bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel kernel based approach to arbitrary length symbolic data with application to type 2 diabetes risk
Authors: Nwegbu Nnanyelugo , Tirunagari Santosh , Windridge David 
Published: March 2022

AbstractPredictive modeling of clinical data is fraught with challenges arising from the manner in which events are recorded. Patients typically fall ill at irregular intervals and experience dissimilar intervention trajectories. This results in irregularly sampled and uneven length data which poses a problem for standard multivariate tools. The alternative of feature extraction into equal-length vectors via methods like Bag-of-Words (BoW) potentially discards useful information. We propose an approach based on a kernel framework in which data is maintained in its native form: discrete sequences of symbols. Kernel functions derived from the edit distance between pairs of sequences may then be utilized in conjunction with support vector machines to classify the data. Our method is evaluated in the context of the prediction task of determining patients likely to develop type 2 diabetes following an earlier episode of elevated blood pressure of 130/80 mmHg. Kernels combined via multi kernel learning achieved an F1-score of 0.96, outperforming classification with SVM 0.63, logistic regression 0.63, Long Short Term Memory 0.61 and Multi-Layer Perceptron 0.54 applied to a BoW representation of the data. We achieved an F1-score of 0.97 on MKL on external dataset. The proposed approach is consequently able to overcome limitations associated with feature-based classification in the context of clinical data.
Effects of melatonin and metformin in preventing lysosome-induced autophagy and oxidative stress in rat models of carcinogenesis and the impact of high-fat diet
Authors: Kurhaluk Natalia , Tkachenko Halyna 
Published: March 2022

AbstractImbalanced glucose tolerance and insulin resistance remain important as high cancer risk factors. Metformin administration to diabetic patients may be associated with a reduced risk of malignancy. The combined effects of the hormone melatonin and metformin in oncology practice have shown positive results. The relevance of our study is to find out the role of specific biomarkers of lysosome destruction and oxidative stress data in carcinogenesis models. The present study was designed to investigate the comparative synergic effect of peroral antidiabetic metformin (MF) and pineal hormone melatonin (MEL) administered alone and in combination in two different rat’s models of mammary tumour proliferation in vivo (N-methyl-N-nitrosourea, NMU or 7,12-dimethylbenz[a]anthracene, DMBA). We have studied the processes of lysosomal destruction (alanyl aminopeptidase AAP, leucyl aminopeptidase LAP, acid phosphatase AcP, β-N-acetylglucosaminidase NAG, β-galactosidase β-GD and β-glucuronidase β-GR) caused by evaluated oxidative stress in three types of tissues (liver, heart, and spleen) in female Sprague–Dawley rats fed a high-fat diet (10% of total fat: 2.5% from lard and 7.5% from palm olein). Our results revealed an increase in the activity of the studied lysosomal enzymes and their expression in a tissue-specific manner depending on the type of chemical agent (NMU or DMBA). MANOVA tests in our study confirmed the influence of the three main factors, type of tissue, chemical impact, and chemopreventive agents, and the combinations of these factors on the lysosomal activity induced during the process of cancerogenesis. The development and induction of the carcinogenesis process in the different rat models with the high-fat diet impact were also accompanied by initiation of free-radical oxidation processes, which we studied at the initial (estimated by the level of diene conjugates) and final (TBARS products) stages of this process. The combined effects of MEL and MF for the two models of carcinogenesis at high-fat diet impact for AAP, LAP, and AcP showed a significant synergistic effect when they impact together when compared with the effects of one substance alone (either MEL or MF) in the breast cancer model experiments. Synergistic effects of limiting destructive processes of lysosomal functioning β-GD enzyme activity we obtained in experiments with MEL and MF chemoprevention for both models of carcinogenesis for three tissues. The statistical SS test allowed us to draw the following conclusions on the role of each lysosomal parameter analyzed as an integral model: NAG > AcP > β-GD > β-GR > AAP > LAP.
Potential risk assessment for safe driving of autonomous vehicles under occluded vision
Authors: Wang Denggui , Fu Weiping , Song Qingyuan , Zhou Jincao 
Published: March 2022

AbstractThis study aimed to explore how autonomous vehicles can predict potential risks and efficiently pass through the dangerous interaction areas in the face of occluded scenes or limited visual scope. First, a Dynamic Bayesian Network based model for real-time assessment of potential risks is proposed, which enables autonomous vehicles to observe the surrounding risk factors, and infer and quantify the potential risks at the visually occluded areas. The risk distance coefficient is established to integrate the perception interaction ability of traffic participants into the model. Second, the predicted potential risk is applied to vehicle motion planning. The vehicle movement is improved by adjusting the speed and heading angle control. Finally, a dynamic simulation platform is built to verify the proposed model in two specific scenarios of view occlusion. The model has been compared with the existing methods, the autonomous vehicles can accurately assess the potential danger of the occluded areas in real-time and can safely, comfortably, and effectively pass through the dangerous interaction areas.
Renalase and its receptor, PMCA4b, are expressed in the placenta throughout the human gestation
Authors: Wang Melinda , Silva Tatiana , Toothaker Jessica M. , McCourt Blake T. , Shugrue Christine , Desir Gary , Gorelick Fred , Konnikova Liza 
Published: March 2022

AbstractPlacental function requires organized growth, transmission of nutrients, and an anti-inflammatory milieu between the maternal and fetal interface, but placental factors important for its function remain unclear. Renalase is a pro-survival, anti-inflammatory flavoprotein found to be critical in other tissues. We examined the potential role of renalase in placental development. PCR, bulk RNA sequencing, immunohistochemistry, and immunofluorescence for renalase and its binding partners, PMCA4b and PZP, were performed on human placental tissue from second-trimester and full-term placentas separated into decidua, placental villi and chorionic plates. Quantification of immunohistochemistry was used to localize renalase across time course from 17 weeks to term. Endogenous production of renalase was examined in placental tissue and organoids. Renalase and its receptor PMCA4b transcripts and proteins were present in all layers of the placenta. Estimated RNLS protein levels did not change with gestation in the decidual samples. However, placental villi contained more renalase immunoreactive cells in fetal than full-term placental samples. RNLS co-labeled with markers for Hofbauer cells and trophoblasts within the placental villi. Endogenous production of RNLS, PMCA4b, and PZP by trophoblasts was validated in placental organoids. Renalase is endogenously expressed throughout placental tissue and specifically within Hofbauer cells and trophoblasts, suggesting a potential role for renalase in placental development and function. Future studies should assess renalase’s role in normal and diseased human placenta.
Estimating the density of deep eutectic solvents applying supervised machine learning techniques
Authors: Abdollahzadeh Mohammadjavad , Khosravi Marzieh , Hajipour Khire Masjidi Behnam , Samimi Behbahan Amin , Bagherzadeh Ali , Shahkar Amir , Tat Shahdost Farzad 
Published: March 2022

AbstractDeep eutectic solvents (DES) are recently synthesized to cover limitations of conventional solvents. These green solvents have wide ranges of potential usages in real-life applications. Precise measuring or accurate estimating thermophysical properties of DESs is a prerequisite for their successful applications. Density is likely the most crucial affecting characteristic on the solvation ability of DESs. This study utilizes seven machine learning techniques to estimate the density of 149 deep eutectic solvents. The density is anticipated as a function of temperature, critical pressure and temperature, and acentric factor. The LSSVR (least-squares support vector regression) presents the highest accuracy among 1530 constructed intelligent estimators. The LSSVR predicts 1239 densities with the mean absolute percentage error (MAPE) of 0.26% and R2 = 0.99798. Comparing the LSSVR and four empirical correlations revealed that the earlier possesses the highest accuracy level. The prediction accuracy of the LSSVR (i.e., MAPE = 0. 26%) is 74.5% better than the best-obtained results by the empirical correlations (i.e., MAPE = 1.02%).
Demonstration of multiple quantum interference and Fano resonance realization in far-field from plasmonic nanostructure in Er3+-doped tellurite glass
Authors: Lozano C. G. , Silva O. B. , Ferri F. A. , Rivera V. A. G. , Marega E. 
Published: March 2022

AbstractIt is crucial to control the tuning and improve the emission of a quantum emitter at the nanoscale. We report multiple Fano resonances in metallic nanostructures on an Er3+-doped tellurite glass. Periodic nanoslits were fabricated with a focused gallium ion beam on a gold thin film deposited on the tellurite glass. Is proposed a coupling function with Fano line-shape form, and the asymmetric parameter q for each resonance wavelength in the 515 to 535 nm region was calculated. This asymmetric resonance effect is a consequence of the quantum interaction between the continuum state, generated in the nanostructure, and the Stark splits of the $$^2$$

2

H$$_{11/2}$$

11
/
2

state.
Machine learning-assisted non-destructive plasticizer identification and quantification in historical PVC objects based on IR spectroscopy
Authors: Rijavec Tjaša , Ribar David , Markelj Jernej , Strlič Matija , Kralj Cigić Irena 
Published: March 2022

AbstractNon-destructive spectroscopic analysis combined with machine learning rapidly provides information on the identity and content of plasticizers in PVC objects of heritage value. For the first time, a large and diverse collection of more than 100 PVC objects in different degradation stages and of diverse chemical compositions was analysed by chromatographic and spectroscopic techniques to create a dataset used to construct classification and regression models. Accounting for this variety makes the model more robust and reliable for the analysis of objects in museum collections. Six different machine learning classification algorithms were compared to determine the algorithm with the highest classification accuracy of the most common plasticizers, based solely on the spectroscopic data. A classification model capable of the identification of di(2-ethylhexyl) phthalate, di(2-ethylhexyl) terephthalate, diisononyl phthalate, diisodecyl phthalate, a mixture of diisononyl phthalate and diisodecyl phthalate, and unplasticized PVC was constructed. Additionally, regression models for quantification of di(2-ethylhexyl) phthalate and di(2-ethylhexyl) terephthalate in PVC were built. This study of real-life objects demonstrates that classification and quantification of plasticizers in a general collection of degraded PVC objects is possible, providing valuable data to collection managers.
Identification of potentially functional circular RNAs hsa_circ_0070934 and hsa_circ_0004315 as prognostic factors of hepatocellular carcinoma by integrated bioinformatics analysis
Authors: Morovat Pejman , Morovat Saman , Ashrafi Arash M. , Teimourian Shahram 
Published: March 2022

AbstractHepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, which has a high mortality rate and poor treatment outcomes with yet unknown molecular basis. It seems that gene expression plays a pivotal role in the pathogenesis of the disease. Circular RNAs (circRNAs) can interact with microRNAs (miRNAs) to regulate gene expression in various malignancies by acting as competitive endogenous RNAs (ceRNAs). However, the potential pathogenesis roles of the ceRNA network among circRNA/miRNA/mRNA in HCC are unclear. In this study, first, the HCC circRNA expression data were obtained from three Gene Expression Omnibus microarray datasets (GSE164803, GSE94508, GSE97332), and the differentially expressed circRNAs (DECs) were identified using R limma package. Also, the liver hepatocellular carcinoma (LIHC) miRNA and mRNA sequence data were retrieved from TCGA and differentially expressed miRNAs (DEMIs) and mRNAs (DEGs) were determined using the R DESeq2 package. Second, CSCD website was used to uncover the binding sites of miRNAs on DECs. The DECs' potential target miRNAs were revealed by conducting an intersection between predicted miRNAs from CSCD and downregulated DEMIs. Third, candidate genes were uncovered by intersecting targeted genes predicted by miRWalk and targetscan online tools with upregulated DEGs. The ceRNA network was then built using the Cytoscape software. The functional enrichment and the overall survival time of these potential targeted genes were analyzed, and a PPI network was constructed in the STRING database. Network visualization was performed by Cytoscape, and ten hub genes were detected using the CytoHubba plugin tool. Four DECs (hsa_circ_0000520, hsa_circ_0008616, hsa_circ_0070934, hsa_circ_0004315) were obtained and six miRNAs (hsa-miR-542-5p, hsa-miR-326, hsa-miR-511-5p, hsa-miR-195-5p, hsa-miR-214-3p, and hsa-miR-424-5p) which are regulated by the above DECs were identified. Then 543 overlapped genes regulated by six miRNAs mentioned above were predicted. Functional enrichment analysis showed that these genes are mostly associated with regulatory pathways in cancer. Ten hub genes (TTK, AURKB, KIF20A, KIF23, CEP55, CDC6, DTL, NCAPG, CENPF, PLK4) have been screened from the PPI network of the 204 survival-related genes. KIF20A, NCAPG, TTK, PLK4, and CDC6 were selected for the highest significance p-values. At the end, a circRNA-miRNA-mRNA regulatory axis was established for five final selected hub genes. This study implies the potential pathogenesis of the obtained network and proposes that the two DECs (has_circ_0070934 and has_circ_0004315) may be important prognostic markers for HCC.
Copper-doped functionalized β-cyclodextrin as an efficient green nanocatalyst for synthesis of 1,2,3-triazoles in water
Authors: Tajbakhsh Mahdieh , Naimi-Jamal Mohammad Reza 
Published: March 2022

AbstractThe synthesis of 1,2,3-triazoles with immobilized Cu(I) in thiosemicarbazide-functionalized β-cyclodextrin (Cu@TSC-β‐CD) as a supramolecular catalyst was discussed. The catalyst was characterized by Fourier-transform infrared spectroscopy (FT-IR), thermogravimetric analysis (TGA), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) measurements. The catalyst showed high activity (up to 95% yields of triazole products under optimized reaction conditions), providing a one-pot, atom-economic, and highly regioselective green method for 1,2,3-triazoles synthesis in an azide-alkyne cycloaddition (AAC) protocol in water. High stability and no appreciable leaching of Cu(I) were observed, owing to its strong binding via the coordination with thiosemicarbazide functionality.
Exploring mitogenome evolution in Branchiopoda (Crustacea) lineages reveals gene order rearrangements in Cladocera
Authors: Castellucci Filippo , Luchetti Andrea , Mantovani Barbara 
Published: March 2022

AbstractThe class Branchiopoda, whose origin dates back to Cambrian, includes ~ 1200 species which mainly occupy freshwater habitats. The phylogeny and systematics of the class have been debated for long time, until recent phylogenomic analyses allowed to better clarify the relationships among major clades. Based on these data, the clade Anostraca (fairy and brine shrimps) is sister to all other branchiopods, and the Notostraca (tadpole shrimps) results as sister group to Diplostraca, which includes Laevicaudata + Spinicaudata (clam shrimps) and Cladoceromorpha (water fleas + Cyclestherida). In the present analysis, thanks to an increased taxon sampling, a complex picture emerges. Most of the analyzed mitogenomes show the Pancrustacea gene order while in several other taxa they are found rearranged. These rearrangements, though, occur unevenly among taxa, most of them being found in Cladocera, and their taxonomic distribution does not agree with the phylogeny. Our data also seems to suggest the possibility of potentially homoplastic, alternative gene order within Daphniidae.
Comparison of intuitive assessment and palliative care screening tool in the early identification of patients needing palliative care
Authors: Yen Yung-Feng , Hu Hsiao-Yun , Lai Yun-Ju , Chou Yi-Chang , Chen Chu-Chieh , Ho Chin-Yu 
Published: March 2022

AbstractThe intuitive assessment of palliative care (PC) needs and Palliative Care Screening Tool (PCST) are the assessment tools used in the early detection of patients requiring PC. However, the comparison of their prognostic accuracies has not been extensively studied. This cohort study aimed to compare the validity of intuitive assessment and PCST in terms of recognizing patients nearing end-of-life (EOL) and those appropriate for PC. All adult patients admitted to Taipei City Hospital from 2016 through 2019 were included in this prospective study. We used both the intuitive assessment of PC and PCST to predict patients’ 6-month mortality and identified those appropriate for PC. The c-statistic value was calculated to indicate the predictive accuracies of the intuition and PCST. Of 111,483 patients, 4.5% needed PC by the healthcare workers’ intuitive assessment, and 6.7% had a PCST score ≥ 4. After controlling for other covariates, a positive response ‘yes’ to intuitive assessment of PC needs [adjusted odds ratio (AOR) = 9.89; 95% confidence interval (CI) 914–10.71] and a PCST score ≥ 4 (AOR = 6.59; 95%CI 6.17–7.00) were the independent predictors of 6-month mortality. Kappa statistics showed moderate concordance between intuitive assessment and PCST in predicting patients' 6-month mortality (k = 0.49). The c-statistic values of the PCST at recognizing patients’ 6-month mortality was significantly higher than intuition (0.723 vs. 0.679; p < 0.001). As early identification of patients in need of PC could improve the quality of EOL care, our results suggest that it is imperative to screen patients’ palliative needs by using a highly accurate screening tool of PCST.
Impact of virtual embodiment and exercises on functional ability and range of motion in orthopedic rehabilitation
Authors: Matamala-Gomez Marta , Slater Mel , Sanchez-Vives Maria V. 
Published: March 2022

AbstractRecent evidence supports the use of immersive virtual reality (immersive VR) as a means of applying visual feedback techniques in neurorehabilitation. In this study, we investigated the benefits of an embodiment-based immersive VR training program for orthopedic upper limb rehabilitation, with the aim of improving the motor functional ability of the arm and accelerating the rehabilitation process in patients with a conservatively managed distal radius fracture. We designed a rehabilitation program based on developing ownership over a virtual arm and then exercising it in immersive VR. We carried out a between 3-group controlled trial with 54 patients (mean age = 61.80 ± 14.18): 20 patients were assigned to the experimental training group (immersive VR), 20 to the conventional digit mobilization (CDM) training control group, and 14 to a non-immersive (non-immersive VR) training control group. We found that functional recovery of the arm in the immersive VR group was correlated with the ownership and agency scores over the virtual arm. We also found larger range of joint movements and lower disability of the fractured arm compared with patients in the Non-immersive VR and CDM groups. Feeling embodied in a virtual body can be used as a rehabilitation tool to speed up and improve motor functional recovery of a fractured arm after the immobilization period.
SLM-processed MoS2/Mo2S3 nanocomposite for energy conversion/storage applications
Authors: Alinejadian Navid , Kazemi Sayed Habib , Odnevall Inger 
Published: March 2022

AbstractMoS2-based nanocomposites have been widely processed by a variety of conventional and 3D printing techniques. In this study, selective laser melting (SLM) has for the first time successfully been employed to tune the crystallographic structure of bulk MoS2 to a 2H/1T phase and to distribute Mo2S3 nanoparticles in-situ in MoS2/Mo2S3 nanocomposites used in electrochemical energy conversion/storage systems (EECSS). The remarkable results promote further research on and elucidate the applicability of laser-based powder bed processing of 2D nanomaterials for a wide range of functional structures within, e.g., EECSS, aerospace, and possibly high-temperature solid-state EECSS even in space.
Intrinsic bursts facilitate learning of Lévy flight movements in recurrent neural network models
Authors: Ohta Morihiro , Asabuki Toshitake , Fukai Tomoki 
Published: March 2022

AbstractIsolated spikes and bursts of spikes are thought to provide the two major modes of information coding by neurons. Bursts are known to be crucial for fundamental processes between neuron pairs, such as neuronal communications and synaptic plasticity. Neuronal bursting also has implications in neurodegenerative diseases and mental disorders. Despite these findings on the roles of bursts, whether and how bursts have an advantage over isolated spikes in the network-level computation remains elusive. Here, we demonstrate in a computational model that not isolated spikes, but intrinsic bursts can greatly facilitate learning of Lévy flight random walk trajectories by synchronizing burst onsets across a neural population. Lévy flight is a hallmark of optimal search strategies and appears in cognitive behaviors such as saccadic eye movements and memory retrieval. Our results suggest that bursting is crucial for sequence learning by recurrent neural networks when sequences comprise long-tailed distributed discrete jumps.