1 Versus 2-cm Excision Margins for pT2-pT4 Primary Cutaneous Melanoma (MelMarT): A Feasibility Study

Abstract Background There is a lack of consensus regarding optimal surgical excision margins for primary cutaneous melanoma &gt; 1 mm in Breslow thickness (BT). A narrower surgical margin is expected to be associated with lower morbidity, improved quality of life (QoL), and reduced cost. We report the results of a pilot international study (MelMarT) comparing a 1 versus 2-cm surgical margin for patients with primary melanoma &gt; 1 mm in BT. Methods This phase III, multicentre trial [NCT02385214] administered by the Australia &amp; New Zealand Medical Trials Group (ANZMTG 03.12) randomised patients with a primary cutaneous melanoma &gt; 1 mm in BT to a 1 versus 2-cm wide excision margin to be performed with sentinel lymph node biopsy. Surgical closure technique was at the discretion of the treating surgeon. Patients’ QoL was measured (FACT-M questionnaire) at baseline, 3, 6, and 12 months after randomisation. Results Between January 2015 and June 2016, 400 patients were randomised from 17 centres in 5 countries. A total of 377 patients were available for analysis. Primary melanomas were located on the trunk (56.9%), extremities (35.6%), and head and neck (7.4%). More patients in the 2-cm margin group required reconstruction (34.9 vs. 13.6%; p &lt; 0.0001). There was an increased wound necrosis rate in the 2-cm arm (0.5 vs. 3.6%; p = 0.036). After 12 months’ follow-up, no differences were noted in QoL between groups. Discussion This pilot study demonstrates the feasibility of a large international RCT to provide a definitive answer to the optimal excision margin for patients with intermediate- to high-risk primary cutaneous melanoma. </jats:sec

Host adaptation and unexpected symbiont partners enable reef-building corals to tolerate extreme temperatures

© 2016 John Wiley & Sons Ltd. Understanding the potential for coral adaptation to warming seas is complicated by interactions between symbiotic partners that define stress responses and the difficulties of tracking selection in natural populations. To overcome these challenges, we characterized the contribution of both animal host and symbiotic algae to thermal tolerance in corals that have already experienced considerable warming on par with end-of-century projections for most coral reefs. Thermal responses in Platygyra daedalea corals from the hot Persian Gulf where summer temperatures reach 36°C were compared with conspecifics from the milder Sea of Oman. Persian Gulf corals had higher rates of survival at elevated temperatures (33 and 36°C) in both the nonsymbiotic larval stage (32-49% higher) and the symbiotic adult life stage (51% higher). Additionally, Persian Gulf hosts had fixed greater potential to mitigate oxidative stress (31-49% higher) and their Symbiodinium partners had better retention of photosynthetic performance under elevated temperature (up to 161% higher). Superior thermal tolerance of Persian Gulf vs. Sea of Oman corals was maintained after 6-month acclimatization to a common ambient environment and was underpinned by genetic divergence in both the coral host and symbiotic algae. In P. daedalea host samples, genomewide SNP variation clustered into two discrete groups corresponding with Persian Gulf and Sea of Oman sites. Symbiodinium within host tissues predominantly belonged to ITS2 rDNA type C3 in the Persian Gulf and type D1a in the Sea of Oman contradicting patterns of Symbiodinium thermal tolerance from other regions. Our findings provide evidence that genetic adaptation of both host and Symbiodinium has enabled corals to cope with extreme temperatures in the Persian Gulf. Thus, the persistence of coral populations under continued warming will likely be determined by evolutionary rates in both, rather than single, symbiotic partners

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)

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

Scoping review of indicators and methods of measurement used to evaluate the impact of dog population management interventions

Background: Dogs are ubiquitous in human society and attempts to manage their populations are common to most countries. Managing dog populations is achieved through a range of interventions to suit the dog population dynamics and dog ownership characteristics of the location, with a number of potential impacts or goals in mind. Impact assessment provides the opportunity for interventions to identify areas of inefficiencies for improvement and build evidence of positive change. Methods: This scoping review collates 26 studies that have assessed the impacts of dog population management interventions. Results: It reports the use of 29 indicators of change under 8 categories of impact and describes variation in the methods used to measure these indicators. Conclusion: The relatively few published examples of impact assessment in dog population management suggest this field is in its infancy; however this review highlights those notable exceptions. By describing those indicators and methods of measurement that have been reported thus far, and apparent barriers to efficient assessment, this review aims to support and direct future impact assessment

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

Language endangerment and language documentation in Africa

Non peer reviewe

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

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