Purpose: In advanced breast cancer, endocrine therapy is preferred in the absence of visceral crisis. Cyclin-dependent kinase inhibitors (CDKi) are the gold standards. The selection of subsequent treatments after CDKi treatment is still controversial, and the efficacy of everolimus (EVE) combinations is unknown.
View Article and Find Full Text PDFOur aim was to assess the efficacy of adjuvant programmed cell death protein-1 (PD-1) inhibitors and compare the other adjuvant treatments in patients with surgically resected stage III or IV acral melanoma. This study is a multicenter, retrospective analysis. We included 114 patients with stage III or IV acral malignant melanoma who underwent surgery within the past 10 years.
View Article and Find Full Text PDFGoats are of significant economic importance, yet our knowledge of the molecular pathways involved in their pregnancy remains limited. This study aims to investigate the role of IGFs in uterine and ovarian cellular events during pregnancy in goats. Forty-two Hair Goats were examined, including four pregnancy groups representing embryo-positive (G1, n=7), early (G2, n=7), mid (G3, n=7), and late pregnancy (G4, n=7), as well as two luteal stage groups representing early (G5, n=7) and late (G6, n=7) phases.
View Article and Find Full Text PDFBackground: Endometritis is a prevalent and challenging condition that affects livestock, and its effective treatment is the use of intrauterine antibiotics. Antibiotic use may lead to negative consequences, including residue in tissues and the emergence of antibiotic resistance.
Objectives: The aim of this study was to assess the therapeutic potential of ozonated bidistilled water in the treatment of Escherichia coli-induced endometritis in rat models, comparing it to conventional antibiotic treatment.
Glaucoma disease is optic neuropathy; in glaucoma, the optic nerve is damaged because the long duration of intraocular pressure can be caused blindness. Nowadays, deep learning classification algorithms are widely used to diagnose various diseases. However, in general, the training of deep learning algorithms is carried out by traditional gradient-based learning techniques that converge slowly and are highly likely to fall to the local minimum.
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