Predicting Brain Age and Gender from Brain Volume Data Using Variational Quantum Circuits.

The morphology of the brain undergoes changes throughout the aging process, and accurately predicting a person's brain age and gender using brain morphology features can aid in detecting atypical brain patterns. Neuroimaging-based estimation of brain age is commonly used to assess an individual's brain health relative to a typical aging trajectory, while accurately classifying gender from neuroimaging data offers valuable insights into the inherent neurological differences between males and females. In this study, we aimed to compare the efficacy of classical machine learning models with that of a quantum machine learning method called a variational quantum circuit in estimating brain age and predicting gender based on structural magnetic resonance imaging data. We evaluated six classical machine learning models alongside a quantum machine learning model using both combined and sub-datasets, which included data from both in-house collections and public sources. The total number of participants was 1157, ranging from ages 14 to 89, with a gender distribution of 607 males and 550 females. Performance evaluation was conducted within each dataset using training and testing sets. The variational quantum circuit model generally demonstrated superior performance in estimating brain age and gender classification compared to classical machine learning algorithms when using the combined dataset. Additionally, in benchmark sub-datasets, our approach exhibited better performance compared to previous studies that utilized the same dataset for brain age prediction. Thus, our results suggest that variational quantum algorithms demonstrate comparable effectiveness to classical machine learning algorithms for both brain age and gender prediction, potentially offering reduced error and improved accuracy.

Functional and Structural Brain Abnormalities and Clinical Characteristics of Male Patients with Alcohol Dependence.

Even though many previous studies have reported structural or functional brain abnormalities in patients with alcohol dependence (ADPs), studies observing the structural and functional abnormalities associated with the clinical characteristics of ADPs utilizing a multimodal approach are still scarce. The aim of this study was to demonstrate structural and functional brain abnormalities and their association with the clinical characteristics of alcoholism in male ADPs. Fifteen healthy male controls (HCs) and 15 male ADPs who had been diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders 5 criteria underwent T1-weighted imaging and resting-state functional magnetic resonance imaging (MRI) scans. The MRI data were postprocessed using statistical parametric mapping for structural analysis and CONN-fMRI functional connectivity (FC) tools for functional analysis. In comparison with male HCs, male ADPs were characterized by significantly reduced volumes of the white matter in the left globus pallidus (GP) (p-FDR < 0.05). This region affected the altered resting-state FC patterns in male ADPs. Interestingly, an abnormal FC in the precuneus and its positive correlation with the alcohol-use disorder identification test score were observed in ADPs (r = 0.546, p = 0.036). Based on the observations, it could be concluded that the GP serves as a neural marker that impacts abnormal functional networks in men with alcohol dependence. These findings have important clinical implications as they provide insights into the neural mechanism underlying the anatomical, functional, and clinical features of alcoholism.

Salvia miltiorrhiza Alleviates Memory Deficit Induced by Ischemic Brain Injury in a Transient MCAO Mouse Model by Inhibiting Ferroptosis.

Salvia miltiorrhiza (SM) has been used in oriental medicine for its neuroprotective effects against cardiovascular diseases and ischemic stroke. In this study, we investigated the therapeutic mechanism underlying the effects of SM on stroke using a transient middle cerebral artery occlusion (tMCAO) mouse model. Our results showed that SM administration significantly attenuated acute brain injury, including brain infarction and neurological deficits, 3 days after tMCAO. This was confirmed by our magnetic resonance imaging (MRI) study, which revealed a reduction in brain infarction with SM administration, as well as our magnetic resonance spectroscopy (MRS) study, which demonstrated the restoration of brain metabolites, including taurine, total creatine, and glutamate. The neuroprotective effects of SM were associated with the reduction in gliosis and upregulation of inflammatory cytokines, such as interleukin-6 (IL-6) and Tumor necrosis factor-α (TNF-α), along with the upregulation of phosphorylated STAT3 in post-ischemic brains. SM also reduced the levels of 4-Hydroxynonenal (4-HNE) and malondialdehyde (MDA), which are markers of lipid peroxidation, induced by oxidative stress upregulation in the penumbra of the tMCAO mouse brain. SM administration attenuated ischemic neuronal injury by inhibiting ferroptosis. Additionally, post-ischemic brain synaptic loss and neuronal loss were alleviated by SM administration, as demonstrated by Western blot and Nissl staining. Moreover, daily administration of SM for 28 days after tMCAO significantly reduced neurological deficits and improved survival rates in tMCAO mice. SM administration also resulted in improvement in post-stroke cognitive impairment, as measured by the novel object recognition and passive avoidance tests in tMCAO mice. Our findings suggest that SM provides neuroprotection against ischemic stroke and has potential as a therapeutic agent.

Signal-to-Noise Ratio Enhancement of Single-Voxel In Vivo 31P and 1H Magnetic Resonance Spectroscopy in Mice Brain Data Using Low-Rank Denoising.

Magnetic resonance spectroscopy (MRS) is a noninvasive technique for measuring metabolite concentration. It can be used for preclinical small animal brain studies using rodents to provide information about neurodegenerative diseases and metabolic disorders. However, data acquisition from small volumes in a limited scan time is technically challenging due to its inherently low sensitivity. To mitigate this problem, this study investigated the feasibility of a low-rank denoising method in enhancing the quality of single voxel multinuclei (31P and 1H) MRS data at 9.4 T. Performance was evaluated using in vivo MRS data from a normal mouse brain (31P and 1H) and stroke mouse model (1H) by comparison with signal-to-noise ratios (SNRs), Cramer-Rao lower bounds (CRLBs), and metabolite concentrations of a linear combination of model analysis results. In 31P MRS data, low-rank denoising resulted in improved SNRs and reduced metabolite quantification uncertainty compared with the original data. In 1H MRS data, the method also improved the SNRs, CRLBs, but it performed better for 31P MRS data with relatively simpler patterns compared to the 1H MRS data. Therefore, we suggest that the low-rank denoising method can improve spectra SNR and metabolite quantification uncertainty in single-voxel in vivo 31P and 1H MRS data, and it might be more effective for 31P MRS data. The main contribution of this study is that we demonstrated the effectiveness of the low-rank denoising method on small-volume single-voxel MRS data. We anticipate that our results will be useful for the precise quantification of low-concentration metabolites, further reducing data acquisition voxel size, and scan time in preclinical MRS studies.

Association between Changes in Cortical Thickness and Functional Connectivity in Male Patients with Alcohol-dependence.

Many studies have reported structural or functional brain changes in patients with alcohol-dependence (ADPs). However, there has been an insufficient number of studies that were able to identify functional changes along with structural abnormalities in ADPs. Since neuronal cell death can lead to abnormal brain function, a multimodal approach combined with structural and functional studies is necessary to understand definitive neural mechanisms. Here, we explored regional difference in cortical thickness and their impact on functional connection along with clinical relevance. Fifteen male ADPs who have been diagnosed by the Diagnostic and Statistical Manual of Mental Disorders 5 (DSM-5) underwent highresolution T1 and resting-state functional magnetic resonance imaging (MRI) scans together with 15 male healthy controls (HCs). The acquired MRI data were post-processed using the Computational Anatomy Toolbox (CAT 12) and CONN-fMRI functional connectivity (FC) toolbox with Statistical Parametric Mapping (SPM 12). When compared with male HCs, the male ADPs showed significantly reduced cortical thickness in the left postcentral gyrus (PoCG), an area responsible for altered resting-state FC patterns in male ADPs. Statistically higher FCs in PoCG-cerebellum (Cb) and lower FCs in PoCG-supplementary motor area (SMA) were observed in male ADPs. In particular, the FCs with PoCG-Cb positively correlated with alcohol use disorders identification test (AUDIT) scores in male ADPs. Our findings suggest that the association of brain structural abnormalities and FC changes could be a characteristic difference in male ADPs. These findings can be useful in understanding the neural mechanisms associated with anatomical, functional and clinical features of individuals with alcoholism.

7 Tesla magnetic resonance imaging of caudal anterior cingulate and posterior cingulate cortex atrophy in patients with trigeminal neuralgia.

The cingulate cortex (CC) is a brain region that plays a key role in pain processing, but CC abnormalities are not unclear in patients with trigeminal neuralgia (TN). The purpose of this study was to determine the central causal mechanisms of TN and the surrounding brain structure in healthy controls and patients with TN using 7 Tesla (T) magnetic resonance imaging (MRI). Whole-brain parcellation in gray matter volume and thickness was assessed in 15 patients with TN and 16 healthy controls matched for sex, age, and regional variability using T1-weighted imaging. Regions of interest (ROIs) were measured in rostral anterior CC (rACC), caudal anterior CC (cACC) and posterior CC (PCC). We also investigated associations between gray matter volume or thickness and clinical symptoms, such as pain duration, Barrow Neurologic Institute (BNI) scores, offender vessel, and medications, in patients with TN. The cACC and PCC exhibited gray matter atrophy and reduced thickness between the TN and control groups. However, the rACC did not. Cortical volumes were negatively correlated with pain duration in transverse and inferior temporal areas, and thickness was also negatively correlated with pain duration in superior frontal and parietal areas. The cACC and PCC gray matter atrophy occurred in the patients with TN, and pain duration was associated with frontal, parietal, and temporal cortical regions. These results suggest that the cACC, PCC but not the rACC are associated with central pain mechanisms in TN.