Management of secondary poor response to botulinum toxin in cervical dystonia: a multicentre audit

Background: Botulinum toxin A (BoNT‐A) is an effective treatment for cervical dystonia. Nevertheless, up to 30‐40% patients discontinue treatment, often due to poor response. The British Neurotoxin Network (BNN) recently published guidelines on the management of poor response to BoNT‐A in cervical dystonia, but adherence to these has not yet been assessed. Objectives: To assess adherence to and usefulness of BNN guidelines in clinical practice. Methods: We undertook a retrospective medical notes audit of adherence to the BNN guidelines in three U.K. tertiary neurosciences centres. Results: Out of 76 patients identified with poor response, 42 (55%) had a suboptimal response and, following BNN recommendations, 25 of them (60%) responded to adjustments in BoNT dose, muscle selection or injection technique. Of the remaining 34 (45%) patients with no BoNT response, 20 (59%) were tested for immune resistance, 8 [40%] of whom showed resistance. 14 (18%) of all patients were switched to BoNT‐B, and 27 (36%) were referred for deep brain stimulation surgery. In those not immune to BoNT‐A, clinical improvement was seen in 5 (41%) after adjusting their dose and injection technique. Conclusion: Our audit shows that optimizing BoNT dose or injection strategy largely led to improvements in those with suboptimal response and in those reporting no response without resistance. It would be helpful to standardize investigations of potential resistance in those with no therapeutic response

Evolution of the hypoxia-sensitive cells involved in amniote respiratory reflexes

The evolutionary origins of the hypoxia-sensitive cells that trigger amniote respiratory reflexes – carotid body glomus cells, and ‘pulmonary neuroendocrine cells’ (PNECs) - are obscure. Homology has been proposed between glomus cells, which are neural crest-derived, and the hypoxia-sensitive ‘neuroepithelial cells’ (NECs) of fish gills, whose embryonic origin is unknown. NECs have also been likened to PNECs, which differentiate in situ within lung airway epithelia. Using genetic lineage-tracing and neural crest-deficient mutants in zebrafish, and physical fate-mapping in frog and lamprey, we find that NECs are not neural crest-derived, but endoderm-derived, like PNECs, whose endodermal origin we confirm. We discover neural crest-derived catecholaminergic cells associated with zebrafish pharyngeal arch blood vessels, and propose a new model for amniote hypoxia-sensitive cell evolution: endoderm-derived NECs were retained as PNECs, while the carotid body evolved via the aggregation of neural crest-derived catecholaminergic (chromaffin) cells already associated with blood vessels in anamniote pharyngeal arches

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Stimulation of Na⁺/H⁺ Exchanger Isoform 1 Promotes Microglial Migration

Regulation of microglial migration is not well understood. In this study, we proposed that Na+/H+ exchanger isoform 1 (NHE-1) is important in microglial migration. NHE-1 protein was co-localized with cytoskeletal protein ezrin in lamellipodia of microglia and maintained its more alkaline intracellular pH (pHi). Chemoattractant bradykinin (BK) stimulated microglial migration by increasing lamellipodial area and protrusion rate, but reducing lamellipodial persistence time. Interestingly, blocking NHE-1 activity with its potent inhibitor HOE 642 not only acidified microglia, abolished the BK-triggered dynamic changes of lamellipodia, but also reduced microglial motility and microchemotaxis in response to BK. In addition, NHE-1 activation resulted in intracellular Na+ loading as well as intracellular Ca2+ elevation mediated by stimulating reverse mode operation of Na+/Ca2+ exchange (NCXrev). Taken together, our study shows that NHE-1 protein is abundantly expressed in microglial lamellipodia and maintains alkaline pHi in response to BK stimulation. In addition, NHE-1 and NCXrev play a concerted role in BK-induced microglial migration via Na+ and Ca2+ signaling. © 2013 Shi et al

Multiway modeling and analysis in stem cell systems biology

<p>Abstract</p> <p>Background</p> <p>Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.). A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models) can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells.</p> <p>Results</p> <p>We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC) models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a collagen I substrate accelerated the osteogenic differentiation induced by a static collagen I substrate.</p> <p>Conclusion</p> <p>Our results suggest gene- and protein-level models whereby stem cells undergo transdifferentiation to osteoblasts, and lay the foundation for mechanistic, hypothesis-driven studies. Our analysis methods are applicable to a wide range of stem cell differentiation models.</p

Accurate masses and radii of normal stars: modern results and applications

This paper presents and discusses a critical compilation of accurate, fundamental determinations of stellar masses and radii. We have identified 95 detached binary systems containing 190 stars (94 eclipsing systems, and alpha Centauri) that satisfy our criterion that the mass and radius of both stars be known to 3% or better. To these we add interstellar reddening, effective temperature, metal abundance, rotational velocity and apsidal motion determinations when available, and we compute a number of other physical parameters, notably luminosity and distance. We discuss the use of this information for testing models of stellar evolution. The amount and quality of the data also allow us to analyse the tidal evolution of the systems in considerable depth, testing prescriptions of rotational synchronisation and orbital circularisation in greater detail than possible before. The new data also enable us to derive empirical calibrations of M and R for single (post-) main-sequence stars above 0.6 M(Sun). Simple, polynomial functions of T(eff), log g and [Fe/H] yield M and R with errors of 6% and 3%, respectively. Excellent agreement is found with independent determinations for host stars of transiting extrasolar planets, and good agreement with determinations of M and R from stellar models as constrained by trigonometric parallaxes and spectroscopic values of T(eff) and [Fe/H]. Finally, we list a set of 23 interferometric binaries with masses known to better than 3%, but without fundamental radius determinations (except alpha Aur). We discuss the prospects for improving these and other stellar parameters in the near future.Comment: 56 pages including figures and tables. To appear in The Astronomy and Astrophysics Review. Ascii versions of the tables will appear in the online version of the articl

Evolution of the hypoxia-sensitive cells involved in amniote respiratory reflexes

The evolutionary origins of the hypoxia-sensitive cells that trigger amniote respiratory reflexes - carotid body glomus cells, and 'pulmonary neuroendocrine cells' (PNECs) - are obscure. Homology has been proposed between glomus cells, which are neural crest-derived, and the hypoxia-sensitive 'neuroepithelial cells' (NECs) of fish gills, whose embryonic origin is unknown. NECs have also been likened to PNECs, which differentiate in situ within lung airway epithelia. Using genetic lineage-tracing and neural crest-deficient mutants in zebrafish, and physical fate-mapping in frog and lamprey, we find that NECs are not neural crest-derived, but endoderm-derived, like PNECs, whose endodermal origin we confirm. We discover neural crest-derived catecholaminergic cells associated with zebrafish pharyngeal arch blood vessels, and propose a new model for amniote hypoxia-sensitive cell evolution: endoderm-derived NECs were retained as PNECs, while the carotid body evolved via the aggregation of neural crest-derived catecholaminergic (chromaffin) cells already associated with blood vessels in anamniote pharyngeal arches.This work was funded by the Wellcome Trust (Ph.D. Studentship 086804/Z/08/Z to DH; Senior Investigator Award 102889/Z/13/Z to AST), the NIDCR/NIH (R21-DE021509 to SF; R01-DE018477 to EWK), the NIDDK/NIH (1DP2DK098092 to PDSD), the NIH (R01-HL092217 to EWK), the Zebrafish Initiative of the Vanderbilt University Academic Venture Capital Fund (to EWK), the Vanderbilt International Scholar Program (to GU), the HFSP (Long-Term Fellowship to CM) and the Swiss National Science Foundation (Advanced Postdoctoral Fellowship and Professorship to CM). For further information, please visit the publisher's website