bluuebunny/crossref_metadata_2025_split huggingface dataset:
The prevention of hospital-acquired pressure injuries among adult immobilized patients in a mental health department: a best practice implementation project
Authors: Dobre Claudia E. , Gagiu Corina , Jitianu Dorinela A. , Zazu Mariana , Mazilu Doina C. , Jiménez Marina Gallego 
Published: July 2022

Abstract

Objectives:
The aim of this implementation project was to promote evidence-based practices regarding hospital-acquired pressure injuries prevention practices among immobilized adult patients in a mental health department and to measure the level of compliance with the best practice in this field.

Introduction:
Pressure injuries can have significant restrictions on the patient's quality of life; affect the patient physically, psychologically, and socially; lead to increased costs and length of hospital stay; and are closely linked to increased mortality. Thus, the best evidence practice implementation project was conducted in the mental health ward of a large teaching hospital in Bucharest.

Method:
The current evidence implementation project used the JBI Practical Application of Clinical Evidence System and Getting Research into Practice. The best practices project was carried out in a mental health department with 70 beds at Bucharest's largest mental health hospital. This analysis of nursing practice included all immobile patients who were hospitalized in the ward.

Results:
Through the project to implement best practices for the prevention of pressure injuries, the activity of nurses was improved. If initially, the prevention of pressure injuries was a deficient activity in the hospital (compliance between 0 and 82%), after the implementation of the project, compliance with the recommendations of evidence-based practices was radically improved, obtaining a maximum percentage of 100% for all these activities: patient assessment, use of assessment tools, use of necessary devices, provision of high protein diet and patient education.

Conclusion:
The current project contributed to the standardization and improvement of nurses’ practice of pressure injuries prevention in patients with mental illness and immobility hospitalized in a psychiatric ward. The development of future audits will help identify the sustainability of the implemented prevention measures.
Preparation of large biological samples for high-resolution, hierarchical, multi-modal imaging
Authors: Brunet J. , Walsh C. L. , Wagner W. L. , Bellier A. , Werlein C. , Marussi S. , Jonigk D. D. , Verleden S. E. , Ackermann M. , Lee Peter D. , Tafforeau Paul 
Published: July 2022

AbstractImaging the different scales of biological tissue is essential for understanding healthy organ behavior and pathophysiological changes. X-ray micro-tomography using both laboratory (µCT) and synchrotron sources (sCT) is a promising tool to image the 3D morphology at the macro- and micro-scale of large samples, including intact human organs. Preparation of large samples for high resolution imaging techniques remains a challenge due to limitations with current methods, such as sample shrinkage, insufficient contrast, movement of the sample and bubble formation during mounting or scanning. Here, we describe a protocol to prepare, stabilize, and image large soft-tissue samples with X-ray microtomography. We demonstrate the protocol using intact human organs and Hierarchical Phase-Contrast Tomography (HiP-CT) imaging at the European Synchrotron Radiation Facility, but the protocol is equally applicable to a range of biological samples, including complete organisms, for both laboratory and synchrotron source tomography. Our protocol enhances the contrast of the sample, while preventing sample motion during the scan, even in case of different sample orientations. Bubbles trapped during mounting and those formed during scanning (in case of synchrotron X-ray imaging) are mitigated by multiple degassing steps. The sample preparation is also compatible with magnetic resonance imaging (MRI), CT, and histological observation. We describe a protocol for sample preparation and mounting which requires 25 to 34 days for a large organ such as an intact human brain or heart. This preparation time varies depending on the composition, size, and fragility of the tissue. Use of the protocol enables scanning of intact organs with a diameter of 150 mm with a local pixel size of one micron using HiP-CT.
COVID-19 Causes Ciliary Dysfunction as Demonstrated by Human Intranasal Micro-Optical Coherence Tomography Imaging
Authors: Vijaykumar Kadambari , Leung Hui Min , Barrios Amilcar , Fernandez-Petty Courtney M. , Solomon George M. , Hathorne Heather Y. , Wade Justin D. , Monroe Kathryn , Slaten Katie Brand , Li Qian , Leal Sixto M. , Moates Derek B. , Pierce Hannah M. , Olson Kristian R. , Currier Paul , Foster Sam , Marsden Doug , Tearney Guillermo J. , Rowe Steven M. 
Published: July 2022

AbstractSevere acute respiratory syndrome coronavirus (SARS-CoV-2), causative agent of coronavirus disease 2019 (COVID-19), binds via ACE2 receptors, highly expressed in ciliated cells of the nasal epithelium. Micro-optical coherence tomography (μOCT) is a minimally invasive intranasal imaging technique that can determine cellular and functional dynamics of respiratory epithelia at 1-μm resolution, enabling real time visualization and quantification of epithelial anatomy, ciliary motion, and mucus transport. We hypothesized that respiratory epithelial cell dysfunction in COVID-19 will manifest as reduced ciliated cell function and mucociliary abnormalities, features readily visualized by μOCT. Symptomatic outpatients with SARS-CoV-2 aged ≥ 18 years were recruited within 14 days of symptom onset. Data was interpreted for subjects with COVID-19 (n=13) in comparison to healthy controls (n=8). Significant reduction in functional cilia, diminished ciliary beat frequency, and abnormal ciliary activity were evident. Other abnormalities included denuded epithelium, presence of mucus rafts, and increased inflammatory cells. Our results indicate that subjects with mild but symptomatic COVID-19 exhibit functional abnormalities of the respiratory mucosa underscoring the importance of mucociliary health in viral illness and disease transmission. Ciliary imaging enables investigation of early pathogenic mechanisms of COVID-19 and may be useful for evaluating disease progression and therapeutic response.Graphical abstract
Compression-enabled interpretability of voxelwise encoding models
Authors: Kamali Fatemeh , Suratgar Amir Abolfazl , Menhaj Mohammadbagher , Abbasi-Asl Reza 
Published: July 2022

AbstractVoxelwise encoding models based on convolutional neural networks (CNNs) have emerged as state-of-the-art predictive models of brain activity evoked by natural movies. Despite their superior predictive performance, the huge number of parameters in CNN-based models have made them difficult to interpret. Here, we investigate whether model compression can build more interpretable and more stable CNN-based voxelwise models while maintaining accuracy. We used multiple compression techniques to prune less important CNN filters and connections, a receptive field compression method to select receptive fields with optimal center and size, and principal component analysis to reduce dimensionality. We demonstrate that the model compression improves the accuracy of identifying visual stimuli in a hold-out test set. Additionally, compressed models offer a more stable interpretation of voxelwise pattern selectivity than uncompressed models. Finally, the receptive field-compressed models reveal that the optimal model-based population receptive fields become larger and more centralized along the ventral visual pathway. Overall, our findings support using model compression to build more interpretable voxelwise models.
Imputing the parental origin of the sibling’s haplotype from parental phenotypes
Authors: Liang Yanyu 
Published: July 2022

AbstractTo recruit cases for late-onset disease study is challenging since these diseases occur in elder people. Moreover, typically we have a very limited number of late-onset disease cases in Biobank data. But, on the other hand, the parental disease status may be available by questionnaire. Because of this, methods have been developed to utilize parental disease status instead Liu et al. (2017); Hujoel et al. (2020). In these approaches, the late-onset phenotype of the participant is imputed from parental statuses. And, downstream, a genome-wide association study (GWAS) is performed using the participant’s genotype and imputed phenotype. In this paper, we take another view on utilizing parental phenotypes. We treat this problem as missing parental genotype rather than missing participant’s phenotype. First, we propose an imputation scheme to infer the parental origin of the participant’s genotype from a collection of extra parental phenotypes (non-focal phenotypes) and the participant’s genotype. Second, we propose a computationally efficient approach to incorporate the imputed parental origin information into the downstream GWAS. We explore the feasibility of the proposed two-step approach on simulated and real data. And we derive the power increase of GWAS as a function of imputation quality. These results indicate that the imputation scheme needs about 100 non-focal phenotypes to achieve enough accuracy to facilitate the GWAS downstream.
Multimodal wearable sensors inform cycles of seizure risk
Authors: Gregg Nicholas M. , Pal Attia Tal , Nasseri Mona , Joseph Boney , Karoly Philippa J. , Cui Jie , Stirling Rachel E. , Viana Pedro F. , Richner Thomas J. , Nurse Ewan S. , Schulze-Bonhage Andreas , Cook Mark J. , Worrell Gregory A. , Richardson Mark P. , Freestone Dean R. , Brinkmann Benjamin H. 
Published: July 2022

AbstractObjectiveSeizure unpredictability is a major source of disability for people with epilepsy. Recent work using chronic brain recordings has established that for many individuals with epilepsy seizure risk is not random, but corresponds to circadian and multiday (multidien) cycles in brain excitability. Here, we aimed to evaluate whether multimodal wearable device recordings can characterize cycles of seizure risk, and compare wearables performance with concurrent chronic brain recordings.MethodsFourteen subjects underwent long-term ambulatory monitoring with a multimodal wrist worn device (measuring heart rate, heart rate variability, accelerometry, tonic and phasic electrodermal activity, temperature) and an implanted responsive neurostimulation system (measuring interictal epileptiform abnormalities (IEA) and electrographic seizures). Wavelet time-frequency analyses identified circadian and multiday cycles in wearable and brain recordings. Circular statistics assessed seizure phase locking to cycles in physiology.ResultsTen subjects met inclusion criteria. The mean recording duration was 232 days. Seven subjects had reliable electrographic seizure detections (mean 76 seizures). Seizure phase locking to multiday cycles occurred in six (IEA), five (temperature), four (heart rate, phasic electrodermal activity), and three (accelerometry, heart rate variability, tonic electrodermal activity) subjects. Seizure phase locking to residual HR multiday cycles (HR after regression of correlated physical activity (ACC)) increased to six subjects.InterpretationLong timescale cyclical changes in wearable recordings are common in epilepsy, and seizures occur at preferred phases of these cycles for many individuals. Broadly accessible wearable technology can provide new insights into the chronobiology of epilepsy with implications for seizure forecasting.
Individual tree-based vs pixel-based approaches to mapping forest functional traits and diversity by remote sensing
Authors: Zheng Zhaoju , Zeng Yuan , Schuman Meredith C. , Jiang Hailan , Schmid Bernhard , Schaepman Michael E. , Morsdorf Felix 
Published: July 2022

AbstractTrait-based approaches, focusing on the functional characteristics of vascular plants in a community, have been increasingly used in plant ecology and biodiversity research. Compared with traditional field survey (which typically samples individual trees), remote sensing enables quantifying functional traits over large contiguous areas, but assigning trait values to biological units such as species and individuals is difficult with pixel-based approaches. We used a subtropical forest landscape in China to compare an approach based on LiDAR-delineated individual tree crowns (ITCs) with a pixel-based approach for assessing functional traits from remote sensing data. We compared trait distributions, trait–trait relationships and functional diversity metrics obtained by the two approaches at changing grain and extent. We found that morphological traits derived from airborne laser scanning showed more differences between ITC- and pixel-based approaches than physiological traits estimated by imaging spectroscopy data. Pixel sizes approximating average tree crowns yielded similar results as ITCs, but 95th quantile height and foliage height diversity tended to be overestimated and leaf area index underestimated relative to ITC-based values. With increasing pixel size, the differences to ITC- based trait values became larger and less trait variance was captured, indicating information loss. The consistency of ITC- and pixel-based functional richness measures also decreased with increasing pixel grain, and changed with the observed extent for functional diversity monitoring. We conclude that whereas ITC-based approaches in principle allow partitioning of variation between individuals, genotypes and species, at high resolution, pixel-based approaches come close to this and can be suitable for assessing ecosystem-scale trait variation by weighting individuals and species according to coverage.
Reliability metrics of outcome measures during the single and double leg drop jump tests
Authors: Celik Huseyin , Yildirim Ahmet , Unver Evrim , Mavili Caner , Yilmaz Ekrem , Ozturk Ferhat , Arpinar-Avsar Pinar , Cinemre Sukru Alpan 
Published: July 2022

AbstractAlthough a number of previous studies have studied reliability metrics of outcome measures during single and double leg drop jump tests, none of them presented detailed reliability information for both tests with a group of collegiate athletes of both genders. The aim of this study was therefore to assess the reliability of outcome measures during the single and double leg drop jump tests with proper reliability metrics. Seventeen handball players (11 male and 6 female) participated in the experiments. Each player performed three double leg and three single drop jumps from a 30 cm height box onto a portable force plate in two sessions a week apart. Sixteen outcome measures, including jump height (JH), ground contact time (GCT), reactive strength index (RSI), were calculated. Four groups of reliability metrics like absolute agreement and consistency intraclass correlation coefficients (inter-day and intra-day), standard error of measurement, coefficient of variation, and minimal metrically detectable change were estimated for reliability assessment. The outcome measures as RSI and its individual components JH and GCT together with normalized vertical stiffness (Kvert) yielded high inter-day and intra-day intraclass correlation coefficients and low standard error of measurement and coefficient of variation levels for the double leg drop jump test. The more challenging single leg drop jump test could also be considered reproducible with some other highly reliable outcome measure set by keeping JH, GCT, and normalized Kvert and replacing vertical jump impulse with RSI. The results of the current study therefore suggested the drop jump tests could be deemed reliable to be used for short-term and long-term monitoring needs for a group of collegiate athletes of both genders.
Genetic drift shapes the evolution of a highly dynamic metapopulation
Authors: Angst Pascal , Ameline Camille , Ebert Dieter , Fields Peter D. 
Published: July 2022

AbstractThe dynamics of extinction and (re)colonization in habitat patches are common features of metapopulations, causing them to evolve differently than large, stable populations. The propagule model, which assumes genetic bottlenecks during colonization, posits that newly founded subpopulations have low genetic diversity and are genetically highly differentiated from each other. Immigration may then increase diversity and decrease differentiation between subpopulations. Thus, older and/or less isolated subpopulations are expected to have higher genetic diversity and less genetic differentiation. We tested this theory using whole-genome pool-sequencing to characterize nucleotide diversity and differentiation in 60 subpopulations of a natural metapopulation of the cyclical parthenogenDaphnia magna. For comparison, we characterized diversity in a single, large, stableD. magnapopulation. We found reduced (synonymous) genomic diversity, a proxy for effective population size, weak purifying selection, and low rates of adaptive evolution in the metapopulation compared to the large, stable population. These differences suggest that genetic bottlenecks during colonization reduce effective population sizes, which leads to strong genetic drift and reduced selection efficacy in the metapopulation. Consistent with the propagule model, we found lower diversity and increased differentiation in more isolated, younger subpopulations. Our study sheds light on the genomic consequences of extinction–(re)colonization dynamics to an unprecedented degree, giving strong support for the propagule model. We demonstrate that the metapopulation evolves differently from a large, stable population and that the evolutionary process is largely driven by genetic drift.
A scalable assay for chemical preference of small freshwater fish
Authors: Gallois Benjamin , Pontani Léa-lætitia , Debrégeas Georges , Candelier Raphaël 
Published: July 2022

ABSTRACTSensing the chemical world is of primary importance for aquatic organisms, and small freshwater fish are increasingly used in toxicology, ethology, and neuroscience by virtue of their ease of manipulation, tissue imaging amenability, and genetic tractability. However, precise behavioral analyses are generally challenging to perform due to the lack of knowledge of what chemical the fish are exposed to at any given moment. Here we developed a behavioral assay and a specific infrared dye to probe the preference of young zebrafish for virtually any compound. We found that the innate aversion of zebrafish to citric acid is not mediated by modulation of the swim but rather by immediate avoidance reactions when the product is sensed and that the preference of juvenile zebrafish for ATP changes from repulsion to attraction during successive exposures. We propose an information-based behavioral model for which an exploration index emerges as a relevant behavioral descriptor, complementary to the standard preference index. Our setup features a high versatility in protocols and is automatic and scalable, which paves the way for high-throughput preference compound screening at different ages.
Accurate delineation of individual tree crowns in tropical forests from aerial RGB imagery using Mask R-CNN
Authors: Ball James G. C. , Hickman Sebastian H. M. , Jackson Tobias D. , Koay Xian Jing , Hirst James , Jay William , Archer Matthew , Aubry-Kientz Mélaine , Vincent Grégoire , Coomes David A. 
Published: July 2022

Tropical forests are a major component of the global carbon cycle and home to two-thirds of terrestrial species. Upper-canopy trees store the majority of forest carbon and can be vulnerable to drought events and storms. Monitoring their growth and mortality is essential to understanding forest resilience to climate change, but in the context of forest carbon storage, large trees are underrepresented in traditional field surveys, so estimates are poorly constrained. Aerial photographs provide spectral and textural information to discriminate between tree crowns in diverse, complex tropical canopies, potentially opening the door to landscape monitoring of large trees. Here we describe a new deep convolutional neural network method,Detectree2, which builds on the Mask R-CNN computer vision framework to recognise the irregular edges of individual tree crowns from airborne RGB imagery. We trained and evaluated this model with 3,797 manually delineated tree crowns at three sites in Malaysian Borneo and one site in French Guiana. As an example application, we combined the delineations with repeat lidar surveys (taken between 3 and 6 years apart) of the four sites to estimate the growth and mortality of upper-canopy trees.Detectree2delineated 65,000 upper-canopy trees across 14 km2of aerial images. The skill of the automatic method in delineating unseen test trees was good (F1score = 0.64) and for the tallest category of trees was excellent (F1score = 0.74). As predicted from previous field studies, we found that growth rate declined with tree height and tall trees had higher mortality rates than intermediate-size trees. Our approach demonstrates that deep learning methods can automatically segment trees in widely accessible RGB imagery. This tool (provided as an open-source Python package) has many potential applications in forest ecology and conservation, from estimating carbon stocks to monitoring forest phenology and restoration.Python package available to install athttps://github.com/PatBall1/Detectree2
Frameshifts may carry oncogenic potential beyond loss of function and categorize genes’ role in tumor development
Authors: Kirov Stefan 
Published: July 2022

AbstractIn this work I present evidence that frameshift mutations represent substantial oncogenic potential across multiple tumor types and may change our understanding of the function of some genes with well established tumor suppressor. I analyzed data deposited in Cbio portal and show that frameshifts, even when they result in the removal of a substantial part of a protein have the potential to create recurring large domains with unknown function. Based on this analysis I propose a novel categorization of genes according to their association with cancer that is more reflective of a complex nature that goes beyond the simple division to tumor suppressors and oncogenes.
Measurement of Cervical Neuronal Activity during Stress Challenge Using Novel Flexible Adhesive Surface Electrodes
Authors: Bu Yifeng , Kurniawa Jonas F. , Prince Jacob , Nguyen Andrew K. L. , Ho Brandon , Sit Nathan L. J. , Pham Timothy , Wu Vincent M. , Tjhia Boris , Shin Andrew J. , Wu Tsung-Chin , Tu Xin M. , Rao Ramesh , Coleman Todd P. , Lerman Imanuel 
Published: July 2022

AbstractThis study introduces a flexible, adhesive-integrated electrode array that was developed to enable non-invasive monitoring of cervical nerve activity. The device uses silver-silver chloride as the electrode material of choice and combines it with a novel electrode array consisting of a customized biopotential data acquisition unit and integrated graphical user interface (GUI) for visualization of real-time monitoring. Preliminary testing demonstrated this novel electrode design can achieve a high signal to noise ratio during cervical neural recordings. To demonstrate the capability of the surface electrodes to detect changes in cervical neuronal activity, the cold-pressor test (CPT) and a timed respiratory challenge were employed as stressors to the autonomic nervous system. This sensor system recording, a new novel technique, was termed Cervical Electroneurography (CEN). By applying a custom spike sorting algorithm to the novel electrode measurements, neural activity was classified in two ways: 1) pre-to-post CPT, and 2) during a timed respiratory challenge. Unique to this work: 1) rostral to caudal channel position-specific (cephalad to caudal) firing patterns and 2) cross challenge biotype-specific change in average CEN firing, were observed with both CPT and the timed respiratory challenge. Future work is planned to develop an ambulatory CEN recording device that could provide immediate notification of autonomic nervous system activity changes that might indicate autonomic dysregulation in healthy subjects and clinical disease states.