Upregulation of toll-like receptors in chronic enteropathies in dogs

Background: Inflammatory bowel disease (IBD) is thought to result from a dysregulated interaction between the host immune system and commensal microflora. Toll-like receptors (TLRs) recognize microbe-associated molecular patterns (MAMPs), but their role in enteropathies in dogs is unknown. Hypothesis: That there is a dysregulation of TLRs recognizing bacterial MAMPs in dogs with IBD. Animals: Sixteen healthy beagles and 12 dogs with steroid-treated (ST) and 23 dogs with food-responsive (FR) diarrhea. Methods: Prospective, observational study. mRNA expression of canine TLR2, 4, and 9 was evaluated by quantitative real-time RT-PCR in duodenal and colonic biopsies obtained before and after standard therapy. Samples from control dogs were taken at necropsy, with additional biopsies of stomach, jejunum, ileum, and mesenteric lymph node in 6 dogs. Results: There were significant differences (P small intestine >/= colon). Before therapy, ST expressed more mRNA than control dogs for all 3 receptors (P < .05). There were no significant differences between pretreatment and posttreatment values, even though 32/35 dogs improved clinically. No associations were found when comparing receptor mRNA expression with either histology or clinical activity scores. Conclusions and Clinical Importance: Bacteria-responsive TLR2, 4, and 9 are upregulated in duodenal and colonic mucosa in IBD. This might lead to increased inflammation through interaction with the commensal flora. The absence of significant changes after therapy despite clinical improvement might point toward the existence of a genetic predisposition to IBD as described in human IBD.

Alcohol and colorectal cancer: the role of alcohol dehydrogenase 1C polymorphism

BACKGROUND: Chronic alcohol consumption is a risk factor for colorectal cancer. Animal experiments as well as genetic linkage studies in Japanese individuals with inactive acetaldehyde dehydrogenase leading to elevated acetaldehyde concentrations following ethanol ingestion support the hypothesis that acetaldehyde may be responsible for this carcinogenic effect of alcohol. In Caucasians, a polymorphism of alcohol dehydrogenase 1C (ADH1C) exists resulting in different acetaldehyde concentrations following ethanol oxidation. METHODS: To evaluate whether the association between alcohol consumption and colorectal tumor development is modified by ADH1C polymorphism, we recruited 173 individuals with colorectal tumors diagnosed by colonoscopy and 788 control individuals without colorectal tumors. Genotyping was performed using genomic DNA extracted from whole blood followed by polymerase chain reaction. RESULTS: Genotype ADH1C*1/1 was more frequent in patients with alcohol-associated colorectal neoplasia compared to patients without cancers in the multivariate model controlling for age, gender, and alcohol intake (odds ratio = 1.674, 95% confidence interval = 1.110-2.524, 2-sided p from Wald test = 0.0139). In addition, the joint test of the genetic effect and interaction between ADH1C genotype and alcohol intake (2-sided p = 0.0007) indicated that the difference in ADH1C*1 polymorphisms between controls and colorectal neoplasia is strongly influenced by the alcohol consumption and that only individuals drinking more than 30 g ethanol per day with the genotype ADH1C*1/1 had an increased risk for colorectal tumors. CONCLUSIONS: These data identify ADH1C homozygosity as a genetic risk marker for colorectal tumors in individuals consuming more than 30 g alcohol per day and emphasize the role of acetaldehyde as a carcinogenic agent in alcohol-related colorectal carcinogenesis.

Lung volume reduction surgery versus conservative treatment in severe emphysema

Lung volume reduction surgery (LVRS) has been proposed for patients with severe emphysema to improve dyspnoea and pulmonary function. It is unknown, however, whether prognosis and pulmonary function in these patients can be improved compared to conservative treatment. The effect of LVRS and conservative therapy were compared prospectively in 57 patients with emphysema, who fulfilled the standard criteria for LVRS. The patients were divided into two groups according to their own decision. Patients in group 1 (n=29, eight females, mean+/-SEM 58.8+/-1.7 yrs, forced expiratory volume in one second (FEV1) 27.6+/-1.3% of the predicted value) underwent LVRS. Patients in group 2 (n=28, five females, 58.5+/-1.8 yrs, FEV1 30.8+/-1.4% pred) preferred to postpone LVRS. There were no significant differences in lung function between the two groups at baseline; however, there was a tendency towards better functional status in the control group. The control group had a better modified Medical Research Council (MMRC) dyspnea score (3.1+/-0.15 versus 3.5+/-0.1, p<0.04). Model-based comparisons were used to estimate the differences between the two groups over 18 months. Significant improvements were observed in the LVRS group compared to the control group in FEV1, total lung capacity (TLC), Residual volume (RV), MMRC dyspnea score and 6-min walking distance on all follow up visits. The estimated difference in FEV1 was 33% (95% confidence interval 13-58%; p>0.0001), in TLC 12.9% (7.9-18.8%; p>0.0001), in RV 60.9% 32.6-89.2%; p>0.0001), in 6-min walking distance 230 m (138-322 m; p<0.002) and in MMRC dyspnoea score 1.17 (0.79-1.55; p<0.0001). In conclusion, lung volume reduction surgery is more effective than conservative treatment for the improvement of dyspnoea, lung function and exercise capacity in selected patients with severe emphysema.

Integration of electrical neuroimaging with other functional imaging methods

Integrating evidence from different imaging modalities is important to overcome specific limitations of any given imaging method, such as insensitivity of the EEG to unsynchronized neural events, or the lack of fMRI sensitivity to events of low metabolic demand. Processes that are visible in one modality may be related in a nontrivial way to other processes visible in another modality and insight may only be obtained by integrating both methods through a common analysis. For example, brain activity at rest seems to be at least partly determined by an interaction of cortical rhythms (visible to EEG but not to fMRI) with sub-cortical activity (visible to fMRI, but usually not to EEG without averaging). A combination of EEG and fMRI data during rest may thus be more informative than the sum of two separate analyses in both modalities. Integration is also an important source of converging evidence about specific aspects and general principles of neural functions and their dysfunctions in certain pathologies. This is because not only electrical, but also energetic, biochemical, hemodynamic and metabolic processes characterize neural states and functions, and because brain structure provides crucial constraints upon neural functions. Focusing on multimodal integration of functional data should not distract from the privileged status of the electric field as the primary direct, noninvasive real-time measure of neural transmission. The preceding chapters illustrate how electrical neuroimaging has turned scalp EEG into an imaging modality which directly captures the full temporal dynamics of neural activity in the brain.

Scalp field maps and their characterization

The present chapter gives a comprehensive introduction into the display and quantitative characterization of scalp field data. After introducing the construction of scalp field maps, different interpolation methods, the effect of the recording reference and the computation of spatial derivatives are discussed. The arguments raised in this first part have important implications for resolving a potential ambiguity in the interpretation of differences of scalp field data. In the second part of the chapter different approaches for comparing scalp field data are described. All of these comparisons can be interpreted in terms of differences of intracerebral sources either in strength, or in location and orientation in a nonambiguous way. In the present chapter we only refer to scalp field potentials, but mapping also can be used to display other features, such as power or statistical values. However, the rules for comparing and interpreting scalp field potentials might not apply to such data. Generic form of scalp field data Electroencephalogram (EEG) and event-related potential (ERP) recordings consist of one value for each sample in time and for each electrode. The recorded EEG and ERP data thus represent a two-dimensional array, with one dimension corresponding to the variable “time” and the other dimension corresponding to the variable “space” or electrode. Table 2.1 shows ERP measurements over a brief time period. The ERP data (averaged over a group of healthy subjects) were recorded with 19 electrodes during a visual paradigm. The parietal midline Pz electrode has been used as the reference electrode.

Statistical analysis of multichannel scalp field data

High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

Overview of analytical approaches

The general model The aim of this chapter is to introduce a structured overview of the different possibilities available to display and analyze brain electric scalp potentials. First, a general formal model of time-varying distributed EEG potentials is introduced. Based on this model, the most common analysis strategies used in EEG research are introduced and discussed as specific cases of this general model. Both the general model and particular methods are also expressed in mathematical terms. It is however not necessary to understand these terms to understand the chapter. The general model that we propose here is based on the statement made in Chapter 3, stating that the electric field produced by active neurons in the brain propagates in brain tissue without delay in time. Contrary to other imaging methods that are based on hemodynamic or metabolic processes, the EEG scalp potentials are thus “real-time,” not delayed and not a-priori frequency-filtered measurements. If only a single dipolar source in the brain were active, the temporal dynamics of the activity of that source would be exactly reproduced by the temporal dynamics observed in the scalp potentials produced by that source. This is illustrated in Figure 5.1, where the expected EEG signal of a single source with spindle-like dynamics in time has been computed. The dynamics of the scalp potentials exactly reproduce the dynamics of the source. The amplitude of the measured potentials depends on the relation between the location and orientation of the active source, its strength and the electrode position.

Electrical neuroimaging in the time domain

A publication entitled “A default mode of brain function” initiated a new way of looking at functional imaging data. In this PET study the authors discussed the often-observed consistent decrease of brain activation in a variety of tasks as compared with the baseline. They suggested that this deactivation is due to a task-induced suspension of a default mode of brain function that is active during rest, i.e. that there exists intrinsic well-organized brain activity during rest in several distinct brain regions. This suggestion led to a large number of imaging studies on the resting state of the brain and to the conclusion that the study of this intrinsic activity is crucial for understanding how the brain works. The fact that the brain is active during rest has been well known from a variety of EEG recordings for a very long time. Different states of the brain in the sleep–wake continuum are characterized by typical patterns of spontaneous oscillations in different frequency ranges and in different brain regions. Best studied are the evolving states during the different sleep stages, but characteristic EEG oscillation patterns have also been well described during awake periods (see Chapter 1 for details). A highly recommended comprehensive review on the brain's default state defined by oscillatory electrical brain activities is provided in the recent book by György Buzsaki, showing how these states can be measured by electrophysiological procedures at the global brain level as well as at the local cellular level.

Brain electrical microstates in subjects with panic disorder

Brain electrical microstates represent spatial configurations of scalp recorded brain electrical activity and are considered to be the basic elements of stepwise processing of information in the brain. In the present study, the hypothesis of a temporo-limbic dysfunction in panic disorder (PD) was tested by investigating the topographic descriptors of brain microstates, in particular the one corresponding to the Late Positive Complex (LPC), an event-related potential (ERP) component with generators in these regions. ERPs were recorded in PD patients and matched healthy subjects during a target detection task, in a central (CC) and a lateral condition (LC). In the CC, a leftward shift of the LPC microstate positive centroid was observed in the patients with PD versus the healthy control subjects. In the LC, the topographic descriptor of the first microstate showed a rightward shift, while those of both the second and the fourth microstate, corresponding to the LPC, revealed a leftward shift in the PD patients versus the healthy control subjects. These findings indicate an overactivation of the right hemisphere networks involved in early visual processing and a hypoactivation of the right hemisphere circuits involved in LPC generators in PD. In line with this interpretation, the abnormal topography of the LPC microstate, observed in the CC, was associated with a worse performance on a test exploring right temporo-hippocampal functioning. Topographical abnormalities found for the LPC microstate in the LC were associated with a higher number of panic attacks, suggesting a pathogenetic role of the right temporo-hippocampal dysfunction in PD.

Pathways that make voices - White matter changes in auditory hallucinations

BACKGROUND: The origin of auditory hallucinations, which are one of the core symptoms of schizophrenia, is still a matter of debate. It has been hypothesized that alterations in connectivity between frontal and parietotemporal speech-related areas might contribute to the pathogenesis of auditory hallucinations. These networks are assumed to become dysfunctional during the generation and monitoring of inner speech. Magnetic resonance diffusion tensor imaging is a relatively new in vivo method to investigate the directionality of cortical white matter tracts. OBJECTIVE: To investigate, using diffusion tensor imaging, whether previously described abnormal activation patterns observed during auditory hallucinations relate to changes in structural interconnections between the frontal and parietotemporal speech-related areas. METHODS: A 1.5 T magnetic resonance scanner was used to acquire twelve 5-mm slices covering the Sylvian fissure. Fractional anisotropy was assessed in 13 patients prone to auditory hallucinations, in 13 patients without auditory hallucinations, and in 13 healthy control subjects. Structural magnetic resonance imaging was conducted in the same session. Based on an analysis of variance, areas with significantly different fractional anisotropy values between groups were selected for a confirmatory region of interest analysis. Additionally, descriptive voxel-based t tests between the groups were computed. RESULTS: In patients with hallucinations, we found significantly higher white matter directionality in the lateral parts of the temporoparietal section of the arcuate fasciculus and in parts of the anterior corpus callosum compared with control subjects and patients without hallucinations. Comparing patients with hallucinations with patients without hallucinations, we found significant differences most pronounced in the left hemispheric fiber tracts, including the cingulate bundle. CONCLUSION: Our findings suggest that during inner speech, the alterations of white matter fiber tracts in patients with frequent hallucinations lead to abnormal coactivation in regions related to the acoustical processing of external stimuli. This abnormal activation may account for the patients' inability to distinguish self-generated thoughts from external stimulation.