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Enregistrement W4388014598 · doi:10.1111/odi.14796

Artificial intelligence, cell therapies, acupuncture, and tight junctions: Advances in salivary research

2023· editorial· en· W4388014598 sur OpenAlexaff
Simon D. Tran

Notice bibliographique

RevueOral Diseases · 2023
Typeeditorial
Langueen
DomaineMedicine
ThématiqueSalivary Gland Disorders and Functions
Établissements canadiensMcGill University
Organismes subventionnairesnon disponible
Mots-clésOral medicineOral healthCitationLibrary scienceBiomedical sciencesMedicinePsychologyFamily medicineComputer scienceDentistryPathology

Résumé

récupéré en direct d'OpenAlex

Many scientific disciplines, including salivary research, are benefiting from major advances in science such as the use of artificial intelligence to accelerate discovery, cell-based therapies for intractable diseases, and improved analytical instrumentations to study cellular structures. Also, oriental therapies, such as acupuncture that is widely accepted in the East, are becoming increasingly popular in the West. In this issue of Oral Diseases, the section on Advances in Salivary Research includes four invited papers on topics relevant to researchers, clinicians, and students. The first paper is a review of salivary biomarker discovery and validation using artificial intelligence by Adeoye and Su from the University of Hong Kong (Adeoye & Su, 2023). Second is a review of cell-based therapies to treat salivary dysfunctions due to radiotherapy and Sjögren's syndrome by I and colleagues from Nagasaki University, Japan (I et al., 2023). Third is a review of tight junctions in the regulation of salivary gland secretion by Cong and colleagues from Peking University (Cong et al., 2023). Fourth is an original paper on the use of acupuncture to treat Sjögren's syndrome patients and nonobese diabetic mice with Sjögren's-like disease by Liu and colleagues from the China Academy of Chinese Medical Sciences (Liu et al., 2023). Artificial intelligence (AI) can accelerate research and discovery because of currently available large data sets, fast computing, and new algorithms. AI has revolutionized research workflows by providing accurate predictions (Wang et al., 2023). Adeoye and Su reviewed AI current techniques for salivary biomarker discovery and validation in oral diseases (Adeoye & Su, 2023). AI uses contemporary analytical techniques, multi-omics data sets, and patient information to optimize the selection, validation, and operationalization of potential salivary biomarkers for diagnosing and managing oral diseases. Adeoye and Su listed in great detail the current applications of AI liquid (saliva) biopsy platforms for biomarker discovery and validation in oral cancers, dental caries, periodontal diseases, temporomandibular joint dysfunctions, halitosis, Sjogren syndrome, oral lichen planus, and oral mucositis. Cell therapies involve the administration of cells as living agents to fight diseases. Recently, there has been a growth in the clinical deployment of cell therapies in the pharmaceutical sector (Bashor et al., 2022). Certain cell therapies have received regulatory approval and are being marketed in Europe, Japan, and North America. Examples are chimeric antigen receptor (CAR)-T cells for the treatment of lymphoid cancers, limbal stem cells to repair damaged corneal epithelial, and adipose-derived mesenchymal stem cells to treat fistulas in Crohn's disease (Bashor et al., 2022). I and colleagues reviewed the current progress of cell therapies for salivary gland dysfunction, such as salivary hypofunction due to radiotherapy or Sjögren's syndrome (I et al., 2023). The authors reported that from over 100 experimental studies supporting the therapeutic potential of cell therapies to treat salivary hypofunction, seven studies have been tested in clinical studies for their safety and efficacy. These promising cell therapies to treat salivary hypofunction used either mesenchymal stem cells (MSCs) from adipose tissue, MSCs from bone marrow, MSCs from umbilical cord, or enhanced-mononuclear cells (E-MNC) from peripheral blood. Of particular note is the E-MNC approach which harvests cells from a blood sample and enhances the anti-inflammatory and vasculogenic characteristics of isolated mononuclear cells in a serum-free defined culture media supplemented with five factors for 5–7 days before reinjecting these E-MNC back to the patient. Tight junctions function as selective gates controlling paracellular diffusion of ions and solutes across epithelial and endothelial cells, define apical and basolateral membrane domains (cell polarization), and affect cell signaling, gene expression, and cell proliferation (Zihni et al., 2016). In a comprehensive review, Cong and colleagues enrich our understanding of the cellular and molecular functions of epithelial and endothelial cells tight junctions in the regulation of salivary secretion during physiological and pathophysiological conditions such as those encountered in Sjögren's syndrome, diabetes mellitus, and radiotherapy (Cong et al., 2023). Acupuncture, a traditional Chinese medicine nonpharmacologic approach, has been used for over 2000 years to treat numerous disorders, including xerostomia. Acupuncture is gaining popularity outside of China but as with any medical treatments, there are associated adverse events (Chan et al., 2017). Clinical studies testing acupuncture as a therapy for Sjögren's syndrome are still being standardized for their reporting on primary and long-term outcomes (Liu et al., 2021). Liu and colleagues, an experienced group of acupuncturists from the China Academy of Chinese Medical Sciences in Beijing, report promising results from a clinical study assessing the role of acupuncture on patients with Sjögren's syndrome as well as on nonobese diabetic mice in regulating cytokines and the expression of aquaporins (Liu et al., 2023). Overall, the series on ‘Advances in Salivary Research’ allows us to bring internationally established researchers and clinicians together to share their knowledge and expertise for the advancement of salivary research. Oral Diseases is proud to support this initiative to our journal readership worldwide.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,048
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,056
Tête enseignante GPT0,382
Écart entre enseignants0,326 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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