Molecular roadmap links stomach infection to cancer risk
Peer-Reviewed Publication
Updates every hour. Last Updated: 6-Nov-2025 04:11 ET (6-Nov-2025 09:11 GMT/UTC)
For brain tumors, radiology reports provide essential imaging perspectives while pathology reports deliver microscopic confirmation, but each type of report typically requires domain experts to interpret separately. This separation can make it difficult to form a consistent basis for diagnosis and to reliably link findings to patient survival. Leveraging the integrative capabilities of large language models (LLMs), both sources can now be analyzed within a unified framework, reducing fragmentation and improving the accuracy of diagnostic classification and survival prediction.
To address this, a team led by Dr. Zhuoqi Ma (1st author) and Dr. Zhicheng Jiao (corresponding) from the Department of Radiology at Brown University and Brown University Health developed a large language model (LLM)-based pipeline that integrates radiology and pathology reports within a unified framework. By leveraging the integrative capabilities of LLMs, both sources can be analyzed together and improving the accuracy of diagnostic classification and survival prediction. Their findings demonstrate the potential of this approach to enhance diagnostic reliability and support precision neuro-oncology.
This study examines the short- and long-term stock performance of small- and medium-sized enterprises (SMEs) following the issuance of hybrid securities—including bonds with warrants, convertible bonds, and exchangeable bonds—in the KOSDAQ market from 2016 to 2020. Using a sample of 204 issuers, we employ event study methodology and buy-and-hold abnormal returns to evaluate stock performance around the announcement date and over extended periods. Our findings indicate significantly positive cumulative abnormal returns in the short run, suggesting investor optimism. However, long-run analysis reveals substantial underperformance, particularly for bonds with warrants and exchangeable bonds, with significant declines over two- and three-year horizons. These results imply that managers may exploit overvaluations in hybrid securities markets, leading to long-term underperformance. Firm-specific factors such as growth opportunities, financial investor involvement, and corporate governance also influence performance. This study contributes to the literature by focusing on an emerging market context and incorporating exchangeable bonds, offering novel insights for investors and policymakers in emerging economies.
Hydrogels derived from biopolymers have numerous applications in bioengineering, drug delivery, wound healing, and wearable devices. Yet, their strong swelling and uncontrollable degradation stimulate the development of hydrogels that overcome these limitations. Here, we report nanocolloidal hydrogels formed from nanoparticles of methacryloyl-modified biopolymers that exhibit resistance to swelling and enzymatic degradation both in vitro and in vivo, along with exhibiting a broad-range of mechanical and lubrication properties, wear resistance and biocompatibility. The nonswelling behavior of nanocolloidal hydrogels takes origin in the resistance to swelling of their hydrophobic regions which are resulted from the nanophase of hydrophobic methacryloyl groups in the interior of the constituent nanoparticles. The developed approach to the preparation of nanocolloidal hydrogel with greatly enhanced properties will have applications in long-term drug delivery and cell culture, soft tissue augmentation, and implantable bioelectronics.