Background and Objectives: The immunomodulatory potential of mesenchymal stem cells (MSCs) can be regulated by a variety of molecules, especially cytokines. The inflammatory cytokine, TNF-like ligand 1A (TL1A), has been reported as an inflammation stimulator in-multiple autoimmune diseases. Here, we studied the effects of TL1A/TNF-receptor 2 (TNFR2) pathway on the therapeutic potency of bone marrow-derived MSCs (BMSCs). Methods: and Results: BMSCs, fibroblast-like synoviocytes (FLSs), and H9 and jurkat human T lymphocytes were used in this study. BMSCs paracrine activities, differentiation, proliferation, and migration were investigated after stimulation with TL1A, and intervened with anti-TNFR2. Additionally, the effects of TL1A on BMSCs therapeutic potency were evaluated by treating RA-FLSs, and H9 and jurkat T cells with TL1A-stimulated BMSCs conditioned medium (CM). Indian hedgehog (IHH) involvement was determined by gene silencing and treatment by recombinant IHH (rIHH). TL1A induced BMSCs stemness-related genes, COX-2, IL-6, IDO, TGF-β and HGF through TNFR2. Also, TL1A corrected biased differentiation and increased proliferation, and migration through TNFR2. Meanwhile, CM of TL1A-stimulated BMSCs decreased the inflammatory markers of RA-FLSs and T cells. Moreover, TL1A-stimulated BMSCs experienced IHH up-regulation coupled with NF-κB and STAT3 signaling up-regulation, while p53 and oxidative stress were down-regulated. Furthermore, treatment of BMSCs by rIHH increased their anti-inflammatory effects.More importantly, knockdown of IHH decreased the ability of TL1A-stimulated BMSCs to alleviating the inflammation in RA-FLSs and T cells. Conclusions This study reports the effects of TL1A/TNFR2 pathway on the biological behaviors and therapeutic potency of BMSCs through IHH. These findings could introduce novel procedures to increase the stemness of MSCs in cellular therapy.

This systematic review evaluates current evidence regarding the feasibility of using needleless jet injection instead of a conventional local anesthetic needle. EBSCO, ProQuest, PubMed, and Scopus databases were used to identify relevant literature published in English from 2005 to 2020. Ten studies were selected. Five of them were randomized clinical trials, 3 case-control studies, and 2 equivalence trials. Using the Critical Appraisal Skills Program checklist, 6 studies scored between 67% and 100%, and 4 studies scored between 34% and 66%. According to Jadad’s scale, 2 studies were considered strong, and 8 studies were considered moderate in quality. The results of the 10 studies showed differences in patient preference for needleless jet injection. Needleless injection technique has been found to be particularly useful in uncooperative patients with anxiety and needle phobia.Needleless jet injection is not technique sensitive. However, with needleless jet anesthesia, most treatments require additional anesthesia. Conventional needle anesthesia is less costly, has a longer duration of action, and has better pain control during dental extraction. Needleless jet anesthesia has been shown to be moderately accepted by patients with a fear of needles, has a faster onset of action, and is an efficient alternative to conventional infiltration anesthesia technique.

Purpose: Artificial intelligence (AI) is poised to play a major role in medical diagnostics. Periodontal disease is one of the most common oral diseases. The early diagnosis of periodontal disease is essential for effective treatment and a favorable prognosis. This study aimed to assess the effectiveness of AI in diagnosing periodontal bone loss through radiographic analysis. Materials and Methods: A literature search involving 5 databases (PubMed, ScienceDirect, Scopus, Health and Medical Collection, Dentistry and Oral Sciences) was carried out. A specific combination of keywords was used to obtain the articles. The PRISMA guidelines were used to filter eligible articles. The study design, sample size, type ofAI software, and the results of each eligible study were analyzed. The CASP diagnostic study checklist was used to evaluate the evidence strength score. Results: Seven articles were eligible for review according to the PRISMA guidelines. Out of the 7 eligible studies, 4 had strong CASP evidence strength scores (7-8/9). The remaining studies had intermediate CASP evidence strength scores (3.5-6.5/9). The highest area under the curve among the reported studies was 94%, the highest F1 score was91%, and the highest specificity and sensitivity were 98.1% and 94%, respectively. Conclusion AI-based detection of periodontal bone loss using radiographs is an efficient method. However, more clinical studies need to be conducted before this method is introduced into routine dental practice.