Frontiers in Aging Neuroscience最新文献

Autophagy is an intracellular degradation system, which plays a crucial role in regulating the inflammatory functions of neutrophils. Neutrophils, as crucial immunological phagocytes, are integral to inflammatory responses. In central nervous system diseases, neutrophils' malfunction is closely associated with disease progression. Autophagy in neutrophils is highly conserved and plays a crucial regulatory role in both the biological functions and pathophysiological processes of neutrophils. In this review, we comprehensively explore the mechanisms of autophagy and its regulatory roles in various aspects of neutrophil biology, including the neutrophil life cycle, extracellular net traps (NETs) formation, degranulation, migration and adhesion, and phagocytosis. We also analyze the role of neutrophil autophagy in different central nervous system diseases such as Alzheimer's disease, stroke, and neuroglioma. Regulating autophagy to control neutrophil inflammatory functions may emerge as a novel therapeutic strategy for treating central nervous system disorders.

Introduction: Alzheimer's disease (AD) is a neurodegenerative disease that can only be managed rather than cured, bringing a substantial burden to society. Frailty and cognition are intertwined in a cycle of decline, affecting the prognosis of AD. Qi-Fu-Yin (QFY) is a classic prescription in traditional Chinese medicine for dementia. While most studies have focused on cognitive impairment, research on physiological frailty remains relatively scarce in AD, especially in 5xFAD mice. We aimed to investigate the impacts of QFY on the physiological frailty of male 5xFAD mice.

Methods: Male 5xFAD mice received QFY, followed by grip strength test, rotarod test, grading score of frailty, lipofuscin staining, SA-β-gal and Aβ co-staining. The metabolite alteration and the intestinal flora composition were analyzed by non-targeted metabolomics and 16S rRNA sequencing. Moreover, Spearman's correlation analysis was used to integrate behavioral results, differentially expressed metabolites, and altered bacterial genera.

Results: We discovered that QFY improved grip strength, riding time, score of frailty, lipofuscin deposition, SA-β-gal, and Aβ in male 5xFAD mice. The results of untargeted metabolomics showed that metabolites such as proline, PS (18:1/18:0), and PFSA-CI were downregulated in the male 5xFAD mice compared with C57BJ/6JXSJL mice, while PE (18:1/18:1) was upregulated. QFY treatment reversed these changes, restoring metabolite levels toward those of C57BJ/6JXSJL mice. Arginine and proline metabolism, alanine, aspartate and glutamate metabolism, and butyrate metabolism were filtered out as the important metabolic pathways between the C57BJ/6JXSJL mice and the male 5xFAD mice, as well as between the 5xFAD mice and the 5xFAD mice with QFY treatment. Moreover, Ruminococcaceae, Subdoligranulum, Bacteroides, Alistipes, Rikenellaceae_RC9_gut_group, and Odoribacter, which were lower in male 5xFAD mice, were improved after QFY intervention.

Discussion: The differential intestinal flora might improve the metabolism of brain tissue as well as muscle strength and coordination through Short-chain fatty acids (SCFAs). The differential metabolites caused by QFY intervention also have an improving effect on physiological frailty. We suggest that QFY exerts protective impacts against the physiological frailty in AD by adjusting the muscle-gut-brain axis.

Introduction: Mild cognitive impairment (MCI) represents the initial stage of dementia, and early diagnosis is crucial in clinical practice. This study aimed to investigate the predictive performance of three models based on clinical features, radiomics features of hippocampal T1-weighted imaging, and a combination of these features for identifying MCI in patients with secondary hydrocephalus.

Methods: Of the 378 patients with secondary hydrocephalus, 124 were ultimately included in the study and divided into two cohorts: those with Mild Cognitive Impairment (MCI, n = 49) and those without MCI (n = 75). The samples were randomly stratified into a training set (34 MCI and 52 non-MCI patients) and a validation set (15 MCI and 23 non-MCI patients). Radiomic features from the bilateral hippocampi were extracted based on the region of interest, and the optimal parameters were selected through dimensionality reduction. Predictive models were constructed using clinical data, radiomic data, and a combination of both, with the radiomic score being utilized. The performance of each model was then assessed in both training and validation sets. Additionally, the diagnostic performance of the optimal model was compared with that of the Montreal Cognitive Assessment (MoCA) Scale.

Results: In the clinical model, the disease course, serum uric acid, serum cystatin C, and the lateral ventricular temporal horn ratio emerged as independent risk factors for MCI following hydrocephalus. In the radiomics model, four optimal hippocampal features were identified. The AUC values for the clinical, radiomics, and combined models in the training/validation sets were 0.827 (0.736 ~ 0.919)/0.812 (0.666 ~ 0.957), 0.864 (0.790 ~ 0.937)/0.849 (0.724 ~ 0.974), and 0.937 (0.889 ~ 0.985)/0.907 (0.804 ~ 1.000), respectively. The combined model exhibited higher AUC values than the MoCA scale in both datasets. There was a significant difference in the training set, and while the validation set showed a consistent trend, it did not achieve statistical significance.

Conclusion: The combined model achieved optimal performance and demonstrated superior predictive capabilities for MCI in the patients with secondary hydrocephalus outperforming other models.

Background: Despite substantial progress in biomarker research, Parkinson's disease (PD) still lacks widely validated, easily deployable diagnostic tests for reliable early-stage detection, particularly in resource-limited circumstances.

Objective: This study aimed to develop and externally validate a lightweight machine learning model for the first-diagnosis prediction of PD using baseline cerebrospinal fluid (CSF) biomarkers from the Parkinson's Progression Markers Initiative (PPMI).

Methods: Baseline CSF data from 665 participants (PD = 415, controls = 190, SWEDD = 60) were used. Five machine learning classifiers-L2-regularized logistic regression (L2-LR), random forest (RF), histogram-based gradient boosting (HistGB), support vector machine with RBF kernel (SVM-RBF), and multilayer perceptron (MLP)-were trained and compared. Feature selection focused on five core CSF biomarkers (Aβ42, α-synuclein, total tau, phosphorylated tau181 and hemoglobin). Model performance was evaluated using AUC, PR-AUC, and Brier scores, followed by isotonic calibration and independent validation using the University of Pennsylvania dataset.

Results: A lightweight, biomarker-based RF model effectively distinguishes first-diagnosis PD cases using limited baseline CSF indicators. Its offline Streamlit deployment offers a practical tool for resource-limited settings, bridging the gap between computational prediction and real-world neurological diagnosis.

Introduction: Multicomponent exercise (MCE) is a promising strategy for enhancing cognitive function in older adults. This umbrella review aimed to synthesize and critically appraise the evidence from systematic reviews and meta-analyses on the effects of multicomponent physical exercise on cognition in this population.

Methods: An umbrella review of systematic reviews with or without meta-analysis was conducted. Six electronic databases (PubMed, Web of Science, Embase, Scopus, SPORTDiscus, and the Cochrane Library) were searched from their inception to September 2025 to identify eligible studies. The methodological quality of the included reviews was assessed using the AMSTAR-2 tool, and the overall certainty of the evidence for key outcomes was evaluated using the GRADE framework.

Results: The synthesis included 27 systematic reviews. MCE demonstrated consistently statistically significant, moderate positive effects on global cognitive function (SMD = 0.45) and executive function (SMD = 0.31). regarding memory, while the overall effect and verbal memory showed significant improvements, specific sub-domains such as working memory and delayed memory did not reach statistical significance. Similarly, no significant effect was observed for attention/processing speed. Despite these positive findings, the methodological quality of the majority of the included reviews (22 of 27) was rated as "Low" or "Critically Low" by AMSTAR-2. Consequently, the certainty of the evidence according to GRADE was predominantly "Low" to "Very Low" for most cognitive outcomes, with "Moderate" certainty achieved only for global cognitive function.

Conclusion: Multicomponent exercise is an effective intervention for improving global cognitive function and executive function in older adults. While benefits for specific memory domains and processing speed were less consistent, these findings support the clinical and public health promotion of MCE, while simultaneously highlighting an urgent need for more methodologically rigorous research to solidify the evidence base.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/ CRD420251161230, identifier CRD420251161230.

Objective: This study aimed to evaluate the diagnostic and prognostic value of the Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score, the Pan-Immune-Inflammation Value (PIV), and the Systemic-Immune-Inflammation Index (SII) in Alzheimer's disease (AD), exploring their association with dementia severity and their potential utility in diagnosis and monitoring disease progression.

Methods: In a retrospective case-control study, 261 AD patients and 176 healthy controls were enrolled. Propensity score matching (PSM) generated a balanced cohort of 176 patient-control pairs. Demographic, clinical, and hematologic variables were collected, including HALP, PIV, and SII, and dementia severity was assessed using the mini-mental state examination (MMSE). Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for AD, while spearman's correlation and receiver operating characteristic (ROC) curve analysis with bootstrap internal validation were used to evaluate the biomarker's performance.

Results: Following matching, AD patients exhibited significantly lower HALP and higher PIV and SII levels indicating a chronic pro-inflammatory state. HALP, PIV, and SII showed gradual but non-significant changes with dementia severity. HALP exhibited inverse correlation trend with dementia severity, though it did not reach statistical significance. Logistic regression identified education level and elevated neutrophil counts as independent risk factors of AD. ROC analysis revealed modest diagnostic performance for indices (AUC from 0.627 to 0.655), while combination of them did not significantly improve the diagnostic power.

Conclusion: HALP, PIV, and SII are promising blood-based biomarkers for AD diagnosis and progression monitoring. HALP may help track disease progression. These low cost, accessible composite inflammatory indices offer potential as adjunct tools for early detection and severity assessment in AD, especially in resource limited settings.

Alzheimer's disease (AD) involves progressive cognitive decline and neuropsychiatric symptoms that are strongly linked to neuroinflammation and aberrant hippocampal neurogenesis. We examined whether dexmedetomidine (Dex), a clinically used selective α₂-adrenergic agonist, could mitigate Aβ_1-42-induced pathology in mice. After intracerebroventricular Aβ_1-42 injection, animals were treated with Dex (25 or 50 μg/kg/day) for 7 days; a subgroup additionally received the α₂ antagonist Yohimbine. Behavioral tests showed improved memory performance across recognition and spatial paradigms, accompanied by reduced anxiety-like behavior in exploratory assays. Histological analyses with Nissl and doublecortin (DCX) staining indicated preserved neuronal integrity, fewer degenerating cells, and normalization of pathological neurogenesis. At the molecular level, Dex suppressed the expression of pro-inflammatory and apoptotic genes (CXCL2, IL-1β, iNOS, SPHK1) and lowered hippocampal malondialdehyde, consistent with reduced oxidative stress and improved cellular resilience. Yohimbine partly reversed these effects, supporting α₂-adrenergic involvement but leaving open the possibility of additional pathways contributing to the response. Overall, our results suggest that Dex protects against Aβ-driven injury through coordinated regulation of neuroinflammation, oxidative stress, and neurogenesis, underscoring its promise as a molecularly targeted candidate for early therapeutic strategies in AD management.

Introduction: Parkinson's disease (PD) has become the fastest-growing neurological disease worldwide. This network meta-analysis evaluated the efficacy of transcranial stimulation combined with four rehabilitation approaches for improving gait and motor function in Parkinson's disease.

Methods: We systematically searched seven databases: PubMed, Embase, Cochrane Library, Web of Science, CNKI, and Wanfang. Data from 23 randomized controlled trials (n = 669 patients) were analyzed using a frequentist network meta-analysis approach. Primary outcomes included gait parameters (velocity, cadence, stride length) and motor function (Timed Up and Go test, Unified Parkinson's Disease Rating Scale Part III). Statistical analyses incorporated the Surface Under the Cumulative Ranking curve rankings and sensitivity analyses.

Results: (1) For gait outcomes, Dual-Task Training showed optimal efficacy for improving stride length (SUCRA = 100%) and velocity (86.5%), while Exercise Rehabilitation best improved cadence (100%). (2) For motor function, Conventional Rehabilitation demonstrated superior improvement in the Timed Up and Go test (100%), and Dual-Task Training showed advantages in Unified Parkinson's Disease Rating Scale Part III scores (85.1%). All combined interventions significantly outperformed the control groups (p < 0.05), and sensitivity analyses confirmed the robustness of these findings.

Conclusion: The results support the use of personalized rehabilitation strategies: Dual-Task Training for patients with stride deficits and prominent motor symptoms, Exercise Rehabilitation for cadence improvement, and Conventional Rehabilitation for enhancing general mobility. These findings provide evidence-based guidance for optimizing neurorehabilitation protocols in the management of Parkinson's disease.

Objectives: To evaluate cognitive and mood changes 3 months after shunting for idiopathic normal-pressure hydrocephalus (iNPH), and compare postoperative outcomes with matched healthy controls across cognitive domains.

Methods: Thirty-three iNPH patients underwent neuropsychological testing preoperatively and at 3 months; 71 age-, sex-, and education-matched controls were assessed once. Tests were grouped into six cognitive domains.

Results: Shunting yielded significant gains in Verbal Memory and Psychomotor Pace; Executive Functions improved selectively. Non-Verbal Memory, Language, and Visuospatial Abilities showed no postoperative change. Depressive symptoms decreased significantly. However, at 3 months patients still performed worse than controls on all tests (all p < 0.001).

Conclusion: Shunt surgery produces measurable yet domain-limited cognitive benefits in iNPH at 3 months, particularly in verbal learning and processing speed, alongside mood improvement. Performance remains below healthy norms, indicating partial recovery. Larger, prospective cohorts and longer follow-up are needed to determine durability, breadth of cognitive change, and predictors of response.