The Kansas City palliative care curriculum--medical schools improve end-of-life training

Midwest Bioethics Center believes that encouraging palliative care training in the school milieu is one of the keys to achieving lasting improvement in end-of-life care. Therefore, a cooperative venture to increase palliative care education in medical schools was among the first strategies envisioned in the Center's PATHWAYS initiative. Its implementation, no less than its goal, requires both time and effort.     

Robust approach to combining multiple markers to improve surrogacy

Identifying effective and valid surrogate markers to make inference about a treatment effect on long-term outcomes is an important step in improving the efficiency of clinical trials. Replacing a long-term outcome with short-term and/or cheaper surrogate markers can potentially shorten study duration and reduce trial costs. There is sizable statistical literature on methods to quantify the effectiveness of a single surrogate marker. Both parametric and nonparametric approaches have been well developed for different outcome types. However, when there are multiple markers available, methods for combining markers to construct a composite marker with improved surrogacy remain limited. In this paper, building on top of the optimal transformation framework of Wang et al. (2020), we propose a novel calibrated model fusion approach to optimally combine multiple markers to improve surrogacy. Specifically, we obtain two initial estimates of optimal composite scores of the markers based on two sets of models with one set approximating the underlying data distribution and the other directly approximating the optimal transformation function. We then estimate an optimal calibrated combination of the two estimated scores which ensures both validity of the final combined score and optimality with respect to the proportion of treatment effect explained by the final combined score. This approach is unique in that it identifies an optimal combination of the multiple surrogates without strictly relying on parametric assumptions while borrowing modeling strategies to avoid fully nonparametric estimation which is subject to the curse of dimensionality. Our identified optimal transformation can also be used to directly quantify the surrogacy of this identified combined score. Theoretical properties of the proposed estimators are derived, and the finite sample performance of the proposed method is evaluated through simulation studies. We further illustrate the proposed method using data from the Diabetes Prevention Program study.     

An approach to improve Wang-Smith chaotic simulated annealing

Previous research shows that Wang-Smith chaotic simulated annealing, which employs a gradually decreasing time-step, has only a scaling effect to computational energy of the Hopfield model without changing its shape. This makes the net has sensitive dependence on the value of damping factor. Considering Chen-Aihara chaotic simulated annealing with decaying self-coupling has a shape effect to computational energy of the Hopfield model, a novel approach to improve Wang-Smith chaotic simulated annealing, which reaps the benefits of Wang-Smith model and Chen-Aihara model, is proposed in this paper. With the aid of this method the improved model can affect on computational energy of the Hopfield model from scaling and shape. By adjusting the time-step, the improved neural network can also pass from a chaotic to a non-chaotic state. From numerical simulation experiments, we know that the improved model can escape from local minima more efficiently than original Wang-Smith model.     

A value chain approach to improve biomass policy formation

Biomass value chains for energy, fuels and bio‐based products involve complex, cross sector interactions between their upstream and downstream stages. Overarching policymaking to date has included the use of biomass to deliver sector specific aims (e.g. climate change, energy, etc.) however, this is mostly planned without adjusting support across the most challenging stages of biomass value chains and exploiting specific advantages related to their geographic settings (e.g. domestic feedstocks, local markets, etc.). Policies to date have, therefore, resulted in fragmented, suboptimal biomass use and debates for sustainability and resource efficiency. This opinion paper arose from the project Strategic Initiative for Resource Efficient Biomass Policies Funded by the EU Commission. It discusses the development of a dedicated Biomass Policy Framework which applies the principles of value chain analysis in policy design to enable the market uptake of sustainable, domestic, resource efficient biomass solutions. Firstly, it explains how to provide context by identifying value chains which can offer competitive advantages for biomass mobilization, market infrastructures, rural and economic development within their geographic setting. Then the work builds on the context and prioritized value chains and further rationalizes policy needs and aims within individual value chain stages. This is done by identifying policy‐related challenges and gaps that constrain sustainable and resource efficient deployment of the selected value chains. Also, it suggests policy interventions that will overcome challenges, resolve gaps and as a result mobilize local biomass and improve market uptake. Finally, it discusses the contrasting paradigms for biomass policy formation within single sector target setting and the value chain approach of the Biomass Policy Framework and uses the case of low carbon biomass heat to illustrate the strengths of the suggested approach. The paper concludes with remarks for the concept of biomass value chain analysis in policy.     

Scaling of biological community structure: a systems approach to community complexity

Local community dynamics are determined by the interaction of environmental variation and the biotic properties of communities. This interaction occurs on many spatial and temporal scales, hence the expectation is that community dynamics will be complex. Previous theoretical approaches to communities have assumed linear, near equilibrium dynamics. An alternative approach suggests that community dynamics are the result of the balance between energy use by the community and its tendency to move towards thermodynamic equilibrium, in this case extinction of all species in the community. Because this balance will be imprecise, community dynamics should be oscillatory. Furthermore, because energy use by a community can be broken down into a hierarchical set of processes occurring on different time scales, community dynamics should reflect multiple periodicities. The above theoretical treatment suggests that since community dynamics are scaled, a hierarchical observational approach should help resolve important aspects of community structure. This approach of scaling community observations provides a technique for evaluation of community responses to environmental change, including human induced perturbations. A thermodynamic approach to community dynamics can also provide the basis for new theoretical and empricial discoveries about biological communities.     

Multivariate geometry as an approach to algal community analysis

Multivariate analyses are put in the context of more usual approaches to phycological investigations. The intuitive common-sense involved in methods of ordination, classification and discrimination are emphasised by simple geometric accounts which avoid jargon and matrix algebra. Warnings are given that artifacts result from technique abuses by the naive or over-enthusiastic. An analysis of a simple periphyton data set is presented as an example of the approach. Suggestions are made as to situations in phycological investigations, where the techniques could be appropriate. The discipline is reprimanded for its neglect of the multivariate approach.     

An organism-centered approach to some community and ecosystem concepts

We present a discussion of the ecological concept of the niche based on the perspective of the individual organism, rather than that of a population or species. This discussion is then expanded to include other related ecological concepts such as guild, environment, habitat and functional group.Using the individual as the focus permits the development of a system of concepts which, we believe, approximate the way that ecological interactions occur in nature.     

A niche-based modeling approach to phytoplankton community assembly rules

Six niche-based models proposed by Tokeshi, based on different assumptions of resource allocation by species, were fitted on phytoplankton relative abundance distributions, and potential environmental and biotic factors supporting the applicability of the fitted models were discussed. Overall 16 assemblages corresponding to different sampling times, various environmental conditions, and resource regimes within a year were fitted to the models. Phytoplankton biovolume was used as a measure of abundance, and a randomization test was applied to compare the model fit to the field data. The majority of the phytoplankton assemblages (11 of 16) were successfully described by the Random Fraction model, which is based on the theoretical assumption that resource is apportioned by the species in a random way. Only a few assemblages (three of 16), characterized by extremes in resource availability or disturbance, were not fitted by any of the models. The Random Fraction model in particular was rejected due to a steep slope during the first ranks, while the rest of the distribution remained relatively even, providing further evidence of resilience in phytoplankton communities. Although larger cells seem to have the potential to develop higher biomass, it seems that other factors, including the surface-to-volume ratio, counterbalance this advantage, resulting in a random-like behaviour in resource acquisition by phytoplankton, irrespective of cell size or species identity.     

A stringent approach to improve the quality of nitrotyrosine peptide identifications

Tyrosine nitration is the consequence of a complex machinery of formation and merging of oxygen and nitrogen radicals, and has been associated with both physiological pathways as well as with several human diseases. The latter turned this posttranslational protein modification into an interesting biomarker, being either a consequence of the disease or a factor contributing to the disease onset. However, the interpretation of MS and MS/MS data of peptides containing nitrotyrosine has proven to be very challenging and consequently, the risk of linking MS/MS spectra to incorrect peptide sequences exists and has been reported. Here, we discuss the causes of data misinterpretation and describe a general method to avoid mistakes of MS/MS spectrum misinterpretation. Central in our approach is the reduction of nitrotyrosine into aminotyrosine and the use of the Peptizer algorithm to inspect MS/MS quality-related assumptions.     

Applying an animal‐centric approach to improve ecological restoration

Traditionally, ecological restoration is based on re‐establishing patterns of vegetation communities with the expectation that wildlife will recolonize, restoring the ecological function. However, in many restoration projects, wildlife fails to recolonize, even when vegetation is restored, in many cases because revegetated habitats lack the critical features required by wildlife. We present a new approach to restoration, based on a detailed understanding of ecological process, the mechanisms by which wildlife respond to landscape patterns. Our animal‐centric approach involves measuring the risk‐sensitive decision‐making of individual animals as they balance searching for food, mates, and breeding sites with avoiding being eaten by predators and relates this to fine‐scale habitat and landscape structure. The outcome of these decisions can be measured in occupancy of habitat, the information on which conventional restoration is based. Incorporating landscape genetics allows retrospective assessment of the outcome of dispersal decisions by individual animals on a deeper time frame and at regional scales. Fine‐scale connectivity models can be parameterized with these multiscale spatial and temporal data to direct restoration efforts. We are translating this novel approach to practice in the large Midlands restoration project (4 years, AUD $6 million) in Tasmania, Australia, in partnership with Greening Australia. More than 200 years of intensive agricultural practice in this National Biodiversity Hotspot has resulted in extensive landscape modification, high densities of feral cats, and decline of many native mammals. Our research–practice partnership will alter the way that restoration is done, leading hopefully to successful restoration of wildlife, gene flow, and ecological function.     

A statistical approach to improve compound screening in cell culture media

The Chinese hamster ovary (CHO) cell line is widely used for the production of recombinant proteins due to its high growing capacity and productivity, as well as other cell lines derived later than CHO. Adapting cell culture media for each specific cell line is a key to exploit these features for cost effective and fast product generation. Media supplementation is generally addressed by means of one‐factor‐at‐a‐time or classical design of experiments approaches but these techniques may not be efficient enough in preliminary screening phases. In this study, a novel strategy consisting in folding over the Plackett–Burman design was used to increase cell growth and trastuzumab production of different CHO cell lines through supplementation with nonanimal recombinant compounds. Synergies between compounds could be detected with a reduced number of experiments by using this methodology in comparison to more conventional fractional factorial designs. In the particular case reported here, the sequential use of this modified Plackett–Burman in combination with a Box‐Behnken design led to a 1.5‐fold increase in cell growth (10 × 10⁶ cells/mL) and a two‐fold in trastuzumab titer (122 mg/L) in suspension batch culture.     

3D-Jury: a simple approach to improve protein structure predictions

MOTIVATION: Consensus structure prediction methods (meta-predictors) have higher accuracy than individual structure prediction algorithms (their components). The goal for the development of the 3D-Jury system is to create a simple but powerful procedure for generating meta-predictions using variable sets of models obtained from diverse sources. The resulting protocol should help to improve the quality of structural annotations of novel proteins. Results: The 3D-Jury system generates meta-predictions from sets of models created using variable methods. It is not necessary to know prior characteristics of the methods. The system is able to utilize immediately new components (additional prediction providers). The accuracy of the system is comparable with other well-tuned prediction servers. The algorithm resembles methods of selecting models generated using ab initio folding simulations. It is simple and offers a portable solution to improve the accuracy of other protein structure prediction protocols. AVAILABILITY: The 3D-Jury system is available via the Structure Prediction Meta Server (http://BioInfo.PL/Meta/) to the academic community. SUPPLEMENTARY INFORMATION: 3D-Jury is coupled to the continuous online server evaluation program, LiveBench (http://BioInfo.PL/LiveBench/)     

An analytical approach to spatio-temporal dynamics of neutral community models

We propose a spatial version of the neutral community model on a network of interconnected patches. The dynamical equations for the abundances and higher order moments of the abundances are established. Due to the neutrality assumption these equations are autonomous, enabling an exact analysis of spatio-temporal dynamics. We compute local (i.e., inside a patch) and global (i.e., between patches) diversities, and illustrate our results with two examples: (1) a non-spatial community, for which we recover previous results, and (2) a model with a finite number of patches which are all connected to each other with equal migration intensity. We discuss the relevance of this model for experiments in microbial ecology.     

Measuring biodiversity to explain community assembly: a unified approach

One of the oldest challenges in ecology is to understand the processes that underpin the composition of communities. Historically, an obvious way in which to describe community compositions has been diversity in terms of the number and abundances of species. However, the failure to reject contradictory models has led to communities now being characterized by trait and phylogenetic diversities. Our objective here is to demonstrate how species, trait and phylogenetic diversity can be combined together from large to local spatial scales to reveal the historical, deterministic and stochastic processes that impact the compositions of local communities. Research in this area has recently been advanced by the development of mathematical measures that incorporate trait dissimilarities and phylogenetic relatedness between species. However, measures of trait diversity have been developed independently of phylogenetic measures and conversely most of the phylogenetic diversity measures have been developed independently of trait diversity measures. This has led to semantic confusions particularly when classical ecological and evolutionary approaches are integrated so closely together. Consequently, we propose a unified semantic framework and demonstrate the importance of the links among species, phylogenetic and trait diversity indices. Furthermore, species, trait and phylogenetic diversity indices differ in the ways they can be used across different spatial scales. The connections between large‐scale, regional and local processes allow the consideration of historical factors in addition to local ecological deterministic or stochastic processes. Phylogenetic and trait diversity have been used in large‐scale analyses to determine how historical and/or environmental factors affect both the formation of species assemblages and patterns in species richness across latitude or elevation gradients. Both phylogenetic and trait diversity have been used at different spatial scales to identify the relative impacts of ecological deterministic processes such as environmental filtering and limiting similarity from alternative processes such as random speciation and extinction, random dispersal and ecological drift. Measures of phylogenetic diversity combine phenotypic and genetic diversity and have the potential to reveal both the ecological and historical factors that impact local communities. Consequently, we demonstrate that, when used in a comparative way, species, trait and phylogenetic structures have the potential to reveal essential details that might act simultaneously in the assembly of species communities. We highlight potential directions for future research. These might include how variation in trait and phylogenetic diversity alters with spatial distances, the role of trait and phylogenetic diversity in global‐scale gradients, the connections between traits and phylogeny, the importance of trait rarity and independent evolutionary history in community assembly, the loss of trait and phylogenetic diversity due to human impacts, and the mathematical developments of biodiversity indices including within‐species variations.     

A novel approach to improve the efficacy of tumour ablation during cryosurgery

Freezing tumours and ablating it using cryosurgery is becoming a popular surgical procedure for treatment of carcinomas. In order to improve the efficiency of the cryosurgical procedure different approaches have been implemented till now, e.g., injecting high thermal conductivity fluid inside the tumour, low latent heat fluids inside the tumour prior to cryosurgery etc. These techniques improve the cryosurgical process to some extent but lack in minimising the damage to the surrounding healthy tissues. In this study, a novel concept is proposed which advocates the use of solutions with specific thermophysical properties around the interface of tumour. Numerical modelling has been done to determine the location of the ice fronts in the presence of this solution around the boundary of the tumour. It is noticed that in the presence of solution layer, owing to its distinct thermophysical properties like low thermal conductivity, not only the cellular destruction is enhanced but also the damage to the surrounding healthy tissue is minimised. Further, results indicate that this strategy leads to a faster ablation rate reducing the surgical time immensely. Also, an optimal offset, the minimum distance between the tip of cryoprobe and the boundary of the tumour, is identified for a given tumour radius with a given active length which gives maximum tumour necrosis in less time. This optimal offset which has been identified for each case will help the surgeons in proper planning of cryosurgery and improving the effectiveness of this technique greatly, making it a better treatment modality than its counterparts in many ways. It is also observed that for a 2 mm increase in activelength of the cryoprobe, the decrease in optimal offset is approximately 1 mm, i.e. optimal offset decreases linearly with an increase in the activelength for a given radius of the tumour. Also, for tumour with different radii, ranging between 10 mm to 15 mm, with same active length, the time taken for complete ablation by the larger tumour is nearly 2.7 times the time taken by the smaller one for every 2.5 mm increase in the tumour radius.