Plasma versican and plasma exosomal versican as potential diagnostic markers for non-small cell lung cancer.

BACKGROUND AND AIMS: This study aimed to investigate the expression of plasma versican and plasma exosomal versican in non-small cell lung cancer (NSCLC) and its correlation with clinicopathological features, and to evaluate its diagnostic performance in NSCLC and its predictive function for NSCLC incidence and metastasis risk. MATERIALS AND METHODS: There were 110 instances of NSCLC, 42 cases of benign lung disease, and 55 healthy controls from September 2018 to October 2020 at Tongji Hospital Affiliated to Tongji University. Blood was collected and plasma was separated before surgery, and plasma exosomes were extracted by ExoQuick kit. Morphological and molecular phenotype identification of exosomes was performed by transmission electron microscopy, Nanosight particle tracking analysis, and western blotting. Plasma versican and plasma exosomal versican were detected in all subjects to assess their expression levels and diagnostic value in NSCLC. Clinicopathological data were collected to explore correlations between abnormal plasma versican and plasma exosomal versican expression and clinicopathological parameters. Receiver operating characteristic (ROC) curve was used to judge its diagnostic performance in NSCLC, and binary logistic regression analysis was used to predict the risk of NSCLC incidence and metastasis. RESULTS: Plasma versican and plasma exosomal versican expression in NSCLC patients was significantly upregulated and was significantly higher in T3 + T4 patients compared with T1 + T2 patients (P < 0.05); the levels of plasma versican and plasma exosomal versican were positively correlated with lymph node metastasis, distant metastases (e.g., brain, bone), and mutation(e.g., EGFR,ALK)in NSCLC patients (all P < 0.05). Furthermore, ROC curve analysis showed that plasma versican and plasma exosomal versican had higher AUC values than NSE, CYFRA21-1, and SCC, and better diagnostic performance in NSCLC patients. However, the AUC and diagnostic performances of plasma versican and plasma exosomal versican in advanced-stage NSCLC patients were not shown to be significantly better than CEA. The results of binary logistic regression analysis showed that high levels of plasma exosomal versican had higher predictive value for lung cancer incidence, while high levels of plasma versican had higher predictive value for lung cancer metastasis. CONCLUSION: Our findings showed that plasma versican and plasma exosomal versican might be potential diagnostic markers for NSCLC. High plasma exosomal versican expression can be used as a predictor of NSCLC risk and high plasma versican expression can be used as a predictor of NSCLC metastasis risk.

Is early time to positivity of blood culture associated with clinical prognosis in patients with Klebsiella pneumoniae bloodstream infection?

The association between time to positivity (TTP) of blood culture and the clinical prognosis of patients with Klebsiella pneumoniae bloodstream infection (BSI) remains unclear. A retrospective study of 148 inpatients with BSI caused by K. pneumoniae was performed at Shanghai Tongji Hospital, China, from October 2016-2020. The total in-hospital fatality rate was 32%. The median TTP was 11.0 (7.7-16.1) h and the optimal cutoff for prediction of in-hospital mortality was 9.4 h according to the ROC curve. Early TTP (<9.4 h) was a risk factor for in-hospital mortality by univariate analysis (OR = 2.5, 95% CI 1.2-5.0, P = 0.01), but not by multivariate analysis (OR = 2.7, 95% CI 1.0-7.4, P = 0.06). Old age, serum creatinine, white blood cells, and C-reactive protein values were risk factors for in-hospital mortality by multivariate analysis. Early TTP was not a risk factor for septic shock (OR = 1.8, 95% CI 0.6-5.1, P = 0.27) or ICU admission (OR = 1.0, 95% CI 1.0-1.0, P = 0.32). In conclusion, the in-hospital fatality rate of patients with K. pneumoniae BSI was relatively high and associated with an early TTP of blood cultures. However, no increased risk of mortality, septic shock or ICU admission was evident in early TTP patients.

Side-Scan Sonar Image Segmentation Based on Multi-Channel CNN for AUV Navigation.

The AUV (Autonomous Underwater Vehicle) navigation process relies on the interaction of a variety of sensors. The side-scan sonar can collect underwater images and obtain semantic underwater environment information after processing, which will help improve the ability of AUV autonomous navigation. However, there is no practical method to utilize the semantic information of side scan sonar image. A new convolutional neural network model is proposed to solve this problem in this paper. The model is a standard codec structure, which extracts multi-channel features from the input image and then fuses them to reduce parameters and strengthen the weight of feature channels. Then, a larger convolution kernel is used to extract the features of large-scale sonar images more effectively. Finally, a parallel compensation link with a small-scale convolution kernel is added and spliced with features extracted from a large convolution kernel in the decoding part to obtain features of different scales. We use this model to conduct experiments on self-collected sonar data sets, which were uploaded on github. The experimental results show that ACC and MIoU reach 0.87 and 0.71, better than other classical small-order semantic segmentation networks. Furthermore, the 347.52 g FOLP and the number of parameters around 13 m also ensure the computing speed and portability of the network. The result can extract the semantic information of the side-scan sonar image and assist with AUV autonomous navigation and mapping.

Path Planning in Localization Uncertaining Environment Based on Dijkstra Method.

Path planning obtains the trajectory from one point to another with the robot's kinematics model and environment understanding. However, as the localization uncertainty through the odometry sensors is inevitably affected, the position of the moving path will deviate further and further compared to the original path, which leads to path drift in GPS denied environments. This article proposes a novel path planning algorithm based on Dijkstra to address such issues. By combining statistical characteristics of localization error caused by dead-reckoning, the replanned path with minimum cumulative error is generated with uniforming distribution in the searching space. The simulation verifies the effectiveness of the proposed algorithm. In a real scenario with measurement noise, the results of the proposed algorithm effectively reduce cumulative error compared to the results of the conventional planning algorithm.

Underwater Localization and Mapping Based on Multi-Beam Forward Looking Sonar.

SLAM (Simultaneous Localization And Mapping) plays a vital role in navigation tasks of AUV (Autonomous Underwater Vehicle). However, due to a vast amount of image sonar data and some acoustic equipment's inherent high latency, it is a considerable challenge to implement real-time underwater SLAM on a small AUV. This paper presents a filter based methodology for SLAM algorithms in underwater environments. First, a multi-beam forward looking sonar (MFLS) is utilized to extract environmental features. The acquired sonar image is then converted to sparse point cloud format through threshold segmentation and distance-constrained filtering to solve the calculation explosion issue caused by a large amount of original data. Second, based on the proposed method, the DVL, IMU, and sonar data are fused, the Rao-Blackwellized particle filter (RBPF)-based SLAM method is used to estimate AUV pose and generate an occupancy grid map. To verify the proposed algorithm, the underwater vehicle is equipped as an experimental platform to conduct field tasks in both the experimental pool and wild lake, respectively. Experiments illustrate that the proposed approach achieves better performance in both state estimation and suppressing divergence.

PLAC8 inhibits oral squamous cell carcinogenesis and epithelial-mesenchymal transition via the Wnt/ß-catenin and PI3K/Akt/GSK3ß signaling pathways.

Placenta-specific 8 (PLAC8) is closely associated with the proliferation, apoptosis and autophagy of several tumor cells. However, the expression and function of PLAC8 in oral squamous cell carcinoma (OSCC) remain unknown. Therefore, the present study investigated the function and mechanism of PLAC8 in OSCC. Reverse transcription-quantitative PCR and western blot analyses were performed to quantify the expression of PLAC8 in OSCC cell lines. The function of PLAC8 in OSCC was investigated via transfection, the Transwell and Cell Counting Kit-8 assays, immunofluorescence staining and western blotting. The results demonstrated that PLAC8 exspression was downregulated in OSCC cell lines. PLAC8 inhibited the cell proliferation in OSCC. In addition, PLAC8 restrained invasion and epithelial-mesenchymal transition of OSCC cells. Furthermore, ß-catenin helped to repress PLAC8 expression by regulating the Wnt/ß-catenin and PI3K/Akt/GSK3ß signaling pathways in OSCC cells. Collectively, the results of the present study suggest that PLAC8 acts as a tumor suppressor in OSCC by downregulating ß-catenin.

Plasma Exosomal miRNA-139-3p is a Novel Biomarker of Colorectal Cancer.

Objectives: This study investigated plasma exosomal miRNA-139-3p as a blood-based biomarker for the early diagnosis and metastasis monitoring of colorectal cancer (CRC). Patients and Methods: Exosome-rich fractions were isolated from the plasma of 80 CRC patients, and 23 controls using a kit method. We then used real-time polymerase chain reaction (RT-qPCR) to detect miR-139-3p levels in all subjects to evaluate expression levels and the predictive value of plasma exosomal miR-139-3p in CRC. We also collected clinicopathological data to explore correlations between abnormal miR-139-3p expression and clinicopathological parameters. Results: When compared with healthy controls, exosomal miR-139-3p expression levels in CRC patients were significantly down-regulated. Furthermore, these expression levels were lower in metastatic colorectal cancer (mCRC) and submucosal patients. Receiver operating characteristic (ROC) curve analysis showed that exosomal miR-139-3p levels were differentiated between CRC patients and healthy controls, as well as between non-metastatic and metastatic patients. Conclusion: Our findings show that decreased exosomal miR-139-3p expression levels in CRC patient plasma may act as a novel biomarker for the early diagnosis and metastasis monitoring in CRC.

The value of red blood cell distribution width in diagnosis of patients with colorectal cancer.

BACKGROUND: Red blood cell distribution width (RDW) is a parameter of standard full blood count tests that reflects the size variability of erythrocytes In recent studies, RDW levels have been associated with ischemic heart disease, acute and chronic heart failure, hypertension, and inflammatory bowel disease. However, it is unclear whether RDW is associated with colorectal cancer. METHODS: Eighty-five patients were diagnosed with colorectal cancer. Fifty-four other patients each diagnosed with colon polyps during the same period served as the control group. The patients were classified according to the seventh edition of the AJCC Cancer Staging Manual of 2009 into groups of different cancer stages, and simultaneously divided into groups with or without metastasis. The multigroup metering data was tested by a non-parametric Kruskal-Wallis H test, and the two subsets of patients formed above were compared using a Mann-Whitney U test. The association between continuous variables was assessed by Spearman correlation analysis while the association between RDW and colorectal cancer metastasis was estimated by receiver operating characteristic (ROC) curve analysis. RESULTS: Increased RDW was observed in patients with colorectal cancer. The RDW was significantly different for each subgroup of colorectal cancer as follows: stage III + IV > stage III, T3 + T4 > T1 + T2, N1 + N2 > N0, and M1 > M0 (P < 0.05). The area under the receiver-operating characteristic curve of the RDW in the diagnosis of colorectal cancer metastasis was 0.721 (95% confidence interval of 0.612-0.831). CONCLUSIONS: The value of RDW is closely related to colorectal cancer metastasis.