bluuebunny/crossref_metadata_2025_split huggingface dataset:
Forecasting Patient Discharge Before Noon: A Comparison Between Holt's and Box-Jenkins' Models
Authors: Berríos Rolando A. 
Published: September 2019

Background:
The uncertainty and ambiguity of not knowing how many patients will be discharged impact patient throughput in hospitals, causing concerns for responding to demand for admissions. Understanding the potential number of patients to be discharged can support caregivers, ability to concentrate on the range of interactions that patients require to ensure early discharge. Accurate forecasting of patients expected to be discharged by noon is beneficial in accommodating patients who need services and in achieving sustainable patient satisfaction.

Method:
Models to predict patient discharge before noon (DBN) were formulated using Holt's double exponential smoothing and Box-Jenkins' methods with the aim of achieving minimal errors in each model. The models are applied to 24 months of weekly patient discharge historic data in a medical observation unit and a short-stay clinical unit of a health care hospital system located on the East Coast of United States.

Results:
DBN prediction outcomes were more accurate when applying Box-Jenkins' method than Holt's method. Analysis revealed that the model of ARIMA(3,1,2) is most suitable for forecasting. Upon the outcomes of forecast error metrics, the study identifies the mean absolute percent error for the ARIMA model is 14%.

Conclusion:
Box-Jenkins forecasting performance is superior in predicting DBN with the least forecast error. Predicted values are significant to decision-making interventions aimed at taking new patients, improving quality patient care, and meeting patient throughput performance goals.
A National Cohort Study Evaluating the Association Between Short-term Outcomes and Long-term Survival After Esophageal and Gastric Cancer Surgery
Authors: van der Werf Leonie R. , Wijnhoven Bas P. L. , Fransen Laura F. C. , van Sandick Johanna W. , Nieuwenhuijzen Grard A. P. , Busweiler Linde A. D. , van Hillegersberg Richard , Wouters Michel W. J. M. , Luyer Misha D. P. , van Berge Henegouwen Mark I. 
Published: September 2019

Objective:
The aim of this study was to investigate the association between short-term outcome indicators and long-term survival after esophagogastric resections.

Summary Background Data:
Short-term outcome indicators are often used to compare performance between care providers. Some short-term outcome indicators concern the direct quality of care, that is, complications, others are used because they are expected to be associated with long-term outcomes.

Method:
For this national cohort study, all patients who underwent esophagectomy or gastrectomy for cancer with curative intent between 2011 and 2016 and were registered in the Dutch Upper gastrointestinal Cancer Audit were included. Primary outcome was conditional survival (under the condition of surviving the first postoperative 30 days and hospital admission). Cox regression modeling was used to study the independent association between “textbook outcome” with survival. “Textbook outcome,” a composite quality indicator, was defined as a pathological complete resection with at least 15 retrieved lymph nodes, an uneventful postoperative course, and no hospital readmission.

Results:
In total, 4414 and 2943 patients with esophageal or gastric cancer, respectively, were included. The 1-, 2-, and 3-year overall survival rates were 76%, 62%, and 54%, and 71%, 56%, and 49% for esophageal and gastric cancer, respectively. Textbook outcome was achieved in 33% and 35% of patients respectively. “Textbook outcome” was independently associated with longer conditional survival [hazard ratio: 0.75 (95% confidence interval, 0.68–0.84) and 0.69 (0.60–0.79), respectively].

Conclusion:
This study showed that the short-term outcome indicator textbook outcome is associated with long-term overall survival and therefore may accentuate the importance of using these indicators in clinical audits.
The path forward for anti-programmed cell death-1 therapy in gliomas
Authors: Majd Nazanin , Kamiya-Matsuoka Carlos , de Groot John 
Published: September 2019

Purpose of review
Checkpoint inhibitors (CPIs) represent the forefront of novel immunotherapeutic approaches for the treatment of solid cancers. However, the clinical development of CPIs in glioblastoma (GBM) has been challenging owing to an immunosuppressive tumor microenvironment and, possibly, low tumor mutation burden. Here, we review possible mechanisms responsible for the success of programmed cell death-1 (PD-1) blockade in patients with hypermutated GBM, recent clinical trials of anti-PD-1 monotherapy, trials incorporating neoadjuvant strategies, and trials of immunotherapy combination approaches in GBM. Mechanisms of resistance to immunotherapy and methods to overcome these challenges are also discussed.

Recent findings
Although two large phase III trials failed to demonstrate the superior efficacy of CPI in comparison with the standard of care in newly diagnosed and recurrent GBM, recent studies suggest that opportunities exist in some patients with GBM. A phase II study showed longer survival in patients with recurrent GBM who received neoadjuvant anti-PD-1 therapy than in those who received it as adjuvant therapy. In addition, cases of response to anti-PD-1 therapy in GBM patients with clonal hypermutator tumors have been reported.

Summary
Even though anti-PD-1 therapy does not seem to provide a benefit for molecularly unselected GBM patients, the success of PD-1 blockade in certain subsets of patients is encouraging.
Anteroposterior balance reactions of children with and without cerebral palsy: a cross-sectional, observational study of children age 5-12 years
Authors: Crenshaw Jeremy R. , Petersen Drew A. , Conner Benjamin C. , Tracy James B. , Pigman Jamie , Wright Henry G. , Miller Freeman , Johnson Curtis L. , Modlesky Christopher M. 
Published: September 2019

ABSTRACTAimTo compare anterior and posterior standing balance reactions, as measured by single-stepping thresholds, of children with and without cerebral palsy (CP).MethodSeventeen ambulatory children with CP and 28 typically developing children, all 5-12 years of age, were recruited for this cross-sectional, observational study. Balance reaction skill was quantified as anterior and posterior single-stepping thresholds, or the treadmill-induced perturbations that consistently elicited a step in that direction. In order to understand underlying mechanisms of between-group differences in stepping thresholds, dynamic stability was quantified using the minimum margin of stability. Ankle muscle activation latency, magnitude, and co-contraction were assessed with surface electromyography.ResultsWe observed large between-group differences in anterior, but not posterior, thresholds. Between-group differences were most evident in older children, with typically developing children having larger anterior thresholds than those with CP. In response to near-threshold anterior perturbations, older typically developing children recovered from more instability than their CP peers. Older children had no between-group differences in ankle muscle activity.InterpretationThe effects of CP on balance reactions are age- and direction-specific. In response to an anterior perturbation, older typically developing children recovered from more instability than their peers with CP.What this paper addsChildren with CP have age- and direction-specific balance-reaction impairments.Impairment was most evident in the anterior reactions of older children (≈11 years).Typically developing children recovered from more anterior instability than those with CP.Graphical Abstract
Predicting Under-five mortality across 21 Low and Middle-Income Countries using Deep Learning Methods
Authors: Adegbosin Adeyinka E , Stantic Bela , Sun Jing 
Published: September 2019

AbstractObjectivesTo explore the efficacy of Machine Learning (ML) techniques in predicting under-five mortality in LMICs and to identify significant predictors of under-five mortality (U5M).DesignThis is a cross-sectional, proof-of-concept study.Settings and participantsWe analysed data from the Demographic and Health Survey (DHS). The data was drawn from 21 Low-and-Middle Income Countries (LMICs) countries (N = 1,048,575). Eligible mothers in each household were asked information about their children and the reproductive care they received during the pregnancy.Primary and secondary outcome measuresThe primary outcome measure was under-five mortality; secondary outcome was comparing the efficacy of deep learning algorithms: Deep Neural Network (DNN); Convolution Neural Network (CNN); Hybrid CNN-DNN with Logistic Regression (LR) for the prediction of child survival.ResultsWe found that duration of breast feeding, household wealth index and the level of maternal education are the most important predictors of under-five mortality. We found that deep learning techniques are superior to LR for the classification of child survival: LR sensitivity = 0.47, specificity = 0.53; DNN sensitivity = 0.69, specificity = 0.83; CNN sensitivity = 0.68, specificity = 0.83; CNN-DNN sensitivity = 0.71, specificity = 0.83.ConclusionOur findings provide an understanding of interventions that needs to be prioritized, in order to reduce levels of U5M in LMICs. It also demonstrates that deep learning models are more efficacious than a traditional analytical approach.Strengths and limitations of this studyThe models were tested using a very large data sample, drawn from over 1 million households.The survey utilised a cluster sampling approach and are representative of each country included.Socio-economic, political and cultural differences between the included countries may limit generalisability of the results.The cross-sectional design of the study means we can only infer association and not causality.
Evaluation of Reproducibility in Urology Publications
Authors: Rauh Shelby Lynn , Johnson Bradley S. , Bowers Aaron , Tritz Daniel , Vassar Benjamin Matthew 
Published: September 2019

Take Home MessageMany components of transparency and reproducibility are lacking in urology publications, making study replication, at best, difficult.IntroductionReproducibility is essential for the integrity of scientific research. Reproducibility is measured by the ability of investigators to replicate the outcomes of an original publication by using the same materials and procedures.MethodsWe sampled 300 publications in the field of urology for assessment of multiple indicators of reproducibility, including material availability, raw data availability, analysis script availability, pre-registration information, links to protocols, and whether the publication was freely available to the public. Publications were also assessed for statements about conflicts of interest and funding sources.ResultsOf the 300 sample publications, 171 contained empirical data and could be analyzed for reproducibility. Of the analyzed articles, 0.58% (1/171) provided links to protocols, and none of the studies provided analysis scripts. Additionally, 95.91% (164/171) did not provide accessible raw data, 97.53% (158/162) did not provide accessible materials, and 95.32% (163/171) did not state they were pre-registered.ConclusionCurrent urology research does not consistently provide the components needed to reproduce original studies. Collaborative efforts from investigators and journal editors are needed to improve research quality, while minimizing waste and patient risk.
Cannabis, Connectivity, and Coming of Age: Associations between Cannabis Use and Anterior Cingulate Cortex Connectivity during the Transition to Adulthood
Authors: Lichenstein Sarah D. , Shaw Daniel S. , Forbes Erika E. 
Published: September 2019

AbstractBackgroundCannabis use is common among adolescents and emerging adults and is associated with significant adverse consequences for a subset of users. Rates of use peak between the ages of 18-25, yet the neurobiological consequences for neural systems that are actively developing during this time remain poorly understood. In particular, cannabis exposure may interfere with adaptive development of white matter pathways underlying connectivity of the anterior cingulate cortex, including the cingulum and anterior thalamic radiations (ATR).MethodsThe current study examined the association between cannabis use during adolescence and emerging adulthood and white matter microstructure of the cingulum and ATR among 158 male subjects enrolled in the Pitt Mother & Child Project, a prospective, longitudinal study of risk and resilience among men of low socioeconomic status. Participants were recruited in infancy, completed follow-up assessments throughout childhood and adolescence, and underwent diffusion imaging at age 20 and 22.ResultsAt age 20, moderate cannabis use across adolescence (age 12-19) was associated with higher fractional anisotropy of the cingulum and ATR, relative to both minimal and heavy adolescent use. Longitudinally, moderate and heavy extended cannabis use (age 12-21) was associated with reduced positive change in FA in both pathways from age 20 to 22, relative to minimal use.ConclusionsThese results suggest that precocious white matter development may be linked to increased risk for use, whereas cannabis exposure may delay white matter maturation during the transition to adulthood and potentially impact individuals’ functioning later in development.
Common gene expression signatures in Parkinson’s disease are driven by changes in cell composition
Authors: Nido Gonzalo S. , Dick Fiona , Toker Lilah , Petersen Kjell , Alves Guido , Tysnes Ole-Bjørn , Jonassen Inge , Haugarvoll Kristoffer , Tzoulis Charalampos 
Published: September 2019

AbstractBackgroundThe etiology of Parkinson’s disease (PD) is largely unknown. Genome-wide transcriptomic studies in bulk brain tissue have identified several molecular signatures associated with the disease. While these studies have the potential to shed light into the pathogenesis of PD, they are also limited by two major confounders: RNA post mortem degradation and heterogeneous cell type composition of bulk tissue samples. We performed RNA sequencing following ribosomal RNA depletion in the prefrontal cortex of 49 individuals from two independent case-control cohorts. Using cell-type specific markers, we estimated the cell-type composition for each sample and included this in our analysis models to compensate for the variation in cell-type proportions.ResultsRibosomal RNA depletion results in substantially more even transcript coverage, compared to poly(A) capture, in post mortem tissue. Moreover, we show that cell-type composition is a major confounder of differential gene expression analysis in the PD brain. Correcting for cell-type proportions attenuates numerous transcriptomic signatures that have been previously associated with PD, including vesicle trafficking, synaptic transmission, immune and mitochondrial function. Conversely, pathways related to endoplasmic reticulum, lipid oxidation and unfolded protein response are strengthened and surface as the top differential gene expression signatures in the PD prefrontal cortex.ConclusionsDifferential gene expression signatures in PD bulk brain tissue are significantly confounded by underlying differences in cell-type composition. Modeling cell-type heterogeneity is crucial in order to unveil transcriptomic signatures that represent regulatory changes in the PD brain and are, therefore, more likely to be associated with underlying disease mechanisms.
Tissue ingrowth markedly reduces mechanical anisotropy and stiffness in fibre direction of highly aligned electrospun polyurethane scaffolds
Authors: Krynauw Hugo , Buescher Jannik , Koehne Josepha , Verrijt Loes , Limbert Georges , Davies Neil H , Bezuidenhout Deon , Franz Thomas 
Published: September 2019

AbstractPurposeThe lack of long-term patency of synthetic vascular grafts currently available on the market has directed research towards improving the performance of small diameter grafts. Improved radial compliance matching and tissue ingrowth into the graft scaffold are amongst the main goals for an ideal vascular graft.MethodsBiostable polyurethane scaffolds were manufactured by electrospinning and implanted in subcutaneous and circulatory positions in the rat for 7, 14 and 28 days. Scaffold morphology, tissue ingrowth, and mechanical properties of the scaffolds were assessed before implantation and after retrieval.ResultsTissue ingrowth after 24 days was 96.5 ± 2.3% in the subcutaneous implants and 77.8 ± 5.4% in the circulatory implants. Over the 24 days implantation, the elastic modulus at 12% strain decreased by 59% in direction of the fibre alignment whereas it increased by 1379% transverse to the fibre alignment of the highly aligned scaffold of the subcutaneous implants. The lesser aligned scaffold of the circulatory graft implants exhibited an increase of the elastic modulus at 12% strain by 77% in circumferential direction.ConclusionBased on the observations, it is proposed that the mechanism underlying the softening of the highly aligned scaffold in the predominant fibre direction is associated with scaffold compaction and local displacement of fibres by the newly formed tissue. The stiffening of the scaffold, observed transverse to highly aligned fibres and for more a random fibre distribution, represents the actual mechanical contribution of the tissue that developed in the scaffold.
Illuminating the dark side of the human transcriptome with TAMA Iso-Seq analysis
Authors: Kuo Richard I. , Cheng Yuanyuan , Smith Jacqueline , Archibald Alan L. , Burt David W. 
Published: September 2019

AbstractThe human transcriptome is one of the most well-annotated of the eukaryotic species. However, limitations in technology biased discovery toward protein coding spliced genes. Accurate high throughput long read RNA sequencing now has the potential to investigate genes that were previously undetectable. Using our Transcriptome Annotation by Modular Algorithms (TAMA) tool kit to analyze the Pacific Bioscience Universal Human Reference RNA Sequel II Iso-Seq dataset, we discovered thousands of potential novel genes and identified challenges in both RNA preparation and long read data processing that have major implications for transcriptome annotation.
Disease swamps molecular signatures of genetic-environmental associations to abiotic factors in Tasmanian devil (Sarcophilus harrisii) populations
Authors: Fraik Alexandra K. , Margres Mark J. , Epstein Brendan , Barbosa Soraia , Jones Menna , Hendricks Sarah , Schönfeld Barbara , Stahlke Amanda R. , Veillet Anne , Hamede Rodrigo , McCallum Hamish , Lopez-Contreras Elisa , Kallinen Samantha J. , Hohenlohe Paul A. , Kelley Joanna L. , Storfer Andrew 
Published: September 2019

AbstractLandscape genomics studies focus on identifying candidate genes under selection via spatial variation in abiotic environmental variables, but rarely by biotic factors such as disease. The Tasmanian devil (Sarcophilus harrisii) is found only on the environmentally heterogeneous island of Tasmania and is threatened with extinction by a nearly 100% fatal, transmissible cancer, devil facial tumor disease (DFTD). Devils persist in regions of long-term infection despite epidemiological model predictions of species’ extinction, suggesting possible adaptation to DFTD. Here, we test the extent to which spatial variation and genetic diversity are associated with the abiotic environment and/or by DFTD. We employ genetic-environment association (GEAs) analyses using a RAD-capture panel consisting of 6,886 SNPs from 3,286 individuals sampled pre- and post-disease arrival. Pre-disease, we find significant correlations of allele frequencies with environmental variables, including 349 unique loci linked to 64 genes, suggesting local adaptation to abiotic environment. Following DFTD arrival, however, we detected few of the pre-disease candidate loci, but instead frequencies of candidate loci linked to 14 genes correlated with disease prevalence. Loss of apparent signal of abiotic local adaptation following disease arrival suggests swamping by the strong selection imposed by DFTD. Further support for this result comes from the fact that post-disease candidate loci are in linkage disequilibrium with genes putatively involved in immune response, tumor suppression and apoptosis. This suggests the strength GEA associations of loci with the abiotic environment are swamped resulting from the rapid onset of a biotic selective pressure.
Processive activity of the replicative DNA polymerases in the replisome of live eukaryotic cells
Authors: Kapadia Nitin , El-Hajj Ziad W. , Zheng Huan , Beattie Thomas R. , Yu Angela , Reyes-Lamothe Rodrigo 
Published: September 2019

ABSTRACTDNA replication is carried out by a multi-protein machine called the replisome. InSaccharomyces cerevisiae, the replisome is composed of over 30 different proteins arranged into multiple subassemblies, each performing distinct activities. Synchrony of these activities is required for efficient replication and preservation of genomic integrity. How this is achieved is particularly puzzling at the lagging strand, where current models of the replisome architecture propose turnover of the canonical lagging strand polymerase, Pol δ, at every cycle of Okazaki fragment synthesis. Here we established single-molecule fluorescence microscopy protocols to study the binding kinetics of individual replisome subunits in liveS. cerevisiae. Our results show long residence times for most subunits at the active replisome, supporting a model where all subassemblies bind tightly and work in a coordinated manner for extended periods, including Pol δ, hence redefining the architecture of the active eukaryotic replisome.
Single cell transcriptome profiling of the human alcohol-dependent brain
Authors: Brenner Eric , Tiwari Gayatri R. , Liu Yunlong , Brock Amy , Mayfield R. Dayne 
Published: September 2019

AbstractBackgroundAlcoholism remains a prevalent health concern throughout the world. Previous studies have identified transcriptomic patterns in the brain associated with alcohol dependence in both humans and animal models. But none of these studies have systematically investigated expression within the unique cell types present in the brain.ResultsWe utilized single nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of over 16,000 nuclei isolated from prefrontal cortex of alcoholic and control individuals. Each nucleus was assigned to one of seven major cell types by unsupervised clustering. Cell type enrichment patterns varied greatly among neuroinflammatory-related genes, which are known to play roles in alcohol dependence and neurodegeneration. Differential expression analysis identified cell type-specific genes with altered expression in alcoholics. The largest number of differentially expressed genes (DEGs), including both protein-coding and non-coding, were detected in astrocytes, oligodendrocytes, and microglia.ConclusionsTo our knowledge, this is the first single cell transcriptome analysis of alcohol-associated gene expression in any species, and the first such analysis in humans for any addictive substance. These findings greatly advance understanding of transcriptomic changes in the brain of alcohol-dependent individuals.