bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thirty years after Jensen’s prediction: Is private equity a superior form of ownership?
Authors: Morris Peter , Phalippou Ludovic 
Published: February 2020

Abstract
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

Abstract

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.
Magnetic Resonance Imaging of Prostate Adenocarcinoma
Authors: Ward Ryan D. , Purysko Andrei S. 
Published: February 2020

Abstract
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

Abstract
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

Abstract
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.
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

ABSTRACTAcetyl-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.HighlightThe 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

AbstractMetabolic 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 summaryPredicting 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

AbstractStroke 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

AbstractAn 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

ABSTRACTWe 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

AbstractReceiving 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

AbstractResting-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

AbstractMycobacterium 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.
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

AbstractCommonly 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.