Search

In a previous study we noted significant THP binding to TNF-α, but did not explore the molecular basis of the structure-binding relationship. In this study, we used lectin-binding ELISA to assess the carbohydrate compositions of THP, BSA, IgG, TNF-α, and IFN-g. We identified β(1,4)-N-acetylglucosamine oligomers (GlcNAc) and GlcNAc/branched mannose in BSA, IgG, TNF-α, and THP, but not in IFN-g. These carbohydrate moieties mediated binding with THP. Small amounts of Siaα(2,3)Gal/ GalNAc, Sia(2,6)Gal/GalNAc, and mannose residues were also present in THP and TNF-α. Binding affinity (Kd) between THP and TNF-α by Scatchard plot analysis was 1.4–1.7 × 10−6 M, lower than antigen-antibody or ligand-receptor binding affinities. To elucidate the structure-binding relationship of THP-TNF-α, THP was digested with neuraminidase, β-galactosidase, O-sialoglycoprotein endopeptidase, carboxypeptidase Y, or proteinase K. β-galactosidase increased binding capacity of THP for TNF-α. Monosaccharide inhibition suggested that α-methyl-D-mannoside, GlcNAc, and GalNAc, but not sialic acid, suppress THP-TNF-α binding as detected by ELISA. We conclude that sugar-lectin and sugar-protein interactions between cognate sites in THP and TNF-α mediate their binding.

Adaptive antenna array processing is widely known to provide significant anti-interference capabilities within a Global Navigation Satellite Systems (GNSS) receiver. A main challenge in the quest for such receiver architecture has always been the computational/processing requirements. Even more demanding would be to try and incorporate the flexibility of the Software-Defined Radio (SDR) design philosophy in such an implementation. This paper documents a feasible approach to a real-time SDR implementation of a beam-steered GNSS receiver and validates its performance. This research implements a real-time software receiver on a widely-available x86-based multi-core microprocessor to process four-element antenna array data streams sampled with 16-bit resolution. The software receiver is capable of 12 channels all-in-view Controlled Reception Pattern Antenna (CRPA) array processing capable of rejecting multiple interferers. Single Instruction Multiple Data (SIMD) instructions assembly coding and multithreaded programming, the key to such an implementation to reduce computational complexity, are fully documented within the paper. In conventional antenna array systems, receivers use the geometry of antennas and cable lengths known in advance. The documented CRPA implementation is architected to operate without extensive set-up and pre-calibration and leverages Space-Time Adaptive Processing (STAP) to provide adaptation in both the frequency and space domains. The validation component of the paper demonstrates that the developed software receiver operates in real time with live Global Positioning System (GPS) and Wide Area Augmentation System (WAAS) L1 C/A code signal. Further, interference rejection capabilities of the implementation are also demonstrated using multiple synthetic interferers which are added to the live data stream.

Due to their weak received signal power, Global Positioning System (GPS) signals are vulnerable to radio frequency interference. Adaptive beam and null steering of the gain pattern of a GPS antenna array can significantly increase the resistance of GPS sensors to signal interference and jamming. Since adaptive array processing requires intensive computational power, beamsteering GPS receivers were usually implemented using hardware such as field-programmable gate arrays (FPGAs). However, a software implementation using general-purpose processors is much more desirable because of its flexibility and cost effectiveness. This paper presents a GPS software-defined radio (SDR) with adaptive beamsteering capability for anti-jam applications. The GPS SDR design is based on an optimized desktop parallel processing architecture using a quad-core Central Processing Unit (CPU) coupled with a new generation Graphics Processing Unit (GPU) having massively parallel processors. This GPS SDR demonstrates sufficient computational capability to support a four-element antenna array and future GPS L5 signal processing in real time. After providing the details of our design and optimization schemes for future GPU-based GPS SDR developments, the jamming resistance of our GPS SDR under synthetic wideband jamming is presented. Since the GPS SDR uses commercial-off-the-shelf hardware and processors, it can be easily adopted in civil GPS applications requiring anti-jam capabilities.

BACKGROUND AND PURPOSE:For metastatic non-small cell lung cancer (NSCLC) patients with controlled extrathoracic disease after systemic treatment, stable or progressive primary lung lesions may cause respiratory symptoms and increase comorbidities. In the present study, we sought to investigate whether aggressive palliative thoracic radiotherapy (RT) can enhance local control and improve the survival for this subgroup of patients. MATERIALS AND METHODS:Between March 2006 and December 2014, 56 patients with metastatic NSCLC who had responsive or stable extrathoracic diseases after chemotherapy and/or molecular targets, and received thoracic RT for stable and progressive primary lung lesions were included. RT with a median dose of 55 Gy (range, 40-62 Gy) was administered in 1.8-2.5 Gy fractions to primary lung tumor and regional mediastinal lymph nodes using modern RT technique. Overall survival (OS) from diagnosis, and locoregional progression-free survival (LRPFS), and survival calculated from radiotherapy (OS-RT) were estimated using the Kaplan-Meier method. RESULTS:There were 37 men and 19 women with a median age of 60 years at diagnosis. The median interval from the diagnosis of metastatic disease to thoracic RT was 8 months. Following thoracic RT, 26 patients (46%) achieved complete or partial response (overall response rate, ORR). Patients with squamous cell carcinoma or poorly-differentiated carcinoma had a higher ORR than those with adenocarcinoma (63% vs. 34%, P = 0.034). EGFR mutations was closely associated with a better ORR (45% vs. 29%, P = 0.284). At a median follow-up time of 44 months, the median OS, LRPFS after RT, and OS-RT were 50 months, 15 months, and 18 months. CONCLUSION:Radical palliative throractic RT is safe and might be beneficial for primary lung lesions of metastatic NSCLC patients with controlled extrathoracic diseases.

Enterohaemorrhagic E. coli (EHEC) is a type of human pathogenic bacteria. The main virulence characteristics of EHEC include the formation of attaching and effacing lesions (A/E lesions) and the production of one or more Shiga-like toxins, which may induce human uremic complications. When EHEC infects host cells, it releases translocated intimin receptor (Tir) and effector proteins inside the host cells, inducing the rearrangement and accumulation of the F-actin cytoskeleton, a phenotype leading to the formation of pedestals in the apical cell surface, and the growth of stress fibers at the base of the cells. To examine the effect of EHEC infection on cell mechanics, we carried out a series of experiments to examine HeLa cells with and without EHEC infection to quantify the changes in (1) focal adhesion area, visualized by anti-vinculin staining; (2) the distribution and orientation of stress fibers; and (3) the intracellular viscoelasticity, via directional video particle tracking microrheology. Our results indicated that in EHEC-infected HeLa cells, the focal adhesion area increased and the actin stress fibers became thicker and more aligned. The cytoskeletal reorganization induced by EHEC infection mediated a dramatic increase in the cytoplasmic elastic shear modulus of the infected cells, and a transition in the viscoelastic behavior of the cells from viscous-like to elastic-like. These changes in mechanobiological characteristics might modulate the attachments between EHEC and the host cell to withstand exfoliation, and between the host cell and the extracellular matrix, and might also alter epithelial integrity.

Citrus bacterial canker caused by Xanthomonas axonopodis pv. citri is a serious disease that impacts citrus production worldwide, and X. axonopodis pv. citri is listed as a quarantine pest in certain countries. Biofilm formation is important for the successful development of a pathogenic relationship between various bacteria and their host(s). To understand the mechanisms of biofilm formation by X. axonopodis pv. citri strain XW19, the strain was subjected to transposon mutagenesis. One mutant with a mutation in a two-component response regulator gene that was deficient in biofilm formation on a polystyrene microplate was selected for further study. The protein was designated as BfdR for biofilm formation defective regulator. BfdR from strain XW19 shares 100% amino acid sequence identity with XAC1284 of X. axonopodis pv. citri strain 306 and 30-100% identity with two-component response regulators in various pathogens and environmental microorganisms. The bfdR mutant strain exhibited significantly decreased biofilm formation on the leaf surfaces of Mexican lime compared with the wild type strain. The bfdR mutant was also compromised in its ability to cause canker lesions. The wild-type phenotype was restored by providing pbfdR in trans in the bfdR mutant. Our data indicated that BfdR did not regulate the production of virulence-related extracellular enzymes including amylase, lipase, protease, and lecithinase or the expression of hrpG, rfbC, and katE; however, BfdR controlled the expression of rpfF in XVM2 medium, which mimics cytoplasmic fluids in planta. In conclusion, biofilm formation on leaf surfaces of citrus is important for canker development in X. axonopodis pv. citri XW19. The process is controlled by the two-component response regulator BfdR via regulation of rpfF, which is required for the biosynthesis of a diffusible signal factor.

Incorporating style-related objectives into shape design has been centrally important to maximize product appeal. However, algorithmic style capture and reuse have not fully benefited from automated data-driven methodologies due to the challenging nature of design describability. This paper proposes an AI-driven method to fully automate the discovery of brand-related features. First, to tackle the scarcity of vectorized product images, this research proposes two data acquisition workflows: parametric modeling from small curve-based datasets, and vectorization from large pixel-based datasets. Second, this study constructs BIGNet, a two-tier Brand Identification Graph Neural Network, to learn from both scalar vector graphics' curve-level and chunk-level parameters. In the first case study, BIGNet not only classifies phone brands but also captures brand-related features across multiple scales, such as lens' location, as confirmed by AI evaluation. In the second study, this paper showcases the generalizability of BIGNet learning from a vectorized car image dataset and validates the consistency and robustness of its predictions given four scenarios. The results match the difference commonly observed in luxury versus economy brands in the automobile market. Finally, this paper also visualizes the activation maps generated from a convolutional neural network and shows BIGNet's advantage of being a more explainable style-capturing agent. [ABSTRACT FROM AUTHOR]