Toll-like receptor signaling adapter proteins govern spread of neuropathic pain and recovery following nerve injury in male mice.

BackgroundSpinal Toll-like receptors (TLRs) and signaling intermediaries have been implicated in persistent pain states. We examined the roles of two major TLR signaling pathways and selected TLRs in a mononeuropathic allodynia.MethodsL5 spinal nerve ligation (SNL) was performed in wild type (WT, C57BL/6) male and female mice and in male Tlr2-/-Tlr3-/-, Tlr4-/-, Tlr5-/-, Myd88-/-, Triflps2, Myd88/Triflps2, Tnf-/-, and Ifnar1-/- mice. We also examined L5 ligation in Tlr4-/- female mice. We examined tactile allodynia using von Frey hairs. Iba-1 (microglia) and GFAP (astrocytes) were assessed in spinal cords by immunostaining. Tactile thresholds were analyzed by 1- and 2-way ANOVA and the Bonferroni post hoc test was used.ResultsIn WT male and female mice, SNL lesions resulted in a persistent and robust ipsilateral, tactile allodynia. In males with TLR2, 3, 4, or 5 deficiencies, tactile allodynia was significantly, but incompletely, reversed (approximately 50%) as compared to WT. This effect was not seen in female Tlr4-/- mice. Increases in ipsilateral lumbar Iba-1 and GFAP were seen in mutant and WT mice. Mice deficient in MyD88, or MyD88 and TRIF, showed an approximately 50% reduction in withdrawal thresholds and reduced ipsilateral Iba-1. In contrast, TRIF and interferon receptor null mice developed a profound ipsilateral and contralateral tactile allodynia. In lumbar sections of the spinal cords, we observed a greater increase in Iba-1 immunoreactivity in the TRIF-signaling deficient mice as compared to WT, but no significant increase in GFAP. Removing MyD88 abrogated the contralateral allodynia in the TRIF signaling-deficient mice. Conversely, IFNβ, released downstream to TRIF signaling, administered intrathecally, temporarily reversed the tactile allodynia.ConclusionsThese observations suggest a critical role for the MyD88 pathway in initiating neuropathic pain, but a distinct role for the TRIF pathway and interferon in regulating neuropathic pain phenotypes in male mice

Early identification of first-year students at risk of dropping out of high-school entry medical school: the usefulness of teachers' ratings of class participation

Dropping out from undergraduate medical education is costly for students, medical schools, and society in general. Therefore, the early identification of potential dropout students is important. The contribution of personal features to dropout rates has merited exploration. However, there is a paucity of research on aspects of student experience that may lead to dropping out. In this study, underpinned by theoretical models of student commitment, involvement, and engagement, we explored the hypothesis of using inferior participation as an indicator of a higher probability of dropping out in year 1. Class participation was calculated as an aggregate score based on teachers' daily observations in class. The study used a longitudinal dataset of six cohorts of high-school entry students (N = 709, 67% females) in one medical school with an annual intake of 120 students. The findings confirmed the initial hypothesis and showed that lower scores of class participation in year 1 added predictive ability to pre-entry characteristics (Pseudo-R2 raised from 0.22 to 0.28). Even though the inclusion of course failure in year 1 resulted in higher explanatory power than participation in class (Pseudo-R2 raised from 0.28 to 0.63), ratings of class participation may be advantageous to anticipate dropout identification, as those can be collected prior to course failure. The implications for practice are that teachers' ratings of class participation can play a role in indicating medical students who may eventually drop out. We conclude that the scores of class participation can contribute to flagging systems for the early detection of student dropouts.(undefined)info:eu-repo/semantics/acceptedVersio

Method validation and preliminary qualification of pharmacodynamic biomarkers employed to evaluate the clinical efficacy of an antisense compound (AEG35156) targeted to the X-linked inhibitor of apoptosis protein XIAP

Data are presented on pharmacodynamic (PD) method validation and preliminary clinical qualification of three PD biomarker assays. M65 Elisa, which quantitates different forms of circulating cytokeratin 18 (CK18) as putative surrogate markers of both apoptotic and nonapoptotic tumour cell death, was shown to be highly reproducible: calibration curve linearity r2=0.996, mean accuracy >91% and mean precision <3%, n=27. Employing recombinant (r) CK18 and caspase cleaved CK18 (CK18 Asp396 neo-epitope) as external standards, kit to kit reproducibly was <6% (n=19). rCK18 was stable in plasma for 4 months at −20°C and −80°C, for 4 weeks at 4°C and had a half-life of 2.3 days at 37°C. Cytokeratin 18 Asp396 NE, the M30 Apoptosense Elisa assay antigen, was stable in plasma for 6 months at −20°C and −80°C, for 3 months at 4°C, while its half-life at 37°C was 3.8 days. Within-day variations in endogenous plasma concentrations of the M30 and M65 antigens were assessed in two predose blood samples collected from a cohort of 15 ovarian cancer patients receiving carboplatin chemotherapy and were shown to be no greater than the variability associated with methods themselves. Between-day fluctuations in circulating levels of the M30 and M65 antigens and in XIAP mRNA levels measured in peripheral blood mononuclear cells by quantitative (q) RT–PCR were evaluated in two predose blood samples collected with a 5- to 7-day gap from 23 patients with advanced cancer enrolled in a phase I trial. The mean variation between the two pretreatment values ranged from 13 to 14 to 25%, respectively, for M65, M30 and qRT–PCR. These data suggest that the M30 and M65 Elisa's and qRT–PCR as PD biomarker assays have favourable performance characteristics for further investigation in clinical trials of anticancer agents which induce tumour apoptosis/necrosis or knockdown of the anti-apoptotic protein XIAP

Statistical Techniques Complement UML When Developing Domain Models of Complex Dynamical Biosystems

Computational modelling and simulation is increasingly being used to complement traditional wet-lab techniques when investigating the mechanistic behaviours of complex biological systems. In order to ensure computational models are fit for purpose, it is essential that the abstracted view of biology captured in the computational model, is clearly and unambiguously defined within a conceptual model of the biological domain (a domain model), that acts to accurately represent the biological system and to document the functional requirements for the resultant computational model. We present a domain model of the IL-1 stimulated NF-κB signalling pathway, which unambiguously defines the spatial, temporal and stochastic requirements for our future computational model. Through the development of this model, we observe that, in isolation, UML is not sufficient for the purpose of creating a domain model, and that a number of descriptive and multivariate statistical techniques provide complementary perspectives, in particular when modelling the heterogeneity of dynamics at the single-cell level. We believe this approach of using UML to define the structure and interactions within a complex system, along with statistics to define the stochastic and dynamic nature of complex systems, is crucial for ensuring that conceptual models of complex dynamical biosystems, which are developed using UML, are fit for purpose, and unambiguously define the functional requirements for the resultant computational model

The regulation of IL-10 expression

Interleukin (IL)-10 is an important immunoregulatory cytokine and an understanding of how IL-10 expression is controlled is critical in the design of immune intervention strategies. IL-10 is produced by almost all cell types within the innate (including macrophages, monocytes, dendritic cells (DCs), mast cells, neutrophils, eosinophils and natural killer cells) and adaptive (including CD4(+) T cells, CD8(+) T cells and B cells) immune systems. The mechanisms of IL-10 regulation operate at several stages including chromatin remodelling at the Il10 locus, transcriptional regulation of Il10 expression and post-transcriptional regulation of Il10 mRNA. In addition, whereas some aspects of Il10 gene regulation are conserved between different immune cell types, several are cell type- or stimulus-specific. Here, we outline the complexity of IL-10 production by discussing what is known about its regulation in macrophages, monocytes, DCs and CD4(+) T helper cells