What to keep? What to discard? Virtual or in-person learning after the pandemic: Expectations of French neurology residents

IssueTo define the relevance of online courses for neurology residents in a post-COVID environment and how to improve existing programs.EvidenceIn total, 99 French neurology residents voluntarily chose to participate in this survey. They were asked about the proportion of online courses they followed before and during the pandemic, the advantages and inconveniences of each format, the type of environment in which they attended online classes, and their preference for either online or in-person learning. Out of the 99 French neurology residents who responded, 65% of them had less than 25% of their course load online before the pandemic, whereas in 2022, 38% of them had more than 75% of their courses in a virtual format. With 56% of students being able to attend online classes from home and another 25% attending from their hospital unit, general access was not an issue. However, only 18% of residents reported that these online courses increased their attendance and 74% of them reported preferring in-person courses to those online. To improve the current offer of online courses, residents suggested a more interactive learning method, such as through clinical cases (49%).ImplicationsAlthough a small portion of students is satisfied with this change toward online learning, most residents seek to go back to in-person courses and conferences. Virtual programs did not increase student attendance and instead highlighted the lack of dedicated time available for specialized education during neurology residency. Returning to in-person training and education could improve residents’ focus and help develop a network of health professionals across the country.     

Usefulness of circulating tumor DNA from cerebrospinal fluid in recurrent high-grade glioma

Molecular documentation at relapse of high-grade glioma is an urgent need for patient care. A prospective pilot study was conducted to assess the rate of mutation detection using targeted deep sequencing on circulating tumor DNA from cerebrospinal fluid (CSF) after chemo-radiotherapy based treatment. Fifteen patients were included: 13 patients with glioblastoma, 1 patient with gliosarcoma and 1 patient with anaplastic astrocytoma. At progression, 10/15 patients (67%) had detectable mutations in the CSF. Among them, 5/10 patients harbored at least one common mutation between initial tumor and ctDNA. CSF protein level and cfDNA concentration were higher, although not significant, in the ctDNA positive group versus ctDNA negative group (1.17 g/L vs. 0.79 g/L). Molecular documentation obtained from ctDNA in CSF at the time of relapse is informative in around two-thirds of the patients.     

Les symptômes non-moteurs de la maladie de Parkinson de la physiopathologie au diagnostic précoce

Parkinson's disease is the second most common neurodegenerative disease after Alzheimer's disease. The pathophysiology of Parkinson's disease is complex and imperfectly known. Primum movens is abnormal intra-neuronal accumulation of the protein α-synuclein, leading to metabolic disturbances and neurodegeneration. This abnormal accumulation of α-synuclein is also found in dementia with Lewy bodies and multiple system atrophy, which together with Parkinson's disease form the group of α-synucleinopathies. Well known by its motor signs (bradykinesia, rest tremor, cogwheel rigidity and gait disturbance), Parkinson's disease is above all a systemic disease composed of a myriad of non-motor symptoms (constipation, sense of smell disorders, rapid eye movement sleep behaviour disorders, genitourinary disorders…). These non-motor symptoms caused by accumulation and migration of α-synuclein deposits from the gut and the olfactory bulb to the central nervous system may precede motor signs by ten years and therefore be of interest for early diagnosis. Furthermore, non-motor symptoms have a poorer impact on quality of life than motor signs themselves. Therefore, understanding, recognition and management of non-motor symptoms are crucial in management of parkinsonian patient. In this paper, we offer an update on the main non-motor symptoms of Parkinson's disease, from their pathophysiology to their screening, ending with their management.     

Sirtuins as novel players in the pathogenesis of diabetes mellitus

Diabetes mellitus (DM) is a systemic and complex disease with micro and macrovascular complications that result from impaired metabolic pathways and genetic susceptibilities. DM has been accepted as an epidemic worldwide during the last two decades. A substantial gap in our knowledge exists regarding the pathophysiology of this metabolic disorder despite the improved diagnostic tools and therapeutic approaches. Sirtuins are a group of NAD⁺ dependent enzymes that are involved in cellular homeostasis due to their deacetylating activity. In the present review, we aimed to discuss the role of associated sirtuins in the pathogenesis and treatment of diabetes mellitus.     

Safety and efficacy of single-agent bevacizumab-containing therapy in elderly patients with platinum-resistant recurrent ovarian cancer: Subgroup analysis of the randomised phase III AURELIA trial

Background

The AURELIA trial demonstrated significantly improved progression-free survival (PFS) with bevacizumab added to chemotherapy for platinum-resistant ovarian cancer (PROC).

Inclusion complexes of 2-chloroethylnitrososulfamides (CENS) with beta-cyclodextrin

Host-guest association between four CENS (derivated from piperidine, dibenzylamine, dicyclohexylamine and methyl prolinate) and beta-cyclodextrin was carried out in solution and solid state. Characterisation, stoichiometry, solubility, dissociation constants and stability of such complexes were studied, showing that the inclusion with beta-CD appears as a promising mode of formulation of 2-chloroethylnitrososulfamides.     

Deep adversarial domain adaptation for breast cancer screening from mammograms

The early detection of breast cancer greatly increases the chances that the right decision for a successful treatment plan will be made. Deep learning approaches are used in breast cancer screening and have achieved promising results when a large-scale labeled dataset is available for training. However, they may suffer from a dramatic decrease in performance when annotated data are limited. In this paper, we propose a method called deep adversarial domain adaptation (DADA) to improve the performance of breast cancer screening using mammography. Specifically, our aim is to extract the knowledge from a public dataset (source domain) and transfer the learned knowledge to improve the detection performance on the target dataset (target domain). Because of the different distributions of the source and target domains, the proposed method adopts an adversarial learning technique to perform domain adaptation using the two domains. Specifically, the adversarial procedure is trained by taking advantage of the disagreement of two classifiers. To evaluate the proposed method, the public well-labeled image-level dataset Curated Breast Imaging Subset of the Digital Database for Screening Mammography (CBIS-DDSM) is employed as the source domain. Mammography samples from the West China Hospital were collected to construct our target domain dataset, and the samples are annotated at case-level based on the corresponding pathological reports. The experimental results demonstrate the effectiveness of the proposed method compared with several other state-of-the-art automatic breast cancer screening approaches.