Miracle-dz/UniFAR-FTUs huggingface dataset:
A randomised, double-blind, parallel-group study to demonstrate equivalence in efficacy and safety of CT-P13 compared with innovator infliximab when coadministered with methotrexate in patients with active rheumatoid arthritis: the PLANETRA study

Objectives To compare the efficacy and safety of innovator infliximab (INX) and CT-P13, an INX biosimilar, in active rheumatoid arthritis patients with inadequate response to methotrexate (MTX) treatment. Methods Phase III randomised, double-blind, multicentre, multinational, parallel-group study. Patients with active disease despite MTX (12.5–25 mg/week) were randomised to receive 3 mg/kg of CT-P13 (n=302) or INX (n=304) with MTX and folic acid. The primary endpoint was the American College of Rheumatology 20% (ACR20) response at week 30. Therapeutic equivalence of clinical response according to ACR20 criteria was concluded if the 95% CI for the treatment difference was within ±15%. Secondary endpoints included ACR response criteria, European League Against Rheumatism (EULAR) response criteria, change in Disease Activity Score 28 (DAS28), Medical Outcomes Study Short-Form Health Survey (SF-36), Simplified Disease Activity Index, Clinical Disease Activity Index, as well as pharmacokinetic (PK) and pharmacodynamic (PD) parameters, safety and immunogenicity. Results At week 30, ACR20 responses were 60.9% for CT-P13 and 58.6% for INX (95% CI −6% to 10%) in the intention-to-treat population. The proportions in CT-P13 and INX groups achieving good or moderate EULAR responses (C reactive protein (CRP)) at week 30 were 85.8% and 87.1%, respectively. Low disease activity or remission according to DAS28–CRP, ACR–EULAR remission rates, ACR50/ACR70 responses and all other PK and PD endpoints were highly similar at week 30. Incidence of drug-related adverse events (35.2% vs 35.9%) and detection of antidrug antibodies (48.4% vs 48.2%) were highly similar for CT-P13 and INX, respectively. Conclusions CT-P13 demonstrated equivalent efficacy to INX at week 30, with a comparable PK profile and immunogenicity. CT-P13 was well tolerated, with a safety profile comparable with that of INX. ClinicalTrials.gov Identifier NCT01217086
Functional magnetic resonance imaging analysis of food-related brain activity in patients with lipodystrophy undergoing leptin replacement therapy.

CONTEXT Lipodystrophy is a disease characterized by a paucity of adipose tissue and low circulating concentrations of adipocyte-derived leptin. Leptin-replacement therapy improves eating and metabolic disorders in patients with lipodystrophy. OBJECTIVE The aim of the study was to clarify the pathogenic mechanism of eating disorders in lipodystrophic patients and the action mechanism of leptin on appetite regulation. SUBJECTS AND INTERVENTIONS We investigated food-related neural activity using functional magnetic resonance imaging in lipodystrophic patients with or without leptin replacement therapy and in healthy controls. We also measured the subjective feelings of appetite. RESULTS Although there was little difference in the enhancement of neural activity by food stimuli between patients and controls under fasting, postprandial suppression of neural activity was insufficient in many regions of interest including amygdala, insula, nucleus accumbens, caudate, putamen, and globus pallidus in patients when compared with controls. Leptin treatment effectively suppressed postprandial neural activity in many of these regions of interest, whereas it showed little effect under fasting in patients. Consistent with these results, postprandial formation of satiety feeling was insufficient in patients when compared with controls, which was effectively reinforced by leptin treatment. CONCLUSIONS This study demonstrated the insufficiency of postprandial suppression of food-related neural activity and formation of satiety feeling in lipodystrophic patients, which was effectively restored by leptin. The findings in this study emphasize the important pathological role of leptin in eating disorders in lipodystrophy and provide a clue to understanding the action mechanism of leptin in human, which may lead to development of novel strategies for prevention and treatment of obesity.
IA3, an aspartic proteinase inhibitor from Saccharomyces cerevisiae, is intrinsically unstructured in solution.

IA(3) is a highly specific and potent 68-amino acid endogenous inhibitor of yeast proteinase A (YprA), and X-ray crystallographic studies have shown that IA(3) binds to YprA as an alpha-helix [Li, M. , Phylip, L. H. , Lees, W. E. , Winther, J. R. , Dunn, B. M. , Wlodawer, A. , Kay, J., and Gustchina, A. (2000) Nat. Struct. Biol. 7, 113-117]. Surprisingly, only residues 2-32 of IA(3) are seen in the X-ray structure, and the remaining residues are believed to be disordered in the complex. We have used circular dichroism (CD) and nuclear magnetic resonance (NMR) spectroscopy to show that IA(3) is unstructured in the absence of YprA. Specifically, IA(3) produced a CD spectrum characteristic of an unstructured peptide, and the (15)N HSQC NMR spectra of IA(3) were characteristic of a polypeptide lacking intrinsic structure. We characterized the unstructured state of IA(3) by using singular-value decomposition (SVD) to analyze the CD data in the presence of TFE, by fully assigning the unbound IA(3) protein by NMR and comparing the chemical shifts to published random-coil values, and by measuring (1)H-(15)N heteronuclear NOEs, which are all consistent with an unfolded protein. The IA(3) samples used for NMR analyses were active and inhibited YprA with an inhibition constant (K(i)) of 1.7 nM, and the addition of YprA led to a large spectral transition in IA(3). Calorimetric (ITC) data also show that the overall enthalpy of the interaction between IA(3) and YprA is exothermic.
Safe parallelism for robotic control

During the Spring 2008 semester at Olin College, we introduced the programming language occam-pi to undergraduates as part of their first course in robotics. Students were able to explore image processing and autonomous behavioral control in a parallel programming language on a small mobile robotics platform with just two weeks of tutorial instruction. Our experiences to date suggest that the language and tools we have developed allow the concise expression of complex robotic control systems, and enable the integration of events from the environment in a consistent and safe model for parallel control that is directly expressed in software.
HIV-DNA in the Genital Tract of Women on Long-Term Effective Therapy Is Associated to Residual Viremia and Previous AIDS-Defining Illnesses

Objectives To assess the impact of long-term combined antiretroviral therapy (cART) on HIV-RNA and HIV-DNA levels in cervicovaginal secretions of HIV-1-infected women with sustained undetectable plasma RNA viral load (PVL); to explore factors predictive of residual viral shedding; and to evaluate the risk of heterosexual transmission. Methods Women with undetectable PVL (<50 copies/mL) for >6 months were included in this cross-sectional study. HIV-RNA and HIV-DNA were measured in blood and cervicovaginal lavage fluid (CVL). Women were systematically tested for genital infections. The risk of transmission to male partners during unprotected intercourse was estimated. Results Eighty-one women composed the study population: all had HIV-RNA <40 copies/mL in CVL. HIV-DNA was detectable in CVL of 29/78 patients (37%). There was a weak positive correlation between HIV-DNA levels in PBMCs and CVL (r = 0.20; p = 0.08). In multivariate analysis, two factors were associated with HIV-DNA detection in CVL: previous AIDS-defining illnesses (OR = 11; 95%CI = 2–61) and current residual viremia (20<PVL<50 cp/mL) (OR = 3.4; 95%CI = 1.1–10.9). Neither the classes of cART regimen nor the presence of genital bacterial or fungal colonization were associated with HIV-DNA detection in CVL. Twenty-eight percent of the women had unprotected intercourse with their regular HIV-seronegative male partner, for between 8 and 158 months. None of their male partners became infected, after a total of 14 000 exposures. Conclusion In our experience, HIV-RNA was undetectable in the genital tract of women with sustained control of PVL on cART. HIV-DNA shedding persisted in about one third of cases, with no substantial evidence of residual infectiousness.
Antihyperglycemic activity of Catharanthus roseus leaf powder in streptozotocin-induced diabetic rats

Catharanthus roseus Linn (Apocynaceae), is a traditional medicinal plant used to control diabetes, in various regions of the world. In this study we evaluated the possible antidiabetic and hypolipidemic effect of C. roseus (Catharanthus roseus) leaf powder in diabetic rats. Diabetes was induced by intraperitoneal injection of streptozotocin (STZ, 55 mg/kg body wt) to male Wistar rats. The animals were divided into four groups: Control, control-treated, diabetic, and diabetic-treated group. Diabetic-treated and control-treated rats were treated with C. roseus leaf powder suspension in 2 ml distilled water, orally (100 mg/kg body weight/day/60 days). In diabetic rats (D-group) the plasma glucose was increased and the plasma insulin was decreased gradually. In the diabetic-treated group lowering of plasma glucose and an increase in plasma insulin were observed after 15 days and by the end of the experimental period the plasma glucose had almost reached the normal level, but insulin had not. The significant enhancement in plasma total cholesterol, triglycerides, LDL and VLDL-cholesterol, and the atherogenic index of diabetic rats were normalized in diabetic-treated rats. Decreased hepatic and muscle glycogen content and alterations in the activities of enzymes of glucose metabolism (glycogen phosphorylase, hexokinase, phosphofructokinase, pyruvate kinase, and glucose-6-phosphate dehydrogenase), as observed in the diabetic control rats, were prevented with C. roseus administration. Our results demonstrated that C. roseus with its antidiabetic and hypolipidemic properties could be a potential herbal medicine in treating diabetes.
L-Ascorbate Attenuates the Endotoxin-Induced Production of Inflammatory Mediators by Inhibiting MAPK Activation and NF-κB Translocation in Cortical Neurons/Glia Cocultures

In response to acute insults to the central nervous system, such as pathogen invasion or neuronal injuries, glial cells become activated and secrete inflammatory mediators such as nitric oxide (NO), cytokines, and chemokines. This neuroinflammation plays a crucial role in the pathophysiology of chronic neurodegenerative diseases. Endogenous ascorbate levels are significantly decreased among patients with septic encephalopathy. Using the bacterial endotoxin lipopolysaccharide (LPS) to induce neuroinflammation in primary neuron/glia cocultures, we investigated how L-ascorbate (vitamin C; Vit. C) affected neuroinflammation. LPS (100 ng/ml) induced the expression of inducible NO synthase (iNOS) and the production of NO, interleukin (IL)-6, and macrophage inflammatory protein-2 (MIP-2/CXCL2) in a time-dependent manner; however, cotreatment with Vit. C (5 or 10 mM) attenuated the LPS-induced iNOS expression and production of NO, IL-6, and MIP-2 production. The morphological features revealed after immunocytochemical staining confirmed that Vit. C suppressed LPS-induced astrocytic and microglial activation. Because Vit. C can be transported into neurons and glia via the sodium-dependent Vit. C transporter-2, we examined how Vit. C affected LPS-activated intracellular signaling in neuron/glia cocultures. The results indicated the increased activation (caused by phosphorylation) of mitogen-activated protein kinases (MAPKs), such as p38 at 30 min and extracellular signal-regulated kinases (ERKs) at 180 min after LPS treatment. The inhibition of p38 and ERK MAPK suppressed the LPS-induced production of inflammatory mediators. Vit. C also inhibited the LPS-induced activation of p38 and ERK. Combined treatments of Vit. C and the inhibitors of p38 and ERK yielded no additional inhibition compared with using the inhibitors alone, suggesting that Vit. C functions through the same signaling pathway (i.e., MAPK) as these inhibitors. Vit. C also reduced LPS-induced IκB-α degradation and NF-κB translocation. Thus, Vit. C suppressed the LPS-stimulated production of inflammatory mediators in neuron/glia cocultures by inhibiting the MAPK and NF-κB signaling pathways.
Towards a Model Driven Service Engineering Process

Developments in the realm of business services have opened new challenges in the business consulting world. Consequently, new procedures for services system development are being proposed. In this work, we present a model driven approach for streamlining the service engineering process. An important aspect of our work is a method for model transformation, which is essential for providing and enhancing the management and governance capabilities of the service engineering process. We then introduce a novel infrastructure which leverages Web 2.0 technologies to address the challenge of developing semantic modeling editors. Finally, we use this infrastructure as the target platform to validate our work.
Modèles combinatoires des structures d'ARN avec ou sans pseudonoeuds, application à la comparaison de structures. (Combinatorial models for RNA structures, with or without pseudoknots and application to structures comparison)

Ces travaux de these proposent une modelisation des structures secondaires d'ARN avec ou sans pseudonoeuds. Selon une approche combinatoire, nous concevons differents modeles de ces structures que nous etudions sous deux aspects. D'une part, nous definissons des modeles de generation aleatoire qui nous permettent de definir une mesure permettant une meilleure reconnaissance des structures biologiques. D'autre part, grâce a des codages appropries et des bijections vers des langages representes par des grammaires non-contextuelles, nous denombrons les structures composant l'espace de prediction des algorithmes exacts de prediction de structures secondaires avec pseudonoeuds. La premiere partie concerne des modeles aleatoires de structures d'ARN sans pseudonoeuds. Nous montrons que ces structures aleatoires constituent une source de bruit pertinente lorsqu'il s'agit de determiner si les logiciels de comparaison de structures attribuent un meilleur score a des comparaisons entre structures issues de la meme famille d'ARN qu'a des alignements entre structures reelles et aleatoires. Nous comparons ensuite la sensibilite et la specificite de RNAdistance, un programme de comparaison de structures, selon l'usage du score "brut" ou bien de la Z-valeur de ce score. Nous calculons plusieurs Z-valeurs selon differents modeles de structures aleatoires. Nous montrons que la Z-valeur calculee a partir d'un modele de Markov ameliore la detection des ARN de grande taille tandis que la Z-valeur calculee a partir d'un modele base sur des grammaires ponderees ameliore la detection des ARN de petite taille. Nous nous interessons ensuite, dans une deuxieme partie, aux algorithmes de prediction de structure secondaire avec pseudonoeuds. Nous completons tout d'abord la classification de Condon et al. en decrivant les structures par leur graphe de coherence et nous caracterisons egalement la restriction planaire de la classe de Rivas et Eddy. Nous etudions ensuite le compromis entre complexite des algorithmes existant et la taille de leur espace de prediction. Nous denombrons les structures en les codant par des mots de langages algebriques. Nous en deduisons alors des formules asymptotiques de denombrement. Nous mettons aussi en evidence une bijection entre la classe de Lyngso et Pedersen et des cartes planaires ainsi qu'une bijection entre la classe des pseudonoeuds indifferencies, que nous avons introduite, et les arbres ternaires. Nous montrons alors que les differences de complexite observees des algorithmes de prediction ne sont pas toujours justifiees par la taille de l'espace de prediction. A partir de ces grammaires, nous concevons des algorithmes efficaces de generation aleatoire, uniforme ou non uniforme controlee, de structures d'ARN avec pseudonoeuds.
Millimeter-Wave V2V Communications: Distributed Association and Beam Alignment

Recently, millimeter-wave (mmWave) bands have been postulated as a means to accommodate the foreseen extreme bandwidth demands in vehicular communications, which result from the dissemination of sensory data to nearby vehicles for enhanced environmental awareness and improved safety level. However, the literature is particularly scarce in regards to principled resource allocation schemes that deal with the challenging radio conditions posed by the high mobility of vehicular scenarios. In this paper, we propose a novel framework that blends together matching theory and swarm intelligence to dynamically and efficiently pair vehicles and optimize both transmission and reception beamwidths. This is done by jointly considering channel state information and queue state information when establishing vehicle-to-vehicle (V2V) links. To validate the proposed framework, simulation results are presented and discussed, where the throughput performance as well as the latency/reliability tradeoffs of the proposed approach are assessed and compared with several baseline approaches recently proposed in the literature. The results obtained in this paper show performance gains of 25% in reliability and delay for ultra-dense vehicular scenarios with 50% more active V2V links than the baselines. These results shed light on the operational limits and practical feasibility of mmWave bands, as a viable radio access solution for future high-rate V2V communications.
Depression, anxiety, stress, and motivation over the course of smoking cessation treatment

Objective: To evaluate changes in the levels of patient anxiety, depression, motivation, and stress over the course of smoking cessation treatment. Methods: This cohort study involved patients enrolled in a smoking cessation program in Cuiabá, Brazil. We selected patients who completed the program in six months or less (n = 142). Patient evaluations were conducted at enrollment (evaluation 1 [E1]); after 45 days of treatment with medication and cognitive-behavioral therapy (E2); and at the end of the six-month study period (E3). Patients were evaluated with a standardized questionnaire (to collect sociodemographic data and determine smoking status), as well as with the University of Rhode Island Change Assessment scale, Beck Anxiety Inventory, Beck Depression Inventory, and Lipp Inventory of Stress Symptoms for Adults. The data were analyzed with the nonparametric Wilcoxon test for paired comparisons. To compare treatment success (smoking cessation) with treatment failure, the test for two proportions was used. Results: Among the 142 patients evaluated, there were improvements, in terms of the levels of anxiety, depression, motivation, and stress, between E1 and E2, as well as between E1 and E3. In addition, treatment success correlated significantly with the levels of motivation and anxiety throughout the study period, whereas it correlated significantly with the level of depression only at E2 and E3. Conclusions: We conclude that there are in fact changes in the levels of patient anxiety, depression, motivation, and stress over the course of smoking cessation treatment. Those changes appear to be more pronounced in patients in whom the treatment succeeded.
Negative Bias Temperature Stress on PFETs within fast Wafer Level Reliability Monitoring

The challenges of measuring by means of fast WLR the Vt degradation caused by temperature bias stress are discussed in this work. Two methods, the fast two point measurement with smart intermediate stress (SIS) and the back-extrapolation based on measuring the recovery curve are compared. Considering the properties of the test equipment an adjusted SIS approach is implemented in order to get an equivalent method to the stress interruption free OTF-method. Nevertheless recovery causes a stronger degradation vs. time dependence at short times than at long times leading to the implementation of the back-extrapolation of the recovery curve. This method requires the implementation of a curve fitting algorithm like the Levenberg-Marquardt algorithm in the fWLR stress routine for data evaluation upon completion of the stress. The method was tested on three PFET types with different oxide thickness and in all cases shows reasonable results for various stress conditions.
Human-Algorithm Interaction Biases in the Big Data Cycle: A Markov Chain Iterated Learning Framework

Early supervised machine learning algorithms have relied on reliable expert labels to build predictive models. However, the gates of data generation have recently been opened to a wider base of users who started participating increasingly with casual labeling, rating, annotating, etc. The increased online presence and participation of humans has led not only to a democratization of unchecked inputs to algorithms, but also to a wide democratization of the "consumption" of machine learning algorithms' outputs by general users. Hence, these algorithms, many of which are becoming essential building blocks of recommender systems and other information filters, started interacting with users at unprecedented rates. The result is machine learning algorithms that consume more and more data that is unchecked, or at the very least, not fitting conventional assumptions made by various machine learning algorithms. These include biased samples, biased labels, diverging training and testing sets, and cyclical interaction between algorithms, humans, information consumed by humans, and data consumed by algorithms. Yet, the continuous interaction between humans and algorithms is rarely taken into account in machine learning algorithm design and analysis. In this paper, we present a preliminary theoretical model and analysis of the mutual interaction between humans and algorithms, based on an iterated learning framework that is inspired from the study of human language evolution. We also define the concepts of human and algorithm blind spots and outline machine learning approaches to mend iterated bias through two novel notions: antidotes and reactive learning.
Hierarchical Block-Based Disparity Estimation Considering Neighbourhood Constraints

A block–based isparity estimation approach is pres ented that increases the robustness of the estimator by considering neighbourhood constraints and by esti mating hierarchically on a multi–resolutional image pyramid of a stereoscopic image pair . This approach is applied to 3–D reconstruction of moving scenes in the field of 3–D video communications and to land scape and architectural reconstruction. The shape of the reconstructed objects, which is computed from the estimated disparities, is significantly improved using the presented approach compared to conven tional block–matching.