bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical effects of cardiac contractility modulation in heart failure with mildly reduced systolic function
Authors: Tschöpe Carsten , Butler Javed , Farmakis Dimitrios , Morley Deborah , Rao Ishu , Filippatos Gerasimos 
Published: December 2020

AbstractAimsIncreasing attention is being given to patients with heart failure and ‘mid‐range’ left ventricular ejection fraction (LVEF, ≥40% and <50%) for whom there are no approved therapies that improve prognosis. We aim to assess for the first time the effects of cardiac contractility modulation (CCM) therapy in this patient population.Methods and resultsWe assessed the effects of 6‐ month CCM therapy on functional status, exercise tolerance and quality of life in a subgroup of 53 patients with a LVEF of 40–45% recruited in previous CCM studies, including 37 patients in the CCM group and 16 in the control group. New York Heart Association classification improved by ≥1 class from baseline to 24 weeks in 80.6% (95% confidence interval [62.5%, 92.5%]) of patients in the CCM group compared with 57.1% in the control group (95% confidence interval [28.9%, 82.3%], P = 0.15). Six‐minute walk distance increased significantly in the CCM group with a net between‐group treatment effect of 53.9 ± 74.2 m (P = 0.05). Peak VO2 improved in the CCM group with a net between‐group treatment effect of 2.0 ± 2.8 mL/kg/min (P = 0.02). Minnesota Living with Heart Failure Questionnaire score decreased from baseline to 24 weeks with a net between‐group treatment effect of −13.1 ± 21.0 (P = 0.10). There were no significant differences in the adverse event rate between the CCM and control groups.ConclusionsThese preliminary results suggest that CCM exerts favourable effects on exercise tolerance and quality of life in patients with LVEF in the range of 40–45% with an acceptable safety profile. Further randomized controlled studies are planned to prove these effects.
Metabolomic and kinetic investigations on the electricity‐aided production of butanol by Clostridium pasteurianum strains
Authors: Arbter Philipp , Sabra Wael , Utesch Tyll , Hong Yaeseong , Zeng An‐Ping 
Published: December 2020

AbstractIn this contribution, we studied the effect of electro‐fermentation on the butanol production of Clostridium pasteurianum strains by a targeted metabolomics approach. Two strains were examined: an electrocompetent wild type strain (R525) and a mutant strain (dhaB mutant) lacking formation of 1,3‐propanediol (PDO). The dhaB‐negative strain was able to grow on glycerol without formation of PDO, but displayed a high initial intracellular NADH/NAD ratio which was lowered subsequently by upregulation of the butanol production pathway. Both strains showed a 3–5 fold increase of the intracellular NADH/NAD ratio when exposed to cathodic current in a bioelectrochemical system (BES). This drove an activation of the butanol pathway and resulted in a higher molar butanol to PDO ratio for the R525 strain. Nonetheless, macroscopic electron balances suggest that no significant amount of electrons derived from the BES was harvested by the cells. Overall, this work points out that electro‐fermentation can be used to trigger metabolic pathways and improve product formation, even when the used microbe cannot be considered electroactive. Accordingly, further studies are required to unveil the underlying (regulatory) mechanisms.
Parameter and state estimation of backers yeast cultivation with a gas sensor array and unscented Kalman filter
Authors: Yousefi‐Darani Abdolrahimahim , Paquet‐Durand Olivier , Hinrichs Jörg , Hitzmann Bernd 
Published: December 2020

AbstractReal‐time information about the concentrations of substrates and biomass is the key to accurate monitoring and control of bioprocess. However, on‐line measurement of these variables is a challenging task and new measurement systems are still required. An alternative are software sensors, which can be used for state and parameter estimation in bioprocesses. The software sensors predict the state of the process by using mathematical models as well as data from measured variables. The Kalman filter is a type of such sensors.In this paper, we have used the Unscented Kalman Filter (UKF) which is a nonlinear extension of the Kalman filter for on‐line estimation of biomass, glucose and ethanol concentration as well as for estimating the growth rate parameters in S. cerevisiae batch cultivation, based on infrequent ethanol measurements. The UKF algorithm was validated on three different cultivations with variability of the substrate concentrations and the estimated values were compared to the off‐line values.The results obtained showed that the UKF algorithm provides satisfactory results with respect to estimation of concentrations of substrates and biomass as well as the growth rate parameters during the batch cultivation.
Morphology and evolution of supraglacial hummocks on debris‐covered Himalayan glaciers
Authors: Bartlett Oliver T. , Ng Felix S.L. , Rowan Ann V. 
Published: December 2020

AbstractThick supraglacial debris layers often have an undulating, hummocky topography that influences the lateral transport of debris and meltwater and provides basins for supraglacial ponds. The role of ablation and other processes associated with supraglacial debris in giving rise to this hummocky topography is poorly understood. Characterizing hummocky topography is a first step towards understanding the feedbacks driving the evolution of debris‐covered glacier surfaces and their potential impacts on mass balance, hydrology and glacier dynamics. Here we undertake a geomorphological assessment of the hummocky topography on five debris‐covered glaciers in the Everest region of the central Himalaya. We characterize supraglacial hummocks through statistical analyses of their vertical relief and horizontal geometry. Our results establish supraglacial hummocks as a distinct landform. We find that a typical hummock has an elongation ratio of 1.1:1 in the direction of ice flow, length of 214 ± 109 m and width of 192 ± 88 m. Hummocky topography has a greater amplitude across‐glacier (15.4 ± 10.9 m) compared to along the glacier flow line (12.6 ± 8.3 m). Consequently, hummock slopes are steeper in the across‐glacier direction (8.7 ± 4.3°) than in the direction of ice flow (5.6 ± 4.0°). Longer, wider and higher‐amplitude hummocks are found on larger glaciers. We postulate that directional anisotropy in the hummock topography arises because, while the pattern of differential ablation driving topography evolution is moderated by processes including the gravitational redistribution of debris across the glacier surface, it also inherits an orientation preference from the distribution of englacial debris in the underlying ice. Our morphometric data inform future efforts to model these interactions, which should account for additional factors such as the genesis of supraglacial ponds and ice cliffs and their impact on differential ablation.
A new reconstruction of numerical fluxes for conservation laws using fuzzy operators
Authors: Lochab Ruchika , Kumar Vivek 
Published: December 2020

AbstractThis article develops a new hybrid flux‐limited scheme for a numerical solution of the hyperbolic conservation laws by applying fuzzy logic‐based operator functions. The construction of the proposed flux‐limiter is explored using a fuzzy modifier function, having a suitable intensity. The purpose of this article is to present an efficient finite volume flux‐limited technique, derived from an entirely different subject of fuzzy mathematics, for tackling hyperbolic partial differential equations. Several standard test cases in one and two dimensions are solved numerically for demonstrating the robustness of the proposed new hybrid flux‐limited scheme.
Risk factors for subsequent recurrence after surgical treatment of recurrent pleomorphic adenoma of the parotid gland
Authors: Rooker Steven A. , Van Abel Kathryn M. , Yin Linda X. , Nagelschneider Alex A. , Price Daniel L. , Olsen Kerry D. , Janus Jeffrey R. , Kasperbauer Jan L. , Moore Eric J. 
Published: December 2020

AbstractBackgroundRecurrent pleomorphic adenoma (PA) can be a lifelong disease, and rates of subsequent recurrence are high.MethodsPatients between 2000 and 2015 were identified. Primary outcome was subsequent recurrence after surgical salvage.ResultsTwenty‐seven of 84 patients developed a subsequent recurrence. Risk factors for subsequent recurrence included a higher number of previous recurrences (P < .01), worse preoperative facial nerve function (P < .01), and deep parotid lesion(s) (P < .01). Interval since last surgery was protective (P < .01), specifically >10 years since last surgery (P < .01). For patients with a >10‐year interval since their last surgery, the subsequent recurrence‐free rate at 10 years follow‐up was 80.2% vs 31.8%.ConclusionsFor patients presenting with a >10‐year interval since their last surgery, subsequent recurrence rates are low, which may allow for as needed surveillance recommendations. For patients presenting with recurrent PA and ≤10 years since their last surgery, a closer surveillance is warranted.
Unsteady flow and heat transfer of tangent‐hyperbolic fluid: Legendre wavelet‐based analysis
Authors: Usman Muhammad , Zubair Tamour , Hamid Muhammad , Haq Rizwan Ul , Khan Zafar Hayat 
Published: December 2020

AbstractThe objective of the current article is to explore the unsteady flow and heat transfer of magnetohydrodynamics tangent‐hyperbolic fluid flow over a stretching sheet. The governing flow model is transformed into a nonlinear set of ordinary differential equations by utilizing the appropriate similarity techniques. A new modification is introduced into the traditional Legendre wavelet method to obtain the results of the model mentioned above. The classic wavelet scheme is unable to find the solution for an infinite domain. Hence, we successfully extended it for an infinite domain and used it to attain the significant findings of the fluid problem. Additionally, the study of emerging parameters on temperature and velocity profiles is reported graphically. The velocity behavior is decreasing for the physical parameters, namely, power‐lax index, unsteadiness, Hartmann number, and Weissenberg number. The temperature profile is an increasing function for power‐law index and Eckert number while the behavior is the opposite for the Prandtl number. Moreover, a tabular form comparison of outcomes with existing literature, convergence, and error analysis is provided in our study, which confirms the credibility of the suggested method. The obtained results endorse the credibility and reliability of the proposed method; therefore, it could be extended for other nonlinear problems of complex nature.
Multiregional assessment of CIMP in primary colorectal cancers: Phenotype concordance but marker variability
Authors: Flatin Bjørnar T.B. , Vedeld Hege Marie , Pinto Rita , Langerud Jonas , Lind Guro E. , Lothe Ragnhild A. , Sveen Anita , Jeanmougin Marine 
Published: December 2020

AbstractIntratumor heterogeneity of colorectal cancers (CRCs) is manifested both at the genomic and epigenomic levels. Early genetic aberrations in carcinogenesis are clonal and present throughout the tumors, but less is known about the heterogeneity of the epigenetic CpG island methylator phenotype (CIMP). CIMP characterizes a subgroup of CRCs thought to originate from specific precursor lesions, and it is defined by widespread DNA methylation within promoter regions. In this work, we investigated CIMP in two to four multiregional samples from 30 primary tumors (n = 86 samples) using the consensus Weisenberger gene panel (CACNA1G, IGF2, NEUROG1, RUNX3 and SOCS1). Twenty‐nine of 30 tumors (97%) showed concordant CIMP status in all samples, and percent methylated reference (PMR) values of all five markers had higher intertumor than intratumor variation (P value = 1.5e−09). However, a third of the CIMP+ tumors exhibited discrepancies in methylation status in at least one of the five gene markers. To conclude, CIMP status was consistent within primary CRCs, and it is likely a clonal phenotype. However, spatial discordances of the individual genes suggest that large‐scale analysis of multiregional samples could be of interest for identifying CIMP markers that are robust to intratumor heterogeneity.
Deep learning‐assisted magnetic resonance imaging prediction of tumor response to chemotherapy in patients with colorectal liver metastases
Authors: Zhu Hai‐Bin , Xu Da , Ye Meng , Sun Li , Zhang Xiao‐Yan , Li Xiao‐Ting , Nie Pei , Xing Bao‐Cai , Sun Ying‐Shi 
Published: December 2020

AbstractAccurate evaluation of tumor response to preoperative chemotherapy is crucial for assigning appropriate patients with colorectal liver metastases (CRLM) to surgery or conservative therapy. However, there is no well‐recognized method for predicting pathological response before surgery. Our study constructed and validated a deep learning algorithm using prechemotherapy and postchemotherapy magnetic resonance imaging (MRI) to predict pathological response in CRLM. CRLM patients from center one who had ≤5 lesions and were scheduled to receive preoperative chemotherapy followed by liver resection between January 2013 and November 2016, were included prospectively and chronologically divided into a training cohort (80% of patients) and a testing cohort (20% of patients). Patients from center two were included January 2017 and December 2018 as an external validation cohort. MRI‐based models were constructed to discriminate according to pathology tumor regression grade (TRG) between the response (TRG1/2) and nonresponse (TRG3/4/5) groups at the lesion level. From center one, 155 patients (328 lesions) were included; chronologically, 101 (264 lesions) in the training cohort and 54 (64 lesions) in the testing cohort. The model achieved better accuracy (0.875 vs 0.578) and AUC (0.849 vs 0.615) than RECIST for discriminating response; it also distinguished the survival outcomes after hepatectomy better than the RECIST criteria. Evaluations of the external validation cohort (25 patients, 61 lesions) also showed good ability with an AUC of 0.833. In conclusion, the MRI‐based deep learning model provided accurate prediction of pathological tumor response to preoperative chemotherapy in patients with CRLM and may inform individualized treatment.
Optimized segmentation and classification for liver tumor segmentation and classification using opposition‐based spotted hyena optimization
Authors: Rela Munipraveena , Nagaraja Rao Suryakari , Ramana Reddy Patil 
Published: December 2020

AbstractIn today's world, liver cancers are one of the mainly popular cancers occurring in the human body. The greater part of liver carcinomas is more prone to alcohol‐related hepatitis and cirrhosis conditions. Moreover, there is another form of cancer namely, metastatic liver cancer, where the tumor is initiated from other organs and extends to the liver. Early and premature diagnosis of liver cancer is necessary as it tends to improvise life expectancy. Nowadays, discriminating the liver and tumor parts from medical images with the aid of completely automated computer‐aided software is a more challenging task, since the liver disease can vary from person to person. This article attempts to implement the novel liver tumor segmentation and classification model using the optimization driven segmentation and classification model. The developed model carries out the task in five steps (a) Pre‐processing, (b) liver segmentation, (c) tumor segmentation, (d) feature extraction, and (e) classification. At first, the gathered CT images are subjected to pre‐processing with three steps that follow contrast enhancement by histogram equalization and noise filtering by the median filter. Next to the pre‐processing of the image, the liver is segmented from the CT abdominal image using adaptive thresholding pursued by level set segmentation. Further, a modified algorithm termed as Fuzzy Centroid‐based Region Growing Algorithm with tolerance optimization is developed and used for the tumor segmentation. From the segmented tumor image, three sets of features like gray‐level co‐occurrence matrix (GLCM), shape features, and local binary pattern (LBP) is utilized for the classifier training. In the classification side, two deep learning algorithms are used: recurrent neural network (RNN), and convolutional neural network (CNN). The tumor segmented image is given as input to the CNN, and the extracted features are given as input to the RNN. As an improvement, an optimized hybrid classifier is adopted for the hidden neuron optimization. Moreover, an improved meta‐heuristic algorithm called opposition‐based spotted hyena optimization (O‐SHO) is introduced to perform the optimized segmentation and classification. The experimental results show that the overall accuracy attained by the proposed model is efficient, less sensitive to noise, and performs superior on a diverse set of CT images.
In vitro and in vivo comparative performance studies of gadolinium‐loaded zeolites and Gd‐DOTA as contrast agents for MRI applications
Authors: Contro Janine , Silva Danilo Antonio , Santisteban Oscar A. N. , Narayana Ponnada A. , Nery José G. 
Published: December 2020

AbstractGadolinium‐based contrast agents (CAs) were synthesized using faujasite zeolite (NaX) and zeolite beta (BEA) and their performances in vitro and in vivo were compared to the widely used commercial CA, gadoteric acid (Gd‐DOTA). Magnetic resonance imaging (MRI) relaxometry studies (considering longitudinal [T1] and transverse [T2] relaxation times) were performed using Gd‐DOTA and the zeolitic materials loaded with Gd3+. The Gd‐loaded NaX, which presented large pores and cavities (7.35 and 11.24 Å, respectively), exhibited relaxivity values of around 52 mM−1 s−1, while BEA, which presented smaller pore and cavity diameters (5.95 and 6.68 Å, respectively) showed lower relaxivity values of ~4.8 mM−1 s−1. The effect of the Gd‐loaded NaX as MRI CA was tested in vivo in Sprague–Dawley rats, employing a 7 T scanner, with comparison to Gd‐DOTA MRI angiography. The relaxivity measurements showed that the Gd‐loaded NaX (50 mM−1 s−1) provided better image contrast than Gd‐DOTA (5.1 mM−1 s−1). Clearance studies of the CAs using urine and blood showed that both Gd‐loaded NaX and Gd‐DOTA were eliminated from the body after 2 days, demonstrating the potential of Gd‐loaded NaX for use as an MRI CA.
Bone Mineral Density in Antiretroviral Therapy‐Naïve HIV‐1–Infected Young Adult ‐Women Using Depot Medroxyprogesterone Acetate or Nonhormonal Contraceptives in Uganda
Authors: Matovu Flavia Kiweewa , Nabwana Martin , Kiwanuka Noah , Scholes Delia , Isingel Esther , Nolan Monica L , Fowler Mary G , Musoke Philippa , Pettifor John M , Brown Todd T , Beksinska Mags E ,   for the BONE CARE Study Team
Published: December 2020

ABSTRACTMost studies evaluating BMD in human immunodeficiency virus (HIV)‐infected populations have focused on antiretroviral therapy (ART)‐experienced patients. In this study, the association between HIV‐1 and/or depot medroxyprogesterone acetate (DMPA) and BMD among untreated HIV‐1–infected women in a resource‐limited setting was assessed before long‐term exposure to ART. The data were then compared with that of the 2005–2008 United States National Health and Nutrition Examination Survey data for non‐Hispanic White and Black women. Women aged 18–35 years, recruited from health facilities in Kampala, Uganda, were classified based on their combination of HIV‐1 status and DMPA use: (i) HIV‐1–infected current DMPA users, (ii) HIV‐1–infected previous DMPA users, (iii) HIV‐1–infected nonhormonal‐contraceptive users, and (iv) HIV‐uninfected nonhormonal‐contraceptive users. All HIV‐1–infected women reported being ART‐naïve at baseline. BMD was measured at the lumbar spine, total hip, and femoral neck using DXA. Multivariate linear regression was used to assess the association between HIV‐1 and/or DMPA and BMD Z‐scores. Baseline data were analyzed for 452 HIV‐1–infected (220 nonhormonal users, and 177 current and 55 previous DMPA users) and 69 HIV‐1–uninfected nonhormonal‐contraceptive users. The mean age was 26.1 years (SD, 4.2) with a median duration of DMPA use among current users of 24.0 months [medians (interquartile range), 12‐48]. A higher proportion of HIV‐1–infected previous (12.7%) or current DMPA users (20.3%) and nonhormonal users (15.0%) had low BMD (Z‐score ≤−2 at any of the three sites) compared with age‐matched HIV‐1–uninfected women (2.9%). HIV‐1 infection and DMPA use were independently associated with significantly lower mean BMD Z‐scores at all sites, with the greatest difference being among HIV‐1–infected current DMPA users (5.6%–8.0%) versus uninfected nonhormonal users. Compared with non‐Hispanic White and Black women, the Ugandan local reference population had generally lower mean BMD at all sites. Newer treatment interventions are needed to mitigate BMD loss in HIV‐1–infected women in resource‐limited settings. © 2020 The Authors. JBMR Plus published by Wiley Periodicals LLC. on behalf of American Society for Bone and Mineral Research.
A green one‐pot pseudo‐five‐component sequential protocol for the synthesis of novel 6,6′‐(arylmethylene)bis(benzo[a]phenazin‐5‐ol) derivatives
Authors: Olyaei Abolfazl , Aghajanzadeh Atiye , Feizy Elaheh , Sadeghpour Mahdieh 
Published: December 2020

AbstractA simple and efficient synthesis of novel 6,6′‐(arylmethylene)bis(benzo[a]phenazin‐5‐ol) derivatives has been developed via a sequential one‐pot, two‐step, pseudo‐five‐component tandem reaction starting from 2‐hydroxynaphthalene‐1,4‐dione, o‐phenylenediamine, and aromatic aldehydes in the presence of 2‐aminopyridine as co‐catalyst and p‐TsOH as catalyst at 90°C under solvent‐free conditions. This sequential green process offers several advantages, such as operational simplicity, high yield, low cost, easy handling, clean reactions, absence of any tedious work‐up, and purification of products by non‐chromatographic methods.
The Importance of Clinical Research in Pregnant Women to Inform Prescription Drug Labeling
Authors: Dinatale Miriam , Roca Catherine , Sahin Leyla , Johnson Tamara , Mulugeta Lily Yeruk , Fletcher Elimika Pfuma , Yao Lynne 
Published: December 2020

AbstractPregnant women have historically been an understudied population and have been excluded from clinical trials. Recent efforts by stakeholders have raised awareness of the importance of clinical research in pregnant women to inform prescribing decisions. The Food and Drug Administration continues working to improve the format and content of prescription drug labeling for pregnant and lactating women, as demonstrated with the Pregnancy and Lactation Labeling Rule (PLLR), effective in 2015. The pregnancy labeling subsection now includes a subheading dedicated to the inclusion of pharmacokinetic (PK) data that inform the need for dose adjustments during pregnancy and the postpartum period. In addition, the PLLR also requires prescription drug labeling to be updated when important pregnancy information becomes available. Although PLLR improved the presentation of pregnancy‐related information in labeling, there is a need to increase the quality and quantity of human data on the use of prescription drugs during pregnancy. PK studies in pregnant women should be incorporated into drug development programs and prioritized to obtain important information about safe and appropriate doses of a drug when used during pregnancy. In addition, opportunistic PK studies, postapproval pregnancy safety studies, ex vivo studies, and in silico modeling can be leveraged to better inform the risks and benefits of using a drug during pregnancy to inform study design and to further understand various mechanisms impacting pharmacokinetic/pharmacodynamic of drugs during pregnancy. It is important to address the significant existing data gaps and better inform the safety and dosing of prescription drugs for pregnant women.