bluuebunny/crossref_metadata_2025_split huggingface dataset:
Model-based clustering for flow and mass cytometry data with clinical information
Authors: Abe Ko , Minoura Kodai , Maeda Yuka , Nishikawa Hiroyoshi , Shimamura Teppei 
Published: September 2020

Abstract
Background
High-dimensional flow cytometry and mass cytometry allow systemic-level characterization of more than 10 protein profiles at single-cell resolution and provide a much broader landscape in many biological applications, such as disease diagnosis and prediction of clinical outcome. When associating clinical information with cytometry data, traditional approaches require two distinct steps for identification of cell populations and statistical test to determine whether the difference between two population proportions is significant. These two-step approaches can lead to information loss and analysis bias.

Results
We propose a novel statistical framework, called LAMBDA (Latent Allocation Model with Bayesian Data Analysis), for simultaneous identification of unknown cell populations and discovery of associations between these populations and clinical information. LAMBDA uses specified probabilistic models designed for modeling the different distribution information for flow or mass cytometry data, respectively. We use a zero-inflated distribution for the mass cytometry data based the characteristics of the data. A simulation study confirms the usefulness of this model by evaluating the accuracy of the estimated parameters. We also demonstrate that LAMBDA can identify associations between cell populations and their clinical outcomes by analyzing real data. LAMBDA is implemented in R and is available from GitHub (https://github.com/abikoushi/lambda).
Biomedical document triage using a hierarchical attention-based capsule network
Authors: Wang Jian , Li Mengying , Diao Qishuai , Lin Hongfei , Yang Zhihao , Zhang YiJia 
Published: September 2020

Abstract
Background
Biomedical document triage is the foundation of biomedical information extraction, which is important to precision medicine. Recently, some neural networks-based methods have been proposed to classify biomedical documents automatically. In the biomedical domain, documents are often very long and often contain very complicated sentences. However, the current methods still find it difficult to capture important features across sentences.

Results
In this paper, we propose a hierarchical attention-based capsule model for biomedical document triage. The proposed model effectively employs hierarchical attention mechanism and capsule networks to capture valuable features across sentences and construct a final latent feature representation for a document. We evaluated our model on three public corpora.

Conclusions
Experimental results showed that both hierarchical attention mechanism and capsule networks are helpful in biomedical document triage task. Our method proved itself highly competitive or superior compared with other state-of-the-art methods.
A consensus multi-view multi-objective gene selection approach for improved sample classification
Authors: Acharya Sudipta , Cui Laizhong , Pan Yi 
Published: September 2020

AbstractBackgroundIn the field of computational biology, analyzing complex data helps to extract relevant biological information. Sample classification of gene expression data is one such popular bio-data analysis technique. However, the presence of a large number of irrelevant/redundant genes in expression data makes a sample classification algorithm working inefficiently. Feature selection is one such high-dimensionality reduction technique that helps to maximize the effectiveness of any sample classification algorithm. Recent advances in biotechnology have improved the biological data to include multi-modal or multiple views. Different‘omics’resources capture various equally important biological properties of entities. However, most of the existing feature selection methodologies are biased towards considering only one out of multiple biological resources. Consequently, some crucial aspects of available biological knowledge may get ignored, which could further improve feature selection efficiency.ResultsIn this present work, we have proposed a Consensus Multi-View Multi-objective Clustering-based feature selection algorithm calledCMVMC. Three controlled genomic and proteomic resources like gene expression, Gene Ontology (GO), and protein-protein interaction network (PPIN) are utilized to build two independent views. The concept of multi-objective consensus clustering has been applied within our proposed gene selection method to satisfy both incorporated views. Gene expression data sets ofMultiple tissuesandYeastfrom two different organisms (Homo SapiensandSaccharomyces cerevisiae, respectively) are chosen for experimental purposes. As the end-product of CMVMC, a reduced set of relevant and non-redundant genes are found for each chosen data set. These genes finally participate in an effective sample classification.ConclusionsThe experimental study on chosen data sets shows that our proposed feature-selection method improves the sample classification accuracy and reduces the gene-space up to a significant level. In the case ofMultiple Tissuesdata set, CMVMC reduces the number of genes (features) from 5565 to 41, with 92.73% of sample classification accuracy. ForYeastdata set, the number of genes got reduced to 10 from 2884, with 95.84% sample classification accuracy. Two internal cluster validity indices - Silhouette and Davies-Bouldin (DB) and one external validity index Classification Accuracy (CA) are chosen for comparative study. Reported results are further validated through well-known biological significance test and visualization tool.
Liver imaging features by convolutional neural network to predict the metachronous liver metastasis in stage I-III colorectal cancer patients based on preoperative abdominal CT scan
Authors: Lee Sangwoo , Choe Eun Kyung , Kim So Yeon , Kim Hua Sun , Park Kyu Joo , Kim Dokyoon 
Published: September 2020

Abstract
Background
Introducing deep learning approach to medical images has rendered a large amount of un-decoded information into usage in clinical research. But mostly, it has been focusing on the performance of the prediction modeling for disease-related entity, but not on the clinical implication of the feature itself. Here we analyzed liver imaging features of abdominal CT images collected from 2019 patients with stage I – III colorectal cancer (CRC) using convolutional neural network (CNN) to elucidate its clinical implication in oncological perspectives.

Results
CNN generated imaging features from the liver parenchyma. Dimension reduction was done for the features by principal component analysis. We designed multiple prediction models for 5-year metachronous liver metastasis (5YLM) using combinations of clinical variables (age, sex, T stage, N stage) and top principal components (PCs), with logistic regression classification. The model using “1st PC (PC1) + clinical information” had the highest performance (mean AUC = 0.747) to predict 5YLM, compared to the model with clinical features alone (mean AUC = 0.709). The PC1 was independently associated with 5YLM in multivariate analysis (beta = − 3.831, P < 0.001). For the 5-year mortality rate, PC1 did not contribute to an improvement to the model with clinical features alone. For the PC1, Kaplan-Meier plots showed a significant difference between PC1 low vs. high group. The 5YLM-free survival of low PC1 was 89.6% and the high PC1 was 95.9%. In addition, PC1 had a significant correlation with sex, body mass index, alcohol consumption, and fatty liver status.

Conclusion
The imaging features combined with clinical information improved the performance compared to the standardized prediction model using only clinical information. The liver imaging features generated by CNN may have the potential to predict liver metastasis. These results suggest that even though there were no liver metastasis during the primary colectomy, the features of liver imaging can impose characteristics that could be predictive for metachronous liver metastasis.
PAWER: protein array web exploreR
Authors: Fishman Dmytro , Kuzmin Ivan , Adler Priit , Vilo Jaak , Peterson Hedi 
Published: September 2020

Abstract
Background
Protein microarray is a well-established approach for characterizing activity levels of thousands of proteins in a parallel manner. Analysis of protein microarray data is complex and time-consuming, while existing solutions are either outdated or challenging to use without programming skills. The typical data analysis pipeline consists of a data preprocessing step, followed by differential expression analysis, which is then put into context via functional enrichment. Normally, biologists would need to assemble their own workflow by combining a set of unrelated tools to analyze experimental data. Provided that most of these tools are developed independently by various bioinformatics groups, making them work together could be a real challenge.

Results
Here we present PAWER, the online web tool dedicated solely to protein microarray analysis. PAWER enables biologists to carry out all the necessary analysis steps in one go. PAWER provides access to state-of-the-art computational methods through the user-friendly interface, resulting in publication-ready illustrations. We also provide an R package for more advanced use cases, such as bespoke analysis workflows.

Conclusions
PAWER is freely available at https://biit.cs.ut.ee/pawer.
Five gene signatures were identified in the prediction of overall survival in resectable pancreatic cancer
Authors: Wu Chao , Wu Zuowei , Tian Bole 
Published: September 2020

Abstract
Background
Although genes have been previously detected in pancreatic cancer (PC), aberrant genes that play roles in resectable pancreatic cancer should be further assessed.

Methods
Messenger RNA samples and clinicopathological data corrected with PC were downloaded from The Cancer Genome Atlas (TCGA). Resectable PC patients were randomly divided into a primary set and a validation set. Univariable Cox regression analysis, lasso-penalized Cox regression analysis, and multivariable Cox analysis were implemented to distinguish survival-related genes (SRGs). A risk score based on the SRGs was calculated by univariable Cox regression analysis. A genomic-clinical nomogram was established by integrating the risk score and clinicopathological data to predict overall survival (OS) in resectable PC.

Results
Five survival-related genes (AADAC, DEF8, HIST1H1C, MET, and CHFR) were significantly correlated with OS in resectable PC. The resectable PC patients, based on risk score, were sorted into a high-risk group that showed considerably unfavorable OS (p < 0.001) than the low-risk group, in both the primary set and the validation set. The concordance index (C-index) was calculated to evaluate the predictive performance of the nomogram were respectively in the primary set [0.696 (0.608–0.784)] and the validation set [0.682 (0.606–0.758)]. Additionally, gene set enrichment Analysis discovered several meaningful enriched pathways.

Conclusion
Our study identified five prognostic gene biomarkers for OS prediction and which facilitate postoperative molecular target therapy for the resectable PC, especially the nomic-clinical nomogram which may be used as an effective model for the postoperative OS evaluation and also an optimal therapeutic tool for the resectable PC.
Microglial-associated responses to comorbid amyloid pathology and hyperhomocysteinemia in an aged knock-in mouse model of Alzheimer’s disease
Authors: Braun David J. , Dimayuga Edgardo , Morganti Josh M. , Van Eldik Linda J. 
Published: September 2020

Abstract
Background
Elevated blood homocysteine levels, termed hyperhomocysteinemia (HHcy), is a prevalent risk factor for Alzheimer’s disease (AD) in elderly populations. While dietary supplementation of B-vitamins is a generally effective method to lower homocysteine levels, there is little if any benefit to cognition. In the context of amyloid pathology, dietary-induced HHcy is known to enhance amyloid deposition and certain inflammatory responses. Little is known, however, about whether there is a more specific effect on microglia resulting from combined amyloid and HHcy pathologies.

Methods
The present study used a knock-in mouse model of amyloidosis, aged to 12 months, given 8 weeks of B-vitamin deficiency-induced HHcy to better understand how microglia are affected in this comorbidity context.

Results
We found that HHcy-inducing diet increased amyloid plaque burden, altered the neuroinflammatory milieu, and upregulated the expression of multiple damage-associated and “homeostatic” microglial genes.

Conclusions
Taken together, these data indicate complex effects of comorbid pathologies on microglial function that are not driven solely by increased amyloid burden. Given the highly dynamic nature of microglia, their central role in AD pathology, and the frequent occurrence of various comorbidities in AD patients, it is increasingly important to understand how microglia respond to mixed pathological processes.
The relationship between dietary patterns and rheumatoid arthritis: a case–control study
Authors: Nezamoleslami Shokufeh , Ghiasvand Reza , Feizi Awat , Salesi Mansour , Pourmasoumi Makan 
Published: September 2020

Abstract
Background and aim
A number of studies have investigated the effects of individual foods and/or nutrients on rheumatoid arthritis (RA), but research focusing on whole dietary patterns remains limited. The association of dietary patterns and rheumatoid arthritis is therefore not well elucidated. This study aims to determine existing relationships between major identified dietary patterns and RA.

Methods
This matched case–control study was conducted on 297 individuals in Isfahan, Iran. The presence of RA was determined by an expert rheumatologist, based on the American College of Rheumatology definitions, 2010. A 168-item questionnaire was used to collect dietary data. Major dietary patterns were identified using the factor analysis method.

Results
Two major dietary patterns, namely, healthy and western dietary patterns, were identified. Lower adherence to the healthy dietary pattern was associated with increased risk of RA (OR = 2.80; 95% CI 1.74–4.67; P < 0.001). The association remained significant even after taking other confounders into account (OR = 2.85; 95% CI 1.12–7.45; P = 0.03). A positively significant association was also observed between adherence to western dietary pattern and RA in the fully-adjusted final model (OR = 2.22; 95% CI 1.04–4.72; P = 0.03).

Conclusions
The study suggests that there is an inverse association between adherence to a healthy dietary pattern and the odds of RA, and a positive significant relationship was found between western dietary pattern and RA. Further studies are required to confirm these findings.
Comparative study on mid- and long-term clinical effects of medial pivot prosthesis and posterior-stabilized prosthesis after total knee arthroplasty
Authors: Shi Weipeng , Jiang Yaping , Wang Changyao , Zhang Haining , Wang Yingzhen , Li Tao 
Published: September 2020

AbstractObjectiveThe purpose of this study was to explore the mid-and long-term clinical effects of Chinese patients with medial pivot (MP) prosthesis and posterior-stabilized (PS) prosthesis after total knee arthroplasty (TKA), to provide a reference for the recommendation of clinical prostheses.MethodsA retrospective analysis of 802 patients who received TKA was performed from June 2010 to December 2013. A total of 432 patients received a MP prosthesis (MP group) and 375 patients received a PS prosthesis (PS group). Postoperative range of motion (ROM), clinical scores including the knee scoring system (KSS), the Western Ontario and McMaster Universities osteoarthritis index (WOMAC), the forgotten joint score (FJS), and postoperative complications were compared between the two groups.ResultsA total of 527 patients were followed up, including 290 in the MP group and 237 in the PS group. Both groups achieved satisfactory results in terms of KSS score, WOMAC score, and postoperative ROM, which were significantly improved compared with those before surgery, but the difference between the groups was not statistically significant (P> 0.05). The FJS scores of the MP group and the PS group were satisfactory and no significant difference was observed (P= 0.426). Postoperative complications occurred in 5 and 11 patients in the MP group and PS group, respectively.ConclusionThe clinical results of TKA with MP or PS in Chinese patients at mid- and long-term are encouraging, and no significant differences were observed between the two types of prostheses. Studies have also shown that both prostheses are safe for Chinese patients.
Comparison of suprapatellar versus infrapatellar approaches of intramedullary nailing for distal tibia fractures
Authors: Lu Yao , Wang Gen , Hu Bin , Ren Cheng , Sun Liang , Wang Zhimeng , He Changjun , Xue Hanzhong , Li Zhong , Zhang Kun , Ma Teng , Wang Qian 
Published: September 2020

Abstract
Background
This study aimed to analyze and compare the clinical and functional outcomes of distal tibia fractures treated with intramedullary nailing (IMN) using the suprapatellar (SP) and infrapatellar (IP) surgical approaches.

Methods
A retrospective analysis was performed in 63 patients with distal fractures that were treated with IMN between August 2014 and August 2018. A total of 27 and 36 patients underwent IMN using the SP and IP techniques, respectively. The surgical time, blood loss, closed reduction rate, rate of adjuvant reduction technique, fracture healing time, and complications were reviewed in this study. Anterior knee pain was assessed using the visual analog scale. The Lysholm Knee Scoring Scale and American Orthopaedic Foot and Ankle Society (AOFAS) scale were used as clinical measurements.

Results
A total of 63 patients, with a minimum follow-up of 12 months, were evaluated. The average surgical time, blood loss, rate of adjuvant reduction technique, closed reduction rate, fracture healing time, and Lysholm Knee Scoring Scale score were insignificantly different (P > 0.05) between the two groups. However, the SP approach was superior to the IP approach in terms of pain score, AOFAS score, and fracture deformity rate (P < 0.05).

Conclusions
In the treatment of distal tibia fractures, the SP IMN technique is associated with a significantly higher functional outcome, lower knee pain, and lower rate of fracture deformity than the IP IMN technique.
Bifrost: highly parallel construction and indexing of colored and compacted de Bruijn graphs
Authors: Holley Guillaume , Melsted Páll 
Published: September 2020

AbstractMemory consumption of de Bruijn graphs is often prohibitive. Most de Bruijn graph-based assemblers reduce the complexity by compacting paths into single vertices, but this is challenging as it requires the uncompacted de Bruijn graph to be available in memory. We present a parallel and memory-efficient algorithm enabling the direct construction of the compacted de Bruijn graph without producing the intermediate uncompacted graph. Bifrost features a broad range of functions, such as indexing, editing, and querying the graph, and includes a graph coloring method that maps eachk-mer of the graph to the genomes it occurs in.Availabilityhttps://github.com/pmelsted/bifrost
Overlap between adverse events (AEs) and serious adverse events (SAEs): a case study of a phase III cancer clinical trial
Authors: James Elizabeth C. , Dunn David , Cook Adrian D. , Clamp Andrew R. , Sydes Matthew R. 
Published: September 2020

Abstract
Background
Safety data is required to be collected in all clinical trials and can be separated into two types of data, adverse events and serious adverse events. Often, these types of safety data are collected as two discrete data sets, where adverse events that also meet the criteria for seriousness should be reported in both datasets. Safety analyses are often conducted using only the adverse event dataset, which should feature all safety events reported. We investigated whether the reporting of safety in both datasets was systematically followed and explored the impact of this on safety analyses in ICON8, an ovarian cancer clinical trial.

Methods
Text searches of serious adverse event data identified events that could potentially match the data reported in the adverse event dataset (looking at pre-specified AE terms only). These serious adverse events were then mapped to adverse event data according to predefined criteria: (a) event term matches, (b) date of onset and date of assessment within 30 days of each other, (c) date of assessment lies between date of onset and date of resolution and (d) events confirmed to occur in the same chemotherapy cycle. A combined dataset of all unique safety events (whether originally reported in the adverse event or serious adverse event dataset) was created and safety analyses re-performed.

Results
51,019 adverse events were reported in ICON8, of which 42,410 were included in the mapping exercise. One thousand five hundred six serious adverse event elements were reported, of which 668 were included in the mapping exercise. Sixty-one percent of serious adverse event elements was matched to an already-reported adverse event. Supplementing these additional safety events and re-performing safety analyses increased the proportion of patients with at least one grade 3 or worse safety events in all arms from 42 to 47% in the control arm and 61 to 65% and 52 to 59% in the research arms. The difference in proportions of grade 3 or worse event in the research arms compared to the control arm changed by 18% (95% confidence interval [CI] 12 to 24%) and 12% (95% CI 6 to 18%), respectively.

Conclusions
There was low agreement in mapping serious adverse events to already reported adverse events, with nearly 40% of serious adverse events included in the mapping exercise not mapped to an already reported adverse event. Any analyses of safety data that use only adverse event datasets or do not clearly account for serious adverse event data will likely be missing important safety information. Reporting standards should make clear which datasets were used for analyses.