bluuebunny/crossref_metadata_2025_split huggingface dataset:
Home Auditory Environments of Children With Cochlear Implants and Children With Normal Hearing
Authors: Wang Yuanyuan , Cooke Molly , Reed Jessa , Dilley Laura , Houston Derek M. 
Published: September 2021

Objectives:
Early home auditory environment plays an important role in children’s spoken language development and overall well-being. This study explored differences in the home auditory environment experienced by children with cochlear implants (CIs) relative to children with normal hearing (NH).

Design:
Measures of the child’s home auditory environment, including adult word count (AWC), conversational turns (CTs), child vocalizations (CVs), television and media (TVN), overlapping sound (OLN), and noise (NON), were gathered using the Language Environment Analysis System. The study included 16 children with CIs (M = 22.06 mo) and 25 children with NH (M = 18.71 mo). Families contributed 1 to 3 daylong recordings quarterly over the course of approximately 1 year. Additional parent and infant characteristics including maternal education, amount of residual hearing, and age at activation were also collected.

Results:
The results showed that whereas CTs and CVs increased with child age for children with NH, they did not change as a function of age for children with CIs; NON was significantly higher for the NH group. No significant group differences were found for the measures of AWC, TVN, or OLN. Moreover, measures of CTs, CVs, TVN, and NON from children with CIs were associated with demographic and child factors, including maternal education, age at CI activation, and amount of residual hearing.

Conclusions:
These findings suggest that there are similarities and differences in the home auditory environment experienced by children with CIs and children with NH. These findings have implications for early intervention programs to promote spoken language development for children with CIs.
A New Trick for an Old Dog: L-Epinephrine Delivered Continuously in the Vapor Phase
Authors: Winter Meredith C. , Newth Christopher J. L. , Castro Cristina , Hotz Justin C. , Ross Patrick A. 
Published: September 2021

OBJECTIVES:
Inhaled L-epinephrine is a known treatment of severe croup and postextubation upper airway obstruction. L-epinephrine can be delivered continuously in the vapor phase, but the indications, safety, and efficacy of this novel practice have yet to be evaluated. Theoretical risks are tachycardia, hypertension, and dysrhythmias. The study objective was to describe patient characteristics and vital sign changes related to continuous vaporized L-epinephrine use in critically ill children with the hypothesis that it can be practically and safely administered to children with subglottic edema and lower airway obstruction.

DESIGN:
Retrospective cohort study.

SETTING:
PICU and cardiothoracic ICU in a tertiary academic children’s hospital.

PATIENTS:
Patients age 0–21 years treated with continuous vaporized L-epinephrine from 2013 to 2019.

INTERVENTIONS:
None.

MEASUREMENTS AND MAIN RESULTS:
Continuous vaporized L-epinephrine was administered 140 times to 129 subjects via a high-flow nasal oxygen device. The median age was 10.6 months (1.3; interquartile range, 4.8–17.1 mo). The most common indications were lower respiratory tract obstruction (45%), postextubation subglottic edema (31%), and croup (16%). Eighty-eight percent had no escalation of respiratory support within 24 hours of initiation of continuous vaporized L-epinephrine, 5% progressed to require endotracheal intubation, and 3% were reintubated within 24 hours of initiation of continuous vaporized L-epinephrine following an extubation attempt. After starting continuous vaporized L-epinephrine, 85% of subjects had a decrease in heart rate and 80% had a decrease in respiratory rate. Six subjects had an increase in heart rate, and eight had an increase in blood pressure of more than 20% from baseline. These subjects did not receive interventions specific to these vital sign changes, including discontinuation of continuous vaporized L-epinephrine.

CONCLUSIONS:
Continuous vaporized L-epinephrine was safely administered to critically ill children with most subjects demonstrating a decrease in heart rate, blood pressure, and respiratory rate.
The Effectiveness of High-Flow Nasal Cannula in Coronavirus Disease 2019 Pneumonia: A Retrospective Cohort Study
Authors: Burnim Michael S. , Wang Kunbo , Checkley William , Nolley Eric P. , Xu Yanxun , Garibaldi Brian T. 
Published: September 2021

OBJECTIVES:
High-flow nasal cannula is widely used in acute hypoxemic respiratory failure due to coronavirus disease 2019, yet data regarding its effectiveness is lacking. More evidence is needed to guide patient selection, timing of high-flow nasal cannula initiation, and resource allocation. We aimed to assess time to discharge and time to death in severe coronavirus disease 2019 in patients treated with high-flow nasal cannula compared with matched controls. We also evaluated the ability of the respiratory rate-oxygenation ratio to predict progression to invasive mechanical ventilation.

DESIGN:
Time-dependent propensity score matching was used to create pairs of individuals who were then analyzed in a Cox proportional-hazards regression model to estimate high-flow nasal cannula’s effect on time to discharge and time to death. A secondary analysis excluded high-flow nasal cannula patients intubated within 6 hours of admission. A Cox proportional-hazards regression model was used to assess risk of invasive mechanical ventilation among high-flow nasal cannula patients stratified by respiratory rate-oxygenation.

SETTING:
The five hospitals of the Johns Hopkins Health System.

PATIENTS:
All patients who were admitted with a laboratory-confirmed diagnosis of coronavirus disease 2019 were eligible for inclusion.

INTERVENTIONS:
None.

MEASUREMENTS AND MAIN RESULTS:
High-flow nasal cannula was associated with longer median time to discharge: 10.6 days (interquartile range, 7.1–15.8 d) versus 7.8 days (interquartile range, 4.9–12.1 d). Respiratory rate-oxygenation index performed poorly in predicting ventilation or death. In the primary analysis, there was no significant association between high-flow nasal cannula and hazard of death (adjusted hazard ratio, 0.79; 95% CI, 0.57–1.09). Excluding patients intubated within 6 hours of admission, high-flow nasal cannula was associated with reduced hazard of death (adjusted hazard ratio, 0.67; 95% CI, 0.45–0.99).

CONCLUSIONS:
Among unselected patients with severe coronavirus disease 2019 pneumonia, high-flow nasal cannula was not associated with a statistically significant reduction in hazard of death. However, in patients not mechanically ventilated within 6 hours of admission, high-flow nasal cannula was associated with a significantly reduced hazard of death.
Association Between Urine Output and Mortality in Critically Ill Patients: A Machine Learning Approach
Authors: Heffernan Aaron J. , Judge Stephanie , Petrie Stephen M. , Godahewa Rakshitha , Bergmeir Christoph , Pilcher David , Nanayakkara Shane 
Published: September 2021

OBJECTIVES:
Current definitions of acute kidney injury use a urine output threshold of less than 0.5 mL/kg/hr, which have not been validated in the modern era. We aimed to determine the prognostic importance of urine output within the first 24 hours of admission to the ICU and to evaluate for variance between different admission diagnoses.

DESIGN:
Retrospective cohort study.

SETTING:
One-hundred eighty-three ICUs throughout Australia and New Zealand from 2006 to 2016.

PATIENTS:
Patients greater than or equal to 16 years old who were admitted with curative intent who did not regularly receive dialysis. ICU readmissions during the same hospital admission and patients transferred from an external ICU were excluded.

MEASUREMENTS AND MAIN RESULTS:
One hundred and sixty-one thousand nine hundred forty patients were included with a mean urine output of 1.05 mL/kg/hr and an overall in-hospital mortality of 7.8%. A urine output less than 0.47 mL/kg/hr was associated with increased unadjusted in-hospital mortality, which varied with admission diagnosis. A machine learning model (extreme gradient boosting) was trained to predict in-hospital mortality and examine interactions between urine output and survival. Low urine output was most strongly associated with mortality in postoperative cardiovascular patients, nonoperative gastrointestinal admissions, nonoperative renal/genitourinary admissions, and patients with sepsis.

CONCLUSIONS:
Consistent with current definitions of acute kidney injury, a urine output threshold of less than 0.5 mL/kg/hr is modestly predictive of mortality in patients admitted to the ICU. The relative importance of urine output for predicting survival varies with admission diagnosis.
Cancer stem cells in gliomas: evolving concepts and therapeutic implications
Authors: Alcantara Llaguno Sheila , Parada Luis F. 
Published: September 2021

Purpose of review
Cancer stem cells (CSCs) have been implicated in the hierarchical heterogeneity and treatment resistance of hematologic and solid tumor malignancies, including gliomas, for several decades now but their therapeutic targeting has not been fully realized. Recent studies have uncovered deeper layers of CSC complexity, related to developmental origins, plasticity, cellular states, and interface with the microenvironment.

Recent findings
Sequencing and in-vivo lineage-tracing studies in mouse and patient-derived models show evidence of stem and progenitor origin of glioma, at the same time that genomic studies show a relatedness of glioma CSCs with radial glia. The spate of single-cell sequencing analyses demonstrates the diversity of transcriptional cellular states, which are susceptible to transitions, indicating the plasticity of glioma CSCs. The evolution of glioma CSCs and their interactions with niche cells play important roles in CSC treatment resistance and immune evasion, with epigenetic modulation as one of the emerging mechanisms.

Summary
To harness the potential of CSCs for clinical application, there is urgent need to investigate their complex nature and myriad interactions, to better understand the contribution of these self-renewing, stem-like cancer cells in the pathogenesis and therapy resistance of malignant brain tumors.
OUTCOME AND ASSOCIATED FACTORS AMONG ROAD TRAFFIC ACCIDENT VICTIMS AT WOLAITA SODDO CHRISTIAN HOSPITAL, WOLAITA SODDO, SOUTH ETHIOPIA 2020, INSTITUTION-BASED CROSS-SECTIONAL STUDY
Authors: Hizkel Asrat , Gebru Teklemichael , Yisihak Eshetu , Markos Desta 
Published: September 2021

ABSTRACTBackgroundIn today’ s world road traffic accident victims are treated as a major epidemic of non-communicable disease. Road traffic accidents caused numerous family tragedies such as serious economic loss to the community and the death of young people. The problem is more severe in low and middle-income countries. In Ethiopia, the largest proportion of series injuries comes from road traffic accidents and become major causes of death in the emergency room. Despite this, only a little is known about treatment outcomes of road traffic accident victims and its associated factors in Ethiopia.MethodAn institution-based Cross-sectional study design was conducted at Wolaita Soddo Christian hospital with a sample of 400 road traffic accidents. The medical record was selected using a systematic sampling method. Data was entered using Epi-data version 4.1 and was exported to and analyzed using SPSS version 23. A multivariable logistic regression model was used to assess the association between the independent variables and dependent variables.RESULTThe overall death rate was 9.5%. Being out of hospital catchment area [AOR= 2.16, 95% CI= (1.01-4.70)] presence of co-morbid condition [AOR= 6.77 95% CI= (2.44-18.81)] lack of first aid help [AOR= 2.77 95% CI= (1.17-6.52)] and severity of the injury [AOR= 3.85 95% CI= (1.50-9.89)] were found to be significantly associated with outcome of road traffic accident victims.ConclusionThe study shows that the death rate from road traffic accidents was high. Therefore, designing strategies to decrease death from road traffic accidents by giving great emphasis to road traffic accident victims with co-morbid conditions and severe injury and focusing on the availability and accessibility of pre-hospital care service.
Analysis of modular gene co-expression networks reveals molecular pathways underlying Alzheimer’s disease and progressive supranuclear palsy
Authors: Carvalho Lukas Iohan , Lambert Jean-Charles , Costa Marcos R. 
Published: September 2021

AbstractA comprehensive understanding of the pathological mechanisms involved at different stages of neurodegenerative diseases is key for the advance of preventive and disease-modifying treatments. Gene expression alterations in the diseased brain is a potential source of information about biological processes affected by pathology. In this work, we performed a systematic comparison of gene expression alterations in the brains of human patients diagnosed with Alzheimer’s disease (AD) or Progressive Supranuclear Palsy (PSP) and animal models of amyloidopathy and tauopathy. Using a systems biology approach to uncover biological processes associated with gene expression alterations, we could pinpoint processes more strongly associated with tauopathy/PSP and amyloidopathy/AD. We show that gene expression alterations related to immune-inflammatory responses preponderate in younger, whereas those associated to synaptic transmission are mainly observed in older AD patients. In PSP, however, changes associated with immune-inflammatory responses and synaptic transmission overlap. These two different patterns observed in AD and PSP brains are fairly recapitulated in animal models of amyloidopathy and tauopathy, respectively. Moreover, in AD, but not PSP or animal models, gene expression alterations related to RNA splicing are highly prevalent, whereas those associated with myelination are enriched both in AD and PSP, but not in animal models. Finally, we identify 12 AD and 4 PSP genetic risk factors in cell-type specific co-expression modules, thus contributing to unveil the possible role of these genes to pathogenesis. Altogether, this work contributes to unravel the potential biological processes affected by amyloid versus tau pathology and how they could contribute to the pathogenesis of AD and PSP.
Improved survival byHelicobacter pylori-modulated immunity in gastric cancer patients with S-1 adjuvant chemotherapy
Authors: Koizumi Yuka , Ahmad Sheny , Ikeda Miyuki , Yashima-Abo Akiko , Espina Ginny , Sugimoto Ryo , Sugai Tamotsu , Iwaya Takeshi , Koeda Keisuke , Liotta Lance A. , Takahashi Fumiaki , Nishizuka Satoshi S. 
Published: September 2021

AbstractBackgroundParadoxically,Helicobacter pylori-positive (HP+) advanced gastric cancer patients have a better prognosis than those who are HP-negative (HP-). Immunologic and statistical analyses can be used to verify whether systematic mechanisms modulated by HP are involved in this more favorable outcome.MethodsA total of 658 advanced gastric cancer patients who underwent gastrectomy were enrolled. HP infection, mismatch repair, programmed death-ligand 1 (PD-L1), and CD4/CD8 proteins, and microsatellite instability were analyzed. Overall survival (OS) and relapse free survival (RFS) rates were analyzed after stratifying clinicopathological factors. Cox proportional hazards regression analysis was performed to identify independent prognostic factors.ResultsAmong 491 cases that were analyzed, 175 (36%) and 316 (64%) cases were HP+and HP−, respectively. Analysis of RFS indicated an interaction of HP status among the subgroups for S-1 Dose (P=0.0487) and PD-L1 (P=0.016). HP+patients in the PD-L1 group had significantly higher five-year OS and RFS than HP-patients (81% vs. 68%;P=0.0011; HR 0.477; and 76% vs. 63%;P=0.0011; HR 0.508, respectively). The five-year OS and RFS was also significantly higher for HP+compared to HP-patients in the PD-L1-/S-1-reduced group (86% vs. 46%;p=0.0014; HR 0.205; 83% vs. 34%;p=0.001; HR 0.190, respectively). Thus, HP status was identified as one of the most potentially important independent factors to predict prolonged survival.ConclusionModulation of host immune system function by HP may contribute to prolonged survival in the absence of immune escape mechanisms of gastric cancer.
CNN for a Connectivity Based Epilepsy Diagnosis with Resting-state EEG
Authors: Rijnders Berjo , Korkmaz Emin Erkan , Yildirim Funda 
Published: September 2021

ABSTRACTObjectiveThis study investigates the performance of a CNN algorithm on epilepsy diagnosis. Without pathology, diagnosis involves long and costly electroencephalographic (EEG) monitoring. Novel approaches may overcome this by comparing brain connectivity using graph metrics. This study, however, uses deep learning to learn connectivity patterns directly from easily acquired EEG data.MethodsA convolutional neural network (CNN) algorithm was applied on directed Granger causality (GC) connectivity measures, derived from 50 seconds of resting-state surface EEG recordings from 30 subjects with epilepsy and a 30 subject control group.ResultsThe learned CNN filters reflected reduced delta band connectivity in frontal regions and increased left lateralized frontal-posterior gamma band connectivity. A diagnosis accuracy of 85% (F1-score 85%) was achieved by an ensemble of CNN models, each trained on differently prepared data from different electrode combinations.ConclusionsAppropriate preparation of connectivity data enables generic CNN algorithms to be used for detection of multiple discriminative epileptic features. Differential patterns revealed in this study may help to shed light on underlying altered cognitive abilities in epilepsy patients.SignificanceThe accuracy achieved in this study shows that, in combination with other methods, this approach could prove a valuable clinical decision support system for epilepsy diagnosis.
The mathematics of erythema: Development of machine learning models for artificial intelligence assisted measurement and severity scoring of radiation induced dermatitis
Authors: Ranjan Rahul , Partl Richard , Erhart Ricarda , Kurup Nithin , Schnidar Harald 
Published: September 2021

ABSTRACTAlthough significant advancements in computer-aided diagnostics using artificial intelligence (AI) have been made, to date, no viable method for radiation-induced skin reaction (RISR) analysis and classification is available. The objective of this single-center study was to develop machine learning and deep learning approaches using deep convolutional neural networks (CNNs) for automatic classification of RISRs according to the Common Terminology Criteria for Adverse Events (CTCAE) grading system. Scarletred® Vision, a novel and state-of-the-art digital skin imaging method capable of remote monitoring and objective assessment of acute RISRs was used to convert 2D digital skin images using the CIELAB color space and conduct SEV* measurements. A set of different machine learning and deep convolutional neural network-based algorithms has been explored for the automatic classification of RISRs. A total of 2263 distinct images from 209 patients were analyzed for training and testing the machine learning and CNN algorithms. For a 2-class problem of healthy skin (grade 0) versus erythema (grade ≥ 1), all machine learning models produced an accuracy of above 70%, and the sensitivity and specificity of erythema recognition were 67-72% and 72-83%, respectively. The CNN produced a test accuracy of 74%, sensitivity of 66%, and specificity of 83% for predicting healthy and erythema cases. For the severity grade prediction of a 3-class problem (grade 0 versus 1 versus 2), the overall test accuracy was 60-67%, and the sensitivities were 56-82%, 35-59%, and 65-72%, respectively. For estimating the severity grade of each class, the CNN obtained an accuracy of 73%, 66%, and 82%, respectively. Ensemble learning combines several individual predictions to obtain a better generalization performance. Furthermore, we exploited ensemble learning by deploying a CNN model as a meta-learner. The ensemble CNN based on bagging and majority voting shows an accuracy, sensitivity and specificity of 87%, 90%, and 82% for a 2-class problem, respectively. For a 3-class problem, the ensemble CNN shows an overall accuracy of 66%, while for each grade (0, 1, and 2) accuracies were 76%, 69%, and 87%, sensitivities were 70%, 57%, and 71%, and specificities were 78%, 75%, and 95%, respectively. This study is the first to focus on erythema in radiation-dermatitis and produces benchmark results using machine learning models. The outcome of this study validates that the proposed system can act as a pre-screening and decision support tool for oncologists or patients to provide fast, reliable, and efficient assessment of erythema grading.
DAVI: a tool for clustering and visualising protein domain architectures
Authors: Saighi Paul , Jaouadi Chadi , Vieira Fabio R.J , Bernardes Juliana Silva 
Published: September 2021

The characterization of protein functions is one of the main challenges in bioinformatics. Proteins are often composed of individual units termed domains, motifs that can evolve independently. The domain architecture of a given protein is the particular order and the content of its numerous domains. Some computational approaches predict the most likely domain architecture for a set of proteins. However, a few numbers of visualization tools exist, and most of them are unavailable. Here we present DAVI, an efficient and user-friendly web server for protein domain architecture clustering and visualization. DAVI accepts the output of most used domain architecture prediction tools and also produces domain architectures for a set of protein sequences. It provides a rich visualization for comparing, analyzing, and visualizing domain architectures.Availabilityhttp://genome.lcqb.upmc.fr/Domain-Architecture-Viewer