First principles calculation of structural and magnetic properties for Fe monolayers and bilayers on W(110)

Structure optimizations were performed for 1 and 2 monolayers (ML) of Fe on a 5 ML W(110) substrate employing the all-electron full-potential linearized augmented plane-wave (FP-LAPW) method. The magnetic moments were also obtained for the converged and optimized structures. We find significant contractions ($\sim$ 10 %) for both the Fe-W and the neighboring Fe-Fe interlayer spacings compared to the corresponding bulk W-W and Fe-Fe interlayer spacings. Compared to the Fe bcc bulk moment of 2.2 $\mu_B$, the magnetic moment for the surface layer of Fe is enhanced (i) by 15% to 2.54 $\mu_B$ for 1 ML Fe/5 ML W(110), and (ii) by 29% to 2.84 $\mu_B$ for 2 ML Fe/5 ML W(110). The inner Fe layer for 2 ML Fe/5 ML W(110) has a bulk-like moment of 2.3 $\mu_B$. These results agree well with previous experimental data

Electron correlation effects and magnetic ordering at the Gd(0001) surface

Effects of electron correlation on the electronic structure and magnetic properties of the Gd(0001) surface are investigated using of the full-potential linearized augmented plane wave implementation of correlated band theory ("LDA+U"). The use of LDA+U instead of LDA (local density approximation) total energy calculations produces the correct ferromagnetic ground state for both bulk Gd and the Gd surface. Surface strain relaxation leads to an 90 % enhancement of the interlayer surface-to-bulk effective exchange coupling. Application of a Landau-Ginzburg type theory yields a 30 % enhancement of the Curie temperature at the surface, in very good agreement with the experiment.Comment: revised version: minor typos correcte

Cystatin C is associated with adverse COVID-19 outcomes in diverse populations

COVID-19 has highly variable clinical courses. The search for prognostic host factors for COVID-19 outcome is a priority. We performed logistic regression for ICU admission against a polygenic score (PGS) for Cystatin C (CyC) production in patients with COVID-19. We analyzed the predictive value of longitudinal plasma CyC levels in an independent cohort of patients hospitalized with COVID-19. In four cohorts spanning European and African ancestry populations, we identified a significant association between CyC-production PGS and odds of critical illness (n cases=2,319), with the strongest association captured in the UKB cohort (OR 2.13, 95% CI 1.58-2.87, p=7.12e-7). Plasma proteomics from an independent cohort of hospitalized COVID-19 patients ( n cases = 131) demonstrated that CyC production was associated with COVID-specific mortality (p=0.0007). Our findings suggest that CyC may be useful for stratification of patients and it has functional role in the host response to COVID-19.Peer reviewe

The role of the EP receptors for prostaglandin E2 in skin and skin cancer

One of the most common features of exposure of skin to ultraviolet (UV) light is the induction of inflammation, a contributor to tumorigenesis, which is characterized by the synthesis of cytokines, growth factors and arachidonic acid metabolites, including the prostaglandins (PGs). Studies on the role of the PGs in non-melanoma skin cancer (NMSC) have shown that the cyclooxygenase-2 (COX-2) isoform of the cyclooxygenases is responsible for the majority of the pathological effects of PGE2. In mouse skin models, COX-2 deficiency significantly protects against chemical carcinogen- or UV-induced NMSC while overexpression confers endogenous tumor promoting activity. Current studies are focused on identifying which of the G protein-coupled EP receptors mediate the tumor promotion/progression activities of PGE2 and the signaling pathways involved. As reviewed here, the EP1, EP2, and EP4 receptors, but not the EP3 receptor, contribute to NMSC development, albeit through different signaling pathways and with somewhat different outcomes. The signaling pathways activated by the specific EP receptors are context specific and likely depend on the level of PGE2 synthesis, the differential levels of expression of the different EP receptors, as well as the levels of expression of other interacting receptors. Understanding the role and mechanisms of action of the EP receptors potentially offers new targets for the prevention or therapy of NMSCs

Cystatin C is glucocorticoid responsive, directs recruitment of Trem2+ macrophages, and predicts failure of cancer immunotherapy

Cystatin C (CyC), a secreted cysteine protease inhibitor, has unclear biological functions. Many patients exhibit elevated plasma CyC levels, particularly during glucocorticoid (GC) treatment. This study links GCs with CyC’s systemic regulation by utilizing genome-wide association and structural equation modeling to determine CyC production genetics in the UK Biobank. Both CyC production and a polygenic score (PGS) capturing predisposition to CyC production were associated with increased all-cause and cancer-specific mortality. We found that the GC receptor directly targets CyC, leading to GC-responsive CyC secretion in macrophages and cancer cells. CyC-knockout tumors displayed significantly reduced growth and diminished recruitment of TREM2+ macrophages, which have been connected to cancer immunotherapy failure. Furthermore, the CyC-production PGS predicted checkpoint immunotherapy failure in 685 patients with metastatic cancer from combined clinical trial cohorts. In conclusion, CyC may act as a GC effector pathway via TREM2+ macrophage recruitment and may be a potential target for combination cancer immunotherapy.publishedVersio

A time-resolved proteomic and prognostic map of COVID-19

COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease

A proteomic survival predictor for COVID-19 patients in intensive care

Global healthcare systems are challenged by the COVID-19 pandemic. There is a need to optimize allocation of treatment and resources in intensive care, as clinically established risk assessments such as SOFA and APACHE II scores show only limited performance for predicting the survival of severely ill COVID-19 patients. Additional tools are also needed to monitor treatment, including experimental therapies in clinical trials. Comprehensively capturing human physiology, we speculated that proteomics in combination with new data-driven analysis strategies could produce a new generation of prognostic discriminators. We studied two independent cohorts of patients with severe COVID-19 who required intensive care and invasive mechanical ventilation. SOFA score, Charlson comorbidity index, and APACHE II score showed limited performance in predicting the COVID-19 outcome. Instead, the quantification of 321 plasma protein groups at 349 timepoints in 50 critically ill patients receiving invasive mechanical ventilation revealed 14 proteins that showed trajectories different between survivors and non-survivors. A predictor trained on proteomic measurements obtained at the first time point at maximum treatment level (i.e. WHO grade 7), which was weeks before the outcome, achieved accurate classification of survivors (AUROC 0.81). We tested the established predictor on an independent validation cohort (AUROC 1.0). The majority of proteins with high relevance in the prediction model belong to the coagulation system and complement cascade. Our study demonstrates that plasma proteomics can give rise to prognostic predictors substantially outperforming current prognostic markers in intensive care

Control of the induction of type I interferon by Peste des petits ruminants virus.

Peste des petits ruminants virus (PPRV) is a morbillivirus that produces clinical disease in goats and sheep. We have studied the induction of interferon-β (IFN-β) following infection of cultured cells with wild-type and vaccine strains of PPRV, and the effects of such infection with PPRV on the induction of IFN-β through both MDA-5 and RIG-I mediated pathways. Using both reporter assays and direct measurement of IFN-β mRNA, we have found that PPRV infection induces IFN-β only weakly and transiently, and the virus can actively block the induction of IFN-β. We have also generated mutant PPRV that lack expression of either of the viral accessory proteins (V&C) to characterize the role of these proteins in IFN-β induction during virus infection. Both PPRV_ΔV and PPRV_ΔC were defective in growth in cell culture, although in different ways. While the PPRV V protein bound to MDA-5 and, to a lesser extent, RIG-I, and over-expression of the V protein inhibited both IFN-β induction pathways, PPRV lacking V protein expression can still block IFN-β induction. In contrast, PPRV C bound to neither MDA-5 nor RIG-I, but PPRV lacking C protein expression lost the ability to block both MDA-5 and RIG-I mediated activation of IFN-β. These results shed new light on the inhibition of the induction of IFN-β by PPRV