bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development and validation of the Terminal Delirium-Related Distress Scale to assess irreversible terminal delirium
Authors: Uchida Megumi , Akechi Tatsuo , Morita Tatsuya , Shima Yasuo , Igarashi Naoko , Miyashita Mitsunori ,   J-HOPE group
Published: January 2021

AbstractObjectiveThere is no tool to appropriately assess terminal delirium, including the natural terminal course. The objective of this study was to develop an evaluation scale to assess distress from irreversible terminal delirium and to examine the validity of the scale.MethodBased on previous qualitative analysis and systematic literature searches, we carried out a survey regarding the views of bereaved families and developed a questionnaire. We extracted items that bereaved families regarded as important and constructed an evaluation scale of terminal delirium. Then, we applied the questionnaire in a cross-sectional questionnaire survey of bereaved relatives of cancer patients who were admitted to a hospice or a palliative care unit.ResultsWe developed the Terminal Delirium-Related Distress Scale (TDDS), a 24 item questionnaire consisting of five subscales (support for families and respect for a patient, ability to communicate, hallucinations and delusions, adequate information about the treatment of delirium, and agitation and restlessness). Two hundred and eighty-one bereaved relatives participated in the validation phase. The construct validity was shown to be good by repeated factor analysis. Convergent validity, confirmed by the correlation between the TDDS and the Care Evaluation Scale (r = 0.651, P < 0.001), was also good. The TDDS had good internal consistency (Cronbach's alpha coefficient for all 24 items = 0.84).Significance of resultsThis study showed that the TDDS is a valid and feasible measure of irreversible terminal delirium.
Seasonal nonstructural carbohydrate patterns in dewberry (Rubus spp.) roots
Authors: Ghantous Katherine M. , Sandler Hilary A. 
Published: January 2021

AbstractApplying control measures when carbohydrate levels are low can decrease the likelihood of plant survival, but little is known about the carbohydrate cycles of dewberry (Rubus spp.), a problematic weed group on cranberry (Vaccinium macrocarpon Aiton) farms. Weedy Rubus plants were collected from areas adjacent to production beds on commercial cranberry farms in Massachusetts, two locations per year for 2 yr. For each site and year, four entire plants were collected at five phenological stages: budbreak, full leaf expansion, flowering, fruit maturity, and after onset of dormancy. Root sections were analyzed for total nonstructural carbohydrates (TNC; starch, sucrose, fructose, and glucose). Overall trends for all sites and years showed TNC were lowest at full leaf expansion or flowering; when sampled at dormancy, TNC concentrations were greater than or equal to those measured at budbreak. Starch, a carbohydrate form associated with long-term storage, had low levels at budbreak, leaf expansion, and/or flowering with a significant increase at fruit maturity and the onset of dormancy, ending at levels higher than those found at budbreak. The concentration of soluble sugars, carbohydrate forms readily usable by plants, was highest at budbreak compared with the other four phenological samplings. Overall, our findings supported the hypothesis that TNC levels within the roots of weedy Rubus plants can be predicted based on different phenological growth stages in Massachusetts. However, recommendations for timing management practices cannot be based on TNC cycles alone; other factors such as temporal proximity to dormancy may also impact Rubus plants recovery, and further research is warranted. Late-season damage should allow less time for plants to replenish carbohydrate reserves (before the onset of dormancy), thereby likely enhancing the effectiveness of weed management tactics over time. Future studies should consider tracking the relationship between environmental conditions, phenological stages, and carbohydrate trends.
Trends and patterns of the double burden of malnutrition (DBM) in Peru: a pooled analysis of 129,159 mother–child dyads
Authors: Pomati Marco , Mendoza-Quispe Daniel , Anza-Ramirez Cecilia , Hernández-Vásquez Akram , Carrillo Larco Rodrigo M. , Fernandez Gabriela , Nandy Shailen , Miranda J. Jaime , Bernabé-Ortiz Antonio 
Published: January 2021

Abstract
Background
This study aims to evaluate trends of DBM in Peru over the last 20 years.

Methods
Using individual-level data collected in nationally representative household surveys from Peru between 1996 and 2017, we analysed trends in the prevalence and patterning of the DBM. We classified the nutritional status of children and their mothers as undernourished (either underweight, stunted or wasted for children), normal, overweight or obese. Children classified as experiencing the DBM were those undernourished and living with an overweight or obese mother. We also fitted logistic regression models to evaluate the probability of children having an overweight/obese mother across subgroups of socioeconomic status, place of residence and education.

Results
The overall percentage of children experiencing the DBM in 2016 was 7%, and constitutes ~203,600 children (90% of whom were stunted). Between 1996 and 2016, undernourished children have seen the largest relative increase in the risk of having an overweight mother (31% vs. 37%) or obese mother (6% vs. 17%); however, due to the substantial decrease in the absolute number of undernourished children, the DBM has not grown. Moreover, all children, irrespective of their own nutritional status, are now more likely to live with an overweight or obese mother, a consistent pattern across wealth, location and education subgroups, and all regions of Peru.

Conclusions
DBM prevalence in Peru has decreased, although the number of DBM cases is estimated to be above 200,000. In addition, all children are now more likely to live with overweight or obese mothers. The basic pattern has shifted from one of undernourished children whose mothers have a ‘normal’ BMI, to one where now most children have a ‘normal’ or healthy anthropometric status, but whose mothers are overweight or obese. This suggest that Peru is on the cusp of a major public health challenge requiring significant action.
Therapeutic anti-glioma effect of the combined action of PCSK inhibitor with the anti-tumoral factors secreted by Poly (I:C)-stimulated macrophages
Authors: Rose Mélanie , Duhamel Marie , Aboulouard Soulaimane , Kobeissy Firas , Tierny Dominique , Fournier Isabelle , Rodet Franck , Salzet Michel 
Published: January 2021

AbstractMacrophages plasticity is a key feature in cancer progression. Neoplastic cells can alter their immune functions and orient them into a pro-tumoral phenotype. In this context, we developed a new therapeutic strategy to switch macrophages phenotype and reactivate their anti-tumoral functions. We showed a dual activity of a proprotein convertases inhibitor as anti-glioma drug and anti-tumoral macrophages’ reactivation drug. Proprotein convertases are proteases that cleave proteins into functional proteins. Several of their substrates are involved in tumorigenesis and immunosuppression. We combine here proprotein convertases inhibitor with Poly (I:C), a TLR3 ligand, to increase the anti-tumoral activity of macrophages. With mass spectrometry-based proteomics, system biology, combined with biological assays, we established that a stimulation of macrophages with Poly (I:C) increased their secretion of pro-inflammatory cytokines and anti-tumoral factors. 3D invasion assay showed the efficacy of these anti-tumoral factors against mixed glioma cells and macrophages spheroids. Besides, immunofluorescence and proliferation assays showed an additive effect of the proprotein convertases inhibitor and the anti-tumoral factors secreted by Poly (I:C)-treated macrophages on both anti-glioma activity and macrophages anti-tumoral orientation directly in tumor microenvironment, leading to an innovative glioma therapy.
Convolutional neural network-assisted recognition of nanoscale L12 ordered structures in face-centred cubic alloys
Authors: Li Yue , Zhou Xuyang , Colnaghi Timoteo , Wei Ye , Marek Andreas , Li Hongxiang , Bauer Stefan , Rampp Markus , Stephenson Leigh T. 
Published: January 2021

AbstractNanoscale L12-type ordered structures are widely used in face-centered cubic (FCC) alloys to exploit their hardening capacity and thereby improve mechanical properties. These fine-scale particles are typically fully coherent with matrix with the same atomic configuration disregarding chemical species, which makes them challenging to be characterized. Spatial distribution maps (SDMs) are used to probe local order by interrogating the three-dimensional (3D) distribution of atoms within reconstructed atom probe tomography (APT) data. However, it is almost impossible to manually analyze the complete point cloud (>10 million) in search for the partial crystallographic information retained within the data. Here, we proposed an intelligent L12-ordered structure recognition method based on convolutional neural networks (CNNs). The SDMs of a simulated L12-ordered structure and the FCC matrix were firstly generated. These simulated images combined with a small amount of experimental data were used to train a CNN-based L12-ordered structure recognition model. Finally, the approach was successfully applied to reveal the 3D distribution of L12–type δ′–Al3(LiMg) nanoparticles with an average radius of 2.54 nm in a FCC Al-Li-Mg system. The minimum radius of detectable nanodomain is even down to 5 Å. The proposed CNN-APT method is promising to be extended to recognize other nanoscale ordered structures and even more-challenging short-range ordered phenomena in the near future.
Multimodal phenotypic axes of Parkinson’s disease
Authors: Markello Ross D. , Shafiei Golia , Tremblay Christina , Postuma Ronald B. , Dagher Alain , Misic Bratislav 
Published: January 2021

AbstractIndividuals with Parkinson’s disease present with a complex clinical phenotype, encompassing sleep, motor, cognitive, and affective disturbances. However, characterizations of PD are typically made for the “average” patient, ignoring patient heterogeneity and obscuring important individual differences. Modern large-scale data sharing efforts provide a unique opportunity to precisely investigate individual patient characteristics, but there exists no analytic framework for comprehensively integrating data modalities. Here we apply an unsupervised learning method—similarity network fusion—to objectively integrate MRI morphometry, dopamine active transporter binding, protein assays, and clinical measurements from n = 186 individuals with de novo Parkinson’s disease from the Parkinson’s Progression Markers Initiative. We show that multimodal fusion captures inter-dependencies among data modalities that would otherwise be overlooked by field standard techniques like data concatenation. We then examine how patient subgroups derived from the fused data map onto clinical phenotypes, and how neuroimaging data is critical to this delineation. Finally, we identify a compact set of phenotypic axes that span the patient population, demonstrating that this continuous, low-dimensional projection of individual patients presents a more parsimonious representation of heterogeneity in the sample compared to discrete biotypes. Altogether, these findings showcase the potential of similarity network fusion for combining multimodal data in heterogeneous patient populations.
Nematic fluctuations in iron-oxychalcogenide Mott insulators
Authors: Freelon B. , Sarkar R. , Kamusella S. , Brückner F. , Grinenko V. , Acharya Swagata , Laad Mukul , Craco Luis , Yamani Zahra , Flacau Roxana , Swainson Ian , Frandsen Benjamin , Birgeneau Robert , Liu Yuhao , Karki Bhupendra , Alfailakawi Alaa , Neuefeind Joerg C. , Everett Michelle , Wang Hangdong , Xu Binjie , Fang Minghu , Klauss H.-H. 
Published: January 2021

AbstractNematic fluctuations occur in a wide range physical systems from biological molecules to cuprates and iron pnictide high-Tc superconductors. It is unclear whether nematicity in pnictides arises from electronic spin or orbital degrees of freedom. We studied the iron-based Mott insulators La2O2Fe2OM2M = (S, Se), which are structurally similar to pnictides. Nuclear magnetic resonance revealed a critical slowing down of nematic fluctuations and complementary Mössbauerr spectroscopy data showed a change of electrical field gradient. The neutron pair distribution function technique detected local C2 fluctuations while neutron diffraction indicates that global C4 symmetry is preserved. A geometrically frustrated Heisenberg model with biquadratic and single-ion anisotropic terms provides the interpretation of the low temperature magnetic fluctuations. The nematicity is not due to spontaneous orbital order, instead it is linked to geometrically frustrated magnetism based on orbital selectivity. This study highlights the interplay between orbital order and spin fluctuations in nematicity.
Sparsely-connected autoencoder (SCA) for single cell RNAseq data mining
Authors: Alessandri Luca , Cordero Francesca , Beccuti Marco , Licheri Nicola , Arigoni Maddalena , Olivero Martina , Di Renzo Maria Flavia , Sapino Anna , Calogero Raffaele 
Published: January 2021

AbstractSingle-cell RNA sequencing (scRNAseq) is an essential tool to investigate cellular heterogeneity. Thus, it would be of great interest being able to disclose biological information belonging to cell subpopulations, which can be defined by clustering analysis of scRNAseq data. In this manuscript, we report a tool that we developed for the functional mining of single cell clusters based on Sparsely-Connected Autoencoder (SCA). This tool allows uncovering hidden features associated with scRNAseq data. We implemented two new metrics, QCC (Quality Control of Cluster) and QCM (Quality Control of Model), which allow quantifying the ability of SCA to reconstruct valuable cell clusters and to evaluate the quality of the neural network achievements, respectively. Our data indicate that SCA encoded space, derived by different experimentally validated data (TF targets, miRNA targets, Kinase targets, and cancer-related immune signatures), can be used to grasp single cell cluster-specific functional features. In our implementation, SCA efficacy comes from its ability to reconstruct only specific clusters, thus indicating only those clusters where the SCA encoding space is a key element for cells aggregation. SCA analysis is implemented as module in rCASC framework and it is supported by a GUI to simplify it usage for biologists and medical personnel.
Estimating and explaining the spread of COVID-19 at the county level in the USA
Authors: Ives Anthony R. , Bozzuto Claudio 
Published: January 2021

AbstractThe basic reproduction number, R0, determines the rate of spread of a communicable disease and therefore gives fundamental information needed to plan public health interventions. Using mortality records, we estimated the rate of spread of COVID-19 among 160 counties and county-aggregates in the USA at the start of the epidemic. We show that most of the high among-county variance is explained by four factors (R2 = 0.70): the timing of outbreak, population size, population density, and spatial location. For predictions of future spread, population density and spatial location are important, and for the latter we show that SARS-CoV-2 strains containing the G614 mutation to the spike gene are associated with higher rates of spread. Finally, the high predictability of R0allows extending estimates to all 3109 counties in the conterminous 48 states. The high variation of R0argues for public health policies enacted at the county level for controlling COVID-19.
Facile access to benzofuran-fused tetrahydropyridines via catalytic asymmetric [4 + 2] cycloaddition of aurone-derived 1-azadienes with 3-vinylindoles
Authors: Koay Wai Lean , Mei Guang-Jian , Lu Yixin 
Published: January 2021

A highly enantioselective [4 + 2] cycloaddition reaction of 1-azadienes with 3-vinylindoles, catalyzed by chiral phosphoric acid has been developed to furnish a range of benzofuran-fused tetrahydropyridines with three contiguous stereogenic centers.
Speech and Anxiety Management With Persistent Stuttering: Current Status and Essential Research
Authors: Lowe Robyn , Menzies Ross , Onslow Mark , Packman Ann , O'Brian Sue 
Published: January 2021

PurposeThe purpose of this review article is to provide an overview of the current evidence base for the behavioral management of stuttering and associated social anxiety.MethodWe overview recent research about stuttering and social anxiety in the context of contemporary cognitive models of social anxiety disorder. That emerging evidence for self-focused attention and safety behavior use with those who stutter is considered in relation to current treatment approaches for stuttering: speech restructuring and social anxiety management.ResultsThe emerging information about social anxiety and stuttering suggests a conflict between the two clinical approaches. For those clients who wish to control their stuttering and where speech restructuring is deemed the most suitable approach, it is possible that speech restructuring may (a) induce or increase self-focused attention, (b) promote the use of safety behaviors, and (c) become a safety behavior itself. This conflict needs to be explored further within clinical and research contexts.ConclusionsThe issues raised in this review article are complex. It appears that evidence-based speech treatment procedures are in conflict with current best-practice treatment procedures that deal with social anxiety. In this review article, we propose directions for future research to inform the development of improved treatments for those who stutter and recommendations for interim clinical management of stuttering.
Use of Design Thinking to Inform Eligibility Recommendations for Children With Spoken Language and Literacy Disorders in Schools
Authors: Farquharson Kelly , Coleman Jaumeiko J. , Moore Barbara J. , Montgomery Judy K. 
Published: January 2021

PurposeThe purpose of this tutorial was to consider and apply design thinking to the clinical process of determining eligibility for special education and related services for students with spoken language and literacy disorders in school-based settings. Specifically, we will consider some of the predicaments that multidisciplinary assessment teams face when applying legal criteria and local procedures to referral and assessment processes, as well as the actual application of eligibility criteria, particularly when considering issues related to referral for an assessment for a suspected spoken language or literacy disorder.MethodDesign thinking is a human-centered, iterative process that can be used to problem solve issues at the individual and system levels. We applied the IDEO design thinking process model, which includes five phases (i.e., discovery, interpretation, ideation, experimentation, and evolution), to the process of determining eligibility in school-based settings. Our exploration included a review of predicaments that sometimes arise during the eligibility determination process.ResultsWe applied design thinking to a specific predicament in the eligibility determination process. We also used design thinking to develop several guiding questions for two additional eligibility predicaments.ConclusionsDesign thinking is a robust and structured framework used to make decisions and solve problems in a variety of settings. Given its human-centered focus, it is appropriate to use within the context of the Individuals with Disabilities Education Improvement Act of 2004. Using a human-centered approach helps retain the “I” in “IEP” (Individualized Education Program) and ensure that the unique needs of students with communication disorders are met.
An energy‐efficient non‐uniform clustering routing protocol based on improved shuffled frog leaping algorithm for wireless sensor networks
Authors: Huamei Qi , Chubin Lin , Yijiahe Gao , Wangping Xiong , Ying Jiao 
Published: January 2021

AbstractWireless sensor networks have been used widely in environmental tracking and monitoring. Nevertheless, WSNs are facing a number of challenges, such as unreasonable cluster head selection and energy‐hole problems while nodes have unbalanced energy consumption. Thus, the paper aims to propose an energy‐efficient non‐uniform clustering routing protocol to enhance nodes energy efficiency and balance the energy consumption in WSNs. In addition, a non‐uniform clustering network partition is introduce to reduce the probability of energy hole occurrences and optimize cluster heads dynamical selection method to suggest an improved shuffled frog leaping algorithm. Ultimately, the simulation experiment has demonstrated a 20% gain of energy efficiency to extend network lifetime by the proposed protocol and enhanced algorithm.
Medical JPEG image steganography method according to the distortion reduction criterion based on an imperialist competitive algorithm
Authors: Damghani Hamidreza , Mofrad Farshid Babapour , Damghani Leila 
Published: January 2021

AbstractIn most of the digital steganography methods provided for natural digital images, the embedding of the confidential message is based on the minimisation of the defined distortion functions. It is often done based on choosing the most optimal criterion of distortion. Although the distortion functions are designed innovatively, steganography algorithms will be optimal. In such approaches, embedding interactions are often overlooked. Unlike usual images that have areas with a variety of tissue features, there are many smooth areas in medical images that will make the changes more visible if they are manipulated. Therefore, this study presents an adaptive approach that comes from the interactions between the changes made during the embedding algorithm to reduce the probability of recognising the message embedded in medical images and reducing the distortion caused by embedding in a discrete cosine transform space and based on the imperialist competitive algorithm for joint photographic experts group images, especially in medical images due to the importance of information steganography in them. The results obtained show the high efficiency of the proposed algorithm in comparison with the state‐of‐the‐art methods that are presented in this area.