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Objectives: The purpose of this study was to investigate localised prostate cancer treated with or without neoadjuvant androgen deprivation therapy prior to robot-assisted laparoscopic prostatectomy, and the impact of Covid-19 treatment disruption, on clinico-pathologic outcomes. Patients and methods: Data was retrospectively collected from 124 consecutive patients treated with robot-assisted laparoscopic prostatectomy between November 2019–September 2020. Sixty-two patients were treated before 13 March 2020 (historic cohort) and 62 afterwards (covid cohort). Thirty-seven patients in the covid cohort additionally received neoadjuvant androgen deprivation therapy (mean duration of 3 months) consisting of bicalutamide 150 mg once a day for 4 weeks, with leuprolide 3.75 mg monthly injections commencing after week 1, up until the date of surgery. Results: Statistical analysis found no difference in peri-operative measures and length of stay for patients treated with or without neoadjuvant androgen deprivation therapy. Patients with delayed surgical treatment offered neoadjuvant androgen deprivation therapy showed a trend towards a reduction in positive surgical margins ( p=0.134), N1 disease ( p=0.424) and pathological down-staging (50% patients with pT2 disease). Patients within the covid cohort experienced significantly increased detectable prostate-specific antigen levels ( pConclusion: Our study demonstrated that a three-month duration of neoadjuvant androgen deprivation therapy prior to robot-assisted laparoscopic prostatectomy may improve pathological outcomes but this time-frame is inadequate to influence detectable prostate-specific antigen levels. Covid-19-related treatment delays led to significantly increased detectable prostate-specific antigen levels. Level of evidence: 2b

We have developed periscope, a tool for the detection and quantification of sub-genomic RNA (sgRNA) in SARS-CoV-2 genomic sequence data. The translation of the SARS-CoV-2 RNA genome for most open reading frames (ORFs) occurs via RNA intermediates termed “sub-genomic RNAs”. sgRNAs are produced through discontinuous transcription which relies on homology between transcription regulatory sequences (TRS-B) upstream of the ORF start codons and that of the TRS-L which is located in the 5’ UTR. TRS-L is immediately preceded by a leader sequence. This leader sequence is therefore found at the 5’ end of all sgRNA. We applied periscope to 1,155 SARS-CoV-2 genomes from Sheffield, UK and validated our findings using orthogonal datasets and in vitro cell systems. Using a simple local alignment to detect reads which contain the leader sequence we were able to identify and quantify reads arising from canonical and non-canonical sgRNA. We were able to detect all canonical sgRNAs at expected abundances, with the exception of ORF10. A number of recurrent non-canonical sgRNAs are detected. We show that the results are reproducible using technical replicates and determine the optimum number of reads for sgRNA analysis. In VeroE6 ACE2+/− cell lines, periscope can detect the changes in the kinetics of sgRNA in orthogonal sequencing datasets. Finally, variants found in genomic RNA are transmitted to sgRNAs with high fidelity in most cases. This tool can be applied to all sequenced COVID-19 samples worldwide to provide comprehensive analysis of SARS-CoV-2 sgRNA.

Policymakers and national, regional, and local authorities will require to cater to growing demands for public services and facilities, including the implementation of better and safer infrastructure. This should be conducted focusing on the urban poor and other vulnerable groups for their basic needs for transportation, housing, education, health care, and, more importantly, a safe and liveable urban environment. Meanwhile, pedestrians are often the most vulnerable road users in society, so investigating pedestrian accidents' causes and consequences is essential. Like neighboring countries in Asia, Indonesia experiences a high pedestrian fatality rate. This study investigates pedestrian perceptions toward traffic safety and identifies novel measures to improve pedestrian safety, with a particular focus on developing cities. Data collection involved self-reporting using questionnaires by respondents based in Denpasar, the capital city of Bali Province. Binary and multinomial logit models were estimated using pedestrian perception data to identify the factors that influence pedestrian accidents. This study found that reckless or careless driving/riding contributed significantly to pedestrian accidents at both night and day times. Besides, junctions and pedestrian crossings were perceived to be dangerous for pedestrians compared to other road infrastructure such as footpaths. The outcome of the study also reveals that motorcycles will be more influential for pedestrian accidents than cars. To reflect upon the findings, some countermeasures for enhancing pedestrian safety in Denpasar were discussed with attention to engineering, policy, enforcement, and education perspectives.