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For over 25 years, genomic data have been distributed in two key file formats: FASTA and GFF. These formats are used in nearly all genomic analyses and encode both genomic sequence data and the positions of annotated features. Long-read sequencing, chromatin conformation capture, and advanced assembly algorithms now enable chromosome-level assemblies and pangenomes even for the largest eukaryotic genomes. Genome consortia routinely update assemblies and re-annotate gene models as methods and knowledge improve, yet these updates occur without systematic documentation of what has been modified. As genomics enters the next era, the lack of systematic versioning becomes limiting: different annotation versions cannot be computationally compared, algorithmic improvements are invisible to downstream users, and accumulated biological knowledge exists only in human-readable documentation disconnected from the data itself. Conventional flat-file formats lack the structure to reflect this evolving landscape. While software engineering solved analogous challenges with version control decades ago, for genomics, version control is left to researchers to organise with filenames, directories, or README files. This approach cannot scale to the continuous generation and improvement of millions of genomes. We examine the limitations of genome file formats, demonstrate why incremental improvements are insufficient, and argue that genomics must adopt version control with the same gusto that is applied to generating new sequencing data. Drawing on lessons from software engineering, we outline requirements for better scientific collaboration, machine-readable formats that can capture changes, maintain complete provenance, and enable the reproducible, large-scale biology that the next 25 years demands.

This work aimed to examine the geometrical, metallurgical, and static mechanical properties of five reciprocating NiTi endodontic files with similar cross-sectional geometries. Reciproc Blue, ProDesign R, V File, V+ File, and Univy One systems were evaluated using a multimethod approach including geometrical analysis, scanning electron microscopy, energy-dispersive spectroscopy, differential scanning calorimetry, X-ray diffraction, bending resistance, and torsional tests. R-phase was predominant in most instruments, while the Univy One system showed indications of a combined martensitic and R-phase structure. ProDesign R demonstrated superior flexibility, whereas Reciproc Blue and V File exhibited greater torsional resistance. Cross-sectional area was an important factor influencing the mechanical characteristics of the instruments, although metallurgical aspects appeared to influence the behavior of specific systems. Geometry and metallurgical characteristics influenced the observed static mechanical behavior of the evaluated reciprocating instruments. Instruments exhibiting higher proportions of martensite and R-phase demonstrated enhanced flexibility, while bending resistance was also strongly affected by cross-sectional geometry, highlighting the combined influence of material properties and design on mechanical performance. However, the findings should be interpreted within the limitations of static mechanical evaluation, since cyclic fatigue testing was not performed.

Pathway and functional enrichment analysis is a cornerstone of omics data interpretation, enabling researchers to map differentially expressed proteins or genes onto curated biological processes, signaling cascades, and molecular functions. While tools such as Ingenuity Pathway Analysis (IPA), g:Profiler, and Enrichr are widely used to generate ranked enrichment results, translating these tabular outputs into clear, publication-ready figures remains a time-consuming step that typically requires custom scripting and familiarity with visualization libraries - a significant barrier for researchers without a computational background. Here we present EnrichViz, a self-contained, browser-based R Shiny application that enables interactive, code-free visualization of pathway and functional enrichment results from quantitative proteomics, transcriptomics, and metabolomics experiments. EnrichViz accepts three standard CSV files as input - a normalized abundance matrix, a sample annotation or metadata file, and enrichment results from any platform that exports tabular output - and produces six complementary, publication-ready visualizations: bar and bubble plots for ranking enriched terms by significance, chord diagrams for exploring pathway-molecule connectivity, clustered heatmaps for displaying Z-score normalized expression patterns across experimental groups, and boxplots or violin plots for examining the abundance distribution of individual proteins, genes, or metabolites. The application supports both raw p-values and pre-transformed -log10(p) values through automatic detection, and all plot parameters are adjustable in real time through a graphical sidebar. Every figure can be exported as a high-resolution PNG file at 300 dpi. EnrichViz is implemented in R using the Shiny, ggplot2, pheatmap, and circlize packages, and is freely available at https://rgmilian.shinyapps.io/EnrichViz/ .

End-stage kidney disease continues to disproportionally impact the lives of First Nations(FN) peoples. This paper examines the trajectory of chronic kidney disease (CKD) care in FN individuals who started dialysis. We used health administrative data held at the Manitoba Centre for Health Policy (MCHP) for the period of 2000-2019, which was linked to the Manitoba First Nations Research File to identify Registered FN. Data we used included: Diagnostic Services Manitoba Laboratory Data, Medical Claims, Hospital Discharge Abstracts, Drug Program Information Network Data, Public Canadian Census Files, Manitoba Health Insurance Registry, and Physician Resource File. All records are de-identified. Our primary outcome was to assess the frequency of uninformed dialysis starts among FN. We identified 1,686 FN people who started dialysis during the study period. Of those, 396 (23.5%) started dialysis within three months of their first nephrology visit. We compared those initiating dialysis within 3 month to other FN with longer nephrology follow-up: as a group, FN initiating dialysis within 3 month of their first nephrology visit were more unwell as evidenced by a significantly higher Elixhauser co-morbidity index (5 vs. 3 P&#x2009;<&#x2009;0.001), hypertension (70.7% vs. 57.1% p&#x2009;<&#x2009;0.001) and congestive heart failure (31.1 vs17.4% P&#x2009;<&#x2009;0.001). Primary care visits in all FN groups with CKD occurred in over 95% and CKD screening was similar in all groups at over 40% a year prior to the first nephrology visit. Less than 70% of FN with CKD were on appropriate preventative medications (69 vs. 68% p&#x2009;=&#x2009;NS)) IMPLICATIONS: Improvements in primary prevention at the primary care level are needed to avoid late nephrology referrals and improve overall care of FN with CKD.

This article provides a dataset collected through semi-structured interviews with stakeholders involved in industrial symbiosis and circular economy practices in Slovenia. The dataset includes anonymized transcripts in Slovene and English translations, offering insights into sustainability practices, collaboration mechanisms, and stakeholder trust in the context of the Slovenian transition to a circular economy. All interviews were conducted in Slovene, converted into note-based transcripts, anonymized, and translated into English, resulting in 50 transcripts. The article also presents a structured coding scheme developed from the interview material, including main categories, subthemes, operational definitions, inclusion and exclusion criteria, and illustrative quotations. The coding scheme enhances the dataset's reuse potential by supporting thematic analysis, comparative research, and methodological training in qualitative coding. The Zenodo record contains 54 relevant files across versions v3 and v4: 25 anonymized Slovene transcripts, 25 English translations, 2 interview protocols, 1 README file, and 1 structured codebook file in Excel format. The dataset provides qualitative insights into organizational structures, sustainability goals, collaboration mechanisms, regulatory frameworks, and relational trust dynamics in symbiotic networks. It is openly available for reuse in thematic analysis, discourse studies, comparative policy research, and training in qualitative research methods.

Parkinson's disease (PD) is a progressive neurodegenerative disorder in which neuroinflammation is recognized as a contributor to clinical progression. This study aimed to characterize the cerebrospinal fluid (CSF) inflammatory profile in mid- to late-stage PD patients and identify specific inflammatory proteins with potential clinical relevance to motor symptoms and disease severity. In this preliminary retrospective cross-sectional study, CSF samples were obtained from 25 patients with mid- to late-stage PD undergoing evaluation for deep brain stimulation (DBS) (mean disease duration: 10.24&#x2009;&#xb1;&#x2009;4.65 years) and 15 non-PD controls (essential tremor or dystonia) undergoing identical surgical procedures. The levels of 92 inflammation-related proteins were quantified using the Olink proximity extension assay (PEA). Based on the identified differentially expressed proteins (DEPs), we next performed preliminary exploratory comparisons of inflammatory profiles between the postural instability and gait difficulty (PIGD, n&#x2009;=&#x2009;10) and tremor-dominant (TD, n&#x2009;=&#x2009;10) PD subtypes. Additionally, preliminary correlation analyses were performed between the DEPs and Movement Disorder Society-Unified Parkinson's Disease Rating Scale Part-III (MDS-UPDRS-III) scores to generate preliminary observations with limited clinical inference. Using the Olink platform, 28 DEPs were identified between the PD and non-PD groups (p&#x2009;<&#x2009;0.05). Subsequent protein-protein interaction network analysis identified IFN-&#x3b3; as the central hub. Exploratory descriptive analyses of TD and PIGD subgroups are provided in Additional file 1: Supplementary Figure S1. Among all DEPs, IL-10RB (r&#x2009;=&#x2009;0.440, 95% CI [0.054, 0.711], p&#x2009;=&#x2009;0.028), CD8A (r&#x2009;=&#x2009;0.415, 95% CI [0.024, 0.696], p&#x2009;=&#x2009;0.039), and CXCL9 (r&#x2009;=&#x2009;0.414, 95% CI [0.023, 0.696], p&#x2009;=&#x2009;0.040) showed moderate correlations with MDS-UPDRS-III scores. In profiling 92 CSF inflammation-related proteins from 25 advanced PD patients (Hoehn-Yahr 3-4) and 11 controls, we identified 28 upregulated DEPs. IFN-&#x3b3; emerged as a topologically connected hub in protein-protein interaction networks, and three proteins (IL-10RB, CD8A, CXCL9) showed moderate correlations with motor scores. As cross-sectional descriptive observations, these findings establish a preliminary framework to generate hypotheses for future mechanistic validation and biomarker discovery, while no functional causality can be inferred from the present results.

Rational drug design typically relies on a sequential workflow comprising virtual screening, flexible redocking, and free energy calculations. Specialized tools exist for individual steps, including our Binding Free-Energy Estimator 3 (BFEE3) for absolute binding free-energy (ABFE) calculations. However, the field lacks an open-source platform that seamlessly connects virtual screening to rigorous free-energy evaluation while allowing nonspecialists to customize intermediate stages. Although commercial suites offer such integration, they often suffer from limited accessibility. To address this limitation, we develop BFEE-docking as a companion platform to BFEE3, extending BFEE3 toward an integrated, automated drug-discovery workflow. Requiring only a standard protein PDB file and a ligand database (SMI/SDF), this cross-platform software automates GPU-accelerated virtual screening, flexible redocking, and free-energy estimation using either MM-GBSA or BFEE3-based ABFE calculations. The software autonomously handles complex preparatory tasks, including pH-based protonation, chain cleaning, binding site identification, and file format conversion. Notably, BFEE-docking interfaces directly with PyMOL to provide real-time visualization of intermediate results, including binding site locations, docked ligand conformations, and flexible residue configurations. This feature allows the end-user, regardless of their computational background, to inspect and customize the protocol on the fly. We demonstrate the usefulness of BFEE-docking through a challenging inhibitor screening campaign against the epidermal growth factor receptor triple mutant (EGFRTM), achieving formally exact binding free-energy evaluation within the screening workflow while preserving protonation-state-specific docking poses for separate MM-GBSA or ABFE calculations. The pipeline successfully identifies two novel potential inhibitors overlooked in our previous studies, showing the reliability and effectiveness of BFEE-docking in drug discovery.

Major vascular injury during laparoscopic surgery is rare but potentially catastrophic. Existing literature is largely limited to case series and registry-based analyses without reliable denominators or validated measures of disease severity. Procedure-specific risk and overall population burden remain incompletely defined. This study aimed to determine the statewide incidence, severity profile, and procedure-specific risk of iatrogenic major vascular injury during inpatient laparoscopic surgery. We conducted a retrospective population-based cohort study using the 2024 Texas Inpatient and Outpatient Public Use Data File (PUDF). Adult patients (&#x2265;&#x2009;18&#xa0;years) undergoing inpatient laparoscopic procedures were identified using ICD-10-PCS approach codes. Iatrogenic major vascular injury was defined using ICD-10-CM diagnosis codes T81.71* and/or I97.5*. The primary outcome was statewide incidence per 10,000 inpatient laparoscopic procedures. Secondary outcomes included markers of clinical severity, including mortality, ICU admission, conversion to open surgery, transfusion, organ failure, and length of stay. Among 119,652 inpatient laparoscopic procedures, 84 cases of iatrogenic major vascular injury were identified, yielding an incidence of 7.02 per 10,000 procedures. (R3C3) These injuries were associated with high clinical severity, including an in-hospital mortality rate of 7.2% and ICU admission in 66.3% of cases. Surgical management often required escalation, with 55.4% of cases undergoing conversion to open surgery and 30.1% requiring blood transfusion. Acute kidney injury (26.5%) and respiratory failure (24.1%) were common. The median length of stay was 6&#xa0;days (IQR 3-11), compared with 3&#xa0;days (IQR 1-5) without injury. Diagnostic laparoscopy demonstrated the highest incidence (20.59 per 10,000), whereas colorectal resection had the lowest (0.89 per 10,000). Iatrogenic major vascular injury during inpatient laparoscopic surgery was rare but associated with substantial morbidity and mortality. The elevated incidence observed during diagnostic laparoscopy may suggest abdominal access as an important contributing mechanism of injury, reinforcing the need for continued emphasis on safe-entry techniques and heightened specialty-specific risk awareness. (R2C1).

Population genomic workflows frequently rely on fragmented command-line utilities, custom conversion scripts, and programming language-specific environments, complicating computational reproducibility and obscuring data provenance. As analytical workflows become increasingly automated and computationally intensive, dependence on disparate preprocessing tools can introduce friction between raw genotype files, quality-control decisions, statistical analyses, and downstream workflows. We developed SNPio, a Python-native framework that consolidates single nucleotide polymorphism data parsing, filtering, visualization, numerical genotype encoding, and population genomic summary-statistic calculation within a unified software architecture. VCF file parsing and filtering benchmarks were compared against vcfR and SNPfiltR. SNPio demonstrated faster execution times but used more memory than its R-based comparators, reflecting SNPio's retention of genotype arrays, metadata, and provenance-tracking attributes. Pairwise Weir and Cockerham's FST and Nei's genetic distance estimates aligned with HierFstat expectations based on Pearson correlations and aggregate error metrics. D-statistics conformed to theoretical expectations across eleven simulated datasets spanning a range of introgression signal strengths. SNPio provides a reproducible Python-native workflow for processing, filtering, encoding, visualizing, and analyzing SNP datasets. It integrates common early-stage population genomic operations into a transparent, scriptable framework, which ultimately promotes workflow provenance and reduces reliance on disjointed software tools, unsaved terminal commands, and custom scripts. SNPio is particularly suited for population genomic studies of non-model organisms in ecological, evolutionary, and conservation contexts, where reproducible preprocessing and interoperability with downstream analyses are becoming increasingly important.

Preservation of the original root canal anatomy is essential for the long-term success of endodontic treatment. Effective cleaning and shaping of the root canal system are critical steps in this process; however, canal transportation is a common procedural error during the preparation of curved canals. This study aimed to compare canal transportation and centering ability between two rotary file systems, ProTaper Next and Bassi Logic, in curved root canals using cone-beam computed tomography (CBCT). Forty extracted human mandibular first molars with mature apices and an apical curvature ranging from 10&#xb0; to 30&#xb0; were selected. These samples were randomly allocated into two groups of 20 teeth, ensuring similar average curvatures. Root canal preparation was performed using either the ProTaper Next or Bassi Logic rotary file systems, strictly adhering to the manufacturers' protocols. CBCT images were acquired using a Kodak 9600 system (Care Stream, Paris, France), both before and after instrumentation. Canal transportation is a common procedural error during the preparation of curved canals. Statistical analysis was performed using an independent t-test to compare the two groups, with the significance level set at P&#x2009;<&#x2009;0.05. Statistical analysis was performed using an independent t-test, with the significance level set at P&#x2009;<&#x2009;0.05. The ProTaper Next system demonstrated greater canal transportation and a lower centering ratio across all evaluated apical levels compared to the Bassi Logic system. Statistically significant differences in canal transportation were observed at the 3&#xa0;mm level in the mesiodistal plane and at the 5&#xa0;mm level in the buccolingual direction (P&#x2009;<&#x2009;0.05). However, no statistically significant differences in centering ratio were found between the two systems at any of the evaluated levels (P&#x2009;>&#x2009;0.05). Within the limitations of this in vitro study, both systems demonstrated acceptable shaping ability in curved canals; however, Bassi Logic showed less canal transportation at certain apical levels, which may support better preservation of canal anatomy in clinical practice.

Fluorescence lifetime imaging microscopy (FLIM) can probe the metabolic environment of living cells in a label-free and noninvasive manner. However, endogenous fluorophores have low absorption and quantum yields, requiring long integration times to acquire the high photon counts needed for accurate pixel-wise multi-exponential decay fitting. A computationally light "region-of-interest" photon pooling technique was used to expedite label-free, single-cell FLIM acquisition and analysis, and its accuracy was compared with standard fitting techniques. We first characterized the accuracy and precision of "region-of-interest" photon pooling using known fluorescence standards and tested its ability to recover fluorescence lifetimes of single cells and large regions of interest with low photon budgets. Single-cell metabolic information was accurately extracted from scanning periods as low as 1&#xa0;s, and large FLIM mosaics were acquired 15 times faster than was possible with conventional pixel-level analysis. Lifetimes extracted using photon pooling were comparable to standard measurements requiring much longer integration times. The technique was also applied to measure fluorescence lifetimes in highly dynamic live samples. "Region-of-interest" (ROI) photon pooling extracts fluorescence lifetimes from live, dynamic samples with low photon budgets, expediting image acquisition while preserving cell-level or ROI-level lifetime information while sacrificing intra-ROI spatial resolution. The technique is computationally light, does not require machine learning algorithms, and can be integrated with commonly used analysis software and file types.

Background Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (AB-PMJAY) represents India's flagship publicly funded health insurance initiative aimed at advancing universal health coverage by improving access to secondary and tertiary care while reducing out-of-pocket expenditure (OOPE). Despite its scale and policy significance, real-world evidence on awareness, utilization, patient experience, and residual financial burden in rural settings remains limited. Objectives To assess the awareness, utilization, satisfaction, and OOPE associated with AB-PMJAY among rural beneficiaries in the district of Meerut, Uttar Pradesh. Methods A community-based cross-sectional study was conducted from November 2024 to November 2025 across four randomly selected villages within a 10-km rural radius of Subharti Medical College, Meerut. A total of 208 households possessing and utilizing AB-PMJAY cards were included. Data were collected through house-to-house interviews using a pretested semi-structured questionnaire. Key outcome variables included awareness (scheme knowledge, empanelled hospitals, grievance redressal), utilization (enrolment duration, documentation, coverage), satisfaction (clinical care, staff behaviour, administrative services), and OOPE.&#xa0; Results Overall awareness of AB-PMJAY was high (96.6%), and most participants were aware of scheme benefits (96.2%) and service availability in both public and private hospitals (94.7%). However, awareness of empanelled hospitals (30.3%) and grievance redressal mechanisms (26.4%) remained low. All participants reported utilizing the scheme, with 43.8% enrolled for more than three years. Most beneficiaries (74.0%) reported coverage utilization up to Rs. 1 lakh. Despite insurance coverage, 100% of participants incurred OOPE, though the majority (78.8%) spent less than Rs. 10,000. Additionally, awareness alone may not be sufficient to prevent OOPE and may reflect a more complex pattern of healthcare use and hidden costs. Satisfaction with clinical services (97.2%) and healthcare staff behaviour (99%) was high; however, satisfaction with administrative aspects such as file management (17.8%) and food quality (14.4%) was substantially lower. Socio-demographic factors, including education, caste, and socioeconomic status, were significantly associated with awareness indicators. Conclusion While AB-PMJAY demonstrates high awareness, substantial utilization, and strong satisfaction with clinical care among rural beneficiaries, critical gaps persist in functional awareness, particularly regarding empanelled facilities and grievance mechanisms. Importantly, persistent OOPE across all beneficiaries highlights incomplete financial risk protection. Strengthening beneficiary education, improving administrative efficiency, and addressing hidden healthcare costs are essential to optimize the scheme's impact.

Digital pathology continues to transform the daily routine of pathology, in terms of the increasingly automated laboratory and in the diagnostic paradigm through the adoption of artificial intelligence (AI) tools to support diagnosis-computational pathology. The reliability and performance of these tools depend on the whole-slide image (WSI) quality being guaranteed a priori. Pre-analytical quality control step that underpins this guarantee, and artifact detection remains largely qualitative and is frequently overlooked in routine digital pathology. This operational feasibility study evaluated whether an adaptation of GrandQC, an open-source AI tool, enables automated, quantitative artifact assessment of a complete single-day biopsy workload from a high-throughput digital pathology laboratory, analyzed retrospectively. A random biopsies day of 2025 at Centro de Anatomia Patol&#xf3;gica Germano de Sousa (CAPGS) was selected as a sample to test the performance of GrandQC on the WSI generated (n&#x202f;=&#x202f;544) in order to simulate the daily workflow. A script was created to quantify the pixels corresponding to the type of artifact automatically, creating an Excel file for registering and statistical analysis. Analysis took a median of 24&#x202f;s per WSI, detecting a median of 1.46% of tissue area with some type of artifact. Dark Spots and blurring areas were the most representative detected artifacts. GrandQC is a valuable tool in the quantitative quality control of biopsies tissue, allowing quick evaluation, signaling types of artifacts, and identifying cases that need to be reviewed before being handed over to the pathologist allowing the recognition of opportunities to improve laboratory histology quality and precision medicine.

Chimeric RNAs are composed of sequences from different genomic loci caused by various chromosomal rearrangements and splicing events. They are recognized as both biomarkers present in cancer as well as a source of transcriptomic diversity in normal tissues. Numerous computational prediction tools have been developed and aim to analyze and predict chimeric RNAs. However, the performance of these tools vary in accuracy and depend on the sequencing context, necessitating a combination of multiple existing tools to produce the most comprehensive and accurate results. First, this study reviews several major chimeric RNA prediction tools: STAR-Fusion, Arriba, and FuSeq. It highlights the advantages of each program, as demonstrated by benchmarking studies. Second, it presents an integrated pipeline that combines all three top-ranking programs to produce a single output file including detailed annotations, such as chimeric RNA class, breakpoint types, and protein coding potential. The final computational product is a unified framework that supports results for high-confidence fusion transcript predictions for both research and clinical applications.

TB preventive therapy (TPT) is one of three key interventions for reducing TB in South Africa, but uptake and completion rates remain low. In South Africa, the current TPT options include isoniazid and rifapentine or isoniazid and rifampicin. Evidence and lessons learned from programmatic uses of isoniazid preventative therapy (IPT) could provide operational advice to enhance the implementation of new TPT regimens. We conducted 28 in-depth provider interviews (IDIs) to elicit experiences of and preferences for the different TPT regimens between 04/2022 and 12/2022 in the City of Johannesburg, Gauteng and Greater Tzaneen sub-district, Mopani district, Limpopo Provinces. We used purposive sampling to recruit doctors (n=7), pharmacists (n=8) and nurses (n=13) in high and low volume TB and/or HIV facilities. IDIs were recorded for quality, transcription, and translation purposes. Data analysis was conducted using a thematic approach in NVivo 11. We present provider preferences and perspectives for TPT uptake. The most important attributes relating to preferences for TPT regimens attributes among healthcare providers included medication safety, efficacy and low pill burden. Despite valid preferences for different regimens, healthcare service providers had varied experiences around factors that influence the uptake of the different TPT regimens they offered at their facilities. Many providers indicated that patient booking errors, missing patient records, staff shortages, long queues, medication side effects and limited understanding of the benefits of TPT were reasons for poor patient TPT uptake and adherence. Limited knowledge was attributed to a lack of educational materials and insufficient staff-patient engagement time. Providers noted that increased clinician awareness and patient counselling contribute to a higher rate of TPT prescriptions, as well as improved patient uptake and adherence. Thus counselling, staff training, side-effects management, and improved file documentation are key factors for TPT uptake.

To improve access for people of Aboriginal background with traumatic brain injury (TBI) to the New South Wales Mid North Coast Brain Injury Rehabilitation Service (MNCBIRS). The participatory action research (PAR) project was led by the Dunghutti Muri steering committee, comprising key Aboriginal Health Workers from the region alongside MNCBIRS staff. A service file audit described current and recent Aboriginal clients, with a subset of clients/family members participating in semi-structured interviews around access facilitators/barriers to MNCBIRS. Audit and interview data then drove a series of initiatives to enhance service access. A time series analysis tested whether the project increased Aboriginal clients as an overall proportion of the service caseload. The audit identified 27 Aboriginal clients (Male = 19/Female = 8; TBI = 21/ABI = 6), with 11 clients/family members interviewed. Thematic/inductive analysis elicited themes within the six categories of the Theory of Access framework (Accessibility, Availability, Affordability, Accommodation, Acceptability, Awareness). Ten new service initiatives were implemented to improve access. Timeseries models found a significant increasing proportion of the caseload were Aboriginal since Dunghutti Muri Project inception, compared to pre-program (P-value = 0.038). Initial evidence was found for improved Aboriginal access to mainstream specialised brain injury rehabilitation services using PAR. The Theory of Access provides a framework to evaluate access issues for disenfranchised groups.The PAR approach embeds cultural respect within an evaluative methodology without subordinating Aboriginal people&#x2019;s priorities to Western agendas.Accessible mainstream rehabilitation remains a crucial complement to Aboriginal specific services, ensuring treatment and support after brain injury.