Proteomics-derived basal biomarker DNA-PKcs is associated with intrinsic subtype and long-term clinical outcomes in breast cancer

Precise biomarkers are needed to guide better diagnostics and therapeutics for basal-like breast cancer, for which DNA-dependent protein kinase catalytic subunit (DNA-PKcs) has been recently reported by the Clinical Proteomic Tumor Analysis Consortium as the most specific biomarker. We evaluated DNA-PKcs expression in clinically-annotated breast cancer tissue microarrays and correlated results with immune biomarkers (training set: n = 300; validation set: n = 2401). Following a pre-specified study design per REMARK criteria, we found that high expression of DNA-PKcs was significantly associated with stromal and CD8 + tumor infiltrating lymphocytes. Within the basal-like subtype, tumors with low DNA-PKcs and high tumor-infiltrating lymphocytes displayed the most favourable survival. DNA-PKcs expression by immunohistochemistry identified estrogen receptor-positive cases with a basal-like gene expression subtype. Non-silent mutations in PRKDC were significantly associated with poor outcomes. Integrating DNA-PKcs expression with validated immune biomarkers could guide patient selection for DNA-PKcs targeting strategies, DNA-damaging agents, and their combination with an immune-checkpoint blockade

Metachronal propulsion of a magnetized particle-fluid suspension in a ciliated channel with heat and mass transfer

Biologically inspired pumping systems are of great interest in modern engineering since they achieve enhanced efficiency and circumvent the need for moving parts and maintenance. Industrial applications also often feature two-phase flows. In this article, motivated by these applications, the pumping of an electrically conducting particle-fluid suspension due to metachronal wave propulsion of beating cilia in a two-dimensional channel with heat and mass transfer under a transverse magnetic field is investigated theoretically. The governing equations for mass and momentum conservation for fluid- and particle-phases are formulated by ignoring the inertial forces and invoking the long wavelength approximation. The Jeffrey viscoelastic model is employed to simulate non-Newtonian characteristics. The normalized resulting differential equations are solved analytically. Symbolic software is employed to evaluate the results and simulate the influence of different parameters on flow characteristics. Results are visualized graphically with carefully selected and viable data

Self-organizing hierarchical particle swarm optimization of correlation filters for object recognition

Advanced correlation filters are an effective tool for target detection within a particular class. Most correlation filters are derived from a complex filter equation leading to a closed form filter solution. The response of the correlation filter depends upon the selected values of the optimal trade-off (OT) parameters. In this paper, the OT parameters are optimized using particle swarm optimization with respect to two different cost functions. The optimization has been made generic and is applied to each target separately in order to achieve the best possible result for each scenario. The filters obtained using standard particle swarm optimization (PSO) and hierarchal particle swarm optimization (HPSO) algorithms have been compared for various test images with the filter solutions available in the literature. It has been shown that optimization improves the performance of the filters significantly

Rotation, magnetism, and metallicity of M dwarf systems

Close M-dwarf binaries and higher multiples allow the investigation of rotational evolution and mean magnetic flux unbiased from scatter in inclination angle and age since the orientation of the spin axis of the components is most likely parallel and the individual systems are coeval. Systems composed of an early (M0.0 -- M4.0) and a late (M4.0 -- M8.0) type component offer the possibility to study differences in rotation and magnetism between partially and fully convective stars. We have selected 10 of the closest dM systems to determine the rotation velocities and the mean magnetic field strengths based on spectroscopic analysis of FeH lines of Wing-Ford transitions at 1 $\mu$m observed with VLT/CRIRES. We also studied the quality of our spectroscopic model regarding atmospheric parameters including metallicity. A modified version of the Molecular Zeeman Library (MZL) was used to compute Land\'e g-factors for FeH lines. Magnetic spectral synthesis was performed with the Synmast code. We confirmed previously reported findings that less massive M-dwarfs are braked less effectively than objects of earlier types. Strong surface magnetic fields were detected in primaries of four systems (GJ 852, GJ 234, LP 717-36, GJ 3322), and in the secondary of the triple system GJ 852. We also confirm strong 2 kG magnetic field in the primary of the triple system GJ 2005. No fields could be accurately determined in rapidly rotating stars with \vsini>10 \kms. For slow and moderately rotating stars we find the surface magnetic field strength to increase with the rotational velocity \vsini which is consistent with other results from studying field stars.Comment: Accepted by MNRAS, 10 pages, 4 figures, 4 table

Predicting humans future motion trajectories in video streams using generative adversarial network

Understanding the behavior of human motion in social environments is important for various domains of a smart city, e.g, smart transportation, automatic navigation of service robots, efficient navigation of autonomous cars and surveillance systems. Examining past trajectories or environmental factors alone are not enough to address this problem. We propose a novel methodology to predict future motion trajectories of humans based on past attitude of individuals, crowd attitude and environmental context. Many researchers have proposed different techniques based on different features extraction and features fusion to predict the future motion trajectory. They used traditional machine learning algorithms like SVM,social forces, probabilistic models and LSTM to analyze the heuristic motion trajectories but they didn’t consider the other environmental factors e.g relative positions of other humans present in environment and positions of objects present in environment which can affect the motion trajectories of humans. We intend to achieve this goal by employing Long Short Term Memory(LSTM) units to analyze motion histories, convolution neural networks to environmental facts e.g. human-human, human-object interaction and relative positioning of 80 different objects including pedestrians and generative adversarial networks(GANs) to predict possible future motion paths. Our proposed method achieved 70% lower Average Displacement Error(ADE) and 41% lower Final Displacement Error(FDE) in comparison to other state of the art techniques

The immune microenvironment and relation to outcome in patients with advanced breast cancer treated with docetaxel with or without gemcitabine

Preclinical studies suggest that some effects of conventional chemotherapy, and in particular, gemcitabine, are mediated through enhanced antitumor immune responses. The objective of this study was to use material from a randomized clinical trial to evaluate whether patients with preexisting immune infiltrates responded better to treatment with gemcitabine + docetaxel (GD) compared to docetaxel alone. Formalin fixed, paraffin-embedded breast cancer tissues from SBG0102 phase 3 trial patients randomly assigned to treatment with GD or docetaxel were used. Immunohistochemical staining for CD8, FOXP3, LAG3, PD-1, PD-L1 and CD163 was performed. Tumor infiltrating lymphocytes (TILs) and tumor associated macrophages were evaluated. Prespecified statistical analyses were performed in a formal prospective-retrospective design. Time to progression was primary endpoint and overall survival secondary endpoint. Correlations between biomarker status and endpoints were evaluated using the Kaplan-Meier method and Cox proportional hazards models. Biomarker data was obtained for 237 patients. There was no difference in treatment effect according to biomarker status for the whole cohort. In planned subgroup analysis by PAM50 subtype, in non-luminal (basal-like and HER2E) breast cancers FOXP3 was a significant predictor of treatment effect with GD compared to docetaxel, with a HR of 0.22 (0.09-0.52) for tumors with low FOXP3 compared to HR 0.92 (0.47-1.80) for high FOXP3 TILs (Pinteraction = 0.01). Immune biomarkers were not predictive of added benefit of gemcitabine in a cohort of mixed breast cancer subtypes. However, in non-luminal breast cancers, patients with low FOXP3+ TILs may have significant benefit from added gemcitabine

Astrometric confirmation of young low-mass binaries and multiple systems in the Chamaeleon star-forming regions

The star-forming regions in Chamaeleon are one of the nearest (distance ~165 pc) and youngest (age ~2 Myrs) conglomerates of recently formed stars and the ideal target for population studies of star formation. We investigate a total of 16 Cha targets, which have been suggested, but not confirmed as binaries or multiple systems in previous literature. We used the adaptive optics instrument Naos-Conica (NACO) at the Very Large Telescope Unit Telescope 4 of the Paranal Observatory, at 2-5 different epochs, in order to obtain relative and absolute astrometric measurements, as well as differential photometry in the J, H, and K band. On the basis of known proper motions and these observations, we analyse the astrometric results in our "Proper Motion Diagram" (PMD: angular separation / position angle versus time), to eliminate possible (non-moving) background stars, establish co-moving binaries and multiples, and search for curvature as indications for orbital motion. All previously suggested close components are co-moving and no background stars are found. The angular separations range between 0.07 and 9 arcseconds, corresponding to projected distances between the components of 6-845 AU. Thirteen stars are at least binaries and the remaining three (RX J0919.4-7738, RX J0952.7-7933, VW Cha) are confirmed high-order multiple systems with up to four components. In 13 cases, we found significant slopes in the PMDs, which are compatible with orbital motion whose periods range from 60 to 550 years. However, in only four cases there are indications of a curved orbit, the ultimate proof of a gravitational bond. Massive primary components appear to avoid the simultaneous formation of equal-mass secondary components. (abridged)Comment: 33 pages, 22 figures, accepted for publication in A&A, 2nd version: typos and measurement unit added in Table