bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Lagrangian Stochastic Model of a Volcanic Eruption Column
Authors: Devenish B. J. , Cerminara M. 
Published: March 2021

AbstractWe present a Lagrangian stochastic model (LSM) of a volcanic plume in which the mean flow is provided by an integral plume model of the eruption column and fluctuations in the vertical velocity are modeled by a suitably constructed stochastic differential equation. This model is based on that of Bisignano and Devenish (2015,http://doi.org/10.1007/s10546-015-0055-3) with the mean flow provided by the integral plume model of Devenish (2013,http://doi.org/10.1016/j.jvolgeores.2013.02.015). The LSM is applied to the two eruptions considered by Costa et al. (2016,http://doi.org/10.1016/j.jvolgeores.2016.01.017) for the volcanic‐plume intercomparison study with no ambient wind and to the hypothetical cases with ambient wind considered by Aubry et al. (2019,http://doi.org/10.1029/2019GL083975). Vertical profiles of the mass concentration computed from the LSM are compared with equivalent results from large eddy simulations (LES). The LSM captures the order of magnitude of the LES mass concentrations and aspects of their profiles: for example, in contrast with a standard integral plume model, that is, without fluctuations, the mass concentration computed from the LSM decays (to zero) toward the top of the plume consistent with the LES plumes. In the lower part of the plume, we show that the presence of ash leads to a peak in the mass concentration at the level at which there is a transition from a negatively buoyant jet to a positively buoyant plume. A quantitative analysis of the cases with ambient wind shows generally good agreement between the LSM and the LES for a number of quantities including the maximum concentration, the level at which it occurs, the maximum rise height, and the total erupted mass.
Towards automatic freeform optics design: coarse and fine search of the three-mirror solution space
Authors: Zhang Benqi , Jin Guofan , Zhu Jun 
Published: March 2021

AbstractDesign of an optical system, whether classic or novel, in the past or the present, requires significant effort from the designer. In addition to design methods and theories, the designer’s skills and experience in optical system design are particularly important, which may require years of practice to learn. The diversity and variety of results are limited because of the difficulty, time, and labor costs required. In this article, we propose an automatic design method for freeform optics that can achieve a diverse range of three-mirror designs. The optical specifications and the design constraints are the only inputs required, and a variety of results can be obtained automatically. The output results have various structures and various optical power distributions with high imaging qualities. By implementing the design method, designers can not only realize an overview of the solution space of the three-mirror freeform system, but can also focus on specific designs.
Cancer-associated fibroblasts-mediated ATF4 expression promotes malignancy and gemcitabine resistance in pancreatic cancer via the TGF-β1/SMAD2/3 pathway and ABCC1 transactivation
Authors: Wei Lusheng , Lin Qing , Lu Yanan , Li Guolin , Huang Leyi , Fu Zhiqiang , Chen Rufu , Zhou Quanbo 
Published: March 2021

AbstractCancer-associated fibroblasts (CAFs) contribute to malignant progression and chemoresistance in pancreatic ductal adenocarcinoma (PDAC). However, little is known about the underlying mechanism. In this study, we investigated the potential role and mechanisms of activating transcription factor 4 (ATF4) in CAFs-induced malignancy and gemcitabine resistance. We demonstrated that ATF4 is overexpressed in PDAC and associated with a poor prognosis. Silencing ATF4 expression decreased proliferation, colony formation, migration, gemcitabine sensitivity, and sphere formation. Subsequently, we revealed that CAFs secrete TGF-β1 to upregulate the expression of ATF4 in PDAC cells via the SMAD2/3 pathway and induce cancer progression, cancer stemness, and gemcitabine resistance. Furthermore, we demonstrated that ATF4 directly binds to the ABCC1 promoter region to activate transcription. In summary, these data demonstrate that CAFs contribute to malignancy and gemcitabine resistance in PDAC by upregulating the expression of ATF4 via the TGF-β1/SMAD2/3 axis and highlight that ATF4 is an attractive therapeutic target for combating gemcitabine resistance in PDAC.
HOXBLINC long non-coding RNA activation promotes leukemogenesis in NPM1-mutant acute myeloid leukemia
Authors: Zhu Ganqian , Luo Huacheng , Feng Yang , Guryanova Olga A. , Xu Jianfeng , Chen Shi , Lai Qian , Sharma Arati , Xu Bing , Zhao Zhigang , Feng Ru , Ni Hongyu , Claxton David , Guo Ying , Mesa Ruben A. , Qiu Yi , Yang Feng-Chun , Li Wei , Nimer Stephen D. , Huang Suming , Xu Mingjiang 
Published: March 2021

AbstractNucleophosmin (NPM1) is the most commonly mutated gene in acute myeloid leukemia (AML) resulting in aberrant cytoplasmic translocation of the encoded nucleolar protein (NPM1c+). NPM1c+ maintains a unique leukemic gene expression program, characterized by activation of HOXA/B clusters and MEIS1 oncogene to facilitate leukemogenesis. However, the mechanisms by which NPM1c+ controls such gene expression patterns to promote leukemogenesis remain largely unknown. Here, we show that the activation of HOXBLINC, a HOXB locus-associated long non-coding RNA (lncRNA), is a critical downstream mediator of NPM1c+-associated leukemic transcription program and leukemogenesis. HOXBLINC loss attenuates NPM1c+-driven leukemogenesis by rectifying the signature of NPM1c+ leukemic transcription programs. Furthermore, overexpression of HoxBlinc (HoxBlincTg) in mice enhances HSC self-renewal and expands myelopoiesis, leading to the development of AML-like disease, reminiscent of the phenotypes seen in the Npm1 mutant knock-in (Npm1c/+) mice. HoxBlincTg and Npm1c/+ HSPCs share significantly overlapped transcriptome and chromatin structure. Mechanistically, HoxBlinc binds to the promoter regions of NPM1c+ signature genes to control their activation in HoxBlincTg HSPCs, via MLL1 recruitment and promoter H3K4me3 modification. Our study reveals that HOXBLINC lncRNA activation plays an essential oncogenic role in NPM1c+ leukemia. HOXBLINC and its partner MLL1 are potential therapeutic targets for NPM1c+ AML.
Development of highly efficient platinum catalysts for hydroalkoxylation and hydroamination of unactivated alkenes
Authors: Zhou Yali , Xu Xingjun , Sun Hongwei , Tao Guanyu , Chang Xiao-Yong , Xing Xiangyou , Chen Bo , Xu Chen 
Published: March 2021

AbstractHydrofunctionalization, the direct addition of an X–H (e.g., X=O, N) bond across an alkene, is a desirable strategy to make heterocycles that are important structural components of naturally occurring molecules. Described here is the design and discovery of “donor–acceptor”-type platinum catalysts that are highly effective in both hydroalkoxylation and hydroamination of unactivated alkenes over a broad range of substrates under mild conditions. A number of alkene substitution patterns are accommodated, including tri-substituted, 1,1-disubstituted, (E)-disubstituted, (Z)-disubstituted and even mono-substituted double bonds. Detailed mechanistic investigations suggest a plausible pathway that includes an unexpected dissociation/re-association of the electron-deficient ligand to form an alkene-bound “donor–acceptor”-type intermediate. These mechanistic studies help understand the origins of the high reactivity exhibited by the catalytic system, and provide a foundation for the rational design of chiral catalysts towards asymmetric hydrofunctionalization reactions.
Application of chemometrics for modeling and optimization of ultrasound-assisted dispersive liquid–liquid microextraction for the simultaneous determination of dyes
Authors: Shojaei Siroos , Shojaei Saeed , Nouri Arezoo , Baharinikoo Leila 
Published: March 2021

AbstractAs the world population continues to grow, so does the pollution of water resources. It is, therefore, important to identify ways of reducing pollution as part of our effort to significantly increase the supply of clean and safer water. In this study, the efficiency of ultrasound-assisted dispersive liquid–liquid microextraction (UA-DLLME) as a fast, economical, and simple method for extraction malachite green (MG) and rhodamine B (RB) dyes from water samples is investigated. In optimal conditions, the linear dynamic range (LDR) for RB and MG is 7.5–1500 ng mL−1 and 12–1000 ng mL−1, respectively. The limit of detection (LOD) is 1.45 ng mL−1 and 2.73 ng mL−1, and limit of quantification (LOQ) is 4.83 ng mL−1 and 9.10 ng mL−1 for RB and MG, respectively. Extraction efficiency is obtained in the range of 95.53–99.60%. The relative standard deviations (RSD) in real water and wastewater samples are less than 3.5. The developed method is used successfully in the determination of RB and MG dyes from water samples and there are satisfactory results.
Solid state phase transformation kinetics in Zr-base alloys
Authors: Massih A. R. , Jernkvist Lars O. 
Published: March 2021

AbstractWe present a kinetic model for solid state phase transformation ($$\alpha \rightleftharpoons \beta$$

α
⇌
β

) of common zirconium alloys used as fuel cladding material in light water reactors. The model computes the relative amounts of $$\beta$$
β
or $$\alpha$$
α
phase fraction as a function of time or temperature in the alloys. The model accounts for the influence of excess oxygen (due to oxidation) and hydrogen concentration (due to hydrogen pickup) on phase transformation kinetics. Two variants of the model denoted by A and B are presented. Model A is suitable for simulation of laboratory experiments in which the heating/cooling rate is constant and is prescribed. Model B is more generic. We compare the results of our model computations, for both A and B variants, with accessible experimental data reported in the literature covering heating/cooling rates of up to 100 K/s. The results of our comparison are satisfactory, especially for model A. Our model B is intended for implementation in fuel rod behavior computer programs, applicable to a reactor accident situation, in which the Zr-based fuel cladding may go through $$\alpha \rightleftharpoons \beta$$

α
⇌
β

phase transformation.
Human health impact assessment and temporal distribution of trace elements in Copșa Mică- Romania
Authors: Bodor Katalin , Bodor Zsolt , Szép Alexandru , Szép Róbert 
Published: March 2021

AbstractThe present study aims to analyze the temporal variations of PM10 and to assess the health risk indexes caused by trace elements from particulate matter (PM10) via inhalation, ingestion, and dermal absorption by adults and children in Copșa Mică (Romania) during 2009–2019. The results revealed a high multi-annual mean concentration of PM10 and trace elements. The analyzed air pollutants showed a decreasing trend during the studied years, therefore 44.11%, 43.48%, 36.07%, 16.02%, and 15.80% lower values were observed for As, Cd, Ni, PM10, and Pb, respectively, due to environmental regulations. The daily exceedance percentage of Pb and Cd was very high, representing 21.74% and 11.26%, followed by PM10 and As concentrations with 4.72% and 3.92%. The ratio between the trace element concentration measured in Copșa Mică and the country average was 2.46, 4.01, 2.44 and 10.52 times higher for As, Cd, Ni and Pb. The calculated Hazard Quotient values via inhalation were higher than the safe limit (1), which accounted 1.81, 3.89 and 4.52, for As, Cd and Ni, respectively, indicating that the trace elements might present a non-carcinogenic risk to both adults and children. Furthermore, the concentration of all studied trace elements in Copșa Mică showed cancer risk for adults via inhalation and dermal absorption as well.
Ordinal classification of the affectation level of 3D-images in Parkinson diseases
Authors: Durán-Rosal Antonio M. , Camacho-Cañamón Julio , Gutiérrez Pedro Antonio , Guiote Moreno Maria Victoria , Rodríguez-Cáceres Ester , Vallejo Casas Juan Antonio , Hervás-Martínez César 
Published: March 2021

AbstractParkinson’s disease is characterised by a decrease in the density of presynaptic dopamine transporters in the striatum. Frequently, the corresponding diagnosis is performed using a qualitative analysis of the 3D-images obtained after the administration of$$^{123}$$123I-ioflupane, considering a binary classification problem (absence or existence of Parkinson’s disease). In this work, we propose a new methodology for classifying this kind of images in three classes depending on the level of severity of the disease in the image. To tackle this problem, we use an ordinal classifier given the natural order of the class labels. A novel strategy to perform feature selection is developed because of the large number of voxels in the image, and a method for generating synthetic images is proposed to improve the quality of the classifier. The methodology is tested on 434 studies conducted between September 2015 and January 2019, divided into three groups: 271 without alteration of the presynaptic nigrostriatal pathway, 73 with a slight alteration and 90 with severe alteration. Results confirm that the methodology improves the state-of-the-art algorithms, and that it is able to find informative voxels outside the standard regions of interest used for this problem. The differences are assessed by statistical tests which show that the proposed image ordinal classification could be considered as a decision support system in medicine.
Use of propensity score matching to create counterfactual group to assess potential HIV prevention interventions
Authors: Abaasa Andrew , Mayanja Yunia , Asiki Gershim , Price Matt A. , Fast Patricia E. , Ruzagira Eugene , Kaleebu Pontiano , Todd Jim 
Published: March 2021

AbstractThe design of HIV prevention trials in the context of effective HIV preventive methods is a challenge. Alternate designs, including using non-randomised ‘observational control arms’ have been proposed. We used HIV simulated vaccine efficacy trials (SiVETs) to show pitfalls that may arise from using such observational controls and suggest how to conduct the analysis in the face of the pitfalls. Two SiVETs were nested within previously established observational cohorts of fisherfolk (FF) and female sex workers (FSW) in Uganda. SiVET participants received a licensed Hepatitis B vaccine in a schedule (0, 1 and 6 months) similar to that for a possible HIV vaccine efficacy trial. All participants received HIV counselling and testing every quarter for one year to assess HIV incidence rate ratio (IRR) between SiVET and non-SiVET (observational data). Propensity scores, conditional on baseline characteristics were calculated for SiVET participation and matched between SiVET and non-SiVET in the period before and during the SiVET study. We compared IRR before and after propensity score matching (PSM). In total, 3989 participants were enrolled into observational cohorts prior to SiVET, (1575 FF prior to Jul 2012 and 2414 FSW prior to Aug 2014). SiVET enrolled 572 participants (Jul 2012 to Apr 2014 in FF and Aug 2014 to Apr 2017 in FSW), with 953 non-SiVET participants observed in the SiVET concurrent period and 2928 from the pre-SiVET period (before Jul 2012 in FF or before Apr 2014 in FSW). Imbalances in baseline characteristics were observed between SiVET and non-SiVET participants in both periods before PSM. Similarly, HIV incidence was lower in SiVET than non-SiVET; SiVET-concurrent period, IRR = 0.59, 95% CI 0.31–0.68, p = 0.033 and pre-SiVET period, IRR = 0.77, 95% CI 0.43–1.29, p = 0.161. After PSM, participants baseline characteristics were comparable and there were minimal differences in HIV incidence between SiVET and non-SiVET participants. The process of screening for eligibility for efficacy trial selects participants with baseline characteristics different from the source population, confounding any observed differences in HIV incidence. Propensity score matching can be a useful tool to adjust the imbalance in the measured participants’ baseline characteristics creating a counterfactual group to estimate the effect of interventions on HIV incidence.
Detection of extended spectrum beta-lactamase genes in Pseudomonas aeruginosa isolated from patients in rural Eastern Cape Province, South Africa
Authors: Hosu Mojisola C. , Vasaikar Sandeep D. , Okuthe Grace E. , Apalata Teke 
Published: March 2021

AbstractThe proliferation of extended spectrum beta-lactamase (ESBL) producing Pseudomonas aeruginosa represent a major public health threat. In this study, we evaluated the antimicrobial resistance patterns of P. aeruginosa strains and characterized the ESBLs and Metallo- β-lactamases (MBL) produced. Strains of P. aeruginosa cultured from patients who attended Nelson Mandela Academic Hospital and other clinics in the four district municipalities of the Eastern Cape between August 2017 and May 2019 were identified; antimicrobial susceptibility testing was carried out against thirteen clinically relevant antibiotics using the BioMérieux VITEK 2 and confirmed by Beckman autoSCAN-4 System. Real-time PCR was done using Roche Light Cycler 2.0 to detect the presence of ESBLs; blaSHV, blaTEM and blaCTX-M genes; and MBLs; blaIMP, blaVIM. Strains of P. aeruginosa demonstrated resistance to wide-ranging clinically relevant antibiotics including piperacillin (64.2%), followed by aztreonam (57.8%), cefepime (51.5%), ceftazidime (51.0%), piperacillin/tazobactam (50.5%), and imipenem (46.6%). A total of 75 (36.8%) multidrug-resistant (MDR) strains were observed of the total pool of isolates. The blaTEM, blaSHV and blaCTX-M was detected in 79.3%, 69.5% and 31.7% isolates (n = 82), respectively. The blaIMP was detected in 1.25% while no blaVIM was detected in any of the strains tested. The study showed a high rate of MDR P. aeruginosa in our setting. The vast majority of these resistant strains carried blaTEM and blaSHV genes. Continuous monitoring of antimicrobial resistance and strict compliance towards infection prevention and control practices are the best defence against spread of MDR P. aeruginosa.
Anti-estrogenic and anti-aromatase activities of citrus peels major compounds in breast cancer
Authors: El-Kersh Dina M. , Ezzat Shahira M. , Salama Maha M. , Mahrous Engy A. , Attia Yasmeen M. , Ahmed Mahmoud Salama , Elmazar Mohey M. 
Published: March 2021

AbstractEstrogen signaling is crucial for breast cancer initiation and progression. Endocrine-based therapies comprising estrogen receptor (ER) modulators and aromatase inhibitors remain the mainstay of treatment. This study aimed at investigating the antitumor potential of the most potent compounds in citrus peels on breast cancer by exploring their anti-estrogenic and anti-aromatase activities. The ethanolic extract of different varieties of citrus peels along with eight isolated flavonoids were screened against estrogen-dependent breast cancer cell lines besides normal cells for evaluating their safety profile. Naringenin, naringin and quercetin demonstrated the lowest IC50sand were therefore selected for further assays. In silico molecular modeling against ER and aromatase was performed for the three compounds. In vivo estrogenic and anti-estrogenic assays confirmed an anti-estrogenic activity for the isolates. Moreover, naringenin, naringin and quercetin demonstrated in vitro inhibitory potential against aromatase enzyme along with anticancer potential in vivo, as evidenced by decreased tumor volumes. Reduction in aromatase levels in solid tumors was also observed in treated groups. Overall, this study suggests an antitumor potential for naringenin, naringin and quercetin isolated from citrus peels in breast cancer via possible modulation of estrogen signaling and aromatase inhibition suggesting their use in pre- and post-menopausal breast cancer patients, respectively.
Applying a hierarchical clustering on principal components approach to identify different patterns of the SARS-CoV-2 epidemic across Italian regions
Authors: Maugeri Andrea , Barchitta Martina , Basile Guido , Agodi Antonella 
Published: March 2021

AbstractItaly has experienced the epidemic of Severe Acute Respiratory Syndrome Coronavirus 2, which spread at different times and with different intensities throughout its territory. We aimed to identify clusters with similar epidemic patterns across Italian regions. To do that, we defined a set of regional indicators reflecting different domains and employed a hierarchical clustering on principal component approach to obtain an optimal cluster solution. As of 24 April 2020, Lombardy was the worst hit Italian region and entirely separated from all the others. Sensitivity analysis—by excluding data from Lombardy—partitioned the remaining regions into four clusters. Although cluster 1 (i.e. Veneto) and 2 (i.e. Piedmont and Emilia-Romagna) included the most hit regions beyond Lombardy, this partition reflected differences in the efficacy of restrictions and testing strategies. Cluster 3 was heterogeneous and comprised regions where the epidemic started later and/or where it spread with the lowest intensity. Regions within cluster 4 were those where the epidemic started slightly after Veneto, Emilia-Romagna and Piedmont, favoring timely adoption of control measures. Our findings provide policymakers with a snapshot of the epidemic in Italy, which might help guiding the adoption of countermeasures in accordance with the situation at regional level.
Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study
Authors: Dou Qi , So Tiffany Y. , Jiang Meirui , Liu Quande , Vardhanabhuti Varut , Kaissis Georgios , Li Zeju , Si Weixin , Lee Heather H. C. , Yu Kevin , Feng Zuxin , Dong Li , Burian Egon , Jungmann Friederike , Braren Rickmer , Makowski Marcus , Kainz Bernhard , Rueckert Daniel , Glocker Ben , Yu Simon C. H. , Heng Pheng Ann 
Published: March 2021

AbstractData privacy mechanisms are essential for rapidly scaling medical training databases to capture the heterogeneity of patient data distributions toward robust and generalizable machine learning systems. In the current COVID-19 pandemic, a major focus of artificial intelligence (AI) is interpreting chest CT, which can be readily used in the assessment and management of the disease. This paper demonstrates the feasibility of a federated learning method for detecting COVID-19 related CT abnormalities with external validation on patients from a multinational study. We recruited 132 patients from seven multinational different centers, with three internal hospitals from Hong Kong for training and testing, and four external, independent datasets from Mainland China and Germany, for validating model generalizability. We also conducted case studies on longitudinal scans for automated estimation of lesion burden for hospitalized COVID-19 patients. We explore the federated learning algorithms to develop a privacy-preserving AI model for COVID-19 medical image diagnosis with good generalization capability on unseen multinational datasets. Federated learning could provide an effective mechanism during pandemics to rapidly develop clinically useful AI across institutions and countries overcoming the burden of central aggregation of large amounts of sensitive data.