Brain Research最新文献

{"title":"EAE models of neuropathic pain in multiple sclerosis do not require pertussis toxin","authors":"Sydney R. Lamerand ,&nbsp;Paramita Basu ,&nbsp;Nina E. Gakii ,&nbsp;Skyy S. Steber ,&nbsp;Bradley K. Taylor","doi":"10.1016/j.brainres.2026.150162","DOIUrl":"10.1016/j.brainres.2026.150162","url":null,"abstract":"<div><h3>Background</h3><div>Experimental autoimmune encephalomyelitis (EAE) is a preclinical model of multiple sclerosis (MS), typically induced with two inoculations of myelin oligodendrocyte glycoprotein (MOG_35-55) emulsified in complete Freund’s adjuvant (CFA), and supplemented with pertussis toxin (PTX). Although PTX has been considered essential, recent studies suggest that EAE pathology can develop without it.</div></div><div><h3>Objectives</h3><div>Indices of clinical disease and neuropathic pain were evaluated in a conventional model of EAE that included PTX (EAE-PTX) and one that lacked PTX (EAE-nPTX), as well as in multiple control groups that lacked MOG_35-55 (CFA-PTX and CFA-nPTX).</div></div><div><h3>Methods</h3><div>A battery of behavioral tests were used to evaluate motor dysfunction and hypersensitivity to mechanical, cold, and heat stimuli with a repeated-measures design in male and female C57BL/6 mice. One month after the first EAE inoculation, fluoromyelin staining was used to evaluate demyelination in spinal cord, cortex, and peripheral nerve, while ATF3 was used as a marker of injury in sensory neurons of lumbar L4-L5 dorsal root ganglia (DRG).</div></div><div><h3>Results</h3><div>Compared to CFA-PTX and CFA-nPTX controls, both EAE-PTX and EAE-nPTX groups developed motor dysfunction, behavioral hypersensitivity, and demyelination in ventral spinal cord but not cortex. Spinal demyelination was greater in EAE-nPTX than in EAE-PTX. ATF3 was detected in lumbar DRG of all EAE and CFA control groups, suggesting that systemic inflammation, rather than MOG_35-55-driven neuropathology, contributes to neuron damage.</div></div><div><h3>Conclusions</h3><div>PTX is not required for the manifestation of motor dysfunction and neuropathic pain in MOG_35-55-based EAE models. Newer EAE-nPTX models have the distinct advantage of mimicking MS disease while avoiding confounding effects of pertussis toxin.</div></div>","PeriodicalId":9083,"journal":{"name":"Brain Research","volume":"1875 ","pages":"Article 150162"},"PeriodicalIF":2.6,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145965186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aperiodic slope reflects glutamatergic tone in the human brain","authors":"Aislin A. Sheldon ,&nbsp;Hannah R. Moser ,&nbsp;Kamar S. Abdullahi ,&nbsp;Karly D. Allison ,&nbsp;Carter B. Mulder ,&nbsp;Samantha A. Montoya ,&nbsp;Scott R. Sponheim ,&nbsp;Małgorzata Marjańska ,&nbsp;Michael-Paul Schallmo","doi":"10.1016/j.brainres.2026.150161","DOIUrl":"10.1016/j.brainres.2026.150161","url":null,"abstract":"<div><div>Excitatory and inhibitory neural processes are essential for every aspect of brain function, but current non-invasive neuroimaging methods to study these in the human brain are limited. Recent studies which separate oscillatory and aperiodic components of electrophysiological power spectra have highlighted a relationship between aperiodic activity and functional brain states. Studies in both animal models and humans suggest that the aperiodic slope of electrophysiological power spectra reflects the local balance of excitatory:inhibitory (E:I) synaptic transmission. Aperiodic slope varies across individuals, brain states, and clinical populations, which may reflect important differences in E:I balance. However, there is currently a lack of evidence linking aperiodic slope to other measures of excitation and inhibition in the human brain. Here, we show that flatter (less steep) aperiodic slopes from human electroencephalography (EEG) are associated with higher concentrations of the excitatory neural metabolite glutamate measured with 7 T magnetic resonance spectroscopy (MRS) in the occipital lobe at rest. This suggests that individual differences in aperiodic neural activity reflect cortical glutamate concentrations, providing important insight for understanding changes in neural excitation across brain states and neuropsychiatric populations (e.g., schizophrenia) where glutamatergic function may differ. Our results support the use of aperiodic slope as a non-invasive marker for excitatory tone in the human brain.</div></div>","PeriodicalId":9083,"journal":{"name":"Brain Research","volume":"1874 ","pages":"Article 150161"},"PeriodicalIF":2.6,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145951467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From truth to deception: a network control theory perspective on brain connectivity and cognitive dynamics","authors":"Ali Rahimi Saryazdi ,&nbsp;Farnaz Ghassemi ,&nbsp;Fatemeh Parastesh ,&nbsp;Karthikeyan Rajagopal ,&nbsp;Sajad Jafari","doi":"10.1016/j.brainres.2026.150159","DOIUrl":"10.1016/j.brainres.2026.150159","url":null,"abstract":"<div><div>Deception represents a sophisticated mental activity that modifies the brain’s dynamic operations. Understanding how brain activity changes during deceptive behavior is important for both cognitive neuroscience and practical applications such as lie detection. Recently, network control theory (NCT) has emerged as a novel tool that combines principles from network science and control theory, offering a powerful framework for quantifying how easily the brain can transition between different cognitive states. In this study, NCT is applied for the first time to examine the effects of deception on brain functional connectivity (FC). Electroencephalogram signals are recorded from 22 participants during a visual task designed to elicit deception. The phase lag index method is then employed to construct FC networks for both truthful and deceptive conditions. The brain is modeled as a linear dynamical system, and two control metrics, average controllability and modal controllability, are computed across five frequency bands: delta, theta, alpha, beta, and gamma. The results reveal significant differences in brain dynamics between the two conditions. In the delta and beta bands, average controllability is significantly higher during truthful responses (p-value &lt; 0.005), while in the gamma band, it is elevated during deception. Additionally, in the beta and gamma bands, modal controllability is significantly higher during deceptive responses (p-value &lt; 0.005). It is observed that during deception, the control energy spectrum shifts from predominance in lower frequencies, which is more evident in truthful responses, toward higher frequencies where energy increases during deception. The outcomes imply that brain connectivity patterns are affected by deceptive behavior and highlight the potential of NCT in advancing deception-related investigations.</div></div>","PeriodicalId":9083,"journal":{"name":"Brain Research","volume":"1875 ","pages":"Article 150159"},"PeriodicalIF":2.6,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145951490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"K-means++ guided multi-view CNN with channel attention for EEG emotion recognition","authors":"Yi Zhou,&nbsp;Ruiwen Jiang,&nbsp;Jingxiang Zhang","doi":"10.1016/j.brainres.2026.150160","DOIUrl":"10.1016/j.brainres.2026.150160","url":null,"abstract":"<div><div>The use of artificial intelligence for emotion recognition is the focus of improving human–computer interaction. Recently, deep learning has been widely used in the study of emotion recognition. However, how to correctly identify emotions still faces a huge challenge. We propose a multi-view deep CNN based on channel attention (MVACNN) for EEG emotion recognition. MVACNN first clustered the channels and divided the channels with high similarity into the same view. Channels within the same view have highly similar patterns of neural activity, which can extract the synergistic features of specific brain regions more intensively and reduce the interference of irrelevant noise. To extract more discriminative features, MVACNN integrates channel attention into each view. Channel attention gives different channel weights to effectively learn the importance of different channels. In addition, MVACNN uses residual blocks to learn the residual variation to better represent the relationship between input and output. The residual structure preserves the original information, improving feature utilization and thus maintaining performance. Experimental results show that MVACNN achieves good results on different datasets.</div></div>","PeriodicalId":9083,"journal":{"name":"Brain Research","volume":"1874 ","pages":"Article 150160"},"PeriodicalIF":2.6,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145951512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The mechanism of Calhm2 regulating the expression of CaMKIIα in spinal dorsal horn involved in the pathogenesis of bone cancer pain","authors":"Mengyuan Xiong ,&nbsp;Xiaohui Li ,&nbsp;Shanchun Su ,&nbsp;Xueqin Xu ,&nbsp;Jiaqi Yu ,&nbsp;Wei Tian ,&nbsp;Linhan Wang ,&nbsp;Changbin Ke","doi":"10.1016/j.brainres.2026.150158","DOIUrl":"10.1016/j.brainres.2026.150158","url":null,"abstract":"<div><div>Bone cancer pain (BCP) is one of the most common and debilitating types of pain in cancer patients, severely impairing the quality of life in advanced stages of the disease. However, its underlying mechanisms remain poorly understood, highlighting the urgent need to clarify its pathogenesis and identify novel therapeutic targets. Increasing evidence suggests that altered excitability of spinal dorsal horn neurons is a prerequisite for pain generation. The dynamic balance of intracellular and extracellular calcium ion concentrations is critical for maintaining normal neuronal excitability. In this study, we investigated the role of calcium homeostasis modulator 2 (Calhm2) in BCP. In BCP mice, the expression of Calhm2 in the spinal dorsal horn was significantly upregulated, accompanied by a concomitant increase in calcium/calmodulin-dependent protein kinase II α (CaMKIIα). Lentiviral-mediated knockdown of Calhm2 in the spinal dorsal horn reduced CaMKIIα expression, alleviated mechanical allodynia, and decreased c-fos expression. These findings suggest that Calhm2 regulates CaMKIIα to promote neuronal activation in the spinal dorsal horn, thereby contributing to the development of bone cancer pain. Calhm2 may represent a promising target for therapeutic intervention in BCP.</div></div>","PeriodicalId":9083,"journal":{"name":"Brain Research","volume":"1874 ","pages":"Article 150158"},"PeriodicalIF":2.6,"publicationDate":"2026-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145951440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Elevated FKBP5 expression associates with epilepsy-related molecular changes and promotes neuronal hyperexcitability","authors":"Meng Cai ,&nbsp;Shuyang Wang ,&nbsp;Mingsu Liu ,&nbsp;Bin Lai ,&nbsp;Chen Chen ,&nbsp;Jing Ding ,&nbsp;Xin Wang","doi":"10.1016/j.brainres.2026.150157","DOIUrl":"10.1016/j.brainres.2026.150157","url":null,"abstract":"<div><h3>Objective</h3><div>Epilepsy is one of the neurological disorders, characterized by recurrent, spontaneous seizures arising from neuronal hyperexcitability and hypersynchrony in the brain. The mechanisms of epilepsy are intricate and remain elusive. FKBP5 has emerged as a significant protein implicated in neurological disorders such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). This study aims to investigate the role of FKBP5 in a kainic acid (KA)-induced intrahippocampal epilepsy model and assessed how FKBP5 gain-of-function and FKBP51 inhibition influence neurotransmitter dynamics and neuronal excitability.</div></div><div><h3>Methods</h3><div>We examined the expression of FKBP5 in the hippocampus of the kainic acid (KA)-induced epilepsy model. To explore the impact of FKBP5 on neuronal activity, we overexpressed FKBP5 in primary cortical neurons and astrocytes, assessing extracellular glutamate levels in neuron–astrocytes co-cultures with or without the FKBP51-selective inhibitor SAFit2 (250 nM). Intrinsic excitability, voltage-gated Na⁺ currents, and network activity were evaluated using whole-cell patch-clamp recordings and high-density microelectrode arrays (HD-MEAs).</div></div><div><h3>Results</h3><div>We observed an elevated level of FKBP5 in the hippocampus of a kainic acid (KA)-induced chronic epilepsy mouse model, whereas cortical FKBP5 did not show clear changes across the examined post-insult time points.. Moreover, FKBP5 overexpression induced a remarkable increase in the extracellular glutamate level in co-cultured primary cortical neurons and astrocytes. Intriguingly, FKBP5 overexpression modifies the electrophysiological properties of primary neurons, resulting in increased intrinsic excitability and enhanced Na⁺ currents. Additionally, the network activity exhibits hyperexcitability with FKBP5 overexpression. Notably, SAFit2 treatment was also associated with elevated extracellular glutamate in the co-culture system, while intracellular FKBP5 and EAAT2 protein levels showed no significant group differences in the current dataset.</div></div><div><h3>Conclusion</h3><div>These findings suggested that FKBP5 played a significant role in regulating neuronal excitability and extracellular glutamate homeostasis. However, due to discrete sampling and the lack of continuous seizure monitoring, the present <em>in vivo</em> data do not establish a definitive causal contribution of FKBP5 to epileptogenesis, warranting future studies integrating longitudinal EEG and cell-type-specific manipulations.</div></div>","PeriodicalId":9083,"journal":{"name":"Brain Research","volume":"1874 ","pages":"Article 150157"},"PeriodicalIF":2.6,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145948667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of the dentate gyrus of hippocampus on acute pain modulation: Investigating of dopaminergic-opioidergic interactions in pain-related behaviors in the tail-flick test","authors":"Sahar Sadeghzadeh Sotoudeh ,&nbsp;Shima Abtin ,&nbsp;Roghayeh Mozafari ,&nbsp;Abbas Haghparast","doi":"10.1016/j.brainres.2026.150155","DOIUrl":"10.1016/j.brainres.2026.150155","url":null,"abstract":"<div><div>Previous studies have shown that injections of opioid and dopamine agonists alone into the dentate gyrus (DG) increase the threshold for acute pain responses. Therefore, this study aimed to investigate whether the opioid and D1-like dopamine receptor (D1R) interact to modulate acute pain in DG. One hundred and forty-seven adult male Wistar rats were cannulated unilaterally in the DG. Separate groups of animals received different doses of SCH23390 (6, 12, and 24 mmol/0.5 μL), a D1R antagonist, before injection of an effective dose of morphine (25 mmol/0.5 μL). In another experiment, animals received different naloxone (5, 15, and 45 mmol/0.5 μL) dose, an opioid receptor antagonist, before administering the effective dose of SKF38393 (6 mmol/0.5 μL). Acute pain threshold was assessed using the tail-flick test. Behavioral data analysis indicated that blockade of D1R in the DG significantly attenuated morphine-induced antinociception (P &lt; 0.001). Furthermore, the antinociceptive effects of SKF38393 were significantly reduced by blocking opioid receptors in the DG (P &lt; 0.01). Interestingly, the effect of SCH23390 in reducing the antinociceptive effects of morphine (η2 = 0.65) was numerically higher than the effect of naloxone in reducing the antinociceptive effects of SKF38393 (η2 = 0.46). The results suggest a strong interaction between opioidergic and dopaminergic systems in the DG in modulating acute pain. These findings can be used to reveal the precise mechanisms of pain modulation in brain circuits and to develop new strategies in pain management with greater efficacy and fewer side effects.</div></div>","PeriodicalId":9083,"journal":{"name":"Brain Research","volume":"1875 ","pages":"Article 150155"},"PeriodicalIF":2.6,"publicationDate":"2026-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145942368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diffusion spectrum imaging-based machine learning for temporal lobe epilepsy lateralization","authors":"Zhen-Ming Wang ,&nbsp;Yaqin Hou ,&nbsp;Chunxue Wu ,&nbsp;Miao Zhang ,&nbsp;Jie Lu","doi":"10.1016/j.brainres.2026.150154","DOIUrl":"10.1016/j.brainres.2026.150154","url":null,"abstract":"<div><h3>Objective</h3><div>Accurate preoperative lateralization of temporal lobe epilepsy (TLE) remains challenging, particularly in cases with subtle or MRI-negative lesions. This study aimed to overcome limitations of conventional MRI by developing a diffusion spectrum imaging (DSI)-based machine learning approach for noninvasive TLE lateralization.</div></div><div><h3>Methods</h3><div>We retrospectively analyzed DSI scans from 49 unilateral TLE patients (29 left, 20 right) and 25 healthy controls (HC). Local connectome fingerprints and quantitative anisotropy (QA) features were extracted. A support vector machine (SVM) was trained to classify patients from controls and to identify the epileptogenic hemisphere. Model performance was evaluated using 10-fold stratified cross-validation, with feature selection and dimensionality reduction performed within each training fold.</div></div><div><h3>Results</h3><div>The DSI-based SVM achieved high accuracy in distinguishing TLE from HC. With fingerprint features, accuracy was 97.3% (sensitivity 0.959, specificity 1.000); QA features yielded the same accuracy 97.3% (sensitivity 0.980, specificity 0.960). For lateralization among patients, the fingerprint model reached 100% accuracy versus 91.8% for QA. In the three-class classification task (left TLE, right TLE and HC), the models achieved accuracies of 78.4% (fingerprint) and 73.0% (QA). The fingerprint-based classifier yielded F1-scores of 0.943 for HC, 0.727 for LTLE, and 0.650 for RTLE; QA achieved F1-scores of 0.875, 0.677, and 0.632, respectively. DeLong’s test found no significant AUC differences.</div></div><div><h3>Conclusion</h3><div>DSI-derived metrics combined with machine learning enable accurate, noninvasive lateralization of TLE. This approach addresses clinical necessities by reliably detecting epileptogenic zones, including cases with subtle structural abnormalities, offering significant potential to enhance presurgical decision-making and patient outcomes.</div></div>","PeriodicalId":9083,"journal":{"name":"Brain Research","volume":"1874 ","pages":"Article 150154"},"PeriodicalIF":2.6,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145932088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of the disulfidptosis-related gene IQGAP1 as a potential diagnostic biomarker in Parkinson’s disease","authors":"Jianlin Li ,&nbsp;Jianhang You ,&nbsp;Zaipu Li ,&nbsp;Jing Zang ,&nbsp;Lin Wu ,&nbsp;Tao Zhao","doi":"10.1016/j.brainres.2026.150153","DOIUrl":"10.1016/j.brainres.2026.150153","url":null,"abstract":"<div><h3>Background</h3><div>Parkinson’s disease is the second most common and fastest-growing neurodegenerative disorder worldwide. However, its complex pathogenic mechanisms remain incompletely understood, and effective therapeutic strategies are still lacking. Disulfidptosis is a newly identified form of regulated cell death that has been shown to be closely associated with multiple diseases; nevertheless, its role in Parkinson’s disease has not yet been elucidated. In this study, we systematically investigated the expression patterns and potential functions of disulfidptosis-related differentially expressed genes that are significantly associated with Parkinson’s disease risk, using bulk transcriptomic data and single-cell RNA sequencing analyses.</div></div><div><h3>Methods</h3><div>We integrated single-cell RNA sequencing data with large-scale transcriptomic datasets to construct a disulfidptosis-related diagnostic model for Parkinson’s disease. First, twenty-five known disulfidptosis-related genes were collected from published literature and public databases. Differential expression analysis of GEO datasets was then performed to identify significantly differentially expressed genes between Parkinson’s disease and healthy control samples, which were subsequently used to build an initial diagnostic model. The expression profiles of key genes were further validated in external cohorts to enhance the robustness and reliability of the model. Next, single-cell RNA sequencing data from patients with Parkinson’s disease were incorporated to refine the identification of DRGs that were significantly associated with disease risk. Finally, quantitative real-time reverse transcription PCR was employed to experimentally validate the expression of the critical genes.</div></div><div><h3>Results</h3><div>We identified four DRGs in total. Using least absolute shrinkage and selection operator regression and random forest algorithms, three hub genes with diagnostic potential were further screened. After validation in external datasets and at the single-cell level, <em>IQGAP1</em> was ultimately confirmed as the key gene by quantitative real-time reverse transcription PCR, showing significantly upregulated expression in Parkinson’s disease samples.</div></div><div><h3>Conclusion</h3><div>This study provides the first evidence suggesting that disulfidptosis-related genes may be involved in the pathogenesis of Parkinson’s disease and highlights <em>IQGAP1</em> as a key molecule with potential value in Parkinson’s disease risk assessment and diagnosis. These findings not only offer a new perspective for elucidating the molecular mechanisms underlying Parkinson’s disease, but also provide a theoretical basis for identifying potential biomarkers and optimizing individualized therapeutic strategies, thereby further promoting the application of precision medicine in the field of Parkinson’s disease.</div></div>","PeriodicalId":9083,"journal":{"name":"Brain Research","volume":"1874 ","pages":"Article 150153"},"PeriodicalIF":2.6,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145932082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measurement of respiration in ex vivo mitochondria isolated from fresh human brain","authors":"Patrick J. McCarty ,&nbsp;Brianna A. Werner ,&nbsp;Adrienne C. Scheck ,&nbsp;Eric Wang ,&nbsp;Indrapal N. Singh ,&nbsp;John Gaitanis ,&nbsp;P. David Adelson ,&nbsp;Richard E. Frye","doi":"10.1016/j.brainres.2026.150156","DOIUrl":"10.1016/j.brainres.2026.150156","url":null,"abstract":"","PeriodicalId":9083,"journal":{"name":"Brain Research","volume":"1874 ","pages":"Article 150156"},"PeriodicalIF":2.6,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145932091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}