To design and develop artificial intelligence (AI) hydrocephalus (HYC) imaging diagnostic model using a transfer learning algorithm and evaluate its application in the diagnosis of HYC by non-contrast material-enhanced head computed tomographic (CT) images.
A training and validation dataset of non-contrast material-enhanced head CT examinations that comprised of 1000 patients with HYC and 1000 normal people with no HYC accumulating to 28,500 images. Images were pre-processed, and the feature variables were labeled. The feature variables were extracted by the neural network for transfer learning. AI algorithm performance was tested on a separate dataset containing 250 examinations of HYC and 250 of normal. Resident, attending and consultant in the department of radiology were also tested with the test sets, their results were compared with the AI model.
Final model performance for HYC showed 93.6% sensitivity (95% confidence interval: 77%, 97%) and 94.4% specificity (95% confidence interval: 79%, 98%), with area under the characteristic curve of 0.93. Accuracy rate of model, resident, attending, and consultant were 94.0%, 93.4%, 95.6%, and 97.0%.
AI can effectively identify the characteristics of HYC from CT images of the brain and automatically analyze the images. In the future, AI can provide auxiliary diagnosis of image results and reduce the burden on junior doctors.
Pavements always play a predominant role in transportation. Health monitoring of pavements is becoming more and more significant, as frequently suffering from cracks, rutting, and slippage renders them prematurely out of service. Effective and reliable sensing elements are thus in high demand to make prognosis on the mechanical properties and occurrence of damage to pavements. Therefore, in this paper, various types of functionality enhancement of industrialized optical fiber sensors for pavement monitoring are developed, with the corresponding operational principles clarified in theory and the performance double checked by basic experiments. Furthermore, a self-healing optical fiber sensing network system is adopted to accomplish full-scale monitoring of pavements. The application of optical fiber sensors assembly and self-healing network system in pavement has been carried out to validate the feasibility. It has been proved that the research in this article provides a valuable method and meaningful guidance for the integrity monitoring of civil structures, especially pavements.
Temperature distribution is a critical indicator of the health condition for Liquefied Petroleum Gas (LPG) storage tanks. In this paper, we present a large-scale wireless temperature monitoring system to evaluate the safety of LPG storage tanks. The system includes wireless sensors networks, high temperature fiber-optic sensors, and monitoring software. Finally, a case study on real-world LPG storage tanks proves the feasibility of the system. The unique features of wireless transmission, automatic data acquisition and management, local and remote access make the developed system a good alternative for temperature monitoring of LPG storage tanks in practical applications.
Forkhead box (FOX) proteins are multifaceted transcription factors that have been shown to be involved in cell cycle progression, proliferation and metastasis. FOXP4, a member of the FOX family, has been implicated in diverse biological processes in tumor initiation and progression. However, the molecular mechanisms of FOXP4 in laryngeal squamous cell carcinoma (LSCC) remain unknown. In the present study, differentially expressed transcripts in transforming growth factor-β-treated TU177 cells were screened using microarrays and it was found that FOXP4 was significantly upregulated. The high expression of FOXP4 was detected in LSCC tissues and cells, and predicted poor prognosis. The role of FOXP4 in laryngeal cancer cell proliferation, migration and invasion was determined by gain- and loss-of-function assays. Besides, FOXP4 was demonstrated to participate in the epithelial-mesenchymal transition process at the mRNA and protein levels. Mechanically, FOXP4 directly bound to the promoter of lymphoid enhancer-binding factor 1 and activated Wnt signaling pathway, which was confirmed via chromatin immunoprecipitation and luciferase reporter assays. Consequently, these findings provided novel mechanisms of FOXP4 in LSCC progression, which may be considered as potential therapeutic and prognostic targets for LSCC.
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