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1,638 results for “Mm.”
CDK7 inhibition interdicts deregulated transcription and cell cycle control in multiple myeloma [Sensitive_MM_Cell_Lines_RNA-seq]
GEO Series GSE172444. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Fly_embryos_4-6_hr_600_mM_Salt_Extracted_Chromatin_Pellet
GEO Series GSE25380. Drosophila melanogaster. 3 samples. Type: Genome binding/occupancy profiling by genome tiling array.
Kc 600 mM Salt Extracted Chromatin Pellet
GEO Series GSE25386. Drosophila melanogaster. 2 samples. Type: Genome binding/occupancy profiling by genome tiling array.
2-Aminobenzimidazole treatment with 5 mM for 2 h
GEO Series GSE9324. Saccharomyces cerevisiae. 3 samples. Type: Expression profiling by array.
Fly wing disc 600 mM Salt Extracted Chromatin
GEO Series GSE25383. Drosophila melanogaster. 2 samples. Type: Genome binding/occupancy profiling by genome tiling array.
Expression data of lentivirus sponge MicroRNA16 (miR16) downregulated RPMI 8226 and MMS1 multiple myeloma (MM) cell lines compared with control lentivirus sponge
GEO Series GSE24522. Homo sapiens. 12 samples. Type: Expression profiling by array.
Tetrachloroethylene treatment with 3.3 mM for 2 h
GEO Series GSE9192. Saccharomyces cerevisiae. 6 samples. Type: Expression profiling by array.
Data set from the article Dozio E, Vianello E, Bandera F, Longhi E, Brizzola S, Nebuloni M, Corsi Romanelli MM. Soluble Receptor for Advanced Glycation End Products: A Protective Molecule against Intramyocardial Lipid Accumulation in Obese Zucker Rats? Mediators Inflamm. 2019 Feb 28;2019:2712376. doi: 10.1155/2019/2712376. PMID: 30944546; PMCID: PMC6421753.
<p>Data Set on the article: Dozio E, Vianello E, Bandera F, Longhi E, Brizzola S, Nebuloni M, Corsi Romanelli MM. Soluble Receptor for Advanced Glycation End Products: A Protective Molecule against Intramyocardial Lipid Accumulation in Obese Zucker Rats? Mediators Inflamm. 2019 Feb 28;2019:2712376. doi: 10.1155/2019/2712376. PMID: 30944546; PMCID: PMC6421753.</p> <p>This is the abrasct:</p> <p>Most of the obesity-related complications are due to ectopic fat accumulation. Recently, the activation of the cell-surface receptor for advanced glycation end products (RAGE) has been associated with lipid accumulation in different organs. Nevertheless, the role of RAGE and sRAGE, the soluble form that prevents ligands to activate RAGE, in intramyocardial lipid accumulation is presently unknown. To this aim, we analyzed whether, in obesity, intramyocardial lipid accumulation and lipid metabolism-related transcriptome are related to RAGE and sRAGE. Heart and serum samples were collected from 10 lean (L) and 10 obese (OB) Zucker rats. Oil red staining was used to detect lipids on frozen heart sections. The lipid metabolism-related transcriptome (84 genes) was analyzed by a specific PCR array. Heart RAGE expression was explored by real-time RT-PCR and Western blot analyses. Serum levels of sRAGE (total and endogenous secretory form (esRAGE)) were quantified by ELISA. Genes promoting fatty acid transport, activation, and oxidation in mitochondria/peroxisomes were upregulated in OB hearts. Intramyocardial lipid content did not differ between OB and L rats, as well as RAGE expression. A slight increase in epicardial adipose tissue was observed in OB hearts. Total sRAGE and esRAGE concentrations were significantly higher in OB rats. sRAGE may protect against obesity-induced intramyocardial lipid accumulation by preventing RAGE hyperexpression, therefore allowing lipids to be metabolized. EAT also played a protective role by working as a buffering system that protects the myocardium against exposure to excessively high levels of fatty acids. These observations reinforce the potential role of RAGE pathway as an interesting therapeutic target for obesity-related complications, at least at the cardiovascular level.</p>
Data set from the article Vianello E, Dozio E, Bandera F, Schmitz G, Nebuloni M, Longhi E, Tacchini L, Guazzi M, Corsi Romanelli MM. Dysfunctional EAT thickness may promote maladaptive heart remodeling in CVD patients through the ST2-IL33 system, directly related to EPAC protein expression. Sci Rep. 2019 Jul 17;9(1):10331. doi: 10.1038/s41598-019-46676-w. Erratum in: Sci Rep. 2020 Jan 21;10(1):1182. PMID: 31316160; PMCID: PMC6637132.
<p>Data set from the article Vianello E, Dozio E, Bandera F, Schmitz G, Nebuloni M, Longhi E, Tacchini L, Guazzi M, Corsi Romanelli MM. Dysfunctional EAT thickness may promote maladaptive heart remodeling in CVD patients through the ST2-IL33 system, directly related to EPAC protein expression. Sci Rep. 2019 Jul 17;9(1):10331. doi: 10.1038/s41598-019-46676-w. Erratum in: Sci Rep. 2020 Jan 21;10(1):1182. PMID: 31316160; PMCID: PMC6637132.</p> <p>This is the abstract:</p> <p>Dysfunctional epicardial adipose tissue (EAT) secretome can influence the heart's stretch response. However, the molecular mechanisms are still poorly understood. The aim of this study was to clarify how dysfunctional EAT promotes maladaptive heart remodeling in cardiovascular disease (CVD) through ST2 production associated with exchange protein directly activated by cAMP (EPAC) proteins. A series of 55 CVD males were enrolled and their EAT thickness, LV mass and volumes were measured by echocardiography. Blood, plasma and EAT biopsies were collected for molecular and proteomic assays. Taking EAT thickness as a continuous variable there was a direct correlation between the ST2 cardiac stretch mediator and EAT thickness (r = 0.54, p < 0.01) and an inverse relation between the ST2 gene and IL-33 expression (r -0.50, p < 0.01). In the CVD population EPAC2 expression directly correlated with the ST2 gene (r = 0.74, p < 0.0001) causing an ST2/IL-33 system local (p < 0.001) and systemic (sST2 = 57.33 ± 3.22 and IL-33 = 0.53 ± 017 pg/mL; p < 0.0001) protein imbalance associated with maladaptive remodeling. This indicated that dysfunctional EAT is a source of both EPAC and ST2 protein and an EPAC2 isoform seems involved in ST2 production in adipose tissue. Both EPAC2 and ST2 expression were directly related to maladaptive heart remodeling indices, suggesting EAT measurements could be useful in the early assessment of CVD complications.</p>
data set from the article Iacobellis G, Malavazos AE, Basilico S, Tresoldi S, Rinaldo RF, Dubini C, Capitanio G, Serpi F, Schiaffino S, Oliva OA, Cariati M, Morricone L, Centanni S, Sardanelli F, Carruba M, Corsi Romanelli MM, Secchi F. Epicardial fat inflammation response to COVID-19 therapies. Obesity (Silver Spring). 2021 Sep;29(9):1427-1433. doi: 10.1002/oby.23232. Epub 2021 Aug 3. PMID: 34028990; PMCID: PMC8242726.
<p>data set from the article Iacobellis G, Malavazos AE, Basilico S, Tresoldi S, Rinaldo RF, Dubini C, Capitanio G, Serpi F, Schiaffino S, Oliva OA, Cariati M, Morricone L, Centanni S, Sardanelli F, Carruba M, Corsi Romanelli MM, Secchi F. Epicardial fat inflammation response to COVID-19 therapies. Obesity (Silver Spring). 2021 Sep;29(9):1427-1433. doi: 10.1002/oby.23232. Epub 2021 Aug 3. PMID: 34028990; PMCID: PMC8242726.</p> <p> </p> <p>Abstract:</p> <p><strong>Objective: </strong>Adipose tissue plays a role in the novel coronavirus disease 2019 (COVID-19). Epicardial adipose tissue (EAT), a unique visceral fat, presents with a high degree of inflammation in severe COVID-19. Whether and how adipose tissue may respond to the COVID-19 therapies is unknown.</p> <p><strong>Methods: </strong>The difference in computed tomography-measured EAT and subcutaneous (SAT) attenuation, defined as mean attenuation expressed in Hounsfield units (HU), was retrospectively analyzed in 72 patients (mean [SD] age was 59.6 [12.4] years, 50 patients [69%] were men) at the hospital admission for COVID-19 and 99 days (interquartile range = 71-129) after discharge.</p> <p><strong>Results: </strong>At the admission, EAT-HU was significantly correlated with blood glucose levels, interleukin 6, troponin T levels, and waist circumference. EAT-HU decreased from -87.21 (16.18) to -100.0 (11) (p < 0.001), whereas SAT-HU did not change (-110.21 [12.1] to -111.11 [27.82]; p = 0.78) after therapy. Changes in EAT-HU (expressed as ∆) significantly correlated with dexamethasone therapy (r = -0.46, p = 0.006) and when dexamethasone was combined with tocilizumab (r = -0.24, p = 0.04).</p> <p><strong>Conclusions: </strong>Dexamethasone therapy was associated with significant reduction of EAT inflammation in COVID-19 patients, whereas SAT showed no changes. Anti-inflammatory therapies targeting visceral fat may be helpful in COVID-19.</p>
Fine sand content (sandfine; 0.10 to 0.25 mm) soil maps of the Upper Colorado River Basin
<p>The data here were originally posted to facilitate timely and transparent peer review. The final public data release with formal metadata is now available from at the following location:</p> <p>Nauman, T.W., and Duniway, M.C., 2020, Predictive soil property maps with prediction uncertainty at 30 meter resolution for the Colorado River Basin above Lake Mead: U.S. Geological Survey data release,<a href="http://https//doi.org/10.5066/P9SK0DO2"> https://doi.org/10.5066/P9SK0DO2</a>.</p> <p>Associated publication:</p> <p>Nauman, T. W., and Duniway, M. C., 2020, A hybrid approach for predictive soil property mapping using conventional soil survey data: Soil Science Society of America Journal, v. 84, no. 4, p. 1170-1194. <a href="https://doi.org/10.1002/saj2.20080">https://doi.org/10.1002/saj2.20080</a>.</p> <p>Repository includes maps of fine sand content (sandfine; 0.10 to 0.25 mm) as defined by United States soil survey program. Content is calculated on the fine earth fraction (<2mm).</p> <p>These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data.</p> <p>The creation and interpretation of this data is documented in the following article. Please note this article has not been reviewed yet and this citation will be updated as the peer review process proceeds.</p> <p>Nauman, T. W., Duniway, M. C., In Preparation. Predictive reconstruction of soil survey property maps for field scale adaptive land management. Soil Science Society of America Journal.</p> <p>File Name Details:</p> <p>ACCURACY!! Please see manuscript and Github repository (https://github.com/naumi421/SoilReconProps) for full details on accuracy. We do provide cross validation (CV) accuracy plots in this repository for both the overall sample (NRCS field pedons plus NRCS laboratory pedons; file ending _CV_plots.tif) and for just the CV results at laboratory pedons (file ending _CV_SCD_plots.tif). These plots compare CV predictions with observed values relative to a 1:1 line. Values plotted near the 1:1 line are more accurate. Note that values are plotted in hex-bin density scatter plots because of the large number of observations (most are >3000).</p> <p>Elements are separated by underscore (_) in the following sequence:</p> <p>property_r_depth_cm_geometry_model_additional_elements.extension</p> <p>Example: sandfine_r_0_cm_2D_QRF.tif</p> <p>Indicates fine sand content (sandfine) at 0 cm depth using a 2D model (separate model for each depth) employing a quantile regression forest. This file is the raster prediction map for this model. There may be additional GIS files associated with this file (e.g. pyramids) that have the same file name, but different extensions.</p> <p>The following elements may also exist on the end of filenames indicating other spatial files that characterize a given model's uncertainty (see below).</p> <p>_95PI_h: Indicates the layer is the upper 95% prediction interval value.</p> <p>_95PI_l: Indicates the layer is the lower 95% prediction interval value.</p> <p>_95PI_relwidth: Indicates the layer is the 95% relative prediction interval (RPI). The RPI is a standardization of the prediction interval that indicates that model is constraining uncertainty relative to the original sample. RPI values less than one represent uncertainty is being improved by the model relative to the original sample, and values less than 0.5 indicate low uncertainty in predictions. See paper listed above and also Nauman and Duniway (In revision) for more details on RPI.</p> <p>References</p> <p> Nauman, T. W., and Duniway, M. C., In Revision, Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data: Geoderma.</p>
Video S3: MHD flow at presence of semi-conductive shell and immersion depth of 100 mm
<p>This video presents the MHD flow modelling results inside an electrically insulated continuous casting mold at the presence of the solid shell. The induced electric current density paths tend to close through the conductive solid, leading to the moderate braking effects from the applied EMBr.</p>
Video S1: MHD flow with electrically insulated mold and immersion depth of 100 mm
<p>This video presents the MHD flow modelling results inside an electrically insulated continuous casting mold under the applied EMBr. The self-inducing MHD vortex structures, aligned with the magnetic field, are causing the instability and waving of the free surface.</p>
Video S2: MHD flow with electrically insulated mold and immersion depth of 50 mm
<p>This video presents the MHD flow modelling results inside an electrically insulated continuous casting mold under the applied EMBr. The self-inducing MHD vortex structures, aligned with the magnetic field, are causing the instability and waving of the free surface. Due to the shallow SEN immersion depth the MHD vortices are restricted in the vicinity of the free surface, which leads to their destruction.</p>
Video S4: MHD flow at presence of semi-conductive shell and immersion depth of 50 mm
<p>This video presents the MHD flow modelling results inside an electrically insulated continuous casting mold at the presence of the solid shell. The induced electric current density paths tend to close through the conductive solid, leading to the moderate braking effects from the applied EMBr. Due to the shallow SEN immersion depth, the attached solid is partially above the meniscus. The e-current lines, going above the free surface remain inside the conductive shell.</p>
doi_dedup___::2e262ca08c37de67282406f5e9745d9c
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doi_dedup___::4959f5205a671b3fb80296c25ed9a8b7
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doi_dedup___::91866c89444c04598d4a76303bc4c4a6
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.