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Prenatal exposure to buprenorphine renders offspring vulnerable to cerebral impairments. In this study, our data demonstrate, for the first time, that prenatal exposure to buprenorphine escalates astrocyte activation concurrent with indications of endoplasmic reticulum (ER) stress in the hippocampi of neonates, and this can be prevented by the coadministration of dextromethorphan with buprenorphine. Furthermore, dextromethorphan can inhibit the accumulation of GPR37 in the hippocampus of newborns caused by buprenorphine and is accompanied by the proapoptotic ER stress response that involves the procaspase-3/CHOP pathway. Primary astrocyte cultures derived from the neonates of the buprenorphine group also displayed aberrant ER calcium mobilization and elevated basal levels of cyclooxygenase-2 (COX-2) at 14 days in vitro while showing sensitivity to lipopolysaccharide-activated expression of COX-2. Similarly, these long-lasting defects in the hippocampus and astrocytes were abolished by dextromethorphan. Our findings suggest that prenatal exposure to buprenorphine might instigate long-lasting effects on hippocampal and astrocytic functions. The beneficial effects of prenatal coadministration of dextromethorphan might be, at least in part, attributed to its properties in attenuating astrocyte activation and hippocampal ER stress in neonates.

In magnetic resonance imaging (MRI), noise is a limiting factor for higher spatial resolution and a major cause of prolonged scan time, owing to the need for repeated scans. Improving the signal-to-noise ratio is therefore key to faster and higher-resolution MRI. Here we propose a method for mapping and reducing noise in MRI by leveraging the inherent redundancy in complex-valued multi-channel MRI data. Our method leverages a provably optimal strategy for shrinking the singular values of a data matrix, allowing it to outperform state-of-the-art methods such as Marchenko-Pastur PCA in noise reduction. Our method reduces the noise floor in brain diffusion MRI by 5-fold and remarkably improves the contrast of spiral lung \(^{19}\)F MRI. Our framework is fast and does not require training and hyper-parameter tuning, therefore providing a convenient means for improving SNR in MRI.

In this paper, we present a robust reconstruction scheme for diffusion MRI (dMRI) data acquired using slice-interleaved diffusion encoding (SIDE). When combined with SIDE undersampling and simultaneous multi-slice (SMS) imaging, our reconstruction strategy is capable of significantly reducing the amount of data that needs to be acquired, enabling high-speed diffusion imaging for pediatric, elderly, and claustrophobic individuals. In contrast to the conventional approach of acquiring a full diffusion-weighted (DW) volume per diffusion wavevector, SIDE acquires in each repetition time (TR) a volume that consists of interleaved slice groups, each group corresponding to a different diffusion wavevector. This strategy allows SIDE to rapidly acquire data covering a large number of wavevectors within a short period of time. The proposed reconstruction method uses a diffusion spectrum model and multi-dimensional total variation to recover full DW images from DW volumes that are slice-undersampled due to unacquired SIDE volumes. We formulate an inverse problem that can be solved efficiently using the alternating direction method of multipliers (ADMM). Experiment results demonstrate that DW images can be reconstructed with high fidelity even when the acquisition is accelerated by 25 folds.

Functional MRI (fMRI) has become an important translational tool for studying brain activity and connectivity in animal models and humans. For accurate and reliable measurement of functional connectivity, nuisance removal strategies developed for human brain, such as regressing motion parameters, cerebrospinal fluid (CSF)/white matter-derived signals and the global signal, have been applied to rodent. However, due to the very different anatomy, with the majority of the rodent brain being gray matter, and experimental conditions, in which animals are anesthetized and head-fixed, these methods may not be suitable for rodent fMRI. In this study, we assessed various nuisance regression methods and the effects of motion correction on a large dataset of both task and resting fMRI of anesthetized rat brain. Sensitivity and specificity were assessed in the somatosensory pathway under forepaw stimulation and resting state. Reproducibility at various sample sizes was simulated by randomly subsampling the dataset. To overcome the difficulty in extracting nuisance from the brain, a method using principal components estimated from tissues outside the brain was evaluated. Our results showed that neither detrend, motion correction, motion regression nor CSF signal regression could improve specificity despite increasing temporal signal-to-noise ratios. Although global signal regression increased the specificity of task activation and functional connectivity, the sensitivity and connectivity strength was drastically reduced, likely due to its strong correlation with the cortical signal. Motion parameters also correlated with task activation and the global signal, indicating that motion correction detected intensity variations in the brain. The nuisance estimated from tissues outside the brain produced a moderate improvement in specificity. In conclusion, nuisance removal suitable for human fMRI may not be optimal for rodents. While further development is needed, estimating nuisance from tissues outside the brain may be an alternative.

We present a reconstruction scheme for diffusion MRI data acquired using slice-interleaved diffusion encoding (SIDE). We show that, when combined with multi-band imaging, the method is capable of reducing the amount of data that needs to be acquired by as much as 25 times, therefore remarkably speeding up acquisition and making high angular resolution diffusion imaging much more feasible, particularly for pediatric, elderly, and claustrophobic patients. In contrast to the conventional approach of acquiring a full diffusion-weighted (DW) volume for each diffusion wavevector, SIDE acquires for each repetition time (TR) a volume consisting of interleaved slice groups, each corresponding to a different diffusion wavevector. This allows SIDE to rapidly acquire information associated with a larger number of wavevectors within a short period of time. We formulate the inverse problem involved in recovering the full DW images as a constrained variational problem regularized by multidimensional total variation. The problem can be solved efficiently using the alternating direction method of multipliers (ADMM). Experiment results based on SIDE data of adults indicate that DW images can be recovered with high fidelity despite high undersampling for multifold acceleration.

The hippocampus is critical for learning and memory and may be separated into anatomically-defined hippocampal subfields (aHPSFs). Many studies have shown that aHPSFs, and their respective functional networks, are differentially vulnerable to a variety of disorders. Hippocampal functional networks, particularly during resting state, are generally analyzed using aHPSFs as seed regions, with the underlying assumption that the function within a subfield is homogeneous, yet heterogeneous between subfields. However, several prior studies that have utilized aHPSFs and assessed brain-wide cortical connectivity have observed similar resting-state functional connectivity profiles between aHPSFs. Alternatively, data-driven approaches offer a means to investigate hippocampal functional organization without a priori assumptions. However, insufficient spatial resolution may lead to partial volume effects at the boundaries of hippocampal subfields, resulting in a number of caveats concerning the reliability of the results. Hence, we developed a functional Magnetic Resonance Imaging (fMRI) sequence on a 7T MR scanner achieving 0.94 mm isotropic resolution with a TR of 2s and brain-wide coverage to 1) investigate whether hippocampal functional segmentation with ultrahigh-resolution data demonstrate similar anatomical, lamellar structures in the hippocampus, and 2) define and compare the brain-wide FC associated with fine-grained aHPSFs and functionally-defined hippocampal subfields (fHPSFs). Using a spatially restricted hippocampal Independent Component Analysis (ICA) approach, this study showed that fHPSFs were arranged along the longitudinal axis of the hippocampus that were not comparable to the lamellar structures of aHPSFs. Contrary to the anatomically defined hippocampal subfields which are bilaterally symmetrical, 13 out of 20 fHPSFs were unilateral. For brain-wide FC, the fHPSFs rather than aHPSFs revealed that a number of fHPSFs connected specifically with some of the functional networks. The visual and sensorimotor networks preferentially connected with different portions of CA1, CA3 and CA4/DG. The DMN was also found to connect more extensively with posterior subfields rather than anterior subfields. Finally, the frontoparietal network (FPN) was anticorrelated with the head portion of CA1. The investigation of functional networks associated with the fHPSFs may enhance the sensitivity of biomarkers for a range of neurological disorders, as network-based approaches take into account disease-related alterations in brain-wide interconnections rather than measuring the regional changes of hippocampus.

The ability to achieve submillimter isotropic resolution diffusion MR imaging (dMRI) is critically important to study fine-scale brain structures, particularly in the cortex. One of the major challenges in performing submillimeter dMRI is the inherently low signal-to-noise ratio (SNR). While approaches capable of mitigating the low SNR in high resolution dMRI have been proposed, namely simultaneous multi-slab (SMSlab) and generalized slice dithered enhanced resolution with simultaneous multislice (gSlider-SMS), limitations are associated with these approaches. The SMSlab sequences suffer from the slab boundary artifacts and require additional navigators for phase estimation. On the other hand, gSlider sequences require relatively high RF power and peak amplitude, which increase the SAR and complicate the RF excitation. In this work, we developed a navigator-free multishot-encoded simultaneous multi-slice (MUSIUM) imaging approach on a 3T MR scanner, achieving enhanced SNR, low RF power and peak amplitude, and being free from slab boundary artifacts. The dMRI with ultrahigh resolution (0.86 mm isotropic resolution), whole brain coverage and ~12.5 minute acquisition time were achieved, revealing detailed structures at cortical and white matter areas. The simulated and in vivo results also demonstrated that the MUSIUM imaging was minimally affected by the motion. Taken together, the MUSIUM imaging is a promising approach to achieve submillimeter diffusion imaging on 3T MR scanners within clinically feasible scan time., 6 Figures in the main text and 2 figures in the supplementary materials

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) represent two ends of the same disease spectrum of adult-onset neurodegenerative diseases that affect the motor and cognitive functions, respectively. Multiple common genetic loci such as fused in sarcoma (FUS) have been identified to play a role in ALS and FTD etiology. Current studies indicate that FUS mutations incur gain-of-toxic functions to drive ALS pathogenesis. However, how the disease-linked mutations of FUS affect cognition remains elusive. Using a mouse model expressing an ALS-linked human FUS mutation (R514G-FUS) that mimics endogenous expression patterns, we found that FUS proteins showed an age-dependent accumulation of FUS proteins despite the downregulation of mouse FUS mRNA by the R514G-FUS protein during aging. Furthermore, these mice developed cognitive deficits accompanied by a reduction in spine density and long-term potentiation (LTP) within the hippocampus. At the physiological expression level, mutant FUS is distributed in the nucleus and cytosol without apparent FUS aggregates or nuclear envelope defects. Unbiased transcriptomic analysis revealed a deregulation of genes that cluster in pathways involved in nonsense-mediated decay, protein homeostasis, and mitochondrial functions. Furthermore, the use of in vivo functional imaging demonstrated widespread reduction in cortical volumes but enhanced functional connectivity between hippocampus, basal ganglia and neocortex in R514G-FUS mice. Hence, our findings suggest that disease-linked mutation in FUS may lead to changes in proteostasis and mitochondrial dysfunction that in turn affect brain structure and connectivity resulting in cognitive deficits.

Contains fulltext : 219632.pdf (Publisher’s version ) (Open Access) Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

In this paper, we introduce a technique for super-resolution reconstruction of diffusion MRI, harnessing fiber-continuity (FC) as a constraint in a global whole-brain optimization framework. FC is a biologically-motivated constraint that relates orientation information between neighboring voxels. We show that it can be used to effectively constrain the inverse problem of recovering high-resolution data from low-resolution data. Since voxels are inter-related by FC, we devise a global optimization framework that allows solutions pertaining to all voxels to be solved simultaneously. We demonstrate that the proposed super-resolution framework is effective for diffusion MRI data of a glioma patient, a healthy subject, and a macaque.

The antiobesity effects of quercetin-rich supplement (QRS), which contain quercetin, lycopene, taurine, and litchi flower extract, on a high-fat diet (HFD)-induced obese rats were investigated. The rats that consume HFD with QRS (185 mg/kg rat) have significantly modulated the final body weights [490 ± 11 (HFD) → 441 ± 11 (HFD+QRS) g], total body fat [112.9 ± 4.5 (HFD) → 86.6 ± 5.7 (HFD+QRS) g], liver weights [14.8 ± 0.4 (HFD) → 12.6 ± 0.4 (HFD+QRS) g/rat], and the serum TG [102.5 ± 7.3 (HFD) → 90.7 ± 6.5 (HFD+QRS) mg/dL] to a level that resembled the regular diet-consumed rats (p < 0.05). The excretion of lipid in the faeces augmented in QRS groups as compared with the nonsupplemented HFD group [faecal total lipid: 62.43 ± 2.80 (HFD) → 73.15 ± 0.88 (HFD+QRS) mg/g dried faeces, p < 0.05]. In the histological analysis, quercetin-rich formulation supplemented groups presented a much less lipid accumulation and smaller size of adipocytes. Moreover, a decreased serum thiobarbituric acid reactive substances [1.55 ± 0.17 (HFD) → 0.78 ± 0.04 (HFD+QRS) nmol MDA eq/mL serum] increased levels of serum Trolox equivalent antioxidant capacity [3.89 ± 0.08 (HFD) → 6.46 ± 0.20 (HFD+QRS) μmol/mL serum], and more active hepatic antioxidant enzymes were observed in the supplemented groups (p < 0.05). The result of this work is a good demonstration of how a combination of bioactive compounds could work synergistically and become very effective in disease prevention.

Black garlic (also called aged garlic) is a type of fermented garlic product from fresh garlic that is often used as a food ingredient and a functional food in Asian countries. The aim of this study was to investigate whether black garlic ameliorates obesity induced by a high-fat diet in rats. Male Wistar rats were fed a normal diet or a high-fat diet (HFD) (30% lard, w/w) combined with 0, 0.2, 0.6, or 1.2% black garlic (BG) (w/w) for a period of six weeks. The results demonstrated that body weight, tissue weights of liver, peritoneal fat, and epididymal fat, serum triglycerides, and hepatic lipid profiles (total lipids, triglycerides, and cholesterol) in the HFD+BG groups were significantly decreased compared with those in the HFD group. BG also reduced hepatic oxidative stress (reduced GSSG and enhanced TEAC, GSH, GRd, and GPx) in HFD-induced obese rats. These results suggest that black garlic may be useful for the treatment of obesity.

Phytochemicals have multifunctional bioactivities, such as anti-inflammatory and anti-obesity activities. However, there are still relatively few studies that have investigated the possible anti-fatigue of functional phytochemical compounds (such as resveratrol, triterpenoids, and catechins) in animal models. Therefore, the aim of this study was to develop of in vitro models as tools for cellular and molecular studies of anti-fatigue. C2C12 myotubes were used for evaluating in vitro the anti-fatigue of functional compounds. The results indicated that treatment with some functional compounds (including resveratrol, quercetin, epigallocatechin gallate, and epicatechin) significantly increased the expression of mitochondrial DNA genes (including cytochrome b and cytochrome c oxidase subunit II ) and the activities of mitochondrial enzymes (including citrate synthase and cytochrome c oxidase) in C2C12 myotubes. These results demonstrated that resveratrol, quercetin, epigallocatechin gallate, and epicatechin have great potential as novel mitochondrial-activating agents that may play an important role in anti-fatigue.

Despite recent advances in auditory neuroscience, the exact functional organization of human auditory cortex (AC) has been difficult to investigate. Here, using reversals of tonotopic gradients as the test case, we examined whether human ACs can be more precisely mapped by avoiding signals caused by large draining vessels near the pial surface, which bias blood-oxygen level dependent (BOLD) signals away from the actual sites of neuronal activity. Using ultra-high field (7T) fMRI and cortical depth analysis techniques previously applied in visual cortices, we sampled 1 mm isotropic voxels from different depths of AC during narrow-band sound stimulation with biologically relevant temporal patterns. At the group level, analyses that considered voxels from all cortical depths, but excluded those intersecting the pial surface, showed (a) the greatest statistical sensitivity in contrasts between activations to high vs. low frequency sounds and (b) the highest inter-subject consistency of phase-encoded continuous tonotopy mapping. Analyses based solely on voxels intersecting the pial surface produced the least consistent group results, even when compared to analyses based solely on voxels intersecting the white-matter surface where both signal strength and within-subject statistical power are weakest. However, no evidence was found for reduced within-subject reliability in analyses considering the pial voxels only. Our group results could, thus, reflect improved inter-subject correspondence of high and low frequency gradients after the signals from voxels near the pial surface are excluded. Using tonotopy analyses as the test case, our results demonstrate that when the major physiological and anatomical biases imparted by the vasculature are controlled, functional mapping of human ACs becomes more consistent from subject to subject than previously thought.

MR Fingerprinting (MRF) is a relatively new imaging framework capable of providing accurate and simultaneous quantification of multiple tissue properties for improved tissue characterization and disease diagnosis. While 2D MRF has been widely available, extending the method to 3D MRF has been an actively pursued area of research as a 3D approach can provide a higher spatial resolution and better tissue characterization with an inherently higher signal-to-noise ratio. However, 3D MRF with a high spatial resolution requires lengthy acquisition times, especially for a large volume, making it impractical for most clinical applications. In this study, a high-resolution 3D MR Fingerprinting technique, combining parallel imaging and deep learning, was developed for rapid and simultaneous quantification of T(1) and T(2) relaxation times. Parallel imaging was first applied along the partition-encoding direction to reduce the amount of acquired data. An advanced convolutional neural network was then integrated with the MRF framework to extract features from the MRF signal evolution for improved tissue characterization and accelerated mapping. A modified 3D-MRF sequence was also developed in the study to acquire data to train the deep learning model that can be directly applied to prospectively accelerate 3D MRF scans. Our results of quantitative T(1) and T(2) maps demonstrate that improved tissue characterization can be achieved using the proposed method as compared to prior methods. With the integration of parallel imaging and deep learning techniques, whole-brain (26 × 26 × 18 cm(3)) quantitative T(1) and T(2) mapping with 1-mm isotropic resolution were achieved in ~7 min. In addition, a ~7-fold improvement in processing time to extract tissue properties was also accomplished with the deep learning approach as compared to the standard template matching method. All of these improvements make high-resolution whole-brain quantitative MR imaging feasible for clinical applications.

Objectives: The neuroprotective effects of resveratrol against excitatory neurotoxicity have been associated with N-methyl-D-aspartate receptor (NMDAR) inhibition. This study examined the different...

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

T1-weighted image (T1WI) and T2-weighted image (T2WI) are the two routinely acquired magnetic resonance (MR) modalities that can provide complementary information for clinical and research usages. However, the relatively long acquisition time makes the acquired image vulnerable to motion artifacts. To speed up the imaging process, various algorithms have been proposed to reconstruct high-quality images from under-sampled k -space data. However, most of the existing algorithms only rely on mono-modality acquisition for the image reconstruction. In this paper, we propose to combine complementary MR acquisitions (i.e., T1WI and under-sampled T2WI particularly) to reconstruct the high-quality image (i.e., corresponding to the fully sampled T2WI). To the best of our knowledge, this is the first work to fuse multi-modal MR acquisitions through deep learning to speed up the reconstruction of a certain target image. Specifically, we present a novel deep learning approach, namely Dense-Unet, to accomplish the reconstruction task. The proposed Dense-Unet requires fewer parameters and less computation, while achieving promising performance. Our results have shown that Dense-Unet can reconstruct a three-dimensional T2WI volume in less than 10 s with an under-sampling rate of 8 for the k -space and negligible aliasing artifacts or signal-noise-ratio loss. Experiments also demonstrate excellent transferring capability of Dense-Unet when applied to the datasets acquired by different MR scanners. The above-mentioned results imply great potential of our method in many clinical scenarios.

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories worldwide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a mouse default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. RSN spatial specificity was enhanced in datasets acquired at higher field strength, with cryoprobes, in ventilated animals, and under medetomidine-isoflurane combination sedation. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

Recent studies suggest that neurodegenerative diseases could affect brain structure and function in disease-specific network patterns; however, how spontaneous activity affects structural covariance network (SC) is not clear. We hypothesized that hyper-excitability in Huntington disease (HD) disrupts the coordinated structural and functional connectivity, and treatment with memantine helps to reduce excitotoxicity and normalize the connectivity. MRI was conducted to measure somatosensory activation, resting-state functional-connectivity (rsFC), SC, amplitude of low frequency fluctuation (ALFF) and ALFF covariance (ALFFC) in the YAC128 mouse model of HD. We found somatosensory activation was unchanged but the subcortical ALFF was increased in HD mice, indicating subcortical but not cortical hyperactivity. The reduced sensorimotor rsFC but spared hippocampal and default mode networks in the HD mice was consistent with the more pronounced impairment in motor function compared with cognitive performance. The disease suppressed SC globally and reduced ALFFC in the basal ganglia network as well as its anti-correlation with the default mode network. By comparing these connectivity measures, we found that the originally coupled rsFC-SC relationship was impaired whereas SC-ALFFC correlation was increased by HD, suggesting disease facilitated covariation of brain volume and activity amplitude but not neural synchrony. The comparison with mono-synaptic axonal projection supports the hypothesis that rsFC, but not SC or ALFFC, is highly dependent on structural connectivity under healthy conditions. Treatment with memantine had a strong effect on normalizing the SC and reducing ALFF while slightly increasing other connectivity measures and restoring the rsFC-SC coupling, which is consistent with its effect on alleviating hyper-excitability and improving the coordinated neural growth. These results indicate that HD affects the cerebral structure–function relationship which could be partially reverted by NMDA antagonism. These connectivity measures provide unique insights into pathological and pharmaceutical effects in brain circuitry, and could be translatable biomarkers for evaluating drug effect and refining its efficacy.

T1-weighted image (T1WI) and T2-weighted image (T2WI) are the two routinely acquired Magnetic Resonance Imaging (MRI) protocols that provide complementary information for diagnosis. However, the total acquisition time of ~10 min yields the image quality vulnerable to artifacts such as motion. To speed up MRI process, various algorithms have been proposed to reconstruct high quality images from under-sampled k-space data. These algorithms only employ the information of an individual protocol (e.g., T2WI). In this paper, we propose to combine complementary MRI protocols (i.e., T1WI and under-sampled T2WI particularly) to reconstruct the high-quality image (i.e., fully-sampled T2WI). To the best of our knowledge, this is the first work to utilize data from different MRI protocols to speed up the reconstruction of a target sequence. Specifically, we present a novel deep learning approach, namely Dense-Unet, to accomplish the reconstruction task. The Dense-Unet requires fewer parameters and less computation, but achieves better performance. Our results have shown that Dense-Unet can reconstruct a 3D T2WI volume in less than 10 s, i.e., with the acceleration rate as high as 8 or more but with negligible aliasing artefacts and signal-noise-ratio (SNR) loss.

Garlic and its related products (such as black garlic) exhibit multiple biological functions and attributed to the presence of organo-sulphur compounds. The aim of this study was to investigate the inhibitory effects of garlic-derived organo-sulphur compounds [including diallyl sulphide (DAS), diallyl disulphide (DADS), diallyl trisulphide (DATS), S-allylcysteine (SAC), and S-allyl-L-cysteine sulphoxide (alliin)] on adipogenesis in 3T3-L1 adipocytes. The result indicated that DATS significantly decreased the intracellular triacylglycerol, oil red O-stained material (OROSM), and glycerol-3-phosphate dehydrogenase (GPDH) activity and significantly increased the adiponectin production in 3T3-L1 adipocytes. Real-time RT-PCR analysis showed that DATS decreased the gene levels of adipogenesis (C/EBPα, PPARγ, ACC, and FAS), fatty acid transport (aP2, CD36, and LPL), and adipocytokines (leptin, MCP-1, PAI-1, and resistin), and increased the gene levels of fatty acid oxidation (PGC-1β and UCP1) and adiponectin in 3T3-L1 adipocytes. DATS is capable of inhibiting adipogenesis in 3T3-L1 adipocytes possibly through regulation of gene levels of lipogenesis, lipolysis, and adipokines.

Auditory working memory (WM) processing in everyday acoustic environments depends on our ability to maintain relevant information online in our minds, and to suppress interference caused by competing incoming stimuli. A challenge in communication settings is that the relevant content and irrelevant inputs may emanate from a common source, such as a talkative conversationalist. An open question is how the WM system deals with such interference. Will the distracters become inadvertently filtered before processing for meaning because the primary WM operations deplete all available processing resources? Or are they suppressed post perceptually, through an active control process? We tested these alternative hypotheses by measuring magnetoencephalography (MEG), EEG, and functional MRI (fMRI) during a phonetic auditory continuous performance task. Contextual WM maintenance load was manipulated by adjusting the number of "filler" letter sounds in-between cue and target letter sounds. Trial-to-trial variability of pre- and post-stimulus activations in fMRI-informed cortical MEG/EEG estimates was analyzed within and across 14 subjects using generalized linear mixed effect (GLME) models. High contextual WM maintenance load suppressed left auditory cortex (AC) activations around 250-300 ms after the onset of irrelevant phonetic sounds. This effect coincided with increased 10-14 Hz alpha-range oscillatory functional connectivity between the left dorsolateral prefrontal cortex (DLPFC) and left AC. Suppression of AC responses to irrelevant sounds during active maintenance of the task context also correlated with increased pre-stimulus 7-15 Hz alpha power. Our results suggest that under high auditory WM load, irrelevant sounds are suppressed through a "late" active suppression mechanism, which prevents short-term consolidation of irrelevant information without affecting the initial screening of potentially meaningful stimuli. The results also suggest that AC alpha oscillations play an inhibitory role during auditory WM processing.

This study aimed to investigate the antioxidant and anticancer effects of ethanolic and aqueous extracts of the roots of Ficus beecheyana (EERFB and AERFB) and their phenolic components. In this study, total phenolic content and antioxidant activity of EERFB were higher than those of AERFB. Major phenolic compounds in the extracts were gallic acid, p-hydroxybenzoic acid, caffeic acid, chlorogenic acid, p-coumaric acid, and rutin; which were identified by high-performance liquid chromatography. Flow cytometric analysis of HL-60 cells exposed to EERFB showed that the percentage of apoptotic cells increased in a dose-dependent manner. EERFB treatment resulted in the loss of mitochondrial membrane potential and induced the apoptosis of HL-60 cells through a Fas- and mitochondrial-mediated pathway. Finally, pretreatment with general caspase-9/-3 inhibitors prevented EERFB from inhibiting cell viability in HL-60 cells. Our finding suggests that EERFB is an agent that may have antioxidant activity and inhibit the growth of cancer cells.

2-[{[2-(Dimethylamino)ethyl]imino}methyl]-6-methoxyphenol (LH) is a potential tetradentate monoanionic N2O2 chelator; however, this precursor coordinates to cobalt(II) centres in two ways, as neutral bidentate-NO and as terdentate-N2O, along with a pseudohalide, like thiocyanate and azide, to afford [Co(LH)2(NCS)]NO3 (1) and [Co(LH)2(N3)]NO3 (2), respectively. Both the complexes are characterized by spectroscopic (IR, UV–Vis) analysis, thermal and redox studies. The room temperature magnetic moments for 1 and 2 are 4.91 and 4.93 B.M, respectively. Single crystal X-ray diffraction analysis confirms the distorted octahedral geometry around Co(II). These two complexes (1 and 2) inhibit the cell growth of human lung carcinoma cells (A549 cells), human colorectal carcinoma cells (COLO 205 cells), human hepatocellular carcinoma cells (PLC5 cells) and human fibroblasts cells (NIH3T3). Complex 2 shows a higher inhibitory activity, with 46.00 ± 1.09 μM IC50 in human colorectal carcinoma cells (COLO 205 cells).

Based on the infamous left-lateralized neglect syndrome, one might hypothesize that the dominating right parietal cortex has a bilateral representation of space, whereas the left parietal cortex represents only the contralateral right hemispace. Whether this principle applies to human auditory attention is not yet fully clear. Here, we explicitly tested the differences in cross-hemispheric functional coupling between the intraparietal sulcus (IPS) and auditory cortex (AC) using combined magnetoencephalography (MEG), EEG, and functional MRI (fMRI). Inter-regional pairwise phase consistency (PPC) was analyzed from data obtained during dichotic auditory selective attention task, where subjects were in 10-s trials cued to attend to sounds presented to one ear and to ignore sounds presented in the opposite ear. Using MEG/EEG/fMRI source modeling, parietotemporal PPC patterns were (a) mapped between all AC locations vs. IPS seeds and (b) analyzed between four anatomically defined AC regions-of-interest (ROI) vs. IPS seeds. Consistent with our hypothesis, stronger cross-hemispheric PPC was observed between the right IPS and left AC for attended right-ear sounds, as compared to PPC between the left IPS and right AC for attended left-ear sounds. In the mapping analyses, these differences emerged at 7–13 Hz, i.e., at the theta to alpha frequency bands, and peaked in Heschl's gyrus and lateral posterior non-primary ACs. The ROI analysis revealed similarly lateralized differences also in the beta and lower theta bands. Taken together, our results support the view that the right parietal cortex dominates auditory spatial attention.

Neuronal activation sequence information is essential for understanding brain functions. Extracting such timing information from blood oxygenation level dependent (BOLD) fMRI is confounded by interregional neurovascular differences and poorly understood relations between BOLD and electrophysiological response delays. Here, we recorded whole-head BOLD fMRI at 100 ms resolution and magnetoencephalography (MEG) during a visuomotor reaction-time task. Both methods detected the same activation sequence across five regions, from visual towards motor cortices, with linearly correlated interregional BOLD and MEG response delays. The smallest significant interregional BOLD delay was 100 ms; all delays ≥ 400 ms were significant. Switching the order of external events reversed the sequence of BOLD activations, indicating that interregional neurovascular differences did not confound the results. This may open new avenues for using fMRI to follow rapid activation sequences in the brain.

The acquisition time of BOLD contrast functional MRI (fMRI) data with whole-brain coverage typically requires a sampling rate of one volume in 1–3 s. Although the volumetric sampling time of a few seconds is adequate for measuring the sluggish hemodynamic response (HDR) to neuronal activation, faster sampling of fMRI might allow for monitoring of rapid physiological fluctuations and detection of subtle neuronal activation timing information embedded in BOLD signals. Previous studies utilizing a highly accelerated volumetric MR inverse imaging (InI) technique have provided a sampling rate of one volume per 100 ms with 5 mm spatial resolution. Here, we propose a novel modification of this technique, the echo-shifted InI, which allows TE to be longer than TR, to measure BOLD fMRI at an even faster sampling rate of one volume per 25 ms with whole-brain coverage. Compared with conventional EPI, echo-shifted InI provided an 80-fold speedup with similar spatial resolution and less than 2-fold temporal SNR loss. The capability of echo-shifted InI to detect HDR timing differences was tested empirically. At the group level (n = 6), echo-spaced InI was able to detect statistically significant HDR timing differences of as low as 50 ms in visual stimulus presentation. At the level of individual subjects, significant differences in HDR timing were detected for 400 ms stimulus-onset differences. Our results also show that the temporal resolution of 25 ms is necessary for maintaining the temporal detecting capability at this level. With the capabilities of being able to distinguish the timing differences in the millisecond scale, echo-shifted InI could be a useful fMRI tool for obtaining temporal information at a time scale closer to that of neuronal dynamics.

The reactions of a tridentate hydrazone ligand, N′-[1-(pyridin-2-yl)ethylidene]acetohydrazide (LH), derived from condensation of 2-acetylpyridine with acetic hydrazide, with M(NO3)2·nH2O [M = Cu, Co and Ni] in the presence of thiocyanate afford three end-to-end zig-zag coordination polymers, [CuLH(NO3)(μ1,3-NCS)]n·nH2O (1), [CoLH(NCS)(μ1,3-NCS)]n (2) and [NiLH(NCS)(μ1,3-NCS)]n (3) (where LH = CH3C( O)–N–N CCH3C5H4N). Single-crystal X-ray structural determination studies reveal that in all the complexes, the hydrazone ligand in the neutral keto form (LH) coordinates a MII ion that is bridged to two neighboring metal centers by SCN− anions, generating a 1-D helical coordination chain. In 1, the CuII atom adopts a distorted tetragonal bipyramid geometry whereas in 2 and 3, the central CoII or NiII atom possesses into a distorted octahedral environment. All the aforementioned compounds have been fully characterized by elemental analysis, IR, UV–Vis and EPR spectra. Variable temperature magnetic susceptibility measurement of 1 accounts the weak antiferromagnetic interactions whereas 2 shows single-ion anisotropy. Compound 3 is well described as a 3-D ferromagnetic. The inhibitory effects of all the complexes on the cell population growth of human lung carcinoma cells (A549 cells), human colorectal carcinoma cells (COLO 205 cells and HT-29 cells), and human hepatocellular carcinoma cells (PLC5 cells) were determined by MTT assays.

The objective of this study was to investigate the anticancer activity of caffeate derivatives in human cancer cells. Our results demonstrate that caffeate derivatives decreased the population growth of COLO 205, assessed using the MTT assay. However, caffeate derivatives, at the concentrations used in this study (0–250 μM) did not affect the viability of HepG2, Huh7, PLC5, and SK-Hep-1 cells. Flow cytometric analysis of COLO 205 cells exposed to decyl caffeate showed that the number of apoptotic cells increased in a time- and dose-dependent manner. Western blot analysis revealed that decyl caffeate stimulated an increase in protein expression levels of p53, Fas, FasL, AIF, and Apaf-1. Additionally, treatment with decyl caffeate changed the expression levels of Bcl-2 family members and subsequently induced the activation of caspase-12, caspase-9, and caspase-3, which was followed by cleavage of PARP. Our findings highlight the chemopreventive potential of decyl caffeate.

Spatially focal source estimates for magnetoencephalography (MEG) and electroencephalogra- phy (EEG) data can be obtained by imposing a minimum ' 1 -norm constraint on the distribution of the source currents. Anatomical information about the expected locations and orientations of the sources can be included in the source models. In particular, the sources can be assumed to be oriented perpendicular to the cortical surface. We introduce a minimum ' 1 -norm estimation source modeling approach with loose orientation constraints (' 1 LOC), which integrates the estimation of the orientation, location, and strength of the source currents into a cost function to jointly model the residual error and the ' 1 -norm of the source estimates. Evaluation with simulated MEG data indicated that the ' 1 LOC method can provide low spatial dispersion, high localization accuracy, and high source detection rates. Application to somato- sensory and auditory MEG data resulted in physiologically reasonable source distributions. The proposed ' 1 LOC method appears useful for incorporating anatomical information about the source orientations into sparse source estimation of MEG data. Hum Brain Mapp 34:2190-2201, 2013. V C 2012 Wiley Periodicals, Inc.