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37 results for “mechanical feedback”

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zenodo44/100

Supplemental data for "Intramolecular feedback regulation of the LRRK2 Roc G domain by a LRRK2 kinase dependent mechanism" (Gilsbach et al., eLife 2024, doi:10.7554/eLife.91083)

<p><strong>Supportive data for the eLife version of record.</strong></p> <p><strong>(1) Data used for the Michaelis Menten Kinetics.</strong></p> <p><strong>HPLC-based assay.</strong> Steady-state kinetic measurements of LRRK2-mediated GTP hydrolysis were performed as previously described (Ahmadian et al., 1997). Briefly, 0.1 &micro;M of full-length LRRK2 was incubated with different amounts of GTP (0, 25, 75, 150, 250, 500, 1000, 2000, 3000 and 5000 &micro;M) and production of GDP was monitored by reversed phase C18 HPLC. To this end, the samples (10 &micro;l) were directly injected on a reversed-phase C18 column (pre-column: Hypersil Gold, 3&micro;m particle size, 4.6x10mm; main column: Hypersil Gold, 5&micro;m particle size, 4.6x250mm, Thermo Scientific) using an Ultimate 3000 HPLC system (Thermo Scientific, Waltham, MA, USA) in HPLC-buffer containing 50 mM KH<sub>2</sub>PO<sub>4</sub>/K<sub>2</sub>HPO<sub>4</sub> pH 6.0, 10&nbsp;mM tetrabutylammonium bromide and 10-15% acetonitrile. Subsequently, samples were analyzed using the HPLC integrator (Chromeleon 7.2, Thermo Scientific, Waltham, MA, USA). Initial rates of GDP production were plotted against the GTP concentration using GraFit5 (v.5.0.13, Erithacus Software). The number of experiments is indicated in the graph and data point is the average (&plusmn;s.e.m.) of indicated repetitions. The Michaelis-Menten equation was fitted to determine K<sub>M</sub> (&plusmn;s.e.) and k<sub>cat</sub> (&plusmn;s.e.). Excel sheets used for the calculation of means are provided. No values are reported if the HPLC separation failed (e.g. unstable baseline).</p> <p><strong>Charcoal GTP hydrolysis assay. </strong>The [&gamma;-32P]GTP charcoal assay was performed as previously described (Bollag and McCormick, 1995). Briefly, 0.1 &micro;M full-length LRRK2 or 0.5 &micro;M 6xHIS-MBP-RocCOR was incubated with different GTP concentrations, ranging from 75 &micro;M to 8 mM, in the presence of [&gamma;-<sup>32</sup>P] GTP in GTPase assay buffer (30 mM Tris pH 8, 150 mM NaCl, 10 mM MgCl<sub>2</sub>, 5% (v/v) Glycerol and 3 mM DTT). Samples were taken at different time-points and immediately quenched with 5% activated charcoal in 20 mM phosphoric acid. All non-hydrolyzed GTP and proteins were stripped by the activated charcoal and sedimented by centrifugation. The radioactivity of the isolated inorganic phosphates was then measured by scintillation counting. The initial rates of &gamma;-phosphate release and the Michaelis-Menten kinetics were calculated as described above.</p> <p><strong>(2) Profile plots (Raw data) obtained for the Mass photometry analysis for T1343A vs WT LRRK2.</strong></p> <p>MP was performed as described in (Guaitoli et al., 2023).<strong> </strong>Briefly, the dimer ratio of LRRK2 was determined on a Refeyn Two MP instrument (Refeyn). Prior to the experiment, a standard curve relating particle contrasts to molecular weight was established using a Native molecular weight standard (Invitrogen, 1:200 dilution in HEPES-based elution buffer: 50 mM HEPES [pH 8.0], 150 mM NaCl supplemented with 200 &micro;M desthiobiotin). Prior to mass photometry, the proteins, either WT or T1343A LRRK2, were incubated with 0.5 mM ATP or buffer (control) for 30 min at 30 ℃. The LRRK2 protein was diluted to 2x of the final concentration (end concentrations: 75 nM and 100 nM) in elution buffer. The optical setup was focused in 10 &mu;l elution buffer before adding 10 &micro;l of the adjusted protein sample. Depending on the obtained count numbers, acquisition times were chosen between 20 s to 1 min. The dimer ratio in each measurement was normalize according to the equation. The measurement was perfomed in triplicates.</p> <p><strong>(3) AlphaFold3 model of LRRK2-pT1343 either bound to GDP/Mg or GTP/Mg.</strong></p> <p>Using AlphaFold3 (Abramson et al., 2024), we modeled and compared the GDP vs the GTP-state of phospho-T1343 LRRK2. Interestingly, the AlphaFold3 model suggests, that the phosphate group of the pT1343 residue is orientated inwards thereby substituting the gamma phosphate of the GTP in the GDP-bound state of LRRK2. This finding is in well agreement with MD simulations published recently (Stormer et al., 2023).</p> <p><strong>(4) Western blot RAW files for the cell-based phospho Rab asssay (RAW data for Figure 6 supplement 2/ Supplemental Figure 4 in the preprint version, Gilsbach et al, 2024)</strong></p> <p>Cell-based LRRK2 activity assays were performed as previously described (Singh et al., 2022). Briefly,<strong> </strong>HEK293T cells were cultured in DMEM (supplemented with 10% Fetal Bovine Serum and 0.5% Pen/Strep). For the assay, the cells were seeded onto six-well plates and transfected at a confluency of 50-70% with SF-tagged LRRK2 variants using PEI-based lipofection. After 48 hours cells were lysed in lysis buffer [30 mM Tris-HCl (pH7.4), 150 mM NaCl, 1% NonidentP-40 substitute, complete protease inhibitor cocktail, PhosStop phosphatase inhibitors (Roche)]. Lysates were cleared by centrifugation at 10,000 x g and adjusted to a protein concentration of 1 &micro;g/&micro;l in 1x Laemmli Buffer. Samples were subsequently subjected to SDS PAGE and Western Blot analysis to determine LRRK2 pS935 and Rab10 T73 phosphorylation levels, as described below. Total LRRK2 and Rab10 levels were determined as a reference for normalization. For Western blot analysis, protein samples were separated by SDS&ndash;PAGE using NuPAGE 10% Bis-Tris gels (Invitrogen) and transferred onto PVDF membranes (Thermo Fisher). To allow simultaneous probing for LRRK2 on the one hand and Rab10 on the other hand, membranes were cut horizontally at the 140 kDa MW marker band. After blocking non-specific binding sites with 5% non-fat dry milk in TBST (1 h, RT) (25 mM Tris, pH 7.4, 150 mM NaCl, 0.1% Tween-20), membranes were incubated overnight at 4&deg;C with primary antibodies at dilutions specified below. Phospho-specific antibodies were diluted in TBST/ 5% BSA (Roth GmbH). Non-phospho-specific antibodies were diluted in TBST/ 5% non-fat dry milk powder (BioRad). Phospho-Rab10 levels were determined by the site-specific rabbit monoclonal antibody anti-pRAB10(pT73) (Abcam, ab230261) and LRRK2 pS935 was determined by the site-specific rabbit monoclonal antibody UDD2 (Abcam, ab133450), both at a dilution of 1:2,000. Total LRRK2 levels were determined by the in-house rat monoclonal antibody anti-pan-LRRK2 (clone 24D8; 1:10,000) (Carrion et al., 2017). Total Rab10 levels were determined by the rabbit monoclonal antibody anti-RAB10/ERP13424 (Abcam, ab181367) at a dilution of 1:5,000. For detection, goat anti-rat IgG or anti-rabbit IgG HRP-coupled secondary antibodies (Jackson ImmunoResearch) were used at a dilution of 1:15,000 in TBST/ 5% non-fat dry milk powder. Antibody&ndash;antigen complexes were visualized using the ECL plus chemiluminescence detection system (GE Healthcare) using the Stella imaging system (Raytest) for detection and quantification.</p> <p><strong>Figure 6 Source Data 1:</strong> <span>Images generated by the Stella system are shown which were used for quantification. The annotation file equals Figure6-figure supplement 2 (Gilsbach et al., eLife 2024, doi:10.7554/eLife.91083). The lines corresponding to&nbsp;</span>LRRK2 pS935, total LRRK2, Rab10 pT73 and total Rab10 were <span>used for the quantification shown in Figure 6.</span></p>

opencc-by-4.0Nov 2024View details →
zenodo44/100

Dataset for "Low-cloud feedback in CAM5-CLUBB: physical mechanisms and parameter sensitivity analysis"

<p>This repository contains the data of&nbsp;512&nbsp;perturbed-parameter&nbsp;ensemble experiments&nbsp;and CAM5-CLUBB default experiments for the paper &quot;Low-cloud feedback in CAM5-CLUBB: physical mechanisms and parameter sensitivity analysis&quot;.</p> <p>In this paper, the quasi-Monte Carlo (QMC) sampling approach is applied to explore the high-dimensional space. 512 samples are generated with the 18 perturbed parameters. For each parameter sample, a pair of experiments is performed: the control one is based on the climatological sea surface temperature (SST), and the 4K experiment applies a uniform +4K SST perturbation to the control experiment. The total of 1024 simulations are then performed.&nbsp;In addition, CAM5-CLUBB default experiments that adopt the default values of the 18 selected parameters as in Bogenschutz et al. (2013) are performed to provide detailed model diagnostics for analyzing physical mechanisms of the cloud feedback, and they include both control and +4K simulations. Each simulation is run for 5 years and 4 months, forced by climatological SSTs. Monthly mean results from the last 5 years are analysed in this study.</p> <p>Note: data uploaded here is&nbsp;annual-mean and&nbsp;the dimension name &#39;time&#39; in the files (CAM5-CLUBB_PPE_512*.nc) is the number of 512 PPE member.</p>

opencc-by-4.0Jun 2018View details →
dryad36/100

Data from: Mechanical feedback and robustness of apical constrictions in Drosophila embryo ventral furrow formation

<p>Formation of the ventral furrow in the Drosophila embryo relies on the apical constriction of cells in the ventral region to produce bending forces that drive tissue invagination. Recently [J Phys Condens Matter. 2016;28(41):414021], we observed that apical constrictions during the initial phase of ventral furrow formation produce elongated patterns of cellular constriction chains prior to invagination, and argued that these are indicative of tensile stress feedback. Here, we quantitatively analyze the constriction patterns preceding ventral furrow formation and find that they are consistent with the predictions of our active-granular-fluid model of a monolayer of mechanically coupled stress-sensitive constricting particles. Our model shows that tensile feedback causes constriction chains to develop along underlying precursor tensile stress chains that gradually strengthen with subsequent cellular constrictions. As seen in both our model and available optogenetic experiments, this mechanism allows constriction chains to penetrate or circumvent zones of reduced cell contractility, thus increasing the robustness of ventral furrow formation to spatial variation of cell contractility by rescuing cellular constrictions in the disrupted regions.</p>

opencc-zeroJun 2021View details →
zenodo36/100

Raw data to: Biochemical Analyses of Cystatin-C Dimers and Cathepsin-B reveals a Trypsin-Driven Feedback Mechanism in Acute Pancreatitis

<p>This repository contains the initial structures, full conformational ensembles sampled using the TIGER2hPE replica-exchange MD simulation technique, and clusters resulting from subsequent ccPCA analysis, to extract major complex structures between proteins. Also attached are the initial structures of mCTSB and mCST3 predicted by AlphaFold2.</p> <table> <tbody> <tr> <td> <p><strong>Simulation Nr.</strong></p> </td> <td> <p><strong>Components simulated<br></strong></p> </td> </tr> <tr> <td> <p><strong>1</strong></p> </td> <td> <p>CTSB</p> </td> </tr> <tr> <td> <p><strong>2</strong></p> </td> <td> <p>CTSB</p> </td> </tr> <tr> <td> <p><strong>3</strong></p> </td> <td> <p>CTSB + mCST3</p> </td> </tr> <tr> <td> <p><strong>4</strong></p> </td> <td> <p>CTSL + mCST3</p> </td> </tr> <tr> <td> <p><strong>5</strong></p> </td> <td> <p>CTSB + mCST3-R71</p> </td> </tr> <tr> <td> <p><strong>6</strong></p> </td> <td> <p>CTSB + mCST3-R45</p> </td> </tr> <tr> <td> <p><strong>7</strong></p> </td> <td> <p>CTSB + dCST3-R45</p> </td> </tr> <tr> <td> <p><strong>8</strong></p> </td> <td> <p>CTSB + dCST3-R28</p> </td> </tr> </tbody> </table>

opencc-by-4.0Sep 2024View details →
dryad36/100

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>

opencc-zeroDec 2021View details →
zenodo36/100

Assignment Feedback in School Choice Mechanisms

<p>Data and supplementary materials for the manuscript entitled &quot;Assignment Feedback in School Choice Mechanisms.&quot;&nbsp;</p>

opencc-by-4.0Dec 2021View details →
zenodo36/100

Data from: Active-feedback quantum control of an integrated, low-frequency mechanical resonator

<p>Source data for Figures.</p>

opencc-by-4.0Jul 2023View details →
ClinicalTrials.gov36/100

Preference on the Feedback Mechanisms of Dose Delivery Confirmation With the Breezhaler® Device Compared to the Ellipta® Device in Patients With Chronic Obstructive Pulmonary Disease (COPD)

ClinicalTrials.gov study NCT02551224. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad36/100

Data from: Mechanical feedback and robustness of apical constrictions in Drosophila embryo ventral furrow formation

Open the record for dataset details and reuse information.

publicJun 2021View details →
dryad32/100

Data from: Beyond plant-soil feedbacks: mechanisms driving plant community shifts due to land-use legacies in post-agricultural forests

Although biotic legacies of past agricultural practices are widespread and increasing in contemporary ecosystems, our understanding of the mechanisms driving such legacies is still poor. Forest understories on former agricultural land show low frequencies and abundance of typical woodland species when compared with ancient forests. These community shifts have been ascribed to the effects of dispersal limitation. A rarely considered mechanism is that post-dispersal processes driven by plant-associated communities determine the poor performance and recruitment of woodland indicators. Given the strong alterations in soil conditions due to former agricultural practices, we hypothesized that (abiotic) plant–soil feedbacks could be a major factor in community shifts. We addressed this hypothesis by comparing plant-associated communities in the soil and above the ground in ancient and post-agricultural alluvial forests; then, we experimentally tested whether the changes in biotic and abiotic soil properties could affect above-ground herbivore abundance and pressure and plant performance. Ancient and post-agricultural communities clearly differed in composition at different levels of the food web. Besides the plant community, we also observed the differences in the microbial and nematode community with increased abundance of root-feeding nematodes in post-agricultural soils. The composition of the above-ground invertebrate community did not differ in ancient and post-agricultural forest parcels; however, plants growing in post-agricultural sites showed higher abundance of invertebrate herbivores and suffered more herbivory. Nutrient analyses of soil and plants showed that increased levels of phosphorus (and to a lesser extent, nitrogen) made plants more nutritious for insect herbivores. Laboratory experiments further pointed to this mechanism as an explanation of the poorer performance of woodland indicators in post-agricultural woodlands. Our results point to biotic and abiotic plant–soil feedbacks coupled with herbivory as a new mechanism to explain the legacy effects in temperate forests. The modification of the below-ground community and soil abiotic characteristics by previous agricultural activity affects not only the plant growth but also the plant nutrient content in the compared understorey species, making them more susceptible to above-ground herbivory. Our results provide one of the first examples of integrating plant–soil feedback and above- and below-ground interactions to explain land-use legacies.

opencc-zeroDec 2015View details →
zenodo32/100

SUSTAINED PITUITARY T3 PRODUCTION EXPLAINS THE T4-MEDIATED TSH FEEDBACK MECHANISM

<p>Supplemental data for the manuscript &quot;Sustained pituitary T3 production explains the T4-mediated TSH feedback&quot;</p>

opencc-by-4.0Aug 2023View details →
dryad32/100

The temporal dimension of plant-soil microbe interactions: mechanisms promoting feedback between generations

Open the record for dataset details and reuse information.

publicMay 2021View details →
dryad32/100

Data from: Beyond plant-soil feedbacks: mechanisms driving plant community shifts due to land-use legacies in post-agricultural forests

Open the record for dataset details and reuse information.

publicApr 2017View details →
dryad32/100

Data from: Mechanisms of resilience: empirically quantified positive feedbacks produce alternate stable states dynamics in a model of a tropical reef

Open the record for dataset details and reuse information.

publicMay 2017View details →
zenodo28/100

Data from: Feedback cooling of a room temperature mechanical oscillator close to its motional groundstate

<p>Source data for figures.</p>

opencc-by-4.0Nov 2019View details →
geo24/100

A system of checks and balances: an ERK-dependent feedback mechanism prevents hematopoietic stem cell exhaustion

GEO Series GSE112842. Mus musculus. 13 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenMay 2018View details →
geo24/100

Krüppel-like Transcription Factor-10 (KLF10) Provides a Negative Feedback Mechanism to Suppress TGFβ-Induced Epithelial-to-Mesenchymal Transition

GEO Series GSE90567. Homo sapiens. 46 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenMar 2017View details →
geo24/100

Chimeric activators and repressors define HY5 activity and a feedback control mechanism in Arabidopsis (HY5_RNAseq)

GEO Series GSE132859. Arabidopsis thaliana. 32 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenApr 2020View details →
ClinicalTrials.gov24/100

Effects of Lumbar Repositioning Feedback and Transversus Abdominis Training on Lumbar Propricption in Patients With Chronic Mechanical Low Back Pain

ClinicalTrials.gov study NCT05047614. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov24/100

Optimizing Gait Symmetry After Stroke Using Mechanical Constraints and Sensory Feedback

ClinicalTrials.gov study NCT07087769. IPD Sharing: NO. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →

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