bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interactive effects of phosphorus fertilization and salinity on plant growth, phosphorus and sodium status, and tartrate exudation by roots of two alfalfa cultivars
Authors: Su Rui , Zhang Zekun , Chang Chao , Peng Qi , Cheng Xiao , Pang Jiayin , He Honghua , Lambers Hans 
Published: September 2021

Abstract

Background and Aims
Soil phosphorus (P) deficiency and salinity are constraints to crop productivity in arid and semiarid regions. Salinity may weaken the effect of P fertilization on plant growth. We investigated the interactive effects of soil P availability and salinity on plant growth, P nutrition and salt tolerance of two alfalfa (Medicago sativa) cultivars.

Methods
A pot experiment was carried out to grow two cultivars of alfalfa in a loess soil under a combination of different rates of added P (0, 40, 80 and 160 mg P kg−1 soil as monopotassium phosphate) and sodium chloride (0, 0.4, 0.8 and 1.6 g NaCl kg−1 soil). Plant biomass, concentrations of P ([P]), sodium ([Na]) and potassium ([K]) were determined, and rhizosheath carboxylates were analysed.

Key Results
There were significant interactions between soil P availability and salinity on some, but not all, of the parameters investigated, and interactions depended on cultivar. Plant growth and P uptake were enhanced by P fertilization, but inhibited by increased levels of salinity. Increasing the salinity resulted in decreased plant P-uptake efficiency and [K]/[Na]. Only soil P availability had a significant effect on the amount of tartrate in the rhizosheath of both cultivars.

Conclusions
Increased salinity aggravated P deficiency. Appropriate application of P fertilizers improved the salt tolerance of alfalfa and increased its productivity in saline soils.
Explainable nucleus classification using Decision Tree Approximation of Learned Embeddings
Authors: Amgad Mohamed , Atteya Lamees A , Hussein Hagar , Mohammed Kareem Hosny , Hafiz Ehab , Elsebaie Maha A T , Mobadersany Pooya , Manthey David , Gutman David A , Elfandy Habiba , Cooper Lee A D 
Published: September 2021

Abstract

Motivation
Nucleus detection, segmentation and classification are fundamental to high-resolution mapping of the tumor microenvironment using whole-slide histopathology images. The growing interest in leveraging the power of deep learning to achieve state-of-the-art performance often comes at the cost of explainability, yet there is general consensus that explainability is critical for trustworthiness and widespread clinical adoption. Unfortunately, current explainability paradigms that rely on pixel saliency heatmaps or superpixel importance scores are not well-suited for nucleus classification. Techniques like Grad-CAM or LIME provide explanations that are indirect, qualitative and/or nonintuitive to pathologists.

Results
In this article, we present techniques to enable scalable nuclear detection, segmentation and explainable classification. First, we show how modifications to the widely used Mask R-CNN architecture, including decoupling the detection and classification tasks, improves accuracy and enables learning from hybrid annotation datasets like NuCLS, which contain mixtures of bounding boxes and segmentation boundaries. Second, we introduce an explainability method called Decision Tree Approximation of Learned Embeddings (DTALE), which provides explanations for classification model behavior globally, as well as for individual nuclear predictions. DTALE explanations are simple, quantitative, and can flexibly use any measurable morphological features that make sense to practicing pathologists, without sacrificing model accuracy. Together, these techniques present a step toward realizing the promise of computational pathology in computer-aided diagnosis and discovery of morphologic biomarkers.

Availability and implementation
Relevant code can be found at github.com/CancerDataScience/NuCLS

Supplementary information
Supplementary data are available at Bioinformatics online.
AlphaMap: an open-source Python package for the visual annotation of proteomics data with sequence-specific knowledge
Authors: Voytik Eugenia , Bludau Isabell , Willems Sander , Hansen Fynn M , Brunner Andreas-David , Strauss Maximilian T , Mann Matthias 
Published: September 2021

Abstract

Summary
Integrating experimental information across proteomic datasets with the wealth of publicly available sequence annotations is a crucial part in many proteomic studies that currently lacks an automated analysis platform. Here, we present AlphaMap, a Python package that facilitates the visual exploration of peptide-level proteomics data. Identified peptides and post-translational modifications in proteomic datasets are mapped to their corresponding protein sequence and visualized together with prior knowledge from UniProt and with expected proteolytic cleavage sites. The functionality of AlphaMap can be accessed via an intuitive graphical user interface or—more flexibly—as a Python package that allows its integration into common analysis workflows for data visualization. AlphaMap produces publication-quality illustrations and can easily be customized to address a given research question.

Availability and implementation
AlphaMap is implemented in Python and released under an Apache license. The source code and one-click installers are freely available at https://github.com/MannLabs/alphamap.

Supplementary information
Supplementary data are available at Bioinformatics online.
MuWU: Mutant-seq library analysis and annotation
Authors: Stöcker Tyll , Altrogge Lena , Marcon Caroline , Win Yan Naing , Hochholdinger Frank , Schoof Heiko 
Published: September 2021

Abstract

Motivation
Insertional mutagenesis allows for the creation of loss-of-function mutations on a genome-wide scale. In theory, every gene can be ‘knocked out’ via the insertion of an additional DNA sequence. Resources of sequence-indexed mutants of plant and animal model organisms are instrumental for functional genomics studies. Such repositories significantly speed up the acquisition of interesting genotypes and allow for the validation of hypotheses regarding phenotypic consequences in reverse genetics. To create such resources, comprehensive sequencing of flanking sequence tags using protocols such as Mutant-seq requires various downstream computational tasks, and these need to be performed in an efficient and reproducible manner.

Results
Here, we present MuWU, an automated Mutant-seq workflow utility initially created for the identification of Mutator insertion sites of the BonnMu resource, representing a reverse genetics mutant collection for functional genetics in maize (Zea mays). MuWU functions as a fast, one-stop downstream processing pipeline of Mutant-seq reads. It takes care of all complex bioinformatic tasks, such as identifying tagged genes and differentiating between germinal and somatic mutations/insertions. Furthermore, MuWU automatically assigns insertions to the corresponding mutated seed stocks. We discuss the implementation and how parameters can easily be adapted to use MuWU for other species/transposable elements.

Availability and implementation
MuWU is a Snakemake-based workflow and freely available at https://github.com/tgstoecker/MuWU.

Supplementary information
Supplementary data are available at Bioinformatics online.
Effects of a novel ectoparasite on condition and mouth coloration of nestling barn swallows
Authors: Dugas Matthew B , Border Shana E 
Published: September 2021

AbstractParasites have profound and widespread implications for the ecology and evolution of hosts, and human activity has increased the frequency of interactions between hosts and parasites that have not co-evolved. For example, by building habitat attractive for nesting, humans might have facilitated range expansion by cliff swallows (Petrochelidon pyrrhonata) and barn swallows (Hirundo rustica) in North America, concurrently allowing a haematophagous ectoparasite of cliff swallows, the swallow bug (Oeciacus vicarious), to infest the nests of barn swallows. We found that in barn swallow nests infested with swallow bugs, nestlings weighed less and had lower haematocrit, and the within-brood variation in body mass and tarsus length was higher. Information about these negative effects might be available to parents via mouth coloration, a condition-dependent component of the begging signal. We found that nestlings from infested broods had lower-intensity carotenoid-based and ultraviolet mouth colours, although most elements of colour were unrelated to parasites. Host switching by the swallow bug offers excellent opportunities to understand the direct and indirect effects of a novel parasite and might also afford insights into how parasites cope with selective pressures exerted by closely related hosts with key ecological differences.
A note on median regression for complex surveys
Authors: Fraser Raphael A , Lipsitz Stuart R , Sinha Debajyoti , Fitzmaurice Garrett M 
Published: September 2021

Summary
There is a great need for statistical methods for analyzing skewed responses in complex sample surveys. Quantile regression is a logical option in addressing this problem but is often accompanied by incorrect variance estimation. We show how the variance can be estimated correctly by including the survey design in the variance estimation process. In a simulation study, we illustrate that the variance of the median regression estimator has a very small relative bias with appropriate coverage probability. The motivation for our work stems from the National Health and Nutrition Examination Survey where we demonstrate the impact of our results on iodine deficiency in females compared with males adjusting for other covariates.
The Latin American Dialysis and Renal Transplantation Registry: report 2019
Authors: Luxardo Rosario , Ceretta Laura , González-Bedat María , Ferreiro Alejandro , Rosa-Diez Guillermo 
Published: September 2021

ABSTRACT

Background
Chronic kidney disease (CKD) in Latin America (LA) continues to represent a challenge due to the burden of disease it causes and the difficulty in accessing treatment. LA has a total population of 652 million people living in 20 countries that occupy an area of 19.2 million km2. The Latin American Dialysis and Renal Transplantation Registry (LADRTR), founded in 1991, has collected data and reports on patients receiving kidney replacement therapy (KRT) since 1993. This article summarizes the registry data for 2019.

Methods
Participating countries complete an annual survey collecting aggregated data on incident and prevalent patients on KRT in all modalities. The different treatment modalities considered were hemodialysis (HD), peritoneal dialysis (PD) and living functioning kidney graft (LFG). National gross domestic product per capita (GDP, expressed in US dollars) and life expectancy at birth (LEB) corresponding to the year 2019 were collected from the World Bank Data Bank. Prevalence and incidence were compared with previous years and were also correlated with GDP and LEB.

Results
On 31 December 2019 a total of 432 610 patients were in KRT in LA, corresponding to an overall unadjusted prevalence of 866 per million population (pmp). Regarding treatment modality, 66.7% of the prevalent patients were treated with HD and 9.3% with PD while 24% of the patients had an LFG. A total of 85 224 patients started KRT in LA, representing a total unadjusted incidence rate of 168 pmp. Diabetic nephropathy as a cause of CKD continues to be a relevant percentage (36%) and five countries reported CKD of nontraditional causes. The kidney transplant rate in the region was 22 pmp, varying from 1 to &gt;60 pmp. The total prevalence of KRT correlated positively with GDP per capita (r2 = 0.6, P &lt; 0.01) and LEB (r2 = 0.23, P &lt; 0.05). The overall incidence rate also significantly correlated with GDP (r2 = 0.307, P &lt; 0.05). The overall unadjusted mortality rate was 13%.

Conclusion
Accessibility to KRT is still limited in LA. It is necessary to continue the efforts made by each country and the Latin American Society of Nephrology and Hypertension to guarantee equal access to treatment.
The World Spider Trait database: a centralized global open repository for curated data on spider traits
Authors: Pekár Stano , Wolff Jonas O , Černecká Ľudmila , Birkhofer Klaus , Mammola Stefano , Lowe Elizabeth C , Fukushima Caroline S , Herberstein Marie E , Kučera Adam , Buzatto Bruno A , Djoudi El Aziz , Domenech Marc , Enciso Alison Vanesa , Piñanez Espejo Yolanda M G , Febles Sara , García Luis F , Gonçalves-Souza Thiago , Isaia Marco , Lafage Denis , Líznarová Eva , Macías-Hernández Nuria , Magalhães Ivan , Malumbres-Olarte Jagoba , Michálek Ondřej , Michalik Peter , Michalko Radek , Milano Filippo , Munévar Ana , Nentwig Wolfgang , Nicolosi Giuseppe , Painting Christina J , Pétillon Julien , Piano Elena , Privet Kaïna , Ramírez Martín J , Ramos Cândida , Řezáč Milan , Ridel Aurélien , Růžička Vlastimil , Santos Irene , Sentenská Lenka , Walker Leilani , Wierucka Kaja , Zurita Gustavo Andres , Cardoso Pedro 
Published: September 2021

AbstractSpiders are a highly diversified group of arthropods and play an important role in terrestrial ecosystems as ubiquitous predators, which makes them a suitable group to test a variety of eco-evolutionary hypotheses. For this purpose, knowledge of a diverse range of species traits is required. Until now, data on spider traits have been scattered across thousands of publications produced for over two centuries and written in diverse languages. To facilitate access to such data, we developed an online database for archiving and accessing spider traits at a global scale. The database has been designed to accommodate a great variety of traits (e.g. ecological, behavioural and morphological) measured at individual, species or higher taxonomic levels. Records are accompanied by extensive metadata (e.g. location and method). The database is curated by an expert team, regularly updated and open to any user. A future goal of the growing database is to include all published and unpublished data on spider traits provided by experts worldwide and to facilitate broad cross-taxon assays in functional ecology and comparative biology.Database URL: https://spidertraits.sci.muni.cz/
Greater plaque burden and cholesterol content may explain an increased incidence of non-culprit events in diabetic patients: a Lipid-Rich Plaque substudy
Authors: Demola Pierluigi , Di Mario Carlo , Torguson Rebecca , Ten Cate Tim , Bambagioni Gabriele , Ali Ziad , Skinner William , Artis Andre , Zhang Cheng , Garcia-Garcia Hector M , Doros Gheorghe , Mintz Gary S , Waksman Ron 
Published: September 2021

AbstractAimsDiabetes mellitus (DM) is associated with increased cardiovascular morbidity and mortality. The multicentre, prospective Lipid-Rich Plaque trial (LRP) examined non-culprit (NC) non-obstructive coronary segments with a combined near-infrared spectroscopy (NIRS)-intravascular ultrasound (IVUS) catheter. This study assessed the differences in NC plaque characteristics and their influence on major adverse cardiac events (MACE) in diabetic and non-diabetic patients.Methods and resultsPatients with known DM status were divided into no diabetes, diabetes not treated with insulin (non-ITDM), and insulin-treated diabetes (ITDM). The association between presence and type of DM and NC-MACE was assessed at both the patient and coronary segment levels by Cox proportional regression modelling. Out of 1552 patients enrolled, 1266 who had their diabetes status recorded were followed through 24 months. Female sex, hypertension, chronic kidney disease, peripheral vascular disease, and high body mass index were significantly more frequent in diabetic patients. The ITDM group had more diseased vessels, at least one NC segment with a maxLCBI4 mm ≥400 in 46.2% of patients, and maxLCBI4 mm ≥400 in nearly one out of six Ware segments (15.2%, 125/824 segments). The average maxLCBI4 mm significantly increased from non-diabetic patients (NoDM) to non-insulin-treated diabetic patients (non-ITDM) to insulin-treated diabetic patients (ITDM; 137.7 ± 161.9, 154.8 ± 173.6, 182.9 ± 193.2, P &lt; 0.001, respectively). In patients assigned to follow-up (692 ± 129 days), ITDM doubled the incidence of NC-MACE compared with the absence of diabetes (15.7% vs. 6.9%, P = 0.0008). The presence of maxLCBI4 mm&gt;400 further increased the NC-MACE rate to 21.6% (Kaplan–Meier estimate).ConclusionCholesterol-rich NC plaques detected by NIRS-IVUS were significantly more frequent in diabetic patients, especially those who were insulin-treated, and were associated with an increased NC-MACE during follow-up.
Aortic arch reconstruction in the Norwood procedure using a curved polytetrafluorethylene patch
Authors: Sames-Dolzer Eva , Gierlinger Gregor , Kreuzer Michaela , Mair Roland , Gitter Roland , Prandstetter Christoph , Tulzer Gerald , Mair Rudolf 
Published: September 2021

Abstract

OBJECTIVES
The aortic arch enlargement in the Norwood procedure is classically carried out using a curved homograft patch on the inner curvature of the neoaortic arch. The study investigates the outcome of a newly used artificial patch from a vascular prosthesis as an alternative to a homograft patch.

METHODS
Since April 2007, we used curved polytetrafluorethylene (PTFE) patches cut out of a prosthesis as an alternative to homograft patches for the aortic arch reconstruction. The decision for either patch material was made due to anatomic reasons, preferring PTFE patches in larger aortas. In this study, 224 Norwood patients, operated between April 2007 and April 2018, were analysed. A total of 104 patients received a PTFE patch (group PTFE), and 120 patients got a pulmonary homograft patch (group homograft). A single-centre retrospective analysis was carried out concerning postoperative course and long-term follow-up regarding aortic arch interventions and reoperations and comparing the 2 material groups.

RESULTS
There were no material associated operative or postoperative complications. In-hospital mortality was 13% in group PTFE. Six children died late during follow-up (6%). One aortic isthmus dilatation (1%) was carried out 12 months after the Norwood procedure in this group, no arch reoperation was necessary during the complete follow-up.

CONCLUSIONS
The curved PTFE patch showed good qualities in operative technical demands and excellent long-term results. In selected cases of hypoplastic left heart syndrome, it can be well used as alternative to the pulmonary homograft.
Characterizing Amino Acid Substitution with Complete Linkage of Sites on a Lineage
Authors: Stark Tristan L , Liberles David A 
Published: September 2021

AbstractAmino acid substitution models are commonly used for phylogenetic inference, for ancestral sequence reconstruction, and for the inference of positive selection. All commonly used models explicitly assume that each site evolves independently, an assumption that is violated by both linkage and protein structural and functional constraints. We introduce two new models for amino acid substitution which incorporate linkage between sites, each based on the (population-genetic) Moran model. The first model is a generalized population process tracking arbitrarily many sites which undergo mutation, with individuals replaced according to their fitnesses. This model provides a reasonably complete framework for simulations but is numerically and analytically intractable. We also introduce a second model which includes several simplifying assumptions but for which some theoretical results can be derived. We analyze the simplified model to determine conditions where linkage is likely to have meaningful effects on sitewise substitution probabilities, as well as conditions under which the effects are likely to be negligible. These findings are an important step in the generation of tractable phylogenetic models that parameterize selective coefficients for amino acid substitution while accounting for linkage of sites leading to both hitchhiking and background selection.
Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design
Authors: Weber Lukas M , Hippen Ariel A , Hickey Peter F , Berrett Kristofer C , Gertz Jason , Doherty Jennifer Anne , Greene Casey S , Hicks Stephanie C 
Published: September 2021

Abstract

Background
Pooling cells from multiple biological samples prior to library preparation within the same single-cell RNA sequencing experiment provides several advantages, including lower library preparation costs and reduced unwanted technological variation, such as batch effects. Computational demultiplexing tools based on natural genetic variation between individuals provide a simple approach to demultiplex samples, which does not require complex additional experimental procedures. However, to our knowledge these tools have not been evaluated in cancer, where somatic variants, which could differ between cells from the same sample, may obscure the signal in natural genetic variation.

Results
Here, we performed in silico benchmark evaluations by combining raw sequencing reads from multiple single-cell samples in high-grade serous ovarian cancer, which has a high copy number burden, and lung adenocarcinoma, which has a high tumor mutational burden. Our results confirm that genetic demultiplexing tools can be effectively deployed on cancer tissue using a pooled experimental design, although high proportions of ambient RNA from cell debris reduce performance.

Conclusions
This strategy provides significant cost savings through pooled library preparation. To facilitate similar analyses at the experimental design phase, we provide freely accessible code and a reproducible Snakemake workflow built around the best-performing tools found in our in silico benchmark evaluations, available at https://github.com/lmweber/snp-dmx-cancer.
Bias-invariant RNA-sequencing metadata annotation
Authors: Wartmann Hannes , Heins Sven , Kloiber Karin , Bonn Stefan 
Published: September 2021

Abstract

Background
Recent technological advances have resulted in an unprecedented increase in publicly available biomedical data, yet the reuse of the data is often precluded by experimental bias and a lack of annotation depth and consistency. Missing annotations makes it impossible for researchers to find datasets specific to their needs.

Findings
Here, we investigate RNA-sequencing metadata prediction based on gene expression values. We present a deep-learning–based domain adaptation algorithm for the automatic annotation of RNA-sequencing metadata. We show, in multiple experiments, that our model is better at integrating heterogeneous training data compared with existing linear regression–based approaches, resulting in improved tissue type classification. By using a model architecture similar to Siamese networks, the algorithm can learn biases from datasets with few samples.

Conclusion
Using our novel domain adaptation approach, we achieved metadata annotation accuracies up to 15.7% better than a previously published method. Using the best model, we provide a list of &gt;10,000 novel tissue and sex label annotations for 8,495 unique SRA samples. Our approach has the potential to revive idle datasets by automated annotation making them more searchable.