molecular therapies against GBM. Accumulating evidence indicates that Nα-terminal acetyltransferases (NATs), that are dysregulated in numerous human cancers, can serve as therapeutic targets. Methods Microarrays were used to study the expression of several NATs including NAT12/NAA30 in clinical samples and stem cell cultures. The expression of NAT12/NAA30 was analyzed using qPCR, immunolabeling and western blot. We conducted shRNA-mediated knockdown of NAT12/NAA30 gene in GICs and studied the effects on cell viability, sphere-formation and hypoxia sensitivity. Intracranial transplantation to SCID mice enabled us to investigate the effects of NAT12/NAA30 depletion in vivo. Using microarrays we identified genes and biochemical pathways whose expression was altered upon NAT12/NAA30 down-regulation. Results While decreased expression of the distal 3’UTR of NAT12/NAA30 was generally observed in GICs and GBMs, this gene was strongly up-regulated at the protein level in GBM and GICs. The increased protein levels were not caused by increased levels of the steady state mRNA but rather by other mechanisms. Also, shorter 3’UTR of NAT12/NAA30 correlated with poor survival in glioma patients. As well, we observed previously not described nuclear localization of this typically cytoplasmic protein. When compared to non-silencing controls, cells featuring NAT12/NAA30 knockdown exhibited reduced cell viability, sphere-forming ability, and mitochondrial hypoxia tolerance. Intracranial transplantation showed that knockdown of NAT12/NAA30 resulted in prolonged animal survival. Microarray analysis of the knockdown cultures showed reduced levels of HIF1α and altered expression of several other genes involved in the hypoxia response. Furthermore, NAT12/NAA30 knockdown correlated with expressional dysregulation of genes involved in the p53 pathway, ribosomal assembly and cell proliferation. Western blot analysis revealed reduction of HIF1α, phospho-MTOR(Ser2448) and higher levels of p53 and GFAP in these cultures. Conclusion NAT12/NAA30 plays an important role in growth and survival of GICs possibly by regulating hypoxia response (HIF1α), levels of p-MTOR (Ser2448) and the p53 pathway

Combined expressional analysis, bioinformatics and targeted proteomics identify new potential therapeutic targets in glioblastoma stem cells

Glioblastoma (GBM) is both the most common and the most lethal primary brain tumor. It is thought that GBM stem cells (GSCs) are critically important in resistance to therapy. Therefore, there is a strong rationale to target these cells in order to develop new molecular therapies.To identify molecular targets in GSCs, we compared gene expression in GSCs to that in neural stem cells (NSCs) from the adult human brain, using microarrays. Bioinformatic filtering identified 20 genes (PBK/TOPK, CENPA, KIF15, DEPDC1, CDC6, DLG7/DLGAP5/HURP, KIF18A, EZH2, HMMR/RHAMM/CD168, NOL4, MPP6, MDM1, RAPGEF4, RHBDD1, FNDC3B, FILIP1L, MCC, ATXN7L4/ATXN7L1, P2RY5/LPAR6 and FAM118A) that were consistently expressed in GSC cultures and consistently not expressed in NSC cultures. The expression of these genes was confirmed in clinical samples (TCGA and REMBRANDT). The first nine genes were highly co-expressed in all GBM subtypes and were part of the same protein-protein interaction network. Furthermore, their combined up-regulation correlated negatively with patient survival in the mesenchymal GBM subtype. Using targeted proteomics and the COGNOSCENTE database we linked these genes to GBM signalling pathways.Nine genes: PBK, CENPA, KIF15, DEPDC1, CDC6, DLG7, KIF18A, EZH2 and HMMR should be further explored as targets for treatment of GBM