cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14747933
title: Redox signaling and antioxidant therapies in acute respiratory distress syndrome: a systematic review and meta-analysis

description: <b>Objectives</b>: No pharmacologic treatment that targets the pathophysiologic alterations of acute respiratory distress syndrome (ARDS) has proven effective. Previous studies have revealed overactive oxidative stress as a potential therapeutic target. Thus we conducted this systematic review to assess the efficacyof antioxidant therapy on the clinical outcomes of ARDS patients. <b>Methods</b>: We retrieved clinical trials from electronic databases. Articles and conference abstracts about antioxidant therapies for patients with ARDS were identified in which the overall effect of each antioxidant therapy on the mortality of ARDS patients was summarized. <b>Results</b>: We identified 18 relevant studies that met the inclusion criteria, including 899 patients in the experimental group and 870 patients in the control group. The pooled results indicated that most antioxidant therapies could not improve all-cause mortality and might even be harmful in ARDS patients at low risk of death. <b>Conclusion</b>: Unclassified patients could not benefit from the antioxidant therapies, and thus discretion must be exercised when using these therapies. <b>Abbreviations</b> ARDS: Acute respiratory distress syndrome; ICU: Intensive care unit; NAC: N-acetylcysteine; ROS: Reactive oxygen species; RNS: Reactive nitrogen species; RR: Relative risk; CI: Confidence interval; OTC: L-2-oxothiazolidine-4-carboxylic acid; EPA: Eicosapentaenoic acid; DHA: Docosahexaenoic acid; GLA: Gamma-linolenic acid; NA: Not applicable; PaO<sub>2</sub>/FiO<sub>2</sub> ratio: The ratio of partial pressure arterial oxygen and fraction of inspired oxygen; ALI: Acute lung injury.
DOI: 10.6084/m9.figshare.14541145
title: Outcomes of acute respiratory distress syndrome in COVID-19 patients compared to the general population: a systematic review and meta-analysis

description: Acute respiratory distress syndrome (ARDS) due to coronavirus disease 2019 (COVID-19) often leads to mortality. Outcomes of patients with COVID-19-related ARDS compared to ARDS unrelated to COVID-19 is not well characterized. We performed a systematic review of PubMed, Scopus, and MedRxiv 11/1/2019 to 3/1/2021, including studies comparing outcomes in COVID-19-related ARDS (COVID-19 group) and ARDS unrelated to COVID-19 (ARDS group). Outcomes investigated were duration of mechanical ventilation-free days, intensive care unit (ICU) length-of-stay (LOS), hospital LOS, and mortality. Random effects models were fit for each outcome measure. Effect sizes were reported as pooled median differences of medians (MDMs), mean differences (MDs), or odds ratios (ORs). Ten studies with 2,281 patients met inclusion criteria (COVID-19: 861 [37.7%], ARDS: 1420 [62.3%]). There were no significant differences between the COVID-19 and ARDS groups for median number of mechanical ventilator-free days (MDM: −7.0 [95% CI: −14.8; 0.7], p = 0.075), ICU LOS (MD: 3.1 [95% CI: −5.9; 12.1], p = 0.501), hospital LOS (MD: 2.5 [95% CI: −5.6; 10.7], p = 0.542), or all-cause mortality (OR: 1.25 [95% CI: 0.78; 1.99], p = 0.361). Compared to the general ARDS population, results did not suggest worse outcomes in COVID-19-related ARDS.
DOI: 10.6084/m9.figshare.14541145.v1
title: Outcomes of acute respiratory distress syndrome in COVID-19 patients compared to the general population: a systematic review and meta-analysis

description: Acute respiratory distress syndrome (ARDS) due to coronavirus disease 2019 (COVID-19) often leads to mortality. Outcomes of patients with COVID-19-related ARDS compared to ARDS unrelated to COVID-19 is not well characterized. We performed a systematic review of PubMed, Scopus, and MedRxiv 11/1/2019 to 3/1/2021, including studies comparing outcomes in COVID-19-related ARDS (COVID-19 group) and ARDS unrelated to COVID-19 (ARDS group). Outcomes investigated were duration of mechanical ventilation-free days, intensive care unit (ICU) length-of-stay (LOS), hospital LOS, and mortality. Random effects models were fit for each outcome measure. Effect sizes were reported as pooled median differences of medians (MDMs), mean differences (MDs), or odds ratios (ORs). Ten studies with 2,281 patients met inclusion criteria (COVID-19: 861 [37.7%], ARDS: 1420 [62.3%]). There were no significant differences between the COVID-19 and ARDS groups for median number of mechanical ventilator-free days (MDM: −7.0 [95% CI: −14.8; 0.7], p = 0.075), ICU LOS (MD: 3.1 [95% CI: −5.9; 12.1], p = 0.501), hospital LOS (MD: 2.5 [95% CI: −5.6; 10.7], p = 0.542), or all-cause mortality (OR: 1.25 [95% CI: 0.78; 1.99], p = 0.361). Compared to the general ARDS population, results did not suggest worse outcomes in COVID-19-related ARDS.
DOI: 10.6084/m9.figshare.14747933.v2
title: Redox signaling and antioxidant therapies in acute respiratory distress syndrome: a systematic review and meta-analysis

description: <b>Objectives</b>: No pharmacologic treatment that targets the pathophysiologic alterations of acute respiratory distress syndrome (ARDS) has proven effective. Previous studies have revealed overactive oxidative stress as a potential therapeutic target. Thus we conducted this systematic review to assess the efficacyof antioxidant therapy on the clinical outcomes of ARDS patients. <b>Methods</b>: We retrieved clinical trials from electronic databases. Articles and conference abstracts about antioxidant therapies for patients with ARDS were identified in which the overall effect of each antioxidant therapy on the mortality of ARDS patients was summarized. <b>Results</b>: We identified 18 relevant studies that met the inclusion criteria, including 899 patients in the experimental group and 870 patients in the control group. The pooled results indicated that most antioxidant therapies could not improve all-cause mortality and might even be harmful in ARDS patients at low risk of death. <b>Conclusion</b>: Unclassified patients could not benefit from the antioxidant therapies, and thus discretion must be exercised when using these therapies. <b>Abbreviations</b> ARDS: Acute respiratory distress syndrome; ICU: Intensive care unit; NAC: N-acetylcysteine; ROS: Reactive oxygen species; RNS: Reactive nitrogen species; RR: Relative risk; CI: Confidence interval; OTC: L-2-oxothiazolidine-4-carboxylic acid; EPA: Eicosapentaenoic acid; DHA: Docosahexaenoic acid; GLA: Gamma-linolenic acid; NA: Not applicable; PaO<sub>2</sub>/FiO<sub>2</sub> ratio: The ratio of partial pressure arterial oxygen and fraction of inspired oxygen; ALI: Acute lung injury.
DOI: 10.6084/m9.figshare.14747933.v1
title: Redox signaling and antioxidant therapies in acute respiratory distress syndrome: a systematic review and meta-analysis

description: <b>Objectives</b>: No pharmacologic treatment that targets the pathophysiologic alterations of acute respiratory distress syndrome (ARDS) has proven effective. Previous studies have revealed overactive oxidative stress as a potential therapeutic target. Thus we conducted this systematic review to assess the efficacyof antioxidant therapy on the clinical outcomes of ARDS patients. <b>Methods</b>: We retrieved clinical trials from electronic databases. Articles and conference abstracts about antioxidant therapies for patients with ARDS were identified in which the overall effect of each antioxidant therapy on the mortality of ARDS patients was summarized. <b>Results</b>: We identified 18 relevant studies that met the inclusion criteria, including 899 patients in the experimental group and 870 patients in the control group. The pooled results indicated that most antioxidant therapies could not improve all-cause mortality and might even be harmful in ARDS patients at low risk of death. <b>Conclusion</b>: Unclassified patients could not benefit from the antioxidant therapies, and thus discretion must be exercised when using these therapies. <b>Abbreviations</b> ARDS: Acute respiratory distress syndrome; ICU: Intensive care unit; NAC: N-acetylcysteine; ROS: Reactive oxygen species; RNS: Reactive nitrogen species; RR: Relative risk; CI: Confidence interval; OTC: L-2-oxothiazolidine-4-carboxylic acid; EPA: Eicosapentaenoic acid; DHA: Docosahexaenoic acid; GLA: Gamma-linolenic acid; NA: Not applicable; PaO<sub>2</sub>/FiO<sub>2</sub> ratio: The ratio of partial pressure arterial oxygen and fraction of inspired oxygen; ALI: Acute lung injury.
DOI: 10.25625/cvagrl/ocnhom
title: t7-7_Ar_0_355_K_375_K_1p5_mm_12x4_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/qcjnmy
title: t5-5_Ar_0_350_K_360_K_1p5_mm_15x4_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/gchoai
title: 0-F_Ar_0_330_K_340_K_1p0_mm_8x4_min_0p35_bar.dat

description: :unav
DOI: 10.25625/cvagrl/8rtqfx
title: 0-MM_Ar_0_315_K_325_K_1p25_mm_12x4_min_1p0_bar.dat

description: :unav
DOI: 10.25625/cvagrl/cfk3rg
title: c6-6_Ar_0_355_K_375_K_2p0_mm_10x4_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/669qgq
title: CP-CP_Ar_0_395_K_415_K_1p0_mm_8x4_min_0p35_bar.dat

description: :unav
DOI: 10.25625/cvagrl/7oqunx
title: 0-M_Ar_0_315_K_325_K_1p5_mm_9x10_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/vxi8tp
title: t6-6_Ar_10_375_K_395_K_1p25_mm_17x4_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/cidunh
title: M-MM_Ar_0_315_K_325_K_0p75_mm_5x3_min_0p35_bar.dat

description: :unav
DOI: 10.25625/cvagrl/oydyj4
title: 0-0_Ar_0_315_K_325_K_2p0_mm_10x10_min_1p0_bar.dat

description: :unav
DOI: 10.25625/cvagrl/guf8c0
title: 0-V_Ar_0_325_K_335_K_1p5_mm_21x4_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/00aj8z
title: 0-M_Ar_6_315_K_325_K_1p5_mm_10x10_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/pdmkkc
title: 0-M_Ar_14_315_K_325_K_1p5_mm_10x10_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/ic7qbt
title: rM-M_Ar_0_315_K_325_K_1p0_mm_12x4_min_0p8_bar.dat

description: :unav
DOI: 10.25625/cvagrl/ghvoa3
title: 0-Ph_Ar_0_355_K_375_K_1p0_mm_9x4_min_0p35_bar.dat

description: :unav
DOI: 10.25625/cvagrl/iy05e8
title: 0-Ph_Ar_15_355_K_375_K_1p0_mm_11x4_min_0p35_bar.dat

description: :unav
DOI: 10.25625/cvagrl/vlczpp
title: CP-MM_Ar_0_325_K_345_K_1p0_mm_7x4_min_0p35_bar.dat

description: :unav
DOI: 10.25625/cvagrl/hjlzja
title: MM-MM_Ar_0_300_K_300_K_1p5_mm_12x12_min_1p2_bar.dat

description: :unav
DOI: 10.25625/cvagrl/dcvzcq
title: t6-6_Ar_2p5_375_K_395_K_1p25_mm_10x4_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/9lrurf
title: c6-6_Ar_0_355_K_375_K_1p25_mm_7x4_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/r24td8
title: 0-Ph_Ar_27_355_K_375_K_1p0_mm_14x4_min_0p35_bar.dat

description: :unav
DOI: 10.25625/cvagrl/uuw78k
title: t6-6_Ar_0_375_K_395_K_1p25_mm_8x4_min_1p4_bar.dat

description: :unav
DOI: 10.25625/cvagrl/kjb4ao
title: t4-4_Ar_0_325_K_345_K_0p5_mm_17x3_min_0p35_bar.dat

description: :unav
DOI: 10.6084/m9.figshare.14959356
title: Scripts and data from "Prediction Markets for Probabilistic Forecasting of Renewable Energy Sources"

description: The MATLAB scripts and data inputs underlying this paper.<br>
DOI: 10.5066/p9sq1y3t
title: Estimated Use of Water by Subbasin (HUC8) in the Red River Basin, 2010 and 2015

description: The Red River basin is one of several national "focus area studies" in the U.S. Geological Survey National Water Census. The objective of the National Water Census is to provide nationally-consistent base layers of well-documented data that account for water availability and use nationally. A focus area study (FAS) is a stakeholder-driven assessment of water availability in river basins with known or potential conflict. The Red River basin covers more than 93,000 square miles with a population of over 4 million people. Water resources in the basin are being stressed by increasing water demands and increasingly severe droughts. The results of the FAS will facilitate better management of water resources for human use and help maintain ecological flows in the basin. The Red River FAS is a comprehensive water-resource assessment of the basin, which is needed to enable sustainable water use. The Red River FAS is organized around four study components that are intended to improve the quality and accessibility of water information in the basin, and to advance technical water assessment capabilities: water use, groundwater, rainfall-runoff (surface water) model, and ecological flows. This data release is a component of the water use assessment. The dataset contains estimates of water withdrawals from the Red River basin in the states of Arkansas, Louisiana, New Mexico, Oklahoma, and Texas based on drainage basins delineated by 8-digit hydrologic unit codes (HUC8s). The dataset includes groundwater and surface-water withdrawals for public supply, domestic, irrigation, thermoelectric power, industrial, mining, livestock and aquaculture water-use categories. The dataset is a refinement of the 2010 and 2015 data compiled at the county level for the United States Geological Survey (USGS) National Water Use Science Project. Additionally, these data complement and support the USGS Web application located at: https://webapps.usgs.gov/watercensus/redriver_fas/wateruse.html.
DOI: 10.25345/c5nv82
title: MassIVE MSV000088125 - Metabolome profiling of induced overexpression of S cerevisiae genes
title: Metabolite extracts were collected for 86 inducible overexpression strains in Saccharomyces cerevisiae in the presence and absence of inducer. Induction was carried out for 1.5 hours prior to metabolite extraction. Extracts were subjected to flow injection analysis.
DOI: 10.5281/zenodo.5517675
title: Supplemental Material: An Experimental Evaluation of ITL, TDD and BDD: An extended study

description: The supplementary material is distributed as follows:<br> 1) The list of figures that have not been included in the paper due to formatting limitations. <br> 2) A list of tables that have not been included in the paper due to formatting limitations.<br> 3) The data collection files that are part of the experimental process.<br> 4) The experimental plan document describing the activities performed in the experiment.
DOI: 10.5281/zenodo.5517674
title: Supplemental Material: An Experimental Evaluation of ITL, TDD and BDD: An extended study

description: The supplementary material is distributed as follows:<br> 1) The list of figures that have not been included in the paper due to formatting limitations. <br> 2) A list of tables that have not been included in the paper due to formatting limitations.<br> 3) The data collection files that are part of the experimental process.<br> 4) The experimental plan document describing the activities performed in the experiment.
DOI: 10.25810/8196-e820.41
title: United Kingdom Newspaper Coverage of Climate Change or Global Warming, 2000-2021 - August 2021

description:         The Media and Climate Change Observatory Data monitors 127 sources (across newspapers, radio and TV) in 59 countries in seven different regions around the world. Data is assembled by accessing archives through the Lexis Nexis, Proquest and Factiva databases via the University of Colorado libraries. More information may be found at: http://mecco.colorado.edu.
DOI: 10.6084/m9.figshare.15081620
title: A new prognostic model for predicting 30-day mortality in acute oncology patients

description: Acute oncology services (AOS) provide rapid review and expedited pathways for referral to specialist care for cancer patients. Blood tests may support AOS in providing estimates of prognosis. We aimed to develop and validate a prognostic model of 30-day mortality based on routine blood markers to inform an AOS decision to actively treat or palliate patients. Using clinical data from 752 AOS referrals, multivariable logistic regression analysis was conducted to develop a 30-day mortality prognostic model. Internal validation and then internal–external cross-validation were used to examine overfitting and generalizability of the model’s predictive performance. Urea, alkaline phosphatase, albumin and neutrophils were the strongest predictors of outcome. The model separated patients into distinct prognostic groups from the cross-validation (C Statistic: 0.70; 95% CI: 0.64–0.76). Admission year was included as a predictor in the model to improve the model calibration. The developed prediction model was able to classify patients into distinct prognostic risk groups, which is clinically useful for delivering an evidence-based AOS. Collation of data from other AOS centers would allow for the development of a more generalizable prognostic model.
DOI: 10.6084/m9.figshare.14602594
title: Phosphatidylinositol 3-kinase (PI3K) inhibitors: a recent update on inhibitor design and clinical trials (2016–2020)

description: <b>Introduction</b>: The phosphatidylinositol 3-kinase/protein kinase-B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway plays a central role in regulating cell growth and proliferation and thus has been considered as effective anticancer drug targets. Many PI3K inhibitors have been developed and progressed to various stages of clinical trials, and some have been approved as anticancer treatment. In this review, we discuss the drug design and clinical development of PI3K inhibitors over the past 4 years. We review the selectivity and potency of 47 PI3K inhibitors. Structural determinants for increasing selectivity toward PI3K subtype-selectivity or mutant selectivity are discussed. Future research direction and current clinical development in combination therapy of inhibitors involved in PI3Ks are also discussed. <b>Area covered</b>: This review covers clinical trial reports and patent literature on PI3K inhibitors and their selectivity published between 2016 and 2020. <b>Expert opinion</b>: To PI3Kα mutants (E542K, E545K, and H1047R), it is highly desirable to design and develop mutant-specific PI3K inhibitors. It is also necessary to develop subtype-selective PI3Kα inhibitors to minimize toxicity. To reduce drug resistance and to improve efficacy, future studies should include combination therapy of PI3K inhibitors with existing anticancer drugs from different pathways.
DOI: 10.6084/m9.figshare.14602594.v1
title: Phosphatidylinositol 3-kinase (PI3K) inhibitors: a recent update on inhibitor design and clinical trials (2016–2020)

description: <b>Introduction</b>: The phosphatidylinositol 3-kinase/protein kinase-B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway plays a central role in regulating cell growth and proliferation and thus has been considered as effective anticancer drug targets. Many PI3K inhibitors have been developed and progressed to various stages of clinical trials, and some have been approved as anticancer treatment. In this review, we discuss the drug design and clinical development of PI3K inhibitors over the past 4 years. We review the selectivity and potency of 47 PI3K inhibitors. Structural determinants for increasing selectivity toward PI3K subtype-selectivity or mutant selectivity are discussed. Future research direction and current clinical development in combination therapy of inhibitors involved in PI3Ks are also discussed. <b>Area covered</b>: This review covers clinical trial reports and patent literature on PI3K inhibitors and their selectivity published between 2016 and 2020. <b>Expert opinion</b>: To PI3Kα mutants (E542K, E545K, and H1047R), it is highly desirable to design and develop mutant-specific PI3K inhibitors. It is also necessary to develop subtype-selective PI3Kα inhibitors to minimize toxicity. To reduce drug resistance and to improve efficacy, future studies should include combination therapy of PI3K inhibitors with existing anticancer drugs from different pathways.
DOI: 10.6084/m9.figshare.15081620.v2
title: A new prognostic model for predicting 30-day mortality in acute oncology patients

description: Acute oncology services (AOS) provide rapid review and expedited pathways for referral to specialist care for cancer patients. Blood tests may support AOS in providing estimates of prognosis. We aimed to develop and validate a prognostic model of 30-day mortality based on routine blood markers to inform an AOS decision to actively treat or palliate patients. Using clinical data from 752 AOS referrals, multivariable logistic regression analysis was conducted to develop a 30-day mortality prognostic model. Internal validation and then internal–external cross-validation were used to examine overfitting and generalizability of the model’s predictive performance. Urea, alkaline phosphatase, albumin and neutrophils were the strongest predictors of outcome. The model separated patients into distinct prognostic groups from the cross-validation (C Statistic: 0.70; 95% CI: 0.64–0.76). Admission year was included as a predictor in the model to improve the model calibration. The developed prediction model was able to classify patients into distinct prognostic risk groups, which is clinically useful for delivering an evidence-based AOS. Collation of data from other AOS centers would allow for the development of a more generalizable prognostic model.
DOI: 10.6084/m9.figshare.15081620.v1
title: A new prognostic model for predicting 30-day mortality in acute oncology patients

description: Acute oncology services (AOS) provide rapid review and expedited pathways for referral to specialist care for cancer patients. Blood tests may support AOS in providing estimates of prognosis. We aimed to develop and validate a prognostic model of 30-day mortality based on routine blood markers to inform an AOS decision to actively treat or palliate patients. Using clinical data from 752 AOS referrals, multivariable logistic regression analysis was conducted to develop a 30-day mortality prognostic model. Internal validation and then internal–external cross-validation were used to examine overfitting and generalizability of the model’s predictive performance. Urea, alkaline phosphatase, albumin and neutrophils were the strongest predictors of outcome. The model separated patients into distinct prognostic groups from the cross-validation (C Statistic: 0.70; 95% CI: 0.64–0.76). Admission year was included as a predictor in the model to improve the model calibration. The developed prediction model was able to classify patients into distinct prognostic risk groups, which is clinically useful for delivering an evidence-based AOS. Collation of data from other AOS centers would allow for the development of a more generalizable prognostic model.
DOI: 10.5281/zenodo.5510442
title: swmm-nrtestsuite: Regression Test Suite for OWA SWMM

description: Open Water Analytics (OWA) Stormwater Management Model (SWMM) Project Link: <br> https://github.com/OpenWaterAnalytics/swmm-nrtestsuite
DOI: 10.5281/zenodo.5510260
title: swmm-nrtestsuite: Regression Test Suite for OWA SWMM

description: Open Water Analytics (OWA) Stormwater Management Model (SWMM) Project Link: <br> https://github.com/OpenWaterAnalytics/swmm-nrtestsuite
DOI: 10.5281/zenodo.5517692
title: Recovery and Resilience of Oyster Reefs in the Big Bend of Florida - Oyster transect count data

description: These data represent counts of live and dead oysters from line-transect surveys used to evaluate status and trends in intertidal Eastern Oyster (“oyster”) reefs in the Suwannee Sound region of the northeastern Gulf of Mexico. For details on methods and example application see Moore et al. 2020.
description: {"references": ["Moore, J. F., Pine III, W. E., Frederick, P. C., Beck, S., Moreno, M., Dodrill, M. J., ... & Yurek, S. (2020). Trends in oyster populations in the Northeastern Gulf of Mexico: an assessment of river discharge and fishing effects over time and space. Marine and Coastal Fisheries, 12(3), 191-204.", "Moore, J. F., & Pine III, W. E. (2021). Bootstrap methods can help evaluate monitoring program performance to inform restoration as part of an adaptive management program. PeerJ, 9, e11378."]}