bluuebunny/crossref_metadata_2025 huggingface dataset:
Dual‐transformer soft‐switching DC–DC resonant converter with multiple resonant elements
Authors: Wang Yifeng , Han Fuqiang , Yang Liang , Wang Chengshan , Zhou Biao
Published: October 2018

A novel dual‐transformer DC–DC converter with multiple resonant elements is proposed. Owing to the multi‐resonant feature, the converter is able to achieve a wide DC voltage gain range through the proper selection of resonant parameters. The operating frequency is restricted within a narrow scope. The potential high‐frequency losses are avoided, which apparently contributes to efficiency improvement. Besides, since the proposed converter contains more resonant frequencies, it is possible to additionally transmit the third‐order active power to the load. All the power switches have realised the turn‐on soft‐switching, while the diodes obtain the soft‐switching or quasi‐soft‐switching for both the turn‐on and turn‐off periods. To verify the theoretical analyses, a 500 W prototype is established in the laboratory. The experimental results demonstrate that the proposed converter can maintain relatively high efficiency (∼95%) among a wide load range. The highest efficiency reaches 95.4% at 300 W.
Electric vehicles in smart grid: a survey on charging load modelling
Authors: Xiang Yue , Hu Shuai , Liu Youbo , Zhang Xin , Liu Junyong
Published: October 2018

Electric vehicles (EVs) have been rapidly developed during the last few years due to the low‐carbon industry and smart grid initiatives. Meanwhile, the impact of large‐scale EVs' integration on the reliability and safety of power grids is becoming increasingly prominent. To address and solve these problems, challenges on EV charging control have been presented. Besides, the EV charging load modelling with improved accuracy and rationality is required. To investigate the influencing factors of EV charging load, this survey summarises the existing EV charging load modelling methods. In addition, a new research framework for a scale EV evolution model of charging load is proposed, with an emphasis on reducing the deficiencies of the existing research in dealing with the EV scale development. Moreover, the future research prospect of EV charging load modelling on power system planning, operation, and market design has also been discussed.
Chemoenzymatic synthesis of hydroxytyrosol monoesters and their suppression effect on nitric oxide production stimulated by lipopolysaccharides
Authors: Sakakura Ayaka , Pauze Martin , Namiki Atsuhiro , Funakoshi-Tago Megumi , Tamura Hiroomi , Hanaya Kengo , Higashibayashi Shuhei , Sugai Takeshi
Published: October 2018

Fatty acid monoesters of hydroxytyrosol [2-(3,4-dihydroxyphenyl)ethanol] were synthesized in two steps from tyrosol (4-hydroxyphenylethanol) by successive Candida antarctica lipase B-catalyzed chemoselective acylation on the primary aliphatic hydroxy group over phenolic hydroxy group in tyrosol, and 2-iodoxybenzoic acid (IBX)-mediated hydroxylation adjacent to the remaining free phenolic hydroxy group. Examination of their suppression effects on nitric oxide production stimulated by lipopolysaccharides in RAW264.7 cells showed that hydroxytyrosol butyrate exhibited the highest inhibition (IC50 7.0 μM) among the tested compounds.
Poly-4-Hydroxybutyrate (P4HB) Scaffold Internal Support: Preliminary Experience with Direct Implant Opposition During Complex Breast Revisions
Authors: Nair Narayanan M , Mills Daniel C
Published: October 2018

Background

The GalaFLEX scaffold is a mesh composed of resorbable poly-4-hydroxybutyrate (P4HB) monofilament fibers that aids in providing immediate internal soft tissue support, similar to that offered by an underwire bra, after breast reduction, lift, or augmentation.

Objectives

Our goal was to explore the possibility of using GalaFLEX as an internal support to prevent future sagging, predominantly in the lower pole of the breast. This preliminary study investigated GalaFLEX as a direct alternative to implants in a variety of complex revisional breast cases. Our intention was to establish a safety and efficacy profile in an effort to promote further investigation.

Methods

A retrospective case series of 5 patients over 2 years were evaluated. Inclusion criteria were capsular contracture with concerns over soft tissue coverage and future ptosis, along with complicated muscle coverage deficits secondary to plane switching.

Results

A retrospective review of photographs taken at the most recent follow-up consistently showed retention of implant position and soft implants. Additionally, patients presented with a mean ± SD Baker Grade Contraction score of 2.8 ± 0.9189 preoperatively compared with a score of 1 ± 0 postoperatively.

Conclusions

This preliminary study shows the initial safety of GalaFLEX but indicates the need for a multicenter, exhaustive study. Its versatility for complex revisional cases combined with acceptable aesthetic outcomes makes GalaFLEX an invaluable tool for plastic surgeons to consider.

Level of Evidence: 4
SCALOP: sequence-based antibody canonical loop structure annotation
Authors: Wong Wing Ki , Georges Guy , Ros Francesca , Kelm Sebastian , Lewis Alan P , Taddese Bruck , Leem Jinwoo , Deane Charlotte M
Published: October 2018

Motivation

Canonical forms of the antibody complementarity-determining regions (CDRs) were first described in 1987 and have been redefined on multiple occasions since. The canonical forms are often used to approximate the antibody binding site shape as they can be predicted from sequence. A rapid predictor would facilitate the annotation of CDR structures in the large amounts of repertoire data now becoming available from next generation sequencing experiments.

Results

SCALOP annotates CDR canonical forms for antibody sequences, supported by an auto-updating database to capture the latest cluster information. Its accuracy is comparable to that of a standard structural predictor but it is 800 times faster. The auto-updating nature of SCALOP ensures that it always attains the best possible coverage.

Availability and implementation

SCALOP is available as a web application and for download under a GPLv3 license at opig.stats.ox.ac.uk/webapps/scalop.

Supplementary information

Supplementary data are available at Bioinformatics online.
Extended optical/NIR observations of Type Iax supernova 2014dt: Possible signatures of a bound remnant
Authors: Kawabata Miho , Kawabata Koji S , Maeda Keiich , Yamanaka Masayuki , Nakaoka Tatsuya , Takaki Katsutoshi , Fukushima Daiki , Kojiguchi Naoto , Masumoto Kazunari , Matsumoto Katsura , Akitaya Hiroshi , Itoh Ryosuke , Kanda Yuka , Moritani Yuki , Takata Koji , Uemura Makoto , Ui Takahiro , Yoshida Michitoshi , Hattori Takashi , Lee Chien-Hsiu , Tominaga Nozomu , Nomoto Ken’ichi
Published: October 2018

We present optical and near-infrared observations of the nearby Type Iax supernova (SN) 2014dt from 14 to 410 d after the maximum light. The velocities of the iron absorption lines in the early phase indicated that SN 2014dt showed slower expansion than the well-observed Type Iax SNe 2002cx, 2005hk, and 2012Z. In the late phase, the evolution of the light curve and that of the spectra were considerably slower. The spectral energy distribution kept roughly the same shape after ∼100 d, and the bolometric light curve flattened during the same period. These observations suggest the existence of an optically thick component that almost fully trapped the γ-ray energy from 56Co decay. These findings are consistent with the predictions of the weak deflagration model, leaving a bound white dwarf remnant after the explosion.
ESTIMATION OF PATIENT LENS DOSE ASSOCIATED WITH C-ARM CONE-BEAM COMPUTED TOMOGRAPHY USAGE DURING INTERVENTIONAL NEURORADIOLOGY
Authors: Kawauchi Satoru , Chida Koichi , Moritake Takashi , Matsumaru Yuji , Hamada Yusuke , Sakuma Hideyuki , Yoda Shogo , Sun Lue , Sato Masayuki , Tsuruta Wataro
Published: October 2018

The purpose of this study was to investigate the dose distribution and lens doses associated with C-arm cone-beam computed tomography (CBCT), using a head phantom, and to estimate the contribution ratio of C-arm CBCT to each patient’s lens dose during interventional neuroradiology (‘lens dose ratio’) in 109 clinical cases. In the phantom study, the peak skin doses and respective right and left lens doses of C-arm CBCT were as follows: 63.0 ± 1.9 mGy, 19.7 ± 1.4 mGy and 21.9 ± 0.8 mGy in whole brain C-arm CBCT and 39.2 ± 1.4 mGy, 4.7 ± 0.9 mGy and 3.6 ± 0.3 mGy in high-resolution C-arm CBCT. In the clinical study, the lens dose ratios were 25.4 ± 8.7% in the right lens and 19.1 ± 9.8% in the left lens. This study shows that, on average, ~25% of patients’ total lens dose was contributed by C-arm CBCT.
Roy Porter Student Prize Essay How (Not) to Survive a Plague: The Theology of Fleeing Disease in Sixteenth-century England
Authors: Weinreich Spencer J
Published: October 2018

Early modern medicine favoured flight as the best prophylactic against epidemic disease. Theologically, however, flight savoured of an attempt to defy divine providence, or a dereliction of Christian charity, while staying could seem an act of presumption or recklessness. This essay studies six theologians whose writings on the issue circulated in sixteenth-century England. Long dismissed as inconclusive and derivative, these ‘flight theologies’ can be better understood as products of theological principle and communal experience, whose combined influence precluded definitive prescriptions. Instead, authors marshalled the rhetoric of ‘conscience’ to displace the decision back onto their readers, while retaining interpretive authority over the key factors of Scripture and personal obligations. Flight theology thus seeks less to solve a practical problem, than to produce a particular kind of political subjectivity, bound to the community and predicated on persuasion. In so doing, the discourse fuelled the emergence of an early modern English public sphere.
Women’s Work in Fragile States: Evidence from a Firm-Level Dataset in Somaliland
Authors: Nelson-Nuñez Jami , Cyr Christopher
Published: October 2018

What explains variation in women’s employment in fragile states with conflict-affected histories and limited state capacity? Employment builds stability and including women in labor markets can yield peace dividends. We use data from a firm-level survey in Somaliland, a de facto state in northern Somalia, to investigate why some firms employ more women than others. We analyze firm characteristics affected by state fragility and conflict, including female firm ownership, diaspora ownership and management, and limited access to services. This research contributes to our understanding of economic growth in fragile contexts and identifies opportunities to address gender inequalities in the developing world.
Design of RNA hairpin modules that predictably tune translation in yeast
Authors: Weenink Tim , van der Hilst Jelle , McKiernan Robert M , Ellis Tom
Published: October 2018

Modular parts for tuning translation are prevalent in prokaryotic synthetic biology but lacking for eukaryotic synthetic biology. Working in Saccharomyces cerevisiae yeast, we here describe how hairpin RNA structures inserted into the 5′ untranslated region (5′UTR) of mRNAs can be used to tune expression levels by 100-fold by inhibiting translation. We determine the relationship between the calculated free energy of folding in the 5′UTR and in vivo protein abundance, and show that this enables rational design of hairpin libraries that give predicted expression outputs. Our approach is modular, working with different promoters and protein coding sequences, and outperforms promoter mutation as a way to predictably generate a library where a protein is induced to express at a range of different levels. With this new tool, computational RNA sequence design can be used to predictably fine-tune protein production for genes expressed in yeast.
Computational modeling of the crosstalk between macrophage polarization and tumor cell plasticity in the tumor microenvironment
Authors: Li Xuefei , Jolly Mohit Kumar , George Jason T. , Pienta Kenneth J. , Levine Herbert
Published: October 2018

Tumor microenvironments contain multiple cell types interacting among one another via different signaling pathways. Furthermore, both cancer cells and different immune cells can display phenotypic plasticity in response to these communicating signals, thereby leading to complex spatiotemporal patterns that can impact therapeutic response. Here, we investigate the crosstalk between cancer cells and macrophages in a tumor microenvironment through in silico (computational) co-culture models. In particular, we investigate how macrophages of different polarization (M1 vs. M2) can interact with epithelial-mesenchymal plasticity of cancer cells, and conversely, how cancer cells exhibiting different phenotypes (epithelial vs. mesenchymal) can influence the polarization of macrophages. Based on interactions documented in the literature, an interaction network of cancer cells and macrophages is constructed. The steady states of the network are then analyzed. Various interactions were removed or added into the constructed-network to test the functions of those interactions. Also, parameters in the mathematical models were varied to explore their effects on the steady states of the network. In general, the interactions between cancer cells and macrophages can give rise to multiple stable steady-states for a given set of parameters and each steady state is stable against perturbations. Importantly, we show that the system can often reach one type of stable steady states where cancer cells go extinct. Our results may help inform efficient therapeutic strategies.
A 117 year retrospective analysis of Pennsylvania tick community dynamics
Authors: Pak Damie , Jacobs Steven B. , Sakamoto Joyce M.
Published: October 2018

Background

Tick-borne diseases have been increasing at the local, national, and global levels. Researchers studying ticks and tick-borne disease need a thorough knowledge of the pathogens, vectors, and epidemiology of disease spread. Three surveillance approaches are commonly used to provide insight into tick-borne disease risk: human disease case surveillance, active tick surveillance, and passive tick surveillance. Long-term passive surveillance can provide up-to-date data on the spatial variability and temporal dynamics of ectoparasite communities and shed light into the ecology of rarer tick species. We present a retrospective analysis on compiled data of ticks from Pennsylvania over the last 117 years.

Methods

We compiled data from ticks collected during tick surveillance research, and from citizen-based submissions to the Penn State University Department of Entomology (PSUEnt). Specimens were deposited at the PSUEnt arthropod collections that eventually became The Frost Entomological Museum. While most of the specimens were submitted by the public, a subset of the data were collected through active methods (flagging or dragging, or removal of ticks from wildlife). We analyzed all data from 1900-2017 for tick community composition, host associations, and spatio-temporal dynamics.

Results

In total there were 4,491 submission lots consisting of 7,132 tick specimens. Twenty-four different species were identified, with the large proportion of submissions represented by five tick species. We observed a shift in tick community composition in which the dominant species of tick (Ixodes cookei) was overtaken in abundance byDermacentor variabilisin the early 1990s, and then replaced in abundance byI. scapularis. We analyzed host data and identified overlaps in host range amongst tick species, suggesting potential hubs of pathogen transfer between different tick vectors and their reservoir hosts.

Conclusions

We highlight the importance of long-term passive tick surveillance in investigating the ecology of both common and rare tick species. Information on the geographic distribution, host-association, and seasonality of the tick community can help researchers and health-officials to identify high-risk areas.
A free boundary model of epithelial dynamics
Authors: Baker Ruth E , Parker Andrew , Simpson Matthew J
Published: October 2018

In this work we analyse a one-dimensional, cell-based model of an epithelial sheet. In this model, cells interact with their nearest neighbouring cells and move deterministically. Cells also proliferate stochastically, with the rate of proliferation specified as a function of the cell length. This mechanical model of cell dynamics gives rise to a free boundary problem. We construct a corresponding continuum-limit description where the variables in the continuum limit description are expanded in powers of the small parameter 1/N, where N is the number of cells in the population. By carefully constructing the continuum limit description we obtain a free boundary partial differential equation description governing the density of the cells within the evolving domain, as well as a free boundary condition that governs the evolution of the domain. We show that care must be taken to arrive at a free boundary condition that conserves mass. By comparing averaged realisations of the cell-based model with the numerical solution of the free boundary partial differential equation, we show that the new mass-conserving boundary condition enables the coarsegrained partial differential equation model to provide very accurate predictions of the behaviour of the cell-based model, including both evolution of the cell density, and the position of the free boundary, across a range of interaction potentials and proliferation functions in the cell based model.
Cleft lip/palate and educational attainment: cause, consequence, or correlation? A Mendelian randomization study
Authors: Dardani Christina , Howe Laurence J , Stergiakouli Evie , Wren Yvonne , Humphries Kerry , Davies Amy , Ho Karen , Mangold Elisabeth , Ludwig Kerstin U , Relton Caroline L , Smith George Davey , Lewis Sarah J , Sandy Jonathan , Davies Neil M , Sharp Gemma C
Published: October 2018

Importance

Previous studies have found that children born with a non-syndromic form of cleft lip and/or palate have lower-than-average educational attainment. These differences could be due to a genetic predisposition to low intelligence and academic performance, factors arising due to the cleft phenotype (such as school absence, social stigmatization and impaired speech and language development), or confounding by the prenatal environment. A clearer understanding of this mechanism will inform development of interventions to improve educational attainment in individuals born with a cleft, which could have wide-ranging knock-on effects on their quality of life.

Objective

To assess evidence for the hypothesis that common variant genetic liability to non-syndromic cleft lip with or without cleft palate (nsCL/P) influences educational attainment.

Design

Using summary data from genome-wide association studies (GWAS), we performed Linkage Disequilibrium (LD)-score regression and two-sample Mendelian randomization to evaluate the relationship between genetic liability to nsCL/P (GWAS n=3,987) and educational attainment (GWAS n=766,345), and intelligence (GWAS n=257,828).

Results

There was little evidence for shared genetic aetiology between nsCL/P and educational attainment (rg −0.03, 95% CI −0.14 to 0.08, P 0.58; βMR 0.002, 95% CI −0.001 to 0.005, P 0.417) or intelligence (rg −0.01, 95% CI −0.12 to 0.10, P 0.85; βMR 0.002, 95% CI −0.010 to 0.014, P 0.669).

Conclusions and relevance

Common genetic variants are unlikely to predispose individuals born with nsCL/P to low educational attainment or intelligence. This information will help tailor clinical-, school-, social- and family-level interventions to improve educational attainment in this group.

Key Points

Question

Do children born with a non-syndromic cleft lip with or without palate (nsCL/P) have lower-than average academic achievement because of an underlying genetic predisposition to educational attainment and/or intelligence?

Findings

There was little evidence for shared common variant genetic correlation between nsCL/P, educational attainment and intelligence.

Meaning

Common genetic variants are unlikely to predispose individuals born with nsCL/P to low educational attainment or intelligence. This information will help tailor clinical-, school-, social- and family-level interventions to improve educational attainment in this group.
XTalkiiS: a tool for finding data-driven cross-talks between intra-/inter-species pathways
Authors: Azad A. K. M.
Published: October 2018

Cell-cell communication via pathway cross-talks within a single species have been studied in silico recently to decipher various disease phenotype. However, computational prediction of pathway cross-talks among multiple species in a data-driven manner is yet to be explored. In this article, I present XTalkiiS (Cross-talks between inter-/intra species pathways), a tool to automatically predict pathway cross-talks from data-driven models of pathway network, both within the same organism (intra-species) and between two organisms (inter-species). XTalkiiS starts with retrieving and listing up-to-date pathway information in all the species available in KEGG database using RESTful APIs (exploiting KEGG web services) and an in-house built web crawler. I hypothesize that data-driven network models can be built by simultaneously quantifying co-expression of pathway components (i.e. genes/proteins) in matched samples in multiple organisms. Next, XTalkiiS loads a data-driven pathway network and applies a novel cross-talk modelling approach to determine interactions among known KEGG pathways in selected organisms. The potentials of XTalkiiS are huge as it paves the way of finding novel insights into mechanisms how pathways from two species (ideally host-parasite) may interact that may contribute to the various phenotype of interests such as malaria disease. XTalkiiS is made open sourced at https://github.com/Akmazad/XTalkiiS and its binary files are freely available for downloading from https://sourceforge.net/projects/xtalkiis/.
Gorilla in our Midst: An online behavioral experiment builder
Authors: Anwyl-Irvine Alexander , Massonnié Jessica , Flitton Adam , Kirkham Natasha , Evershed Jo
Published: October 2018

Behavioural researchers are increasingly conducting their studies online to gain access to large and diverse samples that would be difficult to get in a laboratory environment. However, there are technical access barriers to building experiments online, and web-browsers can present problems for consistent timing – an important issue with reaction time-sensitive measures. For example, to ensure accuracy and test-retest reliability in presentation and response recording, experimenters need a working knowledge of programming languages such as JavaScript. We review some of the previous and current tools for online behavioural research, and how well they address the issues of usability and timing. We then present The Gorilla Experiment Builder (gorilla.sc) a fully tooled experiment authoring and deployment platform, designed to resolve many timing issues, and make reliable online experimentation open and accessible to a wider range of technical abilities. In order to demonstrate the platform’s aptitude for accessible, reliable and scalable research, we administered the task with a range of participant groups (primary school children and adults), settings (without supervision, at home, and under supervision, in schools and public engagement events), equipment (own computers, computer supplied by researcher), and connection types (personal internet connection, mobile phone 3G/4G). We used a simplified flanker task, taken from the Attentional Networks Task (Rueda, Posner, & Rothbart, 2004). We replicated the ‘conflict network’ effect in all these populations, demonstrating the platform’s capability to run reaction time-sensitive experiments. Unresolved limitations of running experiments online are then discussed, along with potential solutions, and some future features of the platform.
A Universal Algorithm to Detect Rare or Novel Cell Types in High-Throughput Single-Cell Gene Expression Data
Authors: Weiss Zoe , Tsoucas Daphne
Published: October 2018

Detecting rare cell types would allow early disease detection of cancers and infections, identification of new cell types, and a deepened understanding of cell differentiation. We developed a universal algorithm to identify rare cell types from a wide variety of single-cell ’omics’ data. We validated our algorithm on single-cell qPCR data from mouse hematopoietic cells and single-cell RNA-seq data from human glioblastoma tumors cells, both with expression values from an ample number of genes. We then applied our algorithm to seq-FISH data from mouse hippocampus cells containing expression values from only 121 genes. Our algorithm detected rare cell types including a putative new hippocampal cell type.

Author summary

Rare cell type detection would advance early disease diagnosis (e.g., cancer, infection), allow identification of new cell types, and increase understanding of cell differentiation. Current computational methods can detect common cell types, but it remains a challenge to detect rare cell types within cell populations, especially with expression data from a relatively small number of genes. We created a powerful algorithm to detect rare cell types in a population of cells. We validated our algorithm on data from mouse blood stem cells and human glioblastoma tumors cells. When we applied our algorithm to mouse hippocampus data containing expression values from only 121 genes, we detected a putative new brain cell type that no previous algorithm has identified. Our universal algorithm can now be applied to a wide range of data to detect the early onset of diseases and discover new cell types.
Marked point process filter for clusterless and adaptive encoding-decoding of multiunit activity
Authors: Arai Kensuke , Liu Daniel F. , Frank Loren M. , Eden Uri T.
Published: October 2018

Real-time, closed-loop experiments can uncover causal relationships between specific neural activity and behavior. An important advance in realizing this is the marked point process filtering framework which utilizes the “mark” or the waveform features of unsorted spikes, to construct a relationship between these features and behavior, which we call the encoding model. This relationship is not fixed, because learning changes coding properties of individual neurons, and electrodes can physically move during the experiment, changing waveform characteristics. We introduce a sequential, Bayesian encoding model which allows incorporation of new information on the fly to adapt the model in real time. A possible application of this framework is to the decoding of the contents of hippocampal ripples in rats exploring a maze. During physical exploration, we observe the marks and positions at which they occur, to update the encoding model, which is employed to decode contents of ripples when rats stop moving, and switch back to updating the model once the rat starts moving again.
Mindfulness meditators do not show differences in electrophysiological measures of error processing
Authors: Bailey Neil W , Raj Kavya , Freedman Gabrielle , Fitzgibbon Bernadette M , Rogasch Nigel C , Van Dam Nicholas T , Fitzgerald Paul B
Published: October 2018

Mindfulness meditation may improve attention and self-regulation. One component of attention and self-regulation that may allow these improvements is performance monitoring. Neural correlates of performance monitoring can be objectively measured with electroencephalogram (EEG) via the error related negativity (ERN) and error positivity (Pe). Previous research assessing the ERN and Pe in meditators has resulted in inconsistent findings; some have reported alteration in peak amplitudes from both very brief meditation practice and long-term meditation practice, while others have failed to provide evidence for differences in the ERN or Pe. However, recently developed EEG analysis techniques allow for more rigorous analyses than have been used in past investigations. The current study measured the ERN and Pe, as well as post-error alpha suppression, during a Go/Nogo task, and emotional and colour Stroop tasks. The measures were compared between 22 experienced meditators (mean of 8 years of practice) and 20 healthy controls. The results suggested no differences in the ERN, Pe, or post-error alpha suppression (all p > 0.05), even when varying multiple analysis parameters. The study showed equivalent statistical power to previous research, and > 85% power to detect medium effect sizes present in previous research. Bayes Factor analysis indicated the null hypotheses were > 3.5 more likely than any of the alternative hypotheses for the ERN or Pe. These results suggest that meditation may not alter neural activity related to error processing, despite prior research suggesting that it does.
Network organization of antibody interactions in sequence and structure space: the RADARS model
Authors: Prechl József
Published: October 2018

Adaptive immunity in vertebrates represents a complex self-organizing network of protein interactions that develops throughout the lifetime of an individual. While deep sequencing of the immune-receptor repertoire may reveal clonal relationships, functional interpretation of such data is hampered by the inherent limitations of converting sequence to structure to function.

In this paper a novel model of antibody interaction space and network, termed radial adjustment of system resolution, RADARS, is proposed. The model is based on the radial growth of interaction affinity of antibodies towards an infinity of directions in structure space, each direction representing particular shapes of antigen epitopes. Levels of interaction affinity appear as free energy shells of the system, where hierarchical B-cell development and differentiation takes place. Equilibrium in this immunological thermodynamic system can be described by a power-law distribution of antibody free energies with an ideal network degree exponent of phi square, representing a scale-free fractal network of antibody interactions. Plasma cells are network hubs, memory B cells are nodes with intermediate degrees and B1 cells represent nodes with minimal degree.

Thus, the RADARS model implies that antibody structure space develops against an infinite antigen structure space via interactions that are individually immunologically controlled, but on a systems level are organized by thermodynamic probability distributions. The network of interactions, which control B-cell development and differentiation, represent pathways of antigen removal on systems level. Understanding such quantitative network properties of the system should help the organization of sequence-derived structural data, offering the possibility to relate sequence to function in a complex, self-organizing biological system.

Graphical Abstract

Graphical abstract
The Dynamic Conformational Landscapes of the Protein Methyltransferase SETD8
Authors: Chen Shi , Wiewiora Rafal P. , Meng Fanwang , Babault Nicolas , Ma Anqi , Yu Wenyu , Qian Kun , Hu Hao , Zou Hua , Wang Junyi , Fan Shijie , Blum Gil , Pittella-Silva Fabio , Beauchamp Kyle A. , Tempel Wolfram , Jiang Hualiang , Chen Kaixian , Skene Robert , Zheng Y. George , Brown Peter J. , Jin Jian , Luo Cheng , Chodera John D. , Luo Minkui
Published: October 2018

Elucidating conformational heterogeneity of proteins is essential for understanding protein functions and developing exogenous ligands for chemical perturbation. While structural biology methods can provide atomic details of static protein structures, these approaches cannot in general resolve less populated, functionally relevant conformations and uncover conformational kinetics. Here we demonstrate a new paradigm for illuminating dynamic conformational landscapes of target proteins. SETD8 (Pr-SET7/SET8/KMT5A) is a biologically relevant protein lysine methyltransferase for in vivo monomethylation of histone H4 lysine 20 and nonhistone targets. Utilizing covalent chemical inhibitors and depleting native ligands to trap hidden high-energy conformational states, we obtained diverse novel X-ray structures of SETD8. These structures were used to seed massively distributed molecular simulations that generated six milliseconds of trajectory data of SETD8 in the presence or absence of its cofactor. We used an automated machine learning approach to reveal slow conformational motions and thus distinct conformational states of SETD8, and validated the resulting dynamic conformational landscapes with multiple biophysical methods. The resulting models provide unprecedented mechanistic insight into how protein dynamics plays a role in SAM binding and thus catalysis, and how this function can be modulated by diverse cancer-associated mutants. These findings set up the foundation for revealing enzymatic mechanisms and developing inhibitors in the context of conformational landscapes of target proteins.
Knockout of the gene encoding the extracellular matrix protein SNED1 results in early neonatal lethality and craniofacial malformations
Authors: Barqué Anna , Jan Kyleen , De La Fuente Emanuel , Nicholas Christina L. , Hynes Richard O. , Naba Alexandra
Published: October 2018

Background

The extracellular matrix (ECM) is a fundamental component of multicellular organisms that orchestrates developmental processes and controls cell and tissue organization. We previously identified the novel ECM protein SNED1 as a promoter of breast cancer metastasis and showed that its level of expression negatively correlated with survival of breast cancer patients. Here we sought to identify the roles of SNED1 during murine development and in physiology.

Results

We generated two novelSned1knockout mouse strains and showed thatSned1is essential since homozygous ablation of the gene led to ~67% early neonatal lethality. Phenotypic analysis of the surviving knockout mice obtained revealed a role for SNED1 in the development of craniofacial and skeletal structures sinceSned1knockout resulted in growth defects, nasal cavity occlusion, and craniofacial malformations.Sned1is widely expressed in embryos, notably in neural-crest derivatives. We further show here that mice with a neural-crest-cell-specific deletion ofSned1survive, but display facial anomalies partly phenocopying the global knockout mice.

Conclusions

Our results demonstrate requisite roles for SNED1 during development and neonatal survival. Importantly, the deletion of 2q37.3 in humans, a region that includes theSNED1locus, has been associated with facial dysmorphism and short stature.
Genome-wide signatures of local adaptation among seven stoneflies species along a nationwide latitudinal gradient in Japan
Authors: Gamboa Maribet , Watanabe Kozo
Published: October 2018

Background

Environmental heterogeneity continuously produces a selective pressure that results in genomic variation among organisms; understanding this relationship remains a challenge in evolutionary biology. Here, we evaluated the degree of genome-environmental association of seven stonefly species across a wide geographic area in Japan and additionally identified putative environmental drivers and their effect on co-existing multiple stonefly species. Double-digest restriction-associated DNA (ddRAD) libraries were independently sequenced for 219 individuals from 23 sites across four geographical regions along a nationwide latitudinal gradient in Japan.

Results

A total of 4,251 candidate single nucleotide polymorphisms (SNPs) strongly associated with local adaptation were discovered using Latent mixed models; of these, 294 SNPs showed strong correlation with environmental variables, specifically precipitation and altitude, using distance-based redundancy analysis. Genome–genome comparison among the seven species revealed a high sequence similarity of candidate SNPs within a geographical region, suggesting the occurrence of a parallel evolution process.

Conclusions

Our results revealed genomic signatures of local adaptation and their influence on multiple, co-occurring species. These results can be potentially applied for future studies on river management and climatic stressor impacts.
The allometry of brain size in mammals
Authors: Robert Burger Joseph , Ashaki George Menshian , Leadbetter Claire , Shaikh Farhin
Published: October 2018

Why some animals have big brains and others do not has intrigued scholars for millennia. Yet, the taxonomic scope of brain size research is limited to a few mammal lineages. Here we present a brain size dataset compiled from the literature for 1552 species with representation from 28 extant taxonomic orders. The brain-body size allometry across all mammals is (Brain) = −1.26 (Body)0.75. This relationship shows strong phylogenetic signal as expected due to shared evolutionary histories. Slopes using median species values for each order, family, and genus, to ensure evolutionary independence, approximate ∼0.75 scaling. Why brain size scales to the ¾ power to body size across mammals is, to our knowledge, unknown. Slopes within taxonomic orders exhibiting smaller size ranges are often shallower than 0.75 and range from 0.24 to 0.81 with a median slope of 0.64. Published brain size data is lacking for the majority of extant mammals (>70% of species) with strong bias in representation from Primates, Carnivores, Perrisodactyla, and Australidelphian marsupials (orders Dasyuromorphia, Diprotodontia, Peramelemorphia). Several orders are particularly underrepresented. For example, brain size data are available for less than 20% of species in each of the following speciose lineages: Soricomorpha, Rodentia, Lagomorpha, Didelphimorphia, and Scandentia. Use of museum collections can decrease the current taxonomic bias in mammal brain size data and tests of hypothesis.
Algorithmic biosynthesis of eukaryotic glycans
Authors: Jaiman Anjali , Thattai Mukund
Published: October 2018

An algorithm converts inputs to corresponding unique outputs through a sequence of actions. Algorithms are used as metaphors for complex biological processes such as organismal development. Here we make this metaphor rigorous for glycan biosynthesis. Glycans are branched sugar oligomers that are attached to cell-surface proteins and convey cellular identity. Eukaryotic O-glycans are synthesized by collections of enzymes in Golgi compartments. A compartment can stochastically convert a single input oligomer to a heterogeneous set of possible output oligomers; yet a given type of protein is invariably associated with a narrow and reproducible glycan oligomer profile. Here we resolve this paradox by borrowing from the theory of algorithmic self-assembly. We rigorously enumerate the sources of glycan microheterogeneity: incomplete oligomers via early exit from the reaction compartment; tandem repeat oligomers via runaway reactions; and competing oligomer fates via divergent reactions. We demonstrate how to diagnose and eliminate each of these, thereby obtaining “algorithmic compartments” that convert inputs to corresponding unique outputs. Given an input and a target output we either prove that the output cannot be algorithmically synthesized from the input, or explicitly construct an ordered series of algorithmic compartments that achieves this synthesis. Our theoretical analysis allows us to infer the causes of non-algorithmic microheterogeneity and species-specific diversity in real glycan datasets.
Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease
Authors: Huang Yi-Fei , Siepel Adam
Published: October 2018

A central challenge in human genomics is to understand the cellular, evolutionary, and clinical significance of genetic variants. Here we introduce a unified population-genetic and machine-learning model, calledLinearAllele-SpecificSelectionInferencE(LASSIE), for estimating the fitness effects of all potential single-nucleotide variants, based on polymorphism data and predictive genomic features. We applied LASSIE to 51 high-coverage genome sequences annotated with 33 genomic features, and constructed a map of allele-specific selection coefficients across all protein-coding sequences in the human genome. We show that this map is informative about both human evolution and disease.
Algorithmic improvements for discovery of germline copy number variants in next-generation sequencing data
Authors: O’Fallon Brendan , Durtschi Jacob , Lewis Tracey , Close Devin
Published: October 2018

Copy number variants (CNVs) play a significant role in human heredity and disease, however sensitive and specific characterization of CNVs from NGS data has remained challenging. Detection is especially problematic for hybridization-capture data in which read counts are the sole source of copy number information. We describe two algorithmic adaptations that improve CNV detection accuracy in a Hidden Markov Model (HMM) context. First, we present a method for com puting target- and copy number state-specific emission distributions. Second, we demonstrate that the Pointwise Maximum a posteriori (PMAP) HMM decoding procedure yields improved sensitivity for small CNV calls compared to the more common Viterbi HMM decoder. We develop a prototype implementation, called Cobalt, and compare it to other CNV detection tools using sets of simulated and previously detected CNVs with sizes spanning a single exon up to a full chromosome. In both the simulation and previously detected CNV studies Cobalt shows similar sensitivity but significantly improved positive predictive value (PPV) compared to other callers. Overall sensitivity is 80%-90% for deletion CNVs spanning 1-4 targets and 90%-100% for larger deletion events, while sensitivity is somewhat lower for small duplication CNVs. Cobalt demonstrates significantly improved positive predictive value (PPV) compared to other callers with similar sensitivity, typically making 5X fewer total calls overall.
Serum triglycerides in Alzheimer’s disease: Relation to neuroimaging and CSF biomarkers
Authors: Bernath Megan M. , Bhattacharyya Sudeepa , Nho Kwangsik , Barupal Dinesh Kumar , Fiehn Oliver , Baillie Rebecca , Risacher SL , Arnold Matthias , Jacobson Tanner , Trojanowski John Q. , Shaw Leslie M. , Weiner Michael W. , Doraiswamy P. Murali , Kaddurah-Daouk Rima , Saykin Andrew J. ,   for the Alzheimer’s Disease Neuroimaging Initiative,   Alzheimer’s Disease Metabolomics Consortium
Published: October 2018

Objective

To investigate the association of triglyceride (TG) principal component scores with Alzheimer’s disease (AD) and the “A/T/N/V” (Amyloid, Tau, Neurodegeneration, and Cerebrovascular disease) biomarkers for AD.

Methods

Serum levels of 84 TG species were measured using untargeted lipid profiling of 689 participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort including 190 cognitively normal older adults (CN) and 339 mild cognitive impairment (MCI) and 160 AD. Principal component analysis with factor rotation was used for dimension reduction of TG species. Differences in principal components between diagnostic groups and associations between principal components and AD biomarkers (including CSF, MRI and [18F]FDG-PET) were assessed using a multivariate generalized linear model (GLM) approach. In both cases, the Bonferroni method of adjustment was employed to correct for multiple comparisons.

Results

The 84 TGs yielded 9 principal components, two of which consisting of long-chain, polyunsaturated fatty acid-containing TGs (PUTGs), were significantly associated with MCI and AD. Lower levels of PUTGs were observed in MCI and AD compared to CN. PUTG principal component scores were also significantly associated with hippocampal volume and entorhinal cortical thickness. In participants carryingAPOEε4 allele, these principal components were significantly associated with CSF amyloid-β1-42values and entorhinal cortical thickness.

Conclusions

This study shows PUTG component scores significantly associated with diagnostic group and AD biomarkers, a finding that was more pronounced inAPOEε4 carriers. Replication in independent larger studies and longitudinal follow-up are warranted.
Predicted asymmetrical effects of warming on nocturnal and diurnal ectotherms
Authors: McMunn Marshall S.
Published: October 2018

Many ectotherms restrict activity to times and places with favorable temperatures. This widespread pattern of habitat use in fluctuating environments may alter predictions of how climate change will affect ectotherms. By considering time elapsed within a range of suitable temperatures as a resource, I demonstrate that warming is expected to affect thermally restricted nocturnal and diurnal activity windows asymmetrically. Under warming scenarios, thermally restricted nocturnal activity windows lengthen while diurnal activity windows contract. This divergent prediction results from the shape of the function relating time to temperature within a day, which is typically concave during the day and convex during the night. This characteristic shape is nearly universal across terrestrial environments due to the changing angle of the sun throughout each day and exponential decay of overnight temperatures. These predicted asymmetries are exacerbated by expectations of diurnally asymmetric warming (more warming during the night compared to the day). Using example data from a montane ant community, I demonstrate that, as predicted, moderate simulated warming expands activity time available to cool active species and reduces activity time available to warm active species. Together these results suggest that the time of day during which an ectotherms optimal temperature occurs can be an important factor in determining response to warming.
Overdispersed gene expression characterizes schizophrenic brains
Authors: Huang Guangzao , Osorio Daniel , Guan Jinting , Ji Guoli , Cai James J.
Published: October 2018

Schizophrenia (SCZ) is a severe, highly heterogeneous psychiatric disorder with varied clinical presentations. The polygenic genetic architecture of SCZ makes identification of causal variants daunting. Gene expression analyses have shown that SCZ may result in part from transcriptional dysregulation of a number of genes. However, most of these studies took the commonly used approach—differential gene expression analysis, assuming people with SCZ are a homogenous group, all with similar expression levels for any given gene. Here we show that the overall gene expression variability in SCZ is higher than that in an unaffected control (CTL) group. Specifically, we applied the test for equality of variances to the normalized expression data generated by the CommonMind Consortium (CMC) and identified 87 genes with significantly higher expression variances in the SCZ group than the CTL group. One of the genes with differential variability,VEGFA, encodes a vascular endothelial growth factor, supporting a vascular-ischemic etiology of SCZ. We also applied a Mahalanobis distance-based test for multivariate homogeneity of group dispersions to gene sets and identified 19 functional gene sets with higher expression variability in the SCZ group than the CTL group. Several of these gene sets are involved in brain development (e.g., development of cerebellar cortex, cerebellar Purkinje cell layer and neuromuscular junction), supporting that structural and functional changes in the cortex cause SCZ. Finally, using expression variability QTL (evQTL) analysis, we show that common genetic variants contribute to the increased expression variability in SCZ. Our results reveal that SCZ brains are characterized by overdispersed gene expression, resulting from dysregulated expression of functional gene sets pertaining to brain development, necrotic cell death, folic acid metabolism, and several other biological processes. Using SCZ as a model of complex genetic disorders with a heterogeneous etiology, our study provides a new conceptual framework for variability-centric analyses. Such a framework is likely to be important in the era of personalized medicine. (313 words)