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With greater population density, the likelihood of viral outbreaks achieving pandemic status is increasing. However, current viral screening techniques use specific reagents, and as viruses mutate, test accuracy decreases. Here, we present the first real-time, reagent-free, portable analysis platform for viral detection in liquid saliva, using COVID-19 as a proof-of-concept. We show that vibrational molecular spectroscopy and machine learning (ML) detect biomolecular changes consistent with the presence of viral infection. Saliva samples were collected from 470 individuals, including 65 that were infected with COVID-19 (28 from hospitalized patients and 37 from a walk-in testing clinic) and 251 that had a negative polymerase chain reaction (PCR) test. A further 154 were collected from healthy volunteers. Saliva measurements were achieved in 6 minutes or less and led to machine learning models predicting COVID-19 infection with sensitivity and specificity reaching 90%, depending on volunteer symptoms and disease severity. Machine learning models were based on linear support vector machines (SVM). This platform could be deployed to manage future pandemics using the same hardware but using a tunable machine learning model that could be rapidly updated as new viral strains emerge.

Purpose: The use of trametinib in the treatment of pediatric low-grade gliomas (PLGG) and plexiform neurofibroma (PN) is being investigated in an ongoing multicenter phase II trial (NCT03363217). Preliminary data shows potential benefits with significant response in the majority of PLGG and PN and an overall good tolerance. Moreover, possible benefits of MEK inhibitor therapy on cognitive functioning in neurofibromatosis type 1 (NF1) were recently shown which supports the need for further evaluation., Methods: Thirty-six patients with NF1 (age range 3-19 years) enrolled in the phase II study of trametinib underwent a neurocognitive assessment at inclusion and at completion of the 72-week treatment. Age-appropriate Wechsler Intelligence Scales and the Trail Making Test (for children over 8 years old) were administered at each assessment. Paired t-tests and Reliable Change Index (RCI) analyses were performed to investigate change in neurocognitive outcomes. Regression analyses were used to investigate the contribution of age and baseline score in the prediction of change., Results: Stable performance on neurocognitive tests was revealed at a group-level using paired t-tests. Clinically significant improvements were however found on specific indexes of the Wechsler intelligence scales and Trail Making Test, using RCI analyses. No significant impact of age on cognitive change was evidenced. However, lower initial cognitive performance was associated with increased odds of presenting clinically significant improvements on neurocognitive outcomes., Conclusion: These preliminary results show a potential positive effect of trametinib on cognition in patients with NF1. We observed significant improvements in processing speed, visuo-motor and verbal abilities. This study demonstrates the importance of including neuropsychological evaluations into clinical trial when using MEK inhibitors for patients with NF1., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Advanced magnetic resonance imaging (MRI) techniques indicate that concussion (i.e., mild traumatic brain injury) disrupts brain structure and function in children. However, the functional connectivity of brain regions within global and local networks (i.e., functional connectome) is poorly understood in pediatric concussion. This prospective, longitudinal study addressed this gap using data from the largest neuroimaging study of pediatric concussion to date to study the functional connectome longitudinally after concussion as compared with mild orthopedic injury (OI). Children and adolescents ( n  = 967) 8-16.99 years with concussion or mild OI were recruited from pediatric emergency departments within 48 h post-injury. Pre-injury and 1-month post-injury symptom ratings were used to classify concussion with or without persistent symptoms based on reliable change. Subjects completed a post-acute (2-33 days) and chronic (3 or 6 months via random assignment) MRI scan. Graph theory metrics were derived from 918 resting-state functional MRI scans in 585 children (386 concussion/199 OI). Linear mixed-effects modeling was performed to assess group differences over time, correcting for multiple comparisons. Relative to OI, the global clustering coefficient was reduced at 3 months post-injury in older children with concussion and in females with concussion and persistent symptoms. Time post-injury and sex moderated group differences in local (regional) network metrics of several brain regions, including degree centrality, efficiency, and clustering coefficient of the angular gyrus, calcarine fissure, cuneus, and inferior occipital, lingual, middle occipital, post-central, and superior occipital gyrus. Relative to OI, degree centrality and nodal efficiency were reduced post-acutely, and nodal efficiency and clustering coefficient were reduced chronically after concussion (i.e., at 3 and 6 months post-injury in females; at 6 months post-injury in males). Functional network alterations were more robust and widespread chronically as opposed to post-acutely after concussion, and varied by sex, age, and symptom recovery at 1-month post-injury. Local network segregation reductions emerged globally (across the whole brain network) in older children and in females with poor recovery chronically after concussion. Reduced functioning between neighboring regions could negatively disrupt specialized information processing. Local network metric alterations were demonstrated in several posterior regions that are involved in vision and attention after concussion relative to OI. This indicates that functioning of superior parietal and occipital regions could be particularly susceptibile to the effects of concussion. Moreover, those regional alterations were especially apparent at later time periods post-injury, emerging after post-concussive symptoms resolved in most and persisted up to 6 months post-injury, and differed by biological sex. This indicates that neurobiological changes continue to occur up to 6 months after pediatric concussion, although changes emerge earlier in females than in males. Changes could reflect neural compensation mechanisms.

Here, we present MCOCT, a Monte Carlo simulator for optical coherence tomography (OCT), incorporating a Gaussian illumination scheme and bias to increase backscattered event collection. MCOCT optical fluence was numerically compared and validated to an established simulator (MCX) and showed concordance at the focus while diverging slightly with distance to it. MCOCT OCT signals were experimentally compared and validated to OCT signals acquired in tissue-mimicking phantoms with known optical properties and showed a similar attenuation pattern with increasing depth while diverging beyond 1.5 mm and proximal to layer interfaces. MCOCT may help in the design of OCT systems for a wide range of applications., Competing Interests: The authors declare no conflicts of interest., (© 2024 Optica Publishing Group.)