Development and validation of machine learning models for predicting lung metastasis risk in differentiated thyroid cancer based on two databases.

Background: Differentiated thyroid cancer (DTC) progresses slowly, but patients with lung metastasis (LM) have a poor prognosis. The aim of this study was to develop and evaluate the predictive ability of machine learning (ML) models in estimating the risk of LM in patients with DTC and to identify the independent risk factors specific to different age and gender subgroups.

Methods: The demographic and clinicopathological data of patients with DTC were obtained from two databases: firstly, the National Institutes of Health Surveillance, Epidemiology, and End Results (SEER) database [2010-2015], which provides extensive epidemiological and clinical information on cancer patients; secondly, the Zhangzhou Municipal Hospital Affiliated to Fujian Medical University [2014-2017], which focuses more on patients' specific clinicopathological characteristics and treatment outcomes.

Central control of dynamic gene circuits governs T cell rest and activation.

The ability of cells to maintain distinct identities and respond to transient environmental signals requires tightly controlled regulation of gene networks. These dynamic regulatory circuits that respond to extracellular cues in primary human cells remain poorly defined. The need for context-dependent regulation is prominent in T cells, where distinct lineages must respond to diverse signals to mount effective immune responses and maintain homeostasis.

Ultrasound evaluation and grading of neuromuscular disease in lower extremities among diabetic patients.

Objective: To explore the clinical utility of ultrasound in evaluating and grading neuromuscular diseases in the lower extremities of patients with diabetes mellitus.

Methods: A total of 126 inpatients from the Department of Diabetes at Zhangzhou Affiliated Hospital of Fujian Medical University, China, were recruited from June 2020 to December 2022. The cohort included 69 patients with type 2 diabetes mellitus (T2DM) and diabetic peripheral neuropathy (DPN group) and 57 patients with T2DM but without DPN (non-DPN group).

Diagnosis of cervical lymphoma using a YOLO-v7-based model with transfer learning.

To investigate the ability of an auxiliary diagnostic model based on the YOLO-v7-based model in the classification of cervical lymphadenopathy images and compare its performance against qualitative visual evaluation by experienced radiologists. Three types of lymph nodes were sampled randomly but not uniformly. The dataset was randomly divided into for training, validation, and testing.

Ultrasound combined with Ki-67 to construct the prognostic model for radioactive iodine therapy outcomes in Graves' disease patients.

The aim of this study was to develop a prognostic model for radioactive iodine (RAI) therapy outcome in patients with Graves' disease. We enrolled 127 patients. Information on RAI therapy, ultrasound indexes of thyroid, and other lifestyle factors was collected.

Prediction of papillary thyroid metastases to the central compartment: proposal of a model taking into consideration other thyroid conditions.

Objective: To construct risk prediction models for cervical lymph node metastasis (CLNM) of papillary thyroid carcinoma (PTC) under different thyroid disease backgrounds and to analyze and compare risk factors among different groups.

Methods: This retrospective study included 518 patients with PTC that was pathologically confirmed post-operatively from January 2021 to November 2021. Demographic, ultrasound and pathological data were recorded.

Endothelial cells are a key target of IFN-g during response to combined PD-1/CTLA-4 ICB treatment in a mouse model of bladder cancer.

To explore mechanisms of response to combined PD-1/CTLA-4 immune checkpoint blockade (ICB) treatment in individual cell types, we generated scRNA-seq using a mouse model of invasive urothelial carcinoma with three conditions: untreated tumor, treated tumor, and tumor treated after CD4 T cell depletion. After classifying tumor cells based on detection of somatic variants and assigning non-tumor cell types using SingleR, we performed differential expression analysis, overrepresentation analysis, and gene set enrichment analysis (GSEA) within each cell type. GSEA revealed that endothelial cells were enriched for upregulated IFN-g response genes when comparing treated cells to both untreated cells and cells treated after CD4 T cell depletion.

Establishment and comparison of piecewise linear regression models to measure thyroid volume by 2D and 3D ultrasound.

Objective: Compared thyroid volumes measured by 2-D and 3-D US with those of resected specimens and proposed new models to improve measurement accuracy.

Methods: This study included 80 patients who underwent total thyroidectomy. One 2D_model and one 3D_model were developed using piecewise linear regression analysis.

Development, Validation, and Comparison of 2 Ultrasound Feature-Guided Machine Learning Models to Distinguish Cervical Lymphadenopathy.

The objective of this study is to develop and validate the performance of 2 ultrasound (US) feature-guided machine learning models in distinguishing cervical lymphadenopathy. We enrolled 705 patients whose US characteristics of lymph nodes were collected at our hospital. B-mode US and color Doppler US features of cervical lymph nodes in both cohorts were analyzed by 2 radiologists.

Endothelial cells are a key target of IFN-g during response to combined PD-1/CTLA-4 ICB treatment in a mouse model of bladder cancer.

To explore mechanisms of response to combined PD-1/CTLA-4 immune checkpoint blockade (ICB) treatment in individual cell types, we generated scRNA-seq using a mouse model of invasive urothelial carcinoma with three conditions: untreated tumor, treated tumor, and tumor treated after CD4+ T cell depletion. After classifying tumor cells based on detection of somatic variants and assigning non-tumor cell types using SingleR, we performed differential expression analysis, overrepresentation analysis, and gene set enrichment analysis (GSEA) within each cell type. GSEA revealed that endothelial cells were enriched for upregulated IFN-g response genes when comparing treated cells to both untreated cells and cells treated after CD4+ T cell depletion.

Calcification, Posterior Acoustic, and Blood Flow: Ultrasonic Characteristics of Triple-Negative Breast Cancer.

Previous studies suggest that triple-negative breast cancer (TNBC) may have unique imaging characteristics, however, studies focused on the imaging characteristics of TNBC are still limited. The aim of the present study is to analyze the ultrasonic characteristics of TNBC and to provide more reliable information on imaging diagnosis of TNBC. This retrospective study was performed including 162 TNBC patients with 184 TNBC lesions.

Circulating microRNA: Myocardium-derived prenatal biomarker of ventricular septal defects.

Recently, circulating microRNAs (miRNAs) from maternal blood and amniotic fluid have been used as biomarkers for ventricular septal defect (VSD) diagnosis. However, whether circulating miRNAs are associated with fetal myocardium remains unknown. Dimethadione (DMO) induced a VSD rat model.

Applications of Mechanical Arm in the Virtual Touch Tissue Imaging Quantification and the Differential Diagnosis of Breast Tumors.

To assess the diagnostic performance of quantitative parameters for virtual touch tissue imaging quantification by the mechanical arm probe, 128 women with 152 breast lesions (90 benign and 62 malignant) were included and maximum elasticity (Vmax), median elasticity (Vmean), maximum elasticity minus minimum (Vmax-min), and minimum elasticity (Vmin) were measured. Intercorrelation coefficients and Bland-Altman plots were used to compare the repeatability and consistency of handheld probe and mechanical arm measurements. Receiver operating characteristic curve was used to evaluate the diagnostic efficiency.

Standards for the classification of pathogenicity of somatic variants in cancer (oncogenicity): Joint recommendations of Clinical Genome Resource (ClinGen), Cancer Genomics Consortium (CGC), and Variant Interpretation for Cancer Consortium (VICC).

Purpose: Several professional societies have published guidelines for the clinical interpretation of somatic variants, which specifically address diagnostic, prognostic, and therapeutic implications. Although these guidelines for the clinical interpretation of variants include data types that may be used to determine the oncogenicity of a variant (eg, population frequency, functional, and in silico data or somatic frequency), they do not provide a direct, systematic, and comprehensive set of standards and rules to classify the oncogenicity of a somatic variant. This insufficient guidance leads to inconsistent classification of rare somatic variants in cancer, generates variability in their clinical interpretation, and, importantly, affects patient care.

Construction of the amniotic fluid-derived exosomal ceRNA network associated with ventricular septal defect.

Ventricular septal defect (VSD) is the most frequent congenital cardiac malformations. Amniotic fluid (AF) contains a higher abundance of biological compounds that could reflect fetal health information. The aims of our study were to construct a competitive endogenous RNA (ceRNA) network based on AF-derived exosomal ncRNAs.

Construction and Validation of a Predictive Nomogram Based on Ultrasound for Lymph Node Metastasis of Papillary Thyroid Carcinoma in the Cervical Central Region.

To establish and validate a nomogram for predicting lymph node metastasis (LNM) of papillary thyroid carcinoma (PTC) in the cervical central region. This retrospective study included 287 PTC patients with 309 nodules treated from December 2018 to May 2020 at our hospital. The cohort was divided randomly into a training set and a testing set according to a 7:3 ratio.

[Establishment of a predictive model for central cervical lymph node metastasis of papillary thyroid carcinoma based on ACR TI-RADS score and evaluation of its diagnostic efficacy].

To establish a predictive model for central lymph node metastasis（CLNM） of papillary thyroid carcinoma（PTC） based on ACR TI-RADS grades（ATR model） and evaluate its diagnostic efficacy. A total of 319 patients with PTC diagnosed from January 2019 to May 2020 were included, including 366 nodules were used as the modeling cohort to construct the risk prediction model. A total of 105 PTC patients with 121 nodules from June to August 2020 were included as the external validation cohort.

Combination of high-frequency ultrasound and virtual touch tissue imaging and quantification improve the diagnostic efficiency for mild carpal tunnel syndrome.

Background: Carpal tunnel syndrome (CTS) is the most common entrapment symptom in the peripheral nerves. High-frequency ultrasound (HFUS) is widely used in the diagnosis of CTS. Virtual Touch Tissue Imaging and Quantification (VTIQ), which provides more information about the hardness of organization, is used to diagnose CTS.

Use of Lung Ultrasound to Differentiate Coronavirus Disease 2019 (COVID-19) Pneumonia From Community-Acquired Pneumonia.

To investigate the feasibility of lung ultrasound in evaluating coronavirus disease 2019 (COVID-19) and distinguish the sonographic features between COVID-19 and community-acquired pneumonia (CAP), a total of 12 COVID-19 patients and 20 CAP patients were selected and underwent lung ultrasound. The modified Buda scoring system for interstitial lung disease was used to evaluate the severity and treatment effect of COVID-19 on ultrasonography. The differences between modified lung ultrasound (MLUS) score and high-resolution computed tomography (HRCT) Warrick score were analyzed to evaluate their correlation.

Development of an Ultrasound Prediction Model to Discriminate between Malignant and Benign Liver Lesions.

To discriminate between malignant and benign liver lesions, we evaluated the ultrasound features of the target lesions in 266 patients and established a prediction model using a logistic regression algorithm. The prediction model based on independent factors was expressed as predictive score = 1.129 × interaction of irregular shape and unclear boundary + 1.

The Clinical Value of New Scoring System of Cervical Lymph Node.

To distinguish malignant cervical lymphadenopathy, we established a new scoring system based on ultrasound features. Two hundred sixty-three patients with cervical lymphadenopathy received ultrasonic examination and underwent ultrasound-guided core needle biopsy or fine needle aspiration. The scoring system was proposed by multivariate logistic regression analysis and compared with Liao scoring system (0.