Age-stratified deep learning model for thyroid tumor classification: a multicenter diagnostic study.

Objectives: Thyroid cancer, the only cancer that uses age as a specific predictor of survival, is increasing in incidence, yet it has a low mortality rate, which can lead to overdiagnosis and overtreatment. We developed an age-stratified deep learning (DL) model (hereafter, ASMCNet) for classifying thyroid nodules and aimed to investigate the effect of age stratification on the accuracy of a DL model, exploring how ASMCNet can help radiologists improve diagnostic performance and avoid unnecessary biopsies.

Methods: In this retrospective study, we used ultrasound images from three hospitals, a total of 10,391 images of 5934 patients were used for training, validation, and testing.

High expression of PPM1G is associated with the progression and poor prognosis of hepatocellular carcinoma.

Background: PPM1G, a member of the serine/threonine protease family, dephosphorylates various proteins and may be involved in cancer development. The role and mechanism of PPM1G in HCC still needs to be verified.

Objective: This study aims to explore the role of PPM1G in the occurrence, development and prognosis of HCC.

High Expression of SLC41A3 Correlates with Poor Prognosis in Hepatocellular Carcinoma.

Purpose: SLC41A3 is a member of the solute carrier family 41 (SLC41) and is involved in many cellular processes as a magnesium ion transporter. Although it plays an important role in cancer formation and development, the correlation between the expression of SLC41A3 and the occurrence and prognosis of hepatocellular carcinoma (HCC) remains unclear. Therefore, this study was focused on the evaluation of the relationship between SLC41A3 and the development and prognosis of HCC.

Expression of VAT1 in hepatocellular carcinoma and its clinical significance.

The objective of this study was to investigate the expression of vesicular amine transporter 1 (VAT1) in hepatocellular carcinoma (HCC) and its prognostic value and to analyze the relationship between VAT1 expression and clinicopathological features of HCC. First, several public databases, including Ualcan, GEPIA, and Oncomine, were used to analyze the expression of VAT1 in HCC and normal liver tissue. Next, 330 HCC and 190 normal liver samples were stained by immunohistochemistry and scored.