Correlates of Cetuximab Efficacy in Recurrent and Metastatic Head and Neck Squamous Cell Carcinoma Previously Treated With Immunotherapy.

Purpose: Immune checkpoint inhibitors (ICIs) are now first-line therapy for most patients with recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC), and cetuximab is most often used as subsequent therapy. However, data describing cetuximab efficacy in the post-ICI setting are limited.

Methods: We performed a single-institution retrospective analysis of patients with R/M HNSCC treated with cetuximab, either as monotherapy or in combination with chemotherapy, after receiving an ICI.

AI-assisted detection for chest X-rays (AID-CXR): a multi-reader multi-case study protocol.

Introduction: A chest X-ray (CXR) is the most common imaging investigation performed worldwide. Advances in machine learning and computer vision technologies have led to the development of several artificial intelligence (AI) tools to detect abnormalities on CXRs, which may expand diagnostic support to a wider field of health professionals. There is a paucity of evidence on the impact of AI algorithms in assisting healthcare professionals (other than radiologists) who regularly review CXR images in their daily practice.

Artificial Intelligence in Breast Cancer Diagnosis and Personalized Medicine.

Breast cancer is a significant cause of cancer-related mortality in women worldwide. Early and precise diagnosis is crucial, and clinical outcomes can be markedly enhanced. The rise of artificial intelligence (AI) has ushered in a new era, notably in image analysis, paving the way for major advancements in breast cancer diagnosis and individualized treatment regimens.

Throughput screening of Bacillus subtilis strains that abundantly secrete surfactin in vitro identifies effective probiotic candidates.

Since the prohibition of antibiotics as animal growth promoters, demand for effective probiotic strains has steadily increased. The goal is to maintain productivity and mitigate environmental concerns in the livestock industry. There are many probiotic animal-diet supplements available, over 2,000 products in the Republic of Korea alone, with little explanation about the desirable properties of each probiotic strain.

Association of Artificial Intelligence-Aided Chest Radiograph Interpretation With Reader Performance and Efficiency.

Importance: The efficient and accurate interpretation of radiologic images is paramount.

Objective: To evaluate whether a deep learning-based artificial intelligence (AI) engine used concurrently can improve reader performance and efficiency in interpreting chest radiograph abnormalities.

Design, Setting, And Participants: This multicenter cohort study was conducted from April to November 2021 and involved radiologists, including attending radiologists, thoracic radiology fellows, and residents, who independently participated in 2 observer performance test sessions.

Development and Validation of a Multimodal-Based Prognosis and Intervention Prediction Model for COVID-19 Patients in a Multicenter Cohort.

The ability to accurately predict the prognosis and intervention requirements for treating highly infectious diseases, such as COVID-19, can greatly support the effective management of patients, especially in resource-limited settings. The aim of the study is to develop and validate a multimodal artificial intelligence (AI) system using clinical findings, laboratory data and AI-interpreted features of chest X-rays (CXRs), and to predict the prognosis and the required interventions for patients diagnosed with COVID-19, using multi-center data. In total, 2282 real-time reverse transcriptase polymerase chain reaction-confirmed COVID-19 patients’ initial clinical findings, laboratory data and CXRs were retrospectively collected from 13 medical centers in South Korea, between January 2020 and June 2021.

Improving the Performance of Radiologists Using Artificial Intelligence-Based Detection Support Software for Mammography: A Multi-Reader Study.

Objective: To evaluate whether artificial intelligence (AI) for detecting breast cancer on mammography can improve the performance and time efficiency of radiologists reading mammograms.

Materials And Methods: A commercial deep learning-based software for mammography was validated using external data collected from 200 patients, 100 each with and without breast cancer (40 with benign lesions and 60 without lesions) from one hospital. Ten readers, including five breast specialist radiologists (BSRs) and five general radiologists (GRs), assessed all mammography images using a seven-point scale to rate the likelihood of malignancy in two sessions, with and without the aid of the AI-based software, and the reading time was automatically recorded using a web-based reporting system.

Eudesmanolides from Taraxacum mongolicum and their inhibitory effects on the production of nitric oxide.

A new eudesmanolide, 1β,3β-dihydroxy-eudesman-11(13)-en-6α,12-olide (1) was isolated and identified from Taraxacum mongolicum, together with two known compounds, 1β,3β-dihydroxyeudesman-6α,12-olide (2) and loliolide (3). The structure of 1 was established by analysis of its physical and spectroscopic data. 1 was found to have an inhibitory activity on nitric oxide production with an IC(50) of 38.

Hydoroxyhibiscone A, a novel human neutrophil elastase inhibitor from Hibiscus syriacus.

In an ongoing investigation of compounds from natural products that exhibit anti-aging properties, hydroxyhibiscone A (1), a new furanosesquiterpenoid, together with hibiscone D (2), was isolated from the root bark of Hibiscus syriacus. Utilizing UV, IR, NMR, and MS spectroscopic analyses, these chemical structures were revealed. Compounds 1 and 2 were found to possess significant anti-aging properties on the human neutrophil elastase (HNE) assay, exhibiting HNE inhibitory activities with IC50 values of 5.