Antagonist conditioning contractions impair agonist functioning

This study assessed the effect of antagonist conditioning contractions (ACC) on the subsequent force and electromyography of an agonist. Twelve subjects performed isokinetic elbow flexion on a dynamometer in 4 test conditions including a baseline condition without, and 1, 3 and 6 seconds after, isometric triceps extension. Average peak torque (T), peak torque/body weight (T:BW), average power (P), and rate of torque development (RTD) were assessed. Electromyographic data were obtained from elbow extensors and flexors. A repeated measures ANOVA with post hoc analysis demonstrated that T, T:BW, P, and RTD were higher in the baseline, compared to the post ACC conditions (P ≤ 0.05), and appears to be due to higher brachioradialis activation in the baseline condition in compared to some post ACC conditions (P ≤ 0.05)

Disordered Fe vacancies and superconductivity in potassium-intercalated iron selenide (K2-xFe4+ySe5)

The parent compound of an unconventional superconductor must contain unusual correlated electronic and magnetic properties of its own. In the high-Tc potassium intercalated FeSe, there has been significant debate regarding what the exact parent compound is. Our studies unambiguously show that the Fe-vacancy ordered K2Fe4Se5 is the magnetic, Mott insulating parent compound of the superconducting state. Non-superconducting K2Fe4Se5 becomes a superconductor after high temperature annealing, and the overall picture indicates that superconductivity in K2-xFe4+ySe5 originates from the Fe-vacancy order to disorder transition. Thus, the long pending question whether magnetic and superconducting state are competing or cooperating for cuprate superconductors may also apply to the Fe-chalcogenide superconductors. It is believed that the iron selenides and related compounds will provide essential information to understand the origin of superconductivity in the iron-based superconductors, and possibly to the superconducting cuprates

The effects of white matter hyperintensities and amyloid deposition on Alzheimer dementia

Background and purpose: Elevated levels of amyloid deposition as well as white matter damage are thought to be risk factors for Alzheimer Disease (AD). Here we examined whether qualitative ratings of white matter damage predicted cognitive impairment beyond measures of amyloid. Materials and methods: The study examined 397 cognitively normal, 51 very mildly demented, and 11 mildly demented individuals aged 42–90 (mean 68.5). Participants obtained a T2-weighted scan as well as a positron emission tomography scan using 11[C] Pittsburgh Compound B. Periventricular white matter hyperintensities (PVWMHs) and deep white matter hyperintensities (DWMHs) were measured on each T2 scan using the Fazekas rating scale. The effects of amyloid deposition and white matter damage were assessed using logistic regressions. Results: Levels of amyloid deposition (ps < 0.01), as well as ratings of PVWMH (p < 0.01) and DWMH (p < 0.05) discriminated between cognitively normal and demented individuals. Conclusions: The amount of amyloid deposition and white matter damage independently predicts cognitive impairment. This suggests a diagnostic utility of qualitative white matter scales in addition to measuring amyloid levels

Inositol phosphorylceramide synthase null Leishmania are viable and virulent in animal infections where salvage of host sphingomyelin predominates

Many pathogens synthesize inositol phosphorylceramide (IPC) as the major sphingolipid (SL), differing from the mammalian host where sphingomyelin (SM) or more complex SLs predominate. The divergence between IPC synthase and mammalian SL synthases has prompted interest as a potential drug target. However, in the trypanosomatid protozoan Leishmania, cultured insect stage promastigotes lack de novo SL synthesis (Δspt

Factors affecting faculty use of learning technologies: Implications for models of technology adoption

This study examines factors associated with the use of learning technologies by higher education faculty. In an online survey in a UK university, 114 faculty respondents completed a measure of Internet self-efficacy, and reported on their use of learning technologies along with barriers to their adoption. Principal components analysis suggested two main barriers to adoption: structural constraints within the University and perceived usefulness of the tools. Regression analyses indicated both these variables, along with Internet self-efficacy, were associated with use of online learning technology. These findings are more consistent with models of technology engagement that recognize facilitating or inhibiting conditions (unified theory of acceptance and use of technology; decomposed theory of planned behavior) than the classic technology acceptance model (TAM). Practical implications for higher education institutions are that while faculty training and digital literacy initiatives may have roles to play, structural factors (e.g., provision of resources and technical support) must also be addressed for optimal uptake of learning technologies