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Diagnostic Accuracy of Histologic Predictors of Dermatophytosis

NIAID Data Ecosystem2026-05-02 收录

真菌病诊断

组织学预测因子验证

数据链接：

https://data.mendeley.com/datasets/53ssrx3cr9 数据链接链接失效反馈

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资源简介：

Included is a dataset of 97 skin biopsies in which PAS was ordered to test for dermatophytosis and 12 binary predictors of possible dermatophytosis were extracted by multiple assessors.

应用场景：

创建时间：

2025-08-21

非编码RNA

真菌病诊断

The occurrence of fungal infection seriously affects the survival and life quality of transplanted patients. The accurate diagnosis is of particular importance in the early stage of infection. To deve

DataCite Commons2024-03-21 更新90

TaqMan primer-probe combinations for detection and distinguishing D . longicolla , D . caulivora , D . eres and D . novem .

分子病原体检测

真菌病诊断

TaqMan primer-probe combinations for detection and distinguishing D. longicolla, D. caulivora, D. eres and D. novem.

NIAID Data Ecosystem30

Identification code, Fusarium oxysporum forma specialis or source of isolation of other fungal species, geographic origin, pathogenicity test and their results of PCR amplification for each isolate used in this study.

真菌病诊断

病原真菌检测

aPathogenic strains of Fusarium oxysporum were isolated from soil, seed, or diseased host tissue. The other F. oxysporum strains were isolated from soil or healthy plant tissue. bF. oxysporum isolates

NIAID Data Ecosystem20

PCR-Based Genotyping of Epidemic and Preepidemic Trichoderma Isolates Associated with Green Mold of Agaricus bisporus

真菌病诊断

病原体分子流行病学

We used randomly amplified polymorphic DNA (RAPD)-PCR to estimate genetic variation among isolates of Trichoderma associated with green mold on the cultivated mushroom Agaricus bisporus. Of 83 isolate

PubMed Central60

The results of tNGS testing in this study.

真菌病诊断

靶向测序技术评估

Cryptococcus neoformans, a WHO critical-priority and neglected fungal pathogen, causes cryptococcosis primarily via inhalation. Clinical manifestations range from asymptomatic infection to fatal menin

NIAID Data Ecosystem20

Diagnostic Accuracy of Histologic Predictors of Dermatophytosis

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