Small High-Density Lipoprotein (HDL) Subclasses are Increased with Decreased Activity of HDL-Associated Phospholipase A2 in Subjects with Prediabetes

Alterations in high-density lipoprotein (HDL) subclass distribution, as well as in the activities of HDL-associated enzymes, have been associated with increased cardiovascular disease (CVD) risk. HDL subclass distribution and the activities of HDL-associated enzymes remain unknown in prediabetic patients, a condition also associated with increased CVD risk. The aim of the present study was to assess any differences in HDL subclass distribution (using polyacrylamide gel electrophoresis) and in activities of HDL-associated enzymes between prediabetic (impaired fasting glucose, IFG, n = 80) and non-prediabetic subjects (n = 105). Subjects with prediabetes had significantly increased waist circumference, blood pressure and triacylglycerol (TAG) levels compared with subjects with fasting glucose levels <100 mg/dL (all p < 0.05). The proportion of small HDL3 over HDL cholesterol (HDL-C) was significantly increased in prediabetic subjects compared with their controls (p < 0.05). The activity of the anti-atherogenic HDL-associated lipoprotein-associated phospholipase A₂ (HDL-LpPLA₂) was significantly lower in subjects with prediabetes (p < 0.05), whereas the activity of paraoxonase 1 (using both paraoxon and phenyl acetate as substrates) did not significantly differ between subjects with or without prediabetes. In a stepwise linear regression analysis, the proportion of small HDL3 over HDL-C concentration was independently associated with the presence of prediabetes and with total cholesterol and TAG concentration (positively), as well as with HDL-C levels (negatively). We also observed a trend of increased small dense low-density lipoprotein cholesterol levels in prediabetic subjects compared with their controls. Subjects with IFG exhibit increased proportion of small HDL3 particles combined with decreased activity of the anti-atherogenic HDL-LpPLA₂.     

Control of particle size distribution described by a population balance model of semibatch emulsion polymerization

This work addresses the computation of surfactant feed profiles for shaping a particle size distribution to a bimodal target distribution. A fundamental population balance model of styrene semibatch emulsion polymerization is used in this control study. Both surfactant feed rate and free surfactant concentration are considered as alternative control variables and a comparison is made of the two approaches. A comparison is also made of several different objective function norms in the optimization. Results suggest that a min–max norm, tied to the distribution modes, is the most appropriate metric.     

Efficient architectures for modulo 2n − 2 arithmetic units

Moduli of the 2ⁿ and 2ⁿ ± 1 forms are usually employed in designs that adopt the residue number system. However, in several cases such as in finite impulse response filters and communication components, a modulo value equal to 2ⁿ ? 2 can be used. So far, modulo 2ⁿ ? 2 arithmetic units have been based either on look-up tables or on generic modulo arithmetic units. In this work, by taking advantage of the properties of modulo 2ⁿ ? 2 arithmetic, we propose efficient modulo 2ⁿ ? 2 multi-operand adder, multiplier as well as squarer architectures. The proposed circuits are based on the corresponding ones for modulo 2^n?1 ? 1 arithmetic and some simple logic. Experimental results validate that the proposed circuits achieve significant area and delay savings compared to those previously presented.     

Immunotherapy as a Therapeutic Strategy for Gastrointestinal Cancer—Current Treatment Options and Future Perspectives

Gastrointestinal (GI) cancer constitutes a highly lethal entity among malignancies in the last decades and is still a major challenge for cancer therapeutic options. Despite the current combinational treatment strategies, including chemotherapy, surgery, radiotherapy, and targeted therapies, the survival rates remain notably low for patients with advanced disease. A better knowledge of the molecular mechanisms that influence tumor progression and the development of optimal therapeutic strategies for GI malignancies are urgently needed. Currently, the development and the assessment of the efficacy of immunotherapeutic agents in GI cancer are in the spotlight of several clinical trials. Thus, several new modalities and combinational treatments with other anti-neoplastic agents have been identified and evaluated for their efficiency in cancer management, including immune checkpoint inhibitors, adoptive cell transfer, chimeric antigen receptor (CAR)-T cell therapy, cancer vaccines, and/or combinations thereof. Understanding the interrelation among the tumor microenvironment, cancer progression, and immune resistance is pivotal for the optimal therapeutic management of all gastrointestinal solid tumors. This review will shed light on the recent advances and future directions of immunotherapy for malignant tumors of the GI system.     

Stability of the spectral responsivity of cryogenically cooled InSb infrared detectors

The spectral responsivity of two cryogenically cooled InSb detectors was observed to drift slowly with time. The origin of these drifts was investigated and was shown to occur due to a water-ice thin film that was deposited onto the active areas of the cold detectors. The presence of the ice film (which is itself a dielectric film) modifies the transmission characteristics of the antireflection coatings deposited on the active areas of the detectors, thus giving rise to the observed drifts. The magnitude of the drifts was drastically reduced by evacuating the detector dewars while baking them at 50 degrees C for approximately 48 h. All InSb detectors have antireflection coatings to reduce the Fresnel reflections and therefore enhance their spectral responsivity. This work demonstrates that InSb infrared detectors should be evacuated and baked at least annually and in some cases (depending on the quality of the dewar and the measurement uncertainty required) more frequently. These observations are particularly relevant to InSb detectors mounted in dewars that use rubber O rings since the ingress of moisture was found to be particularly serious in this type of dewar.     

Distributed algorithms for barrier coverage using relocatable sensors

We study the barrier coverage problem using relocatable sensor nodes. We assume each sensor can sense an intruder or event inside its sensing range. Sensors are initially located at arbitrary positions on the barrier and can move along the barrier. The goal is to find final positions for sensors so that the entire barrier is covered. In recent years, the problem has been studied extensively in the centralized setting. In this paper, we study a barrier coverage problem in the distributed and discrete setting. We assume that we have n identical sensors located at grid positions on the barrier, and that each sensor repeatedly executes a Look-Compute-Move cycle: based on what it sees in its vicinity, it makes a decision on where to move, and moves to its next position. We make two strong but realistic restrictions on the capabilities of sensors: they have a constant visibility range and can move only a constant distance in every cycle. In this model, we give the first two distributed algorithms that achieve barrier coverage for a line segment barrier when there are enough nodes in the network to cover the entire barrier. Our algorithms are synchronous, and local in the sense that sensors make their decisions independently based only on what they see within their constant visibility range. One of our algorithms is oblivious whereas the other uses two bits of memory at each sensor to store the type of move made in the previous step. We show that our oblivious algorithm terminates within \(\varTheta (n^2)\) steps with the barrier fully covered, while the constant-memory algorithm is shown to take \(\varTheta (n)\) steps to terminate in the worst case. Since any algorithm in which a sensor can only move a constant distance in one step requires \(\varOmega (n)\) steps on some inputs, our second algorithm is asymptotically optimal.     

Deep Neural Network Augmentation: Generating Faces for Affect Analysis

International Journal of Computer Vision - This paper presents a novel approach for synthesizing facial affect; either in terms of the six basic expressions (i.e., anger, disgust, fear, joy,...     

Learning Part Boundaries from 3D Point Clouds

We present a method that detects boundaries of parts in 3D shapes represented as point clouds. Our method is based on a graph convolutional network architecture that outputs a probability for a point to lie in an area that separates two or more parts in a 3D shape. Our boundary detector is quite generic: it can be trained to localize boundaries of semantic parts or geometric primitives commonly used in 3D modeling. Our experiments demonstrate that our method can extract more accurate boundaries that are closer to ground-truth ones compared to alternatives. We also demonstrate an application of our network to fine-grained semantic shape segmentation, where we also show improvements in terms of part labeling performance.     

Active neural learners for text with dual supervision

Neural Computing and Applications - Dual supervision for text classification and information retrieval, which involves training the machine with class labels augmented with text annotations that...     

The Role of Marrow Microenvironment in the Growth and Development of Malignant Plasma Cells in Multiple Myeloma

The development and effectiveness of novel therapies in multiple myeloma have been established in large clinical trials. However, multiple myeloma remains an incurable malignancy despite significant therapeutic advances. Accumulating data have elucidated our understanding of the genetic background of the malignant plasma cells along with the role of the bone marrow microenvironment. Currently, the interaction among myeloma cells and the components of the microenvironment are considered crucial in multiple myeloma pathogenesis. Adhesion molecules, cytokines and the extracellular matrix play a critical role in the interplay among genetically transformed clonal plasma cells and stromal cells, leading to the proliferation, progression and survival of myeloma cells. In this review, we provide an overview of the multifaceted role of the bone marrow microenvironment in the growth and development of malignant plasma cells in multiple myeloma.