OSCR

Neuroprotective response against the onset of ischemic stroke by upregulation of histone H3Y99 sulfation.

Code ↔ Paper

1 match 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 1 match
  1. [1] § STAR★Methods › Method details › Bioinformatic analysis ↔ pRSEM/Param.py, lines 19–97 · score 0.73 · seq peaks, RNA Seq, ChIP, Bowtie, RSEM, quantify

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

Python · 178 lines · 7.3 KB · GPL-3.0 · 1 match

  1. __doc__="""
  3. pliu 20150511
  5. python module for all parameters, input arguments
  6. """
  8. class Param:
  9. IDR_THRESHOLD = 0.05
  10. N_PEAK = 300000
  11. PEAK_TYPE = '-savr'
  12. EXCLUSION_ZONE = '-500:85' ## Anshul recommend -500:85
  13. TRAINING_GENE_MIN_LEN = 1003
  14. TRAINING_MIN_MAPPABILITY = 0.8
  15. FLANKING_WIDTH = 500 ## in nt, flanking region around TSS and TES
  16. INFORMATIVE_DATA_MAX_P_VALUE = 0.01 ## external data set is informative if
  17. ## p-value is not more than this value
  19. def __init__(self):
  20. self.argdict = None
  22. ## has to be in the same naming convention as prsem-calculate-expression
  23. self.num_threads = None
  24. self.chipseq_target_read_files = None
  25. self.chipseq_control_read_files = None
  26. self.chipseq_read_files_multi_targets = None
  27. self.chipseq_bed_files_multi_targets = None
  28. self.cap_stacked_chipseq_reads = None
  29. self.n_max_stacked_chipseq_reads = None
  30. self.bowtie_path = None
  31. self.chipseq_peak_file = None
  32. self.mappability_bigwig_file = None
  33. self.partition_model = None
  34. self.gibbs_burnin = None
  35. self.gibbs_number_of_samples = None
  36. self.gibbs_sampling_gap = None
  37. self.quiet = False
  39. ## arguments
  40. self.ref_fasta = None
  41. self.ref_name = None
  42. self.sample_name = None
  43. self.stat_name = None
  44. self.imd_name = None
  46. ## path and pRSEM scripts
  47. self.temp_dir = None ## dir to save RSEM/pRSEM intermediate files
  48. self.prsem_scr_dir = None ## pRSEM scripts dir
  49. self.prsem_rlib_dir = None ## place to install pRSEM required R libraries
  51. ## genome reference: training set isoforms
  52. self.fall_exon_crd = None
  53. self.fall_tr_crd = None ## tr info + mappability
  54. self.ftraining_tr_crd = None ## training set tr
  56. ## ChIP-seq
  57. self.chipseqexperiment_target = None ## reference to ChIP-seq experiment
  58. self.chipseqexperiment_control = None ## reference to ChIP-seq experiment
  59. self.chipseq_rscript = None ## full name of process-chipseq.R
  60. self.filterSam2Bed = None ## full name of filterSam2Bed binary
  61. self.spp_tgz = None
  62. self.spp_script = None
  63. self.idr_scr_dir = None
  64. self.idr_script = None
  65. self.fgenome_table = None
  66. self.fidr_chipseq_peaks = None
  67. self.fall_chipseq_peaks = None
  68. self.fchipseq_peaks = None ## full name of user supplied ChIP-seq peak
  69. ## file, otherwise is fidr_chipseq_peaks
  70. self.chipseq_target_fraglen = None ## spp-estimated fragment length
  71. self.fsppout_target = None ## full name of SPP output
  72. ## this implementation needs to be refined since
  73. ## the var is define in both Param and ChIPSeqExp
  74. self.fchipseq_target_signals = None
  75. self.fchipseq_control_signals = None
  77. ## transcripts and RNA-seq
  78. self.transcripts = None ## reference to all transcripts to be quantified
  79. self.genes = None ## reference to all genes to be quantified
  81. self.rnaseq_rscript = None ## fullname of R script for dealing RNA-seq
  82. self.fti = None ## RSEM's reference .ti file
  83. self.bigwigsummary_bin = None ## bigWigSummary binary
  84. self.fall_tr_features = None ## file for all isoforms' features
  85. self.fall_tr_prior = None ## file for all isoforms' priors
  86. self.fisoforms_results = None ## file for RSEM .isoforms.results
  87. self.fpvalLL = None ## file for p-value on if informative
  88. ## and for log-likelihood
  89. self.fall_pvalLL = None ## file to store all the p-val and log-likelihood
  91. ## for multiple external data sets
  92. self.targetid2fchipseq_alignment = {}
  93. self.finfo_multi_targets = None
  94. self.flgt_model_multi_targets = None
  96. ## for testing procedure
  97. self.targetids = []
  100. def __str__(self):
  101. ss = [ "%-33s %s\n" % (key, val) for (key, val) in self.argdict.items()] + \
  102. [ "%-33s %s\n" % ('RSEM_temp_dir', self.temp_dir ) ] + \
  103. [ "%-33s %s\n" % ('pRSEM_scr_dir', self.prsem_scr_dir) ]
  104. return ''.join(ss)
  107. @classmethod
  108. def initFromCommandLineArguments(cls, argdict):
  109. import os
  110. prm = cls()
  111. prm.argdict = argdict
  112. for (key, val) in argdict.items():
  113. setattr(prm, key, val)
  115. if prm.imd_name is not None:
  116. prm.temp_dir = os.path.split(prm.imd_name)[0] + '/'
  117. prm.prsem_scr_dir = os.path.dirname(os.path.realpath(__file__)) + '/'
  118. prm.prsem_rlib_dir = prm.prsem_scr_dir + 'RLib/'
  119. if not os.path.exists(prm.prsem_rlib_dir):
  120. os.mkdir(prm.prsem_rlib_dir)
  122. ## genome reference: pRSEM training set isoforms
  123. prm.fall_exon_crd = prm.ref_name + '_prsem.all_exon_crd'
  124. prm.fall_tr_crd = prm.ref_name + '_prsem.all_tr_crd'
  125. prm.ftraining_tr_crd = prm.ref_name + '_prsem.training_tr_crd'
  127. ## ChIP-seq
  128. prm.chipseq_rscript = prm.prsem_scr_dir + 'process-chipseq.R'
  129. prm.filterSam2Bed = prm.prsem_scr_dir + 'filterSam2Bed'
  130. prm.spp_tgz = prm.prsem_scr_dir + 'phantompeakqualtools/spp_1.10.1.tar.gz'
  131. prm.spp_script = prm.prsem_scr_dir + 'phantompeakqualtools/run_spp.R'
  132. prm.idr_scr_dir = prm.prsem_scr_dir + 'idrCode/'
  133. prm.idr_script = prm.idr_scr_dir + 'batch-consistency-analysis.r'
  134. prm.fgenome_table = prm.ref_name + '.chrlist'
  136. if prm.temp_dir is not None:
  137. prm.fsppout_target = prm.temp_dir + 'target_phantom.tab'
  138. prm.fchipseq_target_signals = prm.temp_dir + 'target.tagAlign.gz'
  139. prm.fchipseq_control_signals = prm.temp_dir + 'control.tagAlign.gz'
  140. prm.fidr_chipseq_peaks = "%s/%s" % (prm.temp_dir,
  141. 'idr_target_vs_control.regionPeak.gz')
  142. ## have to name it this way due to run_spp.R's wired naming convention
  143. ## this names depens on the next two names
  144. prm.fall_chipseq_peaks = "%s/%s" % (prm.temp_dir,
  145. 'target.tagAlign_VS_control.tagAlign.regionPeak.gz')
  147. if prm.chipseq_peak_file is not None:
  148. prm.fchipseq_peaks = prm.chipseq_peak_file
  149. else:
  150. prm.fchipseq_peaks = prm.fidr_chipseq_peaks
  153. ## transcripts and RNA-seq
  154. prm.rnaseq_rscript = prm.prsem_scr_dir + 'process-rnaseq.R'
  155. prm.fti = prm.ref_name + '.ti'
  156. prm.ffasta = prm.ref_name + '.transcripts.fa'
  157. prm.bigwigsummary_bin = prm.prsem_scr_dir + 'bigWigSummary'
  158. #prm.fall_exon_crd = prm.imd_name + '_prsem.all_exon_crd'
  159. #prm.fall_tr_crd = prm.imd_name + '_prsem.all_tr_crd'
  160. #prm.ftraining_tr_crd = prm.imd_name + '_prsem.training_tr_crd'
  161. if prm.sample_name is not None: ## for calc-expr
  162. prm.fall_tr_gc = prm.imd_name + '_prsem.all_tr_gc'
  163. prm.fall_tr_features = prm.stat_name + '_prsem.all_tr_features'
  164. prm.fall_tr_prior = prm.stat_name + '_prsem.all_tr_prior'
  165. prm.fpvalLL = prm.stat_name + '_prsem.pval_LL'
  167. prm.fisoforms_results = prm.sample_name + '.isoforms.results'
  168. prm.fall_pvalLL = prm.sample_name + '.all.pval_LL'
  170. ## for multiple external data sets
  171. prm.finfo_multi_targets = prm.temp_dir + 'multi_targets.info'
  172. prm.flgt_model_multi_targets = prm.stat_name + '_prsem.lgt_mdl.RData'
  174. return prm
  177. def initFromCommandLineArguments(argdict):
  178. return Param.initFromCommandLineArguments(argdict)

Param.py at commit 800234e, under GPL-3.0 · at the source

Overview

Authors: Li Jiang1,2, Junchang Xie3,4, Jianfeng Wang1, Yili Yi2, Runxin Zhou3, Dingyuan Guo3, Yu Wang3, Xiao Zeng3, Mingxuan Shi3, Jianing Ding5, Jiadi Wu6, Jun Zhao6, Siyu Feng7, Nan Wang7, Qian Shen4, Yuping Yin5, Mingchang Li1, Yugang Wang3,8
ORCID iDs: Runxin Zhou
  1. Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China
  2. Department of Neurology, The Affiliated Nanhua Hospital, Hengyang Medical College, University of South China, Hengyang, Hunan 421002, China
  3. Department of Biochemistry and Molecular Biology, School of Basic Medicine, Tongji Medical College and State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, Wuhan 430030, Hubei, China
  4. Department of Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
  5. Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, China
  6. Department of Anatomy, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
  7. School of Chemistry and Chemical Engineering and Hubei Key Laboratory of Bioinorganic Chemistry and Materia Medical, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
  8. Cell Architecture Research Center, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
Institutions: Renmin Hospital of Wuhan University (China); University of South China (China); Tongji Hospital (China); Huazhong University of Science and Technology (China); Wuhan Union Hospital (China)
Journal: Cell reports. Medicine, volume 7, issue 3, article 102684
Dates: received 7 May 2025; accepted 13 February 2026; published online 17 March 2026; in print March 2026
Type: Research article · Language: English
License: CC BY-NC
Identifiers: DOI 10.1016/j.xcrm.2026.102684 · PMID 41850229 · PMCID PMC13006531 · OpenAlex W7138007052
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: human (organism), mouse (organism), stroke (population), clinical / translational (subfield)
Methods: Statistics, Connectivity
Keywords: histone sulfation, ischemic stroke, neuroprotective response
MeSH: Brain Ischemia*, Histones*, Ischemic Stroke*, Neuroprotection*, Neuroprotective Agents*, Sulfates*, Up-Regulation*, Animals, Disease Models, Animal, Humans, Infarction, Middle Cerebral Artery, Male, Mice, Mice, Inbred C57BL (* major topic)
Topic: Neuroinflammation and Neurodegeneration Mechanisms (Neurology, Neuroscience), according to OpenAlex
Funding: National Natural Science Foundation of China; Natural Science Foundation of Hunan Province; Key Technologies Research and Development Program
Citations: not cited yet (Europe PMC); 72 references in the paper
Research resources: Sheep anti-SULT1B1 RRID:AB_10571701, RRID:AB_141637, Rabbit anti-PAPSS1 RRID:AB_2159487, Rabbit anti-PAPSS2 RRID:AB_2159498, Goat anti-CD31 RRID:AB_2161028, RRID:AB_2534102, Rabbit anti-Histone H3 RRID:AB_2631273, Rabbit anti-SULT1B1 RRID:AB_2636248, Mouse anti-α-Tubulin RRID:AB_2768341, Rabbit anti-ARG1 RRID:AB_2800207, Rabbit anti-PDK1 RRID:AB_2863629, Mouse anti-PKM2 RRID:AB_2881388, Rabbit anti-CD86 RRID:AB_2892094, Mouse anti-PFKP RRID:AB_2923656, Guinea pig anti-NeuN RRID:AB_2934234, Guinea pig anti-Olig2 RRID:AB_2934243, Guinea pig anti-iba1 RRID:AB_2934253, Guinea pig anti-GFAP RRID:AB_2938933, Donkey anti-Guinea pig IgG, 594nm RRID:AB_3694202, Goat anti-Guinea pig IgG, 488nm RRID:AB_3717497

Abstract

Protective cerebral responses against stresses are fundamental quests of medical science. Here, we report that upregulation of histone sulfation is a protective cerebral response against ischemic injury. Ischemia upregulates the SLC26A1-PAPSS1-SULT1B1 axis, which mediates the transportation of sulfate into cells, conversion of sulfate into PAPS, and catalysis of histone sulfation (H3Y99sulf) using PAPS, respectively. Upregulated H3Y99sulf promotes metabolic genes transcription and glycolysis, sustaining cell survival in ischemic stress. In the mouse model of transient middle cerebral artery occlusion, both PAPSS1 overexpression and sulfate supplementation can boost the neuroprotective H3Y99sulf mechanism, reduce brain injury, and improve neurological functions; disruption of H3Y99sulf exacerbates ischemia-induced brain injury and counteracts the neuroprotective effect of sulfate. Ischemia patients with higher serum sulfate levels are prone to have smaller infarcts, alleviated severity assessments, and better clinical outcomes. This study unearths an undocumented protective cerebral response against ischemia that might be targeted for ischemic stroke treatment.

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

Repository

Its files are read in the Code ↔ Paper reader above, with 1 match between paragraphs and lines of code.

deweylab/RSEM

License: GPL-3.0
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 800234e0d25d16bf7042804604c4371f12b96d9e, 3 August 2026
Languages: C/C++ (180), C (111), C++ (48), Perl (16), Python (11), R (11), Shell (7), Java (1)
Size: 3,057 files, 385 scripts
Software Heritage: not archived
Found in: the resources table
Holds: README, license file, environment (tests/environment.yml, pRSEM/phantompeakqualtools/spp_1.10.1_on_R3.2/DESCRIPTION, pRSEM/phantompeakqualtools/spp_1.10.1_on_R3.3/DESCRIPTION), tests, continuous integration, documentation
Not found: CITATION.cff
Tools: data.table (2 files), STAR (1 file)
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
387 files
At the source: github.com/deweylab/RSEM

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;
  • 385 scripts, each with its path and the digest of its content;
  • 1 match 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 and code availability

The ChIP-seq data and the RNA-seq data reported in this paper have been deposited in the Genome Sequence Archive for Humans (GSA-Human): HRA009597 (https://ncbi.nlm.nih.gov/protein/HRA009597), HRA016220, HRA009627, HRA016257 and are publicly available as of the date of publication. The accession number is listed in the key resources table as well.

This paper does not report original code.

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Reproduced under the paper's license (CC BY-NC), 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, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 18 authors, 3 keywords, 14 MeSH terms, 3 funders, 72 references, 20 RRIDs.

Cite

This paper

Jiang, L., Xie, J., Wang, J., Yi, Y., Zhou, R., Guo, D., Wang, Y., Zeng, X., Shi, M., Ding, J., Wu, J., Zhao, J., Feng, S., Wang, N., Shen, Q., Yin, Y., Li, M., & Wang, Y. (2026). Neuroprotective response against the onset of ischemic stroke by upregulation of histone H3Y99 sulfation. Cell reports. Medicine, 7(3), 102684. https://doi.org/10.1016/j.xcrm.2026.102684

BibTeX

@article{jiang2026neuroprotective,
author = {Jiang, Li and Xie, Junchang and Wang, Jianfeng and Yi, Yili and Zhou, Runxin and Guo, Dingyuan and Wang, Yu and Zeng, Xiao and Shi, Mingxuan and Ding, Jianing and Wu, Jiadi and Zhao, Jun and Feng, Siyu and Wang, Nan and Shen, Qian and Yin, Yuping and Li, Mingchang and Wang, Yugang},
title = {{Neuroprotective response against the onset of ischemic stroke by upregulation of histone H3Y99 sulfation}},
journal = {Cell reports. Medicine},
year = {2026},
month = mar,
volume = {7},
number = {3},
pages = {102684},
publisher = {Elsevier},
issn = {2666-3791},
doi = {10.1016/j.xcrm.2026.102684},
url = {https://doi.org/10.1016/j.xcrm.2026.102684},
pmid = {41850229},
pmcid = {PMC13006531}
}

RIS

TY - JOUR
AU - Jiang, Li
AU - Xie, Junchang
AU - Wang, Jianfeng
AU - Yi, Yili
AU - Zhou, Runxin
AU - Guo, Dingyuan
AU - Wang, Yu
AU - Zeng, Xiao
AU - Shi, Mingxuan
AU - Ding, Jianing
AU - Wu, Jiadi
AU - Zhao, Jun
AU - Feng, Siyu
AU - Wang, Nan
AU - Shen, Qian
AU - Yin, Yuping
AU - Li, Mingchang
AU - Wang, Yugang
TI - Neuroprotective response against the onset of ischemic stroke by upregulation of histone H3Y99 sulfation
T2 - Cell reports. Medicine
J2 - Cell Rep Med
PY - 2026
DA - 2026/03/01
VL - 7
IS - 3
SP - 102684
SN - 2666-3791
PB - Elsevier
DO - 10.1016/j.xcrm.2026.102684
UR - https://doi.org/10.1016/j.xcrm.2026.102684
LA - en
ER -

CSL-JSON

{
"id": "10.1016/j.xcrm.2026.102684",
"type": "article-journal",
"title": "Neuroprotective response against the onset of ischemic stroke by upregulation of histone H3Y99 sulfation",
"container-title": "Cell reports. Medicine",
"author": [
{
"family": "Jiang",
"given": "Li"
},
{
"family": "Xie",
"given": "Junchang"
},
{
"family": "Wang",
"given": "Jianfeng"
},
{
"family": "Yi",
"given": "Yili"
},
{
"family": "Zhou",
"given": "Runxin"
},
{
"family": "Guo",
"given": "Dingyuan"
},
{
"family": "Wang",
"given": "Yu"
},
{
"family": "Zeng",
"given": "Xiao"
},
{
"family": "Shi",
"given": "Mingxuan"
},
{
"family": "Ding",
"given": "Jianing"
},
{
"family": "Wu",
"given": "Jiadi"
},
{
"family": "Zhao",
"given": "Jun"
},
{
"family": "Feng",
"given": "Siyu"
},
{
"family": "Wang",
"given": "Nan"
},
{
"family": "Shen",
"given": "Qian"
},
{
"family": "Yin",
"given": "Yuping"
},
{
"family": "Li",
"given": "Mingchang"
},
{
"family": "Wang",
"given": "Yugang"
}
],
"container-title-short": "Cell Rep Med",
"volume": "7",
"issue": "3",
"page": "102684",
"DOI": "10.1016/j.xcrm.2026.102684",
"PMID": "41850229",
"PMCID": "PMC13006531",
"ISSN": "2666-3791",
"publisher": "Elsevier",
"URL": "https://doi.org/10.1016/j.xcrm.2026.102684",
"language": "en",
"issued": {
"date-parts": [
[
2026,
3,
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:10.1038/s41586-026-10512-9 [code]
Astrocyte glucocorticoid receptor signalling restricts neuronal plasticity.
Journal: Nature
In common: STAR, data.table, mouse, 5 references
[2] doi:10.21203/rs.3.rs-9927928/v1 [code]
Genome-wide and allele-resolved maps of the radial architecture of the mouse genome
Journal: Research Square (preprint)
In common: STAR, data.table, mouse, 4 references
[3] doi:10.1016/j.xhgg.2026.100652 [code]
CRISPR-engineered deletion of POGZ alters transcription factor binding at promoters of genes involved in synaptic signaling.
Journal: HGG advances
In common: STAR, data.table, 4 references
[4] doi:10.1016/j.neuron.2026.01.018 [code]
DCPS modulates TDP-43-linked neurodegeneration through P-body-mediated RNA decay.
Journal: Neuron
In common: STAR, 5 references
[5] doi:10.1038/s41467-026-71803-3 [code]
Charting the transition from in vitro gliogenesis to the in vivo maturation of human glial progenitor cells transplanted into the hypomyelinated mouse brain.
Journal: Nature communications
In common: data.table, mouse, 5 references
[6] doi:10.1016/j.isci.2026.116429 [code]
<i>HMGA2</i> regulates fear and growth: Canine GWAS and functional evidence.
Journal: iScience
In common: STAR, data.table, mouse, 3 references
[7] doi:10.1126/sciadv.aed2952 [code]
Activation of transposable elements is linked to a region- and cell type-specific interferon response in Parkinson's disease.
Journal: Science advances
In common: STAR, data.table, 3 references
[8] 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, data.table, 3 references
[9] doi:10.7554/elife.107393 [code]
Chromosome-scale genome assembly of the European common cuttlefish <i>Sepia officinalis</i>.
Journal: eLife
In common: STAR, data.table, 3 references
[10] doi:10.3389/fimmu.2026.1835359
Perinatal morphine exposure induces chromatin and transcriptomic remodeling to alter immune and metabolic function.
Journal: Frontiers in immunology
In common: mouse, 6 references

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.