cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25452/figshare.plus.21817914
title: Histology dataset supporting paper "A preclinical randomized controlled multicenter trial of anti-IL-17A treatment for acute ischemic stroke"

description: This folder contains the raw histology data from the study "A preclinical randomized controlled multicenter trial of anti-IL-17A treatment for acute ischemic stroke". These data were used for counting of the infiltrating neutrophilic granulocytes. <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6371439 <br> Manuscript abstract Multiple consensus statements have called for preclinical randomized controlled trials (pRCT) to improve translation in stroke research. We investigated the efficacy of an IL-17A neutralizing antibody in a multicenter pRCT using a murine ischemia reperfusion stroke model. Twelve week old, male C57BL/6 mice were subjected to 45 minutes of transient middle cerebral artery occlusion (tMCAO) in four centers. Mice were randomly assigned (1:1) to receive either an anti-IL-17A (500 µg) or isotype antibody (500 µg) intravenously one hour after reperfusion. The primary endpoint was infarct volume measured by MRI three days after tMCAO. Secondary analysis included mortality, neurological score, neutrophil infiltration and the impact of the gut microbiome on treatment effects. Out of 136 mice, 109 mice were included in the analysis of the primary endpoint. Mixed model analysis revealed that IL-17A neutralization significantly reduced infarct sizes (anti-IL-17A: 61.77 ± 31.04 mm3; IgG control: 75.66 ± 34.79 mm3; p=0.01). Secondary outcome measures showed a decrease in mortality (Hazard Ratio=3.43, 95% CI=1.157-10.18; p=0.04) and neutrophil invasion into ischemic cortices (anti-IL-17A: 7222 ± 6108 cells; IgG control: 28153 ± 23206 cells; p&lt;0.01). There was no difference in Bederson score. The analysis of the gut microbiome showed significant heterogeneity between centers (R=0.78, p&lt;0.001, n=40). Taken together, neutralization of IL-17A in a therapeutic time window resulted in a significant reduction of infarct sizes and mortality compared to isotype control. It suggests IL-17A neutralization as a potential therapeutic target in stroke.
DOI: 10.25452/figshare.plus.21817914.v1
title: Histology dataset supporting paper "A preclinical randomized controlled multicenter trial of anti-IL-17A treatment for acute ischemic stroke"

description: This folder contains the raw histology data from the study "A preclinical randomized controlled multicenter trial of anti-IL-17A treatment for acute ischemic stroke". These data were used for counting of the infiltrating neutrophilic granulocytes. <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6371439 <br> Manuscript abstract Multiple consensus statements have called for preclinical randomized controlled trials (pRCT) to improve translation in stroke research. We investigated the efficacy of an IL-17A neutralizing antibody in a multicenter pRCT using a murine ischemia reperfusion stroke model. Twelve week old, male C57BL/6 mice were subjected to 45 minutes of transient middle cerebral artery occlusion (tMCAO) in four centers. Mice were randomly assigned (1:1) to receive either an anti-IL-17A (500 µg) or isotype antibody (500 µg) intravenously one hour after reperfusion. The primary endpoint was infarct volume measured by MRI three days after tMCAO. Secondary analysis included mortality, neurological score, neutrophil infiltration and the impact of the gut microbiome on treatment effects. Out of 136 mice, 109 mice were included in the analysis of the primary endpoint. Mixed model analysis revealed that IL-17A neutralization significantly reduced infarct sizes (anti-IL-17A: 61.77 ± 31.04 mm3; IgG control: 75.66 ± 34.79 mm3; p=0.01). Secondary outcome measures showed a decrease in mortality (Hazard Ratio=3.43, 95% CI=1.157-10.18; p=0.04) and neutrophil invasion into ischemic cortices (anti-IL-17A: 7222 ± 6108 cells; IgG control: 28153 ± 23206 cells; p&lt;0.01). There was no difference in Bederson score. The analysis of the gut microbiome showed significant heterogeneity between centers (R=0.78, p&lt;0.001, n=40). Taken together, neutralization of IL-17A in a therapeutic time window resulted in a significant reduction of infarct sizes and mortality compared to isotype control. It suggests IL-17A neutralization as a potential therapeutic target in stroke.
DOI: 10.25452/figshare.plus.21817875
title: FACS dataset supporting paper "A preclinical randomized controlled multicenter trial of anti-IL-17A treatment for acute ischemic stroke"

description: This folder contains the raw fcs files and TTC stainings, used for the study "A preclinical randomized controlled multicenter trial of anti-IL-17A treatment for acute ischemic stroke". <br> See related materials in Collection at: https://doi.org/10.25452/figshare.plus.c.6371439 <br> Manuscript abstract Multiple consensus statements have called for preclinical randomized controlled trials (pRCT) to improve translation in stroke research. We investigated the efficacy of an IL-17A neutralizing antibody in a multicenter pRCT using a murine ischemia reperfusion stroke model. Twelve week old, male C57BL/6 mice were subjected to 45 minutes of transient middle cerebral artery occlusion (tMCAO) in four centers. Mice were randomly assigned (1:1) to receive either an anti-IL-17A (500 µg) or isotype antibody (500 µg) intravenously one hour after reperfusion. The primary endpoint was infarct volume measured by MRI three days after tMCAO. Secondary analysis included mortality, neurological score, neutrophil infiltration and the impact of the gut microbiome on treatment effects. Out of 136 mice, 109 mice were included in the analysis of the primary endpoint. Mixed model analysis revealed that IL-17A neutralization significantly reduced infarct sizes (anti-IL-17A: 61.77 ± 31.04 mm3; IgG control: 75.66 ± 34.79 mm3; p=0.01). Secondary outcome measures showed a decrease in mortality (Hazard Ratio=3.43, 95% CI=1.157-10.18; p=0.04) and neutrophil invasion into ischemic cortices (anti-IL-17A: 7222 ± 6108 cells; IgG control: 28153 ± 23206 cells; p&lt;0.01). There was no difference in Bederson score. The analysis of the gut microbiome showed significant heterogeneity between centers (R=0.78, p&lt;0.001, n=40). Taken together, neutralization of IL-17A in a therapeutic time window resulted in a significant reduction of infarct sizes and mortality compared to isotype control. It suggests IL-17A neutralization as a potential therapeutic target in stroke.
DOI: 10.6084/m9.figshare.21861684
title: Seurat cluster markers.xlsx

description: This file is the scRNA-seq data seurat cluster markers
DOI: 10.6084/m9.figshare.21861684.v1
title: Seurat cluster markers.xlsx

description: This file is the scRNA-seq data seurat cluster markers
DOI: 10.25919/rwwe-7n90
title: East Australian Current mooring raw data collection 2019-2021

description: The East Australian Current mooring raw data collection 2019-2021 contains all the raw instrument data files and instrument setup information, build documentation, deployment and recovery log sheets and scanned paper documentation for the deployment covering the period September, 2019 to May, 2021. Quality controlled data and gridded data products from this mooring deployment can be accessed via the links in the Related Links section of this collection record.
DOI: 10.25919/egf9-3510
title: East Australian Current mooring raw data collection 2021-2022

description: The East Australian Current mooring raw data collection 2021-2022 contains all the raw instrument data files and instrument setup information, build documentation, deployment and recovery log sheets and scanned paper documentation for the deployment covering the period May, 2021 to July, 2022. Quality controlled data and gridded data products from this mooring deployment can be accessed via the links in the Related Links section of this collection record.
DOI: 10.5281/zenodo.7516957
title: Breast cancer IMC dataset for InterSTELLAR training

description: <strong>graph_data.npy</strong>: preprocessed Breast cancer IMC dataset for InterSTELLAR training, saved as a<strong> .npy</strong> file. Read this file with python and get a list named <strong>all_graph</strong>. This list includes <strong>368 </strong>elements. The first <strong>366 </strong>elements are the information from each tissue, the last two elements are the <strong>mean </strong>and<strong> standard deviation</strong> of the cell feature data after log-transformation with shape <strong>30x1</strong>. Each sub-element <strong>all_graph[i]</strong> is alone a new list with three elements, including <strong>cell feature matrix all_graph[i][0]</strong>,<strong> cell locations all_graph[i][1],</strong> <strong>tissue labels all_graph[i][2] </strong>and <strong>cell phenotypes</strong> <strong>all_graph[i][3]</strong>. <strong>all_graph[i][0]</strong> is a <strong>Nx30</strong> matrix, corresponding to<strong> 30 cell markers</strong>; <strong>all_graph[i][1]</strong> is a<strong> Nx2</strong> matrix, corresponding to <strong>x </strong>and <strong>y </strong>locations of a single cell; <strong> all_graph[i][2]</strong> is a list with<strong> 5</strong> elements, corresponding to <strong>tissue phenotypes</strong> (0: healthy, 1: TNBC, 2: Non-TNBC cancers), <strong>tissue area</strong> (um<sup>2</sup>),<strong> tumor grade</strong>, <strong>overall survival time </strong>(month) and <strong>patient status</strong> (alive or death); <strong>all_graph[i][3] </strong>is a list with <strong>N </strong>elements corresponding to the <strong>cell phenotypes</strong>. <strong>cell_maskes.npy</strong>: the cell segmentation maskes corresponding to the 366 tissues.
DOI: 10.5281/zenodo.7516958
title: Breast cancer IMC dataset for InterSTELLAR training

description: Preprocessed Breast cancer IMC dataset for InterSTELLAR training, saved as a<strong> .npy</strong> file. 1. Read this file with python and get a list named <strong>all_graph</strong>. This list includes <strong>366 </strong>elements as <strong>366 </strong>tissues. 2. Each sub-element <strong>all_graph[i]</strong> is alone a new list with three elements, including <strong>cell feature matrix all_graph[i][0]</strong>,<strong> cell locations all_graph[i][1]</strong> and<strong> tissue labels all_graph[i][2]</strong>. 3.<strong> all_graph[i][0]</strong> is a <strong>Nx30</strong> matrix, corresponding to<strong> 30 cell markers</strong>; <strong>all_graph[i][1]</strong> is a<strong> Nx2</strong> matrix, corresponding to <strong>x </strong>and <strong>y </strong>locations of a single cell; <strong> all_graph[i][2]</strong> is a list with<strong> 5</strong> elements, corresponding to <strong>tissue phenotypes</strong> (0: healthy, 1: TNBC, 2: Non-TNBC cancers), <strong>tissue area</strong> (um<sup>2</sup>),<strong> tumor grade</strong>, <strong>overall survival time </strong>(month) and <strong>patient status</strong> (alive or death).
DOI: 10.5281/zenodo.7527692
title: Breast cancer IMC dataset for InterSTELLAR training

description: <strong>graph_data.npy</strong>: preprocessed Breast cancer IMC dataset for InterSTELLAR training, saved as a<strong> .npy</strong> file. Read this file with python and get a list named <strong>all_graph</strong>. This list includes <strong>368 </strong>elements. The first <strong>366 </strong>elements are the information from each tissue, the last two elements are the <strong>mean </strong>and<strong> standard deviation</strong> of the cell feature data after log-transformation with shape <strong>30x1</strong>. Each sub-element <strong>all_graph[i]</strong> is alone a new list with three elements, including <strong>cell feature matrix all_graph[i][0]</strong>,<strong> cell locations all_graph[i][1],</strong> <strong>tissue labels all_graph[i][2] </strong>and <strong>cell phenotypes</strong> <strong>all_graph[i][3]</strong>. <strong>all_graph[i][0]</strong> is a <strong>Nx30</strong> matrix, corresponding to<strong> 30 cell markers</strong>; <strong>all_graph[i][1]</strong> is a<strong> Nx2</strong> matrix, corresponding to <strong>x </strong>and <strong>y </strong>locations of a single cell; <strong> all_graph[i][2]</strong> is a list with<strong> 5</strong> elements, corresponding to <strong>tissue phenotypes</strong> (0: healthy, 1: TNBC, 2: Non-TNBC cancers), <strong>tissue area</strong> (um<sup>2</sup>),<strong> tumor grade</strong>, <strong>overall survival time </strong>(month) and <strong>patient status</strong> (alive or death); <strong>all_graph[i][3] </strong>is a list with <strong>N </strong>elements corresponding to the <strong>cell phenotypes</strong>. <strong>cell_maskes.npy</strong>: the cell segmentation maskes corresponding to the 366 tissues.
DOI: 10.5519/qd.4h0ghxpb
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (4 records)
DOI: 10.6084/m9.figshare.21875355
title: Dataset for Are Ensemble Perception and Object Recognition Separate Abilities?

description: Dataset for Chang et al. (submitted) <strong>Are Ensemble Perception and Object Recognition Separate Abilities?</strong>
DOI: 10.5281/zenodo.7527712
title: Basal stress fluctuation: Reply to Comment by Cagnoli on "Slope-break Collisions: Comment on 'Insight into Granular Flow Dynamics Relying on Basal Stress Measurements: From Experimental Flume Tests' by K. Li et al."

description: Data supporting the depth-averaged velocities for granular flows with different fractal dimension and the relationship between depth averaged velocity and equivalent friction coefficient for granular flows with different fractal dimension in Figure 1a and Figure 1b.
DOI: 10.5439/1908440
title: ARM: 60VARANARUCV1

description: varanal
DOI: 10.25582/data.2020-09.2048116/1908606
title: Data from EMSL Project 51579
DOI: 10.25582/data.2020-09.2046506/1908607
title: Data from EMSL Project 51579
DOI: 10.25582/data.2020-09.2046501/1908608
title: Data from EMSL Project 51579
DOI: 10.25582/data.2020-09.2059166/1908611
title: Data from EMSL Project 51595
DOI: 10.25582/data.2020-09.2059177/1908612
title: Data from EMSL Project 51595
DOI: 10.25582/data.2020-09.2059141/1908613
title: Data from EMSL Project 51595
DOI: 10.25582/data.2020-09.2059167/1908614
title: Data from EMSL Project 51595
DOI: 10.25582/data.2020-10.2073416/1908615
title: Data from EMSL Project 51580
DOI: 10.21227/c8xx-3v17
title: Parameters of Self-Sustained Highway Transportation Systems.

description: Simulation parameters
DOI: 10.14457/nida.the.2017.87
title: ปัญหาการระงับข้อพิพาทในคดีที่ราชพัสดุ
DOI: 10.14457/nida.the.2017.88
title: การสื่อสารที่ส่งผลต่อการตัดสินใจเลือกบริโภคอาหารคลีนของผู้บริโภคในเขตกรุงเทพมหานคร
DOI: 10.14457/nida.the.2017.89
title: ความผิดทางอาญา: กรณีการคุกคามทางเพศ
DOI: 10.14457/nida.the.2017.90
title: การข่มขืนกระทำชำเราระหว่างคู่ชีวิตเพศเดียวกันศึกษากรณีมาตรา 276 แห่งประมวลกฎหมายอาญา
DOI: 10.14457/nida.the.2017.91
title: วิเคราะห์การรับรู้และการปฏิบัติตนในเศรษฐกิจชุมชน ตามหลักคิดเศรษฐกิจพอเพียงและหลักคิดเศรษฐกิจบุญนิยม: กรณีศึกษาชุมชนราชธานีอโศก จังหวัดอุบลราชธานี
DOI: 10.14457/nida.the.2017.92
title: ปัญหาการฟ้องคดีเกี่ยวกับ "กฎ" ต่อศาลปกครอง
DOI: 10.14457/nida.the.2020.54
title: อิทธิพลของการได้รับการอบรมเลี้ยงดู ทัศนคติ การรับข่าวสาร และแรงจูงใจ ที่มีต่อพฤติกรรมจิตสาธารณะของผู้ที่อยู่ในวัยทำงานในกรุงเทพมหานคร
DOI: 10.14457/nida.the.2020.57
title: การพัฒนาตัวแบบทางคณิตศาสตร์เพื่อเพิ่มความจุของทางวิ่งด้วยการปรับลำดับการลงจอด : กรณีศึกษาสนามบินสุวรรณภูมิ
DOI: 10.14457/nida.the.2020.58
title: แบบจำลองสถานการณ์เพื่อการจัดตารางรถขนส่งที่เหมาะสมสำหรับคลังสินค้าแบบทันเวลาพอดีภายใต้ความไม่แน่นอนด้านเวลาการขนส่ง
DOI: 10.14457/nida.the.2020.59
title: การพัฒนาระบบสแกนวัตถุเพื่อการจัดเก็บข้อมูลพื้นผิวสามมิติรายละเอียดสูงสำหรับพิ้นผิวแบบระนาบและไม่ระนาบ
DOI: 10.14457/nida.the.2020.60
title: An adaptive multi-level sequential floating feature selection
DOI: 10.14457/nida.the.2021.40
title: Cryptocurrencies and traditional assets: the empirical study in dynamic linkages and portfolio optimization
DOI: 10.14457/nida.the.2020.61
title: The development of awareness on green ict through the implications of self-directed learning
DOI: 10.14457/nida.the.2020.62
title: Supporting knowledge management processes by enhancing knowledge management systems functionalities
DOI: 10.14457/nida.the.2020.63
title: การใช้ระบบแนะนำแบบผสมในการแก้ปัญหาผู้ใช้งานระบบรายใหม่ร่วมกับการใช้บริบทสำหรับร้านอาหาร
DOI: 10.6084/m9.figshare.21875346
title: Intertidal macroalgal and epiphytic polychaete distributions strengthen marine ecoregions of Western Australia

description: This dataset contains macroalgal, polychaete, and substrate data for the paper: Hadiyanto, H., J. Prince, R.K. Hovey, and C.J. Glasby. 2023. Intertidal macroalgal and epiphytic polychaete distributions strengthen marine ecoregions of Western Australia. Frontiers of Biogeography. Accepted. <br> The ZIP file contains 10 data: macroalgal species.csv, macroalgal genera.csv, macroalgal families.csv, macroalgal functional groups.csv, polychaete species.csv, polychaete genera.csv, polychaete families.csv, polychaete functional groups.csv, substrate.csv, and macroalgal complexity & heterogeneity.csv. The README file contains an explanation of the data.
DOI: 10.6084/m9.figshare.21875346.v1
title: Intertidal macroalgal and epiphytic polychaete distributions strengthen marine ecoregions of Western Australia

description: This dataset contains macroalgal, polychaete, and substrate data for the paper: Hadiyanto, H., J. Prince, R.K. Hovey, and C.J. Glasby. 2023. Intertidal macroalgal and epiphytic polychaete distributions strengthen marine ecoregions of Western Australia. Frontiers of Biogeography. Accepted. <br> The ZIP file contains 10 data: macroalgal species.csv, macroalgal genera.csv, macroalgal families.csv, macroalgal functional groups.csv, polychaete species.csv, polychaete genera.csv, polychaete families.csv, polychaete functional groups.csv, substrate.csv, and macroalgal complexity & heterogeneity.csv. The README file contains an explanation of the data.
DOI: 10.25914/nkv1-p133
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within the Northern Territory, 2016 to 2018 (Level 0 products)
DOI: 10.25914/5e7032d6ad272
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within the Northern Territory, 2016 to 2018 (Level 1 products)
DOI: 10.25914/5hy9-fc60
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within the Northern Territory, 2016 to 2018 (packed raw time series data)
DOI: 10.25914/r1yv-qe70
title: Magnetotelluric surveys of Tasmania as part of the Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP)
DOI: 10.25914/m8bb-xx89
title: Magnetotelluric surveys of mainland Tasmania and Flinders Island as part of the AusLAMP Tasmania project, 2016 (packed raw time series data)
DOI: 10.25914/e4dz-q275
title: Magnetotelluric surveys of mainland Tasmania and Flinders Island as part of the AusLAMP project, 2016
DOI: 10.25914/q9p9-q215
title: Magnetotelluric surveys of New South Wales (long period)
DOI: 10.25914/hmcw-yx66
title: Magnetotelluric surveys of South Australia (broadband)
DOI: 10.25914/0s9d-8d34
title: Magnetotelluric surveys of South Australia (long period)
DOI: 10.25914/0ped-yh77
title: Magnetotelluric surveys of Tasmania (long period)
DOI: 10.25914/d69t-wr81
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within South Australia, 2016 to 2018
DOI: 10.25914/58gr-1550
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within South Australia, 2016 to 2018 (Level 0 concatenated ASCII time series per day)
DOI: 10.25914/yyg7-e549
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within South Australia, 2016 to 2018 (Level 0 concatenated NetCDF time series)
DOI: 10.25914/d2zj-6r93
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within South Australia, 2016 to 2018 (Level 0 products)
DOI: 10.25914/bdhm-dn80
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within South Australia, 2016 to 2018 (Level 1 concatenated, resampled, rotated NetCDF time series)
DOI: 10.25914/3hrt-a687
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within South Australia, 2016 to 2018 (Level 1 products)
DOI: 10.25914/2jz4-cz52
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within South Australia, 2016 to 2018 (packed raw time series data)
DOI: 10.25914/4ks0-v478
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within the Northern Territory, 2016 to 2018
DOI: 10.25914/9c6r-vt07
title: Magnetotelluric surveys of the AusLAMP Musgraves Province within Western Australia, 2016 to 2018
DOI: 10.14457/nida.the.2020.55
title: Thai EFL teachers' beliefs and practices in CLT in a Thai university context: a study of Rajabhat universities in lower Northeastern area
DOI: 10.14457/nida.the.2020.56
title: ตัวแบบทำนายวันนอนและการกลับมารักษาซ้ำผู้ป่วยสิทธิข้าราชการ
DOI: 10.25914/rrm2-b189
title: Magnetotelluric surveys of the AusLAMP Musgraves Province, 2016 to 2018
DOI: 10.34740/kaggle/dsv/4841192
title: Aksara Jawa / Hanacaraka
DOI: 10.25376/hra.21875409
title: AHA Proposal Final Marisa 2021.docx

description: Acute myocardial infarction (AMI) causes cardiac cell death, reduced myocardial capillary density, and subsequent scar formation. Cardiac damage due to AMI is accompanied by dynamic changes in the expression of microRNAs (miRs), small non-coding RNAs that post-transcriptionally downregulate target genes. Previous studies revealed fundamental impacts of miRs on cardiovascular function in humans. Intriguingly, <strong>novel miR therapies are being used in clinical trials</strong> for other diseases and more recently for <strong>heart failure</strong> (<strong>HF</strong>). We have focused on miR-532-5p (hereinafter referred to as miR-532), which is upregulated β-adrenergic receptor (βAR) antagonist [β-blocker] carvedilol (Carv) acting through β-arrestin-biased β2AR signaling. We reported for the first time that miR-532 plays a vital cardioprotective role in AMI and represses protease serine 23 (prss23). Interestingly, miR-532 expression is significantly enriched in cardiac endothelial cells (CECs) and selectively downregulated in CECs isolated from ischemic myocardium, which is inversely associated with the expression of prss2315. Despite the correlative relationship between prss23 and miR-532, their <em>in vivo</em> functional relationship has never been established, and mechanisms that regulate cell-specific prss23 or miR-532 expression and function in HF are unknown.
DOI: 10.25376/hra.21875409.v1
title: AHA Proposal Final Marisa 2021.docx

description: Acute myocardial infarction (AMI) causes cardiac cell death, reduced myocardial capillary density, and subsequent scar formation. Cardiac damage due to AMI is accompanied by dynamic changes in the expression of microRNAs (miRs), small non-coding RNAs that post-transcriptionally downregulate target genes. Previous studies revealed fundamental impacts of miRs on cardiovascular function in humans. Intriguingly, <strong>novel miR therapies are being used in clinical trials</strong> for other diseases and more recently for <strong>heart failure</strong> (<strong>HF</strong>). We have focused on miR-532-5p (hereinafter referred to as miR-532), which is upregulated β-adrenergic receptor (βAR) antagonist [β-blocker] carvedilol (Carv) acting through β-arrestin-biased β2AR signaling. We reported for the first time that miR-532 plays a vital cardioprotective role in AMI and represses protease serine 23 (prss23). Interestingly, miR-532 expression is significantly enriched in cardiac endothelial cells (CECs) and selectively downregulated in CECs isolated from ischemic myocardium, which is inversely associated with the expression of prss2315. Despite the correlative relationship between prss23 and miR-532, their <em>in vivo</em> functional relationship has never been established, and mechanisms that regulate cell-specific prss23 or miR-532 expression and function in HF are unknown.
DOI: 10.25914/f7qf-g927
title: Magnetotelluric surveys of Victoria (broadband)
DOI: 10.25914/3g2k-dx82
title: Magnetotelluric surveys of Victoria (long period)
DOI: 10.25914/ksmz-6s19
title: Magnetotelluric surveys of Western Australia (broadband)