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68 results for “topic modeling”
Figure 11 from: Almudaris SA, Gatea FK (2024) Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings. Pharmacia 71: 1-14. https://doi.org/10.3897/pharmacia.71.e114753
Figure 11 Comparison between induced non-treated group and all induced treated groups regarding histopathological scores (Baker score) and observational score (PASI score).
Figure 4 from: Almudaris SA, Gatea FK (2024) Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings. Pharmacia 71: 1-14. https://doi.org/10.3897/pharmacia.71.e114753
Figure 4 Histopathological section of mice skin (healthy control group) showing normal skin architecture including K = keratin, E = epidermis, D = dermis, AD = adnexa, S.C = subcutaneous tissue, M = muscles, B.V = blood vessels. H&E stain (4×,10×).
Figure 3 from: Almudaris SA, Gatea FK (2024) Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings. Pharmacia 71: 1-14. https://doi.org/10.3897/pharmacia.71.e114753
Figure 3 Scoring for skin inflammation severity, the pictures show different inflammation levels of the dorsal skin on which the test substances were applied on day 8 of the Experiment. A. Represents the healthy group; B. Represents the IMQ-induced group; C. Represents the vehicle group; D. Represents Clobetasol treated group; E. Represents the Ivermectin treated group; F. Represents Ivermectin + Clobetasol treated group.
Figure 6 from: Almudaris SA, Gatea FK (2024) Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings. Pharmacia 71: 1-14. https://doi.org/10.3897/pharmacia.71.e114753
Figure 6 Histopathological section of mice skin (vehicle group) showing hyperkeratosis, parakeratosis (black arrow), with focal neutrophilic infiltration (the Munro's abscess) in red arrow, with epidermal acanthosis and thinning papillae and elongated rete ridges (green arrow), and lack of granular layer. The dermis shows moderate to severe inflammatory lymphocytic infiltration (blue arrow). H&E stain (4×,10×).
Figure 9 from: Almudaris SA, Gatea FK (2024) Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings. Pharmacia 71: 1-14. https://doi.org/10.3897/pharmacia.71.e114753
Figure 9 Histopathological section of mice skin (Ivermectin treatment group) showing mild keratosis (black arrow), with the absence of Munro's abscess and parakeratosis and epidermal mild acanthosis with few rete ridges and mild papillary thinning (green arrow). The dermis shows severe lymphocytic infiltrate. H&E stain (4×,10×).
Figure 2 from: Almudaris SA, Gatea FK (2024) Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings. Pharmacia 71: 1-14. https://doi.org/10.3897/pharmacia.71.e114753
Figure 2 Induction of Psoriasis in mice. A Mouse before Induction. B Mouse after Induction by Imiquimod cream.
Figure 8 from: Almudaris SA, Gatea FK (2024) Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings. Pharmacia 71: 1-14. https://doi.org/10.3897/pharmacia.71.e114753
Figure 8 Histopathological section of mice skin (Ivermectin treatment group) showing mild keratosis (black arrow), with the absence of Munro's abscess and parakeratosis and epidermal mild acanthosis with few rete ridges and mild papillary thinning (green arrow). The dermis shows severe lymphocytic infiltrate. H&E stain (4×,10×, 40×).
Figure 10 from: Almudaris SA, Gatea FK (2024) Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings. Pharmacia 71: 1-14. https://doi.org/10.3897/pharmacia.71.e114753
Figure 10 Comparison between induced non-treated group and all induced treated groups regarding tissue biomarkers (IL-10, IL-17, TNF-a, and VEGF).
Figure 5 from: Almudaris SA, Gatea FK (2024) Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings. Pharmacia 71: 1-14. https://doi.org/10.3897/pharmacia.71.e114753
Figure 5 Histopathological section of mice skin (induction group) showing hyperkeratosis, parakeratosis (black arrow), with multifocal dense neutrophilic infiltration (the Munro's abscess) in red arrow, with epidermal acanthosis and thinning papillae and rete ridges appearance (green arrow), and lack of granular layer. The dermis shows moderate to severe inflammatory lymphocytic infiltration (blue arrow). H&E stain (4×,10×, 40×).
Visualization Data for Topic Modeling in the Field of Biotechnology (Bachelor's Thesis)
<p>Visualization Data for Topic Modeling in the Field of Biotechnology (Bachelor's Thesis at UPM)</p>
Frame Analysis of Chinese COVID-19 Press Conference Texts during 2020-2023: A LDA Topic Modelling Approach
Open the record for dataset details and reuse information.
Evaluation of the Efficacy of Topical Ophthalmic Steroids in a Modified Conjunctival Allergen Challenge (CAC) Model
ClinicalTrials.gov study NCT00689078. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of the Efficacy of Topical Ophthalmic Steroids in a Modified Conjunctival Allergen Challenge (CAC) Model
ClinicalTrials.gov study NCT01534195. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Peer-reviewed papers included in topic model of old animal ecology and conservation
Open the record for dataset details and reuse information.
Nanoparticle-coupled topical methotrexate effectively inhibits inflammation and induces re-modeling in pre-clinical psoriasis
GEO Series GSE126066. Homo sapiens. 13 samples. Type: Expression profiling by high throughput sequencing.
cisTopic: cis-regulatory topic modelling on single-cell ATAC-seq data
GEO Series GSE114557. Homo sapiens. 771 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Science Education Research Topic Modeling Dataset
<p>This dataset contains scraped and processed text from roughly 100 years of articles published in the Wiley journal <em>Science Education </em>(formerly <em>General Science Quarterly</em>). This text has been cleaned and filtered in preparation for analysis using natural language processing techniques, particularly topic modeling with <a href="https://dl.acm.org/doi/10.5555/944919.944937">latent Dirichlet allocation</a> (LDA). We also include a Jupyter Notebook illustrating how one can use LDA to analyze this dataset and extract latent topics from it, as well as analyze the rise and fall of those topics over the history of the journal.</p> <p>The articles were downloaded and scraped in December of 2019. Only non-duplicate articles with a listed author (according to the <a href="https://www.crossref.org/">CrossRef metadata</a> database) were included, and due to missing data and text recognition issues we excluded all articles published prior to 1922. This resulted in 5577 articles in total being included in the dataset. The text of these articles was then cleaned in the following way:</p> <ul> <li>We removed duplicated text from each article: prior to 1969, articles in the journal were published in a magazine format in which the end of one article and the beginning of the next would share the same page, so we developed an automated detection of article beginnings and endings that was able to remove any duplicate text.</li> <li>We removed the reference sections of the articles, as well headings (in all caps) such as “ABSTRACT”.</li> <li>We reunited any partial words that were separated due to line breaks, text recognition issues, or British vs. American spellings (for example converting “per cent” to “percent”) </li> <li>We removed all numbers, symbols, special characters, and punctuation, and lowercased all words.</li> <li>We removed all <em>stop words</em>, which are words without any semantic meaning on their own—“the”, “in,” “if”, “and”, “but”, etc.—and all single-letter words.</li> <li>We lemmatized all words, with the added step of including a part-of-speech tagger so our algorithm would only aggregate and lemmatize words from the same part of speech (e.g., nouns vs. verbs).</li> <li>We detected and create <em>bi-grams</em>, sets of words that frequently co-occur and carry additional meaning together. These words were combined with an underscore: for example, “problem_solving” and “high_school”.</li> </ul> <p>After filtering, each document was then turned into a list of individual words (or tokens) which were then collected and saved (using the python pickle format) into the file scied_words_bigrams_V5.pkl.</p> <p>In addition to this file, we have also included the following files:</p> <ol> <li>SciEd_paper_names_weights.pkl: A file containing limited metadata (title, author, year published, and DOI) for each of the papers, in the same order as they appear within the main datafile. This file also includes the weights assigned by an LDA model used to analyze the data</li> <li>Science Education LDA Notebook.ipynb: A notebook file that replicates our LDA analysis, with a written explanation of all of the steps and suggestions on how to explore the results.</li> <li>Supporting files for the notebook. These include the requirements, the README, a helper script with functions for plotting that were too long to include in the notebook, and two HTML graphs that are embedded into the notebook. </li> </ol> <p>This dataset is shared under the terms of the <a href="https://olabout.wiley.com/WileyCDA/Section/id-826542.html">Wiley Text and Data Mining Agreement,</a> which allows users to share text and data mining output for non-commercial research purposes. Any questions or comments can be directed to Tor Ole Odden, t.o.odden@fys.uio.no.</p>
Tutorial: Drei Methoden für bessere Topics beim Topic Modeling
<p>In der Videoreihe „Topic Modeling und digitale Literaturanalyse“ stellen wir den DARIAH Topics Explorer vor. Dafür erklären wir die einzelnen Funktionalitäten des Tools und wie Ergebnisse gelesen und interpretiert werden können. Außerdem präsentieren wir 3 Methoden zur Verbesserung der Topics.<br>In diesem Video zeigen wir Schritt für Schritt, wie Topics aus dem DARIAH Topics Explorer verbessert werden können. Dabei zeigen und erklären wir die drei effektivsten Methoden zur Verbesserung der Topic-Modeling-Ergebnisse und erklären, warum sie zu genaueren Daten führen.</p> <p>Mehr Infos:</p> <ul> <li>Schriftliche Einführung in die Methodik des Topic Modelings: <a href="https://fortext.net/routinen/methoden/topic-modeling">https://fortext.net/routinen/methoden/topic-modeling</a></li> <li>Schriftliche Lerneinheit zur Stilometrie: <a href="https://fortext.net/routinen/lerneinheiten/topic-modeling-mit-dem-dariah-topics-explorer">https://fortext.net/routinen/lerneinheiten/topic-modeling-mit-dem-dariah-topics-explorer</a></li> <li>Download DARIAH Topics Explorer: <a href="https://dariah-de.github.io/TopicsExplorer/">https://dariah-de.github.io/TopicsExplorer/</a></li> </ul> <p>Übersicht der Videoreihe auf Zenodo:</p> <ol> <li><a href="../records/10371074">Tutorial: DARIAH Topics Explorer installieren</a></li> <li><a href="../records/10372228">Tutorial: DARIAH Topics Explorer zur Literaturanalyse nutzen</a></li> <li><a href="../records/10378213">Tutorial: Drei Methoden für bessere Topics beim Topic Modeling</a></li> <li>Fallbeispiel: <a href="../records/10276975">Themen von Autoren und Autorinnen der Literatur des 19. Jahrhunderts</a></li> </ol> <p><a href="https://www.youtube.com/watch?v=uckoY80J0cE&list=PLu-M0KuYw64oGJyHMr4e_rNIzYqdPvApr">Hier</a> zur Videoreihe auf Youtube</p>
Figure 1 from: Almudaris SA, Gatea FK (2024) Effects of topical Ivermectin on imiquimod-induced Psoriasis in mouse model – Novel findings. Pharmacia 71: 1-14. https://doi.org/10.3897/pharmacia.71.e114753
Figure 1 Flow chart of the study.
Topical Agents Containing Magnesium Sulfate & Wound Healing in the Rat Model
ClinicalTrials.gov study NCT04886882. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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.