数据表1：假设与理论：利用细胞平台表征能量代谢异常作为阿尔茨海默病个性化医疗方法

数据集获取（Figshare）

• 源站标题：Data_Sheet_1_Hypothesis and Theory: Characterizing Abnormalities of Energy Metabolism Using a Cellular Platform as a Personalized Medicine Approach for Alzheimer’s Disease.pdf
• DOI：10.3389/fcell.2021.697578.s001
• 发布日期：2021-07-30
• 文件数：1 个
• 文件总体积：1.66 MB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Hypothesis_and_Theory_Characterizing_Abnormalities_of_Energy_Metabolism_Using_a_Cellular_Platform_as_a_Personalized_Medicine_Approach_for_Alzheimer_s_Disease_pdf/15080970

命令行下载

curl -L -o "Data_Sheet_1_Hypothesis and Theory: Characterizing Abnormalities of Energy Metabolism Using a Cellular Platform as a Personalized Medicine Approach fo.pdf" "https://ndownloader.figshare.com/files/28996383"

文件清单

• Data_Sheet_1_Hypothesis and Theory: Characterizing Abnormalities of Energy Metabolism Using a Cellular Platform as a Personalized Medicine Approach fo.pdf（1.66 MB）

文件总体积 1.66 MB（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

Sporadic or late-onset Alzheimer’s disease (LOAD) is characterized by slowly progressive deterioration and death of CNS neurons. There are currently no substantially disease-modifying therapies. LOAD pathology is closely related to changes with age and include, among others, accumulation of toxic molecules and altered metabolic, microvascular, biochemical and inflammatory processes. In addition, there is growing evidence that cellular energy deficits play a critical role in aging and LOAD pathophysiology. However, the exact mechanisms and causal relationships are largely unknown. In our studies we tested the hypothesis that altered bioenergetic and metabolic cell functions are key elements in LOAD, using a cellular platform consisting of skin fibroblasts derived from LOAD patients and AD-unaffected control individuals and therefrom generated induced pluripotent stem cells that are differentiated to brain-like cells to study LOAD pathogenic processes in context of age, disease, genetic background, cell development, and cell type. This model has revealed that LOAD cells exhibit a multitude of bioenergetic and metabolic alterations, providing evidence for an innate inefficient cellular energy management in LOAD as a prerequisite for the development of neurodegenerative disease with age. We propose that this cellular platform could ultimately be used as a conceptual basis for a personalized medicine tool to predict altered aging and risk for development of dementia, and to test or implement customized therapeutic or disease-preventive intervention strategies.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fcell.2021.697578.s001（source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Hypothesis_and_Theory_Characterizing_Abnormalities_of_Energy_Metabolism_Using_a_Cellular_Platform_as_a_Personalized_Medicine_Approach_for_Alzheimer_s_Disease_pdf/15080970）。