bluuebunny/crossref_metadata_2025 huggingface dataset:
Computer-aided SPT-based reliability model for probability of liquefaction using hybrid PSO and GA
Authors: Goharzay Maral , Noorzad Ali , Ardakani Ahmadreza Mahboubi , Jalal Mostafa
Published: February 2020

In this paper, an approach for soil liquefaction evaluation using probabilistic method based on the world-wide SPT databases has been presented. In this respect, the parameters’ uncertainties for liquefaction probability have been taken into account. A calibrated mapping function is developed using Bayes’ theorem in order to capture the failure probabilities in the absence of the knowledge of parameter uncertainty. The probability models provide a simple, but also efficient decision-making tool in engineering design to quantitatively assess the liquefaction triggering thresholds. Within an extended framework of the first-order reliability method considering uncertainties, the reliability indices are determined through a well-performed meta-heuristic optimization algorithm called hybrid particle swarm optimization and genetic algorithm to find the most accurate liquefaction probabilities. Finally, the effects of the level of parameter uncertainty on liquefaction probability, as well as the quantification of the limit state model uncertainty in order to incorporate the correct model uncertainty, are investigated in the context of probabilistic reliability analysis. The results gained from the presented probabilistic model and the available models in the literature show the fact that the developed approach can be a robust tool for engineering design and analysis of liquefaction as a natural disaster.
Modeling and assessing cyber resilience of smart grid using Bayesian network-based approach: a system of systems problem
Authors: Ibne Hossain Niamat Ullah , Nagahi Morteza , Jaradat Raed , Shah Chiranjibi , Buchanan Randy , Hamilton Michael
Published: February 2020

Due to the widespread of new technologies, the modern electric power system has become much more complex and uncertain. The Integration of technologies in the electric power system has increased the exposure of cyber threats and correlative susceptibilities from malicious cyber-attacks. To better address these cyber risks and minimize the effects of the power system outage, this research identifies the potential causes and mitigation techniques for the smart grid (SG) and assesses the overall cyber resilience of smart grid systems using a Bayesian network approach. Bayesian network is a powerful analytical tool predominantly used in risk, reliability, and resilience assessment under uncertainty. The quantification of the model is examined, and the results are analyzed through different advanced techniques such as predictive inference reasoning and sensitivity analysis. Different scenarios have been developed and analyzed to identify critical variables that are susceptible to the cyber resilience of a smart grid system of systems. Insight drawn from these analyses suggests that overall cyber resilience of the SG system of systems is dependent upon the status of identified factors, and more attention should be directed towards developing the countermeasures against access domain vulnerability. The research also shows the efficacy of a Bayesian network to assess and enhance the overall cyber resilience of the smart grid system of systems.
Identification of an Emergent Pathogen, Bartonella vinsonii, Using Next-Generation Sequencing in a Patient With Culture-Negative Endocarditis
Authors: Downey Rachel D , Russo Susan M , Hauger Sarmistha B , Murphey Donald K , Marx Grace , Huynh Thanhthao , Denison Amy M , Quirt Rachel , Bailey Ann , Fernandez Marisol
Published: February 2020

Diagnosis and treatment of culture negative endocarditis remains a challenge. This report describes a rare cause of endocarditis in humans, Bartonella vinsonii, identified through next generation sequencing of plasma microbial cell-free DNA with confirmation of cardiac valve tissue infection through immunohistochemical staining and polymerase chain reaction.
Inside the ‘Red Circle’: the production of China’s corporate legal elite
Authors: Zhu Jingqi , Zhao Yang , Liu Sida
Published: February 2020

This article examines the production of corporate legal elite through a systematic analysis of the profiles of the first three cohorts of partners in nine elite corporate law firms in Beijing. We argue that the social production of the Chinese corporate legal elite is primarily an outcome of domestic social factors rather than international factors. It is characterized by local elite recruitment from elite universities and endogenous elite circulation within the Red Circle firms. International credentials and work experience come only secondary to education and work experience in elite Chinese law schools and law firms for achieving elite status in the profession. Yet, international experience plays a role in promoting gender equality in elite professional service firms. This article contributes to the study of globalization and elite production in professional service firms by investigating how local and global forces manifest themselves in elite production in a major emerging market.
Thirty years after Jensen’s prediction: Is private equity a superior form of ownership?
Authors: Morris Peter , Phalippou Ludovic
Published: February 2020

Almost exactly 30 years ago, a famous article by Michael Jensen in the Harvard Business Review predicted that private equity would ‘eclipse’ the public corporation because it was a superior form of corporate ownership. Trends since 1989 seem to bear out Jensen’s prediction. Much time and energy has gone into studying whether the private equity model does see companies being run better for investors and society. Progress has been made and most studies find positive results. But samples are usually relatively small. And the relative complexity of private equity transactions, combined with a high level of privacy, makes it hard to find financial statements that are tractable enough for meaningful analysis. After 30 years of research, we argue that a conclusive answer to the question remains further away than might seem to be the case. In the meantime, the appropriate regulatory response involves narrowing the ‘regulatory gap’ between public and private markets.
Effectiveness of inactivated influenza vaccine in autoimmune rheumatic diseases treated with disease-modifying anti-rheumatic drugs
Authors: Nakafero Georgina , Grainge Matthew J , Myles Puja R , Mallen Christian D , Zhang Weiya , Doherty Michael , Nguyen-Van-Tam Jonathan S , Abhishek Abhishek
Published: February 2020

Objectives

The effectiveness of inactivated influenza vaccine in people with autoimmune rheumatic disease (AIRDs) is not known. We investigated whether the influenza vaccine is effective in preventing respiratory morbidity, mortality and all-cause mortality in AIRD patients.

Methods

Adults with AIRDs treated with DMARDs prior to 1 September of each year between 2006 and 2009, and 2010 and 2015 were identified from the Clinical Practice Research Datalink. Exposure and outcome data were extracted. Data from multiple seasons were pooled. Propensity score (PS) for vaccination was calculated. Cox-proportional hazard ratios (HRs) and 95% CIs were calculated, and were (i) adjusted, (ii) matched for PS for vaccination.

Results

Data for 30 788 AIRD patients (65.7% female, 75.5% with RA, 61.1% prescribed MTX) contributing 125 034 influenza cycles were included. Vaccination reduced risk of influenza-like illness [adjusted HR (aHR) 0.70], hospitalization for pneumonia (aHR 0.61) and chronic obstructive pulmonary disease exacerbations (aHR 0.67), and death due to pneumonia (aHR 0.56) on PS-adjusted analysis in the influenza active periods (IAPs). The associations were of similar magnitude and remained statistically significant on PS-matched analysis except for protection from influenza-like illness, which became non-significant. Sub-analysis restricted to pre-IAP, IAP and post-IAP did not yield evidence of residual confounding on influenza-like illness and death due to pneumonia. Vaccination reduced risk of all-cause mortality, although IAP-restricted analysis demonstrated residual confounding for this outcome.

Conclusion

Influenza vaccine associates with reduced risk of respiratory morbidity and mortality in people with AIRDs. These findings call for active promotion of seasonal influenza vaccination in immunosuppressed people with AIRDs by healthcare professionals.
House dust mite-specific immunotherapy alters the natural course of atopic march
Authors: Tang Ren-Bin
Published: February 2020

Allergen immunotherapy (AIT) is an effective treatment for patients with allergic diseases; it has been shown to modify the underlying cause of the disease. The house dust mite (HDM) is a major perennial allergen source and a significant cause of allergic-related diseases such as allergic rhinitis, asthma, and atopic dermatitis. HDM allergen is an important factor in the pathogenesis of allergic diseases. Sensitization to HDM allergen often occurs early in life and appears to play an important role in the progression from allergic rhinitis to asthma in children. The role of HDM AIT results in immunologic tolerance, provides an alternative option for treating HDM allergy through targeting the mechanisms of allergic reaction, and creates a long-term benefit. There are two forms of testing for aeroallergen, either detect by skin testing or by in vitro IgE assays. Both subcutaneous immunotherapy and sublingual immunotherapy are effective in the treatment of allergic diseases. In the future, new forms of allergen extracts can help improve safety and efficacy of AIT. Novel approaches to immunotherapy currently being explored include the use of adjuvants, allergen-derived peptides, modified recombinant allergen vaccines, and gene-specific immunotherapy.
Magnetic Resonance Imaging of Prostate Adenocarcinoma
Authors: Ward Ryan D. , Purysko Andrei S.
Published: February 2020

Prostate cancer (PCa) is common among men worldwide and is a major cause of morbidity and mortality. The detection of PCa has historically followed a stepwise process of prostate-specific antigen screening followed with systematic transrectal ultrasound-guided biopsy. Magnetic resonance imaging (MRI), utilizing a set of sequences to assess morphology and function, has gained clinical acceptance to detect, characterize, and stage PCa. The Prostate Imaging – Reporting and Data System has helped facilitate the standardization of reporting across institutions and increased adoption of this method. In this review, we will (1) discuss the strengths and weaknesses of conventional diagnostic methods; (2) describe the clinical utility of prostate MRI, specifically addressing its uses in the detection and staging of PCa; and (3) list important technical parameters required for state-of-the-art prostate MRI.
Prostate Benign Diseases
Authors: Guimaraes Cassia T.S. , Sauer Luisa J. , Romano Ricardo F.T. , Pacheco Eduardo O. , Bittencourt Leonardo K.
Published: February 2020

Magnetic resonance imaging (MRI) has been increasingly used in the detection, localization, and staging of prostate cancer. Because of its excellent soft tissue contrast and multiplane imaging, it can be also very useful in the evaluation of benign prostate diseases. Prostatic benign disorders have a high prevalence, vastly represented by benign prostatic hyperplasia and prostatitis. On the contrary, benign prostatic neoplasms are extremely rare, represented by multilocular cystadenoma, leiomyomas, hemangioma, and granular cell tumor, although these uncommon tumors have been most encountered due to widespread use of MRI. Congenital prostatic anomalies are associated with defects in the development of the prostate embryology, including hypoplasia, ectopia, and vascular malformations, abnormalities rarely seen on cross-sectional imaging. Prostatic cysts are the most common development abnormalities and occasionally are related to clinical symptoms, mainly due to infection and hemorrhage. As with prostate cancer, multiparametric MRI is a reliable tool for the diagnosis and management of benign prostatic diseases as well, providing additional information such morphological changes of the prostate, more accurate prostatic measurements, and functional characteristics of nonmalignant prostatic lesions. In this review, we discuss MRI findings of these benign prostatic diseases.
Prostate Cancer
Authors: Ferraro Daniela A. , Burger Irene A.
Published: February 2020

Positron-emission tomography (PET) with prostate-specific membrane antigen (PSMA) has been increasingly used to image prostate cancer in the last decade. In the staging setting several studies have already been published suggesting PSMA PET can be a valuable tool. They, however, did not translate into recommendations by guidelines. Both PSMA PET/computed tomography (CT) and PET/magnetic resonance imaging have been investigated in the staging setting, showing higher detection rate of prostate cancer lesions over the conventional imaging work-up and some studies already showed an impact on disease management. The aim of this review is to provide an overview of the existing published data regarding PSMA PET for staging prostate cancer, with emphasis on PET/magnetic resonance imaging. Despite the fact that PSMA is a relatively new tool and not officially recommended for staging yet, there are >50 original studies in the literature assessing PSMA PET performance in the staging setting of prostate cancer, and some meta-analyses.
A Review of the Application of Distributed Practice Principles to Naming Treatment in Aphasia
Authors: Middleton Erica L. , Schuchard Julia , Rawson Katherine A.
Published: February 2020

It is uncontroversial in psychological research that different schedules of practice, which govern the distribution of practice over time, can promote radically different outcomes in terms of gains in performance and durability of learning. In contrast, in speech–language treatment research, there is a critical need for well-controlled studies examining the impact of distribution of treatment on efficacy. In this article, we enumerate key findings from psychological research on learning and memory regarding how different schedules of practice differentially confer durable learning. We review existing studies of aphasia treatment with a focus on naming impairment that have examined how the distribution of practice affects treatment efficacy. We close by discussing potential productive lines of research to elaborate the clinical applicability of distributed practice principles to language treatment.
Modulation of plant acetyl CoA synthetase activity by post-translational lysine acetylation
Authors: Sofeo Naazneen , Winkelman Dirk C. , Leung Karina , Nikolau Basil J.
Published: February 2020

Acetyl-CoA synthetase (ACS) is one of several enzymes that generate the key metabolic intermediate, acetyl-CoA. ACS in plant cells is part of a two-enzyme system that maintains acetate homeostasis, but its post-translational regulation is unknown. In microbes and mammals ACS activity is regulated by the post-translational acetylation of a key lysine residue that is positioned in a conserved domain near the carboxyl-end of the protein sequence. This study demonstrates that the plant ACS activity can be regulated by the acetylation of a specific lysine residue that is homologous to the regulatory lysine residue of microbial and mammalian ACS. The inhibitory effect of the acetylation of residue Lys-622 of the Arabidopsis ACS was demonstrated by site-directed mutagenesis, including the genetic substitution of this residue with the non-canonical N-ε-acetyl-lysine residue. This latter modification lowered the catalytic efficiency of the enzyme by a factor of more than 500-fold. Michaelis-Menten kinetic analysis of the mutant enzyme indicates that this acetylation affects the first half-reaction of the ACS catalyzed reaction, namely the formation of the acetyl adenylate enzyme intermediate. The post-translational acetylation of the plant ACS would thus affect acetate flux in the plastids and overall acetate homeostasis.

Highlight

The study demonstrates that acetylation of a specific lysine residue can regulate the activity of acetyl-CoA synthetase, a new regulatory mechanism for maintaining acetate homeostasis.
Metabolic pathway inference using multi-label classification with rich pathway features
Authors: Basher Abdur Rahman M. A. , McLaughlin Ryan J. , Hallam Steven J.
Published: February 2020

Metabolic inference from genomic sequence information is a necessary step in determining the capacity of cells to make a living in the world at different levels of biological organization. A common method for determining the metabolic potential encoded in genomes is to map conceptually translated open reading frames onto a database containing known product descriptions. Such gene-centric methods are limited in their capacity to predict pathway presence or absence and do not support standardized rule-sets for automated and reproducible research. Pathway-centric methods based on defined rule sets or machine learning algorithms provide an adjunct or alternative inference method that supports hypothesis generation and testing of metabaolic relationships within and between cells. Here, we present mlLGPR,multi-label based onlogistic regression forpathway prediction, a software package that uses supervised multi-label classification and rich pathway features to infer metabolic networks at the individual, population and community levels of organization. We evaluated mlLGPR performance using a corpora of 12 experimental datasets manifesting diverse multi-label properties, including manually curated organismal genomes, synthetic microbial communities and low complexity microbial communities. Resulting performance metrics equaled or exceeded previous reports for organismal genomes and identify specific challenges associated with features engineering and training data for community-level metabolic inference.

Author summary

Predicting the complex series of metabolic interactions e.g. pathways, within and between cells from genomic sequence information is an integral problem in biology linking genotype to phenotype. This is a prerequisite to both understanding fundamental life processes and ultimately engineering these processes for specific biotechnological applications. A pathway prediction problem exists because we have limited knowledge of the reactions and pathways operating in cells even in model organisms likeEsherichia coliwhere the majority of protein functions are determined. To improve pathway prediction outcomes for genomes at different levels of complexity and completion we have developed mlLGPR,multi-label based onlogistic regression forpathway prediction, a scalable open source software package that uses supervised multi-label classification and rich pathway features to infer metabolic networks. We benchmark mlLGPR performance against other inference methods providing a code base and metrics for continued application of machine learning methods to the pathway prediction problem at the individual, population and community levels of biological organization.
Direct reprogramming of astrocytes to neurons leads to functional recovery after stroke
Authors: Livingston Jessica , Lee Tina , Daniele Emerson , Phillips Clara , Krassikova Alexandra , Enbar Tom , Kortebi Ines , Bang K.W. Annie , Donville Brennan , Ibragimov Omadyor , Sachewsky Nadia , Morshead Cindi M , Faiz Maryam
Published: February 2020

Stroke is the leading cause of adult disability with few treatment options for stroke survivors. Astrocyte reprogramming to neurons enables the targetedin vivogeneration of new cells at the site of injury and represents a novel approach for brain repair. A number of studies have demonstrated successful conversion of astrocytes to neurons in various models of brain injury and disease; however, the impact of this strategy on tissue and functional outcome following stroke is not well established. Using AAV delivery of the transcription factor NeuroD1, we reprogrammed astrocytes 7 days after endothelin-1 induced cortical stroke, and studied the long-term cellular and functional outcomes. We found that by 63 days post-stroke, 20% of neurons in the perilesional cortex were reprogrammed. Furthermore, reprogrammed neurons had matured into regionally appropriate neuronal subtypes. Importantly, this treatment was associated with improved functional outcome using the foot fault test and gait analysis. Together, our findings indicate thatin vivoreprogramming is a promising regenerative approach for stroke repair.
Iterative transfer learning with neural network for clustering and cell type classification in single-cell RNA-seq analysis
Authors: Hu Jian , Li Xiangjie , Hu Gang , Lyu Yafei , Susztak Katalin , Li Mingyao
Published: February 2020

An important step in single-cell RNA-seq (scRNA-seq) analysis is to cluster cells into different populations or types. Here we describe ItClust, anIterativeTransfer learning algorithm with neural network for scRNA-seqClustering. ItClust learns cell type knowledge from well-annotated source data, but also leverages information in the target data to make it less dependent on the source data quality. Through extensive evaluations using datasets from different species and tissues generated with diverse scRNA-seq protocols, we show that ItClust significantly improves clustering and cell type classification accuracy compared to popular unsupervised clustering and supervised cell type classification algorithms.
New Lipophilic Fluorescent Dyes for Exosome Labeling: Monitoring of Cellular Uptake of Exosomes
Authors: Shimomura Takashi , Seino Ryo , Umezaki Kaori , Shimoda Asako , Ezoe Takatoshi , Ishiyama Munetaka , Akiyoshi Kazunari
Published: February 2020

We have developed three types of exosomal membrane binding fluorescent probes, Mem Dye-Green, Mem Dye-Red and Mem Dye-Deep Red, to monitor exosome uptake into cells. The dyes contain a cyanine group as a fluorescent scaffold, which allows for highly sensitive fluorescence imaging of the exosome. These dyes can also be used to observe the dynamics of exosomes in live cells. The use of PKH dyes (Figure 1), which are currently the most widely-used fluorescent probes for exosome labeling, has some limitations. For example, PKH dyes tend to aggregate to form exosome-like nanoparticles, and these nanoparticles are uptaken by cells. Moreover, Mehdi suggested that the use of PKH dyes triggers an enlargement of the exosome size owing to membrane fusion or intercalation. To overcome the limitations of PKH dyes, we introduce amphiphilic moieties to the cyanine. To investigate the characteristics of the Mem Dyes as exosome labeling probes, we perform nanoparticle tracking analysis (NTA), zeta potential measurement and confocal microscopy. The Mem Dyes show excellent performance for exosome labeling (no aggregation and less size shift).
The hidden cost of receiving favors: A theory of indebtedness
Authors: Gao Xiaoxue , Jolly Eshin , Yu Hongbo , Liu Huiying , Zhou Xiaolin , Chang Luke J.
Published: February 2020

Receiving help or a favor from another person can sometimes have a hidden cost for the beneficiary. In this study, we explore these hidden costs by developing and validating a conceptual model of indebtedness across three studies that combine a large scale online questionnaire, an interpersonal game, computational modeling, and neuroimaging. Our model captures how individuals perceive the altruistic and strategic intentions of the benefactor. These inferences produce distinct feelings of guilt and obligation that together comprise indebtedness and motivate reciprocity. Perceived altruistic intentions convey care and concern and are associated with activity in insula, ventromedial prefrontal cortex and dorsolateral prefrontal cortex, while inferred strategic intentions convey expectations of future reciprocity and are associated with activation in temporal parietal junction and dorsomedial prefrontal cortex. We further develop a neural utility model of indebtedness using multivariate patterns of brain activity that captures the tradeoff between these feelings and reliably predicts reciprocity behavior.
Long-range Temporal Correlations in the Broadband Resting state Activity of the Human Brain revealed by Neuronal Avalanches
Authors: Lombardi Fabrizio , Shriki Oren , Herrmann Hans J. , de Arcangelis Lucilla
Published: February 2020

Resting-state brain activity is characterized by the presence of neuronal avalanches showing absence of characteristic size. Such evidence has been interpreted in the context of criticality and associated with the normal functioning of the brain. At criticality, a crucial role is played by long-range power-law correlations. Thus, to verify the hypothesis that the brain operates close to a critical point and consequently assess deviations from criticality for diagnostic purposes, it is of primary importance to robustly and reliably characterize correlations in resting-state brain activity. Recent works focused on the analysis of narrow band electroencephalography (EEG) and magnetoencephalography (MEG) signal amplitude envelope, showing evidence of long-range temporal correlations (LRTC) in neural oscillations. However, this approach is not suitable for assessing long-range correlations in broadband resting-state cortical signals. To overcome such limitation, here we propose to characterize the correlations in the broadband brain activity through the lens of neuronal avalanches. To this end, we consider resting-state EEG and long-term MEG recordings, extract the corresponding neuronal avalanche sequences, and study their temporal correlations. We demonstrate that the broadband resting-state brain activity consistently exhibits long-range power-law correlations in both EEG and MEG recordings, with similar values of the scaling exponents. Importantly, although we observe that avalanche size distribution depends on scale parameters, scaling exponents characterizing long-range correlations are quite robust. In particular, they are independent of the temporal binning (scale of analysis), indicating that our analysis captures intrinsic characteristics of the underlying dynamics. Because neuronal avalanches constitute a fundamental feature of neural systems with universal characteristics, the proposed approach may serve as a general, systems- and experiment-independent procedure to infer the existence of underlying long-range correlations in extended neural systems, and identify pathological behaviors in the complex spatio-temporal interplay of cortical rhythms.
A lung-on-chip model reveals an essential role for alveolar epithelial cells in controlling bacterial growth during early tuberculosis
Authors: Thacker Vivek V. , Dhar Neeraj , Sharma Kunal , Barrile Riccardo , Karalis Katia , McKinney John D.
Published: February 2020

Mycobacterium tuberculosis(Mtb) makes ‘first contact’ with a host in the alveolar space, an interaction largely inaccessible to experimental observation. We establish a lung-on-chip model for early tuberculosis and use time-lapse imaging to reveal the dynamics of host-Mtb interactions at an air-liquid interface with a spatiotemporal resolution unattainable in animal models. By reconstituting host physiology in a modular manner, we probe the role of pulmonary surfactant secreted by alveolar epithelial cells (AECs) in early infection. This is difficult to study directly in animal models, as surfactant-deficient animals are either non-viable or develop acute lung pathologies. We demonstrate that surfactant deficiency results in rapid and uncontrolled Mtb growth in both macrophages and AECs. In contrast, under normal surfactant levels, a significant fraction of intracellular bacteria are non-growing. The surfactant-deficient phenotype is rescued by exogenous addition of surfactant replacement formulations, which have no effect on bacterial viability in the absence of host cells. Surfactant partially removes virulence-associated lipids and proteins1,2from the bacterial cell surface and consistent with this mechanism of action, we show that attenuation of bacteria lacking the virulence-associated ESX-1 secretion system is independent of surfactant levels. These findings may partly explain why individuals with compromised surfactant function, such as smokers and elderly persons, are at increased risk of developing active tuberculosis.
Hybridization-based In Situ Sequencing (HybISS): spatial transcriptomic detection in human and mouse brain tissue
Authors: Gyllborg Daniel , Langseth Christoffer Mattsson , Qian Xiaoyan , Salas Sergio Marco , Hilscher Markus M. , Lein Ed S. , Nilsson Mats
Published: February 2020

Visualization of the transcriptome in situ has proven to be a valuable tool in exploring single-cell RNA-sequencing data, providing an additional dimension to investigate spatial cell typing and cell atlases, disease architecture or even data driven discoveries. The field of spatially resolved transcriptomic technologies is emerging as a vital tool to profile gene-expression, continuously pushing current methods to accommodate larger gene panels and larger areas without compromising throughput efficiency. Here, we describe a new version of the in situ sequencing (ISS) method based on padlock probes and rolling circle amplification. Modifications in probe design allows for a new barcoding system via sequence-by-hybridization chemistry for improved spatial detection of RNA transcripts. Due to the amplification of probes, amplicons can be visualized with standard epifluorescence microscopes with high-throughput efficiency and the new sequencing chemistry removes limitations bound by sequence-by-ligation chemistry of ISS. Here we present hybridization-based in situ sequencing (HybISS) that allows for increased flexibility and multiplexing, increased signal-to-noise, all without compromising throughput efficiency of imaging large fields of view. Moreover, the current protocol is demonstrated to work on human brain tissue samples, a source that has proven to be difficult to work with image-based spatial analysis techniques. Overall, HybISS technology works as a target amplification detection method for improved spatial transcriptomic visualization, and importantly, with an ease of implementation.
The usefulness of multi-parent multi-environment QTL analysis: an illustration in different NAM populations
Authors: Garin Vincent , Malosetti Marcos , van Eeuwijk Fred
Published: February 2020

Commonly QTL detection in multi-parent population (MPPs) data measured in multiple environments (ME) is done by a single environment analysis on phenotypic values ‘averaged’ across environments. This method can be useful to detect QTLs with a consistent effect across environments but it does not allow to estimate environment-specific QTL (QTLxE) effects. Running separate single environment analyses is a possibility to measure QTLxE effects but those analyses do not model the genetic covariance due to the use of the same genotype in different environments. In this paper, we propose methods to analyze MPP-ME QTL experiments using simultaneously the data from several environments and modelling the genotypic covariances. Using data from the EU-NAM and the US-NAM populations, we show that these methods allow to estimate the QTLxE effects and that they give a more precise description of the trait genetic architecture than separate within environment analyses. The MPP-ME models we propose can also be extended to integrate environmental indices (e.g. temperature, precipitation, etc.) to understand better the mechanisms behind the QTLxE effects. Therefore, our methodology allows to exploit the full potential of MPP-ME data: to estimate QTL effect variations a) within the MPP between sub-populations due to different genetic backgrounds; and b) between environments.
MLQ is responsible for stabilisation of subunit a in the holoenzyme of mammalian ATP synthase
Authors: Tauchmannová K , Ho DH , Nůsková H , Pecinová A , Alán L , Rodinová M , Koňaříková E , Vrbacký M , Puertas G , Kaplanová V , Houštěk J , Pecina P , Mráček T
Published: February 2020

The biogenesis of mammalian ATP synthase is complex process believed to proceed via several modules. It starts with the formation of F1 catalytic part, which is in the later steps connected with the membranous subcomplex. The final phase is represented by incorporation of the two mtDNA-encoded subunits Fo-a and A6L. However, little is known about the position of two newly described Fo accessory subunits DAPIT (also termed Usmg5) and MLQ (also known as c14orf2) in the assembly scheme and about their role in regulation of ATP synthase biogenesis. To resolve this, we have utilised several model systems, namely rho0 cells lacking mtDNA and thus both subunits Fo-a and A6L, cells harbouring 9205delTA microdeletion, which results in the absence of the subunit Fo-a, HEK293 cells with knockdown of DAPIT protein and HEK293 cells with knockout of MLQ protein and followed the assembly state of ATP synthase among them.

Contrary to previously reported data, we observed normal levels of assembled ATP synthase in DAPIT knockdown and MLQ knockout cells. Our results indicate that lack of DAPIT protein leads to the assembly of more labile, but complete and functional holoenzyme. Absence of either Fo-a alone or Fo-a and A6L results into the normal levels of structurally altered, labile, and ~60 kDa smaller vestigial enzyme complex, which also lacks DAPIT and MLQ. This complex retains the ATP hydrolytic activity but is unable to synthesize ATP. Cells with the MLQ knockout presented with the phenotype similar to the lack of Fo-a: normal content of smaller and labile complex. In the absence of MLQ, vestigial ATP synthase did not contain also subunits Fo-a and A6L. This complex also retained ATP hydrolytic activity, while its phosphorylating capacity was affected. In all the cell lines tested, the individual subunits seemed to be associated only with assembled ATP synthase complex, indicating that once subunits dissociate from the complex, they are degraded in the cell. This hypothesis is supported by the fact, that in the cells lacking subunit MLQ the biosynthesis of both mtDNA-encoded subunits Fo-a and A6L is normal, but they are degraded at faster pace than the rest of the complex.

Based on our data, we conclude that MLQ and Fo-a closely associate and their incorporation into the enzyme complex depends on each another. On the contrary, DAPIT protein seems to be incorporated at the very last step and its presence stabilises the holoenzyme.
Rotational snapping: Illusory rhythmicity induced by global and local motion binding
Authors: Han Hio-Been
Published: February 2020

The complexity of human perceptual system has often been investigated through its atypical function; the illusion. Here, I introduce a new visual illusion induced by rotational motion binding, which leads to a gestalt perception of illusory object rhythmically popping out and fading away. In this illusion, observers reported non-existing rhythm out of rotating Gabor patches (e.g., local rotation) that also have orbital trajectory with opposite direction (e.g., global rotation), only under the particular combinations of parameters. This illusory rhythmicity was four times faster than the average of global/local rotational speed. Image reconstruction using the response-triggered average revealed the rhythmicity is explained by the circular alignment of array, demonstrating the effect of repeated contour integration and its perceptual consequences.
MaTAR25LncRNA Regulates theTensin1Gene to Impact Breast Cancer Progression
Authors: Chang Kung-Chi , Diermeier Sarah D. , Yu Allen T. , Brine Lily D. , Russo Suzanne , Bhatia Sonam , Alsudani Habeeb , Kostroff Karen , Bhuiya Tawfiqul , Brogi Edi , Bennett C. Frank , Rigo Frank , Spector David L.
Published: February 2020

Misregulation of long non-coding RNA genes has been linked to a wide variety of cancer types. Here we report onMammaryTumorAssociatedRNA 25 (MaTAR25), a nuclear enriched and chromatin associated lncRNA that plays a role in mammary tumor cell proliferation, migration, and invasion, bothin vitroandin vivo.MaTAR25functions by interacting with purine rich element binding protein B (PURB), and associating with a major downstream target geneTensin 1(Tns1) to regulate its expression intrans. Knockout ofMaTAR25results in down-regulation ofTns1leading to a reorganization of the actin cytoskeleton, and a reduction of focal adhesions and microvilli. The human ortholog ofMaTAR25,LINC01271, is upregulated with human breast cancer stage and metastasis.

SIGNIFICANCE

LncRNAs have great potential to reveal new regulatory mechanisms of function as well as having exciting therapeutic capacity given their ease of being targeted by nucleic acid drugs. Our study ofMaTAR25,and its human orthologLINC01271,reveal an unexpected function of this lncRNA in breast cancer progression by regulatingTns1gene expression, whose protein product is a critical component of focal adhesions linking signaling between the extracellular matrix and the actin cytoskeleton. We identifiedLINC01271 asthe human ortholog ofMaTAR25, and importantly, increased expression ofLINC01271is associated with poor patient prognosis and cancer metastasis. Our findings demonstrate thatLINC01271represents an exciting therapeutic target to alter breast cancer progression.
JEDI: Circular RNA Prediction based on Junction Encoders and Deep Interaction among Splice Sites
Authors: Jiang Jyun-Yu , Ju Chelsea J.-T. , Hao Junheng , Chen Muhao , Wang Wei
Published: February 2020

Circular RNA is a novel class of endogenous non-coding RNAs that have been largely discovered in eukaryotic transcriptome. The circular structure arises from a non-canonical splicing process, where the donor site backsplices to an upstream acceptor site. These circular form of RNAs are conserved across species, and often show tissue or cell-specific expression. Emerging evidences have suggested its vital roles in gene regulation, which are further associated with various types of diseases. As the fundamental effort to elucidate its function and mechanism, numerous efforts have been devoted to predicting circular RNA from its primary sequence. However, statistical learning methods are constrained by the information presented with explicit features, and the existing deep learning approach falls short on fully exploring the positional information of the splice sites and their deep interaction.

We present an effective and robust end-to-end framework, JEDI, for circular RNA prediction using only the nucleotide sequence. Our framework first leverages the attention mechanism to encode each junction site based on deep bidirectional recurrent neural networks and then presents the novel cross-attention layer to model deep interaction among these sites for backsplicing. Finally, JEDI is capable of not only addressing the task of circular RNA prediction but also interpreting the relationships among splice sites to discover the hotspots for backsplicing within a gene region. Experimental evaluations demonstrate that JEDI significantly outperforms several state-of-the-art approaches in circular RNA prediction on both isoform-level and gene-level. Moreover, JEDI also shows promising results on zero-shot backsplicing discovery, where none of the existing approaches can achieve.

The implementation of our framework is available athttps://github.com/hallogameboy/JEDI.
cDNA library screening to identify interacting proteins of Golgi-localized type II membrane proteins
Authors: Lund Christian Have , Bromley Jennifer R. , López-Marqués Rosa Laura , Sakuragi Yumiko
Published: February 2020

In eukaryotes, biosynthesis of many extracellular matrix glycans occurs in the Golgi apparatus. These proteins include glycosyltransferases, modifying enzymes and nucleotide-sugar conversion enzymes, many of which possess a type II membrane topology. Growing evidence indicates that both the function and Golgi localization of many of these proteins are regulated through protein-protein interactions (PPIs). Given the essential nature and conservation of extracellular matrix polysaccharides, it is likely that PPIs are more prevalent among biosynthetic enzymes. However the identification of PPIs among Golgi proteins has been technically challenging due to the generally low abundance and unique membrane topology of these proteins. The aim of this article is to explore the feasibility of cDNA library screening by a yeast-based modified split ubiquitin system as a mean for unbiased screening for PPIs involving a Golgi-localized type II membrane. As a test case, a galacturonosyltransferase1 (GAUT1), involved in pectin biosynthesis in the higher plant Arabidopsis thaliana, was used as the bait. Construction and screening of Arabidopsis cDNA libraries using GAUT1 as the bait successfully led to identification of GAUT7, a previously reported interaction partner of GAUT1, which validates the method. Furthermore, 25 novel candidate interaction partners were identified. The results contribute to shape a field guide for identifying PPIs involving glycan biosynthetic enzymes in eukaryotic cells.
A Comprehensive Assessment of Human Natural Killer Cell Phenotype and Function in Whole Blood
Authors: Market M , Tennakoon G , Ng J , Scaffidi M , Kennedy M A , de Souza C Tanese , Auer R C
Published: February 2020

The majority of data on human Natural Killer (NK) cell phenotype and function has been generated using cryopreserved peripheral blood mononuclear cells (PBMCs). However, cryopreservation can have adverse effects on PBMCs. In contrast, investigating immune cells in whole blood can reduce the time, volume of blood required, and potential artifacts associated with manipulation of the cells. Whole blood collected from healthy donors and cancer patients was processed by three separate protocols that can be used independently or in parallel to assess extracellular receptors, intracellular signaling protein phosphorylation, and intracellular and extracellular cytokine production in human NK cells. To assess extracellular receptor expression, 200 μL of whole blood was incubated with an extracellular staining (ECS) mix and cells were subsequently fixed and RBCs lysed prior to analysis. The phosphorylation status of signaling proteins was assessed in 500 μL of whole blood following co-incubation with interleukin (IL)−2/12 and the ECS mix for 20 minutes prior to cell fixation and RBC lysis and subsequent permeabilization for staining with an intracellular staining (ICS) mix. Cytokine production (IFNγ) was similarly assessed by incubating 1 mL of whole blood with PMA-ionomycin or IL−2/12 prior to incubation with ECS and subsequent ICS antibodies. In addition, plasma was collected from stimulated samples prior to ECS for quantification of secreted IFNγ by ELISA. Results were consistent, despite inherent interpatient variability. Although we did not investigate an exhaustive list of targets, this approach enabled quantification of representative ECS surface markers including activating (NKG2D and DNAM−1) and inhibitory (NKG2D, PD−1, TIGIT, and TIM−3) receptors, cytokine receptors (CD25, CD122, CD132, and CD212) and ICS markers associated with NK cell activation following stimulation, including signaling protein phosphorylation (p-STAT4, p-STAT5, p-p38 MAPK, p-S6K) and IFNγ in both healthy donors and cancer patients. In addition, we compared extracellular receptor expression using whole blood versus cryopreserved PBMCs and observed a significant difference in the expression of almost all receptors. The methods presented permit a relatively rapid parallel assessment of immune cell receptor expression, signaling protein activity, and cytokine production in a minimal volume of whole blood from both healthy donors and cancer patients.
Analysis of spherical shell structure based on SBFEM
Authors: Lin Gao , Ye Wen-Bin , Li Zhi-Yuan , Liu Jun
Published: February 2020

Purpose

The purpose of this paper is to present an accurate and efficient element for analysis of spherical shell structures.

Design/methodology/approach

A scaled boundary finite element method is proposed, which offers more advantages than the finite element method and boundary element method. Only the boundary of the computational domain needs to be discretized, but no fundamental solution is required.

Findings

The method applies to thin as well as thick spherical shells, irrespective of the shell geometry, boundary conditions and applied loading. The numerical solution converges to highly accurate result with raising the order of high-order elements.

Originality/value

The modeling strictly follows three-dimensional theory of elasticity. Formulation of the surface finite elements using three translational degree of freedoms per node is required, which results in considerably simplifying the computation. In the thickness directions, it is solved analytically, no problem of high aspect ratio arises and transverse shear locking can be successfully avoided.
An experimental/numerical hydrothermal analysis on natural convection and TiO2-SiO2/W-EG nanofluid’s properties in a hollow/finned cavity
Authors: Zaresharif Mahshid , Zarei Fatemeh , Ranjbar Ali Mohammad , Kok Foong Loke , Ross David
Published: February 2020

Purpose

This paper aims to provide an experimental/numerical analysis of free convection within a hollow/finned cavity.

Design/methodology/approach

The hollow square cavity is equipped with eight active fins which have a similar configuration and different temperatures. Furthermore, four different thermal arrangements are considered to determine the order of temperature for each fin. The coupled lattice Boltzmann method is used, which not only maintains the considerable advantages of standard lattice Boltzmann method such as accuracy but also enhances the stability of this method.

Findings

The cavity is filled with TiO2-SiO2/Water-Ethylene Glycol nanofluid. The thermal conductivity and dynamic viscosity of nanofluid are experimentally measured using high-precision devices in six concentrations of the nanoparticle. In this study, some main parameters, including a range of Rayleigh number (103 < Ra < 106), the concentration of nanofluid (0.5 to 3 Vol.%) and thermal arrangements of fins, are considered. The effects of these main parameters on the flow, isotherms, heat transfer performance and entropy generation are studied.

Originality/value

The originality of this paper is combining the numerical simulation (lattice Boltzmann method) using a modern approach with experimental observations of nanofluid’s properties.
Natural convection from cross blade inside a nanofluid-filled cavity using ISPH method
Authors: Raizah Zehba A.S.
Published: February 2020

Purpose

The purpose of this study is to apply the incompressible smoothed particle hydrodynamics method for simulating the natural convection flow inside a cavity including cross blades or circular cylinder cylinder.

Design/methodology/approach

The base fluid is water and copper-water nanofluid is treated as a working fluid. The left and rights walls are maintained at a cool temperature, the horizontal cavity walls are isolated and the inner shape was heated. The physical parameters are the length of the blades L_Blade, the number of cross blades, circular cylinder radius L_R, Rayleigh number Ra and the nanoparticles volume fraction.

Findings

The results reveal that the lengths of the cross blade, number of the blades and radius of the circular cylinder is working as an enhancement factor for heat transfer and fluid flows inside a cavity. Adding nanoparticles augments heat transfer and reduces the fluid flow intensity inside a cavity. The best case for buoyancy-driven flow was obtained when the inner shape is the circular cylinder at a higher Rayleigh number.

Originality/value

This work uses a distinctive numerical method to study the natural convection heat from cross blades inside a cavity filled with nanofluid. It provides a new analysis of this issue and presented good results.