Acceptability of Allogeneic Mesenchymal Stromal Cell-Based Tissue Engineering for the Treatment of Periodontitis: A Qualitative Study in France.

INTRODUCTION AND AIMS: Periodontitis, the main cause of tooth loss in adults, is a public health concern; its incidence increases with age, and its prevalence increases with increasing life expectancy of the population. Innovative therapies such as cell therapy represent promising future solutions for guided tissue regeneration. However, these therapies may be associated with fears and mistrust from the general public. The aim of this study was to estimate the acceptability of an advanced therapy medicinal product combining allogeneic mesenchymal stromal cells from adipose tissue with a natural fibrin hydrogel in the treatment of periodontitis. METHODS: The methodology was based on a qualitative study conducted through semi-structured interviews with patients followed for periodontitis in the Oral Medicine Department of the Toulouse University Hospital, Toulouse, France. Qualitative studies are essential methodologies to understand the patterns of health behaviours, describe illness experiences, and design health interventions in a humanistic and person-centred way of discovering. RESULTS: Eleven interviews (with 4 men and 7 women) were required to reach thematic saturation. Analysis allowed 4 main themes to emerge: (1) perception of new treatments, science, and caregivers; (2) conditions that the treatment must meet; (3) patient perception of the disease; and (4) factors related to the content of the treatment. CONCLUSIONS: Patients find cell therapy for periodontitis to be acceptable. If they express a need to be informed about the benefit/risk ratio, they are not particularly worried about side effects of the treatment, for either allogeneic or blood-derived products. Periodontitis is a prototypical model of chronic inflammatory pathology and is multitissular, with hard- and soft-tissue lesions. In a patient-centred approach, the success of cell therapy will require a bilateral, informed decision, taking into account potential therapeutic effectiveness and patient expectations for regeneration.

The oral organ: A new vision of the mouth as a whole for a gerophysiological approach to healthy aging.

This article brings a new perspective on oral physiology by presenting the oral organ as an integrated entity within the entire organism and its surrounding environment. Rather than considering the mouth solely as a collection of discrete functions, this novel approach emphasizes its role as a dynamic interphase, supporting interactions between the body and external factors. As a resilient ecosystem, the equilibrium of mouth ecological niches is the result of a large number of interconnected factors including the heterogeneity of different oral structures, diversity of resources, external and internal pressures and biological actors. The manuscript seeks to deepen the understanding of age-related changes within the oral cavity and throughout the organism, aligning with the evolving field of gerophysiology. The strategic position and fundamental function of the mouth make it an invaluable target for early prevention, diagnosis, treatment, and even reversal of aging effects throughout the entire organism. Recognizing the oral cavity capacity for sensory perception, element capture and information processing underscores its vital role in continuous health monitoring. Overall, this integrated understanding of the oral physiology aims at advancing comprehensive approaches to the oral healthcare and promoting broader awareness of its implications on the overall well-being.

The Role of Dysbiotic Oral Microbiota in Cardiometabolic Diseases: A Narrative Review.

Over the past decade, there have been significant advancements in the high-flow analysis of "omics," shedding light on the relationship between the microbiota and the host. However, the full recognition of this relationship and its implications in cardiometabolic diseases are still underway, despite advancements in understanding the pathophysiology of these conditions. Cardiometabolic diseases, which include a range of conditions from insulin resistance to cardiovascular disease and type 2 diabetes, continue to be the leading cause of mortality worldwide, with a persistently high morbidity rate. While the link between the intestinal microbiota and cardiometabolic risks has been extensively explored, the role of the oral microbiota, the second-largest microbiota in the human body, and specifically the dysbiosis of this microbiota in causing these complications, remains incompletely defined. This review aims to examine the association between the oral microbiota and cardiometabolic diseases, focusing on the dysbiosis of the oral microbiota, particularly in periodontal disease. Additionally, we will dive into the mechanistic aspects of this dysbiosis that contribute to the development of these complications. Finally, we will discuss potential prevention and treatment strategies, including the use of prebiotics, probiotics, and other interventions.

Explainable machine learning framework to predict personalized physiological aging.

Attaining personalized healthy aging requires accurate monitoring of physiological changes and identifying subclinical markers that predict accelerated or delayed aging. Classic biostatistical methods most rely on supervised variables to estimate physiological aging and do not capture the full complexity of inter-parameter interactions. Machine learning (ML) is promising, but its black box nature eludes direct understanding, substantially limiting physician confidence and clinical usage. Using a broad population dataset from the National Health and Nutrition Examination Survey (NHANES) study including routine biological variables and after selection of XGBoost as the most appropriate algorithm, we created an innovative explainable ML framework to determine a Personalized physiological age (PPA). PPA predicted both chronic disease and mortality independently of chronological age. Twenty-six variables were sufficient to predict PPA. Using SHapley Additive exPlanations (SHAP), we implemented a precise quantitative associated metric for each variable explaining physiological (i.e., accelerated or delayed) deviations from age-specific normative data. Among the variables, glycated hemoglobin (HbA1c) displays a major relative weight in the estimation of PPA. Finally, clustering profiles of identical contextualized explanations reveal different aging trajectories opening opportunities to specific clinical follow-up. These data show that PPA is a robust, quantitative and explainable ML-based metric that monitors personalized health status. Our approach also provides a complete framework applicable to different datasets or variables, allowing precision physiological age estimation.

Explanations as a New Metric for Feature Selection: A Systematic Approach.

With the extensive use of Machine Learning (ML) in the biomedical field, there was an increasing need for Explainable Artificial Intelligence (XAI) to improve transparency and reveal complex hidden relationships between variables for medical practitioners, while meeting regulatory requirements. Feature Selection (FS) is widely used as a part of a biomedical ML pipeline to significantly reduce the number of variables while preserving as much information as possible. However, the choice of FS methods affects the entire pipeline including the final prediction explanations, whereas very few works investigate the relationship between FS and model explanations. Through a systematic workflow performed on 145 datasets and an illustration on medical data, the present work demonstrated the promising complementarity of two metrics based on explanations (using ranking and influence changes) in addition to accuracy and retention rate to select the most appropriate FS/ML models. Measuring how much explanations differ with/without FS are particularly promising for FS methods recommendation. While reliefF generally performs the best on average, the optimal choice may vary for each dataset. Positioning FS methods in a tridimensional space, integrating explanations-based metrics, accuracy and retention rate, would allow the user to choose the priorities to be given on each of the dimensions. In biomedical applications, where each medical condition may have its own preferences, this framework will make it possible to offer the healthcare professional the appropriate FS technique, to select the variables that have an important explainable impact, even if this comes at the expense of a limited drop of accuracy.

Gingival Orofacial Granulomatosis Clinical and 2D/3D Microscopy Features after Orthodontic Therapy: A Pediatric Case Report.

Orofacial granulomatosis (OFG) represents a heterogeneous group of rare orofacial diseases. When affecting gingiva, it appears as a chronic soft tissue inflammation, sometimes combined with the enlargement and swelling of other intraoral sites, including the lips. Gingival biopsy highlights noncaseating granulomatous inflammation, similar to that observed in Crohn's disease and sarcoidosis. At present, the etiology of OFG remains uncertain, although the involvement of the genetic background and environmental triggers, such as oral conditions or therapies (including orthodontic treatment), has been suggested. The present study reports the results of a detailed clinical and 2D/3D microscopy investigation of a case of gingival orofacial granulomatosis in an 8-year-old male patient after orthodontic therapy. Intraoral examination showed an erythematous hyperplasia of the whole gingiva with a granular appearance occurring a few weeks after the installation of a quad-helix. Peri-oral inspection revealed upper labial swelling and angular cheilitis. General investigations did not report ongoing extra-oral disturbances with the exception of a weakly positive anti-Saccharomyces cerevicae IgG auto-antibody. Two- and three-dimensional microscopic investigations confirmed the presence of gingival orofacial granulomatosis. Daily corticoid mouthwashes over a period of 3 months resulted in a slight improvement in clinical signs, despite an intermittent inflammation recurrence. This study brings new insights into the microscopic features of gingival orofacial granulomatosis, thus providing key elements to oral practitioners to ensure accurate and timely OFG diagnosis. The accurate diagnosis of OFG allows targeted management of symptoms and patient monitoring over time, along with early detection and treatment of extra-oral manifestations, such as Crohn's disease.

Characterization and Safety Profile of a New Combined Advanced Therapeutic Medical Product Platelet Lysate-Based Fibrin Hydrogel for Mesenchymal Stromal Cell Local Delivery in Regenerative Medicine.

Adipose-derived mesenchymal stromal cells (ASC) transplant to recover the optimal tissue structure/function relationship is a promising strategy to regenerate tissue lesions. Because filling local tissue defects by injection alone is often challenging, designing adequate cell carriers with suitable characteristics is critical for in situ ASC delivery. The aim of this study was to optimize the generation phase of a platelet-lysate-based fibrin hydrogel (PLFH) as a proper carrier for in situ ASC implantation and (1) to investigate in vitro PLFH biomechanical properties, cell viability, proliferation and migration sustainability, and (2) to comprehensively assess the local in vivo PLFH/ASC safety profile (local tolerance, ASC fate, biodistribution and toxicity). We first defined the experimental conditions to enhance physicochemical properties and microscopic features of PLFH as an adequate ASC vehicle. When ASC were mixed with PLFH, in vitro assays exhibited hydrogel supporting cell migration, viability and proliferation. In vivo local subcutaneous and subgingival PLFH/ASC administration in nude mice allowed us to generate biosafety data, including biodegradability, tolerance, ASC fate and engraftment, and the absence of biodistribution and toxicity to non-target tissues. Our data strongly suggest that this novel combined ATMP for in situ administration is safe with an efficient local ASC engraftment, supporting the further development for human clinical cell therapy.

Oral health status in patients with inherited epidermolysis bullosa: a comparative multicenter study.

OBJECTIVE: Epidermolysis bullosa (EB) is a rare genetic mucocutaneous disorder characterized by epithelial fragility leading to blister formation on skin and mucous membranes with even minor mechanical trauma. Most EB oral health publications give fragmented information, focusing on only one oral health aspect or one EB type. The aim of this study was to expand the knowledge of the overall oral health status of individuals with dystrophic, junctional, and simplex EB. METHOD AND MATERIALS: A comparative multicenter study, including a control group, and based on questionnaires and clinical examinations, was undertaken in three EB expert centers. RESULTS: Most EB (90.2%) participants brushed their teeth at least once a day despite the pain. The prevalence of enamel defects and caries experience did not differ between the 42 EB participants and the 42 age-/sex-matched healthy controls. Gingival inflammation unrelated to dental plaque accumulation was found in EB participants. Blisters, erythema, and erosion/ulceration mainly involved gingiva, buccal mucosa, lips, and palate, with different topographic patterns according to EB type. EB patients whatever the age showed a similar lesion distribution. Simplex and dystrophic EB patients under 12 years old displayed higher lesion severity than junctional EB ones. Only dystrophic type exhibited microstomia and ankyloglossia. CONCLUSION: Oral health status seemed to benefit from a close collaboration between dental practitioner and dermatologist, and from regular dental examination, starting at a young age and with a focus on prevention. The new appreciation of oral health involvement highlighted by this study is essential for EB patients care, regarding comorbidities and quality of life.

Improvement of Mucosal Lesion Diagnosis with Machine Learning Based on Medical and Semiological Data: An Observational Study.

Despite artificial intelligence used in skin dermatology diagnosis is booming, application in oral pathology remains to be developed. Early diagnosis and therefore early management, remain key points in the successful management of oral mucosa cancers. The objective was to develop and evaluate a machine learning algorithm that allows the prediction of oral mucosa lesions diagnosis. This cohort study included patients followed between January 2015 and December 2020 in the oral mucosal pathology consultation of the Toulouse University Hospital. Photographs and demographic and medical data were collected from each patient to constitute clinical cases. A machine learning model was then developed and optimized and compared to 5 models classically used in the field. A total of 299 patients representing 1242 records of oral mucosa lesions were used to train and evaluate machine learning models. Our model reached a mean accuracy of 0.84 for diagnostic prediction. The specificity and sensitivity range from 0.89 to 1.00 and 0.72 to 0.92, respectively. The other models were proven to be less efficient in performing this task. These results suggest the utility of machine learning-based tools in diagnosing oral mucosal lesions with high accuracy. Moreover, the results of this study confirm that the consideration of clinical data and medical history, in addition to the lesion itself, appears to play an important role.

A Spectral Principal Component Analysis-Based Framework for Composite Hard/Soft Tissue Fluorescence Image Investigation.

Traditional thin sectioning microscopy of large bone and dental tissue samples using demineralization may disrupt structure morphologies and even damage soft tissues, thus compromising the histopathological investigation. Here, we developed a synergistic and original framework on thick sections based on wide-field multi-fluorescence imaging and spectral Principal Component Analysis (sPCA) as an alternative, fast, versatile, and reliable solution, suitable for highly mineralized tissue structure sustain and visualization. Periodontal 2-mm thick sections were stained with a solution containing five fluorescent dyes chosen for their ability to discriminate close tissues, and acquisitions were performed with a multi-zoom macroscope for blue, green, red, and NIR (near-infrared) emissions. Eigen-images derived from both standard scaler (Std) and Contrast Limited Adaptive Histogram Equalization (Clahe) pre-preprocessing significantly enhanced tissue contrasts, highly suitable for histopathological investigation with an in-depth detail for sub-tissue structure discrimination. Using this method, it is possible to preserve and delineate accurately the different anatomical/morphological features of the periodontium, a complex tooth-supporting multi-tissue. Indeed, we achieve characterization of gingiva, alveolar bone, cementum, and periodontal ligament tissues. The ease and adaptability of this approach make it an effective method for providing high-contrast features that are not usually available in standard staining histology. Beyond periodontal investigations, this first proof of concept of an sPCA solution for optical microscopy of complex structures, especially including mineralized tissues opens new perspectives to deal with other chronic diseases involving complex tissue and organ defects. Overall, such an imaging framework appears to be a novel and convenient strategy for optical microscopy investigation.

Periodontal Cell Therapy: A Systematic Review and Meta-analysis.

BACKGROUND: Periodontitis is a chronic inflammatory disease characterized by the loss of tooth-supporting tissues (or periodontium) leading to the formation of periodontal pocket then to tooth loss. Conventional therapies that involve tooth root debridement are still disappointing because they are more centered on periodontal repair than disease pathophysiology causes. The meta-analysis we present here focused on the results of experimental studies that investigated periodontal mesenchymal stromal cells (MSCs) therapy, a promising strategy to regenerate tissue, given to their immunomodulatory and trophic properties. METHODS: Using PubMed database and ICTRP search portal, 84 animal and 3 randomized human studies were analyzed. RESULTS: Overall, our results highlighted that MSCs grafting, regardless of their tissue origin, enhances periodontal regeneration. A defect morphology suitable for an initial clot stabilization increases the procedure efficacy, especially if cells are carried using a vehicle from natural origin. Nevertheless, methodological biases have been highlighted and still limit the translation to human with high prognosis and regulatory considerations. Besides, because only 2 randomized human trials demonstrated the efficacy of the procedure, further studies are needed to investigate periodontal regeneration procedures on experimental models closer to human pathophysiology. CONCLUSION: Although MSCs grafting in periodontal disease demonstrated therapeutic benefits in animal, it is critical to define more accurately protocols translatable to human and focus on the treatment of the pathology as a whole rather than on the restitution of the sole destroyed tissues.

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.

Broad-Spectrum Antibacterial Effects of Human Adipose-Derived Stromal Cells.

INTRODUCTION: Many pathological conditions may benefit from cell therapy using mesenchymal stromal cells, particularly from adipose tissue (ASCs). Cells may be grafted in an environment with a remnant polymicrobial component. The aim is to investigate the behavior of ASCs when brought in contact with a large panel of bacteria. MATERIALS AND METHODS: Carboxyfluorescein-labelled bacterial interaction with ASCs was followed by confocal time-lapse microscopy. Costaining with LAMP-1 was also analyzed. Viability of 4 gram-negative and 4 gram-positive bacterial strains after 6 h of coculture with ASCs was assessed by agar colony counting and by flow cytometry using SYTO-62®/propidium iodide (PI) for membrane permeabilization and DiOC6 for depolarization. A murine model of periodontitis was used to assess in vivo antibacterial capacities of ASCs. RESULTS: A significant increase of PI-positive events for all bacterial strains and an increase of the DiOC6 signal were obtained after contact with ASCs. The number of CFU was also significantly decreased for several bacterial strains. 0.4 µm transwell systems illustrated the necessary direct contact to induce maximal bacterial membrane damages. Some bacteria were observed into phagolysosomes, confirming macrophage-like properties of ASCs. In vivo, the bacterial load was significantly lower in the ASC-grafted side compared to the control. CONCLUSION: Our results highlight for the first time a broad range of antibacterial actions of ASCs, by phagocytosis, secretion of oxygenated free radicals and antibacterial molecules. These data are in line with the development of new therapeutic strategies based on ASC transplantation, appropriated in immune-dysbiotic tissue context such as periodontitis or chronic wounds.

Trichomonas tenax and periodontal diseases: a concise review.

Periodontal diseases (gingivitis and periodontitis), result from a disruption of the host-oral microbiome homoeostasis. Whereas the pathological role of some specific bacterial strains during periodontal diseases is well documented, the impact of parasites in periodontium pathophysiology is still under debate. This review aims to collect data about the prevalence and the potential role of Trichomonas tenax during periodontal diseases. Data from 47 studies revealed that T. tenax prevalence in diseased periodontium ranged from 0 to 94·1%. The prevalence of oral protozoan infections was found to be largely greater in patients with periodontal diseases than with healthy periodontium. The parasite detection was mainly performed by direct microscopy. Trichomonas tenax presence was clearly correlated with periodontal disease. The high heterogeneity of its periodontal prevalence may be correlated with the diversity of the population screened (age, sex, systemic diseases), and the methods used for diagnosis. This protozoan seems to have the capacity to be involved in the inflammatory process of gum disease. Animal experimentation, using relevant physiopathological models of periodontitis, needs to be performed to investigate the ability of T. tenax to cause and/or worsen the disease. Further investigations using standardized experimental designs of epidemiologic studies are also needed.

Periodontal Tissue Regeneration Using Syngeneic Adipose-Derived Stromal Cells in a Mouse Model.

Current treatment of periodontitis is still associated with a high degree of variability in clinical outcomes. Recent advances in regenerative medicine by mesenchymal cells, including adipose stromal cells (ASC) have paved the way to improved periodontal regeneration (PD) but little is known about the biological processes involved. Here, we aimed to use syngeneic ASCs for periodontal regeneration in a new, relevant, bacteria-induced periodontitis model in mice. Periodontal defects were induced in female C57BL6/J mice by oral gavage with periodontal pathogens. We grafted 2 × 105 syngeneic mouse ASCs expressing green fluorescent protein (GFP) (GFP+/ASC) within a collagen vehicle in the lingual part of the first lower molar periodontium (experimental) while carrier alone was implanted in the contralateral side (control). Animals were sacrificed 0, 1, 6, and 12 weeks after treatment by GFP+/ASC or vehicle graft, and microscopic examination, immunofluorescence, and innovative bio-informatics histomorphometry methods were used to reveal deep periodontium changes. From 1 to 6 weeks after surgery, GFP+ cells were identified in the periodontal ligament (PDL), in experimental sites only. After 12 weeks, cementum regeneration, the organization of PDL fibers, the number of PD vessels, and bone morphogenetic protein-2 and osteopontin expression were greater in experimental sites than in controls. Specific stromal cell subsets were recruited in the newly formed tissue in ASC-implanted periodontium only. These data suggest that ASC grafting in diseased deep periodontium, relevant to human pathology, induces a significant improvement of the PDL microenvironment, leading to a recovery of tooth-supporting tissue homeostasis. Stem Cells Translational Medicine 2017;6:656-665.

Spatial and temporal structure of the clinical research based on mesenchymal stromal cells: A network analysis.

BACKGROUND AIMS: Using innovative tools derived from social network analysis, the aims of this study were (i) to decipher the spatial and temporal structure of the research centers network dedicated to the therapeutic uses of mesenchymal stromal cells (MSCs) and (ii) to measure the influence of fields of applications, cellular sources and industry funding on network topography. METHODS: From each trial using MSCs reported on ClinicalTrials.gov, all research centers were extracted. Networks were generated using Cytoscape 3.2.2, where each center was assimilated to a node, and one trial to an edge connecting two nodes. RESULTS: The analysis included 563 studies. An independent segregation was obvious between continents. Asian, South American and African centers were significantly more isolated than other centers. Isolated centers had fewer advanced phases (P <0.001), completed studies (P = 0.01) and industry-supported studies (P <0.001). Various thematic priorities among continents were identified: the cardiovascular, digestive and nervous system diseases were strongly studied by North America, Europe and Asia, respectively. The choice of cellular sources also affected the network topography; North America was primarily involved in bone-marrow-derived MSC research, whereas Europe and Asia dominated the use of adipose-derived MSCs. Industrial funding was the highest for North American centers (90.5%). CONCLUSIONS: Strengthening of international standards and statements with institutional, federal and industrial partners is necessary. More connections would facilitate the transfer of knowledge, sharing of resources, mobility of researchers and advancement of trials. Developing partnerships between industry and academic centers seems beneficial to the advancement of trials across different phases and would facilitate the translation of research discoveries.

Periodontitis induced by Porphyromonas gingivalis drives periodontal microbiota dysbiosis and insulin resistance via an impaired adaptive immune response.

OBJECTIVE: To identify a causal mechanism responsible for the enhancement of insulin resistance and hyperglycaemia following periodontitis in mice fed a fat-enriched diet. DESIGN: We set-up a unique animal model of periodontitis in C57Bl/6 female mice by infecting the periodontal tissue with specific and alive pathogens like Porphyromonas gingivalis (Pg), Fusobacterium nucleatum and Prevotella intermedia. The mice were then fed with a diabetogenic/non-obesogenic fat-enriched diet for up to 3 months. Alveolar bone loss, periodontal microbiota dysbiosis and features of glucose metabolism were quantified. Eventually, adoptive transfer of cervical (regional) and systemic immune cells was performed to demonstrate the causal role of the cervical immune system. RESULTS: Periodontitis induced a periodontal microbiota dysbiosis without mainly affecting gut microbiota. The disease concomitantly impacted on the regional and systemic immune response impairing glucose metabolism. The transfer of cervical lymph-node cells from infected mice to naive recipients guarded against periodontitis-aggravated metabolic disease. A treatment with inactivated Pg prior to the periodontal infection induced specific antibodies against Pg and protected the mouse from periodontitis-induced dysmetabolism. Finally, a 1-month subcutaneous chronic infusion of low rates of lipopolysaccharides from Pg mimicked the impact of periodontitis on immune and metabolic parameters. CONCLUSIONS: We identified that insulin resistance in the high-fat fed mouse is enhanced by pathogen-induced periodontitis. This is caused by an adaptive immune response specifically directed against pathogens and associated with a periodontal dysbiosis.

An Innovative, Comprehensive Mapping and Multiscale Analysis of Registered Trials for Stem Cell-Based Regenerative Medicine.

UNLABELLED: We aim to provide an innovative, comprehensive way of mapping the profusion of stem cell-based clinical trials registered at ClinicalTrials.gov to explore the diversity of the fields of application and the temporal complexity of the domain. We used a chord diagram and phylogenetic-like tree visualizations to assist in data mining and knowledge discovery. The search strategy used the following terms: "stromal OR stem OR mesenchymal OR progenitor." The Medical Subject Headings (MeSH) thesaurus was used to more finely classify diseases treated by stem cells, from large fields of application to specific diseases. Of the 5,788 trials screened, 939 were included, 51.1% of which were related to mesenchymal stem cells (MSCs). No real specificity emerged as to the therapeutic uses of the different types of stem cells. More than half the MSC studies concerned allogeneic MSCs and received more support from industry than autologous MSC studies (p < .001). Over time, the uses of cultured cells have increased greatly, particularly since 2009. Cells derived from adipose tissue are also increasingly used in trials compared with bone marrow cells. The use of adipose-derived stromal cells was predominantly autologous (p < .001), restricted to European countries (p < .01), and supported by industry (p = .02) compared with other MSCs. Details about MeSH keywords are available at http://multireview.perso.sfr.fr/. In conclusion, mapping may reveal a lack of global strategy despite the regulations and the related costs associated with good manufacturing practices. A systematic approach to preclinical data, intended to objectively and robustly reveal the most appropriate fields with the most efficient cells, is needed. Repeated exchanges between the bench and the bedside are necessary. SIGNIFICANCE: Except for a few trials concerning specific tissue stem cells used in their corresponding tissues, this global analysis revealed no real specificity of stem cell uses (including mesenchymal stromal cells). This raised the question of the physiopathological rationale for these uses and the lack of a global strategy despite the regulations and the related costs associated with good manufacturing practices. This original method, leading to the development of new concepts from already available data, would help policymakers to optimize resources and investments in terms of public health priorities. Such an approach should draw parallels between in vitro, in vivo, and human data. Exchanges in both directions between preclinical and clinical research could optimize the parameters of clinical trials step by step.

Clinical research activity in periodontal medicine: a systematic mapping of trial registers.

AIM: The primary aim of the study was to systematically map registration records on periodontal medicine in clinical trial registers. The secondary aim was to assess the evolution of periodontal medicine in clinical periodontal research as a whole. MATERIAL AND METHODS: We searched all registration records related to periodontology in the World Health Organization International Clinical Trials Registry Platform. For registration records classified in the field of periodontal medicine, we assigned the 2015 MeSH(®) term for the most precisely corresponding systemic condition. RESULTS: Fifty-seven systemic conditions have been hypothesized to be linked with periodontal diseases, covering nearly 2% of the diseases indexed in MeSH. In addition to diabetes, cardiovascular disease or preterm birth, other systemic conditions have been the subject of registration records, such as anaemia, liver diseases, dyspepsia or ankylosing spondylitis. A trend towards increasing diversification of systemic conditions has appeared over time. About a third of registration records in clinical periodontal research deals with periodontal medicine. CONCLUSIONS: Periodontal medicine now constitutes an important part of clinical periodontal research. Research activity in periodontal medicine has grown continuously since the early 2000s, and exploration of registers gives a useful up-to-date snapshot of this constantly evolving field of research.