questionsmedicales.fr
Eucaryotes
Champignons
Ascomycota
Onygenales
Arthrodermataceae
Arthrodermataceae : Questions médicales fréquentes
Termes MeSH sélectionnés :
Single-Cell Gene Expression Analysis
Diagnostic
5
Dermatophytose
Infection fongique
Culture fongique
Examen microscopique
Lésions cutanées
Démangeaisons
Biopsie cutanée
Diagnostic
Tests sérologiques
Infection fongique
Symptômes
5
Onychomycose
Infection fongique
Symptômes systémiques
Infection fongique
Propagation
Contact direct
Prévention
5
Hygiène personnelle
Prévention
Chaussures
Infection fongique
Douches publiques
Infection fongique
Traitements
5
Durée du traitement
Infection fongique
Remèdes maison
Infection fongique
Infections récurrentes
Traitement
Prévention
Infection fongique
Complications
5
Complications
Infection bactérienne
Cicatrices
Infection fongique
Infection systémique
Immunodéprimé
Qualité de vie
Infection fongique
Facteurs de risque
5
Facteurs de risque
Hygiène
Immunodéprimé
Infection fongique
Diabète
Infection fongique
Athlètes
Infection fongique
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"position": 8,
"acceptedAnswer": {
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"@type": "Question",
"name": "Y a-t-il des symptômes systémiques associés ?",
"position": 9,
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"name": "Les lésions peuvent-elles se propager ?",
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"name": "Les chaussures peuvent-elles favoriser les infections ?",
"position": 12,
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"name": "Les animaux de compagnie peuvent-ils transmettre ces infections ?",
"position": 13,
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"position": 15,
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}
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"@type": "Question",
"name": "Quels traitements sont efficaces contre les infections fongiques ?",
"position": 16,
"acceptedAnswer": {
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"text": "Les antifongiques topiques ou oraux sont généralement prescrits pour traiter ces infections."
}
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{
"@type": "Question",
"name": "Combien de temps dure le traitement habituel ?",
"position": 17,
"acceptedAnswer": {
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"text": "Le traitement peut durer de quelques semaines à plusieurs mois selon la gravité."
}
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"@type": "Question",
"name": "Les remèdes maison sont-ils efficaces ?",
"position": 18,
"acceptedAnswer": {
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}
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{
"@type": "Question",
"name": "Les infections récurrentes nécessitent-elles un traitement différent ?",
"position": 19,
"acceptedAnswer": {
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"name": "Les traitements préventifs existent-ils ?",
"position": 20,
"acceptedAnswer": {
"@type": "Answer",
"text": "Des traitements préventifs peuvent être envisagés pour les personnes à risque élevé d'infection."
}
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{
"@type": "Question",
"name": "Quelles complications peuvent survenir avec ces infections ?",
"position": 21,
"acceptedAnswer": {
"@type": "Answer",
"text": "Des complications comme des infections secondaires bactériennes peuvent survenir si non traitées."
}
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{
"@type": "Question",
"name": "Les infections peuvent-elles causer des cicatrices ?",
"position": 22,
"acceptedAnswer": {
"@type": "Answer",
"text": "Oui, des infections cutanées sévères peuvent entraîner des cicatrices permanentes."
}
},
{
"@type": "Question",
"name": "Y a-t-il un risque d'infection systémique ?",
"position": 23,
"acceptedAnswer": {
"@type": "Answer",
"text": "Rarement, mais des infections fongiques peuvent devenir systémiques chez les immunodéprimés."
}
},
{
"@type": "Question",
"name": "Les infections peuvent-elles affecter la qualité de vie ?",
"position": 24,
"acceptedAnswer": {
"@type": "Answer",
"text": "Oui, les démangeaisons et l'inconfort peuvent affecter la qualité de vie des patients."
}
},
{
"@type": "Question",
"name": "Les complications sont-elles fréquentes ?",
"position": 25,
"acceptedAnswer": {
"@type": "Answer",
"text": "Les complications sont rares si l'infection est traitée rapidement et correctement."
}
},
{
"@type": "Question",
"name": "Quels sont les principaux facteurs de risque ?",
"position": 26,
"acceptedAnswer": {
"@type": "Answer",
"text": "Les facteurs incluent l'humidité, le contact avec des animaux infectés et une mauvaise hygiène."
}
},
{
"@type": "Question",
"name": "Les personnes immunodéprimées sont-elles plus à risque ?",
"position": 27,
"acceptedAnswer": {
"@type": "Answer",
"text": "Oui, les personnes immunodéprimées sont plus susceptibles de développer des infections fongiques."
}
},
{
"@type": "Question",
"name": "Le diabète augmente-t-il le risque d'infection ?",
"position": 28,
"acceptedAnswer": {
"@type": "Answer",
"text": "Oui, le diabète peut affaiblir le système immunitaire et augmenter le risque d'infections fongiques."
}
},
{
"@type": "Question",
"name": "Les athlètes sont-ils plus exposés ?",
"position": 29,
"acceptedAnswer": {
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"text": "Oui, les athlètes, en raison de l'humidité et du contact, sont plus exposés aux infections fongiques."
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{
"@type": "Question",
"name": "Les enfants sont-ils plus vulnérables ?",
"position": 30,
"acceptedAnswer": {
"@type": "Answer",
"text": "Oui, les enfants peuvent être plus vulnérables en raison de leur système immunitaire en développement."
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}
Expert en Médecine, Optimisation des Parcours de Soins et Révision Médicale
Validation scientifique effectuée le 17/02/2025
Contenu vérifié selon les dernières recommandations médicales
1 publication dans cette catégorie
Affiliations :
Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands.
Institute of Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands.
Institute of Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands.
Microbiology, Parasitology and Pathology Post-Graduation Program, Department of Basic Pathology, Federal University of Paraná, Curitiba, Brazil.
Center of Expertise in Mycology of Radboudumc/Canisius Wilhelmina Hospital, Nijmegen, The Netherlands.
Foundation Atlas of Clinical Fungi, Hilversum, The Netherlands.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands.
Thermo Fisher Scientific, Landsmeer, The Netherlands.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands.
Thermo Fisher Scientific, Landsmeer, The Netherlands.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Microbiology, Parasitology and Pathology Post-Graduation Program, Department of Basic Pathology, Federal University of Paraná, Curitiba, Brazil.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Institute of Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Westerdijk Fungal Biodiversity Institute, Utrecht, The Netherlands. s.ahmed@westerdijkinstitute.nl.
Foundation Atlas of Clinical Fungi, Hilversum, The Netherlands. s.ahmed@westerdijkinstitute.nl.
Faculty of Medical Laboratory Sciences, University of Khartoum, Khartoum, Sudan. s.ahmed@westerdijkinstitute.nl.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Nitte (deemed to be University), Nitte University Centre for Science Education and Research, Mangaluru, Karnataka, India.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Nitte (deemed to be University), Nitte University Centre for Science Education and Research, Mangaluru, Karnataka, India.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Nitte (deemed to be University), KS. Hedge Medical Academy, Mangaluru, Karnataka, India.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Nitte (deemed to be University), Nitte University Centre for Science Education and Research, Mangaluru, Karnataka, India.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Department of Ecology, College of Life Sciences, Institute of Fungus Resources, Guizhou University, Guiyang, China.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Department of Ecology, College of Life Sciences, Institute of Fungus Resources, Guizhou University, Guiyang, China.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Department of Ecology, College of Life Sciences, Institute of Fungus Resources, Guizhou University, Guiyang, China.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Department of Microbiology, Guiyang College of Traditional Chinese Medicine, Guiyang, China.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Department of Microbiology, Guiyang College of Traditional Chinese Medicine, Guiyang, China.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Department of Ecology, College of Life Sciences, Institute of Fungus Resources, Guizhou University, Guiyang, China. swallow1128@126.com.
Publications dans "Arthrodermataceae" :
1 publication dans cette catégorie
Affiliations :
Department of Ecology, College of Life Sciences, Institute of Fungus Resources, Guizhou University, Guiyang, China.
Publications dans "Arthrodermataceae" :
Single-cell (SC) gene expression analysis is crucial to dissect the complex cellular heterogeneity of solid tumors, which is one of the main obstacles for the development of effective cancer treatment...
scMuffin provides a series of functions to calculate qualitative and quantitative scores, such as: expression of marker sets for normal and tumor conditions, pathway activity, cell state trajectories,...
The analyses offered by scMuffin and the results achieved in the case study show that our tool helps addressing the main challenges in the bioinformatics analysis of SC expression data from solid tumo...
A common feature of single-cell RNA-seq (scRNA-seq) data is that the number of cells in a cell cluster may vary widely, ranging from a few dozen to several thousand. It is not clear whether scRNA-seq ...
We addressed this question by performing scRNA-seq and poly(A)-dependent bulk RNA-seq in comparable aliquots of human induced pluripotent stem cells-derived, purified vascular endothelial and smooth m...
Findings of the current study provide a quantitative reference for designing studies that aim for identifying DEGs for specific cell clusters using scRNA-seq data and for interpreting results of such ...
There is a wealth of software that utilizes single-cell RNA-seq (scRNA-seq) data to deconvolve spatial transcriptomic spots, which currently are not yet at single-cell resolution. Here we provide prot...
Normalization is a crucial step in the analysis of single-cell RNA-sequencing (scRNA-seq) counts data. Its principal objectives are reduction of systematic biases primarily introduced through technica...
The widely adopted bulk RNA-seq measures the gene expression average of cells, masking cell type heterogeneity, which confounds downstream analyses. Therefore, identifying the cellular composition and...
We propose a new deconvolution algorithm, DSSC, which infers cell type-specific gene expression and cell type proportions of heterogeneous samples simultaneously by leveraging gene-gene and sample-sam...
DSSC provides a practical and promising alternative to the experimental techniques to characterize cellular composition and heterogeneity in the gene expression of heterogeneous samples....
Cell clustering is a prerequisite for identifying differentially expressed genes (DEGs) in single-cell RNA sequencing (scRNA-seq) data. Obtaining a perfect clustering result is of central importance f...
Here, we propose single-cell minimum enclosing ball (scMEB), a novel and fast method for detecting single-cell DEGs without prior cell clustering results. The proposed method utilizes a small part of ...
We compared scMEB to two different approaches that could be used to identify DEGs without cell clustering. The investigation of 11 real datasets revealed that scMEB outperformed rival methods in terms...
The aim of this study was to reveal the key genes associated with macrophage polarization in liver cancer....
Data were downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas databases (TCGA). R package Seurat 4.0 was used to preprocess the downloaded single-cell sequencing data, princi...
Two thousand highly variable genes were obtained after the normalization of single-cell profiles. In all, 16 principal components and 15 cell clusters were obtained. Monocytes and macrophages were the...
The key genes associated with macrophage polarization, namely CD53, TGFBI, S100A4, pyruvate kinase M, LSP1, and SPP1, may be potential therapeutic targets for liver cancer....
As an essential regulator of type I interferon (IFN) response, TMEM173 participates in immune regulation and cell death induction. In recent studies, activation of TMEM173 has been regarded as a promi...
Quantitative real-time PCR (qRT-PCR) and western blotting (WB) were applied to determine the mRNA and protein levels of TMEM173 in peripheral blood mononuclear cells (PBMCs). TMEM173 mutation status w...
The mRNA and protein levels of TMEM173 were increased in PBMCs from B-ALL patients. Besides, frameshift mutation was presented in TMEM173 sequences of 2 B-ALL patients. ScRNA-seq analysis identified t...
Our findings provide insights into the transcriptomic features of TMEM173 in the BM of high-risk B-ALL patients. Targeted activation of TMEM173 in specific cells might provide new therapeutic strategi...
The poor prognosis of sepsis warrants the investigation of biomarkers for predicting the outcome. Several studies have indicated that PANoptosis exerts a critical role in tumor initiation and developm...
We obtained Sepsis samples and scRNA-seq data from the GEO database. PANoptosis-related genes were subjected to consensus clustering and functional enrichment analysis, followed by identification of d...
Unsupervised clustering analysis using 16 PANoptosis-related genes identified three subtypes of sepsis. Kaplan-Meier analysis showed significant differences in patient survival among the subtypes, wit...
We developed a machine learning based Boruta algorithm for profiling PANoptosis related subgroups with in predicting survival and clinical features in the sepsis....
Macrophages play an important role in the occurrence and development of atherosclerosis. However, few existing studies have deliberately analyzed the changes in characteristic genes in the process of ...
Carotid atherosclerotic plaque single-cell RNA (scRNA) sequencing data were analyzed to define the cells involved and determine their transcriptomic characteristics. KEGG enrichment analysis, CIBERSOR...
Nine cell clusters were identified. M1 macrophages, M2 macrophages, and M2/M1 macrophages were identified as three clusters within the macrophages. According to pseudotime analysis, M2/M1 macrophages ...
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