bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of chitin and chitosan on root growth, biochemical defense response and exudate proteome of Cannabis sativa
Authors: Suwanchaikasem Pipob , Nie Shuai , Idnurm Alexander , Selby‐Pham Jamie , Walker Robert , Boughton Berin A. 
Published: April 2023

AbstractFungal pathogens pose a major threat to Cannabis sativa production, requiring safe and effective management procedures to control disease. Chitin and chitosan are natural molecules that elicit plant defense responses. Investigation of their effects on C. sativa will advance understanding of plant responses towards elicitors and provide a potential pathway to enhance plant resistance against diseases. Plants were grown in the in vitro Root‐TRAPR system and treated with colloidal chitin and chitosan. Plant morphology was monitored, then plant tissues and exudates were collected for enzymatic activity assays, phytohormone quantification, qPCR analysis and proteomics profiling. Chitosan treatments showed increased total chitinase activity and expression of pathogenesis‐related (PR) genes by 3–5 times in the root tissues. In the exudates, total peroxidase and chitinase activities and levels of defense proteins such as PR protein 1 and endochitinase 2 were increased. Shoot development was unaffected, but root development was inhibited after chitosan exposure. In contrast, chitin treatments had no significant impact on any defense parameters, including enzymatic activities, hormone quantities, gene expression levels and root secreted proteins. These results indicate that colloidal chitosan, significantly enhancing defense responses in C. sativa root system, could be used as a potential elicitor, particularly in hydroponic scenarios to manage crop diseases.
Whole microbe arrays accurately predict interactions and overall antimicrobial activity of galectin-8 toward distinct strains of Streptococcus pneumoniae
Authors: Wu Shang-Chuen , Jan Hau-Ming , Vallecillo-Zúniga Mary L. , Rathgeber Matthew F. , Stowell Caleb S. , Murdock Kaleb L. , Patel Kashyap R. , Nakahara Hirotomo , Stowell Carter J. , Nahm Moon H. , Arthur Connie M. , Cummings Richard D. , Stowell Sean R. 
Published: April 2023

AbstractMicrobial glycan microarrays (MGMs) populated with purified microbial glycans have been used to define the specificity of host immune factors toward microbes in a high throughput manner. However, a limitation of such arrays is that glycan presentation may not fully recapitulate the natural presentation that exists on microbes. This raises the possibility that interactions observed on the array, while often helpful in predicting actual interactions with intact microbes, may not always accurately ascertain the overall affinity of a host immune factor for a given microbe. Using galectin-8 (Gal-8) as a probe, we compared the specificity and overall affinity observed using a MGM populated with glycans harvested from various strains of Streptococcus pneumoniae to an intact microbe microarray (MMA). Our results demonstrate that while similarities in binding specificity between the MGM and MMA are apparent, Gal-8 binding toward the MMA more accurately predicted interactions with strains of S. pneumoniae, including the overall specificity of Gal-8 antimicrobial activity. Taken together, these results not only demonstrate that Gal-8 possesses antimicrobial activity against distinct strains of S. pneumoniae that utilize molecular mimicry, but that microarray platforms populated with intact microbes present an advantageous strategy when exploring host interactions with microbes.
NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities
Authors: Loukachevitch Natalia , Manandhar Suresh , Baral Elina , Rozhkov Igor , Braslavski Pavel , Ivanov Vladimir , Batura Tatiana , Tutubalina Elena 
Published: April 2023

Abstract

Motivation
This article describes NEREL-BIO—an annotation scheme and corpus of PubMed abstracts in Russian and smaller number of abstracts in English. NEREL-BIO extends the general domain dataset NEREL by introducing domain-specific entity types. NEREL-BIO annotation scheme covers both general and biomedical domains making it suitable for domain transfer experiments. NEREL-BIO provides annotation for nested named entities as an extension of the scheme employed for NEREL. Nested named entities may cross entity boundaries to connect to shorter entities nested within longer entities, making them harder to detect.

Results
NEREL-BIO contains annotations for 700+ Russian and 100+ English abstracts. All English PubMed annotations have corresponding Russian counterparts. Thus, NEREL-BIO comprises the following specific features: annotation of nested named entities, it can be used as a benchmark for cross-domain (NEREL → NEREL-BIO) and cross-language (English → Russian) transfer. We experiment with both transformer-based sequence models and machine reading comprehension models and report their results.

Availability and implementation
The dataset and annotation guidelines are freely available at https://github.com/nerel-ds/NEREL-BIO.
Environmental and economic evaluation of the high-pressured and cryogenic vessels for hydrogen storage on the sedan
Authors: Ye Linghe , Lu Lin 
Published: April 2023

AbstractThis paper carried out the environmental and economic evaluation for the hydrogen storage technologies on the sedan with Type 3 and Type 4 high-pressured and cryogenic vessels based on life cycle analysis (LCA) method. It is found that Type 4 high-pressured vessel manufacture emits minimum greenhouse gas (GHG) with 5539 kgCO2 eq, which is lower than Type 3 high-pressured vessel of 7219 kgCO2 eq and cryogenic vessel of 135 000 kgCO2 eq in their whole life cycle. The economic analysis shows that Type 4 high-pressure vessel has the lowest cost of 10.4 US$/kgH2 and the minimum energy consumption of 5.2 kWh/kgH2, which is lower than Type 3 high-pressure vessel and cryogenic vessel. With this result, Type 4 high-pressure vessel is a promising choice for hydrogen mobility on the sedan regarding its environmental impact and economic performance.
SARS-CoV-2 Reinfection With Different SARS-CoV-2 Variants in Children, Ohio, United States
Authors: Wang Huanyu , Wright Tori , Everhart Kathy , Oyeniran Sophonie J , Mejias Asuncion , Leber Amy L 
Published: April 2023

Abstract

Background
Beginning in late 2021, we observed a significant increase in SARS-CoV-2 reinfections in pediatric patients evaluated at our institution. We aimed to characterize the children with SARS-CoV-2 reinfection, determine the number of SARS-CoV-2 reinfections, and characterize the intervals between two infections in our patient population.

Methods
From March 2020 to September 2022, we identified children ≤21 years old who had ≥2 SARS-CoV-2 infections using laboratory reports. We then defined the type of SARS-CoV-2 variant in the first and subsequent infections by mutation-specific typing or local epidemiology data. Clinical outcomes and the intervals between SARS-CoV-2 infections were assessed.

Results
We identified 541 children with ≥2 SARS-CoV-2 infections. The median interval between two infections was 229 days. The hospitalization rate was lower in the second infection. Reinfection counts were higher during the periods that Omicron variants predominated. Reinfection occurred more rapidly when Omicron variants were circulating with some occurring in less than 90 days.

Conclusions
As SARS-CoV-2 continues to evolve, there is a need for ongoing surveillance to identify the frequency and time interval between reinfections and to re-evaluate the definition of SARS-CoV-2 reinfections.
Who Can Participate, Where, and How? Connections between Language-in-Education and Social Justice in Policies of Refugee Inclusion
Authors: Reddick Celia 
Published: April 2023

Abstract
Amidst growing displacement, global policy is increasingly oriented towards the inclusion of refugees in national education systems in countries of exile. This shift is understood to enable improved education for refugees as well as post-school opportunities but also means that refugee young people must often contend with education in unfamiliar languages. This article engages the definition of social justice as ‘parity of participation’ to examine the relationship between economic, political, and cultural participation and language in refugee education. Analysing 76 semi-structured interviews with Sudanese and South Sudanese refugee heads-of-households living in Uganda, national Ugandan teachers working in schools attended by refugee and national children, and policymakers and program leaders intervening in refugee education, this article considers tensions between education policies premised on English for economic opportunity and the kinds of political, cultural, and economic participation refugees seek in the present and for the future.
Sleep health dimensions and shift work as longitudinal predictors of cognitive performance in the UK Biobank cohort
Authors: Ell Johanna , Schiel Julian E , Feige Bernd , Riemann Dieter , Nyhuis Casandra C , Fernandez-Mendoza Julio , Vetter Céline , Rutter Martin K , Kyle Simon D , Spiegelhalder Kai 
Published: April 2023

AbstactStudy ObjectivesThe long-term effects of sleep health and shift work on cognitive performance are unclear. In addition, research has been limited by small sample sizes and short follow-up periods. We conducted one of the largest examinations of the longitudinal influence of sleep health dimensions and shift work on cognitive performance in people of middle and old age using data from the UK Biobank. The hypothesis was that poor sleep health and shift work would predict lower cognitive performance.MethodsSelf-reported sleep duration, daytime sleepiness, insomnia symptoms, chronotype, and shift work status were assessed as predictors at baseline. Cognitive performance was operationalized by a touchscreen test battery at follow-up between 7.4 ± 2.2 and 9.0 ± 0.9 years after baseline assessment, depending on the specific task. Models were performed for each cognitive domain including relevant confounders (e.g. depression). The alpha level was set at p &lt; 0.01 for all analyzes.ResultsThe study sample comprised 9394 participants for the reasoning task, 30 072 for the reaction time task, 30 236 for the visual memory task, 2019 for the numeric memory task, and 9476 for the prospective memory task. Shift work without night shifts (β = −2.0 × 10−1 ± 6.5 × 10−2, p = 0.002) and with night shifts (β = −1.9 × 10−1 ± 7.2 × 10−2, p = 0.010) predicted a significantly reduced performance in the reasoning task. Short sleep duration (β = −2.4 × 10−1 ± 7.9 × 10−2, p = 0.003) and shift work without night shifts (β = −3.9 × 10−1 ± 1.2 × 10−1, p = 0.002) predicted a significantly lower performance in the task probing prospective memory.ConclusionsOur results suggest that, after controlling for confounding variables, shift work, and short sleep duration are important predictors for cognitive performance in people of middle and old age. Further work is required to examine causal mechanisms of the observed associations.
Large-scale template-based structural modeling of T-cell receptors with known antigen specificity reveals complementarity features
Authors: Shcherbinin Dmitrii S. , Karnaukhov Vadim K. , Zvyagin Ivan V. , Chudakov Dmitriy M. , Shugay Mikhail 
Published: April 2023

AbstractT-cell receptor (TCR) recognition of foreign peptides presented by the major histocompatibility complex (MHC) initiates the adaptive immune response against pathogens. A large number of TCR sequences specific to different antigens are known to date, however, the structural data describing the conformation and contacting residues for TCR:antigen:MHC complexes is relatively limited. In the present study we aim to extend and analyze the set of available structures by performing highly accurate template-based modeling of TCR:antigen:MHC complexes using TCR sequences with known specificity. Using the set of 29 complex templates (including a template with SARS-CoV-2 antigen) and 732 specificity records, we built a database of 1585 model structures carrying substitutions in either TCRα or TCRβ chains with some models representing the result of different mutation pathways for the same final structure. This database allowed us to analyze features of amino acid contacts in TCR:antigen interfaces that govern antigen recognition preferences and interpret these interactions in terms of physicochemical properties of interacting residues. Our results provide a methodology for creating high-quality TCR:antigen:MHC models for antigens of interest that can be utilized to predict TCR specificity.
Cytogeography ofGagea bohemica(Liliaceae) outside the Mediterranean: two ploidy levels, spatial differentiation of cytotypes, and occurrence of mixed-ploidy populations
Authors: Horák David , Trávníček Bohumil , Király Gergely , Détraz-Méroz Jacqueline , Vymyslický Tomáš , Kozoni Marianthi , Harpke Dörte , Hroneš Michal 
Published: April 2023

AbstractGagea bohemicas. lat. is a morphologically and karyologically highly variable group with many morphologically similar “narrow” taxa currently considered as a single variable species. It is predominantly distributed in Mediterranean and warmer parts of temperate belt of Europe. The large-scale data on its cytogeography and population cytotype structure which could provide a basis for taxonomy is lacking, only scattered data on ploidy have been published from various parts of its range. In this study, we sampled 106 populations in broader Central Europe, the northeastern Balkan Peninsula and the northwestern Black Sea coast in order to analyse their ploidy level, genome size and pollen stainability. Two cytotypes, i.e., tetraploid (2n = 48) and pentaploid (2n = 60), were found in the study area using chromosome counting and flow cytometry, both in pure and mixed-ploidy populations. Pure pentaploid populations are mainly distributed in Austria, Czechia, northwestern Hungary and Slovakia while tetraploid cytotype in pure and mixed-ploidy populations forming two lineages which are concentrated into two disjunct geographical areas: a western lineage in Germany and Switzerland, and an eastern one in Bulgaria, southeastern Hungary, northern Greece, Romania, Serbia and Ukraine. The two lineages differ in their genome size regardless of their ploidy, indicating their independent origin. Analysis of pollen stainability using a modified Alexander stain revealed an unusual pattern with tetraploids having a lower pollen stainability (mean 44.29 %) than pentaploids (mean 70.70 %) but the western and eastern populations differed again from each other.
Model-based differential sequencing analysis
Authors: Busia Akosua , Listgarten Jennifer 
Published: April 2023

AbstractCharacterizing differences in biological sequences between two conditions using high-throughput sequencing data is a prevalent problem wherein we seek to (i) quantify how sequence abundances change between conditions, and (ii) build predictive models to estimate such differences for unobserved sequences. A key shortcoming of current approaches is their extremely limited ability to share information across related but non-identical reads. Consequently, they cannot make effective use of sequencing data, nor can they be directly applied in many settings of interest. We introducemodel-based enrichment(MBE) to overcome this shortcoming. MBE is based on sound theoretical principles, is easy to implement, and can trivially make use of advances in modernday machine learning classification architectures or related innovations. We extensively evaluate MBE empirically, both in simulation and on real data. Overall, we find that our new approach improves accuracy compared to current ways of performing such differential analyses.
Deterministic Genetic Barcoding for Multiplexed Behavioral and Single-Cell Transcriptomic Studies
Authors: Mendana Jorge Blanco , Donovan Margaret , O’Brien Lindsey G. , Auch Benjamin , Garbe John , Gohl Daryl M. 
Published: April 2023

AbstractAdvances in single-cell sequencing technologies have provided novel insights into the dynamics of gene expression throughout development, been used to characterize somatic variation and heterogeneity within tissues, and are currently enabling the construction of transcriptomic cell atlases. However, despite these remarkable advances, linking anatomical information to transcriptomic data and positively identifying the cell types that correspond to gene expression clusters in single-cell sequencing data sets remains a challenge. We describe a straightforward genetic barcoding approach that takes advantage of the powerful genetic tools available in Drosophila to allowin vivotagging of defined cell populations. This method, calledTargetedGenetically-EncodedMultiplexing (TaG-EM), involves inserting a DNA barcode just upstream of the polyadenylation site in a Gal4-inducibleUAS-GFPconstruct so that the barcode sequence can be read out during single-cell sequencing, labeling a cell population of interest. By creating many such independently barcoded fly strains, TaG-EM will enable a number of potential applications that will improve the quality and information content of single-cell transcriptomic data including positive identification of cell types in cell atlas projects, identification of multiplet droplets, and barcoding of experimental timepoints, conditions, and replicates. Furthermore, we demonstrate that the barcodes from TaG-EM fly lines can be read out using next-generation sequencing to facilitate population-scale behavioral measurements. Thus, TaG-EM has the potential to enable large-scale behavioral screens in addition to improving the ability to reliably annotate cell atlas data, expanding the scope, and improving the robustness of single-cell transcriptomic experiments.
Leveraging medical Twitter to build a visual–language foundation model for pathology AI
Authors: Huang Zhi , Bianchi Federico , Yuksekgonul Mert , Montine Thomas , Zou James 
Published: April 2023

AbstractThe lack of annotated publicly available medical images is a major barrier for innovations. At the same time, many de-identified images and much knowledge are shared by clinicians on public forums such as medical Twitter. Here we harness these crowd platforms to curate OpenPath, a large dataset of 208,414 pathology images paired with natural language descriptions. This is the largest public dataset for pathology images annotated with natural text. We demonstrate the value of this resource by developing PLIP, a multimodal AI with both image and text understanding, which is trained on OpenPath. PLIP achieves state-of-the-art zero-shot and transfer learning performances for classifying new pathology images across diverse tasks. Moreover, PLIP enables users to retrieve similar cases by either image or natural language search, greatly facilitating knowledge sharing. Our approach demonstrates that publicly shared medical information is a tremendous resource that can be harnessed to advance biomedical AI.
Ensemble of BLUP, Machine Learning, and Deep Learning Models Predict Maize Yield Better Than Each Model Alone
Authors: Kick Daniel R. , Washburn Jacob D. 
Published: April 2023

AbstractPredicting phenotypes accurately from genomic, environment, and management factors is key to accelerating the development of novel cultivars with desirable traits. Inclusion of management and environmental factors enablesin silicostudies to predict the effect of specific management interventions or future climates. Despite the value such models would confer, much work remains to improve the accuracy of phenotypic predictions. Rather than advocate for a single specific modeling strategy, here we demonstrate within large multi-environment and multi-genotype maize trials that combining predictions from disparate models using simple ensemble approaches most often results in better accuracy than using any one of the models on their own. We investigated various ensemble combinations of different model types, model numbers, and model weighting schemes to determine the accuracy of each.We find that ensembling generally improves performance even when combining only two models. The number and type of models included alter accuracy with improvements diminishing as the number of models included increases. Using a genetic algorithm to optimize ensemble composition reveals that, when weighted by the inverse of each model’s expected error, using combinations of best linear unbiased predictors, linear fixed effects models, deep learning models, and select machine learning models perform best on our datasets.
Dietary environmental factors shape the immune defence againstCryptosporidiuminfection
Authors: Maradana Muralidhara Rao , Marzook N. Bishara , Diaz Oscar E. , Mkandawire Tapoka , Diny Nicola Laura , Li Ying , Liebert Anke , Shah Kathleen , Tolaini Mauro , Kváč Martin , Stockinger Brigitta , Sateriale Adam 
Published: April 2023

SUMMARYCryptosporidiumis a leading cause of diarrheal-related deaths in children, especially in resource-poor settings. It also targets the immunocompromised, chronically infecting people living with HIV and primary immunodeficiencies. There is no vaccine or effective treatment. While it is known from human cases and animal models that CD4+T-cells play a role in curbingCryptosporidium, the role of CD8+cells remains to be defined. Using aCryptosporidium tyzzerimouse model, we show that gut-resident CD8+intraepithelial lymphocytes (IELs) confer resistance to parasite growth. CD8+IELs express, and are dependent on, the ligand-dependent transcription factor aryl hydrocarbon receptor (AHR). AHR deficiency reduced CD8+IELs, decreased their cytotoxicity, and worsened infection. Transfer of CD8+IELs rescued severely immunodeficient mice from death followingCryptosporidiumchallenge. Finally, dietary supplementation of the AHR pro-ligand indole-3-carbinol to new-born mice promoted resistance to infection. Therefore, common dietary metabolites augment the host immune response to cryptosporidiosis, protecting against disease.