Role of IL-33 and ST2 signaling and inflammatory responses in non-small cell lung cancer

Purpose: To investigate the role of the interleukin (IL)-33 and ST2 pathway in  non-small cell lung cancer (NSCLC), and to further explore the critical relationships among inflammation, immunity, and cancer.Methods: From January 2014 to December 2015, paraffin-embedded sections of surgical specimens were obtained from 40 patients definitively diagnosed with NSCLC by pathological examination in Changzhou Wujin People's Hospital and Taicang Hospital of Traditional Chinese Medicine. Sections were further  immunostained with antibodies directed against IL-33 and ST2 cardiac biomarker.Inflammatory reactions were determined by hematoxylin and eosin (H&E) staining. Paracancerous control sample tissues were also collected. In addition, 60 primary NSCLC patients without any complications were enrolled, and 60 healthy volunteers were enrolled at the same institutions. Serum samples of patients were collected, and protein expressions of IL-33, ST2, IL-4, and interferon (IFN)-γ were detected by enzyme-linked immunosorbent assay (ELISA) or western blot assay.Results: The results indicate that IL-33, ST2 and IL-4 expressions in cancer tissues and blood were significantly increased when compared with control groups.Conclusion: IL-33/ST2 in NSCLC microenvironment enhances T helper cell 2 (Th2) response, which may be beneficial for tumor growth.Keywords: Interleukin, IL-33, ST2, IL-4, non-small cell lung cancer (NSCLC

Call for papers for IET special issue: Emerging technologies in analogue and RF integrated circuits and systems enabling 5/6G communication

Since its renaissance, the 5G technologies deliver tremendous new and advanced electronic products and tools to the public and industries. It must attribute to the invention, optimization, and designs of varies advanced Analogue and RF integrated circuits and systems, both from academia, industry, and government. 6G follows the footsteps of 5G. Recently, the 5/6G millimetre-wave (mmW) and terahertz (THz) frequency bands are developing rapidly, facing the demand for ultra-high capacity and transmission rate of 5/6G networks in near future. It becomes essential to continuously dig into the Analogue and RF integrated circuits for the dedicated mmW and THz systems

Current advances in cancer vaccines targeting NY-ESO-1 for solid cancer treatment

New York-esophageal cancer 1 (NY-ESO-1) belongs to the cancer testis antigen (CTA) family, and has been identified as one of the most immunogenic tumor-associated antigens (TAAs) among the family members. Given its ability to trigger spontaneous humoral and cellular immune response and restricted expression, NY-ESO-1 has emerged as one of the most promising targets for cancer immunotherapy. Cancer vaccines, an important element of cancer immunotherapy, function by presenting an exogenous source of TAA proteins, peptides, and antigenic epitopes to CD4+ T cells via major histocompatibility complex class II (MHC-II) and to CD8+ T cells via major histocompatibility complex class I (MHC-I). These mechanisms further enhance the immune response against TAAs mediated by cytotoxic T lymphocytes (CTLs) and helper T cells. NY-ESO-1-based cancer vaccines have a history of nearly two decades, starting from the first clinical trial conducted in 2003. The current cancer vaccines targeting NY-ESO-1 have various types, including Dendritic cells (DC)-based vaccines, peptide vaccines, protein vaccines, viral vaccines, bacterial vaccines, therapeutic whole-tumor cell vaccines, DNA vaccines and mRNA vaccines, which exhibit their respective benefits and obstacles in the development and application. Here, we summarized the current advances in cancer vaccines targeting NY-ESO-1 for solid cancer treatment, aiming to provide perspectives for future research

Antitumor activity and mechanisms of action of total glycosides from aerial part of Cimicifuga dahurica targeted against hepatoma

<p>Abstract</p> <p>Background</p> <p>Medicinal plant is a main source of cancer drug development. Some of the cycloartane triterpenoids isolated from the aerial part of <it>Cimicifuga dahurica </it>showed cytotoxicity in several cancer cell lines. It is of great interest to examine the antiproliferative activity and mechanisms of total triterpenoid glycosides of <it>C. dahurica </it>and therefore might eventually be useful in the prevention or treatment of Hepatoma.</p> <p>Methods</p> <p>The total glycosides from the aerial part (TGA) was extracted and its cytotoxicity was evaluated in HepG2 cells and primary cultured normal mouse hepatocytes by an MTT assay. Morphology observation, Annexin V-FITC/PI staining, cell cycle analysis and western blot were used to further elucidate the cytotoxic mechanism of TGA. Implanted mouse H₂₂hepatoma model was used to demonstrate the tumor growth inhibitory activity of TGA <it>in vivo</it>.</p> <p>Results</p> <p>The IC₅₀values of TGA in HepG2 and primary cultured normal mouse hepatocytes were 21 and 105 μg/ml, respectively. TGA induced G₀/G₁cell cycle arrest at lower concentration (25 μg/ml), and triggered G₂/M arrest and apoptosis at higher concentrations (50 and 100 μg/ml respectively). An increase in the ratio of Bax/Bcl-2 was implicated in TGA-induced apoptosis. In addition, TGA inhibited the growth of the implanted mouse H₂₂tumor in a dose-dependent manner.</p> <p>Conclusion</p> <p>TGA may potentially find use as a new therapy for the treatment of hepatoma.</p

A 77-GHz Fully Integrated Power Amplifier for Automotive Radar Application in 40-nm CMOS

This paper presents a compact 77-GHz four-way differential power combined power amplifier for automotive radar application. At E-band, the insertion loss of matching network and power combining network are the limiting factor for the power amplifier's performance. In this work, the insertion loss of the matching networks is reduced by taking advantage of the proposed coplanar waveguide differential transmission line with floating substrate noise shielding grids. The voltage-current power combining method that takes care of impedance matching and power combining is adopted to decrease the insertion loss from power combining and output matching network. The power amplifier is implemented in a 40 nm CMOS process. From 69 to 85 GHz, the power amplifier delivers more than 19 dBm output power with the maximum $P_{sat}$ of 19.7 GHz at 77 GHz. The final layout power amplifier achieves 19.4 dB peak small signal gain, and the maximum PAE is 22.7 %

Toward New-Generation Intelligent Manufacturing

Intelligent manufacturing is a general concept that is under continuous development. It can be categorized into three basic paradigms: digital manufacturing, digital-networked manufacturing, and new-generation intelligent manufacturing. New-generation intelligent manufacturing represents an in-depth integration of new-generation artificial intelligence (AI) technology and advanced manufacturing technology. It runs through every link in the full life-cycle of design, production, product, and service. The concept also relates to the optimization and integration of corresponding systems; the continuous improvement of enterprises’ product quality, performance, and service levels; and reduction in resources consumption. New-generation intelligent manufacturing acts as the core driving force of the new industrial revolution and will continue to be the main pathway for the transformation and upgrading of the manufacturing industry in the decades to come. Human-cyber-physical systems (HCPSs) reveal the technological mechanisms of new-generation intelligent manufacturing and can effectively guide related theoretical research and engineering practice. Given the sequential development, cross interaction, and iterative upgrading characteristics of the three basic paradigms of intelligent manufacturing, a technology roadmap for “parallel promotion and integrated development” should be developed in order to drive forward the intelligent transformation of the manufacturing industry in China. Keywords: Advanced manufacturing, New-generation intelligent manufacturing, Human-cyber-physical system, New-generation AI, Basic paradigms, Parallel promotion, Integrated developmen

A 40–50 GHz RF Front-End with Integrated Local Oscillator Leakage Calibration

This article presents a transmitter (TX) front-end operating at frequencies covering 40–50 GHz, including a differential quadrature mixer with integrated amplitude and phase imbalance tuning, a power amplifier, and a detection mixer (DM) that supports local oscillator (LO) leakage signal or image signal calibration. Benefiting from the amplitude and phase imbalance tuning network of the in-phase quadrature (IQ) signal generator at the LO input, the TX exhibits more than 30 dBc image signal rejection over the full frequency band without any post-calibration. Based on the LO leakage signal fed back by the DM integrated at the RF output, the LO leakage of the TX has been improved by more than 10 dB through the LO leakage calibration module integrated in the quadrature mixer. When the intermediate frequency (IF) signal is fixed at 1 GHz, the TX’s 1 dB compressed output power (OP1 dB) is higher than 13.5 dBm over the operating band. Thanks to the LO leakage signal calibration unit and the IQ signal generator, the TX is compliant with the error vector magnitude (EVM) requirement of the IEEE 802.11aj standard up to the 64-quadrature amplitude modulation (QAM) operating mode

A Method to Improve the Accuracy of Pavement Crack Identification by Combining a Semantic Segmentation and Edge Detection Model

In recent years, deep learning-based detection methods have been applied to pavement crack detection. In practical applications, surface cracks are divided into inner and edge regions for pavements with rough surfaces and complex environments. This creates difficulties in the image detection task. This paper is inspired by the U-Net semantic segmentation network and holistically nested edge detection network. A side-output part is added to the U-Net decoder that performs edge extraction and deep supervision. A network model combining two tasks that can output the semantic segmentation results of the crack image and the edge detection results of different scales is proposed. The model can be used for other tasks that need both semantic segmentation and edge detection. Finally, the segmentation and edge images are fused using different methods to improve the crack detection accuracy. The experimental results show that mean intersection over union reaches 69.32 on our dataset and 61.05 on another pavement dataset group that did not participate in training. Our model is better than other detection methods based on deep learning. The proposed method can increase the MIoU value by up to 5.55 and increase the MPA value by up to 10.41 when compared to previous semantic segmentation models