Background: It is estimated that up to 90% of head and neck infections have an odontogenic origin, which are considered among the most common in the oral cavity and maxillofacial region. Bacterial resistance has been 1 of the main problems related to the treatment of this type of infection in recent years. The frequency of this resistance is increasing, which is mainly due to patient self-medication and the mutations that bacteria present. Therefore, the objective of this study is to analyze the antimicrobial resistance of antibiotics commonly administered for the treatment of odontogenic infections. Method: To carry out the study, PubMed, ScienceDirect, and Scopus databases were reviewed using the keywords “odontogenic infection”, “pharmacological treatment”, and “microbial resistance. Studies whose main objective was the pharmacological treatment of odontogenic infections were selected. Exclusions were review-type studies, systematic reviews, or in vitro or animal model studies. For the analysis of risk of bias, the Checklist for Analytical Cross-Sectional Studies of the Joanna Briggs Institute was used. The search and analysis of the studies was carried out by 2 researchers independently. Results: A total of 13 studies were included in this review. The mean age was 39.6 years; the location of the infection in the study subjects was in the submandibular and vestibular spaces; there were periodontal, periapical, and dentoalveolar lesions; the main microorganisms identified were Streptococcus, Staphylococcus, Prevotella, Peptostreptococcus, Clostridium, and Klebsiella; and finally, the main microorganisms identified for bacterial resistance were penicillin, clindamycin and amoxicillin. Conclusion: The health professional is obliged to update their knowledge to avoid such antibiotic resistance and thus provide better patient care.

Introduction. Periodontal disease (PD) is a chronic inflammation of the soft tissues that support the structure of the tooth, and miRNAs are highly dynamic molecules that participate in the regulation of gene expression interfering with multiple genetic targets. The dysregulation of the expression of miRNAs has been associated with different types of pathologies; therefore, they are excellent molecules to be studied as biomarkers. Material and Methods. A search was made in the electronic databases of PubMed, Scopus, and Science Direct. The following key words were used: “microRNAs,” “miRNAs,” “periodontal disease,” “periodontitis,” and “biomarker”; employee independent search strategies with the Boolean operators “OR” and “AND”; a further search of the references of the selected studies was performed to detect potential studies that met the selection criteria. The data recollected from each article were author, country, year of publication, sample size, type of sample used to identify miRNAs, methodology used to identify miRNAs, type of periodontal disease, and miRNAs identified. Results. Of the 13 selected studies, 6 used gingival tissue as a sample for the identification of miRNAs, 3 used gingival fluid, 2 used saliva, 1 used serum, and another used periodontal tissue. Chronic periodontitis was the most studied periodontal disease in 9 of the 13 selected articles; 7 used microarrays as the main technique for the identification of miRNAs. qRT‐PCR was the assay choice to validate the identified miRNAs. Conclusion. The main type of periodontal disease on which most studies are focused is chronic periodontitis, with the main miRNAs being hsa‐miR‐146a, hsa‐miR‐146b, hsa‐miR‐155, and hsa‐miR‐200. This systematic review is one of the first to carry out an analysis of the current role of miRNAs in PD as biomarkers.

A biomarker is defined as a characteristic that is measured as an indicator of a normal biological or pathological process, a response to an exposure or intervention. Biomarkers with a diagnostic approach must identify not only the presence but also the absence of the disease with high precision, so having the biological source of the said marker is of vital importance to ensure precision and accuracy; the aim was to carry out a review of its diagnostic potential. The search strategy was carried out in three databases: PubMed, ScienceDirect, and Scopus. The keywords that were used were as follows: “gingival crevicular fluid”, “Biomarker”, and “Diagnosis”, using the Boolean operator “AND”. The filter was used at 10 years. Within the type of molecules most studied, the cytokine family was the most abundant with 25.42% of the studies, followed by metalloproteinases and proteins with 16.9% each one. Studies that included RNA‐type genetic material were less frequently found. As has been demonstrated, the use of GCF as a source of biomolecules for diagnostic use has been increasing, both for oral diseases, which reflects the local conditions of the disease; it also has the ability to reflect the development of distant diseases; and this is because GCF is a blood ultrafiltrate.

To evaluate a predictive model of microalbuminuria by using anthropometric, clinical and genetic variables in relatives of subjects with diabetic nephropathy.