Resting State Brain Networks under Inverse Agonist versus Complete Knockout of the Cannabinoid Receptor 1.

The cannabinoid receptor 1 (CB1) is famous as the target of Δ9-tetrahydrocannabinol (THC), which is the active ingredient of marijuana. Suppression of CB1 is frequently suggested as a drug target or gene therapy for many conditions (e.g., obesity, Parkinson's disease). However, brain networks affected by CB1 remain elusive, and unanticipated psychological effects in a clinical trial had dire consequences. To better understand the whole brain effects of CB1 suppression we performed in vivo imaging on mice under complete knockout of the gene for CB1 (cnr1-/-) and also under the CB1 inverse agonist rimonabant. We examined white matter structural changes and brain function (network activity and directional uniformity) in cnr1-/- mice. In cnr1-/- mice, white matter (in both sexes) and functional directional uniformity (in male mice) were altered across the brain but network activity was largely unaltered. Conversely, under rimonabant, functional directional uniformity was not altered but network activity was altered in cortical regions, primarily in networks known to be altered by THC (e.g., neocortex, hippocampal formation). However, rimonabant did not alter many brain regions found in both our cnr1-/- results and previous behavioral studies of cnr1-/- mice (e.g., thalamus, infralimbic area). This suggests that chronic loss of cnr1 is substantially different from short-term suppression, subtly rewiring the brain but largely maintaining the network activity. Our results help explain why pathological mutations in CB1 (e.g., chronic pain) do not always provide insight into the side effects of CB1 suppression (e.g., clinical depression), and thus urge more preclinical studies for any drugs that suppress CB1.

Benchmarking spatial clustering methods with spatially resolved transcriptomics data.

Spatial clustering, which shares an analogy with single-cell clustering, has expanded the scope of tissue physiology studies from cell-centroid to structure-centroid with spatially resolved transcriptomics (SRT) data. Computational methods have undergone remarkable development in recent years, but a comprehensive benchmark study is still lacking. Here we present a benchmark study of 13 computational methods on 34 SRT data (7 datasets). The performance was evaluated on the basis of accuracy, spatial continuity, marker genes detection, scalability, and robustness. We found existing methods were complementary in terms of their performance and functionality, and we provide guidance for selecting appropriate methods for given scenarios. On testing additional 22 challenging datasets, we identified challenges in identifying noncontinuous spatial domains and limitations of existing methods, highlighting their inadequacies in handling recent large-scale tasks. Furthermore, with 145 simulated data, we examined the robustness of these methods against four different factors, and assessed the impact of pre- and postprocessing approaches. Our study offers a comprehensive evaluation of existing spatial clustering methods with SRT data, paving the way for future advancements in this rapidly evolving field.

Gamma-ray irradiation as an effective method for mitigating antibiotic resistant bacteria and antibiotic resistance genes in aquatic environments.

The prevalence of antibiotic resistance genes (ARGs) in municipal wastewater treatment plants (MWTPs) has emerged as a significant environmental concern. Despite advanced treatment processes, high levels of ARGs persist in the secondary effluent from MWTPs, posing ongoing environmental risks. This study explores the potential of gamma-ray irradiation as a novel approach for sterilizing antibiotic-resistant bacteria (ARB) and reducing ARGs in MWTP secondary effluent. Our findings reveal that gamma-ray irradiation at an absorbed dose of 1.6 kGy effectively deactivates all culturable bacteria, with no subsequent revival observed after exposure to 6.4 kGy and a 96-h incubation in darkness at room temperature. The removal efficiencies for a range of ARGs, including tetO, tetA, blaTEM-1, sulI, sulII, and tetW, were up to 90.5% with a 25.6 kGy absorbed dose. No resurgence of ARGs was detected after irradiation. Additionally, this study demonstrates a considerable reduction in the abundances of extracellular ARGs, with the transformation efficiencies of extracellular tetracycline and sulfadiazine resistance genes decreasing by 56.3-81.8% after 25.6 kGy irradiation. These results highlight the effectiveness of gamma-ray irradiation as an advanced and promising method for ARB sterilization and ARG reduction in the secondary effluent of MWTPs, offering a potential pathway to mitigate environmental risks associated with antibiotic resistance.

A neural signature for the subjective experience of threat anticipation under uncertainty.

Uncertainty about potential future threats and the associated anxious anticipation represents a key feature of anxiety. However, the neural systems that underlie the subjective experience of threat anticipation under uncertainty remain unclear. Combining an uncertainty-variation threat anticipation paradigm that allows precise modulation of the level of momentary anxious arousal during functional magnetic resonance imaging (fMRI) with multivariate predictive modeling, we train a brain model that accurately predicts subjective anxious arousal intensity during anticipation and test it across 9 samples (total n = 572, both gender). Using publicly available datasets, we demonstrate that the whole-brain signature specifically predicts anxious anticipation and is not sensitive in predicting pain, general anticipation or unspecific emotional and autonomic arousal. The signature is also functionally and spatially distinguishable from representations of subjective fear or negative affect. We develop a sensitive, generalizable, and specific neuroimaging marker for the subjective experience of uncertain threat anticipation that can facilitate model development.

pH Mapping of Gliomas Using Quantitative Chemical Exchange Saturation Transfer MRI: Quasi-Steady-State, Spillover-, and MT-Corrected Omega Plot Analysis.

BACKGROUND: Quantitative in-situ pH mapping of gliomas is important for therapeutic interventions, given its significant association with tumor progression, invasion, and metastasis. Although chemical exchange saturation transfer (CEST) offers a noninvasive way for pH imaging based on the pH-dependent exchange rate (ksw ), the reliable quantification of ksw in glioma remains constrained due to technical challenges. PURPOSE: To quantify the pH of gliomas by measuring the proton exchange rate through optimized omega plot analysis. STUDY TYPE: Prospective. PHANTOMS/ANIMAL MODEL/SUBJECTS: Creatine and murine brain lysates phantoms, six rats with glioma xenograft model, and three patients with World Health Organization grade 2-4 gliomas. FIELD STRENGTH/SEQUENCE: 11.7 T, 7.0 T, CEST imaging, T2 -weighted (T2 W) imaging, and T1 -mapping. ASSESSMENT: Omega plot analysis, quasi-steady-state (QUASS) analysis, multi-pool Lorentzian fitting, amine and amide concentration-independent detection, pH enhanced method with the combination of amide and guanidyl (pHenh ), and magnetization transfer ratio (MTR) were utilized for pH metric quantification. The clinical outcomes were determined through radiologic follow-up and histopathological analysis. STATISTICAL TESTS: Mann-Whitney U test was performed to compare glioma with normal tissue, and Pearson's correlation analysis was used to assess the relationship between ksw and other parameters. RESULTS: In vitro experiments reveal that the determined ksw at 2 ppm increases exponentially with pH (creatine phantoms: ksw = 106 + 0.147 × 10(pH-4.198) ; lysates: ksw = 185.1 + 0.101 × 10(pH-3.914) ). Omega plot analysis exhibits a linear correlation between 1/MTRRex and 1/ω1 2 in the glioma xenografts (R2 > 0.98) and glioma patients (R2 > 0.99). The exchange rate in the rat glioma decreases compared to the contralateral normal tissue (349.46 ± 30.40 s-1 vs. 403.54 ± 51.01 s-1 , P = 0.025), while keeping independence from changes in concentration (r = 0.5037, P = 0.095). Similar pattern was observed in human data. DATA CONCLUSION: Utilizing QUASS-based, spillover-, and MT-corrected omega plot analysis for the measurement of exchange rates, offers a feasible method for quantifying pH within glioma. LEVEL OF EVIDENCE: NA TECHNICAL EFFICACY: Stage 1.

Assessment of early anthracycline-induced cardiotoxicity and liver injury with T2 and T2* mapping in rabbit models.

OBJECTIVES: To evaluate the early prevalence of anthracycline-induced cardiotoxicity (AIC) and anthracycline-induced liver injury (AILI) using T2 and T2* mapping and to explore their correlations. MATERIALS AND METHODS: The study included 17 cardiotoxic rabbits that received weekly injections of doxorubicin and magnetic resonance imaging (MRI) every 2 weeks for 10 weeks. Cardiac function and T2 and T2* values were measured on each period. Histopathological examinations for two to five rabbits were performed after each MRI scan. The earliest sensitive time and the threshold of MRI parameters for detecting AIC and AILI based on these MRI parameters were obtained. Moreover, the relationship between myocardial and liver damage was assessed. RESULTS: Early AIC could be detected by T2 mapping as early as the second week and focused on the 7th, 11th, and 12th segments of left ventricle. The cutoff value of 46.64 for the 7th segment had the best diagnostic value, with an area under the curve (of 0.767, sensitivity of 100%, and specificity of 52%. T2* mapping could detect the change in iron content for early AIC at the middle interventricular septum and AILI as early as the sixth week (p = 0.014, p = 0.027). The T2* values of the middle interventricular septum showed a significant positive association with the T2* values of the liver (r = 0.39, p = 0.002). CONCLUSION: T2 and T2* mapping showed value one-stop assessment of AIC and AILI and could obtain the earliest MRI diagnosis point and optimal parameter thresholds for these conditions. CLINICAL RELEVANCE STATEMENT: Anthracycline-induced cardiotoxicity could be detected by T2 mapping as earlier as the second week, mainly focusing on the 7th, 11th, and 12th segments of left ventricle. Combined with T2* mapping, hepatoxicity and supplementary cardiotoxicity were assessed by one-stop scan. KEY POINTS: • MRI screening time of cardiotoxicity was as early as the second week with focusing on T2 values of the 7th, 11th, and 12th segments of left ventricle. • T2* mapping could be used as a complement to T2 mapping to evaluate cardiotoxicity and as an effective index to detect iron change in the early stages of chemotherapy. • The T2* values of the middle interventricular septum showed a significant positive association with the T2* values of the liver, indicating that iron content in the liver and heart increased with an increase in the chemotherapeutic drugs.

Accelerated 3D MR neurography of the brachial plexus using deep learning-constrained compressed sensing.

OBJECTIVES: To explore the use of deep learning-constrained compressed sensing (DLCS) in improving image quality and acquisition time for 3D MRI of the brachial plexus. METHODS: Fifty-four participants who underwent contrast-enhanced imaging and forty-one participants who underwent unenhanced imaging were included. Sensitivity encoding with an acceleration of 2 × 2 (SENSE4x), CS with an acceleration of 4 (CS4x), and DLCS with acceleration of 4 (DLCS4x) and 8 (DLCS8x) were used for MRI of the brachial plexus. Apparent signal-to-noise ratios (aSNRs), apparent contrast-to-noise ratios (aCNRs), and qualitative scores on a 4-point scale were evaluated and compared by ANOVA and the Friedman test. Interobserver agreement was evaluated by calculating the intraclass correlation coefficients. RESULTS: DLCS4x achieved higher aSNR and aCNR than SENSE4x, CS4x, and DLCS8x (all p < 0.05). For the root segment of the brachial plexus, no statistically significant differences in the qualitative scores were found among the four sequences. For the trunk segment, DLCS4x had higher scores than SENSE4x (p = 0.04) in the contrast-enhanced group and had higher scores than SENSE4x and DLCS8x in the unenhanced group (all p < 0.05). For the divisions, cords, and branches, DLCS4x had higher scores than SENSE4x, CS4x, and DLCS8x (all p ≤ 0.01). No overt difference was found among SENSE4x, CS4x, and DLCS8x in any segment of the brachial plexus (all p > 0.05). CONCLUSIONS: In three-dimensional MRI for the brachial plexus, DLCS4x can improve image quality compared with SENSE4x and CS4x, and DLCS8x can maintain the image quality compared to SENSE4x and CS4x. CLINICAL RELEVANCE STATEMENT: Deep learning-constrained compressed sensing can improve the image quality or accelerate acquisition of 3D MRI of the brachial plexus, which should be benefit in evaluating the brachial plexus and its branches in clinical practice. KEY POINTS: •Deep learning-constrained compressed sensing showed higher aSNR, aCNR, and qualitative scores for the brachial plexus than SENSE and CS at the same acceleration factor with similar scanning time. •Deep learning-constrained compressed sensing at acceleration factor of 8 had comparable aSNR, aCNR, and qualitative scores to SENSE4x and CS4x with approximately half the examination time. •Deep learning-constrained compressed sensing may be helpful in clinical practice for improving image quality and acquisition time in three-dimensional MRI of the brachial plexus.

MosaicNet: A deep-learning-based multi-tile biomedical image stitching method.

Multi-tile image stitching aims to merge multiple natural or biomedical images into a single mosaic. This is an essential step in whole-slide imaging and large-scale pathological imaging systems. To tackle this task, a multi-step framework is usually used by first estimating the optimal transformation for each image and then fusing them into a whole image. However, the traditional approaches are usually time-consuming and require manual adjustments. Advances in deep learning techniques provide an end-to-end solution to register and fuse information of multiple tile images. In this paper, we present a deep learning model for multi-tile biomedical image stitching, namely MosaicNet, consisting of an aligning network and a fusion network. We trained the MosaicNet network on a large simulation dataset based on the VOC2012 dataset and evaluated the model on multiple types of datasets, including simulated natural images, mouse brain T2-weighted Magnetic Resonance Imaging (T2w-MRI) data, and mouse brain polarization sensitive-optical coherence tomography (PS-OCT) data. Our method outperformed traditional approaches on both natural images and brain imaging data. The proposed method is robust to different settings of hyper-parameters and shows high computational efficiency, up to approximately 32 times faster than the conventional methods.

Downregulation of mGluR1-mediated signaling underlying autistic-like core symptoms in Shank1 P1812L-knock-in mice.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by core symptoms that consist of social deficits and repetitive behaviors. Unfortunately, no effective medication is available thus far to target the core symptoms of ASD, since the pathogenesis remains largely unknown. To investigate the pathogenesis of the core symptoms in ASD, we constructed Shank1 P1812L-knock-in (KI) mice corresponding to a recurrent ASD-related mutation, SHANK1 P1806L, to achieve construct validity and face validity. Shank1 P1812L-KI heterozygous (HET) mice presented with social deficits and repetitive behaviors without the presence of confounding comorbidities. HET mice also exhibited downregulation of metabotropic glutamate receptor (mGluR1) and associated signals, along with structural abnormalities in the dendritic spines and postsynaptic densities. Combined with findings from Shank1 R882H-KI mice, our study confirms that mGluR1-mediated signaling dysfunction is a pivotal mechanism underlying the core symptoms of ASD. Interestingly, Shank1 P1812L-KI homozygous (HOM) mice manifested behavioral signs of impaired long-term memory rather than autistic-like core traits; thus, their phenotype was markedly different from that of Shank1 P1812L-KI HET mice. Correspondingly, at the molecular level, Shank1 P1812L-KI HOM displayed upregulation of AMPA receptor (GluA2)-related signals. The different patterns of protein changes in HOM and HET mice may explain the differences in behaviors. Our study emphasizes the universality of mGluR1-signaling hypofunction in the pathogenesis of the core symptoms in ASD, providing a potential target for therapeutic drugs. The precise correspondence between genotype and phenotype, as shown in HOM and HET mice, indicates the importance of reproducing disease-related genotypes in mouse models.

Assessment of early anthracycline-induced cardiotoxicity using segmental strain of cardiac magnetic resonance compared with global strain and functional parameters: an animal study.

Background: The identification of anthracycline-induced cardiotoxicity holds significant importance in guiding subsequent treatment strategies, and recent research has demonstrated the efficacy of cardiac magnetic resonance (CMR) global strain analysis for its diagnosis. On the other hand, it is noteworthy that abnormal global myocardial strain may exhibit a temporal delay due to different cardiac movement in each segment of the left ventricle. To address this concern, this study aims to assess the diagnostic utility of CMR segmental strain analysis as an early detection method for cardiotoxicity. Methods: A serials of CMR scans were performed in 18 adult males New Zealand rabbits at baseline time (n=15), followed by scans at week 2 (n=15), week 4 (n=9), week 6 (n=6), and week 8 (n=5) after each week's anthracycline injection. Additionally, following each CMR scan, two to three rabbits were euthanized for pathological comparison. Cardiac functional parameters, global peak strain parameters, segmental peak strain parameters of the left ventricle, and the presence of myocardial cells damage were obtained. A mixed linear model was employed to obtain the earliest CMR diagnostic time. Receiver operating characteristic (ROC) analysis was performed to get the parameter threshold indicative of cardiotoxicity. Results: The left ventricular ejection fraction decreased at week 8 (P=0.002). There were no statistical differences in global strain throughout the experiment period (P>0.05). Regarding segmental strain analysis, the peak segmental radial strain of the apical lateral wall exhibited a decrease starting from week 2 and reached its lowest point at this week (P=0.011). Conversely, peak segmental circumferential strain of the apical anterior wall showed an increase at week 2 and reached its peak at week 6 (P=0.026). The cutoff strain value by ROC analysis for these two walls were 46.285 and -16.920, with the respective areas under the curve (AUC) 0.593 [specificity =0.267, sensitivity =1.000, 95% confidence interval (CI): 0.471-0.777] and 0.764 (specificity =0.733, sensitivity =0.784, 95% CI: 0.511-0.816). Peak segmental longitudinal strain of the apical anterior and apical lateral wall showed relatively delayed changes, occurring in the 4th week (P=0.030 and P=0.048), the cutoff values for these strains were -12.415 and -15.960, with corresponding AUCs of 0.645 (specificity =0.333, sensitivity =0.955, 95% CI: 0.495-0.795) and 0.717 (specificity =0.433, sensitivity =0.955, 95% CI: 0.566-0.902), respectively. Notably, the myocardial injury was also observed at the corresponding periods. Conclusions: Based on experimental evidence, the peak segmental strain of the apical lateral and anterior wall, as determined by CMR, demonstrated an earlier detection of anthracycline-induced cardiotoxicity compared to peak global strain and cardiac function.

A-GCL: Adversarial graph contrastive learning for fMRI analysis to diagnose neurodevelopmental disorders.

Accurate diagnosis of neurodevelopmental disorders is a challenging task due to the time-consuming cognitive tests and potential human bias in clinics. To address this challenge, we propose a novel adversarial self-supervised graph neural network (GNN) based on graph contrastive learning, named A-GCL, for diagnosing neurodevelopmental disorders using functional magnetic resonance imaging (fMRI) data. Taking advantage of the success of GNNs in psychiatric disease diagnosis using fMRI, our proposed A-GCL model is expected to improve the performance of diagnosis and provide more robust results. A-GCL takes graphs constructed from the fMRI images as input and uses contrastive learning to extract features for classification. The graphs are constructed with 3 bands of the amplitude of low-frequency fluctuation (ALFF) as node features and Pearson's correlation coefficients (PCC) of the average fMRI time series in different brain regions as edge weights. The contrastive learning creates an edge-dropped graph from a trainable Bernoulli mask to extract features that are invariant to small variations of the graph. Experiment results on three datasets - Autism Brain Imaging Data Exchange (ABIDE) I, ABIDE II, and attention deficit hyperactivity disorder (ADHD) - with 3 atlases - AAL1, AAL3, Shen268 - demonstrate the superiority and generalizability of A-GCL compared to the other GNN-based models. Extensive ablation studies verify the robustness of the proposed approach to atlas selection and model variation. Explanatory results reveal key functional connections and brain regions associated with neurodevelopmental disorders.

Intra-Operative Definition of Glioma Infiltrative Margins by Visualizing Immunosuppressive Tumor-Associated Macrophages.

Accurate delineation of glioma infiltrative margins remains a challenge due to the low density of cancer cells in these regions. Here, a hierarchical imaging strategy to define glioma margins by locating the immunosuppressive tumor-associated macrophages (TAMs) is proposed. A pH ratiometric fluorescent probe CP2-M that targets immunosuppressive TAMs by binding to mannose receptor (CD206) is developed, and it subsequently senses the acidic phagosomal lumen, resulting in a remarkable fluorescence enhancement. With assistance of CP2-M, glioma xenografts in mouse models with a tumor-to-background ratio exceeding 3.0 for up to 6 h are successfully visualized. Furthermore, by intra-operatively mapping the pH distribution of exposed tissue after craniotomy, the glioma allograft in rat models is precisely excised. The overall survival of rat models significantly surpasses that achieved using clinically employed fluorescent probes. This work presents a novel strategy for locating glioma margins, thereby improving surgical outcomes for tumors with infiltrative characteristics.

Diagnostic value of Kaiser score combined with breast vascular assessment from breast MRI for the characterization of breast lesions.

Objectives: The Kaiser scoring system for breast magnetic resonance imaging is a clinical decision-making tool for diagnosing breast lesions. However, the Kaiser score (KS) did not include the evaluation of breast vascularity. Therefore, this study aimed to use KS combined with breast vascular assessment, defined as KS*, and investigate the effectiveness of KS* in differentiating benign from malignant breast lesions. Methods: This retrospective study included 223 patients with suspicious breast lesions and pathologically verified results. The histopathological diagnostic criteria were according to the fifth edition of the WHO classification of breast tumors. The KS* was obtained after a joint evaluation combining the original KS and breast vasculature assessment. The receiver operating characteristic (ROC) curve was used for comparing differences in the diagnostic performance between KS* and KS, and the area under the receiver operating characteristic (AUC) was compared. Results: There were 119 (53.4%) benign and 104 (46.6%) malignant lesions in total. The overall sensitivity, specificity, and accuracy of increased ipsilateral breast vascularity were 69.2%, 76.5%, and 73.1%, respectively. The overall sensitivity, specificity, and accuracy of AVS were 82.7%, 76.5%, and 79.4%, respectively. For all lesions included the AUC of KS* was greater than that of KS (0.877 vs. 0.858, P = 0.016). The largest difference in AUC was observed in the non-mass subgroup (0.793 vs. 0.725, P = 0.029). Conclusion: Ipsilaterally increased breast vascularity and a positive AVS sign were significantly associated with malignancy. KS combined with breast vascular assessment can effectively improve the diagnostic ability of KS for breast lesions, especially for non-mass lesions.

Deep Learning-Assisted Quantitative Susceptibility Mapping as a Tool for Grading and Molecular Subtyping of Gliomas.

This study aimed to explore the value of deep learning (DL)-assisted quantitative susceptibility mapping (QSM) in glioma grading and molecular subtyping. Forty-two patients with gliomas, who underwent preoperative T2 fluid-attenuated inversion recovery (T2 FLAIR), contrast-enhanced T1-weighted imaging (T1WI + C), and QSM scanning at 3.0T magnetic resonance imaging (MRI) were included in this study. Histopathology and immunohistochemistry staining were used to determine glioma grades, and isocitrate dehydrogenase (IDH) 1 and alpha thalassemia/mental retardation syndrome X-linked gene (ATRX) subtypes. Tumor segmentation was performed manually using Insight Toolkit-SNAP program (www.itksnap.org). An inception convolutional neural network (CNN) with a subsequent linear layer was employed as the training encoder to capture multi-scale features from MRI slices. Fivefold cross-validation was utilized as the training strategy (seven samples for each fold), and the ratio of sample size of the training, validation, and test dataset was 4:1:1. The performance was evaluated by the accuracy and area under the curve (AUC). With the inception CNN, single modal of QSM showed better performance in differentiating glioblastomas (GBM) and other grade gliomas (OGG, grade II-III), and predicting IDH1 mutation and ATRX loss (accuracy: 0.80, 0.77, 0.60) than either T2 FLAIR (0.69, 0.57, 0.54) or T1WI + C (0.74, 0.57, 0.46). When combining three modalities, compared with any single modality, the best AUC/accuracy/F1-scores were reached in grading gliomas (OGG and GBM: 0.91/0.89/0.87, low-grade and high-grade gliomas: 0.83/0.86/0.81), predicting IDH1 mutation (0.88/0.89/0.85), and predicting ATRX loss (0.78/0.71/0.67). As a supplement to conventional MRI, DL-assisted QSM is a promising molecular imaging method to evaluate glioma grades, IDH1 mutation, and ATRX loss. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00087-6.

Retrograde percutaneous coronary intervention of chronic total occlusion via discontinuous septal channels.

OBJECTIVES: The study aims to investigate the safety and feasibility of retrograde CTO intervention via collateral connection grade 0 (CC-0) septal channel and to identify predictors of collateral tracking failure. BACKGROUND: Guidewire crossing a collateral channel is a critical step for successful retrograde percutaneous coronary intervention (PCI) of chronic total occlusion (CTO). METHODS: Retrograde PCI was attempted in 122 cases of CTO with CC-0 septal collaterals from December 2018 to May 2021. A hydrophilic polymer coating guidewire was used for crossing all intended CC-0 collaterals. A multivariable logistic regression analysis was performed to identify the predictors of guidewire tracking failure via the CC-0 collaterals. RESULTS: Successful guidewire tracking via CC-0 septal channel was achieved in 98 (80.3%) of 122 cases. The independent predictors of CC-0 septal channel guidewire tracking failure included well-developed non-septal collateral (OR: 5.297, 95% CI: 1.107-25.353, p = 0.037) and the ratio length of posterior descending artery (PDA) versus the distance of PDA ostium to cardiac apex ≤2/3 (OR: 3.970, 95% CI: 1.454-10.835, p = 0.007). Collateral perforation, target vessel perforation, and cardiac tamponade occurred in 5 (4.1%), 3 (2.5%), and 6 (4.9%) cases, respectively. There were no complications requiring emergency cardiac surgery or revascularization of nontarget vessel. CONCLUSIONS: Retrograde PCI via CC-0 septal channels with a hydrophilic polymer-coated guidewire is feasible and safe in patients with CTO. Well-developed nonseptal collaterals and short PDA length influence the procedure success and the risk of guidewire tracking failure via CC-0 septal channels.

Cross-sectional Exploration of the Relationship Between Glutamate Abnormalities and Tic Disorder Severity Using Proton Magnetic Resonance Spectroscopy.

Glutamate (Glu) has been reported to be closely related to the pathophysiology of Tic Disorders (TD). By using proton magnetic resonance spectroscopy (1H-MRS), we aimed to investigate the relationship between in vivo Glu levels and the severity of TD. We performed a cross-sectional study in medication-free patients with TD and healthy controls aged between 5 and 13 years using 1H-MRS at 3 T. First, we measured the Glu levels in both patients and controls and observed the difference in subgroups, including mild TD patients and moderate TD patients. We then examined the correlations between the Glu levels and clinical features of the patients. Finally, we assessed the diagnostic value of 1H-MRS and the influencing factors. Our results show that the Glu levels in the striatum of all patients with TD were not significantly different from those of the healthy controls. Subgroup analysis revealed that the Glu levels in the moderate TD group were higher than those in the mild TD group and healthy controls. The correlation analysis showed that Glu levels are strongly positive correlated with TD severity. The optimal cutoff value of Glu levels to differentiate mild tics from moderate tics was 1.244, with a sensitivity of 88.2% and a specificity of 94.7%. Multiple linear regression models revealed that the severity of TD is one of the important factors that affect Glu levels. We conclude that Glu levels are mainly associated with the severity of tics, thus it could serve as a key biomarker for TD classification.

The extract of Curcumae Longae Rhizoma suppresses angiogenesis via VEGF-induced PI3K/Akt-eNOS-NO pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Curcumae Longae Rhizoma (CLR) is a safe natural herbal medicine, and which has been widely used for centuries as functional food and health products, but its effects on angiogenesis and related underlying mechanism remain unclear. AIM OF THE STUDY: The abnormal angiogenesis is closely related with various diseases, and therefore the precise control of angiogenesis is of great importance. The well-known angiogenic factor, vascular endothelial growth factor (VEGF), mediates angiogenesis and induces multiple signalling pathways via binding to VEGF receptor (VEGFR). The attenuation of VEGF-triggered angiogenic-related signalling pathways may relieve various diseases through suppression of angiogenesis. Here, we aimed to elucidate that CLR extract could exert striking anti-angiogenic activities both in vitro and in vivo. MATERIALS AND METHODS: The viability of human umbilical vascular endothelial cell (HUVEC) was examined by LDH and MTT assays. Migrative and invasive ability of the endothelial cells were independently evaluated by wound healing and transwell assays. The activities of CLR extract on in vitro angiogenesis was tested by tube formation assay. In vivo vascularization was determined by using zebrafish embryo model in the present of CLR extract. Western blotting was applied to determine the phosphorylated levels of VEGFR2, PI3K, AKT and eNOS. Besides, the levels of nitric oxide (NO) and reactive oxygen species (ROS) were separately evaluated by Griess assay and 2'7'-dichlorofluorescein diacetate reaction. In addition, the cell migrative ability of cancer cell was estimated by using cultured human colon carcinoma cells (HT-29 cell line), and immunofluorescence assay was applied to evaluate the effect of CLR extract on nuclear translocation of NF-κB p65 subunit in the VEGF-treated HT-29 cultures. RESULTS: CLR extract significantly suppressed a series of VEGF-mediated angiogenic responses, including endothelial cell proliferation, migration, invasion, and tube formation. Moreover, CLR extract reduced in vivo sub-intestinal vessel formation in zebrafish embryo model. Mechanistically, the extract of CLR attenuated the VEGF-triggered signalling, as demonstrated by decreased level of phosphorylated VEGFR2 and subsequently inactivated its downstream regulators, e.g. phospho-PI3K, phospho-AKT and phospho-eNOS. The production of NO and formation of ROS were markedly inhibited in HUVECs. Furthermore, CLR extract suppressed cell migration and NF-κB translocation in cultured HT-29 cells. CONCLUSIONS: These preclinical findings demonstrate that the extract of CLR remarkably attenuates angiogenesis and which has great potential as a natural drug candidate with excellent anti-angiogenic activity.

TW-Net: Transformer Weighted Network for Neonatal Brain MRI Segmentation.

Accurate neonatal brain MRI segmentation is valuable for investigating brain growth patterns and tracking the progression of neurodevelopmental disorders. However, it is a challenging task to use intensity-based methods to segment neonatal brain structures because of small contrast differences between brain regions caused by the inherent myelination process. Although convolutional neural networks offer the potential to segment brain structures in an intensity-independent manner, they suffer from lack of in-plane long-range dependency which is essential for the segmentation. To solve this problem, we propose a novel Transformer-Weighted network (TW-Net) to incorporate in-plane long-range dependency information. TW-Net employs a conventional encoder-decoder architecture with a Transformer module in the middle. The Transformer module uses a rotate-and-flip layer to better calculate the similarity between two patches in a slice to leverage similar patterns of geometrical and texture features within brain structures. In addition, a deep supervision module and squeeze-and-excitation blocks are introduced to incorporate boundary information of brain structures. Compared with state-of-the-art deep learning algorithms, TW-Net outperforms these methods for multiple-label tasks in 2D and 2.5D configurations on two independent public datasets, demonstrating that TW-Net is a promising method for neonatal brain MRI segmentation.

MouseGAN++: Unsupervised Disentanglement and Contrastive Representation for Multiple MRI Modalities Synthesis and Structural Segmentation of Mouse Brain.

Segmenting the fine structure of the mouse brain on magnetic resonance (MR) images is critical for delineating morphological regions, analyzing brain function, and understanding their relationships. Compared to a single MRI modality, multimodal MRI data provide complementary tissue features that can be exploited by deep learning models, resulting in better segmentation results. However, multimodal mouse brain MRI data is often lacking, making automatic segmentation of mouse brain fine structure a very challenging task. To address this issue, it is necessary to fuse multimodal MRI data to produce distinguished contrasts in different brain structures. Hence, we propose a novel disentangled and contrastive GAN-based framework, named MouseGAN++, to synthesize multiple MR modalities from single ones in a structure-preserving manner, thus improving the segmentation performance by imputing missing modalities and multi-modality fusion. Our results demonstrate that the translation performance of our method outperforms the state-of-the-art methods. Using the subsequently learned modality-invariant information as well as the modality-translated images, MouseGAN++ can segment fine brain structures with averaged dice coefficients of 90.0% (T2w) and 87.9% (T1w), respectively, achieving around +10% performance improvement compared to the state-of-the-art algorithms. Our results demonstrate that MouseGAN++, as a simultaneous image synthesis and segmentation method, can be used to fuse cross-modality information in an unpaired manner and yield more robust performance in the absence of multimodal data. We release our method as a mouse brain structural segmentation tool for free academic usage at https://github.com/yu02019.

SH2B1 Tunes Hippocampal ERK Signaling to Influence Fluid Intelligence in Humans and Mice.

Fluid intelligence is a cognitive domain that encompasses general reasoning, pattern recognition, and problem-solving abilities independent of task-specific experience. Understanding its genetic and neural underpinnings is critical yet challenging for predicting human development, lifelong health, and well-being. One approach to address this challenge is to map the network of correlations between intelligence and other constructs. In the current study, we performed a genome-wide association study using fluid intelligence quotient scores from the UK Biobank to explore the genetic architecture of the associations between obesity risk and fluid intelligence. Our results revealed novel common genetic loci (SH2B1, TUFM, ATP2A1, and FOXO3) underlying the association between fluid intelligence and body metabolism. Surprisingly, we demonstrated that SH2B1 variation influenced fluid intelligence independently of its effects on metabolism but partially mediated its association with bilateral hippocampal volume. Consistently, selective genetic ablation of Sh2b1 in the mouse hippocampus, particularly in inhibitory neurons, but not in excitatory neurons, significantly impaired working memory, short-term novel object recognition memory, and behavioral flexibility, but not spatial learning and memory, mirroring the human intellectual performance. Single-cell genetic profiling of Sh2B1-regulated molecular pathways revealed that Sh2b1 deletion resulted in aberrantly enhanced extracellular signal-regulated kinase (ERK) signaling, whereas pharmacological inhibition of ERK signaling reversed the associated behavioral impairment. Our cross-species study thus provides unprecedented insight into the role of SH2B1 in fluid intelligence and has implications for understanding the genetic and neural underpinnings of lifelong mental health and well-being.