In vitro growth environment produces lipidomic and electron transport chain abnormalities in mitochondria from non-tumorigenic astrocytes and brain tumours

The mitochondrial lipidome influences ETC (electron transport chain) and cellular bioenergetic efficiency. Brain tumours are largely dependent on glycolysis for energy due to defects in mitochondria and oxidative phosphorylation. In the present study, we used shotgun lipidomics to compare the lipidome in highly purified mitochondria isolated from normal brain, from brain tumour tissue, from cultured tumour cells and from non-tumorigenic astrocytes. The tumours included the CT-2A astrocytoma and an EPEN (ependymoblastoma), both syngeneic with the C57BL/6J (B6) mouse strain. The mitochondrial lipidome in cultured CT-2A and EPEN tumour cells were compared with those in cultured astrocytes and in solid tumours grown in vivo. Major differences were found between normal tissue and tumour tissue and between in vivo and in vitro growth environments for the content or composition of ethanolamine glycerophospholipids, phosphatidylglycerol and cardiolipin. The mitochondrial lipid abnormalities in solid tumours and in cultured cells were associated with reductions in multiple ETC activities, especially Complex I. The in vitro growth environment produced lipid and ETC abnormalities in cultured non-tumorigenic astrocytes that were similar to those associated with tumorigenicity. It appears that the culture environment obscures the boundaries of the Crabtree and the Warburg effects. These results indicate that in vitro growth environments can produce abnormalities in mitochondrial lipids and ETC activities, thus contributing to a dependency on glycolysis for ATP production

Crystal Growth of Thiol-Stabilized Gold Nanoparticles by Heat-Induced Coalescence

A monolayer of dodecanethiol-stabilized gold nanoparticles changed into two-dimensional and three-dimensional self-organized structures by annealing at 323 K. Subsequent crystal growth of gold nanoparticles occurred. Thiol molecules, although chemisorbed, form relatively unstable bonds with the gold surface; a few thiols desorbed from the surface and oxidized to disulfides at 323 K, because the interaction energy between thiol macromolecules is larger than that between a thiol and a nanoparticle. The gold nanoparticles approached each other and grew into large single or twinned crystals because of the van der Waals attraction and the heat generated by the exothermic formation of disulfides

Spike pattern recognition by supervised classification in low dimensional embedding space

© The Author(s) 2016. This article is published with open access at Springerlink.com under the terms of the Creative Commons Attribution License 4.0, (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Epileptiform discharges in interictal electroencephalography (EEG) form the mainstay of epilepsy diagnosis and localization of seizure onset. Visual analysis is rater-dependent and time consuming, especially for long-term recordings, while computerized methods can provide efficiency in reviewing long EEG recordings. This paper presents a machine learning approach for automated detection of epileptiform discharges (spikes). The proposed method first detects spike patterns by calculating similarity to a coarse shape model of a spike waveform and then refines the results by identifying subtle differences between actual spikes and false detections. Pattern classification is performed using support vector machines in a low dimensional space on which the original waveforms are embedded by locality preserving projections. The automatic detection results are compared to experts’ manual annotations (101 spikes) on a whole-night sleep EEG recording. The high sensitivity (97 %) and the low false positive rate (0.1 min−1), calculated by intra-patient cross-validation, highlight the potential of the method for automated interictal EEG assessment.Peer reviewedFinal Published versio

Cultural Phylogenetics of the Tupi Language Family in Lowland South America

Background: Recent advances in automated assessment of basic vocabulary lists allow the construction of linguistic phylogenies useful for tracing dynamics of human population expansions, reconstructing ancestral cultures, and modeling transition rates of cultural traits over time. Methods: Here we investigate the Tupi expansion, a widely-dispersed language family in lowland South America, with a distance-based phylogeny based on 40-word vocabulary lists from 48 languages. We coded 11 cultural traits across the diverse Tupi family including traditional warfare patterns, post-marital residence, corporate structure, community size, paternity beliefs, sibling terminology, presence of canoes, tattooing, shamanism, men’s houses, and lip plugs. Results/Discussion: The linguistic phylogeny supports a Tupi homeland in west-central Brazil with subsequent major expansions across much of lowland South America. Consistently, ancestral reconstructions of cultural traits over the linguistic phylogeny suggest that social complexity has tended to decline through time, most notably in the independent emergence of several nomadic hunter-gatherer societies. Estimated rates of cultural change across the Tupi expansion are on the order of only a few changes per 10,000 years, in accord with previous cultural phylogenetic results in other languag

Urban Biodiversity and Landscape Ecology: Patterns, Processes and Planning

Effective planning for biodiversity in cities and towns is increasingly important as urban areas and their human populations grow, both to achieve conservation goals and because ecological communities support services on which humans depend. Landscape ecology provides important frameworks for understanding and conserving urban biodiversity both within cities and considering whole cities in their regional context, and has played an important role in the development of a substantial and expanding body of knowledge about urban landscapes and communities. Characteristics of the whole city including size, overall amount of green space, age and regional context are important considerations for understanding and planning for biotic assemblages at the scale of entire cities, but have received relatively little research attention. Studies of biodiversity within cities are more abundant and show that longstanding principles regarding how patch size, configuration and composition influence biodiversity apply to urban areas as they do in other habitats. However, the fine spatial scales at which urban areas are fragmented and the altered temporal dynamics compared to non-urban areas indicate a need to apply hierarchical multi-scalar landscape ecology models to urban environments. Transferring results from landscape-scale urban biodiversity research into planning remains challenging, not least because of the requirements for urban green space to provide multiple functions. An increasing array of tools is available to meet this challenge and increasingly requires ecologists to work with planners to address biodiversity challenges. Biodiversity conservation and enhancement is just one strand in urban planning, but is increasingly important in a rapidly urbanising world

In quest of a systematic framework for unifying and defining nanoscience

This article proposes a systematic framework for unifying and defining nanoscience based on historic first principles and step logic that led to a “central paradigm” (i.e., unifying framework) for traditional elemental/small-molecule chemistry. As such, a Nanomaterials classification roadmap is proposed, which divides all nanomatter into Category I: discrete, well-defined and Category II: statistical, undefined nanoparticles. We consider only Category I, well-defined nanoparticles which are >90% monodisperse as a function of Critical Nanoscale Design Parameters (CNDPs) defined according to: (a) size, (b) shape, (c) surface chemistry, (d) flexibility, and (e) elemental composition. Classified as either hard (H) (i.e., inorganic-based) or soft (S) (i.e., organic-based) categories, these nanoparticles were found to manifest pervasive atom mimicry features that included: (1) a dominance of zero-dimensional (0D) core–shell nanoarchitectures, (2) the ability to self-assemble or chemically bond as discrete, quantized nanounits, and (3) exhibited well-defined nanoscale valencies and stoichiometries reminiscent of atom-based elements. These discrete nanoparticle categories are referred to as hard or soft particle nanoelements. Many examples describing chemical bonding/assembly of these nanoelements have been reported in the literature. We refer to these hard:hard (H-n:H-n), soft:soft (S-n:S-n), or hard:soft (H-n:S-n) nanoelement combinations as nanocompounds. Due to their quantized features, many nanoelement and nanocompound categories are reported to exhibit well-defined nanoperiodic property patterns. These periodic property patterns are dependent on their quantized nanofeatures (CNDPs) and dramatically influence intrinsic physicochemical properties (i.e., melting points, reactivity/self-assembly, sterics, and nanoencapsulation), as well as important functional/performance properties (i.e., magnetic, photonic, electronic, and toxicologic properties). We propose this perspective as a modest first step toward more clearly defining synthetic nanochemistry as well as providing a systematic framework for unifying nanoscience. With further progress, one should anticipate the evolution of future nanoperiodic table(s) suitable for predicting important risk/benefit boundaries in the field of nanoscience

Remote detection of invasive alien species

The spread of invasive alien species (IAS) is recognized as the most severe threat to biodiversity outside of climate change and anthropogenic habitat destruction. IAS negatively impact ecosystems, local economies, and residents. They are especially problematic because once established, they give rise to positive feedbacks, increasing the likelihood of further invasions and spread. The integration of remote sensing (RS) to the study of invasion, in addition to contributing to our understanding of invasion processes and impacts to biodiversity, has enabled managers to monitor invasions and predict the spread of IAS, thus supporting biodiversity conservation and management action. This chapter focuses on RS capabilities to detect and monitor invasive plant species across terrestrial, riparian, aquatic, and human-modified ecosystems. All of these environments have unique species assemblages and their own optimal methodology for effective detection and mapping, which we discuss in detail

An overview of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) project: aerosol–cloud–radiation interactions in the southeast Atlantic basin

This is the final version. Available on open access from the European Geosciences Union via the DOI in this recordData availability: All ORACLES data are accessible via the digital object identifiers (DOIs) provided under ORACLES Science Team (2020a–d) references: https://doi.org/10.5067/Suborbital/ORACLES/P3/2018_V2 (ORACLES Science Team, 2020a), https://doi.org/10.5067/Suborbital/ORACLES/P3/2017_V2 (ORACLES Science Team, 2020b), https://doi.org/10.5067/Suborbital/ORACLES/P3/2016_V2 (ORACLES Science Team, 2020c), and https://doi.org/10.5067/Suborbital/ORACLES/ER2/2016_V2 (ORACLES Science Team, 2020d). The only exceptions are noted as footnotes to Table B2.Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June–October), aerosol particles reaching 3–5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ∼350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ∼100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.NAS