Silver nanoparticles in Zebrafish (Danio rerio) embryos: Uptake, growth and molecular responses

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. Silver nanoparticles (AgNPs) are widely used in commercial applications as antimicrobial agents, but there have recently been increasing concerns raised about their possible environmental and health impacts. In this study, zebrafish embryos were exposed to two sizes of AgNP, 4 and 10 nm, through a continuous exposure from 4 to 96 h post‐fertilisation (hpf), to study their uptake, impact and molecular defense responses. Results showed that zebrafish embryos were significantly impacted by 72 hpf when continuously exposed to 4 nm AgNPs. At concentrations above 0.963 mg/L, significant in vivo uptake and delayed yolk sac absorption was evident; at 1.925 mg/L, significantly reduced body length was recorded compared to control embryos. Additionally, 4 nm AgNP treatment at the same concentration resulted in significantly upregulated hypoxia inducible factor 4 (HIF4) and peroxisomal membrane protein 2 (Pxmp2) mRNA expression in exposed embryos 96 hpf. In contrast, no significant differences in terms of larvae body length, yolk sac absorption or gene expression levels were observed following exposure to 10 nm AgNPs. These results demonstrated that S4 AgNPs are available for uptake, inducing developmental (measured as body length and yolk sac area) and transcriptional (specifically HIF4 and Pxmp2) perturbations in developing embryos. This study suggests the importance of particle size as one possible factor in determining the developmental toxicity of AgNPs in fish embryos

Hypusination of Eif5a Regulates Cytoplasmic TDP-43 Aggregation and Accumulation in a Stress-Induced Cellular Model

TAR DNA-binding protein 43 (TDP-43) is a nuclear RNA/DNA binding protein involved in mRNA metabolism. Aberrant mislocalization to the cytoplasm and formation of phosphorylated/aggregated TDP-43 inclusions remains the hallmark pathology in a spectrum of neurodegenerative diseases, including frontotemporal disorders and Alzheimer\u27s disease. Eukaryotic Translation Initiation Factor 5A undergoes a unique post-translation modification of lysine to hypusine (K50), which determines eIF5A binding partners. We used a sodium arsenite-induced cellular stress model to investigate the role of hypusinated eIF5A (eIF5AHypK50) in governing TDP-43 cytoplasmic mislocalization and accumulation in stress granule. Our proteomics and functional data provide evidence that eIF5A interacts with TDP-43 in a hypusine-dependent manner. Additionally, we showed that following stress TDP-43 interactions with eIF5AHypK50 were induced both in the cytoplasm and stress granules. Pharmacological reduction of hypusination or mutations of lysine residues within the hypusine loop decreased phosphorylated and insoluble TDP-43 levels. The proteomic and biochemical analysis also identified nuclear pore complex importins KPNA1/2, KPNB1, and RanGTP as interacting partners of eIF5AHypK50. These findings are the first to provide a novel pathway and potential therapeutic targets that require further investigation in models of TDP-43 proteinopathies

Spatial gradients in the cosmological constant

It is possible that there may be differences in the fundamental physical parameters from one side of the observed universe to the other. I show that the cosmological constant is likely to be the most sensitive of the physical parameters to possible spatial variation, because a small variation in any of the other parameters produces a huge variation of the cosmological constant. It therefore provides a very powerful {\em indirect} evidence against spatial gradients or temporal variation in the other fundamental physical parameters, at least 40 orders of magnitude more powerful than direct experimental constraints. Moreover, a gradient may potentially appear in theories where the variability of the cosmological constant is connected to an anthropic selection mechanism, invoked to explain the smallness of this parameter. In the Hubble damping mechanism for anthropic selection, I calculate the possible gradient. While this mechanism demonstrates the existence of this effect, it is too small to be seen experimentally, except possibly if inflation happens around the Planck scale.Comment: 12 page

Prospectus, October 17, 1979

CANTEEN STILL IN TROUBLE; Language: Big adjustment; Across the globe; In the nation; Throughout the state; Around the town; Fire guts Athenaeum; Briefs: \u27Living Newspaper\u27 performs Oct. 23, German foods, Seniors to visit, Costumes display, Apply no more, Ciricle K events, Krannert events; Letter to editor: Ohio inmate wants pen-pal; Field trips to view artwork; French cooking offered Weds.; I.O.E. to evaluate Parkland College Oct. 30; Everyone would like a Vette; Feature: Fast Freddie wows women; Reviews: \u27Long Run\u27 ran, Science fiction and yesteryear unite in \u27time after time\u27, STYX book-album; Jumping out of a plane -- FOR FUN; Classifieds; Concerts: Frampton -- yea, Simms -- nay, Kenny Loggins storms C-U; Cross Country running well; Outlaws are a crowd pleaser; Sports: Cobras win 4 more; Superman Fast Freddy did it again? 4-9; Freddy\u27s picks; Fast Freddy Contest; Intramural Standingshttps://spark.parkland.edu/prospectus_1979/1008/thumbnail.jp

Learning from text-based close call data

A key feature of big data is the variety of data sources that are available; which include not just numerical data but also image or video data or even free text. The GB railways collects a large volume of free text data daily from railway workers describing close call hazard reports: instances where an accident could have – but did not – occur. These close call reports contain valuable safety information which could be useful in managing safety on the railway, but which can be lost in the very large volume of data – much larger than is viable for a human analyst to read. This paper describes the application of rudimentary natural language processing (NLP) techniques to uncover safety information from close calls. The analysis has proven that basic information extraction is possible using the rudimentary techniques, but has also identified some limitations that arise using only basic techniques. Using these findings further research in this area intends to look at how the techniques that have been proven to date can be improved with the use of more advanced NLP techniques coupled with machine-learning

Can forest management based on natural disturbances maintain ecological resilience?

Given the increasingly global stresses on forests, many ecologists argue that managers must maintain ecological resilience: the capacity of ecosystems to absorb disturbances without undergoing fundamental change. In this review we ask: Can the emerging paradigm of natural-disturbance-based management (NDBM) maintain ecological resilience in managed forests? Applying resilience theory requires careful articulation of the ecosystem state under consideration, the disturbances and stresses that affect the persistence of possible alternative states, and the spatial and temporal scales of management relevance. Implementing NDBM while maintaining resilience means recognizing that (i) biodiversity is important for long-term ecosystem persistence, (ii) natural disturbances play a critical role as a generator of structural and compositional heterogeneity at multiple scales, and (iii) traditional management tends to produce forests more homogeneous than those disturbed naturally and increases the likelihood of unexpected catastrophic change by constraining variation of key environmental processes. NDBM may maintain resilience if silvicultural strategies retain the structures and processes that perpetuate desired states while reducing those that enhance resilience of undesirable states. Such strategies require an understanding of harvesting impacts on slow ecosystem processes, such as seed-bank or nutrient dynamics, which in the long term can lead to ecological surprises by altering the forest's capacity to reorganize after disturbance

Fitting the integrated Spectral Energy Distributions of Galaxies

Fitting the spectral energy distributions (SEDs) of galaxies is an almost universally used technique that has matured significantly in the last decade. Model predictions and fitting procedures have improved significantly over this time, attempting to keep up with the vastly increased volume and quality of available data. We review here the field of SED fitting, describing the modelling of ultraviolet to infrared galaxy SEDs, the creation of multiwavelength data sets, and the methods used to fit model SEDs to observed galaxy data sets. We touch upon the achievements and challenges in the major ingredients of SED fitting, with a special emphasis on describing the interplay between the quality of the available data, the quality of the available models, and the best fitting technique to use in order to obtain a realistic measurement as well as realistic uncertainties. We conclude that SED fitting can be used effectively to derive a range of physical properties of galaxies, such as redshift, stellar masses, star formation rates, dust masses, and metallicities, with care taken not to over-interpret the available data. Yet there still exist many issues such as estimating the age of the oldest stars in a galaxy, finer details ofdust properties and dust-star geometry, and the influences of poorly understood, luminous stellar types and phases. The challenge for the coming years will be to improve both the models and the observational data sets to resolve these uncertainties. The present review will be made available on an interactive, moderated web page (sedfitting.org), where the community can access and change the text. The intention is to expand the text and keep it up to date over the coming years.Comment: 54 pages, 26 figures, Accepted for publication in Astrophysics & Space Scienc