Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of the anti-IL-17 antibody on allergic inflammation in an obesity-related asthma model

Background/Aims The co-occurrence of obesity aggravates asthma symptoms. Diet-induced obesity increases helper T cell (TH) 17 cell differentiation in adipose tissue and the spleen. The 3-hydroxy-3-methylglutaryl-coenzyme A reductase inhibitor pravastatin can potentially be used to treat asthma in obese patients by inhibiting interleukin 17 (IL-17) expression. This study investigated the combined effects of pravastatin and anti-IL-17 antibody treatment on allergic inflammation in a mouse model of obesity-related asthma. Methods High-fat diet (HFD)-induced obesity was induced in C57BL/6 mice with or without ovalbumin (OVA) sensitization and challenge. Mice were administered the anti-IL-17 antibody, pravastatin, or both, and pathophysiological and immunological responses were analyzed. Results HFD exacerbated allergic airway inflammation in the bronchoalveolar lavage fluid of HFD-OVA mice as compared to OVA mice. Blockading of the IL-17 in the HFD-OVA mice decreased airway hyper-responsiveness (AHR) and airway inflammation compared to the HFD-OVA mice. Moreover, the administration of the anti-IL-17 antibody decreased the leptin/adiponectin ratio in the HFD-OVA but not the OVA mice. Co-administration of pravastatin and anti-IL-17 inhibited airway inflammation and AHR, decreased goblet cell numbers, and increased adipokine levels in obese asthmatic mice. Conclusions These results suggest that the IL-17–leptin/adiponectin axis plays a key role in airway inflammation in obesity-related asthma. Our findings suggest a potential new treatment for IL-17 as a target that may benefit obesity-related asthma patients who respond poorly to typical asthma medications.
Ant colony optimisation combined with variable neighbourhood search for scheduling preventive railway maintenance activities

Railway infrastructure maintenance is of fundamental importance in order to ensure a good service in terms of punctuality, safety and efficiently operation of trains on railway track and also for passenger comfort. Track maintenance covers a large amount of different activities such as inspections, repairs, and renewals. In this paper, we address the NP-hard problem of scheduling the preventive railway maintenance activities in order to minimise the overall cost of these activities. Given the complexity of the problem, we propose two meta-heuristics, a variable neighbourhood search (VNS), and an ant colony optimisation (ACO) based on opportunities to deal with this problem. Then, we develop a hybrid approach combining ACO with VNS. The performance of our proposed algorithms is tested by numerical experiments on a large number of randomly generated instances. Comparisons with optimal solutions are presented. The results show the effectiveness of our proposed methods.
Age at natural menopause and associated factors in adult women: Findings from the China Kadoorie Biobank study in Zhejiang rural area

Objectives To investigate the factors associated with age at natural menopause in a large population of Chinese adult women. Methods This cross-sectional study was part of the baseline survey of China Kadoorie Biobank in Zhejiang Province. A total of 17,076 postmenopausal women were included in the present study. Relevant data of socio-demographic, lifestyle, dietary and reproductive characteristics were collected. Multinomial logistic regression models were used to examine the associated factors of age at natural menopause with adjusted odds ratios (ORs) and their 95% confidence intervals (CIs) were reported. Results The mean age at natural menopause was 48.94 years, with 3.40% of the women experienced premature menopause and 6.75% early menopause. Younger age, higher education, consumption of meat (1–3 days per week) and increased parity were associated with late menopause. Current smoking, underweight, higher physical activity, consumption of sea food (1–3 days per week), fresh eggs (≥4 days per week), fresh fruits (≥1 day per week), taking vitamins, experiencing severe food shortage, earlier age at menarche and older age at first birth were associated with earlier age at natural menopause. Conclusions These results suggest that certain factors involved with socio-demographic, lifestyle, dietary and reproductive characteristics are related to the age at natural menopause in Chinese women.
Effect of Hydroalcoholic Extract of Rosmarinus officinalis L. Leaf on Anxiety in Mice

In today’s stressful world, psychopathy (especially anxiety) is receiving increased importance. Most of the drugs used to treat this disease have several side effects. Medicinal plants derived from natural products have fewer side effects and can be used in the treatment of this disease. The aim of this study was to evaluate the effect of the hydroalcoholic extract of Rosmarinus officinalis L. on anxiety in mice. In this experimental study, 50 male mice were randomly divided into 5 groups. To evaluate anxiety, the Elevated Plus Maze test was performed. The control group received normal saline, the positive control group received diazepam (1 mg/kg) as intraperitoneal injection, and the experimental groups received doses of 100, 200, and 400 mg/kg body weight of rosemary extract. The data were analyzed using SPSS 15 and ANOVA statistical tests. The results show that rosemary extract dose-dependently increases the mice spending time and the entries number of mice in plus maze open arms (indicating less stress). This effect at a dose of 400 mg/kg was similar to diazepam, which, in comparison to the control group, was statistically significant (P < .01), while the evaluation of locomotor activity in treated groups, compared with the control groups, showed no significant difference (P > .05). On the other hand, the rosemary extract, similar to the standard drug diazepam, showed an anti-anxiety effect. This effect is probably due to the presence of flavonoids in this plant and their antioxidant property.
Long non‐coding RNA SNHG14 contributes to gastric cancer development through targeting miR‐145/SOX9 axis

This study aimed to elucidate the roles of long non‐coding RNA SNHG14 in gastric cancer development. LncRNA SNHG14 was markedly up‐regulated in gastric cancer tissues and cells. Knockdown of SNHG14 significantly inhibited SGC‐7901 cell viability, migration, invasion, and promoted cell apoptosis. In addition, miR‐145 was negatively regulated by SNHG14 and the effects of SNHG14 knockdown on cell viability, apoptosis, migration, invasion, and the expression of apoptosis‐related proteins and EMT‐markers were reversed by inhibition of miR‐145 at the same time. Furthermore, SOX9 was verified as a functional target of miR‐145, and miR‐145 regulated tumor malignant behaviors through regulating SOX9. Besides, knockdown of SNHG14 inhibited the expression of p‐PI3 K, p‐AKT, and p‐mTOR and promoted PTEN expression, where miR‐145 inhibition had opposite effects. Moreover, the activated PI3 K/AKT/mTOR pathway caused by miR‐145 inhibition was counteracted after knockdown of SOX9. Our findings indicate that up‐regulation of lncRNA SNHG14 may contribute to gastric cancer development via targeting miR‐145/SOX9 axis and involving in PI3 K/AKT/mTOR pathway. SNHG14‐miR‐145/SOX9 axis may be a promising therapeutic strategy for gastric cancer treatment.
On symbolic dynamics of a chaotic second-order digital filter

This paper presents a contribution to the symbolic analysis of fractal patterns exhibited by a second-order digital filter with modular adder overflow characteristic. We use symbolic dynamics for the analysis of phenomena encountered in the system. We present several new results concerning the existence of admissible sequences for periodic orbits in the filter. an efficient computational algorithm based on rigorous mathematical results presented in the paper enabled us to calculate sequences with long periods, thus allowing deeper understanding of the underlying mechanisms of complex behaviour encountered in the filter.
Clinical Outcomes of Extended-Spectrum Beta-Lactamase-Producing Enterobacteriaceae Infections with Susceptibilities among Levofloxacin, Cefepime, and Carbapenems

Purpose Highly resistant Gram-negative bacterial infections are associated with high mortality. Increasing resistance to standard therapy illustrates the need for alternatives when treating resistant organisms, especially extended-spectrum beta-lactamase- (ESBL-) producing Enterobacteriaceae. Methods A retrospective chart review at a community hospital was performed. Patients who developed ESBL-producing infections were included. Patients less than eighteen years old, who were pregnant, or who were incarcerated were excluded. The primary outcome was hospital mortality. The secondary outcomes included intensive care unit (ICU) mortality, ICU length of stay, and hospital length of stay. Results 113 patients with ESBL-producing infections met the criteria for review. Hospital mortality: carbapenem (16.6%), cefepime (0%), and levofloxacin (15.3%) (p=0.253). ICU mortality: carbapenem (4.5%), cefepime, (0%), and levofloxacin (3.7%) (p=0.616). Mean ICU and hospital length of stay: carbapenem (9.8 ± 16, 12.1 ± 1 days), cefepime (7.8 ± 6, 11.1 ± 10.5 days), and levofloxacin (5.4 ± 4.1, 11.1 ± 10.4 days) (p=0.805, 0.685). No predictors were clearly found between the source of infection and mortality. Conclusion Cefepime or levofloxacin can be a potential alternative agent for infections with ESBL-producing Enterobacteriaceae, and larger clinical trials investigating these outcomes are warranted.
Understanding the in vivo fate of radioimmunoconjugates for nuclear imaging.

Over the past 25 years, antibodies have emerged as extraordinarily promising vectors for the delivery of radionuclides to tumors for nuclear imaging. While radioimmunoconjugates often produce very high activity concentrations in target tissues, they also are frequently characterized by elevated activity concentrations in healthy organs as well. The root of this background uptake lies in the complex network of biological interactions between the radioimmunoconjugate and the subject. In this review, we seek to provide an overview of these interactions and thus paint a general picture of the in vivo fate of radioimmunoconjugates. To cover the entire story, we have divided our discussion into 2 parts. First, we will address the path of the entire radioimmunoconjugate as it travels through the body. And second, we will cover the fate of the radionuclide itself, as its course can diverge from the antibody under certain circumstances. Ultimately, our goal is to provide the nuclear imaging field with a resource covering these important-yet often underestimated-pathways.
Deep Probabilistic Programming Languages: A Qualitative Study

Deep probabilistic programming languages try to combine the advantages of deep learning with those of probabilistic programming languages. If successful, this would be a big step forward in machine learning and programming languages. Unfortunately, as of now, this new crop of languages is hard to use and understand. This paper addresses this problem directly by explaining deep probabilistic programming languages and indirectly by characterizing their current strengths and weaknesses.
From C to elastic circuits

Today's high-level synthesis (HLS) tools rely on static scheduling. When control and/or data dependencies that cannot be resolved at compile time are present in program code, HLS tools produce pessimistic schedules based on worst-case assumptions, which may not be the common case or may never even occur in practice. At present, the only alternative is for circuit designers to eschew HLS, and to instead implement dynamic scheduling, which stalls or slows execution when control or data hazards manifest themselves at runtime, in hardware. This paper examines these issues in detail using a histogram kernel as a case-study. Starting with an inefficiently scheduled implementation produced by Vivado HLS, we introduce a latency-insensitive control mechanism that enables reaching a point in the design space that Vivado HLS could not discover on its own. We describe a step-by-step process by which a compiler could infer a dynamically scheduled circuit, starting from a high-level C language specification.
A multilevel Bayesian spatial logistic regression in South Western Sydney

The purpose is to explore the multilevel spatial distribution of depressive symptoms among migrant mothers in South Western Sydney and to identify any group level associations that could inform subsequent theory building and local public health interventions. Migrant mothers (n = 7256) delivering in 2002 and 2003 were assessed at 2–3 weeks after delivery for risk factors for depressive symptoms. The binary outcome variables were Edinburgh Postnatal Depression Scale scores (EPDS) of >9 and >12. Individual level variables included were: financial income, self-reported maternal health, social support network, emotional support, practical support, baby trouble sleeping, baby demanding and baby not content. The group level variable reported here is aggregated social support networks. We used Bayesian hierarchical multilevel spatial modelling with conditional autoregression. Migrant mothers were at higher risk of having depressive symptoms if they lived in a community with predominantly Australian-born mothers and strong social capital as measured by aggregated social networks. These findings suggest that migrant mothers are socially isolated and current home visiting services should be strengthened for migrant mothers living in communities where they may have poor social networks. 2013 The Authors. Published by Elsevier Ltd.Open access under CC BY license.
DAMBE7: New and Improved Tools for Data Analysis in Molecular Biology and Evolution

Abstract DAMBE is a comprehensive software package for genomic and phylogenetic data analysis on Windows, Linux, and Macintosh computers. New functions include imputing missing distances and phylogeny simultaneously (paving the way to build large phage and transposon trees), new bootstrapping/jackknifing methods for PhyPA (phylogenetics from pairwise alignments), and an improved function for fast and accurate estimation of the shape parameter of the gamma distribution for fitting rate heterogeneity over sites. Previous method corrects multiple hits for each site independently. DAMBE’s new method uses all sites simultaneously for correction. DAMBE, featuring a user-friendly graphic interface, is freely available from http://dambe.bio. uottawa.ca (last accessed, April 17, 2018).
CIS: The Crypto Intelligence System for automatic detection and localization of cryptographic functions in current malware

Finding and extracting crypto algorithms in binary code is often a tedious reverse engineering task. A significant amount of manual work is required when unknown implementations are used. This is especially true for malware that contains variants of existing or even completely new algorithms. So far, no flexible and generic crypto detection framework exists that can support analysts in this task. The framework must be able to handle various heuristics that each are ideal to detect specific types of cryptographic algorithms. In addition, a suitable set of heuristics must be selected that can identify a wide range of crypto algorithms from various classes since the type of crypto implemented in a binary is not always known. In this paper, we present the architecture of CIS, the Crypto Intelligence System, that fulfills the requirements for such a framework. Furthermore, we evaluate different heuristics for the real-world usage in the framework. The overall evaluation, using real programs, shows that CIS simplifies the job of an analysts significantly with a high detection and low false positive ratio.
Microbleeds in ischemic vs hemorrhagic strokes on novel oral anticoagulants

To identify differences in clinical characteristics and severity of cerebral small vessel disease (CSVD) including cerebral microbleeds (CMBs), between patients suffering ischemic stroke (IS) or intracerebral hemorrhage (ICH) while taking novel (non‐vitamin K antagonists) oral anticoagulants (NOACs).
Usage pattern analysis of smartphones

Recently, mobile traffic has increased tremendously due to the deployment of smart devices such as smartphones and smart tablets. These devices use various types of access networks such as 3G, WiFi, and mobile WiMAX. Network service providers also provide these access networks with various types of plans. There is a growing need to manage these smart devices and mobile networks. However, research on mobile network management has focused on the performance of the network itself. Few research has focused on applying the usage patterns of smartphone users to mobile network management. In this paper, we present an analysis of smartphone usage patterns. We define the five possible states of a smartphone based on such a phone's basic operations. We collected real usage log data from real smartphone users over a two month period. We show that all users have their own usage pattern. We present a case study in order to show how to apply usage pattern information to power management of smartphones. We also discuss how to apply such information to mobile device management and network management.
The myofibroblast in wound healing and fibrocontractive diseases

The demonstration that fibroblastic cells acquire contractile features during the healing of an open wound, thus modulating into myofibroblasts, has open a new perspective in the understanding of mechanisms leading to wound closure and fibrocontractive diseases. Myofibroblasts synthesize extracellular matrix components such as collagen types I and III and during normal wound healing disappear by apoptosis when epithelialization occurs. The transition from fibroblasts to myofibroblasts is influenced by mechanical stress, TGF‐β and cellular fibronectin (ED‐A splice variant). These factors also play important roles in the development of fibrocontractive changes, such as those observed in liver cirrhosis, renal fibrosis, and stroma reaction to epithelial tumours. Copyright © 2003 John Wiley & Sons, Ltd.
Priority effects can persist across floral generations in nectar microbial metacommunities

Author(s): Toju, H; Vannette, RL; Gauthier, MPL; Dhami, MK; Fukami, T | Abstract: © 2017 The Authors The order of species arrival can influence how species interact with one another and, consequently, which species may coexist in local communities. This phenomenon, called priority effects, has been observed in various types of communities, but it remains unclear whether priority effects persist over the long term spanning multiple generations of local communities in metacommunities. Focusing on bacteria and yeasts that colonize floral nectar of the sticky monkey flower, Mimulus aurantiacus, via hummingbirds and other flower-visiting animals, we experimentally manipulated initial microbial dominance on plants (regarded as metacommunities) to examine whether its effects persisted across multiple generations of flowers (regarded as local microbial habitats). The experimental introduction of Neokomagataea (= Gluconobacter) bacteria and Metschnikowia yeasts into wild flowers showed that the effects of initial dominance were observable across multiple floral generations. Three weeks after introduction, corresponding approximately to three floral generations, Neokomagataea introduction led to exclusion of yeasts, whereas Metschnikowia introduction did not result in the exclusion of Neokomagataea. Our results suggest that, even when local habitats are ephemeral, priority effects may influence multiple generations of local communities within metacommunities.
Quantifying anti-gravity torques in the design of a powered exoskeleton

Designing an upper extremity exoskeleton for people with arm weakness requires knowledge of the passive and active residual force capabilities of users. This paper experimentally measures the passive gravitational torques of 3 groups of subjects: able-bodied adults, able bodied children, and children with neurological disabilities. The experiment involves moving the arm to various positions in the sagittal plane and measuring the gravitational force at the wrist. This force is then converted to static gravitational torques at the elbow and shoulder. Data are compared between look-up table data based on anthropometry and empirical data. Results show that the look-up torques deviate from experimentally measured torques as the arm reaches up and down. This experiment informs designers of Upper Limb orthoses on the contribution of passive human joint torques.
AGR 2 promotes the proliferation , migration and regulates epithelial-mesenchymal transition in salivary adenoid cystic carcinoma

Salivary adenoid cystic carcinoma (AdCC) is a common head and neck cancer with the propensity for local spread and distant metastasis. In our previous study, elevated expression of Anterior gradient 2 (AGR2) was detected in head and neck squamous cell carcinoma (HNSCC), associated with epithelial-mesenchymal transition (EMT) and cancer stemness. However, to date, the expression and function of AGR2 in AdCC has yet to be elucidated. In the present study, human AdCC tissue microarrays including 18 cases of normal salivary gland (NSG), 12 cases of pleomorphic adenoma (PMA) and 72 cases of AdCC were employed for immunohistochemical staining analysis. Results indicated that AGR2, which was remarkably correlated with Ki-67, transforming growth factor beta-1 (TGF-β1) and CD147, was significantly elevated in human salivary AdCC tissues. Knockdown of AGR2 significantly repressed the proliferation and migration of human SACC-83 and SACC-LM cell lines. Additionally, AGR2 silencing obviously reversed the EMT phenomena induced by TGF-β1. Taken together, our present study revealed the potential pro-metastasis role of AGR2 in AdCC, indicating that AGR2 might be a novel therapeutic target of AdCC with distant metastasis.
Feature Genes Selection Using Supervised Locally Linear Embedding and Correlation Coefficient for Microarray Classification

The selection of feature genes with high recognition ability from the gene expression profiles has gained great significance in biology. However, most of the existing methods have a high time complexity and poor classification performance. Motivated by this, an effective feature selection method, called supervised locally linear embedding and Spearman's rank correlation coefficient (SLLE-SC2), is proposed which is based on the concept of locally linear embedding and correlation coefficient algorithms. Supervised locally linear embedding takes into account class label information and improves the classification performance. Furthermore, Spearman's rank correlation coefficient is used to remove the coexpression genes. The experiment results obtained on four public tumor microarray datasets illustrate that our method is valid and feasible.
Feedback-Based Admission Control for Firm Real-Time Task Allocation with Dynamic Voltage and Frequency Scaling

Feedback-based mechanisms can be employed to monitor the performance of Multiprocessor Systems-on-Chips (MPSoCs) and steer the task execution even if the exact knowledge of the workload is unknown a priori. In particular, traditional proportional-integral controllers can be used with firm real-time tasks to either admit them to the processing cores or reject in order not to violate the timeliness of the already admitted tasks. During periods with a lower computational power demand, dynamic voltage and frequency scaling (DVFS) can be used to reduce the dissipation of energy in the cores while still not violating the tasks’ time constraints. Depending on the workload pattern and weight, platform size and the granularity of DVFS, energy savings can reach even 60% at the cost of a slight performance degradation.