Search

Objective To investigate the expression and clinical significance of TM9SF3 in lung adenocarcinoma (LUAD). Methods TCGA and GEPIA databases were used to screen the differentially-expressed TM9SF family molecules and analyze their effects on patient prognosis with LUAD. The expression and localization of TM9SF3 in LUAD patients were verified by a human proteomic mapping database, Western blot assay, and polymerase chain reaction assay. Herein, the GSEA was used for the signal pathway enrichment analysis of TM9SF3-related genes. Meanwhile, the TIMER database and CIBERSORT algorithm were used to analyze the correlation between differentially-expressed TM9SF3 and the degree of immune cell infiltration. Results The expression of TM9SF3 in LUAD was significantly increased and had a significant adverse effect on the prognosis of LUAD patients. In addition, immunoblotting and polymerase chain reaction confirmed that TM9SF3 was highly expressed in LUAD. Meanwhile, the genes related to TM9SF3 expression were mainly enriched in cell signaling pathways regulating immune cell activity. The expression of TM9SF3 was significantly correlated with the expression changes of six immune cells. Conclusion TM9SF3 is differentially expressed in LUAD and may be used as a potential prognostic marker for LUAD patients. TM9SF3 can also change the level of immune cell infiltration in LUAD patients and is expected to be a new potential target for LUAD immunotherapy.

This study discusses the narrative strategy of medical documentary and aims to analyze how its narrative technique promotes the effectiveness of health communication to the masses. This study takes Depression and Me as an example, using literature and text analysis. Based on Genette's narratology theory, this medical documentary is analyzed from the aspects of narrative speech and transformed speech in narrative discourse as well as internal focalization (fixed internal focalization and multiple internal focalization) in narrative focalization. It is found that the narrative mode of this documentary is conducive to generating emotional resonance with the audience, thereby improving the public's understanding of depression, and achieving the effect of health communication. However, this study also has problems with sample limitations and subjective interpretation, as well as limitations of data collection methods.

Carbon nanotubes (CNTs) were synthesized by floating catalyst chemical vapor deposition (FCCVD) reactions. The complicated processing parameters that included a precursor solution composition, reaction temperature, flow rate of the carrier gas, weak oxidants, and injection rate of the precursor solution were controlled to synthesize single‐walled carbon nanotubes (SWCNTs) during the reaction process. The effects of the processing parameters were analyzed with respect to the formation of SWCNTs, yield, and the crystallinity in the CNTs structure. The SWCNTs were characterized by the Raman spectroscopy, scanning electron microscope, high‐resolution transmission electron microscopy, and thermogravimetric analysis. A high reaction temperature, high H2 flow rate, low injection rate of solution precursor, and low concentrations of iron catalysts in the reaction were important factors to improve the crystalline quality of the SWCNTs. The purity of the initial product grown by the standard process was more than 90 wt %, with a yield of 0.5 g/h. The average G/D ratio of the initial product was 178, and it had a distinct RBM peak. HRTEM confirmed that the synthesized SWCNTs had high purity and crystallinity. The SWCNTs could be tunable to meet a particular application by varying the reaction conditions. [ABSTRACT FROM AUTHOR]

Purpose: Arthroscopic Bankart repair combined with remplissage and autologous scapular spine bone grafting have been described as a treatment for off‐track Hill–Sachs lesions with subcritical glenoid bone defects in the anterior shoulder instability. However, whether these two techniques can achieve satisfactory postoperative outcomes is unclear, and there are few comparative studies between them. Therefore, this study compared the postoperative efficacy of the two techniques for off‐track Hill–Sachs lesions with subcritical glenoid bone loss. Method: Between June 2017 and December 2020, 62 patients with shoulder instability due to Off‐Track Hill–Sachs lesions with subcritical glenoid bone loss underwent surgical treatment and were included in this regression study. Thirty‐two patients underwent arthroscopic Bankart repair combined with remplissage (B + R group), and 30 patients underwent additional autologous scapular glenoid bone grafting (additional bone grafting group). The general information of the patients was recorded. The patient's activity before and after surgery was recorded. The DASH score and Constant–Murley (CM) score were used to assess the patient's functional status; the Rowe score was used to evaluate the patient's shoulder stability. The shoulder function and stability before and after surgery were analyzed and compared between the two groups. Results: The final DASH scores of the B + R group and the additional bone grafting group were significantly lower than those before surgery, with a statistically significant difference (9.76 ± 4.32 vs. 27.89 ± 6.63, 8.50 ± 3.32 vs. 28.0 ± 4.27, p = 0.000); the final CM scores of the two groups were significantly higher than those before surgery (88.71 ± 3.74 vs. 73.68 ± 3.74, 87.16 ± 2.29 vs. 71.37 ± 2.68, p = 0.000). There was no statistical difference in the final DASH score and final CM score between the two groups (p > 0.05). In terms of postoperative stability, the final Rowe scores of the two groups were significantly higher than those before surgery, with a statistically significant difference (89.06 ± 9.19 vs. 41.71 ± 4.13; 93.16 ± 4.99 vs. 42.33 ± 2.53, p = 0.000). Compared with the control group, the additional bone graft group achieved higher final Rowe scores (93.16 ± 4.99 vs. 89.06 ± 9.19, p = 0.032). Conclusion: For patients with anterior shoulder instability due to off‐track Hill–Sachs lesions with subcritical glenoid bone loss, although Bankart and remplissage can achieve satisfactory clinical results, additional autogenous scapular spine bone grafting can provide better stability of the shoulder, especially for patients with high sports demands. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a new well‐structured emerging technology with communication of smart devices using the 5G technology, infrastructures of roads, vehicles, smart cities, traffic systems and user applications. The IoT applications facilitate providing prompt emergency responses, and improved quality of vehicles, and road services, with cost‐effective activities in the intelligent transportation systems. Federated Learning (FL) enhances privacy and security in intelligent transportation systems and the Internet of Vehicles (IoV), using advanced prediction methods. Integrating blockchain with IoT, particularly in FL for transportation systems and IoV, bolsters security and data integrity. This approach keeps data local while only sharing model updates, enhancing privacy. Blockchain's transparency aids in efficient IoT collaboration, crucial for accountability. Its consensus algorithms further ensure network integrity, validating transactions and updates across devices, protecting against attacks, and fostering a transparent, collaborative environment. This comprehensive review paper delves into the innovative integration of blockchain technology with federated learning and the dynamic domain of IoV. It extensively analyzes the primary concepts, methodologies, and challenges associated with the deployment of FL in IoVs. This review presents a novel categorization examining three main types of blockchain‐based FL approaches vertical, horizontal, and decentralized each tailored to specific IoV communication scenarios like Vehicle‐to‐Vehicle (V2V), Vehicle‐to‐Infrastructure (V2I), and Vehicle‐to‐Cloud (V2C). It highlights FL applications in cyber‐attack detection, data sharing, traffic prediction, and privacy, considering Quality of Service factors. Finally, some main challenges and new open issues are discussed and assessed for federated machine learning approaches in the IoV. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) necessitates secure communication and high availability among objects at the network edge to ensure reliable object-to-object transactions. In the IoT networks, despite resource limitations, especially at the edge of the network, the potential for error is high. Therefore, a mechanism to increase the reliability, lifetime, and stability of the network is necessary. In this paper, we introduce a trust evaluation framework based on a reliability-based friendly relationship method in IoT networks. We present a conceptual trust model that captures the overall performance of the IoT social network based on parameters such as nodes' communication history experiences. Trust in the IoT network is built upon a harmonious communication environment that aligns with the trustworthiness of each object and its ability to maintain continuous interactions. We propose an empirical Trust Indicator (TI) that captures individual agents' experiences in IoT groups, considering the results of system executions, current experience values, and timestamps of interactions. Mathematical models are developed to analyze the dynamics of trust, including trust increase through increased reliability and collaborative interactions and trust decay due to non-cooperative interactions and lack of communication. The model parameters in IoT groups through simulation show that in this system based on the level of reliability and its increase or decrease, its direct effect can be evaluated by quantitative measurement of mean time to failure (MTTF), which is a measure of devices trust and the network itself. [ABSTRACT FROM AUTHOR]

The degradation of the pretightening state of bolts is a multistage process. Utilising a single model to monitor the pretightening state in the full degradation stage and continuously updating the monitoring model is important. Therefore, a quantitative monitoring method for the pretightening state of bolts based on nonlinear Lamb waves and incremental learning is proposed. In the proposed method, phase reversal technology is first adopted to enhance the sensitivity for bolt loosening, and then a relative nonlinear coefficient based on phase reversal (RCP) is constructed. The disadvantage that linear indicators are insensitive to early loosening is overcome and the critical points of the multidegradation process are identified by this indicator, the tight contact stage (TCS) and the significant loosening stage. After the TCS is determined, a quantitative monitoring model, which fuses seven nonlinear damage indexes, is established based on incremental canonical correlation forests (ICCF). This algorithm achieves incremental learning by continuously increasing the number of decision trees. To verify the effectiveness of the method, an experimental study is carried out on four bolts. The monitoring effects of different indicators show that the method has higher accuracy and retains the ability to dynamically update data. [ABSTRACT FROM AUTHOR]

Background: The primary cause of cancer‐related fatalities globally is lung cancer. Although the chemotherapy drug cisplatin (DDP) has brought certain benefits to patients, the rapid development of drug resistance has greatly hindered treatment success. Methods: We used the lung squamous cell carcinoma (LUSC) mRNA data set to explore the differentially expressed gene (RND1) in LUSC and detected RND1 expression in LUSC cells and DDP‐resistant cells by qRT‐PCR. Meanwhile, we performed abnormal expression treatment on RND1 and conducted CCK8, colony formation, and flow cytometry to evaluate the impact of RND1 expression on cell proliferation, apoptosis, and DDP resistance. In addition, we analyzed metabolism pathways involving RND1 using GSEA. We also used online tools such as hTFtarget and JASPAR to screen for the upstream transcription factor FOXA2 of RND1 and verified their relationship through CHIP and dual luciferase experiments. Finally, we validated the role of FOXA2‐RND1 in DDP resistance in LUSC through the above experiments. Results: RND1 was downregulated in LUSC, and overexpression of RND1 repressed proliferation and DDP resistance of LUSC cells and facilitated cell apoptosis. RND1 modulated the arachidonic acid (AA) metabolism pathway, and FOXA2 positively manipulated RND1 expression. By activating FOXA2, stabilizing RND1, and regulating AA levels, the sensitivity of LUSC cells to DDP could be enhanced. Conclusion: Our study suggested that FOXA2 positively modulated the RND1‐AA pathway, which repressed the resistance of LUSC cells to DDP. [ABSTRACT FROM AUTHOR]