Next-generation MRI scanner designed for ultra-high-resolution human brain imaging at 7 Tesla.

To increase granularity in human neuroimaging science, we designed and built a next-generation 7 Tesla magnetic resonance imaging scanner to reach ultra-high resolution by implementing several advances in hardware. To improve spatial encoding and increase the image signal-to-noise ratio, we developed a head-only asymmetric gradient coil (200 mT m-1, 900 T m-1s-1) with an additional third layer of windings. We integrated a 128-channel receiver system with 64- and 96-channel receiver coil arrays to boost signal in the cerebral cortex while reducing g-factor noise to enable higher accelerations. A 16-channel transmit system reduced power deposition and improved image uniformity. The scanner routinely performs functional imaging studies at 0.35-0.45 mm isotropic spatial resolution to reveal cortical layer functional activity, achieves high angular resolution in diffusion imaging and reduces acquisition time for both functional and structural imaging.

Specifically adsorbed ferrous ions modulate interfacial affinity for high-rate ammonia electrosynthesis from nitrate in neutral media.

The electrolysis of nitrate reduction to ammonia (NRA) is promising for obtaining value-added chemicals and mitigating environmental concerns. Recently, catalysts with high-performance ammonia synthesis from nitrate has been achieved under alkaline or acidic conditions. However, NRA in neutral solution still suffers from the low yield rate and selectivity of ammonia due to the low binding affinity and nucleophilicity of NO3-. Here, we confirmed that the in-situ-generated Fe(II) ions existed as specifically adsorbed cations in the inner Helmholtz plane (IHP) with a low redox potential. Inspired by this, a strategy (Fe-IHP strategy) was proposed to enhance NRA activity by tuning the affinity of the electrode-electrolyte interface. The specifically adsorbed Fe(II) ions [SA-Fe(II)] greatly alleviated the electrostatic repulsion around the interfaceresulting in a 10-fold lower in the adsorption-free energy of NO3- when compared to the case without SA-Fe(II). Meanwhile, the modulated interface accelerated the kinetic mass transfer process by 25 folds compared to the control. Under neutral conditions, a Faraday efficiency of 99.6%, a selectivity of 99%, and an extremely high NH3 yield rate of 485.8 mmol h-1 g-1 FeOOH were achieved. Theoretical calculations and in-situ Raman spectroscopy confirmed the electron-rich state of the SA-Fe(II) donated to p orbitals of N atom and favored the hydrogenation of *NO to *NOH for promoting the formation of high-selectivity ammonia. In sum, these findings complement the textbook on the specific adsorption of cations and provide insights into the design of low-cost NRA catalysts with efficient ammonia synthesis.

Electrophysiological Mechanisms and Validation of Ferritin-Based Magnetogenetics for Remote Control of Neurons.

Magnetogenetics was developed to remotely control genetically targeted neurons. A variant of magnetogenetics uses magnetic fields to activate transient receptor potential vanilloid (TRPV) channels when coupled with ferritin. Stimulation with static or radiofrequency (RF) magnetic fields of neurons expressing these channels induces Ca2+ transients and modulates behavior. However, the validity of ferritin-based magnetogenetics has been questioned due to controversies surrounding the underlying mechanisms and deficits in reproducibility. Here, we validated the magnetogenetic approach FeRIC using electrophysiological and imaging techniques. Previously, interference from RF stimulation rendered patch-clamp recordings inaccessible for magnetogenetics. We solved this limitation for FeRIC, and we studied the bioelectrical properties of neurons expressing TRPV4 (non-selective cation channel) and TMEM16A (chloride permeable channel) coupled to ferritin (FeRIC channels) under RF stimulation. We used cultured neurons obtained from rat hippocampus of either sex. We show that RF decreases the membrane resistance and depolarizes the membrane potential in neurons expressing TRPV4FeRIC RF does not directly trigger action potential firing but increases the neuronal basal spiking frequency. In neurons expressing TMEM16AFeRIC, RF decreases the membrane resistance, hyperpolarizes the membrane potential, and decreases the spiking frequency. Additionally, we corroborated the previously described biochemical mechanism responsible for RF-induced activation of ferritin-coupled ion channels. We solved an enduring problem for ferritin-based magnetogenetics, obtaining direct electrophysiological evidence of RF-induced activation of ferritin-coupled ion channels. We found that RF does not yield instantaneous changes in neuronal membrane potentials. Instead, RF produces responses that are long-lasting and moderate, but effective in controlling the bioelectrical properties of neurons.Significance statement Cell-specific and non-invasive stimulation can be a powerful tool for modulating neuronal circuits and functions. Magnetogenetic techniques that are fully genetically encoded provide such tools. However, there have been significant controversies surrounding the efficacy and underlying mechanisms of magnetogenetics. Here, we demonstrate that by employing a fully genetically encoded magnetogenetic approach called FeRIC, we can modulate neuronal voltage, inducing either depolarization or hyperpolarization through the activation of ion channels with magnetic fields; we validate this modulation mechanism with the gold-standard patch-clamp technique. We further discover that this neuronal modulation is not achieved by instantaneously triggering action potentials as previously assumed, but by modulating neuronal excitability.

Interpretable deep learning in single-cell omics.

MOTIVATION: Single-cell omics technologies have enabled the quantification of molecular profiles in individual cells at an unparalleled resolution. Deep learning, a rapidly evolving sub-field of machine learning, has instilled a significant interest in single-cell omics research due to its remarkable success in analysing heterogeneous high-dimensional single-cell omics data. Nevertheless, the inherent multi-layer nonlinear architecture of deep learning models often makes them 'black boxes' as the reasoning behind predictions is often unknown and not transparent to the user. This has stimulated an increasing body of research for addressing the lack of interpretability in deep learning models, especially in single-cell omics data analyses, where the identification and understanding of molecular regulators are crucial for interpreting model predictions and directing downstream experimental validations. RESULTS: In this work, we introduce the basics of single-cell omics technologies and the concept of interpretable deep learning. This is followed by a review of the recent interpretable deep learning models applied to various single-cell omics research. Lastly, we highlight the current limitations and discuss potential future directions.

Multi-task learning from multimodal single-cell omics with Matilda.

Multimodal single-cell omics technologies enable multiple molecular programs to be simultaneously profiled at a global scale in individual cells, creating opportunities to study biological systems at a resolution that was previously inaccessible. However, the analysis of multimodal single-cell omics data is challenging due to the lack of methods that can integrate across multiple data modalities generated from such technologies. Here, we present Matilda, a multi-task learning method for integrative analysis of multimodal single-cell omics data. By leveraging the interrelationship among tasks, Matilda learns to perform data simulation, dimension reduction, cell type classification, and feature selection in a single unified framework. We compare Matilda with other state-of-the-art methods on datasets generated from some of the most popular multimodal single-cell omics technologies. Our results demonstrate the utility of Matilda for addressing multiple key tasks on integrative multimodal single-cell omics data analysis. Matilda is implemented in Pytorch and is freely available from https://github.com/PYangLab/Matilda.

Quantitative susceptibility mapping in the brain reflects spatial expression of genes involved in iron homeostasis and myelination.

Quantitative susceptibility mapping (QSM) is an MRI modality used to non-invasively measure iron content in the brain. Iron exhibits a specific anatomically varying pattern of accumulation in the brain across individuals. The highest regions of accumulation are the deep grey nuclei, where iron is stored in paramagnetic molecule ferritin. This form of iron is considered to be what largely contributes to the signal measured by QSM in the deep grey nuclei. It is also known that QSM is affected by diamagnetic myelin contents. Here, we investigate spatial gene expression of iron and myelin related genes, as measured by the Allen Human Brain Atlas, in relation to QSM images of age-matched subjects. We performed multiple linear regressions between gene expression and the average QSM signal within 34 distinct deep grey nuclei regions. Our results show a positive correlation (p < .05, corrected) between expression of ferritin and the QSM signal in deep grey nuclei regions. We repeated the analysis for other genes that encode proteins thought to be involved in the transport and storage of iron in the brain, as well as myelination. In addition to ferritin, our findings demonstrate a positive correlation (p < .05, corrected) between the expression of ferroportin, transferrin, divalent metal transporter 1, several gene markers of myelinating oligodendrocytes, and the QSM signal in deep grey nuclei regions. Our results suggest that the QSM signal reflects both the storage and active transport of iron in the deep grey nuclei regions of the brain.

Ensemble deep learning of embeddings for clustering multimodal single-cell omics data.

MOTIVATION: Recent advances in multimodal single-cell omics technologies enable multiple modalities of molecular attributes, such as gene expression, chromatin accessibility, and protein abundance, to be profiled simultaneously at a global level in individual cells. While the increasing availability of multiple data modalities is expected to provide a more accurate clustering and characterization of cells, the development of computational methods that are capable of extracting information embedded across data modalities is still in its infancy. RESULTS: We propose SnapCCESS for clustering cells by integrating data modalities in multimodal single-cell omics data using an unsupervised ensemble deep learning framework. By creating snapshots of embeddings of multimodality using variational autoencoders, SnapCCESS can be coupled with various clustering algorithms for generating consensus clustering of cells. We applied SnapCCESS with several clustering algorithms to various datasets generated from popular multimodal single-cell omics technologies. Our results demonstrate that SnapCCESS is effective and more efficient than conventional ensemble deep learning-based clustering methods and outperforms other state-of-the-art multimodal embedding generation methods in integrating data modalities for clustering cells. The improved clustering of cells from SnapCCESS will pave the way for more accurate characterization of cell identity and types, an essential step for various downstream analyses of multimodal single-cell omics data. AVAILABILITY AND IMPLEMENTATION: SnapCCESS is implemented as a Python package and is freely available from https://github.com/PYangLab/SnapCCESS under the open-source license of GPL-3. The data used in this study are publicly available (see section 'Data availability').

Multiphoton simultaneous multislice imaging.

PURPOSE: To develop multiphoton excitation techniques for simultaneous multislice (SMS) imaging and evaluate their performance and specific absorption rate (SAR) benefit. To improve multiphoton SMS reconstruction quality with a novel CAIPIRINHA (controlled aliasing in parallel imaging results in higher acceleration) design. THEORY AND METHODS: When a conventional single-slice RF field is applied together with an oscillating gradient field, the two can combine to generate multiphoton excitation at multiple discrete spatial locations. Because the conventional RF is reused at multiple spatial locations, multiphoton excitation offers reduced SAR for SMS applications. CAIPIRINHA shifts are often used to improve parallel-imaging acceleration. Interestingly, CAIPIRINHA-type shifts can be obtained for multiphoton SMS by updating the oscillating gradient phase at every phase encode. In this work, both a gradient-echo and a spin-echo sequence with multiphoton CAIPIRINHA-SMS excitation pulses are implemented for in vivo human imaging at 3 T. RESULTS: For three slices, multiphoton SMS provides a 51% reduction in SAR compared with conventional superposition SMS, whereas for five slices, SAR is reduced by 66%. Multiphoton SMS outperforms PINS (power independent of number of slices) and MultiPINS in terms of SAR reduction especially when the pulse duration is short, slices are thin, and/or the slice spacing is large. A custom CAIPIRINHA phase-encoding design for multiphoton SMS significantly improves reconstruction quality. CONCLUSION: Multiphoton SMS excitation can be obtained by combining conventional single-slice RF pulses with an oscillating gradient and offers significant SAR benefits compared with conventional superposition SMS. A novel CAIPIRINHA design allows higher multiband factors for multiphoton SMS imaging.

Any-nucleus distributed active programmable transmit coil.

PURPOSE: There are 118 known elements. Nearly all of them have NMR active isotopes and at least 39 different nuclei have biological relevance. Despite this, most of today's MRI is based on only one nucleus-1H. To facilitate imaging all potential nuclei, we present a single transmit coil able to excite arbitrary nuclei in human-scale MRI. THEORY AND METHODS: We present a completely new type of RF coil, the Any-nucleus Distributed Active Programmable Transmit Coil (ADAPT Coil), with fast switches integrated into the structure of the coil to allow it to operate at any relevant frequency. This coil eliminates the need for the expensive traditional RF amplifier by directly converting direct current (DC) power into RF magnetic fields with frequencies chosen by digital control signals sent to the switches. Semiconductor switch imperfections are overcome by segmenting the coil. RESULTS: Circuit simulations demonstrated the effectiveness of the ADAPT Coil approach, and a 9 cm diameter surface ADAPT Coil was implemented. Using the ADAPT Coil, 1H, 23Na, 2H, and 13C phantom images were acquired, and 1H and 23Na ex vivo images were acquired. To excite different nuclei, only digital control signals were changed, which can be programmed in real time. CONCLUSION: The ADAPT Coil presents a low-cost, scalable, and efficient method for exciting arbitrary nuclei in human-scale MRI. This coil concept provides further opportunities for scaling, programmability, lowering coil costs, lowering dead-time, streamlining multinuclear MRI workflows, and enabling the study of dozens of biologically relevant nuclei.

Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group.

This article provides recommendations for implementing QSM for clinical brain research. It is a consensus of the International Society of Magnetic Resonance in Medicine, Electro-Magnetic Tissue Properties Study Group. While QSM technical development continues to advance rapidly, the current QSM methods have been demonstrated to be repeatable and reproducible for generating quantitative tissue magnetic susceptibility maps in the brain. However, the many QSM approaches available have generated a need in the neuroimaging community for guidelines on implementation. This article outlines considerations and implementation recommendations for QSM data acquisition, processing, analysis, and publication. We recommend that data be acquired using a monopolar 3D multi-echo gradient echo (GRE) sequence and that phase images be saved and exported in Digital Imaging and Communications in Medicine (DICOM) format and unwrapped using an exact unwrapping approach. Multi-echo images should be combined before background field removal, and a brain mask created using a brain extraction tool with the incorporation of phase-quality-based masking. Background fields within the brain mask should be removed using a technique based on SHARP or PDF, and the optimization approach to dipole inversion should be employed with a sparsity-based regularization. Susceptibility values should be measured relative to a specified reference, including the common reference region of the whole brain as a region of interest in the analysis. The minimum acquisition and processing details required when reporting QSM results are also provided. These recommendations should facilitate clinical QSM research and promote harmonized data acquisition, analysis, and reporting.

Melatonin attenuates diabetic cardiomyopathy by increasing autophagy of cardiomyocytes via regulation of VEGF-B/GRP78/PERK signaling pathway.

AIMS: Diabetic cardiomyopathy (DCM) is a major cause of mortality in patients with diabetes, and the potential strategies for treating DCM are insufficient. Melatonin (Mel) has been shown to attenuate DCM, however, the underlying mechanism remains unclear. The role of vascular endothelial growth factor-B (VEGF-B) in DCM is little known. In present study, we aimed to investigate whether Mel alleviated DCM via regulation of VEGF-B and explored its underlying mechanisms. METHODS AND RESULTS: We found that Mel significantly alleviated cardiac dysfunction and improved autophagy of cardiomyocytes in type 1 diabetes mellitus (T1DM) induced cardiomyopathy mice. VEGF-B was highly expressed in DCM mice in comparison with normal mice, and its expression was markedly reduced after Mel treatment. Mel treatment diminished the interaction of VEGF-B and Glucose-regulated protein 78 (GRP78) and reduced the interaction of GRP78 and protein kinase RNA -like ER kinase (PERK). Furthermore, Mel increased phosphorylation of PERK and eIF2α, then up-regulated the expression of ATF4. VEGF-B-/- mice imitated the effect of Mel on wild type diabetic mice. Interestingly, injection with Recombinant adeno-associated virus serotype 9 (AAV9)-VEGF-B or administration of GSK2656157 (GSK), an inhibitor of phosphorylated PERK abolished the protective effect of Mel on DCM. Furthermore, rapamycin, an autophagy agonist displayed similar effect with Mel treatment; while 3-Methyladenine (3-MA), an autophagy inhibitor neutralized the effect of Mel on high glucose-treated neonatal rat ventricular myocytes. CONCLUSIONS: These results demonstrated that Mel attenuated DCM via increasing autophagy of cardiomyocytes, and this cardio-protective effect of Mel was dependent on VEGF-B/GRP78/PERK signaling pathway.

Liver transplantation for pediatric patients with congenital heart disease: A single-center study in mainland China.

BACKGROUND: Liver transplantation (LT) is a serious cardiovascular stressor for patients with end-stage liver disease (ESLD). Data on the effects of cardiovascular diseases on pediatric LT is limited. No study on LT for pediatric patients with ESLD combined with congenital heart disease (CHD) has been reported from mainland China. METHODS: A total of 1005 patients were included in this study. The Kaplan-Meier method with log-rank testing was used to evaluate survival outcomes between groups. Univariable and multivariable Cox regression models were used to determine the risk factors for patient and graft survival. RESULTS: The most common indication for LT was biliary atresia (BA 90.3%). The prevalence of CHD was 3.8% (38). 42 CHD were found in 38 patients. The incidence of death and graft loss was more common in the CHD group than in the no-CHD group (13.2% vs. 5.0%, p = .045 and 15.8% vs. 6.2%, p = .019, respectively). The 5-year patient survival and graft survival in the CHD group versus the no-CHD group was 86.8% versus 94.7% (log-rank p = .022) and 84.2% versus 93.5% (log-rank p = .015), respectively. No significant differences were observed in re-transplantation, hepatic artery thrombosis (HAT), and portal vein thrombosis (PVT). After adjusting for age, BMI, etiology of LT, and other confounding factors, we can still find that the presence of CHD was associated with patient and graft survival after LT. CONCLUSION: The presence of CHD was associated with higher mortality and lower graft survival after LT. If possible, the cardiac defects should be addressed prior to LT.

Quercetin induces ferroptosis by inactivating mTOR/S6KP70 pathway in oral squamous cell carcinoma.

Although recent studies increasingly suggest the potential anti-cancer effect of quercetin, the exact underlying mechanism remains poorly demonstrated in oral squamous cell carcinoma (oSCC). Therefore, our research explored the impacts of quercetin on the ferroptosis and mTOR/S6KP70 axis in oSCC cell lines. After treating oSCC cells with quercetin or indicated compounds and transfection with SLC7A11- or S6KP70-overexpressing plasmid, cell viability was detected by CCK-8 assay. The level of ferroptosis in oSCC cells was assessed by measuring ROS and GSH levels. The activation of mTOR/S6KP70 axis was assessed by Western blotting. Quercetin promoted ferroptosis in an mTOR/S6KP70-dependent manner to inhibit tumor growth in oSCC cells. Mechanistically, we revealed that quercetin induced lipid peroxidation and reduced GSH levels by repressing SLC7A11 expression in oSCC cells. Specifically, the effects of quercetin on ferroptosis and mTOR and S6KP70 phosphorylation were partially blocked by both mTOR agonist and S6KP70 overexpression. Moreover, mTOR inhibitor promoted ferroptosis in quercetin-treated oSCC cells. Our findings showed that ferroptosis may be a new anti-tumor mechanism of quercetin. Additionally, we identified that quercetin can target mTOR/S6KP70 cascade to inhibit the growth of oSCC cells.

SPI1 involvement in malignant melanoma pathogenesis by regulation of HK2 through the AKT1/mTOR pathway.

Spi-1 proto-oncogene (SPI1) plays a vital role in carcinogenesis. Our work aimed to investigate the potential regulatory mechanism of SPI1 in melanoma. The mRNA and protein levels were measured via qRT-PCR and Western blotting. Cell viability was assessed by CCK-8 assay. The target relationship between SPI1 and hexokinase 2 (HK2) was determined using dual-luciferase reporter detection. ChIP was conducted to confirm the targeted relationship between SPI1 and the HK2 promoter. Immunohistochemistry analysis was conducted to measure the positive cell number of SPI1 and HK2 in melanoma tissues. The cell migration abilities were determined using a wound healing assay. Glucose consumption, pyruvate dehydrogenase activity, lactate production and ATP levels were measured to assess glycolysis. SPI1 transcription in melanoma cells and tissues was dramatically higher than that in adjacent normal tissues and epidermal melanocyte HEMa-LP, respectively. Knockdown of SPI1 restrained cell viability, metastasis and glycolysis in melanoma cells. SPI1 directly targeted HK2, and knockdown of SPI1 repressed HK2 expression. Overexpression of HK2 weakened the inhibitory effects of SPI1 knockdown on the viability, metastasis and glycolysis of melanoma cells. The serine-threonine kinase 1 (AKT1)/mammalian target of rapamycin (mTOR) axis is involved in melanoma progression. SPI1 knockdown restrained melanoma cell proliferation, metastasis and glycolysis by regulating the AKT1/mTOR pathway.

The diamagnetic component map from quantitative susceptibility mapping (QSM) source separation reveals pathological alteration in Alzheimer's disease-driven neurodegeneration.

A sensitive and accurate imaging technique capable of tracking the disease progression of Alzheimer's Disease (AD) driven amnestic dementia would be beneficial. A currently available method for pathology detection in AD with high accuracy is Positron Emission Tomography (PET) imaging, despite certain limitations such as low spatial resolution, off-targeting error, and radiation exposure. Non-invasive MRI scanning with quantitative magnetic susceptibility measurements can be used as a complementary tool. To date, quantitative susceptibility mapping (QSM) has widely been used in tracking deep gray matter iron accumulation in AD. The present work proposes that by compartmentalizing quantitative susceptibility into paramagnetic and diamagnetic components, more holistic information about AD pathogenesis can be acquired. Particularly, diamagnetic component susceptibility (DCS) can be a powerful indicator for tracking protein accumulation in the gray matter (GM), demyelination in the white matter (WM), and relevant changes in the cerebrospinal fluid (CSF). In the current work, voxel-wise group analysis of the WM and the CSF regions show significantly lower |DCS| (the absolute value of DCS) value for amnestic dementia patients compared to healthy controls. Additionally, |DCS| and τ PET standardized uptake value ratio (SUVr) were found to be associated in several GM regions typically affected by τ deposition in AD. Therefore, we propose that the separated diamagnetic susceptibility can be used to track pathological neurodegeneration in different tissue types and regions of the brain. With the initial evidence, we believe the usage of compartmentalized susceptibility demonstrates substantive potential as an MRI-based technique for tracking AD-driven neurodegeneration.

High angular resolution susceptibility imaging and estimation of fiber orientation distribution functions in primate brain.

Uncovering brain-tissue microstructure including axonal characteristics is a major neuroimaging research focus. Within this scope, anisotropic properties of magnetic susceptibility in white matter have been successfully employed to estimate primary axonal trajectories using mono-tensorial models. However, anisotropic susceptibility has not yet been considered for modeling more complex fiber structures within a voxel, such as intersecting bundles, or an estimation of orientation distribution functions (ODFs). This information is routinely obtained by high angular resolution diffusion imaging (HARDI) techniques. In applications to fixed tissue, however, diffusion-weighted imaging suffers from an inherently low signal-to-noise ratio and limited spatial resolution, leading to high demands on the performance of the gradient system in order to mitigate these limitations. In the current work, high angular resolution susceptibility imaging (HARSI) is proposed as a novel, phase-based methodology to estimate ODFs. A multiple gradient-echo dataset was acquired in an entire fixed chimpanzee brain at 61 orientations by reorienting the specimen in the magnetic field. The constant solid angle method was adapted for estimating phase-based ODFs. HARDI data were also acquired for comparison. HARSI yielded information on whole-brain fiber architecture, including identification of peaks of multiple bundles that resembled features of the HARDI results. Distinct differences between both methods suggest that susceptibility properties may offer complementary microstructural information. These proof-of-concept results indicate a potential to study the axonal organization in post-mortem primate and human brain at high resolution.

Direct localization and delineation of human pedunculopontine nucleus based on a self-supervised magnetic resonance image super-resolution method.

The pedunculopontine nucleus (PPN) is a small brainstem structure and has attracted attention as a potentially effective deep brain stimulation (DBS) target for the treatment of Parkinson's disease (PD). However, the in vivo location of PPN remains poorly described and barely visible on conventional structural magnetic resonance (MR) images due to a lack of high spatial resolution and tissue contrast. This study aims to delineate the PPN on a high-resolution (HR) atlas and investigate the visibility of the PPN in individual quantitative susceptibility mapping (QSM) images. We combine a recently constructed Montreal Neurological Institute (MNI) space unbiased QSM atlas (MuSus-100), with an implicit representation-based self-supervised image super-resolution (SR) technique to achieve an atlas with improved spatial resolution. Then guided by a myelin staining histology human brain atlas, we localize and delineate PPN on the atlas with improved resolution. Furthermore, we examine the feasibility of directly identifying the approximate PPN location on the 3.0-T individual QSM MR images. The proposed SR network produces atlas images with four times the higher spatial resolution (from 1 to 0.25 mm isotropic) without a training dataset. The SR process also reduces artifacts and keeps superb image contrast for further delineating small deep brain nuclei, such as PPN. Using the myelin staining histological atlas as guidance, we first identify and annotate the location of PPN on the T1-weighted (T1w)-QSM hybrid MR atlas with improved resolution in the MNI space. Then, we relocate and validate that the optimal targeting site for PPN-DBS is at the middle-to-caudal part of PPN on our atlas. Furthermore, we confirm that the PPN region can be identified in a set of individual QSM images of 10 patients with PD and 10 healthy young adults. The contrast ratios of the PPN to its adjacent structure, namely the medial lemniscus, on images of different modalities indicate that QSM substantially improves the visibility of the PPN both in the atlas and individual images. Our findings indicate that the proposed SR network is an efficient tool for small-size brain nucleus identification. HR QSM is promising for improving the visibility of the PPN. The PPN can be directly identified on the individual QSM images acquired at the 3.0-T MR scanners, facilitating a direct targeting of PPN for DBS surgery.

Estrogen ameliorates sepsis-induced vascular hyporeactivity in thoracic aorta of female rats via permissive effect of GRα expression.

OBJECTIVE: Estrogen is correlated to the lower mortality and disease severity of female than that of male, which indicates the potential therapeutic role of estrogen supplement therapy in sepsis. The structure of Daidzein is similar to that of 17ß estradiol (E2), an estrogen in human body, causing the exogenous Daidzein can interact with estrogen receptor as well as E2 in the body. We aim to explore the therapeutic role of estrogen in sepsis-induced vascular dysfunction. Also, we wonder if estrogen regulates blood pressure via glucocorticoid-mediated vascular reactivity. METHODS: Female SD rats received ovariectomy (OVX) to induce estrogen deficiency. After 12 weeks of administration, cecal ligation and puncture (CLP) was used to establish the in vivo model of sepsis. Lipopolysaccharide (LPS) was used to construct the in vitro model of sepsis in vascular smooth muscle cells (VSMCs). E2 and Daidzein were used for estrogen supplement therapy. RESULTS: E2 and Daidzein significantly inhibited inflammation infiltration and histopathological injury in thoracic aorta in the rat model with CLP. E2 and Daidzein improved carotid pressure and vascular hyporeactivity in sepsis rats with OVX. Importantly, E2 and Daidzein promoted glucocorticoid permissive action and increased glucocorticoid receptor α (GRα) expression in thoracic aorta smooth muscle cells. E2 and Daidzein upregulated GRα, and inhibits cytokine production, proliferative phenotype and cell migration in LPS-induced VSMCs. CONCLUSION: Estrogen improved vascular hyporeactivity in thoracic aorta induced by sepsis via permissive effect of GRα expression.

An improved asymmetric susceptibility tensor imaging model with frequency offset correction.

PURPOSE: To improve susceptibility tensor imaging (STI) reconstruction using the asymmetric STI model with the correction of non-bulk-magnetic-susceptibility (NBMS) effects. METHOD: A frequency offset term was introduced into the asymmetric STI model to account for the bias between measured MRI frequency signals and conventional susceptibility tensor models because of NBMS contributions. Experiments were conducted to compare the proposed model with conventional STI, conventional STI with the proposed frequency offset correction, and asymmetric STI on simulation, ex vivo mouse brain, and in vivo human brain data. RESULTS: In the simulation where NBMS contributions are head rotation-invariant, the proposed method achieves the lowest errors in mean magnetic susceptibility (MMS) and magnetic susceptibility anisotropy (MSA) and is more robust to noise in the estimation of principal eigenvector (PEV). When considering the head orientation dependency of NBMS contributions, the proposed method shows advantages in estimating MSA and PEV. On the mouse and human brain data, the proposed method produces more reliable MSA maps and more consistent white matter fiber directions when referring to those from DTI than the compared STI methods. CONCLUSION: The proposed method can reduce the effects of NBMS-related frequency shifts on the susceptibility tensors in the brain white matter. This study inspires STI reconstruction from the perspective of better modeling the sources of frequency shifts.

Age-Related Changes in the Spatial Variation of Magnetic Susceptibility of Human Articular Cartilage.

BACKGROUND: Quantitative susceptibility mapping (QSM) has shown great potential for revealing the layer structure of articular cartilage based on the laminar susceptibility difference at different depths. However, more information is needed on the effects of age on the spatial distribution of magnetic susceptibility in human cartilage. PURPOSE: To assess the ability of QSM to quantify the age-related differences in depth-wise cartilage susceptibility values in healthy populations. STUDY TYPE: Prospective. POPULATION: A total of 94 healthy asymptomatic subjects in three age cohorts: 19-30 (n = 36, 20 males), 31-50 (n = 45, 27 males), and 51-66 years (n = 13, 7 males). FIELD STRENGTH/SEQUENCE: 3D gradient echo sequences at 3.0 T. ASSESSMENT: Four cartilage compartments were analyzed, including the central lateral/medial femur (cLF/cMF) and the lateral/medial tibia (LT/MT). The spatial susceptibility profile and the corresponding 95% confidence interval (CI) of each age cohort were obtained as functions of the normalized distance from the bone-cartilage interface to the cartilage surface (cartilage depth from 0.0 to 1.0). STATISTICAL TESTS: The relationship between age and cartilage thickness of each cartilage subregion was tested by Pearson correlation with P < 0.05 considered significant. Cartilage depths with separations of 95% CIs were considered to have significant susceptibility differences between two age cohorts with a Bonferroni-corrected P < 0.05. RESULTS: The cartilage thickness did not change significantly with age (P value range: 0.06-0.85). Susceptibilities were significantly higher in the 51-66-year-olds compared with the 31-50-year-olds in the deep layer of cMF (cartilage depth: 0.0-0.22) and LT (0.05-0.28). Susceptibilities were significantly higher in the 51-66-year-olds compared with the 19-30-year-olds near the cartilage-bone interface of cMF (0.0-0.34), cLF (0.0-0.28), and LT (0.0-0.58). There were also significantly higher susceptibilities in the 31-50-year-olds compared with the 19-30-year-olds in the deeper regions of cMF (0.26-0.57), cLF (0.0-0.40), and LT (0.07-0.80). DATA CONCLUSION: Age-related susceptibility changes in the deeper regions of knee cartilage were observed using QSM. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.