A Multi-center Dental Panoramic Radiography Image Dataset for Impacted Teeth, Periodontitis, and Dental Caries: Benchmarking Segmentation and Classification Tasks.

Panoramic radiography imaging plays a crucial role in the diagnostic process of dental diseases. However, current artificial intelligence research datasets for panoramic radiography dental image processing are often limited to single-center and single-task scenarios, making it difficult to generalize their results. To address this, we present a multi-center, multi-task labeled dataset. In this study, our dataset comprises three datasets obtained from different hospitals. The first set has 4940 panoramic radiography images and corresponding labels from the Stemmatological Hospital of the General Hospital of Ningxia Medical University. The second set includes 716 panoramic radiography images and labels from the People's Hospital of Yinchuan City, Ningxia. The third dataset contains 880 panoramic radiography images and labels from a hospital in Shenzhen, Guangdong Province. This comprehensive dataset encompasses three types of dental diseases: impacted teeth, periodontitis, and dental caries. Specifically, it comprises 2555 images related to impacted teeth, 2735 images related to periodontitis, and 1246 images related to dental caries. In order to evaluate the performance of the dataset, we conducted benchmark tests for segmentation and classification tasks on our dataset. The results show that the presented dataset could be effectively used for benchmarking segmentation and classification tasks critical to the diagnosis of dental diseases. To request our multi-center dataset, please visit the address: https://github.com/qinxin99/qinxini .

The use of the sleep apnea-specific hypoxic burden to predict obstructive sleep apnea hypopnea syndrome: Evidence from a large cross-sectional study.

OBJECTIVES: Obstructive sleep apnea hypopnea syndrome (OSA) is an independent risk factor for neurocognitive and behavioral problems and cardiovascular and metabolic morbidities, ultimately increasing mortality. However, OSA diagnosis is time-consuming, labor-intensive, and expensive. We evaluated the predictive utility of the sleep apnea-specific hypoxic burden (SASHB) in terms of OSA and the severity thereof in Han Chinese individuals. METHODS: From January 2019 to July 2022, subjects with suspected OSA were recruited in the sleep center of the Shanghai Sixth People's Hospital during sleep evaluation via standard polysomnography. Basic anthropometric measurements and polysomnographic indicators were collected; SASHB was calculated based on the SpO2 trends of apnea or hypopnea events. Models predictive of OSA were established via logistic regression in the experimental group and verified in an independent group by drawing receiver operating characteristic (ROC) curves. RESULTS: A total of 2303 subjects with suspected OSA (1200 in the experimental group and 1103 in the validation group) were included. SASHB was positively correlated with the apnea-hyponea index (AHI) in all subjects (r = 0.823, P < 0.001). SASHB distinguished OSA from non-OSA subjects in both the experimental group {area under the curve (AUC) 0.948 [0.934∼0.962]} and the validation group (AUC 0.931 [0.913∼0.949]). SASHB predicted OSA severity well, better than did the neck, waist, or hip circumference; the lowest or mean oxygen saturation; and the Epworth sleepiness scale score. CONCLUSION: SASHB predicted OSA both accurately and efficiently in a Chinese Han population. Further studies are warranted to verify our findings in community samples.

Authentication of duck blood tofu binary and ternary adulterated with cow and pig blood-based gel using Fourier transform near-infrared coupled with fast chemometrics.

This work aims to investigate a feasible and practical technique for the authentication of edible animal blood food (EABF) using Fourier transform near-infrared (FT-NIR) coupled with fast chemometrics. A total of 540 samples were used, including raw duck blood tofu (DBT), cow blood-based gel (CBG), pig blood-based gel (PBG), and DBT binary and ternary adulterated with CBG and PBG. The protein, fat, total sugar, and 16 kinds of amino acids were measured to validate the difference in basic organic matters among EABFs according to species. Fisher linear discriminate analysis (Fisher LDA) and extreme learning machine (ELM) were implemented comparatively to identify the adulterated EABF. To predict adulteration levels, four extreme learning machine regression (ELMR) models were constructed and optimized. Results showed that, by analyzing 27 crucial spectral variables, the ELM model provides higher accuracy of 93.89% than Fisher LDA for the independent samples. All the correlation coefficients of the optimized ELMR models' training and prediction sets were better than 0.94, the root mean square errors were all less than 3.5%, and the residual prediction deviation and the range error ratios were all higher than 4.0 and 12.0, respectively. In conclusion, the FT-NIR paired with ELM have great potential in authenticating the EABF. This work presents amino acids content in EABFs for the first time and built tracing models for rapid authentication of DBT, which can be used to manage the EABF market, thereby preventing illegal adulteration and unfair competition.

The use of autogenous tooth bone graft powder in the treatment of osseous defects after impacted mandibular third molar extraction: a prospective split-mouth clinical pilot study.

BACKGROUND: Impaction of mandibular third molars (M3) is one of the most common diseases. Extraction of M3 usually exacerbates osseous defects at the distal aspect of the adjacent second molar (M2). BonMaker® ATB has been cited as a novel autogenous bone grafting material. The aim of this pilot study was to introduce a novel method for repairing the distal osseous defects of M2 after the surgical removal of M3 with autogenous tooth graft powder (ATGP). METHOD: A total of five patients were enrolled in this prospective split-mouth clinical pilot study. Four impacted wisdom teeth were extracted bilaterally from each patient with proximal alveolar bone loss ≥ 5 mm of M3. The ATGP was prepared chairside from two extracted one side third molars and randomly implanted in one of the M3 extraction sockets, and the other side was treated with a blank and considered the control site. Patients were followed up at 6 months. RESULTS: The five patients included three males and two females. Their ages ranged from 25 to 30 years, with a median of 27 years. Primary wound healing without complications was achieved in all the patients. There was a greater tendency for swelling of the cheeks and trismus to occur at the experimental site on the third postoperative day. Compared with the control site, the experimental site exhibited progressive bone filling and ossification in the sixth postoperative month. Moreover, the probing pocket depth of the experimental site was lower than that of the control site. CONCLUSION: The results of this study demonstrate that ATGP effectively and economically repairs distal osseous defects of M2. Further study is required to validate the effectiveness with a larger study population.

Machine-learning assisted modelling of multiple elements for authenticating edible animal blood food.

Elemental fingerprint coupled with machine learning modelling was proposed for species authentication of the edible animal blood gel (EABG). A total of 25 elements were determined by inductively coupled plasma mass spectrometry (ICP-MS) and atomic absorption spectroscopy (AAS) in 150 EABG samples prepared from five species of animals, namely duck, chicken, bovine, pig, and sheep. Extreme learning machine (ELM) models were constructed and optimized. Principal component analysis and Fisher linear discriminant analysis were comparatively utilized for dimension reduction of the crucial input elements selected via stepwise discriminant analysis and one-way ANOVA. The optimal ELM model was obtained with the crucial elements selected by one-way ANOVA from the relative content of the measured elements, which afforded accuracies of 98.0% and 96.0% for the training and test set, respectively. All findings suggest that elemental fingerprint accompanied by ELM have great potential in authenticating the edible animal blood food.

Fusion of a low-cost electronic nose and Fourier transform near-infrared spectroscopy for qualitative and quantitative detection of beef adulterated with duck.

A low-cost electronic nose (E-nose) based on colorimetric sensors fused with Fourier transform-near-infrared (FT-NIR) spectroscopy was proposed as a rapid and convenient technique for detecting beef adulterated with duck. The total volatile basic nitrogen, protein, fat, total sugar and ash contents were measured to investigate the differences of basic properties between raw beef and duck; GC-MS was employed to analyze the difference of the volatile organic compounds emitted from these two types of meat. For variable selection and spectra denoising, the simple T-test (p < 0.05) separately intergraded with first derivative, second derivative, centralization, standard normal variate transform, and multivariate scattering correction were performed and the results compared. Extreme learning machine models were built to identify the adulterated beef and predict the adulteration levels. Results showed that for recognizing the independent samples of raw beef, beef-duck mixtures, and raw duck, FT-NIR offered a 100% identification rate, which was superior to the E-nose (83.33%) created herein. In terms of predicting adulteration levels, the root means square error (RMSE) and the correlation coefficient (r) for independent meat samples using FT-NIR were 0.511% and 0.913, respectively. At the same time, for E-nose, these two indicators were 1.28% and 0.841, respectively. When the E-nose and FT-NIR data were fused, the RMSE decreased to 0.166%, and the r improved to 0.972. All the results indicated that fusion of the low-cost E-nose and FT-NIR could be employed for rapid and convenient testing of beef adulterated with duck.

Cone-beam computed tomography study of upper airway morphology in children with obstructive sleep apnea-hypopnea syndrome / 口腔疾病防治

Objective @#To evaluate the morphology of the upper airway of children with obstructive sleep apnea-hypopnea syndrome (OSAHS) using cone-beam computed tomography (CBCT) combined with polysomnography (PSG) and provide references for clinical practice.@*Methods@# CBCT data of 45 OSAHS children and 45 normal children and PSG data of the OSAHS group were retrospectively collected. Three-dimensional reconstructions were performed using NNT 9.0 software. The total upper airway volume, nasopharyngeal volume, palatopharyngeal volume, glossopharyngeal volume, laryngopharyngeal volume, minimum cross-sectional area, anterior-posterior diameter of the minimum cross-section, and lateral diameter of the minimum cross-section were measured and recorded. According to PSG monitoring results, patients with an obstructive apnea hypopnea index (OAHI) and lowest oxygen saturation (LSaO2) were assessed. Body mass index (BMI) was recorded. The correlation between airway volume parameters, BMI and PSG test results was analyzed. @*Results@#The total upper airway volume, nasopharyngeal volume, palatopharyngeal volume, glossopharyngeal volume, laryngopharyngeal volume, minimum cross-sectional area, anterior-posterior diameter of the minimum cross-section, and lateral diameter of the minimum cross-section of the OSAHS group were significantly reduced compared with those of the control group (P<0.05). In the OSAHS group, the total upper airway volume, the minimum cross-sectional area and the lateral diameter of the minimum cross-section showed moderate negative correlations with the obstructive apnea hypopnea index (OAHI) (P<0.05). Moreover, the total upper airway volume, minimum cross-sectional area, anterior-posterior diameter of the minimum cross-section and lateral diameter of the minimum cross-section showed no correlation with the minimum blood oxygen saturation (P>0.05). No significant correlation was noted between BMI and PSG in the OSAHS group (P>0.05).@*Conclusion @#The morphology of the upper airway of children with OSAHS was significantly smaller than that of normal children. CBCT three-dimensional technology for analyzing the upper airway has a certain value in evaluating the morphology and degree of obstruction of the upper airway in children with OSAHS.

Artificial bionic taste sensors coupled with chemometrics for rapid detection of beef adulteration.

The purpose of this study was to investigate the potential of taste sensors coupled with chemometrics for rapid determination of beef adulteration. A total of 228 minced meat samples were prepared and analyzed via raw ground beef mixed separately with chicken, duck, and pork in the range of 0 ~ 50% by weight at 10% intervals. Total sugars, protein, fat, and ash contents were also measured to validate the differences between raw meats. For sensing the water-soluble chemicals in the meats, an electronic tongue based on multifrequency large-amplitude pulses and six metal electrodes (platinum, gold, palladium, tungsten, titanium, and silver) was employed. Fisher linear discriminant analysis (Fisher LDA) and extreme learning machine (ELM) were used to model the identification of raw and the adulterated meats. While an adulterant was detected, the level of adulteration was predicted using partial least squares (PLS) and ELM and the results compared. The results showed that superior recognition models derived from ELM were obtained, as the recognition rates for the independent samples in different meat groups were all over 90%; ELM models were more precisely than PLS models for prediction of the adulteration levels of beef mixed with chicken, duck, and pork, with root mean squares error for the independent samples of 0.33, 0.18, and 0.38% and coefficients of variance of 0.914, 0.956, and 0.928, respectively. The results suggested that taste sensors combined with ELM could be useful in the rapid detection of beef adulterated with other meats.

[Shanghai municipal expert consensus on standardized prevention and control of COVID-19 during procedures of oral radiology].

The announcement of National Health Commission on January 20, 2020 (No.1 of 2020) has included novel coronavirus pneumonia into the B class infectious diseases according to the law of the People's Republic of China on the prevention and control of infectious diseases, and has been managed as A class infectious diseases. People's governments at all levels and health administration departments have been paying high attention to it. With the alleviation of COVID-19 nationwide, dental clinics gradually resume to work. The main transmission routes of COVID-19 are respiratory droplets and contact transmission, hence oral radiological examination is kind of a high-risk operation. Standardized radiologic process is of great significance to reduce the risk of COVID-19 transmission. In accordance with the national and Shanghai epidemic prevention requirements, and in combination with the actual situation of various medical institutions, Oral and Maxillofacial Radiology Committee of Shanghai Stomatological Association formulated the expert consensus on standardized prevention and control of COVID-19 for clinical reference. This recommendation will be updated according to the situation of epidemic prevention and control in China and the new relevant diagnosis and treatment plans.

Integration of a low-cost electronic nose and a voltammetric electronic tongue for red wines identification.

The purpose of this present study was to develop a rapid and effective approach for identification of red wines that differ in geographical origins, brands, and grape varieties, a multi-sensor fusion technology based on a novel cost-effective electronic nose (E-nose) and a voltammetric electronic tongue (E-tongue) was proposed. The E-nose sensors was created using porphyrins or metalloporphyrins, pH indicators and Nile red printed on a C2 reverse phase silica gel plate. The voltammetric E-Tongue with six metallic working electrodes, namely platinum, gold, palladium, tungsten, titanium, and silver was employed to sense the taste of red wines. Principal component analysis (PCA) was utilized for dimensionality reduction and decorrelation of the raw sensors datasets. The fusion models derived from extreme learning machine (ELM) were built with PCA scores of E-nose and tongue as the inputs. Results showed superior performance (100% recognition rate) using combination of odor and taste sensors than individual artificial systems. The results suggested that fusion of the novel cost-effective E-nose created and voltammetric E-tongue coupled with ELM has a powerful potential in rapid quality evaluation of red wine.

Ultrasound enhanced biosynthesis of L-theanine from L-glutamine and ethylamine by recombinant γ-glutamyltranspeptidase.

A mutant library of the key amino acid residue site E387 in γ-glutamyltranspeptidase was constructed to screen the mutant enzymes with significantly improved thermal stability (E387Q). The reaction temperature of the mutant enzyme (E387Q) was 10℃ higher than that of the parent enzyme. Ultrasound-assisted synthesis of L-theanine by γ-glutamyltranspeptidase was investigated. The effects of ultrasonic power, reaction pH and substrate concentration on the enzymatic synthesis of L-theanine were studied by the response surface method. The results showed that the optimal process conditions are ultrasonic power of 100 W, reaction pH of 9, substrate L-glutamine concentration of 120 mmol/L, reaction temperature of 45℃, and L-theanine yield of 89.1%. The yield of L-theanine is 2.61 times higher than that obtained without ultrasound. Ultrasound can significantly promote the synthesis of L-theanine by γ-glutamyltranspeptidase.

Engineering Improves Enzymatic Synthesis of L-Tryptophan by Tryptophan Synthase from Escherichia coli.

To improve the thermostability of tryptophan synthase, the molecular modification of tryptophan synthase was carried out by rational molecular engineering. First, B-FITTER software was used to analyze the temperature factor (B-factor) of each amino acid residue in the crystal structure of tryptophan synthase. A key amino acid residue, G395, which adversely affected the thermal stability of the enzyme, was identified, and then, a mutant library was constructed by site-specific saturation mutation. A mutant (G395S) enzyme with significantly improved thermal stability was screened from the saturated mutant library. Error-prone PCR was used to conduct a directed evolution of the mutant enzyme (G395S). Compared with the parent, the mutant enzyme (G395S /A191T) had a Km of 0.21 mM and a catalytic efficiency kcat/Km of 5.38 mM-1∙s-1, which was 4.8 times higher than that of the wild-type strain. The conditions for L-tryptophan synthesis by the mutated enzyme were a L-serine concentration of 50 mmol/L, a reaction temperature of 40 °C, pH of 8, a reaction time of 12 h, and an L-tryptophan yield of 81%. The thermal stability of the enzyme can be improved by using an appropriate rational design strategy to modify the correct site. The catalytic activity of tryptophan synthase was increased by directed evolution.

Detection of Beef Adulterated with Pork Using a Low-Cost Electronic Nose Based on Colorimetric Sensors.

The present study was aimed at developing a low-cost but rapid technique for qualitative and quantitative detection of beef adulterated with pork. An electronic nose based on colorimetric sensors was proposed. The fresh beef rib steaks and streaky pork were purchased and used from the local agricultural market in Suzhou, China. The minced beef was mixed with pork ranging at levels from 0%~100% by weight at increments of 20%. Protein, fat, and ash content were measured for validation of the differences between the pure beef and pork used in basic chemical compositions. Fisher linear discriminant analysis (Fisher LDA) and extreme learning machine (ELM) were utilized comparatively for identification of the ground pure beef, beef-pork mixtures, and pure pork. Back propagation-artificial neural network (BP-ANN) models were built for prediction of the adulteration levels. Results revealed that the ELM model built was superior to the Fisher LDA model with higher identification rates of 91.27% and 87.5% in the training and prediction sets respectively. Regarding the adulteration level prediction, the correlation coefficient and the root mean square error were 0.85 and 0.147 respectively in the prediction set of the BP-ANN model built. This suggests, from all the results, that the low-cost electronic nose based on colorimetric sensors coupled with chemometrics has a great potential in rapid detection of beef adulterated with pork.

Downregulation of GATS gene inhibits proliferation, clonogenicity and migration in triple negative breast cancer cells MDA-MB-231 by cell autophagy.

The triple negative breast cancer (TNBC) accounts for 15% to 20% of the total number of breast cancer diagnosed. A number of clinical studies have shown that TNBC has a high risk of early recurrence and distant metastasis, and a low rate of disease free survival and total survival. The premise of TNBC deterioration was abnormal proliferation and migration of tumor cells, and this study firstly showed that GATS gene could promote proliferation of MDA-MB-231 breast cancer cells. Through lentiviral expression system, the GATS gene was konckdown by shGATS lentivirus infection in the MDA-MB-231 cells, and the result indicated it could remarkably decrease the ability of cell proliferation and migration. Real-time PCR, western blot and immunofluorescence experiments showed the expressions of protein LC3, and p-Akt in shGATS cell group were lower than the shCtrl group. Therefore, we suggest the GATS could promote the MDA-MB-231 cell proliferation, migration and clonogenicity through cell autophagy by the PI3K/Akt pathway, which paved the way for further study the function of GATS in TNBC, and GATS may potentially be a target for gene therapy against triple negative breast cancer.

Salicin from Alangium chinense Ameliorates Rheumatoid Arthritis by Modulating the Nrf2-HO-1-ROS Pathways.

Rheumatoid arthritis (RA) is a chronic inflammatory disorder linked to oxidative stress of rheumatoid arthritis fibroblast-like synoviocytes (RA-FLSs). The effects and potential mechanism of salicin on inflammation and oxidative stress of RA-FLSs were examined by MTT, ELISA, and Western blot methods. Salicin significantly reduced cell viability (82.03 ± 7.06, P < 0.01), cytokines (47.70 ± 1.48 ng/L for TNF-α, 30.03 ± 3.49 ng/L for IL-6) ( P < 0.01), and matrix metalloproteinases-1/-3 expression ( P < 0.01) in IL-1ß-induced RA-FLSs and inhibited ROS generation and p65 phosphorylation ( P < 0.01) as compared with IL-1ß-induced treatment. Moreover, salicin promoted Nrf2 nuclear translocation (2.15 ± 0.21) and HO-1 expression (1.12 ± 0.05) and reduced ROS production in IL-1ß-induced RA-FLSs ( P < 0.01). Salicin not only reduced the collagen-induced arthritis by reducing the clinical score ( P < 0.01), inflammatory infiltration, and synovial hyperplasia in vivo but also suppressed the oxidative damage indexes (SOD 155.40 ± 6.53 U/mg tissue, MDA 152.80 ± 5.89 nmol/g tissue, GSH 50.98 ± 3.45 nmol/g tissue, and CAT 0.92 ± 0.10 U/g protein) ( P < 0.01) of ankle joint cells. Conclusively, our findings indicate that salicin ameliorates rheumatoid arthritis, which may be associated with oxidative stress and Nrf2-HO-1-ROS pathways in RA-FLSs.

Protective effects of paeonol on inflammatory response in IL-1ß-induced human fibroblast-like synoviocytes and rheumatoid arthritis progression via modulating NF-κB pathway.

Various investigations have demonstrated that human fibroblast-like synoviocytes rheumatoid arthritis (HFLS-RA) take part in the chronic inflammatory responses and RA progression. Inhibition of synovium activation and inflammatory processes may represent a therapeutic target to alleviate RA. Paeonol, a major natural product, has many biological and pharmacological activities. However, its protective effects against RA considering HFLS-RA have not been explored. In this study, anti-inflammatory effects of paeonol were detected in interleukin-1ß (IL-1ß)-treated HFLS-RA. Our results demonstrated that paeonol had no effect on cell survival and IL-1ß-induced proliferation in HFLS-RA. Pretreatment with paeonol significantly suppressed the production of pro-inflammatory TNF-α, IL-6 and IL-1ß, and the expressions of matrix metalloproteinase-1/-3 in vitro and in vivo. Mice treated with paeonol (10 mg/kg) remarkablely attenuated arthritic symptoms based on clinical arthritis scores and histopathology in collagen-induced arthritis mice. Furthermore, the TLR4 expression and NF-κB p65 activation were inhibited by paeonol in vitro and in vivo. Our findings illustrated that paeonol had significantly suppressed inflammation effects in synovial tissues and RA progression. The potential mechanism might be based on the attenuation TLR4-NF-κB activation. These collective results indicated that paeonol might be a promising therapeutic agent for alleviating RA progress through inhibiting inflammations and NF-κB signalling pathway.

Recurrent Keratocystic Odontogenic Tumor After Effective Decompression.

Keratocystic odontogenic tumor (KCOT) has potential aggressive and infiltrative behavior. Decompression has been widely preferred for large KCOTs due to safety and lower recurrence rates. However, KCOT is still likely to recur even after effective decompression. Here, we present a rare and interesting case of recurrent KCOT after effective decompression with adjunctive enucleation. Redecompression was then performed again, and the effect was still satisfactory on long-term follow-up.