Natural products that alleviate depression: The putative role of autophagy.

Major depressive disorder (MDD) is a common mental disorder that severely disrupts psychosocial function and decreases the quality of life. Although the pathophysiological mechanism underlying MDD is complex and remains unclear, emerging evidence suggests that autophagy dysfunction plays a role in MDD occurrence and progression. Natural products serve as a major source of drug discovery and exert tremendous potential in developing antidepressants. Recently published reports are paying more attention on the autophagy regulatory effect of antidepressant natural products. In this review, we comprehensively discuss the abnormal changes occurred in multiple autophagy stages in MDD patients, and animal and cell models of depression. Importantly, we emphasize the regulatory mechanism of antidepressant natural products on disturbed autophagy, including monomeric compounds, bioactive components, crude extracts, and traditional Chinese medicine formulae. Our comprehensive review suggests that enhancing autophagy might be a novel approach for MDD treatment, and natural products restore autophagy homeostasis to facilitate the renovation of mitochondria, impede neuroinflammation, and enhance neuroplasticity, thereby alleviating depression.

Estimating trans-ancestry genetic correlation with unbalanced data resources.

The aim of this paper is to propose a novel method for estimating trans-ancestry genetic correlations in genome-wide association studies (GWAS) using genetically-predicted observations. These correlations describe how genetic architecture of complex traits varies among populations. Our new estimator corrects for biases arising from prediction errors in high-dimensional weak GWAS signals, while addressing the ethnic diversity inherent in GWAS data, such as linkage disequilibrium (LD) differences. A distinguishing feature of our approach is its flexibility regarding sample sizes: it necessitates a large GWAS sample only from one population, while the secondary population may have a much smaller cohort, even in the hundreds. This design directly addresses the existing imbalance in GWAS data resources, where datasets for European populations typically outnumber those of non-European ancestries. Through extensive simulations and real data analysis from the UK Biobank study encompassing 26 complex traits, we validate the reliability of our method. Our results illuminate the broader implications of transferring genetic findings across diverse populations.

ON BLOCKWISE AND REFERENCE PANEL-BASED ESTIMATORS FOR GENETIC DATA PREDICTION IN HIGH DIMENSIONS.

Genetic prediction holds immense promise for translating genetic discoveries into medical advances. As the high-dimensional covariance matrix (or the linkage disequilibrium (LD) pattern) of genetic variants often presents a block-diagonal structure, numerous methods account for the dependence among variants in predetermined local LD blocks. Moreover, due to privacy considerations and data protection concerns, genetic variant dependence in each LD block is typically estimated from external reference panels rather than the original training data set. This paper presents a unified analysis of blockwise and reference panel-based estimators in a high-dimensional prediction framework without sparsity restrictions. We find that, surprisingly, even when the covariance matrix has a block-diagonal structure with well-defined boundaries, blockwise estimation methods adjusting for local dependence can be substantially less accurate than methods controlling for the whole covariance matrix. Further, estimation methods built on the original training data set and external reference panels are likely to have varying performance in high dimensions, which may reflect the cost of having only access to summary level data from the training data set. This analysis is based on novel results in random matrix theory for block-diagonal covariance matrix. We numerically evaluate our results using extensive simulations and real data analysis in the UK Biobank.

An atlas of genetic effects on the monocyte methylome across European and African populations.

Elucidating the genetic architecture of DNA methylation (DNAm) is crucial for decoding the etiology of complex diseases. However, current epigenomic studies often suffer from incomplete coverage of methylation sites and the use of tissues containing heterogeneous cell populations. To address these challenges, we present a comprehensive human methylome atlas based on deep whole-genome bisulfite sequencing (WGBS) and whole-genome sequencing (WGS) of purified monocytes from 298 European Americans (EA) and 160 African Americans (AA) in the Louisiana Osteoporosis Study. Our atlas enables the analysis of over 25 million DNAm sites. We identified 1,383,250 and 1,721,167 methylation quantitative trait loci (meQTLs) in cis -regions for EA and AA populations, respectively, with 880,108 sites shared between ancestries. While cis -meQTLs exhibited population-specific patterns, primarily due to differences in minor allele frequencies, shared cis -meQTLs showed high concordance across ancestries. Notably, cis -heritability estimates revealed significantly higher mean values in the AA population (0.09) compared to the EA population (0.04). Furthermore, we developed population-specific DNAm imputation models using Elastic Net, enabling methylome-wide association studies (MWAS) for 1,976,046 and 2,657,581 methylation sites in EA and AA, respectively. The performance of our MWAS models was validated through a systematic multi-ancestry analysis of 41 complex traits from the Million Veteran Program. Our findings bridge the gap between genomics and the monocyte methylome, uncovering novel methylation-phenotype associations and their transferability across diverse ancestries. The identified meQTLs, MWAS models, and data resources are freely available at www.gcbhub.org and https://osf.io/gct57/ .

The Interaction Effects of Sex, Age, APOE and Common Health Risk Factors on Human Brain Functions.

Importance: Nonlinear changes in brain function during aging are shaped by a complex interplay of factors, including sex, age, genetics, and modifiable health risk factors. However, the combined effects and underlying mechanisms of these factors on brain functional connectivity remain poorly understood. Objective: To comprehensively investigate the combined associations of sex, age, APOE genotypes, and ten common modifiable health risk factors with brain functional connectivities during aging. Design Setting and Participants: This analysis used data from 36,630 UK Biobank participants, aged 44-81, who were assessed for sex, age, APOE genotypes, 10 health risk factors, and brain functional connectivities through resting-state functional magnetic resonance imaging. Main Outcomes and Measures: Brain functional connectivities were evaluated through within- and between-network functional connectivities and connectivity strength. Associations between risk factors and brain functional connectivities, including their interaction effects, were analyzed. Results: Hypertension, BMI, and education were the top three influential factors. Sex-specific effects were also observed in interactions involving APOE4 gene, smoking, alcohol consumption, diabetes, BMI, and education. Notably, a negative sex-excessive alcohol interaction showed a stronger negative effect on functional connectivities in males, particularly between the dorsal attention network and the language network, while moderate alcohol consumption appeared to have protective effects. A significant negative interaction between sex and APOE4 revealed a greater reduction in functional connectivity between the cingulo-opercular network and the posterior multimodal network in male APOE4 carriers. Additional findings included a negative age-BMI interaction between the visual and dorsal attention networks, and a positive age-hypertension interaction between the frontoparietal and default mode networks. Conclusions and Relevance: The findings highlight significant sex disparities in the associations between age, the APOE-ε4 gene, modifiable health risk factors, and brain functional connectivity, emphasizing the necessity of jointly considering these factors to gain a deeper understanding of the complex processes underlying brain aging.

Benchmarking DNA Foundation Models for Genomic Sequence Classification.

The rapid advancement of DNA foundation language models has revolutionized the field of genomics, enabling the decoding of complex patterns and regulatory mechanisms within DNA sequences. However, the current evaluation of these models often relies on fine-tuning and limited datasets, which introduces biases and limits the assessment of their true potential. Here, we present a benchmarking study of three recent DNA foundation language models, including DNABERT-2, Nucleotide Transformer version-2 (NT-v2), and HyenaDNA, focusing on the quality of their zero-shot embeddings across a diverse range of genomic tasks and species through analyses of 57 real datasets. We found that DNABERT-2 exhibits the most consistent performance across human genome-related tasks, while NT-v2 excels in epigenetic modification detection. HyenaDNA stands out for its exceptional runtime scalability and ability to handle long input sequences. Importantly, we demonstrate that using mean token embedding consistently improves the performance of all three models compared to the default setting of sentence-level summary token embedding, with average AUC improvements ranging from 4.3% to 9.7% for different DNA foundation models. Furthermore, the performance differences between these models are significantly reduced when using mean token embedding. Our findings provide a framework for selecting and optimizing DNA language models, guiding researchers in applying these tools effectively in genomic studies.

Eye-brain connections revealed by multimodal retinal and brain imaging genetics.

The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.

Hybridization of bimetallic cobalt-molybdenum oxide multihole nanosheets with selenium adulteration as advanced bifunctional electrocatalysts for boosting overall water splitting.

Electrocatalytic water splitting produces green and pollution-free hydrogen as a clean energy carrier, which can effectively alleviate energy crisis. In this paper, bimetallic and selenium doped cobalt molybdate (Se-CoMoO4) nanosheets with rough surface are resoundingly prepared. The multihole Se-CoMoO4 nanosheets display ultrathin and rectangular architecture with the dimensions of âˆ¼ 3.5 µm and 700 nm for length and width, respectively. The Se-CoMoO4 electrocatalyst shows remarkable water electrolysis activity and stability. The overpotentials of oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) are 270 and 63.3 mV at 10 mA cm-2, along with low Tafel slopes of 51.6 and 62.0 mV dec-1. Furthermore, the Se-CoMoO4 couple electrolyzer merely requires a cell voltage of 1.48 V to achieve 10 mA cm-2 current density and presents no apparent attenuation for 30 h. This investigation declares that the hybridization of transition bimetallic oxide with nonmetallic adulteration can afford a tactic for the preparation of bifunctional non-precious metal-based electrocatalysts.

The genetic architecture of biological age in nine human organ systems.

Investigating the genetic underpinnings of human aging is essential for unraveling the etiology of and developing actionable therapies for chronic diseases. Here, we characterize the genetic architecture of the biological age gap (BAG; the difference between machine learning-predicted age and chronological age) across nine human organ systems in 377,028 participants of European ancestry from the UK Biobank. The BAGs were computed using cross-validated support vector machines, incorporating imaging, physical traits and physiological measures. We identify 393 genomic loci-BAG pairs (P < 5 × 10-8) linked to the brain, eye, cardiovascular, hepatic, immune, metabolic, musculoskeletal, pulmonary and renal systems. Genetic variants associated with the nine BAGs are predominantly specific to the respective organ system (organ specificity) while exerting pleiotropic links with other organ systems (interorgan cross-talk). We find that genetic correlation between the nine BAGs mirrors their phenotypic correlation. Further, a multiorgan causal network established from two-sample Mendelian randomization and latent causal variance models revealed potential causality between chronic diseases (for example, Alzheimer's disease and diabetes), modifiable lifestyle factors (for example, sleep duration and body weight) and multiple BAGs. Our results illustrate the potential for improving human organ health via a multiorgan network, including lifestyle interventions and drug repurposing strategies.

Associations between longitudinal changes in sleep stages and risk of cognitive decline in older men.

STUDY OBJECTIVES: To investigate the relationships between longitudinal changes in sleep stages and the risk of cognitive decline in older men. METHODS: This study included 978 community-dwelling older men who participated in the first (2003-2005) and second (2009-2012) sleep ancillary study visits of the Osteoporotic Fractures in Men Study. We examined the longitudinal changes in sleep stages at the initial and follow-up visits, and the association with concurrent clinically relevant cognitive decline during the 6.5-year follow-up. RESULTS: Men with low to moderate (quartile 2, Q2) and moderate increase (Q3) in N1 sleep percentage had a reduced risk of cognitive decline on the modified mini-mental state examination compared to those with a substantial increase (Q4) in N1 sleep percentage. Additionally, men who experienced a low to moderate (Q2) increase in N1 sleep percentage had a lower risk of cognitive decline on the Trails B compared with men in the reference group (Q4). Furthermore, men with the most pronounced reduction (Q1) in N2 sleep percentage had a significantly higher risk of cognitive decline on the Trails B compared to those in the reference group (Q4). No significant association was found between changes in N3 and rapid eye movement sleep and the risk of cognitive decline. CONCLUSIONS: Our results suggested that a relatively lower increase in N1 sleep showed a reduced risk of cognitive decline. However, a pronounced decrease in N2 sleep was associated with concurrent cognitive decline. These findings may help identify older men at risk of clinically relevant cognitive decline.

A new 3,4-dinorsteroid from the marine sponge Cliona sp.

A new steroid, 2a-oxa-2-oxo-5ß-hydroxy-3,4-dinor-24-methylcholesta-22E-ene (1), together with 10 known ones (2-11), was isolated from the marine sponge Cliona sp. The structures of these compounds were determined by the spectroscopic methods (UV, IR, MS, and NMR) and X-ray diffraction analysis. Compound 1 was the third example of 3,4-dinorsteroid with a hemiketal at C-5 that was isolated from the natural source. In addition, the antibacterial activities of these compounds were also evaluated. However, none of them exhibited significant inhibition effects.

Multi-organ imaging-derived polygenic indexes for brain and body health.

The UK Biobank (UKB) imaging project is a crucial resource for biomedical research, but is limited to 100,000 participants due to cost and accessibility barriers. Here we used genetic data to predict heritable imaging-derived phenotypes (IDPs) for a larger cohort. We developed and evaluated 4,375 IDP genetic scores (IGS) derived from UKB brain and body images. When applied to UKB participants who were not imaged, IGS revealed links to numerous phenotypes and stratified participants at increased risk for both brain and somatic diseases. For example, IGS identified individuals at higher risk for Alzheimer's disease and multiple sclerosis, offering additional insights beyond traditional polygenic risk scores of these diseases. When applied to independent external cohorts, IGS also stratified those at high disease risk in the All of Us Research Program and the Alzheimer's Disease Neuroimaging Initiative study. Our results demonstrate that, while the UKB imaging cohort is largely healthy and may not be the most enriched for disease risk management, it holds immense potential for stratifying the risk of various brain and body diseases in broader external genetic cohorts.

Thoracic Aortic 3-Dimensional Geometry: Effects of Aging and Genetic Determinants.

Background: Aortic structure impacts cardiovascular health through multiple mechanisms. Aortic structural degeneration occurs with aging, increasing left ventricular afterload and promoting increased arterial pulsatility and target organ damage. Despite the impact of aortic structure on cardiovascular health, three-dimensional (3D) aortic geometry has not been comprehensively characterized in large populations. Methods: We segmented the complete thoracic aorta using a deep learning architecture and used morphological image operations to extract aortic geometric phenotypes (AGPs, including diameter, length, curvature, and tortuosity) across multiple subsegments of the thoracic aorta. We deployed our segmentation approach on imaging scans from 54,241 participants in the UK Biobank and 8,456 participants in the Penn Medicine Biobank. Age-related structural remodeling was quantified on a reference cohort of normative participants. The genetic architecture of three-dimensional aortic geometry was quantified using genome-wide association studies, followed by gene-level analysis and drug-gene interactions. Results: Aging was associated with various 3D-geometric changes, reflecting structural aortic degeneration, including decreased arch unfolding, descending aortic lengthening and luminal dilation across multiple subsegments of the thoracic aorta. Male aortas exhibited increased length and diameters compared to female aortas across all age ranges, whereas female aortas exhibited increased curvature compared with males. We identified 209 novel genetic loci associated with various 3D-AGPs. 357 significant gene-level associations were uncovered, with Fibrillin-2 gene polymorphisms being identified as key determinants of aortic arch structure. Drug-gene interaction analysis identified 25 cardiovascular drugs potentially interacting with aortic geometric loci. Conclusion: Our analysis identified key patterns of aortic structural degeneration linked to aging. We present the first GWAS results for multiple 3D-structural parameters of the aorta, including length, curvature, and tortuosity. Additionally, we confirm various loci associated with aortic diameter. These results expand the genetic loci associated aortic structure and will provide crucial insights into the joint interplay between aging, genetics and cardiovascular structure.

The Janus face of HIF-1α in ischemic stroke and the possible associated pathways.

Stroke is the most devastating disease, causing paralysis and eventually death. Many clinical and experimental trials have been done in search of a new safe and efficient medicine; nevertheless, scientists have yet to discover successful remedies that are also free of adverse effects. This is owing to the variability in intensity, localization, medication routes, and each patient's immune system reaction. HIF-1α represents the modern tool employed to treat stroke diseases due to its functions: downstream genes such as glucose metabolism, angiogenesis, erythropoiesis, and cell survival. Its role can be achieved via two downstream EPO and VEGF strongly related to apoptosis and antioxidant processes. Recently, scientists paid more attention to drugs dealing with the HIF-1 pathway. This review focuses on medicines used for ischemia treatment and their potential HIF-1α pathways. Furthermore, we discussed the interaction between HIF-1α and other biological pathways such as oxidative stress; however, a spotlight has been focused on certain potential signalling contributed to the HIF-1α pathway. HIF-1α is an essential regulator of oxygen balance within cells which affects and controls the expression of thousands of genes related to sustaining homeostasis as oxygen levels fluctuate. HIF-1α's role in ischemic stroke strongly depends on the duration and severity of brain damage after onset. HIF-1α remains difficult to investigate, particularly in ischemic stroke, due to alterations in the acute and chronic phases of the disease, as well as discrepancies between the penumbra and ischemic core. This review emphasizes these contrasts and analyzes the future of this intriguing and demanding field.

Diagnostic Performance of Radiomics and Deep Learning to Identify Benign and Malignant Soft Tissue Tumors: A Systematic Review and Meta-analysis.

RATIONALE AND OBJECTIVES: To systematically evaluate the application value of radiomics and deep learning (DL) in the differential diagnosis of benign and malignant soft tissue tumors (STTs). MATERIALS AND METHODS: A systematic review was conducted on studies published up to December 11, 2023, that utilized radiomics and DL methods for the diagnosis of STTs. The methodological quality and risk of bias were evaluated using the Radiomics Quality Score (RQS) 2.0 system and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, respectively. A bivariate random-effects model was used to calculate the summarized sensitivity and specificity. To identify factors contributing to heterogeneity, meta-regression and subgroup analyses were performed to assess the following covariates: diagnostic modality, region/volume of interest, imaging examination, study design, and pathology type. The asymmetry of Deeks' funnel plot was used to assess publication bias. RESULTS: A total of 21 studies involving 3866 patients were included, with 13 studies using independent test/validation sets included in the quantitative statistical analysis. The average RQS was 21.31, with substantial or near-perfect inter-rater agreement. The combined sensitivity and specificity were 0.84 (95% CI: 0.76-0.89) and 0.88 (95% CI: 0.69-0.96), respectively. Meta-regression and subgroup analyses showed that study design and the region/volume of interest were significant factors affecting study heterogeneity (P < 0.05). No publication bias was observed. CONCLUSION: Radiomics and DL can accurately distinguish between benign and malignant STTs. Future research should concentrate on enhancing the rigor of study designs, conducting multicenter prospective validations, amplifying the interpretability of DL models, and integrating multimodal data to elevate the diagnostic accuracy and clinical utility of soft tissue tumor assessments.

Analyzing bivariate cross-trait genetic architecture in GWAS summary statistics with the BIGA cloud computing platform.

As large-scale biobanks provide increasing access to deep phenotyping and genomic data, genome-wide association studies (GWAS) are rapidly uncovering the genetic architecture behind various complex traits and diseases. GWAS publications typically make their summary-level data (GWAS summary statistics) publicly available, enabling further exploration of genetic overlaps between phenotypes gathered from different studies and cohorts. However, systematically analyzing high-dimensional GWAS summary statistics for thousands of phenotypes can be both logistically challenging and computationally demanding. In this paper, we introduce BIGA (https://bigagwas.org/), a website that aims to offer unified data analysis pipelines and processed data resources for cross-trait genetic architecture analyses using GWAS summary statistics. We have developed a framework to implement statistical genetics tools on a cloud computing platform, combined with extensive curated GWAS data resources. Through BIGA, users can upload data, submit jobs, and share results, providing the research community with a convenient tool for consolidating GWAS data and generating new insights.

The value of ultrasound in combination with 99mTc-MIBI imaging department of ultrasound medicine, for the diagnosis of ectopic parathyroid glands in the thyroid gland in patients with secondary hyperparathyroidism.

To investigate the value of preoperative ultrasound combined with 99mTc-MIBI imaging for the diagnosis of ectopic intrathyroid parathyroid gland (ETPG) in patients with secondary hyperparathyroidism (SHPT). One hundred and eleven patients with SHPT who underwent total parathyroidectomy plus forearm transplantation from January 2015 to January 2022 in the Third Hospital of Hebei Medical University were selected. All patients underwent routine preoperative ultrasonography and 99mTc-MIBI imaging, and with pathological diagnosis as the gold standard, the clinical data of ETPG patients were selected, including clinical manifestations, laboratory tests, preoperative ultrasonography and 99mTc-MIBI imaging for localization and diagnosis, intraoperative exploration and postoperative pathology, and postoperative follow-up. To analyze the ultrasound manifestations of preoperative parathyroid hyperplasia and the results of 99mTc-MIBI imaging in patients with ETPG. Among 111 patients with SHPT, there were 5 patients with ETPG, 1 male and 4 females with a mean age of (45.00 ±â€…5.05) years, and 6 ectopic parathyroid glands were located in the thyroid gland. The incidence of ETPG was 4.5% (5/111), 4 were detected by ultrasound, 2 were not detected with a diagnostic accuracy of 66.7% (4/6), 3 were positive for 99mTc-MIBI imaging, 3 were negative with a diagnostic accuracy of 50.0% (3/6). Among them, one was not detected by ultrasound, but was positive for 99mTc-MIBI imaging, 2 with negative 99mTc-MIBI imaging, but all were detected by ultrasound, and one with negative 99mTc-MIBI imaging was detected by ultrasound but misdiagnosed as a thyroid nodule. A total of 5 ETPGs were detected by ultrasound combined with 99mTc-MIBI imaging, with a diagnostic accuracy of 83.3% (5/6). Patients' postoperative serum calcium and serum parathyroid hormone (PTH) levels were normalized or significantly decreased from preoperative levels. Ultrasound combined with 99mTc-MIBI imaging can achieve higher accuracy than either examination alone in the preoperative localization and diagnosis of ETPG in SHPT patients.

Two new diketopiperazines from the marine sponge Dysidea sp.

A chemical investigation on the marine sponge Dysidea sp. resulted in the isolation of a series of diketopiperazines, including two new compounds, dysidines A (1) and B (2) as well as six known ones (3-8). Their structures with absolute configurations were determined on the basis of UV, IR, HRMS, NMR and calculated ECD method. Additionally, the cytotoxic, anti-inflammatory, antibacterial and antiviral activities of 1-8 were also tested. However, none of them exhibited significant bioactivities.

The genetic architecture of multimodal human brain age.

The complex biological mechanisms underlying human brain aging remain incompletely understood. This study investigated the genetic architecture of three brain age gaps (BAG) derived from gray matter volume (GM-BAG), white matter microstructure (WM-BAG), and functional connectivity (FC-BAG). We identified sixteen genomic loci that reached genome-wide significance (P-value < 5×10-8). A gene-drug-disease network highlighted genes linked to GM-BAG for treating neurodegenerative and neuropsychiatric disorders and WM-BAG genes for cancer therapy. GM-BAG displayed the most pronounced heritability enrichment in genetic variants within conserved regions. Oligodendrocytes and astrocytes, but not neurons, exhibited notable heritability enrichment in WM and FC-BAG, respectively. Mendelian randomization identified potential causal effects of several chronic diseases on brain aging, such as type 2 diabetes on GM-BAG and AD on WM-BAG. Our results provide insights into the genetics of human brain aging, with clinical implications for potential lifestyle and therapeutic interventions. All results are publicly available at https://labs.loni.usc.edu/medicine .

Thymoquinone regulates microglial M1/M2 polarization after cerebral ischemia-reperfusion injury via the TLR4 signaling pathway.

Acute ischemic stroke followed by microglia activation, and the regulation of neuroinflammatory responses after ischemic injury involves microglia polarization. microglia polarization is involved in the regulation of neuroinflammatory responses and ischemic stroke-related brain damage. Thymoquinone (TQ) is an anti-inflammatory agent following ischemic stroke onset. However, the significance of TQ in microglia polarization following acute ischemic stroke is still unclear. We predicted that TQ might have neuroprotective properties by modulating microglia polarization. In this work, we mimicked the clinical signs of acute ischemic stroke using a mouse middle cerebral artery ischemia-reperfusion (I/R) model. It was discovered that TQ treatment decreased I/R-induced infarct volume, cerebral oedema, and promoted neuronal survival, as well as improved the histopathological changes of brain tissue. The sensorimotor function was assessed by the Garica score, foot fault test, and corner test, and it was found that TQ could improve the motor deficits caused by I/R. Secondly, real-time fluorescence quantitative PCR, immuno-fluorescence, ELISA, and western blot were used to detect the expression of M1/M2-specific markers in microglia to explore the role of TQ in the modulation of microglial cell polarization after cerebral ischemia-reperfusion. We found that TQ was able to promote the polarization of microglia with extremely secreted inflammatory factors from M1 type to M2 type. Furthermore, TQ could block the TLR4/NF-κB signaling pathway via Hif-1α activation which subsequently may attenuate microglia differentiation following the cerebral ischemia, establishing a mechanism for the TQ's beneficial effects in the cerebral ischemia-reperfusion model.