Miracle-dz/UniFAR-FTUs huggingface dataset:
Immature monocytes acquire antigens from other cells in the bone marrow and present them to T cells after maturing in the periphery

Monocytes are circulating precursors for tissue macrophages and dendritic cells (DCs) but are not recognized to directly participate in antigen presentation. We developed techniques to label mouse monocyte subsets with particulate tracers in vivo. Gr-1lo but not Gr-1hi monocytes were stably labeled by intravenous injection of 0.5-μm microspheres. Gr-1hi monocytes could be labeled when the microspheres were injected after systemic depletion of blood monocytes and spleen macrophages. In this condition, the phagocytic tracer was transferred to immature bone marrow monocytes by neutrophils and B cells that first carried the particles to the bone marrow. Moreover, antigens from B cells or proteins conjugated to the tracer particles were processed for presentation by monocytes and could induce T cell responses in the periphery. Cell-associated antigen taken up by bone marrow monocytes was retained intracellularly for presentation of the antigen days later when monocyte-derived DCs migrated to lymph nodes or in vitro after differentiation with granulocyte/macrophage colony-stimulating factor. These data reveal that immature monocytes unexpectedly sample antigen from the bone marrow environment and that they can present these antigens after they leave the bone marrow.
Finite-sample analysis of Approximate Message Passing

This paper studies the performance of Approximate Message Passing (AMP), in the regime where the problem dimension is large but finite. We consider the setting of high-dimensional regression, where the goal is to estimate a high-dimensional vector β0 from an observation y = Aβ0 + w. AMP is a low-complexity, scalable algorithm for this problem. It has the attractive feature that its performance can be accurately characterized in the asymptotic large system limit by a simple scalar iteration called state evolution. Previous proofs of the validity of state evolution have all been asymptotic convergence results. In this paper, we derive a concentration result for AMP with i.i. d. Gaussian measurement matrices with finite dimension n × N. The result shows that the probability of deviation from the state evolution prediction falls exponentially in n. Our result provides theoretical support for empirical findings that have demonstrated excellent agreement of AMP performance with state evolution predictions for moderately large dimensions.
Analysis of Transforming Growth Factor- β1 Expression in Resorptive Lacunae following Orthodontic Tooth Movement in An Animal Model

Objective Root resorption is a complication of orthodontic treatment and till date, there is a dearth of information regarding this issue. The aim of this study was to determine whether the expression of transforming growth factor-β1 (TGF-β1, an inflammatory cytokine) is related to orthodontic force. Moreover, if associated, the expression level may be helpful in differential diagnosis, control and ultimate treatment of the disease. Materials and Methods In this experimental study, a total of 24 eight-week-old male Wistar rats were selected randomly. On day 0, an orthodontic appliance, which consisted of a closed coil spring, was ligated to the upper right first molar and incisor. The upper left first molar in these animals was not placed under orthodontic force, thus serving as the control group. On day 21, after anesthesia, the animals were sacrificed. The rats were then divided into two equal groups where the first group was subjected to histological evaluation and the second group to reverse transcriptase-polymerase chain reaction (RT-PCR). Orthodontic tooth movement was measured in both groups to determine the influence of the applied force. Results Statistical analysis of data showed a significant root resorption between the experimental group and control group (P<0.05), however, there was no significant difference in the expression level of the inflammatory cytokine, TGF-β1. Conclusion Based on the findings of this study, we suggest that there is a direct relationship between orthodontic force and orthodontic induced inflammatory root resorption. In addition, no relationship is likely to exist between root resorption and TGF-β1 expression in the resorptive lacunae.
Percutaneous coronary intervention in patients with multi-vessel coronary artery disease: a focus on physiology

Multi-vessel coronary artery disease (MVD) frequently features ambiguous or intermediate lesions that may be both serial and complex, suggesting that multiple regions require revascularization. Percutaneous coronary intervention (PCI) is associated with various challenges such as appropriate identification of lesions that should be treated, the choice of an optimum revascularization method, and limitations of long-term outcomes. Optimal patient selection and careful targeting of lesions are key when planning treatment. Physiology-guided decision-making (based on the fractional flow reserve) can overcome the current limitations of PCI used to treat MVD regardless of clinical presentation or disease subtype, as confirmed in recent clinical trials. Here, we review the use of physiology-guided PCI for patients with MVD, and their early and late outcomes.
Preparation, Purification, and Use of Fatty Acid-containing Liposomes

Liposomes containing single-chain amphiphiles, particularly fatty acids, exhibit distinct properties compared to those containing diacylphospholipids due to the unique chemical properties of these amphiphiles. In particular, fatty acid liposomes enhance dynamic character, due to the relatively high solubility of single-chain amphiphiles. Similarly, liposomes containing free fatty acids are more sensitive to salt and divalent cations, due to the strong interactions between the carboxylic acid head groups and metal ions. Here we illustrate techniques for preparation, purification, and use of liposomes comprised in part or whole of single chain amphiphiles (e.g., oleic acids).
Sharable Ontologies as a Basis for Communication and Collaboration in Conceptual Modeling Jeffrey

We are interested in improving collaboration among researchers, domain experts, and knowledge engineers through better knowledge sharing. Building models is not only a way to formulate domain knowledge, but serves more importantly as a means to communicate and come to understand the evolving problem space. An important prerequisite to effective communication is mutual agreement on important terms and concepts, the ontology of the domain. We give an overview of the CODE4 conceptual modeling representation and the DDUCKS modeling environment. We focus on how different classes of ontologies are developed within the tools: top level ontologies with very general concepts, ontologies with modeling concepts, and ontologies for particular domains. We are evaluating theories and contexts as mechanisms for partitioning and managing relationships between groups of concepts. We describe some of the mechanisms we are exploring for exchanging these ontologies with other research groups, and conclude by reviewing important research issues for future work.
Application of Mesenchymal Stem Cells for Therapeutic Agent Delivery in Anti-tumor Treatment

Mesenchymal stem cells (MSCs) are non-hematopoietic progenitor cells, which can be isolated from different types of tissues including bone marrow, adipose tissue, tooth pulp, and placenta/umbilical cord blood. There isolation from adult tissues circumvents the ethical concerns of working with embryonic or fetal stem cells, whilst still providing cells capable of differentiating into various cell lineages, such as adipocytes, osteocytes and chondrocytes. An important feature of MSCs is the low immunogenicity due to the lack of co-stimulatory molecules expression, meaning there is no need for immunosuppression during allogenic transplantation. The tropism of MSCs to damaged tissues and tumor sites makes them a promising vector for therapeutic agent delivery to tumors and metastatic niches. MSCs can be genetically modified by virus vectors to encode tumor suppressor genes, immunomodulating cytokines and their combinations, other therapeutic approaches include MSCs priming/loading with chemotherapeutic drugs or nanoparticles. MSCs derived membrane microvesicles (MVs), which play an important role in intercellular communication, are also considered as a new therapeutic agent and drug delivery vector. Recruited by the tumor, MSCs can exhibit both pro- and anti-oncogenic properties. In this regard, for the development of new methods for cancer therapy using MSCs, a deeper understanding of the molecular and cellular interactions between MSCs and the tumor microenvironment is necessary. In this review, we discuss MSC and tumor interaction mechanisms and review the new therapeutic strategies using MSCs and MSCs derived MVs for cancer treatment.
A fragment of the alarmin prothymosin α as a novel biomarker in murine models of bacteria-induced sepsis

Sepsis is a life-threatening condition that requires urgent care. Thus, the identification of specific and sensitive biomarkers for its early diagnosis and management are of clinical importance. The alarmin prothymosin alpha (proTα) and its decapeptide proTα(100-109) are immunostimulatory peptides related to cell death. In this study, we generated bacterial models of sepsis in mice using two Klebsiella pneumoniae strains (L-78 and ATCC 43816) and monitored sepsis progression using proTα(100-109) as a biomarker. Serum concentration of proTα(100-109) gradually increased as sepsis progressed in mice infected with L-78, a strain which, unlike ATCC 43816, was phagocytosed by monocytes/macrophages. Analysis of splenocytes from L-78-infected animals revealed that post-infection spleen monocytes/macrophages were gradually driven to caspase-3-mediated apoptosis. These results were verified in vitro in L-78-infected human monocytes/macrophages. Efficient phagocytosis of L-78 by monocytes stimulated their apoptosis and the concentration of proTα(100-109) in culture supernatants increased. Human macrophages strongly phagocytosed L-78, but resisted cell death. This is the first report suggesting that high levels of proTα(100-109) correlate, both in vitro and in vivo, with increased percentages of cell apoptosis. Moreover, we showed that low levels of proTα(100-109) early post-infection likely correlate with sepsis resolution and thus, the decapeptide could eventually serve as an early surrogate biomarker for predicting bacteria-induced sepsis outcome.
Quantization bit allocation for reporting-throughput tradeoff in cooperative cognitive radio networks

In cognitive radio (CR) networks, secondary users (SUs) detect and share a spectrum band assigned to a primary user (PU) to communicate with their respective secondary receivers. In order to increase the reliability of the detection performance, the SUs cooperatively sense the spectrum by reporting their local information to a fusion center (FC) after quantization. For an accurate information transferring, the use of the enormous number of quantization bits for reporting is preferred, however, it simultaneously degrades the throughput performance in the perspective of reporting-throughput tradeoff. To tackle this problem, in this paper, we focus on the throughput enhancement for the secondary networks while satisfying a target sensing performance. To this end, we derive the quantized local test statistics of energy detector and propose the quantization bit allocation strategy that maximizes the throughput performance. Moreover, we introduce an adaptive framework to employ the proposed resource allocation scheme in a dynamic environment. Through the numerical results, it is shown that the proposed work exhibits the enhanced throughput performance unlike the conventional schemes.
Structure ofProteusmirabilis bio ¢ lmsgrown inarti ¢ cial urine and standard laboratorymedia

and standard laboratorymedia Steven M. Jones, Jerome Yerly, Yaoping Hu, Howard Ceri & Robert Martinuzzi Calgary Centre for Innovation and Technology (CCIT), University of Calgary, Calgary, Alberta, Canada; Department of Electrical and Computer Engineering, University of Calgary, Calgary, Alberta, Canada; Biofilm Research Group, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada; and Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada
Fast Normal Estimation for Point Clouds with Sharp Features using a Robust Randomized Hough Transform

This paper presents a new method for estimating normals on unorganized point clouds that preserves sharp features. It is based on a robust version of the Randomized Hough Transform (RHT). We consider the filled Hough transform accumulator as an image of the discrete probability distribution of possible normals. The normals we estimate corresponds to the maximum of this distribution. We use a fixed-size accumulator for speed, statistical exploration bounds for robustness, and randomized accumulators to prevent discretization effects. We also propose various sampling strategies to deal with anisotropy, as produced by laser scans due to differences of incidence. Our experiments show that our approach offers an ideal compromise between precision, speed, and robustness: it is at least as precise and noise-resistant as state-of-the-art methods that preserve sharp features, while being almost an order of magnitude faster. Besides, it can handle anisotropy with minor speed and precision losses.
Adaptive Tube-Based Nonlinear MPC for Economic Autonomous Cruise Control of Plug-In Hybrid Electric Vehicles

This paper proposes an adaptive tube-based nonlinear model predictive control (AT-NMPC) approach to the design of autonomous cruise control systems. The proposed method utilizes two separate models to define the constrained receding horizon optimal control problem. A fixed nominal model is used to handle the problem constraints based on a robust tube-based approach. A separate adaptive model is used to define the objective function, which utilizes least square online parameter estimators for adaption. By having two separate models, this method takes into account uncertainties, modeling errors, and delayed data in the design of the controller and guaranties robust constraint handling, while adapting to them to improve control performance. Furthermore, to be able to implement the designed AT-NMPC in real-time, a Newton/GMRES fast solver is employed to solve the optimization problem. Simulations performed on a high-fidelity model of the baseline vehicle, the Toyota plug-in Prius, which is a plug-in hybrid electric vehicle, show that the proposed controller is able to handle the defined constraints in the presence of uncertainty, while improving the energy cost of the trip. Moreover, the result of the hardware-in-loop experiment demonstrates the performance of the proposed controller in a real-time application.
Latency-aware joint virtual machine and policy consolidation for mobile edge computing

To guarantee an efficient and high-performance environment for mobile devices to perform offloading with low end-to-end delay, it is important to ensure no network policies are violated. In this paper, we explore the simultaneous, dynamic virtual machine (VM) and policy consolidation, and formulate the Policy-VM Latency-aware Consolidation problem for Mobile Edge Computing, which is shown to be NP-Hard. We propose the PL-Edge, an efficient scheme to jointly consolidate network policies and virtual machines for mobile edge computing to reduce communication end-to-end delays among devices and virtual machines. Our simulation results demonstrate that the proposed PL-Edge can significantly reduces policy-flows end-to-end delay by nearly 45% while adhering strictly to the requirements of network policies.
How neuroscience can inform the study of individual differences in cognitive abilities

Abstract Theories of human mental abilities should be consistent with what is known in neuroscience. Currently, tests of human mental abilities are modeled by cognitive constructs such as attention, working memory, and speed of information processing. These constructs are in turn related to a single general ability. However, brains are very complex systems and whether most of the variability between the operations of different brains can be ascribed to a single factor is questionable. Research in neuroscience suggests that psychological processes such as perception, attention, decision, and executive control are emergent properties of interacting distributed networks. The modules that make up these networks use similar computational processes that involve multiple forms of neural plasticity, each having different time constants. Accordingly, these networks might best be characterized in terms of the information they process rather than in terms of abstract psychological processes such as working memory and executive control.
Vector network coding based on subspace codes outperforms scalar linear network coding

This paper considers vector network coding based on rank-metric codes and subspace codes. Our main result is that vector network coding can significantly reduce the required field size compared to scalar linear network coding in the same multicast network. The achieved gap between the field size of scalar and vector network coding is in q(h-2)t2/h+o(t) for any q ≥ 2 and any even h ≥ 4, where t denotes the dimension of the vector solution and h the number of messages. If h ≥ 5 is odd, then the achieved gap of the field size between the scalar network coding solution and the vector network coding solution is q(h-3)t2/(h-1)+o(t). Previously, only a gap of constant size had been shown. This implies also the same gap between the field size in linear and non-linear scalar network coding for multicast networks. The results are obtained by considering several multicast networks which are variations of the well-known combination network.
Relational programming with CrocoPat

Many structural analyses of software systems are naturally formalized as relational queries, for example, the detection of design patterns, patterns of problematic design, code clones, dead code, and differences between the as-built and the as-designed architecture. This paper describes CrocoPat, an application-independent tool for relational programming. Through its efficiency and its expressive language, CrocoPat enables practically important analyses of real-world software systems that are not possible with other graph analysis tools, in particular analyses that involve transitive closures and the detection of patterns in graphs. The language is easy to use, because it is based on the well-known first-order predicate logic. The tool is easy to integrate into other software systems, because it is a small command-line tool that uses a simple text format for input and output of relations.
Lymphocytes Contribute to the Pathophysiology of Neonatal Brain Injury

Background Periventricular leukomalacia (PVL) is the most common form of preterm brain injury affecting the cerebral white matter. This type of injury involves a multiphase process and is induced by many factors, including hypoxia–ischemia (HI) and infection. Previous studies have suggested that lymphocytes play a significant role in the pathogenesis of brain injury, and the aim of this study was to determine the contribution of lymphocyte subsets to preterm brain injury. Methods Immunohistochemistry on brain sections from neonatal mice was performed to evaluate the extent of brain injury in wild-type and T cell and B cell-deficient neonatal mice (Rag1−/− mice) using a mouse model of HI-induced preterm brain injury. Flow cytometry was performed to determine the presence of different types of immune cells in mouse brains following HI. In addition, immunostaining for CD3 T cells and CD20 B cells was performed on postmortem preterm human infant brains with PVL. Results Mature lymphocyte-deficient Rag1−/− mice showed protection from white matter loss compared to wild type mice as indicated by myelin basic protein immunostaining of mouse brains. CD3+ T cells and CD20+ B cells were observed in the postmortem preterm infant brains with PVL. Flow cytometry analysis of mouse brains after HI-induced injury showed increased frequency of CD3+ T, αβT and B cells at 7 days after HI in the ipsilateral (injured) hemisphere compared to the contralateral (control, uninjured) hemisphere. Conclusion Lymphocytes were found in the injured brain after injury in both mice and humans, and lack of mature lymphocytes protected neonatal mice from HI-induced brain white matter injury. This finding provides insight into the pathology of perinatal brain injury and suggests new avenues for the development of therapeutic strategies.
Adhesive bond strength and compressive strength of a novel bulk fill composite with zirconia nano-hybrid filler

Abstract The aim of the study was to investigate the adhesive bond and compressive strength of novel bulk fill resin composite with zirconia (Zr) nano-hybrid filler. Sixty molars were mounted in acrylic resin with flat occlusal surface. Half of the specimen (n = 30) were bonded using total etch (TE) and the other half with self-etch (SE) technique. Specimens treated with SE (n = 30) and TE (n = 30) bonding protocol were divided into three groups, based on the type of bulk fill build-up materials (ZC–ZirconCore, MC–MulticCore Flow and LC–Luxacore Dual), resulting in six study groups [MC-TE, MC-SE, LC-TE, LC-SE, ZC-TE, ZC-SE]. Cylindrical (3 × 3 mm) build-ups were performed followed by shear bond strength testing (crosshead speed-1 mm/min). Ten specimens for each bulk fill build-up material (MC, LC and ZC) were prepared for compressive strength testing. All specimens were tested for maximum failure loads (crosshead speed−0.5 cm/min). Analysis of variance and paired t-test were performed to statistically analyze the data. TE technique showed significantly higher bond strength values as compared to SE technique (p < 0.001) for all three materials (MC, LC and ZC). Shear bond strength for MC [TE,17.88(2.00)-SE,9.43(0.98)] and LC [TE,18.91(2.57)-SE,6.35(1.12)] groups were significantly higher than ZC group [TE,13.99(1.09)-SE,4.61(0.84)]. Specimens in ZC group (266.73 ± 9.76) showed significantly higher compressive strength in comparison to MC (247.66 ± 9.72) (p = 0.004) and LC (249.87 ± 13.17) (p < 0.001) groups. Zirconia nano-hybrid filler resin bulk fill material has comparatively high compressive strength and low bond strength making them suitable for clinical applications in the posterior region with favorable conditions for adhesive bonding.
Improving the AMSR-E Soil Moisture Algorithm of the University of Tokyo through Field Experiments and Parameters Optimization

This paper reports the progresses of AMSR-E soil moisture algorithm development at the University of Tokyo. The first progress is made through improving the forward model, i.e. radiative transfer model (RTM), based on field experiment and numerical simulation. The second progress is the development of a new parameterization method, through which the parameters necessary for the algorithm are optimized by a land data assimilation system developed at the University of Tokyo (LDAS-UT). The capability of LDAS-UT was validated successfully with winter wheat experiment data. Finally, the new RTM and parameterization method was validated on AMSR-E match up data set. The results demonstrate that the simulated brightness temperature is in good agreements with the one observed by AMSR-E.