Results 181 to 190 of about 459,286 (299)

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

Molecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee, Byung‐Cheol Han, Gi‐Bang Koo, Jihye Park, Mijin Kwon, Young Bin Park, Jae‐Mun Choi, Seung‐Ho Lee, Sangho Roh   +8 more
wiley   +1 more source

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

A new low-rank adaptation method for brain structure and metastasis segmentation via decoupled principal weight direction and magnitude. [PDF]

Sci Rep
Zhu H, Yang H, Wang Y, Hu K, He G, Zhou J, Li Z, Alzheimer’s Disease Neuroimaging Initiative.   +7 more
europepmc   +1 more source

Low-Rank Approximation, Adaptation, and Other Tales

Low-rank approximation is a fundamental technique in modern data analysis, widely utilized across various fields such as signal processing, machine learning, and natural language processing. Despite its ubiquity, the mechanics of low-rank approximation and its application in adaptation can sometimes be obscure, leaving practitioners and researchers ...
openaire   +2 more sources

LoRA-Composer: Leveraging Low-Rank Adaptation for Multi-Concept Customization in Training-Free Diffusion Models [PDF]

Yang Yang, Wang Wen, Liang Peng, Chaotian Song, Yao Chen, Hengjia Li, Xiaolong Yang, Qinglin Lu, Deng Cai, Boxi Wu, Wei Liu   +10 more
openalex   +1 more source

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source

Low-Rank Adaptation for Scalable Large Language Models: A Comprehensive Survey [PDF]

Chia Xin Liang, Zhuming Bi, Tianyang Wang, Ming Liu, Xinyuan Song, Yichao Zhang, Junhao Song, Qian Niu, Benji Peng, Keyu Chen, Junyu Liu, Junfeng Hao, I‐Lin Ho   +12 more
openalex   +1 more source

Targeting p38α in cancer: challenges, opportunities, and emerging strategies

Molecular Oncology, EarlyView.
p38α normally regulates cellular stress responses and homeostasis and suppresses malignant transformation. In cancer, however, p38α is co‐opted to drive context‐dependent proliferation and dissemination. p38α also supports key functions in cells of the tumor microenvironment, including fibroblasts, myeloid cells, and T lymphocytes.
Angel R. Nebreda
wiley   +1 more source

FlexLoRA: Entropy-Guided Flexible Low-Rank Adaptation [PDF]

Muqing Liu, Chongjie Si, Yuheng Jia
openalex  

MTL-LoRA: Low-Rank Adaptation for Multi-Task Learning [PDF]

Yaming Yang, Dilxat Muhtar, Yelong Shen, Yuefeng Zhan, Jianfeng Liu, Yujing Wang, Hao Sun, Denvy Deng, Feng Sun, Qi Zhang, Weizhu Chen, Yunhai Tong   +11 more
openalex   +1 more source