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"Rizzo, M"
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Scale-up approach for the preparation of magnetic ferrite nanocubes and other shapes with benchmark performance for magnetic hyperthermia applications
Magnetic nanoparticles are increasingly used in medical applications, including cancer treatment by magnetic hyperthermia. This protocol describes a solvothermal-based process to prepare, at the gram scale, ferrite nanoparticles with well-defined shape, i.e., nanocubes, nanostars and other faceted nanoparticles, and with fine control of structural/magnetic properties to achieve point-of-reference magnetic hyperthermia performance. This straightforward method comprises simple steps: (i) making a homogeneous alcoholic solution of a surfactant and an alkyl amine; (ii) adding an organometallic metal precursor together with an aldehyde molecule, which acts as the key shape directing agent; and (iii) reacting the mixture in an autoclave for solvothermal crystallization. The shape of the ferrite nanoparticles can be controlled by the structure of the aldehyde ligand. Benzaldehyde and its aromatic derivatives favor the formation of cubic ferrite nanoparticles while aliphatic aldehydes result in spherical nanoparticles. The replacement of the primary amine, used in the nanocubes synthesis, with a secondary/tertiary amine results in nanoparticles with star-like shape. The well-defined control in terms of shape, narrow size distribution (below 5%), compositional tuning and crystallinity guarantees the preparation, at the gram scale, of nanocubes/star-like nanoparticles that possess, under magnetic field conditions of clinical use, specific adsorption rates comparable to or even superior to those obtained through thermal decomposition methods, which are typically prepared at the milligram scale. Here, gram-scale nanoparticle products with benchmark features for magnetic hyperthermia applications can be prepared in ~10 h with an average level of expertise in chemistry.
This protocol describes a solvothermal-based process to prepare gram-scale ferrite nanoparticles with well-defined shapes (nanocubes, nanostars, faceted and spherical) having heating properties appealing for clinical magnetic hyperthermia treatments.
Journal Article
Economic Burden of Chronic Obstructive Pulmonary Disease (COPD): A Systematic Literature Review
Chronic obstructive pulmonary disease (COPD) affects over 250 million people globally, carrying a notable economic burden. This systematic literature review aimed to highlight the economic burden associated with moderate-to-very severe COPD and to investigate key drivers of healthcare resource utilization (HRU), direct costs and indirect costs for this patient population.
Relevant publications published between January 1, 2006 and November 14, 2016 were captured from the Embase, MEDLINE and MEDLINE In-Process databases. Supplemental searches from relevant 2015-2016 conferences were also performed. Titles and abstracts were reviewed by two independent researchers against pre-defined inclusion and exclusion criteria. Studies were grouped by the type of economic outcome presented (HRU or costs). Where possible, data were also grouped according to COPD severity and/or patient exacerbation history.
In total, 73 primary publications were included in this review: 66 reported HRU, 22 reported direct costs and one reported indirect costs. Most of the studies (94%) reported on data from either Europe or North America. Trends were noted across multiple studies for higher direct costs (including mean costs per patient per year and mean costs per exacerbation) being associated with increasingly severe COPD and/or a history of more frequent or severe exacerbations. Similar trends were noted according to COPD severity and/or exacerbation history for rate of hospitalization and primary care visits. Multivariate analyses were reported by 29 studies and demonstrated the statistical significance of these associations. Several other drivers of increased costs and HRU were highlighted for patients with moderate-to-very severe COPD, including comorbidities, and treatment history.
Moderate-to-very severe COPD represents a considerable economic burden for healthcare providers despite the availability of efficacious treatments and comprehensive guidelines on their use. Further research is warranted to ensure cost-efficient COPD management, to improve treatments and ease budgetary pressures.
Journal Article
THE POLITICAL ECONOMY OF AN URBAN MEGAPROJECT: THE BUS RAPID TRANSIT PROJECT IN TANZANIA
This article analyses the political economy of the Bus Rapid Transit project implemented in Dar es Salaam between 2002 and 2014. It discusses the recent rapid growth of Bus Rapid Transit systems and the vested interests of the actors promoting them as a \"win-win\" solution to tackle the crisis of public transport in developing countries. The article discredits such \"win-win\" narratives by showing what some Tanzanian actors stood to lose from the implementation of the Dar es Salaam Rapid Transit scheme and their capacity to resist the project. It analyses tensions over the inclusion of the current public transport workforce, employment destruction, displacement of current paratransit operators, compensation, and the affordability of the new service. The article argues that slow implementation of the transport system was rooted in the tepid commitment to the project by the Tanzanian government. In turn, this lack of political will can be explained by domestic politics, and in particular the government's attempt to respond to the priorities of the World Bank without alienating local actors, some of whom wield considerable electoral power.
Journal Article
VISTA is an acidic pH-selective ligand for PSGL-1
Co-inhibitory immune receptors can contribute to T cell dysfunction in patients with cancer
1
,
2
. Blocking antibodies against cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and programmed cell death 1 (PD-1) partially reverse this effect and are becoming standard of care in an increasing number of malignancies
3
. However, many of the other axes by which tumours become inhospitable to T cells are not fully understood. Here we report that V-domain immunoglobulin suppressor of T cell activation (VISTA) engages and suppresses T cells selectively at acidic pH such as that found in tumour microenvironments. Multiple histidine residues along the rim of the VISTA extracellular domain mediate binding to the adhesion and co-inhibitory receptor P-selectin glycoprotein ligand-1 (PSGL-1). Antibodies engineered to selectively bind and block this interaction in acidic environments were sufficient to reverse VISTA-mediated immune suppression in vivo. These findings identify a mechanism by which VISTA may engender resistance to anti-tumour immune responses, as well as an unexpectedly determinative role for pH in immune co-receptor engagement.
V-domain immunoglobulin suppressor of T cell activation (VISTA) selectively engages P-selectin glycoprotein ligand-1 (PSGL-1) and suppresses T cells at acidic pH similar to those in tumour microenvironments, thereby mediating resistance to anti-tumour immune responses.
Journal Article
Plant health and its effects on food safety and security in a One Health framework: four case studies
Although healthy plants are vital to human and animal health, plant health is often overlooked in the One Health literature. Plants provide over 80% of the food consumed by humans and are the primary source of nutrition for livestock. However, plant diseases and pests often threaten the availability and safety of plants for human and animal consumption. Global yield losses of important staple crops can range up to 30% and hundreds of billions of dollars in lost food production. To demonstrate the complex interrelationships between plants and public health, we present four case studies on plant health issues directly tied to food safety and/or security, and how a One Health approach influences the perception and mitigation of these issues. Plant pathogens affect food availability and consequently food security through reductions in yield and plant mortality as shown through the first case study of banana Xanthomonas wilt in East and Central Africa. Case studies 2, 3 and 4 highlight ways in which the safety of plant-based foods can also be compromised. Case study 2 describes the role of mycotoxin-producing plant-colonizing fungi in human and animal disease and examines lessons learned from outbreaks of aflatoxicosis in Kenya. Plants may also serve as vectors of human pathogens as seen in case study 3, with an example of
Escherichia coli (E. coli)
contamination of lettuce in North America. Finally, case study 4 focuses on the use of pesticides in Suriname, a complex issue intimately tied to food security though protection of crops from diseases and pests, while also a food safety issue through misuse. These cases from around the world in low to high income countries point to the need for interdisciplinary teams to solve complex plant health problems. Through these case studies, we examine challenges and opportunities moving forward for mitigating negative public health consequences and ensuring health equity. Advances in surveillance technology and functional and streamlined workflow, from data collection, analyses, risk assessment, reporting, and information sharing are needed to improve the response to emergence and spread of plant-related pathogens and pests. Our case studies point to the importance of collaboration in responses to plant health issues that may become public health emergencies and the value of the One Health approach in ensuring food safety and food security for the global population.
Journal Article
Amphetamines signal through intracellular TAAR1 receptors coupled to Gα13 and GαS in discrete subcellular domains
The extensive use of amphetamines to treat attention deficit hyperactivity disorders in children provides a compelling rationale for understanding the mechanisms of action of amphetamines and amphetamine-related drugs. We have previously shown that acute amphetamine (AMPH) regulates the trafficking of both dopamine and glutamate transporters in dopamine neurons by increasing activation of the small GTPase RhoA and of protein kinase A. Here we demonstrate that these downstream signaling events depend upon the direct activation of a trace amine-associated receptor, TAAR1, an intracellular G-protein coupled receptor (GPCR) that can be activated by amphetamines, trace amines, and biogenic amine metabolites. Using cell lines and mouse lines in which TAAR1 expression has been disrupted, we demonstrate that TAAR1 mediates the effects of AMPH on both RhoA and cAMP signaling. Inhibition of different Gα signaling pathways in cell lines and in vivo using small cell-permeable peptides confirms that the endogenous intracellular TAAR1 couples to G13 and to GS α-subunits to increase RhoA and PKA activity, respectively. Results from experiments with RhoA- and PKA-FRET sensors targeted to different subcellular compartments indicate that AMPH-elicited PKA activation occurs throughout the cell, whereas G13-mediated RhoA activation is concentrated near the endoplasmic reticulum. These observations define TAAR1 as an obligate intracellular target for amphetamines in dopamine neurons and support a model in which distinct pools of TAAR1 mediate the activation of signaling pathways in different compartments to regulate excitatory and dopaminergic neurotransmission.
Journal Article
Improving decision support systems with machine learning: Identifying barriers to adoption
Precision agriculture (PA) has been defined as a “management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.” This definition suggests that because PA should simultaneously increase food production and reduce the environmental footprint, the barriers to adoption of PA should be explored. These barriers include (1) the financial constraints associated with adopting decision support system (DSS); (2) the hesitancy of farmers to change from their trusted advisor to a computer program that often behaves as a black box; (3) questions about data ownership and privacy; and (4) the lack of a trained workforce to provide the necessary training to implement DSSs on individual farms. This paper also discusses the lessons learned from successful and unsuccessful efforts to implement DSSs, the importance of communication with end users during DSS development, and potential career opportunities that DSSs are creating in PA. Core Ideas Decision support systems (DSSs) are one component of precision agriculture (PA). The accuracy of DSSs may be improved by using algorithms based on machine learning. Barriers to DSSs include financial constraints, hesitancy to change, data privacy, and workforce limitations. Professional opportunities exist to overcome DSS adoption barriers.
Journal Article
A Spatiotemporal Interrogation of Hydrologic Drought Model Performance for Machine Learning Model Interpretability
The predictive accuracy of regional hydrologic models often varies across both time and space. Interpreting relationships between watershed characteristics, hydrologic regimes, and model performance can reveal potential areas for model improvement. In this study, we use machine learning to assess model performance of a regional hydrologic model to forecast the occurrence of streamflow drought. We demonstrate our methodology using a regional long short‐term memory (LSTM) deep learning model developed by the U.S. Geological Survey (USGS) and data from 384 streamgages across the Colorado River Basin region. Performance was assessed by clustering catchments using: (a) physical and climatological catchment attributes, and (b) streamflow drought signatures time series. We examined the association of USGS LSTM model error measures with clusters generated by both approaches to interpret meaningful spatial and temporal information about LSTM model performance. Clustering static catchment attributes identified elevation, degree of streamflow regulation, baseflow contribution, catchment aridity, and drainage area as the most influential attributes to model performance. Clustering gages by their drought signatures revealed that catchments with significant seasonal peak runoff between January and June generally exhibited better model performance. Additionally, a Random Forest classifier was trained to successfully predict LSTM model performance (F1 score of 0.72) based on physical and climatological catchment attributes. Low degree of flow regulation was identified as a key indicator of better LSTM model performance. These findings point to the opportunities for improving the USGS LSTM model performance in future hydrologic drought prediction efforts across regional and CONUS scales.
Journal Article
Phytophthora ramorum: Integrative Research and Management of an Emerging Pathogen in California and Oregon Forests
Phytophthora ramorum, causal agent of sudden oak death, is an emerging plant pathogen first observed in North America associated with mortality of tanoak (Lithocarpus densiflorus) and coast live oak (Quercus agrifolia) in coastal forests of California during the mid-1990s. The pathogen is now known to occur in North America and Europe and have a host range of over 40 plant genera. Sudden oak death has become an example of unintended linkages between the horticultural industry and potential impacts on forest ecosystems. This paper examines the biology and ecology of P. ramorum in California and Oregon forests as well discussing research on the pathogen in a broader management context.
Journal Article