Journal of Neurotrauma

Accurate quantification of locomotor recovery is essential for evaluating therapeutic outcomes in spinal cord injury (SCI) models. Manual scoring systems remain observer-dependent, and commercial gait-analysis platforms are costly and proprietary. Markerless pose-estimation tools such as DeepLabCut generate accurate body-part coordinates, but converting these coordinates into biologically meaningful locomotor parameters typically requires custom programming and multiple external tools. We developed KiMA (Kinematic Motion Analysis), an open-source, browser-based suite for integrated analysis of rodent gait and hindlimb kinematics. KiMA accepts DeepLabCut coordinate files and performs automated coordinate parsing, stick-figure reconstruction, frame-by-frame movement inspection, and single- and multi-sample analysis, with dedicated workflows for ladder and rung analysis, footfall detection, and CatWalk gait analysis. The platform quantifies joint angles (metatarsophalangeal, ankle, knee, hip, and pelvic), stride length, stride width, cadence, stance and swing durations, paw-contact events, swing clearance, and locomotor symmetry, and supports cohort-level comparisons, correlation analysis, principal component analysis, and export of processed datasets and publication-quality figures. Because KiMA runs entirely within a standard web browser, it requires no software installation or local programming environment, supporting cross-platform accessibility and data privacy. By unifying gait quantification, visualization, and multivariate analysis in a single interface, KiMA lowers the computational barrier to markerless locomotor analysis and helps researchers detect subtle functional recovery after SCI.

Importance: Outcomes following traumatic brain injury (TBI) vary substantially, with a subset of individuals experiencing neuropsychiatric morbidity and worse prognosis. Exposure to psychosocial and environmental stressors may be an important, yet understudied, modifier of TBI trajectory. Allostatic load (AL) represents the cumulative physiological burden of chronic stress and provides a useful framework for evaluating pre-injury vulnerability. Objective: To assess the relationship between pre-injury AL burden and risk of mortality and incident neuropsychiatric diagnosis following TBI. Design, Setting, and Participants: This cohort study leveraged electronic health record, survey, and laboratory data from the All of Us Research Program, version 8. Participants aged 18 years or older enrolled between May 6, 2018, and October 1, 2023, were queried for TBI diagnosis using clinical diagnostic codes. Data were analyzed between November 11, 2024, and January 7, 2026. Exposure: The physiological burden of pre-injury chronic stress exposure was estimated using an AL index (pALI) derived from anthropometric and laboratory biomarkers collected before index TBI. Main Outcomes and Measures: Post-TBI mortality and incident neuropsychiatric diagnosis clusters. Mortality risk was assessed using Cox proportional hazards models (hazard ratio [HR] with 95% CI), and risk of incident neuropsychiatric diagnosis was modeled using competing-risk regression with death as a competing event (sub-distribution HR with 95% CI). Results: The primary cohort included 4,552 individuals with an established TBI diagnosis and sufficient biomarker data to estimate pALI. The pALI measure differed across sociodemographic groups and was positively correlated with perceived stress (r=.08, p=.002). Higher pALI was associated with increased post-TBI mortality risk (adjusted HR=1.71; 95%CI, 1.36-2.14). Elevated pALI was also associated with greater risk of incident post-traumatic stress disorder (PTSD; adjusted HR=1.28; 95%CI, 1.10-1.50) and sleep disorder (adjusted HR=1.42 95%CI, 1.29-1.57) diagnoses. Conclusions and Relevance: Higher pre-injury ALI was associated with increased risk of mortality and select neuropsychiatric outcomes following TBI, suggesting that AL burden may shape post-injury trajectories. Pre-injury chronic stress exposure and underlying stress biology may represent underrecognized determinants of vulnerability and resilience in brain injury recovery.

Acute traumatic spinal cord injury comprises a primary mechanical injury followed by a delayed secondary cellular injury cascade. No current monitoring modality directly detects ongoing cellular damage or its response to treatment. Essentially all spinal serotonin derives from descending raphe-spinal projections that travel alongside spinal motor and sensory pathways. Experimental spinal cord injury results in a robust release of serotonin into the surrounding interstitial tissue. We therefore asked whether cerebrospinal fluid 5-hydroxyindoleacetic acid (5-HIAA), the stable metabolite of serotonin, tracks primary and secondary spinal cord injury in humans. In this prospective observational cohort study at a single level-one trauma center, cerebrospinal fluid was collected at 8-hour intervals for up to 5 days through indwelling lumbar drains from 11 participants with acute cervical or thoracic traumatic spinal cord injuries (American Spinal Injury Association Impairment Scale [AIS] grade A-C) and from 7 non-injured control participants. Cerebrospinal fluid 5-HIAA was quantified by high-performance liquid chromatography. Participants with acute traumatic spinal cord injury demonstrated a reproducible rise in cerebrospinal fluid 5-HIAA within 12 hours of injury that regressed toward control values. Two participants neurologically declined during the 5-day observation period, and in both a delayed secondary 5-HIAA elevation accompanied the decline; in one participant this elevation coincided with a documented episode of critical spinal cord hypoperfusion and resolved within 8 hours of its correction. Across the cohort, the 5 participants with a secondary 5-HIAA elevations above 400 nM more than 36 hours after index trauma were AIS A at 12 months regardless of initial injury severity, whereas all 6 participants without a secondary elevation in cerebrospinal fluid 5-HIAA levels were AIS C or better. In this small exploratory cohort, cerebrospinal fluid 5-HIAA was associated with the presence of acute traumatic spinal cord injury, with acute secondary neurological decline, and with long-term motor outcome. Unlike glial fibrillary acidic protein and neurofilament light chain, whose concentrations evolve over days to weeks, 5-HIAA rose and regresses within hours, a kinetic profile compatible with real-time detection of secondary injury and confirmation of treatment response. These findings are hypothesis-generating and require validation in larger, multicenter cohorts before clinical application.

Background/Objectives: Traumatic Brain Injuries (TBIs) often cause profound functional impairments, yet the influence of TBI mechanisms on stair-climbing functional independence over extended timelines remains poorly understood. This study assesses whether Rasch-transformed FIM Stairs scores varied by TBI mechanism over follow-ups spanning 10 years or more. Methods: Data from the TBI Model Systems database were analyzed. The original 30,768 data entries were reduced to 6,226, corresponding to individuals with at least 10 years of data. Functional Independence Measure Stairs data were transformed to logit units via Rasch analysis before being evaluated with a linear mixed-effects regression, incorporating TBI mechanisms, age, follow-up time, and their interactions, with random effects accounting for the participant ID and pre-injury residence location. Results: TBI mechanisms meaningfully shape very long-term stair-climbing. Gunshot wounds and pedestrian-related accidents are associated with poorer performances, whereas motorcycles, bicycles, unclassified vehicular accidents, winter sports, other sports, and fall-related TBIs demonstrated relatively better function. Age, follow-up time, and their interaction also reached significance. Conclusions: Stair-climbing recovery trajectories over extended time significantly vary by TBI mechanism, with individuals with TBIs from gunshots and pedestrian-related accidents showing the most unfavorable recoveries. These findings support the development of mechanism-specific prognostic guidance and individualized rehabilitation strategies, thereby encouraging tailored approaches to improve outcomes.

Background Machine learning (ML) models for traumatic brain injury (TBI) prediction increasingly demand extensive data, computational resources, and energy consumption, yet simpler models may offer comparable clinical benefit with lower barriers to deployment. This study compares predictive performance, computational efficiency, carbon footprint, and real-world feasibility of resource-efficient ("pauci-parameter") versus data-intensive ("multiparameter") ML models for predicting TBI patient care pathways and outcomes. Methods External validation study in a level 1 trauma center (n=534 adult TBI patients with GCS<9 and/or intracranial injuries). Seven models tested: two pauci-parameter models using only routine prehospital variables (PREHOSP, 15 variables) or CT image analysis (CT-TIQUA), and five multiparameter models integrating clinical and imaging data. Primary outcome: positive likelihood ratio for predicting neurocritical care intensity, mortality (7/30-day, 6-month), and functional outcome (Glasgow Outcome Scale Extended). Secondary outcomes: computation time, carbon footprint, clinical implementability. Results Multiparameter models showed superior performance but did not consistently translate to better clinical utility. PREHOSP (pauci-parameter) showed comparable performance to complex models for most outcomes. The best-performing multiparameter model (MULTI-PRE) required 100-fold longer inference time and 10-fold higher carbon emissions per prediction versus simple models, while net clinical benefit was nearly identical (0.06 vs 0.05). Models using only prehospital data demonstrated greater generalizability and lower deployment barriers. Interpretation Computational complexity and resource intensity should factor equally with predictive performance in clinical AI deployment decisions. For sustainable digital health implementation--especially in resource-limited settings--simpler models with comparable clinical benefit may enable broader access while reducing environmental and financial costs.

Traumatic brain injury (TBI) is a leading cause of death and long-term disability in children, with many experiencing persistent symptoms even after mild TBIs. Exposure to adverse childhood experiences (ACEs) can have physiological effects that may alter how the brain responds to injury, yet the effects of ACEs on white matter injury and recovery processes remain unclear. This study examined whether a history of ACEs is associated with patterns of longitudinal change in white matter microstructure in children with mTBI. Ninety-six concussed adolescents (mean age=14.9 years, range =11.4-17.9, 51% female) from the CARE4Kids consortium completed the Pediatric ACEs and Related Life-Events Screener and underwent diffusion-weighted MRI at baseline (7-35 days after injury) and follow-up (2 months later). Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), orientation dispersion index (ODI), and intracellular volume fraction (ICVF) were estimated using tract-based spatial statistics and harmonized across sites. Differences in the magnitude and direction of change in diffusion metrics over time were examined in 15 tracts of interest. Higher ACE exposure was associated with smaller absolute change in AD, MD, ODI, and ICVF across several white matter tracts, including the corpus callosum, internal and external capsules, corona radiata, and posterior thalamic radiation. Groups did not differ in the direction of white matter change for any tract-metric combination. These findings suggest that ACE exposure may blunt white matter reactivity to injury and/or reorganization during recovery processes.

Sport-related concussions (SRC) are heterogenous injuries that produce a variety of symptoms and recovery trajectories. This heterogenous nature and focus on group-level analyses in current literature may obscure individual level results that could better inform clinical SRC management. In a prospective case-control study, we used diffusion magnetic resonance imaging (dMRI) to quantify longitudinal, whole-brain microstructural white matter changes reflecting axonal injury and inflammation and structural network-level alterations following SRC in adolescent athletes. Differential tractography assessed individual white matter track changes from acute injury to clinical recovery on an individual level. Acutely after SRC, but not after recovery, concussed adolescents demonstrated increased (i) quantitative anisotropy, (ii) restricted diffusion imaging, and (iii) isotropy, indicating increased microstructural disruptions early after injury. At the network level, differences were seen not acutely but after clinical recovery: whole brain network structure was more similar with reduced capacity for information spread among the concussed adolescents compared with controls. At the individual level, consistent patterns of damaged white matter tracks persisted in the concussed males but not in the concussed females. These results indicate that adolescent athlete brains are impacted acutely at the microstructural level following SRC, but that macroscale network disruptions appear after microstructure damage resolution, and they can persist beyond clinical recovery. Sex differences in the brains microstructural response to SRC, highlight the need for future research to include individualized and sex-stratified analyses to guide targeted SRC management.

Background/Objectives: This systematic review examines how different mechanisms of Traumatic Brain Injury (TBI) influence post-injury functional independence and aims to clarify whether recovery patterns vary by injury type. A total of 105 studies (n = 59,621) involving adults with TBI were synthesized. These findings can guide clinicians and researchers in predicting outcomes and effectively customizing rehabilitation plans. Methods: A review following PRISMA standards analyzed English-language studies published from 1975 to 2025, assessed functional outcomes using the Functional Independence Measure (FIM) or the Glasgow Outcome Scale-Extended (GOSE), converted them to z-scores, and aggregated them via a random-effects model with inverse-variance weighting to demonstrate their relevance. Results: Recreational TBIs show the highest functional independence (z = +1.77), followed by MVAs (z = +1.56), with falls (z = +0.70) and assault-related TBIs (z = -0.12) showing moderate outcomes, and TBIs with penetrating trauma (z = -1.15) indicating the most adverse results. Conclusions: TBI mechanisms appear to meaningfully influence long-term post-injury functional independence. Highlighting this can inspire clinicians and researchers to trust these insights to improve prognosis and rehabilitation strategies, underscoring their crucial role in advancing patient care.

Objective We aimed to evaluate the performance of the recently updated Sequential Organ Failure Assessment Score-2 (SOFA-2) on organ dysfunction classification and prognostication compared to SOFA-1 in critically injured trauma patients. Methods Adult trauma patients admitted to critical care at four urban Major Trauma Centres between 2011 and 2024 were included. Daily organ dysfunction scoring was performed using SOFA-1 and SOFA-2 until death or discharge. The primary outcome was MODS, defined as SOFA score [&ge;]6. Results In 2162 severely injured patients (median Injury Severity Score 25 [IQR, 17-34]), SOFA-2 reduced the proportion of patients classified as having MODS compared with SOFA-1 (61.6% vs 68.5%, p<0.001). SOFA-2 scores on the first day after admission were lower than SOFA-1 (median 6 [IQR, 3-8] vs 7 [IQR, 4-10], p<0.001), driven predominantly by lower respiratory and cardiovascular scoring. Critical care mortality in trauma patients was increased in respiratory, cardiovascular and renal components of SOFA-2 at the higher ends of the scores, consistent with the aims of the SOFA-2 reclassification. A group of 159 severely injured patients (7.3%) classified as MODS by SOFA-1 were reclassified to no-MODS by SOFA-2. Despite this reclassification, these patients had substantially higher ICU mortality (7.5% vs 0.7%, p<0.01), greater ventilator and vasopressor requirements, and longer hospital stays than patients classified as no-MODS by both systems. Conclusions SOFA-2 reduces MODS prevalence in severely injured patients and changes organ dysfunction classification, with lower rates of severe respiratory and cardiovascular dysfunction. This represents an important update in trauma MODS measurement and has implications for future trauma trial design. However SOFA-2 reclassification generates a small cohort a small but clinically significant group with occult MODS that warrants further evaluation in severely injured trauma patients.

Background/Objectives: Traumatic Brain Injuries (TBIs) affect more than 50 million individuals worldwide each year. Approximately 90% of individuals survive and experience persistent motor, cognitive, and emotional deficits, substantially contributing to a reduced quality of life and a global economic burden. TBI mechanisms are a foundational determinant of long-term recovery. The objective of this study was to examine long-term trends in functional locomotion ability over extended follow-up durations (>10 years) across distinct TBI mechanisms. The researchers hypothesized that TBIs caused by falls or violent mechanisms would be associated with poorer functional locomotor abilities and, subsequently, lower item scores than those sustained through automotive or recreational activities. Methods: Data were obtained from the Traumatic Brain Injury Model Systems (TBIMS) database at Craig Hospital in Englewood, Colorado, the largest longitudinal TBI data repository in the world. Functional locomotion was assessed using the Functional Independence Measure (FIM) Locomotion item as the primary outcome measure. To enhance measurement precision and ensure interval-level scaling, raw FIM scores were converted into logit-based estimates of latent functional ability using Rasch modeling. Longitudinal changes of these Rasch-transformed scores were analyzed using linear mixed-effects regression, accounting for individual-level variability and unbalanced follow-up data. Results: The findings demonstrated a clinically meaningful decline in functional ability among individuals with TBIs from violent mechanisms, particularly assault-related injuries and gunshot wounds, which were associated with chronic medical complications and limited functional independence. Conversely, TBIs from bicycling, unclassified vehicular incidents, and winter sports showed significant positive estimates, possibly reflecting higher premorbid physical fitness. Motor vehicle, motorcycle, pedestrian, and fall-related TBIs demonstrated steep early gains, followed by a period of recovery stabilization and plateau. In contrast, violence-related mechanisms were characterized by consistently low median scores, with minimal long-term improvement. Falls, gymnastics, track & field, and water sports did not exhibit meaningful changes in the context of the primary hypothesis. Conclusions: TBI mechanisms play a vital role in shaping long-term functional locomotion outcomes, with violence-related TBIs associated with poorer long-term functional independence. The results have clinically important implications, supporting earlier identification of high-risk populations and the development of targeted rehabilitation strategies during periods of heightened neuroplasticity. Rasch analysis integrated with linear mixed-effects modeling yields a robust analytic framework that uncovers subtle but meaningful differences in recovery trajectories across TBI mechanisms.

Traumatic brain injury (TBI) triggers pathological cascades that evolve across acute, subacute, and chronic phases. Astrocytes play a central role across these phases, and astrocyte reactivity is commonly evaluated using glial fibrillary acidic protein (GFAP) immunolabeling. However, in many TBI studies GFAP changes are characterized qualitatively or with manual or simple threshold-based measures on a small set of sections, limiting throughput and constraining analysis of region-specific heterogeneity in astrocyte responses. To overcome these limitations, we employed a ferret model of diffuse TBI (5 TBI, 5 sham), leveraging the ferrets gyrencephalic cortex, human-like regional fractional brain volumes, and astrocyte features that more closely resemble the human brain than rodent models. An AI-driven segmentation model validated for GFAP-stained ferret histology was integrated with atlas-based mapping to achieve whole-brain, region-resolved quantification of astrocyte reactivity over an average of 10 coronal slices per animal. Morphometric analysis using a custom SMorph-based pipeline characterized branching complexity and spatial domain features across defined regions. At seven days post-injury, TBI animals showed elevated astrocyte reactivity and hypertrophic remodeling, with significant expansion of convex hull area and elongation of secondary branches at the whole-brain level, most pronounced in the atlas-defined gray-matter region and cerebellum and brain-stem subregions, whereas white-matter showed a similar but less marked trend. Morphological changes were also detected in the hippocampus that did not show significant increases in astrocyte reactivity, indicating that structural remodeling represents a partially independent dimension of the astroglial response. These regional patterns are consistent with expected large tissue deformation and axonal strain in brainstem-cerebellar pathways and gray-matter at gray-white junctions in sagittal rotation, motivating future computational studies to quantify these links more directly. By combining region-resolved GFAP mapping with large-scale morphometry, this work provides a scalable framework for region-specific astrocyte mapping to support future multimodal, computational, and targeted neuroprotective studies.

Purpose. Prognostic assessments after acute brain injury are largely narrative, and how prognostic language relates to subsequent care has not been measured at scale. We quantified where it is written and its association with a subsequent code-status limitation. Materials and Methods. Multidatabase observational study of adults with acute brain injury or a related neurologic emergency, using MIMIC-IV (2008-2019; discharge summaries and radiology reports) and a timestamped MIMIC-III cohort (notes and code-status orders). The exposure was documented prognostic language; outcomes were its association with a subsequent full-code-to-limitation transition, note-stream location, and completeness of documented command-following relative to structured Glasgow Coma Scale (GCS) motor scores. Results. Among 31,993 admissions (27,054 patients; median age, 69 years; 54.9% male), prognostic language in the timestamped cohort (MIMIC-III) was associated with a subsequent code-status limitation after multivariable adjustment (adjusted hazard ratio, 4.3; 95% CI, 2.9-6.5; unadjusted 14-day cumulative incidence, 40% vs 8.5%), including the comfort-measures component (3.9), a higher-risk subgroup (4.4), and after acute-physiology adjustment (4.1); the association was concentrated in the first 3 days. Non-prognostic severity language showed no comparable association (hazard ratios, 1.1-1.3). Prognostic language localized almost entirely to the narrative (4.9% of discharge summaries vs 0.015% of radiology reports); command-following was undocumented in 55.7% of summaries, and no final-24-hour GCS motor score was charted in 72.8%. Conclusions. Documented prognostic language after acute brain injury was written in the narrative, not structured fields, and was associated with a subsequent code-status limitation after multivariable adjustment. This observational association cannot establish causation but warrants prospective study.

Traumatic brain injury (TBI) severity is typically classified using clinical indices that may have limited prognostic value. Objective measures of olfactory function depend on sensory, limbic, and memory networks and may provide a more specific marker of injury-related neural dysfunction. Seventy-nine individuals with TBI (48 mild, 31 moderate-to-severe) and 59 healthy controls completed an olfactory battery, including tests of odor percept identification (OPID9, OPID18), odor discrimination (OD10), and odor memory (POEM) ~4.04 (4.45) years after their most recent TBI. General linear models examined associations between olfactory outcomes and TBI severity, adjusting for age, age, sex, and education. Additional models examined the relationship between loss of consciousness (LOC) and olfactory functioning. The severity of the most recent TBI was significantly associated with all olfactory outcomes, after adjusting for age, sex, and education. Compared with controls, participants with moderate-to-severe TBI showed lower OPID9, OPID18, POEM, and OD10 performance, while participants with mild TBI showed lower OPID18 and POEM performance. LOC was associated specifically with odor memory in these models, as participants with prolonged (> 30min) LOC or LOC of unknown duration had lower POEM scores than those with no LOC. In TBI-only models, LOC remained associated with POEM after adjustment for TBI severity, whereas TBI severity was not associated with POEM after LOC was included. Long term olfactory functioning is sensitive to TBI severity, with generalized impairments across odor identification, discrimination, and odor memory. LOC characteristics appear especially relevant to odor memory, suggesting that olfactory memory may capture injury-related features beyond TBI severity classification alone.

Background: Early risk stratification in traumatic brain injury (TBI) is essential for timely triage, resource allocation, and clinical decision-making within the critical first hours of admission. This study aimed to compare the predictive performance of five established clinical scoring systems includes the Glasgow Coma Scale (GCS), Revised Trauma Score (RTS), Mechanism, GCS, Age, and Arterial Pressure (MGAP) score, Modified Early Warning Score (MEWS), and Rapid Emergency Medicine Score (REMS) for early mortality prediction in patients with blunt TBI. Methods: This single-center retrospective observational cohort study evaluated 444 patients aged 18 to 89 years with blunt TBI admitted to the intensive care unit of a tertiary trauma center in Tehran, Iran, between March 2022 and March 2025. The primary outcome was early mortality, defined as death within 24 hours of admission. Discriminative performance was assessed using the area under the receiver operating characteristic curve (AUC) with 95% confidence intervals (CI) derived via bootstrap resampling (1,000 iterations). Pairwise comparisons of AUCs were conducted, and optimal diagnostic cutoffs were identified using the Youden Index. Results: Within 24 hours of hospital admission, early mortality occurred in 97 patients (21.8%), while 347 patients (78.2%) survived. The trauma-specific and neurological scoring systems demonstrated the highest discriminative capacities: RTS achieved the highest accuracy (AUC = 0.676, 95% CI: 0.617-0.737), followed closely by GCS (AUC = 0.669, 95% CI: 0.608-0.727) and MGAP (AUC = 0.657, 95% CI: 0.594-0.724). General physiological scores exhibited lower performance, with MEWS achieving an AUC of 0.651 (95% CI: 0.595-0.707) and REMS demonstrating the lowest discriminative ability (AUC = 0.601, 95% CI: 0.538-0.659). Pairwise analysis confirmed that RTS GCS and MGAP significantly outperformed REMS, though no statistically significant differences were observed among RTS, GCS, and MGAP themselves. All evaluated systems demonstrated only modest overall predictive performance (AUC < 0.70). Conclusion: Trauma-specific and neurologically oriented scoring systems (RTS, GCS, and MGAP) provide superior and comparable prognostic accuracy for 24-hour mortality in blunt TBI compared to general emergency scores like REMS. However, the absolute predictive power of all evaluated models remains modest. Traditional systems relying on static admission variables fail to capture the dynamic, multifactorial nature of secondary brain injury, highlighting the critical need for multidimensional prognostic tools incorporating physiological time-series data or machine learning algorithms.

Importance: Neuroinflammation is a key component of the response to injury after concussion, but direct links between diffusion MRI metrics and specific plasma inflammatory pathways in human concussion have not been established. Objective: To examine associations between diffusion MRI metrics and pathway-level inflammatory proteomic signatures in adolescents during the subacute period after concussion. Design, Setting, and Participants: Cross-sectional analysis of data from the CARE4Kids Consortium, a six-site prospective study. Participants were English-speaking adolescents ages 11-17.99 with concussion and symptoms at 7-35 days post-injury. Data were collected between 2022-2024. Of 370 enrolled participants, 122 had both diffusion MRI and plasma proteomics available for analysis. Exposure: Advanced diffusion MRI metrics were converted to z-scores and participants were grouped by the spatial extent of outlier values (potholes and peaks) across 15 white matter regions of interest. Nine non-redundant groupings were selected for primary analysis. Main Outcomes and Measures: Pathway-level inflammatory profiles derived from gene set enrichment analysis (GSEA) of ~5,400 plasma proteins measured by Olink proximity extension assay, targeting nine hallmark inflammatory pathways spanning initiation through resolution. Persistent symptoms were assessed 64-115 days post-injury. Results: Diffusion metrics reflecting tissue disorganization were associated with upregulation of the coagulation pathway, consistent with hemostatic-inflammatory signaling. Metrics reflecting reduced tissue complexity and neurite density were associated with upregulation of interferon- and interferon-{gamma} response pathways, consistent with microstructural remodeling driven by cellular immune activation. Elevated free water content was associated with downregulation of most inflammatory pathways and trend-level transforming growth factor - {beta} upregulation, reflecting inflammatory resolution. Time since injury did not differ between groups based on free water (Kolmogorov-Smirnov p = 0.97), suggesting these differences reflect individual variability in recovery pace. Exploratory analyses showed a trend toward lower odds of persistent symptoms in the group with elevated free water content (odds ratio = 0.51, p = 0.18). Conclusions and Relevance: Multiple diffusion MRI metrics are differentially sensitive to distinct neuroinflammatory states in the subacute period after adolescent concussion. These findings suggest that diffusion imaging could serve as a non-invasive tool for inflammatory phenotyping, with potential implications for identifying patients who may benefit from targeted immunomodulatory intervention.

Traumatic brain injury (TBI) is one of the leading causes of emergency room visits in children under 10. Children are potentially more vulnerable to the adverse effects of TBI, given that their brains are still developing at the time of injury. Indeed, early life TBI has been linked to cognitive, social, and mood-related impairments later in life. The neuroimmune system has been implicated in adult TBI mechanisms and plays numerous key roles in brain development, making it an interesting candidate for linking pediatric TBI and prolonged behavioral alterations. Here we establish a rat model of mild pediatric TBI to investigate the relationship between early life TBI, acute responses of neuroimmune cells, and chronic behavioral dysregulation. At postnatal day 15, which is roughly equivalent to toddler age, male and female rat pups received a TBI via lateral fluid percussion injury. At 3 days post injury, TBI increased microglia and astrocyte coverage locally in the Perilesional Cortex but not in more distant corticolimbic regions. However, the hippocampus and prefrontal cortex did exhibit increased expression of the phagocytic marker CD68 in microglia, suggesting widespread glial activation even in the absence of gross coverage change. TBI also impacted mast cells, early-response innate immune cells, increasing their number and degranulation in multiple regions. In the juvenile and early adult periods, TBI impaired cognitive function, reduced sociability, and increased avoidance, with no change in anxiety-like behavior. Later in adulthood, TBI continued to impact cognitive behavior, increasing risky decision-making and impairing optimization months after injury. Together, these results suggest that pediatric TBI causes lasting cognitive and social dysregulation, possibly via acute neuroimmune alterations following injury at a critical period of brain development.

BackgroundTraumatic brain injury (TBI) is increasingly recognized as a chronic condition with lasting systemic consequences. Beyond persistent neuroinflammation, long-term TBI disrupts peripheral immune homeostasis, increasing susceptibility to infection and organ dysfunction, particularly in older patients. The voltage-gated proton channel Hv1, expressed in microglia and peripheral immune cells, regulates oxidative injury via modulation of NADPH oxidase activity. Yet few animal studies extend long enough to recapitulate the lifelong trajectory of human TBI, leaving the long-term effects of Hv1 deficiency on systemic immune homeostasis unresolved. MethodsYoung adult (3-month-old) male wild-type (WT) and Hv1 knockout (Hv1KO) mice were subjected to a moderate controlled cortical impact (CCI), and survival was monitored for up to 18 months post-injury, with endpoint analyses performed at 21 months of age. After neurological behavioral assessments, spleen, lung, liver, gut, ipsilateral cortex, and blood samples were collected for flow cytometry, qPCR, NanoString nCounter Panels, and in vivo plasma transfer studies. ResultsHv1 deficiency resulted in significantly increased mortality following TBI, starting at 14 months post-injury, compared with WT/TBI mice. No significant difference in survival was observed between the two sham groups. At 18 months post-injury, Hv1KO mice exhibited significant weight loss and splenomegaly. qPCR revealed an approximately 30-fold increase of pan-bacterial 16S rRNA levels in the spleens of Hv1KO/TBI mice, but not in the lungs or liver. Furthermore, chronic TBI in the Hv1KO mice led to a compromised intestinal tight junction and mucus barrier integrity, accompanied by aberrant activation of the cyclic GMP-AMP synthase-stimulator of interferon genes pathway in the spleen. Transcriptomic profiling of the spleen, liver, and lung revealed distinct post-injury immune signatures in Hv1KO mice. In contrast, surviving Hv1KO/TBI mice showed modest behavioral resilience and a partially neuroprotective cortical transcriptomic profile. Lastly, systemic transfer of plasma from WT/TBI or Hv1KO donors into naive young adult mice altered immune responses in the spleen, lung, and brain. ConclusionsHv1 plays a critical role in maintaining peripheral immune integrity and antibacterial defense throughout the chronic course of TBI. Despite conferring modest neuroprotection through attenuation of microglial-mediated oxidative stress, Hv1 deficiency exacerbated systemic phagocyte dysfunction and significantly reduced long-term survival.

Background: Serial glial fibrillary acidic protein (GFAP) trajectories have become an important framework for contextualizing evolving secondary-injury pathophysiology after moderate-to-severe traumatic brain injury (msTBI). However, total GFAP pools release and clearance signals that may be less useful for longitudinal bedside decisions than a proteoform-resolved assay. We compared total GFAP with neoGFAP, defined here as calpain-generated GFAP proteoforms intended to index active astroglial proteolysis during the subacute phase. Methods: We analyzed 651 serial serum samples from 95 msTBI patients from a previously described single-site cohort. Total GFAP and neoGFAP were measured on the same MSD platform from 6 to 240 hours after injury. Early (6 to 72 h) and late (96 to 240 h) windows, data-derived tertiles, and serial trajectory summaries were calculated directly from serial samples. Models were benchmarked against age plus admission post-resuscitation Glasgow Coma Scale (GCS) and the admission IMPACT extended risk score using five-fold stratified cross-validation. Outcomes were unfavorable outcome (GOSE 1 to 4), less-than-good recovery (GOSE 1 to 6), Disability Rating Scale (DRS) [&ge;]15, mortality, and neuroimaging worsening at 6 months. Results: The cohort contributed 95 serial biomarker profiles, with 90 participants evaluable for 6-month GOSE and 89 for DRS. Unfavorable outcome occurred in 57/90 (63.3%), and less-than-good recovery in 79/90 (87.8%). For unfavorable outcome, IMPACT plus early neoGFAP reached AUROC 0.85 versus 0.84 for IMPACT plus early total GFAP and 0.81 for IMPACT alone. For less-than-good recovery, IMPACT plus late neoGFAP achieved AUROC 0.90 versus 0.84 for late total GFAP and 0.82 for IMPACT alone. Secondary analyses for DRS, mortality, and neuroimaging worsening showed smaller differences. Conclusions: In this retrospective analysis, neoGFAP provided clearer incremental value than total GFAP for recovery-oriented monitoring, especially when late-window reassessment of patients who remained at risk for less-than-good recovery was required. Results support prospective testing of neoGFAP as a pathophysiology-informed adjunct to serial bedside decision making, repeat-assessment thresholds, and recovery stratification.

Purpose: Identifying head impacts linked to brain injury in sport remains challenging. Instrumented mouthguards quantify head-impact kinematics, and finite element (FE) modelling can transform these data into brain strain estimates, which may better reflect injury risk than kinematics alone. Here, we examined associations between mouthguard-measured kinematics, FE-derived strain, and plasma brain injury biomarker GFAP following head impacts. Methods: We analysed 41 video-verified impacts from male Australian football players, including 22 assessed for concussion (17 diagnosed) and 19 unassessed. Instrumented mouthguards recorded peak linear acceleration (PLA), peak rotational acceleration, and peak rotational velocity (PRV). Brain strain was estimated using the Imperial College FE brain model, and plasma GFAP was quantified using Simoa. Biomechanical-GFAP associations were examined using Spearman correlations and segmented regression. Results: For impacts overall, plasma GFAP was moderately correlated with PLA ({rho}=0.46, 95% CI: 0.20-0.66), PRV ({rho}=0.53, 95% CI: 0.20-0.78), and strain ({rho}=0.60, 95% CI: 0.32-0.80). Associations were stronger within concussion cases for strain ({rho}=0.86, 95% CI: 0.58-0.97) and PRV ({rho}=0.64, 95% CI: 0.15-0.93). Piecewise regression identified strain levels above which strain-GFAP relationships steepened across the whole-brain and brainstem. In concussion cases, supra-threshold brainstem strain was associated with greater symptoms. Conclusion: Finite element brain strain may better predict brain injury risk following a sport-related head impact than peak acceleration metrics. Stronger associations with plasma GFAP, particularly among concussion cases, and evidence of a biomechanical threshold, support the use of biomarker-informed strain measures in future risk modelling and the development of brain injury screening thresholds.

Objective: To identify brain injury metrics suitable for supporting sports head injury assessment by evaluating their association with brain tissue strain and consistency across sports. Methods: Head kinematics from 3,139 impacts in boxing, mixed martial arts, and rugby matches were recorded using instrumented mouthguards and used to calculate nine brain injury metrics. Impacts were simulated using an anatomically detailed finite element brain model to estimate peak 95th-percentile maximum principal strain (MPS) in the brain and brainstem, a measure of tissue deformation associated with long-term pathology. Sport-specific ordinary least squares models estimated xE, the metric value equivalent to a reference MPS of 0.21. Metric-MPS correlations and xE uncertainties were quantified using 5000 bootstrap resamples. Cross-sport consistency was assessed using the coefficient of variation (CV) of sport-specific median xE values, and uncertainty using the normalised confidence interval size (NCIS). Results: XGB, an extreme gradient boosting strain-prediction model, showed the strongest and most consistent correlations with whole-brain (r=0.924-0.974) and brainstem MPS (r=0.887-0.954) across all sports. PRV, BrIC and UBrIC also correlated strongly with whole-brain (r=0.724-0.930) and brainstem MPS (r=0.739-0.900), whereas HIC15 and HARM showed weaker correlation with MPS, particularly in rugby. XGB showed the lowest cross-sport variability (CV=0.034) and uncertainty (median NCIS=0.056). HARM, DAMAGE and HIC15 showed the greatest sport dependence (CV=0.575-0.588) and uncertainty (median NCIS=0.331-0.791). Conclusions: XGB, BrIC, and UBrIC demonstrated the strongest associations with brain tissue strain and the greatest consistency across sports. This study provides a biomechanically informed framework for selecting suitable metrics for sports HIA protocols.