Fluoride induces hepatointestinal damage and vitamin B2 mitigation by regulating IL-17A and Bifidobacterium in ileum.

INTRODUCTION: Fluorosis is a global public health disease affecting more than 50 countries and 500 million people. Excessive fluoride damages the liver and intestines, yet the mechanisms and therapeutic approaches remain unclear. OBJECTIVES: To explore the mechanisms by which fluoride-induced intestinal-hepatic damage and vitamin B2 alleviation. METHODS: Fluoride and/or vitamin B2-treated IL-17A knockout and wild-type mouse models were established, the morphological and functional changes of liver and gut, total bile acid biosynthesis, metabolism, transport, and regulation of FXR-FGF15 signaling pathways were evaluated, the ileal microbiome was further analyzed by 16S rDNA sequence. Finally, Bifidobacterium supplementation mouse model was designed and re-examined the above indicators. RESULTS: The results demonstrated that fluoride induced hepatointestinal injury and enterohepatic circulation disorder by altering the synthesis, transporters, and FXR-FGF15 pathway regulation of total bile acid. Importantly, the ileum was found to be the most sensitive and fluoride changed ileal microbiome particularly by reducing abundance of Bifidobacterium. While vitamin B2 supplementation attenuated fluoride-induced enterohepatic circulation dysfunction through IL-17A and ileal microbiome, Bifidobacterium supplementation also reversed fluoride-induced hepatointestinal injury. CONCLUSION: Fluoride induces morphological and functional impairment of liver and gut tissues, as well as enterohepatic circulation disorder by altering total bile acid (TBA) synthesis, transporters, and FXR-FGF15 signaling regulation. Vitamin B2 attenuated fluoride-induced enterohepatic circulation disorder through IL-17A knockout and ileal microbiome regulation. The ileum was found to be the most sensitive to fluoride, leading to changes in ileal microbiome, particularly the reduction of Bifidobacterium. Furthermore, Bifidobacterium supplementation reversed fluoride-induced hepatointestinal injury. This study not only elucidates a novel mechanism by which fluoride causes hepatointestinal toxicity, but also provides a new physiological function of vitamin B2, which will be useful in the therapy of fluorosis and other hepatoenterological diseases.

An efficient channel recurrent Criss-cross attention network for epileptic seizure prediction.

Epilepsy is a chronic disease caused by repeated abnormal discharge of neurons in the brain. Accurately predicting the onset of epilepsy can effectively improve the quality of life for patients with the condition. While there are many methods for detecting epilepsy, EEG is currently considered one of the most effective analytical tools due to the abundant information it provides about brain activity. The aim of this study is to explore potential time-frequency and channel features from multi-channel epileptic EEG signals and to develop a patient-specific seizure prediction network. In this paper, an epilepsy EEG signal classification algorithm called Channel Recurrent Criss-cross Attention Network (CRCANet) is proposed. Firstly, the spectrograms processed by the short-time fourier transform is input into a Convolutional Neural Network (CNN). Then, the spectrogram feature map obtained in the previous step is input into the channel attention module to establish correlations between channels. Subsequently, the feature diagram containing channel attention characteristics is input into the recurrent criss-cross attention module to enhance the information content of each pixel. Finally, two fully connected layers are used for classification. We validated the method on 13 patients in the public CHB-MIT scalp EEG dataset, achieving an average accuracy of 93.8 %, sensitivity of 94.3 %, and specificity of 93.5 %. The experimental results indicate that CRCANet can effectively capture the time-frequency and channel characteristics of EEG signals while improving training efficiency.

The PRMT6/STAT1/ACSL1 axis promotes ferroptosis in diabetic nephropathy.

Hyperglycaemia-induced ferroptosis is a significant contributor to kidney dysfunction in diabetic nephropathy (DN) patients. In addition, targeting ferroptosis has clinical implications for the treatment of DN. However, effective therapeutic targets for ferroptosis have not been identified. In this study, we aimed to explore the precise role of protein arginine methyltransferase 6 (PRMT6) in regulating ferroptosis in DN. In the present study, we utilized a mouse DN model consisting of both wild-type and PRMT6-knockout (PRMT6-/-) mice. Transcriptomic and lipidomic analyses, along with various molecular biological methodologies, were used to determine the potential mechanism by which PRMT6 regulates ferroptosis in DN. Our results indicate that PRMT6 downregulation participates in kidney dysfunction and renal cell death via the modulation of ferroptosis in DN. Moreover, PRMT6 reduction induced lipid peroxidation by upregulating acyl-CoA synthetase long-chain family member 1 (ACSL1) expression, ultimately contributing to ferroptosis. Furthermore, we investigated the molecular mechanism by which PRMT6 interacts with signal transducer and activator of transcription 1 (STAT1) to jointly regulate ACSL1 transcription. Additionally, treatment with the STAT1-specific inhibitor fludarabine delayed DN progression. Furthermore, we observed that PRMT6 and STAT1 synergistically regulate ACSL1 transcription to mediate ferroptosis in hyperglycaemic cells. Our study demonstrated that PRMT6 and STAT1 comodulate ACSL1 transcription to induce the production of phospholipid-polyunsaturated fatty acids (PL-PUFAs), thus participating in ferroptosis in DN. These findings suggest that the PRMT6/STAT1/ACSL1 axis is a new therapeutic target for the prevention and treatment of DN.

Fluoride induces immunotoxicity by regulating riboflavin transport and metabolism partly through IL-17A in the spleen.

The impairment of the immune system by fluoride is a public health concern worldwide, yet the underlying mechanism is unclear. Both riboflavin and IL-17A are closely related to immune function and regulate the testicular toxicity of fluoride. However, whether riboflavin or IL-17A is involved in fluoride-induced immunotoxicity is unknown. Here, we first established a male ICR mouse model by treating mice with sodium fluoride (NaF) (100 mg/L) via the drinking water for 91 days. The results showed that fluoride increased the expression of the proinflammatory factors IL-1ß and IL-17A, which led to splenic inflammation and morphological injury. Moreover, the expression levels of the riboflavin transporters SLC52A2 and SLC52A3; the transformation-related enzymes RFK and FLAD1; and the key mitochondrial functional determinants SDH, COX, and ATP in the spleen were measured via real-time PCR, Western blotting, and ELISA. The results revealed that fluoride disrupted riboflavin transport, transformation, metabolism, and mitochondrial function. Furthermore, wild-type (WT) and IL-17A knockout (IL-17A-/-) C57BL/6 J male mice of the same age were treated with NaF (24 mg/kg·bw, equivalent to 100 mg/L) and/or riboflavin sodium phosphate (5 mg/kg·bw) via gavage for 91 days. Similar parameters were evaluated as above. The results confirmed that fluoride increased riboflavin metabolism through RFK but not through FLAD1. Fluoride also affected mitochondrial function and activated neutrophils (marked with Ly6g) and macrophages (marked with CD68) in the spleen. Interestingly, IL-17A partly mediated fluoride-induced riboflavin metabolism disorder and immunotoxicity in the spleen. This work not only reveals a novel toxic mechanism for fluoride but also provides new clues for exploring the physiological function of riboflavin and for diagnosing and treating the toxic effects of fluoride in the environment.

Escherichia coli infection induces ferroptosis in bovine mammary epithelial cells by activating the Wnt/ß-catenin pathway-mediated mitophagy.

Iron overload causes mitochondrial damage, and then activates mitophagy, which may directly trigger and amplify ferroptosis. Our objective was to investigate whether Escherichia coli (E. coli) isolated from clinical bovine mastitis induces ferroptosis in bovine mammary epithelial cells (bMECs) and if so, the underlying regulatory mechanism. E. coli infection caused mitochondrial damage, mitophagy, and ferroptosis. Rapamycin and chloroquine increased and suppressed ferroptosis, respectively, in E. coli-treated bMECs. Moreover, E. coli infection activated the Wnt/ß-catenin pathway, but foscenvivint alleviated it. In conclusion, E. coli infection induced ferroptosis through activation of the Wnt/ß-catenin pathway-promoted mitophagy, and it also suppressed GPX4 expression.

Two-stage convolutional neural network for segmentation and detection of carotid web on CT angiography.

BACKGROUND: Carotid web (CaW) is a risk factor for ischemic stroke, mainly in young patients with stroke of undetermined etiology. Its detection is challenging, especially among non-experienced physicians. METHODS: We included patients with CaW from six international trials and registries of patients with acute ischemic stroke. Identification and manual segmentations of CaW were performed by three trained radiologists. We designed a two-stage segmentation strategy based on a convolutional neural network (CNN). At the first stage, the two carotid arteries were segmented using a U-shaped CNN. At the second stage, the segmentation of the CaW was first confined to the vicinity of the carotid arteries. Then, the carotid bifurcation region was localized by the proposed carotid bifurcation localization algorithm followed by another U-shaped CNN. A volume threshold based on the derived CaW manual segmentation statistics was then used to determine whether or not CaW was present. RESULTS: We included 58 patients (median (IQR) age 59 (50-75) years, 60% women). The Dice similarity coefficient and 95th percentile Hausdorff distance between manually segmented CaW and the algorithm segmented CaW were 63.20±19.03% and 1.19±0.9 mm, respectively. Using a volume threshold of 5 mm3, binary classification detection metrics for CaW on a single artery were as follows: accuracy: 92.2% (95% CI 87.93% to 96.55%), precision: 94.83% (95% CI 88.68% to 100.00%), sensitivity: 90.16% (95% CI 82.16% to 96.97%), specificity: 94.55% (95% CI 88.0% to 100.0%), F1 measure: 0.9244 (95% CI 0.8679 to 0.9692), area under the curve: 0.9235 (95%CI 0.8726 to 0.9688). CONCLUSIONS: The proposed two-stage method enables reliable segmentation and detection of CaW from head and neck CT angiography.

DSFE: Decoding EEG-Based Finger Motor Imagery Using Feature-Dependent Frequency, Feature Fusion and Ensemble Learning.

Accurate decoding finger motor imagery is essential for fine motor control using EEG signals. However, decoding finger motor imagery is particularly challenging compared with ordinary motor imagery. This paper proposed a novel EEG decoding method of feature-dependent frequency band selection, feature fusion, and ensemble learning (DSFE) for finger motor imagery. First, a feature-dependent frequency band selection method based on correlation coefficient (FDCC) was proposed to select feature-specific effective bands. Second, a feature fusion method was proposed to fuse different types of candidate features to produce multiple refined sets of decoding features. Finally, an ensemble model using the weighted voting strategy was proposed to make full use of these diverse sets of final features. The results on a public EEG dataset of five fingers motor imagery showed that the DSFE method is effective and achieves the highest decoding accuracy of 50.64%, which is 7.64% higher than existing studies using exactly the same data. The experiments further revealed that both the effective frequency bands of different subjects and the effective frequency bands of different types of features are different in finger motor imagery. Furthermore, compared with two-hand motor imagery, the effective decoding information of finger motor imagery is transferred to the lower frequency. The idea and findings in this paper provide a valuable perspective for understanding fine motor imagery in-depth.

Automatically Extracting and Utilizing EEG Channel Importance Based on Graph Convolutional Network for Emotion Recognition.

Graph convolutional network (GCN) based on the brain network has been widely used for EEG emotion recognition. However, most studies train their models directly without considering network dimensionality reduction beforehand. In fact, some nodes and edges are invalid information or even interference information for the current task. It is necessary to reduce the network dimension and extract the core network. To address the problem of extracting and utilizing the core network, a core network extraction model (CWGCN) based on channel weighting and graph convolutional network and a graph convolutional network model (CCSR-GCN) based on channel convolution and style-based recalibration for emotion recognition have been proposed. The CWGCN model automatically extracts the core network and the channel importance parameter in a data-driven manner. The CCSR-GCN model innovatively uses the output information of the CWGCN model to identify the emotion state. The experimental results on SEED show that: 1) the core network extraction can help improve the performance of the GCN model; 2) the models of CWGCN and CCSR-GCN achieve better results than the currently popular methods. The idea and its implementation in this paper provide a novel and successful perspective for the application of GCN in brain network analysis of other specific tasks.

Combining Early Ischemic Change and Collateral Extent for Functional Outcomes After Endovascular Therapy: An Analysis From AcT Trial.

BACKGROUND: Early ischemic change and collateral extent are colinear with ischemic core volume (ICV). We investigated the relationship between a combined score using the Alberta Stroke Program Early Computed Tomography Score and multiphase computed tomography angiography (mCTA) collateral extent, named mCTA-ACE score, on functional outcomes in endovascular therapy-treated patients. METHODS: We performed a post hoc analysis of a subset of endovascular therapy-treated patients from the Alteplase Compared to Tenecteplase trial which was conducted between December 2019 and January 2022 at 22 centers across Canada. Ten-point mCTA collateral corresponding to M2 to M6 regions of the Alberta Stroke Program Early Computed Tomography Score grid was evaluated as 0 (poor), 1 (moderate), or 2 (normal) and additively combined with the 10-point Alberta Stroke Program Early Computed Tomography Score to produce a 20-point mCTA-ACE score. We investigated the association of mCTA-ACE score with modified Rankin Scale score ≤2 and return to prestroke level of function at 90 to 120 days using mixed-effects logistic regression. In the subset of patients who underwent baseline computed tomography perfusion imaging, we compared the mCTA-ACE score and ICV for outcome prediction. RESULTS: Among 1577 intention-to-treat population in the trial, 368 (23%; 179 men; median age, 73 years) were included, with Alberta Stroke Program Early Computed Tomography Score, mCTA collateral, and combination of both (mCTA-ACE score: median [interquartile range], 8 [7-10], 9 [8-10], and 17 [16-19], respectively). The probability of modified Rankin Scale score ≤2 and return to prestroke level of function increased for each 1-point increase in mCTA-ACE score (odds ratio, 1.16 [95% CI, 1.06-1.28] and 1.22 [95% CI, 1.06-1.40], respectively). Among 173 patients in whom computed tomography perfusion data was assessable, the mCTA-ACE score was inversely correlated with ICV (ρ=-0.46; P<0.01). The mCTA-ACE score was comparable to ICV to predict a modified Rankin Scale score ≤2 and return to prestroke level of function (C statistics 0.71 versus 0.69 and 0.68 versus 0.64, respectively). CONCLUSIONS: The mCTA-ACE score had a significant positive association with functional outcomes after endovascular therapy and had a similar predictive performance as ICV.

Bifidobacterium Relieved Fluoride-Induced Hepatic and Ileal Toxicity via Inflammatory Response and Bile Acid Transporters in Mice.

Fluoride is a pervasive environmental contaminant. Prolonged excessive fluoride intake can inflict severe damage on the liver and intestines. Previous 16S rDNA sequencing revealed a decrease in ileal Bifidobacterium abundance during fluoride-induced hepatointestinal injury. Hence, this work aimed to investigate the possible mitigating function of Bifidobacterium on hepatointestinal injury caused by fluoride. Thirty-six 6-week-old C57BL/6J mice (equally divided between males and females) were allotted randomly to three groups: Ctrl group (distilled water), NaF group, and NaF + Ba group (100 mg/L NaF distilled water). After 10 weeks, the mice were given 1 × 109 CFU/mL Bifidobacterium solution (0.2 mL/day) intragastrically in the NaF + Ba group for 8 weeks, and the mice in other groups were given the same amount of distilled water. Dental damage, bone fluoride content, blood routine, liver and intestinal microstructure and function, inflammatory factors, and regulatory cholic acid transporters were examined. Our results showed that fluoride increased glutamic-oxalacetic transaminase (GOT), glutamic-pyruvic transaminase (GPT) activities, and the levels of lipopolysaccharide (LPS), IL-1ß, IL-6, TNF-α, and IL-10 levels in serum, liver, and ileum. However, Bifidobacterium intervention alleviated fluoride-induced changes in the above indicators. In addition, Bifidobacterium reduced the mRNA expression levels of bile acid transporters ASBT, IBABP, OST-α, and OST-ß in the ileum. In summary, Bifidobacterium supplementation relieved fluoride-induced hepatic and ileal toxicity via an inflammatory response and bile acid transporters in the liver and ileum of mice.

Fluoride induces pyroptosis via IL-17A-mediated caspase-1/11-dependent pathways and Bifidobacterium intervention in testis.

Fluoride, a ubiquitous environmental pollutant, poses a significant public health threat. Our previous study revealed a correlation between fluoride-induced testicular pyroptosis and male reproductive dysfunction. However, the underlying mechanism remains unclear. Wild-type and interleukin 17A knockout mice were exposed to sodium fluoride (100 mg/L) in deionized drinking water for 18 weeks. Bifidobacterium intervention (1 × 109 CFU/mL, 0.2 mL/day, administered via gavage) commenced in the 10th week. Sperm quality, testicular morphology, key pyroptosis markers, spermatogenesis key genes, IL-17A signaling pathway, and pyroptosis pathway related genes were determined. The results showed that fluoride reduced sperm quality, damaged testicular morphology, affected spermatogenesis, elevated IL-17A levels, and induced testicular pyroptosis. Bifidobacterium intervention alleviated adverse reproductive outcomes. Fluoride-activated testicular pyroptosis through both typical and atypical pathways, with IL-17A involvement. Bifidobacterium supplementation attenuated pyroptosis by downregulating IL-17A, inhibiting NLRP3 and PYRIN-mediated caspase-1 and caspase-11 dependent pathways in testis, thereby alleviating fluoride-induced male reproductive damage. In summary, this study uncovers the mechanism underlying fluorine-induced testicular pyroptosis and illustrates the novel protecting feature of Bifidobacterium against fluoride-induced harm to male reproduction, along with its potential regulatory mechanism. These results provide fresh perspectives on treating male reproductive dysfunction resulting from fluoride or other environmental toxins.

Riboflavin Attenuates Fluoride-Induced Testicular Injury via Interleukin 17A-Mediated Classical Pyroptosis.

Male reproductive toxicity of fluoride is of great concern worldwide, yet the underlying mechanism is unclear. Pyroptosis is a novel mode of inflammatory cell death, and riboflavin with anti-inflammatory properties has the potential to protect against fluoride damage. However, it is unknown whether pyroptosis is involved in fluoride-induced testicular injury and riboflavin intervention. Here, we first found that riboflavin could alleviate fluoride-caused lower sperm quality and damaged testicular morphology by reducing pyroptosis based on a model of ICR mice treated with NaF (100 mg/L) and/or riboflavin supplementation (40 mg/L) via drinking water for 13 weeks. And then, together with the results of in vitro Leydig cell modelsm it was confirmed that the pyroptosis occurs predominantly through classical NLRP3/Caspase-1/GSDMD pathway. Furthermore, our results reveal that interleukin-17A mediates the process of pyroptosis in testes induced by fluoride and riboflavin attenuation according to the results of our established models of riboflavin- and/or fluoride-treated IL-17A knockout mice. The results not only declare a new mechanism by which fluoride induces testicular injury via interleukin 17A-mediated classical pyroptosis but also provide evidence for the potential clinical application of riboflavin as an effective therapy for fluoride toxicity.

spatialHeatmap: visualizing spatial bulk and single-cell assays in anatomical images.

Visualizing spatial assay data in anatomical images is vital for understanding biological processes in cell, tissue, and organ organizations. Technologies requiring this functionality include traditional one-at-a-time assays, and bulk and single-cell omics experiments, including RNA-seq and proteomics. The spatialHeatmap software provides a series of powerful new methods for these needs, and allows users to work with adequately formatted anatomical images from public collections or custom images. It colors the spatial features (e.g. tissues) annotated in the images according to the measured or predicted abundance levels of biomolecules (e.g. mRNAs) using a color key. This core functionality of the package is called a spatial heatmap plot. Single-cell data can be co-visualized in composite plots that combine spatial heatmaps with embedding plots of high-dimensional data. The resulting spatial context information is essential for gaining insights into the tissue-level organization of single-cell data, or vice versa. Additional core functionalities include the automated identification of biomolecules with spatially selective abundance patterns and clusters of biomolecules sharing similar abundance profiles. To appeal to both non-expert and computational users, spatialHeatmap provides a graphical and a command-line interface, respectively. It is distributed as a free, open-source Bioconductor package (https://bioconductor.org/packages/spatialHeatmap) that users can install on personal computers, shared servers, or cloud systems.

Transfer learning with data alignment and optimal transport for EEG based motor imagery classification.

Objective. The non-stationarity of electroencephalogram (EEG) signals and the variability among different subjects present significant challenges in current Brain-Computer Interfaces (BCI) research, which requires a time-consuming specific calibration procedure to address. Transfer Learning (TL) offers a potential solution by leveraging data or models from one or more source domains to facilitate learning in the target domain, so as to address these challenges.Approach. In this paper, a novel Multi-source domain Transfer Learning Fusion (MTLF) framework is proposed to address the calibration problem. Firstly, the method transforms the source domain data with the resting state segment data, in order to decrease the differences between the source domain and the target domain. Subsequently, feature extraction is performed using common spatial pattern. Finally, an improved TL classifier is employed to classify the target samples. Notably, this method does not require the label information of target domain samples, while concurrently reducing the calibration workload.Main results. The proposed MTLF is assessed on Datasets 2a and 2b from the BCI Competition IV. Compared with other algorithms, our method performed relatively the best and achieved mean classification accuracy of 73.69% and 70.83% on Datasets 2a and 2b respectively.Significance.Experimental results demonstrate that the MTLF framework effectively reduces the discrepancy between the source and target domains and acquires better classification performance on two motor imagery datasets.

Riboflavin alleviates fluoride-induced ferroptosis by IL-17A-independent system Xc-/GPX4 pathway and iron metabolism in testicular Leydig cells.

Fluoride is widely found in groundwater, soil, animal and plant organisms. Excessive fluoride exposure can cause reproductive dysfunction by activating IL-17A signaling pathway. However, the adverse effects of fluoride on male reproductive system and the mechanisms remain elusive. In this study, the wild type and IL-17A knockout C57BL/6J mouse were treated with 24 mg/kg·bw·d sodium fluoride and/or 5 mg/kg·bw·d riboflavin-5'-phosphate sodium for 91 days. Results showed that fluoride caused dental fluorosis, increased the levels of ROS in testicular Leydig cells and GSSG in testicular tissue, and did not affect the iron and serum hepcidin levels in testicular tissue. Riboflavin alleviated above adverse changes, whereas IL-17A does not participate in the oxidative stress-mediated reproductive toxicity of fluoride. Based on this, TM3 cells were used to verify the injury of fluoride on Leydig cells. Results showed that fluoride increased mRNA levels of ferroptosis marker SLC3A2, VDAC3, TFRC, and SLC40A1 and decreased Nrf2 mRNA levels in TM3 cells. The ferroptosis inhibitor Lip-1 and DFO were used to further investigate the relationship between male reproductive toxicity and ferroptosis induced by fluoride. We found that the fluoride-induced decrease in cell viability, increase in xCT, TFRC, and FTH protein expression, and decrease in GPX4 protein expression, can all be rescued by Lip-1 and DFO. Similar results were also observed in the riboflavin treatment group. Moreover, riboflavin mitigated fluoride-induced increases in ROS levels and SLC3A2 protein levels. In all, our work revealed that riboflavin inhibited ferroptosis in testicular Leydig cells and improved the declined male reproductive function caused by fluoride. This study provides new perspectives for revealing new male reproductive toxicity mechanisms and mitigating fluoride toxicity damage.

A time segment adaptive optimization method based on separability criterion and correlation analysis for motor imagery BCIs.

Motor imagery (MI) plays a crucial role in brain-computer interface (BCI), and the classification of MI tasks using electroencephalogram (EEG) is currently under extensive investigation. During MI classification, individual differences among subjects in terms of response and time latency need to be considered. Optimizing the time segment for different subjects can enhance subsequent classification performance. In view of the individual differences of subjects in motor imagery tasks, this article proposes a Time Segment Adaptive Optimization method based on Separability criterion and Correlation analysis (TSAOSC). The fundamental principle of this method involves applying the separability criterion to various sizes of time windows within the training data, identifying the optimal raw reference signal, and adaptively adjusting the time segment position for each trial's data by analyzing its relationship with the optimal reference signal. We evaluated our method on three BCI competition datasets, respectively. The utilization of the TSAOSC method in the experiments resulted in an enhancement of 4.90% in average classification accuracy compared to its absence. Additionally, building upon the TSAOSC approach, this study proposes a Nonlinear-TSAOSC method (N-TSAOSC) for analyzing EEG signals with nonlinearity, which shows improvements in the classification accuracy of certain subjects. The results of the experiments demonstrate that the proposed method is an effective time segment optimization method, and it can be integrated into other algorithms to further improve their accuracy.

Exploring the mechanism of Jingshen Xiaoke decoction in treating T2DM mice based on network pharmacology and molecular docking.

BACKGROUND: Jingshen Xiaoke decoction (JS) was prepared by studying the classic prescriptions of famous scholars in the past dynasties to prevent and treat diabetes. The related mechanism of JS against hyperlipidemia has yet to be revealed. OBJECTIVE: To investigate the mechanism of action of JS in treating diabetes mellitus by using bioinformatics methods. METHODS: A database was used to search the active ingredients and targets of the JS and targets for type 2 diabetes mellitus (T2DM). The protein interaction between the intersection targets, and the constructed the PPI network diagram was analyzed using the STRING database. Furthermore, the gene annotation tool DAVID was used to enrich the intersecting targets for the Gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway. Finally, Maestro software was used for molecular docking to verify the binding ability of the active ingredients to the core target genes. RESULTS: A total of 45 active ingredients in JS were screened out corresponding to 239 effective targets, of which 64 targets were potential targets for treating T2DM. The analysis of PPI network diagram analysis revealed that the ingredients' active components are quercetin, ß-sitosterol, stigmasterol, luteolin, and 7-Methoxy-2-methyl isoflavone. GO functional enrichment analysis indicated 186 biological processes (BP), 23 molecular functions (MF) and 13 cellular components (CC). KEGG pathway enrichment analysis revealed the enrichment of 59 signal pathways. The molecular docking results demonstrated that the active ingredients and core targets had a good docking affinity with a binding activity less than -7 kcal/mol. Finally, the western blotting illustrated that JS could up-regulate the liver PI3K/AKT-signaling pathway. CONCLUSION: JS can regulate glucolipid metabolism, reduce the inflammatory response, improve insulin resistance and modulate the immune response through PI3K/AKT signaling pathway treating of T2DM and its complications effects.

Instance-representation transfer method based on joint distribution and deep adaptation for EEG emotion recognition.

Electroencephalogram (EEG) emotion recognition technology is essential for improving human-computer interaction. However, the practical application of emotion recognition technology is limited due to the variety of subjects and sessions. Transfer learning has been applied to address this issue and has received extensive research and application. Studies mainly concentrate on either instance transfer or representation transfer methods. This paper proposes an emotion recognition method called Joint Distributed Instances Represent Transfer (JD-IRT), which includes two core components: Joint Distribution Deep Adaptation (JDDA) and Instance-Representation Transfer (I-RT). Specifically, JDDA is different from common representation transfer methods in transfer learning. It bridges the discrepancies of marginal and conditional distributions simultaneously and combines multiple adaptive layers and kernels for deep domain adaptation. On the other hand, I-RT utilizes instance transfer to select source domain data for better representation transfer. We performed experiments and compared them with other representative methods in the SEED, SEED-IV, and SEED-V datasets. In cross-subject experiments, our approach achieved an average accuracy of 83.21% in SEED, 52.12% in SEED-IV, and 60.17% in SEED-V. Similarly, in cross-session experiments, the accuracy was 91.29% in SEED, 59.02% in SEED-IV, and 65.91% in SEED-V. These results demonstrate the improvement in the accuracy of EEG emotion recognition using the proposed approach.