bluuebunny/crossref_metadata_2025_split huggingface dataset:
FtsZ phosphorylation brings about growth arrest upon DNA damage in Deinococcus radiodurans
Authors: Chaudhary Reema , Mishra Shruti , Maurya Ganesh Kumar , Misra Hari S 
Published: June 2022

AbstractThe polymerization/depolymerization dynamics of FtsZ plays the pivotal role in cell division in majority bacteria. Deinococcus radiodurans, a radiation resistant bacterium, shows an arrest of growth in response to DNA damage, despite no change in the level of FtsZ. This bacterium does not deploy LexA/RecA type of DNA damage response and cell cycle regulation, and its genome does not encode homologs of E. coli’s SulA, which attenuate FtsZ functions in response to DNA damage in different bacteria. A radiation responsive Ser/Thr quinoprotein kinase (RqkA) characterized for its role in radiation resistance in this bacterium, could phosphorylate several cognate proteins including FtsZ (drFtsZ) at Serine 235 (S235) and Serine 335 (S335) residues. Here, we report the detailed characterization of S235 and S335 phosphorylation effect in the regulation of drFtsZ functions, and demonstrated that the phospho-mimetic replacements of these residues in drFtsZ had grossly affected its functions that could result in cell cycle arrest in response to DNA damage in D. radiodurans. Interestingly, the phospho-ablative replacements were found to be nearly similar to drFtsZ while phospho-mimetic mutant showed the loss of signatures characteristics to wild type enzyme including the arrest in its dynamics under normal conditions. The post-bleaching recovery kinetics for drFtsZ and phospho-mimetic mutant was nearly similar at 2h post irradiation recovery but found to be different under normal conditions. These results highlighted the role of S/T phosphorylation in the regulation of drFtsZ functions and cell cycle arrest in response to DNA damage and is first time demonstrated in this prokaryote.
Bayesian parameter estimation for phosphate dynamics during hemodialysis
Authors: Bangsgaard Katrine O. , Andersen Morten , Heaf James G. , Ottesen Johnny T. 
Published: June 2022

AbstractHyperphosphatemia in patients with renal failure is associated with increased vascular calcification and mortality. Hemodialysis is a conventional treatment for patients with hyperphosphatemia. Phosphate kinetics during hemodialysis may be described by a diffusion process and modeled by ordinary differential equations. We propose a Bayesian model approach for estimating patient-specific parameters for phosphate kinetics during hemodialysis. The Bayesian approach allows us to both analyze the full parameter space using uncertainty quantification and to compare two types of hemodialysis treatments, the conventional single-pass and the novel multiple-pass treatment. We validate and test our models on synthetic and real data. The results show limited identifiability of the model parameters when only single-pass data are available, and that the Bayesian model greatly reduces the relative standard deviation compared to existing estimates. Moreover, the analysis of the Bayesian models reveal improved estimates with reduced uncertainty when considering consecutive sessions and multiple-pass treatment compared to single-pass treatment.
Biomolecular Condensate Regulates Enzymatic Activity under Crowded Milieu: Synchronization of Liquid-Liquid Phase separation and Enzymatic Transformation
Authors: Saini Bhawna , Mukherjee Tushar Kanti 
Published: June 2022

AbstractCellular crowding plays a key role in regulating the enzymatic reactivity in physiological conditions, which is challenging to realize in the dilute phase. Enzymes drive a wide range of complex metabolic reactions with high efficiency and selectivity under extremely heterogeneous and crowded cellular environments. However, the molecular interpretation behind the enhanced enzymatic reactivity under a crowded milieu is poorly understood. Herein, using horseradish peroxidase (HRP) and glucose oxidase (GOx) cascade pair, we demonstrate for the first time that macromolecular crowding induces liquid-liquid phase separation (LLPS) via the formation of liquid-like condensates/droplets and thereby increases the intrinsic catalytic efficiencies of HRP and GOx. Both these enzymes undergo crowding induced homotypic LLPS via enthalpically driven multivalent electrostatic as well as hydrophobic interactions. Using a set of kinetic and microscopic experiments, we show that precise synchronization of spontaneous LLPS and enzymatic transformations is key to realize the enhanced enzymatic activity under the crowded environments. Our findings reveal an unprecedented enhancement (91–205-fold) in the catalytic efficiency (kcat/Km) of HRP at pH 4.0 within the droplet phase relative to that in the bulk aqueous phase in the presence of different crowders. In addition, we have shown that other enzymes also undergo spontaneous LLPS under macromolecular crowding, signifying the generality of this phenomenon under the crowded environments. More importantly, coalescence driven highly regulated GOx/HRP cascade reactions within the fused droplets have been demonstrated with enhanced activity and specificity under the crowded environments. The present discovery highlights the active role of membraneless condensates in regulating the enzymatic efficacy for complex metabolic reactions under the crowded cellular environments and may find significant importance in the field of biocatalysis.
Development and Evaluation of RT-LAMP Assays to Identify Variants of SARS-CoV-2
Authors: Park Gun-Soo , Kim Seong-Jun , Maeng Jin-Soo 
Published: June 2022

AbstractEmergence of new variants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) during current pandemic of Coronavirus Disease 2019 (COVID-19) and several waves of infections by some of variants emphasized the importance of continuous surveillance. While genomic surveillance through whole genome sequencing is performed as a standard method, identification of known variants through mutation-targeting molecular diagnosis such as qRT-PCR is also useful for timely investigation. However, there are limited studies regarding the concurrent detection and identification of SARS-CoV-2 variants through a LAMP-based method. In this study, we developed and evaluated RT-LAMP assays to detect characteristic deletions of SARS-CoV-2 variants. In addition, we evaluated a fluorescent probe mediated method for identification of single nucleotide substitution by RT-LAMP. Finally, we discussed restrictions and perspectives regarding pathogen screening and surveillance of variants by RT-LAMP based on our observations.
Robust phylodynamic analysis of genetic sequencing data from structured populations
Authors: Scire Jérémie , Barido-Sottani Joëlle , Kühnert Denise , Vaughan Timothy G. , Stadler Tanja 
Published: June 2022

AbstractThe multi-type birth-death model with sampling is a phylodynamic model which enables quantification of past population dynamics in structured populations, based on phylogenetic trees. The BEAST 2 package bdmm implements an algorithm for numerically computing the probability density of a phylogenetic tree given the population dynamic parameters under this model. In the initial release of bdmm, analyses were limited computationally to trees consisting of up to approximately 250 genetic samples. We implemented important algorithmic changes to bdmm which dramatically increase the number of genetic samples that can be analyzed, and improve the numerical robustness and efficiency of the calculations. Including more samples leads to improved precision of parameter estimates, particularly for structured models with a high number of inferred parameters. Furthermore, we report on several model extensions to bdmm, inspired by properties common to empirical datasets. We apply this improved algorithm to two partly overlapping datasets of Influenza A virus HA sequences sampled around the world, one with 500 samples, the other with only 175, for comparison. We report and compare the global migration patterns and seasonal dynamics inferred from each dataset. In that way, we show what information is gained by analyzing the bigger dataset which became possible with the presented algorithmic changes to bdmm. In summary, bdmm allows for robust, faster and more general phylodynamic inference of larger datasets.
Dynamics of spike time encoding in the olfactory bulb
Authors: Werth Jesse C. , Einhorn Matthew , Cleland Thomas A. 
Published: June 2022

AbstractIn the mammalian olfactory bulb (OB), gamma oscillations in the local field potential are generated endogenously during odor sampling. Such oscillations arise from dynamical systems that generate organized periodic behavior in neural circuits, and correspond to spike timing constraints at fine timescales. While the cellular and network mechanisms of gamma oscillogenesis in the OB are reasonably well established, it remains unclear how these fine-timescale dynamics serve to represent odors. Are patterns of spike synchrony on the gamma timescale replicable and odor-specific? Does the transformation to a spike-timing metric embed additional computations? To address these questions, we used OB slices to examine the spike timing dynamics evoked by “fictive odorants” generated via spatiotemporally patterned optogenetic stimulation of olfactory sensory neuron axonal arbors. We found that a small proportion of mitral/tufted cells phase-lock strongly to the fast oscillations evoked by fictive odorants, and exhibit tightly coupled spike-spike synchrony on the gamma timescale during this stimulation. Moreover, the specific population of synchronized neurons differed based on the “quality”, but not the “concentration”, of the fictive odorant presented, and was conserved across multiple presentations of the same fictive odorant. Given the established selectivity of piriform cortical pyramidal neurons for inputs synchronized on this timescale, we conclude that spike synchronization on a milliseconds timescale is a metric by which the OB encodes and exports afferent odor information in a concentration-invariant manner. As a corollary, mitral/tufted cell spikes that are not organized in time may not contribute effectively to the ensemble odor representation.
Spectral neural approximations for models of transcriptional dynamics
Authors: Gorin Gennady , Carilli Maria , Chari Tara , Pachter Lior 
Published: June 2022

AbstractThe advent of high-throughput transcriptomics provides an opportunity to advance mechanistic understanding of transcriptional processes and their connections to cellular function at an un-precedented, genome-wide scale. These transcriptional systems, which involve discrete, stochastic events, are naturally modeled using Chemical Master Equations (CMEs), which can be solved for probability distributions to fit biophysical rates that govern system dynamics. While CME models have been used as standards in fluorescence transcriptomics for decades to analyze single species RNA distributions, there are often no closed-form solutions to CMEs that model multiple species, such as nascent and mature RNA transcript counts. This has prevented the application of standard likelihood-based statistical methods for analyzing high-throughput, multi-species transcriptomic datasets using biophysical models. Inspired by recent work in machine learning to learn solutions to complex dynamical systems, we leverage neural networks and statistical understanding of system distributions to produce accurate approximations to a steady-state bivariate distribution for a model of the RNA life-cycle that includes nascent and mature molecules. The steady-state distribution to this simple model has no closed-form solution and requires intensive numerical solving techniques: our approach reduces likelihood evaluation time by several orders of magnitude. We demonstrate two approaches, where solutions are approximated by (1) learning the weights of kernel distributions with constrained parameters, or (2) learning both weights and scaling factors for parameters of kernel distributions. We show that our strategies, denoted by kernel weight regression (KWR) and parameter scaled kernel weight regression (psKWR), respectively, enable broad exploration of parameter space and can be used in existing likelihood frameworks to infer transcriptional burst sizes, RNA splicing rates, and mRNA degradation rates from experimental transcriptomic data.Statement of significanceThe life-cycles of RNA molecules are governed by a set of stochastic events that result in heterogeneous gene expression patterns in genetically identical cells, resulting in the vast diversity of cellular types, responses, and functions. While stochastic models have been used in the field of fluorescence transcriptomics to understand how cells exploit and regulate this inherent randomness, biophysical models have not been widely applied to high-throughput transcriptomic data, as solutions are often intractable and computationally impractical to scale. Our neural approximations of solutions to a two-species transcriptional system enable efficient inference of rates that drive the dynamics of gene expression, thus providing a scalable route to extracting mechanistic information from increasingly available multi-species single-cell transcriptomics data.
Dynamic top-down biasing implements rapid adaptive changes to individual movements
Authors: Tian Lucas Y , Warren Timothy L. , Brainard Michael S. 
Published: June 2022

AbstractComplex behaviors depend on the coordinated activity of neural ensembles in interconnected brain areas. The behavioral function of such coordination, often measured as co-fluctuations in neural activity across areas, is poorly understood. One hypothesis is that rapidly varying co-fluctuations may be a signature of moment-by-moment task-relevant influences of one area on another. We tested this possibility for error-corrective adaptation of birdsong, a form of motor learning which has been hypothesized to depend on the top-down influence of a higher-order area, LMAN, in shaping moment-by-moment output from a primary motor area, RA. In paired recordings of LMAN and RA in singing birds, we discovered a neural signature of a top-down influence of LMAN on RA, quantified as an LMAN-leading co-fluctuation between these areas. During learning, this cofluctuation strengthened in a premotor temporal window linked to the specific movement, sequential context, and acoustic modification associated with learning. Moreover, transient perturbation of LMAN activity specifically within this premotor window caused rapid occlusion of pitch modifications, consistent with LMAN conveying a temporally localized motor-biasing signal. Combined, our results reveal a dynamic top-down influence of LMAN on RA that varies on the rapid timescale of individual movements and is flexibly linked to contexts associated with learning. This finding indicates that inter-area co-fluctuations can be a signature of dynamic top-down influences that support complex behavior and its adaptation.
Leptospira enrichment culture followed by ONT Nanopore sequencing allows better detection of Leptospira presence and diversity in water and soil samples
Authors: Gorman Myranda , Xu Ruijie , Prakoso Dhani , Salvador Liliana C.M. , Rajeev Sreekumari 
Published: June 2022

AbstractBackgroundLeptospirosis, a life-threatening disease in humans and animals, is one of the most widespread global zoonosis. Contaminated soil and water are the major transmission sources in humans and animals. Clusters of disease outbreaks are common during rainy seasons.Methodology/Principal FindingsIn this study, to detect the presence of Leptospira, we applied PCR, direct metagenomic sequencing, and enrichment culture followed by metagenomic sequencing on water and soil samples. Direct sequencing and enrichment cultures followed by PCR or sequencing effectively detected pathogenic and nonpathogenic Leptospira compared to direct PCR and 16S amplification-based metagenomic sequencing in soil or water samples. Among multiple culture media evaluated, Ellinghausen-McCullough-Johnson-Harris (EMJH) media containing antimicrobial agents was superior in recovering and detecting Leptospira from the environmental samples. Our results show that enrichment culture followed by PCR can be used to confirm the presence of pathogenic Leptospira in environmental samples. Metagenomic sequencing on enrichment cultures effectively detects the abundance and diversity of Leptospira spp from environmental samples.Conclusions/SignificanceThe selection of methodology is critical when testing environmental samples for the presence of Leptospira. Selective enrichment culture improves Leptospira detection efficacy by PCR or metagenomic sequencing and can be used successfully to understand the presence and diversity of pathogenic Leptospira during environmental surveillance.Author SummaryLeptospirosis, a life-threatening disease in humans and animals, is one of the most widespread global zoonosis. Contaminated soil and water are major sources of transmission in humans and animals. For this reason, clusters of disease outbreaks are common during the rainy season. In this study, Leptospira enrichment cultures followed by PCR and sequencing detected pathogenic and nonpathogenic Leptospira in soil and water samples. The pathogenic and intermediate groups of Leptospira were more prevalent in soil samples tested. Metagenomic sequencing on enrichment culture is effective in detecting the abundance and diversity of various Leptospira spp. in environmental samples. Soil samples in proximity to water may be an ideal niche for Leptospira growth and survival and may be an appropriate sample of choice for testing.
Bystander memory-phenotype conventional CD4+T cells exacerbating autoimmune neuroinflammation
Authors: Cho Min-Zi , Lee Hong-Gyun , Yoon Jae-Won , Kim Gil-Ran , Koo Ja-Hyun , Taneja Reshma , Edelson Brian T. , Lee You Jeong , Choi Je-Min 
Published: June 2022

AbstractMemory-phenotype (MP) CD4+T cells are a substantial population of conventional T cells that exist in steady-state mice, and their immunologic functions in autoimmune disease have not yet been studied. In this work, we unveil a unique phenotype of MP CD4+T cells by analyzing single-cell transcriptomics and T cell receptor (TCR) repertoires. We found that steady-state MP CD4+T cells exist regardless of germ and food-antigen which are composed of heterogenous effector subpopulations. Distinct subpopulations of MP CD4+T cells are specifically activated by IL-1 family cytokines and STAT activators, revealing that the cells have TCR-independent effector functions. Especially, CCR6highMP CD4+T cells are major responders to IL-1β and IL-23 without MOG35-55antigen reactivity, which gives them pathogenic-Th17 characteristics and allows them to contribute to autoimmune encephalomyelitis. We identified Bhlhe40 in CCR6highMP CD4+T cells drives the expression of GM-CSF, contributing to CNS pathology in experimental autoimmune encephalomyelitis. Collectively, our findings reveal heterogeneity of MP CD4+T cells that can contribute to autoimmune neuroinflammation in bystander manner synergistically with antigen-specific T cells.
Australian parents' and children's food-related interactions during the COVID-19 pandemic
Authors: Nanayakkara Janandani , Boddy Gail , Aydin Gozde , Kombanda Krupa Thammaiah , Larsson Christel , Worsley Anthony , Margerison Claire , Booth Alison O. 
Published: June 2022

PurposeDuring the COVID-19 pandemic people worldwide in the same household spent more time together and school children engaged in remote learning throughout extended lockdowns and restrictions. The present study aimed to explore parents' perceptions of their involvement and enjoyment in food-related interactions with their children during coronavirus disease 2019 (COVID-19)-associated lockdowns/restrictions and changes in their children's food intake, especially children's lunches during the remote learning period.Design/methodology/approachData from parents (n = 136) were collected via an online survey in 2020. Parents' responses to closed-ended questions were analysed via descriptive statistics and open-ended responses were analysed thematically.FindingsMost parents (62%) reported that they interacted more with their school-aged (5–17 years) children about food during COVID-19 compared to pre-pandemic times. These interactions included cooking, menu planning, eating, conversations around food, and gardening. Most parents (74%) prepared meals with their children during the pandemic and most of them (89%) reported that they enjoyed it. Most parents (n = 91 out of 121) perceived that their children's lunches during remote learning were different to when attending school in person and these changes included eating hot and home-cooked food and more elaborate meals.Originality/valueThis study sheds important insights into a sample of Australian parents' food-related interactions with their school-aged children during the COVID-19 pandemic and associated lockdowns and parents' observations and perceptions of changes in the children's food intake during the remote learning period.
Do open access journals have a greater citation impact? A study of journals in library and information science
Authors: Khan Daud , Ashar Mohammad , Yuvaraj Mayank 
Published: June 2022

Purpose
This study aims to investigate the research and citation impact of open access (OA) journals versus non-OA journals being published in the spectrum of library and information science (LIS) across the world and to further ascertain whether OA journals have greater citation counts than subscription-based journals in LIS discipline.

Design/methodology/approach
A total of 116 LIS journals (58 OA and 58 non-OA) were chosen from Scimago website. After selecting the journals, Publish or Perish software program was used to retrieve the publications and their corresponding academic citations by using International Standard Serial Number of journals from Google Scholar for the period of 2011–2018. The non-parametric Mann–Whitney U-test was applied on various research and citation indicators, namely, citation count, citations per author, citations per paper; g-index, h-index, hI norm and hI annual through SPSS.

Findings
Findings of the study demonstrate that non-OA journals in LIS have a significant citation advantage over OA journals. Moreover, Mann–Whitney U-test analysis rejected all the eight null hypotheses and reveals that non-OA journals in LIS discipline have greater citation counts, citations per author, citations per paper; g-index, h-index, hI norm and hI annual than OA journals.

Originality/value
To the best of the authors’ knowledge, this is the first study that embarks upon a whole-scale investigation of citation impact of OA and non-OA journals in LIS, which has implications for both research and practice. This study would serve as a reference guide to all involved in scholarly communication activities including academic communities, librarians, research funders, publishers and policymakers for publishing research work, grant funding, designing policies and subscriptions.