A nodal model for shape optimization of offset strip fin heat exchanger

Paper presented to the 10th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Florida, 14-16 July 2014.A methodology of a nodal model implementation for heat exchanger optimization is presented as an alternative to direct CFD-based optimization. The accuracy and the interest of the use of a nodal model in the frame of optimization process for heat exchanger geometries composed of a base pattern such as offset strip fins (OSF) geometries is detailed. Then an example of optimization of OSF profiles using the nodal model and a genetic algorithm is performed.cf201

Reconstructing parametric gravitational-wave population fits from nonparametric results without refitting the data

Combining multiple events into population analyses is a cornerstone ofgravitational-wave astronomy. A critical component of such studies is theassumed population model, which can range from astrophysically motivatedfunctional forms to non-parametric treatments that are flexible but difficultto interpret. In practice, the current approach is to fit the data multipletimes with different population models to identify robust features. We proposean alternative strategy: assuming the data have already been fit with aflexible model, we present a practical recipe to reconstruct the populationdistribution of a different model. As our procedure postprocesses existingresults, it avoids the need to access the underlying gravitational-wave dataagain and handle selection effects. Additionally, our reconstruction metricprovides a goodness-of-fit measure to compare multiple models. We apply thismethod to the mass distribution of black-hole binaries detected byLIGO/Virgo/KAGRA. Our work paves the way for streamlined gravitational-wavepopulation analyses by fitting the data once and for all with advancednon-parametric methods and careful handling of selection effects, while theastrophysical interpretation is then made accessible using our reconstructionprocedure on targeted models. The key principle is that of conceptuallyseparating data description from data interpretation.<br

Comparing astrophysical models to gravitational-wave data in the observable space

Comparing population-synthesis models to the results of hierarchical Bayesian inference in gravitational-wave astronomy requires a careful understanding of the domain of validity of the models fitted to data. This comparison is usually done using the inferred astrophysical distribution: from the data that were collected, one deconvolves selection effects to reconstruct the generating population distribution. In this letter, we demonstrate the benefits of instead comparing observable populations directly. In this approach, the domain of validity of the models is trivially respected, such that only the relevant parameter space regions as predicted by the astrophysical models of interest contribute to the comparison. We clarify that unbiased inference of the observable compact-binary population is indeed possible. Crucially, this approach still requires incorporating selection effects, but in a manner that differs from the standard implementation. We apply our observable-space reconstruction to LIGO-Virgo-KAGRA data from their third observing run and illustrate its potential by comparing the results to the predictions of a fiducial population-synthesis model

Heterozygous BTNL8 variants in individuals with multisystem inflammatory syndrome in children (MIS-C)

\ua9 2024 Bellos et al.Multisystem inflammatory syndrome in children (MIS-C) is a rare condition following SARS-CoV-2 infection associated with intestinal manifestations. Genetic predisposition, including inborn errors of the OAS-RNAseL pathway, has been reported. We sequenced 154 MIS-C patients and utilized a novel statistical framework of gene burden analysis, “burdenMC,” which identified an enrichment for rare predicted-deleterious variants in BTNL8 (OR = 4.2, 95% CI: 3.5-5.3, P &lt; 10-6). BTNL8 encodes an intestinal epithelial regulator of Vγ4+γδ T cells implicated in regulating gut homeostasis. Enrichment was exclusive to MIS-C, being absent in patients with COVID-19 or bacterial disease. Using an available functional test for BTNL8, rare variants from a larger cohort of MIS-C patients (n = 835) were tested which identified eight variants in 18 patients (2.2%) with impaired engagement of Vγ4+γδ T cells. Most of these variants were in the B30.2 domain of BTNL8 implicated in sensing epithelial cell status. These findings were associated with altered intestinal permeability, suggesting a possible link between disrupted gut homeostasis and MIS-C-associated enteropathy triggered by SARS-CoV-2

Gain-of-function human STAT1 mutations impair IL-17 immunity and underlie chronic mucocutaneous candidiasis

Chronic mucocutaneous candidiasis disease (CMCD) may be caused by autosomal dominant (AD) IL-17F deficiency or autosomal recessive (AR) IL-17RA deficiency. Here, using whole-exome sequencing, we identified heterozygous germline mutations in STAT1 in 47 patients from 20 kindreds with AD CMCD. Previously described heterozygous STAT1 mutant alleles are loss-of-function and cause AD predisposition to mycobacterial disease caused by impaired STAT1-dependent cellular responses to IFN-γ. Other loss-of-function STAT1 alleles cause AR predisposition to intracellular bacterial and viral diseases, caused by impaired STAT1-dependent responses to IFN-α/β, IFN-γ, IFN-λ, and IL-27. In contrast, the 12 AD CMCD-inducing STAT1 mutant alleles described here are gain-of-function and increase STAT1-dependent cellular responses to these cytokines, and to cytokines that predominantly activate STAT3, such as IL-6 and IL-21. All of these mutations affect the coiled-coil domain and impair the nuclear dephosphorylation of activated STAT1, accounting for their gain-of-function and dominance. Stronger cellular responses to the STAT1-dependent IL-17 inhibitors IFN-α/β, IFN-γ, and IL-27, and stronger STAT1 activation in response to the STAT3-dependent IL-17 inducers IL-6 and IL-21, hinder the development of T cells producing IL-17A, IL-17F, and IL-22. Gain-of-function STAT1 alleles therefore cause AD CMCD by impairing IL-17 immunity

Autoantibodies against type I IFNs in patients with life-threatening COVID-19

Interindividual clinical variability in the course of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is vast. We report that at least 101 of 987 patients with life-threatening coronavirus disease 2019 (COVID-19) pneumonia had neutralizing immunoglobulin G (IgG) autoantibodies (auto-Abs) against interferon-w (IFN-w) (13 patients), against the 13 types of IFN-a (36), or against both (52) at the onset of critical disease; a few also had auto-Abs against the other three type I IFNs. The auto-Abs neutralize the ability of the corresponding type I IFNs to block SARS-CoV-2 infection in vitro. These auto-Abs were not found in 663 individuals with asymptomatic or mild SARS-CoV-2 infection and were present in only 4 of 1227 healthy individuals. Patients with auto-Abs were aged 25 to 87 years and 95 of the 101 were men. A B cell autoimmune phenocopy of inborn errors of type I IFN immunity accounts for life-threatening COVID-19 pneumonia in at least 2.6% of women and 12.5% of men

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19

Background: We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15–20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases. Methods: We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded. Results: No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5–528.7, P = 1.1 × 10−4) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR = 3.70[95%CI 1.3–8.2], P = 2.1 × 10−4). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR = 19.65[95%CI 2.1–2635.4], P = 3.4 × 10−3), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR = 4.40[9%CI 2.3–8.4], P = 7.7 × 10−8). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD] = 43.3 [20.3] years) than the other patients (56.0 [17.3] years; P = 1.68 × 10−5). Conclusions: Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60&nbsp;years old