Neurovascular and Inflammatory Effects of Biperiden in the Acute Phase of Moderate Traumatic Brain Injury: Evidence from a Non-Human Primate Model

Neurovascular and Inflammatory Effects of Biperiden in the Acute Phase of Moderate Traumatic Brain Injury: Evidence from a Non-Human Primate Model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Neurovascular and Inflammatory Effects of Biperiden in the Acute Phase of Moderate Traumatic Brain Injury: Evidence from a Non-Human Primate Model Viviam Sanabria, Christiane Gimenes, Simone Romariz, Amarildo Souza Gois, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9272332/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Traumatic brain injury (TBI) leads to extensive structural damage, neuronal loss, and functional deficits, along with marked disruption of cholinergic signaling and acute surges in acetylcholine. Biperiden, a muscarinic cholinergic antagonist, has emerged as a potential neuroprotective agent due to its ability to modulate synaptic plasticity and reduce excitotoxicity. Here, we evaluated the acute effects of biperiden in a translational non-human primate model of moderate TBI. Marmosets ( Callithrix jacchus, n=39 ) subjected to lateral fluid percussion injury (LFPI) received intraperitoneal biperiden (8 mg/kg) beginning 6 h post-injury, followed by two additional doses administered at 8 h intervals. At 24 h post-injury, brain tissue and serum were assessed using histology, immunofluorescence, and Single Molecule Array (SIMOA). Twenty-four hours post-trauma, biperiden treatment, which blocks M1 receptors, markedly reduced hippocampal neuronal degeneration, decreased UCH-L1 levels, and attenuated astrocyte activation compared to saline-treated controls. These findings demonstrate that repeated dosing with biperiden confers early neurovascular and glial protection and provides acute neuroprotection following moderate TBI, mitigating neuronal injury, excitotoxicity, and inflammation. This work highlights biperiden as a promising therapeutic candidate for early intervention after traumatic brain injury. Health sciences/Neurology Biological sciences/Neuroscience acute glia vessels biperiden hematomas SIMOA Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction A traumatic brain injury (TBI) originates when an external force impacts the head, potentially leading to anatomical lesions, brain dysfunction, and neuronal damage 1 . Following TBI of severity (moderate and severe), the risk of developing neurodegenerative disorders such as dementia, Parkinson’s, Alzheimer’s disease, and Epilepsy increases 2 – 4 . Therefore, it represents a significant cause of long-term disability, socioeconomic burden, and mortality 5 , 6 . To investigate the mechanisms underlying TBI and potential neuroprotective therapies, animal models have been developed to reproduce distinct injury paradigms and to elucidate the primary and secondary sequelae associated with human head trauma 7 . One of these models is the lateral fluid percussion injury (LFPI), which reproduces pathologies associated with human TBI, including neuronal loss, inflammation, gliosis, vascular disruptions, hemorrhages, and molecular disturbances 8 , 9 . In this research path, rodents (mice and rats) are the most widely used species 10 . However, it's important to note that rodents per se are not the best models to replicate the biomechanical and physiological parameters of human TBI 10 , mainly because their smooth or lissencephalic brains lack the cortical folding (gyri and sulci) present in the human gyrencephalic brain 11 . This is a significant limitation in TBI research, as the structural difference influences how the brain deforms within the skull 12 . In lissencephalic brains, trauma is uniformly distributed near the surface. Conversely, sulci cause concentrated stress at their bases, resulting in maximum mechanical stress occurring deeper in gyrencephalic brain tissue 11 . Moreover, rodents have less white matter than marmosets, sheep, and pigs, a distinction that is particularly relevant in studies of diffuse axonal injury or edema 11 . The gray-to-white matter ratio in the marmoset brain closely resembles that of humans 11 . The marmoset ( Callithrix jacchus ), a New World primate that diverged from humans approximately 45 million years ago, has a quasi-gyrencephalic brain with underdeveloped sulci 13 . This brain architecture, combined with the marmoset's primate-specific neurobiology, higher cognitive complexity, and its closer translational relevance 14 , positions it as a superior model for studying the mechanisms and consequences of TBI. Even though ferrets 15 and pigs 16 have also been investigated and both feature gyrencephalic brains, marmosets provide a better understanding of human neurobiology, offering hope for more effective treatments and interventions (e.g., potential therapeutic development, biomarkers) that may require primate-specific responses and offer increased regulatory and clinical relevance 17 . TBI profoundly disrupts cholinergic signaling 18 , with hippocampal acetylcholine levels increasing by approximately 74% immediately post-injury, and similar alterations have been reported after fluid percussion injury (a widely used TBI model) 19 – 21 . Biperiden, a muscarinic cholinergic antagonist, has been proposed as a potential modulator of neural plasticity following TBI, where it delays seizure onset and reduces severity 22 . Studies deploying biperiden to alter disease progression (epileptogenesis) after TBI in humans have, so far, not clearly shown its effectiveness 23 . There is a great debate as to whether models of status epilepticus (SE), the condition in which biperiden has mostly been tested, are the best strategy to study TBI 21 . In the present study, our aim is to investigate the effects of biperiden during the acute phase (24 hours) of moderate TBI in a non-human primate model, to observe and analyze structural and cellular alterations within the brain. We hypothesize that biperiden treatment during the acute phase of moderate TBI may affect neuronal and glial injury. We hope to shed light on relevant mechanistic understanding in ongoing clinical trials with biperiden in TBI 24 . 2. Methods 2.1 Animals: Thirty-nine adult marmosets ( C. jacchus) (24 males, 15 females; age: 2–6 years; weight: 180–380 g) were obtained from the Centro de Manejo e Conservação de Animais (CeMaCAS) and transported to the Federal University of São Paulo primate facility. They were housed individually in wire cages (50 cm × 50 cm × 50 cm) under controlled conditions, with stable room temperatures (25 ± 2ºC) and a 12-hour light-dark cycle starting at 7:00 AM. Animals received enrichment items (branches and wooden swings), free access to water, and fresh fruit twice daily. All procedures followed ARRIVE, NIH, and the Brazilian Institute of Environment and Renewable Natural Resources (IBAMA) guidelines, with approval of the Board for Ethics in the Use of Animals (CEUA, Comissão de Ética no Uso de Animais), an institutional ethics committee of the UNIFESP, protocol nº 5138271222, and were conducted following the guidelines for animal care and use of laboratory animals. All efforts were made to minimize the number of animals and their suffering. 2.2 Experimental Design and Groups: Animals were randomly assigned to four groups. The investigators were blinded to group allocation throughout the experiments and during outcome assessments. The experimental design is shown in Fig. 1 a. NAÏVE : Intact animals that underwent neither craniotomy nor LFPI (n = 8; 5 females and 3 males). SHAM-SAL : Animals underwent craniotomy but did not receive the LFPI impact. They were treated with a saline solution injection via intraperitoneal (i.p.) route (n = 9; 4 females and 5 males). TBI-SAL : Animals underwent LFPI and were treated with saline solution injections (i.p.) (n = 9; 3 females and 6 males). TBI-BIP : Animals underwent LFPI, were treated with biperiden injections (i.p) (n = 8; 2 females and 6 males). 2.3 LFPI model of brain trauma: Animals were anesthetized with isoflurane (3% for inhalation and 2% for maintenance, at a flow rate of 1-1.5L/min in freely breathing oxygen), followed by an intradermal injection of lidocaine (10 mg/kg) for local anesthesia. A 15 mm midline incision was made to expose the skull, and a 5 mm burr hole was drilled using an electric drill (Stoelting, Wood Dale, IL), ensuring the integrity of the dura mater in all trauma regions. At the craniotomy site, a cannula (a female Luer lock) was fixed with dental cement. After the cannula was securely placed and filled with sterile 0.9% saline solution. The female Luer lock on the animal's skull was then connected to the male Luer lock of the fluid percussion device (Model FP301 Signal Conditioner, AmScien Instruments). Stereotaxic coordinates for trauma induction were: +1.78 mm anterior-posterior (AP) to bregma, + 10 mm medial-lateral (ML), + 13 mm dorso-ventral (DV). The LFPI model was applied at a 17° angle, with a brief (10–15 ms) transient fluid-pressure pulse impacting the exposed dura. Pulse pressures were measured by an extracranial transducer and recorded on a storage oscilloscope (Fig. 1 a). After the LFPI, the cannula was removed from the skull, and the animal was sutured with 2 − 0 non-absorbable nylon. During stereotaxic surgery, animals were maintained normothermic (36–38°C) using a thermostatically controlled heating blanket, with rectal temperature continuously monitored (RightTemp Jr., Kent Scientific, USA). Physiological parameters, including heart rate, respiratory rate, and oxygen saturation, were continuously monitored using a pulse oximeter with paw sensors (Kent Scientific). Mucous membrane color was also assessed to ensure stable physiological conditions. At the time of injury induction, animals were fully recovered from isoflurane anesthesia. Animals received post-surgical care, including pentabiotic (0.1 mL/kg, i.m.) and flunixin meglumine (1 mg/kg, i.p.). They were kept on a heated blanket and hydrated until they had fully recovered. At 24-hour post-trauma, animals were deeply anesthetized with pentobarbital (100 mg/kg, i.p.) and transcardially perfused with phosphate-buffered saline, followed by 4% paraformaldehyde. 2.4 Biperiden treatment Animals were treated with biperiden hydrochloride dissolved in 0.9% saline at a concentration of 8 mg/Kg, i.p. (Cristália, Brazil). Saline (0.9%) served as a vehicle. Treatment started six hours after the induction of TBI or six hours after the induction of anesthesia in the sham-operated marmosets. The second dose was administered 8 hours after the first, and the third dose was administered 8 hours after the second. The biperiden dose of 8 mg/Kg was selected based on prior rodent studies demonstrating its safety and efficacy in modulating excitotoxicity and epileptogenesis 22 , 25 . The dose-dependent effects of similar anticholinergic treatments was demonstrated by Benassi et al. 25 therefore it can be safely administered after TBI. 2.5 Brain tissue preparation Twenty-four hours after LFPI-TBI, the animals were deeply anesthetized with sodium pentobarbital (100mg/kg, i.p.). A sternotomy was made to access the heart. Then, the animals were perfused through the heart. Perfusion started with 100 mL of 0.1M PBS solution (phosphate buffer solution; 5.52 g of monobasic sodium phosphate plus 21.88 g of dibasic sodium phosphate), then 100 mL of 4% paraformaldehyde (diluted in PBS solution). The brains were removed and post-fixed in 4% formaldehyde, then cryoprotected in 30% sucrose (diluted in PBS). They remained in this solution until they showed signs of dehydration, a procedure that usually occurred within 24 hours. Immediately after this period, the brains were dried and then frozen at -80°C. Subsequently, the brains were sectioned in a cryostat (Leica CM1850) in coronal sections (40 µm thick). Then, the sections were stored in an antifreeze solution (300 g of sucrose, 500 mL of PBS, and 300 mL of ethylene glycol) at -20°C until processed for histological and immunohistochemical analysis. Brain sections were selected according to the stereotaxic atlas 26 , ranging from + 3.64 to − 1.84 mm in the anterior–posterior axis relative to bregma (dorsal hippocampus), ensuring consistent sampling of both neocortical and hippocampal ipsilateral regions for histological assessment. 2.6 Histological Nissl staining Brain slices were mounted on gelatin-coated glass slides and stained for 8 min with 1% cresyl violet dissolved in distilled water and filtered. Stained slides were dehydrated for 1 minute using 100%, 96%, and 70% ethanol, cleared in xylene for 2 minutes, then covered with Entellan mounting medium, and coverslipped. Slides were imaged (6 brain sections for each animal), and the lesion area was assessed among the groups: NAIVE, SHAM-SAL, TBI-SAL, and TBI-BIP. Images were analyzed and imported into Fiji ( http://fiji.sc , a version of ImageJ; National Institutes of Health, http://imagej.nih.gov/ij ). The percentage of lesion volume was calculated as per the following formula 27 : \(\:Lesion\:volume=\frac{volume\:of\:contralateral\:hemisphere-volume\:of\:ipsilateral\:hemisphere\:}{volume\:\:contralateral\:hemisphere}\) * 100 2.7 Fluoro-Jade® B Fluoro-Jade® B (FJ-B, AG310 Merck-Millipore) was used to stain degenerating neurons. Fixed sections were mounted on glass slides, and FJ-B staining was performed as follows: The slides were mounted and let dry at room temperature for 3 to 5 days. Then, the slices were placed in an oven at 37°C for 20 minutes. The slices were then immersed in 100% ethanol for 3 minutes, followed by 1 minute each in 70% ethanol and distilled water. The slides were then incubated in 0.06% potassium permanganate (KMnO₄) in distilled water for 15 minutes. Next, the slides were rinsed in distilled water and transferred to a 0.0001% FJ-B staining solution in 0.1% acetic acid for 30 minutes. The FJ-B working solution was prepared from a stock FJ-B solution (0.01% in distilled water). After rinsing, the slides were coverslipped with DPX. The slides were analyzed using a 20X objective and a computer-based digitizing image system (Zeiss Axiovert; Carl Zeiss, Germany) connected to an Axiocam 208 color camera. Image analysis was conducted with ImageJ, the analyze particles plugin for cell counting in areas of interest. Because the lesion site was often absent or too damaged for reliable analysis (Fig. 1 ), we quantified only the adjacent intact tissue—the neocortex (motor, parietal, and temporal cortices) and hippocampus (CA1, CA3, and dentate gyrus (DG))—located within 2mm of the lesion border. 2.8 Immunofluorescence Immunofluorescence was performed to identify astrocytes, microglia, and vessels. Free-floating sections (six brain slices per animal) were washed five times with PBS solution to remove all anti-freezing solution and then incubated in a blocking solution (250 µL of Triton X-100, 90 mL of 0.1 M PBS, and 40 µL of goat serum) for 30 min at room temperature under constant stirring. After blocking, cells were incubated overnight with the following primary antibodies: polyclonal rabbit anti-Iba-1 (1:1000, Wako, 019-19741) for microglia/macrophages, and monoclonal mouse anti-glial fibrillary acidic protein (GFAP) (1:1000, Sigma, G3893) for astrocytes, diluted in blocking solution. The following day, after washing the sections in PBS, they were incubated for 2 hours with secondary antibodies (anti-mouse Alexa Fluor 488, anti-rabbit Alexa Fluor 568, 1:600, all from Invitrogen) in blocking solution. For vessel staining, after three PBS washes, the sections were incubated with Tomato lectin (TL; Lycopersicon esculentum; 1:200; Vector Laboratories; FL-1171-1) for 1 hour. Nuclei were stained with DAPI (4’,6-diamidino-2-phenylindole, 1:10,000; Thermo Fisher Scientific, Carlsbad, CA, USA). Finally, the sections were coverslipped with Fluoromount G™ (Thermo Fisher Scientific). For the analysis of Iba-1, GFAP, and TL, the slides were examined using a computer-based digitizing image system, Zeiss Axiocam 506 color ( https://www.zeiss.com/axiocam ), with a 20X objective. The laser and detector were maintained at constant settings for both cases during the acquisition of each staining set. For each slide, cells were qualitatively evaluated for their localization and morphology in the brain areas of interest only on the ipsilateral side of the trauma (the neocortex (motor, parietal, and temporal cortices) and hippocampus (CA1, CA3, and DG)). Slides and resultant images were coded, and fluorescence signals were quantified. Stained cells were quantified by branch count and average branch length using skeleton and vascular density analysis in Fiji ( http://fiji.sc , a version of ImageJ software, National Institutes of Health, http://imagej.nih.gov/ij ). Additionally, the number of vessels was counted manually. Three were randomly chosen from the six brain slices. For each region (the neocortex (motor, parietal, and temporal cortices) and hippocampus (CA1, CA3, and DG), three photos were taken, yielding a total of nine pictures per animal per region and 54 images per experimental group. For Iba-1 and GFAP analyses, the skeleton-derived parameters—number of branches and average branch length—were subjected to agglomerative hierarchical clustering using the average linkage method. This approach groups data based on their similarity, producing a hierarchical dendrogram in which the branching levels represent the degree of dissimilarity between clusters. In the dendrogram, clusters are depicted as nodes, and the vertical axis represents the degree of similarity between them. Naive groups are represented by numbers from 1–4, SHAM-SAL from 5–8, TBI-SAL from 9–12, and TBI-BIP from 13–16. 2.9 Single Molecule Array (SIMOA)® Detection of blood-derived brain biomarkers associated with TBI was performed using the SIMOA platform (Quanterix Corporation, Lexington, MA). Total tau (T-tau; a marker of neuronal function), Neurofilament Light Chain (NfL, an indicator of neuronal damage), Glial Fibrillary Acidic Protein (GFAP; a marker of astrocytic damage), and Ubiquitin C-Terminal Hydrolase L1 (UCH-L1; an early marker of neuronal injury). These biomarkers were selected for their sensitivity to TBI-related damage. Serum biomarker levels were quantified using the Neurology 4-Plex B (N4PB) assay, a specific immunoassay kit that detects NFL, total tau, GFAP, and UCHL-1. The samples were thawed, vortexed, and centrifuged for the analysis. The analysis was performed at Richet/IDOR in Rio de Janeiro using the SIMOA HD-1 device. Serum samples from animal models were thawed, and 60 µL of each sample was pipetted into each well of a 96-well plate, along with the assay-validated calibrators. The device was loaded with the necessary reagents and supplies, including pipettes, commercial kit beads, discs, and the sample plate. After adjusting the parameters, the assay was initiated and lasted approximately 4–5 hours. The automated calibration cycles, pipetting, washing, incubation, matrix transfer, and signal reading recorded the intensity of the fluorescent signals emitted by the microparticles, expressed in picograms per milliliter (pg/mL). The calibration curve converted the signals obtained from the samples into quantifiable concentrations of the biomarkers, a conversion typically performed automatically by the SIMOA software. 2.10 Statistical analysis Sample size calculation was performed a priori using G*Power (v 3.1.9.7). The calculation is based on one-way ANOVA (fixed effects, considering four groups), a small effect size (f = 0.19), a significance level of 5% (α = 0.05), and a statistical power of 0.95. Effect size was calculated using Cohen´s d, and randomization and group allocation were performed by blind investigators. Normality and homogeneity were assessed. To compare independent groups, the Kruskal-Wallis (KW) test was applied appropriately, followed by the Dunn post-hoc test. As an exploratory analysis, hierarchical clustering with the average linkage method and Euclidean distance was employed. Correlation matrix, though the Spearman r was employed to identify immunohistochemical variables. Principal component analysis (PCA) was performed to explain the greatest variation in the immunohistochemical variable and reduce data dimensionality. All variables were standardized (mean-centered and scaled to unit variance) prior to analysis. Data are presented as the mean ± standard deviation (SD), and P-values < 0.05 are considered statistically significant. Data analyses were performed using GraphPad Prism version 11.0 (GraphPad Software Inc., San Diego, CA., http://www.graphpad.com ), R version 4.3.2, and RStudio. 3. Results 3.1 Moderate LFP-induced TBI in marmosets resulted in variable hematoma formation Following parameter standardization for inducing moderate TBI in marmosets, the optimal pressure range was determined to be 1.38–2.25 atm (mean 1.78 ± 0.26 atm; Fig. 1 b), with a 17° impact angle consistently producing moderate injury, as established in our previous study (Sanabria et al., 2025, unpublished data) 28 . Of the 39 animals, 2 died during anesthesia, and 3 died due to trauma. The acute mortality rate in the TBI group (within 24 h post-impact) was 15% (3/20), with all deaths occurring immediately after injury. Among the 17 animals that survived LFPI, 8 (47%) developed subdural hematomas and 2 (12%) developed epidural hematomas (Fig. 1 c). Hematomas were identified at euthanasia by blind investigators after removal of the cranium and dura mater. Among animals with hematomas (n = 8), 5 belonged to the TBI-SAL group (1.66–2.25 atm) and 3 to the TBI-BIP group (1.50–1.61 atm), with a mean pressure of 1.81 ± 0.07 atm. Animals without hematomas were exposed to pressures ranging from 1.38 to 2.02 atm. 3.2 TBI-SAL animals exhibited a significantly larger lesion volume The percentage of lesion volume induced by TBI was quantified using Nissl staining. Lesion volume was calculated by subtracting the volume of the ipsilateral hemisphere from that of the contralateral hemisphere. Statistical analysis with the Kruskal–Wallis test (KW (3) = 10.13; p = 0.0051) revealed significant differences between the Naïve and TBI group. Specifically, TBI-SAL animals displayed a significantly greater lesion volume compared with Naïve animals ( p = 0.016; Fig. 1 d). 3.3 Neuronal degeneration was significantly higher in the TBI-SAL group in CA1 FJ-B staining was employed to evaluate neuronal degeneration in the neocortex (motor, parietal, and temporal cortices) and hippocampus (CA1, CA3, and DG). In the neocortex (across the three analyzed areas), a statistically significant group difference was revealed (KW(3) = 10.42; p = 0.0038). Post-hoc analysis (Dunn’s test) indicated that both TBI-SAL (145 ± 43.01; p = 0.024) and TBI-BIP (132 ± 39.37; p = 0.047) groups exhibited significantly greater neuronal degeneration compared with the Naïve group (20.75 ± 16.30; Fig. 2 b I). When we analyzed the cortical regions independently, statistically significant differences were observed in the parietal (KW(3) = 11.35; p = 0.0014) and temporal cortex (KW(3) = 11.18; p = 0.0016). In both cortical regions, TBI groups (TBI-SAL and TBI-BIP) had more neuronal degeneration compared with Naive group (See Supplemental Materials and Figure S1 ). In the hippocampus, the CA1 region showed statistically significant group differences (KW(3) = 10.94; p = 0.0022). TBI-SAL group (126 ± 37.73; p = 0.007) displayed significantly higher neuronal degeneration compared with the Naïve group (21.25 ± 8.92; Fig. 2 b II). While, in the CA3 region, no statistically significant differences were detected among groups. In the DG, statistically significant differences (KW(3) = 11.02; p = 0.0020) were observed. The SHAM-SAL group (84.60 ± 22.66; p = 0.043) exhibited significantly higher neuronal degeneration compared with the TBI-BIP group (30.25 ± 7.84; Figs. 2 b III-IV). 3.4 Biperiden increased vessel numbers across cortical and hippocampal regions, whereas vascular density remained unchanged. Concerning the number of vessels in the different areas analyzed. In the neocortex (across the three analyzed areas), we observed statistically significant differences among the groups (KW(3) = 10.38; p = 0.0040 ). The TBI-SAL group had an increase in the number of vessels (62.08 ± 19.28) compared to the Naïve group (30.21 ± 8.22; p = 0.0250; Fig. 3 b I). However, when we analyzed different parts of the neocortex independently, we observed statistically significant differences in the parietal cortex (KW(3) = 9.50; p = 0.0093 ) and in the temporal cortex (KW(3) = 11.47; p = 0.0012 ). In the parietal cortex, the SHAM-SAL (59.46 ± 20.81; p = 0.009 ) group and the TBI-BIP (54.00 ± 3.65; p = 0.017 ) group had more vessels than Naive (31.13 ± 8.04; see Supplemental Material and Figure S2). In the hippocampus, in the CA1 region, we observed statistically significant differences among the groups (KW(3) = 12.51; p = 0.0002). The SHAM-SAL had more vessels (57.71 ± 12.59) compared to the Naïve (22.56 ± 2.78; p = 0.011 ) and the TBI-SAL (30.71 ± 8.00; p = 0.04 ). Moreover, the TBI-BIP (57.29 ± 5.99 vessels) group also had more vessels than the Naïve ( p = 0.012 ) and more than TBI-SAL ( p = 0.039; Fig. 3 b II). Similarly to the cortex, in CA3 (KW(3) = 11.15; p = 0.0017 ) and DG (KW(3) = 9.42; p = 0.0087 ) we observed statistically significant differences among the groups, in both cases the SHAM-SAL [in CA3:59.29 ± 18.17, in DG:67.39 ± 24.75] group had more vessels than the Naïve group [in CA3:24.90 ± 3.76, in DG:24.67 ± 6.68; Figs. 3 b III-IV]. No significant differences in vascular density were observed among the groups across the analyzed regions (Figs. 3 c I-VIII). 3.5 Astrocytes in the TBI-SAL group exhibited reduced astrocytic branching, while TBI-BIP had longer processes A skeleton analysis was performed to assess astrocyte morphology by measuring branch number and length in the neocortex and hippocampus. Significant differences in astrocyte branch number were observed only in the cortex (KW(3) = 14.49; p < 0.0001). Post hoc analysis showed that both TBI-SAL (61.25 ± 11.00 branches; p = 0.047) and TBI-BIP (47.50 ± 10.41 branches; p = 0.0024) had significantly fewer branches compared to the SHAM-SAL group (326.2 ± 97.61 branches; Fig. 4 b I-IV). When cortical regions were analyzed separately, branch numbers also differed significantly across groups. In the motor cortex (KW(3) = 10.94; p < 0.01), SHAM-SAL showed more branches than TBI-BIP. In the parietal and temporal cortex (both KW(3) = 13.06; p < 0.001), both TBI groups exhibited reduced branching compared to SHAM-SAL. Astrocyte branch length differed significantly between groups in the cortex (KW(3) = 14.11; p < 0.0001), with the TBI-BIP group (29.82 ± 9.25 µm) showing longer branches than the TBI-SAL group (3.53 ± 2.27 µm; p = 0.0097). Similar differences were observed across all cortical regions—motor (KW(3) = 8.82; p = 0.01), parietal (KW(3) = 12.95; p < 0.0001), and temporal cortex (KW(3) = 11.76; p < 0.001)—with TBI-BIP consistently showing greater branch length than TBI-SAL (see Supplemental Material and Figure S3). In the hippocampus, branch length also differed significantly among groups. In CA1 (KW(3) = 10.47; p = 0.0036), CA3 (KW(3) = 12.31; p = 0.0004), and DG (KW(3) = 10.94; p = 0.0022), the TBI-BIP group showed significantly longer astrocyte branches than the TBI-SAL group. In the DG, the Naive group also exhibited longer branches than TBI-SAL (Figs. 4 c III-IV). Hierarchical cluster analysis based on branch number and average branch length revealed two main clusters for branch number across the cortex and hippocampus, separating SHAM-SAL from the other experimental groups. For branch length, clustering separated TBI-BIP from the other groups in the cortex and CA3, while in the DG, Naive clustered with TBI-BIP, and in CA1, these groups formed separate clusters. 3.6 Microglia in the TBI-SAL group exhibited a reduced number of microglia branching, accompanied by longer process length Skeleton analysis was also performed to evaluate microglia morphology by measuring branch number and branch length in the neocortex and hippocampus (CA1, CA3, DG) (Fig. 5 a-b). Regarding the number of microglial branches in the cortex, statistically significant differences were observed among groups (KW (3) = 10.16; p = 0.0048 ). Dunn's post-hoc analysis indicated that the NAIVE (51.75 ± 22.75 branches; p = 0.044) group had a higher number of microglia branches than TBI-SAL (12.25 ± 5.18 branches). Moreover, when we analyzed different parts of the neocortex independently, we observed statistically significant differences in the NAÏVE and SHAM-SAL groups, which had more branches than TBI-SAL [in motor (KW(3) 6.81; p = 0.0062) , parietal (KW(3) = 7.42; p = 0.0045 ), and temporal (KW(3) = 8.25; p = 0.0030 ) cortices ] (See Supplemental Material, S4). In the hippocampus, CA1 and CA3 had statistically significant differences in branch number, which were observed among groups (CA1: KW (3) = 10.92; p = 0.0022; CA3: KW(3) = 11.83; p = 0.0008). Dunn's post-hoc analysis indicated that the SHAM-SAL (CA1 60.60 ± 26.43 branches; p = 0.014; CA3: 61.60 ± 20.38 branches; p = 0.042 ) group had a higher number of microglia branches than TBI-SAL (CA1 13.50 ± 10.88 branches; CA3 19.00 ± 12.19 branches ). In DG, statistically significant differences in the number of branches were observed among the groups KW(3) = 13.48; p < 0.0001 ).Dunn's post-hoc analysis indicated that the SHAM-SAL (65.60 ± 20.18 branches) group had a higher number of microglia branches than TBI-SAL(8.00 ± 5.35 branches; p = 0.0062 ) and TBI-BIP (12.75 ± 1.50 branches ; p = 0.042 ). Regarding the microglial average branch length, no statistically significant differences were observed among groups in the cortex, CA1, or DG. However, when we analyze the different parts of the neocortex, only the temporal cortex (KW(3) 3.87; p = 0.038) showed significant differences in the microglial branches between the TBI-BIP group (47.32 ± 10.12 µm) and the SHAM-SAL (18.17 ± 4.45 µm). In the hippocampus, in CA3, significant differences were detected (KW(3) = 8.07; p = 0.029 ). The TBI-BIP group displayed longer microglial branches (31.45 ± 7.00 µm) compared to the SHAM-SAL group (15.31 ± 1.71 µm; p = 0.038 ). Hierarchical clustering of microglial morphology, based on branch number and average branch length, revealed distinct grouping patterns. For the number of branches, two main clusters were identified in the cortex and CA1: one comprising the Naïve and SHAM-SAL groups, and another including the remaining experimental groups. In CA3 and DG, the SHAM-SAL group clustered separately from the others. Regarding average branch length, two clusters were observed in the cortex and CA1 (TBI-SAL and TBI-BIP versus the remaining groups), while in CA3, TBI-SAL separated from the others. In the DG, SHAM-SAL and TBI-SAL formed a distinct cluster from the remaining groups. 3.7 Correlation matrix and Principal component analysis (PCA) among the immunohistochemical variables In the correlation matrix, we observed a significantly strong positive correlation between the number of GFAP (astrocytes) and Iba-1 (microglia) branches (r = 0.71, p < 0.001), and a moderate positive correlation between GFAP and Iba-1 average branch length (r = 0.40,p = 0.001), FJ-B (degenerative neurons) and the number of vessels(r = 0.29, p = 0.017) and the number of vessels and GFAP branch count (r = 0.26, p = 0.029). In contrast, there was a significant negative correlation between Iba-1 branch count and average branch length (r= -0.36, p = 0.002), FJ-B and GFAP branch length (r=-0.41, p < 0.001), as well as between GFAP branch count and Iba-1 branch length (r=-0.32, p = 0.008; Fig. 6 a). Regarding PCA analysis, we observe that the first two principal components explain 49.02% of the total variance: 30.63% by the first component and 18.39% by the second (Fig. 6 b). Therefore, we can say that principal component 1 (PC1) is mainly driven by GFAP and Iba-1 average branch length and FJ-B (Fig. 6 c), while PC2 is mainly driven by the number of GFAP and Iba-1 branches, and the number of vessels (Fig. 6 d),. Two dimensions were selected as plot shown in Supplemental Material S5. 3.8 Early neuronal injury marker was more expressed in the TBI-SAL group than in the TBI-BIP group Regarding the biomarkers of our interest (t-Tau, NfL, GFAP, and UCH-L1). Significant statistical differences were observed only in the UCH-L1 among the groups (KW (2) = 5.79; p = 0.0457 ). Post-hoc test revealed that the TBI-SAL group has higher levels of UCH-L1 (1380 ± 588 pg/mL) compared to SHAM-SAL (211 ± 145 pg/mL; p = 0.03 ) and TBI-BIP (234 ± 77.27pg/mL; p = 0.04 ). No statistically significant difference was observed in the other biomarkers (Figs. 7 I-IV). 3. Discussion This study investigated the acute (24 hours) effects of biperiden on structural and cellular alterations following moderate TBI, as assessed by LFPI, in a non-human primate model ( C. jacchus ). While previous studies have examined the impact of biperiden in SE models 22 , 25 and LFPI in rodents 29 , this is the first study to assess its impact in a quasi-gyrencephalic species (marmoset), whose neuroanatomical and immunological features offer greater translational relevance to human TBI. Serum analysis revealed elevated levels of the early neuronal injury marker UCH-L1 in TBI-SAL animals compared with SHAM-SAL and TBI-BIP groups within 24 hours after TBI, indicating greater acute neuronal injury in the absence of biperiden. UCH-L1 is a small neuronal protein that regulates the addition and removal of ubiquitin from proteins targeted for degradation 30 . The elevated serum UCH-L1 levels observed in the TBI-SAL group may be attributed to neuronal injury and blood–brain barrier (BBB) disruption 31 , as we maintained the integrity of the dura mater in all regions during stereotaxic surgery. Thus, under both physiological and pathological conditions, UCH-L1 plays a critical role in maintaining axonal integrity and neuronal homeostasis 30 , 32 . Previous studies have reported significantly elevated UCH-L1 levels in cerebrospinal fluid (CSF) and serum of severe TBI patients compared to controls, with strong correlations to injury severity, particularly during the acute phase 30 . Conversely, UCH-L1 levels from the TBI-BIP group suggest unreported protection conferred by biperiden after traumatic brain injury. Brophy and colleagues also demonstrated that serum UCH-L1 was a better predictor of survival at three months post-injury than CSF levels 32 . Interestingly, while previous work from our laboratory showed no differences in plasma UCH-L1 levels among groups 24 h after TBI in male rats 29 , the present study in marmosets revealed significant increases in serum UCH-L1 levels, consistent with findings from Saletti and collaborators (2023) 33 . In contrast, Morris and colleagues suggested that UCH-L1 may not be a TBI-specific biomarker but rather reflect broader ischemic or neurovascular injury, which aligns with the possibility that its elevation indicates general neuronal stress rather than trauma specificity 34 ; however, our data did not show an increase in the TBI-BIP and SHAM-SAL as both passed for the stereotaxic surgery that may generate at some degree a neurovascular injury. Although changes in GFAP and T-tau were not statistically significant. It was curious to observe an increase in both biomarkers in the TBI-SAL group. Elevated serum GFAP levels are commonly found in patients following an acute stroke or TBI, reflecting the extent of astroglial injury 35 . While T-tau is correlated more with acute injury and/or rate of ongoing neurodegeneration rather than damage to neuronal axons from trauma 36 . Histological analysis further demonstrated that TBI-SAL animals had larger lesion volumes than the Naive group, with subdural and epidural hematomas present in both TBI conditions. Interestingly, the incidence of hematomas was approximately 25% higher in the TBI-SAL group than in the TBI-BIP animals. Regarding lesion volume, Villapol and colleagues 37 reported that cortical lesions following controlled cortical impact in male mice expand within the first 24 hours, peak at 3 days, and gradually decrease thereafter (7–60 days). In our study, no prominent lesion cavity was observed, likely because the analysis was performed 24 hours post-injury. Interestingly, with biperiden, we did not observe this statistical difference compared to the Naive group. This may be because, in untreated TBI animals, elevated acetylcholinesterase activity in the brain or microvessels may promote opening of the BBB and exacerbate brain injury 38 . Therefore, biperiden's inhibitory activity might have reduced brain injury. After traumatic brain injury, excessive acetylcholine release contributes to neuronal hyperexcitability and glutamate-mediated 29 , 39 , 40 Biperiden, a competitive antagonist at M1 muscarinic receptors, competes with acetylcholine in a 1:1 manner and modulates receptor activity. Reducing postsynaptic excitability may help attenuate early neuronal stress and excitotoxic processes. 41,42 At the cellular level, TBI-SAL animals exhibited increased neuronal degeneration in the cortex and CA1 regions compared to Naive controls. Moreover, in the CA1, a larger number of blood vessels were observed in the TBI-BIP and SHAM-SAL groups than in the TBI-SAL group, suggesting that untreated TBI animals exhibited reduced vascularization. After TBI, the neurovascular unit is disrupted. Continuous blood flow supplying oxygen and glucose is vital for brain integrity; when flow is reduced or fails to meet metabolic demands, neuronal function declines, and delayed cell death pathways are activated 37 , 43 . Early alterations in cerebral vasculature are evident after TBI, and these vascular deficits do not appear to fully recover, persisting for weeks to months after the initial injury. 44 In contrast, the TBI-BIP group showed higher TL-positive cell counts in CA1 than the TBI-SAL group, indicating enhanced functional recovery and potentially improved cerebral blood flow. Although the difference between TBI-BIP and TBI-SAL was statistically significant only in the CA1 region, TL-positive vessel counts were consistently higher in TBI-BIP across regions. A similar increase was observed in the TBI-BIP group compared to the NAIVE group in the parietal cortex and CA3 region. Furthermore, the TBI-BIP group displayed a broader distribution of cell density, despite the absence of other significant differences. Reduced cerebral blood flow contributes to an excitotoxic cascade characterized by excessive glutamate release and accumulation of toxic metabolites in the extracellular space. This process leads to rapid neuronal death accompanied by intense astrocytic activation 37 . Therefore, the lower TL-positive vessel counts observed in our TBI-SAL group may be related to a reduction in GFAP and Iba-1 branch number and average branch length in this group. As well as the increased number of FJ-B positive cell count on the cortex and CA1 of the TBI-SAL group. Moreover, a study comparing changes in BBB permeability in gyrencephalic and lissencephalic models following TBI suggests that gyrencephalic brain structures may be more vulnerable to vascular disruption than lissencephalic models. Cerebrovascular alterations were observed in ferret brains after blast TBI, including microvascular bleeds followed by significant astrocytosis and microglial activation, consistent with neuroinflammation compared to rodents 45 . GFAP-positive astrocytes in the TBI-BIP group displayed longer branches in the motor cortex, parietal cortex, temporal cortex, CA1, CA3, and DG regions than in the TBI-SAL group, indicating a potentially enhanced capacity for synaptic support and tissue repair. Regarding astrocytes and microglia, our data showed a reduced number of branches in the TBI-SAL and TBI-BIP groups compared to Naive and SHAM-SAL animals 24 hours after injury. This reduction may reflect the early activation of resident glial cells, as astrocytes and microglia are among the first to initiate the post-traumatic inflammatory cascade 46 , 47 . A similar decrease in glial complexity within the ipsilateral cortex has been reported by Villapol and colleagues, who showed hypertrophic astrocytes in the lesion and peri-lesional areas three days post-TBI 37 . Dihné and colleagues (2001) described an acute decrease in astrocyte number and immunoreactivity within 24 hours after TBI, followed by a reactive increase through proliferation and hypertrophy, leading to astrogliosis at later stages 48 . Furthermore, astrocytic apoptosis can occur as early as 6 hours after trauma, and has been proposed to precede neuronal degeneration by several hours 49 . Following CNS injury, microglia undergo substantial morphological remodeling, characterized by retraction of their processes and adoption of an amoeboid phenotype 50 . Studies have also demonstrated that Iba-1 expression is upregulated in activated microglia compared with their non-reactive, surveillant counterparts 29 , 50 . Curiously, the hierarchical analysis revealed that, with respect to the number of microglia branches that the SHAM-SAL and Naïve separate apart from the TBI groups except in CA3 and DG, where the SHAM-SAL separate from the others. Regarding the number of astrocytic branches, the SHAM-SAL group clustered separately from all other groups, with the greatest number of GFAP+ branches. This is particularly concerning, as Sham animals demonstrate significant neuronal degeneration in certain regions, increased vessel counts, and distinct astrocytic and microglial clustering patterns. This raises important questions about the biological impact of the craniotomy procedure itself, even though we maintained dura mater integrity during the experiments. One plausible explanation for this distinction is the craniotomy procedure itself, which has been shown in previous studies to cause measurable structural and functional alterations in the underlying brain tissue. This is likely due to the disruption of the intricate network of nerve fibers and blood vessels connecting the brain to the skull during bone flap removal 51 . Moreover, as was mentioned before gyrencephalic brain structures may be more vulnerable to vascular disruption than lissencephalic models 40 . In contrast, when examining the average branch length of astrocytes, two main clusters emerged: one composed of the Naïve and TBI-BIP groups, and another comprising the remaining groups. This pattern suggests that biperiden may help preserve glial homeostasis following injury. The pronounced astrocytic hypertrophy observed in the TBI-SAL group may reflect a maladaptive glial response, potentially impairing neuronal plasticity, as described by Burda and colleagues 52 . Moreover, our correlation matrix shows a strong correlation between GFAP and Iba-1 branch count, which is also evident in the PCA analysis. The PCA analysis indicated that astrocytic and microglial morphological complexity, GFAP, and Iba-1 average branch length vary independently. Suggesting that branching features are the dominant source of variation across samples, as well as number of vessels potentially reflecting structural remodeling in response to TBI and to biperiden. Taking together, these findings underscore the central role of the cholinergic system, not only in PTE but also in epileptogenesis. Recent studies have demonstrated that anticholinergic interventions can modulate this process; for example, prolonged scopolamine treatment after lithium–pilocarpine–induced SE markedly reduced spontaneous recurrent seizures (SRS) at six months, even though its early effects were minimal 53 . Consistent with this, work from our group has shown that biperiden administration following pilocarpine-induced SE reduces both the number and intensity of seizures 22 . This study possesses several limitations, including the absence of subacute and chronic assessments, which would clarify whether functional improvements develop over time. The short observational window precluded evaluation of cognitive function. This parameter was intentionally excluded to avoid confounding potential memory deficits with early inflammatory responses. The study focused on a single time point (24 h) to specifically investigate the acute phase of injury, when excitotoxicity, neuronal damage, and glial activation are at their peak, allowing the early effects of biperiden in non-human primates to be evaluated before later-stage changes occur. Additionally, the use of animals from a conservation facility rather than captive-bred individuals introduces uncertainty regarding possible prior trauma that may have influenced the outcomes. The heterogeneity of the sample with respect to age and weight also limits data interpretation. Furthermore, the absence of a SHAM-biperiden group complicates interpretation, as it prevents determining whether biperiden's effects are specific to TBI or reflect a more general modulation of surgical injury responses. Nevertheless, this work represents an important first step toward understanding the effects of biperiden on marmosets. In summary, our study was the first to demonstrate the acute effects of biperiden in non-human primates following a moderate TBI induced by LFPI. Untreated TBI animals exhibited significantly elevated UCH-L1 levels, indicating greater neuronal injury and BBB disruption, whereas animals treated with biperiden (TBI-BIP) showed a mitigated effect. Histologically, biperiden appeared to preserve vascular integrity and neuronal viability, particularly in the hippocampal CA1 and CA3 regions. However, in glia analyses, the biperiden effect was less pronounced, with reduced glial branching observed in both TBI groups; biperiden-treated animals exhibited longer astrocytic and microglia processes, suggesting improved glial homeostasis and repair potential. Overall, these findings indicate that biperiden confers an early neurovascular and glial protection during the acute phase of TBI in a non-human primate model. Declarations Acknowledgments In memory of our dear veterinarian, Paulo Varoni Cavalcanti. We also extend our sincere thanks to Professor Fábio Cruz for kindly allowing us to use his microscope, to Master Simone Cinini for her help with the marmoset’s transportation, and to Mery Liz Alfaro for her help. Funding Fundação de Amparo à Pesquisa supported this work do Estado de São Paulo (FAPESP grants 2018/24561-5 and 2022/00249-8), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brazil (CAPES; Finance Code 001), and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq; grants 311619/2019-3, and 312904/2021-5). VS and SR (2017/05242-3) received post-doctoral fellowships from the São Paulo Research Foundation (FAPESP). CRediT authorship contribution statement V. S.: Conceptualization, Methodology, Formal Analysis, Validation, and Data Curation, Writing- Original Draft . C. G. : Conceptualization, Methodology, Formal Analysis, Review. S. R.: Methodology and Review . A. S. G.: Methodology and Review. M. B. B.: Methodology and Review. M. L. C.: Methodology, Formal Analysis, Validation, and Data Curation, Review. J. L. W.: Methodology and Review. M. L. F. : Conceptualization, Validation, Review, and Editing. L. E. M.: Conceptualization, Review, and Editing . B. M. L. : Conceptualization, Methodology, Review, Editing, and Supervision Ethics Statement: All procedures were conducted in compliance with ARRIVE, NIH, and IBAMA (Brazilian Institute of Environment and Renewable Natural Resources) guidelines, and were approved by the institutional Animal Care and Use Committee (protocol #5138271222). Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper. Consent for publication All authors have agreed to the published version of this manuscript. Data Availability The datasets used and/or analyzed during the current study are available at the following link https://osf.io/zq5am/overview upon reasonable request References Menon, D. K., Schwab, K., Wright, D. W. & Maas, A. I. Position statement: Definition of traumatic brain injury. Arch. Phys. Med. Rehabil. 91 , 1637–1640 (2010). Brett, B. L., Gardner, R. C., Godbout, J., Dams-O’Connor, K. & Keene, C. D. Traumatic Brain Injury and Risk of Neurodegenerative Disorder. Biol. Psychiatry 91 , 498–507 (2022). Sivanandam, T. M. & Thakur, M. K. Traumatic brain injury: A risk factor for Alzheimer’s disease. Neurosci. Biobehav. Rev. 36 , 1376–1381 (2012). Pitkänen, A. et al. Epileptogenesis in experimental models. Epilepsia 48 , 13–20 (2007). Teasdale, G. & Jennett, B. Assessment of coma and impaired consciousness. A practical scale. Lancet 37 , 52–56 (1974). Maas, A. I. R. et al. Traumatic brain injury: progress and challenges in prevention, clinical care, and research. Lancet Neurol. 21 , 1004–1060 (2022). Xiong, Y., Mahmood, A. & Chopp, M. Animal models of traumatic brain injury. Nat. Rev. Neurosci. 14 , 128–142 (2013). McIntosh, T. K. et al. Traumatic brain injury in the rat: characterization of lateral fluid-percussion model. Neuroscience 28 , 233–244 (1989). Dixon, C. E. et al. A fluid percussion model of experimental brain injury in the rat. J. Neurosurg. 67 , 110–119 (1987). Cenci, M. A., Whishaw, I. Q. & Schallert, T. Animal models of neurological deficits: How relevant is the rat? Nat. Rev. Neurosci. 3 , 574–579 (2002). Vink, R. Large animal models of traumatic brain injury. J Neuro Res 1–9 (2017) doi:10.1002/jnr.24079. Finnie, J. W. Animal models of traumatic brain injury: a review. Aust Vet J. 79 , (2001). Zhang, N. & Zhang, Y. Correlation between gyral size, brain size, and head impact risk across mammalian species. Brain Res. 1828 , 148768 (2024). Prins, N. W. et al. Common Marmoset (Callithrix jacchus) as a Primate Model for Behavioral Neuroscience Studies. J Neurosci Methods. 1 , 35–46 (2017). Shinmyo, Y., Hamabe-Horiike, T., Saito, K. & Kawasaki, H. Investigation of the Mechanisms Underlying the Development and Evolution of the Cerebral Cortex Using Gyrencephalic Ferrets. Front. Cell Dev. Biol. 10 , 1–12 (2022). Donat, C. K. et al. Effects of lateral fluid percussion injury on cholinergic markers in the newborn piglet brain. Int. J. Dev. Neurosci. 28 , 31–38 (2010). Homman-Ludiye, J. & Bourne, J. A. The Marmoset: The Next Frontier in Understanding the Development of the Human Brain. ILAR J. 61 , 248–259 (2020). McIntosh, T. K. Neurochemical sequelae of traumatic brain injury: therapeutic implications. Cerebrovasc. Brain Metab. Rev. 6 , 109–162 (1994). Gorman, L. K., Fu, K., Hovda, D. A., Becker, D. P. & Katayama, Y. Analysis of acetylcholine release following concussive brain injury in the rat. J Neurotrauma 6 , 203 (1989). Gorman, L., Fu, K., Hovda, D. A., Murray, M. & Traystman, R. J. Effects of Traumatic Brain Injury on the in the Rat. J Neurotrauma 13 , 457–463 (1996). Andrade, P. et al. Seizure Susceptibility and Sleep Disturbance as Biomarkers of Epileptogenesis after Experimental TBI. Biomedicines 10 , (2022). Bittencourt, A. S. et al. Modification of the natural progression of epileptogenesis by means of biperiden in the pilocarpine model of epilepsy. Epilepsy Res. (2017). Foresti, M. L. et al. Initial clinical evidence on biperiden as antiepileptogenic after traumatic brain injury — a randomized clinical trial. Front. Neurol. 1–10 (2024) doi:10.3389/fneur.2024.1443982. Foresti, M. L. et al. Biperiden for prevention of post-traumatic epilepsy: A protocol of a double-blinded placebo-controlled randomized clinical trial (Biperiden trial). PLoS One 17 , 1–11 (2022). Benassi, S. K. et al. Two decades of research towards a potential first anti-epileptic drug. Seizure 90 , 99–109 (2021). Paxinos, G., Watson, C., Petrides, M., Rosa, M. & Tokuno, H. The marmoset brain in stereotaxic coordinates . The Marmoset Brain in Stereotaxic Coordinates (2012). doi:10.1007/978-0-387-78385-7. Boyko, M. et al. Traumatic brain injury-induced submissive behavior in rats : link to depression and anxiety. 1–10 (2022) doi:10.1038/s41398-022-01991-1. Sanabria, V. et al. Standardizing the lateral fluid percussion model of trauma in marmosets (Callithrix jacchus): regional vulnerability and inflammatory response. Brazilian J. Med. Biol. Res. 59 , (2026). Braga, M. et al. Effects of acute biperiden treatment following traumatic brain injury in male rats. Sci Rep 29 , 44775 (2025). Papa, L. et al. UCH-L1 is a novel biomarker for severe traumatic brain injury in human. Crit. Care Med. 38 , 138–44 (2010). Mondello, S. et al. Ubiquitin Carboxy-Terminal Hydrolase L1 (UCH-L1) is increased in cerebrospinal fluid and plasma of patients after epileptic seizure. BMC Neurol. 12 , 1 (2012). Brophy, G. M. et al. Biokinetic analysis of ubiquitin C-terminal hydrolase-L1 (UCH-L1) in severe traumatic brain injury patient biofluids. J. Neurotrauma 28 , 861–870 (2011). Saletti, P. G. et al. Early preclinical plasma protein biomarkers of brain trauma are influenced by early seizures and levetiracetam. Epilepsia Open 8 , 586–608 (2023). Morris, M. C. et al. UCH-L1 is a Poor Serum Biomarker of Murine Traumatic Brain Injury After Polytrauma. J Surg Res 244 , 63–68 (2019). Sacco, M. A. et al. The Role of GFAP in Post-Mortem Analysis of Traumatic Brain Injury : A Systematic Review. Int. J. Mol. Sci. 26 , 185 (2025). Schöll, M. et al. Molecular and Cellular Neuroscience Biomarkers for tau pathology. Mol. Cell. Neurosci. 97 , 18–33 (2019). Villapol, S., Byrnes, K. R. & Symes, A. J. Temporal dynamics of cerebral blood flow, cortical damage, apoptosis, astrocyte-vasculature interaction and astrogliosis in the pericontusional region after traumatic brain injury. Front. Neurol. 5 JUN , 1–9 (2014). Chen, Y., Shohami, E., Bass, R. & Weinstock, M. Cerebro-protective effects of ENA713 , a novel acetylcholinesterase inhibitor , in closed head injury in the rat. Brain Res. 18–24 (1998). Dixon, C. E. et al. Time course of increased vulnerability of cholinergic neurotransmission following traumatic brain injury in the rat. Behav. Brain Res. 70 , 125–131 (1995). Shin, S. S. & Dixon, C. E. Alterations in cholinergic pathways and therapeutic strategies targeting cholinergic system after traumatic brain injury. J. Neurotrauma 32 , 1429–1440 (2015). Sanabria, V. et al. Anticholinergics : A potential option for preventing posttraumatic epilepsy. Front. Neurosci. 1–8 (2023) doi:10.3389/fnins.2022.1100256. Scarr, E. Muscarinic Receptors: Their Roles in Disorders of the Central Nervous System and Potential as Therapeutic Targets. CNS Neurosci. Ther. 18 , 369–379 (2012). Westergren, H., Ryding, E., Zbornickova, V. & Hillman, J. Traumatic Occlusion of the Internal Carotid Artery in a Healthy Young Male : Effects on the Regional Cerebral Blood Flow. Acta Neurochir. (Wien). 113 , 91–95 (1991). Salehi, A., Zhang, J. H. & Obenaus, A. Response of the cerebral vasculature following traumatic brain injury. J. Cereb. Blood Flow Metab. 37 , 2320–2339 (2017). Rao, K. V. R. et al. Comparison of blood-brain barrier permeability changes in gyrencephalic ( ferret & non-human primate ) and lissencephalic ( rat ) models following blast overpressure exposures. Exp. Neurol. 392 , 115375 (2025). Hernandez-Ontiveros, D. G. et al. Microglia activation as a biomarker for traumatic brain injury. Front. Neurol. 4 MAR , 1–9 (2013). Diaz-Arrastia, R. et al. Pharmacotherapy of Traumatic Brain Injury : State of the Science and the Road Forward : Report of the Department of Defense Neurotrauma Pharmacology Workgroup. J. Neurotr 158 , 135–158 (2014). Dihné, M., Block, F., Korr, H. & Töpper, R. Time course of glial proliferation and glial apoptosis following excitotoxic CNS injury. Brain Res. 902 , 178–189 (2001). Huang, T. et al. Traumatic injury activates MAP kinases in astrocytes: Mechanisms of hypothermia and hyperthermia. J. Neurotrauma 26 , 1535–1545 (2009). Caplan, H. W. et al. Spatiotemporal Distribution of Microglia After Traumatic Brain Injury in Male Mice. ASN Neuro 12 , (2020). Cole, J. T. et al. Craniotomy: True sham for traumatic brain injury, or a sham of a sham? J. Neurotrauma 28 , 359–369 (2011). Burda, J. E., Bernstein, A. M., Sofroniew, M. V & Angeles, L. Astrocyte roles in traumatic brain injury. Exp Neurol. 275 , 305–315 (2016). Meller, S., Käufer, C., Gailus, B., Brandt, C. & Löscher, W. Scopolamine prevents aberrant mossy fiber sprouting and facilitates remission of epilepsy after brain injury. Neurobiol. Dis. 158 , (2021). Additional Declarations No competing interests reported. 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Braga","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Matheus","middleName":"B.","lastName":"Braga","suffix":""},{"id":623877881,"identity":"0583644e-4f5a-47a6-ba40-aabd0a60e32a","order_by":5,"name":"Michele Longoni Calió","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Michele","middleName":"Longoni","lastName":"Calió","suffix":""},{"id":623877882,"identity":"43d6b2ad-f63d-4bbe-8386-0edc24f71502","order_by":6,"name":"Juliana Lima Willers","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Juliana","middleName":"Lima","lastName":"Willers","suffix":""},{"id":623877883,"identity":"63feeb4f-6fcf-4dde-8ba0-2b52e3300a4d","order_by":7,"name":"Maira L. Foresti","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Maira","middleName":"L.","lastName":"Foresti","suffix":""},{"id":623877884,"identity":"5d33859d-e915-4074-8c07-c4093783b0c8","order_by":8,"name":"Luiz Eugênio Mello","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Luiz","middleName":"Eugênio","lastName":"Mello","suffix":""},{"id":623877885,"identity":"6b4dd6be-13d3-448e-b9e9-590fc7f4b6b8","order_by":9,"name":"Beatriz M. Longo","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Beatriz","middleName":"M.","lastName":"Longo","suffix":""}],"badges":[],"createdAt":"2026-03-30 23:08:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9272332/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9272332/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107173269,"identity":"efcb648e-c5e4-47f4-a90b-447e82606d0b","added_by":"auto","created_at":"2026-04-17 15:12:22","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":889654,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExperimental design and LFPI model standardization.\u003c/strong\u003e \u003cstrong\u003ea- \u003c/strong\u003eOverview of the experimental design. Stereotaxic surgery and induction of traumatic brain injury (TBI) by lateral fluid percussion injury (LFPI) were performed on day 1 in \u003cem\u003eC. jacchus\u003c/em\u003e. Twenty-four hours after trauma, animals were euthanized and perfused for histological analyses. \u003cstrong\u003eb-\u003c/strong\u003eGeneral pressure value in atmospheres (ATM). \u003cstrong\u003ec-\u003c/strong\u003ePercentage of Hematoma's presence in animals submitted to TBI (n=17). \u003cstrong\u003ed-\u003c/strong\u003e \u003cem\u003e\u003cstrong\u003eI\u003c/strong\u003e\u003c/em\u003e\u003cem\u003e.\u003c/em\u003ePercentage of lesion volume among the groups and \u003cem\u003e\u003cstrong\u003eII. \u003c/strong\u003e\u003c/em\u003eImages of Nissl staining across the groups; arrows indicate the location of the cortex and hippocampus. Statistical significance: \u003cem\u003e*p \u0026lt; 0.05; **, p\u0026lt; 0.01; ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001.\u003c/em\u003e Data are shown as the mean ± standard deviation of the mean.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9272332/v1/7b2af6730017fa6eab193707.png"},{"id":107173272,"identity":"e2bbdddc-94cd-4536-9195-b345ccedbb1f","added_by":"auto","created_at":"2026-04-17 15:12:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1765757,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFluorojade B (FJ-B) positive cells in neocortex and dorsal hippocampus (CA1, CA3, and DG).\u003c/strong\u003e \u003cstrong\u003ea-\u003c/strong\u003e Photomicrographs of FJ-B in the cortex for each group NAIVE, SHAM-SAL, TBI-SAL, and TBI-BIP. \u003cstrong\u003eb-\u003c/strong\u003e Graphic representation of the number of FJ-B positive cells in \u003cstrong\u003eI-\u003c/strong\u003e Cortex , \u003cstrong\u003eII-\u003c/strong\u003eCA1, \u003cstrong\u003eIII-\u003c/strong\u003eCA3, \u003cstrong\u003eIV-\u003c/strong\u003eDG. Yellow arrows represent the degenerating neurons. Statistical significance: \u003cem\u003e*p \u0026lt; 0.05; **, p\u0026lt; 0.01; ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001.\u003c/em\u003e Data are shown as the mean ± standard deviation of the mean. Scale bars = 40 μm.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-9272332/v1/22b38848797809f366b2295d.png"},{"id":107173357,"identity":"4446d176-6cb6-491e-9973-8e851ae73400","added_by":"auto","created_at":"2026-04-17 15:12:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2830229,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTomato Lectin (TL) results.\u003c/strong\u003e \u003cstrong\u003ea- \u003c/strong\u003ePhotomicrographs of TL immunofluorescence of all groups; cortex and dorsal hippocampus regions (CA1, CA3, and DG). TL (green), DAPI (blue).\u003cstrong\u003e b-\u003c/strong\u003e TL positive cells count in the \u003cstrong\u003eI-\u003c/strong\u003eCortex, \u003cstrong\u003eII-\u003c/strong\u003eCA1, \u003cstrong\u003eIII-\u003c/strong\u003eCA3, and \u003cstrong\u003eIV-\u003c/strong\u003eDG. \u003cstrong\u003ec- \u003c/strong\u003ePercentage of vascular density. \u003cstrong\u003eI -\u003c/strong\u003eCortex; \u003cstrong\u003eII- \u003c/strong\u003eCA1;\u003cstrong\u003eIII-\u003c/strong\u003eCA3; I\u003cstrong\u003eV\u003c/strong\u003e-DG. Statistical significance: \u003cem\u003e*p \u0026lt; 0.05; **, p\u0026lt; 0.01; ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001.\u003c/em\u003e Data are shown as the mean ± standard deviation of the mean. Scale bars = 40 μm.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-9272332/v1/f9f7290043854cae9cc764e4.png"},{"id":107173350,"identity":"562dfa14-ac08-4a4e-a60a-4ad43868d79b","added_by":"auto","created_at":"2026-04-17 15:12:39","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3021711,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAstrocytes (GFAP) results\u003c/strong\u003e. \u003cstrong\u003ea-\u003c/strong\u003ePhotomicrographs of GFAP immunofluorescence of all groups' cortex and dorsal hippocampus regions (CA1, CA3, and DG). GFAP (red), and DAPI (blue). \u0026nbsp;Small boxes with dashed lines indicate the selected zoom-in areas. \u003cstrong\u003eb-\u003c/strong\u003eNumber of GFAP branches \u003cstrong\u003eI-\u003c/strong\u003eCortex, \u003cstrong\u003eII-\u003c/strong\u003eCA1, \u003cstrong\u003eIII-\u003c/strong\u003eCA3, \u003cstrong\u003eIV-\u003c/strong\u003eDG. \u003cstrong\u003ec-\u003c/strong\u003eAverage GFAP branch length (µm). \u003cstrong\u003eI-\u003c/strong\u003eCORTEX, \u003cstrong\u003eII-\u003c/strong\u003eCA1, \u003cstrong\u003eIII-\u003c/strong\u003eCA3, \u003cstrong\u003eIV-\u003c/strong\u003eDG. \u003cstrong\u003ed-\u003c/strong\u003eHierarchical cluster analysis Naive groups are represented by numbers from 1-4, SHAM-SAL from 5-8, TBI-SAL from 9-12, and TBI-BIP from 13-16.\u003cstrong\u003e I- \u003c/strong\u003eGFAP number branches. Orange boxes represent the SHAM-SAL cluster, and blue boxes represent OTHER (NAIVE, TBI-SAL, and TBI-BIP) cluster . \u003cstrong\u003eII-\u003c/strong\u003e GFAP Average branch. Orange boxes represent the TBI-BIP or NAIVE and TBI-BIP clusters, and blue boxes represent OTHER (NAIVE, SHAM-SAL, and TBI-SAL) clusters. Statistical significance: \u003cem\u003e*p \u0026lt; 0.05; **, p\u0026lt; 0.01; ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001.\u003c/em\u003e Data are shown as the mean ± standard deviation of the mean. Scale bars = 40 μm.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-9272332/v1/3942d47b3e522dac591c7462.png"},{"id":107173351,"identity":"a9fc0dea-df97-4bf6-81b5-29bc2d4f5302","added_by":"auto","created_at":"2026-04-17 15:12:39","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2650280,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMicroglia (Iba-1) results\u003c/strong\u003e. \u003cstrong\u003ea-\u003c/strong\u003ePhotomicrographs of Iba-1 immunofluorescence of all groups cortex and dorsal hippocampus regions (CA1, CA3, and DG). Iba-1 (red), and DAPI (blue). Small boxes with dashed lines indicate the selected zoom-in areas. \u003cstrong\u003eb-\u003c/strong\u003eNumber of GFAP branches \u003cstrong\u003eI-\u003c/strong\u003eCortex, \u003cstrong\u003eII-\u003c/strong\u003eCA1, \u003cstrong\u003eIII-\u003c/strong\u003eCA3, \u003cstrong\u003eIV-\u003c/strong\u003eDG. \u003cstrong\u003ec-\u003c/strong\u003eAverage GFAP branch length (µm). \u003cstrong\u003eI-\u003c/strong\u003eCORTEX, \u003cstrong\u003eII-\u003c/strong\u003eCA1, \u003cstrong\u003eIII-\u003c/strong\u003eCA3, \u003cstrong\u003eIV-\u003c/strong\u003eDG. \u003cstrong\u003ed-\u003c/strong\u003eHierarchical cluster analysis Naive groups are represented by numbers from 1-4, SHAM-SAL from 5-8, TBI-SAL from 9-12, and TBI-BIP from 13-16.\u003cstrong\u003e I-\u003c/strong\u003eIba-1 number branches. Orange boxes represent the SHAM-SAL cluster, and blue boxes represent OTHER (NAIVE, TBI-SAL, and TBI-BIP) cluster. \u003cstrong\u003eII-\u003c/strong\u003e Iba-1 Average branch. Orange boxes represent the TBI-BIP or NAIVE and TBI-BIP clusters and blue boxes represent OTHER (NAIVE, SHAM-SAL, and TBI-SAL) cluster. Statistical significance: \u003cem\u003e*p \u0026lt; 0.05; **, p\u0026lt; 0.01; ***, p \u0026lt; 0.001; ****, p \u0026lt; 0.0001.\u003c/em\u003e Data are shown as the mean ± standard deviation of the mean. Scale bars = 40 μm.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-9272332/v1/d192cc6b7e23e6570de30670.png"},{"id":107173330,"identity":"d2736b68-dc53-4328-bdc7-b54edcb76d84","added_by":"auto","created_at":"2026-04-17 15:12:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":709741,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation matrix and principal component analysis (PCA) of immunohistochemical variables. a-\u003c/strong\u003eHeatmap showing Spearman correlation coefficients for all pairwise comparisons. The scale on the right indicates coefficient values, where 1.0 denotes a perfect positive correlation, −1.0 a perfect negative correlation, and 0 no correlation. Color intensity ranges from yellow to dark purple: yellow to orange indicates positive correlations, while dark purple indicates negative correlations; stronger relationships are represented by greater color intensity. \u003cstrong\u003eb–d\u003c/strong\u003e PCA analysis. \u003cstrong\u003eb-\u003c/strong\u003e PCA biplot showing the first two principal components, with PC1 explaining 30.63% and PC2 explaining 18.39% of the variance. Loadings are shown in gray, and PC scores are shown in lilac. \u003cstrong\u003ec-\u003c/strong\u003e Distribution of PC scores for PC1. \u003cstrong\u003ed-\u003c/strong\u003e Distribution of PC scores for PC2. The color scale on the right indicates contribution levels: high contributors in yellow, intermediate in orange, and low in purple.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-9272332/v1/0e1b9d3ff63d0017b8d2ad41.png"},{"id":107173358,"identity":"6864b176-5864-492b-9269-3bdf112af8b4","added_by":"auto","created_at":"2026-04-17 15:12:44","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":367469,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSIMOA analysis.\u003c/strong\u003e \u003cstrong\u003ea--\u003c/strong\u003eSingle Molecule Array (SIMOA) among the groups \u003cstrong\u003eI-\u003c/strong\u003et-Tau, \u003cstrong\u003eII-\u003c/strong\u003eNeurofilament Light Chain (NfL), \u003cstrong\u003eIII-\u003c/strong\u003e Glial Fibrillary Acidic Protein (GFAP), \u003cstrong\u003eIV-\u003c/strong\u003e Ubiquitin C-Terminal Hydrolase L1 (UCHL-1). Data are shown as the mean ± standard deviation of the mean. Levels marked with asterisk (*) indicate significant differences: \u003cem\u003e*p \u0026lt; 0.05, **p \u0026lt; 0.01, ***p \u0026lt; 0.001.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-9272332/v1/4cdbaec67232a3dace719efd.png"},{"id":107481648,"identity":"ab22ed62-b10a-4ca3-a989-cd54ae75a6c1","added_by":"auto","created_at":"2026-04-22 02:19:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":12196859,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9272332/v1/ee9eefa9-32dc-41ef-9dc2-1c76de0d5a4d.pdf"},{"id":107173349,"identity":"ad0d4207-e989-4e8d-a898-a0026ab6e7fc","added_by":"auto","created_at":"2026-04-17 15:12:38","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2305882,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalmaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-9272332/v1/6c4d0abfc3e6592491083b78.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Neurovascular and Inflammatory Effects of Biperiden in the Acute Phase of Moderate Traumatic Brain Injury: Evidence from a Non-Human Primate Model","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eA traumatic brain injury (TBI) originates when an external force impacts the head, potentially leading to anatomical lesions, brain dysfunction, and neuronal damage \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Following TBI of severity (moderate and severe), the risk of developing neurodegenerative disorders such as dementia, Parkinson\u0026rsquo;s, Alzheimer\u0026rsquo;s disease, and Epilepsy increases \u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Therefore, it represents a significant cause of long-term disability, socioeconomic burden, and mortality \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo investigate the mechanisms underlying TBI and potential neuroprotective therapies, animal models have been developed to reproduce distinct injury paradigms and to elucidate the primary and secondary sequelae associated with human head trauma\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. One of these models is the lateral fluid percussion injury (LFPI), which reproduces pathologies associated with human TBI, including neuronal loss, inflammation, gliosis, vascular disruptions, hemorrhages, and molecular disturbances \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this research path, rodents (mice and rats) are the most widely used species\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. However, it's important to note that rodents \u003cem\u003eper se\u003c/em\u003e are not the best models to replicate the biomechanical and physiological parameters of human TBI\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, mainly because their smooth or lissencephalic brains lack the cortical folding (gyri and sulci) present in the human gyrencephalic brain\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. This is a significant limitation in TBI research, as the structural difference influences how the brain deforms within the skull\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn lissencephalic brains, trauma is uniformly distributed near the surface. Conversely, sulci cause concentrated stress at their bases, resulting in maximum mechanical stress occurring deeper in gyrencephalic brain tissue\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Moreover, rodents have less white matter than marmosets, sheep, and pigs, a distinction that is particularly relevant in studies of diffuse axonal injury or edema\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The gray-to-white matter ratio in the marmoset brain closely resembles that of humans\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe marmoset (\u003cem\u003eCallithrix jacchus\u003c/em\u003e), a New World primate that diverged from humans approximately 45\u0026nbsp;million years ago, has a quasi-gyrencephalic brain with underdeveloped sulci\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. This brain architecture, combined with the marmoset's primate-specific neurobiology, higher cognitive complexity, and its closer translational relevance\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, positions it as a superior model for studying the mechanisms and consequences of TBI. Even though ferrets\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e and pigs\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e have also been investigated and both feature gyrencephalic brains, marmosets provide a better understanding of human neurobiology, offering hope for more effective treatments and interventions (e.g., potential therapeutic development, biomarkers) that may require primate-specific responses and offer increased regulatory and clinical relevance\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTBI profoundly disrupts cholinergic signaling\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, with hippocampal acetylcholine levels increasing by approximately 74% immediately post-injury, and similar alterations have been reported after fluid percussion injury (a widely used TBI model)\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Biperiden, a muscarinic cholinergic antagonist, has been proposed as a potential modulator of neural plasticity following TBI, where it delays seizure onset and reduces severity\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Studies deploying biperiden to alter disease progression (epileptogenesis) after TBI in humans have, so far, not clearly shown its effectiveness\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. There is a great debate as to whether models of status epilepticus (SE), the condition in which biperiden has mostly been tested, are the best strategy to study TBI \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the present study, our aim is to investigate the effects of biperiden during the acute phase (24 hours) of moderate TBI in a non-human primate model, to observe and analyze structural and cellular alterations within the brain. We hypothesize that biperiden treatment during the acute phase of moderate TBI may affect neuronal and glial injury. We hope to shed light on relevant mechanistic understanding in ongoing clinical trials with biperiden in TBI \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Animals:\u003c/h2\u003e \u003cp\u003eThirty-nine adult marmosets (\u003cem\u003eC. jacchus)\u003c/em\u003e (24 males, 15 females; age: 2\u0026ndash;6 years; weight: 180\u0026ndash;380 g) were obtained from the Centro de Manejo e Conserva\u0026ccedil;\u0026atilde;o de Animais (CeMaCAS) and transported to the Federal University of S\u0026atilde;o Paulo primate facility. They were housed individually in wire cages (50 cm \u0026times; 50 cm \u0026times; 50 cm) under controlled conditions, with stable room temperatures (25\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026ordm;C) and a 12-hour light-dark cycle starting at 7:00 AM. Animals received enrichment items (branches and wooden swings), free access to water, and fresh fruit twice daily. All procedures followed ARRIVE, NIH, and the Brazilian Institute of Environment and Renewable Natural Resources (IBAMA) guidelines, with approval of the Board for Ethics in the Use of Animals (CEUA, Comiss\u0026atilde;o de \u0026Eacute;tica no Uso de Animais), an institutional ethics committee of the UNIFESP, protocol n\u0026ordm; 5138271222, and were conducted following the guidelines for animal care and use of laboratory animals. All efforts were made to minimize the number of animals and their suffering.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Experimental Design and Groups:\u003c/h2\u003e \u003cp\u003eAnimals were randomly assigned to four groups. The investigators were blinded to group allocation throughout the experiments and during outcome assessments. The experimental design is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eNA\u0026Iuml;VE\u003c/b\u003e: Intact animals that underwent neither craniotomy nor LFPI (n\u0026thinsp;=\u0026thinsp;8; 5 females and 3 males).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSHAM-SAL\u003c/b\u003e: Animals underwent craniotomy but did not receive the LFPI impact. They were treated with a saline solution injection via intraperitoneal (i.p.) route (n\u0026thinsp;=\u0026thinsp;9; 4 females and 5 males).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eTBI-SAL\u003c/b\u003e: Animals underwent LFPI and were treated with saline solution injections (i.p.) (n\u0026thinsp;=\u0026thinsp;9; 3 females and 6 males).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eTBI-BIP\u003c/b\u003e: Animals underwent LFPI, were treated with biperiden injections (i.p) (n\u0026thinsp;=\u0026thinsp;8; 2 females and 6 males).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 LFPI model of brain trauma:\u003c/h2\u003e \u003cp\u003eAnimals were anesthetized with isoflurane (3% for inhalation and 2% for maintenance, at a flow rate of 1-1.5L/min in freely breathing oxygen), followed by an intradermal injection of lidocaine (10 mg/kg) for local anesthesia. A 15 mm midline incision was made to expose the skull, and a 5 mm burr hole was drilled using an electric drill (Stoelting, Wood Dale, IL), ensuring the integrity of the dura mater in all trauma regions. At the craniotomy site, a cannula (a female Luer lock) was fixed with dental cement. After the cannula was securely placed and filled with sterile 0.9% saline solution. The female Luer lock on the animal's skull was then connected to the male Luer lock of the fluid percussion device (Model FP301 Signal Conditioner, AmScien Instruments).\u003c/p\u003e \u003cp\u003eStereotaxic coordinates for trauma induction were: +1.78 mm anterior-posterior (AP) to bregma, +\u0026thinsp;10 mm medial-lateral (ML), +\u0026thinsp;13 mm dorso-ventral (DV). The LFPI model was applied at a 17\u0026deg; angle, with a brief (10\u0026ndash;15 ms) transient fluid-pressure pulse impacting the exposed dura. Pulse pressures were measured by an extracranial transducer and recorded on a storage oscilloscope (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). After the LFPI, the cannula was removed from the skull, and the animal was sutured with 2\u0026thinsp;\u0026minus;\u0026thinsp;0 non-absorbable nylon.\u003c/p\u003e \u003cp\u003eDuring stereotaxic surgery, animals were maintained normothermic (36\u0026ndash;38\u0026deg;C) using a thermostatically controlled heating blanket, with rectal temperature continuously monitored (RightTemp Jr., Kent Scientific, USA). Physiological parameters, including heart rate, respiratory rate, and oxygen saturation, were continuously monitored using a pulse oximeter with paw sensors (Kent Scientific). Mucous membrane color was also assessed to ensure stable physiological conditions. At the time of injury induction, animals were fully recovered from isoflurane anesthesia. Animals received post-surgical care, including pentabiotic (0.1 mL/kg, i.m.) and flunixin meglumine (1 mg/kg, i.p.). They were kept on a heated blanket and hydrated until they had fully recovered. At 24-hour post-trauma, animals were deeply anesthetized with pentobarbital (100 mg/kg, i.p.) and transcardially perfused with phosphate-buffered saline, followed by 4% paraformaldehyde.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Biperiden treatment\u003c/h2\u003e \u003cp\u003eAnimals were treated with biperiden hydrochloride dissolved in 0.9% saline at a concentration of 8 mg/Kg, i.p. (Crist\u0026aacute;lia, Brazil). Saline (0.9%) served as a vehicle. Treatment started six hours after the induction of TBI or six hours after the induction of anesthesia in the sham-operated marmosets. The second dose was administered 8 hours after the first, and the third dose was administered 8 hours after the second. The biperiden dose of 8 mg/Kg was selected based on prior rodent studies demonstrating its safety and efficacy in modulating excitotoxicity and epileptogenesis\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The dose-dependent effects of similar anticholinergic treatments was demonstrated by Benassi et al.\u003csup\u003e25\u003c/sup\u003e therefore it can be safely administered after TBI.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Brain tissue preparation\u003c/h2\u003e \u003cp\u003eTwenty-four hours after LFPI-TBI, the animals were deeply anesthetized with sodium pentobarbital (100mg/kg, i.p.). A sternotomy was made to access the heart. Then, the animals were perfused through the heart. Perfusion started with 100 mL of 0.1M PBS solution (phosphate buffer solution; 5.52 g of monobasic sodium phosphate plus 21.88 g of dibasic sodium phosphate), then 100 mL of 4% paraformaldehyde (diluted in PBS solution).\u003c/p\u003e \u003cp\u003eThe brains were removed and post-fixed in 4% formaldehyde, then cryoprotected in 30% sucrose (diluted in PBS). They remained in this solution until they showed signs of dehydration, a procedure that usually occurred within 24 hours. Immediately after this period, the brains were dried and then frozen at -80\u0026deg;C. Subsequently, the brains were sectioned in a cryostat (Leica CM1850) in coronal sections (40 \u0026micro;m thick). Then, the sections were stored in an antifreeze solution (300 g of sucrose, 500 mL of PBS, and 300 mL of ethylene glycol) at -20\u0026deg;C until processed for histological and immunohistochemical analysis. Brain sections were selected according to the stereotaxic atlas\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, ranging from +\u0026thinsp;3.64 to \u0026minus;\u0026thinsp;1.84 mm in the anterior\u0026ndash;posterior axis relative to bregma (dorsal hippocampus), ensuring consistent sampling of both neocortical and hippocampal ipsilateral regions for histological assessment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Histological Nissl staining\u003c/h2\u003e \u003cp\u003eBrain slices were mounted on gelatin-coated glass slides and stained for 8 min with 1% cresyl violet dissolved in distilled water and filtered. Stained slides were dehydrated for 1 minute using 100%, 96%, and 70% ethanol, cleared in xylene for 2 minutes, then covered with Entellan mounting medium, and coverslipped. Slides were imaged (6 brain sections for each animal), and the lesion area was assessed among the groups: NAIVE, SHAM-SAL, TBI-SAL, and TBI-BIP. Images were analyzed and imported into Fiji (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://fiji.sc\u003c/span\u003e\u003cspan address=\"http://fiji.sc\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, a version of ImageJ; National Institutes of Health, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://imagej.nih.gov/ij\u003c/span\u003e\u003cspan address=\"http://imagej.nih.gov/ij\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The percentage of lesion volume was calculated as per the following formula\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e:\u003c/p\u003e \u003cp\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:Lesion\\:volume=\\frac{volume\\:of\\:contralateral\\:hemisphere-volume\\:of\\:ipsilateral\\:hemisphere\\:}{volume\\:\\:contralateral\\:hemisphere}\\)\u003c/span\u003e \u003c/span\u003e* 100\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Fluoro-Jade\u0026reg; B\u003c/h2\u003e \u003cp\u003eFluoro-Jade\u0026reg; B (FJ-B, AG310 Merck-Millipore) was used to stain degenerating neurons. Fixed sections were mounted on glass slides, and FJ-B staining was performed as follows: The slides were mounted and let dry at room temperature for 3 to 5 days. Then, the slices were placed in an oven at 37\u0026deg;C for 20 minutes.\u003c/p\u003e \u003cp\u003eThe slices were then immersed in 100% ethanol for 3 minutes, followed by 1 minute each in 70% ethanol and distilled water. The slides were then incubated in 0.06% potassium permanganate (KMnO₄) in distilled water for 15 minutes. Next, the slides were rinsed in distilled water and transferred to a 0.0001% FJ-B staining solution in 0.1% acetic acid for 30 minutes. The FJ-B working solution was prepared from a stock FJ-B solution (0.01% in distilled water). After rinsing, the slides were coverslipped with DPX.\u003c/p\u003e \u003cp\u003eThe slides were analyzed using a 20X objective and a computer-based digitizing image system (Zeiss Axiovert; Carl Zeiss, Germany) connected to an Axiocam 208 color camera. Image analysis was conducted with ImageJ, the analyze particles plugin for cell counting in areas of interest. Because the lesion site was often absent or too damaged for reliable analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), we quantified only the adjacent intact tissue\u0026mdash;the neocortex (motor, parietal, and temporal cortices) and hippocampus (CA1, CA3, and dentate gyrus (DG))\u0026mdash;located within 2mm of the lesion border.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Immunofluorescence\u003c/h2\u003e \u003cp\u003eImmunofluorescence was performed to identify astrocytes, microglia, and vessels. Free-floating sections (six brain slices per animal) were washed five times with PBS solution to remove all anti-freezing solution and then incubated in a blocking solution (250 \u0026micro;L of Triton X-100, 90 mL of 0.1 M PBS, and 40 \u0026micro;L of goat serum) for 30 min at room temperature under constant stirring. After blocking, cells were incubated overnight with the following primary antibodies: polyclonal rabbit anti-Iba-1 (1:1000, Wako, 019-19741) for microglia/macrophages, and monoclonal mouse anti-glial fibrillary acidic protein (GFAP) (1:1000, Sigma, G3893) for astrocytes, diluted in blocking solution.\u003c/p\u003e \u003cp\u003eThe following day, after washing the sections in PBS, they were incubated for 2 hours with secondary antibodies (anti-mouse Alexa Fluor 488, anti-rabbit Alexa Fluor 568, 1:600, all from Invitrogen) in blocking solution. For vessel staining, after three PBS washes, the sections were incubated with Tomato lectin (TL; Lycopersicon esculentum; 1:200; Vector Laboratories; FL-1171-1) for 1 hour. Nuclei were stained with DAPI (4\u0026rsquo;,6-diamidino-2-phenylindole, 1:10,000; Thermo Fisher Scientific, Carlsbad, CA, USA). Finally, the sections were coverslipped with Fluoromount G\u0026trade; (Thermo Fisher Scientific).\u003c/p\u003e \u003cp\u003eFor the analysis of Iba-1, GFAP, and TL, the slides were examined using a computer-based digitizing image system, Zeiss Axiocam 506 color (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.zeiss.com/axiocam\u003c/span\u003e\u003cspan address=\"https://www.zeiss.com/axiocam\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), with a 20X objective. The laser and detector were maintained at constant settings for both cases during the acquisition of each staining set.\u003c/p\u003e \u003cp\u003eFor each slide, cells were qualitatively evaluated for their localization and morphology in the brain areas of interest only on the ipsilateral side of the trauma (the neocortex (motor, parietal, and temporal cortices) and hippocampus (CA1, CA3, and DG)). Slides and resultant images were coded, and fluorescence signals were quantified. Stained cells were quantified by branch count and average branch length using skeleton and vascular density analysis in Fiji (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://fiji.sc\u003c/span\u003e\u003cspan address=\"http://fiji.sc\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, a version of ImageJ software, National Institutes of Health, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://imagej.nih.gov/ij\u003c/span\u003e\u003cspan address=\"http://imagej.nih.gov/ij\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Additionally, the number of vessels was counted manually. Three were randomly chosen from the six brain slices. For each region (the neocortex (motor, parietal, and temporal cortices) and hippocampus (CA1, CA3, and DG), three photos were taken, yielding a total of nine pictures per animal per region and 54 images per experimental group.\u003c/p\u003e \u003cp\u003eFor Iba-1 and GFAP analyses, the skeleton-derived parameters\u0026mdash;number of branches and average branch length\u0026mdash;were subjected to agglomerative hierarchical clustering using the average linkage method. This approach groups data based on their similarity, producing a hierarchical dendrogram in which the branching levels represent the degree of dissimilarity between clusters. In the dendrogram, clusters are depicted as nodes, and the vertical axis represents the degree of similarity between them. Naive groups are represented by numbers from 1\u0026ndash;4, SHAM-SAL from 5\u0026ndash;8, TBI-SAL from 9\u0026ndash;12, and TBI-BIP from 13\u0026ndash;16.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Single Molecule Array (SIMOA)\u0026reg;\u003c/h2\u003e \u003cp\u003eDetection of blood-derived brain biomarkers associated with TBI was performed using the SIMOA platform (Quanterix Corporation, Lexington, MA). Total tau (T-tau; a marker of neuronal function), Neurofilament Light Chain (NfL, an indicator of neuronal damage), Glial Fibrillary Acidic Protein (GFAP; a marker of astrocytic damage), and Ubiquitin C-Terminal Hydrolase L1 (UCH-L1; an early marker of neuronal injury). These biomarkers were selected for their sensitivity to TBI-related damage. Serum biomarker levels were quantified using the Neurology 4-Plex B (N4PB) assay, a specific immunoassay kit that detects NFL, total tau, GFAP, and UCHL-1. The samples were thawed, vortexed, and centrifuged for the analysis. The analysis was performed at Richet/IDOR in Rio de Janeiro using the SIMOA HD-1 device.\u003c/p\u003e \u003cp\u003eSerum samples from animal models were thawed, and 60 \u0026micro;L of each sample was pipetted into each well of a 96-well plate, along with the assay-validated calibrators. The device was loaded with the necessary reagents and supplies, including pipettes, commercial kit beads, discs, and the sample plate. After adjusting the parameters, the assay was initiated and lasted approximately 4\u0026ndash;5 hours. The automated calibration cycles, pipetting, washing, incubation, matrix transfer, and signal reading recorded the intensity of the fluorescent signals emitted by the microparticles, expressed in picograms per milliliter (pg/mL). The calibration curve converted the signals obtained from the samples into quantifiable concentrations of the biomarkers, a conversion typically performed automatically by the SIMOA software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Statistical analysis\u003c/h2\u003e \u003cp\u003eSample size calculation was performed a priori using G*Power (v 3.1.9.7). The calculation is based on one-way ANOVA (fixed effects, considering four groups), a small effect size (f\u0026thinsp;=\u0026thinsp;0.19), a significance level of 5% (α\u0026thinsp;=\u0026thinsp;0.05), and a statistical power of 0.95. Effect size was calculated using Cohen\u0026acute;s d, and randomization and group allocation were performed by blind investigators.\u003c/p\u003e \u003cp\u003eNormality and homogeneity were assessed. To compare independent groups, the Kruskal-Wallis (KW) test was applied appropriately, followed by the Dunn post-hoc test. As an exploratory analysis, hierarchical clustering with the average linkage method and Euclidean distance was employed. Correlation matrix, though the Spearman r was employed to identify immunohistochemical variables. Principal component analysis (PCA) was performed to explain the greatest variation in the immunohistochemical variable and reduce data dimensionality. All variables were standardized (mean-centered and scaled to unit variance) prior to analysis.\u003c/p\u003e \u003cp\u003eData are presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD), and P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 are considered statistically significant. Data analyses were performed using GraphPad Prism version 11.0 (GraphPad Software Inc., San Diego, CA., \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.graphpad.com\u003c/span\u003e\u003cspan address=\"http://www.graphpad.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), R version 4.3.2, and RStudio.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Moderate LFP-induced TBI in marmosets resulted in variable hematoma formation\u003c/h2\u003e \u003cp\u003eFollowing parameter standardization for inducing moderate TBI in marmosets, the optimal pressure range was determined to be 1.38\u0026ndash;2.25 atm (mean 1.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26 atm; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb), with a 17\u0026deg; impact angle consistently producing moderate injury, as established in our previous study (Sanabria et al., 2025, unpublished data)\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOf the 39 animals, 2 died during anesthesia, and 3 died due to trauma. The acute mortality rate in the TBI group (within 24 h post-impact) was 15% (3/20), with all deaths occurring immediately after injury. Among the 17 animals that survived LFPI, 8 (47%) developed subdural hematomas and 2 (12%) developed epidural hematomas (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). Hematomas were identified at euthanasia by blind investigators after removal of the cranium and dura mater.\u003c/p\u003e \u003cp\u003eAmong animals with hematomas (n\u0026thinsp;=\u0026thinsp;8), 5 belonged to the TBI-SAL group (1.66\u0026ndash;2.25 atm) and 3 to the TBI-BIP group (1.50\u0026ndash;1.61 atm), with a mean pressure of 1.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07 atm. Animals without hematomas were exposed to pressures ranging from 1.38 to 2.02 atm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.2 TBI-SAL animals exhibited a significantly larger lesion volume\u003c/h2\u003e \u003cp\u003eThe percentage of lesion volume induced by TBI was quantified using Nissl staining. Lesion volume was calculated by subtracting the volume of the ipsilateral hemisphere from that of the contralateral hemisphere. Statistical analysis with the Kruskal\u0026ndash;Wallis test (KW (3)\u0026thinsp;=\u0026thinsp;10.13; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0051) revealed significant differences between the Na\u0026iuml;ve and TBI group. Specifically, TBI-SAL animals displayed a significantly greater lesion volume compared with Na\u0026iuml;ve animals (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ed).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Neuronal degeneration was significantly higher in the TBI-SAL group in CA1\u003c/h2\u003e \u003cp\u003eFJ-B staining was employed to evaluate neuronal degeneration in the neocortex (motor, parietal, and temporal cortices) and hippocampus (CA1, CA3, and DG). In the neocortex (across the three analyzed areas), a statistically significant group difference was revealed (KW(3)\u0026thinsp;=\u0026thinsp;10.42; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0038). Post-hoc analysis (Dunn\u0026rsquo;s test) indicated that both TBI-SAL (145\u0026thinsp;\u0026plusmn;\u0026thinsp;43.01; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.024) and TBI-BIP (132\u0026thinsp;\u0026plusmn;\u0026thinsp;39.37; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047) groups exhibited significantly greater neuronal degeneration compared with the Na\u0026iuml;ve group (20.75\u0026thinsp;\u0026plusmn;\u0026thinsp;16.30; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb I). When we analyzed the cortical regions independently, statistically significant differences were observed in the parietal (KW(3)\u0026thinsp;=\u0026thinsp;11.35; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0014) and temporal cortex (KW(3)\u0026thinsp;=\u0026thinsp;11.18; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0016). In both cortical regions, TBI groups (TBI-SAL and TBI-BIP) had more neuronal degeneration compared with Naive group (See Supplemental Materials and Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the hippocampus, the CA1 region showed statistically significant group differences (KW(3)\u0026thinsp;=\u0026thinsp;10.94; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0022). TBI-SAL group (126\u0026thinsp;\u0026plusmn;\u0026thinsp;37.73; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007) displayed significantly higher neuronal degeneration compared with the Na\u0026iuml;ve group (21.25\u0026thinsp;\u0026plusmn;\u0026thinsp;8.92; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb II). While, in the CA3 region, no statistically significant differences were detected among groups. In the DG, statistically significant differences (KW(3)\u0026thinsp;=\u0026thinsp;11.02; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0020) were observed. The SHAM-SAL group (84.60\u0026thinsp;\u0026plusmn;\u0026thinsp;22.66; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.043) exhibited significantly higher neuronal degeneration compared with the TBI-BIP group (30.25\u0026thinsp;\u0026plusmn;\u0026thinsp;7.84; Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb III-IV).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Biperiden increased vessel numbers across cortical and hippocampal regions, whereas vascular density remained unchanged.\u003c/h2\u003e \u003cp\u003eConcerning the number of vessels in the different areas analyzed. In the neocortex (across the three analyzed areas), we observed statistically significant differences among the groups (KW(3)\u0026thinsp;=\u0026thinsp;10.38; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0040\u003c/em\u003e). The TBI-SAL group had an increase in the number of vessels (62.08\u0026thinsp;\u0026plusmn;\u0026thinsp;19.28) compared to the Na\u0026iuml;ve group (30.21\u0026thinsp;\u0026plusmn;\u0026thinsp;8.22; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0250;\u003c/em\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb I). However, when we analyzed different parts of the neocortex independently, we observed statistically significant differences in the parietal cortex (KW(3)\u0026thinsp;=\u0026thinsp;9.50; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0093\u003c/em\u003e) and in the temporal cortex (KW(3)\u0026thinsp;=\u0026thinsp;11.47; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0012\u003c/em\u003e). In the parietal cortex, the SHAM-SAL (59.46\u0026thinsp;\u0026plusmn;\u0026thinsp;20.81; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.009\u003c/em\u003e) group and the TBI-BIP (54.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.65; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.017\u003c/em\u003e) group had more vessels than Naive (31.13\u0026thinsp;\u0026plusmn;\u0026thinsp;8.04; see Supplemental Material and Figure S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the hippocampus, in the CA1 region, we observed statistically significant differences among the groups (KW(3)\u0026thinsp;=\u0026thinsp;12.51; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003e0.0002).\u003c/em\u003e The SHAM-SAL had more vessels (57.71\u0026thinsp;\u0026plusmn;\u0026thinsp;12.59) compared to the Na\u0026iuml;ve (22.56\u0026thinsp;\u0026plusmn;\u0026thinsp;2.78; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.011\u003c/em\u003e) and the TBI-SAL (30.71\u0026thinsp;\u0026plusmn;\u0026thinsp;8.00; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.04\u003c/em\u003e). Moreover, the TBI-BIP (57.29\u0026thinsp;\u0026plusmn;\u0026thinsp;5.99 vessels) group also had more vessels than the Na\u0026iuml;ve (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.012\u003c/em\u003e) and more than TBI-SAL (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.039;\u003c/em\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb II).\u003c/p\u003e \u003cp\u003eSimilarly to the cortex, in CA3 (KW(3)\u0026thinsp;=\u0026thinsp;11.15; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0017\u003c/em\u003e) and DG (KW(3)\u0026thinsp;=\u0026thinsp;9.42; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0087\u003c/em\u003e) we observed statistically significant differences among the groups, in both cases the SHAM-SAL [in CA3:59.29\u0026thinsp;\u0026plusmn;\u0026thinsp;18.17, in DG:67.39\u0026thinsp;\u0026plusmn;\u0026thinsp;24.75] group had more vessels than the Na\u0026iuml;ve group [in CA3:24.90\u0026thinsp;\u0026plusmn;\u0026thinsp;3.76, in DG:24.67\u0026thinsp;\u0026plusmn;\u0026thinsp;6.68; Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb III-IV].\u003c/p\u003e \u003cp\u003eNo significant differences in vascular density were observed among the groups across the analyzed regions (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec I-VIII).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Astrocytes in the TBI-SAL group exhibited reduced astrocytic branching, while TBI-BIP had longer processes\u003c/h2\u003e \u003cp\u003eA skeleton analysis was performed to assess astrocyte morphology by measuring branch number and length in the neocortex and hippocampus.\u003c/p\u003e \u003cp\u003eSignificant differences in astrocyte branch number were observed only in the cortex (KW(3)\u0026thinsp;=\u0026thinsp;14.49; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Post hoc analysis showed that both TBI-SAL (61.25\u0026thinsp;\u0026plusmn;\u0026thinsp;11.00 branches; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047) and TBI-BIP (47.50\u0026thinsp;\u0026plusmn;\u0026thinsp;10.41 branches; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0024) had significantly fewer branches compared to the SHAM-SAL group (326.2\u0026thinsp;\u0026plusmn;\u0026thinsp;97.61 branches; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb I-IV). When cortical regions were analyzed separately, branch numbers also differed significantly across groups. In the motor cortex (KW(3)\u0026thinsp;=\u0026thinsp;10.94; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), SHAM-SAL showed more branches than TBI-BIP. In the parietal and temporal cortex (both KW(3)\u0026thinsp;=\u0026thinsp;13.06; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), both TBI groups exhibited reduced branching compared to SHAM-SAL.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAstrocyte branch length differed significantly between groups in the cortex (KW(3)\u0026thinsp;=\u0026thinsp;14.11; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with the TBI-BIP group (29.82\u0026thinsp;\u0026plusmn;\u0026thinsp;9.25 \u0026micro;m) showing longer branches than the TBI-SAL group (3.53\u0026thinsp;\u0026plusmn;\u0026thinsp;2.27 \u0026micro;m; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0097). Similar differences were observed across all cortical regions\u0026mdash;motor (KW(3)\u0026thinsp;=\u0026thinsp;8.82; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01), parietal (KW(3)\u0026thinsp;=\u0026thinsp;12.95; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and temporal cortex (KW(3)\u0026thinsp;=\u0026thinsp;11.76; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001)\u0026mdash;with TBI-BIP consistently showing greater branch length than TBI-SAL (see Supplemental Material and Figure S3).\u003c/p\u003e \u003cp\u003eIn the hippocampus, branch length also differed significantly among groups. In CA1 (KW(3)\u0026thinsp;=\u0026thinsp;10.47; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0036), CA3 (KW(3)\u0026thinsp;=\u0026thinsp;12.31; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0004), and DG (KW(3)\u0026thinsp;=\u0026thinsp;10.94; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0022), the TBI-BIP group showed significantly longer astrocyte branches than the TBI-SAL group. In the DG, the Naive group also exhibited longer branches than TBI-SAL (Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ec III-IV).\u003c/p\u003e \u003cp\u003eHierarchical cluster analysis based on branch number and average branch length revealed two main clusters for branch number across the cortex and hippocampus, separating SHAM-SAL from the other experimental groups. For branch length, clustering separated TBI-BIP from the other groups in the cortex and CA3, while in the DG, Naive clustered with TBI-BIP, and in CA1, these groups formed separate clusters.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.6 Microglia in the TBI-SAL group exhibited a reduced number of microglia branching, accompanied by longer process length\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSkeleton analysis was also performed to evaluate microglia morphology by measuring branch number and branch length in the neocortex and hippocampus (CA1, CA3, DG) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea-b). Regarding the number of microglial branches in the cortex, statistically significant differences were observed among groups (KW (3)\u0026thinsp;=\u0026thinsp;10.16; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0048\u003c/em\u003e). Dunn's post-hoc analysis indicated that the NAIVE (51.75\u0026thinsp;\u0026plusmn;\u0026thinsp;22.75 branches; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.044)\u003c/em\u003e group had a higher number of microglia branches than TBI-SAL (12.25\u0026thinsp;\u0026plusmn;\u0026thinsp;5.18 branches). Moreover, when we analyzed different parts of the neocortex independently, we observed statistically significant differences in the NA\u0026Iuml;VE and SHAM-SAL groups, which had more branches than TBI-SAL [in motor (KW(3) 6.81; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0062)\u003c/em\u003e, parietal (KW(3)\u0026thinsp;=\u0026thinsp;7.42; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0045\u003c/em\u003e), and temporal (KW(3)\u0026thinsp;=\u0026thinsp;8.25; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0030\u003c/em\u003e) cortices ] (See Supplemental Material, S4).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the hippocampus, CA1 and CA3 had statistically significant differences in branch number, which were observed among groups (CA1: KW (3)\u0026thinsp;=\u0026thinsp;10.92; p\u0026thinsp;=\u0026thinsp;0.0022; CA3: KW(3)\u0026thinsp;=\u0026thinsp;11.83; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0008).\u003c/em\u003e Dunn's post-hoc analysis indicated that the SHAM-SAL (CA1 60.60\u0026thinsp;\u0026plusmn;\u0026thinsp;26.43 branches; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.014;\u003c/em\u003e CA3: 61.60\u0026thinsp;\u0026plusmn;\u0026thinsp;20.38 branches; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.042\u003c/em\u003e ) group had a higher number of microglia branches than TBI-SAL (CA1 13.50\u0026thinsp;\u0026plusmn;\u0026thinsp;10.88 branches; CA3 19.00\u0026thinsp;\u0026plusmn;\u0026thinsp;12.19 branches ). In DG, statistically significant differences in the number of branches were observed among the groups KW(3)\u0026thinsp;=\u0026thinsp;13.48; \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/em\u003e).Dunn's post-hoc analysis indicated that the SHAM-SAL (65.60\u0026thinsp;\u0026plusmn;\u0026thinsp;20.18 branches) group had a higher number of microglia branches than TBI-SAL(8.00\u0026thinsp;\u0026plusmn;\u0026thinsp;5.35 branches; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0062\u003c/em\u003e) and TBI-BIP (12.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.50 branches ;\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.042\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eRegarding the microglial average branch length, no statistically significant differences were observed among groups in the cortex, CA1, or DG. However, when we analyze the different parts of the neocortex, only the temporal cortex (KW(3) 3.87; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.038)\u003c/em\u003e showed significant differences in the microglial branches between the TBI-BIP group (47.32\u0026thinsp;\u0026plusmn;\u0026thinsp;10.12 \u0026micro;m) and the SHAM-SAL (18.17\u0026thinsp;\u0026plusmn;\u0026thinsp;4.45 \u0026micro;m). In the hippocampus, \u003cem\u003ein\u003c/em\u003e CA3, significant differences were detected (KW(3)\u0026thinsp;=\u0026thinsp;8.07; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.029\u003c/em\u003e). The TBI-BIP group displayed longer microglial branches (31.45\u0026thinsp;\u0026plusmn;\u0026thinsp;7.00 \u0026micro;m) compared to the SHAM-SAL group (15.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71 \u0026micro;m; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.038\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eHierarchical clustering of microglial morphology, based on branch number and average branch length, revealed distinct grouping patterns. For the number of branches, two main clusters were identified in the cortex and CA1: one comprising the Na\u0026iuml;ve and SHAM-SAL groups, and another including the remaining experimental groups. In CA3 and DG, the SHAM-SAL group clustered separately from the others. Regarding average branch length, two clusters were observed in the cortex and CA1 (TBI-SAL and TBI-BIP versus the remaining groups), while in CA3, TBI-SAL separated from the others. In the DG, SHAM-SAL and TBI-SAL formed a distinct cluster from the remaining groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.7 Correlation matrix and Principal component analysis (PCA) among the immunohistochemical variables\u003c/h2\u003e \u003cp\u003eIn the correlation matrix, we observed a significantly strong positive correlation between the number of GFAP (astrocytes) and Iba-1 (microglia) branches (r\u0026thinsp;=\u0026thinsp;0.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and a moderate positive correlation between GFAP and Iba-1 average branch length (r\u0026thinsp;=\u0026thinsp;0.40,p\u0026thinsp;=\u0026thinsp;0.001), FJ-B (degenerative neurons) and the number of vessels(r\u0026thinsp;=\u0026thinsp;0.29, p\u0026thinsp;=\u0026thinsp;0.017) and the number of vessels and GFAP branch count (r\u0026thinsp;=\u0026thinsp;0.26, p\u0026thinsp;=\u0026thinsp;0.029). In contrast, there was a significant negative correlation between Iba-1 branch count and average branch length (r= -0.36, p\u0026thinsp;=\u0026thinsp;0.002), FJ-B and GFAP branch length (r=-0.41, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as well as between GFAP branch count and Iba-1 branch length (r=-0.32, p\u0026thinsp;=\u0026thinsp;0.008; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ea).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eRegarding PCA analysis, we observe that the first two principal components explain 49.02% of the total variance: 30.63% by the first component and 18.39% by the second (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eb). Therefore, we can say that principal component 1 (PC1) is mainly driven by GFAP and Iba-1 average branch length and FJ-B (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ec), while PC2 is mainly driven by the number of GFAP and Iba-1 branches, and the number of vessels (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003ed),. Two dimensions were selected as plot shown in Supplemental Material S5.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.8 Early neuronal injury marker was more expressed in the TBI-SAL group than in the TBI-BIP group\u003c/b\u003e \u003c/p\u003e \u003cp\u003eRegarding the biomarkers of our interest (t-Tau, NfL, GFAP, and UCH-L1). Significant statistical differences were observed only in the UCH-L1 among the groups (KW (2)\u0026thinsp;=\u0026thinsp;5.79; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0457\u003c/em\u003e). Post-hoc test revealed that the TBI-SAL group has higher levels of UCH-L1 (1380\u0026thinsp;\u0026plusmn;\u0026thinsp;588 pg/mL) compared to SHAM-SAL (211\u0026thinsp;\u0026plusmn;\u0026thinsp;145 pg/mL; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.03\u003c/em\u003e) and TBI-BIP (234\u0026thinsp;\u0026plusmn;\u0026thinsp;77.27pg/mL; \u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.04\u003c/em\u003e). No statistically significant difference was observed in the other biomarkers (Figs.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eI-IV).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eThis study investigated the acute (24 hours) effects of biperiden on structural and cellular alterations following moderate TBI, as assessed by LFPI, in a non-human primate model (\u003cem\u003eC. jacchus\u003c/em\u003e). While previous studies have examined the impact of biperiden in SE models \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e and LFPI in rodents \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, this is the first study to assess its impact in a quasi-gyrencephalic species (marmoset), whose neuroanatomical and immunological features offer greater translational relevance to human TBI.\u003c/p\u003e \u003cp\u003eSerum analysis revealed elevated levels of the early neuronal injury marker UCH-L1 in TBI-SAL animals compared with SHAM-SAL and TBI-BIP groups within 24 hours after TBI, indicating greater acute neuronal injury in the absence of biperiden. UCH-L1 is a small neuronal protein that regulates the addition and removal of ubiquitin from proteins targeted for degradation\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. The elevated serum UCH-L1 levels observed in the TBI-SAL group may be attributed to neuronal injury and blood\u0026ndash;brain barrier (BBB) disruption\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, as we maintained the integrity of the dura mater in all regions during stereotaxic surgery. Thus, under both physiological and pathological conditions, UCH-L1 plays a critical role in maintaining axonal integrity and neuronal homeostasis\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Previous studies have reported significantly elevated UCH-L1 levels in cerebrospinal fluid (CSF) and serum of severe TBI patients compared to controls, with strong correlations to injury severity, particularly during the acute phase\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Conversely, UCH-L1 levels from the TBI-BIP group suggest unreported protection conferred by biperiden after traumatic brain injury.\u003c/p\u003e \u003cp\u003eBrophy and colleagues also demonstrated that serum UCH-L1 was a better predictor of survival at three months post-injury than CSF levels\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Interestingly, while previous work from our laboratory showed no differences in plasma UCH-L1 levels among groups 24 h after TBI in male rats\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, the present study in marmosets revealed significant increases in serum UCH-L1 levels, consistent with findings from Saletti and collaborators (2023)\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. In contrast, Morris and colleagues suggested that UCH-L1 may not be a TBI-specific biomarker but rather reflect broader ischemic or neurovascular injury, which aligns with the possibility that its elevation indicates general neuronal stress rather than trauma specificity\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e; however, our data did not show an increase in the TBI-BIP and SHAM-SAL as both passed for the stereotaxic surgery that may generate at some degree a neurovascular injury.\u003c/p\u003e \u003cp\u003eAlthough changes in GFAP and T-tau were not statistically significant. It was curious to observe an increase in both biomarkers in the TBI-SAL group. Elevated serum GFAP levels are commonly found in patients following an acute stroke or TBI, reflecting the extent of astroglial injury\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. While T-tau is correlated more with acute injury and/or rate of ongoing neurodegeneration rather than damage to neuronal axons from trauma \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHistological analysis further demonstrated that TBI-SAL animals had larger lesion volumes than the Naive group, with subdural and epidural hematomas present in both TBI conditions. Interestingly, the incidence of hematomas was approximately 25% higher in the TBI-SAL group than in the TBI-BIP animals. Regarding lesion volume, Villapol and colleagues\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e reported that cortical lesions following controlled cortical impact in male mice expand within the first 24 hours, peak at 3 days, and gradually decrease thereafter (7\u0026ndash;60 days). In our study, no prominent lesion cavity was observed, likely because the analysis was performed 24 hours post-injury. Interestingly, with biperiden, we did not observe this statistical difference compared to the Naive group. This may be because, in untreated TBI animals, elevated acetylcholinesterase activity in the brain or microvessels may promote opening of the BBB and exacerbate brain injury\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Therefore, biperiden's inhibitory activity might have reduced brain injury.\u003c/p\u003e \u003cp\u003eAfter traumatic brain injury, excessive acetylcholine release contributes to neuronal hyperexcitability and glutamate-mediated \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e Biperiden, a competitive antagonist at M1 muscarinic receptors, competes with acetylcholine in a 1:1 manner and modulates receptor activity. Reducing postsynaptic excitability may help attenuate early neuronal stress and excitotoxic processes. \u003csup\u003e41,42\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAt the cellular level, TBI-SAL animals exhibited increased neuronal degeneration in the cortex and CA1 regions compared to Naive controls. Moreover, in the CA1, a larger number of blood vessels were observed in the TBI-BIP and SHAM-SAL groups than in the TBI-SAL group, suggesting that untreated TBI animals exhibited reduced vascularization. After TBI, the neurovascular unit is disrupted. Continuous blood flow supplying oxygen and glucose is vital for brain integrity; when flow is reduced or fails to meet metabolic demands, neuronal function declines, and delayed cell death pathways are activated \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e,\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Early alterations in cerebral vasculature are evident after TBI, and these vascular deficits do not appear to fully recover, persisting for weeks to months after the initial injury.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn contrast, the TBI-BIP group showed higher TL-positive cell counts in CA1 than the TBI-SAL group, indicating enhanced functional recovery and potentially improved cerebral blood flow. Although the difference between TBI-BIP and TBI-SAL was statistically significant only in the CA1 region, TL-positive vessel counts were consistently higher in TBI-BIP across regions. A similar increase was observed in the TBI-BIP group compared to the NAIVE group in the parietal cortex and CA3 region. Furthermore, the TBI-BIP group displayed a broader distribution of cell density, despite the absence of other significant differences.\u003c/p\u003e \u003cp\u003eReduced cerebral blood flow contributes to an excitotoxic cascade characterized by excessive glutamate release and accumulation of toxic metabolites in the extracellular space. This process leads to rapid neuronal death accompanied by intense astrocytic activation\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Therefore, the lower TL-positive vessel counts observed in our TBI-SAL group may be related to a reduction in GFAP and Iba-1 branch number and average branch length in this group. As well as the increased number of FJ-B positive cell count on the cortex and CA1 of the TBI-SAL group.\u003c/p\u003e \u003cp\u003eMoreover, a study comparing changes in BBB permeability in gyrencephalic and lissencephalic models following TBI suggests that gyrencephalic brain structures may be more vulnerable to vascular disruption than lissencephalic models. Cerebrovascular alterations were observed in ferret brains after blast TBI, including microvascular bleeds followed by significant astrocytosis and microglial activation, consistent with neuroinflammation compared to rodents \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGFAP-positive astrocytes in the TBI-BIP group displayed longer branches in the motor cortex, parietal cortex, temporal cortex, CA1, CA3, and DG regions than in the TBI-SAL group, indicating a potentially enhanced capacity for synaptic support and tissue repair. Regarding astrocytes and microglia, our data showed a reduced number of branches in the TBI-SAL and TBI-BIP groups compared to Naive and SHAM-SAL animals 24 hours after injury. This reduction may reflect the early activation of resident glial cells, as astrocytes and microglia are among the first to initiate the post-traumatic inflammatory cascade\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. A similar decrease in glial complexity within the ipsilateral cortex has been reported by Villapol and colleagues, who showed hypertrophic astrocytes in the lesion and peri-lesional areas three days post-TBI\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Dihn\u0026eacute; and colleagues (2001) described an acute decrease in astrocyte number and immunoreactivity within 24 hours after TBI, followed by a reactive increase through proliferation and hypertrophy, leading to astrogliosis at later stages\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Furthermore, astrocytic apoptosis can occur as early as 6 hours after trauma, and has been proposed to precede neuronal degeneration by several hours \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFollowing CNS injury, microglia undergo substantial morphological remodeling, characterized by retraction of their processes and adoption of an amoeboid phenotype\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Studies have also demonstrated that Iba-1 expression is upregulated in activated microglia compared with their non-reactive, surveillant counterparts\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCuriously, the hierarchical analysis revealed that, with respect to the number of microglia branches that the SHAM-SAL and Na\u0026iuml;ve separate apart from the TBI groups except in CA3 and DG, where the SHAM-SAL separate from the others. Regarding the number of astrocytic branches, the SHAM-SAL group clustered separately from all other groups, with the greatest number of GFAP+ branches. This is particularly concerning, as Sham animals demonstrate significant neuronal degeneration in certain regions, increased vessel counts, and distinct astrocytic and microglial clustering patterns. This raises important questions about the biological impact of the craniotomy procedure itself, even though we maintained dura mater integrity during the experiments. One plausible explanation for this distinction is the craniotomy procedure itself, which has been shown in previous studies to cause measurable structural and functional alterations in the underlying brain tissue. This is likely due to the disruption of the intricate network of nerve fibers and blood vessels connecting the brain to the skull during bone flap removal\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Moreover, as was mentioned before gyrencephalic brain structures may be more vulnerable to vascular disruption than lissencephalic models\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn contrast, when examining the average branch length of astrocytes, two main clusters emerged: one composed of the Na\u0026iuml;ve and TBI-BIP groups, and another comprising the remaining groups. This pattern suggests that biperiden may help preserve glial homeostasis following injury. The pronounced astrocytic hypertrophy observed in the TBI-SAL group may reflect a maladaptive glial response, potentially impairing neuronal plasticity, as described by Burda and colleagues\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Moreover, our correlation matrix shows a strong correlation between GFAP and Iba-1 branch count, which is also evident in the PCA analysis. The PCA analysis indicated that astrocytic and microglial morphological complexity, GFAP, and Iba-1 average branch length vary independently. Suggesting that branching features are the dominant source of variation across samples, as well as number of vessels potentially reflecting structural remodeling in response to TBI and to biperiden.\u003c/p\u003e \u003cp\u003eTaking together, these findings underscore the central role of the cholinergic system, not only in PTE but also in epileptogenesis. Recent studies have demonstrated that anticholinergic interventions can modulate this process; for example, prolonged scopolamine treatment after lithium\u0026ndash;pilocarpine\u0026ndash;induced SE markedly reduced spontaneous recurrent seizures (SRS) at six months, even though its early effects were minimal \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Consistent with this, work from our group has shown that biperiden administration following pilocarpine-induced SE reduces both the number and intensity of seizures\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study possesses several limitations, including the absence of subacute and chronic assessments, which would clarify whether functional improvements develop over time. The short observational window precluded evaluation of cognitive function. This parameter was intentionally excluded to avoid confounding potential memory deficits with early inflammatory responses. The study focused on a single time point (24 h) to specifically investigate the acute phase of injury, when excitotoxicity, neuronal damage, and glial activation are at their peak, allowing the early effects of biperiden in non-human primates to be evaluated before later-stage changes occur.\u003c/p\u003e \u003cp\u003eAdditionally, the use of animals from a conservation facility rather than captive-bred individuals introduces uncertainty regarding possible prior trauma that may have influenced the outcomes. The heterogeneity of the sample with respect to age and weight also limits data interpretation. Furthermore, the absence of a SHAM-biperiden group complicates interpretation, as it prevents determining whether biperiden's effects are specific to TBI or reflect a more general modulation of surgical injury responses. Nevertheless, this work represents an important first step toward understanding the effects of biperiden on marmosets.\u003c/p\u003e \u003cp\u003eIn summary, our study was the first to demonstrate the acute effects of biperiden in non-human primates following a moderate TBI induced by LFPI. Untreated TBI animals exhibited significantly elevated UCH-L1 levels, indicating greater neuronal injury and BBB disruption, whereas animals treated with biperiden (TBI-BIP) showed a mitigated effect. Histologically, biperiden appeared to preserve vascular integrity and neuronal viability, particularly in the hippocampal CA1 and CA3 regions. However, in glia analyses, the biperiden effect was less pronounced, with reduced glial branching observed in both TBI groups; biperiden-treated animals exhibited longer astrocytic and microglia processes, suggesting improved glial homeostasis and repair potential. Overall, these findings indicate that biperiden confers an early neurovascular and glial protection during the acute phase of TBI in a non-human primate model.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn memory of our dear veterinarian, Paulo Varoni Cavalcanti. We also extend our sincere thanks to Professor F\u0026aacute;bio Cruz for kindly allowing us to use his microscope, to Master Simone Cinini for her help with the marmoset\u0026rsquo;s transportation, and to Mery Liz Alfaro for her help.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunda\u0026ccedil;\u0026atilde;o de Amparo \u0026agrave; Pesquisa supported this work do Estado de S\u0026atilde;o Paulo (FAPESP grants 2018/24561-5 and 2022/00249-8), Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior, Brazil (CAPES; Finance Code 001), and Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq; grants 311619/2019-3, and 312904/2021-5). VS and SR (2017/05242-3) received post-doctoral fellowships from the S\u0026atilde;o Paulo Research Foundation (FAPESP).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eV. S.:\u0026nbsp;\u003c/strong\u003eConceptualization, Methodology, Formal Analysis, Validation, and Data Curation, Writing- Original Draft\u003cstrong\u003e. C. G.\u003c/strong\u003e: Conceptualization, Methodology, Formal Analysis, Review. \u003cstrong\u003eS. R.:\u0026nbsp;\u003c/strong\u003eMethodology and Review\u003cstrong\u003e. A. S. G.:\u0026nbsp;\u003c/strong\u003eMethodology and Review.\u003cstrong\u003e\u0026nbsp;M. B. B.:\u0026nbsp;\u003c/strong\u003eMethodology and Review. \u003cstrong\u003eM. L. C.:\u0026nbsp;\u003c/strong\u003eMethodology, Formal Analysis, Validation, and Data Curation, Review. \u003cstrong\u003eJ. L. W.:\u0026nbsp;\u003c/strong\u003eMethodology and Review.\u003cstrong\u003e\u0026nbsp;M. L. F.\u003c/strong\u003e: Conceptualization, Validation, Review, and Editing. \u003cstrong\u003eL. E. M.:\u003c/strong\u003e Conceptualization, Review, and Editing\u003cstrong\u003e. B. M. L.\u003c/strong\u003e: Conceptualization, Methodology, Review, Editing, and Supervision\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement:\u0026nbsp;\u003c/strong\u003eAll procedures were conducted in compliance with ARRIVE, NIH, and IBAMA (Brazilian Institute of Environment and Renewable Natural Resources) guidelines, and were approved by the institutional Animal Care and Use Committee (protocol #5138271222).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have agreed to the published version of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available at the following link https://osf.io/zq5am/overview upon reasonable request\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMenon, D. K., Schwab, K., Wright, D. W. \u0026amp; Maas, A. I. Position statement: Definition of traumatic brain injury. \u003cem\u003eArch. Phys. Med. Rehabil.\u003c/em\u003e \u003cstrong\u003e91\u003c/strong\u003e, 1637\u0026ndash;1640 (2010).\u003c/li\u003e\n\u003cli\u003eBrett, B. L., Gardner, R. C., Godbout, J., Dams-O\u0026rsquo;Connor, K. \u0026amp; Keene, C. D. Traumatic Brain Injury and Risk of Neurodegenerative Disorder. \u003cem\u003eBiol. Psychiatry\u003c/em\u003e \u003cstrong\u003e91\u003c/strong\u003e, 498\u0026ndash;507 (2022).\u003c/li\u003e\n\u003cli\u003eSivanandam, T. M. \u0026amp; Thakur, M. K. Traumatic brain injury: A risk factor for Alzheimer\u0026rsquo;s disease. \u003cem\u003eNeurosci. Biobehav. Rev.\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 1376\u0026ndash;1381 (2012).\u003c/li\u003e\n\u003cli\u003ePitk\u0026auml;nen, A. \u003cem\u003eet al.\u003c/em\u003e Epileptogenesis in experimental models. \u003cem\u003eEpilepsia\u003c/em\u003e \u003cstrong\u003e48\u003c/strong\u003e, 13\u0026ndash;20 (2007).\u003c/li\u003e\n\u003cli\u003eTeasdale, G. \u0026amp; Jennett, B. Assessment of coma and impaired consciousness. A practical scale. \u003cem\u003eLancet\u003c/em\u003e \u003cstrong\u003e37\u003c/strong\u003e, 52\u0026ndash;56 (1974).\u003c/li\u003e\n\u003cli\u003eMaas, A. I. R. \u003cem\u003eet al.\u003c/em\u003e Traumatic brain injury: progress and challenges in prevention, clinical care, and research. \u003cem\u003eLancet Neurol.\u003c/em\u003e \u003cstrong\u003e21\u003c/strong\u003e, 1004\u0026ndash;1060 (2022).\u003c/li\u003e\n\u003cli\u003eXiong, Y., Mahmood, A. \u0026amp; Chopp, M. Animal models of traumatic brain injury. \u003cem\u003eNat. Rev. Neurosci.\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 128\u0026ndash;142 (2013).\u003c/li\u003e\n\u003cli\u003eMcIntosh, T. K. \u003cem\u003eet al.\u003c/em\u003e Traumatic brain injury in the rat: characterization of lateral fluid-percussion model. \u003cem\u003eNeuroscience\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 233\u0026ndash;244 (1989).\u003c/li\u003e\n\u003cli\u003eDixon, C. E. \u003cem\u003eet al.\u003c/em\u003e A fluid percussion model of experimental brain injury in the rat. \u003cem\u003eJ. Neurosurg.\u003c/em\u003e \u003cstrong\u003e67\u003c/strong\u003e, 110\u0026ndash;119 (1987).\u003c/li\u003e\n\u003cli\u003eCenci, M. A., Whishaw, I. Q. \u0026amp; Schallert, T. Animal models of neurological deficits: How relevant is the rat? \u003cem\u003eNat. Rev. Neurosci.\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 574\u0026ndash;579 (2002).\u003c/li\u003e\n\u003cli\u003eVink, R. Large animal models of traumatic brain injury. \u003cem\u003eJ Neuro Res\u003c/em\u003e 1\u0026ndash;9 (2017) doi:10.1002/jnr.24079.\u003c/li\u003e\n\u003cli\u003eFinnie, J. W. Animal models of traumatic brain injury: a review. \u003cem\u003eAust Vet J.\u003c/em\u003e \u003cstrong\u003e79\u003c/strong\u003e, (2001).\u003c/li\u003e\n\u003cli\u003eZhang, N. \u0026amp; Zhang, Y. Correlation between gyral size, brain size, and head impact risk across mammalian species. \u003cem\u003eBrain Res.\u003c/em\u003e \u003cstrong\u003e1828\u003c/strong\u003e, 148768 (2024).\u003c/li\u003e\n\u003cli\u003ePrins, N. W. \u003cem\u003eet al.\u003c/em\u003e Common Marmoset (Callithrix jacchus) as a Primate Model for Behavioral Neuroscience Studies. \u003cem\u003eJ Neurosci Methods.\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, 35\u0026ndash;46 (2017).\u003c/li\u003e\n\u003cli\u003eShinmyo, Y., Hamabe-Horiike, T., Saito, K. \u0026amp; Kawasaki, H. Investigation of the Mechanisms Underlying the Development and Evolution of the Cerebral Cortex Using Gyrencephalic Ferrets. \u003cem\u003eFront. Cell Dev. Biol.\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 1\u0026ndash;12 (2022).\u003c/li\u003e\n\u003cli\u003eDonat, C. K. \u003cem\u003eet al.\u003c/em\u003e Effects of lateral fluid percussion injury on cholinergic markers in the newborn piglet brain. \u003cem\u003eInt. J. Dev. Neurosci.\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 31\u0026ndash;38 (2010).\u003c/li\u003e\n\u003cli\u003eHomman-Ludiye, J. \u0026amp; Bourne, J. A. The Marmoset: The Next Frontier in Understanding the Development of the Human Brain. \u003cem\u003eILAR J.\u003c/em\u003e \u003cstrong\u003e61\u003c/strong\u003e, 248\u0026ndash;259 (2020).\u003c/li\u003e\n\u003cli\u003eMcIntosh, T. K. Neurochemical sequelae of traumatic brain injury: therapeutic implications. \u003cem\u003eCerebrovasc. Brain Metab. Rev.\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 109\u0026ndash;162 (1994).\u003c/li\u003e\n\u003cli\u003eGorman, L. K., Fu, K., Hovda, D. A., Becker, D. P. \u0026amp; Katayama, Y. Analysis of acetylcholine release following concussive brain injury in the rat. \u003cem\u003eJ Neurotrauma\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 203 (1989).\u003c/li\u003e\n\u003cli\u003eGorman, L., Fu, K., Hovda, D. A., Murray, M. \u0026amp; Traystman, R. J. Effects of Traumatic Brain Injury on the in the Rat. \u003cem\u003eJ Neurotrauma\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 457\u0026ndash;463 (1996).\u003c/li\u003e\n\u003cli\u003eAndrade, P. \u003cem\u003eet al.\u003c/em\u003e Seizure Susceptibility and Sleep Disturbance as Biomarkers of Epileptogenesis after Experimental TBI. \u003cem\u003eBiomedicines\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, (2022).\u003c/li\u003e\n\u003cli\u003eBittencourt, A. S. \u003cem\u003eet al.\u003c/em\u003e Modification of the natural progression of epileptogenesis by means of biperiden in the pilocarpine model of epilepsy. \u003cem\u003eEpilepsy Res.\u003c/em\u003e (2017).\u003c/li\u003e\n\u003cli\u003eForesti, M. L. \u003cem\u003eet al.\u003c/em\u003e Initial clinical evidence on biperiden as antiepileptogenic after traumatic brain injury \u0026mdash; a randomized clinical trial. \u003cem\u003eFront. Neurol.\u003c/em\u003e 1\u0026ndash;10 (2024) doi:10.3389/fneur.2024.1443982.\u003c/li\u003e\n\u003cli\u003eForesti, M. L. \u003cem\u003eet al.\u003c/em\u003e Biperiden for prevention of post-traumatic epilepsy: A protocol of a double-blinded placebo-controlled randomized clinical trial (Biperiden trial). \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 1\u0026ndash;11 (2022).\u003c/li\u003e\n\u003cli\u003eBenassi, S. K. \u003cem\u003eet al.\u003c/em\u003e Two decades of research towards a potential first anti-epileptic drug. \u003cem\u003eSeizure\u003c/em\u003e \u003cstrong\u003e90\u003c/strong\u003e, 99\u0026ndash;109 (2021).\u003c/li\u003e\n\u003cli\u003ePaxinos, G., Watson, C., Petrides, M., Rosa, M. \u0026amp; Tokuno, H. \u003cem\u003eThe marmoset brain in stereotaxic coordinates\u003c/em\u003e. \u003cem\u003eThe Marmoset Brain in Stereotaxic Coordinates\u003c/em\u003e (2012). doi:10.1007/978-0-387-78385-7.\u003c/li\u003e\n\u003cli\u003eBoyko, M. \u003cem\u003eet al.\u003c/em\u003e Traumatic brain injury-induced submissive behavior in rats : link to depression and anxiety. 1\u0026ndash;10 (2022) doi:10.1038/s41398-022-01991-1.\u003c/li\u003e\n\u003cli\u003eSanabria, V. \u003cem\u003eet al.\u003c/em\u003e Standardizing the lateral fluid percussion model of trauma in marmosets (Callithrix jacchus): regional vulnerability and inflammatory response. \u003cem\u003eBrazilian J. Med. Biol. Res.\u003c/em\u003e \u003cstrong\u003e59\u003c/strong\u003e, (2026).\u003c/li\u003e\n\u003cli\u003eBraga, M. \u003cem\u003eet al.\u003c/em\u003e Effects of acute biperiden treatment following traumatic brain injury in male rats. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 44775 (2025).\u003c/li\u003e\n\u003cli\u003ePapa, L. \u003cem\u003eet al.\u003c/em\u003e UCH-L1 is a novel biomarker for severe traumatic brain injury in human. \u003cem\u003eCrit. Care Med.\u003c/em\u003e \u003cstrong\u003e38\u003c/strong\u003e, 138\u0026ndash;44 (2010).\u003c/li\u003e\n\u003cli\u003eMondello, S. \u003cem\u003eet al.\u003c/em\u003e Ubiquitin Carboxy-Terminal Hydrolase L1 (UCH-L1) is increased in cerebrospinal fluid and plasma of patients after epileptic seizure. \u003cem\u003eBMC Neurol.\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 1 (2012).\u003c/li\u003e\n\u003cli\u003eBrophy, G. M. \u003cem\u003eet al.\u003c/em\u003e Biokinetic analysis of ubiquitin C-terminal hydrolase-L1 (UCH-L1) in severe traumatic brain injury patient biofluids. \u003cem\u003eJ. Neurotrauma\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 861\u0026ndash;870 (2011).\u003c/li\u003e\n\u003cli\u003eSaletti, P. G. \u003cem\u003eet al.\u003c/em\u003e Early preclinical plasma protein biomarkers of brain trauma are influenced by early seizures and levetiracetam. \u003cem\u003eEpilepsia Open\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 586\u0026ndash;608 (2023).\u003c/li\u003e\n\u003cli\u003eMorris, M. C. \u003cem\u003eet al.\u003c/em\u003e UCH-L1 is a Poor Serum Biomarker of Murine Traumatic Brain Injury After Polytrauma. \u003cem\u003eJ Surg Res\u003c/em\u003e \u003cstrong\u003e244\u003c/strong\u003e, 63\u0026ndash;68 (2019).\u003c/li\u003e\n\u003cli\u003eSacco, M. A. \u003cem\u003eet al.\u003c/em\u003e The Role of GFAP in Post-Mortem Analysis of Traumatic Brain Injury : A Systematic Review. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 185 (2025).\u003c/li\u003e\n\u003cli\u003eSch\u0026ouml;ll, M. \u003cem\u003eet al.\u003c/em\u003e Molecular and Cellular Neuroscience Biomarkers for tau pathology. \u003cem\u003eMol. Cell. Neurosci.\u003c/em\u003e \u003cstrong\u003e97\u003c/strong\u003e, 18\u0026ndash;33 (2019).\u003c/li\u003e\n\u003cli\u003eVillapol, S., Byrnes, K. R. \u0026amp; Symes, A. J. Temporal dynamics of cerebral blood flow, cortical damage, apoptosis, astrocyte-vasculature interaction and astrogliosis in the pericontusional region after traumatic brain injury. \u003cem\u003eFront. Neurol.\u003c/em\u003e \u003cstrong\u003e5 JUN\u003c/strong\u003e, 1\u0026ndash;9 (2014).\u003c/li\u003e\n\u003cli\u003eChen, Y., Shohami, E., Bass, R. \u0026amp; Weinstock, M. Cerebro-protective effects of ENA713 , a novel acetylcholinesterase inhibitor , in closed head injury in the rat. \u003cem\u003eBrain Res.\u003c/em\u003e 18\u0026ndash;24 (1998).\u003c/li\u003e\n\u003cli\u003eDixon, C. E. \u003cem\u003eet al.\u003c/em\u003e Time course of increased vulnerability of cholinergic neurotransmission following traumatic brain injury in the rat. \u003cem\u003eBehav. Brain Res.\u003c/em\u003e \u003cstrong\u003e70\u003c/strong\u003e, 125\u0026ndash;131 (1995).\u003c/li\u003e\n\u003cli\u003eShin, S. S. \u0026amp; Dixon, C. E. Alterations in cholinergic pathways and therapeutic strategies targeting cholinergic system after traumatic brain injury. \u003cem\u003eJ. Neurotrauma\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 1429\u0026ndash;1440 (2015).\u003c/li\u003e\n\u003cli\u003eSanabria, V. \u003cem\u003eet al.\u003c/em\u003e Anticholinergics : A potential option for preventing posttraumatic epilepsy. \u003cem\u003eFront. Neurosci.\u003c/em\u003e 1\u0026ndash;8 (2023) doi:10.3389/fnins.2022.1100256.\u003c/li\u003e\n\u003cli\u003eScarr, E. Muscarinic Receptors: Their Roles in Disorders of the Central Nervous System and Potential as Therapeutic Targets. \u003cem\u003eCNS Neurosci. Ther.\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 369\u0026ndash;379 (2012).\u003c/li\u003e\n\u003cli\u003eWestergren, H., Ryding, E., Zbornickova, V. \u0026amp; Hillman, J. Traumatic Occlusion of the Internal Carotid Artery in a Healthy Young Male : Effects on the Regional Cerebral Blood Flow. \u003cem\u003eActa Neurochir. (Wien).\u003c/em\u003e \u003cstrong\u003e113\u003c/strong\u003e, 91\u0026ndash;95 (1991).\u003c/li\u003e\n\u003cli\u003eSalehi, A., Zhang, J. H. \u0026amp; Obenaus, A. Response of the cerebral vasculature following traumatic brain injury. \u003cem\u003eJ. Cereb. Blood Flow Metab.\u003c/em\u003e \u003cstrong\u003e37\u003c/strong\u003e, 2320\u0026ndash;2339 (2017).\u003c/li\u003e\n\u003cli\u003eRao, K. V. R. \u003cem\u003eet al.\u003c/em\u003e Comparison of blood-brain barrier permeability changes in gyrencephalic ( ferret \u0026amp; non-human primate ) and lissencephalic ( rat ) models following blast overpressure exposures. \u003cem\u003eExp. Neurol.\u003c/em\u003e \u003cstrong\u003e392\u003c/strong\u003e, 115375 (2025).\u003c/li\u003e\n\u003cli\u003eHernandez-Ontiveros, D. G. \u003cem\u003eet al.\u003c/em\u003e Microglia activation as a biomarker for traumatic brain injury. \u003cem\u003eFront. Neurol.\u003c/em\u003e \u003cstrong\u003e4 MAR\u003c/strong\u003e, 1\u0026ndash;9 (2013).\u003c/li\u003e\n\u003cli\u003eDiaz-Arrastia, R. \u003cem\u003eet al.\u003c/em\u003e Pharmacotherapy of Traumatic Brain Injury : State of the Science and the Road Forward : Report of the Department of Defense Neurotrauma Pharmacology Workgroup. \u003cem\u003eJ. Neurotr\u003c/em\u003e \u003cstrong\u003e158\u003c/strong\u003e, 135\u0026ndash;158 (2014).\u003c/li\u003e\n\u003cli\u003eDihn\u0026eacute;, M., Block, F., Korr, H. \u0026amp; T\u0026ouml;pper, R. Time course of glial proliferation and glial apoptosis following excitotoxic CNS injury. \u003cem\u003eBrain Res.\u003c/em\u003e \u003cstrong\u003e902\u003c/strong\u003e, 178\u0026ndash;189 (2001).\u003c/li\u003e\n\u003cli\u003eHuang, T. \u003cem\u003eet al.\u003c/em\u003e Traumatic injury activates MAP kinases in astrocytes: Mechanisms of hypothermia and hyperthermia. \u003cem\u003eJ. Neurotrauma\u003c/em\u003e \u003cstrong\u003e26\u003c/strong\u003e, 1535\u0026ndash;1545 (2009).\u003c/li\u003e\n\u003cli\u003eCaplan, H. W. \u003cem\u003eet al.\u003c/em\u003e Spatiotemporal Distribution of Microglia After Traumatic Brain Injury in Male Mice. \u003cem\u003eASN Neuro\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, (2020).\u003c/li\u003e\n\u003cli\u003eCole, J. T. \u003cem\u003eet al.\u003c/em\u003e Craniotomy: True sham for traumatic brain injury, or a sham of a sham? \u003cem\u003eJ. Neurotrauma\u003c/em\u003e \u003cstrong\u003e28\u003c/strong\u003e, 359\u0026ndash;369 (2011).\u003c/li\u003e\n\u003cli\u003eBurda, J. E., Bernstein, A. M., Sofroniew, M. V \u0026amp; Angeles, L. Astrocyte roles in traumatic brain injury. \u003cem\u003eExp Neurol.\u003c/em\u003e \u003cstrong\u003e275\u003c/strong\u003e, 305\u0026ndash;315 (2016).\u003c/li\u003e\n\u003cli\u003eMeller, S., K\u0026auml;ufer, C., Gailus, B., Brandt, C. \u0026amp; L\u0026ouml;scher, W. Scopolamine prevents aberrant mossy fiber sprouting and facilitates remission of epilepsy after brain injury. \u003cem\u003eNeurobiol. Dis.\u003c/em\u003e \u003cstrong\u003e158\u003c/strong\u003e, (2021).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"acute, glia, vessels, biperiden, hematomas, SIMOA","lastPublishedDoi":"10.21203/rs.3.rs-9272332/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9272332/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTraumatic brain injury (TBI) leads to extensive structural damage, neuronal loss, and functional deficits, along with marked disruption of cholinergic signaling and acute surges in acetylcholine. Biperiden, a muscarinic cholinergic antagonist, has emerged as a potential neuroprotective agent due to its ability to modulate synaptic plasticity and reduce excitotoxicity. Here, we evaluated the acute effects of biperiden in a translational non-human primate model of moderate TBI. Marmosets (\u003cem\u003eCallithrix jacchus, n=39\u003c/em\u003e) subjected to lateral fluid percussion injury (LFPI) received intraperitoneal biperiden (8 mg/kg) beginning 6 h post-injury, followed by two additional doses administered at 8 h intervals. At 24 h post-injury, brain tissue and serum were assessed using histology, immunofluorescence, and Single Molecule Array (SIMOA). Twenty-four hours post-trauma, biperiden treatment, which blocks M1 receptors, markedly reduced hippocampal neuronal degeneration, decreased UCH-L1 levels, and attenuated astrocyte activation compared to saline-treated controls. These findings demonstrate that repeated dosing with biperiden confers early neurovascular and glial protection and provides acute neuroprotection following moderate TBI, mitigating neuronal injury, excitotoxicity, and inflammation. This work highlights biperiden as a promising therapeutic candidate for early intervention after traumatic brain injury.\u003c/p\u003e","manuscriptTitle":"Neurovascular and Inflammatory Effects of Biperiden in the Acute Phase of Moderate Traumatic Brain Injury: Evidence from a Non-Human Primate Model","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-17 15:11:33","doi":"10.21203/rs.3.rs-9272332/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-23T08:07:29+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-22T03:29:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81882207207956634774813042005939294538","date":"2026-04-15T21:03:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"182045895914901696133457798341743361066","date":"2026-04-15T13:25:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-14T12:37:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"11579752843993120597786689402180619896","date":"2026-04-09T20:20:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-09T14:11:41+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-09T12:11:53+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-09T11:36:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-06T14:45:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-04-06T13:21:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"31ffdf70-df30-46b9-bbcd-da61db97a045","owner":[],"postedDate":"April 17th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":66398557,"name":"Health sciences/Neurology"},{"id":66398558,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2026-05-11T07:26:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-17 15:11:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9272332","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9272332","identity":"rs-9272332","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}