cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/ffx7vnmgcb.2
title: Supplemental Materials for "Pre-operative and intra-operative dermoscopy of nail unit squamous cell carcinoma and its relationship with the depth of invasion: a retrospective study."

description: Supplemental figure 1
Supplemental table 1 and 2
DOI: 10.5281/zenodo.10064011
title: Microcrystal electron diffraction (microED) datasets of 5,5,13,13-tetramethyl-3,7,11,15-tetraoxa-1,9(1,4)-dibenzenacyclohexadecaphane-2,8,10,16-tetraone and xylariaopyrone A

description: xylariaopyrone A: KN869S-D12
5,5,13,13-tetramethyl-3,7,11,15-tetraoxa-1,9(1,4)-dibenzenacyclohexadecaphane-2,8,10,16-tetraone: Q649
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.5281/zenodo.10064010
title: Microcrystal electron diffraction (microED) datasets of 5,5,13,13-tetramethyl-3,7,11,15-tetraoxa-1,9(1,4)-dibenzenacyclohexadecaphane-2,8,10,16-tetraone and xylariaopyrone A

description: xylariaopyrone A: KN869S-D12
5,5,13,13-tetramethyl-3,7,11,15-tetraoxa-1,9(1,4)-dibenzenacyclohexadecaphane-2,8,10,16-tetraone: Q649
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.17632/5w7bh793hk.1
title: Construction and validation of nomogram model for risk of perioperative cardiovascular events in patients with colorectal cancer recovering from AMI

description: Data from this study were obtained from the Chinese Colorectal Cancer surgery Database (CCCD). The CCCD was established by the Colorectal Surgery Group of the Surgery Branch of the Chinese Medical Association. It involves the participation of 73 medical centers across 26 provinces, autonomous regions, and municipalities. Since its initiation in March 2018, the database has incorporated information from approximately 100,000 patients. The CCCD adopts a hospital-centered entry model for surgical cases of CRC. It contains relatively comprehensive registration information encompassing a total of 77 variables including preoperative comorbidities and surgical complications. In this study, we used the keyword "history of AMI" to screen CCCD cases from March 2018 to March 2023. In total, 196 patients met the inclusion criteria. Clinical data were retrospectively analyzed and the patients were divided into perioperative cardiovascular events (PCE) and non-PCE groups according to the occurrence of PCE (occurrence of PCE=1, absence of PCE=0). This research study was conducted retrospectively from data obtained for clinical purposes.
DOI: 10.17632/78ypd9b4m8.1
title: Research and correlation analysis of a time compression algorithm based on GNSS visible satellites

description: Used to reproduce some table data and pictures in the paper
DOI: 10.17632/wwrd6zkrn4.1
title: Editorial Lugones

description: Prestación de servicios editoriales de alta calidad para la comunicación de contenidos sobre temas médicos, científicamente comprobables, dirigidos a la población médica y a la comunidad en general de nuestro país y de Latinoamérica
DOI: 10.17632/wwrd6zkrn4.2
title: Estudio de seguridad y eficacia del ácido hialurónico reticulado en relleno de surcos nasolabiales

description: Introducción: el envejecimiento facial provoca cambios celulares y anatómicos que resultan en la pérdida de volumen de los tejidos blandos. Ante la demanda estética, el ácido hialurónico (AH) es una muy buena opción para el relleno de surcos y arrugas faciales.
Objetivos: comprobar la eficacia y seguridad de la aplicación de ácido hialurónico reticulado (AHR) para el relleno de surcos nasolabiales (SNL), y su permanencia en el tiempo.
Diseño: clínico observacional y descriptivo, longitudinal y prospectivo, de 12 meses de duración.
Materiales y métodos: se estudió un total de 100 pacientes (86 mujeres y 14 hombres) con SNL de moderados a graves, entre julio de 2018 y diciembre de 2019. Se utilizó AHR 30 mg/ml para relleno facial (Estrianon Hyaluronic Implant 30®, Allanmar International Company S.R.L., Argentina).
Resultados: los efectos adversos remitieron a los 7 días en el 97% de los pacientes y en el resto a los 14 días. La aplicación inicial fue de hasta 1 ml por surco en los casos más graves. En cuanto a su eficacia como relleno, se comprobó que su duración promedio es de hasta 8 meses con las reaplicaciones correspondientes.
Conclusiones: Estrianon Hyaluronic Implant 30® es un producto seguro. Su duración depende, en gran medida, de la edad del paciente, sus hábitos y el estado de su piel, superando los 8 meses y pudiendo alcanzar el año.
DOI: 10.5281/zenodo.10410021
title: Selected properties of galaxy, MBHs and MBHBs populations (Izquierdo-Villalba et al. 2022)

description: This is a catalogue of galaxies, massive black holes (MBHs) and massive black hole binaries (MBHBs) generated with L-Galaxies semi-analytical model in the version of Izquierdo-Villalba et al. 2022and the dark matter merger trees extracted from the Millennium simulation (Springel et al. 2005). The catalogue is created by making use of only 9 sub-volumes of the Millennium box (~2% of the wholesimulation, Volume = 5562144.30 Mpc3) and it contains galaxies, MBHs and MBHBs at51 different redshifts (0 < z < 12.5). This catalogue is suited for studying the populationof MBHBs and their hosts. The properties stored in this catalogue are the following:

Redshift: Redshift of the galaxy/MBH/MBHB
SnapNum: Snapnum of the simulation
Pos: Position of the galaxy/MBH/MBHB inside the comoving box. It is an array of dimension 3. [Mpc/h]
Vel: Velocity of the galaxy/MBH/MBHB inside the comoving box. It is an array of dimension 3. [km/s]
Mvir: Virial mass of the dark matter sub-halo [1e10 Msun/h]
Rvir: Virial radius of the dark matter sub-halo [Mpc/h]
Vvir: Virial velocity of the dark matter sub-halo [km/s]
Vmax: Maximum circular velocity of the dark matter halo [km/s]
HotRadius: Radius of the hot gas atmosphere that surrounds the galaxy [1e10 Msun/h]
ColdGas: Cold gas component of the galaxy [1e10 Msun/h]
BulgeMass: Stellar mass of the bulge component [1e10 Msun/h]
DiskMass:  Stellar mass of the disc component [1e10 Msun/h]. The total stellar mass of the galaxy should be BulgeMass+DiskMass
HotGas:    Hot gas component of the galaxy [1e10 Msun/h]
BlackHoleMass: Mass of the primary MBH of the galaxy [1e10 Msun/h]
Lbol: Bolometric luminosity of the primary MBH of the galaxy [1e40 erg/s]
fEDD: Ratio between the Lbol of the primary and the Eddington luminosity (<=1) [No dimensions]
spin: Spin of the primary MBH [0,1]
M_dot_acc: Accretion rate of the primary MBH of the galaxy [Msun/yr]
BlackHoleMassSec: Mass of the secondary MBH (if exists) of the galaxy [1e10 Msun/h]
LbolSec: Bolometric luminosity of the secondary MBH (if exists) of the galaxy [1e40 erg/s]
fEDDSec: Ratio between the Lbol of the secondary MBH (if exists) and the Eddington luminosity (<=1) [No dimensions]
spinSec: Spin of the primary MBH (if exists) [0,1]
M_dot_acc_sec: Accretion rate of the secondary MBH (if exists) of the galaxy [Msun/yr]
BinarySemiMajorAxis: Semi-major axis of the MBHB [Mpc/h]
BinaryEccentricity: Eccentricity of the MBHB
Sfr: Star formation rate of the galaxy [Msun/yr]
BulgeSize: Size of the bulge stellar component [Mpc/h]
StellarDiskRadius: Scale length of the disc stellar component [Mpc/h]
GasDiskRadius: Scale length of the disc gas component [Mpc/h]

The file can be read as follows:

import h5py
hf = h5py.File('LGal_IzquierdoVillalba2022_SubVol_0_9.h5', 'r')
DOI: 10.5281/zenodo.10410022
title: Selected properties of galaxy, MBHs and MBHBs populations (Izquierdo-Villalba et al. 2022)

description: This is a catalogue of galaxies, massive black holes (MBHs) and massive black hole binaries (MBHBs) generated with L-Galaxies semi-analytical model in the version of Izquierdo-Villalba et al. 2022and the dark matter merger trees extracted from the Millennium simulation (Springel et al. 2005). The catalogue is created by making use of only 9 sub-volumes of the Millennium box (~2% of the wholesimulation, Volume = 5562144.30 Mpc3) and it contains galaxies, MBHs and MBHBs at51 different redshifts (0 < z < 12.5). This catalogue is suited for studying the populationof MBHBs and their hosts. The properties stored in this catalogue are the following:

Redshift: Redshift of the galaxy/MBH/MBHB
SnapNum: Snapnum of the simulation
Pos: Position of the galaxy/MBH/MBHB inside the comoving box. It is an array of dimension 3. [Mpc/h]
Vel: Velocity of the galaxy/MBH/MBHB inside the comoving box. It is an array of dimension 3. [km/s]
Mvir: Virial mass of the dark matter sub-halo [1e10 Msun/h]
Rvir: Virial radius of the dark matter sub-halo [Mpc/h]
Vvir: Virial velocity of the dark matter sub-halo [km/s]
Vmax: Maximum circular velocity of the dark matter halo [km/s]
HotRadius: Radius of the hot gas atmosphere that surrounds the galaxy [1e10 Msun/h]
ColdGas: Cold gas component of the galaxy [1e10 Msun/h]
BulgeMass: Stellar mass of the bulge component [1e10 Msun/h]
DiskMass:  Stellar mass of the disc component [1e10 Msun/h]. The total stellar mass of the galaxy should be BulgeMass+DiskMass
HotGas:    Hot gas component of the galaxy [1e10 Msun/h]
BlackHoleMass: Mass of the primary MBH of the galaxy [1e10 Msun/h]
Lbol: Bolometric luminosity of the primary MBH of the galaxy [1e40 erg/s]
fEDD: Ratio between the Lbol of the primary and the Eddington luminosity (<=1) [No dimensions]
spin: Spin of the primary MBH [0,1]
M_dot_acc: Accretion rate of the primary MBH of the galaxy [Msun/yr]
BlackHoleMassSec: Mass of the secondary MBH (if exists) of the galaxy [1e10 Msun/h]
LbolSec: Bolometric luminosity of the secondary MBH (if exists) of the galaxy [1e40 erg/s]
fEDDSec: Ratio between the Lbol of the secondary MBH (if exists) and the Eddington luminosity (<=1) [No dimensions]
spinSec: Spin of the primary MBH (if exists) [0,1]
M_dot_acc_sec: Accretion rate of the secondary MBH (if exists) of the galaxy [Msun/yr]
BinarySemiMajorAxis: Semi-major axis of the MBHB [Mpc/h]
BinaryEccentricity: Eccentricity of the MBHB
Sfr: Star formation rate of the galaxy [Msun/yr]
BulgeSize: Size of the bulge stellar component [Mpc/h]
StellarDiskRadius: Scale length of the disc stellar component [Mpc/h]
GasDiskRadius: Scale length of the disc gas component [Mpc/h]

The file can be read as follows:

import h5py
hf = h5py.File('LGal_IzquierdoVillalba2022_SubVol_0_9.h5', 'r')
DOI: 10.17632/s62jkk3fkt.1
title: ACTi graphs: Datasets of physiological experiments associated with measurement on stress and energy expenditure

description: The database presented combines the data from the ActiGraphs worn by the test participants. During these tests, the participants wore three ActiGraphs placed on their ankle, waist and wrist. The published data is pre-processed data that has been processed in the ActiLife software. This database made it possible to compare energy expenditure with the number of mistakes made and with the participants' perception of stress. The data is divided into folders, with each folder referring to a participant. Within each participant folder there are three folders and a file. Each folder stores the pre-processed data from the ACTiGraphs and is divided by the body zones where the sensors are placed (ankle, waist and wrist). The "performance.xlsx" file details the participant's performance during the test. The pre-processed ACTiGraphs files show the counts of the sensor axis. These counts are calculated by the ACTiLife software, and the method of calculation is something that the company does not make public. There is also other information in these files, such as the indication of inclinometers and step counts, data that was not used in this study. The "performace.xlsx" file describes the conditions and results of the tasks that each participant had to carry out. It details the start and end time of each task, the number of errors made while performing the task, and the environmental and noise conditions ("Temperature" and "Noise"). This file also records the answers to a stress questionnaire that was applied at the end of each task. This questionnaire can be found in the attached documents under "Stress Questionnaire.pdf".
DOI: 10.17632/s62jkk3fkt.2
title: ACTi graphs: Datasets of physiological experiments associated with measurement on stress and energy expenditure

description: The database presented combines the data from the ActiGraphs worn by the test participants. During these tests, the participants wore three ActiGraphs placed on their ankle, waist and wrist. The published data is pre-processed data that has been processed in the ActiLife software. This database made it possible to compare energy expenditure with the number of mistakes made and with the participants' perception of stress.
The data is divided into folders, with each folder referring to a participant. Within each participant folder there are three folders and a file. Each folder stores the pre-processed data from the ACTiGraphs and is divided by the body zones where the sensors are placed (ankle, waist and wrist). The "performance.xlsx" file details the participant's performance during the test.
The pre-processed ACTiGraphs files show the counts of the sensor axis. These counts are calculated by the ACTiLife software, and the method of calculation is something that the company does not make public. There is also other information in these files, such as the indication of inclinometers and step counts, data that was not used in this study.
The "performace.xlsx" file describes the conditions and results of the tasks that each participant had to carry out. It details the start and end time of each task, the number of errors made while performing the task, and the environmental and noise conditions ("Temperature" and "Noise"). This file also records the answers to a stress questionnaire that was applied at the end of each task. This questionnaire can be found in the attached documents under "Stress Questionnaire.pdf". The "NoStress_Processing.py" is a python script that allow to process the data.
DOI: 10.17632/s62jkk3fkt.3
title: ACTi graphs: Datasets of physiological experiments associated with measurement on stress and energy expenditure

description: The database presented combines the data from the ActiGraphs worn by the test participants. During these tests, the participants wore three ActiGraphs placed on their ankle, waist and wrist. The published data is pre-processed data that has been processed in the ActiLife software. This database made it possible to compare energy expenditure with the number of mistakes made and with the participants' perception of stress.
The data is divided into folders, with each folder referring to a participant. Within each participant folder there are three folders and a file. Each folder stores the pre-processed data from the ACTiGraphs and is divided by the body zones where the sensors are placed (ankle, waist and wrist). The "performance.xlsx" file details the participant's performance during the test.
The pre-processed ACTiGraphs files show the counts of the sensor axis. These counts are calculated by the ACTiLife software, and the method of calculation is something that the company does not make public. There is also other information in these files, such as the indication of inclinometers and step counts, data that was not used in this study.
The "performace.xlsx" file describes the conditions and results of the tasks that each participant had to carry out. It details the start and end time of each task, the number of errors made while performing the task, and the environmental and noise conditions ("Temperature" and "Noise"). This file also records the answers to a stress questionnaire that was applied at the end of each task. This questionnaire can be found in the attached documents under "Stress Questionnaire.pdf". The "NoStress_Processing.py" is a python script that allow to process the data.
DOI: 10.5281/zenodo.10059863
title: Microcrystal electron diffraction (microED) datasets of hinnuliquinone, pachybasin, and pachybasin/chrysophanol

description: pachybasin: The22-E7
pachybasin/chrysophanol: The22-E8
hinnuliquinone: KN869S-E4
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.5281/zenodo.10059864
title: Microcrystal electron diffraction (microED) datasets of hinnuliquinone, pachybasin, and pachybasin/chrysophanol

description: pachybasin: The22-E7
pachybasin/chrysophanol: The22-E8
hinnuliquinone: KN869S-E4
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.5281/zenodo.8206532
title: Microcrystal electron diffraction (microED) datasets of calcium oxalate, calliterpenone acetate, chrysophanol, and emodin

description: Calcium oxalate: KN869S-H10
Calliterpenone acetate: Q649
Chrysophanol: The22-E9
Emodin: The22-D9 & The22-D10
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.5281/zenodo.8206533
title: Microcrystal electron diffraction (microED) datasets of calcium oxalate, calliterpenone acetate, chrysophanol, and emodin

description: Calcium oxalate: KN869S-H10
Calliterpenone acetate: Q649
Chrysophanol: The22-E9
Emodin: The22-D9 & The22-D10
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.5281/zenodo.10059841
title: Microcrystal electron diffraction (microED) datasets of demethoxyviridin, hinnuliquinone, mannitol

description: demethoxyviridin: KN869S
hinnuliquinone: KN869S-E4
mannitol: KN-1487-D3
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.5281/zenodo.10059842
title: Microcrystal electron diffraction (microED) datasets of demethoxyviridin, hinnuliquinone, mannitol

description: demethoxyviridin: KN869S
hinnuliquinone: KN869S-E4
mannitol: KN-1487-D3
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.5281/zenodo.10059795
title: Microcrystal electron diffraction (microED) datasets of 6B-hydroxyeremophilenolide, 7-chloro-3,4-dihydro-8-hydroxy-6-methoxy-3-methylisocoumarin, 5-hydroxy-7,4-dimethoxyflavone

description:  6B-hydroxyeremophilenolide: KN334-E2
 7-chloro-3,4-dihydro-8-hydroxy-6-methoxy-3-methylisocoumarin: KN334-E3
5-hydroxy-7,4-dimethoxyflavone: flavone
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.5281/zenodo.10059796
title: Microcrystal electron diffraction (microED) datasets of 6B-hydroxyeremophilenolide, 7-chloro-3,4-dihydro-8-hydroxy-6-methoxy-3-methylisocoumarin, 5-hydroxy-7,4-dimethoxyflavone

description:  6B-hydroxyeremophilenolide: KN334-E2
 7-chloro-3,4-dihydro-8-hydroxy-6-methoxy-3-methylisocoumarin: KN334-E3
5-hydroxy-7,4-dimethoxyflavone: flavone
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.5281/zenodo.10059575
title: Microcrystal electron diffraction (microED) datasets of calliterpenone, emodin, 6B-hydroxyeremophilenolide

description: Emodin: The22-D10
Calliterpenone: Q649
 6B-hydroxyeremophilenolide: KN334-E2
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.5281/zenodo.10059574
title: Microcrystal electron diffraction (microED) datasets of calliterpenone, emodin, 6B-hydroxyeremophilenolide

description: Emodin: The22-D10
Calliterpenone: Q649
 6B-hydroxyeremophilenolide: KN334-E2
Data processed using Python script located at github.com/jess-burch/microed
DOI: 10.6084/m9.figshare.24878490
title: Data of Nutritional changes in trees during drought-induced mortality, a comprehensive meta-analysis and a field study

description: The impact of the nutritional status of trees on their ability to withstand drought-induced mortality remains inconclusive. Our meta-analysis indicated that tissue phosphorus (P), potassium (K), iron (Fe) and copper (Cu) concentrations declined obviously with decreasing tree vitalities, implying their roles as a potential early-warning signal for impending tree mortality. However, our field study showed no significant differences in tissue nutrient concentrations among Scots pine trees of different vitalities. This discrepancy could be explained by several critical variables including experimental design types, tree ontogenetic stages, organ types, phylum, leaf life traits, forest biomes, and soil types.
DOI: 10.17632/gfx5dwt2tg.1
title: Gemcitabine in Atypical Teratoid/Rhabdoid Tumors

description: Raw RNA-seq data belonging to the 'Gemcitabine therapeutically disrupts essential SIRT1-mediated p53 repression in Atypical Teratoid/Rhabdoid Tumors' manuscript. 

VUMC-ATRT-03, VUMC-DIPG-10, VUMC-DIPG-11, VUMC-HGG-09, JHH-DIPG-01, HSJD-DIPG-07, and SU-pcGBM-2 neurospheres were treated with 5nM gemcitabine or DMSO as control. After 24h, cells were collected and processed as described previously. Sequencing, performed on an Illumina Nextseq 500 sequencer, data processing in the R2 platform (R2.amc.nl), and statistical analysis were also assessed as previously described.
DOI: 10.17632/b2k4gmwhmm.1
title: Human dermal fibroblast secretomes (normal & Huntington's disease)

description: Comparative analysis of the composition of the non-vesicular fraction of the secretomes of human dermal fibroblasts from a patient with Huntington's disease (HDDF line, sample #42) and a healthy person (DF262 line, sample #32).
DOI: 10.17632/r4zm9sj6cf.1
title: MLRN

description: This is an image dataset designed for restoring old photos. This dataset contains both noisy and original images.
Due to the constraints in dataset size, here we have only uploaded the raw, noisy images of old photos. For the original photo dataset, please refer to DIV2K and CelebA. In addition, this dataset will be continuously updated. Please feel free to contact us via email (haoqingbo4546@163.com) if you have any specific requirements.
DIV2K：https://data.vision.ee.ethz.ch/cvl/DIV2K
CelebA：http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
DOI: 10.17632/n4mccs2zfg.1
title: The reference human induced pluripotent stem cell line KOLF2.1J maintains mitochondrial DNA integrity

description: This data corresponds to a manuscript submitted to eLife with the same title. It includes the results of whole genome sequencing (WGS) analysis on mitochondrial DNA (mtDNA) integrity of the human induced pluripotent stem cell line KOLF2.1J (single nucleotide variant (SNV) calling results). It further includes sequencing data derived from long read nanopore sequencing using a minION and a Flongle adaptor (FASTQ, SNV calling results), and the reuslts of Sanger sequencing targeting a position (m625) of concern (chromatogramms, FASTA files).
DOI: 10.17632/n4mccs2zfg.2
title: Mitochondrial DNA integrity and metabolome profile are preserved in the human induced pluripotent stem cell reference line KOLF2.1J

description: This dataset corresponds to a manuscript submitted to Stem Cell Reports with the same title. 
It includes the files necessary to reproduce the results described in the manuscript:
- GT19-38445_with_p_MT.bam (short-read whole genome sequencing data containing only reads mapped to the mitochondrial DNA)
- KOLF2.1J targeted ONT mtDNA.fastq (long-read targeted mitochondrial DNA sequencing of nine PCR amplicons spanning the entire mitochondrial genome)
- KOLF2.1J WGS ONT.bam (long-read whole genome sequencing data containing only reads mapped to the mitochondrial DNA)
- Jupyter Notebooks containing the code used to reproduce the results: Short-read WGS data processing.ipynb and Short-read WGS data visualization.ipynb; The latter is also used to visualize ONT data (file names need to be changed accordingly)
- The reference used for alignment and a shifted version to account for the artificial breakage point: rCRS.fasta and rCRS_shifted.fasta
- Jupyter Notebook containing code for targeted ONT mitochondrial DNA sequencing variant calling using Mutserve: Targeted ONT seq variant calling.ipynb
-- For analysis of WGS data, the BAM file KOLF2.1J WGS ONT.bam is used and variants are called according to the Targeted ONT seq variant calling.ipynb notebook with adjustment of the calling threshold to 0.01.
- Sanger sequencing results of m625 conspicuous position described in the manuscript: kolf_mt2_rev_mt2_internal_rev.fasta, kolf_mt2_rev_mt2_internal_rev.ab1, kolf_mt2_fwd_mt2_internal_fwd.fasta, kolf_mt2_fwd_mt2_internal_fwd.ab1

Additional information can be found below.
In case of any problems, please contact the authors.