ABSTRACT
Background and Aims: Shear wave elastography is a potential method for evaluating peripheral neuropathy, but lacking reference values. The aim of this study was to measure tibial nerve stiffness in healthy individuals using shear wave elastography and to investigate the influencing factors of tibial nerve stiffness. Methods: Shear wave elastography of bilateral tibial nerves was performed in 50 healthy individuals 4 cm proximal to the medial malleolus. Mean shear modulus data of tibial nerves were obtained and recorded. Intra- and interobserver agreement were assessed using intraclass correlation coefficients. Differences among groups (grouped by laterality, sex, age, and body mass index) were analyzed with independent-samples t-tests and paired t-tests. Effect size (Cohen's d) was also calculated. Results: The intra-and interobserver agreement were moderate (intraclass correlation coefficient, 0.700-0.747) for all participants, and was poor (intraclass correlation coefficient, 0.265-0.088) in very thin people (body mass index <18.5 kg/m2). The shear wave elastography measurements of the tibial nerve did not show a significant difference between legs, sexes, or different age groups. Higher values of tibial nerve stiffness were found in thinner participants. Conclusions: Shear wave elastography is a method to evaluate the stiffness of peripheral nerves. The measurement results were likely influenced by body mass index of the participants.
ABSTRACT
Pine needle gall midge (T. japonensis), native to Japan, has become a serious invasive pest in South Korea and, more recently in 2006, in China. It was first discovered in Qingdao, Shandong Province, and has caused serious damage to local Pinus thunbergii. The insect's small size makes morphological-based identification difficult; therefore, molecular detection techniques are urgently needed for monitoring and preventing its further spread. At present, there is no simple and accurate field molecular identification tool. To solve this problem, a LAMP-based molecular diagnosis technology of T. japonensis was developed. Four LAMP primers were designed to specifically amplify T. japonensis DNA. Positive LAMP reactions usually produce amplification in one hour. The optimal incubation conditions for LAMP detection were determined with 4 LAMP primers for 60 min at 61 °C. The LAMP detection range of gDNA concentrations is wide, with a minimum detectable gDNA concentration of 300 fg. A non-destructive DNA-releasing procedure, HotSHOT "HS6", which could extract "crude DNA" for LAMP assay in 10 min, was used for larval and adult samples. Therefore, we established a LAMP-based rapid molecular identification method that can be applied in the monitoring and management of T. japonensis.
ABSTRACT
PURPOSE: In this study we aimed to leverage deep learning to develop a computer aided diagnosis (CAD) system toward helping radiologists in the diagnosis of SARS-CoV-2 virus syndrome on Lung ultrasonography (LUS). METHOD: A CAD system is developed based on a transfer learning of a residual network (ResNet) to extract features on LUS and help radiologists to distinguish SARS-CoV-2 virus syndrome from healthy and non-SARS-CoV-2 pneumonia. A publicly available LUS dataset for SARS-CoV-2 virus syndrome consisting of 3909 images has been employed. Six radiologists with different experiences participated in the experiment. A comprehensive LUS data set was constructed and employed to train and verify the proposed method. Several metrics such as accuracy, recall, precision, and F1-score, are used to evaluate the performance of the proposed CAD approach. The performances of the radiologists with and without the help of CAD are also evaluated quantitively. The p-values of the t-test shows that with the help of the CAD system, both junior and senior radiologists significantly improve their diagnosis performance on both balanced and unbalanced datasets. RESULTS: Experimental results indicate the proposed CAD approach and the machine features from it can significantly improve the radiologists' performance in the SARS-CoV-2 virus syndrome diagnosis. With the help of the proposed CAD system, the junior and senior radiologists achieved F1-score values of 91.33% and 95.79% on balanced dataset and 94.20% and 96.43% on unbalanced dataset. The proposed approach is verified on an independent test dataset and reports promising performance. CONCLUSIONS: The proposed CAD system reports promising performance in facilitating radiologists' diagnosis SARS-CoV-2 virus syndrome and might assist the development of a fast, accessible screening method for pulmonary diseases.
Subject(s)
COVID-19 , SARS-CoV-2 , Computers , Diagnosis, Computer-Assisted , Humans , UltrasonographyABSTRACT
We have successfully fabricated x(0.65PMN-0.35PT)-(1 - x)PZT (xPMN-PT-(1 - x)PZT), where x is 0.1, 0.3, 0.5, 0.7 and 0.9, thick films with a thickness of approximately 9 µm on platinized silicon substrate by employing a composite sol-gel technique. X-ray diffraction analysis and scanning electron microscopy revealed that these films are dense and creak-free with well-crystallized perovskite phase in the whole composition range. The dielectric constant can be controllably adjusted by using different compositions. Higher PZT content of xPMN-PT-(1 - x)PZT films show better ferroelectric properties. A representative 0.9PMN-PT-0.1PZT thick film transducer is built. It has 200 MHz center frequency with a -6 dB bandwidth of 38% (76 MHz). The measured two-way insertion loss is 65 dB.
