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10,561 results for “mechanics”
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (13/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Keizer et al. "Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics" – Data, software and documentation (16/16)
<p>Data, software and documentation to reproduce the results presented in [<a href="https://www.science.org/doi/10.1126/science.abi9810">Keizer <em>et al.</em> (2022) ‘<strong>Live-cell micromanipulation of a genomic locus reveals interphase chromatin mechanics</strong>’ Science, 377:6605</a>, DOI: 10.1126/science.abi9810].</p> <table> <tbody> <tr> <td> <p><strong>Description</strong></p> </td> <td> <p><strong>Location</strong></p> </td> </tr> <tr> <td> <p><strong>Centralized GitHub repository</strong> with:</p> <ul> <li>Local copy of all the code and trajectory/force files</li> <li>Jupyter notebooks to make all the graphs in Keizer <em>et al</em>.</li> <li>Pointers to all the datasets also shown in this table</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/Keizer-et-al">Keizer <em>et al.</em></a> repository</p> </td> </tr> <tr> <td> <p><strong>Raw microscopy data</strong>:</p> <ul> <li>Experiments performed with the <strong>30’-PR</strong> scheme</li> <li>Experiment performed with the<strong> 100”-PR</strong> scheme</li> <li>Experiment performed with high frame rate (<strong>dt = 0.5”</strong>)</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4626942">Zenodo 1</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627034">Zenodo 2</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626909">Zenodo 3</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626914">Zenodo 4</a> (30’-PR)<br> <a href="https://zenodo.org/record/4627010">Zenodo 5</a> (30’-PR)<br> <a href="https://zenodo.org/record/4626981">Zenodo 6</a> (100”-PR)<br> <a href="https://zenodo.org/record/6510099">Zenodo 7</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510103">Zenodo 8</a> (30’-PR)<br> <a href="https://zenodo.org/record/6510065">Zenodo 9</a> (dt = 0.5")<br> <a href="https://zenodo.org/record/6510105">Zenodo 10</a> (30’-PR)</p> </td> </tr> <tr> <td> <p>Concatenated TIFFs and timestamp files for all of the 30’-PR data.</p> </td> <td> <p><a href="https://zenodo.org/record/6510107">Zenodo 11</a> (1/2)<br> <a href="https://zenodo.org/record/6510109">Zenodo 12</a> (2/2)</p> </td> </tr> <tr> <td> <p><strong>Python pipeline </strong>to generate (i) concatenated movies, (ii) cropped and rotated movies for each cell, and (iii) force time profiles for each cell.</p> </td> <td> <p><a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository</p> </td> </tr> <tr> <td> <ul> <li><strong>Final registered and rotated TIFF files</strong>: <ul> <li><strong>30’-PR</strong> experiments: n = 35 cells</li> <li><strong>100”-PR</strong> experiment, including time projections & kymograph</li> <li><strong>dt = 0.5”</strong> experiments: n = 3 cells</li> <li><strong>no force</strong>: n = 11 cells before manipulation, n = 8 cells after manipulation</li> </ul> </li> <li><strong>Data files with trajectories and force time profiles</strong> for all analyzed cells</li> <li>Instructions and Fiji/Python scripts to reproduce these files.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510207">Zenodo 13</a></p> </td> </tr> <tr> <td> <p><strong>Single-MNPs fluorescence</strong>: raw data, Python/Fiji scripts and instructions</p> </td> <td> <p><a href="https://zenodo.org/record/6510209">Zenodo 14</a></p> </td> </tr> <tr> <td> <ul> <li>MagSim, <strong>Python library for magnetic simulations</strong></li> <li>Jupyter notebook for calibrating and generating maps (Fig. S5 & Fig. S6).</li> </ul> </td> <td> <p><a href="https://github.com/CoulonLab/MagSim">MagSim</a> repository</p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 1</strong>: Gradient of free GFP-ferritin in solution</p> <ul> <li>Raw microscopy data (6 pillars; Fig. S6B-C)</li> <li>Calculated force maps, with Fiji scripts and instructions to generate them.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/4627062">Zenodo 15</a></p> </td> </tr> <tr> <td> <p><strong>Force calibration – Method 2</strong>: Attraction of ferritin-coated beads (Fig. S7)</p> <ul> <li>Raw microscopy data (free diffusion and attraction)</li> <li>Python/Fiji scripts to calculate forces.</li> </ul> </td> <td> <p><a href="https://zenodo.org/record/6510211">Zenodo 16</a></p> </td> </tr> <tr> <td> <ul> <li><strong>Python library for force inference</strong> using different polymer models</li> </ul> </td> <td> <p><a href="https://github.com/SGrosse-Holz/rouselib">rouselib</a> repository</p> </td> </tr> </tbody> </table> <p><strong>License:</strong> All the code, data and documentation in this repository is under <a href="https://www.gnu.org/licenses/gpl-3.0.en.html">GPLv3</a> license. The <a href="https://hal-cnrs.archives-ouvertes.fr/hal-03740646"><em>Author Accepted Manuscript</em></a> of the study [Keizer <em>et al.</em> 2022] is under <a href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a> license. The <a href="https://www.science.org/doi/10.1126/science.abi9810"><em>Final Published Version</em></a>, published by AAAS, is not (<a href="https://www.science.org/content/page/science-licenses-journal-article-reuse">more information</a>).</p> <p> </p> <p><strong>Overview of the raw data repositories (Zenodo 1-10)</strong></p> <p><em>Refer to the Material and Methods section of the article for details on data production.</em></p> <p>Each Zenodo dataset represents one day of acquisition. It includes the data that was not retained for further downstream analysis. Each dataset contains:</p> <ul> <li>The raw MicroManager folder architecture (one folder contains multiple positions on the coverslip). On occasions where placement or removal of the external magnet led to a loss of focus, the acquisition was stopped and restarted, creating a new MicroManager folder each time. For instance: <ul> <li>The various positions were imaged before injection (folder with the <em>_preInjection,</em> <em>_1-pre-inj or _1-inj_1</em> suffix)</li> <li>These positions were imaged again after injection (suffix <em>_postInjection,</em> <em>_2-post-inj </em>or <em>_1-inj_2</em>) and before the magnet was added (suffix <em>_beforeexp</em> or <em>_before-attr</em>)</li> <li>They were imaged again with the magnet added (suffix <em>_attraction1</em>). If acquisition was stopped and restarted an extra folder is created (suffix <em>_attraction2</em>)</li> <li>They were then imaged after the magnet was removed (suffix <em>_release1</em>)</li> <li>Finally, the cells were monitored after the experiment (suffix <em>_after-exp</em> or <em>_postexp</em>)</li> </ul> </li> <li>A text file named <em>lab_journal_[...].txt</em> contains extra information the acquisition and experimental procedure</li> <li>Note: the MicroManager metadata in the TIFF file are fully populated</li> </ul> <p> </p> <p><strong>Overview of the concatenated datasets (Zenodo 11-12)</strong></p> <p>In these Zenodo repository, each position (acquired in different folders), is concatenated into a single TIFF movie using code available in the <a href="https://github.com/CoulonLab/chromag-pipeline">ChroMag-pipeline</a> repository. The folder contains:</p> <ul> <li>One TIFF file per selected position</li> <li>One .xls file per selected position, with one line per frame, and columns with the following information: <ul> <li><strong>path</strong> (Relative path): Reference to the original (raw MicroManager) file</li> <li><strong>start_time</strong> (Timestamp): Timestamp saved by MicroManager when the acquisition was started (the «acquire » button was pressed).</li> <li><strong>time_in_file</strong> (seconds): Number of seconds between start_time and the acquisition of the current timepoint</li> <li><strong>start_time_s</strong> (seconds): Variable start_time converted to a number of seconds</li> <li><strong>time</strong> (seconds): Sum of start_time and time_in_file</li> <li><strong>timestamp</strong> (Timestamp): Variable time, back-converted to a timestamp</li> <li><strong>timeOn</strong> (Timestamp): Time(s) when the magnet was added. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>timeOff</strong> (Timestamp): Time(s) when the magnet was removed. This timestamp is provided in the datasets.cfg file in the github repository chromag-pipeline</li> <li><strong>forceActivated</strong> (Boolean): If the magnet is present during the current frame (calculated from timeOn and timeOff)</li> <li><strong>seconds_since_first_magnet_ON</strong> (seconds): Number of (relative) seconds since the magnet was added for the first time.</li> <li><strong>Frame</strong> (Integer) Frame number (1-indexed)</li> <li><strong>Positions</strong> (Integer): The position number</li> </ul> </li> </ul> <p> </p> <p><strong>Processed datasets (Zenodo 13) and calibration datasets (Zenodo 14-16)</strong></p> <p>These datasets and their analysis are fully described in the <em>Materials and Methods</em> section of the article and in the different README.md files within the various folders of the datasets.</p>
Mechanical energy fluctuation in lower limbs during walking in participants with and without total hip replacement
<p>Mechanical energy fluctuation of the segments in the lower limbs during walking has not been fully investigated. It was hypothesised that the segments of the lower limbs may work as a pendulum, i.e., the kinetic and potential energies exchanged out of phase. This study aimed to investigate energy changes and recovery during gait in hip replacement patients. The gait data for 12 participants with total hip replacement and 12 age-matched controls were compared. The kinetic, potential, and rotative energies for the whole lower limb and thigh, calf, and foot, were calculated. The effectiveness of a pendulum effect was analysed. Gait parameters, e.g., walking speeds, cadence, and stride length were calculated. The results showed that the thigh had significant effectiveness as a pendulum during gait with an energy recovery coefficient of approximately 40% while the calf and foot were less like a pendulum during gait. In comparison, energy recoveries of the lower limbs in the two groups were not significantly different. If the centre of the pelvis was considered as approximate to the centre of mass, however, the control group had a higher energy recovery than the total hip replacement group by roughly 10%. This study concluded that the mechanical energy recovery mechanism in the lower limbs during walking exists for two groups.</p>
Chiral monoterpenes reveal forest emission mechanisms and drought responses
<p>This data was obtained during the Biosphere 2 - Water and Life Dynamics measurement campaign between September 2019 and December 2019 inside the Biosphere 2 tropical rainforest, Arizona, USA (DOI: 10.1126/science.abj6789). The Biosphere 2 tropical rainforest was subjected to a 4 month drought and rewetting experiment. This data includes mixing ratios of Isoprene, (-)-alpha-pinene, (+)-alpha-pinene, (-)-beta-pinene, (-)-limonene, (+)-limonene, (-)-camphene, (+)-camphene and gamma-terpinene calculated from data measured with a gas chromatograph - mass spectrometer. This data was sampled to see how the atmospheric concentration of compounds changed due to drought and rewetting.<br> The data also includes the 13C enrichment measurements of chiral monoterpenes and isoprene taken with a gas chromatograph - isotope ratio mass spectrometer and proton reaction mass spectrometer, respectively. The 13C enrichment experiments were conducted on two individual days during the campaign, once during pre-drought and once during the severe drought. This experiment was conducted to see which compounds became enriched in 13C when the atmosphere was exposed to a large amount of 13CO2.<br> Also included are sorbent tube measurements taken from branch cuvettes attached to Piper sp. and Clitoria fairchildiana plants, and also taken from soil chambers. The purpose of these measurements was to see how the emissions or uptakes of compounds from the plants and soil contributed to the total atmospheric concentration. The sorbent tubes were subsequently thermally desorbed into a gas chromatograph time of flight mass spectrometer.<br> Also included is the temperature, photosynthetically active radiation, relative humidity, vapour pressure deficit, soil moisture, and photosynthesis rate data</p>
A B cell actomyosin arc network couples integrin co-stimulation to mechanical force-dependent immune synapse formation
<p>B-cell activation and immune synapse (IS) formation with membrane-bound antigens are actin-dependent processes that scale positively with the strength of antigen-induced signals. Importantly, ligating the B-cell integrin, LFA-1, with ICAM-1 promotes IS formation when antigen is limiting. Whether the actin cytoskeleton plays a specific role in integrin-dependent IS formation is unknown. Here we show using super-resolution imaging of mouse primary B cells that LFA-1: ICAM-1 interactions promote the formation of an actomyosin network that dominates the B-cell IS. This network is created by the formin mDia1, organized into concentric, contractile arcs by myosin 2A, and flows inward at the same rate as B-cell receptor (BCR): antigen clusters. Consistently, individual BCR microclusters are swept inward by individual actomyosin arcs. Under conditions where integrin is required for synapse formation, inhibiting myosin impairs synapse formation, as evidenced by reduced antigen centralization, diminished BCR signaling, and defective signaling protein distribution at the synapse. Together, these results argue that a contractile actomyosin arc network plays a key role in the mechanism by which LFA-1 co-stimulation promotes B-cell activation and IS formation.</p>
Elevated O3 inhibited isoprene emission of a diploid and a triploid genotype of Populus tomentosa by different mechanisms
<p>Ozone (O<sub>3</sub>) pollution affects plant growth and isoprene (ISO) emission. However, the response mechanism of isoprene emission rate (ISO<sub>rate</sub>) to elevated O<sub>3</sub> (EO<sub>3</sub>) remains poorly understood. ISO<sub>rate</sub> was investigated in two genotypes (diploid and triploid) of Chinese white poplar (<em>Populus tomentosa</em> Carr.) exposed to EO<sub>3</sub> in an open top chamber (OTC) system. The triploid genotype had higher photosynthesis rate (A) and stomatal conductance (g<sub>s</sub>) than the diploid one. EO<sub>3</sub> significantly decreased A, g<sub>s</sub>, and ISO<sub>rate</sub> of middle and lower leaf positions in both genotypes. In the diploid genotype, the reduction of ISO<sub>rate</sub> was caused by a systematic decrease related to ISO synthesis capacity, as indicated by decreased contents of isoprene precursor dimethylallyl diphosphate (DMADP) and isoprene synthase (ISPS) protein and activity of ISPS. On the other hand, the negative effect of O<sub>3</sub> on ISO<sub>rate</sub> of the triploid genotype did not result from inhibited ISO synthesis capacity, but from increased ISO oxidative loss within the leaf. Our findings will be useful for breeding poplar genotypes with high-yield and lower ISO<sub>rate</sub>, depending on local atmospheric VOC/NO<sub>x</sub> ratio, to cope with both the rising O<sub>3</sub> concentrations and increasing biomass demand. They can also enlighten the incorporation of O<sub>3</sub> effects into process-based models of isoprene emission.</p>
A novel nematode species from the Siberian permafrost shares adaptive mechanisms for cryptobiotic survival with C. elegans dauer larva
<p>Some organisms in nature have developed the ability to enter a state of suspended metabolism called cryptobiosis<sup>1</sup> when environmental conditions are unfavorable. This state-transition requires the execution of complex genetic and biochemical programs<sup>1</sup><sup>,</sup><sup>2</sup><sup>,</sup><sup>3</sup>, that enables the organism to survive for prolonged periods. Recently, nematode individuals have been reanimated from Siberian permafrost after remaining in cryptobiosis. Preliminary analysis indicates that these nematodes belong to the genera <em>Panagrolaimus</em> and <em>Plectus</em><sup>4</sup>. Here, we present precise radiocarbon dating indicating that the <em>Panagrolaimus</em> individuals have remained in cryptobiosis since the late Pleistocene (~46,000 years). Phylogenetic inference based on our genome assembly and a detailed morphological analysis demonstrate that they belong to an undescribed species, which we named <em>Panagrolaimus n. sp</em>. Comparative genome analysis revealed that the molecular toolkit for cryptobiosis in <em>Panagrolaimus n. sp. </em>and in <em>C. elegans</em> is partly orthologous. We show that biochemical mechanisms employed by these two species to survive desiccation and freezing under laboratory conditions are similar. Our experimental evidence also reveals that <em>C. elegans</em> dauer larvae can remain viable for longer periods in suspended animation than previously reported. Altogether, our findings demonstrate that nematodes evolved mechanisms potentially allowing them to suspend life over geological time scales.</p>
Reaction Mechanism of the PET Degrading Enzyme PETase Studied with DFT/MM Molecular Dynamics Simulations
<p>Raw simulations of the acylation step by PETase on a PET dimer model substrate, ran with CP2K 6.1 software at the PBE:AMBER level. Details can be found in the original manuscript (<a href="https://doi.org/10.1021/acscatal.1c03700">https://doi.org/10.1021/acscatal.1c03700</a>): Molecular topology in AMBER Parameter Topology format and Trajectories in CHARMM binary coordinate format DCD.</p> <p>RESIDUE LIST:<br> GLY57<br> TYR58<br> SER131<br> MET132<br> TRP156<br> ASP177<br> SER178<br> ILE179<br> ALA180<br> HID208<br> MOL262</p> <p>VMD selection:<br> (name CA C O HA2 HA3 and resname GLY and resid 57) or (name N CA CB H HA HB2 HB3 and resname TYR and resid 58) or (name CA C O OG CB HA HB2 HB3 HG and resname SER and resid 131) or (name N CA SD CE CB CG H HA HB2 HB3 HG2 HG3 HE1 HE2 HE3 and resname MET and resid 132) or (name CB CG CD1 CD2 CE2 CE3 NE1 CZ2 CZ3 CH2 HB2 HB3 HD1 HE1 HE3 HZ2 HZ3 HH2 and resname TRP and resid 156) or (name CG OD1 OD2 CB HB2 HB3 and resname ASP and resid 177) or (name C O and resname SER and resid 178) or (name N CA C O CG2 CD1 CB CG1 H HA HB HG12 HG13 HG21 HG22 HG23 HD11 HD12 HD13 and resname ILE and resid 179) or (name N CA H HA and resname ALA and resid 180) or (name CB CG CD2 ND1 CE1 NE2 HB2 HB3 HD1 HD2 HE1 and resname HID and resid 208) or (name C1 C10 C11 C12 C13 C14 C15 C16 C17 C18 C19 C2 C20 C3 C4 C5 C6 C7 C8 C9 H1 H10 H11 H12 H13 H14 H15 H16 H17 H2 H3 H4 H5 H6 H7 H8 H9 O1 O2 O3 O4 O5 O6 O7 O8 O9 and resname MOL and resid 262)</p> <p>PYMOL selection:<br> (name CA+C+O+HA2+HA3 & resn GLY & resi 57) | (name N+CA+CB+H+HA+HB2+HB3 & resn TYR & resi 58) | (name CA+C+O+OG+CB+HA+HB2+HB3+HG & resn SER & resi 131) | (name N+CA+SD+CE+CB+CG+H+HA+HB2+HB3+HG2+HG3+HE1+HE2+HE3 & resn MET & resi 132) | (name CB+CG+CD1+CD2+CE2+CE3+NE1+CZ2+CZ3+CH2+HB2+HB3+HD1+HE1+HE3+HZ2+HZ3+HH2 & resn TRP & resi 156) | (name CG+OD1+OD2+CB+HB2+HB3 & resn ASP & resi 177) | (name C+O & resn SER & resi 178) | (name N+CA+C+O+CG2+CD1+CB+CG1+H+HA+HB+HG12+HG13+HG21+HG22+HG23+HD11+HD12+HD13 & resn ILE & resi 179) | (name N+CA+H+HA & resn ALA & resi 180) | (name CB+CG+CD2+ND1+CE1+NE2+HB2+HB3+HD1+HD2+HE1 & resn HID & resi 208) | (name C1+C10+C11+C12+C13+C14+C15+C16+C17+C18+C19+C2+C20+C3+C4+C5+C6+C7+C8+C9+H1+H10+H11+H12+H13+H14+H15+H16+H17+H2+H3+H4+H5+H6+H7+H8+H9+O1+O2+O3+O4+O5+O6+O7+O8+O9 & resn MOL & resi 262)</p>
Nanoindentation Dataset for the Microscale Mechanical Property of Granites
<p>This dataset contains the raw results of nanoindentation testing, which are used to determine the elastic and failure property of rock-forming minerals in granites, which then provides the input parameters for accurate grain-based modeling. The dataset is presented and utilized in the paper 'Thermally induced microcracks in granite and their effect on the macroscale mechanical behavior'. Full details of the experimental setup, procedure, and imaging analysis are able to be found in this paper.</p> <p>The results of nanoindentation testing of different rock-forming minerals by different indents are contained within six files: Berkovich_quartz, Berkovich_feldspar, Berkovich_biotite, Cube corner_quartz, Cube corner_feldspar and Cube corner_biotite. In these files, the raw data of nanoindentation testing includes elastic modulus, hardness, maximum load fore, maximum contact area, and contact depth. These results are then applied to calculate the elastic and failure properties of rock-forming minerals.</p>
Applying an Inconsistency Repair Mechanism for clone-and-own Code Smell Analysis: the Apo-games Case Study (Evaluation Data)
<p>This is a repository containing the artifacts and the results of the evaluation of the solution paper "Applying an Inconsistency Repair Mechanism for <em>clone-and-own</em> Code Smell Analysis: the Apo-games Case Study"</p>
Finite element models from: Mechanical compensation in the evolution of the early hominin feeding apparatus
<p>Australopiths, a group of hominins from the Plio-Pleistocene of Africa, are characterized by derived traits in their crania hypothesized to strengthen the facial skeleton against feeding loads and increase the efficiency of bite force production. The crania of robust australopiths are further thought to be stronger and more efficient than those of gracile australopiths. Results of prior mechanical analyses have been broadly consistent with this hypothesis, but here we show that the predictions of the hypothesis with respect to mechanical strength are not met: some gracile australopith crania are as strong as that of a robust australopith, and the strength of gracile australopith crania overlaps substantially with that of chimpanzee crania. We hypothesize that the evolution of cranial traits that increased the efficiency of bite force production in australopiths may have simultaneously weakened the face, leading to the compensatory evolution of additional traits that reinforced the facial skeleton. The evolution of facial form in early hominins can therefore be thought of as a trade-off between the need to increase the efficiency of bite force production and the need to maintain the structural integrity of the face. This may have implications for interpreting cranial form in other vertebrates.</p>
Elevational shifts in foliar-soil δ15N in the Hengduan Mountains and different potential mechanisms
<p><span>The natural abundance of stable nitrogen isotopes (δ<sup>15</sup>N) provides insights into the N dynamics of </span><span>terrestrial ecosystems, the determination of which is considered</span><span> an effective approach for gaining a better understanding ecosystem N cycling</span><span>. </span><span>However, there is currently little information available regarding the patterns and mechanisms underlying the variation in foliar-soil δ<sup>15</sup>N among mountain ecosystems. </span><span>In this study, we examined the determinants of foliar-soil δ<sup>15</sup>N in association with N transportation rates along an elevational gradient in the </span><span>Hengduan </span><span>Mountains.</span><span> Despite the relatively high levels of available N produced from high N fixation and mineralization, we detected the lowest levels of foliar δ<sup>15</sup>N at 3500 m a.s.l., reflecting the stronger vegetation N limitation at medium high elevations. The enhanced vegetation N limitation was driven by the combined effects of higher microbial immobilization and inherent plant dynamic (the shifts of δ<sup>15</sup>N in vegetation preference, including </span><span>vegetation community</span><span>) </span><span>with changing </span><span>climate along the elevational gradient.</span><span> </span><span>Unexpectedly</span><span>, we established that soil δ<sup>15</sup>N was characterized by an undulating rise and uncoupled correlation with foliar δ<sup>15</sup>N with increasing elevation, thereby indicating that litter input might not be a prominent driver of soil δ<sup>15</sup>N. Conversely, soil nitrification and denitrification were found to make a more pronounced contribution to the pattern of soil δ<sup>15</sup>N along the elevational gradient. Collectively, our results serve to highlight the importance of microbial immobilization in soil N dynamics and provide novel insights that will contribute to enhancing our understanding of N cycling</span><span> </span><span>as indicated by foliar-soil δ<sup>15</sup>N along elevational gradients.</span></p>
Atmospheric hydroxyl distribution from the EMAC model (MOM kinetic chemistry mechanism)
<p>This dataset contains the output from the simulations with the EMAC model implementing the MOM kinetic chemistry mechanism presented in <a href="https://doi.org/10.5194/acp-16-12477-2016">Lelieveld et al. (2016)</a> study. In addition to the computed atmospheric hydroxyl (OH) and hydroperoxyl (HO2) radicals abundance distributions, we add related model fields facilitating usage/comparison of these results with other estimates.</p><p>The data containers format is netCDF v.4 (compressed); please refer to the container variables/attributes for the extended information. We present here the actual model output (weekly averages for the 2013−2014 period, in EMAC-MOM__*.nc) and the monthly "climatology" fields (average, SD, minima and maxima of the time steps falling in particular month, in EMAC-MOM__*--clim.nc, respectively).</p><p>See the .README.pdf file for additional notes.</p><p>Changes w.r.t. initial version from 2020/09/22:</p><p>2020/10/30: Updated attributes and DOIs in .nc/.jnl files, added OH "climatology", updated README.</p><p>2020/10/31: Updated description and "climatology" (SD fields were missing).</p><p>2022/06/19: Added hydroperoxyl (HO2) fields, updated species average concentration plot sample script.</p><p>2023/10/26: Dataset title adjusted for clarity</p>
Data From: Shifts in morphological covariation and evolutionary rates across multiple acquisitions of the trap-jaw mechanism in Strumigenys
<p class="MsoNormal">A long-standing question in comparative biology is how the evolution of biomechanical systems influence morphological evolution. The need for functional fidelity implies that the evolution of such systems should be associated with tighter morphological covariation, which may promote or dampen rates of morphological evolution. I examine this question across multiple evolutionary origins of the trap-jaw mechanism in the genus <em>Strumigenys</em>. Trap-jaw ants have latch-mediated, spring actuated systems that amplify the power output of their mandibles. I use Bayesian estimates of covariation and evolutionary rates to test the hypotheses that the evolution of this high-performance system is associated with tighter morphological covariation in the head and mandibles relative to non-trap-jaw forms and that this leads to shifts in rates of morphological evolution. Contrary to these hypotheses, there is no evidence of a large-scale shift to higher covariation in trap-jaw forms while different traits show both increased and decreased evolutionary rates between forms. These patterns may be indicative of many-to-one mapping and/or mechanical sensitivity in the trap-jaw LaMSA system. Overall, it appears that the evolution of trap-jaw forms in <em>Strumigenys</em> did not require a correlated increase in morphological covariation, partly explaining the proclivity with which the system has evolved.</p>
Assignment feedback in school choice mechanisms
<p>This paper experimentally investigates the provision of real-time feedback about school assignments during the preference reporting period in three widely employed mechanisms: deferred acceptance, top trading cycles, and the Boston mechanism. Adaptive models predict that greater sensitivity to tentative assignments during the reporting period will produce more equilibrium assignments in all three mechanisms. Consistent with adaptive predictions, real-time assignment feedback consistently increased equilibrium assignments but did not increase truthful reporting. These findings suggest that providing feedback about assignments during the preference reporting period could help student assignment mechanisms more reliably achieve policy goals.</p>
Triaxial cycling loading of Westerly granite: Mechanical and Ultrasonic data
<p>Data obtained from triaxial cyclic loading experiments conducted on dry Westerly granite at confining pressure ranging from 40 to 120 MPa.</p> <p>Text files (.txt) are raw, unprocessed time series of mechanical data including load, shortening and radial and axial strain gauge measurements. Except noted, units are in Volts. Strain gauge voltages can be converted into strain using gauge factor of 2.11 and amplification factor of 40. External shortening can be converted to sample shortening using a machine stiffness of 480 kN/mm.</p> <p>Raw ultrasonic data are combined in folders named BSF*. Data format is binary, and can be read using ASC ltd. software "Insite".</p> <p>Files "sensors.txt" contain ultrasonic sensor positions and time offset corrections.</p>
Assignment Feedback in School Choice Mechanisms
<p>Data and supplementary materials for the manuscript entitled "Assignment Feedback in School Choice Mechanisms." </p>
Effects of hydrostatic dissolution and seepage on the transport and mechanical properties of glauberite
<p>Data presented and discussed in the article entitled "Effects of hydrostatic dissolution and seepage on the transport and mechanical properties of glauberite".</p>
Dataset for Cox et al. (2022), "Short communication: Mechanism and prevention of irreversible trapping of atmospheric He during mineral crushing," Geochronology 2021-42
<p>Dataset for Cox, S. E., Miller, H. B. D., Hofmann, F., and Farley, K. A.: Short Communication: Mechanism and Prevention of Irreversible Trapping of Atmospheric He During Mineral Crushing, Geochronology, https://doi.org/10.5194/gchron-2021-42, 2022.</p>
Additional movies for a manuscript titled 'Leaf epidermal cells respond to application and removal of mechanical force by distinct cytosolic calcium waves'
<p>This repository provides 21 additional videos that highlight the spectrum of mechanically stimulated calcium responses observed in the leaf epidermis of <em>Arabidopsis t</em>. expressing the genetically encoded calcium indicator R-GECO1. These movies correspond to figures in a manuscript entitled 'Leaf epidermal cells respond to application and removal of mechanical force by distinct cytosolic calcium waves'. In each movie, a cantilever exerts approximately 5 mN force to the epidermis (where the cantilever looks like a shadow in the movies). Each movie contains a scale bar and the relative time (hr:min:sec). Placement of the cantilever generally occurs after approximately 1 minute.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.