Protective Effects of Baicalin on Lipopolysaccharide-Induced Injury in Caenorhabditis elegans.

OBJECTIVES: Sepsis-induced inflammation injury and oxidative stress are well known causes of mortality. The anti-inflammatory effects of baicalin have been proposed in a mouse model of experimental sepsis. Here, we investigated its protective effects and associated mechanisms with respect to lipopolysaccharide (LPS)-induced injury in Caenorhabditis elegans. METHODS: Worms were stimulated by LPS (100 µg/mL), with baicalin (1, 10, 100 µmol/L), for 24 h. Animal survival rates and behaviors (reversal and omega turn) were then determined. Further, levels of the inflammatory cytokines interleukin 6 (IL-6), IL-1, and tumor necrosis factor (TNF)-α were detected by enzyme-linked immunosorbent assay. Western blotting was also performed to determine the protein expression levels of Toll-like receptor 4 (TLR4), nuclear factor-κB (NF-κB), Bax, and Bcl-2. The activities of malondialdehyde (MDA) and superoxide dismutase (SOD) contents were determined using corresponding kits. RESULTS: Baicalin (10, 100 µmol/L) improved LPS-stimulated C. elegans survival and rescued behavioral phenotypes. It also suppressed the oxidative stress related to LPS injury by decreasing MDA levels and increasing SOD activity. Moreover, the inflammatory response was inhibited as evidenced by decreased levels of cytokines including IL-6, IL-1, and TNF-α. In addition, baicalin treatment significantly decreased cleaved Bax levels and increased Bcl-2 expression in C. elegans treated with LPS. Simultaneously, the expression of NF-κB and TLR4 was significantly decreased. CONCLUSION: Baicalin treatment protects against LPS-induced injury by decreasing oxidative stress, repressing the inflammatory cascade, and inhibiting apoptosis.

Relationships between PON1 Q192R polymorphism and clinical outcome of antiplatelet treatment after percutaneous coronary intervention: a meta-analysis.

This meta-analysis was performed to assess the relationships between the PON1 Q192R (rs662 T>C) polymorphism and the clinical outcome of antiplatelet treatment after percutaneous coronary intervention (PCI). A range of electronic databases were searched: Web of Science (1945-2013), the Cochrane Library Database (Issue 12, 2013), PubMed (1966-2013), EMBASE (1980-2013), CINAHL (1982-2013) and the Chinese Biomedical Database (CBM) (1982-2013) without language restrictions. Meta-analysis was conducted using the STATA 12.0 software. The crude odds ratio (OR) with their 95 % confidence interval (CI) were calculated. Six clinical cohort studies with a total number of 5,189 patients undergoing PCI for coronary heart disease were included. Our meta-analysis revealed that the PON1 Q192R polymorphism was correlated with an increased risk of major adverse cardiovascular events (MACE) in patients receiving antiplatelet treatment after PCI (C allele vs. T allele: OR = 1.22, 95 % CI 1.04-1.43, P = 0.014; CT+CC vs. TT: OR = 1.38, 95 % CI 1.03-1.86, P = 0.029; CC vs. TT: OR = 1.45, 95 % CI 1.05-1.99, P = 0.024; respectively), especially among Asians. Furthermore, we found significantly positive correlations between the PON1 Q192R polymorphism and the incidence of stent thrombosis in patients receiving antiplatelet treatment after PCI (C allele vs. T allele: OR = 1.42, 95 % CI 1.08-1.87, P = 0.011; CT+CC vs. TT: OR = 1.93, 95 % CI 1.01-3.67, P = 0.046; CC vs. TT: OR = 2.18, 95 % CI 1.09-4.35, P = 0.027; respectively). Our meta-analysis of clinical cohort studies provides evidence that the PON1 Q192R polymorphism may increase the risk of MACE and stent thrombosis in patients receiving antiplatelet treatment after PCI.

Predicting fracture risk for elderly osteoporosis patients by hybrid machine learning model.

Background and Objective: Osteoporotic fractures significantly impact individuals's quality of life and exert substantial pressure on the social pension system. This study aims to develop prediction models for osteoporotic fracture and uncover potential risk factors based on Electronic Health Records (EHR). Methods: Data of patients with osteoporosis were extracted from the EHR of Xinhua Hospital (July 2012-October 2017). Demographic and clinical features were used to develop prediction models based on 12 independent machine learning (ML) algorithms and 3 hybrid ML models. To facilitate a nuanced interpretation of the results, a comprehensive importance score was conceived, incorporating various perspectives to effectively discern and mine critical features from the data. Results: A total of 8530 patients with osteoporosis were included for analysis, of which 1090 cases (12.8%) were fracture patients. The hybrid model that synergistically combines the Support Vector Machine (SVM) and XGBoost algorithms demonstrated the best predictive performance in terms of accuracy and precision (above 90%) among all benchmark models. Blood Calcium, Alkaline phosphatase (ALP), C-reactive Protein (CRP), Apolipoprotein A/B ratio and High-density lipoprotein cholesterol (HDL-C) were statistically found to be associated with osteoporotic fracture. Conclusions: The hybrid machine learning model can be a reliable tool for predicting the risk of fracture in patients with osteoporosis. It is expected to assist clinicians in identifying high-risk fracture patients and implementing early interventions.

Insights into spinal muscular atrophy from molecular biomarkers.

ABSTRACT: Spinal muscular atrophy is a devastating motor neuron disease characterized by severe cases of fatal muscle weakness. It is one of the most common genetic causes of mortality among infants aged less than 2 years. Biomarker research is currently receiving more attention, and new candidate biomarkers are constantly being discovered. This review initially discusses the evaluation methods commonly used in clinical practice while briefly outlining their respective pros and cons. We also describe recent advancements in research and the clinical significance of molecular biomarkers for spinal muscular atrophy, which are classified as either specific or non-specific biomarkers. This review provides new insights into the pathogenesis of spinal muscular atrophy, the mechanism of biomarkers in response to drug-modified therapies, the selection of biomarker candidates, and would promote the development of future research. Furthermore, the successful utilization of biomarkers may facilitate the implementation of gene-targeting treatments for patients with spinal muscular atrophy.

Podocyte injury of diabetic nephropathy: Novel mechanism discovery and therapeutic prospects.

Diabetic nephropathy (DN) is a severe complication of diabetes mellitus, posing significant challenges in terms of early prevention, clinical diagnosis, and treatment. Consequently, it has emerged as a major contributor to end-stage renal disease. The glomerular filtration barrier, composed of podocytes, endothelial cells, and the glomerular basement membrane, plays a vital role in maintaining renal function. Disruptions in podocyte function, including hypertrophy, shedding, reduced density, and apoptosis, can impair the integrity of the glomerular filtration barrier, resulting in elevated proteinuria, abnormal glomerular filtration rate, and increased creatinine levels. Hence, recent research has increasingly focused on the role of podocyte injury in DN, with a growing emphasis on exploring therapeutic interventions targeting podocyte injury. Studies have revealed that factors such as lipotoxicity, hemodynamic abnormalities, oxidative stress, mitochondrial dysfunction, and impaired autophagy can contribute to podocyte injury. This review aims to summarize the underlying mechanisms of podocyte injury in DN and provide an overview of the current research status regarding experimental drugs targeting podocyte injury in DN. The findings presented herein may offer potential therapeutic targets and strategies for the management of DN associated with podocyte injury.

Flower-like WSe2 used as bio-matrix in ultrasensitive label-free electrochemical immunosensor for human immunoglobulin G determination.

The abnormal concentrations of human immunoglobulin G (hIgG) refers to many kinds of diseases. Analytical methods with the characteristics of rapid response, easy operation and high sensitivity should be designed to accurately determinate the hIgG levels in human serum. In this work, a label-free electrochemical immunosensor based on WSe2/rGO was developed to sensitively detect human immunoglobulin G. First, the flower-like transition metal dichalcogenides (TMDCs) Tungsten Diselenide (WSe2) with large effective specific surface area and porous structure was synthesized by hydrothermal synthesis. As a bio-matrix, the flower-like WSe2 efficiently increased the active sites for loading antibodies. Meanwhile, reduced graphene oxide (rGO) obtained by tannic acid reduction was used to improve the current response of the sensing interface. WSe2 was combined with rGO and the electrochemical active surface area (ECSA) of the sensing interface was enlarged to 2.1 times that of GCE. Finally, the combination of flower-like WSe2 and rGO broadened the detection range and reduced the detection limit of the sensing platform. The immunosensor exhibited a high sensitivity with a wide linear range of 0.01-1000 ng/mL and low detection limit of 4.72 pg/mL. The real sample analysis of hIgG were conducted under optimal conditions, and the spiked recovery rates were between 95.5 and 104.1%. Moreover, satisfactory results were obtained by testing the stability, specificity and reproducibility of the immunosensor. Therefore, it can be concluded that the as-proposed immunosensor has the application potential of clinical analyze of hIgG in human serum.

Lomerizine attenuates LPS-induced acute lung injury by inhibiting the macrophage activation through reducing Ca2+ influx.

Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are life-threatening lung diseases with high mortality rates, predominantly attributable to acute and severe pulmonary inflammation. Lomerizine (LMZ) is a calcium channel blocker previously used in preventing and treating migraine. Here, we found that LMZ inhibited inflammatory responses and lung pathological injury by reducing pulmonary edema, neutrophil infiltration and pro-inflammatory cytokine production in lipopolysaccharide (LPS)-induced ALI mice. In vitro experiments, upon treating with LMZ, the expression of interleukin (IL)-1ß, IL-6 and tumor necrosis factor (TNF)-α was attenuated in macrophages. The phosphorylation of p38 MAPK, ERK1/2, JNK, and NF-κB p65 was inhibited after LMZ treatment. Furthermore, LPS-induced Ca2+ influx was reduced by treating with LMZ, which correlated with inhibition of pro-inflammatory cytokine production. And L-type Ca2+ channel agonist Bay K8644 (BK) could restore cytokine generation. In conclusion, our study demonstrated that LMZ alleviates LPS-induced ALI and is a potential agent for treating ALI/ARDS.

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis.

The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia, usage of diabetes drugs, changes in insulin levels, and excretion, and this risk begins as early as adolescence. Many factors including demographic data (such as age, height, weight, and gender), medical history (such as smoking, drinking, and menopause), and examination (such as bone mineral density, blood routine, and urine routine) may be related to bone metabolism in patients with diabetes. However, most of the existing methods are qualitative assessments and do not consider the interactions of the physiological factors of humans. In addition, the fracture risk of patients with diabetes and osteoporosis has not been further studied previously. In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fracture risk of patients with diabetes and osteoporosis, and investigate the effect of patients' physiological factors on fracture risk. A total of 147 raw input features are considered in our model. The presented model is compared with several benchmarks based on various metrics to prove its effectiveness. Moreover, the top 18 influencing factors of fracture risks of patients with diabetes are determined.

Evaluation of in vivo antibacterial drug efficacy using Caenorhabditis elegans infected with carbapenem-resistant Klebsiella pneumoniae as a model host.

Objective: This study was developed to assess the in vivo antimicrobial activity of specific drugs using a model system consisting of Caenorhabditis elegans (C. elegans) infected with Carbapenem-resistant Klebsiella pneumoniae (CRKP) in an effort to identify promising drugs for CRKP-infected patient treatment. Methods: A C. elegans-CRKP liquid assay platform was developed and used to conduct limited in vivo screening for antimicrobial agents with potential activity against CRKP. Time curves for 10 different concentrations of tested antimicrobial agents were tested in this model system at 0, 2, 6, 8, and 12 h after treatment. The protective effects of these different antimicrobial agents were compared at different time points. Furthermore, ten CRKP strains samples were isolated from clinical specimens to demonstrate the applicability of the nematode model method, and two typical clinical cases are presented. Results: CRKP bacteria were sufficient to induce C. elegans death in a dose- and time-dependent fashion, while effective antimicrobial agents improved the survival of these nematodes in a dose-dependent manner. Notably, PB and TGC exhibited robust antibacterial protection within 12 h even at low tested concentrations, and clear efficacy remained evident for high doses of CAZ at this same time point as mediators of improved nematode survival. The results of C. elegans model method were well consistent with that using the Kirby-Bauer method in 10 CRKP strains samples, and two typical clinical cases showed applicability, reliability and efficacy of C. elegans model method. Conclusion: Overall, nematode models in drug sensitivity testing have shown advantages in clinical settings. Our results highlight the value of C. elegans model systems as tools for the simultaneous screening of different agents for in vivo antibacterial efficacy and are deserved further study.

A specific identification platform based on biscuit-like bismuth nanosheets for label-free electrochemical immunosensor.

A label-free electrochemical immunosensor based on the biscuit-like bismuth nanosheets (BiNSs) and multi-wall carbon nanotubes-chitosan-gold nanoparticles (MWCNTs-Chit-AuNPs) was constructed for the detection of human immunoglobulin G (hIgG). The biscuit-like BiNSs prepared by one-step aqueous phase reduction method had a large electroactive surface area, 1.7 times that of bare glassy carbon electrode (GCE), which could load more antibodies and were used as a larger platform for the specific identification of antigens and antibodies. In addition, MWCNTs and AuNPs with good conductivity could be used to regulate the sensing interface, which promoted electron transfer greatly. Moreover, the AuNPs could stably anchor anti-hIgG by the affinity interaction between amine group of antibody and AuNPs, which greatly increased the number of anti-hIgG attached to the sensing platform. Under the optimal conditions, the proposed immunosensor exhibited excellent analytical performance for hIgG with a wide linear response of 0.01-1000 ng/mL and a low detection limit of 4.26 pg/mL. The electrochemical immunosensor exhibited favorable reproducibility, excellent specificity and high storage stability. Additionally, the immunosensor could be applied to determining hIgG in human serum samples as well. Considering these advantages, the electrochemical immunosensor has the potential application in clinical diagnosis.

Gandi Capsule Improved Podocyte Lipid Metabolism of Diabetic Nephropathy Mice through SIRT1/AMPK/HNF4A Pathway.

Podocyte lipid accumulation is a potential therapeutic target for diabetic nephropathy (DN). This study was aimed at clarifying the mechanism of Gandi capsule (GDC) ameliorating DN by regulating the lipid metabolism of podocytes. Network pharmacology methods were performed to screen the key molecules and potential targets of GDC for constructing the molecular-protein interaction network of GDC and conducting signal pathway enrichment analysis. GDC was predicted to ameliorate DN through SIRT1/AMPK/HNF4A pathway. Our results showed that GDC improved renal function in db/db mice. Besides, GDC exhibited effectiveness in relieving kidney tissue damage and renal lipid accumulation in db/db mice, and same effects were present in GDC-active ingredient baicalin. We further proved the new role of HNF4A in the lipid metabolism of DN mediated by SIRT1 and AMPK signaling pathways. The results suggested decreased expression of SIRT1 and p-AMPKα in the kidney tissue and increased expression of HNF4A of db/db mice compared with the control group. GDC and baicalin could reverse these expression changes. Furthermore, similar expression changes were observed in the murine podocyte cell line (MPC-5) treated with different concentrations of GDC and baicalin. Our research suggested that GDC and its active ingredient baicalin could alleviate the abnormal lipid metabolism in the kidney of db/db mice and might exert renal protection through the SIRT1/AMPK/HNF4A pathway.

Protective effects of baicalin in a Caenorhabditis elegans model of Parkinson's disease.

Parkinson's disease (PD) is a common neurodegenerative disorder of the central nervous system. However, the pathogenetic mechanisms of PD are far from understood. The aim of this study was to determine the protective effect of baicalin in a Caenorhabditis elegans model of PD. C. elegans worms were stimulated for 24 h with 6-hydroxydopamine (6-OHDA, 50 mM) and treated with or without baicalin (1, 10, or 100 µM). At all tested concentrations, baicalin improved the reversal and omega turn behavioral phenotypes, as well as the survival, of 6-OHDA-stimulated worms. It also inhibited 6-OHDA-induced oxidative stress by decreasing malondialdehyde levels, increasing superoxide dismutase, glutathione reductase, catalase, and glutathione levels and up-regulating mRNA expression of the antioxidant-related genes sod-1, sod-2, sod-3, daf-2, and daf-16. Additionally, it significantly decreased the expression of the apoptosis-related gene ced-3 and increased that of the anti-apoptosis-related gene ced-9. The expression levels of cleaved caspase-3 and B-cell lymphoma 2 in 6-OHDA-treated worms were reversed by baicalin. Apoptosis was suppressed by 6-OHDA in loss-of-function strains via the p38 mitogen-activated protein kinase (MAPK) signaling pathway. Furthermore, the apoptotic effects of 6-OHDA were blocked in sek-1 and pmk-1 mutants. Finally, the mRNA expression of sek-1 and pmk-1 and the protein expression of p38 MAPK and stress-activated protein kinase/extracellular signal-regulated kinase 1 were up-regulated by 6-OHDA and reversed by baicalin. Baicalin may protect against 6-OHDA injury by inhibiting apoptosis and decreasing oxidative stress through the p38 MAPK signaling pathway.

Active-Ingredient Screening and Synergistic Action Mechanism of Shegan Mixture for Anti-Asthma Effects Based on Network Pharmacology in a Mouse Model of Asthma.

BACKGROUND: Shegan Mixture (SGM) is a traditional Chinese medicine that has anti-inflammatory and therapeutic effects on asthma. However, its active ingredients and combined action mechanism have not been fully elucidated so far. The purpose of this study was to screen the effective ingredients and targets and elucidate the synergistic action mechanism of SGM in asthma mice using the network pharmacological approach. METHODS: A mouse model of asthma model was used in this study. Mice were orally administered SGM at three doses for 4 weeks and the effect of SGM on asthma was evaluated. The active ingredients and their targets of SGM were identified by searching databases, such as Traditional Chinese Medicine Systems Pharmacology Database (TCMSP). The main active ingredients were selected with parameters OB and DL. The synergistic action mechanisms of SGM in asthma were studied through key active ingredient-target interaction network and verified using surface plasmon resonance assay (SPR). RESULTS: SGM exerts anti-asthmatic effects by reducing lung tissue damage and inflammatory factors (IFN-γ, IL-4, IL-5, and IL-13) in asthmatic mice. Twenty ingredients and 45 related proteins were selected as potential nodes using enrichment analysis and network analysis. Inflammation and smooth muscle regulation-related pathways were considered to be the main pharmacological mechanisms of SGM in the treatment of asthma. Especially, 5 molecule-target pairs (including 3 ingredients and 4 proteins) were well docked with each other and the SPR assay revealed that glabridin-PTGS2 had good binding with 44.5 µM Kd value. CONCLUSION: SGM exerts the synergistic anti-asthma effects by virtue of reducing lung-tissue damage and inflammatory factors in asthmatic mice, which explains the theoretical basis for the traditional Chinese medicine, SGM, to treat asthma. Our study thus sheds light on a variety of options including Chinese medicine that could potentially be used in the clinical treatment of asthma.

An ensemble learning based framework to estimate warfarin maintenance dose with cross-over variables exploration on incomplete data set.

MOTIVATION: Warfarin is a widely used oral anticoagulant, but it is challenging to select the optimal maintenance dose due to its narrow therapeutic window and complex individual factor relationships. In recent years, machine learning techniques have been widely applied for warfarin dose prediction. However, the model performance always meets the upper limit due to the ignoration of exploring the variable interactions sufficiently. More importantly, there is no efficient way to resolve missing values when predicting the optimal warfarin maintenance dose. METHODS: Using an observational cohort from the Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, we propose a novel method for warfarin maintenance dose prediction, which is capable of assessing variable interactions and dealing with missing values naturally. Specifically, we examine single variables by univariate analysis initially, and only statistically significant variables are included. We then propose a novel feature engineering method on them to generate the cross-over variables automatically. Their impacts are evaluated by stepwise regression, and only the significant ones are selected. Lastly, we implement an ensemble learning based approach, LightGBM, to learn from incomplete data directly on the selected single and cross-over variables for dosing prediction. RESULTS: 377 unique patients with eligible and time-independent 1173 warfarin order events are included in this study. Through the comprehensive experimental results in 5-fold cross-validation, our proposed method demonstrates the efficiency of exploring the variable interactions and modeling on incomplete data. The R2 can achieve 75.0% on average. Moreover, the subgroup analysis results reveal that our method performs much better than other baseline methods, especially in the medium-dose and high-dose subgroups. Lastly, the IWPC dosing prediction model is used for further comparison, and our approach outperforms it by a significant margin. CONCLUSION: In summary, our proposed method is capable of exploring the variable interactions and learning from incomplete data directly for warfarin maintenance dose prediction, which has a great premise and is worthy of further research.

Prediction of vancomycin dose on high-dimensional data using machine learning techniques.

OBJECTIVES: Despite therapeutic vancomycin is regularly monitored, its dose requirements vary considerably between individuals. Various innovative vancomycin dosing strategies have been developed for dose optimization; however, the utilization of individual factors and extensibility is insufficient. We aimed to develop an optimal dosing algorithm for vancomycin based on the high-dimensional data using the proposed variable engineering and machine-learning methods. METHODS: This study proposed a variable engineering process that automatically generates second-order variable interactions. We performed an initial examination of independent variables and interactive variables using eXtreme Gradient Boosting. The vancomycin dose prediction model was established based on the derived variables. RESULTS: Based on the evaluation of the model performance in the validation cohort, our algorithm accounted for 67.5% of variations in the vancomycin doses. Subgroup analysis showed better performance in patients with medium and high body weight (with the ideal predictive percentage of 72.7% and 73.7%), and low and medium levels of serum creatinine (with the ideal predictive percentage of 77.8% and 73.1%) than in other groups. CONCLUSION: The new vancomycin dose prediction model is potentially useful for patients whose population profiles are similar to those of our patients and yielded desired reference of clinical indicators with specific breakpoints.

Roles of hypothalamic subgroup histamine and orexin neurons on behavioral responses to sleep deprivation induced by the treadmill method in adolescent rats.

Sleep deprivation induces several negative effects on behavior, emotion, attention, and learning ability. Sleep appears to be particularly important during adolescent brain development. In the present study, we examined the effects of sleep deprivation on behavior and hypothalamic neurotransmission including histamine and orexin neurons in adolescent rats using the treadmill method. Adolescent male rats were divided into three groups: treadmill sleep-deprived, treadmill control, and cage control groups. Energy expenditure, anxiety-like behavior, and locomotor activity were examined among the three groups. Histamine concentration in the cortex and diencephalon and the number of c-Fos-positive neurons in the hypothalamus were also examined. In addition, histamine and orexin neurons in the hypothalamus were simultaneously identified using rat histidine decarboxylase and orexin-A immunohistochemistry, respectively. Both energy expenditure and anxiety-related behavior significantly increased by the experimental 3-day sleep deprivation, while exploratory locomotor activity significantly decreased. Histamine contents did not change in the cortex, but significantly decreased in the diencephalon of sleep-deprived rats. Increased expression of c-Fos-positive neurons, including subgroup histamine and orexin neurons, was observed in the hypothalamus. These findings indicate that sleep deprivation increases energy expenditure and anxiety in adolescent rats and provide evidence for the pivotal role of hypothalamus subgroup histamine and orexin neurons in the behavioral response to sleep deprivation.

Ultraviolet light activates PMK-1/p38 MAPK signaling via MOM-4 and JKK-1 in Caenorhabditis elegans.

P38 mitogen-activated protein kinase (p38 MAPK) plays an important role in innate immunity and is activated by ultraviolet (UV) radiation. However, the molecular mechanism underlying UV stress remains unclear. In this study, we reported that UV activated PMK-1/p38 MAPK signaling via JKK-1 and MOM-4 in Caenorhabditis elegans. In C. elegans, different UV radiation doses resulted in PMK-1 phosphorylation. However, pmk-1 mutants failed to demonstrate an altered survival time in response to UV when compared with wild-type worms. Further analysis showed that JKK-1, but not SEK-1 mutants, displayed impaired PMK-1 activation following UV irradiation, suggesting that JKK-1 is the upstream MAP2K for the activation of PMK-1 in C. elegans under UV stimulation. UV-induced activation of PMK-1 was markedly reduced in MOM-4, but not in NSY-1 and DLK-1 mutant worms, suggesting that MOM-4 is the upstream MAP3K regulator of PMK-1 activation in response to UV stress in C. elegans. Additionally, daf-16 mutants displayed a shorter lifespan under UV stress, but UV-induced activation of PMK-1 was not markedly reduced in daf-16 and age-1 mutant worms. Our results revealed the signaling pathway involved in PMK-1 activation in C. elegans in response to UV radiation.

Lipopolysaccharide exposure induces oxidative damage in Caenorhabditis elegans: protective effects of carnosine.

BACKGROUND: The present study was designed to investigate the protective effects and mechanisms of carnosine on lipopolysaccharide (LPS)-induced injury in Caenorhabditis elegans. METHODS: C. elegans individuals were stimulated for 24 h with LPS (100 µg/mL), with or without carnosine (0.1, 1, 10 mM). The survival rates and behaviors were determined. The activities of superoxide dismutase (SOD), glutathione reductase (GR), and catalase (CAT) and levels of malondialdehyde (MDA) and glutathione (GSH) were determined using the respective kits. Reverse transcription polymerase chain reaction (RT-PCR) was performed to validate the differential expression of sod-1, sod-2, sod-3, daf-16, ced-3, ced-9, sek-1, and pmk-1. Western blotting was used to determine the levels of SEK1, p38 mitogen-activated protein kinase (MAPK), cleaved caspase3, and Bcl-2. C. elegans sek-1 (km2) mutants and pmk-1 (km25) mutants were used to elucidate the role of the p38 MAPK signaling pathway. RESULTS: Carnosine improved the survival of LPS-treated C. elegans and rescued behavioral phenotypes. It also restrained oxidative stress by decreasing MDA levels and increasing SOD, GR, CAT, and GSH levels. RT-PCR results showed that carnosine treatment of wild-type C. elegans up-regulated the mRNA expression of the antioxidant-related genes sod-1, sod-2, sod-3, and daf-16. The expression of the anti-apoptosis-related gene ced-9 and apoptosis-related gene ced-3 was reversed by carnosine. In addition, carnosine treatment significantly decreased cleaved caspase3 levels and increased Bcl-2 levels in LPS-treated C. elegans. Apoptosis in the loss-of-function strains of the p38 MAPK signaling pathway was suppressed under LPS stress; however, the apoptotic effects of LPS were blocked in the sek-1 and pmk-1 mutants. The expression levels of sek-1 and pmk-1 mRNAs were up-regulated by LPS and reversed by carnosine. Finally, the expression of p-p38MAPK and SEK1 was significantly increased by LPS, which was reversed by carnosine. CONCLUSION: Carnosine treatment protected against LPS injury by decreasing oxidative stress and inhibiting apoptosis through the p38 MAPK pathway.

Revealing active components, action targets and molecular mechanism of Gandi capsule for treating diabetic nephropathy based on network pharmacology strategy.

BACKGROUND: Gandi capsule is a traditional Chinese herbal formula used to promote blood circulation and removing blood stasis in clinical. Our previous study has shown that it reduces proteinuria with routine treatment in diabetic nephrophy (DN), but its pharmacological action mechanism is still unknown. METHODS: To facilitate the identification of components, a component database of Gandi capsule and target database of DN were established by ourselves. The components absorbed in blood circle were identified in rat plasma after oral administration of Gandi capsule by UHPLC-QQQ-MS/MS. The potential targets were screened by using Libdock tolls in Discovery studio 3.0. Then Pathway and Network analyses were used to enrich the screened targets. The possible targets were verified by using a surface plasmon resonance (SPR) test and the molecular mechanism focusing these targets for treating DN was clarified by western blot. RESULTS: Six components in Gandi capsule were identified detected in rat plasma after oral administration by UHPLC-QQQ-MS/MS. After molecular docking analyses in KEGG and Discovery studio, four protein targets including HNF4A, HMGCR, JAK3, and SIRT1, were screened out, and proved as effective binding with baicalin, wogonoside by SPR. And the molecular mechanism was clarified that baicalin and wogonoside inhibit the effect of high glucose (HG)-induced decreased cell viability and podocin expression, and strengthen the activation p-AKT, p-PI3K, and p-AMPK. CONCLUSION: Baicalin and wogonoside were screened out to be the active compounds in Gandi capsule and can ameliorate HG-induced podocyte damage by influencing the AMPK and PI3K-AKT signaling pathways by binding with HNF4A, HMGCR, JAK3, and SIRT1.

Intraocular pharmacokinetics of anti-vascular endothelial growth factor agents by intraoperative subretinal versus intravitreal injection in silicone oil-filled eyes of proliferative diabetic retinopathy: a randomized controlled pilot study.

PURPOSE: Intraoperative subretinal anti-vascular endothelial growth factor (VEGF) injections have been used clinically in some case, but the pharmacokinetic characteristics have not yet been determined. In this pilot study, we investigate the pharmacokinetic parameters of anti-VEGF agents by intraoperative subretinal or intravitreal injection in silicone oil (SiO)-filled eyes of patients with proliferative diabetic retinopathy (PDR). METHODS: Randomized controlled trial including 13 patients (16 eyes) with PDR underwent pars plana vitrectomy (PPV) with SiO tamponade and randomly received a subretinal (8 eyes) or intravitreal (8 eyes) conbercept injection (0.5 mg/0.05 ml) intraoperatively. Aqueous humour (AH) was obtained on the 1st, 3rd, 7th, 10th, 14th, 21st and 28th day after the injection. Drug concentrations in the AH were determined by enzyme-linked immunosorbent assay (ELISA). The last best-corrected visual acuity (BCVA) was examined 6 months postoperatively. RESULTS: The clearance rate of anti-VEGF agents by subretinal injection was reduced in vitrectomized eyes with SiO tamponade (p < 0.05). With the same drug dose, subretinal injection (5.49 ± 6.11 µg/ml) resulted in higher drug concentrations in the AH when compared with intravitreal injection (0.42 ± 0.46 µg/ml, p = 0.001) 4 weeks after the treatment. The mean residence time last (MRT0-t ) by subretinal injection (11.57 ± 0.83 days) was significantly longer than the mean MRT0-t by intravitreal injection (7.10 ± 1.00 days, p < 0.001). A self-paired analysis showed that subretinal injection led to the BCVA improvement by +28.59 letters 6 months postoperatively (p = 0.028) while the BCVA did not improve significantly by intravitreal injection (p = 0.715). CONCLUSIONS: The drug maintenance phase was prolonged by intraoperative subretinal injection in SiO-filled eyes of PDR. The results suggest that subretinal injection might be a valuable treatment option for the management of PDR.