cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20291939
title: An overview of the characteristics and methodological standards across systematic reviews with Meta-analysis of efficacy/effectiveness of influenza antiviral drugs

description: Influenza antiviral drugs remain controversial and it is not clear if conclusions on their efficacy/effectiveness are based on high quality systematic reviews (SRs). We systematically identified, critically appraised, and summarized the characteristics and adherence to methodological standards in SRs with meta-analysis of efficacy/effectiveness of influenza antiviral drugs for prevention and/or treatment of influenza. We searched MEDLINE, Embase, Scopus, CINAHL, Global Health, and CDSR for English-language SR publications up to July 2020. We summarized the characteristics, adherence to methodological standards and SR quality (AMSTAR 2). From a total 3,898 citations after removal of duplicates from all identified citations, we included 24 SRs. Seventy-five percent (<i>n</i> = 18) were of a critically low quality, 8% (<i>n</i> = 2) of a low quality, 17% (<i>n</i> = 4) of a moderate quality, and none were of a high quality. Seventeen percent (<i>n</i> = 4) were industry-funded, 4% (<i>n</i> = 1) coauthored by industry employee(s), and 33% (<i>n</i> = 8) commissioned by an organization or authority. Only 33% percent (<i>n</i> = 8) reported protocol registration, 4% (<i>n</i> = 1) reported collaboration with a knowledge synthesis librarian/information specialist, and 17% (<i>n</i> = 4) utilized a systematic review reporting checklist. The evidence suggests that SRs of efficacy/effectiveness of influenza antiviral drugs are mostly of critically low quality and do not follow current best SR practices. These findings are significant in view of the important role of SRs in decision-making and the controversies that surround the use of the influenza antiviral drugs. However, the findings should not be interpreted to mean curtailment/cessation of use of antiviral drugs for influenza.
DOI: 10.6084/m9.figshare.21064884
title: Increasing clinical impact and microbiological difficulties in diagnosing coagulase-negative staphylococci in infective endocarditis – a review starting from a series of cases

description: Coagulase-negative staphylococci (CoNS) are an emergent aetiology of infective endocarditis (IE) on native valves in previously healthy individuals, its presence is associated with prosthetic valves or with other cardiac implants. The identification of CoNS in cultures was customarily seen as contamination, but more recent epidemiological studies have revealed an increasing number of causative and virulent new CoNS species. Starting from two clinical cases of community-acquired CoNS IE on native valves, the review debates the difficulties in identifying CoNS as the causal pathogens, comprising differentiation of contamination from infection in IE, alongside the challenges raised by antibiotic resistance. Even if the risk of CoNS IE is more increased in subjects with prosthetic materials or other foreign devices and immunodeficiencies, native valve infections with these staphylococci are increasing and should be considered important pathogens in IE. Despite the lack of sensitive and specific tools to correctly differentiate contamination from infection in CoNS endocarditis, a comprehensive evaluation with clinical and paraclinical data accurately succeeds in establishing the diagnosis. The genetic profile of CoNS predisposes to antibiotic multi-resistance, making the treatment of IE challenging; the rapid identification of antibiotic susceptibility is essential to prescribe the appropriate therapy and improve outcomes.
DOI: 10.6084/m9.figshare.21064884.v2
title: Increasing clinical impact and microbiological difficulties in diagnosing coagulase-negative staphylococci in infective endocarditis – a review starting from a series of cases

description: Coagulase-negative staphylococci (CoNS) are an emergent aetiology of infective endocarditis (IE) on native valves in previously healthy individuals, its presence is associated with prosthetic valves or with other cardiac implants. The identification of CoNS in cultures was customarily seen as contamination, but more recent epidemiological studies have revealed an increasing number of causative and virulent new CoNS species. Starting from two clinical cases of community-acquired CoNS IE on native valves, the review debates the difficulties in identifying CoNS as the causal pathogens, comprising differentiation of contamination from infection in IE, alongside the challenges raised by antibiotic resistance. Even if the risk of CoNS IE is more increased in subjects with prosthetic materials or other foreign devices and immunodeficiencies, native valve infections with these staphylococci are increasing and should be considered important pathogens in IE. Despite the lack of sensitive and specific tools to correctly differentiate contamination from infection in CoNS endocarditis, a comprehensive evaluation with clinical and paraclinical data accurately succeeds in establishing the diagnosis. The genetic profile of CoNS predisposes to antibiotic multi-resistance, making the treatment of IE challenging; the rapid identification of antibiotic susceptibility is essential to prescribe the appropriate therapy and improve outcomes.
DOI: 10.6084/m9.figshare.20291555
title: The evidence from clinical trials on colchicine and corticosteroids’ effect on COVID-19: a systematic review and meta-analysis

description: With no clear end for the outbreak, identifying the drugs that are effective in COVID-19’s management is of utmost importance to reduce the impact on the general population and the healthcare systems. This is a systematic review and a meta-analysis evaluating the evidence from clinical trials on the effect of colchicine and corticosteroids against COVID-19. In this review, we have systematically searched five databases [(PubMed, Embase, clinicaltrials.gov, ICTRP, CINAHL (EBSCO)]. Cochrane’s data extraction sheet was used to collect the required information, and RevMan-5.4.1 was used to conduct the meta-analysis and to assess the risk of bias. The review was registered in Prospero (CRD42022299718) The total number of included studies was 17, with 18,956 participants; the majority were male 12,001. Out of which, 8772 participants were on colchicine, 569 took methylprednisolone, and 64 patients received prednisolone. The meta-analysis has shown that colchicine had no significant effect on reducing the mortality rate among COVID-19 patients [OR 0.98(95% CI 0.90–1.08), <i>p</i> = .70), <i>I<sup>2</sup></i>:1%)], corticosteroids have significantly reduced the mortality rates [OR 0.55 (95% CI 0.33–0.91), <i>p</i> = .02, <i>I<sup>2</sup></i>:40]. Colchicine did not reduce the incidence of ICU admissions [OR 0.74 (95% CI 0.39–1.40), <i>p</i> = .35, <i>I<sup>2</sup></i>:0%], while steroidal drugs significantly reduced the ICU admissions [OR 0.42 (95% CI 0.23–0.78), <i>p</i> = .005, <i>I<sup>2</sup></i>:0%]. Unlike steroidal drugs [OR 0.53 (95% CI 0.30–0.95), <i>p</i> = .03, <i>I<sup>2</sup></i>:61%], colchicine failed to reduce the need for mechanical ventilation [OR 0.73 (95% CI 0.48–1.10), <i>p</i> = .13, <i>I<sup>2</sup></i>:76%]. Steroidal drugs significantly reduced the duration of hospitalization among COVID-19 patients [OR −0.50 (95% CI −0.79–0.21), <i>p</i> = .0007, <i>I<sup>2</sup></i>:36%]. The use of colchicine did not significantly reduce the mortality rate, ICU admissions, and mechanical ventilation among COVID-19 patients. Conversely, corticosteroids significantly reduced the mortality rate, ICU admissions, mechanical ventilation, and hospitalization duration among COVID-19 patients.
DOI: 10.6084/m9.figshare.21064884.v1
title: Increasing clinical impact and microbiological difficulties in diagnosing coagulase-negative staphylococci in infective endocarditis- a review starting from a series of cases

description: Coagulase-negative staphylococci (CoNS) are an emergent aetiology of infective endocarditis (IE) on native valves in previously healthy individuals, its presence being associated with prosthetic valves or with other cardiac implants. The identification of CoNS in cultures was customarily seen as contamination, but more recent epidemiological studies have revealed an increasing number of causative and virulent new CoNS species. Starting from two clinical cases of community-acquired CoNS IE on native valves, the review debates the difficulties in identifying CoNS as the causal pathogens, comprising differentiation of contamination from infection in IE, alongside the challenges raised by antibiotic resistance. Even if the risk of CoNS IE is more increased in subjects with prosthetic materials or other foreign devices and immunodeficiencies, native valve infections with these staphylococci are increasing and should be considered important pathogens in IE. Despite the lack of sensitive and specific tools to correctly differentiate contamination from infection in CoNS endocarditis, a comprehensive evaluation with clinical and paraclinical data accurately succeeds in establishing the diagnosis. The genetic profile of CoNS predisposes to antibiotic multi-resistance, making the treatment of IE challenging; the rapid identification of antibiotic susceptibility is essential to prescribe the appropriate therapy and improve outcomes.
DOI: 10.6084/m9.figshare.20291555.v1
title: The evidence from clinical trials on colchicine and corticosteroids’ effect on COVID-19: a systematic review and meta-analysis

description: With no clear end for the outbreak, identifying the drugs that are effective in COVID-19’s management is of utmost importance to reduce the impact on the general population and the healthcare systems. This is a systematic review and a meta-analysis evaluating the evidence from clinical trials on the effect of colchicine and corticosteroids against COVID-19. In this review, we have systematically searched five databases [(PubMed, Embase, clinicaltrials.gov, ICTRP, CINAHL (EBSCO)]. Cochrane’s data extraction sheet was used to collect the required information, and RevMan-5.4.1 was used to conduct the meta-analysis and to assess the risk of bias. The review was registered in Prospero (CRD42022299718) The total number of included studies was 17, with 18,956 participants; the majority were male 12,001. Out of which, 8772 participants were on colchicine, 569 took methylprednisolone, and 64 patients received prednisolone. The meta-analysis has shown that colchicine had no significant effect on reducing the mortality rate among COVID-19 patients [OR 0.98(95% CI 0.90–1.08), <i>p</i> = .70), <i>I<sup>2</sup></i>:1%)], corticosteroids have significantly reduced the mortality rates [OR 0.55 (95% CI 0.33–0.91), <i>p</i> = .02, <i>I<sup>2</sup></i>:40]. Colchicine did not reduce the incidence of ICU admissions [OR 0.74 (95% CI 0.39–1.40), <i>p</i> = .35, <i>I<sup>2</sup></i>:0%], while steroidal drugs significantly reduced the ICU admissions [OR 0.42 (95% CI 0.23–0.78), <i>p</i> = .005, <i>I<sup>2</sup></i>:0%]. Unlike steroidal drugs [OR 0.53 (95% CI 0.30–0.95), <i>p</i> = .03, <i>I<sup>2</sup></i>:61%], colchicine failed to reduce the need for mechanical ventilation [OR 0.73 (95% CI 0.48–1.10), <i>p</i> = .13, <i>I<sup>2</sup></i>:76%]. Steroidal drugs significantly reduced the duration of hospitalization among COVID-19 patients [OR −0.50 (95% CI −0.79–0.21), <i>p</i> = .0007, <i>I<sup>2</sup></i>:36%]. The use of colchicine did not significantly reduce the mortality rate, ICU admissions, and mechanical ventilation among COVID-19 patients. Conversely, corticosteroids significantly reduced the mortality rate, ICU admissions, mechanical ventilation, and hospitalization duration among COVID-19 patients.
DOI: 10.6084/m9.figshare.19145348
title: Median true principal strain 1

description: Principal true strain 1 of each specimen in every different condition<br>
DOI: 10.6084/m9.figshare.19145348.v1
title: Median true principal strain 1

description: Principal true strain 1 of each specimen in every different condition<br>
DOI: 10.6084/m9.figshare.19145363
title: Median true principal strain 2

description: Median true principal strain 2 for each specimen in all the conditions<br>
DOI: 10.6084/m9.figshare.19145363.v1
title: Median true principal strain 2

description: Median true principal strain 2 for each specimen in all the conditions<br>
DOI: 10.6084/m9.figshare.19145231
title: Posterior disc height

description: PDH for each specimen at peak load in flexion/extension, nucleotomy/discoplasty<br>
DOI: 10.6084/m9.figshare.19145231.v1
title: Posterior disc height

description: PDH for each specimen at peak load in flexion/extension, nucleotomy/discoplasty<br>
DOI: 10.6084/m9.figshare.19145213
title: Range of motion

description: Range of motion of every specimen under the different conditions (flexion/extension, nucleotomy/discoplasty)<br>
DOI: 10.6084/m9.figshare.19145213.v1
title: Range of motion

description: Range of motion of every specimen under the different conditions (flexion/extension, nucleotomy/discoplasty)<br>
DOI: 10.6084/m9.figshare.21667652
title: Phytoplankton Aydat 2020

description: Taxon phytoplankton at Aydat
DOI: 10.6084/m9.figshare.21667652.v1
title: phytoplankton_Aydat2020

description: Taxon phytoplankton at Aydat
DOI: 10.6084/m9.figshare.19145255
title: Stiffness parameters

description: Stiffness parameters for each specimen in every conditions (flexion/extension, nucleotomy/discoplasty)<br>
DOI: 10.6084/m9.figshare.19145255.v1
title: Stiffness parameters

description: Stiffness parameters for each specimen in every conditions (flexion/extension, nucleotomy/discoplasty)<br>
DOI: 10.5258/soton/d2160
title: Dataset in support of the Southampton doctoral thesis 'Fish behavioural response to static visual cues'

description: This dataset contains raw fish coordinate data from four experiments that made up the thesis 'Fish Behavioural Response to Static Visual Cues'. All experiments were conducted within open channel flumes or tanks at the University of Southampton. Ethical apporval was granted by the University of Southampton Ethics and Research Governance committee (ID: 52245). The data is in .csv and .xlsx files so can be viewed within excel.
DOI: 10.6084/m9.figshare.19145378
title: Geometry segmentation DSI

description: Assessment of the geometry segmentation:<br>- cement volume- DSI computation<br>
DOI: 10.6084/m9.figshare.19145378.v1
title: Geometry segmentation DSI

description: Assessment of the geometry segmentation:<br>- cement volume- DSI computation<br>
DOI: 10.6084/m9.figshare.21673745
title: Lake abiotic factors

description: Lake abiotic factors
DOI: 10.6084/m9.figshare.21673745.v1
title: Lake abiotic factors

description: Lake abiotic factors
DOI: 10.5258/soton/d2136
title: Demonstration of Up to 480-km WDM Direct-detection Transmission in the O-band

description: Dataset to support the paper presented at the 48th European Conference on Optical Communication (ECOC 2022) This dataset contains: Fig. 1: Insets: optical spectra of the CWDM QPSK transmission and the DWDM QPSK transmission and gain and NF performance of the in-loop BDFA at -20 dBm input. Fig. 2: BER versus transmission distance for the 50-Gb/s/lambda O-band CWDM transmission using Nyquist OOK.
DOI: 10.5281/zenodo.7014384
title: Compilation of hydrological datasets at the global scale

description: Hydrological variables (evapotranspiration, precipitation, runoff, and terrestrial water storage) are distributed through several datasets that do not have the same characteristics (spatial and temporal coverage, spatial and temporal resolution). This dataset aims at providing a coherent gathering of all datasets available as of January 2021, covering at least the period from 2003 to 2014, and from 50°S to 50°N. This file contains: 14 datasets for evapotranspiration (ERA5-Land, FLUXCOM, GLDAS2.2 CLSM2.5, GLDAS2.1 CLSM2.5, GLDAS2.1 NOAH3.6, GLDAS VIC4.1.2, GLDAS2.0 CLSM2.5, GLDAS2.0 NOAH3.6, GLDAS2.0 VIC4.1.2, GLEAM, JRA55, MERRA2, MOD16, and SEBBop) 11 datasets for precipitation (CPC, CRU, ERA5-Land, PGF, GPCC, GPCP, GPM, JRA55, MERRA2, MSWEP, and TRMM) 11 datasets for runoff (ERA5-Land, GLDAS2.2 CLSM2.5, GLDAS2.1 CLSM2.5, GLDAS2.1 NOAH3.6, GLDAS VIC4.1.2, GLDAS2.0 CLSM2.5, GLDAS2.0 NOAH3.6, GLDAS2.0 VIC4.1.2, GRUN, JRA55, and MERRA2) 2 datasets for terrestrial water storage (GRACE CSR mascons, and GRACE JPL mascons) Each dataset is given as the original version (on a regular grid) and also as a post-treated file averaged for 189 river basins (whose borders are also provided).
description: This dataset was used in the article "How well are we able to close the water budget at the global scale?" (https://doi.org/10.5194/hess-26-35-2022) by Lehmann et al. 2022.
DOI: 10.5281/zenodo.7014385
title: Compilation of hydrological datasets at the global scale

description: Hydrological variables (evapotranspiration, precipitation, runoff, and terrestrial water storage) are distributed through several datasets that do not have the same characteristics (spatial and temporal coverage, spatial and temporal resolution). This dataset aims at providing a coherent gathering of all datasets available as of January 2021, covering at least the period from 2003 to 2014, and from 50°S to 50°N. This file contains: 14 datasets for evapotranspiration (ERA5-Land, FLUXCOM, GLDAS2.2 CLSM2.5, GLDAS2.1 CLSM2.5, GLDAS2.1 NOAH3.6, GLDAS VIC4.1.2, GLDAS2.0 CLSM2.5, GLDAS2.0 NOAH3.6, GLDAS2.0 VIC4.1.2, GLEAM, JRA55, MERRA2, MOD16, and SEBBop) 11 datasets for precipitation (CPC, CRU, ERA5-Land, PGF, GPCC, GPCP, GPM, JRA55, MERRA2, MSWEP, and TRMM) 11 datasets for runoff (ERA5-Land, GLDAS2.2 CLSM2.5, GLDAS2.1 CLSM2.5, GLDAS2.1 NOAH3.6, GLDAS VIC4.1.2, GLDAS2.0 CLSM2.5, GLDAS2.0 NOAH3.6, GLDAS2.0 VIC4.1.2, GRUN, JRA55, and MERRA2) 2 datasets for terrestrial water storage (GRACE CSR mascons, and GRACE JPL mascons) Each dataset is given as the original version (on a regular grid) and also as a post-treated file averaged for 189 river basins (whose borders are also provided).
description: This dataset was used in the article "How well are we able to close the water budget at the global scale?" (https://doi.org/10.5194/hess-26-35-2022) by Lehmann et al. 2022.
DOI: 10.5281/zenodo.7404286
title: Sample

description: Sample 2
DOI: 10.5281/zenodo.7404287
title: Sample

description: Sample
DOI: 10.5281/zenodo.7404297
title: Sample

description: Sample 2
DOI: 10.24339/66b623b4-8b01-4698-ba06-7324dcfad73e
title: RFPM_Validation_Raw_Data
DOI: 10.6084/m9.figshare.21679409.v1
title: Climate and glacier data

description: Above data and analysis codes include: 1) AnalysisData_Climate.m: Analysis code for climate experiments. Use Matlab to open and run this file. Note: some pathways in this code file are absolute pathways and should be changed, otherwise errors will be reported. 2) AnalysisData_Glacier.m: Analysis code for glacier simulations. Use Matlab to open and run this file. Results of the analysis part have been stored at Glacier_difference.mat. Note: some pathways in this code file are absolute pathways and should be changed, otherwise errors will be reported. 3) Basedata.mat: Store the base dataset used for the analysis in AnalysisData_Climate.m. 4) Climate_difference.mat: All the variables in this mat are derived from the climate experiments. GlobalX means the annual mean results, SummerX means the boreal summer results. The size of these variables: longitude*latitude*(atmospheric layer)*3 (CTL results, SCE results, significant). This data is used for AnalysisData_Climate.m. 5) Glacier_difference,mat: The meaning of each variables in this data is list in AnalysisData_Glacier.m. This data is used for AnalysisData_Glacier.m. 6) AnalysisData.zip: store the 99-year simulation results of some variables used in the AnalysisData_Climate.m. 7) Wilcoxon.m: Judge whether the difference is significant ( non-parametric Wilcoxon signed-rank test). 8) TPPolygon.shp: the shp file of the Tibetan Plateau. 9) brewermap.m: generate the colormap of each figure. 10) 00_rgi60_regions_xxx: shp file of the 13 (or 15) second-order regions over the Tibetan Plateau and its surrounding regions (Pfeffer et al., 2014; RGI Consortium et al., 2017). 11) draw_radar2.m: this file is used to draw figure 2(b). 12) p50_degree_glacier_volume_km3.tif: This tif is provided by Farinotti et al., 2019. 13) suppl_GlacierMIP_results.nc: this nc file is provided by Marzeion et al., 2020
DOI: 10.5281/zenodo.6983054
title: 3D S-wave velocity profiles with random fields

description: This dataset contains 40,000 3D matrices representing S-wave velocity profiles with random fields. The spatial resolution corresponds to a grid of 9.6 x 9.6 x 9.6km with a spatial step of 300m (matrices are of size 33 x 33 x 33). Velocities go from 1,071 to 4,500m/s. Each profile contains a 1.8km-thick bottom layer at constant velocity 4500m/s. Above, the profile contains between 1 and 6 layers of random thickness. In each layer, the mean velocity is chosen uniformly in [1,785; 3,214m/s] and the coefficient of variation follows a Gaussian distribution N(0.2; 0.1). Then, correlation lengths are chosen once for all the profile's layers among 1.5, 3, 4.5, 6 km in all three directions. The random fields' kernel has a von Karman correlation with a Hurst exponent of 0.1 and log-normal marginal distributions.
DOI: 10.6084/m9.figshare.21641564.v1
title: Annual Ground Observations and Study Area

description: Here are included the shapefile for the spatio-temporal data extraction of remote sensing data from ground observation. Ground observations are sub-divided annually, while study area cover all observation, and is required for geospatial data prepration.
DOI: 10.5281/zenodo.7404185
title: 3D S-wave velocity profiles with random fields

description: This dataset contains 100,000 3D matrices representing S-wave velocity profiles with random fields. The spatial resolution corresponds to a grid of 9.6 x 9.6 x 9.6km with a spatial step of 300m (matrices are of size 33 x 33 x 33). Velocities go from 1,071 to 4,500m/s. Each profile contains a 1.8km-thick bottom layer at constant velocity 4500m/s. Above, the profile contains between 1 and 6 layers of random thickness. In each layer, the mean velocity is chosen uniformly in [1,785; 3,214m/s] and the coefficient of variation follows a Gaussian distribution N(0.2; 0.1). Then, a correlation length is chosen randomly among 1.5, 3, 4.5, 6 km in all three directions for each layer. The random fields' kernel has a von Karman correlation with a Hurst exponent of 0.1 and log-normal marginal distributions.
DOI: 10.5281/zenodo.6983053
title: 3D S-wave velocity profiles with random fields

description: This dataset contains 100,000 3D matrices representing S-wave velocity profiles with random fields. The spatial resolution corresponds to a grid of 9.6 x 9.6 x 9.6km with a spatial step of 300m (matrices are of size 33 x 33 x 33). Velocities go from 1,071 to 4,500m/s. Each profile contains a 1.8km-thick bottom layer at constant velocity 4500m/s. Above, the profile contains between 1 and 6 layers of random thickness. In each layer, the mean velocity is chosen uniformly in [1,785; 3,214m/s] and the coefficient of variation follows a Gaussian distribution N(0.2; 0.1). Then, a correlation length is chosen randomly among 1.5, 3, 4.5, 6 km in all three directions for each layer. The random fields' kernel has a von Karman correlation with a Hurst exponent of 0.1 and log-normal marginal distributions.