bluuebunny/crossref_metadata_2025_split huggingface dataset:
NIDM: network impulsive dynamics on multiplex biological network for disease-gene prediction
Authors: Xiang Ju , Zhang Jiashuai , Zheng Ruiqing , Li Xingyi , Li Min 
Published: February 2021

Abstract
The prediction of genes related to diseases is important to the study of the diseases due to high cost and time consumption of biological experiments. Network propagation is a popular strategy for disease-gene prediction. However, existing methods focus on the stable solution of dynamics while ignoring the useful information hidden in the dynamical process, and it is still a challenge to make use of multiple types of physical/functional relationships between proteins/genes to effectively predict disease-related genes. Therefore, we proposed a framework of network impulsive dynamics on multiplex biological network (NIDM) to predict disease-related genes, along with four variants of NIDM models and four kinds of impulsive dynamical signatures (IDSs). NIDM is to identify disease-related genes by mining the dynamical responses of nodes to impulsive signals being exerted at specific nodes. By a series of experimental evaluations in various types of biological networks, we confirmed the advantage of multiplex network and the important roles of functional associations in disease-gene prediction, demonstrated superior performance of NIDM compared with four types of network-based algorithms and then gave the effective recommendations of NIDM models and IDS signatures. To facilitate the prioritization and analysis of (candidate) genes associated to specific diseases, we developed a user-friendly web server, which provides three kinds of filtering patterns for genes, network visualization, enrichment analysis and a wealth of external links (http://bioinformatics.csu.edu.cn/DGP/NID.jsp). NIDM is a protocol for disease-gene prediction integrating different types of biological networks, which may become a very useful computational tool for the study of disease-related genes.
An enhanced loss function simplifies the deep learning model for characterizing the 3D organoid models
Authors: Winkelmaier Garrett , Parvin Bahram 
Published: February 2021

Abstract

Motivation
Organization of the organoid models, imaged in 3D with a confocal microscope, is an essential morphometric index to assess responses to stress or therapeutic targets. In fact, differentiating malignant and normal cells is often difficult in monolayer cultures. But in 3D culture, colony organization can provide a clear set of indices for differentiating malignant and normal cells. The limiting factors are delineating each cell in a 3D colony in the presence of perceptual boundaries between adjacent cells and heterogeneity associated with cells being at different cell cycles.

Results
In a previous paper, we defined a potential field for delineating adjacent nuclei, with perceptual boundaries, in 2D histology images by coupling three deep networks. This concept is now extended to 3D and simplified by an enhanced cost function that replaces three deep networks with one. Validation includes four cell lines with diverse mutations, and a comparative analysis with the UNet models of microscopy indicates an improved performance with the F1-score of 0.83.

Availability and implementation
All software and annotated images are available through GitHub and Bioinformatics online. The software includes the proposed method, UNet for microscopy that was extended to 3D and report generation for profiling colony organization.

Supplementary information
Supplementary data are available at Bioinformatics online.
Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography
Authors: Du Xuefeng , Wang Haohan , Zhu Zhenxi , Zeng Xiangrui , Chang Yi-Wei , Zhang Jing , Xing Eric , Xu Min 
Published: February 2021

Abstract

Motivation
Cryo-Electron Tomography (cryo-ET) is a 3D bioimaging tool that visualizes the structural and spatial organization of macromolecules at a near-native state in single cells, which has broad applications in life science. However, the systematic structural recognition and recovery of macromolecules captured by cryo-ET are difficult due to high structural complexity and imaging limits. Deep learning-based subtomogram classification has played critical roles for such tasks. As supervised approaches, however, their performance relies on sufficient and laborious annotation on a large training dataset.

Results
To alleviate this major labeling burden, we proposed a Hybrid Active Learning (HAL) framework for querying subtomograms for labeling from a large unlabeled subtomogram pool. Firstly, HAL adopts uncertainty sampling to select the subtomograms that have the most uncertain predictions. This strategy enforces the model to be aware of the inductive bias during classification and subtomogram selection, which satisfies the discriminativeness principle in AL literature. Moreover, to mitigate the sampling bias caused by such strategy, a discriminator is introduced to judge if a certain subtomogram is labeled or unlabeled and subsequently the model queries the subtomogram that have higher probabilities to be unlabeled. Such query strategy encourages to match the data distribution between the labeled and unlabeled subtomogram samples, which essentially encodes the representativeness criterion into the subtomogram selection process. Additionally, HAL introduces a subset sampling strategy to improve the diversity of the query set, so that the information overlap is decreased between the queried batches and the algorithmic efficiency is improved. Our experiments on subtomogram classification tasks using both simulated and real data demonstrate that we can achieve comparable testing performance (on average only 3% accuracy drop) by using less than 30% of the labeled subtomograms, which shows a very promising result for subtomogram classification task with limited labeling resources.

Availability and implementation
https://github.com/xulabs/aitom.

Supplementary information
Supplementary data are available at Bioinformatics online.
Molecular biogeography of the fungus-dwelling saproxylic beetle Bolitophagus reticulatus indicates rapid expansion from glacial refugia
Authors: Eberle Jonas , Husemann Martin , Doerfler Inken , Ulrich Werner , Müller Jörg , Bouget Christophe , Brin Antoine , Gossner Martin M , Heilmann-Clausen Jacob , Isacsson Gunnar , Krištín Anton , Lachat Thibault , Larrieu Laurent , Rigling Andreas , Schmidl Jürgen , Seibold Sebastian , Vandekerkhove Kris , Habel Jan Christian 
Published: February 2021

Abstract
The geographical distributions of species associated with European temperate broadleaf forests have been significantly influenced by glacial–interglacial cycles. During glacial periods, these species persisted in Mediterranean and extra-Mediterranean refugia and later, during interglacial periods, expanded northwards. The widespread saproxylic beetle Bolitophagus reticulatus depends closely on European temperate broadleaf forests. It usually develops in the tinder fungus Fomes fomentarius, a major decomposer of broadleaf-wood. We sampled B. reticulatus in sporocarps from European beech (Fagus sylvatica) and Oriental beech (Fagus orientalis) across Europe and the Caucasus region. We analysed mitochondrial gene sequences (cox1, cox2, cob) and 17 microsatellites to reconstruct the geographical distribution of glacial refugia and postglacial recolonization pathways. We found only marginal genetic differentiation of B. reticulatus, except for a significant split between populations of the Caucasus region and Europe. This indicates the existence of past refugia south of the Great Caucasus, and a contact zone with European populations in the Crimean region. Further potential refugia might have been located at the foothills of the Pyrenees and in the Balkan region. Our genetic data suggest a phalanx-wise recolonization of Europe, a reflection of the high mobility of B. reticulatus.
Incarceration as a Fundamental Social Cause of Health Inequalities: Jails, Prisons and Vulnerability to COVID-19
Authors: Novisky Meghan A , Nowotny Kathryn M , Jackson Dylan B , Testa Alexander , Vaughn Michael G 
Published: February 2021

Abstract
Although research has established the disproportionate health burdens among incarcerated persons, the literature has yet to identify a theoretical framework for outlining the harms of incarceration associated with pandemics. We advance the literature theoretically by arguing two points. First, we assert that incarceration is a potent structural driver of health inequalities that must be considered as a fundamental social cause of disease. To underscore this point, we review how incarceration meets each of the four fundamental social cause criteria originally proposed by Link and Phelan. Second, given that incarceration is a fundamental social cause of disease, both currently and formerly incarcerated populations are likely to face heightened vulnerabilities to pandemics, including COVID-19, further exacerbating health disparities among incarceration-exposed groups.
Place, Strengths and Assets: A Case Study of How Local Area Coordination is Supporting Individuals and Families Under Conditions of Austerity
Authors: Bainbridge Laura , Lunt Neil 
Published: February 2021

AbstractWe report findings of a mixed-method evaluation of Local Area Coordination (LAC) in one English Local Authority—an approach that draws on principles of earlier intervention, and place-, asset- and strengths-based activity. We drew on documentary materials, unstructured observation and qualitative interviews. In total, fifty-five qualitative interviews were conducted with professional stakeholders (including Coordinators, statutory agencies and community organisations), and a purposive sample of individuals supported by LAC. Positively, LAC is operating as intended. It is a flexible and agile approach, and one that is less constrained by the expectations and methods associated with traditional service delivery. Reported impacts include: tackling isolation and loneliness; building a positive vision of the future; identifying non-service solutions and being heard. We discuss the ongoing conceptual and methodological challenges to building the LAC evidence base, fostering professional support and understanding, and managing expectations of individuals and communities in furthering development. Resolving these would allow LAC to move beyond being a promising, local and small-scale transformative development for individuals and families. Its future trajectory is enmeshed in the implications of COVID-19 for individuals, families and communities: rising poverty and widening inequality, a fragile Third Sector, and concerns about community fatigue and erosion of trust.
Age-Related Differences in White Matter: Understanding Tensor-Based Results Using Fixel-Based Analysis
Authors: Kelley Shannon , Plass John , Bender Andrew R , Polk Thad A 
Published: February 2021

Abstract
Aging is associated with widespread alterations in cerebral white matter (WM). Most prior studies of age differences in WM have used diffusion tensor imaging (DTI), but typical DTI metrics (e.g., fractional anisotropy; FA) can reflect multiple neurobiological features, making interpretation challenging. Here, we used fixel-based analysis (FBA) to investigate age-related WM differences observed using DTI in a sample of 45 older and 25 younger healthy adults. Age-related FA differences were widespread but were strongly associated with differences in multi-fiber complexity (CX), suggesting that they reflected differences in crossing fibers in addition to structural differences in individual fiber segments. FBA also revealed a frontolimbic locus of age-related effects and provided insights into distinct microstructural changes underlying them. Specifically, age differences in fiber density were prominent in fornix, bilateral anterior internal capsule, forceps minor, body of the corpus callosum, and corticospinal tract, while age differences in fiber cross section were largest in cingulum bundle and forceps minor. These results provide novel insights into specific structural differences underlying major WM differences associated with aging.
Development and Validation of an Administrative Codes Algorithm to Identify Abdominal Surgery and Bowel Obstruction in Patients With Inflammatory Bowel Disease
Authors: Gandle Cassandra , Scott Frank I , Waljee Akbar , Vajravelu Ravy K , Sansgiry Shubhada , Hou Jason K 
Published: February 2021

Abstract

Background
Validated administrative codes (CPT and ICD) can permit the use of large databases to study diseases and outcomes. The aim of this study was to validate administrative codes for surgery and obstructive complications in patients with inflammatory bowel disease (IBD).

Methods
We performed a retrospective study of IBD patients within the Veterans Affairs Health Administration (VA) from 2000 to 2015 with administrative codes for bowel surgery and complications validated by chart review. Positive predictive values (PPVs) and negative predictive value (NPV) were calculated.

Results
The PPV for bowel surgery was 96.4%; PPV of obstruction codes for bowel obstruction was 80.5% (95% confidence interval: 69.1%, 89.2%).

Conclusions
CPT and ICD codes for abdominal surgery and obstructive complications can be accurately utilized in IBD patients in VA.
Incidental finding and conservative management of left main coronary atresia in an adult patient: a case report
Authors: Talanas Giuseppe , Corda Giulia , Parodi Guido , Portoghese Michele 
Published: February 2021

Abstract

Background
Left main (LM) coronary atresia (LMCA) is a rare coronary anomaly where the LM is congenitally absent and a variable clinical spectrum can follow. The diagnosis of LMCA is generally made in youth because of the development of symptoms, but very rarely in adulthood. In symptomatic patients, surgical revascularization is recommended, whereas, in asymptomatic patients with LMCA and without inducible myocardial ischaemia, preventive surgical treatment is controversial.

Case summary
A 58-year-old male patient with aortic ectasia detected during an echocardiogram performed to evaluate a hypertension-related preclinical cardiac damage and, due to this finding, an echocardiographic follow-up was suggested. Three years later, he was admitted to undergo coronary angiography (CA) after the computed tomography finding of a suspected occlusion of the LM with collateral circulation from right coronary artery (RCA) to left anterior descending and circumflex arteries. CA confirmed an LMCA and the RCA provided blood supply to the left coronary artery through collaterals whose calibre was similar to that of the target left-sided vessels. No obstructive coronary artery disease was detected. In order to detect potential myocardial ischaemia, a technetium-tetrofosmin cardiac single-photon emission computed tomography during maximal exercise-stress test was performed and it did not show a perfusion defect. Medical management with scheduled follow-up visits was deemed to be the best therapeutic option.

Discussion
LMCA is a rare anomaly where LM is absent and the RCA provides collateral circulation for left coronary artery. In asymptomatic patients, preventive surgical treatment is controversial.
Utility of mobile learning in Electrocardiography
Authors: Viljoen Charle André , Millar Rob Scott , Hoevelmann Julian , Muller Elani , Hähnle Lina , Manning Kathryn , Naude Jonathan , Sliwa Karen , Burch Vanessa Celeste 
Published: February 2021

Abstract

Aims
Mobile learning is attributed to the acquisition of knowledge derived from accessing information on a mobile device. Although increasingly implemented in medical education, research on its utility in Electrocardiography remains sparse. In this study, we explored the effect of mobile learning on the accuracy of electrocardiogram (ECG) analysis and interpretation.

Methods and results
The study comprised 181 participants (77 fourth- and 69 sixth-year medical students, and 35 residents). Participants were randomized to analyse ECGs with a mobile learning strategy [either searching the Internet or using an ECG reference application (app)] or not. For each ECG, they provided their initial diagnosis, key supporting features, and final diagnosis consecutively. Two weeks later, they analysed the same ECGs, without access to any mobile device. ECG interpretation was more accurate when participants used the ECG app (56%), as compared to searching the Internet (50.3%) or neither (43.5%, P = 0.001). Importantly, mobile learning supported participants in revising their initial incorrect ECG diagnosis (ECG app 18.7%, Internet search 13.6%, no mobile device 8.4%, P &lt; 0.001). However, whilst this was true for students, there was no significant difference amongst residents. Internet searches were only useful if participants identified the correct ECG features. The app was beneficial when participants searched by ECG features, but not by diagnosis. Using the ECG reference app required less time than searching the Internet (7:44 ± 4:13 vs. 9:14 ± 4:34, P &lt; 0.001). Mobile learning gains were not sustained after 2 weeks.

Conclusion
Whilst mobile learning contributes to increased ECG diagnostic accuracy, the benefits were not sustained over time.
Delivering an integrated sexual reproductive health and rights and HIV programme to high-school adolescents in a resource-constrained setting
Authors: Shaikh Najma , Grimwood Ashraf , Eley Brian , Fatti Geoffrey , Mathews Catherine , Lombard Carl , Galea Sandro 
Published: February 2021

Abstract
Southern Africa remains the epicentre of the human immunodeficiency virus (HIV) epidemic with AIDS the leading cause of death amongst adolescents. Poor policy translation, inadequate programme implementation and fragmentation of services contribute to adolescents’ poor access to sexual and reproductive health and rights (SRHR) services. This study assessed an integrated, school-based SRHR and HIV programme, modelled on the South African Integrated School Health Policy in a rural, high HIV-prevalence district. A retrospective cohort study of 1260 high-school learners was undertaken to assess programme uptake, change in HIV knowledge and behaviour and the determinants of barrier-methods use at last sexual intercourse. Programme uptake increased (2%–89%; P�&lt;�0.001) over a 16-month period, teenage-pregnancy rates declined (14%–3%; P�&lt;�0.050) and accurate knowledge about HIV transmission through infected blood improved (78.3%–93.8%; P�&lt;�0.050), a year later. Post-intervention, attending a clinic perceived as adolescent-friendly increased the odds of barrier-methods use during the last sexual encounter (aOR=1.85; 95% CI: 1.31–2.60), whilst being female (aOR=0.69; 95% CI: 0.48–0.99), &lt;15 years (aOR=0.44; 95% CI: 0.24–0.80), or having &gt;5 sexual partners in the last year (aOR=0.59; 95% CI: 0.38–0.91) reduced the odds. This study shows that the unmet SRHR needs of under-served adolescents can be addressed through integrated, school-based SRHR programmes.
Fluoroethylnormemantine, A Novel Derivative of Memantine, Facilitates Extinction Learning Without Sensorimotor Deficits
Authors: Chen Briana K , Le Pen Gwenaëlle , Eckmier Adam , Rubinstenn Gilles , Jay Therese M , Denny Christine A 
Published: February 2021

Abstract

Background
Memantine, a noncompetitive N-methyl-D-aspartate receptor antagonist, has been approved for use in Alzheimer’s disease, but an increasing number of studies have investigated its utility for neuropsychiatric disorders. Here, we characterized a novel compound, fluoroethylnormemtantine (FENM), which was derived from memantine with an extra Fluor in an optimized position for in vivo biomarker labeling. We sought to determine if FENM produced similar behavioral effects as memantine and/or if FENM has beneficial effects against fear, avoidance, and behavioral despair.

Methods
We administered saline, FENM, or memantine prior to a number of behavioral assays, including paired-pulse inhibition, open field, light dark test, forced swim test, and cued fear conditioning in male Wistar rats.

Results
Unlike memantine, FENM did not produce nonspecific side effects and did not alter sensorimotor gating or locomotion. FENM decreased immobility in the forced swim test. Moreover, FENM robustly facilitated fear extinction learning when administered prior to either cued fear conditioning training or tone reexposure.

Conclusions
These results suggest that FENM is a promising, novel compound that robustly reduces fear behavior and may be useful for further preclinical testing.
Breaking the waves: asymmetric random periodic features for low-bitrate kernel machines
Authors: Schellekens Vincent , Jacques Laurent 
Published: February 2021

Abstract
Many signal processing and machine learning applications are built from evaluating a kernel on pairs of signals, e.g., to assess the similarity of an incoming query to a database of known signals. This nonlinear evaluation can be simplified to a linear inner product of the random Fourier features (RFFs) of those signals: random projections followed by a periodic map, the complex exponential. It is known that a simple quantization of those features (corresponding to replacing the complex exponential by a different periodic map that takes binary values, which is appealing for their transmission and storage) distorts the approximated kernel, which may be undesirable in practice. Our take-home message is that when the features of only one of the two signals are quantized, the original kernel is recovered without distortion; its practical interest appears in several cases where the kernel evaluations are asymmetric by nature, such as a client-server scheme. Concretely, we introduce the general framework of asymmetric random periodic features, where the two signals of interest are observed through random periodic features—random projections followed by a general periodic map, which is allowed to be different for both signals. We derive the influence of those periodic maps on the approximated kernel and prove uniform probabilistic error bounds holding for all pair of signals picked in an infinite low-complexity set. Interestingly, our results allow the periodic maps to be discontinuous, thanks to a new mathematical tool, i.e., the mean Lipschitz smoothness. We then apply this generic framework to semi-quantized kernel machines (where only one of the signals has quantized features and the other has classical RFFs), for which we show theoretically that the approximated kernel remains unchanged (with the associated error bound) and confirm the power of the approach with numerical simulations.