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opencc-by-4.0May 2020View details →

The Unfolding Journey of Superoxide Dismutase 1 Barrels Under Crowding: Atomistic Simulations Shed Light on Intermediate States and Their Interactions With Crowders

This data accompanies the article entitled The Unfolding Journey of Superoxide Dismutase 1 Barrels Under Crowding: Atomistic Simulations Shed Light on Intermediate States and Their Interactions With Crowders, published in J. Phys. Chem. Lett. (<a href="https://doi.org/10.1021/acs.jpclett.0c00699">https://doi.org/10.1021/acs.jpclett.0c00699</a>). 01_SOD1bar_unfolding_REST2.zip: The zip archive includes REST2 trajectories for the three systems investigated in the paper: 1:1 packing, 2:1 packing, and the dilute case. The trajectories are saved in the GROMACS XTC file format, separately for each temperature (i=0,...,23). Given the large trajectory sizes, only protein coordinates (SOD1bar + crowders) are reported, and the output frequency is reduced to 100 ps. A starting geometry (in the Gromos87 GRO format) after equilibration of the initial packing is provided for each REST2 simulation (conf_prot.gro). Moreover, for each REST2 simulation, an xarray (http://xarray.pydata.org) dataset, saved in the netCDF file format, is included with computed fraction of native contacts, secondary structure content, and the Calpha RMSD of the barrel core (beta sheets beta1 - beta8) with respect to the crystal structure. 02_SOD1bar_geometries_representative_unfolding.zip: Representative SOD1bar geometries along the unfolding pathway (presented in Figure 3 of the paper). 03_SOD1bar_geometries_loopVII.zip: SOD1bar geometries with varying loop VII conformation which were isolated from dilute REST2 and which are presented in Figure S9 of the paper.

opencc-by-4.0Aug 2020View details →

An interactive figure of the 2016 and 2020 X-ray light curves of LMC 1968 as observed by the XRT instrument on Swift

This repository contains all the files necessary to create the interactive figure in the Research Note ov Schwarz, Page, Kuin, & Darnley 2020. The figure was created using the <a href="https://aas-timeseries.readthedocs.io/en/latest/">aas-timeseries</a> package of the <a href="https://www.astropy.org">astropy</a> project. The file lmc68.py is the underlying python code while the two lmcrel*.csv are the input files for the 2016 and 2020 eruptions of the recurrent nova LMC 1968 as observed by the XRT instrument on board the Neil Gehrels Swift observatory. A Jupyter notebook is required to preview the interactive figure. The output from the code is saved in the interactive.tar.gz package. It consists of four files: <ul> <li>index.html</li> <li>figure.json</li> <li>data_75e74aca-09f1-4846-966e-9e33c7acc8d3.csv</li> <li>data_5402e718-01cf-4ad7-92a5-7679d4076ed5.csv</li> </ul> The first file, index.html, is the html framework that houses the interactive figure. figure.json contains the interactive figure commands while the two data*csv files are the underlying data. The interactive figure can be viewed if this package is opened on a web server.  A copy of this interactive figure is available <a href="https://authortools.aas.org/LMC1968/">here</a> so you can try it out.

opencc-by-4.0Dec 2021View details →

Coral calcification mechanisms in a warming ocean and the interactive effects of temperature and light

Ross et al 2022 Supplementary data for coral (Acropora nasuta) temperature and light experiments.

opencc-by-4.0Mar 2023View details →

Dataset: Correlative Light, Electron Microscopy and Raman Spectroscopy Workflow to Detect and Observe Microplastic Interactions with Whole Jellyfish

ABSTRACT Many researchers have turned their attention to understanding microplastic interaction with marine fauna. Efforts are being made to monitor exposure pathways and concentrations, and to assess the impact such interactions may have. To answer these questions, it is important to select appropriate experimental parameters and analytical protocols. This study focuses on medusae of Cassiopea andromeda jellyfish: a unique benthic jellyfish known to favor (sub-)tropical coastal regions which are potentially exposed to plastic waste from land-based sources. Juvenile medusae were exposed to fluorescent poly(ethylene terephthalate) and polypropylene microplastics (< 300 µm), resin embedded, and sectioned before analysis with confocal laser scanning microscopy as well as transmission electron microscopy and Raman Spectroscopy. Results show the fluorescent microplastics were stable enough to be detected with the optimized analytical protocol presented, and that their observed interaction with medusae occurs in a manner which is likely driven by the microplastic properties (e.g. density, hydrophobicity).

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Unveiling the genetic networks: Exploring the dynamic interaction of photosynthetic phenotypes in woody plants across varied light gradients

Background: Understanding the mechanisms by which genes control and regulate complex quantitative traits during periods of fluctuating resources remains a challenging and uncertain task in photosynthesis studies. Most studies have focused on the structure of photosynthesis, the photosynthetic response under stress, or the genetic mechanisms involved in photosynthetic effects and neglected the interactive genetic mechanism that governs various traits through significant quantitative trait loci (QTLs). Results In this study, we have developed a differential dynamic system that enables the identification of QTLs based on the photosynthetic phenotypic and genotypic data under varying levels of light intensity gradients. The framework not only allows for the assessment of the direct effects of QTLs on phenotypes but also captures how they influence interactions among phenotypes as light intensities change. We have analyzed the genetic effects and genetic variance, visualized the genetic network associated with photosynthesis interactions, and validated the effectiveness and stability of the DDS framework. Pivotal QTLs were identified individually to uncover the process and pattern of interaction. Through functional annotation, we made an intriguing discovery that seemingly unimportant QTLs can still have significant genetic effects on phenotypic changes through their regulation with other QTLs. Conclusions This finding emphasizes the significance of considering the interactive genetic architecture when seeking to understand the genetic interaction mechanism of photosynthesis in natural populations of woody plants. Moreover, our research provides a novel framework that can be extended to explore the interactive genetic architecture among organisms, contributing to a deeper understanding of stress resistance mechanisms in woody plants.

opencc-zeroNov 2023View details →

opencc-by-4.0Jan 2024View details →

Data and code for: Shedding light on overlooked pollinators: Global insights into floral interactions of velvet ants (Hymenoptera: Mutillidae and Myrmosidae)

Data and code used in the article "Shedding light on overlooked pollinators: Global insights into floral interactions of velvet ants (Hymenoptera: Mutillidae and Myrmosidae)".

opencc-by-4.0Aug 2022View details →

Dataset: Complex effects of chytrid parasites on the growth of the cyanobacterium Planktothrix rubescens across interacting temperature and light gradients

This dataset contains the raw and processed data used in the manuscript "Complex effects of chytrid parasites on the growth of the cyanobacterium Planktothrix rubescens across interacting temperature and light gradients", by Wierenga et al. (preprint: https://doi.org/10.1101/2022.02.24.481659). An explanation of the experiment and measurements is found in the manuscript, and detailed descriptions of the data files are available in the "_file_description.txt" files inside each folder of the dataset.

Fig. 5 in The effects of light-emitting diode and conventional lighting on sorghum physiology and sugarcane aphid interaction

Fig. 5. Mean ± SE photosynthetic rates (μmol CO2 m−2 s−1) of resistant (TX-7000 and KS-585) and susceptible (TX-2783 and DKS-37-07) sorghum cultivars grown under either conventional or light-emitting diodes. All plants were measured at 15 d afer infestation with sugarcane aphids. Bars with different letters are significantly different (Kruskal-Wallis ANOVA, df = 3; H> 27.14; P <0.01).

Fig. 7 in The effects of light-emitting diode and conventional lighting on sorghum physiology and sugarcane aphid interaction

Fig. 7. Mean ± SE chlorophyll loss at 15 d afer infestation under lightemitting diode and conventional lights (control-infested)/control.Different letters represent significant differences (P <0.001) with a Kruskal-Wallis ANOVA followed by Dunn's multiple comparison test (H = 62.629; df = 7).

Fig. 3 in The effects of light-emitting diode and conventional lighting on sorghum physiology and sugarcane aphid interaction

Fig. 3. Susceptible sorghum variety KS-585 across 4 treatments: (A) control under light-emitting diodes; (B) infested under light-emitting diodes; (C) control under conventional lights; (D) infested under conventional lights. Plants were infested with sugarcane aphids and assessed 15 d post infestation.

Fig. 2 in The effects of light-emitting diode and conventional lighting on sorghum physiology and sugarcane aphid interaction

Fig. 2. Resistant sorghum variety TX-2783 across 4 treatments: (A) control under light-emitting diodes; (B) infested under light-emitting diodes; (C) control under conventional lights; (D) infested under conventional lights. Plants were infested with sugarcane aphids and assessed 15 d post infestation.

Fig. 1 in The effects of light-emitting diode and conventional lighting on sorghum physiology and sugarcane aphid interaction

Fig. 1. Light emission spectrum of the 9 band 60-watt light-emitting diode grow panels over the visible spectrum and into the near infrared.

Fig. 6 in The effects of light-emitting diode and conventional lighting on sorghum physiology and sugarcane aphid interaction

Fig. 6. Mean ± SE stomatal conductance (mol H2O m−2 s−1) at 15 d af- ter infestation under light-emitting diode and conventional lights. Bars with different letters are significantly different (Kruskal-Wallis ANOVA, df = 3; H> 24.13; P <0.01).

Fig. 4 in The effects of light-emitting diode and conventional lighting on sorghum physiology and sugarcane aphid interaction

Fig. 4. Mean ± SE number of sugarcane aphids per plant 15 d afer infestation when grown for resistant (TX-2783 and DKS-37-07) and susceptible (TX-7000 and KS-585) sorghum cultivars grown under either conventional or light-emitting diodes. P-values represent results of a Student's t-test (df = 22) for each variety.

Fig. 2 in LED grow lights alter sorghum growth and sugarcane aphid (Hemiptera: Aphididae) plant interactions in a controlled environment

Fig. 2. Growth characteristics of grain sorghum grown under conventional lighting (A) from within an environmental chamber, fitted with a W2238 LED grow panel (B and C, see Fig. 1 for light spectrum measured), and for sorghum cv MORHC 858, DKS 37-07, TX 2783, and WSH117 afer 21 d in a growth chamber fitted with a W2238 LED grow panel.

Fig. 3 in LED grow lights alter sorghum growth and sugarcane aphid (Hemiptera: Aphididae) plant interactions in a controlled environment

Fig. 3. Number of true leaves on 4 different sorghum entries grown under conventional and LED light sources.

Fig. 4 in LED grow lights alter sorghum growth and sugarcane aphid (Hemiptera: Aphididae) plant interactions in a controlled environment

Fig. 4. Plant height (cm) for 2 different sorghum entries grown under conventional and LED light sources.

Fig. 1 in LED grow lights alter sorghum growth and sugarcane aphid (Hemiptera: Aphididae) plant interactions in a controlled environment

Fig. 1. Light emission spectrum of the W2238 LED grow panel over the visible spectrum and into the near infrared. The inset spectrum is zoomed vertically to show details of any weaker emissions.