Miracle-dz/UniFAR-FTUs huggingface dataset:
Persistence of antibiotic resistance plasmids in bacterial biofilms

The emergence and spread of antibiotic resistance is a crisis in health care today. Antibiotic resistance is often horizontally transferred to susceptible bacteria by means of multi-drug resistance plasmids that may or may not persist in the absence of antibiotics. Because bacterial pathogens often grow as biofilms, there is a need to better understand the evolution of plasmid persistence in these environments. Here we compared the evolution of plasmid persistence in the pathogen Acinetobacter baumannii when grown under antibiotic selection in biofilms versus well-mixed liquid cultures. After four weeks, clones in which the plasmid was more stably maintained in the absence of antibiotic selection were present in both populations. On average plasmid persistence increased more in liquid batch cultures, but variation in the degree of persistence was greater among biofilm-derived clones. The results of this study show for the first time that the persistence of MDR plasmids improves in biofilms.
Sub-100-fs 1.87 GHz mode-locked fiber laser using stretched-soliton effects

Current pulsed fiber lasers that are capable of delivering stable sub-100-fs pulses at megahertz repetition rates require intracavity pulse energies in the nanojoule range. Scaling these lasers to gigahertz repetition rates necessitates, therefore, very high average power levels and complex cladding-pumped configurations. Here we report a type of stretched-soliton all-fiber laser that generates broadband, soliton-like pulses at 1.55 μm with intracavity pulse energies of only tens of picojoules. In the laser cavity, strong dispersion management leads to a temporal breathing ratio of ∼70, while the weak residual anomalous dispersion is perfectly balanced by the low Kerr nonlinearity, resulting in the formation of temporally stretched, hyperbolic-secant pulses. A lumped wavelength-dependent attenuator compensates for the effects of the gain filtering on the pulse spectrum, ensuring intracavity pulse self-consistency. This unique stretched-soliton mechanism, combined with a harmonic mode-locking technique based on intense optoacoustic interactions in solid-core photonic crystal fiber, yields for the first time stable gigahertz-rate, sub-100-fs, dispersive-wave-free pulse trains at moderate pump powers.
Metalloproteases and inhibitors in arthritic diseases.

Controlling degradation of the extracellular matrix is crucial in arthritic diseases such as osteoarthritis (OA) and rheumatoid arthritis (RA), as conventional treatments do not positively affect the structural properties of the articular tissues. Metalloproteases, a family of zinc-dependent enzymes, and more specifically the matrix metalloproteases (MMPs), play a premier role in joint articular tissue degeneration. Additional enzymes of the metalloprotease family, such as the membrane-type metalloproteases (MT-MMPs) and the adamalysins that include the ADAMs and the ADAMTS families, have also been found to be involved in these disease processes. At present, therapeutic intervention based on the inhibition of metalloproteases, and more particularly of the MMPs, is under intensive investigation, and several MMP inhibitors are in clinical development. Currently, MMP inhibitors are exemplified by several chemical classes: hydroxamic acids, carboxylic acids and thiols. One key issue in the clinical development of MMP inhibitors relates to whether broad-spectrum inhibitors active against a range of different enzymes or selective inhibitors targeted against a single enzyme or particular subset of the MMPs represents the optimal strategy. In this chapter, we address the different metalloprotease enzymes and sub-families and their implication in arthritic diseases. Furthermore, we assess physiological and chemical metalloprotease inhibitors, and for the latter, the current inhibitory classes of compounds being studied.
Speaker-Independent Malay Syllable Recognition Using Singular and Modular Neural Networks

This paper describes a design procedure for a fuzzy logic based power system stabilizer (FLPSS) and adaptive neuro–fuzzy inference system (ANFIS) and investigates their robustness for a multi–machine power system. Speed deviation of a machine and its derivative are chosen as the input signals to the FLPSS. A four–machine and a two–area power system is used as the case study. Computer simulations for the test system subjected to transient disturbances i.e. a three phase fault, were carried out and the results showed that the proposed controller is able to prove its effectiveness and improve the system damping when compared to a conventional lead–lag based power system stabilizer controller.
TSLP acts on infiltrating effector T cells to drive allergic skin inflammation

Thymic stromal lymphopoietin (TSLP) is a cytokine expressed by epithelial cells, including keratinocytes, and is important in allergic inflammation. Allergic skin inflammation elicited by epicutaneous immunization of mice with ovalbumin (OVA), a potential model of atopic dermatitis, was severely impaired in TSLPR−/− mice, as evidenced by decreased infiltration of eosinophils and decreased local expression of T helper 2 (Th2) cytokines. However, secretion of Th2 cytokines by splenocytes from epicutaneous sensitized TSLPR−/− mice in response to OVA was normal. Skin dendritic cells from TSLPR−/− mice were normal in their ability to migrate to draining lymph nodes, express activation markers, and induce proliferation and Th2 cytokine production by naïve T cells. CD4+ T cells from TSLPR−/− mice expressed the skin homing receptor E-selectin ligand normally, and homed to the skin normally, but failed to transfer allergic skin inflammation to WT recipients. TSLP enhanced Th2 cytokine secretion in vitro by targeting TSLPR on antigen specific T cells. Intradermal injection of anti-TSLP blocked the development of allergic skin inflammation after cutaneous antigen challenge of OVA immunized WT mice. These findings suggest that TSLP is essential for antigen driven Th2 cytokine secretion by skin infiltrating effector T cells and could be a therapeutic target in allergic skin inflammation.
Bayes-Adaptive POMDPs

Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning. However most investigations of Bayesian reinforcement learning to date focus on the standard Markov Decision Processes (MDPs). Our goal is to extend these ideas to the more general Partially Observable MDP (POMDP) framework, where the state is a hidden variable. To address this problem, we introduce a new mathematical model, the Bayes-Adaptive POMDP. This new model allows us to (1) improve knowledge of the POMDP domain through interaction with the environment, and (2) plan optimal sequences of actions which can tradeoff between improving the model, identifying the state, and gathering reward. We show how the model can be finitely approximated while preserving the value function. We describe approximations for belief tracking and planning in this model. Empirical results on two domains show that the model estimate and agent's return improve over time, as the agent learns better model estimates.
Thread-based Programming for the EM-4 Hybrid Dataflow Machine

In this paper, we present a thread-based programming model for the EM-4 hybrid dataflow machine, where parallelism and synchronization among threads of sequential execution are described explicitly by the programmer. Although EM-4 was originally designed as a dataflow machine, we demonstrate that it provides effective architectural support for a variety of programming styles, including message passing and distributed data sharing in imperative languages. Our approach allows the programmer to control the parallelism and maintain data locality explicitly to achieve high performance. EM-4 can be thought of as a multi-threaded architecture that can exploit both von Neumann and dataflow compiling technology. Thread-based programming provides the first step to explore better programming/compiling technology for a hybrid dataflow ma- chine as well as EM-4.
Analysis of the biosynthetic gene cluster for the polyether antibiotic monensin in Streptomyces cinnamonensis and evidence for the role of monB and monC genes in oxidative cyclization

The analysis of a candidate biosynthetic gene cluster (97 kbp) for the polyether ionophore monensin from Streptomyces cinnamonensis has revealed a modular polyketide synthase composed of eight separate multienzyme subunits housing a total of 12 extension modules, and flanked by numerous other genes for which a plausible function in monensin biosynthesis can be ascribed. Deletion of essentially all these clustered genes specifically abolished monensin production, while overexpression in S. cinnamonensis of the putative pathway‐specific regulatory gene monR led to a fivefold increase in monensin production. Experimental support is presented for a recently‐proposed mechanism, for oxidative cyclization of a linear polyketide intermediate, involving four enzymes, the products of monBI, monBII, monCI and monCII. In frame deletion of either of the individual genes monCII (encoding a putative cyclase) or monBII (encoding a putative novel isomerase) specifically abolished monensin production. Also, heterologous expression of monCI, encoding a flavin‐linked epoxidase, in S. coelicolor was shown to significantly increase the ability of S. coelicolor to epoxidize linalool, a model substrate for the presumed linear polyketide intermediate in monensin biosynthesis.
Process development and adhesion behavior of electroless copper on liquid crystal polymer (LCP) for electronic packaging application

Liquid crystal polymer (LCP) has potentially a very wide application as substrate material in electronic packaging applications because of its unique advantages. The work in this paper was performed to realize the metallization of LCP for the purpose of board fabrication, and to study the adhesion between deposited copper and LCP. A homogenous electroless plated copper layer on LCP with 4 to 5 /spl mu/m thickness was achieved, while it increased up to 40 /spl mu/m with the subsequent electroplating. The timescale of etching, deposit ion rate, and pH value were gradually changing during the plating process and the influences on copper layer quality were investigated. The adhesion force of the copper-LCP layer system was measured by a shear-off-method. Scanning electron microscopy (SEM) was used to check the surface morphology after etching and the interface after shearing on both the backside of the copper layer and the LCP side. The relationship between the shear-off adhesion of copper and the time of chemical etching before plating was examined, and the optimal etching time is discussed. Heat treatment after plating was used, and it was shown that this significantly improved the adhesion strength.
2.5D Active Contour for Surface Reconstruction

In this paper, we present a new deformable model — 2.5D Active Contour— that is capable of directly extracting shape geometry from 3D unorganized point cloud datasets. The reconstructed surfaces are either open or closed. Furthermore, the new model can reconstruct and discover non-manifold geometry hidden in the point-cloud dataset. Our algorithm starts from a simple seed (e.g. a triangle) that can be automatically initialized, and always enlarges the model boundary outwards along its tangent direction suggested by the underlying dataset. This mechanism ensures that our novel models “flow” directly over the data boundary through the expansion of its bounding contour. To maintain the regularity of the model and the stability of the numerical integration process, commonly used mesh optimization techniques are employed throughout the deformation process. In addition, the new model can recover fine details of the underlying shape through local/adaptive refinements. We demonstrate both the accuracy and the robustness of our algorithm through a number of experiments on both real and synthetic datasets.
Cancer Immunotherapy: Whence and Whither

The current concepts and practice of cancer immunotherapy evolved from classical experiments that distinguished "self" from "non-self" and the finding that humoral immunity is complemented by cellular immunity. Elucidation of the biology underlying immune checkpoints and interactions between ligands and ligand receptors that govern the immune system's ability to recognize tumor cells as foreign has led to the emergence of new strategies that mobilize the immune system to reverse this apparent tolerance. Some of these approaches have led to new therapies such as the use of mAbs to interfere with the immune checkpoint. Others have exploited molecular technologies to reengineer a subset of T cells to directly engage and kill tumor cells, particularly those of B-cell malignancies. However, before immunotherapy can become a more effective method of cancer care, there are many challenges that remain to be addressed and hurdles to overcome. Included are manipulation of tumor microenvironment (TME) to enhance T effector cell infiltration and access to the tumor, augmentation of tumor MHC expression for adequate presentation of tumor associated antigens, regulation of cytokines and their potential adverse effects, and reduced risk of secondary malignancies as a consequence of mutations generated by the various forms of genetic engineering of immune cells. Despite these challenges, the future of immunotherapy as a standard anticancer therapy is encouraging. Mol Cancer Res; 15(6); 635–50. ©2017 AACR.
Prolonged Antiretroviral Therapy Preserves HIV-1-Specific CD8 T Cells with Stem Cell-Like Properties

ABSTRACT HIV-1-specific CD8 T cells can influence HIV-1 disease progression during untreated HIV-1 infection, but the functional and phenotypic properties of HIV-1-specific CD8 T cells in individuals treated with suppressive antiretroviral therapy remain less well understood. Here we show that a subgroup of HIV-1-specific CD8 T cells with stem cell-like properties, termed T memory stem cells (TSCM cells), is enriched in patients receiving suppressive antiretroviral therapy compared with their levels in untreated progressors or controllers. In addition, a prolonged duration of antiretroviral therapy was associated with a progressive increase in the relative proportions of these stem cell-like HIV-1-specific CD8 T cells. Interestingly, the proportions of HIV-1-specific CD8 TSCM cells and total HIV-1-specific CD8 TSCM cells were associated with the CD4 T cell counts during treatment with antiretroviral therapy but not with CD4 T cell counts, viral loads, or immune activation parameters in untreated patients, including controllers. HIV-1-specific CD8 TSCM cells had increased abilities to secrete interleukin-2 in response to viral antigen, while secretion of gamma interferon (IFN-γ) was more limited in comparison to alternative HIV-1-specific CD8 T cell subsets; however, only proportions of IFN-γ-secreting HIV-1-specific CD8 TSCM cells were associated with CD4 T cell counts during antiretroviral therapy. Together, these data suggest that HIV-1-specific CD8 TSCM cells represent a long-lasting component of the cellular immune response to HIV-1 that persists in an antigen-independent fashion during antiretroviral therapy but seems unable to survive and expand under conditions of ongoing viral replication during untreated infection. IMPORTANCE Memory CD8 T cells that imitate the functional properties of stem cells to maintain lifelong cellular immunity have been hypothesized for many years, but only recently have such cells, termed T memory stem cells (TSCM cells), been physically identified and isolated in humans, mice, and nonhuman primates. Here, we investigated whether cellular immune responses against HIV-1 include such T memory stem cells. Our data show that HIV-1-specific CD8 T memory stem cells are detectable during all stages of HIV-1 infection but occur most visibly at times of prolonged viral antigen suppression by antiretroviral combination therapy. These cells may therefore be particularly relevant for designing antiviral immune defense strategies against the residual reservoir of HIV-1-infected cells that persists despite treatment and leads to viral rebound upon treatment discontinuation.
Endovascular coil embolization of aneurysm neck for the treatment of ruptured intracranial aneurysm with bleb formation

Background Ruptured intracranial aneurysm (ICA) with bleb formation (RICABF) is a special type of ruptured ICA. However, the exact role and effectiveness of endovascular coil embolization (ECE) in RICABF is unknown. We aimed to investigate the effectiveness and safety of ECE of aneurysm neck for RICABF treatment. Material/Methods We retrospectively assessed consecutive patients who were hospitalized in our endovascular intervention center between October 2004 and May 2012. Overall, 86 patients underwent ECE of aneurysm neck for 86 RICABF. Treatments outcomes included secondary rupture/bleeding rate, aneurysm neck embolization rate, residual/recurrent aneurysm, intraoperative incidents, and post-embolization complications, as well as improvements in the Glasgow outcome scale (extended) (GOS-E). Results Complete occlusion was achieved in 72 aneurysms (72/86, 83.7%), while 12 aneurysms (12/86, 14.0%) had a residual neck, and 2 aneurysms (2/86, 2.3%) had a residual aneurysm. The postoperative GOS-E was 3 in 3 patients (3.5%), 4 in 10 patients (11.6%), and 5 in 73 patients (84.9%). Follow-up angiography was performed in all patients (mean 9.0 months, interquartile range of 9.0). Recurrence was found in 3 patients (3/86, 3.5%). No aneurysm rupture or bleeding was reported. Conclusions Our mid-term follow-up study showed that ECE of aneurysm neck was an effective and safe treatment modality for RICABF. The long-term effectiveness and safety of this interventional radiology technique need to be investigated in prospective and comparative studies.
Compact in-fiber polarizer based on the hollow-core photonic bandgap fiber

A broadband, compact in-fiber polarizer was fabricated by using a pulsed CO2 laser to modify the air-holes along oneside of a hollow-core photonic bandgap fiber. The polarizer has a length of 3 to 6mm and exhibits a polarization extinction ratio of better than 20 dB over a wavelength range of 100nm around 1550nm.
Construction of Forestry Resource Classification Rule Decision Tree Based on ID3 Algorithm

This paper emphasized on the implementation of ID3 algorithm in forestry resource classification rule decision tree. Use ID3 algorithm to analysis the correlation information among forestry species, altitude, origin, forest group and rows by establishing decision tree model, and provide reference for the related decision support. It is proved that this method has a good application prospect in forest resource mode evaluation.
Genome duplications and other features in 12 Mb of DNA sequence from human chromosome 16p and 16q.

Several publicly funded large-scale sequencing efforts have been initiated with the goal of completing the first reference human genome sequence by the year 2005. Here we present the results of analysis of 11.8 Mb of genomic sequence from chromosome 16. The apparent gene density varies throughout the region, but the number of genes predicted (84) suggests that this is a gene-poor region. This result may also suggest that the total number of human genes is likely to be at the lower end of published estimates. One of the most interesting aspects of this region of the genome is the presence of highly homologous, recently duplicated tracts of sequence distributed throughout the p-arm. Such duplications have implications for mapping and gene analysis as well as the predisposition to recurrent chromosomal structural rearrangements associated with genetic disease.
A Theory of Credit Scoring and Competitive Pricing of Default Risk

We propose a theory of unsecured consumer credit where: (i) borrowers have the legal option to default; (ii) defaulters are not exogenously excluded from future borrowing; (iii) there is free entry of lenders; and (iv) lenders cannot collude to punish defaulters. In our framework, limited credit or credit at higher interest rates following default arises from the lender's optimal response to limited information about the agent's type and earnings realizations. The lender learns from an individual's borrowing and repayment behavior about his type and encapsulates his reputation for not defaulting in a credit score. We take the theory to data choosing the parameters of the model to match key data moments such as the overall and subprime delinquency rates. We test the theory by showing that our underlying framework is broadly consistent with the way credit scores affect unsecured consumer credit market behavior. The framework can be used to shed light on household consumption smoothing with respect to transitory income shocks and to examine the welfare consequences of legal restrictions on the length of time adverse events can remain on one's credit record.
The homeobox protein Prox 1 is a negative modulator of ERR a / PGC-1 a bioenergetic functions

Goodman Cancer Centre, McGill University, Montréal, Québec H3A 1A3, Canada; Department of Biochemistry, McGill University, Montréal, Québec H3G 1Y6, Canada; Department of Systems Biology, Massachusetts General Hospital, Cambridge, Massachusetts 02142, USA; Centre for Human Genetic Research, Massachusetts General Hospital, Cambridge, Massachusetts 02142, USA; Broad Institute of Massachusetts Institute of Technology/Harvard, Cambridge, Massachusetts 02142, USA; Department of Medicine, McGill University, Montréal, Québec H3G 1Y6, Canada; Department of Oncology, McGill University, Montréal, Québec H3G 1Y6, Canada
The Role of Endothelial Mechanosensing in Capillary Development and Organization.

xi Chapter 1: Introduction . 1 Motivation & Significance . 1 Cellular Migration & Mechanics . 7 Synthetic ECM for Endothelial Cell Culture . 9 Objectives & Specific Aims . 13 Overview of Methods . 15 References . 17 Chapter 2: Development of a biosynthetic material platform for endothelial cell culture . 29 Introduction . 29 Methods . 31
Fast estimation of software energy consumption using IPI(Inter-Prefetch Interval) energy model

In this paper, we present the way of fast and accurate estimation of software energy consumption in off-the-shelf pro- cessor using IPI(Inter-Prefetch Interval) energy model. In our previous work[1], we proposed a new energy estimation method, and presented the way to characterize IPI energy model. However, there were some drawbacks in our previous work. First, the previous IPI energy model was only able to cover basic block. Second, it took too much time to estimate energy consumption of software due to the absence of energy estimator. To tackle these problems, in this paper, we propose modified IPI energy model, and present the way to implement IPI energy estimator using off-the-shelf system-level simulator. By using this, we can analyze such dynamic effect as address jump due to branch instructions and stalls due to hazard fast and accurately. The major challenging issue when implementing IPI energy estimator is cycle-by-cycle behavioral discrepancy between physical chip and ISS(Instruction Set Simulator) in system-level simulator. In order to overcome this problem, we propose training method to reduce the discrepancy. To verify our method, we applied our idea to ARM1136JF-S real chip. By the result of this work, the accuracy of energy estimation is more than 90% compared to measured data on prototyping board.