On the importance of long-term functional assessment after stroke to improve translation from bench to bedside

Despite extensive research efforts in the field of cerebral ischemia, numerous disappointments came from the translational step. Even if experimental studies showed a large number of promising drugs, most of them failed to be efficient in clinical trials. Based on these reports, factors that play a significant role in causing outcome differences between animal experiments and clinical trials have been identified; and latest works in the field have tried to discard them in order to improve the scope of the results. Nevertheless, efforts must be maintained, especially for long-term functional evaluations. As observed in clinical practice, animals display a large degree of spontaneous recovery after stroke. The neurological impairment, assessed by basic items, typically disappears during the firsts week following stroke in rodents. On the contrary, more demanding sensorimotor and cognitive tasks underline other deficits, which are usually long-lasting. Unfortunately, studies addressing such behavioral impairments are less abundant. Because the characterization of long-term functional recovery is critical for evaluating the efficacy of potential therapeutic agents in experimental strokes, behavioral tests that proved sensitive enough to detect long-term deficits are reported here. And since the ultimate goal of any stroke therapy is the restoration of normal function, an objective appraisal of the behavioral deficits should be done

A Biphasic and Brain-Region Selective Down-Regulation of Cyclic Adenosine Monophosphate Concentrations Supports Object Recognition in the Rat

Background: We aimed to further understand the relationship between cAMP concentration and mnesic performance. Methods and Findings: Rats were injected with milrinone (PDE3 inhibitor, 0.3 mg/kg, i.p.), rolipram (PDE4 inhibitor, 0.3 mg/ kg, i.p.) and/or the selective 5-HT4R agonist RS 67333 (1 mg/kg, i.p.) before testing in the object recognition paradigm. Cyclic AMP concentrations were measured in brain structures linked to episodic-like memory (i.e. hippocampus, prefrontal and perirhinal cortices) before or after either the sample or the testing phase. Except in the hippocampus of rolipram treated-rats, all treatment increased cAMP levels in each brain sub-region studied before the sample phase. After the sample phase, cAMP levels were significantly increased in hippocampus (1.8 fold), prefrontal (1.3 fold) and perirhinal (1.3 fold) cortices from controls rat while decreased in prefrontal cortex (,0.83 to 0.62 fold) from drug-treated rats (except for milrinone+RS 67333 treatment). After the testing phase, cAMP concentrations were still increased in both the hippocampus (2.76 fold) and the perirhinal cortex (2.1 fold) from controls animals. Minor increase were reported in hippocampus and perirhinal cortex from both rolipram (respectively, 1.44 fold and 1.70 fold) and milrinone (respectively 1.46 fold and 1.56 fold)-treated rat. Following the paradigm, cAMP levels were significantly lower in the hippocampus, prefrontal and perirhinal cortices from drug-treated rat when compared to controls animals, however, only drug-treated rats spent longer time exploring the novel object during the testing phase (inter-phase interval of 4 h)

A comparative study of two automated solutions for cross‐sectional skeletal muscle measurement from abdominal computed tomography images

International audienceBackground: Measurement of cross-sectional muscle area (CSMA) at the mid third lumbar vertebra (L3) level from computed tomography (CT) images is becoming one of the reference methods for sarcopenia diagnosis. However, manual skeletal muscle segmentation is tedious and is thus restricted to research. Automated solutions are required for use in clinical practice. Purpose: The aim of this study was to compare the reliability of two automated solutions for the measurement of CSMA. Methods: We conducted a retrospective analysis of CT images in our hospital database.We included consecutive individuals hospitalized at the Grenoble University Hospital in France between January and May 2018 with abdominal CT images and sagittal reconstruction. We used two types of software to automatically segment skeletal muscle: ABACS, a module of the SliceOmatic software solution "ABACS-SliceOmatic,"and a deep learning-based solution called "Auto-MATiCA." Manual segmentation was performed by a medical expert to generate reference data using "SliceOmatic." The Dice similarity coefficient (DSC) was used to measure overlap between the results of the manual and the automated segmentations. The DSC value for each method was compared with the Mann-Whitney U test. Results: A total of 676 hospitalized individuals was retrospectively included (365 males [53.8%] and 312 females [46.2%]).The median DSC for SliceOmatic vs AutoMATiCA (0.969 [5th percentile: 0.909]) was greater than the median DSC for SliceOmatic vs. ABACS-SliceOmatic (0.949 [5th percentile: 0.836]) (p < 0.001). Conclusions: AutoMATiCA, which used artificial intelligence, was more reliable than ABACS-SliceOmatic for skeletal muscle segmentation at the L3 level in a cohort of hospitalized individuals. The next step is to develop and validate a neural network that can identify L3 slices, which is currently a fastidious process

Questionnaire about therapeutic drugmonitoring (TDM) of psychotropics for a panel of French psychiatrists

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