Miracle-dz/UniFAR-FTUs huggingface dataset:
Type 2 Diabetes: Local Inflammation and Direct Effect of Bacterial Toxic Components

Objectives: It has been known for almost a century that amyloidosis is frequently associated with chronic bacte- rial infection. Islet amyloid deposit is characteristic of type 2 diabetes. Periodontal disease, which is predominantly caused by several Gram negative bacteria, is a risk factor for type 2 diabetes. The goal of the study was to explore whether bacte- ria or their toxic components may play a role in type 2 diabetes. Material & Methods: The pancreas in 22 autopsy cases was analyzed for the presence of lipopolysaccharide (LPS), bacte- rial peptidoglycan (BPG) and local inflammatory processes. Ten of the cases had clinically diagnosed type 2 diabetes, and 12 were age matched controls. Results: The results of an immunohistochemical analysis showed the presence of LPS and BPG in association with islet amyloid deposits in all the 10 diabetic cases as well as in 3 controls with clinically silent amyloid deposits. Chlamydia pneumoniae and Helicobacter pylori specific antigens were detected in the affected islets in a subset of diabetic patients. Clumps of HLA-DR positive activated macrophages, abundant immunoreactivity to the activated complement compo- nents C3d, C4d and C5b-9, the terminal attack complex, and a moderate numbers of T4 and particularly of T8 lympho- cytes were present in the pancreas of all diabetic cases. Conclusions: These results suggest that bacteria or their slowly degradable remnants may initiate and sustain chronic in- flammation in the pancreas and therefore play a role in the pathogenesis of type 2 diabetes. They also indicate that local immune responses, including activation of the classical complement pathway are important in the pathogenesis of type 2 diabetes. There may also be some involvement of the adaptive immune system. Further investigations are essential since a parallel use of antibacterial and anti-inflammatory drugs may prevent or slow down the disease progression.
A hybrid method based on conjugate gradient trained neural network and differential evolution for non linear systems identification

A hybrid method based on Differential Evolution and Neural Network training algorithms is presented in this paper for improving the performance of neural network in the non linear system identification. For this purpose, the local optimization algorithm of conjugate gradients (CG) is combined with the differential evolution algorithm (DE), which is a population-based stochastic global search method, to yield a computationally efficient algorithm for training multilayer perceptron networks for nonlinear system identification. After, a series of simulation studies of our method on the different nonlinear systems it has been confirmed that the proposed CG+DE algorithm has yielded better identification results in terms of time of convergence and less identification error.
Cross-peak-specific two-dimensional electronic spectroscopy

Intermolecular electronic coupling dictates the optical properties of molecular aggregate systems. Of particular interest are photosynthetic pigment–protein complexes that absorb sunlight then efficiently direct energy toward the photosynthetic reaction center. Two-dimensional (2D) ultrafast spectroscopy has been used widely in the infrared (IR) and increasingly in the visible to probe excitonic couplings and observe dynamics, but the off-diagonal spectral signatures of coupling are often obscured by broad diagonal peaks, especially in the visible regime. Rotating the polarizations of the laser pulses exciting the sample can highlight certain spectral features, and the use of polarized pulse sequences to elucidate cross-peaks in 2D spectra has been demonstrated in the IR for vibrational transitions. Here we develop 2D electronic spectroscopy using cross-peak-specific pulse polarization conditions in an investigation of the Fenna–Matthews–Olson light harvesting complex from green photosynthetic bacteria. Our measurements successfully highlight off-diagonal features of the 2D spectra and, in combination with an analysis based on the signs of features arising from particular energy level pathways and theoretical simulation, we characterize the dominant response pathways responsible for the spectral features. Cross-peak-specific 2D electronic spectroscopy provides insight into the interchromophore couplings, as well as into the energetic pathways giving rise to the signal. With femtosecond resolution, we also observe dynamical processes that depend on these couplings and interactions with the protein environment.
MicroTESK: An Extendable Framework for Test Program Generation

Creation of test programs and analysis of their execution is the main approach to system-level verification of microprocessors. A lot of techniques have been proposed to automate test program generation, ranging from completely random to well directed ones. However, no "silver bullet" has been found. In good industrial practices, various methods are combined complementing each other. Unfortunately, there is no solution that could integrate all (or at least most) of the techniques in a single framework. Engineers are forced to use a number of tools, which leads to the following problems: (1) it is required to maintain duplicating data (each tool uses its own representation of the target design); (2) to be used together, tools need to be integrated (engineers have to deal with different formats and interfaces). This paper proposes a concept of an extendable framework (MicroTESK) that follows a unified methodology for defining test program generation techniques. The framework supports random and combinatorial generation and (what is even more important) can be easily extended with new techniques being implemented as the framework's plugins.
Next Generation Phenotyping Using the Unified Medical Language System

Background Structured information within patient medical records represents a largely untapped treasure trove of research data. In the United States, privacy issues notwithstanding, this has recently become more accessible thanks to the increasing adoption of electronic health records (EHR) and health care data standards fueled by the Meaningful Use legislation. The other side of the coin is that it is now becoming increasingly more difficult to navigate the profusion of many disparate clinical terminology standards, which often span millions of concepts. Objective The objective of our study was to develop a methodology for integrating large amounts of structured clinical information that is both terminology agnostic and able to capture heterogeneous clinical phenotypes including problems, procedures, medications, and clinical results (such as laboratory tests and clinical observations). In this context, we define phenotyping as the extraction of all clinically relevant features contained in the EHR. Methods The scope of the project was framed by the Common Meaningful Use (MU) Dataset terminology standards; the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), RxNorm, the Logical Observation Identifiers Names and Codes (LOINC), the Current Procedural Terminology (CPT), the Health care Common Procedure Coding System (HCPCS), the International Classification of Diseases Ninth Revision Clinical Modification (ICD-9-CM), and the International Classification of Diseases Tenth Revision Clinical Modification (ICD-10-CM). The Unified Medical Language System (UMLS) was used as a mapping layer among the MU ontologies. An extract, load, and transform approach separated original annotations in the EHR from the mapping process and allowed for continuous updates as the terminologies were updated. Additionally, we integrated all terminologies into a single UMLS derived ontology and further optimized it to make the relatively large concept graph manageable. Results The initial evaluation was performed with simulated data from the Clinical Avatars project using 100,000 virtual patients undergoing a 90 day, genotype guided, warfarin dosing protocol. This dataset was annotated with standard MU terminologies, loaded, and transformed using the UMLS. We have deployed this methodology to scale in our in-house analytics platform using structured EHR data for 7931 patients (12 million clinical observations) treated at the Froedtert Hospital. A demonstration limited to Clinical Avatars data is available on the Internet using the credentials user “jmirdemo” and password “jmirdemo”. Conclusions Despite its inherent complexity, the UMLS can serve as an effective interface terminology for many of the clinical data standards currently used in the health care domain.
Competition and collaboration shaping the digital payment infrastructure

Digital artifacts take increasingly prominent positions in the life of individuals, organizations and the society at large. This paper inquires into the effects of digitalization on the payment industry. In the case of payments, the ecosystem surrounding a payment historically involved two parties exchanging goods and services for money (banknotes and coins). Today, payment increasingly consists of digital representations of money in a globally intertwined system that involve many parties, such as payers, payment services providers, banks, telecom operators, mobile phone manufactures, and payees. We study how technological payment innovations influence the payment ecosystem, and find that digitalization has caused ecosystem turbulence by influencing competitive and collaborative dimensions of the ecosystem. The digitalization creates a new arena for competition that will require new collaboration forms among involved stockholders. In the extension, we find that future developments of the digital payment infrastructure are something very different from a traditional IT systems development project, which makes existing methods and approaches to systems development inadequate in addressing the challenge.
Fast Constraint Propagation on Specialized Allen Networksand its Application to Action Recognition and ControlClaudio Pinhanez

In this paper we present a specialization of Allen interval networks that permits the rapid determination as to whether a given interval must be occurring at the current point in time. The Allen-closure of the interval network is projected into a 3-valued (past,now,fut) constraint network called a PNF-network. We show that the minimal domain of a PNF-network can be approximately computed in linear time by using arc-consistency. This computation is the key factor in the PNF propagation method of determining, for each instant of time and given information from perceptual sensors, the PNF-state of each interval, that is, happening (now), already happened (past), or has not happened (fut). We show how the computation of PNF-states can support both action recognition and the control of real-time interactive environments in which the actions are described by Allen interval networks.
A ug 2 00 5 UWThPh-2005-5 S 3 × Z 2 model for neutrino mass matrices

We propose a model for lepton mass matrices based on the seesaw mechanism, a complex scalar gauge singlet and a horizontal symmetry S3 × Z2. In a suitable weak basis, the charged-lepton mass matrix and the neutrino Dirac mass matrix are diagonal, but the vacuum expectation value of the scalar gauge singlet renders the Majorana mass matrix of the right-handed neutrinos non-diagonal, thereby generating lepton mixing. When the symmetry S3 is not broken in the scalar potential, the effective light-neutrino Majorana mass matrix enjoys μ–τ interchange symmetry, thus predicting maximal atmospheric neutrino mixing together with Ue3 = 0. A partial and less predictive form of μ–τ interchange symmetry is obtained when the symmetry S3 is softly broken in the scalar potential. Enlarging the symmetry group S3 × Z2 by an additional discrete electron-number symmetry Z 2 , a more predicitive model is obtained, which is in practice indistinguishable from a previous one based on the group D4. E-mail: walter.grimus@univie.ac. at E-mail: balio@cftp.ist. utl.pt
NY-ESO-1 Based Immunotherapy of Cancer: Current Perspectives

NY-ESO-1 or New York esophageal squamous cell carcinoma 1 is a well-known cancer-testis antigen (CTAs) with re-expression in numerous cancer types. Its ability to elicit spontaneous humoral and cellular immune responses, together with its restricted expression pattern, have rendered it a good candidate target for cancer immunotherapy. In this review, we provide background information on NY-ESO-1 expression and function in normal and cancerous tissues. Furthermore, NY-ESO-1-specific immune responses have been observed in various cancer types; however, their utility as biomarkers are not well determined. Finally, we describe the immune-based therapeutic options targeting NY-ESO-1 that are currently in clinical trial. We will highlight the recent advancements made in NY-ESO-1 cancer vaccines, adoptive T cell therapy, and combinatorial treatment with checkpoint inhibitors and will discuss the current trends for future NY-ESO-1 based immunotherapy. Cancer treatment has been revolutionized over the last few decades with immunotherapy emerging at the forefront. Immune-based interventions have shown promising results, providing a new treatment avenue for durable clinical responses in various cancer types. The majority of successful immunotherapy studies have been reported in liquid cancers, whereas these approaches have met many challenges in solid cancers. Effective immunotherapy in solid cancers is hampered by the complex, dynamic tumor microenvironment that modulates the extent and phenotype of the antitumor immune response. Furthermore, many solid tumor-associated antigens are not private but can be found in normal somatic tissues, resulting in minor to detrimental off-target toxicities. Therefore, there is an ongoing effort to identify tumor-specific antigens to target using various immune-based modalities. CTAs are considered good candidate targets for immunotherapy as they are characterized by a restricted expression in normal somatic tissues concomitant with a re-expression in solid epithelial cancers. Moreover, several CTAs have been found to induce a spontaneous immune response, NY-ESO-1 being the most immunogenic among the family members. Hence, this review will focus on NY-ESO-1 and discuss the past and current NY-ESO-1 targeted immunotherapeutic strategies.
Slow Breathing and Hypoxic Challenge: Cardiorespiratory Consequences and Their Central Neural Substrates

Controlled slow breathing (at 6/min, a rate frequently adopted during yoga practice) can benefit cardiovascular function, including responses to hypoxia. We tested the neural substrates of cardiorespiratory control in humans during volitional controlled breathing and hypoxic challenge using functional magnetic resonance imaging (fMRI). Twenty healthy volunteers were scanned during paced (slow and normal rate) breathing and during spontaneous breathing of normoxic and hypoxic (13% inspired O2) air. Cardiovascular and respiratory measures were acquired concurrently, including beat-to-beat blood pressure from a subset of participants (N = 7). Slow breathing was associated with increased tidal ventilatory volume. Induced hypoxia raised heart rate and suppressed heart rate variability. Within the brain, slow breathing activated dorsal pons, periaqueductal grey matter, cerebellum, hypothalamus, thalamus and lateral and anterior insular cortices. Blocks of hypoxia activated mid pons, bilateral amygdalae, anterior insular and occipitotemporal cortices. Interaction between slow breathing and hypoxia was expressed in ventral striatal and frontal polar activity. Across conditions, within brainstem, dorsal medullary and pontine activity correlated with tidal volume and inversely with heart rate. Activity in rostroventral medulla correlated with beat-to-beat blood pressure and heart rate variability. Widespread insula and striatal activity tracked decreases in heart rate, while subregions of insular cortex correlated with momentary increases in tidal volume. Our findings define slow breathing effects on central and cardiovascular responses to hypoxic challenge. They highlight the recruitment of discrete brainstem nuclei to cardiorespiratory control, and the engagement of corticostriatal circuitry in support of physiological responses that accompany breathing regulation during hypoxic challenge.
Protective Role of Angiopoietin-1 in Endotoxic Shock

Background—Angiopoietin-1 (Ang1) plays an essential role in embryonic vasculature development, protects the adult peripheral vasculature from leakage, and has antiinflammatory properties. Because endotoxin-induced shock is a condition with microvascular leakage resulting from inflammation, we examined the potential therapeutic benefit of Ang1 in a murine model of lipopolysaccharide (LPS)-induced endotoxic shock. Methods and Results—To induce endotoxic shock, LPS was injected intraperitoneally into C57BL/6 mice. Half of the mice received an intravenous application of 1.0×109 plaque-forming units of an adenoviral construct expressing human Ang1 (AdhAng1); in the other half an identical vector expressing green fluorescent protein (AdGFP) was injected as a control. In the AdhAng1-treated mice, hepatic transfection and high expression of circulating Ang1 protein were observed. Whereas in LPS-treated control mice, hemodynamic function was severely depressed 12 hours after LPS injection (decrease of blood pressure from 91±3 to 49±7 mm Hg, dP/dtmax from 7284±550 to 2699±233 mm Hg/s, cardiac output from 11.3±1.2 to 2.8±0.8 mL/min; P<0.0005), in LPS-treated AdhAng1 mice blood pressure fell only to 76±3 mm Hg, dP/dtmax to 5091±489 mm Hg/s, and cardiac output to 6.7±1.4 mL/min (P<0.05). This resistance to LPS-induced hemodynamic changes was reflected by an improved Kaplan-Meier survival rate of the AdhAng1 mice. Histological analysis revealed that lung injury after LPS injection was markedly attenuated in AdhAng1 mice. In addition, LPS-induced increase in lung water content and pulmonary myeloperoxidase activity was significantly reduced. Furthermore, LPS-induced increases in the expression level of vascular cell adhesion molecule-1, intracellular adhesion molecule-1, and E-selectin protein in the lungs were markedly lower in AdhAng1 mice than in control mice. Finally, in the mice overexpressing Ang1, pulmonary endothelial NO synthase (eNOS) expression and activity remained preserved after LPS challenge, providing evidence that the beneficial effect of Ang1 in endotoxic shock is mediated by eNOS-derived NO. Conclusions—Our study demonstrates an improved mortality rate in mice with endotoxic shock pretreated with an adenoviral construct encoding Ang1. The enhanced survival rate induced by Ang1 was accompanied by an improvement in hemodynamic function, reduced lung injury, a lower expression of inflammatory adhesion molecules, and preserved eNOS activity in the lung tissue. Ang1 may therefore have utility as an adjunctive agent for the treatment of septic shock condition.
Mineralogy of the lunar crust: Results from Clementine

Abstract— The central peaks of 109 impact craters across the Moon are examined with Clementine ultraviolet‐visible (UVVIS) camera multispectral data. The craters range in diameter from 40 to 180 km and are believed to have exhumed material from 5–30 km beneath the surface to form the peaks, including both upper and lower crustal rocks depending on whether craters have impacted into highlands or basins. Representative five‐color spectra from spectrally and spatially distinct areas within the peaks are classified using spectral parameters, including “key ratio” (which is related to mafic mineral abundance) and “spectral curvature” (linked to absorption band shape, which distinguishes between low‐ and high‐Ca pyroxene and olivine). The spectral parameters are correlated to mineralogical abundances, related in turn to highland plutonic rock compositions. The derived rock compositions for the various central peaks are presented in a global map. From these results, it is evident that the lunar crust is compositionally diverse, both globally and at local 100 m scales found within individual sets of central peaks. Although the central peaks compositions imply a crust that is generally consistent with previous models of crustal structure, they also indicate a more anorthositic crust than generally assumed, with a bulk plagioclase content of ∼81%, evolving from “pure” anorthosite near the surface towards more mafic, low‐Ca pyroxene‐rich compositions with depth (comparable to anorthositic norite). Evidence for mafic plutons occurs in both highlands and basins and represent all mafic highland rock types. However, the lower crust is more compositionally diverse than the highlands, with both a greater range of rock types and more diversity within individual sets of central peaks.
Retrieving infinite numbers of patterns in a spin-glass model of immune networks

The similarity between neural and (adaptive) immune networks has been known for decades, but so far we did not understand the mechanism that allows the immune system, unlike associative neural networks, to recall and execute a large number of memorized defense strategies in parallel. The explanation turns out to lie in the network topology. Neurons interact typically with a large number of other neurons, whereas interactions among lymphocytes in immune networks are very specific, and described by graphs with finite connectivity. In this paper we use replica techniques to solve a statistical mechanical immune network model with “coordinator branches” (T-cells) and “effector branches” (B-cells), and show how the finite connectivity enables the coordinators to manage an extensive number of effectors simultaneously, even above the percolation threshold (where clonal cross-talk is not negligible). A consequence of its underlying topological sparsity is that the adaptive immune system exhibits only weak ergodicity breaking, so that also spontaneous switch-like effects as bi-stabilities are present: the latter may play a significant role in the maintenance of immune homeostasis.
Constructive Privacy for Shared Genetic Data

The need for the sharing of genetic data, for instance, in genome-wide association studies is incessantly growing. In parallel, serious privacy concerns rise from a multi-party access to genetic information. Several techniques , such as encryption, have been proposed as solutions for the privacy-preserving sharing of genomes. However, existing programming means do not support guarantees for privacy properties and the performance optimization of genetic applications involving shared data. We propose two contributions in this context. First, we present new cloud-based architectures for cloud-based genetic applications that are motivated by the needs of geneticians. Second, we propose a model and implementation for the composition of watermarking with encryption, fragmentation, and client-side computations for the secure and privacy-preserving sharing of genetic data in the cloud.
The Organizing Model and the Management of Change: A Comparative Study of Unions in Australia and Britain

Trade unions in nearly all developed countries are facing major difficulties in maintaining membership levels and political influence. The U.S. labour movement has been increasingly attracted to an organizing model of trade unionism and, in turn, this response has caught the imagination of some sections of other Anglo-Saxon movements, most notably in Australia, New Zealand and Britain. Despite similarities in the problems that national union movements face, however, the histories and current experiences of trade unions in the various countries show marked differences. This article, based on extensive fieldwork in Britain and Australia, examines attempts to assess the importance of national contexts in the adoption of the organizing model through a comparative study of an Australian and a British union.