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8,038 results for “Validity”
Data from: Identification of intraductal carcinoma of the prostate on tissue specimens using Raman micro-spectroscopy: A diagnostic accuracy case-control study with multicohort validation
<p class="AbstractSummary"><b>Background</b></p> <p class="AbstractSummary">Prostate cancer (PC) is the most frequently diagnosed cancer in North American men. Pathologists are in critical need of accurate biomarkers to characterize PC, particularly to confirm the presence of intraductal carcinoma of the prostate (IDC-P), an aggressive histopathological variant for which therapeutic options are now available. Our aim was to identify IDC-P with Raman micro-spectroscopy and machine learning technology following a protocol suitable for routine clinical histopathology laboratories.</p> <p class="AbstractSummary"><b>Methods and findings</b></p> <p class="AbstractSummary">We used Raman micro-spectroscopy to differentiate IDC-P from PC, as well as PC and IDC-P from benign tissue on formalin-fixed paraffin-embedded first-line radical prostatectomy specimens (embedded in tissue microarrays, TMAs) from 483 patients treated in three Canadian institutions between 1993 and 2013. The main measures were the presence or absence of IDC-P and of PC, regardless of the clinical outcomes. Most of the 483 patients were pT2 stage (44–69%), and pT3a (22–49%) was more frequent than pT3b (9–12%). After approval of the construction of the TMAs by local ethics review board, the diagnostic accuracy study was approved by the Centre hospitalier de l'Université de Montréal (CHUM) ethics review board. Briefly, two consecutive sections of each TMA block were cut. The first section was transferred onto a glass slide to perform immunohistochemistry with H&E counterstaining for cell identification. The second section was placed on an aluminum slide, dewaxed, and then used to acquire an average of 7 Raman spectra per specimen (between 4 and 24 Raman spectra, 4 acquisitions / TMA core). Raman spectra of each cell type were then analyzed to retrieve tissue-specific molecular information and to generate classification models using machine learning technology. <span>Models were trained and cross-validated using data from one institution. Accuracy, sensitivity and specificity were respectively of 87 ± 5%, 86 ± 6% and 89 ± 8% to differentiate PC from benign tissue, and of 95 ± 2%, 96 ± 4% and 94 ± 2% respectively to differentiate IDC-P from PC. The trained models were then tested on data from two independent institutions, reaching accuracies, sensitivities and specificities of 84 and 86%, 84 and 87%, and 81 and 82%, respectively</span><span> to diagnose PC, and of 85 and 91%, 85 and 88%, and 86 and 93% respectively for the identification of IDC-P.</span> IDC-P could further be differentiated from high-grade prostatic intraepithelial neoplasia (HGPIN), a pre-malignant intraductal proliferation which can be mistaken as IDC-P, with accuracies, sensitivities and specificities >95% in both training and testing cohorts. As we used stringent criteria to diagnose IDC-P, the main limitation of our study is the exclusion of borderline, difficult to classify lesions from our datasets.</p> <p class="AbstractSummary"><b>Conclusions</b></p> <p>In this study, we developed classification models for the analysis of Raman micro-spectroscopy data to differentiate IDC-P, PC and benign tissue, including HGPIN. Raman micro-spectroscopy could be a next-generation histopathological technique used to <span>reinforce the identification of high-risk PC patients and lead to more precise diagnosis of IDC-P.</span></p>
Data from: Intra-Rater reliability and validity of outcome measures in Myotonic Dystrophy Type 1
<p>Objective</p> <p>To investigate intra-rater reliability, concurrent- and construct validity of muscle strength, balance, and functional mobility measures in individuals with non-congenital DM1.</p> <p>Methods</p> <p><a name="_Hlk4397329">Seventy-eight adults with non-congenital DM1 participated in visit 1 and 73 of the subjects participated in visit 2 separated by 1-2 weeks. The assessments consisted of </a>muscle strength tests with Hand-Held Dynamometry (HHD) and Stationary Dynamometry in the lower limb. The balance tests comprised of Step Test, Timed Up and Go test, Feet-Together stance, Tandem-Stance, One-Leg-Stance, and modified Clinical Test of Sensory Integration and Balance on a balance platform. The functional mobility tests consisted of the 10-meter Walk Test (10mWT) and 10-times Sit-To-Stand test.</p> <p><a name="_Hlk14169462">Results</a></p> <p>The HHD and Stationary Dynamometry were sufficiently intra-rater reliable for most muscle groups on a group- (SEM<sub>%</sub>≤15%) and individual level (MDD<sub>95%</sub>≤30%), but HHD was most reliable. Stationary Dynamometry measured a higher torque than HHD for all extensor muscles, but for single individuals none of the devices were favored. Overall, intra-rater reliability and validity were only sufficient for the dynamic balance tests and not the static balance tests. Both functional mobility tests were sufficiently reliable and valid, but the 10mWT was most reliable.</p> <p>Conclusion</p> <p>Overall, HHD is recommended as a reliable and valid tool for single individuals and for flexor muscles on a group level. For balance assessments, the dynamic balance tests are recommended as the most valid and reliable balance tests. Both functional mobility tests are recommended for valid and reliable outcomes, but the 10mWT was superior for reliability.</p>
Reproducible Validation and Replication Studies in Nanoscale Physics (problem datasets for validation and replications from Ellis et al., 2016)
<p>Problem folders including all the input files necessary to reproduce the computations of the results related to Validation and replication of Ellis et al. 2016, on the paper: Reproducible Validation and Replication Studies in Nanoscale Physics</p>
Reproducible Validation and Replication Studies in Nanoscale Physics (repro results plots - Rockstuhl et al., 2005)
<p>This archive contains the Jupyter notebooks needed to reproduce the figures of the paper that are related to the replication of Rockstuhl et al. 2005. For further information direct to the README.md file. </p>
Figure 4 from: Horyn M, Logoyda L (2020) Bioanalytical method development and validation for the determination of metoprolol and meldonium in human plasma. Pharmacia 67(2): 39-48. https://doi.org/10.3897/pharmacia.67.e50397
Figure 4 Typical multiple reaction monitoring chromatograms of meldonium and internal standard in dipotassium ethylenediaminetetraacetic acid human blank plasma.
Figure 2 from: Logoyda L (2020) Efficient validated method of HPLC to determine amlodipine in combinated dosage form containing amlodipine, enalapril and bisoprolol and in vitro dissolution studies with in vitro/ in vivo correlation. Pharmacia 67(2): 55-61. https://doi.org/10.3897/pharmacia.67.e48220
Figure 2 Representative chromatogram of amlodipine in combinated tablets (1- peak of bisoprolol, 2- peak of enalapril, 3 – peak of amlodipine).
Figure 3 from: Horyn M, Logoyda L (2020) Bioanalytical method development and validation for the determination of metoprolol and meldonium in human plasma. Pharmacia 67(2): 39-48. https://doi.org/10.3897/pharmacia.67.e50397
Figure 3 Typical multiple reaction monitoring chromatograms of metoprolol and internal standard in dipotassium ethylenediaminetetraacetic acid human blank plasma.
Validation of the Swedish diabetes regrouping scheme in adult-onset diabetes in China
<p><span><b>Abstract</b></span></p> <p><b>Background </b>Re-classification of diabetes is vital in providing precise management and reducing risk of diabetes complications. This study aimed to validate the practicality of the Swedish diabetes re-grouping scheme in Chinese adults with newly diagnosed diabetes. We conducted a cross-sectional survey of 15772 patients with adult-onset newly-diagnosed diabetes in China from April 2015 to October 2017. Cluster analysis used by the Swedish study was employed to re-group our patients. Glutamate decarboxylase antibodies (GADA), age onset, body mass index (BMI), Hemoglobin A<sub>1c</sub> (HbA<sub>1c</sub>), homoeostatic model assessment 2 estimates of β-cell function (HOMA2-B) and insulin resistance (HOMA2-IR) were used to perform the TwoStep and k-means clustering. Characteristics of the clusters were compared between the patients from this study and those from the Swedish study.</p> <p><b>Results </b><span>Our patients clustered into five subgroups: 6.2% were gathered in the severe autoimmune diabetes (SAID) subgroup, 24.8% were in the severe insulin deficient diabetes (SIDD) subgroup, 16.6% were in the severe insulin resistance diabetes (SIRD) subgroup, 21.6% were in the mild obesity-related diabetes (MOD) subgroup and 30.9% were in the mild age-related diabetes (MARD) subgroup. When compared with the Swedish population, the proportion of SIDD subgroup was higher. In general, Chinese patients had younger age, lower BMI, higher HbA<sub>1c</sub>, lower HOMA2-B and HOMA2-IR, and higher insulin use but lower metformin usage than the Swedish patients. </span></p> <p><strong>Content</strong> The data contains the figures and tables to describe the characteristics and the variable distributions of Chinese diabetic patients in each of the five clusters. Additionally, the comparisons between the Chinese and Swedish patients with diabetes were presented in it as well.</p> <p><span><b>Conclusion </b>The Swedish diabetes regrouping scheme is applicable to adult-onset diabetes in China, with a high proportion of patients with the severe insulin deficient diabetes. Further validations of long-term diabetes complications remain warranted in future studies. </span></p>
Figure 9 in Five new species of Enchytraeidae (Annelida: Clitellata) from Mediterranean woodlands of Italy and reaffirmed validity of Achaeta etrusca, Fridericia bulbosa and F. miraflores
Figure 9. Fridericia rara sp. nov. (A) Anterior body segments (dorsolateral view), showing the pharyngeal glands, the left spermatheca and the preclitellar nephridia; (B and C) details of clitellum on its dorsal (B) and ventrolateral sides (C). Note the absence of gland cells ventrally in XII. Squared contour on midventral interruption indicates the position of (D). (D) Close-up of male pore; (E) sperm funnel; (F) lateral view of segments IV–V, showing the left spermatheca; (G) chylus cells showing through intestinal wall in segments XIII–XIV. All from permanent whole-mounted specimens, anterior to the left.
Figure 6 in Five new species of Enchytraeidae (Annelida: Clitellata) from Mediterranean woodlands of Italy and reaffirmed validity of Achaeta etrusca, Fridericia bulbosa and F. miraflores
Figure 6. Fridericia bargaglii sp. nov. (A) Semi-schematic drawing of segments IV–VII in a live specimen (dorsal view), showing the spermathecae and the pharyngeal glands; (B and C) spermathecae from whole-mounted specimens (in (C) diverticula seen in a side view); (D) peptonephridia (free-hand sketches) in living specimens; (E) shape and reciprocal distance of the male openings (ventral view). In all, anterior to the top.
Figure 5 in Five new species of Enchytraeidae (Annelida: Clitellata) from Mediterranean woodlands of Italy and reaffirmed validity of Achaeta etrusca, Fridericia bulbosa and F. miraflores
Figure 5. Fridericia bargaglii sp. nov. (A) Cephalic region (lateral view), showing the midventral glandular papilla in IV; (B) ventrolateral view of segments X–XV; the elliptical contour shows the continuity of the clitellum behind the male pores; arrows indicate the subneural glands in XIII–XV; (C) sagittal optical section through XI–XIII (lateral) in a preclitellate specimen, showing the male inner reproductive organs. All from permanent whole-mounted specimens, anterior to the right.
Figure 4. Achaeta etrusca Rota, 1995 in Five new species of Enchytraeidae (Annelida: Clitellata) from Mediterranean woodlands of Italy and reaffirmed validity of Achaeta etrusca, Fridericia bulbosa and F. miraflores
Figure 4. Achaeta etrusca Rota, 1995. (A) Cephalic region in a dorsolateral view. Arrows and arrowheads point to the body wall structures in I and II–IV, respectively; uppermost arrow and arrowhead indicate the corresponding protrusions on the right inner side of I and II. (B and C) Dorsal views of segments I–IV and VI–IX, respectively, showing the conspicuous loops of the oesophagus in IV and VII. All from live specimens, anterior to the left.
Figure 2 in Five new species of Enchytraeidae (Annelida: Clitellata) from Mediterranean woodlands of Italy and reaffirmed validity of Achaeta etrusca, Fridericia bulbosa and F. miraflores
Figure 2. Achaeta bohemica (Vejdovský, 1879a) as illustrated by Michaelsen (1889). (A) Crosssection through segment XII, showing the conspicuous hyaline gland cells on the dorsolateral sides of the clitellum, the flask-shaped glands (b), and the glands surrounding the male openings (p); (B) arrangement of the longitudinal muscle fibres in the body wall; (C) intestinal epithelial cells of segment IX, showing their fine intracellular canals in cross (q) and longitudinal (l) section.
Data from: Validation of a simple extraction procedure for bisphenol A identification from human plasma
The general population is exposed to bisphenol A (BPA) orally, parenterally, transdermally, and environmentally as a result of the use of BPA in food packaging, plastics, and personal care products. The majority of the population nowadays (91–99%) has detectable levels of BPA inside their body. In this study, we successfully performed an inexpensive, rapid, and simple protein precipitation procedure for extraction of BPA from human plasma, followed by analysis by LC-MS/MS. This method was specifically developed for handling large numbers of samples with minimum cost and volume of sample. The developed method was accurate, precise, and reproducible for quantification of BPA from human plasma samples in the concentration range of 10–2000 ng/mL. The method was performed on samples from 150 healthy volunteers who were enrolled in the study. The mean of observed BPA level was 2.22 ± 9.91 ng/mL. Higher BPA levels were observed for females compare to that of males (p-value = 0.002), the BPA levels were higher in participants 33 years of age and older compared to those less than 33 years of age (p-value = 0.000), then the BPA levels higher in subjects with tap water as source of drinking (p-value = 0.005). This method may be valuable for general risk assessment of BPA for a large and varied population because of its efficiency and economical aspects.
Validation of ESA CCI SM combined v05.2 vs ISMN 20191211 global
QA4SM validation of soil moisture data: ESA CCI SM combined v05.2 vs ISMN 20191211 global. URL: https://qa4sm.eu/result/1333c236-de5b-4835-be24-407b115c4980/. Produced on QA4SM (https://qa4sm.eu)
Validation results of Non-parametric models of pH Neutralization plant Dataset
<p>This repository contains a table with different validation results of a series of models tested in pH Neutralization plant and Clarke plant.</p> <p>In this case, the naming protocol was as follows: [plant name]_DataSet_[model variable].</p> <p>The content of every CSV file is presented as follows: </p> <p>Column 1: { name: Model_No, type: numeric integer, limit: None, description: Code to identifiy the model (Primary Key)}</p> <p>Column 2: { name: KS, type: numeric float, limits: [0 1], description: Kolgomorov-Smirnov test}</p> <p>Column 3: { name: AD, type: numeric float, limits: [0 1], description: Anderson-Darling test}</p> <p>Column 4: { name: SW, type: numeric float, limits: [0 1], description: Shapiro-Wilk test}</p> <p>Column 5: { name: WX, type: numeric float, limits: [0 1], description: Wilcoxon test}</p> <p>Column 6: { name: FIT, type: numeric float, limits: [-Inf 1], description: Goodness of Fit metric}</p> <p>Column 7: { name: TIC, type: numeric float, limits: [0 1], description: Theil Inequality Index}</p> <p>Column 8: { name: Willmott, type: numeric float, limits: [0 1], description: Willmott metric}</p> <p>Column 9: { name: Russell_Pr, type: numeric float, limits: [0 1], description: Phase of Russell }</p> <p>Column 10: { name: Russell_Mr, type: numeric float, limits: [0 Inf], description: Magnitude of Russell }</p> <p>Column 11: { name: SG_Mr, type: numeric float, limits: [-Inf 1], description: Sprague & Geers}</p> <p>Column 12: { name: Anova, type: numeric float, limits: [0 1], description: Anova test}</p> <p>Column 13: { name: Dvure, type: numeric float, limits: [0 100], description: Dvurecenska metric}</p> <p>Column 14: { name: DTW, type: numeric float, limits: [0 Inf], description: DTW metric}</p> <p>Column 15: { name: D_DTW, type: numeric float, limits: [0 Inf], description: derivative of DTW metric}</p>
Gene validation and remodelling using proteogenomics of Phytophthora cinnamomi, the causal agent of Dieback
<p>This spectral data is in support for the manuscript 'Gene validation and remodelling using proteogenomics of Phytophthora cinnamomi, the causal agent of Dieback'. This data was used to detect errors in the draft genome and curate previously undescribed genes in the <em>Phytophthora cinnamomi</em> genome. </p>
Pilot implementation, monitoring, co-evaluation and validation data_v2
<p>These data have been collected in the context of monitoring and assessing the pilot operation of the INVITE project (H2020 GA 763651) and its OI2Lab platform during their 2nd deployment round.</p>
Validation of ESA CCI SM combined v04.7 vs ESA CCI SM combined v05.2 vs ISMN 20191211 global
QA4SM validation of soil moisture data: ESA CCI SM combined v04.7 vs ESA CCI SM combined v05.2 vs ISMN 20191211 global. URL: https://qa4sm.eu/result/8098cf4a-726b-4f56-a4cb-fb180c884c5c/. Produced on QA4SM (https://qa4sm.eu)
Validation of ESA CCI SM combined v05.2 vs ESA CCI SM combined v04.7 vs ERA5 v20190613 - Whole period
QA4SM validation of soil moisture data: ESA CCI SM combined v05.2 vs ESA CCI SM combined v04.7 vs ERA5 v20190613. URL: https://qa4sm.eu/result/84315e3c-bd2d-4eab-82f4-076b153dff24/. Produced on QA4SM (https://qa4sm.eu)
ScienceDex guides
Understand access before you commit
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.