Measuring rainfall from above and below the sea surface

Satellites play a major role in the determination of the rainfall at sea. Researchers at Southampton Oceanography Centre (SOC) have been involved in two projects addressing this task. First they have been instrumental in developing techniques to retrieve rain rate information from the 10+ years of dual-frequency altimeter data. The TOPEX radar measures rainfall via the attenuation it causes, producing a climatology that is independent of those derived from passive microwave (PM) and infrared (IR) sensors. Because TOPEX is an active microwave sensor, it can have a much smaller footprint than PM sensors. Therefore it can be used to estimate the size of rain cells, showing that the ITCZ and mid-latitude storm tracks are characterized by larger rain systems than elsewhere. TOPEX’s simultaneous recording of wind and wave data reveal that, for mid-latitude systems, rain is most likely in association with developing seas.All satellite-based datasets require validation, and SOC's work on the development and testing of acoustic rain gauges is the second aspect of this paper. By listening at a range of frequencies, an underwater hydrophone may distinguish the spectra of wind, rain, shipping etc., and estimate the wind speed or rain rate according to the magnitude of the signals. All our campaigns have shown a good acoustic response to changes in wind speed. However the quantitative inversion for recent trials has given values that are too high, possibly because of significant acoustic reflection from the sea bottom. The changes in spectral slope often agree with other observations of rain, although validation experiments in coastal regions are hampered by the extraneous sources present. Acoustic rain gauges would eventually see service not only for routine satellite validation, but also for real-time monitoring of locations of interest

Weathering the storm: developments in the acoustic sensing of wind and rain

An Acoustic Rain Gauge (ARG) analyses the underwater sound levels across a wide frequency range, classifies the observed spectrum according to likely source and then determines the local wind speed or rain rate as appropriate. Thispaper covers a trial on the Scotian Shelf off Canada, comparing the geophysical information derived from the acoustic signals with those obtained from other sources

The photochemistry of N-p-toluenesulfonyl peptides: the peptide bond as an electron donor

The scope of photobiological processes that involve absorbers within a protein matrix may be limited by the vulnerability of the peptide group to attack by highly reactive redox centers consequent upon electronic excitation. We have explored the nature of this vulnerability by undertaking comprehensive product analyses of aqueous photolysates of 12 N-p-toluene-sulfonyl peptides with systematically selected structures. The results indicate that degradation includes a major pathway that is initiated by intramolecular electron transfer in which the peptide bond serves as electron donor, and the data support the likelihood of a relay process in dipeptide derivatives

Ambient noise tomography reveals upper crustal structure of Icelandic rifts

The structure of oceanic spreading centres and subsurface melt distribution within newly formed crust is largely understood from marine seismic experiments. In Iceland, however, sub-aerial rift elevation allows both accurate surface mapping and the installation of large broadband seismic arrays. We present a study using ambient noise Rayleigh wave tomography to image the volcanic spreading centres across Iceland. Our high resolution model images a continuous band of low seismic velocities, parallelling all three segments of the branched rift in Iceland. The upper 10 km contains strong velocity variations, with shear wave velocities 0.5 km s$^{−1}$ faster in the older non-volcanically active regions compared to the active rifts. Slow velocities correlate very closely with geological surface mapping, with contours of the anomalies parallelling the edges of the neo-volcanic zones. The low-velocity band extends to the full 50 km width of the neo-volcanic zones, demonstrating a significant contrast with the narrow (8 km wide) magmatic zone seen at fast spreading ridges, where the rate of melt supply is similarly high. Within the seismically slow rift band, the lowest velocity cores of the anomalies occur above the centre of the mantle plume under the Vatnajökull icecap, and in the Eastern Volcanic Zone under the central volcano Katla. This suggests localisation of melt accumulation at these specific volcanic centres, demonstrating variability in melt supply into the shallow crust along the rift axis. Shear velocity inversions with depth show that the strongest velocity contrasts are found in the upper 8 km, and show a slight depression in the shear velocity through the mid crust (10–20 km) in the rifts. Our model also shows less intensity to the slow rift anomaly in the Western Volcanic Zone, supporting the notion that rift activity here is decreasing as the ridge jumps to the Eastern Volcanic Zone.Seismometers were borrowed from the Natural Environment Research Council (NERC) SEIS-UK (loans 968 and 1022). The work was funded by a graduate studentship from the NERC and research grants from the NERC (grants NE/F01140711, NE/M017427/1, NE/H025006/1) and the European Community's Seventh Framework Programme Grant No. 308377 (FUTUREVOLC) ... IMAGE project has received funding from the European Union's Seventh Programme for research, technological development and demonstration under grant agreement number 608553. Stations for this project were provided by the Geophysical Instrument Pool of Potsdam (GFZ). Dept. Earth Sciences, Cambridge contribution number ESC3818

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 hospitalization2–4 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

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

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

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio