OSCR

Rapamycin Partially Reverts Cavernoma Endothelial Cell Phenotype and, When Combined With Lapatinib, Ameliorates Chronic Lesions.

Code ↔ Paper

2 matches between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 2 matches
  1. [1] § Materials and Methods › Bioinformatic Analysis of RNA‐Seq ↔ EXECUTE_ALIGNMENT_AND_QUANTIFICATION.sh, lines 48–87 · score 0.72 · FastQC, strandedness, v0, v1, verified, Genome
  2. [2] § Materials and Methods › Bioinformatic Analysis of RNA‐Seq ↔ EXECUTE_ALIGNMENT_AND_QUANTIFICATION.sh, lines 89–144 · score 0.64 · Seq Poly, adapter, unstranded, Novogene, quality, RNA

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

Shell · 144 lines · 5.4 KB · no license · 2 matches

  1. #############
  2. ## SAMPLES ##
  3. #############
  5. #ID run condition strand
  6. #E15_KO_NT E15_KO_NT_htseq KO_NT Unstranded
  7. #E15_KO_P E15_KO_P_htseq KO_P Unstranded
  8. #E15_KO_R24 E15_KO_R24_htseq KO_R24 Unstranded
  9. #E15_KO_R3 E15_KO_R3_htseq KO_R3 Unstranded
  10. #E15_WT_NT E15_WT_NT_htseq WT_NT Unstranded
  11. #E15_WT_P E15_WT_P_htseq WT_P Unstranded
  12. #E15_WT_R24 E15_WT_R24_htseq WT_R24 Unstranded
  13. #E15_WT_R3 E15_WT_R3_htseq WT_R3 Unstranded
  14. #E29_KO_NT E29_KO_NT_htseq KO_NT Unstranded
  15. #E29_KO_P E29_KO_P_htseq KO_P Unstranded
  16. #E29_KO_R24 E29_KO_R24_htseq KO_R24 Unstranded
  17. #E29_KO_R3 E29_KO_R3_htseq KO_R3 Unstranded
  18. #E29_WT_NT E29_WT_NT_htseq WT_NT Unstranded
  19. #E29_WT_P E29_WT_P_htseq WT_P Unstranded
  20. #E29_WT_R24 E29_WT_R24_htseq WT_R24 Unstranded
  21. #E29_WT_R3 E29_WT_R3_htseq WT_R3 Unstranded
  22. #E31_KO_NT E31_KO_NT_htseq KO_NT Unstranded
  23. #E31_KO_P E31_KO_P_htseq KO_P Unstranded
  24. #E31_KO_R24 E31_KO_R24_htseq KO_R24 Unstranded
  25. #E31_KO_R3 E31_KO_R3_htseq KO_R3 Unstranded
  26. #E31_WT_NT E31_WT_NT_htseq WT_NT Unstranded
  28. # Conda environments:
  29. # STRAND --> how_are_we_stranded_here v1.0.1
  30. # HTSEQ --> htseq-count v0.13.5
  31. # STAR --> STAR v2.7.9a
  33. ####################
  34. ## Create Folders ##
  35. ####################
  37. #mkdir 0.MISCELLANEOUS
  38. #mkdir RESULTS_STAR
  39. #mkdir RESULTS_STAR/NO_FILTERED
  40. #mkdir RESULTS_STAR/FILTERED
  41. #mkdir RESULTS_HTSEQ
  42. #mkdir RESULTS_HTSEQ/NO_FILTERED
  43. #mkdir RESULTS_HTSEQ/FILTERED
  44. #mkdir RESULTS_HTSEQ_REMOVED
  45. #mkdir RESULTS_HTSEQ_REMOVED/NO_FILTERED
  46. #mkdir RESULTS_HTSEQ_REMOVED/FILTERED
  48. #####################################
  49. ######### CHECK STRANDENESS #########
  50. ## how_are_we_stranded_here v1.0.1 ##
  51. #####################################
  53. conda activate STRAND
  55. # Done:
  57. for Sample in E15_KO_NT E15_KO_P E15_KO_R24 E15_KO_R3 E15_WT_NT E15_WT_P E15_WT_R24 E15_WT_R3 E29_KO_NT E29_KO_P E29_KO_R24 E29_KO_R3 E29_WT_NT E29_WT_P E29_WT_R24 E29_WT_R3 E31_KO_NT E31_KO_P E31_KO_R24 E31_KO_R3 E31_WT_NT
  59. do
  61. check_strandedness \
  62. --gtf ./UBUNTU_LAB/DATA/INDEX/MOUSE/STAR/Genome_Mus_musculus_GrcM39_104/Mus_musculus.GRCm39.104.gtf \
  63. --transcripts ./UBUNTU_LAB/DATA/INDEX/MOUSE/STAR/Genome_Mus_musculus_GrcM39_104/GRCm39_STAR_index/Mus_musculus.GRCm39.cdna.all.fa \
  64. --reads_1 ./SAMPLES/NO_FILTERED/"$Sample"/"$Sample"_1.fq.gz \
  65. --reads_2 ./SAMPLES/NO_FILTERED/"$Sample"/"$Sample"_2.fq.gz \
  66. > ./STRAND/"$Sample".txt
  68. done
  70. #########################
  71. ##### Check quality #####
  72. #########################
  73. ##### fqc 0.11.5 ########
  74. #########################
  76. # FastQC (v0.12.1) results previously generated by Novogene and verified locally.
  78. # Done:
  80. #for Sample in E15_KO_NT E15_KO_P E15_KO_R24 E15_KO_R3 E15_WT_NT E15_WT_P E15_WT_R24 E15_WT_R3 E29_KO_NT E29_KO_P E29_KO_R24 E29_KO_R3 E29_WT_NT E29_WT_P E29_WT_R24 E29_WT_R3 E31_KO_NT E31_KO_P E31_KO_R24 E31_KO_R3 E31_WT_NT
  82. #do
  84. # fastqc ./SAMPLES/NO_FILTERED/"$Sample"_1.fastq.gz
  85. # fastqc ./SAMPLES/NO_FILTERED/"$Sample"_2.fastq.gz
  87. #done
  89. ##############################
  90. ## Alignment (STAR 2.7.9a): ##
  91. ##############################
  93. # Star_index GRCm39 --> ./UBUNTU_LAB/DATA/INDEX/MOUSE/STAR/Genome_Mus_musculus_GrcM39_104/GRCm39_STAR_index
  95. # GTF GRCm39 --> ./UBUNTU_LAB/DATA/INDEX/MOUSE/STAR/Genome_Mus_musculus_GrcM39_104/Mus_musculus.GRCm39.104.gtf
  97. ######################
  98. ## Genome alignment ##
  99. ######################
  101. # --runMode: alignReads ==> Type of the run.
  102. # --clip3pAdapterSeq polyA
  103. # --genomeDir: ==> Directory where the genome is established.
  104. # --sjdbGTFfile ==> GTF file.
  105. # --outSAMtype BAM ==> BAM format (output).
  106. # SortedByCoordinate: output sorted by coordinate Aligned.sortedByCoord.out.bam file, similar to samtools sort command.
  107. # Inputs: 2 inputs files.
  109. # FILTERED_NOVOGENE_VERSION:
  111. # Done:
  113. for Sample in E15_KO_NT E15_KO_P E15_KO_R24 E15_KO_R3 E15_WT_NT E15_WT_P E15_WT_R24 E15_WT_R3 E29_KO_NT E29_KO_P E29_KO_R24 E29_KO_R3 E29_WT_NT E29_WT_P E29_WT_R24 E29_WT_R3 E31_KO_NT E31_KO_P E31_KO_R24 E31_KO_R3 E31_WT_NT
  115. do
  117. STAR --runMode alignReads --runThreadN 6 --readFilesCommand zcat --genomeDir ./UBUNTU_LAB/DATA/RNA-SEQ/INDEX/MOUSE/STAR/Genome_Mus_musculus_GrcM39_104/GRCm39_STAR_index --sjdbGTFfile ./UBUNTU_LAB/DATA/RNA-SEQ/INDEX/MOUSE/STAR/Genome_Mus_musculus_GrcM39_104/Mus_musculus.GRCm39.104.gtf --outSAMtype BAM SortedByCoordinate --outFileNamePrefix ./RESULTS_STAR/FILTERED_NOVOGENE/"$Sample"/"$Sample"_ --readFilesIn ./SAMPLES/FILTERED_NOVOGENE/"$Sample"/"$Sample"_1.clean.fq.gz ./SAMPLES/FILTERED_NOVOGENE/"$Sample"/"$Sample"_2.clean.fq.gz
  119. done
  121. # Using Novogene-filtered reads (*.clean.fq.gz), which have already had adapter/low-quality bases removed.
  123. ######################################################
  124. ## Count reads to features (Ensembl -> GRCm39.104): ##
  125. ######################################################
  127. # -s no --> library unstranded (confirmed by how_are_we_stranded_here)
  128. # -a 10 --> minimum alignment quality (MAPQ)
  130. conda activate htseq
  132. # FILTERED_NOVOGENE_VERSION:
  134. # Done:
  136. for Sample in E15_KO_NT E15_KO_P E15_KO_R24 E15_KO_R3 E15_WT_NT E15_WT_P E15_WT_R24 E15_WT_R3 E29_KO_NT E29_KO_P E29_KO_R24 E29_KO_R3 E29_WT_NT E29_WT_P E29_WT_R24 E29_WT_R3 E31_KO_NT E31_KO_P E31_KO_R24 E31_KO_R3 E31_WT_NT
  138. do
  140. htseq-count -a 10 -m intersection-nonempty -i gene_id -f bam -s no -r pos ./RESULTS_STAR/FILTERED_NOVOGENE/"$Sample"/"$Sample"_Aligned.sortedByCoord.out.bam ./UBUNTU_LAB/DATA/RNA-SEQ/INDEX/MOUSE/STAR/Genome_Mus_musculus_GrcM39_104/Mus_musculus.GRCm39.104.gtf > ./RESULTS_HTSEQ/FILTERED_NOVOGENE/"$Sample"/"$Sample"_htseq.txt
  142. done
  144. ##############################################################################################################

EXECUTE_ALIGNMENT_AND_QUANTIFICATION.sh at commit d966f9b, no license · at the source

Overview

Authors: Mar García‐Colomer1, José E. Martínez1, Luis Díaz‐Gómez2, Miriam Sartages1, Eva M. Esquinas‐Román3, Cristina Riobello3, David Martínez‐Delgado1, Diego González‐Pérez3, Aurora Gómez‐Durán3, Miguel Fidalgo1, Marta Varela‐Rey3, Celia M. Pombo1, Juan Zalvide1
ORCID iDs: Mar García‐Colomer, José E. Martínez, Luis Díaz‐Gómez, Miriam Sartages, Eva M. Esquinas‐Román, Cristina Riobello, David Martínez‐Delgado, Diego González‐Pérez, Aurora Gómez‐Durán, Miguel Fidalgo, Marta Varela‐Rey, Celia M. Pombo, Juan Zalvide
  1. Department of Physiology, Centro Singular De Medicina Molecular E Enfermedades Crónicas (CiMUS) and Instituto Sanitario De Santiago De Compostela (IDIS) Universidade De Santiago De Compostela (USC) Santiago de Compostela A Coruña Spain
  2. Department of Pharmacology, Pharmacy, and Pharmaceutical Technology Instituto De Materiales (iMATUS), and Instituto Sanitario De Santiago De Compostela (IDIS), Universidade De Santiago De Compostela Santiago de Compostela A Coruña Spain
  3. Department of Biochemistry and Molecular Biology, Centro Singular De Medicina Molecular E Enfermedades Crónicas (CiMUS) and Instituto Sanitario De Santiago De Compostela (IDIS) Universidade de Santiago de Compostela (USC) Santiago de Compostela A Coruña Spain
Institutions: Universidade de Santiago de Compostela (Spain); Center for Research in Molecular Medicine and Chronic Diseases (Spain); Instituto de Investigación Sanitaria de Santiago (Spain)
Journal: Journal of cellular and molecular medicine, volume 30, issue 13, article e71280
Dates: received 2 March 2026; accepted 26 June 2026; published online 9 July 2026; in print July 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1111/jcmm.71280 · PMID 42427156 · PMCID PMC13351306 · OpenAlex W7167964971
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: genetics / omics (modality), structural MRI / diffusion (modality), mouse (organism), cellular / molecular (subfield)
Methods: Spectral & time-frequency, Statistics, Smoothing, state filtering, decompositions, Connectivity
Keywords: cerebral cavernous malformations, Lapatinib, PDCD10, Propranolol, Rapamycin
MeSH: Endothelial Cells*, Hemangioma, Cavernous, Central Nervous System*, Lapatinib*, Sirolimus*, Animals, Disease Models, Animal, Male, Mice, Mice, Knockout, Phenotype (* major topic)
Topic: Vascular Malformations Diagnosis and Treatment (Neurology, Medicine), according to OpenAlex
Funding: Agencia Estatal de Investigación (PID2021‐123365OB‐I00, PID2020‐119486RB‐100, PID2023‐152685OB‐I00); Consellería de Cultura, Educación e Ordenación Universitaria, Xunta de Galicia (ED431C 2023/10)
Citations: not cited yet (Europe PMC); 56 references in the paper

Abstract

This study investigates the impact of rapamycin and propranolol on cerebral cavernous malformations (CCMs). Employing an unbiased transcriptomic analysis, we aimed to comprehensively elucidate the molecular mechanisms underlying these drug effects. Mouse Brain Microvascular Endothelial Cells (mBMEC) deficient in Ccm3 were treated with propranolol or rapamycin and were analysed by RNA‐seq and immunofluorescence. While propranolol shows limited efficacy in modulating the CCM transcriptomic phenotype in mBMEC, rapamycin demonstrates a significant impact. Rapamycin partially reverses gene expression changes induced by Ccm3 deficiency, restoring KLF2/4‐dependent genes like Nos3, Adamts1, and Thbs1. Notably, we observed a reduction in KLF2 protein levels in Ccm3 KO cells treated with rapamycin. We also sought to determine whether rapamycin, especially in combination with the tyrosine kinase inhibitor lapatinib, which induces proapoptotic gene expression in Ccm3‐deficient endothelium, can reduce lesion volume even after lesion growth has occurred. Ccm3 iEC mice in which cavernoma development had been induced were treated with rapamycin alone or combined with lapatinib, assessing lesion volume using micro‐CT imaging. Notably, a combination of rapamycin and lapatinib effectively reduces lesion volume in a chronic CCM model. In summary, our work reveals a mechanism by which rapamycin modulates Ccm3 KO endothelial cells and identifies rapamycin plus lapatinib as a possible combination therapy for cavernomas.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above, with 2 matches between paragraphs and lines of code.

dvidmd/GSE298723_Differential_Gene_Expression_Analysis_Garcia_Colomer_et_al

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: d966f9be30f3f48b597ef3d4216d0c112a368b9e, 29 October 2025
Languages: R (10), Shell (1)
Size: 17 files, 11 scripts
Software Heritage: not archived
Found in: “Data Availability Statement”
Holds: README, 10 notebooks
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: tidyverse (10 files), ggplot2 (7 files), DESeq2 (5 files), circlize (2 files), ComplexHeatmap (2 files), STAR (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
12 files
At the source: github.com/dvidmd/GSE298723_Differential_Gene_Expression_Analysis_Garcia_Colomer_et_al

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 11 scripts, each with its path and the digest of its content;
  • 2 matches between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data Availability Statement

The RNA‐seq data is available in the NCBI GEO repository (accession GSE298723). RNA‐seq differential expression bioinformatic analysis and figure creation are at https://github.com/dvidmd/GSE298723_Differential_Gene_Expression_Analysis_Garcia_Colomer_et_al.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 13 authors, 5 keywords, 10 MeSH terms, 2 funders, 55 references.

Cite

This paper

García‐Colomer, M., Martínez, J. E., Díaz‐Gómez, L., Sartages, M., Esquinas‐Román, E. M., Riobello, C., Martínez‐Delgado, D., González‐Pérez, D., Gómez‐Durán, A., Fidalgo, M., Varela‐Rey, M., Pombo, C. M., & Zalvide, J. (2026). Rapamycin Partially Reverts Cavernoma Endothelial Cell Phenotype and, When Combined With Lapatinib, Ameliorates Chronic Lesions. Journal of cellular and molecular medicine, 30(13), e71280. https://doi.org/10.1111/jcmm.71280

BibTeX

@article{garciacolomer2026rapamycin,
author = {García‐Colomer, Mar and Martínez, José E. and Díaz‐Gómez, Luis and Sartages, Miriam and Esquinas‐Román, Eva M. and Riobello, Cristina and Martínez‐Delgado, David and González‐Pérez, Diego and Gómez‐Durán, Aurora and Fidalgo, Miguel and Varela‐Rey, Marta and Pombo, Celia M. and Zalvide, Juan},
title = {{Rapamycin Partially Reverts Cavernoma Endothelial Cell Phenotype and, When Combined With Lapatinib, Ameliorates Chronic Lesions}},
journal = {Journal of cellular and molecular medicine},
year = {2026},
month = jul,
volume = {30},
number = {13},
pages = {e71280},
publisher = {Wiley},
issn = {1582-1838},
doi = {10.1111/jcmm.71280},
url = {https://doi.org/10.1111/jcmm.71280},
pmid = {42427156},
pmcid = {PMC13351306}
}

RIS

TY - JOUR
AU - García‐Colomer, Mar
AU - Martínez, José E.
AU - Díaz‐Gómez, Luis
AU - Sartages, Miriam
AU - Esquinas‐Román, Eva M.
AU - Riobello, Cristina
AU - Martínez‐Delgado, David
AU - González‐Pérez, Diego
AU - Gómez‐Durán, Aurora
AU - Fidalgo, Miguel
AU - Varela‐Rey, Marta
AU - Pombo, Celia M.
AU - Zalvide, Juan
TI - Rapamycin Partially Reverts Cavernoma Endothelial Cell Phenotype and, When Combined With Lapatinib, Ameliorates Chronic Lesions
T2 - Journal of cellular and molecular medicine
J2 - J Cell Mol Med
PY - 2026
DA - 2026/07/01
VL - 30
IS - 13
SP - e71280
SN - 1582-1838
PB - Wiley
DO - 10.1111/jcmm.71280
UR - https://doi.org/10.1111/jcmm.71280
LA - en
ER -

CSL-JSON

{
"id": "10.1111/jcmm.71280",
"type": "article-journal",
"title": "Rapamycin Partially Reverts Cavernoma Endothelial Cell Phenotype and, When Combined With Lapatinib, Ameliorates Chronic Lesions",
"container-title": "Journal of cellular and molecular medicine",
"author": [
{
"family": "García‐Colomer",
"given": "Mar"
},
{
"family": "Martínez",
"given": "José E."
},
{
"family": "Díaz‐Gómez",
"given": "Luis"
},
{
"family": "Sartages",
"given": "Miriam"
},
{
"family": "Esquinas‐Román",
"given": "Eva M."
},
{
"family": "Riobello",
"given": "Cristina"
},
{
"family": "Martínez‐Delgado",
"given": "David"
},
{
"family": "González‐Pérez",
"given": "Diego"
},
{
"family": "Gómez‐Durán",
"given": "Aurora"
},
{
"family": "Fidalgo",
"given": "Miguel"
},
{
"family": "Varela‐Rey",
"given": "Marta"
},
{
"family": "Pombo",
"given": "Celia M."
},
{
"family": "Zalvide",
"given": "Juan"
}
],
"container-title-short": "J Cell Mol Med",
"volume": "30",
"issue": "13",
"page": "e71280",
"DOI": "10.1111/jcmm.71280",
"PMID": "42427156",
"PMCID": "PMC13351306",
"ISSN": "1582-1838",
"publisher": "Wiley",
"URL": "https://doi.org/10.1111/jcmm.71280",
"language": "en",
"issued": {
"date-parts": [
[
2026,
7,
1
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1186/s10020-026-01495-4
Identification of the adhesion GPCR ADGRL4/ELTD1 as a novel potential prognostic biomarker for cerebral cavernous malformation disease.
Journal: Molecular medicine (Cambridge, Mass.)
In common: genetics / omics, mouse, 7 references
[2] doi:10.1038/s41467-026-73796-5 [code]
Cross-species transcriptomic analysis of rodent model fidelity to human mesial temporal lobe epilepsy.
Journal: Nature communications
In common: STAR, DESeq2, circlize, 3 other tools, genetics / omics, mouse, cellular / molecular, 1 reference
[3] doi:10.1038/s41386-026-02406-1 [code]
Functional genomic profiling of schizophrenia-associated genes reveals key microglial regulators.
Journal: Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
In common: STAR, DESeq2, circlize, 3 other tools, genetics / omics, cellular / molecular, 1 reference
[4] doi:10.1038/s41586-026-10512-9 [code]
Astrocyte glucocorticoid receptor signalling restricts neuronal plasticity.
Journal: Nature
In common: STAR, DESeq2, circlize, 3 other tools, mouse, cellular / molecular
[5] doi:10.1093/bioinformatics/btag592 [code]
Network-based stratification of allele-specific expression reveals patient subgroups in Huntington's disease.
Journal: Bioinformatics (Oxford, England)
In common: STAR, DESeq2, circlize, 3 other tools, genetics / omics
[6] doi:10.7554/elife.107393 [code]
Chromosome-scale genome assembly of the European common cuttlefish <i>Sepia officinalis</i>.
Journal: eLife
In common: STAR, DESeq2, circlize, 3 other tools, cellular / molecular
[7] doi:10.1038/s41593-026-02367-0 [code]
A reproducible three-dimensional model of human brain tissue to investigate physiological and disease-associated microglia phenotypes.
Journal: Nature neuroscience
In common: DESeq2, circlize, ComplexHeatmap, 2 other tools, cellular / molecular, 2 references
[8] doi:10.1038/s41467-026-71919-6 [code]
Suppression of astrocyte BMP signaling improves molecular signatures and functional deficits in a fragile X syndrome mouse model.
Journal: Nature communications
In common: STAR, DESeq2, ggplot2, 1 other tool, genetics / omics, mouse, cellular / molecular, 2 references
[9] doi:10.1016/j.isci.2026.116439 [code]
Decoding the role of transcriptomic clocks in the human prefrontal cortex.
Journal: iScience
In common: STAR, circlize, ComplexHeatmap, 2 other tools, genetics / omics, 1 reference
[10] doi:10.1016/j.xcrm.2026.102766 [code]
A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma.
Journal: Cell reports. Medicine
In common: DESeq2, circlize, ComplexHeatmap, 2 other tools, genetics / omics, cellular / molecular, 1 reference

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.