A guide to group effective connectivity analysis, part 2: Second level analysis with PEB

This paper provides a worked example of using Dynamic Causal Modelling (DCM) and Parametric Empirical Bayes (PEB) to characterise inter-subject variability in neural circuitry (effective connectivity). It steps through an analysis in detail and provides a tutorial style explanation of the underlying theory and assumptions (i.e, priors). The analysis procedure involves specifying a hierarchical model with two or more levels. At the first level, state space models (DCMs) are used to infer the effective connectivity that best explains a subject's neuroimaging timeseries (e.g. fMRI, MEG, EEG). Subject-specific connectivity parameters are then taken to the group level, where they are modelled using a General Linear Model (GLM) that partitions between-subject variability into designed effects and additive random effects. The ensuing (Bayesian) hierarchical model conveys both the estimated connection strengths and their uncertainty (i.e., posterior covariance) from the subject to the group level; enabling hypotheses to be tested about the commonalities and differences across subjects. This approach can also finesse parameter estimation at the subject level, by using the group-level parameters as empirical priors. The preliminary first level (subject specific) DCM for fMRI analysis is covered in a companion paper. Here, we detail group-level analysis procedures that are suitable for use with data from any neuroimaging modality. This paper is accompanied by an example dataset, together with step-by-step instructions demonstrating how to reproduce the analyses

MEG Can Map Short and Long-Term Changes in Brain Activity following Deep Brain Stimulation for Chronic Pain

Deep brain stimulation (DBS) has been shown to be clinically effective for some forms of treatment-resistant chronic pain, but the precise mechanisms of action are not well understood. Here, we present an analysis of magnetoencephalography (MEG) data from a patient with whole-body chronic pain, in order to investigate changes in neural activity induced by DBS for pain relief over both short- and long-term. This patient is one of the few cases treated using DBS of the anterior cingulate cortex (ACC). We demonstrate that a novel method, null-beamforming, can be used to localise accurately brain activity despite the artefacts caused by the presence of DBS electrodes and stimulus pulses. The accuracy of our source localisation was verified by correlating the predicted DBS electrode positions with their actual positions. Using this beamforming method, we examined changes in whole-brain activity comparing pain relief achieved with deep brain stimulation (DBS ON) and compared with pain experienced with no stimulation (DBS OFF). We found significant changes in activity in pain-related regions including the pre-supplementary motor area, brainstem (periaqueductal gray) and dissociable parts of caudal and rostral ACC. In particular, when the patient reported experiencing pain, there was increased activity in different regions of ACC compared to when he experienced pain relief. We were also able to demonstrate long-term functional brain changes as a result of continuous DBS over one year, leading to specific changes in the activity in dissociable regions of caudal and rostral ACC. These results broaden our understanding of the underlying mechanisms of DBS in the human brain

A Linear Model for Transcription Factor Binding Affinity Prediction in Protein Binding Microarrays

Protein binding microarrays (PBM) are a high throughput technology used to characterize protein-DNA binding. The arrays measure a protein's affinity toward thousands of double-stranded DNA sequences at once, producing a comprehensive binding specificity catalog. We present a linear model for predicting the binding affinity of a protein toward DNA sequences based on PBM data. Our model represents the measured intensity of an individual probe as a sum of the binding affinity contributions of the probe's subsequences. These subsequences characterize a DNA binding motif and can be used to predict the intensity of protein binding against arbitrary DNA sequences. Our method was the best performer in the Dialogue for Reverse Engineering Assessments and Methods 5 (DREAM5) transcription factor/DNA motif recognition challenge. For the DREAM5 bonus challenge, we also developed an approach for the identification of transcription factors based on their PBM binding profiles. Our approach for TF identification achieved the best performance in the bonus challenge

BID-F1 and BID-F2 Domains of Bartonella henselae Effector Protein BepF Trigger Together with BepC the Formation of Invasome Structures

The gram-negative, zoonotic pathogen Bartonella henselae (Bhe) translocates seven distinct Bartonella effector proteins (Beps) via the VirB/VirD4 type IV secretion system (T4SS) into human cells, thereby interfering with host cell signaling [1], [2]. In particular, the effector protein BepG alone or the combination of effector proteins BepC and BepF trigger massive F-actin rearrangements that lead to the establishment of invasome structures eventually resulting in the internalization of entire Bhe aggregates [2], [3]. In this report, we investigate the molecular function of the effector protein BepF in the eukaryotic host cell. We show that the N-terminal [E/T]PLYAT tyrosine phosphorylation motifs of BepF get phosphorylated upon translocation but do not contribute to invasome-mediated Bhe uptake. In contrast, we found that two of the three BID domains of BepF are capable to trigger invasome formation together with BepC, while a mutation of the WxxxE motif of the BID-F1 domain inhibited its ability to contribute to the formation of invasome structures. Next, we show that BepF function during invasome formation can be replaced by the over-expression of constitutive-active Rho GTPases Rac1 or Cdc42. Finally we demonstrate that BID-F1 and BID-F2 domains promote the formation of filopodia-like extensions in NIH 3T3 and HeLa cells as well as membrane protrusions in HeLa cells, suggesting a role for BepF in Rac1 and Cdc42 activation during the process of invasome formation

Pan-RAF and MEK vertical inhibition enhances therapeutic response in non-V600 BRAF mutant cells

BACKGROUND: Currently, there are no available targeted therapy options for non-V600 BRAF mutated tumors. The aim of this study was to investigate the effects of RAF and MEK concurrent inhibition on tumor growth, migration, signaling and apoptosis induction in preclinical models of non-V600 BRAF mutant tumor cell lines. METHODS: Six BRAF mutated human tumor cell lines CRL5885 (G466 V), WM3629 (D594G), WM3670 (G469E), MDAMB231 (G464 V), CRL5922 (L597 V) and A375 (V600E as control) were investigated. Pan-RAF inhibitor (sorafenib or AZ628) and MEK inhibitor (selumetinib) or their combination were used in in vitro viability, video microscopy, immunoblot, cell cycle and TUNEL assays. The in vivo effects of the drugs were assessed in an orthotopic NSG mouse breast cancer model. RESULTS: All cell lines showed a significant growth inhibition with synergism in the sorafenib/AZ628 and selumetinib combination. Combination treatment resulted in higher Erk1/2 inhibition and in increased induction of apoptosis when compared to single agent treatments. However, single selumetinib treatment could cause adverse therapeutic effects, like increased cell migration in certain cells, selumetinib and sorafenib combination treatment lowered migratory capacity in all the cell lines. Importantly, combination resulted in significantly increased tumor growth inhibition in orthotropic xenografts of MDAMB231 cells when compared to sorafenib - but not to selumetinib - treatment. CONCLUSIONS: Our data suggests that combined blocking of RAF and MEK may achieve increased therapeutic response in non-V600 BRAF mutant tumors

Long non-coding RNA RAMS11 promotes metastatic colorectal cancer progression

Colorectal cancer (CRC) is the most common gastrointestinal malignancy in the U.S.A. and approximately 50% of patients develop metastatic disease (mCRC). Despite our understanding of long non-coding RNAs (lncRNAs) in primary colon cancer, their role in mCRC and treatment resistance remains poorly characterized. Therefore, through transcriptome sequencing of normal, primary, and distant mCRC tissues we find 148 differentially expressed RNAs Associated with Metastasis (RAMS). We prioritize RAMS11 due to its association with poor disease-free survival and promotion of aggressive phenotypes in vitro and in vivo. A FDA-approved drug high-throughput viability assay shows that elevated RAMS11 expression increases resistance to topoisomerase inhibitors. Subsequent experiments demonstrate RAMS11-dependent recruitment of Chromobox protein 4 (CBX4) transcriptionally activates Topoisomerase II alpha (TOP2α). Overall, recent clinical trials using topoisomerase inhibitors coupled with our findings of RAMS11-dependent regulation of TOP2α supports the potential use of RAMS11 as a biomarker and therapeutic target for mCRC

Advances in short bowel syndrome: an updated review

Short bowel syndrome (SBS) continues to be an important clinical problem due to its high mortality and morbidity as well as its devastating socioeconomic effects. The past 3 years have witnessed many advances in the investigation of this condition, with the aim of elucidating the cellular and molecular mechanisms of intestinal adaptation. Such information may provide opportunities to exploit various factors that act as growth agents for the remaining bowel mucosa and may suggest new therapeutic strategies to maintain gut integrity, eliminate dependence on total parenteral nutrition, and avoid the need for intestinal transplantation. This review summarizes current research on SBS over the last few years.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47168/1/383_2005_Article_1500.pd