We retrospectively analyzed the medical documentation of 194 children infected with Epstein-Barr virus. The diagnosis was based on clinical symptoms and the presence of the viral capsid antigen IgM antibody. Patients with severe neurologic complications also underwent neurologic examination, magnetic resonance imaging (MRI), and electroencephalography (EEG). There were 2 peaks in incidence of infection; the first one in young children aged 1 to 5 years represented 62.0% of cases. The second peak (24.6% of patients) occurred in teenagers. Febrile seizures were confirmed in 3.1% of affected children younger than 5 years and headaches in 24.2% patients, mostly older children. Ten children presented severe, neurologic complications: meningoencephalitis, acute encephalitis, acute cerebellitis, transverse myelitis, and myeloradiculitis. Our study identified a variety of Epstein-Barr virus–related neurologic complications. Epstein-Barr virus should be routinely tested for when a child presents with an apparent neuroinfection as it is a common pathogen that can induce a wide variety of signs and symptoms.

Hydrocephalus is a common neurological condition that can have traumatic ramifications and can be lethal without treatment. Nowadays, during therapy radiologists have to spend a vast amount of time assessing the volume of cerebrospinal fluid (CSF) by manual segmentation on Computed Tomography (CT) images. Further, some of the segmentations are prone to radiologist bias and high intraobserver variability. To improve this, researchers are exploring methods to automate the process, which would enable faster and more unbiased results. In this study, we propose the application of U-Net convolutional neural network in order to automatically segment CT brain scans for location of CSF. U-Net is a neural network that has proven to be successful for various interdisciplinary segmentation tasks. We optimised training using state of the art methods, including “1cycle” learning rate policy, transfer learning, generalized dice loss function, mixed float precision, self-attention, and data augmentation. Even though the study was performed using a limited amount of data (80 CT images), our experiment has shown near human-level performance. We managed to achieve a 0.917 mean dice score with 0.0352 standard deviation on cross validation across the training data and a 0.9506 mean dice score on a separate test set. To our knowledge, these results are better than any known method for CSF segmentation in hydrocephalic patients, and thus, it is promising for potential practical applications.

MicroRNAs are small non-coding RNAs that regulate immune response and inflammation. We assumed that miRNAs may be involved in the immune response during cystic fibrosis pulmonary exacerbations (CFPE) and that altered expression profile in the airways and blood may underlie clinical outcomes in CF pediatric patients. Methods: We included 30 pediatric patients diagnosed with cystic fibrosis. The biologic material (blood, sputum, exhaled breath condensate) was collected during pulmonary exacerbation and in stable condition. The miRNA expression profile from blood and sputum (n = 6) was done using the next-generation sequencing. For validation, selected four miRNAs were analyzed by qPCR in exosomes from sputum supernatant and exhaled breath condensate (n = 24). NGS analysis was done in Base Space, correlations of gene expression with clinical data were done in Statistica. Results: The miRNA profiling showed that four miRNAs (miR-223, miR-451a, miR-27b-3p, miR-486-5p) were significantly altered during pulmonary exacerbation in CF patients in sputum but did not differ significantly in blood. MiRNA differently expressed in exhaled breath condensate (EBC) and sputum showed correlation with clinical parameters in CFPE. Conclusion: MiRNA expression profile changes in the airways during pulmonary exacerbation in CF pediatric patients. We suggest that miRNA alterations during CFPE are restricted to the airways and strongly correlate with clinical outcome.

Transient signal changes in magnetic resonance imaging (MRI) of the splenium of the corpus callosum (SCC) can result from many different reasons, including encephalitis and encephalopathy caused by infection, seizures, metabolic disorders and asphyxia. We report a case of a 6-year-old Polish girl with rotavirus infection demonstrating a reversible SCC lesion on diffusion-weighted MRI images. She presented six episodes of generalized tonic seizures with mild acute gastroenteritis. Stool test for rotavirus antigen was positive. At the time of admission imaging showed the hyperintense region in T2-weighted and fluid-attenuated inversion-recovery MRI, a well-defined lesion in the splenium of the corpus callosum with restricted diffusion in diffusion-weighted MRI and no enhancement in post contrast T1-weighted imaging. Her first EEG showed slow brain activity in the posterior occipitotemporal portion, consisting mainly of theta waves with a frequency of 4.5–5.5 Hz and amplitude of 40 uV. The lesion had completely disappeared on follow-up MRI 10 days later. The patient recovered fully without any sequelae.