bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fast parallel construction of variable-length Markov chains
Authors: Gustafsson Joel , Norberg Peter , Qvick-Wester Jan R. , Schliep Alexander 
Published: October 2021

Abstract
Background
Alignment-free methods are a popular approach for comparing biological sequences, including complete genomes. The methods range from probability distributions of sequence composition to first and higher-order Markov chains, where a k-th order Markov chain over DNA has $$4^k$$

4
k

formal parameters. To circumvent this exponential growth in parameters, variable-length Markov chains (VLMCs) have gained popularity for applications in molecular biology and other areas. VLMCs adapt the depth depending on sequence context and thus curtail excesses in the number of parameters. The scarcity of available fast, or even parallel software tools, prompted the development of a parallel implementation using lazy suffix trees and a hash-based alternative.

Results
An extensive evaluation was performed on genomes ranging from 12Mbp to 22Gbp. Relevant learning parameters were chosen guided by the Bayesian Information Criterion (BIC) to avoid over-fitting. Our implementation greatly improves upon the state-of-the-art even in serial execution. It exhibits very good parallel scaling with speed-ups for long sequences close to the optimum indicated by Amdahl’s law of 3 for 4 threads and about 6 for 16 threads, respectively.

Conclusions
Our parallel implementation released as open-source under the GPLv3 license provides a practically useful alternative to the state-of-the-art which allows the construction of VLMCs even for very large genomes significantly faster than previously possible. Additionally, our parameter selection based on BIC gives guidance to end-users comparing genomes.
Hsa-mir-548 family expression in human reproductive tissues
Authors: Rooda Ilmatar , Kaselt Birgitta , Liivrand Maria , Smolander Olli-Pekka , Salumets Andres , Velthut-Meikas Agne 
Published: October 2021

Abstract
Background
Hsa-miR-548ba expressed in ovarian granulosa cells targets PTEN and LIFR, which are essential for ovarian follicle activation and growth. The expression pattern of hsa-miR-548ba correlates with its host gene follicle-stimulating hormone receptor (FSHR), and FSH has a positive influence on hsa-miR-548ba expression. However, hsa-miR-548ba is a member of a large hsa-mir-548 family with potentially overlapping targets. The current study aims to investigate the co-expression of hsa-mir-548 family members in FSHR-positive reproductive tissues and to explore the potential co-regulation of pathways.

Results
For the above-described analysis, small RNA sequencing data from public data repositories were used. Sequencing results revealed that hsa-miR-548ba was expressed at the highest level in the ovarian granulosa cells and uterine myometrial samples together with another twelve and one hsa-miR-548 family members, respectively. Pathway enrichment analysis of microRNA targets in the ovarian samples revealed the hsa-miR-548ba and hsa-miR-548b-5p co-regulation of RAB geranylgeranylation in mural granulosa cells. Moreover, other hsa-mir-548 family members co-regulate pathways essential for ovarian functions (PIP3 activates AKT signalling and signalling by ERBB4). In addition to hsa-miR-548ba, hsa-miR-548o-3p is expressed in the myometrium, which separately targets the peroxisome proliferator-activated receptor alpha (PPARA) pathway.

Conclusion
This study reveals that hsa-mir-548 family members are expressed in variable combinations in the reproductive tract, where they potentially fulfil different regulatory roles. The results provide a reference for further studies of the hsa-mir-548 family role in the reproductive tract.
Difference in left atrial D-dimer level in patients with atrial fibrillation treated with direct oral anticoagulant
Authors: Watanabe Tetsuya , Tachibana Koichi , Shinoda Yukinori , Minamisaka Tomoko , Fukuoka Hidetada , Inui Hirooki , Ueno Keisuke , Inoue Souki , Mine Kentaro , Hoshida Shiro 
Published: October 2021

Abstract
Background
Atrial fibrillation (AF) may cause cerebral and systemic embolism. An increased D-dimer level indicates hyperactivation of secondary fibrinolysis, resulting in predilection for thrombosis. To clarify the differential effects of anticoagulation therapy, we compared the D-dimer levels in peripheral and left atrial (LA) blood of atrial fibrillation patients scheduled for ablation.

Methods
We analyzed 141 patients with non-valvular AF (dabigatran, n = 30; apixaban, n = 47; edoxaban, n = 64; mean age: 68 years, male: 60%). Peripheral venous blood and LA blood was collected before pulmonary vein isolation. We examined the laboratory and echocardiographic parameters.

Results
After adjusting for baseline characteristics, D-dimer level in the LA was significantly higher in patients treated with edoxaban than that in those on apixaban (0.77 ± 0.05 vs. 0.60 ± 0.05 μg/mL, P = 0.047), although there were no significant differences in peripheral D-dimer levels. We classified the D-dimer value of the LA into a normal group (< 0.9) and a high value group (≥ 1.0); the peripheral prothrombin fragment F1 + 2 level (odds ratio [OR] 1.012; 95% confidence interval [CI]: 1.003–1.022; P = 0.008) and left ventricular ejection fraction (LVEF) (OR, 0.947; 95% CI, 0.910–0.986; P = 0.008) were potential predictors of high LA D-dimer levels.

Conclusions
In apixaban-treated patients, the D-dimer level in the left atrium was lower than in edoxaban-treated patients on the day of ablation, suggesting that the anticoagulant effect of apixaban on the left atrium is better than that of edoxaban in patients with AF.
Development of a target product profile for a point-of-care cardiometabolic device
Authors: Vetter Beatrice , Beran David , Boulle Philippa , Chua Arlene , de la Tour Roberto , Hattingh Lucy , Perel Pablo , Roglic Gojka , Sampath Rangarajan , Woodman Michael , Perone Sigiriya Aebischer 
Published: October 2021

Abstract
Introduction
Multi-parameter diagnostic devices can simplify cardiometabolic disease diagnosis. However, existing devices may not be suitable for use in low-resource settings, where the burden of non-communicable diseases is high. Here we describe the development of a target product profile (TPP) for a point-of-care multi-parameter device for detection of biomarkers for cardiovascular disease and metabolic disorders, including diabetes, in primary care settings in low- and middle-income countries (LMICs).

Methods
A draft TPP developed by an expert group was reviewed through an online survey and semi-structured expert interviews to identify device characteristics requiring refinement. The draft TPP included 41 characteristics with minimal and optimal requirements; characteristics with an agreement level for either requirement of ≤ 85% in either the survey or among interviewees were further discussed by the expert group and amended as appropriate.

Results
Twenty people responded to the online survey and 18 experts participated in the interviews. Twenty-two characteristics had an agreement level of ≤ 85% in either the online survey or interviews. The final TPP defines the device as intended to be used for basic diagnosis and management of cardiometabolic disorders (lipids, glucose, HbA1c, and creatinine) as minimal requirement, and offering an expanded test menu for wider cardiometabolic disease management as optimal requirement. To be suitable, the device should be intended for level 1 healthcare settings or lower, used by minimally trained healthcare workers and allow testing using self-contained cartridges or strips without the need for additional reagents. Throughput should be one sample at a time in a single or multi-analyte cartridge, or optimally enable testing of several samples and analytes in parallel with random access.

Conclusion
This TPP will inform developers of cardiometabolic multi-parameter devices for LMIC settings, and will support decision makers in the evaluation of existing and future devices.
Assessment of breathing in cardiac arrest: a randomised controlled trial of three teaching methods among laypersons
Authors: Breindahl Niklas , Granholm Anders , Jensen Theo Walther , Ersbøll Annette Kjær , Myklebust Helge , Lippert Freddy , Lippert Anne 
Published: October 2021

Abstract
Background
The aim of this trial was to compare a video- and a simulation-based teaching method to the conventional lecture-based method, hypothesizing that the video- and simulation-based teaching methods would lead to improved recognition of breathing patterns during cardiac arrest.

Methods
In this Danish, investigator-initiated, stratified, randomised controlled trial, adult laypersons (university students, military conscripts and elderly retirees) participating in European Resuscitation Council Basic Life Support courses were randomised to receive teaching on how to recognise breathing patterns using a lecture- (usual practice), a video-, or a simulation-based teaching method. The primary outcome was recognition of breathing patterns in nine videos of actors simulating normal breathing, no breathing, and agonal breathing (three of each). We analysed outcomes using logistic regression models and present results as odds ratios (ORs) with 95% confidence intervals (CIs) and P-values from likelihood ratio tests.

Results
One hundred fifty-three participants were included in the analyses from February 2, 2018 through May 21, 2019 and recognition of breathing patterns was statistically significantly different between the teaching methods (P = 0.013). Compared to lecture-based teaching (83% correct answers), both video- (90% correct answers; OR 1.77, 95% CI: 1.19–2.64) and simulation-based teaching (88% correct answers; OR 1.48; 95% CI: 1.01–2.17) led to significantly more correct answers. Video-based teaching was not statistically significantly different compared to simulation-based teaching (OR 1.20; 95% CI: 0.78–1.83).

Conclusion
Video- and simulation-based teaching methods led to improved recognition of breathing patterns among laypersons participating in adult Basic Life Support courses compared to the conventional lecture-based teaching method.
Methods for the inclusion of real-world evidence in network meta-analysis
Authors: Jenkins David A. , Hussein Humaira , Martina Reynaldo , Dequen-O’Byrne Pascale , Abrams Keith R. , Bujkiewicz Sylwia 
Published: October 2021

Abstract
Background
Network Meta-Analysis (NMA) is a key component of submissions to reimbursement agencies world-wide, especially when there is limited direct head-to-head evidence for multiple technologies from randomised controlled trials (RCTs). Many NMAs include only data from RCTs. However, real-world evidence (RWE) is also becoming widely recognised as a valuable source of clinical data. This study aims to investigate methods for the inclusion of RWE in NMA and its impact on the level of uncertainty around the effectiveness estimates, with particular interest in effectiveness of fingolimod.

Methods
A range of methods for inclusion of RWE in evidence synthesis were investigated by applying them to an illustrative example in relapsing remitting multiple sclerosis (RRMS). A literature search to identify RCTs and RWE evaluating treatments in RRMS was conducted. To assess the impact of inclusion of RWE on the effectiveness estimates, Bayesian hierarchical and adapted power prior models were applied. The effect of the inclusion of RWE was investigated by varying the degree of down weighting of this part of evidence by the use of a power prior.

Results
Whilst the inclusion of the RWE led to an increase in the level of uncertainty surrounding effect estimates in this example, this depended on the method of inclusion adopted for the RWE. ‘Power prior’ NMA model resulted in stable effect estimates for fingolimod yet increasing the width of the credible intervals with increasing weight given to RWE data. The hierarchical NMA models were effective in allowing for heterogeneity between study designs, however, this also increased the level of uncertainty.

Conclusion
The ‘power prior’ method for the inclusion of RWE in NMAs indicates that the degree to which RWE is taken into account can have a significant impact on the overall level of uncertainty. The hierarchical modelling approach further allowed for accommodating differences between study types. Consequently, further work investigating both empirical evidence for biases associated with individual RWE studies and methods of elicitation from experts on the extent of such biases is warranted.
Need-based care of multi-morbid patients – supporting general practitioners with algorithm-generated recommendations of healthcare services (telemedicine-project ATMoSPHÄRE)
Authors: Borchers Peggy , Piller Steve , Böhme Mandy , Voigt Karen , Bergmann Antje 
Published: October 2021

Abstract
Background
The patient-oriented and need-based care of multi-morbid patients with healthcare services and assistive products can be a highly complex task for the general practitioners (GPs). An algorithm-based digital recommendation system (DRS) for healthcare services was developed within the context of the telemedicine research project ATMoSPHÄRE. The plausibility of the DRS was tested and the results used to examine if, and to what degree, the DRS provides useful assistance to GPs.

Methods
The plausibility of the recommendations of the DRS were tested with the Delphi procedure (n = 8) and Interviews (n = 4) in collaboration with the GPs. They proposed services and assistive products they considered appropriate for two multi-morbid patients. Furthermore, GPs had to report whether, and to what degree they deemed the algorithm-generated recommendations appropriate. Significant quantitative differences between the GPs’, and the algorithm-generated, recommendations were evaluated with paired-samples-Wilcoxon-test.

Results
The first Delphi round revealed a high variability regarding the amount and character of services recommended by the physicians (1 to 10 recommendations, mean = 5.6, sd = 2.8). These professional recommendations converged after consideration of the algorithm-generated recommendations. The number of algorithm-generated recommendations which were judged as appropriate ranged between 7 and 17 of a total of 20 (mean = 11.9, sd = 2.5). The interviews revealed that the additional algorithm-generated recommendations which were judged appropriate contained mainly social care services.

Conlusion
The DRS provides GPs with additional appropriate recommendations for the need-based care of patients, which may not have been previously considered. It can therefore be assessed as a helpful complement in the primary care of multi-morbid patients.
Early detection of anaemia in primary care with haemoglobinometry: ANHEMOG clinical trial protocol
Authors: Luengo Boris Trenado , García-Sierra Rosa , Trinxant Maria Asunción Wilke , Mondelo Esther Díaz , Baseda Ramon Miralles , Blanch Maria Magdalena Lladó , del Pilar Montero Alia Maria , Toran-Monserrat Pere 
Published: October 2021

Abstract

Background
Detecting, treating and monitoring anaemia has a functional, social and economic impact on patients’ quality of life and the health system, since inadequate monitoring can lead to more accident & emergency visits and hospitalizations. The aim of this study is to evaluate the impact in the patient clinical outcomes of using haemoglobinometry to early detect anaemia in patients with chronic anaemia in primary care.

Methods
Randomized controlled trial Capillary haemoglobin will be measured using a haemoglobinometer on a monthly basis in the intervention group. In the control group, the protocol currently in force at the primary care centre will be followed and venous haemoglobin will be measured. Any cases of anaemia detected in either group will be referred to the transfusion circuit of the reference hospital.

Discusion
The results will shed light on the impact of the intervention on the volume of hospitalizations and accident & emergency (A&E) visits due to anaemia, as well as patients’ quality of life. Chronic and repeated bouts of anaemia are detected late, thus leading to decompensation in chronic diseases and, in turn, more A&E visits and hospitalizations. The intervention should improve these outcomes since treatment could be performed without delay. Improving response times would decrease decompensation in chronic diseases, as well as A&E visits and hospitalizations, and improve quality of life. The primary care nurse case manager will perform the intervention, which should improve existing fragmentation between different care levels.

Trial registration
NCT04757909. Registered 17 February 2021. Retrospectively registered.
Letter to editor: is laboratory index really a practical and valid tool to predict mortality?
Authors: Oytun Merve Güner , Ercan Polat , Ceylan Serdar , Baş Arzu Okyar , Halil Meltem , Cankurtaran Mustafa , Doğu Burcu Balam 
Published: October 2021

AbstractWe carefully studied the article titled “A practical laboratory index to predict institutionalization and mortality – an 18-year population-based follow-up study” written by Heikkilä et al. and published in BMC Geriatrics on 25 February 2021 with great interest. We would like to make some comments regarding this article and tool. Laboratory Index (LI) has been executed with the data of 728 patients who had followed-up in our center, however the LI score was not able to predict the 10-year and 18-year mortality. Therefore, a question mark has been aroused in our minds at some points. Neither frailty nor comorbidities were considered in this index. For a geriatric patient, it would be inadequate to evaluate laboratory results regardless of the clinical status. Similarly, it would not be appropriate to predict mortality only on the basis of laboratory results without considering the clinical status of the patient.We think that although the recent study has a great impact, it can be improved by incorporating data on the comorbidities and frailty status of the patients into the analysis.
Image quality assessment of pediatric chest and abdomen CT by deep learning reconstruction
Authors: Yoon Haesung , Kim Jisoo , Lim Hyun Ji , Lee Mi-Jung 
Published: October 2021

Abstract
Background
Efforts to reduce the radiation dose have continued steadily, with new reconstruction techniques. Recently, image denoising algorithms using artificial neural networks, termed deep learning reconstruction (DLR), have been applied to CT image reconstruction to overcome the drawbacks of iterative reconstruction (IR). The purpose of our study was to compare the objective and subjective image quality of DLR and IR on pediatric abdomen and chest CT images.

Methods
This retrospective study included pediatric body CT images from February 2020 to October 2020, performed on 51 patients (34 boys and 17 girls; age 1–18 years). Non-contrast chest CT (n = 16), contrast-enhanced chest CT (n = 12), and contrast-enhanced abdomen CT (n = 23) images were included. Standard 50% adaptive statistical iterative reconstruction V (ASIR-V) images were compared to images with 100% ASIR-V and DLR at medium and high strengths. Attenuation, noise, contrast to noise ratio (CNR), and signal to noise (SNR) measurements were performed. Overall image quality, artifacts, and noise were subjectively assessed by two radiologists using a four-point scale (superior, average, suboptimal, and unacceptable). A phantom scan was performed including the dose range of the clinical images used in our study, and the noise power spectrum (NPS) was calculated. Quantitative and qualitative parameters were compared using repeated-measures analysis of variance (ANOVA) with Bonferroni correction and Wilcoxon signed-rank tests.

Results
DLR had better CNR and SNR than 50% ASIR-V in both pediatric chest and abdomen CT images. When compared with 50% ASIR-V, high strength DLR was associated with noise reduction in non-contrast chest CT (33.0%), contrast-enhanced chest CT (39.6%), and contrast-enhanced abdomen CT (38.7%) with increases in CNR at 149.1%, 105.8%, and 53.1% respectively. The subjective assessment of overall image quality and the noise was also better on DLR images (p < 0.001). However, there was no significant difference in artifacts between reconstruction methods. From NPS analysis, DLR methods showed a pattern of reducing the magnitude of noise while maintaining the texture.

Conclusion
Compared with 50% ASIR-V, DLR improved pediatric body CT images with significant noise reduction. However, artifacts were not improved by DLR, regardless of strength.
Rationale and design of the Diet Restriction and Exercise-induced Adaptations in Metastatic breast cancer (DREAM) study: a 2-arm, parallel-group, phase II, randomized control trial of a short-term, calorie-restricted, and ketogenic diet plus exercise during intravenous chemotherapy versus usual care
Authors: Kirkham Amy A. , King Karen , Joy Anil A. , Pelletier André B. , Mackey John R. , Young Kelvin , Zhu Xiaofu , Meza-Junco Judith , Basi Sanraj K. , Hiller Julie Price , Brkin Tina , Michalowski Bonnie , Pituskin Edith , Paterson D. Ian , Courneya Kerry S. , Thompson Richard B. , Prado Carla M. 
Published: October 2021

Abstract
Background
An underlying cause of solid tumor resistance to chemotherapy treatment is diminished tumor blood supply, which leads to a hypoxic microenvironment, dependence on anaerobic energy metabolism, and impaired delivery of intravenous treatments. Preclinical data suggest that dietary strategies of caloric restriction and low-carbohydrate intake can inhibit glycolysis, while acute exercise can transiently enhance blood flow to the tumor and reduce hypoxia. The Diet Restriction and Exercise-induced Adaptations in Metastatic Breast Cancer (DREAM) study will compare the effects of a short-term, 50% calorie-restricted and ketogenic diet combined with aerobic exercise performed during intravenous chemotherapy treatment to usual care on changes in tumor burden, treatment side effects, and quality of life.

Methods
Fifty patients with measurable metastases and primary breast cancer starting a new line of intravenous chemotherapy will be randomly assigned to usual care or the combined diet and exercise intervention. Participants assigned to the intervention group will be provided with food consisting of 50% of measured calorie needs with 80% of calories from fat and ≤ 10% from carbohydrates for 48–72 h prior to each chemotherapy treatment and will perform 30–60 min of moderate-intensity cycle ergometer exercise during each chemotherapy infusion, for up to six treatment cycles. The diet and exercise durations will be adapted for each chemotherapy protocol. Tumor burden will be assessed by change in target lesion size using axial computed tomography (primary outcome) and magnetic resonance imaging (MRI)-derived apparent diffusion coefficient (secondary outcome) after up to six treatments. Tertiary outcomes will include quantitative MRI markers of treatment toxicity to the heart, thigh skeletal muscle, and liver, and patient-reported symptoms and quality of life. Exploratory outcome measures include progression-free and overall survival.

Discussion
The DREAM study will test a novel, short-term diet and exercise intervention that is targeted to mechanisms of tumor resistance to chemotherapy. A reduction in lesion size is likely to translate to improved cancer outcomes including disease progression and overall survival. Furthermore, a lifestyle intervention may empower patients with metastatic breast cancer by actively engaging them to play a key role in their treatment.

Trial registration
ClinicalTrials.gov, NCT03795493, registered 7 January, 2019.