Brain connectivity during Alzheimer's disease progression and its cognitive impact in a transgenic rat model

The research of Alzheimer's disease (AD) in its early stages and its progression till symptomatic onset is essential to understand the pathology and investigate new treatments. Animal models provide a helpful approach to this research, since they allow for controlled follow-up during the disease evolution. In this work, transgenic TgF344-AD rats were longitudinally evaluated starting at 6 months of age. Every 3 months, cognitive abilities were assessed by a memory-related task and magnetic resonance imaging (MRI) was acquired. Structural and functional brain networks were estimated and characterized by graph metrics to identify differences between the groups in connectivity, its evolution with age, and its influence on cognition. Structural networks of transgenic animals were altered since the earliest stage. Likewise, aging significantly affected network metrics in TgF344-AD, but not in the control group. In addition, while the structural brain network influenced cognitive outcome in transgenic animals, functional network impacted how control subjects performed. TgF344-AD brain network alterations were present from very early stages, difficult to identify in clinical research. Likewise, the characterization of aging in these animals, involving structural network reorganization and its effects on cognition, opens a window to evaluate new treatments for the disease

The natural hallucinogen 5-MeO-DMT, component of Ayahuasca, disrupts cortical function in rats: reversal by antipsychotic drugs

5-Methoxy-N,N-dimethyltryptamine (5-MeO-DMT) is a natural hallucinogen component of Ayahuasca, an Amazonian beverage traditionally used for ritual, religious and healing purposes that is being increasingly used for recreational purposes in US and Europe. 5MeO-DMT is of potential interest for schizophrenia research owing to its hallucinogenic properties. Two other psychotomimetic agents, phencyclidine and 2,5-dimethoxy-4-iodo-phenylisopropylamine (DOI), markedly disrupt neuronal activity and reduce the power of low frequency cortical oscillations (<4 Hz, LFCO) in rodent medial prefrontal cortex (mPFC). Here we examined the effect of 5-MeO-DMT on cortical function and its potential reversal by antipsychotic drugs. Moreover, regional brain activity was assessed by blood-oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). 5-MeO-DMT disrupted mPFC activity, increasing and decreasing the discharge of 51 and 35% of the recorded pyramidal neurons, and reducing (−31%) the power of LFCO. The latter effect depended on 5-HT1A and 5-HT2A receptor activation and was reversed by haloperidol, clozapine, risperidone, and the mGlu2/3 agonist LY379268. Likewise, 5-MeO-DMT decreased BOLD responses in visual cortex (V1) and mPFC. The disruption of cortical activity induced by 5-MeO-DMT resembles that produced by phencyclidine and DOI. This, together with the reversal by antipsychotic drugs, suggests that the observed cortical alterations are related to the psychotomimetic action of 5-MeO-DMT. Overall, the present model may help to understand the neurobiological basis of hallucinations and to identify new targets in antipsychotic drug development

Early brain connectivity alterations and cognitive impairment in a rat model of Alzheimer's disease

Background: Animal models of Alzheimer's disease (AD) are essential to understanding the disease progression and to development of early biomarkers. Because AD has been described as a disconnection syndrome, magnetic resonance imaging (MRI)-based connectomics provides a highly translational approach to characterizing the disruption in connectivity associated with the disease. In this study, a transgenic rat model of AD (TgF344-AD) was analyzed to describe both cognitive performance and brain connectivity at an early stage (5 months of age) before a significant concentration of β-amyloid plaques is present. Methods: Cognitive abilities were assessed by a delayed nonmatch-to-sample (DNMS) task preceded by a training phase where the animals learned the task. The number of training sessions required to achieve a learning criterion was recorded and evaluated. After DNMS, MRI acquisition was performed, including diffusion-weighted MRI and resting-state functional MRI, which were processed to obtain the structural and functional connectomes, respectively. Global and regional graph metrics were computed to evaluate network organization in both transgenic and control rats. Results: The results pointed to a delay in learning the working memory-related task in the AD rats, which also completed a lower number of trials in the DNMS task. Regarding connectivity properties, less efficient organization of the structural brain networks of the transgenic rats with respect to controls was observed. Specific regional differences in connectivity were identified in both structural and functional networks. In addition, a strong correlation was observed between cognitive performance and brain networks, including whole-brain structural connectivity as well as functional and structural network metrics of regions related to memory and reward processes. Conclusions: In this study, connectivity and neurocognitive impairments were identified in TgF344-AD rats at a very early stage of the disease when most of the pathological hallmarks have not yet been detected. Structural and functional network metrics of regions related to reward, memory, and sensory performance were strongly correlated with the cognitive outcome. The use of animal models is essential for the early identification of these alterations and can contribute to the development of early biomarkers of the disease based on MRI connectomics

Effects of Orientation and Anisometry of Magnetic Resonance Imaging Acquisitions on Diffusion Tensor Imaging and Structural Connectomes

Diffusion-weighted imaging (DWI) quantifies water molecule diffusion within tissues and is becoming an increasingly used technique. However, it is very challenging as correct quantification depends on many different factors, ranging from acquisition parameters to a long pipeline of image processing. In this work, we investigated the influence of voxel geometry on diffusion analysis, comparing different acquisition orientations as well as isometric and anisometric voxels. Diffusion-weighted images of one rat brain were acquired with four different voxel geometries (one isometric and three anisometric in different directions) and three different encoding orientations (coronal, axial and sagittal). Diffusion tensor scalar measurements, tractography and the brain structural connectome were analyzed for each of the 12 acquisitions. The acquisition direction with respect to the main magnetic field orientation affected the diffusion results. When the acquisition slice-encoding direction was not aligned with the main magnetic field, there were more artifacts and a lower signal-to-noise ratio that led to less anisotropic tensors (lower fractional anisotropic values), producing poorer quality results. The use of anisometric voxels generated statistically significant differences in the values of diffusion metrics in specific regions. It also elicited differences in tract reconstruction and in different graph metric values describing the brain networks. Our results highlight the importance of taking into account the geometric aspects of acquisitions, especially when comparing diffusion data acquired using different geometries

Wavefront reconstruction by adding modulation capabilities of two liquid crystal devices

We analyze the behavior of complex information in the Fresnel domain, taking into account the limited capability to display complex values of liquid crystal devices when they are used as holographic displays. To do this analysis we study the reconstruction of Fresnel holograms at several distances using the different parts of the complex distribution. We also use the information adjusted with a method that combines two configurations of the devices in an adding architecture. The results of the error analysis show different behavior for the reconstructions when using the different methods. Simulated and experimental results are presented

Resting state networks in the TgF344-AD rat model of Alzheimer's Disease are altered from early stages

A better and non-invasive characterization of the preclinical phases of Alzheimer's disease (AD) is important to advance its diagnosis and obtain more effective benefits from potential treatments. The TgF344-AD rat model has been well characterized and shows molecular, behavioral and brain connectivity alterations that resemble the silent period of the pathology. Our aim was to longitudinally investigate functional brain connectivity in established resting-state networks (RSNs) obtained by independent component analysis (ICA) in a cohort of TgF344-AD and control rats every 3 months, from 5 to 18 months of age, to cover different stages of the disease. Before each acquisition, working memory performance was evaluated by the delayed non match-to-sample (DNMS) task. Differences in the temporal evolution were observed between groups in the amplitude and shape of the somatosensorial and sensorimotor networks but not in the whole default mode network (DMN). Subsequent high dimensional ICA analysis showed early alterations in the anterior DMN subnetwork activity of TgF344-AD rats compared to controls. Performance of DNMS task was positively correlated with somatosensorial network at 5 months of age in the wild-type animals but not in the Tg-F344 rats. At different time points, DMN showed negative correlation with cognitive performance in the control group while in the transgenic group the correlation was positive. In addition, behavioral differences observed at 5 months of age correlated with alterations in the posterior DMN subnetwork. We have demonstrated that functional connectivity using ICA represents a useful biomarker also in animal models of AD such as the TgF344AD rats, as it allows the identification of alterations associated with the progression of the disease, detecting differences in specific networks even at very early stages

Anti-obesity sodium tungstate treatment triggers axonal and glial plasticity in hypothalamic feeding centers

Objective: This study aims at exploring the effects of sodium tungstate treatment on hypothalamic plasticity, which is known to have an important role in the control of energy metabolism. Methods: Adult lean and high-fat diet-induced obese mice were orally treated with sodium tungstate. Arcuate and paraventricular nuclei and lateral hypothalamus were separated and subjected to proteomic analysis by DIGE and mass spectrometry. Immunohistochemistry and in vivo magnetic resonance imaging were also performed. Results: Sodium tungstate treatment reduced body weight gain, food intake, and blood glucose and triglyceride levels. These effects were associated with transcriptional and functional changes in the hypothalamus. Proteomic analysis revealed that sodium tungstate modified the expression levels of proteins involved in cell morphology, axonal growth, and tissue remodeling, such as actin, CRMP2 and neurofilaments, and of proteins related to energy metabolism. Moreover, immunohistochemistry studies confirmed results for some targets and further revealed tungstate-dependent regulation of SNAP25 and HPC-1 proteins, suggesting an effect on synaptogenesis as well. Functional test for cell activity based on c-fos- positive cell counting also suggested that sodium tungstate modified hypothalamic basal activity. Finally, in vivo magnetic resonance imaging showed that tungstate treatment can affect neuronal organization in the hypothalamus. Conclusions: Altogether, these results suggest that sodium tungstate regulates proteins involved in axonal and glial plasticity. The fact that sodium tungstate could modulate hypothalamic plasticity and networks in adulthood makes it a possible and interesting therapeutic strategy not only for obesity management, but also for other neurodegenerative illnesses like Alzheimer's disease

Evaluating the performance of Bayesian and frequentist approaches for longitudinal modeling: application to Alzheimers disease

Linear mixed effects (LME) modelling under both frequentist and Bayesian frameworks can be used to study longitudinal trajectories. We studied the performance of both frameworks on different dataset configurations using hippocampal volumes from longitudinal MRI data across groups-healthy controls (HC), mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients, including subjects that converted from MCI to AD. We started from a big database of 1250 subjects from the Alzheimer's disease neuroimaging initiative (ADNI), and we created different reduced datasets simulating real-life situations using a random-removal permutation-based approach. The number of subjects needed to differentiate groups and to detect conversion to AD was 147 and 115 respectively. The Bayesian approach allowed estimating the LME model even with very sparse databases, with high number of missing points, which was not possible with the frequentist approach. Our results indicate that the frequentist approach is computationally simpler, but it fails in modelling data with high number of missing values

Elevated glucose is associated with hemorrhagic transformation after mechanical thrombectomy in acute ischemic stroke patients with severe pretreatment hypoperfusion

Several pretreatment variables such as elevated glucose and hypoperfusion severity are related to brain hemorrhage after endovascular treatment of acute stroke. We evaluated whether elevated glucose and severe hypoperfusion have synergistic effects in the promotion of parenchymal hemorrhage (PH) after mechanical thrombectomy (MT). We included 258 patients MT-treated who had a pretreatment computed tomography perfusion (CTP) and a post-treatment follow-up MRI. Severe hypoperfusion was defined as regions with cerebral blood volume (CBV) values < 2.5% of normal brain [very-low CBV (VLCBV)-regions]. Median baseline glucose levels were 119 (IQR = 105-141) mg/dL. Thirty-nine (15%) patients had pretreatment VLCBV-regions, and 42 (16%) developed a PH after MT. In adjusted models, pretreatment glucose levels interacted significantly with VLCBV on the prediction of PH (p-interaction = 0.011). In patients with VLCBV-regions, higher glucose was significantly associated with PH (adjusted-OR = 3.15; 95% CI = 1.08-9.19, p = 0.036), whereas this association was not significant in patients without VLCBV-regions. CBV values measured at pretreatment CTP in coregistered regions that developed PH or infarct at follow-up were not correlated with pretreatment glucose levels, thus suggesting the existence of alternative deleterious mechanisms other than direct glucose-driven hemodynamic impairments. Overall, these results suggest that both severe hypoperfusion and glucose levels should be considered in the evaluation of adjunctive neuroprotective strategies

A simple method for displaying Fresnel holograms on liquid crystal panels

In this paper we present a method for reconstructing Fresnel holograms using two liquid crystal devices, one to display the amplitude information and the other to display the phase. The theoretical approach has been adapted to real configurations of VGA panels removed from a commercial video projector. The optical setup is based on the projection of the phase plane into the amplitude plane by means of an imaging lens. Simulated and experimental results are presented