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Executive function skills are a set of cognitive processes that help individuals to engage in goal-directed behavior and have been linked to benefits in academic achievement and other learning-related outcomes. Recently, there has been interest in understanding how attending center-based preschool may relate to the development of executive function skills. This study used the nationally representative Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011 (n ~ 9,270) to examine the association between preschool attendance and executive function skills in each grade of elementary school. The results of the analysis suggest small initial associations of preschool attendance with some subdomains of executive function (working memory) but not others (cognitive flexibility). These associations are heterogenous based on preschool type (i.e., public vs. private). The longitudinal analysis revealed rapid attenuation of initially positive associations, but also some indications of so-called “sleeper effects” emerged in late elementary school for working memory. Implications for research and policy are discussed. 

Many antibacterial and antiparasitic drugs work by competitively inhibiting dihydrofolate reductase (DHFR), a vital enzyme in folate metabolism. The interactions between inhibitors and DHFR active site residues are known in many homologs but the contributions from distal residues are less understood. Identifying distal residues that aid in inhibitor binding can improve targeted drug development programs by accounting for distant influences that may be less conserved and subject to frequent resistance causing mutations. Previously, a novel, homologybased, computational approach that mines ligand inhibition data was used to predict residues involved in inhibitor selectivity in the DHFR family. Expectedly, some inhibitor selectivity determining residue positions were predicted to lie in the active site and coincide with experimentally known inhibitor selectivity determining positions. However, other residues that group spatially in clusters distal to the active site have not been previously investigated. In this study, the effect of introducing amino acid substitutions at one of these predicted clusters (His38-Ala39-Ile40) on the inhibitor selectivity profile in Bacillus stearothermophilus dihydrofolate reductase (Bs DHFR) was investigated. Mutations were introduced into these cluster positions to change sidechain chemistry and size. We determined kcat and KM values and measured KD values at equilibrium for two competitive DHFR inhibitors, trimethoprim (TMP) and pyrimethamine (PYR). Mutations in the His38-Ala39-Ile40 cluster significantly impacted inhibitor binding and TMP/PYR selectivity - seven out of nine mutations resulted in tighter binding to PYR when compared to TMP. These data suggest that the His38-Ala39-Ile40 cluster is a distal inhibitor selectivity determining region that favors PYR binding in Bs DHFR and, possibly, throughout the DHFR family. 

Tens of thousands of landslides were generated over 10,000 km2 of North Canterbury and Marlborough as a consequence of the 14 November 2016, Mw7.8 Kaikōura Earthquake. The most intense landslide damage was concentrated in 3500 km2 around the areas of fault rupture. Given the sparsely populated area affected by landslides, only a few homes were impacted and there were no recorded deaths due to landslides. Landslides caused major disruption with all road and rail links with Kaikōura being severed. The landslides affecting State Highway 1 (the main road link in the South Island of New Zealand) and the South Island main trunk railway extended from Ward in Marlborough all the way to the south of Oaro in North Canterbury. The majority of landslides occurred in two geological and geotechnically distinct materials reflective of the dominant rock types in the affected area. In the Neogene sedimentary rocks (sandstones, limestones and siltstones) of the Hurunui District, North Canterbury and around Cape Campbell in Marlborough, first-time and reactivated rock-slides and rock-block slides were the dominant landslide type. These rocks also tend to have rock material strength values in the range of 5-20 MPa. In the Torlesse ‘basement’ rocks (greywacke sandstones and argillite) of the Kaikōura Ranges, first-time rock and debris avalanches were the dominant landslide type. These rocks tend to have material strength values in the range of 20-50 MPa. A feature of this earthquake is the large number (more than 200) of valley blocking landslides it generated. This was partly due to the steep and confined slopes in the area and the widely distributed strong ground shaking. The largest landslide dam has an approximate volume of 12(±2) M m3 and the debris from this travelled about 2.7 km2 downslope where it formed a dam blocking the Hapuku River. The long-term stability of cracked slopes and landslide dams from future strong earthquakes and large rainstorms are an ongoing concern to central and local government agencies responsible for rebuilding homes and infrastructure. A particular concern is the potential for debris floods to affect downstream assets and infrastructure should some of the landslide dams breach catastrophically. At least twenty-one faults ruptured to the ground surface or sea floor, with these surface ruptures extending from the Emu Plain in North Canterbury to offshore of Cape Campbell in Marlborough. The mapped landslide distribution reflects the complexity of the earthquake rupture. Landslides are distributed across a broad area of intense ground shaking reflective of the elongate area affected by fault rupture, and are not clustered around the earthquake epicentre. The largest landslides triggered by the earthquake are located either on or adjacent to faults that ruptured to the ground surface. Surface faults may provide a plane of weakness or hydrological discontinuity and adversely oriented surface faults may be indicative of the location of future large landslides. Their location appears to have a strong structural geological control. Initial results from our landslide investigations suggest predictive models relying only on ground-shaking estimates underestimate the number and size of the largest landslides that occurred.