Search Results (1,545)

Background: Fibromyalgia (FM) is a chronic condition characterized by widespread pain, fatigue, cognitive difficulties, and psychological symptoms. Patients often present distinct personality traits and psychopathological patterns associated with symptom severity. Objective: To examine psychopathological profiles in FM patients based on functional, physical–somatic, and emotional impairment domains, as well as on cumulative disease severity. Materials and Methods: A cross-sectional study was conducted with 70 women clinically diagnosed with FM at a specialized Fibromyalgia Unit. Psychological functioning was assessed using the Personality Assessment Inventory, and disease impact was measured with the Fibromyalgia Impact Questionnaire. Hierarchical cluster analyses were used to classify participants into mild and severe clusters across FIQ domains, and psychological profiles were compared. Results: Patients with severe functional impairment had more affective dysregulation (76.43 vs. 70.20, p < 0.01) and somatic complaints (85.57 vs. 79.76, p < 0.05) than those with mild impairment. The severe–physical cluster showed greater mood instability, somatization, and suicidal ideation (60.94 vs. 53.61, p < 0.05). The severe–emotional cluster had higher rates of major depression (85.71% vs. 64.28%) and persistent depressive disorder (76.19% vs. 70.61%, p < 0.05). Severe showed more emotional instability and somatization, distinguishing it from mild. Greater cumulative severity intensified depressive and somatic disorders. Discussion: Findings support FM’s biopsychosocial profile, where emotional distress may relate to psychological and physical symptoms, reinforcing the need for personalized, multidisciplinary care and comprehensive assessment. Full article

Background: We recently reported sex-dependent impairment in cognitive functions in male and female mice exposed for 24 h, 48 h or 15 days to 2G hypergravity (HG). Methods: In the present study, we investigated brain functional correlates by analyzing synaptic activity and plasticity in the CA1 area of the hippocampus in both genders of mice previously exposed to 2G for the same duration. This was assessed by electrophysiological extracellular recordings in ex vivo slice preparations. Results: Basal synaptic transmission and glutamate release were unchanged regardless of HG duration. However, plasticity was altered in a sex- and time-specific manner. In males, long-term potentiation (LTP) induced by strong high-frequency stimulation and NMDA receptor (NMDAr) activation was reduced by 26% after 24 h of exposure but recovered at later timepoints. This deficit was reversed by D-serine or glycine, suggesting decreased activation at the NMDAr co-agonist site. In females, LTP deficits (23%) were found only after 15 days following mild theta burst stimulation and were not reversed by D-serine. Long-term depression (LTD) was unaffected in both sexes. Conclusions: This study highlights, for the first time, sex-dependent divergence in the CA1 hippocampal plasticity timeline following 2G exposure. The synaptic changes depend on exposure duration and the stimulation protocol and could underlie the previously observed cognitive deficits. Full article

In individuals exposed to relatively mild methylmercury, even if they appeared to be independent in activities of daily living (ADL), slower judgment and motor responses in daily activities were observed, suggesting potential cognitive impairment. To quantitatively assess this impairment, we measured reaction time (RT) in a visual search test, as a visual cognitive ability test. The study participants included 24 residents from contaminated areas with sensory impairments in the limbs but no visual field defects (E group), as well as 12 individuals from non-contaminated areas (Group C). The 24 participants from contaminated areas were further divided into two groups: 12 without hand motor coordination disorders (Group E-HA) and 12 with such disorders (Group E+HA). Participants were instructed to search for the target letter “Z” on a computer screen, and the visual stimuli consisted of two, six, or ten alphabet letters. An equal number of trials contained “Z” and did not contain “Z,” for a total of thirty trials, which were conducted twice. RT was significantly longer in Group E+HA, followed by Group E-HA, and then Group C. However, in the second test, RT decreased in all cases, with a greater reduction in the exposed groups compared to the control group. These results suggest that methylmercury exposure may cause cognitive impairment, yet it also possesses plasticity. Full article

Background/Objectives: Solanezumab is a humanized monoclonal antibody designed to bind soluble amyloid-beta (Aβ) and facilitate its clearance from the brain, aiming to slow the progression of Alzheimer’s disease (AD). Methods: A systematic search was applied in four medical databases through October 2024 to identify phase 2 or 3 randomized controlled trials evaluating solanezumab in patients aged ≥50 years with mild AD or in preclinical stages. The primary outcomes were changes in cognitive and functional scales, including ADAS-cog14, MMSE, ADCS-ADL, and CDR-SB. Data were pooled using a random-effects model, and certainty of evidence was assessed using GRADE. Results: Seven trials involving 4181 participants were included. Solanezumab did not significantly reduce cognitive decline based on ADAS-cog14 (MD = −0.75; 95% CI: −2.65 to 1.15; very low certainty) or improve functional scores on ADCS-ADL (MD = 0.85; 95% CI: −1.86 to 3.56; very low certainty) and CDR-SB (MD = −0.15; 95% CI: −0.89 to 0.60; very low certainty). A modest but statistically significant improvement was observed in MMSE scores (MD = 0.59; 95% CI: 0.33 to 0.86; moderate certainty). Conclusions: While solanezumab may offer slight benefits in general cognitive performance, its overall impact on clinically meaningful outcomes remains limited. The results do not support its use as a disease-modifying therapy for Alzheimer’s disease in either preclinical or symptomatic stages. Full article

Background: Despite the growing demand for amyloid PET quantification, practical challenges remain. As automated software platforms are increasingly adopted to address these limitations, we evaluated the reliability of commercial tools for Centiloid quantification against the original Centiloid Project method. Methods: This retrospective study included 332 amyloid PET scans (165 [¹⁸F]Florbetaben; 167 [¹⁸F]Flutemetamol) performed for suspected mild cognitive impairments or dementia, paired with T1-weighted MRI within one year. Centiloid values were calculated using three automated software platforms, BTXBrain, MIMneuro, and SCALE PET, and compared with the original Centiloid method. The agreement was assessed using Pearson’s correlation coefficient, the intraclass correlation coefficient (ICC), a Passing–Bablok regression, and Bland–Altman plots. The concordance with the visual interpretation was evaluated using receiver operating characteristic (ROC) curves. Results: BTXBrain (R = 0.993; ICC = 0.986) and SCALE PET (R = 0.992; ICC = 0.991) demonstrated an excellent correlation with the reference, while MIMneuro showed a slightly lower agreement (R = 0.974; ICC = 0.966). BTXBrain exhibited a proportional underestimation (slope = 0.872 [0.860–0.885]), MIMneuro showed a significant overestimation (slope = 1.053 [1.026–1.081]), and SCALE PET demonstrated a minimal bias (slope = 1.014 [0.999–1.029]). The bias pattern was particularly noted for FMM. All platforms maintained their trends for correlations and biases when focusing on subthreshold-to-low-positive ranges (0–50 Centiloid units). However, all platforms showed an excellent agreement with the visual interpretation (areas under ROC curves > 0.996 for all). Conclusions: Three automated platforms demonstrated an acceptable reliability for Centiloid quantification, although software-specific biases were observed. These differences did not impair their feasibility in aiding the image interpretation, as supported by the concordance with visual readings. Nevertheless, users should recognize the platform-specific characteristics when applying diagnostic thresholds or interpreting longitudinal changes. Full article

Background/Objectives: We studied the possible protective effect of dietary curcumin in curry meals against cognitive decline and mild cognitive impairment (MCI) and dementia in a population-based Singapore Longitudinal Ageing cohort study. Methods: Baseline curry consumption frequency was categorized as five categories ranging from ‘never or rarely’ to ‘daily’. Among 2920 participants (mean age 65.5 ± SD 7.1 years) free of stroke, Parkinson’s disease, or traumatic brain injury at baseline, cognitive decline (MMSE drop ≥2) was assessed at 3–5 years (mean 4.5) follow-up. Occurrence of incident MCI-dementia was assessed at follow-up among 2446 participants without neurocognitive disorder at baseline. Results: A decreasing linear trend was observed between higher levels of curry consumption and cognitive decline (p = 0.037). The cumulative incidence of MCI-dementia decreased from 13.1% in those who never or rarely consumed curry to 3.6% in those who consumed curry daily (linear p < 0.001). The adjusted OR across levels of curry consumption exhibited a linear trend (p = 0.021) from OR = 0.61 (p < 0.05) for occasional consumption to OR = 0.21 (p < 0.001) for daily consumption. Conclusions: The intake of dietary curcumin through curry shows a dose-dependent reduction in incidence of cognitive decline and MCI-dementia in this Asian population of community-based elders. Full article

Alzheimer’s Disease and Dementia (ADD) progresses along a continuum of cognitive decline, typically from Subjective Cognitive Impairment (SCI) to Mild Cognitive Impairment (MCI) and eventually to dementia. While many studies have focused on classifying these clinical stages, fewer have examined whether brain connectomes encode this continuum in a low-dimensional, interpretable form. Motivated by the hypothesis that structural brain connectomes undergo complex yet compact changes across cognitive decline, we propose a Graph Neural Network (GNN)-based framework that embeds these connectomes into a two-dimensional manifold to capture the evolving patterns of structural connectivity associated with cognitive deterioration. Using attention-based graph aggregation and Principal Component Analysis (PCA), we find that MCI subjects consistently occupy an intermediate position between SCI and ADD, and that the observed transitions align with known clinical biomarkers of ADD pathology. This hypothesis-driven analysis is further supported by the model’s robust separation performance, with ROC-AUC scores of 0.93 for ADD vs. SCI and 0.81 for ADD vs. MCI. These findings offer an interpretable and neurologically grounded representation of dementia progression, emphasizing structural connectome alterations as potential markers of cognitive decline. Full article

About one billion people worldwide are affected by neurologic disorders. Among the various neurologic disorders, one of the most common is Alzheimer’s disease (AD). AD is a neurodegenerative disorder that progressively affects cognitive functions, disrupting the daily lives of millions of individuals. Mild cognitive impairment (MCI) is often considered a prodromal stage of Alzheimer’s disease. In this article, we retrieved data from the online available dataset GSE63060, which includes transcriptomic data of 329 blood samples, of which there are 104 cognitively normal controls, 80 MCI patients, and 145 AD patients. We used transcriptomic data related to all three groups to perform an over-representation analysis of the gene ontologies followed by a network analysis. The aim of our study is to pinpoint alterations, detectable through a non-invasive method, in biological processes affected in MCI that persist during AD. Our goal is to uncover transcriptomic changes that could support earlier diagnosis and the development of more effective therapeutic strategies, starting from the early stages of the disease, to slow down or mitigate its progression. Our work provides a consistent picture of the transcriptomic unbalance of many genes strongly involved in ribosomal formation and biogenesis and splicing processes both in patients with MCI and with AD. Full article

Mild cognitive impairment (MCI) is the transitional stage between normal cognition and dementia and is associated with arterial stiffness, which may lead to cardiovascular disease. A water-based exercise (W) presents a low-impact activity for the joints and increases resistance compared to exercises performed in the air, which benefits older adults. However, little evidence has been found regarding the effect of W on promoting cognitive and physical performance in older individuals with MCI. Therefore, this study aimed to investigate and compare the post-training effects of W alone and in combination with cognitive training on cognitive function, cardiovascular fitness, and arterial stiffness in older adults with MCI. Forty-six adults with MCI, aged 65 years or older, were enrolled. Participants were divided into two groups: a W group and a water-based exercise combined with cognitive training (W-COG) group. Both groups performed an aerobic exercise program in water for 60 min per/day, 3 day/week, for 12 weeks. Participants in the W-COG group simultaneously performed aerobic exercise and cognitive training in water. Cognitive performance, cardiovascular fitness, and arterial stiffness were examined before and after the intervention. The results revealed improvements in cognitive performance and cardiovascular fitness in both the W and W-COG groups after 12 weeks of intervention. However, there were no significant differences in cognitive and cardiovascular fitness changes between the two groups. Neither the W nor the W-COG groups showed a decrease in brachial pulse wave velocity. Therefore, W interventions have the potential to enhance cognitive function, restore cognition, and improve cardiovascular fitness in older adults with MCI. Full article

With a rapidly growing incidence and prevalence, Alzheimer’s disease (AD) is rapidly becoming one of the most disabling, lethal, and expensive diseases of the century. To diagnose AD as early as possible, the scientific world struggles to find reliable and non-invasive biomarkers that could predict the conversion of mild cognitive impairment to AD and delineate the ongoing pathogenic vicious pathways to be targeted with therapy. Research supports the use of blood biomarkers, such as Aβ_1-42/Aβ_1-40 ratio, phosphorylated tau181, and p-tau217 for diagnostic purposes, although the cut-offs are not clearly established and can depend on the assays used. For more accurate diagnosis, markers of neurodegeneration (neurofilament light) and neuroinflammation (glial fibrillary acidic protein) could be introduced in the biomarker panel. The recent approval of the Lumipulse G p-tau217/Aβ_1-42 plasma ratio by the FDA for the early detection of amyloid plaques associated with Alzheimer’s disease in adult patients, aged 55 years and older, exhibiting signs and symptoms of the disease represents a significant advancement in the diagnosis of Alzheimer’s disease, offering a more accessible and less invasive way to diagnose this devastating disease and allow potentially earlier access to treatment options. Full article

Background/Objectives: Dystonia, traditionally regarded as a purely motor disorder, is now increasingly recognized as involving clinically significant non-motor symptoms (NMSs) that can adversely affect patients’ health-related quality of life (HRQoL). This study aimed to assess HRQoL in Romanian patients with isolated dystonia and to evaluate the impact of two key NMSs, depression and cognitive impairment, on their HRQoL. We hypothesized that depression would have a greater adverse effect on HRQoL than cognitive impairment. Methods: A cross-sectional study was conducted involving 65 adult Romanian patients with isolated dystonia. HRQoL was measured using the Short Form-36 Health Survey (SF-36), including the physical component summary (PCS) and mental component summary (MCS). Depressive symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9), and cognitive impairment was assessed using the Montreal Cognitive Assessment (MoCA). Descriptive statistics, correlation analysis, and parametric and non-parametric tests were used. Multiple regression analysis was employed to evaluate associations between NMS and HRQoL. Results: The mean (SD) age was 56.6 (14.3) years, and 80% of participants were female. Depression and cognitive function were significantly associated with PCS (0.33 and −0.51, respectively) and MCS (0.26 and −0.78, respectively). Multiple regression analysis showed that the two NMS explained 38% of the variance in PCS and 58% of the variance in MCS. Depression had a greater impact on PCS and MCS than cognitive impairment (−0.47 vs. 0.33 and −0.72 vs. 0.16, respectively). Cognitive impairment (MoCA < 26) was present in 35.4% of patients, while 46.2% had at least mild depressive symptoms (PHQ-9 ≥ 5); 23.1% met criteria for moderate-to-severe depression (PHQ-9 ≥ 10). Depressive symptoms showed strong negative correlations with all SF-36 domains, while cognitive performance correlated modestly. Conclusions: Both depression and cognitive impairment have a significant negative impact on HRQoL in dystonia, with depression having a stronger effect, as we hypothesized. Routine screening for non-motor symptoms is essential to support better clinical outcomes and enhance patients’ quality of life. Full article

Background: Mild Cognitive Impairment (MCI) represents an intermediate stage between normal cognitive aging and Alzheimer’s Disease (AD). Early and accurate identification of MCI is crucial for implementing interventions that may delay or prevent further cognitive decline. This study aims to develop a machine learning-based model for differentiating between Cognitively Normal (CN) individuals and MCI patients using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Methods: An ensemble classification approach was designed by integrating Extra Trees, Random Forest, and Light Gradient Boosting Machine (LightGBM) algorithms. Feature selection emphasized clinically relevant biomarkers, including Amyloid-β 42, phosphorylated tau, diastolic blood pressure, age, and gender. The dataset was split into training and held-out test sets. A probability thresholding strategy was employed to flag uncertain predictions for potential deferral, enhancing model reliability in borderline cases. Results: The final ensemble model achieved an accuracy of 83.2%, a recall of 80.2%, and a precision of 86.3% on the independent test set. The probability thresholding mechanism flagged 23.3% of cases as uncertain, allowing the system to abstain from low-confidence predictions. This strategy improved clinical interpretability and minimized the risk of misclassification in ambiguous cases. Conclusions: The proposed AI-driven ensemble model demonstrates strong performance in classifying MCI versus CN individuals using multimodal ADNI data. Incorporating a deferral mechanism through uncertainty estimation further enhances the model’s clinical utility. These findings support the integration of machine learning tools into early screening workflows for cognitive impairment. Full article

Background and Aims: Primary biliary cholangitis (PBC) is a chronic autoimmune liver disease frequently associated with fatigue and mild cognitive impairment. Brain-derived neurotrophic factor (BDNF) plays key roles in neuroplasticity, immune regulation, and metabolism. This study aimed to evaluate plasma BDNF levels in early-stage PBC and examine their clinical and biochemical associations. Methods: In this observational study, plasma BDNF, IL-6, and IL-18 concentrations were measured by ELISA in 45 patients with early-stage PBC and 31 age- and sex-matched healthy controls (mean age 60.5 years; 96% women). All participants underwent liver elastography using point shear wave elastography (ElastPQ), Doppler ultrasound, laboratory testing, and assessment of cognitive function (PHES) and fatigue severity (MFIS). Non-invasive fibrosis scores (APRI, FIB-4) were calculated. Results: Median plasma BDNF concentrations were significantly higher in PBC patients than in controls [median: 21.04 ng/mL (IQR: 10.68–38.07) vs. 5.80 ng/mL (IQR: 4.58–7.54); p < 0.0001]. In PBC patients, higher BDNF levels correlated inversely with liver stiffness measured by ElastPQ (R = −0.39, p = 0.0258), spleen dimensions, splenic vein flow volume (R = −0.49, p = 0.0018), suggesting an association with milder liver fibrosis and early hemodynamic alterations. A trend toward association between BDNF and IL-6 levels was observed in multivariate analysis. No significant associations were found between BDNF concentrations and markers of hepatocellular injury, cognitive performance, or fatigue severity. Conclusions: Plasma BDNF concentrations are elevated in early-stage PBC and inversely correlate with liver fibrosis severity. No significant associations were found with hepatocellular injury, cognitive function, or fatigue. These findings suggest that BDNF may play a protective role against hepatic fibrogenesis, or alternatively, that BDNF concentrations may decline with advancing liver disease. Further studies are needed to clarify its significance in PBC. Full article

Background/Objectives: The prognostic uncertainty of Mild Cognitive Impairment (MCI) imposes comprehensive neuropsychological evaluations beyond mere memory assessment. However, previous investigations into other cognitive domains, such as attention, have yielded divergent findings. Furthermore, while evidence suggests the presence of sex differences across the spectrum of dementia-related conditions, no study has systematically explored attentional disparities between genders within this context. The current study aims to investigate differences in the attentional subcomponents, i.e., alerting, orienting, and executive control, between patients with MCI and healthy older controls (HOCs), emphasizing interactions between biological sex and cognitive impairment. Methods: Thirty-six participants (18 MCI, and 18 HOCs) were evaluated using the Attention Network Test (ANT). Raw RTs as well as RTs corrected for general slowing were analyzed using Generalized Mixed Models. Results: Both health status and sex influenced ANT performance, when considering raw RTs. Nevertheless, after adjusting for the baseline processing speed, the effect of cognitive impairment was no longer evident in men, while it persisted in women, suggesting specific vulnerabilities in females not attributable to general slowing nor to the MCI diagnosis. Moreover, women appeared significantly slower and less accurate when dealing with conflicting information. Orienting and alerting did not differ between groups. Conclusions: To the best of our knowledge, this is the first study investigating sex differences in attentional subcomponents in the aging population. Our results suggest that previously reported inconsistencies about the decline of attentional subcomponents may be attributable to such diversities. Systematically addressing sex differences in cognitive decline appears pivotal for informing the development of precision medicine approaches. Full article

Hip fractures in elderly patients pose significant clinical challenges, confronting us with high morbidity and mortality rates. A comprehensive geriatric assessment plays an important role in determining prognosis as well as the indication for surgery. Aim: In this study, we aim to (1) assess frailty-based functional status in seniors with hip fractures, (2) evaluate geriatric assessment’s predictive value for postoperative recovery, and (3) analyze 1-year postoperative survival. Material and Methods: This prospective study included 60 senior patients admitted for hip fracture in the Orthopedics Department. Patients were examined using geriatric assessment instruments Mini Mental State Examination (MMSE), Geriatric Depression Scale (GDS), Mini Nutritional Assessment (MNA), and Frailty Groningen Indicator (GFI). We recorded the sex, marital status, number of comorbidities, and number of recommended drugs. Results: In total, 65% of patients were frail pre-surgery; the proportion increased post-surgery to 86.7%; (p = 0.005). Age greater than 80 years and unmarried marital status were associated with higher frailty risk (p = 0.04; p = 0.03). Preoperatively, important predictors of frailty were mild–moderate cognitive impairment (p = 0.017), mild–moderate depression (p = 0.01), and malnutrition (p = 0.04). Postoperatively, only mild–moderate cognitive impairment (p = 0.04) and mild–moderate depression (p = 0.01) proved to be important predictors of frailty. According to the ROC curve, good predictors of postoperative frailty were shown to be preoperative frailty and the degree of polypharmacy and comorbidity. Of all parameters predictive of postoperative frailty, only the number of medications reached statistical significance (p < 0.038). The study identified a 1-year all-cause mortality rate of 42.6% in elderly patients who underwent hip fracture surgery, with a significant association between mortality and preoperative MMSE, GDS, and MNA scores. Conclusions: Complex geriatric assessment of senior patients with hip fracture can stratify postoperative risk and predict 1-year mortality and postoperative functional recovery. Key predictors include cognitive status, depression, malnutrition, and comorbidities. Multidisciplinary care and standardized evaluation are essential for improving outcomes. Full article