bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nozzle-free droplet generation with focused acoustic beams for encapsulation of single circulating tumor cells
Authors: Li Rui , Gong Zhiyi , Wu Zezheng , Chen Hui , Xia Yu , Liu Yichao , Wang Fubing , Guo Shishang 
Published: October 2020

Abstract
The recovery of single circulating tumor cells (CTCs) from the peripheral blood of cancer patients has great potential for the study of cell heterogeneity and cancer metastasis and the development of personalized cancer immunotherapy. Here we present nozzleless droplet generation with focused acoustic beams for cell encapsulation. The mechanism of droplet generation is sensitive to the pulse width and the droplet diameter ranges from 350 to 550 μm. The pulse width duration (520 μs) and cell concentration (5 × 103 cells ml−1) can be adjusted to obtain the maximum probability (11.61%) of single cell encapsulation. Three-color fluorescence is used to identify encapsulated cells in the droplet and target cells are extracted by microcapillarity for conducting single cell analysis. The reported method of using acoustic tweezers to eject the droplet has advantages of convenience, speed and biocompatibility while being non-invasive, and could become a powerful tool for encapsulating single CTCs.
Carbon dots-based nanocarrier system with intrinsic tumor targeting ability for cancer treatment
Authors: Yang Xiaojing , Wang Yingying , Du Xiangfu , Xu Jingjing , Zhao Mei-Xia 
Published: October 2020

Abstract
Doxorubicin (DOX) is a traditional broad-spectrum antitumor drug, which has a wide range of clinical applications, but has no tumor non-specificity. Nanoparticles have been explored as drug delivery agents to enhance the therapeutic efficacy and reduce toxic and side effects. Carbon dots (CDs), a carbon-based nanomaterial, has many unique advantages such as easy synthesis, good biocompatibility, and low toxicity. In this study, folic acid was used as raw material to prepare new CDs, and DOX was loaded on the surface of CDs through electrostatic interaction. The prepared nano-drugs CDs/DOX could effectively release DOX under mild acidic pH stimulation. Cell imaging showed that CDs/DOX could transport doxorubicin (DOX) to cancer cells and make them accumulated in nucleus freely. Flow cytometry tests and cellular toxicity assay together confirmed that CDs/DOX could target tumor cells with high expression of folate receptor and increase anti-tumor activity. The therapeutic effect on 4T1 tumor-bearing mice model indicated that CDs/DOX could alleviate DOX-induced toxicity, effectively inhibit tumor growth, and prolong the survival time. Hence, such a targeting nanocarrier is likely to be a candidate for cancer treatment.
Perching Behavior by Dung Beetles (Coleoptera: Scarabaeidae): A Spatial Segregation Mechanism to Dilute Interspecific Competition in Highly Rich Assemblages?
Authors: Noriega Jorge Ari , Vulinec Kevina 
Published: October 2020

AbstractSit-and-wait is a common strategy to optimize time and energy devoted to foraging activities. Among Coleoptera, dung beetles are one of the groups that display this behavior. Although diverse aspects of natural history have been reviewed, no agreement exists on which theory may explain this food searching tactic. We performed a systematic literature review about this behavior in dung beetles, analyzing existing studies, and discussing potential explanations. We identified six different hypotheses (resource partitioning, food detection, foraging time, predator’s avoidance, thermoregulation, and resting). Based on the evidence that we found, we support the hypothesis that the main driver of perching behavior is a strategy of spatial segregation. We found reports for several tribes in different biogeographical regions, especially in Neotropical forests. Few studies explore the relationship between perching height and dung beetles’ size. However, recent findings sustained that dung beetles perch at a height proportional to its size, large beetles prefer bigger leaves, and functional groups perch at different heights. Dung beetles observed perching were strictly coprophagous and there is no specific relationship between dial activity and perching behavior. We also found perching records of the three main functional guilds (tunnelers, rollers, and dwellers). Despite several studies of dung beetles perching, there is a lack of experimental analyses. One aspect to analyze in future investigations is the relationship between perching behavior and functional traits. Finally, it is essential to explore and solve some questions that we propose to understand the functional role of this behavior in the structure of assemblages.
Pathologists at the Leading Edge of Optimizing the Tumor Tissue Journey for Diagnostic Accuracy and Molecular Testing
Authors: De Las Casas Luis E , Hicks David G 
Published: October 2020

Abstract

Objectives
Tumor biomarker analyses accompanying immuno-oncology therapies are coupled with a tumor tissue journey aiming to guide tissue procurement and allow for accurate diagnosis and delivery of test results. The engagement of pathologists in the tumor tissue journey is essential because they are able to link the preanalytic requirements of this process with pathologic evaluation and clinical information, ultimately influencing treatment decisions for patients with cancer. The aim of this review is to provide suggestions on how cancer diagnosis and the delivery of molecular test results may be optimized, based on the needs and available resources of institutions, by placing the tumor tissue journey under the leadership of pathologists.

Methods
Literature searches on PubMed and personal experience provided the necessary material to satisfy the objectives of this review.

Results
Pathologists are usually involved across many steps of the tumor tissue journey and have the requisite knowledge to ensure its efficiency.

Conclusions
The expansion of oncology diagnostic testing emphasizes the need for pathologists to acquire a leadership role in the multidisciplinary effort to optimize the accuracy, completeness, and delivery of diagnoses guiding personalized treatments.
NetCoMi: network construction and comparison for microbiome data in R
Authors: Peschel Stefanie , Müller Christian L , von Mutius Erika , Boulesteix Anne-Laure , Depner Martin 
Published: October 2020

AbstractMotivationEstimating microbial association networks from high-throughput sequencing data is a common exploratory data analysis approach aiming at understanding the complex interplay of microbial communities in their natural habitat. Statistical network estimation workflows comprise several analysis steps, including methods for zero handling, data normalization and computing microbial associations. Since microbial interactions are likely to change between conditions, e.g. between healthy individuals and patients, identifying network differences between groups is often an integral secondary analysis step. Thus far, however, no unifying computational tool is available that facilitates the whole analysis workflow of constructing, analysing and comparing microbial association networks from high-throughput sequencing data.ResultsHere, we introduce NetCoMi (Network Construction and comparison for Microbiome data), an R package that integrates existing methods for each analysis step in a single reproducible computational workflow. The package offers functionality for constructing and analysing single microbial association networks as well as quantifying network differences. This enables insights into whether single taxa, groups of taxa or the overall network structure change between groups. NetCoMi also contains functionality for constructing differential networks, thus allowing to assess whether single pairs of taxa are differentially associated between two groups. Furthermore, NetCoMi facilitates the construction and analysis of dissimilarity networks of microbiome samples, enabling a high-level graphical summary of the heterogeneity of an entire microbiome sample collection. We illustrate NetCoMi’s wide applicability using data sets from the GABRIELA study to compare microbial associations in settled dust from children’s rooms between samples from two study centers (Ulm and Munich).AvailabilityR scripts used for producing the examples shown in this manuscript are provided as supplementary data. The NetCoMi package, together with a tutorial, is available at https://github.com/stefpeschel/NetCoMi.ContactTel:+49 89 3187 43258; stefanie.peschel@mail.deSupplementary informationSupplementary data are available at Briefings in Bioinformatics online.
MolTrans: Molecular Interaction Transformer for drug–target interaction prediction
Authors: Huang Kexin , Xiao Cao , Glass Lucas M , Sun Jimeng 
Published: October 2020

Abstract

Motivation
Drug–target interaction (DTI) prediction is a foundational task for in-silico drug discovery, which is costly and time-consuming due to the need of experimental search over large drug compound space. Recent years have witnessed promising progress for deep learning in DTI predictions. However, the following challenges are still open: (i) existing molecular representation learning approaches ignore the sub-structural nature of DTI, thus produce results that are less accurate and difficult to explain and (ii) existing methods focus on limited labeled data while ignoring the value of massive unlabeled molecular data.

Results
We propose a Molecular Interaction Transformer (MolTrans) to address these limitations via: (i) knowledge inspired sub-structural pattern mining algorithm and interaction modeling module for more accurate and interpretable DTI prediction and (ii) an augmented transformer encoder to better extract and capture the semantic relations among sub-structures extracted from massive unlabeled biomedical data. We evaluate MolTrans on real-world data and show it improved DTI prediction performance compared to state-of-the-art baselines.

Availability and implementation
The model scripts are available at https://github.com/kexinhuang12345/moltrans.

Supplementary information
Supplementary data are available at Bioinformatics online.
The effect of statistical normalization on network propagation scores
Authors: Picart-Armada Sergio , Thompson Wesley K , Buil Alfonso , Perera-Lluna Alexandre 
Published: October 2020

Abstract

Motivation
Network diffusion and label propagation are fundamental tools in computational biology, with applications like gene–disease association, protein function prediction and module discovery. More recently, several publications have introduced a permutation analysis after the propagation process, due to concerns that network topology can bias diffusion scores. This opens the question of the statistical properties and the presence of bias of such diffusion processes in each of its applications. In this work, we characterized some common null models behind the permutation analysis and the statistical properties of the diffusion scores. We benchmarked seven diffusion scores on three case studies: synthetic signals on a yeast interactome, simulated differential gene expression on a protein–protein interaction network and prospective gene set prediction on another interaction network. For clarity, all the datasets were based on binary labels, but we also present theoretical results for quantitative labels.

Results
Diffusion scores starting from binary labels were affected by the label codification and exhibited a problem-dependent topological bias that could be removed by the statistical normalization. Parametric and non-parametric normalization addressed both points by being codification-independent and by equalizing the bias. We identified and quantified two sources of bias—mean value and variance—that yielded performance differences when normalizing the scores. We provided closed formulae for both and showed how the null covariance is related to the spectral properties of the graph. Despite none of the proposed scores systematically outperformed the others, normalization was preferred when the sought positive labels were not aligned with the bias. We conclude that the decision on bias removal should be problem and data-driven, i.e. based on a quantitative analysis of the bias and its relation to the positive entities.

Availability
The code is publicly available at https://github.com/b2slab/diffuBench and the data underlying this article are available at https://github.com/b2slab/retroData

Supplementary information
Supplementary data are available at Bioinformatics online.
Integrative analysis of multi-omics data for discovering low-frequency variants associated with low-density lipoprotein cholesterol levels
Authors: Yang Tianzhong , Wei Peng , Pan Wei 
Published: October 2020

Abstract

Motivation
The abundance of omics data has facilitated integrative analyses of single and multiple molecular layers with genome-wide association studies focusing on common variants. Built on its successes, we propose a general analysis framework to leverage multi-omics data with sequencing data to improve the statistical power of discovering new associations and understanding of the disease susceptibility due to low-frequency variants. The proposed test features its robustness to model misspecification, high power across a wide range of scenarios and the potential of offering insights into the underlying genetic architecture and disease mechanisms.

Results
Using the Framingham Heart Study data, we show that low-frequency variants are predictive of DNA methylation, even after conditioning on the nearby common variants. In addition, DNA methylation and gene expression provide complementary information to functional genomics. In the Avon Longitudinal Study of Parents and Children with a sample size of 1497, one gene CLPTM1 is identified to be associated with low-density lipoprotein cholesterol levels by the proposed powerful adaptive gene-based test integrating information from gene expression, methylation and enhancer–promoter interactions. It is further replicated in the TwinsUK study with 1706 samples. The signal is driven by both low-frequency and common variants.

Availability and implementation
Models are available at https://github.com/ytzhong/DNAm.

Supplementary information
Supplementary data are available at Bioinformatics online.
CSF tau microtubule binding region identifies tau tangle and clinical stages of Alzheimer’s disease
Authors: Horie Kanta , Barthélemy Nicolas R , Sato Chihiro , Bateman Randall J 
Published: October 2020

Abstract
Tau is a microtubule associated protein in the brain that aggregates in Alzheimer’s disease to form pathological tangles and neurites. Insoluble tau aggregates composed of the microtubule binding region (MTBR) of tau are highly associated with the cognitive and clinical symptoms of Alzheimer’s disease. In contrast, levels of soluble forms of tau, such as CSF total tau and phosphorylated tau-181 and tau-217, increase prior to tau aggregation in Alzheimer’s disease, but these biomarkers do not measure the MTBR of tau. Thus, how CSF MTBR-tau is altered in Alzheimer’s disease remains unclear. In this study, we used sequential immunoprecipitation and chemical extraction methods followed by mass spectrometry to analyse MTBR-tau species in Alzheimer’s disease and control CSF. We quantified MTBR-tau-specific regions in the CSF and identified that species containing the region beginning at residue 243 were the most highly correlated with tau PET and cognitive measures. This finding suggests that CSF level of tau species containing the upstream region of MTBR may reflect changes in tau pathology that occur in Alzheimer’s disease and could serve as biomarkers to stage Alzheimer’s disease and track the development of tau-directed therapeutics.
A Behavioral and Electrophysiological Investigation of Effects of Visual Congruence on Olfactory Sensitivity During Habituation to Prolonged Odors
Authors: Fallon Nicholas , Giesbrecht Timo , Thomas Anna , Stancak Andrej 
Published: October 2020

Abstract
Congruent visual cues augment sensitivity to brief olfactory presentations and habituation of odor perception is modulated by central-cognitive processing including context. However, it is not known whether habituation to odors could interact with cross-modal congruent stimuli. The present research investigated the effect of visual congruence on odor detection sensitivity during continuous odor exposures. We utilized a multimethod approach, including subjective behavioral responses and reaction times (RTs; study 1) and electroencephalography (EEG, study 2). Study 1: 25 participants received 2-min presentations of moderate-intensity floral odor delivered via olfactometer with congruent (flower) and incongruent (object) image presentations. Participants indicated odor perception after each image. Detection sensitivity and RTs were analyzed in epochs covering the period of habituation. Study 2: 25 new participants underwent EEG recordings during 145-s blocks of odor presentations with congruent or incongruent images. Participants passively observed images and intermittently rated the perceived intensity of odor. Event-related potential analysis was utilized to evaluate brain processing related to odor–visual pairs across the period of habituation. Odor detection sensitivity and RTs were improved by congruent visual cues. Results highlighted a diminishing influence of visual congruence on odor detection sensitivity as habituation occurred. Event-related potential analysis revealed an effect of congruency on electrophysiological processing in the N400 component. This was only evident in early periods of odor exposure when perception was strong. For the first time, this demonstrates the modulation of central processing of odor–visual pairs by habituation. Frontal negativity (N400) responses encode the aspects of cross-modal congruence for odor–vision cross-modal tasks.
Interferon-γ Release Assay for Accurate Detection of Severe Acute Respiratory Syndrome Coronavirus 2 T-Cell Response
Authors: Murugesan Kanagavel , Jagannathan Prasanna , Pham Tho D , Pandey Suchitra , Bonilla Hector F , Jacobson Karen , Parsonnet Julie , Andrews Jason R , Weiskopf Daniela , Sette Alessandro , Pinsky Benjamin A , Singh Upinder , Banaei Niaz 
Published: October 2020

Abstract
We investigated feasibility and accuracy of an interferon-γ release assay (IGRA) for detection of T-cell responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Whole blood IGRA accurately distinguished between convalescent and uninfected healthy blood donors with a predominantly CD4+ T-cell response. SARS-CoV-2 IGRA may serve as a useful diagnostic tool in managing the coronavirus disease 2019 pandemic.
A Novel Approach for Determining Meal Plan for Gestational Diabetes Mellitus Using Artificial Intelligence
Authors: Huynh Hieu Trung , Hoang Tran Minh 
Published: October 2020

Abstract
Estimating energy expenditure and meal plan plays important roles in the treatment of gestational diabetes mellitus, which is defined as any degree of glucose intolerance with onset or first recognition during pregnancy. Some approaches have been proposed; however, they have limitations including high cost, relative complexity, trained personnel requirements or locality. In this study, we propose an approach for estimating the energy expenditure and meal plan by using artificial intelligence. The proposed approach consists of three main stages including energy expenditure estimation, macronutrient intake estimation and meal plan determination. The neural network is used to estimate the energy expenditure, and then the meal plan is determined by using the genetic algorithm (GA), which is a popular method for solving optimization problems based on natural selection and genetics. The fitness function with penalty was used in GA to deal with constraint problems. The proposed method can obtain the root mean square error and mean absolute percentage error of 15.23 ± 7.4 kcal and 1 ± 0.8%, respectively. The Pearson correlation coefficient, which measures the strength of the association between the two measurements, was 0.99. In meal plan determination, the results from GA agreed with those from nutritionists. The Pearson correlation coefficient was 0.95. The energy expenditure and meal plan are determined by soft computing with flexible ways. They can adapt to particular regions or group of patients.
BLINDED BY THE LIES? Toward an integrated definition of conspiracy theories
Authors: Baden Christian , Sharon Tzlil 
Published: October 2020

AbstractDespite widespread concern over the alleged rise of conspiracy theories, scholars continue to disagree whether it is possible to distinguish specific kinds of conspiracist accounts that can justifiably be denounced as objectionable. In this article, we review scholarship from multiple disciplines to develop a composite definition of “conspiracy theories proper” (CTP) that violate fundamental norms of democratic discourse. Besides referring to grand conspiracies to account for social phenomena, we argue, such conspiracy theories: (a) assume conspirators’ pervasive control over events and information, (b) construct dissent as a Manichean binary, and (c) employ an elusive, dogmatic epistemology. We discuss the operational potential and limitations of our definition using news user talkbacks on the U.S., British and German online editions of Russia Today (RT), a popular platform among proponents of out-of-mainstream political views. Identifying key operational challenges in the classification of natural discourse, we sketch avenues toward a more rigorous study of contentious political talk.
Omega-3 fatty acids improve flow-induced vasodilation by enhancing TRPV4 in arteries from diet-induced obese mice
Authors: Zhu Yifei , Wen Lei , Wang Sheng , Zhang Ka , Cui Yue , Zhang Chi , Feng Lei , Yu Fan , Chen Yongquan , Wang Ruxing , Ma Xin 
Published: October 2020

AbstractAimsPrevious studies have shown the intake of omega-3 polyunsaturated fatty acids is associated with low rates of obesity and ischaemic pathologies. Omega-3 also have anti-inflammatory and plaque-stabilization effects and regulate vasodilation and constriction. However, there are few studies of the role of omega-3 in flow-induced vasodilation involving Ca2+-permeable ion channel TRPV4 in high-fat diet-induced obese (DIO) mouse. Here, we determined whether omega-3 protect against vascular dysfunction induced by a high-fat diet by enhancing TRPV4 activity and subsequently improving flow-mediated vasodilation.Methods and resultsFlow-mediated vasodilation in second-order mesenteric arteries from mice was measured using a pressure myograph. The intracellular Ca2+ concentration in response to flow and GSK1016790A (a TRPV4 agonist) was measured by Fluo-4 fluorescence. Whole-cell current was measured by patch clamp. Cell membrane tether force was measured by atomic force microscopy. Impairment of flow-mediated vasodilation in arteries and Ca2+ influx in endothelial cells from DIO mice was restored by omega-3 treatment. The improved flow-induced vasodilation was inhibited by the TRPV4 antagonist HC067047 and in TRPV4−/− mice. Omega-3 treatment enhanced endothelial TRPV4 activity and altered cell membrane mechanic property, as indicated by enhanced GSK1016790A-induced Ca2+ influx and whole-cell current and altered membrane mean tether force in endothelial cells from DIO mice.ConclusionOmega-3 improve vascular function by improving flow-induced vasodilation via enhancing TRPV4 activity in the endothelium of obese mice which may be related to improved cell membrane physical property. Activation of TRPV4 in endothelium plays an important role in the protective mechanisms of omega-3 against vascular dysfunction in obesity by improving flow-mediated vasodilation.