Loss of tolerance precedes triggering and lifelong persistence of pathogenic type I interferon autoantibodies.

Autoantibodies neutralizing type I interferons (IFN-Is) can underlie infection severity. Here, we trace the development of these autoantibodies at high-resolution using longitudinal samples from 1,876 well-treated individuals living with HIV over a 35-year period. Similar to general populations, ∼1.9% of individuals acquired anti-IFN-I autoantibodies as they aged (median onset ∼63 years). Once detected, anti-IFN-I autoantibodies persisted lifelong, and titers increased over decades. Individuals developed distinct neutralizing and non-neutralizing autoantibody repertoires at discrete times that selectively targeted combinations of IFNα, IFNβ, and IFNω. Emergence of neutralizing anti-IFNα autoantibodies correlated with reduced baseline IFN-stimulated gene levels and was associated with subsequent susceptibility to severe COVID-19 several years later. Retrospective measurements revealed enrichment of pre-existing autoreactivity against other autoantigens in individuals who later developed anti-IFN-I autoantibodies, and there was evidence for prior viral infections or increased IFN at the time of anti-IFN-I autoantibody triggering. These analyses suggest that age-related loss of self-tolerance prior to IFN-I immune-triggering poses a risk of developing lifelong functional IFN-I deficiency

SNP genotyping to screen for a common deletion in CHARGE Syndrome

BACKGROUND: CHARGE syndrome is a complex of birth defects including coloboma, choanal atresia, ear malformations and deafness, cardiac defects, and growth delay. We have previously hypothesized that CHARGE syndrome could be caused by unidentified genomic microdeletion, but no such deletion was detected using short tandem repeat (STR) markers spaced an average of 5 cM apart. Recently, microdeletion at 8q12 locus was reported in two patients with CHARGE, although point mutation in CHD7 on chromosome 8 was the underlying etiology in most of the affected patients. METHODS: We have extended our previous study by employing a much higher density of SNP markers (3258) with an average spacing of approximately 800 kb. These SNP markers are diallelic and, therefore, have much different properties for detection of deletions than STRs. RESULTS: A global error rate estimate was produced based on Mendelian inconsistency. One marker, rs431722 exceeded the expected frequency of inconsistencies, but no deletion could be demonstrated after retesting the 4 inconsistent pedigrees with local flanking markers or by FISH with the corresponding BAC clone. Expected deletion detection (EDD) was used to assess the coverage of specific intervals over the genome by deriving the probability of detecting a common loss of heterozygosity event over each genomic interval. This analysis estimated the fraction of unobserved deletions, taking into account the allele frequencies at the SNPs, the known marker spacing and sample size. CONCLUSIONS: The results of our genotyping indicate that more than 35% of the genome is included in regions with very low probability of a deletion of at least 2 Mb

KIM-1 and NGAL: new markers of obstructive nephropathy

Congenital obstructive nephropathy is the primary cause of chronic renal failure in children. Rapid diagnosis and initiation of the treatment are vital to preserve function and/or to slow down renal injury. The aim of our study was to determine whether urinary (u) kidney injury molecule-1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL) may be useful non-invasive biomarkers in children with congenital hydronephrosis (HN) caused by ureteropelvic junction obstruction. The study cohort consisted of 20 children with severe HN who required surgery (median age 2.16 years) and two control groups (control group 1: 20 patients with mild, non-obstructive HN; control group 2: 25 healthy children). All of the children had normal renal function. Immunoenzymatic ELISA commercial kits were used to measure uKIM-1 and uNGAL concentrations. The preoperative median uKIM-1/creatinine (cr.) and uNGAL levels were significantly greater in the children with severe HN than in both control groups. Three months after surgery, uNGAL had decreased significantly (p < 0.05) in the children with severe HN, but was still higher than that in control group 2 children (p < 0.05). Receiver operator characteristic analyses revealed a good diagnostic profile for uKIM-1 and uNGAL in terms of identifying a differential renal function of <40% in HN patients (area under the curve (AUC) 0.8 and 0.814, respectively) and <45% in all examined children (AUC 0.779 and 0.868, respectively). Based on these results, we suggest that increasing uNGAL and uKIM-1 levels are associated with worsening obstruction. Further studies are required to confirm a potential application of uKIM-1 and uNGAL as useful biomarkers for the diagnosis and progression of chronic kidney disease

Bayesian learning and the psychology of rule induction

In recent years, Bayesian learning models have been applied to an increasing variety of domains. While such models have been criticized on theoretical grounds, the underlying assumptions and predictions are rarely made concrete and tested experimentally. Here, I use Frank and Tenenbaum’s (2011) Bayesian model of rule-learning as a case study to spell out the underlying assumptions, and to confront them with the empirical results Frank and Tenenbaum (2011) propose to simulate, as well as with novel experiments. While rule-learning is arguably well suited to rational Bayesian approaches, I show that their models are neither psychologically plausible nor ideal observer models. Further, I show that their central assumption is unfounded: humans do not always preferentially learn more specific rules, but, at least in some situations, those rules that happen to be more salient. Even when granting the unsupported assumptions, I show that all of the experiments modeled by Frank and Tenenbaum (2011) either contradict their models, or have a large number of more plausible interpretations. I provide an alternative account of the experimental data based on simple psychological mechanisms, and show that this account both describes the data better, and is easier to falsify. I conclude that, despite the recent surge in Bayesian models of cognitive phenomena, psychological phenomena are best understood by developing and testing psychological theories rather than models that can be fit to virtually any data

How well do the theory of reasoned action and theory of planned behaviour predict intentions and attendance at screening programmes? A meta-analysis

Meta-analysis was used to quantify how well the Theories of Reasoned Action and Planned Behaviour have predicted intentions to attend screening programmes and actual attendance behaviour. Systematic literature searches identified 33 studies that were included in the review. Across the studies as a whole, attitudes had a large-sized relationship with intention, while subjective norms and perceived behavioural control (PBC) possessed medium-sized relationships with intention. Intention had a medium-sized relationship with attendance, whereas the PBC-attendance relationship was small sized. Due to heterogeneity in results between studies, moderator analyses were conducted. The moderator variables were (a) type of screening test, (b) location of recruitment, (c) screening cost and (d) invitation to screen. All moderators affected theory of planned behaviour relationships. Suggestions for future research emerging from these results include targeting attitudes to promote intention to screen, a greater use of implementation intentions in screening information and examining the credibility of different screening providers

A Computational Approach to Analyze the Mechanism of Action of the Kinase Inhibitor Bafetinib

Prediction of drug action in human cells is a major challenge in biomedical research. Additionally, there is strong interest in finding new applications for approved drugs and identifying potential side effects. We present a computational strategy to predict mechanisms, risks and potential new domains of drug treatment on the basis of target profiles acquired through chemical proteomics. Functional protein-protein interaction networks that share one biological function are constructed and their crosstalk with the drug is scored regarding function disruption. We apply this procedure to the target profile of the second-generation BCR-ABL inhibitor bafetinib which is in development for the treatment of imatinib-resistant chronic myeloid leukemia. Beside the well known effect on apoptosis, we propose potential treatment of lung cancer and IGF1R expressing blast crisis

Evaluating everyday explanations

People frequently rely on explanations provided by others to understand complex phenomena. A fair amount of attention has been devoted to the study of scientific explanation, and less on understanding how people evaluate naturalistic, everyday explanations. Using a corpus of diverse explanations from Reddit's "Explain Like I'm Five" and other online sources, we assessed how well a variety of explanatory criteria predict judgments of explanation quality. We find that while some criteria previously identified as explanatory virtues do predict explanation quality in naturalistic settings, other criteria, such as simplicity, do not. Notably, we find that people have a preference for complex explanations that invoke more causal mechanisms to explain an effect. We propose that this preference for complexity is driven by a desire to identify enough causes to make the effect seem inevitable