Nuclear pleomorphism in canine cutaneous mast cell tumors: Comparison of reproducibility and prognostic relevance between estimates, manual morphometry, and algorithmic morphometry.

Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics can improve reproducibility, but current manual methods are time-consuming. The aim of this study was to explore the limitations of estimates and develop alternative morphometric solutions for canine cutaneous mast cell tumors (ccMCTs).

Information mismatch in PHH3-assisted mitosis annotation leads to interpretation shifts in H&E slide analysis.

The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker, as it is a measure for tumor cell proliferation. However, the identification of MFs has a known low inter-rater agreement. In a computer-aided setting, deep learning algorithms can help to mitigate this, but they require large amounts of annotated data for training and validation.

A ONECUT1 regulatory, non-coding region in pancreatic development and diabetes.

In a patient with permanent neonatal syndromic diabetes clinically similar to cases with ONECUT1 biallelic mutations, we identified a disease-causing deletion located upstream of ONECUT1. Through genetic, genomic, and functional studies, we identified a crucial regulatory region acting as an enhancer of ONECUT1 specifically during pancreatic development. This enhancer region contains a low-frequency variant showing a strong association with type 2 diabetes and other glycemic traits, thus extending the contribution of this region to common forms of diabetes.

Automated Nuclear Morphometry: A Deep Learning Approach for Prognostication in Canine Pulmonary Carcinoma to Enhance Reproducibility.

The integration of deep learning-based tools into diagnostic workflows is increasingly prevalent due to their efficiency and reproducibility in various settings. We investigated the utility of automated nuclear morphometry for assessing nuclear pleomorphism (NP), a criterion of malignancy in the current grading system in canine pulmonary carcinoma (cPC), and its prognostic implications. We developed a deep learning-based algorithm for evaluating NP (variation in size, i.

What Self-Management Skills Do Turkish Caregivers Have in Caring for People with Dementia? Results of a Qualitative Survey.

Family caregivers can be overwhelmed by the care they provide within the family without external support. The development of self-management skills and the associated ability to actively and responsibly manage one's own health or illness situation therefore plays a vital role in the home care of people living with dementia. As part of an individualized intervention for family caregivers of people of Turkish origin with dementia, existing self-management skills were examined through qualitative interviews to gain insight into health literacy and empowerment in caregiving and in interviewees' own practices to maintain their health.