cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/j4bck84rpr.3
title: Whole-body kinematic adaptations to running on an unstable, irregular, and compliant surface: Data, code, and supplemental files

description: This data set contains the raw data and participant information underlying a study on whole-body movement adaptations to running on an unstable surface in recreational runners. The underlying study compared the whole-body running motion and indicators of whole-body motor control between running on asphalt (stable) and a wood chip track (unstable) on five separate testing days. 

The running motion was measured outdoors using an inertial-based motion analysis suit (Xsens Link). This measurement system computes segment positions of 23 body segments and joint angles for 22 joints. On each of the five testing days, runners completed one "test" on each of the two surfaces. One "test" included 2 runs back and forth along a 140m path. The data from each run were split and the 180° turn in the middle was cut out, yielding two repetitions per run. Therefore, the data set includes four files per "test" (run 1 - repetition 1, run 1 - repetition 2, run 2 - repetition 1, run 2 - repetition 2) for a total of 40 files per participant (four files x two surfaces x five testing days). The sample rate of the motion analysis suit was 240 Hz but the data were downsampled to 120 Hz during post-processing.
 
This data set contains the following items:
1) "Raw_JointAngles_And_SegmentPositions.zip": This file contains 17 folders; one for each of the 17 runners that were evaluated in this study. Each folder contains four .mat files. a) Angles.mat - joint angle time series, b) Positions.mat - segment position time series, c) RF_indices.mat - the frame numbers of the detected right foot strikes (see associated publication), d) Mean_Speed.mat - the average running speed for each surface and day. Angles.mat and Positions.mat contain 40 files corresponding to the 40 running repetitions as explained above. 

2)  "PCA_Output.mat": The segment positions in the underlying study were analyzed by means of a kinematic principal component analysis. This file contains the resulting "principal positions" (PP_TrialSubj matrix, 40 running repetitions x 17 runners), "PCs" (the principal component vectors), "EV" (the eigenvalues). More details about the PCA and the data processing modalities can be found in the associated publication. The underlying software is publicly available (PMAnalyzer; https://www.uibk.ac.at/de/isw/forschung/neurophysiology-of-exercise/pm_analyzer/) and described in this publication (https://www.frontiersin.org/articles/10.3389/fninf.2019.00024/full)

3) "Participant Information.xlsx": Basic participant information. Note, that 2 participants had experience running on a woodchip track and were excluded from the analysis in the publication.

4) "Angles_Columns_Names.xlsx" & "Positions_Columns_Names.xlsx": Descriptors of position and angle signals. 

5) "TrialNumbers.xlsx": Explanation of the forty running repetitions.

6) "Supplementary Figures.docx" & "Supplementary Videos.zip": Supplementary Files of the associated publication.

7) Code to be added in next version.
DOI: 10.17632/j4bck84rpr.4
title: Whole-body kinematic adaptations to running on an unstable, irregular, and compliant surface: Data, code, and supplemental files

description: This data set contains the raw data and participant information underlying a study on whole-body movement adaptations to running on an unstable surface in recreational runners. The underlying study compared the whole-body running motion and indicators of whole-body motor control between running on asphalt (stable) and a wood chip track (unstable) on five separate testing days. 

The running motion was measured outdoors using an inertial-based motion analysis suit (Xsens Link). This measurement system computes segment positions of 23 body segments and joint angles for 22 joints. On each of the five testing days, runners completed one "test" on each of the two surfaces. One "test" included 2 runs back and forth along a 140m path. The data from each run were split and the 180° turn in the middle was cut out, yielding two repetitions per run. Therefore, the data set includes four files per "test" (run 1 - repetition 1, run 1 - repetition 2, run 2 - repetition 1, run 2 - repetition 2) for a total of 40 files per participant (four files x two surfaces x five testing days). The sample rate of the motion analysis suit was 240 Hz but the data were downsampled to 120 Hz during post-processing.
 
This data set contains the following items:
1) "Raw_JointAngles_And_SegmentPositions.zip": This file contains 17 folders; one for each of the 17 runners that were evaluated in this study. Each folder contains four .mat files. a) Angles.mat - joint angle time series, b) Positions.mat - segment position time series, c) RF_indices.mat - the frame numbers of the detected right foot strikes (see associated publication), d) Mean_Speed.mat - the average running speed for each surface and day. Angles.mat and Positions.mat contain 40 files corresponding to the 40 running repetitions as explained above. 

2)  "PCA_Output.mat": The segment positions in the underlying study were analyzed by means of a kinematic principal component analysis. This file contains the resulting "principal positions" (PP_TrialSubj matrix, 40 running repetitions x 17 runners), "PCs" (the principal component vectors), "EV" (the eigenvalues). More details about the PCA and the data processing modalities can be found in the associated publication. The underlying software is publicly available (PMAnalyzer; https://www.uibk.ac.at/de/isw/forschung/neurophysiology-of-exercise/pm_analyzer/) and described in this publication (https://www.frontiersin.org/articles/10.3389/fninf.2019.00024/full)

3) "Participant Information.xlsx": Basic participant information. Note, that 2 participants had experience running on a woodchip track and were excluded from the analysis in the publication.

4) "Angles_Columns_Names.xlsx" & "Positions_Columns_Names.xlsx": Descriptors of position and angle signals. 

5) "TrialNumbers.xlsx": Explanation of the forty running repetitions.

6) "Supplementary Figures.docx" & "Supplementary Videos.zip": Supplementary Files of the associated publication.

7) Code to be added in next version.
DOI: 10.17632/j4bck84rpr.1
title: Whole-body kinematic adaptations to running on an unstable, irregular, and compliant surface: Data, code, and supplemental files

description: Data underlying a study on whole-body movement adaptations to running on an unstable surface.
DOI: 10.17632/j4bck84rpr.2
title: Whole-body kinematic adaptations to running on an unstable, irregular, and compliant surface: Data, code, and supplemental files

description: This data set contains the raw data and participant information underlying a study on whole-body movement adaptations to running on an unstable surface in recreational runners. The underlying study compared the whole-body running motion and indicators of whole-body motor control between running on asphalt (stable) and a wood chip track (unstable) on five separate testing days. 

The whole-body running motion was measured while running outdoors using an inertial-based full-body motion analysis suit (Xsens Link). This measurement system computes segment positions of 23 body segments and joint angles for 22 joints. On each of the five testing days, runners completed one "test" on each of the two surfaces. One "test" included 2 runs back and forth along a 140m path. The data from each run were split and the 180° turn in the middle was cut out, yielding two repetitions per run. Therefore, the data set includes four files per "test" (run 1 - repetition 1, run 1 - repetition 2, run 2 - repetition 1, run 2 - repetition 2) for a total of 40 files per participant (four files x two surfaces x five testing days). The sample rate of the motion analysis suit was 240 Hz but the data were downsampled to 120 Hz during post-processing.
 
This data set contains the following items:
1) "Raw_JointAngles_And_SegmentPositions.zip": This file contains 17 folders; one for each of the 17 runners that were evaluated in this study. Each folder contains four .mat files. a) Angles.mat - joint angle time series, b) Positions.mat - segment position time series, c) RF_indices.mat - the frame numbers of the detected right foot strikes (see associated publication), d) Mean_Speed.mat - the average running speed for each surface and day. Angles.mat and Positions.mat contain 40 files corresponding to the 40 running repetitions as explained above. 

2)  "PCA_Output.mat": The segment positions in the underlying study were analyzed by means of a kinematic principal component analysis. This file contains the resulting "principal positions" (PP_TrialSubj matrix, 40 running repetitions x 17 runners), "PCs" (the principal component vectors), "EV" (the eigenvalues). More details about the PCA and the data processing modalities can be found in the associated publication. The underlying software is publicly available (PMAnalyzer; https://www.uibk.ac.at/de/isw/forschung/neurophysiology-of-exercise/pm_analyzer/) and described in this publication (https://www.frontiersin.org/articles/10.3389/fninf.2019.00024/full)

3) "Participant Information.xlsx": Basic participant information. Note, that 2 participants had experience running on a woodchip track and were excluded from the analysis in the publication.

4) "Angles_Columns_Names.xlsx" & "Positions_Columns_Names.xlsx": Descriptors of position and angle signals. 

5) "TrialNumbers.xlsx": Explanation of the forty running repetitions.
DOI: 10.17632/j4bck84rpr.5
title: Whole-body kinematic adaptations (and its reliability) to running on an unstable, irregular, and compliant surface: Data and supplemental files

description: This data set contains the raw data and participant information underlying a study on whole-body movement adaptations (and its reliability) to running on an unstable surface in recreational runners. The underlying study compared the whole-body running motion and indicators of whole-body motor control between running on asphalt (stable) and a wood chip track (unstable) on five separate testing days. A parallel study investigated the reliability of XSens-based joint angles within- and between-days.

The running motion was measured outdoors using an inertial-based motion analysis suit (Xsens Link). This measurement system computes segment positions of 23 body segments and joint angles for 22 joints. On each of the five testing days, runners completed one "test" on each of the two surfaces. One "test" included 2 runs back and forth along a 140m path. The data from each run were split and the 180° turn in the middle was cut out, yielding two repetitions per run. Therefore, the data set includes four files per "test" (run 1 - repetition 1, run 1 - repetition 2, run 2 - repetition 1, run 2 - repetition 2) for a total of 40 files per participant (four files x two surfaces x five testing days). The sample rate of the motion analysis suit was 240 Hz but the data were downsampled to 120 Hz during post-processing.
 
This data set contains the following items:
1) "Raw_JointAngles_And_SegmentPositions.zip": This file contains 17 folders; one for each of the 17 runners that were evaluated in this study. Each folder contains four .mat files. a) Angles.mat - joint angle time series, b) Positions.mat - segment position time series, c) RF_indices.mat - the frame numbers of the detected right foot strikes (see associated publication), d) Mean_Speed.mat - the average running speed for each surface and day. Angles.mat and Positions.mat contain 40 files corresponding to the 40 running repetitions as explained above. NEW in version 5: This folder now also contains Angles_recal.mat. These data can be used to estimate the calibration error of the XSens suit. The publication of the reliability methods and results will be linked as soon as it becomes available.

2) "PCA_Output.mat": The segment positions in the underlying study were analyzed by means of a kinematic principal component analysis. This file contains the resulting "principal positions" (PP_TrialSubj matrix, 40 running repetitions x 17 runners), "PCs" (the principal component vectors), "EV" (the eigenvalues). More details about the PCA and the data processing modalities can be here:https://www.frontiersin.org/articles/10.3389/fninf.2019.00024/full

3) "Participant Information.xlsx": Basic participant information. 

4) "Angles_Columns_Names.xlsx" & "Positions_Columns_Names.xlsx": Descriptors of position and angle signals. 

5) "TrialNumbers.xlsx": Explanation of the forty running repetitions.

6) "Supplementary Figures.docx" & "Supplementary Videos.zip": Supplementary Files of the associated publication
DOI: 10.17632/ntktm2sfgg.1
title: 5% dextrose

description: Effect of 5% glucose on postoperative recovery
DOI: 10.5281/zenodo.10436061
title: СОВРЕМЕННЫЕ МЕТОДЫ ЛЕЧЕНИЯ РЕВМАТОИДНОГО АРТРИТА (ОБЗОР ЛИТЕРАТУРЫ)
DOI: 10.5281/zenodo.10436060
title: СОВРЕМЕННЫЕ МЕТОДЫ ЛЕЧЕНИЯ РЕВМАТОИДНОГО АРТРИТА (ОБЗОР ЛИТЕРАТУРЫ)
DOI: 10.6084/m9.figshare.1084449
title: Sequence of the p007ampGFP plasmid

description: Sequence of a plasmid used in the teaching resoruces for synthetic biology developed in the UNIGEMS project. For more detailes please go to https://doi.org/10.1099/acmi.0.000596.v3.
DOI: 10.6084/m9.figshare.1084448
title: Sequence of the p006kanGFP plasmid

description: Sequence of a plasmid used in the teaching resoruces for synthetic biology developed in the UNIGEMS project. For more detailes please go to https://doi.org/10.1099/acmi.0.000596.v3.
DOI: 10.6084/m9.figshare.1084448.v1
title: Sequence of the p006kanGFP plasmid

description: Sequence of a plasmid used in the teaching resoruces for synthetic biology developed in the UNIGEMS project. For more detailes please go to https://doi.org/10.1099/acmi.0.000596.v3.
DOI: 10.6084/m9.figshare.1084447
title: Sequence of the p005kanRFP plasmid

description: Sequence of a plasmid used in the teaching resoruces for synthetic biology developed in the UNIGEMS project. For more detailes please go to https://doi.org/10.1099/acmi.0.000596.v3.<br>
DOI: 10.6084/m9.figshare.24908082
title: 20231228_starrydata2

description: All data on Starrydata2, a database of experimental properties in the field of inorganic materials
DOI: 10.6084/m9.figshare.24908082.v1
title: 20231228_starrydata2

description: All data on Starrydata2, a database of experimental properties in the field of inorganic materials
DOI: 10.6084/m9.figshare.24200700
title: Antismash secondary metabolite results for Erwinia comparative genomics analysis

description: Antismash v7 HTML summaries of the secondary metabolites detected in Erwinia genomes assessed in the comparative genomics analysis of Erwinia impunctatus.
DOI: 10.34740/kaggle/dsv/7291455
title: Mahanagar Yatayat Transport Dataset
DOI: 10.34740/kaggle/dsv/7291474
title: MoviesDatasets
DOI: 10.5281/zenodo.10436092
title: serinus_pusillus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.10436091
title: serinus_pusillus_spades_01.fasta.gz

description: .
DOI: 10.6084/m9.figshare.24908274
title: Supplementary Material for: Association between periodontitis and mild cognitive impairment: a systematic review and meta-analysis

description: Introduction: The connection between periodontitis and mild cognitive impairment (MCI) continues to receive attention. However, whether periodontitis is a risk factor for MCI remains still uncertain. This study aims to systematically analyze the available literature regarding the relationship between periodontitis and the risk of developing MCI, and whether the periodontal health of MCI patients is poorer.
Methods: A literature search of PubMed, Scopus, Embase and Web of Science databases was conducted to include all studies on the relationship between periodontitis and MCI from inception to April 2023. The studies were independently screened by 2 researchers, and those meeting the inclusion criteria were extracted and cross-checked. Pooled odds ratio (OR) or mean difference (MD) with 95% confidence intervals (CI) was calculated using either a fixed-effects or random-effects model.
Results: Seven studies with a total of 3973 participants were included. Meta-analysis results showed a statistically significant higher incidence of MCI in patients with periodontitis OR,1.70 (95% CI: 1.24-2.32, p&lt;0.001) compared to healthy participants. A subgroup meta-analysis showed that the pooled OR for the risk of MCI in patients with severe periodontitis was 2.09 (95% CI: 1.49-2.92, p&lt;0.001). In addition, attachment loss (MD=0.44, 95% CI: 0.12-0.75, p&lt;0.001) and plaque index (MD=0.72, 95% CI: 0.50-0.93, p&lt;0.001) were higher in MCI patients compared with the control group, but the pocket probing depth (MD=0.21, 95% CI: -0.08-0.49, p=0.15) was not significantly different in between two groups.
Conclusions: Patients with periodontitis are at a higher risk of developing MCI and the periodontal health of MCI patients is generally compromised.
DOI: 10.6084/m9.figshare.24908295
title: Supplementary Material for: Association between periodontitis and mild cognitive impairment: a systematic review and meta-analysis

description: Introduction: The connection between periodontitis and mild cognitive impairment (MCI) continues to receive attention. However, whether periodontitis is a risk factor for MCI remains still uncertain. This study aims to systematically analyze the available literature regarding the relationship between periodontitis and the risk of developing MCI, and whether the periodontal health of MCI patients is poorer.
Methods: A literature search of PubMed, Scopus, Embase and Web of Science databases was conducted to include all studies on the relationship between periodontitis and MCI from inception to April 2023. The studies were independently screened by 2 researchers, and those meeting the inclusion criteria were extracted and cross-checked. Pooled odds ratio (OR) or mean difference (MD) with 95% confidence intervals (CI) was calculated using either a fixed-effects or random-effects model.
Results: Seven studies with a total of 3973 participants were included. Meta-analysis results showed a statistically significant higher incidence of MCI in patients with periodontitis OR,1.70 (95% CI: 1.24-2.32, p&lt;0.001) compared to healthy participants. A subgroup meta-analysis showed that the pooled OR for the risk of MCI in patients with severe periodontitis was 2.09 (95% CI: 1.49-2.92, p&lt;0.001). In addition, attachment loss (MD=0.44, 95% CI: 0.12-0.75, p&lt;0.001) and plaque index (MD=0.72, 95% CI: 0.50-0.93, p&lt;0.001) were higher in MCI patients compared with the control group, but the pocket probing depth (MD=0.21, 95% CI: -0.08-0.49, p=0.15) was not significantly different in between two groups.
Conclusions: Patients with periodontitis are at a higher risk of developing MCI and the periodontal health of MCI patients is generally compromised.
DOI: 10.6084/m9.figshare.24908295.v1
title: Supplementary Material for: Association between periodontitis and mild cognitive impairment: a systematic review and meta-analysis

description: Introduction: The connection between periodontitis and mild cognitive impairment (MCI) continues to receive attention. However, whether periodontitis is a risk factor for MCI remains still uncertain. This study aims to systematically analyze the available literature regarding the relationship between periodontitis and the risk of developing MCI, and whether the periodontal health of MCI patients is poorer.
Methods: A literature search of PubMed, Scopus, Embase and Web of Science databases was conducted to include all studies on the relationship between periodontitis and MCI from inception to April 2023. The studies were independently screened by 2 researchers, and those meeting the inclusion criteria were extracted and cross-checked. Pooled odds ratio (OR) or mean difference (MD) with 95% confidence intervals (CI) was calculated using either a fixed-effects or random-effects model.
Results: Seven studies with a total of 3973 participants were included. Meta-analysis results showed a statistically significant higher incidence of MCI in patients with periodontitis OR,1.70 (95% CI: 1.24-2.32, p&lt;0.001) compared to healthy participants. A subgroup meta-analysis showed that the pooled OR for the risk of MCI in patients with severe periodontitis was 2.09 (95% CI: 1.49-2.92, p&lt;0.001). In addition, attachment loss (MD=0.44, 95% CI: 0.12-0.75, p&lt;0.001) and plaque index (MD=0.72, 95% CI: 0.50-0.93, p&lt;0.001) were higher in MCI patients compared with the control group, but the pocket probing depth (MD=0.21, 95% CI: -0.08-0.49, p=0.15) was not significantly different in between two groups.
Conclusions: Patients with periodontitis are at a higher risk of developing MCI and the periodontal health of MCI patients is generally compromised.
DOI: 10.5281/zenodo.10436117
title: linurgus_olivaceus_spades_01.fasta.gz

description: .
DOI: 10.5281/zenodo.10436118
title: linurgus_olivaceus_spades_01.fasta.gz

description: .
DOI: 10.6084/m9.figshare.24908265
title: DB_644_QC.zip

description: The SNP genotyping data containing variant information for the French Yorkshire pigs.
DOI: 10.57967/hf/1529
title: TuPy-Dataset
DOI: 10.6084/m9.figshare.24647790.v1
title: Supplementary Material for: Mitochondrial Common Deletion Level in Adipose Tissue is Not Associated with Obesity but is Associated with a Structural Change in Triglycerides as Revealed by FTIR Spectroscopy

description: Objective: Several studies have shown that the mitochondrial metabolism may be disrupted if the rate of the specific 4977 bp deletion of mitochondrial DNA (mtDNA) reaches a threshold. This study aims to investigate the possible associations between the mtDNA4977 deletion load and obesity-related metabolic abnormalities in the adipose tissue. Methods: The study included thirty obese individuals, who underwent bariatric surgery, and twelve control subjects. mtDNA4977 deletion, adenine nucleotides and lactate levels, which show the bioenergetic status were evaluated in visceral adipose tissues. Fourier transform infrared (FTIR) spectroscopy was used to investigate the structural variations and composition of adipose tissue in the context of deletion load. Results: There were no differences between the two groups in terms of mtDNA4977 deletion, adenine nucleotides, and lactate levels. The FTIR spectra indicated a few obesity-related alterations in adipose tissue that were not related to the mtDNA deletion load. Also, statistical analysis showed a correlation between deletion load and a band shift of 1744 cm-1, which assigns C = O stretching of the carbonyl group of the ester group in triglycerides and other esterified fatty acids, although it is not associated with obesity. Conclusions: Our data suggest that the mtDNA4977 deletion in visceral adipose tissue of obese individuals do not have a significant impact on bioenergetic status. However, the increased accumulation of deletion may be associated with a specific change in the ester bond, indicating structural differences in the lipids. These findings shed light on our understanding of the tissue-specific distribution of mtDNA deletions and obesity-related adipose tissue pathogenesis.