bluuebunny/crossref_metadata_2025_split huggingface dataset:
Eutrophication drives regime shift via changes in stoichiometric homeostasis-based submerged macrophyte assemblages
Authors: Zhang Chengxiang , Pei Hongcui , Lu Cai , Liu Peizhong , Liu Cunqi , Lei Guangchun 
Published: May 2022

AbstractHomeostasis for phosphorus (HP) in submerged macrophytes may influence the susceptibility of lakes to regime shifts; however, the mechanisms linking submerged macrophyte HP to regime shifts remain unclear. We conducted an in situ mesocosm experiment to compare the dynamic responses of a high-HP species, Potamogeton maackianus, and a low-HP species, Hydrilla verticillata, to different phosphorus (P) level gradients, as well as their effects on phytoplankton inhibition. The biomass of P. maackianus under mesotrophic P (MP; P concentration 0.05 mg L−1) and eutrophic P (EP; P concentration 0.10 mg L−1) conditions was either non-significantly different from, or lower than that under oligotrophic P conditions (OP; P concentration under detection limit of 0.01 mg L−1). Conversely, H. verticillata biomass under EP was significantly higher than that under MP on day 90, whereas it died under OP. This variable response of submerged macrophyte species to P level gradients increased the relative growth advantage of H. verticillata compared to P. maackianus during eutrophication. The inhibition ratio of phytoplankton (IRP) for P. maackianus was ~15 times higher than that for H. verticillata under EP. Our study demonstrated a trend that submerged macrophyte assemblage IRP increased along with its assemblage HP. Thus, the changes in submerged macrophyte assemblages from high-HP species-dominance to low-HP species-dominance would erode its phytoplankton inhibition capacity, and further promote the regime shift from a clear-water state to a turbid state. Our results advance the regime shift theory from an ecological stoichiometry perspective and highlight the importance of high-HP submerged macrophyte species in the restoration of eutrophic lakes.
Thermal neutron beam optimization for PGNAA applications using Q-learning algorithm and neural network
Authors: Zolfaghari Mona , Masoudi S. Farhad , Rahmani Faezeh , Fathi Atefeh 
Published: May 2022

AbstractAs a powerful, non-destructive analysis tool based on thermal neutron capture reaction, prompt gamma neutron activation analysis (PGNAA) indeed requires the appropriate neutron source. Neutrons produced by electron Linac-based neutron sources should be thermalized to be appropriate for PGNAA. As a result, thermalization devices (TDs) are used for the usual fast neutron beam to simultaneously maximize the thermal neutron flux and minimize the non- thermal neutron flux at the beam port of TD. To achieve the desired thermal neutron flux, the optimized geometry of TD including the proper materials for moderators and collimator, as well as the optimized dimensions are required. In this context, TD optimization using only Monte Carlo approaches such as MCNP is a multi-parameter problem and time-consuming task. In this work, multilayer perceptron (MLP) neural network has been applied in combination with Q-learning algorithm to optimize the geometry of TD containing collimator and two moderators. Using MLP, both thickness and diameter of the collimator at the beam port of TD have first been optimized for different input electron energies of Linac as well as for moderators’ thickness values and the collimator. Then, the MLP has been learned by the thermal and non-thermal neutron flux simultaneously at the beam port of TD calculated by MCNPX2.6 code. After selecting the optimized geometry of the collimator, a combination of Q-learning algorithm and MLP artificial neural network have been used to find the optimal moderators’ thickness for different input electron energies of Linac. Results verify that the final optimum setup can be obtained based on the prepared dataset in a considerably smaller number of simulations compared to conventional calculation methods as implemented in MCNP.
Active Brownian motion of strongly coupled charged grains driven by laser radiation in plasma
Authors: Petrov Oleg F. , Statsenko Konstantin B. , Vasiliev Mikhail M. 
Published: May 2022

AbstractThe systems of active Brownian grains can be considered as open systems, in which there is an exchange of energy and matter with the environment. The collective phenomena of active Brownian grains can demonstrate analogies with ordinary phase transitions. We study the active Brownian motion of light-absorbing and strongly interacting grains far from equilibrium suspended in gas discharge under laser irradiation when the nature and intensity of the active motion depend on the effect of radiation. Active Brownian motion is caused by photophoresis, i.e., absorption of laser radiation at the metal-coated surface of the grain creates radiometric force, which in turn drives the grains. We experimentally observed the active Brownian motion of charged grains in the transition of the grain monolayer from the solid to liquid state. An analysis of the character of motion, including the mean-square and linear displacement and persistence length at various values of the randomization (coupling parameter) of the grain structure, was presented.
Expression and function of the luteinizing hormone choriogonadotropin receptor in human endometrial stromal cells
Authors: Mann O. N. , Kong C.-S. , Lucas E. S. , Brosens J. J. , Hanyaloglu A. C. , Brighton P. J. 
Published: May 2022

AbstractThe human luteinising hormone choriogonadotropin receptor (LHCGR) is a G-protein coupled receptor activated by both human chorionic gonadotropin (hCG) and luteinizing hormone (LH), two structurally related gonadotropins with essential roles in ovulation and maintenance of the corpus luteum. LHCGR expression predominates in ovarian tissues where it elicits functional responses through cyclic adenosine mononucleotide (cAMP), Ca2+ and extracellular signal-regulated kinase (ERK) signalling. LHCGR expression has also been localized to the human endometrium, with purported roles in decidualization and implantation. However, these observations are contentious. In this investigation, transcripts encoding LHCGR were undetectable in bulk RNA sequencing datasets from whole cycling endometrial tissue and cultured human endometrial stromal cells (EnSC). However, analysis of single-cell RNA sequencing data revealed cell-to-cell transcriptional heterogeneity, and we identified a small subpopulation of stromal cells with detectable LHCGR transcripts. In HEK-293 cells expressing recombinant LHCGR, both hCG and LH elicited robust cAMP, Ca2+ and ERK signals that were absent in wild-type HEK-293 cells. However, none of these responses were recapitulated in primary EnSC cultures. In addition, proliferation, viability and decidual transformation of EnSC were refractory to both hCG and LH, irrespective of treatment to induce differentiation. Although we challenge the assertion that LHCGR is expressed at a functionally active level in the human endometrium, the discovery of a discrete subpopulation of EnSC that express LHCGR transcripts may plausibly account for the conflicting evidence in the literature.
Aerosol emission from playing wind instruments and related COVID-19 infection risk during music performance
Authors: Firle Carl , Steinmetz Anke , Stier Oliver , Stengel Dirk , Ekkernkamp Axel 
Published: May 2022

AbstractThe pandemic of COVID-19 led to restrictions in all kinds of music activities. Airborne transmission of SARS-CoV-2 requires risk assessment of wind instrument playing in various situations. Previous studies focused on short-range transmission, whereas long-range transmission risk has not been assessed. The latter requires knowledge of aerosol emission rates from wind instrument playing. We measured aerosol concentrations in a hermetically closed chamber of 20 m3in an operating theatre as resulting from 20 min standardized wind instrument playing (19 flute, 11 oboe, 1 clarinet, 1 trumpet players). We calculated aerosol emission rates showing uniform distribution for both instrument groups. Aerosol emission from wind instrument playing ranged from 11 ± 288 particles/second (P/s) up to 2535 ± 195 P/s, expectation value ± uncertainty standard deviation. The analysis of aerosol particle size distributions shows that 70–80% of emitted particles had a size of 0.25–0.8 µm and thus are alveolar. Masking the bell with a surgical mask did not reduce aerosol emission. Aerosol emission rates were higher from wind instrument playing than from speaking or breathing. Differences between instrumental groups could not be found but high interindividual variance, as expressed by uniform distribution of aerosol emission rates. Our findings indicate that aerosol emission depends on physiological factors and playing techniques rather than on the type of instrument, in contrast to some previous studies. Based on our results, we present transmission risk calculations for long-range transmission of COVID-19 for three typical woodwind playing situations.
Blood compatibility of widely used central venous catheters; an experimental study
Authors: Thorarinsdottir Hulda , Kander Thomas , Johansson Dorota , Nilsson Bo , Klarin Bengt , Sanchez Javier 
Published: May 2022

AbstractAn inserted central venous catheter (CVC) is considered foreign material by the inert host defence systems and induce inflammation and thrombus formation. The objective of this study was to evaluate blood compatibility of six commonly used CVCs. Three coated and three uncoated CVC materials were tested in a modified Chandler loop model. Each catheter material circulated in blood from ten different healthy volunteers for 1 h. Blood cell counts and measurements of the inert host defence systems were performed on blood samples from the loop. All the tested catheters demonstrated impact on blood cells, contact coagulation, the complement system, or inflammatory markers, although the impact varied significantly. Of the catheters we evaluated, the most unfavourable blood compatibility profile was found for the polyurethane CVC coated with chlorohexidine and silver sulfadiazine. The greatest variation in blood compatibility between test runs was noted for the silicone dialysis catheter. Poor blood compatibility should be taken seriously but given the experimental design of the current study the clinical significance remains to be evaluated.
Deep learning for blind structured illumination microscopy
Authors: Xypakis Emmanouil , Gosti Giorgio , Giordani Taira , Santagati Raffaele , Ruocco Giancarlo , Leonetti Marco 
Published: May 2022

AbstractBlind-structured illumination microscopy (blind-SIM) enhances the optical resolution without the requirement of nonlinear effects or pre-defined illumination patterns. It is thus advantageous in experimental conditions where toxicity or biological fluctuations are an issue. In this work, we introduce a custom convolutional neural network architecture for blind-SIM: BS-CNN. We show that BS-CNN outperforms other blind-SIM deconvolution algorithms providing a resolution improvement of 2.17 together with a very high Fidelity (artifacts reduction). Furthermore, BS-CNN proves to be robust in cross-database variability: it is trained on synthetically augmented open-source data and evaluated on experiments. This approach paves the way to the employment of CNN-based deconvolution in all scenarios in which a statistical model for the illumination is available while the specific realizations are unknown or noisy.
A novel early diagnostic framework for chronic diseases with class imbalance
Authors: Yuan Xiaohan , Chen Shuyu , Sun Chuan , Yuwen Lu 
Published: May 2022

AbstractChronic diseases are one of the most severe health issues in the world, due to their terrible clinical presentations such as long onset cycle, insidious symptoms, and various complications. Recently, machine learning has become a promising technique to assist the early diagnosis of chronic diseases. However, existing works ignore the problems of feature hiding and imbalanced class distribution in chronic disease datasets. In this paper, we present a universal and efficient diagnostic framework to alleviate the above two problems for diagnosing chronic diseases timely and accurately. Specifically, we first propose a network-limited polynomial neural network (NLPNN) algorithm to efficiently capturehigh-levelfeatures hidden in chronic disease datasets, which is data augmentation in terms of its feature space and can also avoid over-fitting. Then, to alleviate the class imbalance problem, we further propose an attention-empowered NLPNN algorithm to improve the diagnostic accuracy for sick cases, which is also data augmentation in terms of its sample space. We evaluate the proposed framework on nine public and two real chronic disease datasets (partly with class imbalance). Extensive experiment results demonstrate that the proposed diagnostic algorithms outperform state-of-the-art machine learning algorithms, and can achieve superior performances in terms of accuracy, recall, F1, and G_mean. The proposed framework can help to diagnose chronic diseases timely and accurately at an early stage.
Repetitive afterglow in zirconia by pulsed near-infrared irradiation toward biological temperature sensing
Authors: Ohashi Masaharu , Takahashi Yoshihiro , Terakado Nobuaki , Onoue Noriko , Shinozaki Tsuyoshi , Fujiwara Takumi 
Published: May 2022

AbstractPhotoluminescence provides information about the surrounding environment. In this study, aiming to develop a non-invasive deep body-temperature sensing method, we investigated photoluminescence properties of afterglow zirconia (ZrO2) by pulsed near-infrared (NIR) light irradiation based on the biological temperature. Pulsed light irradiation produced optically stimulated luminescence, followed by afterglow, with the property of repeating 100 times or more. Furthermore, the basic principle of temperature measurement was demonstrated through afterglow decay curve measurements. The use of harmless ZrO2 as a sensing probe and NIR light, which is relatively permeable to living tissues, is expected to realize temperature measurements in the brain and may also facilitate optogenetic treatment.
Bone marrow-derived macrophages from a murine model of Sjögren's syndrome demonstrate an aberrant, inflammatory response to apoptotic cells
Authors: Witas Richard , Shen Yiran , Nguyen Cuong Q. 
Published: May 2022

AbstractSjögren's syndrome (SjS) is a female-dominated autoimmune disease involving lymphocytic infiltration of the exocrine glands. We have previously demonstrated cleavage of the TAM (Tyro3, Axl, Mer) receptor Mer is enhanced in SjS, leading to defective efferocytosis. Mer also plays a role in modulating phagocyte inflammatory response to apoptotic cells. Here we investigated the SjS macrophage response to apoptotic cells (AC). Bone marrow-derived macrophages (BMDMs) from SjS-susceptible (SjSs) C57BL/6.NOD-Aec1Aec2 mice and C57BL/6 (B6) controls were treated with either AC or CpG-oligodeoxynucleotides. RNA was collected from macrophages and bulk sequencing was performed to analyze transcripts. Cytokine expression was confirmed by Bio-plex. RT-qPCR was used to determine toll-like receptor (TLR) 7 and 9 involvement in BMDM inflammatory response to apoptotic cells. SjSS BMDMs exhibited a distinct transcriptional profile involving upregulation of a broad array of inflammatory genes that were not elevated in B6 BMDMs by AC. Inhibition of TLR 7 and 9 was found to limit the inflammatory response of SjSS BMDMs to ACs. ACs elicit an inflammatory reaction in SjSS BMDMs distinct from that observed in B6 BMDMs. This discovery of aberrant macrophage behavior in SjS in conjunction with previously described efferocytosis defects suggests an expanded role for macrophages in SjS, where uncleared dead cells stimulate an inflammatory response through macrophage TLRs recruiting lymphocytes, participating in co-stimulation and establishing an environment conducive to autoimmunity.
Terahertz waves dynamic diffusion in 3D printed structures
Authors: Missori Mauro , Pilozzi Laura , Conti Claudio 
Published: May 2022

AbstractApplications of metamaterials in the realization of efficient devices in the terahertz band have recently been considered to achieve wave deflection, focusing, amplitude manipulation and dynamical modulation. Terahertz metamaterials offer practical advantages since their structures have typical sizes of hundreds microns and are within the reach of current three-dimensional (3D) printing technologies. Here, we propose terahertz photonic structures composed of dielectric rods layers made of acrylonitrile styrene acrylate realized by low-cost, rapid, and versatile fused deposition modeling 3D-printing. Terahertz time-domain spectroscopy is employed for the experimental study of their spectral and dynamic response. Measured spectra are interpreted by using simulations performed by an analytical exact solution of the Maxwell equations for a general incidence geometry, by a field expansion as a sum over reciprocal lattice vectors. Results show that the structures possess specific spectral forbidden bands of the incident THz radiation depending on their optical and geometrical parameters. We also find evidence of disorder in the 3D printed structure resulting in the closure of the forbidden bands at frequencies above 0.3 THz. The size disorder of the structures is quantified by studying the dynamics diffusion of THz pulses as a function of the numbers of layers of dielectric rods. Comparison with simulations of light diffusion in photonic crystals with increasing disorder allows estimating the size distributions of elements. By using a Mean Squared Displacement model, from the broadening of the pulses’ widths it is also possible to estimate the diffusion coefficient of the terahertz radiation in the photonic structures.
A generalizable one health framework for the control of zoonotic diseases
Authors: Ghai Ria R. , Wallace Ryan M. , Kile James C. , Shoemaker Trevor R. , Vieira Antonio R. , Negron Maria E. , Shadomy Sean V. , Sinclair Julie R. , Goryoka Grace W. , Salyer Stephanie J. , Barton Behravesh Casey 
Published: May 2022

AbstractEffectively preventing and controlling zoonotic diseases requires a One Health approach that involves collaboration across sectors responsible for human health, animal health (both domestic and wildlife), and the environment, as well as other partners. Here we describe the Generalizable One Health Framework (GOHF), a five-step framework that provides structure for using a One Health approach in zoonotic disease programs being implemented at the local, sub-national, national, regional, or international level. Part of the framework is a toolkit that compiles existing resources and presents them following a stepwise schematic, allowing users to identify relevant resources as they are required. Coupled with recommendations for implementing a One Health approach for zoonotic disease prevention and control in technical domains including laboratory, surveillance, preparedness and response, this framework can mobilize One Health and thereby enhance and guide capacity building to combat zoonotic disease threats at the human–animal–environment interface.
No effect of dual exposure to sulfoxaflor and a trypanosome parasite on bumblebee olfactory learning
Authors: Vaughan Owen P. , Straw Edward A. , Linguadoca Alberto , Brown Mark J. F. 
Published: May 2022

AbstractBees are important pollinators in wild and agricultural ecosystems, and understanding the factors driving their global declines is key to maintaining these pollination services. Learning, which has been a focus of previous ecotoxicological studies in bees, may play a key role in driving colony fitness. Here we move beyond the standard single-stressor approach to ask how multiple stressors, an agrochemical (sulfoxaflor, a relatively new insecticide) and a parasite (Crithidia bombi, a prevalent gut parasite of bumblebees), impact learning in the bumblebee Bombus terrestris. We developed a modified version of the classic proboscis extension reflex assay to assess the combined effects of acute oral sulfoxaflor exposure and infection by C. bombi on olfactory learning of bumblebee workers. We found no evidence that either sulfoxaflor, C. bombi, or their combination had any significant effect on bumblebee olfactory learning, despite their known negative impacts on other aspects of bumblebee health. This suggests that losses in cognitive ability, as measured here, are unlikely to explain the impacts of sulfoxaflor and its interactions with other stressors on bumblebees. Our novel methodology provides a model system within which to test interactive effects of other key stressors on bee health.
SARS-CoV-2 detection using a nanobody-functionalized voltammetric device
Authors: Pagneux Quentin , Roussel Alain , Saada Hiba , Cambillau Christian , Amigues Béatrice , Delauzun Vincent , Engelmann Ilka , Alidjinou Enagnon Kazali , Ogiez Judith , Rolland Anne Sophie , Faure Emmanuel , Poissy Julien , Duhamel Alain , Boukherroub Rabah , Devos David , Szunerits Sabine 
Published: May 2022

Abstract
Background
An ongoing need during the COVID-19 pandemic has been the requirement for accurate and efficient point-of-care testing platforms to distinguish infected from non-infected people, and to differentiate SARS-CoV-2 infections from other viruses. Electrochemical platforms can detect the virus via its envelope spike protein by recording changes in voltammetric signals between samples. However, this remains challenging due to the limited sensitivity of these sensing platforms.

Methods
Here, we report on a nanobody-functionalized electrochemical platform for the rapid detection of whole SARS-CoV-2 viral particles in complex media such as saliva and nasopharyngeal swab samples. The sensor relies on the functionalization of gold electrode surface with highly-oriented Llama nanobodies specific to the spike protein receptor binding domain (RBD). The device provides results in 10 min of exposure to 200 µL of unprocessed samples with high specificity to SARS-CoV-2 viral particles in human saliva and nasopharyngeal swab samples.

Results
The developed sensor could discriminate between different human coronavirus strains and other respiratory viruses, with 90% positive and 90% negative percentage agreement on 80 clinical samples, as compared to RT-qPCR.

Conclusions
We believe this diagnostic concept, also validated for RBD mutants and successfully tested on Delta variant samples, to be a powerful tool to detect patients’ infection status, easily extendable to other viruses and capable of overcoming sensing-related mutation effects.
Layered baud‐space modulation: Flexible SM scheme under transmit‐ and receive spatial correlation
Authors: Akuon Peter O. , Xu Hongjun 
Published: May 2022

AbstractThis paper discusses layered baud‐space modulation system under arbitrary spatial correlation both at the transmitter and the receiver. Layered baud‐space modulation provides better reliability in spatial modulation systems as well as flexibility in data rates compared to multiple‐active space modulation. Several transmissions occur asynchronously within the time slot. As a result, fractional sampling is employed at the receiver to detect the signals. For this scheme, it is more practical to analyse spatial correlation both at the transmitter and the receiver, since temporal correlation is a likely occurrence. However, asynchronous transmission will lead to higher probability of packet drops when synchronization errors are present. Lower bounds of bit error rates are derived from theoretical criteria based on mutual information and sample covariance of the joint spatial and modulation space. Analytical results for bit error probability are tightly verified from simulations. The channel is assumed to be of frequency‐flat Rayleigh fading form. The tests are carried out under different antenna spacing, amplitude and phase modulation schemes and various number of transmit and receive antenna configurations.