Identification of subjective cognitive decline due to Alzheimer's disease using multimodal MRI combining with machine learning.

Subjective cognitive decline (SCD) is a preclinical asymptomatic stage of Alzheimer's disease (AD). Accurate diagnosis of SCD represents the greatest challenge for current clinical practice. The multimodal magnetic resonance imaging (MRI) features of 7 brain networks and 90 regions of interests from Chinese and ANDI cohorts were calculated. Machine learning (ML) methods based on support vector machine (SVM) were used to classify SCD plus and normal control. To assure the robustness of ML model, above analyses were repeated in amyloid ß (Aß) and apolipoprotein E (APOE) ɛ4 subgroups. We found that the accuracy of the proposed multimodal SVM method achieved 79.49% and 83.13%, respectively, in Chinese and ANDI cohorts for the diagnosis of the SCD plus individuals. Furthermore, adding Aß pathology and ApoE ɛ4 genotype information can further improve the accuracy to 85.36% and 82.52%. More importantly, the classification model exhibited the robustness in the crossracial cohorts and different subgroups, which outperforms any single and 2 modalities. The study indicates that multimodal MRI imaging combining with ML classification method yields excellent and powerful performances at categorizing SCD due to AD, suggesting potential for clinical utility.

The link between gut microbiome and Alzheimer's disease: From the perspective of new revised criteria for diagnosis and staging of Alzheimer's disease.

Over the past decades, accumulating evidence suggests that the gut microbiome exerts a key role in Alzheimer's disease (AD). The Alzheimer's Association Workgroup is updating the diagnostic criteria for AD, which changed the profiles and categorization of biomarkers from "AT(N)" to "ATNIVS." Previously, most of studies focus on the correlation between the gut microbiome and amyloid beta deposition ("A"), the initial AD pathological feature triggering the "downstream" tauopathy and neurodegeneration. However, limited research investigated the interactions between the gut microbiome and other AD pathogenesis ("TNIVS"). In this review, we summarize current findings of the gut microbial characteristics in the whole spectrum of AD. Then, we describe the association of the gut microbiome with updated biomarker categories of AD pathogenesis. In addition, we outline the gut microbiome-related therapeutic strategies for AD. Finally, we discuss current key issues of the gut microbiome research in the AD field and future research directions. HIGHLIGHTS: The new revised criteria for Alzheimer's disease (AD) proposed by the Alzheimer's Association Workgroup have updated the profiles and categorization of biomarkers from "AT(N)" to "ATNIVS." The associations of the gut microbiome with updated biomarker categories of AD pathogenesis are described. Current findings of the gut microbial characteristics in the whole spectrum of AD are summarized. Therapeutic strategies for AD based on the gut microbiome are proposed.

Coupling relationship between glucose and oxygen metabolisms to differentiate preclinical Alzheimer's disease and normal individuals.

The discovery of preclinical Alzheimer's disease (preAD) provides a wide time window for the early intervention of AD. The coupling relationships between glucose and oxygen metabolisms from hybrid PET/MRI can provide complementary information on the brain's physiological state for preAD. In this study, we purpose to explore the change of coupling relationship among 27 normal controls (NCs), 20 preADs, and 15 cognitive impairments (CIs). For each subject, we calculated the Spearman partial correlation between the fractional amplitude of low-frequency fluctuations (fALFF) and the regional homogeneity (ReHo) from functional image (fMRI), and the standard uptake value ratio (SUVR) from [18F] fluorodeoxyglucose positron emission tomography (18 F-FDG PET), in the whole-brain and default mode network (DMN) as a novel potential biomarker. The diagnostic performance of this biomarker was evaluated by the receiver operating characteristic analysis. Significant Spearman correlations between the FDG SUVR and the fALFF/ReHo were found in 98% of subjects. For the DMN-based biomarker, there was a significant decreasing trend for the preAD and CI groups compared to the NC group, whereas no significant difference in preAD based on whole-brain. The correlation ρ value for the FDG SUVR/ReHo showed the highest area under curve of the preAD classification (0.787). The results imply the coupling relationship changed during the preAD stage in the DMN area.

Multi-source sensor based urban habitat and resident health sensing: A case study of Wuhan, China.

The COVID-19 pandemic undoubtedly has a great impact on the world economy, especially the urban economy. It is urgent to study the environmental pathogenic factors and transmission route of it. We want to discuss the relationship between the urban living environment and the number of confirmed cases at the community scale, and examine the driving forces of community infection (e.g., environment, ecology, convenience, livability, and population density). Besides, we hope that our research will help make our cities more inclusive, safe, resilient, and sustainable. 650 communities with confirmed COVID-19 cases in Wuhan were selected as the research objects. We utilize deep learning semantic segmentation technology to calculate the Visible Green Index (VGI) and Sky View Factor (SVF) of street view and use Partial Least Squares Structural Equation Modeling (PLS-SEM) to study the driving forces of pandemic situation. Temperature and humidity information recorded by sensors was also used for urban sensing. We find that the more SVF has a certain inhibitory effect on the virus transmission, but contrary to our intuitive perception, higher VGI has a certain promotion effect. Also, the structural equation model constructed in this paper can explain the variance of 28.9% of the number of confirmed cases, and results (path coef.) demonstrate that residential density of community (0.517) is a major influencing factor for pandemic cases, whereas convenience of community living (0.234) strongly influence it. Communities with good suitability of community human settlement (e.g., construction time, price) are safer in the face of pandemic events. Does the influence of SVF and VGI on the results of the pandemic situation mean that sunlight can effectively block the spread of the virus? This spatial heterogeneity in different communities is helpful for us to explore the environmental transmission route of COVID-19.

Improved synthesis of phosphatidylserine using bio-based solvents, limonene and p-cymene.

PURPOSE OF WORK: The bio-based solvents limonene and p-cymene obtained from citrus waste were innovatively employed as the reaction media for enzymatic synthesis of phosphatidylserine. (R)-(+)-Limonene, which is available in large quantities from citrus waste, and its close derivative p-cymene, are promising green solvents. Herein, they were successfully employed as reaction media for enzyme-mediated transphosphatidylation of phosphatidylcholine with L-serine for phosphatidylserine synthesis for the first time. A 95 % yield of phosphatidylserine was achieved after 12 h and the side-reactions (which are the undesirable hydrolysis of phosphatidylcholine and phosphatidylserine) did not happen. This work presents an alternative strategy for preparing phosphatidylserine that possesses obvious advantages over the traditional processes in terms of high efficiency combined with environmental friendliness.

APOEε4 Carriers Exhibit Objective Cognitive Deficits: A Cross-Sectional Study in a Single Center Trial.

OBJECTIVE: To explore the association between the apolipoprotein E (APOE) genotype and objectively assessed cognitive function. METHODS: In this cross-sectional study, 537 participants underwent a neuropsychological assessment for cognitive function and blood testing for APOE genotype. Based on cognitive test results, participants were stratified into two cohorts: Cognitively Unimpaired participants (CU) and Cognitively Impaired participants (CI). The CI group was further divided into Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD). Furthermore, we conducted age stratification, categorizing participants into three age groups: age 1: <65 years, age 2: 65-75 years, and age 3: >75 years. We assessed the disparities in cognitive function associated with ε4 carrier status across different age brackets. Plasma amyloid-ß levels were measured in a cohort of 294 participants to investigate potential interactions involving ε4 carrier status, diagnosis, sex, or plasma markers. RESULTS: The APOE genotypic distribution among the 537 participants was characterized as follows: ε2/ε2 (5 participants), ε2/ε3 (67), ε2/ε4 (13), ε3/ε3 (330), ε3/ε4 (113), and ε4/ε4 (9). Allele frequencies were: ε3 at 78.21%, ε4 at 13.41%, and ε2 at 8.38%. Notably, the ε4 carrier frequency was markedly elevated in the AD group at 81.8% when compared to MCI at 32.8% and CU at 21.3% (p < 0.05). Within the Cognitively Unimpaired (CU) cohort, the sole discernible contrast between ε4+ and ε4- emerged in STT-B (p < 0.05). Within the CI group, ε4 carriers showed statistically poorer scores as compared to non-ε4 carriers in several cognitive tests (p < 0.05). Age stratification result revealed that, among ε4 carriers, cognitive function scores within the age 3 group were significantly inferior to those of age 1 and age 2 groups (p < 0.05). Plasma amyloid-ß detection was applied to the 294 participants. We tested plasma amyloid-ß (Aß42) and plasma amyloid-ß (Aß40) levels and calculated the Aß42/Aß40 ratio. We found that among female ε4 carriers, both Aß42 and the Aß42/Aß40 ratio were notably lower than their male counterparts (p < 0.05). CONCLUSIONS: The ε3/ε3 was the most prevalent among participants, succeeded by ε3/ε4 and ε2/ε3. The least prevalent were ε2/ε4, ε4/ε4, and ε2/ε2 genotypes. The ε3 was predominant, followed by the ε4 and ε2. Individuals with the ε4 allele exhibited significant cognitive impairment, with an especially high prevalence in AD group at 81.8%. The study unveils a pronounced correlation between the ε4 allele and cognitive deficits, implying its potential role in the advancement and severity of cognitive disorders, notably Alzheimer's disease. Cognitive function declines with age in individuals carrying the ε4, and women are more affected by ε4.

An integrated neuroimaging-omics approach for the gut-brain communication pathways in Alzheimer's disease.

A key role of the gut microbiota in the pathogenesis of neurodegenerative diseases, such as Alzheimer's disease (AD), has been identified over the past decades. Increasing clinical and preclinical evidence implicates that there is bidirectional communication between the gut microbiota and the central nervous system (CNS), which is also known as the microbiota-gut-brain axis. Nevertheless, current knowledge on the interplay between gut microbiota and the brain remains largely unclear. One of the primary mediating factors by which the gut microbiota interacts with the host is peripheral metabolites, including blood or gut-derived metabolites. However, mechanistic knowledge about the effect of the microbiome and metabolome signaling on the brain is limited. Neuroimaging techniques, such as multi-modal magnetic resonance imaging (MRI), and fluorodeoxyglucose-positron emission tomography (FDG-PET), have the potential to directly elucidate brain structural and functional changes corresponding with alterations of the gut microbiota and peripheral metabolites in vivo. Employing a combination of gut microbiota, metabolome, and advanced neuroimaging techniques provides a future perspective in illustrating the microbiota-gut-brain pathway and further unveiling potential therapeutic targets for AD treatments.

MCP-1 levels in astrocyte-derived exosomes are changed in preclinical stage of Alzheimer's disease.

Background: Alzheimer's disease (AD) is the most common form of dementia in older adults. There is accumulating evidence that inflammatory processes play a critical role in AD pathogenesis. In this study, we investigated whether inflammatory factors in plasma and astrocyte-derived exosomes (ADEs) from plasma are differentially expressed in the early stages of AD and their potential role in pathological processes in the AD continuum. Method: We included 39 normal controls (NCs), 43 participants with subjective cognitive decline (SCD), and 43 participants with amnestic mild cognitive impairment (aMCI)/AD. IL-6, IL-8, and MCP-1 in plasma and ADEs from plasma were evaluated using a commercial multiplex Luminex-based kit. Results: Pairwise comparisons between the groups showed no significant differences in plasma levels of IL-6, IL-8, or MCP-1. However, ADEs in the SCD group showed an increase in MCP-1 levels compared to the NC group. To differentiate the preclinical group, discriminant analysis was performed using sex, age, years of education, and genotype. This revealed a difference between the SCD and NC groups (area under the curve: 0.664). A Spearman correlation analysis of MCP-1 in plasma and ADEs showed no or weak correlation in the SCD (R = 0.150, p = 0.350) and aMCI/AD (R = 0.310, p = 0.041) groups, while a positive correlation in the NC group (R = 0.360, p = 0.026). Conclusion: Plasma IL-6, IL-8, and MCP-1 levels were not significantly different. However, the concentration of MCP-1 in ADEs is slightly altered during the preclinical phase of AD, which could be a potential role of the central neuron system (CNS) immune response in the AD continuum. Clinical trial registration: www.ClinicalTrials.gov, identifier: NCT03370744.

Alterations in Peripheral Metabolites as Key Actors in Alzheimer's Disease.

Growing evidence supports that Alzheimer's disease (AD) could be regarded as a metabolic disease, accompanying central and peripheral metabolic disturbance. Nowadays, exploring novel and potentially alternative hallmarks for AD is needed. Peripheral metabolites based on blood and gut may provide new biochemical insights about disease mechanisms. These metabolites can influence brain energy homeostasis, maintain gut mucosal integrity, and regulate the host immune system, which may further play a key role in modulating the cognitive function and behavior of AD. Recently, metabolomics has been used to identify key AD-related metabolic changes and define metabolic changes during AD disease trajectory. This review aims to summarize the key blood- and microbial-derived metabolites that are altered in AD and identify the potential metabolic biomarkers of AD, which will provide future targets for precision therapeutic modulation.

Brain Photobiomodulation Improves Sleep Quality in Subjective Cognitive Decline: A Randomized, Sham-Controlled Study.

BACKGROUND: Sleep appears to be a sensitive biomarker that facilitates early detection and effective intervention for Alzheimer's disease, while subjective cognitive decline (SCD) is a risk factor for Alzheimer's disease. Prefrontal cortex atrophy is associated with both sleep disruption and cognitive decline. Transcranial brain photobiomodulation (PBM) therapy can enhance frontal cortex oxygen consumption, increasing frontal cortex mediated memory function. OBJECTIVE: This study aimed to test whether PBM therapy targeting the frontal cortex could improve sleep and cognitive function in SCD. METHODS: Fifty-eight SCDs were divided into the PBM group (N = 32) in which real light therapy was administered and a sham light therapy group (N = 26). All the participants received either real light or sham light therapy for 6 days consecutively, while the sleep data were recorded. The n-back task was employed to measure each participant's working memory. RESULTS: We found no differences in sleep efficiency change (F = 211, p = 0.279), REM stage percent change (F = 420, p = 0.91), and wake-up time (F = 212, p = 0.277) between the two groups. The sleep efficiency and REM were improved within the true light group on the fifth day. The true light group perform better than the control group in the n-back test, the accuracy was higher in the 2-back test (88.6% versus 79.6%, p = 0.001), and the reaction time in 1-back was shorter (544.80±202.00 versus 592.87±222.05, p = 0.003). CONCLUSION: After five days of PBM therapy targeting the prefrontal cortex, sleep efficiency and N-back cognitive performance were improved on the fifth day.

Combination of gut microbiota and plasma amyloid-ß as a potential index for identifying preclinical Alzheimer's disease: a cross-sectional analysis from the SILCODE study.

BACKGROUND: Plasma amyloid-ß (Aß) may facilitate identification of individuals with brain amyloidosis. Gut microbial dysbiosis in Alzheimer's disease (AD) is increasingly being recognized. However, knowledge about alterations of gut microbiota in preclinical AD, as well as whether the combination of plasma Aß and gut microbiota could identify preclinical AD, remains largely unknown. METHODS: This study recruited 34 Aß-negative cognitively normal (CN-) participants, 32 Aß-positive cognitively normal (CN+) participants, and 22 patients with cognitive impairment (CI), including 11 patients with mild cognitive impairment (MCI) and 11 AD dementia patients. All participants underwent neuropsychological assessments and fecal microbiota analysis through 16S ribosomal RNA (rRNA) Illumina Miseq sequencing technique. Meso Scale Discovery (MSD) kits were used to quantify the plasma Aß40, Aß42, and Aß42/Aß40 in CN- and CN+ participants. Using Spearman's correlation analysis, the associations of global standard uptake value rate (SUVR) with altered gut microbiota and plasma Aß markers were separately evaluated. Furthermore, the discriminative power of the combination of gut microbiota and plasma Aß markers for identifying CN+ individuals was investigated. RESULTS: Compared with the CN- group, the CN+ group showed significantly reduced plasma Aß42 (p = 0.011) and Aß42/Aß40 (p = 0.003). The relative abundance of phylum Bacteroidetes was significantly enriched, whereas phylum Firmicutes and class Deltaproteobacteria were significantly decreased in CN+ individuals in comparison with that in CN- individuals. Particularly, the relative abundance of phylum Firmicutes and its corresponding SCFA-producing bacteria exhibited a progressive decline tendency from CN- to CN+ and CI. Besides, the global brain Aß burden was negatively associated with the plasma Aß42/Aß40 (r = -0.298, p = 0.015), family Desulfovibrionaceae (r = -0.331, p = 0.007), genus Bilophila (r = -0.247, p = 0.046), and genus Faecalibacterium (r = -0.291, p = 0.018) for all CN participants. Finally, the combination of plasma Aß markers, altered gut microbiota, and cognitive performance reached a relatively good discriminative power in identifying individuals with CN+ from CN- (AUC = 0.869, 95% CI 0.782 ~ 0.955). CONCLUSIONS: This study provided the evidence that the gut microbial composition was altered in preclinical AD. The combination of plasma Aß and gut microbiota may serve as a non-invasive, cost-effective diagnostic tool for early AD screening. Targeting the gut microbiota may be a novel therapeutic strategy for AD. TRIAL REGISTRATION: This study has been registered in ClinicalTrials.gov (NCT03370744, https://www.clinicaltrials.gov ) in November 15, 2017.

Cross-Cultural Longitudinal Study on Cognitive Decline (CLoCODE) for Subjective Cognitive Decline in China and Germany: A Protocol for Study Design.

BACKGROUND: Subjective cognitive decline (SCD) is considered as the first symptomatic manifestation of Alzheimer's disease (AD), which is also affected by different cultural backgrounds. Establishing cross-cultural prediction models of SCD is challenging. OBJECTIVE: To establish prediction models of SCD available for both the Chinese and European populations. METHODS: In this project, 330 SCD from China and 380 SCD from Germany are intended to be recruited. For all participants, standardized assessments, including clinical, neuropsychological, apolipoprotein E (APOE) genotype, blood, and multi-parameter magnetic resonance imaging (MRI) at baseline will be conducted. Participants will voluntarily undergo amyloid positron emission tomography (PET) and are classified into amyloid-ß (Aß) positive SCD (SCD+) and Aß negative SCD (SCD-). First, baseline data of all SCD individuals between the two cohorts will be compared. Then, key features associated with brain amyloidosis will be extracted in SCD+ individuals, and the diagnosis model will be established using the radiomics method. Finally, the follow-up visits will be conducted every 12 months and the primary outcome is the conversion to mild cognitive impairment or dementia. After a 4-year follow-up, we will extract factors associated with the conversion risk of SCD using Cox regression analysis. RESULTS: At present, 141 SCD from China and 338 SCD from Germany have been recruited. Initial analysis showed significant differences in demographic information, neuropsychological tests, and regional brain atrophy in SCD compared with controls in both cohorts. CONCLUSION: This project may be of great value for future implications of SCD studies in different cultural backgrounds. TRIAL REGISTRATION: ClinicalTrials.gov, NCT04696315. Registered 3 January 2021.

Women Exhibit Lower Global Left Frontal Cortex Connectivity Among Cognitively Unimpaired Elderly Individuals: A Pilot Study from SILCODE.

BACKGROUND: Mounting evidence suggests that sex differences exist in cognitive reserve (CR) for cognitively unimpaired (CU) elderly individuals. Global left frontal connectivity (gLFC connectivity) is a reliable neural substrate of CR. OBJECTIVE: The purpose of this study was to explore sex differences in gLFC connectivity among CU elderly individuals. METHODS: One hundred thirteen normal controls (NCs) (women = 66) and 132 individuals with subjective cognitive decline (SCD) (women = 92) were recruited from the Sino Longitudinal Study on Cognitive Decline (SILCODE) (data 1). Among them, 88 subjects underwent amyloid-ß (Aß) imaging, including 32 Aß+ and 56 Aß-subjects. Forty-six subjects underwent another rs-fMRI examination (data 2) to validate the repeatability of the calculation of gLFC connectivity, which was determined through seed-based functional connectivity between the LFC and voxels throughout the whole brain. Independent-sample t-tests were used to evaluate the sex differences in gLFC connectivity across different subgroups (NC versus SCD, Aß+ versus Aß-). Partial correlation analysis was used to calculate the correlations between gLFC connectivity and cognitive assessments. RESULTS: Women exhibited lower gLFC connectivity in both the NC (p = 0.001) and SCD (p = 0.020) subgroups than men. Women also exhibited lower gLFC connectivity in both the Aß-(p = 0.006) and Aß+ (p = 0.025) groups. However, the significant difference disappeared in the Aß+ group when considering the covariates of age, education, total intracranial volume, and APOE4-carrying status. In addition, gLFC connectivity values were negatively correlated with Geriatric Depression Scale scores in the SCD group (r = -0.176, p = 0.047). CONCLUSION: Women showed lower gLFC connectivity among CU elderly individuals.

Feature level-based group lasso method for amnestic mild cognitive impairment diagnosis.

BACKGROUND AND OBJECTIVE: Previous studies have indicated that brain morphological measures change in patients with amnestic mild cognitive impairment (aMCI). However, most existing classification methods cannot take full advantage of these measures. In this study, we improve traditional multitask learning framework by fully considering the relevance among related tasks and supplementary information from other unrelated tasks at the same time. METHODS: We propose a feature level-based group lasso (FL-GL) method in which a feature represents the average value of each ROI for each measure. First, we design a correlation matrix in which each row represents the relationship among different measures for each ROI. And this matrix is used to guide the feature selection based on a group lasso framework. Then, we train specific support vector machine (SVM) classifiers with the selected features for each measure. Finally, a weighted voting strategy is applied to combine these classifiers for a final prediction of aMCI from normal control (NC). RESULTS: We use the leave-one-out cross-validation strategy to verify our method on two datasets, the Xuan Wu Hospital dataset and the ADNI dataset. Compared with the traditional method, the results show that the classification accuracies can be improved by 6.12 and 4.92% with the FL-GL method on the two datasets. CONCLUSIONS: The results of an ablation study indicated that feature level-based group sparsity term was the core of our method. So, considering correlation at the feature level could improve the traditional multitask learning framework and our FL-GL method obtained better classification performance of patients with MCI and NCs.

Differences in Functional Brain Networks Between Subjective Cognitive Decline with and without Worry Groups: A Graph Theory Study from SILCODE.

BACKGROUND: Evidence suggests that subjective cognitive decline (SCD) individuals with worry have a higher risk of cognitive decline. However, how SCD-related worry influences the functional brain network is still unknown. OBJECTIVE: In this study, we aimed to explore the differences in functional brain networks between SCD subjects with and without worry. METHODS: A total of 228 participants were enrolled from the Sino Longitudinal Study on Cognitive Decline (SILCODE), including 39 normal control (NC) subjects, 117 SCD subjects with worry, and 72 SCD subjects without worry. All subjects completed neuropsychological assessments, APOE genotyping, and resting-state functional magnetic resonance imaging (rs-fMRI). Graph theory was applied for functional brain network analysis based on both the whole brain and default mode network (DMN). Parameters including the clustering coefficient, shortest path length, local efficiency, and global efficiency were calculated. Two-sample T-tests and chi-square tests were used to analyze differences between two groups. In addition, a false discovery rate-corrected post hoc test was applied. RESULTS: Our analysis showed that compared to the SCD without worry group, SCD with worry group had significantly increased functional connectivity and shortest path length (p = 0.002) and a decreased clustering coefficient (p = 0.013), global efficiency (p = 0.001), and local efficiency (p < 0.001). The above results appeared in both the whole brain and DMN. CONCLUSION: There were significant differences in functional brain networks between SCD individuals with and without worry. We speculated that worry might result in alterations of the functional brain network for SCD individuals and then result in a higher risk of cognitive decline.

Impaired cerebral vascular and metabolic responses to parametric N-back tasks in subjective cognitive decline.

Previous studies reported abnormally increased and/or decreased blood oxygen level-dependent (BOLD) activations during functional tasks in subjective cognitive decline (SCD). The neurophysiological basis underlying these functional aberrations remains debated. This study aims to investigate vascular and metabolic responses and their dependence on cognitive processing loads during functional tasks in SCD. Twenty-one SCD and 18 control subjects performed parametric N-back working-memory tasks during MRI scans. Task-evoked percentage changes (denoted as δ) in cerebral blood volume (δCBV), cerebral blood flow (δCBF), BOLD signal (δBOLD) and cerebral metabolic rate of oxygen (δCMRO2) were evaluated. In the frontal lobe, trends of decreased δCBV, δCBF and δCMRO2 and increased δBOLD were observed in SCD compared with control subjects under lower loads, and these trends increased to significant differences under the 3-back load. δCBF was significantly correlated with δCMRO2 in controls, but not in SCD subjects. As N-back loads increased, the differences between SCD and control subjects in δCBF and δCMRO2 tended to enlarge. In the parietal lobe, no significant between-group difference was observed. Our findings suggested that impaired vascular and metabolic responses to functional tasks occurred in the frontal lobe of SCD, which contributed to unusual BOLD hyperactivation and was modulated by cognitive processing loads.

A New Geo-Propagation Model of Event Evolution Chain Based on Public Opinion and Epidemic Coupling.

The online public opinion is the sum of public views, attitudes and emotions spread on major public health emergencies through the Internet, which maps out the scope of influence and the disaster situation of public health events in real space. Based on the multi-source data of COVID-19 in the context of a global pandemic, this paper analyzes the propagation rules of disasters in the coupling of the spatial dimension of geographic reality and the dimension of network public opinion, and constructs a new gravity model-complex network-based geographic propagation model of the evolution chain of typical public health events. The strength of the model is that it quantifies the extent of the impact of the epidemic area on the surrounding area and the spread of the epidemic, constructing an interaction between the geographical reality dimension and online public opinion dimension. The results show that: The heterogeneity in the direction of social media discussions before and after the "closure" of Wuhan is evident, with the center of gravity clearly shifting across the Yangtze River and the cyclical changing in public sentiment; the network model based on the evolutionary chain has a significant community structure in geographic space, divided into seven regions with a modularity of 0.793; there are multiple key infection trigger nodes in the network, with a spatially polycentric infection distribution.

Dynamic network connectivity predicts subjective cognitive decline: the Sino-Longitudinal Cognitive impairment and dementia study.

Subjective cognitive decline (SCD) is the preclinical stage of Alzheimer's disease (AD), the most common neurodegenerative disease in the elderly. We collected resting-state functional MRI data and applied novel graph-theoretical analyses to investigate the dynamic spatiotemporal cerebral connectivities in 63 individuals with SCD and 67 normal controls (NC). Temporal flexibility and spatiotemporal diversity were mapped to reflect dynamic time-varying functional interactions among the brain regions within and outside communities. Temporal flexibility indicates how frequently a brain region interacts with regions of other communities across time; spatiotemporal diversity describes how evenly a brain region interacts with regions belonging to other communities. SCD and NC differed in large-scale brain dynamics characterized by the two measures, which, with support vector machine, demonstrated higher classification accuracies than conventional static parameters and structural metrics. The findings characterize dynamic network dysfunction that may serve as a biomarker of the preclinical stage of AD.

Combining Visual Rating Scales for Medial Temporal Lobe Atrophy and Posterior Atrophy to Identify Amnestic Mild Cognitive Impairment from Cognitively Normal Older Adults: Evidence Based on Two Cohorts.

BACKGROUND: Visual rating scales for medial temporal lobe atrophy (MTA) and posterior atrophy (PA) have been reported to be useful for Alzheimer's disease diagnosis in routine clinical practice. OBJECTIVE: To investigate the efficacy of combined MTA and PA visual rating scales to discriminate amnestic mild cognitive impairment (aMCI) patients from healthy controls. METHODS: This study included T1-weighted MRI images from two different cohorts. In the first cohort, we recruited 73 patients with aMCI and 48 group-matched cognitively normal controls for training and validation. Visual assessments of MTA and PA were carried out for each participant. Global gray matter volume and density were estimated using voxel-based morphometry analysis as the objective reference. We investigated the discriminative power of a single visual rating scale and the combination of the MTA and PA rating scales for identifying aMCI. The second cohort, consisting of 33 aMCI patients and 45 controls, was used to verify the reliability of the visual assessments. RESULTS: Compared with the single visual rating scale, the combination of the MTA and PA exhibited the best discriminative power, with an AUC of 0.818±0.041, which was similar to the diagnostic accuracy of the gray matter volumetric measures. The discriminative power of the combined MTA and PA was verified in the second cohort (AUC 0.824±0.058). CONCLUSION: The combined MTA and PA rating scales demonstrated practical diagnostic value for distinguishing aMCI patients from controls, suggesting its potential to serve as a convenient and reproducible method to assess the degree of atrophy in clinical settings.

Clinical Characteristics in Subjective Cognitive Decline with and without Worry: Baseline Investigation of the SILCODE Study.

BACKGROUND: Subjective cognitive decline (SCD) refers to the self-perception of cognitive decline among cognitively normal elderly individuals. SCD related worry confers a higher risk of developing cognitive decline. However, the clinical characteristics of SCD patients with worry are not clear. OBJECTIVE: To explore the clinical characteristics of SCD patients with worry. METHODS: A cross-sectional study was carried out, with 270 consecutive participants of the Sino Longitudinal Study on Cognitive Decline (SILCODE) study. Participants were classified as normal controls (n = 36), SCD patients without worry (n = 91), or SCD patients with worry (n = 143) and were comprehensively compared on 1) their self-perception of cognitive decline, 2) multiple cognitive domains, 3) neuropsychiatric symptoms, and 4) sleep status. RESULTS: SCD patients with worry had significantly more self-perception of cognitive decline (p < 0.001); increased depression (p < 0.001) and anxiety (p < 0.001); decreased sleep quality (p < 0.001), sleep latency (p < 0.05), sleep time (p < 0.01), and sleep efficiency (p < 0.05); more sleep disorders (p < 0.05) and daytime dysfunction (p < 0.05); and a higher global score on the Pittsburgh Sleep Quality Index (p < 0.001) than normal controls. Although there was a significant increase only in self-perception of cognitive decline (p < 0.001), anxiety (p < 0.001), and Pittsburgh Sleep Quality Index scores (p < 0.05), the severity of the increase in those without worry was between that in SCD patients with worry and normal controls. CONCLUSION: Our findings show that participants who had SCD with worry showed distinct clinical characteristics compared with normal controls and SCD patients without worry, which could be useful for understanding the higher risk in SCD patients with worry of subsequently developing Alzheimer's disease.