Justice and equal opportunities in health care

The principle that each individual is entitled to an equal opportunity to benefit from any public health care system, and that this entitlement is proportionate neither to the size of their chance of benefitting, nor to the quality of the benefit, nor to the length of lifetime remaining in which that benefit may be enjoyed, runs counter to most current thinking about the allocation of resources for health care. It is my contention that any system of prioritisation of the resources available for healthcare or of rationing such resources must be governed by this principle.
This can have apparently paradoxical conclusions in that it can seem wasteful to give someone with a very slim chance of a lifesaving treatment the same priority as someone with a much better chance. In an important and thoughtful recent paper, Julian Savulescu has concentrated on this apparent weakness and has argued for a particular conception of the good or benefit to be achieved by a healthcare system which purports to demonstrate the inadequacies of an equal opportunities approach to prioritisation and to replace it with an altogether better account. This paper will show that a rational 'reasons based consequentialism' is more in line with the equal opportunities approach, which I defended some time ago in these pages, than with that of Savulescu. I shall then examine more closely the conception of equal opportunities in health care and show that if we give weight to an individual's reasons, and what is expected to be good for them, we will opt for exactly the equality based account of distributive justice that I have recommended.     

Lentiviral-Mediated Transgene Expression Can Potentiate Intestinal Mesenchymal-Epithelial Signaling

Mesenchymal-epithelial signaling is essential for the development of many organs and is often disrupted in disease. In this study, we demonstrate the use of lentiviral-mediated transgene delivery as an effective approach for ectopic transgene expression and an alternative to generation of transgenic animals. One benefit to this approach is that it can be used independently or in conjunction with established transgenic or knockout animals for studying modulation of mesenchymal-epithelial interactions. To display the power of this approach, we explored ectopic expression of a Wnt ligand in the mouse intestinal mesenchyme and demonstrate its functional influence on the adjacent epithelium. Our findings highlight the efficient use of lentiviral-mediated transgene expression for modulating mesenchymal-epithelial interactions in vivo.     

Quantitative Outcomes of a One Health approach to Study Global Health Challenges

Having gained momentum in the last decade, the One Health initiative promotes a holistic approach to address complex global health issues. Before recommending its adoption to stakeholders, however, it is paramount to first compile quantitative evidence of the benefit of such an approach. The aim of this scoping review was to identify and summarize primary research that describes monetary and non-monetary outcomes following adoption of a One Health approach. An extensive literature search yielded a total of 42,167 references, of which 85 were included in the final analysis. The top two biotic health issues addressed in these studies were rabies and malaria; the top abiotic health issue was air pollution. Most studies described collaborations between human and animal (n = 42), or human and environmental disciplines (n = 41); commonly reported interventions included vector control and animal vaccination. Monetary outcomes were commonly expressed as cost–benefit or cost–utility ratios; non-monetary outcomes were described using disease frequency or disease burden measurements. The majority of the studies reported positive or partially positive outcomes. This paper illustrates the variety of health challenges that can be addressed using a One Health approach, and provides tangible quantitative measures that can be used to evaluate future implementations of the One Health approach.     

The choice of allogeneic or autologous hematopoietic transplantation for NHL

NHL constitutes the sixth most common malignancy diagnosed in the USA every year, accounting for approximately 24,400 deaths. Although a subset of patients can be cured with chemotherapy or radiation therapy, the outlook is generally poor for patients with refractory or recurrent disease. High-dose therapy supported by both autologous and allogeneic transplantation has been widely studied in this group of patients. Autologous transplantation may be considered standard therapy for patients with diffuse large-cell NHL in chemotherapy-sensitive relapse. Selected categories of patients with other histologic subtypes may also benefit from this strategy. Allogeneic transplantation using high-dose myeloablative conditioning regimen is an effective, yet hazardous approach. A GvL effect leads to a lower rate of disease recurrence than occurs with autologous transplants, but this benefit is offset by higher risk of treatment related mortality. The recent use of less toxic non-myeloablative conditioning regimens for allogeneic transplantation has reduced the risk of transplant-related mortality, allowing this approach even in older or medically infirm patients. Nonablative allogeneic transplants are a promising strategy, particularly for patients with indolent lymphoid malignancies.     

Induced pluripotent stem cell-derived extracellular vesicles: A novel approach for cell-free regenerative medicine

In recent years, induced pluripotent stem cells (iPSCs) have been considered as a promising approach in the field of regenerative medicine. iPSCs can be generated from patients’ somatic cells and possess the potential to differentiate, under proper conditions, into any cell type. However, the clinical application of iPS cells is restricted because of their tumorigenic potential. Recent studies have indicated that stem cells exert their therapeutic benefit via a paracrine mechanism, and extracellular vesicles have been demonstrated that play a critical role in this paracrine mechanism. Due to lower immunogenicity, easier management, and presenting no risk of tumor formation, in recent years, researchers turned attention to exosomes as potential alternatives to whole-cell therapy. Application of exosomes derived from iPSCs and their derived precursor provides a promising approach for personalized regenerative medicine. This study reviews the physiological functions of extracellular vesicles and discusses their potential therapeutic benefit in regenerative medicine.     

Do We Know Whether Researchers and Reviewers are Estimating Risk and Benefit Accurately?

Accurate estimation of risk and benefit is integral to good clinical research planning, ethical review, and study implementation. Some commentators have argued that various actors in clinical research systems are prone to biased or arbitrary risk/benefit estimation. In this commentary, we suggest the evidence supporting such claims is very limited. Most prior work has imputed risk/benefit beliefs based on past behavior or goals, rather than directly measuring them. We describe an approach – forecast analysis – that would enable direct and effective measure of the quality of risk/benefit estimation. We then consider some objections and limitations to the forecasting approach.     

Hierarchical semantic composition of biosimulation models using bond graphs

Simulating complex biological and physiological systems and predicting their behaviours under different conditions remains challenging. Breaking systems into smaller and more manageable modules can address this challenge, assisting both model development and simulation. Nevertheless, existing computational models in biology and physiology are often not modular and therefore difficult to assemble into larger models. Even when this is possible, the resulting model may not be useful due to inconsistencies either with the laws of physics or the physiological behaviour of the system. Here, we propose a general methodology for composing models, combining the energy-based bond graph approach with semantics-based annotations. This approach improves model composition and ensures that a composite model is physically plausible. As an example, we demonstrate this approach to automated model composition using a model of human arterial circulation. The major benefit is that modellers can spend more time on understanding the behaviour of complex biological and physiological systems and less time wrangling with model composition.     

Selection of biomarkers by a multivariate statistical processing of composite metabonomic data sets using multiple factor analysis

We introduce a statistical approach for integrating data from several analytical platforms. We illustrate this approach using (1)H-(13)C Heteronuclear Multiple Bond Connectivity nuclear magnetic resonance spectroscopy ((1)H-(13)C HMBC NMR) and Pyrolysis Metastable Atom Bombardment Time-of-Flight mass spectrometry (Py-MAB-TOF-MS) to perform metabolic fingerprinting on cattle treated with anabolic steroids. Multiple factor analysis (MFA) integrates complementary aspects from NMR and MS data into a unique metabolic signature describing the biomarkers related to the dose-response. This work also indicates that, from a practical point of view, metabonomics and other "-omics" biotechnologies can benefit significantly from a generalized multi-platform integrative approach using multiple factor analysis.     

Prioritising source populations for supplementing genetic diversity of reintroduced southern brown bandicoots Isoodon obesulus obesulus

Conservation Genetics - Reintroduction programs can benefit from optimisation of source populations to maximise genetic diversity. Here, we report an approach to guide genetic supplementation of...     

Nuclear excision repair-based personalized therapy for non-small cell lung cancer: from hypothesis to reality

The crucial 'flaw' in the existing treatment paradigm for non-small cell lung cancer (NSCLC) is the 'one size fits all approach'. Consequently, adjuvant chemotherapy is given to all patients to benefit a minority and, in the metastatic setting doublet chemotherapy only provides modest improvements in response rates and survival. A personalized approach of treatment selection is therefore desperately needed. Genetic information is stored in the chemical structure of DNA. To maintain the structural integrity of DNA, an intricate network of DNA repair systems have evolved. One of these is the nucleotide excision repair (NER), a highly versatile and sophisticated DNA damage removal pathway. We show here that this DNA repair mechanism is instrumental in defining prognosis and response to treatment. ERCC1, one of the proteins in this pathway, is measured to assess its functional status of the NER pathway. In patients with early stage NSCLC, low ERCC1 predicts for relapse and selects for patients who will benefit from adjuvant cisplatin-based chemotherapy. Conversely, ERCC1-positive resected patients have a better intrinsic prognosis and are not likely to benefit from platinum based chemotherapy. In a phase II trial in metastatic disease, we show that by tailoring chemotherapy using ERCC1 and RRM1 we can obtain 1-year survival of 60% (versus approximately 36% in historical controls) and response rates of 42% (versus 25% in historical controls). This approach is currently being validated in a prospective phase III trial. In the future, assessment of NER function may play a central role in NSCLC treatment decision making.     

The debate over risk-related standards of competence

This discussion paper continues the debate over risk-related standards of mental competence which appears in Bioethics 5. Dan Brock there defends an approach to mental competence in patients which defines it as being relative to differing standards, more or less rigorous depending on the degree of risk involved in proposed treatments. But Mark Wicclair raises a problem for this approach: if significantly different levels of risk attach, respectively, to accepting and refusing the same treatment, then it is possible, on this account, for a patient to be considered competent to accept, but not refuse, the treatment, or vice versa. I argue that this puzzle does not constitute a genuine problem for a risk-related standard.
To this end I focus on the situation where, of two mutually exclusive options, one is riskier, but offering more pronounced benefit, while the other is safer, but offering less benefit. I argue for this proposition: it can take far less insight to know that the safe option is good than to know that the risky option is better. Now say one is actually informed enough to know that the safe option is good, but not enough to know whether the risky option is better; in such a case one is competent to say yes to that first option (the safe one), but not to say yes to the other. (I argue in passing that Pascal's Wager can be interpreted as having precisely this deliberative structure.)
I thus conclude that cases do indeed exist where one can be competent to say yes but not no, or vice versa; and that it is thus not an anomaly in the risk-related standard that it entails the existence of such cases.     

Pre-execution power consumption prediction of computational multithreaded workloads

Power management in large-scale computational environments can significantly benefit from predictive models. Such models provide information about the power consumption behavior of workloads prior to running them. Power consumption depends on the characteristics of both the machine and the workload. However, combinational features such as the cache miss rate cannot be considered due to their unavailability before running the workload. Therefore, pre-execution power modeling requires both machine-independent workload characteristics and workload-independent machine characteristics. In this paper the predictive modeling problem is tackled by the proposal of a two-stage modeling framework. In the first stage, a machine learning approach is taken to predict single-threaded workload power consumption at a specific frequency. The second stage analytically scales this output to any intended thread/frequency configuration. Experimental results show that the proposed approach can yield highly accurate predictions about workload power consumption with an average error of 3.7 % on six different test platforms.     

Could ecologists be more random? Straightforward alternatives to haphazard spatial sampling

When conducting field studies, it is common for ecologists to choose the locations of sampling units arbitrarily at the time sampling occurs, rather than using a properly randomised sampling design. Unfortunately, this ‘haphazard’ sampling approach cannot provide formal statistical inference from the sample to the population without making untestable assumptions. Here, we argue that two recent technological developments remove the need for haphazard sampling in many situations. A general approach to simple randomised sampling designs is outlined, and some examples demonstrate that even complicated designs can be implemented easily using software that is widely used among ecologists. We consider that more rigorous, randomised sampling designs would strengthen the validity of the conclusions drawn from ecological studies, to the benefit of the discipline as a whole.     

Updated Risk/Benefit Analysis of Fish Consumption Effects on Neurodevelopment: Implications for Setting Advisories

Epidemiological studies indicate that fish consumption during pregnancy leads to improved neurodevelopment. This suggests that the beneficial nutrients in fish may offset the adverse effects of mercury in the case of the average fish meal. However, our previous risk/benefit model predicted a net neurodevelopmental risk for the majority of species analyzed. In this article the previous model is calibrated against fish benefit data and then compared to other fish risk/benefit models, including recent models from the World Health Organization and USFDA. Our calibrated model estimated greater benefit for low mercury species but greater risk for high mercury species than the other models. With respect to a commonly eaten high mercury fish, swordfish, the calibrated model yielded risks that are supportive of current fish advisories but, in contrast, the other models predicted net neurodevelopmental benefits. The calibrated model was used in a proposed 3 step framework for setting fish consumption advisories: (1) Set initial consumption level based upon mercury RfD; (2) Adjust consumption upward if risk/benefit model indicates a net benefit; (3) Cap fish consumption based upon saturation of O-3 benefit. The implications of this approach for 7 varieties of fish are used to illustrate the framework.     

Statistical inference for net benefit measures in biomarker validation studies

Referral strategies based on risk scores and medical tests are commonly proposed. Direct assessment of their clinical utility requires implementing the strategy and is not possible in the early phases of biomarker research. Prior to late-phase studies, net benefit measures can be used to assess the potential clinical impact of a proposed strategy. Validation studies, in which the biomarker defines a prespecified referral strategy, are a gold standard approach to evaluating biomarker potential. Uncertainty, quantified by a confidence interval, is important to consider when deciding whether a biomarker warrants an impact study, does not demonstrate clinical potential, or that more data are needed. We establish distribution theory for empirical estimators of net benefit and propose empirical estimators of variance. The primary results are for the most commonly employed estimators of net benefit: from cohort and unmatched case-control samples, and for point estimates and net benefit curves. Novel estimators of net benefit under stratified two-phase and categorically matched case-control sampling are proposed and distribution theory developed. Results for common variants of net benefit and for estimation from right-censored outcomes are also presented. We motivate and demonstrate the methodology with examples from lung cancer research and highlight its application to study design.     

RNA Isolation from Cell Specific Subpopulations Using Laser-capture Microdissection Combined with Rapid Immunolabeling

Laser capture microdissection (LCM) allows the isolation of specific cells from thin tissue sections with high spatial resolution. Effective LCM requires precise identification of cells subpopulations from a heterogeneous tissue. Identification of cells of interest for LCM is usually based on morphological criteria or on fluorescent protein reporters. The combination of LCM and rapid immunolabeling offers an alternative and efficient means to visualize specific cell types and to isolate them from surrounding tissue. High-quality RNA can then be extracted from a pure cell population and further processed for downstream applications, including RNA-sequencing, microarray or qRT-PCR. This approach has been previously performed and briefly described in few publications. The goal of this article is to illustrate how to perform rapid immunolabeling of a cell population while keeping RNA integrity, and how to isolate these specific cells using LCM. Herein, we illustrated this multi-step procedure by immunolabeling and capturing dopaminergic cells in brain tissue from one-day-old mice. We highlight key critical steps that deserve special consideration. This protocol can be adapted to a variety of tissues and cells of interest. Researchers from different fields will likely benefit from the demonstration of this approach.     

Exploring the causes and consequences of cooperative behaviour in wild animal populations using a social network approach

Understanding why individuals carry out behaviours that benefit others, especially genetically unrelated others, has been a major undertaking in many fields and particularly in biology. Here, we focus on the cooperation literature from natural populations and present the benefits of a social network approach in terms of how it can help to identify and understand factors that influence the maintenance and spread of cooperation, but are not easily captured when solely considering independent dyadic interactions. We describe how various routes to cooperation can be tested within the social network framework. Applying the social network approach to data from natural populations can help to uncover the evolutionary and ecological pressures that lead to differences in cooperation and other social processes.     

Estimating Treatment Effects for Recurrent Events in the Presence of Rescue Medications: An Application to the Immune Thrombocytopenia Study

In many clinical studies, patients may experience the same type of event of interest repeatedly over time. However, the assessment of treatment effects is often complicated by the rescue medication uses due to ethical reasons. For example, in the motivating trial in studying the Immune Thrombocytopenia (ITP), when the interest lies in evaluating the treatment benefit of investigational product (IP) on reducing patient’s repeated bleeding, rescue medication such as platelet transfusions may be allowed to raise platelet counts. Both the intention-to-treat analysis and treating the intermediate rescue medication as covariate tend to attenuate the treatment benefit, and the estimates can be biased if interpreted as causal. In this paper, we propose a general causal framework when intermediate rescue medications are informative. We adopt the inverse weighted estimation approach to estimate the treatment effect, where weights are constructed to reflect time-dependent medication use probabilities. The proposed estimators are shown to be asymptotically normal and are demonstrated to perform well in small-sample simulation studies. The application to the ITP studies reveals a stronger benefit of using IP in reducing bleeding.