Transcriptomic insights into the anti-inflammatory mechanisms of Protaetia brevitarsis seulensis larvae in IL-1β-driven chondrosarcoma cells.

Osteoarthritis (OA) is a complex, degenerative, multi-factorial joint disease. Because of the difficulty in treating OA, developing new targeting strategies that can be used to understand its molecular mechanisms is critical. Protaetia brevitarsis seulensis larvae offer much therapeutic value; however, the presence of various active compounds and the multi-factorial risk factors for OA render the precise mechanisms of action unclear.

An Investigation of the Anticancer Mechanism of L. Extract Against Colorectal Cancer by Integrating a Network Pharmacological Analysis and Experimental Validation.

L. has exhibited various pharmacological effects, yet its anticancer activities against colorectal cancer (CRC) and underlying molecular mechanisms remain unclear. This study investigated the anticancer properties of an ethanol extract of L.

Survival benefits of adjuvant chemotherapy after conversion surgery in patients with advanced pancreatic cancer.

Background: Oncologic outcomes of conversion surgery for advanced pancreatic cancer (PC) have scarcely been reported. Therefore, this study aimed to investigate the outcomes of conversion surgery with preoperative treatment of FOLFIRINOX or gemcitabine with nab-paclitaxel (GnP) for patients with advanced PC including locally advanced or metastatic PC.

Methods: Using the National Health Insurance database between 2005 and 2020, we identified patients who underwent conversion surgery after chemotherapy with FOLFIRINOX or GnP for advanced PC.

Abdominal synthetic CT generation for MR-only radiotherapy using structure-conserving loss and transformer-based cycle-GAN.

Purpose: Recent deep-learning based synthetic computed tomography (sCT) generation using magnetic resonance (MR) images have shown promising results. However, generating sCT for the abdominal region poses challenges due to the patient motion, including respiration and peristalsis. To address these challenges, this study investigated an unsupervised learning approach using a transformer-based cycle-GAN with structure-preserving loss for abdominal cancer patients.

Automated Screening of Precancerous Cervical Cells Through Contrastive Self-Supervised Learning.

Cervical cancer is a significant health challenge, yet it can be effectively prevented through early detection. Cytology-based screening is critical for identifying cancerous and precancerous lesions; however, the process is labor-intensive and reliant on trained experts to scan through hundreds of thousands of mostly normal cells. To address these challenges, we propose a novel distribution-augmented approach using contrastive self-supervised learning for detecting abnormal squamous cervical cells from cytological images.