Brain multiphysics最新文献

{"title":"Two for tau: Automated model discovery reveals two-stage tau aggregation dynamics in Alzheimer’s disease","authors":"Charles A. Stockman ,&nbsp;Alain Goriely ,&nbsp;Ellen Kuhl ,&nbsp;Alzheimer’s Disease Neuroimaging Initiative","doi":"10.1016/j.brain.2024.100103","DOIUrl":"10.1016/j.brain.2024.100103","url":null,"abstract":"<div><div>Alzheimer’s disease is a neurodegenerative disorder characterized by the presence of amyloid-<span><math><mi>β</mi></math></span> plaques and the accumulation of misfolded tau proteins and neurofibrillary tangles in the brain. A thorough understanding of the local accumulation of tau is critical to develop effective therapeutic strategies. Tau pathology has traditionally been described using reaction–diffusion models, which succeed in capturing the global spread, but fail to accurately describe the local aggregation dynamics. Current mathematical models enforce a single-peak behavior in tau aggregation, which does not align well with clinical observations. Here we identify a more accurate description of tau aggregation that reflects the complex patterns observed in patients. We propose an innovative approach that uses constitutive neural networks to autonomously discover bell-shaped aggregation functions with multiple peaks from clinical positron emission tomography (PET) data of misfolded tau protein. Our method reveals previously overlooked two-stage aggregation dynamics by uncovering a two-term ordinary differential equation that links the local accumulation rate to the tau concentration. When trained on data from amyloid-<span><math><mi>β</mi></math></span> positive and negative subjects, the neural network clearly distinguishes between both groups and uncovers a more subtle relationship between amyloid-<span><math><mi>β</mi></math></span> and tau than previously postulated. In line with the amyloid–tau dual pathway hypothesis, our results show that the presence of toxic amyloid-<span><math><mi>β</mi></math></span> influences the accumulation of tau, particularly in the earlier disease stages. We expect that our approach to autonomously discover the accumulation dynamics of pathological proteins will improve simulations of tau dynamics in Alzheimer’s disease and provide new insights into disease progression.</div><div><strong>Significance Statement</strong></div><div>In Alzheimer’s disease, understanding the local dynamics of tau protein aggregation is crucial for developing effective treatments. Traditional models for tau protein dynamics use reaction–diffusion models that fail to accurately capture these local patterns. Our study introduces a novel approach that leverages constitutive neural networks to autonomously discover the complex, multi-peak aggregation dynamics from clinical PET data. This method reveals a previously overlooked two-stage tau accumulation process and a nuanced relationship between amyloid-<span><math><mi>β</mi></math></span> and tau. By distinguishing between amyloid-<span><math><mi>β</mi></math></span> positive and negative subjects, our model supports the amyloid–tau dual pathway hypothesis and offers novel insights into tau protein aggregation that have the potent to advance our understanding of Alzheimer’s disease progression.</div></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"7 ","pages":"Article 100103"},"PeriodicalIF":0.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusive secondary injuries in neuronal networks following a blast impact: A morphological and electrophysiological study using a TBI-on-a-Chip model","authors":"Timothy B. Beauclair ,&nbsp;Edmond A. Rogers ,&nbsp;Jhon Martinez ,&nbsp;Shatha J. Mufti ,&nbsp;Nikita Krishnan ,&nbsp;Riyi Shi","doi":"10.1016/j.brain.2024.100104","DOIUrl":"10.1016/j.brain.2024.100104","url":null,"abstract":"<div><div>Traumatic brain injury (TBI) is a worldwide health issue. Increasing prevalence of blast-induced TBI (bTBI), a predominantly combat-related injury, is an alarming trend necessitating a better understanding of the associated pathogenesis to develop treatments. Further, most bTBI injuries are mild and undiagnosed, permitting secondary biochemical injuries to propagate beyond possible intervention. Unfortunately, few treatment options are available due to a limited understanding of the underlying mechanisms. Additional investigative tools are urgently needed to elucidate the mechanisms behind immediate and long-term bTBI-induced damage. Therefore, we introduce “bTBI-on-a-Chip,” an <em>in vitro</em> blast injury model, capable of simultaneous morphological, biochemical, and bioelectrical assessments before, during, and after blast injury. We show correlated increases in markers of oxidative stress (acrolein) and inflammation (TNF-α) accompanied by electrophysiological deficits post-blast injury. Additionally, we show that these pathological consequences are mitigated by acrolein scavenging. We also show that injury products released by cultures post-injury diffuse through culture media and instigate biochemical injury in uninjured neuronal networks. Furthermore, we show that acrolein, a diffusive component of post-TBI secondary injury, is sufficient to increase inflammation in uninjured cultures. These findings validate bTBI-on-a-Chip as an appropriate model for recapitulating and investigating blast injury <em>in vitro</em> by showing its capabilities of recreating primary and secondary bTBI, monitoring biochemical and electrophysiological responses to injury, and screening possible pharmacological interventions post-injury. We expect that this model could provide insights into the pathological biochemical mechanisms that will be critical in developing future diagnostic and treatment strategies for bTBI patients.</div></div><div><h3>Statement of Significance</h3><div>The findings in the current study validate bTBI-on-a-Chip as an appropriate model for recapitulating and investigating blast injury <em>in vitro</em> by demonstrating its capabilities of recreating primary and secondary bTBI, monitoring biochemical and electrophysiological responses to injury, and screening possible pharmacological interventions post-injury. We expect that this model could provide insights into the pathological biochemical mechanisms that will be critical in developing future diagnostic and treatment strategies for bTBI patients.</div></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"7 ","pages":"Article 100104"},"PeriodicalIF":0.0,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scaling in the brain","authors":"D. Le Bihan","doi":"10.1016/j.brain.2024.100102","DOIUrl":"10.1016/j.brain.2024.100102","url":null,"abstract":"<div><div>Proper scaling is an important concept in physics. It allows theoretical frameworks originally developed to address a specific question to be generalized or recycled to solve another problem at a different scale. The rescaling of the theory of heat to link diffusion and Brownian motion is a famous example set out by Einstein. We have recently shown how the special and general relativity theories could be scaled down to the action potential propagation speed in the brain to explain some of its functioning: Functional “distances” between neural nodes (geodesics), depend on both the spatial distances between nodes and the time to propagate between them, through a connectome spacetime with four intricated dimensions. This spacetime may further be curved by neural activity suggesting how conscious activity could act in a similar the gravitational field curved the physical spacetime. Indeed, the apparent gap between the microscopic and macroscopic connectome scales may find an echo in the AdS/CFT correspondence. Applied to the brain connectome, this means that consciousness may appear as the emergence in a 5D spacetime of the neural activity present as its boundaries, the 4D cortical spacetime, as a holographic 5D construction by our inner brain. We explore here how the conflict between ‘consciousness and matter’ could be resolved by considering that the spacetime of our cerebral connectome has five dimensions, the fifth dimension allowing the natural, immaterial emergence of consciousness as a dual form of the 4D spacetime embedded in our material cerebral cortex.</div></div><div><h3>Statement Of Significance</h3><div>Scaling to the brain the AdS/CFT framework which shows how the General Gravity framework, hence gravitation, naturally (mathematically) emerges from a “flat”, gravitationless Quantum 4D spacetime once a fifth dimension is considered, we conjecture that the conflict between ‘consciousness and matter’ might be ill-posed and could be resolved by considering that the spacetime of our cerebral connectome has five dimensions, the fifth dimension allowing the natural, immaterial (mind, private) emergence of consciousness as a dual form of the 4D spacetime activity embedded in our material (body, public) cerebral cortex.</div></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"7 ","pages":"Article 100102"},"PeriodicalIF":0.0,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142656329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying CSF Dynamics disruption in idiopathic normal pressure hydrocephalus using phase lag between transmantle pressure and volumetric flow rate","authors":"Pragalv Karki ,&nbsp;Stephanie Sincomb ,&nbsp;Matthew C. Murphy ,&nbsp;Jeffrey L. Gunter ,&nbsp;Matthew L. Senjem ,&nbsp;Jonathan Graff-Radford ,&nbsp;David T. Jones ,&nbsp;Hugo Botha ,&nbsp;Jeremy K. Cutsforth-Gregory ,&nbsp;Benjamin D. Elder ,&nbsp;John Huston III ,&nbsp;Petrice M. Cogswell","doi":"10.1016/j.brain.2024.100101","DOIUrl":"10.1016/j.brain.2024.100101","url":null,"abstract":"<div><h3>Background and purpose</h3><div>Idiopathic normal pressure hydrocephalus (iNPH) is a cerebrospinal fluid (CSF) dynamics disorder as evidenced by the delayed ascent of radiotracers over the cerebral convexity on radionuclide cisternography. However, the exact mechanism causing this disruption remains unclear. Elucidating the pathophysiology of iNPH is crucial, as it is a treatable cause of dementia. Improving the diagnosis and treatment prognosis rely on the better understanding of this disease. In this study, we calculated the pulsatile transmantle pressure and investigated the phase lag between this pressure and the volumetric CSF flow rate as a novel biomarker of CSF dynamics disruption in iNPH.</div></div><div><h3>Methods</h3><div>44 iNPH patients and 44 age- and sex-matched cognitively unimpaired (CU) control participants underwent MRI scans on a 3T Siemens scanner. Pulsatile transmantle pressure was calculated analytically and computationally using volumetric CSF flow rate, cardiac frequency, and aqueduct dimensions as inputs. CSF flow rate through the aqueduct was acquired using phase-contrast MRI. The aqueduct length and radius were measured using 3D T1-weighted anatomical images.</div></div><div><h3>Results</h3><div>Peak pressure amplitudes and the pressure load (integrated pressure exerted over a cardiac cycle) were similar between the groups, but the non-dimensionalized pressure load (adjusted for anatomical factors) was significantly lower in the iNPH group (<em>p&lt;0.001</em>, Welch's t-test). The phase lag between the pressure and the flow rate, arising due to viscous drag, was significantly higher in the iNPH group (<em>p&lt;0.001</em>).</div></div><div><h3>Conclusion</h3><div>The increased phase lag is a promising new biomarker for quantifying CSF dynamics dysfunction in iNPH.</div></div><div><h3>Statement of Significance</h3><div>The exact mechanism causing the disruption of CSF circulation in idiopathic normal pressure hydrocephalus (iNPH) remains unclear. Elucidating the pathophysiology of iNPH is crucial, as it is a treatable cause of dementia. In this study, we provided an analytical and a computational method to calculate the pulsatile transmantle pressure and the phase lag between the pressure and the volumetric CSF flow rate across the cerebral aqueduct. The phase lag was significantly higher in iNPH patients than in controls and may serve as a novel biomarker of CSF dynamics disruption in iNPH.</div></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"7 ","pages":"Article 100101"},"PeriodicalIF":0.0,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increased hindbrain motion in Chiari I malformation patients measured through 3D amplified MRI (3D aMRI)","authors":"Javid Abderezaei ,&nbsp;Fargol Rezayaraghi ,&nbsp;Aymeric Pionteck ,&nbsp;Ya-Chen Chuang ,&nbsp;Alejandro Carrasquilla ,&nbsp;Gizem Bilgili ,&nbsp;Tianyi Ren ,&nbsp;Tyson Lam ,&nbsp;Tse-An Lu ,&nbsp;Miriam Scadeng ,&nbsp;Patrick Fillingham ,&nbsp;Peter Morgenstern ,&nbsp;Michael R. Levitt ,&nbsp;Richard G. Ellenbogen ,&nbsp;Yang Yang ,&nbsp;Samantha J. Holdsworth ,&nbsp;Raj Shrivastava ,&nbsp;Mehmet Kurt","doi":"10.1016/j.brain.2024.100100","DOIUrl":"10.1016/j.brain.2024.100100","url":null,"abstract":"<div><div>Chiari Malformation type 1 (CM-I) is a neurological disorder characterized by morphological defects including excessive cerebellar tonsillar ectopia and associated manifestations. We used 3D amplified MRI on a cohort of healthy and CM-I subjects to investigate the brain’s intrinsic motion, its association with the morphology and patient’s symptomatology, and surgical outcomes. We observed that the regional brain motion in CM-I was significantly higher than that of the healthy subjects, with anterior-posterior (AP) and superior-inferior (SI) displacements in cerebellar tonsils and medulla having the highest differences between the healthy and CM-I (<span><math><mo>∼</mo></math></span>45%–<span><math><mo>∼</mo></math></span>73% increased motion in the CM-I group). Interestingly, we found the ratio of neural tissue in the foramen magnum to be directly correlated with the SI tonsillar motion (<span><math><mrow><mi>r</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>58</mn></mrow></math></span>). Tonsillar herniation was directly correlated with the AP motion of the tonsils (<span><math><mrow><mi>r</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>61</mn></mrow></math></span>), and AP and medial-lateral (ML) motions of the medulla (<span><math><mrow><mi>r</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>66</mn></mrow></math></span>, and <span><math><mrow><mi>r</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>57</mn></mrow></math></span>). Subjects with higher tonsillar ML motion prior to surgery showed improved outcome (<span><math><mrow><mi>p</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>03</mn></mrow></math></span>, and <span><math><mrow><mi>A</mi><mi>U</mi><mi>C</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>95</mn></mrow></math></span>). Although we did not observe a significant correlation between the brains motion and morphometrics on the CM-I symptoms (perhaps due to our small sample size), illustrative cases increase our hope for the development of a future tool based on brain biomechanics.</div></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"7 ","pages":"Article 100100"},"PeriodicalIF":0.0,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142418347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring tau protein and amyloid-beta propagation: A sensitivity analysis of mathematical models based on biological data","authors":"Mattia Corti","doi":"10.1016/j.brain.2024.100098","DOIUrl":"10.1016/j.brain.2024.100098","url":null,"abstract":"<div><p>Alzheimer’s disease is the most common dementia worldwide. Its pathological development is well known to be connected with the accumulation of two toxic proteins: tau protein and amyloid-<span><math><mi>β</mi></math></span>. Mathematical models and numerical simulations can predict the spreading patterns of misfolded proteins in this context. However, the calibration of the model parameters plays a crucial role in the final solution. In this work, we perform a sensitivity analysis of heterodimer and Fisher–Kolmogorov models to evaluate the impact of the equilibrium values of protein concentration on the solution patterns. We adopt advanced numerical methods such as the IMEX-DG method to accurately describe the propagating fronts in the propagation phenomena in a polygonal mesh of sagittal patient-specific brain geometry derived from magnetic resonance images. We calibrate the model parameters using biological measurements in the brain cortex for the tau protein and the amyloid-<span><math><mi>β</mi></math></span> in Alzheimer’s patients and controls. Finally, using the sensitivity analysis results, we discuss the applicability of both models in the correct simulation of the spreading of the two proteins.</p><p><strong>Statement of significance:</strong> Alzheimer’s disease is related to the accumulation of tau protein and amyloid-<span><math><mi>β</mi></math></span>. Mathematical models to predict the spreading patterns require accurate parameter calibration. In this work, we perform a sensitivity analysis of heterodimer and Fisher–Kolmogorov models to evaluate the impact of the equilibrium values of protein concentration on the solution patterns obtained with advanced numerical simulations on patient-specific brain geometry derived from magnetic resonance images. By using biological measurements in the brain cortex for the proteins in Alzheimer’s patients and controls, we use sensitivity analysis to discuss the applicability of models in simulating protein spreading.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"7 ","pages":"Article 100098"},"PeriodicalIF":0.0,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666522024000091/pdfft?md5=aeceabaf3cdacef18e0177333e021da0&pid=1-s2.0-S2666522024000091-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142095874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Erratum: Bok's equi-volume principle: Translation, historical context, and a modern perspective","authors":"Jack Consolini ,&nbsp;Nagehan Demirci ,&nbsp;Andrew Fulwider ,&nbsp;Jeffrey J. Hutsler ,&nbsp;Maria A. Holland","doi":"10.1016/j.brain.2024.100099","DOIUrl":"10.1016/j.brain.2024.100099","url":null,"abstract":"","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"7 ","pages":"Article 100099"},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666522024000108/pdfft?md5=85bffcba8e1f2fefe558acba8058145a&pid=1-s2.0-S2666522024000108-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142089579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical modelling of multiple sclerosis: A tissue-scale model of brain lesions","authors":"H Hutchison ,&nbsp;AC Szekely-Kohn ,&nbsp;W Li ,&nbsp;DET Shepherd ,&nbsp;DM Espino","doi":"10.1016/j.brain.2024.100097","DOIUrl":"10.1016/j.brain.2024.100097","url":null,"abstract":"<div><p>Multiple Sclerosis (MS) is an autoimmune condition leading to the degeneration of brain tissue, occurring when the immune system attacks the myelin sheath surrounding axons of white brain matter thereby disrupting brain signals. This study aimed to evaluate how MS lesions alter stress distribution through grey and white brain matter with lesions (active, chronic, and inactive). A linear viscoelastic model represents the tissue-scale dynamic deformation and time dependency of brain tissue. A Prony series expansion was used to model viscous effects including stress relaxation. An elastic modulus, within the viscoelastic model, was either reduced by 11 % for active lesions, or increased by 35 % increase for inactive lesions. These material properties were then implemented to model healthy tissue, active, chronically inflamed, and inactive lesions. Finite element analysis enabled stress evaluation in response to a peak cyclic displacement of 0.5 mm (1 % strain) with the healthy model acting as a control model. Chronic lesions had the largest effect on stress induced, in terms of high (171 Pa) and low stress (108 Pa). Inactive lesions induced an increase in stress of 11 Pa with areas of low stress (105 Pa). Active lesions caused the least deviation in peak induced stress (7 Pa). In conclusion, a hierarchy in stress induced across the lesion types has been found, from highest to lowest: chronic, inactive and active, with potential implications for lesion progression. In conclusion, MS lesions within brain tissue should model lesions, avoid assuming homogeneity during degeneration, and should distinguish between active and passive lesions.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"7 ","pages":"Article 100097"},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266652202400008X/pdfft?md5=c61e0d8bb0c1c5deae2abbe79eb2f37a&pid=1-s2.0-S266652202400008X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141985374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Alzheimer’s disease and the mathematical mind","authors":"Travis B. Thompson,&nbsp;Bradley Z. Vigil,&nbsp;Robert S. Young","doi":"10.1016/j.brain.2024.100094","DOIUrl":"10.1016/j.brain.2024.100094","url":null,"abstract":"<div><p>Throughout the 19th and 20th centuries, aided by advances in medical imaging, discoveries in physiology and medicine have added nearly 25 years to the average life expectancy. This resounding success brings with it a need to understand a broad range of age-related health conditions, such as dementia. Today, mathematics, neuroimaging and scientific computing are being combined with fresh insights, from animal models, to study the brain and to better understand the etiology and progression of Alzheimer’s disease, the most common cause of age-related dementia in humans. In this manuscript, we offer a brief primer to the reader interested in engaging with the exciting field of mathematical modeling and scientific computing to advance the study of the brain and, in particular, human AD research.</p><p><strong>Statement of Significance</strong> Modeling Alzheimer’s disease is a highly interdisciplinary field and finding an effective starting point can be a considerable challenge. To address this challenge, this manuscript briefly highlights some central components of AD related protein pathology, useful classes of mathematical models for brain and AD research and effective computational resources for the practical prospective practitioner.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"6 ","pages":"Article 100094"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666522024000054/pdfft?md5=68c335b8652a866dd25fe222cee1915e&pid=1-s2.0-S2666522024000054-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140770887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revealing the heterogeneity of plasma protein and cognitive decline trajectory among Mild Cognitive Impairment patients by clustering of brain atrophy features","authors":"My Nguyen ,&nbsp;Bao Pham ,&nbsp;Toi Vo ,&nbsp;Huong Ha","doi":"10.1016/j.brain.2024.100093","DOIUrl":"https://doi.org/10.1016/j.brain.2024.100093","url":null,"abstract":"<div><p>Alzheimer's disease (AD) is suggested to be a heterogeneous disorder, but limited studies explore the heterogeneity of the Mild Cognitive Impairment (MCI) stage. This study aimed to tackle such problems using the CIMLR (Cancer Integration via Multikernel Learning) algorithm to cluster brain structural features extracted from T1-weighted Magnetic Resonance Images of MCI patients from Alzheimer's Disease Neuroimaging Initiative. The demographic and cognitive results, characteristics of brain structural features, plasma biomarkers, and longitudinal cognitive trajectory were analyzed for each cluster. The CIMLR clustering analysis revealed four distinct clusters. Cluster 1 is the oldest group but has had mild atrophy and moderate progression with elevated Tumor Necrosis Factor Receptor 2 level; and low Brain-Derived Neurotrophic Factor and CD40 Ligand levels. Cluster 2 showed the highest risk for aggressive MCI progression, with abnormal Leptin, Adiponectin, and Creatine kinase-MB values. Cluster 3 exhibited a low level of Monokine Induced by Gamma Interferon and mild atrophy that shared similar patterns with Cluster 1. Cluster 4 represented the healthiest group during longitudinal tracking, with the mildest Parahippocampal atrophy, which was found to be positively correlated with cognitive impairment and amino acid levels. The longitudinal analyses showed the potential of Hepatocyte Growth Factor as a marker for slow cognitive impairment; Cortisol and Neurofilament Light Polypeptide as prognosis markers for aggressive MCI progression. These findings may lay out new suggestions for further research contributing to the accurate diagnosis and precision medicine for dementia and AD.</p></div>","PeriodicalId":72449,"journal":{"name":"Brain multiphysics","volume":"6 ","pages":"Article 100093"},"PeriodicalIF":0.0,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666522024000042/pdfft?md5=46b752042d20179714382c09e7dd6e1c&pid=1-s2.0-S2666522024000042-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140341135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}