bluuebunny/crossref_metadata_2025 huggingface dataset:
Long‐term outcomes of endoscopic submucosal dissection versus surgery in early gastric cancer: a systematic review and meta-analysis
Authors: Abdelfatah Mohamed M. , Barakat Mohamed , Ahmad Dina , Ibrahim Mariam , Ahmed Yahia , Kurdi Yahia , Grimm Ian S. , Othman Mohamed O.
Published: January 2019

Endoscopic submucosal dissection (ESD) and gastrectomy with lymph node dissection are considered acceptable treatment modalities for early gastric cancer (EGC). In the last decade, ESD has become more favorable than surgery as it offers faster recovery, lower costs, and a superior quality of life when compared to gastrectomy. The aim of this study is to compare the long-term outcome of ESD versus surgery in EGC. We performed a systematic and comprehensive search of major reference databases (Medline, Embase, CINHAL) for all studies that compared the outcome of EGC for patients underwent ESD or surgery in the same cohort. A systematic review was conducted through November 2017, using pooled analysis to calculate 5-year overall survival (OS) rate, disease-specific survival (DSS) rate, disease-free survival (DFS) rate, and recurrence-free survival (RFS) rate of ESD versus gastrectomy. Five-year OS and DSS were similar between ESD and gastrectomy groups 96 versus 96% and 99.4 versus 99.2%, respectively. Likewise, DFS was similar in both groups 95.9 versus 98.5% odds ratio 1.86 (0.57–6.0) P=0.3. However, ESD had a lower RFS compared to surgery 92.4 versus 98.3% odds ratio 0.17 (0.1–4.9) P=0.001. Overall, there was a higher recurrence rate in patients who underwent ESD compared to surgery [40/2943 (1.4%) vs. 12/3116 (0.4) risk ratio (RR) 2.5 (1.3–4.8) P=0.005]. Moreover, synchronous and metachronous cancers were more prevalent in the ESD group compared to the surgery group [1.5 vs. 0.1% RR 5.7 (1.5–21.9) P=0.01] [16/1082 (1.5%) vs. 1/1485 (0.1%) RR 10.1 (5.9–17.1) P=0.0001]. Five-year OS, DSS and DFS were similar between ESD and surgery groups. However, recurrent, synchronous and metachronous cancers were more prevalent in patients treated by ESD compared to patients treated by surgery, resulting in a lower RFS. Adequate surveillance with upper endoscopy is crucial after ESD to detect early recurrence and metachronous lesions.
Mansoura simple scoring system for prediction of spontaneous bacterial peritonitis: lesson learnt
Authors: Abdel-Razik Ahmed , Mousa Nasser , Abdel-Aziz Mahmoud , Elsherbiny Walid , Zakaria Sahar , Shabana Walaa , Abed Sally , Elhelaly Rania , Elzehery Rasha , Eldars Waleed , El-bendary Mahmoud
Published: January 2019

Background and objective

Spontaneous bacterial peritonitis (SBP) is a common bacterial infection with life-threatening sequelae in cirrhotic ascites. The purpose of this retrospective cohort study was to recognize the predictors of SBP to build up a noninvasive system to exclude or establish an episode of SBP.

Patients and methods

Of 1194 consecutive patients with cirrhotic ascites, only 966 patients were enrolled in this study. SBP was diagnosed once polymorphonuclear count was at least 250 cells/mm3 and/or there was a positive ascitic fluid culture result. Biochemical and clinical parameters were evaluated as predictors of SBP. A scoring system was established in the training group of 682 and validated in a second group of 284 participants.

Results

The incidence of SBP was 12.3 and 12% in the training and validation groups, respectively. Age of at least 55 years, mean platelet volume (MPV) of at least 8.5 fl, neutrophil-to-lymphocyte ratio (NLR) of at least 2.5, and C-reactive protein (CRP) of at least 40 mg/l were identified as independent predictors of SBP. A scoring system including these four variables (age, MPV, and NLR with 1 point each, whereas CRP with 2 points) achieves a specificity of 98.2% with a positive predictive value for the diagnosis of SBP of 88.1% (score≥4). At a threshold of 1 point, the negative predictive value is 97.5% with a sensitivity of 92.9%. SBP is not associated with a high Model for End-stage Liver Disease score (P=0.135).

Conclusion

The combination of age, MPV, NLR, and CRP in a simple scoring system, Mansoura simple scoring system, supports quick and accurate exclusion or diagnosis of SBP.
Methylobacterium infection of an arthritic knee
Authors: Beck Eric T. , Bateman Allen C. , Maccoux Darin
Published: January 2019

Introduction. Osteoarthritis (OA) is a common cause of knee pain in older adults. OA is primarily caused by deterioration of cartilage in the knee, which decreases the ability of synovial fluid to absorb shock and increases the opportunity for bones of the joint to rub together. Hylan G-F 20 (Synvisc-One) is a compound that can be injected directly into the knee to help combat the pain associated with OA by lubricating and cushioning the joint.

Case presentation. A 92-year-old male reported to his primary care provider with complaints of pain due to OA. An ultrasound-guided injection of Hylan G-F 20 was administered without complication; however, the patient presented to an emergency department approximately 10 h after the injection complaining of stabbing pain and swelling in the same knee. Specimens submitted for culture 12 h post-injection yielded a

Methylobacterium

spp. that was identified following biochemical testing, MALDI-TOF (matrix-assisted laser desorption/ionization-time of flight) MS analysis and bacterial sequencing. Interestingly, symptoms began to subside following aspiration of synovial fluid, and new cultures of synovial fluid collected 24 h post-Hylan G-F 20 injection were negative for the presence of

Methylobacterium

. The patient’s knee returned to baseline with diminished pain due to OA approximately 1 week after the initial injection without antibiotic treatment.

Conclusion. We report short-term complications following treatment of OA with a

Methylobacterium

-contaminated lot of Hylan G-F 20.
Virome heterogeneity and connectivity in waterfowl and shorebird communities
Authors: Wille Michelle , Shi Mang , Klaassen Marcel , Hurt Aeron C. , Holmes Edward C.
Published: January 2019

Models of host-microbe dynamics typically assume a single-host population infected by a single pathogen. In reality, many hosts form multi-species aggregations and may be infected with an assemblage of pathogens. We used a meta-transcriptomic approach to characterize the viromes of nine avian species in the Anseriformes (ducks) and Charadriiformes (shorebirds). This revealed the presence of 27 viral species, of which 24 were novel, including double-stranded RNA viruses (Picobirnaviridae and Reoviridae), single-stranded RNA viruses (Astroviridae, Caliciviridae, Picornaviridae), a retro-transcribing DNA virus (Hepadnaviridae), and a single-stranded DNA virus (Parvoviridae). These viruses comprise multi-host generalist viruses and those that are host-specific, indicative of both virome connectivity and heterogeneity. Virome connectivity was apparent in two well described multi-host virus species (avian coronavirus and influenza A virus) and a novel Rotavirus species that were shared among some Anseriform species, while heterogeneity was reflected in the absence of viruses shared between Anseriformes and Charadriiformes. Notably, within avian host families there was no significant relationship between either host taxonomy or foraging ecology and virome composition, although Anseriform species positive for influenza A virus harboured more additional viruses than those negative for influenza virus. Overall, we demonstrate complex virome structures across host species that co-exist in multi-species aggregations.
Evaluating potential drug targets through human loss-of-function genetic variation
Authors: Minikel Eric Vallabh , Karczewski Konrad J , Martin Hilary C , Cummings Beryl B , Whiffin Nicola , Alföldi Jessica , Trembath Richard C , van Heel David A , Daly Mark J ,   Genome Aggregation Database Production Team, Schreiber Stuart L , MacArthur Daniel G
Published: January 2019

Human genetics has informed the clinical development of new drugs, and is beginning to influence the selection of new drug targets. Large-scale DNA sequencing studies have created a catalogue of naturally occurring genetic variants predicted to cause loss of function in human genes, which in principle should provide powerfulin vivomodels of human genetic “knockouts” to complement model organism knockout studies and inform drug development. Here, we consider the use of predicted loss-of-function (pLoF) variation catalogued in the Genome Aggregation Database (gnomAD) for the evaluation of genes as potential drug targets. Many drug targets, including the targets of highly successful inhibitors such as aspirin and statins, are under natural selection at least as extreme as known haploinsufficient genes, with pLoF variants almost completely depleted from the population. Thus, metrics of gene essentiality should not be used to eliminate genes from consideration as potential targets. The identification of individual humans harboring “knockouts” (biallelic gene inactivation), followed by individual recall and deep phenotyping, is highly valuable to study gene function. In most genes, pLoF alleles are sufficiently rare that ascertainment will be largely limited to heterozygous individuals in outbred populations. Sampling of diverse bottlenecked populations and consanguineous individuals will aid in identification of total “knockouts”. Careful filtering and curation of pLoF variants in a gene of interest is necessary in order to identify true LoF individuals for follow-up, and the positional distribution or frequency of true LoF variants may reveal important disease biology. Our analysis suggests that the value of pLoF variant data for drug discovery lies in deep curation informed by the nature of the drug and its indication, as well as the biology of the gene, followed by recall-by-genotype studies in targeted populations.
Long-distance dispersal shaped the diversity of tribe Dorstenieae (Moraceae)
Authors: Zhang Qian , Gardner Elliot , Zerega Nyree , Sauquet Hervé
Published: January 2019

Aim

The Neotropics have the highest terrestrial biodiversity on earth. Investigating the relationships between the floras of the Neotropics and other tropical areas is critical to understanding the origin and evolution of this mega-diverse region. Tribe Dorstenieae (Moraceae) has a pantropical distribution and almost equal number of species on both sides of the Atlantic. In this study, we investigate the relationship between the African and Neotropical floras using Dorstenieae (15 genera, 156 species, Moraceae) as a model clade.

Location

the Neotropics and Africa.

Methods

We used a targeted enrichment strategy with herbarium samples and a nuclear bait set to assemble a data set of 102 genes sampled from 83 (53%) species and fifteen genera (100%) of Dorstenieae, and five outgroup species. Phylogenetic relationships were reconstructed with maximum likelihood and coalescent approaches. This phylogeny was dated with a Bayesian relaxed clock model and four fossil calibrations. The biogeographic history of the group was then reconstructed with several dispersal-extinction-cladogenesis models (incl. DEC and DEC+J).

Results

The crown-group ages of Dorstenieae andDorsteniawere estimated in the Cretaceous (65.8-79.8 Ma) and the Paleocene (50.8-67.3 Ma), respectively. Tribe Dorstenieae as a whole appears to have originated in the joint area of continental Africa, Madagascar and Asia-Oceania area. The Neotropical species ofDorsteniadiversified in the Eocene (29.8-44.7 Ma) and formed a clade nested within the African lineages in the genus.Brosimums.l., with a crown-group age at the period of the Oligocene and Miocene (14.9-31.1 Ma), represents another Neotropical clade in Dorstenieae.

Main conclusions

Tribe Dorstenieae originated in the joint area of continental Africa, Madagascar and Asia-Oceania area in the Cretaceous and then dispersed into Neotropics twice. Neotropical diversification after long-distance dispersal across the Atlantic is the most plausible explanation for the extant distribution pattern of Dorstenieae.
3D super-resolution imaging using a generalized and scalable progressive refinement method on sparse recovery (PRIS)
Authors: Yi Xiyu , Piestun Rafael , Weiss Shimon
Published: January 2019

Within the family of super-resolution (SR) fluorescence microscopy, single-molecule localization microscopies (PALM[1], STORM[2] and their derivatives) afford among the highest spatial resolution (approximately 5 to 10 nm), but often with moderate temporal resolution. The high spatial resolution relies on the adequate accumulation of precise localizations of bright fluorophores, which requires the bright fluorophores to possess a relatively low spatial density. Several methods have demonstrated localization at higher densities in both two dimensions (2D)[3, 4] and three dimensions (3D)[5-7]. Additionally, with further advancements, such as functional super-resolution[8, 9] and point spread function (PSF) engineering with[8-11] or without[12] multi-channel observations, extra information (spectra, dipole orientation) can be encoded and recovered at the single molecule level. However, such advancements are not fully extended for high-density localizations in 3D. In this work, we adopt sparse recovery using simple matrix/vector operations, and propose a systematic progressive refinement method (dubbed as PRIS) for 3D high-density reconstruction. Our method allows for localization reconstruction using experimental PSFs that include the spatial aberrations and fingerprint patterns of the PSFs[13]. We generalized the method for PSF engineering, multi-channel and multi-species observations using different forms of matrix concatenations. Reconstructions with both double-helix and astigmatic PSFs, for both single and biplane settings are demonstrated, together with the recovery capability for a mixture of two different color species.
Investigating metabolic interactions in a microbial co-culture through integrated modelling and experiments
Authors: Ravikrishnan Aarthi , Blank Lars M , Srivastava Smita , Raman Karthik
Published: January 2019

Microbial co-cultures have been used in several biotechnological applications. Within these co-cultures, the micro-organisms tend to interact with each other and perform complex actions vis-à-vis a single organism. Investigating metabolic interactions in microbial co-cultures is crucial in designing microbial consortia tailored for specific applications. In this study, we present a pipeline integrating modelling and experimental approaches to understand metabolic interactions between organisms in a community. We define a new index named Metabolic Support Index (MSI), which quantifies the benefits derived by each organism in the presence of the other when grown as a co-culture. We computed MSI for several experimentally demonstrated co-culture systems and showed that MSI, as a metric, accurately identifies the organism that derives the maximum benefit. We also computed MSI for a commonly used yeast co-culture consisting of Saccharomyces cerevisiae and Pichia stipitis and observed that the latter derives higher benefit from the interaction. Further, we designed two-stage experiments to study mutual interactions and showed that P. stipitis indeed derives the maximum benefit from the interaction, as shown from our computational predictions. Also, using our previously developed computational tool MetQuest, we identified all the metabolic exchanges happening between these organisms by analysing the pathways spanning the two organisms. By analysing the HPLC profiles and studying the isotope labelling, we show that P. stipitis consumes the ethanol produced by S. cerevisiae when grown on glucose-rich medium under aerobic conditions, as also indicated by our in silico pathway analyses. Our approach represents an important step in understanding metabolic interactions in microbial communities through an integrating framework of modelling and experiments.
LSD impairs working memory, executive functions, and cognitive flexibility, but not risk-based decision making
Authors: Pokorny Thomas , Duerler Patricia , Seifritz Erich , Vollenweider Franz X. , Preller Katrin H.
Published: January 2019

Psychiatric and neurodegenerative illnesses are characterized by cognitive impairments, in particular deficits in working memory, decision making, and executive functions including cognitive flexibility. However, the neuropharmacology of these cognitive functions is poorly understood. The serotonin (5-HT) 2A receptor might be a promising candidate for the modulation of cognitive processes. However, pharmacological studies investigating the role of this receptor system in humans are rare. Recent evidence demonstrates that the effects of Lysergic acid diethylamide (LSD) are mediated via agonistic action at the 5-HT2A receptor. Yet, the effects of LSD on specific cognitive domains using standardized neuropsychological test have not been studied. Therefore, we examined the acute effects of LSD (100µg) alone and in combination with the 5-HT2A antagonist ketanserin (40mg) on cognition, employing a double-blind, randomized, placebo-controlled, within-subject design in 25 healthy participants. Executive functions, cognitive flexibility, spatial working memory, and risk-based decision-making were examined by the Intra/Extra-Dimensional shift task (IED), Spatial Working Memory task (SWM), and Cambridge Gambling Task (CGT) of the Cambridge Neuropsychological Test Automated Battery. Compared to placebo, LSD significantly impaired executive functions, cognitive flexibility, and working memory on the IED and SWM, but did not influence quality of decision-making and risk taking on the CGT. Pretreatment with the 5-HT2A antagonist ketanserin normalized all LSD-induced cognitive deficits. The present findings highlight the role of the 5-HT2A receptor system in executive functions and working memory and suggest that specific 5-HT2A antagonists may be relevant for improving cognitive dysfunctions in psychiatric disorders.
Impact and evolutionary determinants of Neanderthal introgression on transcriptional and post-transcriptional regulation
Authors: Silvert Martin , Quintana-Murci Lluis , Rotival Maxime
Published: January 2019

Archaic admixture is increasingly recognized as an important source of diversity in modern humans, with Neanderthal haplotypes covering 1-3% of the genome of present-day Eurasians. Recent work has shown that archaic introgression has contributed to human phenotypic diversity, mostly through the regulation of gene expression. Yet, the mechanisms through which archaic variants alter gene expression, and the forces driving the introgression landscape at regulatory regions remain elusive. Here, we explored the impact of archaic introgression on transcriptional and post-transcriptional regulation, focusing on promoters and enhancers across 127 different tissues as well as microRNA-mediated regulation. Although miRNAs themselves harbor few archaic variants, we found that some of these variants may have a strong impact on miRNA-mediated gene regulation. Enhancers were by far the regulatory elements most affected by archaic introgression, with one third of the tissues tested presenting significant enrichments. Specifically, we found strong enrichments of archaic variants in adipose-related tissues and primary T cells, even after accounting for various genomic and evolutionary confounders such as recombination rate and background selection. Interestingly, we identified signatures of adaptive introgression at enhancers of some key regulators of adipogenesis, raising the interesting hypothesis of a possible adaptation of early Eurasians to colder climates. Collectively, this study sheds new light onto the mechanisms through which archaic admixture have impacted gene regulation in Eurasians and, more generally, increases our understanding of the contribution of Neanderthals to the regulation of acquired immunity and adipose homeostasis in modern humans.
VarSight: Prioritizing Clinically Reported Variants with Binary Classification Algorithms
Authors: Holt James M. , Wilk Brandon , Birch Camille L. , Brown Donna M. , Gajapathy Manavalan , Moss Alexander C. , Sosonkina Nadiya , Wilk Melissa A. , Anderson Julie A. , Harris Jeremy M. , Kelly Jacob M. , Shaterferdosian Fariba , Uno-Antonison Angelina E. , Weborg Arthur ,   Undiagnosed Diseases Network, Worthey Elizabeth A.
Published: January 2019

Motivation

In genomic medicine for rare disease patients, the primary goal is to identify one or more variants that cause their disease. Typically, this is done through filtering and then prioritization of variants for manual curation. However, prioritization of variants in rare disease patients remains a challenging task due to the high degree of variability in phenotype presentation and molecular source of disease. Thus, methods that can identify and/or prioritize variants to be clinically reported in the presence of such variability are of critical importance.

Results

We tested the application of classification algorithms that ingest variant predictions along with phenotype information for predicting whether a variant will ultimately be clinically reported and returned to a patient. To test the classifiers, we performed a retrospective study on variants that were clinically reported to 237 patients in the Undiagnosed Diseases Network. We treated the classifiers as variant prioritization systems and compared them to another variant prioritization algorithm and two single-measure controls. We showed that these classifiers outperformed the other methods with the best classifier ranking 73% of all reported variants and 97% of reported pathogenic variants in the top 20.

Availability

The scripts used to generate results presented in this paper are available at https://github.com/HudsonAlpha/VarSight.

Contact

jholt@hudsonalpha.org
A Minimal Self-organisation model of the Golgi Apparatus
Authors: Vagne Quentin , Vrel Jean-Patrick , Sens Pierre
Published: January 2019

The design principles dictating the spatio-temporal organisation of eukaryotic cells, and in particular the mechanisms controlling the self-organisation and dynamics of membrane-bound organelles such as the Golgi apparatus, remain elusive. Although this organelle was discovered 120 years ago, such basic questions as whether vesicular transport through the Golgi occurs in an anterograde (from entry to exit) or retrograde fashion are still strongly debated. Here, we address these issues by studying a quantitative model of organelle dynamics that includes: de-novo compartment generation, inter-compartment vesicular exchange, and biochemical conversion of membrane components. We show that anterograde or retrograde vesicular transports are asymptotic behaviors of a much richer dynamical system. Indeed, the structure and composition of cellular compartments and the directionality of vesicular exchange are intimately linked. They are emergent properties that can be tuned by varying the relative rates of vesicle budding, fusion and biochemical conversion.
Experimental design for large scale omic studies
Authors: Ogut Funda , Newman Jeremy R.B. , Bacher Rhonda , Concannon Patrick J. , Verhoeven Koen J.F. , McIntyre Lauren M.
Published: January 2019

Molecular phenotyping has expanded from small sample sizes to larger complex studies and are now a common element in genetic studies. When large scale studies add a molecular phenotyping component, balancing omics batches for the factors of interest (e.g. treatment), regardless of the initial sample collection strategy always improves power. Where possible, confounding sources of experimental error that are not of interest (sample collection blocks and data collection plates) improves power as does planning batches for molecular phenotyping based on constraints during initial sample collection. Power for testing differences in molecular phenotypes is always higher when accounting for the entire experimental design during modeling. The inclusion of metadata that tracks sources variation is critical to our shared goals of enabling reproducible research.
Cost of preterm birth during initial hospitalization: A care provider’s perspective
Authors: Zainal Hadzri , Dahlui Maznah , Soelar Shahrul Aiman , Su Tin Tin
Published: January 2019

Preterm birth incidence has risen globally and remains a major cause of neonatal mortality despite improved survival. The demand and cost of initial hospitalization has also increased. This study assessed care provider cost in neonatal intensive care units of two hospitals in the state of Kedah, Malaysia. It utilized universal sampling and prospectively followed up preterm infants till discharge. Care provider cost was assessed using mixed method of top down approach and activity based costing. A total of 112 preterm infants were recruited from intensive care (93 infants) and minimal care (19 infants). Majority were from the moderate (23%) and late (36%) preterm groups followed by very preterm (32%) and extreme preterm (9%). Mean total cost per infant increased with level of care and degree of prematurity from MYR 2,751 (MYR 374 - MYR 10,103) for preterm minimal care, MYR 8,478 (MYR 817 - MYR 47,354) for late preterm intensive care to MYR 41,598 (MYR 25,351- MYR 58,828) for extreme preterm intensive care. Mean cost per infant per day increased from MYR 401 (MYR 363- MYR 534), MYR 444 (MYR 354 – MYR 916) to MYR 532 (MYR 443-MYR 939) respectively. Cost was dominated by overhead (fixed) costs for general (hospital), intermediate (clinical support services) and final (NICU) cost centers where it constituted at least three quarters of mean admission cost per infant while the remainder was consumables (variable) costs. Breakdown of overhead cost showed NICU specific overhead contributing at least two thirds of mean admission cost per infant. Personnel salary made up three quarters of NICU specific overhead. Laboratory investigation was the cost driver for consumables ranging from 29% (intensive care) to 84% (minimal care) of mean total consumables cost per infant. Gender, birth weight and length of stay were significant factors and cost prediction was developed with these variables.
Splice donor site sgRNAs enhance CRISPR/Cas9-mediated knockout efficiency
Authors: García-Tuñón Ignacio , Alonso-Pérez Verónica , Vuelta Elena , Pérez-Ramos Sandra , Herrero María , Méndez Lucía , Hernández-Sánchez Jesús María , Martín-Izquierdo Marta , Saldaña Raquel , Sevilla Julián , Sánchez-Guijo Fermín , Hernández-Rivas Jesús María , Sánchez-Martín Manuel
Published: January 2019

CRISPR/Cas9 enables the generation of knockout cell lines and null zygotes by inducing site-specific double-stranded breaks. In most cases the DSB is repaired by non-homologous end joining, resulting in small nucleotide insertions or deletions that can be used to construct knockout alleles. However, these mutations do not produce the desired null result in all cases, but instead generate a similar, functionally active protein. This effect could limit the therapeutic efficiency of gene therapy strategies based on abrogating oncogene expression, and therefore needs to be considered carefully. If there is an acceptable degree of efficiency of CRISPR/Cas9 delivery to cells, the key step for success lies in the effectiveness of a specific sgRNA at knocking out the oncogene, when only one sgRNA can be used. This study shows that the null effect could be increased with an sgRNA targeting the splice donor site (SDS) of the chosen exon. Following this strategy, the generation of null alleles would be facilitated in two independent ways: the probability of producing a frameshift mutation and the probability of interrupting the canonical mechanism of pre-mRNA splicing. In these contexts, we propose to improve the loss-of-function yield driving the CRISPR system at the SDS of critical exons.
Applying stochastic spike train theory for high-accuracy MEG/EEG
Authors: Haumann Niels Trusbak , Huotilainen Minna , Vuust Peter , Brattico Elvira
Published: January 2019

The accuracy of electroencephalography (EEG) and magnetoencephalography (MEG) is challenged by overlapping sources from within the brain. This lack of accuracy is a severe limitation to the possibilities and reliability of modern stimulation protocols in basic research and clinical diagnostics. As a solution, we here introduce a theory of stochastic neuronal spike timing probability densities for describing the large-scale spiking activity in neural networks, and a novel spike density component analysis (SCA) method for isolating specific neural sources. Three studies are conducted based on 564 cases of evoked responses to auditory stimuli from 94 human subjects each measured with 60 EEG electrodes and 306 MEG sensors. In the first study we show that the large-scale spike timing (but not non-encephalographic artifacts) in MEG/EEG waveforms can be modeled with Gaussian probability density functions with high accuracy (median 99.7%-99.9% variance explained), while gamma and sine functions fail describing the MEG and EEG waveforms. In the second study we confirm that SCA can isolate a specific evoked response of interest. Our findings indicate that the mismatch negativity (MMN) response is accurately isolated with SCA, while principal component analysis (PCA) fails supressing interference from overlapping brain activity, e.g. from P3a and alpha waves, and independent component analysis (ICA) distorts the evoked response. Finally, we confirm that SCA accurately reveals inter-individual variation in evoked brain responses, by replicating findings relating individual traits with MMN variations. The findings of this paper suggest that the commonly overlapping neural sources in single-subject or patient data can be more accurately separated by applying the introduced theory of large-scale spike timing and method of SCA in comparison to PCA and ICA.

Significance statement

Electroencephalography (EEG) and magnetoencelopraphy (MEG) are among the most applied non-invasive brain recording methods in humans. They are the only methods to measure brain function directly and in time resolutions smaller than seconds. However, in modern research and clinical diagnostics the brain responses of interest cannot be isolated, because of interfering signals of other ongoing brain activity. For the first time, we introduce a theory and method for mathematically describing and isolating overlapping brain signals, which are based on prior intracranial in vivo research on brain cells in monkey and human neural networks. Three studies mutually support our theory and suggest that a new level of accuracy in MEG/EEG can achieved by applying the procedures presented in this paper.
How many cubs can a mum raise? Maternal age and size influence litter size in polar bears
Authors: Folio Dorinda Marie , Aars Jon , Gimenez Olivier , Derocher Andrew E. , Wiig Øystein , Cubaynes Sarah
Published: January 2019

Life history theory predicts that females’ age and size affect the level of maternal investment in current reproduction, balanced against future reproductive effort, maintenance and survival. Using long-term (30 years) individual data on 231 female polar bears (Ursus maritimus), we assessed age- and size-specific variation on litter size. Litter size varied with maternal age, younger females had higher chances of losing a cub during their first months of life. Results suggest an improvement of breeding abilities early in life due to experience with subsequent reproductive senescence. Litter size increased with maternal size, indicating that size may reflect individual quality. Heterogeneity was observed among the largest females, suggesting that large size comes at a cost. Maternal traits and environmental conditions may act together to influence reproductive success.
Individual Tree-Crown Detection in RGB Imagery Using Semi-Supervised Deep Learning Neural Networks
Authors: Weinstein Ben G. , Marconi Sergio , Bohlman Stephanie , Zare Alina , White Ethan
Published: January 2019

Remote sensing can transform the speed, scale, and cost of biodiversity and forestry surveys. Data acquisition currently outpaces the ability to identify individual organisms in high resolution imagery. We outline an approach for identifying tree-crowns in RGB imagery while using a semi-supervised deep learning detection network. Individual crown delineation has been a long-standing challenge in remote sensing and available algorithms produce mixed results. We show that deep learning models can leverage existing Light Detection and Ranging (LIDAR)-based unsupervised delineation to generate trees that are used for training an initial RGB crown detection model. Despite limitations in the original unsupervised detection approach, this noisy training data may contain information from which the neural network can learn initial tree features. We then refine the initial model using a small number of higher-quality hand-annotated RGB images. We validate our proposed approach while using an open-canopy site in the National Ecological Observation Network. Our results show that a model using 434,551 self-generated trees with the addition of 2848 hand-annotated trees yields accurate predictions in natural landscapes. Using an intersection-over-union threshold of 0.5, the full model had an average tree crown recall of 0.69, with a precision of 0.61 for the visually-annotated data. The model had an average tree detection rate of 0.82 for the field collected stems. The addition of a small number of hand-annotated trees improved the performance over the initial self-supervised model. This semi-supervised deep learning approach demonstrates that remote sensing can overcome a lack of labeled training data by generating noisy data for initial training using unsupervised methods and retraining the resulting models with high quality labeled data.
CADHERIN-11 BLOCKADE REDUCES INFLAMMATION-DRIVEN FIBROTIC REMODELING AND IMPROVES OUTCOMES AFTER MYOCARDIAL INFARCTION
Authors: Schroer Alison K. , Bersi Matthew R. , Clark Cynthia R. , Zhang Qinkun , Sanders Lehanna H. , Hatzopoulos Antonis K. , Force Thomas L. , Majka Susan M. , Lal Hind , Merryman W. David
Published: January 2019

Background

Over one million Americans experience myocardial infarction (MI) every year, and the resulting scar and subsequent cardiac fibrosis contribute to heart failure and death. A specialized cell-cell adhesion protein, cadherin-11 (CDH11), contributes to inflammation and fibrosis in rheumatoid arthritis, pulmonary fibrosis, and aortic valve calcification but has not yet been studied in the context of cardiac remodeling after MI. We hypothesized that targeting CDH11 function after MI would reduce inflammation-driven fibrotic remodeling and infarct expansion to improve functional outcomes in mice.

Methods

MI was induced by ligation of the left anterior descending artery in transgenic mice with reduced or ablated CDH11, wild type mice receiving bone marrow transplants fromCdh11transgenic animals, and wild type mice treated with a functional blocking antibody against CDH11 (SYN0012). Cardiac function was measured by echocardiography, expression of cell populations was quantified by flow cytometry, and tissue remodeling by altered histological assessment and transcription of inflammatory and pro-angiogenic genes by qPCR. Co-culture was used to assess interactions between cardiac fibroblasts and macrophages.

Results

MI increased transcription ofCdh11in non-cardiomyocyte cells. Mice with deletion ofCdh11and wild type mice receiving bone marrow transplants fromCdh11transgenic animals had improved cardiac function and dimensions after MI. Animals given SYN0012 had improved cardiac function, reduced tissue remodeling, and altered transcription of inflammatory and proangiogenic genes. Targeting CDH11 also reduced the number of bone marrow-derived myeloid cells and increased pro-angiogenic cells in the heart three days after MI, consistent with a decrease in transcription and expression of IL-6 in the infarct region. Cardiac fibroblast and macrophage interactions led to an increase in IL-6 secretion that was reduced with SYN0012 treatment in vitro.

Conclusions

Our findings suggest that CDH11-expressing cells contribute to inflammation-driven fibrotic remodeling after MI, and that targeting CDH11 with a blocking antibody improves cardiac function after MI. This improvement is likely mediated by altered recruitment of bone marrow-derived cells, thereby limiting the macrophage-induced expression of IL-6 by fibroblasts and promoting vascularization.
Novel IRE1-dependent proinflammatory signaling controls tumor infiltration by myeloid cells
Authors: Obacz Joanna , Archambeau Jérôme , Sicari Daria , Le Reste Pierre Jean , Pineau Raphael , Martin Sophie , Barroso Kim , Vlachavas Efstathios , Voutetakis Konstantinos , Fainsod-Levi Tanya , Obiedat Akram , Granot Zvi , Tirosh Boaz , Samal Juhi , Pandit Abhay , Patterson John , Zheng Qinping , Négroni Luc , Chatziioannou Aristotelis , Quillien Véronique , Avril Tony , Chevet Eric
Published: January 2019

Tumor cells are exposed to intrinsic and environmental challenges that trigger endoplasmic reticulum (ER) homeostasis alteration, in turn leading to ER stress. To cope with this, tumor cells engage an adaptive signaling pathway, the unfolded protein response (UPR) thus promoting the acquisition of malignant features. As such, glioblastoma multiforme (GBM), the most aggressive primary brain tumors, exhibit constitutive UPR signals to sustain growth. Herein, we showed that signaling elicited by one of the UPR sensors, IRE1, promotes GBM tumor invasion, angiogenesis and infiltration by macrophages. Hence, high IRE1 activity in tumors predicts worse outcome. We further dissect IRE1-dependent mechanisms that shape the brain tumor immune microenvironment towards myeloid cells. We identify an IRE1-dependent signaling pathway that directly controls the expression/release of proinflammatory chemokines (CXCL2, IL6, IL8) leading to tumor cell-mediated chemoattraction of neutrophils and macrophages. This pathway requires XBP1 non-conventional mRNA splicing and XBP1s-dependent expression of the E2 ubiquitin enzyme UBE2D3. The latter contributes to the degradation of the NFκB inhibitor IκB, leading to the up-regulation of proinflammatory chemokines. Our work identifies a novel IRE1/UBE2D3 proinflammatory signaling axis instrumental to pro-tumoral immune regulation of GBM.
Phosphatidylinositol 3,5-Bisphosphate regulates Ca2+Transport During Yeast Vacuolar Fusion through Activation of the Ca2+ATPase Pmc1
Authors: Miner Gregory E. , Sullivan Katherine D. , Guo Annie , Starr Matthew L. , Ellis EZ C. , Jones Brandon C. , Fratti Rutilio A.
Published: January 2019

The transport of Ca2+across membranes precedes the fusion and fission of various lipid bilayers. Yeast vacuoles during hyperosmotic shock become fragmented through fission events that require Ca2+efflux of their luminal stores through the TRP channel Yvc1. This requires the production of the lipid PI(3,5)P2by Fab1. Ca2+is also released during vacuole fusion upontrans-SNARE complex assembly, however, the role of PI(3,5)P2remains unclear. Here we demonstrate that elevated PI(3,5)P2levels abolish Ca2+efflux during fusion, indicating that PI(3,5)P2has opposing effects on Ca2+transport in fission versus fusion. Notably, Ca2+efflux was enhanced when PI(3,5)P2levels were reduced. Importantly, the effect of PI(3,5)P2on Ca2+flux was independent of Yvc1. Rather, the effect was dependent on the Ca2+pump Pmc1. Vacuoles lacking Pmc1 were resistant to the effects of PI(3,5)P2, while those lacking Yvc1 remained sensitive. Furthermore altering PI(3,5)P2levels affects the interactions of Pmc1 with the Vocomponent Vph1 and the R-SNARE Nyv1. We now propose a model in which elevated PI(3,5)P2activates continued Pmc1 function to prevent the accumulation of released extraluminal Ca2+.

During osmotic stress PI(3,5)P2triggers Ca2+release from vacuoles. Here we show PI(3,5)P2stimulates Ca2+uptake by vacuoles during fusion, illustrating that it has a dual role in Ca2+transport.
N-terminal 45 amino acids of DEF6 are necessary and sufficient to spontaneously colocalise with DCP1 in P-bodies
Authors: Cheng Huaitao , Alsayegh Maha , Sablitzky Fred
Published: January 2019

DEF6 (Differentially Expressed in FDCP 6, also known as IBP and/or SLAT) is critical for the development of autoimmune disease and cancer. In T cells, DEF6 participates in TCR-mediated signalling determining T helper cell-mediated immune responses. In addition, DEF6 acts as a guanine nucleotide exchange factor (GEF) for Rho GTPases facilitating F-actin assembly and stabilisation of the immunological synapse (IS). However, DEF6 is also a component of mRNA processing bodies (P-bodies) linking it to mRNA metabolism. Including DEF6, more than 34 proteins have been shown to localise in P-bodies many of which contain a coiled coil domain, a super-secondary structure likely to facilitate interaction between these proteins. Accordingly, we suggested that the coiled coil domain in the C-terminal end of DEF6 was mediating P-body localisation of DEF6 under cellular stress conditions. However, a comprehensive analysis of wild type and mutant DEF6 proteins expressed in COS7 cells revealed that the coiled coil domain is dispensable for P-body colocalisation. Instead, we show here that the N-terminal 45 amino acids of DEF6 that contain one Ca2+-binding EF hand motif are sufficient to target DEF6 to P-bodies whereas the N-terminal 30 amino acids containing a disrupted EF hand motif are insufficient.
Impoverished auditory cues fail to engage brain networks controlling spatial selective attention
Authors: Deng Yuqi , Choi Inyong , Shinn-Cunningham Barbara , Baumgartner Robert
Published: January 2019

Spatial selective attention enables listeners to process a signal of interest in natural settings. However, most past studies on auditory spatial attention used impoverished spatial cues: presenting competing sounds to different ears, using only interaural differences in time (ITDs) and/or intensity (IIDs), or using non-individualized head-related transfer functions (HRTFs). Here we tested the hypothesis that impoverished spatial cues impair spatial auditory attention by only weakly engaging relevant cortical networks. Eighteen normal-hearing listeners reported the content of one of two competing syllable streams simulated at roughly +30 ° and −30° azimuth. The competing streams consisted of syllables from two different-sex talkers. Spatialization was based on natural spatial cues (individualized HRTFs), individualized IIDs, or generic ITDs. We measured behavioral performance as well as electroencephalographic markers of selective attention. Behaviorally, subjects recalled target streams most accurately with natural cues. Neurally, spatial attention significantly modulated early evoked sensory response magnitudes only for natural cues, not in conditions using only ITDs or IIDs. Consistent with this, parietal oscillatory power in the alpha band (8-14 Hz; associated with filtering out distracting events from unattended directions) showed significantly less attentional modulation with isolated spatial cues than with natural cues. Our findings support the hypothesis that spatial selective attention networks are only partially engaged by impoverished spatial auditory cues. These results not only suggest that studies using unnatural spatial cues underestimate the neural effects of spatial auditory attention, they also illustrate the importance of preserving natural spatial cues in assistive listening devices to support robust attentional control.
Structural basis for the recognition of K48-linked Ub chain by proteasomal receptor Rpn13
Authors: Liu Zhu , Dong Xu , Yi Hua-Wei , Yang Ju , Gong Zhou , Wang Yi , Liu Kan , Zhang Wei-Ping , Tang Chun
Published: January 2019

The interaction between K48-linked ubiquitin (Ub) chain and Rpn13 is important for proteasomal degradation of ubiquitinated substrate proteins. Only the complex structure between the N-terminal domain of Rpn13 (Rpn13NTD) and Ub monomer has been characterized, and it remains unclear how Rpn13 specifically recognizes K48-linked Ub chain. Using single-molecule FRET, here we show that K48-linked diubiquitin (K48-diUb) fluctuates among three distinct conformational states, and a preexisting compact state is selectively enriched by Rpn13NTD. The same binding mode is observed for full-length Rpn13 and longer K48-linked Ub chain. Using solution NMR spectroscopy, we have solved the complex structure between Rpn13NTDand K48-diUb. In the structure, Rpn13NTDsimultaneously interacts with proximal and distal Ub subunits of K48-diUb that remain associated in the complex, thus corroborating smFRET findings. The proximal Ub interacts with Rpn13NTDsimilarly as the Ub monomer in the known Rpn13NTD:Ub structure, while the distal Ub binds to a largely electrostatic surface of Rpn13NTD. Thus, a charge reversal mutation in Rpn13NTDcan weaken the interaction between Rpn13 and K48-linked Ub chain, causing accumulation of ubiquitinated proteins. Moreover, blockage of the access of the distal Ub to Rpn13NTDwith a proximity attached Ub monomer can also disrupt the interaction between Rpn13 and K48-diUb. Together, the bivalent interaction of K48-linked Ub chain with Rpn13 provides the structural basis for Rpn13 linkage selectivity, which opens a new window for modulating proteasomal function.
DeepTRIAGE: Interpretable and Individualised Biomarker Scores using Attention Mechanism for the Classification of Breast Cancer Sub-types
Authors: Beykikhoshk Adham , Quinn Thomas P. , Lee Samuel C. , Tran Truyen , Venkatesh Svetha
Published: January 2019

Motivation

Breast cancer is a collection of multiple tissue pathologies, each with a distinct molecular signature that correlates with patient prognosis and response to therapy. Accurately differentiating between breast cancer sub-types is an important part of clinical decision-making. Already, this problem has been addressed using machine learning methods that separate tissue samples into distinct groups. However, there remains unexplained heterogeneity within the established sub-types that cannot be resolved by the commonly used classification algorithms. In this paper, we propose a novel deep learning architecture, calledDeepTRIAGE(Deep learning for the TRactable Individualised Analysis of Gene Expression), which not only classifies cancer sub-types with comparable accuracy, but simultaneously assigns each patient their own set of interpretable and individualised biomarker scores. These personalised scores describe how important each feature is in the classification of each patient, and can be analysed post-hoc to generate new hypotheses about intra-class heterogeneity.

Results

We apply theDeepTRIAGEframework to classify the gene expression signatures of luminal A and luminal B breast cancer sub-types, and illustrate its use for genes and gene set (i.e., GO and KEGG) features. Using DeepTRIAGE, we find that the GINS1 gene and the kinetochore organisation GO term are the most important features for luminal sub-type classification. Through classification,DeepTRIAGEsimultaneously reveals heterogeneity within the luminal A biomarker scores that significantly associate with tumour stage, placing all luminal samples along a continuum of severity.

Availability and implementation

The proposed model is implemented in Python using Py-Torch framework. The analysis is done in Python and R. All Methods and models are freely available fromhttps://github.com/adham/BiomarkerAttend.