bluuebunny/crossref_metadata_2025 huggingface dataset:
Optogenetic Modulation of Cortical Neurons Using Organic Light Emitting Diodes (OLEDs)
Authors: Sridharan Arati , Shah Ankur , Kumar Swathy Sampath , Kyeh James , Smith Joseph , Blain-Christen Jennifer , Muthuswamy Jit
Published: June 2019

Objective

There is a need for low power, scalable photoelectronic devices and systems for emerging optogenetic needs in neuromodulation. Conventional light emitting diodes (LEDs) are constrained by power and lead-counts necessary for scalability. Organic LEDs (OLEDs) offer an exciting approach to decrease power and lead-counts while achieving high channel counts on thin, flexible substrates that conform to brain surfaces or peripheral neuronal fibers. In this study, we investigate the potential for using OLEDs to modulate neuronal networks cultured in vitro on a transparent microelectrode array (MEA) and subsequently validate neurostimulation in vivo in a transgenic mouse model.

Approach

Cultured mouse cortical neurons were transfected with light-sensitive opsins such as blue-light sensitive channel-rhodopsin (ChR2) and green-light sensitive chimeric channel-rhodopsin (C1V1tt) and stimulated using blue and green OLEDs (with 455 and 520 nm peak emission spectra respectively) at a power of 1 mW/mm2 under pulsed conditions.

Main results

We demonstrate neuromodulation and optostimulus-locked, single unit-neuronal activity in neurons expressing stimulating and inhibiting opsins (n=4 MEAs, each with 16 recordable channels). We also validated the optostimulus-locked response in a channel-rhodopsin expressing transgenic mouse model, where at least three isolatable single neuronal cortical units respond to OLED stimulation.

Significance

The above results indicate the feasibility of generating sufficient luminance from OLEDs to perform neuromodulation both in vitro and in vivo. This opens up the possibility of developing thin, flexible OLED films with multiple stimulation sites that can conform to the shape of the neuronal targets in the brain or the peripheral nervous system. However, stability of these OLEDs under chronic conditions still needs to be carefully assessed with appropriate packaging approaches.
Cortical thickness and functional networks modules by cortical lobes
Authors: Vuksanović Vesna
Published: June 2019

1

This study aims to investigate topological organization of cortical thickness and functional networks by cortical lobes. First, I demonstrated modular organization of these networks by the cortical surface frontal, temporal, parietal and occipital divisions. Secondly, I mapped the overlapping edges of cortical thickness and functional networks for positive and negative correlations. Finally, I showed that overlapping positive edges map onto within-lobe cortical interactions and negative onto between-lobes interactions.
CelltrackR: an R package for fast and flexible analysis of immune cell migration data
Authors: Wortel Inge M. N. , Dannenberg Katharina , Berry Jeffrey C. , Miller Mark J. , Textor Johannes
Published: June 2019

Visualization of cell migration via time-lapse microscopy has greatly advanced our understanding of the immune system. However, subtle differences in migration dynamics are easily obscured by biases and imaging artifacts. While several analysis methods have been suggested to address these issues, an integrated tool implementing them is currently lacking. Here, we present CelltrackR, an R package containing a diverse set of state-of-the-art analysis methods for (immune) cell tracks. CelltrackR supports the complete pipeline for track analysis by providing methods for data management, quality control, extracting and visualizing migration statistics, clustering tracks, and simulating cell migration.

Availability and Implementation

CelltrackR is an open-source package released under the GPL-2 license, and is freely available on GitHub at https://github.com/ingewortel/celltrackR.

Contact

mmiller23@wustl.edu, Johannes.Textor@radboudumc.nl
Cortisol levels after cold exposure are independent of adrenocorticotropic hormone stimulation
Authors: Shida Alissa , Ikeda Tomoya , Tani Naoto , Morioka Fumiya , Aoki Yayoi , Ikeda Kei , Watanabe Miho , Ishikawa Takaki
Published: June 2019

We previously showed that postmortem serum levels of adrenocorticotropic hormone (ACTH) were significantly higher in cases of hypothermia (cold exposure) than other causes of death. This study examined how the human hypothalamic-pituitary-adrenal axis, and specifically cortisol, responds to hypothermia.

Human samples

Autopsies on 205 subjects (147 men and 58 women; age 15-98 years, median 60 years) were performed within 3 days of death. Cause of death was classified as either hypothermia (cold exposure,n=14) or non-cold exposure (controls;n=191). Cortisol levels were determined in blood samples obtained from the left and right cardiac chambers and common iliac veins using a chemiluminescent enzyme immunoassay. Adrenal gland tissue samples were stained for cortisol using a rabbit anti-human polyclonal antibi.

Cell culture

AtT20, a mouse ACTH secretory cell line, and Y-1, a corticosterone secretory cell line derived from a mouse adrenal tumor, were analyzed in mono-and co-culture, and times courses of ACTH (in AtT20) and corticosterone (in Y-1) secretion were assessed after low temperature exposure mimicking hypothermia and compared with data for samples collected postmortem for other causes of death. However, no correlation between ACTH concentration and cortisol levels was observed in hypothermia cases. Immunohistologic analyses of samples from hypothermia cases showed that cortisol staining was localized primarily to the nucleus rather than the cytoplasm of cells in the zona fasciculata of the adrenal gland. During both mono-culture and co-culture, AtT20 cells secreted high levels of ACTH after 10-15 minutes of cold exposure, whereas corticosterone secretion by Y-1 cells increased slowly during the first 15-20 minutes of cold exposure. Similar to autopsy results, no correlation was detected between ACTH levels and corticosterone secretion, either in mono-culture or co-culture experiments. These results suggested that ACTH-independent cortisol secretion may function as a stress response during cold exposure.
Decomposition disentangled: a test of the multiple mechanisms by which nitrogen enrichment alters litter decomposition
Authors: Pichon Noémie A. , Cappelli Seraina , Soliveres Santiago , Hölzel Norbert , Klaus Valentin H. , Kleinebecker Till , Allan Eric
Published: June 2019

Nitrogen (N) enrichment has direct effects on ecosystem functioning by altering soil abiotic conditions and indirect effects by reducing plant diversity and shifting plant functional composition from dominance by slow to fast growing species. Litter decomposition is a key ecosystem function and is affected by N enrichment either by a change in litter quality (the recalcitrance of the plant material) or through a change in soil quality (the abiotic and biotic components of the soil that affect decomposition). The relative importance of soil and litter quality and how the direct and effects of N alter them remains poorly known.

We designed a large grassland field experiment manipulating N enrichment, plant species richness and functional composition in a full factorial design. We used three complementary litter bag experiments and a novel structural equation modelling approach to quantify the relative effects of the treatments on litter and soil quality and their importance for total decomposition.

Our results indicate that total decomposition was mostly driven by changes in litter quality rather than soil quality. Litter quality was affected by the nutrient contents (N and calcium) and structural components of the litter (leaf dry matter content, fibres). N enrichment increased litter decomposition mostly indirectly through a shift in functional composition toward faster growing plant species producing higher quality litter. N enrichment also had effects on soil, by directly and indirectly affected vegetation cover, but this had relatively few consequences for the total decomposition rate.

Synthesis. Our approach provides a mechanistic tool to test the drivers of litter decomposition across different ecosystems. Our results show that functional composition is more important than richness or soil quality in determining litter decomposition and that N enrichment effects mainly occur via above- rather than belowground processes. This highlights the importance of considering shifts in plant species composition when assessing the effects of N enrichment on decomposition.
Herbal tablet of Pueraria tuberosa water extract suppresses the alloxan induced liver damage and hyperglycemia in rats
Authors: Pandey Harsh , Srivastava Shivani , Tripathi Yamini Bhusan
Published: June 2019

Aim

To study the protective response of herbal formulation (tablets) of Pueraria tuberosa water extract (PTAB) on alloxan induced rat diabetic model.

Methodology

Alloxan (120 mg/kg bw) was injected intraperitonially. Rats were divided into three groups: group 1 as normal, group 2 as diabetic control and group 3 were given PTAB upto 14 days. Blood glucose and liver function tests were done using their respective kits. Hematoxylene and eosin staining was done to evaluate the morphological changes in liver tissues. Through immunohistochemistry, we have checked the protein expression of VEGF, MMP9 and ki67.

Result

PTAB significantly decreases blood glucose level in a time dependent manner up to 14 days. As compared to diabetic control, PTAB decreases SGOT, SGPT and alkaline phosphates after 14 days of treatment. In diabetic control, the morphology of liver tissues were found damaged due to deformed hepatocytes and dilated lobules. Most of the hepatocytes after PTAB treatment were comparatively found similar to normal rats tissues, along with dilated blood vessels and normalized liver lobules. In addition to these results, PTAB suppresses the expressions of VEGF and MMP 9.

Conclusion

PTAB was found to act as an effective hypoglycemic agent. In addition to this, PTAB also found to inhibit inflammation and apoptosis of liver. Thus, can be taken as a potential drug in liver diseases.
Distinct roles of parvalbumin and somatostatin interneurons in the synchronization of spike-times in the neocortex
Authors: Jang Hyun Jae , Chung Hyowon , Rowland James M. , Richards Blake A. , Kohl Michael M. , Kwag Jeehyun
Published: June 2019

Synchronization of precise spike-times across multiple neurons carries information about sensory stimuli. Inhibitory interneurons are suggested to promote this synchronization, but it is unclear whether distinct interneuron subtypes provide different contributions. To test this, we examined single-unit recordings from barrel cortex in vivo and used optogenetics to determine the contribution of two classes of inhibitory interneurons: parvalbumin (PV)- and somatostatin (SST)-positive interneurons to spike-timing synchronization across cortical layers. We found that PV interneurons preferentially promote the synchronization of spike-times when instantaneous firing-rates are low (<12 Hz), whereas SST interneurons preferentially promote the synchronization of spike-times when instantaneous firing-rates are high (>12 Hz). Furthermore, using a computational model, we demonstrate that these effects can be explained by PV and SST interneurons having preferential contribution to feedforward and feedback inhibition, respectively. Our findings demonstrate that distinct subtypes of inhibitory interneurons have frequency-selective roles in spatio-temporal synchronization of precise spike-times.
Insights into Membrane Protein-Lipid Interactions from Free Energy Calculations
Authors: Corey Robin A. , Vickery Owen N. , Sansom Mark S. P. , Stansfeld Phillip J.
Published: June 2019

Integral membrane proteins are regulated by specific interactions with lipids from the surrounding bilayer. The structures of protein-lipid complexes can be determined through a combination of experimental and computational approaches, but the energetic basis of these interactions is difficult to resolve. Molecular dynamic simulations provide the primary computational technique to estimate the free energies of these interactions. We demonstrate that the energetics of protein-lipid interactions may be reliably and reproducibly calculated using three simulation-based approaches: potential of mean force calculations. alchemical free energy perturbation, and well-tempered metadynamics. We employ these techniques within the framework of a coarse-grained force field, and apply them to both bacterial and mammalian membrane protein-lipid systems. We demonstrate good agreement between the different techniques, providing a robust framework for their automated implementation within a pipeline for annotation of newly determined membrane protein structures.
Robust estimation of heritability and predictive accuracy in plant breeding: evaluation using simulation and empirical data
Authors: Lourenço Vanda M , Ogutu Joseph O , Piepho Hans-Peter
Published: June 2019

Background

Genomic prediction (GP) is used in animal and plant breeding to help identify the best genotypes for selection. One of the most important measures of the effectiveness and reliability of GP in plant breeding is predictive accuracy. An accurate estimate of this measure is thus central to GP. Moreover, regression models are the models of choice for analyzing field trial data in plant breeding. However, models that use the classical likelihood typically perform poorly, often resulting in biased parameter estimates, when their underlying assumptions are violated. This typically happens when data are contaminated with outliers. These biases often translate into inaccurate estimates of heritability and predictive accuracy, compromising the performance of GP. Since phenotypic data are susceptible to contamination, improving the methods for estimating heritability and predictive accuracy can enhance the performance of GP. Robust statistical methods provide an intuitively appealing and a theoretically well justified framework for overcoming some of the drawbacks of classical regression, most notably the departure from the normality assumption. We compare the performance of robust and classical approaches to two recently published methods for estimating heritability and predictive accuracy of GP using simulation of several plausible scenarios of random and block data contamination with outliers and commercial maize and rye breeding datasets.

Results

The robust approach generally performed as good as or better than the classical approach in phenotypic data analysis and in estimating the predictive accuracy of heritability and genomic prediction under both the random and block contamination scenarios. Notably, it consistently outperformed the classical approach under the random contamination scenario. Analyses of the empirical maize and rye datasets further reinforce the stability and reliability of the robust approach in the presence of outliers or missing data.

Conclusions

The proposed robust approach enhances the predictive accuracy of heritability and genomic prediction while alleviating the need for performing outlier detection for a broad range of simulation scenarios and empirical breeding datasets. Accordingly, plant breeders should seriously consider regularly using the robust alongside the classical approach and increasing the number of replicates to three or more, to further enhance the accuracy of the robust approach.
Cas9HF1 enhanced specificity inUstilago maydis
Authors: Zuo Weiliang , Depotter Jasper RL , Doehlemann Gunther
Published: June 2019

The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system is widely used as a tool to precisely manipulate genomic sequence targeted by sgRNA (single guide RNA) and is adapted in different species for genome editing. One of the major concerns of CRISPR-Cas9 is the possibility of off-target effects, which can be remedied by the deployment of high fidelity Cas9 variants.Ustilago maydisis a maize fungal pathogen, which has served as a model organism for biotrophic pathogens for decades. The successful adaption of CRISPR-Cas9 inU. maydisgreatly facilitated effector biology studies. Here, we constructed anU. maydisreporter strain that allowsin vivoquantification of efficiency and target specificity of three high fidelity Cas9 variants, Cas9HF1, Cas9esp1.1 and Cas9hypa. This approach identified Cas9HF1 as most specific Cas9 variant inU. maydis. Furthermore, whole genome sequencing showed absence of off-target effects inU. maydisby CRISPR-Cas9 editing.
Modeling and Characterization of Inter-Individual Variability in CD8 T Cell Responses in Mice
Authors: Audebert Chloe , Laubreton Daphné , Arpin Christophe , Gandrillon Olivier , Marvel Jacqueline , Crauste Fabien
Published: June 2019

To develop vaccines it is mandatory yet challenging to account for inter-individual variability during immune responses. Even in laboratory mice, T cell responses of single individuals exhibit a high heterogeneity that may come from genetic backgrounds, intra-specific processes (e.g. antigen-processing and presentation) and immunization protocols.

To account for inter-individual variability in CD8 T cell responses in mice, we propose a dynamical model coupled to a statistical, nonlinear mixed effects model. Average and individual dynamics during a CD8 T cell response are characterized in different immunization contexts (vaccinia virus and tumor). On one hand, we identify biological processes that generate inter-individual variability (activation rate of naive cells, the mortality rate of effector cells, and dynamics of the immunogen). On the other hand, introducing categorical covariates to analyze two different immunization regimens, we highlight the steps of the response impacted by immunogens (priming, differentiation of naive cells, expansion of effector cells and generation of memory cells). The robustness of the model is assessed by confrontation to new experimental data.

Our approach allows to investigate immune responses in various immunization contexts, when measurements are scarce or missing, and contributes to a better understanding of inter-individual variability in CD8 T cell immune responses.
Auditory predictions and prediction errors in response to self-initiated vowels
Authors: Knolle Franziska , Schwartze Michael , Schröger Erich , Kotz Sonja A.
Published: June 2019

It has been suggested that speech production is accomplished by an internal forward model, reducing processing activity directed to self-produced speech in the auditory cortex. The current study uses an established N1-suppression paradigm comparing self- and externally-initiated natural speech sounds to answer two questions:

Are forward predictions generated to process complex speech sounds, such as vowels, initiated via a button press?

Are prediction errors regarding self-initiated deviant vowels reflected in the corresponding ERP components?

Results confirm an N1-suppression in response to self-initiated speech sounds. Furthermore, our results suggest that predictions leading to the N1-suppression effect are specific, as self-initiated deviant vowels do not elicit an N1-suppression effect. Rather, self-initiated deviant vowels elicit an enhanced N2b and P3a compared to externally-generated deviants, externally-generated standard, or self-initiated standards, again confirming prediction specificity.

Results show that prediction errors are salient in self-initiated auditory speech sounds, which may lead to more efficient error correction in speech production.
The ATPase cycle of Human Muscle Myosin II Isoforms: Adaptation of a single mechanochemical cycle for different physiological roles
Authors: Johnson Chloe A. , Walklate Jonathan , Svicevic Marina , Mijailovich Srboljub M. , Vera Carlos , Karabina Anastasia , Leinwand Leslie A. , Geeves Michael A.
Published: June 2019

Striated muscle myosins are encoded by a large gene family in all mammals, including human. These isoforms define several of the key characteristics of the different striated muscle fiber types including maximum shortening velocity. We have previously used recombinant isoforms of the motor domains of eight different human myosin isoforms to define the actin.myosin cross-bridge cycle in solution. Here, we use a recently developed modeling approach MUSICO to explore how well the experimentally defined cross-bridge cycles for each isoform in solution can predict the characteristics of muscle fiber contraction including duty ratio, shortening velocity, ATP economy and the load dependence of these parameters. The work shows that the parameters of the cross-bridge cycle predict many of the major characteristics of each muscle fiber type and raises the question of what sequence changes are responsible for these characteristics.
Increased O-GlcNAcylation rapidly decreases GABAAR currents in hippocampus yet depresses neuronal output
Authors: Stewart Luke T. , Abiraman Kavitha , Chatham John C. , McMahon Lori L.
Published: June 2019

O-GlcNAcylation, a post-translational modification involving O-linkage of β-N-acetylglucosamine to Ser/Thr residues on target proteins, is increasingly recognized as a critical regulator of brain function in health and disease. Enzymes that catalyze O-GlcNAcylation are found at both presynaptic and postsynaptic sites, and O-GlcNAcylated proteins localize to synaptosomes. An acute increase in O-GlcNAcylation induces long-term depression (LTD) of excitatory transmission at hippocampal CA3-CA1 synapses, and depresses hyperexcitable circuits in vitro and in vivo. Yet, no study has investigated how O-GlcNAcylation modulates the efficacy of inhibitory neurotransmission. Here we show an acute increase in O-GlcNAc dampens GABAergic currents onto principal cells in rodent hippocampus likely through a postsynaptic mechanism, and has a variable effect on the excitation/inhibition balance. The overall effect of increased O-GlcNAc is reduced synaptically-driven spike probability via synaptic depression and decreased intrinsic excitability. Our results position O-GlcNAcylation as a novel regulator of the overall excitation/inhibition balance and neuronal output.
Multi-Subject Stochastic Blockmodels for Adaptive Analysis of Individual Differences in Human Brain Network Cluster Structure
Authors: Pavlović Dragana M. , Guillaume Bryan R. L. , Towlson Emma K. , Kuek Nicole M. Y. , Afyouni Soroosh , Vértes Petra E. , Yeo Thomas B. T. , Bullmore Edward T. , Nichols Thomas E.
Published: June 2019

There is great interest in elucidating the cluster structure of brain networks in terms of modules, blocks or clusters of similar nodes. However, it is currently challenging to handle data on multiple subjects since most of the existing methods are applicable only on a subject-by-subject basis or for analysis of a group average network. The main limitation of per-subject models is that there is no obvious way to combine the results for group comparisons, and of group-averaged models that they do not reflect the variability between subjects. Here, we propose two novel extensions of the classical Stochastic Blockmodel (SBM) that use a mixture model to estimate blocks or clusters of connected nodes, combined with a regression model to capture the effects on cluster structure of individual differences on subject-level covariates. Multi-subject Stochastic Blockmodels (MS-SBM) can flexibly account for between-subject variability in terms of a homogenous or heterogeneous effect on connectivity of covariates such as age or diagnostic status. Using synthetic data, representing a range of block sizes and cluster structures, we investigate the accuracy of the estimated MS-SBM parameters as well as the validity of inference procedures based on Wald, likelihood ratio and Monte Carlo permutation tests. We show that multi-subject SBMs recover the true cluster structure of synthetic networks more accurately and adaptively than standard methods for modular decomposition. Permutation tests of MS-SBM parameters were more robustly valid for statistical inference and Type I error control than tests based on standard asymptotic assumptions. Applied to analysis of multi-subject resting state fMRI networks (13 healthy volunteers; 12 people with schizophrenia; N = 268 brain regions), we show that the Heterogeneous Stochastic Blockmodel estimates ‘core-on-modules’ architecture. The intra-block and inter-block connection weights vary between individual participants and can be modelled as a logistic function of subject-level covariates like age or diagnostic status. Multi-subject Stochastic Blockmodels are likely to be useful tools for statistical analysis of individual differences in human brain graphs and other networks whose prior cluster structure needs to be estimated from the data.
Rigbox: an Open-Source Toolbox for Probing Neurons and Behavior
Authors: Bhagat Jai , Wells Miles J. , Peters Andrew , Harris Kenneth D , Carandini Matteo , Burgess Christopher P
Published: June 2019

Setting up an experiment in behavioral neuroscience is a complex process that is often managed with ad hoc solutions. To streamline this process we developed Rigbox, a high-performance, open-source software toolbox that facilitates a modular approach to designing experiments (github.com/cortex-lab/Rigbox). Rigbox simplifies hardware I/O, synchronizes data streams from multiple sources, communicates with remote databases, and implements visual and auditory stimuli presentation. Its main submodule, Signals, allows intuitive programming of behavioral tasks. Here we illustrate its function with two interactive examples: a human psychophysics experiment, and the game of Pong. We give an overview of the other packages in Rigbox, provide benchmarks, and conclude with a discussion on the extensibility of the software and comparisons with similar toolboxes. Rigbox runs in MATLAB, with Java components to handle network communication, and a C library to boost performance.
PICRUSt2: An improved and customizable approach for metagenome inference
Authors: Douglas Gavin M. , Maffei Vincent J. , Zaneveld Jesse , Yurgel Svetlana N. , Brown James R. , Taylor Christopher M. , Huttenhower Curtis , Langille Morgan G. I.
Published: June 2019

One major limitation of microbial community marker gene sequencing is that it does not provide direct information on the functional composition of sampled communities. Here, we present PICRUSt2 (https://github.com/picrust/picrust2), which expands the capabilities of the original PICRUSt method1 to predict the functional potential of a community based on marker gene sequencing profiles. This updated method and implementation includes several improvements over the previous algorithm: an expanded database of gene families and reference genomes, a new approach now compatible with any OTU-picking or denoising algorithm, and novel phenotype predictions. Upon evaluation, PICRUSt2 was more accurate than PICRUSt1 and other current approaches overall. PICRUSt2 is also now more flexible and allows the addition of custom reference databases. We highlight these improvements and also important caveats regarding the use of predicted metagenomes, which are related to the inherent challenges of analyzing metagenome data in general.
Scale-dependent effects of geography, host ecology, and host genetics, on species composition and co-occurrence in a stickleback parasite metacommunity
Authors: Bolnick Daniel I. , Resetarits Emlyn J. , Ballare Kimberly , Stuart Yoel E. , Stutz William E.
Published: June 2019

ABSTRACT

A core goal of ecology is to understand the abiotic and biotic variables that regulate species distributions and community composition. A major obstacle is that the rules governing species distribution can change with spatial scale. Here, we illustrate this point using data from a spatially nested metacommunity of parasites infecting a metapopulation of threespine stickleback fish from 34 lakes on Vancouver Island, British Columbia. Parasite communities differ among host individuals within each host population and between host populations. The distribution of each parasite taxon depends, to varying degrees, on individual host traits (e.g., mass, diet) and on host population characteristics (e.g., lake size, mean diet). However, in most cases, a given parasite was regulated by different factors at the host-individual and host-population scales, contributing to scale-dependent patterns of parasite-species co-occurrence.
Neuropathology of RAN translation proteins in Fragile X-associated Tremor/Ataxia Syndrome
Authors: Krans Amy , Skariah Geena , Zhang Yuan , Bayly Bryana , Todd Peter K.
Published: June 2019

CGG repeat expansions in FMR1 cause the neurodegenerative disorder Fragile X-associated Tremor/Ataxia Syndrome (FXTAS). Ubiquitinated neuronal intranuclear inclusions (NIIs) are the neuropathological hallmark of FXTAS. Both sense strand derived CGG repeats and antisense strand derived CCG repeats support non-AUG initiated (RAN) translation of homopolymeric proteins in potentially 6 different reading frames. However, the relative abundance of these proteins in FXTAS brains and their co-localization with each other and NIIs is lacking. Here we describe rater-blinded assessment of immunohistochemical and immunofluorescence staining with newly generated antibodies to different CGG RAN translation products in FXTAS and control brains as well as co-staining with ubiquitin, p62/SQSTM1, and ubiquilin 2. We find that both FMRpolyG and a second CGG repeat derived RAN translation product, FMRpolyA, accumulate in aggregates in FXTAS brains. FMRpolyG is a near-obligate component of both ubiquitin-positive and p62-positive NIIs in FXTAS, with occurrence of aggregates in 20% of all hippocampal neurons and >90% of all inclusions. A subset of these inclusions also stain positive for the ALS/FTD associated protein ubiquilin 2. Ubiquitinated inclusions and FMRpolyG+ aggregates are rarer in cortex and cerebellum. Intriguingly, FMRpolyG staining is also visible in control neuronal nuclei. In contrast to FMRpolyG, staining for FMRpolyA and CCG antisense derived RAN translation products were less abundant and were infrequent components of FMRpolyG+ inclusions. In conclusion, RAN translated FMRpolyG is a common component of ubiquitin and p62 positive inclusions in FXTAS patient brains.
Oct4-mediated inhibition of Lsd1 activity promotes the active and primed state of pluripotency enhancers
Authors: AlAbdi Lama , Saha Debapriya , He Ming , Dar Mohd Saleem , Utturkar Sagar M. , Sudyanti Putu Ayu , McCune Stephen , Spears Brice H. , Breedlove James A. , Lanman Nadia A. , Gowher Humaira
Published: June 2019

An aberrant increase in pluripotency gene (PpG) expression due to enhancer reactivation could induce stemness and enhance tumorigenicity of cancer stem cells. Silencing of PpG enhancers (PpGe) during embryonic stem cell differentiation involves Lsd1–mediated H3K4me1 demethylation and DNA methylation. Here, we observed retention of H3K4me1 and DNA hypomethylation at PpGe associated with a partial repression of PpGs in F9 embryonal carcinoma cells (ECCs) post-differentiation. H3K4me1 demethylation in F9 ECCs could not be rescued by Lsd1 overexpression. Given our observation that H3K4me1 demethylation is accompanied by strong Oct4 repression in P19 ECCs, we tested if Oct4 interaction with Lsd1 affects its catalytic activity. Our data show a dose-dependent inhibition of Lsd1 activity by Oct4 and retention of H3K4me1 at PpGe in Oct4 overexpressing P19 ECCs. These data suggest that Lsd1-Oct4 interaction in cancer stem cells could establish a primed enhancer state that is susceptible to reactivation leading to aberrant PpG expression.
Integrated analysis of directly captured microRNA targets reveals the impact of microRNAs on mammalian transcriptome
Authors: Bjerke Glen A. , Yi Rui
Published: June 2019

MicroRNA (miRNA)-mediated regulation is widespread, relatively mild but functionally important. Despite extensive efforts to identify miRNA targets, it remains unclear how miRNAs bind to mRNA targets globally and how changes in miRNA levels affects the transcriptome. Here we apply an optimized method for simultaneously capturing miRNA and targeted RNA sites to wildtype, miRNA knockout and induced epithelial cells. We find that abundantly expressed miRNAs can bind to thousands of different transcripts and many different miRNAs can regulate the same gene. Although mRNA sites that are bound by miRNAs and also contain matches to seed sequences confer the strongest regulation, ∼50% of miRNAs bind to RNA regions without seed matches. In general, these bindings have little impact on mRNA levels and reflect a scanning activity of miRNAs. In addition, different miRNAs have different preferences to seed matches and 3’end base-pairing. For a single miRNA, the effectiveness of mRNA regulation is highly correlated with the number of captured miRNA:RNA fragments. Notably, elevated miRNA expression effectively represses existing targets with little impact on newly recognized targets. Global analysis of directly captured mRNA targets reveals pathways that are involved in cancer, cell adhesion and signaling pathways are highly regulated by many different miRNAs in epithelial cells. Comparison between experimentally captured and TargetScan predicted targets indicates that our approach is more effective to identify bona fide targets by reducing false positive and negative predictions. This study reveals the global binding landscape and impact of miRNAs on mammalian transcriptome.
A mechanical model reveals that non-axisymmetric buckling lowers the energy barrier associated with membrane neck constriction
Authors: Vasan R. , Rudraraju S. , Akamatsu M. , Garikipati K. , Rangamani P.
Published: June 2019

Membrane neck formation is essential for scission, which, as recent experiments on tubules have demonstrated, can be location dependent. The diversity of biological machinery that can constrict a neck such as dynamin, actin, ESCRTs and BAR proteins, and the range of forces and deflection over which they operate, suggest that the constriction process is functionally mechanical and robust to changes in biological environment. In this study, we used a mechanical model of the lipid bilayer to systematically investigate the influence of location, symmetry constraints, and helical forces on membrane neck constriction. Simulations from our model demonstrated that the energy barriers associated with constriction of a membrane neck are location-dependent. Importantly, if symmetry restrictions are relaxed, then the energy barrier for constriction is dramatically lowered and the membrane buckles at lower values of forcing parameters. Our simulations also show that constriction due to helical proteins further reduces the energy barrier for neck formation compared to cylindrical proteins. These studies establish that despite different molecular mechanisms of neck formation in cells, the mechanics of constriction naturally leads to a loss of symmetry that can lower the energy barrier to constriction.

Significance statement

Membrane tubule constriction is a critical step of cellular membrane trafficking processes and is thought to be mechanically regulated. Mechanical modeling techniques employing the Helfrich Hamiltonian and axisymmetric continuum frameworks have previously described energy barriers to constriction as a function of location along a 26 membrane tubule. Recent advances in numerical modeling using spline basis functions (Isogeometric Analysis) enable us to conduct our analyses of membrane mechanics in a generalized 3D framework. Here, we implement a novel 3D Isogeometric Analysis framework and juxtapose it against an axisymmetric model to study the influence of location, symmetry constraints and helical collars on the constriction pathway. We show that an unsymmetric, “crushed soda can” neck consistently displays a lower energy barrier than a symmetric neck.
Single-Cell Transcriptomic Analysis of mIHC Images via Antigen Mapping
Authors: Govek Kiya W. , Troisi Emma C. , Miao Zhen , Woodhouse Steven , Camara Pablo G.
Published: June 2019

Highly-multiplexed immunohistochemistry (mIHC) enables the staining and quantification of dozens of antigens in a tissue section with single-cell resolution. However, annotating cell populations that differ little in the profiled antigens or for which the antibody panel does not include specific markers is challenging. To overcome this obstacle, we have developed an approach for enriching mIHC images with single-cell RNA-seq data, building upon recent experimental procedures for augmenting single-cell transcriptomes with concurrent antigen measurements. Spatially-resolved Transcriptomics via Epitope Anchoring (STvEA) performs transcriptome-guided annotation of highly-multiplexed cytometry datasets. It increases the level of detail in histological analyses by enabling annotation of subtle cell populations, spatial patterns of transcription, and interactions between cell types. More generally, it enables the systematic annotation of cell populations in cytometry data. We demonstrate the utility of STvEA by uncovering the architecture of poorly characterized cell types in the murine spleen using published highly-multiplexed cytometry and mIHC data.
Virulence phenotypes result from an interaction between pathogen ploidy and genetic background
Authors: Feistel Dorian J. , Elmostafa Rema , Hickman Meleah A.
Published: June 2019

Studying fungal virulence is often challenging and frequently depends on many contexts, including host immune status and pathogen genetic background. However, ploidy has often been overlooked when studying virulence in eukaryotic pathogens. Since fungal pathogens, including the human opportunistic pathogen Candida albicans, can display extensive ploidy variation, assessing how ploidy impacts virulence has important clinical relevance. Here, we assessed how C. albicans ploidy and genetic background impact virulence phenotypes in both healthy and immunocompromised nematode hosts. In addition to reducing overall host survival, Candida negatively impacted host reproduction, which allowed us to survey lethal and non-lethal virulence phenotypes. While we did not detect any global differences in virulence between diploid and tetraploid pathogens, there were significant interactions between ploidy and C. albicans genetic background, regardless of host immune function.
Binned Relative Environmental Change Indicator (BRECI): A tool to communicate the nature of differences between environmental niche model outputs
Authors: Wilson Peter D.
Published: June 2019

Niche models are now widely used in many branches of the biological sciences and are often used to contrast the distribution of favourable environments between regions or under changes in environmental conditions such as climate change. Evaluating model performance and selecting optimal models is now accepted as best-practice, and a number of methods are available assist this process. One aspect of ENM application which has not received as much attention is developing methods to communicate the degree and nature of changes between model outputs (typically as raster maps). The method described in this paper, Binned Relative Environmental Change Index (BRECI), seeks to address this shortfall in communicating model results.
Transcriptome characterization analysis and molecular profiles of obligatory diapause induction of the Chinese citrus fruit fly,Bactrocera minax(Diptera: Tephritidae)
Authors: Zhou Zhixiong , Dong Xiaolin , Li Chuanren
Published: June 2019

The Chinese citrus fruit fly,Bactrocera minax, is a devastating citrus pest in China, Bhutan and India. It will enter obligatory pupal diapause in each generation at specific stage, while little is known about the course and the molecular mechanisms of diapause induction. To gain insight into possible mechanisms of obligatory pupal diapause induction, high-throughput RNA-seq data were generated from second-instar larvae (2L), third-instar larvae (3L) and pupal (P, one week after pupating). A total of 116,402 unigenes were assembled and researched against public databases, and 54,781 unigenes matched to proteins in the NCBI database using the BLAST search. Three pairwise comparisons were performed, and significantly differentially regulated transcripts were identified. Several differentially expressed genes (DEGs) expression patterns revealed that those highly or lowly expressed genes in pupal stage were predicted to be involved in diapause induction. Moreover, GO function and KEGG pathway analysis were performed on all DEGs and showed that 20-hydroxyecdysone (20E) biosynthesis, insulin signaling pathway, FoxO signaling pathway, cell cycle and metabolism pathway may be related to the obligatory diapause of the Chinese citrus fruit fly. This study provides valuable information about the Chinese citrus fruit fly transcriptome for future gene function research, and contributes to the in-depth elucidation of the molecular regulation mechanism of insect obligatory diapause induction.
The Effects of Quantitative Trait Architecture on Detection Power in Artificial Selection Experiments
Authors: Lou R. Nicolas , Therkildsen Nina O. , Messer Philipp W.
Published: June 2019

Evolve and resequence (E&R) experiments, in which artificial selection is imposed on organisms in a controlled environment, are becoming an increasingly accessible tool for studying the genetic basis of adaptation. Previous work has assessed how different experimental design parameters affect the power to detect the quantitative trait loci (QTLs) that underlie adaptive responses in such experiments, but so far there has been little exploration of how this power varies with the genetic architecture of the evolving traits. In this study, we use forward simulation to build a realistic model of an E&R experiment in which a quantitative polygenic trait experiences a short, but strong, episode of truncation selection. We study the expected power for QTL detection in such an experiment and how this power is influenced by different aspects of trait architecture, including the number of QTLs affecting the trait, their starting frequencies, effect sizes, clustering along a chromosome, dominance, and epistasis patterns. We show that all of the above parameters can affect allele frequency dynamics at the QTLs and linked loci in complex and often unintuitive ways, and thus influence our power to detect them. One consequence of this is that existing detection methods based on models of independent selective sweeps at individual QTLs often have lower detection power than a simple measurement of allele frequency differences before and after selection. Our findings highlight the importance of taking trait architecture into account in designing studies of molecular adaptation with temporal data. We provide a customizable modeling framework that will enable researchers to easily simulate E&R experiments with different trait architectures and parameters tuned to their specific study system, allowing for assessment of expected detection power and optimization of experimental design.
ModEx: A text mining system for extracting mode of regulation of Transcription Factor-gene regulatory interaction
Authors: Farahmand Saman , Riley Todd , Zarringhalam Kourosh
Published: June 2019

Background

Transcription factors (TFs) are proteins that are fundamental to transcription and regulation of gene expression. Each TF may regulate multiple genes and each gene may be regulated by multiple TFs. TFs can act as either activator or repressor of gene expression. This complex network of interactions between TFs and genes underlies many developmental and biological processes and is implicated in several human diseases such as cancer. Hence deciphering the network of TF-gene interactions with information on mode of regulation (activation vs. repression) is an important step toward understanding the regulatory pathways that underlie complex traits. There are many experimental, computational, and manually curated databases of TF-gene interactions. In particular, high-throughput ChIP-Seq datasets provide a large-scale map or transcriptional regulatory interactions. However, these interactions are not annotated with information on context and mode of regulation. Such information is crucial to gain a global picture of gene regulatory mechanisms and can aid in developing machine learning models for applications such as biomarker discovery, prediction of response to therapy, and precision medicine.

Methods

In this work, we introduce a text-mining system to annotate ChIP-Seq derived interaction with such meta data through mining PubMed articles. We evaluate the performance of our system using gold standard small scale manually curated databases.

Results

Our results show that the method is able to accurately extract mode of regulation with F-score 0.77 on TRRUST curated interaction and F-score 0.96 on intersection of TRUSST and ChIP-network. We provide a HTTP REST API for our code to facilitate usage.

Availibility

Source code and datasets are available for download on GitHub: https://github.com/samanfrm/modex HTTP REST API: https://watson.math.umb.edu/modex/[type query]
Appropriate Correction for Multiple Comparisons in Decoding of ERP Data: A Re-Analysis of Bae & Luck (2018)
Authors: Bae Gi-Yeul , Luck Steven J.
Published: June 2019

Bae & Luck (2018) reported a study of visual working memory in which the orientation being held in memory was decoded from the scalp distribution of sustained ERP activity and alpha-band EEG oscillations. Decoding accuracy was compared to chance at each point during the delay interval, and a correction for multiple comparisons was applied to find clusters of consecutive above-chance time points that were stronger than would be expected by chance. However, the correction used in that study did not account for the autocorrelation of the noise and may have been overly liberal. Here, we describe a more appropriate correction procedure and apply it to the data from Bae & Luck (2018). We find that the major clusters of time points that were significantly above chance with the original correction procedure remained above chance with the updated correction procedure. However, some minor clusters that were significant with the original procedure were no longer significant with the updated procedure. We recommend that future studies use the updated correction procedure.
Robust Optimization in Possibility Theory
Authors: Hose Dominik , Mäck Markus , Hanss Michael
Published: June 2019

In this contribution, the optimization of systems under uncertainty is considered. The possibilistic evaluation of the fuzzy-valued constraints and the adoption of a multicriteria decision making technique for the fuzzy-valued objective function enable a meaningful solution to general fuzzy-valued optimization problems. The presented approach is universally applicable, which is demonstrated by reformulating and solving the linear quadratic regulator problem for fuzzy-valued system matrices and initial conditions.
Administration of a long-acting antipsychotic injection to a child while managing contraindicated polypharmacy interactions and transition between services
Authors: Akram Gazala , Mitchell Fiona
Published: June 2019

Second-generation antipsychotics are used to treat a variety of psychiatric symptoms and illnesses as well as the behavioural aspects of various neurodevelopmental disorders. However, there is reluctance in using second-generation long-acting injectable antipsychotics in child psychiatry services. We present a case of a 12-year-old child whose presentation and medication regime warranted the use of aripiprazole long-acting injection against a backdrop of potential CYP P450 enzyme interactions as a consequence of polypharmacy. The case also describes the difficulties encountered working across different health sectors and agencies and highlights the ongoing need for skills-based Continuous Professional Development for Child and Adolescent Mental Health Services-based nursing staff.