bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of the Diagnostic Accuracy of the CareStart™ Glucose-6-Phosphate Dehydrogenase Deficiency Rapid Diagnostic Test among Chinese Newborns
Authors: Yu Fengting , Zhang Sufen , Chen Binhuan , Zhou Yuqiu , Ma Chengjie , Yang Siyuan , Tang Yunxia , Huang Dan , Xie Xiaohui , Xiao Qizhi , Wang Linghang
Published: February 2020

Previous studies have shown that the CareStart™ G6PD Deficiency rapid diagnostic test has high diagnostic accuracy on G6PD deficiency in Africa and Thailand, but not in China. As there are regional differences of G6PD genotype distribution, we are attending to verify the effectiveness of the kit in Chinese population. The study cohort included 247 newborns admitted to our hospital for jaundice. The quantitative detection of G6PD enzyme activity and G6PD gene mutations analysis was used to classify the status of G6PD deficiency. The performance of CareStart™ assays was verified by calculating the sensitivity, specificity and area under the receiver operating characteristic curve (AUC) based on the corrected G6PD deficiency status. In male newborns, the sensitivity of the CareStart™ assay was 98.9%, the specificity was 94.2% and the AUC was 0.97. In female newborns, the sensitivity was 58.5% when the cutoff value of residual enzyme activity was 100%; however, the sensitivity was 100% when the cutoff value was 60%. Therefore, the CareStart™ test can effectively screen G6PD deficiency in male newborns and female infants with less than 60% residual enzyme activity, female infants with residual enzyme activities of 60–100% are more likely to be missed diagnosed among Chinese newborns.
Population Genetics and Fungicide Resistance of Botrytis cinerea on Vitis and Prunus spp. in California
Authors: DeLong Jeffery A. , Saito Seiya , Xiao Chang-Lin , Naegele Rachel P.
Published: February 2020

Botrytis cinerea, the causal agent of gray mold, has high genetic diversity and a broad host range. In Vitis sp. and Prunus spp., B. cinerea causes pre- and postharvest diseases, and fungicides are routinely applied to prevent yield loss. In total, 535 isolates of B. cinerea collected from Vitis sp. and Prunus spp. in 2012, 2016, and 2017 were genotyped using 18 microsatellite markers and the transposable elements (TEs) Boty and Flipper. Only nine of the polymorphic markers and the two TEs were considered informative and retained for the final analyses. Of the 532 isolates, 297 were tested for resistance to seven fungicides representing six Fungicide Resistance Action Committee classes. After clone correction, 295 multilocus genotype groups were retained across the 3 years in 326 individuals, and four genetic subpopulations were detected. High levels of clonality were observed across the dataset. Significant pairwise differentiation was detected among years, locations, and TE composition. However, most of the diversity observed was within a subpopulation and not among subpopulations. No genetic differentiation was detected among resistant and sensitive isolates for individual fungicide classes. When resistance to the total number of fungicides was compared, regardless of the fungicide class, significant differentiation was detected among isolates that are resistant to two fungicide classes and those resistant to three or four fungicide groups. Fungicide resistance frequencies were stable for most chemistries evaluated with the exception of fluopyram, which increased from 2012 to 2016/2017.
The clinicopathological characteristics and genetic alterations of mucinous carcinoma of the stomach
Authors: Tseng Chien-Hsun , Fang Wen-Liang , Huang Kuo-Hung , Chen Ming-Huang , Chao Yee , Lo Su-Shun , Li Anna Fen-Yau , Wu Chew-Wun , Shyr Yi-Ming
Published: February 2020

Background:

Mucinous gastric carcinoma (MGC) is rare and often associated with an advanced stage. The clinicopathological features and prognosis of MGC and non-MGC (NMGC) are controversial.

Methods:

In total, 2637 gastric cancer (GC) patients receiving curative surgery were enrolled. The clinicopathological features and genetic alterations were compared between patients with MGC and NMGC.

Results:

Among the 2637 GC patients, 92 (3.5%) had MGC. After propensity score matching, compared to patients with NMGC, patients with MGC had more poorly differentiated tumors, medullary stromal reaction-type tumors, tumors with infiltrating Ming’s classification, diffuse-type tumors, more abnormal preoperative serum carbohydrate antigen 19-9 levels, and more advanced T categories. After propensity score matching, there were no significant differences between MGC and NMGC regarding the initial recurrence patterns, 5-year overall survival (OS), and disease-free survival (DFS) rates. Multivariate analysis demonstrated that the MGC cell type is not an independent prognostic factor of OS and DFS. No significant differences in microsatellite instability status, Epstein–Barr virus infection, Helicobacter pylori infection, or genetic mutations were observed between MGC and NMGC. The expression of programmed death-ligand 1 (PD-L1) was significantly higher in MGC than that in NMGC. MGC was diagnosed at a more advanced stage compared with NMGC.

Conclusion:

MGC itself was not an independent prognostic factor of worse survival. MGC was correlated with higher PD-L1 expression than NMGC, which may have a clinical impact on the treatment of MGC in the future.
Drug-induced proarrhythmia: Discussion and considerations for clinical practice
Authors: Klotzbaugh Ralph J. , Martin Alejandra , Turner John Rick
Published: February 2020

The clinical practice of pharmaceutical medicine includes contributions from physicians, pharmacists, nurse practitioners, and physician assistants. Drug safety considerations are of considerable importance. This article discusses drug-induced proarrhythmia, with a specific focus on Torsade de Pointes (Torsade), a polymorphic ventricular tachycardia that typically occurs in self-limiting bursts that can lead to dizziness, palpitations, syncope, and seizures, but on rare occasions can progress to ventricular fibrillation and sudden cardiac death. A dedicated clinical pharmacology study conducted during a drug's clinical development program has assessed its propensity to induce Torsade using prolongation of the QT interval as seen on the surface electrocardiogram (ECG) as a biomarker. Identification of QT-interval prolongation does not necessarily prevent a drug from receiving marketing approval if its overall benefit-risk balance is favorable, but, if approved, a warning is placed in its Prescribing Information. This article explains why drugs can have a proarrhythmic propensity and concludes with a case presentation.
On the front lines of disaster recovery: Nurse practitioners fill the health care void
Authors: Wilson Kathleen P.
Published: February 2020

Hurricane Michael made landfall in Florida's northwest Gulf Coast on October 10, 2018, causing massive destruction. It was the first Category 5 storm in recorded history to make landfall in the northeast Gulf Coast and the third most destructive hurricane to hit the continental United States. The health care infrastructure collapsed due to the severe damage to two main acute care hospitals, several heath care facilities, and clinics, resulting in large staff layoffs with many physicians relocating out of the area due to lack or support. With many schools and business destroyed, nearly 3,000 children left the school system along with their families. Ultimately, there were not enough living spaces for first responders and recovery crews, so posthurricane recovery efforts were gravely affected. Here are the stories of four nurse practitioners (NPs) who stepped up and recreated themselves to provide needed health care to several communities ravaged by Hurricane Michael. NPs, as skilled and trusted health care providers, are well-prepared to address the pressing life-threatening needs often associated with disasters such as hurricanes, thus ultimately making a difference in health outcomes in affected communities. It is a testimony for NPs across the state of Florida to be able to practice to their full extent of their education and preparation.
Uncommon Prostate Malignant Neoplasms
Authors: Horvat Natally , Gusmao Marcelo , Coelho Fernando Morbeck Almeida , Dias Adriano Basso , Bordini Andre Leopoldino , Panizza Pedro Sergio Brito , Cardili Leonardo , Horvat Joao Vicente , Viana Publio Cesar Cavalcante
Published: February 2020

Prostate adenocarcinoma is the most common prostate cancer; however, there are several other malignant neoplasms that radiologists should be familiar with. The histological classification of malignant prostate neoplasms includes epithelial tumors, mesenchymal tumors, neuroendocrine tumors, hematolymphoid tumors, and stromal tumors. Knowledge of the main clinical and prostate magnetic resonance imaging features of uncommon tumors beyond adenocarcinoma is important for radiologists to enlarge their diagnostic ability and guide referring physician regarding the appropriate patient workup.

The aim of this review article is to (1) review the main anatomical and histological concepts of the prostate gland and (2) provide an overview of uncommon prostate malignant neoplasms, emphasizing the key clinical, pathological, and imaging findings that may help radiologists in their daily interpretation of prostate magnetic resonance imaging.
Development and validation of the Irish Science Self-Efficacy Children’s Questionnaire to assess the short-term influence of scientists facilitating outreach
Authors: Carroll Sarah , Sheahan Jerome , McCauley Veronica , Grenon Muriel
Published: February 2020

Despite the positive relationship between science self-efficacy and science motivation, and the prevalence of scientist-led outreach programs, there is limited research on the effect of scientists on children’s science self-efficacy beliefs. Furthermore, there is no extant science self-efficacy research on primary pupils in Ireland, possibly due to the absence of a suitable and valid assessment instrument. This multi-study research aimed to develop and validate a questionnaire suitable for investigating the effect of scientist-facilitated science outreach on the science self-efficacy of children aged 11-12 years old. In Study 1 the first version of the Irish Science Self-Efficacy Children’s Questionnaire (IS-SEC-Q) was developed and tested with 92 primary school students. In Study 2, the revised questionnaire was re-tested with 282 students. For both studies, construct validity was examined through factor analysis. Questionnaire interpretation and comprehension were investigated via interviews (N=4 and 25 respectively). In Study 2, convergent and criterion validity of the scales was also examined. The final IS-SEC-Q contained 5 scales (63 items), including an adaptation of Usher and Pajares ‘Sources of Self-Efficacy in Mathematics’ scale. Study 2 interviews indicated possible misinterpretations of the Emotional State subscale. The questionnaire demonstrated good psychometric properties and should serve well for informal science education practitioners endeavouring to assess their impact on primary children’s science self-efficacy.
Divided attention for feature-based selection in visual cortex
Authors: Moreland James C. , Boynton Geoffrey M.
Published: February 2020

Feature-based attention can select relevant features such as colors or directions of motion from the visual field irrespective of the spatial position. In visual cortex not only do we see feature-specific attention affecting responses in neurons with receptive fields at an attended location, but that effect also spreads to neurons with receptive fields beyond the spatially relevant location. When only one feature is task relevant, the spread of activity across space can act to facilitate perception of behaviorally relevant stimuli. However, when multiple features are relevant, what is the effect on behavior and brain activity? We tested this question by having observers divide attention between two patches (left and right of fixation) of moving dot stimuli, each containing overlapping upward and downward motion fields. In one condition, subjects performed a task on motion fields moving in the same direction in both patches. In another condition attention was divided between opposite directions of motion. Replicating a previous behavioral study, we found that observers showed better performance when dividing attention to the same directions of motion than opposing directions of motion. We analyzed the BOLD responses while observers performed this task using an inverted encoding model approach that provides estimates of responses to each of the four component dot fields. We found larger responses to the attended components, replicating previous studies of spatial and feature-based attention. However, these effects were much larger when attention was divided to between the same directions of motion than to opposing directions. Our fMRI results in area hMT+ predict our behavioral results by extending the normalization model of attention to include a global feature-based attention component in that leads to suppressed responses to attended stimulus components when attention is directed to opposing directions of motion.
Detecting strawberry cultivar misidentification in the Philippines using single nucleotide polymorphism markers from the anthocyanin reductase gene
Authors: Ledesma Nadine Adellia , Matulac John Mark , Sevilleja Jesus Emmanuel , Enriquez Maria Luisa
Published: February 2020

BACKGROUND

Commercial strawberry production in the Philippines is done by small-holder farmers in La Trinidad, Benguet, where the climate is conducive for optimal growth of this temperate crop. However, these farmers are not cognizant of the importance of proper cultivar identification, particularly during runner propagation, distribution, and transplanting. Thus, there is a high likelihood that misidentification of commonly grown cultivars has taken place.

OBJECTIVE

The study aimed to develop single nucleotide polymorphism markers and use them to detect possible misidentification among strawberry cultivars.

METHODS

Leaf samples from several cultivars were obtained from farmers and the germplasm collection of a local university in La Trinidad, Benguet, Philippines. Expressed sequence tags from theANRgene were screened for putative SNPs. Eleven SNP markers were developed and used to discriminate among the collected samples.

RESULTS

The SNP markers grouped the cultivars into five genotypic clusters with seven distinct genotypic identities. Clustering analysis revealed inconsistencies between the farmers’ identification and the molecular classification. ‘Sweet Charlie’ samples were assigned to four genotypic clusters and ‘Strawberry Festival’ samples were grouped into three separate clusters.

CONCLUSION

There is a high probability that cultivar misidentification has indeed occurred. The molecular markers developed in this study could assist in future cultivar verification efforts, germplasm management, and breeding programs.
TRACE: An unbiased method to permanently tag transiently activated inputs
Authors: Krauth Nathalie , Khalil Valentina , Jariwala Meet , Mermet-Joret Noëmie , Vestergaard Anne-Katrine , Capogna Marco , Nabavi Sadegh
Published: February 2020

A fundamental interest in circuit analysis is to parse out the synaptic inputs underlying a behavioral experience. Toward this aim, we have devised an unbiased strategy that specifically labels the afferent inputs that are activated by a defined stimulus in an activity-dependent manner. We validated this strategy in four brain areas receiving known sensory inputs. This strategy, as demonstrated here, accurately identifies these inputs.
Finding recurrent RNA structural networks with fast maximal common subgraphs of edge-colored graphs
Authors: Soulé Antoine , Reinharz Vladimir , Sarrazin-Gendron Roman , Denise Alain , Waldispühl Jérôme
Published: February 2020

Motivations

RNA tertiary structure is crucial to its many non-coding molecular functions. RNA architecture is shaped by its secondary structure composed of stems, stacked canonical base pairs, enclosing loops. While stems are captured by free-energy models, loops composed of non-canonical base pairs are not. Nor are distant interactions linking together those secondary structure elements (SSEs). Databases of conserved 3D geometries (a.k.a. modules) not captured by energetic models are lever-aged for structure prediction and design, but the computational complexity has limited their study to local elements, loops, and recently to those covering pairs of SSEs. Systematically capturing recurrent patterns on a large scale is a main challenge in the study of RNA structures.

Results

In this paper, we present an efficient algorithm to compute maximal isomorphisms in edge colored graphs. This framework is well suited to RNA structures and allows us to generalize previous approaches. In particular, we apply our techniques to find for the first time modules spanning more than 2 SSEs, while improving speed a hundredfold. We extract all recurrent base pair networks among all non-redundant RNA tertiary structures and identify a module connecting 36 different SSEs common to the 23S ribosome ofE. ColiandThermus thermophilus. We organize this information as a hierarchy of modules sharing similarities in their structure, which can serve as a basis for future research on the emergence of structural patterns.

Availability

http://csb.cs.mcgill.ca/carnaval2
Cellpose: a generalist algorithm for cellular segmentation
Authors: Stringer Carsen , Wang Tim , Michaelos Michalis , Pachitariu Marius
Published: February 2020

Many biological applications require the segmentation of cell bodies, membranes and nuclei from microscopy images. Deep learning has enabled great progress on this problem, but current methods are specialized for images that have large training datasets. Here we introduce a generalist, deep learning-based segmentation method called Cellpose, which can precisely segment cells from a wide range of image types and does not require model retraining or parameter adjustments. We trained Cellpose on a new dataset of highly-varied images of cells, containing over 70,000 segmented objects. We also demonstrate a 3D extension of Cellpose which reuses the 2D model and does not require 3D-labelled data. To support community contributions to the training data, we developed software for manual labelling and for curation of the automated results, with optional direct upload to our data repository. Periodically retraining the model on the community-contributed data will ensure that Cellpose improves constantly.
Optimal anticipatory control as a theory of motor preparation: a thalamo-cortical circuit model
Authors: Kao Ta-Chu , Sadabadi Mahdieh S. , Hennequin Guillaume
Published: February 2020

Across a range of motor and cognitive tasks, cortical activity can be accurately described by low-dimensional dynamics unfolding from specific initial conditions on every trial. These “preparatory states” largely determine the subsequent evolution of both neural activity and behaviour, and their importance raises questions regarding how they are — or ought to be — set. Here, we formulate motor preparation as optimal anticipatory control of future movements, and show that the solution requires a form of internal feedback control of cortical circuit dynamics. In contrast to a simple feedforward strategy, feedback control enables fast movement preparation and orthogonality between preparatory and movement activity, a distinctive feature of peri-movement activity in reaching monkeys. We propose a circuit model in which optimal preparatory control is implemented as a thalamo-cortical loop gated by the basal ganglia.
Electrostatic effects in proteins are governed by pH-redistribution of the conformational ensemble
Authors: Kougentakis Christos M. , Majumdar Ananya , Bertrand García-Moreno E.
Published: February 2020

The imperative for charges to be hydrated is one of the most important organizing principles in biology, responsible for the general architecture of biological macromolecules and for energy storage in the form of electrochemical gradients. Paradoxically, many functional sites in proteins have buried ionizable groups1. These groups are tolerated because they are usually buried in the neutral state2. However, when they become charged they can drive structural transitions to open states in which the charge can be stabilized, mostly through interactions with water3. This coupling between the ionization of a buried group and conformational reorganization is precisely the mechanism used by proteins to perform energy transduction4,5,6. By applying this principle to a family of 25 variants of staphylococcal nuclease with internal Lys residues, it was possible to characterize in detail the range of localized partial unfolding events that even a highly stable protein that unfolds cooperatively can undergo in response to H+-binding. Conformational states that constitute vanishingly small populations of the equilibrium native state ensemble of this protein were identified by correlation of structural and thermodynamic data, providing a map of the conformational landscape of this protein with unprecedented detail. The data demonstrate that the apparent pKavalues of buried ionizable residues are not determined by the properties of their microenvironment but by the intrinsic propensity of the protein to populate open states in which internal charged residues can be hydrated. The role of buried residues in functional sites in proteins relies on their ability to tune the conformational ensemble for redistribution in response to small changes in pH. These results provide the physical framework necessary for understanding the role of pH-driven conformational changes in driving biological energy transduction4, the identification of pH-sensing proteins in nature7, and for the engineering of pH-sensitive dynamics and function inde novodesigned proteins8.
The Oft-Overlooked Massively Parallel Reporter Assay: Where, When, and Which Psychiatric Genetic Variants are Functional?
Authors: Mulvey Bernard , Lagunas Tomas , Dougherty Joseph D.
Published: February 2020

Neuropsychiatric phenotypes have been long known to be influenced by heritable risk factors. The past decade of genetic studies have confirmed this directly, revealing specific common and rare genetic variants enriched in disease cohorts. However, the early hope for these studies—that only a small set of genes would be responsible for a given disorder—proved false. The picture that has emerged is far more complex: a given disorder may be influenced by myriad coding and noncoding variants of small effect size, and/or by rare but severe variants of large effect size, manyde novo. Noncoding genomic sequences harbor a large portion of these variants, the molecular functions of which cannot usually be inferred from sequence alone. This creates a substantial barrier to understanding the higher-order molecular and biological systems underlying disease risk. Fortunately, a proliferation of genetic technologies—namely, scalable oligonucleotide synthesis, high-throughput RNA sequencing, CRISPR, and CRISPR derivatives—have opened novel avenues to experimentally identify biologically significant variantsen masse. These advances have yielded an especially versatile technique adaptable to large-scale functional assays of variation in both untranscribed and untranslated regulatory features: Massively Parallel Reporter Assays (MPRAs). MPRAs are powerful molecular genetic tools that can be used to screen tens of thousands of predefined sequences for functional effects in a single experiment. This approach has several ideal features for psychiatric genetics, but remains underutilized in the field to date. To emphasize the opportunities MPRA holds for dissecting psychiatric polygenicity, we review here its applications in the literature, discuss its ability to test several biological variables implicated in psychiatric disorders, illustrate this flexibility with a proof-of-principle,in vivocell-type specific implementation of the assay, and envision future outcomes of applying MPRA to both computational and experimental neurogenetics.
Unsupervised Topological Alignment for Single-Cell Multi-Omics Integration
Authors: Cao Kai , Bai Xiangqi , Hong Yiguang , Wan Lin
Published: February 2020

Single-cell multi-omics data provide a comprehensive molecular view of cells. However, single-cell multi-omics datasets consist of unpaired cells measured with distinct unmatched features across modalities, making data integration challenging. In this study, we present a novel algorithm, termed UnionCom, for the unsupervised topological alignment of single-cell multi-omics integration. UnionCom does not require any correspondence information, either among cells or among features. It first embeds the intrinsic low-dimensional structure of each single-cell dataset into a distance matrix of cells within the same dataset and then aligns the cells across single-cell multi-omics datasets by matching the distance matrices via a matrix optimization method. Finally, it projects the distinct unmatched features across single-cell datasets into a common embedding space for feature comparability of the aligned cells. To match the complex nonlinear geometrical distorted low-dimensional structures across datasets, UnionCom proposes and adjusts a global scaling parameter on distance matrices for aligning similar topological structures. It does not require one-to-one correspondence among cells across datasets, and it can accommodate samples with dataset-specific cell types. UnionCom outperforms state-of-the-art methods on both simulated and real single-cell multi-omics datasets. UnionCom is robust to parameter choices, as well as subsampling of features. UnionCom software is available athttps://github.com/caokai1073/UnionCom.
Individual differences in social reward and threat expectancies linked to grey matter volumes in key regions of the social brain
Authors: Crawford Bonni , Muhlert Nils , MacDonald Geoff , Lawrence Andrew D.
Published: February 2020

Prospection (mentally simulating future events) generates emotionally charged mental images that guide social decision-making. Positive and negative social expectancies – imagining new social interactions to be rewarding vs. threatening – are core components of social approach and avoidance motivation, respectively. Stable individual differences in such positive and negative future-related cognitions may be underpinned by distinct neuroanatomical substrates. Here, we asked 100 healthy adults to vividly imagine themselves in a novel self-relevant social scenario that was ambiguous with regards to possible social acceptance or rejection. During this task we measured their expectancies for social reward (e.g. anticipated feelings of social connection) or threat (e.g. anticipated feelings of rejection). On a separate day they underwent structural MRI; voxel-based morphometry (VBM) was used to explore the relation between their social reward and threat expectancies and regional grey matter volumes (rGMV). Increased rGMV in key regions involved in prospection, subjective valuation and emotion regulation (including ventromedial prefrontal cortex), correlated with both higher social reward and lower social threat expectancies. In contrast, social threat expectancies were uniquely linked with rGMV of regions involved in social attention (posterior superior temporal sulcus) and interoception (somatosensory cortex). These findings provide novel insight into the neurobiology of future-oriented cognitive-affective processes critical to adaptive social functioning.
Proteome Exploration of Legionella pneumophila for Identifying Novel Therapeutics: A Hierarchical Subtractive Genomics and Reverse Vaccinology Approach
Authors: Khan Md Tahsin , Mahmud Araf , Hasan Mahmudul , Azim Kazi Faizul , Begum Musammat Kulsuma , Akter Arzuba , Mondal Shakhinur Islam
Published: February 2020

Legionella pneumophila, the causative agent of a serious type of pneumonia (lung infection) called Legionnaires’ disease. It is emerging as an antibacterial resistant strain day by day. Hence, the identification of novel drug targets and vaccine candidates is essential to fight against this pathogen. Herein attempts were taken through subtractive genomics approach on complete proteome of L. pneumophila to address the challenges of multidrug resistance. A total 2930 proteins from L. pneumophila proteome were investigated through diverse subtractive proteomics approaches, e.g., identification of human non-homologous and pathogen-specific essential proteins, druggability and ‘anti-target’ analysis, prediction of subcellular localization, human microbiome non-homology screening, protein-protein interactions studies in order to find out effective drug and vaccine targets. Only 3 were identified that fulfilled all these criteria and proposed as novel drug targets against L. pneumophila. Furthermore, outer membrane protein TolB was identified as potential vaccine target with better antigenicity score and allowed for further in silico analysis to design a unique multiepitope subunit vaccine against it. Antigenicity and transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis, and molecular docking approach were adopted to generate the most potent epitopes. The final vaccine was constructed by the combination of highly immunogenic epitopes along with suitable adjuvant and linkers. The designed vaccine construct showed higher binding interaction with different MHC molecules and human immune TLR2 receptors with minimum deformability at molecular level. The translational potency and microbial expression of the vaccine protein was also analyzed using pET28a(+) vector. The present study aids in the development of novel therapeutics and vaccine candidates for efficient treatment of the infections caused by Legionella pneumophila. However, further wet lab-based investigations and in vivo trials are highly recommended to experimentally validate our prediction.
aNy-way Independent Component Analysis
Authors: Duan Kuaikuai , Silva Rogers F. , Calhoun Vince D. , Liu Jingyu
Published: February 2020

Multimodal data fusion is a topic of great interest. Several fusion methods have been proposed to investigate coherent patterns and corresponding linkages across modalities, such as joint independent component analysis (jICA), multiset canonical correlation analysis (mCCA), mCCA+jICA, disjoint subspace using ICA (DS-ICA) and parallel ICA. JICA exploits source independence but assumes shared loading parameters. MCCA maximizes correlation linkage across modalities directly but is limited to orthogonal features. While there is no theoretical limit to the number of modalities analyzed together by jICA, mCCA, or the two-step approach mCCA+jICA, these approaches can only extract common features and require thesamenumber of sources/components for all modalities. On the other hand, DS-ICA and parallel ICA can identify both common and distinct features but are limited to two modalities. DS-ICA assumes shared loading parameters among common features, which works well when links are strong. Parallel ICA simultaneously maximizes correlation between modalities and independence of sources, while allowing different number of sources for each modality. However, only a very limited number of modalities and linkage pairs can be optimized. To overcome these limitations, we propose aNy-way ICA, a new model to simultaneously maximize the independence of sources and correlations across modalities. aNy-way ICA combines infomax ICA and Gaussian independent vector analysis (IVA-G) via a shared weight matrix model without orthogonality constraints. Simulation results demonstrate that aNy-way ICA not only accurately recovers sources and loadings, but also the true covariance/linkage patterns, whether different modalities have the same or different number of sources. Moreover, aNy-way ICA outperforms mCCA and mCCA+jICA in terms of source and loading recovery accuracy, especially under noisy conditions.

Clinical Relevance

This establishes a model for N-way data fusion of any number of modalities and linkage pairs, allowing different number of non-orthogonal sources for different modalities.
UFMylation regulates translational homeostasis and cell cycle progression
Authors: Gak Igor A. , Vasiljevic Djordje , Zerjatke Thomas , Yu Lu , Brosch Mario , Roumeliotis Theodoros I. , Horenburg Cindy , Klemm Nancy , Bakos Gábor , Herrmann Alexander , Hampe Jochen , Glauche Ingmar , Choudhary Jyoti S. , Mansfeld Jörg
Published: February 2020

UFMylation, the posttranslational modification of proteins with ubiquitin fold modifier 1 (UFM1) is essential for metazoan life and is associated with multiple human diseases. Although UFMylation has been linked to endoplasmic reticulum (ER) stress, its biological functions and relevant cellular targets beyond the ER are obscure. Here, we show that UFMylation directly controls translation and cell division in a manner otherwise known for cellular homeostasis-sensing pathways such as mTOR. By combining cell cycle analyses, mass spectrometry and ribosome profiling we demonstrate that UFMylation is required for eIF4F translation initiation complex assembly and recruitment of the ribosome. Interference with UFMylation shuts down global translation, which is sensed by cyclin D1 and halts the cell cycle independently of integrated stress response signalling. Our findings establish UFMylation as a key regulator of translation and uncover a pathway that couples translational homeostasis to cell cycle progression via a ubiquitin-like modification.
Calibrated rare variant genetic risk scores for complex disease prediction using large exome sequence repositories
Authors: Lali Ricky , Chong Michael , Omidi Arghavan , Mohammadi-Shemirani Pedrum , Le Ann , Paré Guillaume
Published: February 2020

Rare variants are collectively numerous and may underlie a considerable proportion of complex disease risk. However, identifying genuine rare variant associations is challenging due to small effect sizes, presence of technical artefacts, and heterogeneity in population structure. We hypothesized that rare variant burden over a large number of genes can be combined into predictive rare variant genetic risk score (RVGRS). We propose a novel method (RV-EXCALIBER) that leverages summary-level data from a large public exome sequencing database (gnomAD) as controls and robustly calibrates rare variant burden to account for the aforementioned biases. A RVGRS was found to strongly associate with coronary artery disease (CAD) in European and South Asian populations. Calibrated RVGRS capture the aggregate effect of rare variants through a polygenic model of inheritance, identifies 1.5% of the population with substantial risk of early CAD, and confers risk even when adjusting for known Mendelian CAD genes, clinical risk factors, and common variant gene scores.
Designing an occupancy framework to monitor an endemic rainforest duck: Methodological and modelling considerations
Authors: Jelil Shah Nawaz , Parasar Murchana , Cancino Laura , Cook Kimberly
Published: February 2020

Understanding species trend, decline or growth, is vital to further conservation efforts. Species-habitat relationship studies are equally important for conservation as it helps in understanding the habitat a particular species depends upon, i.e. habitat conservation. However, rare and endemic species are inherently difficult to study and occupancy models are especially useful in such cases. We conducted the first detection, non-detection survey for the white winged duck in Dehing Patkai Wildlife Sanctuary, India to assess site occupancy and test habitat factors that explain its occupancy. We found that white winged duck occupancy was low (0.27 ± 0.21 SE) and detection probability was 0.44 ± 0.30 SE. We found that increasing tree richness and decreasing elevation increased species occupancy. Detection probability was influenced by our effort in that detection increased with increasing number of survey hours. Using two standard approaches, we estimated the optimal number of sites and replicate surveys for future occupancy studies. We further present considerations for future surveys. Considering the sporadic and fragmented information available, we recommend long-term ecological research to better understand the present and future population trends of the species.
Computational investigation of visually guided learning of spatially aligned auditory maps in the colliculus
Authors: Oess Timo , Ernst Marc O. , Neumann Heiko
Published: February 2020

The development of spatially registered auditory maps in the external nucleus of the inferior colliculus in young owls and their maintenance in adult animals is visually guided and evolves dynamically. To investigate the underlying neural mechanisms of this process, we developed a model of stabilized neoHebbian correlative learning which is augmented by an eligibility signal and a temporal trace of activations. This 3-component learning algorithm facilitates stable, yet flexible, formation of spatially registered auditory space maps composed of conductance-based topographically organized neu- ral units. Spatially aligned maps are learned for visual and auditory input stimuli that arrive in temporal and spatial registration. The reliability of visual sensory inputs can be used to regulate the learning rate in the form of an eligibility trace. We show that by shifting visual sensory inputs at the onset of learning the topography of auditory space maps is shifted accordingly. Simulation results explain why a shift of auditory maps in mature animals is possible only if corrections are induced in small steps. We conclude that learning spatially aligned auditory maps is flexibly controlled by reliable visual sensory neurons and can be formalized by a biological plausible unsupervised learning mechanism.
RAS activation via CRLF2 signaling is a widespread mechanism in Down syndrome acute lymphoblastic leukemia regardless of RAS mutations
Authors: Koschut David , Ray Debleena , Li Zhenhua , Giarin Emanuela , Groet Jürgen , Alić Ivan , Kham Shirley Kow-Yin , Chng Wee Joo , Ariffin Hany , Weinstock David M. , Yeoh Allen Eng-Juh , Basso Giuseppe , Nižetić Dean
Published: February 2020

Background

Down syndrome acute lymphoblastic leukemia (DS-ALL) is characterized by the high frequency of CRLF2-rearrangements, JAK2-mutations, or RAS-pathway mutations. Intriguingly, JAK2 and RAS mutations are mutually exclusive in leukemic sub-clones, causing dichotomy in therapeutic target choices.

Results

Here we show that in primary leukemic cells from DS-ALL, in the absence of RAS-mutations, wild-type (wt)RAS is active, and/or can be induced by the physiological ligand TSLP of the transmembrane-receptor CRLF2. We show active/inducible RAS in 14/20 (70%) of primary DS-ALL samples analyzed, 8 of which had no RAS-mutations, but 75% of those had either mutated or hyperphosphorylated JAK2. No wtRAS cases with mutated/hyperphosphorylated JAK2 were observed that lacked activated RAS protein. We prove in a cell model that elevated CRLF2 in combination with constitutionally active JAK2 is sufficient to activate wtRAS. We show that TSLP boosts the direct binding of active PTPN11 to wtRAS. Pre-inhibition of RAS or PTPN11, but not of PI3K or JAK signaling, prevented TSLP-induced RAS-GTP boost.

Using multivariate-clustering based on RAS-activity/inducibility we show significant separation between standard-risk and high-risk DS-ALL groups. Cox proportional-hazards model showed protein-activity (but not mutation status) as independently predictive of outcome.

Conclusions

Our data indicate that RAS protein activity levels (and not JAK2/RAS mutation profiles), are predictive of outcome. Importantly, our data suggest that inhibition of RAS and direct RAS-pathway components should be combined with PI3K/mTOR and/or JAK2 inhibitors for high-risk cases. Therapeutically this is relevant for >75% of DS-ALL and our additional data suggest that it warrants further investigation in high-risk non-DS-ALL.
Deficiency of complement component C1Q prevents cerebrovascular damage and white matter loss in a mouse model of chronic obesity
Authors: Graham Leah C. , Kocalis Heidi E. , Soto Ileana , Howell Gareth R.
Published: February 2020

Age-related cognitive decline and many dementias involve complex interactions of both genetic and environmental risk factors. Recent evidence has demonstrated a strong association of obesity with the development of dementia. Furthermore, white matter damage is found in obese subjects and mouse models of obesity. Here, we found that components of the complement cascade, including C1QA and C3 are increased in the brain of western diet (WD)-fed obese mice, particularly in white matter regions. To functionally test the role of the complement cascade in obesity induced brain pathology, female and male mice deficient in complement component 1qa (C1QA), an essential molecule in the activation of the classical pathway of the complement cascade, were fed a WD and compared to WD-fed WT mice, and toC1qaknockout (KO) and WT mice fed a control diet (CD).C1qaKO mice fed a WD became obese but did not show pericyte loss or a decrease in laminin density in the cortex and hippocampus that was observed in obese WT controls. Furthermore, obesity-induced microglia phagocytosis and breakdown of myelin in the corpus callosum were also prevented by deficiency of C1QA. Collectively, these data show that C1QA is necessary for damage to the cerebrovasculature and white matter damage in diet-induced obesity.

SIGNIFICANCE STATEMENT

Economic growth, an increasingly sedentary lifestyle and a nutritional transition to processed foods and high calorie diets have led to a significant increase in obesity prevalence. Several chronic diseases have been associated with obesity, including dementia. Obesity-induced, peripheral inflammation has been proposed as a possible trigger of pathological changes in the brain that lead to cognitive dysfunction and predisposition to dementia. Here we show that genetic deletion of the complement component C1QA prevents cerebrovascular damage, neuroinflammation and white matter degradation in a mouse model of western diet-induced obesity, demonstrating that inflammatory responses play a significant role in obesity-induced brain pathology. The complement pathway is an attractive therapeutic target to prevent cognitive decline and reduction of dementia risk caused by obesity.
Anin vivoProbabilistic Atlas of the Human Locus Coeruleus at Ultra-high Field
Authors: Ye Rong , Rua Catarina , O’Callaghan Claire , Jones P Simon , Hezemans Frank , Kaalund Sanne S. , Tsvetanov Kamen A. , Rodgers Christopher T. , Williams Guy , Passamonti Luca , Rowe James B.
Published: February 2020

Early and profound pathological changes are evident in the locus coeruleus (LC) in dementia and Parkinson’s disease, with effects on arousal, attention, cognitive and motor control. The LC can be identifiedin vivousing non-invasive magnetic resonance imaging techniques which have potential as biomarkers for detecting and monitoring disease progression. Technical limitations of existing imaging protocols have impaired the sensitivity to regional contrast variance or the spatial variability on the rostrocaudal extent of the LC, with spatial mapping consistent withpost mortemfindings. The current study employs a sensitive magnetisation transfer sequence using ultrahigh field 7T MRI to investigate the LC structurein vivoat high-resolution (resolution 0.4×0.4×0.5 mm, duration seven minutes). Magnetisation transfer images from 53 healthy older volunteers (52-84 years) revealed the spatial features of the LC and were used to create a probabilistic LC atlas for older adults, appropriate for clinical research. Consistent rostrocaudal gradients of slice-wise volume, contrast and variance differences of the LC were observed, mirroring distinctiveex vivospatial distributions of LC cells in its subregions. The contrast-to-noise ratios were calculated for the peak voxels, and for the averaged signals within the atlas, to accommodate the volumetric differences in estimated contrast. The probabilistic atlas is freely available, and the MRI dataset is available for researchers, for replication or to facilitate accurate LC localisation and unbiased contrast extraction in future studies.
A deep learning approach to identify new gene targets of a novel therapeutic for human splicing disorders
Authors: Gao Dadi , Morini Elisabetta , Salani Monica , Krauson Aram J. , Ragavendran Ashok , Erdin Serkan , Logan Emily M. , Chekuri Anil , Li Wencheng , Dakka Amal , Naryshkin Nikolai , Trotta Chris , Effenberger Kerstin A. , Woll Matt , Gabbeta Vijayalakshmi , Karp Gary , Yu Yong , Johnson Graham , Paquette William D. , Talkowski Michael E. , Slaugenhaupt Susan A.
Published: February 2020

Pre-mRNA splicing is a key control point in human gene expression. Disturbances in splicing due to mutation or aberrant splicing regulatory networks lead to dysregulated protein expression and contribute to a substantial fraction of human disease. Several classes of active and selective splicing modulator compounds have been recently identified, thus proving that pre-mRNA splicing is a viable target for therapy. We describe herein the identification of BPN-15477, a novel splicing modulator compound, that restores correct splicing of exon 20 in the Elongator complex protein 1(ELP1)gene carrying the major IVS20+6T>C mutation responsible for familial dysautonomia. We then developed a machine learning approach to evaluate the therapeutic potential of BPN-15477 to correct splicing in other human genetic diseases. Using transcriptome sequencing from compound-treated fibroblast cells, we identified treatment responsive sequence signatures, the majority of which center at the 5’ splice site of exons whose inclusion or exclusion is modulated by SMC treatment. We then leveraged this model to identify 155 human disease genes that harbor ClinVar mutations predicted to alter pre-mRNA splicing as potential targets for BPN-15477 treatment. Usingin vitrosplicing assays, we validated representative predictions by demonstrating successful correction of splicing defects caused by mutations in genes responsible for cystic fibrosis (CFTR), cholesterol ester storage disease (LIPA), Lynch syndrome (MLH1) and familial frontotemporal dementia (MAPT). Our study shows that deep learning techniques can identify a complex set of sequence signatures and predict response to pharmacological modulation, strongly supporting the use ofin silicoapproaches to expand the therapeutic potential of drugs that modulate splicing.
Leukotriene B4licenses inflammasome activation to enhance skin host defense
Authors: Salina Ana Carolina G , Brandt Stephanie , Klopfenstein Nathan , Blackman Amondrea , Byers-Glosson Nicole , Brodskyn Claudia , Tavares Natalia Machado , Silva Icaro Bonyek Santos Da , de Medeiros Alexandra I , Serezani C. Henrique
Published: February 2020

The initial production of inflammatory mediators dictates host defense as well as tissue injury. Inflammasome activation is a constituent of the inflammatory response by recognizing pathogen and host-derived products and eliciting the production of IL-1β, IL-18 as well as inducing a type of inflammatory cell death termed “pyroptosis”. Leukotriene B4(LTB4) is a lipid mediator produced quickly (seconds to minutes) by phagocytes and induces chemotaxis, enhances cytokine/chemokine production, and enhances antimicrobial effector functions. Whether LTB4directly activates the inflammasome is not well understood. Our data show that endogenously produced LTB4is required for the expression of pro-IL-1βin vivoandin vitroand enhances inflammasome assembly. Furthermore, LTB4-mediated Bruton’s tyrosine kinase (BTK) activation is required for inflammasome assemblyin vivoas well for IL-1β-enhanced skin host defense. Together, these data unveil a new role for LTB4in enhancing the expression and assembly of inflammasome components and suggest that while blocking LTB4actions could be a promising therapeutic strategy to prevent inflammasome-mediated diseases, exogenous LTB4can be used as an adjuvant to boost inflammasome-dependent host defense.