bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preoperative Colonic Decompression With Decompression Tube Insertion Versus Stent Insertion in Patients With Malignant Left Colonic Obstruction
Authors: Xu Yuan-Shun , Fu Yu-Fei , Li De-Chun , Song Tao 
Published: July 2019

Purpose:
To compare the clinical effectiveness of preoperative colonic decompression (PCD) performed with stent or decompression tube insertion in patients with malignant left colonic obstruction (MLCO).

Materials and Methods:
Between September 2014 and September 2018, 63 patients with MLCO underwent PCD (decompression tube: 35; stent: 28) in our center. Elective surgery was performed for patients with clinical success of PCD.

Results:
The rates of technical success for PCD with tube and stent insertion were 91.4% (32/35) and 96.4% (27/28), respectively (P=0.773). Clinical success rates for PCD with tube and stent insertion were 90.6% (29/32) and 85.2% (23/27), respectively (P=0.811). Tumor resection with primary anastomosis was performed in all patients with clinical success in both groups. No significant differences were found between 2 groups regarding the duration of surgery and rates of postoperative complications.

Conclusion:
Decompression tube and stent insertion had similar effectiveness for PCD in patients with MLCO.
Variants in the degron ofAFF3cause a multi-system disorder with mesomelic dysplasia, horseshoe kidney and developmental and epileptic encephalopathy
Authors: Voisin Norine , Schnur Rhonda E. , Douzgou Sofia , Hiatt Susan M. , Rustad Cecilie F. , Brown Natasha J. , Earl Dawn L. , Keren Boris , Levchenko Olga , Geuer Sinje , Amor David , Brusco Alfredo , Bebin E. Martina , Cappuccio Gerarda , Charrow Joel , Chatron Nicolas , Cooper Gregory M. , Dadali Elena , Delafontaine Julien , Del Giudice Ennio , Douglas Ganka , Funari Tara , Giannuzzi Giuliana , Guex Nicolas , Heron Delphine , Holla Øystein L. , Hurst Anna C.E. , Juusola Jane , Kronn David , Lavrov Alexander , Lee Crystle , Merckoll Else , Mikhaleva Anna , Norman Jennifer , Pradervand Sylvain , Sanders Victoria , Sirchia Fabio , Takenouchi Toshiki , Tanaka Akemi J. , Taska-Tench Heidi , Tønne Elin , Tveten Kristian , Vitiello Giuseppina , Uehara Tomoko , Nava Caroline , Yalcin Binnaz , Kosaki Kenjiro , Donnai Dian , Mundlos Stefan , Brunetti-Pierri Nicola , Chung Wendy K. , Reymond Alexandre 
Published: July 2019

AbstractThe ALF transcription factor paralogs,AFF1, AFF2, AFF3andAFF4, are components of the transcriptional super elongation complex that regulates expression of genes involved in neurogenesis and development. We describe a new autosomal dominant disorder associated withde novomissense variants in the degron of AFF3, a nine amino acid sequence important for its degradation. Consistent with a causative role ofAFF3variants, the mutated AFF3 proteins show reduced clearance. Ten affected individuals were identified, and present with a recognizable pattern of anomalies, which we named KINSSHIP syndrome (KI for horseshoeKIdney, NS forNievergelt/Savarirayan type of mesomelic dysplasia, S forSeizures, H forHypertrichosis, I forIntellectual disability and P forPulmonary involvement), partially overlapping theAFF4associated CHOPS syndrome. An eleventh individual with a microdeletion encompassing only the transactivation domain and degron motif ofAFF3exhibited overlapping clinical features. A zebrafish overexpression model that shows body axis anomalies provides further support for the pathological effect of increased amount of AFF3 protein.Whereas homozygousAff3knockout mice display skeletal anomalies, kidney defects, brain malformation and neurological anomalies, knock-in animals modeling the microdeletion and the missense variants identified in affected individuals presented with lower mesomelic limb deformities and early lethality, respectively.Transcriptome analyses as well as the partial phenotypic overlap of syndromes associated withAFF3andAFF4variants suggest that ALF transcription factors are not redundant in contrast to what was previously suggested
Integrative prediction of gene expression with chromatin accessibility and conformation data
Authors: Schmidt Florian , Kern Fabian , Schulz Marcel H. 
Published: July 2019

AbstractBackgroundEnhancers play a fundamental role in orchestrating cell state and development. Although several methods have been developed to identify enhancers, linking them to their target genes is still an open problem. Several theories have been proposed on the functional mechanisms of enhancers, which triggered the development of various methods to infer promoter enhancer interactions (PEIs). The advancement of high-throughput techniques describing the three-dimensional organisation of the chromatin, paved the way to pinpoint long-range PEIs. Here we investigated whether including PEIs in computational models for the prediction of gene expression improves performance and interpretability.ResultsWe have extended our Tepic framework to include DNA contacts deduced from chromatin conformation capture experiments and compared various methods to determine PEIs using predictive modelling of gene expression from chromatin accessibility data and predicted transcription factor (TF) motif data. We found that including long-range PEIs deduced from both HiC and HiChIP data indeed improves model performance. We designed a novel machine learning approach that allows to prioritize TFs in distal loop and promoter regions with respect to their importance for gene expression regulation. Our analysis revealed a set of core TFs that are part of enhancer-promoter loops involving YY1 in different cell lines.ConclusionWe show that the integration of chromatin conformation data improves gene expression prediction, underlining the importance of enhancer looping for gene expression regulation. Our general approach can be used to prioritize TFs that are involved in distal and promoter-proximal regulation using accessibility, conformation and expression data.
Leveraging Gene Co-expression Patterns to Infer Trait-Relevant Tissues in Genome-wide Association Studies
Authors: Shang Lulu , Smith Jennifer A. , Zhou Xiang 
Published: July 2019

AbstractGenome-wide association studies (GWASs) have identified many SNPs associated with various common diseases. Understanding the biological functions of these identified SNP associations requires identifying disease/trait relevant tissues or cell types. Here, we develop a network method, CoCoNet, to facilitate the identification of trait-relevant tissues or cell types. Different from existing approaches, CoCoNet incorporates tissue-specific gene co-expression networks constructed from either bulk or single cell RNA sequencing (RNAseq) studies with GWAS data for trait-tissue inference. In particular, CoCoNet relies on a covariance regression network model to express gene-level effect sizes for the given GWAS trait as a function of the tissue-specific co-expression adjacency matrix. With a composite likelihood-based inference algorithm, CoCoNet is scalable to tens of thousands of genes. We validate the performance of CoCoNet through extensive simulations. We apply CoCoNet for an in-depth analysis of four neurological disorders and four autoimmune diseases, where we integrate the corresponding GWASs with bulk RNAseq data from 38 tissues and single cell RNAseq data from 10 cell types. In the real data applications, we show how CoCoNet can help identify specific glial cell types relevant for neurological disorders and identify disease-targeted colon tissues as relevant for autoimmune diseases. Our results also provide empirical evidence supporting one hypothesis of the omnigenic model: that trait-relevant gene co-expression networks underlie disease etiology.
Identification of selection and inhibition components in a Go/NoGo task from EEG spectra using a machine learning model
Authors: DeLaRosa Bambi L. , Spence Jeffrey S. , Motes Michael A. , To Wing , Vanneste Sven , Hart John , Kraut Michael A. 
Published: July 2019

AbstractPrior Go/NoGo studies have localized specific regions and EEG spectra for which traditional approaches have distinguished between Go and NoGo conditions. A more detailed characterization of the spatial distribution and timing of the synchronization of frequency bands would contribute substantially to the clarification of neural mechanisms that underlie performance of the Go/NoGo task. The present study used a machine learning approach to learn the features that distinguish between ERSPs involved in selection and inhibition in a Go/NoGo task. A neural network classifier was used to predict task conditions for each subject to characterize ERSPs associated with Go versus NoGo trials. The final model accurately identified individual task conditions at an overall rate of 92%, estimated by 5-fold cross-validation. The detailed accounting of EEG time-frequency patterns localized to brain sources (i.e., thalamus, preSMA, orbitofrontal cortex, and superior parietal cortex) provides elaboration on previous findings from fMRI and EEG studies and more information about EEG power changes in multiple frequency bands (i.e., primarily theta power increase, alpha decreases, and beta increases and decreases) within these regions underlying the selection and inhibition processes engaged in the Go and NoGo trials. This extends previous findings, providing more information about neural mechanisms underlying selection and inhibition processes engaged in the Go and NoGo trials, respectively, and may offer insight into therapeutic uses of neuromodulation in neural dysfunction.
Cortical bone gain following loading is site-specifically enhanced by prior and concurrent disuse in aged male mice
Authors: Galea Gabriel , Delisser Peter J , Meakin Lee , Lanyon Lance E , Price Joanna S , Windahl Sara H 
Published: July 2019

AbstractThe primary aim of bone anabolic therapies is to strategically increase bone mass in skeletal regions likely to experience high strains. This is naturally achieved by mechanical loading of the young healthy skeleton. However, these bone anabolic responses fail with age. Here, we applied site specificity analysis to map regional differences in bone anabolic responses to axial loading of the tibia (tri-weekly, for two weeks) between young (19-week-old) and aged (19-month-old), male and female mice. Loading increased bone mass specifically in the proximal tibia in both sexes and ages. Young female mice gained more cortical bone than young males in specific regions of the tibia. However, these site-specific sex difference were lost with age such that bone gain following loading was not significantly different between old males and females. Having previously demonstrated that prior and concurrent disuse enhances bone gain following loading in old females, we established whether this “rescue” is sex-specific. Old male mice were subjected to sciatic neurectomy or sham surgery, and tri-weekly loading was initiated four days after surgery. Disuse augmented cortical bone gain in response to loading in old male mice, but only in the regions of the tibia which were load-responsive in the young. Increased understanding of how locally-activated load-responsive processes lead to site-specific bone formation, and how the age-related diminution of these processes can be site-specifically enhanced by disuse, may lead to the next generation of strategic bone anabolic therapies.HighlightsSex differences in cortical tissue area of young and old mice are not site-specificThe loading response in young, but not old, mice is sex- and site-specificThe cortical loading response is site-specifically enhanced by disuse in old mice of both sexesThe trabecular loading response can be rescued by disuse in old male, but not female, mice
Fitness and community feedbacks: the two axes that drive long-term invasion impacts
Authors: Arnoldi Jean-François , Barbier Matthieu , Kelly Ruth , Barabás György , Jackson Andrew L. 
Published: July 2019

AbstractMany facets of ecological theory rely on the analysis of invasion processes, and general approaches exist to understand the early stages of an invasion. However, predicting the long-term transformations of communities following an invasion remains a challenging endeavour. We propose an analytical method that uses community structure and invader dynamical features to predict when these impacts can be large, and show it to be applicable across a wide class of dynamical models. Our approach reveals that short-term invasion success and long-term consequences are two distinct axes of variation controlled by different properties of both invader and resident community. Whether a species can invade is controlled by its invasion fitness, which depends on environmental conditions and direct interactions with resident species. But whether this invasion will cause significant transformations, such as extinctions or a regime shift, depends on a specific measure of indirect feedbacks that may involve the entire resident community. Our approach applies to arbitrarily complex communities, from few competing phenotypes in adaptive dynamics to large nonlinear food webs. It hints at new questions to ask as part of any invasion analysis, and suggests that long-term indirect interactions are key determinants of invasion outcomes.
Weak and uneven associations of home, neighborhood and school environments with stress hormone output across multiple time scales
Authors: Malanchini Margherita , Engelhardt Laura E. , Raffington Laurel , Sabhlok Aditi , Grotzinger Andrew D. , Briley Daniel A. , Madole James W. , Freis Samantha M. , Patterson Megan W. , Harden K. Paige , Tucker-Drob Elliot M. 
Published: July 2019

ABSTRACTThe progression of lifelong trajectories of socioeconomic inequalities in health and mortality begins in childhood. Dysregulation in cortisol, a stress hormone that is the primary output of the hypothalamus-pituitary-adrenal (HPA) axis, has been hypothesized to be a mechanism for how early environmental adversity compromises health. However, despite the popularity of cortisol as a biomarker for stress and adversity, little is known about whether cortisol output differs in children being raised in socioeconomically disadvantaged environments. Here, we show that there are few differences between advantaged and disadvantaged children in their cortisol output. In 8- to 14-year-old children from the population-based Texas Twin Project, we measured cortisol output at three different time-scales: (1) diurnal fluctuation in salivary cortisol (n= 400), (2) salivary cortisol reactivity and recovery after exposure to the Trier Social Stress Test (n= 444), and (3) and cortisol concentration in hair (n= 1,210). These measures converged on two moderately correlated, yet distinguishable, dimensions of HPA function. We then tested differences in cortisol output across nine aspects of social disadvantage at the home (e.g., family socioeconomic status), school (e.g., average levels of academic achievement), and neighborhood (e.g., concentrated poverty). Children living in neighborhoods with higher concentrated poverty had higher diurnal cortisol output, as measured in saliva; otherwise, child cortisol output was unrelated to any other aspect of social disadvantage. Overall, we find limited support for alteration in HPA axis functioning as a general mechanism for the health consequences of socioeconomic inequality in childhood.
Seeing distinct groups where there are none: spurious patterns from between-group PCA
Authors: Cardini Andrea , O’Higgins Paul , Rohlf F. James 
Published: July 2019

AbstractUsing sampling experiments, we found that, when there are fewer groups than variables, between-groups PCA (bgPCA) may suggest surprisingly distinct differences among groups for data in which none exist. While apparently not noticed before, the reasons for this problem are easy to understand. A bgPCA captures the g-1 dimensions of variation among the g group means, but only a fraction of the ∑ni − g dimensions of within-group variation (ni are the sample sizes), when the number of variables, p, is greater than g-1. This introduces a distortion in the appearance of the bgPCA plots because the within-group variation will be underrepresented, unless the variables are sufficiently correlated so that the total variation can be accounted for with just g-1 dimensions. The effect is most obvious when sample sizes are small relative to the number of variables, because smaller samples spread out less, but the distortion is present even for large samples. Strong covariance among variables largely reduces the magnitude of the problem, because it effectively reduces the dimensionality of the data and thus enables a larger proportion of the within-group variation to be accounted for within the g-1-dimensional space of a bgPCA. The distortion will still be relevant though its strength will vary from case to case depending on the structure of the data (p, g, covariances etc.). These are important problems for a method mainly designed for the analysis of variation among groups when there are very large numbers of variables and relatively small samples. In such cases, users are likely to conclude that the groups they are comparing are much more distinct than they really are. Having many variables but just small sample sizes is a common problem in fields ranging from morphometrics (as in our examples) to molecular analyses.
The role of the pre-commissural fornix in episodic autobiographical memory and simulation
Authors: Williams Angharad N. , Ridgeway Samuel , Postans Mark , Graham Kim S. , Lawrence Andrew D. , Hodgetts Carl J. 
Published: July 2019

AbstractNeuropsychological and functional magnetic resonance imaging (MRI) evidence suggests that the ability to vividly remember our personal past, and imagine future scenarios, involves two closely connected regions: the hippocampus and ventromedial prefrontal cortex (vmPFC). Despite evidence of a direct anatomical connection from hippocampus to vmPFC, it is unknown whether hippocampal-vmPFC structural connectivity supports both past and future-oriented episodic thinking. To address this, we applied diffusion-weighted magnetic resonance imaging (dMRI) and a novel deterministic tractography protocol to reconstruct distinct subdivisions of the fornix previously detected in axonal tracer studies, namely pre-commissural (connecting the hippocampus to vmPFC) and post-commissural (linking the hippocampus and medial diencephalon) fornix, in a group of healthy young adult humans who undertook an adapted past-future autobiographical interview. As predicted, we found that inter-individual differences in pre-commissural - but not post-commissural - fornix microstructure (fractional anisotropy) was significantly correlated with the episodic richness of both past and future autobiographical narratives. Notably, these results remained significant when controlling for both non-episodic narrative content and grey matter volumes of the hippocampus and vmPFC. This study provides novel evidence that reconstructing events from one’s personal past, and constructing possible future events, involves a distinct, structurally-instantiated hippocampal-vmPFC pathway.Significance StatementA novel anatomically-guided protocol that allows the pre-commissural and post-commissural fornix fibers to be separately reconstructed in vivo (Christiansen et al., 2016) was applied to reconstruct the pre-commissural subdivision of the white matter fornix tract (anatomically linking the hippocampal formation to the vmPFC) and investigate its contribution to episodic memory and future simulation. We demonstrated that the amount of episodic details contained in past and future narratives, collected via an adapted autobiographical interview, was positively correlated with pre-, but not post-, commissural fornix microstructure. These findings highlight how inter-individual variation in the pre-commissural subdivision of the fornix underpins the construction of self-reflective, contextual events – for both the past and future.
Neural correlates of the DMT experience as assessed via multivariate EEG
Authors: Timmermann Christopher , Roseman Leor , Schartner Michael , Milliere Raphael , Williams Luke , Erritzoe David , Muthukumaraswamy Suresh , Ashton Michael , Bendrioua Adam , Kaur Okdeep , Turton Samuel , Nour Matthew M , Day Camilla M , Leech Robert , Nutt David , Carhart-Harris Robin 
Published: July 2019

AbstractStudying transitions in and out of the altered state of consciousness caused by intravenous (IV) N,N-Dimethyltryptamine (DMT – a fast-acting tryptamine psychedelic) offers a safe and powerful means of advancing knowledge on the neurobiology of conscious states. Here we sought to investigate the effects of IV DMT on the power spectrum and signal diversity of human brain activity (6 female, 7 male) recorded via multivariate EEG, and plot relationships between subjective experience, brain activity and drug plasma concentrations across time. Compared with placebo, DMT markedly reduced oscillatory power in the alpha and beta bands and robustly increased spontaneous signal diversity. Time-referenced analyses revealed close relationships between changes in various aspects of subjective experience and changes in brain activity. Importantly, the emergence of oscillatory activity within the delta and theta frequency bands was found to correlate with the peak of the experience, and particularly its eyes-closed visual component. These findings highlight marked changes in oscillatory activity and signal diversity with DMT that parallel broad and specific components of the relevant subjective experience and thus further our understanding of the neurobiological underpinnings of immersive states of consciousness.
Urgency, Leakage, and the Relative Nature of Information Processing in Decision-making
Authors: Trueblood Jennifer S. , Heathcote Andrew , Evans Nathan J. , Holmes William R. 
Published: July 2019

AbstractOver the last decade, there has been a robust debate in decision neuroscience and psychology about what mechanism governs the time course of decision making. Historically, the most prominent hypothesis is that neural architectures accumulate information over time until some threshold is met, the so-called Evidence Accumulation hypothesis. However, most applications of this theory rely on simplifying assumptions, belying a number of potential complexities. Is changing stimulus information perceived and processed in an independent manner or is there a relative component? Does urgency play a role? What about evidence leakage? Although the latter questions have been the subject of recent investigations, most studies to date have been piecemeal in nature, addressing one aspect of the decision process or another. Here we develop a modeling framework, an extension of the Urgency Gating Model, in conjunction with a changing information experimental paradigm to simultaneously probe these aspects of the decision process. Using state-of-the-art Bayesian methods to perform parameter-based inference, we find that 1) information processing is relative with early information influencing the perception of late information, 2) time varying urgency and evidence accumulation are of roughly equal importance in the decision process, and 3) leakage is present with a time scale of ~200-250ms. To our knowledge, this is the first comprehensive study to utilize a changing information paradigm to jointly and quantitatively estimate the temporal dynamics of human decision-making.