Evidence map›Paper›PMID 40626671›Full record

ArticlePathologica2025

Histological and proteomic characterization of musculoskeletal amyloidomas.

Raffaele Gaeta, Francesco Greco, Federica Anastasi, Lorenzo Andreani, Rodolfo Capanna, Liam A McDonnell, Alessandro Franchi

Abstract readCase Reports
In one paragraph

Article in Pathologica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Raffaele Gaeta *Division of Surgical Pathology, University of Pisa, Pisa, Italy.
Francesco Greco *Fondazione Pisana per la Scienza ONLUS, San Giuliano Terme (PI), Italy.
Federica AnastasiFondazione Pisana per la Scienza ONLUS, San Giuliano Terme (PI), Italy.
Lorenzo AndreaniDepartment of Orthopaedic and Trauma Surgery, University of Pisa, Pisa, Italy.
Rodolfo CapannaDepartment of Orthopaedic and Trauma Surgery, University of Pisa, Pisa, Italy.
Liam A McDonnellFondazione Pisana per la Scienza ONLUS, San Giuliano Terme (PI), Italy.
Alessandro FranchiDepartment of Translational Research and of New Technologies in Medicine and Surgery, University of Pisa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The term amyloidoma applies to localized deposits of amyloid in the absence of systemic amyloidosis. Skeletal and soft tissue amyloidomas are very rare and the pathogenesis is usually associated with lymphoproliferative disorders (plasmacytomas or plasmacytoid lymphomas) or as a consequence of local chronic inflammation. Methods: In this paper we report the histological and immunohistochemical features of four cases of musculoskeletal amyloidoma in association with combined laser capture microdissection (LCM) of Congo Red positive regions with a recent microproteomics workflow that improves the sensitivity of the analysis in order to confirm the nature of the protein deposit. Results: Proteomic techniques allowed to elucidate the nature of the amyloid protein deposit, improving the results obtained by immunohistochemistry (IHC). IHC results were confirmed in two cases while LCM coupled with bottom-up microproteomics was necessary to type the other two cases, for which IHC was inconclusive. Conclusions: In conclusion, proteomic techniques were thus confirmed as a fundamental tool for the complete investigation of protein deposits.

Indexed as

AmyloidosisMusculoskeletal DiseasesProteomicsHumansImmunohistochemistryLaser Capture MicrodissectionamyloidomahistologyimmunohistochemistryLC-MS/MSproteomics

Identifiers

PMID40626671
PMCPMC12236136

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.