ArticleMethods in molecular biology (Clifton, N.J.)2023
Microcomputed Tomography to Visualize and Quantify Fungal Infection Burden and Inflammation in the Mouse Lung Over Time.
Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Can micro-CT distinguish between solid lung tumors? A comparative evaluation including solid adenocarcinoma, non-keratinizing squamous cell carcinoma, and carcinoid tumor.Journal of pathology and translational medicine · 2026Article
- Fungal infections in focus: accelerating non-invasive imaging from preclinical insights to clinical breakthroughs.Npj imaging · 2025Review
- Pulmonary Hypertension Secondary to Fungal Infections: Underexplored Pathological Links.Infectious disease reports · 2025Article
- Preclinical Models for Cryptococcosis of the CNS and Their Characterization Using In Vivo Imaging Techniques.Journal of fungi (Basel, Switzerland) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pulmonary mycoses are an important threat for immunocompromised patients, and although current treatments are effective, they suffer from multiple limitations and fail to further reduce mortality. With the increasing immunocompromised population and increased antifungal resistance, fungal infection research is more relevant than ever. In preclinical respiratory fungal infection research, animal models are indispensable. However, too often researchers still rely on endpoint measurements to assess fungal burden while the dynamics of disease progression are left undiscovered. To open up this "black box", microcomputed tomography (μCT) can be implemented to longitudinally visualize lung pathology in a noninvasive way and to quantify μCT-image derived biomarkers. That way, disease onset, progression, and responsiveness to treatment can be followed up with high resolution spatially and temporally in individual mice, increasing statistical power. Here, we describe a general method for the use of low-dose high-resolution μCT to longitudinally visualize and quantify lung pathology in mouse models of respiratory fungal infections, applied to mouse models of aspergillosis and cryptococcosis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.