Skip to content
#gene editing Open access

Mitoxyperilysis-ARDS: analysis code, six-layer gene signature, and frozen statistical outputs for "Mitoxyperilysis-consistent L4 de-protection in human sepsis-associated ARDS blood: a compartment- and etiology-bounded transcriptomic boundary map" (archive v4; manuscript v2.30)

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

This archive supports the manuscript "Mitoxyperilysis-consistent L4 de-protection in human sepsis-associated ARDS blood: a compartment- and etiology-bounded transcriptomic boundary map" (submission target: Critical Care, BMC; manuscript version v2.30, September 2026). Contents: (1) complete analysis code (R 4.6.1 / Python 3.11) covering score construction (ssGSEA/UCell), four-cohort meta-analysis with Hartung-Knapp inference, leave-one-gene-out robustness, three-method deconvolution, single-cell localization (Scissor, diffusion pseudotime), transcription-factor activity inference (decoupleR/DoRothEA, PROGENy), Mendelian randomization (eQTLGen instruments; ARDS GWAS GCST90700332; FinnGen R13 endpoints), pharmacological layers (DSigDB, CMap/LINCS, AutoDock Vina docking, DGIdb/Open Targets), and permissive-state cross-disease comparisons; (2) the six-layer mitoxyperilysis gene signature (GMT/CSV); (3) frozen statistical outputs (module CSV files plus eTables) serving as the audit anchor for every statistic reported in the manuscript; (4) data-lineage documentation, the pre-specified analysis plan, and contemporaneous analysis logs. Version v4 changes relative to v3: the frozen-output set and analysis code have been extended to cover the R35 extensions (sepsis-prognosis survival analysis in GSE65682; protein-layer coverage screen including pQTL colocalisation and Mendelian randomisation for the HMGCR-RhoA axis; structured plasma/phospho/ATAC screens), the R37 analyses, the R39 Task F.1 NETosis orthogonality benchmark, and the R40 sensitivity-endpoint analyses. The data-lineage document in metadata.zip has been updated accordingly (raw-archive manifest now 228 entries). A read-only metadata verifier for the associated OSF registration is included in the code archive. All frozen values reported in manuscript versions up to v2.30 are represented. Title correspondence: earlier manuscript versions and the associated OSF registration (osf.io/p3wcy, registered 2026-08-28) carry the former title "...in human sepsis-associated ARDS neutrophils: a shared stress program constrained by compartment and etiology". The first revision was wording-level (the compartment claim was narrowed to blood; the subtitle was removed) and altered no data, statistic, direction, or conclusion. The title was subsequently revised twice more, again without any change to the data, statistics, effect directions, frozen outputs, or conclusions: at v2.28 the headline claim was re-scoped from a uniform blood signature to a compartment- and etiology-bounded boundary map, the description of which was already reported, with the composite MAS score moved to a secondary readout in the abstract and the L4 arm named as the discriminating signal; and at v2.29 the modality name "mitoxyperilysis" was restored to the headline, with the v2.28 boundary-map framing retained as the subtitle. The OSF registration at osf.io/p3wcy was not retro-edited; the divergence between the submission title and the registered title is disclosed in the registered amendment osf.io/2qkg3 (doi:10.17605/OSF.IO/2QKG3, 2026-09-12) and in the manuscript itself. All primary datasets are publicly available (GEO accessions GSE66890, GSE32707, GSE10474, GSE76293, GSE235046, GSE200848, GSE326212, GSE145926, GSE151263, GSE167363, GSE188288, GSE65682; PRIDE PXD060437; Metabolomics Workbench ST002738; GWAS summary statistics via GWAS Catalog GCST90700332, FinnGen R13 and eQTLGen official portals) and are NOT redistributed here. GWAS summary statistics are not redistributed because FinnGen and eQTLGen distribute them under their own access terms; use the official portals. This record is the fourth version of a continuously versioned archive; the concept DOI 10.5281/zenodo.22135916 always resolves to the latest version, and the manuscript cites the concept DOI.

View source

Similar papers

#computer vision Conference Aug 2008

A Preliminary Roadmap for Empirical Research on Agile Software Development

Some claim that especially in the field of agile software development the research lags years behind of the practice. In this paper, we characterize the status and main challenges for research on agile software development, and propose a preliminary roadmap, focusing on providing more empirical research, primarily on experienced agile teams and organizations, connecting better to existing streams of research in more established fields, giving more attention to management-oriented approaches, and finally give more emphasis to the core ideas in agile software development in order to increase our understanding. We hope that this preliminary roadmap serves as a starting point for creating a common research agenda and enables the generation of fruitful discussions and research results from the field.

Torgeir Dingsøyr, T. Dybå, P. Abrahamsson · 92 citations · ⚡7
#computer vision Book Open access Mar 2017

On the Unhappiness of Software Developers

The results indicate that software developers are a slightly happy population, but the need for limiting the unhappiness of developers remains, and 219 factors representing causes of unhappiness while developing software are identified.

D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al. · 84 citations · ⚡6
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Review Apr 2024

AI-powered Code Review with LLMs: Early Results

The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.

Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al. · 62 citations · ⚡3
#computer vision Conference Aug 2008

Scrum in a Multiproject Environment: An Ethnographically-Inspired Case Study on the Adoption Challenges

Agile methods continue to gain popularity. In particular, the Scrum method appears to be on the verge of becoming a de-facto standard in the industry, leading the so called Agile movement. While there are success stories and recommendations, there is little scientifically valid evidence of the challenges in the adoption of Agile methods in general, and Scrum in particular. Little, if anything, is empirically known about the application and adoption of Scrum in a multi-team and multi-project situation. The authors carried out an ethnographically informed longitudinal case study in industrial settings and closely followed how the Scrum method was adopted in a 20-person department, working in a simultaneous multi-project R&D environment. Altogether 10 challenges pertinent to the case of multi-team multi-project Scrum adoption were identified in the study. The authors contend that these results carry great relevance for other industrial teams. Future research avenues arising from the study are indicated.

A. Marchenko, P. Abrahamsson · 59 citations · ⚡11

Related blog posts

GPT-Lab Sep 17, 2026

Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering

AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.

MIT News · Artificial Intelligence Sep 14, 2026

New method enables AI for safety-critical situations

The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.