Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of gut microbiota in the regulation of standard metabolic rate in female Periplaneta americana

Insect gut microbiota contribute significantly to host nutritional ecology. Disrupting insect gut microbial assemblages impacts nutrient provisioning functions, and can potentially affect host standard metabolic rate (SMR), a measure of host energy balance. In this study, we evaluated the effect of disrupting gut microbial assemblages on the SMR of female Periplaneta americana cockroaches fed dog food (DF, high protein/carbohydrate (p/c) ratio), and cellulose-amended dog food (CADF, 30% dog food, 70% cellulose, low p/c ratio) diets, supplemented with none, low, or high antibiotic doses. Bacterial loads decreased significantly between diet types (P = 0.04) and across antibiotic doses (P = 0.04). There was a significant diet type x antibiotic dose interaction on SMR of females on both diets (P = 0.05) by the end of the seven-day experimental period. In CADF-fed females, SMR decreased linearly with decreasing bacterial load. However, SMR of DF-fed females on the low dose was significantly higher than those in the control and high dose groups. This is interpreted as a diet-dependent response by low dose DF-fed females to the loss of nutritional services provided by gut bacteria. Severe reductions in bacterial load at high doses reduced SMR of females on both diet types. This study provides insights into the potential role of gut bacteria as modulators of host energy expenditure under varying dietary conditions.
Use of cluster analysis to characterize patterns of sensitization in childhood allergy

Multiple tests are available to determine food and aero-allergen sensitization (1,2), but it is unclear if distinct sensitization patterns can be determined by using a combination of three testing modalities; skin prick test (SPT), specific IgE test and component resolved diagnostic tests to characterize or identify certain clinical phenotypes. This is a novel paper utilizing sensitization clusters (SPT, specific IgE tests and component resolved diagnostics) in an unselected cohort of 10/11 year-old children and its association with asthma, eczema, rhinitis and IgE-mediated food allergy. A birth cohort recruited in 2001 (Isle of Wight), was followed up prospectively to 10 years of age (3) (n = 827). This article is protected by copyright. All rights reserved.
Betulinic Acid Exerts Cytotoxic Activity Against Multidrug-Resistant Tumor Cells via Targeting Autocrine Motility Factor Receptor (AMFR)

Betulinic acid (BetA) is a naturally occurring pentacyclic triterpene isolated from the outer bark of white-barked birch trees and many other medicinal plants. Here, we studied betulinic acid's cytotoxic activity against drug-resistant tumor cell lines. P-glycoprotein (MDR1/ABCB1) and BCRP (ABCG2) are known ATP-binding cassette (ABC) drug transporters that mediating MDR. ABCB5 is a close relative to ABCB1, which also mediates MDR. Constitutive activation of the EGF receptor is tightly linked to the development of chemotherapeutic resistance. BetA inhibited P-gp, BCRP, ABCB5 and mutation activated EGFR overexpressing cells with similar efficacy as their drug-sensitive parental counterparts. Furthermore, the mRNA expressions of ABCB1, BCRP, ABCB5 and EGFR were not related to the 50% inhibition concentrations (IC50) for BetA in a panel of 60 cell lines of the National Cancer Institute (NCI), USA. In addition to well-established MDR mechanisms, we attempted to identify other molecular mechanisms that play a role in mediating BetA's cytotoxic activity. For this reason, we performed COMPARE and hierarchical cluster analyses of the transcriptome-wide microarray-based mRNA expression of the NCI cell lines panel. Various genes significantly correlating to BetA's activity were involved in different biological processes, e.g., cell cycle regulation, microtubule formation, signal transduction, transcriptional regulation, chromatin remodeling, cell adhesion, tumor suppression, ubiquitination and proteasome degradation. Immunoblotting and in silico analyses revealed that the inhibition of AMFR activity might be one of the mechanisms for BetA to overcome MDR phenotypes. In conclusion, BetA may have therapeutic potential for the treatment of refractory tumors.
Diversifying Citation Contexts in Academic Literature for Knowledge Recommendation

Citation contexts of an article refer to sentences or paragraphs that cite that article. Citation contexts are especially useful for recommendation and summarization tasks. However, few studies have recognized the diversity of these citation contexts, thus leading to redundant recommendation lists and abstract [3]. To address this gap, we compared several strategies that can recommend a set of diverse citation contexts by re-ranking extracted citation contexts. Diversification was achieved by combining one of two semantic distance algorithms with one of two re-ranking algorithms. Experimenting with CiteSeerX dataset, our program produced a diverse list of 10 citation contexts that could be recommended to users. We evaluated the experiment results based on a user case study of 15 articles. The case study revealed that a diversity strategy that combined the "ESA" and "MMR" led to a better reading experience for participants compared to other diversity strategies. Our study provides insights to develop better automatic academic recommendation and summarization systems.
TagNet: Toward Tag-Based Sentiment Analysis of Large Social Media Data

Hashtags and replies, originally introduced on Twitter, have become the most popular ways to tag short messages in social networks. While the primary uses of these human-labeled metadata are still for message retrieval and clustering, there have been increasing attempts to use them as subject or topic indicators in measuring people's continuous sentiments in large message corpora. However, conducting the analysis for large social media data is still challenging due to the message volume, heterogeneity, and temporal dependence. In this paper, we present TagNet, a novel visualization approach tailored to the tag-based sentiment analysis. TagNet combines traditional tag clouds with an improved node-link diagram to represent the time-varying heterogeneous information with reduced visual clutter. A force model is leveraged to generate layout aesthetics from which the temporal patterns of tags can be easily compared across different subsets of data. It is enhanced by visual encodings for quickly estimating the time-varying sentiment. Interaction tools are provided to improve the scalability for exploring large corpora. An example Twitter corpus illustrates the applicability and usefulness of TagNet.
Cannabis and cannabinoids for the treatment of people with chronic noncancer pain conditions: a systematic review and meta-analysis of controlled and observational studies

Abstract This review examines evidence for the effectiveness of cannabinoids in chronic noncancer pain (CNCP) and addresses gaps in the literature by: considering differences in outcomes based on cannabinoid type and specific CNCP condition; including all study designs; and following IMMPACT guidelines. MEDLINE, Embase, PsycINFO, CENTRAL, and clinicaltrials.gov were searched in July 2017. Analyses were conducted using Revman 5.3 and Stata 15.0. A total of 91 publications containing 104 studies were eligible (n = 9958 participants), including 47 randomised controlled trials (RCTs) and 57 observational studies. Forty-eight studies examined neuropathic pain, 7 studies examined fibromyalgia, 1 rheumatoid arthritis, and 48 other CNCP (13 multiple sclerosis–related pain, 6 visceral pain, and 29 samples with mixed or undefined CNCP). Across RCTs, pooled event rates (PERs) for 30% reduction in pain were 29.0% (cannabinoids) vs 25.9% (placebo); significant effect for cannabinoids was found; number needed to treat to benefit was 24 (95% confidence interval [CI] 15-61); for 50% reduction in pain, PERs were 18.2% vs 14.4%; no significant difference was observed. Pooled change in pain intensity (standardised mean difference: −0.14, 95% CI −0.20 to −0.08) was equivalent to a 3 mm reduction on a 100 mm visual analogue scale greater than placebo groups. In RCTs, PERs for all-cause adverse events were 81.2% vs 66.2%; number needed to treat to harm: 6 (95% CI 5-8). There were no significant impacts on physical or emotional functioning, and low-quality evidence of improved sleep and patient global impression of change. Evidence for effectiveness of cannabinoids in CNCP is limited. Effects suggest that number needed to treat to benefit is high, and number needed to treat to harm is low, with limited impact on other domains. It seems unlikely that cannabinoids are highly effective medicines for CNCP.
Acquired 5-Fluorouracil Resistance in Human Pancreatic Carcinoma Cells. A Paradigm for Chemoresistance Mechanisms in Pancreatic Cancer

Context Pancreatic ductal adenocarcinoma is a dismal disease with one of the worst prognoses amongst solid tumors. Its ability to develop chemoresistance mechanisms towards cytotoxic drugs is the main cause of treatment failure. Objective Here, we have established a drug-resistance model for pancreatic cancer in which Capan-1 pancreatic carcinoma cells (designated Capan-1 5-FU2000) acquired 5-fluorouracil (5-FU) resistance and were used as a paradigm to reveal alterations in intracellular signaling cascades that. Those alterations may contribute to the circumvention of apoptosis during the course of the disease, culminating in treatment failure. Methods We made use of 2-D-gelelectrophoresis, mass-spectrometry, sandwich-ELISA and western blotting to compare the proteomic expression patterns of respective mediators involved in pro- and antiapoptotic as well as inflammatory processes in both cell lines. An ATP-based chemosensitivity assay validated the chemoresistant phenotype of the Capan-1 5-FU2000 clones. Results We detected specific changes in our resistant cell clones in particular a decreased expression of S100A4. We also found a decreased basal phosphorylation of SAPK/JNK and P38. The expression of the pro-apoptotic mediators Bok and Bad was down- and up-regulated in these cells, respectively. In case of NfkB p65 and IkB-alpha treatment with 5-FU (2,000 µg/mL for 96 h) markedly induced phosphorylation in native Capan-1 cells. In contrast in resistant clones it decreased phosphorylation of NfkB p65 and did not affect IkB-alpha phosphorylation. Basal phosphorylation of S6-ribosomal-protein was markedly increased in resistant clones, treatment with 5-FU decreased this phosphorylation, while in native Capan-1 cells it was vice versa. Conclusion Thus we can conclude that several pathways were found to be altered in chemoresistant Capan-1 5-FU2000 cells. Moreover these alterations are most likely the consequence of a multistep adaption towards gradual cytotoxic exposure finally culminating in a chemoresistant phenotype. Interfering with these pathways may possibly reverse the phenotype and thus open up alternative treatment options. Image: Effect of 5-FU treatment on NfkB p65 phosphorylation in native and 5-FU resistant cells.
An automatic visible watermark removal technique using image inpainting algorithms

This paper introduces a technique to remove visible watermark automatically using image inpainting algorithms. The pending images which need watermark re-moval are assumed to have same resolution and watermark region and we will show this assumption is reasonable. Our proposed technique includes two basic step. The first step is detecting the watermark region, we propose a statistical method to detect the watermark region. Thresholding algorithm for segmentation proceeds at the accumulation image which is calculated by accumulation of the gray-scale maps of pending images. The second step is removing the watermark using image inpainting algorithms. Since watermarks are usually with large re-gion areas, an exemplar-based inpainting algorithm through investigating the sparsity of natural image patches is proposed for this step. Experiments were im-plemented in a test image set of 889 images downloaded from a shopping web-site with the resolution of 800∗800 and same watermark regions.
Integrative Modeling Identifies Key Determinants of Inhibitor Sensitivity in Breast Cancer Cell Lines.

Cancer cell lines differ greatly in their sensitivity to anticancer drugs as a result of different oncogenic drivers and drug resistance mechanisms operating in each cell line. Although many of these mechanisms have been discovered, it remains a challenge to understand how they interact to render an individual cell line sensitive or resistant to a particular drug. To better understand this variability, we profiled a panel of 30 breast cancer cell lines in the absence of drugs for their mutations, copy number aberrations, mRNA, protein expression and protein phosphorylation, and for response to seven different kinase inhibitors. We then constructed a knowledge-based, Bayesian computational model that integrates these data types and estimates the relative contribution of various drug sensitivity mechanisms. The resulting model of regulatory signaling explained the majority of the variability observed in drug response. The model also identified cell lines with an unexplained response, and for these we searched for novel explanatory factors. Among others, we found that 4E-BP1 protein expression, and not just the extent of phosphorylation, was a determinant of mTOR inhibitor sensitivity. We validated this finding experimentally and found that overexpression of 4E-BP1 in cell lines that normally possess low levels of this protein is sufficient to increase mTOR inhibitor sensitivity. Taken together, our work demonstrates that combining experimental characterization with integrative modeling can be used to systematically test and extend our understanding of the variability in anticancer drug response.Significance: By estimating how different oncogenic mutations and drug resistance mechanisms affect the response of cancer cells to kinase inhibitors, we can better understand and ultimately predict response to these anticancer drugs.Graphical Abstract: http://cancerres.aacrjournals. org/content/canres/78/15/4396/F1.large. jpg Cancer Res; 78(15); 4396-410. ©2018 AACR.
“Booze is the main factor that got me where I am today”: alcohol use and HIV risk for MSM in rural South Africa

ABSTRACT Excessive alcohol consumption has been shown to increase HIV risk for men who have sex with men (MSM) and compromise HIV prevention behaviors. However, there is limited contextual understanding of alcohol use for MSM in rural sub-Saharan African settings, which can inform and direct HIV interventions. Applying an adaptation of PhotoVoice, we worked with 35 HIV-positive MSM who created photo-essays about alcohol and HIV in Mpumalanga. A semi-structured protocol was used in focus group discussions that were audio-recorded, translated and transcribed. Transcript data and visual data of 24 photo-essays were analyzed using a constant comparison approach. We found that participants used alcohol to build and sustain social networks, meet sexual partners, and enhance sexual experience. Excessive alcohol use was common, which was associated with increased HIV risk behaviors within a community of MSM who maintained multiple partnerships. Our study suggests that HIV interventions need to address excessive alcohol use to mitigate the associated HIV risk at both the individual and community levels.
Charge-Depleting of the Batteries Makes Smartphones Recognizable

Many components of smartphones are used to generate device fingerprinting, such as screens, CPUs and various sensors. These device fingerprinting can be used to identify the smartphones. However, there are many restrictions with these device fingerprinting. Invariable information in screens and CPUs may lead to privacy risks. Moreover, strict experimental steps are required when fingerprinting the sensors. The effectiveness and effeciency of these device fingerprinting is reduced in practice. In this paper, we present a novel hardware fingerprinting based on the battery. Instead of relying on invariable information of the battery, we focus on the charge-depleting of the smartphone. The discrepencies on manufacturing of smartphones make that the charge-depleting is different when performs the same task. Moreover, charge-depleting information can easily be obtained without strict operating steps. We design a highly accurate algorithm to fingerprint the batteries which is based on the unsupervised learning. Besides, we stimulate the algorithm with different charge-depleting of tasks to improve the performance. We use 15 smartphones to evaluate the performance of the battery fingerprinting in both laboratory and public conditions. The experimental results show that battery fingerprinting is quite effective, the recognition accuracy rate can reach 86%.
Speech and language pathologists’ perceptions and practises of communication partner training to support children’s communication with high-tech speech generating devices

Abstract Purpose: This study examined speech and language pathologists’ (SLPs’) perceptions and practices of communication partner training with high-tech speech generating devices (SGDs). Method: Fifteen SLPs were recruited throughout Sweden. The SLPs answered a study-specific questionnaire on communication partner training in relation to communication partners to children with severe cerebral palsy and intellectual disability. The results were analysed with descriptive statistics (closed-ended questions, responses on Likert scales) and content analysis (open-ended question) using ICF-CY. Results: Twelve SLPs completed the survey. Half had no or one training session with communication partners in the last year. One-third never used documents for goal-setting. Half seldom or never taught communication partner strategies. Three quarters only used verbal instructions. The main obstacles were environmental factors. Conclusions: This study contributes valuable knowledge about high-tech SGD interventions targeting communication partners. The high-tech SGD intervention may benefit from goal-setting, extended number of training sessions and a range of instructional approaches. Implications for Rehabilitation Speech and language pathologist (SLPs) reported that children with severe cerebral palsy and intellectual disability (SSPI) can benefit from speech generating device (SGD) communication. Communication partner strategies and goal-setting supports the development of communication with SGD. SLPs seldom taught stakeholder communication partner strategies and instruments for goal-setting. Because stakeholders may vary in their way of learning SLPs need to use a variety of instructional approaches. SLPs used few instructional approaches, typically verbal information.
Neonatal Immunity, Respiratory Virus Infections, and the Development of Asthma

Infants are exposed to a wide range of potential pathogens in the first months of life. Although maternal antibodies acquired transplacentally protect full-term neonates from many systemic pathogens, infections at mucosal surfaces still occur with great frequency, causing significant morbidity and mortality. At least part of this elevated risk is attributable to the neonatal immune system that tends to favor T regulatory and Th2 type responses when microbes are first encountered. Early-life infection with respiratory viruses is of particular interest because such exposures can disrupt normal lung development and increase the risk of chronic respiratory conditions, such as asthma. The immunologic mechanisms that underlie neonatal host–virus interactions that contribute to the subsequent development of asthma have not yet been fully defined. The goals of this review are (1) to outline the differences between the neonatal and adult immune systems and (2) to present murine and human data that support the hypothesis that early-life interactions between the immune system and respiratory viruses can create a lung environment conducive to the development of asthma.
Binding, Thermodynamics, and Selectivity of a Non-peptide Antagonist to the Melanocortin-4 Receptor

The melanocortin-4 receptor (MC4R) is a potential drug target for treatment of obesity, anxiety, depression, and sexual dysfunction. Crystal structures for MC4R are not yet available, which has hindered successful structure-based drug design. Using microsecond-scale molecular-dynamics simulations, we have investigated selective binding of the non-peptide antagonist MCL0129 to a homology model of human MC4R (hMC4R). This approach revealed that, at the end of a multi-step binding process, MCL0129 spontaneously adopts a binding mode in which it blocks the agonistic-binding site. This binding mode was confirmed in subsequent metadynamics simulations, which gave an affinity for human hMC4R that matches the experimentally determined value. Extending our simulations of MCL0129 binding to hMC1R and hMC3R, we find that receptor subtype selectivity for hMC4R depends on few amino acids located in various structural elements of the receptor. These insights may support rational drug design targeting the melanocortin systems.
Topologies and Operating Principles of Basic Full‐Bridge Converters

High-frequency switching is one of the most important features of power electronics technology, enabling power electronics converters to meet the required specifications and performance. High-frequency power devices and components, including magnetic devices and capacitors, are the basic elements of high-frequency power electronics. Metal-oxide-semiconductor field-effect transistors (MOSFETs) and insulated-gate bipolar transistors (IGBTs) have become the dominant choices for the implementation of power switches, and MOSFETs with low gate charges and low junction capacitors further boost the development of high-frequency power electronics. Recently, there has been significant progress in the development of silicon carbide (SiC)-based power devices, including SiC diodes [1], SiC MOSFETs, and SiC IGBTs [2], and SiC-based commercial products have become strong competitors to Si-based fast-recovery diodes and MOSFETs in medium power conversion applications. Gallium nitride (GaN) power devices have drawn attention for achieving ultra-fast switching. Furthermore, recent progress in the development of amorphous, microcrystalline cores and high-frequency ferrites has been significant. Circuit topology is another important aspect of high-frequency power electronics. Switching losses in switching devices have been drastically reduced through the systematic development of resonant converters [3, 4], quasi-resonant converters [5], and multi-resonant converters [5, 6], zero-voltage-switching (ZVS) pulse-width modulation (PWM) and zero-current-switching (ZCS) PWM converters [7, 8],