Miracle-dz/UniFAR-FTUs huggingface dataset:
Wnt/β-Catenin Signaling Modulates Human Airway Sensitization Induced by β2-Adrenoceptor Stimulation

Background Regular use of β2-agonists may enhance non-specific airway responsiveness. The wingless/integrated (Wnt) signaling pathways are responsible for several cellular processes, including airway inflammation and remodeling while cAMP–PKA cascade can activate the Wnt signaling. We aimed to investigate whether the Wnt signaling pathways are involved in the bronchial hyperresponsiveness induced by prolonged exposure to β2-adrenoceptor agonists in human isolated airways. Methods Bronchi were surgically removed from 44 thoracic surgery patients. After preparation, bronchial rings and primary cultures of bronchial epithelial cells were incubated with fenoterol (0.1 µM, 15 hours, 37°C), a β2-agonist with high intrinsic efficacy. The effects of inhibitors/blockers of Wnt signaling on the fenoterol-induced airway sensitization were examined and the impact of fenoterol exposure on the mRNA expression of genes interacting with Wnt signaling or cAMP–PKA cascade was assessed in complete bronchi and in cultured epithelial cells. Results Compared to paired controls, fenoterol-sensitization was abolished by inhibition/blockage of the Wnt/β-catenin signaling, especially the cell-surface LRP5/6 co-receptors or Fzd receptors (1 µM SFRP1 or 1 µM DKK1) and the nuclear recruitment of TCF/LEF transcriptions factors (0.3 µM FH535). Wnt proteins secretion did not seem to be involved in the fenoterol-induced sensitization since the mRNA expression of Wnt remained low after fenoterol exposure and the inactivator of Wnt secretion (1 µM IWP2) had no effect on the fenoterol-sensitization. Fenoterol exposure did not change the mRNA expression of genes regulating Wnt signaling or cAMP–PKA cascade. Conclusions Collectively, our pharmacological investigations indicate that fenoterol-sensitization is modulated by the inhibition/blockage of canonical Wnt/β-catenin pathway, suggesting a phenomenon of biased agonism in connection with the β2-adrenoceptor stimulation. Future experiments based on the results of the present study will be needed to determine the impact of prolonged fenoterol exposure on the extra- and intracellular Wnt signaling pathways at the protein expression level.
IL-18 and Cutaneous Inflammatory Diseases

Interleukin (IL)-18, an IL-1 family cytokine, is a pleiotropic immune regulator. IL-18 plays a strong proinflammatory role by inducing interferon (IFN)-γ. Previous studies have implicated IL-18 in the pathogenesis of various diseases. However, it is not well understood biologic activities of IL-18 in the diverse skin diseases. Here, we have reviewed the expression and function of IL-18 in skin diseases including inflammatory diseases. This article provides an evidence-based understanding of the role of IL-18 in skin diseases and its relationship with disease activities.
Life Tree: Understanding the Design of Breathing Exercise Games

Regular breathing exercises can be a beneficial part of leading a healthy life. Digital games may have the potential to help people practice breathing exercises in an engaging way, however designing breathing exercise games is not well understood. To contribute to such an understanding, we created Life Tree as the culmination of three prototypal breathing games. Life Tree is a virtual reality (VR) game in which a player controls the growth of a tree by practicing pursed-lip breathing. We selected VR head-mounted display technology because it allows players to focus and limit external distractions, which is beneficial for breathing exercises. 32 participants played Life Tree and analysis of the collected data identified four key themes: 1) Designing Breathing Feedback; 2) Increasing Self-Awareness of Breathing and Body; 3) Facilitating Focused Immersion; and, 4) Engagement with Breathing Hardware. We used these themes to articulate a set of breathing exercise game design strategies that future game designers may consider to develop engaging breathing exercise games.
Phase I, dose-finding study of AZD8931, an inhibitor of ErbB1, 2, and 3 receptor signaling, in combination with paclitaxel (P).

3105 Background: AZD8931 is an oral, equipotent inhibitor of ErbB1, ErbB2 and ErbB3 receptor signaling. METHODS This open-label (3+3 design) study ( NCT00900627 ) evaluated the MTD, safety, tolerability and PK of AZD8931 (40-160 mg bid) combined with P (90 mg/m2 on days 1, 8 and 15 of a 28-day cycle). DLTs were evaluated during Cycle 1. AZD8931 dosing started at 160 mg bid (based on monotherapy study results; NCT00637039 ). RESULTS 20 pts with advanced refractory tumors (16 breast) received AZD8931. Median exposure to AZD8931 was 52 days and to P was 3 cycles. In the 160 mg bid cohort, DLTs occurred in 2/6 pts (Gr 3 rash; Gr 3 keratitis and Gr 3 photophobia), leading to lower dose cohorts. DLTs occurred in 1/2 pts at 120 mg bid (Gr 3 diarrhea) and 2/6 pts at 80 mg bid (Gr 3 rash; Gr 3 esophagitis). AZD8931 40 mg bid was the protocol-defined MTD. At AZD8931 40 mg bid + P, skin rash (n=6) and diarrhea (n=5) were the most common dermatology and GI-related AEs; the majority were of short duration, and responded to appropriate management and/or temporary AZD8931 interruption. At 40 mg bid, AZD8931 steady-state concentrations exceeded preclinical IC50s for target receptors. Combination treatment did not alter exposure of AZD8931 or P (preliminary data). CONCLUSIONS AZD8931 40 mg bid was generally well tolerated, considered suitable for chronic administration, and is progressing into phase II. Experience in this study has highlighted the importance of early rash management and robust guidelines have been adopted. The difference in AZD8931 MTD between this and the monotherapy study most probably reflects differences in clinical interpretation of DLT criteria as they pertained to non life-threatening and subjective events such as rash, more long-term exposure in the present study, and the possible augmentation of rash when EGFR inhibition is combined with P. [Table: see text].
DAG-Structured Long Short-Term Memory for Semantic Compositionality

Recurrent neural networks, particularly long short-term memory (LSTM), have recently shown to be very effective in a wide range of sequence modeling problems, core to which is effective learning of distributed representation for subsequences as well as the sequences they form. An assumption in almost all the previous models, however, posits that the learned representation (e.g., a distributed representation for a sentence), is fully compositional from the atomic components (e.g., representations for words), while non-compositionality is a basic phenomenon in human languages. In this paper, we relieve the assumption by extending the chain-structured LSTM to directed acyclic graphs (DAGs), with the aim to endow linear-chain LSTMs with the capability of considering compositionality together with non-compositionality in the same semantic composition framework. From a more general viewpoint, the proposed models incorporate additional prior knowledge into recurrent neural networks, which is interesting to us, considering most NLP tasks have relatively small training data and appropriate prior knowledge could be beneﬁcial to help cover missing semantics. Our experiments on sentiment composition demonstrate that the proposed models achieve the state-of-the-art performance, outperforming models that lack
Data Association Using Visual Object Recognition for EKF-SLAM in Home Environment

Reliable data association is crucial to localization and map building for mobile robot applications. For that reason, many mobile robots tend to choose vision-based SLAM solutions. In this paper, a SLAM scheme based on visual object recognition, not just a scene matching, in home environment is proposed without using artificial landmarks. For the object-based SLAM, the following algorithms are suggested: 1) a novel local invariant feature extraction by combining advantages of multi-scale Harris corner as a detector and its SIFT descriptor for natural object recognition, 2) the RANSAC clustering for robust object recognition in the presence of outliers and 3) calculating accurate metric information for SLAM update. The proposed algorithms increase robustness by correct data association and accurate observation. Moreover, it also can be easily implemented real-time by reducing the number of representative landmarks, i.e. objects. The performance of the proposed algorithm was verified by experiments using EKF-SLAM with a stereo camera in home-like environments, and it showed that the final pose error was bounded after battery-run-out autonomous navigation for 50 minutes
Adrenal Splanchnic Innervation Modulates Adrenal Cortical Responses to Dehydration Stress in Rats

Classically, the production of glucocorticoids by the adrenal gland is thought to be controlled exclusively by adrenocorticotropic hormone (ACTH). However, there are several examples in stressed humans and animals of increased plasma glucocorticoids in the absence of increased plasma ACTH, suggesting that an additional, non-ACTH mechanism(s) may contribute to the control of glucocorticoid production. The present studies were designed to determine the role of the thoracic splanchnic nerve in controlling plasma corticosterone levels in response to chronic water deprivation in rats, a model previously reported to demonstrate dissociations between plasma corticosterone and ACTH. Briefly, rats underwent right unilateral adrenalectomy and left thoracic splanchnic nerve transection or sham transection. After recovery, rats were water deprived for 48 h or given free access to water, and then sacrificed for collection of plasma and adrenal glands. Water deprivation resulted in consistent, robust increases in plasma corticosterone that were attenuated by splanchnic nerve transection, in the absence of changes in post-dehydration plasma ACTH. Adrenal content of steroidogenic acute regulatory factor (StAR) and cyclic AMP (cAMP) were increased after dehydration; splanchnic nerve transection decreased post-dehydration adrenal cAMP, but not StAR. Splanchnic nerve transection also attenuated plasma corticosterone responses to submaximal doses of ACTH in dexamethasone-blocked, dehydrated rats, suggesting a decreased adrenal sensitivity to ACTH. Collectively, the present results demonstrate that the thoracic splanchnic nerve normally augments the adrenal corticosterone response to dehydration stress by increasing adrenal sensitivity to ACTH, and this augmentation is associated with elevations in adrenal cAMP content. These data support the hypothesis that the splanchnic innervation of the adrenal gland represents an additional physiological mechanism to control stress-induced adrenal cortical responses in vivo.
Automatic inference of memory fences

This paper addresses the problem of placing memory fences in a concurrent program running on a relaxed memory model. Modern architectures implement relaxed memory models which may reorder memory operations or execute them non-atomically. Special instructions called memory fences are provided to the programmer, allowing control of this behavior. To ensure correctness of many algorithms, in particular of non-blocking ones, a programmer is often required to explicitly insert memory fences into her program. However, she must use as few fences as possible, or the benefits of the relaxed architecture may be lost. Placing memory fences is challenging and very error prone, as it requires subtle reasoning about the underlying memory model. We present a framework for automatic inference of memory fences in concurrent programs, assisting the programmer in this complex task. Given a finite-state program, a safety specification and a description of the memory model, our framework computes a set of ordering constraints that guarantee the correctness of the program under the memory model. The computed constraints are maximally permissive: removing any constraint from the solution would permit an execution violating the specification. Our framework then realizes the computed constraints as additional fences in the input program. We implemented our approach in a tool called FENDER and used it to infer correct and efficient placements of fences for several non-trivial algorithms, including practical concurrent data structures.
Oral candidiasis: a comparison between conventional methods and multiplex polymerase chain reaction for species identification.

BACKGROUND/AIM Oral candidiasis is the most common fungal infection in dental practice, and is caused by yeasts that are normally present in the endogenous flora. METHODS To evaluate a rapid diagnostic method for identification of Candida oral isolates, a multiplex polymerase chain reaction (PCR) was carried out on colonies and on oral rinse solutions from 95 subjects with suspected oral candidiasis and results were compared with those from seven commonly used phenotypic identification systems. RESULTS Between four and nine species were characterized in the samples by the phenotypic methods. PCR identified the same species in 60 (74%) samples from both colony and oral rinse solutions. Statistical analysis, carried out only for the three most frequently isolated species (Candida albicans, Candida glabrata, and Candida tropicalis), showed good concordance in the comparison of multiplex PCR with API 20C AUX and with the Rapid Yeast Identification Panel; conversely, significant differences were registered in the comparison between the molecular method and other phenotypic systems, including four chromogenic media and the automated system Vitek2. DISCUSSION Multiplex PCR was rapid and effective in the identification of Candida species and allowed the detection of more than one species in the same sample.
Treatment of early rheumatoid arthritis

Recent advances in the understanding of the pathophysiology, aggressive treatment, and early detection of rheumatoid arthritis (RA) have changed the clinical, pathologic, and functional outcomes in patients with RA. Early aggressive treatment of RA has now become the norm in clinical practice rather than the use of the traditional pyramid approach of the last half of the twentieth century. Early treatment with monotherapy of traditional disease-modifying antirheumatic drugs (DMARDs) or biologics, combination traditional DMARD therapy and, especially, combination of biologic therapy and methotrexate, have revolutionized the treatment of RA, producing significant improvement in clinical, radiographic, and functional outcomes not seen previously. For the individual patient, we still cannot determine which medication or combination of medications will give the most complete response. There have been a number of recent, well-designed clinical trials that have tried to answer this question. Herein we review the evidence-based medicine that addresses these issues.
Neural Classifier for Detection and Classification of Spikes and Sharp Waves

In this article is discussed the application of a hybrid approach that uses the Wavelet Transform and Artificial Neural Networks in detection and recognition of epileptiform events in EEG signals. It is presented the methodology used to develop a Neural Classifier as well as the experiments and its results through the Neural Networks and Wavelet Transform. The developed Neural Classifier showed good results in the classification of Epileptiform events with and without pre-processing achieving sensitive of 97.14%, specificity of 94.55% and accuracy of 96.14%, suggesting the high sample rate of the EEG signals contributed to achieve these values.
Predictors and consequences of food neophobia and pickiness in young girls.

OBJECTIVE Vegetable intake among children is well below recommended levels. We assessed whether food neophobia and pickiness contribute to low vegetable intake in school-aged girls and if there are distinct predictors for neophobia and pickiness. Children with food neophobia are reluctant to eat new foods whereas picky children resist eating many familiar foods. Design/subjects Participants were 192 7-year-old girls and their parents, recruited for a study of girls' nutrition and development. We examined relationships between food neophobia and pickiness and assessed whether these variables predicted girls' vegetable consumption and predictors of food neophobia and pickiness. ANALYSES The data were analyzed using a two-step process. First, we used a two-way analysis of variance to assess whether girls who scored high or low on food neophobia and pickiness measures had different levels of vegetable consumption. We used multiple regression analysis to determine predictors of food neophobia and pickiness in the girls. RESULTS Girls with both food neophobia and pickiness consumed fewer vegetables (1.1+/-0.1) than girls with neither neophobia nor pickiness (1.6+/-0.1). Neophobia and pickiness were modestly related in this sample, but had different predictors. Girls with food neophobia were more anxious and had mothers with food neophobia. Picky girls had mothers with less variety in their vegetable intake (r=-0.22) and mothers who perceived their family to have little time to eat healthful foods (r=0.36). In addition, picky eaters were breastfed for fewer than 6 months (r=-0.25). Pickiness was predicted primarily by environmental or experiential factors subject to changes; neophobia was predicted by more enduring and dispositional factors. APPLICATIONS Because food neophobia and pickiness negatively influence vegetable intake, intervention strategies to increase vegetable intake should focus on predictors of neophobia and pickiness, especially those subject to change.
Comparing the Capitalisation Benefits of Light-rail Transit and Overlay Zoning for Single-family Houses and Condos by Neighbourhood Type in Metropolitan Phoenix, Arizona

Light rail transit (LRT) is increasingly accompanied by overlay zoning which specifies the density and type of future development to encourage landscapes conducive to transit use. Neighbourhood type (based on land use mix) is used to partition data and investigate how pre-existing land use, treatment with a park-and-ride (PAR) versus walk-and-ride (WAR) station and overlay zoning interrelate. Hedonic models estimate capitalisation effects of LRT-related accessibility and overlay zoning on single-family houses and condos in different neighbourhoods for the system in metropolitan Phoenix, Arizona. Impacts differ by housing and neighbourhood type. Amenity-dominated mixed-use neighbourhoods—predominantly WAR communities—experience premiums of 6 per cent for single-family houses and over 20 per cent for condos, the latter boosted an additional 37 per cent by overlay zoning. Residential neighbourhoods—predominantly PAR communities—experience no capitalisation benefits for single-family houses and a discount for condos. The results suggest that land use mix is an important variable to select comparable neighbourhoods.
Factors Associated to Vaccination against Influenza among Elderly in a Large Brazilian Metropolis

Background This study aimed to estimate coverage and identify factors associated to vaccination against influenza in the elderly population. Methods The study design was cross-sectional and population based. Data was collected in 2010 by the Health, Well-Being and Aging Study. Sample consisted of 1,341 community-dwelling elderly, in São Paulo, Brazil. Association between vaccination and covariates was evaluated by means of prevalence ratios estimated by Poisson regression models. Results Self-reported vaccination coverage was 74.2% (95% confidence interval: 71.3–76.9). Remaining physically active and having had recent interaction with health services, mainly with public units of healthcare, were the main incentives to increase vaccination coverage among the elderly; whereas lower age, living alone and absent interaction with health services were the main constraints to influenza vaccination at the community level. These covariates had already been reported to influence influenza vaccination of elders in previous years. Conclusion Previous knowledge already available on the main constraints to influenza vaccination has not allowed to remove them. Influenza campaigns should be strengthened to increase vaccination coverage, especially in the group more reticent to vaccination. Instructing healthcare providers to recommend vaccine uptake is an important piece of this puzzle.
Dialog-based Language Learning

A long-term goal of machine learning research is to build an intelligent dialog agent. Most research in natural language understanding has focused on learning from fixed training sets of labeled data, with supervision either at the word level (tagging, parsing tasks) or sentence level (question answering, machine translation). This kind of supervision is not realistic of how humans learn, where language is both learned by, and used for, communication. In this work, we study dialog-based language learning, where supervision is given naturally and implicitly in the response of the dialog partner during the conversation. We study this setup in two domains: the bAbI dataset of (Weston et al., 2015) and large-scale question answering from (Dodge et al., 2015). We evaluate a set of baseline learning strategies on these tasks, and show that a novel model incorporating predictive lookahead is a promising approach for learning from a teacher's response. In particular, a surprising result is that it can learn to answer questions correctly without any reward-based supervision at all.
Band-gap engineering of Germanium monolithic light sources using tensile strain and n-type doping

Band-gap engineering of bulk germanium (Ge) holds the potential for realizing a laser source, permitting full integration of monolithic circuitry on CMOS platforms. Techniques rely mainly on tensile strain and n-type doping. In this thesis, we focus on studying diffusion-based phosphorus (P) doping of Ge using spin-on dopants (SOD), and tensile strain engineering using freestanding micro-electro-mechanical systems (MEMS)-like structures. Process development of a reliable SOD recipe was conducted using furnace and rapid-thermal annealing, and successful doping up to 2.5 × 1019cm-3 was achieved, resulting in approximately 10× enhancement in direct-gap emission. A transition in Ge direct-gap-photoluminescence (PL) behaviour is observed upon doping, from being quadratically dependent on excitation power to linear. We have also demonstrated that the limited doping concentration of P in Ge using SOD is not source limited, but more probably related to the diffusion mechanism. The other part of the project concentrated on Ge strain engineering. Previous works reported high tensile strain values based on freestanding MEMS-like structures made of Ge, yet without embedding an optical cavity (until recently). In this project, we realize this combination by fabricating Ge micro-disks as an optical cavity on top of freestanding SiO2 structures, utilizing Ge-on- Insulator wafers (GOI). 3D computer simulations were used to understand and optimize the devices, in terms of strain and optical performance. Raman spectroscopy and PL measurements confirmed simulation results showing higher tensile strain for beams with shorter lengths, with a maximum uniaxial strain of 1.3%. Splitting of light and heavy hole energy bands was observed by PL as the strain increases, agreeing with theoretical models. Direct-gap sharp-peak whispering-gallery modes (WGMs) were confined in 3 µm disks with a maximum quality-factor of ~200. Two loss mechanisms could be distinguished, red-shift of the absorption edge, and free-carrier absorption. In order to avoid these excitation-related losses, higher strain values combined with heavy n-type doping are required. A possible implementation using the same GOI platform is proposed for future work.