bluuebunny/crossref_metadata_2025_split huggingface dataset:
A machine learning approach to identifying objective biomarkers of anxiety and stress
Authors: Ramakrishnan Arjun , Pardes Adam , Lynch William , Molaro Christopher , Platt Michael Louis 
Published: August 2019

AbstractAnxiety and stress-related disorders are highly prevalent and debilitating conditions that impose an enormous burden on society. Sensitive measurements that can enable early diagnosis could mitigate suffering and potentially prevent onset of these conditions. Self-reports, however, are intrusive and vulnerable to biases that can conceal the true internal state. Physiological responses, on the other hand, manifest spontaneously and can be monitored continuously, providing potential objective biomarkers for anxiety and stress. Recent studies have shown that algorithms trained on physiological measurements can predict stress states with high accuracy. Whether these predictive algorithms generalize to untested situations and participants, however, remains unclear. Further, whether biomarkers of momentary stress indicate trait anxiety – a vulnerability foreshadowing development of anxiety and mood disorders – remains unknown. To address these gaps, we monitored skin conductance, heart rate, heart rate variability and EEG in 39 participants experiencing physical and social stress and compared these measures to non-stressful periods of talking, rest, and playing a simple video game. Self-report measures were obtained periodically throughout the experiment. A support vector machine trained on physiological measurements identified stress conditions with ~96% accuracy. A decision tree that optimally combined physiological and self-report measures identified individuals with high trait anxiety with ~84% accuracy. Individuals with high trait anxiety also displayed high baseline state anxiety but a muted physiological response to acute stressors. Overall, these results demonstrate the potential for using machine learning tools to identify objective biomarkers useful for diagnosing and monitoring mental health conditions like anxiety and depression.
Antiviral activity of N-ω-Chloroacetyl-L-Ornithine on in vitro replication of Chikungunya virus
Authors: Luna-Rojas Lucero , Avila-Trejo Amanda M. , Alcántara-Farfán Verónica , Rodríguez-Páez Lorena I. , Pastor-Alonso Marvin Omar , Aguilar-Faisal J. Leopoldo 
Published: August 2019

AbstractThe infections causes by Chikungunya virus (CHIKV), family Togaviridae, genus Alfavirus, have become a health problem around the world, due to its widespread occurrence, the high morbidity rate and the absence of vaccines or antiviral treatments. We analyzed a competitive inhibitor of ornithine decarboxylase, enzyme key in the biosynthesis of Polyamines (PAs), N-ω-chloroacetyl-L-ornithine (NCAO), as a possible inhibitor of CHIKV replication because intracellular polyamines participate in the transcription andin vitrotranslation of CHIKV. NCAO does not have any cytotoxic effect on C6/36 cells even at a concentration of 1000μM at 72h after post-exposure but in Vero cells the cytotoxic effect was presented above 380μM at 48h post-exposure, which was considered when determining the inhibitory effect on viral replication. We demonstrate that NCAO inhibits the replication of CHIKV in Vero and C6/36 cells in a dose-dependent manner causing a decrease in the PFU/mL of at least 4-logarithm (p <0.01) in both cell lines. Viral yields were restored by the addition of exogenous polyamines, mainly putrescine. HPLC analyses it shown that NCAO decrease content of intracellular PAs even though in infected cells mainly decreased spermidine and spermine, so NCAO inhibits CHIKV replication, by depleting the intracellular polyamines in Vero and C6/36 cells, suggesting that this compound is a possible antiviral in CHIKV infections.ImportanceThe infections caused by Chikungunya virus (CHIKV), genus Alfavirus, have become a worldwide health problem, due to its high morbidity rate and the absence of vaccines or antiviral treatments. It is known that CHIKV use intracellular poliamines during transcription and traduction process, so the depletion of intracellular putrescine, spermidine and spermine reduce the viral replication. N-ω-chloroacetyl-L-ornithine (NCAO) is known as a competitive inhibitor of ornithine decarboxylase, key enzyme in Polyamines biosynthesis, but no studies have proven its activity on the inhibition of polyamine-dependent viral replication. Here we demonstrate NCAO inhibits in vitro CHIKV replication, so we propose NCAO as an antiviral candidate.
Algal photosynthesis converts nitric oxide into nitrous oxide
Authors: Burlacot Adrien , Richaud Pierre , Gosset Arthur , Li-Beisson Yonghua , Peltier Gilles 
Published: August 2019

AbstractNitrous oxide (N2O), a potent greenhouse gas in the atmosphere, is produced mostly from aquatic ecosystems, to which algae substantially contribute. However, mechanisms of N2O production by photosynthetic organisms are poorly described. Here, we show that the green microalgaChlamydomonas reinhardtiireduces NO into N2O using the photosynthetic electron transport. Through the study ofC. reinhardtiimutants deficient in flavodiiron proteins (FLVs) or in a cytochrome p450 (CYP55), we show that FLVs contribute to NO reduction in the light, while CYP55 operates in the dark. Furthermore, NO reduction by both pathways is restricted to Chlorophytes, organisms particularly abundant in ocean N2O-producing hotspots. Our results provide a mechanistic understanding of N2O production in eukaryotic phototrophs and represent an important step toward a comprehensive assessment of greenhouse gas emission by aquatic ecosystems.One sentence summaryGreen microalgae produce N2O using flavodiiron proteins in the light and a cytochrome P450 NO reductase in the dark.
Gut Microbiome Biomarkers in Adolescent Obesity: a Regional Study
Authors: Gao Xuefeng , Wu Binbin , Pan Yonglong , Zhou Shaoming , Zhang Ming , Cai Yunpeng , Liang Yan 
Published: August 2019

ABSTRACTPurposeThis study aimed to characterize the gut microbiota in obese Shenzhen adolescents, and evaluate the influence of gender on BMI-related differences in the gut microbiome.MethodsPhysical examinations, blood pressure measurement, serological assay, and body composition evaluation were conducted on two-hundred and five adolescents from Shenzhen. Fecal microbiome composition was profiled via 16S rRNA gene sequencing. A Random Forest (RF) classifier model was built to distinguish the BMI categories based on the gut bacterial composition.ResultsFifty-six taxa consisting mainly of Firmicutes were identified that having significant associations with BMI; two OTUs belonging to Ruminococcaceae and one belonging to Lachnospiraceae had relatively strong positive correlations with body fate rate, waistline, and most of serum biochemical parameters. Based on the 56 BMI-associated OTUs, the RF model showed a robust classification accuracy (AUC 0.96) for predicting the obese phenotype. Gender-specific differences in the gut microbiome composition was obtained, and a lower relative abundance of Odoribacter was particularly found in obese boys. Functional analysis revealed a deficiency in bacterial gene contents related to PPAR signaling pathway in obese subjects for both genders; significantly lower levels of adipocytokine signaling pathway and ethylbenzene degradation were particularly detected in obese girls.ConclusionsThis study revealed unique features of gut microbiome in terms of microbial composition and metabolic functions in obese Shenzhen adolescents. The effect of geographical location, age and gender on the gut microbiome should be carefully considered in case–control studies.
Modelling functional human neuromuscular junctions in a differentially-perturbable microfluidic environment, validated through recombinant monosynaptic pseudotyped ΔG-rabies virus tracing
Authors: Bauer Ulrich Stefan , van de Wijdeven Rosanne , Raveendran Rajeevkumar Nair , Fiskum Vegard , Kentros Clifford , Sandvig Ioanna , Sandvig Axel 
Published: August 2019

AbstractCompartmentalized microfluidic culture systems provide new perspectives in in vitro disease modelling as they enable co-culture of different relevant cell types in interconnected but fluidically isolated microenvironments. Such systems are thus particularly interesting in the context of in vitro modelling of mechanistic aspects of neurodegenerative diseases such as amyotrophic lateral sclerosis, which progressively affect the function of neuromuscular junctions, as they enable the co-culture of motor neurons and muscle cells in separate, but interconnected compartments. In combination with cell reprogramming technologies for the generation of human (including patient-specific) motor neurons, microfluidic platforms can thus become important research tools in preclinical studies. In this study, we present the application of a microfluidic chip with a differentially-perturbable microenvironment as a platform for establishing functional neuromuscular junctions using human induced pluripotent stem cell derived motor neurons and human myotubes. As a novel approach, we demonstrate the functionality of the platform using a designer pseudotyped ΔG-rabies virus for retrograde monosynaptic tracing.Graphical abstractFunctional neuromuscular junction in a microfluidic chip(a) Overview of microfluidic chip. Human iPS cell-derived motor neuron aggregates (spheroids indicated by black arrows) are seeded in the three lateral compartments of the chip, while human myotubes (white arrows) are seeded in the middle compartment.(b) Directed connectivity and retrograde virus tracing. Outgrowing axons (yellow arrow) from the motor neuron aggregate enter the directional axon tunnels (grey rectangles) and form connections with the myotubes (white arrow) within the opposite compartment. Addition of a designer monosynaptic pseudotyped ΔG-rabies virus to the myotube compartment, infects the myotubes (green) expressing an exogenous receptor (TVA) and rabies glycoprotein (G), subsequently making infectious viruses that are retrogradely transported through the motor neuron axons (green arrow) back to the neuronal cell bodies within the aggregate, validating neuromuscular junction functionality.
Assessing seasonal demographic covariation to understand environmental-change impacts on a hibernating mammal
Authors: Paniw Maria , Childs Dylan , Armitage Kenneth B , Blumstein Daniel T , Martin Julien , Oli Madan K. , Ozgul Arpat 
Published: August 2019

ABSTRACTNatural populations are exposed to seasonal variation in environmental factors that simultaneously affect several demographic rates (survival, development, reproduction). The resulting covariation in these rates determines population dynamics, but accounting for its numerous biotic and abiotic drivers is a significant challenge. Here, we use a factor-analytic approach to capture partially unobserved drivers of seasonal population dynamics. We use 40 years of individual-based demography from yellow-bellied marmots (Marmota flaviventer) to fit and project population models that account for seasonal demographic covariation using a latent variable. We show that this latent variable, by producing positive covariation among winter demographic rates, depicts a measure of environmental quality. Simultaneous, negative responses of winter survival and reproductive-status change to declining environmental quality result in a higher risk of population quasi-extinction, regardless of summer demography where recruitment takes place. We demonstrate how complex environmental processes can be summarized to understand population persistence in seasonal environments.
Evaluation of the impact of seasonal variations in photoperiod on the hepatic metabolism of medaka (Oryzias latipes)
Authors: Fujisawa Koichi , Takami Taro , Shintani Haruko , Sasai Nanami , Matsumoto Toshihiko , Yamamoto Naoki , Sakaida Isao 
Published: August 2019

AbstractOrganisms living in temperate regions are sensitive to seasonal variations in the environment; they are known to accumulate energy as fat in their livers during the winter when days are shorter, temperatures are lower, and food is scarce. However, the impact of variations in photoperiod alone on hepatic lipid metabolism has not been well-studied. Therefore, in this study, we analyzed lipid metabolism in the liver of medaka,Oryzias latipes, while varying the length of days at constant temperature. Larger amounts of fatty acids accumulated in the liver after 14 days under short-day conditions than under long-day conditions. Metabolome analysis showed no accumulation of the long-chain unsaturated fatty acids required at low temperatures, but showed a significant accumulation of long-chain saturated fatty acids. Short-day conditions induced decreased levels of succinate, fumarate, and malate in the tricarboxylic acid cycle, decreased expression of PPARα, and decreased accumulation of acylcarnitine, which suggested inhibition of lipolysis. In addition, when a high-fat diet was administered to transparent medaka under short-day conditions, larger amounts of fat accumulated and medaka with fatty liver were efficiently produced. Detailed analysis of the relationship between seasonal changes and hepatic steatosis will be important in the future as hepatic diseases become more prevalent in modern society; the findings obtained in our study will be useful for research studies pertaining to the relationship between photoperiod and disorders such as hepatic steatosis and non-alcoholic steatohepatitis.
Dynamic architecture and regulatory implications of the miRNA network underlying the response to stress in melon
Authors: Sanz-Carbonell Alejandro , Marques Maria Carmen , Martinez German , Gomez Gustavo 
Published: August 2019

SUMMARYmiRNAs are small RNAs that regulate mRNAs at both transcriptional and posttranscriptional level. In plants, miRNAs are involved in the regulation of different processes including development and stress-response. Elucidating how stress-responsive miRNAs are regulated is key to understand the global response to stress but also to develop efficient biotechnological tools that could help to cope with stress. Here, we describe a computational approach based on sRNA sequencing, transcript quantification and degradome data to analyze the accumulation, function and structural organization of melon miRNAs reactivated under seven biotic and abiotic stress conditions at two and four days post-treatment. Our pipeline allowed us to identify fourteen stress-responsive miRNAs (including evolutionary conserved such as miR156, miR166, miR172, miR319, miR398, miR399, miR894 and miR408) at both analyzed times. According to our analysis miRNAs were categorized in three groups showing a broad-, intermediate- or narrow- response range. miRNAs reactive to a broad range of environmental cues appear as central components in the stress-response network. The strictly coordinated response of miR398 and miR408 (broad response-range) to the seven stress treatments during the period analyzed here reinforces this notion. Although both, the amplitude and diversity of the miRNA-related response to stress changes during the exposition time, the architecture of the miRNA-network is conserved. This organization of miRNA response to stress is also conserved in rice and soybean supporting the conservation of miRNA-network organization in other crops. Overall, our work sheds light into how miRNA networks in plants organize and function during stress.
Quantitative Single-Cell Proteomics as a Tool to Characterize Cellular Hierarchies
Authors: Schoof Erwin M. , Furtwängler Benjamin , Üresin Nil , Rapin Nicolas , Savickas Simonas , Gentil Coline , Lechman Eric , auf dem Keller Ulrich , Dick John E. , Porse Bo T. 
Published: August 2019

AbstractLarge-scale single-cell analyses are of fundamental importance in order to capture biological heterogeneity within complex cell systems, but have largely been limited to RNA-based technologies. Here we present a comprehensive benchmarked experimental and computational workflow, which establishes global single-cell mass spectrometry-based proteomics as a tool for large-scale single-cell analyses.By exploiting a primary leukemia model system, we demonstrate both through pre-enrichment of cell populations and through a non-enriched unbiased approach that our workflow enables the exploration of cellular heterogeneity within this aberrant developmental hierarchy. Our approach is capable of consistently quantifying approximately 1000 proteins per cell across thousands of individual cells using limited instrument time. Furthermore, we developed a computational workflow (SCeptre) that effectively normalizes the data, integrates available FACS data and facilitates downstream analysis. The approach presented here lays a solid foundation for implementing global single-cell proteomics studies across the world.
An Interpretable Performance Metric for Auditory Attention Decoding Algorithms in a Context of Neuro-Steered Gain Control
Authors: Geirnaert Simon , Francart Tom , Bertrand Alexander 
Published: August 2019

AbstractIn a multi-speaker scenario, a hearing aid lacks information on which speaker the user intends to attend, and therefore it often mistakenly treats the latter as noise while enhancing an interfering speaker. Recently, it has been shown that it is possible to decode the attended speaker from the brain activity, e.g., recorded by electroencephalography sensors. While numerous of these auditory attention decoding (AAD) algorithms appeared in the literature, their performance is generally evaluated in a non-uniform manner. Furthermore, AAD algorithms typically introduce a trade-off between the AAD accuracy and the time needed to make an AAD decision, which hampers an objective benchmarking as it remains unclear which point in each algorithm’s trade-off space is the optimal one in a context of neuro-steered gain control. To this end, we present an interpretable performance metric to evaluate AAD algorithms, based on an adaptive gain control system, steered by AAD decisions. Such a system can be modeled as a Markov chain, from which the minimal expected switch duration (MESD) can be calculated and interpreted as the expected time required to switch the operation of the hearing aid after an attention switch of the user, thereby resolving the trade-off between AAD accuracy and decision time. Furthermore, we show that the MESD calculation provides an automatic and theoretically founded procedure to optimize the number of gain levels and decision time in an AAD-based adaptive gain control system.
Extending the small molecule similarity principle to all levels of biology
Authors: Duran-Frigola Miquel , Pauls Eduardo , Guitart-Pla Oriol , Bertoni Martino , Alcalde Víctor , Amat David , Juan-Blanco Teresa , Aloy Patrick 
Published: August 2019

AbstractWe present the Chemical Checker (CC), a resource that provides processed, harmonized and integrated bioactivity data on 800,000 small molecules. The CC divides data into five levels of increasing complexity, ranging from the chemical properties of compounds to their clinical outcomes. In between, it considers targets, off-targets, perturbed biological networks and several cell-based assays such as gene expression, growth inhibition and morphological profilings. In the CC, bioactivity data are expressed in a vector format, which naturally extends the notion of chemical similarity between compounds to similarities between bioactivity signatures of different kinds. We show how CC signatures can boost the performance of drug discovery tasks that typically capitalize on chemical descriptors, including target identification and library characterization. Moreover, we demonstrate and experimentally validate that CC signatures can be used to reverse and mimic biological signatures of disease models and genetic perturbations, options that are otherwise impossible using chemical information alone.
Phase-based coordination of hippocampal and neocortical oscillations during human sleep
Authors: Cox Roy , Rüber Theodor , Staresina Bernhard P , Fell Juergen 
Published: August 2019

AbstractDuring sleep, new memories undergo a gradual transfer from the hippocampus (HPC) to the neocortex (NC). Precisely timed neural oscillations interacting within and between these brain structures are thought to mediate this sleep-dependent memory consolidation, but exactly which sleep oscillations instantiate the HPC-NC dialog, and via what mechanisms, remains elusive. Employing invasive electroencephalography in ten neurosurgical patients across a full night of sleep, we identified three broad classes of phase-based HPC-NC communication. First, we observed interregional phase synchrony for non-rapid eye movement (NREM) spindles, N2 and rapid eye movement (REM) theta, and N3 beta activity. Second, and most intriguingly, we found asymmetrical N3 cross-frequency phase-amplitude coupling between HPC SOs and NC activity spanning the delta to high-gamma/ripple bands, but not in the opposite direction. Lastly, N2 theta and NREM spindle synchrony were themselves modulated by HPC SOs. These novel forms of phase-based interregional communication emphasize the role of HPC SOs in the HPC-NC dialog, and may offer a physiological basis for the sleep-dependent reorganization of mnemonic content.
Practicing one thing at a time: the secret to reward-based learning?
Authors: van der Kooij Katinka , van Mastrigt Nina M , Smeets Jeroen BJ 
Published: August 2019

AbstractBinary reward feedback on movement success is sufficient for learning in some simple reaching tasks, but not in some more complex ones. It is unclear what the critical conditions for learning are. Here, we ask how reward-based sensorimotor learning depends on the number of factors that are task-relevant. In a task that involves two factors, we test whether learning improves by giving feedback on each factor in a separate phase of the learning. Participants learned to perform a 3D trajectory matching task on the basis of binary reward-feedback in three phases. In the first and second phase, the reward could be based on the produced slant, the produced length or the combination of the two. In the third phase, the feedback was always based on the combination of the two factors. The results showed that reward-based learning did not depend on the number of factors that were task-relevant. Consistently, providing feedback on a single factor in the first two phases did not improve motor learning in the third phase.
CRISPR-Cas9 mediated genome editing in vancomycin resistantEnterococcus faecium
Authors: de Maat Vincent , Stege Paul B. , Dedden Mark , Hamer Maud , van Pijkeren Jan-Peter , Willems Rob J.L. , van Schaik Willem 
Published: August 2019

AbstractThe Gram-positive bacteriumEnterococcus faeciumis becoming increasingly prevalent as a cause of hospital-acquired, antibiotic-resistant infections. There is thus an urgent need to mechanistically characterize the traits that contribute to the emergence ofE. faeciumas a multidrug resistant opportunistic pathogen. A fundamental part of research intoE. faeciumbiology relies on the ability to generate targeted mutants, but this process is currently labour-intensive and time-consuming, taking 4 to 5 weeks per mutant. In this report we describe a method relying on the high recombination rates ofE. faeciumand the application of the Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-Cas9 genome editing tool to more efficiently generate targeted mutants in theE. faeciumchromosome. Using this tool and the multi-drug resistant clinicalE. faeciumstrain E745, we generated a deletion mutant in thelacLgene, which encodes the large subunit of theE. faeciumβ-galactosidase. Blue/white screening using 5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside (X-gal) could be used to distinguish between the wild-type andlacLdeletion mutant. We also inserted two copies ofgfpinto the intrinsicE. faeciummacrolide resistance genemsrCto generate stable green fluorescent cells. We conclude that CRISPR-Cas9 can be used to generate targeted genome modifications inE. faeciumin 3 weeks, with limited hands-on time. This method can potentially be implemented in other Gram-positive bacteria with high intrinsic recombination rates.