bluuebunny/crossref_metadata_2025_split huggingface dataset:
M-Band Wavelet-Based Imputation of scRNA-seq Matrix and Multi-view Clustering of Cell
Authors: Liu Zihuan , Liu Tong , Sun Wenke , Zhao Yongzhong , Wang Xiaodi 
Published: December 2022

AbstractWavelet analysis has been recognized as a cutting-edge and promising tool in the fields of signal processing and data analysis. However, application of wavelet-based method in single-cell RNA sequencing (scRNA-seq) data is little known. Here, we present M-band wavelet-based imputation of scRNA-seq matrix and multi-view clustering of cells (WIMC). We applied integration of M-band wavelet analysis and uniform manifold approximation and projection (UMAP) to a panel of single cell sequencing datasets by breaking up the data matrix into a trend (low frequency or low resolution) component and (M-1) fluctuation (high frequency or high resolution) components. We leverage a non-parametric wavelet-based imputation algorithm of sparse data that integrates M-band wavelet transform for recovering dropout events of scRNA-seq datasets. Our method is armed with multi-view clustering of cell types, identity, and functional states, enabling missing cell types visualization and new cell types discovery. Distinct to standard scRNA-seq workflow, our wavelet-based approach is a new addition to resolve the notorious chaotic sparsity of scRNA-seq matrix and to uncover rare cell types with a fine-resolution.Author summaryWe develop M-band wavelet-based imputation of scRNA-seq matrix and multi-view clustering of cells. Our new approach integrates M-band wavelet analysis and UMAP to a panel of single cell sequencing datasets via breaking up the data matrix into a trend (low frequency or low resolution) component and (M– 1) fluctuation (high frequency or high resolution) components. Our method enables us to efficiently impute sparse scRNA-seq data matrix and to examine multi-view clustering of cell types, identity, and functional states, potentializing missing cell types recovery, fine rare cell types discovery, as well as functional cell states exploration.
Design principles for perfect adaptation in biological networks with nonlinear dynamics
Authors: Bhattacharya Priyan , Raman Karthik , Tangirala Arun K. 
Published: December 2022

AbstractEstablishing a mapping between the emergent biological properties and the repository of network structures has been of great relevance in systems and synthetic biology. Adaptation is one such biological property of paramount importance that promotes regulation in the presence of environmental disturbances. This paper presents a nonlinear systems theory-driven framework to identify the design principles for perfect adaptation. Based on the prior information about the network, we frame precise mathematical conditions for adaptation using nonlinear systems theory. We first deduce the mathematical conditions for perfect adaptation for constant input disturbances. Subsequently, we first translate these conditions to specific necessary structural requirements for adaptation in networks of small size and then extend to argue that there exist only two classes of architectures for a network of any size that can provide local adaptation in the entire state space, namely, incoherent feed-forward structure and negative feedback loop with buffer node. The additional positiveness constraints further narrow the admissible set of network structures. This also aids in establishing the global asymptotic stability for the steady state given a constant input disturbance. The entire method does not assume any explicit knowledge of the underlying rate kinetics, barring some minimal assumptions. Finally, we also discuss the infeasibility of the incoherent feed-forward networks (IFFLP) to provide adaptation in the presence of downstream connections. Detailed and extensive simulation studies corroborate the theoretical findings. Moreover, we propose a generic and novel algorithm based on a nonlinear systems theory to unravel the design principles for global adaptation.
Optimising a coordinate ascent algorithm for the meta-analysis of test accuracy studies
Authors: Baragilly Mohammed , Willis Brian H 
Published: December 2022

AbstractMeta-analysis may be used to summarise a test’s accuracy. Often the sensitivity and specificity are the measures of interest and as these are correlated a bivariate random effects model is commonly used to fit the data. This model has five parameters and it may be optimised using a Newton-Raphson based algorithm providing adequate initial values of the parameters are identified. Numerical methods may be used to estimate robust initial values but estimating these is computationally expensive and it is not clear whether they provide a significant advantage over closed form methods in terms of reducing bias, mean square error, average relative error, and coverage probability. Here we consider six closed form methods for estimating the initial values of the parameters for a co-ordinate ascent algorithm used to fit the bivariate model and compare them with numerically derived robust initial values. Using simulation studies we demonstrate that all the closed form methods lead to a reduction in computation time of around 80% and rank higher overall across the metrics when compared with the robust initial values method. Although no initial values estimator dominated the others across all parameters and metrics, the two-step Hedges-Olkin estimator ranked highest overall across the different scenarios.
A Meta-analysis of 2D vs. 3D Ovarian Cancer Cellular Models
Authors: Kerslake Rachel , Belay Birhanu , Panfilov Suzana , Hall Marcia , Kyrou Ioannis , Randeva Harpal S. , Hyttinen Jari , Karteris Emmanouil , Sisu Cristina 
Published: December 2022

AbstractThree-dimensional (3D) cancer models are revolutionizing research, allowing for the recapitulation ofin vivolike response through the use of anin vitrosystem, more complex and physiologically relevant than traditional mono-layer culture. Cancers such as ovarian (OvCa), are prone to developing resistance and are often lethal, and stand to benefit greatly from the enhanced modelling emulated by 3D culture. However current models often fall short of predicted response where reproducibility is limited owing to the lack of standardized methodology and established protocols. This meta-analysis aims to assess the current scope of 3D OvCa models and the differences in genetic profile presented by a vast array of 3D cultures. A meta-analysis of the literature (Pubmed.gov) spanning 2012 – 2022, was used to identify studies with comparable monolayer (2D) counterparts in addition to RNA sequencing and microarray data. From the data 19 cell lines were found to show differential regulation in their gene expression profiles depending on the bio-scaffold (i.e. agarose, collagen or Matrigel) compared to 2D cell cultures. Top genes differentially expressed 2D vs. 3D include C3, CXCL1, 2 and 8, IL1B, SLP1, FN1, IL6, DDIT4, PI3, LAMC2, CCL20, MMP1, IFI27, CFB, and ANGPTL4. Top Enriched Gene sets for 2D vs. 3D include IFN-α and IFN-γ Response, TNF-α signalling, IL-6-JAK-STAT3 signalling, angiogenesis, hedgehog signalling, apoptosis, epithelial mesenchymal transition, hypoxia, and inflammatory response. Our transversal comparison of numerous scaffolds allowed us to highlight the variability that can be induced by these scaffolds in the transcriptional landscape as well as identifying key genes and biological processes that are hallmarks of cancer cells grown in 3D cultures. Future studies are needed to identify which is the most appropriate in vitro/preclinical model to study tumour microenvironment.SummaryOvarian cancer is one of the most lethal forms of female cancers. Cell culture is often the go to model to study the molecular processes of cancer. However, this is an oversimplification of the reality. 3D tissue culture has been developed to address the cell culture limitations and to provide a more realistic model of the system studied. Cells grown in 3D represent better the human tumour microenvironment. This meta-analysis is exploring the use of 3D tissue culture as a model of ovarian cancer. Our analysis shows that ovarian cancer cells grown in 3D exhibit enhanced regulation in processes pertinent to tumour development and progression. We identify a panel of genes associated with specific 3D growth conditions that could be used as conditional markers. Finally, we present an overview of the state-of-art of 3D culture with an extensive profile of the genes and pathways enhanced in ovarian cancer models.
3D-Mass Spectrometry Imaging of Micro-scale 3D Cell Culture Models in Cancer Research
Authors: Iakab Stefania-Alexandra , Keller Florian , Schmidt Stefan , Cordes Jonas , Zhou Qiuqin , Cairns James L. , Fischer Frank , Schneider Richard , Wolf Ivo , Rudolf Rüdiger , Hopf Carsten 
Published: December 2022

AbstractThree-dimensional (3D) human cell culture models have emerged as a key technology for personalized medicine and for phenotypic compound screening in more disease-likein-vitrosystems. Mass spectrometry imaging (MSI) is one of the most versatile label-free techniques that enables simultaneous generation of spatial maps for multiple relevant molecules in these 3D-models. Here, we present an integrated platform for 3D-MSI of 3D-cell cultures comprising 3D-printed metal casting molds for freezing and embedding, MS imaging of 100 serial cryosections and their computational elastic 3D-reconstruction. With this platform, we monitored multiple lipids that were selectively associated with different cell-types or cell-cell interactions within 300 μm-scale fibroblast and colon cancer biculture spheroids. Our findings suggest that 3D-printing-aided precise preparation of serial sections from small spheroids and visualization of marker molecules in 3D can provide a detailed overview of the cellular metabolic interplay in 3D cell culture models in cancer research and drug discovery.
From Multi-Allele Fish to Non-Standard Environments, How ZFIN Assigns Phenotypes, Human Disease Models, and Gene Expression Annotations to Genes
Authors: Bradford Yvonne M. , Van Slyke Ceri E. , Howe Douglas G. , Fashena David , Frazer Ken , Martin Ryan , Paddock Holly , Pich Christian , Ramachandran Sridhar , Ruzicka Leyla , Singer Amy , Taylor Ryan , Tseng Wei-Chia , Westerfield Monte 
Published: December 2022

AbstractDanio reriois a model organism used to investigate vertebrate development. Manipulation of the zebrafish genome and resultant gene products by mutation or targeted knockdown has made the zebrafish a good system for investigating gene function, providing a resource to investigate genetic contributors to phenotype and human disease. Phenotypic outcomes can be the result of gene mutation, targeted knockdown of gene products, manipulation of experimental conditions, or any combination thereof. Zebrafish have been used in various genetic and chemical screens to identify genetic and environmental contributors to phenotype and disease outcomes. The Zebrafish Information Network (ZFIN) is the central repository for genetic, genomic, and phenotypic data that result from research usingDanio rerio. Here we describe how ZFIN annotates phenotype, expression, and disease model data across various experimental designs, how we computationally determine wild-type gene expression, the phenotypic gene, and how these results allow us to propagate gene expression, phenotype, and disease model data to the correct gene, or gene related entity.
Persistence of cultivar alleles in wild carrot (Daucus carotaL.) populations in the United States
Authors: Hernández Fernando , Palmieri Luciano , Brunet Johanne 
Published: December 2022

ABSTRACTCultivated species and their wild relatives often hybridize in the wild and crop-wild hybrids can survive and reproduce in some environments. However, it is unclear whether crop alleles are permanently incorporated into the wild genomes in the long run or whether they are purged by natural selection. This question is key to accurately assessing the risk of escape and spread of cultivar genes into wild populations. Here, we use genomic data and population genomic methods to study hybridization and introgression between cultivated and wild carrots (Daucus carotaL.) in the United States. We used single nucleotide polymorphisms (SNPs) obtained via genotyping by sequencing for 450 wild individuals from 29 wild georeferenced populations in seven states and 144 cultivars from the United States, Europe, and Asia. Cultivated and wild carrots formed two well differentiated groups, and evidence of crop-wild admixture was detected in several but not all the wild populations in the United States. Two regions were identified where cultivar alleles were introgressed into wild carrots: California and the Nantucket Island, in Massachusetts. In these areas, we found no support for adaptive (or maladaptive) introgression, instead, most crop alleles seemed to be neutral. Surprisingly, there was no evidence of introgression in some populations with a long-known history of sympatry with the crop, suggesting that post-hybridization barriers might prevent introgression in some areas. Further studies are needed to better delineate the geographic patterns of introgression, but our results support the introgression and persistence of cultivar genes in wild carrot populations.
Inducible CRISPRi-based operon silencing and selectivein transgene complementation inBorrelia burgdorferi
Authors: Murphy Bryan T. , Wiepen Jacob J. , He Huan , Pramanik Ankita S. , Peters Jason M. , Stevenson Brian , Zückert Wolfram R. 
Published: December 2022

ABSTRACTTo accelerate genetic studies on the Lyme disease pathogenBorrelia burgdorferi, we developed an enhanced CRISPR interference (CRISPRi) approach for IPTG-inducible repression of specificB. burgdorferigenes. The entire system is encoded on a compact 11-kb shuttle vector plasmid that allows for inducible expression of both the sgRNA module and a non-toxic codon-optimized dCas9 protein. We validated this CRISPRi system by targeting the genes encoding for OspA and OspB, abundant surface lipoproteins co-expressed by a single operon, and FlaB, the major subunit forming the periplasmic flagella. As in other systems, sgRNAs complementary to the non-template strand were consistently effective in gene repression, with 4- to 994-fold reductions in targeted transcript levels and concomitant reductions of in proteins levels. Furthermore, we showed thatospABknockdowns could be selectively complementedin transfor OspA expression via the insertion of synonymous or non-synonymous CRISPRi-resistant PAM mutant (PAM*)ospAalleles into a unique site within the plasmid. Together, this establishes CRISPRi PAM* as a robust new genetic tool to simplify the study ofB. burgdorferigenes, bypassing the need for gene disruptions by allelic exchange and avoiding rare-codon toxicity from heterologous expression of dCas9.SIGNIFICANCEBorrelia burgdorferi, the causative agent of Lyme disease, is a tick-borne pathogen of global importance. Here, we expand the genetic toolbox for studyingB. burgdorferiphysiology and pathogenesis by establishing a single-plasmid-based CRISPRi system with optionalin transcomplementation for the functional study of essential and non-essential proteins.
The two-component system CroRS regulates isoprenoid flux to mediate antimicrobial tolerance in the bacterial pathogenEnterococcus faecalis
Authors: Todd Rose Francesca O , Darnell Rachel L , Morris Sali , Paxie Olivia , Campbell Georgia , Cook Gregory M , Gebhard Susanne 
Published: December 2022

AbstractAntimicrobial tolerance is the ability of a microbial population to survive, but not proliferate, during antimicrobial exposure. Significantly, it has been shown to precede the development of bona fide antimicrobial resistance. We have previously identified the two-component system CroRS as a critical regulator of tolerance to antimicrobials like teixobactin in the bacterial pathogenEnterococcus faecalis. To understand the molecular mechanism of this tolerance, we carried out RNA-seq analyses in theE. faecaliswild-type and isogenic ΔcroRSmutant to determine the teixobactin-induced CroRS regulon. We identified a 132 gene CroRS regulon and show CroRS upregulates expression of all major components of the enterococcal cell envelope in response to teixobactin challenge. To gain further insight into the function of this regulon we isolated and characterized ΔcroRSmutants recovered for wild-type growth and tolerance. We show introduction of a single stop codon in a heptaprenyl diphosphate synthase (hppS), a key enzyme in the synthesis of the quinone electron carrier demethylmenaquinone (DMK), is sufficient to rescue loss of cell envelope integrity in thecroRSdeletion strain. Based on these findings, we propose a model where CroRS acts as a gate-keeper of isoprenoid biosynthesis, mediating flux of isoprenoids needed for cell wall synthesis (undecaprenyl pyrophosphate; UPP) and respiration (DMK) to maintain cell wall homeostasis upon antimicrobial challenge. Dysregulation of this flux in the absence ofcroRSleads to a loss of tolerance, which is rescued by loss of function mutations in HppS, allowing an increase in isoprenoid flow to UPP and subsequently cell wall synthesis.ImportanceAntimicrobial tolerance is the ability of a microorganism to survive, but not grow upon antimicrobial challenge, and is an important precursor to the development of antimicrobial resistance (the ability to profilerate). Understanding the molecular mechanisms that underpin tolerance will therefore aid in hampering the development of resistance to novel antimicrobials such as teixobactin. CroRS is an essential two-component regulator of antimicrobial tolerance in the bacterial pathogenEnterococcus faecalis. We have determined the antimicrobial-induced CroRS regulon and identified key mutations in a heptaprenyl diphosphate synthase to uncover a novel mechanism of antimicrobial tolerance.
External validation and updating of clinical severity scores to guide referral of young children with acute respiratory infections in resource-limited primary care settings
Authors: Chandna Arjun , Mwandigha Lazaro , Koshiaris Constantinos , Limmathurotsakul Direk , Nosten Francois , Lubell Yoel , Perera-Salazar Rafael , Turner Claudia , Turner Paul 
Published: December 2022

ABSTRACTBackgroundAccurate and reliable guidelines for referral of children from resource-limited primary care settings are lacking. We identified three practicable paediatric severity scores (Liverpool quick Sequential Organ Failure Assessment [LqSOFA], quick Pediatric Logistic Organ Dysfunction-2 [qPELOD-2], and the modified Systemic Inflammatory Response Syndrome [mSIRS]) and externally validated their performance in young children presenting with acute respiratory infections to a primary care clinic located within a refugee camp on the Thailand-Myanmar border.MethodsThis secondary analysis of data from a longitudinal birth cohort study consisted of 3,010 acute respiratory infections in children aged ≤ 24 months. The primary outcome was receipt of supplemental oxygen. We externally validated the discrimination, calibration, and net-benefit of the scores, and quantified gains in performance that might be expected if they were deployed as simple clinical prediction models, and updated to include nutritional status and respiratory distress.Results104/3,010 (3.5%) presentations met the primary outcome. The LqSOFA score demonstrated the best discrimination (AUC 0.84; 95% CI 0.79-0.89) and achieved a sensitivity and specificity > 0.80. Converting the scores into clinical prediction models improved performance, resulting in ∼20% fewer unnecessary referrals and ∼30-60% fewer children incorrectly managed in the community.ConclusionsThe LqSOFA score is a promising triage tool for young children presenting with acute respiratory infections in resource-limited primary care settings. Where feasible, deploying the score as a simple clinical prediction model might enable more accurate and nuanced risk stratification, increasing applicability across a wider range of contexts.
A Randomized Placebo Controlled Clinical Trial of a Metabolic Shifting Probiotic, Sugar Shift, for the Treatment of T2DM
Authors: García Gissel , Soto Josanne , Rodríguez Lays , Nuez Maricela , Domínguez Noraika , Buchaca Emilio F. , Martínez Duniesky , Gómez Rolando J. , Ávila Yohanka , Carlin Martha R. , Cano Raúl J. 
Published: December 2022

AbstractType 2 diabetes mellitus (T2DM) is a chronic metabolic disorder characterized by hyperglycemia, insulin resistance and chronic inflammation. Probiotics have been claimed effective in the management of obesity and type 2 diabetes mellitus. BiotiQuest™ Sugar Shift is a symbiotic formulation rationally designed for the endogenous conversion of glucose and fructose to support restoration of the human gut microbiota, modulation of intestinal glucose, and the production of anti-inflammatory metabolites.We report the results of a 12-week, double blind, placebo-controlled study designed to evaluate Sugar Shift in Cuban T2DM patients. Clinical parameters, including fasting and 2h post-prandial glucose, hemoglobin A1c, a lipid panel, insulin, creatinine, and serum lipopolysaccharide levels were assessed. Microbiome composition was assessed by 16S amplicon sequencing of the variable region V3-V4 of the 16S rRNA gene. Metabolic biomarkers were inferred from microbiome data by Kruskal-Wallis H test and LEfSe.Fasting glucose, Insulin, and serum LPS levels decreased significantly at day 84 as compared to day 1 in the treated group and to control group. Hb A1c remained stable in the treatment group as compared to the controls but not show significant improvement in the study period.Microbiome analysis showed significant increase in Chao1 alpha diversity in the treated group between day 1 and day 84. Taxonomic and functional biomarkers revealed significant differences between the Day 1 and Day 84 microbiome profiles in the treatment group, primarily associated with acetate, propionate, and butyrate production.Our results indicate that Sugar Shift can be a suitable adjunct therapy to standard of care therapy in the management of T2DM based upon the improvement in key inflammatory and insulin resistance markers. These results were interpreted as an indication of favorable microbiome changes during the course of the treatment for 12 weeks.
A Binary RNA and DNA Self-Amplifying Platform for Next Generation Vaccines and Therapeutics
Authors: Jefferies Wilfred A. , Choi Kyung Bok , Ribeca Paolo , Kari Suresh , Young Jay , Hui Elizabeth , Qi Simon Yong , Garrosvillas Emmanuel , Lincez Pamela , Welch Tracy , Saranchova Iryna , Pfeifer Cheryl G. 
Published: December 2022

ABSTRACTConventional mRNA-based vaccines were instrumental in lowering the burden of the pandemic on healthcare systems and in reducing mortality. However, such first-generation vaccines have significant weaknesses. Here, we describe a high-performance binary recombinant vectoral platform offering the flexibility to be used as a self-amplifying mRNA or a self-amplifying DNA. Both formats drive long-lasting expression and actuate robust antibody responses against SAR-CoV-2 spike, and neither format require encapsulation with lipid nanoparticles (LNP) in the generation immune responses. The platform combines the power of conventional mRNA with the low-dosage of self-amplifying vectors together with the simplicity, rapid creation, ease of storage, and convenience of distribution of plasmid DNA vectors. This platform promises to pave the way for more effective, less expensive, and truly democratized vaccines and therapeutics.One-Sentence SummaryGemini: a versatile platform that improves on existing vaccine formats in terms of effectiveness, manufacturing, distribution, and cost.