Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder. Its pathogenic framework has evolved beyond the conventional amyloid-β (Aβ) cascade hypothesis toward a multifactorial interactive network model. Aβ, tau, neuroinflammation, synaptic dysfunction, the microbiota-gut-brain axis, and epigenetic regulation collectively form a complex pathological loop that drives progressive cognitive decline. In addition to cerebrospinal fluid and molecular imaging biomarkers, emerging blood-based biomarkers show considerable promise for clinical application. Therapeutic strategies targeting Aβ clearance have demonstrated disease-modifying effects, yet amyloid-related imaging abnormalities demand improved risk prediction and management. Concurrently, novel approaches including anti-tau antibodies, TREM2 agonists, and multi-target agents are advancing rapidly. Evidence also supports multimodal lifestyle interventions in delaying disease onset. Moving forward, elucidating the intricate interactions within AD pathological pathways using cutting-edge technologies, integrating and expanding the clinical implementation of multimodal biomarkers, and addressing therapeutic bottlenecks arising from pathological heterogeneity will be pivotal to achieving effective risk prediction, early detection and interception, and personalized treatment in AD.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by a long preclinical phase and a cascade of pathological events. With recent advances in blood and imaging biomarkers, the dynamic tracking of AD progression has become increasingly feasible. However, most studies have focused on single-modality markers, with limited integration across biological systems and time scales. This review adopts a time-dynamic perspective to summarize the longitudinal evolution of key blood biomarkers (e.g., Aβ42/40 ratio, p-tau217, NfL, GFAP) and imaging markers (e.g., Aβ-PET, Tau-PET, MRI) across the AD continuum. We compare the timing of initial abnormalities, progression patterns, and correlations with cognitive decline. Furthermore, we highlight integrative modeling approaches, including event-based models, and deep learning frameworks, which enable multi-modal risk prediction and individualized disease staging. The clinical potential of such integration in early screening, disease trajectory forecasting, and therapeutic decision-making is discussed, along with current limitations and future directions. This review provides a framework for developing dynamic, biology-driven precision diagnostic strategies in AD.

Accurate early diagnosis of Alzheimer’s disease (AD) represents a major challenge against the backdrop of global aging. This paper reviews research advances combining generative Artificial Intelligence (AI) with multimodal neuroimaging (including MRI and PET) to achieve early and accurate diagnosis of AD. This review systematically analyzes the applications of generative models in AD diagnosis across key areas: brain image data augmentation, pathological feature representation learning, and brain network modeling. We provide a detailed analysis of how these technologies effectively overcome critical challenges such as neuroimaging data scarcity and class imbalance. These technologies enhance the models’ classification performance on AD datasets and its ability to predict the progression of AD. Specifically, in the analysis of functional and structural brain networks, generative AI offers a new paradigm for understanding AD pathological mechanisms and enabling early prediction by constructing high-fidelity networks. Furthermore, this paper discusses the clinical translation prospects of these technologies in personalized prognosis and treatment monitoring, as well as the technical and ethical challenges in implementation. This review provides a comprehensive framework to understand the potential and development trends of generative AI, multimodal neuroimaging, and their derived functional brain network features in the auxiliary diagnosis of early AD.

Alzheimer's disease (AD) is a neurodegenerative disorder, by the time clinical symptoms manifest, irreversible pathological changes have already occurred in the brain; therefore, early diagnosis and intervention are critical to improving patient prognosis. With the advantages of being minimally invasive, convenient, and low-cost, blood-based testing has overcome the limitations of traditional diagnostic methods and has become a research hotspot in the early diagnosis of AD. Based on key domestic and international research findings in recent years, this paper systematically reviews the types, mechanisms of action, and relevant detection technologies of blood biomarkers for AD. The main biomarkers include core pathological markers (Aβ-related markers, phosphorylated tau protein), nerve injury markers (NfL, GFAP), and genetic risk markers (APOE ε4). Detection technologies cover fully automated immune detection platforms, high-sensitivity single-molecule array technology, and high-throughput detection techniques. As systematically reviewed, blood biomarkers and their detection technologies exhibit important clinical significance and application prospects in the early screening, accurate diagnosis, disease progression evaluation, and new drug development of Alzheimer's disease.

Deutetrabenazine, a deuterated derivative of tetrabenazine, has emerged as an effective treatment for Huntington's chorea and tardive dyskinesia. By selectively inhibiting vesicular monoamine transporter 2 (VMAT2), it reduces the synaptic release of dopamine and other monoamines, thereby alleviating involuntary movement symptoms. Compared to its precursor, deutetrabenazine demonstrates an improved safety profile, with significantly lower incidences of sedation and depression, enhancing patient adherence and suitability for long-term use. It is especially well-tolerated in vulnerable populations such as children and the elderly, showing better emotional stability and pharmacokinetic advantages. While its therapeutic potential is being explored in other neurodegenerative conditions like Parkinson's and Alzheimer's diseases, its current indications remain limited. Long-term administration poses challenges such as drug resistance and mood-related side effects, underscoring the need for psychological monitoring and individualized treatment plans. Furthermore, its high cost and inconsistent insurance coverage constrain global accessibility. Future strategies involving neuromodulation technologies, optimized reimbursement policies, and precision medicine approaches may expand its clinical utility and improve availability worldwide.

Alzheimer's disease (AD) is a complex neurodegenerative disorder caused by multiple factors, characterized primarily by the deposition of amyloid β-protein (Aβ) plaques and the formation of phosphorylated Tau protein neurofibrillary tangles in the brain, which together lead to memory loss and cognitive impairment. In recent years, microRNAs(miRNAs), as an essential class of non-coding RNA molecules, have demonstrated a pivotal role in the pathogenesis of AD. miRNAs tightly regulate the generation and clearance of Aβ by targeting key genes such as APP and BACE1. Meanwhile, specific miRNAs can significantly influence the phosphorylation state of Tau protein, exerting a profound impact on neuronal stability and survival. However, despite the enormous potential of miRNAs in AD research, numerous challenges remain. For instance, the differences in miRNA expression patterns between AD patients and healthy controls, as well as their biological significance and translational relevance, require further validation. Additionally, there is currently a lack of unified and accurate criteria for assessing the reliability of miRNAs as biomarkers, and miRNA-based therapies have not yet been approved for clinical use. Therefore, future research needs to further delve into the specific mechanisms of miRNAs in AD, systematically evaluate their potential as therapeutic targets, and actively overcome existing technical and methodological challenges, in order to provide new theoretical foundations and practical strategies for the diagnosis and treatment of AD.

Alzheimer's disease is a common neurodegenerative disease with pathological features including amyloid beta deposits and neurofibrillary tangles. Microglia-mediated neuroinflammation plays an important role in the occurrence and development of AD, mainly manifested by microglial activation and release of pro-inflammatory factors. Recent studies have found that microglia activate and differentiate into a variety of phenotypes and interact with Aβ and Tau, jointly affecting the pathology of AD. The expression of various inflammatory molecules in activated microglia is up-regulated, and NF-kB and NLRP3 are involved in the regulation. Recent treatments targeting microglia activation, phenotypic transformation, and inflammatory signals have been fruitful: new drug formulations such as LNP have enhanced the ability to penetrate the blood-brain barrier, and many natural ingredients derived from Chinese herbal medicines have also been effective. In this review, we will introduce the pathogenesis and treatment of AD from two aspects: activation and phenotypes of microglia, and activation of microglia-related inflammatory molecules(mainly NF-kB and NLRP3).

Objective: To evaluate and summarize the relevant evidence for the management of mild cognitive impairment in patients with Parkinson's disease, and provide evidence-based support for the development of scientific and effective management of mild cognitive impairment in Parkinson's disease. Methods: According to the "6S" model of evidence-based resources, the author systematically searched guidelines, expert consensus, clinical decision, evidence summary and systematic review on the management of mild cognitive impairment in Parkinson's disease patients from domestic and foreign guide websites, professional association websites and databases. The search period is up to December 2024. Literature quality assessment, evidence extraction and summary were conducted by two researchers trained in evidence-based systems. Results: A total of 14 literatures were included, including 6 guidelines, 5 expert consensus articles and 3 systematic reviews. The 34 evidences were summarized from 7 aspects: assessment object and time, assessment content and screening tool, risk factor management, safety management, medication management, non-drug intervention and follow-up management. Conclusion: This study systematically summarizes evidences in the field of mild cognitive impairment management in patients with Parkinson's disease, which can provide scientific reference for clinical nursing staff's practice. Nursing staff should select evidence based on the actual clinical situation and individual factors of patients to guide Parkinson's patients to improve mild cognitive impairment.

Senile dementia has attracted much attention due to its complex pathogenesis and the increasing incidence rate along with the aging population. Currently, modern medicine is confronted with problems such as low early recognition rate, limited treatment methods and high costs. In contrast, traditional Chinese medicine (TCM) has advantages in emphasizing syndrome differentiation and treatment, as well as treating different diseases with the same therapy. In recent years, many studies on the treatment of different syndrome types of senile dementia with Chinese patent medicines have been published. Based on the core pathogenesis theory of "deficiency at the root and excess at the surface" in TCM, this article screens the existing research literature on clear syndrome types of this disease, aiming to provide evidence-based support for the clinical application of Chinese patent medicines.

Alzheimer's disease (AD) is a chronic neurodegenerative disease with an insidious onset, often occurring in old age or pre old age. The main symptoms of the disease are a decline in memory and cognitive function, accompanied by language disorders, spatial orientation disorders, and behavioral impairments. AD is a common type of irreversible dementia, and its pathophysiological processes are initiated decades before clinical symptoms appear. Therefore, exploring biomarkers that can reveal early functional changes in AD and establishing objective and accurate auxiliary diagnostic tools have become the forefront and core of current research. Resting state functional magnetic resonance imaging (rs-fMRI) provides a unique window for non-invasive, in vivo evaluation of the functional integration and separation characteristics of large-scale brain networks by capturing spontaneous fluctuations in blood oxygen level dependent signals. This article reviews the research on combining artificial intelligence technology (AI) with rs-fMRI to achieve early auxiliary diagnosis of AD. This review first systematically introduces the biomarker potential of rs-fMRI in early diagnosis of AD; Secondly, the AI methodology applied to rs-fMRI analysis was elaborated, and the evolution of these AI methodologies, as well as multimodal fusion and interpretable AI strategies, were analyzed in detail; Finally, this article discusses the current challenges of these technologies, such as model generalization, data heterogeneity, interpretability barriers, and clinical translation obstacles, and provides prospects for the future development of this field. The deep integration of AI and rs-fMRI is driving a profound transformation in the early diagnosis of AD from an experience-based paradigm toward a data-driven, quantitative, and personalized paradigm. It will assist clinical doctors to cultivate and optimize medical decision-making, improve clinical diagnosis and treatment levels, and promote precision medicine.

Objective: To obtain the clinical basis for non-drug intervention in mild cognitive impairment (MCI) by exploring the efficacy of auricular acupuncture combined working memory (WM) training in patients with MCI. Methods: A total of 40 MCI patients who were hospitalized in the Department of Geriatrics at Hangzhou Wuyunshan Hospital from January to December 2023 were included and randomly divided into an observation group of 20 patients who received 3-week WM training and a control group of 20 patients who did not receive training by drawing lots. The Montreal Cognitive Assessment (MoCA) was used to evaluate the patients' cognitive function. Results: Before training, there was no significant difference in cognitive function between the two groups(P>0.05). In the observation group, the visual-spatial and executive ability and MoCA total scores of patients followed up for 6 months after training were higher than those before training, and the difference was statistically significant (P<0.05). After training, followed up for 6 months, the visual-spatial and executive function and MoCA total scores of patients in the observation group were higher than those in the control group, and the difference was statistically significant (P<0.05). Conclusion: Auricular acupoint stimulation combined with WM training can improve some cognitive functions in MCI population.

Objective: To evaluate clinical phenotypes and nocturnal sleep structure characteristics with mild cognitive impairment due to Alzheimer's disease (AD). Methods: Based on cerebrospinal fluid or positron emission tomography imaging to detect the concentration or deposition status of β-amyloid protein (Aβ) to distinguish between MCI due to AD and control group. All patients underwent polysomnography monitoring (PSG), APOE gene testing, Montreal Cognitive Assessment (MoCA), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD) assessments. Results: ① Significant differences were found in clinical characteristics such as sleep disturbance, body mass index (BMI), education years, occupations, combined with risk factors, and APOEε4 gene mutation (P<0.05); ② There were statistically significant differences in MoCA and HAMA scores between these two groups (P<0.05); ③Significant differences in N1/total sleep time (TST)%, N2/TST%, N3/TST% and rapid eye movement sleep time (REM)/TST%, average blood oxygen concentration during night-sleep time, sleep-related apnea-hypopnea index (AHI), obstructive sleep apnea (OSA) index between these two groups (P<0.05); ④Clinical phenotypes including sleep disorders, APOEε4 mutation, multiple risk factors, cognitively demanding occupations and sleep microstructural parameters were significantly correlated with MCI due to AD (P<0.05); ⑤Gender, sleep disturbance, APOEε4 gene mutation, BMI and polysomnographic indices (N1/TST%, N2/TST%, REM/TST% and OSA index) were key factors in MCI due to AD (P<0.05); ⑥N1/TST%, N2/TST%, REM/TST% and OSA index demonstrated significant linear correlations with MoCA scores (P<0.01). Conclusion: Patients with MCI due to AD exhibited distinct clinical features, including a higher prevalence of sleep disorders, elevated APOEε4 allele carrier rates, lower prevalence of multiple risk factors, a higher proportion of cognitively demanding occupations and lower BMI. Sleep parameters, including N1/TST%, N2/TST%, REM/TST% and OSA index, demonstrated significant correlations with cognitive impairment. Characteristic changes in the proportion of N1, N2 and REM sleep among MCI patients may serve as potential biomarkers for early identification of MCI due to AD.

Alzheimer's disease (AD) represents a major global health challenge. In recent years, driven by big data and cutting-edge technologies, precision medicine has been guiding AD research and practice through a profound transformation. The core of this shift moves away from a reactive, symptom-based, "one-size-fits-all" model towards a new paradigm of precise diagnosis and treatment grounded in biological evidence and aimed at early disease modification. This review systematically explores the latest advances in early prevention, diagnosis, and treatment of AD within this framework, aiming to provide new perspectives and feasible pathways towards ultimately conquering the disease.

Objective: To comprehensively evaluate the effectiveness of driving ability as a predictor for Alzheimer's disease (AD), explore relevant data collection and analysis methods, and identify valid early warning indicators. Methods: Computerized searches were conducted in databases including CNKI, CBM, Wanfang, VIP, PubMed, and Web of Science to identify studies using driving ability for AD prediction. Literature meeting inclusion criteria was screened, and data quality was assessed. Relevant information was extracted, and heterogeneous data were integrated. Principal component analysis (PCA) was used to evaluate the importance of indicators in the driving-based warning system. Meta-analysis was performed to assess the effect of AD on driving ability. Subgroup analysis was conducted to reduce intergroup heterogeneity, with stratification based on age, gender, and Mini-Mental State Examination (MMSE) scores to examine differences in effects across groups. A multifactorial interaction subgroup analysis was further proposed to minimize intergroup heterogeneity, analyzing the combined influence of age, gender, and MMSE scores on statistical outcomes. Results: After screening, 12 studies were included. PCA results identified the three most significant indicators: spatial control (9.13%), emotional adaptation (8.78%), and navigation execution (8.36%). Meta-analysis and subgroup analysis revealed that older female patients with low MMSE scores exhibited the most severe driving-related cognitive impairment (SMD = -0.75, P < 0.001). Additionally, among male AD patients, the high-score MMSE group showed a greater absolute effect size (ΔSMD = -0.22, P < 0.001). Multifactorial interaction subgroup analysis explained 78% of the heterogeneity (Q = 12.37, P = 0.006). Conclusion: This study provides preliminary evidence that abnormal driving behavior can serve as a novel biomarker for early AD detection, with spatial orientation, emotional stability, and navigation ability identified as core indicators. However, the warning system must account for population differences (higher sensitivity in older females) and individual baseline variations (longitudinal self-referencing).

Objective: To examine the clinical manifestations, imaging features, potential pathological mechanisms, differential diagnosis, and clinical significance of atypical Alzheimer's disease (AD), with the objective of enhancing comprehension of atypical AD and elevating the standard of clinical diagnosis. Methods: The clinical manifestations, laboratory findings and imaging features, and differential diagnosis of three patients with atypical AD were reviewed, and their pathological mechanisms were analyzed accordingly. Results: There was a decrease in Aβ and an increase in Tau in all three patients' cerebrospinal fluid (CSF) tests. The patient with frontal variant of AD (FvAD) started with memory loss and mental behavior abnormalities, and the brain Magnetic Resonance Imaging (MRI) showed symmetrical atrophy of bilateral frontal lobe, temporal lobe, parietal cortex and hippocampus. The patient with logopenic variant primary progressive aphasia (LvPPA) has the onset of speech clumsiness. Brain MRI shows that the left lateral fissure is wider than the right, and bilateral hippocampal atrophy is relatively mild. The patient with posterior cortical atrophy (PCA) presented with memory loss and visuospatial impairment. Brain MRI showed bilateral partooccipital lobe atrophy, widening of the right lateral fissure, and relatively mild bilateral hippocampal atrophy. Conclusions: Atypical AD are starting with speech impairment, mental behavior abnormalities, and visuospatial disorders. Because the dysmnesia symptoms of atypical AD are not typical, it is not easy to identify them early, and it is easy to be confused with frontotemporal dementia, cortical basal ganglia degeneration and Lewy body dementia. The clinical diagnosis requires a comprehensive consideration of detailed medical history and neurological examination, combined with neuropsychiatric scales, imaging, and biomarkers.

Objective: To explore the association between the levels of adaptor protein complex 2 (AP2) in cerebrospinal fluid (CSF) of patients with Alzheimer's disease (AD) and AD pathology, brain structural changes, and cognitive function. Methods: This study enrolled 138 patients with Alzheimer's disease (AD), 403 patients with mild cognitive impairment (MCI), and 167 cognitively normal (CN) subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Levels of AP2 (α2 and β1 subunits) in the cerebrospinal fluid (CSF) were measured. Data on core AD biomarkers, including amyloid-beta 1-42 (Aβ₄₂), total tau protein (t-Tau), and phosphorylated tau at threonine 181 (p-Tau₁₈₁), brain structural measures including ventricular volume, hippocampal volume, and entorhinal cortex thickness, and cognitive scores, including the Mini-Mental State Examination (MMSE) and the Clinical Dementia Rating - Sum of Boxes (CDRSB) were collected at baseline and over a five-year follow-up period. Statistical analyses were performed using one-way analysis of covariance, multiple linear regression models, and linear mixed-effects models. Results: At baseline, there were no significant differences in CSF AP2 levels among the CN, MCI, and AD groups, but they were significantly elevated in apolipoprotein (APOE) ε4 carriers. CSF AP2 levels increased with age, consistent with AD pathology progression. Elevated CSF AP2 levels were significantly associated with increased CSF Aβ42, T-tau, and p-Tau181 concentrations and smaller ventricular volume, especially in the CN and MCI stages. CSF AP2β1 was negatively correlated with CDRSB and positively correlated with hippocampal volume and entorhinal cortex thickness. Additionally, CSF AP2 affected longitudinal changes in brain structure and cognition, particularly in the non-AD group. Conclusion: CSF AP2 may be involved in early Aβ and tau pathology and is closely related to changes in ventricular volume, hippocampal volume, entorhinal cortex thickness, and cognition, especially in the preclinical and prodromal stages of AD.

Objective: To analyze the differences in the triglyceride-glucose index (TyG) and its combination with obesity indicators in the assessment of cognitive function, and to further explore their mediating effects between physical activity (PA) and cognitive function. Methods: Questionnaires of the physical examination population in Youyi Road Community Health Service Centre for Baoshan District, Shanghai from April to December 2020 were collected. A total of 3937 subjects were included. The association between PA and cognitive function, the association between TyG and its combined obesity indicators and cognitive function were analyzed using generalized linear regression models, and gender stratified analysis was conducted. The mediating effects of TyG and its combined obesity indicators in the relationship between PA and cognitive function were evaluated using the mediation models. Results: After full adjustment, there was a significant association between PA and cognitive function (β=0.337, P < 0.05), and the trend of the analysis results in men was consistent with that of the total population (β=0.374, P < 0.05). There was no significant association between TyG and the mini-mental state examination (MMSE) score in the total population. Compared with TyG-body mass index (TyG-BMI) and TyG-waist circumference (TyG-WC), the association between TyG-waist-to-height ratio (TyG-WHtR) and MMSE score was significantly enhanced (β=-0.588, P < 0.001), and the results of the gender subgroup analysis were consistent with those of the total population. TyG-BMI, TyG-WC and TyG-WHtR all played significant mediating roles between PA and cognitive function, among which the mediating effect of TyG-WHtR was the strongest (9.81%, P < 0.05). Conclusion: There is a significant association between PA, TyG and its combination with obesity indicators and cognitive function. TyG-BMI, TyG-WC and TyG-WHtR all played significant mediating roles between PA and cognitive function, and TyG-WHtR plays the strongest mediating role in the association. The TyG-obesity combined indexes provide basis for formulating cognitive function protection strategies for individuals with metabolic abnormalities..

Objective: To evaluate the clinical efficacy of low-frequency transcranial magnetic stimulation (TMS) combined with mirror therapy (MT) in patients with hemiplegia and cognitive impairment following hemorrhagic stroke.Methods: Between February 2022 and February 2025, 92 patients with hemiplegia and cognitive impairment following hemorrhagic stroke admitted to our hospital were enrolled. They were randomly assigned to either the TMS group or the combined group, each comprising 46 subjects. The TMS group received conventional therapy plus low-frequency TMS, while the combined group added mirror therapy to the TMS regimen. Upper limb motor function, balance function, neurophysiological indicators, cognitive function, and activities of daily living were compared between the two groups. Results: Baseline upper limb FMA, BBS, MMSE, MBI scores, MEP amplitude, and CMCT were comparable between the TMS and combined groups, with no statistically significant differences (P > 0.05). After 4 weeks of treatment and 1 month post-treatment, both groups showed significant improvements in upper limb FMA, BBS, MMSE, and MBI scores compared to baseline (P < 0.05). Post-treatment scores in the combined group were significantly higher than those in the TMS group (P < 0.05). Additionally, at 4 weeks and 1 month post-treatment, the combined group showed greater improvements in MEP amplitude and CMCT (P < 0.05). Conclusion: Combined TMS and MT therapy promotes upper limb motor function and balance recovery in patients with hemiplegia and cognitive impairment following hemorrhagic stroke. It improves neuroelectrophysiological indicators, enhances cognitive function, and increases activities of daily living capabilities.

Objective: To study the effect of pramipexole hydrochloride in the treatment of Parkinson's disease and its influence on neurological function and adverse reactions. Methods: A total of 80 patients with Parkinson's disease in our hospital from February 2021 to May 2025 were selected and randomly divided into control group and pramipexole hydrochloride group, 40 cases in each group. The pramipexole hydrochloride group was treated with pramipexole hydrochloride tablets, and the control group was treated with placebo. The neurological function of the patients was evaluated by the Parkinson's disease autonomic nervous symptoms scale (SCOPA-AUT), and the clinical efficacy and quality of life were evaluated by the Unified Parkinson's Disease Rating Scale (UPDRS) and quality of life score. The levels of dopamine, norepinephrine (NA), serotonin (5-HT) and epinephrine were detected by high performance liquid chromatography. The level of superoxide dismutase (SOD) was detected by xanthine oxidase method, the level of glutathione (GSH) was detected by colorimetric quantitative analysis, and the level of malondialdehyde was detected by thiobarbituric acid colorimetric analysis. The incidence of adverse reactions was counted. Results: After treatment, the scores of SCOPA-AUT and UPDRS in pramipexole group were significantly lower than those in the control group, and the quality of life score was significantly improved (P<0.05). In pramipexole group, the levels of serum polyamine, Na, 5-HT, GSH and SOD increased, while the levels of epinephrine and MDA decreased (P<0.05). There was no significant difference in the incidence of adverse reactions between the two groups (P>0.05). Conclusion: Pramipexole hydrochloride can improve the neurological function and antioxidant stress state of patients with Parkinson's disease, with good safety.

Objective: To evaluate the effectiveness of caregiver group support skills training on coaches' attitudes towards dementia care and their sense of competence. Methods: A total of 56 participants in the dementia caregiver group support skills training (referred to as "coaches"; 10 male and 46 female) completed assessments of their dementia care attitudes and sense of competence before and after the training. Paired t-tests were used to compare the differences in scores for dementia care attitudes and sense of competence before and after the training. Multivariate analysis was conducted to explore the demographic factors associated with the changes in dementia care attitudes and sense of competence. Results: After the training, coaches showed a significant increase in scores for the "hope" and "personhood validation" factors of the dementia care attitude scale, as well as the total scale score (P < 0.05). Additionally, scores for the "professionalism," "relationship building," "managing caregiving challenges," and "maintaining personhood" factors of the dementia care competence scale, as well as the total scale score, significantly increased after the training (P < 0.05). Multivariate analysis indicated that only the occupation was associated with changes in the total score and "relationship building" factor of dementia care competence before and after the training; no other sociodemographic characteristics were associated with the changes in dementia care attitudes and other factors of competence scale. Conclusion: Caregiver group support skills training can improve coaches’ attitudes towards dementia care and enhance their sense of competence in caregiving.

Objective: To conduct a meta-analysis on the incidence of frailty in patients with Alzheimer's Disease (AD), in order to provide a scientific basis for the prevention of frailty in AD patients. Methods: By systematically searching CNKI, Wanfang, VIP Chinese databases, PubMed, Web of Science, Embase and Cochrane Library English databases, the epidemiological evidence of the incidence of frailness in AD patients was comprehensively obtained. The literature search period was set from the establishment of the database to March 10, 2025, and literature screening, data extraction and bias risk assessment were carried out by two researchers respectively. Statistical software Stata14.0 was used to conduct a meta-analysis of the included studies. Results: Thirteen studies were included, covering 2806 patients with Alzheimer's disease, and the analysis suggested an overall incidence of frailty of 34% (95%CI: 27%~41%). Study area, measurement tool, study time, sample size and other factors have an impact on the incidence of frailty in patients with Alzheimer's disease. Conclusion: The incidence of frailties in patients with Alzheimer's disease is high. Attention should be paid to frailties in patients with Alzheimer's disease, and early detection and intervention measures should be taken to reduce the occurrence of frailties in this population.

Objective: To assessment of the incidence and risk factors of cognitive decline in maintenance hemodialysis (MHD) patients. Methods: A total of 89 MHD patients and 30 Non-dialysis individuals with matched age and sex in the same community were enrolled. The cognitive functions of MHD patients and Non-dialysis individuals were evaluated by mini-mental State Examination (MMSE). The values below 27 indicative of cognitive impairment, which was corrected by the educational background. The clinical data, previous medical history, biochemical indicators of malnutrition, bone mineral metabolism and inflammation were evaluated. Logistic regression analysis was performed to find out the risk factors of cognitive decline in MHD patients. Results: Out of 89 enrolled MHD patients, 43.8% were classified with cognitive impairment, significantly higher than that in the healthy individuals group (13.3%, P=0.003). In the cognitive impairment group, age and MCV were significantly higher than that of the normal cognitive group, and the HDL was significantly lower than that of the normal cognitive group (P<0.05). Further analysis found that the scores in all fields of the cognitive impairment group were significantly lower than those with normal cognitive function, especially in attention, computational power and language ability (P<0.05). The results of logistic regression analysis showed that age(β=-0.110, P=0.008), MCV(β=-0.168, P=0.022) and HDL(β=3.071, P=0.038) were the independent risk factors affecting cognitive impairment in MHD patients. Conclusion: The incidence of cognitive impairment in MHD patients was significantly higher than that in matched healthy individuals in the same community. Age, MCV and HDL were independent risk factors for cognitive impairment in MHD patients.

In the context of an aging society, the management of chronic diseases in patients with dementia has become a public health issue that requires urgent attention. This article expounds the current situation of chronic disease management for dementia, analyzes the characteristics of dementia, the process of chronic disease management for dementia, and the management characteristics in medical care institutions. It proposes a series of targeted countermeasures and suggestions from multiple aspects,including improving cognitive abilities, optimizing medication management, managing behavioral and psychological symptoms of dementia (BPSD), building care systems, promoting health, and prevention. These efforts aim to provide new ideas and references for the chronic disease management of dementia patients, aiming to provide more comprehensive and effective chronic disease management services for patients with dementia, improve their quality of life, reduce the burden on families and society, and provide work ideas and references for the management of chronic diseases in elderly dementia patients in China.

Objective: To explore the impact of geriatric syndrome on cognitive function in patients with mild cognitive impairment. Methods: This study included 422 elderly people who completed outpatient physical examinations at Hangzhou Wuyunshan Hospital from January to December 2022. All subjects were evaluated using the Montreal Cognitive Assessment (MoCA) and the Comprehensive Geriatric Assessment (CGA). The clinical data and geriatric syndromes of the two groups were compared, and the impact of geriatric syndromes on cognitive function in patients with mild cognitive impairment was observed. Results: A total of 422 elderly patients were enrolled, with 157 in the observation group (MoCA < 26) and 265 in the control group (MoCA ≥ 26). The observation group had significantly lower decreased grip strength, decreased calf circumference, 3-meter stand and walk, normal gait speed, comorbidity index, number of teeth, dentures, dental problems affecting eating, gum pain, and sleep disturbances than the control group (P < 0.05). Binary logistic regression analysis showed that comorbidity index (OR = 2.093, P = 0.012), decreased grip strength (OR = 19.488, P < 0.001), dental problems affecting eating (OR = 4.591, P = 0.001), gum pain (OR = 2.798, P = 0.009), and sleep disturbances (OR = 2.253, P = 0.031) were risk factors for cognitive function in patients with MCI. The number of teeth (OR = 0.740, P < 0.001) and wearing dentures (OR = 0.021, P < 0.001) were protective factors for cognitive function in patients with MCI. Conclusion: Geriatric syndrome has a certain degree of impact on the cognitive function of MCI patients. CGA should be emphasized in the MCI population and attention should be paid to geriatric syndrome to improve the quality of life of the elderly.

Alzheimer's disease is a neurodegenerative disorder characterized by β-amyloid deposition and pathological phosphorylation of tau protein. Traditional population-level sequencing has been limited in resolving the highly heterogeneous cellular populations and their spatiotemporal dynamics in brain tissue due to resolution constraints. In recent years, single-cell sequencing technologies—including single-cell RNA sequencing, single-cell assay for transposase-accessible chromatin sequencing, single-cell whole-genome sequencing, and spatial transcriptomics—have overcome these limitations. These technologies enable systematic exploration of subpopulation heterogeneity and pathological response mechanisms in neurons, microglia, astrocytes, and oligodendrocytes at single-cell resolution, offering novel insights into the cellular and molecular mechanisms underlying Alzheimer's disease. Studies demonstrate that single-cell RNA sequencing combined with spatial topological information can map cell-specific distributions of β-amyloid plaques and neurofibrillary tangles. Multi-omics integrative analyses have revealed the epigenetic mechanisms by which APOE ε4 regulates microglial phagocytic function and delineated the brain-gut axis and neuroinflammatory network atlas. Although single-cell technologies still face challenges in sensitivity, cost, spatial resolution, and data analysis, their integration with artificial intelligence algorithms and high-throughput microfluidic platforms is driving a paradigm shift in Alzheimer's Disease research—from pathological description to systems biology and precision medicine. Future advancements in detection efficiency, multi-omics integration, three-dimensional spatial mapping, and clinical validation are essential to enable ultra-early diagnosis and personalized therapies for Alzheimer's Disease. This review systematically summarizes the progress of single-cell sequencing technologies in elucidating key cell types in AD and discusses their technical limitations and future prospects.

Objective: To evaluate the predictive performance of biomarkers for the conversion of mild cognitive impairment（MCI） to Alzheimer's disease（AD）. Methods: A literature review summarized the predictive accuracy of individual and combined biomarkers for MCI-to-AD progression.Results: CSF amyloid-beta 42（Aβ42） showed 81% sensitivity at 64% specificity, while Aβ-PET sensitivity ranged 83%-100% and specificity 46%-88%. Phosphorylated Tau217 （P-tau217） had an accuracy of 0.88. Medial temporal lobe MRI demonstrated 0.65-0.7 sensitivity and 0.64-0.68 specificity. CSF total tau（T-tau） showed 75% sensitivity at 72% specificity, and FDG-PET 76% sensitivity at 82% specificity. Plasma neurofilament light chain（NfL） had high sensitivity （98.1%） but low specificity（16.1%）, accuracy 0.631; plasma GFAP accuracy was 0.77-0.84. Multi-biomarker models achieved accuracy 0.72-0.96, sensitivity 0.56-0.85, and specificity 0.56-0.91. Conclusions: Aβ biomarkers showed higher sensitivity than FDG-PET, while FDG-PET had higher specificity. Multi-biomarker combinations, particularly cognitive scales with MRI, provided superior prediction for MCI-to-AD conversion.

Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder. Air pollution, characterized by its complex composition, diverse pollutant types, and significant spatiotemporal variability, poses both localized and long-range threats due to atmospheric transport. Certain pollutants exhibit persistence and bioaccumulative properties, exerting profound impacts on human health and social equity. These effects are further modulated by natural geographical and meteorological conditions, rendering them uniquely complex. An increasing body of evidence identifies air pollution as a significant environmental risk factor for AD. In response to growing interest, this paper provides a comprehensive review of the epidemiological evidence, pathophysiological mechanisms, and emerging methodological approaches related to air pollution's role in AD. Furthermore, it explores how compounded social determinants interact with environmental exposure to influence AD risk.

Objective: To explore the real-world application performance of the urine β-amyloid protein detection kit in screening the risk of cognitive decline in multiple hospitals and communities in China. Methods: In this study, the clinical values of One-Step Dementia Risk Test Kit in early screening were further validated by community health screening in Changsha （n=51 187） and a multi-center, case-control study with a total of 898 participants including 266 healthy age-matched controls, 167 MCI/AD patients and 465 non-AD patients with various comorbidities and age-related diseases. Results: The number of weak positive/ positive/negative in the healthy, non-AD and MCI/AD group was 8/12/246 （positivity 7.52%）, 41/16/409 （12.23%） and 77/44/46 （72.46%）, respectively, resulting in a Kappa value of 0.669 which indicated a good diagnostic performance. Comorbidity analysis identified memory decline as the most significant risk factor （P = 9.6×10^-23, Fisher's Exact Test）, followed by hyperlipidemia （P = 3.2×10^-12）, history of stroke （P = 0.0011） and hypertension （P = 0.00058）. Therapeutics analysis showed medications for cardiovascular diseases and anti-thrombosis significantly reduced risk of dementia （P = 0.0061 and 0.0081, respectively）. For AD patients, only patients receiving memantine treatment showed a slight reduction in kit positivity （P = 0.0532）. The kit also showed a clear age-dependent increase of positivity from 6.29%-15.40%, in health screening. Conclusions: Our results confirmed the diagnostic value of the kit in MCI and AD-dementia. Moreover, the kit can be used in the real world to assess the risk of various conditions towards AD as well as the treatment efficacy.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by gradual decline in cognition and daily functioning. Its pathological basis involves β-amyloid (Aβ) deposition, tau hyperphosphorylation, neuroinflammation, and synaptic dysfunction. This review summarizes recent advances in integrative Chinese and Western medicine for AD. In Western medicine, symptomatic pharmacotherapy remains the cornerstone, mainly included cholinesterase inhibitors and N-methyl-D-aspartate (NMDA) receptor antagonists, while disease-modifying strategies targeting Aβ（such as anti-Aβ monoclonal antibodies) are being actively explored. In addition, non-pharmacological interventions, including cognitive training, transcranial magnetic stimulation (TMS), and comprehensive management of modifiable risk factors, are widely applied to slow functional decline and optimize long-term care. From the perspective of traditional Chinese medicine (TCM), AD is generally considered a condition with "root deficiency and branch excess," with kidney essence deficiency as the root and phlegm turbidity and blood stasis as major contributing factors; common syndromes include kidney essence deficiency and phlegm obstruction of the orifices. TCM interventions such as herbal formulas and bioactive constituents may exert multi-target effects by modulating Aβ-related processes, reducing oxidative stress and inflammatory responses, and improving synaptic plasticity. Acupuncture has also been reported to benefit cognitive performance potentially through improving cerebral perfusion and regulating neural networks. Available clinical studies suggest that combining Chinese herbal medicine and/or acupuncture with standard Western therapy may improve cognitive scale scores, activities of daily living, and neuropsychiatric symptoms. Regarding outcome assessment, beyond conventional scales such as the Mini-Mental State Examination (MMSE), integrating biomarker-based evaluation (e.g., Aβ and tau-related biomarkers) with TCM syndrome differentiation may help refine stratification and monitoring of therapeutic response. Future research should prioritize high-quality clinical studies with standardized outcome measures and longer follow-up to strengthen evidence for integrative management strategies in AD.

Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder characterized by progressive memory loss and cognitive decline. Sleep disorders, recognized both as an early clinical manifestation and as an important risk factor for AD, have attracted increasing attention in recent years. A growing body of evidence indicates that impaired sleep quality and reduced sleep duration are closely associated with the accumulation of amyloid-β (Aβ) and tau protein in the brains of AD patients. Microglia, the resident immune cells of the central nervous system, play pivotal roles in maintaining neural homeostasis, clearing Aβ, and regulating neuroinflammation. Sleep disturbances can activate microglia by disrupting circadian rhythms and inducing inflammatory responses, driving them toward a pro-inflammatory phenotype while impairing their phagocytic and clearance capacities. These alterations exacerbate Aβ deposition, promote tau pathology, and thereby accelerate AD progression. This review systematically summarizes current findings on the interplay among sleep disorders, microglial dysfunction, and AD pathogenesis, with a particular focus on mechanistic links and bidirectional regulation. In addition, we highlight recent advances in non-pharmacological interventions, pharmacotherapies, and related emerging regulatory strategies targeting sleep disorders and AD. A deeper understanding of these mechanisms may provide early clues for AD onset and offer novel targets for its prevention and treatment.

To report a case of Alzheimer's disease (AD) mainly manifesting as corticobasal syndrome, share the diagnosis and treatment experience, and improve clinicians' understanding of this atypical type of AD. The medical history, results of neurocognitive assessment tests, and cranial structure and molecular neuroimaging data of a patient with corticobasal syndrome due to Alzheimer’s disease (AD-CBS) were collected, and discussions were made referring to relative articles. The patient mainly presented with motor dysfunction, apraxia and alien limb phenomenon of the left limb, accompanied by progressive cognitive impairments and sensory somatic cortical disorder. Cranial magnetic resonance imaging (MRI) showed obvious atrophy of the right parietal lobe, and cranial positron emission tomography (PET) showed abnormal deposition of Aβ and tau in the cerebral cortex, which was consistent with the characteristic manifestations of AD-CBS. Corticobasal syndrome (CBS) is mainly characterized by asymmetric atrophy of the cortex and extrapyramidal symptoms clinically. Due to the relatively late onset of cognitive impairment compared to motor dysfunctions, it is prone to misdiagnosis. Early diagnosis and medication can help slow the progression of AD-CBS. Meanwhile, due to the diverse causes of CBS, neuroimaging and laboratory examinations are required for differential diagnosis in clinical practice, and the possibility of co-pathology should be considered, raising the importance of long-term follow-up.

Objective: To observe values of the third generation sequencing（TGS）in detecting tandem repeats of NIID（neuronal intranuclear inclusion disease). Methods: Peripheral blood samples were collected from 10 confirmed NIID patients (confirmed group), 10 clinically suspected cases (suspected group), and 10 healthy controls (control group) between January 2017 and December 2023. The NOTCH2NLC GGC repeats were amplified by long-range PCR (LR-PCR) and repeat-primed PCR (RP-PCR). The amplification products were first screened using capillary electrophoresis (CE). Results: The ten confirmed cases were again found with clinically significant GGC repeats in all cases, but in the earlier testing lab and the current testing lab the exact sequence repeats number were not available in 2 cases when the repeats were estimated to be more than 110. In the suspected group, there were 4 cases found with significant GGC repeats, but there were also two cases where CE platform could not give exact numbers of GGC repeats when the repeat numbers were estimated to be more than 110. In contrast,TGS could give exact numbers of GGC repeats, including the four cases where CE could not give the exact numbers of GGC repeats. There were no false positive or negative result in either platforms.Conclusions: This study confirms that TGS effectively overcomes the technical limitations of CE in quantifying highly repetitive sequences in NIID, enabling precise quantification and structural resolution of sequences, thereby providing more reliable technical support for molecular subtyping and precise diagnosis and treatment of NIID.

Objective: To retrospectively investigate the correlation between the monocyte to high-density lipoprotein cholesterol ratio（MHR）, tumor necrosis factor（TNF-α）, and brain-derived neurotrophic factor （BDNF） levels in the serum of early stroke patients and post-stroke cognitive impairment（PSCI）, and to explore the role of early serum MHR, TNF-α, and BDNF levels in predicting and evaluating PSCI. Methods: Stroke patients who were hospitalized in the Department of Neurology of the Fourth People's Hospital of Wujiang District, Suzhou City from January 2022 to June 2025 and returned to our hospital for follow-up within 6 months were selected. The cognitive function of all patients was evaluated using the Mini-Mental State Examination（MMSE）. According to the MMSE results and educational background, the patients were divided into the PSCI group and the non-PSCI group. All patients had detailed blood tests. The differences in MHR, TNF-α, and BDNF levels between the two groups were statistically analyzed. Results: A total of 60 patients were collected, with 30 patients in each group. Statistical analysis showed no significant differences in gender, age, and MHR between the two groups. There were significant differences in TNF-α and BDNF levels between the two groups（P<0.05）. Pearson correlation analysis showed that TNF-α level was negatively correlated with MMSE score （rs = -0.256, P = 0.048）, while BDNF level was not correlated with MMSE score （rs=0.198,P=0.129）. Logistic regression analysis showed that TNF-α （P<0.05, OR=0.903, 95% CI: 0.854 - 0.956） was an independent risk factor for PSCI. The area under the ROC curve for TNF-α level in predicting PSCI was 0.819 （0.711 - 0.928）, and the critical value was 36.965 ng/L when the Youden index was at its maximum value of 0.600. Conclusions: The TNF-α level in early stroke patients is significantly negatively correlated with the occurrence of PSCI. A higher TNF-α level is an independent risk factor for PSCI. The TNF-α level has certain predictive and diagnostic value for the occurrence of PSCI. A serum TNF-α level higher than 36.965 ng/L may increase the risk of PSCI.

Objective: Based on interpretable machine learning methods, to explore the application value of multimodal MRI radiomics in the diagnosis of Alzheimer's disease (AD) and provide imaging tools for accurate clinical diagnosis of AD. Methods: A retrospective study was conducted on 110 subjects, including 48 in the AD group and 62 in the control group (HC), all of whom completed 3D-T1WI, DWI, and T₂WI MRI sequence scans. Randomly stratified sampling was conducted at a ratio of 7:3 to divide the data into training and testing sets, and 8 AD related core brain regions (hippocampus, entorhinal cortex, etc.) were segmented. Extract 107 radiomics features, screen the core features, and construct 8 diagnostic models (2 algorithms x 3 sequences, 2 algorithms x 2 sequences combined) based on logistic regression (LR) and random forest (RF) algorithms. Evaluate the model performance using area under the curve (AUC), and analyze the model interpretability using SHAP analysis. Results: 16 core radiomics features were ultimately selected. The joint sequence model has the best diagnostic performance, with AUC values of 0.989 (95% CI: 0.960~1.00) and 0.970 (95% CI: 0.920~1.00) for the LR and RF algorithm test sets, respectively, which are significantly higher than those of the single sequence model; The accuracy, sensitivity, and specificity of the LR joint model test set were 0.882, 0.800, and 0.947, respectively. SHAP analysis shows that the 3D-T₁WI sequence with short run length and high grayscale emphasized features, and the DWI sequence with grayscale co-occurrence matrix information measurement are the core indicators for AD diagnosis. Conclusions: The multimodal MRI radiomics model can efficiently achieve AD diagnosis, and the LR combined model has the best comprehensive performance. SHAP analysis can clearly analyze the decision-making basis of the model, providing strong support for the clinical translation of the model and accurate diagnosis of AD.

Objective: To expolre the changes in cerebral white matter microstructure and cerebral blood flow (CBF) in patients with plateau Alzheimer's disease (AD) using multimodal MRI. Methods: A total of 18 AD patients with long-term plateau residence and 20 healthy subjects were prospectively enrolled. 3.0T MRI scanner was used to acquire diffusion tensor imaging (DTI), T1-weighted, and arterial spin labeling (ASL) sequences. DPABI Pro post-processing software was applied to obtain tract-based spatial statistics (TBSS) images based on fiber tractography and region of interest (ROI) images.Comprehensive analysis of the characteristics of white matter microstructure changes in plateau AD patients was performed by combining CBF data and cognitive scales. Results: 1. TBSS results showed that the regions of white matter fiber tract damage in plateau AD patients were basically consistent with those in plainland AD patients. Compared with the normal control (NC) group, ROI analysis revealed that axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) in the AD group were significantly increased in multiple brain regions (P < 0.05). 2. In plateau AD patients, decreased CBF coexisted with abnormal DTI findings in regions including the temporal lobe, corona radiata, parietal lobe, precuneus, cingulate gyrus, prefrontal lobe, and thalamus. 3. In plateau AD patients, AD and MD values of the cingulate gyrus were positively correlated with ADL scores; AD and MD values of the thalamus were significantly negatively correlated with MMSE scores; RD value of the hippocampus was negatively correlated with MMSE scores. Conclusions: Widespread and significant damage to global cerebral white matter and fiber tracts is observed in plateau AD patients, with regional specificity characterized by extensive involvement of the visual cortex, thalamus, and motor cortex. Additionally, there is substantial overlap between regions of decreased CBF and abnormal DTI indices in plateau AD patients, reflecting that the "blood flow-microstructure" synergistic damage mechanism caused by neurovascular coupling (NVC) impairment may exacerbate the pathological progression of plateau AD, and is closely related to global cognitive function and daily living ability.

Objective: To systematically evaluate the efficacy and safety of repetitive transcranial magnetic stimulation (rTMS) in the treatment of vascular dementia(VaD). Methods: Randomized controlled trials (RCTs) investigating rTMS for VaD were retrieved from Chinese and English databases from inception to May 2025. After screening based on predefined inclusion and exclusion criteria, a meta-analysis was performed using RevMan 5.4 software. Results: A total of 15 eligible RCTs involving 1,296 patients were included. The meta-analysis demonstrated that, compared with the control group, rTMS significantly improved clinical response rate [RR=1.26,95%CI(1.18,1.35),P<0.00001], Montreal Cognitive Assessment (MoCA) score [MD=1.84,95%CI(1.27,2.41),P<0.00001], Mini-Mental State Examination (MMSE) score [MD=3.81,95%CI(3.43,4.19),P<0.00001], Hasegawa Dementia Scale (HDS) score [MD=3.48,95%CI(2.94,4.03),P<0.00001], National Institutes of Health Stroke Scale (NIHSS) score [MD=-1.23,95%CI(-1.47,-0.99),P<0.00001], and Activities of Daily Living (ADL) score [MD=6.72,95%CI(5.70,7.74),P<0.00001]. All differences were statistically significant. Adverse effects of rTMS were mild, with good patient tolerance and high safety. Conclusion: rTMS demonstrates significant efficacy in improving cognitive function, activities of daily living, andneurological deficits in VaD patients, while maintaining high treatment safety.

Objective: Frontotemporal dementia（FTD） and Alzheimer's disease（AD） exhibit overlapping clinical symptoms and neuroimaging features, complicating differential diagnosis and increasing misdiagnosis risks. This study aimed to explore gray matter volume（GMV） patterns between FTD and AD using 3D high-resolution T1-weighted MRI and machine learning to establish an objective diagnostic method. Methods: Voxel-based morphometry（VBM） was applied to analyze whole-brain GMV differences in 20 FTD and 35 AD patients. The relationships between GMV exhibiting significant differences and cognitive scores（MMSE, MoCA, CDT, ADAS-cog, CDR, ADL） were assessed. A support vector machine（SVM） classifier was constructed using GMV features from significant regions. Results: Significant GMV differences in FTD versus AD were observed in the right hemisphere（FWE-corrected, cluster level, P<0.05）, including the occipital（superior/middle/inferior gyri）, parietal（superior parietal lobule, supramarginal gyrus, angular gyrus）, and temporal lobes（superior/middle/inferior gyri）. GMV in the right occipital and temporal regions was significantly and positively associated with MMSE, MoCA and CDT scores（beta = 0.263-0.399, P<0.05）. The SVM model achieved moderate classification accuracy（60.00%, AUC = 0.6729）. Conclusion: VBM combined with cognitive assessment identified neuroimaging biomarkers distinguishing FTD from AD. Although the SVM model shows moderate performance, these findings provide objective evidence for clinical differentiation. This work not only advances understanding of neuroanatomy but also lays a foundation for optimizing machine learning models to improve diagnostic accuracy, demonstrating promising clinical translation potential.

Pulse pressure (PP), an indicator of arterial stiffness and pulsatile hemodynamic load, may offer superior value in risk assessment compared to static blood pressure indices. Recent studies have reported an association between PP and cognitive impairment or dementia; however, the findings have been inconsistent. This review summarizes the current evidence on the association between PP and cognitive impairment, with particular emphasis on its overall relationship with cognitive function, the modifying effects of age, sex, and APOE ε4 genotype, and the potential underlying mechanisms. Current evidence suggests that persistently elevated PP is associated with an increased risk of cognitive decline, and this association may be partly independent of traditional blood pressure indices and common vascular risk factors. Mechanistically, elevated PP may promote excessive transmission of pulsatile energy into the cerebral microcirculation, leading to perfusion mismatch, impaired cerebral autoregulation, and disruption of the blood-brain barrier. It may also contribute to cerebral small vessel remodeling, white matter microstructural damage, neuroinflammation, and impaired clearance of pathological proteins such as amyloid beta (Aβ) and tau, ultimately compromising brain network integrity and cognitive function. Given its noninvasive, simple, low-cost, and repeatable nature, PP may serve as a useful adjunctive marker for the early identification, risk stratification, and clinical assessment of individuals at high risk of cognitive impairment. However, its risk thresholds, causal relationship with cognitive decline, and therapeutic implications still require further investigation.

Objective: To explore the application effect of rapid sedation combined with Cognitive Arousal Therapy in the emergency treatment of agitation in Alzheimer's disease patients. Methods: A total of 115 Alzheimer's disease patients admitted to our hospital from January 2023 to December 2025 were selected as subjects and randomly divided into a conventional group and an experimental group using a random number table method. The conventional emergency agitation treatment was administered to 57 cases in the conventional group, while rapid sedation combined with cognitive awakening therapy was applied to 58 cases in the experimental group. The intervention outcomes were compared. Results: The total effective rate of agitation control in the experimental group was 94.83%, significantly higher than that in the conventional group (80.70%), with a statistically significant difference (P < 0.05). Compared with the conventional group, the experimental group exhibited faster onset of sedation and longer duration of sedation, with a statistically significant difference (P < 0.05). At 24 hours post-intervention, the Confusion Assessment Method (CAM) scores were significantly lower in the experimental group than in the conventional group (P < 0.05). The overall compliance rate in the experimental group was 93.10%, significantly higher than that in the conventional group (77.19%), with a statistically significant difference (P < 0.05). The adverse reaction rate in the experimental group was 6.90%, significantly lower than that in the conventional group (21.05%), with a statistically significant difference (P < 0.05). Conclusion: Combining rapid sedation with cognitive awakening therapy in the emergency treatment of agitation in Alzheimer's disease patients can achieve rapid and sustained sedation, maintain good compliance, and improve disease control effectiveness.

Creutzfeldt-Jakob disease is one of the most common diseases causing rapid progressive dementia. How to identify Creutzfeldt-Jakob disease at an early stage and reduce misdiagnosis is a challenge faced by our medical staff. This article reports the clinical characteristics and auxiliary examination results of a patient who is highly likely to have Creutzfeldt-Jakob disease and combines literature to explore methods for early identification and diagnosis of Creutzfeldt-Jakob disease.