Optimized Mouse Model of Sepsis‐Associated Encephalopathy: A Rational Standard Based on Modified SHIRPA Score and Neurobehaviors in Mice DOI Creative Commons

Yuewen Xin,

Mi Tian, Xu Pei

et al.

CNS Neuroscience & Therapeutics, Journal Year: 2025, Volume and Issue: 31(4)

Published: April 1, 2025

ABSTRACT Background Sepsis‐associated encephalopathy (SAE), a severe neurological disorder, is marked by widespread brain dysfunction. At present, there no universally accepted criterion for diagnosing SAE in animal models. This study proposes standardized evaluation method mice, addressing inconsistencies current research. Method Using cecal ligation and puncture (CLP) model to induce sepsis, we assessed the physiological status of mice with modified SHIRPA score differentiate from non‐SAE, validating our findings through various behavioral tests evaluations neuroinflammation neuronal damage. Results Our revealed that conventional mild–moderate–severe categorization was insufficient distinguishing between non‐SAE. To enhance differentiation, classified based on median score, this approach including Y‐maze, three‐chamber social test, open field test. effectively identified impairments septic mice. Further validation involved assessing damage, neuroinflammation, Morris water maze, long‐term potentiation (LTP) hippocampal CA1 region. indicated up‐Median group exhibited greater injury, cognitive deficits compared down‐Median group. Conclusions establishes reliable murine models, facilitating improved differentiation Such advancements will understanding pathogenesis guide more effective treatment strategies.

Language: Английский

Identification and Evaluation of Lipocalin-2 in Sepsis-Associated Encephalopathy via Machine Learning Approaches DOI Creative Commons
Jia Hu, Zengze Chen,

Jinyan Wang

et al.

Journal of Inflammation Research, Journal Year: 2025, Volume and Issue: Volume 18, P. 3843 - 3858

Published: March 1, 2025

Sepsis-associated encephalopathy (SAE) critically contributes to poor prognosis in septic patients. Identifying and screening key genes responsible for SAE, as well exploring potential targeted therapies, are vital improving the management of sepsis advancing precision medicine. Single-cell RNA sequencing (scRNA-seq) was administrated identify cell subpopulations related Next, hierarchical dynamic weighted gene co-expression network analysis (hdWGCNA) employed associated with specific neutrophil subpopulations. Enrichment revealed biological functions these genes. Subsequently, neuroinflammation-related were obtained construct a signature. The AddModuleScore algorithm used calculate neuroinflammation scores each subpopulation, whereas CellCall assess crosstalk between neutrophils other To accurately, four binary classification machine learning algorithms utilized. Finally, Western blotting behavioral tests confirm role LCN2-related mice. This study utilized scRNA-seq reveal critical peripheral during sepsis, identifying contributors neuroinflammation. On basis various algorithms, we discovered that Lipocalin-2 (LCN2) may be involved neutrophil-induced SAE. prove findings, conducted vivo experiments an animal model. Increased LCN2 expression cognitive dysfunction occurred Additionally, levels markers astrocytes microglia inflammatory factors such TNF-α IL-6 significantly increased. All phenomena reversed by downregulation LCN2. upregulation on is step triggers central nervous system

Language: Английский

Citations

0
Magnesium Hexacyanoferrate Mitigates Sepsis-Associated Encephalopathy through Inhibiting Microglial Activation and Neuronal Cuproptosis DOI

Yabing Zhang,

Juan Xin,

Di Zhao

et al.

Biomaterials, Journal Year: 2025, Volume and Issue: unknown, P. 123279 - 123279

Published: March 1, 2025

Language: Английский

Citations

0
A novel postoperative delayed neurocognitive recovery model established based on preoperative rapid eye movement sleep deprivation in adult mice DOI

Kaixi Liu,

Jingshu Hong, Yitong Li

et al.

International Immunopharmacology, Journal Year: 2025, Volume and Issue: 153, P. 114508 - 114508

Published: March 28, 2025

Language: Английский

Citations

0
Astragalin-functionalized ultrasmall nanoparticles modulate the complement pathway to inhibit microglial synaptic phagocytosis for reducing anesthetic neurotoxicity DOI
Gang Wang,

Yaobao Han,

Ke Peng

et al.

Materials Today Bio, Journal Year: 2025, Volume and Issue: 32, P. 101714 - 101714

Published: April 1, 2025

Language: Английский

Citations

0
Optimized Mouse Model of Sepsis‐Associated Encephalopathy: A Rational Standard Based on Modified SHIRPA Score and Neurobehaviors in Mice DOI Creative Commons

Yuewen Xin,

Mi Tian, Xu Pei

et al.

CNS Neuroscience & Therapeutics, Journal Year: 2025, Volume and Issue: 31(4)

Published: April 1, 2025

ABSTRACT Background Sepsis‐associated encephalopathy (SAE), a severe neurological disorder, is marked by widespread brain dysfunction. At present, there no universally accepted criterion for diagnosing SAE in animal models. This study proposes standardized evaluation method mice, addressing inconsistencies current research. Method Using cecal ligation and puncture (CLP) model to induce sepsis, we assessed the physiological status of mice with modified SHIRPA score differentiate from non‐SAE, validating our findings through various behavioral tests evaluations neuroinflammation neuronal damage. Results Our revealed that conventional mild–moderate–severe categorization was insufficient distinguishing between non‐SAE. To enhance differentiation, classified based on median score, this approach including Y‐maze, three‐chamber social test, open field test. effectively identified impairments septic mice. Further validation involved assessing damage, neuroinflammation, Morris water maze, long‐term potentiation (LTP) hippocampal CA1 region. indicated up‐Median group exhibited greater injury, cognitive deficits compared down‐Median group. Conclusions establishes reliable murine models, facilitating improved differentiation Such advancements will understanding pathogenesis guide more effective treatment strategies.

Language: Английский

Citations

0