In this work, we have developed a simple synthetic approach using Et3N·3HF as an alternative to the DAST reagent. We controlled the stereochemistry of the nucleophilic fluorination at C4 of 1,6-anhydro-2,3-dideoxy-2,3-difluoro-4-O-triflate-β-ᴅ-talopyranose using Et3N·3HF or in situ generated Et3N·1HF. The influence of the fluorine atom at C2 on reactivity at C4 could contribute to a new fluorine effect in nucleophilic substitution. Finally, with the continuous objective of synthesizing novel multi-vicinal fluorosugars, we prepared one difluorinated and one trifluorinated alditol analogue.
BackgroundBenzodiazepines are among the most commonly prescribed drugs for anxiety disorders. While they are indicated as adjunctive treatment for short-term use according to clinical practice guidelines, previous studies have shown patterns of long-term use of benzodiazepines, which is problematic due to side effects, dependence and potential of abuse. The aims of this study were to examine among a large sample of primary care adults suffering from anxiety disorders: 1) benzodiazepine use patterns; and 2) correlates of long-term benzodiazepine use.MethodsData were drawn from the “Dialogue” project, a large primary care study conducted in 64 primary care clinics in the province of Quebec, Canada. Following a mental health screening in waiting rooms, patients at risk of anxiety or depression completed the Composite International Diagnostic Interview-Simplified (CIDIS). A sample of 740 adults meeting DSM-IV criteria for Generalized Anxiety Disorder, Panic Disorder or Social Anxiety Disorder in the past 12 months took part in this study.ResultsBenzodiazepines were used by 22.6% of participants with anxiety disorders in our primary care sample. A large majority of benzodiazepine users (88.4%) met our indicator of long-term use, as defined by utilization for more than 12 weeks including regular and as-needed use. Based on a logistic regression model, individual correlates associated with long-term benzodiazepine use included: being 30 years or older, having a comorbid physical illness, meeting criteria for comorbid agoraphobia, reporting the use of sleep-aids, and concurrent SSRI utilization.LimitationData collection with self-reported questionnaires may be subject to information bias.ConclusionsDespite knowledge of the risks of long-term use of benzodiazepines, this remains a pervasive problem. Clinicians need to be mindful of patterns and risk factors leading to long-term use of benzodiazepines in patients with anxiety disorders. Results of this study should raise awareness regarding appropriate prescription practices for benzodiazepines, including decision-making in initiation, duration of prescription, and use of strategies for discontinuation in current long-term benzodiazepine users.
There is growing interest in the preparation of fluorine‐containing organic molecules. Multivicinal‐fluorine analogues are among the most intriguing and promising compounds, but their physical and biological investigations are held back by challenging syntheses. Herein, we report on the synthesis of a large set of novel polyfluorohexitols. The dominant solution‐state conformation of all trifluorohexitols was determined, and the solid‐state conformations of some analogues were compared. Finally, the lipophilicity of a large set of polyfluorinated hexopyranose and hexitol analogues was attributed by using a log P determination method based on 19F NMR spectroscopy.
Although multivicinal inter-halide alkane units are represented in several natural products, many questions remain unanswered regarding the synthesis and physical properties of these unique molecules. Over the past decades, studies...
Teeth segmentation is an important topic in dental restorations that is essential for crown generation, diagnosis, and treatment planning. In the dental field, the variability of input data is high and there are no publicly available 3D dental arch datasets. Although there has been improvement in the field provided by recent deep learning architectures on 3D data, there still exists some problems such as properly identifying missing teeth in an arch. We propose to use spectral clustering as a self-supervisory signal to joint-train neural networks for segmentation of 3D arches. Our approach is motivated by the observation that K-means clustering provides cues to capture margin lines related to human perception. The main idea is to automatically generate training data by decomposing unlabeled 3D arches into segments relying solely on geometric information. The network is then trained using a joint loss that combines a supervised loss of annotated input and a self-supervised loss of non-labeled input. Our collected data has a variety of arches including arches with missing teeth. Our experimental results show improvement over the fully supervised state-ofthe-art MeshSegNet when using semi-supervised learning. Finally, we contribute code and a dataset.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.