19 research outputs found
Enumeration of bacteria from the Clostridium leptum subgroup in human faecal microbiota using Clep1156 16S rRNA probe in combination with helper and competitor oligonucleotides
International audienceTarget site inaccessibility represents a significant problem for fluorescent in situ hybridisation (FISH) of 16S rRNA oligonucleotide probes. For this reason, the Clep1156 probe targeting 16S rRNA of the Clostridium leptum phylogenetic subgroup used for dot blot experiments could not be used until now for FISH. Considering that bacteria from the C. leptum subgroup are very abundant in the human faecal microbiota and may play a significant role in host health, we have used unlabelled helper and competitor oligonucleotides to improve the 16S rRNA in situ accessibility and specificity of the Clep1156 probe and applied this approach to enumerate C. leptum bacteria in this ecosystem. Nine C. leptum target strains and five non-target strains were selected to develop and validate the helper-competitor strategy. Depending on the target strains, the use of helpers enhanced the fluorescence intensity signal of Clep1156 from 0.4-fold to 8.4-fold with a mean value of 3.6-fold, switching this probe from the brightness class V-VI (masked sites) to III-IV (accessible sites). The simultaneous use of helper and competitor oligonucleotides with Clep1156 probe allowed the expected specificity without disturbing in situ accessibility. Quantified by FISH combined with flow cytometry, C. leptum bacteria in human faecal samples (n=22) represented 19 +/- 7% of bacteria on average [4.9-37.5]. We conclude that helper oligonucleotides are very useful to circumvent the problem of target site in situ accessibility, especially when probe design is limited to only one 16S rRNA area and that helpers and competitors may be efficiently combined
Identification of Similar Patients Through Medical Concept Embedding from Electronic Health Records: A Feasibility Study for Rare Disease Diagnosis
International audienceTo identify patients with similar clinical profiles and derive insights from the records and outcomes of similar patients can help fast and precise diagnosis and other clinical decisions for rare diseases. Similarity methods are required to take into account the semantic relations between medical concepts and also the different relevance of all medical concepts presented in patients' medical records. In this paper, we introduce the methods developed in the context of rare disease screening/diagnosis from clinical data warehouse using medical concept embedding and adjusted aggregations. Our methods provided better preliminary results than baseline methods, with a significant improvement of precision among the top ranked similar patients, which is encouraging for further fine-tuning and application on a large-scale dataset for new/candidate patient identification
Perceptions et reprĂ©sentations des internes de mĂ©decine gĂ©nĂ©rale Ă lâĂ©gard dâun outil pĂ©dagogique issu du paradigme dâapprentissage
Contexte : En 2002, au sein de facultés
de médecine, plusieurs départements de médecine générale en France
sont passĂ©s dâun enseignement traditionnel Ă une pĂ©dagogie centrĂ©e
sur les apprentissages. Ce changement a nécessité la mise en place
de nouveaux outils tels que les entretiens collectifs monitorés (ECM).
Les ECM sont un lieu dâĂ©change de pratique, qui rĂ©unissent autour
dâun moniteur un groupe de six Ă huit Ă©tudiants en troisiĂšme cycle
dâĂ©tudes mĂ©dicales. Ils ont pour but dâouvrir le champ des acquisitions
et de faire Ă©merger des objectifs personnels dâapprentissage, au travers
des interactions. Objectif : Recueillir les représentations
et perceptions des étudiants en troisiÚme cycle de médecine générale
Ă lâĂ©gard des entretiens collectifs monitorĂ©s en tant que dispositif pĂ©dagogique.
Méthodes : Réalisation de trois groupes de discussion
focalisĂ©e, soit un par annĂ©e dâĂ©tude, composĂ©s dâĂ©tudiants de la
facultĂ© de Paris Ăle-de-France-Ouest. RĂ©sultats : Lâanalyse
des verbatim montre que les étudiants de premiÚre année du troisiÚme
cycle ont une vision trÚs négative des entretiens collectifs monitorés.
Ils ne repĂšrent aucun des objectifs fixĂ©s et ne perçoivent pas lâutilitĂ©
de cet enseignement. Les étudiants de deuxiÚme année du troisiÚme
cycle sont plus nuancés. Certains sont capables de citer quelques
objectifs fixés et les bénéfices attendus de la méthode. Ils pensent
que cela peut servir Ă leur formation. Enfin, les Ă©tudiants de derniĂšre
année y adhÚrent totalement et émettent peu de réserves. Ils citent
comme intĂ©rĂȘts principaux lâaide Ă lâacquisition de lâautonomie
et la formation de lâesprit critique
Enriching UMLS-Based Phenotyping of Rare Diseases Using Deep-Learning: Evaluation on Jeune Syndrome
International audienceThe wide adoption of Electronic Health Records (EHR) in hospitals provides unique opportunities for high throughput phenotyping of patients. The phenotype extraction from narrative reports can be performed by using either dictionary-based or data-driven methods. We developed a hybrid pipeline using deep learning to enrich the UMLS Metathesaurus for automatic detection of phenotypes from EHRs. The pipeline was evaluated on a French database of patients with a rare disease characterized by skeletal abnormalities, Jeune syndrome. The results showed a 2.5-fold improvement regarding the number of detected skeletal abnormalities compared to the baseline extraction using the standard release of UMLS. Our method can help enrich the coverage of the UMLS and improve phenotyping, especially for languages other than English