Evidence map›Paper›PMID 17186410›Full record

ArticleVeterinary research communications2007

Immunohistochemical study of phospho-Stat3-ser727 expression in feline mammary gland tumours.

C Petterino, G Podestà, A Ratto, M Drigo, C Pellegrino

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Article in Veterinary research communications, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact, top 92% of its field
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

6 citing papers in PubMed, 10 citations in OpenAlex.

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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

5 authors at 3 institutions in 2 countries.

C PetterinoDepartment of Public Health, Comparative Pathology and Veterinary Hygiene School of Veterinary Medicine, University of Padua, Agripolis, Legnaro. claudio.petterino@unipd.it
G Podestà
A Ratto
M Drigo
C Pellegrino
Laboratoire National de Référence · MAUniversity of Padua · ITIstituto Zooprofilattico Sperimentale del Piemonte Liguria e Valle d'Aosta · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We describe the expression of pStat3-ser727 (signal transducer and activator of transcription 3 phosphorylated on serine 727) in normal, hyperplastic and neoplastic feline mammary gland tissue assessed by immunohistochemistry in 56 cats. The samples included 4 normal mammary non-lactating tissues, 13 hyperplastic lesions (9 lobular and 4 fibroepithelial) and 39 tumours (6 benign and 33 carcinomas). For immunohistochemistry, tissue sections were incubated with anti-pStat3-ser727 monoclonal antibodies and visualized with EnVision-DAB polymer. pStat3-ser727 positivity was quantified in a semi-quantitative manner, differentiating cytoplasmic and nuclear localization. Intense anti-pStat3-ser727 immunoreactivity was detected in epithelial neoplastic cells and in the fibro-component in two fibroepithelial hyperplastic lesions. The immunostaining was dot-like in the cytoplasm and homogeneous in the nuclei in both benign and malignant lesions. Statistically significant relations were observed between nuclear expression of pStat3-ser727 and the pleomorphism score (p = 0.006), mitotic activity (p < 0.0001), and histological grade (p < 0.0001). In contrast, no significant correlations were observed for cytoplasmic pStat3-ser727. These findings add new and interesting information on the potential role of the phosphorylated form of Stat3 in malignant lesions.

Indexed as

AnimalsCarcinomaCat DiseasesCatsFemaleImmunohistochemistryMammary Neoplasms, AnimalPhosphorylationSerineSTAT3 Transcription FactorStatistics, NonparametricSerineSTAT3 Transcription Factor

Identifiers

PMID17186410
OpenAlexW1997253570

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.