Carbene-Catalyzed [4+2] Cycloaddition of Cyclobutenones and Isatins for Quick Access to Chiral Chlorine-Containing Spirocyclic δ-Lactones.

Here we report a carbene-catalyzed enantio- and diastereoselective [4+2] cycloaddition reaction of cyclobutenones with isatins for the quick and efficient synthesis of spirocyclic δ-lactones bearing a chiral chlorine. A broad range of substrates with various substitution patterns proceed smoothly in this reaction, with the spirooxindole δ-lactone products afforded in generally good to excellent yields and optical purities under mild reaction conditions.

MMSyn: A New Multimodal Deep Learning Framework for Enhanced Prediction of Synergistic Drug Combinations.

Combination therapy is a promising strategy for the successful treatment of cancer. The large number of possible combinations, however, mean that it is laborious and expensive to screen for synergistic drug combinations in vitro. Nevertheless, because of the availability of high-throughput screening data and advances in computational techniques, deep learning (DL) can be a useful tool for the prediction of synergistic drug combinations. In this study, we proposed a multimodal DL framework, MMSyn, for the prediction of synergistic drug combinations. First, features embedded in the drug molecules were extracted: structure, fingerprint, and string encoding. Then, gene expression data, DNA copy number, and pathway activity were used to describe cancer cell lines. Finally, these processed features were integrated using an attention mechanism and an interaction module and then input into a multilayer perceptron to predict drug synergy. Experimental results showed that our method outperformed five state-of-the-art DL methods and three traditional machine learning models for drug combination prediction. We verified that MMSyn achieved superior performance in stratified cross-validation settings using both the drug combination and cell line data. Moreover, we performed a set of ablation experiments to illustrate the effectiveness of each component and the efficacy of our model. In addition, our visual representation and case studies further confirmed the effectiveness of our model. All results showed that MMSyn can be used as a powerful tool for the prediction of synergistic drug combinations.

Based on Virtual Screening and Simulation Exploring the Mechanism of Plant-Derived Compounds with PINK1 to Postherpetic Neuralgia.

Accumulating evidence strongly supports that PINK1 mutation can mediate mitochondrial autophagy dysfunction in dopaminergic neurons. This study was conducted to determine the role of PINK1 in the pathogenesis of postherpetic neuralgia (PHN) and find new targets for its treatment. A rigorous literature review was conducted to identify 2801 compounds from more than 200 plants in Asia. Virtual screening was used to shortlist the compounds into 20 groups based on their binding energies. MM/PBSA was used to further screen the compound dataset, and vitexin, luteoloside, and 2'-deoxyadenosine-5'-monophosphate were found to have a score of - 59.439, - 52.421, and - 47.544 kcal/mol, respectively. Pain behavioral quantification, enzyme-linked immunosorbent assay, quantitative polymerase chain reaction, western blotting, and transmission electron microscopy were used to confirm the effective mechanism. Vitexin had the most significant therapeutic effect on rats with PHN followed by luteoloside; 2'-deoxyadenosine-5'-monophosphate had no significant effect. Our findings suggested that vitexin could alleviate PHN by regulating mitochondrial autophagy through PINK1.

Evaluation of Rhododendri Mollis Flos and its representative component as a potential analgesic.

Rhododendri Mollis Flos (R. mole Flos), the dried flowers of Rhododendron mole G. Don, have the ability to relieve pain, dispel wind and dampness, and dissolve blood stasis, but they are highly poisonous. The significance of this study is to explore the analgesic application potential of R. mole Flos and its representative component. According to the selected processing methods recorded in ancient literature, the analgesic activities of wine- and vinegar-processed R. mole Flos, as well as the raw product, were evaluated in a writhing test with acetic acid and a formalin-induced pain test. Subsequently, the HPLC-TOP-MS technique was utilized to investigate the changes in active components before and after processing once the variations in activities were confirmed. Based on the results, rhodojaponin VI (RJ-Vl) was chosen for further study. After processing, especially in vinegar, R. mole Flos did not only maintain the anti-nociception but also showed reduced toxicity, and the chemical composition corresponding to these effects also changed significantly. Further investigation of its representative components revealed that RJ-VI has considerable anti-nociceptive activity, particularly in inflammatory pain (0.3 mg/kg) and peripheral neuropathic pain (0.6 mg/kg). Its toxicity was about three times lower than that of rhodojaponin III, which is another representative component of R. mole Flos. Additionally, RJ-VI mildly inhibits several subtypes of voltage-gated sodium channels (IC50 > 200 µM) that are associated with pain or cardiotoxicity. In conclusion, the chemical substances and biological effects of R. mole Flos changed significantly before and after processing, and the representative component RJ-VI has the potential to be developed into an effective analgesic.

Treatment of neuropathic pain by traditional Chinese medicine: An updated review on their effect and putative mechanisms of action.

Neuropathic pain (NP) is a common chronic pain with heterogeneous clinical features, and consequent lowering of quality of life. Currently, although conventional chemical drugs can effectively manage NP symptoms in the short term, their long-term efficacy is limited, and they come with significant side effects. In this regard, traditional Chinese medicine (TCM) provides a promising avenue for treating NP. Numerous pharmacological and clinical studies have substantiated the effectiveness of TCM with multiple targets and mechanisms. We aimed to outline the characteristics of TCM, including compound prescriptions, single Chinese herbs, active ingredients, and TCM physical therapy, for NP treatment and discussed their efficacy by analyzing the pathogenesis of NP. Various databases, such as PubMed, Web of Science, China National Knowledge Infrastructure, and Wanfang database, were searched. We focused on recent research progress in NP treatment by TCM. Finally, we proposed the future challenges and emerging trends in the treatment of NP. TCM demonstrates significant clinical efficacy in NP treatment, employing multi-mechanisms. Drawing from the theory of syndrome differentiation, four types of dialectical treatments for NP by compound TCM prescriptions were introduced: promoting blood circulation and removing blood stasis; promoting blood circulation and promote Qi flow; warming Yang and benefiting Qi; soothing the liver and regulating Qi. Meanwhile, 33 single Chinese herbs and 25 active ingredients were included. In addition, TCM physical therapy (e.g., acupuncture, massage, acupoint injection, and fumigation) also showed good efficacy in NP treatment. TCM, particularly through the use of compound prescriptions and acupuncture, holds bright prospects in treating NP owing to its diverse holistic effects. Nonetheless, the multi-targets of TCM may result in possible disadvantages to NP treatment, and the pharmacological mechanisms of TCM need further evaluation. Here, we provide an overview of NP treatment via TCM, based on the pathogenesis and the potential therapeutic mechanisms, thus providing a reference for further studies.

Design, Synthesis, Formulation, and Bioevaluation of Trisubstituted Triazines as Highly Selective mTOR Inhibitors for the Treatment of Human Breast Cancer.

The aberrant activation of the PI3K/mTOR signaling pathway is implicated in various human cancers. Thus, the development of inhibitors targeting mTOR has attracted considerable attention. In this study, we used a structure-based drug design strategy to discover a highly potent and kinase-selective mTOR inhibitor 24 (PT-88), which demonstrated an mTOR inhibitory IC50 value of 1.2 nM without obvious inhibition against another 195 kinases from the kinase profiling screening. PT-88 displayed selective inhibition against MCF-7 cells (IC50: 0.74 µM) with high biosafety against normal cells, in which autophagy induced by mTOR inhibition was implicated. After successful encapsulation in a lipodisc formulation, PT-88 demonstrated favorable pharmacokinetic and biosafety profiles and exerted a large antitumor effect in an MCF-7 subcutaneous bearing nude mice model. Our study shows the discovery of a highly selective mTOR inhibitor using a structure-based drug discovery strategy and provides a promising antitumor candidate for future study and development.

The impact of social support for older adults in nursing homes on successful aging: a moderated mediation model.

Objective: To investigate the connection between social support (SS) and successful aging (SA) in older adults residing in nursing homes, examining the mediating role of meaning in life (MIL). Additionally, this study aims to assess whether frailty moderates the mediation model. Methods: A cross-sectional survey approach was employed to recruit older adults from six nursing homes in Sichuan Province between August 2022 and December 2022. Questionnaires, including the General Information Questionnaire, Social Support Rating Scale (SSRS), Meaning in Life Questionnaire (MLQ), Tilburg Frailty Indicator (TFI), and Successful Aging Inventory (SAI), were administered. Data obtained from the completed questionnaires were analyzed using SPSS and its macro program PROCESS. Results: SS emerged as a noteworthy positive predictor of SA in older adults of nursing homes. MIL was identified as a partial mediator in the link between SS and SA. Furthermore, frailty attenuated the positive predictive impact of MIL on SA and moderated the latter part of the mediation model, wherein SS influences SA through MIL. The influence of MIL on SA was more pronounced in older adults with lower frailty levels in nursing homes, while it was diminished in those with higher levels of frailty. Conclusion: Apart from ensuring the availability of essential medical resources in long-term care for older adults, workers in nursing homes should also recognize the significance of "spiritual aging" to cultivate a sense of MIL among older adults. Simultaneously, attention must be directed toward screening for frailty indicators in older adults. Psychological care and physical exercise programs should be intensified for older adults with a high level of frailty, aiming to decelerate the progression of frailty in nursing home residents. This approach leverages the mediating role of MIL and the moderating influence of frailty, ultimately enhancing SA and promoting healthy aging in older adults within nursing home settings.

The effect of occupational coping self-efficacy on presenteeism among ICU nurses in Chinese public hospitals: a cross-sectional study.

Background: Nurses are the largest occupational group in the health field, with inestimable value in realizing universal health coverage, and nurses' physical and mental health has become an ordinary global reality. Compared with explicit absence, nurses' presenteeism has a more lasting impact and significant harm and loss. It has become an essential factor affecting nurses' physical and mental health, declining quality of healthcare services, and elevated healthcare-related risks. There is a lack of research exploring whether occupational coping self-efficacy influences nurses' presenteeism behavior, especially in less-developed regions of China. Objective: This study aimed to investigate the current status of ICU nurses' occupational coping self-efficacy and presenteeism in public hospitals in western China and to explore the impact of ICU nurses' occupational coping self-efficacy on presenteeism. Methods: A cross-sectional research design selected 722 ICU nurses in western China from January to February 2023 as survey respondents. A general information questionnaire, Occupational Coping Self-Efficacy Scale (OCSE-N), and Stanford Presenteeism Scale (SPS-6) were used. SPSS 21.0 software was used for statistical analysis. Pearson correlation analysis and multivariate hierarchical regression were used to explore the influence of ICU nurses' occupational coping self-efficacy on presenteeism. Results: A total of 722 ICU nurses completed the questionnaire. The OCSE-N score of ICU nurses was (22.24 ± 6.15), and the SPS-6 score was (16.83 ± 4.24). The high presenteeism was 67.23%. Correlation analysis showed that in ICU nurses, OCSE-N total score was negatively correlated with SPS-6 total score (r = -0.421, p < 0.05), indicating that the higher the level of occupational coping self-efficacy, the lower the presenteeism. Multiple hierarchical regression analysis showed that occupational coping self-efficacy strongly predicted presenteeism, accounting for approximately 18.35% of the total variance. Conclusion: There is a correlation between ICU nurses' occupational coping self-efficacy and presenteeism, and nurses' occupational coping self-efficacy affects presenteeism differently. Managers should pay attention to nurses' occupational coping self-efficacy to promote nurses' presenteeism reduction.

Synthesis and bioevaluation of Scutellarein-Tertramethylpyrazine hybrid molecules for the treatment of ischemic stroke.

Ischemic stroke caused by insufficient blood supply to the brain may produce a sequence of cascade reactions, leading to oxidative stress and ultimately inducing nerve cell damage. Therefore, hybrid molecules with multiple therapeutic effects have irreplaceable advantages for the treatment of ischemic stroke. Based on the previous works, two types of Scutellarein and Tertramethylpyrazine hybrid molecules were designed and synthesized according to the PepT 1-based design. After systematic research, all synthesized hybrid molecules exhibited more excellent neuroprotective effect and antiplatelet activity compared to the original drugs. Among them, the selected compound 1e with superior neuroprotective and antiplatelet effects could significantly enhance the permeability on the Caco-2 monolayer membrane and inhibit the Gly-Sar uptake on Caco-2 cells. Meanwhile, the result of intestinal perfusion has also confirmed that the absorption of the selected compound 1e is indeed increased. Further, the selected compound 1e significantly reduce the cerebral infarction volume of middle cerebral artery occlusion/reperfusion rats. Especially, the cerebral infarction volume of the high-dose 1e group reduced to one fourth of the model group. Meanwhile, results of hematoxylin-eosin staining also indicated that the damage in the hippocampus CA1 region was significantly alleviated after treatment with the compound 1e. Accordingly, molecular hybridization strategy is one of the simple and feasible ways to improve the therapeutic effect of single targeted drug.

Latent profile analysis and influence factors study of presenteeism among ICU nurses in China.

Background: Presenteeism is a significant global public health problem, and nurses are a high-prevalence group of presenteeism, affecting not only nurses' physical and mental health, work efficiency, and quality of work but even poses a serious threat to patient safety. Objective: The categorization of presenteeism among ICU nurses is unclear. Our research aims to explore the subtypes of presenteeism among ICU nurses based on latent profile analysis, analyze the influencing factors of different subtypes, and provide a reference basis for developing targeted interventions to reduce the presenteeism rate. Methods: From January to February 2023, 509 ICU nurses in Sichuan Province, China, were selected as respondents and surveyed using the general information questionnaire, the presenteeism scale, and the perceived social support scale. Potential categories of presenteeism among ICU nurses were explored using potential profile analysis, and factors influencing the potential types of presenteeism among ICU nurses were investigated using the chi-square test and multivariate logistic regression analysis. Results: The best model was suggested to consist of three profiles: low presenteeism-normal coping group (18.3%), moderate presenteeism group (47.9%), and high presenteeism-work limitation group (33.8%). Multiple logistic regression results showed that secondary hospitals (OR = 0.116, p = 0.015), good physical health (OR = 0.084, p = 0.023), general physical health (OR = 0.016, p = 0.037), ICU human resource allocation = 1:2.5 to 3 (OR = 0.315, p = 0.007), and higher social support scores (OR = 0.975, p = 0.047) were more likely to be grouped into low presenteeism-normal coping group; married with no children (OR = 24.554, p = 0.005) were more likely to be grouped into moderate presenteeism group; and having experienced workplace violence in the past year (OR = 1.182, p = 0.049) were more likely to be grouped into high presenteeism-work limitation group. Conclusion: There is group heterogeneity in the presenteeism of ICU nurses, and nursing managers should develop targeted interventions to reduce the presenteeism rate of ICU nurses according to the characteristics and influencing factors of each type of presenteeism of ICU nurses.

Virtual screening of novel mTOR inhibitors for the potential treatment of human colorectal cancer.

The abnormal activation of the mTOR pathway is closely related to the occurrence and progression of cancer, especially colorectal cancer. In this study, a rational virtual screening strategy has been established and MT-5, a novel mTOR inhibitor with a quinoline scaffold, was obtained from the ChemDiv database. MT-5 showed potent kinase inhibitory activity (IC50: 8.90 µM) and antiproliferative effects against various cancer cell lines, especially HCT-116 cells (IC50: 4.61 µM), and this was 2.2-fold more potent than that of the cisplatin control (IC50: 9.99 µM). Western blot, cell migration, cycle arrest, and apoptosis assays were performed with HCT-116 cells to investigate the potential anticancer mechanism of MT-5. Metabolic stability results in vitro indicated that MT-5 exhibited good stability profiles in artificial gastrointestinal fluids, rat plasma, and liver microsomes. In addition, the key contribution of the residues around the binding pocket of MT-5 in binding to the mTOR protein was also investigated from a computational perspective.

Design, synthesis and bioevaluation of PI3Kα-selective inhibitors as potential colorectal cancer drugs.

The dysregulation of the phosphoinositide 3-kinase (PI3K)/mammalian target of rapamycin signaling pathway has been implicated in various human cancers, and isoform-selective inhibitors targeting PI3Kα have received significant interest in recent years. In this study, we have designed and synthesized three series of substituted benzoxazole derivatives based on the clinical candidate TAK-117 (8a). A detailed structure-activity relationship (SAR) study has identified the optimal compound 18a bearing a quinoxaline scaffold. Compared to the control 8a, 18a exhibited 4.4-fold more potent inhibitory activity against PI3Kα (IC50: 2.5 vs 11 nM) and better isoform-selective profiles over other PI3Ks. In addition, 18a showed a 1.5-fold more potent antiproliferative effect against HCT-116 cell lines (IC50: 3.79 vs 5.80 µM) and a better selectivity over the normal tissue cells. The potential antitumor mechanism and in vitro metabolic stability of 18a were also investigated. Notably, pharmacokinetic assays indicated that 18a had a higher plasma exposure, a higher maximum concentration and shorter elimination time compared to 8a.

Climate predicts wildland fire extent across China.

Wildland fire extent varies seasonally and interannually in response to climatic and landscape-level drivers, yet predicting wildfires remains a challenge. Existing linear models that characterize climate and wildland fire relationships fail to account for non-stationary and non-linear associations, thus limiting prediction accuracy. To account for non-stationary and non-linear effects, we use time-series climate and wildfire extent data from across China with unit root methods, thus providing an approach for improved wildfire prediction. Results from this approach suggest that wildland area burned is sensitive to vapor pressure deficit (VPD) and maximum temperature changes over short and long-term scenarios. Moreover, repeated fires constrain system variability resulting in non-stationarity responses. We conclude that an autoregressive distributed lag (ARDL) approach to dynamic simulation models better elucidates interactions between climate and wildfire compared to more commonly used linear models. We suggest that this approach will provide insights into a better understanding of complex ecological relationships and represents a significant step toward the development of guidance for regional planners hoping to address climate-driven increases in wildfire incidence and impacts.

An innovative ensemble model based on deep learning for predicting COVID-19 infection.

Nowadays, global public health crises are occurring more frequently, and accurate prediction of these diseases can reduce the burden on the healthcare system. Taking COVID-19 as an example, accurate prediction of infection can assist experts in effectively allocating medical resources and diagnosing diseases. Currently, scholars worldwide use single model approaches or epidemiology models more often to predict the outbreak trend of COVID-19, resulting in poor prediction accuracy. Although a few studies have employed ensemble models, there is still room for improvement in their performance. In addition, there are only a few models that use the laboratory results of patients to predict COVID-19 infection. To address these issues, research efforts should focus on improving disease prediction performance and expanding the use of medical disease prediction models. In this paper, we propose an innovative deep learning model Whale Optimization Convolutional Neural Networks (CNN), Long-Short Term Memory (LSTM) and Artificial Neural Network (ANN) called WOCLSA which incorporates three models ANN, CNN and LSTM. The WOCLSA model utilizes the Whale Optimization Algorithm to optimize the neuron number, dropout and batch size parameters in the integrated model of ANN, CNN and LSTM, thereby finding the global optimal solution parameters. WOCLSA employs 18 patient indicators as predictors, and compares its results with three other ensemble deep learning models. All models were validated with train-test split approaches. We evaluate and compare our proposed model and other models using accuracy, F1 score, recall, AUC and precision metrics. Through many studies and tests, our results show that our prediction models can identify patients with COVID-19 infection at the AUC of 91%, 91%, and 93% respectively. Other prediction results achieve a respectable accuracy of 92.82%, 92.79%, and 91.66% respectively, f1-score of 93.41%, 92.79%, and 92.33% respectively, precision of 93.41%, 92.79%, and 92.33% respectively, recall of 93.41%, 92.79%, and 92.33% respectively. All of these exceed 91%, surpassing those of comparable models. The execution time of WOCLSA is also an advantage. Therefore, the WOCLSA ensemble model can be used to assist in verifying laboratory research results and predict and to judge various diseases in public health events.

Laser operation at 1.2†µm in Ho3+-doped ZBYA glass fibers.

Powerful 1.2-µm laser operation was produced in Ho3+-doped single-cladding, in-house fabricated ZrF4-BaF2-YF3-AlF3 (ZBYA) glass fibers. The fibers were fabricated based on ZBYA glass with a composition of ZrF4-BaF2-YF3-AlF3. Pumped by an 1150-nm Raman fiber laser, the maximum combined laser output power emitted from both sides of a 0.5-mol% Ho3+-doped ZBYA fiber was 6.7 W, with a slope efficiency of 40.5%. We also observed lasing at 2.9 µm with an output power of 350 mW, which was ascribed to the transition of Ho3+:5I6 → 5I7. The effect of rare earth (RE) doping concentration and the length of the gain fiber were also investigated to determine their effect on laser performance at 1.2 µm and 2.9 µm.

Source and health risk assessment of soil polycyclic aromatic hydrocarbons under straw burning condition in Changchun City, China.

Changchun, China is located in one of the world's three golden corn belts. As a key commodity grain base in China, Changchun plays a vital role in providing food security in the northeast. A total of 16 polycyclic aromatic hydrocarbons (PAHs) was analyzed to determine the influence of anthropogenic activities on the environmental quality of agricultural soils under straw burning conditions. The polycyclic aromatic hydrocarbons soil contamination severity was evaluated using the Maliszewska-Kordybach method. The results indicated that the agricultural soils of Changchun are substantial contaminated with PAHs. Petroleum, biomass, and coal combustion are the primary sources of PAH and have been determined using principal component analysis (PCA) and the isomeric ratio approach. The degree of hazard to human health was assessed using toxicity equivalence and increased lifetime cancer risk (ILCR) factors, except in localized areas during adulthood, the general risk was found to be modest. This study provides important information on PAH exposure in agricultural soils in northeast China, and the findings aid in the exploitation of straw and the mitigation of soil environmental concerns, allowing northeast China to achieve green agricultural development.

Residues, potential source and ecological risk assessment of polycyclic aromatic hydrocarbons (PAHs) in surface water of the East Liao River, Jilin Province, China.

The environmental risks posed by polycyclic aromatic hydrocarbons (PAHs) and the diversity of their anthropogenic origins make them a global issue. Therefore, it is of utmost significance for protecting the aquatic environment and the growth of neighboring populations to identify their possible origins and ecological risk. Here, we detail the contamination profiles of 15 PAHs found in the East Liao River's surface waters in Jilin Province and use the receptor model Absolute Principal Component Analysis - Multiple Linear Regression (APCS-MLR) and diagnostic ratios method to identify the primary potential sources of pollution. Based on the natural hazard risk formation theory (NHRFT), an ecological risk assessment (ERA) model for PAHs in the East Liao River was developed. The method assesses the ecological risk status of PAHs by integrating the risk quotient (RQ) approach and the DPSIRM (driving force, pressure, state, impact, response, management) conceptual framework. Total concentrations in the surface water body were between 396.42 and 624.06 ng/L, with an average of 436.99 ng/L. The source research revealed that coal, biomass, and traffic emission sources are the most likely PAH contributors to the East Liao River. The ERA found that the majority of the sites' locations of the study were at low risk for PAHs in surface water bodies (30.7 % and 32.2 %, respectively), while only a tiny percentage of sites were at high or very high risk (1.8 % and 13.6 %). The study results provide theoretical support for the East Liao River's ecological, environmental protection, and policy formulation.

High doses of rosuvastatin induce impaired branched-chain amino acid catabolism and lead to insulin resistance.

NEW FINDINGS: What is the central question of this study? Is there a risk of developing diabetes associated with statin treatment? What is the underlying mechanism of the increased incidence rate of new-onset diabetes in patients treated with rosuvastatin? What is the main finding and its importance? Rosuvastatin therapy reduced intraperitoneal glucose tolerance and changed the catabolism of branched-chain amino acid (BCAAs) in white adipose tissue and skeletal muscle. Protein phosphatase 2Cm knockdown completely abolished the effects of insulin and rosuvastatin on glucose absorption. This study provides mechanistic support for recent clinical data on rosuvastatin-related new-onset diabetes and underscores the logic for intervening in BCAA catabolism to prevent the harmful effects of rosuvastatin. ABSTRACT: Accumulating evidence indicates that patients treated with rosuvastatin have an increased risk of developing new-onset diabetes. However, the underlying mechanism remains unclear. In this study, we administered rosuvastatin (10 mg/kg body weight) to male C57BL/6J mice for 12 weeks and found that oral rosuvastatin dramatically reduced intraperitoneal glucose tolerance. Rosuvastatin-treated mice showed considerably higher serum levels of branched-chain amino acids (BCAAs) than control mice. They also showed dramatically altered expression of BCAA catabolism-related enzymes in white adipose tissue and skeletal muscle, including downregulated mRNA expression of BCAT2 and protein phosphatase 2Cm (PP2Cm) and upregulated mRNA expression of branched-chain ketoacid dehydrogenase kinase (BCKDK). The levels of BCKD in the skeletal muscle were reduced in rosuvastatin-treated mice, which was associated with lower PP2Cm protein levels and increased BCKDK levels. We also investigated the effects of rosuvastatin and insulin administration on glucose metabolism and BCAA catabolism in C2C12 myoblasts. We observed that incubation with insulin enhanced glucose uptake and facilitated BCAA catabolism in C2C12 cells, which was accompanied by elevated Akt and glycogen synthase kinase 3 ß (GSK3ß) phosphorylation. These effects of insulin were prevented by co-incubation of the cells with 25 µM rosuvastatin. Moreover, the effects of insulin and rosuvastatin administration on glucose uptake and Akt and GSK3ß signaling in C2C12 cells were abolished when PP2Cm was knocked down. Although the relevance of these data, obtained with high doses of rosuvastatin in mice, to therapeutic doses in humans remains to be elucidated, this study highlights a potential mechanism for the diabetogenic effects of rosuvastatin, and suggests that BCAA catabolism could be a pharmacological target for preventing the adverse effects of rosuvastatin.

Identifying novel selective PPO inhibitors through structure-based virtual screening and bio-evaluation.

Protoporphyrinogen oxidase (PPO) is a key enzyme in chlorophyll and heme biosynthesis, and the development of its inhibitors is of great importance both in the pharmaceutical and pesticide industries. However, the currently developed PPO inhibitors have insignificant bio-selectivity and have a serious impact on non-target organisms. In this study, a docking-based virtual screening approach combined with bio-activity testing was used to obtain novel selective inhibitors of PPO. The results of the bio-activity test showed that thirteen compounds showed 10-fold selectivity over human PPO. And the best selective compound, ZINC70338, has a K i value of 2.21 µM for Nicotiana tabacum PPO and >113-fold selectivity for human PPO. The selectivity mechanism of ZINC70338 in different species of PPO was then analyzed by molecular dynamics simulations to provide a design basis and theoretical guidance for the design of novel selective inhibitors.