195 papers
This study utilized a Bayesian multimodal subtyping framework on over 121,000 cognitively unimpaired adults to identify four distinct risk profiles, revealing that those with cardiometabolic-depressive multimorbidity face the highest risk of developing mild cognitive impairment and derive the greatest protective benefit from antihypertensive and specific antidiabetic treatments.
The Slow-SPEED protocol outlines the design of the world's first non-pharmacological randomized controlled trials investigating the feasibility and efficacy of a remotely delivered, gamified exercise intervention for preventing Parkinson's disease across three distinct prodromal subgroups in the Netherlands, the United Kingdom, and the United States.
This study of over 228,000 individuals reveals that specific dietary factors, particularly alcohol and high-sugar intake, are significantly associated with distinct patterns of brain iron accumulation in motor regions, which in turn correlate with altered risks for Parkinson's disease, challenging prior assumptions about the relationship between central iron levels and disease susceptibility.
This post-hoc analysis of the AB10015 study demonstrates that excluding ALS patients with severe baseline functional loss reveals a significantly enhanced and favorable benefit-risk profile for masitinib, yielding greater improvements in functional decline, progression-free survival, and overall survival compared to the original primary analysis.
This retrospective study demonstrates that quantified brain atrophy is independently associated with a reduced risk of severe midline shift in patients with large MCA ischemic strokes and significantly improves the predictive accuracy of established clinical models for life-threatening cerebral edema.
Nine weeks of paced breathing training in adults aged 50–70 induced volume increases in the left orbitofrontal cortex driven by oscillatory heart rate power, which subsequently correlated with enhanced attentional control and memory performance, suggesting a frequency-general mechanism for improving neurovisceral integration and cognitive resilience in aging.
This retrospective study reveals that angiography-negative subarachnoid hemorrhage (anSAH) exhibits an early cerebrospinal fluid cytokine profile and inflammatory signature more similar to intracerebral hemorrhage than to aneurysmal subarachnoid hemorrhage, suggesting that anSAH represents a biologically distinct phenotype.
This study demonstrates that in cognitively unimpaired individuals, a concurrent decline in both episodic memory and awareness of that decline is significantly associated with higher levels of multimodal Alzheimer's disease biomarkers, suggesting that reduced awareness of cognitive impairment may serve as an early indicator of underlying AD pathology.
By analyzing rare damaging coding variants in large-scale population biobanks and disease cohorts, this study confirmed known genetic risks and identified novel risk genes for Alzheimer's and Parkinson's diseases, with the strongest novel signal found in ANKRD27.
This study demonstrates that a machine learning model utilizing multimodal data from the rapid, digital Clock and Recall (DCR) assessment can accurately and equitably predict Mini-Mental State Examination (MMSE) scores, offering a scalable solution to streamline eligibility screening for Alzheimer's disease-modifying therapies while mitigating the educational and cultural biases of traditional testing.
This paper presents a deep learning framework that uses CNN-based detection to selectively remove specific EEG artifacts only from contaminated segments, thereby preserving the fidelity of clean data and outperforming traditional global removal methods in clinical settings.
This study identifies biallelic loss-of-function variants in the THAP12 gene as a novel cause of severe autosomal recessive developmental and epileptic encephalopathy, demonstrating through mouse and zebrafish models that THAP12 is essential for early brain development and neuronal survival.
This study utilizing a large electronic health record database reveals that both cardiovascular factors (specifically higher systolic blood pressure and lower BMI) and social determinants (including non-English language preference, certain racial/ethnic backgrounds, and widowhood) independently predict a faster progression from mild cognitive impairment to dementia, highlighting the potential of integrating clinical and social data for early risk identification.
This study found that while cardiorespiratory fitness is positively associated with cerebral blood flow in individuals with coronary artery disease, this relationship is not observed in cognitively normal older adults and is largely mediated by body mass index.
This systematic review and meta-analysis evaluates blood-based biomarkers for identifying the ischaemic penumbra in acute ischaemic stroke, finding that while several candidates like MR-proADM, IL-10, and NSE show significant associations, substantial heterogeneity and risk of bias currently preclude their clinical implementation pending further rigorous validation.
This study found no significant differences in the volumes of hippocampus, amygdala, thalamus, and brainstem subregions between narcolepsy type 1 patients and healthy controls using automated MRI-based segmentation.
This study demonstrates that Kinematic adaptive Deep Brain Stimulation (KaDBS), a novel system utilizing wearable inertial sensors to dynamically adjust stimulation based on real-time gait metrics, is safe and significantly reduces freezing of gait and gait impairment in Parkinson's disease patients compared to conventional continuous stimulation.
This study demonstrates that baseline blood transcriptomic profiles analyzed through pathway-level gene sets can accurately predict distinct motor and non-motor progression trajectories in Parkinson's disease, offering a potential framework for identifying novel biomarkers and optimizing clinical trial designs.
This study demonstrates that spinal cord fMRI, when combined with nerve rootlet-based spatial normalization and optimized stimulation parameters, can reliably map the rostrocaudal distribution of sensory-evoked activity to specific spinal segments in humans, thereby overcoming previous localization uncertainties and supporting future translational research.
By analyzing multimodal data from over 10,000 UK Biobank participants, this study demonstrates that lifestyle and environmental factors robustly predict cognitive functioning, with a substantial portion of this association mediated by measurable brain and body health markers.