Soft X-ray resonant scattering study of single-crystal LaSr2_2Mn2_2O7_7

Soft X-ray resonant scattering studies at the Mn $L_{\texttt{II, III}}$- and the La $M_{\texttt{IV, V}}$- edges of single-crystal LaSr$_2$Mn$_2$O$_7$ are reported. At low temperatures, below $T_\texttt{N} \approx 160$ K, energy scans with a fixed momentum transfer at the \emph{A}-type antiferromagnetic (0 0 1) reflection around the Mn $L_{\texttt{II, III}}$-edges with incident linear $\sigma$ and $\pi$ polarizations show strong resonant enhancements. The splitting of the energy spectra around the Mn $L_{\texttt{II, III}}$-edges may indicate the presence of a mixed valence state, e.g., Mn$^{3+}$/Mn$^{4+}$. The relative intensities of the resonance and the clear shoulder-feature as well as the strong incident $\sigma$ and $\pi$ polarization dependences strongly indicate its complex electronic origin. Unexpected enhancement of the charge Bragg (0 0 2) reflection at the La $M_{\texttt{IV, V}}$-edges with $\sigma$ polarization has been observed up to 300 K, with an anomaly appearing around the orbital-ordering transition temperature, $T_{\texttt{OO}} \approx 220$ K, suggesting a strong coupling (competition) between them.Comment: Accepted by European Physical Journal

DDX3 depletion represses translation of mRNAs with complex 5' UTRs

DDX3 is an RNA chaperone of the DEAD-box family that regulates translation. Ded1, the yeast ortholog of DDX3, is a global regulator of translation, whereas DDX3 is thought to preferentially affect a subset of mRNAs. However, the set of mRNAs that are regulated by DDX3 are unknown, along with the relationship between DDX3 binding and activity. Here, we use ribosome profiling, RNA-seq, and PAR-CLIP to define the set of mRNAs that are regulated by DDX3 in human cells. We find that while DDX3 binds highly expressed mRNAs, depletion of DDX3 particularly affects the translation of a small subset of the transcriptome. We further find that DDX3 binds a site on helix 16 of the human ribosomal rRNA, placing it immediately adjacent to the mRNA entry channel. Translation changes caused by depleting DDX3 levels or expressing an inactive point mutation are different, consistent with different association of these genetic variant types with disease. Taken together, this work defines the subset of the transcriptome that is responsive to DDX3 inhibition, with relevance for basic biology and disease states where DDX3 is altered

Data quality considerations for evaluating COVID-19 treatments using real world data: learnings from the National COVID Cohort Collaborative (N3C)

Background: Multi-institution electronic health records (EHR) are a rich source of real world data (RWD) for generating real world evidence (RWE) regarding the utilization, benefits and harms of medical interventions. They provide access to clinical data from large pooled patient populations in addition to laboratory measurements unavailable in insurance claims-based data. However, secondary use of these data for research requires specialized knowledge and careful evaluation of data quality and completeness. We discuss data quality assessments undertaken during the conduct of prep-to-research, focusing on the investigation of treatment safety and effectiveness. Methods: Using the National COVID Cohort Collaborative (N3C) enclave, we defined a patient population using criteria typical in non-interventional inpatient drug effectiveness studies. We present the challenges encountered when constructing this dataset, beginning with an examination of data quality across data partners. We then discuss the methods and best practices used to operationalize several important study elements: exposure to treatment, baseline health comorbidities, and key outcomes of interest. Results: We share our experiences and lessons learned when working with heterogeneous EHR data from over 65 healthcare institutions and 4 common data models. We discuss six key areas of data variability and quality. (1) The specific EHR data elements captured from a site can vary depending on source data model and practice. (2) Data missingness remains a significant issue. (3) Drug exposures can be recorded at different levels and may not contain route of administration or dosage information. (4) Reconstruction of continuous drug exposure intervals may not always be possible. (5) EHR discontinuity is a major concern for capturing history of prior treatment and comorbidities. Lastly, (6) access to EHR data alone limits the potential outcomes which can be used in studies. Conclusions: The creation of large scale centralized multi-site EHR databases such as N3C enables a wide range of research aimed at better understanding treatments and health impacts of many conditions including COVID-19. As with all observational research, it is important that research teams engage with appropriate domain experts to understand the data in order to define research questions that are both clinically important and feasible to address using these real world data

Intraislet glucagon signaling is critical for maintaining glucose homeostasis

Glucagon, a hormone released from pancreatic a cells, plays a key role in maintaining proper glucose homeostasis and has been implicated in the pathophysiology of diabetes. In vitro studies suggest that intraislet glucagon can modulate the function of pancreatic ß cells. However, because of the lack of suitable experimental tools, the in vivo physiological role of this intraislet cross-talk has remained elusive. To address this issue, we generated a mouse model that selectively expressed an inhibitory designer GPCR (Gi DREADD) in a cells only. Drug-induced activation of this inhibitory designer receptor almost completely shut o? glucagon secretion in vivo, resulting in markedly impaired insulin secretion, hyperglycemia, and glucose intolerance. Additional studies with mouse and human islets indicated that intraislet glucagon stimulates insulin release primarily by activating β cell GLP-1 receptors. These fndings strongly suggest that intraislet glucagon signaling is essential for maintaining proper glucose homeostasis in vivo. Our work may pave the way toward the development of novel classes of antidiabetic drugs that act by modulating intraislet cross-talk between a and ß cells

Diabetes medications and associations with Covid-19 outcomes in the N3C database: A national retrospective cohort study

Background While vaccination is the most important way to combat the SARS-CoV-2 pandemic, there may still be a need for early outpatient treatment that is safe, inexpensive, and currently widely available in parts of the world that do not have access to the vaccine. There are in-silico, in-vitro, and in-tissue data suggesting that metformin inhibits the viral life cycle, as well as observational data suggesting that metformin use before infection with SARS-CoV2 is associated with less severe COVID-19. Previous observational analyses from single-center cohorts have been limited by size. Methods Conducted a retrospective cohort analysis in adults with type 2 diabetes (T2DM) for associations between metformin use and COVID-19 outcomes with an active comparator design of prevalent users of therapeutically equivalent diabetes monotherapy: metformin versus dipeptidyl-peptidase-4-inhibitors (DPP4i) and sulfonylureas (SU). This took place in the National COVID Cohort Collaborative (N3C) longitudinal U.S. cohort of adults with +SARS-CoV-2 result between January 1 2020 to June 1 2021. Findings included hospitalization or ventilation or mortality from COVID-19. Back pain was assessed as a negative control outcome. Results 6,626 adults with T2DM and +SARS-CoV-2 from 36 sites. Mean age was 60.7 +/- 12.0 years; 48.7% male; 56.7% White, 21.9% Black, 3.5% Asian, and 16.7% Latinx. Mean BMI was 34.1 +/- 7.8kg/m2. Overall 14.5% of the sample was hospitalized; 1.5% received mechanical ventilation; and 1.8% died. In adjusted outcomes, compared to DPP4i, metformin had non-significant associations with reduced need for ventilation (RR 0.68, 0.32–1.44), and mortality (RR 0.82, 0.41–1.64). Compared to SU, metformin was associated with a lower risk of ventilation (RR 0.5, 95% CI 0.28–0.98, p = 0.044) and mortality (RR 0.56, 95% CI 0.33–0.97, p = 0.037). There was no difference in unadjusted or adjusted results of the negative control. Conclusions There were clinically significant associations between metformin use and less severe COVID-19 compared to SU, but not compared to DPP4i. New-user studies and randomized trials are needed to assess early outpatient treatment and post-exposure prophylaxis with therapeutics that are safe in adults, children, pregnancy and available worldwide

A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative

Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients’ predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm's parameters and data-related modeling choices are also both crucial and challenging. In this paper we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques. We demonstrate the feasibility of our approach on a large cohort of type-2 diabetes patients provided by the National COVID Cohort Collaborative (N3C) Enclave, where we explored the influence of various patient characteristics on outcomes related to COVID-19. Our analysis included classic multiple imputation techniques as well as simple complete-case Inverse Probability Weighted models. Extensive experiments show that our approach can effectively highlight the most promising and performant missing-data handling strategy for our case study. Moreover, our methodology allowed a better understanding of the behavior of the different models and of how it changed as we modified their parameters. Our method is general and can be applied to different research fields and on datasets containing heterogeneous types

Loss-of-function ABCC8 mutations in pulmonary arterial hypertension

Background: In pulmonary arterial hypertension (PAH), pathological changes in pulmonary arterioles progressively raise pulmonary artery pressure and increase pulmonary vascular resistance, leading to right heart failure and high mortality rates. Recently, the first potassium channelopathy in PAH, because of mutations in KCNK3, was identified as a genetic cause and pharmacological target. Methods: Exome sequencing was performed to identify novel genes in a cohort of 99 pediatric and 134 adult-onset group I PAH patients. Novel rare variants in the gene identified were independently identified in a cohort of 680 adult-onset patients. Variants were expressed in COS cells and function assessed by patch-clamp and rubidium flux analysis. Results: We identified a de novo novel heterozygous predicted deleterious missense variant c.G2873A (p.R958H) in ABCC8 in a child with idiopathic PAH. We then evaluated all individuals in the original and a second cohort for rare or novel variants in ABCC8 and identified 11 additional heterozygous predicted damaging ABCC8 variants. ABCC8 encodes SUR1 (sulfonylurea receptor 1)—a regulatory subunit of the ATP-sensitive potassium channel. We observed loss of ATP-sensitive potassium channel function for all ABCC8 variants evaluated and pharmacological rescue of all channel currents in vitro by the SUR1 activator, diazoxide. Conclusions: Novel and rare missense variants in ABCC8 are associated with PAH. Identified ABCC8 mutations decreased ATP-sensitive potassium channel function, which was pharmacologically recovered

Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Background: In this study, we aimed to evaluate the effects of tocilizumab in adult patients admitted to hospital with COVID-19 with both hypoxia and systemic inflammation. Methods: This randomised, controlled, open-label, platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing several possible treatments in patients hospitalised with COVID-19 in the UK. Those trial participants with hypoxia (oxygen saturation <92% on air or requiring oxygen therapy) and evidence of systemic inflammation (C-reactive protein ≥75 mg/L) were eligible for random assignment in a 1:1 ratio to usual standard of care alone versus usual standard of care plus tocilizumab at a dose of 400 mg–800 mg (depending on weight) given intravenously. A second dose could be given 12–24 h later if the patient's condition had not improved. The primary outcome was 28-day mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN (50189673) and ClinicalTrials.gov (NCT04381936). Findings: Between April 23, 2020, and Jan 24, 2021, 4116 adults of 21 550 patients enrolled into the RECOVERY trial were included in the assessment of tocilizumab, including 3385 (82%) patients receiving systemic corticosteroids. Overall, 621 (31%) of the 2022 patients allocated tocilizumab and 729 (35%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0·85; 95% CI 0·76–0·94; p=0·0028). Consistent results were seen in all prespecified subgroups of patients, including those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital within 28 days (57% vs 50%; rate ratio 1·22; 1·12–1·33; p<0·0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (35% vs 42%; risk ratio 0·84; 95% CI 0·77–0·92; p<0·0001). Interpretation: In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes. These benefits were seen regardless of the amount of respiratory support and were additional to the benefits of systemic corticosteroids. Funding: UK Research and Innovation (Medical Research Council) and National Institute of Health Research