OSCR

Interactions of LINE-1 ORF1p with proteins and chromatin suggest a role in neuronal physiology.

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] § Materials and Methods › ATAC sequencing and analysis ↔ bin/stats2multiqc.sh, lines 88 to 142 · score 0.67 · deepTools, peak calling, filtered, duplicates, Profiles, mapping · Report a mismatch

Paper

Loaded from Europe PMC by your browser; OSCR does not store it: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

Shell · 143 lines · 5 KB · CECILL-2.1 · 1 match

  1. #!/bin/bash
  3. function usage {
  4. echo -e "usage : stats2multiqc.sh -s SAMPLE_PLAN -d DESIGN -a ALIGNER [-p][-h]"
  5. echo -e "Use option -h|--help for more information"
  6. }
  8. function help {
  9. usage;
  10. echo
  11. echo "stat2multiqc.sh"
  12. echo "---------------"
  13. echo "OPTIONS"
  14. echo
  15. echo " -s SAMPLE_PLAN"
  16. echo " -d DESIGN"
  17. echo " -a ALIGNER"
  18. echo " [-p]: paired-end mode"
  19. echo " [-m]: Mitochondrial chromosome name"
  20. echo " [-h]: help"
  21. exit;
  22. }
  24. is_pe=0
  25. mito_name="chrM"
  26. while getopts "s:d:a:m:ph" OPT
  27. do
  28. case $OPT in
  29. s) splan=$OPTARG;;
  30. d) design=$OPTARG;;
  31. a) aligner=$OPTARG;;
  32. m) mito_name=$OPTARG;;
  33. p) is_pe=1;;
  34. h) help ;;
  35. \?)
  36. echo "Invalid option: -$OPTARG" >&2
  37. usage
  38. exit 1
  39. ;;
  40. :)
  41. echo "Option -$OPTARG requires an argument." >&2
  42. usage
  43. exit 1
  44. ;;
  45. esac
  46. done
  48. if [[ -z $splan ]]; then
  49. usage
  50. exit
  51. fi
  53. all_samples=$(awk -F, '{print $1}' $splan)
  55. echo -e "Sample_ID,Sample_name,Number_of_reads,Number_of_aligned_reads,Percent_of_aligned_reads,Number_of_mito,Percent_of_mito,Number_of_hq_mapped_reads,Percent_of_hq_mapped_reads,Number_of_lq_mapped_reads,Percent_of_lq_mapped_reads,Number_of_duplicates,Percent_of_duplicates,Number_of_usable_reads,Percent_of_usable_reads,TSS_enrichment,Fraction_of_reads_in_peaks" > mqc.stats
  57. for sample in $all_samples
  58. do
  59. #SAMPLE NAME
  60. sname=$(grep "$sample," $splan | awk -F, '{print $2}')
  62. #ALIGNMENT
  63. if [ $aligner == "bowtie2" ]; then
  64. nb_frag=$(grep "reads;" mapping/${sample}_bowtie2.log | sed 's/ .*//')
  65. if [[ $is_pe == 1 ]]; then
  66. nb_reads=$(( $nb_frag * 2 ))
  67. else
  68. nb_reads=$nb_frag
  69. fi
  70. elif [ $aligner == "bwa-mem" ]; then
  71. # bwa.log file is in reads number (not pairs)
  72. nb_reads=$(grep 'Total' mapping/${sample}_bwa.log | awk -F "\t" '{print $2}')
  73. if [[ $is_pe == 1 ]]; then
  74. nb_frag=$(( $nb_reads / 2 ))
  75. else
  76. nb_frag=$nb_reads
  77. fi
  78. tail -n +3 mapping/${sample}_bwa.log > mapping/${sample}_bwa.mqc
  79. elif [ $aligner == "star" ]; then
  80. nb_frag=$(grep "Number of input reads" mapping/${sample}Log.final.out | cut -d"|" -f 2 | sed -e 's/\t//g')
  81. if [[ $is_pe == 1 ]]; then
  82. nb_reads=$(( $nb_frag * 2 ))
  83. else
  84. nb_reads=$nb_frag
  85. fi
  86. fi
  88. #Mapping stats (always in reads - so must be converted for PE)
  89. #These statistics are calculated after spike cleaning but before filtering
  90. nb_mapped=$(awk -F, '$1=="Mapped"{print $2}' mapping/${sample}_mappingstats.mqc)
  91. nb_mapped_hq=$(awk -F, '$1=="HighQual"{print $2}' mapping/${sample}_mappingstats.mqc)
  92. nb_mapped_lq=$(awk -F, '$1=="LowQual"{print $2}' mapping/${sample}_mappingstats.mqc)
  93. perc_mapped=$(echo "${nb_mapped} ${nb_reads}" | awk ' { printf "%.*f",2,$1*100/$2 } ')
  94. perc_mapped_hq=$(echo "${nb_mapped_hq} ${nb_reads}" | awk ' { printf "%.*f",2,$1*100/$2 } ')
  95. perc_mapped_lq=$(echo "${nb_mapped_lq} ${nb_reads}" | awk ' { printf "%.*f",2,$1*100/$2 } ')
  97. ##MITO
  98. if [[ -e mapping/stats/${sample}_raw.idxstats ]]; then
  99. nb_mito=$(awk -v mt=${mito_name} '$1==mt{print $3}' mapping/stats/${sample}_raw.idxstats)
  100. perc_mito=$(echo "${nb_mito} ${nb_mapped}" | awk ' { printf "%.*f",2,$1*100/$2 } ')
  101. else
  102. nb_mito='NA'
  103. perc_mito='NA'
  104. fi
  106. #PICARD
  107. if [[ -e mapping/${sample}.MarkDuplicates.metrics.txt ]]; then
  108. nb_dups_pair=$(grep -a2 "## METRICS" mapping/${sample}.MarkDuplicates.metrics.txt | tail -1 | awk -F"\t" '{print $7}')
  109. nb_dups_single=$(grep -a2 "## METRICS" mapping/${sample}.MarkDuplicates.metrics.txt | tail -1 | awk -F"\t" '{print $6}')
  110. nb_dups_optical=$(grep -a2 "## METRICS" mapping/${sample}.MarkDuplicates.metrics.txt | tail -1 | awk -F"\t" '{print $8}')
  111. nb_dups=$(( $nb_dups_pair * 2 + $nb_dups_single + $nb_dups_optical ))
  112. perc_dups=$(echo "${nb_dups} ${nb_mapped}" | awk ' { printf "%.*f",2,$1*100/$2 } ')
  113. else
  114. nb_dups='NA'
  115. perc_dups='NA'
  116. fi
  118. #Filtered bam
  119. if [[ -e mapping/stats/${sample}_filtered.stats ]]; then
  120. nb_filt=$(grep ^SN mapping/stats/${sample}_filtered.stats | cut -f 2- | grep "reads mapped:" | cut -f 2)
  121. perc_filt=$(echo "${nb_filt} ${nb_mapped}" | awk ' { printf "%.*f",2,$1*100/$2 } ')
  122. fi
  124. #TSS Enrichment
  125. if [[ -e deepTools/${sample}_NFR.plotProfile_corrected.tab ]]; then
  126. tsse=$(awk -F"\t" 'NR==3{mn=mx=$3;for(i=3;i<=NF;i++){if($i>mx){mx=$i}};printf("%.*f",2, mx-mn)}' deepTools/${sample}_NFR.plotProfile_corrected.tab)
  127. else
  128. tsse='NA'
  129. fi
  131. #PeakCalling
  132. if [ -e peakCalling/${sample}_macs2_peaks.FRiP_mqc.tsv ]; then
  133. frip=$(grep "$sample" peakCalling/${sample}_macs2_peaks.FRiP_mqc.tsv | awk '{print $2}')
  134. elif [ -e peakCalling/${sample}_macs2_peaks.FRiP_mqc.tsv ]; then
  135. frip=$(grep "$sample" peakCalling/${sample}_genrich_peaks.FRiP_mqc.tsv | awk '{print $2}')
  136. else
  137. frip='NA'
  138. fi
  140. #To file
  141. echo -e ${sample},${sname},${nb_frag},${nb_mapped},${perc_mapped},${nb_mito},${perc_mito},${nb_mapped_hq},${perc_mapped_hq},${nb_mapped_lq},${perc_mapped_lq},${nb_dups},${perc_dups},${nb_filt},${perc_filt},${tsse},${frip} >> mqc.stats
  142. done

stats2multiqc.sh at commit 1b162c1, under CECILL-2.1 · at the source

Overview

Authors: Sandra Sinnassamy1, Olivia Massiani Beaudoin1, Berangère Lombard2, Damarys Loew2, Tom Bonnifet1, Magali Fradet3, Héloïse Monnet3, Thomas Caille3, Nicolas Servant4, Rajiv L Joshi1, Julia Fuchs1
ORCID iDs: Olivia Massiani Beaudoin, Berangère Lombard, Damarys Loew, Héloïse Monnet, Thomas Caille, Rajiv L Joshi, Julia Fuchs
  1. CIRB, Collège de France, Université PSL, INSERM, CNRS, Paris, France
  2. Institut Curie, Université PSL, CurieCoreTech Mass Spectrometry Proteomics, Paris, France
  3. Orion Technological Core, CIRB, Collège de France, Université PSL, INSERM, CNRS, Paris, France
  4. Institut Curie, INSERM U900, Mines Paris Tech, Université PSL, Paris, France
Institutions: Université Paris Sciences et Lettres (France)
Journal: Life science alliance, volume 9, issue 11, article e202503546
Dates: received 24 October 2025; accepted 10 August 2026; published online 21 August 2026; in print November 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.26508/lsa.202503546 · PMID 42629196 · PMCID PMC13498733 · OpenAlex W7203929265
Open access: gold, a free copy (OpenAlex)
Status: code verified (how the code is found and verified)
Categories: human (organism), mouse (organism), cellular / molecular (subfield)
Methods: Spectral & time-frequency, Statistics
MeSH: Chromatin*, Long Interspersed Nucleotide Elements*, Neurons*, Animals, Cell Nucleus, Cells, Cultured, Gene Expression Regulation, Humans, Mice, Neurites, Protein Binding (* major topic)
Topic: Chromosomal and Genetic Variations (Genetics, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: Agence Nationale de la Recherche (ANR-20-CE16-0022 NEURAGE, ANR-10-EQPX-03, ANR-10-INBS-09-08); Fondation du Collège de France; Institut de France; Fondation Alzheimer; Fédération pour la Recherche sur le Cerveau; SiRIC-Curie program (INCa-DGOS-465, INCa-DGOS-Inserm_12554)
Citations: not cited yet (Europe PMC); 104 references in the paper

Abstract

Retrotransposons are emerging as novel regulators of embryonic and brain development. We recently demonstrated that the LINE-1–encoded protein ORF1p is abundantly expressed in adult mouse and human neurons, although its function remains unclear. Here, we characterize the ORF1p interactome in differentiated mouse and human neurons using mass spectrometry and identify novel partners implicated in gene regulation and neuron-specific processes. ORF1p localizes not only to neuronal nuclei, where it associates with chromatin under steady-state conditions, but also to neurites, supporting a role in neuronal physiology. To further explore its nuclear functions, we sorted human post-mortem neurons with high or low nuclear ORF1p levels and performed ORF1p knockdown in cultured human neurons, followed by chromatin accessibility assays. Both approaches revealed consistent patterns of differential chromatin accessibility dependent on ORF1p. Loss of ORF1p also led to the down-regulation of long, neuron-specific genes and altered neurite morphology. Together, these findings point to a physiological role of ORF1p in post-mitotic neurons, mediated through converging interactions with proteins and chromatin.

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

Repositories

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

orion-cirb/Axon_Skel_Analyzer

License: none: the authors keep all their rights
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: debbd7ca96c6e73d8a48c6c3ae0d404190f3490f, 22 May 2025
Size: 3 files, 0 scripts
Software Heritage: not archived
Found in: the text, “Image analysis”
Holds: README
Not found: license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 27 September 2026: the link answers
  • 27 September 2026: the link answers
1 file
At the source: github.com/orion-cirb/Axon_Skel_Analyzer

bioinfo-pf-curie/atac-seq

License: CECILL-2.1
State: the link answers, verified on 27 September 2026
Evidence: files inventoried
Commit: 1b162c12d313677f8836c657adc3d8ec74c0e94d, 22 October 2021
Languages: Python (6), Shell (2), R (2)
Size: 119 files, 10 scripts
Software Heritage: not archived
Found in: the text, “ATAC sequencing and analysis”
Holds: README, license file, environment (environment.yml, conf/singularity.config, recipes/docker/bedtobigbed.Dockerfile, recipes/docker/bowtie2.Dockerfile, recipes/docker/bwa.Dockerfile, recipes/docker/deeptools.Dockerfile, recipes/docker/fastqc.Dockerfile, recipes/docker/genrich.Dockerfile, recipes/docker/homer.Dockerfile, recipes/docker/macs2.Dockerfile, recipes/docker/multiqc.Dockerfile, recipes/docker/onlyLinux.Dockerfile), documentation
Not found: CITATION.cff, tests, continuous integration
Tools: ggplot2 (2 files), reshape2 (2 files), NumPy (1 file), pandas (1 file), SAMtools (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/bioinfo-pf-curie/ATAC-seq/releases/tag/v1.0.2

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:

  • 2 repositories of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 10 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

Datasets cited

Data Availability

The ATAC-seq and RNA-seq data stemming from human differentiated neurons in culture (LUHMES) are available at EBI-EMBL ArrayExpress database under the following accession numbers: ATAC-seq: E- (https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-MTAB-15871?query=E-MTAB-15871)MTAB-15871 (https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-MTAB-15871?query=E-MTAB-15871) RNA-seq: E- (https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-15856)MTAB-15856 (https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-15856)

The mass spectrometry raw data are available on the PRIDE database with the accession number PXD066047 (https://www.ebi.ac.uk/pride/archive?keyword=PXD066047). The ATAC-seq data stemming from post-mortem human brain tissue are only available upon request from the authors because of privacy and ethical restrictions.

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, 11 authors, 11 MeSH terms, 6 funders, 104 references.

Cite

This paper

Sinnassamy, S., Massiani Beaudoin, O., Lombard, B., Loew, D., Bonnifet, T., Fradet, M., Monnet, H., Caille, T., Servant, N., Joshi, R. L., & Fuchs, J. (2026). Interactions of LINE-1 ORF1p with proteins and chromatin suggest a role in neuronal physiology. Life science alliance, 9(11), e202503546. https://doi.org/10.26508/lsa.202503546

BibTeX

@article{sinnassamy2026interactions,
author = {Sinnassamy, Sandra and Massiani Beaudoin, Olivia and Lombard, Berangère and Loew, Damarys and Bonnifet, Tom and Fradet, Magali and Monnet, Héloïse and Caille, Thomas and Servant, Nicolas and Joshi, Rajiv L and Fuchs, Julia},
title = {{Interactions of LINE-1 ORF1p with proteins and chromatin suggest a role in neuronal physiology}},
journal = {Life science alliance},
year = {2026},
month = aug,
volume = {9},
number = {11},
pages = {e202503546},
publisher = {Life Science Alliance LLC},
issn = {2575-1077},
doi = {10.26508/lsa.202503546},
url = {https://doi.org/10.26508/lsa.202503546},
pmid = {42629196},
pmcid = {PMC13498733}
}

RIS

TY - JOUR
AU - Sinnassamy, Sandra
AU - Massiani Beaudoin, Olivia
AU - Lombard, Berangère
AU - Loew, Damarys
AU - Bonnifet, Tom
AU - Fradet, Magali
AU - Monnet, Héloïse
AU - Caille, Thomas
AU - Servant, Nicolas
AU - Joshi, Rajiv L
AU - Fuchs, Julia
TI - Interactions of LINE-1 ORF1p with proteins and chromatin suggest a role in neuronal physiology
T2 - Life science alliance
J2 - Life Sci Alliance
PY - 2026
DA - 2026/08/21
VL - 9
IS - 11
SP - e202503546
SN - 2575-1077
PB - Life Science Alliance LLC
DO - 10.26508/lsa.202503546
UR - https://doi.org/10.26508/lsa.202503546
LA - en
ER -

CSL-JSON

{
"id": "10.26508/lsa.202503546",
"type": "article-journal",
"title": "Interactions of LINE-1 ORF1p with proteins and chromatin suggest a role in neuronal physiology",
"container-title": "Life science alliance",
"author": [
{
"family": "Sinnassamy",
"given": "Sandra"
},
{
"family": "Massiani Beaudoin",
"given": "Olivia"
},
{
"family": "Lombard",
"given": "Berangère"
},
{
"family": "Loew",
"given": "Damarys"
},
{
"family": "Bonnifet",
"given": "Tom"
},
{
"family": "Fradet",
"given": "Magali"
},
{
"family": "Monnet",
"given": "Héloïse"
},
{
"family": "Caille",
"given": "Thomas"
},
{
"family": "Servant",
"given": "Nicolas"
},
{
"family": "Joshi",
"given": "Rajiv L"
},
{
"family": "Fuchs",
"given": "Julia"
}
],
"container-title-short": "Life Sci Alliance",
"volume": "9",
"issue": "11",
"page": "e202503546",
"DOI": "10.26508/lsa.202503546",
"PMID": "42629196",
"PMCID": "PMC13498733",
"ISSN": "2575-1077",
"publisher": "Life Science Alliance LLC",
"URL": "https://doi.org/10.26508/lsa.202503546",
"language": "en",
"issued": {
"date-parts": [
[
2026,
8,
21
]
]
}
}

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:10.7554/elife.100687 [code]
Steady-state neuron-predominant LINE-1 encoded ORF1p protein and LINE-1 RNA increase with aging in the mouse and human brain.
Journal: eLife
In common: pandas, NumPy, mouse, cellular / molecular, 26 references, 4 authors
[2] doi:10.1016/j.xgen.2025.100979 [code]
LINE-1 retrotransposons mediate cis-acting transcriptional control in human pluripotent stem cells and regulate early brain development.
Journal: Cell genomics
In common: reshape2, ggplot2, pandas, 11 references
[3] doi:10.1093/nar/gkag100 [code]
Loss of SETDB1-mediated H3K9me3 in human neural progenitor cells leads to transcriptional activation of L1 retrotransposons.
Journal: Nucleic acids research
In common: 12 references
[4] doi:10.1007/s00401-024-02835-6
Elevated expression of the retrotransposon LINE-1 drives Alzheimer's disease-associated microglial dysfunction.
Journal: Acta neuropathologica
In common: cellular / molecular, 10 references
[5] doi:10.1038/s41467-024-47985-z [code]
VC-resist glioblastoma cell state: vessel co-option as a key driver of chemoradiation resistance.
Journal: Nature communications
In common: reshape2, ggplot2, pandas, 1 other tool, mouse, cellular / molecular, 4 references, author Damarys Loew
[6] doi:10.1242/dev.202292
Foxg1 bimodally tunes L1-mRNA and -DNA dynamics in the developing murine neocortex.
Journal: Development (Cambridge, England)
In common: mouse, 9 references
[7] doi:10.1101/gr.276451.121
Somatic retrotransposition in the developing rhesus macaque brain.
Journal: Genome research
In common: cellular / molecular, 8 references
[8] doi:10.1126/sciadv.aeg5791 [code]
Retroviral insertions contributed to the divergence of human and chimpanzee brains.
Journal: Science advances
In common: SAMtools, ggplot2, pandas, cellular / molecular, 5 references
[9] doi:10.1093/nar/gkad049 [code]
LINE-1 retrotransposon expression in cancerous, epithelial and neuronal cells revealed by 5' single-cell RNA-Seq.
Journal: Nucleic acids research
In common: reshape2, ggplot2, mouse, cellular / molecular, 5 references
[10] doi:10.1002/jdn.70161 [code]
Spatio-Temporal Dynamics of Macroglial Cell Organization and Proximity to Blood Vessels During Postnatal Development.
Journal: International journal of developmental neuroscience : the official journal of the International Society for Developmental Neuroscience
In common: pandas, NumPy, mouse, 3 references, author Héloïse Monnet

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.

Add the badge to the code's README

OSCR: the badge of this paper

If you are an author or a maintainer of this paper's code, you can add this badge. It says what OSCR knows of the paper (its code, its validated tracing map) and links the code to this page. Paste one of these snippets under the README's title. Keep the two marks around it, so that the badge can be replaced in place and is never added twice. OSCR changes nothing in your repository.

Markdown
<!-- oscr-badge:start -->
[![OSCR](https://openscicode.org/badge/doi/10.26508/lsa.202503546.svg)](https://openscicode.org/badge/doi/10.26508/lsa.202503546)
<!-- oscr-badge:end -->
reStructuredText
.. oscr-badge:start

.. image:: https://openscicode.org/badge/doi/10.26508/lsa.202503546.svg
   :target: https://openscicode.org/badge/doi/10.26508/lsa.202503546
   :alt: OSCR

.. oscr-badge:end
HTML
<!-- oscr-badge:start -->
<a href="https://openscicode.org/badge/doi/10.26508/lsa.202503546"><img src="https://openscicode.org/badge/doi/10.26508/lsa.202503546.svg" alt="OSCR"></a>
<!-- oscr-badge:end -->

On GitHub, open the README, choose Edit (the pencil), paste the snippet under the title, then "Commit changes".

If you choose to, you can have the badge kept up to date for you, with oscr badge --write from the command line or with the GitHub Action in your repository's workflows. Every other form and option (a card, AsciiDoc, LaTeX, shields.io) is on the badge 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: code errors and mismatches between the code and the paper about this paper and its code, from readers and its authors, beside the paper and its tracing map.

Report a mismatch between the code and the paper · Report a code error (signed in)

Reproductions: reports from readers who ran the authors' code and did not get the paper's result, what they ran, with which environment, commit and data.

Report a reproduction failure (signed in)

Versions of its code: the releases of its code tied to a version of this paper (the preprint, the accepted manuscript, the version of record…), each with the tracing map versioned with it.

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