幼儿囊性纤维化患者的病毒感染与气道微生物组
该数据集来自 clinicaltrials.gov,聚焦幼儿囊性纤维化(CF)患者的病毒感染与气道微生物组。CF 是比利时最常见的遗传性致死性疾病,因 CFTR 通道功能异常导致黏液黏稠、肺部清除能力下降,进而引发慢性感染、炎症和呼吸衰竭

基本信息
资源简介
幼儿囊性纤维化患者的病毒感染与气道微生物组
该数据集来自 clinicaltrials.gov,聚焦幼儿囊性纤维化(CF)患者的病毒感染与气道微生物组。CF 是比利时最常见的遗传性致死性疾病,因 CFTR 通道功能异常导致黏液黏稠、肺部清除能力下降,进而引发慢性感染、炎症和呼吸衰竭。CF 肺病自出生即因黏液炎症过程而起,患儿气道微生物定植与无 CF 婴儿显著不同。幼儿 CF 患者病毒感染频率与健康同龄人相当,但源站描述在此处截断。数据可用于研究 CF 患儿呼吸道细菌与病毒感染、肺部炎症及呼吸系统疾病负担(来源 clinicaltrials.gov)。
【数据内容】
源站描述(机器翻译,仅供参考):条件:儿童囊性纤维化、呼吸道细菌感染、呼吸道病毒感染、肺部炎症、呼吸系统疾病负担。囊性纤维化(CF)是比利时最常见的遗传性致死性疾病。由于囊性纤维化跨膜传导调节因子(CFTR)通道功能异常,氯离子无法移动到细胞表面,黏液变得更加黏稠。因此,CF 患者无法有效清除肺部,滞留的细菌可导致慢性感染和肺部炎症,最终导致呼吸衰竭。CF 肺病自出生即因黏液炎症过程而起,与无 CF 的婴儿相比,CF 婴儿气道的微生物定植显著改变。此外,患有 CF 的幼儿与健康同龄人一样频繁地遭受病毒感染,但 e
【主题与分类】
主题标签:Cystic Fibrosis in Children、Respiratory Bacterial Infection、Respiratory Viral Infection、Inflammation Lungs、Respiratory Morbidity。本站分类:呼吸系统疾病。
【获取与许可】
源站页面:https://clinicaltrials.gov/study/NCT06188988
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取
源站:https://clinicaltrials.gov/study/NCT06188988
标准获取流程:
- 访问源站链接,注册/登录账号;
- 进入数据集详情页,按页面指引申请权限或直接下载;
- 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。
- OpenDataLab:
数据说明
Conditions: Cystic Fibrosis in Children, Respiratory Bacterial Infection, Respiratory Viral Infection, Inflammation Lungs, Respiratory Morbidity. Cystic fibrosis (CF) is the most common hereditary life-threatening condition in Belgium. Because of a dysfunctional cystic fibrosis transmembrane conductance regulator (CFTR) channel, chloride is unable to move to the cell surface and mucus becomes more viscous. Consequently, CF patients are not able to clear their lungs efficiently, and trapped bacteria can lead to chronic infection and inflammation of the lungs, and ultimately respiratory failure. CF lung disease starts at birth due to muco-inflammatory processes and is associated with a significantly altered microbial colonization of the infant airways compared to infants without CF. Additionally, young children with CF suffer from viral infections as often as their healthy peers, but the episodes are more severe and often prolonged. Moreover, frequent viral infections in children with CF contribute towards a more pathogenic airway microbiome at a young age. Although this link has been previously reported, the exact mechanisms by which this occurs need to be elucidated. A pulmonary exacerbation in CF is characterized by an increase in respiratory symptoms, general symptoms and a decline in lung function. Most young children with CF suffer from a mean of 4 exacerbations per year for which antibiotics are prescribed. Despite the current novel therapies in CF, treatment of respiratory infections stay relevant and is a greater challenge with increasing survival. The key objective of this study is to gain insights into the mechanisms by which viral infections leading to pulmonary exacerbations induce a more pathogenic microbiome in young children with CF. About forty participants will be recruited at the paediatric CF clinic of the Antwerp University Hospital. Inclusion criteria are an age of less than 5 years and a diagnosis of CF. There are no exclusion criteria. Duration of the study is 1 year to cover for seasonality of clinical symptoms. Study visits are scheduled at 3-month intervals corresponding with the regu
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。
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