Intrinsic properties of the developing motor cortex in the rat: in vitro axons from the medial somatomotor cortex grow faster than axons from the lateral somatomotor cortex

The axons that originate in the medial somatomotor cortex of the rat depart, during development, after those from the lateral somatomotor cortex, yet they arrive in the cervical spinal cord first. Either the medially originating axons elongate faster, or the laterally originating ones pause along the descent pathway. To investigate the presence of an intrinsic difference of the axonal elongation velocity between the lateral and medial somatomotor cortical areas, we cultured explants taken from these areas for 2 days, and measured the length of the outgrowth. After 2 days the explants were surrounded by a radiate corona of axons of which the longest measured 1.95 mm. A significant difference was detected between the medial and lateral somatomotor cortical areas in vitro. Axons originating from explants taken from the medial somatomotor cortical area are, after 2 days in culture, on average 0.16 mm longer than those from the lateral somatomotor cortical area. Though the observed difference is not large enough to allow for the overtaking observed in vivo, it does indicate that intrinsic differences exist within the developing rat somatomotor cortex. This in turn indicates that intrinsic cortical traits not only influence regionalization and targeting behavior of cortical projection neurons, but also their axonal elongation speed

Modeling Dutch Medical Texts for Detecting Functional Categories and Levels of COVID-19 Patients

© European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.Electronic Health Records contain a lot of information in natural language that is not expressed in the structured clinical data. Especially in the case of new diseases such as COVID-19, this information is crucial to get a better understanding of patient recovery patterns and factors that may play a role in it. However, the language in these records is very different from standard language and generic natural language processing tools cannot easily be applied out-of-the-box. In this paper, we present a fine-tuned Dutch language model specifically developed for the language in these health records that can determine the functional level of patients according to a standard coding framework from the World Health Organization. We provide evidence that our classification performs at a sufficient level (F1-score above 80% for the main categories and error rates of less than 1 level on a 5-point Likert scale for levels) to generate patient recovery patterns that can be used to analyse factors that contribute to the rehabilitation of COVID-19 patients and to predict individual patient recovery of functioning