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Enregistrement W4405060040 · doi:10.22456/1679-9216.134166

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

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

Notice bibliographique

RevueACTA SCIENTIAE VETERINARIAE · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueVeterinary Oncology Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPathologyMammary glandCarcinosarcomaMyoepithelial cellMammary tumorNeoplasmCarcinomaMedicineCancerFibrosarcomaBiologyBreast cancerInternal medicineImmunohistochemistry

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,850
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,036
Tête enseignante GPT0,326
Écart entre enseignants0,290 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2024
Routes d'admission1
Résumé présentoui

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