bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Spanish version of the Mothers' Postnatal Sense of Security Scale: Psychometric properties and predictive utility
Authors: Escribano Silvia , Oliver‐Roig Antonio , Cano‐Climent Antoni , Richart‐Martínez Miguel , Persson Eva K. , Juliá‐Sanchis Rocío 
Published: August 2020

AbstractPostnatal sense of security is a relevant construct related to several variables of motherhood. However, it has not yet been studied in the Spanish context. The aims were: (a) To analyze the psychometric properties of a Spanish version of the Mothers' Postnatal Sense of Security Scale (PPSS‐S); (b) analyze the factors related to mothers' sense of security during the first 2 weeks following childbirth (sociodemographic variables and factors related to maternity); and (c) examine the predictive utility that mothers' sense of security has on symptoms of postpartum depression 6–11 months after childbirth. This was a prospective longitudinal study performed in the first 6–11 months post‐partum in four regions of Spain. A total of 928 mothers whose mean age was 33.67 years (standard deviation = 4.54) participated. The confirmatory factor analysis showed adequate adjustment to the original structure (χ2 = 17,272.79, df = 153, p < .001; Tucker–Lewis index = 0.98; comparative fit index = 0.98; root mean square error of approximation = 0.058 [0.053‐0.063])and the overall internal consistency was 0.89. Direct relationships were shown between women' sense of security and already having had a child, the absence of postpartum health complications (either in the mother or the newborn) and receiving consistent information from healthcare professionals. Our results showed adequate evidence for the reliability and validity of the Spanish version of the PPSS‐S. Understanding mothers' sense of security during the early months of motherhood, as well as related factors in the postpartum period, will allow health professionals to implement preventive measures to promote mental health and could help reduce symptoms of postpartum depression.
Defibrotide treatment but not prophylaxis is useful in hepatic sinusoidal obstruction syndrome in children undergoing autologous stem cell transplant following high‐dose chemotherapy: A single‐center experience from the Royal Marsden Hospital, UK
Authors: Roy Moulik Nirmalya , Johnson Indranee , Van Bruggen Lucia , Petterson Toni , Mycroft Julie , Vaidya Sucheta J. 
Published: August 2020

AbstractBackgroundHepatic sinusoidal obstruction syndrome (SOS) is a serious complication of autologous stem cell transplant (ASCT) in children with historically high mortality rates. Defibrotide has shown proven benefit in its treatment and may have a modest role in prevention. We report our experience with SOS in children undergoing autologous transplant.MethodsCase records of 82 consecutive patients undergoing ASCT following high‐dose chemotherapy between 2010 and 2017 were reviewed. Defibrotide was used for treatment of all with SOS and prophylactically in patients receiving busulfan‐based conditioning until 2014.ResultsFourteen of the 82 children (17%) were diagnosed with SOS. The incidence was higher in those receiving busulfan‐based conditioning (13/42 vs 1/40, P = 0.008). Mean (±SD) time to diagnosis of SOS was 19 (±5.6) days following stem cell rescue. Bilirubin levels and ultrasound were normal in 7/14 and 3/14 patients. Coagulopathy was noted in 10/14; one child developed multiorgan involvement. Nine children had mild SOS, whereas two and three had moderate and severe SOS, respectively. Intensive care was required for four of five non‐mild cases. Patients with SOS had significantly delayed platelet recovery, higher transfusion requirement, and longer hospital stay. Unavailability of defibrotide prophylaxis for 17/42 receiving busulfan did not change the incidence of SOS (7/25 with defibrotide vs 6 /17 without defibrotide, P = 0.74). There was no significant difference in the severity of SOS between these groups.ConclusionHepatic SOS was more commonly seen in children receiving busulfan‐based conditioning. Stopping the use of prophylactic defibrotide did not increase incidence or severity of SOS. Overall outcome was excellent with supportive care and timely treatment with defibrotide.
Outcome misclassification: Impact, usual practice in pharmacoepidemiology database studies and an online aid to correct biased estimates of risk ratio or cumulative incidence
Authors: Hall Gillian C. , Lanes Stephan , Bollaerts Kaatje , Zhou Xiaofeng , Ferreira Germano , Gini Rosa 
Published: August 2020

AbstractPurposeIt is well documented that outcome misclassification can bias a point estimate. We aimed to understand current practice in addressing this bias in pharmacoepidemiology database studies and to develop an open source application (app) from existing methodology to demonstrate the impact and mechanism of this bias on results.MethodsStudies of an exposure and a clinical outcome were selected from all Pharmacoepidemiology and Drug Safety publications during 2017 and any reference to outcome misclassification described. An app to correct risk ratio (RR) and cumulative incidence for outcome misclassification was developed from a published methodology and used to demonstrate the impact of correction on point estimates.ResultsEight (19%) of 43 papers selected reported estimates of outcome ascertainment accuracy with positive predictive value (PPV) the most commonly reported measure (7 of 8 studies). Three studies (7%) corrected for the bias, 1 by exposure strata, and 5 (12%) restricted analyses to confirmed cases. The app (app http://apps.p-95.com/ISPE/) uses values of PPV and sensitivity (or a range of possible values) in each exposure strata and returns corrected point estimates and confidence intervals. The app demonstrates that small differences between comparison groups in PPV or sensitivity can introduce bias even when accuracy estimates are high.ConclusionsOutcome misclassification is not usually corrected in pharmacoepidemiology database studies although correction methods using routinely measured indices are available. Error indices are needed for each comparison group to correct RR estimates for these errors. The app should encourage understanding of this bias and increase adjustment.
Recent progress in functional materials from lyotropic chromonic liquid crystals
Authors: Bosire Reuben , Ndaya Dennis , Kasi Rajeswari M 
Published: August 2020

AbstractResearch on lyotropic chromonic liquid crystals has grown tremendously from fundamental studies to designing functional materials for applications in biological fields and other technological areas. The majority of the research has centered on utilizing chromonic small molecules predominantly dissolved in aqueous solvents. But these often present processing difficulties and a host of other unattractive features including poor mechanical and chemical stabilities. Mesophase properties of chromonic liquid crystals as characterized using X‐ray diffraction and scattering techniques, spectroscopy and light microscopy are explored. We review potential applications and future perspectives of this subfield where methods of transforming chromonic molecules into functional materials are highlighted. © 2020 Society of Industrial Chemistry
Tail‐Robust Quantile Normalization
Authors: Brombacher Eva , Schad Ariane , Kreutz Clemens 
Published: August 2020

AbstractHigh‐throughput biological data—such as mass spectrometry (MS)‐based proteomics data—suffer from systematic non‐biological variance due to systematic errors. This hinders the estimation of “real” biological signals and, in turn, decreases the power of statistical tests and biases the identification of differentially expressed proteins. To remove such unintended variation, while retaining the biological signal of interest, analysis workflows for quantitative MS data typically comprise normalization prior to their statistical analysis. Several normalization methods, such as quantile normalization (QN), have originally been developed for microarray data. In contrast to microarray data proteomics data may contain features, in the form of protein intensities that are consistently high across experimental conditions and, hence, are encountered in the tails of the protein intensity distribution. If QN is applied in the presence of such proteins statistical inferences of the features’ intensity profiles are impeded due to the biased estimation of their variance. A freely available, novel approach is introduced which serves as an improvement of the classical QN by preserving the biological signals of features in the tails of the intensity distribution and by accounting for sample‐dependent missing values (MVs): The “tail‐robust quantile normalization” (TRQN).
Meeting report from the Prostate Cancer Foundation PSMA theranostics state of the science meeting
Authors: Miyahira Andrea K. , Pienta Kenneth J. , Babich John W. , Bander Neil H. , Calais Jeremie , Choyke Peter , Hofman Michael S. , Larson Steven M. , Lin Frank I. , Morris Michael J. , Pomper Martin G. , Sandhu Shahneen , Scher Howard I. , Tagawa Scott T. , Williams Scott , Soule Howard R. 
Published: August 2020

AbstractIntroductionThe Prostate Cancer Foundation (PCF) convened a PCF prostate‐specific membrane antigen (PSMA) Theranostics State of the Science Meeting on 18 November 2019, at Weill Cornell Medicine, New York, NY.MethodsThe meeting was attended by 22 basic, translational, and clinical researchers from around the globe, with expertise in PSMA biology, development and use of PSMA theranostics agents, and clinical trials. The goal of this meeting was to discuss the current state of knowledge, the most important biological and clinical questions, and critical next steps for the clinical development of PSMA positron emission tomography (PET) imaging agents and PSMA‐targeted radionuclide agents for patients with prostate cancer.ResultsSeveral major topic areas were discussed including the biology of PSMA, the role of PSMA‐targeted PET imaging in prostate cancer, the physics and performance of different PSMA‐targeted PET imaging agents, the current state of clinical development of PSMA‐targeted radionuclide therapy (RNT) agents, the role of dosimetry in PSMA RNT treatment planning, barriers and challenges in PSMA RNT clinical development, optimization of patient selection for PSMA RNT trials, and promising combination treatment approaches with PSMA RNT.DiscussionThis article summarizes the presentations from the meeting for the purpose of globally disseminating this knowledge to advance the use of PSMA‐targeted theranostic agents for imaging and treatment of patients with prostate cancer.
Modulation of granulocyte colony stimulating factor conformation and receptor binding by methionine oxidation
Authors: Singh Sumit Kumar , Mishra Avinash , Goel Gaurav , Chirmule Narendra , Rathore Anurag S. 
Published: August 2020

AbstractBiosimilars offer an avenue for potential cost savings and enhanced patient access to various emerging therapies in a budget neutral way. Biosimilars of the granulocyte colony stimulating factor (GCSF) are an excellent example in this regard with as many as 18 versions of the drug being currently approved across globe for treatment of neutropenia. Here, we identified oxidation of the various methionine residues in GCSF as a key heterogeneity that adversely impact its efficacy. In agreement with earlier studies, it was found that oxidation of Met 122 and Met 127 significantly contributes toward reduction of GCSF efficacy, measured using binding affinity to the GCSF receptor. The combination of molecular dynamics simulation along with structural characterization studies established that oxidation of Met 127 and Met 122 brings about a small local conformational change around the B‐C loop in GCSF structure due to slight displacement of Asp113 and Thr117 residues. The simulation studies were validated using fluorescence quenching experiments using acrylamide as quencher and site‐directed mutagenesis by replacing Met 122 and Met 127 residues with alanine. The results of this study lead to an enhanced mechanistic understanding of the oxidation in GCSF and should be useful in protein engineering efforts to design stable, safe, and efficacious GCSF product. In addition, the structure‐function information can provide targets for protein engineering during early drug development and setting specifications of allowable limits of product variants in biosimilar products.
A stochastically curtailed two‐arm randomised phaseIItrial design for binary outcomes
Authors: Law Martin , Grayling Michael J. , Mander Adrian P. 
Published: August 2020

SummaryRandomised controlled trials are considered the gold standard in trial design. However, phase II oncology trials with a binary outcome are often single‐arm. Although a number of reasons exist for choosing a single‐arm trial, the primary reason is that single‐arm designs require fewer participants than their randomised equivalents. Therefore, the development of novel methodology that makes randomised designs more efficient is of value to the trials community. This article introduces a randomised two‐arm binary outcome trial design that includes stochastic curtailment (SC), allowing for the possibility of stopping a trial before the final conclusions are known with certainty. In addition to SC, the proposed design involves the use of a randomised block design, which allows investigators to control the number of interim analyses. This approach is compared with existing designs that also use early stopping, through the use of a loss function comprised of a weighted sum of design characteristics. Comparisons are also made using an example from a real trial. The comparisons show that for many possible loss functions, the proposed design is superior to existing designs. Further, the proposed design may be more practical, by allowing a flexible number of interim analyses. One existing design produces superior design realisations when the anticipated response rate is low. However, when using this design, the probability of rejecting the null hypothesis is sensitive to misspecification of the null response rate. Therefore, when considering randomised designs in phase II, we recommend the proposed approach be preferred over other sequential designs.
Accurate prediction of standard enthalpy of formation based on semiempirical quantum chemistry methods with artificial neural network and molecular descriptors
Authors: Wan Zhongyu , Wang Quan‐De , Liang Jinhu 
Published: August 2020

AbstractThis work investigates possible improvements in the accuracy of semiempirical quantum chemistry (SQC) methods for the prediction of standard enthalpy of formation (ΔfHo) through the use of an artificial neural network (ANN) with molecular descriptors. A total of 142 organic compounds with enough structural diversity has been considered in the training set. Standard enthalpy of formation for the selected compounds at the semiempirical PM3 and PM6 quantum chemistry methods is collected from literature and is calculated by using the semiempirical PM7 method in this work. The multiple stepwise regression is first used to screen effective molecular descriptors, which are highly correlated with the error terms of the standard enthalpy of formation compared with experimental values. The obtained seven effective molecular descriptors are then used as input set to establish three 7‐11‐1 neural network‐based correction models to improve the accuracy of SQC methods. By using the developed correction models, the mean absolute errors for ΔfHo of PM3, PM6, and PM7 methods are reduced from 22.36, 18.60, and 17.27 to 9.86, 9.83, and 8.95, respectively, in kJ/mol. Meanwhile, the results of the test set show that the neural network does not have the problem of overfitting. Detailed analysis of the seven effective molecular descriptors indicates that the major source of the correction models is the electron‐withdrawing effect. The developed ANN models for the three selected SQC methods provide an efficient method for the quick and accurate prediction of thermodynamic properties.
Structural, vibrational, mechanical, and optoelectronic properties of LiBH4 for hydrogen storage and optoelectronic devices: First‐principles study
Authors: Khalil R. M. Arif , Hussain Muhammad Iqbal , Hussain Fayyaz , Rana Anwar Manzoor , Murtaza G. , Shakeel Muhammad , Asif Javed Hafiz M. 
Published: August 2020

AbstractIn order to cope with the energy crisis and global warming issues, researchers are rendering their efforts and paying attention to analyzing and fabricating hydrogen storage devices. That is why comprehensive investigations are made to unfold the structural, vibrational, mechanical, and optoelectronic properties of lithium borohydride (LiBH4), a hydrogen storage material. For this purpose, calculations of the structural properties were performed using local, nonlocal, and hybrid functionals within the framework of density functional theory. For the determination of lattice constants in the orthorhombic phase, local density approximation (LDA), Perdew‐Burke‐Ernzerhof (PBE), and Heyd‐Scuseria‐Ernzerhof (HSE06) density functionals were chosen, and their results were compared with available experimental and theoretical studies. In order to determine infrared (IR) and Raman active modes of vibrations, vibrational spectroscopy was utilized through density functional perturbation theory. Li, B, and H atoms are noted to contribute in different modes of vibrations among various ranges of frequencies, that is, 0 to 400 cm−1, 1100 to 1300 cm−1, and 2250 to 2400 cm−1. Values of the energy band gap are found to be 6.35, 6.81, and 7.58 eV for LDA, PBE, and HSE06 functionals, respectively, indicating the insulating nature of LiBH4. Such fascinating properties make these compounds promising candidates for future applications in optoelectronic devices. Mechanical analysis revealed that LiBH4 is a brittle and stiffer material. Other optical properties, such as dielectric constant, refractive index, reflectivity, absorptivity, conductivity, and loss function, were also calculated with the assistance of the well‐recognized Kramer‐Kronig relation. The energy loss function depicted a plasma frequency of 13.7 eV, noted from the highest loss peak. It can be concluded that this material is not only suitable for hydrogen storage but also for optoelectronic devices.
Thunderstorm‐related asthma can occur in New Zealand
Authors: Sabih Ayan , Russell Claire , Chang Catherina L. 
Published: August 2020

AbstractThunderstorm asthma is induced by specific weather conditions causing breakdown and widespread distribution of allergens. Thunderstorm asthma had previously been considered unlikely to occur in New Zealand (NZ), given its local weather patterns. Storm events on 2 December 2017 led to increased asthma presentations at Waikato Hospital in Hamilton. Analyses of patient presentations led us to conclude that these presentations were similar to international descriptions of thunderstorm asthma. This is the first time such presentations have been reported in NZ. Documenting these events accurately is important as this is the first step to making a plan that would enable paramedics and emergency facilities across NZ to respond to any larger scale thunderstorm asthma events in the future.
Machine Learning Lattice Constants for Cubic Perovskite Compounds
Authors: Zhang Yun , Xu Xiaojie 
Published: August 2020

AbstractCubic perovskites have attracted great attention in the past decade due to unique and tunable optical, mechanical, and electrical properties, which are promising candidates for various applications such as solar cells, light emitting diodes, actuators, and laser cooling devices. The lattice constant, a, as the only variable parameter among the six parameters in the crystal structure, has a significant impact on the structural stability, bandgap structure, and thus materials performance. In this study, we develop the Gaussian process regression (GPR) model to shed light on the statistical relationship between ionic radii and lattice constants for cubic perovskite
compounds. A total of 135 samples with lattice constants ranging from 3.680 Å to 6.330 Å are explored. The model has a high degree of accuracy and stability that contributes to fast and robust lattice constant estimations.
Disposable 3D GNAs/AuNPs DNA‐Circuit Strip for miRNAs Dynamic Quantification
Authors: Bao Jing , Qiu Xiaopei , Yang Huisi , Lu Wenqiang , Yang Mei , Gu Wei , Wu Lixiang , Huo Danqun , Luo Yang , Hou Changjun 
Published: August 2020

AbstractReal‐time quantitative monitoring of miRNAs plays an essential role in diagnosis and therapeutics. Herein, a DSN‐coupled graphene nanoarray/gold nanoparticles (GNAs/AuNPs) carbon paper (CP) electrode for the dynamic, sensitive, and real‐time analysis of miRNAs is reported. GNAs are vertically grown on the conductive CP by radio frequency plasma enhanced chemical vapor deposition, and AuNPs are electrodeposited on CP/GNAs to build a 3D ultrasensitive sensing interface with large specific surface area, good conductivity and biocompatibility. The dynamic quantitative monitoring of microRNA‐21 (miR‐21) is realized by cyclic voltammetry with a series of different concentrations within 16 min, and this 3D GNAs/AuNPs DNA‐circuit strip shows good performance for the simultaneous detection of miR‐21 and miR‐155, and the detection limits are as low as 21.4 and 30.3 am, respectively. Moreover, comparable detection results are achieved for clinical samples between the proposed sensor and qRT‐PCR, suggesting the reliability of the constructed sensor. This ultrasensitive sensing and disposable DNA‐circuit strip with 3D structure can efficiently shorten the diffusion distance between reactive biomolecules and the sensing interface, enhance the hybridization of probes and improve the sensitivity of the biosensor, holding great promise for the rapid, quantitative and dynamic monitoring of multiple low concentrations of biomolecules in point‐of‐care clinical analysis.
A revised subtribal classification of Gnaphalieae (Asteraceae)
Authors: Smissen Rob D. , Bayer Randall J. , Bergh Nicola G. , Breitwieser Ilse , Freire Susana E. , Galbany‐Casals Mercè , Schmidt‐Lebuhn Alexander N. , Ward Josephine M. 
Published: August 2020

AbstractGnaphalieae are one of the larger tribes of the daisy family Asteraceae (Compositae) with c. 2100 species in 178 genera, occurring globally across a wide range of temperate habitats. Recent years have seen considerable advances in our understanding of their phylogenetics and evolution, but there is no widely accepted, stable subtribal classification. The present paper summarises the taxonomic history and presents the various major clades that have been named informally in phylogenetic studies. We also provide the most comprehensive phylogenetic analysis of DNA sequence data to date, including over 1000 species. Based on published studies and our new phylogenetic analyses, we suggest a subdivision of the tribe into two subtribes. These are a largely African‐endemic Relhaniinae (124 species in 11 genera) and a much enlarged Gnaphaliinae, the latter accounting for more than 90% of the species diversity (c. 2000 species in 167 genera). Although a finer division of Gnaphaliinae sensu amplo may be desirable, there are at present several obstacles to such a classification, in particular contradictory or ambiguous inferences of relationships.