bluuebunny/crossref_metadata_2025_split huggingface dataset:
Towards Environmental Control of Microbiomes
Authors: Sharpless Will , Sander Kyle , Song Fangchao , Kuehl Jennifer , Arkin Adam Paul 
Published: November 2022

AbstractMicrobial communities have consequential effects on health and the environment yet remain uncontrollable due to their complex dynamics. Ecological modeling offers a platform to overcome their nonlinear and interconnected nature but traditionally does not account for context-dependence. Here, we extend the generalized Lotka-Volterra (gLV) model to accommodate a varying environment by identifying how environmental changes alter species growth rates and interactions in a manner that predicts full community trajectories across environmental gradients. We identify key environment-varying interactions within a synthetic community derived from the Oryzae sativa rhizosphere, and demonstrate how variations in the environment change fixed point compositions and rates of convergence. With our model, we simulate how precise perturbations of the environment can offer improvements in an optimal control problem of driving a community to a target composition. We show that environmental perturbation can minimize the total species input (direct species perturbation) and greatly expand the set of initial states from which a desired target can be reached despite stochasticity. This work demonstrates that a formal perspective on environmental influence of community dynamics is valuable for not only understanding seasonal changes or anthropogenic manipulations, but is critical for improving control of the microbiome.
Optical tuning of polymer functionalized zinc oxide quantum dots as a selective probe for specific detection of antibiotics
Authors: Verma Awadhesh Kumar , Dhiman Tarun Kumar , Lakshmi GBVS , Solanki Pratima 
Published: November 2022

AbstractIt is crucial to monitor the antibiotic levels in the environment like water, food products in the current scenario as the antibiotic concentration above threshold is harmful for the human health. Excess consumption of antibiotics leads to antibiotic resistance that hinders the control and cure of microbial diseases. So, these challenges motivated to devise an optical nano-senor which can sense the ultra-low concentration of antibiotics. In this proposed research work, emphasis is to develop a method which is simple and selective to analyze the detection and presence of antibiotics in various samples like tape water milk etc. using fluorescent ZnO QDs based nano-sensor. For this, fluorescent and different polymers (polyvinylalcohol – PVA and polyvinylpyrrolidine – PVP) capped ZnO QDs were synthesized using modified sol-gel technique. These were used as fluorescent probe to monitor the presence of antibiotics. The optical characterizations of synthesized QDs were performed using UV-Visible absorption & fluorescence spectroscopic methods while structural characteristics were analyzed by using FTIR, XRD and EDX. Charge on the synthesized QDs were obtained with the help of ZETA potential. Here ten different antibiotics were targeted among, Ciprofloxacin and Moxifloxacin have shown excellent sensing and specificity with PVA-ZnO QDs and PVP-ZnO QDs respectively.
Pairing Metagenomics and Metaproteomics to Characterize Ecological Niches and Metabolic Essentiality of gut microbiomes
Authors: Wang Tong , Li Leyuan , Figeys Daniel , Liu Yang-Yu 
Published: November 2022

AbstractThe genome of a microorganism encodes its potential functions that can be implemented through expressed proteins. It remains elusive how a protein’s selective expression depends on its metabolic essentiality to microbial growth or its ability to claim resources as ecological niches. To reveal a protein’s metabolic or ecological role, we developed a computational pipeline, which pairs metagenomics and metaproteomics data to quantify each protein’s gene-level and protein-level functional redundancy simultaneously. We first illustrated the idea behind the pipeline using simulated data of a consumer-resource model. We then validated it using real data from human and mouse gut microbiome samples. In particular, we analyzed ABC-type transporters and ribosomal proteins, confirming that the metabolic and ecological roles predicted by our pipeline agree well with prior knowledge. Finally, we performedin vitrocultures of a human gut microbiome sample and investigated how oversupplying various sugars involved in ecological niches influences the community structure and protein abundance. The presented results demonstrate the performance of our pipeline in identifying proteins’ metabolic and ecological roles, as well as its potential to help us design nutrient interventions to modulate the human microbiome.
A graph clustering algorithm for detection and genotyping of structural variants from long reads
Authors: Gaitán Nicolás , Duitama Jorge 
Published: November 2022

ABSTRACTStructural variants (SV) are polymorphisms defined by their length (>50 bp). The usual types of SVs are deletions, insertions, translocations, inversions, and copy number variants. SV detection and genotyping is fundamental given the role of SVs in phenomena such as phenotypic variation and evolutionary events. Thus, methods to identify SVs using long read sequencing data have been recently developed. We present an accurate and efficient algorithm to predict SVs from long-read sequencing data. The algorithm starts collecting evidence (Signatures) of SVs from read alignments. Then, signatures are clustered based on a Euclidean graph with coordinates calculated from lengths and genomic positions. Clustering is performed by the DBSCAN algorithm, which provides the advantage of delimiting clusters with high resolution. Clusters are transformed into SVs and a Bayesian model allows to precisely genotype SVs based on their supporting evidence. This algorithm is integrated in the single sample variants detector of the Next Generation Sequencing Experience Platform (NGSEP), which facilitates the integration with other functionalities for genomics analysis. For benchmarking, our algorithm is compared against different tools using VISOR for simulation and the GIAB SV dataset for real data. For indel calls in a 20x depth Nanopore simulated dataset, the DBSCAN algorithm performed better, achieving an F-score of 98%, compared to 97.8 for Dysgu, 97.8 for SVIM, 97.7 for CuteSV, and 96.8 for Sniffles. We believe that this work makes a significant contribution to the development of bioinformatic strategies to maximize the use of long read sequencing technologies.
Human influenza A virus H1N1 in marine mammals in California, 2019
Authors: Plancarte Magdalena , Kovalenko Ganna , Baldassano Julie , Ramírez Ana L. , Carrillo Selina , Duignan Pádraig J. , Goodfellow Ian , Bortz Eric , Dutta Jayeeta , van Bakel Harm , Coffey Lark L. 
Published: November 2022

AbstractFrom 2011-2018, we conducted surveillance in marine mammals along the California coast for influenza A virus (IAV), frequently detecting anti-influenza antibodies and intermittently detecting IAV. In spring 2019, this pattern changed. Despite no change in surveillance intensity, we detected IAV RNA in 10 samples in March and April, mostly in nasal and rectal swabs from northern elephant seals (Mirounga angustirostris). Although virus isolation was unsuccessful, IAV sequenced from one northern elephant seal nasal swab showed close genetic identity with pandemic H1N1 IAV subclade 6B.1A.1 that was concurrently circulating in humans in the 2018/19 influenza season. This represents the first report of human A(H1N1)pdm09 IAV in northern elephant seals since 2010, suggesting IAV continues to spill over from humans to pinnipeds.
Design And Optimization Studies Of Tablet In Tablet Formulation Of Diclofenac And Misoprostol: Application Of Response Surface Methodology And Compressional Behaviour Strategy
Authors: Shah Shabana Naz , Ali Huma , Yasmin Riffat , Perveen Shaheen , Zafar Farya , Israr Fozia , Aslam Nousheen 
Published: November 2022

AbstractThe present study was aimed to develop compression coated tablets of diclofenac sodium (75mg) in the inner core and misoprostol (200 mg) as the outer shell for the effective treatment of rheumatoid arthritis as this dosing frequency is not available in the market yet. Diclofenac sodium inner tablet was manufactured by wet granulation and its enteric coating was applied by Eudragit L 100-55, Isopropyl Alcohol and Opadry II Blue 85 F205034. While immediate-release misoprostol outer shell was also manufactured by wet granulation and coated by Opadry white and Polyethylene glycol 6000. Design of experiment®software was used for formulation design and optimization. Quality attributes such as tablet weight, hardness, disintegration time, percent drug dissolution and assay were performed as per official methods and satisfactory results were reported. Physical and chemical stability of selected formulations was evaluated following the ICH guidelines for accelerated stability testing. The compressional analysis of optimized formulation was performed to check the optimum compression pressure to obtain a stable formulation. Based on satisfactory quality attributes; formulation DF9MF7 was successfully developed as compression coated tablet with calculated shelf life of 4.8years. Compression coated tablets comprising of enteric coated diclofenac sodium as inner core and misoprostol as outer shell were successfully developed by wet granulation.
Disruption ofZea mays isochorismate synthase1decreases PHENYLALANINE AMMONIA LYASE activity and suppresses hypersensitive response-induced metabolism
Authors: Benke Ryan L. , McCoy Rachel M. , Ibrahim Iskander M. , Simpson Jeffery P. , Muro-Villanueva Fabiola , Zhan Ross , Chapple Clint , Widhalm Joshua R. , Puthiyaveetil Sujith , Johal Gurmukh S. , Dilkes Brian P. 
Published: November 2022

AbstractISOCHORISMATE SYNTHASE (ICS) catalyzes the isomerization of chorismate to isochorismate, an essential precursor in the biosynthesis of the Photosystem I electron carrier phylloquinone and of one of two pathways for the biosynthesis of the defense response hormone salicylic acid (SA). We characterized aZea mays ics1mutant for impacts on metabolism, photosynthesis, and immune signaling. Phylloquinone was reduced in the mutant resulting in low electron transfer rates and high electron backflow rates. SA accumulation induced by autoactive alleles of the nucleotide-binding leucine-rich repeat (NLR) geneResistance to Puccinia sorgi1(Rp1)requiredics1. Induced accumulation of SA was not required for lesion formation by the autoactiveRp1-D21#4allele. Metabolomic analyses and SA supplementation ofRp1-D21#4mutants,ics1-1mutants andRp1-D21#4; ics1-1double mutants demonstrated that most hypersensitive response-induced metabolism requiredics1but this was independent of SA accumulation. Both the PAL and ICS pathways contributed to SA biosynthesis in maize as labeled phenylalanine was incorporated into SA glucoside. Maizeics1-1mutants had low PHENYLALANINE AMMONIA LYASE activity, accumulated phenylalanine, and decreased abundance of phenylalanine derived metabolites. This demonstrates that the ICS and PAL pathways interact by a yet unknown mechanism complicating the interpretation of SA biosynthesis in plants from genetics alone.
Challenges in screening forde novononcoding variants contributing to genetically complex phenotypes
Authors: Castro Christopher P. , Diehl Adam G. , Boyle Alan P. 
Published: November 2022

AbstractUnderstanding the genetic basis for complex, heterogeneous disorders, such as autism spectrum disorder (ASD), is a persistent challenge in human medicine. Owing to their phenotypic complexity, the genetic mechanisms underlying these disorders may be highly variable across individual patients. Furthermore, much of their heritability is unexplained by known regulatory or coding variants. Indeed, there is evidence that much of the causal genetic variation stems from rare andde novovariants arising from ongoing mutation. These variants occur mostly in noncoding regions, likely affecting regulatory processes for genes linked to the phenotype of interest. However, because there is no uniform code for assessing regulatory function, it is difficult to separate these mutations into likely functional and nonfunctional subsets. This makes finding associations between complex diseases and potentially causalde novosingle-nucleotide variants (dnSNVs) a difficult task. To date, all but one published study in this area has failed to find any significant associations between dnSNVs from ASD patients and any class of known regulatory elements. We sought to identify the underlying reasons for this and present strategies for overcoming these challenges. We show that, contrary to previous claims, the main reason for failure to find robust statistical enrichments is not the number of families sampled, but the quality and relevance to ASD of the annotations used to prioritize dnSNVs, and the reliability of the set of dnSNVs itself. We present a list of recommendations for designing future studies of this sort that will help researchers avoid common pitfalls.
“Peptidergic modulation of motor neuron output via CART signaling at C bouton synapses”
Authors: Eleftheriadis Panagiotis E. , Pothakos Konstantinos , Sharples Simon A. , Apostolou Panagiota E. , Mina Maria , Tetringa Efstathia , Miles Gareth B. , Zagoraiou Laskaro 
Published: November 2022

AbstractThe intensity of muscle contraction, and therefore movement vigour, needs to be adaptable to enable complex motor behaviors. This can be achieved by adjusting the properties of motor neurons, which form the final common pathway for all motor output from the central nervous system. Here we identify novel roles for a neuropeptide, Cocaine and Amphetamine Regulated Transcript (CART), in the control of movement vigour. We reveal distinct, but parallel mechanisms by which CART and acetylcholine, both released at C bouton synapses on motor neurons, selectively amplify the output of subtypes of motor neurons that are recruited during intense movement. We find that mice with broad genetic deletion of CART or selective elimination of acetylcholine from C boutons exhibit deficits in behavioral tasks that require higher levels of motor output. Overall, these data uncover novel spinal modulatory mechanisms that control movement vigour to support movements that require a high degree of muscle force.
Structural transitions in TCTP tumor protein upon Mcl-1 binding
Authors: Malard Florian , Sizun Christina , Thureau Aurélien , Carlier Ludovic , Lescop Ewen 
Published: November 2022

AbstractSummaryTranslationally Controlled Tumour Protein (TCTP) is a pro-survival factor in tumor cells. TCTP inhibits the mitochondrial apoptosis pathway by potentiating the anti-apoptotic Bcl-2 family members Mcl-1 and Bcl-xL. Specifically, TCTP binds Bcl-xL and inhibits the Bax-dependent Bcl-xL-induced cytochrome c release and TCTP reduces Mcl-1 turnover by inhibiting its ubiquitinylation, thus resulting in decreased Mcl-1 mediated apoptosis. TCTP owns a BH3-like motif forming a β-strand buried in the globular domain of the protein. The crystal structure of TCTP BH3-like peptide in complex with Bcl-xL highlighted the α-helical conformation of TCTP BH3-like motif, suggesting major changes in TCTP structure upon complex formation. However, the structural impact of the interaction on the full-length TCTP and the structural description of TCTP/Mcl-1 interaction are still lacking. Here using biophysical/biochemical methods (NMR, SAXS, circular dichroism, limited proteolysis), we provide an in-depth description of the TCTP/Mcl-1 complex. We demonstrate that full length TCTP binds to the BH3 binding groove of Mcl-1 via its BH3-like motif which interconverts between different binding modes at the micro- to milli-second timescale. As a consequence of the engagement of the BH3-like motif in the interface, the TCTP globular domain is destabilized into a molten-globule state. We also establish that the residue D16 in TCTP BH3-like motif is crucial for the stability and dynamics of the intermolecular interface. As a conclusion, we reveal here in details the structural plasticity of TCTP and discuss its implications for TCTP biology and for future anticancer drug design strategies aiming at targeting TCTP complexes.ContactEwen Lescop,ewen.lescop@cnrs.fr.Supplementary InformationSupplementary figures, tables and files.
Uncovering molecular grammars of intrinsically disordered regions that organize nucleolar fibrillar centers
Authors: King Matthew R. , Lin Andrew Z. , Ruff Kiersten M. , Farag Mina , Ouyang Wei , Vahey Michael D. , Lundberg Emma , Pappu Rohit V. 
Published: November 2022

AbstractThe nucleolus is a multilayered structure. Each layer is thought to be a compositionally distinct phase, although how these phases form and interface with one another remains unclear. Using computational, proteomics,in vitro, andin vivostudies, we uncover distinct molecular grammars within intrinsically disordered regions (IDRs) of nucleolar proteins that localize to fibrillar centers (FCs) and dense fibrillar components (DFCs). FC and DFC proteins feature two distinct types of IDRs namely those with long tracts of acidic residues and those with blocks of lysines interspersed by acid-rich-regions. We find that phase separation driven by complex coacervation in mixtures of nucleolar proteins, with their distinctive IDRs, and ribosomal DNA and RNA molecules is sufficient to drive the formation of structural facsimiles of FCs and DFCs.One-Sentence SummaryFacsimiles of core nucleolar substructures were reconstituted via phase separation of key protein and nucleic acid mixtures.
Parent-reported phenotype data on chromosome 6 aberrations collected via an online questionnaire: data consistency and data availability
Authors: Engwerda Aafke , Frentz Barbara , Rraku Eleana , Simoes de Souza Nadia F. , Swertz Morris A. , Plantinga Mirjam , Kerstjens-Frederikse Wilhelmina S. , Ranchor Adelita V. , van Ravenswaaij-Arts Conny M. A. 
Published: November 2022

AbstractBackgroundEven with the introduction of new genetic techniques that enable accurate genomic characterization, knowledge about the phenotypic spectrum of rare chromosomal disorders is still limited, both in literature and existing databases. Yet this clinical information is of utmost importance for health professionals and the parents of children with rare diseases. Since existing databases are often hampered by the limited time and willingness of health professionals to input new data, we collected phenotype data directly from parents of children with a chromosome 6 disorder. These parents were reached via social media, and the information was collected via the online Chromosome 6 Questionnaire, which includes 115 main questions on congenital abnormalities, medical problems, behaviour, growth and development. Here, we assess data consistency by comparing parent-reported phenotypes to phenotypes based on copies of medical files for the same individual and data availability by comparing the data available on specific characteristics reported by parents to data available in existing literature.ResultsThe reported answers to the main questions on phenotype characteristics were 85–95% consistent, and the consistency of answers to subsequent more detailed questions was 77–96%. For all but two main questions, significantly more data was collected from parents via the Chromosome 6 Questionnaire than was currently available in literature. For the topics developmental delay and brain abnormalities, no significant difference in the amount of available data was found. The only feature for which significantly more data was available in literature was a sub-question on the type of brain abnormality present.ConclusionsThis is the first study to compare phenotype data collected directly from parents to data extracted from medical files on the same individuals. We found that the data was highly consistent, and phenotype data collected via the online Chromosome 6 Questionnaire resulted in more available information on most clinical characteristics when compared to phenotypes reported in literature reports thus far. We encourage active patient participation in rare disease research and have shown that parent-reported phenotypes are very reliable and contribute to our knowledge of the phenotypic spectrum of rare chromosomal disorders.
Periodic neglect after frontoparietal lesions provides causal evidence for rhythmic attention sampling
Authors: Raposo Isabel , Szczepanski Sara M. , Haaland Kathleen , Endestad Tor , Solbakk Anne-Kristin , Knight Robert T. , Helfrich Randolph F. 
Published: November 2022

SummaryContemporary models conceptualize spatial attention as a blinking spotlight that sequentially samples visual space. Hence, behavior fluctuates over time even in states of presumed ‘sustained’ attention. Recent evidence suggested that rhythmic neural activity in the frontoparietal network constitutes the functional basis of rhythmic attentional sampling. However, causal evidence to support this notion remains absent. Using a lateralized spatial attention task, we addressed this issue in patients with focal lesions in the frontoparietal attention network. Our results uncovered that frontoparietal lesions introduce periodic neglect, i.e., temporally-specific behavioral deficits that were aligned with the underlying neural oscillations. Attention-guided perceptual sensitivity was on par with healthy controls during optimal phases but attenuated during the less excitable sub-cycles. Theta-dependent sampling (3 – 8 Hz) was causally dependent on prefrontal cortex, while alpha-band sampling (8 – 14 Hz) emerged from parietal areas. Collectively, our findings reveal that lesion-induced high amplitude, low frequency brain activity is not epiphenomenal, but has immediate behavioral consequences. More generally, these results provide causal evidence for the hypothesis that the functional architecture of attention is inherently rhythmic.
CellSighter – A neural network to classify cells in highly multiplexed images
Authors: Amitay Yael , Bussi Yuval , Feinstein Ben , Bagon Shai , Milo Idan , Keren Leeat 
Published: November 2022

AbstractMultiplexed imaging enables measurement of multiple proteinsin situ, offering an unprecedented opportunity to chart various cell types and states in tissues. However, cell classification, the task of identifying the type of individual cells, remains challenging, labor-intensive, and limiting to throughput. Here, we present CellSighter, a deep-learning based pipeline to accelerate cell classification in multiplexed images. Given a small training set of expert-labeled images, CellSighter outputs the label probabilities for all cells in new images. CellSighter achieves over 80% accuracy for major cell types across imaging platforms, which approaches inter-observer concordance. Ablation studies and simulations show that CellSighter is able to generalize its training data and learn features of protein expression levels, as well as spatial features such as subcellular expression patterns. CellSighter’s design reduces overfitting, and it can be trained with only thousands or even hundreds of labeled examples. CellSighter also outputs a prediction confidence, allowing downstream experts control over the results. Altogether, CellSighter drastically reduces hands-on time for cell classification in multiplexed images, while improving accuracy and consistency across datasets.