Helminthes in Feral Raccoon (Procyon lotor) as an Alien Species in Iran.

BACKGROUND: The raccoon, Procyon lotor Linn. (Procyonidae) is native to North and Central America but has been introduced in several European and Asian countries including Japan, Germany and Iran. Objective of this study was to determine frequency of gastrointestinal and tissue helminthes from feral raccoons in Iran. METHODS: During 2015-2017, 30 feral raccoons including 12 males and 18 females were collected from Guilan Province, northern Iran (the only region in Iran where raccoons are found). The gastrointestinal tracts and tissues such as lung, liver and muscles were examined for presence of helminthes. RESULTS: Twenty raccoons (66.7%) were found infected with five intestinal helminth species. The prevalence of infection with Strongyloides procyonis Little, 1966 (Nematoda) was 63.3%, Plagiorchis koreanus Ogata, 1938 (Trematoda) (13.3%), Centrorhynchus sp. Lühe, 1911 (Acanthocephala) (10.0%), Camerostrongylus didelphis Wolfgang, 1951 (Nematoda) (3.3%), and Spirocerca lupi Rudolphi, 1809 (Nematoda) (3.3%). No larvae or adult worms were found in other tissues of the examined raccoons. CONCLUSION: Most of the raccoons were infected with S. procyonis. The public health importance of zoonotic parasites transmittable through raccoons, the rapid control and decrease of raccoon populations and their distribution in Iran are also discussed.

The role of prefrontal cortex in a moral judgment task using functional near-infrared spectroscopy.

BACKGROUND: Understanding the neural basis of moral judgment (MJ) and human decision-making has been the subject of numerous studies because of their impact on daily life activities and social norms. Here, we aimed to investigate the neural process of MJ using functional near-infrared spectroscopy (fNIRS), a noninvasive, portable, and affordable neuroimaging modality. METHODS: We examined prefrontal cortex (PFC) activation in 33 healthy participants engaging in MJ exercises. We hypothesized that participants presented with personal (emotionally salient) and impersonal (less emotional) dilemmas would exhibit different brain activation observable through fNIRS. We also investigated the effects of utilitarian and nonutilitarian responses to MJ scenarios on PFC activation. Utilitarian responses are those that favor the greatest good while nonutilitarian responses favor moral actions. Mixed effect models were applied to model the cerebral hemodynamic changes that occurred during MJ dilemmas. RESULTS AND CONCLUSIONS: Our analysis found significant differences in PFC activation during personal versus impersonal dilemmas. Specifically, the left dorsolateral PFC was highly activated during impersonal MJ when a nonutilitarian decision was made. This is consistent with the majority of relevant fMRI studies, and demonstrates the feasibility of using fNIRS, with its portable and motion tolerant capacities, to investigate the neural basis of MJ dilemmas.

A machine learning approach to identify functional biomarkers in human prefrontal cortex for individuals with traumatic brain injury using functional near-infrared spectroscopy.

BACKGROUND: We have explored the potential prefrontal hemodynamic biomarkers to characterize subjects with Traumatic Brain Injury (TBI) by employing the multivariate machine learning approach and introducing a novel task-related hemodynamic response detection followed by a heuristic search for optimum set of hemodynamic features. To achieve this goal, the hemodynamic response from a group of 31 healthy controls and 30 chronic TBI subjects were recorded as they performed a complexity task. METHODS: To determine the optimum hemodynamic features, we considered 11 features and their combinations in characterizing TBI subjects. We investigated the significance of the features by utilizing a machine learning classification algorithm to score all the possible combinations of features according to their predictive power. RESULTS AND CONCLUSIONS: The identified optimum feature elements resulted in classification accuracy, sensitivity, and specificity of 85%, 85%, and 84%, respectively. Classification improvement was achieved for TBI subject classification through feature combination. It signified the major advantage of the multivariate analysis over the commonly used univariate analysis suggesting that the features that are individually irrelevant in characterizing the data may become relevant when used in combination. We also conducted a spatio-temporal classification to identify regions within the prefrontal cortex (PFC) that contribute in distinguishing between TBI and healthy subjects. As expected, Brodmann areas (BA) 10 within the PFC were isolated as the region that healthy subjects (unlike subjects with TBI), showed major hemodynamic activity in response to the High Complexity task. Overall, our results indicate that identified temporal and spatio-temporal features from PFC's hemodynamic activity are promising biomarkers in classifying subjects with TBI.

Relative brain signature: a population-based feature extraction procedure to identify functional biomarkers in the brain of alcoholics.

BACKGROUND: A novel feature extraction technique, Relative-Brain-Signature (RBS), which characterizes subjects' relationship to populations with distinctive neuronal activity, is presented. The proposed method transforms a set of Electroencephalography's (EEG) time series in high dimensional space to a space of fewer dimensions by projecting time series onto orthogonal subspaces. METHODS: We apply our technique to an EEG data set of 77 abstinent alcoholics and 43 control subjects. To characterize subjects' relationship to the alcoholic and control populations, one RBS vector with respect to the alcoholic and one with respect to the control population is constructed. We used the extracted RBS vectors to identify functional biomarkers over the brain of alcoholics. To achieve this goal, the classification algorithm was used to categorize subjects into alcoholics and controls, which resulted in 78% accuracy. RESULTS AND CONCLUSIONS: Using the results of the classification, regions with distinctive functionality in alcoholic subjects are detected. These affected regions, with respect to their spatial extent, are frontal, anterior frontal, centro-parietal, parieto-occiptal, and occipital lobes. The distribution of these regions over the scalp indicates that the impact of the alcohol in the cerebral cortex of the alcoholics is spatially diffuse. Our finding suggests that these regions engage more of the right hemisphere relative to the left hemisphere of the alcoholics' brain.

Compact non-contact total emission detection for in vivo multiphoton excitation microscopy.

We describe a compact, non-contact design for a total emission detection (c-TED) system for intra-vital multiphoton imaging. To conform to a standard upright two-photon microscope design, this system uses a parabolic mirror surrounding a standard microscope objective in concert with an optical path that does not interfere with normal microscope operation. The non-contact design of this device allows for maximal light collection without disrupting the physiology of the specimen being examined. Tests were conducted on exposed tissues in live animals to examine the emission collection enhancement of the c-TED device compared to heavily optimized objective-based emission collection. The best light collection enhancement was seen from murine fat (5×-2× gains as a function of depth), whereas murine skeletal muscle and rat kidney showed gains of over two and just under twofold near the surface, respectively. Gains decreased with imaging depth (particularly in the kidney). Zebrafish imaging on a reflective substrate showed close to a twofold gain throughout the entire volume of an intact embryo (approximately 150 µm deep). Direct measurement of bleaching rates confirmed that the lower laser powers, enabled by greater light collection efficiency, yielded reduced photobleaching in vivo. The potential benefits of increased light collection in terms of speed of imaging and reduced photo-damage, as well as the applicability of this device to other multiphoton imaging methods is discussed.

Capturing dynamic patterns of task-based functional connectivity with EEG.

A new approach to trace the dynamic patterns of task-based functional connectivity, by combining signal segmentation, dynamic time warping (DTW), and Quality Threshold (QT) clustering techniques, is presented. Electroencephalography (EEG) signals of 5 healthy subjects were recorded as they performed an auditory oddball and a visual modified oddball tasks. To capture the dynamic patterns of functional connectivity during the execution of each task, EEG signals are segmented into durations that correspond to the temporal windows of previously well-studied event-related potentials (ERPs). For each temporal window, DTW is employed to measure the functional similarities among channels. Unlike commonly used temporal similarity measures, such as cross correlation, DTW compares time series by taking into consideration that their alignment properties may vary in time. QT clustering analysis is then used to automatically identify the functionally connected regions in each temporal window. For each task, the proposed approach was able to establish a unique sequence of dynamic pattern (observed in all 5 subjects) for brain functional connectivity.