bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cancer Incidence and Mortality in the Oldest Old: A Nationwide Study in Finland
Authors: Tanskanen Tomas , Seppä Karri J M , Virtanen Anni , Malila Nea K , Pitkäniemi Janne M 
Published: October 2020

Abstract
The world’s population is aging rapidly. This study reports the burden of cancer in the “oldest old” (aged ≥85 years) in Finland, 1953–2017, and estimates age-specific cancer rates in the older population (65–99 years) for 1988–2017. The Finnish Cancer Registry provided data on all cancer diagnoses, cancer deaths, and other deaths in cancer patients in Finland for 1953–2017. Between 1953–1957 and 2013–2017, the proportion of incident cancers in those aged ≥85 years increased from 1.5% to 9.6% (597 to 15,360 new cases), and in 2013–2017, more new cancers were diagnosed at ages ≥85 years than ages &lt;50 years. Cancer incidence and excess mortality attributable to cancer peaked at ages 85–94 years and declined subsequently, whereas cancer-specific mortality continued to increase or plateaued. Due to demographic changes, the number of new cancers in the oldest old has increased substantially in Finland, and currently nearly 1 in 10 cancers are diagnosed in this age group. The increasing cancer burden in the oldest old poses a major challenge for health care and needs to be addressed in designing clinical research and reporting of cancer registries. In older populations with competing risks of death, we propose excess cancer mortality as a measure of cancer-related mortality.
Computational methods for annotation of plant regulatory non-coding RNAs using RNA-seq
Authors: Vivek A T , Kumar Shailesh 
Published: October 2020

AbstractPlant transcriptome encompasses numerous endogenous, regulatory non-coding RNAs (ncRNAs) that play a major biological role in regulating key physiological mechanisms. While studies have shown that ncRNAs are extremely diverse and ubiquitous, the functions of the vast majority of ncRNAs are still unknown. With ever-increasing ncRNAs under study, it is essential to identify, categorize and annotate these ncRNAs on a genome-wide scale. The use of high-throughput RNA sequencing (RNA-seq) technologies provides a broader picture of the non-coding component of transcriptome, enabling the comprehensive identification and annotation of all major ncRNAs across samples. However, the detection of known and emerging class of ncRNAs from RNA-seq data demands complex computational methods owing to their unique as well as similar characteristics. Here, we discuss major plant endogenous, regulatory ncRNAs in an RNA sample followed by computational strategies applied to discover each class of ncRNAs using RNA-seq. We also provide a collection of relevant software packages and databases to present a comprehensive bioinformatics toolbox for plant ncRNA researchers. We assume that the discussions in this review will provide a rationale for the discovery of all major categories of plant ncRNAs.
DriverGroup: a novel method for identifying driver gene groups
Authors: Pham Vu V H , Liu Lin , Bracken Cameron P , Goodall Gregory J , Li Jiuyong , Le Thuc D 
Published: October 2020

Abstract

Motivation
Identifying cancer driver genes is a key task in cancer informatics. Most existing methods are focused on individual cancer drivers which regulate biological processes leading to cancer. However, the effect of a single gene may not be sufficient to drive cancer progression. Here, we hypothesize that there are driver gene groups that work in concert to regulate cancer, and we develop a novel computational method to detect those driver gene groups.

Results
We develop a novel method named DriverGroup to detect driver gene groups by using gene expression and gene interaction data. The proposed method has three stages: (i) constructing the gene network, (ii) discovering critical nodes of the constructed network and (iii) identifying driver gene groups based on the discovered critical nodes. Before evaluating the performance of DriverGroup in detecting cancer driver groups, we firstly assess its performance in detecting the influence of gene groups, a key step of DriverGroup. The application of DriverGroup to DREAM4 data demonstrates that it is more effective than other methods in detecting the regulation of gene groups. We then apply DriverGroup to the BRCA dataset to identify driver groups for breast cancer. The identified driver groups are promising as several group members are confirmed to be related to cancer in literature. We further use the predicted driver groups in survival analysis and the results show that the survival curves of patient subpopulations classified using the predicted driver groups are significantly differentiated, indicating the usefulness of DriverGroup.

Availability and implementation
DriverGroup is available at https://github.com/pvvhoang/DriverGroup

Supplementary information
Supplementary data are available at Bioinformatics online.
Measuring reproducibility of virus metagenomics analyses using bootstrap samples from FASTQ-files
Authors: Saremi Babak , Kohls Moritz , Liebig Pamela , Siebert Ursula , Jung Klaus 
Published: October 2020

Abstract

Motivation
High-throughput sequencing data can be affected by different technical errors, e.g. from probe preparation or false base calling. As a consequence, reproducibility of experiments can be weakened. In virus metagenomics, technical errors can result in falsely identified viruses in samples from infected hosts. We present a new resampling approach based on bootstrap sampling of sequencing reads from FASTQ-files in order to generate artificial replicates of sequencing runs which can help to judge the robustness of an analysis. In addition, we evaluate a mixture model on the distribution of read counts per virus to identify potentially false positive findings.

Results
The evaluation of our approach on an artificially generated dataset with known viral sequence content shows in general a high reproducibility of uncovering viruses in sequencing data, i.e. the correlation between original and mean bootstrap read count was highly correlated. However, the bootstrap read counts can also indicate reduced or increased evidence for the presence of a virus in the biological sample. We also found that the mixture-model fits well to the read counts, and furthermore, it provides a higher accuracy on the original or on the bootstrap read counts than on the difference between both. The usefulness of our methods is further demonstrated on two freely available real-world datasets from harbor seals.

Availability and implementation
We provide a Phyton tool, called RESEQ, available from https://github.com/babaksaremi/RESEQ that allows efficient generation of bootstrap reads from an original FASTQ-file.

Supplementary information
Supplementary data are available at Bioinformatics online.
Simultaneous Determination of Paracetamol, Propyphenazone and Caffeine in Presence of Paracetamol Impurities Using Dual-Mode Gradient HPLC and TLC Densitometry Methods
Authors: Ibrahim Hany , Hamdy Abdallah M , Merey Hanan A , Saad Ahmed S 
Published: October 2020

Abstract
Two chromatographic methods were validated for the determination of the widely prescribed analgesic and antipyretic drug combination of paracetamol (PC) (recently integrated into the supportive treatment of COVID-19), propyphenazone (PZ) and caffeine (CF) in the presence of two PC impurities, namely 4-aminophenol and 4-nitrophenol. A “dual-mode” gradient high-performance liquid chromatography method was developed, where the separation was achieved via “dual-mode” gradient by changing both the ternary mobile phase composition (acetonitrile: methanol: water) and the flow rate. This enables a good resolution within a relatively shorter analysis time. The analysis was realized using Zorbax Eclipse XDB column C18, 5 μm (250 × 4.6 mm) and the UV detector was set at 220 nm. The other method is a thin-layer chromatography densitometry method, where the separation was achieved using a mobile phase composed of chloroform: toluene: ethyl acetate: methanol: acetic acid (6: 6: 1: 2: 0.1, by volume). Densitometric detection was performed at 220 nm on silica gel 60 F254 plates. The developed methods were fully validated as per the ICH guidelines and proved to be accurate, robust, specific and suitable for application as purity indicating methods for routine analysis of PC in pure form or in pharmaceuticals with PZ and CF in quality control laboratories.
Quantitative Determination of Fosfomycin in 10 μL of Plasma and Dialysate by Hydrophilic Interaction Liquid Chromatography Electrospray Ionization Mass Spectrometry
Authors: Shopova Teodora , Hüppe Tobias , Wolf Beate , Sessler Daniel I , Volk Thomas , Groesdonk Heinrich V , Kreuer Sascha , Maurer Felix 
Published: October 2020

Abstract
Fosfomycin is an antibiotic with a broad spectrum of activity against many multidrug-resistant bacterial strains. It is mainly excreted unchanged by the kidneys, and its half-life therefore depends on kidney function which varies considerably among individuals, and within individuals over time. Proper fosfomycin dosing thus depends on assaying blood concentration of the drug. We developed and validated a simple, sensitive and specific chromatography assay, which was coupled to electrospray ionization mass spectrometry for determination of fosfomycin. Separation of fosfomycin was based on the method of the hydrophilic interaction liquid chromatography; specifically, plasma and dialysate samples were acidified and the protein precipitated with acetonitrile. The calibration curves showed excellent coefficients of determination (R2 &gt; 0.999) over the relevant concentration range of 25–700 μg/mL. Intraday precision was 1.1–1.2% and accuracy was −5.9% to 0.9% for quality control samples. Interday precision was 2.9–3.4% and accuracy was −3.7% to 5.5%. Extraction recovery was ≥87% and matrix effects ranged from 2.2% to 4.3%. After laboratory validation, the method was successfully applied to clinical samples.
Scope and heterogeneity of outcomes reported in randomized trials in patients receiving peritoneal dialysis
Authors: Manera Karine E , Johnson David W , Cho Yeoungjee , Sautenet Benedicte , Shen Jenny , Kelly Ayano , Yee-Moon Wang Angela , Brown Edwina A , Brunier Gillian , Perl Jeffrey , Dong Jie , Wilkie Martin , Mehrotra Rajnish , Pecoits-Filho Roberto , Naicker Saraladevi , Dunning Tony , Craig Jonathan C , Tong Allison 
Published: October 2020

Abstract

Background
Randomized trials can provide evidence to inform decision-making but this may be limited if the outcomes of importance to patients and clinicians are omitted or reported inconsistently. We aimed to assess the scope and heterogeneity of outcomes reported in trials in peritoneal dialysis (PD).

Methods
We searched the Cochrane Kidney and Transplant Specialized Register for randomized trials in PD. We extracted all reported outcome domains and measurements and analyzed their frequency and characteristics.

Results
From 128 reports of 120 included trials, 80 different outcome domains were reported. Overall, 39 (49%) domains were surrogate, 23 (29%) patient-reported and 18 (22%) clinical. The five most commonly reported domains were PD-related infection [59 (49%) trials], dialysis solute clearance [51 (42%)], kidney function [45 (38%)], protein metabolism [44 (37%)] and inflammatory markers/oxidative stress [42 (35%)]. Quality of life was reported infrequently (4% of trials). Only 14 (12%) trials included a patient-reported outcome as a primary outcome. The median number of outcome measures (defined as a different measurement, aggregation and metric) was 22 (interquartile range 13–37) per trial. PD-related infection was the most frequently reported clinical outcome as well as the most frequently stated primary outcome. A total of 383 different measures for infection were used, with 66 used more than once.

Conclusions
Trials in PD include important clinical outcomes such as infection, but these are measured and reported inconsistently. Patient-reported outcomes are infrequently reported and nearly half of the domains were surrogate. Standardized outcomes for PD trials are required to improve efficiency and relevance.
Safety, Pharmacokinetics, and Efficacy of Olorinab, a Peripherally Acting, Highly Selective, Full Agonist of the Cannabinoid Receptor 2, in a Phase 2a Study of Patients With Chronic Abdominal Pain Associated With Crohn’s Disease
Authors: Yacyshyn Bruce R , Hanauer Stephen , Klassen Preston , English Brett A , Stauber Kathe , Barish Charles F , Gilder Kye , Turner Stewart , Higgins Peter D R 
Published: October 2020

AbstractBackgroundThis randomized, open-label phase 2a study investigated the safety/tolerability, pharmacokinetics, and efficacy of olorinab—a highly selective, peripherally acting, full agonist of the cannabinoid receptor 2—in patients with Crohn’s disease (CD) experiencing abdominal pain.MethodsEligible subjects 18–80 years of age with quiescent to mildly active CD were randomized to receive olorinab 25 or 100 mg three times daily for 8 weeks. The primary objective was to assess safety/tolerability.ResultsFourteen subjects received olorinab 25 mg (N = 6) or 100 mg (N = 8). Ten subjects [4 (67%) in the 25-mg group and 6 (75%) in the 100-mg group] reported a total of 34 treatment-emergent adverse events (TEAEs; 32 grade 1/2, not serious events; 2 grade 3, serious, not treatment-related events). No dose reductions or discontinuations due to TEAEs or deaths were reported. Dose-proportional increases in olorinab exposure from 25 to 100 mg were observed, with minimal accumulation at both doses. At week 8, the mean (SD) change from baseline in average abdominal pain score at peak olorinab plasma concentrations was −4.61 (1.77) in the 25-mg group (P = 0.0043) and −4.57 (2.17) in the 100-mg group (P = 0.0036). The change from baseline at week 8 in the mean (SD) number of pain-free days per week was +1.60 (2.61) in the 25-mg group and +2.33 (3.62) in the 100-mg group. No subject required pain medication on study.ConclusionsPatients with quiescent to mildly active CD receiving olorinab experienced mild-to-moderate adverse events and an improvement in abdominal pain scores in this study.
Long-term outcome of myocardial scarring and deformation with cardiovascular magnetic resonance in out of hospital cardiac arrest survivors
Authors: Baritussio Anna , Biglino Giovanni , Scatteia Alessandra , De Garate Estefania , Dastidar Amardeep Ghosh , Palazzuoli Alberto , Harries Iwan , Strange Julian W , Diab Ihab , Bucciarelli-Ducci Chiara 
Published: October 2020

Abstract

Aims
Cardiovascular magnetic resonance (CMR) is increasingly recognized as a diagnostic and prognostic tool in out of hospital cardiac arrest (OHCA) survivors. After assessing CMR findings early after ventricular fibrillation (VF) OHCA, we sought to explore the long-term outcome of myocardial scarring and deformation.

Methods and results
We included 121 consecutive VF OHCA survivors (82% male, median 62 years) undergoing CMR within 2 weeks from cardiac arrest. Late gadolinium-enhancement (LGE) was quantified using the full width at half maximum method and tissue tracking analysis software was used to assess myocardial deformation. LGE was found in 71% of patients (median LGE mass 6.2% of the left ventricle, LV), mainly with an ischaemic pattern. Myocardial deformation was overall impaired and showed a significant correlation with LGE presence and extent (P &lt; 0.001). A composite end-point of all-cause mortality and appropriate ICD discharge/anti-tachycardia pacing was met in 24% of patients. Patients meeting the end-point had significantly greater LGE extent (8.6% of LV myocardium vs. 4.1%, P = 0.02), while there was no difference with regards to myocardial deformation. Survival rate was significantly lower in patients with LGE (P = 0.05) and LGE mass &gt;4.4% of the LV identified a group of patients at higher risk of adverse events (P = 0.005).

Conclusions
We found a high prevalence of LGE, early after OHCA, and an overall impaired myocardial deformation. On long-term follow-up both LGE presence and extent showed a significant association with recurrent adverse events, while LV ejection fraction and myocardial deformation did not identify patients with an unfavourable outcome.
Modelling risk factors for high/low Psychosocial Impact of Dental Aesthetics Questionnaire (PIDAQ) in the Australian adults
Authors: Wahab Adam , Ju Xiangqun , Jamieson Lisa , Dreyer Craig 
Published: October 2020

Summary

Objective
Psychosocial Impact of Dental Aesthetics Questionnaire (PIDAQ) is an instrument to assess the subjective perception needed for orthodontic treatment (OT). The study aimed to (1) evaluate the psychosocial impact of dental aesthetics and the potential role of OT and (2) determine associations between PIDAQ with self-rated general and oral health, oral health-related quality of life (OHRQOL), and receipt of OT among Australian adults.

Methods
Data were obtained from the 2013 Australian National Dental Telephone Interview Survey (NDTIS). The PIDAQ was utilized as main outcome, comprising items from four conceptual domains: self-confidence, social impact, psychological impact, and aesthetic concern. Participants reported their socio-demographic, behavioural, self-rated general and oral health as well as the poor OHRQOL using the Oral Impact on Daily Performance (OIDP) instrument and OT. The mean of PIDAQ and four subscales score and their 95% confidence intervals (CI) were estimated. Generalized liner regression was used to estimate association between PIDAQ and covariates by calculating the mean ratio (MR) and their 95% CI.

Results
There were 2936 Australian adults who completed the PIDAQ items. The mean PIDAQ score was 28.8 (95% CI: 28.0–29.6). Higher PIDAQ scores were identified among those who reported non-Australian birth, lower incomes, infrequent dental visits, less than 21 teeth and brushing teeth less than twice a day, fair/poor self-rated general and oral health, and poor OHRQOL. In multivariable modelling, the mean PIDAQ score was 1.91 (95% CI: 1.82–2.00) times higher among those with OIDP score &gt;3 and 1.06 (95% CI:1.01–1.10) times higher in those who had OT, comparing with their counterparts. Also, higher PIDAQ scores were identified among females, last visiting a dentist more than 2 years ago, fair or poor self-rated oral and general health.

Conclusions
Higher PIDAQ scores that have a greater impact on OHRQOL were associated with poorer self-rated general and oral health. This may be explained by unfavourable dental attendance and oral health habits. The positive correlation with OIDP scores verifies the validity of the PIDAQ. Those who had received OT had lower PIDAQ and OIDP scores.
A single-cell RNA-sequencing training and analysis suite using the Galaxy framework
Authors: Tekman Mehmet , Batut Bérénice , Ostrovsky Alexander , Antoniewski Christophe , Clements Dave , Ramirez Fidel , Etherington Graham J , Hotz Hans-Rudolf , Scholtalbers Jelle , Manning Jonathan R , Bellenger Lea , Doyle Maria A , Heydarian Mohammad , Huang Ni , Soranzo Nicola , Moreno Pablo , Mautner Stefan , Papatheodorou Irene , Nekrutenko Anton , Taylor James , Blankenberg Daniel , Backofen Rolf , Grüning Björn 
Published: October 2020

AbstractBackgroundThe vast ecosystem of single-cell RNA-sequencing tools has until recently been plagued by an excess of diverging analysis strategies, inconsistent file formats, and compatibility issues between different software suites. The uptake of 10x Genomics datasets has begun to calm this diversity, and the bioinformatics community leans once more towards the large computing requirements and the statistically driven methods needed to process and understand these ever-growing datasets.ResultsHere we outline several Galaxy workflows and learning resources for single-cell RNA-sequencing, with the aim of providing a comprehensive analysis environment paired with a thorough user learning experience that bridges the knowledge gap between the computational methods and the underlying cell biology. The Galaxy reproducible bioinformatics framework provides tools, workflows, and trainings that not only enable users to perform 1-click 10x preprocessing but also empower them to demultiplex raw sequencing from custom tagged and full-length sequencing protocols. The downstream analysis supports a range of high-quality interoperable suites separated into common stages of analysis: inspection, filtering, normalization, confounder removal, and clustering. The teaching resources cover concepts from computer science to cell biology. Access to all resources is provided at the singlecell.usegalaxy.eu portal.ConclusionsThe reproducible and training-oriented Galaxy framework provides a sustainable high-performance computing environment for users to run flexible analyses on both 10x and alternative platforms. The tutorials from the Galaxy Training Network along with the frequent training workshops hosted by the Galaxy community provide a means for users to learn, publish, and teach single-cell RNA-sequencing analysis.
Milk Components by In-Line Fiber Optic Probe-Based FT-NIR: Commercial Scale Evaluation of a Potential Alternative Measurement Approach for Milk Payment
Authors: Tang Shuaikun , Johnson J Chris , Jarto Iswandi , Smith Bridgette , Morris Scott 
Published: October 2020

Abstract

Background
Mid-infrared (MIR) spectroscopy has traditionally been used to determine the macronutrients in bovine milk, as the basis of milk payment. Recent studies have demonstrated that NIR/FT-NIR spectroscopic systems can not only achieve MIR measurement performance, but are also generally simpler, more robust, and thus much more amenable to actual industrial process applications.

Objective
The goal of this unique study was to investigate the feasibility of in-line FT-NIR spectroscopy for milk fat, protein, and total solids (TS) determination in a large industrial dairy processing facility, as an alternative basis for milk payment.

Method
Multivariant chemometric models using partial least squares (PLS) regression were built to predict the milk components. Over 1000 composite FT-NIR results gathered from the milk unloading process were compared directly to independent third-party FT-IR results.

Results
Accuracy, precision, and linearity of the method were shown by Standard Error of Prediction (SEP) and Range/SEP of individual components. The SEP for fat, protein, and TS models were 0.09, 0.11, and 0.52, respectively. Range/SEP were 25.10, 12.60, and 6.40 for fat, protein, and TS, respectively. Accuracy and precision for the three components were further evaluated by the mean differences (0.01, 0.05, and 0.51) from dairy FT-IR results and the standard deviations of the mean difference (0.09, 0.09, and 0.13). Robustness was demonstrated by evaluating milk with natural variation over 6 months and using multiple instrumentation setups. The repeatability was also evaluated.

Conclusions
Overall, the in-line FT-NIR technology was found to have accurate, reliable, consistent performance similar to dairy FT-IR technology.
Not Too Far to Help: Residential Mobility, Global Identity, and Donations to Distant Beneficiaries
Authors: Wang Yajin , Kirmani Amna , Li Xiaolin 
Published: October 2020

Abstract
Extant research shows that consumers are more likely to donate to close than distant others, making donations to geographically distant beneficiaries a challenge. This article introduces residential mobility as a novel variable that can lead to increased donations toward distant beneficiaries. This article proposes that residential mobility (vs. stability) leads consumers to have a stronger global identity, whereby they see themselves as world citizens. This global identity results in higher donations to distant beneficiaries. A multi-method approach provides evidence for this prediction. An analysis of a national panel dataset demonstrates that high residential mobility is correlated with donations to distant beneficiaries. Lab experiments, including one with real monetary donations, replicate these effects using both actual moving experience and a residential mobility mindset.