Chemico-nutritional characterization and anti-inflammatory potential of Chirabilva (Holoptelea integrifolia Roxb.) seed: alternate source of protein supplement and fatty acids.

Exploring unconventional protein sources can be an alternative strategy to meet the deficiency. The seeds of Chirabilva (Holoptelea integrifolia Roxb., Family- Ulmaceae) are eaten raw by the ethnic communities of Southeast Asian countries. The present study assessed the chemical, nutritional, and biological potential of the seeds (HIS) and pericarp (HISP) of H. integrifolia. The seeds contain mainly fixed and very few essential oils. The fixed oil of HIS is composed primarily of unsaturated oleic (47%) and saturated palmitic (37%) acids. The HIS are exceptional due to a high content of lipid (50%), protein (24%), carbohydrates (19%), fiber (4%), and anti-nutritional components within permissible limits. The high content (in mg/Kg) of phosphorus (6000), magnesium (422), Calcium (279), and essential nutrients (Ni, Co, Zn, Fe, Cu, Mn, and Cr) in the range of (0.04-6.69) were observed. The moderate anti-oxidant potential of HISP was evident in single electron transfer in-vitro assays. Moreover, HISP extract and HIS solvent-extracted fixed oil showed anti-inflammatory action in lipopolysaccharide-induced HaCaT cells by significantly attenuating pro-inflammatory cytokines (TNF-α) without causing cytotoxicity. Results support de-oiled HIS cake as an alternative source of a high-protein diet and its oil with anti-inflammatory attributes for topical applications.

The relationship between MMP-2 rs243865, MMP-9 rs398242 and CXCL-12 rs1801157 gene polymorphisms with Japanese encephalitis disease and disease outcome in North Indian population.

BACKGROUND & OBJECTIVES: Japanese encephalitis virus (JEV) is one of the most important causes of acute and uncontrolled inflammatory disease in Asia. Matrix metalloproteinases (MMPs) and chemokines play a detrimental role in the host response to JE disease, aetiology, and disease outcome. Evidently, MMPs are widely circulated in the brain and regulate various process including microglial activation, inflammation, blood-brain barrier disruption as well as affects central nervous system (CNS). The present study was to assess the association of single nucleotide polymorphisms of MMP-2, MMP-9 and chemokine (CXCL-12/SDF1-3') in the north Indian population. METHODS: We performed case-control study comprising of 125 patients and 125 healthy controls in north Indian population. Genomic DNA was extracted from whole blood and gene polymorphism have been determined by PCR-RFLP method. RESULTS: MMP-2, MMP-9 and CXCL-12 gene was not significantly associated with JE disease, but homozygous (T/T) genotype of MMP-2 was statically associated with disease outcome (p=0.05, OR=0.110). A/G and G/G genotype of CXCL-12 was significantly associated with severity of disease. (p=0.032, OR=5.500, p=0.037, OR= 9.167). The serum level of MMP-2 was observed significantly increased in JE patients with homozygous (T/T) genotype whereas increased MMP-9 level was associated with heterozygous genotype. INTERPRETATION & CONCLUSION: MMP-2, MMP-9 and CXCL-12 gene polymorphism were not associated with JE susceptibility, but MMP-2 may be contributed to disease protection. CXCL-12 was associated with disease severity. In our concern this is the first report from northern India.

Improving in situ acoustic intensity estimates using MR acoustic radiation force imaging in combination with multifrequency MR elastography.

PURPOSE: Magnetic resonance acoustic radiation force imaging (MR-ARFI) enables focal spot localization during nonablative transcranial ultrasound therapies. As the acoustic radiation force is proportional to the applied acoustic intensity, measured MR-ARFI displacements could potentially be used to estimate the acoustic intensity at the target. However, variable brain stiffness is an obstacle. The goal of this study was to develop and assess a method to accurately estimate the acoustic intensity at the focus using MR-ARFI displacements in combination with viscoelastic properties obtained with multifrequency MR elastography (MRE). METHODS: Phantoms with a range of viscoelastic properties were fabricated, and MR-ARFI displacements were acquired within each phantom using multiple acoustic intensities. Voigt model parameters were estimated for each phantom based on storage and loss moduli measured using multifrequency MRE, and these were used to predict the relationship between acoustic intensity and measured displacement. RESULTS: Using assumed viscoelastic properties, MR-ARFI displacements alone could not accurately estimate acoustic intensity across phantoms. For example, acoustic intensities were underestimated in phantoms stiffer than the assumed stiffness and overestimated in phantoms softer than the assumed stiffness. This error was greatly reduced using individualized viscoelasticity measurements obtained from MRE. CONCLUSION: We demonstrated that viscoelasticity information from MRE could be used in combination with MR-ARFI displacements to obtain more accurate estimates of acoustic intensity. Additionally, Voigt model viscosity parameters were found to be predictive of the relaxation rate of each phantom's time-varying displacement response, which could be used to optimize patient-specific MR-ARFI pulse sequences.

Correcting heat-induced chemical shift distortions in proton resonance frequency-shift thermometry.

PURPOSE: To reconstruct proton resonance frequency-shift temperature maps free of chemical shift distortions. THEORY AND METHODS: Tissue heating created by thermal therapies such as focused ultrasound surgery results in a change in proton resonance frequency that causes geometric distortions in the image and calculated temperature maps, in the same manner as other chemical shift and off-resonance distortions if left uncorrected. We propose an online-compatible algorithm to correct these distortions in 2DFT and echo-planar imaging acquisitions, which is based on a k-space signal model that accounts for proton resonance frequency change-induced phase shifts both up to and during the readout. The method was evaluated with simulations, gel phantoms, and in vivo temperature maps from brain, soft tissue tumor, and uterine fibroid focused ultrasound surgery treatments. RESULTS: Without chemical shift correction, peak temperature and thermal dose measurements were spatially offset by approximately 1 mm in vivo. Spatial shifts increased as readout bandwidth decreased, as shown by up to 4-fold greater temperature hot spot asymmetry in uncorrected temperature maps. In most cases, the computation times to correct maps at peak heat were less than 10 ms, without parallelization. CONCLUSION: Heat-induced proton resonance frequency changes create chemical shift distortions in temperature maps resulting from MR-guided focused ultrasound surgery ablations, but the distortions can be corrected using an online-compatible algorithm. Magn Reson Med 76:172-182, 2016. © 2015 Wiley Periodicals, Inc.

Accelerated MRI thermometry by direct estimation of temperature from undersampled k-space data.

PURPOSE: Acceleration of magnetic resonance (MR) thermometry is desirable for several applications of MR-guided focused ultrasound, such as those requiring greater volume coverage, higher spatial resolution, or higher frame rates. METHODS: We propose and validate a constrained reconstruction method that estimates focal temperature changes directly from k-space without spatial or temporal regularization. A model comprising fully-sampled baseline images is fit to undersampled k-space data, which removes aliased temperature maps from the solution space. Reconstructed temperature maps are compared to maps reconstructed using parallel imaging (iterative self-consistent parallel imaging reconstruction [SPIRiT]) and conventional hybrid thermometry, and temporally constrained reconstruction thermometry. RESULTS: Temporal step response simulations demonstrate finer temporal resolution and lower error in 4×-undersampled radial k-space reconstructions compared to temporally constrained reconstruction. Simulations show that the k-space method can achieve higher accelerations with multiple receive coils. Phantom heating experiments further demonstrate the algorithm's advantage over reconstructions relying on parallel imaging alone to overcome undersampling artifacts. In vivo model error comparisons show the algorithm achieves low temperature error at higher acceleration factors (up to 32× with a radial trajectory) than compared reconstructions. CONCLUSION: High acceleration factors can be achieved using the proposed temperature reconstruction algorithm, without sacrificing temporal resolution or accuracy.

Continuous Monitoring of Heart Rate Variability in Free-Living Conditions Using Wearable Sensors: Exploratory Observational Study.

BACKGROUND: Wearable physiological monitoring devices are promising tools for remote monitoring and early detection of potential health changes of interest. The widespread adoption of such an approach across communities and over long periods of time will require an automated data platform for collecting, processing, and analyzing relevant health information. OBJECTIVE: In this study, we explore prospective monitoring of individual health through an automated data collection, metrics extraction, and health anomaly analysis pipeline in free-living conditions over a continuous monitoring period of several months with a focus on viral respiratory infections, such as influenza or COVID-19. METHODS: A total of 59 participants provided smartwatch data and health symptom and illness reports daily over an 8-month window. Physiological and activity data from photoplethysmography sensors, including high-resolution interbeat interval (IBI) and step counts, were uploaded directly from Garmin Fenix 6 smartwatches and processed automatically in the cloud using a stand-alone, open-source analytical engine. Health risk scores were computed based on a deviation in heart rate and heart rate variability metrics from each individual's activity-matched baseline values, and scores exceeding a predefined threshold were checked for corresponding symptoms or illness reports. Conversely, reports of viral respiratory illnesses in health survey responses were also checked for corresponding changes in health risk scores to qualitatively assess the risk score as an indicator of acute respiratory health anomalies. RESULTS: The median average percentage of sensor data provided per day indicating smartwatch wear compliance was 70%, and survey responses indicating health reporting compliance was 46%. A total of 29 elevated health risk scores were detected, of which 12 (41%) had concurrent survey data and indicated a health symptom or illness. A total of 21 influenza or COVID-19 illnesses were reported by study participants; 9 (43%) of these reports had concurrent smartwatch data, of which 6 (67%) had an increase in health risk score. CONCLUSIONS: We demonstrate a protocol for data collection, extraction of heart rate and heart rate variability metrics, and prospective analysis that is compatible with near real-time health assessment using wearable sensors for continuous monitoring. The modular platform for data collection and analysis allows for a choice of different wearable sensors and algorithms. Here, we demonstrate its implementation in the collection of high-fidelity IBI data from Garmin Fenix 6 smartwatches worn by individuals in free-living conditions, and the prospective, near real-time analysis of the data, culminating in the calculation of health risk scores. To our knowledge, this study demonstrates for the first time the feasibility of measuring high-resolution heart IBI and step count using smartwatches in near real time for respiratory illness detection over a long-term monitoring period in free-living conditions.

Transcranial ultrasound neuromodulation of the thalamic visual pathway in a large animal model and the dose-response relationship with MR-ARFI.

Neuromodulation of deep brain structures via transcranial ultrasound stimulation (TUS) is a promising, but still elusive approach to non-invasive treatment of brain disorders. The purpose of this study was to confirm that MR-guided TUS of the lateral geniculate nucleus (LGN) can modulate visual evoked potentials (VEPs) in the intact large animal; and to study the impact on cortical brain oscillations. The LGN on one side was identified with T2-weighted MRI in sheep (all male, n = 9). MR acoustic radiation force imaging (MR-ARFI) was used to confirm localization of the targeted area in the brain. Electroencephalographic (EEG) signals were recorded, and the visual evoked potential (VEP) peak-to-peak amplitude (N70 and P100) was calculated for each trial. Time-frequency spectral analysis was performed to elucidate the effect of TUS on cortical brain dynamics. The VEP peak-to-peak amplitude was reversibly suppressed relative to baseline during TUS. Dynamic spectral analysis demonstrated a change in cortical oscillations when TUS is paired with visual sensory input. Sonication-associated microscopic displacements, as measured by MR-ARFI, correlated with the TUS-mediated suppression of visual evoked activity. TUS non-invasively delivered to LGN can neuromodulate visual activity and oscillatory dynamics in large mammalian brains.

Arsenic-induced differential expression of oxidative stress and secondary metabolite content in two genotypes of Andrographis paniculata.

The present study explores the differential responses of two genotypes (APwC: wild collection and APMS: mass selection line) of A. paniculata against the three application rates of arsenic (42, 126, and 200 mg kg-1). The oxidative enzymes, As accumulation in different tissues, plant growth, and content of pharmacologically important ent-labdane-related diterpenes (ent-LRDs) of the two genotypes were evaluated in the study. Results demonstrated that As uptake significantly reduced plant biomass in APwC and APMS by 5-41.5% and 9-33% in a dose-response manner, respectively. The APMS exhibited lower bioconcentration and translocation factors, higher As tolerance index, and higher content of ent-LRDs as compared to APWC. As treatment induced a decrease in the sum of four metabolite content of APMS (1.43 times) and an increase in that of APWC (1.12 times) as compared to control. Likewise, variance in the production of 5,7,2',3'-tetramethoxyflavanone, and stress enzymes was also observed between APwC and APMS. The increase in the expression of ApCPS2 suggested its involvement in channeling of metabolic flux towards the biosynthesis of ent-LRDs under As stress.

Histologic safety of transcranial focused ultrasound neuromodulation and magnetic resonance acoustic radiation force imaging in rhesus macaques and sheep.

BACKGROUND: Neuromodulation by transcranial focused ultrasound (FUS) offers the potential to non-invasively treat specific brain regions, with treatment location verified by magnetic resonance acoustic radiation force imaging (MR-ARFI). OBJECTIVE: To investigate the safety of these methods prior to widespread clinical use, we report histologic findings in two large animal models following FUS neuromodulation and MR-ARFI. METHODS: Two rhesus macaques and thirteen Dorset sheep were studied. FUS neuromodulation was targeted to the primary visual cortex in rhesus macaques and to subcortical locations, verified by MR-ARFI, in eleven sheep. Both rhesus macaques and five sheep received a single FUS session, whereas six sheep received repeated sessions three to six days apart. The remaining two control sheep did not receive ultrasound but otherwise underwent the same anesthetic and MRI procedures as the eleven experimental sheep. Hematoxylin and eosin-stained sections of brain tissue (harvested zero to eleven days following FUS) were evaluated for tissue damage at FUS and control locations as well as tissue within the path of the FUS beam. TUNEL staining was used to evaluate for the presence of apoptosis in sheep receiving high dose FUS. RESULTS: No FUS-related pre-mortem histologic findings were observed in the rhesus macaques or in any of the examined sheep. Extravascular red blood cells (RBCs) were present within the meninges of all sheep, regardless of treatment group. Similarly, small aggregates of perivascular RBCs were rarely noted in non-target regions of neural parenchyma of FUS-treated (8/11) and untreated (2/2) sheep. However, no concurrent histologic abnormalities were observed, consistent with RBC extravasation occurring as post-mortem artifact following brain extraction. Sheep within the high dose FUS group were TUNEL-negative at the targeted site of FUS. CONCLUSIONS: The absence of FUS-related histologic findings suggests that the neuromodulation and MR-ARFI protocols evaluated do not cause tissue damage.

Visuospatial processing in children with neurofibromatosis type 1.

Neuroimaging studies investigating the neural network of visuospatial processing have revealed a right hemisphere network of activation including inferior parietal lobe, dorsolateral prefrontal cortex, and extrastriate regions. Impaired visuospatial processing, indicated by the Judgment of Line Orientation (JLO), is commonly seen in individuals with neurofibromatosis type 1 (NF-1). Nevertheless, few studies have examined the neural activity associated with visuospatial processing in NF-1, in particular, during a JLO task. This study used functional neuroimaging to explore differences in volume of activation in predefined regions of interest between 13 individuals with NF-1 and 13 controls while performing an analogue JLO task. We hypothesized that participants with NF-1 would show anomalous right hemisphere activation and therefore would recruit regions within the left hemisphere to complete the task. Multivariate analyses of variance were used to test for differences between groups in frontal, temporal, parietal, and occipital regions. Results indicate that, as predicted, controls utilized various right hemisphere regions to complete the task, while the NF-1 group tended to recruit left hemisphere regions. These results suggest that the NF-1 group has an inefficient right hemisphere network. An additional unexpected finding was that the NF-1 group showed decreased volume of activation in primary visual cortex (BA 17). Future studies are needed to examine whether the decrease in primary visual cortex is related to a deficit in basic visual processing; findings could ultimately lead to a greater understanding of the nature of deficits in NF-1 and have implications for remediation.

Spatially-segmented undersampled MRI temperature reconstruction for transcranial MR-guided focused ultrasound.

BACKGROUND: Volumetric thermometry with fine spatiotemporal resolution is desirable to monitor MR-guided focused ultrasound (MRgFUS) procedures in the brain, but requires some form of accelerated imaging. Accelerated MR temperature imaging methods have been developed that undersample k-space and leverage signal correlations over time to suppress the resulting undersampling artifacts. However, in transcranial MRgFUS treatments, the water bath surrounding the skull creates signal variations that do not follow those correlations, leading to temperature errors in the brain due to signal aliasing. METHODS: To eliminate temperature errors due to the water bath, a spatially-segmented iterative reconstruction method was developed. The method fits a k-space hybrid signal model to reconstruct temperature changes in the brain, and a conventional MR signal model in the water bath. It was evaluated using single-channel 2DFT Cartesian, golden angle radial, and spiral data from gel phantom heating, and in vivo 8-channel 2DFT data from a FUS thalamotomy. Water bath signal intensity in phantom heating images was scaled between 0-100% to investigate its effect on temperature error. Temperature reconstructions of retrospectively undersampled data were performed using the spatially-segmented method, and compared to conventional whole-image k-space hybrid (phantom) and SENSE (in vivo) reconstructions. RESULTS: At 100% water bath signal intensity, 3 ×-undersampled spatially-segmented temperature reconstruction error was nearly 5-fold lower than the whole-image k-space hybrid method. Temperature root-mean square error in the hot spot was reduced on average by 27 × (2DFT), 5 × (radial), and 12 × (spiral) using the proposed method. It reduced in vivo error 2 × in the brain for all acceleration factors, and between 2 × and 3 × in the temperature hot spot for 2-4 × undersampling compared to SENSE. CONCLUSIONS: Separate reconstruction of brain and water bath signals enables accelerated MR temperature imaging during MRgFUS procedures with low errors due to undersampling using Cartesian and non-Cartesian trajectories. The spatially-segmented method benefits from multiple coils, and reconstructs temperature with lower error compared to measurements from SENSE-reconstructed images. The acceleration can be applied to increase volumetric coverage and spatiotemporal resolution.

Maintenance and Representation of Mind Wandering during Resting-State fMRI.

Major advances in resting-state functional magnetic resonance imaging (fMRI) techniques in the last two decades have provided a tool to better understand the functional organization of the brain both in health and illness. Despite such developments, characterizing regulation and cerebral representation of mind wandering, which occurs unavoidably during resting-state fMRI scans and may induce variability of the acquired data, remains a work in progress. Here, we demonstrate that a decrease or decoupling in functional connectivity involving the caudate nucleus, insula, medial prefrontal cortex and other domain-specific regions was associated with more sustained mind wandering in particular thought domains during resting-state fMRI. Importantly, our findings suggest that temporal and between-subject variations in functional connectivity of above-mentioned regions might be linked with the continuity of mind wandering. Our study not only provides a preliminary framework for characterizing the maintenance and cerebral representation of different types of mind wandering, but also highlights the importance of taking mind wandering into consideration when studying brain organization with resting-state fMRI in the future.

Preschool anxiety disorders predict different patterns of amygdala-prefrontal connectivity at school-age.

OBJECTIVE: In this prospective, longitudinal study of young children, we examined whether a history of preschool generalized anxiety, separation anxiety, and/or social phobia is associated with amygdala-prefrontal dysregulation at school-age. As an exploratory analysis, we investigated whether distinct anxiety disorders differ in the patterns of this amygdala-prefrontal dysregulation. METHODS: Participants were children taking part in a 5-year study of early childhood brain development and anxiety disorders. Preschool symptoms of generalized anxiety, separation anxiety, and social phobia were assessed with the Preschool Age Psychiatric Assessment (PAPA) in the first wave of the study when the children were between 2 and 5 years old. The PAPA was repeated at age 6. We conducted functional MRIs when the children were 5.5 to 9.5 year old to assess neural responses to viewing of angry and fearful faces. RESULTS: A history of preschool social phobia predicted less school-age functional connectivity between the amygdala and the ventral prefrontal cortices to angry faces. Preschool generalized anxiety predicted less functional connectivity between the amygdala and dorsal prefrontal cortices in response to fearful faces. Finally, a history of preschool separation anxiety predicted less school-age functional connectivity between the amygdala and the ventral prefrontal cortices to angry faces and greater school-age functional connectivity between the amygdala and dorsal prefrontal cortices to angry faces. CONCLUSIONS: Our results suggest that there are enduring neurobiological effects associated with a history of preschool anxiety, which occur over-and-above the effect of subsequent emotional symptoms. Our results also provide preliminary evidence for the neurobiological differentiation of specific preschool anxiety disorders.

A kernel machine-based fMRI physiological noise removal method.

Functional magnetic resonance imaging (fMRI) technique with blood oxygenation level dependent (BOLD) contrast is a powerful tool for noninvasive mapping of brain function under task and resting states. The removal of cardiac- and respiration-induced physiological noise in fMRI data has been a significant challenge as fMRI studies seek to achieve higher spatial resolutions and characterize more subtle neuronal changes. The low temporal sampling rate of most multi-slice fMRI experiments often causes aliasing of physiological noise into the frequency range of BOLD activation signal. In addition, changes of heartbeat and respiration patterns also generate physiological fluctuations that have similar frequencies with BOLD activation. Most existing physiological noise-removal methods either place restrictive limitations on image acquisition or utilize filtering or regression based post-processing algorithms, which cannot distinguish the frequency-overlapping BOLD activation and the physiological noise. In this work, we address the challenge of physiological noise removal via the kernel machine technique, where a nonlinear kernel machine technique, kernel principal component analysis, is used with a specifically identified kernel function to differentiate BOLD signal from the physiological noise of the frequency. The proposed method was evaluated in human fMRI data acquired from multiple task-related and resting state fMRI experiments. A comparison study was also performed with an existing adaptive filtering method. The results indicate that the proposed method can effectively identify and reduce the physiological noise in fMRI data. The comparison study shows that the proposed method can provide comparable or better noise removal performance than the adaptive filtering approach.

Interleaved EPI based fMRI improved by multiplexed sensitivity encoding (MUSE) and simultaneous multi-band imaging.

Functional magnetic resonance imaging (fMRI) is a non-invasive and powerful imaging tool for detecting brain activities. The majority of fMRI studies are performed with single-shot echo-planar imaging (EPI) due to its high temporal resolution. Recent studies have demonstrated that, by increasing the spatial-resolution of fMRI, previously unidentified neuronal networks can be measured. However, it is challenging to improve the spatial resolution of conventional single-shot EPI based fMRI. Although multi-shot interleaved EPI is superior to single-shot EPI in terms of the improved spatial-resolution, reduced geometric distortions, and sharper point spread function (PSF), interleaved EPI based fMRI has two main limitations: 1) the imaging throughput is lower in interleaved EPI; 2) the magnitude and phase signal variations among EPI segments (due to physiological noise, subject motion, and B0 drift) are translated to significant in-plane aliasing artifact across the field of view (FOV). Here we report a method that integrates multiple approaches to address the technical limitations of interleaved EPI-based fMRI. Firstly, the multiplexed sensitivity-encoding (MUSE) post-processing algorithm is used to suppress in-plane aliasing artifacts resulting from time-domain signal instabilities during dynamic scans. Secondly, a simultaneous multi-band interleaved EPI pulse sequence, with a controlled aliasing scheme incorporated, is implemented to increase the imaging throughput. Thirdly, the MUSE algorithm is then generalized to accommodate fMRI data obtained with our multi-band interleaved EPI pulse sequence, suppressing both in-plane and through-plane aliasing artifacts. The blood-oxygenation-level-dependent (BOLD) signal detectability and the scan throughput can be significantly improved for interleaved EPI-based fMRI. Our human fMRI data obtained from 3 Tesla systems demonstrate the effectiveness of the developed methods. It is expected that future fMRI studies requiring high spatial-resolvability and fidelity will largely benefit from the reported techniques.

Identification and attenuation of physiological noise in fMRI using kernel techniques.

Functional magnetic resonance imaging (fMRI) techniques enable noninvasive studies of brain functional activity under task and resting states. However, the analysis of brain activity could be significantly affected by the cardiac- and respiration-induced physiological noise in fMRI data. In most multi-slice fMRI experiments, the temporal sampling rates are not high enough to critically sample the physiological noise, and the noise is aliased into frequency bands where useful brain functional signal exists, compromising the analysis. Most existing approaches cannot distinguish between the aliased noise and signal if they overlap in the frequency domain. In this work, we further developed a kernel principal component analysis based physiological removal method based on our previous work. Specifically, two kernel functions were evaluated based on a newly proposed criterion that can measure the capability of a kernel to separate the aliased physiological noise from fMRI signal. In addition, a mutual information based criterion was designed to select principal components for noise removal. The method was evaluated by human experimental fMRI studies, and the results demonstrate that the proposed method can effectively identify and attenuate the aliased physiological noise in fMRI data.