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26 results for “force enhancement”
Cisplatin enhances cell stiffness and decreases invasiveness rate in prostate cancer cells by actin accumulation: Confocal and atomic force microscopy
<p><strong>Summary</strong></p> <p>Dataset of imaging data related to the publication Raudenska, M., Kratochvilova, M., Vicar, T., Gumulec, J., Balvan, J., Polanska, H. Pribyl, J. & Masarik, M.:Cisplatin enhances cell stiffness and decreases invasiveness rate in prostate cancer cells by actin accumulation. <em>Scientific Reports </em><strong>2019, </strong>9, 1660</p> <p>This dataset includes image data of <em>atomic force microcopy</em> (Young modulus) and <em>confocal microscopy</em>(staining of F-actin and β-tubulin) of prostate cell lines PNT1A, 22Rv1, and PC-3. </p> <p><strong>Materials and Methods</strong></p> <p><em>Cells, cell culture conditions</em></p> <p>Cells confluent up to 50–60% were washed with a FBS-free medium and treated with a fresh medium with FBS and required antineoplastic drug concentration (IC50 concentration for the particular cell line). The cells were treated with 93 µM (PC-3), 38 µM (PNT1A), and 24 µM (22Rv1) of cisplatin (Sigma-Aldrich, St. Louis, Missouri), respectively. IC50 concentrations used for treatment with docetaxel (Sigma-Aldrich, St. Louis, Missouri) were 200nM for PC-3, 70nM for PNT1A, and 150nM for 22Rv1. </p> <p><em>Long-term zinc (II) treatment of cell cultures</em></p> <p>Cells were cultivated in the constant presence of zinc(II) ions. Concentrations of zinc(II) sulphate in the medium were increased gradually by small changes of 25 or 50 µM. The cells were cultivated at each concentration no less than one week before harvesting and their viability was checked before adding more zinc. This process was used to select zinc resistant cells naturally and to ensure better accumulation of zinc within the cells (accumulation of zinc is usually poor during the short-term treatment of prostate cancer cells). Total time of the cultivation of cell lines in the zinc(II)-containing media exceeded one year. Resulting concentrations of zinc(II) in the media (IC50 for the particular cell line) were 50 µM for the PC-3 cell line, 150 µM for the PNT1A cell line, and 400 µM for the 22Rv1 cell line. The concentrations of zinc(II) in the media and FBS were taken into account. </p> <p><em>Actin and tubulin staining</em></p> <p>β-tubulin was labeled with anti- β tubulin antibody [EPR1330] (ab108342) at a working dilution of 1/300. The secondary antibody used was Alexa Fluor® 555 donkey anti-rabbit (ab150074) at a dilution of 1/1000. Actin was labeled with Alexa Fluor™ 488 Phalloidin (A12379, Invitrogen); 1 unit per slide. For mounting Duolink® In Situ Mounting Medium with DAPI (DUO82040) was used. The cells were fixed in 3.7% paraformaldehyde and permeabilized using 0.1% Triton X-100. </p> <p><em>Confocal microscopy</em></p> <p>The microscopy of samples was performed at the Institute of Biophysics, Czech Academy of Sciences, Brno, Czech Republic. Leica DM RXA microscope (equipped with DMSTC motorized stage, Piezzo z-movement, MicroMax CCD camera, CSU-10 confocal unit and 488, 562, and 714 nm laser diodes with AOTF) was used for acquiring detailed cell images (100× oil immersion Plan Fluotar lens, NA 1.3). Total 50 Z slices was captured with Z step size 0.3 μm.</p> <p><em>Atomic force microscopy</em></p> <p>We used the bioAFM microscope JPK NanoWizard 3 (JPK, Berlin, Germany) placed on the inverted optical microscope Olympus IX‑81 (Olympus, Tokyo, Japan) equipped with the fluorescence and confocal module, thus allowing a combined experiment (AFM‑optical combined images). The maximal scanning range of the AFM microscope in X‑Y‑Z range was 100‑100‑15 µm. The typical approach/retract settings were identical with a 15 μm extend/retract length, Setpoint value of 1 nN, a pixel rate of 2048 Hz and a speed of 30 µm/s. The system operated under closed-loop control. After reaching the selected contact force, the cantilever was retracted. The retraction length of 15 μm was sufficient to overcome any adhesion between the tip and the sample and to make sure that the cantilever had been completely retracted from the sample surface. Force‑distance (FD) curve was recorded at each point of the cantilever approach/retract movement. AFM measurements were obtained at 37°C (Petri dish heater, JPK) with force measurements recorded at a pulling speed of 30 µm/s (extension time 0.5 sec).</p> <p>The Young's modulus (E) was calculated by fitting the Hertzian‑Sneddon model on the FD curves measured as force maps (64x64 points) of the region containing either a single cell or multiple cells. JPK data evaluation software was used for the batch processing of measured data. The adjustment of the cantilever position above the sample was carried out under the microscope by controlling the position of the AFM‑head by motorized stage equipped with Petri dish heater (JPK) allowing precise positioning of the sample together with a constant elevated temperature of the sample for the whole period of the experiment. Soft uncoated AFM probes HYDRA-2R-100N (Applied NanoStructures, Mountain View, CA, USA), i.e. silicon nitride cantilevers with silicon tips are used for stiffness studies because they are maximally gentle to living cells (not causing mechanical stimulation). Moreover, as compared with coated cantilevers, these probes are very stable under elevated temperatures in liquids – thus allowing long-time measurements without nonspecific changes in the measured signal.</p> <p><em>Image analysis</em></p> <p>Fluorescence microscopy data were analyzed in ImageJ 1.52h and Python 3.7.1 as follows: cells were manually segmented using actin fluorescence channel, two regions were created for analysis: whole cell and cell periphery, lining a 4 μm thick region around cell border and including most of periphery actin cytoskeleton. In these two regions following parameters were measured for both actin and tubulin fluorescence: Integrated intensity, median intensity, and following regions were measured to describe cell morphology: Cell area, Maximum caliper (max feret diameter), roundness, and aspect ratio. Moreover, stress fibers were manually segmented in every cell and following parameters were measured: number of fibers per cell, feret angle of fiber, integrated intensity, fiber length, mean intensity. Next, a standard deviation of feret angles of individual fibers was calculated relatively to mean of feret angle using a circstd function from scipy package for Python.</p> <p><strong>Identification of files</strong></p> <p><em>Microscopy data</em></p> <p>Files are separated into individual zip files. The dataset of <em>confocal microscopy </em>is separated based on treatments: untreated control, docetaxel-treated cells, cisplatin-treated cells, zinc-treated cells. Filenames actin_tubulin_Zstack_cisplatin.zip, actin_tubulin_Zstack_untreated_control.zip, actin_tubulin_Zstack_zinc.zip, actin_tubulin_Zstack_docetaxel.zip. Files included in these ZIP archives are named as follows: "cellline_treatment_FOV". Files are 3-layer 16bit tiff files with layer sequence as follows: F-Actin (Phalloidin)/b-tubulin/Hoechst 33342. The dataset contains 242 FOVs of three cell line types/three treatments + one control, files are Z-stacks made of 50 slices.</p> <p>The dataset of <em>atomic force microscopy </em>(AFM) is included in one ZIP archive "AFM_YoungModulus_SetpointHeight.zip", which includes data on Young modulus and Setpoint Height of cell lines 22Rv1, PNT1A and PC-3 and treatments zinc, docetaxel, cisplatin (+control), i.e. identical like for confocal microscopy. The file naming is as follows: "AFM_cellline_treatment_FOV_Youngmodulus.tif" for Young modulus and "AFM_cellline_treatment_FOV_setpointheight.tif" for setpoint height. The data are filtered 32-bit tiff images, where the pixel value correspond to cell stiffness (young modulus) in Pa or setpoint height in m.</p> <p><em>Confocal microscopy analysis files</em></p> <p>Following files are csv tables including image analysis of actin/tubulin staining captured by confocal microscope:</p> <p>Cytoskeleton_fluo_analysis_Cell_Cell_periphery_morphology.csv: table includes analyzed data for actin and tubulin staining in following cellular regions: cell, cell periphery. Standard ImageJ parameters regarding intensity and morphology included.</p> <p>Cytoskeleton_fluo_analysis_Fibers.csv: table includes results of manual segmentation and consequent analysis of actin stres fibers in the cells. Apart from standard ImageJ parameters, also number of stress fibers per cell and standard deviation of fiber angle relative to the cell mean angle (for details see methods) are included.</p>
Mask or Enhance: Data Curation Aiding the Discovery of Piezoresponse Force Microscopy Contributors
<p>This repository contains the data used in the corresponding study:</p> <p>Mask or Enhance: Data Curation Aiding the Discovery of Piezoresponse Force Microscopy Contributors</p> <p><strong>Abstract</strong></p> <p>Piezoresponse force microscopy (PFM) is routinely used to probe the nanoscale electromechanical response of ferroelectric and piezoelectric materials. However, many challenges remain in the interpretation of the recovered signal. Specifically, many non-ferroelectric contributions affect the measured response, ranging from electrostatics, to charge injection and trapping, and topographic cross-talk. Recently, machine learning (ML) has been utilized to identify multiple contributors within complex data systems, such as PFM response. A substantial advancement in ML approaches for PFM techniques is offered by dimensional stacking, enabling encoding of physical and/or chemical correlations within the materials’ response across different data dimensions spanning varying ranges. However, dimensional stacking requires appropriate scaling for each dimension (before ML analysis) to minimize undesired information loss. Here, the impact of clustering globally and locally scaled parameters in polarization switching experiments via resonant PFM (RPFM) are discussed. Specifically, dimensional stacking of scaled parameters can mask or enhance ferroelectric and non-ferroelectric behaviors, and aid identification of various physical phenomena contributing to the measured RPFM response. This study highlights the importance of data curation for ML, and its role in identifying signal contributors to scanning probe microscopy (SPM)-based techniques with multidimensional data, such as resonant and/or spectroscopic SPM.</p>
Data for Figures 4, S2, S7-9 and emission data in the Publication "Enhanced Light Absorption and Radiative Forcing by Black Carbon Agglomerates"
<p>This repository contains the data to produce Figure 4, S2, S7-9 and emission data for the paper:</p> <p>"Kelesidis, G. A., Neubauer, D., Fan, L.-S., Lohmann, U., & Pratsinis, S. E. (2022). Enhanced light absorption and radiative forcing by black carbon agglomerates. <em>Environmental Science and Technology</em>, 56(12), 8610– 8618. <a href="https://doi.org/10.1021/acs.est.2c00428">https://doi.org/10.1021/acs.est.2c00428</a> "</p> <p>Note that the scripts are to be found in the accompanying package (https://doi.org/10.5281/zenodo.8167401)</p>
Data from: Effects of a titin mutation on force enhancement and force depression in mouse soleus muscles
The force produced by muscles varies with muscle length. Compared to isometric contractions at the same final length, force increases after lengthening, known as force enhancement, and decreases after shortening, known as force depression. The mechanisms of force enhancement remain unexplained by the sliding-filament and cross-bridge theories of muscle contraction. Although cross-bridge mechanisms have been proposed to account for force depression, so too have other mechanisms. In addition to cross bridges, titin has been suggested to contribute to both force enhancement and depression. Although titin is too compliant in passive muscles to contribute to active stiffness, recent evidence suggests that calcium activation increases titin stiffness. To test the hypothesis that titin plays a role in force enhancement and depression, we investigated muscle force in active and passive wild type and mdm soleus muscles after isovelocity stretching and shortening at three activation levels. Muscles from mdm mice (muscular dystrophy with myositis) have a predicted 83 amino acid deletion in the N2A region of titin and show no increase in stiffness when activated. We found that: 1) force enhancement and depression were reduced in mdm soleus compared to wild type muscles; 2) force enhancement increased with the amplitude of stretch across all activation levels in wild type and mdm muscles, while force depression increased with amplitude in wild type but not in mdm muscles; and 3) maximal shortening velocity of wild type and mdm muscles was similar, although active stress was reduced in mdm compared to wild type muscles. The results of this study suggest a role for titin in force enhancement and depression, which contribute importantly to regulation of muscle force during natural movements.
Residual force enhancement is reduced in permeabilized fiber bundles from mdm muscles
<p>Residual force enhancement (RFE) is the increase in steady-state force after active stretch relative to the force after isometric contraction at the same final length. The mdm mutation in mice, characterized by a small deletion in N2A titin, has been proposed to prevent N2A titin-actin interactions so that active mdm muscles are more compliant than WT. This decrease in active muscle stiffness should be associated with reduced RFE. We investigated RFE in permeabilized soleus (SOL) and extensor digitorum longus (EDL) fiber bundles from wild type and mdm mice. On each fiber bundle, we performed active and passive stretch from an average sarcomere length of 2.6 - 3.0 &[mu]m at a slow rate of 0.04 &[mu]m/s, as well as isometric contractions at the initial and final lengths. One-way ANOVA showed that SOL and EDL fiber bundles from mdm mice exhibited significantly lower RFE than WT (P < 0.0001). This result is consistent with previous observations in single myofibrils and intact muscles. However, it contradicts the results from a previous study which appeared to show that compensatory mechanisms could restore titin force enhancement in single fibers from mdm psoas. We suggest that force enhancement measured previously in mdm single fibers was an artifact of the high variability in passive tension found in degenerating fibers, which begins after ~24 days of age. The results are consistent with the hypothesis that RFE is reduced in mdm skeletal muscles due to impaired Ca2+ dependent titin-actin interactions resulting from the small deletion in N2A titin.</p>
Other Supplementary Material for 'Myosin-I Synergizes with Arp2/3 Complex to Enhance Pushing Forces of Branched Actin Networks' by Xu et al.
<div> <p>Other Supplementary Material for "Myosin-I Synergizes with Arp2/3 Complex to Enhance Pushing Forces of Branched Actin Networks" by Xu, Rutkowski, Rebowski, Boczkowska, Pollard, Dominguez, Vavylonis, and Ostap, bioRxiv, <a href="https://doi.org/10.1101/2024.02.09.579714" rel="nofollow">https://doi.org/10.1101/2024.02.09.579714</a> </p> <p> </p> </div>
Data for manuscript "Mechanisms and Impacts of a Partial AMOC Recovery Under Enhanced Freshwater Forcing"
<p><strong>Data repository for manuscript "Mechanisms and Impacts of a Partial AMOC Recovery Under Enhanced Freshwater Forcing"</strong></p> <p>Here we describe the data stored in this archive, which has been used for the manuscript "Mechanisms and Impacts of a Partial AMOC Recovery Under Enhanced Freshwater Forcing", submitted to Geophysical Research Letters. This data archive includes two primary folders, one containing the CESM data and one containing the 2D model data. Within each of those folders are appropriately titled subfolders for the different model simulations and variables, in accordance with the descriptions provided in the manuscript. The following provides a description of the data within each folder: </p> <p><br> ----------------------------------------<br> ------------- CESM DATA --------------<br> ----------------------------------------<br> The CESM data folder has been split into four subfolders, one for each simulation: Control simulation (CESM_controlrun), 0.1 Sv freshwater flux simulation (CESM_0pt1Sv_FWFrun), the longer repeat of the 0.1 Sv freshwater flux simulation (CESM_0pt1Sv_FWFrun_repeat), and the 0.15 Sv freshwater flux simulation (CESM_0pt15Sv_FWFrun). Within each of these can be found folders for each of the 6 variables we have used: 4D temperature fields (TEMP), 4D salinity fields (SALT), 4D potential density fields (PD), 3D MOC fields (MOC), 3D mixed layer depth fields (HMXL), and 2D meridional heat transport fields (N_HEAT). Each CESM data file (one per monthly time step) is saved in netcdf format (.nc4), containing all appropriate dimensional data and descriptive meta data. Note that only the data used in the manuscript has been stored (e.g. only MOC data is provided for the CESM_0pt15Sv_FWFrun, while all fields have been provided for the CESM_0pt1Sv_FWFrun). </p> <p>----------------------------------------<br> ------------ 2D MODEL DATA -----------<br> ----------------------------------------<br> As described in the manuscript, the 2D model has been run using various choices of input parameter and freshwater flux. For each selection of parameter choice a new control run is first required, from which a set of experiments is then initiated. The 2D model data folder therefore contains 2 main subfolders, one containing the control run data for each of set of parameter choices (control_runs),and one containing the freshwater perturbation experiments for each set of parameter choices (fwp_change_exps). Within those, each control and experiment folder is titled according to the choices of vertical viscosity (kvd), Southern Ocean wind stress perturbation (txp), and the freshwater perturbation (fwp); when absent from the title, the default value for that variable is used (i.e. kvd=1e4 m2/s; txp=0.2 N/m2). The naming convention for the Southern Ocean wind stress is minpt07 for 0.13 N/m2 (i.e. minus 0.07) and pt07 for 0.27 N/m2. </p> <p>Model output data has been provided in ascii format for: the 2D Eulerian AMOC fields (MOC_EUL.dat.dat), 2D Quasi-Lagrangian fields (MOC_QLag.dat), 2D Salinity fields (salt2D.dat), 2D temperature fields (temp2d.dat), 2D density fields (rho.dat), the latitude values (ytdeg.dat; ydeg.dat) and depth values (zt.dat, zw.dat), and the timeseries values for a number of variables (timeseries.dat): The timeseries.dat data has 19 columns, of which the first 13 are useful: </p> <p> column: description:<br> 1 time (year)<br> 2 mean basin temperature (deg.C)<br> 3 mean basin salinity (psu)<br> 4 mean basin density (kg/m3) <br> 5 kinetic energy (KE) density<br> 6 potential energy (PE)<br> 7 mean surface heat flux<br> 8 mean surface salinity flux<br> 9 minimum meridional overturning streamfunction (Sv)<br> 10 maximum meridional overturning streamfunction (Sv)<br> 11 minimum advective poleward heat transport (PW)<br> 12 maximum advective poleward heat transport (PW)<br> 13 MOC (Sv) = max(psi) in the north Atlantic</p> <p>The final subfolder in the 2D model directory is titled 'additional_data': The first folder contains the snapshot data (fwp025_snapshots; one subfolder for each snapshot) for the experiment run with 25 cm/s freshwater flux as shown in Fig. S6, in which the data is stored in the same format as described above. The second folder contains the tendency terms as shown in Fig. S7 (fwp025_tendency; one subfolder per tendency term for each of the control and 25 cm/s freshwater flux experiment), in which the data is provided in ascii format for the 2D tendency term and the depth and latitude values. </p>
Data from "Enhanced radiative forcing from aerosol-cloud interactions due to large-scale circulation adjustments" by Guy Dagan, Netta Yeheskel and Andrew I. L. Williams.
<p>This is the data presented in "Enhanced radiative forcing from aerosol-cloud interactions due to large-scale circulation adjustments" by Guy Dagan, Netta Yeheskel and Andrew I. L. Williams.</p> <p> </p> <p>Please read the README file for explanations about the data.</p> <p> </p>
Data from: Effects of a titin mutation on force enhancement and force depression in mouse soleus muscles
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Data from: Population spatial synchrony enhanced by periodicity and low detuning with environmental forcing
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Data from: IL-13 and IL-17A activate β1 integrin through an NF-kB/Rho kinase/PIP5K1γ pathway to enhance force transmission in airway smooth muscle
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Residual force enhancement is reduced in permeabilized fiber bundles from mdm muscles
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Tetanus-driven biohybrid multi-joint robots powered by muscle rings with enhanced contractile force
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Weak signal enhancement by non-linear resonance control in a forced nano-electromechanical resonator
<p>All the data for figures shown in the article entitled "Weak signal enhancement by non-linear resonance control in a forced nano-electromechanical resonator"</p>
Data for "Snow albedo feedbacks enhance snow impurity-induced radiative forcing in the Sierra Nevada"
<p>This is the data prepared for submission of "<strong>Snow albedo feedbacks enhance snow impurity-induced radiative forcing in the Sierra Nevada</strong>". Three folders are included: 1) The model output with aerosol deposition in snow (aero); 2) The model output without aerosol deposition in snow (noaero) 3) processed observations used to validate the model results (SPIReS)</p>
Compensating atmospheric adjustments reduce the volcanic forcing from Hunga stratospheric water vapor enhancement
<p>The uploaded scripts and data generate the figures of the manuscript "Compensating atmospheric adjustments reduce the volcanic forcing from Hunga stratospheric water enhancement."</p>
Impact of Enhanced External Counterpulsation (EECP) on Cardiac Force Index
ClinicalTrials.gov study NCT05080023. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
A Sensor-enhanced Mouth Guard to Quantitatively Measure Bite Compression Forces.
ClinicalTrials.gov study NCT06688474. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: Enhancement of optical force acting on vesicles via the binding of gold nanoparticles
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Forced enhancer-promoter rewiring to alter gene expression in animal models
GEO Series GSE221182. Homo sapiens. 10 samples. Type: Expression profiling by high throughput sequencing.
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