The proteasome biogenesis regulator Rpn4 cooperates with the unfolded protein response to promote ER stress resistance

Misfolded proteins in the endoplasmic reticulum (ER) activate the unfolded protein response (U PR), which enhances protein folding to restore homeostasis. Additional pathways respond to ER stress, but how they help counteract protein misfolding is incompletely understood. Here, we develop a titratable system for the induction of ER stress in yeast to enable a genetic screen for factors that augment stress resistance independently of the UPR. We identify the proteasome biogenesis regulator Rpn4 and show that it cooperates with the UPR. Rpn4 abundance increases during ER stress, first by a post-transcriptional, then by a transcriptional mechanism. Induction of RPN4 transcription is triggered by cytosolic mislocalization of secretory proteins, is mediated by multiple signaling pathways and accelerates clearance of misfolded proteins from the cytosol. Thus, Rpn4 and the UPR are complementary elements of a modular cross-compartment response to ER stress

Assessing rotation-invariant feature classification for automated wildebeest population counts

Accurate and on-demand animal population counts are the holy grail for wildlife conservation organizations throughout the world because they enable fast and responsive adaptive management policies. While the collection of image data from camera traps, satellites, and manned or unmanned aircraft has advanced significantly, the detection and identification of animals within images remains a major bottleneck since counting is primarily conducted by dedicated enumerators or citizen scientists. Recent developments in the field of computer vision suggest a potential resolution to this issue through the use of rotation-invariant object descriptors combined with machine learning algorithms. Here we implement an algorithm to detect and count wildebeest from aerial images collected in the Serengeti National Park in 2009 as part of the biennial wildebeest count. We find that the per image error rates are greater than, but comparable to, two separate human counts. For the total count, the algorithm is more accurate than both manual counts, suggesting that human counters have a tendency to systematically over or under count images. While the accuracy of the algorithm is not yet at an acceptable level for fully automatic counts, our results show this method is a promising avenue for further research and we highlight specific areas where future research should focus in order to develop fast and accurate enumeration of aerial count data. If combined with a bespoke image collection protocol, this approach may yield a fully automated wildebeest count in the near future

The Pairwise Peculiar Velocity Dispersion of Galaxies: Effects of the Infall

We study the reliability of the reconstruction method which uses a modelling of the redshift distortions of the two-point correlation function to estimate the pairwise peculiar velocity dispersion of galaxies. In particular, the dependence of this quantity on different models for the infall velocity is examined for the Las Campanas Redshift Survey. We make extensive use of numerical simulations and of mock catalogs derived from them to discuss the effect of a self-similar infall model, of zero infall, and of the real infall taken from the simulation. The implications for two recent discrepant determinations of the pairwise velocity dispersion for this survey are discussed.Comment: minor changes in the discussion; accepted for publication in ApJ; 8 pages with 2 figures include

Balancing conservation with national development: a socio-economic case study of the alternatives to the Serengeti Road

Developing countries often have rich natural resources but poor infrastructure to capitalize on them, which leads to significant challenges in terms of balancing poverty alleviation with conservation. The underlying premise in development strategies is to increase the socio-economic welfare of the people while simultaneously ensuring environmental sustainability, however these objectives are often in direct conflict. National progress is dependent on developing infrastructure such as effective transportation networks, however roads can be ecologically catastrophic in terms of disrupting habitat connectivity and facilitating illegal activity. How can national development and conservation be balanced? The proposed Serengeti road epitomizes the conflict between poverty alleviation on one hand, and the conservation of a critical ecosystem on the other. We use the Serengeti as an exemplar case-study in which the relative economic and social benefits of a road can be assessed against the ecological impacts. Specifically, we compare three possible transportation routes and ask which route maximizes the socio-economic returns for the people while minimizing the ecological costs. The findings suggest that one route in particular that circumnavigates the Serengeti links the greatest number of small and medium sized entrepreneurial businesses to the largest labour force in the region. Furthermore, this route connects the most children to schools, provisions the greatest access to hospitals, and opens the most fertile crop and livestock production areas, and does not compromise the ecology and tourism revenue of the Serengeti. This route would improve Tanzania’s food security and self-reliance and would facilitate future infrastructure development which would not be possible if the road were to pass through the Serengeti. This case study provides a compelling example of how a detailed spatial analysis can balance the national objectives of poverty alleviation while maintaining ecological integrity

Watershed services of smallholder agriculture in the Eastern Amazon.

Abstract: Several hydrobiogeochemical research activities have been conducted in the Eastern Amazon, contributing to the understanding of how changes in forests and agro-ecosystems affect ecosystem service provision. Findings have demonstrate that good agricultural practices and the presence of natural secondary vegetation favored by smallholder farm management are important factors for hydrobiogeochemical cycling, aquatic ecosystem conservation, soil conservation, and mitigation of trace emissions from biomass burning in Amazonian small catchments. Two challenges for watershed service management arise in this context. First, low population densities and the relatively flat landscape mean that a critical mass of downstream beneficiaries of such services - a prerequisite for public intervention - is more difficult to identify than in more densely populated mountainous areas. Second, although watershed service providers (farmers) are also to considerable extent service beneficiaries, conflicts over land and cultural heterogeneities among settlers inhibit local collective action to safeguard stream water quality. Including smallholders in carbon payment schemes that and other alternatives to slash-and-burn agriculture by compensating farmers for additional watershed services, including forest conservation. The development of payments for watershed services schemes currently hinges on a better understanding of the biophysical determinants of hydrological service provision, especially in the Amazon region

The cross-correlation between galaxies of different luminosities and Colors

We study the cross-correlation between galaxies of different luminosities and colors, using a sample selected from the SDSS Dr 4. Galaxies are divided into 6 samples according to luminosity, and each of these samples is divided into red and blue subsamples. Projected auto-correlation and cross-correlation is estimated for these subsample. At projected separations r_p > 1\mpch, all correlation functions are roughly parallel, although the correlation amplitude depends systematically on luminosity and color. On r_p < 1\mpch, the auto- and cross-correlation functions of red galaxies are significantly enhanced relative to the corresponding power laws obtained on larger scales. Such enhancement is absent for blue galaxies and in the cross-correlation between red and blue galaxies. We esimate the relative bias factor on scales r > 1\mpch for each subsample using its auto-correlation function and cross-correlation functions. The relative bias factors obtained from different methods are similar. For blue galaxies the luminosity-dependence of the relative bias is strong over the luminosity range probed (-23.0<M_r < -18.0),but for red galaxies the dependence is weaker and becomes insignificant for luminosities below L^*. To examine whether a significant stochastic/nonlinear component exists in the bias relation, we study the ratio R_ij= W_{ii}W_{jj}/W_{ij}^2, where W_{ij} is the projected correlation between subsample i and j. We find that the values of R_ij are all consistent with 1 for all-all, red-red and blue-blue samples, however significantly larger than 1 for red-blue samples. For faint red - faint blue samples the values of R_{ij} are as high as ~ 2 on small scales r_p < 1 \mpch and decrease with increasing r_p.Comment: 25 pages, 18 figures, Accepted for publication in Ap

Protocol

The Perseus software provides a comprehensive framework for the statistical analysis of large-scale quantitative proteomics data, also in combination with other omics dimensions. Rapid developments in proteomics technology and the ever-growing diversity of biological studies increasingly require the flexibility to incorporate computational methods designed by the user. Here, we present the new functionality of Perseus to integrate self-made plugins written in C#, R, or Python. The user-written codes will be fully integrated into the Perseus data analysis workflow as custom activities. This also makes language-specific R and Python libraries from CRAN (cran.r-project.org), Bioconductor (bioconductor.org), PyPI (pypi.org), and Anaconda (anaconda.org) accessible in Perseus. The different available approaches are explained in detail in this article. To facilitate the distribution of user-developed plugins among users, we have created a plugin repository for community sharing and filled it with the examples provided in this article and a collection of already existing and more extensive plugins. © 2020 The Authors. Basic Protocol 1: Basic steps for R plugins Support Protocol 1: R plugins with additional arguments Basic Protocol 2: Basic steps for python plugins Support Protocol 2: Python plugins with additional arguments Basic Protocol 3: Basic steps and construction of C# plugins Basic Protocol 4: Basic steps of construction and connection for R plugins with C# interface Support Protocol 4: Advanced example of R Plugin with C# interface: UMAP Basic Protocol 5: Basic steps of construction and connection for python plugins with C# interface Support Protocol 5: Advanced example of python plugin with C# interface: UMAP Support Protocol 6: A basic workflow for the analysis of label-free quantification proteomics data using perseus. © 2020 The Authors

Microscale Analysis of Spacecraft Heat Shields

Imagine entering Earths atmosphere after returning from the outer solar system. A heat shield less than 2 inches thick protects you from temperatures up to 2,900 Celsius (5,252 Fahrenheit). Such conditions were experienced by NASAs Stardust capsule during reentry in 2006. The only materials capable of providing the necessary protection are composites with complex microstructures. Evaluating these materials is difficult, requiring precise knowledge of their properties. To this end, NASA scientists are developing research codes to compute material properties and simulate ablation at the microscale using agency supercomputers. Utilizing these tools, along with experiments, researchers are working to push the limits of spaceflight, allowing for greater flexibility in future space missions