bluuebunny/crossref_metadata_2025_split huggingface dataset:
An explainable artificial intelligence-based typification of chronic inflammatory responses enhances glioma prognosis
Authors: Chowdhury Debajyoti , Yip Hiu Fung , Li Zeming , Ren Qing , Liu Hao , Tai Xuecheng , Zhang Lu , Lu Aiping 
Published: March 2023

AbstractGlioma is one of the most aggressive solid brain tumors with a poor prognosis. A chronic tumor inflammatory microenvironment drives glioma promotion and progression. The neutrophil-to-lymphocyte ratio and other clinicopathological variables usually serve as prognostic glioma markers. However, they are not ubiquitous prognostic markers for glioma as they fail to reveal the intricacy between the glioma-specific tumor inflammatory microenvironment and the systemic inflammatory responses, especially those chronic inflammatory responses, which vary among individuals fabricating diverse prognostic outcomes. Here, we introduced an explainable artificial intelligence model to typify chronic inflammatory responses as prognostic markers for glioma using 694-patients’ data from The Cancer Genome Atlas. We characterized the glioma-specific personalized inflammatory mediators using multi-layered regulators such as transcriptional networks, cellular infiltration markers, and cellular senescence markers, which identified five unique chronic inflammatory responses (p-value<0.0001). We defined its prognostic significance using overall survival analyses. The chronic inflammatory responses were positively correlated with poor overall survival in glioma. The patients with higher chronic inflammatory responses showed significantly shorter overall survival than those with lower chronic inflammatory responses. Interestingly, optimizing those chronic inflammatory responses improved the overall survival of glioma patients. We identified the effector genes within the personalized inflammatory mediators’ networks, indicating them as the targets for optimizing individualized chronic inflammatory response profiles through co-drug intervention.SignificanceExplainable artificial intelligence-based typification of chronic inflammatory responses accelerates glioma prognosis and supports co-drug discovery to modulate inflammatory responses alongside cancer therapy, suggested by 694-glioma patients’ data analysis.
A novel in-vivo phagocytosis assay to gain cellular insights on sponge-microbe interactions
Authors: Marulanda-Gomez Angela M. , Bayer K Kristina , Pita Lucia , Hentschel Ute 
Published: March 2023

AbstractSponges harbor diverse, specific, and stable microbial communities, but at the same time, they efficiently feed on microbes from the surrounding water column. This filter-feeding lifestyle poses the need to distinguish between three categories of bacteria: food to digest, symbionts to incorporate, and pathogens to eliminate. How sponges discriminate between these categories is still largely unknown. Phagocytosis is conceivable as the cellular mechanism taking part in such discrimination, but experimental evidence is missing. We developed a quantitative in-vivo phagocytosis assay using an emerging experimental model, the spongeHalichondria panicea. We incubated whole sponge individuals with different particles, recovered the sponge (host) cells, and tracked the particles into the sponge cells to quantify the sponge’s phagocytic activity. Fluorescence-activated cell sorting (FACS) and fluorescent microscopy were used to quantify and verify phagocytic activity (i.e., the population of sponge cells with internalized particles). Sponges were incubated with a green microalgae to test the effect of particle concentration on the percentage of phagocytic activity, and to determine the timing where the maximum of phagocytic cells are captured in a pulse-chase experiment. Lastly, we investigated the application of our phagocytic assay with other particle types (i.e., bacteria and fluorescent beads). The percentage of phagocytic cells that had incorporated algae, bacteria, and beads ranged between 5 to 24 %. We observed that the population of phagocytic sponge cell exhibited different morphologies and sizes depending on the type of particle presented to the sponge. Phagocytosis was positively related to algal concentration suggesting that sponge cells adjust their phagocytic activity depending on the number of particles they encounter. Our results further revealed that sponge phagocytosis initiates within minutes after exposure to the particles. Fluorescent and TEM microscopy rectified algal internalization and potential digestion in sponge cells, and suggests translocation between choanocyte and archeocyte-like cells over time. To our knowledge, this is the first quantitative in-vivo phagocytosis assay established in sponges that could be used to further explore phagocytosis as a cellular mechanism for sponges to differentiate between different microorganisms.
Agronomic treatments combined with embryo rescue for rapid generation advancement in tomato speed breeding
Authors: Gimeno-Páez Esther , Prohens Jaime , Moreno-Cerveró María , de Luis-Margarit Ana , Díez María José , Gramazio Pietro 
Published: March 2023

AbstractUnlike other major crops, little research has been performed on tomato for reducing generation time for speed breeding. We evaluated several agronomic treatments for reducing the generation time of tomato in the M82 (determinate) and Moneymaker (indeterminate) varieties and evaluated the best combination in conjunction with embryo rescue. In a first experiment under the autumn cycle, five container sizes, from 0.2 1 (XS) to 6 1 (XL), were evaluated. We found that plants from the XL containers exhibited better development and required less time from sowing to anthesis (DSA) and for anthesis to fruit ripening (DAR). In a second experiment, using XL containers in the autumn-winter cycle, we evaluated cold priming at the cotyledonary stage, water stress, P supplementation, and K supplementation on generation time. We found that, compared to the control, cold priming significantly reduced the number of leaves and plant height to first inflorescence as well as DSA (2.7 d), while K supplementation reduced DAR (8.8 d). No effects of these treatments were observed for other growth of physiological traits. In a third experiment with XL containers in the spring-summer cycle, the combination of cold priming plus K supplementation was tested, confirming the significant effect of the combination on generation time (2.9 d for DSA and 3.9 d for DAR). Embryo rescue during the cell expansion cycle (average of 22.0 d and 23.3 d after anthesis for M82 and Moneymaker, respectively) allowed shortening the generation time by 8.7 d in M82 and 11.6 d in Moneymaker compared to thein plantafruit ripening. The combination of agronomic treatments with embryo rescue can make an effective contribution to increase the number of generations per year for speed breeding in tomato from the current three to four.
In vivo ephaptic coupling allows memory network formation
Authors: Pinotsis Dimitris A. , Miller Earl K. 
Published: March 2023

AbstractIt is increasingly clear that memories are distributed across multiple brain areas. Such “engram complexes” are important features of memory formation and consolidation. Here, we test the hypothesis that engram complexes are formed in part by bioelectric fields that sculpt and guide the neural activity and tie together the areas that participate in engram complexes. Like the conductor of an orchestra, the fields influence each musician or neuron and orchestrate the output, the symphony. Our results use the theory of synergetics, machine learning and data from a spatial delayed saccade task and provide evidence for in vivo ephaptic coupling in memory representations.
MEDIPIPE: an automated and comprehensive pipeline for cfMeDIP-seq data quality control and analysis
Authors: Zeng Yong , Wenbin Ye , Stutheit-Zhao Eric Y. , Han Ming , Bratman Scott V. , Pugh Trevor J. , He Housheng Hansen 
Published: March 2023

AbstractSummarycell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) has emerged as a promising non-invasive technology to detect cancers and monitor treatments. Several bioinformatics tools are available for cfMeDIP-seq data analysis. However, an easy to implement and flexible pipeline, particularly, for large-scale cfMeDIP-seq profiling, is still lacking. Here we present the MEDIPIPE, which provides a one-stop solution for cfMeDIP-seq data quality control, methylation quantification and sample aggregation. The major advantages of MEDIPIPE are: 1) it is easy to implement and reproduce with automatically deployed execution environments; 2) it can handle different experimental settings with a single input configuration file; 3) it is computationally efficient for large-scale cfMeDIP-seq profiling data analysis and aggregation.Availability and implementationThis pipeline is an open-source software under the MIT license and it is freely available athttps://github.com/yzeng-lol/MEDIPIPE.Contactyzeng@uhnresearch.caortrevor.pugh@utoronto.caorhansenhe@uhnresearch.caSupplementary informationSupplementary data are appended.
Evaluating Tuning Strategies for Sequence Generation with Protein Language Models
Authors: Nathansen Andrea , Klein Kevin , Renard Bernhard Y. , Nowicka Melania , Bartoszewicz Jakub M. 
Published: March 2023

AbstractDesigning artificial proteins with specialized functions promises new solutions for biological, medical, and environmental use cases. This field benefits from advances in natural language processing, with state-of-the-art text generation models already being successfully applied to protein sequences. Openly available pre-trained protein language models are able to generate artificial protein sequences and can be finetuned on very specific tasks. Considering the high computational cost of finetuning a model exclusively for one downstream task, prompt tuning has been proposed as a more cost-efficient alternative that shares one model across different tasks. However, no openly available implementation of this approach compatible with protein language models has been previously published. Thus, we adapt an open-source codebase designed for NLP models to build a pipeline for prompt tuning on protein sequence data, supporting the protein language models ProtGPT2 and RITA. We benchmark this implementation for generating proteins of a specific family and evaluate the approach using text processing metrics as well as family membership prediction and protein activity prediction of generated sequences. Our results confirm the advantages of prompt tuning in resource usage, especially storage, encouraging further research and expansion of this technique to related use cases. For our evaluated use case, prompt tuning does not reach up to finetuning in terms of the quality of generated protein sequences, indicating the need for more extensive optimization. Lastly, we observe discrepancies between results of similar evaluation tools, highlighting open problems for principled assessment of protein sequence generation quality.
Predicting CRISPR-Cas12a guide efficiency for targeting using Machine Learning
Authors: O’Brien Aidan , Bauer Denis C. , Burgio Gaetan 
Published: March 2023

AbstractGenome editing through the development of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeat) – Cas technology has revolutionized many fields in biology. Beyond Cas9 nucleases, Cas12a (formerly Cpf1) has emerged as a promising alternative to Cas9 for editing AT-rich genomes. Despite the promises, guide RNA efficiency prediction through computational tools search still lacks accuracy. Through a computational meta-analysis, here we report that Cas12a target and off-target cleavage behaviour are factor of nucleotide bias combined with nucleotide mismatches relative to the protospacer adjacent motif (PAM) site. These features helped to train a machine learning random forest algorithm to improve the accuracy by at least 15% to existing algorithms to predict guide RNA efficiency for Cas12a enzyme. Despite the progresses, our report underscores the need for more representative datasets and further benchmarking to reliably and accurately predict guide RNA efficiency and off-target effects for Cas12a enzymes.
Importance of genetic architecture in marker selection decisions for genomic prediction
Authors: Coletta Rafael Della , Fernandes Samuel B. , Monnahan Patrick J. , Mikel Mark A. , Bohn Martin O. , Lipka Alexander E. , Hirsch Candice N. 
Published: March 2023

AbstractBreeders commonly use genetic markers to predict the performance of untested individuals as a way to improve the efficiency of breeding programs. These genomic prediction models have almost exclusively used single nucleotide polymorphisms (SNPs) as their source of genetic information, even though other types of markers exist, such as structural variants (SVs). Given that SVs are associated with environmental adaptation and not all of them are in linkage disequilibrium to SNPs, SVs have the potential to bring additional information to multi-environment prediction models that are not captured by SNPs alone. Here, we evaluated different marker types (SNPs and/or SVs) on prediction accuracy across a range of genetic architectures for simulated traits across multiple environments. Our results show that SVs can improve prediction accuracy by up to 19%, but it is highly dependent on the genetic architecture of the trait. Differences in prediction accuracy across marker types were more pronounced for traits with high heritability, high number of QTLs, and SVs as causative variants. In these scenarios, using SV markers resulted in better prediction accuracies than SNP markers, especially when predicting untested genotypes across environments, likely due to more predictors being in linkage disequilibrium with causative variants. The simulations revealed little impact of different effect sizes between SNPs and SVs as causative variants on prediction accuracy. This study demonstrates the importance of knowing the genetic architecture of a trait in deciding what markers and marker types to use in large scale genomic prediction modeling in a breeding program.Key messageWe demonstrate potential for improved multi-environment genomic prediction accuracy using structural variant markers. However, the degree of observed improvement is highly dependent on the genetic architecture of the trait.
Bacteriophage-mediated lysis supports robust growth of amino acid auxotrophs
Authors: Pherribo Gordon J. , Taga Michiko E. 
Published: March 2023

AbstractThe majority of microbes are auxotrophs – organisms unable to synthesize one or more metabolites required for their growth. Auxotrophy is thought to confer an evolutionary advantage, yet auxotrophs must rely on other organisms that produce the metabolites they require. The mechanisms of metabolite provisioning by “producers” remain unknown. In particular, it is unclear how metabolites such as amino acids and cofactors, which are found inside the cell, are released by producers to become available to auxotrophs. Here, we explore metabolite secretion and cell lysis as two distinct possible mechanisms that result in release of intracellular metabolites from producer cells. We measured the extent to which secretion or lysis ofEscherichia coliandBacteroides thetaiotaomicronamino acid producers can support the growth of engineeredEscherichia coliamino acid auxotrophs. We found that cell-free supernatants and mechanically lysed cells provide minimal levels of amino acids to auxotrophs. In contrast, bacteriophage lysates of the same producer bacteria can support as many as 47 auxotroph cells per lysed producer cell. Each phage lysate released distinct levels of different amino acids, suggesting that in a microbial community the collective lysis of many different hosts by multiple phages could contribute to the availability of an array of intracellular metabolites for use by auxotrophs. Based on these results, we speculate that viral lysis could be a dominant mechanism of provisioning of intracellular metabolites that shapes microbial community structure.
Inhibition of broomrape germination by 2,4-diacetylphloroglucinol produced by environmentalPseudomonas
Authors: Lurthy Tristan , Perot Ségolène , Gerin-Eveillard Florence , Rey Marjolaine , Wisniewski-Dyé Florence , Vacheron Jordan , Prigent-Combaret Claire 
Published: March 2023

AbstractPhloroglucinol compounds (PGCs) produced by environmentalPseudomonasare well known for their capacity to limit plant-pathogen infection. Although PGCs and more specifically 2,4-diacetylphloroglucinol (DAPG) are well studied for their antimicrobial properties, they are to some extent toxic for crop plants. Parasitic weeds such as broomrapes (Phelipanche ramosaandOrobanche cumana) cause severe damage to crops and their development must be controlled. Here, we assessed the potential herbicidal effect of the bacterial modelPseudomonas ogaraeF113, a PGCs-producing bacterium, on parasitic weed germination. We show using a mutagenesis approach that PGCs produced in bacterial supernatants are the main determinant inhibiting the germination of broomrapes. The use of individual or cocktails of pure PGCs revealed that the inhibition of the germination depends on the PGCs molecular structure and their concentrations as well as the broomrape species and pathovars. Furthermore, the inhibition caused by the PGCs is irreversible, causing a brown coloration of the broomrape seeds. Then, we evaluated in non-sterile soils the ability of bacterial inoculants or chemical DAPG to limit the infection of broomrapes on oil seed rape. Only the inoculation of PGCs-producing bacteria limited the infection ofP. ramosa. Moreover, elemental profiling analysis of oil seed rape revealed that neither the inoculant nor applied DAPG affected the nutrition capacity of the oil seed rape. Our study expands the knowledge on the role that these multi-talented plant-beneficialPseudomonasplay in the environment and open new avenues for the development of natural bioherbicides to ward off parasitic plant infection.
Humoral and T-cell-mediated responses to a pre-clinical Zika vaccine candidate that utilizes a unique insect-specific flavivirus platform
Authors: Porier Danielle L. , Adam Awadalkareem , Kang Lin , Michalak Pawel , Tupik Juselyn , Santos Matthew A. , Lee Christy , Allen Irving C. , Wang Tian , Auguste Albert J. 
Published: March 2023

ABSTRACTVaccination is critical for the control and prevention of viral outbreaks, yet conventional vaccine platforms may involve trade-offs between immunogenicity and safety. Insect-specific viruses have emerged as a novel vaccine platform to overcome this challenge. Detailed studies of humoral and T-cell responses induced by new insect-specific flavivirus (ISFV)-based vaccine platforms are needed to better understand correlates of protection and improve vaccine efficacy. Previously, we used a novel ISFV called Aripo virus (ARPV) to create a Zika virus (ZIKV) vaccine candidate (designated ARPV/ZIKV). ARPV/ZIKV demonstrated exceptional safety and single-dose efficacy, completely protecting mice from a lethal ZIKV challenge. Here, we explore the development of immune responses induced by ARPV/ZIKV immunization and evaluate its correlates of protection. Passive transfer of ARPV/ZIKV-induced immune sera to naïve mice prior to challenge emphasized the importance of neutralizing antibodies as a correlate of protection. Depletion of T-cells in vaccinated mice and adoptive transfer of ARPV/ZIKV-primed T-cells to naïve mice prior to challenge indicated that ARPV/ZIKV-induced CD4+and CD8+T-cell responses contribute to the observed protection but may not be essential for protection during ZIKV challenge. However, vaccination of Rag1 KO, Tcra KO, and muMt−mice demonstrated the critical role for ARPV/ZIKV-induced T-cells in developing protective immune responses following vaccination. Overall, both humoral and T-cell-mediated responses induced by ISFV-based vaccines are important for comprehensive immunity, and ISFV platforms continue to be a promising method for future vaccine development.
Bulk RNA-Sequencing of small airway cell cultures from IPF and post-COVID lung fibrosis patients illustrates disease signatures and differential responses to TGF-β1 treatment
Authors: Uhl Katie , Paithankar Shreya , Leshchiner Dmitry , Jager Tara E , Abdelgied Mohamed , Tripp Kaylie , Peraino Angela M , Kakazu Maximiliano Tamae , Lawson Cameron , Chesla Dave W , Murphy Edward R. , Prokop Jeremy , Chen Bin , Girgis Reda E , Li Xiaopeng 
Published: March 2023

AbstractIPF is a condition in which an injury to the lung leads to the accumulation of scar tissue. This fibrotic tissue reduces lung compliance and impairs gas exchange. Studies have shown that infection with COVID-19 significantly worsens the clinical outcomes of IPF patients. The exact etiology of IPF is unknown, but recent evidence suggests that the distal small airways, (those having a diameter less than 2 mm in adults), play a role in the early pathogenesis of IPF. TGF-β1 is a main driver of fibrosis in a variety of tissues; the binding of TGF-β1 to its receptor triggers a signaling cascade that results in inflammatory signaling, accumulation of collagen and other components of the extracellular matrix, and immune system activation. This study aimed to investigate possible mechanisms that contribute to worsening lung fibrosis in IPF patients after being diagnosed with COVID-19, with a particular focus on the role of TGF-β1. Small airway cell cultures derived from IPF and post-COVID-19 IPF patient transplant tissues were submitted for RNA-sequencing and differential gene expression analysis. The genetic signatures for each disease state were determined by comparing the differentially expressed genes present in the cells cultured under control conditions to cells cultured with TGF-β1. The genes shared between the culture conditions laid the framework for determining the genetic signatures of each disease. Our data found that genes associated with pulmonary fibrosis appeared to be more highly expressed in the post-COVID fibrosis samples, under both control and TGF-β1-treated conditions. A similar trend was noted for genes involved in the TGF-β1 signaling pathway; the post-COVID fibrosis cell cultures seemed to be more responsive to treatment with TGF-β1. Gene expression analysis, RT-PCR, and immunohistochemistry confirmed increased levels of BMP signaling in the IPF small airway cell cultures. These findings suggest that TGF-β1 signaling in IPF small airway cells could be inhibited by BMP signaling, leading to the differences in genetic signatures between IPF and post-COVID fibrosis.
Small Molecule Screen Identifies Non-Catalytic USP3 Chemical Handle
Authors: Mann Mandeep K. , Wolf Esther , Silva Madhushika , Kwak Haejin , Wilson Brian , Wilson Derek J. , Harding Rachel J. , Schapira Matthieu 
Published: March 2023

ABSTRACTZinc-finger ubiquitin binding domains (ZnF-UBDs) are non-catalytic domains mostly found in deubiquitylases (DUBs). They represent an underexplored opportunity for the development of deubiquitylase-targeting chimeras (DUBTACs) to pharmacologically induce the deubiquitination of target proteins. We have previously shown that ZnF-UBDs are ligandable domains. Here, a focused small molecule library screen against a panel of eleven ZnF-UBDs led to the identification of59, a ligand engaging the ZnF-UBD of USP3 with a KDof 14 µM. The compound binds the expected C-terminal ubiquitin binding pocket of USP3 as shown by hydrogen-deuterium exchange mass spectrometry experiments and does not inhibit the cleavage of K48-linked di-ubiquitin by USP3. As such this compound could serve as a chemical starting point to develop bifunctional DUBTACs recruiting USP3 for targeted deubiquitination.Table of contents graphic