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BackgroundArtificial intelligence-assisted colonoscopy (AIAC) has been proposed and validated in recent years, but the effectiveness of clinic application remains unclear since it was only validated in some clinical trials rather than normal conditions. In addition, previous clinical trials were mostly concerned with colorectal polyp identification, while fewer studies are focusing on adenoma identification and polyps size measurement. In this study, we validated the effectiveness of AIAC in the clinical environment and further investigated its capacity for adenoma identification and polyps size measurement.MethodsThe information of 174 continued patients who went for coloscopy in Chongqing Rongchang District People’s hospital with detected colon polyps was retrospectively collected, and their coloscopy images were divided into three validation datasets, polyps dataset, polyps/adenomas dataset (all containing narrow band image, NBI images), and polyp size measurement dataset (images with biopsy forceps and polyps) to assess the competence of the artificial intelligence system, and compare its diagnostic ability with endoscopists with different experiences.ResultsA total of 174 patients were included, and the sensitivity of the colorectal polyp recognition model was 99.40%, the accuracy of the colorectal adenoma diagnostic model was 93.06%, which was higher than that of endoscopists, and the mean absolute error of the polyp size measurement model was 0.62 mm and the mean relative error was 10.89%, which was lower than that of endoscopists.ConclusionArtificial intelligence-assisted model demonstrated higher competence compared with endoscopists and stable diagnosis ability in clinical use.

Background: The advent of immune checkpoint inhibitors (ICIs) has revolutionized the treatment landscape for tumor patients, dramatically improving survival rate. However, patients treated with immunotherapy are inevitably at risk of immune-related adverse events (irAEs). Immune checkpoint inhibitor-related pneumonitis (ICI-P) is an important type of IrAEs with a potentially lethal risk, which should be given more attention. Diagnosis and timely treatment of ICI-P is challenging due to the lack of specificity of its clinical and radiological features. Besides, poor understanding of biological mechanisms of ICI-P has led to a lack of reliable biomarkers to identify patients at risk, limiting timely treatment and proper management of it. Case presentation: We presented longitudinal clinical features and successful treatment experience in a metastatic esophageal squamous cell carcinoma (ESCC) patient treated with immunochemotherapy followed by palliative radiotherapy for cervical lymph nodes who developed severe pneumonitis outside of the radiation field ten days after completion of radiotherapy suggestive of ICI-P. In addition, analysis of circulating biomarkers demonstrated an increase in platelet-to-lymphocyte ratio (PLR) and platelet-to-monocyte ratio (PMR), as well as the levels of CD4+T and CD8+T cells that tracked with the progression of ICI-P, and then decreased with corticosteroid treatment. Conclusions: Our data highlight the imaging manifestations associated with ICI-related pulmonary toxicity and describe the dynamics of the corresponding circulating markers. Although our results reveal that dynamic monitoring of PLR and PMR as well as the levels of CD4+T and CD8+T cells may predict the risk of ICI-P, further investigations are needed to elucidate the underlying molecular and biological mechanisms for better management of ICI-P. [ABSTRACT FROM AUTHOR]

Terahertz waves can be widely used for short‐range communication in complex indoor environments and non‐destructive object detection applications. Metasurfaces are widely used in terahertz sensing and communication devices because they can modulate terahertz waves in multiple dimensions. Metamaterial robot brain can utilize metasurfaces' powerful direct modulation ability to achieve sensing and communication functions. The metasurface devices realized based on Dynamic Heterogeneous Redundancy (DHR) architecture can improve the confidentiality and security of terahertz wave wireless communication. While the intrinsic ohmic loss and quality factor of usual metallic metamaterials are usually low, the concept of bound states in the continuum (BIC) has been proposed for stronger terahertz‐matter interactions. Among them, high‐order BICs are of interest because of their strong robustness to structural defects. Therefore, an aluminium‐graphene hybrid metasurface with high‐order BIC is proposed. We have the principle of excitation of high‐order BICs is investigated and creatively proposed with high robustness realized using the magnetical EIT effect. The robustness of the high‐order BIC is also utilized to design security hardware based on DHR architecture. The designed secure hardware can satisfy the demand for an intelligent robotic brain to the internal terahertz wave confidential wireless communication. [ABSTRACT FROM AUTHOR]

Abstract Fog‐based VANETs (Vehicular Ad hoc NETworks) is a new model with vehicular cloud and fog computing benefits. Fog‐based VANETs consist of a series of mobile nodes that are fully dynamic without any central management. These networks have some limitations due to the use of the mobile power source. There are many challenges in extending mobile‐based networks' life span. Many methods have been suggested to minimize the nodes' energy consumption and extend the network life. Also, some works have been developed for load‐balanced routing. Still, energy‐efficient routing and load balancing in VANETs are challenges. The purpose of this study is to present a suitable method based on energy awareness for load balancing in fog‐based VANETs using a hybrid optimization algorithm (employing ant colony optimization and artificial bee colony (ACO‐ABC)). The simulation results in the Network Simulator 2 (NS2) environment showed that as the number of nodes increased, the consumed amount of energy in the VANET is increased. Also, with the increasing number of tasks, load balancing by the proposed method has been improved. Finally, the simulation experiments showed that the proposed hybrid algorithm (ACO‐ABC) outperforms all other algorithms.