bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.05.09.653091

An All-In-One Software Solution for Automated Processing of LA-ICP-TOF-MS datasets

Crawford, A. M.·Zee, D. Z.·Jin, Q.·Sue, A.·Sinha, N.·Ahn, S. H.·MacRenaris, K. W.·O'Halloran, T.
View original source ↗Export metadata ↓

Abstract

LA-ICP-TOF-MS provides rapid, high resolution elemental analysis of biological and non-biological samples. However, accurate real-time data analysis frequently requires the user to account for several instrumental and experimental variables that can change during data acquisition. AutoSpect is a novel software tool designed to automate the processing and fitting of LA-ICP-TOF-MS data, addressing key challenges such as time-dependent spectral drift, instrument sensitivity drift calibration inaccuracies, and peak deconvolution, enabling researchers to rapidly and accurately process complex datasets. The tool is optimized to be robustly applicable across scientific fields (e.g., geochemistry, biology, and materials science), providing a streamlined solution for end users seeking to maximize the potential of LA-ICP-TOF-MS for high-resolution elemental mapping and isotopic analysis. Significance to JAASAnalysis of fast transient signals using laser ablation inductively coupled plasma time-of-flight mass spectrometry (LA-ICP-TOF-MS) has become mainstream for elemental mapping. Advancements in LA-ICP-TOF-MS technology continue to accelerate the collective understanding of the role inorganic chemistry plays in dynamic processes. To ensure accurate quantitative results, the vast amount of complex spectral data generated requires elegant solutions to perform a variety of functions including data partitioning, peak fitting, drift correction, mass-to-charge calibration, peak profiling, and spectral fitting. AutoSpect is an all-in-one software solution that provides high level automation with a user-friendly graphical interface to perform complex data analyses for ICP-TOF-MS datasets.

Source connections

Explore related subjects

scientific communication and educationPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Crawford, A. M., Zee, D. Z., Jin, Q., Sue, A., Sinha, N., Ahn, S. H., MacRenaris, K. W., O'Halloran, T.. 2025-05-12. An All-In-One Software Solution for Automated Processing of LA-ICP-TOF-MS datasets. https://doi.org/10.1101/2025.05.09.653091

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Auditing Biomedical Literature with Blinded AI Peer Review: Where Peer Review Works, Where It Fails, and How to Strengthen It

Biomedical publishing has grown more than elevenfold since 1991, outstripping human peer review. Unblinded language models cannot audit this literature objectively because they recognize famous authors and journals from training memory. We built BARS (Blinded AI Review System), an automated referee that strips titles, author names, institutions, journal headers, and dates before grading full-text manuscripts on a 10-point scale covering methods, evidence, biology, and reproducibility. We used BARS to generate 1,874 blind reviews across 1,714 unique papers. BARS passed 100% of verified sound controls, caught 77% to 91% of internally flawed papers, eliminated a +0.35-point prestige boost, and more than doubled human referee consistency. Across 320 recent open-access articles (2020-2025) from eight fields, 54% failed on core scientific rigor (<5.0/10; 41% excluding megajournals). Revision at selective journals improved preprints more than twice as much as revision at commercial megajournals (+0.62 vs. +0.30 points; baseline-adjusted p = 0.033), and BARS recalled 98% of unresolved human referee critiques across 100 open-review papers. Across 915 date-blinded papers from 1991 to 2025, average scores fell from 7.6/10 to 5.8/10 as megajournals and template database studies expanded. Blinded self-audits of 238 papers by two senior authors -- and of this manuscript itself -- caught real statistical, control, and table errors in our own work. At four cents per paper, BARS offers a practical quality check for authors, journals, and readers (https://veg.github.io/BARS/).

scientific communication and education↗
bioRxiv2026

From Problems to Solutions: How Self-Questions Drive Strong Scientific Reasoning

Metacognition, or awareness and control of thinking, is essential for problem solving because it helps solvers select strategies for learning and decide when to enact them (planning), check their understanding in the moment (monitoring), and assess effectiveness of solutions and learning strategies (evaluating). Most studies that examine metacognition do so retrospectively, leaving a critical gap in how metacognition is used in-the-moment for problem solving. In this study, we utilized a think-aloud interview approach to capture and characterize the metacognitive skills that senior undergraduate life science students at three institution types in the United States used spontaneously while solving challenging biology problems. We found that the students (n = 39) displayed a wide variety and quantity of monitoring, some evaluating, and nearly no planning skills while creating a solution backed with high-quality reasoning. Students frequently used self-questions to monitor and evaluate their thinking. We found that self-questioning is a critical skill for generating solutions, but it only moves problem solving forward if the student asks and correctly answers the self-question out loud. This study illustrates how self-questioning and other metacognitive regulation skills provide links to bridge the gap between a student's prior knowledge and specific features of a challenging problem. Based on our student data, we conceptualized a model of metacognitive phases during problem solving with high-quality reasoning. Finally, we present a self-question scaffold to facilitate the proposed phases (planning, monitoring, reasoning, and evaluating) so educators can equip students with metacognitive and scientific reasoning tools for effective problem solving.

scientific communication and education↗
bioRxiv2026

Preprint solicitation as a natural experiment in scholarly publishing

Preprinting is a growing and increasingly recognized mechanism for scientific communication and productivity and a way to facilitate global access to science. The interplay of preprinting practices with formal peer-reviewed publication is an open question that is now tractable to targeted analysis. Here, we take advantage of nearly a decade of preprint solicitation at Proceedings B to address this question, which offers a quasi-experimental setting for comparing outcomes for solicited preprints and traditionally submitted manuscripts. We used submission records from 15,368 manuscripts from 2018-2024 to assess whether preprint solicitation affects acceptance rates, journal scope, author geographic diversity, and post-publication uptake. Solicited manuscripts were accepted at nearly twice the rate of traditional submissions and received more downloads and citations after publication. Submission topics were broadly similar between the two routes, though solicited manuscripts showed marginally greater subject diversity. Geographic disparities favoring the Global North persisted, but acceptance rates for solicited manuscripts converged across regions, narrowing the gap seen in traditional submissions. These findings extend earlier work on this initiative and indicate that editor-driven solicitation can identify high-quality preprints, broaden geographic representation, and increase research visibility, offering a replicable model for journals seeking to diversify authorship while maintaining editorial standards.

scientific communication and education↗