bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Incidence of Acute Kidney Injury and Its Effect on Neonatal and Pediatric Extracorporeal Membrane Oxygenation Outcomes: A Multicenter Report From the Kidney Intervention During Extracorporeal Membrane Oxygenation Study Group
Authors: Fleming Geoffrey M. , Sahay Rashmi , Zappitelli Michael , King Eileen , Askenazi David J. , Bridges Brian C. , Paden Matthew L. , Selewski David T. , Cooper David S. 
Published: October 2016

Objective:
In a population of neonatal and pediatric patients on extracorporeal membrane oxygenation; to describe the prevalence and timing of acute kidney injury utilizing a consensus acute kidney injury definition and investigate the association of acute kidney injury with outcomes (length of extracorporeal membrane oxygenation and mortality).

Design:
Multicenter retrospective observational cohort study.

Setting:
Six pediatric extracorporeal membrane oxygenation centers.

Patients:
Pediatric patients (age, < 18 yr) on extracorporeal membrane oxygenation at six centers during a period of January 1, 2007, to December 31, 2011.

Interventions:
None.

Measurements and Main Results:
Complete data were analyzed for 832 patients on extracorporeal membrane oxygenation. Sixty percent of patients had acute kidney injury utilizing the serum creatinine Kidney Disease Improving Global Outcomes criteria (AKISCr) and 74% had acute kidney injury using the full Kidney Disease Improving Global Outcomes criteria including renal support therapy (AKISCr + RST). Of those who developed acute kidney injury, it was present at extracorporeal membrane oxygenation initiation in a majority of cases (52% AKISCr and 65% AKISCr + RST) and present by 48 hours of extracorporeal membrane oxygenation support in 86% (AKISCr) and 93% (AKISCr + RST). When adjusted for patient age, center of support, mode of support, patient complications and preextracorporeal membrane oxygenation pH, the presence of acute kidney injury by either criteria was associated with a significantly longer duration of extracorporeal membrane oxygenation support (AKISCr, 152 vs 110 hr; AKISCr + RST, 153 vs 99 hr) and increased adjusted odds of mortality at hospital discharge (AKISCr: odds ratio, 1.77; 1.22–2.55 and AKISCr + RST: odds ratio, 2.50; 1.61–3.90). With the addition of renal support therapy to the model, acute kidney injury was associated with a longer duration of extracorporeal membrane oxygenation support (AKISCr, 149 vs 121 hr) and increased risk of mortality at hospital discharge (AKISCr: odds ratio, 1.52; 1.04–2.21).

Conclusion:
Acute kidney injury is present in 60–74% of neonatal-pediatric patients supported on extracorporeal membrane oxygenation and is present by 48 hours of extracorporeal membrane oxygenation support in 86–93% of cases. Acute kidney injury has a significant association with increased duration of extracorporeal membrane oxygenation support and increased adjusted odds of mortality at hospital discharge.
A Novel Electrocardiogram Algorithm Utilizing ST-Segment Instability for Detection of Cardiopulmonary Arrest in Single Ventricle Physiology: A Retrospective Study
Authors: Vu Eric L. , Rusin Craig G. , Penny Dan J. , Kibler Kathy K. , Easley Ronald Blaine , Smith Brendan , Andropoulos Dean , Brady Ken 
Published: October 2016

Objective:
We evaluated ST-segment monitoring to detect clinical decompensation in infants with single ventricle anatomy. We proposed a signal processing algorithm for ST-segment instability and hypothesized that instability is associated with cardiopulmonary arrests.

Design:
Retrospective, observational study.

Setting:
Tertiary children’s hospital 21-bed cardiovascular ICU and 36-bed step-down unit.

Patients:
Twenty single ventricle infants who received stage 1 palliation surgery between January 2013 and January 2014. Twenty rapid response events resulting in cardiopulmonary arrests (arrest group) were recorded in 13 subjects, and nine subjects had no interstage cardiopulmonary arrest (control group).

Interventions:
None.

Measurements and Main Results:
Arrest data were collected over the 4-hour time window prior to cardiopulmonary arrest. Control data were collected from subjects with no interstage arrest using the 4-hour time window prior to cardiovascular ICU discharge. A paired subgroup analysis was performed comparing subject 4-hour windows prior to arrest (prearrest group) with 4-hour windows prior to discharge (postarrest group). Raw values of ST segments were compared between groups. A 3D ST-segment vector was created using three quasi-orthogonal leads (II, aVL, and V5). Magnitude and instability of this continuous vector were compared between groups. There was no significant difference in mean unprocessed ST-segment values in the arrest and control groups. Utilizing signal processing, there was an increase in the ST-vector magnitude (p = 0.02) and instability (p = 0.008) in the arrest group. In the paired subgroup analysis, there was an increase in the ST-vector magnitude (p = 0.05) and instability (p = 0.05) in the prearrest state compared with the postarrest state prior to discharge.

Conclusions:
In single ventricle patients, increased ST instability and magnitude were associated with rapid response events that required intervention for cardiopulmonary arrest, whereas conventional ST-segment monitoring did not differentiate an arrest from control state.
Feasibility Study of an Optical Caustic Plasmonic Light Scattering Sensor for Human Serum Anti-Dengue Protein E Antibody Detection
Authors: Garcia A.A. , Franco L.S. , Pirez-Gomez M.A. , Pech-Pacheco J.L. , Mendez-Galvan J.F. , Machain-Williams C. , Talavera-Aguilar L. , Espinosa-Carrillo J.H. , Duarte-Villaseñor M.M. , Be Ortiz Ch.J. , Espinosa de los Monteros L.E. , Castillo-Pacheco A. , García-Rejon J.E. , Chavez B 
Published: October 2016

AbstractAntibody detection and accurate diagnosis of tropical diseases is essential to help prevent the spread of disease. However, most detection methods lack cost-effectiveness and field-portability, which are essential features for achieving diagnosis in a timely manner in developing countries. To address this problem, transparent 3D printed sample chambers with a total volume of 700 microliters and an oblate spheroid shape were fabricated to measure green light scattering of gold nanoparticles using an optical caustic focus to detect antibodies. Scattering signals from 90 degree scattering of 20, 40, 50, 60, 80, 100, and 200 nm gold nanoparticles using a green laser and standard quartz cuvette were compared to the scattering signals from a green LED light source with an oblate spheroid sample chamber and to Mie theory by fitting the data to a logistic curve. The change in signal from 60 nm to 120 nm decreased in the order of Mie Theory > Optical Caustic scattering > standard laser 90 degree scattering. These results suggested that conjugating 60 nm gold nanoparticles with Dengue Protein E and using an optical caustic system to detect plasmonic light scattering would result in a sensitive test for detecting human antibodies against Dengue Protein E in serum. To explore this possibility, we studied the light scattering response of protein E conjugated gold nanoparticles exposed to different concentrations of anti-protein E antibody, and posteriorly via a feasibility study consisting of 10 human serum samples using a modified dot blot protocol and a handheld optical caustic-based sensor device. The overall agreement between the benchtop light scattering and dot blot results and the handheld optical caustic sensor suggest that the new sensor concept shows promise to detect gold nanoparticle aggregation caused by the presence of the antibody using a homogeneous assay. Further testing and protocol optimization is needed in order to draw conclusions on the positive predictive and negative predictive values for this new testing system.
DNA Methylation Landscape Reflects the Spatial Organization of Chromatin in Different Cells
Authors: Zhang Ling , Xie Wen Jun , Liu Sirui , Meng Luming , Gu Chan , Gao Yi Qin 
Published: October 2016

AbstractThe relation between DNA methylation and chromatin structure is still largely unknown. By analyzing a large set of sequencing data, we observed a long-range power law correlation of DNA methylation with cell-class-specific scaling exponents in the range of thousands to millions of base pairs. We showed such cell-class-specific scaling exponents are caused by different patchiness of DNA methylation in different cells. By modeling the chromatin structure using Hi-C data and mapping the methylation level onto the modeled structure, we demonstrated the patchiness of DNA methylation is related to chromatin structure. The scaling exponents of the power law correlation is thus a display of the spatial organization of chromatin. Besides, the local correlation of DNA methylation is associated with nucleosome positioning and different between partially-methylated-domain and non-partially-methylated-domain, suggesting their different chromatin structures at several nucleosomes level. Our study provides a novel view of the spatial organization of chromatin structure from a perspective of DNA methylation, in which both long-range and local correlations of DNA methylation along the genome reflect the spatial organization of chromatin.
Effect of error and missing data on population structure inference using microsatellite data
Authors: Reeves Patrick A. , Bowker Cheryl L. , Fettig Christa E. , Tembrock Luke R. , Richards Christopher M. 
Published: October 2016

ABSTRACTMissing data and genotyping errors are common in microsatellite data sets. We used simulated data to quantify the effect of these data aberrations on the accuracy of population structure inference. Data sets with complex, randomly-generated, population histories were simulated under the coalescent. Models describing the characteristic patterns of missing data and genotyping error in real microsatellite data sets were used to modify the simulated data sets. Accuracy of ordination, tree-based, and model-based methods of inference was evaluated before and after data set modifications. The ability to recover correct population clusters decreased as missing data increased. The rate of decrease was similar among analytical procedures, thus no single analytical approach was preferable. For every 1% of a data matrix that contained missing genotypes, 2–4% fewer correct clusters were found. For every 1% of a matrix that contained erroneous genotypes, 1–2% fewer correct clusters were found using ordination and tree-based methods. Model-based procedures that minimize the deviation from Hardy-Weinberg equilibrium in order to assign individuals to clusters performed better as genotyping error increased. We attribute this surprising result to the inbreeding-like nature of microsatellite genotyping error, wherein heterozygous genotypes are mischaracterized as homozygous. We show that genotyping error elevates estimates of the level of genetic admixture. Overall, missing data negatively impact population structure inference more than typical genotyping errors.
Assessing sampling sufficiency of network metrics using bootstrap
Authors: Casas Grasiela , Bastazini Vinicius A.G. , Debastiani Vanderlei J. , Pillar Valério D. 
Published: October 2016

AbstractSampling the full diversity of interactions in an ecological community is a highly intensive effort. Recent studies have demonstrated that many network metrics are sensitive to both sampling effort and network size. Here, we develop a statistical framework, based on bootstrap resampling, that aims to assess sampling sufficiency for some of the most widely used metrics in network ecology, namely connectance, nestedness (NODF-nested overlap and decreasing fill) and modularity (using the QuaBiMo algorithm). Our framework can generate confidence intervals for each network metric with increasing sample size (i.e., the number of sampled interaction events, or number of sampled individuals), which can be used to evaluate sampling sufficiency. The sample is considered sufficient when the confidence limits reach stability or lie within an acceptable level of precision for the aims of the study. We illustrate our framework with data from three quantitative networks of plant and frugivorous birds, varying in size from 16 to 115 species, and 17 to 2,745 interactions. These data sets illustrate that, for the same dataset, sampling sufficiency may be reached at different sample sizes depending on the metric of interest. The bootstrap confidence limits reached stability for the two largest networks, but were wide and unstable with increasing sample size for all three metrics estimated based on the smallest network. The bootstrap method is useful to empirical ecologists to indicate the minimum number of interactions necessary to reach sampling sufficiency for a specific network metric. It is also useful to compare sampling techniques of networks in their capacity to reach sampling sufficiency. Our method is general enough to be applied to different types of metrics and networks.
An equation-free method reveals the ecological interaction networks within complex microbial ecosystems
Authors: Suzuki Kenta , Yoshida Katsuhiko , Nakanishi Yumiko , Fukuda Shinji 
Published: October 2016

AbstractMapping the network of ecological interactions is key to understanding the composition, stability, function and dynamics of microbial communities. In recent years various approaches have been used to reveal microbial interaction networks from metagenomic sequencing data, such as time-series analysis, machine learning and statistical techniques. Despite these efforts it is still not possible to capture details of the ecological interactions behind complex microbial dynamics.We developed the sparse S-map method (SSM), which generates a sparse interaction network from a multivariate ecological time-series without presuming any mathematical formulation for the underlying microbial processes. The advantage of the SSM over alternative methodologies is that it fully utilizes the observed data using a framework of empirical dynamic modelling. This makes the SSM robust to non-equilibrium dynamics and underlying complexity (nonlinearity) in microbial processes.We showed that an increase in dataset size or a decrease in observational error improved the accuracy of SSM whereas, the accuracy of a comparative equation-based method was almost unchanged for both cases and equivalent to the SSM at best. Hence, the SSM outperformed a comparative equation-based method when datasets were large and the magnitude of observational errors were small. The results were robust to the magnitude of process noise and the functional forms of inter-specific interactions that we tested. We applied the method to a microbiome data of six mice and found that there were different microbial interaction regimes between young to middle age (4-40 week-old) and middle to old age (36-72 week-old) mice.The complexity of microbial relationships impedes detailed equation-based modeling. Our method provides a powerful alternative framework to infer ecological interaction networks of microbial communities in various environments and will be improved by further developments in metagenomics sequencing technologies leading to increased dataset size and improved accuracy and precision.
Comparing the responses of bryophytes and short‐statured vascular plants to climate shifts and eutrophication
Authors: Virtanen Risto , Eskelinen Anu , Harrison Susan 
Published: October 2016

Summary

Few experimental studies have tested how abundance and diversity of grassland bryophytes respond to global environmental changes such as climate shifts and eutrophication. Because bryophytes in grasslands are low‐statured, and because plant height is a key functional trait governing plant responses to resource gradients, their responses to these factors could resemble those of better‐studied small vascular plants. Alternatively, traits unique to bryophytes could lead to qualitatively different responses than those of small vascular plants.

In a semi‐arid Californian grassland system, where bryophytes are at relatively low abundance and their ecology has been little studied, we compared changes in cover and species richness of bryophytes and short‐statured vascular plants in response to 5 years of experimental fertilization, springtime watering and fertilization + watering, which produced strong gradients in vascular plant biomass.

Supporting our hypotheses, the cover and richness of both bryophytes and short vascular plants were negatively related to total community biomass and tall vascular plant cover, and declined in response to the fertilization + watering treatment, in which the cover of tall vascular plants most strongly increased.

Two divergent responses were also observed as follows: watering alone increased the cover of bryophytes but not short vascular plants, while fertilization alone reduced the cover of short vascular plants but not bryophytes.

Bryophytes and short‐statured vascular plants in grasslands both may be expected to decline under projected global changes in climate and nutrient deposition that enhance total community biomass and competitive pressure. However, shifts in either precipitation or eutrophication regimes alone may have differential effects on bryophytes and short vascular plants in grasslands, and organism‐specific plant functional traits must also be considered.

A lay summary is available for this article.
Optimizing management to enhance multifunctionality in a boreal forest landscape
Authors: Triviño María , Pohjanmies Tähti , Mazziotta Adriano , Juutinen Artti , Podkopaev Dmitry , Le Tortorec Eric , Mönkkönen Mikko 
Published: October 2016

Summary

The boreal biome, representing approximately one‐third of remaining global forests, provides a number of crucial ecosystem services. A particular challenge in forest ecosystems is to reconcile demand for an increased timber production with provisioning of other ecosystem services and biodiversity. However, there is still little knowledge about how forest management could help solve this challenge. Hence, studies that investigate how to manage forests to reduce trade‐offs between ecosystem services and biodiversity are urgently needed to help forest owners and policy makers take informed decisions.

We applied seven alternative forest management regimes using a forest growth simulator in a large boreal forest production landscape. First, we estimated the potential of the landscape to provide harvest revenues, store carbon and maintain biodiversity across a 50‐year time period. Then, we applied multiobjective optimization to identify the trade‐offs between these three objectives and to identify the optimal combination of forest management regimes to achieve these objectives.

It was not possible to achieve high levels of either carbon storage or biodiversity if the objective of forest management was to maximize timber harvest revenues. Moreover, conflicts between biodiversity and carbon storage became stronger when simultaneously targeting high levels of timber revenues. However, with small reductions in timber revenues, it was possible to greatly increase the multifunctionality of the landscape, especially the biodiversity indicators.

Forest management actions, alternative to business‐as‐usual management, such as reducing thinnings, extending the rotation period and increasing the amount of area set aside from forestry may be necessary to safeguard biodiversity and non‐timber ecosystem services in Fennoscandia.

Synthesis and applications. Our results show that no forest management regime alone is able to maximize timber revenues, carbon storage and biodiversity individually or simultaneously and that a combination of different regimes is needed to resolve the conflicts among these objectives. We conclude that it is possible to reduce the trade‐offs between different objectives by applying diversified forest management planning at the boreal landscape level and that we need to give up the all‐encompassing objective of very intensive timber production, which is prevailing particularly in Fennoscandian countries.
Increasing the germination envelope under water stress improves seedling emergence in two dominant grass species across different pulse rainfall events
Authors: Lewandrowski Wolfgang , Erickson Todd E. , Dixon Kingsley W. , Stevens Jason C. 
Published: October 2016

Summary

Demographic recruitment processes, such as seed germination and seedling emergence, are critical transitional phases to the re‐establishment of degraded plant populations, but often fail due to rainfall not supporting plant requirements. Using species from the widespread arid Australian perennial grass genus Triodia, we investigated the interactions of seeds in different dormancy states and their functional germination envelope in response to water stress after simulated pulse rainfall events.

Seed dormancy was alleviated in Triodia species to varying degrees by wet/dry cycling or by removing floret structures from seeds. The seeds were then exposed to different rainfall frequency and quantity events mimicking the 25th, median, 75th and 95th percentile rainfall events found in natural habitats for the study species in the north‐west Australian arid zone.

Under 95th percentile rainfall conditions recruitment was highest, but still limited to 35% germination and 10% emergence of cleaned seeds (i.e. the least dormant state evaluated). This was related to the functional germination envelope as indicated by more negative base water potential thresholds (Ψb50) for cleaned seeds (≥ −0·33 MPa) compared to intact florets (≥ −0·26 MPa). As a result, the maximum cumulative time where soil water potentials were optimal for germination (Ψsoil ≥ Ψb50) was 1·6–2·6 times longer for cleaned seeds in large frequent rainfall events when compared to intact florets. Furthermore, seed dormancy, that usually prolongs seed survival, was linked to a short‐term reduction in seed viability, which may further reduce recruitment rates.

Synthesis and applications. Our findings indicate that large frequent rainfall events raised soil water potentials above critical thresholds for germination and are important for successful plant establishment. If recruitment bottlenecks are a result of seed dormancy and variable rainfall for arid grass species, then this study shows benefits for alleviating seed dormancy prior to seeding in restoration sites, as this increases the environmental envelope for germination.