Smoothed Particle Hydrodynamics with particle splitting, applied to self-gravitating collapse

We describe and demonstrate a method for increasing the resolution locally in a Smoothed Particle Hydrodynamic (SPH) simulation, by splitting particles. We show that in simulations of self-gravitating collapse (of the sort which are presumed to occur in star formation) the method is stable, and affords great savings in computer time and memory. When applied to the standard Boss & Bodenheimer test -- which has been shown to depend critically on fulfilment of the Jeans Condition -- the results are comparable both with those obtained using Adaptive Mesh Refinement, and with those obtained using a standard high-resolution SPH simulation, but they are achieved with considerably less computational resource. Further development and testing is required before the method can safely be applied to more general flows.Comment: 8 pages, 6 figure

Uncoupling vaccination from politics: a call to action

Political polarisation in the USA is impeding vaccination of the population against SARS-CoV-2. Today, the lowest COVID-19 vaccination rates in the USA are overwhelmingly in Republican-leaning states and counties. At a time when the delta variant is spreading, these are also the areas experiencing surges in admissions to hospital and intensive care.1 If political divides on COVID-19 vaccination become ingrained, the consequences could include greater resistance to all vaccination and outbreaks of other vaccine-preventable diseases. Understanding and countering this trend are urgent public health priorities

Confronting the evolution and expansion of anti-vaccine activism in the USA in the COVID-19 era

Over the past two decades, anti-vaccine activism in the USA has evolved from a fringe subculture into an increasingly well organised, networked movement with important repercussions for public health. The COVID-19 pandemic has exacerbated this evolution and magnified the reach of vaccine misinformation. Anti-vaccine activists, who for many years spoke primarily to niche communities hesitant about childhood vaccinations, have used traditional and social media to amplify vaccine-related mistruths about COVID-19 vaccines while also targeting historically marginalised racial and ethnic communities. These efforts contributed to COVID-19 vaccine hesitancy and expanded the movement, with early indications suggesting that this hesitancy could now also be increasing hesitancy that existed pre-pandemic towards other vaccines. It is important to understand the implications of this recent evolution of anti-vaccine activism on vaccination uptake and the promotion of sound public health strategies. In this Viewpoint, we summarise the latest developments in US-based anti-vaccine activism and propose strategies for confronting them

Assessment of droplet digital polymerase chain reaction for measuring BCR-ABL1 in chronic myeloid leukaemia in an international interlaboratory study

Measurement of BCR activator of RhoGEF and GTPase -ABL proto-oncogene 1, non-receptor tyrosine kinase (BCR-ABL1) mRNA levels by reverse transcription quantitative polymerase chain reaction (RTqPCR) has been critical to treatment protocols and clinical trials in chronic myeloid leukaemia; however, interlaboratory variation remains a significant issue. Reverse transcriptase droplet digital PCR (RTddPCR) has shown potential to improve testing but a large-scale interlaboratory study is required to definitively establish this. In the present study, 10 BCR-ABL1-positive samples with levels ranging from molecular response (MR)1·0–MR5·0 were tested by 23 laboratories using RTddPCR with the QXDX BCR-ABL %IS kit. A subset of participants tested the samples using RTqPCR. All 23 participants using RTddPCR detected BCR-ABL1 in all samples to MR4·0. Detection rates for deep-response samples were 95·7% at MR4·5, 78·3% at MR4·7 and 87·0% at MR5·0. Interlaboratory coefficient of variation was indirectly proportional to BCR-ABL1 level ranging from 29·3% to 69·0%. Linearity ranged from 0·9330 to 1·000 (average 0·9936). When results were compared for the 11 participants who performed both RTddPCR and RTqPCR, RTddPCR showed a similar limit of detection to RTqPCR with reduced interlaboratory variation and better assay linearity. The ability to detect deep responses with RTddPCR, matched with an improved linearity and reduced interlaboratory variation will allow improved patient management, and is of particular importance for future clinical trials focussed on achieving and maintaining treatment-free remission

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease