Who will use pre-exposure prophylaxis (PrEP) and why?: Understanding PrEP awareness and acceptability amongst men who have sex with men in the UK – a mixed methods study

Background: Recent clinical trials suggest that pre-exposure prophylaxis (PrEP) may reduce HIV transmission by up to 86% for men who have sex with men (MSM), whilst relatively high levels of PrEP acceptability have been reported to date. This study examines PrEP awareness amongst sub-groups of MSM communities and acceptability amongst MSM in a low prevalence region (Scotland, UK), using a mixed methods design. Methods: Quantitative surveys of n = 690 MSM recruited online via social and sociosexual media were analysed using descriptive statistics and multivariate logistic regression. In addition, n = 10 in-depth qualitative interviews with MSM were analysed thematically. Results: Under one third (29.7%) of MSM had heard of PrEP, with awareness related to living in large cities, degree level education, commercial gay scene use and reporting an HIV test in the last year. Just under half of participants (47.8%) were likely to use PrEP if it were available but there was no relationship between PrEP acceptability and previous PrEP awareness. Younger men (18–25 years) and those who report higher risk UAI were significantly more likely to say they would use PrEP. Qualitative data described specific PrEP scenarios, illustrating how risk, patterns of sexual practice and social relationships could affect motivation for and nature of PrEP use. Conclusion: These findings suggest substantial interest PrEP amongst MSM reporting HIV risk behaviours in Scotland. Given the Proud results, there is a strong case to investigate PrEP implementation within the UK. However, it appears that disparities in awareness have already emerged along traditional indicators of inequality. Our research identifies the need for comprehensive support when PrEP is introduced, including a key online component, to ensure equity of awareness across diverse MSM communities (e.g. by geography, education, gay scene use and HIV proximity), as well as to responding to the diverse informational and sexual health needs of all MSM communities

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Reduction in Radiation Exposure through a Stress Test Algorithm in an Emergency Department Observation Unit

Introduction: Clinicians are urged to decrease radiation exposure from unnecessary medical procedures. Many emergency department (ED) patients placed in an observation unit (EDOU) do not require chest pain evaluation with a nuclear stress test (NucST). We sought to implement a simple ST algorithm that favors non-nuclear stress test (Non-NucST) options to evaluate the effect of the algorithm on the proportion of patients exposed to radiation by comparing use of NucST versus Non-NucST pre- and post-algorithm.Methods: An ST algorithm was introduced favoring Non-NucST and limiting NucST to a subset of EDOU patients in October 2008. We analyzed aggregate data before (Jan-Sept 2008, period 1) and after (Jan-Sept 2009 and Jan-Sept 2010, periods 2 and 3 respectively) algorithm introduction. A random sample of 240 EDOU patients from each period was used to compare 30-day major adverse cardiac events (MACE). We calculated confidence intervals for proportions or the difference between two proportions.Results: A total of 5,047 STs were performed from Jan-Sept 2008-2010. NucST in the EDOU decreased after algorithm introduction from period 1 to 2 (40.7%, 95% CI [38.3-43.1] vs. 22.1%, 95% CI [20.1-24.1]), and remained at 22.1%, 95% CI [20.3-24.0] in period 3. There was no difference in 30-day MACE rates before and after algorithm use (0.1% for period 1 and 3, 0% for period 2).Conclusion: Use of a simple ST algorithm that favors non-NucST options decreases the proportion of EDOU chest pain patients exposed to radiation exposure from ST almost 50% by limiting NucST to a subset of patients, without a change in 30-day MACE

Reduction in Radiation Exposure through a Stress Test Algorithm in an Emergency Department Observation Unit

INTRODUCTION: Clinicians are urged to decrease radiation exposure from unnecessary medical procedures. Many emergency department (ED) patients placed in an observation unit (EDOU) do not require chest pain evaluation with a nuclear stress test (NucST). We sought to implement a simple ST algorithm that favors non-nuclear stress test (Non-NucST) options to evaluate the effect of the algorithm on the proportion of patients exposed to radiation by comparing use of NucST versus Non-NucST pre- and post-algorithm. METHODS: An ST algorithm was introduced favoring Non-NucST and limiting NucST to a subset of EDOU patients in October 2008. We analyzed aggregate data before (Jan-Sept 2008, period 1) and after (Jan-Sept 2009 and Jan-Sept 2010, periods 2 and 3 respectively) algorithm introduction. A random sample of 240 EDOU patients from each period was used to compare 30-day major adverse cardiac events (MACE). We calculated confidence intervals for proportions or the difference between two proportions. RESULTS: A total of 5,047 STs were performed from Jan-Sept 2008–2010. NucST in the EDOU decreased after algorithm introduction from period 1 to 2 (40.7%, 95% CI [38.3–43.1] vs. 22.1%, 95% CI [20.1–24.1]), and remained at 22.1%, 95% CI [20.3–24.0] in period 3. There was no difference in 30-day MACE rates before and after algorithm use (0.1% for period 1 and 3, 0% for period 2). CONCLUSION: Use of a simple ST algorithm that favors non-NucST options decreases the proportion of EDOU chest pain patients exposed to radiation exposure from ST almost 50% by limiting NucST to a subset of patients, without a change in 30-day MACE