bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aminoglycoside treatment alters hearing‐related genes and depicts behavioral defects in Drosophila
Authors: Dhar Gyanaseni , Paikra Sanjeev K. , Mishra Monalisa 
Published: February 2022

AbstractThe hearing organ of Drosophila is present within the second segment of antennae. The hearing organ of Drosophila (Johnston's organ [JO]) shares much structural, developmental, and functional similarity with the vertebrate hearing organ (Organ of Corti). JO is evolving as a potential model system to examine the hearing‐associated defects in vertebrates. In the vertebrates, aminoglycosides like gentamicin, kanamycin, and neomycin have been known to cause defects in the hearing organ. However, a complete mechanism of toxicity is not known. Taking the evolutionary conservation into account the current study aims to test various concentrations of aminoglycoside on the model organism, Drosophila melanogaster. The current study uses the oral route to check the toxicity of various aminoglycosides at different concentrations (50, 100, 150, 200, and 250 μg ml−1). In Drosophila, many foreign particles enter the body through the gut via food. The aminoglycoside treated third instar larvae show defective crawling and sound avoidance behavior. The adult flies release lower amounts of acetylcholine esterase and higher amounts of reactive oxygen species than control untreated animals, accompanied by defective climbing and aggressive behavior. All these behavioral defects are further confirmed by the altered expression level of hearing genes such as nompC, inactive, nanchung, pyrexia. All the behavioral and genetic defects are reported as a readout of aminoglycoside toxicity.
Therapists facing masks: A qualitative study of the nature of relationships between masks and relational depth
Authors: Kidd Andrew 
Published: February 2022

AbstractBackgroundCentral to this research was exploring characteristics facilitating and disinhibiting meetings at relational depth to explore underlying driving factors of change. The overall aim was to explore relationships between masks and relational depth. Viewing masks as a characteristic sought to understand further the socio‐cultural impacts of masks on client/patient care and decision‐making to meet at depth. This research demonstrates immediate social and international context due to COVID‐19.MethodsA phenomenological methodology was utilised. The primary research vehicle was an examination of primary data from semi‐structured interviews. Four therapists who had used masks within sessions (where both therapist and clients wore masks) provided data on meetings at relational depth.FindingsInterpretative phenomenological analysis revealed four themes: ‘epicentre of aetiology’, ‘loss’, ‘masked‐disinhibition’ and ‘disconnection paradox: depth through disconnection’. Findings suggest masks are a characteristic that can facilitate and inhibit meetings at depth—acknowledging common factors, including how therapists related to masks as an extended part of the client, and mutuality within disconnection to masks, not one another, was significant.ConclusionsFindings suggest the exigent presence of masks could facilitate or inhibit meetings at depth, regulated by what masks represented to therapists/clients at moments of contact. Yet, when both therapist and client appeared mutually disconnected (to masks, not each other), they found moments of relational depth within the disconnection. Masks are suggested as a characteristic that can influence meetings at depth. Opportunities for depth seemed reliant on individual capabilities to offer depth, emphasising therapists' experiential awareness of their interoceptive process.
Selective removal of Cr (VI) from hydrometallurgical effluent using modified cellulose nanocrystals (CNCs) with succinic anhydride and ethylenediaminetetraacetic acid: Isotherm, kinetics, and thermodynamic studies
Authors: Banza Musamba , Rutto Hilary 
Published: February 2022

AbstractBiological sources are renewable basic resources that may be used for several purposes, including the development of green materials for the removal of heavy metal ions. Cellulose nanocrystals (CNCs) extracted from waste papers via acid hydrolysis were modified and utilized as adsorbents to remove Cr (VI) ions from metallurgical effluent in this work. X‐ray diffraction, scanning electron microscopy, Fourier‐transform infrared spectroscopy, thermogravimetric analysis, and zeta potentiometer were used to characterize the CNCs. The CNCs treated with succinic anhydride and ethylenediaminetetraacetic acid tetrasodium salt have thin particle sizes and are porous. The carboxylate functional group is primarily engaged in the coordination and selective removal of metal ions (–COO2−) and thermal degradation of 85%, observed at temperatures between 250–380°C. On the surface of the modified CNCs, the zeta potential data showed a decrease in negative value. The results revealed that the modified CNCs had a maximum adsorption capacity of 387.25 ± 0.88 mg L−1 at pH 5, at CNCs doses of 25 and 400 mg L−1 as starting concentrations. The adsorption equilibrium period was 300 min and the temperature was 313 K. The equilibrium results fit the Langmuir isotherm model with an R2 of 0.993 and a qmax of 340 ± 0.97. The Chi‐square (X2) and Marquardt's percent standard deviation tests confirmed that the adsorption process was pseudo‐second‐order with an R2 of 0.998, and the Elovich model revealed that Cr (VI) complexed with the adsorbent's functional groups. The reaction was endothermic due to positive ΔH and spontaneous due to negative ΔG. The positive ΔS indicates that the adsorption process enhances the unpredictability of the solid/liquid interface, according to thermodynamic analysis. After acid treatment, the CNCs may be effectively reused for six cycles with an adsorption capacity of 220 ± 0.78 mg g−1.
Dancing on Ropes ‐ Enantioselective Functionalization of Preformed Four‐Membered Carbocycles
Authors: Chen Jun , Zhou Qiang , Fang Huayi , Lu Ping 
Published: February 2022

Comprehensive SummaryCyclobutane derivatives have been recognized as useful structural motifs in organic synthesis and drug design. With the revival of photochemistry, the enantioselective synthesis of cyclobutane derivatives using [2 + 2]‐cycloadditions has garnered numerous attentions. On the other hand, enantioselective functionalization of preformed four‐membered carbocycles is emerging as an important complementary approach to access chiral cyclobutane derivatives with versatile structural patterns. Herein, we summarize recent advances in this field from 2012. To avoid undesired C—C bond cleavage driven by strain‐releasing, it is crucial to choose compatible methods for enantioselective functionalization and meanwhile preserving intact four‐membered ring skeleton. Guided by calculated hydrogenation enthalpies, which are used to evaluate the strain energy of indicated C—C bond, a clear picture of the developed methodologies on functionalization of four‐membered carbocycles combining the strain energy and enhanced reactivity is presented.
Secretory protein beta‐lactoglobulin in cattle stable dust may contribute to the allergy‐protective farm effect
Authors: Pali‐Schöll Isabella , Bianchini Rodolfo , Afify Sheriene Moussa , Hofstetter Gerlinde , Winkler Simona , Ahlers Stella , Altemeier Theresa , Mayerhofer Hanna , Hufnagl Karin , Korath Anna D. J. , Pranger Christina , Widhalm Raimund , Hann Stephan , Wittek Thomas , Kasper‐Giebl Anne , Pacios Luis F. , Roth‐Walter Franziska , Vercelli Donata , von Mutius Erika , Jensen‐Jarolim Erika 
Published: February 2022

AbstractBackgroundGrowing up on a cattle farm and consuming raw cow's milk protects against asthma and allergies. We expect a cattle‐specific protein as active component in this farm effect.MethodsDust was collected from cattle and poultry stables and from mattresses of households. Urine was obtained from cattle, and ambient aerosols were sampled. Samples were analysed for BLG by SDS PAGE/immunoblot and mass spectrometry, and for association with metals by SEC‐ICP‐MS. PBMC of healthy donors were incubated with BLG +/− zinc, and proliferation and cytokines determined. BALB/c mice were pre‐treated intranasally with stable dust extract containing BLG or depleted of BLG, and subsequent allergy response after sensitization was evaluated on antibody and symptom level.ResultsA major protein in dust from cattle farms and ambient air was identified as BLG. Urine from female and male cattle is a major source of BLG. In dust samples, BLG was associated with zinc. In vitro, zinc‐BLG provoked significantly lower proliferation of CD4+ and CD8+ cells while inducing significantly higher levels of IFN‐γ and IL‐6 than the apo‐BLG devoid of zinc. In vivo, pre‐treatment of mice with dust extract containing BLG resulted in lower allergy symptom scores to BLG and unrelated Bet v 1 than pre‐treatment with extract depleted of BLG. These in vitro and in vivo effects were independent of endotoxin.ConclusionThe lipocalin BLG is found in large amounts in cattle urine, accumulates in bovine dust samples and is aerosolized around farms. Its association with zinc favorably shapes the human cellular immune response towards Th1‐cytokines in vitro. BLG together with zinc in stable dust protects mice from allergic sensitization. BLG with its associated ligands may in an innate manner contribute to the allergy‐protective farm effect.
Birkhoff Normal Form and Long Time Existence for Periodic Gravity Water Waves
Authors: Berti Massimiliano , Feola Roberto , Pusateri Fabio 
Published: February 2022

AbstractWe consider the gravity water waves system with a periodic one‐dimensional interface in infinite depth and give a rigorous proof of a conjecture of Dyachenko‐Zakharov [16] concerning the approximate integrability of these equations. More precisely, we prove a rigorous reduction of the water waves equations to its integrable Birkhoff normal form up to order 4. As a consequence, we also obtain a long‐time stability result: periodic perturbations of a flat interface that are initially of size ε remain regular and small up to times of order . This time scale is expected to be optimal. © 2022 The Authors. Communications on Pure and Applied Mathematics published by Wiley Periodicals LLC.
Masseter muscle thickness and vertical cephalometric characteristics in children with Class II malocclusion
Authors: Tentolouri Eirini , Antonarakis Gregory S. , Georgiakaki Ioanna , Kiliaridis Stavros 
Published: February 2022

AbstractBackgroundMasseter muscle thickness and its relationship with vertical craniofacial morphology have been extensively studied in adults, but data on children are lacking.ObjectiveTo examine the association between masseter muscle thickness and vertical cephalometric parameters in a group of Class II malocclusion growing children.MethodsThe current study design was retrospective and cross‐sectional, looking at a sample of 211 growing children with Class II malocclusion between the ages of 6 and 15 derived from two centers. Ultrasonographic masseter muscle thickness measurements and vertical cephalometric variables, including the gonial angle, were evaluated before any orthodontic treatment had been carried out. Multiple linear regression analysis was used to examine the association between masseter muscle thickness and vertical cephalometric measurements, including age and patient origin as independent variables in the analysis.ResultsIn the present sample, masseter muscle thickness was found to be independent of sex, but correlated with age, with older children presenting thicker masseter muscles. In the total patient sample, using multiple regression analyses, children with thicker masseter muscles had significantly smaller intermaxillary and gonial angles. No other cephalometric vertical characteristics showed associations with masseter muscle thickness.ConclusionIn growing children with Class II malocclusion, those with thicker masseter muscles are more likely to display smaller intermaxillary and gonial angles respectively.
High Performance 3D Self‐Supporting Cu−Bi Aerogels for Electrocatalytic Reduction of CO2 to Formate
Authors: Li Huaxin , Yue Xian , Che Jing , Xiao Zhou , Yu Xianbo , Sun Fenglei , Xue Chao , Xiang Junhui 
Published: February 2022

AbstractThe electrocatalytic reduction of CO2 (CO2RR) to CO, formate, methane, and other high‐value compounds is a promising technique. However, current electrocatalysts suffer from drawbacks such as few active catalytic sites, poor selectivity and low stability, etc, which restrict the practical application. Although monatomic metal catalysts have been widely reported in recent years, high performance non‐noble metal aerogels were rarely investigated for electrocatalytic CO2RR. Herein, Cu−Bi aerogels with boosted CO2RR activity were well constructed by a simple one‐step self‐assembly method. The resultant Cu1Bi2 exhibits excellent CO2RR activity with high faradaic efficiency (FE) of 96.57 % towards HCOOH at a potential of −0.9 V vs. RHE, and the FEHCOOH remains over 80.18 % in a wide potential window (−0.8 V to −1.2 V vs. RHE). It demonstrated that the enhanced CO2RR activity of Cu−Bi aerogels could be attributed to the 3D self‐supporting structure of the catalysis, synergistic effect, and low interfacial charge transfer resistance.
Feasibility analysis of machine learning applied to magnetized plasma diagnosis
Authors: Guan Qiuyu , Qu Zhenshen , Zeng Ming , Zhao Pengbo , Liu Junyu 
Published: February 2022

AbstractIn the paper, machine learning is demonstrated for the diagnostic enhancement of magnetized plasma probes. In the plasma experiment, the magnetic field greatly affects the properties of plasma and the performance of the probe, which limits the range of measurement parameters and reduces the accuracy of probe diagnostic results. Existing probe correction methods based on improved theory and mechanics cannot completely eliminate the influence of magnetic field and often introduce additional errors. In this paper, a novel machine learning method is proposed to improve magnetized plasma probe diagnostic based on existing methods and traditional probe correction theory. The pressure of the plasma, the total voltage of the circuit, and the magnetic induction intensity are used as input parameters, and the electron density obtained from the probe diagnostics are used as output parameters. The paper presents experiments to analyse the original probe results and the probe results revised by magnetic field probe theory through the machine learning algorithm and compare them with the results of theoretical simulations. The experimental results prove that the machine learning model based on revised data has better learning efficiency and prediction results, which can expand the application scope of traditional probe correction theory and predict results closer to the theoretical value.
Spectroscopic diagnostic of oscillating electric fields in edge plasmas
Authors: Hannachi Ibtissem , Stamm Roland J , Rosato Joel , Marandet Yannick 
Published: February 2022

AbstractThe changes of plasma radiative properties in the presence of oscillating electric fields can be used for a diagnostic of the electric fields in the edge plasma. We present the modelling of hydrogen line shapes emitted in edge plasmas where powerful radio frequency (RF) waves are launched. RF waves are used for plasma heating and current drive, and understanding the details of their coupling to the plasma is an important issue in tokamak physics. Our model relies on a computer simulation of the plasma microfield and retains the emitter quantum evolution by solving numerically the Schrödinger equation. We calculate Lyman and Balmer lines of hydrogen in conditions where a significant part of the central intensity is transferred to satellite components under the simultaneous effects of the oscillating field and stochastic plasma microfield.
Barcoding of live peripheral blood mononuclear cells to assess immune cell phenotypes using full spectrum flow cytometry
Authors: Junker Fabian , Camillo Teixeira Priscila 
Published: February 2022

AbstractBarcoded flow cytometry is a multiplexing technique allowing for the simultaneous acquisition of cells from different donors or experimental conditions in a high‐throughput manner. This approach allows to synchronize acquisition of samples and reduce variance introduced through the operator or technical platform. However, to date, only very few flow cytometry barcoding protocols have been developed, which often suffer from technical limitations. Here, we developed a novel barcoding protocol for a full‐spectrum flow cytometry platform. We developed a 21‐color immunophenotyping assay for up to 20 different samples analyzed simultaneously with comparable variance between repeated single‐tube acquisition and postde‐multiplexing. Barcoding offers great potential in parallelizing the analysis of complex cell populations such as peripheral blood mononuclear cells (PBMCs). Consequently, we assessed the performance of our method in situations where PBMCs were challenged with phytohaemagglutinin (PHA), a strong mitogen and broad activator of B cells and T cells, and superantigenStaphylococcusenterotoxin B (SEB) that has been reported to induce polyclonal T cell activation. PBMCs were either barcoded before pooled challenge or challenged individually pre‐barcoding. Our final workflow included pooled immunophenotyping followed by machine learning aided single‐cell data analysis and enabled us to identify robust PHA and SEB mode of action related phenotypic changes in PBMC immune cell lineages. Conclusively, we present a novel technique allowing the barcoded acquisition and analysis of PBMCs from up to 20 different donors and present a valid basis for the future development of complex immunophenotyping protocols.
Unsupervised cluster analysis and subset characterization of abnormal erythropoiesis using the bioinformatic Flow‐Self Organizing Maps algorithm
Authors: Porwit Anna , Violidaki Despoina , Axler Olof , Lacombe Francis , Ehinger Mats , Béné Marie C. 
Published: February 2022

AbstractBackgroundThe Flow‐Self Organizing Maps (FlowSOM) artificial intelligence (AI) program, available within the Bioconductor open‐source R‐project, allows for an unsupervised visualization and interpretation of multiparameter flow cytometry (MFC) data.MethodsApplied to a reference merged file from 11 normal bone marrows (BM) analyzed with an MFC panel targeting erythropoiesis, FlowSOM allowed to identify six subpopulations of erythropoietic precursors (EPs). In order to find out how this program would help in the characterization of abnormalities in erythropoiesis, MFC data from list‐mode files of 16 patients (5 with non‐clonal anemia and 11 with myelodysplastic syndrome [MDS] at diagnosis) were analyzed.ResultsUnsupervised FlowSOM analysis identified 18 additional subsets of EPs not present in the merged normal BM samples. Most of them involved subtle unexpected and previously unreported modifications in CD36 and/or CD71 antigen expression and in side scatter characteristics. Three patterns were observed in MDS patient samples: i) EPs with decreased proliferation and abnormal proliferating precursors, ii) EPs with a normal proliferating fraction and maturation defects in late precursors, and iii) EPs with a reduced erythropoietic fraction but mostly normal patterns suggesting that erythropoiesis was less affected. Additionally, analysis of sequential samples from an MDS patient under treatment showed a decrease of abnormal subsets after azacytidine treatment and near normalization after allogeneic hematopoietic stem‐cell transplantation.ConclusionUnsupervised clustering analysis of MFC data discloses subtle alterations in erythropoiesis not detectable by cytology nor FCM supervised analysis. This novel AI analytical approach sheds some new light on the pathophysiology of these conditions.
An Efficient Intra‐Cluster Data Aggregation and finding the Best Sink location in WSN using EEC‐MA‐PSOGA approach
Authors: Sreedevi Pogula , Venkateswarlu S. 
Published: February 2022

SummaryWireless sensor networks (WSNs) consist of nodes. Issues involved with the use of a sensor network are energy‐saving and the effective use of energy. Clustering in WSNs is a proven technique for energy optimization. The relationship between sensor nodes and cluster heads (CHs) has only been considered prior to cluster‐based routing protocols. However, most clustering algorithms have failed to address the routing overhead and the energy consumption rate between CH nodes and SINK. In this paper, a new framework named as EEC‐MA‐PSOGA ‐ an energy‐efficient (EE) intra‐cluster mobile agent (INC‐MA)‐based particle swarm optimization–genetic algorithm (PSO‐GA), has been presented to initiate the distance communication and place the SINK optimally in WSNs. The cluster members send the collected data towards their respective CHs for aggregation. To find the sink's best position, the PSO‐GA‐based location estimation algorithm is initiated based on the network structure. The limited capability of WSNs makes them more vulnerable to attackers. The prevention mechanism must be less complex to ensure the fair operations in the network. Here, the attack detection ability of the proposed solution has been tested against clone attack. With varied communication range, simulation time, and sensor nodes, the tests are conducted extensively on various scenarios of WSNs. When compared with the prior mechanisms, the framework provides better results and better prevention with less overhead by analyzing the experimental results such as energy consumption, network lifetime, and throughput.
Fear of fatness and desire for thinness as distinct experiences: A qualitative exploration
Authors: Rodgers Rachel F. , Fischer Laura E. , Laveway Katherine , Laws Kristen , Bui Eric 
Published: February 2022

AbstractObjectiveThe pursuit of thinness and fear of gaining weight have been found to play an important role in eating disorder symptomatology. While these dimensions have typically been considered conjointly, emerging evidence suggests they may be distinct dimensions. The aim of this study was to explore the subjective experiences of fear of fatness and drive for thinness in young women with body image concerns.MethodYoung women endorsing weight concerns (N = 29, mean age = 20.86, SD = 2.70 years) were interviewed and asked to describe an experience of fear of fat and drive for thinness, respectively.ResultsQualitative analysis was conducted and identified four themes: (1) precipitating events; (2) physiological, emotional, cognitive, and proprioceptive experiences; (3) coping strategies; and (4) sociocultural influences. While similarities emerged, the experiences of fear of fatness, and of drive for thinness also evidenced clear differences situating the former in the context of fear‐based avoidance patterns, and the latter in approach‐based reward models.DiscussionThese findings provide additional support for the usefulness of considering fear of fat and drive for thinness as distinct constructs. Further research examining the contributions of each of these constructs to eating pathology is warranted.