[Identification model of tooth number abnormalities on pediatric panoramic radiographs based on deep learning]

Objective: To identify tooth number abnormalities on pediatric panoramic radiographs based on deep learning. Methods: Eight hundred panoramic radiographs of children aged 4 to 11 years meeting the inclusion and exclusion criteria were selected and randomly assigned by writing programs in Python (version 3.9) to the training set (480 images), verification set (160 images) and internal test set (160 images), taken in Department of Pediatric Dentistry, Peking University School and Hospital of Stomatology between November 2012 to August 2020. And all panoramic radiographs of children aged 4 to 11 years taken in the First Outpatient Department of Peking University School and Hospital of Stomatology from June 2022 to December 2022 were collected as the external test set (907 images). All of the 1 707 images were obtained by operators to determine the outline and to label the tooth position of each deciduous tooth, permanent tooth, permanent tooth germ and additional tooth. The deep learning model with ResNet-50 as the backbone network was trained on the training set, validated on the verification set, tested on the internal test set and external test set. The images of test sets were divided into two categories according to whether there was abnormality of tooth number, to calculate sensitivity, specificity, positive predictive value and negative predictive value, and then divided into four types of extra teeth and missing permanent teeth both existed, extra teeth existed only, missing permanent teeth existed only, and normal teeth number, to calculate Kappa values. Results: The sensitivity, specificity, positive predictive value and negative predictive value were 98.0%, 98.3%, 99.0% and 96.7% in the internal test set, and 97.1%, 98.4%, 91.9% and 99.5% in the external test set respectively, according to whether there was abnormality of tooth number. While images were divided into four types, the Kappa value obtained in the internal test set was 0.886, and that in the external test set was 0.912. Conclusions: In this study, a deep learning-based model for identifying abnormal tooth number of children was developed, which could identify the position of additional teeth and output the position of missing permanent teeth on the basis of identifying normal deciduous and permanent teeth and permanent tooth germs on panoramic radiographs, so as to assist in diagnosing tooth number abnormalities.

[Analysis of nasal microbial characteristics in patients with allergic rhinitis and non-allergic rhinitis]

Objective: To investigate the characteristics of nasal flora and the pathogenic role of differential microbiome in patients with allergic rhinitis (AR) and non-allergic rhinitis (nAR). Methods: Thirty-five patients with AR who attended the rhinology outpatient clinic of the Second Hospital of Harbin Medical University from February to July 2022 were selected. A total of 35 nAR patients were selected as the test group, and 20 cases of healthy people with physical examination at the same period were selected as the control group, including 39 males and 51 females, aged 8 to 55 years. 16SrDNA High-throughput sequencing was used to analyze the relative abundance from nasal flora in the three groups of subjects. Alpha diversity index analysis was conducted with R software, and differences between groups were analyzed with LEfSe, Metastats, and t tests. At the same time, the role of microbiome and its relationship with environmental factors were analyzed with R software. Results: There was a significant difference in the bacterial composition of the samples from the three groups, with the relative abundance of Staphylococcus aureus (P=0.032) and Corynebacterium proinquum (P=0.032) within the AR group being significantly higher than that of the nAR group, and that of Lactobacillus murinus, Lactobacillus kunkeei, and Alcaligenes faecalis (P value was 0.016, 0.005, and 0.001, respectively) being significantly lower than that of the nAR group. The relative abundance of Ackermannia muciniphila within the nAR group was higher than that of the control group (P=0.009). Correlation analysis of environmental factors showed a negative correlation between Lactobacillus kunkeei and IgE (P=0.044), and a positive correlation between Lactobacillus murinus and age (P=0.019). AR and nAR random forest prediction models were constructed for the five genera, respectively, and the area under the curve (AUC) of the models of Streptococcus-SP-FF10, Pseudoalteromonas luteoviolacea, Pseudomonas parafulva, Acinetobacter ursingii, and Azotobacter chroococcum in the AR group was 100% (95%CI: 100% to 100%). The AUC for the Pseudomonas parafulva, Azotobacter chroococcum, Closoridium baratii, Turicibacter-SP-H121, and Streptococcus lutetiensis models in the nAR group was 98.4% (95%CI: 94.9% to 100%). Conclusions: The distribution of nasal flora in AR patients, nAR patients and healthy subjects is significantly different, and the changes of bacterial flora abundance are significantly related to the occurrence of AR and nAR. Combined detection of microbiota has the potential to diagnose AR and nAR patients.

[Efficacy and safety of anti-PD-1 monoclonal antibody in advanced hepatocellular carcinoma after TACE combined with TKI therapy]

Objective: To evaluate the efficacy and safety of anti-programmed cell death 1 (PD-1) receptor monoclonal antibody (MoAb) in patients with advanced hepatocellular carcinoma (HCC) after treatment of transcatheter arterial chemoembolization (TACE) combined with tyrosine kinase inhibitor (TKI). Methods: From February 2019 to February 2020, 56 HCC patients who relapsed after TACE-TKI treatment in Department of Interventional Radiology, The Second Affiliated Hospital of Guangzhou Medical University were enrolled. All patients received anti-PD-1 MoAb (sintilimab injection) and followed up every 6 weeks. According to mRECIST, the curative effect was evaluated as complete response (CR), partial response (PR), stable disease (SD) or progressive disease (PD). Objective response rate (ORR) and disease control rate (DCR), progression-free survival (PFS) and treatment-related adverse events (TRAEs) were recorded. Univariate analysis by Chi-square test and binary logistic regression model was used to determine the influencing factors of DCR. The Kaplan-Meier method and Cox proportional hazard regression model were used to analyze the survival data. Results: A total of 48 patients were enrolled in this study including 42 males and 6 females, with a median age of 55 years (29-71 years). ECOG scores comprised of 0 in 24 cases, 1-2 in 24 cases. Thirty-six patients were in Child-Pugh grade A of liver function and 12 cases were grade B. The median follow-up time was 4.5 months. There were 2 patients achieved CR, 12 patients with PR and 16 with SD. ORR was 29.2%, DCR was 62.5%. The independent influencing factors of DCR was ECOG score and AFP level (P=0.031, P=0.012). Median PFS was 4.1 months (95%CI 2.7-5.4 months), and ECOG score was the independent influencing factor of PFS (P=0.042). Treatment-related adverse events were reported in 70.8% (34/48) patients. Incidence of grade Ⅲ-Ⅳ TRAEs was 22.9% (11/48). Conclusion: In patients with HCC who relapse from TACE and TKI treatment, anti-PD-1 monoclonal antibody is efficacious safe especially in those with ECOG 0 score.

A fast key parameter extraction algorithm for long fiber distributed sensing based on Brillouin scattering

A fast key parameter extraction algorithm is proposed to improve the real-time performance of temperature and strain measurements when performing Brillouin scattering-based fiber-distributed sensing. The algorithm uses a new initial value method that takes the extracted key parameters of the current point in the fiber as the initial guesses for the next point. Based on the old and new initial value method, the existing objective method, optimization algorithm, and convergence criterion, the key parameter extraction algorithms developed are implemented in Matlab using the typical Lorentzian, Gaussian, and pseudo-Voigt profiles. These algorithms are used to extract the parameters over a large range of measured Brillouin spectra for the entire fiber with different averaging times. The results reveal that apart from the case when the frequency sweep spans is less than the linewidth and the pseudo-Voigt profile is used (in this case, the mean computation time of the proposed algorithm is 1.1% larger than that of the referenced algorithm), the proposed algorithm not only ensures high accuracy in extracting the key parameters, but also improves the arithmetic efficiency by 16.3%-49.1%.

Effects of exercise training on carbohydrate and lipid catabolism in the swimming muscles of Nile tilapia (Oreochromis niloticus)

This study aims to determine the effects of exercise training on carbohydrate and lipid catabolism in the swimming muscles of Nile tilapia (Oreochromis niloticus) by measuring the levels of related enzymes, lipids and free fatty acids. We designed one control group and two training groups of fish that were exercised at different training intensities [0, 1 and 1.5 body lengths per second (bl/s)]. The fish in the experimental groups were trained for 12 h/day for 4 weeks. Compared with the control group, the 1 and 1.5 bl/s groups showed significantly increased hexokinase and pyruvate kinase activities in red muscle (p < 0.05). In white muscle, pyruvate kinase activity was significantly higher in the 1.5 bl/s group than in the control group (p < 0.05), and hexokinase activity did not significantly differ between the groups. The activities of hormone-sensitive lipase and carnitine palmitoyltransferase I in both muscle types were significantly lower in the training groups than in the control group (p < 0.05). The plasma-free fatty acid level decreased (p < 0.05), while the lipid percentages increased in red muscle (p < 0.05) after exercise training. These findings clearly indicated that with exercise training, glycolysis increased and lipid oxidation decreased in the swimming muscle of tilapia.

A highly accurate dynamic contact angle algorithm for drops on inclined surface based on ellipse-fitting

To improve the accuracy in the calculation of dynamic contact angle for drops on the inclined surface, a significant number of numerical drop profiles on the inclined surface with different inclination angles, drop volumes, and contact angles are generated based on the finite difference method, a least-squares ellipse-fitting algorithm is used to calculate the dynamic contact angle. The influences of the above three factors are systematically investigated. The results reveal that the dynamic contact angle errors, including the errors of the left and right contact angles, evaluated by the ellipse-fitting algorithm tend to increase with inclination angle/drop volume/contact angle. If the drop volume and the solid substrate are fixed, the errors of the left and right contact angles increase with inclination angle. After performing a tremendous amount of computation, the critical dimensionless drop volumes corresponding to the critical contact angle error are obtained. Based on the values of the critical volumes, a highly accurate dynamic contact angle algorithm is proposed and fully validated. Within nearly the whole hydrophobicity range, it can decrease the dynamic contact angle error in the inclined plane method to less than a certain value even for different types of liquids.

An algorithm for selecting the most accurate protocol for contact angle measurement by drop shape analysis

In this study, an error analysis is performed to study real water drop images and the corresponding numerically generated water drop profiles for three widely used static contact angle algorithms: the circle- and ellipse-fitting algorithms and the axisymmetric drop shape analysis-profile (ADSA-P) algorithm. The results demonstrate the accuracy of the numerically generated drop profiles based on the Laplace equation. A significant number of water drop profiles with different volumes, contact angles, and noise levels are generated, and the influences of the three factors on the accuracies of the three algorithms are systematically investigated. The results reveal that the above-mentioned three algorithms are complementary. In fact, the circle- and ellipse-fitting algorithms show low errors and are highly resistant to noise for water drops with small/medium volumes and contact angles, while for water drop with large volumes and contact angles just the ADSA-P algorithm can meet accuracy requirement. However, this algorithm introduces significant errors in the case of small volumes and contact angles because of its high sensitivity to noise. The critical water drop volumes of the circle- and ellipse-fitting algorithms corresponding to a certain contact angle error are obtained through a significant amount of computation. To improve the precision of the static contact angle measurement, a more accurate algorithm based on a combination of the three algorithms is proposed. Following a systematic investigation, the algorithm selection rule is described in detail, while maintaining the advantages of the three algorithms and overcoming their deficiencies. In general, static contact angles over the entire hydrophobicity range can be accurately evaluated using the proposed algorithm. The ease of erroneous judgment in static contact angle measurements is avoided. The proposed algorithm is validated by a static contact angle evaluation of real and numerically generated water drop images with different hydrophobicity values and volumes.

[The effects of different glucose feeding modes on hEGF production in an excretory recombinant Escherichia coli K12 system]

The effects of different glucose feeding modes on hEGF expression were evaluated in an excretory recombinant E. coli K12 system. The results showed that, compared with batch cultivation, the plasmid stability and density of plasmid-retaining cells were improved by all three glucose feeding modes (intermittent, pH-stat and constant-rate). It was shown that hEGF yields were improved up to 25.5% and 28.1% by intermittent or pH-stat glucose feeding respectively. Especially, up to 150% improvement of hEGF production was achieved by constant feeding of 200 g/L glucose solution at a rate of 0.11 mL/min. The effects of further combined feeding with other medium components (ampicillin, nitrogen sources, and inorganic salts) and inducer on hEGF yield were also examined in the bench-top fermentor.