Osteoporosis is becoming a global health issue due to increased life expectancy. However, it is difficult to detect in its early stages owing to a lack of discernible symptoms. Hence, screening for ...osteoporosis with widely used dental panoramic radiographs would be very cost-effective and useful. In this study, we investigate the use of deep learning to classify osteoporosis from dental panoramic radiographs. In addition, the effect of adding clinical covariate data to the radiographic images on the identification performance was assessed. For objective labeling, a dataset containing 778 images was collected from patients who underwent both skeletal-bone-mineral density measurement and dental panoramic radiography at a single general hospital between 2014 and 2020. Osteoporosis was assessed from the dental panoramic radiographs using convolutional neural network (CNN) models, including EfficientNet-b0, -b3, and -b7 and ResNet-18, -50, and -152. An ensemble model was also constructed with clinical covariates added to each CNN. The ensemble model exhibited improved performance on all metrics for all CNNs, especially accuracy and AUC. The results show that deep learning using CNN can accurately classify osteoporosis from dental panoramic radiographs. Furthermore, it was shown that the accuracy can be improved using an ensemble model with patient covariates.
Pell and Gregory, and Winter's classifications are frequently implemented to classify the mandibular third molars and are crucial for safe tooth extraction. This study aimed to evaluate the ...classification accuracy of convolutional neural network (CNN) deep learning models using cropped panoramic radiographs based on these classifications. We compared the diagnostic accuracy of single-task and multi-task learning after labeling 1330 images of mandibular third molars from digital radiographs taken at the Department of Oral and Maxillofacial Surgery at a general hospital (2014-2021). The mandibular third molar classifications were analyzed using a VGG 16 model of a CNN. We statistically evaluated performance metrics accuracy, precision, recall, F1 score, and area under the curve (AUC) for each prediction. We found that single-task learning was superior to multi-task learning (all p < 0.05) for all metrics, with large effect sizes and low p-values. Recall and F1 scores for position classification showed medium effect sizes in single and multi-task learning. To our knowledge, this is the first deep learning study to examine single-task and multi-task learning for the classification of mandibular third molars. Our results demonstrated the efficacy of implementing Pell and Gregory, and Winter's classifications for specific respective tasks.
The Wnt/β‐catenin signaling and TGFβ signaling pathways play a key role in osteoblast differentiation. The miRNAs play important roles in regulating gene expression at the post‐transcriptional level ...through fine‐tuning of protein‐encoding gene expression. However, involvement of miRNAs is not established for Wnt3a and TGFβ signaling pathways in osteoblast differentiation. Here, we examined the role of miRNAs expressed differentially after Wnt3a expression during osteoblast differentiation. Over‐expression of the Wnt3a gene increased ALP transcription, but decreased Col1, Runx2, and OCN transcription in osteoblastic MC3T3‐E1 cells. Expression profiling and quantitative PCR for miRNAs showed that miR‐140‐3p decreased in Wnt3a‐over‐expressing osteoblastic cells. Wnt3a over‐expression increased TGFβ3 expression, whereas transfection of the miR‐140‐3p mimic into MC3T3‐E1 cells significantly inhibited TGFβ3 expression. Luciferase assay for the TGFβ3 transcript showed that TGFβ3 was a direct target of miR‐140‐3p. miR‐140‐3p mimic transfection resulted in significantly increased OCN transcription, but did not affect ALP, Col1, and Runx2 transcription in MC3T3‐E1 cells. rTGFβ3 treatment decreased OCN transcription in MC3T3‐E1 cells. These results suggest that the miR‐140‐3p is involved in osteoblast differentiation as a critical regulatory factor between Wnt3a and TGFβ3 signaling pathways.
The Wnt/β‐catenin signaling and TGFβ signaling pathways play a key role in osteoblast differentiation. The miRNAs play important roles in regulating gene expression at the post‐transcriptional level through fine‐tuning of protein‐encoding gene expression. However, involvement of miRNAs is not established for Wnt3a and TGFβ signaling pathways in osteoblast differentiation. Here, we examined the role of miRNAs expressed differentially after Wnt3a expression during osteoblast differentiation. Over‐expression of the Wnt3a gene increased ALP transcription, but decreased Col1, Runx2, and OCN transcription in osteoblastic MC3T3‐E1 cells. Expression profiling and quantitative PCR for miRNAs showed that miR‐140‐3p decreased in Wnt3a‐over‐expressing osteoblastic cells. Wnt3a over‐expression increased TGFβ3 expression, whereas transfection of the miR‐140‐3p mimic into MC3T3‐E1 cells significantly inhibited TGFβ3 expression. Luciferase assay for the TGFβ3 transcript showed that TGFβ3 was a direct target of miR‐140‐3p. miR‐140‐3p mimic transfection resulted in significantly increased OCN transcription, but did not affect ALP, Col1, and Runx2 transcription in MC3T3‐E1 cells. rTGFβ3 treatment decreased OCN transcription in MC3T3‐E1 cells. These results suggest that the miR‐140‐3p is involved in osteoblast differentiation as a critical regulatory factor between Wnt3a and TGFβ3 signaling pathways.
Outer membrane vesicles (OMVs) are nanosized particles derived from the outer membrane of gram-negative bacteria. Oral bacterium Porphyromonas gingivalis (Pg) is known to be a major pathogen of ...periodontitis that contributes to the progression of periodontal disease by releasing OMVs. The effect of Pg OMVs on systemic diseases is still unknown. To verify whether Pg OMVs affect the progress of diabetes mellitus, we analyzed the cargo proteins of vesicles and evaluated their effect on hepatic glucose metabolism. Here, we show that Pg OMVs were equipped with Pg-derived proteases gingipains and translocated to the liver in mice. In these mice, the hepatic glycogen synthesis in response to insulin was decreased, and thus high blood glucose levels were maintained. Pg OMVs also attenuated the insulin-induced Akt/glycogen synthase kinase-3 β (GSK-3β) signaling in a gingipain-dependent fashion in hepatic HepG2 cells. These results suggest that the delivery of gingipains mediated by Pg OMV elicits changes in glucose metabolisms in the liver and contributes to the progression of diabetes mellitus.
•P. gingivalis (Pg) releases outer membrane vesicles (OMVs) containing gingipains.•Pg OMVs were transferred to the mouse liver, where gingipains were also detected.•Pg OMVs increased blood glucose levels by decreasing hepatic glycogen synthesis.•Pg OMVs attenuated the insulin signaling in a gingipain-dependent fashion in HepG2.•Pg OMVs may contribute to diabetes mellitus by delivering gingipains to the liver.
For doctors and other medical staff treating oral cancer, it is necessary to standardize the basic concepts and rules for oral cancer to achieve progress in its treatment, research, and diagnosis. ...Oral cancer is an integral part of head and neck cancer and is treated in accordance with the general rules for head and neck cancer. However, detailed rules based on the specific characteristics of oral cancer are essential. The objective of this article was to contribute to the development of the diagnosis, treatment, and research of oral cancer, based on the correct and useful medical information of clinical, surgical, pathological, and imaging findings accumulated from individual patients at various institutions. Our general rules were revised as the UICC was revised for the 8th edition and were published as the Japanese second edition in 2019. In this paper, the English edition of the “Rules” section is primarily presented.
In this study, the accuracy of the positional relationship of the contact between the inferior alveolar canal and mandibular third molar was evaluated using deep learning. In contact analysis, we ...investigated the diagnostic performance of the presence or absence of contact between the mandibular third molar and inferior alveolar canal. We also evaluated the diagnostic performance of bone continuity diagnosed based on computed tomography as a continuity analysis. A dataset of 1279 images of mandibular third molars from digital radiographs taken at the Department of Oral and Maxillofacial Surgery at a general hospital (2014-2021) was used for the validation. The deep learning models were ResNet50 and ResNet50v2, with stochastic gradient descent and sharpness-aware minimization (SAM) as optimizers. The performance metrics were accuracy, precision, recall, specificity, F1 score, and area under the receiver operating characteristic curve (AUC). The results indicated that ResNet50v2 using SAM performed excellently in the contact and continuity analyses. The accuracy and AUC were 0.860 and 0.890 for the contact analyses and 0.766 and 0.843 for the continuity analyses. In the contact analysis, SAM and the deep learning model performed effectively. However, in the continuity analysis, none of the deep learning models demonstrated significant classification performance.
This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective ...labeling, we collected a dataset containing 1131 images from patients who underwent both skeletal bone mineral density measurement and hip radiography at a single general hospital between 2014 and 2019. Osteoporosis was assessed from the hip radiographs using five convolutional neural network (CNN) models. We also investigated ensemble models with clinical covariates added to each CNN. The accuracy, precision, recall, specificity, negative predictive value (npv), F1 score, and area under the curve (AUC) score were calculated for each network. In the evaluation of the five CNN models using only hip radiographs, GoogleNet and EfficientNet b3 exhibited the best accuracy, precision, and specificity. Among the five ensemble models, EfficientNet b3 exhibited the best accuracy, recall, npv, F1 score, and AUC score when patient variables were included. The CNN models diagnosed osteoporosis from hip radiographs with high accuracy, and their performance improved further with the addition of clinical covariates from patient records.
The importance of macrophages in tissue development and regeneration has been strongly emphasized. However, the specific roles of macrophage colony-stimulating factor (MCSF), the key regulator of ...macrophage differentiation, in glandular tissue development have been unexplored. Here, we disclose new macrophage-independent roles of MCSF in tissue development. We initially found that MCSF is markedly upregulated at embryonic day (E)13.5, at a stage preceding the colonization of macrophages (at E15.5), in mouse submandibular gland (SMG) tissue. Surprisingly, MCSF-induced branching morphogenesis was based on a direct effect on epithelial cells, as well as indirectly, by modulating the expression of major growth factors of SMG growth, FGF7 and FGF10, via the phosphoinositide 3-kinase (PI3K) pathway. Additionally, given the importance of neurons in SMG organogenesis, we found that MCSF-induced SMG growth was associated with regulation of neurturin expression and neuronal network development during early SMG development in an
organogenesis model as well as
These results indicate that MCSF plays pleiotropic roles and is an important regulator of early SMG morphogenesis.
Recently, attention has been focused on the role of hyperpolarization-activated cyclic nucleotide-gated (HCN) channels in the mechanism of and as a treatment target for neuropathic and inflammatory ...pain. Ivabradine, a blocker of HCN channels, was demonstrated to have an effect on neuropathic pain in an animal model. Therefore, in the present study, we evaluated the effect of ivabradine on inflammatory pain, and under the hypothesis that ivabradine can directly influence inflammatory responses, we investigated its effect in in vivo and in vitro studies.
After approval from our institution, we studied male Sprague-Dawley rats aged 8 weeks. Peripheral inflammation was induced by the subcutaneous injection of carrageenan into the hindpaw of rats. The paw-withdrawal threshold (pain threshold) was evaluated by applying mechanical stimulation to the injected site with von Frey filaments. Ivabradine was subcutaneously injected, combined with carrageenan, and its effect on the pain threshold was evaluated. In addition, we evaluated the effects of ivabradine on the accumulation of leukocytes and TNF-alpha expression in the injected area of rats. Furthermore, we investigated the effects of ivabradine on LPS-stimulated production of TNF-alpha in incubated mouse macrophage-like cells.
The addition of ivabradine to carrageenan increased the pain threshold lowered by carrageenan injection. Both lamotrigine and forskolin, activators of HCN channels, significantly reversed the inhibitory effect of ivabradine on the pain threshold. Ivabradine inhibited the carrageenan-induced accumulation of leukocytes and TNF-alpha expression in the injected area. Furthermore, ivabradine significantly inhibited LPS-stimulated production of TNF-alpha in the incubated cells.
The results of the present study demonstrated that locally injected ivabradine is effective against carrageenan-induced inflammatory pain via HCN channels. Its effect was considered to involve not only an action on peripheral nerves but also an anti-inflammatory effect.
Cancer cachexia causes skeletal muscle atrophy, impacting the treatment and prognosis of patients with advanced cancer, but no treatment has yet been established to control cancer cachexia. We ...demonstrated that transcutaneous application of carbon dioxide (CO2) could improve local blood flow and reduce skeletal muscle atrophy in a fracture model. However, the effects of transcutaneous application of CO2 in cancer-bearing conditions are not yet known. In this study, we calculated fat-free body mass (FFM), defined as the skeletal muscle mass, and evaluated the expression of muscle atrophy markers and uncoupling protein markers as well as the cross-sectional area (CSA) to investigate whether transcutaneous application of CO2 to skeletal muscle could suppress skeletal muscle atrophy in cancer-bearing mice. Human oral squamous cell carcinoma was transplanted subcutaneously into the upper dorsal region of nude mice, and 1 week later, CO2 gas was applied to the legs twice a week for 4 weeks and FFM was calculated by bioimpedance spectroscopy. After the experiment concluded, the quadriceps were extracted, and muscle atrophy markers (muscle atrophy F-box protein (MAFbx), muscle RING-finger protein 1 (MuRF-1)) and uncoupling protein markers (uncoupling protein 2 (UCP2) and uncoupling protein 3 (UCP3)) were evaluated by real-time polymerase chain reaction and immunohistochemical staining, and CSA by hematoxylin and eosin staining. The CO2-treated group exhibited significant mRNA and protein expression inhibition of the four markers. Furthermore, immunohistochemical staining showed decreased MAFbx, MuRF-1, UCP2, and UCP3 in the CO2-treated group. In fact, the CSA in hematoxylin and eosin staining and the FFM revealed significant suppression of skeletal muscle atrophy in the CO2-treated group. We suggest that transcutaneous application of CO2 to skeletal muscle suppresses skeletal muscle atrophy in a mouse model of oral squamous cell carcinoma.
PDF
