Edgar Guevara

Imaging of an Inflammatory Injury in the Newborn Rat Brain with Photoacoustic Tomography

Background The precise assessment of cerebral saturation changes during an inflammatory injury in the developing brain, such as seen in periventricular leukomalacia, is not well defined. This study investigated the impact of inflammation on locoregional cerebral oxygen saturation in a newborn rodent model using photoacoustic imaging. Methods 1 mg/kg of lipopolysaccharide(LPS) diluted in saline or saline alone was injected under ultrasound guidance directly in the corpus callosum of P3 rat pups. Coronal photoacoustic images were carried out 24 h after LPS exposure. Locoregional oxygen saturation (SO2) and resting state connectivity were assessed in the cortex and the corpus callosum. Microvasculature was then evaluated on cryosection slices by lectin histochemistry. Results Significant reduction of SO2 was found in the corpus callosum; reduced SO2 was also found in the cortex ipsilateral to the injection site. Seed-based functional connectivity analysis showed that bilateral connectivity was not affected by LPS exposure. Changes in locoregional oxygen saturation were accompanied by a significant reduction in the average length of microvessels in the left cortex but no differences were observed in the corpus callosum. Conclusion Inflammation in the developing brain induces marked reduction of locoregional oxygen saturation, predominantly in the white matter not explained by microvascular degeneration. The ability to examine regional saturation offers a new way to monitor injury and understand physiological disturbance non-invasively.

Optical imaging of acute epileptic networks in mice

Abstract. The potential of intrinsic optical imaging and resting-state analysis under anesthetized conditions as a tool to study brain networks associated with epileptic seizures is investigated. Using an acute model of epileptiform activity, the 4-aminopyridine model in live mice, we observe the changes in resting-state networks with the onset of seizure activity and in conditions of spiking activity. Resting-state networks identified before and after the onset of epileptiform activity show both decreased and increased homologous correlations, with a small dependence on seizure intensity. The observed changes are not uniform across the different hemodynamic measures, suggesting a potential decoupling between blood flow and metabolism in the low-frequency networks. This study supports the need for a more extensive investigation of epileptic networks including more than one independent hemodynamic measurement.

Prediction of Glucose Concentration by Impedance Phase Measurements

In recent years researchers have explored non‐invasive techniques for glucose testing such as near infrared spectroscopy, light scattering, photoacoustic spectroscopy, and electrical impedance measurements, without achieving the accuracy of the traditional invasive method. In this paper, measurements in the 1–13 MHz band show that glucose directly affects the impedance parameters of solutions and the effect is more evident in the phase angle; therefore, these impedance phase measurements can be employed to predict the concentration of glucose in vitro, obtaining a smaller error of prediction than previous techniques.

Optical imaging of resting-state functional connectivity in a novel arterial stiffness model

This study aims to assess the impact of unilateral increases in carotid stiffness on cortical functional connectivity measures in the resting state. Using a novel animal model of induced arterial stiffness combined with optical intrinsic signals and laser speckle imaging, resting state functional networks derived from hemodynamic signals are investigated for their modulation by isolated changes in stiffness of the right common carotid artery. By means of seed-based analysis, results showed a decreasing trend of homologous correlation in the motor and cingulate cortices. Furthermore, a graph analysis indicated a randomization of the cortex functional networks, suggesting a loss of connectivity, more specifically in the motor cortex lateral to the treated carotid, which however did not translate in differentiated metabolic activity.

Functional electrical stimulation post-spinal cord injury improves locomotion and increases afferent input into the central nervous system in rats.

Abstract Background Functional electrical stimulation (FES) has been found to be effective in restoring voluntary functions after spinal cord injury (SCI) and stroke. However, the central nervous system (CNS) changes that occur in as a result of this therapy are largely unknown. Objective To examine the effects of FES on the restoration of voluntary locomotor function of the CNS in a SCI rat model. Methods SCI rats were instrumented with chronic FES electrodes in the hindlimb muscles and were divided into two groups: (a) FES therapy and (b) sedentary. At day 7 post-SCI, the animals were assessed for locomotion performance by using a Basso, Beattie and Bresnahan (BBB) scale. They were then anesthetized for a terminal in vivo experiment. The lumbar spinal cord and somatosensory cortex were exposed and the instrumented muscles were stimulated electrically. Associated neurovascular responses in the CNS were recorded with an intrinsic optical imaging system. Results FES greatly improved locomotion recovery by day 7 post-SCI, as measured by BBB scores (P < 0.05): (a) FES 10 ± 2 and (b) controls 3 ± 1. Furthermore, the FES group showed a significant increase (P < 0.05) of neurovascular activation in the spinal cord and somatosensory cortex when the muscles were stimulated between 1 and 3 motor threshold (MT). Conclusion Hind limb rehabilitation with FES is an effective strategy to improve locomotion during the acute phase post-SCI. The results of this study indicate that after FES, the CNS preserves/acquires the capacity to respond to peripheral electrical stimulation.

Carotid Calcification in Mice: A New Model to Study the Effects of Arterial Stiffness on the Brain

Background Arterial stiffness has been identified as an important risk factor for cognitive decline. However, its effects on the brains health are unknown, and there is no animal model available to study the precise impact of arterial stiffness on the brain. Therefore, the objective of the study was to develop and characterize a new model specific to arterial stiffness in order to study its effects on the brain. Methods and Results Calcium chloride (CaCl2) was applied to carotid arteries of mice, inducing an increase in collagen distribution and intima–media thickness, a fragmentation of elastin, a decrease in arterial compliance and distensibility, and an increase in cerebral blood flow pulsatility (n=3 to 11). Calcium deposits were only present at the site of CaCl2 application, and there was no increase in systemic blood pressure or change in vessel radius making this model specific for arterial stiffness. The effects of carotid stiffness were then assessed in the brain. Carotid calcification induced an increase in the production of cerebral superoxide anion and neurodegeneration, detected with Fluoro‐Jade B staining, in the hippocampus (n=3 to 5), a key region for memory and cognition. Conclusions A new model of arterial stiffness based on carotid calcification was developed and characterized. This new model meets all the characteristics of arterial stiffness, and its specificity allows the study of the effects of arterial stiffness on the brain.

Altered Functional Connectivity Following an Inflammatory White Matter Injury in the Newborn Rat: A High Spatial and Temporal Resolution Intrinsic Optical Imaging Study

Very preterm newborns have an increased risk of developing an inflammatory cerebral white matter injury that may lead to severe neuro-cognitive impairment. In this study we performed functional connectivity (fc) analysis using resting-state optical imaging of intrinsic signals (rs-OIS) to assess the impact of inflammation on resting-state networks (RSN) in a pre-clinical model of perinatal inflammatory brain injury. Lipopolysaccharide (LPS) or saline injections were administered in postnatal day (P3) rat pups and optical imaging of intrinsic signals were obtained 3 weeks later. (rs-OIS) fc seed-based analysis including spatial extent were performed. A support vector machine (SVM) was then used to classify rat pups in two categories using fc measures and an artificial neural network (ANN) was implemented to predict lesion size from those same fc measures. A significant decrease in the spatial extent of fc statistical maps was observed in the injured group, across contrasts and seeds (*p = 0.0452 for HbO2 and **p = 0.0036 for HbR). Both machine learning techniques were applied successfully, yielding 92% accuracy in group classification and a significant correlation r = 0.9431 in fractional lesion volume prediction (**p = 0.0020). Our results suggest that fc is altered in the injured newborn brain, showing the long-standing effect of inflammation.

Quality control of mezcal combining multivariate analysis techniques and Raman spectroscopy

A fast method to discriminate between mezcal samples with different aging times was proposed using Raman spectroscopy and multivariate analysis techniques. The multivariate analysis were performed using Principal component analysis (PCA) and Partial least squares discriminant analysis (PLS-DA). The first principal component separates the matured aged mezcal (rested and aged) while the second principal component separates the non-matured from the matured mezcal. PLS-DA was chosen as supervised classifier to predict the belonging of unlabeled spectra to one of aging classes. The results demonstrated that Raman spectroscopy in combination with multivariate analysis could be used as fast method for discrimination between matured mezcal with different aging time.

Ex-vivo multi-modal microscopy of healthy skin

The thorough characterization of skin samples is a critical step in investigating dermatological diseases. The combination of depth-sensitive anatomical imaging with molecular imaging has the potential to provide vast information about the skin. In this proof-of-concept work we present high-resolution mosaic images of skin biopsies using Optical Coherence Tomography (OCT) manually co-registered with standard microscopy, bi-dimensional Raman spectral mapping and fluorescence imaging. A human breast skin sample, embedded in paraffin, was imaged with a swept-source OCT system at 1310 nm. Individual OCT volumes were acquired in fully automated fashion in order to obtain a large field-of-view at high resolution (~10μm). Based on anatomical features, the other three modalities were manually co-registered to the projected OCT volume, using an affine transformation. A drawback is the manual co-registration, which may limit the utility of this method. However, the results indicate that multiple imaging modalities provide complementary information about the sample. This pilot study suggests that multi-modal microscopy may be a valuable tool in the characterization of skin biopsies.

Comparison of the performance of two depth-resolved optical imaging systems: laminar optical tomography and spatially modulated imaging

The objective of this work is to compare quantitatively the imaging capabilities of a laminar optical tomography (LOT) system with those of a spatially modulated imaging (SMI) system. LOT is a three dimensional optical imaging technique that achieves depth sensitivity by measuring multiple-scattered light at different source-detector separations. The SMI method is based on spatially modulated illumination-detection patterns, which encode both optical properties and depth information. In this work, simulation studies are carried out at different noise levels, to obtain the figures of merit of tomographic reconstructions for both systems. Experiments on phantoms are performed to demonstrate the validity of the numerical results.