Self-control and early adolescent antisocial behavior: A longitudinal analysis

Contains fulltext : 73179.pdf (publisher's version ) (Closed access)The article discusses a three-wave longitudinal study that investigates the relationship between self-control and aggressive and delinquent behavior of early adolescent boys and girls. The sample consists of 1,012 Dutch adolescents (mean age = 12.3) in their first year of secondary education. Structural equation modeling analyses reveal that high levels of self-control consistently decrease aggressive and delinquent behavior in the subsequent 6 months follow-up intervals. Results for the total sample do not support the hypothesis that self-control is influenced by previous levels of aggression or delinquency. For boys, the partial evidence found indicates reciprocal effects of self-control and delinquency.21 p

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Control of Alzheimer's Amyloid Beta Toxicity by the High Molecular Weight Immunophilin FKBP52 and Copper Homeostasis in Drosophila

FK506 binding proteins (FKBPs), also called immunophilins, are prolyl-isomerases (PPIases) that participate in a wide variety of cellular functions including hormone signaling and protein folding. Recent studies indicate that proteins that contain PPIase activity can also alter the processing of Alzheimer's Amyloid Precursor Protein (APP). Originally identified in hematopoietic cells, FKBP52 is much more abundantly expressed in neurons, including the hippocampus, frontal cortex, and basal ganglia. Given the fact that the high molecular weight immunophilin FKBP52 is highly expressed in CNS regions susceptible to Alzheimer's, we investigated its role in Aβ toxicity. Towards this goal, we generated Aβ transgenic Drosophila that harbor gain of function or loss of function mutations of FKBP52. FKBP52 overexpression reduced the toxicity of Aβ and increased lifespan in Aβ flies, whereas loss of function of FKBP52 exacerbated these Aβ phenotypes. Interestingly, the Aβ pathology was enhanced by mutations in the copper transporters Atox1, which interacts with FKBP52, and Ctr1A and was suppressed in FKBP52 mutant flies raised on a copper chelator diet. Using mammalian cultures, we show that FKBP52 (−/−) cells have increased intracellular copper and higher levels of Aβ. This effect is reversed by reconstitution of FKBP52. Finally, we also found that FKBP52 formed stable complexes with APP through its FK506 interacting domain. Taken together, these studies identify a novel role for FKBP52 in modulating toxicity of Aβ peptides

Stability in Bullying and Victimization and its Association with Social Adjustment in Childhood and Adolescence

This study examined the concurrent and longitudinal associations between stability in bullying and victimization, and social adjustment in childhood and adolescence. Participants were 189 girls and 328 boys who were studied in primary school and in secondary school. The mean age of the participants was 11.1 years in primary school and 14.1 years in secondary school. The measures consisted of peer reported social and personal characteristics. Children who bullied in childhood and adolescence were less liked and more disliked in childhood, and more aggressive and disruptive both in childhood and adolescence, than children who bullied only in childhood or adolescence. Children who bullied or who were victimized only in childhood did not differ largely in adolescence from the children that were never bullies or victims. Children who were victimized in adolescence closely resembled those who were victimized in childhood and adolescence in terms of being liked or disliked, being nominated as a friend, and shyness. The study stresses the need to distinguish between stable and transient bullies and victims

In Vivo Methods to Study Uptake of Nanoparticles into the Brain

Several in vivo techniques have been developed to study and measure the uptake of CNS compounds into the brain. With these techniques, various parameters can be determined after drug administration, including the blood-to-brain influx constant (Kin), the permeability-surface area (PS) product, and the brain uptake index (BUI). These techniques have been mostly used for drugs that are expected to enter the brain via transmembrane diffusion or by carrier-mediated transcytosis. Drugs that have limitations in entering the brain via such pathways have been encapsulated in nanoparticles (based on lipids or synthetic polymers) to enhance brain uptake. Nanoparticles are different from CNS compounds in size, composition and uptake mechanisms. This has led to different methods and approaches to study brain uptake in vivo. Here we discuss the techniques generally used to measure nanoparticle uptake in addition to the techniques used for CNS compounds. Techniques include visualization methods, behavioral tests, and quantitative methods

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta