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醫學研究趨勢

AI精選本週最具影響力的29個專科論文

最後更新: 2026年5月11日

腫瘤科5

影響力 3

Mutations Targeted by Nous-209 Immunotherapy Occur Early in Lynch Syndrome Carriers' Precancer Lesions with Microsatellite Instability.

發表日期: 2026-05-11

Cancer prevention research (Philadelphia, Pa.)

MediLens 收錄日: 2026-05-12

This study characterizes precancerous colorectal lesions in Lynch syndrome carriers and evaluates the potential of Nous-209 immunotherapy for cancer prevention. Among 50 adenomas and 12 advanced adenomas from 26 carriers, 83% of advanced adenomas and 58% of adenomas were found to be MMR-deficient...

在PubMed上閱讀
影響力 3

Multifunctionally Modified Low Molecular Weight PEI for Efficient Gene Delivery and Ferroptosis-Induced Antitumor Activity.

發表日期: 2026-05-11

Biomacromolecules

MediLens 收錄日: 2026-05-12

This study presents a multifunctional cationic polymer (PFFc) designed for efficient gene delivery and induction of ferroptosis in cancer therapy. The polymer demonstrated strong gene-specific cytotoxicity in proliferation assays, outperforming nontherapeutic controls. Mechanistically, PFFc enhan...

在PubMed上閱讀
影響力 3

iS2C2: a cointelligent platform for mechanistic discovery of disease cellular crosstalk.

發表日期: 2026-05-11

Signal transduction and targeted therapy

MediLens 收錄日: 2026-05-12

The study presents iS2C2, a novel platform that integrates computational algorithms with large language models to analyze single-cell RNA-seq and spatial transcriptomics data. This platform addresses the limitations of traditional methods by generating biologically interpretable hypotheses. When ...

在PubMed上閱讀
影響力 3

Comparative Assessment of Free Energy Computational Methods for Revealing the Interactions Driving PARP1 Selective Inhibition.

發表日期: 2026-05-11

Journal of chemical information and modeling

MediLens 收錄日: 2026-05-12

This study evaluates three computational methods for predicting inhibitor selectivity in PARP enzymes relevant to ovarian, breast, and prostate cancers. MM/PBSA provides qualitative insights but is sensitive to conformational changes, while ABFE and US methods yield better alignment with experime...

在PubMed上閱讀
影響力 2

Performance of multimodal large language models for the detection and characterization of bone lesions on radiographs.

發表日期: 2026-05-11

Diagnostic and interventional radiology (Ankara, Turkey)

MediLens 收錄日: 2026-05-12

This study evaluated five large language models (LLMs) for detecting and characterizing bone lesions on plain radiographs using 3,746 images. ChatGPT 5.2 showed the best accuracy (0.803) and specificity (0.916) for lesion detection, while Claude Sonnet 4.6 and Gemini 3 Flash excelled in sensitivi...

在PubMed上閱讀

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