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Background and Objectives: Traumatic brain injury (TBI) is a leading cause of long-term disability in working-age populations. Return to work is a key marker of recovery, yet most studies assess it as binary at fixed time points. We aimed to estimate transition probabilities to and from work disability during 5 years after TBI and how injury severity and preinjury sociodemographic and medical factors influence these probabilities.

Methods: We conducted a nationwide matched cohort study in Sweden using linked registers. Individuals aged 21-60 years with a TBI diagnosis between 2005 and 2016 were compared with up to 10 matched non-TBI individuals. TBI severity was proxied by care characteristics: TBI A (emergency visit or ≤ 2 days), TBI B (≥ 3 days), and TBI C (neurosurgery). Transition probabilities to and from work disability (>14 days sickness absence) were estimated with multistate models. Sociodemographic and medical factors were assessed with Cox regression.

Results: The cohort included 98,256 individuals with TBI and 981,191 matched non-TBI individuals (median age 39 years; 43% women). Transition probabilities to work disability were higher in all TBI groups: at 30 days, 5.5% (95% CI 5.4-5.7) for TBI A, 29% (28.0-30.7) for TBI B, and 43% (38.2-47.3) for TBI C, vs 0.5% (0.5-0.6) in non-TBI; at 5 years, 7.1% (7.0-7.3), 10.9% (10.2-11.7), and 12.9% (10.7-15.7), vs 4.0% (4.0-4.1). In TBI A and B, higher probability was predicted by older age (TBI A hazard ratio 1.23, 95% CI 1.20-1.26; TBI B 1.34, 1.21-1.48), female sex (TBI A 1.59, 1.56-1.62; TBI B 1.35, 1.26-1.44), and psychiatric disorders (TBI A 1.34, 1.30-1.39; TBI B 1.28, 1.11-1.48), while higher education (TBI A 0.83, 0.81-0.86) and city residence (TBI A 0.92, 0.90-0.95; TBI B 0.88, 0.80-0.95) were protective. In TBI C, only older age remained significant (1.59, 1.17-2.14).

Discussion: TBI was associated with persistently elevated transition probabilities to work disability across all severity groups, with early peaks in TBI B and C and a delayed increase in TBI A, influenced by sociodemographic and medical factors. However, the lack of standardized severity grading limits comparison with other studies. Still, these results suggest TBI increases long-term risk of work disability, supporting sustained individualized rehabilitation.

Background and Purpose: Biomarkers for neuronal damage have been shown to be elevated during the acute phase of COVID-19 in plasma and cerebrospinal fluid (CSF) of patients with neurological symptoms. Little is known about the temporal dynamics of these biomarkers and their pathophysiological relationship to neurocognitive post-COVID condition (neuro-PCC). Our aim was to conduct a follow-up of clinical symptoms and biomarkers of patients with neurological symptoms in the acute phase of COVID-19.

Methods: Follow-up was conducted > 4 months after onset of COVID-19 symptoms. Twenty-eight patients were included and underwent neurological examination, neuropsychiatric and cognitive assessments, and serological testing. Eight patients underwent lumbar puncture. Neurofilament light (NfL), total tau (T-tau), glial fibrillary acidic protein (GFAP), and neuronal antibodies were analyzed in serum or plasma and CSF.

Results: New-onset symptoms post-COVID were reported in 82%. Neurological examination revealed abnormalities in 32% of patients. GFAP and T-tau had normalized in CSF in all patients. However, one patient still showed elevated NfL chain levels in CSF, while two patients had elevated NfL in plasma. New-onset neuronal antibodies in serum were found in 5/27 (19%) and in one patient in CSF. No correlation was found between biomarker levels during acute COVID-19 disease and subsequent neurological symptoms or examination findings at follow-up.

Conclusion: Several patients reported new-onset neurological and cognitive symptoms, despite the absence of evidence of ongoing neuronal damage. Additionally, the presence of newly developed autoantibodies was detected in several patients, potentially signaling the emergence of post-COVID autoimmunity.

Long-term symptoms such as pain, fatigue, and cognitive impairments are commonly observed in individuals affected by coronavirus disease 2019 (COVID-19). Metabolites of the kynurenine pathway have been proposed to account for cognitive impairment in COVID-19 patients.

Here, cerebrospinal fluid (CSF) and plasma levels of kynurenine pathway metabolites in 53 COVID-19 patients and 12 non-inflammatory neurological disease controls in Sweden were measured with an ultra-performance liquid chromatography-tandem mass spectrometry system (UPLC-MS/MS) and correlated with immunological markers and neurological markers. Single cell transcriptomic data from a previous study of 130 COVID-19 patients was used to investigate the expression of key genes in the kynurenine pathway.

The present study reveals that the neuroactive kynurenine pathway metabolites quinolinic acid (QUIN) and kynurenic acid (KYNA) are increased in CSF in patients with acute COVID-19. In addition, CSF levels of kynurenine, ratio of kynurenine/tryptophan (rKT) and QUIN correlate with neurodegenerative markers. Furthermore, tryptophan is significantly decreased in plasma but not in the CSF. In addition, the kynurenine pathway is strongly activated in the plasma and correlates with the peripheral immunological marker neopterin. Single-cell transcriptomics revealed upregulated gene expressions of the rate-limiting enzyme indoleamine 2,3- dioxygenase1 (IDO1) in CD14⁺ and CD16⁺ monocytes that correlated with type II-interferon response exclusively in COVID-19 patients.

In summary, our study confirms significant activation of the peripheral kynurenine pathway in patients with acute COVID-19 and, notably, this is the first study to identify elevated levels of kynurenine metabolites in the central nervous system associated with the disease. Our findings suggest that peripheral inflammation, potentially linked to overexpression of IDO1 in monocytes, activates the kynurenine pathway. Increased plasma kynurenine, crossing the blood–brain barrier, serves as a source for elevated brain KYNA and neurotoxic QUIN. We conclude that blocking peripheral-to-central kynurenine transport could be a promising strategy to protect against neurotoxic effects of QUIN in COVID-19 patients.

Understanding how brain connectivity is disrupted across stages of traumatic brain injury (TBI) is essential for improving diagnosis and treatment. TBI poses major challenges in clinical assessment, requiring advanced neuroimaging and machine learning (ML) for effective patient stratification. This study classifies TBI patients into acute, chronic, and control groups using graph convolutional networks (GCNs) applied to structural connectomes derived from diffusion-weighted imaging (DWI). To enhance interpretability, Gradient-weighted Class Activation Mapping (Grad-CAM) was used to identify brain regions contributing to classification. The dataset included 40 participants: 18 acute TBI patients (Glasgow Coma Scale $\leq 6$ , enrolled after $\geq 24$ hours of unresponsiveness), 6 chronic patients with persistent disorders of consciousness, and 16 healthy controls. Nine acute patients who regained consciousness were later included in the chronic group to assess longitudinal changes. The GCN was trained on DWI-derived connectomes and evaluated using leave-one-subject-out (subject-wise) cross-validation. It achieved 83.67% accuracy, with precision, recall, and F1-score of 81.6%, 78%, and 79%, respectively, reported as per-fold averages. Grad-CAM identified thalamus, anterior cingulate cortex, and frontal cortex as key regions for group discrimination. Results suggest a shift from widespread neural disruption in acute TBI to more localized impairments in the chronic stage, possibly reflecting compensatory reorganization. Despite the limited sample size, the model's robustness was supported by conservative regularization and subject-wise validation. Notably, the GCN outperformed classical ML classifiers, offering superior accuracy and greater biological plausibility. These findings support the use of GCN-based pipelines for clinical decision support and highlight their potential to inform interpretable, ML-driven strategies for precision neurorehabilitation.

Patient-tailored treatment, also known as precision-medicine, has been emphasized as a prioritized area in traumatic brain injury research. In fact, pre-injury patient genetic factors alone account for almost 26% of outcome prediction variance following traumatic brain injury. Among implicated genetic variants single-nucleotide polymorphism in apolipoprotein E has been linked to worse prognosis following traumatic brain injury, but the underlying mechanism is still unknown. We hypothesized that apolipoprotein E genotype would affect the levels of pathophysiology-driving structural, or inflammatory, proteins in cerebral microdialysate following severe traumatic brain injury. We conducted a prospective observational study of patients with severe traumatic brain injury treated with invasive neuromonitoring including cerebral microdialysis at Uppsala University Hospital. All patients were characterized regarding apolipoprotein E genotype. Utilizing fluid- and plate-based antibody arrays, we quantified 101 proteins (of which 89 were eligible for analysis) in cerebral microdialysate at 1 day and 3 days following trauma. Statistical analysis included clustering techniques, as well as uni- and multi-variate linear mixed modelling. In total, 26 patients were included, and all relevant genotypes of apolipoprotein E were represented in the data. Among all proteins tested, 41 proteins showed a time-dependent expression level. There was a weak clustering tendency in the data, and not primarily to genotype, either depicted through t-distributed stochastic neighbour embedding or hierarchical clustering. Using linear mixed models, two proteins [the inflammatory protein CD300 molecule like family member f (CLM-1) and the neurotrophic protein glial-derived neurotrophic factor family receptor α1] were found to have protein levels concomitantly dependent upon time and genotype, albeit this effect was not seen following multiple testing corrections. Apart from amyloid-β-40 (Aβ) and Microtubule-associated protein tau, neither Aβ peptide levels nor the Aβ42/40 ratio were seen related to time from trauma or apolipoprotein E genotype. This is the first study in clinical severe traumatic brain injury examining the influence of apolipoprotein E genotype on microdialysate protein expression. Protein levels in cerebral microdialysate following trauma are seen to be strongly dependent on time from trauma, corroborating previous work on protein expression longitudinally following traumatic brain injury. We also identified protein expression level alterations dependent on apolipoprotein E genotype, which might indicate that apolipoprotein E affects ongoing pathophysiology in the injured brain at the proteomic level.

Traumatic brain injury (TBI) is a major cause of morbidity and mortality, not least in the elderly. The incidence of aged TBI patients has increased dramatically during the last decades. High age is a highly negative prognostic factor in TBI, and pharmacological treatment options are lacking. We used the controlled cortical impact (CCI) TBI model in 23-month-old male and female mice and analyzed the effect of post-injury treatment with 7,8 dihydroxyflavone (7,8-DHF), a brain-derived neurotrophic factor (BDNF)-mimetic compound, on white matter pathology. Following CCI or sham injury, mice received subcutaneous 7,8-DHF injections (5 mg/kg) 30 min postinjury and were sacrificed on 2, 7 or 14 days post-injury (dpi) for histological and immunofluorescence analyses. Histological assessment with Luxol Fast Blue (LFB)/Cresyl Violet stain showed that administration of 7,8DHF resulted in preserved white matter tissue at 2 and 7 dpi with no difference in cortical tissue loss at all investigated time points. Treatment with 7,8-DHF led to reduced axonal swellings at 2 and 7 dpi, as visualized by SMI-31 (Neurofilament Heavy Chain) immunofluorescence, and reduced number of TUNEL (Terminal deoxynucleotidyl transferase dUTP nick end labelling)/CC1-positive mature oligodendrocytes at 2 dpi in the perilesional white matter. Post-injury proliferation of Platelet-derived Growth Factor Receptor (PDGFR alpha)-positive oligodendodrocyte progenitor cells was not altered by 7,8-DHF. Our results suggest that 7,8-DHF can attenuate white matter pathology by mitigating axonal injury and oligodendrocyte death in the aged mouse brain following TBI. These data argue that further exploration of 7,8-DHF towards clinical use is warranted.

Acquired brain injury is an urgent situation that requires rapid diagnosis and treatment. Magnetic resonance imaging (MRI) and computed tomography (CT) are required for accurate diagnosis. However, these methods are costly and require substantial infrastructure and specialized staff. Circulatory biomarkers of acute brain injury may help in the management of patients with acute cerebrovascular events and prevent poor outcome and mortality. The purpose of this review is to provide an overview of the development of potential biomarkers of brain damage to increase diagnostic possibilities. For this purpose, we searched the PubMed database of studies on the diagnostic potential of brain injury biomarkers. We also accessed information from Clinicaltrials.gov to identify any clinical trials of biomarker measurements for the diagnosis of brain damage. In total, we present 41 proteins, enzymes and hormones that have been considered as biomarkers for brain injury, of which 20 have been studied in clinical trials. Several microRNAs have also emerged as potential clinical biomarkers for early diagnosis. Combining multiple biomarkers in a panel, along with other parameters, is yielding promising outcomes.

Introduction: Cerebral contusions (CCs) are common traumatic brain injuries known for their propensity to progress. Understanding their mechanical pathogenesis and predictive factors for progression is crucial for optimal management.

Research question: To provide an overview of current knowledge on CCs, including pathomechanisms, predictive factors of contusion progression, and management strategies.

Material and methods: A literature search was conducted using PubMed, Scopus and ISI web of knowledge focused on articles in English with the words "cerebral contusion" together with the words "traumatic brain injury", "pathomechanism", "progression of contusion", "predictive factors" and "management" alone or in combination.

Results: The management of CCs has evolved alongside the advances in neurointensive care, yet there is no consensus. Evidence on the effectiveness of early surgery, importantly, for the group which has the potential to expand, is limited. Some predictive factors for contusion progression have been identified, including age, injury mechanism, coagulopathy and initial contusion volume which could help to guide decision-making.

Discussion and conclusion: While various theories exist on pathomechanisms and several predictive factors for progression have been proposed, consensus on optimal management remains elusive. Individualized care guided by the predictive factors is essential. Challenges posed by antithrombotic medications highlight the need for early intervention strategies. Decompressive craniectomy could serve as a potential tool in severe traumatic brain injury management including contusions. Conducting large cohort studies to refine predictive models and harmonizing management approaches would help to improve outcomes of patients with CCs.

The central nervous system (CNS) evokes a complex inflammatory response to injury. Inflammatory cascades are present in traumatic, infectious, and noninfectious disorders affecting the brain. It contains a mixture of pro- andanti-inflammatory reactions involving well-known proteins, but also numerous proteins less explored in these processes. The aim of this study was to explore the distinct inflammatory response in traumatic brain injury (TBI)compared with other CNS injuries by utilization of mass-spectrometry. In total, 46 patients had their cerebrospinal fluid (CSF) analyzed with the use of mass-spectrometry. Among these, CSF was collected via an external ventricular drain (EVD) from n = 12 patients with acute TBI. The resulting protein findings were then compared with CSF obtained by lumbar puncture from n = 14 patients with noninfectious CNS disorders comprising relapsing–remitting multiple sclerosis, anti-N-methyl-D-aspartate-receptor encephalitis, acute disseminated encephalomyelitis, and n = 13 patients with progressive multifocal leukoencephalopathy, herpes simplex encephalitis, and other types ofviral meningitis. We also utilized n = 7 healthy controls (HC). In the comparison between TBI and noninfectious inflammatory CNS disorders, concentrations of 57 proteins significantly differed between the groups. Among them, 20 and 37 proteins were up- and downregulated, respectively. No proteins were uniquely identified in the TBI group. In the comparison of TBI and HC, 55 proteins were significantly different, with 24 and 31 proteins being up- and downregulated, respectively. Four proteins were uniquely identified in the TBI group, (FGG, HBA1, TKT,CA1). In the TBI versus infectious inflammatory CNS disorders, 57 proteins differed significantly between the groups, with 17 and 40 proteins being up- and down regulated, respectively. No proteins were uniquely identified in the TBI group. Due to large discrepancies between the groups compared, the following proteins were selected for further deeper analysis among those being differentially regulated: APOE, CFB, CHGA, CHI3L1, C3, FCGBP, FGA,GSN, IGFBP7, SERPINA3, SOD3, and TTR. We found distinct proteomic profiles in the CSF of TBI patients compared with HC and different disease controls, indicating a specific interplay between inflammatory factors, metabolic response, and cell integrity. In relation to primarily infectious or inflammatory disorders, unique inflammatory pathways seem to be engaged, and could potentially serve as future treatment targets.