bluuebunny/crossref_metadata_2025_split huggingface dataset:
Competitive effect between roughness and mask pattern on charging phenomena during plasma etching
Authors: ZHANG Peng , DAMBIRE Ruvarashe F 
Published: January 2022

Abstract
In the plasma etching process, the edge roughness and mask pattern usually play a significant role in the deformation of holes under the influence of the charging effect. The competitive effect between these two factors has been investigated, focusing on the surface charging in a hexagonal array, with various values of roughness parameters (amplitude (A) and wavelength (W)) and distances between holes (L). A series of classical particle dynamic simulations of surface charging, surface etching and profile evolution were used to investigate the effect of roughness and pattern on charging. This study showed that various roughness and patterns (represented by different values of L) can significantly influence surface distributions of the electric-field (E-field) and the etching rates on the mask surface. The simulations also showed that (1) the shape of the pattern array influences the mask hole profile during the etching process, i.e. a hexagonal array pattern tends to deform the profile of a circular mask hole into a hexagonal hole; (2) pattern roughness is aggravated during the etching process. These factors were found to be significant only at a small feature pitch and may be ignored at a large feature pitch. Possible mechanisms of these results during the etching process are discussed. This work sheds light on the ways to maintain pattern integrity and further improve the quality of the pattern transfer onto the substrate.
Influence of committed volunteers on helping behavior in emergency evacuations
Authors: Kwak Jaeyoung , Lees Michael H , Cai Wentong , Pourghaderi Ahmad Reza , Ong Marcus E H 
Published: January 2022

AbstractWe study how the presence of committed volunteers influences the collective helping behavior in emergency evacuation scenarios. In this study, committed volunteers do not change their decision to help injured persons, implying that other evacuees may adapt their helping behavior through strategic interactions. An evolutionary game theoretic model is developed which is then coupled to a pedestrian movement model to examine the collective helping behavior in evacuations. By systematically controlling the number of committed volunteers and payoff parameters, we have characterized and summarized various collective helping behaviors in phase diagrams. From our numerical simulations, we observe that the existence of committed volunteers can promote cooperation but adding additional committed volunteers is effective only above a minimum number of committed volunteers. This study also highlights that the evolution of collective helping behavior is strongly affected by the evacuation process.
Towards a reproducible interactome: semantic-based detection of redundancies to unify protein–protein interaction databases
Authors: Melkonian Marc , Juigné Camille , Dameron Olivier , Rabut Gwenaël , Becker Emmanuelle 
Published: January 2022

Abstract

Motivation
Information on protein–protein interactions is collected in numerous primary databases with their own curation process. Several meta-databases aggregate primary databases to provide more exhaustive datasets. In addition to exhaustivity, aggregation contributes to reliability by providing an overview of the various studies and detection methods supporting an interaction. However, interactions listed in different primary databases are partly redundant because some publications reporting protein–protein interactions have been curated by multiple primary databases. Mere aggregation can thus introduce a bias if these redundancies are not identified and eliminated. To overcome this bias, meta-databases rely on the Molecular Interaction ontology that describes interaction detection methods, but they do not fully take advantage of the ontology’s rich semantics, which leads to systematically overestimating interaction reproducibility.

Results
We propose a precise definition of explicit and implicit redundancy and show that both can be easily detected using Semantic Web technologies. We apply this process to a dataset from the Agile Protein Interactomes DataServer (APID) meta-database and show that while explicit redundancies were detected by the APID aggregation process, about 15% of APID entries are implicitly redundant and should not be taken into account when presenting confidence-related metrics. More than 90% of implicit redundancies result from the aggregation of distinct primary databases, whereas the remaining occurs between entries of a single database. Finally, we build a ‘reproducible interactome’ with interactions that have been reproduced by multiple methods or publications. The size of the reproducible interactome is drastically impacted by removing redundancies for both yeast (−59%) and human (−56%), and we show that this is largely due to implicit redundancies.

Availability and implementation
Software, data and results are available at https://gitlab.com/nnet56/reproducible-interactome, https://reproducible-interactome.genouest.org/, Zenodo (https://doi.org/10.5281/zenodo.5595037) and NDEx (https://doi.org/10.18119/N94302 and https://doi.org/10.18119/N97S4D).

Supplementary information
Supplementary data are available at Bioinformatics online.
Incidence of Positive Severe Acute Respiratory Syndrome Coronavirus Polymerase Chain Reaction After Coronavirus Disease 2019 Vaccination With up to 8 Months of Follow-up: Real-life Data From the Capital Region of Denmark
Authors: Heftdal Line Dam , Schultz Martin , Lange Theis , Knudsen Andreas Dehlbæk , Fogh Kamille , Hasselbalch Rasmus Bo , Linander Christine Borgen , Kallemose Thomas , Bundgaard Henning , Grønbæk Kirsten , Valentiner-Branth Palle , Iversen Kasper , Nielsen Susanne Dam 
Published: January 2022

Abstract

Background
Coronavirus disease 2019 (COVID-19) vaccines are implemented worldwide in efforts to curb the pandemic. This study investigates the risk of a positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcriptase polymerase chain reaction (RT-PCR) test following BNT162b2 vaccination in a large real-life population in Denmark.

Methods
Vaccination status and positive SARS-CoV-2 RT-PCR results from adults in the Capital Region of Denmark (n = 1 549 488) were obtained from national registries. PCR testing was free and widely available. The number of positive PCR tests per individual at risk was calculated as weekly rates. Time to positive PCR test was modelled using Kaplan-Meier methods and hazard ratios (HRs) were calculated using Cox regression.

Results
A total of 1 119 574 individuals received the first dose of BNT162b2 and 1 088 879 received a second dose of BNT162b2. Individuals were followed up to 8.7 months after first dose (median: 5.5 months; interquartile ratio: 4.1–8.7). Rates of PCR-confirmed SARS-CoV-2 infection 2–4 months after the second dose were 0.21, 0.33, and 0.36 per 1000 individuals per week at risk for July, August, and September, respectively. Four or more months after the second dose, the rates were 0.56, 0.76, and 0.53 per 1000 individuals per week at risk for July, August, and September, respectively. HR of SARS-CoV-2 infection after the second dose was 0.2 (95% confidence interval, .05–.48; P = .001) for individuals with 8 months’ follow-up.

Conclusions
Individuals who received 2 doses of the BNT162b2 COVID-19 vaccine had a low risk of breakthrough infection after up to 8 months of follow-up. However, there was a tendency toward higher rates with longer follow-up.
Clinical Impact of the Refit CKD-EPI 2021 Creatinine-Based eGFR Equation
Authors: Meeusen Jeffrey W , Kasozi Ramla N , Larson Timothy S , Lieske John C 
Published: January 2022

Abstract

Background
The National Kidney Foundation recently endorsed the refit Chronic Kidney Disease Collaboration (CKD-EPI) equation for estimated glomerular filtration rate (eGFR) using creatinine, age and sex [2021 eGFRCr(AS)] without a coefficient for race. We evaluated the impact of adopting the 2021 eGFRCr(AS) equation or a variation of the 2009 CKD-EPI eGFR equation without race [2009 CKD-EPI eGFRCr(ASR-NB)] compared to the original CKD-EPI eGFR [2009 eGFRCr(ASR)].

Methods
The studied population included patients with a clinically ordered iothalamate clearance (n = 33 889). Bias was assessed as the difference between measured and estimated GFR, P30 was defined as the percentage of estimates within 30% of measured GFR, and concordance was determined according to relevant clinical thresholds.

Results
Among Black patients, the median bias for 2009 eGFRCr(ASR), 2009 eGFRCr(ASR-NB), and 2021 eGFRCr(AS) was −1.32 mL min−1 (1.73 m2)−1 (95CI −2.46 to −0.26), −8.81 mL min−1 (1.73 m2)−1 (95CI −9.93 to −7.58), and −6.08 mL min−1 (1.73 m2)−1 (95CI −7.18 to −4.92), respectively. The median bias among non-Black patients was −0.15 m min−1 (1.73 m2)−1 (95CI −0.84 to −0.08) for 2021 eGFRcr(AS) compared to −3.09 mL min−1 (1.73 m2)−1 (95CI −3.17 to −3.03) for the 2009 eGFRCr(ASR). P30 and concordance were not significantly different in either racial group. The net reclassification improvement at a measured GFR &lt;20 mL min−1 (1.73 m2)−1 was 6.4% (95CI 0.36 to 12.4) for Black patients and −5.1% (95CI −6.0 to −4.1) for non-Black patients using the 2021 eGFRCr(AS) equation.

Conclusions
Overall, the change in reported eGFR was minimal. However, these changes led to significant reclassification improvements at lower eGFR, which will indirectly improve equitable access to CKD resources.
Evaluation of Neutralizing Antibodies against SARS-CoV-2 Variants after Infection and Vaccination Using a Multiplexed Surrogate Virus Neutralization Test
Authors: Lynch Kara L , Zhou Shuxia , Kaul Ravi , Walker Roger , Wu Alan H 
Published: January 2022

Abstract

Background
The SARS-CoV-2 virus has mutated and evolved since the inception of the COVID-19 pandemic bringing into question the future effectiveness of current vaccines and antibody therapeutics. With evolution of the virus updated methods for the evaluation of the immune response in infected and vaccinated individuals are required to determine the durability of the immune response to SARS-CoV-2 variants.

Methods
We developed a multiplexed surrogate virus neutralization test (plex-sVNT) that simultaneously measures the ability of antibodies in serum to inhibit binding between angiotensin converting enzyme-2 (ACE2) and 7 SARS-CoV-2 trimeric spike protein variants, including wild type, B.1.1.7(α), B.1.351(β), P.1(γ), B.1.617.2(δ), B.1.617.1(κ), and B.1.429(ε). The assay was validated against a plaque reduction neutralization test (PRNT).
We evaluated 170 samples from 97 COVID-19 patients and 281 samples from 188 individuals that received the Pfizer-BioNTech or Moderna mRNA vaccines.

Results
The plex-sVNT demonstrated &gt;96% concordance with PRNT. Antibody neutralization activity was significantly reduced for all SARS-CoV-2 variants compared to wild type in both the infected and vaccinated cohorts. There was a decline in overall antibody neutralization activity, within both cohorts, out to 5 months post infection or vaccination, with the rate of decline being more significant for the vaccinated.

Conclusions
The plex-sVNT provides a correlative measure to PRNT and a convenient approach for evaluating antibody neutralization against SARS-CoV-2 variants. Neutralization of SARS-CoV-2 variants is reduced compared to wild type and declines over the ensuing months after exposure or vaccination within each cohort, however it is still unknown what degree of neutralizing capacity is protective.
DDPD 1.0: a manually curated and standardized database of digital properties of approved drugs for drug-likeness evaluation and drug development
Authors: Li Qiang , Ma Shiyong , Zhang Xuelu , Zhai Zhaoyu , Zhou Lu , Tao Haodong , Wang Yachen , Pan Jianbo 
Published: January 2022

Abstract
Drug-likeness is a vital consideration when selecting compounds in the early stage of drug discovery. A series of drug-like properties are needed to predict the drug-likeness of a given compound and provide useful guidelines to increase the likelihood of converting lead compounds into drugs. Experimental physicochemical properties, pharmacokinetic/toxicokinetic properties and maximum dosages of approved small-molecule drugs from multiple text-based unstructured data resources have been manually assembled, curated, further digitized and processed into structured data, which are deposited in the Database of Digital Properties of approved Drugs (DDPD). DDPD 1.0 contains 30 212 drug property entries, including 2250 approved drugs and 32 properties, in a standardized value/unit format. Moreover, two analysis tools are provided to examine the drug-likeness features of given molecules based on the collected property data of approved drugs. Additionally, three case studies are presented to demonstrate how users can utilize the database. We believe that this database will be a valuable resource for the drug discovery and development field.
Database URL: http://www.inbirg.com/ddpd
Interferon regulatory factor-5-dependent CD11c+ macrophages contribute to the formation of rupture–prone atherosclerotic plaques
Authors: Edsfeldt Andreas , Swart Maarten , Singh Pratibha , Dib Lea , Sun Jiangming , Cole Jennifer E , Park Inhye , Al-Sharify Dania , Persson Ana , Nitulescu Mihaela , Borges Patricia Das Neves , Kassiteridi Christina , Goddard Michael E , Lee Regent , Volkov Petr , Orho-Melander Marju , Maegdefessel Lars , Nilsson Jan , Udalova Irina , Goncalves Isabel , Monaco Claudia 
Published: January 2022

Abstract

Aims
Inflammation is a key factor in atherosclerosis. The transcription factor interferon regulatory factor-5 (IRF5) drives macrophages towards a pro-inflammatory state. We investigated the role of IRF5 in human atherosclerosis and plaque stability.

Methods and results
Bulk RNA sequencing from the Carotid Plaque Imaging Project biobank were used to mine associations between major macrophage associated genes and transcription factors and human symptomatic carotid disease. Immunohistochemistry, proximity extension assays, and Helios cytometry by time of flight (CyTOF) were used for validation. The effect of IRF5 deficiency on carotid plaque phenotype and rupture in ApoE−/− mice was studied in an inducible model of plaque rupture. Interferon regulatory factor-5 and ITGAX/CD11c were identified as the macrophage associated genes with the strongest associations with symptomatic carotid disease. Expression of IRF5 and ITGAX/CD11c correlated with the vulnerability index, pro-inflammatory plaque cytokine levels, necrotic core area, and with each other. Macrophages were the predominant CD11c-expressing immune cells in the plaque by CyTOF and immunohistochemistry. Interferon regulatory factor-5 immunopositive areas were predominantly found within CD11c+ areas with a predilection for the shoulder region, the area of the human plaque most prone to rupture. Accordingly, an inducible plaque rupture model of ApoE−/−Irf5−/− mice had significantly lower frequencies of carotid plaque ruptures, smaller necrotic cores, and less CD11c+ macrophages than their IRF5-competent counterparts.

Conclusion
Using complementary evidence from data from human carotid endarterectomies and a murine model of inducible rupture of carotid artery plaque in IRF5-deficient mice, we demonstrate a mechanistic link between the pro-inflammatory transcription factor IRF5, macrophage phenotype, plaque inflammation, and its vulnerability to rupture.
Deep learning for forest inventory and planning: a critical review on the remote sensing approaches so far and prospects for further applications
Authors: Hamedianfar Alireza , Mohamedou Cheikh , Kangas Annika , Vauhkonen Jari 
Published: January 2022

AbstractData processing for forestry applications is challenged by the increasing availability of multi-source and multi-temporal data. The advancements of Deep Learning (DL) algorithms have made it a prominent family of methods for machine learning and artificial intelligence. This review determines the current state-of-the-art in using DL for solving forestry problems. Although DL has shown potential for various estimation tasks, the applications of DL to forestry are in their infancy. The main study line has related to comparing various Convolutional Neural Network (CNN) architectures between each other and against more shallow machine learning techniques. The main asset of DL is the possibility to internally learn multi-scale features without an explicit feature extraction step, which many people typically perceive as a black box approach. According to a comprehensive literature review, we identified challenges related to (1) acquiring sufficient amounts of representative and labelled training data, (2) difficulties to select suitable DL architecture and hyperparameterization among many methodological choices and (3) susceptibility to overlearn the training data and consequent risks related to the generalizability of the predictions, which can however be reduced by proper choices on the above. We recognized possibilities in building time-series prediction strategies upon Recurrent Neural Network architectures and, more generally, re-thinking forestry applications in terms of components inherent to DL. Nevertheless, DL applications remain data-driven, in contrast to being based on causal reasoning, and currently lack many best practices of conventional forestry modelling approaches. The benefits of DL depend on the application, and the practitioners are advised to ex ante subject their requirements to operational data availability, for example. By this review, we contribute to the technical discussion about the prospects of DL for forestry and shed light on properties that require attention from the practitioners.
Patchy Distribution of GTPases of Immunity-Associated Proteins (GIMAP) within Cnidarians and Dinoflagellates Suggests a Complex Evolutionary History
Authors: Coelho Jenny C , Calhoun Ethan D , Calhoun Grant N , Poole Angela Z 
Published: January 2022

Abstract
GTPases of Immunity-Associated Proteins (GIMAP) are a group of small GTP-binding proteins found in a variety of organisms, including vertebrates, invertebrates, and plants. These proteins are characterized by the highly conserved AIG1 domain, and in vertebrates, have been implicated in regulation of the immune system as well as apoptosis and autophagy, though their exact mechanism of action remains unclear. Recent work on cnidarian GIMAPs suggests a conserved role in immunity, apoptosis, and autophagy—three processes involved in coral bleaching, or the breakdown of cnidarian-dinoflagellate symbiosis. Therefore, to further understand the evolution of GIMAPs in this group of organisms, the purpose of this study was to characterize GIMAP or GIMAP-like sequences utilizing publicly available genomic and transcriptomic data in species across the cnidarian phylogeny. The results revealed a patchy distribution of GIMAPs in cnidarians, with three distinct types referred to as L-GIMAP, S-GIMAP, and GIMAP-like. Additionally, GIMAPs were present in most dinoflagellate species and formed seven well-supported clades. Overall, these results elucidate the distribution of GIMAPs within two distantly related eukaryotic groups and represent the first in-depth investigation on the evolution of these proteins within both protists and basal metazoans.
Natural genetic variation as a tool for discovery in Caenorhabditis nematodes
Authors: Andersen Erik C , Rockman Matthew V 
Published: January 2022

Abstract
Over the last 20 years, studies of Caenorhabditis elegans natural diversity have demonstrated the power of quantitative genetic approaches to reveal the evolutionary, ecological, and genetic factors that shape traits. These studies complement the use of the laboratory-adapted strain N2 and enable additional discoveries not possible using only one genetic background. In this chapter, we describe how to perform quantitative genetic studies in Caenorhabditis, with an emphasis on C. elegans. These approaches use correlations between genotype and phenotype across populations of genetically diverse individuals to discover the genetic causes of phenotypic variation. We present methods that use linkage, near-isogenic lines, association, and bulk-segregant mapping, and we describe the advantages and disadvantages of each approach. The power of C. elegans quantitative genetic mapping is best shown in the ability to connect phenotypic differences to specific genes and variants. We will present methods to narrow genomic regions to candidate genes and then tests to identify the gene or variant involved in a quantitative trait. The same features that make C. elegans a preeminent experimental model animal contribute to its exceptional value as a tool to understand natural phenotypic variation.
The Biological Variability of Plasma Ceramides in Healthy Subjects
Authors: Ramos Paola , Jenkins Sarah M , Donato Leslie J , Hartman Stacy J , Saenger Amy , Baumann Nikola A , Block Darci R , Jaffe Allan S , Meeusen Jeffrey W 
Published: January 2022

AbstractBackgroundCeramides are bioactive lipid species that mediate numerous cell-signaling events. Elevated plasma ceramides concentration constitutes a risk factor for several pathologies. Multiple studies have affirmed the plasma concentrations of 4 specific ceramides (Cer16:0, Cer18:0, Cer24:0, and Cer24:1) can predict cardiovascular disease risk. Furthermore, these ceramides can be altered by many lipid-lowering therapies. Understanding the biological variability within an individual, and within a population, will further inform the clinical use of plasma ceramides as a biomarker. In this study, we aimed to define the intra- and interbiological variability of ceramides in a healthy reference population in a weekly and monthly manner.MethodsFasting plasma from 24 healthy adults was collected daily (5 days), weekly (4 weeks), and monthly (7 months). Ceramide concentrations were measured with liquid chromatography–mass spectrometry (LC–MS). For analysis, we used random-effects regression models to estimate variance components.ResultsThe analytical variability was smaller compared to the biological variability overall. The greatest variation reported was between-subject variation for all ceramide species. The critical difference-reference change value (RCV) for within-subject variations monthly were 0.07 mcmol/L (Cer16:0), 0.04 mcmol/L (Cer18:0), 1.09 mcmol/L (Cer24:0), and 0.27 mcmol/L (Cer24:1). The index of individuality (IOI) of ceramides were 0.82 (Cer16:0), 0.96 (Cer18:0), 1.06 (Cer24:0), and 0.89 (Cer24:1). The most consistent ceramide species was Cer18:0 with the lowest within- and between-subject critical differences in weekly and monthly measurements.ConclusionsOverall, this study demonstrates that the variability of ceramide concentrations at different time points is minimal within individuals, allowing a single draw to be sufficient at least in a yearly time frame.