A geometric morphometric approach to the study of variation of shovel-shaped incisors

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A geometric morphometric approach to the study of variation of shovel-shaped incisors

Objectives: The scoring and analysis of dental nonmetric traits are predominantly accomplished by using the Arizona State University Dental Anthropology System (ASUDAS), a standard protocol based on strict definitions and three‐dimensional dental plaques. However, visual scoring, even when controlled by strict definitions of features, visual reference, and the experience of the observer, includes an unavoidable part of subjectivity. In this methodological contribution, we propose a new quantitative geometric morphometric approach to quickly and efficiently assess the variation of shoveling in modern human maxillary central incisors (UI1). Materials and methods: We analyzed 87 modern human UI1s by means of virtual imaging and the ASU‐UI1 dental plaque grades using geometric morphometrics by placing semilandmarks on the labial crown aspect. The modern human sample was composed of individuals from Europe, Africa, and Asia and included representatives of all seven grades defined by the ASUDAS method. Results: Our results highlighted some limitations in the use of the current UI1 ASUDAS plaque, indicating that it did not necessarily represent an objective gradient of expression of a nonmetric tooth feature. Rating of shoveling tended to be more prone to intra‐ and interobserver bias for the highest grades. In addition, our analyses suggest that the observers were strongly influenced by the depth of the lingual crown aspect when assessing the shoveling. Discussion: In this context, our results provide a reliable and reproducible framework reinforced by statistical results supporting the fact that open scale numerical measurements can complement the ASUDAS method

A geometric morphometric approach to the study of variation of shovel‐shaped incisors

Objectives : The scoring and analysis of dental nonmetric traits are predominantly accomplished by using the Arizona State University Dental Anthropology System (ASUDAS), a standard protocol based on strict definitions and three‐dimensional dental plaques. However, visual scoring, even when controlled by strict definitions of features, visual reference, and the experience of the observer, includes an unavoidable part of subjectivity. In this methodological contribution, we propose a new quantitative geometric morphometric approach to quickly and efficiently assess the variation of shoveling in modern human maxillary central incisors (UI1).; Materials and methods : We analyzed 87 modern human UI1s by means of virtual imaging and the ASU‐UI1 dental plaque grades using geometric morphometrics by placing semilandmarks on the labial crown aspect. The modern human sample was composed of individuals from Europe, Africa, and Asia and included representatives of all seven grades defined by the ASUDAS method.; Results : Our results highlighted some limitations in the use of the current UI1 ASUDAS plaque, indicating that it did not necessarily represent an objective gradient of expression of a nonmetric tooth feature. Rating of shoveling tended to be more prone to intra‐ and interobserver bias for the highest grades. In addition, our analyses suggest that the observers were strongly influenced by the depth of the lingual crown aspect when assessing the shoveling.; Discussion : In this context, our results provide a reliable and reproducible framework reinforced by statistical results supporting the fact that open scale numerical measurements can complement the ASUDAS method.Facultad de Ciencias Naturales y MuseoConsejo Nacional de Investigaciones Científicas y Técnica

Stem cells, regenerative medicine and periodontal regeneration

La première partie de ce travail introduit un nouveau concept d'analyse des enregistrements des essais cliniques et de la dynamique de leur évolution, aussi bien thématique que temporelle. Ce concept a été appliqué à la médecine régénérative, démontrant l'absence de corrélation entre la source de cellules souches et le champ d'application. Les pathologies odonto-stomatologiques sont très peu concernées par les essais cliniques en thérapie cellulaire par cellules souches. Pourtant les parodontites, pathologies immuno-infectieuses responsables de la destruction du tissu de soutien des dents, constituent un enjeu majeur de santé publique. Bien que les auteurs s'accordent sur la responsabilité de l'écologie immunitaire et microbienne dans la physiopathologie de la maladie, les raisons de la dysbiose, de la susceptibilité individuelle sont encore mal connues. La greffe de cellules stromales mésenchymateuses (CSM) permettrait le retour à l'homéostasie en favorisant l'activation des CSM endogènes. La deuxième partie de ce travail démontre que les parodontites ont été potentiellement associées avec 57 pathologies systémiques ; le registre des essais cliniques de l'Organisation Mondiale de la Santé ayant été analysé. L'efficacité et la sureté de l'utilisation des CSM pour la régénération parodontale dans des modèles animaux ont été également démontrées. Pourtant, les modèles utilisés souffraient de problèmes méthodologiques dont la faible représentativité physiopathologique des lésions parodontales générées. Cette deuxième partie apporte donc des données quant à l'efficacité des ASC (CSM du tissu adipeux) pour améliorer de manière quantitative et qualitative la régénération des tissus de soutien parodontaux dans un modèle murin où les lésions parodontales ont été générées par l'administration répétée de bactéries parodonto-pathogènes. Il s'agit donc d'un modèle dont la physiopathologie est plus proche de celle retrouvée chez l'Homme. Enfin, la deuxième partie démontre un effet antibactérien à large spectre des ASC dont l'effet est à la fois direct (effet macrophage-like) et indirect (via la sécrétion de facteurs antibactériens).The first part of this work introduces a new concept of analysis of clinical trial records and the dynamics of their evolution, both thematic and temporal. This concept has been applied to regenerative medicine, showing the lack of correlation between the source of stem cells and the fields of application. The stomatognathic diseases are few involved in clinical trials for stem cells therapy. Yet periodontitis, immuno-infectious diseases responsible for the destruction of the tooth supporting tissues, are a major public health issue. While the authors agree on the responsibility of the immune and microbial ecology in the pathophysiology of the disease, the reasons for dysbiosis, individual susceptibilities, are still unclear. Graft of mesenchymal stromal cells (MSCs) would return to homeostasis by promoting the activation of endogenous MSCs. The second part of this work shows that periodontitis were potentially associated with 57 systemic diseases; the clinical trials registry of the World Health Organization have been analyzed. The efficacy and safety of the use of MSCs for periodontal regeneration in animal models have also been demonstrated. Yet the models suffered from methodological problems, periodontal lesions are few representative of the pathophysiology. This second part thus provides data on the effectiveness of ASC (CSM from adipose tissue) to improve quantitative and qualitative regeneration of periodontal supporting tissues in a mouse model where periodontal lesions were generated by repeated administration of parodonto-pathogenic bacteria. It is therefore a model whose pathophysiology is closer to that found in humans. Finally, the second part demonstrates broad antibacterial spectrum of ASC whose effect is both direct (macrophage-like effect) and indirect (via the secretion of antibacterial factors)

Systemic Periodontal Risk Score Using an Innovative Machine Learning Strategy: An Observational Study

Early diagnosis is crucial for individuals who are susceptible to tooth-supporting tissue diseases (e.g., periodontitis) that may lead to tooth loss, so as to prevent systemic implications and maintain quality of life. The aim of this study was to propose a personalized explainable machine learning algorithm, solely based on non-invasive predictors that can easily be collected in a clinic, to identify subjects at risk of developing periodontal diseases. To this end, the individual data and periodontal health of 532 subjects was assessed. A machine learning pipeline combining a feature selection step, multilayer perceptron, and SHapley Additive exPlanations (SHAP) explainability, was used to build the algorithm. The prediction scores for healthy periodontium and periodontitis gave final F1-scores of 0.74 and 0.68, respectively, while gingival inflammation was harder to predict (F1-score of 0.32). Age, body mass index, smoking habits, systemic pathologies, diet, alcohol, educational level, and hormonal status were found to be the most contributive variables for periodontal health prediction. The algorithm clearly shows different risk profiles before and after 35 years of age and suggests transition ages in the predisposition to developing gingival inflammation or periodontitis. This innovative approach to systemic periodontal disease risk profiles, combining both ML and up-to-date explainability algorithms, paves the way for new periodontal health prediction strategies

Cellules souches, médecine régénérative et régénération parodontale

La première partie de ce travail introduit un nouveau concept d'analyse des enregistrements des essais cliniques et de la dynamique de leur évolution, aussi bien thématique que temporelle. Ce concept a été appliqué à la médecine régénérative, démontrant l'absence de corrélation entre la source de cellules souches et le champ d'application. Les pathologies odonto-stomatologiques sont très peu concernées par les essais cliniques en thérapie cellulaire par cellules souches. Pourtant les parodontites, pathologies immuno-infectieuses responsables de la destruction du tissu de soutien des dents, constituent un enjeu majeur de santé publique. Bien que les auteurs s'accordent sur la responsabilité de l'écologie immunitaire et microbienne dans la physiopathologie de la maladie, les raisons de la dysbiose, de la susceptibilité individuelle sont encore mal connues. La greffe de cellules stromales mésenchymateuses (CSM) permettrait le retour à l'homéostasie en favorisant l'activation des CSM endogènes. La deuxième partie de ce travail démontre que les parodontites ont été potentiellement associées avec 57 pathologies systémiques ; le registre des essais cliniques de l'Organisation Mondiale de la Santé ayant été analysé. L'efficacité et la sureté de l'utilisation des CSM pour la régénération parodontale dans des modèles animaux ont été également démontrées. Pourtant, les modèles utilisés souffraient de problèmes méthodologiques dont la faible représentativité physiopathologique des lésions parodontales générées. Cette deuxième partie apporte donc des données quant à l'efficacité des ASC (CSM du tissu adipeux) pour améliorer de manière quantitative et qualitative la régénération des tissus de soutien parodontaux dans un modèle murin où les lésions parodontales ont été générées par l'administration répétée de bactéries parodonto-pathogènes. Il s'agit donc d'un modèle dont la physiopathologie est plus proche de celle retrouvée chez l'Homme. Enfin, la deuxième partie démontre un effet antibactérien à large spectre des ASC dont l'effet est à la fois direct (effet macrophage-like) et indirect (via la sécrétion de facteurs antibactériens).The first part of this work introduces a new concept of analysis of clinical trial records and the dynamics of their evolution, both thematic and temporal. This concept has been applied to regenerative medicine, showing the lack of correlation between the source of stem cells and the fields of application. The stomatognathic diseases are few involved in clinical trials for stem cells therapy. Yet periodontitis, immuno-infectious diseases responsible for the destruction of the tooth supporting tissues, are a major public health issue. While the authors agree on the responsibility of the immune and microbial ecology in the pathophysiology of the disease, the reasons for dysbiosis, individual susceptibilities, are still unclear. Graft of mesenchymal stromal cells (MSCs) would return to homeostasis by promoting the activation of endogenous MSCs. The second part of this work shows that periodontitis were potentially associated with 57 systemic diseases; the clinical trials registry of the World Health Organization have been analyzed. The efficacy and safety of the use of MSCs for periodontal regeneration in animal models have also been demonstrated. Yet the models suffered from methodological problems, periodontal lesions are few representative of the pathophysiology. This second part thus provides data on the effectiveness of ASC (CSM from adipose tissue) to improve quantitative and qualitative regeneration of periodontal supporting tissues in a mouse model where periodontal lesions were generated by repeated administration of parodonto-pathogenic bacteria. It is therefore a model whose pathophysiology is closer to that found in humans. Finally, the second part demonstrates broad antibacterial spectrum of ASC whose effect is both direct (macrophage-like effect) and indirect (via the secretion of antibacterial factors)

Figures for reviewing

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Parodontite et déclin cognitif (revue systématique de la littérature)

TOULOUSE3-BU Santé-Centrale (315552105) / SudocSudocFranceF

Parodontite et polyarthrite rhumatoïde

TOULOUSE3-BU Santé-Centrale (315552105) / SudocSudocFranceF

Doctors in Medical Data Sciences: A New Curriculum

Machine Learning (ML), a branch of Artificial Intelligence, which is competing with human experts in many specialized biomedical fields and will play an increasing role in precision medicine. As with any other technological advances in medicine, the keys to understanding must be integrated into practitioner training. To respond to this challenge, this viewpoint discusses some necessary changes in the health studies curriculum that could help practitioners to interpret decisions the made by a machine and question them in relation to the patient&rsquo;s medical context. The complexity of technology and the inherent criticality of its use in medicine also necessitate a new medical profession. To achieve this objective, this viewpoint will propose new medical practitioners with skills in both medicine and data science: the Doctor in Medical Data Sciences