Expansion of the Human Phenotype Ontology (HPO) knowledge base and resources.

The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO\u27s interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes

A meta-analysis of carbon capture and storage technology assessments: Understanding the driving factors of variability in cost estimates

The estimated cost of reducing carbon emissions through the deployment of carbon capture and storage (CCS) in power systems vary by a factor of five or more across studies published over the past 8 years. The objective of this paper is to understand the contribution of techno-economic variables and modeling assumptions to explain the large variability in the published international literature on cost of avoided CO<inf>2</inf> (CACO2) using statistical methods. We carry out a meta-analysis of the variations in reported CACO2 for coal and natural gas power plants with CCS. We use regression and correlation analysis to explain the variation in reported CACO2. The regression models built in our analysis have strong predictive power (R2 > 0.90) for all power plant types. We find that the parameters that have high variability and large influence on the value of CACO2 estimated are levelized cost of electricity (LCOE) penalty, capital cost of CCS, and efficiency penalty. In addition, the selection of baseline technologies and more attention and transparency around the calculation of capital costs will reduce the variability across studies to better reflect technology uncertainty and improve comparability across studies

A Statistical Activity Cost Analysis of the Relationship Between Physical and Financial Aspects of Fixed Assets

In this paper, Statistical Activity Cost Analysis (SACA) is used to identify the interaction of mutually dependent physical and financial aspects of a fixed asset-like system configuration. The novelty of the approach is, having established a rational description of the uncertainty inherent in both domains, the analysis of their interaction. Little research to date has investigated the duality of engineering and accounting aspects, in a statistical setting. Our approach is conceptual rather than empirical. We use an illustrative 4-component model, a) to explain the concept of SACA by means of a software demonstration tool, b) to relate financial issues of cost to engineering asset capacity to perform specified tasks, and c) to demonstrate how to produce quantified measures of return and risk, both of which are relevant in areas of life-cycle analysis, budgeting and planning decision-making

Antibody responses to the SARS-CoV-2 vaccine in individuals with various inborn errors of immunity

Background: SARS-CoV-2 vaccination is recommended in patients with inborn errors of immunity (IEIs); however, little is known about immunogenicity and safety in these patients. Objective: We sought to evaluate the impact of genetic diagnosis, age, and treatment on antibody response to COVID-19 vaccine and related adverse events in a cohort of patients with IEIs. Methods: Plasma was collected from 22 health care worker controls, 81 patients with IEIs, and 2 patients with thymoma; the plasma was collected before immunization, 1 to 6 days before the second dose of mRNA vaccine, and at a median of 30 days after completion of the immunization schedule with either mRNA vaccine or a single dose of Johnson & Johnson's Janssen vaccine. Anti-spike (anti-S) and anti-nucleocapsid antibody titers were measured by using a luciferase immunoprecipitation systems method. Information on T- and B-cell counts and use of immunosuppressive drugs was extracted from medical records, and information on vaccine-associated adverse events was collected after each dose. Results: Anti-S antibodies were detected in 27 of 46 patients (58.7%) after 1 dose of mRNA vaccine and in 63 of 74 fully immunized patients (85.1%). A lower rate of seroconversion (7 of 11 [63.6%]) was observed in patients with autoimmune polyendocrinopathy–candidiasis–ectodermal dystrophy. Previous use of rituximab and baseline counts of less than 1000 CD3+ T cells/mL and less than 100 CD19+ B cells/mL were associated with lower anti-S IgG levels. No significant adverse events were reported. Conclusion: Vaccinating patients with IEIs is safe, but immunogenicity is affected by certain therapies and gene defects. These data may guide the counseling of patients with IEIs regarding prevention of SARS-CoV-2 infection and the need for subsequent boosts

Pontin is a critical regulator for AML1-ETO-induced leukemia.

International audienceThe oncogenic fusion protein AML1-ETO, also known as RUNX1-RUNX1T1 is generated by the t(8;21)(q22;q22) translocation, one of the most frequent chromosomal rearrangements in acute myeloid leukemia (AML). Identifying the genes that cooperate with or are required for the oncogenic activity of this chimeric transcription factor remains a major challenge. Our previous studies showed that Drosophila provides a genuine model to study how AML1-ETO promotes leukemia. Here, using an in vivo RNA interference screen for suppressors of AML1-ETO activity, we identified pontin/RUVBL1 as a gene required for AML1-ETO-induced lethality and blood cell proliferation in Drosophila. We further show that PONTIN inhibition strongly impaired the growth of human t(8;21)(+) or AML1-ETO-expressing leukemic blood cells. Interestingly, AML1-ETO promoted the transcription of PONTIN. Moreover, transcriptome analysis in Kasumi-1 cells revealed a strong correlation between PONTIN and AML1-ETO gene signatures and demonstrated that PONTIN chiefly regulated the expression of genes implicated in cell cycle progression. Concordantly, PONTIN depletion inhibited leukemic self-renewal and caused cell cycle arrest. All together our data suggest that the upregulation of PONTIN by AML1-ETO participate in the oncogenic growth of t(8;21) cells