接受Elexacaftor/Tezacaftor/Ivacaftor联合治疗的囊性纤维化患者肠-肺轴研究

数据集获取

源站：https://clinicaltrials.gov/study/NCT05937815

标准获取流程：

1. 访问源站链接，注册/登录账号；
2. 进入数据集详情页，按页面指引申请权限或直接下载；
3. 部分平台提供 SDK，例如：
   • OpenDataLab: pip install openxlab 后 openxlab.dataset.get(...)
   • ModelScope: pip install modelscope 后 modelscope download
   • 天池: 登录后页面提供直链下载
     以源站「数据下载/使用文档」页面为准。

数据说明

Conditions: Cystic Fibrosis. Cystic fibrosis is a systemic disease, which affects in particular the respiratory and digestive systems of patients, sites of chronic inflammation. It has also been shown that in these patients, the pulmonary and intestinal microbiota were distinct from those of healthy subjects and that the progression of the disease was associated with alterations in these microbiota. In addition, numerous data suggest the existence of an “intestinal-lung axis” and therefore encourage studying these two organs in parallel and not separately. The management of cystic fibrosis has been marked in recent years by the appearance of CFTR modulators, in particular the combination lumacaftor/ivacaftor (LUM/IVA) (for patients homozygous F508del). The criteria for evaluating the efficacy of these treatments are based on the change in FEV (forced expiratory volume in 1 second), the number of exacerbations, body mass index or quality of life. However, it is essential to be able to document the effect of these treatments on the lung and digestive microbiota and inflammation. Since 2016, we have set up the national “Lum-Iva-Biota” cohort and have been able to show that the effect of LUM/IVA on the pulmonary microbiota was more marked in patients not previously colonized with P. aeruginosa. A new combination of elexacaftor/tezacaftor/ivacaftor has proven its efficacy for the treatment of patients aged 12 years and over with two F508del mutations or a so-called “minimal function” mutation associated with one F508del mutation. European marketing authorization was obtained in August 2020 and access in France should therefore arrive soon. Given that this treatment targets new mutations and that the efficacy seems greater than with LUM/IVA, it is important to assess its impact on the microbiota and the pulmonary and digestive inflammation of patients. It is therefore a question of taking advantage of the experience of the Lum-Iva-Biota cohort, and the validated and operational sample circuit establi

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。