bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mobility, nightlights and air pollution during the early phases of the SARS-CoV-2 pandemic
Authors: Schweikert A E , Flanagan R R , Bui J T , L’Her G F , Kerber S W , Elvidge C D , Deinert M R 
Published: April 2022

Abstract
The SARS-CoV-2 pandemic dramatically shifted daily life in the United States during 2020. The release of high spatial and temporal resolution cell phone data presented a unique opportunity to study the correlation between mobility, electricity use, and tropospheric NO2. While many studies have identified trends of changes in air pollution in locations with reduced mobility due to Covid-19-related restrictions, these studies fall short of assessing whether these trends are statistically significant. Here we analyze if, and how much, mobility, nighttime light and NO2 concentrations correlate. We analyze seven geographically diverse metropolitan areas in the United States (Atlanta, Austin, Boston, Denver, Los Angeles, New York City, Phoenix) in the first half of 2020. Using statistical tests of significance, we find that there is a strong correlation between NO2 levels and nighttime light during February-July 2020 in all urban centers. Mobility and NO2 are correlated strongly in four of the seven urban areas investigated. Together, these results suggest that policies aimed at limiting anthropogenic emissions from fixed (power generation) and mobile (traffic) NO2 sources have an effect on air quality but additional factors should also be considered.
Effects of antidot lattices density on transport features in zigzag graphene nanoribbons
Authors: Zhang Xiaowei , Liu Yuliang 
Published: April 2022

Abstract
Creating antidot lattices in graphene nanoribbons (GNRs) can significantly modify the electronic transport features and may open up an avenue to many practical applications. We here study the effects of antidot lattices on two-terminal transport in GNRs with zigzag edges (ZGNRs), based on the tight-binding method in combination with Green’s function formalism. The antidots in this work are set to be hexagonal structure. For the case of two antidots arranging in ZGNRs, many conductance resonances are found and they become denser and shaper with the increasing of the separation between antidots. However, no any effective transport gap is observed around Fermi energy. For the case of multi-antidots structure, each resonance shows a (m − 1)-splitting, where m is the number of antidots. The analysis on local density of states indicates that all of resonances are related to the quasi-standing waves in ZGNRs. To obtain an effective and stable transport gap, we suggest keeping a dense array of such antidots in ZGNRs. The computed results show that the transport gap decreases very rapidly as the separation between antidots increases. These results might guide the design of the future graphene-based devices.
Collective effects and synchronization of demand in real-time demand response
Authors: Han Chengyuan , Witthaut Dirk , Gorjão Leonardo Rydin , Böttcher Philipp C 
Published: April 2022

Abstract
Future energy systems will be dominated by variable renewable power generation and interconnected sectors, leading to rapidly growing complexity. Flexible elements are required to balance the variability of renewable power sources, including backup generators and storage devices, but also flexible consumers. Demand response (DR) aims to adapt the demand to the variable generation, in particular by shifting the load in time. In this article, we provide a detailed statistic analysis of the collective operation of many DR units. We establish and simulate a model for load shifting in response to real-time electricity pricing using local storage systems. We show that DR drives load shifting as desired but also induces strong collective effects that may threaten system stability. The load of individual households synchronizes, leading to extreme demand peaks. We provide a detailed statistical analysis of the grid load and quantify both the likelihood and extent of extreme demand peaks.
InClass nets: independent classifier networks for nonparametric estimation of conditional independence mixture models and unsupervised classification
Authors: Matchev Konstantin T , Shyamsundar Prasanth 
Published: April 2022

AbstractConditional independence mixture models (CIMMs) are an important class of statistical models used in many fields of science. We introduce a novel unsupervised machine learning technique called the independent classifier networks (InClass nets) technique for the nonparameteric estimation of CIMMs. InClass nets consist of multiple independent classifier neural networks (NNs), which are trained simultaneously using suitable cost functions. Leveraging the ability of NNs to handle high-dimensional data, the conditionally independent variates of the model are allowed to be individually high-dimensional, which is the main advantage of the proposed technique over existing non-machine-learning-based approaches. Two new theorems on the nonparametric identifiability of bivariate CIMMs are derived in the form of a necessary and a (different) sufficient condition for a bivariate CIMM to be identifiable. We use the InClass nets technique to perform CIMM estimation successfully for several examples. We provide a public implementation as a Python package called RainDancesVI.
Public fast charging infrastructure for battery electric trucks—a model-based network for Germany
Authors: Speth Daniel , Plötz Patrick , Funke Simon , Vallarella Emanuel 
Published: April 2022

Abstract
Globally, road freight accounts for 40% of the CO2 emissions in the transport sector, mainly from heavy-duty vehicles (HDVs). All the major truck markets have introduced fuel efficiency regulations for HDV, and the more ambitious regulations require the introduction of zero-emission HDV, for which battery electric trucks (BEVs) are a promising candidate. However, frequent long-distance trips require a dense public high-power charging network if BEV are to meet today's operating schedules in logistics. Here, we develop a model for public BEV high-power fast-charging that uses widely available traffic count data as input and combines this with on-site queueing models. We apply the model to Germany and obtain a fast-charging network where average waiting times do not exceed 5 min. For 15% BEV in the truck stock and 50% public charging, the model shows 267 charging locations, each with 2–8 charging points per location, for a dense network with 50 km distance between charging locations. We calculated 142 charging locations with 2–13 charging points for a wider network with 100 km distance between locations. Our results help to design future charging infrastructure for electric road freight transport.
Platelet reactivity testing in peripheral artery disease
Authors: Zhang Youqi , Chou Jennifer W , Huang Wan-Ting , Derry Katrina , Humber Doug 
Published: April 2022

Abstract

Purpose
Oral antiplatelet therapy is routinely used to prevent adverse cardiovascular events in patients with peripheral artery disease (PAD). Several laboratory tests are available to quantify the degree of platelet inhibition following antiplatelet therapy. This article aims to provide a review of the literature surrounding platelet functional testing in patients with PAD receiving oral P2Y12 inhibitors and to offer guidance to clinicians for the use and interpretation of these tests.

Summary
A literature search of PubMed and the Web of Science Core Collection database was conducted. All studies that performed platelet function testing and reported clinical outcomes in patients with PAD were included. Evaluation of the data suggests that, among the available testing strategies, the VerifyNow platelet reactivity unit (PRU) test is the most widely used. Despite numerous investigations attempting to define a laboratory threshold indicating suboptimal response to antiplatelet therapy, controversy exists about which PRU value best correlates with cardiovascular outcomes (ie, mortality, stent thrombosis, etc). In the PAD literature, the most commonly used PRU thresholds are 208 or higher and 235 or higher. Nonetheless, adjusting antiplatelet regimens based on suboptimal P2Y12 reactivity values has yet to be proven useful in reducing the incidence of adverse cardiovascular outcomes. This review examines platelet function testing in patients with PAD and discusses the interpretation and application of these tests when monitoring the safety and efficacy of P2Y12 inhibitors.

Conclusion
Although platelet functional tests may be simple to use, clinical trials thus far have failed to show benefit from therapy adjustments based on test results. Clinicians should be cautioned against relying on this test result alone and should instead consider a combination of laboratory, clinical, and patient-specific factors when adjusting P2Y12 inhibitor therapy in clinical practice.
Eravacycline infusion–related hypoesthesia: A case report
Authors: Miller R Briley , McClure Kinsey M , Stewart Robby G , Shealy Stephanie C , Brown Krishnan , Bookstaver P Brandon 
Published: April 2022

Abstract

Purpose
Eravacycline (ERV) is often used for drug-resistant gram-negative and nontuberculous mycobacteria (NTM) infections, but infusion site reactions are a potential adverse effect. We report a case of severe hypoesthesia secondary to ERV infusion.

Summary
A 74-year-old man presented with dyspnea, shortness of breath, and hemoptysis after being treated for community-acquired pneumonia. On the basis of respiratory cultures performed several weeks before the index hospitalization, he was diagnosed with Mycobacterium chelonae pneumonia. On hospital day (HD) 2, the infectious diseases consult team, guided by susceptibilities, initiated a regimen of azithromycin, levofloxacin, and ERV 80 mg (1 mg/kg) intravenously every 12 hours infused over 1 hour in 250 mL of normal saline. Approximately 25 minutes after the ERV infusion began, the patient reported tingling and numbness in his fingers, hands, and mouth, with shooting pain in his head. Symptoms resolved with cessation of the ERV infusion. On HD 3, the same ERV dose and volume was administered with an extended infusion time of 2 hours. The patient experienced the same reaction after 58 minutes, which ceased shortly after the infusion was stopped. Use of ERV was subsequently discontinued. The Naranjo adverse drug reaction probability scale score was 9, indicating a definite reaction. A review of the Food and Drug Administration Adverse Event Reporting System through March 2021 identified 22 ERV-associated events. Among these, 18% appear to be related to ERV infusions. Published results from phase 3 clinical trials did not document any hypoesthesia. It is unknown whether there is a correlation between concentration, dose, or infusion time and associated reactions.

Conclusion
This is a unique case of severe hypoesthesia secondary to ERV infusion leading to drug discontinuation. More data are needed to determine effective mitigation strategies.
MTD: a unique pipeline for host and meta-transcriptome joint and integrative analyses of RNA-seq data
Authors: Wu Fei , Liu Yao-Zhong , Ling Binhua 
Published: April 2022

Abstract
Ribonucleic acid (RNA)-seq data contain not only host transcriptomes but also nonhost information that comprises transcripts from active microbiota in the host cells. Therefore, joint and integrative analyses of both host and meta-transcriptome can reveal gene expression of the microbial community in a given sample as well as the correlative and interactive dynamics of the host response to the microbiome. However, there are no convenient tools that can systemically analyze host–microbiota interactions through simultaneously quantifying the host and meta-transcriptome in the same sample at the tissue and the single-cell level. This poses a challenge for interested researchers with limited expertise in bioinformatics. Here, we developed a software pipeline that can comprehensively and synergistically analyze and correlate the host and meta-transcriptome in a single sample using bulk and single-cell RNA-seq data. This pipeline, named meta-transcriptome detector (MTD), can extensively identify and quantify microbiome, including viruses, bacteria, protozoa, fungi, plasmids and vectors, in the host cells and correlate the microbiome with the host transcriptome. MTD is easy to install and run, involving only a few lines of simple commands. It offers researchers with unique genomics insights into host responses to microorganisms.
ELIXIR biovalidator for semantic validation of life science metadata
Authors: Liyanage Isuru , Burdett Tony , Droesbeke Bert , Erdos Karoly , Fernandez Rolando , Gray Alasdair , Haseeb Muhammad , Jupp Simon , Penim Flavia , Pommier Cyril , Rocca-Serra Philippe , Courtot Mélanie , Coppens Frederik 
Published: April 2022

AbstractSummaryTo advance biomedical research, increasingly large amounts of complex data need to be discovered and integrated. This requires syntactic and semantic validation to ensure shared understanding of relevant entities. This article describes the ELIXIR biovalidator, which extends the syntactic validation of the widely used AJV library with ontology-based validation of JSON documents.Availability and implementationSource code: https://github.com/elixir-europe/biovalidator, Release: v1.9.1, License: Apache License 2.0, Deployed at: https://www.ebi.ac.uk/biosamples/schema/validator/validate.Supplementary informationSupplementary data are available at Bioinformatics online.
Impact of protein conformational diversity on AlphaFold predictions
Authors: Saldaño Tadeo , Escobedo Nahuel , Marchetti Julia , Zea Diego Javier , Mac Donagh Juan , Velez Rueda Ana Julia , Gonik Eduardo , García Melani Agustina , Novomisky Nechcoff Julieta , Salas Martín N , Peters Tomás , Demitroff Nicolás , Fernandez Alberti Sebastian , Palopoli Nicolas , Fornasari Maria Silvina , Parisi Gustavo 
Published: April 2022

Abstract

Motivation
After the outstanding breakthrough of AlphaFold in predicting protein 3D models, new questions appeared and remain unanswered. The ensemble nature of proteins, for example, challenges the structural prediction methods because the models should represent a set of conformers instead of single structures. The evolutionary and structural features captured by effective deep learning techniques may unveil the information to generate several diverse conformations from a single sequence. Here, we address the performance of AlphaFold2 predictions obtained through ColabFold under this ensemble paradigm.

Results
Using a curated collection of apo–holo pairs of conformers, we found that AlphaFold2 predicts the holo form of a protein in ∼70% of the cases, being unable to reproduce the observed conformational diversity with the same error for both conformers. More importantly, we found that AlphaFold2's performance worsens with the increasing conformational diversity of the studied protein. This impairment is related to the heterogeneity in the degree of conformational diversity found between different members of the homologous family of the protein under study. Finally, we found that main-chain flexibility associated with apo–holo pairs of conformers negatively correlates with the predicted local model quality score plDDT, indicating that plDDT values in a single 3D model could be used to infer local conformational changes linked to ligand binding transitions.

Availability and implementation
Data and code used in this manuscript are publicly available at https://gitlab.com/sbgunq/publications/af2confdiv-oct2021.

Supplementary information
Supplementary data are available at Bioinformatics online.
Central stress processing, T-cell responsivity to stress hormones and disease severity in multiple sclerosis
Authors: Brasanac Jelena , Hetzer Stefan , Asseyer Susanna , Kuchling Joseph , Bellmann-Strobl Judith , Ritter Kristin , Gamradt Stefanie , Scheel Michael , Haynes John-Dylan , Brandt Alexander U. , Paul Friedemann , Gold Stefan M. , Weygandt Martin 
Published: April 2022

Abstract
Epidemiological, clinical and neuroscientific studies support a link between psychobiological stress and multiple sclerosis. Neuroimaging suggests that blunted central stress processing goes along with higher multiple sclerosis severity, neuroendocrine studies suggest that blunted immune system sensitivity to stress hormones is linked to stronger neuroinflammation. Until now, however, no effort has been made to elucidate whether central stress processing and immune system sensitivity to stress hormones are related in a disease-specific fashion, and if so, whether this relation is clinically meaningful. Consequently, we conducted two functional MRI analyses based on a total of 39 persons with multiple sclerosis and 25 healthy persons. Motivated by findings of an altered interplay between neuroendocrine stress processing and T-cell glucocorticoid sensitivity in multiple sclerosis, we searched for neural networks whose stress task-evoked activity is differentially linked to peripheral T-cell glucocorticoid signalling in patients versus healthy persons as a potential indicator of disease-specific CNS–immune crosstalk. Subsequently, we tested whether this activity is simultaneously related to disease severity. We found that activity of a network comprising right anterior insula, right fusiform gyrus, left midcingulate and lingual gyrus was differentially coupled to T-cell glucocorticoid signalling across groups. This network’s activity was simultaneously linked to patients’ lesion volume, clinical disability and information-processing speed. Complementary analyses revealed that T-cell glucocorticoid signalling was not directly linked to disease severity. Our findings show that alterations in the coupling between central stress processing and T-cell stress hormone sensitivity are related to key severity measures of multiple sclerosis.
Altered spontaneous cortical activity predicts pain perception in individuals with cerebral palsy
Authors: Trevarrow Michael P. , Reelfs Anna , Ott Lauren R. , Penhale Samantha H. , Lew Brandon J. , Goeller Jessica , Wilson Tony W. , Kurz Max J. 
Published: April 2022

Abstract
Cerebral palsy is the most common paediatric neurological disorder and results in extensive impairment to the sensorimotor system. However, these individuals also experience increased pain perception, resulting in decreased quality of life. In the present study, we utilized magnetoencephalographic brain imaging to examine whether alterations in spontaneous neural activity predict the level of pain experienced in a cohort of 38 individuals with spastic diplegic cerebral palsy and 67 neurotypical controls. Participants completed 5 min of an eyes closed resting-state paradigm while undergoing a magnetoencephalography recording. The magnetoencephalographic data were then source imaged, and the power within the delta (2–4 Hz), theta (5–7 Hz), alpha (8–12 Hz), beta (15–29 Hz), low gamma (30–59 Hz) and high gamma (60–90 Hz) frequency bands were computed. The resulting power spectral density maps were analysed vertex-wise to identify differences in spontaneous activity between groups. Our findings indicated that spontaneous cortical activity was altered in the participants with cerebral palsy in the delta, alpha, beta, low gamma and high gamma bands across the occipital, frontal and secondary somatosensory cortical areas (all pFWE &lt; 0.05). Furthermore, we also found that the altered beta band spontaneous activity in the secondary somatosensory cortices predicted heightened pain perception in the individuals with cerebral palsy (P = 0.039). Overall, these results demonstrate that spontaneous cortical activity within individuals with cerebral palsy is altered in comparison to their neurotypical peers and may predict increased pain perception in this patient population. Potentially, changes in spontaneous resting-state activity may be utilized to measure the effectiveness of current treatment approaches that are directed at reducing the pain experienced by individuals with cerebral palsy.
Tinnitus: at a crossroad between phantom perception and sleep
Authors: Milinski Linus , Nodal Fernando R. , Vyazovskiy Vladyslav V. , Bajo Victoria M. 
Published: April 2022

AbstractSensory disconnection from the environment is a hallmark of sleep and is crucial for sleep maintenance. It remains unclear, however, whether internally generated percepts—phantom percepts—may overcome such disconnection and, in turn, how sleep and its effect on sensory processing and brain plasticity may affect the function of the specific neural networks underlying such phenomena. A major hurdle in addressing this relationship is the methodological difficulty to study sensory phantoms, due to their subjective nature and lack of control over the parameters or neural activity underlying that percept. Here, we explore the most prevalent phantom percept, subjective tinnitus—or tinnitus for short—as a model to investigate this. Tinnitus is the permanent perception of a sound with no identifiable corresponding acoustic source. This review offers a novel perspective on the functional interaction between brain activity across the sleep–wake cycle and tinnitus. We discuss characteristic features of brain activity during tinnitus in the awake and the sleeping brain and explore its effect on sleep functions and homeostasis. We ask whether local changes in cortical activity in tinnitus may overcome sensory disconnection and prevent the occurrence of global restorative sleep and, in turn, how accumulating sleep pressure may temporarily alleviate the persistence of a phantom sound. Beyond an acute interaction between sleep and neural activity, we discuss how the effects of sleep on brain plasticity may contribute to aberrant neural circuit activity and promote tinnitus consolidation. Tinnitus represents a unique window into understanding the role of sleep in sensory processing. Clarification of the underlying relationship may offer novel insights into therapeutic interventions in tinnitus management.