bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of particle size on phytochemical composition and antioxidant properties of Sargassum cristaefolium ethanol extract
Authors: Prasedya E. S. , Frediansyah A. , Martyasari N. W. R. , Ilhami B. K. , Abidin A. S. , Padmi H. , Fahrurrozi  , Juanssilfero A. B. , Widyastuti S. , Sunarwidhi A. L. 
Published: September 2021

AbstractSample particle size is an important parameter in the solid–liquid extraction system of natural products for obtaining their bioactive compounds. This study evaluates the effect of sample particle size on the phytochemical composition and antioxidant activity of brown macroalgae Sargassum cristaefolium. The crude ethanol extract was extracted from dried powders of S.cristeafolium with various particle sizes (> 4000 µm, > 250 µm, > 125 µm, > 45 µm, and < 45 µm). The ethanolic extracts of S.cristaefolium were analysed for Total Phenolic Content (TPC), Total Flavonoid Content (TFC), phenolic compound concentration and antioxidant activities. The extract yield and phytochemical composition were more abundant in smaller particle sizes. Furthermore, the TPC (14.19 ± 2.08 mg GAE/g extract to 43.27 ± 2.56 mg GAE/g extract) and TFC (9.6 ± 1.8 mg QE/g extract to 70.27 ± 3.59 mg QE/g extract) values also significantly increased as particle sizes decreased. In addition, phenolic compounds epicatechin (EC), epicatechin gallate (ECG), epigallocatechin (EGC), and Epigallocatechin gallate (EGCG) concentration were frequently increased in samples of smaller particle sizes based on two-way ANOVA and Tukey’s multiple comparison analysis. These results correlate with the significantly stronger antioxidant activity in samples with smaller particle sizes. The smallest particle size (< 45 µm) demonstrated the strongest antioxidant activity based on DPPH, ABTS, hydroxyl assay and FRAP. In addition, ramp function graph evaluates the desired particle size for maximum phytochemical composition and antioxidant activity is 44 µm. In conclusion, current results show the importance of particle size reduction of macroalgae samples to increase the effectivity of its biological activity.
Agricultural impacts of sustainable water use in the United States
Authors: Graham Neal T. , Iyer Gokul , Hejazi Mohamad I. , Kim Son H. , Patel Pralit , Binsted Matthew 
Published: September 2021

AbstractGovernance measures such as restrictions on groundwater pumping and adjustments to sectoral water pricing have been suggested as response strategies to curtail recent increases in groundwater pumping and enhance sustainable water use. However, little is known about the impacts of such sustainability strategies. We investigate the implications of such measures, with the United States (U.S.) as an example. Using the Global Change Analysis Model (GCAM) with state-level details in the U.S., we find that the combination of these two governance measures can drastically alter agricultural production in the U.S. The Southwest stands to lose upwards of 25% of their total agricultural production, much of which is compensated for by production increases in river basins on the east coast of the U.S. The implementation of future sustainable water governance measures will require additional investments that allow farmers to maximize production while minimizing water withdrawals to avoid potentially detrimental revenue losses.
Interaction of MS prevalence, radon gas concentration, and patient nutrition: a case–control study
Authors: Yakhdani Monire Fallah , Jalili Mahrokh , Salehi-Abargouei Amin , Mirzaei Masuod , Rahimdel Abolghasem , Ebrahimi Ali Asghar 
Published: September 2021

AbstractIn general, ecological findings indicate a positive correlation between MS and the intake of certain foods. This study aimed to investigate the relationship between radon (Rn) gas concentration and nutrition of patients in food groups with MS. Demographic information, diet, and building characteristics were collected by a questionnaire. Indoors Rn gas was measured using CR-39 detectors. Three models were used in the study of food intake. The interaction analysis between MS prevalence, diet, residential building characteristics, and Rn gas content was performed using SPSS 2020. The total Rn was significantly associated with cooling devices (P = 0.021). Buildings > 20 years had higher Rn concentrations than buildings < 20 years (P = 0.038). Also, no significant relationship was found between Rn-total and MS concentrations, but the total Rn concentration was higher in people homes with MS. Case group used more processed meat than the control (P < 0.001). The case group consumed more butter than the control, which was significant in Model III (P < 0.04). Tomato consumption in the case group was significantly higher than the control (P < 0.03). According to the results there was no interaction between Rn gas concentration in any of the food groups in each cases. However, future studies with larger sample sizes will be needed prospectively.
Second-generation cryoballoon versus contact force radiofrequency ablation for atrial fibrillation: an updated meta-analysis of evidence from randomized controlled trials
Authors: Wu Chenxia , Li Xinyi , Lv Zhengtian , Chen Qian , Lou Yang , Mao Wei , Zhou Xinbin 
Published: September 2021

AbstractCatheter ablation has been recommended for patients with symptomatic atrial fibrillation (AF), with pulmonary vein isolation being the cornerstone of the ablation procedure. Newly developed technologies, such as cryoballoon ablation with a second-generation cryoballoon (CB2) and the contact force radiofrequency (CF-RF) ablation, have been introduced in recent years to overcome the shortcomings of the widely used RF ablation approach. However, high-quality results comparing CB2 and CF-RF remain controversial. Thus, we conducted this meta-analysis to assess the efficacy and safety between CB2 and CF-RF using evidence from randomized controlled trials (RCTs). Databases including Embase, PubMed, the Cochrane Library, and ClinicalTrials.gov were systematically searched from their date of inception to January 2021. Only RCTs that met the inclusion criteria were included for analysis. The primary outcome of interest was freedom from atrial tachyarrhythmia (AT) during follow-up. Secondary outcomes included procedure-related complications, procedure time and fluoroscopy time. Six RCTs with a total of 987 patients were finally enrolled. No significant differences were found between CB2 and CF-RF in terms of freedom from AT (relative risk [RR] = 1.03, 95% confidence interval [CI] 0.92–1.14,p = 0.616) or total procedural-related complications (RR = 1.25, 95% CI 0.69–2.27,p = 0.457). CB2 treatment was associated with a significantly higher risk of phrenic nerve palsy (PNP) than CF-RF (RR = 4.93, 95% CI 1.12–21.73,p = 0.035). The occurrences of pericardial effusion/tamponade and vascular complications were comparable between the CB2 and CF-RF treatments (RR = 0.41,p = 0.398; RR = 0.82,p = 0.632). In addition, CB2 treatment had a significantly shorter procedure time than CF-RF (weighted mean difference [WMD] = − 20.75 min, 95% CI − 25.44 ~ − 16.05 min,P < 0.001), whereas no difference was found in terms of fluoroscopy time (WMD = 4.63 min,p = 0.179). CB2 and CF-RF treatment are comparable for AF patients regarding freedom from AT and procedure-related complications. Compared to CF-RF, CB2 treatment was associated with a shorter procedure time but a higher incidence of PNP. Further large-scale studies are warranted to compare these two techniques and provide an up-to-date recommendation.
Probiotics combined with rifaximin influence the neurometabolic changes in a rat model of type C HE
Authors: Flatt Emmanuelle , McLin Valérie A. , Braissant Olivier , Pierzchala Katarzyna , Mastromarino Paola , Mitrea Stefanita-Octavian , Sessa Dario , Gruetter Rolf , Cudalbu Cristina 
Published: September 2021

AbstractType C hepatic encephalopathy (HE) is a neuropsychiatric disease caused by chronic liver disease. Management of type C HE remains an important challenge because treatment options are limited. Both the antibiotic rifaximin and probiotics have been reported to reduce the symptoms of HE, but longitudinal studies assessing their effects on brain metabolism are lacking and the molecular mechanisms underpinning their effects are not fully understood. Therefore, we evaluated in detail the effects of these different treatments on the neurometabolic changes associated with type C HE using a multimodal approach including ultra-high field in vivo 1H MRS. We analyzed longitudinally the effect of rifaximin alone or in combination with the probiotic Vivomixx on the brain metabolic profile in the hippocampus and cerebellum of bile duct ligated (BDL) rats, an established model of type C HE. Overall, while rifaximin alone appeared to induce no significant effect on the neurometabolic profile of BDL rats, its association with the probiotic resulted in more attenuated neurometabolic alterations in BDL rats followed longitudinally (i.e. a smaller increase in Gln and milder decrease in Glu and Cr levels). Given that both rifaximin and some probiotics are used in the treatment of HE, the implications of these findings may be clinically relevant.
Light entrainment of the SCN circadian clock and implications for personalized alterations of corticosterone rhythms in shift work and jet lag
Authors: Li Yannuo , Androulakis Ioannis P. 
Published: September 2021

AbstractThe suprachiasmatic nucleus (SCN) functions as the central pacemaker aligning physiological and behavioral oscillations to day/night (activity/inactivity) transitions. The light signal entrains the molecular clock of the photo-sensitive ventrolateral (VL) core of the SCN which in turn entrains the dorsomedial (DM) shell via the neurotransmitter vasoactive intestinal polypeptide (VIP). The shell converts the VIP rhythmic signals to circadian oscillations of arginine vasopressin (AVP), which eventually act as a neurotransmitter signal entraining the hypothalamic–pituitary–adrenal (HPA) axis, leading to robust circadian secretion of glucocorticoids. In this work, we discuss a semi-mechanistic mathematical model that reflects the essential hierarchical structure of the photic signal transduction from the SCN to the HPA axis. By incorporating the interactions across the core, the shell, and the HPA axis, we investigate how these coupled systems synchronize leading to robust circadian oscillations. Our model predicts the existence of personalized synchronization strategies that enable the maintenance of homeostatic rhythms while allowing for differential responses to transient and permanent light schedule changes. We simulated different behavioral situations leading to perturbed rhythmicity, performed a detailed computational analysis of the dynamic response of the system under varying light schedules, and determined that (1) significant interindividual diversity and flexibility characterize adaptation to varying light schedules; (2) an individual’s tolerances to jet lag and alternating shift work are positively correlated, while the tolerances to jet lag and transient shift work are negatively correlated, which indicates trade-offs in an individual’s ability to maintain physiological rhythmicity; (3) weak light sensitivity leads to the reduction of circadian flexibility, implying that light therapy can be a potential approach to address shift work and jet lag related disorders. Finally, we developed a map of the impact of the synchronization within the SCN and between the SCN and the HPA axis as it relates to the emergence of circadian flexibility.
Reinforcement learning derived chemotherapeutic schedules for robust patient-specific therapy
Authors: Eastman Brydon , Przedborski Michelle , Kohandel Mohammad 
Published: September 2021

AbstractThe in-silico development of a chemotherapeutic dosing schedule for treating cancer relies upon a parameterization of a particular tumour growth model to describe the dynamics of the cancer in response to the dose of the drug. In practice, it is often prohibitively difficult to ensure the validity of patient-specific parameterizations of these models for any particular patient. As a result, sensitivities to these particular parameters can result in therapeutic dosing schedules that are optimal in principle not performing well on particular patients. In this study, we demonstrate that chemotherapeutic dosing strategies learned via reinforcement learning methods are more robust to perturbations in patient-specific parameter values than those learned via classical optimal control methods. By training a reinforcement learning agent on mean-value parameters and allowing the agent periodic access to a more easily measurable metric, relative bone marrow density, for the purpose of optimizing dose schedule while reducing drug toxicity, we are able to develop drug dosing schedules that outperform schedules learned via classical optimal control methods, even when such methods are allowed to leverage the same bone marrow measurements.
Prolonged warm ischemia time leads to severe renal dysfunction of donation-after-cardiac death kidney grafts
Authors: Urbanellis Peter , Mazilescu Laura , Kollmann Dagmar , Linares-Cervantes Ivan , Kaths J. Moritz , Ganesh Sujani , Oquendo Fabiola , Sharma Manraj , Goto Toru , Noguchi Yuki , John Rohan , Konvalinka Ana , Mucsi Istvan , Ghanekar Anand , Bagli Darius , Robinson Lisa A. , Selzner Markus 
Published: September 2021

AbstractKidney transplantation with grafts procured after donation-after-cardiac death (DCD) has led to an increase in incidence of delayed graft function (DGF). It is thought that the warm ischemic (WI) insult encountered during DCD procurement is the cause of this finding, although few studies have been designed to definitely demonstrate this causation in a transplantation setting. Here, we use a large animal renal transplantation model to study the effects of prolonged WI during procurement on post-transplantation renal function. Kidneys from 30 kg-Yorkshire pigs were procured following increasing WI times of 0 min (Heart-Beating Donor), 30 min, 60 min, 90 min, and 120 min (n = 3–6 per group) to mimic DCD. Following 8 h of static cold storage and autotransplantation, animals were followed for 7-days. Significant renal dysfunction (SRD), resembling clinical DGF, was defined as the development of oliguria < 500 mL in 24 h from POD3-4 along with POD4 serum potassium > 6.0 mmol/L. Increasing WI times resulted in incremental elevation of post-operative serum creatinine that peaked later. DCD120min grafts had the highest and latest elevation of serum creatinine compared to all groups (POD5: 19.0 ± 1.1 mg/dL, p < 0.05). All surviving animals in this group had POD4 24 h urine output < 500 cc (mean 235 ± 172 mL) and elevated serum potassium (7.2 ± 1.1 mmol/L). Only animals in the DCD120min group fulfilled our criteria of SRD (p = 0.003), and their renal function improved by POD7 with 24 h urine output > 500 mL and POD7 serum potassium < 6.0 mmol/L distinguishing this state from primary non-function. In a transplantation survival model, this work demonstrates that prolonging WI time similar to that which occurs in DCD conditions contributes to the development of SRD that resembles clinical DGF.
Predicting severe outcomes using national early warning score (NEWS) in patients identified by a rapid response system: a retrospective cohort study
Authors: Kim Sang Hyuk , Choi Hye Suk , Jin Eun Suk , Choi Hayoung , Lee Hyun , Lee Sang-Hwa , Lee Chang Youl , Lee Myung Goo , Kim Youlim 
Published: September 2021

AbstractThere are insufficient data in managing patients at high risk of deterioration. We aimed to investigate that national early warning score (NEWS) could predict severe outcomes in patients identified by a rapid response system (RRS), focusing on the patient’s age. We conducted a retrospective cohort study from June 2019 to December 2020. Outcomes were unplanned intensive care unit (ICU) admission, ICU mortality, and in-hospital mortality. We analyzed the predictive ability of NEWS using receiver operating characteristics (ROC) curve and the effect of NEWS parameters using multivariable logistic regression. A total of 2,814 RRS activations were obtained. The predictive ability of NEWS for unplanned ICU admission and in-hospital mortality was fair but was poor for ICU mortality. The predictive ability of NEWS showed no differences between patients aged 80 years or older and under 80 years. However, body temperature affected in-hospital mortality for patients aged 80 years or older, and the inverse effect on unplanned ICU admission was observed. The NEWS showed fair predictive ability for unplanned ICU admission and in-hospital mortality among patients identified by the RRS. The different presentations of patients 80 years or older should be considered in implementing the RRS.
Mean-field model of melting in superheated crystals based on a single experimentally measurable order parameter
Authors: Kryuchkov Nikita P. , Dmitryuk Nikita A. , Li Wei , Ovcharov Pavel V. , Han Yilong , Sapelkin Andrei V. , Yurchenko Stanislav O. 
Published: September 2021

AbstractMelting is one of the most studied phase transitions important for atomic, molecular, colloidal, and protein systems. However, there is currently no microscopic experimentally accessible criteria that can be used to reliably track a system evolution across the transition, while providing insights into melting nucleation and melting front evolution. To address this, we developed a theoretical mean-field framework with the normalised mean-square displacement between particles in neighbouring Voronoi cells serving as the local order parameter, measurable experimentally. We tested the framework in a number of colloidal and in silico particle-resolved experiments against systems with significantly different (Brownian and Newtonian) dynamic regimes and found that it provides excellent description of system evolution across melting point. This new approach suggests a broad scope for application in diverse areas of science from materials through to biology and beyond. Consequently, the results of this work provide a new guidance for nucleation theory of melting and are of broad interest in condensed matter, chemical physics, physical chemistry, materials science, and soft matter.
Modeling hydrogen solubility in hydrocarbons using extreme gradient boosting and equations of state
Authors: Mohammadi Mohammad-Reza , Hadavimoghaddam Fahime , Pourmahdi Maryam , Atashrouz Saeid , Munir Muhammad Tajammal , Hemmati-Sarapardeh Abdolhossein , Mosavi Amir H. , Mohaddespour Ahmad 
Published: September 2021

AbstractDue to industrial development, designing and optimal operation of processes in chemical and petroleum processing plants require accurate estimation of the hydrogen solubility in various hydrocarbons. Equations of state (EOSs) are limited in accurately predicting hydrogen solubility, especially at high-pressure or/and high-temperature conditions, which may lead to energy waste and a potential safety hazard in plants. In this paper, five robust machine learning models including extreme gradient boosting (XGBoost), adaptive boosting support vector regression (AdaBoost-SVR), gradient boosting with categorical features support (CatBoost), light gradient boosting machine (LightGBM), and multi-layer perceptron (MLP) optimized by Levenberg–Marquardt (LM) algorithm were implemented for estimating the hydrogen solubility in hydrocarbons. To this end, a databank including 919 experimental data points of hydrogen solubility in 26 various hydrocarbons was gathered from 48 different systems in a broad range of operating temperatures (213–623 K) and pressures (0.1–25.5 MPa). The hydrocarbons are from six different families including alkane, alkene, cycloalkane, aromatic, polycyclic aromatic, and terpene. The carbon number of hydrocarbons is ranging from 4 to 46 corresponding to a molecular weight range of 58.12–647.2 g/mol. Molecular weight, critical pressure, and critical temperature of solvents along with pressure and temperature operating conditions were selected as input parameters to the models. The XGBoost model best fits all the experimental solubility data with a root mean square error (RMSE) of 0.0007 and an average absolute percent relative error (AAPRE) of 1.81%. Also, the proposed models for estimating the solubility of hydrogen in hydrocarbons were compared with five EOSs including Soave–Redlich–Kwong (SRK), Peng–Robinson (PR), Redlich–Kwong (RK), Zudkevitch–Joffe (ZJ), and perturbed-chain statistical associating fluid theory (PC-SAFT). The XGBoost model introduced in this study is a promising model that can be applied as an efficient estimator for hydrogen solubility in various hydrocarbons and is capable of being utilized in the chemical and petroleum industries.
Acoustic tweezing of microparticles in microchannels with sinusoidal cross sections
Authors: Jannesar Elnaz Attar , Hamzehpour Hossein 
Published: September 2021

AbstractAcoustic tweezing of bioparticles has distinct advantages over other manipulation methods such as electrophoresis or magnetophoresis in biotechnological applications. This manipulation method guarantees the viability of the bio-particles during and after the process. In this paper, the effects of sinusoidal boundaries of a microchannel on acoustophoretic manipulation of microparticles are studied. Our results show that while top and bottom walls are vertically actuated at the horizontal half-wave resonance frequency, a large mono-vortex appears, which is never achievable in a rectangular geometry with flat walls and one-dimensional oscillations. The drag force caused by such a vortex in combination with the tilted acoustic radiation force leads to trapping and micromixing of microparticles with diameters larger and smaller than the critical size, respectively. Simulation results in this paper show that efficient particle trapping occurs at the intermediate sinusoidal boundary amplitudes. It is also indicated that in a square-sinusoidal geometry there are two strong vortices, instead of one vortex. Sub-micrometer particles tend to be trapped dramatically faster in such a geometry than in the rectangular-sinusoidal ones.
Fixation probabilities in network structured meta-populations
Authors: Yagoobi Sedigheh , Traulsen Arne 
Published: September 2021

AbstractThe effect of population structure on evolutionary dynamics is a long-lasting research topic in evolutionary ecology and population genetics. Evolutionary graph theory is a popular approach to this problem, where individuals are located on the nodes of a network and can replace each other via the links. We study the effect of complex network structure on the fixation probability, but instead of networks of individuals, we model a network of sub-populations with a probability of migration between them. We ask how the structure of such a meta-population and the rate of migration affect the fixation probability. Many of the known results for networks of individuals carry over to meta-populations, in particular for regular networks or low symmetric migration probabilities. However, when patch sizes differ we find interesting deviations between structured meta-populations and networks of individuals. For example, a two patch structure with unequal population size suppresses selection for low migration probabilities.