The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests suc...The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.展开更多
Background As the population in China rapidly ages,the prevalence of mild cognitive impairment(MCI)is increasing considerably.However,the causes of MCI vary.The continued lack of understanding of the various subtypes ...Background As the population in China rapidly ages,the prevalence of mild cognitive impairment(MCI)is increasing considerably.However,the causes of MCI vary.The continued lack of understanding of the various subtypes of MCI impedes the implementation of effective measures to reduce the risk of advancing to more severe cognitive diseases.Aims To estimate the prevalence and incidence rates of two MCI subtypes—amnestic MCI(aMCI)and vascular cognitive impairment without dementia(VCIND)—and to determine modifiable factors for them among older individuals in a multiregional Chinese cohort.Method This 1-year longitudinal study surveyed a random sample of participants aged≥60 years from a large,community-dwelling cohort in China.Baseline lifestyle data were self-reported,while vascular and comorbid conditions were obtained from medical records and physical examinations.In total,3514 and 2051 individuals completed the baseline and 1-year follow-up assessments,respectively.Logistic and linear regression analyses were used to identify the modifiable factors for MCI subtypes and predictors of cognitive decline,respectively.Results Among our participants,aMCI and VCIND demonstrated prevalence of 14.83%and 2.71%,respectively,and annual incidence(per 1000 person-years)of 69.6 and 10.6,respectively.The risk factor for aMCI was age,whereas its protective factors were high education level,tea consumption and physical activity.Moreover,VCIND risk factors were age,hypertension and depression.The presence of endocrine disease,cerebral trauma or hypertension was associated with a faster decline in cognition over 1 year.Conclusions MCI is a serious health problem in China that will only worsen as the population ages if no widespread interventions are implemented.Preventive strategies that promote brain activity and support healthy lifestyle choices are required.We identified modifiable factors for MCI in older individuals.The easy-to-adopt solutions such as tea consumption and physical activity can aid in preventing MCI.展开更多
BACKGROUND Mild behavioral impairment(MBI)refers to the neurobehavioral symptoms observed in older adults that may be potential risk factors for neurodegenerative diseases.While a significant number studies have explo...BACKGROUND Mild behavioral impairment(MBI)refers to the neurobehavioral symptoms observed in older adults that may be potential risk factors for neurodegenerative diseases.While a significant number studies have explored the association between cerebrospinal fluid and MBI,only a few have examined the connection between plasma biomarkers and MBI.AIM To examine the prevalence of MBI in healthy older adults(HOAs)and individuals with mild cognitive impairment(MCI),as well as the association between MBI and plasma biomarkers of Alzheimer’s disease(AD).METHODS We enrolled a total of 241 subjects,which included 136 HOAs and 105 MCIs,from the Yuhua District of Shijiazhuang City,Hebei Province,China.The MBI symp-tom checklist(MBI-C)was utilized for the assessment and diagnosis of MBI,and a score of MBI-C≥6.5 was considered indicative of the condition.Fasting venous blood samples were collected from 70 patients,32 HOAs and 38 MCIs,and levels of amyloidβ-protein(Aβ)40,Aβ42,and hyperphosphorylated tau(p-Tau217)in these samples were measured using an enzyme-linked immunosorbent assay.RESULTS The prevalence of MBI in the HOAs and MCI groups was 4.4%and 15.3%,respectively(χ^(2)=7.262,P=0.007),with particularly notable decreases in motivation and increases in impulse dyscontrol(the highest detection rate)and social inappropriateness(P<0.05).The total MBI score correlated with Aβ42 and p-Tau217(r=-0.385,P=0.019;r=-0.330,P=0.041),but not with Aβ40 or the Aβ42/40 ratio.Among the subdomains,impulse dyscontrol was correlated with Aβ42(r=-0.401,P=0.025).CONCLUSION Both MCI and HOAs have exhibited a higher prevalence of MBI,with changes in impulse control behavior being the most common.MBI not only presents as an independent risk factor for cognitive decline but is also linked with AD-related peripheral biomarkers.展开更多
BACKGROUND Older adults with mild cognitive impairment(MCI)often show motor dysfunction,including slower gait and impaired handwriting.While gait and handwriting parameters are promising for MCI screening,their combin...BACKGROUND Older adults with mild cognitive impairment(MCI)often show motor dysfunction,including slower gait and impaired handwriting.While gait and handwriting parameters are promising for MCI screening,their combined potential to distinguish MCI from cognitively normal adults is unclear.AIM To assess gait and handwriting differences and their potential for screening MCI in older adults.METHODS Ninety-five participants,including 34 with MCI and 61 cognitively normal controls,were assessed for gait using the GAITRite^(R)system and handwriting with a dot-matrix pen.Five machine learning models were developed to assess the discriminative power of gait and handwriting data for MCI screening.RESULTS Compared to the cognitively normal group,the MCI group had slower gait velocity(Z=-2.911,P=0.004),shorter stride and step lengths(t=-3.005,P=0.003;t=2.863,P=0.005),and longer cycle,standing,and double support times(t=-2.274,P=0.025;t=-2.376,P=0.018;t=-2.717,P=0.007).They also had reduced cadence(t=2.060,P=0.042)and increased double support time variability(Z=-2.614,P=0.009).In handwriting,the MCI group showed lower average pressure(all tasks:Z=-2.135,P=0.033)and decreased accuracy(graphic task:Z=-2.447,P=0.014;Chinese character task:Z=-3.078,P=0.002).In the graphic task,they demonstrated longer time in air(Z=-2.865,P=0.004),reduced X-axis maximum velocities(Z=-3.237,P=0.001),and lower accelerations(X-axis:Z=-2.880,P=0.004;Y-axis:Z=-1.987,P=0.047)and maximum accelerations(X-axis:Z=-3.998,P<0.001;Y-axis:Z=-2.050,P=0.040).The multimodal analysis achieved the highest accuracy(74.4%)with the Gradient Boosting Classifier.CONCLUSION Integrating gait and handwriting kinematics parameters provides a viable method for distinguishing MCI,potentially supporting large-scale screening,especially in resource-limited settings.展开更多
BACKGROUND Mild cognitive impairment(MCI)is a transitional state between normal aging and Alzheimer's disease(AD),characterized by subtle cognitive decline.Amnestic MCI(aMCI),in particular,is a critical precursor ...BACKGROUND Mild cognitive impairment(MCI)is a transitional state between normal aging and Alzheimer's disease(AD),characterized by subtle cognitive decline.Amnestic MCI(aMCI),in particular,is a critical precursor often progressing to AD.There is growing interest in understanding the neuroanatomical correlates of aMCI,especially the role of gray matter volume(GMV)in cognitive and motor function decline.This study hypothesized that aMCI patients will exhibit reduced GMV,particularly in brain regions associated with cognition and motor control,impacting both cognitive performance and motor abilities.AIM To investigate the association of GMV with cognitive and motor functions in aMCI.METHODS In this cross-sectional study conducted from March 2022 to March 2024,45 aMCI patients and 45 normal controls from our Department of Geratology were enrolled.Voxel-based morphometry was used to compare GMV between groups.Correlation of differential GMV with cognitive scores and gait parameters was assessed via partial correlation analysis.Linear regression was used to assess associations between whole-brain GMV and gait measures.RESULTS GMV of aMCI region of interest(ROI)1 and ROI2 was negatively correlated with Activities of Daily Living(ADL)score.GMV of ROI6 was positively correlated with the total scores of Mini-Mental State Examination and Cambridge Cognitive Examination-Chinese Version(CAMCOG-C)and negatively correlated with ADL score.In the partial correlation analysis of cognitive and motor function parameters,age,gender,educational level,height,and weight were controlled,and the results showed that CAMCOG-C was negatively correlated with Dual Task of Time Up and Go Test(TUG)duration in the aMCI group.The volume of the left occipital gray matter in the aMCI group was negatively correlated with TUG.GMV of the bilateral frontal gyrus,right orbitofrontal gyrus,right occipital cleft,right supraoccipital gyrus,and left anterior central gyrus was positively correlated with walking speed.CONCLUSION GMV reduction in aMCI correlates with impaired cognition and motor function,emphasizing key roles for prefrontal,occipital,and central regions in gait disorders.展开更多
Brain imaging is important in detecting Mild Cognitive Impairment(MCI)and related dementias.Magnetic Resonance Imaging(MRI)provides structural insights,while Positron Emission Tomography(PET)evaluates metabolic activi...Brain imaging is important in detecting Mild Cognitive Impairment(MCI)and related dementias.Magnetic Resonance Imaging(MRI)provides structural insights,while Positron Emission Tomography(PET)evaluates metabolic activity,aiding in the identification of dementia-related pathologies.This study integrates multiple data modalities—T1-weighted MRI,Pittsburgh Compound B(PiB)PET scans,cognitive assessments such as Mini-Mental State Examination(MMSE),Clinical Dementia Rating(CDR)and Functional Activities Questionnaire(FAQ),blood pressure parameters,and demographic data—to improve MCI detection.The proposed improved Convolutional Mixer architecture,incorporating B-cos modules,multi-head self-attention,and a custom classifier,achieves a classification accuracy of 96.3%on the Mayo Clinic Study of Aging(MCSA)dataset(sagittal plane),outperforming state-of-the-art models by 5%–20%.On the full dataset,the model maintains a high accuracy of 94.9%,with sensitivity and specificity reaching 89.1%and 98.3%,respectively.Extensive evaluations across different imaging planes confirm that the sagittal plane offers the highest diagnostic performance,followed by axial and coronal planes.Feature visualization highlights contributions from central brain structures and lateral ventricles in differentiating MCI from cognitively normal subjects.These results demonstrate that the proposed multimodal deep learning approach improves accuracy and interpretability in MCI detection.展开更多
BACKGROUND Mild cognitive impairment(MCI)is a high-risk precursor to Alzheimer’s disease characterized by declining memory or other progressive cognitive functions without compromising daily living abilities.AIM To i...BACKGROUND Mild cognitive impairment(MCI)is a high-risk precursor to Alzheimer’s disease characterized by declining memory or other progressive cognitive functions without compromising daily living abilities.AIM To investigate the efficacy of repetitive transcranial magnetic stimulation(rTMS)in patients with MCI.METHODS This retrospective analysis involved 180 patients with MCI who were admitted to The First Hospital of Shanxi Medical University from January 2021 to June 2023.Participants were allocated into the research(n=98,receiving rTMS)and control groups(n=82,receiving sham stimulation).Memory tests,cognitive function assessments,event-related potential–P300 tests,and electroencephalogram(EEG)examinations were conducted pre-treatment and post-treatment.Further,memory quotient(MQ),cognitive function scores,and EEG grading results were compared,along with adverse reaction incidences.RESULTS Pre-treatment MQ scores,long-term and short-term memory,as well as immediate memory scores,demonstrated no notable differences between the groups.Post-treatment,the research group exhibited significant increases in MQ scores,long-term memory,and short-term memory compared to baseline(P<0.05),with these improvements being statistically superior to those in the control group.However,immediate memory scores exhibited no significant change(P>0.05).Further,the research group demonstrated statistically better post-treatment scores on the Revised Wechsler Memory Scale than the control group.Furthermore,post-treatment P300 latency and amplitude improved significantly in the research group,surpassing the control group.EEG grading in the research group improved,and the incidence of adverse reactions was significantly lower than in the control group.CONCLUSION Patients with MCI receiving rTMS therapy demonstrated improved memory and cognitive functions and EEG grading and exhibited high safety with fewer adverse reactions.展开更多
Objective:As an age-related neurodegenerative disease,the prevalence of mild cognitive impairment(MCI)increases with age.Within the framework of traditional Chinese medicine,spleen-kidney deficiency syndrome(SKDS)is r...Objective:As an age-related neurodegenerative disease,the prevalence of mild cognitive impairment(MCI)increases with age.Within the framework of traditional Chinese medicine,spleen-kidney deficiency syndrome(SKDS)is recognized as the most frequent MCI subtype.Due to the covert and gradual onset of MCI,in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes.There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS(MCI-SKDS).Methods:This investigation enrolled 312 elderly individuals diagnosed with MCI,who were randomly distributed into training and test datasets at a 3:1 ratio.Five machine learning methods,including logistic regression(LR),decision tree(DT),naive Bayes(NB),support vector machine(SVM),and gradient boosting(GB),were used to build a diagnostic prediction model for MCI-SKDS.Accuracy,sensitivity,specificity,precision,F1 score,and area under the curve were used to evaluate model performance.Furthermore,the clinical applicability of the model was evaluated through decision curve analysis(DCA).Results:The accuracy,precision,specificity and F1 score of the DT model performed best in the training set(test set),with scores of 0.904(0.845),0.875(0.795),0.973(0.875)and 0.973(0.875).The sensitivity of the training set(test set)of the SVM model performed best among the five models with a score of 0.865(0.821).The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset.The DCA of all models showed good clinical application value.The study identified ten indicators that were significant predictors of MCI-SKDS.Conclusion:The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical;the model demonstrates good predictive value and clinical applicability,and the DT model had the best performance.展开更多
In the context of global aging,mild behavioral impairment(MBI)is present in 48.9%of patients with mild cognitive impairment(MCI).MBI,a neurobehavioral syndrome in the elderly,is an independent risk factor for cognitiv...In the context of global aging,mild behavioral impairment(MBI)is present in 48.9%of patients with mild cognitive impairment(MCI).MBI,a neurobehavioral syndrome in the elderly,is an independent risk factor for cognitive decline and is closely related to peripheral blood biomarkers associated with Alzheimer's disease,offering new diagnostic and interventional avenues for early MCI.To summarize evidence on peripheral blood biomarkers related to MBI and their underlying mechanisms involving neuroinflammation,tau pathology,and oxidative stress,a systematic review of studies published between 2015 and 2024 was conducted.MBI is closely associated with peripheral blood biomarker changes.Neuroinflammatory markers like glial fibrillary acidic protein and neurofilament light indicate astrocyte activation and neural circuit disruption,with glial fibrillary acidic protein levels correlating with impulse dyscontrol scores.Chitinase-3-like protein 1,a marker of blood-brain barrier integrity,exacerbates neuroinflammation and is linked to depressive symptoms and hippocampal atrophy.Elevated phosphorylated tau proteins in blood correlate with brain tau deposition,increasing the risk of MBI and impairing cognition.Oxidative stress markers damage neurons and disrupt neurotransmission,and concurrent alterations in malondialdehyde and superoxide dismutase levels significantly elevate the risk of MBI.The correlation between MBI and biomarkers offers new diagnostic and interventional directions for early MCI.Future research should standardize MBI assessment,conduct longitudinal studies,explore biomarker-MBI relationships,investigate psychosocial impacts,and develop advanced detection methods.展开更多
Objectives:The current study aimed to perform a meta-analysis to comprehensively investigate effect of physical activity on cognitive function in people with Mild Cognitive Impairment.The findings of this study can of...Objectives:The current study aimed to perform a meta-analysis to comprehensively investigate effect of physical activity on cognitive function in people with Mild Cognitive Impairment.The findings of this study can offer an important basis for identifying the significance of physical activity as an important factor in designing and implementing strategies to enhance cognitive function in mild cognitive impairment.Methods:21 articles were selected through academic databases(EBSCOhost,PubMed,ScienceDirect,Web of Science),and 20 Montreal Cognitive Assessment(MoCA)data and 15 Mini-Mental State Examination(MMSE)data were obtained.The study was conducted using the meta-analysis.To test the validity of each article included in this study,a funnel plot and Egger’s regression analysis were carried out to check for publication bias.Results:The 95%confidence interval(CI)for the effect size was interpreted as a small effect size if the effect size was between 0.2 and 0.5,a moderate effect size if the effect size was between 0.5 and 0.8,and large if the effect size was greater than 0.8.First,the meta-analysis of MoCA data showed a large effect size of 0.96;second,the meta-analysis of MMSE data indicated a large effect size of 0.93;and third,the meta-analysis of MoCA and MMSE data together indicated a moderate effect size of 0.68.Conclusion:The current study demonstrates the significant effect of physical activity on cognitive function and provides a basis for developing programs to improve cognitive function.People diagnosed with mild cognitive impairment generally experience minimal disruption in daily living activities.However,as the severity of the condition progresses,significant challenges emerge,impacting the individual’s ability to carry out daily tasks.Research has demonstrated that physical activity can enhance cognitive function in individuals with MCI.Consequently,it is recommended that these individuals be motivated to participate in physical activity to optimize their cognitive function and enhance their overall quality of life.展开更多
Objective To assess whether quick cognitive screening test （QCST） could quickly identify mild cognitive impairment （MCI）. Methods QCST and a full set of standardized neuropsychological tests, including mini-mental...Objective To assess whether quick cognitive screening test （QCST） could quickly identify mild cognitive impairment （MCI）. Methods QCST and a full set of standardized neuropsychological tests, including mini-mental state examination （MMSE） and montreal cognitive assessment （MoCA） were performed. A total number of 121 cases of MCI [41 cases of amnestic MCI-single domain （aMCI-s）; 44 of amnestic MCI-multiple domain （aMCI-m）; 36 of nonamnestic MCI （naMCI）], 79 cases of mild Alzheimer’s disease （AD） and 186 healthy elderly volunteers were employed in the present study. All the participants （55-85 years old） had an educational level no less than 5 years. QCST subtests included word list recall, naming test, animal fluency test, similarity test, color trail-1min, clock drawing test, finger construction test, and digit span test. The total score of QCST was 90 points, 10 points for each index of subtests. Results The total scores of QCST in MCI, AD and the control groups were （58.13±8.18）, （44.53±10.54） and （72.92±6.85） points, respectively. According to the educational level, the cut off scores of participants with an educational level of 5-8 years, 9-12 years and more than 13 years were 63, 65 and 68 points, respectively. The sensitivity and specificity of QCST in detection of MCI were 87.6% （85.7% for aMCI-s, 90.1% for aMCI-m and 89.5% for naMCI） and 84.3%, respectively. The area under the curve was 0.923 （95% CI： 0.892-0.953）. Delayed memory, color trail-1min and similarity test could help distinguish between aMCI and naMCI. Conclusion QCST may have a good sensitivity and specificity for MCI detection, which warrants its further clinical application.展开更多
Objective To observe the clinical effect of acupuncture in combination with medicine in the treatment of mild cognitive impairment after cerebral infarction as well as the impact on patients＇ daily living ability. Me...Objective To observe the clinical effect of acupuncture in combination with medicine in the treatment of mild cognitive impairment after cerebral infarction as well as the impact on patients＇ daily living ability. Methods Seventy-two patients, in accordance with random number table, were divided into two groups, acupuncture combined with western medicine group （group A） and western medicine group （group B）, each group with 36 patients. In combination with nimodipine tablets, acupuncture which can regulate the mind and reinforce the intelligence [making Baihui （百会 GV 20）, Sishencong （四神聪EX-HN 1）, Sibai （四白 ST 2）, Fengchi （风池 GB 20）, Wanggu （完骨 GB 12）, Tianzhu （天柱 BL 10）, Shenmen （神门 HT 7）, Neiguan （内关 PC 6）, Shuigou （水沟 GV 26）, Sanyinjiao （三阴交 SP 6）, Taichong （太冲 LR 3）, Fenglong （丰隆 ST 40） as the main acupoints] was given in the treatment group （group A） while only nimodipine tablets were given in the control group （group B）. The efficacy of these two groups was evaluated by Montreal Cognitive Assessment （MoCA） Scale after the continuous treatment for three months. Results The remarkably effective rate was 69.4%.and the total effective rate was 91.7% in the treatment group, while the remarkably effective rate was 55.6% and the total effective rate was 80.6% in the control group; the differences between the two groups were statistically significant （P〈0.05）. When comparing the MoCA score before and after treatment, which was 20.23±4.67 before treatment and 26.84±3.87 after treatment in group A; 19.82±3.56 before treatment and 23.33±2.78 after treatment in group B, it was found that the score for both groups became higher after treatment than that before treatment. Furthermore, the increase of the score was higher in the treatment group （6.61±0.80） than that in the control group （3.51±0.78） and the differences were statistically significant （P〈0.05）. Conclusion Acupuncture, which can regulate the mind and reinforce the intelligence, combined with nimodipine tablets is an effective therapy for the treatment of mild cognitive impairment after cerebral infarction, which is superior to single treatment with nimodipine tablets.展开更多
Mild cognitive impairment(MCI)is a precursor to Alzheimer’s disease.It is imperative to develop a proper treatment for this neurological disease in the aging society.This observational study investigated the effects ...Mild cognitive impairment(MCI)is a precursor to Alzheimer’s disease.It is imperative to develop a proper treatment for this neurological disease in the aging society.This observational study investigated the effects of acupuncture therapy on MCI patients.Eleven healthy individuals and eleven MCI patients were recruited for this study.Oxy-and deoxy-hemoglobin signals in the prefrontal cortex during working-memory tasks were monitored using functional near-infrared spectroscopy.Before acupuncture treatment,working-memory experiments were conducted for healthy control(HC)and MCI groups(MCI-0),followed by 24 sessions of acupuncture for the MCI group.The acupuncture sessions were initially carried out for 6 weeks(two sessions per week),after which experiments were performed again on the MCI group(MCI-1).This was followed by another set of acupuncture sessions that also lasted for 6 weeks,after which the experiments were repeated on the MCI group(MCI-2).Statistical analyses of the signals and classifications based on activation maps as well as temporal features were performed.The highest classification accuracies obtained using binary connectivity maps were 85.7%HC vs.MCI-0,69.5%HC vs.MCI-1,and 61.69%HC vs.MCI-2.The classification accuracies using the temporal features mean from 5 seconds to 28 seconds and maximum(i.e,max(5:28 seconds))values were 60.6%HC vs.MCI-0,56.9%HC vs.MCI-1,and 56.4%HC vs.MCI-2.The results reveal that there was a change in the temporal characteristics of the hemodynamic response of MCI patients due to acupuncture.This was reflected by a reduction in the classification accuracy after the therapy,indicating that the patients’brain responses improved and became comparable to those of healthy subjects.A similar trend was reflected in the classification using the image feature.These results indicate that acupuncture can be used for the treatment of MCI patients.展开更多
Objective： To assess functional relationship by calculating inter- and intra-hemispheric electroencephalography （EEG） coherence at rest and during a working memory task of patients with mild cognitive impairment （...Objective： To assess functional relationship by calculating inter- and intra-hemispheric electroencephalography （EEG） coherence at rest and during a working memory task of patients with mild cognitive impairment （MCI）. Methods： The sample consisted of 69 subjects： 35 patients （n = 17 males, n = 18 females; 52-71 years old） and 34 normal controls （n = 17 males, n = 17 females; 51 -63 years old）. Mini-mental state examination （MMSE） of two groups revealed that the scores of MCI patients did not differ significantly from those of normal controls （P〉0.05）. In EEG recording, subjects were performed at rest and during working memory task. EEG signals from F3-F4, C3-C4, P3-P4, T5-T6 and O1-O2 electrode pairs are resulted from the inter-hemispheric action, and EEG signals from F3-C3, F4-C4, C3-P3, C4-P4, P3-O1, P4-O2, T5-C3, T6-C4, T5-P3 and T6-P4 electrode pairs are resulted from the intra-hemispheric action for delta （1.0-3.5 Hz）, theta （4.0-7.5 Hz）, alpha-1 （8.0-10.0 Hz）, alpha-2 （10.5-13.0 Hz）, beta-1 （13.5-18.0 Hz） and beta-2 （18.5-30.0 Hz） frequency bands. The influence of inter- and intra-hemispheric coherence on EEG activity with eyes closed was examined using fast Fourier transformation from the 16 sampled channels. Results： During working memory tasks, the inter- and intra-hemispheric EEG coherences in all bands were significantly higher in the MCI group in comparison with those in the control group （P〈0.05）. However, there was no significant difference in inter- and intra-hemispheric EEG coherences between two groups at rest. Conclusion： Experimental results comprise evidence that MCI patients have higher degree of functional connectivity between hemispheres and in hemispheres during working condition, It suggests that MCI may be associated with compensatory processes during working memory tasks between hemispheres and in hemispheres. Moreover, failure of normal cortical connections may exist in MCI patients.展开更多
Objectives Non-invasive and low-cost virtual reality(VR)technology is important for early evaluation and intervention in mild cognitive impairment(MCI).This study aimed to demonstrate the current status of overseas an...Objectives Non-invasive and low-cost virtual reality(VR)technology is important for early evaluation and intervention in mild cognitive impairment(MCI).This study aimed to demonstrate the current status of overseas and domestic research as well as the focus and frontier of VR technology among individuals with MCI through a bibliometric analysis.Methods Studies from the core collection of Web of Science™between 1995 and 2020 were used;furthermore,CiteSpace 5.7 R3 was utilized to analyse information on authors/cited authors,keywords,burst words,and cited references.Results In total,230 publications were identified.Most studies were published in the USA(45 publications)and Italy(41 publications),where Guiseppe Riva ranks first(14 publications),and Tarnanas I is the author with the highest centrality(0.44).The hot topics in VR applications in the MCI population are‘physical activity,’‘people,’‘single-blind,’‘disease,’‘walking,’‘technology,’‘working memory,’and‘risk’in recent years.The keyword‘mild cognitive impairment’has attracted extensive attention since 2012,showing the strongest citation outbreak(8.28).The clustering results of the literature show the research types and emerging trends,including‘exergame,’‘serious games,’‘spatial navigation,’‘activities of daily living,’‘exercise,’‘enriched environment’and‘wayfinding.‘Conclusions Cognitive assessment and nonpharmacological intervention research on patients with MCI have become the focus of dementia prevention in recent years.Virtual technology,combined with traditional methods such as exercise therapy,provides new ideas for innovative cognitive evaluation and cognitive intervention.展开更多
Subcortical vascular mild cognitive impairment(svMCI)is a common prodromal stage of vascular dementia.Although mounting evidence has suggested abnormalities in several single brain network metrics,few studies have exp...Subcortical vascular mild cognitive impairment(svMCI)is a common prodromal stage of vascular dementia.Although mounting evidence has suggested abnormalities in several single brain network metrics,few studies have explored the consistency between functional and structural connectivity networks in svMCI.Here,we constructed such networks using resting-state f MRI for functional connectivity and diffusion tensor imaging for structural connectivity in 30 patients with svMCI and 30 normal controls.The functional networks were then parcellated into topological modules,corresponding to several well-defined functional domains.The coupling between the functional and structural networks was finally estimated and compared at the multiscale network level(whole brain and modular level).We found no significant intergroup differences in the functional–structural coupling within the whole brain;however,there was significantly increased functional–structural coupling within the dorsal attention module and decreased functional–structural coupling within the ventral attention module in the svMCI group.In addition,the svMCI patients demonstrated decreased intramodular connectivity strength in the visual,somatomotor,and dorsal attention modules as well as decreased intermodular connectivity strength between several modules in the functional network,mainly linking the visual,somatomotor,dorsal attention,ventral attention,and frontoparietal control modules.There was no significant correlation between the altered module-level functional–structural coupling and cognitive performance in patients with svMCI.These findings demonstrate for the first time that svMCI is reflected in a selective aberrant topological organization in multiscale brain networks and may improve our understanding of the pathophysiological mechanisms underlying svMCI.展开更多
Mild cognitive impairment(MCI)is a prodrome of Alzheimer’s disease pathology.Cognitive impairment patients often have a delayed diagnosis because there are no early symptoms or conventional diagnostic methods.Exosome...Mild cognitive impairment(MCI)is a prodrome of Alzheimer’s disease pathology.Cognitive impairment patients often have a delayed diagnosis because there are no early symptoms or conventional diagnostic methods.Exosomes play a vital role in cell-to-cell communications and can act as promising biomarkers in diagnosing diseases.This study was designed to identify serum exosomal candidate proteins that may play roles in diagnosing MCI.Mass spectrometry coupled with tandem mass tag approach-based non-targeted proteomics was used to show the differentially expressed proteins in exosomes between MCI patients and healthy controls,and these differential proteins were validated using immunoblot and enzyme-linked immunosorbent assays.Correlation of cognitive performance with the serum exosomal protein level was determined.Nanoparticle tracking analysis suggested that there was a higher serum exosome concentration and smaller exosome diameter in individuals with MCI compared with healthy controls.We identified 69 exosomal proteins that were differentially expressed between MCI patients and healthy controls using mass spectrometry analysis.Thirty-nine exosomal proteins were upregulated in MCI patients compared with those in control patients.Exosomal fibulin-1,with an area under the curve value of 0.81,may be a biomarker for an MCI diagnosis.The exosomal protein signature from MCI patients reflected the cell adhesion molecule category.In particular,higher exosomal fibulin-1 levels correlated with lower cognitive performance.Thus,this study revealed that exosomal fibulin-1 is a promising biomarker for diagnosing MCI.展开更多
Amnestic mild cognitive impairment （aMCI） is a prodromal stage of Alzheimer＇s disease （AD）, and 75%-80% of aMCI patients finally develop AD. So, early identification of patients with aMCI or AD is of great signif...Amnestic mild cognitive impairment （aMCI） is a prodromal stage of Alzheimer＇s disease （AD）, and 75%-80% of aMCI patients finally develop AD. So, early identification of patients with aMCI or AD is of great significance for prevention and intervention. According to cross-sectional studies, it is known that the hippocampus, posterior cingulate cortex, and corpus callosum are key areas in studies based on structural MRI （sMRI）, functional MRI （fMRI）, and diffusion tensor imaging （DTI） respectively. Recently, longitudinal studies using each MRI modality have demonstrated that the neuroimaging abnormalities generally involve the posterior brain regions at the very beginning and then gradually affect the anterior areas during the progression of aMCI to AD. However, it is not known whether follow-up studies based on multi-modal neuroimaging techniques （e.g., sMRI, fMRI, and DTI） can help build effective MRI models that can be directly applied to the screening and diagnosis of aMCI and AD. Thus, in the future, large-scale multi-center follow-up studies are urgently needed, not only to build an MRI diagnostic model that can be used on a single person, but also to evaluate the variability and stability of the model in the general population. In this review, we present longitudinal studies using each MRI modality separately, and then discuss the future directions in this field.展开更多
Specific patterns of brain atrophy may be helpful in the diagnosis of Alzheimer＇s disease （AD）. In the present study, we set out to evaluate the utility of grey-matter volume in the classification of AD and amnesti...Specific patterns of brain atrophy may be helpful in the diagnosis of Alzheimer＇s disease （AD）. In the present study, we set out to evaluate the utility of grey-matter volume in the classification of AD and amnestic mild cognitive impairment （aMCI） compared to normal control （NC）individuals. Voxel-based morphometric analyses were performed on structural MRIs from 35 AD patients, 27 aMCI patients, and 27 NC participants. A two-sample two-tailed t-test was computed between the NC and AD groups to create a map of abnormal grey matter in AD. The brain areas with significant differences were extracted as regions of interest （ROIs）, and the grey-matter volumes in the ROIs of the aMCI patients were included to evaluate the patterns of change across different disease severities. Next, correlation analyses between the grey-matter volumes in the ROIs and all clinical variables were performed in aMCI and AD patients to determine whether they varied with disease progression. The results revealed significantly decreased grey matter in the bilateral hippocampus/ parahippocampus, the bilateral superior/middle temporal gyri, and the right precuneus in AD patients.The grey-matter volumes with clinical variables were positively correlated Finally, we performed exploratory linear discriminative analyses to assess the classifying capacity of grey-matter volumes in the bilateral hippocampus and parahippocampus among AD, aMCI, and NC. Leave-one-out cross- validation analyses demonstrated that grey-matter volumes in hippocampus and parahippocampus accurately distinguished AD from NC. These findings indicate that grey-matter volumes are useful in the classification of AD.展开更多
OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatm...OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatments to different types. In this paper, we investigate how to properly carry out the classification for patients with VMCI aged 50 or above using a novel data-driven method known as latent tree analysis （LTA）. METHOD： A cross-sectional survey on VMCI was carried out in several regions in Northern China between February 2008 and February 2012 which resulted in a data set that involves 803 patients and 93 symptoms. LTA was performed on the data to reveal symptom co-occurrence patterns, and the patients were partitioned into clusters in multiple ways based on the patterns. The patient clusters were matched up with syndrome types, and population statistics of the clusters are used to quantify the syndrome types and to establish classification rules. RESULTS： Eight syndrome types are identified： Qi deficiency, Qi stagnation, Blood deficiency, Blood stasis, Phlegm-dampness, Fire-heat, Yang deficiency, and Yin deficiency. The prevalence and symptom occurrence characteristics of each syndrome type are determined. Quantitative classification rules are established for determining whether a patient belongs to each of the syndrome types. CONCLUSION： A solution for the TCM syndrome classification problem for patients with VMCI and aged 50 or above is established based on the LTA of unlabeled symptom survey data. The results can be used as a reference in clinic practice to improve the quality of syndrome differentiation and to reduce diagnosis variances across physicians. They can also be used for patient selection in research projects aimed at finding biomarkers for the syndrome types and in randomized control trials aimed at determining the efficacy of TCM treatments of VMCI.展开更多
文摘The increasing global prevalence of mild cognitive impairment(MCI)necessitates a paradigm shift in early detection strategies.Conventional neuropsychological assessment methods,predominantly paper-and-pencil tests such as the Mini-Mental State Examination and the Montreal Cognitive Assessment,exhibit inherent limitations with respect to accessibility,administration burden,and sensitivity to subtle cognitive decline,particularly among diverse populations.This commentary critically examines a recent study that champions a novel approach:The integration of gait and handwriting kinematic parameters analyzed via machine learning for MCI screening.The present study positions itself within the broader landscape of MCI detection,with a view to comparing its advantages against established neuropsychological batteries,advanced neuroimaging(e.g.,positron emission tomography,magnetic resonance imaging),and emerging fluid biomarkers(e.g.,cerebrospinal fluid,blood-based assays).While the study demonstrates promising accuracy(74.44%area under the curve 0.74 with gait and graphic handwriting)and addresses key unmet needs in accessibility and objectivity,we highlight its cross-sectional nature,limited sample diversity,and lack of dual-task assessment as areas for future refinement.This commentary posits that kinematic biomarkers offer a distinctive,scalable,and ecologically valid approach to widespread MCI screening,thereby complementing existing methods by providing real-world functional insights.Future research should prioritize longitudinal validation,expansion to diverse cohorts,integration with multimodal data including dual-tasking,and the development of highly portable,artificial intelligence-driven solutions to achieve the democratization of early MCI detection and enable timely interventions.
基金supported by the Major Project of Wuxi Municipal Health Commission[grant number:Z202406]the Jiangsu Commission of Health Program[grant number:M2024010]+3 种基金the National Key Research and Development Program[grant number:2022YFC3600600]the China Ministry of Science and Technology grants[grant number:2009BAI77B03]the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support[grant number:20172029]the Innovative Research Team of High-level Local Universities in Shanghai[grant number:ZDCX20211201].
文摘Background As the population in China rapidly ages,the prevalence of mild cognitive impairment(MCI)is increasing considerably.However,the causes of MCI vary.The continued lack of understanding of the various subtypes of MCI impedes the implementation of effective measures to reduce the risk of advancing to more severe cognitive diseases.Aims To estimate the prevalence and incidence rates of two MCI subtypes—amnestic MCI(aMCI)and vascular cognitive impairment without dementia(VCIND)—and to determine modifiable factors for them among older individuals in a multiregional Chinese cohort.Method This 1-year longitudinal study surveyed a random sample of participants aged≥60 years from a large,community-dwelling cohort in China.Baseline lifestyle data were self-reported,while vascular and comorbid conditions were obtained from medical records and physical examinations.In total,3514 and 2051 individuals completed the baseline and 1-year follow-up assessments,respectively.Logistic and linear regression analyses were used to identify the modifiable factors for MCI subtypes and predictors of cognitive decline,respectively.Results Among our participants,aMCI and VCIND demonstrated prevalence of 14.83%and 2.71%,respectively,and annual incidence(per 1000 person-years)of 69.6 and 10.6,respectively.The risk factor for aMCI was age,whereas its protective factors were high education level,tea consumption and physical activity.Moreover,VCIND risk factors were age,hypertension and depression.The presence of endocrine disease,cerebral trauma or hypertension was associated with a faster decline in cognition over 1 year.Conclusions MCI is a serious health problem in China that will only worsen as the population ages if no widespread interventions are implemented.Preventive strategies that promote brain activity and support healthy lifestyle choices are required.We identified modifiable factors for MCI in older individuals.The easy-to-adopt solutions such as tea consumption and physical activity can aid in preventing MCI.
基金Supported by the Government Funded Clinical Medicine Excellent Talents Training Project of Hebei Province,No.ZF2024136National Science Foundation of Hebei Province,No.H2022206544Science and Technology Program of Hebei Province,No.SG2021189。
文摘BACKGROUND Mild behavioral impairment(MBI)refers to the neurobehavioral symptoms observed in older adults that may be potential risk factors for neurodegenerative diseases.While a significant number studies have explored the association between cerebrospinal fluid and MBI,only a few have examined the connection between plasma biomarkers and MBI.AIM To examine the prevalence of MBI in healthy older adults(HOAs)and individuals with mild cognitive impairment(MCI),as well as the association between MBI and plasma biomarkers of Alzheimer’s disease(AD).METHODS We enrolled a total of 241 subjects,which included 136 HOAs and 105 MCIs,from the Yuhua District of Shijiazhuang City,Hebei Province,China.The MBI symp-tom checklist(MBI-C)was utilized for the assessment and diagnosis of MBI,and a score of MBI-C≥6.5 was considered indicative of the condition.Fasting venous blood samples were collected from 70 patients,32 HOAs and 38 MCIs,and levels of amyloidβ-protein(Aβ)40,Aβ42,and hyperphosphorylated tau(p-Tau217)in these samples were measured using an enzyme-linked immunosorbent assay.RESULTS The prevalence of MBI in the HOAs and MCI groups was 4.4%and 15.3%,respectively(χ^(2)=7.262,P=0.007),with particularly notable decreases in motivation and increases in impulse dyscontrol(the highest detection rate)and social inappropriateness(P<0.05).The total MBI score correlated with Aβ42 and p-Tau217(r=-0.385,P=0.019;r=-0.330,P=0.041),but not with Aβ40 or the Aβ42/40 ratio.Among the subdomains,impulse dyscontrol was correlated with Aβ42(r=-0.401,P=0.025).CONCLUSION Both MCI and HOAs have exhibited a higher prevalence of MBI,with changes in impulse control behavior being the most common.MBI not only presents as an independent risk factor for cognitive decline but is also linked with AD-related peripheral biomarkers.
基金Supported by National Natural Science Foundation of China,No.72174061 and No.71704053Key Research and Development Program of Zhejiang Province,No.2025C02106+1 种基金China Scholarship Council Foundation,No.202308330251Health Science and Technology Project of Zhejiang Provincial Health Commission,No.2022KY370。
文摘BACKGROUND Older adults with mild cognitive impairment(MCI)often show motor dysfunction,including slower gait and impaired handwriting.While gait and handwriting parameters are promising for MCI screening,their combined potential to distinguish MCI from cognitively normal adults is unclear.AIM To assess gait and handwriting differences and their potential for screening MCI in older adults.METHODS Ninety-five participants,including 34 with MCI and 61 cognitively normal controls,were assessed for gait using the GAITRite^(R)system and handwriting with a dot-matrix pen.Five machine learning models were developed to assess the discriminative power of gait and handwriting data for MCI screening.RESULTS Compared to the cognitively normal group,the MCI group had slower gait velocity(Z=-2.911,P=0.004),shorter stride and step lengths(t=-3.005,P=0.003;t=2.863,P=0.005),and longer cycle,standing,and double support times(t=-2.274,P=0.025;t=-2.376,P=0.018;t=-2.717,P=0.007).They also had reduced cadence(t=2.060,P=0.042)and increased double support time variability(Z=-2.614,P=0.009).In handwriting,the MCI group showed lower average pressure(all tasks:Z=-2.135,P=0.033)and decreased accuracy(graphic task:Z=-2.447,P=0.014;Chinese character task:Z=-3.078,P=0.002).In the graphic task,they demonstrated longer time in air(Z=-2.865,P=0.004),reduced X-axis maximum velocities(Z=-3.237,P=0.001),and lower accelerations(X-axis:Z=-2.880,P=0.004;Y-axis:Z=-1.987,P=0.047)and maximum accelerations(X-axis:Z=-3.998,P<0.001;Y-axis:Z=-2.050,P=0.040).The multimodal analysis achieved the highest accuracy(74.4%)with the Gradient Boosting Classifier.CONCLUSION Integrating gait and handwriting kinematics parameters provides a viable method for distinguishing MCI,potentially supporting large-scale screening,especially in resource-limited settings.
基金Supported by Zhejiang Province Traditional Chinese Medicine Science and Technology Plan Project,No.2023ZL460Zhejiang Province Traditional Chinese Medicine Modernization Special Project,No.2021ZX011。
文摘BACKGROUND Mild cognitive impairment(MCI)is a transitional state between normal aging and Alzheimer's disease(AD),characterized by subtle cognitive decline.Amnestic MCI(aMCI),in particular,is a critical precursor often progressing to AD.There is growing interest in understanding the neuroanatomical correlates of aMCI,especially the role of gray matter volume(GMV)in cognitive and motor function decline.This study hypothesized that aMCI patients will exhibit reduced GMV,particularly in brain regions associated with cognition and motor control,impacting both cognitive performance and motor abilities.AIM To investigate the association of GMV with cognitive and motor functions in aMCI.METHODS In this cross-sectional study conducted from March 2022 to March 2024,45 aMCI patients and 45 normal controls from our Department of Geratology were enrolled.Voxel-based morphometry was used to compare GMV between groups.Correlation of differential GMV with cognitive scores and gait parameters was assessed via partial correlation analysis.Linear regression was used to assess associations between whole-brain GMV and gait measures.RESULTS GMV of aMCI region of interest(ROI)1 and ROI2 was negatively correlated with Activities of Daily Living(ADL)score.GMV of ROI6 was positively correlated with the total scores of Mini-Mental State Examination and Cambridge Cognitive Examination-Chinese Version(CAMCOG-C)and negatively correlated with ADL score.In the partial correlation analysis of cognitive and motor function parameters,age,gender,educational level,height,and weight were controlled,and the results showed that CAMCOG-C was negatively correlated with Dual Task of Time Up and Go Test(TUG)duration in the aMCI group.The volume of the left occipital gray matter in the aMCI group was negatively correlated with TUG.GMV of the bilateral frontal gyrus,right orbitofrontal gyrus,right occipital cleft,right supraoccipital gyrus,and left anterior central gyrus was positively correlated with walking speed.CONCLUSION GMV reduction in aMCI correlates with impaired cognition and motor function,emphasizing key roles for prefrontal,occipital,and central regions in gait disorders.
文摘Brain imaging is important in detecting Mild Cognitive Impairment(MCI)and related dementias.Magnetic Resonance Imaging(MRI)provides structural insights,while Positron Emission Tomography(PET)evaluates metabolic activity,aiding in the identification of dementia-related pathologies.This study integrates multiple data modalities—T1-weighted MRI,Pittsburgh Compound B(PiB)PET scans,cognitive assessments such as Mini-Mental State Examination(MMSE),Clinical Dementia Rating(CDR)and Functional Activities Questionnaire(FAQ),blood pressure parameters,and demographic data—to improve MCI detection.The proposed improved Convolutional Mixer architecture,incorporating B-cos modules,multi-head self-attention,and a custom classifier,achieves a classification accuracy of 96.3%on the Mayo Clinic Study of Aging(MCSA)dataset(sagittal plane),outperforming state-of-the-art models by 5%–20%.On the full dataset,the model maintains a high accuracy of 94.9%,with sensitivity and specificity reaching 89.1%and 98.3%,respectively.Extensive evaluations across different imaging planes confirm that the sagittal plane offers the highest diagnostic performance,followed by axial and coronal planes.Feature visualization highlights contributions from central brain structures and lateral ventricles in differentiating MCI from cognitively normal subjects.These results demonstrate that the proposed multimodal deep learning approach improves accuracy and interpretability in MCI detection.
文摘BACKGROUND Mild cognitive impairment(MCI)is a high-risk precursor to Alzheimer’s disease characterized by declining memory or other progressive cognitive functions without compromising daily living abilities.AIM To investigate the efficacy of repetitive transcranial magnetic stimulation(rTMS)in patients with MCI.METHODS This retrospective analysis involved 180 patients with MCI who were admitted to The First Hospital of Shanxi Medical University from January 2021 to June 2023.Participants were allocated into the research(n=98,receiving rTMS)and control groups(n=82,receiving sham stimulation).Memory tests,cognitive function assessments,event-related potential–P300 tests,and electroencephalogram(EEG)examinations were conducted pre-treatment and post-treatment.Further,memory quotient(MQ),cognitive function scores,and EEG grading results were compared,along with adverse reaction incidences.RESULTS Pre-treatment MQ scores,long-term and short-term memory,as well as immediate memory scores,demonstrated no notable differences between the groups.Post-treatment,the research group exhibited significant increases in MQ scores,long-term memory,and short-term memory compared to baseline(P<0.05),with these improvements being statistically superior to those in the control group.However,immediate memory scores exhibited no significant change(P>0.05).Further,the research group demonstrated statistically better post-treatment scores on the Revised Wechsler Memory Scale than the control group.Furthermore,post-treatment P300 latency and amplitude improved significantly in the research group,surpassing the control group.EEG grading in the research group improved,and the incidence of adverse reactions was significantly lower than in the control group.CONCLUSION Patients with MCI receiving rTMS therapy demonstrated improved memory and cognitive functions and EEG grading and exhibited high safety with fewer adverse reactions.
基金funded by the National Natural Science Foundation of China(No.82405530,81973921 and 72374068)the Science and Technology Research Project of Hubei Provincial Department of Education(No.B2023098)。
文摘Objective:As an age-related neurodegenerative disease,the prevalence of mild cognitive impairment(MCI)increases with age.Within the framework of traditional Chinese medicine,spleen-kidney deficiency syndrome(SKDS)is recognized as the most frequent MCI subtype.Due to the covert and gradual onset of MCI,in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes.There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS(MCI-SKDS).Methods:This investigation enrolled 312 elderly individuals diagnosed with MCI,who were randomly distributed into training and test datasets at a 3:1 ratio.Five machine learning methods,including logistic regression(LR),decision tree(DT),naive Bayes(NB),support vector machine(SVM),and gradient boosting(GB),were used to build a diagnostic prediction model for MCI-SKDS.Accuracy,sensitivity,specificity,precision,F1 score,and area under the curve were used to evaluate model performance.Furthermore,the clinical applicability of the model was evaluated through decision curve analysis(DCA).Results:The accuracy,precision,specificity and F1 score of the DT model performed best in the training set(test set),with scores of 0.904(0.845),0.875(0.795),0.973(0.875)and 0.973(0.875).The sensitivity of the training set(test set)of the SVM model performed best among the five models with a score of 0.865(0.821).The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset.The DCA of all models showed good clinical application value.The study identified ten indicators that were significant predictors of MCI-SKDS.Conclusion:The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical;the model demonstrates good predictive value and clinical applicability,and the DT model had the best performance.
文摘In the context of global aging,mild behavioral impairment(MBI)is present in 48.9%of patients with mild cognitive impairment(MCI).MBI,a neurobehavioral syndrome in the elderly,is an independent risk factor for cognitive decline and is closely related to peripheral blood biomarkers associated with Alzheimer's disease,offering new diagnostic and interventional avenues for early MCI.To summarize evidence on peripheral blood biomarkers related to MBI and their underlying mechanisms involving neuroinflammation,tau pathology,and oxidative stress,a systematic review of studies published between 2015 and 2024 was conducted.MBI is closely associated with peripheral blood biomarker changes.Neuroinflammatory markers like glial fibrillary acidic protein and neurofilament light indicate astrocyte activation and neural circuit disruption,with glial fibrillary acidic protein levels correlating with impulse dyscontrol scores.Chitinase-3-like protein 1,a marker of blood-brain barrier integrity,exacerbates neuroinflammation and is linked to depressive symptoms and hippocampal atrophy.Elevated phosphorylated tau proteins in blood correlate with brain tau deposition,increasing the risk of MBI and impairing cognition.Oxidative stress markers damage neurons and disrupt neurotransmission,and concurrent alterations in malondialdehyde and superoxide dismutase levels significantly elevate the risk of MBI.The correlation between MBI and biomarkers offers new diagnostic and interventional directions for early MCI.Future research should standardize MBI assessment,conduct longitudinal studies,explore biomarker-MBI relationships,investigate psychosocial impacts,and develop advanced detection methods.
文摘Objectives:The current study aimed to perform a meta-analysis to comprehensively investigate effect of physical activity on cognitive function in people with Mild Cognitive Impairment.The findings of this study can offer an important basis for identifying the significance of physical activity as an important factor in designing and implementing strategies to enhance cognitive function in mild cognitive impairment.Methods:21 articles were selected through academic databases(EBSCOhost,PubMed,ScienceDirect,Web of Science),and 20 Montreal Cognitive Assessment(MoCA)data and 15 Mini-Mental State Examination(MMSE)data were obtained.The study was conducted using the meta-analysis.To test the validity of each article included in this study,a funnel plot and Egger’s regression analysis were carried out to check for publication bias.Results:The 95%confidence interval(CI)for the effect size was interpreted as a small effect size if the effect size was between 0.2 and 0.5,a moderate effect size if the effect size was between 0.5 and 0.8,and large if the effect size was greater than 0.8.First,the meta-analysis of MoCA data showed a large effect size of 0.96;second,the meta-analysis of MMSE data indicated a large effect size of 0.93;and third,the meta-analysis of MoCA and MMSE data together indicated a moderate effect size of 0.68.Conclusion:The current study demonstrates the significant effect of physical activity on cognitive function and provides a basis for developing programs to improve cognitive function.People diagnosed with mild cognitive impairment generally experience minimal disruption in daily living activities.However,as the severity of the condition progresses,significant challenges emerge,impacting the individual’s ability to carry out daily tasks.Research has demonstrated that physical activity can enhance cognitive function in individuals with MCI.Consequently,it is recommended that these individuals be motivated to participate in physical activity to optimize their cognitive function and enhance their overall quality of life.
基金supported by the National Natural Science Foundation of China (No. 30570601)
文摘Objective To assess whether quick cognitive screening test （QCST） could quickly identify mild cognitive impairment （MCI）. Methods QCST and a full set of standardized neuropsychological tests, including mini-mental state examination （MMSE） and montreal cognitive assessment （MoCA） were performed. A total number of 121 cases of MCI [41 cases of amnestic MCI-single domain （aMCI-s）; 44 of amnestic MCI-multiple domain （aMCI-m）; 36 of nonamnestic MCI （naMCI）], 79 cases of mild Alzheimer’s disease （AD） and 186 healthy elderly volunteers were employed in the present study. All the participants （55-85 years old） had an educational level no less than 5 years. QCST subtests included word list recall, naming test, animal fluency test, similarity test, color trail-1min, clock drawing test, finger construction test, and digit span test. The total score of QCST was 90 points, 10 points for each index of subtests. Results The total scores of QCST in MCI, AD and the control groups were （58.13±8.18）, （44.53±10.54） and （72.92±6.85） points, respectively. According to the educational level, the cut off scores of participants with an educational level of 5-8 years, 9-12 years and more than 13 years were 63, 65 and 68 points, respectively. The sensitivity and specificity of QCST in detection of MCI were 87.6% （85.7% for aMCI-s, 90.1% for aMCI-m and 89.5% for naMCI） and 84.3%, respectively. The area under the curve was 0.923 （95% CI： 0.892-0.953）. Delayed memory, color trail-1min and similarity test could help distinguish between aMCI and naMCI. Conclusion QCST may have a good sensitivity and specificity for MCI detection, which warrants its further clinical application.
基金Supported by Special Research Project for Practice Development of National TCM Clinical Research Base,State Administration of Traditional Chinese Medicine(JDZX 2012139)
文摘Objective To observe the clinical effect of acupuncture in combination with medicine in the treatment of mild cognitive impairment after cerebral infarction as well as the impact on patients＇ daily living ability. Methods Seventy-two patients, in accordance with random number table, were divided into two groups, acupuncture combined with western medicine group （group A） and western medicine group （group B）, each group with 36 patients. In combination with nimodipine tablets, acupuncture which can regulate the mind and reinforce the intelligence [making Baihui （百会 GV 20）, Sishencong （四神聪EX-HN 1）, Sibai （四白 ST 2）, Fengchi （风池 GB 20）, Wanggu （完骨 GB 12）, Tianzhu （天柱 BL 10）, Shenmen （神门 HT 7）, Neiguan （内关 PC 6）, Shuigou （水沟 GV 26）, Sanyinjiao （三阴交 SP 6）, Taichong （太冲 LR 3）, Fenglong （丰隆 ST 40） as the main acupoints] was given in the treatment group （group A） while only nimodipine tablets were given in the control group （group B）. The efficacy of these two groups was evaluated by Montreal Cognitive Assessment （MoCA） Scale after the continuous treatment for three months. Results The remarkably effective rate was 69.4%.and the total effective rate was 91.7% in the treatment group, while the remarkably effective rate was 55.6% and the total effective rate was 80.6% in the control group; the differences between the two groups were statistically significant （P〈0.05）. When comparing the MoCA score before and after treatment, which was 20.23±4.67 before treatment and 26.84±3.87 after treatment in group A; 19.82±3.56 before treatment and 23.33±2.78 after treatment in group B, it was found that the score for both groups became higher after treatment than that before treatment. Furthermore, the increase of the score was higher in the treatment group （6.61±0.80） than that in the control group （3.51±0.78） and the differences were statistically significant （P〈0.05）. Conclusion Acupuncture, which can regulate the mind and reinforce the intelligence, combined with nimodipine tablets is an effective therapy for the treatment of mild cognitive impairment after cerebral infarction, which is superior to single treatment with nimodipine tablets.
基金supported by National Research Foundation(NRF)of Korea under the auspices of the Ministry of Science and ICT,Republic of Korea(No.NRF-2020R1A2B5B03096000,to KSH).
文摘Mild cognitive impairment(MCI)is a precursor to Alzheimer’s disease.It is imperative to develop a proper treatment for this neurological disease in the aging society.This observational study investigated the effects of acupuncture therapy on MCI patients.Eleven healthy individuals and eleven MCI patients were recruited for this study.Oxy-and deoxy-hemoglobin signals in the prefrontal cortex during working-memory tasks were monitored using functional near-infrared spectroscopy.Before acupuncture treatment,working-memory experiments were conducted for healthy control(HC)and MCI groups(MCI-0),followed by 24 sessions of acupuncture for the MCI group.The acupuncture sessions were initially carried out for 6 weeks(two sessions per week),after which experiments were performed again on the MCI group(MCI-1).This was followed by another set of acupuncture sessions that also lasted for 6 weeks,after which the experiments were repeated on the MCI group(MCI-2).Statistical analyses of the signals and classifications based on activation maps as well as temporal features were performed.The highest classification accuracies obtained using binary connectivity maps were 85.7%HC vs.MCI-0,69.5%HC vs.MCI-1,and 61.69%HC vs.MCI-2.The classification accuracies using the temporal features mean from 5 seconds to 28 seconds and maximum(i.e,max(5:28 seconds))values were 60.6%HC vs.MCI-0,56.9%HC vs.MCI-1,and 56.4%HC vs.MCI-2.The results reveal that there was a change in the temporal characteristics of the hemodynamic response of MCI patients due to acupuncture.This was reflected by a reduction in the classification accuracy after the therapy,indicating that the patients’brain responses improved and became comparable to those of healthy subjects.A similar trend was reflected in the classification using the image feature.These results indicate that acupuncture can be used for the treatment of MCI patients.
基金Project (No. 2003B070) supported by the Science and TechnologyProgram of Zhejiang Province, China
文摘Objective： To assess functional relationship by calculating inter- and intra-hemispheric electroencephalography （EEG） coherence at rest and during a working memory task of patients with mild cognitive impairment （MCI）. Methods： The sample consisted of 69 subjects： 35 patients （n = 17 males, n = 18 females; 52-71 years old） and 34 normal controls （n = 17 males, n = 17 females; 51 -63 years old）. Mini-mental state examination （MMSE） of two groups revealed that the scores of MCI patients did not differ significantly from those of normal controls （P〉0.05）. In EEG recording, subjects were performed at rest and during working memory task. EEG signals from F3-F4, C3-C4, P3-P4, T5-T6 and O1-O2 electrode pairs are resulted from the inter-hemispheric action, and EEG signals from F3-C3, F4-C4, C3-P3, C4-P4, P3-O1, P4-O2, T5-C3, T6-C4, T5-P3 and T6-P4 electrode pairs are resulted from the intra-hemispheric action for delta （1.0-3.5 Hz）, theta （4.0-7.5 Hz）, alpha-1 （8.0-10.0 Hz）, alpha-2 （10.5-13.0 Hz）, beta-1 （13.5-18.0 Hz） and beta-2 （18.5-30.0 Hz） frequency bands. The influence of inter- and intra-hemispheric coherence on EEG activity with eyes closed was examined using fast Fourier transformation from the 16 sampled channels. Results： During working memory tasks, the inter- and intra-hemispheric EEG coherences in all bands were significantly higher in the MCI group in comparison with those in the control group （P〈0.05）. However, there was no significant difference in inter- and intra-hemispheric EEG coherences between two groups at rest. Conclusion： Experimental results comprise evidence that MCI patients have higher degree of functional connectivity between hemispheres and in hemispheres during working condition, It suggests that MCI may be associated with compensatory processes during working memory tasks between hemispheres and in hemispheres. Moreover, failure of normal cortical connections may exist in MCI patients.
基金This study was funded by the Medical Innovation Project of Fujian Province,China(2020CXA002)the National Natural Science Foundation of China(82071222).
文摘Objectives Non-invasive and low-cost virtual reality(VR)technology is important for early evaluation and intervention in mild cognitive impairment(MCI).This study aimed to demonstrate the current status of overseas and domestic research as well as the focus and frontier of VR technology among individuals with MCI through a bibliometric analysis.Methods Studies from the core collection of Web of Science™between 1995 and 2020 were used;furthermore,CiteSpace 5.7 R3 was utilized to analyse information on authors/cited authors,keywords,burst words,and cited references.Results In total,230 publications were identified.Most studies were published in the USA(45 publications)and Italy(41 publications),where Guiseppe Riva ranks first(14 publications),and Tarnanas I is the author with the highest centrality(0.44).The hot topics in VR applications in the MCI population are‘physical activity,’‘people,’‘single-blind,’‘disease,’‘walking,’‘technology,’‘working memory,’and‘risk’in recent years.The keyword‘mild cognitive impairment’has attracted extensive attention since 2012,showing the strongest citation outbreak(8.28).The clustering results of the literature show the research types and emerging trends,including‘exergame,’‘serious games,’‘spatial navigation,’‘activities of daily living,’‘exercise,’‘enriched environment’and‘wayfinding.‘Conclusions Cognitive assessment and nonpharmacological intervention research on patients with MCI have become the focus of dementia prevention in recent years.Virtual technology,combined with traditional methods such as exercise therapy,provides new ideas for innovative cognitive evaluation and cognitive intervention.
基金supported by the Natural Science Foundation of Tianjin Municipal Science and Technology Commission(18JCQNJC10900)Tianjin Natural Science Foundation(17JCZDJC36300)。
文摘Subcortical vascular mild cognitive impairment(svMCI)is a common prodromal stage of vascular dementia.Although mounting evidence has suggested abnormalities in several single brain network metrics,few studies have explored the consistency between functional and structural connectivity networks in svMCI.Here,we constructed such networks using resting-state f MRI for functional connectivity and diffusion tensor imaging for structural connectivity in 30 patients with svMCI and 30 normal controls.The functional networks were then parcellated into topological modules,corresponding to several well-defined functional domains.The coupling between the functional and structural networks was finally estimated and compared at the multiscale network level(whole brain and modular level).We found no significant intergroup differences in the functional–structural coupling within the whole brain;however,there was significantly increased functional–structural coupling within the dorsal attention module and decreased functional–structural coupling within the ventral attention module in the svMCI group.In addition,the svMCI patients demonstrated decreased intramodular connectivity strength in the visual,somatomotor,and dorsal attention modules as well as decreased intermodular connectivity strength between several modules in the functional network,mainly linking the visual,somatomotor,dorsal attention,ventral attention,and frontoparietal control modules.There was no significant correlation between the altered module-level functional–structural coupling and cognitive performance in patients with svMCI.These findings demonstrate for the first time that svMCI is reflected in a selective aberrant topological organization in multiscale brain networks and may improve our understanding of the pathophysiological mechanisms underlying svMCI.
基金supported by the National Natural Science Foundation of China,No.81801071(to YJL)Top-notch Postgraduate Talent Cultivation Program of Chongqing Medical University,No.BJRC202106(to BC).
文摘Mild cognitive impairment(MCI)is a prodrome of Alzheimer’s disease pathology.Cognitive impairment patients often have a delayed diagnosis because there are no early symptoms or conventional diagnostic methods.Exosomes play a vital role in cell-to-cell communications and can act as promising biomarkers in diagnosing diseases.This study was designed to identify serum exosomal candidate proteins that may play roles in diagnosing MCI.Mass spectrometry coupled with tandem mass tag approach-based non-targeted proteomics was used to show the differentially expressed proteins in exosomes between MCI patients and healthy controls,and these differential proteins were validated using immunoblot and enzyme-linked immunosorbent assays.Correlation of cognitive performance with the serum exosomal protein level was determined.Nanoparticle tracking analysis suggested that there was a higher serum exosome concentration and smaller exosome diameter in individuals with MCI compared with healthy controls.We identified 69 exosomal proteins that were differentially expressed between MCI patients and healthy controls using mass spectrometry analysis.Thirty-nine exosomal proteins were upregulated in MCI patients compared with those in control patients.Exosomal fibulin-1,with an area under the curve value of 0.81,may be a biomarker for an MCI diagnosis.The exosomal protein signature from MCI patients reflected the cell adhesion molecule category.In particular,higher exosomal fibulin-1 levels correlated with lower cognitive performance.Thus,this study revealed that exosomal fibulin-1 is a promising biomarker for diagnosing MCI.
基金supported by grants from the National Natural Science Foundation of China(30970823,31371007)the Beijing Municipal Science and Technology Commission(Z131100006813022)the National Key Department of Neurology funded by Chinese Health and Family Planning Committee
文摘Amnestic mild cognitive impairment （aMCI） is a prodromal stage of Alzheimer＇s disease （AD）, and 75%-80% of aMCI patients finally develop AD. So, early identification of patients with aMCI or AD is of great significance for prevention and intervention. According to cross-sectional studies, it is known that the hippocampus, posterior cingulate cortex, and corpus callosum are key areas in studies based on structural MRI （sMRI）, functional MRI （fMRI）, and diffusion tensor imaging （DTI） respectively. Recently, longitudinal studies using each MRI modality have demonstrated that the neuroimaging abnormalities generally involve the posterior brain regions at the very beginning and then gradually affect the anterior areas during the progression of aMCI to AD. However, it is not known whether follow-up studies based on multi-modal neuroimaging techniques （e.g., sMRI, fMRI, and DTI） can help build effective MRI models that can be directly applied to the screening and diagnosis of aMCI and AD. Thus, in the future, large-scale multi-center follow-up studies are urgently needed, not only to build an MRI diagnostic model that can be used on a single person, but also to evaluate the variability and stability of the model in the general population. In this review, we present longitudinal studies using each MRI modality separately, and then discuss the future directions in this field.
基金supported by the National Natural Science Foundation of China (60831004 and 81270020)the CASIA Fund for Young Scientists with Lu-Jia-Xi award+2 种基金the Specific Healthcare Research Projects (13BJZ50)the Clinical Sciences Fund of the Chinese PLA General Hospital (2013FC-TSYS-1006)the Science Technological Innovation Nursery Fund of the Chinese PLA General Hospital (13KMM19), China
文摘Specific patterns of brain atrophy may be helpful in the diagnosis of Alzheimer＇s disease （AD）. In the present study, we set out to evaluate the utility of grey-matter volume in the classification of AD and amnestic mild cognitive impairment （aMCI） compared to normal control （NC）individuals. Voxel-based morphometric analyses were performed on structural MRIs from 35 AD patients, 27 aMCI patients, and 27 NC participants. A two-sample two-tailed t-test was computed between the NC and AD groups to create a map of abnormal grey matter in AD. The brain areas with significant differences were extracted as regions of interest （ROIs）, and the grey-matter volumes in the ROIs of the aMCI patients were included to evaluate the patterns of change across different disease severities. Next, correlation analyses between the grey-matter volumes in the ROIs and all clinical variables were performed in aMCI and AD patients to determine whether they varied with disease progression. The results revealed significantly decreased grey matter in the bilateral hippocampus/ parahippocampus, the bilateral superior/middle temporal gyri, and the right precuneus in AD patients.The grey-matter volumes with clinical variables were positively correlated Finally, we performed exploratory linear discriminative analyses to assess the classifying capacity of grey-matter volumes in the bilateral hippocampus and parahippocampus among AD, aMCI, and NC. Leave-one-out cross- validation analyses demonstrated that grey-matter volumes in hippocampus and parahippocampus accurately distinguished AD from NC. These findings indicate that grey-matter volumes are useful in the classification of AD.
基金supported by the Hong Kong Research Grants Council under grant NO.16202515 and 16212516Guangzhou HKUST Fok Ying Tung Research Institute,China Ministry of Science and Technology TCM Special Research Projects Program under grant No.200807011,No.201007002 and No.201407001-8+2 种基金Beijing Science and Technology Program under grant No.Z111107056811040Beijing New Medical Discipline Development Program under grant No.XK100270569Project of Beijing University of Chinese Medicine under grant No.2011-CXTD-23
文摘OBJECTIVE： To treat patients with vascular mild cognitive impairment （VMCI） using traditional Chinese medicine （TCM）, it is necessary to classify the patients into TCM syndrome types and to apply different treatments to different types. In this paper, we investigate how to properly carry out the classification for patients with VMCI aged 50 or above using a novel data-driven method known as latent tree analysis （LTA）. METHOD： A cross-sectional survey on VMCI was carried out in several regions in Northern China between February 2008 and February 2012 which resulted in a data set that involves 803 patients and 93 symptoms. LTA was performed on the data to reveal symptom co-occurrence patterns, and the patients were partitioned into clusters in multiple ways based on the patterns. The patient clusters were matched up with syndrome types, and population statistics of the clusters are used to quantify the syndrome types and to establish classification rules. RESULTS： Eight syndrome types are identified： Qi deficiency, Qi stagnation, Blood deficiency, Blood stasis, Phlegm-dampness, Fire-heat, Yang deficiency, and Yin deficiency. The prevalence and symptom occurrence characteristics of each syndrome type are determined. Quantitative classification rules are established for determining whether a patient belongs to each of the syndrome types. CONCLUSION： A solution for the TCM syndrome classification problem for patients with VMCI and aged 50 or above is established based on the LTA of unlabeled symptom survey data. The results can be used as a reference in clinic practice to improve the quality of syndrome differentiation and to reduce diagnosis variances across physicians. They can also be used for patient selection in research projects aimed at finding biomarkers for the syndrome types and in randomized control trials aimed at determining the efficacy of TCM treatments of VMCI.
