bluuebunny/crossref_metadata_2025 huggingface dataset:
Population pharmacokinetics of efavirenz in HIV and TB/HIV coinfected children: the significance of genotype-guided dosing
Authors: Alghamdi Wael A , Antwi Sampson , Enimil Anthony , Yang Hongmei , Dompreh Albert , Wiesner Lubbe , Langaee Taimour , Peloquin Charles A , Kwara Awewura
Published: May 2019

Objectives

The current WHO weight-based dosing recommendations for efavirenz result in a wide variability of drug exposure in children. Our objectives are to characterize the effects of rifampicin- and isoniazid-containing anti-TB therapy and CYP2B6 activity on efavirenz concentrations in children, using non-linear mixed-effects modelling.

Methods

This is a pharmacokinetic (PK) substudy of a prospective study that examined the interactions between anti-TB therapy and efavirenz in HIV-infected children with and without TB. PK samples were obtained 4 weeks after starting efavirenz (PK1) and repeated 4 weeks after completing TB therapy (PK2) in TB/HIV coinfected patients. Drug concentrations were measured using LC-MS/MS. Composite CYP2B6 516/983/15582 genotype was determined. Population PK modelling was performed in Monolix. Simulations were performed to obtain the predicted mid-dose concentrations (C12).

Results

One hundred and five HIV-infected Ghanaian children (46 with TB/HIV) were included. The median age and weight were 7 years and 19 kg. The efavirenz concentrations over time were adequately described using a one-compartment model. Weight, composite CYP2B6 genotype and PK visit had a significant influence on the PK parameters, while TB therapy had no significant effect. Simulations showed adequate C12 for intermediate composite CYP2B6 metabolizers only.

Conclusions

Our model showed that rifampicin- and isoniazid-containing anti-TB therapy does not influence efavirenz PK parameters. On the other hand, it describes the effect of efavirenz autoinduction after completing TB treatment. In addition, dosing efavirenz in children based only on weight results in a large variability in drug exposure. We propose dose adjustments for slow and extensive composite CYP2B6 metabolizers.
A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk Model
Authors: Brentnall Adam R , Cohn Wendy F , Knaus William A , Yaffe Martin J , Cuzick Jack , Harvey Jennifer A
Published: May 2019

Background

Accurate breast cancer risk assessment for women attending routine screening is needed to guide screening and preventive interventions. We evaluated the accuracy of risk predictions from both visual and volumetric mammographic density combined with the Tyrer-Cuzick breast cancer risk model.

Methods

A case-control study (474 patient participants and 2243 healthy control participants) of women aged 40–79 years was performed using self-reported classical risk factors. Breast density was measured by using automated volumetric software and Breast Imaging and Reporting Data System (BI-RADS) density categories. Odds ratios (95% CI) were estimated by using logistic regression, adjusted for age, demographic factors, and 10-year risk from the Tyrer-Cuzick model, for a change from the 25th to 75th percentile of the adjusted percent density distribution in control participants (IQ-OR).

Results

After adjustment for classical risk factors in the Tyrer-Cuzick model, age, and body mass index (BMI), BI-RADS density had an IQ-OR of 1.55 (95% CI = 1.33 to 1.80) compared with 1.40 (95% CI = 1.21 to 1.60) for volumetric percent density. Fibroglandular volume (IQ-OR = 1.28, 95% CI = 1.12 to 1.47) was a weaker predictor than was BI-RADS density (Pdiff = 0.014) or volumetric percent density (Pdiff = 0.065). In this setting, 4.8% of women were at high risk (8% + 10-year risk), using the Tyrer-Cuzick model without density, and 7.1% (BI-RADS) compared with 6.8% (volumetric) when combined with density.

Conclusion

The addition of volumetric and visual mammographic density measures to classical risk factors improves risk stratification. A combined risk could be used to guide precision medicine, through risk-adapted screening and prevention strategies.
The Fall of a Giant. Chemical evolution of Enceladus, alias the Gaia Sausage
Authors: Vincenzo Fiorenzo , Spitoni Emanuele , Calura Francesco , Matteucci Francesca , Silva Aguirre Victor , Miglio Andrea , Cescutti Gabriele
Published: May 2019

We present the first chemical evolution model for Enceladus, alias the Gaia Sausage, to investigate the star formation history of one of the most massive satellites accreted by the Milky Way during a major merger event. Our best chemical evolution model for Enceladus nicely fits the observed stellar [α/Fe]–[Fe/H] chemical abundance trends, and reproduces the observed stellar metallicity distribution function, by assuming low star formation efficiency, fast infall time-scale, and mild outflow intensity. We predict a median age for Enceladus stars $12.33^{+0.92}_{-1.36}$ Gyr, and – at the time of the merger with our Galaxy (≈10 Gyr ago from Helmi et al.) – we predict for Enceladus a total stellar mass M⋆ ≈ 5 × 109 M$\odot$. By looking at the predictions of our best model, we discuss that merger events between the Galaxy and systems like Enceladus may have inhibited the gas accretion on to the Galaxy disc at high redshifts, heating up the gas in the halo. This scenario could explain the extended period of quenching in the star formation activity of our Galaxy about 10 Gyr ago, which is predicted by Milky Way chemical evolution models, in order to reproduce the observed bimodality in [α/Fe]–[Fe/H] between thick- and thin-disc stars.
Observed Changes in Natural Killer and T cell Phenotypes with Evaluation of Immune Outcome in a Longitudinal Cohort Following Sofosbuvir-Based Therapy for Chronic Hepatitis C Infection
Authors: Stevenson Timothy J , Barbour Youssef , McMahon Brian J , Townshend-Bulson Lisa , Hewitt Annette M , Espera Hannah G F , Homan Chriss , Holck Peter , Luna Sarah V , Knall Cindy , Simons Brenna C
Published: May 2019

Background

Chronic hepatitis C virus (HCV) infection diminishes immune function through cell exhaustion and repertoire alteration. Direct acting antiviral (DAA)-based therapy can restore immune cell subset function and reduce exhaustion states. However, the extent of immune modulation following DAA-based therapy and the role that clinical and demographic factors play remain unknown.

Methods

We examined natural killer (NK) cell, CD4+, and CD8+ T cell subsets along with activation and exhaustion phenotypes across an observational study of sofosbuvir-based treatment for chronic HCV infection. Additionally, we examined the ability of clinical variables and duration of infection to predict 12 weeks of sustained virologic response (SVR12) immune marker outcomes.

Results

We show that sofosbuvir-based therapy restores NK cell subset distributions and reduces chronic activation by SVR12. Likewise, T cell subsets, including HCV-specific CD8+ T cells, show reductions in chronic exhaustion markers by SVR12. Immunosuppressive CD4+ regulatory T cells decrease at 4-weeks treatment and SVR12. We observe the magnitude and direction of change in immune marker values from pretreatment to SVR12 varies greatly among participants. Although we observed associations between the estimated date of infection, HCV diagnosis date, and extent of immune marker outcome at SVR12, our regression analyses did not indicate any factors as strong SVR12 outcome predictors.

Conclusion

Our study lends further evidence of immune changes following sofosbuvir-based therapy. Further investigation beyond SVR12 and into factors that may predict posttreatment outcome is warranted.
COMPARISON OF BNCT DOSIMETRY CALCULATIONS USING DIFFERENT GEANT4 PHYSICS LISTS
Authors: Chen Zhao , Yang Peng , Lei Qin , Wen Yumei , He Donglin , Wu Zhangwen , Gou Chengjun
Published: May 2019

A comparison of Geant4 physics lists is conducted in the calculation of the total absorbed dose, boron dose, and non-boron dose in phantom, and the total depth-dose, boron depth-dose, and non-boron depth-dose along the beam axis for neutrons in a range of 0.0253 eV to 10 MeV. Physics processes are included for neutrons, photons, and charged particles, and calculations are conducted for neutrons and secondary particles. The results obtained from QBBC, QGSP_BERT, and neutron high precision physics lists with and without S(α, β) data are compared with the FLUKA values. Neutron high precision physics lists with S(α, β) data showed the best agreement with FLUKA in the studied energy range.
A dual role for peripheral GDNF signaling in nociception and cardiovascular reflexes
Authors: Queme Luis F. , Weyler Alex A. , Cohen Elysia R. , Hudgins Renita C , Jankowski Michael P.
Published: May 2019

Group III/IV muscle afferents transduce nociceptive signals and modulate exercise pressor reflexes (EPR). However, the mechanisms governing afferent responsiveness to dually modulate these processes are not well characterized. We and others have shown that ischemic injury can induce both nociception-related behaviors and exacerbated EPRs in the same mice. This correlated with primary muscle afferent sensitization and increased expression of glial cell line-derived neurotrophic factor (GDNF) in injured muscle and increased expression of GDNF family receptor α1 (GFRα1) in DRGs. Here we report that increased GDNF/GFRα1 signaling to sensory neurons from ischemia/reperfusion affected muscle modulated nociceptive-like behaviors, increased EPRs, and group III/IV muscle afferent sensitization. This appeared to have taken effect through increased CREB/CREB-binding protein mediated expression of the purinergic receptor P2X5 in the DRGs. Muscle GDNF signaling to neurons may play an important dual role in nociception and sympathetic reflexes and could provide a novel therapeutic target for treating complications from ischemic injuries.
Association of Obesity with Health Care Costs: A Mendelian Randomization study
Authors: Kurz Christoph , Laxy Michael
Published: May 2019

Causal effect estimates for the association of obesity with health care costs can be biased by reversed causation and omitted variables. In this study, we use genetic variants as instrumental variables to overcome these limitations. We estimate the effect of body mass index (BMI) and waist-to-hip ratio (WHR) on total health care costs using data from a German observational study. We find that the model using genetic instruments identifies additional annual costs of 189€ for a one unit increase in BMI, and additional 1165€ for a 0.1 unit increase in WHR. This is more than two times higher than estimates from linear regression without instrumental variables. We found little evidence of a non-linear relationship between BMI or WHR and health care costs. Our results imply that the use of genetic instruments can be a powerful tool for estimating causal effects in health economic evaluation that might be superior to other types of instruments where there is a strong association with a modifiable risk factor.
ADHD genetic liability and physical health outcomes - A two-sample Mendelian randomization study
Authors: Leppert Beate , Riglin Lucy , Dardani Christina , Thapar Ajay , Staley James R , Tilling Kate , Smith George Davey , Thapar Anita , Stergiakouli Evie
Published: May 2019

Objective

Attention-deficit/hyperactivity disorder (ADHD) has been associated with a broad range of physical health problems, including cardiometabolic, neurological and immunological conditions. Determining whether ADHD plays a causal role in these associations is of great importance for treatment and prevention but also because comorbid health problems further increase the serious social and economic impacts of ADHD on individuals and their families.

Methods

We used a two-sample Mendelian randomization (MR) approach to examine the causal relationships between genetic liability for ADHD and previously implicated physical health conditions. 11 genetic variants associated with ADHD were obtained from the latest summary statistics. Consistent effects obtained from IVW, weighted median and MR Egger methods were taken forward for sensitivity analysis, including bidirectional MR and multivariable MR (MVMR).

Results

We found evidence of a causal effect of genetic liability for ADHD on childhood obesity (OR:1.29 (95% CI:1.02,1.63)) and coronary artery disease (CAD) (OR:1.11 (95% CI:1.03,1.19)) with consistent results across different MR approaches. There was further evidence for a bidirectional relationship between genetic liability for ADHD and childhood obesity. The effect of genetic liability for ADHD on CAD was independent of smoking heaviness but was attenuated when simultaneously controlling for childhood obesity. There was little evidence for a causal effect on other cardiometabolic, immunological, neurological disorders and lung cancer.

Conclusion

Our findings strengthen the argument for early treatment and support for children with ADHD and their families and especially promoting physical activity and providing them with dietary advice to reduce future risk for developing CAD.

Key Message

Epidemiological studies have reported observational associations between ADHD and adult onset physical health outcomes.

Mendelian Randomization can be used to assess causal associations for ADHD on health outcomes that would traditionally require long term follow-up and may suffer confounding

We found that genetic liability for ADHD was associated with coronary artery disease and there was evidence for a bidirectional association between genetic liability for ADHD and childhood obesity

Multivariable mendelian randomization suggests that the link between genetic liability and coronary artery disease might partially act through childhood obesity but was independent of smoking heaviness

There was little evidence of a causal of ADHD on other cardiometabolic and immunological diseases.
Distributed dynamic coding for spatial working memory in hippocampal-prefrontal networks
Authors: Hernan AE , Mahoney JM , Curry W , Mawe S , Scott RC
Published: May 2019

Spatial working memory (SWM) is a central cognitive process during which the hippocampus and prefrontal cortex (PFC) encode and maintain spatial information for subsequent decision-making. This occurs in the context of ongoing computations relating to spatial position, recall of long-term memory, attention, amongst many others. To establish how intermittently presented information is integrated with ongoing computations we recorded single units, in both hippocampus and PFC, in control rats and those with a brain malformation during performance of a SWM task. Neurons that encode intermittent task parameters are also well-modulated in time and incorporated into a functional network across regions. Our results implicate a model in which ongoing oscillatory coordination among neurons in the hippocampal-PFC network defines a functional network that is poised to receive sensory inputs that are then integrated and multiplexed as working memory. These dynamics are systematically altered in disease and may provide potential targets for stimulation-based therapies.
Integrating exposure knowledge and serum suspect screening as a new approach to biomonitoring: An application in firefighters and office workers
Authors: Grashow Rachel , Bessonneau Vincent , Gerona Roy R. , Wang Aolin , Trowbridge Jessica , Lin Thomas , Buren Heather , Rudel Ruthann A. , Morello-Frosch Rachel
Published: May 2019

Background

Women firefighters are exposed to recognized and probable carcinogens, yet there are few studies of chemical exposures and associated health concerns, such as breast cancer. Biomonitoring often requires a priori selection of compounds to be measured, and so may not detect important, lesser known, exposures.

Objectives

The Women Firefighters Biomonitoring Collaborative (WFBC) created a biological sample archive and conducted a general suspect screen (GSS) to address this data gap.

Methods

Using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) we sought to identify candidate chemicals of interest in serum samples from 83 women firefighters (FF) and 79 office workers (OW) in San Francisco. Through the GSS approach we identified chemical peaks by matching accurate mass from serum samples against a custom chemical database of 740 slightly polar phenolic and acidic compounds, including many of relevance to firefighting or breast cancer etiology. We then selected chemicals for confirmation based on a priori criteria: 1) detection frequency or peak area differences between OW and FF; 2) evidence of mammary carcinogenicity, estrogenicity, or genotoxicity; and 3) not currently measured in large biomonitoring studies.

Results

We detected 620 chemicals that matched 300 molecular formulas in the WFBC database, including phthalate metabolites, phosphate flame retardant metabolites, phenols, pesticides, nitro-and nitroso-compounds, and per- and polyfluoroalkyl substances. The average number of chemicals from the database that were detected in participants was 72 and 70 in FF and OW, respectively. We confirmed 8 of the 20 prioritized suspect chemicals –including two alkylphenols, ethyl paraben, BPF, PFOSAA, benzophenone-3, benzyl p-hydroxybenzoate, and triphenyl phosphate--by running a matrix spike of the reference standards and using m/z, retention time and the confirmation of at least two fragment ions as criteria for matching.

Conclusion

GSS provides a powerful high-throughput approach to identify and prioritize novel chemicals for biomonitoring and health studies.
Consensus Machine Learning for Gene Target Selection in Pediatric AML Risk
Authors: Smith Jenny , Maden Sean K. , Lee David , Buie Ronald , Peddu Vikas , Shean Ryan , Busby Ben
Published: May 2019

Acute myeloid leukemia (AML) is a cancer of hematopoietic systems that poses high population burden, especially among pediatric populations. AML presents with high molecular heterogeneity, complicating patient risk stratification and treatment planning. While molecular and cytogenetic subtypes of AML are well described, significance of subtype-specific gene expression patterns is poorly understood and effective modeling of these patterns with individual algorithms is challenging. Using a novel consensus machine learning approach, we analyzed public RNA-seq and clinical data from pediatric AML patients (N = 137 patients) enrolled in the TARGET project.

We used a binary risk classifier (Low vs. Not-Low Risk) to study risk-specific expression patterns in pediatric AML. We applied the following workflow to identify important gene targets from RNA-seq data: (1) Reduce data dimensionality by identification of differentially expressed genes for AML risk (N = 1984 loci); (2) Optimize algorithm hyperparameters for each of 4 algorithm types (lasso, XGBoost, random forest, and SVM); (3) Study ablation test results for penalized methods (lasso and XGBoost); (4) Bootstrap Boruta permutations with a novel consensus importance metric.

We observed recurrently selected features across hyperparameter optimizations, ablation tests, and Boruta permutation bootstrap iterations, including HOXA9 and putative cofactors including MEIS1. Consensus feature selection from Boruta bootstraps identified a larger gene set than single penalized algorithm runs (lasso or XGBoost), while also including correlated and predictive genes from ablation tests.

We present a consensus machine learning approach to identify gene targets of likely importance for pediatric AML risk. The approach identified a moderately sized set of recurrent important genes from across 4 algorithm types, including genes identified across ablation tests with penalized algorithms (HOXA9 and MEIS1). Our approach mitigates exclusion biases of penalized algorithms (lasso and XGBoost) while obviating arbitrary importance cutoffs for other types (SVM and random forest). This approach is readily generalizable for research of other heterogeneous diseases, single-assay experiments, and high-dimensional data. Resources and code to recreate our findings are available online.
Mice tune out not in: Violation of prediction drives auditory saliency
Authors: Rogalla Meike M. , Rauser Inga , Schulze Karsten , Osterhagen Lasse , Hildebrandt K Jannis
Published: May 2019

Successful navigation in complex acoustic scenes requires focusing on relevant sounds while ignoring irrelevant distractors. It has been argued that the ability to track stimulus statistics and generate predictions supports the choice what to attend and what to ignore. However, the role of these predictions about future auditory events in drafting decisions remains elusive. While most psychophysical studies in humans indicate that expected stimuli serve as implicit cues attracting attention, most work studying physiological auditory processing in animals highlights the detection of unexpected, surprising stimuli. Here, we tested whether in the mouse, target probability is used as an implicit cue attracting attention or whether detection is biased towards low-probability deviants using an auditory detection task. We implemented a probabilistic choice model to investigate whether a possible dependence on stimulus statistics arises from short term serial correlations or from integration over longer periods. Our results demonstrate that target detectability in mice decreases with increasing probability, contrary to humans. We suggest that mice indeed track probability over a time scale of at least several minutes but do not use this information in the same way as humans do: instead of maximizing reward by focusing on high-probability targets, the saliency of a target is determined by surprise.
An active inference approach to modeling structure learning: concept learning as an example case
Authors: Smith Ryan , Schwartenbeck Philipp , Parr Thomas , Friston Karl J.
Published: May 2019

Within computational neuroscience, the algorithmic and neural basis of structure learning remains poorly understood. Concept learning is one primary example, which requires both a type of internal model expansion process (adding novel hidden states that explain new observations), and a model reduction process (merging different states into one underlying cause and thus reducing model complexity via meta-learning). Although various algorithmic models of concept learning have been proposed within machine learning and cognitive science, many are limited to various degrees by an inability to generalize, the need for very large amounts of training data, and/or insufficiently established biological plausibility. Using concept learning as an example case, we introduce a novel approach for modeling structure learning – and specifically state-space expansion and reduction – within the active inference framework and its accompanying neural process theory. Our aim is to demonstrate its potential to facilitate a novel line of active inference research in this area. The approach we lay out is based on the idea that a generative model can be equipped with extra (hidden state or cause) ‘slots’ that can be engaged when an agent learns about novel concepts. This can be combined with a Bayesian model reduction process, in which any concept learning – associated with these slots – can be reset in favor of a simpler model with higher model evidence. We use simulations to illustrate this model’s ability to add new concepts to its state space (with relatively few observations) and increase the granularity of the concepts it currently possesses. We also simulate the predicted neural basis of these processes. We further show that it can accomplish a simple form of ‘one-shot’ generalization to new stimuli. Although deliberately simple, these simulation results highlight ways in which active inference could offer useful resources in developing neurocomputational models of structure learning. They provide a template for how future active inference research could apply this approach to real-world structure learning problems and assess the added utility it may offer.
High contribution ofPelagibacteralesto bacterial community composition and activity in spring blooms off Kerguelen Island (Southern Ocean)
Authors: Dinasquet J. , Landa M. , Obernosterer I.
Published: May 2019

The ecology of Pelagibacterales (SAR11 clade), the most abundant bacterial group in the ocean, has been intensively studied in temperate and tropical ocean regions, but the distribution patterns of this clade remains largely unexplored in the Southern Ocean. Through amplicon sequencing of the 16S rRNA genes, we assessed the contribution of Pelagibacterales to bacterial community composition in the naturally iron fertilized region off Kerguelen Island (Southern Ocean). We investigated the upper 300 m water column at seven sites located in early spring phytoplankton blooms and at one site in HNLC waters. Despite pronounced vertical patterns of the bacterioplankton assemblages, the SAR11 clade had high relative abundances at all depths and sites, averaging 40% (±15%) of the total community relative abundance. Micro-autoradiography combined with CARD-FISH further revealed that the SAR11 clade contributed substantially (45-60% in surface waters) to bacterial biomass production (as determined by3H leucine incorporation). A clear niche partitioning of the further resolved SAR11 subclades was observed with depth layers, but differences among sites were detectable for only a few subclades. Our study provides novel observations of the distribution and contribution to the marine carbon cycle of the SAR11 clade in the cold waters of the Southern Ocean.
ADAPTS: Automated Deconvolution Augmentation of Profiles for Tissue Specific cells
Authors: Danziger Samuel A , Gibbs David L , Shmulevich Ilya , McConnell Mark , Trotter Matthew WB , Schmitz Frank , Reiss David J , Ratushny Alexander V
Published: May 2019

Immune cell infiltration of tumors can be an important component for determining patient outcomes, e.g. by inferring immune cell presence by deconvolving gene expression data drawn from a heterogenous mix of cell types. One particularly powerful family of deconvolution techniques uses signature matrices of genes that uniquely identify each cell type as determined from cell type purified gene expression data. Many methods of this type have been recently published, often including new signature matrices appropriate for a single purpose, such as investigating a specific type of tumor. The package ADAPTS helps users make the most of this expanding knowledge base by introducing a framework for cell type deconvolution. ADAPTS implements modular tools for customizing signature matrices for new tissue types by adding custom cell types or building new matrices de novo, including from single cell RNAseq data. It includes a common interface to several popular deconvolution algorithms that use a signature matrix to estimate the proportion of cell types present in heterogenous samples. ADAPTS also implements a novel method for clustering cell types into groups that are hard to distinguish by deconvolution and then re-splitting those clusters using hierarchical deconvolution. We demonstrate that the techniques implemented in ADAPTS improve the ability to reconstruct the cell types present in a single cell RNAseq data set in a blind predictive analysis. ADAPTS is currently available for use in R on CRAN and GitHub.
Genetic homogeneity in face of morphological heterogeneity in the harbor porpoises from the Black Sea and adjacent waters
Authors: Chehida Yacine Ben , Thumloup Julie , Vishnyakova Karina , Gol’din Pavel , Fontaine Michael C.
Published: May 2019

Isolated from North Atlantic populations, the Black Sea harbor porpoise (Phocoena phocoena relicta) is listed as Endangered due to the massive population decline triggered by historical hunting, and subsequently through fisheries bycatch, and other human activities. Of paramount importance for its conservation, is the characterization of the population structure. While morphological heterogeneity suggested population subdivision, previous genetic studies have failed to find any differences. Here, we investigated the population genetic structure of 144 harbor porpoises sampled opportunistically from across the entire subspecies range including the Aegean, Marmara, Black, and Azov Seas. Genetic variation of across one-fourth of the mitochondrial genome, in combination with the analysis of ten microsatellite loci revealed a nearly complete genetic homogeneity. While simulations show that this inability to reject panmixia does not stem from a lack of power (power to detectFSTof 0.008). A genetic time-lag effect limiting our ability to detect population subdivision is also unlikely when effective population size is low, as is the case here. For now, genetic panmixia among porpoises of the Black Sea and adjacent waters cannot be rejected. Population subdivision may well exist, but conclusive evidence would require an improved sampling providing suitable contrasts (e.g., age, sex, season). Also, a genome scale study providing access to neutral and selected genetic variation may reveal cryptic differentiation indicative of ecologically subdivisions. As a precautionary approach, definition of management units should be based on evidence of population heterogeneity obtained from multidisciplinary approaches rather than just genetics.
Predicting functional long non-coding RNAs validated by low throughput experiments
Authors: Zhou Bailing , Yang Yuedong , Zhan Jian , Dou Xianghua , Wang Jihua , Zhou Yaoqi
Published: May 2019

High-throughput techniques have uncovered hundreds and thousands of long non-coding RNAs (lncRNAs). Among them, only a small fraction has experimentally validated functions (EVlncRNAs) by low-throughput methods. What fraction of lncRNAs from high-throughput experiments (HTlncRNAs) is truly functional is an active subject of debate. Here, we developed the first method to distinguish EVlncRNAs from HTlncRNAs and mRNAs by using Support Vector Machines and found that EVlncRNAs can be well separated from HTlncRNAs and mRNAs with 0.6 for Matthews correlation coefficient, 64% for sensitivity, and 81% for precision for the independent human test set. The most discriminative features are related to sequence conservations at RNA (for separating from HTlncRNAs) and protein (for separating from mRNA) levels. The method is found to be robust as the human-RNA-trained model is applicable to independent mouse RNAs with similar accuracy and to a lesser extent to plant RNAs. The method can recover newly discovered EVlncRNAs with high sensitivity. Its application to randomly selected 2000 human HTlncRNAs indicates that a large number of functional lncRNAs are waiting to be validated. The method is expected to speed up and reduce the cost of the discovery by prioritizing potentially functional lncRNAs prior to experimental validation. EVlncRNA-pred is available as a web server at http://biophy.dzu.edu.cn/lncrnapred/index.html. All datasets used in this study can be obtained from the same website.
Jumping To Conclusions, General Intelligence, And Psychosis Liability: Findings From The Multi-Centre EU-GEI Case-Control Study
Authors: Tripoli Giada , Quattrone Diego , Ferraro Laura , Gayer-Anderson Charlotte , Rodriguez Victoria , Cascia Caterina La , Barbera Daniele La , Sartorio Crocettarachele , Tarricone Ilaria , Berardi Domenico , Szöke Andrei , Arango Celso , Tortelli Andrea , Llorca Pierre-Michel , de Haan Lieuwe , Velthorst Eva , Bobes Julio , Bernardo Miguel , Sanjuán Julio , Santos Jose Luis , Arrojo Manuel , Del-Ben Cristina Marta , Menezes Paulo Rossi , Selten Jean-Paul ,   EU-GEI WP2 Group, Jones Peter B , Richards Alex , O’Donovan Michael , Rutten Bart PF , van Os Jim , Morgan Craig , Sham Pak C , Murray Robin M , Murray Graham K , Forti Marta Di
Published: May 2019

Background

The “jumping to conclusions” (JTC) bias is associated with both psychosis and general cognition but their relationship is unclear. In this study, we set out to clarify the relationship between the JTC bias, IQ, psychosis and polygenic liability to schizophrenia and IQ.

Methods

817 FEP patients and 1294 population-based controls completed assessments of general intelligence (IQ), and JTC (assessed by the number of beads drawn on the probabilistic reasoning “beads” task) and provided blood or saliva samples from which we extracted DNA and computed polygenic risk scores for IQ and schizophrenia.

Results

The estimated proportion of the total effect of case/control differences on JTC mediated by IQ was 79%. Schizophrenia Polygenic Risk Score (SZ PRS) was non-significantly associated with a higher number of beads drawn (B= 0.47, 95% CI −0.21 to 1.16, p=0.17); whereas IQ PRS (B=0.51, 95% CI 0.25 to 0.76, p<0.001) significantly predicted the number of beads drawn, and was thus associated with reduced JTC bias. The JTC was more strongly associated with higher level of psychotic-like experiences (PLE) in controls, including after controlling for IQ (B= −1.7, 95% CI −2.8 to −0.5, p=0.006), but did not relate to delusions in patients.

Conclusions

the JTC reasoning bias in psychosis is not a specific cognitive deficit but is rather a manifestation or consequence, of general cognitive impairment. Whereas, in the general population, the JTC bias is related to psychotic-like experiences, independent of IQ. The work has potential to inform interventions targeting cognitive biases in early psychosis.
Nucleosomal DNA dynamics mediate Oct4 pioneer factor binding
Authors: Huertas Jan , MacCarthy Caitlin M. , Schöler Hans , Cojocaru Vlad
Published: May 2019

Transcription factor (TF) proteins bind to DNA to regulate gene expression. Normally, accessibility to DNA is required for their function. However, in the nucleus the DNA is often inaccessible, wrapped around histone proteins in nucleosomes forming the chromatin. Pioneer TFs are thought to induce chromatin opening by recognizing their DNA binding sites on nucleosomes. For example, Oct4, a master regulator and inducer of stem cell pluripotency, binds to DNA in nucleosomes in a sequence specific manner. Here we reveal the structural dynamics of nucleosomes that mediate Oct4 binding. Nucleosome mobility and the amplitude of nucleosome motions such as breathing and twisting correlate with the number of Oct4 binding sites available. Moreover, the regions around the binding sites display higher local mobility. Probing different structures of Oct4-nucleosome complexes, we show that alternative configurations display stable protein-DNA interactions and are compatible with the DNA curvature and DNA-histone interactions.
Dysregulated Alternative Splicing Landscape Identifies Intron Retention as a Hallmark and Spliceosome as a Therapeutic Vulnerability in Aggressive Prostate Cancer
Authors: Zhang Dingxiao , Hu Qiang , Ji Yibing , Chao Hsueh-Ping , Tracz Amanda , Kirk Jason , Buonamici Silvia , Zhu Ping , Wang Jianmin , Liu Song , Tang Dean G.
Published: May 2019

Dysregulation of mRNA alternative splicing (AS) has been implicated in development and progression of hematological malignancies. Here we describe the first comprehensive AS landscape in the spectrum of human prostate cancer (PCa) development, progression and therapy resistance. We find that the severity of splicing dysregulation correlates with disease progression and establish intron retention (IR) as a hallmark of PCa stemness and aggressiveness. Systematic interrogation of 274 splicing-regulatory genes (SRGs) uncovers prevalent SRG mutations associated with, mainly, copy number variations leading to mis-expression of ~68% of SRGs during PCa evolution. Consequently, we identify many SRGs as prognostic markers associated with splicing disruption and patient outcome. Interestingly, androgen receptor (AR) controls a splicing program distinct from its transcriptional regulation. The spliceosome modulator, E7107, reverses cancer aggressiveness and abolishes the growth of castration-resistant PCa (CRPC) models. Altogether, we establish aberrant AS landscape caused by dysregulated SRGs as a novel therapeutic vulnerability for CRPC.

Statement of significance

We present the first comprehensive AS landscape during PCa evolution and link genomic and transcriptional alterations in SRGs to global splicing dysregulation. AR regulates splicing in pri-PCa and CRPC distinct from its transcriptional regulation. Intron retention is a hallmark for and spliceosome represents a therapeutic vulnerability in aggressive PCa.
Sleep deprivation rapidly upregulates serotonin 2A receptor expression via the immediate early gene Egr3
Authors: Zhao X. , Meyers K. T. , McBride A. , Marballi K. K. , Maple A. M. , Beck K. L. , Kang P. , Palner M. , Overgaard A. , Knudsen G. M. , Gallitano A. L.
Published: May 2019

Serotonin 2A receptors (5-HT2ARs) mediate the effects of hallucinogenic drugs and antipsychotic medications, and are reduced in schizophrenia patients’ brains. However, the mechanisms that regulate 5-HT2AR expression remain poorly understood. We show that an environmental stimulus, sleep deprivation, upregulates 5-HT2ARs in the mouse frontal cortex (FC) in just 6-8 hours. This induction requires the immediate early gene transcription factor early growth response 3 (Egr3). Further, EGR3 binds to the Htr2a promoter in the FC in vivo, and drives reporter construct expression in vitro via two Htr2a promoter binding sites. These findings suggest that EGR3 directly regulates FC Htr2a expression in response to physiologic stimuli, providing a mechanism by which environment rapidly alters levels of a brain receptor that mediates symptoms, and treatment, of mental illness.

One Sentence Summary

Just 6-8 hours of sleep deprivation upregulates brain levels of the receptor that mediates the response to hallucinogens.
Real Time Ultrasound Molecular Imaging of Prostate Cancer with PSMA-targeted Nanobubbles
Authors: Perera Reshani , de Leon Al , Wang Xinning , Wang Yu , Ramamurthy Gopal , Peiris Pubudu , Abenojar Eric , Basilion James P. , Exner Agata A.
Published: May 2019

Contrast-enhanced ultrasound with microbubbles has shown promise in detection of prostate cancer (PCa), but sensitivity and specificity of detection remain challenging. Targeted nanoscale contrast agents with improved capability to accumulate in tumors may result in prolonged signal enhancement and improved detection of PCa with ultrasound. Here we report on a new nanobubble contrast agent that specifically targets prostate specific membrane antigen (PSMA) overexpressed in most prostate tumors. The PSMA-targeted bubbles (PSMA-NB) were utilized to simultaneously image dual flank PCa tumors (PSMA-positive PC3pip and PSMA-negative PC3flu) to examine whether the biomarker can be successfully detected and imaged using this probe in a mouse model. Results demonstrate that active targeting of NBs to PSMA rapidly and selectively enhances tumor accumulation and is critical for tumor retention of the contrast agent. Importantly, these processes could be visualized and quantified, in real time, with standard clinical ultrasound. Such demonstration of the immense yet underutilized potential of ultrasound in the area of molecular imaging can open the door to future opportunities for improving sensitivity and specificity of cancer detection using parametric NB-enhanced ultrasound imaging.
Reciprocal connectivity between secondary auditory cortical field and amygdala in mice
Authors: Tsukano Hiroaki , Hou Xubin , Horie Masao , Kitaura Hiroki , Nishio Nana , Hishida Ryuichi , Takahashi Kuniyuki , Kakita Akiyoshi , Takebayashi Hirohide , Sugiyama Sayaka , Shibuki Katsuei
Published: May 2019

Recent studies have examined the feedback pathway from the amygdala to the auditory cortex in conjunction with the feedforward pathway from the auditory cortex to the amygdala. However, these connections have not been fully characterized. Here, to visualize the comprehensive connectivity between the auditory cortex and amygdala, we injected cholera toxin subunit b (CTB), a bidirectional tracer, into multiple subfields in the mouse auditory cortex after identifying the location of these subfields using flavoprotein fluorescence imaging. After injecting CTB into the secondary auditory field (A2), we found densely innervated CTB-positive axon terminals that were mainly located in the lateral amygdala (La), and slight innervations in other divisions such as the basal amygdala. Moreover, we found a large number of retrogradely-stained CTB-positive neurons in La after injecting CTB into A2. When injecting CTB into the primary auditory cortex (A1), a small number of CTB-positive neurons and axons were visualized in the amygdala. Finally, we found a near complete absence of connections between the other auditory cortical fields and the amygdala. These data suggest that reciprocal connections between A2 and La are main conduits for communication between the auditory cortex and amygdala in mice.
Dsuite - fast D-statistics and related admixture evidence from VCF files
Authors: Malinsky Milan , Matschiner Michael , Svardal Hannes
Published: May 2019

Patterson’s D, also known as the ABBA-BABA statistic, and related statistics such as the f4-ratio, are commonly used to assess evidence of gene flow between populations or closely related species. Currently available implementations require custom file formats and are impractical to evaluate all gene flow hypotheses across datasets with many populations or species.

Dsuite is a fast C++ implementation, allowing genome scale calculations of the D and f4-ratio statistics across all combinations of tens or hundreds of populations or species directly from a variant call format (VCF) file. Furthermore, the program can provide evidence of whether introgression is confined to specific loci and aid in interpretation of a system of f4-ratio results by implementing the ‘f-branch’ method.

Dsuite is available at https://github.com/millanek/Dsuite, is straightforward to use, substantially more computationally efficient than other comparable programs, and presents a novel suite of tools and statistics, including some not previously available in any software package.

Thus, Dsuite facilitates assessment of evidence for gene flow, especially across large genomic datasets.
Automated data-intensive forecasting of plant phenology throughout the United States
Authors: Taylor Shawn D. , White Ethan P.
Published: May 2019

Phenology - the timing of cyclical and seasonal natural phenomena such as flowering and leaf out - is an integral part of ecological systems with impacts on human activities like environmental management, tourism, and agriculture. As a result, there are numerous potential applications for actionable predictions of when phenological events will occur. However, despite the availability of phenological data with large spatial, temporal, and taxonomic extents, and numerous phenology models, there has been no automated species-level forecasts of plant phenology. This is due in part to the challenges of building a system that integrates large volumes of climate observations and forecasts, uses that data to fit models and make predictions for large numbers of species, and consistently disseminates the results of these forecasts in interpretable ways. Here we describe a new near-term phenology forecasting system that makes predictions for the timing of budburst, flowers, ripe fruit, and fall colors for 78 species across the United States up to 6 months in advance and is updated every four days. We use the lessons learned in developing this system to provide guidance developing large-scale near-term ecological forecast systems more generally, to help advance the use of automated forecasting in ecology.
Real-time, MinION-based, amplicon sequencing for lineage typing of infectious bronchitis virus from upper respiratory samples
Authors: Butt Salman L. , Erwood Eric C. , Zhang Jian , Sellers Holly S. , Young Kelsey , Lahmers Kevin K. , Stanton James B.
Published: May 2019

Infectious bronchitis (IB) causes significant economic losses in the global poultry industry. Control of infectious bronchitis is hindered by the genetic diversity of the causative agent, infectious bronchitis virus (IBV), which has led to the emergence of several serotypes that lack complete serologic cross-protection. While serotyping by definition requires immunologic characterization, genotyping is an efficient means to identify IBVs detected in samples. Sanger sequencing of the S1 subunit of the spike gene is currently used to genotype IBV; however, the universal S1 PCR was created to work from cultured IBV and it is inefficient at detecting mixed isolates. This paper describes a MinION-based AmpSeq method that genetically typed IBV from clinical samples, including samples with multiple isolates. Total RNA was extracted from fifteen tracheal scrapings and choanal cleft swab samples, randomly reverse transcribed, and PCR amplified using modified S1-targeted primers. Amplicons were barcoded to allow for pooling of samples, processed per manufacturer’s instructions into a 1D MinION sequencing library, and sequenced on the MinION. The AmpSeq method detected IBV in 13 of 14 IBV-positive samples. AmpSeq accurately detected and genotyped both IBV lineages in three of five samples containing two IBV lineages. Additionally, one sample contained three IBV lineages, and AmpSeq accurately detected two of the three. Strain identification, including detection of different strains from the same lineage, was also possible with this AmpSeq method. The results demonstrate the feasibility of using MinION-based AmpSeq for rapid and accurate identification and lineage typing of IBV from oral swab samples.
CRISPR editing of sftb-1/SF3B1 in C. elegans allows the identification of synthetic interactions with cancer-related mutations and the chemical inhibition of splicing
Authors: Serrat Xènia , Kukhtar Dmytro , Cornes Eric , Esteve-Codina Anna , Benlloch Helena , Cecere Germano , Cerón Julián
Published: May 2019

SF3B1 is the most frequently mutated splicing factor in cancer. Mutations in SF3B1 confer growth advantages to cancer cells but they may also confer vulnerabilities that can be therapeutically targeted. In contrast to other animal models, SF3B1 cancer mutations can be maintained in homozygosis in C. elegans, allowing synthetic lethal screens with a homogeneous population of animals. These mutations cause alternative splicing (AS) defects in C. elegans, as it occurs in SF3B1-mutated human cells. In a screen, we identified RNAi of U2 snRNP components that cause synthetic lethality with sftb-1/SF3B1 mutations. We also detected synthetic interactions between sftb-1 mutants and cancer-related mutations in uaf-2/U2AF1 or rsp-4/SRSF2, demonstrating that this model can identify interactions between mutations that are mutually exclusive in human tumors. Finally, we have edited an SFTB-1 domain to sensitize C. elegans to the splicing inhibitor pladienolide B. Thus, we have established a multicellular model for SF3B1 mutations amenable for high-throughput genetic and chemical screens.
Complex community-wide consequences of consumer sexual dimorphism
Authors: De Lisle Stephen P. , Schrieber Sebastian J. , Bolnick Daniel I.
Published: May 2019

Sexual dimorphism is a ubiquitous source of within-species variation, yet the communitylevel consequences of sex differences remain poorly understood. Here, we analyze a bitrophic model of two competing resource species and a sexually-reproducing consumer species. We show that consumer sex differences in resource acquisition can have striking consequences for consumer-resource coexistence, abundance, and dynamics. Under both direct interspecific competition and apparent competition between two resource species, sexual dimorphism in consumers’ attack rates can mediate coexistence of the resource species, while in other cases can lead to exclusion when stable coexistence is typically expected. Slight sex differences in total resource acquisition also can reverse competitive outcomes and lead to density cycles. These effects are expected whenever both consumer sexes require different amounts or types of resources to reproduce. Our results suggest that consumer sexual dimorphism, which is common, has wide-reaching implications for the assembly and dynamics of natural communities.

Statement of authorship

DB SD and SJS designed the study, SJS performed the mathematical analysis, SD performed the simulations and drafted the manuscript. All authors revised the manuscript.

Data accessibility statement

No data is used