In-Vitro Application of Magnetic Hybrid Niosomes: Targeted siRNA-Delivery for Enhanced Breast Cancer Therapy

Even though the administration of chemotherapeutic agents such as erlotinib is clinically established for the treatment of breast cancer, its efficiency and the therapy outcome can be greatly improved using RNA interference (RNAi) mechanisms for a combinational therapy. However, the cellular uptake of bare small interfering RNA (siRNA) is insufficient and its fast degradation in the bloodstream leads to a lacking delivery and no suitable accumulation of siRNA inside the target tissues. To address these problems, non-ionic surfactant vesicles (niosomes) were used as a nanocarrier platform to encapsulate Lifeguard (LFG)-specific siRNA inside the hydrophilic core. A preceding entrapment of superparamagnetic iron-oxide nanoparticles (FexOy-NPs) inside the niosomal bilayer structure was achieved in order to enhance the cellular uptake via an external magnetic manipulation. After verifying a highly effective entrapment of the siRNA, the resulting hybrid niosomes were administered to BT-474 cells in a combinational therapy with either erlotinib or trastuzumab and monitored regarding the induced apoptosis. The obtained results demonstrated that the nanocarrier successfully caused a downregulation of the LFG gene in BT-474 cells, which led to an increased efficacy of the chemotherapeutics compared to plainly added siRNA. Especially the application of an external magnetic field enhanced the internalization of siRNA, therefore increasing the activation of apoptotic signaling pathways. Considering the improved therapy outcome as well as the high encapsulation efficiency, the formulated hybrid niosomes meet the requirements for a cost-effective commercialization and can be considered as a promising candidate for future siRNA delivery agents

Estimating sleep parameters using an accelerometer without sleep diary

This is the final version. Available from the publisher via the DOI in this record.Wrist worn raw-data accelerometers are used increasingly in large-scale population research. We examined whether sleep parameters can be estimated from these data in the absence of sleep diaries. Our heuristic algorithm uses the variance in estimated z-axis angle and makes basic assumptions about sleep interruptions. Detected sleep period time window (SPT-window) was compared against sleep diary in 3752 participants (range = 60–82 years) and polysomnography in sleep clinic patients (N = 28) and in healthy good sleepers (N = 22). The SPT-window derived from the algorithm was 10.9 and 2.9 minutes longer compared with sleep diary in men and women, respectively. Mean C-statistic to detect the SPT-window compared to polysomnography was 0.86 and 0.83 in clinic-based and healthy sleepers, respectively. We demonstrated the accuracy of our algorithm to detect the SPT-window. The value of this algorithm lies in studies such as UK Biobank where a sleep diary was not used.Medical Research Council (MRC)National Institute of Health (NIH

Estimating sleep parameters using an accelerometer without sleep diary

Funding Information: This work was made possible thanks to the following grants: NIH grants HL-094307 (AIP), and; MRC grant MR/ P012167/1. We would like to thank Dr. Sarah Charman, Dr. Paul Innerd, Matthew Goodman and Sara McHugh-Grant for their contributions to the collection of PSG data. Publisher Copyright: © 2018, The Author(s).Peer reviewe

Homozygous microdeletion of exon 5 in ZNF277 in a girl with specific language impairment

Peer reviewedPublisher PD

Genomic Landscape of a Three-Generation Pedigree Segregating Affective Disorder

Bipolar disorder (BPD) is a common psychiatric illness with a complex mode of inheritance. Besides traditional linkage and association studies, which require large sample sizes, analysis of common and rare chromosomal copy number variants (CNVs) in extended families may provide novel insights into the genetic susceptibility of complex disorders. Using the Illumina HumanHap550 BeadChip with over 550,000 SNP markers, we genotyped 46 individuals in a three-generation Old Order Amish pedigree with 19 affected (16 BPD and three major depression) and 27 unaffected subjects. Using the PennCNV algorithm, we identified 50 CNV regions that ranged in size from 12 to 885 kb and encompassed at least 10 single nucleotide polymorphisms (SNPs). Of 19 well characterized CNV regions that were available for combined genotype-expression analysis 11 (58%) were associated with expression changes of genes within, partially within or near these CNV regions in fibroblasts or lymphoblastoid cell lines at a nominal P value <0.05. To further investigate the mode of inheritance of CNVs in the large pedigree, we analyzed a set of four CNVs, located at 6q27, 9q21.11, 12p13.31 and 15q11, all of which were enriched in subjects with affective disorders. We additionally show that these variants affect the expression of neuronal genes within or near the rearrangement. Our analysis suggests that family based studies of the combined effect of common and rare CNVs at many loci may represent a useful approach in the genetic analysis of disease susceptibility of mental disorders

The Nucleoside Diphosphate Kinase Gene Nme3 Acts as Quantitative Trait Locus Promoting Non-Mendelian Inheritance

The t-haplotype, a variant form of the t-complex region on mouse chromosome 17, acts as selfish genetic element and is transmitted at high frequencies (>95%) from heterozygous (t/+) males to their offspring. This phenotype is termed transmission ratio distortion (TRD) and is caused by the interaction of the t-complex responder (Tcr) with several quantitative trait loci (QTL), the t-complex distorters (Tcd1 to Tcd4), all located within the t-haplotype region. Current data suggest that the distorters collectively impair motility of all sperm derived from t/+ males; t-sperm is rescued by the responder, whereas +-sperm remains partially dysfunctional. Recently we have identified two distorters as regulators of RHO small G proteins. Here we show that the nucleoside diphosphate kinase gene Nme3 acts as a QTL on TRD. Reduction of the Nme3 dosage by gene targeting of the wild-type allele enhanced the transmission rate of the t-haplotype and phenocopied distorter function. Genetic and biochemical analysis showed that the t-allele of Nme3 harbors a mutation (P89S) that compromises enzymatic activity of the protein and genetically acts as a hypomorph. Transgenic overexpression of the Nme3 t-allele reduced t-haplotype transmission, proving it to be a distorter. We propose that the NME3 protein interacts with RHO signaling cascades to impair sperm motility through hyperactivation of SMOK, the wild-type form of the responder. This deleterious effect of the distorters is counter-balanced by the responder, SMOKTcr, a dominant-negative protein kinase exclusively expressed in t-sperm, thus permitting selfish behaviour and preferential transmission of the t-haplotype. In addition, the previously reported association of NME family members with RHO signaling in somatic cell motility and metastasis, in conjunction with our data involving RHO signaling in sperm motility, suggests a functional conservation between mechanisms for motility control in somatic cells and spermatozoa

Parental and Grandparental Ages in the Autistic Spectrum Disorders: A Birth Cohort Study

Background: A number of studies have assessed ages of parents of children with autistic spectrum disorders (ASD), and reported both maternal and paternal age effects. Here we assess relationships with grandparental ages. Methods and Findings: We compared the parental and grandparental ages of children in the population-based Avon Longitudinal Study of Parents and Children (ALSPAC), according to their scores in regard to 4 autistic trait measures and whether they had been given a diagnosis of ASD. Mean maternal and paternal ages of ASD cases were raised, but this appears to be secondary to a maternal grandmother age effect (P = 0.006): OR = 1.66[95%CI 1.16, 2.37] for each 10-year increase in the grandmother’s age at the birth of the mother. Trait measures also revealed an association between the maternal grandmother’s age and the major autistic trait–the Coherence Scale (regression coefficient b = 0.142, [95%CI = 0.057, 0.228]P = 0.001). After allowing for confounders the effect size increased to b = 0.217[95%CI 0.125, 0.308](P,0.001) for each 10 year increase in age. Conclusions: Although the relationship between maternal grandmother’s age and ASD and a major autistic trait was unexpected, there is some biological plausibility, for the maternal side at least, given that the timing of female meiosis I permits direct effects on the grandchild’s genome during the grandmother’s pregnancy. An alternative explanation is the meiotic mismatch methylation (3 M) hypothesis, presented here for the first time. Nevertheless the findings should b

Identifying Prototypical Components in Behaviour Using Clustering Algorithms

Quantitative analysis of animal behaviour is a requirement to understand the task solving strategies of animals and the underlying control mechanisms. The identification of repeatedly occurring behavioural components is thereby a key element of a structured quantitative description. However, the complexity of most behaviours makes the identification of such behavioural components a challenging problem. We propose an automatic and objective approach for determining and evaluating prototypical behavioural components. Behavioural prototypes are identified using clustering algorithms and finally evaluated with respect to their ability to represent the whole behavioural data set. The prototypes allow for a meaningful segmentation of behavioural sequences. We applied our clustering approach to identify prototypical movements of the head of blowflies during cruising flight. The results confirm the previously established saccadic gaze strategy by the set of prototypes being divided into either predominantly translational or rotational movements, respectively. The prototypes reveal additional details about the saccadic and intersaccadic flight sections that could not be unravelled so far. Successful application of the proposed approach to behavioural data shows its ability to automatically identify prototypical behavioural components within a large and noisy database and to evaluate these with respect to their quality and stability. Hence, this approach might be applied to a broad range of behavioural and neural data obtained from different animals and in different contexts