The Hedgehog proteins play a crucial role in metazoan embryo development. Constitutive activation of the pathway is associated with multiple types of cancer. Recent experimental data suggest involvement of Hedgehog signaling in vascular remodeling, germ cell migration, and axon guidance. The molecular mechanisms underlying these effects remain elusive. Here we show that yolk sac-derived endothelial cells and embryonic fibroblasts can directly respond to the Hedgehog signal by increased migration in an in vitro scratch (wound) assay. We also identify Hedgehog transcriptional target genes in these cells, many of which participate in cell migration, axon guidance, and angiogenesis processes. Inhibition of one such molecular pathway, neuropilin-flavomonooxygenase, blocks Hedgehog-induced cell migration. These findings suggest that Hedgehog signaling directly affects embryonic endothelial and fibroblast cell migration via molecules and pathways known to regulate cell migration in response to a variety of environmental cues.

Background Currently, postpartum depression (PPD) screening is mainly based on self‐report symptom‐based assessment, with lack of an objective, integrative tool which identifies women at increased risk, before the emergent of PPD. We developed and validated a machine learning‐based PPD prediction model utilizing electronic health record (EHR) data, and identified novel PPD predictors. Methods A nationwide longitudinal cohort that included 214,359 births between January 2008 and December 2015, divided into model training and validation sets, was constructed utilizing Israel largest health maintenance organization's EHR‐database. PPD was defined as new diagnosis of a depressive episode or antidepressant prescription within the first year postpartum. A gradient‐boosted decision tree algorithm was applied to EHR‐derived sociodemographic, clinical, and obstetric features. Results Among the birth cohort, 1.9% (n = 4104) met the case definition of new‐onset PPD. In the validation set, the prediction model achieved an area under the curve (AUC) of 0.712 (95% confidence interval, 0.690–0.733), with a sensitivity of 0.349 and a specificity of 0.905 at the 90th percentile risk threshold, identifying PPDs at a rate more than three times higher than the overall set (positive and negative predictive values were 0.074 and 0.985, respectively). The model's strongest predictors included both well‐recognized (e.g., past depression) and less‐recognized (differing patterns of blood tests) PPD risk factors. Conclusions Machine learning‐based models incorporating EHR‐derived predictors, could augment symptom‐based screening practice by identifying the high‐risk population at greatest need for preventive intervention, before development of PPD.

BackgroundWhile accumulating evidence suggests that vitamin D deficiency may be involved in the risk to develop schizophrenia and its outcome, there are no studies on vitamin D supplementation in this context. We sought to assess the effect of vitamin D supplementation on psychiatric, cognitive and metabolic parameters in chronic clozapine-treated schizophrenia patients.MethodsThis eight-week, randomized, double-blind, placebo-controlled clinical trial, recruited schizophrenia patients who had been maintained on clozapine treatment for at least 18 weeks and had low levels of vitamin D (< 75 nmol/l) and total PANSS scores > 70 (to ascertain the presence of residual symptoms). Patients were randomly allocated to either weekly oral drops of vitamin D (14,000 IU) or placebo and subsequently assessed at two-week intervals for psychosis severity, mood, cognition and metabolic profile.ResultsTwenty four patients were randomly assigned to vitamin D (aged 39.4 ± 9.6 years, 75% males) and the other 23 patients to the placebo arm (aged 42.5 ± 11.2 years, 60.9% males). After eight weeks, the vitamin D group exhibited a significant increase in vitamin D levels (31.4 vs − 0.4 nmol/l, p < 0.0001). There was no significant effect of vitamin D on psychotic, depressive or metabolic parameters. However, in the vitamin D group, there was a trend towards improved cognition (effect size = 0.17, significance lost following Bonferroni correction).ConclusionsVitamin D supplementation was associated with a trend towards improved cognition, but did not affect psychosis, mood or metabolic status. It is possible that the robust decrease in the PANSS scores in both groups may have obscured an effect of vitamin D supplementation.