cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10458941
title: Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping
title: TCGA data with artificial confounding effect

description: TCGA pan-cancer mRNA and DNA data augmented with artificial confounders utilised in "Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping" by Zuqi Li and Sonja Katz (manuscript in preparation).

The following data curation steps were carried out: 



Step 1. Download data from TCGA



R package `TCGAbiolinks`

2547 patients (after step 2) with 6 cancer types:



BRCA (731)

THCA (408)

BLCA (387)

LUSC (297)

HNSC (412)

KIRC (312)



mRNA expression profiles

DNAm expression profiles

Clinical data:



tumor stage: i, ia, ib, ii, iia, iib, iii, iiia, iiib, iiic, iv, iva, ivb, ivc, x

age at diagnosis

race: 'white', 'black or african amarican', 'asian', 'american indian or alaska native'

gender





Step 2. Removal criteria



Patients with



NA or 'not reported' clinical data

race 'american indian or alaska native'

tumor stage x



mRNA and DNAm probes with



0 variance across all included patients

not shared across all cancer types

with missing values





 Step 3. Encode clinical vairables and save datasets



mRNA dataset: 2547 patients x 58,456 mRNAs

DNAm dataset: 2547 patients x 232,088 DNAm

clinic dataset: 2547 patients x 6 variables    1. patient ID    2. tumor stage: 1, 1, 1, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4    3. age at diagnosis    4. race: asian(1), black or african amarican(2), white(3)    5. gender: female(0), male(1)    6. cancer type: BRCA(1), THCA(2), BLCA(3), LUSC(4), HNSC(5), KIRC(6)    



 Step 4. Pre-process the datasets



mRNA dataset: 'TCGA_mRNAs_processed.csv'



Take the 2000 mRNAs with highest variance

Rescale every feature to [0,1]

--> 2547 patients x 2000 mRNAs



DNAm dataset: 'TCGA_DNAm_processed.csv'



Take the 2000 DNAm with highest variance

Rescale every feature to [0,1]

--> 2547 patients x 2000 DNAm



clinic dataset: 'TCGA_clinic.csv'



Step 5. Simulate confounders (instructions can be found in Methods section of manuscript)



Linear confounder:



'TCGA_confounder_linear.csv' - linear confounding classes

'TCGA_DNAm_confounded_linear.csv' - linearly confounded DNAm data

'TCGA_mRNA2_confounded_linear.csv'  - linearly confounded mRNA data



Squared confounder



'TCGA_confounder.csv' - squared confounding classes

'TCGA_DNAm_confounded.csv' - squared confounded DNAm data

'TCGA_mRNA2_confounded.csv'  - squared confounded mRNA data



Categorical confounder 



'TCGA_confounder_categ2.csv' - categorical confounding classes

'TCGA_DNAm_confounded_categ2.csv' - categorically confounded DNAm data

'TCGA_mRNA2_confounded_categ2.csv'  - categorically  confounded mRNA data



Multiple confounders - combined effect (linear + squared + categorical)



'TCGA_confounder_multi.csv' - confounding classes for combined effect

'TCGA_DNAm_confounded_multi.csv' - DNAm data with combined effect

'TCGA_mRNA2_confounded_multi.csv'  - mRNA data with combined effect
DOI: 10.5281/zenodo.10532499
title: Metastable β-Phase Ti–Nb Alloys Fabricated by Powder Metallurgy: Effect of Nb on Superelasticity and Deformation Behavior

description: The data is arranged into 3 folders:

1. SEM folder, which contains the raw SEM images of the microstructure of the materials, fracture surfaces, EDS elemental maps and EBSD analysis

2. TEM folder, which contains the raw TEM images of the sintered materials with the corresponding selected area diffraction (SAED) patterns and dark field (DF) images

3. Mechanical tests folder contains the results of tensile tests and nanoindentation.

Details of all of the above experiments are presented in the reference article.
DOI: 10.5281/zenodo.10532500
title: Metastable β-Phase Ti–Nb Alloys Fabricated by Powder Metallurgy: Effect of Nb on Superelasticity and Deformation Behavior

description: The data is arranged into 3 folders:

1. SEM folder, which contains the raw SEM images of the microstructure of the materials, fracture surfaces, EDS elemental maps and EBSD analysis

2. TEM folder, which contains the raw TEM images of the sintered materials with the corresponding selected area diffraction (SAED) patterns and dark field (DF) images

3. Mechanical tests folder contains the results of tensile tests and nanoindentation.

Details of all of the above experiments are presented in the reference article.
DOI: 10.25405/data.ncl.21931533
title: Data on carrot intake (measured directly or as intake or plasma/serum concentration of alpha-carotene) and cancer incidence from a systematic review and meta-analysis of observational studies

description: These data are the background data for the pre-print of the publication 'Carrot intake is consistently negatively associated with cancer incidence: a systematic review and meta-analysis of prospective observational studies'.
The files contain the data used in the meta-analysis, which corresponds to the pre-print and are also used in subsequent published version(s).
Updated versions of the files correspond to changes during the review and editing process.
One file is the initally extracted data, called 'STUDY COMPREHENSIVE DATA ENTRY SHEET', it contains all the data extracted from each publication.
The other file, called 'FULL DATASET ANALYSED' shows the data that were selected for each analysis and some of the subgroup analyses. In some cases, the total number of data points were different for a subgroup analysis than for the main analysis; this reflected situations where some studies were stratified, e.g. reporting different types of cancer, but representing only one geographical region.
These files supplement the publication and its supplementary data file (also included in the pre-print version) to provide all the relevant data for this study.
Method description is in the publication: https://doi.org/10.1080/10408398.2023.2287176, and the pre-print: https://doi.org/10.2139/ssrn.4316849
<br>
DOI: 10.5281/zenodo.10532773
title: Microtime Machine New

description: Microtime Machine 1.02 Project_new
DOI: 10.5281/zenodo.10532774
title: Microtime Machine New

description: Microtime Machine 1.02 Project_new
DOI: 10.25405/data.ncl.21931533.v1
title: Data on carrot intake (measured directly or as intake or plasma/serum concentration of alpha-carotene) and cancer incidence from a systematic review and meta-analysis of observational studies

description: These data are the background data for the pre-print of the publication 'Carrot intake is consistently negatively associated with cancer incidence: a systematic review and meta-analysis of prospective observational studies'. 
The files contain the data used in the meta-analysis, which corresponds to the pre-print and are also used in subsequent published version(s). 
Updated versions of the files correspond to changes during the review and editing process. 
One file is the initally extracted data, called 'STUDY COMPREHENSIVE DATA ENTRY SHEET', it contains all the data extracted from each publication.
The other file, called 'FULL DATASET ANALYSED' shows the data that were selected for each analysis and some of the subgroup analyses. In some cases, the total number of data points were different for a subgroup analysis than for the main analysis; this reflected situations where some studies were stratified, e.g. reporting different types of cancer, but representing only one geographical region.
These files supplement the publication and its supplementary data file (also included in the pre-print version) to provide all the relevant data for this study.
Method description is in the publication, including the pre-print: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4316849
<br>
DOI: 10.25405/data.ncl.21931533.v2
title: Data on carrot intake (measured directly or as intake or plasma/serum concentration of alpha-carotene) and cancer incidence from a systematic review and meta-analysis of observational studies

description: These data are the background data for the pre-print of the publication 'Carrot intake is consistently negatively associated with cancer incidence: a systematic review and meta-analysis of prospective observational studies'.
The files contain the data used in the meta-analysis, which corresponds to the pre-print and are also used in subsequent published version(s).
Updated versions of the files correspond to changes during the review and editing process.
One file is the initally extracted data, called 'STUDY COMPREHENSIVE DATA ENTRY SHEET', it contains all the data extracted from each publication.
The other file, called 'FULL DATASET ANALYSED' shows the data that were selected for each analysis and some of the subgroup analyses. In some cases, the total number of data points were different for a subgroup analysis than for the main analysis; this reflected situations where some studies were stratified, e.g. reporting different types of cancer, but representing only one geographical region.
These files supplement the publication and its supplementary data file (also included in the pre-print version) to provide all the relevant data for this study.
Method description is in the publication: https://doi.org/10.1080/10408398.2023.2287176, and the pre-print: https://doi.org/10.2139/ssrn.4316849
<br>
DOI: 10.15161/oar.it/143346
title: Carta Geologica d'Italia alla scala 1:50.000, F. 652 Capo Passero

description: Foglio geologico alla scala 1:50.000 basato su rilevamenti alla scala 1:10.000 e 1:25000 comprensivo di legenda, schemi a cornice, sezioni geologiche.
DOI: 10.15161/oar.it/143347
title: Carta Geologica d'Italia alla scala 1:50.000, F. 652 Capo Passero

description: Foglio geologico alla scala 1:50.000 basato su rilevamenti alla scala 1:10.000 e 1:25000 comprensivo di legenda, schemi a cornice, sezioni geologiche.
DOI: 10.5281/zenodo.10532633
title: Galileo INAV data for OSNMA public key revocation exercise in December 2023

description: This dataset contains the Galileo INAV data received between 2023-12-12 and 2023-12-15 by a GNSS receiver located in Madrid, Spain. This data contains the Galileo OSNMA public key revocation exercise that was done on 2023-12-13. The data is formatted using the protobuf wire format used by Galmon.
DOI: 10.5281/zenodo.10532634
title: Galileo INAV data for OSNMA public key revocation exercise in December 2023

description: This dataset contains the Galileo INAV data received between 2023-12-12 and 2023-12-15 by a GNSS receiver located in Madrid, Spain. This data contains the Galileo OSNMA public key revocation exercise that was done on 2023-12-13. The data is formatted using the protobuf wire format used by Galmon.
DOI: 10.5281/zenodo.10531881
title: Exploration of magnon-magnon coupling in an antidot lattice: The role of non-uniform magnetization texture

description: Data for "Exploration of magnon-magnon coupling in an antidot lattice: The role of non-uniform magnetization texture"

Due to the substantial volume of data, this repository contains only the source files for the simulations and the Python code to recreate the figures.

To reproduce the data:



Install our fork of MuMax3 called Amumax: https://github.com/MathieuMoalic/amumax

Run all .mx3 files ( around 40 minutes per simulations on a 3080ti, there are 2030 mx3 files to run,  ~1350 hours total, ~3TB )

Install python dependencies from requirements.txt

Using our post-processing python library `pyzfn`, calculate the spin-wave spectra for each simulation.

Run the fig*.py to generate the figures.


The research has received funding from the National Science Centre of Poland, Grant No. UMO–2020/37/B/ST3/03936 and 2023/49/N/ST3/03538. The simulations were partially performed at the Poznan Supercomputing and Networking Center (Grant No. 398).
DOI: 10.5281/zenodo.10531882
title: Exploration of magnon-magnon coupling in an antidot lattice: The role of non-uniform magnetization texture

description: Data for "Exploration of magnon-magnon coupling in an antidot lattice: The role of non-uniform magnetization texture"

Due to the substantial volume of data, this repository contains only the source files for the simulations and the Python code to recreate the figures.

To reproduce the data:



Install our fork of MuMax3 called Amumax: https://github.com/MathieuMoalic/amumax

Run all .mx3 files ( around 40 minutes per simulations on a 3080ti, there are 2030 mx3 files to run,  ~1350 hours total, ~3TB )

Install python dependencies from requirements.txt

Using our post-processing python library `pyzfn`, calculate the spin-wave spectra for each simulation.

Run the fig*.py to generate the figures.


The research has received funding from the National Science Centre of Poland, Grant No. UMO–2020/37/B/ST3/03936 and 2023/49/N/ST3/03538. The simulations were partially performed at the Poznan Supercomputing and Networking Center (Grant No. 398).
DOI: 10.5281/zenodo.10532625
title: Reducing greenhouse gas emissions uncertainties for chemical production

description: This dataset accompanies the paper: Cullen, L, Meng, F., Lupton, R., Cullen, J. (2023). Reducing greenhouse gas emissions uncertainties for chemical production. (under consideration).



countryEF files contain estimated emissions intensity factors for yearly production from countries with columns for each year and associated uncertainties. These are broken down by emissions sources as explained in the paper and a total EF row is provided. 


 



processEF files contain calculated emissions intensity factors for each process considered in the study and their associated uncertainties from each emissions source. Mass allocation files are complete. Energy and economic allocation values are provided where possible, please refer to methods section of the paper.
DOI: 10.5281/zenodo.10532626
title: Reducing greenhouse gas emissions uncertainties for chemical production

description: This dataset accompanies the paper: Cullen, L, Meng, F., Lupton, R., Cullen, J. (2023). Reducing greenhouse gas emissions uncertainties for chemical production. (under consideration).



countryEF files contain estimated emissions intensity factors for yearly production from countries with columns for each year and associated uncertainties. These are broken down by emissions sources as explained in the paper and a total EF row is provided. 


 



processEF files contain calculated emissions intensity factors for each process considered in the study and their associated uncertainties from each emissions source. Mass allocation files are complete. Energy and economic allocation values are provided where possible, please refer to methods section of the paper.
DOI: 10.5281/zenodo.10532729
title: Dataset related to article "Oligometastatic Prostate Cancer Treated with Stereotactic Body Radiation Therapy: The Role of Three-Dimensional Tumour Volume in Patient Survival"

description: This record contains raw data related to article “Oligometastatic Prostate Cancer Treated with Stereotactic Body Radiation Therapy: The Role of Three-Dimensional Tumour Volume in Patient Survival"

Abstract



 Aims:  The definition of oligometastatic prostate cancer (OPCa) is currently based solely on the maximum number of detectable metastases, as there are no validated biomarkers available. The aim of this study was to identify novel predictive factors for OPCa patients who underwent metastases-directed therapy.

 Materials and methods:  This monocentre, retrospective study included consecutive OPCa patients with a maximum of five metastases in up to two organs, detected with choline- or PSMA-positron emission tomography, who were treated with metastases-directed stereotactic body radiation therapy. Endpoints were overall survival and progression-free survival, assessed with Kaplan-Meier analysis. Univariate and multivariable Cox regression was carried out to evaluate the association between clinical factors and survival outcomes.

 Results:  Between 2009 and 2021, 163 patients and 320 metastases were treated with 226 stereotactic body radiation therapy courses. The median three-dimensional metastatic tumour volume was 4.1 cm3, with a range from 0.01 to 233.4 cm3. In total, 87 (53.4%), 21 (12.9%) and 55 (33.7%) metastases were classified as cN1, cM1a and cM1b, respectively. The median follow-up was 28.5 months. The rates of overall survival at 1, 3 and 5 years were 89.5% (95% confidence interval 83.4-93.4), 74.9% (95% confidence interval 66.1-81.7) and 57.2% (95% confidence interval 45.8-67.1), respectively. Multivariable analysis showed that overall survival reduced with the increase in three-dimensional total tumour volume (hazard ratio 1.93, 95% confidence interval 1.06-3.52; P = 0.030) and confirmed a significant difference between cN1 versus cM1a-b disease (hazard ratio 1.81, 95% confidence interval 1.01-3.25; P = 0.046). The cut-off value of total volume correlated with the highest risk of death was 20 cm3 (hazard ratio 2.37, 95% confidence interval 1.34-4.18; P = 0.003). The median progression-free survival was 17.8 months, with 1-, 3- and 5-year rates of 63.7% (95% confidence interval 55.4-70.9), 31.5% (95% confidence interval 22.8-40.6) and 24.7% (95% confidence interval 16.0-34.3).

 Conclusions:  This study identified three-dimensional total tumour volume and the site of oligometastases as significant predictors of survival in OPCa patients treated with metastases-directed therapy. These parameters can potentially be used to personalised treatment and improve patient outcome.
DOI: 10.5281/zenodo.10532730
title: Dataset related to article "Oligometastatic Prostate Cancer Treated with Stereotactic Body Radiation Therapy: The Role of Three-Dimensional Tumour Volume in Patient Survival"

description: This record contains raw data related to article “Oligometastatic Prostate Cancer Treated with Stereotactic Body Radiation Therapy: The Role of Three-Dimensional Tumour Volume in Patient Survival"

Abstract



 Aims:  The definition of oligometastatic prostate cancer (OPCa) is currently based solely on the maximum number of detectable metastases, as there are no validated biomarkers available. The aim of this study was to identify novel predictive factors for OPCa patients who underwent metastases-directed therapy.

 Materials and methods:  This monocentre, retrospective study included consecutive OPCa patients with a maximum of five metastases in up to two organs, detected with choline- or PSMA-positron emission tomography, who were treated with metastases-directed stereotactic body radiation therapy. Endpoints were overall survival and progression-free survival, assessed with Kaplan-Meier analysis. Univariate and multivariable Cox regression was carried out to evaluate the association between clinical factors and survival outcomes.

 Results:  Between 2009 and 2021, 163 patients and 320 metastases were treated with 226 stereotactic body radiation therapy courses. The median three-dimensional metastatic tumour volume was 4.1 cm3, with a range from 0.01 to 233.4 cm3. In total, 87 (53.4%), 21 (12.9%) and 55 (33.7%) metastases were classified as cN1, cM1a and cM1b, respectively. The median follow-up was 28.5 months. The rates of overall survival at 1, 3 and 5 years were 89.5% (95% confidence interval 83.4-93.4), 74.9% (95% confidence interval 66.1-81.7) and 57.2% (95% confidence interval 45.8-67.1), respectively. Multivariable analysis showed that overall survival reduced with the increase in three-dimensional total tumour volume (hazard ratio 1.93, 95% confidence interval 1.06-3.52; P = 0.030) and confirmed a significant difference between cN1 versus cM1a-b disease (hazard ratio 1.81, 95% confidence interval 1.01-3.25; P = 0.046). The cut-off value of total volume correlated with the highest risk of death was 20 cm3 (hazard ratio 2.37, 95% confidence interval 1.34-4.18; P = 0.003). The median progression-free survival was 17.8 months, with 1-, 3- and 5-year rates of 63.7% (95% confidence interval 55.4-70.9), 31.5% (95% confidence interval 22.8-40.6) and 24.7% (95% confidence interval 16.0-34.3).

 Conclusions:  This study identified three-dimensional total tumour volume and the site of oligometastases as significant predictors of survival in OPCa patients treated with metastases-directed therapy. These parameters can potentially be used to personalised treatment and improve patient outcome.
DOI: 10.6084/m9.figshare.23559837
title: Data from: "Uniform carbon reserve dynamics along the vertical light gradient in mature tree crowns".

description: The files contain the NSC data (NSC.xlsx), the measurements used for fitting the light response curves (LRC.xlsx) and the specific leaf area values (SLA.xlsx) as reported in:Zahnd C, Zehnder M, Arend M, Kahmen A, Hoch G 2024. Uniform carbon reserve dynamics along the vertical light gradient in mature tree crowns. Tree Physiology, tpae005. https://doi.org/10.1093/treephys/tpae005Please refer to the metadata sheets within each file, and to the original publication (https://doi.org/10.1093/treephys/tpae005) for details on the data collection.
DOI: 10.6084/m9.figshare.25027805
title: Supplementary Material for: The role of multiparametric MRI (mpMRI) in the prediction of adverse prostate cancer pathology in radical prostatectomy specimen

description: Introduction: 
Prostate cancer (PCa) risk stratification is essential in guiding therapeutic decision. Multiparametric magnetic resonance tomography (mpMRI) holds promise in prediction of adverse pathologies (AP) after prostatectomy (RP). This study aims to identify clinical and imaging markers in the prediction of adverse pathology.

Methods:
Patients with PCa, diagnosed by targeted biopsy after mpMRI and undergoing RP were included. The predictive accuracy of mpMRI for extraprostatic extension (ECE), seminal vesicle infiltration (SVI) and lymph node positivity was calculated from the final histopathology.

Results: 
846 patients were involved. Independent risk parameters include imaging findings as ECE (OR 3.12), SVI (OR 2.55) and PI-RADS scoring (4: OR 2.01 and 5: OR 4.34). mpMRI parameters such as ECE, SVI and lymph node metastases showed a high prognostic accuracy (73.28% vs. 95.35% vs. 93.38%) with moderate sensitivity compared to the final histopathology. The ROC-analysis of our combined scoring system (D’Amico classification, PSA density and MRI risk factors) improves prediction of adverse pathology (AUC 0.73 vs. 0.69). 

Conclusion:
Our study supports the use of mpMRI for comprehensive pre-treatment risk assessment in PCa. Due to the high accuracy of factors like ECE, SVI and PI-RADS scoring, utilizing mpMRI data enabled accurate prediction of unfavourable pathology after RP.
DOI: 10.7488/ds/3800
title: SUPERSEDED - Rapid Evolution of Colistin Resistance in a Bioreactor Model of Infection of Klebsiella pneumoniae

description: ## SUPERSEDED - This item has been replaced by the one which can be found at https://datashare.ed.ac.uk/handle/10283/8712 ## .Colistin resistance remains an important antibiotic for the therapeutic management of drug-resistant Klebsiella pneumoniae. Despite the numerous reports of colistin resistance in clinical strains, it remains unclear exactly when and how different mutational events arise resulting in reduced colistin susceptibility. Using a bioreactor model of infection, we modelled the emergence of colistin resistance in a susceptible isolate of K. pneumoniae. Genotypic, phenotypic and mathematical analyses of the antibiotic challenged and un-challenged population indicates that after an initial decline, the population recovers within 24h due to a small number of “founder cells” which have single point mutations mainly in the regulatory genes encoding crrB and pmrB and whose phenotype exhibits colistin MICs up to 100-fold higher than the parental strain. Our work underlines that development of colistin resistance during treatment of susceptible K. pneumoniae infections is readily achieved having implications for the use of cationic antimicrobial peptides as a monotherapy. The dataset is related to the paper 'Rapid Evolution of Colistin Resistance in a Bioreactor Model of Infection of Klebsiella pneumoniae' (https://doi.org/10.1101/2022.10.03.510619).
DOI: 10.5281/zenodo.10048092
title: Supplemental Material for Context Switch Sensitive Fault Localization