bluuebunny/crossref_metadata_2025 huggingface dataset:
Microstructural white matter and links with subcortical structures in chronic schizophrenia: A free-water imaging approach
Authors: Gurholt Tiril P. , Haukvik Unn K. , Lonning Vera , Jönsson Erik G. , Pasternak Ofer , Agartz Ingrid
Published: May 2019

Schizophrenia is a severe mental disorder with often a chronic course. Neuroimaging studies report brain abnormalities in both white and gray matter structures. However, the relationship between microstructural white matter differences and volumetric subcortical structures is not known.

We investigated 30 long-term treated patients with schizophrenia (mean age 51.1±7.9 years, illness duration 27.6±8.0 years) and 42 healthy controls (mean age 54.1±9.1 years) using 3 T diffusion and structural magnetic resonance imaging. The free-water imaging method was used to model the diffusion signal, and subcortical volumes were obtained from FreeSurfer. We applied multiple linear regression to investigate associations between (i) patient status and regional white matter microstructure, (ii) medication dose or clinical symptoms on white matter microstructure in patients, and (iii) for interactions between subcortical volumes and diagnosis for microstructural white matter regions showing significant patient-control differences.

The patients had significantly decreased free-water corrected fractional anisotropy (FAt), explained by decreased axial diffusivity and increased radial diffusivity (RDt) bilaterally in the anterior corona radiata (ACR) and the left anterior limb of the internal capsule (ALIC) compared to controls. In the fornix, the patients had significantly increased RDt. In patients, positive symptoms were associated with localized increased free-water and negative symptoms with localized decreased FAtand increased RDt. There were significant interactions between patient status and several subcortical structures on white matter microstructure and the free-water compartment for left ACR and fornix, and limited to the free-water compartment for right ACR and left ALIC. The Cohen’s d effect sizes were medium to large (0.61 to 1.20, absolute values).

The results suggest a specific pattern of frontal white matter axonal degeneration and demyelination and fornix demyelination that is attenuated in the presence of larger structures of the limbic system in patients with chronic schizophrenia. Findings warrants replication in larger samples.
Is useful research data usually shared? An investigation of genome-wide association study summary statistics
Authors: Thelwall Mike A. , Munafò Marcus , Bleda Amalia Mas , Stuart Emma , Makita Meiko , Weigert Verena , Keene Chris , Khan Nushrat , Drax Katie , Kousha Kayvan
Published: May 2019

Primary data collected during a research study is increasingly shared and may be re-used for new studies. To assess the extent of data sharing in favourable circumstances and whether such checks can be automated, this article investigates the summary statistics of primary human genome-wide association studies (GWAS). This type of data is highly suitable for sharing because it is a standard research output, is straightforward to use in future studies (e.g., for secondary analysis), and may be already stored in a standard format for internal sharing within multi-site research projects. Manual checks of 1799 articles from 2010 and 2017 matching a simple PubMed query for molecular epidemiology GWAS were used to identify 330 primary human GWAS papers. Of these, only 10.6% reported the location of a complete set of GWAS summary data, increasing from 4.3% in 2010 to 16.8% in 2017. Whilst information about whether data was shared was usually located clearly within a data availability statement, the exact nature of the shared data was usually unspecified. Thus, data sharing is the exception even in suitable research fields with relatively strong norms regarding data sharing. Moreover, the lack of clear data descriptions within data sharing statements greatly complicates the task of automatically characterising shared data sets.
ADrosophilametainflammation-blood tumor model links aspirin-triggered eicosanoid-like mediators to immune signaling
Authors: Panettieri Silvio , Paddibhatla Indira , Chou Jennifer , Rajwani Roma , Moore Rebecca S. , Goncharuk Tamara , John George , Govind Shubha
Published: May 2019

Accumulating data from epidemiologic studies are linking aspirin’s use to a decline in chronic and metabolic inflammation that underlies many human diseases including some cancers. Aspirin reduces cyclooxygenase-mediated pro-inflammatory prostaglandins and promotes the production of pro-resolution molecules. Aspirin also triggers the production of anti-inflammatory electrophilic mono-oxygenated lipid mediators implicated in human pathologies. With the goal of developing a model system for studying the mechanisms of aspirin in reducing inflammation, we investigated aspirin’s effects in fruit fly models of chronic inflammation. Ectopic Toll/NF-κB and JAK/STAT signaling inD. melanogasterresults in an overproliferation of hematopoietic blood progenitors coupled with metabolic inflammation in adipocytes. We report that, like mammals, flies are sensitive to aspirin treatment and it modulates the Toll-NF-κB axis. Aspirin-treated mutants simultaneously experience reduction in metabolic inflammation, mitosis, ectopic immune signaling, and macrophage infiltration. Moreover, flies synthesize 13-HODE, and aspirin triggers 13-EFOX-L2 production in mutants. In such flies with ectopic immune signaling, providing 13-HODE’s precursor linoleic acid or performing targeted knockdown of transcription factor STAT in inflammatory blood cells boosts 13-EFOX-L2 levels while decreasing metabolic inflammation. Thus, hematopoietic cells regulate metabolic inflammation in flies, and their effects can be reversed by pharmaceutical or dietary intervention, suggesting deep phylogenetic conservation in animals’ ability to resolve systemic inflammation and repair tissue damage. This model system brings the power ofDrosophilagenetics to bear on immuno-metabolic mechanisms that boost systemic health and healing, with the potential to identify new targets for the treatment of chronic diseases in humans.
Legacy Data Confounds Genomics Studies
Authors: Anderson-Trocmé Luke , Farouni Rick , Bourgey Mathieu , Kamatani Yoichiro , Higasa Koichiro , Seo Jeong-Sun , Kim Changhoon , Matsuda Fumihiko , Gravel Simon
Published: May 2019

Recent reports have identified differences in the mutational spectra across human populations. While some of these reports have been replicated in other cohorts, most have been reported only in the 1000 Genomes Project (1kGP) data. While investigating an intriguing putative population stratification within the Japanese population, we identified a previously unreported batch effect leading to spurious mutation calls in the 1kGP data and to the apparent population stratification. Because the 1kGP data is used extensively, we find that the batch effects also lead to incorrect imputation by leading imputation servers and a small number of suspicious GWAS associations. Lower-quality data from the early phases of the 1kGP thus continues to contaminate modern studies in hidden ways. It may be time to retire or upgrade such legacy sequencing data.
Robust Microfabrication of Highly Parallelized Three-Dimensional Microfluidics on Silicon
Authors: Yadavali Sagar , Lee Daeyeon , Issadore David
Published: May 2019

We present a new, robust three dimensional microfabrication method for highly parallel microfluidics, to improve the throughput of on-chip material synthesis by allowing parallel and simultaneous operation of many replicate devices on a single chip. Recently, parallelized microfluidic chips fabricated in Silicon and glass have been developed to increase the throughput of microfluidic materials synthesis to an industrially relevant scale. These parallelized microfluidic chips require large arrays (> 10,000) of Through Silicon Vias (TSVs) to deliver fluid from delivery channels to the parallelized devices. Ideally, these TSVs should have a small footprint to allow a high density of features to be packed into a single chip, have channels on both sides of the wafer, and at the same time minimize debris generation and wafer warping to enable permanent bonding of the device to glass. Because of these requirements and challenges, previous approaches cannot be easily applied to produce three dimensional microfluidic chips with a large array of TSVs. To address these issues, in this paper we report a fabrication strategy for the robust fabrication of three-dimensional Silicon microfluidic chips consisting of a dense array of TSVs, designed specifically for highly parallelized microfluidics. In particular, we have developed a two-layer TSV design that allows small diameter vias (d < 20 µm) without sacrificing the mechanical stability of the chip and a patterned SiO2 etch-stop layer to replace the use of carrier wafers in Deep Reactive Ion Etching (DRIE). Our microfabrication strategy allows >50,000 (d = 15 µm) TSVs to be fabricated on a single 4” wafer, using only conventional semiconductor fabrication equipment, with 100% yield (M = 16 chips) compared to 30% using previous approaches. We demonstrated the utility of these fabrication strategies by developing a chip that incorporates 20,160 flow focusing droplet generators onto a single 4” Silicon wafer, representing a 100% increase in the total number of droplet generators than previously reported. To demonstrate the utility of this chip for generating pharmaceutical microparticle formulations, we generated 5–9 µm polycaprolactone particles with a CV <5% at a rate as high as 60 g/hr (> 1 trillion particles / hour).
DNA energy constraints shape biological evolutionary trajectories
Authors: Fariselli Piero , Taccioli Cristian , Pagani Luca , Maritan Amos
Published: May 2019

Most living systems rely on double-stranded DNA (dsDNA) to store their genetic information and perpetrate themselves. Thus, the biological information contained within a dsDNA molecule, in terms of a linear sequence of nucleotides, has been considered the main target of the evolution. However, in this information-centred perspective, certain DNA sequence symmetries are difficult to explain. Here we show that these patterns can emerge from the physical peculiarities of the dsDNA molecule itself and the maximum entropy principle alone, rather than from biological or environmental evolutionary pressure. Our predictions are valid for both prokaryotes and eukaryotes, and also inform the interpretation of observed codon biases and context-dependent mutation patterns in human populations. Our results suggest that the double helix energy constraints and, more generally, the physical properties of the dsDNA are the hard drivers of the overall DNA sequence architecture, whereas the biological selective processes act as soft drivers, which only under extraordinary circumstances overtake the overall entropy content of the genome.
CROSSalive: a web server for predicting the in vivo structure of RNA molecules
Authors: Ponti Riccardo Delli , Armaos Alexandros , Tartaglia Gian Gaetano
Published: May 2019

Here we introduce CROSSalive, an algorithm to predict the RNA secondary structure profile (double and single stranded regions) in vivo and without sequence length limitations. Using predictions of protein interactions CROSSalive predicts the effect of N6 adenosine methylation (m6a) on RNA structure. Trained on icSHAPE data in presence (m6a+) and absence (m6a-) of methylation CROSSalive achieves an accuracy of 0.88 on the test set. The algorithm was also applied to the murine long non-coding RNA Xist (17900 nt, not present in the training) and shows a Pearson’s correlation of 0.45 with SHAPE-map data. CROSSalive webserver is freely accessible at the following page: http://service.tartaglialab.com/new_submission/crossalive
rpoB, a promising marker for analyzing the diversity of bacterial communities by amplicon sequencing
Authors: Ogier Jean-Claude , Pagès Sylvie , Galan Maxime , Barret Mathieu , Gaudriault Sophie
Published: May 2019

Background

Microbiome composition is frequently studied by the amplification and high-throughput sequencing of specific molecular markers (metabarcoding). Various hypervariable regions of the 16S rRNA gene are classically used to estimate bacterial diversity, but other universal bacterial markers with a finer taxonomic resolution could be employed. We compared specificity and sensitivity between a portion of the rpoB gene and the V3V4 hypervariable region of the 16S rRNA gene.

Results

We first designed universal primers for rpoB suitable for use with Illumina sequencing-based technology and constructed a reference rpoB database of 45,000 sequences. The rpoB and V3V4 markers were amplified and sequenced from (i) a mock community of 19 bacterial strains from both Gram-negative and Gram-positive lineages; (ii) bacterial assemblages associated with entomopathogenic nematodes. In metabarcoding analyses of mock communities with two analytical pipelines (FROGS and DADA2), the estimated diversity captured with the rpoB marker resembled the expected composition of these mock communities more closely than that captured with V3V4. The rpoB marker had a higher level of taxonomic affiliation, a higher sensitivity (detection of all the species present in the mock communities), and a higher specificity (low rates of spurious OTU detection) than V3V4. We applied both primers to infective juveniles of the nematode Steinernema glaseri. Both markers showed the bacterial community associated with this nematode to be of low diversity (< 50 OTUs), but only rpoB reliably detected the symbiotic bacterium Xenorhabdus poinarii.

Conclusions

Our results confirm that different microbiota composition data may be obtained with different markers. We found that rpoB was a highly appropriate marker for assessing the taxonomic structure of mock communities and the nematode microbiota. Further studies on other ecosystems should be considered to evaluate the universal usefulness of the rpoB marker. Our data highlight two crucial elements that should be taken into account to ensure more reliable and accurate descriptions of microbial diversity in high-throughput amplicon sequencing analyses: i) the need to include mock communities as controls; ii) the advantages of using a multigenic approach including at least one housekeeping gene (rpoB is a good candidate) and one variable region of the 16S rRNA gene.
Achieving reproducibility and accuracy in cancer mutation detection with whole-genome and whole-exome sequencing
Authors:   The Somatic Mutation Working Group of the SEQC-II Consortium
Published: May 2019

Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from errors introduced at each step of next generation sequencing (NGS). For NGS to successfully improve patient lives, discriminating between true mutations and artifacts is crucial.

We systematically interrogated somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy. Different types of samples with varying input amount and tumor purity were processed using multiple library construction protocols. Whole-genome and whole-exome sequencing were carried out at six sequencing centers followed by processing with nine bioinformatics pipelines to evaluate their reproducibility. We identified artifacts due to sample and library processing and evaluated the capabilities and limitations of bioinformatics tools for artifact detection and removal.

By examining the interaction and effect of various wet lab and computational parameters concomitantly, here we recommend actionable best practices for mutation detection in clinical applications using NGS technologies.
Extensive and diverse patterns of cell death sculpt neural networks in insects
Authors: Pop Sinziana , Chen Chin-Lin , Sproston Connor J , Kondo Shu , Ramdya Pavan , Williams Darren W
Published: May 2019

Changes to the structure and function of neural networks are thought to underlie the evolutionary adaptation of animal behaviours. Among the many developmental phenomena that generate change programmed cell death appears to play a key role. We show that cell death occurs continuously throughout insect neurogenesis and happens soon after neurons are born. Focusing on two dipterans which have lost flight during evolution we reveal that reductions in populations of flight interneurons are likely caused by increased cell death during development.

Mimicking an evolutionary role for increasing cell numbers, we artificially block programmed cell death in the medial neuroblast lineage inDrosophila melanogaster, which results in the production of ‘undead’ neurons with complex arborisations and distinct neurotransmitter identities. Activation of these ‘undead’ neurons and recordings of neural activity in behaving animals demonstrate that they are functional. Our findings suggest that the evolutionary modulation of death-based patterning could generate novel network configurations.
Competing Fluid Forces Control Endothelial Sprouting in a 3-D Microfluidic Vessel Bifurcation Model
Authors: Akbari Ehsan , Spychalski Griffin B. , Rangharajan Kaushik K. , Prakash Shaurya , Song Jonathan W.
Published: May 2019

Sprouting angiogenesis, the infiltration and extension of endothelial cells from pre-existing blood vessels, helps orchestrate vascular growth and remodeling. It is now agreed that fluid forces, such as laminar shear stress due to unidirectional flow in straight vessel segments, are important regulators of angiogenesis. However, regulation of angiogenesis by the different flow dynamics that arise due to vessel branching, such as impinging flow stagnation at the base of a bifurcating vessel, are not well understood. Here we used a recently developed 3-D microfluidic model to investigate the role of the flow conditions that occur due to vessel bifurcations on endothelial sprouting. We observed that bifurcating fluid flow located at the vessel bifurcation point suppresses the formation of angiogenic sprouts. Similarly, laminar shear stress at a magnitude of ∼3 dyn/cm2 applied in the branched vessels downstream of the bifurcation point, inhibited the formation of angiogenic sprouts. In contrast, co-application of ∼1 µm/s average transvascular flow across the endothelial monolayer with bifurcating fluid flow and laminar shear stress induced the formation of angiogenic sprouts. These results suggest that transvascular flow imparts a competing effect against bifurcating fluid flow and laminar shear stress in regulating endothelial sprouting. To our knowledge, these findings are the first report on the stabilizing role of bifurcating fluid flow on endothelial sprouting. These results also demonstrate the importance of local flow dynamics due to branched vessel geometry in determining the location of sprouting angiogenesis.
Identifying Brain Region Connectivity using Steiner Minimal Tree Approximation and a Genetic Algorithm
Authors: Islam Syed , Sarwar Dewan M.
Published: May 2019

Background

Computation and visualization of connectivity among the brain regions is vital for tasks such as disease identification and drug discovery. An effective visualization can aid clinicians and biologists to perform these tasks addressing a genuine research and industrial need. In this paper, we present SMT-Neurophysiology, a web-based tool in a form of an approximation to the Steiner Minimal Tree (SMT) algorithm to search neurophysiology partonomy and connectivity graph in order to find biomedically-meaningful paths that could explain, to neurologists and neuroscientists, the mechanistic relationship, for example, among specific neurophysiological examinations. We also present SMT-Genetic, a web-based tool in a form of a Genetic Algorithm (GA) to find better paths than SMT-Neurophysiology.

Results

We introduce an approximation to the SMT algorithm to identify the most parsimonious connectivity among the brain regions of interest. We have implemented our algorithm as a highly interactive web application called SMT-Neurophysiology that enables such computation and visualization. It operates on brain region connectivity dataset curated from the Neuroscience Information Framework (NIF) for four species – human, monkey, rat and bird. We present two case studies on finding the most biomedically-meaningful solutions that identifies connections among a set of brain regions over a specific route. The case studies demonstrate that SMT-Neurophysiology is able to find connection among brain regions of interest. Furthermore, SMT-Neurophysiology is modular and generic in nature allowing the underlying connectivity graph to model any data on which the tool can operate. In order to find better connections among a set of brain regions than SMT-Neurophysiology, we have implemented a web-based tool in a form of a GA called SMT-Genetic. We present further three case studies where SMT-Genetic finds better connections among a set of brain regions than SMT-Neurophysiology. SMT-Genetic gives better connections because SMT-Genetic finds global optimum whereas SMT-Neurophysiology finds local optimum although execution time of SMT-Genetic is higher than SMT-Neurophysiology.

Conclusion

Our analysis would provide key insights to clinical investigators about potential mechanisms underlying a particular neurological disease. The web-based tools and the underlying data are useful to clinicians and scientists to understand neurological disease mechanisms; discover pharmacological or surgical targets; and design diagnostic or therapeutic clinical trials. The source codes and links to the live tools are available at https://github.com/dewancse/connected-brain-regions and https://github.com/dewancse/SMT-Genetic.
All of gene expression (AOE): an integrated index for public gene expression databases
Authors: Bono Hidemasa
Published: May 2019

Gene expression data have been archived as microarray and RNA-seq datasets in two public databases, Gene Expression Omnibus (GEO) and ArrayExpress (AE). In 2018, the DNA DataBank of Japan started a similar repository called the Genomic Expression Archive (GEA). These databases are useful resources for the functional interpretation of genes, but have been separately maintained and may lack RNA-seq data, while the original sequence data are available in the Sequence Read Archive (SRA).

We constructed an index for those gene expression data repositories, called All Of gene Expression (AOE), to integrate publicly available gene expression data. The web interface of AOE can graphically query data in addition to the application programming interface. By collecting gene expression data from RNA-seq in the SRA, AOE also includes data not included in GEO and AE.

AOE is accessible as a search tool from the GEA website and is freely available at https://aoe.dbcls.jp/.
The Australian Genetics of Depression Study: Study Description and Sample Characteristics
Authors: Byrne Enda M , Kirk Katherine M , Medland Sarah E , McGrath John J , Parker Richard , Cross Simone , Sullivan Lenore , Statham Dixie J , Levinson Douglas F , Licinio Julio , Wray Naomi R , Hickie Ian B , Martin Nicholas G
Published: May 2019

Objectives

Depression is the most common psychiatric disorder and the largest contributor to global disability. The Australian Genetics of Depression study was established to recruit a large cohort of individuals who have been diagnosed with depression, and to investigate genetic and environmental risk factors for depression and response to commonly prescribed antidepressants. This paper describes the recruitment and characteristics of the sample.

Methods

Participants completed an online questionnaire that consisted of a compulsory module that assessed self-reported psychiatric history, clinical depression using the Composite Interview Diagnostic Interview Short Form, and experiences of using commonly prescribed antidepressants. Further voluntary modules assessed a wide range of traits of relevance to psychopathology. Participants who reported they were willing to provide a DNA sample were sent a saliva kit in the mail.

Results

A total of 20,689 participants, 75% of whom were female, enrolled in the study. The average age of participants was 43 years ± 15 years. 15,807 participants (76% of the participant group) returned saliva kits. The overwhelming majority of participants reported being given a diagnosis of depression by a medical practitioner and 88% met the criteria for a depressive episode. Rates of comorbidity with other psychiatric disorders were high. Two-thirds of the sample reported having taken more than one type of antidepressant during treatment for their depression.

Conclusions

This study was effective in recruiting a large community sample of people with a history of clinical depression, highlighting the willingness of Australians to engage with medical research. A combination of recruitment through health records and media as well as use of an online questionnaire made it feasible to recruit the large sample needed for investigating the genetics of common diseases. It will be a valuable resource for investigating risk factors for depression, treatment response to antidepressants and susceptibility to side effects.
Photoactivation of silicon rhodamines via a light-induced protonation
Authors: Frei Michelle S. , Hoess Philipp , Lampe Marko , Nijmeijer Bianca , Kueblbeck Moritz , Ellenberg Jan , Ries Jonas , Pitsch Stefan , Reymond Luc , Johnsson Kai
Published: May 2019

We present a new type of photoactivatable fluorophore that forms a bright silicon rhodamine derivative through a light-dependent isomerization followed by protonation. In contrast to other photoactivatable fluorophores, no caging groups are required, nor are there any undesired side-products released. Using this photoactivatable fluorophore, we created probes for HaloTag and actin for live-cell single-molecule localization microscopy and single-particle tracking experiments. The unusual mechanism of photoactivation and the fluorophore’s outstanding spectroscopic properties make it a powerful tool for live-cell super-resolution microscopy.
The magnitude of neonatal mortality and its predictors in Ethiopia: a systematic review and meta-analysis
Authors: Asmare Yared , Shibabaw Wondimeneh , Yirga Tadesse , Dargie Abate , Hab-tewold Tesfa Dejenie
Published: May 2019

Abstracts

Background

Although neonatal death is a global burden, it is the highest in Sub Saharan Africa countries such as Ethiopia. This study was aimed to provide pooled national prevalence and predictors of neonatal mortality in Ethiopia.

Objective

To assess the pooled prevalence and predictors of neonatal mortality in Ethiopia.

Search Strategy

global databases were systematically explored. Systematically searched using the following databases: Boolean operator, Cochrane library, PubMed, EMBASE, HINARI, and Google Scholar. Selection, screening, reviewing and data extraction was done by two reviewers independently using Microsoft excel spread sheet. The modified Newcastle–Ottawa Scale (NOS) and the Joanna Briggs Institute Prevalence Critical Appraisal tools were used to assess the quality of evidence

Selection criteria

All studies conducted in Ethiopia and reporting the prevalence and predictors of neonatal mortality were included

Data Collection and Analysis

Data were extracted using a Microsoft Excel spreadsheet software and imported into STATA Version 14 s for further analysis. The pooled effect size with 95% confidence interval of neonatal mortality rate was determined using a weighted inverse variance random-effects model. Publication bias was checked using funnel plots, Egger’s and bagger’s regression test. Heterogeneity also checked by Higgins’s method. A random effects meta-analysis model was computed to estimate the pooled effect size (i.e. prevalence and odds ratio). Moreover, subgroup analysis based on region, sample size and study design were done.

Results

After reviewing 88 studies, 12 studies fulfilled the inclusion criteria and were included in the meta-analysis. The pooled national prevalence of neonatal mortality in Ethiopia was 16.3% (95% CI: 11.9, 20.7, I2 =88.6%). The subgroup analysis indicated that the highest prevalence was observed in Amhara region with a prevalence of 20.3% (95% CI: 9.6, 31.1, I2 =98.8) followed by Oromia, 18.8% (95%CI: 11.9,49.4, I2=99.5). Gestational age AOR,1.14 (95% CI: 0.94, 1.3), neonatal sepsis (OR:1.2(95% CI: 0.8, 1.5), respiratory distros (OR: 1.2(95% CI: 0.8, 1.5) and place of residency (OR:1.93 (95% CI:1.1,2.7) were the most important predictor.

Conclusions

neonatal mortality in Ethiopia was significantly decreased than the national report. There was evidence that neonatal sepsis, gestational age, respiratory distress were the significant predictors. We strongly recommended that health care workers should give a priority for the identified predictors.
Correlation of IL-17 level in gingival crevicular fluid of orthodontically induced inflammatory root resorption
Authors: Zhou Hua , Liang Xiao , Liu Aipeng , Nong Dongmei , Qin Yaqing , Chen Lianxiang , Kang Na
Published: May 2019

Objective

To investigate IL-17 expression in orthodontic tooth movement and orthodontic nickel-titanium spring-induced inflammatory root resorption.

Methods

Orthodontic nickel-titanium springs were ligated between the bilateral maxillary first molar and the incisors of the rats to establish a rat model of orthodontic tooth movement (OTM), each rat was subjected to two cycles of near-GCF and peripheral blood serum collection before and after force application, and IL-17 levels in GCF and serum were measured quantitatively by ELISA. Morphological changes in periodontal tissue and root of the experimental dentine were evaluated by hematoxylin and eosin staining. Tartrate-resistant acid phosphatase staining and immunohistochemistry were used to determine the osteoclast number and expression changes in IL-17, receptor activator of nuclear factor kappa-B ligand (RANKL), and osteoprotegerin (OPG) in the periodontal tissues, respectively, on the pressure side of the experimental tooth.

Results

IL-17 was detected in GCF and serum. The pressure area exhibited alveolar bone resorption only at a force of 20g. Additionally, a force of 60g led to root resorption. IL-17, RANKL/OPG and osteoclast number showed similar trend that all expressed increasing high level at early stage, then significantly decreased from days 5 to 14, and revealed 60g group the highest expression level while 0g group the lowest.

The change in the IL-17 level in the GCF was strongly correlated with IL-17 and RANKL/OPG expression levels and osteoclast numbers in the periodontal ligament.

Conclusions

The results indicated that measuring IL-17 level in GCF can predict the risk of alveolar bone and root resorption induced by orthodontic treatment.
Integration of eQTL and Parkinson’s disease GWAS data implicates 11 disease genes
Authors: Kia Demis A. , Zhang David , Guelfi Sebastian , Manzoni Claudia , Hubbard Leon ,   United Kingdom Brain Expression Consortium (UKBEC),   International Parkinson’s Disease Genomics Consortium (IPDGC), Reynolds Regina H. , Botía Juan , Ryten Mina , Ferrari Raffaele , Lewis Patrick A. , Williams Nigel , Trabzuni Daniah , Hardy John , Wood Nicholas W.
Published: May 2019

Substantial genome-wide association study (GWAS) work in Parkinson’s disease (PD) has led to an increasing number of loci shown reliably and robustly to be associated with the increased risk of the disease. Prioritising causative genes and pathways from these studies has proven problematic. Here, we present a comprehensive analysis of PD GWAS data with expression and methylation quantitative trait loci (eQTL/mQTL) using Colocalisation analysis (Coloc) and transcriptome-wide association analysis (TWAS) to uncover putative gene expression and splicing mechanisms driving PD GWAS signals. Candidate genes were further characterised by determining cell-type specificity, weighted gene co-expression (WGNCA) and protein-protein interaction (PPI) networks.

Gene-level analysis of expression revealed 5 genes (WDR6, CD38, GPNMB, RAB29, TMEM163) that replicated using both Coloc and TWAS analyses in both GTEx and Braineac expression datasets. A further 6 genes (ZRANB3, PCGF3, NEK1, NUPL2, GALC, CTSB) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell-types compared to neurons. The WGNCA analysis showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes related with protein ubiquitination (protein ubiquitination (p=7.47e-10) and ubiquitin-dependent protein catabolic process (p = 2.57e-17) in nucleus accumbens, caudate and putamen, while TMEM163 and ZRANB3 were both important in modules indicating regulation of signalling (p=1.33e-65] and cell communication (p=7.55e-35) in the frontal cortex and caudate respectively. PPI analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known Mendelian PD and parkinsonism proteins than would be expected by chance. The proteins core proteins this network were enriched for regulation of the ERBB receptor tyrosine protein kinase signalling pathways.

Together, these results point to a number of candidate genes and pathways that are driving the associations observed in PD GWAS studies.
Bdellovibrio and Like Organisms are Predictors of Microbiome Diversity in distinct Host Groups
Authors: Johnke Julia , Fraune Sebastian , Bosch Thomas , Hentschel Ute , Schulenburg Hinrich
Published: May 2019

Biodiversity is generally believed to be a main determinant of ecosystem functioning. This principle also applies to the microbiome and could consequently contribute to host health. According to ecological theory, communities are shaped by top predators whose direct and indirect interactions with community members cause stability and diversity. Bdellovibrio and like organisms (BALOs) are a neglected group of predatory bacteria that feed on Gram-negative bacteria and can thereby influence microbiome composition. We asked whether BALOs can predict biodiversity levels in microbiomes from distinct host groups and environments. We demonstrate that genetic signatures of BALOs are commonly found within the 16S rRNA reads from diverse host taxa. In many cases, their presence, abundance, and especially richness are positively correlated with overall microbiome diversity. Our findings suggest that BALOs can act as drivers of microbial alpha-diversity and should therefore be considered as candidates for the restoration of microbiomes and the prevention of dysbiosis.
A cellular and spatial map of the choroid plexus across brain ventricles and ages
Authors: Dani Neil , Herbst Rebecca H. , Habib Naomi , Head Joshua , Dionne Danielle , Nguyen Lan , McCabe Cristin , Cui Jin , Shipley Frederick B. , Jang Ahram , Rodman Christopher , Riesenfeld Samantha J. , Zhang Feng , Rozenblatt-Rosen Orit , Regev Aviv , Lehtinen Maria K.
Published: May 2019

The choroid plexus (ChP), located in each brain ventricle, produces cerebrospinal fluid (CSF) and forms the blood-CSF barrier, but is under-characterized. Here, we combine single cell RNA-Seq and spatial mapping of RNA and proteins to construct an atlas of each ChP in the developing and adult mouse brain. Each ChP comprises of epithelial, endothelial, mesenchymal, immune, neuronal, and glial cells, with distinct subtypes, differentiation states and anatomical locations. Epithelial, fibroblast, and macrophage populations had ventricle-specific, regionalized gene expression programs across the developing brain. Key cell types are retained in adult, with loss of developmental signatures and maturation of ventricle-specific regionalization in the epithelial cells. Expression of cognate ligand-receptor pairs across cell subtypes suggests substantial cell-cell interactions within the ChP. Our atlas sheds new light on the development and function of the ChP brain barrier system, and will facilitate future studies on its role in brain development, homeostasis and disease.
Impaired tumor death receptor signaling drives resistance to CAR T cell therapy
Authors: Singh Nathan , Shestova Olga , Ravikumar Pranali , Hayer Katharina E. , Hong Seok Jae , Orlando Elena J. , Mueller Karen Thudium , Good Charly R. , Berger Shelley L. , Shalem Ophir , Weitzman Matthew D. , Grupp Stephan A. , June Carl H. , Gill Saar , Ruella Marco
Published: May 2019

Cellular immunotherapy using T cells engineered to express chimeric antigen receptors targeting CD19 (CART19) leads to long-term remission in patients with B-cell malignancies1–5. Unfortunately, a significant fraction of patients demonstrate primary resistance to CART19 or experience relapse after achieving remission. Beyond loss of target antigen, the molecular pathways governing CART19 failure are unknown. Here we demonstrate that death receptors, cell surface signaling molecules that induce target cell apoptosis, are key mediators of leukemic resistance and CART19 failure. Using a functional CRISPR/Cas9-based genome-wide knockout screen6 in B-cell acute lymphoblastic leukemia (ALL), we identified the death receptor signaling pathway as a central regulator of sensitivity to CART19-induced cell death. In the absence of the pro-apoptotic death receptor signaling molecules BID or FADD, ALL cells were resistant to CART19 cytotoxicity, resulting in rapid disease progression in mice. We found that this initial resistance to cytotoxicity led to persistence of tumor cells, which drove the development of T cell dysfunction that further compromised anti-tumor immunity and permitted tumor outgrowth. We validated these findings using clinical samples collected from patients with ALL treated with CD19-targeted CAR T cells and found that expression of pro-apoptotic death receptor pathway genes in pre-treatment tumor samples correlated with CAR T cell expansion and persistence, as well as patient response and overall survival. Our findings indicate that tumor-intrinsic death receptor signaling directly contributes to CAR T cell failure.
Fat SIRAH: Coarse-grained phospholipids to explore membrane-protein dynamics
Authors: Barrera Exequiel E. , Machado Matías R. , Pantano Sergio
Published: May 2019

Tne capability to handle highly heterogeneous molecular assemblies in a consistent manner is among the greatest challenges faced when deriving simulation parameters. This is particularly the case for coarse-grained simulations in which chemical functional groups are lumped into effective interaction centers for which transferability between different chemical environments is not guaranteed. Here we introduce the parameterization of a set of CG phospholipids compatible with the latest version of the SIRAH force field for proteins. The newly introduced lipid species include different acylic chain lengths, partial unsaturation, as well as polar and acidic head groups that show a very good reproduction of structural membrane determinants, as areas per lipid, thickness, order parameter, etc., and their dependence with temperature. Simulation of membrane proteins showed unprecedented accuracy in the unbiased description of the thickness-dependent membrane-protein orientation in systems where this information is experimentally available (namely, the SarcoEndoplasmic Reticulum Calcium –SERCA-pump and its regulator Phospholamban). The interactions that lead to this faithful reproduction can be traced down to single amino acid-lipid interaction level and show full agreement with biochemical data present in the literature. Finally, the present parameterization is implemented in the GROMACS and AMBER simulation packages facilitating its use to a wide portion of the Biocomputing community.
Circadian regulation of light-evoked attraction/avoidance in day- vs. night-biting mosquitoes
Authors: Baik Lisa Soyeon , Nave Ceazar , Au David D. , Guda Tom , Chevez Joshua A. , Ray Anandasankar , Holmes Todd C.
Published: May 2019

Mosquitoes pose widespread threats to humans and other animals as disease vectors. Day- vs. night-biting mosquitoes occupy distinct time-of-day niches and exhibit very different innate temporal attraction/avoidance behavioral responses to light, yet little is known about their circuit or molecular mechanisms. Day-biting diurnal mosquitoesAedes aegyptiare attracted to light during the day regardless of spectra. In contrast, night-biting nocturnal mosquitoesAnopheles coluzziiavoid short, but not long wavelength light. Attraction/avoidance behavioral responses to light in both species change with time-of-day and show distinct sex and circuit differences. The basis of diurnal versus nocturnal behavior is driven by clock timing, which cycle anti-phase between day-biting versus night-biting mosquito species. Disruption of the circadian molecular clock severely interferes with light-evoked attraction/avoidance behavior in mosquitoes. In summary, attraction/avoidance mosquito behaviors are circadian and light regulated, which may be applied towards species specific control of harmful mosquitoes.
Identification of the pathway of Rhodoquinone biosynthesis inC.elegans
Authors: Del Borrello Samantha , Lautens Margot , Dolan Kathleen , Tan June H. , Spensley Mark A. , Caudy Amy A. , Fraser Andrew G.
Published: May 2019

Parasitic helminths infect over a billion humans. To survive in the low oxygen environment of their hosts, these parasites use unusual anaerobic metabolism. This requires Rhodoquinone (RQ), an electron carrier that is made by very few animal species — crucially it is not present in any parasitic hosts. RQ synthesis is thus an ideal target for anthelmintics but little is known about how RQ is made and no drugs are known to block RQ synthesis.C.elegansmakes RQ and can use RQ-dependent metabolic pathways — here, we useC.elegansgenetics to identify the pathway for RQ synthesis and show thatC.elegansrequires RQ for survival in hypoxic conditions. Finally, we establish a robust assay for drugs that block RQ-dependent metabolism. This study identifies for the first time how RQ is made in any animal and establishes a novel assay that can drive the development of a new class of anthelmintic drugs.
Transformation and Integration of Microenvironment Microarray Data Improves Discovery of Latent Effects
Authors: Hunt Gregory J. , Dane Mark A. , Korkola James E. , Heiser Laura M. , Gagnon-Bartsch Johann A.
Published: May 2019

The immediate physical and bio-chemical surroundings of a cell, the cellular microenvironment, is an important component of many fundamental cell and tissue level processes and is implicated in many diseases and dysfunctions. Thus understanding the interaction of cells with their microenvironment can further both basic research and aid the discovery of therapeutic agents. To study perturbations of cellular microenvironments a novel image-based cell-profiling technology called the microenvironment microarray (MEMA) has been recently employed. In this paper we explore the effect of preprocessing transformations for MEMA data on the discovery of biological and technical latent effects. We find that Gaussianizing the data and carefully removing outliers can enhance discovery of important biological effects. In particular, these transformations help reveal a relationship between cell morphological features and the extra-cellular-matrix protein THBS1 in MCF10A breast tissue. More broadly, MEMAs are part of a recent and wide-spread adoption of image-based cell-profiling technologies in the quantification of phenotypic differences among cell populations (Caicedo et al., 2017). Thus we anticipate that the advantages of the proposed preprocessing transformations will likely also be realized in the analysis of data from other highly-multiplexed technologies like Cyclic Immunofluorescence. All code and supplementary analysis for this paper is available at gjhunt.github.io/rr.
Differential effects of Doxorubicin and Actinomycin D on the stability of RNA binding proteins, RBM10 and RBM5: Actinomycin D promotes the nuclear speckles targeting of RBM10 and RBM5 through the novel structural elements
Authors: Nishio Koji , Qiao Shanlou , Chang Kung Sang
Published: May 2019

Background

RNA binding motif (RBM) proteins, RBM10v1, RBM10v2 and RBM5 share a high degree of the conserved domains. So far, the drug-sensitivities of the RBMs in tumor cells have not been fully examined.

Objective

The expression profiles of RBM10 and RBM5 in several virus-transformed tumor cells, and the effect of the most established antitumor agents, actinomycin D and doxorubicin, were investigated.

Methods and Results

Doxorubicin and actinomycin D differentially reduced RBM10 and RBM5 protein, respectively in both of HeLa and COS-7 cells. RBM10 protein was highly sensitive to doxorubicin in HeLa, COS-7 and A549 cells. In silico analysis revealed the several sumoylation sites of RBM10 and its sumoylated form could be targeted for the activated ubiquitin proteasome system. Actinomycin D affected the nuclear speckles localization of RBM10 and RBM5 in COS-7 and A549 lung carcinoma cells. Addition of actinomycin D in the culture medium and following culture for 3〜4 hours promoted the prominent nuclear speckles of RBM10v2-GFP and RBM5. Hence, we explored the subnuclear localization of the full length RBM10v2 (852aa) and the amino terminally truncated forms and the responsible structural elements. The amino terminally truncated RBM10v2 [#486-852, #642-852], RBM10v2 [#648-852], RBM10v2 [#681-759, #681-852], and RBM10v2 [#660-852] retained the targeting elements for the nuclear speckles, nucleoplasm, nucleoli and whole nuclei, respectively.

Conclusion

RBM10 is highly sensitive to doxorubicin. Actinomycin D affects the structural elements of RBM10 and promotes the nuclear speckles targeting. The C-terminal regions: RBM10v2 [#642-647], [#642-659], and [#660-680] play critical roles in the targeting to the subnuclear compartments. SIM and sumoylation sits of RBM10 and PML4 are important for molecular interaction of RBM10 and PML.
No evidence for accelerated brain aging in patients with chronic non-cancer pain
Authors: Sörös Peter , Bantel Carsten
Published: May 2019

Chronic pain is often associated with changes in brain structure and function, and also cognitive deficits. It has been noted that these chronic pain-related alterations may resemble changes found in healthy aging, and thus may represent accelerated or pre-mature aging of the brain. Here we test the hypothesis that patients with chronic non-cancer pain demonstrate accelerated brain aging compared to healthy control subjects. The predicted brain age of 59 patients with chronic pain (mean chronological age ± standard deviation: 53.0 ± 9.0 years; 43 women) and 60 pain-free healthy controls (52.6 ± 9.0 years; 44 women) was determined using the softwarebrainageR. This software segments the individual T1-weighted structural MR images into gray and white matter and compares gray and white matter images to a large (n = 2001) training set of structural images, using machine learning. Finally, brain age delta, which is the predicted brain age minus chronological age, was calculated and compared across groups. This study provided no evidence for the hypothesis that chronic pain is associated with accelerated brain aging (Welch’s t-test, p = 0.74, Cohen’s d = 0.061). A Bayesian independent samples t-test indicated moderate evidence in favor of the null hypothesis (BF01 = 4.875, i.e. group means were equal). Our results provide indirect support for recent models of pain related-changes of brain structure, brain function, and cognitive functions. These models postulate network-specific maladaptive plasticity, rather than wide-spread or global neural degeneration, leading to synaptic, dendritic, and neuronal remodeling.