All databases, field notebooks, paper maps, GIS files, photographs, and photo descriptions related to the intensive survey, of tracts and tumuli, and the collection of sites have been made available in PASH Deep Blue Data Realm 1. The data are broadly organized by team (A-K). The surveyed land was divided up into “tracts”. Tracts are labeled with team letter and a consecutive number: e.g., A-001, A-002, B-003, C-122, D-035.
The accurate and rapid prediction of generic nanoscale interactions is a challenging problem with broad applications. Much of biology functions at the nanoscale, and our ability to manipulate materials and purposefully engage biological machinery requires knowledge of nano-bio interfaces. While several protein-protein interaction models are available, they leverage protein-specific information, limiting their abstraction to other structures. Here, we present NeCLAS, a general, and rapid machine learning pipeline that predicts the location of nanoscale interactions, providing human-intelligible predictions. Two key aspects distinguish NeCLAS: coarse-grained representations, and the use of environmental features to encode the chemical neighborhood. We showcase NeCLAS with challenges for protein-protein, protein-nanoparticle and nanoparticle-nanoparticle systems, demonstrating that NeCLAS replicates computationally- and experimentally-observed interactions. NeCLAS outperforms current nanoscale prediction models, and it shows cross-domain validity, qualifying as a tool for basic research, rapid prototyping, and design of nanostructures., Software:
- To reproduce all-atom molecular dynamics (MD) NAMD is required (version 2.14 or later is suggested). NAMD software and documentation can be found at https://www.ks.uiuc.edu/Research/namd/, - To reproduce coarse-grained MD simulations, LAMMPS (version 29 Sep 2021 - Update 2 or later is suggested). LAMMPS software and documentation can be found at https://www.lammps.org, - To rebuild free energy profiles, the PLUMED plugin (version 2.6) was used. PLUMED software and documentation can be found at https://www.plumed.org/ , and - To generate force matching potentials, the was used the OpenMSCG software was used. OpenMSCG software and documentation can be found at https://software.rcc.uchicago.edu/mscg/
This dataset contains all data used to generate the figures in The Cryosphere manuscript “Measuring Snow Specific Surface Area with 1.30 and 1.55 micro-meter Bidirectional Reflectance Factors,” by Adam Schneider, Mark Flanner, and Roger De Roo. These data support the theory, calibration, and application of the Near-Infrared Emitting and Reflectance Monitoring Dome (NERD), an instrument engineered to rapidly retrieve surface snow specific surface area in the field. Note that this deposit includes a microCT scan database for natural snowfall samples collected in New Hampshire during 2015-2017, comprised of raw tiff files as well as reconstructions, binarized reconstructions, and some 3D model reconstructions. and Running python scripts generally require that the following packages are installed: NumPy, SciPy, Matplotlib, Pandas, and ipdb (for debugging).
The items in this bundle are supporting videos to a study of subsea seismo-acoustics carried out regarding an earthquake in the Persian Gulf. The main data used in the study is a diver's recording of the acoustic waves from the earthquake. The epicenter and topography data used in this study are publicly available as cited in the README.txt file.
This data is part of a large program to translate detection and interpretation of HFOs into clinical use. A zip file is included which contains hfo detections, metadata, and Matlab scripts. The matlab scripts analyze this input data and produce figures as in the referenced paper (note: the blind source separation method is stochastic, and so the figures may not be exactly the same). A file "README.txt" provides more detail about each individual file within the zip file.
This data repository includes the quantitative features of high frequency, intracranial EEG along with all necessary scripts to reproduce the figures of the accompanying manuscript.
This dataset includes spectrally-resolved optical properties for volcanic ash particles from the 2010 Eyjafjallajökull volcanic eruptions. These properties were used in the climate simulations described by Flanner et al. (2014, doi:10.1002/2014JD021977) to quantify ash radiative forcing from the eruptions.
Snake venom research has historically focused on front-fanged species (Viperidae and Elapidae), limiting our knowledge of venom evolution in rear-fanged snakes across their ecologically-diverse phylogeny. Three finger toxins (3FTxs) are a known neurotoxic component in the venoms of some rear-fanged snakes (Colubrinae, Colubridae), but it is unclear how prevalent 3FTxs are both in expression within venom glands and more broadly among colubrine species. Here, we used a transcriptomic approach to characterize the venom expression profiles of four species of colubrine snakes from Neotropics that were dominated by 3FTx expression (in the genera Chironius, Oxybelis, Rhinobothryum, and Spilotes) and reconstructed the gene trees of 3FTxs. Overall, our results highlight the importance of exploring the venoms of understudied species in reconstructing the full evolutionary history of toxins across the tree of life.
Srodawa, K., Cerda, P.A., Davis Rabosky, A.R., Crowe-Riddell, J.M. Evolution of Three Finger Toxin Genes in Neotropical Colubrine Snakes (Colubridae). Toxins 2023, 15(9), 523; https://doi.org/10.3390/toxins15090523
This was a small descriptive study to determine whether short chain fatty acids (SCFAs) are detectable in water. It is part of a larger study that assessed the utility of exhaled breath condensate (EBC) as a biofluid for microbiome assays.
Yue, M., Kim, J. H., Evans, C. R., Kachman, M., Erb-Downward, J. R., D’Souza, J., Foxman, B., Adar, S. D., Curtis, J. L., & Stringer, K. A. (2020). Measurement of Short-Chain Fatty Acids in Respiratory Samples: Keep Your Assay above the Water Line. American Journal of Respiratory and Critical Care Medicine, 202(4), 610–612. https://doi.org/10.1164/rccm.201909-1840LE
The main goal of this research was to identify potential molecular pathways that contribute to memory dysregulation and decline that persists long after illness or inflammation. We have previously established a subchronic immune challenge model that results in memory impairments months after the inflammatory challenge. This project aimed to determine whether memory impairments were accompanied by transcriptional dysregulation in memory related brain region (the hippocampus).
These data show the differential gene expression as log2fold change (and p-value) in males and females 3 months after immune challenge (Supp Tables 1 and 2); after a subsequent immune challenge (Supp Tables 3 and 4); the differential regulation of genes in males and females (Supp Table 5); genes differentially expressed in the hippocampus of males and females at baseline (Supp Table 6) and the differential regulation of those genes in males and females after immune challenge (Supp Tables 7,8).
Tchessalova, D., & Tronson, N. C. (2019). Enduring and sex-specific changes in hippocampal gene expression after a subchronic immune challenge. BioRxiv, 566570. https://doi.org/10.1101/566570