Embracing uncertainty in cerebrospinal fluid dynamics: A Bayesian approach to analysing infusion studies.

Introduction: Cerebrospinal fluid (CSF) infusion test analysis allows recognizing and appropriately evaluating CSF dynamics in the context of normal pressure hydrocephalus (NPH), which is crucial for effective diagnosis and treatment. However, existing methodology possesses drawbacks that may compromise the precision and interpretation of CSF dynamics parameters. Research question: This study aims to circumvent these constraints by introducing an innovative analysis method grounded in Bayesian inference. Material and methods: A single-centre retrospective cohort study was conducted on 858 patients who underwent a computerized CSF infusion test between 2004 and 2020. We developed a Bayesian framework-based method for parameter estimation and compared the results to the current, gradient descent-based approach. We evaluated the accuracy and reliability of both methods by analysing erroneous prediction rates and curve fitting errors. Results: The Bayesian method surpasses the gradient descent approach, reflected in reduced inaccurate prediction rates and an improved goodness of model fit. On whole cohort level both techniques produced comparable results. However, the Bayesian method holds an added advantage by providing uncertainty intervals for each parameter. Sensitivity analysis revealed significance of the CSF production rate parameter and its interplay with other variables. The resistance to CSF outflow demonstrated excellent robustness. Discussion and conclusion: The proposed Bayesian approach offers a promising solution for improving robustness of CSF dynamics assessment in NPH, based on CSF infusion tests. Additional provision of the uncertainty measure for each diagnostic metric may perhaps help to explain occasional poor diagnostic performance of the test, offering a robust framework for improved understanding and management of NPH.

MEA-NAP compares microscale functional connectivity, topology, and network dynamics in organoid or monolayer neuronal cultures.

Microelectrode array (MEA) recordings are commonly used to compare firing and burst rates in neuronal cultures. MEA recordings can also reveal microscale functional connectivity, topology, and network dynamics-patterns seen in brain networks across spatial scales. Network topology is frequently characterized in neuroimaging with graph theoretical metrics. However, few computational tools exist for analyzing microscale functional brain networks from MEA recordings. Here, we present a MATLAB MEA network analysis pipeline (MEA-NAP) for raw voltage time-series acquired from single- or multi-well MEAs. Applications to 3D human cerebral organoids or 2D human-derived or murine cultures reveal differences in network development, including topology, node cartography, and dimensionality. MEA-NAP incorporates multi-unit template-based spike detection, probabilistic thresholding for determining significant functional connections, and normalization techniques for comparing networks. MEA-NAP can identify network-level effects of pharmacologic perturbation and/or disease-causing mutations and, thus, can provide a translational platform for revealing mechanistic insights and screening new therapeutic approaches.

Cycling-related cranio-spinal injuries admitted to a Major Trauma Centre in the cycling capital of the UK.

BACKGROUND: The increased popularity of cycling is leading to an anticipated increase in cycling-related traffic accidents and a need to better understand the demographics and epidemiology of craniospinal injuries in this vulnerable road user group. This study aims to systematically investigate and characterise cycling-related head and spine injuries seen in the Major Trauma Centre for the Eastern region, which has the highest cycling rates in the UK. METHODS: We performed a retrospective cohort study comparing the incidence, patterns, and severity of head and spine injuries in pedal cyclists presenting to the Major Trauma Centre in Cambridge between January 2012 and December 2020. Comparisons of injury patterns, characteristics, and associations were made according to mechanism of injury, helmet use, patient age and gender. RESULTS: A total of 851 patients were admitted after being involved in cycling-related collisions over the study period, with 454 (53%) sustaining head or spine injuries. The majority of victims (80%) were male and in mid-adulthood (median age 46 years). Head injuries were more common than spine injuries, with the most common head injuries being intracranial bleeds (29%), followed by skull fractures (12%), and cerebral contusions (10%). The most common spine injuries were cervical segment fractures, particularly C6 (9%), C7 (9%), and C2 (8%). Motorised collisions had a higher prevalence of spine fractures at each segment (p < 0.001) and were associated with a higher proportion of multi-vertebral fractures (p < 0.001). These collisions were also associated with impaired consciousness at the scene and more severe systemic injuries, including a lower Glasgow coma scale (R = -0.23, p < 0.001), higher injury severity score (R = 0.24, p < 0.001), and longer length of stay (R = 0.21, p < 0.001). Helmet use data showed that lack of head protection was associated with more severe injuries and poorer outcomes. CONCLUSION: As cycling rates continue to increase, healthcare providers may expect to see an increase in bicycle-related injuries in their practice. The insights gained from this study can inform the treatment of these injuries while highlighting the need for future initiatives aimed at increasing road safety and accident prevention.

Study of 851 cycling-related trauma patients in Cambridge, UK, shows high rates of head & spine injuries.Motorised collisions were associated with more severe injuries and impaired consciousness at the scene.The lack of helmet use was linked to more severe head injuries and impaired consciousness, but not to a longer hospital stay.Rising cycling rates may lead to increased incidence of these injuries in clinical practice.Our findings may be relevant for clinicians treating cycling-related traumatic injuries to head and spine.