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CNS Neuroscience & Therapeutics

Published by Wiley

Online ISSN: 1755-5949

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Print ISSN: 1755-5930

Disciplines: Neuroscience

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Mechanism of action of ASOs on target RNAs. In the upper panel of the figure is schematically represented the flow of the genetic information leading to gene expression and protein synthesis. DNA can be transcribed in different types of RNA, here noncoding, and protein‐coding RNAs are represented. Noncoding RNAs play crucial roles in the regulation of gene expression through specific interactions and mechanisms. ASO may be applied to target specific RNAs thereby modulating gene or allele‐specific expression, by splicing modulation; masking of specific mRNA sequences to affect translation; targeting RNA for degradation. Created with biorender.com.
Schematic diagram on the selection of papers for the body of the review.
Antisense oligonucleotides as a precision therapy for developmental and epileptic encephalopathies

November 2024

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54 Reads

Paloma García Quilón

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Serena Cappato

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Aims and scope


CNS Neuroscience & Therapeutics, part of Wiley's Influence Series, is an open access journal publishing research related to the central nervous system, clinical pharmacology, drug development and novel methodologies for drug evaluation. We focus on neurological and psychiatric diseases such as stroke, Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, epilepsy, and drug abuse.

Recent articles


CCN1 Promotes Mesenchymal Phenotype Transition Through Activating NF‐κB Signaling Pathway Regulated by S100A8 in Glioma Stem Cells
  • Article
  • Full-text available

December 2024

Xing Guo

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Shuhua Guo

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Feng Tian

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Shuo Xu

Background The presence of glioma stem cells (GSCs) and the occurrence of mesenchymal phenotype transition contribute to the miserable prognosis of glioblastoma (GBM). Cellular communication network factor 1 (CCN1) is upregulated within various malignancies and associated with cancer development and progression, while the implications of CCN1 in the phenotype transition and tumorigenicity of GSCs remain unclear. Methods Data for bioinformatic analysis were obtained from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. A range of primary GBM and GSC cell models were then used to demonstrate the regulatory role of CCN1 via the phenotype validation, tumor sphere formation assays, extreme limiting dilution assays (ELDA), and transwell assays. To screen out the downstream signaling pathway, we employed high‐throughput RNA‐seq. Intracranial xenograft GSC mouse models were used to investigate the role of CCN1 in vivo. Results Among the CCN family members, CCN1 was highly expressed in MES‐GBM/GSCs and was correlated with a poor prognosis. Both in vitro and in vivo assays indicated that knockdown of CCN1 in MES‐GSCs reduced the tumor stemness, proliferation, invasion, and tumorigenicity, whereas CCN1 overexpression in PN‐GSCs exhibited the opposite effects. Mechanistically, CCN1 triggered the FAK/STAT3 signaling in autocrine and paracrine manners to upregulate the expression of S100A8. Knockdown of S100A8 inactivated NF‐κB/p65 pathway and significantly suppressed the tumorigenesis of MES‐GSCs. Conclusion Our findings reveal that CCN1 may be an important factor in the enhanced invasiveness and MES phenotype transition of GSCs and highlight the potential to target CCN1 for treating GBM.


Pleiotrophin Overexpression Reduces Adolescent Ethanol Consumption and Modulates Ethanol‐Induced Glial Responses and Changes in the Perineuronal Nets in the Mouse Hippocampus

December 2024

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12 Reads

Aims To investigate whether pleiotrophin (PTN) overexpression influences ethanol consumption during adolescence and its effects on glial responses, neurogenesis, and perineuronal nets (PNNs) in the mouse hippocampus. Methods Male and female adolescent transgenic mice with elevated PTN levels (Ptn‐Tg) and controls underwent an intermittent access to ethanol (IAE) 2‐bottle choice protocol. Ethanol consumption, PTN levels, neurogenesis, and glial responses were measured in the hippocampus. Immunohistochemistry was used to assess changes in new neurons, microglial and astrocyte populations, and PNNs. Results Ptn‐Tg mice consumed significantly less ethanol compared to controls, irrespective of sex. Chronic alcohol exposure reduced PTN levels in the hippocampus. PTN overexpression decreased the number of new neurons in the dentate gyrus (DG) and prevented ethanol‐induced microglial activation. Ptn‐Tg mice had significantly more astrocytes and fewer PNNs, with a higher percentage of parvalbumin (PV) positive cells surrounded by PNNs under basal conditions. However, ethanol drastically reduced the number of PV+ cells in the DG of Ptn‐Tg mice, despite the presence of PNNs. Conclusion PTN overexpression reduces adolescent ethanol consumption and influences ethanol‐induced effects on hippocampal neurogenesis, glial responses, and PNN remodeling. These findings underscore the importance of PTN in modulating alcohol‐induced neurotoxicity.


A Novel Compound Ligusticum Cycloprolactam Alleviates Neuroinflammation After Ischemic Stroke via the FPR1/NLRP3 Signaling Axis

December 2024

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1 Read

Background Microglia/macrophages, as pivotal immune cells in the central nervous system (CNS), play a critical role in neuroinflammation associated with ischemic brain injury. Targeting their activation through pharmacological interventions represents a promising strategy to alleviate neurological deficits, thereby harboring significant implications for the prevention and treatment of ischemic stroke. Ligusticum cycloprolactam (LIGc), a novel monomeric derivative of traditional Chinese medicine, has shown potential as a therapeutic agent; however, its specific role in cerebral ischemic injury remains unclear. Methods In vitro experiments utilized lipopolysaccharide (LPS)‐induced inflammation models of RAW264.7 cells and primary mouse microglia. In vivo studies employed LPS‐induced neuroinflammation models in mice and a transient middle cerebral artery occlusion (tMCAO) mouse model to evaluate the impact of LIGc on neuroinflammation and microglia/macrophage phenotypic alterations. Further elucidation of the molecular mechanisms underlying these effects was achieved through RNA‐Seq analyses. Results LIGc exhibited the capacity to attenuate LPS‐induced production of pro‐inflammatory markers in macrophages and microglia, facilitating their transition to an anti‐inflammatory phenotype. In models of LPS‐induced neuroinflammation and tMCAO, LIGc ameliorated pathological behaviors and neurological deficits while mitigating brain inflammation. RNA‐seq analyses revealed formyl peptide receptor 1 (FPR1) as a critical mediator of LIGc's effects. Specifically, FPR1 enhances the pro‐inflammatory phenotype of microglia/macrophages and inhibits their anti‐inflammatory response by upregulating NLR family pyrin domain protein 3 (NLRP3) inflammasomes, thus aggravating inflammatory processes. Conversely, LIGc exerts anti‐inflammatory effects by downregulating the FPR1/NLRP3 signaling axis. Furthermore, FPR1 overexpression or NLRP3 agonists reversed the effects of LIGc observed in this study. Conclusion Our findings suggest that LIGc holds promise in improving ischemic brain injury and neuroinflammation through modulation of microglia/macrophage polarization. Mechanistically, LIGc attenuates the pro‐inflammatory phenotype and promotes the anti‐inflammatory phenotype by targeting the FPR1/NLRP3 signaling pathway, ultimately reducing inflammatory responses and mitigating neurological damage.


Synthesis and release of BDNF. Neurons can release mature BDNF, which is formed as a major nutritional signal or the neuroregulatory precursor pro‐BDNF, through transcription, translation, folding, cleavage, and packaging from presynaptic terminals. BDNF is first synthesized in a precursor form called pre‐pro‐BDNF, which is rapidly cleaved to form the precursor protein (pro‐BDNF). In intracellular pathways, the proBDNF precursor sequence is produced in the endoplasmic reticulum and transported to the Golgi apparatus. During intracellular cleavage, the pro‐region sequence is removed, leading to the formation of the immature neurotrophin precursor subtype (proBDNF) and the mature subtype of BDNF (m‐BDNF). The intracellular cleavage that forms m‐BDNF also occurs in intracellular vesicles and is transported to the axon terminal, from where it is subsequently released into the extracellular space through the presynaptic membrane.
TrkB receptor signaling. A: Signal pathways related to the nervous system. BDNF and its receptor TrkB are widely distributed in multiple regions of the human brain. TrkB is a receptor tyrosine kinase. BDNF activates TrkB, exerting neuroprotective effects by inducing neurogenesis and synaptic plasticity. BDNF can bind to TrkB receptors and enhance synaptic plasticity while promoting neuronal protection by activating the MAPK/ERK, PI3K‐Akt, and PLC‐γ‐Ca²⁺ signaling pathways. The PI3K/Akt pathway regulates several proteins essential for neuronal survival. For example, the phosphorylation of Akt can inhibit the pro‐apoptotic function of the protein BAD, thereby exerting a protective effect on neurons. Simultaneously, the MAPK/ERK pathway can promote neuronal differentiation and survival by inhibiting the pro‐apoptotic protein BAD and activating the transcription factor CREB (cAMP response element‐binding protein, a key stimulus‐induced transcription factor). As for the PLC‐γ‐Ca²⁺ pathway, studies have shown that phospholipase C (PLC) associated with activated TrkB (via tyrosine 816 phosphorylation) may elevate intracellular Ca²⁺ levels and activate the calcium/calmodulin kinase pathway. This activation, in turn, activates CREB, promoting neuronal survival. B: Signal pathways related to cancer. Receptor tyrosine kinases (RTKs) are considered a class of receptors that play a crucial role in cancer progression. RTKs regulate various downstream signaling pathways, such as MAPK, PI3K/Akt, and PLC‐γ. The activation of these pathways can promote oncogenic processes, including cancer cell growth, proliferation, survival, migration, and epithelial‐mesenchymal transition (EMT).
Involvement of BDNF–TrkB in mediating cancer‐promoting pathways. The phospholipase C‐γ (PLC‐γ) pathway activates inositol trisphosphate (IP3) receptors, promoting the release of intracellular Ca²⁺. Elevated intracellular calcium levels increase CaMK activity, leading to increased synaptic plasticity in neurons. Furthermore, PLC‐γ allows for the generation of diacylglycerol (DAG). Calcium release and DAG formation indirectly regulate a myriad of cellular activities through the PI3K and MAPK pathways and the direct activation of protein kinase C (PKC). Additionally, TrkB receptor phosphorylation of PLC‐γ drives another pathway in the regulation of transcription factors such as cAMP response element‐binding protein (CREB). This axis promotes vascular endothelial VEGF expression and angiogenesis.
Impact and Mechanisms of Action of BDNF on Neurological Disorders, Cancer, and Cardiovascular Diseases

Brain‐derived neurotrophic factor (BDNF), which is primarily expressed in the brain and nervous tissues, is the most abundant neurotrophic factor in the adult brain. BDNF serves not only as a major neurotrophic signaling agent in the human body but also as a crucial neuromodulator. Widely distributed throughout the central nervous system (CNS), both BDNF and its receptors play a significant role in promoting neuronal survival and growth, thereby exerting neuroprotective effects. It is further considered as a guiding medium for the functionality and structural plasticity of the CNS. Increasingly, research has indicated the critical importance of BDNF in understanding human diseases. Activation of intracellular signaling pathways such as the mitogen‐activated protein kinase pathway, phosphatidylinositol 3‐kinase/protein kinase B/mammalian target of rapamycin pathway, and phospholipase C γ pathway by BDNF can all potentially enhance the growth, survival, proliferation, and migration of cancer cells, influencing cancer development. The loss of BDNF and its receptor, tropomyosin receptor kinase B, in signaling pathways is also associated with increased susceptibility to brain and heart diseases. Additionally, reduced BDNF levels in both the central and peripheral systems have been closely linked to various neurogenic diseases, including neuropathic pain and psychiatric disorders. As such, this review summarizes and analyzes the impact of BDNF on neurogenic diseases, cancer, and cardiovascular diseases. This study thereby aimed to elucidate its effects on these diseases to provide new insights and approaches for their treatment.


Study flowchart.
Intraoperative Hypotension and Postoperative Newly Developed Cerebral Infarction in Patients With Aneurysmal Subarachnoid Hemorrhage: A Retrospective Cohort Study

December 2024

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1 Read

Aims To investigate the association between intraoperative hypotension and newly developed cerebral infarction in patients with aneurysmal subarachnoid hemorrhage (aSAH) undergoing aneurysm clipping or coiling. Methods The patients who had emergent clipping/coiling procedures for aSAH under general anesthesia were included. The major exposure was mean arterial pressure (MAP) below different absolute or relative thresholds characterized by area under curve (AUC), duration, and time‐weighted average (TWA) value. The outcome was newly developed cerebral infarction. The associations between MAP and newly developed cerebral infarction were adjusted by other risk factors. Odds ratio and 95% confidence interval were used to present the statistical difference. Results A total of 1205 patients were included in the analysis. Of these, 260 patients (21.6%) developed new cerebral infarctions assessed by computed tomography. Patients with newly developed cerebral infarction had higher incidence of modified Fisher Scale (mFS) score 3 to 4 (80.0 vs. 69.1%, p < 0.01) and longer duration of anesthesia (4.3 vs. 3.9 h, p < 0.01). In the multivariate model, the AUC‐MAP (adjusted odds ratio: 1.00, 95% CI: 1.000 to 1.000, p = 0.02) and the TWA‐MAP (adjusted odds ratio: 1.01, 95% CI: 1.001 to 1.024, p = 0.04) of 20% decrease from baseline were closely associated with the newly developed cerebral infarction. Conclusions Mean arterial pressure decreased 20% from baseline value were independently associated with postoperative newly developed cerebral infarction in patients with aSAH.


Study flowchart.
Kaplan–Meier curves of cerebrovascular events between patients with MMD and MMS for all cerebrovascular events (A), ischemic strokes (B), and hemorrhagic strokes (C). Kaplan–Meier curves of overall cerebrovascular events between patients treated with and without EDAS for all patients (D), patients with MMD (E), and patients with MMS (F). EDAS, encephaloduroarteriosynangiosis; MMD, moyamoya disease; MMS, moyamoya syndrome.
Subgroup analysis for comparison of prediction of cerebrovascular events between MMD versus MMS cohorts after matching. MMD, moyamoya disease; MMS, moyamoya syndrome; PCI, posterior circulation involvement; Pre‐mRS, pre‐admission modified Rankin Scale.
Comparing Outcomes of Moyamoya Disease and Moyamoya Syndrome in a Real‐World Scenario: A Cohort Study

December 2024

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5 Reads

Background Moyamoya disease (MMD) and moyamoya syndrome (MMS) are rare cerebrovascular conditions with unclear distinctions in clinical presentation and prognosis. Aim This study assessed potential differences between MMD and MMS patients using real‐world data on clinical manifestations, surgical outcomes, and stroke risk factors. Methods This multicenter, retrospective cohort study examined patients with MMD or MMS treated at three tertiary academic hospitals in China, with a mean follow‐up of 11.2 ± 3.1 years. Clinical differences were compared between MMD and MMS, and postoperative cerebrovascular events were compared between patients who underwent surgery and those with conservative management. Primary outcomes were postoperative ischemic and hemorrhagic strokes. Risk factors were evaluated via multivariate Cox regression analysis. Results Of the 2565 patients, 2349 had MMD and 216 had MMS. After 1:1 propensity‐score matching, no significant differences were observed between these two cohorts. Surgical patients had fewer cerebrovascular events than those who received conservative treatment (HR, 0.487; 95% CI, 0.334–0.711; p < 0.001). Preadmission modified Rankin scale scores > 2 (HR, 3.139; 95% CI, 1.254–7.857; p = 0.015) and periprocedural complications (HR, 8.666; 95% CI, 3.476–21.604; p < 0.001) were independent stroke risk factors in patients with MMD. Periprocedural complications (HR, 31.807; 95% CI, 10.916–92.684; p < 0.001) increased stroke risk in patients with MMS. Conclusions This real‐world study revealed substantial clinical overlap between MMD and MMS. Both groups derived significant benefits from surgical revascularization, suggesting distinction may not be necessary to guide surgical management decisions. Optimizing preoperative status and preventing periprocedural complications may improve outcomes in these rare cerebrovascular conditions. Trial Registration This study has been registered in the Chinese Clinical trial registry (registration number: ChiCTR2200064160)


The synthesis and release of BDNF: Transcription of the BDNF gene to generate BDNF mRNA in the nucleus triggers translation and folding of proBDNF from pre‐proBDNF in the rough endoplasmic reticulum (ER). In the Golgi apparatus, proBDNF is cleaved directly by furin to form BDNF, which is released by two regulated and constitutive pathways from the intracellular to the extracellular space.
BDNF signaling: ProBDNF via activation of SORT1 induces the activation of MAPK (mitogen‐activated protein kinase)/JNK and CASP3 resulting in neuronal apoptosis. BDNF via activation of NTRK2‐FL, NTRK2‐T1, and NTRK2‐T2 induces the expression of CAMK (calcium/calmodulin‐dependent protein kinase), CREB (cAMP‐responsive element‐binding protein), InsP3 (inositol trisphosphate), PLCG (phospholipase C gamma), PRKC (protein kinase C), RHOA (ras homolog family member A), and ROCK (Rho‐associated coiled‐coil containing protein kinase) leading to inflammation and regulation of cell survival.
Pathophysiology of MS: Activated plasma cells producing antibodies and activated complement attack the myelin sheath of axons, mainly the oligodendrocytes. Antigen‐presenting cells present genes of oligodendrocytes to the T cells which also interact with microglia and induce the release of IFNG (interferon gamma), IL23A (interleukin 23 subunit alpha), ITGA4 (integrin subunit alpha 4), and SPP1/osteopontin (secreted phosphoprotein 1).
BDNF activators in MS: BDNF activators improve BDNF signaling, which inhibits MS neuropathology and associated neurodegeneration and neuroinflammation.
The Compelling Role of Brain‐Derived Neurotrophic Factor Signaling in Multiple Sclerosis: Role of BDNF Activators

Brain‐derived neurotrophic factor (BDNF) is a neurotrophin, acting as a neurotrophic signal and neuromodulator in the central nervous system (CNS). BDNF is synthesized from its precursor proBDNF within the CNS and peripheral tissues. Through activation of NTRK2/TRKB (neurotrophic receptor tyrosine kinase 2), BDNF promotes neuronal survival, synaptic plasticity, and neuronal growth, whereas it inhibits microglial activation and the release of pro‐inflammatory cytokines. BDNF is dysregulated in different neurodegenerative diseases and depressions. However, there is a major controversy concerning BDNF levels in the different stages of multiple sclerosis (MS). Therefore, this review discusses the potential role of BDNF signaling in stages of MS, and how BDNF modulators affect the pathogenesis and outcomes of this disease.


HFD aggravated neuronal necroptosis and exacerbated neurological impairments following MCAO. (A) Volcano plot illustrated cortical DEGs between HFD‐ and ND‐treated mice 3 days following MCAO. n = 3. (B) Bubble plot showed KEGG enrichment results using DEGs between HFD‐ and ND‐treated mice 3 days following MCAO. (C) GSEA illustrated that necroptosis pathway was activated in the cortex tissue of HFD‐treated mice 3 days following MCAO. (D, E) Representative image of neuron necroptosis in ND‐ and HFD‐treated mice 3 days after MCAO. Quantification of TUNEL⁺ NeuN⁺ (D) and phosphorylated RIPK3⁺ (pRIPK3⁺) NeuN⁺ (E) neuron percentage in the peri‐infarct region. n = 10, One‐way ANOVA with Tukey's multiple comparison test. (F, G) Representative immunoblots for kinases mediating necroptosis in ND‐ and HFD‐treated mice 3 days following MCAO. Quantitative analysis of pRIPK3 (F) and phosphorylated MLKL (pMLKL) (G) relative level in the ischemic cortex. n = 10, One‐way ANOVA with Tukey's multiple comparison test. (H) Representative images and quantification of IgG and MAP2 double staining in the brain of ND‐ and HFD‐treated mice 3 days following MCAO. n = 10, unpaired Student's t‐test. (I, K) Post‐stroke neurological assessment, including modified Garcia Score (I), adhesive removal test (J) and forelimb foot‐faults index (K), in ND‐ and HFD‐treated mice through 28 days following MCAO. n = 8–10, Two‐way ANOVA with post hoc Bonferroni test, *p < 0.05, **p < 0.01, ****p < 0.0001 HFD MCAO versus ND MCAO. All data are presented as means ± SD. ANOVA, analysis of variance; DEGs, Differentially expressing genes; GSEA, gene set enrichment analysis; HFD, high‐fat diet; IgG, immunoglobulin G; KEGG, Kyoto Encyclopedia of Genes and Genomes; ND, normal diet; MAP2, microtube‐associated protein 2; MCAO, middle cerebral artery occlusion; SD, standard deviation; TdT‐mediated dUTP nick‐end labeling (TUNEL).
HFD upregulated CflarR splicing isoform, an upstream pro‐necroptotic regulator, in neurons following MCAO. (A) GSEA illustrated that spliceosome pathway was activated in the cortex tissue of HFD‐treated mice 3 days following MCAO. (B) Volcano plot illustrated top genes in spliceosome gene set between HFD‐ and ND‐treated mice 3 days following MCAO. (C, D) Relative mRNA expression of CflarL (B) and CflarR (C) examined by qPCR in the cortex of ND‐ and HFD‐treated mice 3 days following MCAO. n = 6, One‐way ANOVA with Tukey's multiple comparison test. (E) Representative images of cFLIP localized in neurons of ND‐ and HFD‐treated mice 3 days following MCAO. Quantification of cFLIP⁺ NeuN⁺ neuron percentage in the peri‐infarct region. n = 10, One‐way ANOVA with Tukey's multiple comparison test. (F) Representative immunoblot for cortical cFLIPL and cFLIPR level of ND‐ and HFD‐treated mice 3 days following MCAO. Quantitative analysis of cFLIPL and cFLIPR relative level in ischemic cortex. n = 10, One‐way ANOVA with Tukey's multiple comparison test. All data are presented as means ± SD.
Neuronal Mef2c was upregulated in HFD‐treated stroke mice. (A) Venn plot illustrating the intersection of transcription factors (TFs) which were predicted to be involved in Cflar transcription using five public TF databases. (B) Relative mRNA expression of Mef2c examined by qPCR in the cortex of ND and HFD‐treated mice 3 days following MCAO. n = 9, One‐way ANOVA with Tukey's multiple comparison test. (C) Representative images of Mef2c localized in neurons of ND‐ and HFD‐treated mice 3 days following MCAO. Quantification of Mef2c⁺ NeuN⁺ neuron percentage in the penumbra area. n = 10, One‐way ANOVA with Tukey's multiple comparison test. (D) Representative immunoblot for cortical Mef2c level of ND‐ and HFD‐treated mice 3 days following MCAO. Quantitative analysis of Mef2c relative level in ischemic cortex. n = 10, One‐way ANOVA with Tukey's multiple comparison test. All data are presented as means ± SD.
Neuronal depletion of Mef2c (Emx1CreMef2cfl/fl) suppressed HFD‐induced CflarR splicing following MCAO. (A) Illustration of generating Emx1CreMef2cfl/fl conditional knockout mice. (B) Representative Basescope images of CflarL and CflarR mRNA localized in ischemic neurons of Mef2cfl/fl and Emx1CreMef2cfl/fl mice which were both treated with HFD and sacrificed 3 days after MCAO. Arrows pointing at CflarR signals. (C, D) Relative mRNA expression of CflarL (C) and CflarR (D) examined by qPCR in the cortex of Mef2cfl/fl and Emx1CreMef2cfl/fl mice (both HFD‐treated) 3 days following MCAO. n = 10, One‐way ANOVA with Tukey's multiple comparison test. (E) Representative images of cFLIP localized in neurons of Mef2cfl/fl and Emx1CreMef2cfl/fl mice (both HFD‐treated) 3 days following MCAO. Quantification of cFLIP⁺ NeuN⁺ neuron percentage in the peri‐infarct region. n = 10, One‐way ANOVA with Tukey's multiple comparison test. (F) Representative immunoblot for cortical cFLIPL and cFLIPR level of Mef2cfl/fl and Emx1CreMef2cfl/fl mice (both HFD‐treated) 3 days following MCAO. Quantitative analysis of cFLIPL and cFLIPR relative level in ischemic cortex. n = 10, One‐way ANOVA with Tukey's multiple comparison test. All data are presented as means ± SD.
Emx1CreMef2cfl/fl exhibited mitigated neuronal necroptosis and improved long‐term neurological outcomes following MCAO in the context of HFD. (A, B) Representative images of neuron necroptosis in Mef2cfl/fl and Emx1CreMef2cfl/fl mice (both HFD‐treated) 3 days following MCAO. Quantification of TUNEL⁺ NeuN⁺ (A) and pRIPK3⁺ NeuN⁺ (B) neuron percentage in the peri‐infarct region. n = 10, One‐way ANOVA with Tukey's multiple comparison test. (C, D) Representative immunoblots for necroptotic kinases level of Mef2cfl/fl and Emx1CreMef2cfl/fl mice (both HFD‐treated) 3 days following MCAO. Quantitative analysis of pRIPK3 (C) and pMLKL (D) relative level in ischemic cortex. n = 10, One‐way ANOVA with Tukey's multiple comparison test. (E) Representative images and quantification of IgG and MAP2 double staining in the brain of Mef2cfl/fl and Emx1CreMef2cfl/fl mice 3 days following MCAO (both HFD‐treated). n = 10, unpaired Student's t‐test. (F, H) Post‐stroke neurological assessment, including modified Garcia Score (F), adhesive removal test (G) and forelimb foot‐faults index (H), in Mef2cfl/fl and Emx1CreMef2cfl/fl mice (both HFD‐treated) through 28 days following MCAO. n = 8, Two‐way ANOVA with post hoc Bonferroni test, *p < 0.05, **p < 0.01 HFD MCAO versus ND MCAO. All data are presented as means ± SD.
Mef2c Exacerbates Neuron Necroptosis via Modulating Alternative Splicing of Cflar in Ischemic Stroke With Hyperlipidemia

December 2024

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11 Reads

Aim Hyperlipidemia is a common comorbidity of stroke patients, elucidating the mechanism that underlies the exacerbated ischemic brain injury after stroke with hyperlipidemia is emerging as a significant clinical problem due to the growing proportion of hyperlipidemic stroke patients. Methods Mice were fed a high‐fat diet for 12 weeks to induce hyperlipidemia. Transient middle cerebral artery occlusion was induced as a mouse model of ischemic stroke. Emx1Cre mice were crossed with Mef2cfl/fl mice to specifically deplete Mef2c in neurons. Results We reported that hyperlipidemia significantly aggravated neuronal necroptosis and exacerbated long‐term neurological deficits following ischemic stroke in mice. Mechanistically, Cflar, an upstream necroptotic regulator, was alternatively spliced into pro‐necroptotic isoform (CflarR) in ischemic neurons of hyperlipidemic mice. Neuronal Mef2c was a transcription factor modulating Cflar splicing and upregulated by hyperlipidemia following stroke. Neuronal specific Mef2c depletion reduced cerebral level of CflarR and cFLIPR (translated by CflarR), while mitigated neuron necroptosis and neurological deficits following stroke in hyperlipidemic mice. Conclusions Our study highlights the pathogenic role of CflarR splicing mediated by neuronal Mef2c, which aggravates neuron necroptosis following stroke with comorbid hyperlipidemia and proposes CflarR splicing as a potential therapeutic target for hyperlipidemic stroke patients.


Flowchart of patient selection. AIS, acute ischemic stroke; EVT, endovascular treatment; mRS, modified Rankin Scale; TyG index, triglyceride‐glucose index.
Proportion distribution of different mRS scores at 90 days among groups categorized by the TyG index. There was a statistically significant difference among three groups in the overall distribution of mRS scores (p < 0.05). mRS, modified Rankin Scale; TyG index, triglyceride‐glucose index.
Clinical outcomses measures by tertiles of TyG index. (A) Outcomes measures for poor outcome at 90 days by tertiles of TyG index. (B) Outcomes measures for END by tertiles of TyG index. (C) Outcomes measures for sICH by tertiles of TyG index. (D) Outcomes measures for mortality at 90 days by tertiles of TyG index. *Statistical significance (p < 0.05). Adjusted for significant covariates in Tables S1–S4. END, early neurological deterioration; sICH, symptomatic intracranial hemorrhage; TyG index, triglyceride‐glucose index.
Relationship between the TyG index and clinical outcomes. (A) The linear relationship between the TyG index and poor outcome at 90 days. (B) The linear relationship between the TyG index and END. (C) The linear relationship between the TyG index and sICH. (D) The nonlinear relationship between the TyG index and mortality at 90 days. p < 0.05 is considered statistically significant. END, early neurological deterioration; sICH, symptomatic intracranial hemorrhage; TyG index, triglyceride‐glucose index.
ROC curves for the value of TyG index to predict poor outcome at 90 days. The traditional risk factors model (medical history of prestroke, NIHSS on admission, ASPECTS, mTICI, END, and sICH) was outperformed by the conventional risk factors + TyG index model in predicting poor outcome at 90 days. p < 0.05 is considered statistically significant. ASPECTS, Alberta Stroke Program Early Computed Tomography Score; AUC, area under the curve; ROC, receiver operating characteristic; END, early neurological deterioration; mTICI, modified Thrombolysis in Cerebral Infarction; NIHSS, National Institutes of Health Stroke Scale; sICH, symptomatic intracranial hemorrhage; TyG index, triglyceride‐glucose index.
Influence of TyG Index on Large Vascular Occlusive Stroke Following Endovascular Treatment

Aims This study aimed to investigate the impact of the triglyceride‐glucose index (TyG index) on clinical consequences in individuals with large vascular occlusion (LVO)‐induced acute ischemic stroke (AIS) following endovascular treatment (EVT). Methods We conducted a single‐center retrospective cohort study, including AIS with LVO who underwent EVT. Patients were categorized into TyG index groups, calculated as “(fasting triglyceride [mg/dL] × fasting blood glucose [mg/dL]/2).” Clinical outcomes were assessed, including poor outcome (modified Rankin Scale [mRS] > 2 [3–6]) at 90 days, early neurological deterioration (END), symptomatic intracranial hemorrhage (sICH), and 90‐day mortality after EVT. Logistic regression and restricted cubic splines (RCS) were used to examine the relationship between the TyG index and clinical outcomes. Receiver operating characteristic (ROC) curve was constructed to evaluate the prognostic capacity of the TyG index. Results A total of 424 patients were included. Higher TyG levels were associated with worse functional outcome at 90 days (per unit: p = 0.006), sICH (per unit: p = 0.002, T3 versus T1: p = 0.004), and 90‐day mortality (T2 versus T1: p = 0.011, T3 versus T1: p = 0.029) in logistic regression. A RCS model revealed a linear association between the TyG index and poor outcome at 90 days, sICH, and 90‐day mortality (p for nonlinearity > 0.05). In ROC curve analysis, the traditional risk factors model (area under the curve [AUC]: 0.824, 95% CI: 0.784–0.859) was outperformed by the conventional risk factors + TyG index model (AUC: 0.845, 95% CI: 0.807–0.878) in predicting poor outcome (p = 0.021). Conclusion A higher TyG index is associated with worse clinical outcomes in LVO‐induced AIS patients after EVT. Additionally, the TyG index enhances risk prediction of traditional risk factors for poor outcome.


Applied methodological pipeline of the data analysis. This pipeline consists of two parts, the identification of CM‐targeting group clusters (A‐D) and the use of these clusters to localize individual targets for TMS intervention (a‐g). Here, we show an example of CM targeting on the left (c), which is the same application as that of right CM targeting. CCBD, Center of Cognition and Brain Disorders; CM‐FC, centromedian functional connectivity; EC, eyes closed; EO, eyes open; HCP, Human Connectome Project; TCDQ, TMS Center of Deqing Hospital.
Left CM‐FC and right CM‐FC maps for each session. Sagittal (X = 0), coronal (Y = −14), and axial (Z = 62) brain maps showing areas of significant positive FC strength (p < 0.001, uncorrected for HCP and p < 0.01, uncorrected for CCBD and TCDQ) calculated separately for the left (A) and right (B) CM in each session from the three MR scanners. The red‐to‐yellow scale represents the statistics (t) of the voxelwise analyses testing whether the average connectivity with the left CM (A) and right CM (B) seed regions was statistically significant. The X, Y, and Z coordinates indicate the sagittal, coronal, and axial voxel positions (mm), respectively, in the Montreal Neurological Institute Ch2better template space. CCBD, Center of Cognition and Brain Disorders; CM‐FC, Centromedian functional connectivity; EC, Eyes closed; EO, Eyes open; HCP, Human Connectome Project; TCDQ, TMS Center of Deqing Hospital.
Group CM‐FC pattern and two group clusters. A 2‐cm cortical brain mask was applied to determine the TMS available distance. Spatial connectivity maps for the left CM and right CM in the Ch2 template. The crosshair was located in the voxel within the cluster with a larger overlapping index and more than 30 voxels in each hemisphere. The color bar indicates an overlap index between 0 and 10. The group clusters of the left and right CMs, the left primary sensorimotor cortex, and the right superior frontal gyrus are presented in the three axial panels in the MNI space (thickness = 4 mm).
A sample of watershed segmentation in the left CM‐FC. (A) The spatial relationship of the left CM‐based group cluster (left PSMC) and the individual cluster. (B) The crosshair was the peak with the largest r value (r = 0.237) in the individual cluster (MNI: −21, −27, 63).
Utilizing Centromedian Thalamus Connectivity to Personalize Noninvasive Neuromodulation Targets

December 2024

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10 Reads

Introduction The centromedian nucleus (CM) of the thalamus is essential for arousal, attention, sensory processing, and motor control. Neuromodulation targeting CM dysfunction has shown efficacy in various neurological disorders. However, its individualized precise transcranial magnetic stimulation (TMS) remains unreported. Using resting‐state functional MRI, we mapped CM‐based functional connectivity (CM‐FC) to develop a personalized TMS scheme for neurological conditions. Methods We first analyzed the CM‐FC patterns of healthy subjects via 10 scanning sessions in three MRI scanners spanning two subject groups: one from the Human Connectome Project (n = 20, four sessions) dataset and the other from Hangzhou Normal University (n = 20, three sessions of 3 T MRI and three sessions of 1.5 T MRI). Pearson's correlation was used for CM‐FC evaluation. Then, we proposed an overlapping index ranging from 1 to 10, and group‐level clusters with the highest overlapping index located 4 cm beneath the scalp were identified. In the individual CM‐FC map, watershed image segmentation was used to obtain an individual cluster. The peak voxel with the highest FC value within the individual cluster was defined as a potential individualized target for future TMS. Results The spatial FC patterns were remarkably similar between the left and right CMs. CMs have widespread positive connectivity with cortical areas, including the sensorimotor cortex, supplementary motor area, middle frontal cortex, medial temporal cortex, and middle cingulate. Among the group‐level FC patterns of the left and right CMs, only the left CM had a group cluster in the left primary sensorimotor cortex (PSMC, cluster size = 51) with an overlapping index of 10, that is, 10 sessions showed significant CM‐FC. Conclusions The left PSMC exhibited reproducible FC with the left CM. The individual peak FC location in the left PSMC could be used as a TMS target for indirect modulation of CM activity and aid in the treatment of CM‐related neurological disorders.


The Circadian Clock Gene Bmal1 Regulates Microglial Pyroptosis After Spinal Cord Injury via NF‐κB/MMP9

December 2024

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3 Reads

Background The treatment of spinal cord injury (SCI) is usually ineffective, because neuroinflammatory secondary injury is an important cause of the continuous development of spinal cord injury, and microglial pyroptosis is an important step of neuroinflammation. Recently, Bmal1, a core component of circadian clock genes (CCGs), has been shown to play a regulatory role in various tissues and cells. However, it is still unclear whether Bmal1 regulates microglial pyroptosis after SCI. Methods In this study, we established an in vivo mouse model of SCI using Bmal1 knockout (KO) mice and wild‐type (WT) mice, and lipopolysaccharide (LPS)‐induced pyroptosis in BV2 cells as an in vitro model. A series of molecular and histological methods were used to detect the level of pyroptosis and explore the regulatory mechanism in vivo and in vitro respectively. Results Both in vitro and in vivo results showed that Bmal1 inhibited NLRP3 inflammasome activation and microglial pyroptosis after SCI. Further analysis showed that Bmal1 inhibited pyroptosis‐related proteins (NLRP3, Caspase‐1, ASC, GSDMD‐N) and reduced the release of IL‐18 and IL‐1β by inhibiting the NF‐κB /MMP9 pathway. It was important that NF‐κB was identified as a transcription factor that promotes the expression of MMP9, which in turn regulates microglial pyroptosis after SCI. Conclusions Our study initially identified that Bmal1 regulates the NF‐κB /MMP9 pathway to reduce microglial pyroptosis and thereby reduce secondary spinal cord injury, providing a new promising therapeutic target for SCI.


Ginsenoside Rg1: A Neuroprotective Natural Dammarane‐Type Triterpenoid Saponin With Anti‐Depressive Properties

Background Depression, a widespread mental disorder, presents significant risks to both physical and mental health due to its high rates of recurrence and suicide. Currently, single‐target antidepressants typically alleviate depressive symptoms or delay the progression of depression rather than cure it. Ginsenoside Rg1 is one of the main ginsenosides found in Panax ginseng roots. It improves depressive symptoms through various mechanisms, suggesting its potential as a treatment for depression. Materials and Methods We evaluated preclinical studies to comprehensively discuss the antidepressant mechanism of ginsenoside Rg1 and review its toxicity and medicinal value. Additionally, pharmacological network and molecular docking analyses were performed to further validate the antidepressant effects of ginsenoside Rg1. Results The antidepressant mechanism of ginsenoside Rg1 may involve various pharmacological mechanisms and pathways, such as inhibiting neuroinflammation and over‐activation of microglia, preserving nerve synapse structure, promoting neurogenesis, regulating monoamine neurotransmitter levels, inhibiting hyperfunction of the hypothalamic‐pituitary‐adrenal axis, and combatting antioxidative stress. Moreover, ginsenoside Rg1 preserves astrocyte gap junction function by regulating connexin43 protein biosynthesis and degradation, contributing to its antidepressant effect. Pharmacological network and molecular docking studies identified five targets (AKT1, STAT3, EGFR, PPARG, and HSP90AA1) as potential molecular regulatory sites of ginsenoside Rg1. Conclusions Ginsenoside Rg1 may exert its antidepressant effects via various pharmacological mechanisms. In addition, multicenter clinical case‐control and molecular targeted studies are required to confirm both the clinical efficacy of ginsenoside Rg1 and its potential direct targets.


Perioperative sleep deprivation promotes chronicity of postsurgical pain with decreased GDNF contents and increased cholinergic neuronal apoptosis and autophagy dysfunction in the basal forebrain. (A) Study design. A mouse SMIR model was established, which received 6 h of total sleep deprivation daily from 1 day prior to until 3 days after the surgery, and mechanic and heat‐evoked pain was measured until 21 days after surgery. (B, C) Perioperative sleep deprivation was found to significantly increase mechanical pain intensity (B) and prolong pain maintenance (C) in SMIR mice. (D, E) Percentage of maximal possible effect (%MPE) of groups at different time points (D) and area under the curve (AUC) of %MPE (E). (F, G) Expression of GDNF mRNA at 7 (F) and 21 (G) days after surgery. (H, I) GDNF contents, and markers of apoptosis (Caspase‐3 and cleaved Caspase‐3) and autophagy (LC3 and p62) expression across groups at 7 (H) and 21 (I) days after surgery. (J) Multiplex immunofluorescence (IF) results showing an increased staining of cleaved Caspase‐3 in ChAT‐positive cholinergic neurons. (K) Immunofluorescence showed decreased expression of GDNF in both ChAT‐positive cholinergic neurons and VGluT2‐positive glutamatergic neurons, and decreased c‐Fos expression in ChAT‐positive cholinergic neurons only. Ten mice per group were used for the behavioral tests. Biochemical experiments were performed in three independent samples. *p < 0.05; **p < 0.01; ***p < 0.001; and ****p < 0.0001, SMIR + sleep deprivation versus control. #p < 0.05; ##p < 0.01; ###p < 0.001; and ####p < 0.0001, SMIR + sleep deprivation versus SMIR. ChAT, choline acetyltransferase; SEM, standard error of the mean; SMIR, skin/muscle incision and retraction; VGluT2, vesicular glutamate transporter 2.
AAV‐GDNF promotes GDNF expression, reduces cholinergic neuronal apoptosis and autophagy dysfunction, and counteracts sleep deprivation‐induced postoperative chronic pain. (A) Study design. Mice were injected bilaterally into the lateral basal forebrain with AAV‐GDNF, vector, or saline control. A mouse SMIR model was established, which received 6 h of total sleep deprivation daily from 1 day prior to until 3 days after the surgery, and mechanic and heat‐evoked pain was measured until 21 days after surgery. (B) Immunofluorescence staining showing strong 3 × FLAG expression in the lateral basal forebrain, indicating accurate microinjection and successful overexpression. (C) Expression of GDNF mRNA at 21 days after surgery. (D) GDNF contents, 3 × FLAG Tag, and markers of apoptosis (cleaved Caspase‐3 and Caspase‐3) and autophagy (LC3 and p62) expression across groups at 21 days after surgery. (E) Immunofluorescence showing increased expression of GDNF in mice receiving AAV‐GDNF intervention. (F) Multiplex immunofluorescence showing increased GDNF expression by AAV‐GDNF in both ChAT‐positive cholinergic neurons and VGluT2‐positive glutamatergic neurons. (G) Expression of Caspase‐3 mRNA at 21 days after surgery. (H, I) AAV‐GDNF counteracts surgery plus sleep deprivation‐induced mechanical allodynia (H) and prolonged pain maintenance (I). (J, K) %MPE at different time points (J) and AUC of %MPE (K). Ten mice per group were used for the behavioral tests. Biochemical experiments were performed in three independent samples. *p < 0.05; **p < 0.01; ***p < 0.001; and ****p < 0.0001, SMIR + sleep deprivation + saline versus SMIR + sleep deprivation + AAV‐GDNF. #p < 0.05; ##p < 0.01; ###p < 0.001; and ####p < 0.0001, SMIR + sleep deprivation + vector versus SMIR + sleep deprivation + AAV‐GDNF. AAV‐GDNF, AAV2/9 carrying pAAV‐CMV‐Gdnf‐3×FLAG‐P2A‐mCherry‐WPRE; ChAT, choline acetyltransferase; VGluT2, vesicular glutamate transporter 2.
Mice with lesions of lateral basal forebrain cholinergic neurons are resistant to the pain‐enhancing effects of sleep deprivation and the pain‐alleviating effects of AAV‐GDNF therapy. (A) Study design. Mice were injected bilaterally in the lateral basal forebrain with AAV‐GDNF or mu p75‐SAP before surgery. Mechanic and heat‐evoked pain was measured until 21 days after surgery. (B) Multiplex immunofluorescence showing substantially decreased immunostaining of ChAT‐positive cholinergic neurons after mu p75‐SAP treatment, which was not rescued by AAV‐GDNF treatment. (C) Immunofluorescence showing lesion of the lateral basal forebrain (substantia innominata (SI), magnocellular preoptic nucleus (MCPO), and the horizontal diagonal band Broca (HDB)) cholinergic neurons by mu p75‐SAP. (D, E) Expression of GDNF and Caspase‐3 mRNA at 21 days after surgery. (F) 3 × FLAG Tag, and markers of apoptosis (cleaved Caspase‐3 and Caspase‐3) and autophagy (LC3 and p62) expression across groups at 21 days after surgery. (G, H) Decreased mechanical (G) and thermal (H) pain threshold in mu p75‐SAP‐treated mice, which were not affected by further sleep deprivation or AAV‐GDNF treatment. Ten mice per group for the behavioral tests were used. Western blot and RT‐qPCR experiments were performed in three independent samples. *p < 0.05; **p < 0.01; ***p < 0.001; and ****p < 0.0001, SMIR + sleep deprivation + mu p75‐SAP versus SMIR + sleep deprivation. #p < 0.05; ##p < 0.01; ###p < 0.001; and ####p < 0.0001, SMIR versus SMIR + mu p75‐SAP.
Impaired Basal Forebrain Cholinergic Neuron GDNF Signaling Contributes to Perioperative Sleep Deprivation–Induced Chronicity of Postsurgical Pain in Mice Through Regulating Cholinergic Neuronal Activity, Apoptosis, and Autophagy

December 2024

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13 Reads

Aims This study investigated the roles of lateral basal forebrain glial cell line–derived neurotrophic factor (GDNF) signaling and cholinergic neuron activity, apoptosis, and autophagy dysfunction in sleep deprivation–induced increased risk of chronic postsurgical pain (CPSP) in mice. Methods Sleep deprivation (6 h per day from −1 to 3 days postoperatively) was administered to mice receiving skin/muscle incision and retraction (SMIR) to determine whether perioperative sleep deprivation induces mechanical and thermal pain hypersensitivity, increases the risk of chronic pain, and causes changes of basal forebrain neurons activity (c‐Fos immunostaining), apoptosis (cleaved Caspase‐3 expression), autophagy (LC3 and p62 expression) and GDNF expression. Adeno‐associated virus (AAV)‐GDNF was microinjected into the basal forebrain to see whether increased GDNF expression could reverse sleep deprivation–induced changes in pain duration and cholinergic neuron apoptosis and autophagy. Cholinergic neurons were further depleted by mu p75‐SAP to examine whether the pain‐prolonging effects of sleep deprivation still exist. Results Perioperative sleep deprivation enhanced pain sensation and prolonged pain duration in SMIR mice, which was accompanied by decreased cholinergic neuron activity and GDNF expression, increased apoptosis, and autophagy dysfunction in the substantia innominata (SI), magnocellular preoptic nucleus (MCPO), and horizontal diagonal band Broca (HDB) (hereafter lateral basal forebrain). Normalizing cholinergic neuron GDNF expression by AAV‐GDNF in the lateral basal forebrain inhibited apoptosis and autophagy dysfunction and mitigated sleep deprivation–induced pain maintenance. Mice with selective lesion of lateral basal forebrain cholinergic neurons were resistant to the pain‐enhancing and prolonging effects of sleep deprivation and the pain‐alleviating effects of AAV‐GDNF therapy. Conclusions Perioperative sleep deprivation promotes chronicity of postsurgical pain possibly through decreasing basal forebrain GDNF signaling and causing cholinergic neuronal apoptosis and autophagy dysfunction.


Reprogramming of glucose metabolism for proliferation mechanism in GBM cells. Mitochondrial TSPO deficiency inhibits the mitochondrial respiratory chain, leading to hypoxia. The hypoxia environment activates HIF‐1⍺. HIF‐1⍺ activates HK2, aldolase, LDHA, GPDH, CA‐9, and CA‐12, which promote the conversion of GBM to glycolytic metabolism, and increased lactate levels favor the progression of GBM.
Mechanisms of fatty acid metabolism promoting proliferation and invasion in GBM cells. Fatty acid metabolism consists of FAS and FAO. Overexpression of EGFRvIII, FASN, and ACL promotes FAS. FAO consists of α‐oxidation and β‐oxidation, and FA undergoes α‐oxidation and enters the mitochondria for the β‐oxidation process. CPT1, CPT2, and DECR1 overexpression promotes β‐oxidation. Enhanced expression of CPT1 and CPT2 promotes invasive growth of GBM through CD47. β‐oxidation releases a large amount of energy to support GBM growth and proliferation.
Oxidative stress in GBM cells. Changes in intracellular mitochondrial redox potential lead to high levels of ROS production, and oxidative stress occurs as a result of an imbalance between intracellular ROS and antioxidant factors. High levels of ROS disrupt mitochondrial DNA(mtDNA), nuclear genome, and MMP. Overexpression of AQP8, EGFRvIII, Nox4, and eIF4E genes promotes ROS production. High levels of ROS promote the activation of FAK, Pyk2, and MMP‐9 to promote cell migration and invasion. ROS and MPST can work together to promote cell migration. ROS act as secondary messengers in the intracellular signaling cascade in the GBM cells. IDH1/2 mutations result in the conversion of α‐KG to D‐2HG triggering oxidative stress. Oxidative stress promotes cell growth and proliferation, migration and invasion, and angiogenesis. Nrf2 regulates the production of antioxidants to protect cells from damage caused by oxidative stress. Water channel proteins drain H2O2 into the tumor microenvironment to regulate the cell cycle and induce the production of nutrients and ATP by proximal stromal cells to support GBM cell proliferation.
Mitochondrial dynamics and mitophagy in GBM cells. Mitochondrial fusion‐associated proteins Mfn1, Mfn2, and OPA1‐L isoform (OPA1‐L) were expressed at reduced levels, and a reduction in CPT1 protein induced low expression of OPA1‐L, which reduced mitochondrial fusion and thus promoted cell invasion. KLF4 protein affects mitochondrial fusion and thus the cell cycle. The overexpression of DISC1, TRAP1, Rab32 protein, and HIF‐1 induces a hypoxic environment that promotes DRP1 protein‐mediated mitochondrial fission, which facilitates cell proliferation and invasion. overexpression of DPR1 and OPA1‐S isoform promotes angiogenesis. FAM72A regulates mitochondrial fusion through the Pink1/Parkin signaling pathway. Pink1/Parkin signaling pathway to regulate mitophagy, thereby promoting glioma progression. Targeting of DNM1L at the BCL2L13 Ser616 locus resulted in altered high mitochondrial autophagic fluxes, which significantly promoted GBM cell proliferation and invasion. FOXO3a generates drug resistance by promoting BNIP3‐mediated mitophagy.
The Role and Applied Value of Mitochondria in Glioma‐Related Research

Mitochondria, known as the “energy factory” of cells, are essential organelles with a double membrane structure and genetic material found in most eukaryotic cells. They play a crucial role in tumorigenesis and development, with alterations in mitochondrial structure and function in tumor cells leading to characteristics such as rapid proliferation, invasion, and drug resistance. Glioma, the most common brain tumor with a high recurrence rate and limited treatment options, has been linked to changes in mitochondrial structure and function. This review focuses on the bioenergetics, dynamics, metastasis, and autophagy of mitochondria in relation to glioma proliferation, as well as the potential use of mitochondria‐targeting drugs in glioma treatment.


of patient recruitment and exclusions. ASL, arterial spin labeling; CKD, chronic kidney disease; CKD1–3a, patients with stage 1–3a chronic kidney disease; CKD3b–5, patients with stage 3b–5 chronic kidney disease; fMRI, functional magnetic resonance imaging; HC, healthy control; QSM, quantitative susceptibility mapping; sMRI, structural MRI.
Flowchart of the experiment. ALFF, amplitude of low‐frequency fluctuation; CBF, cerebral blood flow; QSM, quantitative susceptibility mapping; ReHo, regional homogeneity; ROI, region of interest; rs‐fMRI, resting‐state functional magnetic resonance imaging.
Voxel‐based analysis among CKD1–3a patients, CKD3b–5 patients, and HC. The results were shown on the study‐wise magnitude template in the MNI coordinate system. (a) Voxel‐based ALFF analysis among CKD1–3a patients, CKD3b–5 patients, and HC (p < 0.05, FDR corrected). (b) Voxel‐based ReHo analysis among CKD1–3a patients, CKD3b–5 patients, and HC (p < 0.05, FDR corrected). (c) Voxel‐based CBF analysis among CKD1–3a patients, CKD3b–5 patients, and HC (p < 0.05, FDR‐corrected). (d) Voxel‐based QSM analysis among CKD1–3a patients, CKD3b–5 patients, and HC (p < 0.05, FDR corrected). ALFF, amplitude of low‐frequency fluctuations; CBF, cerebral blood flow; CKD, chronic kidney disease; CKD1–3a, patients with stage 1–3a chronic kidney disease; CKD3b–5, patients with stage 3b–5 chronic kidney disease; FDR, false discovery rate; HC, healthy control; MNI, Montreal Neurological Institute; QSM, quantitative susceptibility mapping; ReHo, regional homogeneity.
Whole‐brain and ROI‐based analysis of neurovascular coupling. (a) Whole‐brain‐based analysis of neurovascular coupling. (b) ROI‐based analysis of neurovascular coupling. *p < 0.05; **p < 0.01; ***p < 0.001; ****p < 0.0001; ALFF, amplitude of low‐frequency fluctuations; CBF, cerebral blood flow; CKD1–3a, patients with stage 1–3a chronic kidney disease; CKD3b–5, patients with stage 3b–5 chronic kidney disease; HC, healthy control; ReHo, regional homogeneity; ROI, region of interest.
Mediation analysis. The mediation proportion effect of phosphorus on the MoCA through susceptibility‐ALFF Coupling of the ANG.R was found to be 100%. All requirements for mediating effects are met: Path a (p = 0.018) is significant, b (p = 0.050) is not significant, and the 95% Boot CI of a*b does not include the number 0 (−2.4732, −0.0585), and c′ is not significant. Paths a and b together represent indirect (mediating) effects. Path c′ is the direct effect. ANG.R, right angular gyrus; MoCA scores, Montreal Cognitive Assessment scores.
Combination of rs‐fMRI, QSM, and ASL Reveals the Cerebral Neurovascular Coupling Dysfunction Is Associated With Cognitive Decline in Patients With Chronic Kidney Disease

December 2024

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10 Reads

Background Neurovascular coupling (NVC) reflects the close connection between neural activity and cerebral blood flow (CBF) responses, providing new insights to explore the neuropathological mechanisms of various diseases. Non‐dialysis patients with chronic kidney disease (CKD) exhibit cognitive decline, but the underlying pathological mechanisms are unclear. Methods The prospective study involved 53 patients with stage 1–3a CKD (CKD1–3a), 78 patients with stage 3b–5 CKD (CKD3b–5), and 52 healthy controls (HC). Our investigation involved voxel‐based assessments of both global and regional BOLD signal characteristics. Additionally, we explored the correlations between neuroimaging indices, Montreal Cognitive Assessment (MoCA) scores, and clinical laboratory findings. Results Compared to HC, the CKD3b–5 and CKD1–3a groups exhibited lower ALLF and ReHo in the default mode network (DMN), higher CBF in bilateral hippocampus (HIP), higher susceptibility values in bilateral caudate nucleus (CAU) and putamen (PUT), and lower susceptibility values in bilateral HIP. At the global level, the coupling coefficients were lower in CKD1–3a and CKD3b–5 groups than in HC. At the ROI level, the CBF‐ALFF and CBF‐ReHo coupling in HIP and basal ganglia regions were lower in CKD3b–5 groups than in the CKD1–3a group. Most importantly, susceptibility‐ALFF in ANG.R may mediate the effects of phosphorus on cognitive decompensation in patients with CKD1‐3a. Conclusions Non‐dialysis patients with CKD exhibit abnormal NCV, which is associated with the cognitive decline. Specifically, the susceptibility‐ALFF may serve as a valuable biomarker for early assessment of cognitive decline in CKD, offering insights into the pathogenesis of cognitive decline in CKD.


The flow chart of EL analysis. (A) fNIRS data is organized as a three‐dimensional tensor, with the three dimensions representing channel, frequency, and subject. Among these, the channel dimension requires further selection. (B) Seven channels are selected through the CPD algorithm and Pearson correlation analysis. (C) Signal binarization. Data points above the mean are marked as 1, while those below are marked as 0. (D) Each column represents the 7‐digit code corresponding to a state, and the empirical appearance probability is calculated. (E) A pairwise maximum entropy model is simulated to obtain energy corresponding to each state. (F) Energy landscape model schematic. The higher the energy of a state, the lower its frequency of appearance.
Channels selected through tensor decomposition method.
High‐frequency LM states under different stimuli. Horizontal numbers represent the state numbers, and vertical numbers represent the seven channel numbers retained after channel selection for each stimulus. Filled cells indicate activation of the corresponding channels, while blank cells represent the opposite. Colors are used to distinguish the frequency of occurrence of each state. The red dashed lines mark two major states.
The average duration of major states under each stimulus. MFG (Middle Frontal Gyrus) and SFG (Superior Frontal Gyrus), respectively, represent the regions where major States 1 and 2 are located (HCs, healthy controls; MDDs, individuals with MDD).
Energy features of all participants. (A) number of LMs, (B) mean energy difference between LMs and GM, (C) standard deviation of basin sizes, and (D) duration of GM. The bars graph show the mean value, and the error bars shows the 95% confidence interval for the mean value (HCs, healthy controls; MDDs, Individuals with MDD).
FNIRS‐Based Energy Landscape Analysis to Signify Brain Activity Dynamics of Individuals With Depression

December 2024

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24 Reads

Background Major depressive disorder (MDD) is one of the most common mental disorders, and the number of individuals with MDD (MDDs) continues to increase. Therefore, there is an urgent need for an objective characterization and real‐time detection method for depression. Functional near‐infrared spectroscopy (fNIRS) is a non‐invasive tool, which is widely used in depression research. However, the process of how the brain activity of MDDs changes in response to external stimuli based on fNIRS signals is not yet clear. Method Energy landscape (EL) can describe the brain dynamics under task conditions by assigning energy values to each state. The higher the energy value, the lower the probability of the state occurring. This study compares the EL features of 60 MDDs with 60 healthy controls (HCs). Results Compared to HCs, MDDs have more local minima, smaller energy differences, smaller variations in basin sizes, and longer duration in the basin of global minimum (GM). The classification results indicate that using the four features above for depression detection yields an accuracy of 86.53%. Simultaneously, there are significant differences between the two groups in the duration of the major states. Conclusion The dynamic brain networks of MDDs exhibit more constraints and lower degrees of freedom, which might be associated with depressive symptoms such as negative emotional bias and rumination. In addition, we also demonstrate the strong depression detection capability of EL features, providing a possibility for their application in clinical diagnosis.


E3 Ubiquitin Ligase Ring Finger Protein 2 Alleviates Cerebral Ischemia–Reperfusion Injury by Stabilizing Mesencephalic Astrocyte‐Derived Neurotrophic Factor Through Monoubiquitination

November 2024

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9 Reads

Aim Cerebral ischemic stroke (IS) is one of the leading causes of morbidity and mortality globally. However, the mechanisms underlying IS injury remain poorly understood. Ring finger protein 2 (RNF2), the member of the polycomb family (PcG), has been implicated in diverse biological and pathological conditions. However, whether RNF2 plays a role in IS progression is not clarified. This study aims to investigate the potential effects of RNF2 on IS. Methods The effects of RNF2 were studied in human postmortem IS brains, a rat model of IS, tunicamycin (TM)‐induced mouse neuroblastoma neuro2a (N2a) cells, and oxygen–glucose deprivation/reperfusion (OGD/R)‐induced SH‐SY5Y cells. Results Here, we demonstrated that RNF2 was markedly upregulated both in human postmortem IS brains and ischemic rat brains and RNF2 overexpression alleviated brain injury induced by middle cerebral artery occlusion by reducing neuron apoptosis. Mechanistically, we found that RNF2 is an E3 ubiquitin ligase for the mesencephalic astrocyte‐derived neurotrophic factor (MANF), which confers protection against brain ischemia. RNF2 interacted with MANF and promoted the monoubiquitination of MANF, consequently facilitating its stability and nuclear localization. Conclusion Collectively, RNF2 is identified as a critical inhibitor of IS injury by stabilizing MANF through monoubiquitination, suggesting that RNF2 is a potential therapeutic target for IS.


DRN serotonergic terminal activity changes in the VTA during sleep–wake. (a) Schematic diagram of anterograde tracing virus injection (Left), image of virus expression overlaps with serotonergic immunofluorescence staining in the DRN (Middle), and image of serotonergic terminal expressing in the VTA (Right). (b) Schematic diagram of retrograde tracing virus injection (Left), image of retrograde tracing virus expressing in the VTA(Middle), and image of retrograde tracing virus expression overlaps with serotonergic immunofluorescence staining in the DRN (Right). (c) Schematic of virus injection, fiber, and DSI implantation and image of GCaMP6s expression and optical fiber cannula in the VTA. (d) Representative raw VTA GCaMP6s fluorescence intensity trace and relevant EEG power spectra/EMG traces during sleep–wake. (e) Quantification of VTA GCaMP6s fluorescence intensity during wake, NREM, and REM. (f) Representative raw VTA GCaMP6s fluorescence intensity trace and relevant EEG power spectra/EMG traces in states switches during sleep–wake. (g) Quantification of VTA GCaMP6s fluorescence intensity in wake switch to NREM sleep. (h) Quantification of VTA GCaMP6s fluorescence intensity in NREM sleep switch to wake. (i) Quantification of VTA GCaMP6s fluorescence intensity in NREM sleep switch to REM sleep. (j) Quantification of VTA GCaMP6s fluorescence intensity in REM sleep switch to wake. DR, dorsal raphe; EEG, electroencephalogram; EMG, electromyography; VTA, ventral tegmental area. *p < 0.05, **p < 0.01, ***p < 0.001.
Effects of chemogenetic modulation of VTA‐projecting DRN serotonergic neurons during sleep–wake. (a) Schematic of chemogenetic virus injection and DSI implantation. (b) Image of retrograde chemogenetic virus expression in the VTA (Left) and DRN (Right). (c) Schematic of chemogenetic virus injection and whole cell patch (Left), effect of CNO on hM3Dq and hM4Di in vitro. (d) Representative EEG and EMG changes of chemogenetic modulation in sleep–wake cycle. (e) Quantification of time spent in different states in sleep–wake cycle under chemogenetic modulation. (f) Quantification of time of different states switches in sleep–wake cycle under chemogenetic modulation. 3Dq, hM3Dq; 4Di, hM4Di; CNO, clozapine‐N‐oxide; DR, dorsal raphe; VTA, ventral tegmental area.*p < 0.05, **p < 0.01, ***p < 0.001.
Effects of optogenetic activation of DRN serotonergic terminals in the VTA during sleep. (a) Schematic of optogenetic virus injection and whole‐cell patch. (b) Representative image of DRN serotonergic neurons and whole‐cell patch. (c) Verification of optogenetic stimulation parameters by 473 nm laser at different frequencies (blue bars represent 20 ms laser pulses). (d) Schematic of optogenetic virus injection, fiber, and DSI implantation. (e) Image of optogenetic virus expression overlaps with serotonergic immunofluorescence staining in the DRN (Left) and optical fiber cannula in the VTA (Right). (f) Quantification of latency from NREM sleep to wake after optogenetic activation of VTA serotonergic terminals compared with control group. (g) Quantification of latency from REM sleep to wake after optogenetic stimulation compared with control group. (h) Representative EEG and EMG changes induced by optogenetic stimulation during NREM and REM. (i) Quantification of EEG power changes by optogenetic activation DRN serotonergic terminals in the VTA during NREM sleep in control group. (j) Quantification of EEG power spectra changes after optogenetic stimulation during NREM sleep in experimental group. (k) Quantification of EEG power changes by optogenetic activation during REM sleep in control group. (l) Quantification of EEG power spectra changes after optogenetic stimulation during REM sleep in experimental group. DR, dorsal raphe; VTA, ventral tegmental area. *p < 0.05, **p < 0.01, ***p < 0.001.
Changes of VTA neuronal firing during sleep–wake. (a) Schematic of optogenetic virus injection and opto‐tetrode implantation. (b) Image of optogenetic virus expression in the DRN (Left) and virus expression with opto‐tetrode cannula in the VTA (Right). (c) Raster diagram showing spikes that effectively suppressed by 594 nm laser pulse were identified as dopaminergic neuronal firing and glutamatergic and GABAergic neuronal firing were also identified based on firing characteristics (Left), quantification of VTA dopaminergic neuronal firing rate changes pre, during and post 594 nm laser pulse (Middle), and representative spike waveform of VTA dopaminergic neuronal firing (Right). (d) Representative VTA neuronal firing trances, rasters, and EEG/EMG changes during sleep–wake cycle within optogenetic stimulation. (e) Quantification of VTA dopaminergic neuronal firings during different states during sleep–wake. (f) Quantification of VTA glutamatergic neuronal firings during different states during sleep–wake. (g) Quantification of VTA GABAergic neuronal firings during different states during sleep–wake. DR, dorsal raphe; VTA, ventral tegmental area. *p < 0.05, **p < 0.01, ***p < 0.001.
VTA neuronal firing changes induced by optogenetic activation of DRN serotonergic terminals during NREM sleep and REM sleep. (a) Representative VTA LFP/EMG changes (Left) and quantification of VTA LFP power changes by optogenetic stimulation during NREM sleep (Right). (b) Average firing (Left), quantification (Middle), and percentage (Right) changes of VTA dopaminergic neuronal firing by optogenetic stimulation during NREM sleep. (c) Average firing (Left), quantification (middle), and percentage (Right) changes of VTA glutamatergic neuronal firing by optogenetic stimulation during NREM sleep. (d) Average firing (Left), quantification (Middle), and percentage (Right) changes of VTA GABAergic neuronal firing by optogenetic stimulation during NREM sleep. (e) Representative VTA LFP/EMG changes (Left) and quantification of VTA LFP power changes by optogenetic stimulation during REM sleep (Right). (f) Average firing (Left), quantification (Middle), and percentage (Right) changes of VTA dopaminergic neuronal firing by optogenetic stimulation during REM sleep. (g) Average firing (Left), quantification (Middle), and percentage (Right) changes of VTA glutamatergic neuronal firing by optogenetic stimulation during REM sleep. (h) Average firing (Left), quantification (Middle), and percentage (Right) changes of VTA GABAergic neuronal firing by optogenetic stimulation during REM sleep. DR, dorsal raphe; VTA, ventral tegmental area. *p < 0.05, **p < 0.01, ***p < 0.001.
Dorsal Raphe Serotonergic Neurons‐Ventral Tegmental Area Neural Pathway Promotes Wake From Sleep

November 2024

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7 Reads

Background Dorsal raphe nucleus (DRN) serotonergic neurons projecting to the ventral tegmental area (VTA) neural circuit participate in regulating wake‐related behaviors; however, the effect and mechanism of which in regulating sleep–wake are poorly understood. Methods Fiber photometry was used to study DRN serotonergic afferent activity changes in the VTA during sleep–wake processes. Optogenetics and chemogenetics were took advantage to study the effects of DRN serotonergic afferents modulating VTA during sleep–wake. In vivo electrophysiology was employed to investigate how VTA neuronal firings were influenced by upregulation of DRN serotonergic afferents during sleep–wake. Results We found that DRN serotonergic afferent activity in the VTA was higher during wake than during NREM and REM sleep. Chemogenetic activation of VTA‐projecting DRN serotonergic neurons increased wake, and optogenetic activation of DRN serotonergic terminals in the VTA induced wake during NREM and REM sleep. Furthermore, we found that optogenetic activation of DRN serotonergic terminals in the VTA increased glutamatergic neuronal firing, decreased dopaminergic neuronal firing, but not influenced GABAergic neuronal firing during NREM sleep. Conclusion Our findings provide evidence in understanding the role of DRN serotonergic neurons‐VTA neural pathway in regulating sleep–wake, in which dynamic VTA dopaminergic, glutamatergic, and GABAergic neuronal firing changes responded to the wake promoting effect of DRN serotonergic afferents.


Subject Disposition.
Plasma concentration–time curves following single infusion of 20–750 mg of BAT4406F (Mean ± SD, n = 3) (Left: Linear scale, Right: Semi‐Logarithm scale).
CD19⁺ B‐cell counts in each dose group (Mean ± SD, in Logarithm Scale).
First‐in‐Human Study of BAT4406F, an ADCC‐Enhanced Fully Humanized Anti‐CD20 Monoclonal Antibody in Patients With Neuromyelitis Optica Spectrum Disorders

November 2024

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5 Reads

Introduction Neuromyelitis optica spectrum disorder (NMOSD) is a rare debilitating autoimmune disease of the central nervous system (CNS). This is the first‐in‐human dose‐escalation Phase I clinical study of BAT4406F, an antibody‐dependent cell‐mediated cytotoxicity (ADCC)‐enhanced fully humanized anti‐CD20 monoclonal antibody, in Chinese NMOSD patients. Patients and Methods Using a “3 + 3” design and based on the planned algorithm of dose escalation, the enrolled NMOSD patients were sequentially assigned to one of the five dose‐escalation cohorts of BAT4406F with a single intravenous dose, and were then followed for a 6‐month observation period. The maximum tolerated dose (MTD) and dose‐limiting toxicity (DLT), safety, pharmacokinetics (PK), pharmacodynamics, and immunogenicity of BAT4406F were investigated, and the efficacy of BAT4406F in NMOSD was also preliminarily explored. Results Fifteen Chinese NMOSD patients were enrolled to receive BAT4406F of escalated doses ranging from 20 to 750 mg. No subjects experienced DLT at the studied doses. BAT4406F injection exhibited favorable safety, with most of the adverse events (AE) of CTCAE Grade 1 or 2 in severity, and no Grade ≥ 3 adverse drug reactions (ADR) or serious adverse reactions occurred in any subjects. With the dose increase of BAT4406F, the maximum plasma concentration (Cmax), area under concentration‐time curve from 0 to the last measurable timepoint (AUC0‐t) and area under concentration‐time curve from 0 to infinity (AUC0‐inf) showed an increasing trend, whereas the mean clearance (CLt), terminal elimination rate (λZ), and apparent volume of distribution (Vd) decreased. The mean elimination half‐life (T1/2) was ranged from 9.0–16.4 days. PK profile of BAT4406F was generally nonlinear. BAT4406F led to a rapid and significant B‐cell depletion in all dose groups. Single administration of 500 mg or 750 mg maintains the CD19⁺ B lymphocyte count below 10/μL within the whole 6‐month observation period. Three subjects were antidrug antibody (ADA) positive and all of them were neutralizing antibody (NAb)‐negative. On day 99/180 postdose, several groups had decreased expanded disability status scale (EDSS) scores compared to baseline. During the observation period, NMOSD relapse occurred in two patients (13.3%) and the other 13 (86.7%) subjects remained relapse free. Conclusion BAT4406F was well tolerated at doses up to 750 mg and showed an expected pharmacodynamic effect of significant and long‐term depletion of CD19⁺ B lymphocytes. It has also shown preliminary evidence of activity in NMOSD maintenance treatment, warranting further investigations. Trial Registration ClinicalTrials.gov identifier: NCT04146285


Farnesylthiosalicylic Acid Through Inhibition of Galectin‐3 Improves Neuroinflammation in Alzheimer Disease via Multiple Pathways

November 2024

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11 Reads

Aims Many factors affect the neuroinflammatory response in patients with Alzheimer disease (AD). Galectin‐3 (Gal‐3) is closely related to microglial activation in the nervous system and can promote the aggregation of cancer cells in tumors. This study aimed to investigate the mechanism by which farnesylthiosalicylic acid (FTS) affects neuroinflammation in Aβ1–42 mice through Gal‐3. Methods We used the Morris water maze, reverse transcription–polymerase chain reaction (RT–PCR), Western blotting, enzyme‐linked immunosorbent assay (ELISA), and immunofluorescence to conduct our study. Results FTS reduced the levels of proinflammatory factors and microglial activation in Aβ1–42 mice. FTS inhibited total and membrane expression levels of Gal‐3 in Aβ1–42 mice, and the anti‐inflammatory effect of FTS was reversed by Gal‐3–adeno‐associated viral (AAV). FTS reduced the expression levels of toll‐like receptors (TLRs), effects that were reversed by Gal‐3‐AAV. Moreover, FTS ameliorated Aβ oligomerization and accumulation in Aβ1–42 mice, effects that were also reversed by Gal‐3‐AAV. FTS, through the inhibition of the Gal‐3–c‐Jun N‐terminal kinase (JNK) pathway, reduced PS1 expression; in addition, inhibition of Gal‐3 increased the Aβ‐degrading enzymes in Aβ1–42 mice. FTS‐induced improvements in cognition in Aβ1–42 mice were reversed by Gal‐3‐AAV. Conclusion FTS may through inhibiting Gal‐3 reduce the expression of TLR4 and CD14 and alleviate Aβ pathology, downregulating Aβ‐stimulated TLR2, TLR4, and CD14 expression, and thus alleviate neuroinflammation in Aβ1–42 mice.


Differences in GMV. (A) Case–control t‐map of regional GMV in TLE (left), FBTCS− (middle) and FBTCS+ (right) versus HC. (B) Statistical significant regions in TLE (left), FBTCS− (middle), and FBTCS+ (right) versus HC after FDR correction. (C) The differences in Yeo functional networks and von Economo classes in TLE (left), FBTCS− (middle) and FBTCS+ (right). Asso1, association cortex1; Asso2, association cortex 2; DAN, dorsal attention network; DMN, default mode network; FPN, frontoparietal network; FBTCS−, without focal to bilateral tonic–clonic seizures; FBTCS+, with focal to bilateral tonic–clonic seizures; GMV, gray matter volume; LN, limbic network; Prim motor, primary motor cortex; Prim sens, primary sensory cortex; Sec sens, second sensory cortex; SMN, somato‐motor network; TLE, temporal lobe epilepsy; VAN, ventral attention network; VN, visual network.
Association between regional gene expression profiles and case–control differences of gray matter volume. (A) The scatter plot shows the regional PLS1 scores was correlated with case–control t‐values in left hemisphere of FBTCS−, with each dot representing a brain region. (B) The regional expression of the most positively weighted gene in left hemisphere and the correlation with case–control t‐value of FBTCS−. (C) The most negatively weighted gene and the negative correlation with case–control t‐value of FBTCS−. (D) The regional PLS1 scores and was positively correlated with case–control t‐value in left hemisphere of FBTCS+. (E) The regional expression of the most positively weighted gene in left hemisphere and was positive correlated with case–control t‐value of FBTCS+. (F) The regional expression of the most negatively weighted gene and was negatively correlated with case–control t‐value of FBTCS+. FBTCS−, without focal to bilateral tonic–clonic seizures; FBTCS+, with focal to bilateral tonic–clonic seizures; PLS1, the first component of the PLS analysis.
Pathway Enrichment analysis of the PLS+ genes. (A) The heatmap displayed the GO and KEGG pathways for PLS+ genes. (B) Network of enriched GO and KEGG terms by metascape. GO, gene ontology; KEGG; Kyoto Encylopedia of Gene, Genomes.
Cell type enrichment of PLS+ genes and correlation between regional GABA receptor expression and case–control t‐value. (A) Excitatory and inhibitory neurons were significantly enriched in FBTCS− patients. (B) Only excitatory neurons were significantly enriched in in FBTCS+ patients. (C) The scatter plot shows the regional GABA receptor expression was significantly correlated with case–control t‐value of FBTCS−, with each dot representing a brain region. (D) No significant correlation was found between GABA receptor expression and case–control t‐value of FBTCS+. FBTCS−, without focal to bilateral tonic–clonic seizures; FBTCS+, with focal to bilateral tonic–clonic seizures.
Brain Morphometric Alterations in Focal to Bilateral Tonic–Clonic Seizures in Epilepsy Associated With Excitatory/Inhibitory Imbalance

November 2024

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26 Reads

Background Focal to bilateral tonic–clonic seizures (FBTCS) represent the most severe seizure type in temporal lobe epilepsy (TLE), associated with extensive network abnormalities. Nevertheless, the genetic and cellular factors predispose specific TLE patients to FBTCS remain poorly understood. This study aimed to elucidate the relationship between brain morphometric alterations and transcriptional profiles in TLE patients with FBTCS (FBTCS+) compared to those without FBTCS (FBTCS−). Methods We enrolled 126 unilateral TLE patients (89 FBTCS+ and 37 FBTCS−) along with 60 age‐ and gender‐matched healthy controls (HC). We assessed gray matter volume to identify morphometric differences between patients and HC. Partial least squares regression was employed to investigate the association between the morphometric disparities and human brain transcriptomic data obtained from the Allen Human Brain Atlas. Results Compared with HC, FBTCS+ patients exhibited morphometric alterations in bilateral cortical and subcortical regions. Conversely, FBTCS− patients exhibited more localized alterations. Imaging transcriptomic analysis revealed both FBTCS− and FBTCS+ groups harbored genes that spatially correlated with morphometric alterations. Additionally, pathway enrichment analysis identified common pathways involved in neural development and synaptic function in both groups. The FBTCS− group displayed unique pathway enrichment in catabolic processes. Furthermore, mapping these genes to specific cell types indicated enrichment in excitatory and inhibitory neurons in the FBTCS− group, while FBTCS+ group only enriched in excitatory neurons. The distinct cellular expression differences between FBTCS− and FBTCS+ groups are consistent with the distribution patterns of GABAergic expression. Conclusion We applied imaging transcriptomic analysis linking the morphometric changes and neurobiology in TLE patients with and without FBTCS, including gene expression, biological pathways, cell types, and neurotransmitter receptors. Our findings revealed abnormalities in inhibitory neurons and altered distribution patterns of GABAergic receptors in FBTCS+, suggesting that an excitatory/inhibitory imbalance may contribute to the increased susceptibility of certain individuals to FBTCS.


Discovery and validation of differentially expressed DHCR24 and candidate circRNAs in cohort 1. (A) Cluster heat map shows in cohort 1 (8 CSVD‐CN patients and 10 CSVD‐CI patients), 681 differentially expressed mRNAs with a |log2 (fold change)| > 0.58 and p < 0.05 and an effective test value in any one sample. The bold mRNA is DHCR24. (B) Volcano plot of 681 differentially expressed mRNAs. Horizontal coordinates represent mRNAs with log2 (fold change) (CSVD‐CN/CSVD‐CI) > 0.58 or < −0.58. The vertical axis displays −log10 (p‐value) > 1.30 (mean p < 0.05) of differentially expressed mRNAs. Each point represents an individual mRNA. DHCR24 is regulated mRNA in cohort 1. (C) RT‐qPCR was performed to verify the expression of DHCR24 in cohort 1 (8 CSVD‐CN patients and 10 CSVD‐CI patients). Each sample was tested in triplicate. Independent‐sample t‐test was used for data analysis and all data represents means ± standard deviation. (D) CircRNA‐associated DHCR24 mRNA networks. (E) Volcano plot of 897 differentially expressed circRNAs. Horizontal coordinates represent circRNAs with |log2 (fold change)| > 0.58 (CSVD‐CN/CSVD‐CI). The vertical axis displays −log10 (p‐value) > 1.30 (mean p < 0.05) of differentially expressed circRNAs. Each point represents an individual circRNA. Nine candidate circRNAs were showed in this figure. (F) RT‐qPCR was performed to verify the expression of nine candidate circRNAs in cohort 1 (8 CSVD‐CN patients and 10 CSVD‐CI patients). Each sample was tested in triplicate. Independent‐sample t‐test was used for data analysis and all data represents means ± standard deviation. CSVD‐CI, cerebral small vessel disease‐cognitive impairment; CSVD‐CN, cerebral small vessel disease‐cognitively normal; RT‐qPCR, real‐time quantitative polymerase chain reaction.
Replication and the clinical application of DHCR24 and has_circ_0015335 in the independent replication cohort 2. (A, B) Expression levels of DHCR24 and has_circ_0015335 between CSVD‐CN and CSVD‐CI groups were determined by RT‐qPCR. (C) Correlations between DHCR24 and has_circ_0015335 expression levels in two groups. (D) ROC curves of DHCR24, has_circ_0015335, and the combination of these two indices. CSVD‐CI, cerebral small vessel disease‐cognitive impairment; CSVD‐CN, cerebral small vessel disease‐cognitively normal; RT‐qPCR, real‐time quantitative polymerase chain reaction; ROC, receiver operating characteristic.
Association analyses of DHCR24 and has_circ_0015335 levels with cognitive assessments and 24(S)‐OHC levels in CSVD‐CI patients. (A) Heatmap of correlation analyses of cognitive assessments with DHCR24 and has_circ_0015335 levels. *0.01 ≤ p < 0.05; **0.001 ≤ p < 0.01; ***p < 0.001. (B) Correlation analysis of 24(S)‐OHC levels. (C) Interaction analysis of DHCR24 and has_circ_0015335 for the 24(S)‐OHC levels. 24(S)‐OHC, 24(S)‐hydroxycholesterol; AVLT‐20 min DR, auditory verbal learning test‐20‐min delayed recall; AVLT‐IR, auditory verbal learning test‐immediate recall; CDT, Clock Drawing Test; CSVD‐CI, cerebral small vessel disease‐cognitive impairment; CSVD‐CN, cerebral small vessel disease‐cognitively normal; DST, Digit Span Test; MMSE, mini‐mental state examination; MoCA, montreal cognitive assessment; Stroop‐A, Stroop Color and Word Test A; Stroop‐B, Stroop Color and Word Test B; Stroop‐C, Stroop Color and Word Test C; SVD, small‐vessel disease; TMT‐A, Trail Making Test A; TMT‐B, Trail Making Test B.
Association analyses of DHCR24 and has_circ_0015335 levels with brain MRI features in CSVD‐CI patients. (A–C) Significant difference of cortical surface area (mm²), cortical thickness (mm), and gray matter volume (mm³) in brain between CSVD‐CN and CSVD‐CI patients (p < 0.05, correction based on Monte Carlo Simulation). (D) Heatmap of correlation analyses of brain MRI features with DHCR24 and has_circ_0015335 levels. *0.01 ≤ p < 0.05; **0.001 ≤ p < 0.01; ***p < 0.001. (E) The mediation effects of DHCR24 levels on has_circ_0015335 and brain structure changes. “a,” “b,” and “c′” represent the direct effect between the two variables, and “c” represents the total effect between the two variables. CSVD‐CI, cerebral small vessel disease‐cognitive impairment; MRI, magnetic resonance imaging.
Interaction Between DHCR24 and hsa_circ_0015335 Facilitates Cognitive Impairment in Cerebral Small Vessel Disease Patients

November 2024

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6 Reads

Aims The study attempted to determine the underlying role and regulation mechanism of 3β‐hydroxysterol‐Δ24 reductase (DHCR24) in the pathophysiology of cerebral small vessel disease‐associated cognitive impairment (CSVD‐CI). An RNA high‐throughput sequencing and independent verification were conducted to identify potential circRNAs becoming the upstream regulator. Methods RNA sequencing was performed in whole‐blood samples in cohort 1 (10 CSVD‐CI and 8 CSVD with cognitively normal [CSVD‐CN] patients). The DHCR24 and candidate circRNAs were verified in an independent cohort 2 (45 CSVD‐CI participants and 37 CSVD‐CN ones). The study also analyzed comprehensive cognitive assessments, plasma molecular index, and brain structure imaging. Results The expression of DHCR24 and has_circ_0015335 in whole‐blood samples of CSVD‐CI patients was significantly reduced compared to CSVD‐CN patients in RNA sequencing and independent verification. Furthermore, the levels of DHCR24 and has_circ_0015335 were significantly related to global cognitive impairment in CSVD‐CI patients. Meanwhile, DHCR24 could regulate the correlation between has_circ_0015335 expression and alterations in brain cortex in surface area, thickness, and volume in CSVD‐CI patients. Additionally, hsa_circ_0015335 interacted with DHCR24 for plasma 24(S)‐hydroxycholesterol levels among CSVD‐CI patients. Conclusion Interaction between DHCR24 and hsa_circ_0015335 cognitively impaired CSVD by affecting brain cholesterol metabolism and brain structural changes.


Forest plot of causal effects of body fat indicators on PD. BFM, Whole body fat mass; BFP, body fat percentage; BMI, body mass index; CI, confidence interval; HC, hip circumference; OR, odds ratio; PD, Parkinson disease; WC, waist circumference.
Scatter plot of causal effects of body fat measures on PD. (A) Both sexes. (B) Female. (C) Male. BFM, Whole body fat mass; BFP, body fat percentage; BMI, body mass index; HC, hip circumference; IVW, inverse variance weighted; PD, Parkinson disease; WC, waist circumference; WM, weighted median.
Two colocalized regions between BMI and PD. The x‐axis represents the genomic coordinates and the y‐axis represents the negative log10 transform p value for each genetic variant. BMI, Body mass index; PD, Parkinson disease.
Cross‐trait meta‐analysis and enrichment analysis. (A) Manhattan plot of FUMA analysis of BMI and PD. The x‐axis is the chromosomal position of SNPs, and the y‐axis is the significance of the SNPs (−log10P). (B, C). The genomic loci of BMI and PD. (D) Enrichment analysis of BMI.
Novel Insights Into the Causal Effects and Shared Genetics Between Body Fat and Parkinson Disease

November 2024

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8 Reads

Aims Existing observational studies examining the effect of body fat on the risk of Parkinson disease (PD) have yielded inconsistent results. We aimed to investigate this causal relationship at the genetic level. Methods We employed two‐sample Mendelian randomization (TSMR) to investigate the causal effects of body fat on PD, with multiple sex‐specific body fat measures being involved. We performed Bayesian colocalization analysis and cross‐trait meta‐analysis to reveal pleiotropic genomic loci shared between body mass index (BMI) and PD. Finally, we used the MAGMA tool to perform tissue enrichment analysis of the genome‐wide association study hits of BMI. Results TSMR analysis suggests that except waist circumference, higher measures of body fatness are associated with a decreased risk of PD, including BMI (OR: 0.83), body fat percentage (OR: 0.69), body fat mass (OR: 0.77), and hip circumference (OR: 0.83). The observed effects were slightly more pronounced in females than males. Colocalization analysis highlighted two colocalized regions (chromosome 3p25.3 and chromosome 17p12) shared by BMI and PD and pointed to some genes as possible players, including SRGAP3, MTMR14, and ADORA2B. Cross‐trait meta‐analysis successfully identified 10 novel genomic loci, involving genes of TOX3 and MAP4K4. Tissue enrichment analysis showed that BMI‐associated genetic variants were enriched in multiple brain tissues. Conclusions We found that nonabdominal body fatness exerts a robust protective effect against PD. Our colocalization analysis and cross‐trait meta‐analysis identified pleiotropic genetic variation shared between BMI and PD, providing new clues for understanding the association between body fat and PD.


A schematic overview of established and candidate blood‐based panel biomarker discovery for Alzheimer's disease prediction by proteomics and metabolomics.
Flowchart shows the identification of putative panel biomarkers using the integration of proteomics and metabolomics for Alzheimer's disease prediction.
The early diagnosis of Alzheimer's disease: Blood‐based panel biomarker discovery by proteomics and metabolomics

Diagnosis and prediction of Alzheimer's disease (AD) are increasingly pressing in the early stage of the disease because the biomarker‐targeted therapies may be most effective. Diagnosis of AD largely depends on the clinical symptoms of AD. Currently, cerebrospinal fluid biomarkers and neuroimaging techniques are considered for clinical detection and diagnosis. However, these clinical diagnosis results could provide indications of the middle and/or late stages of AD rather than the early stage, and another limitation is the complexity attached to limited access, cost, and perceived invasiveness. Therefore, the prediction of AD still poses immense challenges, and the development of novel biomarkers is needed for early diagnosis and urgent intervention before the onset of obvious phenotypes of AD. Blood‐based biomarkers may enable earlier diagnose and aid detection and prognosis for AD because various substances in the blood are vulnerable to AD pathophysiology. The application of a systematic biological paradigm based on high‐throughput techniques has demonstrated accurate alterations of molecular levels during AD onset processes, such as protein levels and metabolite levels, which may facilitate the identification of AD at an early stage. Notably, proteomics and metabolomics have been used to identify candidate biomarkers in blood for AD diagnosis. This review summarizes data on potential blood‐based biomarkers identified by proteomics and metabolomics that are closest to clinical implementation and discusses the current challenges and the future work of blood‐based candidates to achieve the aim of early screening for AD. We also provide an overview of early diagnosis, drug target discovery and even promising therapeutic approaches for AD.


LITT procedure was performed in the intraoperative MRI room. (A) Optical fiber implantation under Leksell frame; (B) neurosurgical robot assisted optical fiber insertion; (C) intraoperative MR coil fixation after optical fiber insertion; (D) Fiber‐optic catheter outer (length 4, 10, 15 mm); (E) patients in the intraoperative MRI room; (F, G) the LaserRO system equipped with a dual‐wavelength laser, operating at 980 and 1064 nm, for MRgLITT.
Representative FCD patient's preoperative ablation trajectory planning, intraoperative ablation real‐time thermal monitoring, and postoperative MRI. The top of the figure indicates EEG onset. (A–C) Ablation trajectory planning in coronal, sagittal, and axial plane. (White indicates the planned ablation and yellow indicates the actual ablation); (D) thin‐slice head CT with reconstruction; (E–G) ablation along the first trajectory in axial, sagittal, and coronal plane; (H–J) ablation along the second trajectory in axial, sagittal, and coronal plane; (K–M) postoperative 3‐month MRI in axial, sagittal, and coronal plane.
Representative CM patient's preoperative ablation trajectory planning, intraoperative ablation real‐time thermal monitoring, and postoperative MRI. This patient shows no typical EEG onset. (A–C) Ablation trajectory planning in coronal, sagittal, and axial plane. (White indicates the planned ablation and yellow indicates the actual ablation); (D) thin‐slice head CT with reconstruction; (E–G) ablation along the first trajectory in axial, sagittal, and coronal plane; (H–J) ablation along the second trajectory in axial, sagittal, and coronal plane; (K–M) postoperative 3‐month MRI in axial, sagittal, and coronal plane.
Representative MTLE patient's preoperative ablation trajectory planning, intraoperative ablation real‐time thermal monitoring, and postoperative MRI. The top of the figure indicates EEG onset. (A–C) Ablation trajectory planning in coronal, sagittal, and axial plane. (White indicates the planned ablation and yellow indicates the actual ablation); (D): thin‐slice head CT with reconstruction; (E–G) ablation along the first trajectory in axial, sagittal, and coronal plane; (H–J) ablation along the second trajectory in axial, sagittal, and coronal plane; (K–M) postoperative 3‐month MRI in axial, sagittal, and coronal plane.
Magnetic Resonance‐Guided Laser Interstitial Thermal Therapy Using Dual‐Wavelength Dual‐Output Laser Within Two Probe Trajectories for Treatment of Drug‐Resistant Epilepsy

November 2024

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36 Reads

Objective Magnetic resonance‐guided laser interstitial thermal therapy (MRgLITT) is a novel tool and a minimally invasive treatment to drug‐resistant epilepsy (DRE). The focus of this research was to evaluate the effectiveness and safety of the newly developed dual‐wavelength dual‐output MRgLITT system LaserRO within two probe trajectories in treating DRE patients. Methods This is a retrospective analysis conducted at a single center, examining patients with DRE who received treatment with the LaserRO MRgLITT system. The system utilizes a sophisticated laser technology that can be configured as conventional single output for single wavelength or innovative dual outputs for dual wavelengths. The study involved a comprehensive review of patient information, encompassing demographics, seizure history, details related to the surgical parameters, and the subsequent clinical results. Primary outcome was post‐operation seizure outcome defined as Engel Scale Class at the end of follow‐up time. Results This study included a total of eight DRE patients received MRgLITT surgery between August 2022 and October 2023. Out of these, there were four mesial temporal lobe epilepsy (MTLE), three focal cortical dysplasia (FCD), and one cavernous malformation (CM) patients. Within the two probe trajectories, seven patients had single wavelength (980 or 1064 nm) laser treatment and one patient had dual‐wavelength (980 and 1064 nm) laser treatment. The median age of the patients was 27 (22–31) years, with a median follow‐up period of 9.7 (8.4–12.1) months. The mean BMI was recorded at 20.24 ± 2.95 kg/m², and epilepsy history was 13 ± 6 years. The median intraoperative blood loss was 5 (5–9) mL, operation time was 231 (169–254) minutes, and length of stay (LOS) was 3 (3–5) days. The mean ablation volume ratio was 96.52% ± 3.67%. In terms of outcomes, over a median follow‐up time of 9.7 (range 8.4–12.1) months, there were two patients got Engel I, five patients got seizure‐free, and one patient decreased 75% seizure. Importantly, no serious complications following the procedures occurred. Conclusions The preliminary results indicate that the MRgLITT procedure, which operates dual‐output laser with single or dual wavelengths (980/1064 nm) within the two trajectories, is both effective and safe as a minimally invasive approach for different types of DRE patients.


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4.8 (2023)

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25%

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20 days

Submission to first decision


$3,580 / £2,720 / €3,070

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