bluuebunny/crossref_metadata_2025_split huggingface dataset:
Soil contamination in nearby natural areas mirrors that in urban greenspaces worldwide
Authors: Liu Yu-Rong , van der Heijden Marcel G. A. , Riedo Judith , Sanz-Lazaro Carlos , Eldridge David J. , Bastida Felipe , Moreno-Jiménez Eduardo , Zhou Xin-Quan , Hu Hang-Wei , He Ji-Zheng , Moreno José L. , Abades Sebastian , Alfaro Fernando , Bamigboye Adebola R. , Berdugo Miguel , Blanco-Pastor José L. , de los Ríos Asunción , Duran Jorge , Grebenc Tine , Illán Javier G. , Makhalanyane Thulani P. , Molina-Montenegro Marco A. , Nahberger Tina U. , Peñaloza-Bojacá Gabriel F. , Plaza César , Rey Ana , Rodríguez Alexandra , Siebe Christina , Teixido Alberto L. , Casado-Coy Nuria , Trivedi Pankaj , Torres-Díaz Cristian , Verma Jay Prakash , Mukherjee Arpan , Zeng Xiao-Min , Wang Ling , Wang Jianyong , Zaady Eli , Zhou Xiaobing , Huang Qiaoyun , Tan Wenfeng , Zhu Yong-Guan , Rillig Matthias C. , Delgado-Baquerizo Manuel 
Published: March 2023

AbstractSoil contamination is one of the main threats to ecosystem health and sustainability. Yet little is known about the extent to which soil contaminants differ between urban greenspaces and natural ecosystems. Here we show that urban greenspaces and adjacent natural areas (i.e., natural/semi-natural ecosystems) shared similar levels of multiple soil contaminants (metal(loid)s, pesticides, microplastics, and antibiotic resistance genes) across the globe. We reveal that human influence explained many forms of soil contamination worldwide. Socio-economic factors were integral to explaining the occurrence of soil contaminants worldwide. We further show that increased levels of multiple soil contaminants were linked with changes in microbial traits including genes associated with environmental stress resistance, nutrient cycling, and pathogenesis. Taken together, our work demonstrates that human-driven soil contamination in nearby natural areas mirrors that in urban greenspaces globally, and highlights that soil contaminants have the potential to cause dire consequences for ecosystem sustainability and human wellbeing.
A comprehensive platform for analyzing longitudinal multi-omics data
Authors: Vasaikar Suhas V. , Savage Adam K. , Gong Qiuyu , Swanson Elliott , Talla Aarthi , Lord Cara , Heubeck Alexander T. , Reading Julian , Graybuck Lucas T. , Meijer Paul , Torgerson Troy R. , Skene Peter J. , Bumol Thomas F. , Li Xiao-jun 
Published: March 2023

AbstractLongitudinal bulk and single-cell omics data is increasingly generated for biological and clinical research but is challenging to analyze due to its many intrinsic types of variations. We present PALMO (https://github.com/aifimmunology/PALMO), a platform that contains five analytical modules to examine longitudinal bulk and single-cell multi-omics data from multiple perspectives, including decomposition of sources of variations within the data, collection of stable or variable features across timepoints and participants, identification of up- or down-regulated markers across timepoints of individual participants, and investigation on samples of same participants for possible outlier events. We have tested PALMO performance on a complex longitudinal multi-omics dataset of five data modalities on the same samples and six external datasets of diverse background. Both PALMO and our longitudinal multi-omics dataset can be valuable resources to the scientific community.
Boosting membrane carbon capture via multifaceted polyphenol-mediated soldering
Authors: Zhu Bin , He Shanshan , Yang Yan , Li Songwei , Lau Cher Hon , Liu Shaomin , Shao Lu 
Published: March 2023

AbstractAdvances in membrane technologies are significant for mitigating global climate change because of their low cost and easy operation. Although mixed-matrix membranes (MMMs) obtained via the combination of metal-organic frameworks (MOFs) and a polymer matrix are promising for energy-efficient gas separation, the achievement of a desirable match between polymers and MOFs for the development of advanced MMMs is challenging, especially when emerging highly permeable materials such as polymers of intrinsic microporosity (PIMs) are deployed. Here, we report a molecular soldering strategy featuring multifunctional polyphenols in tailored polymer chains, well-designed hollow MOF structures, and defect-free interfaces. The exceptional adhesion nature of polyphenols results in dense packing and visible stiffness of PIM-1 chains with strengthened selectivity. The architecture of the hollow MOFs leads to free mass transfer and substantially improves permeability. These structural advantages act synergistically to break the permeability-selectivity trade-off limit in MMMs and surpass the conventional upper bound. This polyphenol molecular soldering method has been validated for various polymers, providing a universal pathway to prepare advanced MMMs with desirable performance for diverse applications beyond carbon capture.
Efficient GW calculations in two dimensional materials through a stochastic integration of the screened potential
Authors: Guandalini Alberto , D’Amico Pino , Ferretti Andrea , Varsano Daniele 
Published: March 2023

AbstractMany-body perturbation theory methods, such as the G0W0 approximation, are able to accurately predict quasiparticle (QP) properties of several classes of materials. However, the calculation of the QP band structure of two-dimensional (2D) semiconductors is known to require a very dense BZ sampling, due to the sharp q-dependence of the dielectric matrix in the long-wavelength limit (q → 0). In this work, we show how the convergence of the QP corrections of 2D semiconductors with respect to the BZ sampling can be drastically improved, by combining a Monte Carlo integration with an interpolation scheme able to represent the screened potential between the calculated grid points. The method has been validated by computing the band gap of three different prototype monolayer materials: a transition metal dichalcogenide (MoS2), a wide band gap insulator (hBN) and an anisotropic semiconductor (phosphorene). The proposed scheme shows that the convergence of the gap for these three materials up to 50meV is achieved by using k-point grids comparable to those needed by DFT calculations, while keeping the grid uniform.
Top-down control of human motor thalamic neuronal activity during the auditory oddball task
Authors: Alanazi Frhan I. , Kalia Suneil K. , Hodaie Mojgan , Lopez Rios Adriana L. , Lozano Andrés M. , Milosevic Luka , Hutchison William D. 
Published: March 2023

AbstractThe neurophysiology of selective attention in visual and auditory systems has been studied in animal models but not with single unit recordings in human. Here, we recorded neuronal activity in the ventral intermediate nucleus as well as the ventral oral anterior, and posterior nuclei of the motor thalamus in 25 patients with parkinsonian (n = 6) and non-parkinsonian tremors (n = 19) prior to insertion of deep brain stimulation electrodes while they performed an auditory oddball task. In this task, patients were requested to attend and count the randomly occurring odd or “deviant” tones, ignore the frequent standard tones and report the number of deviant tones at trial completion. The neuronal firing rate decreased compared to baseline during the oddball task. Inhibition was specific to auditory attention as incorrect counting or wrist flicking to the deviant tones did not produce such inhibition. Local field potential analysis showed beta (13–35 Hz) desynchronization in response to deviant tones. Parkinson’s disease patients off medications had more beta power than the essential tremor group but less neuronal modulation of beta power to the attended tones, suggesting that dopamine modulates thalamic beta oscillations for selective attention. The current study demonstrated that ascending information to the motor thalamus can be suppressed during auditory attending tasks, providing indirect evidence for the searchlight hypothesis in humans. These results taken together implicate the ventral intermediate nucleus in non-motor cognitive functions, which has implications for the brain circuitry for attention and the pathophysiology of Parkinson’s disease.
Protection from SARS-CoV-2 Variants by MVAs expressing matched or mismatched S administered intranasally to mice
Authors: Cotter Catherine A. , Americo Jeffrey L. , Earl Patricia L. , Moss Bernard 
Published: March 2023

AbstractSARS-CoV-2 vaccines prevent severe disease but are less efficient in averting infection and transmission of variant strains, making it imperative to explore ways of enhancing protection. Use of inbred mice expressing the human SARS-CoV-2 receptor facilitates such investigations. We employed recombinant MVAs (rMVAs) expressing modified S of several SARS-CoV-2 strains and compared their ability to neutralize variants, bind S proteins and protect K18-hACE2 mice against SARS-CoV-2 challenge when administered intramuscularly or intranasally. The rMVAs expressing Wuhan, Beta and Delta S induced substantial cross neutralizing activities to each other but very low neutralization of Omicron; while rMVA expressing Omicon S induced neutralizing antibody predominanly to Omicron. In mice primed and boosted with rMVA expressing the Wuhan S, neutralizing antibodies to Wuhan increased after one immunization with rMVA expressing Omicron S due to original antigenic sin, but substantial neutralizing antibody to Omicron required a second immunization. Nevertheless, monovalent vaccines with S mismatched to the challenge virus still protected against severe disease and reduced the amounts of virus and subgenomic RNAs in the lungs and nasal turbinates, though not as well as vaccines with matched S. Passive transfer of Wuhan immune serum with Omicron S binding but undetectable neutralizing activity reduced infection of the l–ungs by Omicron suggesting additional effector functions. Notably, there was less infectious virus and viral subgenomic RNAs in the nasal turbinates and lungs when the rMVAs were administered intranasally rather than intramuscularly and this held true for vaccines that were matched or mismatched to the challenge strain of SARS-CoV-2.
An integrated single-cell transcriptomic dataset for non-small cell lung cancer
Authors: Prazanowska Karolina Hanna , Lim Su Bin 
Published: March 2023

AbstractAs single-cell RNA sequencing (scRNA-seq) has emerged as a great tool for studying cellular heterogeneity within the past decade, the number of available scRNA-seq datasets also rapidly increased. However, reuse of such data is often problematic due to a small cohort size, limited cell types, and insufficient information on cell type classification. Here, we present a large integrated scRNA-seq dataset containing 224,611 cells from human primary non-small cell lung cancer (NSCLC) tumors. Using publicly available resources, we pre-processed and integrated seven independent scRNA-seq datasets using an anchor-based approach, with five datasets utilized as reference and the remaining two, as validation. We created two levels of annotation based on cell type-specific markers conserved across the datasets. To demonstrate usability of the integrated dataset, we created annotation predictions for the two validation datasets using our integrated reference. Additionally, we conducted a trajectory analysis on subsets of T cells and lung cancer cells. This integrated data may serve as a resource for studying NSCLC transcriptome at the single cell level.
COVID-19 epidemic peaks distribution in the United-States of America, from epidemiological modeling to public health policies
Authors: Vallée Alexandre , Faranda Davide , Arutkin Maxence 
Published: March 2023

AbstractCOVID-19 prediction models are characterized by uncertainties due to fluctuating parameters, such as changes in infection or recovery rates. While deterministic models often predict epidemic peaks too early, incorporating these fluctuations into the SIR model can provide a more accurate representation of peak timing. Predicting R0, the basic reproduction number, remains a major challenge with significant implications for government policy and strategy. In this study, we propose a tool for policy makers to show the effects of possible fluctuations in policy strategies on different R0 levels. Results show that epidemic peaks in the United States occur at varying dates, up to 50, 87, and 82 days from the beginning of the second, third, and fourth waves. Our findings suggest that inaccurate predictions and public health policies may result from underestimating fluctuations in infection or recovery rates. Therefore, incorporating fluctuations into SIR models should be considered when predicting epidemic peak times to inform appropriate public health responses.
Comparative genome and phylogenetic analysis revealed the complex mitochondrial genome and phylogenetic position of Conopomorpha sinensis Bradley
Authors: Chang Hong , Guo Jianglong , Li Mingzhi , Gao Yan , Wang Siwei , Wang Xiaonan , Liu Yanping 
Published: March 2023

AbstractConopomorpha sinensis Bradley is a destructive pest that causes severe economic damage to litchi and longan. Previous C. sinensis research has focused on population life tables, oviposition selectivity, pest population prediction, and control technology. However, there are few studies on its mitogenome and phylogenetic evolution. In this study, we sequenced the whole mitogenome of C. sinensis by the third-generation sequencing, and analyzed the characteristics of its mitogenome by comparative genome. The complete mitogenome of C. sinensis is a typical circular and double-stranded structure. The ENC-plot analyses revealed that natural selection could affect the information of codon bias of the protein-coding genes in the mitogenome of C. sinensis in the evolutionary process. Compared with 12 other Tineoidea species, the trnA-trnF gene cluster of tRNA in the C. sinensis mitogenome appears to have a new arrangement pattern. This new arrangement has not been found in other Tineoidea or other Lepidoptera, which needs further exploration. Meanwhile, a long AT repeated sequence was inserted between trnR and trnA, trnE and trnF, ND1 and trnS in the mitogenome of C. sinensis, and the reason for this sequence remains to be further studied. Furthermore, the results of phylogenetic analysis showed that the litchi fruit borer belonged to Gracillariidae, and Gracillariidae was monophyletic. The results will contribute to an improved understanding of the complex mitogenome and phylogeny of C. sinensis. It also will provide a molecular basis for further research on the genetic diversity and population differentiation of C. sinensis.
Predicting and understanding human action decisions during skillful joint-action using supervised machine learning and explainable-AI
Authors: Auletta Fabrizia , Kallen Rachel W. , di Bernardo Mario , Richardson Michael J. 
Published: March 2023

AbstractThis study investigated the utility of supervised machine learning (SML) and explainable artificial intelligence (AI) techniques for modeling and understanding human decision-making during multiagent task performance. Long short-term memory (LSTM) networks were trained to predict the target selection decisions of expert and novice players completing a multiagent herding task. The results revealed that the trained LSTM models could not only accurately predict the target selection decisions of expert and novice players but that these predictions could be made at timescales that preceded a player’s conscious intent. Importantly, the models were also expertise specific, in that models trained to predict the target selection decisions of experts could not accurately predict the target selection decisions of novices (and vice versa). To understand what differentiated expert and novice target selection decisions, we employed the explainable-AI technique, SHapley Additive explanation (SHAP), to identify what informational features (variables) most influenced modelpredictions. The SHAP analysis revealed that experts were more reliant on information about target direction of heading and the location of coherders (i.e., other players) compared to novices. The implications and assumptions underlying the use of SML and explainable-AI techniques for investigating and understanding human decision-making are discussed.
Artificial homeostatic temperature regulation via bio-inspired feedback mechanisms
Authors: Feketa Petro , Birkoben Tom , Noll Maximiliane , Schaum Alexander , Meurer Thomas , Kohlstedt Hermann 
Published: March 2023

AbstractHomeostasis comprises one of the main features of living organisms that enables their robust functioning by adapting to environmental changes. In particular, thermoregulation, as an instance of homeostatic behavior, allows mammals to maintain stable internal temperature with tightly controlled self-regulation independent of external temperatures. This is made by a proper reaction of the thermoeffectors (like skin blood vessels, brown adipose tissue (BAT), etc.) on a wide range of temperature perturbations that reflect themselves in the thermosensitive neurons’ activity. This activity is being delivered to the respective actuation points and translated into thermoeffectors’ actions, which bring the temperature of the organism to the desired level, called a set-point. However, it is still an open question whether these mechanisms can be implemented in an analog electronic device: both on a system theoretical and a hardware level. In this paper, we transfer this control loop into a real electric circuit by designing an analog electronic device for temperature regulation that works following bio-inspired principles. In particular, we construct a simplified single-effector regulation system and show how spiking trains of thermosensitive artificial neurons can be processed to realize an efficient feedback mechanism for the stabilization of the a priori unknown but system-inherent set-point. We also demonstrate that particular values of the set-point and its stability properties result from the interplay between the feedback control gain and activity patterns of thermosensitive artificial neurons, for which, on the one hand, the neuronal interconnections are generally not necessary. On the other hand, we show that such connections can be beneficial for the set-point regulation and hypothesize that the synaptic plasticity in real thermosensitive neuronal ensembles can play a role of an additional control layer empowering the robustness of thermoregulation. The electronic realization of temperature regulation proposed in this paper might be of interest for neuromorphic circuits which are bioinspired by taking the basal principle of homeostasis on board. In this way, a fundamental building block of life would be transferred to electronics and become a milestone for the future of neuromorphic engineering.
Deletion of QDR genes in a bioethanol-producing yeast strain reduces propagation of contaminating lactic acid bacteria
Authors: Kapetanakis George C. , Sousa Luis Santos , Felten Charlotte , Mues Loïc , Gabant Philippe , Van Nedervelde Laurence , Georis Isabelle , André Bruno 
Published: March 2023

AbstractBacterial contaminations in yeast fermentation tanks are a recurring problem for the bioethanol production industry. Lactic acid bacteria (LAB), particularly of the genus Lactobacillus, are the most common contaminants. Their proliferation can reduce fermentation efficiency or even impose premature shutdown for cleaning. We have previously reported that laboratory yeast strains naturally excrete amino acids via transporters of the Drug: H+ Antiporter-1 (DHA1) family. This excretion allows yeast to cross-feed LAB, which are most often unable to grow without an external amino acid supply. Whether industrial yeast strains used in bioethanol production likewise promote LAB proliferation through cross-feeding has not been investigated. In this study, we first show that the yeast strain Ethanol Red used in ethanol production supports growth of Lactobacillus fermentum in an amino-acid-free synthetic medium. This effect was markedly reduced upon homozygous deletion of the QDR3 gene encoding a DHA1-family amino acid exporter. We further show that cultivation of Ethanol Red in a nonsterile sugarcane-molasses-based medium is associated with an increase in lactic acid due to LAB growth. When Ethanol Red lacked the QDR1, QDR2, and QDR3 genes, this lactic acid production was not observed and ethanol production was not significantly reduced. Our results indicate that Ethanol Red cultivated in synthetic or molasses medium sustains LAB proliferation in a manner that depends on its ability to excrete amino acids via Qdr transporters. They further suggest that using mutant industrial yeast derivatives lacking DHA1-family amino acid exporters may be a way to reduce the risk of bacterial contaminations during fermentation.
Tunable deterministic lateral displacement of particles flowing through thermo-responsive hydrogel micropillar arrays
Authors: Tottori Naotomo , Nisisako Takasi 
Published: March 2023

AbstractDeterministic lateral displacement (DLD) is a promising technology that allows for the continuous and the size-based separation of suspended particles at a high resolution through periodically arrayed micropillars. In conventional DLD, the critical diameter (Dc), which determines the migration mode of a particle of a particular size, is fixed by the device geometry. Here, we propose a novel DLD that uses the pillars of a thermo-responsive hydrogel, poly(N-isopropylacrylamide) (PNIPAM) to flexibly tune the Dc value. Upon heating and cooling, the PNIPAM pillars in the aqueous solution shrink and swell because of their hydrophobic-hydrophilic phase transitions as the temperature varies. Using the PNIPAM pillars confined in a poly(dimethylsiloxane) microchannel, we demonstrate continuous switching of particle (7-μm beads) trajectories (displacement or zigzag mode) by adjusting the Dc through temperature control of the device on a Peltier element. Further, we perform on/off operation of the particle separation (7-μm and 2-μm beads) by adjusting the Dc values.
Arctic-associated increased fluctuations of midlatitude winter temperature in the 1.5° and 2.0° warmer world
Authors: Hong Yungi , Wang S.-Y. Simon , Son Seok-Woo , Jeong Jee-Hoon , Kim Sang-Woo , Kim Baekmin , Kim Hyungjun , Yoon Jin-Ho 
Published: March 2023

AbstractIn recent decades, the interior regions of Eurasia and North America have experienced several unprecedentedly cold winters despite the global surface air temperature increases. One possible explanation of these increasing extreme cold winters comes from the so-called Warm Arctic Cold Continent (WACC) pattern, reflecting the effects of the amplified Arctic warming in driving the circulation change over surrounding continents. This study analyzed reanalysis data and model experiments forced by different levels of anthropogenic forcing. It is found that WACC exists on synoptic scales in observations, model’s historical and even future runs. In the future, the analysis suggests a continued presence of WACC but with a slightly weakened cold extreme due to the overall warming. Warm Arctic events under the warmer climate will be associated with not only a colder continent in East Asia but also a warmer continent, depending on the teleconnection process that is also complicated by the warmer Arctic. Such an increasingly association suggests a reduction in potential predictability of the midlatitude winter anomalies.