Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Risk Factor Profiles in the Prediction of General and Pain-Specific Functional Limitations 12 Months after Major Pediatric Surgery

Pediatric chronic post-surgical pain is a surgical complication associated with various levels of functional limitation. Two commonly used measures of functional limitations in youth are the Functional Disability Inventory (FDI) and the PROMIS Pediatric Pain Interference Scale (PPIS), where the former is general, and the latter, pain specific. The aim of the present study was to prospectively compare pre-surgical youth and parent risk factors for youth functional limitations, assessed by the FDI and PPIS, 12 months after major pediatric surgery. Risk factors for the FDI and PPIS were compared in 79 dyads consisting of youth (58% female, M = 14.56 years; SD = 2.31) undergoing major surgery and one of their parents. The FDI and PPIS were highly correlated prior to surgery (r = 0.698, p < 0.001) and even more so 12 months after surgery (r = 0.807, p < 0.001). Parent pre-surgical anxiety sensitivity and youth pre-surgical functional disability significantly predicted 12-month FDI (F(6,56) = 4.443, p = 0.001, Adjusted R2 = 0.25), whereas parent pre-surgical anxiety sensitivity, trait anxiety, pain anxiety, as well as youth pain-related anxiety and worry significantly predicted 12-month PPIS (F(6,45) = 4.104, p = 0.002, Adjusted R2 = 0.27). Risk factors for 12-month general and pain-specific functional limitations differ by dyad member and type. Functional limitations in youth after surgery are predicted by youth and parent factors, however the risk factors differ between the FDI and the PPIS.
Global research productivity and publication trends in vesicoureteral reflux: a bibliometric analysis.

BACKGROUND To make a holistic, comprehensive analysis of scientific publications on the subject of vesicoureteral reflux (VUR) between 1980 and 2019 using bibliometric methods, and by determining global research trends, to establish an important resource for future studies. METHODS All the scientific documents were accessed which had the key word "vesicoureteral reflux" in the "Title" section in the Web of Science (WoS) database between 1980 and 2019. Using bibliometric methods, articles related to VUR (access date:20.08.2020) were analyzed. VOS viewer software was used to visualize the bibliometric network. RESULTS A total of 2549 publications related to VUR were identified in literature, of which 1387 were articles. There was observed to be a generally increasing trend in the number of articles. According to the results of the regression analysis, the number of articles is expected to increase to 54 in 2020, and to 63 by 2029. The 5 most productive countries were seen to be the USA, Turkey, Japan, Italy and Germany. The 5 journals contributing most to the literature were the Journal of Urology (397), Urology (86), Journal of Pediatric Urology (75), Pediatric Nephrology (64) and European Urology (37). CONCLUSIONS The number of publications on the subject of VUR is expected to continue increasing in the next 10 years. This study, which has provided a detailed and comprehensive analysis of articles related to VUR, can be considered a useful guide for future studies by physicians and researchers.
Guillain Barre Syndrome as a Complication of COVID-19: A Systematic Review

ABSTRACT: Background: In January 2020, the first case of Guillain Barre syndrome (GBS) due to COVID-19 was documented in China. GBS is known to be postinfectious following several types of infections. Although causality can only be proven through large epidemiological studies, we intended to study this association by a thorough review of the literature. Methods: We searched PubMed, EMBASE, and Google scholar and included all papers with English or Spanish full text and original data of patients with GBS and recent COVID infection. Variables of interest were demographics, diagnostic investigations, and the latency between arboviral and neurological symptoms. Further variables were pooled to identify GBS clinical and electrophysiological variants, used treatments, and outcomes. The certainty of GBS diagnosis was verified using Brighton criteria. Results: We identified a total of 109 GBS cases. Ninety-nine cases had confirmed COVID-19 infection with an average age of 56.07 years. The average latency period between the arboviral symptoms and neurologic manifestations for confirmed COVID-19 cases was 12.2 d. The predominant GBS clinical and electromyography variants were the classical sensorimotor GBS and acute demyelinating polyneuropathy respectively. Forty cases required intensive care, 33 cases required mechanical ventilation, and 6 cases were complicated by death. Conclusions: Studies on COVID-19-related GBS commonly reported sensorimotor demyelinating GBS with frequent facial palsy. The time between the onset of infectious and neurological symptoms suggests a postinfectious mechanism. Early diagnosis of GBS in COVID-19 patients is important as it might be associated with a severe disease course requiring intensive care and mechanical ventilation.
Automated detection of glaucoma with interpretable machine learning using clinical data and multi-modal retinal images

Glaucoma, the leading cause of irreversible blindness worldwide, is a disease that damages the optic nerve. Current machine learning (ML) approaches for glaucoma detection rely on features such as retinal thickness maps; however, the high rate of segmentation errors when creating these maps increase the likelihood of faulty diagnoses. This paper proposes a new, comprehensive, and more accurate ML-based approach for population-level glaucoma screening. Our contributions include: (1) a multi-modal model built upon a large data set that includes demographic, systemic and ocular data as well as raw image data taken from color fundus photos (CFPs) and macular Optical Coherence Tomography (OCT) scans, (2) model interpretation to identify and explain data features that lead to accurate model performance, and (3) model validation via comparison of model output with clinician interpretation of CFPs. We also validated the model on a cohort that was not diagnosed with glaucoma at the time of imaging but eventually received a glaucoma diagnosis. Results show that our model is highly accurate (AUC 0.97) and interpretable. It validated biological features known to be related to the disease, such as age, intraocular pressure and optic disc morphology. Our model also points to previously unknown or disputed features, such as pulmonary capacity and retinal outer layers.
TEMPORAL EVOLUTION AND PREDICTORS OF SUBJECTIVE COGNITIVE COMPLAINTS UP TO 4 YEARS AFTER STROKE

Objective To examine the temporal evolution of subjective cognitive complaints in the long-term after stroke, and to identify predictors of long-term subjective cognitive complaints. Methods Prospective cohort study including 395 stroke patients. Subjective cognitive complaints were assessed at 2 months, 6 months and 4 years post-stroke, using the Checklist for Cognitive and Emotional consequences following stroke (CLCE-24). The temporal evolution of subjective cognitive complaints was described using multilevel growth modelling. Associations between CLCE-24 cognition score at 4 years post-stroke and baseline characteristics, depression, anxiety, cognitive test performance, and adaptive and maladaptive psychological factors were examined. Significant predictors were entered in a multivariate multilevel model. Results A significant increase in subjective cognitive complaints from 2 months up to 4 years (mean 3.7 years, standard deviation (SD) 0.6 years) post-stroke was observed (p≤0.001). Two months post-stroke, 76% of patients reported at least one cognitive complaint, 72% at 6 months, and 89% at 4 years post-stroke. A higher level of subjective cognitive complaints at 2 months and lower scores on adaptive and maladaptive psychological factors were significant independent predictors of a higher level of subjective cognitive complaints at 4 years post-stroke. Conclusion Post-stroke subjective cognitive complaints increase over time and can be predicted by the extent of subjective cognitive complaints and the presence of adaptive and maladaptive psychological factors in the early phases after stroke. LAY ABSTRACT Many people suffer a stroke in the brain leading to consequences in different areas of functioning. Complaints in the domain of thinking (memory, attention, planning and organization) are frequent post-stroke. This study investigated the occurrence and type of complaints experienced in the first years after a stroke. The study found that these complaints increase over time. Longterm complaints are found in those people who already have problems early after stroke.
A Systematic Review of Urban Navigation Systems for Visually Impaired People

Blind and Visually impaired people (BVIP) face a range of practical difficulties when undertaking outdoor journeys as pedestrians. Over the past decade, a variety of assistive devices have been researched and developed to help BVIP navigate more safely and independently. In addition, research in overlapping domains are addressing the problem of automatic environment interpretation using computer vision and machine learning, particularly deep learning, approaches. Our aim in this article is to present a comprehensive review of research directly in, or relevant to, assistive outdoor navigation for BVIP. We breakdown the navigation area into a series of navigation phases and tasks. We then use this structure for our systematic review of research, analysing articles, methods, datasets and current limitations by task. We also provide an overview of commercial and non-commercial navigation applications targeted at BVIP. Our review contributes to the body of knowledge by providing a comprehensive, structured analysis of work in the domain, including the state of the art, and guidance on future directions. It will support both researchers and other stakeholders in the domain to establish an informed view of research progress.
Skin Lesion Segmentation and Multiclass Classification Using Deep Learning Features and Improved Moth Flame Optimization

Manual diagnosis of skin cancer is time-consuming and expensive; therefore, it is essential to develop automated diagnostics methods with the ability to classify multiclass skin lesions with greater accuracy. We propose a fully automated approach for multiclass skin lesion segmentation and classification by using the most discriminant deep features. First, the input images are initially enhanced using local color-controlled histogram intensity values (LCcHIV). Next, saliency is estimated using a novel Deep Saliency Segmentation method, which uses a custom convolutional neural network (CNN) of ten layers. The generated heat map is converted into a binary image using a thresholding function. Next, the segmented color lesion images are used for feature extraction by a deep pre-trained CNN model. To avoid the curse of dimensionality, we implement an improved moth flame optimization (IMFO) algorithm to select the most discriminant features. The resultant features are fused using a multiset maximum correlation analysis (MMCA) and classified using the Kernel Extreme Learning Machine (KELM) classifier. The segmentation performance of the proposed methodology is analyzed on ISBI 2016, ISBI 2017, ISIC 2018, and PH2 datasets, achieving an accuracy of 95.38%, 95.79%, 92.69%, and 98.70%, respectively. The classification performance is evaluated on the HAM10000 dataset and achieved an accuracy of 90.67%. To prove the effectiveness of the proposed methods, we present a comparison with the state-of-the-art techniques.
Tremellomycetes Yeasts in Kernel Ecological Niche: Early Indicators of Enhanced Competitiveness of Endophytic and Mycoparasitic Symbionts against Wheat Pathobiota

Tremellomycetes rDNA sequences previously detected in wheat kernels by MiSeq were not reliably assigned to a genus or clade. From comparisons of ribosomal internal transcribed spacer region (ITS) and subsequent phylogenetic analyses, the following three basidiomycetous yeasts were resolved and identified: Vishniacozyma victoriae, V. tephrensis, and an undescribed Vishniacozyma rDNA variant. The Vishniacozyma variant’s clade is evolutionarily close to, but phylogenetically distinct from, the V. carnescens clade. These three yeasts were discovered in wheat kernel samples from the Canadian prairies. Variations in relative Vishniacozyma species abundances coincided with altered wheat kernel weight, as well as host resistance to chemibiotrophic Tilletia (Common bunt—CB) and necrotrophic Fusarium (Fusarium head blight—FHB) pathogens. Wheat kernel weight was influenced by the coexistence of Vishniacozyma with endophytic plant growth-promoting and mycoparasitic biocontrol fungi that were acquired by plants. Kernels were coated with beneficial Penicillium endophyte and Sphaerodes mycoparasite, each of which had different influences on the wild yeast population. Its integral role in the kernel microbiome renders Vishniacozyma a measurable indicator of the microbiome–plant interaction. The ability of NGS technology to detect specific endophytic DNA variants and early changes in dynamics among symbionts within the kernel ecological niche enables the prediction of crop disease emergence, suggesting that advanced microbiological testing may be a potentially useful tool for both phytoprotection and more efficient wheat breeding programs.
Single‐Molecule FRET of Membrane Transport Proteins

Uncovering the structure and function of biomolecules is a fundamental goal in structural biology. Membrane‐embedded transport proteins are ubiquitous in all kingdoms of life. Despite structural flexibility, their mechanisms are typically studied by ensemble biochemical methods or by static high‐resolution structures, which complicate a detailed understanding of their dynamics. Here, we review the recent progress of single molecule Förster Resonance Energy Transfer (smFRET) in determining mechanisms and timescales of substrate transport across membranes. These studies do not only demonstrate the versatility and suitability of state‐of‐the‐art smFRET tools for studying membrane transport proteins but they also highlight the importance of membrane mimicking environments in preserving the function of these proteins. The current achievements advance our understanding of transport mechanisms and have the potential to facilitate future progress in drug design.
High Rates of Liver Cirrhosis and Hepatocellular Carcinoma in Chronic Hepatitis B Patients with Metabolic and Cardiovascular Comorbidities

Background: The prevalence of metabolic and cardiovascular diseases is rising worldwide. However, little is known about the impact of such disorders on hepatic disease progression in chronic hepatitis B (CHB) during the era of potent nucleo(s)tide analogues (NAs). Methods: We retrospectively analyzed a single-center cohort of 602 CHB patients, comparing the frequency of liver cirrhosis at baseline and incidences of liver-related events during follow-up (hepatocellular carcinoma, liver transplantation and liver-related death) between CHB patients with a history of diabetes, obesity, hypertension or coronary heart disease (CHD). Results: Rates of cirrhosis at baseline and liver-related events during follow-up (median follow-up time: 2.51 years; NA-treated: 37%) were substantially higher in CHB patients with diabetes (11/23; 3/23), obesity (6/13; 2/13), CHD (7/11; 2/11) or hypertension (15/43; 4/43) compared to CHB patients without the indicated comorbidities (26/509; 6/509). Multivariate analysis identified diabetes as the most significant predictor for cirrhosis (p = 0.0105), while comorbidities did not correlate with liver-related events in pre-existing cirrhosis. Conclusion: The combination of metabolic diseases and CHB is associated with substantially increased rates of liver cirrhosis and secondary liver-related events compared to CHB alone, indicating that hepatitis B patients with metabolic comorbidities warrant particular attention in disease surveillance and evaluation of treatment indication.
Seaweed Polysaccharide Based Products and Materials: An Assessment on Their Production from a Sustainability Point of View

Among the various natural polymers, polysaccharides are one of the oldest biopolymers present on the Earth. They play a very crucial role in the survival of both animals and plants. Due to the presence of hydroxyl functional groups in most of the polysaccharides, it is easy to prepare their chemical derivatives. Several polysaccharide derivatives are widely used in a number of industrial applications. The polysaccharides such as cellulose, starch, chitosan, etc., have several applications but due to some distinguished characteristic properties, seaweed polysaccharides are preferred in a number of applications. This review covers published literature on the seaweed polysaccharides, their origin, and extraction from seaweeds, application, and chemical modification. Derivatization of the polysaccharides to impart new functionalities by chemical modification such as esterification, amidation, amination, C-N bond formation, sulphation, acetylation, phosphorylation, and graft copolymerization is discussed. The suitability of extraction of seaweed polysaccharides such as agar, carrageenan, and alginate using ionic solvent systems from a sustainability point of view and future prospects for efficient extraction and functionalization of seaweed polysaccharides is also included in this review article.
Sorting Permutations by Intergenic Operations

Genome Rearrangements are events that affect large stretches of genomes during evolution. Many mathematical models have been used to estimate the evolutionary distance between two genomes based on genome rearrangements. However, most of them focused on the (order of the) genes of a genome, disregarding other important elements in it. Recently, researchers have shown that considering regions between each pair of genes, called intergenic regions, can enhance distance estimation in realistic data. Two of the most studied genome rearrangements are the reversal, which inverts a sequence of genes, and the transposition, which occurs when two adjacent gene sequences swap their positions inside the genome. In this work, we study the transposition distance between two genomes, but we also consider intergenic regions, a problem we name Sorting by Intergenic Transpositions. We show that this problem is NP-hard and propose two approximation algorithms, with factors 3.5 and 2.5, considering two distinct definitions for the problem. We also investigate the signed reversal and transposition distance between two genomes considering their intergenic regions. This second problem is called Sorting by Signed Intergenic Reversals and Intergenic Transpositions. We show that this problem is NP-hard and develop two approximation algorithms, with factors 3 and 2.5. We check how these algorithms behave when assigning weights for genome rearrangements. Finally, we implemented all these algorithms and tested them on real and simulated data.
Psychometric properties of the Jefferson Empathy Scale in four nursing student faculties.

OBJECTIVE To evaluate the psychometric properties of the Jefferson Medical Empathy Scale, Spanish version (JSE-S), its factorial structure, reliability, and the presence of invariance between genders in the behavior of empathy levels among Chilean nursing students. METHOD Instrumental research design. The JSE-S was applied to 1,320 nursing students. A confirmatory factor analysis was used. An invariance study between genders was carried out. Descriptive statistics were estimated. Between genders, Student's T distribution was applied alongside a homoscedasticity analysis. The level of significance was α ≤ 0.05. RESULTS The confirmatory factor analysis determined the existence of three dimensions in the matrix. The statistical results of the invariance tests were significant, and allowed comparison between genders. Differences were found between mean empathy values, as well as in some of its dimensions between genders. CONCLUSION The factor structure of empathy data and its dimensions is in correspondence with the underlying three-dimensional model. There are differences in empathy levels and their dimensions between genders, with the exception of the compassionate care dimension, which was distributed similarly. Women were more empathetic than men.
Trips-Viz: an environment for the analysis of public and user-generated ribosome profiling data

Abstract Trips-Viz (https://trips.ucc.ie/) is an interactive platform for the analysis and visualization of ribosome profiling (Ribo-Seq) and shotgun RNA sequencing (RNA-seq) data. This includes publicly available and user generated data, hence Trips-Viz can be classified as a database and as a server. As a database it provides access to many processed Ribo-Seq and RNA-seq data aligned to reference transcriptomes which has been expanded considerably since its inception. Here, we focus on the server functionality of Trips-viz which also has been greatly improved. Trips-viz now enables visualisation of proteomics data from a large number of processed mass spectrometry datasets. It can be used to support translation inferred from Ribo-Seq data. Users are now able to upload a custom reference transcriptome as well as data types other than Ribo-Seq/RNA-Seq. Incorporating custom data has been streamlined with RiboGalaxy (https://ribogalaxy.ucc.ie/) integration. The other new functionality is the rapid detection of translated open reading frames (ORFs) through a simple easy to use interface. The analysis of differential expression has been also improved via integration of DESeq2 and Anota2seq in addition to a number of other improvements of existing Trips-viz features.
Pharmacokinetics and Pharmacodynamics of Cefepime in Adults with Hematological Malignancies and Febrile Neutropenia after Chemotherapy

Patients with chemotherapy-induced febrile neutropenia (CIFN) may have changes in the pharmacokinetics (PK) compared to patients without malignancies or neutropenia. Those changes in antibiotic PK could lead to negative outcomes for patients if the therapy is not adequately adjusted to this. In this, open-label, non-randomized, prospective, observational, and descriptive study, a PK model of cefepime was developed for patients with hematological neoplasms and post-chemotherapy febrile neutropenia. This study was conducted at a cancer referral center, and study participants were receiving 2 g IV doses of cefepime every 8 h as 30-min infusions. Cefepime PK was well described by a two compartment model with a clearance dependent on a serum creatinine level. Using Monte Carlo simulations, it was shown that continuous infusions of 6g q24h could have a good achievement of PK/PD targets for MIC levels below the resistance cut-off point of Enterobacteriaceae. According to the simulations, it is unnecessary to increase the daily dose of cefepime (above 6 g daily) to increase the probability of target attainment (PTA). Cumulative fraction of response (CFR) using interment dosing was suboptimal for empirical therapy regimens against K. pneumoniae and P. aeruginosa, and continuous infusions could be used in this setting to maximize exposure. Patients with high serum creatinine levels were more likely to achieve predefined PK/PD targets than patients with low levels.