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915 results for “siRNA”
Topical-siRNA-therapy-1: Source data
<p>This repository contains the source data for the scientific article:</p> <p>article title: "Topical siRNA Therapy of Diabetic-Like Wound Healing"</p> <p>author: "Eva Neuhoferova & Marek Kindermann et al"</p> <p>date: "2024-19-12"</p> <p>description: "Functional and biocompatible wound dressing developed to enable a controlled release of a traceable vector loaded with the antisense siRNA against MMP-9 in the wound"</p> <ul> <li>primary data source: <a href="https://github.com/KindermannMarek/Topical-siRNA-therapy-1">https://github.com/KindermannMarek/Topical-siRNA-therapy-1</a></li> <li>the "README.md" file contains a description of the files stored in the repository</li> </ul>
Layer-by-Layer siRNA Particle Assemblies for Localized Delivery of siRNA to Epithelial Cells through Surface-Mediated Particle Uptake
<p>Localized delivery of small interfering RNA (siRNA) is a promising approach for spatial control of cell responses at biomaterial interfaces. Layer-by-layer (LbL) assembly of siRNA with cationic polyelectrolytes has been used in film and nanoparticle vectors for transfection. Herein, we combine the ability of particles to efficiently deliver siRNA with the ability of film polyelectrolyte multilayers to act locally. LbL particles were prepared with alternating layers of poly(l-arginine) and siRNA and capped with hyaluronic acid. Negatively charged LbL particles were subsequently assembled on the poly(l-lysine)-functionalized substrate to form a LbL particle-decorated surface. Cells grown in contact with the particle-decorated surface were able to survive, internalize particles, and undergo gene silencing. This work shows that particle-decorated surfaces can be engineered by using electrostatic interactions and used to deliver therapeutic payloads for cell-instructive biointerfaces.</p>
The role and mechanism of TLR4-siRNA in the impairment of learning and memory in young mice induced by isofurane
<p>This package contains six files:</p> <p>Supplementary Table 1. Morris water maze test results of each group;</p> <p>Supplementary Table 2. TLR4, TNF-ɑ and IL-6 expressions in the hippocampus of each group detected with qPCR and WB;</p> <p>Supplementary Table 3. Serum TNF-ɑ and IL-6 levels of mice in each group detected with ELISA;</p> <p>Supplementary Table 4. Apoptosis rate detected with TUNEL staining;</p> <p>Supplementary Table 5. BDNF and CREB1 mRNA expressions detected with qPCR;</p> <p>Supplementary Table 6. BDNF, CREB1, ERK1/2 and JNK protein expressions detected with WB.</p>
Microscope Image Analysis Course Sept 2109 -- Image Data siRNA Screen
<p>Contains 380 Fluorescence images of DAPI stained HeLa nuclei, acquired in 42 wells of a 384 well plate. individual wells were treated with siRNA according to the layout file. Images were acquired with an Olympus ScanR system at 10x magnification, maetadata is given in the experiment_descriptor.xml file.</p>
Transfection of NSD3-tareting siRNA in H1299 Cells
<p><strong>SGC Open Notebook Project to Characterize the HMTase NSD3</strong></p> <p><strong>Exp019 Objective: </strong> I have identified a putative phenotype in H1299 cells upon overexpression of the NSD3 short<br> isoform. I am also interested in any phenotype resulting from decreased amounts of NSD3 in cells. To<br> do so, I am first testing conditions for RNAi-mediated knockdown of NSD3 in H1299 cells by treating cells<br> with several concentrations of siRNA and evaluating knockdown by western blotting</p>
Microscope Image Analysis Course Sept 2109 -- Images siRNA Screen
<p>Contains 380 Fluorescence images of DAPI stained HeLa nuclei, acquired in 42 wells of a 384 well plate. individual wells were treated with siRNA. Images were acquired with an Olympus ScanR system at 10x magnification.</p>
Microscope Image Analysis Course Sept 2109 -- Images siRNA Screen
<p>Contains 380 Fluorescence images of DAPI stained HeLa nuclei, acquired in 42 wells of a 384 well plate. individual wells were treated with siRNA. Images were acquired with an Olympus ScanR system at 10x magnification.</p>
HUVEC CD44 siRNA perfusion tracking dataset
<p>This dataset contains tracking results of AsPC1 and MiaPaca cells perfused on CD44 siRNA-silenced endothelial monolayers under physiological flow speeds.</p> <p>Videos were recorded using a Nikon Eclipse Ti2-E microscope and 20x objective.</p> <p>Perfused cells from the generated videos were segmented using custom-trained Stardist models. Tracking was performed using TrackMate, and tracking results were analyzed using a custom CellTracksColab notebook. </p> <p>The dataset here contains the CSV files generated by TrackMate (Track and Spots information), the tracking data stored in the CellTracksColab format (Analysis.zip), and the analysis output used in the paper (Analysis.zip). </p> <h3>Specifications</h3> <ul> <li> <p>Sample information</p> </li> <ul> <li> <p>AsPC1 and MiaPaca cells perfused on HUVEC cells under physiological flow speeds: 400 µm/s (p1), 200 µm/s (p2), 100 µm/s (p3) and 400 µm/s (p4). </p> </li> <li> <p>CD44 siRNA silencing of the HUVEC monolayer</p> </li> </ul> <li> <p>Imaging specs</p> </li> <ul> <li> <p>Microscope: Nikon Eclipse Ti2-E, 20x objective</p> </li> <li> <p>Data Type: Brightfield microscopy images (16-bit)</p> </li> <li> <p>Image Size: 1024 x 1022 pixels (Pixel size: 650 nm)</p> </li> <li> <p>Recording speed 25 frames/s</p> </li> </ul> <li> <p>DL models:</p> </li> <ul> <li> <p>Cancer cells: <a href="https://doi.org/10.5281/zenodo.10572122">https://doi.org/10.5281/zenodo.10572122</a> </p> </li> <li> <p>Neutrophils: <a href="https://doi.org/10.5281/zenodo.10572231">https://doi.org/10.5281/zenodo.10572231</a></p> </li> <li> <p>Mononucleated cells: <a href="https://doi.org/10.5281/zenodo.10572200">https://doi.org/10.5281/zenodo.10572200</a></p> </li> <li> <p>Model Training and predictions: Conducted using ZeroCostDL4Mic (<a href="https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist">https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki</a>)</p> </li> </ul> <li> <p>Tracking parameters (TrackMate):</p> </li> <ul> <li> <p>Detection: label detector</p> </li> <li> <p>Tracking: Simple LAP detector: Linking max distance: 20 px; Gap-closing max distance: 20 px; Gap-closing max frame gap: 4. </p> </li> <li> <p>Track filtering: min number of spots in the tracks 11.79 </p> </li> </ul> <li> <p>Tracking analysis</p> </li> <ul> <li> <p>Tracks were analyzed using a customized CellTracksColab notebook (<a href="https://github.com/CellMigrationLab/PDAC_DL/tree/main/CellTracksColab">https://github.com/CellMigrationLab/PDAC_DL/tree/main/CellTracksColab</a>)</p> </li> </ul> </ul> <h3>Contents of the repository</h3> <ul> <li> <p>Analysis.zip</p> </li> <li> <p>As_HUsi1.zip dataset</p> </li> <li> <p>As_HUsi2.zip dataset</p> </li> <li> <p>As_HUsi3.zip dataset</p> </li> <li> <p>As_HUsiCtrl.zip dataset</p> </li> <li> <p>Mia_HUsi1.zip dataset</p> </li> <li> <p>Mia_HUsi2.zip dataset</p> </li> <li> <p>Mia_HUsi3.zip dataset</p> </li> <li> <p>Mia_HUsiCtrl.zip dataset</p> </li> </ul> <div> <h3>Reference</h3> <div><strong>Fast label-free live imaging reveals key roles of flow dynamics and CD44-HA interaction in cancer cell arrest on endothelial monolayers</strong></div> </div> <div>Gautier Follain, Sujan Ghimire, Joanna W. Pylvänäinen, Monika Vaitkevičiūtė, Diana Wurzinger, Camilo Guzmán, James RW Conway, Michal Dibus, Sanna Oikari, Kirsi Rilla, Marko Salmi, Johanna Ivaska, Guillaume Jacquemet</div> <div>bioRxiv 2024.09.30.615654; doi: <a href="https://www.biorxiv.org/content/10.1101/2024.09.30.615654v1">https://doi.org/10.1101/2024.09.30.615654</a></div>
PDAC cells CD44 siRNA perfusion tracking dataset
<p>This dataset contains tracking results of CD44 siRNA-silenced AsPC1, and MiaPaca cells perfused on endothelial monolayers under physiological flow speeds.</p> <p>Videos were recorded using a Nikon Eclipse Ti2-E microscope and 20x objective.</p> <p>Perfused cells from the generated videos were segmented using custom-trained Stardist models. Tracking was performed using TrackMate. Tracking results were analyzed using a custom CellTracksColab notebook. </p> <p>The dataset here contains the CSV files generated by TrackMate (Track and Spots information), the tracking data stored in the CellTracksColab format (Analysis.zip), and the analysis output used in the paper (Analysis.zip). <strong> </strong></p> <h3>Specifications</h3> <ul> <li> <p>Sample information</p> </li> <ul> <li> <p>AsPC1 and MiaPaca cells perfused on HUVEC cells under physiological flow speeds: 400 µm/s (p1), 200 µm/s (p2), 100 µm/s (p3) and 400 µm/s (p4). </p> </li> <li> <p>CD44 siRNA silencing of PDACs prior to perfusion</p> </li> </ul> <li> <p>Imaging specs</p> </li> <ul> <li> <p>Microscope: Nikon Eclipse Ti2-E, 20x objective</p> </li> <li> <p>Data Type: Brightfield microscopy images (16-bit)</p> </li> <li> <p>Image Size: 1024 x 1022 pixels (Pixel size: 650 nm)</p> </li> <li> <p>Recording speed 25 frames/s</p> </li> </ul> <li> <p>DL models:</p> </li> <ul> <li> <p>Cancer cells: <a href="https://doi.org/10.5281/zenodo.10572122">https://doi.org/10.5281/zenodo.10572122</a> </p> </li> <li> <p>Neutrophils: <a href="https://doi.org/10.5281/zenodo.10572231">https://doi.org/10.5281/zenodo.10572231</a></p> </li> <li> <p>Mononucleated cells: <a href="https://doi.org/10.5281/zenodo.10572200">https://doi.org/10.5281/zenodo.10572200</a></p> </li> <li> <p>Model Training and predictions: Conducted using ZeroCostDL4Mic (<a href="https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki/Stardist">https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki</a>)</p> </li> </ul> <li> <p>Tracking parameters (TrackMate):</p> </li> <ul> <li> <p>Detection: label detector</p> </li> <li> <p>Tracking: Simple LAP detector: Linking max distance: 20 px; Gap-closing max distance: 20 px; Gap-closing max frame gap: 4. </p> </li> <li> <p>Track filtering: min number of spots in the tracks 11.79 </p> </li> </ul> <li> <p>Tracking analysis</p> </li> <ul> <li> <p>Tracks were analyzed using a customized CellTracksColab notebook (<a href="https://github.com/CellMigrationLab/PDAC_DL/tree/main/CellTracksColab">https://github.com/CellMigrationLab/PDAC_DL/tree/main/CellTracksColab</a>)</p> </li> </ul> </ul> <h3><strong> </strong>Contents of the repository</h3> <ul> <li> <p>Analysis.zip</p> </li> <li> <p>As_TCsi1.zip dataset</p> </li> <li> <p>As_TCsi2.zip dataset</p> </li> <li> <p>As_TCsi3.zip dataset</p> </li> <li> <p>As_TCsiCtrl.zip dataset</p> </li> <li> <p>Mia_TCsi1.zip dataset</p> </li> <li> <p>Mia_TCsi2.zip dataset</p> </li> <li> <p>Mia_TCsi3.zip dataset</p> </li> <li> <p>Mia_TCsiCtrl.zip dataset</p> </li> </ul> <div> <h3>Reference</h3> <div><strong>Fast label-free live imaging reveals key roles of flow dynamics and CD44-HA interaction in cancer cell arrest on endothelial monolayers</strong></div> </div> <div>Gautier Follain, Sujan Ghimire, Joanna W. Pylvänäinen, Monika Vaitkevičiūtė, Diana Wurzinger, Camilo Guzmán, James RW Conway, Michal Dibus, Sanna Oikari, Kirsi Rilla, Marko Salmi, Johanna Ivaska, Guillaume Jacquemet</div> <div>bioRxiv 2024.09.30.615654; doi: <a href="https://www.biorxiv.org/content/10.1101/2024.09.30.615654v1">https://doi.org/10.1101/2024.09.30.615654</a></div>
High-Capacity Mesoporous Silica Nanocarriers of siRNA for Applications in Retinal Delivery
<p>The main cause of subretinal neovascularisation in wet age-related macular degeneration (AMD) is an abnormal expression in the retinal pigment epithelium (RPE) of the vascular endothelial growth factor (VEGF). Current approaches for the treatment of AMD present considerable issues that could be overcome by encapsulating anti-VEGF drugs in suitable nanocarriers, thus providing better penetration, higher retention times, and sustained release. In this work, the ability of large pore mesoporous silica nanoparticles (LP-MSNs) to transport and protect nucleic acid molecules is exploited to develop an innovative LP-MSN-based nanosystem for the topical administration of anti-VEGF siRNA molecules to RPE cells. siRNA is loaded into LP-MSN mesopores, while the external surface of the nanodevices is functionalised with polyethylenimine (PEI) chains that allow the controlled release of siRNA and promote endosomal escape to facilitate cytosolic delivery of the cargo. The successful results obtained for VEGF silencing in ARPE-19 RPE cells demonstrate that the designed nanodevice is suitable as an siRNA transporter.</p>
Engineering 'smart' viral RNA structures for stable and targeted siRNA delivery
<p>Innovative delivery strategies are needed in order to realize the potential of small interfering RNA (siRNA) in medicine. SiRNAs are short, double-stranded RNA molecules that silence genes by co-opting an endogenous RNA interference (RNAi) pathway. Because they act on messenger RNA (mRNA) sequences via RNAi, siRNAs hold promise as potentially curative therapies for genetic defects, autoimmune disorders, cancers, and other diseases that cannot be treated with traditional, protein-binding small molecule drugs and biologics. However, key physiological barriers largely have precluded the translation of siRNA drugs into clinical practice. <em>In vivo</em>, naked siRNAs are degraded rapidly by nucleases and cleared by the kidneys, resulting in a half-life of less than five minutes. Moreover, by comparison to small molecule drugs, siRNA drugs are relatively large, hydrophilic molecules that do not distribute widely to tissues or passively cross the cell membrane. Therefore, without an effective strategy for delivery, the accumulation of siRNA drugs at target sites is minimal. Today, there are few prominent siRNA delivery approaches, and each has significant limitations. For example, chemical modifications can improve nuclease resistance, but with the increase in stability also come tradeoffs in potency and safety. Lipid nanoparticles (LNPs) physically shield siRNAs from degradation and can be modified to promote biodistribution and uptake; but as LNPs are optimized for efficacy, they become increasingly complex, posing quality assurance, cost, and evaluation problems. Finally, conjugation to the <em>N</em>-Acetylgalactosamine (GalNAc) ligand is a promising delivery strategy for the liver, but targeted delivery to other tissues is a problem that still remains to be solved. Advances in nucleic acid nanotechnology have shown that RNA is an emerging platform for drug delivery. In particular, a three-way junction (3WJ) derived from bacteriophage prohead RNA (pRNA) has gained prominence as a vector for small molecule, microRNA (miRNA), anti-miRNA, and siRNA delivery. As a delivery solution for siRNA, RNA-based platforms like the pRNA 3WJ have many notable advantages. For example, size and shape can be controlled to minimize clearance, and functionalization with aptamers can drive cell uptake. Also, RNA is a fundamentally biocompatible molecule that is simple, straightforward to produce, and multifunctional. However, its metabolic instability is limiting. Exciting new research has uncovered 'smart' RNA structures that are produced by flaviviruses (<em>e.g.</em>, Zika, Dengue, West Nile) to thwart nuclease degradation. Compared to other RNA structures used for drug delivery, these nuclease-resistant structures (NRSs) may be uniquely positioned for <em>in vivo</em> applications. The aim of this project is to harness the inherent stability of flaviviral NRSs in the creation of a supramolecular platform for siRNA delivery. This project has the potential to address a critical need in the field of oligonucleotide therapeutics, which has few promising solutions for harnessing the power of RNAi in the clinic. Additionally, this project will validate new stable structures as building blocks for use in RNA nanotechnology and therefore will help researchers design supramolecular structures for a variety of applications well beyond those described in this proposal.</p>
A Dose Escalation Trial of an Intravitreal Injection of Sirna-027 in Patients With Subfoveal Choroidal Neovascularization (CNV) Secondary to Age-Related Macular Degeneration (AMD)
ClinicalTrials.gov study NCT00363714. IPD Sharing: Not stated. Countries: 1. Publications: 1.
EphA2 siRNA in Treating Patients With Advanced or Recurrent Solid Tumors
ClinicalTrials.gov study NCT01591356. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Engineering ‘smart’ viral RNA structures for stable and targeted siRNA delivery
Open the record for dataset details and reuse information.
Raw data of the article:Proof-of-Concept Study on the Use of Tangerine-Derived Nanovesicles as siRNA Delivery Vehicles toward Colorectal Cancer Cell Line SW480
<p>In the last years, the field of nanomedicine and drug delivery has grown exponentially, providing new platforms to carry therapeutic agents into the target sites. Extracellular vesicles (EVs) are ready-to-use, biocompatible, and non-toxic nanoparticles that are revolutionizing the field of drug delivery. EVs are involved in cell-cell communication and mediate many physiological and pathological processes by transferring their bioactive cargo to target cells. Recently, nanovesicles from plants (PDNVs) are raising the interest of the scientific community due to their high yield and biocompatibility. This study aims to evaluate whether PDNVs may be used as drug delivery systems. We isolated and characterized nanovesicles from tangerine juice (TNVs) that were comparable to mammalian EVs in size and morphology. TNVs carry the traditional EV marker HSP70 and, as demonstrated by metabolomic analysis, contain flavonoids, organic acids, and limonoids. TNVs were loaded with DDHD1-siRNA through electroporation, obtaining a loading efficiency of 13%. We found that the DDHD1-siRNA complex TNVs were able to deliver DDHD1-siRNA to human colorectal cancer cells, inhibiting the target expression by about 60%. This study represents a proof of concept for the use of PDNVs as vehicles of RNA interference (RNAi) toward mammalian cells.</p>
Layer-by-Layer siRNA Particle Assemblies for Localized Delivery of siRNA to Epithelial Cells through Surface-Mediated Particle Uptake
<p>Localized delivery of small interfering RNA (siRNA) is a promising approach for spatial control of cell responses at biomaterial interfaces. Layer-by-layer (LbL) assembly of siRNA with cationic polyelectrolytes has been used in film and nanoparticle vectors for transfection. Herein, we combine the ability of particles to efficiently deliver siRNA with the ability of film polyelectrolyte multilayers to act locally. LbL particles were prepared with alternating layers of poly(l-arginine) and siRNA and capped with hyaluronic acid. Negatively charged LbL particles were subsequently assembled on the poly(l-lysine)-functionalized substrate to form a LbL particle-decorated surface. Cells grown in contact with the particle-decorated surface were able to survive, internalize particles, and undergo gene silencing. This work shows that particle-decorated surfaces can be engineered by using electrostatic interactions and used to deliver therapeutic payloads for cell-instructive biointerfaces.</p>
A Trial to Learn if Receiving ALN-PNP siRNA is Safe and Well Tolerated, and How it Works in Adult Participants With Nonalcoholic Fatty Liver Disease (NAFLD) and a Genetic Risk Factor
ClinicalTrials.gov study NCT06024408. IPD Sharing: YES. Countries: 1. Publications: 0.
A First-in-Human Safety and Efficacy Study of ALN-CFB, a Small Interfering RNA (siRNA) Targeting Complement Factor B, in Adult Participants With Paroxysmal Nocturnal Hemoglobinuria With Persistent Ane
ClinicalTrials.gov study NCT07187401. IPD Sharing: YES. Countries: 2. Publications: 0.
Designing siRNA that distinguish between genes that differ by a single nucleotide
GEO Series GSE5291. Homo sapiens. 18 samples. Type: Expression profiling by array.
RNA-seq of ER-targeted and cytosolic mRNAs with control or CNOT1-targeting siRNA treatment in HEK293 cells
GEO Series GSE183148. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.