CPE correlates with poor prognosis in gastric cancer by promoting tumourigenesis.

Aims: To investigate the potential functions and mechanisms of tumourigenesis in carboxypeptidase E (CPE) and its prognostic value in gastric cancer, and to develop a predictive model for prognosis based on CPE. Results: Transcriptome level variation and the prognostic value of CPE in different types of cancers were investigated using bioinformatics analyses. The association between CPE and clinicopathological characteristics was specifically explored in gastric cancer. Elevated CPE expression was associated with poor survival and recurrence prognosis and was found in cases with a later clinical stage of gastric cancer. The CPE was considered an independent prognostic factor, as assessed using Cox regression analysis. The prognostic value of CPE was further verified through immunohistochemistry and haematoxylin staining. Enrichment analysis provided a preliminary confirmation of the potential functions and mechanisms of CPE. Immune cell infiltration analysis revealed a significant correlation between CPE and macrophage infiltration. Eventually, a prognosis prediction nomogram model based on CPE was developed. Conclusion: CPE was identified as an independent biomarker associated with poor prognosis in gastric cancer. This suggests that CPE overexpression promoted epithelial-mesenchymal transition via the activation of the Erk/Wnt pathways, leading to proliferation, invasion, and metastasis. Targeted therapeutic strategies for gastric cancer may benefit from these findings.

[Determination of multiple residual solvents in ibandronate sodium using headspace-gas chromatography].

Ibandronate sodium, a third-generation diphosphate drug used worldwide to treat osteoporosis, has the advantages of convenient use, low toxicity, and significant therapeutic effects. However, the residual organic solvents in the synthesis process of sodium ibandronate not only have a negative impact on the efficacy of the drug, but also lead to a decrease in drug stability. Moreover, if the residual amounts of these solvents exceed safety standards, they may pose serious threats to human health. This study successfully established a convenient and efficient method based on headspace-gas chromatography (HS-GC) for the simultaneous determination of five residual solvents (methanol, acetone, benzene, toluene, 1-pentanol) in the raw materials of ibandronate sodium. The results indicated that satisfactory analytical performance can be achieved by using DB-624 capillary column (30 m×0.32 mm×1.8 µm) and a flame ionization detector in conjunction with headspace autosampling and a temperature program. The specific operating conditions included an initial temperature of 40 ℃, with a hold of 2 min, followed by a temperature ramp first to 200 ℃ at a rate of 5 ℃/min and then to 240 ℃ at a rate of 20 ℃/min, with a hold of 5 min. Nitrogen with a flow rate of 1 mL/min and split ratio of 14∶1 was used as the carrier gas. The headspace vial temperature was maintained at 80 ℃, and the sample equilibration time was 20 min. Under the established analytical conditions, good linear relationships were obtained between the mass concentrations of methanol (72-216 µg/mL), acetone (120-360 µg/mL), benzene (0.048-0.144 µg/mL), toluene (21.36-64.08 µg/mL), and 1-pentanol (120-360 µg/mL) and their corresponding peak areas, with correlation coefficients (r) greater than 0.990. The limits of detection for these solvents were 2.88, 0.011, 0.90, 0.24, and 0.024 ng/mL, respectively, with limits of quantification of 11.5, 0.043, 3.6, 0.96, and 0.096 ng/mL, respectively. Furthermore, the recoveries of these solvents ranged from 86.3% to 101.9%, with relative standard deviations (RSDs, n=3) of less than 2.49%. The proposed method is simple, accurate, reliable, and suitable for the rapid and simultaneous determination of five residual solvents in the raw materials of ibandronate sodium. This study has important practical significance in improving drug safety and ensuring public health.

Changeable moving window-standard normal variable transformation for visible-NIR spectroscopic analyses.

Based on the assumption of point-by-point local linearity, the changeable moving window-standard normal variable (CMW-SNV) was proposed as a reasonable improvement of the classical SNV. The three examples of quantitative and qualitative visible-near-infrared (Vis-NIR) analysis, quantifications of soil organic matter and corn meal moisture, and discriminant of rice seeds identification, were used to validate the effects of the CMW-SNV, SNV and equal segmentation SNV (ES-SNV) methods. The ES-SNV is another improvement of the SNV, but its algorithm would cause artificial discontinuities of the corrected spectrum. The SNV, ES-SNV and CMW-SNV corrected spectra were used to establish partial least squares (PLS) or partial least squares-discriminant analysis (PLS-DA) models respectively. For soil and corn meal datasets in modeling, the CMW-SNV-PLS models were both significantly better than the global SNV-PLS models; the root mean square errors of prediction in modeling (SEPM) values had the relative decrease of 26.4% and 6.6% respectively. For rice seeds dataset in modeling, the CMW-SNV-PLS-DA model was significantly better than the global SNV-PLS-DA model; the total recognition-accuracy rates in modeling (RARM) value increased by 2.1%. For all three datasets, the CMW-SNV models were better than (or close to) ones of the ES-SNV models. The equidistant combination (EC) and wavelength step-by-step phase-out (WSP) methods were used to perform wavelength selection on the CMW-SNV corrected spectra, determining the optimal EC-WSP-PLS or EC-WSP-PLS-DA models. In independent validation of three datasets, the high precision and high recognition accuracy rates validation results were all obtained. The CMW-SNV was a localized natural improvement of the classic global SNV method, and its correction maintained continuity of the spectra. The number of wavelengths m of the correction window represented the scale of localized SNV, and the algorithm platform of CMW-SNV also included the optimization of parameter m, making the localized CMW-SNV method more reasonable.

Epstein-Barr virus-encoded miR-BART11-3p modulates the DUSP6-MAPK axis to promote gastric cancer cell proliferation and metastasis.

Epstein-Barr virus (EBV)-encoded miRNAs within the BamHI-A rightward transcript (BART) region are abundantly expressed in EBV-associated gastric cancer (EBVaGC), suggesting that they play roles in tumorigenesis. However, how these viral miRNAs contribute to the development of EBVaGC remains largely obscure. In this study, we found that EBV-encoded miR-BART11-3p targets 3' -UTR of dual-specificity phosphatase 6 (DUSP6) mRNA to upregulate ERK phosphorylation and downregulate JNK and p38 phosphorylation. By doing so, miR-BART11-3p promotes gastric cancer (GC) cell proliferation, migration, and invasion in vitro, and facilitates tumor growth in vivo. Restoration of DUSP6 expression reverses the tumor-promoting activity of miR-BART11-3p in AGS GC cells. Consistently, knockdown of DUSP6 ablates the antitumor effects of miR-BART11-3p inhibitors in EBV-positive GC cells. Furthermore, blocking ERK phosphorylation with trametinib inhibited the proliferation, migration, and invasion of miR-BART11-3p-expressing AGS cells. Administration of a miR-BART11-3p antagomir reduced the growth of EBV-positive xenograft tumors. Together, these findings reveal a novel mechanism by which EBV dysregulates MAPK pathways through an EBV-encoded microRNA to promote the development and progression of EBVaGC, which may be harnessed to develop new therapeutics to treat EBVaGC. IMPORTANCE The Epstein-Barr virus (EBV) is the first human tumor virus found to encode miRNAs, which within the BART region have been detected abundantly in EBV-associated gastric cancer (EBVaGC) and play various roles in promoting tumorigenesis. In our study, we observed that EBV-miR-BART11-3p promotes cell proliferation and induces migration and invasion in GC. Interestingly, we showed that miR-BART11-3p upregulates p-ERK and downregulates p-JNK and p-p38 by directly targeting 3'-UTR of dual-specificity phosphatase 6 (DUSP6). Restoration of DUSP6 rescues the effects generated by miR-BART11-3p in GC cells, and blocking ERK phosphorylation with Trametinib augments JNK and p38 phosphorylation and inhibits the effects of miR-BART11-3p-expressing AGS cells, suggesting that miR-BART11-3p promotes cell proliferation, migration, and invasion by modulating DUSP6-MAPK axis in EBVaGC. The findings presented in this study provide new mechanisms into the tumorigenesis in EBVaGC and new avenues for the development of therapeutic strategies to combat EBVaGC targeting miR-BART11-3p or phospho-ERK.

Tightly-coupled fusion of iGPS measurements in optimization-based visual SLAM.

The monocular visual Simultaneous Localization and Mapping (SLAM) can achieve accurate and robust pose estimation with excellent perceptual ability. However, accumulated image error over time brings out excessive trajectory drift in a GPS-denied indoor environment lacking global positioning constraints. In this paper, we propose a novel optimization-based SLAM fusing rich visual features and indoor GPS (iGPS) measurements, obtained by workshop Measurement Position System, (wMPS), to tackle the problem of trajectory drift associated with visual SLAM. Here, we first calibrate the spatial shift and temporal offset of two types of sensors using multi-view alignment and pose optimization bundle adjustment (BA) algorithms, respectively. Then, we initialize camera poses and map points in a unified world frame by iGPS-aided monocular initialization and PnP algorithms. Finally, we employ a tightly-coupled fusion of iGPS measurements and visual observations using a pose optimization strategy for high-accuracy global localization and mapping. In experiments, public datasets and self-collected sequences are used to evaluate the performance of our approach. The proposed system improves the result of absolute trajectory error from the current state-of-the-art 19.16mm (ORB-SLAM3) to 5.87mm in the public dataset and from 31.20mm to 5.85mm in the real-world experiment. Furthermore, the proposed system also shows good robustness in the evaluations.

CLK2 Expression Is Associated with the Progression of Colorectal Cancer and Is a Prognostic Biomarker.

Background: CLK2 is a splicing regulator and expressed ubiquitously in various malignancies. The study is aimed at exploring the potential roles of CLK2 in the development of colorectal cancer (CRC). Methods: Real-time PCR and analyses of The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) database were utilized to evaluate the CLK2 gene transcription level and protein level of colorectal cancer (CRC) tissue. The chi-squared and logistic regression tests were used to evaluate the relationship between CLK2 and clinicopathologic features. Kaplan-Meier survival curve and Cox regression analysis were performed to explore the prognostic significance of CLK2. The association between CLK2 expression and immune landscapes was explored by CIBERSORT and ESTIMATE. Furthermore, GSEA (Gene Set Enrichment Analysis) and alternative splicing (AS) analyses were performed to investigate the relationship between CLK2 expression and downstream signaling pathway. Results: The CLK2 expression was upregulated in CRC in both transcript and protein level. The elevated expression of CLK2 was correlated with local invasion and poor prognosis. Furthermore, CLK2 induced tumor cell adhesion and thereby promotes local invasion of CRC. The CLK2 expression significantly inhibited plasma cells and eosinophil infiltration and showed no relationship with immune and stromal scores of CRC samples. CLK2 might involve in Notch signaling pathway by regulating the AS of CTBP1. Conclusions: CLK2 might be a potential prognostic biomarker and therapeutic target for colorectal cancer.

Photoelectric scanning-based resection method for mobile robot localization.

Indoor localization is a key enabling technology for mobile robot navigation in industrial manufacturing. As a distributed metrology system based on multi-station intersection measurement, the workshop measurement positioning system (wMPS) is gaining increasing attention in mobile robot localization. In this paper, a new, to the best of our knowledge, wMPS-based resection localization method is proposed using a single onmidirectional transmitter mounted on a mobile robot with scanning photoelectric receivers distributed in the work space. Compared to the traditional method that requires multiple stationary transmitters, our new method provides higher flexibility and cost-effectiveness. The position and orientation of the mobile robot are then iteratively optimized with respect to the constraint equations. In order to obtain the optimal solution rapidly, two methods of initial value determination are presented for different numbers of effective receivers. The propagation of the localization uncertainty is also investigated using Monte-Carlo simulations. Moreover, two experiments of automated guided vehicle localization are conducted, and the results demonstrate the high accuracy of the proposed method.

Targeted Thrombolytic Therapy with Metal-Organic-Framework-Derived Carbon Based Platforms with Multimodal Capabilities.

A dual-response (near-infrared, alternating magnetic field) multifunctional nanoplatform was developed based on urokinase plasminogen activators (uPA)-loaded metal-organic-framework (MOF)-derived carbon nanomaterials (referred to uPA@CFs below) for thrombolytic therapy. uPA loaded in mesoporous CFs could be released under the action of near-infrared (NIR)-mediated photothermy to achieve superficial thrombolysis. More importantly, with the assistance of alternating magnetic field (AMF), this system could also precisely heat the thrombosis in the deep tissue area. Quantitative experiments proved that the thrombolytic efficiency of this dual-response system at deep venous thrombosis was nearly 6 times than that of NIR alone. This is the first application that MOF-derived carbon nanomaterials in the field of targeted thrombolysis. To our delight, the MOF-derived carbon nanomaterials (CFs) not only maintained the drug-carrying capacity, but also endowed CFs with reliable magnetic targeting ability. More encouragingly, the CFs also showed extraordinary angiogenic performance, thus opening up the prospect of its clinical application.

Analytical solution of uncertainty with the GUM method for a dynamic stereo vision measurement system.

Directed at the strong correlation among the input parameters and long measurement chain, which are difficult for uncertainty analysis with the guide of the expression of uncertainty in the measurement (GUM) method, a novel dynamic stereo vision measurement system based on the quaternion theory is presented to reduce the orthogonality restrictions of shafting manufacturing and application. According to the quaternion theory in the kinematic model of the cameras and the analytical solution of uncertainty with the GUM method, the complete, detailed, and continuous uncertainty results of the full-scale measurement space can be obtained. Firstly, one-dimensional turntables and rigid connections are utilized to form the motion cores and the automatic control carriers in the system. Secondly, the novel measurement model is used in the measurement process to shorten the calibration and measurement chains. Once the system based on the novel measurement model is set up, the analytical solution of uncertainty is utilized in the accuracy process. During the analysis process, the strong correlation among the extrinsic parameters is decoupled by introducing virtual circles and the measurement strategy with the GUM method. Through analyzing the relationship among the attitude angles, the major factors which influence the uncertainties in each axis and the final uncertainty are clarified. Moreover, the analytical continuous uncertainty maps for the uncertainties along each axis, combined standard uncertainty, and the expanded uncertainty are illustrated and the uncertainty variation tendency is declared. Finally, the analytical solution of uncertainty with the GUM method proposed in this paper predicts the uncertainty in the full-scale space and provides a new idea of the uncertainty analysis for the complicated combined measurement system.

A Framework for the Automatic Integration and Diagnosis of Building Energy Consumption Data.

Buildings account for a majority of the primary energy consumption of the human society, therefore, analyses of building energy consumption monitoring data are of significance to the discovery of anomalous energy usage patterns, saving of building utility expenditures, and contribution to the greater environmental protection effort. This paper presents a unified framework for the automatic extraction and integration of building energy consumption data from heterogeneous building management systems, along with building static data from building information models to serve analysis applications. This paper also proposes a diagnosis framework based on density-based clustering and artificial neural network regression using the integrated data to identify anomalous energy usages. The framework and the methods have been implemented and validated from data collected from a multitude of large-scale public buildings across China.

Absolute angular measurement with optical frequency comb using a dispersive interferometry.

We have demonstrated a simple method to measure high-precision absolute angular displacement using an optical frequency comb (OFC). The dispersive interferometry with parallel configuration can take advantage of its large non-ambiguity range and achieve absolute angular measurement in a large range. The influence factors of the angle accuracy, including the accuracy of optical path difference, the determination of absolute zero position and the correction of sine arm have been analyzed in detail. The angle comparison is performed with the autocollimator and multi-tooth indexing table. The angle accuracy can reach ±2 arcsec (k=2) in the range of 5°, which represents a good agreement with the Monte Carlo simulation. The proposed approach has potential to be extended to multi-degree-of-freedom measurement with a simple structure in future.

Automatic Guidance Method for Laser Tracker Based on Rotary-Laser Scanning Angle Measurement.

Laser-tracking measurement systems (laser tracker) have been playing a critical role in large-scale 3D high-precision coordinate measurement. However, the existing visual guidance of laser trackers is still limited by the disadvantages of operator-dependence, small-angle view field, time-consuming laser-guided process. This paper presents an automatic guidance method for laser trackers based on the rotary-laser scanning angle measurement technology. In this method, a special target consisting of six photoelectric receivers and a retroreflector is integrated into the rotary-laser scanning transmitter' coordinate systems. Real-time constraints calculated by the proposed method would provide the coordinates of the target in a laser tracker coordinates system for guidance. Finally, the experimental results verified the automatic re-establish of sightline can be realized in horizontal 360° angle field within tens of arc-seconds, and this method is robust against the fast movement of the target.

Bibliometric review of visual computing in the construction industry.

In the construction area, visuals such as drawings, photos, videos, and 3D models, play a significant role in the design, build and maintenance of a facility, bringing efficiency to generate, transfer, and store information. Advanced visual computing techniques facilitate the understanding of design contents, work plans, and other types of information shared in the construction industry. Automatic visual data collection and analysis provide many possibilities to the construction industry and a large number of works have investigated how visual computing can improve construction management processes and other problems in the construction area. However, a comprehensive literature review is needed. This study uses bibliometric approaches to review the works published to date, and analyses the development of knowledge, significant research results, and trends. The purpose of this study is to help newcomers to this research field understand knowledge structure and formulate research directions, thereby enhancing knowledge development. From this study, it can be concluded that computer vision is a key axis of improvement. Moreover, building information modeling, laser scanning, and other visualization-related techniques are also important in advancing the construction area.

Precision improvement in frequency scanning interferometry based on suppression of the magnification effect.

Frequency scanning interferometry (FSI) is a promising technique for absolute distance measurement and has been demonstrated in many industrial applications. However, in practice, the measurement precision is limited and sensitive to the variations of the measured distance while sweeping the optical frequency of the laser. The induced errors would be amplified by hundreds of times due to the magnification effect. In this paper, an incremental interferometer was established on the basic scheme of the FSI system for monitoring the variations of distance. The compensation could be achieved by multiplying the heterodyne signals from monitor and measurement interferometer without complex and time-costing data processing. The system performance has been verified by experiments for different kinds of vibrating targets. Finally, after compensation by suppression of the magnification effects, a measurement precision of 4.26 µm has been achieved in a range of 10 m.

Flexible calibration method for visual measurement using an improved target with vanishing constraints.

In this paper, an improved calibration method based on vanishing constraints is proposed for calculating the extrinsic parameters of cameras. First, we come up with a improved target based on the conventional target with two groups of orthogonal parallel lines. The novel target is composed of two groups of parallel lines with a certain angle range from 80° to 90°, which can reduce the difficulty of target production and the manufacturing cost. Furthermore, in the optimization process, we design a new function with a more robust penalty factor instead of using the experienced values to get the extrinsic parameters for the binocular vision sensors. Finally, on account of using the improved target and the novel optimiazation function, the proposed method is more flexible and robust compared with Zhang's method.

A Sub-Regional Calibration Method That Can Accomplish Error Compensation for Photoelectric Scanning Measurement Network.

In the measurement process of photoelectric scanning measurement network, the laser surface edge area has lower measurement accuracy than the middle area due to the geometrical distortions of the laser surface of the transmitter. This paper presents a sub-regional calibration method that can accomplish error compensation for the measurement system. Unlike the camera sub-regional calibration, the regional division and identification of the laser surface are more difficult. In this paper, the pitch angle in the transmitter coordinate frame of the spatial point was used as the basis for the division and identification of the laser surface. In the calibration process, the laser surface of the transmitter was divided into different regions and each region was calibrated independently, so that an intrinsic parameters database containing the intrinsic parameters of different regions could be established. Based on the database, the region identification and error compensation algorithm were designed, and comparison experiments were carried out. With the novel calibration method, the measurement accuracy of the system had an obvious upgrade, especially at the edges of the laser surface within a certain measurement area, which could enlarge the effective measurement area of the transmitter and would broaden and deepen the application fields of photoelectric scanning measurement network.

A Multi-Camera Rig with Non-Overlapping Views for Dynamic Six-Degree-of-Freedom Measurement.

Large-scale measurement plays an increasingly important role in intelligent manufacturing. However, existing instruments have problems with immersive experiences. In this paper, an immersive positioning and measuring method based on augmented reality is introduced. An inside-out vision measurement approach using a multi-camera rig with non-overlapping views is presented for dynamic six-degree-of-freedom measurement. By using active LED markers, a flexible and robust solution is delivered to deal with complex manufacturing sites. The space resection adjustment principle is addressed and measurement errors are simulated. The improved Nearest Neighbor method is employed for feature correspondence. The proposed tracking method is verified by experiments and results with good performance are obtained.

Construction of traceable absolute distances network for multilateration with a femtosecond pulse laser.

The traceable absolute distances network with multiple global targets for multilateration is developed with a femtosecond pulse laser. It is aiming to enhance the ability and flexibility of the coordinate measurement, especially to monitor the positions of distributed stations in real time for some critical industrial environments. Here, multi-target absolute distances are determined by the temporal coherence method simultaneously with the pulse-to-pulse interferometer. Besides, the performance of the proposed system is evaluated in detail by comparing with a conventional interferometer. The experimental results indicate that the accuracy of distances measurement could all reach the sub-micron level and could be traceable to the length standard. Furthermore, a simple scheme of multilateration is presented based on the developed network. The coordinate of the initial point of multiple beams is measured by cooperation with a laser tracker. The results of coordinate measurement show that these methods have the potential for further industrial applications.

A Novel Semi-Supervised Feature Extraction Method and Its Application in Automotive Assembly Fault Diagnosis Based on Vision Sensor Data.

The fault diagnosis of dimensional variation plays an essential role in the production of an automotive body. However, it is difficult to identify faults based on small labeled sample data using traditional supervised learning methods. The present study proposed a novel feature extraction method named, semi-supervised complete kernel Fisher discriminant (SS-CKFDA), and a new fault diagnosis flow for automotive assembly was introduced based on this method. SS-CKFDA is a combination of traditional complete kernel Fisher discriminant (CKFDA) and semi-supervised learning. It adjusts the Fisher criterion with the data global structure extracted from large unlabeled samples. When the number of labeled samples is small, the global structure that exists in the measured data can effectively improve the extraction effects of the projected vector. The experimental results on Tennessee Eastman Process (TEP) data demonstrated that the proposed method can improve diagnostic performance, when compared to other Fisher discriminant algorithms. Finally, the experimental results on the optical coordinate data proves that the method can be applied in the automotive assembly process, and achieve a better performance.

Stereo line-scan sensor calibration for 3D shape measurement.

The stereo line-scan sensor opens up new potentialities for 3D measurement owing to the ultra-high resolution and acquisition rate. Calibration is a crucial key technology for a stereo line-scan sensor. This paper presents a precise calibration method for the stereo line-scan sensor. Several reference points are installed onto the sensor's body as an intermediary. The calibration turns into a two-step process: calibrating the cameras in the laboratory prior to measurement and locating the sensor in an actual measurement field. A mobile apparatus that comprises a planar pattern and extra reference points is designed. By incorporating the apparatus in combination with an auxiliary instrument, an optimal calibration configuration is created by placing the apparatus into multiple positions. A robust algorithm is proposed to enhance the stability of the parameter estimation. The quality of the calibration method is experimentally tested, and the performance is further investigated. Experimental results demonstrate that the proposed method offers a practical solution to calibrate a stereo line-scan sensor for 3D shape measurement.