[A Thyroid Ultrasound Image-based Artificial Intelligence Model for Diagnosis of Central Compartment Lymph Node Metastasis in Papillary Thyroid Carcinoma].

Objective To establish an artificial intelligence model based on B-mode thyroid ultrasound images to predict central compartment lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC). Methods We retrieved the clinical manifestations and ultrasound images of the tumors in 309 patients with surgical histologically confirmed PTC and treated in the First Medical Center of PLA General Hospital from January to December in 2018.The datasets were split into the training set and the test set.We established a deep learning-based computer-aided model for the diagnosis of CLNM in patients with PTC and then evaluated the diagnosis performance of this model with the test set. Result The accuracy,sensitivity,specificity,and area under receiver operating characteristic curve of our model for predicting CLNM were 80%,76%,83%,and 0.794,respectively. Conclusion Deep learning-based radiomics can be applied in predicting CLNM in patients with PTC and provide a basis for therapeutic regimen selection in clinical practice.

Effect of all-trans retinoic acid on casein and fatty acid synthesis in MAC-T cells.

OBJECTIVE: Caseins and fatty acids of milk are synthesized and secreted by the epithelial cells of the mammary gland. All-trans retinoic acid (ATRA), an active metabolite of vitamin A, has been shown to promote mammary development. This study was conducted to determine the effect of ATRA on casein synthesis and fatty acid composition in MAC-T cells. METHODS: MAC-T cells were allowed to differentiate for 4 d, treated with ATRA (0, 1.0, 1.5, and 2.0 µM), and incubated for 3 d. We analyzed the fatty acid composition, the mRNA expression of casein and fatty acid synthesis-related genes, and the phosphorylation of casein synthesis-related proteins of MAC-T cells by gas chromatography, quantitative polymerase chain reaction, and western blotting, respectively. RESULTS: In MAC-T cells, ATRA increased the mRNA levels of αS1-casein and ß-casein, janus kinase 2 (JAK2) and E74-like factor 5 of the signal transducer and activator of transcription 5 ß (STAT5-ß) pathway, ribosomal protein S6 kinase beta-1 (S6K1) and eukaryotic translation initiation factor 4E binding protein 1 of the mammalian target of rapamycin (mTOR) pathway, inhibited the mRNA expression of phosphoinositide 3-kinase and eukaryotic initiation factor 4E of the mTOR pathway, and promoted the phosphorylation of STAT5-ß and S6K1 proteins. Additionally, ATRA increased the de novo synthesis of fatty acids, reduced the content of long-chain fatty acids, the ratio of monounsaturated fatty acids to saturated fatty acids (SFA), the ratio of polyunsaturated fatty acids (PUFA) to SFA, and the ratio of ω-6 to ω-3 PUFA. The mRNA levels of acetyl-CoA carboxylase 1, fatty acid synthase, lipoprotein lipase, stearoyl-CoA desaturase, peroxisome proliferator-activated receptor gamma, and sterol regulatory element-binding protein 1 (SREBP1) were enhanced by ATRA. CONCLUSION: ATRA promotes the synthesis of casein by regulating JAK2/STAT5 pathway and downstream mTOR signaling pathway, and it improves the fatty acid composition of MAC-T cells by regulating SREBP1-related genes.

miR-454 regulates triglyceride synthesis in bovine mammary epithelial cells by targeting PPAR-γ.

Triglycerides account for 99% of milk fat and play a central role in determining dairy product quality. Many factors influence triglyceride synthesis and milk fat secretion. MicroRNAs have been verified to be involved in numerous biological processes, but little is known about their roles in milk fat biosynthesis. In this study, we aim to explore whether miR-454 could regulate triglyceride synthesis in bovine mammary epithelial cells (BMECs) by targeting PPAR-γ. A luciferase reporter assay showed that the predicted target site was correct and that miR-454 and PPAR-γ had a direct interaction. In addition, miR-454 mimics and inhibitors were transfected into BMECs. The results showed that both the mRNA and protein levels of PPAR-γ were negatively correlated with miR-454 expression. Fat droplet accumulation and triglyceride production were also inversely correlated with miR-454 expression. Our results indicate that miR-454 regulates triglyceride synthesis by directly targeting the PPAR-γ 3' UTR in BMECs, suggesting that miR-454 could potentially be a new factor to elevate dairy product quality.