细菌种类与分布

该数据集研究肝素结合蛋白对严重多发伤患者细菌感染的预测价值,包含实验室参数和细菌感染状态数据。

NIAID Data Ecosystem
浏览 21
表格increased vascular permeability52 &# 17700 &# 177roc analysis showsbinding protein increasebinding protein concentrations54 without infectionxlink "> ninetybinding protein combinedbetter predictive valuexlink "> heparinbinding protein
Bacterial species and distribution.

基本信息

模态
表格
大小
0.000005632 GB
许可
CC BY 4.0
创建/更新时间
2026-10-07
版本
v1

资源简介

细菌种类与分布

【一句话概览】

本数据集是 figshare 公开的结构化表格数据集,收录 1 个文件、合计 5.63 KB,主题涵盖 increased vascular permeability、52 &# 177、00 &# 177、roc analysis shows、binding protein increase,可用于统计建模、特征工程与队列分析,CC BY 4.0 许可开放获取。

【数据集背景】

本数据集源站标题为《Bacterial species and distribution.》。源站首次发布:2024-12-26。

【数据内容】

源站原始描述:Introduction Heparin-binding protein is an inflammatory factor with predictive value for sepsis and participates in the inflammatory response through antibacterial effects, chemotaxis, and increased vascular permeability. The role of heparin-binding protein in sepsis has been progressively demonstrated, but few studies have been conducted in the context of polytrauma combined with bacterial infections. This study aims to investigate the predictive value of heparin-binding protein for bacterial i…

【数据结构与技术规格】

文件数 1 个,合计 5.63 KB。Table 2.xls:application/vnd.ms-excel,5.63 KB。数据集 DOI:10.1371/journal.pone.0300692.t002。

【主题与分类】

源站学科分类:Biochemistry、Microbiology、Cell Biology、Genetics、Molecular Biology、Biotechnology。主题标签:increased vascular permeability、52 &# 177、00 &# 177、roc analysis shows、binding protein increase、binding protein concentrations、54 without infection、binding protein combined、better predictive value、binding protein。

【适用方向】

结构化表格数据可直接用于统计建模、特征工程与队列分析。

【获取与许可】

源站页面:https://plos.figshare.com/articles/dataset/Bacterial_species_and_distribution_/28096358

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Li, Li; Tian, Xiao-xi; Feng, Gui-long; Chen, Bing (2024). Bacterial species and distribution.. PLOS ONE. Dataset

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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。

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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(Figshare)

命令行下载

curl -L -o "Table 2.xls" "https://ndownloader.figshare.com/files/51384458"

文件清单

  • Table 2.xls(5.63 KB)

文件总体积 5.63 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

Introduction
Heparin-binding protein is an inflammatory factor with predictive value for sepsis and participates in the inflammatory response through antibacterial effects, chemotaxis, and increased vascular permeability. The role of heparin-binding protein in sepsis has been progressively demonstrated, but few studies have been conducted in the context of polytrauma combined with bacterial infections. This study aims to investigate the predictive value of heparin-binding protein for bacterial infections in patients with severe polytrauma.
Materials and methods
This is a prospective single-center study. Patients with polytrauma in the emergency intensive care unit were selected for the study, and plasma heparin-binding protein concentrations and other laboratory parameters were measured within 48 hours of admission to the hospital. A two-sample comparison and univariate logistic regression analysis investigated the relationship between heparin-binding protein and bacterial infection in polytrauma patients. A multifactor logistic regression model was constructed, and the ROC curve was plotted.
Results
Ninety-seven patients with polytrauma were included in the study, 43 with bacterial infection and 54 without infection. Heparin-binding protein was higher in the infected group than in the control group [(32.00±3.20) ng/mL vs. (18.52±1.33) ng/mL, P = 0.001]. Univariate logistic regression analysis shows that heparin-binding protein is related to bacterial infection (OR = 1.10, Z = 3.91, 95%CI:1.05~1.15, P = 0.001). Multivariate logistic regression equations showed that patients were 1.12 times more likely to have bacterial infections for each value of heparin-binding protein increase, holding neutrophils and Procalcitonin (PCT) constant. ROC analysis shows that heparin-binding protein combined with neutrophils and PCT has better predictive value for bacterial infection [AUC = 0.935, 95%CI:0.870~0.977].
Conclusions
Heparin-binding protein may predict bacterial infection in patients with severe polytrauma. Combining heparin-binding protein, PCT, and neutrophils may improve bacterial infection prediction.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0300692.t002(source: https://plos.figshare.com/articles/dataset/Bacterial_species_and_distribution_/28096358)。

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