Revised Lithostratigraphy of the Sonsela Member (Chinle Formation, Upper Triassic) in the Southern Part of Petrified Forest National Park, Arizona

BACKGROUND: Recent revisions to the Sonsela Member of the Chinle Formation in Petrified Forest National Park have presented a three-part lithostratigraphic model based on unconventional correlations of sandstone beds. As a vertebrate faunal transition is recorded within this stratigraphic interval, these correlations, and the purported existence of a depositional hiatus (the Tr-4 unconformity) at about the same level, must be carefully re-examined. METHODOLOGY/PRINCIPAL FINDINGS: Our investigations demonstrate the neglected necessity of walking out contacts and mapping when constructing lithostratigraphic models, and providing UTM coordinates and labeled photographs for all measured sections. We correct correlation errors within the Sonsela Member, demonstrate that there are multiple Flattops One sandstones, all of which are higher than the traditional Sonsela sandstone bed, that the Sonsela sandstone bed and Rainbow Forest Bed are equivalent, that the Rainbow Forest Bed is higher than the sandstones at the base of Blue Mesa and Agate Mesa, that strata formerly assigned to the Jim Camp Wash beds occur at two stratigraphic levels, and that there are multiple persistent silcrete horizons within the Sonsela Member. CONCLUSIONS/SIGNIFICANCE: We present a revised five-part model for the Sonsela Member. The units from lowest to highest are: the Camp Butte beds, Lot's Wife beds, Jasper Forest bed (the Sonsela sandstone)/Rainbow Forest Bed, Jim Camp Wash beds, and Martha's Butte beds (including the Flattops One sandstones). Although there are numerous degradational/aggradational cycles within the Chinle Formation, a single unconformable horizon within or at the base of the Sonsela Member that can be traced across the entire western United States (the "Tr-4 unconformity") probably does not exist. The shift from relatively humid and poorly-drained to arid and well-drained climatic conditions began during deposition of the Sonsela Member (low in the Jim Camp Wash beds), well after the Carnian-Norian transition

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

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

Les progrès dans la réalisation de la classification quantitative de la psychopathologie

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level'' dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity'' by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach. (C) 2020 Published by Elsevier Masson SAS

Novel pleiotropic risk loci for melanoma and nevus density implicate multiple biological pathways.

The total number of acquired melanocytic nevi on the skin is strongly correlated with melanoma risk. Here we report a meta-analysis of 11 nevus GWAS from Australia, Netherlands, UK, and USA comprising 52,506 individuals. We confirm known loci including MTAP, PLA2G6, and IRF4, and detect novel SNPs in KITLG and a region of 9q32. In a bivariate analysis combining the nevus results with a recent melanoma GWAS meta-analysis (12,874 cases, 23,203 controls), SNPs near GPRC5A, CYP1B1, PPARGC1B, HDAC4, FAM208B, DOCK8, and SYNE2 reached global significance, and other loci, including MIR146A and OBFC1, reached a suggestive level. Overall, we conclude that most nevus genes affect melanoma risk (KITLG an exception), while many melanoma risk loci do not alter nevus count. For example, variants in TERC and OBFC1 affect both traits, but other telomere length maintenance genes seem to affect melanoma risk only. Our findings implicate multiple pathways in nevogenesis

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

Further insights into the molecular complexity of the human sinus node - The role of 'novel' transcription factors and microRNAs

Research purpose: The sinus node (SN) is the heart's primary pacemaker. Key ion channels (mainly the funny channel, HCN4) and Ca2+-handling proteins in the SN are responsible for its function. Transcription factors (TFs) regulate gene expression through inhibition or activation and microRNAs (miRs) do this through inhibition. There is high expression of macrophages and mast cells within the SN connective tissue. ‘Novel’/unexplored TFs and miRs in the regulation of ion channels and immune cells in the SN are not well understood. Using RNAseq and bioinformatics, the expression profile and predicted interaction of key TFs and cell markers with key miRs in the adult human SN vs. right atrial tissue (RA) were determined. Principal results: 68 and 60 TFs significantly more or less expressed in the SN vs. RA respectively. Among those more expressed were ISL1 and TBX3 (involved in embryonic development of the SN) and ‘novel’ RUNX1-2, CEBPA, GLI1-2 and SOX2. These TFs were predicted to regulate HCN4 expression in the SN. Markers for different cells: fibroblasts (COL1A1), fat (FABP4), macrophages (CSF1R and CD209), natural killer (GZMA) and mast (TPSAB1) were significantly more expressed in the SN vs. RA. Interestingly, RUNX1-3, CEBPA and GLI1 also regulate expression of these cells. MiR-486-3p inhibits HCN4 and markers involved in immune response. Major conclusions: In conclusion, RUNX1-2, CSF1R, TPSAB1, COL1A1 and HCN4 are highly expressed in the SN but not miR-486-3p. Their complex interactions can be used to treat SN dysfunction such as bradycardia. Interestingly, another research group recently reported miR-486-3p is upregulated in blood samples from severe COVID-19 patients who suffer from bradycardia.</p

Guideline-indicated treatments and diagnostics, GRACE risk score, and survival for non-ST elevation myocardial infarction

Aim: To investigate whether improved survival from NSTEMI, according to GRACE risk score, was associated with guideline-indicated treatments and diagnostics, and persisted after hospital discharge. Methods and results: National cohort study (n=389,507 patients, n=232 hospitals, MINAP registry), 2003-13. The primary outcome was adjusted all-cause survival estimated using flexible parametric survival modelling with time-varying covariates over a median follow-up of 2.3-years. Receipt of all eligible treatments (optimal care) was inversely related to risk status: 25.6% in low, 18.6% in intermediate and 11.5% in high risk NSTEMI. At 30 days, the use of optimal care was associated with improved survival among high (adjusted hazard ratio [aHR]=0.66 [95% CI 0.53-0.86], difference in absolute mortality rate per 100 patients [AMR/100] –0.19 [95% CI –0.29 to –0.08]), and intermediate (aHR=0.74 [95% CI 0.62-0.92]; AMR/100 –0.15 [95% CI –0.23 to –0.08]) risk NSTEMI. At the end of follow-up (8.4 years), the significant association between the use of all eligible guideline-indicated treatments and improved survival remained only for high risk NSTEMI (aHR=0.66 [95% CI 0.50-0.96]; AMR/100= –0.03 [95% CI –0.06 to –0.01]). For low risk NSTEMI, there was no association between the use of optimal care and improved survival at 30 days (aHR=0.92 [95% CI 0.69-1.38] and at 8.4 years (aHR=0.71 [95% CI 0.39-3.74]). Conclusions: Optimal use of guideline-indicated care for NSTEMI was associated with greater survival gains with increasing GRACE risk, but its use decreased with increasing GRACE risk