Neighborhood structure-guided brain functional networks estimation for mild cognitive impairment identification.

The adoption and growth of functional magnetic resonance imaging (fMRI) technology, especially through the use of Pearson's correlation (PC) for constructing brain functional networks (BFN), has significantly advanced brain disease diagnostics by uncovering the brain's operational mechanisms and offering biomarkers for early detection. However, the PC always tends to make for a dense BFN, which violates the biological prior. Therefore, in practice, researchers use hard-threshold to remove weak connection edges or introduce l 1-norm as a regularization term to obtain sparse BFNs. However, these approaches neglect the spatial neighborhood information between regions of interest (ROIs), and ROI with closer distances has higher connectivity prospects than ROI with farther distances due to the principle of simple wiring costs in resent studies. Thus, we propose a neighborhood structure-guided BFN estimation method in this article. In detail, we figure the ROIs' Euclidean distances and sort them. Then, we apply the K-nearest neighbor (KNN) to find out the top K neighbors closest to the current ROIs, where each ROI's K neighbors are independent of each other. We establish the connection relationship between the ROIs and these K neighbors and construct the global topology adjacency matrix according to the binary network. Connect ROI nodes with k nearest neighbors using edges to generate an adjacency graph, forming an adjacency matrix. Based on adjacency matrix, PC calculates the correlation coefficient between ROIs connected by edges, and generates the BFN. With the purpose of evaluating the performance of the introduced method, we utilize the estimated BFN for distinguishing individuals with mild cognitive impairment (MCI) from the healthy ones. Experimental outcomes imply this method attains better classification performance than the baselines. Additionally, we compared it with the most commonly used time series methods in deep learning. Results of the performance of K-nearest neighbor-Pearson's correlation (K-PC) has some advantage over deep learning.

Diffusion-weighted MRI at the Late Stage after Radiotherapy for Evaluating Salivary Gland Injury.

OBJECTIVE: Salivary gland injury is the main complication of radiotherapy for nasopharyngeal carcinoma (NPC) patients. The purpose of this study was to evaluate the value of diffusion-weighted magnetic resonance imaging (DW-MRI) as a reliable tool to assess salivary gland function in NPC patients after radiotherapy. MATERIALS AND METHODS: This study analysed the MR images of 31 NPC patients at different time points within 2-3 years after radiotherapy. The changes in the apparent diffusion coefficient (ADC) and its relationship with radiation dose were analysed. RESULTS: Both the parotid and submandibular gland ADC values increased significantly 3-6 months after radiotherapy and then decreased gradually. The ADC value of the parotid gland was positively correlated with radiation dose at the late stage (P = 0.012, r = 0.359). The submandibular gland ADC change value (P = 0.035) and change ratio (P = 0.027) of the high radiation dose group were significantly lower than those of the low dose group at the late stage. CONCLUSION: The correlation between ADC values of parotid and submandibular glands and the radiation dose indicated that DW-MRI could be helpful in evaluating salivary gland injury after radiotherapy.

A case of liposarcoma with osteolysis of the maxilla as the first symptom and review of the literature.

Liposarcomas are extremely rare in the oral cavity and mainly observed in the buccal mucosa, tongue, floor of the mouth, gingiva, and lips, while those occurring in the jaws have not been reported so far. Clinically, the initial presentation of liposarcoma is usually a painless soft tissue mass. The aim of this study was to report a case of liposarcoma with osteolysis of the maxilla as the first symptom, and review the relevant literature to summarize its clinical features, imaging features, pathological features and treatment methods.

Neoadjuvant toripalimab combined with gemcitabine and cisplatin in resectable locally advanced head and neck squamous cell carcinoma (NeoTGP01): An open label, single-arm, phase Ib clinical trial.

BACKGROUND: Neoadjuvant programmed death receptor-1 (PD-1) inhibitors have drawn increasing attention in locally advanced head and neck squamous cell carcinoma (HNSCC). In this study, we investigated the safety and efficacy of gemcitabine and cisplatin (GP), combined with a PD-1 inhibitor, in patients with locally advanced HNSCC. MATERIALS AND METHODS: A total of 23 eligible patients were administered two cycles of toripalimab and GP followed by surgical resection. The primary endpoints were safety, treatment-related adverse events (TRAEs), and non-operation delay rates. The secondary endpoints consisted of pathological complete response (pCR) rate, major pathological response (MPR) rate, objective response rate (ORR), and R0 resection rate. RESULTS: The incidence of TRAEs from grades 1 to 4 was 43.5%, 34.8%, 13.0%, and 8.7%, respectively. Grade 3/4 TRAEs included neutropenia, fatigue, hyperglycemia, nausea and vomiting, decreased appetite, rash, and diarrhea. No treatment-related surgical delay was observed. The radiographic response rates were 5.0% (CR), 40.0% (PR), and 55.0% (SD). The ORR reached 45.0%. Eighteen patients underwent successful surgical resection. The R0 resection rate was 100%. The pathological response rates were 16.7% (pCR), 27.8% (MPR, two of five near-pCR), 16.7% (PPR), and 38.8% (NPR). CD4, CD8, CD20, and CD38 expression in the tumors significantly increased after neoadjuvant chemotherapy. The increase in CD20 levels after neoadjuvant treatment in patients with pCR/MPR was significantly higher than in patients with PPR/NPR. CONCLUSION: Triweekly neoadjuvant toripalimab-GP is feasible and achieves promising pCR and MPR rates in patients with resectable locally advanced HNSCC. TRIAL REGISTRATION: Chinese clinical trial registry, ChiCTR2100043743, Registered 27 Febrary 2021- Retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=120570.

Multimodal fusion diagnosis of depression and anxiety based on CNN-LSTM model.

BACKGROUND: In recent years, more and more people suffer from depression and anxiety. These symptoms are hard to be spotted and can be very dangerous. Currently, the Self-Reported Anxiety Scale (SAS) and Self-Reported Depression Scale (SDS) are commonly used for initial screening for depression and anxiety disorders. However, the information contained in these two scales is limited, while the symptoms of subjects are various and complex, which results in the inconsistency between the questionnaire evaluation results and the clinician's diagnosis results. To fully mine the scale data, we propose a method to extract the features from the facial expression and movements, which are generated from the video recorded simultaneously when subjects fill in the scale. Then we collect the facial expression, movements and scale information to establish a multimodal framework for improving the accuracy and robustness of the diagnosis of depression and anxiety. METHODS: We collect the scale results of the subjects and the videos when filling in the scales. Given the two scales, SAS and SDS, we construct a model with two branches, where each branch processes the multimodal data of SAS and SDS, respectively. In the branch, we first build a convolutional neural network (CNN) to extracts the facial expression features in each frame of images. Secondly, we establish a long short-term memory (LSTM) network to further embedding the facial expression feature and build the connections between various frames, so that the movement feature in the video can be generated. Thirdly, we transform the scale scores into one-hot format, and feed them into the corresponding branch of the network to further mining the information of the multimodal data. Finally, we fuse the embeddings of these two branches to generate inference results of depression and anxiety. RESULTS AND CONCLUSIONS: Based on the score results of SAS and SDS, our multimodal model further mines the video information, and can reach the accuracy of 0.946 in diagnosing depression and anxiety. This study demonstrates the feasibility of using our CNN-LSTM-based multimodal model for initial screening and diagnosis of depression and anxiety disorders with high diagnostic performance.

Interactive short-term effects of meteorological factors and air pollution on hospital admissions for cardiovascular diseases.

A substantial number of studies have demonstrated the association between air pollution and adverse health effects. However, few studies have explored the potential interactive effects between meteorological factors and air pollution. This study attempted to evaluate the interactive effects between meteorological factors (temperature and relative humidity) and air pollution ([Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]) on cardiovascular diseases (CVDs). Next, the high-risk population susceptible to air pollution was identified. We collected daily counts of CVD hospitalizations, air pollution, and weather data in Nanning from January 1, 2014, to December 31, 2015. Generalized additive models (GAMs) with interaction terms were adopted to estimate the interactive effects of air pollution and meteorological factors on CVD after controlling for seasonality, day of the week, and public holidays. On low-temperature days, an increase of [Formula: see text] in [Formula: see text], [Formula: see text], and [Formula: see text] was associated with increases of 4.31% (2.39%, 6.26%) at lag 2; 2.74% (1.65%, 3.84%) at lag 0-2; and 0.13% (0.02%, 0.23%) at lag 0-3 in CVD hospitalizations, respectively. During low relative humidity days, a [Formula: see text] increment of lag 0-3 exposure was associated with increases of 3.43% (4.61%, 2.67%) and 0.10% (0.04%, 0.15%) for [Formula: see text] and [Formula: see text], respectively. On high relative humidity days, an increase of [Formula: see text] in [Formula: see text] was associated with an increase of 5.86% (1.82%, 10.07%) at lag 0-2 in CVD hospitalizations. Moreover, elderly (≥ 65 years) and female patients were vulnerable to the effects of air pollution. There were interactive effects between air pollutants and meteorological factors on CVD hospitalizations. The risk that [Formula: see text], [Formula: see text], and [Formula: see text] posed to CVD hospitalizations could be significantly enhanced by low temperatures. For [Formula: see text] and [Formula: see text], CVD hospitalization risk increased in low relative humidity. The effects of [Formula: see text] were enhanced at high relative humidity.

Rural-urban differences in associations between air pollution and cardiovascular hospital admissions in Guangxi, southwest China.

Epidemiological studies found that exposure to air pollution increases cardiovascular hospitalizations. However, studies on rural-urban differences in associations between hospitalizations for cardiovascular diseases and air pollution are limited. The generalized linear model (GLM) was applied to investigate the associations between cardiovascular hospitalizations and air pollution (SO2, NO2, PM2.5, PM10, CO, and O3) in Guangxi, southwest China, in 2015 (January 1-December 31). The relative risk of pollutants (SO2, NO2) on cardiovascular hospital admissions was significantly different between urban and rural areas. The effect of SO2 on cardiovascular hospitalizations was higher in urban areas than in rural areas at lag0 to lag3 and cumulative lag01 to lag03. In urban areas, there were positive associations between NO2 and cardiovascular hospitalizations at lag0, lag1 and cumulative lag01, lag02. In contrast, the effect of NO2 on cardiovascular hospitalizations was not significant in rural areas. Urban residents were more sensitive than rural residents to SO2 and NO2. Subgroup analyses showed statistically significant differences between rural and urban areas in the association between SO2 and NO2 and cardiovascular hospitalizations for males. For age groups, people aged ≥ 65 years appeared to be more vulnerable to SO2 and NO2 in urban areas. The effects of PM2.5 PM10, CO, and O3 on cardiovascular hospitalizations were consistently negative for all groups. Our findings indicated that there were rural-urban differences in associations between cardiovascular hospitalizations and air pollutants. In rural areas, the risk of cardiovascular hospitalizations was mainly influenced by SO2. Therefore, we expect to pay attention to protecting people from air pollution, particularly for those aged ≥ 65 years in urban areas.

Development and validation of a GRGPI model for predicting the prognostic and treatment outcomes in head and neck squamous cell carcinoma.

Background: Head and neck squamous cell carcinoma (HNSCC) is among the most lethal and most prevalent malignant tumors. Glycolysis affects tumor growth, invasion, chemotherapy resistance, and the tumor microenvironment. Therefore, we aimed at identifying a glycolysis-related prognostic model for HNSCC and to analyze its relationship with tumor immune cell infiltrations. Methods: The mRNA and clinical data were obtained from The Cancer Genome Atlas (TCGA), while glycolysis-related genes were obtained from the Molecular Signature Database (MSigDB). Bioinformatics analysis included Univariate cox and least absolute shrinkage and selection operator (LASSO) analyses to select optimal prognosis-related genes for constructing glycolysis-related gene prognostic index(GRGPI), as well as a nomogram for overall survival (OS) evaluation. GRGPI was validated using the Gene Expression Omnibus (GEO) database. A predictive nomogram was established based on the stepwise multivariate regression model. The immune status of GRGPI-defined subgroups was analyzed, and high and low immune groups were characterized. Prognostic effects of immune checkpoint inhibitor (ICI) treatment and chemotherapy were investigated by Tumor Immune Dysfunction and Exclusion (TIDE) scores and half inhibitory concentration (IC50) value. Reverse transcription-quantitative PCR (RT-qPCR) was utilized to validate the model by analyzing the mRNA expression levels of the prognostic glycolysis-related genes in HNSCC tissues and adjacent non-tumorous tissues. Results: Five glycolysis-related genes were used to construct GRGPI. The GRGPI and the nomogram model exhibited robust validity in prognostic prediction. Clinical correlation analysis revealed positive correlations between the risk score used to construct the GRGPI model and the clinical stage. Immune checkpoint analysis revealed that the risk model was associated with immune checkpoint-related biomarkers. Immune microenvironment and immune status analysis exhibited a strong correlation between risk score and infiltrating immune cells. Gene set enrichment analysis (GSEA) pathway enrichment analysis showed typical immune pathways. Furthermore, the GRGPIdel showed excellent predictive performance in ICI treatment and drug sensitivity analysis. RT-qPCR showed that compared with adjacent non-tumorous tissues, the expressions of five genes were significantly up-regulated in HNSCC tissues. Conclusion: The model we constructed can not only be used as an important indicator for predicting the prognosis of patients but also had an important guiding role for clinical treatment.

Synergistic effects of gaseous pollutants on hospital admissions for cardiovascular disease in Liuzhou, China.

Previous studies demonstrated that short-term exposure to gaseous pollutants (nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3)) had a greater adverse effect on cardiovascular disease. However, little evidence exists regarding the synergy between gaseous pollutants and cardiovascular disease (CVD). Therefore, we aimed to estimate the effect of individual gaseous pollutants on hospital admissions for CVD and to explore the possible synergistic effects between gaseous pollutants. Daily hospitalization counts for CVD were collected from January 1, 2014, to December 31, 2015. We also collected daily time series on gaseous pollutants from the Environment of the People's Republic of China, including NO2, SO2, and O3. We used distributed lag nonlinear models (DLNMs) to assess the association of individual gaseous pollutants on CVD hospitalization, after controlling for seasonality, day of the week, public holidays, and weather variables. Then, we explored the variability across age and sex groups. In addition, we analyzed the synergistic effects between gaseous pollutants on CVD. Extremely low NO2 and SO2 increase the risk of CVD in all subgroup at lag 7 days. The greatest effect of high concentration of SO2 was observed in male and the elderly (≥ 65 years) at lag 3 days. Greater effects of high concentration of O3 were more pronounced in the young (< 65 years) and female at lag 3 days, while the effect of low concentration of O3 was greater in male and the young (< 65 years) at lag 0 day. We found a synergistic effect between NO2 and SO2 for CVD, as well as between SO2 and O3. The synergistic effects of NO2 and SO2 on CVD were stronger in the elderly (≥ 65) and female. The female was sensitive to synergistic effects of SO2-O3 and NO2-O3. Interestingly, we found that there was a risk of CVD in the susceptible population even for gaseous pollutant concentrations below the National Environmental Quality Standard. The synergy between NO2 and SO2 was significantly associated with cardiovascular disease hospitalization in the elderly (≥ 65). This study provides evidence for the synergistic effect of gaseous pollutants on hospital admissions for cardiovascular disease.

Interpreting Depression From Question-Wise Long-Term Video Recording of SDS Evaluation.

Self-Rating Depression Scale (SDS) questionnaire has frequently been used for efficient depression preliminary screening. However, the uncontrollable self-administered measure can be easily affected by insouciantly or deceptively answering, and producing the different results with the clinician-administered Hamilton Depression Rating Scale (HDRS) and the final diagnosis. Clinically, facial expression (FE) and actions play a vital role in clinician-administered evaluation, while FE and action are underexplored for self-administered evaluations. In this work, we collect a novel dataset of 200 subjects to evidence the validity of self-rating questionnaires with their corresponding question-wise video recording. To automatically interpret depression from the SDS evaluation and the paired video, we propose an end-to-end hierarchical framework for the long-term variable-length video, which is also conditioned on the questionnaire results and the answering time. Specifically, we resort to a hierarchical model which utilizes a 3D CNN for local temporal pattern exploration and a redundancy-aware self-attention (RAS) scheme for question-wise global feature aggregation. Targeting for the redundant long-term FE video processing, our RAS is able to effectively exploit the correlations of each video clip within a question set to emphasize the discriminative information and eliminate the redundancy based on feature pair-wise affinity. Then, the question-wise video feature is concatenated with the questionnaire scores for final depression detection. Our thorough evaluations also show the validity of fusing SDS evaluation and its video recording, and the superiority of our framework to the conventional state-of-the-art temporal modeling methods.

DLX6 promotes cell proliferation and survival in oral squamous cell carcinoma.

OBJECTIVE: Distal-less homeobox 6 (DLX6) has been reported to play important roles in the development of craniofacial structures, inner ear, limb, and brain. We found in our previous investigation that DLX6 was significantly highly expressed in oral cancer tissues in The Cancer Genome Atlas database. This study aimed to explore its roles and regulation mechanism in oral squamous cell carcinoma. MATERIALS AND METHODS: We analyzed the expression of DLX6 and its association with overall survival in OSCC by real-time quantitative PCR. Besides, clone formation, proliferation, and apoptosis were detected after knocking down DLX6 and microarray analysis was performed to explore the possible regulatory mechanism. RESULTS: DLX6 was overexpressed in oral cancer tissues and was associated with advance tumor stage and poor prognosis. In vitro studies have shown that DLX6 promotes proliferation and inhibits cell apoptosis in oral cancer cells. Microarray analysis along with Western blotting results indicated that DLX6 significantly associated with malignant tumors and may regulate OSCC cells proliferation through EGFR-CCND1 axis. CONCLUSION: DLX6 promotes cell proliferation and suppresses cell apoptosis in oral cancer cells. EGFR-CCND1 pathway might be the potential mechanism participating in the regulating axis.

Deep 3D-CNN for Depression Diagnosis with Facial Video Recording of Self-Rating Depression Scale Questionnaire.

The Self-Rating Depression Scale (SDS) questionnaire is commonly utilized for effective depression preliminary screening. The uncontrolled self-administered measure, on the other hand, maybe readily influenced by insouciant or dishonest responses, yielding different findings from the clinician-administered diagnostic. Facial expression (FE) and behaviors are important in clinician-administered assessments, but they are underappreciated in self-administered evaluations. We use a new dataset of 200 participants to demonstrate the validity of self-rating questionnaires and their accompanying question-by-question video recordings in this study. We offer an end-to-end system to handle the face video recording that is conditioned on the questionnaire answers and the responding time to automatically interpret sadness from the SDS assessment and the associated video. We modified a 3D-CNN for temporal feature extraction and compared various state-of-the-art temporal modeling techniques. The superior performance of our system shows the validity of combining facial video recording with the SDS score for more accurate self-diagnose.

Spatiotemporal variations of asthma admission rates and their relationship with environmental factors in Guangxi, China.

OBJECTIVE: The study aimed to determine if and how environmental factors correlated with asthma admission rates in geographically different parts of Guangxi province in China. SETTING: Guangxi, China. PARTICIPANTS: This study was done among 7804 asthma patients. PRIMARY AND SECONDARY OUTCOME MEASURES: Spearman correlation coefficient was used to estimate correlation between environmental factors and asthma hospitalisation rates in multiple regions. Generalised additive model (GAM) with Poisson regression was used to estimate effects of environmental factors on asthma hospitalisation rates in 14 regions of Guangxi. RESULTS: The strongest effect of carbon monoxide (CO) was found on lag1 in Hechi, and every 10 µg/m3 increase of CO caused an increase of 25.6% in asthma hospitalisation rate (RR 1.26, 95% CI 1.02 to 1.55). According to the correlation analysis, asthma hospitalisations were related to the daily temperature, daily range of temperature, CO, nitrogen dioxide (NO2) and particulate matter (PM2.5) in multiple regions. According to the result of GAM, the adjusted R2 was high in Beihai and Nanning, with values of 0.29 and 0.21, which means that environmental factors are powerful in explaining changes of asthma hospitalisation rates in Beihai and Nanning. CONCLUSION: Asthma hospitalisation rate was significantly and more strongly associated with CO than with NO2, SO2 or PM2.5 in Guangxi. The risk factors of asthma exacerbations were not consistent in different regions, indicating that targeted measures should differ between regions.

Autophagy inhibits TLR4-mediated invasiveness of oral cancer cells via the NF-κB pathway.

OBJECTIVES: Toll-like receptor 4 (TLR4) is abnormally expressed in oral cancer tissues and promotes cancer cell invasion. The purpose of this study was to clarify the mechanism by which autophagy regulates oral cancer invasion through the TLR4-NF-κB pathway. SUBJECTS AND METHODS: We examined TLR4 expression in oral cancer tissues and analysed the relationship between its expression and clinicopathological features. The invasion and migration of LPS-stimulated oral cancer cells with up- or downregulation of TLR4 expression was detected in addition to NF-κB signalling and autophagy levels. Furthermore, the role of autophagy in regulating TLR4-mediated cell invasiveness was explored by silencing the expression of key autophagy genes ATG7 and p62. RESULTS: We found that TLR4 overexpression was closely related to cervical lymphatic metastasis and poor survival. TLR4 activated the NF-κB pathway to promote the invasiveness of OSCC cells, and autophagy partly inhibited invasiveness by suppressing the NF-κB pathway. We observed that p62 translocated from the cytoplasm to the nucleus when autophagy was activated by LPS. Finally, silencing p62 further promoted LPS-mediated cell invasiveness. CONCLUSION: Toll-like receptor 4 significantly enhanced the invasiveness of OSCC cells. Autophagy may regulate cell invasiveness through the NF-κB pathway by modulating both the cytoplasmic and nuclear levels of p62.

Hotspot detection and socio-ecological factor analysis of asthma hospitalization rate in Guangxi, China.

BACKGROUND: Asthma is a major public health concern throughout the world. Numerous researches have shown that the spatial-temporal patterns of asthma are inconsistent, leading to the suggestion that these patterns are determined by multiple factors. This study aims to detect spatial-temporal clusters of asthma and analyze socio-ecological factors associated with the asthma hospitalization rate in Guangxi, China. METHODS: Asthma hospitalization and socio-ecological data for 88 counties/municipal districts in Guangxi, China in 2015 was collected. Space-time scan statistics were applied to identify the high-risk periods and areas of asthma hospital admissions. We further used GeoDetector and Spearman correlation coefficient to investigate the socio-ecological factors associated with the asthma hospitalization rates. RESULTS: There were a total of 7804 asthma admissions in 2015. The high-risk period was from April to June. The age groups of 0-4 and ≥65 years were both at the highest risk, with hospital admission rates of 45.0/105 and 46.5/105, respectively. High-risk areas were found in central and western Guangxi with relative risk (RR) values of asthma hospitalizations greater than 2.0. GDP per capita and altitude were positively associated with asthma hospitalizations, while air pressure and wind speed had a negative association. The explanatory powers of these factors (i.e., GDP per capita, altitude, air pressure, wind speed) were 22%, 20%, 14% and 10%, respectively. CONCLUSIONS: The GDP per capita appears to have the strongest correlation with asthma hospitalization rates. High-risk areas were identified in central and western Guangxi characterized by high GDP per capita. These findings may be helpful for authorities developing targeted asthma prevention policies for high-risk areas and vulnerable populations, especially during high-risk periods.

A cone-beam computed tomography study of the root and canal morphology of maxillary premolars / 口腔疾病防治

Objective @# To study root morphology, the incidence of three root canals and the root canal anatomy of maxillary premolars.@*Methods@#The cone-beam computed tomography (CBCT) data of 779 maxillary first premolars and 728 maxillary second premolars were collected from 412 patients in Zhuhai Stomatological Hospital. The root and canal morphology, incidence of three canals, bilateral symmetry and location of root canal bifurcation were analyzed. @*Results @#The incidence of three canals in the maxillary first premolars was 1.8% and that in the maxillary second premolars was 0.3%. The incidence of three canals in the maxillary first premolars was significantly higher than that in the maxillary second premolars (c2=8.304, P=0.004). The symmetrical ratio of the three-canal maxillary first premolar was 27.3%. There was no symmetrical three-canal maxillary second premolar. The anatomical morphology of the maxillary premolar can be single root, double root or trident root. Its internal root canal system is complex and diverse. There are seven kinds of Vertucci morphology: the first maxillary premolar is mainly Vertucci IV type, and the second maxillary premolar is mainly Vertucci I type. Most of the root canal bifurcations of the three-canal maxillary premolars were observed in the midthird or the cervical third of the root. All three-canal maxillary premolars had three independent apical foramens. @*Conclusion @#The root canal morphology of maxillary premolars is complex and changeable. CBCT plays an important role in the discovery of variation and extra root canals.

Cone-beam computed tomography study of C-shaped root canal of mandibular premolars / 口腔疾病防治

Objective@#To investigate the incidence and morphology of C-shaped root canals in mandibular premolars by cone-beam computed tomography (CBCT) imaging, which provides a reference for clinical diagnosis and treatment.@*Methods @#The CBCT scanning data of 964 mandibular first premolars and 907 mandibular second premolars in 508 cases were collected, and the root canal morphology, incidence of C-shaped root canals, bilateral symmetry and location of radicular grooves were analyzed.@*Results@#The incidence of C-shaped root canals in mandibular first premolars was 4.1% and that in mandibular second premolars was 0.6%. The incidence of C-shaped root canals of mandibular first premolars was significantly higher than that of mandibular second premolars (χ2=25.775, P < 0.001). The symmetrical ratio of C-shaped root canals in the mandibular first premolars was 29%. There were no symmetrical C-shaped root canals in the mandibular second premolars. There were significant differences in the distribution of the C-shaped root canal configuration in the root canal (P < 0.001). The C-shaped configuration mainly existed in the middle axial and apical level of the mandibular premolars. The C2 type was more common. No C-shape was found in the coronal level of the mandibular premolars. Vertucci I single tube type was the most common type of root canal for the mandibular premolars included in this study; the incidences were 81.7% and 98.3% for the mandibular first and second premolars, respectively, and the difference was statistically significant (χ2=140.544, P < 0.001). The other root canal types of mandibular first premolars were more than those of mandibular second premolars. The incidences of Vertucci Ⅱ, Ⅲ, Ⅳ, and Ⅴ and C-shaped root canals in mandibular first premolars were significantly higher than those in mandibular second premolars. C-shaped root canal mandibular premolars had radicular grooves, and most of them were located at the mesiolingual side.@*Conclusion@# The morphology of the C-shaped root canal in mandibular premolars was complicated. CBCT can provide direct and accurate imaging evidence for clinical diagnosis and treatment.

B4GALNT1 enhances cell proliferation and growth in oral squamous cell carcinoma via p38 and JNK MAPK pathway.

BACKGROUND: Beta-1,4-N-Acetyl-Galactosaminyltransferase 1 (B4GALNT1) was reported to play an important role in the development of the central nervous systems. We found higher expression of B4GALNT1 in oral squamous cell carcinoma (OSCC) tissues compared to the paired normal adjacent tissues in the TCGA database. This study aimed to investigate whether there was a potential relationship between B4GALNT1 and OSCC tumorigenesis and further explored the possible regulation mechanism. METHODS: Gene expression level was analyzed by means of real-time quantitative PCR and further cell function experiments were performed including cell proliferation and apoptosis test, cell cycle distribution detection after silencing B4GALNT1 by transfection with B4GALNT1-shRNA lentivirus. Western Blotting was carried out to explore the possible molecular mechanism. RESULTS: The present study confirmed the overexpression of B4GALNT1 in OSCC. Compared to the control group, cell proliferation after silencing B4GALNT1 was significantly inhibited and cell apoptosis percentage was significantly higher. Besides, the knockdown of B4GALNT1 resulted in cell cycle arrest at G1 phase in our experiment. CONCLUSIONS: B4GALNT1 enhances the proliferation and suppress the apoptosis of OSCC cells probably through JNK and p38 signaling pathway.

A method for hand-foot-mouth disease prediction using GeoDetector and LSTM model in Guangxi, China.

Hand-foot-mouth disease (HFMD) is a common infectious disease in children and is particularly severe in Guangxi, China. Meteorological conditions are known to play a pivotal role in the HFMD. Previous studies have reported numerous models to predict the incidence of HFMD. In this study, we proposed a new method for the HFMD prediction using GeoDetector and a Long Short-Term Memory neural network (LSTM). The daily meteorological factors and HFMD records in Guangxi during 2014-2015 were adopted. First, potential risk factors for the occurrence of HFMD were identified based on the GeoDetector. Then, region-specific prediction models were developed in 14 administrative regions of Guangxi, China using an optimized three-layer LSTM model. Prediction results (the R-square ranges from 0.39 to 0.71) showed that the model proposed in this study had a good performance in HFMD predictions. This model could provide support for the prevention and control of HFMD. Moreover, this model could also be extended to the time series prediction of other infectious diseases.

Spatial-temporal variation and risk factor analysis of hand, foot, and mouth disease in children under 5 years old in Guangxi, China.

BACKGROUND: Hand, foot and mouth disease (HFMD) incidence is a critical challenge to disease control and prevention in parts of China, particularly Guangxi. However, the association between socioeconomic factors and meteorological factors on HFMD is still unclear. METHODS: This study applied global and local Moran's I to examine the spatial pattern of HFMD and series analysis to explore the temporal pattern. The effects of meteorological factors and socioeconomic factors on HFMD incidence in Guangxi, China were analyzed using GeoDetector Model. RESULTS: This study collected 45,522 cases from 87 counties in Guangxi during 2015, among which 43,711 cases were children aged 0-4 years. Temporally, there were two HFMD risk peaks in 2015. One peak was in September with 7890 cases. The other appeared in May with 4687 cases of HFMD. A high-risk cluster was located in the valley areas. The tertiary industry, precipitation and second industry had more influence than other risk factors on HFMD incidence with explanatory powers of 0.24, 0.23 and 0.21, respectively. The interactive effect of any two risk factors would enhance the risk of HFMD. CONCLUSIONS: This study suggests that precipitation and tertiary industry factors might have stronger effects on the HFMD incidence in Guangxi, China, compared with other factors. High-risk of HFMD was identified in the valley areas characterized by high temperature and humidity. Local government should pay more attention and strengthen public health services level in this area.