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opencc-by-4.0Jul 2024View details →

Supplementary material for the article "The Crystal Cargo Provides a Chronicle of Pre-Caldera Dynamics in Mafic Volcanic Systems: Insights from Colli Albani"

This repository contains the data and supplementary material associated with the manuscript: Ágreda-López M., Musu A., Jorgenson C., Sǎla M., Giordano G., Caricchi L., Stremtan C., Petrelli M. "The Crystal Cargo Provides a Chronicle of Pre-Caldera Dynamics in Mafic Volcanic Systems: Insights from Colli Albani".  Submitted to the Journal Bulletin of Volcanology. <div> </div>

opencc-by-nc-4.0Sep 2024View details →

Datasets, models and demos associated to "Celldetective: an AI-enhanced image analysis tool for unraveling dynamic cell interactions"

This repository contains datasets, models and demos associated to <a href="https://github.com/remyeltorro/celldetective">Celldetective</a>, a software for single-cell analysis from multimodal time lapse microscopy images.  <h1>Demos</h1> <h2>Cell-cell interaction assay: ADCC</h2> We imaged a co-culture of MCF-7 breast cancer cells (targets) and human primary NK cells (effectors), interacting in the presence of bispecific antibodies, to measure antibody dependent cellular cytotoxicity (ADCC). The nuclei of all cells are marked with the Hoechst nuclear stain, the dead nuclei with the propidium iodide nuclear stain, the cytoplasm of the NK cells with CFSE. The system in epifluorescence and brightfield at either 20 or 40X magnification. We provide a single position demo for the ADCC assay, as "demo_adcc.zip". After unzipping, the demo_adcc folder can be loaded in Celldetective for testing.  <h2>Cell-surface interaction assay: RICM</h2> We imaged human primary NK cells engaging in spreading with a surface coated with a bispecific antibody similar to the one used in the ADCC assay (replacing the target cells with a flat surface). The system is imaged using the RICM technique. Images are normalized using a median estimate of the background, pooled from all the positions in a well and dividing the images by this estimate. Here, we provide a single position demo for the cell-surface interactiona assay imaged in RICM, as "demo_ricm.zip". As above, after unzipping, the experiment can be tested and processed in Celldetective. <h1>Datasets</h1> <h2>Image annotations for segmentation</h2> <h3>Cell-cell interaction assay: ADCC</h3> We generated two sets of annotations from images of a co-culture of MCF-7 breast cancer cells and human primary NK cells, interacting in the presence of bispecific antibodies, to measure antibody dependent cellular cytotoxicity (ADCC). Since there are two separate cell populations of interest, the targets (MCF-7) and effectors (NK cells), we curated two datasets. Each sample in a dataset consists of a multichannel image (up to five channels in the context of ADCC, among brightfield , Hoechst nuclear stain, PI nuclear stain, CFSE, LAMP1), the associated instance segmentation annotation for the population of interest and a json file summarizing the content of each channel and the spatial calibration of the image. These sample data are generated directly in Celldetective, using a custom napari plugin. <ul> <li>db_mcf7_nuclei_w_lymphocytes: MCF-7 cell nuclei are annotated specifically on images where primary NK cells (or rarely primary T cells), and RBCs co-exist. The annotation exploits up to four channels simultaneously.</li> <li>db_primary_NK_w_mcf7: human primary NK cells, with annotated cytoplasm (mostly from CFSE) but exploiting brightfield and Hoechst to segment out of focus or poorly labelled cells.</li> </ul> These datasets are used to train several segmentation models to segment on one hand the MCF-7 nuclei and on the other hand the primary NK cells. <h3>Cell-surface interaction assay: RICM</h3> <ul> <li>db_spreading_lymphocytes: we provide a dataset of primary NK cells (and occasionnaly mice T cells) imaged in RICM (with sometimes paired brightfield images). Cells are detected as soon as they start forming interferences on the image (hovering behavior). A pre-annotation was performed using a threshold based segmentation on the RICM modality. Manuel separation of cell-cell contacts and removal of false positive objects was performed by an expert annotator (using brightfield when available). RBCs are ignored in the annotations. </li> </ul> <h2>Single-cell signal annotations for classification and regression</h2> <h3>Cell-cell interaction assay: ADCC</h3> We generated several signal classification/regression datasets with Celldetective to characterize the ADCC assay. Briefly, for a given event cells can be classified as "the event occured during the observation", "no event occured during the observation", "the event already occured prior to observation". If the event occurred during the observation, we can estimate when (the regression). Each single-cell is a dictionary with a collection of signals. The attribute "class" sets the class and "t0" the time of event (default is -1 for absence of event).  <ul> <li>db-si-NucPI: classification and regression of single-cells with respect to lysis events characterized by a strong PI increase upon lysis (also associated with decreasing nuclear area and sometimes a decreasing Hoechst)</li> <li>db-si-NucCondensation: classification and regression of single-cells with respect to nucleus shrinking events characterized by a decreasing nuclear area (UPDATE on 23/01/2024)</li> </ul> <h1>Models</h1> <h2>Segmentation models</h2> <h3>Generalist models</h3> We integrated in Celldetective select published models for cellular segmentation from StarDist and Cellpose. We wraped the models with an input configuration to help Celldetective handle the normalization, rescaling and channel selection upon inference.  <ul> <li>Cellpose [1,2]: cyto3, livecell, tissuenet, nuclei</li> <li>StarDist [3]: versatile_fluo, versatile_he</li> </ul> If you use any of these models your research, don't forget to cite the StarDist or Cellpose papers accordingly! <h3>ADCC models</h3> <ul> <li>MCF-7 (in the presence of lymphocytes): mcf7_nuc_multimodal, mcf7_nuc_stardist_transfer</li> <li>primary NKs (in the presence of MCF-7): primNK_multimodal, primNK_SD, primNK_cfse</li> </ul> <h3>Spreading-assay models</h3> <ul> <li>Lymphocytes: lymphocytes_ricm</li> </ul> <h2>Signal analysis models</h2> We developed Deep Learning models that classify and regress the time of events from single-cell signals, applied to the ADCC assay. <ul> <li> lysis detection: lysis_H_PI, lysis_PI_area. Detect lysis events characterized at least by an increase of PI from one or more measurements (respectively PI+Hoechst and PI+nucleus area, trained on db-si-NucPI)</li> <li>nucleus shrinking detection: NucCond. Detect nucleus shrinking events from nuclear area signal (db-si-NucCondensation)</li> </ul> <h1>References</h1> <ol> <li>Stringer, C., Wang, T., Michaelos, M. & Pachitariu, M. Cellpose: a generalist algorithm for cellular segmentation. Nat Methods 18, 100–106 (2021).</li> <li>Pachitariu, M. & Stringer, C. Cellpose 2.0: how to train your own model. Nat Methods 19, 1634–1641 (2022).</li> <li>Schmidt, U., Weigert, M., Broaddus, C. & Myers, G. Cell Detection with Star-Convex Polygons. in Medical Image Computing and Computer Assisted Intervention – MICCAI 2018 (eds. Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-López, C. & Fichtinger, G.) 265–273 (Springer International Publishing, Cham, 2018). doi:10.1007/978-3-030-00934-2_30.</li> </ol>

opencc-by-4.0Nov 2022View details →

Neonatal brain dynamic functional connectivity: impact of preterm birth and association with early childhood neurodevelopment (data)

Neonatal brain dynamic functional connectivity: impact of preterm birth and association with early childhood neurodevelopment

opencc-by-4.0Oct 2023View details →

The Dynamics of the India-Eurasia Collision: Faulted Viscous Continuum Models Constrained by High-Resolution Sentinel-1 InSAR and GNSS Velocities

Velocity field for the India-Eurasia collision zone from Sentinel-1 InSAR and GNSS data Citations: [1] Jin Fang, Gregory A Houseman, Tim J Wright, Lynn A Evans, Tim J Craig, John R Elliott and Andy Hooper (2023). The Dynamics of the India-Eurasia Collision: Faulted Viscous Continuum Models Constrained by High-Resolution Sentinel-1 InSAR and GNSS Velocities [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10053499 [2] Jin Fang, Gregory A Houseman, Tim J Wright, Lynn A Evans, Tim J Craig, John R Elliott and Andy Hooper (2024). The Dynamics of the India-Eurasia Collision: Faulted Viscous Continuum Models Constrained by High-Resolution Sentinel-1 InSAR and GNSS Velocities, Journal of Geophysical Research: Solid Earth, https://doi.org/10.1029/2023JB028571 More details about the methodology to generate the velocity field can be found in Wright et al. (2023): [3] Tim J Wright, Greg Houseman, Jin Fang, Yasser Maghsoudi, Andy Hooper, John Elliott, Lynn Evans, Milan Lazecky, Qi Ou, Barry Parsons, Chris Rollins, Lin Shen, Hua Wang (2023). High-resolution geodetic strain rate field reveals dynamics of the India-Eurasia collision, submitted to Science, preprint available at https://doi.org/10.31223/X5G95R.

opencc-zeroOct 2023View details →

A chromosome-scale assembly of the quinoa genome provides insights into the structure and dynamics of its subgenomes

Quinoa (Chenopodium quinoa Willd.) is an allotetraploid seed crop with the potential to help address global food security concerns. Genomes have been assembled for three accessions of quinoa; however, all assemblies are fragmented and do not reflect known chromosome biology. Here, we used in vitro and in vivo Hi-C data to produce a chromosome-scale assembly of the Chilean quinoa accession PI 614886 (QQ74). The final assembly spanned 1.326 Gb, of which 90.5% was assembled into 18 chromosome-scale scaffolds. The genome was annotated with 54,499 protein-coding genes, 97% of which were located on the 18 largest scaffolds. We also produced an updated genome assembly for the B-genome diploid C. suecicum and used it, together with the A-genome diploid C. pallidicaule, to identify genomic rearrangements within the quinoa genome, including a large pericentromeric inversion representing 71.7% of chromosome Cq3B. Repetitive sequences comprise 65.20%, 48.61%, and 57.91% of the quinoa, C. pallidicaule, and C. suecicum genomes, respectively. Evidence suggests that the B subgenome is more dynamic and has expanded more than the A subgenome. These genomic resources will enable more accurate assessments of genome evolution within the Amaranthaceae and will facilitate future efforts to identify variation in genes underlying important agronomic traits in quinoa.

opencc-zeroOct 2023View details →

Molecular Dynamics Simulations and associated data for: Mechanistic and evolutionary insights into isoform-specific 'supercharging' in DCLK family kinases

Catalytic signaling outputs of protein kinases are dynamically regulated by an array of structural mechanisms, including allosteric interactions mediated by intrinsically disordered segments flanking the conserved catalytic domain. The Doublecortin Like Kinases (DCLKs) are a family of microtubule-associated proteins characterized by a flexible C-terminal autoregulatory 'tail' segment that varies in length across the various human DCLK isoforms. However, the mechanism whereby these isoform-specific variations contribute to unique modes of autoregulation is not well understood. Here, we employ a combination of statistical sequence analysis, molecular dynamics simulations and in vitro mutational analysis to define hallmarks of DCLK family evolutionary divergence, including analysis of splice variants within the DCLK1 sub-family, which arise through alternative codon usage and serve to 'supercharge' the inhibitory potential of the DCLK1 C-tail. We identify co-conserved motifs that readily distinguish DCLKs from all other Calcium Calmodulin Kinases (CAMKs), and a 'Swiss-army' assembly of distinct motifs that tether the C-terminal tail to conserved ATP and substrate-binding regions of the catalytic domain to generate a scaffold for auto-regulation through C-tail dynamics. Consistently, deletions and mutations that alter C-terminal tail length or interfere with co-conserved interactions within the catalytic domain alter intrinsic protein stability, nucleotide/inhibitor-binding, and catalytic activity, suggesting isoform-specific regulation of activity through alternative splicing. Our studies provide a detailed framework for investigating kinome–wide regulation of catalytic output through cis-regulatory events mediated by intrinsically disordered segments, opening new avenues for the design of mechanistically-divergent DCLK1 modulators, stabilizers or degraders.

opencc-by-4.0Oct 2023View details →

On the computation of stable coupled state-space models for dynamic substructuring applications

This paper aims at introducing a methodology to compute stable coupled state-space models for dynamic substructuring applications by introducing two novel approaches targeted to accomplish this task: (a) a procedure to impose Newtons's second law without relying on the use of undamped RCMs (residual compensation modes) and (b) a novel approach to impose stability on unstable coupled state-space models. The enforcement of stability is performed by dividing the unstable model into two different models, one composed by the stable poles (stable model) and the other composed by the unstable ones (unstable model). Then, the poles of the unstable state-space model are forced to be stable, leading to the computation of a stabilized state-space model. If this model is composed by real poles, it should be divided into two different ones, one composed by the pairs of complex conjugate poles and the other composed by the real poles. Afterwards, to make sure that the Frequency Response Functions (FRFs) of the stabilized model well match the FRFs of the unstable model, the Least-Squares Frequency Domain (LSFD) method is exploited to update the modal parameters of the stabilized model composed by the pairs of complex conjugate poles. The validity of the proposed methodologies is presented and discussed by exploiting experimental data. Indeed, by exploiting the FRFs of a real system, accurate state-space models respecting Newton's second law are computed. Then, decoupling and coupling operations are performed with the identified state-space models, no matter the models resultant from the decoupling/coupling operations are unstable. Stability is then imposed on the computed unstable coupled model by following the approach proposed in this paper. The methodology proved to work well on these data. Moreover, the paper also shows that the coupled state-space models obtained using this methodology are suitable to be exploited in time-domain analyses and simulations.

XMCD data and XAS spectra, and simulation data for Clocked Dynamics in Artificial Spin Ice

Experimental dataRaw data of XMCD images collected at ALBA Synchrotron between 8th to 12th of September 2022. The data are used to create the experimental magnetization curves and magnetic contrast images in the paper Clocked dynamics in artificial spin ice. Additionally, XAS spectra of the Fe L3 edge obtained prior to imaging are included.Folder numbers starting at 225 through to 320 contain the data for the unipolar clocking experiment. The folder "001_XAS_Fe" contains the XAS spectrum of the sample taken prior to this series.  Folder numbers starting at 166 through to 217 contain the data for the bipolar clocking experiment. The folder "013_XAS_Fe_L3_CN" contains the XAS spectrum of the sample prior to this series.Simulation dataThe resulting data from flatspin simulations that are plotted as magnetization curves in the paper Clocked dynamics in artificial spin ice. The folder "flatspin-unipolar" contains the data for the unipolar clocking experiment. The folder "flatspin-bipolar" contains the data for the bipolar clocking experiment.

Data from: A pioneering experimental investigation of a novel in-situ dynamic characterization of the tensile/compression stress-strain mechanism on human plantar soft tissue

We have conducted the first in-situ and in-vivo dynamic mechanical test on human plantar soft tissue. A dynamic mechanical analysis (DMA)-like device has been invented to perform the in-situ and in-vivo stress-strain tests on living plantar in order to characterize the material mechanism of biological soft tissue, whereas it is nearly impossible to prepare a sample from a living body for classical tests. A series of pioneering tests of tensile/compression on the heel of ten volunteers are reported, with the reference of tests on mimic foot model made by silicon rubber, standard silicon rubber brick sample, and finite elementary analysis. In addition to demonstrating the effectiveness of the device and approach, interesting correlations between the results and clinic data were found, suggesting considerable potential for the invention in future research.

Dynamical Visualisations of Pendulum Motion

This submission includes two animated GIFs showcasing simulations of pendulum motion in two distinct scenarios: a massless pendulum and a damped pendulum. Both animations are generated using Python with the matplotlib library.

opengpl-3.0-or-laterNov 2023View details →

Unveiling Competition Dynamics in Mobile App Markets through User Reviews

This replication package contains the datasets and evaluation results for the research titled "Unveiling Competition Dynamics in Mobile App Markets through User Reviews", by Quim Motger, Xavier Franch, Vincenzo Gervasi and Jordi Marco.Latest version of the full code is available at: <a href="https://github.com/quim-motger/app-market-analysis">https://github.com/quim-motger/app-market-analysis</a>

Hybrid dynamic model for shape memory alloy linear and unimorph actuators

Shape memory alloy morphing actuators are a type of soft actuator with many attractive properties. These actuators exhibit large deformation, small form factor, self-sense ability, and physical reservoir computing potential, while also being inexpensive. These morphing actuators are composed of active shape memory alloy wires and a passive base layer that is used to magnify the overall deflection. Although morphing actuators have great potential, the modeling of shape memory alloy actuators is difficult due to both shape memory alloy characteristics and the nonlinearity of the passive layer. Here, a hybrid dynamical model is proposed that couples the phase kinetics & thermal modeling for the shape memory alloy with a dynamic Cosserat nonlinear beam model. This hybrid model is benchmarked against linear and morphing experimental actuators. The model resulted in a root mean squared error of 1.48 mm and 1.63 mm for the morphing actuator configuration for two different actuators. This model can expand the capability and design of novel morphing actuators for a designed deformation profile for use in soft robotics.

Dynamic energy landscapes of predators and the implications for modifying prey risk

Landscapes of fear describe a spatial representation of an animal's perceived risk of predation and the associated foraging costs, while energy landscapes describe the spatial representation of their energetic cost of moving and foraging. Fear landscapes are often dynamic and change based on predator presence and behavior, and variation in abiotic conditions that modify risk. Energy landscapes are also dynamic and can change across diel, seasonal, and climatic timescales based on variability in temperature, snowfall, wind/current speeds etc. Recently, it was suggested that fear and energy landscapes should be integrated. In this paradigm, the interaction between the landscapes relates to prey being forced into areas of the energy landscape they would avoid if risk were not a factor. However, dynamic energy landscapes experienced by predators must also be considered since they can affect their ability to forage, irrespective of variation in prey behavior. We propose an additional component to the fear and dynamic energy landscape paradigm that integrates landscapes of both prey and predators, where predator foraging behavior is modulated by changes in their energyscape. Specifically, we integrate the predators' energy landscape into foraging theory that predicts prey patch-leaving decisions under the threat of predation. We predict that as a predator's energetic cost of foraging increases in a habitat, then the prey's foraging costs of predation and patch quitting harvest rate will decrease. Prey may also decrease their vigilance in response to increased energetic foraging cost for predators, which will lower prey-giving-up densities. We then provide examples in terrestrial, aerial and marine ecosystems where we might expect to see these effects. These include birds, sharks which use updrafts that vary based on wind and current speeds, tidal state, or temperature and terrestrial predators (e.g. wolves) whose landscapes vary seasonally with snow depth or ice cover which may influence their foraging success and even diet selection. A predator perspective is critical to considering the combination of these landscapes and their ecological consequences. Dynamic predator energy landscapes could add a spatiotemporal component to risk effects which may cascade through food webs.

opencc-by-4.0Oct 2023View details →

The role of dynamics in heterogeneous catalysis: surface diffusivity and N2 decomposition on Fe(111)

Data related to the molecular dynamics simulations reported in the manuscript "The role of dynamics in heterogeneous catalysis: surface diffusivity and N2 decomposition on Fe(111)"- Inputs of the MD simulations of surface morphology and dynamics (LAMMPS)- Inputs of the OPES simulations for N2 adsorption and dissociation (LAMMPS+PLUMED)- MD outputs: trajectory files- Code for analysis and post-processed data- Jupyter notebook to reproduce the pictures reported in the manuscript

Rate-enhancing PETase mutations determined through DFT/MM molecular dynamics simulations†

Raw data for classical MD simulations ran with Gromacs 2018.3 for the two mutants Asp83Asn and Asp89Asn.Raw data for quantum mechanics/molecular mechanics simulations ran with CP2K 6.1 for the two mutants Asp83Asn and Asp89Asn.Distance and free energy analysis from the QM/MM MD simulations  for the wild-type and the two mutants Asp83Asn and Asp89Asn.

opencc-by-4.0Aug 2023View details →

Molecular dynamics trajectories, GROMACS input files, and analysis code from "Rational optimization of a transcription factor activation domain inhibitor" by Basu et. al, Nature Structural & Molecular Biology, 2023

Molecular dynamics trajectories, GROMACS input files, and analysis code from "Rational optimization of a transcription factor activation domain inhibitor" by Basu et. al, Nature Structural & Molecular Biology,  2023

opencc-by-4.0Jul 2023View details →

The steered discrete molecular dynamics simulation data of amyloids with EC1 and EC12 cadherin dimer

The steered discrete molecular dynamics (sDMD) simulation parameters are provided. Binding frequency of amyloids with EC1 and EC1-2 cadherin dimer. Trajectories of sDMD simulations of EC1 cadherin dimer with Abeta species.

opencc-by-4.0Jan 2023View details →

Dataset for Article: Potential of dynamic wind farm control by axial induction in the case of wind gusts

This is the dataset for the article "Potential of dynamic wind farm control by axial induction in the case of wind gusts". We provide the data as OUT-files from FAST.Farm simulation. Submission of revised manuscript: November 2023.

data for publication "Dynamics of soil nitrogen and N-cycling-related genes following the application of biobased fertilizers"

Dataset for the scientific publication titled "Dynamics of soil nitrogen and N-cycling-related genes following the application of biobased fertilizers" in the Journal <a href="https://www.sciencedirect.com/journal/applied-soil-ecology">Applied Soil Ecology</a>. <a href="https://doi.org/10.1016/j.apsoil.2023.105033">https://doi.org/10.1016/j.apsoil.2023.105033</a>

Data from: Evaluation of different bias correction methods for dynamical downscaled future projections of the California Current Upwelling System

Biases in global Earth System Models (ESMs) are an important source of errors when used to obtain boundary conditions for regional models. Here we examine historical and future conditions in the California Current System (CCS) using three different methods to force the regional model: (1) interpolation of ESM output to the regional grid with no bias correction; (2) a "seasonally-varying" delta method that obtains a season-dependent mean climate change signal from the ESM for a 30-year future period; and (3) a "time-varying" delta method that includes the interannual variability of the ESM over the 1980–2100 period. To compare these methods, we use a high-resolution (0.1˚) physical-biogeochemical regional model to dynamically downscale an ESM projection under the RCP8.5 emission scenario. Using different downscaling methods, the sign of future changes agrees for most of the physical and ecosystem variables, but the spatial patterns and magnitudes of these changes differ, with the seasonal- and time-varying delta simulations showing more similar changes. Not correcting the ESM forcing leads to amplification of biases in some ecosystem variables as well as misrepresentation of the California Undercurrent and CCS source waters. In the non-bias corrected and time-varying delta simulations, most of the ecosystem variables inherit trends and decadal variability from the ESM, while in the seasonally-varying delta simulation, the future variability reflects the observed historical variability (1980–2010). Our results demonstrate that bias correcting the forcing prior to downscaling improves historical simulations and that the bias correction method may impact the spatial and temporal variability of future projections.