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Record W4405060040 · doi:10.22456/1679-9216.134166

Canine Mammary Tumors - Breed, Age and Malignant Characteristics as Risk Factors

2024· article· en· W4405060040 on OpenAlexaboutno aff
Arda Selin Tunç, Sevil Atalay Vural

Bibliographic record

VenueACTA SCIENTIAE VETERINARIAE · 2024
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsPathologyMammary glandCarcinosarcomaMyoepithelial cellMammary tumorNeoplasmCarcinomaMedicineCancerFibrosarcomaBiologyBreast cancerInternal medicineImmunohistochemistry

Abstract

fetched live from OpenAlex

Abstract Background: Canine mammary tumor (CMT) is a benign or malignant neoplasm originating from epithelium, myoepithelium and/or mesenchymal cells of the mammary gland. CMTs are the most often diagnosed neoplasia and age, breed, tumor characterizations as risk factors are important in CMTs. Canine mammary tumors are mostly in the malignant form, not in the benign features. There is a connection between the characters and localizations of the CMT and it frequently occurred in the 3rd, 4th and 5th lobes. These mammary lobes have more malignant characteristics than those in the other lobes, and there is no difference in terms of localization in the right and left lobes This study aimed to identify the variety and the differences occurring of breed, age and tumor characteristics in canine mammary tumors in recent years. Materials, Methods & Results: A total of 165 mammary tumors from 64 bitches were collected and investigated morphologically and histopathologically. The tumors were usually elastic or hard in consistency. The cut surfaces were homogeneous or lobular in appearance and gray-white in color. Most tumors were hard and difficult to cut, so had gray-white bone-like areas on the cut section the histopathological examination of tumors; benign mixed tumor (n = 7), carcinoma in situ (n = 9), simple carcinoma (n = 22), comedocarcinoma (n = 1), mucinous carcinoma (n = 1), carcinosarcoma (n = 114), squamous cell cancer (n = 4), basal cell cancer (n = 1), lipoma (n = 5), fibrosarcoma (n = 1) were diagnosed The formation of CMTs especially malignant tumors was mostly in the 9-12 age range (45.31%). According to the breed of other tumors were distributed as follows: Boxer (n = 15), mongrel (n = 9), German Shepherd (n = 7), Cocker Spaniel (n = 6), Poodle (n = 5), Kangal (n = 4), Rottweiler (n = 2) and Golden Retriever (n = 2), unknown breed (n = 11), Pekingese, Russian Poodle and Labrador retriever (n = 1 each). Half of the cases (50%) were Terrier, and it is followed by the mongrel dogs (12.5%). Malignant CMTs were detected in 95% of Terriers (95/101), while 100% were detected in Cocker Spaniel and Mongrel breeds. Although multiple simultaneous tumors in both the right and left mammary lobes (23/64 = 35.94%), CMTs occurred in the 5th mammary lobe with a rate of 15/64 (23.44%). Benign tumors were noticed less frequently (7.2%) in all mammary tumors, while malignant tumors were much more (92.8%). Of these malignant tumors, 13.3% were simple carcinomas and 69.1% were carcinosarcomas. Out of 64 animals, 23 cases (35.94%) had multiple growths and 41 cases (64.06%) had solitary growths. Lymph node metastases were also detected in 13.16% of them; therefore, benign mixed tumors and carcinosarcomas were excluded from grading for similar reasons, and only simple carcinomas were graded. Since the number of subtypes of simple carcinomas is different from each other and few [tubular type (n = 2), tubulopapillary type (n = 1), papillary type (8) and cystic papillary type (n = 4)], there is no statistically significant difference between the gradings. Discussion: In this study, older age, terrier and mongrel breeds, and medium-sized indicate risk factors for malignancy. Likewise, the occurrence of multiple CMTs should be considered a significant risk factor for the development of malignant mammary tumors. Tumor localization and grading in dogs of various ages and breeds in CMTs were updated and examined in detail in the study. Keywords: bitch, neoplasm, tumor type, grading scores, malignancy, myoepithelial cells, metastases, mammary lobes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.326
Teacher spread0.290 · 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 teacher head, not a consensus.

Study designBench or experimental
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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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