Model informed precision medicine of Chinese herbal medicines formulas-A multi-scale mechanistic intelligent model.

Recent trends suggest that Chinese herbal medicine formulas (CHM formulas) are promising treatments for complex diseases. To characterize the precise syndromes, precise diseases and precise targets of the precise targets between complex diseases and CHM formulas, we developed an artificial intelligence-based quantitative predictive algorithm (DeepTCM). DeepTCM has gone through multilevel model calibration and validation against a comprehensive set of herb and disease data so that it accurately captures the complex cellular signaling, molecular and theoretical levels of traditional Chinese medicine (TCM). As an example, our model simulated the optimal CHM formulas for the treatment of coronary heart disease (CHD) with depression, and through model sensitivity analysis, we calculated the balanced scoring of the formulas. Furthermore, we constructed a biological knowledge graph representing interactions by associating herb-target and gene-disease interactions. Finally, we experimentally confirmed the therapeutic effect and pharmacological mechanism of a novel model-predicted intervention in humans and mice. This novel multiscale model opened up a new avenue to combine "disease syndrome" and "macro micro" system modeling to facilitate translational research in CHM formulas.

Zeolite-encapsulated copper(II) complexes with NNO-tridentate Schiff base ligands: catalytic activity for methylene blue (MB) degradation under near neutral conditions.

Three novel copper Schiff base complexes, L1Cu(OAc)-L3Cu(OAc), bearing NNO tridentate ligands were synthesized and successfully entrapped in zeolite. All free and encapsulated complexes were fully characterized through experiments combined with theoretical calculations, and were subsequently employed as catalysts to activate H2O2 for degradation of methylene blue (MB). The catalytic activity of free complexes was tunable by substitution effects. The complex L3Cu(OAc) displayed enhanced efficiency by adopting bulky and donor substitutions due to the lower oxidation states. However, the free complexes exhibited modified structural and catalytic properties upon encapsulation into the zeolite. The constraint from the zeolite holes and coordination geometry caused the alteration of electronic structures and subsequently modified the reactivity. This study revealed that upon encapsulation, the larger molecular dimension of L3Cu(OAc) resulted in additional distorted geometry, leading to higher catalytic efficiency for MB degradation with more blue shifts in the UV-Vis spectrum. There was high catalytic activity by LnCu(OAc)-Y compared to that of the free complex, and high recyclability under near neutral conditions. In addition, the catalytic efficiency of L3Cu(OAc)-Y was higher or equivalent compared to other catalysts. This work provides new complexes with NNO tridentate ligands encapsulated inside zeolite and explains the relationship between the modified structure and functionality.

1,25(OH)2 D3 inhibits Lewis lung cancer cell migration via NHE1-sensitive metabolic reprograming.

High prevalence and metastasis rates are characteristics of lung cancer. Glycolysis provides energy for the development and metastasis of cancer cells. The 1,25-dihydroxy vitamin D3 (1,25(OH)2 D3 ) has been linked to reducing cancer risk and regulates various physiological functions. We hypothesized that 1,25(OH)2 D3 could be associated with the expression and activity of Na+ /H+ exchanger isoform 1 (NHE1) of Lewis lung cancer cells, thus regulating glycolysis as well as migration by actin reorganization. Followed by online public data analysis, Vitamin D3 receptor, the receptor of 1,25(OH)2 D3 has been proved to be abundant in lung cancers. We demonstrated that 1,25(OH)2 D3 treatment suppressed transcript levels, protein levels, and activity of NHE1 in LLC cells. Furthermore, 1,25(OH)2 D3 treatment resets the metabolic balance between glycolysis and OXPHOS, mainly including reducing glycolytic enzymes expression and lactate production. In vivo experiments showed the inhibition effects on tumor growth as well. Therefore, we concluded that 1,25(OH)2 D3 could amend the NHE1 function, which leads to metabolic reprogramming and cytoskeleton reconstruction, finally inhibits the cell migration.

High-Throughput Screening of Gas Sensor Materials for Decomposition Products of Eco-Friendly Insulation Medium by Machine Learning.

Nowadays, trifluoromethyl sulfonyl fluoride (CF3SO2F) has shown great potential to replace SF6 as an eco-friendly insulation medium in the power industry. In this work, an effective and low-cost design strategy toward ideal gas sensors for the decomposed gas products of CF3SO2F was proposed. The strategy achieved high-throughput screening from a large candidate space based on first-principle calculation and machine learning (ML). The candidate space is made up of different transition metal-embedded graphic carbon nitrides (TM/g-C3N4) owing to their high surface area and subtle electronic structure. Four main noteworthy decomposition gases of CF3SO2F, namely, CF4, SO2, SO2F2, and HF, as well as their initial stable structure on TM/g-C3N4 were determined. The best-performing ML model was established and implemented to predict the interaction strength between gas products and TM/g-C3N4, thus determining the promising gas-sensing materials for target gases with the requirements of interaction strength, recovery time, sensitivity, and selectivity. Further analysis guarantees their stability and reveals the origin of excellent properties as a gas sensor. The high-throughput strategy opens a new avenue of rational and low-cost design principles of desirable gas-sensing materials in an interdisciplinary view.

MantaID: a machine learning-based tool to automate the identification of biological database IDs.

The number of biological databases is growing rapidly, but different databases use different identifiers (IDs) to refer to the same biological entity. The inconsistency in IDs impedes the integration of various types of biological data. To resolve the problem, we developed MantaID, a data-driven, machine learning-based approach that automates identifying IDs on a large scale. The MantaID model's prediction accuracy was proven to be 99%, and it correctly and effectively predicted 100,000 ID entries within 2 min. MantaID supports the discovery and exploitation of ID from large quantities of databases (e.g. up to 542 biological databases). An easy-to-use freely available open-source software R package, a user-friendly web application and application programming interfaces were also developed for MantaID to improve applicability. To our knowledge, MantaID is the first tool that enables an automatic, quick, accurate and comprehensive identification of large quantities of IDs and can therefore be used as a starting point to facilitate the complex assimilation and aggregation of biological data across diverse databases.

Silencing of RAB42 down-regulated PD-L1 expression to inhibit the immune escape of hepatocellular carcinoma cells through inhibiting the E2F signaling pathway.

OBJECTIVE: To investigate the mechanistic role of RAB42 and corresponding regulatory path in hepatocellular carcinoma (HCC). METHODS: The expression of RAB42 in HCC tissue was checked by RT-qPCR and immunohistochemical staining assay. Cell proliferation was checked by colony formation and CCK-8 assay. Cell apoptosis and cycle distribution were analyzed with flow cytometry. The relevance of RAB42 and PD-L1 was analyzed from TCGA database. The binding of E2F1 to PD-L1 was detected by JASPAR database, luciferase and ChIP assay. The expression of PD-L1, cell apoptosis- and E2F pathway-related proteins were checked by western blotting. RESULTS: RAB42 was highly expressed in HCC tissue. RAB42 silencing could inhibit proliferation and induce G1 phase arrest and apoptosis of HCC cells. TCGA database disclosed that PD-L1 was highly associated with RAB42 expression. Silencing of RAB42 could retard PD-L1 expression in HCC cells. GSEA analysis showed RAB42 could activate E2F signaling pathway. Silencing of RAB42 could observably weaken the expression of E2F1, CDK1 and CDC20 in HCC cells. JASPAR database predicted the binding site between E2F1 and PD-L1, and E2F1 overexpression could promote PD-L1 expression. Overexpression of E2F1 could reverse the biological function of RAB42 silencing in HCC cells. CONCLUSION: Silencing of RAB42 could down-regulate PD-L1 expression to inhibit immune escape through inhibiting E2F signaling pathway in HCC cells. RAB42 may become a novel clinical diagnostic and therapy marker for HCC.

Gypenosides suppress fibrosis of the renal NRK-49F cells by targeting miR-378a-5p through the PI3K/AKT signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: The incidence of renal fibrosis caused by chronic kidney disease is increasing year by year. Preventing the activation and conversion of kidney-intrinsic fibroblasts to a myofibroblast phenotype is an important target for blocking the development of renal interstitial fibrosis. Our team established a stable renal interstitial fibrosis cell model in the early stage, and the screening results showed that GPs has good anti-fibrosis potential. At this stage, only a few literatures have reported its anti-fibrosis effect, and the mechanism of action is still unclear. AIM OF THE STUDY: The massive synthesis and secretion of extracellular-matrix (ECM) components by activated fibroblasts in the kidneys causes irreversible renal interstitial fibrosis. Gypenosides (GPs) have been shown to decelerate this process, in which micro RNAs (miRNAs) play an important regulatory role. This study aimed to evaluate the mechanism underlying the suppressive effect of GPs on renal fibrosis. MATERIALS AND METHODS: This study used TGF-ß1-stimulated NRK-49F renal cells as an in-vitro model of renal interstitial fibrosis. First, the concentration range of GPs that significantly affects the cytoactive was determined. Then, the anti-fibrotic effects of various concentrations of GPs in the in-vitro model were assessed via immunofluorescence, western blotting, and quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Non-coding-RNA sequencing combined with bioinformatics was used to predict the mechanistic basis of the anti-fibrotic effect of GPs, and qRT-PCR was used to verify the sequencing results and bioinformatic predictions. The identified relationships of the anti-fibrotic effect of GPs with miR-378a-5p and the PI3K/AKT signaling were evaluated using a miR-NC mimic and the PI3K inhibitor LY294002 as controls, respectively. RESULTS: TGF-ß1 stimulation up-regulated α-SMA, COL1, and COL3 in NRK-49F cells, and this effect was suppressed by GPs. Additionally, TGF-ß1 stimulation significantly changed the expression levels of 151 miRNAs, and GPs significantly suppressed the effect of TGF-ß1 on the levels of 18 of these miRNAs. Among them, miR-3588 and miR-378a-5p were down-regulated, and miR-135b-5p and miR-3068-5p were up-regulated upon TGF-ß1 induction. Of these miRNAs, miR-378a-5p was predicted to target the mRNAs of numerous proteins mainly enriched in the PI3K/AKT signaling pathway. The miRNA transfection experiments with the miR-NC mimic and PI3K inhibitor as controls showed that miR-378a-5p overexpression could suppress the TGF-ß1-induced up-regulation of α-SMA, COL1, PI3K, and AKT, including the phosphorylated form (p-AKT). CONCLUSION: GPs inhibit the PI3K/AKT signaling by up-regulating miR-378a-5p in TGF-ß1-stimulated NRK-49F cells and thereby reduce their massive secretion of ECM components. Given that this in-vitro model of renal interstitial fibrosis closely mimics the in-vivo pathogenesis, our results most likely apply to the in-vivo conditions.

Myopenic Obesity Determined by Fat Mass Percentage Predicts Risk of Aspirin-Induced Bleeding in Chinese Older Adults.

Background: Body mass index (BMI) correlates with aspirin-induced bleeding risk. However, skeletal muscle mass (SMM) loss and fat gain commonly occur with aging, making BMI not a reasonable marker of bleeding risk in older individuals. In the present study, we aimed to investigate the prognostic value of myopenic obesity based on the percent of fat mass (%FM) for aspirin-induced bleeding in Chinese patients over 60 years old. Methods: We prospectively analyzed 185 patients taking aspirin for primary and secondary prevention of cardiovascular diseases. Body composition parameters were estimated using bioelectrical impedance analysis. We defined myopenic obesity (MO) as a height-adjusted appendicular SMM <7.0 kg/m2 in males and <5.7 kg/m2 in females with a %FM >29% in males and >41% in females or a BMI ≥25 kg/m2. The patients were categorized into four groups by the presence or absence of myopenia and obesity. Results: Based on the %FM grouping, the bleeding risk was significantly higher in the MO group, followed by the nonmyopenic obesity, myopenic nonobesity, and nonmyopenic nonobesity groups (P = 0.044). No statistically significant differences in the probability of bleeding events were observed among the four BMI-based groups (P = 0.502). Multivariate Cox analysis indicated that MO (hazard ratio [HR] 2.724, 95% confidence interval [CI] 1.073-6.918, P = 0.035), aspirin dose (100 vs 50 mg/day, HR 2.609, 95% CI 1.291-5.273, P = 0.008), concomitant use of histamine-2 receptor antagonists and proton pump inhibitors (HR 1.777, 95% CI 1.007-3.137, P = 0.047), and hemorrhage history (HR 2.576, 95% CI 1.355-4.897, P = 0.004) were associated with bleeding events independently. Conclusion: %FM-based MO was an independent predictor of aspirin-induced bleeding in older Chinese individuals. Reducing %FM rather than BMI should be an optimal strategy for the management of myopenic obesity.

Size-dependent antibacterial of carbon dots by selective absorption and differential oxidative stress of bacteria.

Carbon dots (CDs), as one kind of zero-dimensional carbon-based nanomaterials, show great potential in combating emerging infectious diseases and antimicrobial infections. CDs with outstanding optical properties and benign biocompatibility have been reported as excellent antibacterial agents. However, few reports were focused on the relationship between the CDs' size and their antibacterial activity. Herein, the desired CDs (VCDs) were fabricated by a one-step electrochemical oxidation method using l-ascorbic acid as raw material, and four types of VCDs with different sizes were obtained by adjusting the reaction times. The effectiveness of antibacterial activity demonstrates the VCDs display size-dependent antibacterial activity, where the VCDs-2 (average size: 2.92 nm) exhibit superior antibacterial activity to others, attributing to the synergy of the absorption capacity of bacteria to VCDs and the ROS stimulated by VCDs. The VCDs-2 could more easily penetrate bacterial cells, stimulate the production of ROS, damage the cell walls of E. coli, and inhibit the growth and reproduction of bacteria. This work helps to understand the effect of CDs' size on antibacterial properties, and provides a direction for the design of novel antimicrobials with drug resistance.

Rationale and Design of LAPIS: A Multicenter Prospective Cohort Study to Investigate the Efficacy and Safety of Low-Dose Aspirin in Elderly Chinese Patients.

Purpose: Although aspirin can effectively reduce the occurrence of atherothrombosis, it is significantly associated with increased bleeding, with elderly individuals being at increased risk of cardiovascular diseases(CVDs) and hemorrhage. While the adverse effects of aspirin can be reduced by using the lowest effective dose, its optimal dose remains undetermined in the elderly Chinese population with both higher cardiovascular and bleeding risks. This study aims to assess the current status of aspirin therapy in real-world clinical settings as well as investigate the efficacy and safety of different doses of aspirin intake (≤ 50 mg/d and > 50 mg/d) for CVD prevention and management in elderly Chinese individuals. Patients and Methods: The Low-dose Aspirin for Primary and Secondary Prevention of Cardiovascular Disease in the Elderly Study (LAPIS) is a multicenter, prospective, observational cohort study. At least 10,000 people aged ≥ 60 years who require long-term aspirin therapy will be recruited. The effectiveness outcome is a composite of major cardiovascular events(MACEs), including nonfatal myocardial infarction, unstable angina, arteriosclerotic disease requiring surgery or intervention, nonfatal stroke, transient ischemic attack, or cardiovascular death (excluding intracranial hemorrhage). The safety outcome is a composite of the first occurrence of fatal bleeding, major bleeding and minor bleeding. Information on the incidence of aspirin-associated gastrointestinal adverse events will also be collected for safety analyses. Outcome measurements will be performed at intervals of 30 days, 3 months, 6 months and then every 6 months for the next 3 years. Conclusion: The results of the LAPIS study will ascertain the efficacy and safety of different doses of aspirin for the prevention and management of CVD, thereby providing evidence to determine the optimal evidence-based dose of aspirin therapy in Chinese elderly individuals. Trial Registration: ChiCTR1900021980 (chictr.org.cn). Registered on March 19, 2019.

Differences in treatment for Alzheimer's disease between urban and rural areas in China.

Introduction: In China, the increasing number of people with Alzheimer's disease (AD) poses a great challenge to families and the country. Economic and cultural differences cause a urban-rural gap in medical resources. This multicenter survey aimed to investigate the real-world practice of disease treatment among people with AD. Methods: People with AD and their caregivers from 30 provincial regions in mainland China were enrolled from October 2020 to December 2020 to be surveyed for their treatment experience. Logistic regression was used to explore the factors that influence medication adherence in all areas, urban areas, and rural areas. Results: In this survey, 1,427 participants came from urban areas, and 539 participants came from rural areas. Patients in urban areas were older (mean age 74 vs. 70, p = 0.001), less frequently had mild AD (36.0 vs. 52.1%, p < 0.001), and more often were cared for at professional institutions (8.8 vs. 3.2%, p < 0.001). In terms of pharmacotherapy, 77.8% of people accepted taking lifelong medication, whereas 61.3% of patients insisted on taking medications. Although 72.0% of rural people believed in taking lifelong medication, only 30.0% adhered to drug use. The major factors that influenced medication adherence for all patients with AD were regional distribution (p < 0.001, OR = 6.18, 95% CI: 4.93-7.74) and family earnings (p = 0.003, OR = 1.22, 95% CI: 1.07-1.38). In rural areas, family earnings (p = 0.008, OR = 1.44, 95% CI: 1.10-1.89) and severity of AD (p = 0.033, OR = 1.31, 95% CI: 1.02-1.68) were the main factors. Family earnings (p = 0.038, OR = 1.16, 95% CI: 1.01-1.34) was the only factor among urban areas. Among all non-pharmaceutical activities except for cognitive intervention, the participation rates of rural patients were significantly higher than those of urban patients (p < 0.05). Conclusion: Although national progress has been made in the public awareness of disease treatment, adequate diagnosis and medication adherence need to be prompted, especially in rural areas. Furthermore, lifelong treatment should be improved based on regional characteristics through the joint efforts of the government, health workers, and social volunteers.

Outcomes Associated with 50 mg/d and 100 mg/d Aspirin for the Prevention and Management of Cardiovascular Disease in Chinese Elderly: Single-Center Interim Analysis of a Multicenter, Prospective, Observational Study.

Purpose: Although aspirin can effectively reduce the occurrence of atherothrombosis, it is significantly associated with increased bleeding, with elderly individuals being at increased risk of cardiovascular diseases (CVD) and hemorrhage. This study aims to evaluate the efficacy and safety of aspirin 50 mg/d and 100 mg/d for the prevention and management of CVD in Chinese elderly. Patients and Methods: The Low-dose Aspirin for Primary and Secondary Prevention of Cardiovascular Disease in the Elderly Study (LAPIS) is a multicenter, prospective, observational cohort study, this study was a single-center interim analysis of LAPIS. Patients aged ≥60 and required long-term aspirin for primary and secondary prevention of CVD were eligible. From Apr 1, 2019 to Feb 28, 2022, 165 patients who received 50 mg/d aspirin and 261 patients who received 100 mg/d aspirin were included in the study. The incidence of major cardiovascular events (MACEs), bleeding events, and gastrointestinal adverse events were compared between two groups. Results: After adjusting for patient characteristics using propensity score matching, aspirin 100 mg/d was associated with increased incidence rates of total bleeding events (28.34 vs.17.25 events/100 patient-years, HR 1.671, 95% CI 1.024-2.712, P = 0.040) and minor bleeding events (27.63 vs.15.92 events/100 patient-years, HR 1.738, 95% CI 1.056-2.861, P = 0.031), whereas the incidence of MACE (6.35 vs 6.65 events/100 patient-years, HR 0.921, 95% CI 0.399-2.127, P = 0.848) and gastrointestinal adverse events (12.73 vs.10.42 events/100 patient-years, HR 1.206, 95% CI 0.623-2.337, P = 0.578) were similar between the two groups. Multivariate Cox analysis identified that aspirin dose (100 mg/d vs. 50 mg/d, HR 1.918, 95% CI 1.137-3.235, P = 0.015), concomitant use of other antiplatelets (HR 1.748, 95% CI 1.009-3.028, P = 0.046) and anticoagulants (HR 2.501, 95% CI 1.287-4.862, P = 0.007) were independently associated with bleeding events. Conclusion: 50 mg/d aspirin may be preferred to balance the safety and effectiveness in Chinese individuals over 60 years of age who need long-term aspirin for the prevention and management of CVD. Trial Registration: ChiCTR1900021980 (chictr.org.cn). Registered on 19 March 2019.

Machine-learning-assisted discovery of highly efficient high-entropy alloy catalysts for the oxygen reduction reaction.

High-entropy alloys (HEAs) have recently been applied in the field of heterogeneous catalysis benefiting from vast chemical space. However, huge chemical space also brings extreme challenges for the comprehensive study of HEAs by traditional trial-and-error experiments. Therefore, the machine learning (ML) method is presented to investigate the oxygen reduction reaction (ORR) catalytic activity of millions of reactive sites on HEA surfaces. The well-performed ML model is constructed based on the gradient boosting regression (GBR) algorithm with high accuracy, generalizability, and simplicity. In-depth analysis of the results demonstrates that adsorption energy is a mixture of the individual contributions of coordinated metal atoms near the reactive site. An efficient strategy is proposed to further boost the ORR catalytic activity of promising HEA catalysts by optimizing the HEA surface structure, which recommends a highly efficient HEA catalyst of Ir48Pt74Ru30Rh30Ag74. Our work offers a guide to the rational design and nanostructure synthesis of HEA catalysts.

Chiral Carbon Dots Derived from Serine with Well-Defined Structure and Enantioselective Catalytic Activity.

Carbon dots (C-Dots), with unique properties from tunable photoluminescence to biocompatibility, show wide applications in biotechnology, optoelectronic device and catalysis. Chiral C-Dots are expected to have strongly chirality-dependent biological and catalytic properties. For chiral C-Dots, a clear structure and quantitative structure-property relationship need to be clarified. Here, chiral C-Dots were fabricated by electrooxidation polymerization from serine enantiomers. The oxidized serine has a reversed chiral configuration to serine, which leads to the chiral C-Dots possessing inverse handedness compared with their raw materials. Electron circular dichroism spectrum, together with other diverse characterization techniques and theoretical calculations, confirmed that these chiral C-Dots (2-7 nm) have a well-defined primary structure of polycyclic dipeptide and possess a spatial structure with a c-axis of hexagonal symmetry and two cyclic dipeptides as the spatial structural unit. These chiral C-Dots also show enantioselective catalytic activity on DOPA enantiomers oxidation.

Strain-promoted conductive metal-benzenhexathiolate frameworks for overall water splitting.

Designing efficient catalysts for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is a desirable strategy for overall water splitting and the generation of clean and renewable energies. Herein, the electrocatalytic HER and OER activity of the conductive metal-benzenhexathiolate (M-BHT) frameworks has been evaluated utilizing first-principles calculations. The in-plane π-d conjugation of M-BHT guarantees fast electron transfer during electrocatalytic reactions. Notably, Rh-BHT holds the promise of bifunctional HER/OER activity with the overpotentials of 0.07/0.36 V. Furthermore, the application of strain engineering tailors the adsorption of intermediates and promotes the overall water splitting performance. Rh-BHT with the +1% tensile strain shows the HER/OER overpotential of 0.02/0.37 V. This work not only demonstrates the prospects of conductive metal-organic frameworks in electrocatalysis but also offers new insights into designing efficient catalysts by strain engineering.

A Unified Understanding of Deep NLP Models for Text Classification.

The rapid development of deep natural language processing (NLP) models for text classification has led to an urgent need for a unified understanding of these models proposed individually. Existing methods cannot meet the need for understanding different models in one framework due to the lack of a unified measure for explaining both low-level (e.g., words) and high-level (e.g., phrases) features. We have developed a visual analysis tool, DeepNLPVis, to enable a unified understanding of NLP models for text classification. The key idea is a mutual information-based measure, which provides quantitative explanations on how each layer of a model maintains the information of input words in a sample. We model the intra- and inter-word information at each layer measuring the importance of a word to the final prediction as well as the relationships between words, such as the formation of phrases. A multi-level visualization, which consists of a corpus-level, a sample-level, and a word-level visualization, supports the analysis from the overall training set to individual samples. Two case studies on classification tasks and comparison between models demonstrate that DeepNLPVis can help users effectively identify potential problems caused by samples and model architectures and then make informed improvements.

Molecular Mechanism of Tetramethylpyrazine Ameliorating Neuroexcitotoxicity through Activating the PKA/CREB Signaling Pathway.

BACKGROUND: Excitotoxicity plays a key role in nervous system disease and can trigger a critical cascade of reaction which affects cell viability and promotes neuronal death. Tetramethylpyrazine (TMP) reveals its effect in the treatment of neurovascular diseases by antiapoptosis. Recently, there were several studies that demonstrated that the PKA/CREB signaling pathway played a role in neural disease because of excitotoxicity, such as stroke, AD, and Parkinson's disease. In this study, we wanted to focus on the protective effect of tetramethylpyrazine against excitotoxicity through the PKA/CREB signaling pathway. METHODS: In order to verify whether tetramethylpyrazine can attenuate excitotoxicity through the PKA/CREB signaling pathway, we first used molecular docking technology to predict the combinational strength and mode of tetramethylpyrazine with the proteins in the PKA/CREB signaling pathway. Then, we determined the optimal concentration and time according to the model effect of glutamate (Glu) with different concentration gradients and action times in PC12 cells. After the determination of concentration and time of glutamate in the previous step as the model way, tetramethylpyrazine was added to determine its influence on the cell viability under different doses and times. The TUNEL assay and flow cytometry were used to detect apoptosis. RT-PCR was used to detect the expression of Bcl-2, Bax, PKA, and 5CREB genes, and Western blot was used to detect the expression of these factors. RESULT: Tetramethylpyrazine had a good docking score (-5.312) with PKA and had a moderately docking score (-3.838) with CREB. The CCK-8 cell activity assay showed that the activity of PC12 cells decreased gradually with the increase in glutamate concentration and time, and PC12 cells were treated with 10 mM/L glutamate (the half of the inhibitory concentration (IC50)) for 12 hours. Then, the cell viability increased gradually following the increased concentration of tetramethylpyrazine. When PC12 cells were treated with 0.1 mM/L tetramethylpyrazine, the cell viability was increased significantly compared with the control group (P < 0.05). The TUNEL assay and flow cytometry also showed that tetramethylpyrazine could decrease the apoptosis induced by glutamate. In the result of RT-PCR, the transcriptional levels of Bcl-2, PKA, and CREB were increased and Bax was decreased. Meanwhile, Western blot showed that expression levels of Bcl-2, PKA, CREB, and p-CREB were increased and Bax was decreased. CONCLUSIONS: This study provided evidence that tetramethylpyrazine can protect against apoptosis caused by neuroexcitotoxicity and the protective mechanism is closely related to the activation of the PKA/CREB signaling pathway.

Chiral carbon dots - a functional domain for tyrosinase Cu active site modulation via remote target interaction.

The nano-hybrid enzyme is an ideal catalytic system that integrates various advantages from biocatalysis and nanocatalysis into homogeneous and heterogeneous catalysis. However, great efforts are still needed to fully understand the interactions between nanoparticles and enzymes. Here, we show chiral carbon dots (CDs) as a new functional domain for tyrosinase Cu active site modulation via remote target interaction. Three kinds of chiral CDs (LCDs-1/-2/-3; DCDs-1/-2/-3) were fabricated by thermal treatment of citric acid and L/D-aspartic acid. Then a series of CDs/tyrosinase composites (namely, nano-hybrid-enzymes) were prepared, demonstrating good regulation of enzyme catalytic kinetics. Especially, we find that LCDs-1 is an irreversible inhibitor with great inhibition effect while the others are all reversible inhibitors. Furthermore, it is suggested by both experiments and all-atom molecular dynamics simulations that the joint effect of LCDs-1 and tyrosinase makes LCDs-1 serve as a new functional domain, which has a distinguished ability to control the conformational changes of the key sites of the active center of the tyrosinase (e.g., H60) and thus the escaping behavior of copper ions and the catalytic activity. This work opens a new route for nano-hybrid-enzyme design and enzyme activity regulation with chiral carbon materials as functional domains via remote target interaction.

Corrigendum to "Network Pharmacology-Based Strategy for Predicting Active Ingredients and Potential Targets of Coptis chinensis Franchin Polycystic Ovary Syndrome".

[This corrects the article DOI: 10.1155/2021/6651307.].

A durable and pH-universal self-standing MoC-Mo2C heterojunction electrode for efficient hydrogen evolution reaction.

Efficient water electrolyzers are constrained by the lack of low-cost and earth-abundant hydrogen evolution reaction (HER) catalysts that can operate at industry-level conditions and be prepared with a facile process. Here we report a self-standing MoC-Mo2C catalytic electrode prepared via a one-step electro-carbiding approach using CO2 as the feedstock. The outstanding HER performances of the MoC-Mo2C electrode with low overpotentials at 500 mA cm-2 in both acidic (256 mV) and alkaline electrolytes (292 mV), long-lasting lifetime of over 2400 h (100 d), and high-temperature performance (70 oC) are due to the self-standing hydrophilic porous surface, intrinsic mechanical strength and self-grown MoC (001)-Mo2C (101) heterojunctions that have a ΔGH* value of -0.13 eV in acidic condition, and the energy barrier of 1.15 eV for water dissociation in alkaline solution. The preparation of a large electrode (3 cm × 11.5 cm) demonstrates the possibility of scaling up this process to prepare various carbide electrodes with rationally designed structures, tunable compositions, and favorable properties.