bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analytical and Clinical Considerations in Implementing the Roche Elecsys Troponin T Gen 5 STAT Assay
Authors: Donato Leslie J , Wockenfus Amy M , Katzman Brooke M , Baumann Nikola A , Jaffe Allan S , Karon Brad S 
Published: April 2021

Abstract

Objectives
To evaluate the analytical and clinical performance characteristics of the fifth-generation troponin T reagent.

Methods
Troponin T was measured in 2,332 paired serum and plasma samples from emergency department and hospital patients using the fourth- and fifth-generation reagents. Testing was repeated after recentrifugation to determine the frequency of analytical outliers and percentage of patients with elevated values for each assay. We conducted separate experiments to determine the effects of biotin and hemolysis interference, as well as measure interinstrument variability, for fifth-generation troponin T.

Results
Analytic outliers occurred more frequently using the fifth-generation reagent (3.4%) compared with the fourth-generation reagent (1.0%). The frequency of elevated troponin T above the 99th percentile upper reference limit was 26% for the fourth-generation reagent and 52% for the fifth-generation reagent. Clinically significant assay interference by biotin was observed at 20 ng/mL, but hemolysis interference was not observed until an H index of 150. Instrument-to-instrument variability between e411 and e601/602 instrument platforms is predicted to confound clinical interpretation of troponin changes.

Conclusions
Analytical outliers and instrument-to-instrument variability are the two analytical variables most likely to confound interpretation of changes in fifth-generation troponin T results over time.
Forgetting to Remember: The Impact of Post-traumatic Stress Disorder on Prospective and Retrospective Memory Performance
Authors: Korinek Dale , Resch Zachary J , Soble Jason R , Aase Darrin M , Schroth Christopher , Phan K Luan 
Published: April 2021

Abstract

Objective
We examined the impact of post-traumatic stress disorder (PTSD) on both prospective (PM) and retrospective (RM) memory performance among a cross-sectional veteran sample.

Method
Data from tests of PM/RM memory and PTSD, anxiety, depression and sleep disturbance symptoms were examined among a prospectively recruited sample of 26 veterans with confirmed PTSD (PTSD+) and 26 well-matched, combat-exposed controls who did not meet criteria for PTSD (PTSD−).

Results
Small-to-moderate negative correlations emerged between PTSD symptom severity, visuospatial RM and some aspects of PM; general anxiety correlated more strongly with memory. The PTSD+ group demonstrated significantly worse, but still average visuospatial RM; differences in PM were nonsignificant between groups. Regression analyses implicated generalized anxiety, but not other psychiatric symptomology, as significant contributors to all memory performances.

Conclusions
Minimal memory differences were found between veterans with and without PTSD. PM/RM memory performance was better explained by generalized anxiety rather that PTSD-specific symptoms.
Machine learning approach to gene essentiality prediction: a review
Authors: Aromolaran Olufemi , Aromolaran Damilare , Isewon Itunuoluwa , Oyelade Jelili 
Published: April 2021

Abstract Essential genes are critical for the growth and survival of any organism. The machine learning approach complements the experimental methods to minimize the resources required for essentiality assays. Previous studies revealed the need to discover relevant features that significantly classify essential genes, improve on the generalizability of prediction models across organisms, and construct a robust gold standard as the class label for the train data to enhance prediction. Findings also show that a significant limitation of the machine learning approach is predicting conditionally essential genes. The essentiality status of a gene can change due to a specific condition of the organism. This review examines various methods applied to essential gene prediction task, their strengths, limitations and the factors responsible for effective computational prediction of essential genes. We discussed categories of features and how they contribute to the classification performance of essentiality prediction models. Five categories of features, namely, gene sequence, protein sequence, network topology, homology and gene ontology-based features, were generated for Caenorhabditis elegans to perform a comparative analysis of their essentiality prediction capacity. Gene ontology-based feature category outperformed other categories of features majorly due to its high correlation with the genes’ biological functions. However, the topology feature category provided the highest discriminatory power making it more suitable for essentiality prediction. The major limiting factor of machine learning to predict essential genes conditionality is the unavailability of labeled data for interest conditions that can train a classifier. Therefore, cooperative machine learning could further exploit models that can perform well in conditional essentiality predictions.Short abstractIdentification of essential genes is imperative because it provides an understanding of the core structure and function, accelerating drug targets’ discovery, among other functions. Recent studies have applied machine learning to complement the experimental identification of essential genes. However, several factors are limiting the performance of machine learning approaches. This review aims to present the standard procedure and resources available for predicting essential genes in organisms, and also highlight the factors responsible for the current limitation in using machine learning for conditional gene essentiality prediction. The choice of features and ML technique was identified as an important factor to predict essential genes effectively.
MANIEA: a microbial association network inference method based on improved Eclat association rule mining algorithm
Authors: Liu Maidi , Ye Yanqing , Jiang Jiang , Yang Kewei 
Published: April 2021

Abstract

Motivation
Modeling microbiome systems as complex networks are known as the problem of network inference. Microbial association network inference is of great significance in applications on clinical diagnosis, disease treatment, pathological analysis, etc. However, most current network inference methods focus on mining strong pairwise associations between microorganisms, which is defective in reflecting the comprehensive interactive patterns participated by multiple microorganisms. It is also possible that the microorganisms involved in the generated network are not dominant in the microbiome due to the mere focus on the strength of pairwise associations. Some scholars tried to mine comprehensive microbial associations by association rule mining methods, but the adopted algorithms are relatively basic and have severe limitations such as low calculation efficiency, lacking the ability of mining negative correlations and high redundancy in results, making it difficult to mine high-quality microbial association rules and accurately infer microbial association networks.

Results
We proposed a microbial association network inference method ‘MANIEA’ based on the improved Eclat algorithm for mining positive and negative microbial association rules. We also proposed a new method for transforming association rules into microbial association networks, which can effectively demonstrate the co-occurrence and causal correlations in association rules. An experiment was conducted on three authentic microbial abundance datasets to compare the ‘MANIEA’ with currently popular network inference methods, which demonstrated that the proposed ‘MANIEA’ show advantages in aspects of correlation forms, computation efficiency, adjustability and network characteristics.

Availability and implementation
The algorithms and data are available at: https://github.com/MaidiL/MANIEA.
Dopaminergic restoration of prefrontal cortico-putaminal network in gene therapy for aromatic l-amino acid decarboxylase deficiency
Authors: Onuki Yoshiyuki , Ono Sayaka , Nakajima Takeshi , Kojima Karin , Taga Naoyuki , Ikeda Takahiro , Kuwajima Mari , Kurokawa Yoshie , Kato Mitsuhiro , Kawai Kensuke , Osaka Hitoshi , Sato Toshihiko , Muramatsu Shin-ichi , Yamagata Takanori 
Published: April 2021

Abstract
Aromatic l-amino acid decarboxylase (AADC) is an essential dopamine-synthesizing enzyme. In children with AADC deficiency, the gene delivery of AADC into the putamen, which functionally interacts with cortical regions, was found to improve motor function and ameliorate dystonia. However, how the restoration of dopamine in the putamen in association with cortico-putaminal networks leads to therapeutic effects remains unclear. Here, we examined neuroimaging data of eight patients with AADC deficiency (five males and three females, age range 4–19 years) who received the AADC gene therapy of the bilateral putamen in an open-label phase 1/2 study. Using high-resolution positron emission tomography with a specific AADC tracer, 6-[18F]fluoro-l-m-tyrosine (FMT), we showed that FMT uptake increased in the broad area of the putamen over the years. Then, with the structural connectivity-based parcellation of the putaminal area, we found that motor improvement is associated with dopaminergic restoration of the putaminal area that belongs to the prefrontal cortico-putaminal network. The prefrontal area dominantly belongs to the frontoparietal control network, which contributes to cognitive-motor control function, including motor initiation and planning. The results suggest that putaminal dopamine promotes the development of an immature motor control system, particularly in the human prefrontal cortex that is primarily affected by AADC deficiency.
Harmonization of LC-MS/MS Measurements of Plasma Free Normetanephrine, Metanephrine, and 3-Methoxytyramine
Authors: Peitzsch Mirko , Novos Talia , Kaden Denise , Kurlbaum Max , van Herwaarden Antonius E , Müller Daniel , Adaway Jo , Grouzmann Eric , McWhinney Brett , Hoad Kirsten , Woollard Gerald , Kema Ido , Boot Christopher , Fassnacht Martin , Sweep Fred , Loh Tze P , Horvath Andrea R , Eisenhofer Graeme 
Published: April 2021

Abstract

Background
Plasma-free normetanephrine and metanephrine (metanephrines) are the recommended biomarkers for testing of pheochromocytoma and paraganglioma (PPGL). This study evaluated the status of harmonization of liquid chromatography-tandem mass spectrometry-based measurements of plasma metanephrines and methoxytyramine and clinical interpretation of test results.

Methods
125 plasma samples from patients tested for PPGLs were analyzed in 12 laboratories. Analytical performance was also assessed from results of a proficiency-testing program. Agreement of test results from different laboratories was assessed by Passing-Bablok regression and Bland-Altman analysis. Agreement in clinical test interpretation based on laboratory specific reference intervals was also examined.

Results
Comparisons of analytical test results by regression analysis revealed strong correlations for normetanephrine and metanephrine (R ≥ 0.95) with mean slopes of 1.013 (range 0.975–1.078), and 1.019 (range 0.963–1.081), and intercepts of −0.584 (−53.736 to 54.790) and −3.194 (−17.152 to 5.933), respectively. The mean bias between methods was 1.2% (−11.6% to 16.0%) for metanephrine and 0.1% (−18.0% to 9.5%) for normetanephrine. Measurements of 3-methoxytyramine revealed suboptimal agreement between laboratories with biases ranging from −32.2% to 64.0%. Interrater agreement in test interpretation was &gt;94% for metanephrine and &gt;84% for normetanephrine; improvements in interrater agreement were observed with use of harmonized reference intervals, including age-specific cut-offs for normetanephrine.

Conclusions
Analytical methods for metanephrines are well harmonized between laboratories. However, the 16% disagreement in test interpretation for normetanephrine suggests use of suboptimal method-dependent reference intervals for clinical decision-making for this metabolite. Improved analytical methods and reference interval harmonization are particularly required for 3-methoxytyramine.
Cost-effectiveness calculators for health, well-being and safety promotion: a systematic review
Authors: Hult Marja , Halminen Olli , Linna Miika , Suominen Sakari , Kangasniemi Mari 
Published: April 2021

Abstract

Background
The health, well-being and safety of the general population are important goals for society, but forecasting outcomes and weighing up the costs and benefits of effective promotional programmes is challenging. This study aimed to identify and describe the cost-effectiveness calculators that analyze interventions that promote health, well-being and safety.

Methods
Our systematic review used the CINAHL, PsycINFO, SocINDEX, EconLit, PubMed and Scopus databases to identify peer-reviewed studies published in English between January 2010 and April 2020. The data were analyzed with narrative synthesis.

Results
The searches identified 6880 papers and nine met our eligibility and quality criteria. All nine calculators focussed on interventions that promoted health and well-being, but no safety promotion tools were identified. Five calculators were targeted at group-level initiatives, two at regional levels and two at national levels. The calculators combined different data sources, in addition to data inputted by users. This included empirical research and previous literature. The calculators created baseline estimates and assessed the cost-effectiveness of the interventions before or after they were implemented. The calculators were heterogeneous in terms of outcomes, the interventions they evaluated and the data and methods used.

Conclusion
This review identified nine calculators that assessed the cost-effectiveness of health and well-being interventions and supported decision-making and resource allocations at local, regional and national levels, but none focussed on safety. Producing calculators that work accurately in different contexts might be challenging. Further research should identify how to assess sustainable evaluation of health, well-being and safety strategies.
Quantifying the precision of forest stand height and canopy cover estimates derived from air photo interpretation
Authors: Tompalski Piotr , White Joanne C , Coops Nicholas C , Wulder Michael A , Leboeuf Antoine , Sinclair Ian , Butson Christopher R , Lemonde Marc-Olivier 
Published: April 2021

Abstract
Quality information on forest resources is fundamental for sustainable forest management. Manual aerial photointerpretation is used as a cost-effective source of data for forest inventories; however, the process of photointerpretation is inherently subjective and is often undertaken by multiple photointerpreters for a given forest management area. In contrast, airborne laser scanning (ALS) data enable characterization of forest structure in a systematic fashion with quantifiable levels of accuracy and precision that often exceed required targets and standards. However, the gains associated with the use of new technologies for forest inventory are difficult to measure because the quality of existing photointepreted inventories have rarely been quantified. Using ALS data as reference, the objective of this study was to quantify the precision of photointerpreted estimates of forest stand height and canopy cover (CC). We examined forest inventories from three study sites in three different forest regions of Canada. Each of the study sites was located within a different provincial jurisdiction with unique photointerpretation standards and forest ecosystems. Stand-level estimates of forest height and cover were compared to reference estimates generated from the ALS data. Overall, our results indicated that precision was greater for photointerpreted estimates of height, with a relative standard deviation ranging from 22 per cent to 29 per cent among our three sites, compared to estimates for CC, with precision ranging from 28 per cent to 59 per cent. While the relationship between photointerpreted estimates of height and ALS estimates of height were generally linear and consistent for all study sites, relationships for CC were non-linear. We found that precision for both stand height and cover varied by dominant species, inventory stand structure, age, and ALS canopy complexity, and that in the majority of cases, the differences between the photointerpreted estimate and the ALS estimate were statistically significant. It is also noted that the variability in photointerpretation precision as a function of the aforementioned factors was not consistent among our three study sites, indicating that site-specific forest conditions and photointerpretation procedures influence the precision of photointerpreted estimates. The influence of local forest conditions and interpretation procedures are therefore important considerations when seeking to quantify the potential relative gains in precision, which may be afforded by technologies such as ALS for forest inventory programs. Moreover, approaches to improve consistency in photointerpreted estimates of cover would be useful for operational inventory programs.
Tree-level Growth of Four Oak Species in a Bottomland Hardwood Plantation: Implications for Silvicultural Treatments
Authors: Hossain Shaik M , Olson Matthew G , Bataineh Mohammad 
Published: April 2021

Abstract
A 41-year-old bottomland hardwood plantation experiment located in southeastern Arkansas was revisited in 2017 to evaluate basal area increment (BAI) of four oak species [cherrybark oak (Quercus pagoda Raf.), swamp chestnut oak (Q. michauxii Nutt.), Nuttall oak (Q. texana Buckl.), and water oak (Q. nigra L.)] planted in monoculture in relation with species, spacing, thinning, and neighborhood competition. Species had a significant effect on BAI (P = 0.04), with cherrybark oak and Nuttall oak demonstrating the greatest (21.5 ± 2.5 cm2 year−1) and lowest (12.7 ± 2.9 cm2 year−1) growth rates, respectively, whereas BAI declined significantly with increasing competition (P = 0.03). However, rates of growth decline with competition did not differ between species (P &gt; 0.05 for competition × species term), and thinning and spacing treatments had no effect on BAI (P &gt; 0.05). We recommend that repetitive thinning, rather than a single thinning, would be appropriate to maintain a positive impact on oak growth. Managing stand density would not only provide opportunities for improving timber production, but also would enhance ecological benefits (e.g., wildlife habitat) through diversification of structure within monoculture plantations.
Evaluating Long-Term Seedling Growth Across Densities Using Nelder Plots and the Forest Vegetation Simulator (FVS) in the Black Hills, South Dakota, USA
Authors: Tinkham Wade T , Battaglia Mike A , Hoffman Chad M 
Published: April 2021

Abstract
Small-tree development affects future stand dynamics and dictates many ecological processes within a site. Accurately representing this critical component of stand development is important for evaluating treatment alternatives from fuel hazard reduction to harvest scheduling. As with all forest growth, competition with other vegetation is known to regulate small-tree growth dynamics. This study uses three Nelder plots with 45 years of ponderosa pine growth to understand competition effects on seedling growth and evaluate the Forest Vegetation Simulator (FVS) Central Rockies (CR) variant’s ability to represent these dynamics. Removal of herbaceous competition before planting increased tree diameters by 50–135% and height by 35–75% across a planting density gradient at age 12. However, by age 45, the effect of herbaceous competition on tree size was no longer evident. Instead, trees at the lowest planting density had diameters 2.5–3 times larger than the most densely grown trees. Forest Vegetation Simulator (FVS) simulations underpredicted diameter at breast height (dbh) by 35–50% and 0–35% for 12 and 45-year-old trees, respectively. There was an underprediction bias of 15–20% for heights at age 12 and overpredictions of 5–10% at age 45. Continuous underprediction of dbh will affect the reliability of modeled fuel treatment longevity and sustainable harvest scheduling.
The Complete Nucleotide Sequence of the Mitochondrial Genome of the Lungfish (Protopterus dolloi) Supports Its Phylogenetic Position as a Close Relative of Land Vertebrates
Authors: Zardoya Rafael , Meyer Axel 
Published: April 2021

Abstract
The complete DNA sequence (16,646 bp) of the mitochondrial genome of the African lungfish, Protopterus dolloi, was determined. The evolutionary position of lungfish as possibly the closest living relative among fish of land vertebrates made its mitochondrial DNA sequence particularly interesting. Its mitochondrial gene order conforms to the consensus vertebrate gene order. Several sequence motifs and secondary structures likely involved in the regulation of the initiation of replication and transcription of the mitochondrial genome are conserved in the lungfish and are more similar to those of land vertebrates than those of ray-finned fish. A novel feature discovered is that the putative origin of L-strand replication partially overlaps the adjacent tRNAcys. The phylogenetic analyses of genes coding for tRNAs and proteins confirm the intermediate phylogenetic position of lungfish between ray-finned fishes and tetrapods. The complete nucleotide sequence of the African lungfish mitochondrial genome was used to estimate which mitochondrial genes are most appropriate to elucidate deep branch phylogenies. Only a combined set of either protein or tRNA mitochondrial genes (but not each gene alone) is able to confidently recover the expected phylogeny among vertebrates that have diverged up to but not over ~400 mya.
Mitochondrial DNA Analysis of Mongolian Populations and Implications for the Origin of New World Founders
Authors: Kolman Connie J , Sambuughin Nyamkhishig , Bermingham Eldredge 
Published: April 2021

Abstract
High levels of mitochondrial DNA (mtDNA) diversity were determined for Mongolian populations, represented by the Mongol-speaking Khalkha and Dariganga. Although 103 samples were collected across Mongolia, low levels of genetic substructuring were detected, reflecting the nomadic lifestyle and relatively recent ethnic differentiation of Mongolian populations. mtDNA control region I sequence and seven additional mtDNA polymorphisms were assayed to allow extensive comparison with previous human population studies. Based on a comparative analysis, we propose that indigenous populations in east Central Asia represent the closest genetic link between Old and New World populations. Utilizing restriction/deletion polymorphisms, Mongolian populations were found to carry all four New World founding haplogroups as defined by Wallace and coworkers. The ubiquitous presence of the four New World haplogroups in the Americas but narrow distribution across Asia weakens support for Greenberg and coworkers' theory of New World colonization via three independent migrations. The statistical and geographic scarcity of New World haplogroups in Asia makes it improbable that the same four haplotypes would be drawn from one geographic region three independent times. Instead, it is likely that founder effects manifest throughout Asia and the Americas are responsible for differences in mtDNA haplotype frequencies observed in these regions.