bluuebunny/crossref_metadata_2025_split huggingface dataset:
Molecular signatures of non-typeable Haemophilus influenzae lung adaptation in paediatric chronic lung disease
Authors: Aziz Ammar , Sarovich Derek S. , Nosworthy Elizabeth , Beissbarth Jemima , Chang Anne B. , Smith-Vaughan Heidi , Price Erin P. , Harris Tegan M. 
Published: April 2019

AbstractNon-typeable Haemophilus influenzae (NTHi), an opportunistic pathogen of the upper airways of healthy children, can infect the lower airways, driving chronic lung disease. However, the molecular basis underpinning NTHi transition from a commensal to a pathogen is not clearly understood. Here, we performed comparative genomic and transcriptomic analyses of 12 paired, isogenic NTHi strains, isolated from the nasopharynx (NP) and bronchoalveolar lavage (BAL) of 11 children with chronic lung disease, to identify convergent molecular signatures associated with lung adaptation. Comparative genomic analyses of the 12 NP-BAL pairs demonstrated that five were genetically identical, with the remaining seven differing by only 1 to 3 mutations. Within-patient transcriptomic analyses identified between 2 and 58 differentially expressed genes in 8 of the 12 NP-BAL pairs, including pairs with no observable genomic changes. Whilst no convergence was observed at the gene level, functional enrichment analysis revealed significant under-representation of differentially expressed genes belonging to Coenzyme metabolism, Function unknown, Translation, ribosomal structure and biogenesis Cluster of Orthologous Groups categories. In contrast, Carbohydrate transport and metabolism, Cell motility and secretion, Intracellular trafficking and secretion, and Energy production categories were over-represented. This observed trend amongst genetically-unrelated NTHi strains provides evidence of convergent transcriptional adaptation of NTHi to paediatric airways that deserves further exploration. Understanding the pathoadaptative mechanisms that NTHi employs to infect and persist in the lower paediatric airways is essential for devising targeted diagnostics and treatments aimed at minimising disease severity, and ultimately, preventing NTHi lung infections and subsequent chronic lung disease in children.
Hallmarks of slow translation initiation revealed in mitochondrially localizing mRNA sequences
Authors: Poulsen Thomas M. , Imai Kenichiro , Frith Martin C. , Horton Paul 
Published: April 2019

ABSTRACTThe mRNA of some, but not all, nuclear encoded mitochondrial proteins localize to the periphery of mitochondria. Previous studies have shown that both the nascent polypeptide chain and an mRNA binding protein play a role in this phenomenon, and have noted a positive correlation between mRNA length and mitochondrial localization. Here, we report the first investigation into the relationship between mRNA translation initiation rate and mRNA mitochondrial localization. Our results indicate that translation initiation promoting factors such as Kozak sequences are associated with cytosolic localization, while inhibiting factors such as 5′ UTR secondary structure correlate with mitochondrial localization. Moreover, the frequencies of nucleotides in various positions of the 5′ UTR show higher correlation with localization than the 3′ UTR. These results indicate that mitochondrial localization is associated with slow translation initiation. Interestingly this may help explain why short mRNAs, which are thought to initiate translation rapidly, seldom localize to mitochondria. We propose a model in which translating mRNA has reduced mobility and tends not to reach mitochondria. Finally, we explore this model with a simulation of mRNA diffusion using previously estimated translation initiation probabilities, confirming that our model can produce localization values similar to those measured in experimental studies.
Role of human induced pluripotent stem cell-derived spinal cord astrocytes in the functional maturation of motor neurons in a multielectrode array system
Authors: Taga Arens , Dastgheyb Raha , Habela Christa , Joseph Jessica , Richard Jean-Philippe , Gross Sarah K. , Lauria Giuseppe , Lee Gabsang , Haughey Norman , Maragakis Nicholas J. 
Published: April 2019

AbstractThe ability to generate human induced pluripotent stem cell (hiPSC)-derived neural cells displaying region-specific phenotypes is of particular interest for modeling central nervous system (CNS) biology in vitro. We describe a unique method by which spinal cord hiPSC-derived astrocytes (hiPSC-A) are cultured with spinal cord hiPSC-derived motor neurons (hiPSC-MN) in a multielectrode array (MEA) system to record electrophysiological activity over time. We show that hiPSC-A enhance hiPSC-MN electrophysiological maturation in a time-dependent fashion. The sequence of plating, density, and age in which hiPSC-As are co-cultured with MN, but not their respective hiPSC line origin, are factors that influence neuronal electrophysiology. When compared to co-culture with mouse primary spinal cord astrocytes, we observe an earlier and more robust electrophysiological maturation in the fully human cultures, suggesting that the human origin is relevant to the recapitulation of astrocyte/motor neuron cross-talk. Finally, we test pharmacological compounds on our MEA platform and observe changes in electrophysiological activity which confirm hiPSC-MN maturation. These findings are supported by immunocytochemistry and real time PCR studies in parallel cultures demonstrating human astrocyte mediated changes in the structural maturation and protein expression profiles of the neurons. Interestingly, this relationship is reciprocal and co-culture with neurons influences astrocyte maturation as well. Taken together these data indicate that in a human in vitro spinal cord culture system, astrocytes alter hiPSC-MN maturation in a time-dependent and species specific manner and suggest a closer approximation of in vivo conditions.Main PointsWe developed a method for the co-culture of human iPSC-A/MN for multielectrode array recordings.The morphological, molecular, pharmacological, and electrophysiological characterization of the co-cultures suggests bidirectional maturation.
Modeling the language of life – Deep Learning Protein Sequences
Authors: Heinzinger Michael , Elnaggar Ahmed , Wang Yu , Dallago Christian , Nechaev Dmitrii , Matthes Florian , Rost Burkhard 
Published: April 2019

AbstractBackgroundOne common task in Computational Biology is the prediction of aspects of protein function and structure from their amino acid sequence. For 26 years, most state-of-the-art approaches toward this end have been marrying machine learning and evolutionary information. The retrieval of related proteins from ever growing sequence databases is becoming so time-consuming that the analysis of entire proteomes becomes challenging. On top, evolutionary information is less powerful for small families, e.g. for proteins from theDark Proteome.ResultsWe introduce a novel way to represent protein sequences as continuous vectors (embeddings) by using the deep bi-directional model ELMo taken from natural language processing (NLP). The model has effectively captured the biophysical properties of protein sequences from unlabeled big data (UniRef50). After training, this knowledge is transferred to single protein sequences by predicting relevant sequence features. We refer to these new embeddings asSeqVec(Sequence-to-Vector) and demonstrate their effectiveness by training simple convolutional neural networks on existing data sets for two completely different prediction tasks. At the per-residue level, we significantly improved secondary structure (for NetSurfP-2.0 data set: Q3=79%±1, Q8=68%±1) and disorder predictions (MCC=0.59±0.03) over methods not using evolutionary information. At the per-protein level, we predicted subcellular localization in ten classes (for DeepLoc data set: Q10=68%±1) and distinguished membrane-bound from water-soluble proteins (Q2= 87%±1). All results built upon the embeddings gained from the new toolSeqVecneither explicitly nor implicitly using evolutionary information. Nevertheless, it improved over some methods using such information. Where the lightning-fastHHblitsneeded on average about two minutes to generate the evolutionary information for a target protein,SeqVeccreated the vector representation on average in 0.03 seconds.ConclusionWe have shown that transfer learning can be used to capture biochemical or biophysical properties of protein sequences from large unlabeled sequence databases. The effectiveness of the proposed approach was showcased for different prediction tasks using only single protein sequences.SeqVecembeddings enable predictions that outperform even some methods using evolutionary information. Thus, they prove to condense the underlying principles of protein sequences. This might be the first step towards competitive predictions based only on single protein sequences.AvailabilitySeqVec:https://github.com/mheinzinger/SeqVecPrediction server:https://embed.protein.properties
Crosslinking actin networks produces compressive force
Authors: Ma Rui , Berro Julien 
Published: April 2019

AbstractActin has been shown to be essential for clathrin-mediated endocytosis in yeast. However, actin polymerization alone is likely insufficient to produce enough force to deform the membrane against the huge turgor pressure of yeast cells. In this paper, we used Brownian dynamics simulations to demonstrate that crosslinking of a meshwork of non-polymerizing actin filaments is able to produce compressive forces. We show that the force can be up to thousands of piconewtons if the crosslinker has a high stiffness. The force decays over time as a result of crosslinker turnover, and is a result of converting chemical binding energy into elastic energy.
Ultraviolet light degrades the mechanical and structural properties of human stratum corneum
Authors: Lipsky Z.W. , German G. K. 
Published: April 2019

AbstractProlonged exposure of human skin to sunlight causes photodamage, which induces the early onset of wrinkles and increased tissue fragility. While solar ultraviolet (UV) light is considered to have the most damaging effect, the UV range that is most harmful remains a topic of significant debate. In this study, we take a first step towards elucidating biomechanical photoageing effects by quantifying how exposure to different UV ranges and dosages impacts the mechanical and structural properties of human stratum corneum (SC), the most superficial skin layer. Mechanical testing reveals that irradiation of isolated human SC to UVA (365 nm), UVB (302 nm), or UVC (265 nm) light with dosages of up to 4000 J/cm2notably alters the elastic modulus, fracture stress, fracture strain, and work of fracture. For equivalent incident dosages, UVC degrades SC the greatest. However, upon discounting reflected and transmitted components of the incident light, a generalized scaling law relating the photonic energy absorbed by the SC to the energy cost of tissue fracture emerges. This relationship indicates that no one UV range is more damaging than another. Rather, the magnitude of absorbed UV energy governs the degradation of tissue mechanical integrity. Subsequent structural studies are performed to elucidate the cause of this mechanical degradation. UV absorption scales with the spatial dispersion of desmoglein 1 (Dsg 1), a component of corneocyte cell-cell junctions, away from intercellular sites. Combining both scaling laws, we establish a mechanical-structural model capable of predicting UV induced tissue mechanical integrity from Dsg 1 dispersion.Statement of SignificancePhotoageing from the sun can produce early onset of skin wrinkles and an increase in tissue fragility that heightens the risk of rupture. While solar ultraviolet (UV) light is considered to have the most damaging effect, the UV range that is most harmful remains a topic of significant debate. In this study, we elucidate photoageing effects by quantifying how exposure to different UV ranges and dosages impacts the mechanical and structural properties of human stratum corneum (SC), the most superficial skin layer. Results establish a mechanical-structural model that relates the amount of UV energy absorbed by the tissue, irrespective of UV range, to the energy cost of tissue fracture and spatial dispersion of desmoglein 1.
Time to monitor livestock carcasses for biodiversity conservation and public health
Authors: Mateo‐Tomás Patricia , Olea Pedro P. , López‐Bao José Vicente 
Published: April 2019

Abstract

Law enforcement and integration of environmental issues into other policies able to affect species and ecosystems are cornerstones for the effective protection of biodiversity. We illustrate the necessity of monitoring and improving such enforcement and integration through the example of the European sanitary policies for managing livestock carcasses after the “mad cow disease” outbreak while supporting scavengers’ conservation.

Continuous updates of EU sanitary regulations for reconciling scavenger conservation and public health have led to actions whose implementation and monitoring rely on delineating scavenger feeding zones and estimating livestock mortality and scavenger feeding requirements (SFRs).

However, the lack of clear and homogeneous criteria to calculate SFRs results in remarkable variations (e.g. of up to >450% in some regions). Although we offer a prospective approach to improve SFR calculations, we show here the high levels of uncertainty in these estimates based on the imperfect information available regarding scavengers’ ecology.

Synthesis and applications. The multiple socioeconomic and ecological impacts of sanitary crises such as “mad cow disease” underpin the need for high‐level political commitments to guarantee public health, food security and biodiversity conservation. To effectively integrate scavenger conservation into sanitary policies, the shortfalls here detected when estimating scavenger feeding requirements should be addressed. We recommend policymakers establish systematic on‐ground carcass monitoring for detecting implementation gaps (e.g. food shortages compromising scavenger conservation, potential risks of disease transmission), and to modify EU sanitary regulations accordingly. This monitoring would increase knowledge on scavenging ecology and epidemiological surveillance while enhancing cross‐compliance. Lessons learned in Europe may help to integrate conservation issues into other sectorial policies worldwide.
Multidimensional ecological analyses demonstrate how interactions between functional traits shape fitness and life history strategies
Authors: Pistón Nuria , de Bello Francesco , Dias André T. C. , Götzenberger Lars , Rosado Bruno H. P. , de Mattos Eduardo A. , Salguero‐Gómez Roberto , Carmona Carlos P. 
Published: April 2019

Abstract

Traditionally, trait‐based studies have explored single‐trait‐fitness relationships. However, this approximation in the study of fitness components is often too simplistic, given that fitness is determined by the interplay of multiple traits, which could even lead to multiple functional strategies with comparable fitness (i.e. alternative designs).

Here we suggest that an analytical framework using boosted regression trees (BRT) can prove more informative to test hypotheses on trait combinations compared to standard linear models. We use two published datasets for comparisons: a botanical garden dataset with 557 plant species (Herben, 2012, Journal of Ecology, 100, 1522) and an observational dataset with 83 plant species (Adler, 2014, Proceedings of the National Academy of Sciences, 111, 740).

Using the observational dataset, we found that BRTs predict the role of traits on the relative importance of survival, growth and reproduction for population growth rate better than linear models do. Moreover, we split species cultivated in different habitats within the botanical garden and observed that seed and vegetative reproduction depended on trait combinations in most habitats. Our analyses suggest that, while not all traits impact fitness components to the same degree, it is crucial to consider traits that represent different ecological dimensions.

Synthesis. The analysis of trait combinations, and corresponding alternative designs via BRTs, represent a promising approach for understanding and managing functional changes in vegetation composition through measurement of suites of relatively easily measurable traits.
Functional diversity promotes phytoplankton resource use efficiency
Authors: Ye Lin , Chang Chun‐Wei , Matsuzaki Shin‐ichiro S. , Takamura Noriko , Widdicombe Claire E. , Hsieh Chih‐hao 
Published: April 2019

AbstractUnderstanding the relationship between biodiversity and ecosystem functioning (BEF) is a central topic in ecology. Multi‐trait–based functional diversity has been proposed to improve mechanistic understanding of the BEF relationship; however, how trait‐based functional diversity affects ecosystem functioning and processes has rarely been addressed in aquatic ecosystems.Here, we examined the causal relationships between three phytoplankton functional diversity indices (FAD2, functional diversity based on dendrograms [FDc], FRic) and Shannon diversity index versus resource use efficiency for nitrogen (RUEN), phosphorus (RUEP) and silicate (RUESi), with monthly long‐term datasets from the marine (Western English Channel, 2000–2014) and freshwater (Lake Kasumigaura, 1984–2012) ecosystems.We employed Convergent Cross Mapping (CCM), a novel method developed for identifying causality for nonlinear dynamical systems; this is in contrast to linear approaches that cannot distinguish causality from correlation. CCM found that FDc is the most robust functional diversity index among the selected functional diversity indices (FAD2, FDc, FRic) in predicting phytoplankton resource use efficiency and exhibited a much stronger causal effect than the Shannon index.Furthermore, scenario exploration analysis indicates that most causal effects from phytoplankton diversity indices on resource use efficiency (RUEN, RUEPand RUESi) are on average positive, and FDc exhibited the most consistent positive causal effects on phytoplankton resource efficiency in both marine and freshwater ecosystems. Thus, increasing FDc can enhance phytoplankton resource use efficiency in aquatic ecosystems.Synthesis.Our results show significant causal effects of functional diversity on phytoplankton resource use efficiency in both marine and freshwater ecosystems. Among all selected functional diversity indices, functional diversity based on dendrogram is the most robust functional diversity index in promoting phytoplankton resource efficiency. Our study provides empirical evidences in natural aquatic systems that trait‐based functional diversity represents better species niche partitioning than the Shannon index and thereafter enhances resource use efficiency. This finding can improve our understanding on trophic transfer and nutrient cycling in aquatic ecosystems.
‘You certainly don't go back to the doctor once you've been told, “I'll never understand women like you.”’ Seeking candidacy and structural competency in the dynamics of domestic abuse disclosure
Authors: Mackenzie Mhairi , Gannon Maria , Stanley Nicky , Cosgrove Katie , Feder Gene 
Published: April 2019

AbstractA reticence on the part of women to disclose domestic abuse (DA) to family doctors, allied to front‐line responses that do not always reflect an understanding of the structure and dynamics of DA, hampers the provision of professional support. Using data from 20 qualitative interviews with women who have experienced DA, this paper explores their discourse about interacting with family doctors. It is the first study to explore firsthand accounts of these interactions through Dixon Woods’ lens of candidacy. It finds disclosure to be inherently dynamic as a process and expands the candidacy lens by considering the: (i) conflicting candidacies of victims and perpetrators; (ii) diversionary disclosure tactics deployed by perpetrators and, (iii) the potential role of General Practitioner (GPs) in imagining candidacies from a structural perspective. By exploring the dynamics of disclosure through the concept of ‘structural competency’ it finds that in encounters with women who have experienced abuse GPs ineluctably communicate their views on the legitimacy of women's claims for support; these in turn shape future candidacy and help‐seeking. Greater GP awareness of the factors creating and sustaining abuse offers the potential for better care and reduced stigmatisation of abused women.
Prospective study of gestational diabetes and fatty liver scores 9 to 16 years after pregnancy
Authors: Donnelly Sarah R. , Hinkle Stefanie N. , Rawal Shristi , Grunnet Louise G. , Chavarro Jorge E. , Vaag Allan , Wu Jing , Damm Peter , Mills James L. , Li Mengying , Bjerregaard Anne A. , Thuesen Anne Cathrine B. , Gore‐Langton Robert E. , Francis Ellen C. , Ley Sylvia H. , Hu Frank B. , Tsai Michael Y. , Olsen Sjurdur F. , Zhang Cuilin 
Published: April 2019

AbstractBackgroundWomen with gestational diabetes mellitus (GDM) may be at an increased risk of liver complications because chronic hyperglycemia is a risk factor for liver fat accumulation and potential liver dysfunction. Large prospective studies examining liver fat accumulation following a GDM pregnancy are lacking.MethodsThe Diabetes & Women's Health Study (2012‐2014) examined the association between GDM and subsequent fatty liver scores among 607 women with and 619 women without GDM in the Danish National Birth Cohort. Nine to 16 years postpartum, a clinical examination was performed, with measurement of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and γ‐glutamyl transferase, from which fatty liver scoring indices were calculated to assess liver fat score, fatty liver index, hepatic steatosis index, and liver fat percentage. Relative risks (RR) with 95% confidence intervals (CI) for elevated liver scoring indices by GDM status were assessed adjusting for major risk factors, including prepregnancy body mass index.ResultsWomen with prior GDM had higher adjusted ALT and AST levels than women without GDM (by 6.7% [95% CI 1.7‐12.0] and 4.8% [95% CI 0.6‐9.1], respectively). Women with GDM also had adjusted increased risks for elevated liver fat score (RR 2.34; 95% CI 1.68‐3.27), fatty liver index (RR 1.59; 95% CI 1.27‐1.99), and hepatic steatosis index (RR 1.44; 95% CI 1.21‐1.71).ConclusionsWomen with GDM during pregnancy were at an increased risk for fatty liver 9 to 16 years postpartum. Gestational diabetes mellitus may serve as another risk indicator for the early identification and prevention of liver fat accumulation.