Search

The search for therapeutic options for lung cancer continues to advance, with rapid advances in the search for therapies to improve patient prognosis. At present, systemic chemotherapy, immune checkpoint inhibitor therapy, antiangiogenic therapy, and targeted therapy for driver gene positivity are available in the clinic. Common clinical treatments fail to achieve desired outcomes due to immunosuppression of the tumor microenvironment (TME). Tumor immune evasion is mediated by cytokines, chemokines, immune cells, and other cells such as vascular endothelial cells within the tumor immune microenvironment. Tumor-associated macrophages (TAMs) are important immune cells in the TME, inducing tumor angiogenesis, encouraging tumor cell proliferation and migration, and suppressing antitumor immune responses. Thus, TAM targeting becomes the key to lung cancer immunotherapy. This review focuses on macrophage phenotype, polarization mechanism, role in lung cancer, and advances in macrophage centric immunotherapies. [ABSTRACT FROM AUTHOR]

This paper proposes a highly sensitive and high-resolution resonant MEMS electrostatic field sensor based on electrostatic stiffness perturbation, which uses resonant frequency as an output signal to eliminate the feedthrough interference from the driving voltage. The sensor is composed of a resonator, driving electrode, detection electrode, transition electrode, and electrostatic field sensing plate. The working principle is that when there is an electrostatic field, an induction charge will appear at the surface of the electrostatic field sensing plate and induce electrostatic stiffness on the resonator, which will cause a resonant frequency shift. The resonant frequency is used as the output signal of the microsensor. The characteristics of the electrostatic field sensor are analyzed with a theoretical model and verified by finite element simulation. A device prototype is fabricated based on the Silicon on Insulator (SOI) process and tested under vacuum conditions. The results indicate that the sensitivity of the sensor is 0.1384 Hz / (kV / m) and the resolution is better than 10 V/m. [ABSTRACT FROM AUTHOR]

Background: Small intestinal neuroendocrine tumors (SI-NETs) are the most common neoplasms of the small bowel. The majority of tumors are located in the distal ileum with a high incidence of multiple synchronous primary tumors. Even though up to 50% of SI-NET patients are diagnosed with multifocal disease, the mechanisms underlying multiple synchronous lesions remain elusive. Methods: We performed whole genome sequencing of 75 de-identified synchronous primary tumors, 15 metastases, and corresponding normal samples from 13 patients with multifocal ileal NETs to identify recurrent somatic genomic alterations, frequently affected signaling pathways, and shared mutation signatures among multifocal SI-NETs. Additionally, we carried out chromosome mapping of the most recurrent copy-number alterations identified to determine which parental allele had been affected in each tumor and assessed the clonal relationships of the tumors within each patient. Results: Absence of shared somatic variation between the synchronous primary tumors within each patient was observed, indicating that these tumors develop independently. Although recurrent copy-number alterations were identified, additional chromosome mapping revealed that tumors from the same patient can gain or lose different parental alleles. In addition to the previously reported CDKN1B loss-of-function mutations, we observed potential loss-of-function gene alterations in TNRC6B, a candidate tumor suppressor gene in a small subset of ileal NETs. Furthermore, we show that multiple metastases in the same patient can originate from either one or several primary tumors. Conclusions: Our study demonstrates major genomic diversity among multifocal ileal NETs, highlighting the need to identify and remove all primary tumors, which have the potential to metastasize, and the need for optimized targeted treatments. [ABSTRACT FROM AUTHOR]

This paper proposes a novel wafer-level vacuum packaged electric field microsensor (EFM) featuring a high quality factor, low driving voltage, low noise, and low power consumption. The silicon-on-insulator (SOI) conductive handle layer was innovatively used as the sensing channel to transmit the external electric field to the surface of the sensitive structure, and the vacuum packaging was realized through anodic bonding between the SOI and glass-on-silicon (GOS). The fabrication process was designed and successfully realized, featured with a simplified process and highly efficient batch manufacturing, and the final chip size was only 5 × 5 mm. A theoretical model for the packaged device was set up. The influence of key parameters in the packaging structure on the output characteristics of the microsensor was analyzed on the basis of the proposed model. Experiments were conducted on the wafer-level vacuum-packaged EFM to characterize its performance. Experimental results show that, under the condition of applying 5 V DC driving voltage, the required AC driving voltage of the sensor was only 0.05 VP, and the feedthrough was only 4.2 mV. The quality factor was higher than 5000 and was maintained with no drop in the 50-day test. The vacuum in the chamber of the sensor was about 10 Pa. A sensitivity of 0.16 mV/(kV/m) was achieved within the electrostatic field range of 0–50 kV/m. The linearity of the microsensor was 1.62%, and the uncertainty was 4.42%. [ABSTRACT FROM AUTHOR]

Emerging data suggest that induction of viral mimicry responses through activation of double-stranded RNA (dsRNA) sensors in cancer cells is a promising therapeutic strategy. One approach to induce viral mimicry is to target molecular regulators of dsRNA sensing pathways. Here, we show that the exoribonuclease XRN1 is a negative regulator of the dsRNA sensor protein kinase R (PKR) in cancer cells with high interferon-stimulated gene expression. XRN1 deletion causes PKR pathway activation and consequent cancer cell lethality. Disruption of interferon signaling with the JAK1/2 inhibitor ruxolitinib can decrease cellular PKR levels and rescue sensitivity to XRN1 deletion. Conversely, interferon-β stimulation can increase PKR levels and induce sensitivity to XRN1 inactivation. Lastly, XRN1 deletion causes accumulation of endogenous complementary sense/anti-sense RNAs, which may represent candidate PKR ligands. Our data demonstrate how XRN1 regulates PKR and how this interaction creates a vulnerability in cancer cells with an activated interferon cell state. [Display omitted] • XRN1 is required for survival of cancer cells with interferon pathway activation • XRN1 depletion causes activation of the interferon-inducible dsRNA sensor PKR • Interferon signaling increases PKR levels, rendering cells vulnerable to XRN1 loss • XRN1 loss causes accumulation of putative dsRNAs formed by sense/anti-sense RNAs Zou et al. identify a requirement for the XRN1 exoribonuclease in human cancer cell lines with high expression of interferon-stimulated genes. XRN1 depletion causes accumulation of complementary sense/anti-sense transcript pairs and cell-intrinsic activation of the interferon-inducible double-stranded RNA sensor protein kinase R, leading to cancer cell lethality. [ABSTRACT FROM AUTHOR]

Information on height of pylon is important when planning the routes of unmanned aerial vehicles. This paper proposes a new automatic method for estimating pylon height using shadow differences between GF-2 satellite images taken at different times. Initially, the spectral distribution features and triangular shape of pylon shadows are used for shadow detection to enhance the difference from other land objects using images taken at a greater sun elevation angle. Then, the difference in the shadows of the same pylon in images taken at different times and shadow-imaging principles are used to estimate the vertical of the pylon top to avoid interference from complex land objects. Finally, the height of the pylon is approximated using the distance from the vertical projection point to the shadow point of the pylon top and sun elevation angle. GF-2 images were selected and included five pylons in the target area. The average error of the estimated height was 1.56 m, and the relative error was only 2.74%. [ABSTRACT FROM AUTHOR]

Monascus spp. are commonly used for a wide variety of applications in the food and pharmaceutical industries. In previous studies, the knock-out of mrflbA (a putative regulator of the G protein α subunit) in M. ruber led to autolysis of the mycelia, decreased pigmentation and lowered mycotoxin production. Therefore, we aimed to obtain a comprehensive overview of the underlying mechanism of mrflbA deletion at the proteome level. A two-dimensional gel electrophoresis analysis of mycelial proteins indicated that the abundance of 178 proteins was altered in the ΔmrflbA strain, 33 of which were identified with high confidence. The identified proteins are involved in a range of activities, including carbohydrate and amino acid metabolism, hyphal development and the oxidative stress response, protein modification, and the regulation of cell signaling. Consistent with these findings, the activity of antioxidative enzymes and chitinase was elevated in the supernatant of the ΔmrflbA strain. Furthermore, deletion of mrflbA resulted in the transcriptional reduction of secondary metabolites (pigment and mycotoxin). In short, the mutant phenotypes induced by the deletion of mrflbA were consistent with changes in the expression levels of associated proteins, providing direct evidence of the regulatory functions mediated by mrflbA in M. ruber. [ABSTRACT FROM AUTHOR]

One of the major concerns in the development of three-dimensional (3D) electric field sensors (EFSs) is their susceptibility to cross-axis coupling interference. The output signal for each sensing axis of a 3D EFS is often coupled by electric field components from the two other orthogonal sensing axes. In this paper, a one-dimensional (1D) electric field sensor chip (EFSC) with low cross-axis coupling interference is presented. It is designed to be symmetrical, forming a pair of in-plane symmetrically-located sensing structures. Using a difference circuit, the 1D EFSC is capable of sensing parallel electric fields along symmetrical structures and eliminating cross-axis coupling interference, which is contrast to previously reported 1D EFSCs designed for perpendicular electric field component measurement. Thus, a 3D EFS with low cross-axis coupling interference can be realized using three proposed 1D EFSCs. This 3D EFS has the advantages of low cross-axis coupling interference, small size, and high integration. The testing and calibration systems of the proposed 3D EFS were developed. Experimental results show that in the range of 0–120 kV/m, cross-axis sensitivities are within 5.48%, and the total measurement errors of this 3D EFS are within 6.16%. [ABSTRACT FROM AUTHOR]

This paper proposes a high sensitivity electric field microsensor (EFM) based on torsional resonance. The proposed microsensor adopts torsional shutter, which is composed of shielding electrodes and torsional beams. The movable shielding electrodes and the fixed sensing electrodes are fabricated on the same plane and interdigitally arranged. Push-pull electrostatic actuation method is employed to excite the torsional shutter. Simulation results proved that the torsional shutter has higher efficiency of charge induction. The optimization of structure parameters was conducted to improve its efficiency of charge induction further. A micromachining fabrication process was developed to fabricate the EFM. Experiments were conducted to characterize the EFM. A good linearity of 0.15% was achieved within an electrostatic field range of 0-50 kV/m, and the uncertainty was below 0.38% in the three roundtrip measurements. A high sensitivity of 4.82 mV/(kV/m) was achieved with the trans-resistance of 100 MO, which is improved by at least one order of magnitude compared with previously reported EFMs. The efficiency of charge induction for this microsensor reached 48.19 pA/(kV/m). [ABSTRACT FROM AUTHOR]

Resample method is used to do geometric correction on remotely sensed image. However, geometric correction can lead to decrease of spectral information quality. The research to maintain the spectral information has been the focus in the remote sensing domain. The quality of the images is evaluated and analyzed in the view of the quality assessment of image application. By comparing the results at different spatial resolution, the quality of the aerial images is evaluated objectively. The image application quality evaluation is carried out in three aspects: statistical feature, texture feature and energy feature. The result showed that the evaluation of aerial images can accurately reflect mulfi-scale effect of resampling information loss. [ABSTRACT FROM AUTHOR]

The excision repair cross-complementation group 1 (ERCC1) plays an essential role in DNA repair and has been linked to resistance to platinum-based anticancer drugs among advanced non-small cell lung cancer (NSCLC) patients. We systematically evaluate whether ERCC1 Asn118Asn and C8092A genetic variants are associated with treatment response of platinum chemotherapy. We preformed a meta-analysis using ten eligible cohort studies (including 11 datasets) with a total of 1,252 NSCLC patients to summarize the existing data on the association between the ERCC1 Asn118Asn and C8092A polymorphisms and response to platinum regiments. Odds ratio or hazard ratio with 95% confidence interval were calculated to estimate the correlation. We found that neither ERCC1 C8092A polymorphism nor Asn118Asn variant is associated with different response of platinum-based treatment among advanced NSCLC patients. Additionally, these two genetic variants are not related to treatment response in either Caucasian patients or Asian patients. Our meta-analysis indicates that the ERCC1 Asn118Asn and C8092A polymorphisms may not be good prognostic biomarkers for platinum-based chemotherapy in patients with stage III-IV NSCLC. [ABSTRACT FROM AUTHOR]

Electrostatic voltage is a vital parameter in industrial production lines, for reducing electrostatic discharge harms and improving yields. Due to such drawbacks as package shielding and low resolution, previously reported electric field microsensors are still not applicable for industrial static monitoring uses. In this paper, we introduce a newly designed microsensor package structure, which enhances the field strength inside the package cavity remarkably. This magnification effect was studied and optimized by both theoretical calculation and ANSYS simulation. By means of the digital synthesizer and digital coherent demodulation method, the compact signal processing circuit for the packaged microsensor was also developed. The meter prototype was calibrated above a charged metal plate, and the electric field resolution was 5 V/m, while the measuring error was less than 3 V, from −1 kV to 1 kV in a 2 cm distance. The meter was also installed into a production line and showed good consistency with, and better resolution than, a traditional vibratory capacitance sensor. [ABSTRACT FROM AUTHOR]

This paper proposes an electric field microsensor (EFM) with mutual shielding electrodes. Based on the charge-induction principle, the EFM consists of fixed electrodes and piezoelectric-driving vertically-movable electrodes. All the fixed electrodes and movable electrodes work as both sensing electrodes and shielding electrodes. In other words, all the fixed and movable electrodes are sensing electrodes, and they are mutually shielding electrodes simultaneously. The movable electrodes are driven to periodically modulate the electric field distribution at themselves and the fixed electrodes, and the induced currents from both movable and fixed electrodes are generated simultaneously. The electrode structure adopts an interdigital structure, and the EFM has been simulated by finite element methods. Simulation results show that, since the sensing area of this EFM is doubled, the variation of induced charge is twice, and therefore the output signal of the sensor is increased. The piezoelectric material, lead zirconate titanate (PZT), is prepared by the sol–gel method, and the microsensor chip is fabricated. [ABSTRACT FROM AUTHOR]

As one of the most important active remote sensing technologies, synthetic aperture radar (SAR) provides advanced advantages of all-day, all-weather, and strong penetration capabilities. Due to its unique electromagnetic spectrum and imaging mechanism, the dimensions of remote sensing data have been considerably expanded. Important for fundamental research in microwave remote sensing, SAR image classification has been proven to have great value in many remote sensing applications. Many widely used SAR image classification algorithms rely on the combination of hand-designed features and machine learning classifiers, which still experience many issues that remain to be resolved and overcome, including optimized feature representation, the fuzzy confusion of speckle noise, the widespread applicability, and so on. To mitigate some of the issues and to improve the pattern recognition of high-resolution SAR images, a ConvCRF model combined with superpixel boundary constraint is developed. The proposed algorithm can successfully combine the local and global advantages of fully connected conditional random fields and deep models. An optimizing strategy using a superpixel boundary constraint in the inference iterations more efficiently preserves structure details. The experimental results demonstrate that the proposed method provides competitive advantages over other widely used models. In the land cover classification experiments using the MSTAR, E-SAR and GF-3 datasets, the overall accuracy of our proposed method achieves 90.18 ± 0.37, 91.63 ± 0.27, and 90.91 ± 0.31, respectively. Regarding the issues of SAR image classification, a novel integrated learning containing local and global image features can bring practical implications. [ABSTRACT FROM AUTHOR]

Fine classification of vegetation types has always been the focus and difficulty in the application field of remote sensing. Unmanned Aerial Vehicle (UAV) sensors and platforms have become important data sources in various application fields due to their high spatial resolution and flexibility. Especially, UAV hyperspectral images can play a significant role in the fine classification of vegetation types. However, it is not clear how the ultrahigh resolution UAV hyperspectral images react in the fine classification of vegetation types in highly fragmented planting areas, and how the spatial resolution variation of UAV images will affect the classification accuracy. Based on UAV hyperspectral images obtained from a commercial hyperspectral imaging sensor (S185) onboard a UAV platform, this paper examines the impact of spatial resolution on the classification of vegetation types in highly fragmented planting areas in southern China by aggregating 0.025 m hyperspectral image to relatively coarse spatial resolutions (0.05, 0.1, 0.25, 0.5, 1, 2.5 m). The object-based image analysis (OBIA) method was used and the effects of several segmentation scale parameters and different number of features were discussed. Finally, the classification accuracies from 84.3% to 91.3% were obtained successfully for multi-scale images. The results show that with the decrease of spatial resolution, the classification accuracies show a stable and slight fluctuation and then gradually decrease since the 0.5 m spatial resolution. The best classification accuracy does not occur in the original image, but at an intermediate level of resolution. The study also proves that the appropriate feature parameters vary at different scales. With the decrease of spatial resolution, the importance of vegetation index features has increased, and that of textural features shows an opposite trend; the appropriate segmentation scale has gradually decreased, and the appropriate number of features is 30 to 40. Therefore, it is of vital importance to select appropriate feature parameters for images in different scales so as to ensure the accuracy of classification. [ABSTRACT FROM AUTHOR]