UNASSIGNED: This study aimed to investigate the role of galectin-3 (Gal-3; coded by LGALS3 gene), as a biomarker for MCI in T2DM patients and to develop and validate a predictive nomogram integrating galectin-3 with clinical risk factors for MCI prediction. Additionally, microRNA regulation of LGALS3 was explored.
UNASSIGNED: The study employed a cross-sectional design. A total of 329 hospitalized T2DM patients were recruited and randomly allocated into a training cohort (n = 231) and a validation cohort (n = 98) using 7:3 ratio. Demographic data and neuropsychological assessments were recorded for all participants. Plasma levels of galectin-3 were measured using ELISA assay. We employed Spearman\'s correlation and multivariable linear regression to analyze the relationship between galectin-3 levels and cognitive performance. Furthermore, univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for MCI in T2DM patients. Based on these analyses, a predictive nomogram incorporating galectin-3 and clinical predictors was developed. The model\'s performance was evaluated in terms of discrimination, calibration, and clinical utility. Regulatory miRNAs were identified using bioinformatics and their interactions with LGALS3 were confirmed through qRT-PCR and luciferase reporter assays.
UNASSIGNED: Galectin-3 was identified as an independent risk factor for MCI, with significant correlations to cognitive decline in T2DM patients. The developed nomogram, incorporating Gal-3, age, and education levels, demonstrated excellent predictive performance with an AUC of 0.813 in the training cohort and 0.775 in the validation cohort. The model outperformed the baseline galectin-3 model and showed a higher net benefit in clinical decision-making. Hsa-miR-128-3p was significantly downregulated in MCI patients, correlating with increased Gal-3 levels, while Luciferase assays confirmed miR-128-3p\'s specific binding and influence on LGALS3.
UNASSIGNED: Our findings emphasize the utility of Gal-3 as a viable biomarker for early detection of MCI in T2DM patients. The validated nomogram offers a practical tool for clinical decision-making, facilitating early interventions to potentially delay the progression of cognitive impairment. Additionally, further research on miRNA128\'s regulation of Gal-3 levels is essential to substantiate our results.

UNASSIGNED: Mild cognitive impairment (MCI) is a critical transitional phase from healthy cognitive aging to dementia, offering a unique opportunity for early intervention. However, few studies focus on the correlation of brain structure and functional activity in patients with MCI due to Alzheimer\'s disease (AD). Elucidating the complex interactions between structural-functional (SC-FC) brain connectivity and glymphatic system function is crucial for understanding this condition.
UNASSIGNED: The aims of this study were to explore the relationship among SC-FC coupling values, glymphatic system function and cognitive function. 23 MCI patients and 18 healthy controls (HC) underwent diffusion tensor imaging (DTI) and resting-state functional MRI (fMRI). DTI analysis along the perivascular space (DTI-ALPS) index and SC-FC coupling values were calculated using DTI and fMRI. Correlation analysis was conducted to assess the relationship between Mini-Mental State Examination (MMSE) scores, DTI-ALPS index, and coupling values. Receiver operating characteristic (ROC) curves was conducted on the SC-FC coupling between the whole brain and subnetworks. The correlation of coupling values with MMSE scores was also analyzed.
UNASSIGNED: MCI patients (67.74 ± 6.99 years of age) exhibited significantly lower coupling in the whole-brain network and subnetworks, such as the somatomotor network (SMN) and ventral attention network (VAN), than HCs (63.44 ± 6.92 years of age). Whole-brain network coupling was positively correlated with dorsal attention network (DAN), SMN, and visual network (VN) coupling. MMSE scores were significantly positively correlated with whole-brain coupling and SMN coupling. In MCI, whole-brain network demonstrated the highest performance, followed by the SMN and VAN, with the VN, DAN, limbic network (LN), frontoparietal network (FPN), and default mode network (DMN). Compared to HCs, lower DTI-ALPS index was observed in individuals with MCI. Additionally, the left DTI-ALPS index showed a significant positive correlation with MMSE scores and coupling values in the whole-brain network and SMN.
UNASSIGNED: These findings reveal the critical role of SC-FC coupling values and the ALPS index in cognitive function of MCI. The positive correlations observed in the left DTI-ALPS and whole-brain and SMN coupling values provide a new insight for investigating the asymmetrical nature of cognitive impairments.

Despite the growing interest in precision medicine-based therapies for Alzheimer\'s disease (AD), little research has been conducted on how individual AD risk factors influence changes in cognitive function following transcranial direct current stimulation (tDCS). This study evaluates the cognitive effects of sequential tDCS on 63 mild cognitive impairment (MCI) patients, considering AD risk factors such as amyloid-beta deposition, APOE ε4, BDNF polymorphism, and sex. Using both frequentist and Bayesian methods, we assessed the interaction of tDCS with these risk factors on cognitive performance. Notably, we found that amyloid-beta deposition significantly interacted with tDCS in improving executive function, specifically Stroop Word-Color scores, with strong Bayesian support for this finding. Memory enhancements were differentially influenced by BDNF Met carrier status. However, sex and APOE ε4 status did not show significant effects. Our results highlight the importance of individual AD risk factors in modulating cognitive outcomes from tDCS, suggesting that precision medicine may offer more effective tDCS treatments tailored to individual risk profiles in early AD stages.

BACKGROUND: Mild cognitive impairment (MCI) is a significant public health concern and a potential precursor to Alzheimer\'s disease (AD). This study leverages electronic health record (EHR) data to explore rural-urban differences in MCI incidence, risk factors, and healthcare navigation in West Michigan.
METHODS: Analysis was conducted on 1,528,464 patients from Corewell Health West, using face-to-face encounters between 1/1/2015 and 7/31/2022. MCI cases were identified using International Classification of Diseases (ICD) codes, focusing on patients aged 45+ without prior MCI, dementia, or AD diagnoses. Incidence rates, cumulative incidences, primary care physicians (PCPs), and neuropsychology referral outcomes were examined across rural and urban areas. Risk factors were evaluated through univariate and multivariate Cox regression analyses. The geographic distribution of patient counts, hospital locations, and neurology department referrals were examined.
RESULTS: Among 423,592 patients, a higher MCI incidence rate was observed in urban settings compared to rural settings (3.83 vs. 3.22 per 1,000 person-years). However, sensitivity analysis revealed higher incidence rates in rural areas when including patients who progressed directly to dementia. Urban patients demonstrated higher rates of referrals to and completion of neurological services. While the risk factors for MCI were largely similar across urban and rural populations, urban-specific factors for incident MCI are hearing loss, inflammatory bowel disease, obstructive sleep apnea, insomnia, being African American, and being underweight. Common risk factors include diabetes, intracranial injury, cerebrovascular disease, coronary artery disease, stroke, Parkinson\'s disease, epilepsy, chronic obstructive pulmonary disease, depression, and increased age. Lower risk was associated with being female, having a higher body mass index, and having a higher diastolic blood pressure.
CONCLUSIONS: This study highlights rural-urban differences in MCI incidence and access to care, suggesting potential underdiagnosis in rural areas likely due to reduced access to specialists. Future research should explore socioeconomic, environmental, and lifestyle determinants of MCI to refine prevention and management strategies across geographic settings.
UNASSIGNED: Leveraged EHRs to explore rural-urban differences in MCI in West Michigan.Revealed a significant underdiagnosis of MCI, especially in rural areas.Observed lower rates of neurological referrals and completions for rural patients.Identified risk factors specific to rural and urban populations.

OBJECTIVE: To assess the role of Machine Learning (ML) in identification critical factors of dementia and mild cognitive impairment.
METHODS: 371 elderly individuals were ultimately included in the ML analysis. Demographic information (including gender, age, parity, visual acuity, auditory function, mobility, and medication history) and 35 features from 10 assessment scales were used for modeling. Five machine learning classifiers were used for evaluation, employing a procedure involving feature extraction, selection, model training, and performance assessment to identify key indicative factors.
RESULTS: The Random Forest model, after data preprocessing, Information Gain, and Meta-analysis, utilized three training features and four meta-features, achieving an area under the curve of 0.961 and a accuracy of 0.894, showcasing exceptional accuracy for the identification of dementia and mild cognitive impairment.
CONCLUSIONS: ML serves as a identification tool for dementia and mild cognitive impairment. Using Information Gain and Meta-feature analysis, Clinical Dementia Rating (CDR) and Neuropsychiatric Inventory (NPI) scale information emerged as crucial for training the Random Forest model.

UNASSIGNED: The objective of the current pilot study was to investigate the feasibility and acceptability of a videoconference-based cognitive behavioral (CBT) intervention for caregivers of individuals living with mild cognitive impairment or early Alzheimer\'s disease. The intervention included psychoeducation on emotions, strategies for management of unhelpful emotions and thoughts, behavioral activation, breathing and relaxation, strategies for communication and information on external resources.
UNASSIGNED: This study used a cross-sectional design with two groups of four caregivers who received an 8-week CBT-based intervention via videoconference. Measures of feasibility and acceptability were collected post-intervention as well as suggestions for improvements.
UNASSIGNED: Eight female caregivers were enrolled in the intervention, one participant opted out at the seventh session. Of those who completed the program, all participants reported that it was very easy to participate using the online modality. All participants felt that the intervention was at least partly adapted to their experience and needs as a caregiver. Five out of seven participants (71%) indicated that they felt better and would recommend the intervention to another caregiver.
UNASSIGNED: The current study demonstrated that it is feasible and acceptable to use a videoconference CBT-based group intervention with MCI or mild AD female caregivers.
UNASSIGNED: This is the first videoconference-based cognitive behavioral intervention for caregivers of individuals living with MCI or mild AD.

BACKGROUND: Sodium phenylbutyrate and taurursodiol (PB and TURSO) is hypothesized to mitigate endoplasmic reticulum stress and mitochondrial dysfunction, two of many mechanisms implicated in Alzheimer\'s disease (AD) pathophysiology.
METHODS: The first-in-indication phase 2a PEGASUS trial was designed to gain insight into PB and TURSO effects on mechanistic targets of engagement and disease biology in AD. The primary clinical efficacy outcome was a global statistical test combining three endpoints relevant to disease trajectory (cognition [Mild/Moderate Alzheimer\'s Disease Composite Score], function [Functional Activities Questionnaire], and total hippocampal volume on magnetic resonance imaging). Secondary clinical outcomes included various cognitive, functional, and neuropsychiatric assessments. Cerebrospinal fluid (CSF) biomarkers spanning multiple pathophysiological pathways in AD were evaluated in participants with both baseline and Week 24 samples (exploratory outcome).
RESULTS: PEGASUS enrolled 95 participants (intent-to-treat [ITT] cohort); cognitive assessments indicated significantly greater baseline cognitive impairment in the PB and TURSO (n = 51) versus placebo (n = 44) group. Clinical efficacy outcomes did not significantly differ between treatment groups in the ITT cohort. CSF interleukin-15 increased from baseline to Week 24 within the placebo group (n = 34). In the PB and TURSO group (n = 33), reductions were observed in core AD biomarkers phosphorylated tau-181 (p-tau181) and total tau; synaptic and neuronal degeneration biomarkers neurogranin and fatty acid binding protein-3 (FABP3); and gliosis biomarker chitinase 3-like protein 1 (YKL-40), while the oxidative stress marker 8-hydroxy-2-deoxyguanosine (8-OHdG) increased. Between-group differences were observed for the Aβ42/40 ratio, p-tau181, total tau, neurogranin, FABP3, YKL-40, interleukin-15, and 8-OHdG. Additional neurodegeneration, inflammation, and metabolic biomarkers showed no differences between groups.
CONCLUSIONS: While between-group differences in clinical outcomes were not observed, most likely due to the small sample size and relatively short treatment duration, exploratory biomarker analyses suggested that PB and TURSO engages multiple pathophysiologic pathways in AD.
UNASSIGNED: Proteostasis and mitochondrial stress play key roles in Alzheimer\'s disease (AD).Sodium phenylbutyrate and taurursodiol (PB and TURSO) targets these mechanisms.The PEGASUS trial was designed to assess PB and TURSO effects on biologic AD targets.PB and TURSO reduced exploratory biomarkers of AD and neurodegeneration.Supports further clinical development of PB and TURSO in neurodegenerative diseases.

OBJECTIVE: Rare studies have investigated the association between heterogeneity of motor progression and risk of early cognitive impairment in Parkinson\'s disease (PD). In this study, we aim to identify distinct trajectories of motor progression longitudinally and investigate their impact on predicting mild cognitive impairment (MCI).
METHODS: A 5-year cohort including 415 PD patients at baseline was collected from the Parkinson\'s Progression Markers Initiative. The severity of motor symptoms was evaluated using the Movement Disorder Society Unified Parkinson\'s Disease Rating Scale part III. The latent class trajectory model and nonlinear mixed-effects model were used to analyze and delineate the longitudinal changes in motor symptoms. Propensity score matching (PSM) was used to minimize the impact of potential confounders. Cox proportional hazard models were applied to calculate hazard ratios for MCI, and a Kaplan-Meier curve was generated using the occurrence of MCI during the follow-up as the time-to-event.
RESULTS: Two latent trajectories were identified: a mild and remitting motor symptoms class (Class 1, 33.01%) and a severe and progressive motor symptom class (Class 2, 66.99%). Patients in Class 2 initially exhibited severe motor symptoms that worsened progressively despite receiving anti-PD medications. In comparison, patients in Class 1 exhibited milder symptoms that improved following drug therapy and a slower progression. During a 5-year follow-up, patients in Class 2 showed a higher risk of developing MCI compared to those in Class 1 before PSM (Log-Rank 28.58, p < 0.001) and after PSM (Log-Rank 8.20, p = 0.004).
CONCLUSIONS: PD patients with severe and progressive motor symptoms are more likely to develop MCI than those with mild and stable motor symptoms.

The expression of inflamma-miRs and human leukocyte antigen (HLA) haplotypes could indicate mild cognitive impairment (MCI) and Alzheimer\'s disease (AD). We used international databases to conduct a systematic review of studies on HLA variants and a meta-analysis of research on microRNAs (miRNAs). We aimed to analyze the discriminative value of HLA variants and miRNAs in MCI, AD and controls to evaluate the protective or causative effect of HLA in cognitive decline, establish the role of miRNAs as biomarkers for the early detection of AD, and find a possible link between miRNAs and HLA. Statistical analysis was conducted using Comprehensive Meta-analysis software, version 2.2.050 (Biostat Inc., Englewood, NJ, USA). The effect sizes were estimated by the logarithm base 2 of the fold change. The systematic review revealed that some HLA variants, such as HLA-B*4402, HLA-A*33:01, HLA-A*33:01, HLA-DPB1, HLA-DR15, HLA-DQB1*03:03, HLA-DQB1*06:01, HLA-DQB1*03:01, SNPs on HLA-DRB1/DQB1, and HLA-DQA1, predisposed to cognitive decline before the occurrence of AD, while HLA-A1*01, HLA-DRB1∗13:02, HLA-DRB1*04:04, and HLA-DRB1*04:01 demonstrated a protective role. The meta-analysis identified let-7 and miR-15/16 as biomarkers for the early detection of AD. The association between these two miRNA families and the HLA variants that predispose to AD could be used for the early screening and prevention of MCI.

UNASSIGNED: Earlier research focuses primarily on the cognitive changes due to Alzheimer\'s disease (AD); however, little is known with regard to changes in language competence across the lifespan.
UNASSIGNED: The present study aims to investigate the decline of language skills at the grammatical and syntactic levels due to changes in cognitive function.
UNASSIGNED: We administered the Litmus Sentence Repetition Task (SRT) to 150 native speakers of Greek who fall into five groups: 1) young healthy speakers, 2) cognitively intact elder healthy speakers, 3) speakers with subjective cognitive impairment (SCI), 4) speakers with mild cognitive impairment (MCI); and 5) speakers with AD dementia at the mild/moderate stages. All participants underwent a physical and neurological examination and cognitive screening with a standardized neuropsychological battery to assess cognitive status comprehensively and evaluate aspects like working memory, executive function, attention and memory to appropriately classify them.
UNASSIGNED: The data analysis revealed that the SRT had high discriminatory value in the development of AD; specifically, both accuracy and grammaticality indices were related to cognitive decline. Additionally, syntax significantly affected the performance of speakers with structures such as clitics being particularly challenging and in most structures the performance of speakers with MCI drops significantly compared to speakers with SCI.
UNASSIGNED: Linguistic indices revealed subtle early signs of cognitive decline that can be helpful in the early detection of AD, thus facilitating the clinical process offering support to language-based assessment tools such as sentence repetition, a non-invasive type of assessment to evaluate symptoms of AD.