bluuebunny/crossref_metadata_2025_split huggingface dataset:
State-of-the-art reviews predictive modeling in adult spinal deformity: applications of advanced analytics
Authors: Joshi Rushikesh S. , Lau Darryl , Scheer Justin K. , Serra-Burriel Miquel , Vila-Casademunt Alba , Bess Shay , Smith Justin S. , Pellise Ferran , Ames Christopher P. 
Published: May 2021

AbstractAdult spinal deformity (ASD) is a complex and heterogeneous disease that can severely impact patients’ lives. While it is clear that surgical correction can achieve significant improvement of spinopelvic parameters and quality of life measures in adults with spinal deformity, there remains a high risk of complication associated with surgical approaches to adult deformity. Over the past decade, utilization of surgical correction for ASD has increased dramatically as deformity correction techniques have become more refined and widely adopted. Along with this increase in surgical utilization, there has been a massive undertaking by spine surgeons to develop more robust models to predict postoperative outcomes in an effort to mitigate the relatively high complication rates. A large part of this revolution within spine surgery has been the gradual adoption of predictive analytics harnessing artificial intelligence through the use of machine learning algorithms. The development of predictive models to accurately prognosticate patient outcomes following ASD surgery represents a dramatic improvement over prior statistical models which are better suited for finding associations between variables than for their predictive utility. Machine learning models, which offer the ability to make more accurate and reproducible predictions, provide surgeons with a wide array of practical applications from augmenting clinical decision making to more wide-spread public health implications. The inclusion of these advanced computational techniques in spine practices will be paramount for improving the care of patients, by empowering both patients and surgeons to more specifically tailor clinical decisions to address individual health profiles and needs.
Insights into a possible role of glucagon-like peptide-1 receptor agonists in the treatment of depression
Authors: Detka Jan , Głombik Katarzyna 
Published: May 2021

AbstractDepression is a highly prevalent mood disorder and one of the major health concerns in modern society. Moreover, it is characterized by a high prevalence of coexistence with many other diseases including metabolic disorders such as type 2 diabetes mellitus (T2DM) and obesity. Currently used antidepressant drugs, which mostly target brain monoaminergic neurotransmission, have limited clinical efficacy. Although the etiology of depression has not been fully elucidated, current scientific data emphasize the role of neurotrophic factors deficiencies, disturbed homeostasis between the nervous system and the immune and endocrine systems, as well as disturbances in brain energy metabolism and dysfunctions in the gut-brain axis as important factors in the pathogenesis of this neuropsychiatric disorder. Therefore, therapeutic options that could work in a way other than classic antidepressants are being sought to increase the effectiveness of the treatment. Interestingly, glucagon-like peptide-1 receptor agonists (GLP-1RAs), used in the treatment of T2DM and obesity, are known to show pro-cognitive and neuroprotective properties, and exert modulatory effects on immune, endocrine and metabolic processes in the central nervous system. This review article discusses the potential antidepressant effects of GLP-1RAs, especially in the context of their action on the processes related to neuroprotection, inflammation, stress response, energy metabolism, gut-brain crosstalk and the stability of the gut microbiota.
Graphic abstract
Investigator Initiated Clinical Trials (IICTs): A Systematic Search in Registries to Compare the Czech Republic and Portugal in Terms of Funding Policies and Scientific Outcomes
Authors: Madeira C. , Hořavová L. , dos Santos F. , Batuca J. R. , Nebeska K. , Součková L. , Kubiak C. , Demotes J. , Demlová R. , Monteiro E. C. 
Published: May 2021

Abstract
Objectives
Clinical trials provide one of the highest levels of evidence to support medical practice. Investigator initiated clinical trials (IICTs) answer relevant questions in clinical practice that may not be addressed by industry. For the first time, two European Countries are compared in terms of IICTs, respective funders and publications, envisaging to inspire others to use similar indicators to assess clinical research outcomes.

Methods
A retrospective systematic search of registered IICTs from 2004 to 2017, using four clinical trials registries was carried out in two European countries with similar population, GDP, HDI and medical schools but with different governmental models to fund clinical research. Each IICT was screened for sponsors, funders, type of intervention and associated publications, once completed.

Results
IICTs involving the Czech Republic and Portugal were n = 439 (42% with hospitals as sponsors) and n = 328 (47% with universities as sponsors), respectively. The Czech Republic and Portuguese funding agencies supported respectively 61 and 27 IICTs. Among these, trials with medicinal products represent 52% in Czech Republic and 4% in Portugal. In the first, a higher percentage of IICTs’ publications in high impact factor journals with national investigators as authors was observed, when compared to Portugal (75% vs 15%).

Conclusion
The better performance in clinical research by Czech Republic might be related to the existence of specific and periodic funding for clinical research, although further data are still needed to confirm this relationship. In upcoming years, the indicators used herein might be useful to tracking clinical research outcomes in these and other European countries.
Promoting Scale-Up Across a Global Project Platform: Lessons from the Evidence to Action Project
Authors: Ghiron Laura , Ramirez-Ferrero Eric , Badiani Rita , Benevides Regina , Ntabona Alexis , Fajans Peter , Simmons Ruth 
Published: May 2021

AbstractThe USAID-funded flagship family planning service delivery project named Evidence to Action (E2A) worked from 2011 to 2021 to improve family planning and reproductive health for women and girls across seventeen nations in sub-Saharan Africa using a “scaling-up mindset.” The paper discusses three key lessons emerging from the project’s experience with applying ExpandNet’s systematic approach to scale up. The methodology uses ExpandNet/WHO’s scaling-up framework and guidance tools to design and implement pilot or demonstration projects in ways that look ahead to their future scale-up; develop a scaling-up strategy with local stakeholders; and then strategically manage the scaling-up process. The paper describes how a scaling-up mindset was engendered, first within the project’s technical team in Washington and then how they subsequently sought to build capacity at the country level to support scale-up work throughout E2A’s portfolio of activities. The project worked with local multi-stakeholder resource teams, often led by government officials, to equip them to lead the scale-up of family planning and health system strengthening interventions. Examples from project experience in the Democratic Republic of the Congo, Kenya, Nigeria, and Uganda illustrating key concepts are discussed. E2A also established a community of practice on systematic approaches to scale up as a platform for sharing learning across a variety of technical agencies engaged in scale-up work and to create learning opportunities for interacting with thought leaders around critical scale-up issues.
The value of data matching for public poverty initiatives: a local voucher program example
Authors: Giest Sarah , Miotto Jose M. , Kraaij Wessel 
Published: May 2021

AbstractThe recent surge of data-driven methods in social policy have created new opportunities to assess existing poverty programs. The expectation is that the combination of advanced methods and more data can calculate the effectiveness of public interventions more accurately and tailor local initiatives accordingly. Specifically, nonmonetary indicators are increasingly being measured at micro levels in order to target social exclusion in combination with poverty. However, the multidimensional character of poverty, local context, and data matching pose challenges to data-driven analyses. By linking Dutch household-level data with policy-initiative-specific data at local level, we present an explorative study on the uptake of a local poverty pass. The goal is to unravel pass usage in terms of household income and location as well as the age of users. We find that income and age play a role in whether the pass is used, and usage differs per neighborhood. With this, the paper feeds into the discourse on how to operationalize and design data matching work in the multidimensional space of poverty and nonmonetary government initiatives.
Reimagining data responsibility: 10 new approaches toward a culture of trust in re-using data to address critical public needs
Authors: Verhulst Stefaan G. 
Published: May 2021

Abstract
Data and data science offer tremendous potential to address some of our most intractable public problems (including the Covid-19 pandemic). At the same time, recent years have shown some of the risks of existing and emerging technologies. An updated framework is required to balance potential and risk, and to ensure that data is used responsibly. Data responsibility is not itself a new concept. However, amid a rapidly changing technology landscape, it has become increasingly clear that the concept may need updating, in order to keep up with new trends such as big data, open data, the Internet of things, and artificial intelligence, and machine learning. This paper seeks to outline 10 approaches and innovations for data responsibility in the 21st century. The 10 emerging concepts we have identified include:
End-to-end data responsibility
Decision provenance
Professionalizing data stewardship
From data science to question science
Contextual consent
Responsibility by design
Data asymmetries and data collaboratives
Personally identifiable inference
Group privacy
Data assemblies
Each of these is described at greater length in the paper, and illustrated with examples from around the world. Put together, they add up to a framework or outline for policy makers, scholars, and activists who seek to harness the potential of data to solve complex social problems and advance the public good. Needless to say, the 10 approaches outlined here represent just a start. We envision this paper more as an exercise in agenda-setting than a comprehensive survey.
Dead men tell no tales: the role of cultural transmission in demographic change
Authors: Zakharenko Roman 
Published: May 2021

AbstractThe paper explains long-term changes in birth, death rates, and in attitude to personal consumption by evolution of preferences by means of cultural transmission. When communities are culturally isolated, they are focused on population growth, which results in large fertility and welfare transfers to children, limited adult consumption, and lack of old-age support. With increasing cultural contact across communities, successful cultural traits induce their hosts to increase their social visibility by limiting fertility and increasing longevity via higher individual consumption. Empirical analysis confirms that social visibility, as measured by the number of language versions of Wikipedia biographical pages, is associated with fewer children and longer lifespan. The presence of notable individuals precedes reduced aggregate birth rates.
Idea Generation Through Hackathon Event in Emergencies and Disasters, with Emphasis on Managing Flash Flood Disaster
Authors: Monsef Sanaz , Haghjooy Javanmard Shaghayegh , Amini-Rarani Mostafa , Yarmohammadian Mohammad H. , Yazdi Youseph , Haghshenas Abbas 
Published: May 2021

AbstractObjective:This study was intended to demonstrate the applicability of the hackathon in idea generation for managing emergencies and disasters with a particular focus on flash floods.Methods:A 4-day hackathon event was held, having 60 students, 9 mentors and 6 judges gathered to explore different ideas, and to solve problems of Iran flooding from mid-March to April, 2019. Of these, 10 teams with 6 students were accordingly formed to brainstorm and discuss the idea, while 9 mentors offered advice and guided them to manage their ideas. Then, all teams focused on designing their business models. Finally, the hackathon teams finalized their lean canvas and presented their ideas to the judging panel and the other participants.Results:A total of 10 ideas were presented, and based on the knowledge and experience of the judges, 3 ideas that were more practical and useful were selected.Conclusions:As participants in a hackathon identify and present real-world problems, while ensuring that the prototype solutions address the end-user’s needs, it could be used to drive innovation, generate ideas, promote change in emergencies and disasters, and can increase our preparedness for future events. It helps us to develop tools and applications to better respond to these events.
Spatialising state practices through transnational repression
Authors: Furstenberg Saipira , Lemon Edward , Heathershaw John 
Published: May 2021

AbstractThis article theorises the repressive security practices of authoritarian states in the context of transnationalism and globalisation. While emerging research on transnational repression has identified a range of extraterritorial and exceptional security practices adopted by authoritarian states, it has not fully studied the implications of such practices on space and statecraft. Using data from the Central Asia Political Exile Database project (CAPE) and interviews conducted with exiled Tajik opposition groups based in Russia and Europe, we theorise the spatial connections between the territorial and extraterritorial security practices using the concept of assemblages. We further outline how these practices escalate in a three-stage model, in which exiles go on notice, are detained and then rendered or assassinated. Such an approach sheds light on the inherent links between the normalisation of security practices and the creation of transnational space with distinct forms of geographical state power that is embedded in non-national spaces and is manifested through spatially organised actors, networks, and technologies within assemblages.
A plausible mechanism for longitudinal lock-in of the plant cortical microtubule array after light-induced reorientation
Authors: Saltini Marco , Mulder Bela M. 
Published: May 2021

Abstract
The light-induced reorientation of the cortical microtubule array in dark-grown Arabidopsis thaliana hypocotyl cells is a striking example of the dynamical plasticity of the microtubule cytoskeleton. A consensus model, based on katanin-mediated severing at microtubule crossovers, has been developed that successfully describes the onset of the observed switch between a transverse and longitudinal array orientation. However, we currently lack an understanding of why the newly populated longitudinal array direction remains stable for longer times and re-equilibration effects would tend to drive the system back to a mixed orientation state. Using both simulations and analytical calculations, we show that the assumption of a small orientation-dependent shift in microtubule dynamics is sufficient to explain the long-term lock-in of the longitudinal array orientation. Furthermore, we show that the natural alternative hypothesis that there is a selective advantage in severing longitudinal microtubules, is neither necessary nor sufficient to achieve cortical array reorientation, but is able to accelerate this process significantly.
INJECTIVE LINEAR TRANSFORMATIONS WITH EQUAL GAP AND DEFECT
Authors: MENDES ARAÚJO C. , MENDES-GONÇALVES S. 
Published: May 2021

AbstractLetVbe an infinite-dimensional vector space over a fieldFand let$I(V)$be the inverse semigroup of all injective partial linear transformations onV. Given$\alpha \in I(V)$, we denote the domain and the range of$\alpha $by${\mathop {\textrm {dom}}}\,\alpha $and${\mathop {\textrm {im}}}\,\alpha $, and we call the cardinals$g(\alpha )={\mathop {\textrm {codim}}}\,{\mathop {\textrm {dom}}}\,\alpha $and$d(\alpha )={\mathop {\textrm {codim}}}\,{\mathop {\textrm {im}}}\,\alpha $the ‘gap’ and the ‘defect’ of$\alpha $. We study the semigroup$A(V)$of all injective partial linear transformations with equal gap and defect and characterise Green’s relations and ideals in$A(V)$. This is analogous to work by Sanwong and Sullivan [‘Injective transformations with equal gap and defect’,Bull. Aust. Math. Soc.79(2009), 327–336] on a similarly defined semigroup for the set case, but we show that these semigroups are never isomorphic.
Prevalence of intramammary antibiotic usage in dairy farming
Authors: Burke Niamh , Adley Catherine C. 
Published: May 2021

AbstractThis research communication describes the lactating intramammary (IMM) antibiotic formulation most used by Irish dairy farmers at farm level through interviewing 202 dairy farmers. The IMM antibiotic usage data is not easily available to the researcher and farming community. This study determined that three commercial formulations (Synulox ™, Tetra Delta™ and Terrexine) made up 81% of the products used at farm level. The formulation Synulox™ was the most used at 34% first preference and 32% second preference and contains amoxicillin/clavulanic, a standard broad spectrum antibiotic, for which mastitis pathogen resistance remains low. The aminoglycosides were used in four of the IMM formulations analysed, including Tetra Delta™ and Terrexine. Of the 12 antibiotics identified in the IMM formulations studied, three including cefalexin, benzylpenicillin and penethamate are classified as highly important antibiotics (HIA) by the World Health Organisation (WHO) whilst the other 8 (dihydrostreptomycin, streptomycin, neomycin, framycetin, kanamycin, amoxicillin/clavulanic acid, and cefquinome), are considered critically important (CIA) for use in human health. This study has generated knowledge of the preferences of lactating IMM formulations used at farm level.
A path model examination: maternal anxiety and parenting mediate the association between maternal adverse childhood experiences and children's internalizing behaviors
Authors: Shih Emily W. , Ahmad Shaikh I. , Bush Nicole R. , Roubinov Danielle , Tylavsky Fran , Graff Carolyn , Karr Catherine J. , Sathyanarayana Sheela , LeWinn Kaja Z. 
Published: May 2021

AbstractBackgroundChildren of mothers with adverse childhood experiences (ACEs) are at increased risk for developmental problems. However, the mechanisms through which a mother's experience of ACEs are transmitted to her offspring are understudied. The current study investigates potential modifiable mediators (maternal psychopathology and parenting) of the association between maternal ACEs and children's behavioral problems.MethodsWe utilized data from a pregnancy cohort study (N = 1030; CANDLE study) to investigate longitudinal associations between maternal ACEs, postpartum anxiety, observed parenting behavior, and child internalizing behaviors (meanage = 4.31 years, s.d.age = 0.38) in a racially diverse (67% Black; 33% White/Other) sample. We used structural equation modeling to test for direct associations between maternal ACEs and children's internalizing behaviors, as well as indirect associations via two simple mediations (maternal anxiety and parenting), and one serial mediation (sequence of maternal anxiety to parenting).ResultsSimple mediation results indicated that maternal anxiety and cognitive growth fostering behaviors independently mediated the association between maternal ACEs and child internalizing. We observed no evidence of a serial mediation from ACEs to internalizing via the effects of maternal anxiety on parenting.ConclusionsThis study supports and refines extant literature by confirming the intergenerational association between maternal ACEs and child internalizing behaviors in a large, diverse sample, and identifies potential modifiable mediators: maternal anxiety and parenting behaviors related to fostering cognitive development. Findings may inform interventions targeting mothers who have experienced ACEs and suggest that providing support around specific parenting behaviors and addressing maternal anxiety may reduce internalizing behaviors in children.
Seroprevalence of SARS-CoV-2 antibodies in the poorest region of Brazil: results from a population-based study
Authors: de Souza Araújo Adriano Antunes , Quintans-Júnior Lucindo José , Heimfarth Luana , Schimieguel Dulce Marta , Corrêa Cristiane Bani , de Moura Tatiana Rodrigues , Cavalcante Rafael Ciro Marques , Rodrigues Bomfim Rangel , Grespan Renata , Santana Rodrigues Lorranny , dos Santos Danillo Menezes , de Sá Resende Ayane , de Lima Silva Nathanielly , da Silva Santos Anna Clara Ramos , Dantas Araújo Jéssica Maria , de Souza Mércia Feitosa , de Oliveira Góes Marco Aurélio , Santana Santos Victor , Martins-Filho Paulo Ricardo 
Published: May 2021

Abstract
Population-based seroprevalence studies on coronavirus disease 2019 (COVID-19) in low- and middle-income countries are lacking. We investigated the seroprevalence of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) antibodies in Sergipe state, Northeast Brazil, using rapid IgM−IgG antibody test and fluorescence immunoassay. The seroprevalence was 9.3% (95% CI 8.5–10.1), 10.2% (95% CI 9.2–11.3) for women and 7.9% (IC 95% 6.8–9.1) for men (P = 0.004). We found a decline in the prevalence of SARS-CoV-2 antibodies according to age, but the differences were not statistically significant: 0–19 years (9.9%; 95% CI 7.8–12.5), 20–59 years (9.3%; 95% CI 8.4–10.3) and ≥60 years (9.0%; 95% CI 7.5–10.8) (P = 0.517). The metropolitan area had a higher seroprevalence (11.7%, 95% CI 10.3–13.2) than outside municipalities (8.0%, 95% CI 7.2–8.9) (P < 0.001). These findings highlight the importance of serosurveillance to estimate the real impact of the COVID-19 outbreak and thereby provide data to better understand the spread of the virus, as well as providing information to guide stay-at-home measures and other policies. In addition, these results may be useful as basic data to follow the progress of COVID-19 outbreak as social restriction initiatives start to be relaxed in Brazil.
Explainable dynamic programming
Authors: ERWIG MARTIN , KUMAR PRASHANT 
Published: May 2021

AbstractIn this paper, we present a method for explaining the results produced by dynamic programming (DP) algorithms. Our approach is based on retaining a granular representation of values that are aggregated during program execution. The explanations that are created from the granular representations can answer questions of why one result was obtained instead of another and therefore can increase the confidence in the correctness of program results.Our focus on dynamic programming is motivated by the fact that dynamic programming offers a systematic approach to implementing a large class of optimization algorithms which produce decisions based on aggregated value comparisons. It is those decisions that the granular representation can help explain. Moreover, the fact that dynamic programming can be formalized using semirings supports the creation of a Haskell library for dynamic programming that has two important features. First, it allows programmers to specify programs by recurrence relationships from which efficient implementations are derived automatically. Second, the dynamic programs can be formulated generically (as type classes), which supports the smooth transition from programs that only produce result to programs that can run with granular representation and also produce explanations. Finally, we also demonstrate how to anticipate user questions about program results and how to produce corresponding explanations automatically in advance.