Miracle-dz/UniFAR-FTUs huggingface dataset:
Current perspectives regarding the application and incorporation of silver nanoparticles into dental biomaterials

Introduction The key idea of nanotechnology is to construct and preserve functional structures by means of exploiting atoms and molecules. Nanotechnology has proven to be crucial in pharmacological medicine, tissue engineering, clinical diagnosis, long term conservation of biological tissues in a cryogenic state, protein detection, tumor destruction and magnetic resonance imaging. The aim of this paper is to review the literature on the specific characteristics of nanostructured materials, their applications and advantages that they bring to dentistry. Method We conducted an electronic scientific database research that included PubMed, Cochrane and Medline. The following keywords were used: nanotechnology, nanodentistry and silver nanoparticles. Initially 1650 original articles were retrieved from the these mentioned international databases, which were screened in detail. We included literature reviews that dealt with the comprehensive applications of nanostructured particles and silver nanoparticles in particular, in all fields of contemporary dentistry. Case reports, clinical trials, editorials and opinion letters were excluded in the first phase of our research. Fifty two articles met all the selection criteria and were ultimately selected and reviewed. Results Nanotechnology deals with the production of various types of nanomaterials with potential applications in the field of biomedicine. Silver nanoparticles have the capacity to eliminate dental caries producing bacteria or repair teeth enamel with signs of dental decay. Nanodentistry will allow better oral health by use of nanostructured materials. Treatment opportunities that nanotechnology has to offer in contemporary dentistry include local anesthesia, permanent treatment of dental hypersensitivity, orthodontic and oral health care with nanorobotic dentifrice. Conclusion The studies that we reviewed are largely in favor of nanotechnology and nanostructured materials, highlighting their qualities and enhancements they bring to the field of dentistry. Although many of these products that benefit from silver nanoparticles properties are still expensive and exclusive, we can foresee major improvements and demand regarding dental biomaterials with nanoparticles incorporated in the near future.
A combined approach with gene-wise normalization improves the analysis of RNA-seq data in human breast cancer subtypes

Breast cancer (BC) is increasing in incidence and resistance to treatment worldwide. The challenges in limited therapeutic options and poor survival outcomes in BC subtypes persist because of its molecular heterogeneity and resistance to standard endocrine therapy. Recently, high throughput RNA sequencing (RNA-seq) has been used to identify biomarkers of disease progression and signaling pathways that could be amenable to specific therapies according to the BC subtype. However, there is no single generally accepted pipeline for the analysis of RNA-seq data in biomarker discovery due, in part, to the needs of simultaneously satisfying constraints of sensitivity and specificity. We proposed a combined approach using gene-wise normalization, UQ-pgQ2, followed by a Wald test from DESeq2. Our approach improved the analysis based on within-group comparisons in terms of the specificity when applied to publicly available RNA-seq BC datasets. In terms of identifying differentially expressed genes (DEGs), we combined an optimized log2 fold change cutoff with a nominal false discovery rate of 0.05 to further minimize false positives. Using this method in the analysis of two GEO BC datasets, we identified 797 DEGs uniquely expressed in triple negative BC (TNBC) and significantly associated with T cell and immune-related signaling, contributing to the immunotherapeutic efficacy in TNBC patients. In contrast, we identified 1403 DEGs uniquely expressed in estrogen positive and HER2 negative BC (ER+HER2-BC) and significantly associated with eicosanoid, notching and FAK signaling while a common set of genes was associated with cellular growth and proliferation. Thus, our approach to control for false positives identified two distinct gene expression profiles associated with these two subtypes of BC which are distinguishable by their molecular and functional attributes.
Training Compact Neural Networks with Binary Weights and Low Precision Activations

In this paper, we propose to train a network with binary weights and low-bitwidth activations, designed especially for mobile devices with limited power consumption. Most previous works on quantizing CNNs uncritically assume the same architecture, though with reduced precision. However, we take the view that for best performance it is possible (and even likely) that a different architecture may be better suited to dealing with low precision weights and activations. Specifically, we propose a "network expansion" strategy in which we aggregate a set of homogeneous low-precision branches to implicitly reconstruct the full-precision intermediate feature maps. Moreover, we also propose a group-wise feature approximation strategy which is very flexible and highly accurate. Experiments on ImageNet classification tasks demonstrate the superior performance of the proposed model, named Group-Net, over various popular architectures. In particular, with binary weights and activations, we outperform the previous best binary neural network in terms of accuracy as well as saving more than 5 times computational complexity on ImageNet with ResNet-18 and ResNet-50.
Plant Identification with Deep Learning Ensembles

This work describes the plant identiﬁcation system that we submitted to the ExpertLifeCLEF plant identiﬁcation campaign in 2018. We ﬁne-tuned two pre-trained deep learning architectures (SeNet and DensNetwork) using images shared by the CLEF organizers in 2017. Our main runs are 4 ensembles obtained with diﬀerent weighted combinations of the 4 deep learning architectures. The ﬁfth ensemble is based on deep learning features but uses Error Correcting Output Codes (ECOC) as the ensemble. Our best system has achieved a classiﬁcation accuracy of 74.4%, while the best system obtained 86.7% accuracy, on the whole of the oﬃcial test data. This system ranked 4th place among all the teams, but matched the accuracy of one of the human experts.
Caenorhabditis elegans as an emerging model system in environmental epigenetics

The roundworm Caenorhabitis elegans has been an established model organism for the study of genetics and developmental biology, including studies of transcriptional regulation, since the 1970s. This model organism has continued to be used as a classical model system as the field of transcriptional regulation has expanded to include scientific advances in epigenetics and chromatin biology. In the last several decades, C. elegans has emerged as a powerful model for environmental toxicology, particularly for the study of chemical genotoxicity. Here, we outline the utility and applicability of C. elegans as a powerful model organism for mechanistic studies of environmental influences on the epigenome. Our goal in this article is to inform the field of environmental epigenetics of the strengths and limitations of the well‐established C. elegans model organism as an emerging model for medium‐throughput, in vivo exploration of the role of exogenous chemical stimuli in transcriptional regulation, developmental epigenetic reprogramming, and epigenetic memory and inheritance. As the field of environmental epigenetics matures, and research begins to map mechanisms underlying observed associations, new toolkits and model systems, particularly manipulable, scalable in vivo systems that accurately model human transcriptional regulatory circuits, will provide an essential experimental bridge between in vitro biochemical experiments and mammalian model systems. Environ. Mol. Mutagen. 59:560–575, 2018. © 2018 Wiley Periodicals, Inc.
Characteristics of Sinus Fungus Ball: A Unique Form of Rhinosinusitis

Objective: The purpose of this study was to investigate the characteristics of this unique form of rhinosinusitis. Methods: Ninety-one patients with sinus fungus balls were evaluated for clinical characteristics. Nasal tissues obtained from 38 patients with sinus fungus ball, along with 26 controls were used for histopathological, cytokines/chemokines, western blotting, and genetic analyses. Results: Patients with fungus balls had significantly more females and their age was older. The presentation of fungus ball was predominantly unilateral (97.8%). Thirty-three patients (36.3%) had risk factors for fungal infection. Macrophage and neutrophil dominated cellular infiltration was found in nasal tissues of fungus ball patients. A tendency of reduced tight junction staining (e-cadherin) and protein expression was found. Interleukin 8 (IL8) and granulocyte colony stimulating factor (G-CSF) significantly increased in sinus fungus ball tissue homogenates when compared with those from controls. Higher prevalence of a single single nucleotide polymorphism (SNP) with E-cadherin was found in the patients with fungus ball. Conclusions: We found that patients with sinus fungus ball had robust immune responses, allowing recruitment and activation of macrophages and neutrophils. However, patients with sinus fungus ball could have genetic or acquired weakness in immunity. The fungal hyphae were localized and accumulated within single sinus instead of being eradicated by host.
Lipid Droplets Breakdown: Adipose Triglyceride Lipase Leads the Way.

Previously in Current Protein & Peptide Science, Cerk et al. (2018) reported an updated review of concepts and knowledge regarding structure, function and regulatory mechanism of the adi-pose triglyceride lipase (ATGL), one of the key-enzyme required for intracellular lipolysis. Until recently, lipid droplets (LDs) were just considered as neutral lipid storage sites, thus providing energy through lipolysis and β-oxidation pathway when required during stressful conditions [1]. Nowadays, it is clearly established that LDs are well-organized and extremely dynamic cellular organelles, conserved in eubacteria, fungi, plants and animals plants and animals where they are essential for lipid homeostasis and energy maintenance [2]. Alteration of these two critical physiological processes can lead to important metabolic disorders [3]. The " conventional snapshot representation " of LDs remains a suitable model for defining their general composition which is based on a central organic core of neutral lipids (mainly triacylglycerol (TAG) and sterol esters) surrounded by a phospholipid monolayer [4], associated with a wide range of structural [5], enzymatic [6] and membrane-trafficking proteins [7]. However, we also know that proteins and lipid species of such structures can be extremely diversified depending on the different cell types or metabolic status. Interestingly, LDs anabolism and catabo-lism are well-balanced, and tightly-controlled biological mechanisms involving a large number of actors at both tran-scriptional, translational and post-translational levels [8]. TAG-containing LDs breakdown is achieved during extended starvation period or enhanced energy demand, and this phenomenon is mainly mediated by three distinct lipolytic enzymes (i.e., the adipose triglyceride lipase (ATGL), the hormone-sensitive lipase (HSL) and the mono-glyceride lipase (MGL)) that act sequentially to finally generate free fatty acids (FFA) and glycerol molecules [8]. Since ATGL catalyzes the first step of this essential lipolytic pathway , it is thus crucial to fully define the physiological func-tion(s) and structural properties of this protein, but also to get insights onto the regulatory mechanisms governing ATGL action towards LDs [9].
ELiRF-UPV at MultiStanceCat 2018

This paper describes the participation of ELiRF-UPV team at the Spanish subtasks of the MultiModal Stance Detection in tweets on Catalan #1Oct Referendum workshop. Our best approach is based on Convolutional Neural Networks using word embeddings and polarity/emotion lexicons. We obtained competitive results on the Spanish subtask using only the text of the tweet, dispensing with contexts and images.
Introduction and validation of the Natural Disasters Picture System (NDPS)

Given the growing demand for studies dealing with natural disasters, the research fields of emotion and social cognition require validated picture stimuli of natural hazards. Such material is essential for studying perceptual processes and behaviors of exposed individuals, and it could find practical applications, such as the improvement of communication strategies during crises. We present the Natural Disasters Picture System (NDPS), a database of pictures of natural hazards, with an emphasis on volcanic threats, and their impact on the environment and humans. We first describe in detail the picture selection and database creation. We then report the validation procedure. One hundred twenty participants rated the pictures on the basis of four dimensions: valence, arousal, dominance and certainty. For each picture, we ultimately determined the best-fitting emotion on the basis of its dimensional pattern. The Hierarchical Ascendant Classification, which yielded 4 clusters subdivided into 9 classes, indicated a highly consistent and distinctive classification of the pictures. Overall, 90% of the pictures elicited negative emotions (fear or sadness), and the other 10% induced neutral to positive emotions (e.g., aesthetic emotions). The NDPS offers a new tool for studying natural events and disasters in the field of affective and cognitive sciences, which will benefit from scientific research and its practical applications. The NDPS is unrestrictedly accessible for researchers.
Patient-reported outcomes in a phase II study of alectinib

The ALK fusion gene, NPM-ALK , was originally identified in a case of anaplastic large cell lymphoma in 1994, and the EML4 -ALK fusion gene was discovered in non-small cell lung cancer (NSCLC) by Drs Soda and Mano in 2007.1 2 This was the first report of identification of a fusion gene in NSCLC. The incidence, according to this first report, of EML4-ALK fusion gene in NSCLC is 6.7%. 2 EML4-ALK encodes a transforming fusion kinase, which is a promising therapeutic target for ALK fusion gene-positive (hereinafter ALK-positive) NSCLC. Several fusion partners for ALK other than EML4 , such as KIF5B , TFG and KCL1 , have also been reported in NSCLC.3 ALK fusion genes have also been detected in several solid tumours other than NSCLC, such as renal cell carcinoma, colon cancer, breast cancer, ovarian cancer, pancreas cancer and inflammatory myofibroblastic tumours,3 4 and ALK inhibitors have been shown to be effective for these cancers also harbouring the fusion gene, similar to the case for EML4-ALK- positive NSCLC.4 5 Crizotinib is the first ALK inhibitor that was initially developed as a MET inhibitor and is also known as an ROS inhibitor.6 The phase III PROFILE 1014 trial was conducted to comparatively evaluate the safety and efficacy of crizotinib as a first-line treatment agent for patients with ALK-positive NSCLC.7 Progression-free survival (PFS) was significantly longer in the crizotinib arm than in the conventional chemotherapy arm …
SITIS-ISPED in CLEF eHealth 2018 Task 1 : ICD10 coding using Deep Learning

This paper presents SITIS-ISPED’s participation in the Task 1 : Multilingual Information Extraction ICD10 coding of the CLEF eHealth 2018 challenge which focuses on extraction of causes of death from a corpus of death reports. We used OpenNMT, a deep learning framework specialized in sequence-to-sequence models. An encoder-decoder model with attention transformed diagnostics into ICD10 codes. Our system obtained F-scores of 0.4368 for the raw corpus and 0.5385 for the aligned corpus.
Overview of the Task on Automatic Misogyny Identification at IberEval 2018

Automatic Misogyny Identiﬁcation (AMI) is a new shared task proposed for the ﬁrst time at the IberEval 2018 evaluation campaign. The AMI task proposes misogyny identiﬁcation, misogynistic behaviour categorization and target classiﬁcation both from Spanish and English tweets. We have received a total of 32 runs for English and 24 for Spanish, submitted by 11 diﬀerent teams from 5 countries. We present here the datasets, the evaluation methodology, an overview of the proposed systems and the obtained results. Finally, we draw some conclusions and discuss future work.
Electronic Medical Alerts Increase Screening for Chronic Hepatitis B: A Randomized, Double-Blind, Controlled Trial

Background: Implementation of screening recommendations for chronic hepatitis B (CHB) among foreign-born persons at risk has been sub-optimal. The use of alerts and reminders in the electronic health record (EHR) has led to increased screening for other common conditions. The aim of our study was to measure the effectiveness of an EHR alert on the implementation of hepatitis B surface antigen (HBsAg) screening of foreign-born Asian and Pacific Islander (API) patients. Methods: We used a novel technique to identify API patients by self-identified ethnicity, surname, country of origin, and language preference, and who had no record of CHB screening with HBsAg within the EHR. Patients with Medicare and/or Medicaid insurance were excluded due to lack of coverage for routine HBsAg screening at the time of this study. At-risk API patients were randomized to alert activation in their EHR or not (control). Results: A total of 2,987 patients met inclusion criteria and were randomized to the alert (n = 1,484) or control group (n = 1,503). In the alert group, 119 patients were tested for HBsAg, compared with 48 in the control group (odds ratio, 2.64; 95% confidence interval, 1.88–3.73; P < 0.001). In the alert group, 4 of 119 (3.4%) tested HBsAg-positive compared with 5 of 48 (10.4%) in the control group (P = 0.12). Conclusions: An EHR alert significantly increased HBsAg testing among foreign-born APIs. Impact: Utilization of EHR alerts has the potential to improve implementation of hepatitis B–screening guidelines. Cancer Epidemiol Biomarkers Prev; 27(11); 1352–7. ©2018 AACR.
Cellular Cytotoxicity of Next-Generation CD20 Monoclonal Antibodies

Primary tumor cells from CLL patients were used to compare the efficacy of ADCP and ADCC induced by different CD20-targeting monoclonal antibodies. Results highlight the use of ADCP assays as a better measure of monoclonal antibody-induced cellular cytotoxicity. CD20 monoclonal antibodies (CD20 mAb) induce cellular cytotoxicity, which is traditionally measured by antibody-dependent cellular cytotoxicity (ADCC) assays. However, data suggest that antibody-dependent cellular phagocytosis (ADCP) is the primary cytotoxic mechanism. We directly compared in vitro ADCP versus ADCC using primary human cells. After establishing the primacy of ADCP, we examined next-generation CD20 mAbs, including clinically relevant drug combinations for their effects on ADCP. ADCP and ADCC induction by rituximab, ofatumumab, obinutuzumab, or ocaratuzumab was measured using treatment-naïve chronic lymphocytic leukemia (CLL) target cells and either human monocyte-derived macrophages (for ADCP) or natural killer (NK) cells (for ADCC). Specific effects on ADCP were evaluated for clinically relevant drug combinations using BTK inhibitors (ibrutinib and acalabrutinib), PI3Kδ inhibitors (idelalisib, ACP-319, and umbralisib), and the BCL2 inhibitor venetoclax. ADCP (∼0.5–3 targets/macrophage) was >10-fold more cytotoxic than ADCC (∼0.04–0.1 targets/NK cell). ADCC did not correlate with ADCP. Next-generation mAbs ocaratuzumab and ofatumumab induced ADCP at 10-fold lower concentrations than rituximab. Ofatumumab, selected for enhanced complement activation, significantly increased ADCP in the presence of complement. CD20 mAb-induced ADCP was not inhibited by venetoclax and was less inhibited by acalabrutinib versus ibrutinib and umbralisib versus idelalisib. Overall, ADCP was a better measure of clinically relevant mAb-induced cellular cytotoxicity, and next-generation mAbs could activate ADCP at significantly lower concentrations, suggesting the need to test a wide range of dose sizes and intervals to establish optimal therapeutic regimens. Complement activation by mAbs can contribute to ADCP, and venetoclax, acalabrutinib, and umbralisib are preferred candidates for multidrug therapeutic regimens. Cancer Immunol Res; 6(10); 1150–60. ©2018 AACR.
Efficacy and tolerability of a house dust mite allergoid in allergic bronchial asthma: a randomized dose-ranging trial.

AIM This multicenter randomized placebo-controlled double-blind clinical trial investigated which maintenance dose shows the optimal benefit-risk ratio for subcutaneous immunotherapy with a Dermatophagoides pteronyssinus allergoid preparation. OBJECTIVE To evaluate four maintenance doses of the allergoid preparation versus placebo. METHODS The late-phase reaction of the intracutaneous test was chosen as efficacy parameter and minimal dose of fluticasone required for asthma control. RESULTS A total of 146 adults with bronchial asthma were randomized. After subcutaneous immunotherapy, reductions in swelling size were greatest with 10,000 therapeutic units (TU). The 18,000 TU group showed the highest percentage of patients with fluticasone dose reduced to 0 μg/day. CONCLUSION The optimal dose of allergoid for the investigation in a confirmatory trial with inhaled corticosteroid reduction is 18,000 TU.
CLEF MC2 2018 Lab Technical Overview of Cross Language Microblog Search and Argumentative Mining

MC2 lab mainly focuses on developing processing methods and resources to mine the social media (SM) spheres surrounding cultural events such as festivals, music, books, movies and museums. Two main tasks and one pilot ran in 2018. The first task was specific to movies. Topics were extracted from the French VodKaster website that allows readers to get personal short comments (microcritics) about movies. The challenge was to find related microblogs in four different languages in a large archive. The second task, argumentation mining, aimed to automatically identify reason-conclusion structures that can lead to model social web users positions about a cultural event expressed via Twitter microblogs. The idea was to perform a search process on a massive microblog collection that focuses on claims about a given festival. A pilot task was also launched on a new corpus, extending the 2017 language recognition task to handle also dialects.
Delineating inflammatory bowel disease through transcriptomic studies: current review of progress and evidence

Inflammatory bowel disease (IBD), which comprises of Crohn's disease and ulcerative colitis, is an idiopathic relapsing and remitting disease in which the interplay of different environment, microbial, immunological and genetic factors that attribute to the progression of the disease. Numerous studies have been conducted in multiple aspects including clinical, endoscopy and histopathology for the diagnostics and treatment of IBD. However, the molecular mechanism underlying the aetiology and pathogenesis of IBD is still poorly understood. This review tries to critically assess the scientific evidence at the transcriptomic level as it would help in the discovery of RNA molecules in tissues or serum between the healthy and diseased or different IBD subtypes. These molecular signatures could potentially serve as a reliable diagnostic or prognostic biomarker. Researchers have also embarked on the study of transcriptome to be utilized in targeted therapy. We focus on the evaluation and discussion related to the publications reporting the different approaches and techniques used in investigating the transcriptomic changes in IBD with the intention to offer new perspectives to the landscape of the disease.