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.

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.

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.

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.

Stroke affects over 12 million people annually, leading to high mortality, long-term disability, and substantial healthcare costs. Although East Asian herbal medicines are widely used for stroke treatment, the pathways of operation they use remain poorly understood. Our study investigates the neuroprotective properties of Astragalus mongholicus (AM) in acute ischemic stroke using photothrombotic (PTB) and transient middle cerebral artery occlusion (tMCAO) mouse models, as well as an in vitro oxygen-glucose deprivation (OGD) model. Post-OGD treatment with AM improved cell viability in mouse neuroblastoma cells, likely by reducing reactive oxygen species (ROS). Mice received short-term (0–2 days) or long-term (0–27 days) AM treatment post-stroke. Infarct size was assessed using a 2,3,5-triphenyl tetrazolium chloride (TTC) staining procedure alongside magnetic resonance imaging (MRI). Neuroprotective metabolites including inositol (Ins), glycerophosphocholine+phosphocholine (GPc+ PCh), N-acetylaspartate+N-acetylaspartylglutamate (NAA+NAAG), creatine + phosphocreatine (Cr+PCr), and glutamine+glutamate (Glx) were analyzed via magnetic resonance spectroscopy (MRS). Gliosis was assessed using GFAP and Iba-1 immunohistochemical markers, while neurological deficits were quantified with modified neurological severity scores (mNSS). Motor and cognitive functions were assessed using cylinder, rotarod, and novel object recognition (NOR) tests. AM treatment significantly reduced ischemic damage and improved neurological outcomes in both acute and chronic stages of PTB and tMCAO models. Additionally, AM increased neuroprotective metabolites levels, reduced gliosis, and decreased oxidative stress, as evidenced by reduced inducible nitric oxide synthase (iNOS). These findings highlight the antioxidant properties of AM and its strong therapeutic potential for promoting recovery after ischemic stroke by alleviating neurological deficits, reducing gliosis, and mitigating oxidative stress.

Ischemic stroke, caused by blocked cerebral blood flow, requires prompt intervention to prevent severe motor and cognitive impairments. Despite extensive drug development efforts, the failure rate of clinical trials remains high, highlighting the need for novel therapeutic approaches. This study investigated the therapeutic potential of a natural herbal extract mixture of Astragalus mongholicus Bunge (AM) and Scutellaria baicalensis Georgi (SB), traditionally used in Eastern Asian herbal medicine (EAHM) for ischemic stroke treatment. Using transient middle cerebral artery occlusion (tMCAO) and photothrombotic (PTB) mouse models, oral administration of the AM-SB mixture was evaluated during both acute and chronic phases. Results showed that AM-SB significantly reduced infarction volume, inflammation (IL-1β, TNF-α), and pyroptosis-related markers (NLRP3, GSDMD, ASC, Caspase-1), while decreasing gliosis and improving cerebral metabolites. Behavioral assessments revealed that early and sustained AM-SB intervention enhanced motor and cognitive functions, as measured by mNSS, Rotarod, Novel Object Recognition, and Passive Avoidance tests. These findings suggest that AM-SB extract is a promising alternative therapy for ischemic stroke management.