bluuebunny/crossref_metadata_2025_split huggingface dataset:
Innovative Research Experiences for Underrepresented Undergraduates: A Collaborative STEM Research Program as a Pathway to Graduate School
Authors: Hacisalihoglu Gokhan 
Published: January 2023

ABSTRACTThis paper aims to describe, reflect on, and explore the perceptions of underrepresented undergraduate researcher students towards the plantREU2 internship program of two universities (an HBCU and an R1 university) in Florida, USA. The plantREU2 internship program resulted from a collaboration between UF and FAMU and was located in UF main campus in Gainesville, Florida. A total of 17 students completed 10-week summer projects in plant biology. The program (PlantREU2) had a strong record of success. Over 40% of plantREU2 students co-authored a journal publication and received travel awards to attend Maize Genetics Conference. Furthermore, plantREU2 participants were significantly graduated within six years. The underrepresentation of minorities in STEM is a critical challenge. The findings of this study can be adapted similarly for underrepresented undergraduates. The vast majority of interns enrolled in post-graduate programs could therefore be a model to engage traditionally underrepresented students in STEM disciplines.
Transcription factor AhR regulates glutathione S-transferases (GSTs) conferring resistance tolambda-cyhalothrin inCydia pomonella
Authors: Hu Chao , Liu Yu-Xi , Zhang Shi-Pang , Wang Ya-Qi , Gao Ping , Li Yu-Ting , Yang Xue-Qing 
Published: January 2023

ABSTRACTTranscription factor aryl hydrocarbon receptor (AhR) can enhance insect resistance to insecticides by regulating the detoxification metabolic network. Our previous studies have confirmed that overexpression of cytochrome P450 monooxygenases (P450s) and glutathione S-transferases (GSTs) are both involved inlambda-cyhalothrin resistance inCydia pomonella. In this study, we report that AhR regulates GSTs thus conferringlambda-cyhalothrin resistance inC. pomonella. Spatiotemporal expression patterns indicated thatAhRgene ofC. pomonella(CpAhR) was highly expressed in the Malpighian tubules of larvae. Moreover, the expression ofCpAhRwas induced bylambda-cyhalothrin exposure and was up-regulated in alambda-cyhalothrin-resistant population. RNA interference (RNAi) of the expression ofCpAhRcould effectively decrease the relative expression level ofCpGSTe3and enzyme activity of GSTs, but not P450s, further reducing the tolerance of larvae tolambda-cyhalothrin. Furthermore, β-naphthoflavone (BNF), a novel agonist of AhR, can effectively increase the expression ofCpAhRand the activity of the GSTs enzyme, resulting in the enhancement of larvae tolerance tolambda-cyhalothrin. These results demonstrate thatlambda-cyhalothrin exposure can effectively activate the expression ofCpAhRand increase GSTs enzyme thus leading to the development of resistance tolambda-cyhalothrin, which enriches the theory of insecticide resistance regulation inC. pomonella.
CCR1 Mediates Müller Cell Activation and Photoreceptor Cell Death in Macular and Retinal Degeneration
Authors: Elbaz-Hayoun Sarah , Rinsky Batya , Hagbi-Levi Shira , Grunin Michelle , Chowers Itay 
Published: January 2023

AbstractMononuclear cells are involved in the pathogenesis of retinal diseases, including age-related macular degeneration (AMD). Here, we examined the mechanisms that underlie macrophage-driven retinal cell death. Monocytes were extracted from patients with AMD and differentiated into macrophages (hMdɸs), which were characterized based on proteomics, gene expression, andex vivoandin vivoproperties. Using bioinformatics, we identified the signaling pathway involved in macrophage-driven retinal cell death, and we assessed the therapeutic potential of targeting this pathway. We found that M2a hMdɸs were associated with retinal cell death in retinal explants and following adoptive transfer in a photic injury model. Moreover, M2a hMdɸs express several CCRI (C-C chemokine receptor type 1) ligands. Importantly, CCR1 was upregulated in Müller cells in models of retinal injury and aging, and CCR1 expression was correlated with retinal damage. Lastly, inhibiting CCR1 reduced photic-induced retinal damage, photoreceptor cell apoptosis, and retinal inflammation. These data suggest that hMdɸs, CCR1, and Müller cells work together to drive retinal and macular degeneration, suggesting that CCR1 may serve as a target for treating these sight-threatening conditions.
Identification of a novel enhancer essential forSatb1expression in TH2 cells and activated ILC2s
Authors: Nomura Aneela , Ohno-Oishi Michiko , Kobayashi Tetsuro , Seo Wooseok , Kakugawa Kiyokazu , Muroi Sawako , Yoshida Hideyuki , Endo Takaho A. , Moro Kazuyo , Taniuchi Ichiro 
Published: January 2023

AbstractThe genome organizer, special AT-rich binding protein-1 (SATB1) functions to globally regulate gene networks during primary T cells development and plays a pivotal role in lineage-specification in CD4+helper-, CD8+cytotoxic- and FOXP3+regulatory-T cell subsets. However, it remains unclear howSatb1gene expression is controlled, particularly in effector T cell function. Here, by using a novel reporter mouse strain expressing SATB1-Venus and genome editing, we have identified acis-regulatory enhancer, essential for maintainingSatb1expression specifically in TH2 cells. This enhancer is occupied by STAT6 and interacts withSatb1promoters through chromatin looping in TH2 cells. Reduction ofSatb1expression, by the lack of this enhancer, resulted in elevated IL-5 expression in TH2 cells. In addition, we found thatSatb1is induced in activated group 2 innate lymphoid cells (ILC2s) through this enhancer. Collectively, these results provide novel insights into howSatb1expression is regulated in TH2 cells and ILC2s during type 2 immune responses.
Aging Decreases the Precision of Visual Working Memory
Authors: Mohammadpour Esfahan Shahrzad , H.K Nili Mohammad-Hossein , Sanayei Mehdi , Rezayat Ehsan 
Published: January 2023

AbstractObjectivesWorking memory (WM) is a cognitive ability that enables us to hold information temporarily. As age increases during life, cognitive abilities such as WM performance decrease. Errors in WM tasks arise from different sources, such as decreasing precision and random response. In the current study, we investigated the effect of age on WM and elucidated sources of errors.MethodA total of 102 healthy individuals aged 18 to 71, participated in the study. A face-based visual WM task was designed and performed. Responses were collected using a graded scale in a delayed match-to-sample reproduction task.ResultsThe error of participants increased significantly as they aged. According to our analysis of the source of error, the standard deviation of error distribution increased considerably with age. However, there was no significant change in uniform probability with age. These observations were similar between male and female participants.ConclusionWe found that WM performance declines through the lifespan. Investigating the sources of error, we found that the precision of WM decreased with age. This decline was monotonous without any particular age at which a significant drop-off occurred. The results also indicated that the probability of guessing the response as a measure of random response is not affected by age.
A generative model of electrophysiological brain responses to stimulation: an approach to study perceptual stability
Authors: Vidaurre Diego 
Published: January 2023

AbstractEach brain response to a stimulus is, to a large extent, unique. However this variability, our perceptual experience feels stable. Standard decoding models, which utilise information across several areas to tap into stimuli representation and processing, are fundamentally based on averages. Therefore, they can focus precisely on the features that are most stable across stimulus presentations. But which are these features exactly is difficult to address in the absence of a generative model of the signal. Here, I introducegenephys, a generative model of brain responses to stimulation publicly available as a Python package that, when confronted with a decoding algorithm, can reproduce the structured patterns of decoding accuracy that we observe in real data. Using this approach, I characterise how these patterns may be brought about by the different aspects of the signal, which in turn may translate into distinct putative neural mechanisms. In particular, the model shows that the features in the data that support successful decoding —and, therefore, likely reflect stable mechanisms of stimulus representation— have an oscillatory component that spans multiple channels, frequencies and latencies of response; and an additive, slower response with a specific (cross-frequency) relation to the phase of the oscillatory component. At the individual trial level, still, responses are found to be highly variable, which can be due to various factors including phase noise and probabilistic activations.
An original potentiating mechanism revealed by the cryoEM structures of the human α7 nicotinic receptor in complex with nanobodies
Authors: Prevost Marie S. , Barilone Nathalie , Dejean De La Batie Gabrielle , Pons Stéphanie , Ayme Gabriel , England Patrick , Gielen Marc , Bontems François , Pehau-Arnaudet Gérard , Maskos Uwe , Lafaye Pierre , Corringer Pierre-Jean 
Published: January 2023

AbstractThe human α7 nicotinic receptor is a pentameric channel mediating cellular and neuronal communication. It has attracted considerable interest to design ligands for the treatment of neurological and psychiatric disorders. To develop a novel class of α7 ligands, we recently generated two nanobodies named E3 and C4 acting as positive and silent allosteric modulators respectively. Here, we solved the cryo-EM structures of the nanobody-receptor complexes. E3 and C4 bind to a common epitope involving two subunits at the apex of the receptor. They form by themselves a symmetric pentameric assembly that extends the extracellular domain. Unlike C4, the binding of E3 drives an active or desensitized conformation in the absence of orthosteric agonist, and mutational analysis shows a key contribution of a N-linked sugar moiety in mediating E3 potentiation. The nanobody E3, by remotely controlling the global allosteric conformation of the receptor, implements an original mechanism of regulation which opens new avenues for drug design.
Crystal structure of a mammalian CMTM6 and its interaction model with PD-L1
Authors: Zhang Senfeng , Xie Qingrong , Fu Chunting , Luo Yongbo , Sun Ziyi , Zhou Xiaoming 
Published: January 2023

AbstractCKLF-like MARVEL transmembrane domain-containing protein 6 (CMTM6) is a master regulator of PD-L1. By binding PD-L1 at the plasma membrane and recycling endosomes, CMTM6 prevents the lysosomal degradation of PD-L1 and maintains its cell surface expression, thus stabilizing the inhibitory PD-1/PD-L1 axis. However, the mechanism of CMTM6/PD-L1 interaction is unknown. Here we report the first experimentally determined structure of CMTM6 from bovine. Combined with a low-resolution cryo-EM map, computational docking analysis and a protein binding assay an interaction model between CMTM6 and PD-L1 was proposed, providing a structural framework for the CMTM6 regulation on PD-L1.
Identification of two distinct phylogenomic lineages and model strains for the understudied cystic fibrosis lung pathogenBurkholderia multivorans
Authors: Parfitt Kasia M. , Green Angharad E. , Connor Thomas R. , Neill Daniel R. , Mahenthiralingam Eshwar 
Published: January 2023

AbstractBurkholderia multivoransis the dominantBurkholderiapathogen recovered from lung infection in people with cystic fibrosis. However, as an understudied pathogen there are knowledge gaps in relation to its population biology, phenotypic traits and useful model strains. A phylogenomic study ofB. multivoranswas undertaken using a total of 283 genomes, of which 73 were sequenced and 49 phenotypically characterized as part of this study. Average nucleotide identity analysis (ANI) and phylogenetic alignment of core genes demonstrated that theB. multivoranspopulation separated into two distinct evolutionary clades, defined as lineage 1 (n= 58 genomes) and lineage 2 (n= 221 genomes). To examine the population biology ofB. multivorans, a representative subgroup of 77B. multivoransgenomes (28 from the reference databases and the 49-novel short-read genome sequences) were selected based on multilocus sequence typing (MLST), isolation source and phylogenetic placement criteria. Comparative genomics was used to identifyB. multivoranslineage-specific genes:ghrB_1in lineage 1, andglnM_2in lineage 2, and diagnostic PCRs targeting them successfully developed. Phenotypic analysis of 49 representativeB. multivoransstrains showed considerable variance with the majority of isolates tested being motile and capable of biofilm formation. A striking absence ofB. multivoransprotease activityin vitrowas observed, but no lineage-specific phenotypic differences demonstrated. Using phylogenomic and phenotypic criteria, three modelB. multivoransCF strains were identified, BCC0084 (lineage 1), BCC1272 (lineage 2a) and BCC0033 lineage 2b, and their complete genome sequences determined.B. multivoransCF strains BCC0033 and BCC0084, and the environmental reference strain, ATCC 17616, were all capable of short-term survival within a murine lung infection model. By mapping the population biology, identifying lineage-specific PCRs and model strains, we provide much needed baseline resources for future studies ofB. multivorans.
Computational mutagenesis by using AUTO-MUTE 2.0 to examine X-ray crystallography structures for p53 and the impact of its resolution on predictions
Authors: Sait Shaimaa , Vaisman Isoif 
Published: January 2023

ABSTRACTThe mutation of P53 is found in 50% of all human cancers, affecting the protein structure conformation, which further impacts its function. Identifying the appropriate protein structure for future research has been challenging. Many X-ray crystallography structures exist in the Protein Data Bank (PDB) for a given protein. We compared two proteins with different resolutions to determine whether the differences between the two structures were statistically significant. The present study used mutagenesis to study two structures of the protein P53 with various resolutions to assess how the conformation of the protein changes upon mutation. We used an AUTO-MUTE 2.0, which is a computational geometry method based on the Delaunay tessellation for predicting protein structures. The current study compares the prediction results obtained from different predictive methods. We used logistic regression models and corresponding receiver operating characteristic (ROC) curves to model the differences between structures using the variables available at PDB. We conclude from this study that x-ray crystallography is a sensitive and advanced technique, and the resulting proteins at different resolutions are similar.
The myocardium utilizes Pdgfra-PI3K signaling to steer towards the midline during heart tube formation
Authors: Shrestha Rabina , McCann Tess , Saravanan Harini , Lieberth Jaret , Koirala Prashanna , Bloomekatz Joshua 
Published: January 2023

AbstractCoordinated cell movement is a fundamental process in organ formation. During heart development, bilateral myocardial precursors collectively move towards the midline (cardiac fusion) to form the primitive heart tube. Along with extrinsic influences such as the adjacent anterior endoderm which are known to be required for cardiac fusion, we previously showed that the platelet-derived growth factor receptor alpha (Pdgfra) is also required. However, an intrinsic mechanism that regulates myocardial movement remains to be elucidated. Here, we uncover an essential intrinsic role in the myocardium for the phosphoinositide 3-kinase (PI3K) intracellular signaling pathway in directing myocardial movement towards the midline.In vivoimaging reveals that in PI3K-inhibited zebrafish embryos myocardial movements are misdirected and slower, while midline-oriented dynamic myocardial membrane protrusions become unpolarized. Moreover, PI3K activity is dependent on and genetically interacts with Pdgfra to regulate myocardial movement. Together our findings reveal an intrinsic myocardial steering mechanism that responds to extrinsic cues during the initiation of cardiac development.
Mitochondrial genes in the 22q11.2 deleted region regulate neural stem and progenitor cell proliferation
Authors: Campbell Philip D. , Lee Isaiah , Thyme Summer , Granato Michael 
Published: January 2023

SummaryMicrodeletion of a 3Mbp region encompassing 45 protein-coding genes at chromosome 22q11.2 (22q11.2DS) predisposes to multiple neurodevelopmental disorders and is one of the greatest genetic risk factors for schizophrenia. Defective mitochondrial function has been hypothesized to contribute to 22q11.2DS pathogenesis; however, which of the six mitochondrial genes contribute to neurodevelopmental phenotypes and their underlying mechanisms remain unresolved. To systematically test 22q11.2DS genes for functional roles in neurodevelopment and behavior, we generated genetic mutants for each of the 37 conserved zebrafish orthologs and performed high throughput behavioral phenotyping using seven behavioral assays. Through this unbiased approach, we identified five single-gene mutants with partially overlapping behavioral phenotypes. Two of these genes,mrpl40andprodha, encode for mitochondrial proteins and, similar to what we observed inmrpl40andprodhamutants, pharmacologic inhibition of mitochondrial function during development results in microcephaly. Finally, we show that bothmrpl40andprodhamutants display neural stem and progenitor cell phenotypes, with each gene regulating different neural stem cell populations. Combined, our results demonstrate a critical role for mitochondrial function in neural stem and progenitor cell populations in the developing vertebrate brain and provide compelling evidence that mitochondrial dysfunction during neurodevelopment is linked to brain volume and behavioral phenotypes observed in models of 22q11.2DS.
Sequence-to-sequence translation from mass spectra to peptides with a transformer model
Authors: Yilmaz Melih , Fondrie William E. , Bittremieux Wout , Melendez Carlo F. , Nelson Rowan , Ananth Varun , Oh Sewoong , Noble William Stafford 
Published: January 2023

AbstractA fundamental challenge for any mass spectrometry-based proteomics experiment is the identification of the peptide that generated each acquired tandem mass spectrum. Although approaches that leverage known peptide sequence databases are widely used and effective for well-characterized model organisms, such methods cannot detect unexpected peptides and can be impractical or impossible to apply in some settings. Thus, the ability to assign peptide sequences to the acquired tandem mass spectra without prior information—de novopeptide sequencing—is valuable for gaining biological insights for tasks including antibody sequencing, immunopeptidomics, and metaproteomics. Although many methods have been developed to address thisde novosequencing problem, it remains an outstanding challenge, in part due to the difficulty of modeling the irregular data structure of tandem mass spectra. Here, we describe Casanovo, a machine learning model that uses a transformer neural network architecture to translate the sequence of peaks in a tandem mass spectrum into the sequence of amino acids that comprise the generating peptide. We train a Casanovo model from 30 million labeled spectra and demonstrate that the model outperforms several state-of-the-art methods on a cross-species benchmark dataset. We also develop a version of Casanovo that is fine-tuned for non-enzymatic peptides. Finally, we demonstrate that Casanovo’s superior performance improves the analysis of immunopeptidomics and metaproteomics experiments and allows us to delve deeper into the dark proteome.
Lytic/Lysogenic Transition as a Life-History Switch
Authors: Roughgarden Joan 
Published: January 2023

AbstractThe transition between lytic and lysogenic life cycles is the most important feature of the life history of temperate viruses. To explain this transition, an optimal life-history model is offered based a discrete-time formulation of phage/bacteria population dynamics that features infection of bacteria by Poisson sampling of virions from the environment. The time step is the viral latency period. In this model density-dependent viral absorption onto the bacterial surface produces virus/bacteria coexistence and density-dependence in bacterial growth is not needed.The formula for the transition between lytic and lysogenic phases is termed the “fitness switch”. According to the model, the virus switches from lytic to lysogenic when its population grows faster as prophage than as virions produced by lysis of the infected cells, and conversely for the switch from lysogenic to lytic.A prophage that benefits the bacterium it infects automatically incurs lower fitness upon exiting the bacterial genome, resulting in its becoming locked into the bacterial genome in what is termed here as a “prophage lock”.The fitness switch qualitatively predicts the ecogeographic rule that environmental enrichment leads to microbialization with a concomitant increase in lysogeny, fluctuating environmental conditions promote virus-mediated horizontal gene transfer, and prophage-containing bacteria can integrate into the microbiome of a eukaryotic host forming a functionally integrated tripartite holobiont. These predictions accord more with the “Piggyback-the-Winner” hypothesis than with the “Kill-the-Winner” hypothesis in virus ecology.
PIsToN: Evaluating Protein Binding Interfaces with Transformer Networks
Authors: Stebliankin Vitalii , Shirali Azam , Baral Prabin , Chapagain Prem , Narasimhan Giri 
Published: January 2023

AbstractThe computational studies of protein binding are widely used to investigate fundamental biological processes and facilitate the development of modern drugs, vaccines, and therapeutics. Scoring functions aim to predict complexes that would be formed by the binding of two biomolecules and to assess and rank the strength of the binding at the interface. Despite past efforts, the accurate prediction and scoring of protein binding interfaces remain a challenge. The physics-based methods are computationally intensive and often have to trade accuracy for computational cost. The possible limitations of current machine learning (ML) methods are ineffective data representation, network architectures, and limited training data. Here, we propose a novel approach called PIsToN (evaluatingProtein bindingInterfaceswithTransformerNetworks) that aim to distinguish native-like protein complexes from decoys. Each protein interface is transformed into a collection of 2D images (interface maps), where each image corresponds to a geometric or biochemical property in which pixel intensity represents the feature values. Such a data representation provides atomic-level resolution of relevant protein characteristics. To buildhybridmachine learning models, additional empirical-based energy terms are computed and provided as inputs to the neural network. The model is trained on thousands of native and computationally-predicted protein complexes that contain challenging examples. The multi-attention transformer network is also endowed with explainability by highlighting the specific features and binding sites that were the most important for the classification decision. The developed PIsToN model significantly outperforms existing state-of-the-art scoring functions on well-known datasets.