Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior

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

Comparison of Blood RNA Extraction Methods Used for Gene Expression Profiling in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that causes death within a mean of 2-3 years from symptom onset. There is no diagnostic test and the delay from symptom onset to diagnosis averages 12 months. The identification of prognostic and diagnostic biomarkers in ALS would facilitate earlier diagnosis and faster monitoring of treatments. Gene expression profiling (GEP) can help to identify these markers as well as therapeutic targets in neurological diseases. One source of genetic material for GEP in ALS is peripheral blood, which is routinely accessed from patients. However, a high proportion of globin mRNA in blood can mask important genetic information. A number of methods allow safe collection, storage and transport of blood as well as RNA stabilisation, including the PAXGENE and TEMPUS systems for the collection of whole blood and LEUKOLOCK which enriches for the leukocyte population. Here we compared these three systems and assess their suitability for GEP in ALS. We collected blood from 8 sporadic ALS patients and 7 controls. PAXGENE and TEMPUS RNA extracted samples additionally underwent globin depletion using GlobinClear. RNA was amplified and hybridised onto Affymetrix U133 Plus 2.0 arrays. Lists of genes differentially regulated in ALS patients and controls were created for each method using the R package PUMA, and RT-PCR validation was carried out on selected genes. TEMPUS/GlobinClear, and LEUKOLOCK produced high quality RNA with sufficient yield, and consistent array expression profiles. PAXGENE/GlobinClear yield and quality were lower. Globin depletion for PAXGENE and TEMPUS uncovered the presence of over 60% more transcripts than when samples were not depleted. TEMPUS/GlobinClear and LEUKOLOCK gene lists respectively contained 3619 and 3047 genes differentially expressed between patients and controls. Real-time PCR validation revealed similar reliability between these two methods and gene ontology analyses revealed similar pathways differentially regulated in disease compared to controls

The Hubble higher z supernova search: Supernovae to z ~ 1.6 and constraints on type Ia progenitor models

Erratum for the article 2004 ApJ 613 20