bluuebunny/crossref_metadata_2025_split huggingface dataset:
An integrated prognostic model for diffuse large B‐cell lymphoma treated with immunochemotherapy
Authors: Rodríguez Marta , Alonso‐Alonso Ruth , Fernández‐Miranda Ismael , Mondéjar Rufino , Cereceda Laura , Tráscasa Álvaro , Antonio‐Da Conceiçao Anabel , Borregón Jennifer , Gato Lucía , Tomás‐Roca Laura , Bárcena Carmen , Iglesias Begoña , Climent Fina , González‐Barca Eva , Camacho Francisca Inmaculada , Mayordomo Émpar , Olmedilla Gabriel , Gómez‐Prieto Pilar , Castro Yolanda , Serrano‐López Juana , Sánchez‐García Joaquín , Montes‐Moreno Santiago , García‐Cosío Mónica , Martín‐Acosta Paloma , García Juan F. , Planelles María , Quero Cristina , Provencio Mariano , Mahíllo‐Fernández Ignacio , Rodríguez‐Pinilla Socorro M. , Derenzini Enrico , Pileri Stefano , Sánchez‐Beato Margarita , Córdoba Raúl , Piris Miguel A. 
Published: May 2022

AbstractDiffuse large B‐cell lymphoma (DLBCL), the most frequent non‐Hodgkin's lymphoma subtype, is characterized by strong biological, morphological, and clinical heterogeneity, but patients are treated with immunochemotherapy in a relatively homogeneous way. Here, we have used a customized NanoString platform to analyze a series of 197 homogeneously treated DLBCL cases. The platform includes the most relevant genes or signatures known to be useful for predicting response to R‐CHOP (Rituximab, Cyclophosphamide, Doxorubicin, Vincristine, and Prednisone) in DLBCL cases. We generated a risk score that combines the International Prognostic Index with cell of origin and double expression of MYC/BCL2, and stratified the series into three groups, yielding hazard ratios from 0.15 to 5.49 for overall survival, and from 0.17 to 5.04 for progression‐free survival. Group differences were highly significant (p < 0.0001), and the scoring system was applicable to younger patients (<60 years of age) and patients with advanced or localized stages of the disease. Results were validated in an independent dataset from 166 DLBCL patients treated in two distinct clinical trials. This risk score combines clinical and biological data in a model that can be used to integrate biological variables into the prognostic models for DLBCL cases.
Assessment of reporting practices and reproducibility potential of a cohort of published studies in computational knee biomechanics
Authors: Halloran Jason P. , Abdollahi Nohouji Neda , Hafez Mhd A. , Besier Thor F. , Chokhandre Snehal K. , Elmasry Shady , Hume Donald R. , Imhauser Carl W. , Rooks Nynke B. , Schneider Marco T. Y. , Schwartz Ariel , Shelburne Kevin B. , Zaylor William , Erdemir Ahmet 
Published: May 2022

AbstractReproducible research serves as a pillar of the scientific method and is a foundation for scientific advancement. However, estimates for irreproducibility of preclinical science range from 75% to 90%. The importance of reproducible science has not been assessed in the context of mechanics‐based modeling of human joints such as the knee, despite this being an area that has seen dramatic growth. Framed in the context of five experienced teams currently documenting knee modeling procedures, the aim of this study was to evaluate reporting and the perceived potential for reproducibility across studies the teams viewed as important contributions to the literature. A cohort of studies was selected by polling, which resulted in an assessment of nine studies as opposed to a broader analysis across the literature. Using a published checklist for reporting of modeling features, the cohort was evaluated for both “reporting” and their potential to be “reproduced,” which was delineated into six major modeling categories and three subcategories. Logistic regression analysis revealed that for individual modeling categories, the proportion of “reported” occurrences ranged from 0.31, 95% confidence interval (CI) [0.23, 0.41] to 0.77, 95% CI: [0.68, 0.86]. The proportion of whether a category was perceived as “reproducible” ranged from 0.22, 95% CI: [0.15, 0.31] to 0.44, 95% CI: [0.35, 0.55]. The relatively low ratios highlight an opportunity to improve reporting and reproducibility of knee modeling studies. Ongoing efforts, including our findings, contribute to a dialogue that facilitates adoption of practices that provide both credibility and translation possibilities.
Significance of dimeric surfactant on kinetic study of organophosphorus compounds
Authors: Lakra Jyotsna , Tikariha Deepti , Kumar Birendra 
Published: May 2022

AbstractDimeric surfactants have shown significant role on hydrolysis of organo‐phosphorus compounds. In this study, we have studied the kinetic hydrolysis of p‐nitrophenyl acetate (PNPA), p‐nitrophenyl benzoate (PNPB), and p‐dinitrophenyl diphenyl phosphate (PNPDPP) in presence of novel dimeric surfactants 12‐4‐12, 2Br– (butanediyl‐1,4‐bis(dimethyldodecylammonium bromide), 12–4(OH)‐12, 2Br– (2‐butanol‐1,4‐bis(dimethyldodecylammonium bromide) with conventional nucleophiles, benzohydroxamic acid (BHA), and salicylhydroxamic acid (SHA) by spectrophotometry at 27°C. Kinetic study on effect of micelles on reaction rates have been investigated and rationalization effects of micelles determination using kinetic model. The experimental kinetic data were fitted with micellar pseudophase model for determination micellar substrate binding and parameters. The second order rate constant is processed for comparing the reactivities in aqueous and micellar pseudophase.
Investigating the use of machine learning to generate ventilation images from CT scans
Authors: Grover James , Byrne Hilary L. , Sun Yu , Kipritidis John , Keall Paul 
Published: May 2022

AbstractBackgroundRadiotherapy treatment planning incorporating ventilation imaging can reduce the incidence of radiation‐induced lung injury. The gold‐standard of ventilation imaging, using nuclear medicine, has limitations with respect to availability and cost.PurposeAn alternative type of ventilation imaging to nuclear medicine uses 4DCT (or breath‐hold CT [BHCT] pair) with deformable image registration (DIR) and a ventilation metric to produce a CT ventilation image (CTVI). The purpose of this study is to investigate the application of machine learning as an alternative to DIR‐based methods when producing CTVIs.MethodsA patient dataset of 15 inhale and exhale BHCTs and Galligas PET ventilation images were used to train and test a 2D U‐Net style convolutional neural network. The neural network established relationships between axial input BHCT image pairs and axial labeled Galligas PET images and was evaluated using eightfold cross‐validation. Once trained, the neural network could produce a CTVI from an input BHCT image pair. The CTVIs produced by the neural network were qualitatively assessed visually and quantitatively compared to a Galligas PET ventilation image using a Spearman correlation and Dice similarity coefficient (DSC). The DSC measured the spatial overlap between three segmented equal lung volumes by ventilation (high, medium, and low functioning lung [LFL]).ResultsThe mean Spearman correlation between the CTVIs and the Galligas PET ventilation images was 0.58 ± 0.14. The mean DSC over high, medium, and LFL between the CTVIs and Galligas PET ventilation images was 0.55 ± 0.06. Visually, a systematic overprediction of ventilation within the lung was observed in the CTVIs with respect to the Galligas PET ventilation images, with jagged regions of ventilation in the sagittal and coronal planes.ConclusionsA convolutional neural network was developed that could produce a CTVI from a BHCT image pair, which was then compared with a Galligas PET ventilation image. The performance of this machine learning method was comparable to previous benchmark studies investigating a DIR‐based CTVI, warranting future development, and investigation of applying machine learning to a CTVI.
Adaptive confidence regions for indirect tracking of moving tumors in radiotherapy
Authors: Remy Charlotte , Bouchard Hugo 
Published: May 2022

AbstractBackgroundTarget motion in the course of radiotherapy is one of the largest factors affecting the treatment quality of highly dynamic sites such as lung. A critical component of real‐time motion management is not only the prediction of tumor location at a future point in time but assessment of positional uncertainty for the purposes of margin adjustment and optimization of validation schemes.PurposeIn this study, we propose to investigate the ability of a confidence estimator to accurately reflect the reliability of individual target position predictions and prospectively detect large prediction errors by relying exclusively on a surrogate signal.MethodsThis work uses a Bayesian framework for indirect tracking. While constant covariance estimates are commonly used to express the uncertainty of the models involved, in this study new adaptive estimates are derived from the surrogate behavior to reflect increasing uncertainty when the breathing conditions differ from the reference conditions observed during the training step. The accuracy of the resulting 95% predicted confidence regions (CRs) is evaluated on nine breathing sequences involving changes of respiratory types (free, thoracic, abdominal, deep). The breathing motions are collected simultaneously from a lung target and two different surrogate signals (an external marker and an anatomical location within the liver). Receiver operating characteristic (ROC) analysis is performed to evaluate the ability of the predicted uncertainty to prospectively detect large prediction errors.ResultsHigher CR accuracy is obtained when using the proposed adaptive estimates over using constant estimations: on average over the cohort, the proportion of actual target positions lying within the 95% CR is increased by 40 and 35 p.p. with the internal and external surrogates. The time‐dependent inflation of the CR width tends to match the magnitude variation of the prediction errors: the adaptive CR effectively enlarges when the target position cannot be predicted reliably, which corresponds to potentially high prediction errors. More precisely, the ROC analysis indicates that the proposed uncertainty estimate can detect if prediction errors are greater than 5 mm with on average high sensitivity (90%) and modest specificity (54% and 47% from internal and external surrogates, respectively).ConclusionsWhile relying exclusively on the surrogate motion characteristics being continuously monitored, the Bayesian framework coupled to adaptive uncertainty estimations can provide reliable CR able to detect large prediction errors. The findings of this study could be further used to automatically trigger risk management mechanisms prospectively.
Tuning the performance of PA6/EPDM‐MA nanocomposites reinforced with Ni0.5Zn0.5Fe2O4. Effect of the mixing protocol on mechanical, thermal, thermomechanical, magnetic, and morphological behavior
Authors: Luna Carlos Bruno Barreto , da Silva Barbosa Ferreira Eduardo , da Silva Adriano Lima , Araújo Edcleide Maria , de Melo Costa Ana Cristina Figueiredo , Wellen Renate Maria Ramos 
Published: May 2022

AbstractThe mixing protocol effect was investigated in nanocomposites based on polyamide 6 (PA6) and maleic anhydride grafted ethylene‐propylene‐diene (EPDM‐MA), using Ni‐Zn ferrite as filler. The nanocomposites were processed using an internal mixer and specimens were injection molded. Compounds properties were investigated through Izod impact strength, tensile strength, x‐ray diffraction (XRD), magnetic measurements, differential scanning calorimetry (DSC), thermogravimetry (TG), heat deflection temperature (HDT), and scanning electron microscopy (SEM). PA6/EPDM‐MA mixture showed super‐tough behavior, with an increase of around 918% in impact strength, compared with PA6. However, there was a loss close to 50% in the elastic modulus and 5% in HDT, due to the high flexibility. In view of this, this mixture was selected for the production of nanocomposites toughened with Ni‐Zn ferrite, using three mixing sequences. When the nanocomposite was processed by the simultaneous mixing of all components (PA6/EPDM‐MA/Ni‐Zn), the highest impact strength (458 J/m) was reached, corresponding to a gain of 486%, compared with PA6. On the other hand, when Ni‐Zn ferrite and PA6 were initially premixed by melting, before EPDM‐MA addition in a second processing step, HDT and impact strength properties increased by 6% and 281%, in relation to PA6. In addition, the nanocomposites showed magnetic responses, with a soft material behavior, that is, they magnetize and demagnetize easily. In general, toughened and magnetic nanocomposites were produced, with good mechanical and thermal properties, displaying potential to produce magnetic films.
Obesity is a risk factor for decrease in lung function after COVID‐19 infection in children with asthma
Authors: Soyak Aytekin Elif , Sahiner Umit M. , Tuten Dal Sevda , Unsal Hilal , Hakverdi Ozan , Oguz Berna , Ozsurekci Yasemin , Sekerel Bulent E. , Soyer Ozge 
Published: May 2022

AbstractIntroductionIt is not clear whether asthma, the most frequent chronic disease in childhood, is a risk for severe SARS‐CoV‐2 infection in the pediatric population and how SARS‐CoV‐2 infection affects the lung functions in these patients.PurposeWe aimed to investigate the course and the consequences of SARS‐CoV‐2 infection among children with asthma and determine the risk factors for the decline in lung function tests (LFTs).MethodsIn this retrospective study, asthmatic children with coronavirus disease 2019 (COVID‐19) were compared with a random control group of asthmatic patients without COVID‐19. In addition, the clinical course and the effect on LFTs of COVID‐19 among children with asthma were also evaluated.ResultsOne hundred eighty‐nine patients who had COVID‐19, and 792 who did not were included in the study. Fever, fatigue, and cough were the most frequent symptoms during COVID‐19. Regarding the severity of COVID‐19, 163 patients (87.6%) had a mild clinical condition, 13 (7%) had moderate disease, 1 (0.5%) had severe disease, and 2 had (1.1%) critically ill disease. Two patients were diagnosed with multisystem inflammatory syndrome in children (MIS‐C), one patient suffered from pneumothorax. LFTs of the patients before and after COVID‐19 infection were analyzed; no significant differences were found in FEV1% (91.7% vs. 90.9%, p = 0.513), FVC% (89.8% vs. 90.8%, p = 0.502) and FEV1/FVC (103.1% vs. 100.6%, p = 0.056), while FEF25%–75% values (107.6% vs. 98.4%, p < 0.001) were significantly lower after the COVID‐19 infection. Obesity (odds ratio [OR]: 3.785, 95% confidence interval [CI]: 1.152–12.429, p = 0.028] and having a family history of atopy (OR: 3.359, 95% CI: 1.168–9.657, p = 0.025] were found to be the independent risk factors for ≥25% decrease in FEF25–75 after COVID‐19 infection.ConclusionCOVID‐19 infection leads to dysfunction of the small airways in asthmatic children and obesity is an independent risk factor for a ≥25% decrease in FEF25–75. The long‐term effects of COVID‐19 infection especially on small airways require close monitoring in children with asthma.
The interpretation and implications of the Knutsonet al. 2020 projections of changes in the frequency and intensity of tropical cyclones under climate change
Authors: Jewson Stephen 
Published: May 2022

AbstractA recent meta‐study presented distributions of the possible impacts of climate change on the frequency and intensity of tropical cyclones for the six main tropical cyclone basins, summarizing many previous studies. However, it is not obvious how to interpret the distributions given in the meta‐study. I describe algorithms that can be used to interpret the changes in frequency and intensity in a mutually consistent way. I then investigate the nature of the relationships between the changes in frequency and intensity and find that the intensity changes are just a different way of looking at the information provided by the changes in frequency. The mean of the mean intensity distribution increases in all basins. In some basins this increase is associated mostly with an increasing frequency of the most intense tropical cyclones, while in other basins it is associated mostly with a decreasing frequency of less intense tropical cyclones. I consider the implications for a simple measure of risk that combines changes in frequency and intensity, and find that the most extreme risks increase for five out of six of the basins using this measure. The results of this study can be used to produce mutually consistent simulations of changes in tropical cyclone frequency and intensity. These can be used for further analysis of the effects of climate change on tropical cyclones. However, the results come with the major caveat that there are many uncertainties in the inputs and in the various steps of analysis. Finally, I give recommendations for which metrics could usefully be extracted from climate models in future studies of tropical cyclones under climate change to help with interpretation and impacts studies.
Uniform exponential stability criteria with verification for nonautonomous switched nonlinear systems with uncertainty
Authors: Lu Junjie , She Zhikun , Liu Kairong 
Published: May 2022

AbstractThis article is concerned with the sufficient and necessary conditions for the global uniform exponential stability (GUES) of a class of uncertain nonautonomous switched nonlinear systems (UNSNS), that is, systems with time‐varying uncertain information. To start with, based on a piecewise continuous scalar function and a piecewise differentiable uncertainty‐dependent Lyapunov function along the trajectories, we propose alternative sufficient and necessary conditions for the GUES of UNSNS. Afterwards, for removing the dependence on uncertain information of the required Lyapunov functions, we combine an uncertainty‐independent Lyapunov function with its right upper Dini derivative and the above piecewise continuous scalar function to further obtain other alternative sufficient and necessary conditions for the GUES of UNSNS. Note that our conditions release the requirement on negative definiteness of the time‐derivatives and Dini derivatives of Lyapunov functions respectively, which is illustrated by Example 1. Further, for the rational UNSNS, we propose a linear semidefinite programming based computable approach to mechanically verify our current theoretical results. In the end, the effectiveness of our theoretical results and mechanical approach are illustrated by two examples.
Photosensitizer Anchored Nanoparticles: A Potential Material for Photodynamic Therapy
Authors: Babu Nisha , Rahaman Shaik Abdul , John Athira Maria , Balakrishnan Sreeja Puthenveetil 
Published: May 2022

AbstractDetection and treatment of cancer have been demanding areas with the increase in cancer and malignant diseases across the globe. Photodynamic therapy is a multi‐step treatment procedure using photosensitizers as a drug in the presence of light. Photosensitizers anchored on different nanomaterials through covalent and non‐covalent interactions contribute significantly to photodynamic therapy. Nanoparticles have been employed as promising carriers to transport photosensitizers to the target cells. Photosensitizer functionalized nanoparticles are more effective in terms of stability and water solubility than bare ones. This review is a brief account of different types of nanoparticles functionalized on photosensitizers currently used for photodynamic therapy. We have focused on photosensitizer anchored organic, inorganic, and carbon‐based nanomaterials, which can be effectively used in photodynamic therapy.
Crosslinkable and Chelatable Organic Ligand Enables Interfaces and Grains Collaborative Passivation for Efficient and Stable Perovskite Solar Cells
Authors: Ma Zongwen , Yu Runnan , Xu Zhiyang , Wu Guangzheng , Gao Huaizhi , Wang Ruyue , Gong Yongshuai , Yang Jing , Tan Zhan'ao 
Published: May 2022

AbstractThe organic–inorganic halide perovskite solar cell (PerSC) is the state‐of‐the‐art emerging photovoltaic technology. However, the environmental water/moisture and temperature‐induced intrinsic degradation and phase transition of perovskite greatly retard the commercialization process. Herein, a dual‐functional organic ligand, 4,7‐bis((4‐vinylbenzyl)oxy)‐1,10‐phenanthroline (namely, C1), with crosslinkable styrene side‐chains and chelatable phenanthroline backbone, synthesized via a cost‐effective Williamson reaction, is introduced for collaborative electrode interface and perovskite grain boundaries (GBs) engineering. C1 can chemically chelate with Sn4+ in the SnO2 electron transport layer and Pb2+ in the perovskite layer via coordination bonds, suppressing nonradiative recombination caused by traps/defects existing at the interface and GBs. Meanwhile, C1 enables in situ crosslinking via thermal‐initiated polymerization to form a hydrophobic and stable polymer network, freezing perovskite morphology, and resisting moisture degradation. Consequently, through collaborative interface‐grain engineering, the resulting PerSCs demonstrate high power conversion efficiency of 24.31% with excellent water/moisture and thermal stability. The findings provide new insights of collaborative interface‐grain engineering via a crosslinkable and chelatable organic ligand for achieving efficient and stable PerSCs.
Liquid Phase Oxidation of Hydrocarbons to High‐Value Chemicals in Microfluidic Reactors – Prospects and Challenges
Authors: Siddiquee Muhammad N. , Hossain Mohammad M. , Nazemifard Neda 
Published: May 2022

AbstractLiquid phase oxidation (LPO) of hydrocarbon is an industrially important process to produce petrochemicals and pharmaceuticals. It follows a free radical path having initiation, propagation and termination. The initiation step is slow while the propagation and termination steps are fast. The main challenge of such process is to control product selectivity at an appreciable conversion level. With the advancement of microfluidic reactor technology, it is possible to control the free radical steps. The present contribution critically reviewed the reaction engineering aspects of LPO of hydrocarbon, the influence of microfluidic reactor design and operation on reaction mechanism, conversion and product selectivity. It also outlines the challenges associated with microfluidic reactor operation, and prospects to apply the understanding from microfluidic reactors in few sectors. The understanding from the free radical oxidation process can also be applied to any other free radical processes.
Pathogenesis of neural tube defects: The regulation and disruption of cellular processes underlying neural tube closure
Authors: Engelhardt David M. , Martyr Cara A. , Niswander Lee 
Published: May 2022

AbstractNeural tube closure (NTC) is crucial for proper development of the brain and spinal cord and requires precise morphogenesis from a sheet of cells to an intact three‐dimensional structure. NTC is dependent on successful regulation of hundreds of genes, a myriad of signaling pathways, concentration gradients, and is influenced by epigenetic and environmental cues. Failure of NTC is termed a neural tube defect (NTD) and is a leading class of congenital defects in the United States and worldwide. Though NTDs are all defined as incomplete closure of the neural tube, the pathogenesis of an NTD determines the type, severity, positioning, and accompanying phenotypes. In this review, we survey pathogenesis of NTDs relating to disruption of cellular processes arising from genetic mutations, altered epigenetic regulation, and environmental influences by micronutrients and maternal condition.This article is categorized under:
Congenital Diseases > Genetics/Genomics/Epigenetics
Neurological Diseases > Genetics/Genomics/Epigenetics
Neurological Diseases > Stem Cells and Development