Microbial Profiles in Oral Lichen Planus: Comparisons with Healthy Controls and Erosive vs. Non-Erosive Subtypes.

Recent studies have begun exploring the potential involvement of microbiota in the pathogenesis of oral lichen planus (OLP), yet comprehensive investigations remain limited. Hence, this study aimed to compare the microbial profiles in saliva samples obtained from patients with OLP against those from healthy controls (HC), along with a comparison between erosive (E) and non-erosive (NE) OLP patients. Saliva samples were collected from 60 OLP patients (E: n = 25, NE: n = 35) and 30 HC individuals. Analysis revealed no significant differences in alpha diversity, as assessed by the Chao1 and Shannon index, across the three groups. However, Bray-Curtis distance analysis indicated a significant disparity in microbiome composition distribution between HC and E-OLP, as well as HC and NE-OLP groups. The six most abundant phyla observed across the groups were Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, Fusobacteria, and Saccharibacteria (TM7). Notably, OLP groups exhibited a higher prevalence of Bacteroidetes. Prevotella emerged as the predominant genus in the OLP groups, while Capnocytophaga showed a relatively higher prevalence in E-OLP compared to NE-OLP. This study's findings indicate a notable difference in microbiota composition between HC and patients with OLP. Additionally, differences in the microbiome were identified between the E-OLP and NE-OLP groups. The increase in the proportion of certain bacterial species in the oral microbiome suggests that they may exacerbate the inflammatory response and act as antigens for OLP.

Graph Neural Network Model for Prediction of Non-Small Cell Lung Cancer Lymph Node Metastasis Using Protein-Protein Interaction Network and 18F-FDG PET/CT Radiomics.

The image texture features obtained from 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) images of non-small cell lung cancer (NSCLC) have revealed tumor heterogeneity. A combination of genomic data and radiomics may improve the prediction of tumor prognosis. This study aimed to predict NSCLC metastasis using a graph neural network (GNN) obtained by combining a protein-protein interaction (PPI) network based on gene expression data and image texture features. 18F-FDG PET/CT images and RNA sequencing data of 93 patients with NSCLC were acquired from The Cancer Imaging Archive. Image texture features were extracted from 18F-FDG PET/CT images and area under the curve receiver operating characteristic curve (AUC) of each image feature was calculated. Weighted gene co-expression network analysis (WGCNA) was used to construct gene modules, followed by functional enrichment analysis and identification of differentially expressed genes. The PPI of each gene module and genes belonging to metastasis-related processes were converted via a graph attention network. Images and genomic features were concatenated. The GNN model using PPI modules from WGCNA and metastasis-related functions combined with image texture features was evaluated quantitatively. Fifty-five image texture features were extracted from 18F-FDG PET/CT, and radiomic features were selected based on AUC (n = 10). Eighty-six gene modules were clustered by WGCNA. Genes (n = 19) enriched in the metastasis-related pathways were filtered using DEG analysis. The accuracy of the PPI network, derived from WGCNA modules and metastasis-related genes, improved from 0.4795 to 0.5830 (p < 2.75 × 10-12). Integrating PPI of four metastasis-related genes with 18F-FDG PET/CT image features in a GNN model elevated its accuracy over a without image feature model to 0.8545 (95% CI = 0.8401-0.8689, p-value < 0.02). This model demonstrated significant enhancement compared to the model using PPI and 18F-FDG PET/CT derived from WGCNA (p-value < 0.02), underscoring the critical role of metastasis-related genes in prediction model. The enhanced predictive capability of the lymph node metastasis prediction GNN model for NSCLC, achieved through the integration of comprehensive image features with genomic data, demonstrates promise for clinical implementation.

Prediction of Neoadjuvant Chemoradiotherapy Response in Rectal Cancer Patients Using Harmonized Radiomics of Multcenter 18F-FDG-PET Image.

We developed machine and deep learning models to predict chemoradiotherapy in rectal cancer using 18F-FDG PET images and harmonized image features extracted from 18F-FDG PET/CT images. Patients diagnosed with pathologic T-stage III rectal cancer with a tumor size > 2 cm were treated with neoadjuvant chemoradiotherapy. Patients with rectal cancer were divided into an internal dataset (n = 116) and an external dataset obtained from a separate institution (n = 40), which were used in the model. AUC was calculated to select image features associated with radiochemotherapy response. In the external test, the machine-learning signature extracted from 18F-FDG PET image features achieved the highest accuracy and AUC value of 0.875 and 0.896. The harmonized first-order radiomics model had a higher efficiency with accuracy and an AUC of 0.771 than the second-order model in the external test. The deep learning model using the balanced dataset showed an accuracy of 0.867 in the internal test but an accuracy of 0.557 in the external test. Deep-learning models using 18F-FDG PET images must be harmonized to demonstrate reproducibility with external data. Harmonized 18F-FDG PET image features as an element of machine learning could help predict chemoradiotherapy responses in external tests with reproducibility.

A Comparison of the Condyle and Articular Eminence in Asian Juvenile Idiopathic Osteoarthritis Patients with Unilateral and Bilateral TMJ Involvement: A Retrospective Case-Control Study.

This study compared the condylar volume, length, and articular eminence (AE) characteristics of normal individuals to those with unilateral and bilateral juvenile idiopathic osteoarthritis (JOA). The 116 patients were divided into four groups: Control (n = 16), affected condyle of unilateral JOA (Aff-Uni) (n = 36), non-affected condyle of JOA (NonAff-uni) (n = 36), and bilateral JOA (Bilateral) (n = 28). The differences in condyle volume and length and AE were analyzed using ANOVA and Bonferroni post-hoc tests. The results showed that Bilateral had a significantly different condylar volume, especially in the condylar head (p < 0.01), specifically the middle, anterior, and medial parts (p < 0.05). Condylar length also differed among the groups, with differences observed between the control group and the other three groups, as well as between the bilateral group and the other three groups (p < 0.01). AE total volume differed between the control group and Aff-Uni. In the detailed comparison, Aff-Uni and NonAff-Uni were smaller than the control group in the posterior, lateral, and medial sections (p < 0.05). In conclusion, depending on the involvement of unilateral or bilateral JOA, there were differences in condylar volume and AE when compared to the normal control group. Therefore, a prognosis should be evaluated by distinguishing between patients with unilateral and bilateral JOA.

Establishment of quantitative indicators for an efficient treatment on masticatory muscle pain.

BACKGROUND: Although several studies have investigated effective treatments for masticatory muscle pain (MMP), no unified conclusion has been drawn regarding the effectiveness of these treatments. OBJECTIVES: This study aimed to define quantitative indicators for predicting the outcome of MMP treatment. MATERIALS AND METHODS: In total, patients aged 20-70 years were recruited and divided into the MMP (n = 24) and control (n = 36) groups, based on the presence of MMP according to the Diagnostic Criteria for Temporomandibular Disorders. At pretreatment, the MMP group was assessed using quantitative indicators such as subjective pain levels, pain duration, graded chronic pain scale (GCPS), and perceived stress scale (PSS). Salivary alpha-amylase (sAA) and interleukin-6 (IL-6) levels were analyzed. The masticatory muscle palpation score and the range of mouth opening were measured. At posttreatment, subjective pain levels, mouth opening, and treatment/medication duration were examined. The PSS and sAA levels were assessed in the control group. RESULTS: sAA levels in the MMP group were significantly higher than those in the control group (p < .05). The masseter muscle palpation score (MPS) showed a positive correlation with IL-6 levels (ρ = 0.503, p < .05) and a negative correlation with nonsteroidal anti-inflammatory drug (NSAID) treatment period (ρ = -0.462, p < .05). The temporalis muscle palpation score (TPS) was positively correlated with pain duration and GCPS grade (ρ = 0.483, p < .05, and ρ = 0.445, p < .05, respectively). CONCLUSIONS: Treatment with NSAIDs was effective in the MMP group with high MPS and IL-6 levels, but not in the MMP group with high TPS, pain duration, and GCPS grade.

Nanomaterials for antigen-specific immune tolerance therapy.

Impairment of immune tolerance might cause autologous tissue damage or overactive immune response against non-pathogenic molecules. Although autoimmune disease and allergy have complicated pathologies, the current strategies have mainly focused on symptom amelioration or systemic immunosuppression which can lead to fatal adverse events. The induction of antigen-specific immune tolerance may provide therapeutic benefits to autoimmune disease and allergic response, while reducing nonspecific immune adverse responses. Diverse nanomaterials have been studied to induce antigen-specific immune tolerance therapy. This review will cover the immunological background of antigen-specific tolerance, clinical importance of antigen-specific immune tolerance, and nanomaterials designed for autoimmune and allergic diseases. As nanomaterials for modulating immune tolerances, lipid-based nanoparticles, polymeric nanoparticles, and biological carriers have been covered. Strategies to provide antigen-specific immune tolerance have been addressed. Finally, current challenges and perspectives of nanomaterials for antigen-specific immune tolerance therapy will be discussed.

Lipid nanoparticle-mediated CRISPR/Cas9 gene editing and metabolic engineering for anticancer immunotherapy.

Metabolic engineering of the tumor microenvironment has emerged as a new strategy. Lactate dehydrogenase A (LDHA) is a prominent target for metabolic engineering. Here, we designed a cationic lipid nanoparticle formulation for LDHA gene editing. The plasmid DNA delivery efficiency of our lipid nanoparticle formulations was screened by testing the fluorescence of lipid nanoparticles complexed to plasmid DNA encoding green fluorescence protein (GFP). The delivery efficiency was affected by the ratios of three components: a cationic lipid, cholesterol or its derivative, and a fusogenic lipid. The lipid nanoparticle designated formulation F3 was complexed to plasmid DNA co-encoding CRISPR-associated protein 9 and LDHA-specific sgRNA, yielding the lipoplex, pCas9-sgLDHA/F3. The lipoplex including GFP-encoding plasmid DNA provided gene editing in HeLa-GFP cells. Treatment of B16F10 tumor cells with pCas9-sgLDHA/F3 yielded editing of the LDHA gene and increased the pH of the culture medium. pCas9-sgLDHA/F3 treatment activated the interferon-gamma and granzyme production of T cells in culture. In vivo, combining pCas9-sgLDHA/F3 with immune checkpoint-inhibiting anti-PD-L1 antibody provided a synergistic antitumor effect and prolonged the survival of tumor model mice. This study suggests that combining metabolic engineering of the tumor microenvironment with immune checkpoint inhibition could be a valuable antitumor strategy.

Prediction of anterior open-bite development after stabilization splint treatment in patients with temporomandibular disorder.

OBJECTIVE: To assess the dentoskeletal factors of patients with temporomandibular disorders (TMDs) that can predict anterior open-bite development after stabilization splint treatment (ST). METHODS: Eighty-seven TMD patients were classified into three groups according to the degree of overbite changes after ST. Statistically significant differences in dental and skeletal measurements before ST among the groups were investigated. RESULTS: Pre-ST dental and skeletal measurements that were significantly different among the groups were upper central incisor (U1) to point A-pogonion (A-Pog), facial height ratio (FHR), A point-nasion-B point angle (ANB), Wits appraisal, ramus height, angle of convexity, and sella to condylion. Among these factors, FHR, ramus height, and sella to condylion had a positive relationship with overbite changes. DISCUSSION: Dentoskeletal factors, i.e., FHR, ramus height, and sella to condylion, can predict anterior open-bite development after ST in TMD patients.

Candida Infection Associated with Salivary Gland-A Narrative Review.

Candida species are common global opportunistic pathogens that could repeatedly and chronically cause oral mucosa infection and create an inflammatory environment, leading to organ dysfunction. Oral Candida infections may cause temporary or permanent damage to salivary glands, resulting in the destruction of acinar cells and the formation of scar tissue. Restricted function of the salivary glands leads to discomfort and diseases of the oral mucosa, such as dry mouth and associated infection. This narrative review attempts to summarize the anatomy and function of salivary glands, the associations between Candida and saliva, the effects of Candida infection on salivary glands, and the treatment strategies. Overall, clinicians should proactively manage Candida infections by educating patients on oral hygiene management for vulnerable populations, conducting frequent checks for a timely diagnosis, and providing an effective treatment plan.

Characteristics of patients who perceive dental treatment as a cause of oral mucosal lesions.

This retrospective study aims to investigate the proportion and characteristics of patients who perceive dental treatment (DT) as a cause of oral mucosal lesions (OMLs). A total of 2,302 patients with OMLs visited the Oral Medicine Department of Pusan National University Dental Hospital. The patients were divided into a study group (280 patients who perceived DT as a cause of OMLs) and a control group (300 randomly selected patients). Percentages of DT types, clinical characteristics, and the frequencies of diagnoses and chief complaint (CC) sites were analyzed in both groups. Among the patients with OMLs, 12.2% attributed OMLs to DT. Among the diagnoses, allergic reaction (AR) and traumatic ulcer/irritation (TU) were significantly more frequent in the study group. The DT types most frequently perceived as the cause of OMLs were implants. According to patients, TU and candida occurred most frequently following denture placement (68-79%), whereas oral lichen planus and AR occurred most commonly following implant treatment (52-53%). The gingiva was significantly more frequent as the CC site in the study group than in the control group (P < 0.05 for all outcomes). It is important to inform patients of the potential complications of DT and the importance of regular check-ups.