Verbal memory network mapping in individual patients predicts postoperative functional impairments.

Verbal memory decline is a significant concern following temporal lobe surgeries in patients with epilepsy, emphasizing the need for precision presurgical verbal memory mapping to optimize functional outcomes. However, the inter-individual variability in functional networks and brain function-structural dissociations pose challenges when relying solely on group-level atlases or anatomical landmarks for surgical guidance. Here, we aimed to develop and validate a personalized functional mapping technique for verbal memory using precision resting-state functional MRI (rs-fMRI) and neurosurgery. A total of 38 patients with refractory epilepsy scheduled for surgical interventions were enrolled and 28 patients were analyzed in the study. Baseline 30-min rs-fMRI scanning, verbal memory and language assessments were collected for each patient before surgery. Personalized verbal memory networks (PVMN) were delineated based on preoperative rs-fMRI data for each patient. The accuracy of PVMN was assessed by comparing post-operative functional impairments and the overlapping extent between PVMN and surgical lesions. A total of 14 out of 28 patients experienced clinically meaningful declines in verbal memory after surgery. The personalized network and the group-level atlas exhibited 100% and 75.0% accuracy in predicting postoperative verbal memory declines, respectively. Moreover, six patients with extra-temporal lesions that overlapped with PVMN showed selective impairments in verbal memory. Furthermore, the lesioned ratio of the personalized network rather than the group-level atlas was significantly correlated with postoperative declines in verbal memory (personalized networks: r = -0.39, p = .038; group-level atlas: r = -0.19, p = .332). In conclusion, our personalized functional mapping technique, using precision rs-fMRI, offers valuable insights into individual variability in the verbal memory network and holds promise in precision verbal memory network mapping in individuals.

SUGAR: Spherical ultrafast graph attention framework for cortical surface registration.

Cortical surface registration plays a crucial role in aligning cortical functional and anatomical features across individuals. However, conventional registration algorithms are computationally inefficient. Recently, learning-based registration algorithms have emerged as a promising solution, significantly improving processing efficiency. Nonetheless, there remains a gap in the development of a learning-based method that exceeds the state-of-the-art conventional methods simultaneously in computational efficiency, registration accuracy, and distortion control, despite the theoretically greater representational capabilities of deep learning approaches. To address the challenge, we present SUGAR, a unified unsupervised deep-learning framework for both rigid and non-rigid registration. SUGAR incorporates a U-Net-based spherical graph attention network and leverages the Euler angle representation for deformation. In addition to the similarity loss, we introduce fold and multiple distortion losses to preserve topology and minimize various types of distortions. Furthermore, we propose a data augmentation strategy specifically tailored for spherical surface registration to enhance the registration performance. Through extensive evaluation involving over 10,000 scans from 7 diverse datasets, we showed that our framework exhibits comparable or superior registration performance in accuracy, distortion, and test-retest reliability compared to conventional and learning-based methods. Additionally, SUGAR achieves remarkable sub-second processing times, offering a notable speed-up of approximately 12,000 times in registering 9,000 subjects from the UK Biobank dataset in just 32 min. This combination of high registration performance and accelerated processing time may greatly benefit large-scale neuroimaging studies.

The protective effect of traditional Chinese medicine Jinteng Qingbi granules on rats with rheumatoid arthritis.

Introduction: Jinteng Qingbi granules (JTQBG), a traditional Chinese medicine formulation, are widely used for the treatment of rheumatoid arthritis (RA) due to their satisfactory therapeutic efficacy. However, the underlying mechanism of action remains unclear. This study aims to investigate the protective effects of JTQBG against RA and elucidates its potential molecular mechanisms. Methods: A collagen-induced arthritis (CIA) rat model was utilized, and JTQBG (1.25, 2.5, 5 g/kg/day) or methotrexate (MTX, 1 mg/kg/week) was orally administered. The rats' weight, arthritis index (AI), and paw volume were measured weekly. Synovial hyperplasia of the joints was detected using a small animal ultrasound imaging system. Joint destruction was assessed using an X-ray imaging system. Histopathological examinations were performed using hematoxylin-eosin (H&E), Saffron-O and fast green staining. Serum inflammatory cytokines were detected using ELISA. Furthermore, 4D label-free quantitative proteomics of synovial tissues and non-targeted metabolomics of blood serum were conducted to analyze the molecular mechanisms. Results: JTQBG exerted a significant therapeutic effect on CIA rats by reducing inflammatory cell infiltration, synovial hyperplasia, cartilage erosion, and bone destruction. It also decreased the spleen index, inhibited hyperplasia of the white pulp, and decreased the serum levels of IL-1ß and IL-18. Proteomics analysis identified 367 differentially expressed proteins (DEPs) between the Model and Normal groups, and 71 DEPs between the JTQBG and Model groups. These DEPs were significantly enriched in the NF-κB pathway. 11 DEPs were significantly reversed after treatment with JTQBG. Western blot results further validated the expression levels of Nfkb1, Pdk1, and Pecam1, and analyzed the expression levels of p-IKK, p-IκBα, and IκBα. The therapeutic efficacy of JTQBG was partly attributed to the suppression of the NF-κB pathway in synovial tissues. Serum metabolomics identified 17 potential biomarkers for JTQBG treatment of CIA rats, which were closely related to Alanine, aspartate and glutamate metabolism, Tryptophan metabolism, Ascorbate and aldarate metabolism, Arginine metabolism, and Inositol phosphate metabolism. Conclusion: Our findings demonstrated that JTQBG was effective against RA by alleviating synovial inflammation, synovial hyperplasia, and joint destruction. The anti-RA properties of JTQBG were likely attributed to the inhibition of the NF-κB pathway and the regulation of serum metabolite disorders.

Individualized functional connectivity markers associated with motor and mood symptoms of Parkinson's disease.

Parkinson's disease (PD) is a complex neurological disorder characterized by many motor and non-motor symptoms. While most studies focus on the motor symptoms of the disease, it is important to identify markers that underlie different facets of the disease. In this case-control study, we sought to discover reliable, individualized functional connectivity markers associated with both motor and mood symptoms of PD. Using functional MRI, we extensively sampled 166 patients with PD (64 women, 102 men; mean age=61.8 years, SD=7.81) and 51 healthy control participants (32 women, 19 men; mean age=55.68 years, SD=7.62). We found that a model consisting of 44 functional connections predicted both motor (UPDRS-III: Pearson r=0.21, FDR-adjusted p=0.006) and mood symptoms (HAMD: Pearson r=0.23, FDR-adjusted p=0.006; HAMA: Pearson r=0.21, FDR-adjusted p=0.006). Two sets of connections contributed differentially to these predictions. Between-network connections, mainly connecting the sensorimotor and visual large-scale functional networks, substantially contributed to the prediction of motor measures, while within-network connections in the insula and sensorimotor network contributed more so to mood prediction. The middle to posterior insula region played a particularly important role in predicting depression and anxiety scores. We successfully replicated and generalized our findings in two independent PD datasets. Taken together, our findings indicate that sensorimotor and visual network markers are indicative of PD brain pathology, and that distinct subsets of markers are associated with motor and mood symptoms of PD.

Personalized brain MRI revealed distinct functional and anatomical disruptions in Creutzfeldt-Jakob disease and Alzheimer's disease.

AIMS: Creutzfeldt-Jakob disease (CJD) is a lethal neurodegenerative disorder, which leads to a rapidly progressive dementia. This study aimed to examine the cortical alterations in CJD, changes in these brain characteristics over time, and the differences between CJD and Alzheimer's disease (AD) that show similar clinical manifestations. METHODS: To obtain reliable, subject-specific functional measures, we acquired 24 min of resting-state fMRI data from each subject. We applied an individual-based approach to characterize the functional brain organization of 10 patients with CJD, 8 matched patients with AD, and 8 normal controls. We measured cortical atrophy as well as disruption in resting-state functional connectivity (rsFC) and then investigated longitudinal brain changes in a subset of CJD patients. RESULTS: CJD was associated with widespread cortical thinning and weakened rsFC. Compared with AD, CJD showed distinct atrophy patterns and greater disruptions in rsFC. Moreover, the longitudinal data demonstrated that the progressive cortical thinning and disruption in rsFC mainly affected the association rather than the primary cortex in CJD. CONCLUSIONS: CJD shows unique anatomical and functional disruptions in the cerebral cortex, distinct from AD. Rapid progression of CJD affects both the cortical thickness and rsFC in the association cortex.

Personalized functional imaging-guided rTMS on the superior frontal gyrus for post-stroke aphasia: A randomized sham-controlled trial.

BACKGROUND: Aphasia affects approximately one-third of stroke patients and yet its rehabilitation outcomes are often unsatisfactory. More effective strategies are needed to promote recovery. OBJECTIVE: We aimed to examine the efficacy and safety of the theta-burst stimulation (TBS) on the language area in the superior frontal gyrus (SFG) localized by personalized functional imaging, in facilitating post-stroke aphasia recovery. METHODS: This randomized sham-controlled trial uses a parallel design (intermittent TBS [iTBS] in ipsilesional hemisphere vs. continuous TBS [cTBS] in contralesional hemisphere vs. sham group). Participants had aphasia symptoms resulting from their first stroke in the left hemisphere at least one month prior. Participants received three-week speech-language therapy coupled with either active or sham stimulation applied to the left or right SFG. The primary outcome was the change in Western Aphasia Battery-Revised (WAB-R) aphasia quotient after the three-week treatment. The secondary outcome was WAB-R aphasia quotient improvement after one week of treatment. RESULTS: Ninety-seven patients were screened between January 2021 and January 2022, 45 of whom were randomized and 44 received intervention (15 in each active group, 14 in sham). Both iTBS (estimated difference = 14.75, p < 0.001) and cTBS (estimated difference = 13.43, p < 0.001) groups showed significantly greater improvement than sham stimulation after the 3-week intervention and immediately after one week of treatment (p's < 0.001). The adverse events observed were similar across groups. A seizure was recorded three days after the termination of the treatment in the iTBS group. CONCLUSION: The stimulation showed high efficacy and SFG is a promising stimulation target for post-stroke language recovery.

Focused ultrasound thalamotomy for tremor treatment impacts the cerebello-thalamo-cortical network.

High-intensity Magnetic Resonance-guided Focused Ultrasound (MRgFUS) is a recent, non-invasive line of treatment for medication-resistant tremor. We used MRgFUS to produce small lesions in the thalamic ventral intermediate nucleus (VIM), an important node in the cerebello-thalamo-cortical tremor network, in 13 patients with tremor-dominant Parkinson's disease or essential tremor. Significant tremor alleviation in the target hand ensued (t(12) = 7.21, p < 0.001, two-tailed), which was strongly associated with the functional reorganization of the brain's hand region with the cerebellum (r = 0.91, p < 0.001, one-tailed). This reorganization potentially reflected a process of normalization, as there was a trend of increase in similarity between the hand cerebellar connectivity of the patients and that of a matched, healthy control group (n = 48) after treatment. Control regions in the ventral attention, dorsal attention, default, and frontoparietal networks, in comparison, exhibited no association with tremor alleviation and no normalization. More broadly, changes in functional connectivity were observed in regions belonging to the motor, limbic, visual, and dorsal attention networks, largely overlapping with regions connected to the lesion targets. Our results indicate that MRgFUS is a highly efficient treatment for tremor, and that lesioning the VIM may result in the reorganization of the cerebello-thalamo-cortical tremor network.

Personalized Functional Connectivity Based Spatio-Temporal Aggregated Attention Network for MCI Identification.

Functional connectivity (FC) networks deri- ved from resting-state magnetic resonance image (rs-fMRI) are effective biomarkers for identifying mild cognitive impairment (MCI) patients. However, most FC identification methods simply extract features from group-averaged brain templates, and neglect inter-subject functional variations. Furthermore, the existing methods generally concentrate on spatial correlation among brain regions, resulting in the inefficient capture of the fMRI temporal features. To address these limitations, we propose a novel personalized functional connectivity based dual-branch graph neural network with spatio-temporal aggregated attention (PFC-DBGNN-STAA) for MCI identification. Specifically, a personalized functional connectivity (PFC) template is firstly constructed to align 213 functional regions across samples and generate discriminative individualized FC features. Secondly, a dual-branch graph neural network (DBGNN) is conducted by aggregating features from the individual- and group-level templates with the cross-template FC, which is beneficial to improve the feature discrimination by considering dependency between templates. Finally, a spatio-temporal aggregated attention (STAA) module is investigated to capture the spatial and dynamic relationships between functional regions, which solves the limitation of insufficient temporal information utilization. We evaluate our proposed method on 442 samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, and achieve the accuracies of 90.1%, 90.3%, 83.3% for normal control (NC) vs. early MCI (EMCI), EMCI vs. late MCI (LMCI), and NC vs. EMCI vs. LMCI classification tasks, respectively, indicating that our method boosts MCI identification performance and outperforms state-of-the-art methods.

Individualized Functional Connectome Identified Replicable Biomarkers for Dysphoric Symptoms in First-Episode Medication-Naïve Patients With Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) is a heterogeneous syndrome and can be conceptualized as a mixture of dimensional abnormalities across several specific brain circuits. The neural underpinnings of different symptom dimensions in MDD are not well understood. We aimed to identify robust, generalizable, functional connectivity (FC)-based biomarkers for different symptom dimensions in MDD using individualized functional connectomes. METHODS: Patterns of FC associated with symptom severity were identified using a novel, individualized, functional network parcellation analysis in conjunction with hierarchical clustering. Dimension-specific prediction models were trained to estimate symptom severity in first-episode medication-naïve patients (discovery dataset, n = 95) and replicated in an independent validation dataset (n = 94). The correlation between FC changes and symptom changes was further explored in a treatment dataset (n = 55). RESULTS: Two distinct symptom clusters previously identified in patients with MDD, namely dysphoric and anxiosomatic clusters, were robustly replicated in our data. A connectivity biomarker associated with dysphoric symptoms was identified, which mainly involved the default, dorsal attention, and limbic networks. Critically, this brain-symptom association was confirmed in the validation dataset. Moreover, the marker also tracked dysphoric symptom improvement following a 2-week antidepressant treatment. For comparison, we repeated our analyses using a nonindividualized approach and failed to identify replicable brain-symptom biomarkers. Further quantitative analysis indicated that the generalizability of the connectivity-symptom association was hampered when functional regions were not localized in individuals. CONCLUSIONS: This work reveals robust, replicable FC biomarkers for dysphoric symptoms in MDD, demonstrates the advantage of individual-oriented approach, and emphasizes the importance of independent validation in psychiatric neuroimaging analysis.

A chinese medicine formula (kunbixiao granule) for female rheumatoid arthritis: Study protocol for a double-blind, randomized, placebo-controlled trial.

Introduction: Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting females more than males. Clinical symptoms, disease activity and comorbidities are more severe in females. Moreover, the choice of treatment for females is limited during childbearing age due to the side effects of current drugs. Therefore, developing novel and safer drugs for females is urgently needed. Kunbixiao granules (KBXG), a Chinese medicine formula, has been applied to treat female RA patients in our center as a complementary therapy. However, there is insufficient evidence for its effect. Therefore, we aim to conduct a randomized, controlled, double-blind clinical trial to confirm the efficacy and safety of KBXG for the treatment of female RA. Methods: This study is a single-center, double-blind, randomized, parallel group, placebo-controlled clinical trial. A total of 90 female RA patients with Disease Activity Score for 28 joints (DAS28) > 3.2 will be enrolled. They will be randomly assigned to receive either KBXG or placebo for 12 weeks. The change in DAS28 based on C-reactive protein (DAS28-CRP) and the Clinical Disease Activity Index (CDAI) are the primary outcomes. The secondary outcomes include a rate of achieving 20%, 50% and 70% improvement in the American College Rheumatology criteria (ACR20, ACR50, ACR70), TCM syndrome score, visual analogue scale (VAS), average hands grip strength, the consumption of concomitant medication, Hospital Anxiety and Depression Scale (HADS), lumbar spine bone mineral density (L-BMD) and 7-joint ultrasound score (US7). Any adverse events will also be recorded. Discussion: This trial will provide evidence of KBXG in reducing disease activity, and improving clinical symptoms and quality of life of female RA patients. The long-term effects of KBXG on female RA patients still needs a further follow-up.

The efficacy and safety of Longmu Tang granule for the treatment of atopic dermatitis: study protocol for a single-centred, double-blinded, randomised, placebo-controlled trial.

BACKGROUND: Atopic dermatitis (AD) is a chronic relapsing skin disease that has long-term physical and mental health impacts on children with this condition. Current treatments mainly include anti-inflammatory, antibacterial, and anti-allergic interventions, systemic therapy, and recently emerging target-focused agents. However, these treatments have limited effectiveness and unwanted side effects. The use of traditional Chinese medicine (TCM) in the treatment of AD has a long history, with promising efficacies, low toxicity, and improvements in the quality of life of patients with AD. Longmu Tang granule, a TCM, has been used to effectively treat AD since 2008 through doctors' prescriptions. To scientifically evaluate the clinical efficacy and safety of Longmu Tang granule, we proposed to launch a single-centred, double-blinded, randomised, placebo-controlled trial. METHODS: In this single-centred, double-blinded, randomised, placebo-controlled clinical trial conducted at Xiyuan Hospital of China Academy of Chinese Medical Sciences, a total of 60 participants will be randomly assigned (1:1) to receive the Longmu Tang granule or placebo granule for 8 weeks. The primary outcome will be evaluated using the index of Scoring Atopic Dermatitis. The secondary outcomes will be evaluated using the Children's Dermatology Life Quality Index and the number cancellation test. The mechanistic evidence will be the serum levels of inflammatory cytokines, including immunoglobulin E, tumour necrosis factor-α, interleukin-1, and interleukin-6. DISCUSSION: The results of this trial will provide evidence of the efficacy and safety of the Longmu Tang granule and prove its anti-inflammatory action in patients with AD. TRIAL REGISTRATION: Chinese Clinical Trial Registry Chictr.org ID: ChiCTR2100041591 . Registered on 1 January 2021.

The comparison of curcuminoid formulations or its combination with conventional therapies versus conventional therapies alone for knee osteoarthritis.

BACKGROUND: Presently, curcuminoid formulations or its combination with conventional therapies has been used for the treatment of knee osteoarthritis (KOA). Nevertheless, evidence is limited due to small-sized clinical trials. This study aims to evaluate the efficacy of curcuminoid formulations or its combination with conventional therapies for KOA. METHODS: Randomized controlled trials comparing curcuminoid formulations or its combination with conventional therapies versus conventional therapies, such as non-steroidal antiinflammatory drugs (NSAIDs) and chondroitin sulfate/glucosamine, were searched from databases. RESULTS: In total, 14 studies involving 1533 patients were included. Curcuminoid formulations were comparative to NSAIDs in reducing Visual Analogue Scale (VAS), total Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score, and WOMAC score for pain/stiffness/physical function. No significant difference was seen between the two groups in terms of patients' satisfaction index, patients' global assessment, reduction of several inflammatory factor, rate of drug compliance, and rescue medication. Notably, curcuminoid formulations combined with NSAIDs significantly reduced VAS and WOMAC/Knee injury and OA Outcome Score (KOOS) pain score more than NSAIDs did. In addition, the curcuminoid formulations were superior to chondroitin sulfate/glucosamine in reducing VAS, total WOMAC score, and WOMAC score for stiffness/difficulty in physical function, while no significant difference was seen in reducing WOMAC pain score and Karnofsky Performance Scale score. CONCLUSIONS: Curcuminoid formulations may be considered a promising alternative for treating KOA. Key points • Curcuminoid formulations are comparative to NSAIDs for KOA. • Curcuminoid formulations are superior to chondroitin sulfate/glucosamine for KOA. • Curcuminoid formulations could provide additional benefits in alleviating pain and some adverse events caused by NSAIDs.

Fast cortical surface reconstruction from MRI using deep learning.

Reconstructing cortical surfaces from structural magnetic resonance imaging (MRI) is a prerequisite for surface-based functional and anatomical image analyses. Conventional algorithms for cortical surface reconstruction are computationally inefficient and typically take several hours for each subject, causing a bottleneck in applications when a fast turnaround time is needed. To address this challenge, we propose a fast cortical surface reconstruction (FastCSR) pipeline by leveraging deep machine learning. We trained our model to learn an implicit representation of the cortical surface in volumetric space, termed the "level set representation". A fast volumetric topology correction method and a topology-preserving surface mesh extraction procedure were employed to reconstruct the cortical surface based on the level set representation. Using 1-mm isotropic T1-weighted images, the FastCSR pipeline was able to reconstruct a subject's cortical surfaces within 5 min with comparable surface quality, which is approximately 47 times faster than the traditional FreeSurfer pipeline. The advantage of FastCSR becomes even more apparent when processing high-resolution images. Importantly, the model demonstrated good generalizability in previously unseen data and showed high test-retest reliability in cortical morphometrics and anatomical parcellations. Finally, FastCSR was robust to images with compromised quality or with distortions caused by lesions. This fast and robust pipeline for cortical surface reconstruction may facilitate large-scale neuroimaging studies and has potential in clinical applications wherein brain images may be compromised.

Personalized fMRI Delineates Functional Regions Preserved within Brain Tumors.

OBJECTIVE: Accumulating evidence from invasive cortical stimulation mapping and noninvasive neuroimaging studies indicates that brain function may be preserved within brain tumors. However, a noninvasive approach to accurately and comprehensively delineate individual-specific functional networks in the whole brain, especially in brain tissues within and surrounding tumors, is still lacking. The purpose of the study is to develop a clinically useful technique that can map functional regions within tumoral brains. METHODS: We developed an individual-specific functional network parcellation approach using resting state functional magnetic resonance imaging (rsfMRI) that effectively captured functional networks within and nearby tumors in 20 patients. We examined the accuracy of the functional maps using invasive cortical stimulation and task response. RESULTS: We found that approximately 33.2% of the tumoral mass appeared to be functionally active and demonstrated robust functional connectivity with non-tumoral brain regions. Functional networks nearby tumors were validated by invasive cortical stimulation mapping. Intratumoral sensorimotor networks mapped by our technique could be distinguished by their distinct cortico-cerebellar connectivity patterns and were consistent with hand movement evoked fMRI task activations. Furthermore, in some patients, cognitive networks that were detected in the tumor mass showed long-distance and distributed functional connectivity. INTERPRETATION: Our noninvasive approach to mapping individual-specific functional networks using rsfMRI represents a promising new tool for identifying regions with preserved functional connectivity within and surrounding brain tumors, and could be used as a complement to presurgical planning for patients undergoing tumor resection surgery. ANN NEUROL 2022;91:353-366.

Blood-clotting model and simulation analysis of polyvinyl alcohol-chitosan composite hemostatic materials.

The blood-clotting performance and characteristics of hemostatic materials are critical for their development and actual application. Based on the theory of porous media and characteristics of a non-Newtonian fluid, this study proposed an adsorption factor to characterize the porosity generation and blood coagulation process of hemostatic materials. On this basis, we constructed a physical model of blood coagulation in a porous medium integrated with the power-law fluid model to study the proposed poly(vinyl alcohol)-chitosan (PVA-CS) composite hemostatic material. Moreover, we simulated the dynamic blood flow process and blood coagulation process in the PVA-CS hemostatic material by introducing the physical model. The simulation results show that the blood begins to coagulate, which affects the porosity and permeability of the blood-containing area, resulting in changing the porosity after blood flowed into the hemostatic material. The porosity, permeability, and blood flow rate will approach zero until the generated blood coagulation entirely blocked the porous medium. Besides, simulation can provide the pressure and velocity distribution varying in the coagulation process of hemostatic materials. The temperature will also influence the hemostatic performance of the PVA-CS material. In all, the proposed simulation method enabled the coagulation mechanism of PVA-CS to be revealed from the perspective of blood flow in porous media combined with the adsorption factor.

Dissociable Auditory Cortico-Cerebellar Pathways in the Human Brain Estimated by Intrinsic Functional Connectivity.

The cerebellum, a structure historically associated with motor control, has more recently been implicated in several higher-order auditory-cognitive functions. However, the exact functional pathways that mediate cerebellar influences on auditory cortex (AC) remain unclear. Here, we sought to identify auditory cortico-cerebellar pathways based on intrinsic functional connectivity magnetic resonance imaging. In contrast to previous connectivity studies that principally consider the AC as a single functionally homogenous unit, we mapped the cerebellar connectivity across different parts of the AC. Our results reveal that auditory subareas demonstrating different levels of interindividual functional variability are functionally coupled with distinct cerebellar regions. Moreover, auditory and sensorimotor areas show divergent cortico-cerebellar connectivity patterns, although sensorimotor areas proximal to the AC are often functionally grouped with the AC in previous connectivity-based network analyses. Lastly, we found that the AC can be functionally segmented into highly similar subareas based on either cortico-cerebellar or cortico-cortical functional connectivity, suggesting the existence of multiple parallel auditory cortico-cerebellar circuits that involve different subareas of the AC. Overall, the present study revealed multiple auditory cortico-cerebellar pathways and provided a fine-grained map of AC subareas, indicative of the critical role of the cerebellum in auditory processing and multisensory integration.

Protective Effects of Allicin on Acute Myocardial Infarction in Rats via Hydrogen Sulfide-mediated Regulation of Coronary Arterial Vasomotor Function and Myocardial Calcium Transport.

Acute myocardial infarction (AMI) is a condition with high morbidity and mortality, for which effective treatments are lacking. Allicin has been reported to exert therapeutic effects on AMI, but the underlying mechanisms of its action have not been fully elucidated. To investigate this, a rat model of AMI was generated by ligating the left anterior descending branch of the coronary artery. DL-propargylglycine (PAG), a specific hydrogen sulfide (H2S) synthetase inhibitor, was used to examine the effects of allicin on H2S production. Isolated coronary arteries and cardiomyocytes were assessed for vascular reactivity and cellular Ca2+ transport using a multiwire myography system and a cell-contraction-ion detection system, respectively. Allicin administration improved cardiac function and myocardial pathology, reduced myocardial enzyme levels, and increased H2S and H2S synthetase levels. Allicin administration resulted in concentration-dependent effects on coronary artery dilation, which were mediated by receptor-dependent Ca2+ channels, ATP-sensitive K+ channels, and sarcoplasmic reticulum (SR) Ca2+ release induced by the ryanodine receptor. Allicin administration improved Ca2+ homeostasis in cardiomyocytes by increasing cardiomyocyte contraction, Ca2+ transient amplitude, myofilament sensitivity, and SR Ca2+ content. Allicin also enhanced Ca2+ uptake via SR Ca2+-ATPase and Ca2+ removal via the Na+/Ca2+ exchanger, and it reduced SR Ca2+ leakage. Notably, the protective effects of allicin were partially attenuated by blockade of H2S production with PAG. Our findings provide novel evidence that allicin-induced production of H2S mediates coronary artery dilation and regulation of Ca2+ homeostasis in AMI. Our study presents a novel mechanistic insight into the anti-AMI effects of allicin and highlights the therapeutic potential of this compound.

Large-Scale Functional Brain Network Architecture Changes Associated With Trauma-Related Dissociation.

OBJECTIVE: Dissociative experiences commonly occur in response to trauma, and while their presence strongly affects treatment approaches in posttraumatic spectrum disorders, their etiology remains poorly understood and their phenomenology incompletely characterized. Methods to reliably assess the severity of dissociation symptoms, without relying solely on self-report, would have tremendous clinical utility. Brain-based measures have the potential to augment symptom reports, although it remains unclear whether brain-based measures of dissociation are sufficiently sensitive and robust to enable individual-level estimation of dissociation severity based on brain function. The authors sought to test the robustness and sensitivity of a brain-based measure of dissociation severity. METHODS: An intrinsic network connectivity analysis was applied to functional MRI scans obtained from 65 women with histories of childhood abuse and current posttraumatic stress disorder (PTSD). The authors tested for continuous measures of trauma-related dissociation using the Multidimensional Inventory of Dissociation. Connectivity estimates were derived with a novel machine learning technique using individually defined homologous functional regions for each participant. RESULTS: The models achieved moderate ability to estimate dissociation, after controlling for childhood trauma and PTSD severity. Connections that contributed the most to the estimation mainly involved the default mode and frontoparietal control networks. By contrast, all models performed at chance levels when using a conventional group-based network parcellation. CONCLUSIONS: Trauma-related dissociative symptoms, distinct from PTSD and childhood trauma, can be estimated on the basis of network connectivity. Furthermore, between-network brain connectivity may provide an unbiased estimate of symptom severity, paving the way for more objective, clinically useful biomarkers of dissociation and advancing our understanding of its neural mechanisms.