Correction: Stroke survivors' and informal caregivers' experiences of primary care and community healthcare services - A systematic review and meta-ethnography.

[This corrects the article DOI: 10.1371/journal.pone.0192533.].

Stroke survivors' and informal caregivers' experiences of primary care and community healthcare services - A systematic review and meta-ethnography.

OBJECTIVE: To describe and explain stroke survivors and informal caregivers' experiences of primary care and community healthcare services. To offer potential solutions for how negative experiences could be addressed by healthcare services. DESIGN: Systematic review and meta-ethnography. DATA SOURCES: Medline, CINAHL, Embase and PsycINFO databases (literature searched until May 2015, published studies ranged from 1996 to 2015). ELIGIBILITY CRITERIA: Primary qualitative studies focused on adult community-dwelling stroke survivors' and/or informal caregivers' experiences of primary care and/or community healthcare services. DATA SYNTHESIS: A set of common second order constructs (original authors' interpretations of participants' experiences) were identified across the studies and used to develop a novel integrative account of the data (third order constructs). Study quality was assessed using the Critical Appraisal Skills Programme checklist. Relevance was assessed using Dixon-Woods' criteria. RESULTS: 51 studies (including 168 stroke survivors and 328 caregivers) were synthesised. We developed three inter-dependent third order constructs: (1) marginalisation of stroke survivors and caregivers by healthcare services, (2) passivity versus proactivity in the relationship between health services and the patient/caregiver dyad, and (3) fluidity of stroke related needs for both patient and caregiver. Issues of continuity of care, limitations in access to services and inadequate information provision drove perceptions of marginalisation and passivity of services for both patients and caregivers. Fluidity was apparent through changing information needs and psychological adaptation to living with long-term consequences of stroke. LIMITATIONS: Potential limitations of qualitative research such as limited generalisability and inability to provide firm answers are offset by the consistency of the findings across a range of countries and healthcare systems. CONCLUSIONS: Stroke survivors and caregivers feel abandoned because they have become marginalised by services and they do not have the knowledge or skills to re-engage. This can be addressed by: (1) increasing stroke specific health literacy by targeted and timely information provision, and (2) improving continuity of care between specialist and generalist services. SYSTEMATIC REVIEW REGISTRATION NUMBER: PROSPERO 2015:CRD42015026602.

Primary care interventions and current service innovations in modifying long-term outcomes after stroke: a protocol for a scoping review.

INTRODUCTION: Interventions delivered by primary and/or community care have the potential to reach the majority of stroke survivors and carers and offer ongoing support. However, an integrative account emerging from the reviews of interventions addressing specific long-term outcomes after stroke is lacking. The aims of the proposed scoping review are to provide an overview of: (1) primary care and community healthcare interventions by generalist healthcare professionals to stroke survivors and/or their informal carers to address long-term outcomes after stroke, (2) the scope and characteristics of interventions which were successful in addressing long-term outcomes, and (3) developments in current clinical practice. METHODS AND ANALYSIS: Studies that focused on adult community dwelling stroke survivors and informal carers were included. Academic electronic databases will be searched to identify reviews of randomised controlled trials (RCTs) and controlled trials, trials from the past 5 years; reviews of observational studies. Practice exemplars from grey literature will be identified through advanced Google search. Reports, guidelines and other documents of major health organisations, clinical professional bodies, and stroke charities in the UK and internationally will be included. Two reviewers will independently screen titles, abstracts and full texts for inclusion of published literature. One reviewer will screen search results from the grey literature and identify relevant documents for inclusion. Data synthesis will include analysis of the number, type of studies, year and country of publication, a summary of intervention components/service or practice, outcomes addressed, main results (an indicator of effectiveness) and a description of included interventions. ETHICS AND DISSEMINATION: The review will help identify components of care and care pathways for primary care services for stroke. By comparing the results with stroke survivors' and carers' needs identified in the literature, the review will highlight potential gaps in research and practice relevant to long-term care after stroke.

Making models match measurements: model optimization for morphogen patterning networks.

Mathematical modeling of developmental signaling networks has played an increasingly important role in the identification of regulatory mechanisms by providing a sandbox for hypothesis testing and experiment design. Whether these models consist of an equation with a few parameters or dozens of equations with hundreds of parameters, a prerequisite to model-based discovery is to bring simulated behavior into agreement with observed data via parameter estimation. These parameters provide insight into the system (e.g., enzymatic rate constants describe enzyme properties). Depending on the nature of the model fit desired - from qualitative (relative spatial positions of phosphorylation) to quantitative (exact agreement of spatial position and concentration of gene products) - different measures of data-model mismatch are used to estimate different parameter values, which contain different levels of usable information and/or uncertainty. To facilitate the adoption of modeling as a tool for discovery alongside other tools such as genetics, immunostaining, and biochemistry, careful consideration needs to be given to how well a model fits the available data, what the optimized parameter values mean in a biological context, and how the uncertainty in model parameters and predictions plays into experiment design. The core discussion herein pertains to the quantification of model-to-data agreement, which constitutes the first measure of a model's performance and future utility to the problem at hand. Integration of this experimental data and the appropriate choice of objective measures of data-model agreement will continue to drive modeling forward as a tool that contributes to experimental discovery. The Drosophila melanogaster gap gene system, in which model parameters are optimized against in situ immunofluorescence intensities, demonstrates the importance of error quantification, which is applicable to a wide array of developmental modeling studies.

Experiment design through dynamical characterisation of non-linear systems biology models utilising sparse grids.

The sparse grid-based experiment design algorithm sequentially selects an experimental design point to discriminate between hypotheses for given experimental conditions. Sparse grids efficiently screen the global uncertain parameter space to identify acceptable parameter subspaces. Clustering the located acceptable parameter vectors by the similarity of the simulated model trajectories characterises the data-compatible model dynamics. The experiment design algorithm capitalizes on the diversity of the experimentally distinguishable system output dynamics to select the design point that best discerns between competing model-structure and parameter-encoded hypotheses. As opposed to designing the experiments to explicitly reduce uncertainty in the model parameters, this approach selects design points to differentiate between dynamical behaviours. This approach further differs from other experimental design methods in that it simultaneously addresses both parameter- and structural-based uncertainty that is applicable to some ill-posed problems where the number of uncertain parameters exceeds the amount of data, places very few requirements on the model type, available data and a priori parameter estimates, and is performed over the global uncertain parameter space. The experiment design algorithm is demonstrated on a mitogen-activated protein kinase cascade model. The results show that system dynamics are highly uncertain with limited experimental data. Nevertheless, the algorithm requires only three additional experimental data points to simultaneously discriminate between possible model structures and acceptable parameter values. This sparse grid-based experiment design process provides a systematic and computationally efficient exploration over the entire uncertain parameter space of potential model structures to resolve the uncertainty in the non-linear systems biology model dynamics.

How much lung ventilation is obtained with only chest-compression CPR?

The objective of this 14-pig study was designed to determine the amount of lung ventilation obtainable by only rhythmic chest compression (100/min, 100 lbs). Tidal volume (TV), dead space (DS), and respiration rate (R) were measured with normal breathing and with rhythmic chest compression during ventricular fibrillation. The ratio of TV/DS was calculated in both cases. For normal breathing the ratio was 2.54 +/- 0.68; for chest compression breathing the ratio was 0.80 +/- 0.07. Minute alveolar ventilation (TV - DS)R was computed for both cases. With spontaneous breathing, the minute alveolar volume was 5.48 +/- 2.1 l/min. With only chest-compression breathing, the alveolar ventilation was -1.49 +/- 0.64 l/min. The negative minute alveolar volume and fractional ratio reveals that TV was less than the dead space indicating that chest-compression alone does not ventilate the lungs.

Identification of age-structured models: cell cycle phase transitions.

A methodology is developed that determines age-specific transition rates between cell cycle phases during balanced growth by utilizing age-structured population balance equations. Age-distributed models are the simplest way to account for varied behavior of individual cells. However, this simplicity is offset by difficulties in making observations of age distributions, so age-distributed models are difficult to fit to experimental data. Herein, the proposed methodology is implemented to identify an age-structured model for human leukemia cells (Jurkat) based only on measurements of the total number density after the addition of bromodeoxyuridine partitions the total cell population into two subpopulations. Each of the subpopulations will temporarily undergo a period of unbalanced growth, which provides sufficient information to extract age-dependent transition rates, while the total cell population remains in balanced growth. The stipulation of initial balanced growth permits the derivation of age densities based on only age-dependent transition rates. In fitting the experimental data, a flexible transition rate representation, utilizing a series of cubic spline nodes, finds a bimodal G(0)/G(1) transition age probability distribution best fits the experimental data. This resolution may be unnecessary as convex combinations of more restricted transition rates derived from normalized Gaussian, lognormal, or skewed lognormal transition-age probability distributions corroborate the spline predictions, but require fewer parameters. The fit of data with a single log normal distribution is somewhat inferior suggesting the bimodal result as more likely. Regardless of the choice of basis functions, this methodology can identify age distributions, age-specific transition rates, and transition-age distributions during balanced growth conditions.

Comparative study of parameter sensitivity analyses of the TCR-activated Erk-MAPK signalling pathway.

Parameter estimation is a major challenge for mathematical modelling of biological systems. Given the uncertainties associated with model parameters, it is important to understand how sensitive the model output is to variations in parameter values. A local sensitivity analysis determines the model sensitivity to parameter variations over a localised region around the nominal parameter values, whereas a global sensitivity analysis (GSA) investigates the sensitivity over the entire parameter space. Using a T-cell receptor-activated Erk-MAPK signalling pathway model as an example, the authors present a comparative study of a variety of different sensitivity analysis techniques. These techniques include: local sensitivity analysis, existing GSA methods of partial rank correlation coefficient, Sobol's, extended Fourier amplitude sensitivity test, as well as a weighted average of local sensitivities and a new GSA method to extract global parameter sensitivities from a parameter identification routine. Results of this study revealed critical reactions in the signalling pathway and their impact on the signalling dynamics and provided insights into embedded regulatory mechanisms such as feedback loops in the pathway. From this study, a recommendation emerges for a general sensitivity analysis strategy to efficiently and reliably infer quantitative, dynamic as well as topological properties from systems biology models.

Analysis of resonance chemotherapy in leukemia treatment via multi-staged population balance models.

An age-structured population balance model that explicitly models cell cycle phases is developed to investigate the effects of cell cycle specific (CCS) drugs. In particular, the benefits of timing CCS drug treatments in resonance chemotherapy are predicted and measured directly in vitro before evaluating likely in vivo scenarios. The phase transition rates are measured in vitro for the HL60 leukemia cell line and are used to predict the transient phase dynamics after exposure to the S phase specific drug, camptothecin. The phase oscillations predicted by the model are observed experimentally and the timing of a second camptothecin pulse is shown to significantly alter the overall treatment effectiveness. To explore the feasibility of designing resonance chemotherapeutic treatments to preferentially eliminate one cell type over another, Jurkat and HL60 leukemia cells are exposed to the same dual-pulse camptothecin treatment regimen. With the model framework validated for simplified cases, the model is used to extrapolate the effectiveness of resonance chemotherapy considering in vivo effects such as quiescence, drug metabolism, drug properties, and transport considerations that were not included in the in vitro experiments. While resonance chemotherapy is intuitive and looks promising in vitro, when in vivo considerations are included in the model, the phenomenon is dampened and the window of applicability becomes narrower.

Comparison of antibody functionality using different immobilization methods.

This study investigates the influence of antibody immobilization methods on antigen capture. Adsorption and two surface chemistries, an aminosilane chemistry and a common heterobifunctional crosslinker (N-gamma-maleimidobutyryloxy-succinimide ester, GMBS), were compared and evaluated for their ability to immobilize antibodies and capture antigen. The role of protein A as an orienting protein scaffold component in each of these techniques was also evaluated. Through experimentation it was determined that the GMBS technique immobilized the highest amount of antibody and minimized nonspecific binding. For all techniques, the most functional antibodies were found to be those immobilized with protein A. Interestingly, the aminosilane technique demonstrated the highest antigen capture with antibody alone but also exhibited the highest level of nonspecific binding.

The humoral immune response to Haemophilus influenzae type b: a mathematical model based on T-zone and germinal center B-cell dynamics.

Through careful mapping of the physiology of the T-zone and GC B-blast dynamics to a mathematical representation of the cell processes including proliferation, migration, differentiation, and cell death, a mathematical model is constructed to capture the dominant nominal primary, late follicular, and secondary humoral response to Haemophilus influenzae Type b. This model explicitly incorporates the dynamics of memory B-cells, T-zone and GC B-dynamics, IgM and IgG antibodies, avidity maturation, and IC presentation by FDCs into a coherent framework. This paper describes the relevant immunology, the pertinent physiological assumptions, the developed model, and the parameter identification procedure. The model parameters were found using a parameter identification procedure that capitalizes on the timing and interactions of certain dominant physiological attributes. Simulation results and validation tests indicate that the model reflects not only a nominal primary and secondary humoral immune response but also the tertiary and T-independent responses. The model shows robustness to variations in infection dosage, bacterial growth rate (virulence of the strain), and onset-timing of the secondary response. The utility of this model in studying the humoral immune response is demonstrated through suggested physiological assumptions, mechanisms, and rates to be eventually clinically evaluated as well as insights into vaccination design. The model and parameter identification techniques are easily adapted to other diseases which primarily evoke a humoral immune response.

Systematic method for determining intravenous drug treatment strategies aiding the humoral immune response.

This paper delineates a systematic method for determining "optimal" intravenous drug delivery strategies for patients having illnesses that primarily evoke a humoral immune response and are treatable by antibiotics. The method derives from a nonlinear, distributed predator-prey model that captures the dominant antigen and antibody interaction. This model is developed from relevant physiology, past predator-prey-type modeling work, available data, and pertinent parameter identification. Embedding this predator-prey model into a larger class of uncertain systems, by a finite dimensional approximation and a transformation to a linear fractional representation, enables the application of robust control based on linear matrix inequality optimization techniques. The optimization problem is solved by minimizing an upper bound on a measure of the total drug delivered subject to patient recovery (stability to healthy equilibrium state). Specifically, the paper addresses the treatment of Haemophilus influenzae through modeling, controller development, and simulations of infected adult patients subjected to typical and proposed intravenous antibiotic treatments. Through simulations the proposed intravenous drug strategy shortens patient recovery time, lowers peak drug concentrations and decreases the total drug administered when compared to standard antibiotic strategies.

Cancer gene therapy using plasmid DNA: pharmacokinetic study of DNA following injection in mice.

The fate of plasmid DNA complexed with cationic lipids delivered intravenously in mice was evaluated at selected timepoints up to 6 months postinjection. Blood half-life and tissue distribution of plasmid DNA and potential expression in tissues were examined. Southern blot analyses of blood indicated that intact plasmid DNA was rapidly degraded, with a half-life of less than 5 min for intact plasmid, and was no longer detectable at 1 hr postinjection. Southern analyses of tissue demonstrated that intact DNA was differentially retained in the lung, spleen, liver, heart, kidney, marrow, and muscle up to 24 hr postinjection. After 7 days, no intact plasmid DNA was detectable by Southern blot analysis; however, the plasmid was detectable by the polymerase chain reaction (PCR) in all tissues examined at 7 and 28 days postinjection. At 6 months postinjection, femtogram levels of plasmid were detected only in muscle. Immunohistochemical analyses did not detect encoded protein in the tissues harboring residual plasmid at 1 or 7 days postinjection.

Characterization of humoral immunity after DNA injection.

Antibodies to the influenza virus nucleoprotein are produced after injection of a plasmid DNA expression vector containing the nucleoprotein gene. A single injection of 10 to 100 micrograms of DNA produces IgG antibodies which first appear four to six weeks post injection. Antibody titres peak at six to eight weeks and then remain stable in most animals for many months. The antibody response at early times is dose-dependent, with higher amounts of DNA producing a faster immune response as well as higher antibody titres. Titres observed many months after injection are less dependent on DNA dose.

Gene therapy by intramuscular injection of plasmid DNA: studies on firefly luciferase gene expression in mice.

Direct injection of nonviral, covalently closed circular plasmid DNA into muscle results in expression of the DNA in myofiber cells. We have examined the expression of firefly luciferase DNA constructs injected into adult murine skeletal muscle. Considerable variation in luciferase enzyme expression was noted among constructs with different regulatory elements, among different batches of the same DNA construct, and among similar transfection experiments performed at different times. This variation was minimized by using single batches of plasmid DNA and by performing comparable sets of experiments concurrently. A quantitative experimental protocol was defined for comparing various aspects of the transfection process. We report that a luciferase construct containing the human cytomegalovirus immediate-early gene promoter plus intron A (a construct termed "p-CMVint-lux") showed the highest expression among several constructs tested. Dose-response and time course analyses of p-CMVint-lux DNA injections showed that maximal luciferase expression was achieved with 25 micrograms of DNA at 7-14 days post-injection. Selected manipulations of the transfection process were examined for their influence on luciferase expression. Variations in the rate of DNA injection, needle size, injection volume, and vehicle temperature had no significant effect on luciferase expression. The presence of endotoxin, cationic peptide, muscle stimulants or relaxants, vasoconstrictors, metal chelators, or lysosomal lytic reagents had no significant effect on expression. However, linearization of the DNA, injection of the DNA in water rather than saline, or inclusion of a DNA intercalating agent nearly abolished luciferase expression. And finally, increasing the injection dose by giving multiple injections over a 10-day period increased expression proportionally to the number of injections.

Analysis of a transformed cell line using antisense c-fos RNA.

Simian sarcoma virus (SSV)-infected NIH-3T3 cells (SSV-NIH-3T3), express a homologue of platelet-derived growth factor, (PDGF) a powerful inducer of the c-fos gene. We have used these cells to test the hypothesis that autocrine stimulation by PDGF-like molecules leads to c-fos expression which is functional in the transformed phenotype. We have transfected SSV-NIH-3T3 cells with a c-fos antisense-RNA expression vector, pSVsof, or control plasmids. pSVsof-transfected cells exhibit markedly decreased c-fos mRNA and protein levels, restored density-dependent growth arrest and reduced (three of five clones) tumorigenicity compared to control lines. The results confirm that c-fos cooperates in the transformed phenotype of SSV-NIH-3T3 cells.

Expression of c-fos antisense RNA inhibits the differentiation of F9 cells to parietal endoderm.

To test the putative role of c-fos in F9 differentiation, we have attempted to inhibit c-fos expression in these cells using an SV40-based expression vector (pSVneo-sof) that programs expression of c-fos antisense (sof) sequences as a 3' extension of a neo mRNA transcript. Of six G418-resistant clones isolated in transfection experiments, five expressed neo-sof transcripts. Two clones synthesized polyadenylated mRNA of the expected size (3.8 kb), two were smaller than expected, and one was larger. Two clones that expressed reduced levels of c-fos protein were inhibited in the induction of laminin, type IV collagen, and proteoglycan-19 RNA transcripts measured after 4 days of differentiation induction with RA and dibutyryl cyclic AMP. Also inhibited was the induction of the differentiation markers, TROMA-1 and TROMA-3. Antisense-expressing cells were not inhibited in the differentiation pathway to visceral endoderm since the alpha-fetoprotein gene was activated normally. We conclude that c-fos antisense expression inhibits some aspects of differentiation in F9 cells.

Antisense RNA to the c-fos gene: restoration of density-dependent growth arrest in a transformed cell line.

Fibroblasts transformed by v-sis have elevated levels of c-fos relative to non-transformed controls. Transfection and integration of plasmids directing the synthesis of antisense RNA to the c-fos gene leads to restoration of density-dependent growth arrest in monolayer culture, but does not inhibit colony formation in soft agar.