Nature Protocols

Metabolomics enables the profiling of small-molecule metabolites and thereby captures the biochemical state of a living organism at a given moment and enables to monitor its cellular responses to stimuli. This technique has become a powerful tool in pharmaceutical research, the food industry, and microbial research. Metabolomics aims to obtain an unbiased metabolic profile; however, this is complicated by compound instability, complex and often extensive sample processing, and nonlinear responses in mass spectrometry. Therefore, correcting for metabolite loss and mass spectrometry-related artifacts is essential, typically achieved through relative quantification against an isotopically labelled internal standard for each metabolite of interest. This article describes how to produce 13C-labelled yeast extract and its use as internal standard for metabolomics. More specifically, it provides step-by-step protocols for the fed-batch fermentation, quenching, metabolite extraction, and LC-MS and GC-MS characterization of the internal standard. It also includes a protocol explaining how to use the internal standard for the quantification of metabolites in yeast samples.

Whole-genome sequencing identifies focal DNA amplifications with base-pair resolution but cannot determine whether amplified sequences reside on extrachromosomal DNA (ecDNA, also known as double minutes) or within chromosomally integrated homogeneously staining regions (HSRs). DNA fluorescence in situ hybridization (DNA-FISH) metaphase spreads remain the gold standard for distinguishing these amplification states at single-cell resolution. Here, we present a detailed protocol for DNA-FISH metaphase spreads using human cancer cell lines, encompassing cell culture, metaphase arrest, hypotonic treatment, fixation, chromosome spreading, fluorescent probe hybridization, and fluorescence imaging. The protocol incorporates intermediate quality-control steps to verify successful chromosome dispersion and optimize metaphase spread quality, making the workflow accessible to laboratories without specialized cytogenetics expertise. Results demonstrate clear visualization of ecDNA and HSR amplification states using locus-specific probes and illustrate common technical artifacts that can affect interpretation. This protocol provides a robust and reproducible approach for studying the structural organization of oncogene amplification in cancer cells.

This protocol describes the workflow for the preparation of tissue samples for proteome and phosphoproteome analyses using mass spectrometry. The tissue samples are cryogenically pulverized and homogenized in a sucrose-based buffer to ensure proper tissue disruption. For depletion of lipid contaminants, proteins are purified using chloroform-methanol precipitation, followed by a resuspension in a urea-based buffer for enzymatic digestion. Peptides are desalted and enriched for phosphopeptides prior LC-MS/MS analysis. The workflow was developed for skin biopsies but is compatible with a broad range of tissue types. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=51 SRC="FIGDIR/small/732915v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@6a44aforg.highwire.dtl.DTLVardef@c34dc9org.highwire.dtl.DTLVardef@27d7ecorg.highwire.dtl.DTLVardef@1d1038e_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

Single-cell and single-nucleus RNA sequencing have become increasingly widespread, creating a significant demand for accessible analysis tools in research laboratories. Despite this need, the bioinformatics expertise required for such analyses remains rare. Cell-Hub addresses this gap by enabling single-cell data analysis for all researchers, regardless of computational background. Cell-Hub is a comprehensive, free, and open-source framework built on R/Shiny and distributed as a Docker image, integrating Seurat 5, CellChat 2, and Monocle 3 within a unified graphical interface. It supports all essential steps of single-cell RNA-seq analysis: data loading, quality control, normalization, clustering, multi-dataset integration, differential expression, and biomarker detection. Cell-Hub further incorporates ligand-receptor interaction inference powered by GaspouDB, a consolidated database of 11,563 mouse and 9,604 human interactions derived from CellChat, CellPhoneDB, CellTalkDB, and MultiNicheNet as well as trajectory inference via Monocle 3 and spatial transcriptomics analysis for 10X Visium datasets. All analyses produce publication-ready visualizations with flexible export options. By integrating these analytical frameworks into a single, intuitive interface requiring no programming expertise, Cell-Hub represents a significant step toward democratizing single-cell genomics for the broader research community.

Three-dimensional (3D) spheroid models have become essential in cancer biology, drug screening, and tissue engineering. However, their small size, fragile structure, and tendency to disintegrate during routine histoprocessing present persistent technical challenges. Conventional paraffin embedding often results in tissue fragmentation, loss of spatial orientation, and poor section quality, whereas cryosectioning often compromises cellular morphology. Here, we present a robust, cost-effective protocol for preserving and sectioning fragile 3D spheroids, resulting in high-quality histological sections with intact architecture and excellent cellular detail. The method involves optimized handling and embedding procedures that stabilize spheroids during standard formalin fixation, paraffin infiltration, and microtomy, eliminating mechanical distortion and preserving spherical integrity for consistent sectioning. We demonstrate successful application across different cell line spheroids, with subsequent compatibility with hematoxylin and eosin (H&E) staining protocols. Compared to conventional methods, our approach significantly reduces sample loss, improves inter-section reproducibility, and preserves fine structural features such as necrotic cores, proliferative zones, and extracellular matrix components. This protocol provides a reliable, accessible solution for routine histological analysis of fragile 3D spheroids, facilitating more accurate morphological and molecular assessment in translational research settings. Key featuresO_LIMaintains spheroid integrity: Prevents mechanical distortion, fragmentation, and loss of spatial orientation during processing. C_LIO_LISignificantly reduces sample loss: Decreases failure rate compared to traditional methods, conserving valuable samples. C_LIO_LIBroad spheroid compatibility: Works effectively with primary tumor-derived, stem cell-derived, and co-culture spheroid models. C_LIO_LIEnables high-quality sectioning and staining: Delivers consistent, reproducible sections that are fully compatible with H&E, IHC, and IF. C_LI Graphical overview O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/743094v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1670c4org.highwire.dtl.DTLVardef@145810aorg.highwire.dtl.DTLVardef@1accb1org.highwire.dtl.DTLVardef@17481c0_HPS_FORMAT_FIGEXP M_FIG C_FIG

Very short RNAs play critical roles in modern biology, and are thought to have been crucial for genome replication during the origin of life. Next-generation sequencing is an essential tool for characterizing pools of small RNAs, but current library preparation methods suffer from strong size and sequence biases. Here we present tinyRNA-seq, an optimized library preparation method designed to minimize length- and sequence-dependent capture bias enabling the sequencing of RNA fragments as short as 2 nucleotides. We use degenerate adaptor regions to reduce ligation sequence bias and facilitate unique molecular identifier (UMI) installation. We benchmarked tinyRNA-seq against commercial kits using a model primordial RNA genome consisting of hundreds of defined oligonucleotides ranging from 2 to 12 nucleotides. tinyRNA-seq reproduced the input RNA distribution without the size and sequence bias of the commercial kits. tinyRNA-seq also enables the detection of de novo oligonucleotide generation, an important process for the origins of life. Applied to biologically derived small RNAs including miRNAs, piRNAs, and cityRNAs, tinyRNA-seq showed significantly lower capture bias and recovered a wider range of sequences than commercial kits. tinyRNA-seq may thus provide a more complete and quantitatively accurate representation of small RNAs from both biological and chemical sources. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=94 SRC="FIGDIR/small/743385v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@95ee64org.highwire.dtl.DTLVardef@155fb06org.highwire.dtl.DTLVardef@1d3665forg.highwire.dtl.DTLVardef@1e61404_HPS_FORMAT_FIGEXP M_FIG C_FIG

Animal cell-cultured ingredients are entering the EU and UK pet food markets under frameworks that do not require pre-market, ingredient-level safety assessments, creating an ethical need for transparent safety disclosure. We present the first public safety dossier for this sector, describing the proprietary mouse embryonic stem cell line PE25 and its derived, non-viable cellular and conditioned media ingredient produced in food and feed-grade media. PE25 characterization confirmed Mus musculus identity, sterility, absence of mycoplasma and replication-competent retroviruses, and stable growth. Doxorubicin-induced p53 stress testing, CD44/BMI1 profiling, and soft agar assays showed no cancer-like traits and a non-tumorigenic profile; the final ingredient contains no viable cells. Independent OECD TG 471 and 487 assays confirmed non-genotoxicity. Heavy metals, biogenic amines, solvents, and chemical residues were below regulatory limits. Given process variability, we recommend case-by-case safety evaluation and propose this dossier as a model for responsible commercialization.

Cryogenic electron microscopy (cryoEM) is now routinely used for high-resolution structure determination of biological macromolecules. However, many biological specimens exhibit varying degrees of preferred orientation on cryoEM grids, resulting in uneven sampling of three-dimensional Fourier space. This orientation bias produces anisotropic reconstruction artifacts and, in severe cases, can exacerbate particle misalignment during iterative refinement, thereby limiting the success rate of near-atomic resolution cryoEM structure determination. This protocol provides a practical guide for applying spIsoNet, a self-supervised deep-learning method, to mitigate preferred-orientation issues in cryoEM reconstructions. We describe two complementary workflows: (1) map Anisotropy Correction to correct anisotropic artifacts of cryoEM maps and (2) particle Misalignment Correction, which integrates spIsoNet with RELION external reconstruction to improve particle-pose estimation. We demonstrate these workflows using two influenza hemagglutinin (HA) trimer datasets representing moderate and severe degrees of preferred-orientation bias. The protocol includes installation instructions, parameter-selection guidance, quality-control checkpoints and troubleshooting advice, and can typically be completed in ~7 hours on a workstation equipped with four NVIDIA A100 GPUs. Together, these workflows provide step-by-step guidance for using the open-source spIsoNet software to mitigate the preferred-orientation problem directly from experimental data.

Background: Transcranial magnetic stimulation (TMS) targeting the left dorsolateral prefrontal cortex (dlPFC) is an established treatment option in major depressive disorder. One of the most common approaches for targeting the dlPFC is the Beam F3 method, which determines the stimulation site (F3Beam) as a function of external cranial measurements. Precise knowledge of the individual stimulation site is essential for imaging-based analyses of TMS effects. However, due to the method's reliance on individual anatomy, retrospective identification of F3Beam targets across cohorts is challenging, limiting the analysis of existing datasets. We developed a scalable method to reconstruct subject-specific F3Beam target locations for e-field simulations based on structural imaging. Methods: High-resolution three-dimensional (3D) T1-weighted MRI was used to generate individual scalp meshes via the ''Simulation of Non-Invasive Brain Stimulation'' (SimNIBS) software. Subject-specific anatomical distances and coordinates of interest were measured geodesically using a Python-based script to reconstruct the individual F3Beam targets. Validation included a retrospective comparison between digital geodesic measurements and manual cranial measurements in 20 patients and a prospective comparison with MR-visible scalp markers in 2 healthy controls. To assess the impact of our targeting algorithm on e-field simulations, volumetric e-field maps based on three potential targets (F3Beam, F3MNI, F3Geo) were generated in SimNIBS and compared using voxel-wise statistics in SPM12. Results: Retrospective analysis revealed a systematic bias towards higher in vivo measurements compared to digital geodesic measurements, though deviations in the final distances determining F3Beam (xBeam and yBeam) were minimal ({Delta}xBeam: 0.11 {+/-} 0.08 cm; {Delta}yBeam: 0.14 {+/-} 0.21 cm). Prospective validation demonstrated that F3Beam coordinates better matched in vivo coil positions than group-template-derived targets (F3MNI). Group-level analysis showed method-dependent clustering of coil positions with corresponding voxel-wise e-field differences. Conclusions: Individualized geodesic measurements may enable accurate, scalable and retrospective identification of Beam F3 targets and coil orientations. This approach may yield more accurate e-field simulations than group-template based targeting and provides a practical method for retrospective analysis of existing TMS treatment cohorts. This could be leveraged to identify response predictors or imaging-based biomarkers of treatment response.

Single-cell RNA sequencing now routinely produces detailed maps of cell types and states, but interpreting a finished project remains harder than it should be. Once the analysis is done, the results are usually handed over as static reports, figure panels and supplementary tables. A biologist who later wants to revisit an annotation, recompute a cell-type proportion or check whether a pathway is specific to one group typically has to return to a bioinformatician rather than explore the data directly. We developed scSpark to close this gap. The platform takes the completed outputs of a single-cell project: cell annotations, embeddings, differential-expression tables, trajectories, cell-cell communication networks and enrichment result and serves them through a web browser as an interactive workspace. Heavy computation stays upstream: scSpark indexes the precomputed objects under a single project structure and exposes them through six modules for cell annotation, differential analysis, trajectory exploration, cell-cell communication, functional interpretation and AI-assisted result interrogation. Every action in these modules, from a query to a label change, an export or an AI-generated summary, is linked to a specific project version, data object, parameter set and output file, so that any conclusion can be traced back to the evidence behind it. We illustrate the platform by reworking a published periodontitis dataset through this interface. scSpark does not replace upstream pipelines or expert judgement; it is a layer that makes their results easier to inspect, revise and reuse, and that turns a single-cell project from a one-off report into an interpretation others can follow and check.

Registration of histological sections to a reference atlas is essential for anatomical localization and region-based quantitative analysis. Although established workflows are powerful, image preparation, registration, quantification, and visualization often rely on multiple software packages, some of which require platform-specific installation or locally configured programming environments. Here, we present NeuroFlow, a browser-based workflow for quantitative analysis of mouse brain histology. NeuroFlow integrates image registration, signal detection, quantification, and visualization within a single interface and operates across major operating systems without additional software installation. It supports affine and nonlinear alignment, as well as real-time oblique reslicing of the reference atlas. All processing is performed locally in a desktop browser, without requiring a local Python environment, MATLAB installation, or associated packages and toolboxes, and without uploading images to a remote server. This design preserves user control over data and keeps intermediate results accessible for inspection and review. NeuroFlow is available at https://guangweizhang.com/tool-neuroflow.html.

Within AI4Life, we ran three Open Calls and three Public Challenges (2023-2025), supporting 22 bioimage analysis projects from 151 applications and engaging 225 challenge participants, with the aim of applying FAIR deep learning in the life sciences. Our experience offers a view of the current state of bioimage analysis, the landscape of available tools, as well as the existing gaps between method developers, tool producers and potential users. It highlights that even after careful selection for AI-ready projects, most still require substantial effort to apply deep learning, and that the field still relies heavily on established, well-rounded methods to solve common problems. We come to the conclusion that for scientific AI in biology, the rate-limiting step is not methods and models but data, annotations, and shared infrastructure underneath them.

Plasma membrane sheets generated by controlled mechanical disruption provide direct access to the cytosolic face of the plasma membrane while preserving the native organization of membrane-associated proteins and lipids. Here, we present a protocol for generating and validating sonication-derived plasma membrane sheets from cultured cells, primary neurons, and isolated synaptosomes. We further describe their application for live and fixed imaging of membrane protein localization, organization, conformational dynamics, and protein-protein interactions, as well as quantitative membrane-associated synaptic vesicle recruitment assays. This versatile platform preserves the native membrane environment while enabling direct visualization and quantitative analysis of membrane-associated processes at high spatial resolution. The protocol can be readily adapted to investigate diverse membrane proteins, lipid-dependent mechanisms, and vesicle tethering events across a wide range of cellular systems.

Natural products such as polyketides and nonribosomal peptides (NRPs) are important sources of bioactive compounds, including many antibiotics. Many of them are assembled by modular enzyme complexes and further modified and diversified by tailoring reactions encoded by biosynthetic gene clusters (BGCs). Although natural products and their coding BGCs describe different data modalities of the same biochemical process, a unified language to jointly describe their biochemistry is lacking. Here we introduce a sequence-based representation of the core biosynthesis of modular natural products, which we call primary sequences, that bridges chemical structures and BGCs. We also present RetroMol, an algorithm that parses either natural product structures or their encoding BGCs into their primary sequences of natural product building blocks. RetroMol allows for similarity scoring between natural products and BGCs, enabling the retrieval of compounds, BGCs, and a combination of the two, based on their biosynthetic similarity. This can, for instance, be used to retrieve biosynthetically similar but structurally dissimilar compounds, or link natural products to candidate coding BGCs in large experimental datasets. We demonstrate the latter by rediscovering the nocardichelin B BGC as a proof of principle. We also exemplify the utility of biosynthetic similarity by showing various pairs of biosynthetically similar compounds with low structural similarity. Together, these results establish primary sequences as a shared biosynthetic encoding for natural product comparison and BGC prioritization.

This step-by-step protocol provides a cross-species, non-surgical approach that enables prenatal gene delivery to the developing nervous system in rats and marmosets. Under transabdominal ultrasound guidance, intracerebroventricular injection of recombinant adeno-associated virus vectors into the fetal brain achieves robust and long-term transduction from prenatal stages into adulthood. This approach can be adapted to other species and target sites outside nervous system, enabling safe and selective intrauterine manipulation and the generation of diverse experimental models for basic and preclinical research. For complete details on the use and execution of this protocol, please refer to Ribeiro Gomes et al (2026)1. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=181 SRC="FIGDIR/small/737050v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@696364org.highwire.dtl.DTLVardef@fc3c7forg.highwire.dtl.DTLVardef@1e7c7caorg.highwire.dtl.DTLVardef@1edcef0_HPS_FORMAT_FIGEXP M_FIG C_FIG Before you beginExperimental procedures during gestation allow researchers to study developmental processes, including how manipulations of the fetus and its intrauterine environment influence biological outcomes. Ultrasound imaging guidance greatly facilitates such interventions by providing safe and targeted access to fetal compartments, including for prenatal gene delivery to developing neural cell populations. Critically, delivery of recombinant adeno-associated viruses (rAAVs) into the cerebrospinal fluid (CSF) of developing animals enables widespread gene transfer across the brain. The efficiency and distribution of transduction are strongly influenced by developmental stage, making the timing of delivery an important experimental variable. In altricial species such as mice, major developmental processes, including cortical lamination and the establishment of long-range connections, begin prenatally but continue throughout early postnatal life. In primates, however, development is more advanced at birth, and many equivalent developmental events are shifted to the prenatal period. Consequently, developmental stages that can be targeted postnatally in mice require prenatal access in primates. Here, we present a step-by-step protocol for ultrasound-guided fetal intracerebroventricular viral injection (FIVI) of rAAV in marmosets (Callithrix jacchus) and rats (Rattus norvegicus). The procedure was initially developed and optimized in rats before being translated to marmosets, small New World primates that share key developmental, anatomical, and functional characteristics with humans. Together, these models illustrate the cross-species applicability of the approach, while providing gene delivery strategies for both a genetically tractable rodent model and a translationally relevant nonhuman primate. FIVI enables broad gene transfer and stable, long-term transgene expression in wild type animals, facilitating the generation of complementary quasi-transgenic models for research and translational applications from prenatal development through adulthood.

High-resolution 3D imaging is an important strategy for visualizing and analysing complex skeletal tissue architecture and the bone marrow microenvironment. However, multicolor immunolabeling and imaging of intact skeletal tissues are technologically challenging. The current immunolabeling and clearing methods for intact skeletal elements are very limited, time-consuming and generate low-resolution data or depend on the use of reporter mice. Here, we describe a protocol for efficient clearing and immunolabeling of intact calcified tissues that enables superfast, single-cell resolution, and quantitative 3D light-sheet imaging of intact skeletal elements and teeth. A key aspect of our protocol is the addition of a collagenase digestion step after fixation and decalcification. This step enhances antibody penetration, resulting in deep, comprehensive staining throughout immunostained bones and other calcified tissues. The protocol includes soft tissue removal, fixation, decalcification, bone dehydration, and bleaching, followed by antigen retrieval and permeabilization before the collagenase digestion step. This procedure is performed to prepare the samples for the tissue clearing process that improves bone tissue transparency prior to light-sheet imaging. The entire protocol, from bone collection to image analysis and quantification, takes about 4 days to complete, thus offering significant improvements over previous methods. This protocol is broadly applicable to the visualization of bone microstructure, bone marrow analysis, vascular and neural network mapping, and the study of signaling molecules in bone development and growth. The protocol requires experience with standard tissue processing and immunostaining techniques, and prior experience in tissue clearing and light-sheet imaging is beneficial but not essential. Key pointsO_LIA protocol for efficient clearing and immunolabeling of intact calcified tissues that enables superfast, high-resolution, and quantitative 3D imaging of various intact bones and teeth. C_LIO_LIThe entire protocol takes only 4 days to complete the comprehensive staining and perfect transparency throughout the intact bones, offering significant improvements over previous methods. C_LI Key referencesBiswas, L. et al. Cell 186, 382-397.e24 (2023): https://doi.org/10.1016/j.cell.2022.12.031

Nuclear Magnetic Resonance (NMR) relaxation experiments provide a powerful residue-resolved access to biomolecular dynamics across a wide range of timescales. Unfortunately, the quantitative analysis of the relaxation data remains distributed across specialised and often disconnected tools. Here, we present CcpNmr AnalysisDynamics, the latest addition to the CcpNmr Analysis program suite, providing an integrated framework for relaxation analysis, exchange-aware interpretation and dynamical modelling. The platform unifies relaxation-rate extraction, diagnostic validation, model-based analysis and structural visualisation within reproducible workflows, while supporting future extension through a robust application programming interface and plugin architecture. We introduce ModelAnalysis (ModA), a new analysis engine based on the Lipari-Szabo formalism that incorporates robust optimisation, uncertainty estimation and model-selection strategies designed for heterogeneous relaxation datasets. The framework also supports exchange-focused analysis and integration with specialised external modelling tools, allowing relaxation anomalies to be followed from initial detection to more detailed interpretation. The applicability and reliability of AnalysisDynamics are demonstrated through systematic re-analysis and validation of curated relaxation datasets from the Biological Magnetic Resonance Data Bank. These analyses enable assessment of data consistency, dynamic parameters and model reliability across magnetic fields, providing a reproducible route from NMR relaxation measurements to structure-linked interpretation of biomolecular dynamics.

This document describes the Statistical Analysis Plan (SAP) for PETRA, a randomised controlled trial in people with generalised anxiety disorder comparing pregabalin plus an antidepressant and standard care, with placebo plus an antidepressant and standard care, with respect to the primary outcome of the GAD-7 score at week 12.

Advances in high-throughput mesoscale microscopy and machine learning-based image analysis pipelines have made unbiased whole-brain imaging widely accessible. However, translating the resulting atlas-mapped datasets into biologically meaningful results remains a substantial barrier owing to their sheer magnitude and complex hierarchical organization. Consequently, reporting structure and analysis methods vary widely across studies, under-mining rigor and reproducibility. To address this, we developed a user-friendly data reduction workflow, HERO (Hierarchy-aware Expression Region Organization), designed to perform hierarchy-aware selection, refinement, ranking, and visualization of whole-brain cell detec-tion datasets. The workflow is customizable to specific needs, requires minimal coding expe-rience, and outputs transparent, curated results. HERO is designed to function as a seamless plug-in within larger-scale whole-brain cell-detection analysis pipelines, providing efficient, unbiased region selection to streamline subsequent statistical analyses and comparative evaluations. Although HERO is developed with mouse cell-detection datasets, it can, in prin-ciple, be applied to any atlas-mapped dataset that contains hierarchical information. In sum, HERO offers a standardized analysis workflow to reduce whole-brain cell-detection datasets, transforming raw regional cell counts into curated results and advancing the effectiveness, interpretability, and accessibility of whole-brain imaging in neuroscience.

Introduction: Autism spectrum disorder, or autism, is a common neurodevelopmental condition characterized by socio-communicative problems together with restrictive and repetitive behaviors. Typically, the latter is manifested as deficits in behavioral flexibility, i.e. changing routine behaviors to adapt to environmental changes. Despite noticeable difficulties with flexible behavior in autism, there is to date not adequate knowledge about the intricacies of such challenges and neurobiological processes that may subserve them. This study aims to investigate both cognitive and motor flexibility in autistic compared with neurotypical adults using a novel combination of detailed methods for brain imaging and behavioral investigations in relation to probabilistic reversal learning (PRL) paradigms. In addition, the experiences of autistic adults on flexible behavior in education and everyday activities will be explored. Methods and analysis: Differences in cognitive flexibility between autistic (n[≥]20) and neurotypical (n[≥]20) adults (18-35 years) will be investigated in terms of brain activations, measured by functional magnetic resonance imaging (fMRI), during two-choice PRL performance (cognitive task). In addition, group differences in microcirculation as measured by arterial spin labelling (ASL) will be evaluated. Group differences in motor flexibility will be investigated as expressed in movement planning and execution (spatio-temporal parameters), measured by a robotic manipulandum platform (KinArm End-Point Robot), during two-choice PRL performance (motor task). Semi-structured interviews will be conducted individually with autistic participants (n=15). Questions concern own experiences of cognitive and motor behavior, and strategies used to support flexibility in these behaviors. Data from this qualitative approach will be analyzed by thematic analysis. Ethics and dissemination: Ethical approval has been obtained from the Swedish Ethical Review Authority (ref:2025-07939-01) and the study will be conducted in accordance with the Declaration of Helsinki, the European Union General Data Protection Regulation (GDPR) and national guidelines for the storing of personal data. The different investigations included are well-established, non-invasive and safe. Study outcomes will be published in peer-reviewed international scientific journals (open access), presented at national and international conferences, and to any interested audience/stakeholders.