Periploca forrestii Schltr. ameliorate liver injury caused by fluorosis in rat.

To investigate the impact of the ethanoic fractions of Periploca forrestii Schltr. (P. forrestii) in ameliorating the liver injury caused by fluoride ingestion and to explore the potential mechanisms. Initially, an in vitro fluorosis cell model was constructed using the human normal liver cell line (L-02) induced by fluoride. Cell viability was assessed using the CCK-8 assay kit. The lactate dehydrogenase (LDH) assay kit was utilized to measure LDH content in the cell supernatant, while the malonic dialdehyde (MDA) assay kit was employed to determine MDA levels within the cells. Subsequently, a fluorosis rat model was established, and LDH content in the cell supernatant was measured using the LDH assay kit. Various parameters, including MDA, superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), catalase (CAT), and reactive oxygen species (ROS) content within the cells, were detected using appropriate assay kits. Additionally, cell apoptosis rate was determined using the Annexin V-FITC/PI cell apoptosis assay kit. The protein expression levels of B-cell lymphoma-2 (Bcl-2), Bcl-2-associated X protein (Bax), Caspase-3, Cleaved Caspase-3, Caspase-9, and Cleaved Caspase-9 were analyzed through Western blotting. Compared to the model group, the ethanolic fraction D of P.forrestii (Fr.D) increased cell viability (P < 0.01) and decreased LDH and MDA levels (P < 0.01). In the high-dose Fr.D treatment group of fluoride-poisoned rats, serum ALT, AST, LDH and MDA levels significantly decreased (P < 0.01). Results from rat primary cells exhibited that the Fr.D administration group exhibited significantly higher cell survival rates than the fluoride group (P < 0.01). Similarly, primary rat cells treated with Fr.D showed enhanced cell viability (P < 0.05) and reduced apoptosis rate, LDH, MDA, SOD, GSH-Px, CAT, and ROS levels (P < 0.05) compared to the model group. Western blot analysis indicated that the Fr.D treatment group elevated the Bcl-2/Bax protein expression ratio and reduced Caspase-3 and Caspase-9 activation levels (P < 0.01) compared to the model group. The results suggest that components within the Fr.D from Periploca forrestii may alleviate fluoride-induced liver injury by potentially counteracting oxidative stress and cell apoptosis.

Neuroprotective effects of adjunctive treatments for acute stroke thrombolysis: a review of clinical evidence.

The narrow therapeutic time window and risk of intracranial hemorrhage largely restrict the clinical application of thrombolysis in acute ischemic stroke. Adjunctive treatments added to rt-PA may be beneficial to improve the capacity of neural cell to withstand ischemia, and to reduce the hemorrhage risk as well. This review aims to evaluate the neuroprotective effects of adjunctive treatments in combination with thrombolytic therapy for acute ischemic stroke. Relevant studies were searched in the PubMed, Web of Science and EMBASE database. In this review, we first interpret the potential role of adjunctive treatments to thrombolytic therapy in acute ischemic stroke. Furthermore, we summarize the current clinical evidence for the combination of intravenous recombinant tissue plasminogen activator and various adjunctive therapies in acute ischemic stroke, either pharmacological or non-pharmacological therapy, and discuss the mechanisms of some promising treatments, including uric acid, fingolimod, minocycline, remote ischemic conditioning, hypothermia and transcranial laser therapy. Even though fingolimod, minocycline, hypothermia and remote ischemic conditioning have yielded promising results, they still need to be rigorously investigated in further clinical trials. Further trials should also focus on neuroprotective approach with pleiotropic effects or combined agents with multiple protective mechanisms.

Cross-Subject Lifelong Learning for Continuous Estimation From Surface Electromyographic Signal.

The employment of surface electromyographic (sEMG) signals in the estimation of hand kinematics represents a promising non-invasive methodology for the advancement of human-machine interfaces. However, the limitations of existing subject-specific methods are obvious as they confine the application to individual models that are custom-tailored for specific subjects, thereby reducing the potential for broader applicability. In addition, current cross-subject methods are challenged in their ability to simultaneously cater to the needs of both new and existing users effectively. To overcome these challenges, we propose the Cross-Subject Lifelong Network (CSLN). CSLN incorporates a novel lifelong learning approach, maintaining the patterns of sEMG signals across a varied user population and across different temporal scales. Our method enhances the generalization of acquired patterns, making it applicable to various individuals and temporal contexts. Our experimental investigations, encompassing both joint and sequential training approaches, demonstrate that the CSLN model not only attains enhanced performance in cross-subject scenarios but also effectively addresses the issue of catastrophic forgetting, thereby augmenting training efficacy.

The active components and potential mechanisms of Wuji Wan in the treatment of ethanol-induced gastric ulcer: An integrated metabolomics, network pharmacology and experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: Wuji Wan (WJW) is a traditional Chinese medicine formula that can be found in the "Prescriptions of Taiping Benevolent Dispensary" that has been employed in treating gastric discomfort, burning epigastric pain, and gastric reflux for hundreds of years and has shown promise for treating gastric ulcers (GUs). However, the active components and mechanism of action against GUs remain unclear. AIM OF THE STUDY: The aim of this study was to explore the active components of WJW and elucidate the underlying mechanism involved in treating GUs. MATERIALS AND METHODS: Initially, cell viability was measured by a cell counting kit 8 (CCK-8) assay to evaluate the efficacy of WJW-containing serum in vitro. The gastric ulcer index, ulcer inhibition rate, hematoxylin and staining (H&E), and periodic acid-Schiff (PAS) staining were used to evaluate the therapeutic effect of WJW in vivo. Subsequently, the levels of inflammatory factors and oxidative stress factors were determined using an enzyme-linked immunosorbent assays (ELISA) on in vitro and in vivo samples. Additionally, UPLC-Q Exactive Plus Orbitrap HRMS was used to analyze the components that were absorbed into the blood of WJW and its metabolites. Network pharmacology and metabolomics were subsequently used to identify the targets and pathways. Real-time quantitative PCR (RT‒qPCR) and Western blotting were used to verify the mRNA and protein levels of the key targets and pathways. Finally, the active components were identified by molecular docking to verify the binding stability of the components and key targets. RESULTS: WJW-containing serum ameliorated ethanol-induced damage in GES-1 cells and promoted cell healing. WJW-containing serum reduced IL-6, TNF-α, MDA, and LDH levels while increasing IL-10, SOD, and T-AOC levels in the cells. Moreover, WJW treatment resulted in decreased IL-6, TNF-α, and MDA levels and increased IL-10, SOD, PGE2, and NO levels in GUs rats. In addition, eight components of WJW were absorbed into the blood. The network pharmacology results revealed 192 common targets for blood entry components and GUs, and KEGG analysis revealed that apoptosis signaling pathways were the main pathways involved in WJW activity against GUs. Metabolomic screening was used to identify 13 differential metabolites. There were 23 common targets for blood entry components, GUs, and differential metabolites, with the key targets TNF (TNF-α), AKT1, PTGS2 (COX2) and MAPK1. WJW significantly inhibited the expression of Bax, Caspase-9, Caspase-3, cleaved Caspase-9, cleaved Caspase-3, TNF-α, COX2, and p-p44/42 MAPK while promoting the expression of Bcl-2 and p-AKT1. Molecular docking revealed that the active components of WJW for the treatment of GUs are berberine, palmatine, coptisine, evodiamine, rutaecarpine, evocarpine, and paeoniflorin. CONCLUSIONS: WJW treatment reduces inflammation and oxidative stress injury and inhibits apoptosis signaling pathways. The main active components are berberine, palmatine, coptisine, evodiamine, rutaecarpine, evocarpine, and paeoniflorin. In this paper, we provide a new strategy for exploring the active components of traditional Chinese medicine formulas for the treatment of diseases based on target mechanisms.

A BERT Based Method for Continuous Estimation of Cross-Subject Hand Kinematics From Surface Electromyographic Signals.

Estimation of hand kinematics from surface electromyographic (sEMG) signals provides a non-invasive human-machine interface. This approach is usually subject-specific, so that the training on one individual does not generalise to different subjects. In this paper, we propose a method based on Bidirectional Encoder Representation from Transformers (BERT) structure to predict the movement of hands from the root mean square (RMS) feature of the sEMG signal following µ -law normalization. The method was tested for within-subject and cross-subject conditions. We trained the model with two hard sample mining methods, Gradient Harmonizing Mechanism (GHM) and Online Hard Sample Mining (OHEM). The proposed method was compared with classic approaches, including long short-term memory (LSTM) and Temporal Convolutional Network (TCN) as well as a recent method called Long Exposure Convolutional Memory Network (LE-ConvMN). Correlation coefficient (CC), normalized root mean square error (NRMSE) and time costs were used as performance metrics. Our method (sBERT-OHEM) achieved state-of-the-art performance in cross-subject evaluation as well as high performance in subject-specific tests on the Ninapro dataset. The above tests are based on the same randomly selected 10 subjects. Generally, in the cross-subject situation, with the increasing of the subjects' number, it unavoidably leads to the decline of the performance. While the performance of our method on 38 subjects was significantly higher than the other methods on 10 subjects in cross-subject conditions, which further verified the advantage of our methods.

Mechanistic study of cytochrome P450 enzyme-mediated cytotoxicity of psoralen and isopsoralen.

Psoralen and isopsoralen are the major components responsible for Psoraleae Fructus-induced hepatotoxicity. This study explored the role of metabolic activation by cytochrome P450 (CYP) enzymes in psoralen- and isopsoralen-induced cytotoxicity and its potential mechanisms. Inhibitors of CYP1A2, 2C9, 2C19, 2D6, 2E1, and 3A4 were used to screen specific CYP enzymes responsible for the metabolic activation of psoralen and isopsoralen in mouse primary hepatocytes, which was verified using the corresponding transfected cell lines. Network toxicology and transcriptome analyses were performed to explore the mechanisms underlying toxicity. Psoralen and isopsoralen decreased the viability of mouse primary hepatocytes, whereas the inhibition of CYP2C9, 2C19, 2D6, and 2E1 significantly increased their viability. Psoralen-induced cytotoxicity was significantly enhanced by the overexpression of CYP2C19 in Chinese hamster ovary cells, whereas the overexpression of the above CYP enzymes did not affect the cytotoxicity of isopsoralen. Psoralen- and isopsoralen-induced cytotoxic effects were associated with putative core targets (i.e., Fn1, Thbs1, and Tlr2) and multiple signaling pathways (e.g., PI3K-Akt, MAPK, and TNF pathways). Our results demonstrate that the metabolic activation of psoralen and isopsoralen is mediated by CYP enzymes, thereby regulating multiple core targets and signaling pathways and resulting in cytotoxicity.

Long exposure convolutional memory network for accurate estimation of finger kinematics from surface electromyographic signals.

Objective. Estimation of finger kinematics is an important function of an intuitive human-machine interface, such as gesture recognition. Here, we propose a novel deep learning method, named long exposure convolutional memory network (LE-ConvMN), and use it to proportionally estimate finger joint angles through surface electromyographic (sEMG) signals.Approach. We use a convolution structure to replace the neuron structure of traditional long short-term memory (LSTM) networks, and use the long exposure data structure which retains the spatial and temporal information of the electrodes as input. The Ninapro database, which contains continuous finger gestures and corresponding sEMG signals was used to verify the efficiency of the proposed deep learning method. The proposed method was compared with LSTM and Sparse Pseudo-input Gaussian Process (SPGP) on this database to predict the ten main joint angles on the hand based on sEMG. The correlation coefficient (CC) was evaluated using the three methods on eight healthy subjects, and all the methods adopted the root mean square (RMS) features.Main results.The experimental results showed that the average CC, root mean square error, normalized root mean square error of the proposed LE-ConvMN method (0.82 ± 0.03,11.54 ± 1.89,0.12 ± 0.013) was significantly higher than SPGP (0.65 ± 0.05,p< 0.001; 15.51 ± 2.82,p< 0.001; 0.16 ± 0.01,p< 0.001) and LSTM (0.64 ± 0.06,p< 0.001; 14.77 ± 3.21,p< 0.001; 0.15 ± 0.02,p= < 0.001). Furthermore, the proposed real-time-estimation method has a computation cost of only approximately 82 ms to output one state of ten joints (average value of 10 tests on TitanV GPU).Significance. The proposed LE-ConvMN method could efficiently estimate the continuous movement of fingers with sEMG, and its performance is significantly superior to two established deep learning methods.