228 papers
Neurology explores the intricate workings of the brain and nervous system, tackling everything from memory and movement to complex conditions like epilepsy and Alzheimer's. This field seeks to understand how our minds function and what happens when that delicate machinery falters, aiming to improve lives through better diagnosis and treatment.
At Gist.Science, we make the latest research from medRxiv accessible to everyone. We process every new preprint in this category, offering both straightforward plain-language explanations and detailed technical summaries so you can grasp the science at your own pace. Below are the latest papers in neurology, ready for you to explore.
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 systematic review and meta-analysis of 32 studies involving 3,212 stroke survivors found that theory-based self-management interventions, particularly those grounded in self-efficacy theory, significantly improve self-efficacy and self-management behaviors, although the magnitude of the behavioral improvement is uncertain due to high heterogeneity among the diverse theoretical frameworks used.
This study found that while adults with new-onset epilepsy have a consistently higher risk of starting SSRI treatment compared to the general population, the shift toward newer antiseizure medications did not increase this likelihood, revealing a persistent and potentially widening treatment gap for depression, particularly among young adults.
This systematic review and exploratory meta-analysis finds that while minocycline demonstrates promising biological activity and safety in acute traumatic spinal cord injury, current clinical evidence does not conclusively support its efficacy in improving neurological or functional outcomes, highlighting the need for further robust randomized controlled trials.
This study employs a meta-analytic and unsupervised clustering approach to evaluate riluzole-based treatments for ALS, finding that while no adjunctive therapy significantly outperforms riluzole monotherapy, certain modulator classes show positive trends and highlighting a critical need for diverse, large-scale international trials due to current geographic research biases.
This study demonstrates that automated speech recognition (specifically Whisper), particularly when combined with quality control, offers a cost-effective and accurate alternative to manual transcription for characterizing linguistic impairments and classifying primary progressive aphasia variants, often outperforming manual methods in classification tasks.
This cross-sectional study demonstrates that caregivers' descriptions of movement triggers and affected body regions differ significantly among children with cerebral palsy based on whether they have predominant dystonia, combined dystonia and spasticity, or spasticity alone, suggesting that these observations can help clinicians distinguish between the conditions to guide management.
This study identifies a common human IL-34 loss-of-function variant (Y213X) that significantly reduces IL-34 levels, disrupts microglial homeostasis and network organization, and exacerbates amyloid pathology, thereby establishing IL-34/CSF1R signaling as a critical determinant of microglial resilience in Alzheimer's disease.
This study identifies elevated expression of the TRKβ-SHC isoform in peripheral blood as a neuroprotective factor associated with preserved memory outcomes in post-stroke patients, suggesting that DNA methylation-regulated alternative splicing of NTRK2 could serve as a novel therapeutic target for post-stroke cognitive impairment.
This study demonstrates that a fine-tuned large language model (DeepSeek-R1) can accurately extract expert-level epilepsy and seizure phenotypes from unstructured clinical notes at scale, effectively transforming electronic health records into a valuable resource for longitudinal population research and improved patient care.