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C. elegans long read transcriptomic analysis provides evidence that non-trans-spliced mRNAs display a terminal a hairpin structure mimicking the Spliced Leader. This provides an explanation how the main maturation system might be bypassed.

Knowledge of both the spatial organization and functions of white-matter fiber tracts is steadily increasing. We report here the anatomy and functions of the frontal aslant tract (FAT) in the non-dominant hemisphere (usually the right hemisphere). Despite the structural symmetry between the right and left FAT, these two tracts seem to display functional asymmetry, with several brain functions in common, but others, such as visuospatial and social cognition, music processing, shifting attention or working memory, more exclusively associated with the right FAT. Further studies are required to determine whether damage to the right FAT causes permanent cognitive impairment. Such studies will constitute the best means of testing whether this tract is a critical pathway that must be taken into account during neurosurgical procedures and the essential tasks to be incorporated into intraoperative monitoring during awake craniotomy.

A high-quality, low-cost ventilator, dubbed HEV, has been developed by the particle physics community working together with biomedical engineers and physicians around the world. The HEV design is suitable for use both in and out of hospital intensive care units, provides a variety of modes and is capable of supporting spontaneous breathing and supplying oxygen-enriched air. An external air supply can be combined with the unit for use in situations where compressed air is not readily available. HEV supports remote training and post market surveillance via a Web interface and data logging to complement standard touch screen operation, making it suitable for a wide range of geographical deployment. The HEV design places emphasis on the ventilation performance, especially the quality and accuracy of the pressure curves, reactivity of the trigger, measurement of delivered volume and control of oxygen mixing, delivering a global performance which will be applicable to ventilator needs beyond the COVID-19 pandemic. This article describes the conceptual design and presents the prototype units together with a performance evaluation.

Functional Magnetic Resonance Imaging (fMRI) is an essential tool for the pre-surgical planning of brain tumor removal, which allows the identification of functional brain networks to preserve the patient’s neurological functions. One fMRI technique used to identify the functional brain network is the resting-state-fMRI (rs-fMRI). This technique is not routinely available because of the necessity to have an expert reviewer who can manually identify each functional network. The lack of sufficient unhealthy data has so far hindered a data-driven approach based on machine learning tools for full automation of this clinical task. In this article, we investigate the possibility of such an approach via the transfer learning method from healthy control data to unhealthy patient data to boost the detection of functional brain networks in rs-fMRI data. The end-to-end deep learning model implemented in this article distinguishes seven principal functional brain networks using fMRI images. The best performance of a 75% correct recognition rate is obtained from the proposed deep learning architecture, which shows its superiority over other machine learning algorithms that were equally tested for this classification task. Based on this best reference model, we demonstrate the possibility of boosting the results of our algorithm with transfer learning from healthy patients to unhealthy patients. This application of the transfer learning technique opens interesting possibilities because healthy control subjects can be easily enrolled for fMRI data acquisition since it is non-invasive. Consequently, this process helps to compensate for the usual small cohort of unhealthy patient data. This transfer learning approach could be extended to other medical imaging modalities and pathology.

Background: The optimal management of skull base DAVFs remains controversial. Some groups advocate endovascular therapy, which is an efficient therapeutic option, but can be limited by inadequate access to the fistula point, non-target embolization, and recanalization risk. We report our experience in microsurgical obliteration after embolization failure, emphasizing the importance of a prompt effective treatment for the long-term clinical status improvement. Patients and methods: This is a retrospective review, on 6 patients undergoing surgery for skull base Cognard grade IV DAVF after one or several failed embolization procedures in our institution between January 2006 and July 2016. Patients and treatments characteristics/outcomes are reported. Results: In all patients endovascular therapy had failed prior to surgery. The mean modified Rankin scale from diagnosis to preoperative surgical cure increased from 1.8 range to 2.7. After surgical treatment, symptoms improved in 5 (83.3%), stayed the same in 1 (16.7%). In all cases total elimination of arteriovenous shunting was achieved, without hemorrhage and recurrence during the mean follow-up period of 5.4 years. Conclusion: Surgical occlusion of skull base Cognard IV DAVFs yields excellent exclusion rate. However, complete occlusion of the shunt may not lead to clinical improvement if symptoms had been progressing for an excessively long period of time before curative treatment was initiated. Hence the patient remains at risk of rebleeding as long as the shunt is open. We do believe that a single stage endovascular attempt can be decided, but a failed procedure should lead to immediate surgery. Keywords: DAVF, Intracranial dural arteriovenous fistulas, Surgery

Abstract Introduction Preoperative language mapping using functional magnetic resonance imaging (fMRI) aims to identify eloquent areas in the vicinity of surgically resectable brain lesions. fMRI methodology relies on the blood‐oxygen‐level‐dependent (BOLD) analysis to identify brain language areas. Task‐based fMRI studies the BOLD signal increase in brain areas during a language task to identify brain language areas, which requires patients' cooperation, whereas resting‐state fMRI (rsfMRI) allows identification of functional networks without performing any explicit task through the analysis of the synchronicity of spontaneous BOLD signal oscillation between brain areas. The aim of this study was to compare preoperative language mapping using rsfMRI and task fMRI to cortical mapping (CM) during awake craniotomies. Methods Fifty adult patients surgically treated for a brain lesion were enrolled. All patients had a presurgical language mapping with both task fMRI and rsfMRI. Identified language networks were compared to perioperative language mapping using electric cortical stimulation. Results Resting‐state fMRI was able to detect brain language areas during CM with a sensitivity of 100% compared to 65.6% with task fMRI. However, we were not able to perform a specificity analysis and compare task‐based and rest fMRI with our perioperative setting in the current study. In second‐order analysis, task fMRI imaging included main nodes of the SN and main areas involved in semantics were identified in rsfMRI. Conclusion Resting‐state fMRI for presurgical language mapping is easy to implement, allowing the identification of functional brain language network with a greater sensitivity than task‐based fMRI, at the cost of some precautions and a lower specificity. Further study is required to compare both the sensitivity and the specificity of the two methods and to evaluate the clinical value of rsfMRI as an alternative tool for the presurgical identification of brain language areas.

Primary cell isolation from the central nervous system (CNS) has allowed fundamental understanding of blood-brain barrier (BBB) properties. However, poorly described isolation techniques or suboptimal cellular purity has been a weak point of some published scientific articles. Here, we describe in detail how to isolate and enrich, using a common approach, endothelial cells (ECs) from adult mouse brains, as well as pericytes (PCs) and astrocytes (ACs) from newborn mouse brains. Our approach allowed the isolation of these three brain cell types with purities of around 90%. Furthermore, using our protocols, around 3 times more PCs and 2 times more ACs could be grown in culture, as compared to previously published protocols. The cells were identified and characterized using flow cytometry and confocal microscopy. The ability of ECs to form a tight monolayer was assessed for passages 0 to 3. The expression of claudin-5, occludin, zonula occludens-1, P-glycoprotein-1 and breast cancer resistance protein by ECs, as well as the ability of the cells to respond to cytokine stimuli (TNF-α, IFN-γ) was also investigated by q-PCR. The transcellular permeability of ECs was evaluated in the presence of pericytes or astrocytes in a Transwell® model by measuring the transendothelial electrical resistance (TEER), dextran-FITC and sodium fluorescein permeability. Overall, ECs at passages 0 and 1 featured the best properties valued in a BBB model. Furthermore, pericytes did not increase tightness of EC monolayers, whereas astrocytes did regardless of their seeding location. Finally, ECs resuspended in fetal bovine serum (FBS) and dimethyl sulfoxide (DMSO) could be cryopreserved in liquid nitrogen without affecting their phenotype nor their capacity to form a tight monolayer, thus allowing these primary cells to be used for various longitudinal in vitro studies of the blood-brain barrier.

The authors wish to make the following corrections to this paper [...]

Since most preclinical drug permeability assays across the blood-brain barrier (BBB) are still evaluated in rodents, we compared an in vitro mouse primary endothelial cell model to the mouse b.End3 and the acellular parallel artificial membrane permeability assay (PAMPA) models for drug screening purposes. The mRNA expression of key feature membrane proteins of primary and bEnd.3 mouse brain endothelial cells were compared. Transwell® monolayer models were further characterized in terms of tightness and integrity. The in vitro in vivo correlation (IVIVC) was obtained by the correlation of the in vitro permeability data with log BB values obtained in mice for seven drugs. The mouse primary model showed higher monolayer integrity and levels of mRNA expression of BBB tight junction (TJ) proteins and membrane transporters (MBRT), especially for the efflux transporter Pgp. The IVIVC and drug ranking underlined the superiority of the primary model (r2 = 0.765) when compared to the PAMPA-BBB (r2 = 0.391) and bEnd.3 cell line (r2 = 0.019) models. The primary monolayer mouse model came out as a simple and reliable candidate for the prediction of drug permeability across the BBB. This model encompasses a rapid set-up, a fair reproduction of BBB tissue characteristics, and an accurate drug screening.