Gingivae, as the part of periodontium, are involved in tooth support and possess the ability to heal rapidly, without scar formation. Recently, dental tissues have been identified as a potential source of mesenchymal stem cells (MSCs) and several populations of MSCs were isolated from the orofacial region, including gingival mesenchymal stem cells (GMSCs). GMSCs exhibit robust immunomodulatory and differentiation potential and are easily obtainable, which make them promising candidates for cellular therapies. Apart from being tested for application in immunologic- and inflammatory-related disorders and various tissue regeneration, GMSCs promise to be a valuable tool in cancer treatment, especially in tongue squamous cell carcinoma (TSCC) with the use of targeted therapy, since GMSCs are able to selectively migrate towards the cancerous cells both in vitro and in vivo. In addition to their ability to uptake and release anti-neoplastic drugs, GMSCs may be transduced with apoptosis-inducing factors and used for cancer growth inhibition. Moreover, GMSCs, as most mammalian cells, secrete exosomes, which are a subset of extracellular vesicles with a diameter of 40–160 nm, containing DNA, RNA, lipids, metabolites, and proteins. Such GMSCs-derived exosomes may be useful therapeutic tool in cell-free therapy, as well as their culture medium. GMSCs exhibit molecular and stem-cell properties that make them well suited in preclinical and clinical studies.

The oral mucosal tissue is a compound structure composed of morphologically and physiologically different cell types. The morphological modification involves genetically determined lifespan, which may be recognized as the balance between cell survival and apoptosis. Although the biochemical processes and pathways in oral mucosa, with special regards to drug transport, delivery, and metabolism, are well known, the cellular physiological homeostasis in this tissue requires further investigation. The porcine buccal pouch mucosal cells (BPMCs) collected from 20 pubertal crossbred Landrace gilts, were used in this study. Immediately after recovery, the oral mucosa was separated micro-surgically, and treated enzymatically. The dispersed cells were transferred into primary in vitro culture systems for a long-term cultivation of 30 days. After each step of in vitro culture (IVC), the cells were collected for isolation of total RNA at 24 h, 7, 15, and 30 days of IVC. While the expression was analyzed for days 7, 15, and 30, the 24th hour was used as a reference for outcome calibration. The gene expression profile was determined using Affymetrix microarray assays and necessary procedures. In results, we observed significant up-regulation of SCARB1, PTGS2, DUSP5, ITGB3, PLK2, CCL2, TGFB1, CCL8, RFC4, LYN, ETS1, REL, LIF, SPP1, and FGER1G genes, belonging to two ontological groups, namely “positive regulation of metabolic process”, and “regulation of homeostatic process” at 7 day of IVC as compared to down-regulation at days 15 and 30. These findings suggest that the metabolic processes and homeostatic regulations are much more intense in porcine mucosal cells at day 7 of IVC. Moreover, the increased expression of marker genes, for both of these ontological groups, may suggest the existence of not only “morphological lifespan” during tissue keratinization, but also “physiological checkpoint” dedicated to metabolic processes in oral mucosa. This knowledge may be useful for preclinical experiments with drugs delivery and metabolism in both animals and humans.

The aim of the study was to compare erupted permanent bovine teeth of two types involved in the process of chewing in respect to the localisation and histomorphometric characteristics of enamel tufts. The research material comprised 240 fully erupted premolars and molars from the maxillae and mandibles of 27 heads of cattle from the Polish Black-and-White breed. Overall, 1,986 specimens of bovine teeth were analysed using a Nikon Eclipse E600 microscope with Micro Image v4.0 software. Enamel tufts were relatively numerous in the enamel of smooth surfaces - on average from 5.6 to 6.4 per cross-section of tooth crown. The average length of the enamel tufts expressed by means of a median was smaller for premolars (89.3 μm) than for molars (123.9 μm). The analysis of the value of Spearman's rank correlation coefficient revealed that no relationship existed between the length and width of tufts in molars (r_s =0.26), and a low-level relationship was noted (r_s =0.45) in premolars. On the basis of the Mann-Whitney U test for the metric measurements, no significant differences were discovered for the width of enamel tufts (P=0.427), but significant differences were observed for the length of enamel tufts (P=0.032). The observed differences in the histological structure of the enamel of posterior bovine teeth in comparison to human teeth indicate that a certain degree of caution ought to be considered when using bovine teeth as a substitute for human teeth in in vitro trials.

Intracranial calcifications, particularly within the falx cerebri, serve as crucial diagnostic markers ranging from benign accumulations to signs of severe pathologies. The falx cerebri, a dural fold that separates the cerebral hemispheres, presents challenges in visualization due to its low contrast in standard imaging techniques. Recent advancements in artificial intelligence (AI), particularly in machine learning and deep learning, have significantly transformed radiological diagnostics. This study aims to explore the application of AI in the segmentation and detection of falx cerebri calcifications using Cone-Beam Computed Tomography (CBCT) images through a comprehensive literature review and a detailed case report. The case report presents a 59-year-old patient diagnosed with falx cerebri calcifications whose CBCT images were analyzed using a cloud-based AI platform, demonstrating effectiveness in segmenting these calcifications, although challenges persist in distinguishing these from other cranial structures. A specific search strategy was employed to search electronic databases, yielding four studies exploring AI-based segmentation of the falx cerebri. The review detailed various AI models and their accuracy across different imaging modalities in identifying and segmenting falx cerebri calcifications, also highlighting the gap in publications in this area. In conclusion, further research is needed to improve AI-driven methods for accurately identifying and measuring intracranial calcifications. Advancing AI applications in radiology, particularly for detecting falx cerebri calcifications, could significantly enhance diagnostic precision, support disease monitoring, and inform treatment planning.