It has become increasingly important to study the urban heat island phenomenon due to the adverse effects on summertime cooling energy demand, air and water quality and most importantly, heat-related illness and mortality. The present article analyses the magnitude and the characteristics of the urban heat island in Sydney, Australia. Climatic data from six meteorological stations distributed around the greater Sydney region and covering a period of 10 years are used. It is found that both strong urban heat island (UHI) and oasis phenomena are developed. The average maximum magnitude of the phenomena may exceed 6 K. The intensity and the characteristics of the phenomena are strongly influenced by the synoptic weather conditions and in particular the development of the sea breeze and the westerly winds from the desert area. The magnitude of the urban heat island varies between 0 and 11 • C, as a function of the prevailing weather conditions. The urban heat island mainly develops during the warm summer season while the oasis phenomenon is stronger during the winter and intermediate seasons. Using data from an extended network of stations the distribution of Cooling Degree Days in the greater Sydney area is calculated. It is found that because of the intense development of the UHI, Cooling Degree Days in Western Sydney are about three times higher than in the Eastern coastal zone. The present study will help us to better design and implement urban mitigation strategies to counterbalance the impact of the urban heat island in the city.

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Background Mismatch repair (MMR)/microsatellite instability (MSI) and tumor mutational burden (TMB) are independent biomarkers that complement each other for predicting immune checkpoint inhibitors (ICIs) efficacy. Here we aim to establish a strategy that integrates MSI and TMB determination for colorectal cancer (CRC) in one single assay. Methods Surgical or biopsy specimens retrospectively collected from CRC patients were subjected to NGS analysis. Immunohistochemistry (IHC) and polymerase chain reaction (PCR) were also used to determine MMR/MSI for those having enough tissues. The NGS-MSI method was validated against IHC and PCR. The MSI-high (MSI-H) or microsatellite stable (MSS) groups were further stratified based on tumor mutational burden, followed by validation using the The Cancer Genome Atlas (TCGA) CRC dataset. Immune microenvironment was evaluated for each subgroup be profiling the expression of immune signatures. Results Tissues from 430 CRC patients were analyzed using a 381-gene NGS panel. Alterations in KRAS, NRAS, BRAF, and HER2 occurred at a significantly higher incidence among MSI-H tumors than in MSS patients (83.6% vs. 58.4%, p = 0.0003). A subset comprising 98 tumors were tested for MSI/MMR using all three techniques, where NGS proved to be 99.0 and 93.9% concordant with PCR and IHC, respectively. Four of the 7 IHC-PCR discordant cases had low TMB (1.1–8.1 muts/Mb) and were confirmed to have been misdiagnosed by IHC. Intriguingly, 4 of the 66 MSS tumors (as determined by NGS) were defined as TMB-high (TMB-H) using a cut-off of 29 mut/Mb. Likewise, 15 of the 456 MSS tumors in the TCGA CRC cohort were also TMB-H with a cut-off of 9 muts/Mb. Expression of immune signatures across subgroups (MSS-TMB-H, MSI-H-TMB-H, and MSS-TMB-L) confirmed that the microenvironment of the MSS-TMB-H tumors was similar to that of the MSI-H-TMB-H tumors, but significantly more immune-responsive than that of the MSS-TMB-L tumors, indicating that MSI combined with TMB may be more precise than MSI alone for immune microenvironment prediction. Conclusion This study demonstrated that NGS panel-based method is both robust and tissue-efficient for comprehensive molecular diagnosis of CRC. It also underscores the importance of combining MSI and TMB information for discerning patients with different microenvironment.