Cumulative subgroup analysis to reduce waste in clinical research for individualised medicine

Background: Although subgroup analyses in clinical trials may provide evidence for individualised medicine, their conduct and interpretation remain controversial. Methods: Subgroup effect can be defined as the difference in treatment effect across patient subgroups. Cumulative subgroup analysis refers to a series of repeated pooling of subgroup effects after adding data from each of related trials chronologically, to investigate the accumulating evidence for subgroup effects. We illustrated the clinical relevance of cumulative subgroup analysis in two case studies using data from published individual patient data (IPD) meta-analyses. Computer simulations were also conducted to examine the statistical properties of cumulative subgroup analysis. Results: In case study 1, an IPD meta-analysis of 10 randomised trials (RCTs) on beta blockers for heart failure reported significant interaction of treatment effects with baseline rhythm. Cumulative subgroup analysis could have detected the subgroup effect 15 years earlier, with five fewer trials and 71% less patients, than the IPD meta-analysis which first reported it. Case study 2 involved an IPD meta-analysis of 11 RCTs on treatments for pulmonary arterial hypertension that reported significant subgroup effect by aetiology. Cumulative subgroup analysis could have detected the subgroup effect 6 years earlier, with three fewer trials and 40% less patients than the IPD meta-analysis. Computer simulations have indicated that cumulative subgroup analysis increases the statistical power and is not associated with inflated false positives. Conclusions: To reduce waste of research data, subgroup analyses in clinical trials should be more widely conducted and adequately reported so that cumulative subgroup analyses could be timely performed to inform clinical practice and further research

A Minimal Model of Metabolism Based Chemotaxis

Since the pioneering work by Julius Adler in the 1960's, bacterial chemotaxis has been predominantly studied as metabolism-independent. All available simulation models of bacterial chemotaxis endorse this assumption. Recent studies have shown, however, that many metabolism-dependent chemotactic patterns occur in bacteria. We hereby present the simplest artificial protocell model capable of performing metabolism-based chemotaxis. The model serves as a proof of concept to show how even the simplest metabolism can sustain chemotactic patterns of varying sophistication. It also reproduces a set of phenomena that have recently attracted attention on bacterial chemotaxis and provides insights about alternative mechanisms that could instantiate them. We conclude that relaxing the metabolism-independent assumption provides important theoretical advances, forces us to rethink some established pre-conceptions and may help us better understand unexplored and poorly understood aspects of bacterial chemotaxis

Novel Methods for Analysing Bacterial Tracks Reveal Persistence in Rhodobacter sphaeroides

Tracking bacteria using video microscopy is a powerful experimental approach to probe their motile behaviour. The trajectories obtained contain much information relating to the complex patterns of bacterial motility. However, methods for the quantitative analysis of such data are limited. Most swimming bacteria move in approximately straight lines, interspersed with random reorientation phases. It is therefore necessary to segment observed tracks into swimming and reorientation phases to extract useful statistics. We present novel robust analysis tools to discern these two phases in tracks. Our methods comprise a simple and effective protocol for removing spurious tracks from tracking datasets, followed by analysis based on a two-state hidden Markov model, taking advantage of the availability of mutant strains that exhibit swimming-only or reorientating-only motion to generate an empirical prior distribution. Using simulated tracks with varying levels of added noise, we validate our methods and compare them with an existing heuristic method. To our knowledge this is the first example of a systematic assessment of analysis methods in this field. The new methods are substantially more robust to noise and introduce less systematic bias than the heuristic method. We apply our methods to tracks obtained from the bacterial species Rhodobacter sphaeroides and Escherichia coli. Our results demonstrate that R. sphaeroides exhibits persistence over the course of a tumbling event, which is a novel result with important implications in the study of this and similar species

Engineering an aldehyde dehydrogenase toward its substrates, 3-hydroxypropanal and NAD(+), for enhancing the production of 3-hydroxypropionic acid

3-Hydroxypropionic acid (3-HP) can be produced via the biological route involving two enzymatic reactions: dehydration of glycerol to 3-hydroxypropanal (3-HPA) and then oxidation to 3-HP. However, commercial production of 3-HP using recombinant microorganisms has been hampered with several problems, some of which are associated with the toxicity of 3-HPA and the efficiency of NAD(+) regeneration. We engineered a-ketoglutaric semialdehyde dehydrogenase (KGSADH) from Azospirillum brasilense for the second reaction to address these issues. The residues in the binding sites for the substrates, 3-HPA and NAD(+), were randomized, and the resulting libraries were screened for higher activity. Isolated KGSADH variants had significantly lower Km values for both the substrates. The enzymes also showed higher substrate specificities for aldehyde and NAD(+), less inhibition by NADH, and greater resistance to inactivation by 3-HPA than the wild-type enzyme. A recombinant Pseudomonas denitrificans strain with one of the engineered KGSADH variants exhibited less accumulation of 3-HPA, decreased levels of inactivation of the enzymes, and higher cell growth than that with the wild-type KGSADH. The flask culture of the P. denitrificans strain with the mutant KGSADH resulted in about 40% increase of 3-HP titer (53 mM) compared with that using the wild-type enzyme (37 mM)

2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

S

Evolution of Taxis Responses in Virtual Bacteria: Non-Adaptive Dynamics

Bacteria are able to sense and respond to a variety of external stimuli, with responses that vary from stimuli to stimuli and from species to species. The best-understood is chemotaxis in the model organism Escherichia coli, where the dynamics and the structure of the underlying pathway are well characterised. It is not clear, however, how well this detailed knowledge applies to mechanisms mediating responses to other stimuli or to pathways in other species. Furthermore, there is increasing experimental evidence that bacteria integrate responses from different stimuli to generate a coherent taxis response. We currently lack a full understanding of the different pathway structures and dynamics and how this integration is achieved. In order to explore different pathway structures and dynamics that can underlie taxis responses in bacteria, we perform a computational simulation of the evolution of taxis. This approach starts with a population of virtual bacteria that move in a virtual environment based on the dynamics of the simple biochemical pathways they harbour. As mutations lead to changes in pathway structure and dynamics, bacteria better able to localise with favourable conditions gain a selective advantage. We find that a certain dynamics evolves consistently under different model assumptions and environments. These dynamics, which we call non-adaptive dynamics, directly couple tumbling probability of the cell to increasing stimuli. Dynamics that are adaptive under a wide range of conditions, as seen in the chemotaxis pathway of E. coli, do not evolve in these evolutionary simulations. However, we find that stimulus scarcity and fluctuations during evolution results in complex pathway dynamics that result both in adaptive and non-adaptive dynamics depending on basal stimuli levels. Further analyses of evolved pathway structures show that effective taxis dynamics can be mediated with as few as two components. The non-adaptive dynamics mediating taxis responses provide an explanation for experimental observations made in mutant strains of E. coli and in wild-type Rhodobacter sphaeroides that could not be explained with standard models. We speculate that such dynamics exist in other bacteria as well and play a role linking the metabolic state of the cell and the taxis response. The simplicity of mechanisms mediating such dynamics makes them a candidate precursor of more complex taxis responses involving adaptation. This study suggests a strong link between stimulus conditions during evolution and evolved pathway dynamics. When evolution was simulated under conditions of scarce and fluctuating stimulus conditions, the evolved pathway contained features of both adaptive and non-adaptive dynamics, suggesting that these two types of dynamics can have different advantages under distinct environmental circumstances

An Essential Difference between the Flavonoids MonoHER and Quercetin in Their Interplay with the Endogenous Antioxidant Network

Antioxidants can scavenge highly reactive radicals. As a result the antioxidants are converted into oxidation products that might cause damage to vital cellular components. To prevent this damage, the human body possesses an intricate network of antioxidants that pass over the reactivity from one antioxidant to another in a controlled way. The aim of the present study was to investigate how the semi-synthetic flavonoid 7-mono-O-(β-hydroxyethyl)-rutoside (monoHER), a potential protective agent against doxorubicin-induced cardiotoxicity, fits into this antioxidant network. This position was compared with that of the well-known flavonoid quercetin. The present study shows that the oxidation products of both monoHER and quercetin are reactive towards thiol groups of both GSH and proteins. However, in human blood plasma, oxidized quercetin easily reacts with protein thiols, whereas oxidized monoHER does not react with plasma protein thiols. Our results indicate that this can be explained by the presence of ascorbate in plasma; ascorbate is able to reduce oxidized monoHER to the parent compound monoHER before oxidized monoHER can react with thiols. This is a major difference with oxidized quercetin that preferentially reacts with thiols rather than ascorbate. The difference in selectivity between monoHER and quercetin originates from an intrinsic difference in the chemical nature of their oxidation products, which was corroborated by molecular quantum chemical calculations. These findings point towards an essential difference between structurally closely related flavonoids in their interplay with the endogenous antioxidant network. The advantage of monoHER is that it can safely channel the reactivity of radicals into the antioxidant network where the reactivity is completely neutralized

Medulloblastoma outcome is adversely associated with overexpression of EEF1D, RPL30, and RPS20 on the long arm of chromosome 8

BACKGROUND: Medulloblastoma is the most common malignant brain tumor of childhood. Improvements in clinical outcome require a better understanding of the genetic alterations to identify clinically significant biological factors and to stratify patients accordingly. In the present study, we applied cytogenetic characterization to guide the identification of biologically significant genes from gene expression microarray profiles of medulloblastoma. METHODS: We analyzed 71 primary medulloblastomas for chromosomal copy number aberrations (CNAs) using comparative genomic hybridization (CGH). Among 64 tumors that we previously analyzed by gene expression microarrays, 27 were included in our CGH series. We analyzed clinical outcome with respect to CNAs and microarray results. We filtered microarray data using specific CNAs to detect differentially expressed candidate genes associated with survival. RESULTS: The most frequent lesions detected in our series involved chromosome 17; loss of 16q, 10q, or 8p; and gain of 7q or 2p. Recurrent amplifications at 2p23-p24, 2q14, 7q34, and 12p13 were also observed. Gain of 8q is associated with worse overall survival (p = 0.0141), which is not entirely attributable to MYC amplification or overexpression. By applying CGH results to gene expression analysis of medulloblastoma, we identified three 8q-mapped genes that are associated with overall survival in the larger group of 64 patients (p < 0.05): eukaryotic translation elongation factor 1D (EEF1D), ribosomal protein L30 (RPL30), and ribosomal protein S20 (RPS20). CONCLUSION: The complementary use of CGH and expression profiles can facilitate the identification of clinically significant candidate genes involved in medulloblastoma growth. We demonstrate that gain of 8q and expression levels of three 8q-mapped candidate genes (EEF1D, RPL30, RPS20) are associated with adverse outcome in medulloblastoma

Evolution of response dynamics underlying bacterial chemotaxis

© 2011 Soyer and Goldstein; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: The ability to predict the function and structure of complex molecular mechanisms underlying cellular behaviour is one of the main aims of systems biology. To achieve it, we need to understand the evolutionary routes leading to a specific response dynamics that can underlie a given function and how biophysical and environmental factors affect which route is taken. Here, we apply such an evolutionary approach to the bacterial chemotaxis pathway, which is documented to display considerable complexity and diversity.Results: We construct evolutionarily accessible response dynamics starting from a linear response to absolute levels of attractant, to those observed in current-day Escherichia coli. We explicitly consider bacterial movement as a two-state process composed of non-instantaneous tumbling and swimming modes. We find that a linear response to attractant results in significant chemotaxis when sensitivity to attractant is low and when time spent tumbling is large. More importantly, such linear response is optimal in a regime where signalling has low sensitivity. As sensitivity increases, an adaptive response as seen in Escherichia coli becomes optimal and leads to 'perfect' chemotaxis with a low tumbling time. We find that as tumbling time decreases and sensitivity increases, there exist a parameter regime where the chemotaxis performance of the linear and adaptive responses overlap, suggesting that evolution of chemotaxis responses might provide an example for the principle of functional change in structural continuity.Conclusions: Our findings explain several results from diverse bacteria and lead to testable predictions regarding chemotaxis responses evolved in bacteria living under different biophysical constraints and with specific motility machinery. Further, they shed light on the potential evolutionary paths for the evolution of complex behaviours from simpler ones in incremental fashion

Phase II Trial of Concurrent Sunitinib and Image-Guided Radiotherapy for Oligometastases

BACKGROUND: Preclinical data suggest that sunitinib enhances the efficacy of radiotherapy. We tested the combination of sunitinib and hypofractionated image-guided radiotherapy (IGRT) in a cohort of patients with historically incurable distant metastases. METHODS: Twenty five patients with oligometastases, defined as 1-5 sites of active disease on whole body imaging, were enrolled in a phase II trial from 2/08 to 9/10. The most common tumor types treated were head and neck, liver, lung, kidney and prostate cancers. Patients were treated with the recommended phase II dose of 37.5 mg daily sunitinib (days 1-28) and IGRT 50 Gy (days 8-12 and 15-19). Maintenance sunitinib was used in 33% of patients. Median follow up was 17.5 months (range, 0.7 to 37.4 months). RESULTS: The 18-month local control, distant control, progression-free survival (PFS) and overall survival (OS) were 75%, 52%, 56% and 71%, respectively. At last follow-up, 11 (44%) patients were alive without evidence of disease, 7 (28%) were alive with distant metastases, 3 (12%) were dead from distant metastases, 3 (12%) were dead from comorbid illness, and 1 (4%) was dead from treatment-related toxicities. The incidence of acute grade ≥ 3 toxicities was 28%, most commonly myelosuppression, bleeding and abnormal liver function tests. CONCLUSIONS: Concurrent sunitinib and IGRT achieves major clinical responses in a subset of patients with oligometastases. TRIAL REGISTRATION: ClinicalTrials.gov NCT00463060