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Alzheimer's disease is the most common cause of dementia in elderly people. Research into Alzheimer's disease therapy has been at least partly successful in terms of developing symptomatic treatments, but has also had several failures in terms of developing disease-modifying therapies. These successes and failures have led to debate about the potential deficiencies in our understanding of the pathogenesis of Alzheimer's disease and potential pitfalls in diagnosis, choice of therapeutic targets, development of drug candidates, and design of clinical trials. Many clinical and experimental studies are ongoing, but we need to acknowledge that a single cure for Alzheimer's disease is unlikely to be found and that the approach to drug development for this disorder needs to be reconsidered. Preclinical research is constantly providing us with new information on pieces of the complex Alzheimer's disease puzzle, and an analysis of this information might reveal patterns of pharmacological interactions instead of single potential drug targets. Several promising randomised controlled trials are ongoing, and the increased collaboration between pharmaceutical companies, basic researchers, and clinical researchers has the potential to bring us closer to developing an optimum pharmaceutical approach for the treatment of Alzheimer's disease.

Aims: To investigate midlife cholesterol in relation to Alzheimer’s disease (AD) and vascular dementia (VaD) in a large multiethnic cohort of women and men. Methods: The Kaiser Permanente Northern California Medical Group (healthcare delivery organization) formed the database for this study. The 9,844 participants underwent detailed health evaluations during 1964–1973 at ages 40–45 years; they were still members of the health plan in 1994. AD and VaD were ascertained by medical records between 1 January 1994 and 1 June 2007. Cox proportional hazards models – adjusted for age, education, race/ethnic group, sex, midlife diabetes, hypertension, BMI and late-life stroke – were conducted. Results: In total, 469 participants had AD and 127 had VaD. With desirable cholesterol levels (<200 mg/dl) as a reference, hazard ratios (HR) and 95% CI for AD were 1.23 (0.97–1.55) and 1.57 (1.23–2.01) for borderline (200–239 mg/dl) and high cholesterol (≥240 mg/dl), respectively. HR and 95% CI for VaD were 1.50 (1.01–2.23) for borderline and 1.26 (0.82–1.96) for high cholesterol. Further analyses for AD (cholesterol quartiles, 1st quartile reference) indicated that cholesterol levels >220 mg/dl were a significant risk factor: HR were 1.31 (1.01–1.71; 3rd quartile, 221–248 mg/dl) and 1.58 (1.22–2.06; 4th quartile, 249–500 mg/dl). Conclusion: Midlife serum total cholesterol was associated with an increased risk of AD and VaD. Even moderately elevated cholesterol increased dementia risk. Dementia risk factors need to be addressed as early as midlife, before underlying disease(s) or symptoms appear.

This study investigates the evolution and prospective directions of big data applications within the global digital economy over the past twelve years. A comprehensive bibliometric analysis was conducted using Biblioshiny and included 752 documents authored by 1748 scholars and published in 416 specialized journals and academic books between 2013 and 2024. The findings reveal that scholarly interest in this area peaked in 2024. Co-occurrence network mapping highlights three dominant thematic trends in the applicability of big data within the digital economy: technological innovations, conceptual frameworks, and the role of China. Influential academic publications—such as Sustainability, PLoS ONE, and the proceedings of the 8th International Conference on Information Technology and Quantitative Management—have played a pivotal role in advancing research in this domain. Moreover, leading institutions, including the University of the Chinese Academy of Sciences, Shenzhen University, and Guizhou University, have emerged as pivotal contributors to advancing research in this field. China is the primary driving force and key player in reshaping the digital economy through big data, a role that is expected to contribute to global technological advancement in the future.

Although prevention of dementia and late-life cognitive decline is a major public health priority, there are currently no generally established prevention strategies or operational models for implementing such strategies into practice. This article is a narrative review of available evidence from multidomain dementia prevention trials targeting several risk factors and disease mechanisms simultaneously, in individuals without dementia at baseline. Based on the findings, we formulate recommendations for implementing precision risk reduction strategies into new services called Brain Health Services. A literature search was conducted using medical databases (MEDLINE via PubMed and SCOPUS) to select relevant studies: non-pharmacological multidomain interventions (i.e., combining two or more intervention domains), target population including individuals without dementia, and primary outcomes including cognitive/functional performance changes and/or incident cognitive impairment or dementia. Further literature searches covered the following topics: sub-group analyses assessing potential modifiers for the intervention effect on cognition in the multidomain prevention trials, dementia risk scores used as surrogate outcomes in multidomain prevention trials, dementia risk scores in relation to brain pathology markers, and cardiovascular risk scores in relation to dementia. Multidomain intervention studies conducted so far appear to have mixed results and substantial variability in target populations, format and intensity of interventions, choice of control conditions, and outcome measures. Most trials were conducted in high-income countries. The differences in design between the larger, longer-term trials that met vs. did not meet their primary outcomes suggest that multidomain intervention effectiveness may be dependent on a precision prevention approach, i.e., successfully identifying the at-risk groups who are most likely to benefit. One such successful trial has already developed an operational model for implementing the intervention into practice. Evidence on the efficacy of risk reduction interventions is promising, but not yet conclusive. More long-term multidomain randomized controlled trials are needed to fill the current evidence gaps, especially concerning low- and middle-income countries and integration of dementia prevention with existing cerebrovascular prevention programs. A precision risk reduction approach may be most effective for dementia prevention. Such an approach could be implemented in Brain Health Services.

Cortisol dysregulation, neuroinflammation, and cerebrovascular dysfunction are biological processes that have been separately shown to be affected in Alzheimer’s disease (AD). Here, we aimed to identify biomarker signatures reflecting these pathways in 108 memory clinic patients with subjective cognitive decline (SCD, N = 40), mild cognitive impairment (MCI, N = 39), and AD (N = 29). Participants were from the well-characterized Cortisol and Stress in Alzheimer’s Disease (Co-STAR) cohort, recruited at Karolinska University Hospital. Salivary diurnal cortisol measures and 41 CSF proteins were analyzed. Principal component analysis was applied to identify combined biosignatures related to AD pathology, synaptic loss, and neuropsychological assessments, in linear regressions adjusted for confounders, such as age, sex, education and diagnosis. We found increased CSF levels of C-reactive protein (CRP), interferon γ-inducible protein (IP-10), thymus and activation-regulated chemokine (TARC), intercellular adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1) in MCI patients. Further, markers of cortisol dysregulation (flattened salivary cortisol awakening response and flattened cortisol slope) correlated with increased levels of placental growth factor (PlGF), IP-10, and chitinase 3-like 1 (YKL-40) in the total cohort. A biosignature composed of cortisol awakening response, cortisol slope, and CSF IL-6 was downregulated in AD patients. Moreover, biomarker signatures reflecting overlapping pathophysiological processes of neuroinflammation and vascular injury were associated with AD pathology, synaptic loss, and worsened processing speed. Our findings suggest an early dysregulation of immune and cerebrovascular processes during the MCI stage and provide insights into the interrelationship of chronic stress and neuroinflammation in AD.

Background The Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) was a multicenter randomized controlled trial that reported beneficial effects on cognition for a 2-year multimodal intervention (diet, exercise, cognitive training, vascular risk monitoring) versus control (general health advice). This study reports exploratory analyses of brain MRI measures. Methods FINGER targeted 1260 older individuals from the general Finnish population. Participants were 60–77 years old, at increased risk for dementia but without dementia/substantial cognitive impairment. Brain MRI scans were available for 132 participants (68 intervention, 64 control) at baseline and 112 participants (59 intervention, 53 control) at 2 years. MRI measures included regional brain volumes, cortical thickness, and white matter lesion (WML) volume. Cognition was assessed at baseline and 1- and 2-year visits using a comprehensive neuropsychological test battery. We investigated the (1) differences between the intervention and control groups in change in MRI outcomes (FreeSurfer 5.3) and (2) post hoc sub-group analyses of intervention effects on cognition in participants with more versus less pronounced structural brain changes at baseline (mixed-effects regression models, Stata 12). Results No significant differences between the intervention and control groups were found on the changes in MRI measures. Beneficial intervention effects on processing speed were more pronounced in individuals with higher baseline cortical thickness in Alzheimer’s disease signature areas (composite measure of entorhinal, inferior and middle temporal, and fusiform regions). The randomization group × time × cortical thickness interaction coefficient was 0.198 ( p  = 0.021). A similar trend was observed for higher hippocampal volume (group × time × hippocampus volume interaction coefficient 0.1149, p  = 0.085). Conclusions The FINGER MRI exploratory sub-study did not show significant differences between the intervention and control groups on changes in regional brain volumes, regional cortical thicknesses, or WML volume after 2 years in at-risk elderly without substantial impairment. The cognitive benefits on processing speed of the FINGER intervention may be more pronounced in individuals with fewer structural brain changes on MRI at baseline. This suggests that preventive strategies may be more effective if started early, before the occurrence of more pronounced structural brain changes. Trial registration ClinicalTrials.gov, NCT01041989 . Registered January 5, 2010.

Background Determination of β-amyloid (Aβ) positivity and likelihood of underlying Alzheimer’s disease (AD) relies on dichotomous biomarker cut-off values. Individuals with mild cognitive impairment (MCI) and Aβ within the normal range may still have a substantial risk of developing dementia, primarily of Alzheimer type. Their prognosis, as well as predictors of clinical progression, are not fully understood. The aim of this study was to explore the associations of cerebrospinal fluid (CSF) biomarkers (Aβ42, total tau, phosphorylated tau) and other characteristics, including modifiable vascular factors, with the risk of progression to dementia among patients with MCI and normal CSF Aβ42. Methods Three hundred eighteen memory clinic patients with CSF and clinical data, and at least 1-year follow-up, were included. Patients had normal CSF Aβ42 levels based on clinical cut-offs. Cox proportional hazard models with age as time scale and adjusted for sex, education, and cognition (Mini-Mental State Examination) were used to investigate predictors of progression to dementia and Alzheimer-type dementia. Potential predictors included CSF biomarkers, cognitive performance (verbal learning and memory), apolipoprotein E ( APOE ) ε4 genotype, medial temporal lobe atrophy, family history of dementia, depressive symptoms, and vascular factors, including the Cardiovascular Risk Factors, Aging and Dementia (CAIDE) risk score. Predictive performance of patient characteristics was further explored with Harrell C statistic. Results Lower normal Aβ42 and higher total tau and phosphorylated tau were associated with higher dementia risk, and the association was not driven by Aβ42 values close to cut-off. Additional predictors included poorer cognition, APOE ε4 genotype, higher systolic blood pressure, and lower body mass index, but not the CAIDE dementia risk score. Aβ42 individually and in combination with other CSF biomarkers improved the risk prediction compared to age and cognition alone. Medial temporal lobe atrophy or vascular factors did not increase the predictive performance. Conclusions Possibility of underlying AD pathology and increased dementia risk should not be ruled out among MCI patients with CSF Aβ42 within the normal range. While cut-offs may be useful in clinical practice to identify high-risk individuals, personalized risk prediction tools incorporating continuous biomarkers may be preferable among individuals with intermediate risk. The role of modifiable vascular factors could be explored in this context.

The spread of social networks and the high level of penetration of digital content and mobile devices have created a society in which consumers expect constant communication from companies. In addition, communication on social media is often accompanied by the hope of being able to interact on an equal footing. In this way, companies hope that the use of social networks will not only increase sales, but also increase attention, brand page traffic, and customer loyalty. The purpose of this study was to provide the grounds for identifying the correlations between the interactive potential of social media based on dialogue-oriented communication and the quality of relationships with online customers. To achieve this goal, an online questionnaire was used in which 604 respondents from Romania participated (204 social media managers and 400 online customers). The results of the study showed that it is particularly important for companies to understand the role of interactive communication in social media and to thus build a bridge between the orientation of communication towards dialogue and relationships with online customers. It was found that the correct use of social networks could also support the achievement of public relation (PR) objectives. In addition, this study has implications for the development of customer-oriented online communication strategies by Romanian companies.

Background The pathophysiology of Alzheimer’s disease (AD) involves β -amyloid (A β ) accumulation. Early identification of individuals with abnormal β -amyloid levels is crucial, but A β quantification with positron emission tomography (PET) and cerebrospinal fluid (CSF) is invasive and expensive. Methods We propose a machine learning framework using standard non-invasive (MRI, demographics, APOE, neuropsychology) measures to predict future A β -positivity in A β -negative individuals. We separately study A β -positivity defined by PET and CSF. Results Cross-validated AUC for 4-year A β conversion prediction was 0.78 for the CSF-based and 0.68 for the PET-based A β definitions. Although not trained for the clinical status-change prediction, the CSF-based model excelled in predicting future mild cognitive impairment (MCI)/dementia conversion in cognitively normal/MCI individuals (AUCs, respectively, 0.76 and 0.89 with a separate dataset). Conclusion Standard measures have potential in detecting future A β -positivity and assessing conversion risk, even in cognitively normal individuals. The CSF-based definition led to better predictions than the PET-based definition.

Background Dementia preventive interventions targeting multiple modifiable risk factors are a promising approach. However, the impact of modifiable risk factors in the presence of beta-amyloid or phosphorylated-tau (p-tau) pathology is unclear. Methods The objective of the study was to examine the role of modifiable risk factors (vascular factors, depression, and smoking) in the progression to mild cognitive impairment (MCI) or dementia among 434 cognitively unimpaired (CU) and 611 individuals with MCI from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Vascular risk factors were summarized with the Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) score, dichotomized into higher versus lower risk. Depression and smoking (yes/no) were categorised according to medical history or current symptoms. Analyses were stratified by beta-amyloid negative (A-) and positive (A +), p-tau negative (T-) and positive (T +), or beta-amyloid and p-tau negative (A-T-) and positive (A + T +) biomarker status. Cox proportional hazard models were adjusted for age, sex, education, baseline MMSE score, baseline hippocampal volume and ApoE4 carrier status. Results Higher CAIDE score was associated with increased risk of progression to all-cause dementia in most MCI subgroups: adjusted hazard ratios (aHR) [95% CI] were 3.1 [1.43; 6.53] in the A- subgroup, 1.7 [1.20–2.27] in T + , 2.6 [1.06–6.59] in A-T-, and 1.6 [1.15–2.22] in the A + T + subgroup. Smoking (yes/no) was associated with increased dementia aHR in the A + MCI subgroup: 1.6 [1.07–2.34]. Depression increased dementia aHR in the T + MCI subgroup: 1.5 [1.06–2.02]. No significant associations were found in the CU biomarker subgroups. Conclusion Addressing modifiable risk factors carries an important potential for reducing the risk of dementia even after the onset of Alzheimer's pathology. Knowledge of biomarker status can further optimize prevention strategies.