Miracle-dz/UniFAR-FTUs huggingface dataset:
Plasma endogenous enkephalin levels in early systemic sclerosis: clinical and laboratory associations.

OBJECTIVE Met- and leu-enkephalins are endogenous opioid neuropeptides with potent analgesic, vasoactive, immunomodulatory and anti-apoptotic properties. We hypothesised that clinical or immunological variables of early systemic sclerosis (SSc) might be correlated to plasma enkephalin levels. METHODS Plasma samples were collected at study entry of the Genetics versus Environment in Scleroderma Outcomes Study (GENISOS) cohort (early SSc, n=116). Plasma met-enkephalin and leu-enkephalin levels (microg/ml) were measured by high performance liquid chromatography (HPLC) and correlated to clinical and laboratory parameters in the GENISOS database. Statistical analyses were performed by nonparametric Wilcoxon rank sum tests and Pearson correlation coefficients. RESULTS Significantly lower plasma met-enkephalin levels were associated with anti-topoisomerase-I seropositivity (6+8.3 vs. 14.9+22.8 microg/ml, p=0.02). Plasma leu-enkephalin levels were significantly higher in SSc patients with digital pulp loss (95.6+130 vs. 64.9+101 microg/ml, p=0.02). Lower mean plasma met-enkephalin levels and inversely higher leu-enkephalin levels were noted in SSc patients with Raynaud's phenomena (p=NS). CONCLUSION The associations of plasma enkephalin levels to immunologic or clinical pathologies may underscore their vasogenic or fibrogenic significance and potential as therapeutic targets in early SSc.
Finite Automata and Their Decision Problems

Finite automata are considered in this paper as instruments for classifying finite tapes. Each one-tape automaton defines a set of tapes, a two-tape automaton defines a set of pairs of tapes, et cetera. The structure of the defined sets is studied. Various generalizations of the notion of an automaton are introduced and their relation to the classical automata is determined. Some decision problems concerning automata are shown to be solvable by effective algorithms; others turn out to be unsolvable by algorithms.
Transforming growth factor‐β and forskolin attenuate the adverse effects of long‐term Schwann cell denervation on peripheral nerve regeneration in vivo

Transforming growth factor‐β (TGF‐β) plays a central role in the regulation of Schwann cell (SC) proliferation and differentiation and is essential for the neurotrophic effects of several neurotrophic factors (reviewed by Unsicker and Krieglstein, 2000 ; Unsicker and Strelau, 2000 ). However, its role in peripheral nerve regeneration in vivo is not yet understood. Our studies were carried out to characterize (1) the effects of duration of regeneration, and chronic SC denervation on the number of tibial (TIB) motor neurons that regenerated axons over a fixed distance (25 mm into distal common peroneal [CP] nerve stumps), and (2) the effect of in vitro incubation of 6‐month chronically denervated sciatic nerve explants with TGF‐β and forskolin on their capacity to support axonal regeneration in vivo. TIB–CP cross‐suture in Silastic tubing was used, and regeneration into 0–24‐week chronically denervated CP stumps was allowed for either 1.5 or 3 months. Chronically denervated rat sciatic nerve explants (3 × 3 mm2) were incubated in vitro with either DMEM and 15% fetal calf serum (D‐15) plus TGF‐β/forskolin or D‐15 alone for 48 h and placed into a 10‐mm Silastic tube that bridged the proximal and distal nerve stumps of a freshly cut TIB nerve. The number of tibial motor neurons that regenerated axons through the explants and 25 mm into the distal nerve stump after 6 months, and TIB regeneration into the CP nerve stumps, were assessed using retrograde tracers, fluorogold, or fluororuby. We found that all tibial motor neurons regenerate their axons 25 mm into 0–4‐week denervated CP nerve stumps after a regeneration period of 3 months. Reducing regeneration time to 1.5 months and chronic denervation, reduced the number of motor neurons that regenerated axons over 25 mm. Exposure of 6‐month denervated nerve explants to TGF‐β/forskolin increased the number of motor neurons that regenerated through them from 258 ± 13; mean ± SE to 442 ± 22. Hence, acute treatment of atrophic SC with TGF‐β can reactivate the growth‐permissive SC phenotype to support axonal regeneration. GLIA 37:206–218, 2002. © 2002 Wiley‐Liss, Inc.
Intranasal BMP9 Ameliorates Alzheimer Disease-Like Pathology and Cognitive Deficits in APP/PS1 Transgenic Mice

Alzheimer’s disease (AD) is the most common type of dementia and has no effective therapies. Previous studies showed that bone morphogenetic protein 9 (BMP9), an important factor in the differentiation and phenotype maintenance of cholinergic neurons, ameliorated the cholinergic defects resulting from amyloid deposition. These findings suggest that BMP9 has potential as a therapeutic agent for AD. However, the effects of BMP9 on cognitive function in AD and its underlying mechanisms remain elusive. In the present study, BMP9 was delivered intranasally to 7-month-old APP/PS1 mice for 4 weeks. Our data showed that intranasal BMP9 administration significantly improved the spatial and associative learning and memory of APP/PS1 mice. We also found that intranasal BMP9 administration significantly reduced the amyloid β (Aβ) plaques overall, inhibited tau hyperphosphorylation, and suppressed neuroinflammation in the transgenic mouse brain. Furthermore, intranasal BMP9 administration significantly promoted the expression of low-density lipoprotein receptor-related protein 1 (LRP1), an important membrane receptor involved in the clearance of amyloid β via the blood-brain barrier (BBB), and elevated the phosphorylation levels of glycogen synthase kinase-3β (Ser9), which is considered the main kinase involved in tau hyperphosphorylation. Our results suggest that BMP9 may be a promising candidate for treating AD by targeting multiple key pathways in the disease pathogenesis.
Stable Signal Recovery via Randomly Enhanced Adaptive Subspace Pursuit Method

This letter addresses the stable signal recovery problem in the presence of noisy perturbations, and presents a variant of Subspace Pursuit (SP) method, called Randomly Enhanced Adaptive SP (REASP) method. REASP first adds correlative and irrelative atoms with an adaptive technique and a random strategy respectively, next detects the overall reliability, and then deletes unreliable atoms per iteration. Through these modifications, REASP is expected to achieve superior performance. The complexity analysis shows that the computational complexity of REASP is a bit higher but acceptable. The experimental results illustrate the superior performance of REASP, compared to the frequently used greedy pursuit (GP) and l1 basis pursuit (BP) methods.
Laser power stabilization for the detection of the populations of the atomic double levels in Cs fountain clock

In this paper we present experimental results on the laser power stabilization of the detection system in Cs fountain clock. In order to stabilize the laser power, we have constructed a feedback loop by using an acousto-optic modulator, a photodetector, and a servo controller. The control-loop can make the relative intensity noise of the laser beam reduce from 1.33×10-4 Hz-1/2 to 7.16×10-6 Hz-1/2 at 2 Hz. However, if the beam used in the control-loop is obtained by using PBS, the two detection beams in fountain clock cannot be stabilized at the same time. Therefore, we propose a new scheme by using a piece of uncoated optical glass plate as a splitter to obtain the branch beam used in the control-loop. Experimental results demonstrate that the power stabilities of the two detection beams are both at 10-5 level (based on rms value) for 1.5 hours at the same time.
Demand-Supply Interactions and Unemployment Dynamics: Can there be Path Dependency ? The Case of Belgium, 1955-1994

The proportion of capacity-constrained firms in European economies remains today fairly small, which suggests that capacity shortages cannot be the direct and single cause of unemployment persistence. Inferring from this observation that low investment rates play no role in explaining the persistence of high unemployment rates may however fail to take into account the relationship between demand expectations, capital accumulation and real rigidities. The objective of this paper, is to show how a continuum of excess-supply equilibria can be obtained, in models with real rigidities, similar to those traditionally used to analyse the determinants of equilibrium unemployment (the NAIRU), provided one takes explicitly into account the effect of a ``capital gap" on wage formation, and the relationship between capital accumulation and demand expectations. Such a persistence mechanism might contribute to explain why current unemployment rates seem to depend so much on past history, and why there is no simple explanation that applies equally well to all European countries. The results obtained from an empirical analysis of Belgian post-war data are compatible with such a scenario.
Fast evolution of custom machine representations

Described are new approaches for evaluating computer program representations for use in automated search methodologies such as the evolutionary design of software. Previously, program representations have been either evaluated directly on raw hardware, providing high speed but little control and flexibility; or, programs were interpreted by a software interpreter which can incorporate much flexibility into a program's evaluation, but does so at a large cost in time due to interpretation overheads. In this paper we bridge this gap by providing intermediate compilation techniques for machine representations that approach the speed of running raw bits directly on hardware, but that have all the flexibility and control of custom instruction sets. In particular, we describe two compilation techniques: the first uses just-in-time compilation to convert a custom instruction sequence to machine code; the second compiles an instruction set specification into a specialized interpreter which incurs only small overheads for instruction decoding. We show that both techniques can provide manyfold speedups over direct interpretation while retaining the expressiveness of custom representations
ADvISE: Architectural Decay in Software Evolution

Software systems evolve continuously, requiring continuous maintenance and development. Consequently, their architecture tends to degrade with time as it becomes less relevant to new, emerging requirements. Therefore, stability or resilience is a primary criterion for evaluating an architecture. In this paper, we propose a quantitative approach to study the evolution of the architecture of object oriented systems over time. In particular, we represent an architecture as a set of triplets (S, R, T), where S and T represent two classes and R is a relationship linking them. We use these triplets as basic unit to measure the stability of an architecture. We show the applicability and usefulness of our approach by studying the evolution of three open source systems: JFree Chart and Xerces-J and Rhino.
Deoxyribonucleic acid (DNA) photonics for space environments

When one thinks of suitability in space environments, irradiation tolerance typically is the first property that comes to mind. In addition to irradiation tolerance, however, suitable photonic materials must also possess the desired optical and electromagnetic properties for optimal device performance. Extracted and purified deoxyribonucleic acid (DNA), derived from salmon, has been investigated for use in photonic applications and has shown promise as an excellent optical waveguide material. In this paper we present the properties of DNA that are applicable for both ground and space based photonic applications. Such properties include optical loss, temperature stability, refractive index, resistivity, dielectric constant, microwave insertion loss and gamma ray irradiation tolerance.
INSEARCH: A Platform for Enterprise Semantic Search

This paper discusses the system targeted in the INSEARCH EU project. It embodies most of the state-of-the-art techniques for Enterprise Semantic Search: highly accurate lexical semantics, semantic web tools, collaborative knowledge management and personalization. An advanced information retrieval system has been developed integrating robust semantic technologies and industry-standard software architectures for proactive search as well as personalized domain-specific classification and ranking functionalities.
Prediction of Non-linear Behavior for RC Beam Flexural Strengthened with CFRP Plate

Carbon fiber reinforced polymer (CFRP) plates which have superior mechanical, chemical properties in comparison with conventional materials are used to strengthen reinforced concrete structures and related studies are actively performed. Especially, the studies on behavior prediction of RC beam strengthened with CFRP plate are performed recently. RC beams strengthened with CFRP plate appear material non-linearity, occurrence of cracks, geometric non-linearity, so prediction of behavior based on linear-elastic theory may differ from experimental results. Therefore, in this study, to predict the behavior of RC beam flexural strengthened with CFRP plate, analytical program considering material non-linearity is developed. To analyze, strain compatibility and force equilibrium are applied and internal forces of constitutive material are calculated using non-linear stress-strain relationship. To certainty the reliability of analytical program, deflection, strain of CFRP plate, change of neutral axis on cross section and crack distribution at failure are compared with those of experiment, and each results is almost coincident.
Stages of change for healthy eating in diabetes: relation to demographic, eating-related, health care utilization, and psychosocial factors.

OBJECTIVES To identify diabetes-related characteristics of individuals at different stages of readiness to change to healthy, low-fat eating. RESEARCH DESIGN AND METHODS Stage-based differences in demographic, eating-related, health care utilization, and psychosocial factors were examined in a sample of 768 overweight (BMI >27 kg/m(2)) individuals with diabetes enrolled in a randomized behavioral intervention trial. RESULTS Stage-based differences occurred for type 1 diabetic participants on percent of calories from fat and number of daily vegetable servings. For type 2 diabetic participants, sex, disease-specific quality of life, percent calories from fat, and number of daily vegetables servings differed across stages. Those in action stages were more likely to be female and have a better quality of life and healthier eating habits. Type 2 diabetic insulin-requiring participants in action stages were more likely to be married. Social support was highest for those in the contemplation stage and lowest for those in the action stage. Type 2 diabetic participants on pills in the action stages were older, had a lower BMI, ate more fruit, were nonsmokers, recently attended diabetes education, had a better quality of life and social support, and had less stress. One anomalous finding for type 2 diabetic participants was that precontemplators scored similarly to those in action stages. CONCLUSIONS These data validate the Transtheoretical Model, where those in the action stages displayed healthier eating. They also indicate that demographic and psychosocial factors may mediate readiness to change diet. Precontemplators were a heterogeneous group and may need individually tailored interventions.
Development of PCR Primer Systems for Amplification of Nitrite Reductase Genes (nirK and nirS) To Detect Denitrifying Bacteria in Environmental Samples

ABSTRACT A system was developed for the detection of denitrifying bacteria by the amplification of specific nitrite reductase gene fragments with PCR. Primer sequences were found for the amplification of fragments from both nitrite reductase genes (nirK andnirS) after comparative sequence analysis. Whenever amplification was tried with these primers, the known nirtype of denitrifying laboratory cultures could be confirmed. Likewise, the method allowed a determination of the nir type of five laboratory strains. The nirK gene could be amplified fromBlastobacter denitrificans, Alcaligenes xylosoxidans, and Alcaligenes sp. (DSM 30128); thenirS gene was amplified from Alcaligenes eutrophus DSM 530 and from the denitrifying isolate IFAM 3698. For each of the two genes, at least one primer combination amplified successfully for all of the test strains. Specific amplification products were not obtained with nondenitrifying bacteria or with strains of the other nir type. The specificity of the amplified products was confirmed by subsequent sequencing. These results suggest the suitability of the method for the qualitative detection of denitrifying bacteria in environmental samples. This was shown by applying one generally amplifying primer combination for eachnir gene developed in this study to total DNA preparations from aquatic habitats.
Comparative overview of brain perfusion imaging techniques.

BACKGROUND AND PURPOSE Numerous imaging techniques have been developed and applied to evaluate brain hemodynamics. Among these are positron emission tomography, single photon emission computed tomography, Xenon-enhanced computed tomography, dynamic perfusion computed tomography, MRI dynamic susceptibility contrast, arterial spin labeling, and Doppler ultrasound. These techniques give similar information about brain hemodynamics in the form of parameters such as cerebral blood flow or cerebral blood volume. All of them are used to characterize the same types of pathological conditions. However, each technique has its own advantages and drawbacks. SUMMARY OF REVIEW This article addresses the main imaging techniques dedicated to brain hemodynamics. It represents a comparative overview established by consensus among specialists of the various techniques. CONCLUSIONS For clinicians, this article should offer a clearer picture of the pros and cons of currently available brain perfusion imaging techniques and assist them in choosing the proper method for every specific clinical setting.
Predicting protein residue-residue contacts using deep networks and boosting

MOTIVATION Protein residue-residue contacts continue to play a larger and larger role in protein tertiary structure modeling and evaluation. Yet, while the importance of contact information increases, the performance of sequence-based contact predictors has improved slowly. New approaches and methods are needed to spur further development and progress in the field. RESULTS Here we present DNCON, a new sequence-based residue-residue contact predictor using deep networks and boosting techniques. Making use of graphical processing units and CUDA parallel computing technology, we are able to train large boosted ensembles of residue-residue contact predictors achieving state-of-the-art performance. AVAILABILITY The web server of the prediction method (DNCON) is available at http://iris.rnet. missouri.edu/dncon/. CONTACT chengji@missouri.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
The Value of ITIL in Enterprise Architecture

Enterprise Architecture (EA) and IT Service Management (ITSM) are two complementary IT governance approaches, with distinct IT and organizational perspectives. Nowadays, ITIL is the de facto standard for implementing ITSM. However, it is still unclear how to measure the value that ITIL brings to organizations. This paper addresses the EA of organizations that use ITIL best practices to perform ITSM, focusing on the modeling and assessment of ITIL value in those architectures. Therefore, this paper's goal is threefold: (1) to find out if ITIL already contains the concepts that are usually needed to represent value, (2) to model these concepts according to an EA point of view and (3) to demonstrate how to use an architecture-based approach to choose between ITIL implementation projects.
Association of Nef with p21-Activated Kinase 2 Is Dispensable for Efficient Human Immunodeficiency Virus Type 1 Replication and Cytopathicity in Ex Vivo-Infected Human Lymphoid Tissue

ABSTRACT Interaction of the human immunodeficiency virus type 1 (HIV-1) Nef protein with p21-activated kinase 2 (PAK2) has been proposed to play a role in T-cell activation, viral replication, apoptosis, and progression to AIDS. However, these hypotheses were based on results obtained using Nef mutants impaired in multiple functions. Recently, it was reported that Nef residue F191 is specifically involved in PAK2 binding. However, only a limited number of Nef activities were investigated in these studies. To further evaluate the role of F191 in Nef function and to elucidate the biological relevance of Nef-PAK2 interaction, we performed a comprehensive analysis of HIV-1 Nef mutants carrying F191H and F191R mutations. We found that the F191H mutation reduces and the F191R mutation disrupts the association of Nef with PAK2. Both mutants upregulated the major histocompatibility complex II (MHC-II)-associated invariant chain and downregulated CD4, MHC-I, and CD28, although with reduced efficiency for the latter. Furthermore, the F191H/R changes neither affected the levels of interleukin-2 receptor expression and apoptosis of HIV-1-infected primary T cells nor reduced Nef-mediated induction of NFAT. Unexpectedly, the F191H change markedly reduced and the F191R mutation disrupted the ability of Nef to enhance virion infectivity in P4-CCR5 indicator cells but not in TZM-bl cells or peripheral blood mononuclear cells. Most importantly, all HIV-1 Nef mutants replicated efficiently and caused CD4+ T-cell depletion in ex vivo-infected human lymphoid tissue. Altogether, our data show that the interaction of Nef with PAK2 does not play a major role in T-cell activation, viral replication, and apoptosis.
Finding Likely Errors with Bayesian Specifications

We present a Bayesian framework for learning probabilistic specifications from large, unstructured code corpora, and a method to use this framework to statically detect anomalous, hence likely buggy, program behavior. The distinctive insight here is to build a statistical model that correlates all specifications hidden inside a corpus with the syntax and observed behavior of programs that implement these specifications. During the analysis of a particular program, this model is conditioned into a posterior distribution that prioritizes specifications that are relevant to this program. This allows accurate program analysis even if the corpus is highly heterogeneous. The problem of finding anomalies is now framed quantitatively, as a problem of computing a distance between a "reference distribution" over program behaviors that our model expects from the program, and the distribution over behaviors that the program actually produces. We present a concrete embodiment of our framework that combines a topic model and a neural network model to learn specifications, and queries the learned models to compute anomaly scores. We evaluate this implementation on the task of detecting anomalous usage of Android APIs. Our encouraging experimental results show that the method can automatically discover subtle errors in Android applications in the wild, and has high precision and recall compared to competing probabilistic approaches.