Metal-based Approaches to Fight Cervical Cancer
Drug discovery today（2024）
CICS-UBI-Health Sciences Research Centre | CDRSP-IPL-Centre for Rapid and Sustainable Product Development
Abstract
Cervical cancer (CC) is one of the leading causes of death among women worldwide. The current treatments for this cancer consist of invasive methods such as chemotherapeutic drugs, radiation, immunotherapy and surgery, which could lead to severe side effects and hinder the patient’s life quality. Although metal-based therapies, including cisplatin and ruthenium-based compounds, offer promising alternatives, they lack specificity and harm healthy cells. Combining metal nanoparticles with standard approaches has demonstrated remarkable efficacy and safety in the fight against CC. Overall, this review is intended to show the latest advancements and insights into metal-based strategies, creating a promising path for more effective and safer treatments in the battle against CC.
MoreTranslated text
Key words
cervical cancer,HPV,metal-based strategies,cisplatin,ruthenium,metal nanoparticles
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper