Effects of housing environments on COVID-19 transmission and mental health revealed by COVID-19 Participant Experience data from the All of Us Research Program in the USA: a case-control study.

OBJECTIVES: To examine the association between housing types and COVID-19 infection (or mental health) during the early stages of the pandemic by using the large-scale individual-level All of Us Research Program COVID-19 Participant Experience (COPE) survey data. We hypothesise that housing types with a shared component are associated with elevated COVID-19 infection and subsequent mental health conditions. DESIGN: A retrospective case-control study. SETTING: Secondary analysis of online surveys conducted in the USA. PARTICIPANTS: 62 664 participant responses to COPE from May to July 2020. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome measure is the self-reported COVID-19 status, and the secondary outcome measures are anxiety or stress. Both measures were applied for matched cases and controls of the same race, sex, age group and survey version. RESULTS: A multiple logistic regression analysis revealed that housing types with a shared component are significantly associated with COVID-19 infection (OR=1.19, 95% CI 1.1 to 1.3; p=2×10-4), anxiety (OR=1.26, 95% CI 1.1 to 1.4; p=1.1×10-6) and stress (OR=1.29, 95% CI 1.2 to 1.4; p=4.3×10-10) as compared with free-standing houses, after adjusting for confounding factors. Further, frequent optional shopping or outing trips, another indicator of the built environment, are also associated with COVID-19 infection (OR=1.36, 95% CI 1.1 to 1.8; p=0.02), but not associated with elevated mental health conditions. Confounding factors are controlled in the analysis such as ethnicity, age, social distancing behaviour and house occupancy. CONCLUSION: Our study demonstrates that houses with a shared component tend to have an increased risk of COVID-19 transmission, which consequently leads to high levels of anxiety and stress for their dwellers. The study also suggests the necessity to improve the quality of the built environment such as residential housing and its surroundings through planning, design and management, ensuring a more resilient society that can cope with future pandemics.

Comparison and impact of COVID-19 for patients with cancer: a survival analysis of fatality rate controlling for age, sex and cancer type.

OBJECTIVES: Prior research has reported an increased risk of fatality for patients with cancer, but most studies investigated the risk by comparing cancer to non-cancer patients among COVID-19 infections, where cancer might have contributed to the increased risk. This study is to understand COVID-19's imposed HR of fatality while controlling for covariates, such as age, sex, metastasis status and cancer type. METHODS: We conducted survival analyses of 4606 cancer patients with COVID-19 test results from 16 March to 11 October 2020 in UK Biobank and estimated the overall HR of fatality with and without COVID-19 infection. We also examined the HRs of 13 specific cancer types with at least 100 patients using a stratified analysis. RESULTS: COVID-19 resulted in an overall HR of 7.76 (95% CI 5.78 to 10.40, p<10-10) by following 4606 patients with cancer for 21 days after the tests. The HR varied among cancer type, with over a 10-fold increase in fatality rate (false discovery rate ≤0.02) for melanoma, haematological malignancies, uterine cancer and kidney cancer. Although COVID-19 imposed a higher risk for localised versus distant metastasis cancers, those of distant metastases yielded higher overall fatality rates due to their multiplicative effects. DISCUSSION: The results confirmed prior reports for the increased risk of fatality for patients with COVID-19 plus hematological malignancies and demonstrated similar findings of COVID-19 on melanoma, uterine, and kidney cancers. CONCLUSION: The results highlight the heightened risk that COVID-19 imposes on localised and haematological cancer patients and the necessity to vaccinate uninfected patients with cancer promptly, particularly for the cancer types most influenced by COVID-19. Results also suggest the importance of timely care for patients with localised cancer, whether they are infected by COVID-19 or not.

On fusion methods for knowledge discovery from multi-omics datasets.

Recent years have witnessed the tendency of measuring a biological sample on multiple omics scales for a comprehensive understanding of how biological activities on varying levels are perturbed by genetic variants, environments, and their interactions. This new trend raises substantial challenges to data integration and fusion, of which the latter is a specific type of integration that applies a uniform method in a scalable manner, to solve biological problems which the multi-omics measurements target. Fusion-based analysis has advanced rapidly in the past decade, thanks to application drivers and theoretical breakthroughs in mathematics, statistics, and computer science. We will briefly address these methods from methodological and mathematical perspectives and categorize them into three types of approaches: data fusion (a narrowed definition as compared to the general data fusion concept), model fusion, and mixed fusion. We will demonstrate at least one typical example in each specific category to exemplify the characteristics, principles, and applications of the methods in general, as well as discuss the gaps and potential issues for future studies.

Tryptophan-based fluorophores for studying protein conformational changes.

With the continuing interest in deciphering the interplay between protein function and conformational changes, small fluorescence probes will be especially useful for tracking changes in the crowded protein interior space. Presently, we describe the potential utility of six unnatural amino acid fluorescence donors structurally related to tryptophan and show how they can be efficiently incorporated into a protein as fluorescence probes. We also examine the various photophysical properties of the new Trp analogues, which are significantly redshifted in their fluorescence spectra relative to tryptophan. In general, the Trp analogues were well tolerated when inserted into Escherichia coli DHFR, and did not perturb enzyme activity, although substitution for Trp22 did result in a diminution in DHFR activity. Further, it was demonstrated that D and E at position 37 formed efficient FRET pairs with acridon-2-ylalanine (Acd) at position 17. The same was also true for a DHFR construct containing E at position 79 and Acd at position 17. Together, these findings demonstrate that these tryptophan analogues can be introduced into DHFR with minimal disruption of function, and that they can be employed for the selective study of targeted conformational changes in proteins, even in the presence of unmodified tryptophans.