抗精神病/抗抑郁药物诱导肝毒性的预测与监测生物标志物研究方案

数据集获取（Figshare）

• 源站标题：Biomarkers for the prediction and monitoring of the antipsychotic/antidepressant-induced hepatotoxicity: study protocol
• DOI：10.6084/m9.figshare.28367891.v1
• 发布日期：2025-02-07
• 文件数：2 个
• 文件总体积：59.12 KB
• 源站页面：https://tandf.figshare.com/articles/dataset/Biomarkers_for_the_prediction_and_monitoring_of_the_antipsychotic_antidepressant-induced_hepatotoxicity_study_protocol/28367891

命令行下载

curl -L -o "ipgs_a_2456449_sm2933.docx" "https://ndownloader.figshare.com/files/52196672"
curl -L -o "ipgs_a_2456449_sm2932.docx" "https://ndownloader.figshare.com/files/52196675"

文件清单

• ipgs_a_2456449_sm2933.docx（29.98 KB）
• ipgs_a_2456449_sm2932.docx（29.15 KB）

文件总体积 59.12 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

This study is designed to address the connection between antidepressant and antipsychotic-induced hepatotoxicity with pharmacogenetic and epigenetic indicators, using a novel combined approach of CYP450 polymorphism determination and early liver injury detection via microRNA testing.
The multi-centric retrospective case-control study in Slovakia involves 151 cases with signs of hepatotoxicity and 604 controls without. Participants will be tested for selected CYP450, UGT1A1 polymorphisms, and microRNAs.
Anticipated findings will test if patients with specific CYP450 and UGT1A1 polymorphisms are at higher risk for drug-induced hepatotoxicity and if plasma microRNAs hsa-miR-122-5p and hsa-miR-192-5p, alone or combined, can differentiate patients with abnormal liver function.
The findings could contribute to personalized treatment approach by combining genetic and epigenetic biomarkers.
This study is about making treatment for mental health issues, like depression and anxiety, better and safer. Some patients respond differently to their medications, and some can have serious side effects, such as liver damage. To help with this, we are trying a new approach that uses two tests. The first test looks at certain genes to see how a person might react to medication. The second test checks for small molecules in the blood that can show if there are early signs of liver problems. We want to find out two things: Do people with certain genes have a higher risk of liver problems from their medications? Can these small molecules help us find liver issues better than regular blood tests? We will study about 755 patients from three mental health clinics in Slovakia, who have been taking their medications for at least four weeks. By identifying patients who might struggle with their medications due to their genes, we hope to catch liver problems early. This could lead to more personalized and effective treatments for everyone.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.28367891.v1（source: https://tandf.figshare.com/articles/dataset/Biomarkers_for_the_prediction_and_monitoring_of_the_antipsychotic_antidepressant-induced_hepatotoxicity_study_protocol/28367891）。