ArticleThe Analyst2025
Advancing atmospheric solids analysis probe mass spectrometry applications: a multifaceted approach to optimising clinical data set generation.
Article in The Analyst, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- Optimising the choice of normalisation method for use in machine-learning classification of human blood plasma ambient ionisation mass spectra.International journal of mass spectrometry · 2026Article
- Prediction of clinical outcomes of ST-elevated myocardial infarction patients using atmospheric solids analysis probe mass spectrometry and machine learning.The Analyst · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
The use of rapid mass spectrometry techniques, such as atmospheric-solids-analysis-probe mass spectrometry (ASAP-MS), in the analysis of metabolite patterns in clinical samples holds significant promise for developing new diagnostic tools and enabling rapid disease screening. The rapid measurement times, ease of use, and relatively low cost of ASAP-MS makes it an appealing option for use in clinical settings. However, despite the potential of such approaches, a number of important experimental considerations are often overlooked. As well as instrument-specific choices and settings, these include the treatment of background noise and/or contaminant peaks in the mass spectra, and the influence of consumables, different users, and batch effects more generally. The present study assesses the impact of these various factors on measurement accuracy and reproducibility, using human brain and cerebrospinal fluid samples as examples. Based on our results, we make a series of recommendations relating to optimisation of measurement and cleaning protocols, consumable selection, and batch effect detection and correction, in order to optimise the reliability and reproducibility of ASAP-MS measurements in clinical settings.
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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.