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3,017 results for “grafting”

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zenodo48/100

Histological Dataset for Microvascular Segmentation of Tissue-Engineered Vascular Grafts

Objectives: The pursuit of understanding vascular tissue regeneration within tissue-engineered vascular grafts (TEVGs) is of paramount importance due to the critical role these grafts play in replacing damaged or diseased blood vessels. TEVGs offer a promising alternative to traditional grafts, with the potential to integrate into the host's tissue and support the natural regenerative processes. However, challenges such as thrombosis, inflammation, and the need for grafts that can adapt to the dynamic biological environment remain. By studying the regenerative processes in TEVGs, researchers can gain insights into the mechanisms that underpin successful graft integration and function, which is essential for improving patient outcomes in vascular surgeries. This dataset, with its detailed annotations of histological features, provides a valuable resource for developing and refining machine-learning models that can analyze and predict patterns of vascular tissue regeneration. The ability to accurately segment and quantify microvessels and immune cells in regenerated arteries is a significant step forward in distinguishing between physiological and pathological regeneration, ultimately contributing to the design of more effective and reliable TEVGs for clinical use. Ethical Approval: Experimental strategy of the study is described in detail in <a href="https://www.mdpi.com/2073-4360/14/23/5149" target="_blank" rel="noopener">[1]</a> and <a href="https://www.mdpi.com/1422-0067/24/10/8540" target="_blank" rel="noopener">[2]</a>. The study was conducted according to the guidelines of the Declaration of Helsinki, and was approved by the Local Ethical Committee of the Research Institute for Complex Issues of Cardiovascular Diseases (Kemerovo, Russia, protocol code 2020/06, date of approval: 19 February 2020). Animal experiments were performed in accordance with the European Convention for the Protection of Vertebrate Animals (Strasbourg, 1986) and Directive 2010/63/EU of the European Parliament on the protection of animals used for scientific purposes. For the implantation, we used female Edilbay sheep of 42–45 kg body weight which were received from the Animal Core Facility of the Research Institute for Complex Issues of Cardiovascular Diseases (Kemerovo, Russia) and selected for the surgery by Doppler ultrasonography to identify those having carotid artery diameter of 4.0 ± 0.2 mm. Description: The dataset comprises a collection of Whole Slide Images (WSIs) obtained from biodegradable TEVGs implanted into the carotid arteries of 20 sheep. A total of 104 WSIs were acquired, each measuring an average size of 135,000 x 123,000 pixels. These WSIs were stained using Hematoxylin and Eosin (H&E), a common practice for highlighting the structure of tissue sections, which facilitates the detailed examination of histological features. These WSIs were automatically sliced into 99,831 patches of 3,000 x 3,000 pixels and subsequently filtered, resulting in 1,401 selected patches for manual annotation. Annotation Method: Two pathologists independently selected and meticulously annotated the 1401 patches, identifying nine distinct histological features associated with vascular tissue regeneration. These features include arteriole lumen (AL), arteriole media (AM), arteriole adventitia (AA), venule lumen (VL), venule wall (VW), capillary lumen (CL), capillary wall (CW), immune cells (IC), and nerve trunks (NT). The annotations were performed using binary masks, delineating each feature within the patches. Subsequently, a senior pathologist conducted a triple verification process, reviewing and refining the annotations to ensure accuracy and consistency. The annotations are provided in the form of binary masks, meticulously defined for each feature within the patches. Dataset Split: Given the limited number of subjects studied, comprising 20 sheep, we employed a 5-fold cross-validation technique to split our dataset. This method was chosen because it allows for the efficient use of limited data, ensuring that each observation has the opportunity to be used in both the training and testing sets, thus reducing bias and providing a more accurate estimate of the model's performance. In this approach, each fold involved 16 sheep for training and the remaining 4 for testing (see Table 1 and Figure 3). This partitioning scheme was consistently applied to maintain the integrity of subject groups within each subset and to prevent data leakage. The 5-fold cross-validation is particularly beneficial for our study's objectives as it maximizes the training data available for developing robust machine learning models while also ensuring that the models are tested on unseen data, thereby enhancing the generalizability of our findings. Access to the Study: Further information about this study, including curated source code, dataset details, and trained models, can be accessed through the following repositories: <ul> <li>Source code: <a href="https://github.com/ViacheslavDanilov/histology_segmentation" target="_blank" rel="noopener">https://github.com/ViacheslavDanilov/histology_segmentation</a></li> <li>Dataset: <a href="https://doi.org/10.5281/zenodo.10838384" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10838384</a></li> <li>Models: <a href="https://doi.org/10.5281/zenodo.10838431" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10838431</a></li> </ul> <div> </div> <div>Table 1. Patch and feature distributions across folds and subsets <table> <tbody> <tr> <td> Fold </td> <td> Subset </td> <td> Patches </td> <td> AL </td> <td> AM </td> <td> AA </td> <td> VL </td> <td> VW </td> <td> CL </td> <td> CW </td> <td> IC </td> <td> NT </td> <td> Total </td> </tr> <tr> <td> 1 </td> <td> Train </td> <td> 1168 </td> <td> 510 </td> <td> 512 </td> <td> 220 </td> <td> 675 </td> <td> 648 </td> <td> 770 </td> <td> 765 </td> <td> 409 </td> <td> 448 </td> <td> 4957 </td> </tr> <tr> <td>1</td> <td> Test </td> <td> 233 </td> <td> 81 </td> <td> 84 </td> <td> 36 </td> <td> 186 </td> <td> 169 </td> <td> 178 </td> <td> 182 </td> <td> 91 </td> <td> 25 </td> <td> 1032 </td> </tr> <tr> <td> 2 </td> <td> Train </td> <td> 1053 </td> <td> 406 </td> <td> 411 </td> <td> 179 </td> <td> 678 </td> <td> 638 </td> <td> 743 </td> <td> 746 </td> <td> 423 </td> <td> 315 </td> <td> 4539 </td> </tr> <tr> <td>2</td> <td> Test </td> <td> 348 </td> <td> 185 </td> <td> 185 </td> <td> 77 </td> <td> 183 </td> <td> 179 </td> <td> 205 </td> <td> 201 </td> <td> 77 </td> <td> 158 </td> <td> 1450 </td> </tr> <tr> <td> 3 </td> <td> Train </td> <td> 1127 </td> <td> 507 </td> <td> 511 </td> <td> 222 </td> <td> 743 </td> <td> 702 </td> <td> 759 </td> <td> 760 </td> <td> 299 </td> <td> 423 </td> <td> 4926 </td> </tr> <tr> <td>3</td> <td> Test </td> <td> 274 </td> <td> 84 </td> <td> 85 </td> <td> 34 </td> <td> 118 </td> <td> 115 </td> <td> 189 </td> <td> 187 </td> <td> 201 </td> <td> 50 </td> <td> 1063 </td> </tr> <tr> <td> 4 </td> <td> Train </td> <td> 1064 </td> <td> 466 </td> <td> 472 </td> <td> 199 </td> <td> 611 </td> <td> 566 </td> <td> 759 </td> <td> 758 </td> <td> 423 </td> <td> 291 </td> <td> 4545 </td> </tr> <tr> <td>4</td> <td> Test </td> <td> 337 </td> <td> 125 </td> <td> 124 </td> <td> 57 </td> <td> 250 </td> <td> 251 </td> <td> 189 </td> <td> 189 </td> <td> 77 </td> <td> 182 </td> <td> 1444 </td> </tr> <tr> <td> 5 </td> <td> Train </td> <td> 1192 </td> <td> 475 </td> <td> 478 </td> <td> 204 </td> <td> 737 </td> <td> 714 </td> <td> 761 </td> <td> 759 </td> <td> 446 </td> <td> 415 </td> <td> 4989 </td> </tr> <tr> <td>5</td> <td> Test </td> <td> 209 </td> <td> 116 </td> <td> 118 </td> <td> 52 </td> <td> 124 </td> <td> 103 </td> <td> 187 </td> <td> 188 </td> <td> 54 </td> <td> 58 </td> <td> 1000 </td> </tr> </tbody> </table> </div>

opencc-by-4.0Mar 2024View details →

zenodo40/100

Research data supporting "Pericyte seeded dual peptide scaffold with improved endothelialization for vascular graft tissue engineering"

Raw research data supporting the paper: Campagnolo, P. et al., Pericyte seeded dual peptide scaffold with improved endothelialization for vascular graft tissue engineering, 2016, Advanced Healthcare Materials, 5(23), 3046-3055.

opencc-by-4.0Nov 2016View details →

zenodo40/100

Supported PdZn nanoparticles for selective CO2 conversion, through the grafting of a heterobimetallic complex on CeZrOx

Supplementary material:  IR, PXRD, N2 adsorption, EDS, TEM, XPS, EXAFS, testing data

opencc-by-4.0Mar 2022View details →

zenodo40/100

Local grafting heterogeneities control water intrusion and extrusion in nanopores

Datasets and scripts used to generate data.

opencc-by-4.0Dec 2024View details →

zenodo40/100

Figure 5 in Grafting increases superoxide dismutase and catalase activity to overcome the impact of the two-spotted spider mite on eggplant growth and productivity

Figure 5 Influence of TSSM infestation density on chlorophyll a+b (A) and carotenoids (B) content in grafted and non-grafted eggplant leaves. Means followed by the same letter(s) are not significantly different.

opencc-by-4.0Mar 2024View details →

zenodo40/100

Figure 3 in Grafting increases superoxide dismutase and catalase activity to overcome the impact of the two-spotted spider mite on eggplant growth and productivity

Figure 3 Effect of grafting on fruit number, fruit weight per plant and average fruit weight in grafted A338 on STT3 and non-grafted plants. The asterisk indicates statistical significance (P <0.05), and (ns) indicates not significant (P> 0.05) between two treatment analyzed by Two-tailed paired Student t-test.

opencc-by-4.0Mar 2024View details →

zenodo40/100

Figure 1 in Grafting increases superoxide dismutase and catalase activity to overcome the impact of the two-spotted spider mite on eggplant growth and productivity

Figure 1 Monthly abundance of TSSM egg (A), nymph (B) and adult (C) stages in grafted and nongrafted eggplants. Means followed by the same letter(s) are not significantly different.

opencc-by-4.0Mar 2024View details →

zenodo40/100

Grafting-from" and "grafting-to" PNIPAM functionalization of glass for DNA-biosensors with improved properties

Raw data and metadata for the study “Grafting-from” and “grafting-to” PNIPAM functionalization of glass for DNA-biosensors with improved properties" <ul> <li>Copy of labbooks for synthesis and surface functionalization protocols</li> <li>Molecular characterization: RMN, MS, GPC, LCST</li> <li>Surface characterization : water contact angle, surface quantification, XPS, antifouling properties</li> </ul>

opencc-by-4.0Sep 2023View details →

zenodo40/100

Extending a generic and fast coarse-grained molecular dynamics model to examine the mechanical behavior of grafted polymer nanocomposites: data set

Abstract: from [1] <blockquote> Polymer nanocomposites are an important class of materials for engineering applications due to their high versatility and good mechanical properties combined with low density. By directly attaching the polymer chains to the nanofillers, the so-called grafting, a better load transfer between matrix and filler is achieved, and, in addition, a better dispersion of the fillers is obtained. Both result in enhanced mechanical properties. Since experimental investigations on the nanoscale are extremely challenging, complementary numerical studies are needed to unravel the mechanical behavior of polymer nanocomposites. To this end, molecular dynamics is ideally suited since it captures the microstructure, but is also numerically expensive. Therefore, this contribution presents a fast coarse-grained molecular dynamics model for the investigation of the mechanical behavior of grafted polymer nanocomposites. For this purpose, we extend an existing model by grafting bonds, which allows us to compare the effect of untreated and grafted fillers directly. In particular, we investigate the influence of filler content, grafting degree, and filler size on the stiffness and strength of the polymer (grafted) nanocomposites. We conclude that the grafting bonds have little effect on the stiffness, while the strength is significantly improved compared to the untreated fillers, which is in agreement with the literature. The presented molecular dynamics model for polymer grafted nanocomposites provides the basis for further investigations, particularly of the crucial matrix-filler interphase. In addition, this contribution translates molecular dynamics insights into mechanical properties, which bridges the gap to the engineering scale and thus represents a step towards exploiting the full potential of polymer (grafted) nanocomposites. </blockquote>   Contact: Maximilian Ries Institute of Applied Mechanics Friedrich-Alexander-Universität Erlangen-Nürnberg Egerlandstr. 5 91058 Erlangen Software: All MD simulations were performed with LAMMPS [2,3], version: 29 Oct 2020 / 20201029 Compiled with Compiler: GNU C++ 4.8.5 20150623 (Red Hat 4.8.5-39) with OpenMP not enabled C++ standard: C++11 Active compile time flags: -DLAMMPS_GZIP -DLAMMPS_SMALLBIG Installed packages: CLASS2, KSPACE, MANYBODY, MC, MOLECULE, MPIIO, OPT, VORONOI, USER-INTEL, USER-MISC, USER-MOLFILE, USER-NETCD Polymer and polymer composite samples generated with self-avoiding random-walk algorithm [4] Post-processing Matlab R2019b License: Creative Commons Attribution 4.0 International Context: Data set supplementing  journal paper: [1] M. Ries, S. Reber, P. Steinmann, & S. Pfaller, “Extending a generic and fast coarse-grained molecular dynamics model to examine the mechanical behavior of grafted polymer nanocomposites,” Forces in Mechanics, vol. 12, p. 100 207, 2023. Content: structure of data set: <ul> <li>04_Equilibration folders containing the sample equilibration used in the presented parameter study <ul> <li>01_filler_content variation of filler content</li> <li>02_grafting_density variation of grafting density</li> <li>03_grafting_potential variation of grafting potential</li> <li>04_filler_size variation of filler size</li> <li>05_reference reference samples without grafting</li> </ul> </li> <li>05_UT folders containing the uniaxial tension simulations used in the presented parameter study <ul> <li>01_filler_content variation of filler content</li> <li>02_grafting_density variation of grafting density</li> <li>03_grafting_potential variation of grafting potential</li> <li>04_filler_size variation of filler size</li> <li>05_reference reference samples without grafting</li> </ul> </li> </ul> Each simulation directory contains: <ul> <li> lammps input file (*.in) of the specific simulation </li> <li> data file (*.data) containing the initial sample configuration </li> <li> input.prm: input parameters of the specific simulation (read by the input file) </li> <li> meta.info: meta data of the specific simulation run </li> <li> LAMMPS_out: simulation results (lammps thermo_out) in tabulated form, an overview of columns is given below <ul> <li> thermo_out.Dat: raw output  </li> <li> thermo_out_SG.Dat: smoothed output (Savitzky-Golay filter) </li> <li> thermo_out_STD.Dat: standard deviation of raw output </li> </ul> </li> </ul> Output quantities (columns of *.Dat files): Please note that the normalized Lennard-Jones unit set is used, so all quantities are normalized to fundamental mass, length, energy, time and the Boltzmann constant. Thus all entries are unitless [1]. <ul> <li> Step: time step  </li> <li> Time: time  </li> <li> TotEng: total energy  </li> <li> PotEng: potential energy </li> <li> KinEng: kinetic energy  </li> <li> E_pair: pair energy  </li> <li> E_bond: bond energy  </li> <li> E_angle: angle energy  </li> <li> E_dihed: dihedral energy  </li> <li> Temp: temperature </li> <li> Press: hydrostatic pressure </li> <li> Pxx: xx component of pressure tensor  </li> <li> Pyy: yy component of pressure tensor  </li> <li> Pzz: zz component of pressure tensor  </li> <li> Pxy: xy component of pressure tensor </li> <li> Pxz: xz component of pressure tensor </li> <li> Pyz: yz component of pressure tensor </li> <li> Volume: volume of simulation box  </li> <li> Lx: box length in x direction   </li> <li> Ly: box length in y direction   </li> <li> Lz: box length in z direction   </li> <li> Density: density   </li> <li> c_RG: radius of gyration scalar  </li> <li> c_RG[1]: squared radius of gyration tensor (xx component)   </li> <li> c_RG[2]: squared radius of gyration tensor (yy component)   </li> <li> c_RG[3]: squared radius of gyration tensor (zz component)   </li> <li> c_RG[4]: squared radius of gyration tensor (xy component)   </li> <li> c_RG[5]: squared radius of gyration tensor (xz component)   </li> <li> c_RG[6]: squared radius of gyration tensor (yz component)   </li> <li> c_bondave[1]: bond energy averaged over all atoms   </li> <li> c_bondave[2]: bond distance averaged over all atoms   </li> <li> c_bondave[3]: squared bond distance averaged over all atoms   </li> <li> c_angleave[1]: angle energy averaged over all atoms   </li> <li> c_angleave[2]: angle averaged over all atoms degree </li> <li> c_angleave[3]: cosine of angle  </li> <li> c_angleave[4]: squared cosine of angle  </li> <li> c_MSD[1]: mean squared displacement x-direction   </li> <li> c_MSD[2]: mean squared displacement y-direction   </li> <li> c_MSD[3]: mean squared displacement z-direction   </li> <li> c_MSD[4]: total mean squared displacement   </li> <li> c_COM[1]: x coordinate of center of mass   </li> <li> c_COM[2]: y coordinate of center of mass   </li> <li> c_COM[3]: z coordinate of center of mass   </li> <li> v_strain_xx: xx component of engineering strain tensor    </li> <li> v_strain_yy: yy component of engineering strain tensor     </li> <li> v_strain_zz: zz component of engineering strain tensor     </li> <li> v_vMisesequivstress: von Mises equivalent stress  </li> <li> v_Cauchy_xx: xx component of stress tensor   </li> <li> v_Cauchy_yy: yy component of stress tensor </li> <li> v_Cauchy_zz: zz component of stress tensor </li> <li> v_Cauchy_xy: xy component of stress tensor  </li> <li> v_Cauchy_xz: xz component of stress tensor  </li> <li> v_Cauchy_yz: yz component of stress tensor  </li> <li> v_strain_xy: xy component of engineering strain tensor    </li> <li> v_strain_xz: xz component of engineering strain tensor    </li> <li> v_strain_yz: yz component of engineering strain tensor    </li> </ul> References: [1] M. Ries et al., “Extending a generic and fast coarse-grained molecular dynamics model to examine the mechanical behavior of grafted polymer nanocomposites,” Forces in Mechanics, vol. 12, p. 100 207, 2023. [2] S. Plimpton, “Fast parallel algorithms for short-range molecular dynamics,” Journal of computational physics, 1995, 117, 1-19. [3] A. P. Thompson et al., “LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales,” Computer Physics Communications, vol. 271, p. 108171, 2022. [4] M. Ries, V. Dötschel, J. Seibert, S. Pfaller. “A self-avoiding random walk algorithm (SARW) for generic thermoplastic polymers and nanocomposites”, Zenodo, 2022. <a href="https://doi.org/10.5281/zenodo.6245699">https://doi.org/10.5281/zenodo.6245699</a>

opencc-by-4.0Sep 2023View details →

ClinicalTrials.gov40/100

Bandage Lenses in Treating Patients With Ocular Graft-Versus-Host Disease

ClinicalTrials.gov study NCT01616056. IPD Sharing: YES. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →

ClinicalTrials.gov40/100

Study of Pharmacokinetics, Activity and Safety of Ruxolitinib in Pediatric Patients With Grade II-IV Acute Graft vs. Host Disease

ClinicalTrials.gov study NCT03491215. IPD Sharing: YES. Countries: 8. Publications: 1.

controlledIPD-YESFeb 2026View details →

ClinicalTrials.gov40/100

Vedolizumab in the Prophylaxis of Intestinal Acute Graft Versus Host Disease (aGVHD) in Participants Undergoing Allogeneic Hematopoietic Stem Cell (Allo-HSCT) Transplantation

ClinicalTrials.gov study NCT03657160. IPD Sharing: YES. Countries: 27. Publications: 1.

controlledIPD-YESFeb 2026View details →

ClinicalTrials.gov40/100

Activity, Safety and Pharmacokinetics in Pediatric Subjects With Moderate and Severe Chronic Graft vs. Host Disease After Allogeneic Stem Cell Transplant

ClinicalTrials.gov study NCT03774082. IPD Sharing: YES. Countries: 14. Publications: 1.

controlledIPD-YESFeb 2026View details →

ClinicalTrials.gov40/100

Structural Fat Grafting for Craniofacial Trauma Using Manual Technique for Processing Fat Graft Material

ClinicalTrials.gov study NCT02267187. IPD Sharing: YES. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →

ClinicalTrials.gov40/100

Safety and Efficacy of Ruxolitinib Versus Best Available Therapy in Patients With Corticosteroid-refractory Acute Graft vs. Host Disease After Allogeneic Stem Cell Transplantation

ClinicalTrials.gov study NCT02913261. IPD Sharing: YES. Countries: 22. Publications: 5.

controlledIPD-YESFeb 2026View details →

zenodo36/100

The VSMC RNA-seq datasets for "Strategies for Arterial Grafts Optimization at Single Cell Level"

This dataset collection contains the human vascular smooth muscle cell (VSMC) bulk RNA-seq data generated in the study Strategies for Arterial Grafts Optimization at Single Cell Level. Primary human VSMCs (CP-H167, Pricella) were cultured in DM/F12 medium supplemented with FBS, EGF, bFGF, insulin, and penicillin (CM-P167, Pricella). The media was replaced per 48 hours. VSMCs were treated with 100ng/ml MIF (HY-P7387, MCE) for 24 hours in the absence or presence of 50 µMol ISO1 (HY-16692, MCE). The VSMCs with the passage number 3 to 5 were used in the study. Total RNA was extracted from cultured VSMC under different treatments using RNeasy Mini Kit (74104, Qiagen). A total amount of 1 µg RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using NEBNext® UltraTM RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. The library preparations were sequenced on an Illumina Novaseq platform and 150 bp paired-end reads were generated. The index of the reference genome was built using Hisat2 v2.0.5. and paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5. The sample info for the BAM files and their index files are listed as follows: <table> <tbody> <tr> <td>SampleCode</td> <td>Sample Description</td> </tr> <tr> <td>C1</td> <td>VSMC (replicate 1)</td> </tr> <tr> <td>C2</td> <td>VSMC (replicate 2)</td> </tr> <tr> <td>C3</td> <td>VSMC (replicate 3)</td> </tr> <tr> <td>M1</td> <td>VSMC treated with MIF (replicate 1)</td> </tr> <tr> <td>M2</td> <td>VSMC treated with MIF (replicate 2)</td> </tr> <tr> <td>M3</td> <td>VSMC treated with MIF (replicate 3)</td> </tr> <tr> <td>M_I1</td> <td>VSMC treated with MIF and ISO1 (replicate 1)</td> </tr> <tr> <td>M_I2</td> <td>VSMC treated with MIF and ISO1 (replicate 2)</td> </tr> <tr> <td>M_I3</td> <td>VSMC treated with MIF and ISO1 (replicate 3)</td> </tr> </tbody> </table>

opencc-by-4.0Mar 2024View details →

zenodo36/100

Figure 4 in Grafting increases superoxide dismutase and catalase activity to overcome the impact of the two-spotted spider mite on eggplant growth and productivity

Figure 4 Influence of TSSM infestation density on CAT (A) and SOD (B) enzyme activities, as well

opencc-by-4.0Mar 2024View details →

zenodo36/100

Figure 2 in Grafting increases superoxide dismutase and catalase activity to overcome the impact of the two-spotted spider mite on eggplant growth and productivity

Figure 2 Average total number of TSSM in grafted and non-grafted eggplants. Means followed by

opencc-by-4.0Mar 2024View details →

zenodo36/100

The Effect of Bone Graft Substitute in Healing Fractures with Bone Defects Through Examination of Alkaline Phosphatase and Radiology in the Murine Model (Rattus norvegicus) Wistar strain

Raw data for manuscript with the title The Effect of Bone Graft Substitute in Healing Fractures with Bone Defects Through Examination of Alkaline Phosphatase and Radiology in the Murine Model (Rattus norvegicus) Wistar strain

opencc-by-4.0Feb 2022View details →

dryad36/100

Towards bio-inspired polymer adhesives: Activation assisted via HOBt for grafting of dopamine onto poly(acrylic acid)

The design of bio-inspired polymers has long been an area of intense study, however applications to the design of concrete admixtures for improved materials performance have been relatively unexplored. In this work we functionalized poly(acrylic acid) (PAA), a simple analogue to polycarboxylate ether admixtures in concrete, with dopamine to form a catechol-bearing polymer (PAA-g-DA). Synthetic routes utilizing hydroxybenzotriazole (HOBt) as an activating agent were examined for their ability in grafting dopamine to the PAA backbone. Previous literature using the traditional coupling reagent 1-Ethyl-3-(3-dimethylaminopropyl)-carbodiimide (EDC) to graft dopamine to PAA were found to be inconsistent and the sensitivity of EDC coupling reactions necessitated a search for an alternative. Additionally, HOBt allowed for greater control over percent functionalization of the backbone, is a simple, robust reaction, and showed potential for scalability. This finding also represents a novel synthetic pathway for amide bond formation between dopamine and PAA. Finally, we performed preliminary adhesion studies of our polymer on rose granite specimens and demonstrated a 56% improvement in the median adhesion strength over unfunctionalized PAA. These results demonstrate an early study on the potential of PAA-g-DA to be utilized for improving the bonds within concrete.

opencc-zeroApr 2022View details →

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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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record