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.

18F-fluoro-deoxy-glucose positron emission tomography (FDG-PET) is a useful paraclinical exam for the diagnosis of Alzheimer\'s disease (AD). In this narrative review, we report seminal studies in clinically probable AD that have shown the importance of posterior brain metabolic decrease and the paradoxical variability of the hippocampal metabolism. The FDG-PET pattern was a sensitive indicator of AD in pathologically confirmed cases and it was used for differential diagnosis of dementia conditions. In prodromal AD, the AD FDG-PET pattern was observed in converters and predicted conversion. Automated data analysis techniques provided variable accuracy according to the reported indices and machine learning methods showed variable reliability of results. FDG-PET could confirm AD clinical heterogeneity and image data driven analyses identified hypometabolic subtypes with variable involvement of the hippocampus, reminiscent if the paradoxical FDG uptake. In studies dedicated to clinical and metabolic correlations, episodic memory was related to metabolism in the default mode network (and Papez\'s circuit) in prodromal and mild AD stages, and specific cognitive processes were associated to precisely distributed brain metabolism. Cerebral metabolic correlates of anosognosia could also be related to current neuropsychological models. AD FDG-PET pattern was reported in preclinical AD stages and related to cognition or to conversion to mild cognitive impairment (MCI). Using other biomarkers, the AD FDG-PET pattern was confirmed in AD participants with positive PET-amyloid. Intriguing observations reported increased metabolism related to brain amyloid and/or tau deposition. Preserved glucose metabolism sometimes appear as a compensation, but it was frequently detrimental and the nature of such a preservation of glucose metabolism remains an open question. Limbic metabolic involvement was frequently related to non-AD biomarkers profile and clinical stability, and it was reported in non-AD pathologies, such as the limbic predominant age-related encephalopathy (LATE). FDG-PET abnormalities observed in the absence of classical AD proteinopathies can be useful to search for pathological mechanisms and differential diagnosis of AD.

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.

This article presents the incidence of geriatric syndromes in patients with chronic heart failure 65 years of age and older, depending on cognitive status. At the Russian gerontological center, 149 people with confirmed chronic heart failure were selected according to the European criteria of 2021. In this sample, 50,3% of patients had mild cognitive impairment, and 17,5% had severe cognitive impairment. With age, the incidence and severity of cognitive impairment increased. Among patients with cognitive impairment, there were more patients with reduced basic and instrumental activities of daily living, with a high risk of malnutrition and malnutrition, frailty and patients with hearing loss. Also, as cognitive functions declined, the median score of the Barthel and Lawton index, the mini nutritional assessment, the short physical performance battery, the Lubben social network scale decreased, and the median of the Morse fall risk scale and the geriatric depression scale increased. The presence of hearing loss was associated with a 3,6-fold increase in the odds of being diagnosed with cognitive impairment, and the presence of frailty syndrome, basic dependence in daily life, or the risk of malnutrition by a 2,4-fold increase.
В данной статье представлена частота встречаемости гериатрических синдромов у пациентов 65 лет и старше с ХСН в зависимости от когнитивного статуса. На базе Российского геронтологического научно-клинического центра были отобраны 149 человек с подтвержденной ХСН согласно Европейским критериям 2021 г. В данной выборке 50,3% пациентов имели умеренные когнитивные нарушения, 17,5% — выраженные. С возрастом частота встречаемости и тяжесть когнитивных нарушений возрастала. Среди пациентов с когнитивными нарушениями было больше пациентов со сниженной базовой и инструментальной активностью, с высоким риском развития мальнутриции и непосредственно мальнутрицией, синдромом старческой астении, а также с сенсорным дефицитом по слуху. Также по мере ухудшения когнитивных функций снижалась медиана индексов Бартел, Лоутона, краткой шкалы питания, краткой батареи тестов физического функционирования, шкалы социальной изоляции Люббена и нарастала медиана шкалы Морзе, гериатрической шкалы депрессии. Наличие сенсорного дефицита по слуху ассоциировалось с увеличением шансов выявления когнитивных нарушений в 3,6 раза, а наличие синдрома старческой астении, базовой зависимости в повседневной жизни или риска недостаточности питания — в 2,4 раза.

Computerized cognitive training (CCT) is a rapidly developing area of cognitive rehabilitation at the intersection of information technology and healthcare, the constantly updated results of which can be successfully translated into practical application in clinical medicine and in particular in gerontology. The basis of CCT, as a non-invasive method of influencing the functional activity of the brain and the processes of neuroplasticity, is software for stimulating cognitive functions in order to improve their productivity. The level of scientific and practical interest in CCP technology is growing rapidly. The article reports on the current state of research on the use of CCT aimed at correcting cognitive impairment. The purpose of this work is to systematize the available scientific data in this area, as well as to promote further integration of research in the field of information technology into clinical practice, in particular, to study the potential of CCT as a promising therapeutic tool in the paradigm of successful aging and prevention of the progression of cognitive impairment. This noninvasive intervention may improve global cognitive function in patients with clinically defined impairments and during normal aging in cognitively healthy older adults. However, new studies with fully comparable protocols are needed to evaluate in more detail the duration of the effect and the effectiveness of CCT in preventing cognitive decline in the long term.
Компьютеризированный когнитивный тренинг (ККТ) представляет собой быстро развивающееся направление когнитивной реабилитации на пересечении информационных технологий и здравоохранения, постоянно обновляемые результаты которого возможно с успехом транслировать в сферу практического применения в клинической медицине и, в частности, в геронтологии. Основу ККT, как неинвазивного метода воздействия на функциональную активность мозга и процессы нейропластичности, составляет программное обеспечение для стимуляции когнитивных функций с целью улучшения их продуктивности. Научный и практический интерес к технологии ККТ растет быстрыми темпами, и в определенной степени он даже больше, чем к некоторым другим областям реабилитации, ориентированным на здоровое старение. В статье сообщается о современном состоянии исследований применения ККТ, направленного на коррекцию когнитивных нарушений. Цель настоящей работы — не только систематизировать имеющиеся научные данные в этой области, но также способствовать дальнейшей интеграции быстро развивающихся исследований в области информационных технологий в клиническую практику. В частности, необходимо изучить потенциал ККТ как перспективного терапевтического инструмента в парадигме успешного старения и профилактики прогрессирования когнитивных нарушений. Проведенный анализ показывает, что такое вмешательство может улучшить глобальные когнитивные функции у пациентов с клинически установленными нарушениями и в процессе нормального старения у когнитивно-здоровых людей пожилого возраста. Однако необходимы новые исследования с максимально сопоставимыми протоколами, чтобы более детально оценить длительность эффекта и результативность ККТ для предотвращения снижения когнитивных функций в долгосрочной перспективе.

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.

OBJECTIVE: To investigate motor, non-motor and cognitive progression in early Parkinson\'s disease (PD) patients with Mild Cognitive Impairment (MCI).
METHODS: PD patients were recruited within 1 year of diagnosis and were classified into PD-MCI group and PD with normal cognition (PD-NC) group. H&Y staging scale, MDS-UPDRS part III were used to assess disease severity and motor progression. Non-motor symptom scale (NMSS) was used to evaluate the NMS progression. Cognitive progression was assessed from 5 cognitive domains. Annual progression changes in the longitudinal outcomes were examined via linear mixed model with random intercept effect. False discovery rate (FDR) method was performed to control for multiple testing comparison and q-value was calculated. We set the threshold of q-values as 0.1.
RESULTS: A total of 205 PD patients, including 107 PD-MCI and 98 PD-NC patients were assessed prospectively over a 5-year period. PD-MCI patients, compared to PD-NC group, had a significantly higher progression rate in H&Y score (0.11 vs. 0.06, p=0.03, q=0.08), MDS-UPDRS motor score (3.11 vs. 1.90 p<0.001, q=0.06) and postural instability gait difficulty (PIGD) score (0.40 vs. 0.20, p=0.02, q=0.07). PD-MCI group also exhibited significantly faster deterioration in NMSS perceptual domain (PD-MCI vs. PD-NC: 0.38 vs. -0.04, p=0.01, q=0.06) and cognitive visuospatial domain (PD-MCI vs. PD-NC: 0.13 vs. -0.06, p=0.048, q=0.09) after adjustment for confounders and multiple comparisons.
CONCLUSIONS: PD-MCI patients had faster decline in motor functions, visuo-perceptual and visuospatial performance. These findings provide a more comprehensive prognosis of PD-MCI, which could be helpful for clinician to manage PD-MCI patients.

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.

BACKGROUND: This study aims to evaluate the add-on effects of oral Chinese herbal medicine (CHM) for mild cognitive impairment (MCI), when used in addition to donepezil compared to donepezil alone.
METHODS: Randomized controlled trials comparing these treatments across all types of MCI were identified from nine databases and three registers until August 2023. Outcome measures were Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and adverse events (AEs). Methodological quality was assessed using Cochrane risk-of-bias tool, and evidence certainty was evaluated using the GRADE method.
RESULTS: Involving 1611 participants across 20 studies, meta-analysis results indicate that oral CHM combined with donepezil significantly improved cognitive function in MCI patients compared to donepezil alone, as evidenced by MMSE (1.88 [1.52, 2.24], I2 = 41%, 12 studies, 993 participants) and MoCA (MD: 2.01 [1.57, 2.44], I2 = 52%, 11 studies, 854 participants). Eleven studies reported details of AEs, identifying gastrointestinal symptoms and insomnia as the most common symptoms. No significant difference in AEs frequency was found between the groups (RR: 0.91 [0.59, 1.39], I2 = 4%, 11 studies, 808 participants). All 20 studies were evaluated as having \"some concerns\" regarding the overall risk of bias. The certainty of evidence for MMSE was \"moderate\" and \"low\" for MoCA. From frequently utilized herbs, two classical CHM formulae were identified: Kai xin san and Si wu decoction. The observed treatment effects of commonly used herbs may be exerted through multiple pharmacological mechanisms, including anti-inflammatory, anti-oxidative stress, anti-apoptotic actions, promotion of neuronal survival and modulation of the cholinergic system.
CONCLUSIONS: The concurrent use of oral CHM and donepezil appears to be more effective than donepezil alone in improving the cognitive function of MCI, without leading to an increase in AEs. While recognizing concerns of overall methodological quality, this combined therapy should be considered as an alternative option for clinical practice.

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.