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Record W3084265728 · doi:10.32718/nvlvet9825

Clinical characteristics of mastocytoma in dogs

2020· article· en· W3084265728 on OpenAlexaboutno aff
B. B. Ivashkiv, A. R. Mysak, В. В. Прицак

Bibliographic record

VenueScientific Messenger of LNU of Veterinary Medicine and Biotechnology · 2020
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMastocytomaBreedMedicinePathologyBiopsyIncidence (geometry)DermatologyBiologyTumor cellsAnimal scienceCancer research

Abstract

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According to foreign researchers, mastocytoma is one of the most common (7-12 %) skin tumors in dogs. This neoplasia is caused by excessive proliferation of mast cells and characterized by a specific clinical course, unpredictable biological behavior and prognosis. Researches of clinical and morphological features of mastocytoma in geographical populations of Ukraine has not only scientific and general biological interest, but also important practical significance. The purpose of the research was to establish the frequency of spreading, the features of the clinical ostent and pathogenesis of cutaneous mastocytoma in dogs in conditions in Lviv and in the suburban zone of the regional center. The research was performed on dogs with skin tumors (n = 128), including 24 of them with mastocytoma, who came to the Department of Surgery and Clinic of Small Pets of Stepan Gzhytskyj LNUVMB during 2016–2020. The diagnosis on mastocytoma was verified by the results of physical examination and cytological examination of biopsy material of neoplasms. It was found that in the structure of oncological diseases of dogs the share of skin neoplasms was 32.16 %. Among animals with skin neoplasms, mastocytoma was diagnosed in 18.75 % of dogs aged 4 to 16 years. The highest incidence rates were found among animals aged 8 to 11 years; the median incidence was 9.5 years and fashion – 9 years. In terms of breeds, cutaneous mastocytoma was found in dogs of the breed: Rottweiler – 16.7 %, Sharpei – 12.5 %, Staffordshire Terrier – 12.5 %, Labrador – 8.3 %, Boxer – 8.3 %, Doberman – 8.3 %, chow-chow – 8.3 %. At the same time, the German Shepherd, Alabai, Spaniel, French Bulldog and Pug cases of the disease were isolated (4.2 %). Among sick animals, dogs accounted for 54.2 % and females for 45.8 %. It was found that in 41.7 % of the studied animals the rate of neoplasia was extremely rapid, because in 56.5 ± 1.91 days the tumors were doubled in size, which is evidence of significant aggressiveness of tumor growth. In 29.2 % of dogs the time of doubling the size of the primary tumor reached 122.1 ± 10.6 days, in 20.8 % of dogs the period of tumor development lasted for two years. In 8.3 % of dogs, the dynamics of neoplasia development is not clear. Sonography has shown that skin mastocytomas are usually visualized as heterogeneous, with uneven edges and fuzzy contours hypoechoic structures. Visualization of solid hypervascular foci with central type of vascularization, on the background of diffuse infiltration of neoplasia in the deeper layers of the skin and subcutaneous tissue, with a pronounced perinodular inflammatory reaction of the surrounding tissues is a sign of malignancy of the mastocytoma. The generalization of the neoplastic process in the internal organs was found, in particular the spleen, may indicate a predominance of the hematogenous route of metastasis of the mastocytoma. The obtained data complement and expand knowledge about the pathogenesis of mastocytoma in dogs, and also highlight the frequency of spreading and course features of this oncological pathology in a separate geographical population of Ukraine.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.165
GPT teacher head0.421
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2020
Admission routes1
Has abstractyes

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Same venueScientific Messenger of LNU of Veterinary Medicine and BiotechnologySame topicVeterinary Oncology ResearchFrench-language works237,207