bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exosomes released upon mitochondrial ASncmtRNA knockdown reduce tumorigenic properties of malignant breast cancer cells
Authors: Lobos-González Lorena , Bustos Rocío , Campos América , Silva Valeria , Silva Verónica , Jeldes Emanuel , Salomon Carlos , Varas-Godoy Manuel , Cáceres-Verschae Albano , Duran Eduardo , Vera Tamara , Ezquer Fernando , Ezquer Marcelo , Burzio Verónica A. , Villegas Jaime 
Published: January 2020

AbstractDuring intercellular communication, cells release extracellular vesicles such as exosomes, which contain proteins, ncRNAs and mRNAs that can influence proliferation and/or trigger apoptosis in recipient cells, and have been proposed to play an essential role in promoting invasion of tumor cells and in the preparation of metastatic niches. Our group proposed the antisense non-coding mitochondrial RNA (ASncmtRNA) as a new target for cancer therapy. ASncmtRNA knockdown using an antisense oligonucleotide (ASO-1537S) causes massive death of tumor cells but not normal cells and strongly reduces metastasis in mice. In this work, we report that exosomes derived from ASO-1537S-treated MDA-MB-231 breast cancer cells (Exo-1537S) inhibits tumorigenesis of recipient cells, in contrast to exosomes derived from control-ASO-treated cells (Exo-C) which, in contrast, enhance these properties. Furthermore, an in vivo murine peritoneal carcinomatosis model showed that Exo-1537S injection reduced tumorigenicity compared to controls. Proteomic analysis revealed the presence of Lactadherin and VE-Cadherin in exosomes derived from untreated cells (Exo-WT) and Exo-C but not in Exo-1537S, and the latter displayed enrichment of proteasomal subunits. These results suggest a role for these proteins in modulation of tumorigenic properties of exosome-recipient cells. Our results shed light on the mechanisms through which ASncmtRNA knockdown affects the preparation of breast cancer metastatic niches in a peritoneal carcinomatosis model.
Ocean Sensitivity to Periodic and Constant Volcanism
Authors: Dogar Muhammad Mubashar , Sato Tomonori , Liu Fei 
Published: January 2020

AbstractIt is strongly believed that the explosive eruptions produce negative radiative forcing that causes long-term perturbations in the ocean. Moreover, it is anticipated that a sporadic strong cooling should initiate more vigorous vertical mixing of the upper ocean, and therefore cools the ocean more effectively than a uniform radiative forcing. However, the long-term simulations show that on average the ocean heat content responses to periodic and constant forcings are comparable. To better understand this controversy and to better quantify the post-eruption oceanic response, we conducted two sets of parallel simulations, the first with a uniform/constant volcanic forcing and the second one with a periodic volcanic forcing of magnitude 1×, 5×, 10× and 30× of Pinatubo size eruption using Geophysical Fluid Dynamics Laboratory’s coupled model, CM2.1. We systematically compared the effect of periodic volcanic forcing with an equivalent time-average volcanic cooling. Our results reveal that on average, volcanic-induced perturbations in Ocean Heat Content (OHC), and sea-level rise (SLR) following uniform and periodic eruptions are almost identical. It further emphasizes that the strength of ocean heat uptake at different ocean depths is mainly driven by the strength of the Atlantic Meridional Overturning Circulation (AMOC). These findings are important for ocean initialization in long-term climate studies, and geoengineering applications. It would help to unfold uncertainties related to ocean relaxation process, heat storage, and redistribution.
The absence of intact polar lipid-derived GDGTs in marine waters dominated by Marine Group II: Implications for lipid biosynthesis in Archaea
Authors: Besseling Marc A. , Hopmans Ellen C. , Bale Nicole J. , Schouten Stefan , Damsté Jaap S. Sinninghe , Villanueva Laura 
Published: January 2020

AbstractThe marine pelagic archaeal community is dominated by three major groups, the marine group I (MGI) Thaumarchaeota, and the marine groups II and III (MGII and MGIII) Euryarchaeota. Studies of both MGI cultures and the environment have shown that the MGI core membrane lipids are predominantly composed of glycerol dibiphytanyl glycerol tetraether (GDGT) lipids and the diether lipid archaeol. However, there are no cultured representatives of MGII and III archaea and, therefore, both their membrane lipid composition and potential contribution to the marine archaeal lipid pool remain unknown. Here, we show that GDGTs present in suspended particulate matter of the (sub)surface waters of the North Atlantic Ocean and the coastal North Sea are derived from MGI archaea, and that MGII archaea do not significantly contribute to the pool of GDGTs and archaeol. This implies, in contrast to previous suggestions, that their lipids do not affect the widely used sea surface temperature proxy TEX86. These findings also indicate that MGII archaea are not able to produce any known archaeal lipids, implying that our understanding of the evolution of membrane lipid biosynthesis in Archaea is far from complete.
Metabolomics-Based Discovery of Molecular Signatures for Triple Negative Breast Cancer in Asian Female Population
Authors: Li Lixian , Zheng Xiaodong , Zhou Qi , Villanueva Nathaniel , Nian Weiqi , Liu Xingming , Huan Tao 
Published: January 2020

AbstractTriple negative breast cancer (TNBC) is a devastating cancer disease characterized by its poor prognosis, distinct metastatic patterns, and aggressive biological behavior. Research indicates that the prevalence and presentation of TNBC varies among races, with Asian TNBC patients more commonly presenting with large invasive tumors, high node positivity, and high histologic grade. In this work, we applied ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS)-based metabolomics to discover metabolic signatures in Asian female TNBC patients. Serum samples from 31 TNBC patients and 31 healthy controls (CN) were involved in this study. A total of 2860 metabolic features were detected in the serum samples. Among them, 77 metabolites, whose levels were significantly different between TNBC with CN, were confirmed. Using multivariate statistical analysis, literature mining, metabolic network and pathway analysis, we performed an in-depth study of the metabolic alterations in the Asian TNBC population. In addition, we discovered a panel of metabolic signatures that are highly correlated with the 5-year survival rate of the TNBC patients. This metabolomic study provides a better understanding of the metabolic details of TNBC in the Asian population.
Targeting redox metabolism: the perfect storm induced by acrylamide poisoning in the brain
Authors: Raldúa Demetrio , Casado Marta , Prats Eva , Faria Melissa , Puig-Castellví Francesc , Pérez Yolanda , Alfonso Ignacio , Hsu Chuan-Yu , Arick II Mark A. , Garcia-Reyero Natàlia , Ziv Tamar , Ben-Lulu Shani , Admon Arie , Piña Benjamin 
Published: January 2020

AbstractExposure to acrylamide may lead to different neurotoxic effects in humans and in experimental animals. To gain insights into this poorly understood type of neurotoxicological damage, we used a multi-omic approach to characterize the molecular changes occurring in the zebrafish brain exposed to acrylamide at metabolite, transcript and protein levels. We detected the formation of acrylamide adducts with thiol groups from both metabolites and protein residues, leading to a quasi-complete depletion of glutathione and to the inactivation of different components of the thioredoxin system. We propose that the combined loss-of-function of both redox metabolism-related systems configure a perfect storm that explains many acrylamide neurotoxic effects, like the dysregulation of genes related to microtubules, presynaptic vesicle alteration, and behavioral alterations. We consider that our mechanistical approach may help developing new treatments against the neurotoxic effects of acrylamide and of other neurotoxicants that may share its toxic mode of action.
Impact of contouring variability on oncological PET radiomics features in the lung
Authors: Yang F. , Simpson G. , Young L. , Ford J. , Dogan N. , Wang L. 
Published: January 2020

AbstractRadiomics features extracted from oncological PET images are currently under intense scrutiny within the context of risk stratification for a variety of cancers. However, the lack of robustness assessment poses problems for their application across institutions and for broader patient populations. The objective of the current study was to examine the extent to which radiomics parameters from oncological PET vary in response to manual contouring variability in lung cancer. Imaging data employed in the study consisted of 26 PET scans with lesions in the lung being created through the use of an anthropomorphic phantom in conjunction with Monte Carlo simulations. From each of the simulated lesions, 25 radiomics features related to the gray-level co-occurrence matrices (GLCOM), gray-level size zone matrices (GLSZM), and gray-level neighborhood difference matrices (GLNDM) were extracted from ground truth contour and from manual contours provided by 10 raters in regard to four intensity discretization schemes with number of gray levels of 32, 64, 128, and 256, respectively. The impact of interrater variability in tumor delineation upon the agreement between raters on radiomics features was examined via interclass correlation and leave-p-out assessment. Only weak and moderate correlations were found between segmentation accuracy as measured by the Dice coefficient and percent feature error from ground truth for the vast majority of the features being examined. GLNDM-based texture parameters emerged as the top performing category of radiomcs features in terms of robustness against contouring variability for discretization schemes engaging number of gray levels of 32, 64, and 128 while GLCOM-based parameters stood out for discretization scheme engaging 256 gray levels. How and to what extent interrater reliability of radiomics features vary in response to the number of raters were largely feature-dependent. It was concluded that impact of contouring variability on PET-based radiomics features is present to varying degrees and could be experienced as a barrier to convey PET-based radiomics research to clinical relevance.
Somatostatin receptor mediated targeting of acute myeloid leukemia by photodynamic metal complexes for light induced apoptosis
Authors: Vegi Naidu M. , Chakrabortty Sabyasachi , Zegota Maksymilian M. , Kuan Seah Ling , Stumper Anne , Rawat Vijay P. S. , Sieste Stefanie , Buske Christian , Rau Sven , Weil Tanja , Feuring-Buske Michaela 
Published: January 2020

AbstractAcute myeloid leukemia (AML) is characterized by relapse and treatment resistance in a major fraction of patients, underlining the need of innovative AML targeting therapies. Here we analysed the therapeutic potential of an innovative biohybrid consisting of the tumor-associated peptide somatostatin and the photosensitizer ruthenium in AML cell lines and primary AML patient samples. Selective toxicity was analyzed by using CD34 enriched cord blood cells as control. Treatment of OCI AML3, HL60 and THP1 resulted in a 92, and 99 and 97% decrease in clonogenic growth compared to the controls. Primary AML cells demonstrated a major response with a 74 to 99% reduction in clonogenicity in 5 of 6 patient samples. In contrast, treatment of CD34+ CB cells resulted in substantially less reduction in colony numbers. Subcellular localization assays of RU-SST in OCI-AML3 cells confirmed strong co-localization of RU-SST in the lysosomes compared to the other cellular organelles. Our data demonstrate that conjugation of a Ruthenium complex with somatostatin is efficiently eradicating LSC candidates of patients with AML. This indicates that receptor mediated lysosomal accumulation of photodynamic metal complexes is a highly attractive approach for targeting AML cells.
Long-lead Prediction of ENSO Modoki Index using Machine Learning algorithms
Authors: Pal Manali , Maity Rajib , Ratnam J. V. , Nonaka Masami , Behera Swadhin K. 
Published: January 2020

AbstractThe focus of this study is to evaluate the efficacy of Machine Learning (ML) algorithms in the long-lead prediction of El Niño (La Niña) Modoki (ENSO Modoki) index (EMI). We evaluated two widely used non-linear ML algorithms namely Support Vector Regression (SVR) and Random Forest (RF) to forecast the EMI at various lead times, viz. 6, 12, 18 and 24 months. The predictors for the EMI are identified using Kendall’s tau correlation coefficient between the monthly EMI index and the monthly anomalies of the slowly varying climate variables such as sea surface temperature (SST), sea surface height (SSH) and soil moisture content (SMC). The importance of each of the predictors is evaluated using the Supervised Principal Component Analysis (SPCA). The results indicate both SVR and RF to be capable of forecasting the phase of the EMI realistically at both 6-months and 12-months lead times though the amplitude of the EMI is underestimated for the strong events. The analysis also indicates the SVR to perform better than the RF method in forecasting the EMI.
Moderate Nrf2 Activation by Genetic Disruption of Keap1 Has Sex-Specific Effects on Bone Mass in Mice
Authors: Yin Yukun , Corry Kylie A. , Loughran John P. , Li Jiliang 
Published: January 2020

AbstractKeap1 is a negative controller of the transcription factor Nrf2 for its activity. The Keap1/Nrf2 signaling pathway has been considered as a master regulator of cytoprotective genes, and exists in many cell types including osteoblasts and osteoclasts. Our previous study shows Nrf2 deletion decreases bone formation. Recent studies show hyperactivation of Nrf2 causes osteopenia in Keap1−/− mice, and Keap1−/− osteoblasts have significantly less proliferative potential than Keap1+/− osteoblasts. We aimed to examine if moderate Nrf2 activation by disruption of Keap1 impacts bone metabolism. We examined bone phenotype of Keap1 heterozygotic mice (Ht) in comparison with Keap1 wild type (WT) mice. Deletion or knockdown of Keap1 enhanced the gene expression of Nrf2, ALP and wnt5a in cultured primary osteoblasts compared to WT control. In male mice, compared with their age-matched littermate WT controls, Keap1 Ht mice showed significant increase in bone formation rate (+30.7%, P = 0.0029), but did not change the ultimate force (P < 0.01). The osteoclast cell numbers (−32.45%, P = 0.01) and surface (−32.58%, P = 0.03) were significantly reduced by Keap1 deficiency in male mice. Compared to male WT mice, serum bone resorption marker in male Keap1 Ht mice was significantly decreased. Our data suggest that moderate Nrf2 activation by disruption of Keap1 improved bone mass by regulating bone remodeling in male mice.
Predicting success in the worldwide start-up network
Authors: Bonaventura Moreno , Ciotti Valerio , Panzarasa Pietro , Liverani Silvia , Lacasa Lucas , Latora Vito 
Published: January 2020

AbstractBy drawing on large-scale online data we are able to construct and analyze the time-varying worldwide network of professional relationships among start-ups. The nodes of this network represent companies, while the links model the flow of employees and the associated transfer of know-how across companies. We use network centrality measures to assess, at an early stage, the likelihood of the long-term positive economic performance of a start-up. We find that the start-up network has predictive power and that by using network centrality we can provide valuable recommendations, sometimes doubling the current state of the art performance of venture capital funds. Our network-based approach supports the theory that the position of a start-up within its ecosystem is relevant for its future success, while at the same time it offers an effective complement to the labour-intensive screening processes of venture capital firms. Our results can also enable policy-makers and entrepreneurs to conduct a more objective assessment of the long-term potentials of innovation ecosystems, and to target their interventions accordingly.
Assessment of the heavy metal bioremediation efficiency of the novel marine lactic acid bacterium, Lactobacillus plantarum MF042018
Authors: Ameen Fatma A. , Hamdan Amira M. , El-Naggar Moustafa Y. 
Published: January 2020

AbstractHeavy metal pollution is one of the most serious environmental and human health risk problem associated with industrial progress. The present study was conducted with the goal of isolation and characterization of metal-resistant lactic acid bacteria (LAB) from the Alexandrian Mediterranean Seacoast, Egypt, with their possible exploitation in metal remediation. Lactobacillus plantarum MF042018 exhibited high degree of resistance, up to 500 and 100 ppm, to both nickel and chromium, respectively, with multiple antibiotic resistance (MAR) index above 0.5. In an attempt to improve chromium removal by L. plantarum MF042018, Plackett-Burman followed by Box-Behnken statistical designs were applied. An initial Cr2+ concentration of 100 ppm and inoculum size of 3% presented the best conditions for the accumulation of chromium by L. plantarum MF042018. The study was also navigated to assess the biosorption capacity of L. plantarum MF042018, the maximum uptake capacity (q) of both Cd2+ and Pb2+ was recorded at pH 2.0 and a temperature of 22 °C after 1 hr. The biosorption process of Cd2+ and Pb2+ was well explained by the Langmuir isotherm model better than the Freundlich isotherm. Furthermore, the results revealed that the use of L. plantarum MF042018 is an effective tool for the treatment of hazardous metal-polluted battery-manufacturing effluent. Therefore, the present study implies that L. plantarum MF042018 can be applied as a promising biosorbent for the removal of heavy metals from industrial wasterwaters.
Synthesis of Au/SnO2 nanostructures allowing process variable control
Authors: Choi Myung Sik , Na Han Gil , Kim Sangwoo , Bang Jae Hoon , Oum Wansik , Choi Sun-Woo , Kim Sang Sub , Lee Kyu Hyoung , Kim Hyoun Woo , Jin Changhyun 
Published: January 2020

AbstractTheoretical advances in science are inherently time-consuming to realise in engineering, since their practical application is hindered by the inability to follow the theoretical essence. Herein, we propose a new method to freely control the time, cost, and process variables in the fabrication of a hybrid featuring Au nanoparticles on a pre-formed SnO2 nanostructure. The above advantages, which were divided into six categories, are proven to be superior to those achieved elsewhere, and the obtained results are found to be applicable to the synthesis and functionalisation of other nanostructures. Furthermore, the reduction of the time-gap between science and engineering is expected to promote the practical applications of numerous scientific theories.
Defect states and kinetic parameter analysis of ZnAl2O4 nanocrystals by X-ray photoelectron spectroscopy and thermoluminescence
Authors: Jain Megha , Manju  , Kumar Ravi , Won Sung Ok , Chae Keun Hwa , Vij Ankush , Thakur Anup 
Published: January 2020

AbstractDefect states in ZnAl2O4 have a significant role in its applicability as a luminescent material. To understand the nature and distribution of defects in its crystal lattice, thermoluminescence (TL) study has been carried out. Excellent TL response is observed from γ- and ultraviolet-irradiated samples at different doses and exposure durations, respectively. Different type of fuels employed in combustion synthesis show a remarkable effect on the trap distribution and hence luminescence properties. Shallow and deep traps are observed in crystals attributed to O− vacancies and F+ centers. The mechanism of trapping, retrapping and recombination have been depicted through schematic band model diagram. X-ray photoelectron spectroscopy indicated the presence of various types of defects specifically AlZn antisite defect, oxygen and zinc vacancies which are further upheld by photoluminescence and Raman spectroscopy. All results when summed up, predict ZnAl2O4 to be a quality material for dosimetry.
Retrospective analysis of clinical phenotype and prognosis of hypertrophic cardiomyopathy complicated with hypertension
Authors: Luo Qin , Chen Jin , Zhang Tianhua , Tang Xiaoyu , Yu Bilian 
Published: January 2020

AbstractWe here studied the clinical features, cardiac structure, and functional changes and prognosis of hypertrophic cardiomyopathy (HCM) patients with hypertension (HTN). A total of 90 HCM patients with HTN and 172 patients without HTN were divided into a hypertensive group and non-hypertensive group. The clinical characteristics, cardiac structure and function, and prognosis of the two groups were compared. Our study found that HCM patients with HTN had fewer syncope events in their medical histories (8% vs. 22%, P < 0.01) and sudden deaths in the family (3% vs. 10%, P < 0.05). The prevalence of apical hypertrophy (18% vs. 7%, P < 0.01) and midventricular obstruction (26% vs. 15%, P < 0.05) was higher in the HTN group. Besides, simple HCM patients had more pathogenic gene mutations, while those with HTN were more likely to have mutations of uncertain clinical significance (64% vs. 24%, P < 0.05). Evaluation of 5-year survival rate showed a trend for a worse prognosis in HCM patients with HTN, but the results were not statistically insignificant (P = 0.065). In conclusion, we found that the clinical phenotypes of HCM patients with HTN differed from those of patients with HCM alone, suggesting that HTN may play a pathogenic role in the pathogenesis of hypertensive hypertrophic cardiomyopathy patients.
Degeneracy in the emergence of spike-triggered average of hippocampal pyramidal neurons
Authors: Jain Abha , Narayanan Rishikesh 
Published: January 2020

AbstractHippocampal pyramidal neurons are endowed with signature excitability characteristics, exhibit theta-frequency selectivity — manifesting as impedance resonance and as a band-pass structure in the spike-triggered average (STA) — and coincidence detection tuned for gamma-frequency inputs. Are there specific constraints on molecular-scale (ion channel) properties in the concomitant emergence of cellular-scale encoding (feature detection and selectivity) and excitability characteristics? Here, we employed a biophysically-constrained unbiased stochastic search strategy involving thousands of conductance-based models, spanning 11 active ion channels, to assess the concomitant emergence of 14 different electrophysiological measurements. Despite the strong biophysical and physiological constraints, we found models that were similar in terms of their spectral selectivity, operating mode along the integrator-coincidence detection continuum and intrinsic excitability characteristics. The parametric combinations that resulted in these functionally similar models were non-unique with weak pair-wise correlations. Employing virtual knockout of individual ion channels in these functionally similar models, we found a many-to-many relationship between channels and physiological characteristics to mediate this degeneracy, and predicted a dominant role for HCN and transient potassium channels in regulating hippocampal neuronal STA. Our analyses reveals the expression of degeneracy, that results from synergistic interactions among disparate channel components, in the concomitant emergence of neuronal excitability and encoding characteristics.