Where to enhance rural palliative care? Developing a spatial model to identify suitable communities most in need of service enhancement.

BACKGROUND: In Canada, access to palliative care is a growing concern, particularly in rural communities. These communities have constrained health care services and accessing local palliative care can be challenging. The Site Suitability Model (SSM) was developed to identify rural "candidate" communities with need for palliative care services and existing health service capacity that could be enhanced to support a secondary palliative care hub. The purpose of this study was to test the feasibility of implementing the SSM in Ontario by generating a ranked summary of rural "candidate" communities as potential secondary palliative care hubs. METHODS: Using Census data combined with community-level data, the SSM was applied to assess the suitability of 12 communities as rural secondary palliative care hubs. Scores from 0 to 1 were generated for four equally-weighted components: (1) population as the total population living within a 1-h drive of a candidate community; (2) isolation as travel time from that community to the nearest community with palliative care services; (3) vulnerability as community need based on a palliative care index score; and (4) community readiness as five dimensions of fit between a candidate community and a secondary palliative care hub. Component scores were summed for the SSM score and adjusted to range from 0 to 1. RESULTS: Population scores for the 12 communities ranged widely (0.19-1.00), as did isolation scores (0.16-0.94). Vulnerability scores ranged more narrowly (0.27-0.35), while community readiness scores ranged from 0.4-1.0. These component scores revealed information about each community's particular strengths and weaknesses. Final SSM scores ranged from a low of 0.33 to a high of 0.76. CONCLUSIONS: The SSM was readily implemented in Ontario. Final scores generated a ranked list based on the relative suitability of candidate communities to become secondary palliative care hubs. This list provides information for policy makers to make allocation decisions regarding rural palliative services. The calculation of each community's scores also generates information for local policy makers about how best to provide these services within their communities. The multi-factorial structure of the model enables decision makers to adapt the relative weights of its components.

Gas Fermentation-A Flexible Platform for Commercial Scale Production of Low-Carbon-Fuels and Chemicals from Waste and Renewable Feedstocks.

There is an immediate need to drastically reduce the emissions associated with global fossil fuel consumption in order to limit climate change. However, carbon-based materials, chemicals, and transportation fuels are predominantly made from fossil sources and currently there is no alternative source available to adequately displace them. Gas-fermenting microorganisms that fix carbon dioxide (CO2) and carbon monoxide (CO) can break this dependence as they are capable of converting gaseous carbon to fuels and chemicals. As such, the technology can utilize a wide range of feedstocks including gasified organic matter of any sort (e.g., municipal solid waste, industrial waste, biomass, and agricultural waste residues) or industrial off-gases (e.g., from steel mills or processing plants). Gas fermentation has matured to the point that large-scale production of ethanol from gas has been demonstrated by two companies. This review gives an overview of the gas fermentation process, focusing specifically on anaerobic acetogens. Applications of synthetic biology and coupling gas fermentation to additional processes are discussed in detail. Both of these strategies, demonstrated at bench-scale, have abundant potential to rapidly expand the commercial product spectrum of gas fermentation and further improve efficiencies and yields.

Carbon recovery by fermentation of CO-rich off gases - Turning steel mills into biorefineries.

Technological solutions to reduce greenhouse gas (GHG) emissions from anthropogenic sources are required. Heavy industrial processes, such as steel making, contribute considerably to GHG emissions. Fermentation of carbon monoxide (CO)-rich off gases with wild-type acetogenic bacteria can be used to produce ethanol, acetate, and 2,3-butanediol, thereby, reducing the carbon footprint of heavy industries. Here, the processes for the production of ethanol from CO-rich off gases are discussed and a perspective on further routes towards an integrated biorefinery at a steel mill is given. Recent achievements in genetic engineering as well as integration of other biotechnology platforms to increase the product portfolio are summarized. Already, yields have been increased and the portfolio of products broadened. To develop a commercially viable process, however, the extraction from dilute product streams is a critical step and alternatives to distillation are discussed. Finally, another critical step is waste(water) treatment with the possibility to recover resources.

Traits of selected Clostridium strains for syngas fermentation to ethanol.

Syngas fermentation is an anaerobic bioprocess that could become industrially relevant as a biorefinery platform for sustainable production of fuels and chemicals. An important prerequisite for commercialization is adequate performance of the biocatalyst (i.e., sufficiently high production rate, titer, selectivity, yield, and stability of the fermentation). Here, we compared the performance of three potential candidate Clostridium strains in syngas-to-ethanol conversion: Clostridium ljungdahlii PETC, C. ljungdahlii ERI-2, and Clostridium autoethanogenum JA1-1. Experiments were conducted in a two-stage, continuously fed syngas-fermentation system that had been optimized for stable ethanol production. The two C. ljungdahlii strains performed similar to each other but different from C. autoethanogenum. When the pH value was lowered from 5.5 to 4.5 to induce solventogenesis, the cell-specific carbon monoxide and hydrogen consumption (similar rate for all strains at pH 5.5), severely decreased in JA1-1, but hardly in PETC and ERI-2. Ethanol production in strains PETC and ERI-2 remained relatively stable while the rate of acetate production decreased, resulting in a high ethanol/acetate ratio, but lower overall productivities. With JA1-1, lowering the pH severely lowered rates of both ethanol and acetate production; and as a consequence, no pronounced shift to solventogenesis was observed. The highest overall ethanol production rate of 0.301 g · L(-1) · h(-1) was achieved with PETC at pH 4.5 with a corresponding 19 g/L (1.9% w/v) ethanol concentration and a 5.5:1 ethanol/acetate molar ratio. A comparison of the genes relevant for ethanol metabolism revealed differences between C. ljungdahlii and C. autoethanogenum that, however, did not conclusively explain the different phenotypes.

A survey of the Pseudomonas syringae pv. tomato DC3000 type III secretion system effector repertoire reveals several effectors that are deleterious when expressed in Saccharomyces cerevisiae.

The injection of nearly 30 effector proteins by the type III secretion system underlies the ability of Pseudomonas syringae pv. tomato DC3000 to cause disease in tomato and other host plants. The search for effector functions is complicated by redundancy within the repertoire and by plant resistance (R)-gene sentinels, which may convert effector virulence activities into a monolithic defense response. On the premise that some effectors target universal eukaryotic processes and that yeast (Saccharomyces cerevisiae) lacks R genes, the DC3000 effector repertoire was expressed in yeast. Of 27 effectors tested, HopAD1, HopAO1, HopD1, HopN1, and HopU1 were found to inhibit growth when expressed from a galactose-inducible GAL1 promoter, and HopAA1-1 and HopAM1 were found to cause cell death. Catalytic site mutations affecting the tyrosine phosphatase activity of HopAO1 and the cysteine protease activity of HopN1 prevented these effectors from inhibiting yeast growth. Expression of HopAA1-1, HopAM1, HopAD1, and HopAO1 impaired respiration in yeast, as indicated by tests with ethanol glycerol selective media. HopAA1-1 colocalized with porin to yeast mitochondria and was shown to cause cell death in yeast and plants in a domain-dependent manner. These results support the use of yeast for the study of plant-pathogen effector repertoires.