bluuebunny/crossref_metadata_2025_split huggingface dataset:
Beating cancer‐related fatigue with the Untire mobile app: Results from a waiting‐list randomized controlled trial
Authors: Spahrkäs Simon Sebastian , Looijmans Anne , Sanderman Robbert , Hagedoorn Mariët 
Published: July 2020

AbstractObjectiveThis waiting‐list randomized controlled trial examined the effectiveness of a self‐management mHealth app in improving fatigue and quality of life (QoL) in cancer patients and survivors.MethodsPersons with cancer‐related fatigue (CRF) were recruited across four English speaking countries, via social media, and randomized into intervention (n = 519) and control (n = 280) groups. Whereas the intervention group received immediate access to the Untire app, the control group received access only after 12‐weeks. Primary outcomes fatigue severity and interference, and secondary outcome QoL were assessed at baseline, 4, 8, and 12‐weeks. We ran generalized linear mixed models for all outcomes to determine the effects of app access (yes/no), over 12‐weeks, following the intention‐to‐treat principle.ResultsCompared with the control group, the intervention group showed significantly larger improvements in fatigue severity (d = 0.40), fatigue interference (d = 0.35), and overall QoL on average (d = 0.32) (P's < .01), but not for overall QoL in the past week (P = .07). Sensitivity analyses indicated that participants with medium or high app use benefited most when compared with nonusers and control participants (P's ≤ .02). The intervention effect on fatigue interference was slightly stronger in younger participants (≤56 vs. >56). Effects did not depend on education and cancer status. Reliable change analyses indicated that significantly more people showed full recovery for fatigue in the intervention vs the control group (P's = .02).ConclusionsThe Untire app can be an effective mHealth solution for cancer patients and survivors with moderate to severe CRF.
Classification of Inflammatory Bowel Disease from Formalin‐Fixed, Paraffin‐Embedded Tissue Biopsies via Imaging Mass Spectrometry
Authors: Klein Oliver , Fogt Franz , Hollerbach Stephan , Nebrich Grit , Boskamp Tobias , Wellmann Axel 
Published: July 2020

PurposeDiscrimination between ulcerative colitis (UC) and Crohn's disease (CD) by histologic features alone can be challenging and often leads to inaccurate initial diagnoses in inflammatory bowel disease (IBD) patients. This is mostly due to an overlap of clinical and histologic features. However, exact diagnosis is not only important for patient treatment but it also has a socioeconomic impact. It is therefore important to develop and improve diagnostic tools complementing traditional histomorphological approaches.Experimental DesignIn this retrospective proof‐of‐concept study, the utilization of MALDI imaging is explored in combination with multi‐variate data analysis methods to classify formalin‐fixed, paraffin‐embedded (FFPE) colon biopsies from UC (87 biopsies, 14 patients), CD (71 biopsies, 14 patients), and normal colonic (21 biopsies, 14 patients) tissues.ResultsThe proposed method results in an overall balanced accuracy of 85.7% on patient and of 80.4% on sample level, thus demonstrating that the assessment of IBD from FFPE tissue specimens via MALDI imaging is feasible.Conclusions and Clinical RelevanceThe results emphasize the high potential of this method to distinguish IBD subtypes in FFPE tissue sections, which is a prerequisite for further investigations in retrospective multicenter studies, as well as for a future implementation into clinical routine.
The leading edge: Emerging neuroprotective and neuroregenerative cell-based therapies for spinal cord injury
Authors: Ahuja Christopher S. , Mothe Andrea , Khazaei Mohamad , Badhiwala Jetan H. , Gilbert Emily A. , Kooy Derek , Morshead Cindi M. , Tator Charles , Fehlings Michael G. 
Published: July 2020

Abstract
Spinal cord injuries (SCIs) are associated with tremendous physical, social, and financial costs for millions of individuals and families worldwide. Rapid delivery of specialized medical and surgical care has reduced mortality; however, long-term functional recovery remains limited. Cell-based therapies represent an exciting neuroprotective and neuroregenerative strategy for SCI. This article summarizes the most promising preclinical and clinical cell approaches to date including transplantation of mesenchymal stem cells, neural stem cells, oligodendrocyte progenitor cells, Schwann cells, and olfactory ensheathing cells, as well as strategies to activate endogenous multipotent cell pools. Throughout, we emphasize the fundamental biology of cell-based therapies, critical features in the pathophysiology of spinal cord injury, and the strengths and limitations of each approach. We also highlight salient completed and ongoing clinical trials worldwide and the bidirectional translation of their findings. We then provide an overview of key adjunct strategies such as trophic factor support to optimize graft survival and differentiation, engineered biomaterials to provide a support scaffold, electrical fields to stimulate migration, and novel approaches to degrade the glial scar. We also discuss important considerations when initiating a clinical trial for a cell therapy such as the logistics of clinical-grade cell line scale-up, cell storage and transportation, and the delivery of cells into humans. We conclude with an outlook on the future of cell-based treatments for SCI and opportunities for interdisciplinary collaboration in the field.

Significance statement Traumatic spinal cord injuries (SCIs) result in tremendous lifelong disability and financial burden for millions of patients and caregivers worldwide. Cell-based therapies have emerged as an exciting neuroprotective and neuroregenerative strategy for SCI. This review highlights key preclinical and clinical data in cell therapy with an emphasis on the pathobiology and mechanisms of recovery. Also discussed are adjunct treatments to maximize the efficacy of the grafts. Finally, important translational considerations such as clinical-grade scale-up and delivery techniques are discussed. The article succinctly provides readers with a working knowledge of SCI and cell therapies at the leading edge of research.
Fabrication and Application of Magnetically Catalytic Imprinting Nanozymes
Authors: Hu Yufeng , Liu Jie , Xing Hanwen , Zhou Hao , Wu Minghuo 
Published: July 2020

AbstractNanozymes exhibit excellent enzyme‐like activities but lack specificity. Here, molecularly imprinted polymers (MIPs) based on polypyrrole (PPy) and using methylene blue (MB) as template were grown on Fe3O4 nanozymes to enhance the catalytic selectivity. The obtained composite Fe3O4@PPy MIPs were characterized using a scanning electron microscope, transmission electron microscope, powder X‐ray diffractometer, and vibrating sample magnetometer. The PPy‐encapsulated Fe3O4 nanozymes retained their catalytic ability and almost completely removed MB within 30 min in the presence of sodium persulfate. In comparison with bare Fe3O4 nanozymes, the Fe3O4@PPy MIPs showed superior catalytic selectivity for MB. The apparent rate constants (kapp) for MB, rhodamine B, and methyl orange were 0.073, 0.035, and 0.012 min−1, respectively. Even after five recycling steps, the obtained Fe3O4@PPy MIPs could degrade more than 80% of MB.
Experimental investigations on actively bent concrete shells
Authors: Berger Johannes , Gericke Oliver , Feix Jürgen , Sobek Werner 
Published: July 2020

AbstractThis paper concerns a novel method of constructing shell structures from flat concrete plates by means of active bending. The method is described together with a series of experimental investigations. The theoretical background for this method is given in Berger et al., Actively bent concrete shells, Struct Concrete, 2020. The method makes use of the high capacity for rotation exhibited by thin concrete plates that are reinforced with highly elastic tensile reinforcement. When these plates are subjected to eccentrical forces introduced by external tendons they are raised and bent precisely into a desired curved shape. The method was investigated and refined along with a series of experiments which are the subject of this paper: uniaxial tensile tests on rovings to determine their elongation at fracture, bending tests on small concrete plates to determine possible radii of curvature, and large‐scale tests to demonstrate the erection process of actively bent shells.
An overview of unsupervised drift detection methods
Authors: Gemaque Rosana Noronha , Costa Albert França Josuá , Giusti Rafael , dos Santos Eulanda Miranda 
Published: July 2020

AbstractPractical applications involving big data, such as weather monitoring, identification of customer preferences, Internet log analysis, and sensors warnings require challenging data analysis, since these are examples of problems whose data are generated in streams and usually demand real‐time analytics. Patterns in such data stream problems may change quickly. Consequently, machine learning models that operate in this context must be updated over time. This phenomenon is called concept drift in machine learning and data mining literature. Several different directions have been pursued to learn from data stream and to deal with concept drift. However, most drift detection methods consider that an instance's class label is available right after its prediction, since these methods work by monitoring the prediction results of a base classifier or an ensemble of classifiers. Nevertheless, this constraint is unrealistic in several practical problems. To cope with this constraint, some works are focused on proposing efficient unsupervised or semi‐supervised concept drift detectors. While interesting and recent overview papers dedicated to supervised drift detectors have been published, the scenario is not the same in terms of unsupervised methods. Therefore, this work presents a comprehensive overview of approaches that tackle concept drift in classification problems in an unsupervised manner. Additional contribution includes a proposed taxonomy of state‐of‐the‐art approaches for concept drift detection based on unsupervised strategies.This article is categorized under:
Technologies > Classification
Technologies > Machine Learning
Genomic, transcriptomic and physiological analyses of silver‐resistant Saccharomyces cerevisiae obtained by evolutionary engineering
Authors: Terzioğlu Ergi , Alkım Ceren , Arslan Mevlüt , Balaban Berrak Gülçin , Holyavkin Can , Kısakesen Halil İbrahim , Topaloğlu Alican , Yılmaz Şahin Ülkü , Gündüz Işık Sema , Akman Süleyman , Çakar Zeynep Petek 
Published: July 2020

AbstractSilver is a non‐essential metal used in medical applications as an antimicrobial agent, but it is also toxic for biological systems. To investigate the molecular basis of silver resistance in yeast, we employed evolutionary engineering using successive batch cultures at gradually increased silver stress levels up to 0.25‐mM AgNO3 in 29 populations and obtained highly silver‐resistant and genetically stable Saccharomyces cerevisiae strains. Cross‐resistance analysis results indicated that the silver‐resistant mutants also gained resistance against copper and oxidative stress. Growth physiological analysis results revealed that the highly silver‐resistant evolved strain 2E was not significantly inhibited by silver stress, unlike the reference strain. Genomic and transcriptomic analysis results revealed that there were mutations and/or significant changes in the expression levels of the genes involved in cell wall integrity, cellular respiration, oxidative metabolism, copper homeostasis, endocytosis and vesicular transport activities. Particularly the missense mutation in the RLM1 gene encoding a transcription factor involved in the maintenance of cell wall integrity and with 707 potential gene targets might have a key role in the high silver resistance of 2E, along with its improved cell wall integrity, as confirmed by the lyticase sensitivity assay results. In conclusion, the comparative physiological, transcriptomic and genomic analysis results of the silver‐resistant S. cerevisiae strain revealed potential key factors that will help understand the complex molecular mechanisms of silver resistance in yeast.
NMR Lineshape Analysis of Intrinsically Disordered Protein Interactions
Authors: Waudby Christopher A. , Christodoulou John 
Published: July 2020

AbstractInteractions of intrinsically disordered proteins are central to their cellular functions, and solution-state NMR spectroscopy provides a powerful tool for characterizing both structural and mechanistic aspects of such interactions. Here we focus on the analysis of IDP interactions using NMR titration measurements. Changes in resonance lineshapes in two-dimensional NMR spectra upon titration with a ligand contain rich information on structural changes in the protein and the thermodynamics and kinetics of the interaction, as well as on the microscopic association mechanism. Here we present protocols for the optimal design of titration experiments, data acquisition, and data analysis by two-dimensional lineshape fitting using the TITAN software package.
Indigenous and Scientific Forecasts on Climate Change Perceptions of Arable Farmers: Rwenzori Region, Western Uganda
Authors: Nkuba Michael Robert , Chanda Raban , Mmopelwa Gagoitseope , Adedoyin Akintayo , Mangheni Margaret Najjingo , Lesolle David , Kato Edward 
Published: July 2020

AbstractDespite the dissemination of climate information from national meteorological systems, arable farmers still have challenges of dealing with climate-related risks. This study investigated the effect of using indigenous knowledge-based forecasts (IFs) and scientific knowledge-based forecasts (SFs) on the climate change perceptions of arable farmers in the Rwenzori region, Western Uganda. Data on socio-economic characteristics, use of forecasts, and climate change perceptions was collected from 580 arable farmers and the probit model was used in the analysis. The findings indicated that use of IFs only increased the likelihood of perceiving increase in the frequency in occurrences of droughts and floods. Using both SFs and IFs had a significant positive effect on perception of unpredictable rains and the increase in drought incidence among arable farmers. Although forecasts are important drivers of perceptions, other factors, such as gender, social capital, and dissemination of climate change information by radio, enhance climate change perceptions. Active participation of arable farmers in the dissemination of forecasts by national meteorological services could improve perceptions of climate related risks.
Composite dark matter phenomenology in the presence of lighter degrees of freedom
Authors: Ramos Maria 
Published: July 2020

Abstract
Scalar singlet dark matter in anomaly-free composite Higgs models is accompanied by exotic particles to which the dark matter annihilates. The latter can therefore freeze out even in the absence of couplings to the Standard Model. In this regime, both current and future direct detection constraints can be avoided. Moreover, due to the different decay modes of the extra particles, the dark matter candidate can even escape indirect detection constraints. Assessing this issue requires dedicated simulations of the gamma ray spectrum, that we provide in the present article in the context of SO(7)/SO(6). For the parameter space region that evades constraints from dark matter experiments, we develop new analyses to be performed at a future 100 TeV collider based on the search of the new particles produced in the decay of heavy vector-like quarks.
Classification of equation of state in relativistic heavy-ion collisions using deep learning
Authors: Kvasiuk Yu. , Zabrodin E. , Bravina L. , Didur I. , Frolov M. 
Published: July 2020

Abstract
Convolutional Neural Nets, which is a powerful method of Deep Learning, is applied to classify equation of state of heavy-ion collision event generated within the UrQMD model. Event-by-event transverse momentum and azimuthal angle distributions of protons are used to train a classifier. An overall accuracy of classification of 98% is reached for Au+Au events at $$ \sqrt{s_{NN}} $$

s
NN

= 11 GeV. Performance of classifiers, trained on events at different colliding energies, is investigated. Obtained results indicate extensive possibilities of application of Deep Learning methods to other problems in physics of heavy- ion collisions.
Detection of Coalescent Acute Mastoiditis on MRI in Comparison with CT
Authors: Saat R. , Kurdo G. , Laulajainen-Hongisto A. , Markkola A. , Jero J. 
Published: July 2020

Abstract
Purpose
Current imaging standard for acute mastoiditis (AM) is contrast-enhanced computed tomography (CT), revealing inflammation-induced bone destruction, whereas magnetic resonance imaging (MRI) outperforms CT in detecting intracranial infection. Our aim was to compare the diagnostic performance of MRI with CT in detecting coalescent AM and see to which extent MRI alone would suffice to diagnose or rule out this condition.

Methods
The MR images of 32 patients with AM were retrospectively analyzed. Bone destruction was evaluated from T2 turbo spin echo (TSE) and T1 Gd magnetization-prepared rapid acquisition with gradient echo (MPRAGE) images. Intramastoid enhancement and diffusion restriction were evaluated subjectively and intramastoid apparent diffusion coefficient (ADC) values were measured. The MRI findings were compared with contrast-enhanced CT findings of the same patients within 48 h of the MR scan.

Results
Depending on the anatomical subsite, MRI detected definite bone defects with a sensitivity of 100% and a specificity of 54–82%. Exception was the inner cortical table where sensitivity was only 14% and specificity was 76%. Sensitivity for general coalescent mastoiditis remained 100% due to multiple coexisting lesions. The absence of intense enhancement and non-restricted diffusion had a high negative predictive value for coalescent mastoiditis: an intramastoid ADC above 1.2 × 10−3 mm2/s excluded coalescent mastoiditis with a negative predictive value of 92%.

Conclusion
The MRI did not miss coalescent mastoiditis but was inferior to CT in direct estimation of bone defects. When enhancement and diffusion characteristics are also considered, MRI enables dividing patients into low, intermediate and high-risk categories with respect to coalescent mastoiditis, where only the intermediate risk group is likely to benefit from additional CT.
The Quasiconvex Envelope of Conformally Invariant Planar Energy Functions in Isotropic Hyperelasticity
Authors: Martin Robert J. , Voss Jendrik , Ghiba Ionel-Dumitrel , Sander Oliver , Neff Patrizio 
Published: July 2020

AbstractWe considerconformally invariantenergiesWon the group$${{\,\mathrm{GL}\,}}^{\!+}(2)$$GL+(2)of$$2\times 2$$2×2-matrices with positive determinant, i.e.,$$W:{{\,\mathrm{GL}\,}}^{\!+}(2)\rightarrow {\mathbb {R}}$$W:GL+(2)→Rsuch that$$\begin{aligned} W(A\, F\, B) = W(F) \quad \text {for all }\; A,B\in \{a\, R\in {{\,\mathrm{GL}\,}}^{\!+}(2) \,|\,a\in (0,\infty ),\; R\in {{\,\mathrm{SO}\,}}(2)\}, \end{aligned}$$W(AFB)=W(F)for allA,B∈{aR∈GL+(2)|a∈(0,∞),R∈SO(2)},where$${{\,\mathrm{SO}\,}}(2)$$SO(2)denotes the special orthogonal group and provides an explicit formula for the (notoriously difficult to compute)quasiconvex envelopeof these functions. Our results, which are based on the representation$$W(F)=h\bigl (\frac{\lambda _1}{\lambda _2}\bigr )$$W(F)=h(λ1λ2)ofWin terms of the singular values$$\lambda _1,\lambda _2$$λ1,λ2ofF, are applied to a number of example energies in order to demonstrate the convenience of the singular-value-based expression compared to the more common representation in terms of the distortion$${\mathbb {K}}:=\frac{1}{2}\frac{\Vert F \Vert ^2}{\det F}$$K:=12‖F‖2detF. Applying our results, we answer a conjecture by Adamowicz (in: Atti della Accademia Nazionale dei Lincei. Classe di Scienze Fisiche, Matematiche e Naturali. Rendiconti Lincei. Serie IX. Matematica e Applicazioni, vol 18(2), pp 163, 2007) and discuss a connection between polyconvexity and the Grötzsch free boundary value problem. Special cases of our results can also be obtained from earlier works by Astala et al. (Elliptic partial differential equations and quasiconformal mappings in the plane, Princeton University Press, Princeton, 2008) and Yan (Trans Am Math Soc 355(12):4755–4765, 2003). Since the restricted domain of the energy functions in question poses additional difficulties with respect to the notion of quasiconvexity compared to the case of globally defined real-valued functions, we also discuss more general properties related to the$$W^{1,p}$$W1,p-quasiconvex envelope on the domain$${{\,\mathrm{GL}\,}}^{\!+}(n)$$GL+(n)which, in particular, ensure that a stricter version ofDacorogna’s formulais applicable to conformally invariant energies on$${{\,\mathrm{GL}\,}}^{\!+}(2)$$GL+(2).
Rising extreme sea levels in the German Bight under enhanced $${{\mathrm {CO}}_2}$$ levels: a regionalized large ensemble approach for the North Sea
Authors: Lang Andreas , Mikolajewicz Uwe 
Published: July 2020

AbstractWe quantify the change in extreme high sea level (ESL) statistics in the German Bight under rising $${{\mathrm {CO}}_2}$$

CO
2

concentrations by downscaling a large ensemble of global climate model simulations using the regionally coupled climate system model REMO-MPIOM. While the model setup combines a regionally high resolution with the benefits of a global ocean model, the large ensemble size of 32 members allows the estimation of high return levels with much lower uncertainty. We find that ESLs increase with atmospheric $${{\mathrm {CO}}_2}$$

CO
2

levels, even without considering a rise in the background sea level (BSL). Local increases of up to 0.5 m are found along the western shorelines of Germany and Denmark for ESLs of 20–50 years return periods, while higher return levels remain subject to sampling uncertainty. This ESL response is related to a cascade of an enhanced large-scale activity along the North Atlantic storm belt to a subsequent local increase in predominantly westerly wind speed extremes, while storms of the major West-Northwest track type gain importance. The response is seasonally opposite: summer ESLs and the strength of its drivers decrease in magnitude, contrasting the response of the higher winter ESLs, which governs the annual response. These results have important implications for coastal protection. ESLs do not only scale with the expected BSL rise, but become even more frequent, as preindustrial 50-year return levels could be expected to occur almost every year by the end of the century. The magnitude of the relative change in ESL statistics is hereby up to half of the expected rise in BSL, depending on the location. Changes in the highest extremes are subject to large multidecadal variations and remain uncertain, thus potentially demanding even further safety measures.