bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incidentally discovered cold hemagglutinin disease with massive blood clots in the cardioplegia line and coronary artery, during coronary artery bypass graft
Authors: Chung Euysuk , Park Sungjoon , Lee Jaehoon 
Published: May 2020

Abstract
Background
Cold hemagglutinin disease (CHAD) is a rare autoimmune disease, in which patients manifest symptoms when the body temperature decreases. It causes critical problems with blood clotting and hemolysis during hypothermia in cardiac surgery. Although various methods are recommended, the CHAD discovered incidentally during cardiac surgery is still a clinical challenge.

Case presentation
A 76-year-old male visited our hospital for chest pain. Angiography revealed unstable angina, left-main and three-vessel disease. We performed coronary artery bypass graft (CABG) with cardiopulmonary bypass after heparin injection. Shortly after aorta cross-clamping (ACC) and infusion of cold blood cardioplegia, we found massive blood clots in the cardioplegia line. Upon suspicion of CHAD, we raised the temperature and infused warm blood cardioplegia in a retrograde manner. After performing cardiac arrest, we opened the coronary artery and found blood clots in the coronary artery. We eliminated the clots and washed with warm crystalloid cardioplegia simultaneously in an antegrade and retrograde manner. During the ACC, warm cardioplegia was infused every 15 min, via retrograde and antegrade techniques simultaneously. After distal anastomosis of the saphenous venous graft (SVG) to the coronary artery, we performed a direct SVG warm cardioplegia infusion. Finally, before the proximal SVG anastomosis to the aorta, we used warm cardioplegia to eliminate the remaining microemboli. The cold reactive protein test showed a positive result. The patient was discharged without any complications.

Conclusion
In this rare case, we incidentally discovered CHAD associated with massive blood clots in the cardioplegia line and the coronary artery, during CABG. However, we performed CABG without any complications using a reasonable and appropriate cardioplegia infusion technique, including direct SVG warm cardioplegia infusion.
Reduced complement of dopaminergic neurons in the substantia nigra pars compacta of mice with a constitutive “low footprint” genetic knockout of alpha-synuclein
Authors: Goloborshcheva Valeria V. , Chaprov Kirill D. , Teterina Ekaterina V. , Ovchinnikov Ruslan , Buchman Vladimir L. 
Published: May 2020

AbstractPrevious studies of the alpha-synuclein null mutant mice on the C57Bl6 genetic background have revealed reduced number of dopaminergic neurons in their substantia nigra pars compacta (SNpc). However, the presence in genomes of the studied mouse lines of additional genetic modifications that affect expression of genes located in a close proximity to the alpha-synuclein-encoding Snca gene makes these data open to various interpretations. To unambiguously demonstrate that the absence of alpha-synuclein is the primary cause of the observed deficit of dopaminergic neurons, we employed a recently produced constituent alpha-synuclein knockout mouse line B6(Cg)-Sncatm1.2Vlb/J. The only modification introduced to the genome of these mice is a substitution of the first coding exon and adjusted short intronic fragments of the Snca gene by a single loxP site. We compared the number of dopaminergic neurons in the SNpc of this line, previously studied B6(Cg)-Sncatm1Rosl/J line and wild type littermate mice. A similar decrease was observed in both knockout lines when compared with wild type mice. In a recently published study we revealed no loss of dopaminergic neurons following conditional inactivation of the Snca gene in neurons of adult mice. Taken together, these results strongly suggest that alpha-synuclein is required for efficient survival or maturation of dopaminergic neurons in the developing SNpc but is dispensable for survival of mature SNpc dopaminergic neurons.
ULK1 inhibition as a targeted therapeutic strategy for FLT3-ITD-mutated acute myeloid leukemia
Authors: Hwang Doh Yu , Eom Ju-In , Jang Ji Eun , Jeung Hoi-Kyung , Chung Haerim , Kim Jin Seok , Cheong June-Won , Min Yoo Hong 
Published: May 2020

Abstract
Background
In acute myeloid leukemia (AML), internal tandem duplication mutations in the FLT3 tyrosine kinase receptor (FLT3-ITD) are associated with a dismal outcome. Although uncoordinated 51-like kinase 1 (ULK1), which plays a central role in the autophagy pathway, has emerged as a novel therapeutic target for various cancers, its role in FLT3-ITD AML remains elusive. In this study, we evaluated the effects of ULK1 inhibition on leukemia cell death in FLT3-ITD AML.

Method
We evaluated ULK1 expression and the levels of apoptosis and autophagy following ULK1 inhibition in FLT3-ITD AML cell lines and investigated the mechanism underlying apoptosis induced by ULK1 inhibition. Statistical analysis was performed using GraphPad Prism 4.0 (GraphPad Software Inc).

Results
FLT3-ITD AML cells showed significantly higher ULK1 expression than FLT3-wild-type (WT) AML cells. Two ULK1 inhibitors, MRT 68921 and SBI-0206965, induced apoptosis in FLT3-ITD AML cells, with relatively minimal effects on FLT3-WT AML cells and normal CD34-positive cells. Apoptosis induction by ULK1 inhibition was associated with caspase pathway activation. Interestingly, ULK1 inhibition paradoxically also induced autophagy, showing synergistic interaction with autophagy inhibitors. Hence, autophagy may act as a prosurvival mechanism in FLT3-ITD AML cells. FLT3-ITD protein degradation and inhibition of the ERK, AKT, and STAT5 pathways were also observed in FLT3-ITD AML cells following treatment with ULK1 inhibitors.

Conclusion
ULK1 is a viable drug target and ULK1 inhibition may represent a promising therapeutic strategy against FLT3-ITD AML.
Activated CAMKKβ-AMPK signaling promotes autophagy in a spheroid model of ovarian tumour metastasis
Authors: Laski Jeremi , Singha Bipradeb , Wang Xu , Valdés Yudith Ramos , Collins Olga , Shepherd Trevor G. 
Published: May 2020

AbstractBackgroundA hallmark of epithelial ovarian cancer (EOC) metastasis is the process of spheroid formation, whereby tumour cells aggregate into 3D structures while in suspension in the peritoneal cavity. EOC spheroids are subjected to bioenergetic stress, thereby activating AMP-activated protein kinase (AMPK) signaling to enter a metabolically quiescent state, which can facilitate cell survival under nutrient-limiting conditions. Independently, we have also demonstrated that EOC spheroids induce autophagy, a process that degrades and recycles intracellular components to restore energy and metabolites. Herein, we sought to examine whether AMPK controls autophagy induction as a cell survival mechanism in EOC spheroids.ResultsWe observed a co-ordinate increase in phosphorylated AMPK and the autophagy marker LC3-II during EOC spheroid formation. Reduced AMPK expression by siRNA-mediated knockdown ofPRKAA1 and PRKAA2blocked autophagic flux in EOC spheroids as visualized by fluorescence microscopy using the mCherry-eGFP-LC3B reporter. A complementary approach using pharmacologic agents Compound C and CAMKKβ inhibitor STO-609 to inhibit AMPK activity both yielded a potent blockade of autophagic flux as well. However, direct activation of AMPK in EOC cells using oligomycin and metformin was insufficient to induce autophagy. STO-609 treatment of EOC spheroids resulted in reduced viability in 7 out of 9 cell lines, but with no observed effect in non-malignant FT190 cell spheroids.ConclusionsOur results support the premise that CAMKKβ-mediated AMPK activity is required, at least in part, to regulate autophagy induction in EOC spheroids and support cell viability in this in vitro model of EOC metastasis.
Brain natriuretic peptide to predict successful liberation from mechanical ventilation in critically ill patients: a systematic review and meta-analysis
Authors: Deschamps Jean , Andersen Sarah K. , Webber Jordan , Featherstone Robin , Sebastianski Meghan , Vandermeer Ben , Senaratne Janek , Bagshaw Sean M. 
Published: May 2020

Abstract
Background
Predicting successful liberation from mechanical ventilation (MV) in critically ill patients is challenging. Brain natriuretic peptide (BNP) has been proposed to help guide decision-making for readiness to liberate from MV following a spontaneous breathing trial (SBT).

Methods
We performed a systematic review and meta-analysis of randomized and prospective observational studies that measured BNP levels at the time of SBT in patients receiving MV. The primary endpoint was successful liberation from MV (absence of reintubation or non-invasive ventilation at 48 h). Statistical analyses included bi-variate and Moses-Littenberg models and DerSimonian-Laird pooling of areas under ROC curve (AUROC).

Results
A total of 731 articles were screened. Eighteen adult and 2 pediatric studies were fulfilled pre-specified eligibility. The measure of the relative variation of BNP during SBT (ΔBNP%) after exclusion of SBT failure by clinical criteria in adults yielded a sensitivity and specificity of 0.889 [0.831–0.929] and 0.828 [0.730–0.896] for successful liberation from MV, respectively, with a pooled AUROC of 0.92 [0.88–0.97]. The pooled AUROC for any method of analysis for absolute variation of BNP (ΔBNP), pre-SBT BNP, and post-SBT BNP were 0.89 [0.83–0.95], 0.77 [0.63–0.91], and 0.85 [0.80–0.90], respectively.

Conclusion
The relative change in BNP during a SBT has potential value as an incremental tool after successful SBT to predict successful liberation from MV in adults. There is insufficient data to support the use of BNP in children or as an alternate test to clinical indices of SBT, or the use of ΔBNP, BNP-pre, and BNP-post as an alternate or incremental test.

Trial registration
PROSPERO CRD42018087474 (6 February 2018)
Investigation of the adolescent female breast transcriptome and the impact of obesity
Authors: Burkholder Adam , Akrobetu Dennis , Pandiri Arun R. , Ton Kiki , Kim Sue , Labow Brian I. , Nuzzi Laura C. , Firriolo Joseph M. , Schneider Sallie S. , Fenton Suzanne E. , Shaw Natalie D. 
Published: May 2020

AbstractBackgroundEarly life environmental exposures affect breast development and breast cancer risk in adulthood. The breast is particularly vulnerable during puberty when mammary epithelial cells proliferate exponentially. In overweight/obese (OB) women, inflammation increases breast aromatase expression and estrogen synthesis and promotes estrogen-receptor (ER)-positive breast cancer. In contrast, recent epidemiological studies suggest that obesity during childhood decreases future breast cancer risk. Studies on environmental exposures and breast cancer risk have thus far been limited to animal models. Here, we present the first interrogation of the human adolescent breast at the molecular level and investigate how obesity affects the immature breast.MethodsWe performed RNA-seq in 62 breast tissue samples from adolescent girls/young women (ADOL; mean age 17.8 years) who underwent reduction mammoplasty. Thirty-one subjects were non-overweight/obese (NOB; mean BMI 23.4 kg/m2) and 31 were overweight/obese (OB; BMI 32.1 kg/m2). We also compared our data to published mammary transcriptome datasets from women (mean age 39 years) and young adult mice, rats, and macaques.ResultsThe ADOL breast transcriptome showed limited (30%) overlap with other species, but 88% overlap with adult women for the 500 most highly expressed genes in each dataset; only 43 genes were shared by all groups. In ADOL, there were 120 differentially expressed genes (DEG) in OB compared with NOB samples (padj < 0.05). Based on these DEG, Ingenuity Pathway Analysis (IPA) identified the cytokines CSF1 and IL-10 and the chemokine receptor CCR2 as among the most highly activated upstream regulators, suggesting increased inflammation in the OB breast. Classical ER targets (e.g., PR, AREG) were not differentially expressed, yet IPA identified the ER and PR and growth factors/receptors (VEGF, HGF, HER3) and kinases (AKT1) involved in hormone-independent ER activation as activated upstream regulators in OB breast tissue.ConclusionsThese studies represent the first investigation of the human breast transcriptome during late puberty/young adulthood and demonstrate that obesity is associated with a transcriptional signature of inflammation which may augment estrogen action in the immature breast microenvironment. We anticipate that these studies will prompt more comprehensive cellular and molecular investigations of obesity and its effect on the breast during this critical developmental window.
Constrained expectation maximisation algorithm for estimating ARMA models in state space representation
Authors: Galka Andreas , Moontaha Sidratul , Siniatchkin Michael 
Published: May 2020

AbstractThis paper discusses the fitting of linear state space models to given multivariate time series in the presence of constraints imposed on the four main parameter matrices of these models. Constraints arise partly from the assumption that the models have a block-diagonal structure, with each block corresponding to an ARMA process, that allows the reconstruction of independent source components from linear mixtures, and partly from the need to keep models identifiable. The first stage of parameter fitting is performed by the expectation maximisation (EM) algorithm. Due to the identifiability constraint, a subset of the diagonal elements of the dynamical noise covariance matrix needs to be constrained to fixed values (usually unity). For this kind of constraints, so far, no closed-form update rules were available. We present new update rules for this situation, both for updating the dynamical noise covariance matrix directly and for updating a matrix square-root of this matrix. The practical applicability of the proposed algorithm is demonstrated by a low-dimensional simulation example. The behaviour of the EM algorithm, as observed in this example, illustrates the well-known fact that in practical applications, the EM algorithm should be combined with a different algorithm for numerical optimisation, such as a quasi-Newton algorithm.
A new deep sparse autoencoder for community detection in complex networks
Authors: Fei Rong , Sha Jingyuan , Xu Qingzheng , Hu Bo , Wang Kan , Li Shasha 
Published: May 2020

AbstractFeature dimension reduction in the community detection is an important research topic in complex networks and has attracted many research efforts in recent years. However, most of existing algorithms developed for this purpose take advantage of classical mechanisms, which may be long experimental, time-consuming, and ineffective for complex networks. To this purpose, a novel deep sparse autoencoder for community detection, named DSACD, is proposed in this paper. In DSACD, a similarity matrix is constructed to reveal the indirect connections between nodes and a deep sparse automatic encoder based on unsupervised learning is designed to reduce the dimension and extract the feature structure of complex networks. During the process of back propagation, L-BFGS avoid the calculation of Hessian matrix which can increase the calculation speed. The performance of DSACD is validated on synthetic and real-world networks. Experimental results demonstrate the effectiveness of DSACD and the systematic comparisons with four algorithms confirm a significant improvement in terms of three indexFsame,NMI, and modularityQ. Finally, these achieved received signal strength indication (RSSI) data set can be aggregated into 64 correct communities, which further confirms its usability in indoor location systems.
Data assessment and prioritization in mobile networks for real-time prediction of spatial information using machine learning
Authors: Shinkuma Ryoichi , Nishio Takayuki , Inagaki Yuichi , Oki Eiji 
Published: May 2020

AbstractA new framework of data assessment and prioritization for real-time prediction of spatial information is presented. The real-time prediction of spatial information is promising for next-generation mobile networks. Recent developments in machine learning technology have enabled prediction of spatial information, which will be quite useful for smart mobility services including navigation, driving assistance, and self-driving. Other key enablers for forming spatial information are image sensors in mobile devices like smartphones and tablets and in vehicles such as cars and drones and real-time cognitive computing like automatic number/license plate recognition systems and object recognition systems. However, since image data collected by mobile devices and vehicles need to be delivered to the server in real time to extract input data for real-time prediction, the uplink transmission speed of mobile networks is a major impediment. This paper proposes a framework of data assessment and prioritization that reduces the uplink traffic volume while maintaining the prediction accuracy of spatial information. In our framework, machine learning is used to estimate the importance of each data element and to predict spatial information under the limitation of available data. A numerical evaluation using an actual vehicle mobility dataset demonstrated the validity of the proposed framework. Two extension schemes in our framework, which use the ensemble of importance scores obtained from multiple feature selection methods, are also presented to improve its robustness against various machine learning and feature selection methods. We discuss the performance of those schemes through numerical evaluation.
Inelastic strain in the hypocentral region of the 2000 Western Tottori earthquake (M 7.3) inferred from aftershock seismic moment tensors
Authors: Matsumoto Satoshi , Iio Yoshihisa , Sakai Shinichi , Kato Aitaro 
Published: May 2020

AbstractInelastic deformation due to seismic activity is an important signal that reflects fault evolution. In particular, aftershock sequences indicate the evolution of damage in a medium that has experienced a large earthquake. Herein, we discuss the inelastic strain rate surrounding the fault that produced the M 7.3 Western Tottori earthquake in 2000 using long-term aftershock analysis. To obtain high-resolution focal mechanisms 18 years after the earthquake occurrence, we conducted dense seismic observations in the focal area. The inelastic strain rate estimated from the aftershock seismic moment tensor data showed spatial variations within a range of 10−7–10−11 per year, 18 years after the main shock. By comparing the inelastic strain rates from immediately after the earthquake and 18 years later, we detected the increase in the spatial variations in the inelastic strain rate; the variations are as small as 102 (= 10−5/10−7) for the early stage but as large as 104 (= 10−7/10−11) for the later period. In addition, the decay of the rate during these two periods varied spatially from spatial bin to bin. Certain bins in the northern segment of the earthquake fault, southern edge of the fault, and surrounding the location of the preceding swarm activity to the M 7.3 event showed slower decay rates than the inverse of the lapse time since the occurrence of the M 7.3 earthquake. We modeled this decay rate change as the relaxation response of a power-law fluid to an elastic strain input from the large earthquake. Most parts of the fault can be explained by this model. However, the areas with low decay rates suggest the presence of a dragging mechanism, such as aseismic slip, at or around these locations.
Effect of flavophospholipol on fecal microbiota in weaned pigs challenged with Salmonella Typhimurium
Authors: Nair Saranya , Farzan Abdolvahab , Weese J. Scott , Poljak Zvonimir , Friendship Robert M. 
Published: May 2020

AbstractBackgroundThe heightened prevalence ofSalmonellaTyphimurium remains a public health and food safety concern. Studies have reported antibiotic, flavophospholipol, may have the ability to reduceSalmonellain swine, as well as alter the gut microbiota in favour of beneficial bacteria by inhibiting pathogenic bacteria. Thus, the objective of this study was to investigate the fecal microbiota of weaned pigs receiving in-feed flavophospholipol and challenged withSalmonellaTyphimurium.ResultsTwenty-one weaned pigs were fed either a diet containing 4 ppm of flavophospholipol (treatment group) or a non-medicated feed (control group) for 36 days post-weaning (Day 1 to Day 36). The pigs were orally challenged with a 2 mL dose of 108 CFU/mL ofS.Typhimurium at Day 7 and Day 8. Community bacterial DNA extracted from fecal samples collected at Day 6 (before challenge) and Day 36 (28 days after challenge) were used to assess the fecal microbiota using the V4 region of the 16S rRNA gene with Illumina MiSeq next-generation sequencing. Sequencing data were visualized using mothur and analyzed in JMP and R software. The fecal microbiota of pigs in the treatment group had differences in abundance of phyla (Firmicutes, Proteobacteria) and genera (Lactobacillus, Roseburia,Treponema,unclassified Ruminococcaceae,Blautia,Streptococcus,Megasphaera,Dorea,Sporobacter,Peptococcus, unclassified Firmicutes,ClostridiumIV andCampylobacter)when compared to pigs that were controls, 28 days after challenge withSalmonella(P < 0.05). Specifically, results demonstrated a significant increase in phylum Proteobacteria (P = 0.001) and decrease in Firmicutes (P = 0.012) and genusRoseburia(P = 0.003) in the treated pigs suggestive of possible microbial dysbiosis. An increased abundance of generaLactobacillus(P = 0.012) was also noted in the treated group in comparison to the control.ConclusionBased on these findings, it is difficult to conclude whether treatment with 4 ppm of flavophospholipol is promoting favorable indigenous bacteria in the pig microbiota as previous literature has suggested.
Development of a computerized adaptive test to assess entrepreneurial personality
Authors: Postigo Álvaro , Cuesta Marcelino , Pedrosa Ignacio , Muñiz José , García-Cueto Eduardo 
Published: May 2020

Abstract
Background/objective
Entrepreneurial behavior is of great importance nowadays owing to its significance in the generation of economic, social, personal, and cultural wellbeing. This behavior is influenced by cognitive and personality characteristics, as well as by socioeconomic and contextual factors. Entrepreneurial personality is made up of a set of psychological traits including self-efficacy, autonomy, innovation, internal locus of control, achievement motivation, optimism, stress tolerance, and risk-taking. The aim of this research is the development of a computerized adaptive test (CAT) to evaluate entrepreneurial personality.

Method
A bank of 120 items was created evaluating various aspects of the entrepreneurial personality. The items were calibrated with the Samejima Graded Response Model using a sample of 1170 participants (Mage = 42.34; SDage = 12.96).

Results
The bank of items had an essentially unidimensional fit to the model. The CAT exhibited high accuracy for evaluating a wide range of θ scores, using a mean of 16 items with a very low standard error (M = 0.157). Relative validity evidence for the CAT was obtained with two additional tests of entrepreneurial personality (the Battery for the Assessment of the Enterprising Personality and the Measure of Enterpreneurial Tendencies and Abilities), with correlations of .908 and .657, respectively.

Conclusions
The CAT developed has appropriate psychometric properties for the evaluation of entrepreneurial people.