Predictive Value of Ultrasound Imaging Characteristics and a BRAF V600E Nomogram for Central Lymph Node Metastasis Risk in Papillary Thyroid Microcarcinoma.

Objective: The objective of this study was to construct and validate a nomogram for preoperatively identifying central lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma (PTMC) using ultrasound imaging characteristics and the BRAF V600E gene mutation. Methods: A retrospective data analysis was conducted on 216 PTMC patients who underwent surgery at our facility between February 2016 and June 2022. Univariate and multivariate analyses examined the relationship between CLNM and clinicopathological traits, the BRAF V600E mutation, and ultrasound imaging characteristics. The area under the curve (AUC) was calculated, and receiver operating characteristic (ROC) curves were constructed to assess the predictive efficacy of the model in both the training and validation sets. Calibration curves were generated to evaluate the agreement between predicted and observed outcomes. Decision curve analysis (DCA) was performed to assess the clinical suitability of the model. A nomogram was developed to illustrate the predicted likelihood of CLNM. Results: The incidence rate of CLNM was found to be 38.4% (83/216 patients). Logistic univariate and multivariate analyses revealed that the BRAF V600E mutation, patient age less than 45 years, tumor size greater than 5 mm, thyroid capsule invasion, and presence of microcalcification in the tumor were independent risk factors for CLNM. The model demonstrated high exclusionary performance with AUC values of 0.88 and 0.877 in the training and validation cohorts, respectively. The calibration curve and DCA confirmed the accuracy of the predicted outcomes and the clinical value of the nomogram. Conclusions: A model incorporating ultrasound imaging characteristics and the BRAF V600E mutation can effectively predict the risk of central lymph node metastasis in patients with papillary thyroid microcarcinoma before surgery. The identified risk factors, including tumor size greater than 5 mm3, BRAF V600E mutation, patient age less than 45 years, nodule capsule invasion, and presence of microcalcification, can aid in surgical decision-making. The nomogram provides a valuable tool for clinicians to assess the likelihood of CLNM in PTMC patients.

Molecular Integrative Analysis of the Inhibitory Effects of Dipeptides on Amyloid ß Peptide 1-42 Polymerization.

The major pathological feature of Alzheimer's disease (AD) is the aggregation of amyloid ß peptide (Aß) in the brain. Inhibition of Aß42 aggregation may prevent the advancement of AD. This study employed molecular dynamics, molecular docking, electron microscopy, circular dichroism, staining of aggregated Aß with ThT, cell viability, and flow cytometry for the detection of reactive oxygen species (ROS) and apoptosis. Aß42 polymerizes into fibrils due to hydrophobic interactions to minimize free energy, adopting a ß-strand structure and forming three hydrophobic areas. Eight dipeptides were screened by molecular docking from a structural database of 20 L-α-amino acids, and the docking was validated by molecular dynamics (MD) analysis of binding stability and interaction potential energy. Among the dipeptides, arginine dipeptide (RR) inhibited Aß42 aggregation the most. The ThT assay and EM revealed that RR reduced Aß42 aggregation, whereas the circular dichroism spectroscopy analysis showed a 62.8% decrease in ß-sheet conformation and a 39.3% increase in random coiling of Aß42 in the presence of RR. RR also significantly reduced the toxicity of Aß42 secreted by SH-SY5Y cells, including cell death, ROS production, and apoptosis. The formation of three hydrophobic regions and polymerization of Aß42 reduced the Gibbs free energy, and RR was the most effective dipeptide at interfering with polymerization.