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This page is alzhub.org's plain-English summary of a published study, not the paper itself. It is generated from the record we hold for this study, sourced and linked below — check the original for the full text and methods.

✓ Peer-reviewed alzhub usefulness score 42 out of 100. Laboratory science

Topic: Risk, prevention and care in population studies

Science journalist Charles Piller, working with neuroscientist Matthew Schrag and independent image-forensics experts, published a six-month investigation finding apparent digital manipulation (duplicated bands, spliced images) in Western blot figures from papers by Sylvain Lesné, including his highly influential 2006 Nature paper proposing that a specific amyloid protein (Aβ*56) causes memory loss. The report noted that, 15 years on, few other labs had been able to detect Aβ*56 in human tissue at all. This is documented investigative journalism and forensic image analysis, not a laboratory research study, and it triggered university and journal investigations.

Key findings

Why it matters

Science journalist Charles Piller, working with neuroscientist Matthew Schrag and independent image-forensics experts, published a six-month investigation finding apparent digital manipulation (duplicated bands, spliced images) in Western blot figures from papers by Sylvain Lesné, including his highly influential 2006 Nature paper proposing that a specific amyloid protein (Aβ*56) causes memory loss. The report noted that, 15 years on, few other labs had been able to detect Aβ*56 in human tissue at all.

Study details

Limitations

This is investigative journalism and independent forensic image review, not a peer-reviewed research study or a formal institutional misconduct finding; at the time of publication the allegations were unadjudicated. The subsequent University of Minnesota inquiry reportedly cleared Lesné specifically on the 2006 Nature paper in an initial review even as the paper was later retracted for image manipulation, and investigations into his other papers continued for years afterward — so the full scope of intent versus error was not fully resolved by any single body as of the sources checked.

How this study scored 42/100
How this study's score is builtJournal tier 10 of 10; Journal's citation record left out, no data; Study design 0 of 12; Strength of evidence 3 of 5; Peer-review validation 10 of 10; How recent 3 of 5; Sample size 0 of 4; Effect reported 0 of 3; Studied in people 0 of 3; Randomised / blinded 0 of 2; Times cited left out, no data; Citations per year left out, no data; Impact for its field and year left out, no data; Cited by studies here 0 of 6; Still being cited left out, no data; Senior author's track record left out, no data; Institution's track record left out, no data; Multi-centre collaboration left out, no data; Indexed in PubMed 0 of 2; Free to read left out, no data. 26 of the 62 points it could be judged on, which is 42 of 100. Total 42 of 100.26 of the 62 points we could judge = 42 of 100

Published in a top-tier journal. Scored zero for study design, sample size, effect reported, studied in people, randomised / blinded and indexed in PubMed because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, still being cited, senior author's track record, institution's track record, multi-centre collaboration and free to read, so those were left out: it earned 26 of the 62 points we could judge it on, which is 42 out of 100.

ComponentPointsWhy
Journal tier 10 / 10 Tier 1 — top-tier general journal (Science)
Journal's citation record — / 4 No journal record from OpenAlex — left out of this score
Study design 0 / 12 No study design recorded — scores zero, not guessed (not stated in the record — scored 0)
Strength of evidence 3 / 5 Rated “moderate” in our summary
Peer-review validation 10 / 10 Peer-reviewed. Published as an article in a named peer-reviewed journal.
How recent 3 / 5 2022 — within 6 year(s) of the newest study here
Sample size 0 / 4 Participant count not stated — scores zero (not stated in the record — scored 0)
Effect reported 0 / 3 No effect size reported — scores zero (not stated in the record — scored 0)
Studied in people 0 / 3 Not stated whether this was studied in people — scores zero (not stated in the record — scored 0)
Randomised / blinded 0 / 2 No randomisation or blinding stated — scores zero (not stated in the record — scored 0)
Times cited — / 7 No citation count (not found in OpenAlex) — left out of this score
Citations per year — / 5 No citation count or no year — left out of this score
Impact for its field and year — / 6 No field-weighted citation impact (OpenAlex has none yet) — left out of this score
Cited by studies here 0 / 6 No other study in this library cites it
Still being cited — / 4 No yearly citation counts — left out of this score
Senior author's track record — / 4 Senior author's record not available — left out of this score
Institution's track record — / 3 No institution listed in OpenAlex — left out of this score
Multi-centre collaboration — / 3 Institutions not listed — left out of this score
Indexed in PubMed 0 / 2 No PubMed ID and no DOI — scores zero (not stated in the record — scored 0)
Free to read — / 2 Access not recorded — left out of this score
Points 26 / 62 Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 26 of the 62 points we could judge it on is 42 out of 100.
Total 42 / 100 —

What each of these 20 components measures, and what this score is not →

Read the original

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Cite this study APA, Vancouver, BibTeX · download .bib or .ris

Built from the record alzhub holds for this paper, not looked up. This record has no DOI, so the citation leaves it out. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.

APA 7th

Piller, C. (2022). Blots on a field? Science.

Vancouver

Piller C. Blots on a field? Science. 2022.

BibTeX

@article{piller2022-de5afcd9,
  author  = {Piller, C.},
  title   = {{Blots on a field?}},
  journal = {Science},
  year    = {2022}
}

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