bluuebunny/crossref_metadata_2025_split huggingface dataset:
Essential role for paxillin tyrosine phosphorylation in LPS-induced mitochondrial fission, ROS generation and lung endothelial barrier loss
Authors: Fu Panfeng , Epshtein Yulia , Ramchandran Ramaswamy , Mascarenhas Joseph B. , Cress Anne E. , Jacobson Jeffrey , Garcia Joe G. N. , Natarajan Viswanathan 
Published: September 2021

AbstractWe have shown that both reactive oxygen species (ROS) and paxillin tyrosine phosphorylation regulate LPS-induced human lung endothelial permeability. Mitochondrial ROS (mtROS) is known to increase endothelial cell (EC) permeability which requires dynamic change in mitochondrial morphology, events that are likely to be regulated by paxillin. Here, we investigated the role of paxillin and its tyrosine phosphorylation in regulating LPS-induced mitochondrial dynamics, mtROS production and human lung microvascular EC (HLMVEC) dysfunction. LPS, in a time-dependent manner, induced higher levels of ROS generation in the mitochondria compared to cytoplasm or nucleus. Down-regulation of paxillin expression with siRNA or ecto-expression of paxillin Y31F or Y118F mutant plasmids attenuated LPS-induced mtROS in HLMVECs. Pre-treatment with MitoTEMPO, a scavenger of mtROS, attenuated LPS-induced mtROS, endothelial permeability and VE-cadherin phosphorylation. Further, LPS-induced mitochondrial fission in HLMVECs was attenuated by both a paxillin siRNA, and paxillin Y31F/Y118F mutant. LPS stimulated phosphorylation of dynamin-related protein (DRP1) at S616, which was also attenuated by paxillin siRNA, and paxillinY31/Y118 mutants. Inhibition of DRP1 phosphorylation by P110 attenuated LPS-induced mtROS and endothelial permeability. LPS challenge of HLMVECs enhanced interaction between paxillin, ERK, and DRP1, and inhibition of ERK1/2 activation with PD98059 blocked mitochondrial fission. Taken together, these results suggest a key role for paxillin tyrosine phosphorylation in LPS-induced mitochondrial fission, mtROS generation and EC barrier dysfunction.
MPT64 antigen detection test improves diagnosis of pediatric extrapulmonary tuberculosis in Mbeya, Tanzania
Authors: Grønningen Erlend , Nanyaro Marywinnie , Sviland Lisbet , Ngadaya Esther , Muller William , Torres Lisete , Mfinanga Sayoki , Mustafa Tehmina 
Published: September 2021

AbstractPediatric extrapulmonary tuberculosis (EPTB) is a diagnostic challenge. A new immunochemistry based MPT64 antigen detection test has shown improved sensitivity compared to current laboratory tests. The aim of this study was to implement and validate the test performance in a resource limited African setting. Presumptive pediatric (0–18 y) EPTB patients were prospectively enrolled at Mbeya Zonal Referral Hospital, and followed to the end of treatment or until a final diagnosis was reached. Specimens from suspected sites of infection were subject to routine diagnostics, GeneXpert MTB/RIF assay and the MPT64 test. The performance of the tests was assessed using mycobacterial culture as well as a composite reference standard. 30 patients were categorized as TB cases, 31 as non-TB cases and 2 were uncategorized. In the TB group, the three most common infections were adenitis (30%), peritonitis (30%) and meningitis (20%). The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of the MPT64 test was 92%, 88%, 87%, 92% and 90%, respectively. Mortality was equally high among TB/non-TB cases (23% vs 21%), and malnutrition was the main comorbidity among TB cases. The MPT64 test was implementable in the routine diagnostics in a low-resource setting and improved the diagnosis of pediatric EPTB.
Photoacoustic tomography of fingerprint and underlying vasculature for improved biometric identification
Authors: Zheng Wenhan , Lee Diana , Xia Jun 
Published: September 2021

AbstractCapitalizing on the photoacoustic effect, we developed a new fingerprint sensing system that can reveal both fingerprints and underlying vascular structures at a high spatial resolution. Our system is built on a 15 MHz linear transducer array, a research ultrasound system, and a 532-nm pulsed laser. A 3D image was obtained by scanning the linear array over the fingertip. The acquired fingerprint images strongly agreed with the images acquired from ultrasound. Additional experiments were also conducted to investigate the effect of acoustic coupling. We discovered that high-quality fingerprint and vessel images can be acquired from both wet and dry fingers using our photoacoustic system. The reduced subdermal features in dry coupling can be enhanced through post-processing. Compared to existing fingerprint scanners, the photoacoustic approach provides a higher quality 3D image of the fingerprint, as well as unique subdermal vasculature structures, making the system almost impossible to counterfeit.
Modeling and verifying clustering properties in a vehicular ad hoc network protocol with Event-B
Authors: Sondi Patrick , Abbassi Imed , Ramat Eric , Chebbi Emna , Graiet Mohamed 
Published: September 2021

AbstractVehicular ad hoc network (VANET) routing protocols resort to clustering in order to optimize broadcast traffic flooding. Clustering schemes usually rely on rules which apply to each vehicle in order to reach a targeted organization in a VANET. Most of the literature works which evaluate clustering for VANET focus on performance analysis. However, with autonomous vehicles coming to roadways, more rigorous relationships will be required between clustering rules and the resulting organization, so as to anticipate road safety in a better way. We propose a formal description of the properties which are expected in a VANET, while considering the rules of a given clustering scheme. Using Event-B, we first present a description of the VANET, the vehicles movement and the traffic generated by both routing and application messages. Then, based on an Event-B model of a basic routing protocol of the literature, we describe how the specific rules of a clustering scheme can be modeled along with the properties expected in the resulting organization. Finally, we propose a validation process of the model. This paper aims at showing how our proposals have been applied to the Chain-Branch-Leaf scheme, although they can be adapted to any rule-based clustering scheme for VANET.
Integrative analysis of the gut microbiome and metabolome in a rat model with stress induced irritable bowel syndrome
Authors: Hu Yue , Chen Fang , Ye Haiyong , Lu Bin 
Published: September 2021

AbstractStress is one of the major causes of irritable bowel syndrome (IBS), which is well-known for perturbing the microbiome and exacerbating IBS-associated symptoms. However, changes in the gut microbiome and metabolome in response to colorectal distention (CRD), combined with restraint stress (RS) administration, remains unclear. In this study, CRD and RS stress were used to construct an IBS rat model. The 16S rRNA gene sequencing was used to characterize the microbiota in ileocecal contents. UHPLC-QTOF-MS/MS assay was used to characterize the metabolome of gut microbiota. As a result, significant gut microbial dysbiosis was observed in stress-induced IBS rats, with the obvious enrichment of three and depletion of 11 bacterial taxa in IBS rats, when compared with those in the control group (q < 0.05). Meanwhile, distinct changes in the fecal metabolic phenotype of stress-induced IBS rats were also found, including five increased and 19 decreased metabolites. Furthermore, phenylalanine, tyrosine and tryptophan biosynthesis were the main metabolic pathways induced by IBS stress. Moreover, the altered gut microbiota had a strong correlation with the changes in metabolism of stress-induced IBS rats. Prevotella bacteria are correlated with the metabolism of 1-Naphthol and Arg.Thr. In conclusion, the gut microbiome, metabolome and their interaction were altered. This may be critical for the development of stress-induced IBS.
Evaluating the influence of land use and land cover change on fine particulate matter
Authors: Yang Wei , Jiang Xiaoli 
Published: September 2021

AbstractFine particulate matter (i.e. particles with diameters smaller than 2.5 microns, PM2.5) has become a critical environmental issue in China. Land use and land cover (LULC) is recognized as one of the most important influence factors, however very fewer investigations have focused on the impact of LULC on PM2.5. The influences of different LULC types and different land use and land cover change (LULCC) types on PM2.5 are discussed. A geographically weighted regression model is used for the general analysis, and a spatial analysis method based on the geographic information system is used for a detailed analysis. The results show that LULCC has a stable influence on PM2.5 concentration. For different LULC types, construction lands have the highest PM2.5 concentration and woodlands have the lowest. The order of PM2.5 concentration for the different LULC types is: construction lands > unused lands > water > farmlands >grasslands > woodlands. For different LULCC types, when high-grade land types are converted to low-grade types, the PM2.5 concentration decreases; otherwise, the PM2.5 concentration increases. The result of this study can provide a decision basis for regional environmental protection and regional ecological security agencies.
Association of visual impairment with cognitive decline among older adults in Taiwan
Authors: Fang I.-Mo , Fang Yi-Jen , Hu Hsiao-Yun , Weng Shih-Han 
Published: September 2021

AbstractThis study investigated the association between visual impairment and cognitive decline among the elderly in Taiwan. The data were obtained from a government-sponsored, annual physical examination program for elderly citizens ≥ 65 years in Taipei City during 2005–2012. Distance presenting visual acuity was measured using the Snellen chart. Visual impairment was classified into low vision and blindness. The Short Portable Mental Status Questionnaire (SPMSQ) was selected to measure cognitive decline. The confounding factors including age, sex, sociodemographic factors: living status, marital status, education level, health behaviors: smoking, alcohol consumption, betel nut chewing, and physical comorbidities: BMI, hypertension, diabetes, cholesterol and triglyceride were collected for analysis. We recruited 105,208 participants and 4542 (4.3%) have abnormal SPMSQ. The abnormal SPMSQ had significantly higher prevalence of low vision (44.52% vs 18.79%) and blindness (8.89% vs 0.93%) compared with normal SPMSQ. The hazard ratios of abnormal SPMSQ in low vision and blindness were 2.34 (95% CI 2.17–2.52), and 5.13 (95% CI 4.50–5.85), after adjustment for confounders. In conclusion, visual impairment was independently and significantly associated with greater incident cognitive decline among elderly Asian people. Prevention of visual impairment may help to reduce the incidence of cognitive decline in the aged Asian population.
Model guided extremum seeking control of electromagnetic micromirrors
Authors: Sun Wanyan , Tan Yonghong 
Published: September 2021

AbstractIn this paper, a simplified dynamic model is constructed to describe the main characteristic of electromagnetic micro-mirror. Then, based on the information provided by the derived simplified model, a model-guided extremum seeking control (MGESC) scheme with backtracking line search is developed, which can automatically estimate the best value of step-size at each search iteration to improve the performance of the control system for target tracking. Then, the convergence of the proposed MGES algorithm is proved. Finally, the experimental results and the simulations are presented to verify the proposed method.
Mendelian randomization study of interleukin (IL)-1 family and lung cancer
Authors: Yang Zhao , Schooling C. Mary , Kwok Man Ki 
Published: September 2021

AbstractThe role of interleukin (IL)-1 family members/receptors in lung cancer remains uncertain due to the susceptibility of observed associations to confounding. We appraised the association of IL-1 family members/receptors with lung cancer and its subtypes [lung adenocarcinoma (LUAD) and squamous cell lung cancer (LUSC)] using two-sample Mendelian randomization. This study found that no IL-1 family members/receptors were significantly associated with lung cancer and its subtypes risk after correction for multiple testing. However, suggestive total effects of increased risk were noted for genetically predicted IL-1Racp with lung cancer (P = 0.006), IL-1α with LUAD (P = 0.027), and IL-1Racp with LUSC (P = 0.008). Suggestive direct effects were also noted for IL-1β, IL-1Ra, IL-36γ with lung cancer, IL-1α/β, IL-1Ra with LUAD, and IL-1β, IL-18BP with LUSC, after adjusting for genetically predicted effects of other IL-1 family members/receptors. Taken together, our findings suggest that interventions decreasing IL-1Racp might protect against lung cancer, perhaps via IL-1α/β or IL-1Ra.
Magneto-hydrodynamics of multi-phase flows in heterogeneous systems with large property gradients
Authors: Flint T. F. , Smith M. C. , Shanthraj P. 
Published: September 2021

AbstractThe complex interplay between thermal, hydrodynamic, and electromagnetic, forces governs the evolution of multi-phase systems in high technology applications, such as advanced manufacturing and fusion power plant operation. In this work, a new formulation of the time dependent magnetic induction equation is fully coupled to a set of conservation laws for multi-phase fluid flow, energy transport and chemical species transport that describes melting and solidification state transitions. A finite-volume discretisation of the resulting system of equations is performed, where a novel projection method is formulated to ensure that the magnetic field remains divergence free. The proposed framework is validated by accurately replicating a Hartmann flow profile. Further validation is performed through correctly predicting the experimentally observed trajectory of Argon bubbles rising in a liquid metal under varying applied magnetic fields. Finally, the applicability of the framework to technologically relevant processes is illustrated through the simulation of an electrical arc welding process between dissimilar metals. The proposed framework addresses an urgent need for numerical methods to understand the evolution of multi-phase systems with large electromagnetic property contrast.
A machine learning framework for predicting drug–drug interactions
Authors: Mei Suyu , Zhang Kun 
Published: September 2021

AbstractUnderstanding drug–drug interactions is an essential step to reduce the risk of adverse drug events before clinical drug co-prescription. Existing methods, commonly integrating heterogeneous data to increase model performance, often suffer from a high model complexity, As such, how to elucidate the molecular mechanisms underlying drug–drug interactions while preserving rational biological interpretability is a challenging task in computational modeling for drug discovery. In this study, we attempt to investigate drug–drug interactions via the associations between genes that two drugs target. For this purpose, we propose a simple f drug target profile representation to depict drugs and drug pairs, from which an l2-regularized logistic regression model is built to predict drug–drug interactions. Furthermore, we define several statistical metrics in the context of human protein–protein interaction networks and signaling pathways to measure the interaction intensity, interaction efficacy and action range between two drugs. Large-scale empirical studies including both cross validation and independent test show that the proposed drug target profiles-based machine learning framework outperforms existing data integration-based methods. The proposed statistical metrics show that two drugs easily interact in the cases that they target common genes; or their target genes connect via short paths in protein–protein interaction networks; or their target genes are located at signaling pathways that have cross-talks. The unravelled mechanisms could provide biological insights into potential adverse drug reactions of co-prescribed drugs.
Risk prediction of clinical adverse outcomes with machine learning in a cohort of critically ill patients with atrial fibrillation
Authors: Falsetti Lorenzo , Rucco Matteo , Proietti Marco , Viticchi Giovanna , Zaccone Vincenzo , Scarponi Mattia , Giovenali Laura , Moroncini Gianluca , Nitti Cinzia , Salvi Aldo 
Published: September 2021

AbstractCritically ill patients affected by atrial fibrillation are at high risk of adverse events: however, the actual risk stratification models for haemorrhagic and thrombotic events are not validated in a critical care setting. With this paper we aimed to identify, adopting topological data analysis, the risk factors for therapeutic failure (in-hospital death or intensive care unit transfer), the in-hospital occurrence of stroke/TIA and major bleeding in a cohort of critically ill patients with pre-existing atrial fibrillation admitted to a stepdown unit; to engineer newer prediction models based on machine learning in the same cohort. We selected all medical patients admitted for critical illness and a history of pre-existing atrial fibrillation in the timeframe 01/01/2002–03/08/2007. All data regarding patients’ medical history, comorbidities, drugs adopted, vital parameters and outcomes (therapeutic failure, stroke/TIA and major bleeding) were acquired from electronic medical records. Risk factors for each outcome were analyzed adopting topological data analysis. Machine learning was used to generate three different predictive models. We were able to identify specific risk factors and to engineer dedicated clinical prediction models for therapeutic failure (AUC: 0.974, 95%CI: 0.934–0.975), stroke/TIA (AUC: 0.931, 95%CI: 0.896–0.940; Brier score: 0.13) and major bleeding (AUC: 0.930:0.911–0.939; Brier score: 0.09) in critically-ill patients, which were able to predict accurately their respective clinical outcomes. Topological data analysis and machine learning techniques represent a concrete viewpoint for the physician to predict the risk at the patients’ level, aiding the selection of the best therapeutic strategy in critically ill patients affected by pre-existing atrial fibrillation.
Reconstructing and counting genomic fragments through tagmentation-based haploid phasing
Authors: Leong Patrick P. T. , Mihajlović Aleksandar , Bogdanović Nadežda , Breberina Luka , Xi Larry 
Published: September 2021

AbstractSingle-cell sequencing provides a new level of granularity in studying the heterogeneous nature of cancer cells. For some cancers, this heterogeneity is the result of copy number changes of genes within the cellular genomes. The ability to accurately determine such copy number changes is critical in tracing and understanding tumorigenesis. Current single-cell genome sequencing methodologies infer copy numbers based on statistical approaches followed by rounding decimal numbers to integer values. Such methodologies are sample dependent, have varying calling sensitivities which heavily depend on the sample’s ploidy and are sensitive to noise in sequencing data. In this paper we have demonstrated the concept of integer-counting by using a novel bioinformatic algorithm built on our library construction chemistry in order to detect the discrete nature of the genome.
Epidemiology of Staphylococcus pseudintermedius in cats in Poland
Authors: Bierowiec K. , Miszczak M. , Korzeniowska-Kowal A. , Wzorek A. , Płókarz D. , Gamian A. 
Published: September 2021

AbstractStaphylococcus pseudintermedius is a well-known coagulase-positive staphylococcus that is mainly associated with the asymptomatic colonization of the skin of pets and mucous membranes. Little is still known about the occurrence of S. pseudintermedius in cats. The current study aimed to characterize the isolates of S. pseudintermedius from sick and healthy cats. This was achieved by examining their antibiotic resistance properties, biofilm formation, and genotype differences. Six hundred and seventy-six cats were swabbed (595 healthy and 81 sick cats). Thirty-five distinct S. pseudintermedius isolates from 27 cats were isolated. The prevalence of S. pseudintermedius in healthy and sick cats was 2.49% and 7.61%, respectively. In comparison, MRSP (methicillin-resistant Staphylococcus pseudintermedius) prevalence was 0.12% and 2.98%, respectively. Cats were more frequently colonized with S. pseudintermedius when kept with dogs, regardless of their health condition, with this result being statistically significant. Multidrug resistance was detected in 50%, and 38.46% of S. pseudintermedius isolates from healthy and sick cats, respectively. In contrast, genetic multidrug resistance was detected in 59% and 46.15% cases, respectively. Seven from eight isolated MRSPs were multidrug-resistant. Multi-locus sequence typing (MLST) assigned isolates to 19 types, of which 16 types submitted for the first time to the PubMLST database. The most frequently detected STs (sequence types) were 551 and 71. ST71 and ST551 were mainly isolated from cats with clinical signs of infection. All were MRSPs, regardless of cats’ health. These isolates were characterized with the most frequent antibiotic resistance at the phenotypic and genotypic level.
Transcranial photobiomodulation and thermal stimulation induce distinct topographies of EEG alpha and beta power changes in healthy humans
Authors: Wang Xinlong , Wanniarachchi Hashini , Wu Anqi , Gonzalez-Lima F. , Liu Hanli 
Published: September 2021

AbstractOur recent study demonstrated that prefrontal transcranial photobiomodulation (tPBM) with 1064-nm laser enables significant changes in EEG rhythms, but these changes might result from the laser-induced heat rather than tPBM. This study hypothesized that tPBM-induced and heat-induced alterations in EEG power topography were significantly distinct. We performed two sets of measurements from two separate groups of healthy humans under tPBM (n = 46) and thermal stimulation (thermo_stim; n = 11) conditions. Each group participated in the study twice under true and respective sham stimulation with concurrent recordings of 64-channel EEG before, during, and after 8-min tPBM at 1064 nm or thermo_stim with temperature of 33–41 °C, respectively. After data preprocessing, EEG power spectral densities (PSD) per channel per subject were quantified and normalized by respective baseline PSD to remove the power-law effect. At the group level for each group, percent changes of EEG powers per channel were statistically compared between (1) tPBM vs light-stimulation sham, (2) thermo_stim vs heat-stimulation sham, and (3) tPBM vs thermo_stim after sham exclusion at five frequency bands using the non-parametric permutation tests. By performing the false discovery rate correction for multi-channel comparisons, we showed by EEG power change topographies that (1) tPBM significantly increased EEG alpha and beta powers, (2) the thermal stimulation created opposite effects on EEG power topographic patterns, and (3) tPBM and thermal stimulations induced significantly different topographies of changes in EEG alpha and beta power. Overall, this study provided evidence to support our hypothesis, showing that the laser-induced heat on the human forehead is not a mechanistic source causing increases in EEG power during and after tPBM.