The Impact of Artificial Intelligence on Radiologists' Reading Time in Bone Age Radiograph Assessment: A Preliminary Retrospective Observational Study.

To evaluate the real-world impact of artificial intelligence (AI) on radiologists' reading time during bone age (BA) radiograph assessments. Patients (<19 year-old) who underwent left-hand BA radiographs between December 2021 and October 2023 were retrospectively included. A commercial AI software was installed from October 2022.

Transcriptomic analysis of cellular senescence induced by ectopic expression of ATF6α in human breast cancer cells.

Background: The transcriptomic profile of cellular senescence is strongly associated with distinct cell types, the specific stressors triggering senescence, and temporal progression through senescence stages. This implies the potential necessity of conducting separate investigations for each cell type and a stressor inducing senescence. To elucidate the molecular mechanism that drives endoplasmic reticulum (ER) stress-induced cellular senescence in MCF-7 breast cancer cells, with a particular emphasis on the ATF6α branch of the unfolded protein response.

Aberrant overexpression of the autoantigen protein vimentin promotes Th17 cell differentiation and autoimmune arthritis via activation of STAT3 signaling.

Vimentin contributes to the positioning and function of organelles, cell migration, adhesion, and division. However, secreted vimentin accumulates on the cell surface (Mor-Vaknin et al., 2003; Ramos et al.

Citrus peel powder alters the rheological properties and 3D printing performance of potato starch gel.

Owing to the growing interest in sustainable resource utilization, the current study explores the potential replacement of pectin with citrus peel powder (CP) in starch-based 3D food printing ink formulations. The effect of different concentrations of pectin (1 %, 2 %, 3 %) and CP (1 %, 2 %, 3 %) on the printing fidelity, microstructure, rheological and textural properties of potato starch gel were investigated. The results showed that the 3D printing performance of CP-added inks was higher than that of pectin-added inks at all tested concentrations.

Development of a new prognostic model to predict pneumonia outcome using artificial intelligence-based chest radiograph results.

This study aimed to develop a new simple and effective prognostic model using artificial intelligence (AI)-based chest radiograph (CXR) results to predict the outcomes of pneumonia. Patients aged > 18 years, admitted the treatment of pneumonia between March 2020 and August 2021 were included. We developed prognostic models, including an AI-based consolidation score in addition to the conventional CURB-65 (confusion, urea, respiratory rate, blood pressure, and age ≥ 65) and pneumonia severity index (PSI) for predicting pneumonia outcomes, defined as 30-day mortality during admission.

Bioelectrical impedance parameters add incremental value to waist-to-hip ratio for prediction of metabolic dysfunction associated steatotic liver disease in youth with overweight and obesity.

Introduction: Metabolic dysfunction-associated steatotic liver disease (MASLD) presents a growing health concern in pediatric populations due to its association with obesity and metabolic syndrome. Bioelectrical impedance analysis (BIA) offers a non-invasive and potentially effective alternative for identifying MASLD risk in youth with overweight or obesity. Therefore, this study aimed to assess the utility of BIA for screening for MASLD in the youth.

Impact of AI for Digital Breast Tomosynthesis on Breast Cancer Detection and Interpretation Time.

Purpose To develop an artificial intelligence (AI) model for the diagnosis of breast cancer on digital breast tomosynthesis (DBT) images and to investigate whether it could improve diagnostic accuracy and reduce radiologist reading time. Materials and Methods A deep learning AI algorithm was developed and validated for DBT with retrospectively collected examinations (January 2010 to December 2021) from 14 institutions in the United States and South Korea. A multicenter reader study was performed to compare the performance of 15 radiologists (seven breast specialists, eight general radiologists) in interpreting DBT examinations in 258 women (mean age, 56 years ± 13.

Positive Predictive Values of Abnormality Scores From a Commercial Artificial Intelligence-Based Computer-Aided Diagnosis for Mammography.

Objective: Artificial intelligence-based computer-aided diagnosis (AI-CAD) is increasingly used in mammography. While the continuous scores of AI-CAD have been related to malignancy risk, the understanding of how to interpret and apply these scores remains limited. We investigated the positive predictive values (PPVs) of the abnormality scores generated by a deep learning-based commercial AI-CAD system and analyzed them in relation to clinical and radiological findings.

A Nationwide Study on HER2-Low Breast Cancer in South Korea: Its Incidence of 2022 Real World Data and the Importance of Immunohistochemical Staining Protocols.

Purpose: Notable effectiveness of trastuzumab deruxtecan in patients with human epidermal growth factor receptor 2 (HER2)-low advanced breast cancer (BC) has focused pathologists' attention. We studied the incidence and clinicopathologic characteristics of HER2-low BC, and the effects of immunohistochemistry (IHC) associated factors on HER2 IHC results.

Materials And Methods: The Breast Pathology Study Group of the Korean Society of Pathologists conducted a nationwide study using real-world data on HER2 status generated between January 2022 and December 2022.

Different particle sizes of leaf powder modify the rheological and textural properties of corn starch-based 3D food printing ink.

The study determined the effect of incorporating leaf powder (MCLP) into corn-starch 3D food-printing ink as a functional ingredient. The effects of the particle size (75, 131, and 200 μm) and quantity of MCLP on 3D printing performance, structural, textural, and rheological properties of corn starch gel were evaluated with different concentrations (5, 10, and 15 % (w/w)) of corn starch. The viscoelastic properties of food inks were determined considering their behavior during extrusion and self-recovery after printing.

Diagnostic performance with and without artificial intelligence assistance in real-world screening mammography.

Purpose: To evaluate artificial intelligence-based computer-aided diagnosis (AI-CAD) for screening mammography, we analyzed the diagnostic performance of radiologists by providing and withholding AI-CAD results alternatively every month.

Methods: This retrospective study was approved by the institutional review board with a waiver for informed consent. Between August 2020 and May 2022, 1819 consecutive women (mean age 50.

3-D breast nodule detection on automated breast ultrasound using faster region-based convolutional neural networks and U-Net.

Mammography is currently the most commonly used modality for breast cancer screening. However, its sensitivity is relatively low in women with dense breasts. Dense breast tissues show a relatively high rate of interval cancers and are at high risk for developing breast cancer.

Design of a Bioinspired Robust Three-Dimensional Cross-Linked Polymer Binder for High-Performance Li-Ion Battery Applications.

Si has the highest theoretical capacity (4200 mA h g) among conventional anode materials, such as graphite (372 mA h g), but its large volume expansion leads to deterioration of the battery performance. To overcome this problem (issue), we investigated the use of polysaccharide-based 3D cross-linked network binders for Si anodes, in which the polysaccharide formed an effective 3D cross-linked network around Si particles via cross-linking of polysaccharide with citric acid (CA). Sodium alginate (SA), a natural polysaccharide extracted from brown algae, is a suitable binder material for Si anodes because its abundant hydroxyl (-OH) and carboxyl (-COOH) groups form hydrogen and covalent bonds with the -OH groups present on the Si surface.

Clinical outcomes and actual consequence of lung nodules incidentally detected on chest radiographs by artificial intelligence.

This study evaluated how often clinically significant lung nodules were detected unexpectedly on chest radiographs (CXR) by artificial intelligence (AI)-based detection software, and whether co-existing findings can aid in differential diagnosis of lung nodules. Patients (> 18 years old) with AI-detected lung nodules at their first visit from March 2021 to February 2022, except for those in the pulmonology or thoracic surgery departments, were retrospectively included. Three radiologists categorized nodules into malignancy, active inflammation, post-inflammatory sequelae, or "other" groups.

Merkel Cell Carcinoma of the Trunk: Two Case Reports and Imaging Review.

Merkel cell carcinoma (MCC) is a rare malignant cutaneous tumor primarily located in the head and neck. We report the imaging features of pathologically confirmed MCC in the trunk. On US, MCC showed heterogeneous echogenicity with perpendicular hypoechoic linear bands that resembled "columns of smoke" in the skin and subcutaneous layers as well as prominent vascularity.

Machine Learning Predicts Pathologic Complete Response to Neoadjuvant Chemotherapy for ER+HER2- Breast Cancer: Integrating Tumoral and Peritumoral MRI Radiomic Features.

Background: This study aimed to predict pathologic complete response (pCR) in neoadjuvant chemotherapy for ER+HER2- locally advanced breast cancer (LABC), a subtype with limited treatment response.

Methods: We included 265 ER+HER2- LABC patients (2010-2020) with pre-treatment MRI, neoadjuvant chemotherapy, and confirmed pathology. Using data from January 2016, we divided them into training and validation cohorts.

Combined effect of heating temperature and content of pectin on the textural properties, rheology, and 3D printability of potato starch gel.

Three-dimensional (3D) printing is one of the emerging techniques which fabricates customized foods with desired sensory characteristics. Rheological properties of 3D printing materials are vitally important in printability which govern the flowability and structural stability. Due to its unique gel-forming characteristics, potato starch has been extensively used in myriad food applications, such as 3D printing.

Novel Risks of Unfavorable Corticosteroid Response in Patients with Mild-to-Moderate COVID-19 Identified Using Artificial Intelligence-Assisted Analysis of Chest Radiographs.

The prediction of corticosteroid responses in coronavirus disease 2019 (COVID-19) patients is crucial in clinical practice, and exploring the role of artificial intelligence (AI)-assisted analysis of chest radiographs (CXR) is warranted. This retrospective case-control study involving mild-to-moderate COVID-19 patients treated with corticosteroids was conducted from 4 September 2021, to 30 August 2022. The primary endpoint of the study was corticosteroid responsiveness, defined as the advancement of two or more of the eight-categories-ordinal scale.