Exploiting the layer-by-layer nanoarchitectonics for the fabrication of polymer capsules : A toolbox to provide multifunctional properties to target complex pathologies

Polymer capsules fabricated via the layer-by-layer (LbL) approach have attracted a great deal of attention for biomedical applications thanks to their tunable architecture. Compared to alternative methods, in which the precise control over the final properties of the systems is usually limited, the intrinsic versatility of the LbL approach allows the functionalization of all the constituents of the polymeric capsules following relatively simple protocols. In fact, the final properties of the capsules can be adjusted from the inner cavity to the outer layer through the polymeric shell, resulting in therapeutic, diagnostic, or theranostic (i.e., combination of therapeutic and diagnostic) agents that can be adapted to the particular characteristics of the patient and face the challenges encountered in complex pathologies. The biomedical industry demands novel biomaterials capable of targeting several mechanisms and/or cellular pathways simultaneously while being tracked by minimally invasive tech-niques, thus highlighting the need to shift from monofunctional to multifunctional polymer capsules. In the present review, those strategies that permit the advanced functionalization of polymer capsules are accordingly introduced. Each of the constituents of the capsule (i.e., cavity, multilayer membrane and outer layer) is thor-oughly analyzed and a final overview of the combination of all the strategies toward the fabrication of multi-functional capsules is presented. Special emphasis is given to the potential biomedical applications of these multifunctional capsules, including particular examples of the performed in vitro and in vivo validation studies. Finally, the challenges in the fabrication process and the future perspective for their safe translation into the clinic are summarized.Peer reviewe

Generating human-computer micro-task workflows from domain ontologies

With the growing popularity of micro-task crowdsourcing platforms, a renewed interest in the resolution of complex tasks that require the coopera-tion of human and machine participants has emerged. This interest has led to workflow approaches that present new challenges at different dimensions of the human-machine computation process, namely in micro-task specification and human-computer interaction due to the unstructured nature of micro-tasks in terms of domain representation. In this sense, a semi-automatic generation envi-ronment for human-computer micro-task workflows from domain ontologies is proposed. The structure and semantics of the domain ontology provides a com-mon ground for understanding and enhances human-computer cooperation.This work is partially funded by FEDER Funds and by the ERDF (European Regional Development Fund) through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) under the projects AAL4ALL (QREN13852) and FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012)

The epidemiology and etiology of adhesive capsulitis in the U.S. Medicare population

Abstract Background Adhesive capsulitis (AC) of the shoulder, also known as frozen shoulder, causes substantial pain and disability. In cases of secondary AC, the inflammation and fibrosis of the synovial joint can be triggered by trauma or surgery to the joint followed by extended immobility. However, for primary AC the inciting trigger is unknown. The burden of the disorder among the elderly is also unknown leading to this age group being left out of therapeutic research studies, potentially receiving delayed diagnoses, and unknown financial costs to the Medicare system. The purpose of this analysis was to describe the epidemiology of AC in individuals over the age of 65, an age group little studied for this disorder. The second purpose was to investigate whether specific medications, co-morbidities, infections, and traumas are risk factors or triggers for primary AC in this population. Methods We used Medicare claims data from 2010–2012 to investigate the prevalence of AC and assess comorbid risk factors and seasonality. Selected medications, distal trauma, and classes of infections as potential inflammatory triggers for primary AC were investigated using a case–control study design with patients with rotator cuff tears as the comparison group. Medications were identified from National Drug codes and translated to World Health Organization ATC codes for analysis. Health conditions were identified using ICD9-CM codes. Results We found a one-year prevalence rate of AC of approximately 0.35% among adults aged 65 years and older which translates to approximately 142,000 older adults in the United States having frozen shoulder syndrome. Diabetes and Parkinson’s disease were significantly associated with the diagnosis of AC in the elderly. Cases were somewhat more common from August through December, although a clear seasonal trend was not observed. Medications, traumas, and infections were similar for cases and controls. Conclusions This investigation identified the burden of AC in the US elderly population and applied case–control methodology to identify triggers for its onset in this population. Efforts to reduce chronic health conditions such as diabetes may reduce seemingly unrelated conditions such as AC. The inciting trigger for this idiopathic condition remains elusive

Semi-collapse of turbulent fountains in stratified media and the mechanisms to control their dynamics

Turbulent fountains are widespread natural phenomena with numerous industrial applications. Extensive research has focused on the temporal evolution and maximum height of these fountains, as well as their dependence on Reynolds and Froude numbers. However, the minimum height of the surrounding ambient fluid, which is removed by the fountain due to the entrainment effect, has received little attention. In this study, we investigate the dependence of this minimum height on the characteristics of the fountain and demonstrate how to control it. Our findings present important implications for technological applications of turbulent fountains, particularly in contaminant withdrawal. We discuss the potential of our results to improve the efficiency of such applications.Comment: 16 pages, 10 figure

The evolution of power and standard Wikidata editors: comparing editing behavior over time to predict lifespan and volume of edits

Knowledge bases are becoming a key asset leveraged for various types of applications on the Web, from search engines presenting ‘entity cards’ as the result of a query, to the use of structured data of knowledge bases to empower virtual personal assistants. Wikidata is an open general-interest knowledge base that is collaboratively developed and maintained by a community of thousands of volunteers. One of the major challenges faced in such a crowdsourcing project is to attain a high level of editor engagement. In order to intervene and encourage editors to be more committed to editing Wikidata, it is important to be able to predict at an early stage, whether an editor will or not become an engaged editor. In this paper, we investigate this problem and study the evolution that editors with different levels of engagement exhibit in their editing behaviour over time. We measure an editor’s engagement in terms of (i) the volume of edits provided by the editor and (ii) their lifespan (i.e. the length of time for which an editor is present at Wikidata). The large-scale longitudinal data analysis that we perform covers Wikidata edits over almost 4 years. We monitor evolution in a session-by-session- and monthly-basis, observing the way the participation, the volume and the diversity of edits done by Wikidata editors change. Using the findings in our exploratory analysis, we define and implement prediction models that use the multiple evolution indicators

A method for defining human-machine micro-task workflows for gathering legal information

Series : Lecture notes in computer science, ISSN 0302-9743, vol. 8929With the growing popularity of micro-task crowdsourcing platforms, new workflow-based micro-task crowdsourcing approaches are starting to emerge. Such workflows occur in legal, political and conflict resolution do-mains as well, presenting new challenges, namely in micro-task specification and human-machine interaction, which result mostly from the flow of unstruc-tured data. Domain ontologies provide the structure and semantics required to describe the data flowing throughout the workflow in a way understandable to both humans and machines. This paper presents a method for the construction of micro-task workflows from legal domain ontologies. The method is currently being employed in the context of the UMCourt project in order to formulate in-formation retrieval and conflict resolution workflows.This work is part-funded by FEDER Funds, by the ERDF (Eu-ropean Regional Development Fund) through the COMPETE Programme (operation-al programme for competitiveness) and by National Funds through the FCT (Portu-guese Foundation for Science and Technology) within the project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012). The work of Nuno Luz is supported by the doctoral grant SFRH/BD/70302/2010

All those wasted hours: On task abandonment in crowdsourcing

Crowdsourcing has become a standard methodology to collect manually annotated data such as relevance judgments at scale. On crowdsourcing platforms like Amazon MTurk or FigureEight, crowd workers select tasks to work on based on different dimensions such as task reward and requester reputation. Requesters then receive the judgments of workers who self-selected into the tasks and completed them successfully. Several crowd workers, however, preview tasks, begin working on them, reaching varying stages of task completion without finally submitting their work. Such behavior results in unrewarded effort which remains invisible to requesters. In this paper, we conduct the first investigation into the phenomenon of task abandonment, the act of workers previewing or beginning a task and deciding not to complete it. We follow a threefold methodology which includes 1) investigating the prevalence and causes of task abandonment by means of a survey over different crowdsourcing platforms, 2) data-driven analyses of logs collected during a large-scale relevance judgment experiment, and 3) controlled experiments measuring the effect of different dimensions on abandonment. Our results show that task abandonment is a widely spread phenomenon. Apart from accounting for a considerable amount of wasted human effort, this bears important implications on the hourly wages of workers as they are not rewarded for tasks that they do not complete. We also show how task abandonment may have strong implications on the use of collected data (for example, on the evaluation of IR systems)