bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding COVID-19 vaccine hesitancy in Pakistan: The paradigm of Confidence, Convenience, and Complacency; A Cross-sectional study
Authors: Sheikh Naveen Siddique , Touseef Mumtaz , Sultan Riddah , Cheema Kanwal Hassan , Cheema Sidra Shafiq , Sarwar Afia , Siddique Haniya Zainab 
Published: July 2021

AbstractBackground and objectivesVaccine hesitancy is a big obstacle for vaccination programs, as is anticipated for the COVID-19 vaccination program, resulting in low uptake of vaccines thereby hindering the process of reaching herd immunity. Bearing this in mind the current study was aimed to explore the determinants of vaccine hesitancy amongst the Pakistani population.MethodologyA cross-sectional study was carried out from November 2020 to March 2021. The conceptual framework of the study was based on the 3Cs (Confidence, Convenience, Complacency) model. The google-forms-based questionnaire was disseminated amongst the general population. Data collected were entered into SPSS version 26 and analyzed.ResultsOf the 421 participants, 68.4% were women. Non-healthcare workers were 55.8% of respondents. Of vaccine-hesitant individuals, 26.13% reported they were very unlikely to get vaccinated. The vaccine was not safe as it came out too fast was agreed upon by 12.6% of individuals, 50.6% were worried about experiencing side-effects, 18% believed the vaccine will not offer protection and 5.9% believed the vaccine would cause death. Low Practice of SOP in non-Healthcare workers was the strongest contributor to vaccine hesitancy (OR: 5.338, p=0.040, 95% CI: 1.082-26.330) followed by High complacency (p=0.026) and Moderate Complacency (OR: 0.212, p=0.007, 95% CI: 0.069-0.654) towards COVID-19 vaccination. In Healthcare workers the strongest contributor to vaccine hesitancy was having a Moderate Confidence (OR: 0.323, p=0.042, 95% CI: 0.109-0.958) in the vaccine followed by Moderate Convenience (OR: 0.304, p=0.049, 95% CI: 0.093-0.993) for vaccinationConclusionCampaigning and communication strategies to reaffirm confidence in the COVID-19 vaccine and educating the general population about the vaccine could lead to increased perception of vaccine safety and effectiveness thereby restoring confidence in vaccine and decreasing vaccine hesitancy. Likewise, working to increase vaccine convenience and decreasing complacency towards the COVID-19 vaccine would translate into high vaccine uptake.
Making Strides in Doctoral-Level Career Outcomes Reporting: Surveying the Landscape of Classification and Visualization Methodologies and Creating a Crosswalk Tool
Authors: Collins Tammy , Ramadoss Deepti , Layton Rebekah L. , MacDonald Jennifer , Wheeler Ryan , Bankston Adriana , Stayart Abigail , Hao Yi , Robinson-Hamm Jacqueline N , Sinche Melanie , Burghart Scott , Carlsen-Bryan Aleshia , Eswara Pallavi , Krasna Heather , Xu Hong , Sullivan Mackenzie 
Published: July 2021

ABSTRACTThe recent movement underscoring the importance of career taxonomies has helped usher in a new era of transparency in PhD career outcomes. The convergence of discipline-specific organizational movements, interdisciplinary collaborations, and federal initiatives have all helped to increase PhD career outcomes tracking and reporting. Transparent and publicly available PhD career outcomes are being used by institutions to attract top applicants, as prospective graduate students are factoring these in when deciding on the program and institution in which to enroll for their PhD studies. Given the increasing trend to track PhD career outcomes, the number of institutional efforts and supporting offices for these studies have increased, as has the variety of methods being used to classify and report/visualize outcomes. This report identifies and summarizes currently available PhD career taxonomy tools, resources, and visualization options to help catalyze and empower institutions to develop and publish their own PhD career outcomes. Similar fields between taxonomies were mapped to create a new crosswalk tool. This work serves as an empirical review of the career outcome tracking systems available and highlights organizations, consortia, and funding agencies that are impacting policy change toward greater transparency in PhD career outcomes reporting.
Bidirectionally connected cores in a mouse connectome: Towards extracting the brain subnetworks essential for consciousness
Authors: Kitazono Jun , Aoki Yuma , Oizumi Masafumi 
Published: July 2021

AbstractWhere in the brain consciousness resides remains unclear. It has been suggested that the subnetworks supporting consciousness should be bidirectionally (recurrently) connected because both feed-forward and feedback processing are necessary for conscious experience. Accordingly, evaluating which subnetworks are bidirectionally connected and the strength of these connections would likely aid the identification of regions essential to consciousness. Here, we propose a method for hierarchically decomposing a network into cores with different strengths of bidirectional connection, as a means of revealing the structure of the complex brain network. We applied the method to a whole-brain mouse connectome. We found that cores with strong bidirectional connections consisted of regions presumably essential to consciousness (e.g., the isocortical and thalamic regions, and claustrum) and did not include regions presumably irrelevant to consciousness (e.g., cerebellum). Contrarily, we could not find such correspondence between cores and consciousness when we applied other simple methods which ignored bidirectionality. These findings suggest that our method provides a novel insight into the relation between bidirectional brain network structures and consciousness.
Detecting the state of drowsiness induced by propofol by spatial filter and machine learning algorithm on EEG recording
Authors: Zhou Zhibin , Srinivasan Ramesh 
Published: July 2021

AbstractTo accurately measure the depth of anesthesia has been a challenge for both anesthesiologists and engineers who work on developing tools of measurements. This study aims to use a machine-learning algorithm to predict the drowsy state, a transitional depth of sedation during propofol anesthesia. The data used in this study were scalp EEG (electroencephalogram) recordings selected from the University of Cambridge Repository. Raw EEG recordings were preprocessed into power spectrum matrices one second per sample. A total of 170 samples (110 awake samples and 60 drowsy samples) were used. A CNN (Convolutional Neural Network) for the MNIST (Modified National Institute of Standards and Technology) dataset was applied on these EEG power spectrum matrices. Due to the small dataset volume, Leave-One-Out cross-validation was used to train the data. Results of the training accuracy reached 99.69%. And test accuracy averaged 96.47%. Overall, the model is able to predict the state of drowsiness during propofol anesthesia. This provides the potential to develop EEG monitoring devices with closed-loop feedback of such a machine learning algorithm that controls the titration of the dosage of anesthetic administration and the depth of anesthesia.
In vitro determinants of e-cig aerosol condensate bioavailability and toxicity: Influence of cell culture parameters and utility of a normalized dose metric in e-cigarette studies
Authors: Obodo Udochukwu C. , O’Connor Timothy R. 
Published: July 2021

AbstractElectronic cigarettes (e-cigs) have a strong foothold in the marketplace as a product to replace tobacco cigarette usage. Despite many researchers investigating the use of e-cigs and possible health issues, there is still controversy concerning how to evaluate and use e-cig condensates. Therefore, to identify factors that influence in vitro e-cig studies, we examined parameters that can impact experimental outcomes. We generated high wattage e-cig aerosol condensate (ECAC) to determine reproducible conditions to evaluate ECAC with respect to cellular survival. Cytotoxicity of ECAC was independent of serum conditions. However, cytotoxicity of ECAC is altered by treatment duration and by physical factors, including cell seeding density and volume of ECAC used. In addition, interactions between ECAC components and cells, as well as the culture vessel surface, diminish the bioavailability of ECAC components in vitro and altered the results obtained. Moreover, the cell seeding density changes reactive oxygen species production in response to ECAC exposure. Our data indicated that normalized ECAC doses (ECAC weight per cell) better reflect the toxicity of ECAC than nominal doses (ECAC percentage). These results provide factors for researchers to consider in the design of in vitro experiments using ECAC.
Genetic, bioacoustic and morphological analyses reveal cryptic speciation in the warbling vireo complex (Vireo gilvus: Vireonidae: Passeriformes)
Authors: Carpenter AM , Graham BA , Spellman GM , Klicka J , Burg TM 
Published: July 2021

ABSTRACTCryptic species are closely related taxa that are difficult to separate morphologically, but are reproductively isolated. Here we examine the warbling vireo complex (Vireo gilvus), a widespread songbird speculated to be comprised of more than one cryptic species. We included three taxa within the complex: two of the western (Vireo gilvus swainsonii and V. g. brewsteri) subspecies and the single eastern (V. g. gilvus) subspecies. We used mtDNA and microsatellite loci to assess the congruence of genetic data to the current subspecies boundaries. We then incorporated bioacoustic, morphometric, and ecological niche modeling analyses to further examine differences. We found two genetic groups with mtDNA analysis. Microsatellite analyses revealed four genetic groups: an eastern group, a Black Hills group and two western groups that do not agree with current western subspecies boundaries based on phenotypic data. Our results suggest that eastern and western warbling vireos have been reproductively isolated for a long period of time and therefore, may be best treated as separate species; however, more research into areas of contact to examine the presence of hybridization is advised before making a taxonomic revision. Differences between the two western genetic groups appear less clear, requiring additional research.
Tree-based automated machine learning to predict biogas production for anaerobic co-digestion of organic waste
Authors: Wang Yan , Huntington Tyler , Scown Corinne D. 
Published: July 2021

ABSTRACTThe dynamics of microbial communities involved in anaerobic digestion of mixed organic waste are notoriously complex and difficult to model, yet successful operation of anaerobic digestion is critical to the goals of diverting high-moisture organic waste from landfills. Machine learning (ML) is ideally suited to capturing complex and nonlinear behavior that cannot be modeled mechanistically. This study uses 8 years of data collected from an industrial-scale anaerobic co-digestion (AcoD) operation at a municipal wastewater treatment plant in Oakland, California, combined with a powerful automated ML method, Tree-based Pipeline Optimization Tool, to develop an improved understanding of how different waste inputs and operating conditions impact biogas yield. The model inputs included daily input volumes of 31 waste streams and 5 operating parameters. Because different wastes are broken down at varying rates, the model explored a range of time lags ascribed to each waste input ranging from 0 to 30 days. The results suggest that the waste types (including rendering waste, lactose, poultry waste, and fats, oils, and greases) differ considerably in their impact on biogas yield on both a per-gallon basis and a mass of volatile solids basis, while operating parameters are not useful predictors in a carefully operated facility.
Protozoan predation drives adaptive divergence in Pseudomonas fluorescens SBW25; ecology meets experimental evolution
Authors: Golzar Farhad S. , Ferguson Gayle C. , Hendrickson Heather Lyn 
Published: July 2021

AbstractProtozoan predators can affect the structure of bacterial communities, but investigations of how predation might influence bacterial evolution and antagonistic behaviours are scarce. Here, we performed a 20-day predator-prey evolution experiment on solid media to investigate the effect of continuous protozoan predation on bacterial traits using Pseudomonas fluorescens SBW25 as prey and Naegleria gruberi as an amoeboid predator. We observed the divergence of colony morphotypes coincident with an increase in bacterial grazing resistance and relative prey fitness in selected bacterial isolates. When subjected to these resistant prey, N. gruberi show reduced activity (increased encystment) and limited replication. An investigation of the mutations responsible for predation resistance reveals mutations in wspF and amrZ genes, affecting biofilm formation and motility. The bacterial mutants in the wspF gene successfully colonise the air-liquid interface and produce robust cellulose biofilms that prevent predation. The mutation in the amrZ mutant withstands predation but this variant produces low levels of cellulose and limited swarming motility. Our findings suggest that protozoan predation can profoundly influence the course of genetic and phenotypic evolution in a short period.
Trophic status and local conditions affect microbial potential for denitrification versus internal nitrogen cycling in lake sediments
Authors: Baumann K.B.L. , Thoma R. , Callbeck C.M. , Niederdorfer R. , Schubert C.J. , Müller B. , Lever M.A. , Bürgmann H. 
Published: July 2021

AbstractThe nitrogen (N) cycle is of global importance as N is an essential element and a limiting nutrient in terrestrial and aquatic ecosystems. Excessive anthropogenic N fertilizer usage threatens sensitive downstream aquatic ecosystems. Although freshwater lake sediments remove N through various microbial transformation processes, few studies have investigated the microbial communities involved. In an integrated biogeochemical and microbiological study on a eutrophic and oligotrophic lake, we estimated N removal rates in the sediments from porewater concentration gradients. Simultaneously, the abundance of different microbial N transformation genes was investigated using metagenomics on a seasonal and spatial scale. We observed that contrasting nutrient concentrations in the sediments were reflected in distinct microbial community compositions and significant differences in the abundance of various N transformation genes. Within each lake, we observed a more pronounced spatial than seasonal variability. The eutrophic Lake Baldegg showed a higher denitrification potential with highernosZgene (N2O reductase) abundance and highernirS:nirK(nitrite reductase) ratio, indicating a greater capacity for complete denitrification. Correspondingly, this lake had a higher N removal efficiency. The oligotrophic Lake Sarnen, in contrast, had a higher potential for DNRA and nitrification, and specifically a high abundance ofNitrospirae, including some capable of comammox. In general, the oligotrophic lake ecosystems had a higher microbial diversity, thus acting as an important habitat for oligotrophic microbes. Our results demonstrate that knowledge of the genomic N transformation potential is important for interpreting N process rates and understanding the limitations of the N cycle response to environmental drivers.Importance¶Anthropogenic nitrogen (N) inputs can lead to eutrophication in aquatic systems, specifically in N limited coastal ecosystems. Lakes act as N sinks by transforming reactive N to N2through denitrification or anammox. The N cycle in lake sediments is mediated by microbial processes and affected by environmental drivers such as the amount and quality of settling organic material or nitrate concentration. However, the microbial communities mediating the different N transformation processes and their impact on N removal in freshwater lake sediments remain largely unknown. We provide the first seasonally and spatially resolved metagenomic analysis of the N cycle in the sediments of two lakes with different trophic states. We show that the trophic state of lakes provokes other microbial communities with characteristic key players and functional potential for N transformation.
PD-1 in hippocampal neurons regulates excitability, synaptic plasticity, and cognition
Authors: Zhao Junli , Bang Sangsu , McGinnis Aidan , Furutani Kenta , Jiang Changyu , Roberts Alexus , Donnelly Christopher R , He Qianru , Ko Mei-Chuan , Wang Haichen , Palmiter Richard D. , Ji Ru-Rong 
Published: July 2021

SUMMARYImmunotherapy using monoclonal antibodies against programmed cell death protein 1 (PD-1) demonstrated improved survival in cancer patients through immune activation. Here we show that functional PD-1 is expressed in mouse and primate hippocampal neurons and PD-1 inhibition improves cognition in physiological and pathological conditions. Mice lacking the Pdcd1 gene encoding PD-1 exhibit enhanced long-term potentiation (LTP) and learning and memory. These behavioral and cellular changes can be recapitulated by selective deletion of Pdcd1 in hippocampal excitatory neurons but not in microglia. Perfusion of mouse or nonhuman primate brain slices with anti-PD-1 antibody is sufficient to increase excitability in CA1 hippocampal neurons. Conversely, re-expression of Pdcd1 in PD-1 deficient hippocampal neurons suppresses memory and LTP. Traumatic brain injury impairs learning and memory, which is improved by intraventricular administration of anti-PD-1. These findings suggest that anti-PD-1 treatment has therapeutic potential to counteract cognitive decline.HighlightsAdult mice lacking Pdcd1 in hippocampal neurons exhibit enhanced memory and LTPAnti-PD-1 antibody treatment increases CA1 neuron excitability in brain slices of mice and primatesRe-expression of Pdcd1 in PD-1 deficient hippocampal neurons impairs memory and LTPCognitive deficits after traumatic brain injury are improved by anti-PD-1 treatment
Multiplex base editing to convert TAG into TAA codons in the human genome
Authors: Chen Yuting , Hysolli Eriona , Chen Anlu , Casper Stephen , Liu Songlei , Yang Kevin , Liu Chenli , Church George 
Published: July 2021

AbstractLarge-scale recoding has been shown to enable novel amino acids, biocontainment and viral resistance in bacteria only so far. Here we extend this to human cells demonstrating exceptional base editing to convert TAG to TAA for 33 essential genes via a single transfection, and examine base-editing genome-wide (observing ~ 40 C-to-T off-target events in essential gene exons). We also introduce GRIT, a computational tool for recoding. This demonstrates the feasibility of recoding, and multiplex editing in mammalian cells.
Image-based assessment of plant disease progression identifies new genetic loci for resistance
Authors: Méline Valérian , Caldwell Denise L. , Kim Bong-Suk , Baireddy Sriram , Yang Changye , Sparks Erin E. , Delp Edward J. , Iyer-Pascuzzi Anjali S. 
Published: July 2021

AbstractA major challenge in global crop production is mitigating yield loss due to plant diseases. One of the best means of disease control is plant resistance, but the identification of genes that promote resistance has been limited by the subjective quantification of disease, which is typically scored by the human eye. We hypothesized that image-based, non-destructive quantification of disease phenotypes would enable the rapid identification of new disease resistance loci. We tested this using the interaction between tomato andRalstonia solanacearum, a soilborne pathogen that causes bacterial wilt disease. We acquired over 40,000 time-series images of disease progression in a tomato recombinant inbred line population, and developed an image analysis pipeline providing a suite of ten traits to quantify wilt disease based on plant shape and size. Quantitative trait loci (QTL) analyses using image-based phenotyping identified QTL that were both unique and shared compared with those identified by human assessment of wilting. When shared loci were identified, image-based phenotyping could detect some QTL several days earlier than human assessment. Thus, expanding the phenotypic space of disease with image-based, non- destructive phenotyping allowed both earlier detection and identified new genetic components of resistance.
Capsaicin alters human NaV1.5 mechanosensitivity
Authors: Cowan Luke M. , Strege Peter R. , Rusinova Radda , Andersen Olaf S. , Beyder Arthur , Farrugia Gianrico 
Published: July 2021

ABSTRACTSCN5A-encoded NaV1.5 is a voltage-gated Na+ channel expressed in cardiac myocytes and human gastrointestinal (GI) smooth muscle cells (SMCs). NaV1.5 contributes to electrical excitability in the heart and slow waves in the gut. NaV1.5 is also mechanosensitive, and mechanical force modulates several modes of NaV1.5’s voltage-dependent function. NaV1.5 mutations in patients with cardiac arrhythmias and gastrointestinal diseases lead to abnormal mechano- and voltage-sensitivity. Membrane permeable amphipathic drugs that target NaV1.5 in the heart and GI tract alter NaV1.5 mechanosensitivity (MS), suggesting that amphipaths may be a viable therapeutic option for modulating NaV1.5 function. We therefore searched for membrane-permeable amphipathic agents that would modulate NaV1.5 MS with minimal effect on NaV1.5 voltage-gating intact to more selectively target mechanosensitivity. We used two methods to assess NaV1.5 MS: (1) membrane suction in cell-attached macroscopic patches and (2) fluid shear stress on whole cells. We tested the effect of capsaicin on NaV1.5 MS by examining macropatch and whole-cell Na+ current parameters with and without force. The pressure- and shear-mediated peak current increase and acceleration were effectively abolished by capsaicin. Capsaicin abolished the mechanosensitive shifts in the voltage-dependence of activation (shear) and inactivation (pressure and shear). Exploring the recovery from inactivation and use-dependent entry into inactivation, we found divergent stimulus-dependent effects that could potentiate or mitigate the effect of capsaicin, suggesting that mechanical stimuli may differentially modulate NaV1.5 MS. We conclude that selective modulation of MS makes capsaicin is a novel modulator of NaV1.5 MS and a promising therapeutic candidate.
Long-read transcriptome sequencing analysis with IsoTools
Authors: Lienhard Matthias , van den Beucken Twan , Timmermann Bernd , Hochradel Myriam , Boerno Stefan , Caiment Florian , Vingron Martin , Herwig Ralf 
Published: July 2021

AbstractLong-read transcriptome sequencing (LRTS) holds the promise to boost our understanding of alternative splicing. Recent advances in accuracy and throughput have diminished the major limitations and enabled the direct quantification of isoforms. Considering the complexity of the data and the broad range of potential applications, it is clear that highly flexible, accurate analysis tools are crucial. Here, we present IsoTools, a comprehensive Python-based analysis package, for the improvement of alternative and differential splicing analysis. Iso-Tools provides a comprehensive data structure that integrates genomic information from LRTS transcripts together with the reference annotation, and enables broad functionality to quality control, visualize and analyze the data. Additionally, we implemented a graph-based method for the identification of alternative splicing events and a statistical approach based on the beta binomial distribution for the detection of differential events. To demonstrate our methods, we generated PacBio Iso-Seq data of human hepatocytes treated with the HDAC inhibitor valproic acid, a compound known to induce widespread transcriptional changes. Contrasted with short read RNA-Seq of the same samples, this analysis shows that LRTS provides valuable additional insights for a better understanding of alternative splicing, in particular with respect to complex novel and differential splicing events. IsoTools is made available for the community along with extensive documentation at https://github.com/MatthiasLienhard/isotools.