Quality of life predicts outcome of deep brain stimulation in early Parkinson disease

in Neurology (2019)

Objective Toinvestigatepredictorsforimprovementofdisease-specificqualityoflife(QOL)afterdeepbrainstimulation (DBS) of the subthalamic nucleus (STN) for Parkinson disease (PD) with early motor complications ... [more ▼]

Objective Toinvestigatepredictorsforimprovementofdisease-specificqualityoflife(QOL)afterdeepbrainstimulation (DBS) of the subthalamic nucleus (STN) for Parkinson disease (PD) with early motor complications. Methods We performed a secondary analysis of data from the previously published EARLYSTIM study, a prospective randomizedtrialcomparingSTN-DBS(n= 124)tobestmedicaltreatment(n= 127)after2yearsfollow-up with disease-specific QOL (39-item Parkinson ’s Disease Questionnaire summary index [PDQ-39-SI]) as the primary endpoint. Linear regression analyses of the baseline characteristics age, disease duration, duration of motor complications, and disease severity measured at baseline with the Unified Parkinson’s Disease Rating Scale(UPDRS)(UPDRS-III“off”and“on”medications,UPDRS-IV)wereconductedtodeterminepredictors of change in PDQ-39-SI. Results PDQ-39-SIatbaselinewascorrelatedtothechangeinPDQ-39-SIafter24monthsinbothtreatmentgroups (p<0.05).Thehigherthebaselinescore(worseQOL)thelargertheimprovementinQOLafter24months. No correlation was found for any of the other baseline characteristics analyzed in either treatment group. Conclusion Impaired QOL as subjectively evaluated by the patient is the most important predictor of benefit in patients with PD and early motor complications, fulfilling objective gold standard inclusion criteria for STN-DBS. Our results prompt systematically including evaluation of disease-specific QOL when selecting patients with PD for STN-DBS. [less ▲]

Model order reduction accelerated Monte Carlo stochastic isogeometric method for the analysis of structures with high-dimensional and independent material uncertainties

in Computer Methods in Applied Mechanics and Engineering (2019), 349

Structural stochastic analysis is vital to engineering. However, current material related uncertainty methods are mostly limited to low dimension, and they mostly remain unable to account for spatially ... [more ▼]

Structural stochastic analysis is vital to engineering. However, current material related uncertainty methods are mostly limited to low dimension, and they mostly remain unable to account for spatially uncorrelated material uncertainties. They are not representative of realistic and practical engineering situations. In particular, it is more serious for composite structures comprised of dissimilar materials. Therefore, we propose a novel model order reduction via proper orthogonal decomposition accelerated Monte Carlo stochastic isogeometric method (IGA-POD-MCS) for stochastic analysis of exactly represented (composite) structures. This approach particularly enables high-dimensional material uncertainties wherein the characteristics of each element are independent. And the novelties include: (1) the structural geometry is exactly modeled thanks to isogeometric analysis (IGA), as well as providing more accurate deterministic and stochastic solutions, (2) we innovatively consider high-dimensional and independent material uncertainties by separating the stochastic mesh from the IGA mesh, and modeling different stochastic elements to have different (independent) uncertainty behaviors, (3) the classical Monte Carlo simulation (MCS) is employed to universally solve the high-dimensional uncertainty problem. However, to circumvent its computational expense, we employ model order reduction via proper orthogonal decomposition (POD) into the IGA coupled MCS stochastic analysis. In particular, we observe that this work decouples all IGA elements and hence permits independent uncertainty models easily, thereby the engineering problem is modeled to be more realistic and authentic. Several illustrative numerical examples verify the proposed IGA-POD-MCS approach is effective and efficient; and the larger the scale of the problem is, the more advantageous the method will become. [less ▲]

Interview with Prof. Dr Andrew Prescott (University of Glasgow)

Diverse speeches and writings (2019)

In this interview, Professor Andrew Prescott describes his beginnings as a librarian and how this profession brought him to the field of digital humanities. He emphasizes more broadly the role of curators ... [more ▼]

In this interview, Professor Andrew Prescott describes his beginnings as a librarian and how this profession brought him to the field of digital humanities. He emphasizes more broadly the role of curators in this field including the role of metadata and the configuration of collections in a new way. Andrew Prescott also historicizes the digital turn in humanities and explores the most exciting trends for the future. [less ▲]

The tacit knowledge of entrepreneurial design: interrelating theory, practice and prescription in entrepreneurship research’

in Journal of Business Venturing Insights (2019), 11

An important challenge facing entrepreneurship researchers is the “three-body” knowledge problem of how to use “theoretical knowledge” to produce “prescriptive knowledge” that communicates the “practical ... [more ▼]

An important challenge facing entrepreneurship researchers is the “three-body” knowledge problem of how to use “theoretical knowledge” to produce “prescriptive knowledge” that communicates the “practical knowledge” of situated practice to students and practitioners of entrepreneurship. We argue that a contribution can be made to solving this problem by theorizing practical knowledge as the “know-how” to do a situated entrepreneurial practice. “Know-how” is a cognitive “capacity to act” that prescribes for a practitioner how to produce a type of outcome in a range of circumstances. This “know-how” can potentially, therefore, be reconstructed theoretically as explicit micro-prescriptive guidelines for third-party practice. To exploit this connection between practical knowledge and prescriptive knowledge, however, we first need to overcome the problem that “know-how” is largely tacit in the moment of real-time forward-looking practice. In other words, the practitioner is not directly aware of their tacit “know-how”, or “tacit knowledge”, at the time of practice. In this article, we explore the contribution design theory can make to empirically eliciting, and conceptually inferring, the real-time “tacit knowledge” of entrepreneurial practice as a precursor to producing micro-prescriptive knowledge. [less ▲]

Banana starch nanocomposite with cellulose nanofibers isolated from banana peel by enzymatic treatment: In vitro cytotoxicity assessment

in Carbohydrate Polymers (2019), 207

The potential use of cellulose nanofibers (CNFs) as a reinforcing agent in banana starch-based nanocomposite films was investigated. CNFs were isolated from banana peel (Musa paradisiaca) by enzymatic ... [more ▼]

The potential use of cellulose nanofibers (CNFs) as a reinforcing agent in banana starch-based nanocomposite films was investigated. CNFs were isolated from banana peel (Musa paradisiaca) by enzymatic hydrolysis. Banana starch-based nanocomposite films were prepared with CNFs using the casting method. CNFs effect on cell viability and on nanocomposite films properties’ was investigated. The cytotoxicity of CNFs was assessed on Caco-2 cell line. CNFs were not cytotoxic at 50–2000 μg/mL. However, CNFs above 2000 μg/mL significantly decreased cell viability. Topography analysis showed that the incorporation of CNFs modified the film structure. The nanocomposites exhibited a complex structure due to strong interactions between CNFs and starch matrix, promoting a remarkable improvement on mechanical and water barrier properties, opacity and UV light barrier compared to the control film. CNFs can offer a great potential as reinforcing material for starch-based nanocomposite films, producing a value-added food packaging from a waste material. [less ▲]

Unraveling the Role of Sn Segregation in the Electronic Transport of Polycrystalline Hematite: Raising the Electronic Conductivity by Lowering the Grain-Boundary Blocking Effect

in Advanced Electronic Materials (2019), 0(0), 1900065

This paper describes the role of SnO2 in the electronic transport of polycrystalline hematite (α-Fe2O3). The proper sintering process allows for freezing of a state of electronic defects, in which the ... [more ▼]

This paper describes the role of SnO2 in the electronic transport of polycrystalline hematite (α-Fe2O3). The proper sintering process allows for freezing of a state of electronic defects, in which the electrical properties of hematite are controlled by the grain boundary and Sn segregation. Impedance spectroscopy and dc conductivity measurements show that current flows through preferential pathways associated with Sn segregation that occurs at the grain boundary, leading to a decrease in grain-boundary resistance. Atomic force microscopy and electric force microscopy measurements confirm the results of the impedance analysis. The identification of preferential grain boundaries for electrical conductivity may have a direct influence on the light-induced water-splitting performance of the hematite photoanode. [less ▲]

Non-target screening reveals time trends of polar micropollutants in a riverbank filtration system

in Environmental Science Technology (2019), 53(13), 7584-7594

The historic emissions of polar micropollutants in a natural drinking water source were investigated by nontarget screening with high-resolution mass spectrometry and open cheminformatics tools. The study ... [more ▼]

The historic emissions of polar micropollutants in a natural drinking water source were investigated by nontarget screening with high-resolution mass spectrometry and open cheminformatics tools. The study area consisted of a riverbank filtration transect fed by the river Lek, a branch of the lower Rhine, and exhibiting up to 60-year travel time. More than 18,000 profiles were detected. Hierarchical clustering revealed that 43% of the 15 most populated clusters were characterized by intensity trends with maxima in the 1990s, reflecting intensified human activities, wastewater treatment plant upgrades and regulation in the Rhine riparian countries. Tentative structure annotation was performed using automated in silico fragmentation. Candidate structures retrieved from ChemSpider were scored based on the fit of the in silico fragments to the experimental tandem mass spectra, similarity to openly accessible accurate mass spectra, associated metadata, and presence in a suspect list. Sixty-seven unique structures (72 over both ionization modes) were tentatively identified, 25 of which were confirmed and included contaminants so far unknown to occur in bank filtrate or in natural waters at all, such as tetramethylsulfamide. This study demonstrates that many classes of hydrophilic organics enter riverbank filtration systems, persisting and migrating for decades if biogeochemical conditions are stable. [less ▲]

The metaRbolomics Toolbox in Bioconductor and beyond

in Metabolites (2019), 9(10), 200

Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and ... [more ▼]

Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of high-dimensional and complex experimental data. Open source processing and analysis tools are of major interest in light of innovative, open and reproducible science. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The programming and statistics environment R has emerged as one of the most popular environments to process and analyse Metabolomics datasets. A major benefit of such an environment is the possibility of connecting different tools into more complex workflows. Combining reusable data processing R scripts with the experimental data thus allows for open, reproducible research. This review provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation and identification, and biochemical network and pathway analysis. Multifunctional workflows, possible user interfaces and integration into workflow management systems are also reviewed. In total, this review summarises more than two hundred metabolomics specific packages primarily available on CRAN, Bioconductor and GitHub. [less ▲]

Strengthen the European collaborative environmental research to meet European policy goals for achieving a sustainable, non-toxic environment

in Environmental Sciences Europe (2019), 31(1), 1--9

To meet the United Nations (UN) sustainable development goals and the European Union (EU) strategy for a non-toxic environment, water resources and ecosystems management require cost-efficient solutions ... [more ▼]

To meet the United Nations (UN) sustainable development goals and the European Union (EU) strategy for a non-toxic environment, water resources and ecosystems management require cost-efficient solutions for prevailing complex contamination and multiple stressor exposures. For the protection of water resources under global change conditions, specific research needs for prediction, monitoring, assessment and abatement of multiple stressors emerge with respect to maintaining human needs, biodiversity, and ecosystem services. Collaborative European research seems an ideal instrument to mobilize the required transdisciplinary scientific support and tackle the large-scale dimension and develop options required for implementation of European policies. Calls for research on minimizing society’s chemical footprints in the water–food–energy–security nexus are required. European research should be complemented with targeted national scientific funding to address specific transformation pathways and support the evaluation, demonstration and implementation of novel approaches on regional scales. The foreseeable pressure developments due to demographic, economic and climate changes require solution-oriented thinking, focusing on the assessment of sustainable abatement options and transformation pathways rather than on status evaluation. Stakeholder involvement is a key success factor in collaborative projects as it allows capturing added value, to address other levels of complexity, and find smarter solutions by synthesizing scientific evidence, integrating governance issues, and addressing transition pathways. This increases the chances of closing the value chain by implementing novel solutions. For the water quality topic, the interacting European collaborative projects SOLUTIONS, MARS and GLOBAQUA and the NORMAN network provide best practice examples for successful applied collaborative research including multi-stakeholder involvement. They provided innovative conceptual, modelling and instrumental options for future monitoring and management of chemical mixtures and multiple stressors in European water resources. Advancement of EU water framework directive-related policies has therefore become an option. [less ▲]

High-resolution mass spectrometry to complement monitoring and track emerging chemicals and pollution trends in European water resources

in Environmental Sciences Europe (2019), 31(1), 62

Currently, chemical monitoring based on priority substances fails to consider the majority of known environmental micropollutants not to mention the unexpected and unknown chemicals that may contribute to ... [more ▼]

Currently, chemical monitoring based on priority substances fails to consider the majority of known environmental micropollutants not to mention the unexpected and unknown chemicals that may contribute to the toxic risk of complex mixtures present in the environment. Complementing component- and effect-based monitoring with wide-scope target, suspect, and non-target screening (NTS) based on high-resolution mass spectrometry (HRMS) data is recommended to support environmental impact and risk assessment. This will allow for detection of newly emerging compounds and transformation products, retrospective monitoring efforts, and the identification of possible drivers of toxicity by correlation with effects or modelling of expected effects for future and abatement scenarios. HRMS is becoming increasingly available in many laboratories. Thus, the time is right to establish and harmonize screening methods, train staff, and record HRMS data for samples from regular monitoring events and surveys. This will strongly enhance the value of chemical monitoring data for evaluating complex chemical pollution problems, at limited additional costs. Collaboration and data exchange on a European-to-global scale is essential to maximize the benefit of chemical screening. Freely accessible data platforms, inter-laboratory trials, and the involvement of international partners and networks are recommended. [less ▲]