Tocotrienol Affects Oxidative Stress, Cholesterol Homeostasis and the Amyloidogenic Pathway in Neuroblastoma Cells: Consequences for Alzheimer’s Disease

One of the characteristics of Alzheimer´s disease (AD) is an increased amyloid load and an enhanced level of reactive oxidative species (ROS). Vitamin E has known beneficial neuroprotective effects, and previously, some studies suggested that vitamin E is associated with a reduced risk of AD due to its antioxidative properties. However, epidemiological studies and nutritional approaches of vitamin E treatment are controversial. Here, we investigate the effect of α-tocotrienol, which belongs to the group of vitamin E, on AD-relevant processes in neuronal cell lines. In line with the literature, α-tocotrienol reduced the ROS level in SH-SY5Y cells. In the presence of tocotrienols, cholesterol and cholesterol esters, which have been shown to be risk factors in AD, were decreased. Besides the unambiguous positive effects of tocotrienol, amyloid-β (Aβ) levels were increased accompanied by an increase in the activity of enzymes responsible for Aβ production. Proteins and gene expression of the secretases and their components remained unchanged, whereas tocotrienol accelerates enzyme activity in cell-free assays. Besides enhanced Aβ production, tocotrienols inhibited Aβ degradation in neuro 2a (N2a)-cells. Our results might help to understand the controversial findings of vitamin E studies and demonstrate that besides the known positive neuroprotective properties, tocotrienols also have negative characteristics with respect to AD

The seasonal cycle of ice-nucleating particles linked to the abundance of biogenic aerosol in boreal forests

Ice-nucleating particles (INPs) trigger the formation of cloud ice crystals in the atmosphere. Therefore, they strongly influence cloud microphysical and optical properties and precipitation and the life cycle of clouds. Improving weather forecasting and climate projection requires an appropriate formulation of atmospheric INP concentrations. This remains challenging as the global INP distribution and variability depend on a variety of aerosol types and sources, and neither their short-term variability nor their long-term seasonal cycles are well covered by continuous measurements. Here, we provide the first year-long set of observations with a pronounced INP seasonal cycle in a boreal forest environment. Besides the observed seasonal cycle in INP concentrations with a minimum in wintertime and maxima in early and late summer, we also provide indications for a seasonal variation in the prevalent INP type. We show that the seasonal dependency of INP concentrations and prevalent INP types is most likely driven by the abundance of biogenic aerosol. As current parameterizations do not reproduce this variability, we suggest a new mechanistic description for boreal forest environments which considers the seasonal variation in INP concentrations. For this, we use the ambient air temperature measured close to the ground at 4.2 m height as a proxy for the season, which appears to affect the source strength of biogenic emissions and, thus, the INP abundance over the boreal forest. Furthermore, we provide new INP parameterizations based on the Ice Nucleation Active Surface Site (INAS) approach, which specifically describes the ice nucleation activity of boreal aerosols particles prevalent in different seasons. Our results characterize the boreal forest as an important but variable INP source and provide new perspectives to describe these new findings in atmospheric models.Peer reviewe

The association between failed quit attempts and increased levels of psychological distress in smokers in a large New Zealand cohort

<p>Abstract</p> <p>Background</p> <p>Although the association between smoking status and poorer mental health has been well documented, the association between quit status and psychological distress is less clear. The aim of the present study is to investigate the association of smoking status and quit status with psychological distress.</p> <p>Methods</p> <p>Data for this study is from a single year of the Survey of Families, Income and Employment (SoFIE) conducted in New Zealand (2004/05) (n = 18,525 respondents). Smoking status and quit status were treated as exposure variables, and psychological distress (Kessler-10) was treated as the outcome variable. Logistic regression analyses were performed to determine the association of smoking with psychological distress in the whole adult population and quit status with psychological distress in the ex- and current-smoking population.</p> <p>Results</p> <p>Current smokers had higher rates of high and very high psychological distress compared to never smokers (adjusted odds ratio (aOR) = 1.45; 95% CI: 1.24-1.69). Unsuccessful quitters had much higher levels of high to very high levels of psychological distress (16%) than any other group. Moreover, compared to long-term ex-smokers, unsuccessful quitters had a much higher odds of high to very high levels of psychological distress (aOR = 1.73; 95% CI: 1.36-2.21).</p> <p>Conclusion</p> <p>These findings suggest that the significant association between smoking and psychological distress might be partly explained by increased levels of psychological distress among current smokers who made a quit attempt in the last year. This issue needs further study as it has implications for optimising the design of quitting support.</p

Measurement report : Introduction to the HyICE-2018 campaign for measurements of ice-nucleating particles and instrument inter-comparison in the Hyytiala boreal forest

The formation of ice particles in Earth's atmosphere strongly influences the dynamics and optical properties of clouds and their impacts on the climate system. Ice formation in clouds is often triggered heterogeneously by ice-nucleating particles (INPs) that represent a very low number of particles in the atmosphere. To date, many sources of INPs, such as mineral and soil dust, have been investigated and identified in the low and mid latitudes. Although less is known about the sources of ice nucleation at high latitudes, efforts have been made to identify the sources of INPs in the Arctic and boreal environments. In this study, we investigate the INP emission potential from high-latitude boreal forests in the mixed-phase cloud regime. We introduce the HyICE-2018 measurement campaign conducted in the boreal forest of Hyytiala, Finland, between February and June 2018. The campaign utilized the infrastructure of the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, with additional INP instruments, including the Portable Ice Nucleation Chamber I and II (PINC and PINCii), the SPectrometer for Ice Nuclei (SPIN), the Portable Ice Nucleation Experiment (PINE), the Ice Nucleation SpEctrometer of the Karlsruhe Institute of Technology (INSEKT) and the Microlitre Nucleation by Immersed Particle Instrument (mu L-NIPI), used to quantify the INP concentrations and sources in the boreal environment. In this contribution, we describe the measurement infrastructure and operating procedures during HyICE-2018, and we report results from specific time periods where INP instruments were run in parallel for inter-comparison purposes. Our results show that the suite of instruments deployed during HyICE-2018 reports consistent results and therefore lays the foundation for forthcoming results to be considered holistically. In addition, we compare measured INP concentrations to INP parameterizations, and we observe good agreement with the Tobo et al. (2013) parameterization developed from measurements conducted in a ponderosa pine forest ecosystem in Colorado, USA.Peer reviewe

Measurement report : Introduction to the HyICE-2018 campaign for measurements of ice-nucleating particles and instrument inter-comparison in the Hyytiala boreal forest

The formation of ice particles in Earth's atmosphere strongly influences the dynamics and optical properties of clouds and their impacts on the climate system. Ice formation in clouds is often triggered heterogeneously by ice-nucleating particles (INPs) that represent a very low number of particles in the atmosphere. To date, many sources of INPs, such as mineral and soil dust, have been investigated and identified in the low and mid latitudes. Although less is known about the sources of ice nucleation at high latitudes, efforts have been made to identify the sources of INPs in the Arctic and boreal environments. In this study, we investigate the INP emission potential from high-latitude boreal forests in the mixed-phase cloud regime. We introduce the HyICE-2018 measurement campaign conducted in the boreal forest of Hyytiala, Finland, between February and June 2018. The campaign utilized the infrastructure of the Station for Measuring Ecosystem-Atmosphere Relations (SMEAR) II, with additional INP instruments, including the Portable Ice Nucleation Chamber I and II (PINC and PINCii), the SPectrometer for Ice Nuclei (SPIN), the Portable Ice Nucleation Experiment (PINE), the Ice Nucleation SpEctrometer of the Karlsruhe Institute of Technology (INSEKT) and the Microlitre Nucleation by Immersed Particle Instrument (mu L-NIPI), used to quantify the INP concentrations and sources in the boreal environment. In this contribution, we describe the measurement infrastructure and operating procedures during HyICE-2018, and we report results from specific time periods where INP instruments were run in parallel for inter-comparison purposes. Our results show that the suite of instruments deployed during HyICE-2018 reports consistent results and therefore lays the foundation for forthcoming results to be considered holistically. In addition, we compare measured INP concentrations to INP parameterizations, and we observe good agreement with the Tobo et al. (2013) parameterization developed from measurements conducted in a ponderosa pine forest ecosystem in Colorado, USA.Peer reviewe

Bayesian Cue Integration as a Developmental Outcome of Reward Mediated Learning

Average human behavior in cue combination tasks is well predicted by Bayesian inference models. As this capability is acquired over developmental timescales, the question arises, how it is learned. Here we investigated whether reward dependent learning, that is well established at the computational, behavioral, and neuronal levels, could contribute to this development. It is shown that a model free reinforcement learning algorithm can indeed learn to do cue integration, i.e. weight uncertain cues according to their respective reliabilities and even do so if reliabilities are changing. We also consider the case of causal inference where multimodal signals can originate from one or multiple separate objects and should not always be integrated. In this case, the learner is shown to develop a behavior that is closest to Bayesian model averaging. We conclude that reward mediated learning could be a driving force for the development of cue integration and causal inference

Kinematic analysis of a rolling tensegrity structure with spatially curved members

In this work, a tensegrity structure with spatially curved members is applied as rolling locomotion system. The actuation of the structure allows a variation of the originally cylindrical shape to a conical shape. Moreover, the structure is equipped with internal movable masses to control the position of the center of mass of the structure. To control the locomotion system a reliable actuation strategy is required. Therefore, the kinematics of the system considering the nonholonomic constraints are derived in this paper. Based on the resulting insight in the locomotion behavior a feasible actuation strategy is designed to control the trajectory of the system. To verify this approach kinematic analyses are evaluated numerically. The simulation data confirm the path following due to an appropriate shape change of the tensegrity structure. Thus, this system enables a two-dimensional rolling locomotion

A neutral beryllium(I) radical

The reduction of a cyclic alkyl(amino)carbene (CAAC)-stabilized organoberyllium chloride yields the first neutral beryllium radical, which was characterized by EPR, IR, UV/Vis spectroscopy and X-ray crystallography. DFT calculations show significant spin density at beryllium and confirm donor–acceptor bonding between an alkylberyllium radical fragment and a neutral CAAC ligand

Atomic-scale structure, cation distribution, and bandgap bowing in Cu(In,Ga)Se2 and Cu(In,Ga)S2

Mixed chalcopyrite semiconductors like Cu(In,Ga)S2 and Cu(In,Ga)Se2 are characterized by thecoexistence of different local atomic arrangements around the S or Se anion. The resulting aniondisplacement strongly influences the material bandgap. We studied the atomic-scale structure ofCu(In,Ga)S2 as a function of composition using x-ray absorption spectroscopy and valence forcefield simulations. Applying a specially developed model for not fully random cation distributions,we find that structural relaxation of the anion with respect to In and Ga contributes significantlymore to the bandgap bowing observed for Cu(In,Ga)S2 and Cu(In,Ga)Se2 than relaxation withrespect to Cu and group-III atoms