bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a system to support warfarin dose decisions using deep neural networks
Authors: Lee Heemoon , Kim Hyun Joo , Chang Hyoung Woo , Kim Dong Jung , Mo Jonghoon , Kim Ji-Eon 
Published: July 2021

AbstractThe first aim of this study was to develop a prothrombin time international normalized ratio (PT INR) prediction model. The second aim was to develop a warfarin maintenance dose decision support system as a precise warfarin dosing platform. Data of 19,719 inpatients from three institutions was analyzed. The PT INR prediction algorithm included dense and recurrent neural networks, and was designed to predict the 5th-day PT INR from data of days 1–4. Data from patients in one hospital (n = 22,314) was used to train the algorithm which was tested with the datasets from the other two hospitals (n = 12,673). The performance of 5th-day PT INR prediction was compared with 2000 predictions made by 10 expert physicians. A generator of individualized warfarin dose-PT INR tables which simulated the repeated administration of varying doses of warfarin was developed based on the prediction model. The algorithm outperformed humans with accuracy terms of within ± 0.3 of the actual value (machine learning algorithm: 10,650/12,673 cases (84.0%), expert physicians: 1647/2000 cases (81.9%), P = 0.014). In the individualized warfarin dose-PT INR tables generated by the algorithm, the 8th-day PT INR predictions were within 0.3 of actual value in 450/842 cases (53.4%). An artificial intelligence-based warfarin dosing algorithm using a recurrent neural network outperformed expert physicians in predicting future PT INRs. An individualized warfarin dose-PT INR table generator which was constructed based on this algorithm was acceptable.
Kinetic characterisation and inhibitor sensitivity of Candida albicans and Candida auris recombinant AOX expressed in a self-assembled proteoliposome system
Authors: Copsey Alice C. , Barsottini Mario R. O. , May Benjamin , Xu Fei , Albury Mary S. , Young Luke , Moore Anthony L. 
Published: July 2021

AbstractCandidemia caused by Candida spp. is a serious threat in hospital settings being a major cause of acquired infection and death and a possible contributor to Covid-19 mortality. Candidemia incidence has been rising worldwide following increases in fungicide-resistant pathogens highlighting the need for more effective antifungal agents with novel modes of action. The membrane-bound enzyme alternative oxidase (AOX) promotes fungicide resistance and is absent in humans making it a desirable therapeutic target. However, the lipophilic nature of the AOX substrate (ubiquinol-10) has hindered its kinetic characterisation in physiologically-relevant conditions. Here, we present the purification and expression of recombinant AOXs from C. albicans and C. auris in a self-assembled proteoliposome (PL) system. Kinetic parameters (Km and Vmax) with respect to ubiquinol-10 have been determined. The PL system has also been employed in dose–response assays with novel AOX inhibitors. Such information is critical for the future development of novel treatments for Candidemia.
Enhancing the weighted voting ensemble algorithm for tuberculosis predictive diagnosis
Authors: Osamor Victor Chukwudi , Okezie Adaugo Fiona 
Published: July 2021

AbstractTuberculosis has the most considerable death rate among diseases caused by a single micro-organism type. The disease is a significant issue for most third-world countries due to poor diagnosis and treatment potentials. Early diagnosis of tuberculosis is the most effective way of managing the disease in patients to reduce the mortality rate of the infection. Despite several methods that exist in diagnosing tuberculosis, the limitations ranging from the cost in carrying out the test to the time taken to obtain the results have hindered early diagnosis of the disease. This work aims to develop a predictive model that would help in the diagnosis of TB using an extended weighted voting ensemble method. The method used to carry out this research involved analyzing tuberculosis gene expression data obtained from GEO (Transcript Expression Omnibus) database and developing a classification model to aid tuberculosis diagnosis. A classifier combination of Naïve Bayes (NB), and Support Vector Machine (SVM) was used to develop the classification model. The weighted voting ensemble technique was used to improve the classification model's performance by combining the classification results of the single classifier and selecting the group with the highest vote based on the weights given to the single classifiers. Experimental analysis indicates a performance accuracy of the enhanced ensemble classifier as 0.95, which showed a better performance than the single classifiers, which had 0.92, and 0.87 obtained from SVM and NB, respectively. The developed model can also assist health practitioners in the timely diagnosis of tuberculosis, which would reduce the mortality rate caused by the disease, especially in developing countries.
Survival analysis of patients with primary breast duct carcinoma and lung adenocarcinoma: a population-based study from SEER
Authors: Lv Fengyuan , Cheng Mingliang , Jiang Liang , Zhao Xiaoping 
Published: July 2021

AbstractThe appeal to enroll patients with primary breast and lung cancer in clinical trials is increasing, but survival of these two primary cancers remains to be elucidated. This study analyzed the prognosis of primary breast duct carcinoma with subsequent lung adenocarcinoma (BCLA) and primary breast duct carcinoma with prior lung adenocarcinoma (LABC). Cohorts of 3,515 patients with BCLA and 654 patients with LABC were identified from the Surveillance, Epidemiology, and End Results database. Patients were classified into simultaneous two primary cancer (sTPC), metachronous two primary cancer (mTPC1), or mTPC2 groups when the interval times between breast and lung cancer were within 6 months, between 7 and 60 months, or over 60 months, respectively. The propensity score matching program (PSM) was applied to determine the survival of BCLA/LABC relative to single breast/lung cancer. Cox proportional hazard regression model and competing risk modes were performed to identify confounders associated with all-cause and cancer-specific death, respectively. Survival of patients with LABC/BCLA relative to single breast/lung cancer was accessed via median survival time. The survival of patients with BCLA/LABC was generally poor compared with the survival of those with single breast cancer. The PSM-estimated HR in the sTPC group with BCLA and in the mTPC1 and mTPC2 groups with LABC were 0.75 (95% CI 0.62–0.90), 0.52 (95% CI 0.27–0.98), and 0.36 (95% CI 0.20–0.65), respectively, whereas the SHRs were 0.80 (95% CI 0.66–0.97), 0.68 (95% CI 0.34–1.34), and 0.46 (95% CI 0.27–0.80), respectively, compared with those in the single lung cancer group. By contrast, the survival rates of the remaining patients did not differ. The median survival times since secondary malignancy were 42, 23, and 20 months in the sTPC, mTPC1, and mTPC2 groups with BCLA, respectively, and 18, 60, and 180 months in those with LABC, respectively. For patients with BCLA, the adjusted Cox regression suggested incidences of all-cause deaths in mTPC1group were statically higher than those in sTPC group, whereas the incidences of all-cause and cancer-specific death in the mTPC1 and mTPC2 groups were statistically lower than those in the sTPC group. The prognosis of patients with breast cancer and subsequent lung cancer of over 18 months was not significantly different than that of single lung cancer, which supported the profound appeal to increase the involvement of these two primary cancers in potential beneficial clinical trials. For patients with lung cancer and prior breast cancer of within 6 months and subsequent breast cancer of over 18 months, prognosis was improved relative to single lung cancer. Therefore, additional attention is needed to eliminate the potential bias may when these patients are recruited in the clinical trials.
Exploiting RNA thermometer-driven molecular bioprocess control as a concept for heterologous rhamnolipid production
Authors: Noll Philipp , Treinen Chantal , Müller Sven , Lilge Lars , Hausmann Rudolf , Henkel Marius 
Published: July 2021

AbstractA key challenge to advance the efficiency of bioprocesses is the uncoupling of biomass from product formation, as biomass represents a by-product that is in most cases difficult to recycle efficiently. Using the example of rhamnolipid biosurfactants, a temperature-sensitive heterologous production system under translation control of a fourU RNA thermometer fromSalmonellawas established to allow separating phases of preferred growth from product formation. Rhamnolipids as bulk chemicals represent a model system for future processes of industrial biotechnology and are therefore tied to the efficiency requirements in competition with the chemical industry. Experimental data confirms function of the RNA thermometer and suggests a major effect of temperature on specific rhamnolipid production rates with an increase of the average production rate by a factor of 11 between 25 and 38 °C, while the major part of this increase is attributable to the regulatory effect of the RNA thermometer rather than an unspecific overall increase in bacterial metabolism. The production capacity of the developed temperature sensitive-system was evaluated in a simple batch process driven by a temperature switch. Product formation was evaluated by efficiency parameters and yields, confirming increased product formation rates and product-per-biomass yields compared to a high titer heterologous rhamnolipid production process from literature.
Solar UV-B/A radiation is highly effective in inactivating SARS-CoV-2
Authors: Nicastro Fabrizio , Sironi Giorgia , Antonello Elio , Bianco Andrea , Biasin Mara , Brucato John R. , Ermolli Ilaria , Pareschi Giovanni , Salvati Marta , Tozzi Paolo , Trabattoni Daria , Clerici Mario 
Published: July 2021

AbstractSolar UV-C photons do not reach Earth’s surface, but are known to be endowed with germicidal properties that are also effective on viruses. The effect of softer UV-B and UV-A photons, which copiously reach the Earth’s surface, on viruses are instead little studied, particularly on single-stranded RNA viruses. Here we combine our measurements of the action spectrum of Covid-19 in response to UV light, Solar irradiation measurements on Earth during the SARS-CoV-2 pandemics, worldwide recorded Covid-19 mortality data and our “Solar-Pump” diffusive model of epidemics to show that (a) UV-B/A photons have a powerful virucidal effect on the single-stranded RNA virus Covid-19 and that (b) the Solar radiation that reaches temperate regions of the Earth at noon during summers, is sufficient to inactivate 63% of virions in open-space concentrations (1.5 × 103 TCID50/mL, higher than typical aerosol) in less than 2 min. We conclude that the characteristic seasonality imprint displayed world-wide by the SARS-Cov-2 mortality time-series throughout the diffusion of the outbreak (with temperate regions showing clear seasonal trends and equatorial regions suffering, on average, a systematically lower mortality), might have been efficiently set by the different intensity of UV-B/A Solar radiation hitting different Earth’s locations at different times of the year. Our results suggest that Solar UV-B/A play an important role in planning strategies of confinement of the epidemics, which should be worked out and set up during spring/summer months and fully implemented during low-solar-irradiation periods.
Genomic heterogeneity affects the response to Daylight Saving Time
Authors: Tyler Jonathan , Fang Yu , Goldstein Cathy , Forger Daniel , Sen Srijan , Burmeister Margit 
Published: July 2021

AbstractCircadian clocks control the timing of many physiological events in the 24-h day. When individuals undergo an abrupt external shift (e.g., change in work schedule or travel across multiple time zones), circadian clocks become misaligned with the new time and may take several days to adjust. Chronic circadian misalignment, e.g., as a result of shift work, has been shown to lead to several physical and mental health problems. Despite the serious health implications of circadian misalignment, relatively little is known about how genetic variation affects an individual’s ability to entrain to abrupt external changes. Accordingly, we used the one-hour advance from the onset of daylight saving time (DST) as a natural experiment to comprehensively study how individual heterogeneity affects the shift of sleep/wake cycles in response to an abrupt external time change. We found that individuals genetically predisposed to a morning tendency adjusted to the advance in a few days, while genetically predisposed evening-inclined individuals had not shifted. Observing differential effects by genetic disposition after a one-hour advance underscores the importance of heterogeneity in adaptation to external schedule shifts. These genetic differences may affect how individuals adjust to jet lag or shift work as well.
Predicting critical state after COVID-19 diagnosis: model development using a large US electronic health record dataset
Authors: Rinderknecht Mike D. , Klopfenstein Yannick 
Published: July 2021

AbstractAs the COVID-19 pandemic is challenging healthcare systems worldwide, early identification of patients with a high risk of complication is crucial. We present a prognostic model predicting critical state within 28 days following COVID-19 diagnosis trained on data from US electronic health records (IBM Explorys), including demographics, comorbidities, symptoms, and hospitalization. Out of 15753 COVID-19 patients, 2050 went into critical state or deceased. Non-random train-test splits by time were repeated 100 times and led to a ROC AUC of 0.861 [0.838, 0.883] and a precision-recall AUC of 0.434 [0.414, 0.485] (median and interquartile range). The interpretability analysis confirmed evidence on major risk factors (e.g., older age, higher BMI, male gender, diabetes, and cardiovascular disease) in an efficient way compared to clinical studies, demonstrating the model validity. Such personalized predictions could enable fine-graded risk stratification for optimized care management.
Bromodomain-containing protein BRPF1 is a therapeutic target for liver cancer
Authors: Cheng Carol Lai-Hung , Tsang Felice Hoi-Ching , Wei Lai , Chen Mengnuo , Chin Don Wai-Ching , Shen Jialing , Law Cheuk-Ting , Lee Derek , Wong Carmen Chak-Lui , Ng Irene Oi-Lin , Wong Chun-Ming 
Published: July 2021

AbstractEpigenetic deregulation plays an essential role in hepatocellular carcinoma (HCC) progression. Bromodomains are epigenetic “readers” of histone acetylation. Recently, bromodomain inhibitors have exhibited promising therapeutic potential for cancer treatment. Using transcriptome sequencing, we identifiedBRPF1(bromodomain and PHD finger containing 1) as the most significantly upregulated gene among the 43 bromodomain-containing genes in human HCC. BRPF1 upregulation was significantly associated with poor patient survival. Gene ablation or pharmacological inactivation of BRPF1 significantly attenuated HCC cell growth in vitro and in vivo. BRPF1 was involved in cell cycle progression, senescence and cancer stemness. Transcriptome sequencing revealed that BRPF1 is a master regulator controlling the expression of multiple key oncogenes, includingE2F2andEZH2. We demonstrated that BRPF1 activated E2F2 and EZH2 expression by facilitating promoter H3K14 acetylation through MOZ/MORF complex. In conclusion, BRPF1 is frequently upregulated in human HCCs. Targeting BRPF1 may be an approach for HCC treatment.
Facial synthesis of two-dimensional In2S3/Ti3C2Tx heterostructures with boosted photoactivity for the hydrogenation of nitroaromatic compounds
Authors: Zhu Yisong , Xie Guanshun , Li Guohao , Song Fei , Yu Changqiang , Wu Zhenjun , Xie Xiuqiang , Zhang Nan 
Published: July 2021

In this work, Ti3C2Tx (MXene) acts as the platform for directing the growth of 2D In2S3 nanoflakes, thereby generating 2D In2S3/Ti3C2Tx heterostructures, which exhibited boosted photocatalytic activities compared to bare In2S3.
Transceiver design for MU‐SIMO FSO communication over correlated lognormal channels
Authors: Yan Ruo‐Lin , Zhang Jian , Chen Ru‐Han , Si‐Ma Ling‐Han 
Published: July 2021

AbstractIn this paper, with the assumption of only channel statistics information available at the receivers, a novel concept of multiplicative uniquely decomposable constellations is proposed for multi‐user single‐input multiple‐output (MU‐SIMO) FSO systems in weak atmospheric turbulence, which is modeled by spatially dependent lognormal fading channels. The design enables the fast decoding at the users' sides and meanwhile allows flexibility in assigning each user's ordering to meet different priority needs. Simulation results show that our proposed design has a significant performance improvement over the TDMA scheme at the same rates.
Design and measurement of a novel metal‐only wideband magneto‐electric dipole antenna using asymmetrical structure
Authors: Wang Min , Mo Yuxin , Luo Wei , Yang Huifeng , Chen Zhengchuan 
Published: July 2021

AbstractA novel metal‐only wideband magneto‐electric dipole antenna is designed and measured in this letter. The antenna consists of two rectangular patches etched with asymmetrical slots as electric dipole, two folded patches as magneto‐dipole, trident‐shaped feeding structure and side‐slotted ground, large metallic ground. The electric dipole is horizontally placed on both sides of the feeding structure, and two folded patches are assembled vertically on the small ground. Two symmetrically sided slots are etched on the small ground to reduce the profile and a trident‐shaped feeding strip is employed to widen the bandwidth, while a lower ground with a large size is designed to suppress the radiation in the backward direction. Finally, the antenna prototype is fabricated and measured. The measured results show that −10 dB impedance bandwidth is achieved up to 75.9% at 2.7 GHz from 2.0 to 4.1 GHz. At 2.7 GHz, the measured peak gain is 9.0 dBi.
Impact of size-dependent grain temperature on gas-grain chemistry in protoplanetary disks: The case of low-mass star disks
Authors: Gavino S. , Dutrey A. , Wakelam V. , Guilloteau S. , Kobus J. , Wolf S. , Iqbal W. , Di Folco E. , Chapillon E. , Piétu V. 
Published: July 2021

Context. Grain surface chemistry is fundamental to the composition of protoplanetary disks around young stars.
Aims. The temperature of grains depends on their size. We evaluate the impact of this temperature dependence on the disk chemistry.
Methods. We modeled a moderately massive disk with 16 different grain sizes. We used the 3D Monte Carlo POLARIS code to calculate the dust grain temperatures and the local uv flux. We modeled the chemistry using the three-phase astrochemical code NAUTILUS. Photo processes were handled using frequency-dependent cross sections and a new method to account for self and mutual shielding. The multi-grain model outputs are compared to those of single-grain size models (0.1 μm); there are two different assumptions for their equivalent temperature.
Results. We find that the Langmuir-Hinshelwood mechanism at equilibrium temperature is not efficient to form H2 at 3–4 scale heights (H), and we adopt a parametric fit to a stochastic method to model H2 formation instead. We find the molecular layer composition (1–3 H) to depend on the amount of remaining H atoms. Differences in molecular surface densities between single and multi-grain models are mostly due to what occurs above 1.5 H. At 100 au, models with colder grains produce H2O and CH4 ices in the midplane, and those with warmer grains produce more CO2 ices; both of these allow for an efficient depletion of C and O as soon as CO sticks on grain surfaces. Complex organic molecules production is enhanced by the presence of warmer grains in the multi-grain models. Using a single-grain model mimicking grain growth and dust settling fails to reproduce the complexity of gas-grain chemistry.
Conclusions. Chemical models with a single-grain size are sensitive to the adopted grain temperature and cannot account for all expected effects. A spatial spread of the snowlines is expected to result from the ranges in grain temperature. The amplitude of the effects depends on the dust disk mass.
Plasma densities, flow, and solar EUV flux at comet 67P
Authors: Johansson F. L. , Eriksson A. I. , Vigren E. , Bucciantini L. , Henri P. , Nilsson H. , Bergman S. , Edberg N. J. T. , Stenberg Wieser G. , Odelstad E. 
Published: July 2021

Context.During its two-year mission at comet 67P, Rosetta nearly continuously monitored the inner coma plasma environment for gas production rates varying over three orders of magnitude, at distances to the nucleus ranging from a few to a few hundred kilometres. To achieve the best possible measurements, cross-calibration of the plasma instruments is needed.Aims.Our goal is to provide a consistent plasma density dataset for the full mission, while in the process providing a statistical characterisation of the plasma in the inner coma and its evolution.Methods.We constructed physical models for two different methods to cross-calibrate the spacecraft potential and the ion current as measured by the Rosetta Langmuir probes (LAP) to the electron density as measured by the Mutual Impedance Probe (MIP). We also described the methods used to estimate spacecraft potential, and validated the results with the Ion Composition Analyser (ICA).Results.We retrieve a continuous plasma density dataset for the entire cometary mission with a much improved dynamical range compared to any plasma instrument alone and, at times, improve the temporal resolution from 0.24−0.74 Hz to 57.8 Hz. The physical model also yields, at a three-hour time resolution, ion flow speeds and a proxy for the solar EUV flux from the photoemission from the Langmuir probes.Conclusions.We report on two independent mission-wide estimates of the ion flow speed that are consistent with the bulk H2O+ion velocities as measured by the ICA. We find the ion flow to consistently be much faster than the neutral gas over the entire mission, lending further evidence that the ions are collisionally decoupled from the neutrals in the coma. Measurements of ion speeds from Rosetta are therefore not consistent with the assumptions made in previously published plasma density models of the comet 67P’s ionosphere at the start and end of the mission. Also, the measured EUV flux is perfectly consistent with independently derived values previously published from LAP and lends support for the conclusions drawn regarding an attenuation of solar EUV from a distant nanograin dust population, when the comet activity was high. The new density dataset is consistent with the existing MIP density dataset, but it facilitates plasma analysis on much shorter timescales, and it also covers long time periods where densities were too low to be measured by MIP.