High resolution imaging of the M​L​ 2.9 August 2019 earthquake in Lancashire, UK, induced by hydraulic fracturing during Preston New Road PNR-2 operations

Hydraulic fracturing (HF) at Preston New Road (PNR), Lancashire, United Kingdom, in August 2019, induced a number of felt earthquakes. The largest event (⁠ML 2.9) occurred on 26 August 2019, approximately three days after HF operations at the site had stopped. Following this, in November 2019, the United Kingdom Government announced a moratorium on HF for shale gas in England. Here we provide an analysis of the microseismic observations made during this case of HF‐induced fault activation. More than 55,000 microseismic events were detected during operations using a downhole array, the vast majority measuring less than Mw 0. Event locations revealed the growth of hydraulic fractures and their interaction with several preexisting structures. The spatiotemporal distribution of events suggests that a hydraulic pathway was created between the injection points and a nearby northwest–southeast‐striking fault, on which the largest events occurred. The aftershocks of the ML 2.9 event clearly delineate the rupture plane, with their spatial distribution forming a halo of activity around the mainshock rupture area. Across clusters of events, the magnitude distributions are distinctly bimodal, with a lower Gutenberg–Richter b‐value for events above Mw 0, suggesting a break in scaling between events associated with hydraulic fracture propagation, and events associated with activation of the fault. This poses a challenge for mitigation strategies that rely on extrapolating microseismicity observed during injection to forecast future behavior. The activated fault was well oriented for failure in the regional stress field, significantly more so than the fault activated during previous operations at PNR in 2018. The differing orientations within the stress field likely explain why this PNR‐2 fault produced larger events compared with the 2018 sequence, despite receiving a smaller volume of injected fluid. This indicates that fault orientation and in situ stress conditions play a key role in controlling the severity of seismicity induced by HF

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Impacts of Deep Learning to Detect Induced Seismicity: a Case Study from Preston New Road, UK

Machine learning (ML) phase pickers, like PhaseNet, have emerged as valuable tools for automated phase picking. However, their potential benefits have been largely unexplored in induced microseismicity (Mw < 0). We address this critical research gap by investigating the implications of ML-enhanced phase detection for induced microseismicity at unconventional exploration sites.We applied PhaseNet to a high-frequency (2000 Hz) borehole seismic dataset from a shale gas exploration site, Preston New Road (PNR-1z), UK. Despite being trained on 100 Hz data, PhaseNet detects over 52,000 earthquakes (with 15,800 being newly identified) in a 3-month period. In comparison, the well operator’s prior method, Coalescence Microseismic Mapping, detected over 38,400 events within the -2.8 < Mw < 1.1 magnitude range.We address challenges in magnitude estimation due to waveform clipping by calibrating a coda duration-magnitude scale for larger, clipped event waveforms and the new events. We demonstrate that off-the-shelf PhaseNet detects numerous new small events (Mw < −0.5). This results in denser sampling of magnitude distributions and a lower magnitude of completeness, which affects Gutenberg-Richter b-value estimation. These findings have implications for improving seismic hazard assessments and enable a higher resolution analysis of the spatio-temporal evolution of induced microseismicity

Ambient Seismic Recordings and Distributed Acoustic Sensing (DAS): Imaging the firn layer on Rutford Ice Stream, Antarctica

This dataset contains the following files: 1. 7 hours of continuous DAS data (100 Hz sampling): 2020-01-14T00:00:19.598000Zoffset_****.mseed, with offset referring to the distance from the DAS channel to the interrogator. 2. Corresponding 7 hours of vertical component continuous geophone (A000, located at DAS channel offset 550 m) data