bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effects of taxonomy, diet, and ecology on the microbiota of riverine macroinvertebrates
Authors: Kroetsch Shawn A. , Kidd Karen A. , Monk Wendy A. , Culp Joseph M. , Compson Zacchaeus G. , Pavey Scott A. 
Published: November 2020

AbstractFreshwater macroinvertebrates play key ecological roles in riverine food webs, such as the transfer of nutrients to consumers and decomposition of organic matter. Although local habitat quality drives macroinvertebrate diversity and abundance, little is known about their microbiota. In most animals, the microbiota provides benefits, such as increasing the rate at which nutrients are metabolized, facilitating immune system development, and defending against pathogenic attack. Our objectives were to identify the bacteria within aquatic invertebrates and determine whether their composition varied with taxonomy, habitat, diet, and time of sample collection. In 2016 and 2017, we collected 264 aquatic invertebrates from the mainstem Saint John (Wolastoq) River in New Brunswick, Canada, representing 15 orders. We then amplified the V3‐V4 hypervariable region of the 16S rRNA gene within each individual, which revealed nearly 20,000 bacterial operational taxonomic units (OTUs). The microbiota across all aquatic invertebrates were dominated by Proteobacteria (69.25% of the total sequence reads), but they differed significantly in beta diversity, both among host invertebrate taxa (genus‐, family‐, and order‐levels) and temporally. In contrast to previous work, we observed no microbiota differences among functional feeding groups or traditional feeding habits, and neither water velocity nor microhabitat type structured microbiota variability. Our findings suggest that host invertebrate taxonomy was the most important factor in modulating the composition of the microbiota, likely through a combination of vertical and horizontal bacterial transmission, and evolutionary processes. This is one of the most comprehensive studies of freshwater invertebrate microbiota to date, and it underscores the need for future studies of invertebrate microbiota evolution and linkages to environmental bacteria and physico‐chemical conditions.
Numerical response of predators to large variations of grassland vole abundance and long‐term community changes
Authors: Giraudoux Patrick , Levret Aurélien , Afonso Eve , Coeurdassier Michael , Couval Geoffroy 
Published: November 2020

AbstractVoles can reach high densities with multiannual population fluctuations of large amplitude, and they are at the base of predator communities in Northern Eurasia and Northern America. This status places them at the heart of management conflicts wherein crop protection and health concerns are often raised against conservation issues. Here, a 20‐year survey describes the effects of large variations in grassland vole populations on the densities and the daily theoretical food intakes (TFI) of vole predators based on roadside counts. Our results show how the predator community responded to prey variations of large amplitude and how it reorganized with the increase in a dominant predator, here the red fox, which likely negatively impacted hare, European wildcat, and domestic cat populations. This population increase did not lead to an increase in the average number of predators present in the study area, suggesting compensations among resident species due to intraguild predation or competition. Large variations in vole predator number could be clearly attributed to the temporary increase in the populations of mobile birds of prey in response to grassland vole outbreaks. Our study provides empirical support for more timely and better focused actions in wildlife management and vole population control, and it supports an evidence‐based and constructive dialogue about management targets and options between all stakeholders of such socio‐ecosystems.
Functional connectivity with the anterior and posterior hippocampus during spatial memory
Authors: Fritch Haley A. , Spets Dylan S. , Slotnick Scott D. 
Published: November 2020

AbstractEvidence of differential connectivity and activity patterns across the long‐axis of the hippocampus has led to many hypotheses about functional specialization of the anterior and posterior hippocampus, including a hypothesis linking the anterior hippocampus to memory encoding and the posterior hippocampus to memory retrieval. The hippocampal encoding/retrieval and network (HERNET) model of memory predicts that encoding should engage the anterior hippocampus and the attention network, whereas retrieval should engage the posterior hippocampus and the default network. In a previous fMRI study that employed multivoxel pattern analysis, we found that the patterns of activity in the anterior hippocampus predicted the quadrant of spatial memory encoding. In the current fMRI study, we investigated whether the spatial memory encoding activity in the anterior hippocampus and retrieval activity in the posterior hippocampus had a higher degree of connectivity to the attention network or the default network. During the study phase, abstract shapes were presented in each quadrant of the visual field and participants were instructed to remember each shape's location while maintaining central fixation. During the test phase, the same shapes were presented in the center of the screen and participants identified the previous location of each shape. Generalized psychophysiological interaction analyses were conducted between the anatomically defined anterior and posterior hippocampus and the rest of the brain. This revealed preferential connectivity between the anterior hippocampus and regions of the attention network during encoding and between the posterior hippocampus and regions of the default network during retrieval. In addition, there were location‐specific patterns of connectivity with the anterior hippocampus and posterior hippocampus during encoding and retrieval of right visual field items. These results suggest that the anterior and posterior hippocampus interact with regions of the attention network and default network during spatial memory encoding and retrieval, respectively, and support the HERNET model of memory.
Assessment of dental residents’ professionalism through Professionalism Mini‐Evaluation Exercise (P‐MEX)
Authors: Kazemipoor Maryam , Keshmiri Fatemeh , Owlia Fatemeh , Rashidi Maybodi Fahimeh 
Published: November 2020

AbstractPurpose/objectivesThe aim of the study was to assess the professional behavior of dental residents through Professionalism Mini‐Evaluation Exercise (P‐MEX).MethodsThis was a descriptive‐analytical study. Content validity of P‐MEX form was investigated for use in the context of dentistry. A total of 24‐item version of P‐MEX consisted of doctor–patient relationship skills (n = 7), reflective skills (n = 5), time management (n = 3), and interprofessional relationship skills (n = 9) was used in the present study. Residents in different dental specialties (n = 56) were evaluated by trained raters (448 times). Data were analyzed by descriptive (mean, SD) and analytical tests (Pearson, ANOVA, and post hoc test (Bonferroni)).ResultsValidity of P‐MEX was approved in the field of dentistry. The mean score of professional behavior in residents were reported 2.79 ± 0.24, with minimum and maximum scores of 2.17 and 3.62, respectively. The residents' professional behavior in the domain of reflective skills and doctor–patient relationship skills were lower than the other domains.Conclusion(s)The results showed that the scores of professional behavior among dental residents were classified in the below expectation level and their scores have followed a downward trend from the second year. Therefore, planning for training and continuous assessment of professional behavior among residents in the faculty of dentistry should be considered.
Monocytes differentiated into macrophages and dendritic cells in the presence of human IFN-λ3 or IFN-λ4 show distinct phenotypes
Authors: De Manjarika , Bhushan Anand , Chinnaswamy Sreedhar 
Published: November 2020

AbstractHuman IFN-λ4 is expressed by only a subset of individuals who possess the ΔG variant allele at the dinucleotide polymorphism rs368234815. Recent genetic studies have shown an association between rs368234815 and different infectious and inflammatory disorders. It is not known if IFN-λ4 has immunomodulatory activity. The expression of another type III IFN, IFN-λ3, is also controlled by genetic polymorphisms that are strongly linked to rs368234815. Therefore, it is of interest to compare these two IFNs for their effects on immune cells. Herein, using THP-1 cells, it was confirmed that IFN-λ4 could affect the differentiation status of macrophage-like cells and dendritic cells (DCs). The global gene expression changes induced by IFN-λ4 were also characterized in in vitro generated primary macrophages. Next, human PBMC-derived CD14+ monocytes were used to obtain M1 and M2 macrophages and DCs in the presence of IFN-λ3 or IFN-λ4. These DCs were cocultured with CD4+ Th cells derived from allogenic donors and their in vitro cytokine responses were measured. The specific activity of recombinant IFN-λ4 was much lower than that of IFN-λ3, as shown by induction of IFN-stimulated genes. M1 macrophages differentiated in the presence of IFN-λ4 showed higher IL-10 secretion than those differentiated in IFN-λ3. Coculture experiments suggested that IFN-λ4 could confer a Th2-biased phenotype to allogenic Th cells, wherein IFN-λ3, under similar circumstances, did not induce a significant bias toward either a Th1 or Th2 phenotype. This study shows for the first time that IFN-λ4 may influence immune responses by immunomodulation.
Tuning the Mechanical Properties of Poly(Methyl Acrylate) via Surface‐Functionalized Montmorillonite Nanosheets
Authors: Rauschendorfer Judith Elisabeth , Thien Katharina Maria , Denz Manuela , Köster Sarah , Ehlers Florian , Vana Philipp 
Published: November 2020

AbstractPolymer layered silicate nanocomposites (PLSNs) made of montmorillonite (MMT) nanosheets and poly(methyl acrylate) (PMA) are synthesized and systematically characterized. MMT is first modified with a surface‐bound monomer and then functionalized with PMA via radical addition–fragmentation chain transfer (RAFT) polymerization using a grafting through approach. PMA‐modified MMT nanosheets with grafted polymer chains of variable length are obtained. The successful surface modification is demonstrated by near‐field scanning optical microscopy, thermogravimetric analysis, attenuated total reflection Fourier transform infrared spectroscopy, small‐angle X‐ray scattering, and size‐exclusion chromatography. The mechanical properties of various nanocomposites are evaluated via tensile testing. It can be shown that the mechanical properties (Young's modulus, tensile strength, toughness, and ductility) of these PLSNs can be fully controlled by using two major strategies, i.e., by the variation of the overall content of polymer‐modified MMT and by the variation of the chain length of the surface‐grafted polymer.
A numerical approach of tumor‐immune model with B cells and monoclonal antibody drug by multi‐step differential transformation method
Authors: Dhar Biplab , Gupta Praveen Kumar 
Published: November 2020

Monoclonal antibody (mAb) drugs are used to kill malignant tumors by making them able to see into the immune system. In this article, we developed a mathematical model with the help of tumor‐immune system with antibodies effect and efficacy of mAb drug. We defined the existence of solutions of the model, and by the Lyapunov method, we showed that the solutions are bounded; thereafter, we illustrated the local and global stability phenomenon, which is described by the Lyapunov method and localization of compact invariant sets (LCIS) method for disease‐free equilibrium points including the biological significance. In actual fact, this model suggested some ideas about the malignant tumors reciprocate to mAb drug dosage and its efficacy, eventually to overcome malignancy. It is likely to control the steadiness of the tumor, which is very important for any kind of treatment. The numerical calculations for the proposed model have been carried out by multi‐step differential transformation method (Ms‐DTM). The simulation of the model is depicted through Figures 1–5, which shows the effect of interaction rate of tumor cells and antibodies and dose of the drug for various values of efficacy.
Efficacy of transcutaneous posterior tibial nerve stimulation in children with functional voiding disorders
Authors: Jafarov Ruslan , Ceyhan Erman , Kahraman Oguzhan , Ceylan Taner , Dikmen Zeliha G. , Tekgul Serdar , Dogan Hasan S. 
Published: November 2020

AbstractAimsTo assess the efficacy of transcutaneous posterior tibial nerve stimulation (TPTNS) on functional voiding disorder (FVD) and investigate the utility of urine biomarkers (UBs: nerve growth factor, transforming growth factor‐beta 1, and tissue inhibitor of metalloproteinases 2) in diagnosis and follow‐up.MethodsA total of 44 children were included to this randomized controlled trial prospectively. After randomization, 20 of 30 children with storage phase dysfunction those were unresponsive or noncompliant to medical treatment received TPTNS treatment (test group) and 10 children underwent TPTNS with no current (sham group) for 12 weeks. Fourteen healthy children constituted the nonsymptomatic group. UB levels, dysfunctional voiding and incontinence scoring system (DVISS), voiding diary, and quality of life (QoL) scores were assessed before and after treatment in the treatment groups.ResultsQoL scores, overall and day‐time DVISS scores were significantly decreased in both sham and test groups (p < 0.05). In addition to these findings, the frequency of incontinence and urgency episodes were also significantly reduced (p < 0.05) in the TPTNS treatment group. This effect in the test group was still valid 2 years after intervention. There was no significant difference in UBs measurements between treatment and nonsymptomatic groups and between pretreatment and posttreatment measurements of test and sham groups.ConclusionsTPTNS is an efficient minimally invasive treatment in children with FVD who do not respond to medical treatment. TPTNS provides a significant improvement on episodes of frequency, episodes of incontinence, overall and day‐time DVISS scores, and QoL scores. The effectiveness of treatment continues even at the end of the second year of intervention. UBs were not found to be predictive in terms of diagnosis and evaluating the treatment response.
Pattern recognition algorithm to identify detrusor overactivity on urodynamics
Authors: Wang Hsin‐Hsiao Scott , Cahill Dylan , Panagides John , Nelson Caleb P. , Wu Hau‐Tieng , Estrada Carlos 
Published: November 2020

AbstractAimsDetrusor overactivity (DO) of the bladder is a finding on urodynamic studies (UDS) that often correlates with lower urinary tract symptoms and drives management. However, UDS interpretation remains nonstandardized. We sought to develop a mathematical model to reliably identify DO in UDS.MethodsWe utilized UDS archive files for studies performed at our institution between 2013 and 2019. Raw tracings of vesical pressure, abdominal pressure, detrusor pressure, infused volume, and all annotations during UDS were obtained. Patients less than 1 year old, studies with calibration issues, or those with significant artifacts were excluded.In the training set, five representative DO patterns were identified. Candidate Pdet signal segments were matched to representative DO patterns. Manifold learning and dynamic time warping algorithms were used. Five‐fold cross validation (CV) was used to evaluate the performance.ResultsA total of 799 UDS studies were included. The median age was 9 years (range, 1–33). There were 1,742 DO events that did not overlap with annotated artifacts (cough, cry, valsalva, movements). The AUC of the training sets from the five‐fold CV was 0.84 ± 0.01. The five‐fold CV leads to an overall accuracy 81.35%, and sensitivity and specificity of detecting DO events are 76.92% and 81.41%, respectively, in the testing set.ConclusionsOur predictive model using machine learning algorithms provides promising performance to facilitate automated identification of DO in UDS. This would allow for standardization and potentially more reliable UDS interpretation. Signal processing and machine learning interpretation of the other components of UDS are forthcoming.
Robust linearly constrained extended Kalman filter for mismatched nonlinear systems
Authors: Hrustic Emir , Ben Abdallah Rayen , Vilà‐Valls Jordi , Vivet Damien , Pagès Gaël , Chaumette Eric 
Published: November 2020

SummaryStandard state estimation techniques, ranging from the linear Kalman filter (KF) to nonlinear extended KF (EKF), sigma‐point or particle filters, assume a perfectly known system model, that is, process and measurement functions and system noise statistics (both the distribution and its parameters). This is a strong assumption which may not hold in practice, reason why several approaches have been proposed for robust filtering, mainly because the filter performance is particularly sensitive to different model mismatches. In the context of linear filtering, a solution to cope with possible system matrices mismatch is to use linear constraints. In this contribution we further explore the extension and use of recent results on linearly constrained KF for robust nonlinear filtering under both process and measurement model mismatch. We first investigate how linear equality constraints can be incorporated within the EKF and derive a new linearly constrained extended KF (LCEKF). Then we detail its use to mitigate parametric modeling errors in the nonlinear process and measurement functions. Numerical results are provided to show the performance improvement of the new LCEKF for robust vehicle navigation.
Learning network event sequences using long short‐term memory and second‐order statistic loss
Authors: Sha Hao , Al Hasan Mohammad , Mohler George 
Published: November 2020

AbstractModeling temporal event sequences on the vertices of a network is an important problem with widespread applications; examples include modeling influences in social networks, preventing crimes by modeling their space–time occurrences, and forecasting earthquakes. Existing solutions for this problem use a parametric approach, whose applicability is limited to event sequences following some well‐known distributions, which is not true for many real life event datasets. To overcome this limitation, in this work, we propose a composite recurrent neural network model for learning events occurring in the vertices of a network over time. Our proposed model combines two long short‐term memory units to capture base intensity and conditional intensity of an event sequence. We also introduce a second‐order statistic loss that penalizes higher divergence between the generated and the target sequence's distribution of hop count distance of consecutive events. Given a sequence of vertices of a network in which an event has occurred, the proposed model predicts the vertex where the next event would most likely occur. Experimental results on synthetic and real‐world datasets validate the superiority of our proposed model in comparison to various baseline methods.
Enantiomeric N‐tert‐Butylsulfinyl Imines of Methyl Trifluoropyruvate: Promising Building Blocks in Asymmetric Synthesis of α‐Trifluoromethylated Amino Acids and Derivatives
Authors: Cherednichenko Alona S. , Bezgubenko Ludmyla V. , Rusanov Eduard B. , Onys'ko Petro P. , Rassukana Yuliya V. 
Published: November 2020

AbstractA convenient synthetic method for (R)‐ and (S)‐N‐tert‐butylsulfinyl imines of methyl trifluoropyruvate has been developed. The synthetic potentialities of these chiral building blocks for the preparation of nonracemic trifluoroalanines, trifluoromethylated amino alcohols, β‐nitro‐α‐amino acids, and pyrrolinone carboxylic acid derivatives have been demonstrated.
KSnI3 ⋅ H2O: A New Compound with One‐Dimensional SnI3 Chains of Pyramidal SnI5 Polyhedra
Authors: Li Kuan , Feng Junwei , Su Zhi 
Published: November 2020

AbstractA new compound KSnI3⋅H2O was synthesized through the solid‐state reaction method in a sealed quartz tube. The Sn (II) cations are five‐coordinated with I− ions forming the special pyramidal SnI5 polyhedra which further condense to one‐dimensional SnI3 chains connected by K−I bonds and O−H⋅⋅⋅I hydrogen bonds. Meanwhile, the first principles calculations were also carried out to aid the understanding of optical properties and electronic structure. The electronic localization functions (ELF) prove the stereochemical activity of the Sn (II) lone pair and the electronic structure analysis has been carried out to understand the optical properties deeply. The calculated birefringence of the title compound is 0.121 at 1064 nm which is mainly originated from the contribution of the SnI5 polyhedra.
A Fluorescent Turn‐on Probe Based on Zn‐doped AgIn5S8 Quantum Dots for Imaging of Hydrogen Sulfide in Living Cells
Authors: Dong Yanyu , Sun Wenping , Chang Shiqi , Li Tong , Huang Xiaohua , Xing Shanghua , Bai Tianyu , Ma Huipeng 
Published: November 2020

AbstractH2S has been identified as endogenously generated gasotransmitter in mammalian which acts essential role in various physiological and pathological processes. In this work, we reported the use of hydrophilic, low‐toxic and photostable Zn‐doped AgIn5S8 quantum dots (ZAIS QDs) in H2S detection. Copper ions, acting as recognition moieties, are conjugated on the surface of ZAIS QD to construct the fluorescent probe. The weak fluorescence signal of the probe owing to the quenching effect of paramagnetic Cu2+ center on ZAIS QDs can exhibit significant fluorescence turn‐on property upon the addition of H2S. Simultaneously, the probe possesses high sensitivity at physiological pH, excellent membrane permeability and dose‐dependent fluorescence imaging of exogenous H2S in living cells.
Design, Synthesis and Biological Evaluation of Stilbene Derivatives Containing a 1,3‐Benzodioxole Moiety
Authors: Song Di , Cao Xiufang , Huang Wenbo , Ke Shaoyong 
Published: November 2020

AbstractStilbene is an important class of biologically active metabolites with diarylethene scaffold, and which have a broad range of biological activities as the lead for drug discovery. In this study, a novel series of stilbene derivatives bearing 1,3‐benzodioxole moiety was designed and synthesized via a convenient method with good to excellent yields, and their structures were characterized by 1H NMR, 13C NMR, ESI‐MS spectrum. These newly prepared compounds were evaluated for their potential biological activities including fungicidal, insecticidal, and cytotoxic activities.