bluuebunny/crossref_metadata_2025_split huggingface dataset:
Correlations between autoantibodies and the ATR-FTIR spectra of sera from rheumatoid arthritis patients
Authors: Durlik-Popińska Katarzyna , Żarnowiec Paulina , Konieczna-Kwinkowska Iwona , Lechowicz Łukasz , Gawęda Józef , Kaca Wiesław 
Published: September 2021

AbstractRheumatoid arthritis (RA) is one of the most common autoimmune diseases worldwide. Due to high heterogeneity in disease manifestation, accurate and fast diagnosis of RA is difficult. This study analyzed the potential relationship between the infrared (IR) spectra obtained by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and the presence of autoantibodies and antibodies against urease in sera. Additionally, the wave number of the IR spectrum that enabled the best differentiation between patients and healthy blood donors was investigated. Using a mathematical model involving principal component analysis and discriminant analysis, it was shown that the presence of anti-citrullinated protein antibody, rheumatoid factor, anti-neutrophil cytoplasmic antibodies, and anti-nuclear antibodies correlated significantly with the wave numbers in the IR spectra of the tested sera. The most interesting findings derived from determination of the best predictors for distinguishing RA. Characteristic features included an increased reaction with urease mimicking peptides and a correspondence with particular nucleic acid bands. Taken together, the results demonstrated the potential application of ATR-FTIR in the study of RA and identified potential novel markers of the disease.
Floquet prethermalization and Rabi oscillations in optically excited Hubbard clusters
Authors: Okamoto Junichi , Peronaci Francesco 
Published: September 2021

AbstractWe study the properties of Floquet prethermal states in two-dimensional Mott-insulating Hubbard clusters under continuous optical excitation. With exact-diagonalization simulations, we show that Floquet prethermal states emerge not only off resonance, but also for resonant excitation, provided a small field amplitude. In the resonant case, the long-lived quasi-stationary Floquet states are characterized by Rabi oscillations of observables such as double occupation and kinetic energy. At stronger fields, thermalization to infinite temperature is observed. We provide explanations to these results by means of time-dependent perturbation theory. The main findings are substantiated by a finite-size analysis.
Research on improved convolutional wavelet neural network
Authors: Liu Jingwei , Li Peixuan , Tang Xuehan , Li Jiaxin , Chen Jiaming 
Published: September 2021

AbstractArtificial neural networks (ANN) which include deep learning neural networks (DNN) have problems such as the local minimal problem of Back propagation neural network (BPNN), the unstable problem of Radial basis function neural network (RBFNN) and the limited maximum precision problem of Convolutional neural network (CNN). Performance (training speed, precision, etc.) of BPNN, RBFNN and CNN are expected to be improved. Main works are as follows: Firstly, based on existing BPNN and RBFNN, Wavelet neural network (WNN) is implemented in order to get better performance for further improving CNN. WNN adopts the network structure of BPNN in order to get faster training speed. WNN adopts the wavelet function as an activation function, whose form is similar to the radial basis function of RBFNN, in order to solve the local minimum problem. Secondly, WNN-based Convolutional wavelet neural network (CWNN) method is proposed, in which the fully connected layers (FCL) of CNN is replaced by WNN. Thirdly, comparative simulations based on MNIST and CIFAR-10 datasets among the discussed methods of BPNN, RBFNN, CNN and CWNN are implemented and analyzed. Fourthly, the wavelet-based Convolutional Neural Network (WCNN) is proposed, where the wavelet transformation is adopted as the activation function in Convolutional Pool Neural Network (CPNN) of CNN. Fifthly, simulations based on CWNN are implemented and analyzed on the MNIST dataset. Effects are as follows: Firstly, WNN can solve the problems of BPNN and RBFNN and have better performance. Secondly, the proposed CWNN can reduce the mean square error and the error rate of CNN, which means CWNN has better maximum precision than CNN. Thirdly, the proposed WCNN can reduce the mean square error and the error rate of CWNN, which means WCNN has better maximum precision than CWNN.
Detecting anchored fish aggregating devices (AFADs) and estimating use patterns from vessel tracking data in small-scale fisheries
Authors: Widyatmoko Ahmad Catur , Hardesty Britta Denise , Wilcox Chris 
Published: September 2021

AbstractMonitoring the use of anchored fish aggregating devices (AFADs) is essential for effective fisheries management. However, detecting the use of these devices is a significant challenge for fisheries management in Indonesia. These devices are continually deployed at large scales, due to large numbers of users and high failure rates, increasing the difficulty of monitoring AFADs. To address this challenge, tracking devices were attached to 34 handline fishing vessels in Indonesia over a month period each. Given there are an estimated 10,000–50,000 unlicensed AFADs in operation, Indonesian fishing grounds provided an ideal case study location to evaluate whether we could apply spatial modeling approaches to detect AFAD usage and fish catch success. We performed a spatial cluster analysis on tracking data to identify fishing grounds and determine whether AFADs were in use. Interviews with fishers were undertaken to validate these findings. We detected 139 possible AFADs, of which 72 were positively classified as AFADs. Our approach enabled us to estimate AFAD use and sharing by vessels, predict catches, and infer AFAD lifetimes. Key implications from our study include the potential to estimate AFAD densities and deployment rates, and thus compliance with Indonesia regulations, based on vessel tracking data.
Neutrophil extracellular traps in patients with liver cirrhosis and hepatocellular carcinoma
Authors: Zenlander Robin , Havervall Sebastian , Magnusson Maria , Engstrand Jennie , Ågren Anna , Thålin Charlotte , Stål Per 
Published: September 2021

AbstractNeutrophil extracellular traps (NETs) are web-like structures consisting of DNA, histones and granule proteins, released from neutrophils in thrombus formation, inflammation, and cancer. We asked if plasma levels of the NET markers myeloperoxidase (MPO)-DNA and citrullinated histone H3 (H3Cit)-DNA, are elevated in liver cirrhosis and hepatocellular carcinoma (HCC) and if the levels correlate with clinical parameters. MPO-DNA, H3Cit-DNA, and thrombin–antithrombin (TAT) complex, as a marker of coagulation activity, were measured using ELISA in plasma from 82 patients with HCC, 95 patients with cirrhosis and 50 healthy controls. Correlations were made to clinical parameters and laboratory data and patients were followed for a median of 22.5 months regarding thrombosis development. H3Cit-DNA was significantly (p < 0.01) elevated in plasma from cirrhosis (66.4 ng/mL) and HCC (63.8 ng/mL) patients compared to healthy controls (31.8 ng/mL). TAT levels showed similar pattern (3.1, 3.7, and 0.0 µg/mL respectively, p < 0.01). MPO-DNA was significantly (p < 0.01) elevated in cirrhosis patients (0.53 O.D.) as compared to controls (0.33 O.D.). Levels of MPO-DNA and H3Cit-DNA correlated positively with Child–Pugh and MELD score. TAT was increased in all Child–Pugh and MELD groups. In multivariable logistic regression, Child B and C liver cirrhosis were independent predictors of elevated H3Cit-DNA in plasma. Levels of MPO-DNA and H3Cit-DNA were similar in patients with or without history of thrombosis, or thrombus formation during follow-up. In conclusion, plasma markers of NET formation are elevated in liver cirrhosis and correlate to the degree of liver dysfunction in patients with liver cirrhosis and/or HCC. The presence of HCC did not further increase the plasma levels of NET markers as compared to patients with cirrhosis only.
Well-differentiated gastroenteropancreatic G3 NET: findings from a large single centre cohort
Authors: Lithgow K. , Venkataraman H. , Hughes S. , Shah H. , Kemp-Blake J. , Vickrage S. , Smith S. , Humphries S. , Elshafie M. , Taniere P. , Diaz-Cano S. , Dasari B. V. M. , Almond M. , Ford S. , Ayuk J. , Shetty S. , Shah T. , Geh I. 
Published: September 2021

AbstractNeuroendocrine neoplasms are known to have heterogeneous biological behavior. G3 neuroendocrine tumours (NET G3) are characterized by well-differentiated morphology and Ki67 > 20%. The prognosis of this disease is understood to be intermediate between NET G2 and neuroendocrine carcinoma (NEC). Clinical management of NET G3 is challenging due to limited data to inform treatment strategies. We describe clinical characteristics, treatment, and outcomes in a large single centre cohort of patients with gastroenteropancreatic NET G3. Data was reviewed from 26 cases managed at Queen Elizabeth Hospital, Birmingham, UK, from 2012 to 2019. Most commonly the site of the primary tumour was unknown and majority of cases with identifiable primaries originated in the GI tract. Majority of cases demonstrated somatostatin receptor avidity. Median Ki67 was 30%, and most cases had stage IV disease at diagnosis. Treatment options included surgery, somatostatin analogs (SSA), and chemotherapy with either platinum-based or temozolomide-based regimens. Estimated progression free survival was 4 months following initiation of SSA and 3 months following initiation of chemotherapy. Disease control was observed following treatment in 5/11 patients treated with chemotherapy. Estimated median survival was 19 months; estimated 1 year survival was 60% and estimated 2 year survival was 13%. NET G3 is a heterogeneous group of tumours and patients which commonly have advanced disease at presentation. Prognosis is typically poor, though select cases may respond to treatment with SSA and/or chemotherapy. Further study is needed to compare efficacy of different treatment strategies for this disease.
Explaining COVID-19 outbreaks with reactive SEIRD models
Authors: Menda Kunal , Laird Lucas , Kochenderfer Mykel J. , Caceres Rajmonda S. 
Published: September 2021

AbstractCOVID-19 epidemics have varied dramatically in nature across the United States, where some counties have clear peaks in infections, and others have had a multitude of unpredictable and non-distinct peaks. Our lack of understanding of how the pandemic has evolved leads to increasing errors in our ability to predict the spread of the disease. This work seeks to explain this diversity in epidemic progressions by considering an extension to the compartmental SEIRD model. The model we propose uses a neural network to predict the infection rate as a function of both time and the disease’s prevalence. We provide a methodology for fitting this model to available county-level data describing aggregate cases and deaths. Our method uses Expectation-Maximization to overcome the challenge of partial observability, due to the fact that the system’s state is only partially reflected in available data. We fit a single model to data from multiple counties in the United States exhibiting different behavior. By simulating the model, we show that it can exhibit both single peak and multi-peak behavior, reproducing behavior observed in counties both in and out of the training set. We then compare the error of simulations from our model with a standard SEIRD model, and show that ours substantially reduces errors. We also use simulated data to compare our methodology for handling partial observability with a standard approach, showing that ours is significantly better at estimating the values of unobserved quantities.
Heavy metals content in ashes of wood pellets and the health risk assessment related to their presence in the environment
Authors: Pazalja Mirha , Salihović Mirsada , Sulejmanović Jasmina , Smajović Alisa , Begić Sabina , Špirtović-Halilović Selma , Sher Farooq 
Published: September 2021

AbstractEfforts to reduce air pollution in developing countries may require increased use of biomass fuels. Even biomass fuels are a sustainable alternative to fossil fuels there is limited quantitative information concerning heavy metal content in their ashes. Therefore, this study focuses on the determination of the heavy metal concentrations in wood pellet ash obtained from the combustion of 10 pellet brans from Bosnia and Herzegovina and Italy, the effects of adding the ashes to soils, and the assessment of health risk assessment. Ash content was determined by gravimetric method. The amount and composition of ash remaining after combustion of wood pellets varies considerably according to the type of biomass and wood from which the pellet is made. Samples were prepared by wet digestion using HNO3, and heavy metals are determined by atomic absorption spectroscopy-flame and graphite furnace. The results showed that the lowest concentration in ashes was obtained for Co 0.01 mg kg−1and the highest for Fe 571.63 mg kg−1. The Hazard Index (HI), calculated for non-cancerous substances for children was 2.23E−01, and the total Risk index was 4.54E−05. As for adults, HI was 1.51E−02, while the Risk index value was 3.21E−06. Human health risk calculated through HI and Risk index for children and adults associated with analyzed pellets is not of significant concern. The calculated enrichment factor and metal pollution index for wood pellet ashes indicate the risk of soil contamination with heavy metals. From this point of view, analyzed samples of ashes could be a serious contaminant of soil, so further monitoring is required.
Distinct calcium regulation of TRPM7 mechanosensitive channels at plasma membrane microdomains visualized by FRET-based single cell imaging
Authors: Starostina Irina , Jang Yoon-Kwan , Kim Heon-Su , Suh Jung-Soo , Ahn Sang-Hyun , Choi Gyu-Ho , Suk Myungeun , Kim Tae-Jin 
Published: September 2021

AbstractTransient receptor potential subfamily M member 7 (TRPM7), a mechanosensitive Ca2+ channel, plays a crucial role in intracellular Ca2+ homeostasis. However, it is currently unclear how cell mechanical cues control TRPM7 activity and its associated Ca2+ influx at plasma membrane microdomains. Using two different types of Ca2+ biosensors (Lyn-D3cpv and Kras-D3cpv) based on fluorescence resonance energy transfer, we investigate how Ca2+ influx generated by the TRPM7-specific agonist naltriben is mediated at the detergent-resistant membrane (DRM) and non-DRM regions. This study reveals that TRPM7-induced Ca2+ influx mainly occurs at the DRM, and chemically induced mechanical perturbations in the cell mechanosensitive apparatus substantially reduce Ca2+ influx through TRPM7, preferably located at the DRM. Such perturbations include the disintegration of lipid rafts, microtubules, or actomyosin filaments; the alteration of actomyosin contractility; and the inhibition of focal adhesion and Src kinases. These results suggest that the mechanical membrane environment contributes to the TRPM7 function and activity. Thus, this study provides a fundamental understanding of how the mechanical aspects of the cell membrane regulate the function of mechanosensitive channels.
Three-dimensional structure of the basal lamella of the middle turbinate
Authors: Eördögh Márton , Baksa Gábor , Grimm András , Bárány László , Petneházy Örs , Reisch Robert , Schroeder Henry W. S. , Briner Hans Rudolf , Hosemann Werner 
Published: September 2021

AbstractThe middle turbinate’s basal lamella (3BL) is a variable landmark which needs to be understood in endoscopic transnasal skull base surgery. It comprises an anterior frontal and a posterior horizontal part and appears in its simplest depiction to be “L”-shaped, when viewed laterally. In this study we analyzed its 3D morphology and variations focusing on a precise and systematic description of the anatomy. CBCTs of 25 adults, 19 cadavers and 6 skulls (total: 100 sides) were investigated with the 3DSlicer software, creating 3D models of the 3BL. We introduced a novel geometrical classification of the 3BL’s shape, based on segments. We analyzed their parameters and relationship to neighboring structures. When viewed laterally, there was no consistent “L”-shaped appearance of the 3BL, as it is frequently quoted. A classification of 9 segment types was used to describe the 3BL. The 3BLs had in average of 2.95 ± 0.70 segments (median: 3), the most frequent was the horizontal plate (23.05% of all segments), next a concave/convex plate (22.71%), then a sigma plate (22.37%). Further types were rare. We identified a horizontal plate in 68% of all lateral views whilst 32% of the 3BLs were vertical. A sigma–concave/convex–horizontal trisegmental 3BL was the most common phenotype (27%). Globally, the sigma–concave/convex pattern was present in 42%. The 3BL adhered the ethmoidal bulla in 87%. The segmenting method is eligible to describe the 3BL’s sophisticated morphology.
Air entrapment and bubble formation during droplet impact onto a single cubic pillar
Authors: Ren Weibo , Foltyn Patrick , Geppert Anne , Weigand Bernhard 
Published: September 2021

AbstractWe study the vertical impact of a droplet onto a cubic pillar of comparable size placed on a flat surface, by means of numerical simulations and experiments. Strikingly, during the impact a large volume of air is trapped around the pillar side faces. Impingement upon different positions of the pillar top surface strongly influences the size and the position of the entrapped air. By comparing the droplet morphological changes during the impact from both computations and experiments, we show that the direct numerical simulations, based on the Volume of Fluid method, provide additional and new insight into the droplet dynamics. We elucidate, with the computational results, the three-dimensional air entrapment process as well as the evolution of the entrapped air into bubbles.
Real-time precise microfluidic droplets label-sequencing combined in a velocity detection sensor
Authors: Zamboni R. , Zaltron A. , Chauvet M. , Sada C. 
Published: September 2021

AbstractDroplets microfluidics is broadening the range of Lab on a Chip solutions that, however, still suffer from the lack of an adequate level of integration of optical detection and sensors. In fact, droplets are currently monitored by imaging techniques, mostly limited by a time-consuming data post-processing and big data storage. This work aims to overcome this weakness, presenting a fully integrated opto-microfluidic platform able to detect, label and characterize droplets without the need for imaging techniques. It consists of optical waveguides arranged in a Mach Zehnder’s configuration and a microfluidic circuit both coupled in the same substrate. As a proof of concept, the work demonstrates the performances of this opto-microfluidic platform in performing a complete and simultaneous sequence labelling and identification of each single droplet, in terms of its optical properties, as well as velocity and lengths. Since the sensor is realized in lithium niobate crystals, which is also highly resistant to chemical attack and biocompatible, the future addition of multifunctional stages into the same substrate can be easily envisioned, extending the range of applicability of the final device.
DNAM-1/CD226 is functionally expressed on acute myeloid leukemia (AML) cells and is associated with favorable prognosis
Authors: Chashchina Anna , Märklin Melanie , Hinterleitner Clemens , Salih Helmut R. , Heitmann Jonas S. , Klimovich Boris 
Published: September 2021

AbstractDNAM-1 is reportedly expressed on cytotoxic T and NK cells and, upon interaction with its ligands CD112 and CD155, plays an important role in tumor immunosurveillance. It has also been reported to be functionally expressed by myeloid cells, but expression and function on malignant cells of the myeloid lineage have not been studied so far. Here we analyzed expression of DNAM-1 in leukemic cells of acute myeloid leukemia (AML) patients. We found substantial levels of DNAM-1 to be expressed on leukemic blasts in 48 of 62 (> 75%) patients. Interaction of DNAM-1 with its ligands CD112 and CD155 induced release of the immunomodulatory cytokines IL-6, IL-8 IL-10 and TNF-α by AML cells and DNAM-1 expression correlated with a more differentiated phenotype. Multivariate analysis did not show any association of DNAM-1 positivity with established risk factors, but expression was significantly associated with clinical disease course: patients with high DNAM-1 surface levels had significantly longer progression-free and overall survival compared to DNAM-1lowpatients, independently whether patients had undergone allogenic stem cell transplantation or not. Together, our findings unravel a functional role of DNAM-1 in AML pathophysiology and identify DNAM-1 as a potential novel prognostic maker in AML.
Boosting and lassoing new prostate cancer SNP risk factors and their connection to selenium
Authors: Booth David E. , Gopalakrishna-Remani Venugopal , Cooper Matthew L. , Green Fiona R. , Rayman Margaret P. 
Published: September 2021

AbstractWe begin by arguing that the often used algorithm for the discovery and use of disease risk factors, stepwise logistic regression, is unstable. We then argue that there are other algorithms available that are much more stable and reliable (e.g. the lasso and gradient boosting). We then propose a protocol for the discovery and use of risk factors using lasso or boosting variable selection. We then illustrate the use of the protocol with a set of prostate cancer data and show that it recovers known risk factors. Finally, we use the protocol to identify new and important SNP based risk factors for prostate cancer and further seek evidence for or against the hypothesis of an anticancer function for Selenium in prostate cancer. We find that the anticancer effect may depend on the SNP-SNP interaction and, in particular, which alleles are present.
Nonstationary signal extraction based on BatOMP sparse decomposition technique
Authors: Ge Shuang-chao , Zhou Shida 
Published: September 2021

AbstractSparse decomposition technique is a new method for nonstationary signal extraction in a noise background. To solve the problem of accuracy and efficiency exclusive in sparse decomposition, the bat algorithm combined with Orthogonal Matching Pursuits (BatOMP) was proposed to improve sparse decomposition, which can realize adaptive recognition and extraction of nonstationary signal containing random noise. Two general atoms were designed for typical signals, and dictionary training method based on correlation detection and Hilbert transform was developed. The sparse decomposition was turned into an optimizing problem by introducing bat algorithm with optimized fitness function. By contrast with several relevant methods, it was indicated that BatOMP can improve convergence speed and extraction accuracy efficiently as well as decrease the hardware requirement, which is cost effective and helps broadening the applications.