We don't choose whom we love:Predictors for romantic attraction to villains

INTRODUCTION: Why are women (not) romantically attracted to dark personalities or villains, which might be a risk factor for intimate partner violence (IPV) victimization? In the current study, it is opted to investigate how adult attachment, maladaptive personality traits, and acceptance of couple violence in women predict romantic attraction to heroic/villainous characters using structural equation modeling (SEM). METHOD: First, a pilot study was conducted in 122 heterosexual women (aged 16–25) to select male TV characters. This resulted in the selection of six villains and 10 heroes for the main study, in which 194 other heterosexual women (aged 16–25) were asked to rate the pictures of TV characters through an online questionnaire. This was combined with self-report measures of maladaptive personality traits, acceptance of couple violence, and adult attachment. These variables were entered into a SEM model to assess model fit. RESULTS: Overall, women rated heroes higher on physical appearance (pilot study) and romantic attraction (main study) compared to villains. We found different direct effects of avoidant (negative) and anxious (positive) attachment styles on romantic attraction to heroes. Moreover, maladaptive personality traits fully mediated the positive effect of avoidant attachment style on romantic attraction to villains. DISCUSSION: Despite the limitations of the study design (e.g., low N, low notoriety of the TV characters), this study emphasizes that women are generally more romantically attracted to heroes (vs. villains). Besides, there are different predictors of romantic attraction to heroes and villains, which requires further investigation, especially in the context of IPV

A nonsense mutation in B3GALNT2 is concordant with hydrocephalus in Friesian horses

Background: Hydrocephalus in Friesian horses is a developmental disorder that often results in stillbirth of affected foals and dystocia in dams. The occurrence is probably related to a founder effect and inbreeding in the population. The aim of our study was to find genomic associations, to investigate the mode of inheritance, to allow a DNA test for hydrocephalus in Friesian horses to be developed. In case of a monogenic inheritance we aimed to identify the causal mutation. Results: A genome-wide association study of hydrocephalus in 13 cases and 69 controls using 29,720 SNPs indicated the involvement of a region on ECA1 (P T corresponding to XP_001491595 p.Gln475* was identical to a B3GALNT2 mutation identified in a human case of muscular dystrophy-dystroglycanopathy with hydrocephalus. All 16 available cases and none of the controls were homozygous for the mutation, and all 17 obligate carriers (= dams of cases) were heterozygous. A random sample of the Friesian horse population (n = 865) was tested for the mutation in a commercial laboratory. One-hundred and forty-seven horses were carrier and 718 horses were homozygous for the normal allele; the estimated allele frequency in the Friesian horse population is 0.085. Conclusions: Hydrocephalus in Friesian horses has an autosomal recessive mode of inheritance. A nonsense mutation XM_001491545 c.1423C>T corresponding to XP_001491595 p.Gln475* in B3GALNT2 (1: 75,859,296-75,909,376) is concordant with hydrocephalus in Friesian horses. Application of a DNA test in the breeding programme will reduce the losses caused by hydrocephalus in the Friesian horse population

Dwarfism with joint laxity in Friesian horses is associated with a splice site mutation in B4GALT7

Background: Inbreeding and population bottlenecks in the ancestry of Friesian horses has led to health issues such as dwarfism. The limbs of dwarfs are short and the ribs are protruding inwards at the costochondral junction, while the head and back appear normal. A striking feature of the condition is the flexor tendon laxity that leads to hyperextension of the fetlock joints. The growth plates of dwarfs display disorganized and thickened chondrocyte columns. The aim of this study was to identify the gene defect that causes the recessively inherited trait in Friesian horses to understand the disease process at the molecular level. Results: We have localized the genetic cause of the dwarfism phenotype by a genome wide approach to a 3 Mb region on the p-arm of equine chromosome 14. The DNA of two dwarfs and one control Friesian horse was sequenced completely and we identified the missense mutation ECA14:g.4535550C> T that cosegregated with the phenotype in all Friesians analyzed. The mutation leads to the amino acid substitution p.(Arg17Lys) of xylosylprotein beta 1,4-galactosyltransferase 7 encoded by B4GALT7. The protein is one of the enzymes that synthesize the tetrasaccharide linker between protein and glycosaminoglycan moieties of proteoglycans of the extracellular matrix. The mutation not only affects a conserved arginine codon but also the last nucleotide of the first exon of the gene and we show that it impedes splicing of the primary transcript in cultured fibroblasts from a heterozygous horse. As a result, the level of B4GALT7 mRNA in fibroblasts from a dwarf is only 2 % compared to normal levels. Mutations in B4GALT7 in humans are associated with Ehlers-Danlos syndrome progeroid type 1 and Larsen of Reunion Island syndrome. Growth retardation and ligamentous laxity are common manifestations of these syndromes. Conclusions: We suggest that the identified mutation of equine B4GALT7 leads to the typical dwarfism phenotype in Friesian horses due to deficient splicing of transcripts of the gene. The mutated gene implicates the extracellular matrix in the regular organization of chrondrocyte columns of the growth plate. Conservation of individual amino acids may not be necessary at the protein level but instead may reflect underlying conservation of nucleotide sequence that are required for efficient splicing

Calibration techniques for node classification using graph neural networks on medical image data

Miscalibration of deep neural networks (DNNs) can lead to unreliable predictions and hinder their use in clinical decision-making. This miscalibration is often caused by overconfident probability estimates. Calibration techniques such as model ensembles, regularization terms, and post-hoc scaling of the predictions can be employed to improve the calibration performance of DNNs. In contrast to DNNs, graph neural networks (GNNs) tend to exhibit underconfidence. In this study, we investigate the efficacy of calibration techniques developed for DNNs when applied to GNNs trained on medical image data, and compare the calibration performance of binary and multiclass node classification on a benchmark dataset and a medical image dataset. We find that post-hoc methods using Platt scaling or Temperature scaling, or methods that add a regularization term to the loss function during training are most effective to improve calibration. Our results further indicate that these calibration techniques are more effective for multiclass classification tasks compared to binary classification tasks

High knee loading in male adolescent pre-professional football players: Effects of a targeted training programme

Objective: To assess whether targeted neuromuscular exercises can decrease knee loading of adolescent pre-professional footballers with high knee loading as identified with the field-based Drop Vertical Jump Test (DVJT). Design: Prospective controlled trial, conducted between August and November 2016 at Erasmus Medical Centre, The Netherlands. Methods: Pre-professional football players (aged 14–21 years) were evaluated at baseline and after 12 weeks follow-up with the field-based DVJT. The field-based DVJT is a standardised test in which a player drops from a box and jumps up immediately after landing; knee load is calculated based on five parameters. Players with high knee load (probability ≥ 0.75) from one club performed regular training(control group), and players with high knee load from another other club performed targeted neuromuscular exercises for 12 weeks (intervention group). The difference of change in knee load between both groups after 12 weeks was the primary outcome measure. Results: Of 107 eligible players, 75 had a high knee loading. Knee loading decreased in both groups after 12 weeks of training, but change in probability of high knee load was not significantly different between both groups (95% Confidence Interval [−0.012–0.082], p = 0.139). Conclusion: Targeted neuromuscular exercises had no additional effect in decreasing knee loading of adolescent male pre-professional football players compared to regular training. Trial registration number: The Netherlands Trial Register (ID number: 6044)

Adjusting for confounding by indication in observational studies: a case study in traumatic brain injury.

INTRODUCTION: Observational studies of interventions are at risk for confounding by indication. The objective of the current study was to define the circumstances for the validity of methods to adjust for confounding by indication in observational studies. PATIENTS AND METHODS: We performed post hoc analyses of data prospectively collected from three European and North American traumatic brain injury studies including 1,725 patients. The effects of three interventions (intracranial pressure [ICP] monitoring, intracranial operation and primary referral) were estimated in a proportional odds regression model with the Glasgow Outcome Scale as ordinal outcome variable. Three analytical methods were compared: classical covariate adjustment, propensity score matching and instrumental variable (IV) analysis in which the percentage exposed to an intervention in each hospital was added as an independent variable, together with a random intercept for each hospital. In addition, a simulation study was performed in which the effect of a hypothetical beneficial intervention (OR 1.65) was simulated for scenarios with and without unmeasured confounders. RESULTS: For all three interventions, covariate adjustment and propensity score matching resulted in negative estimates of the treatment effect (OR ranging from 0.80 to 0.92), whereas the IV approach indicated that both ICP monitoring and intracranial operation might be beneficial (OR per 10% change 1.17, 95% CI 1.01-1.42 and 1.42, 95% CI 0.95-1.97). In our simulation study, we found that covariate adjustment and propensity score matching resulted in an invalid estimate of the treatment effect in case of unmeasured confounders (OR ranging from 0.90 to 1.03). The IV approach provided an estimate in the similar direction as the simulated effect (OR per 10% change 1.04-1.05) but was statistically inefficient. CONCLUSION: The effect estimation of interventions in observational studies strongly depends on the analytical method used. When unobserved confounding and practice variation are expected in observational multicenter studies, IV analysis should be considered

A nanobody-based tracer targeting DPP6 for non-invasive imaging of human pancreatic endocrine cells

There are presently no reliable ways to quantify endocrine cell mass (ECM) in vivo, which prevents an accurate understanding of the progressive beta cell loss in diabetes or following islet transplantation. To address this unmet need, we coupled RNA sequencing of human pancreatic islets to a systems biology approach to identify new biomarkers of the endocrine pancreas. Dipeptidyl-Peptidase 6 (DPP6) was identified as a target whose mRNA expression is at least 25-fold higher in human pancreatic islets as compared to surrounding tissues and is not changed by proinflammatory cytokines. At the protein level, DPP6 localizes only in beta and alpha cells within the pancreas. We next generated a high-affinity camelid single-domain antibody (nanobody) targeting human DPP6. The nanobody was radiolabelled and in vivo SPECT/CT imaging and biodistribution studies were performed in immunodeficient mice that were either transplanted with DPP6-expressing Kelly neuroblastoma cells or insulin-producing human EndoC-βH1 cells. The human DPP6-expressing cells were clearly visualized in both models. In conclusion, we have identified a novel beta and alpha cell biomarker and developed a tracer for in vivo imaging of human insulin secreting cells. This provides a useful tool to non-invasively follow up intramuscularly implanted insulin secreting cells