[Chaihu Sanshen Capsules protect rats from myocardial ischemia reperfusion injury via PKCßâ ¡/NOX2/ROS signaling pathway].

This study aims to explore the pathogenesis of myocardial ischaemia reperfusion injury(MIRI) based on oxidative stress-mediated programmed cell death and the mechanism and targets of Chaihu Sanshen Capsules in treating MIRI via the protein kinase Cß(PKCßⅡ)/NADPH oxidase 2(NOX2)/reactive oxygen species(ROS) signaling pathway. The rat model of MIRI was established by the ligation of the left anterior descending branch. Rats were randomized into 6 groups: sham group, model group, clinically equivalent-, high-dose Chaihu Sanshen Capsules groups, N-acetylcysteine group, and CGP53353 group. After drug administration for 7 consecutive days, the area of myocardial infarction in each group was measured. The pathological morphology of the myocardial tissue was observed by hematoxylin-eosin(HE) staining. The apoptosis in the myocardial tissue was observed by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling(TUNEL). Enzyme-linked immunosorbent assay(ELISA) was employed to measure the le-vels of indicators of myocardial injury and oxidative stress. The level of ROS was detected by flow cytometry. The protein and mRNA levels of the related proteins in the myocardial tissue were determined by Western blot and real-time quantitative PCR(RT-qPCR), respectively. Compared with the sham group, the model group showed obvious myocardial infarction, myocardial structural disorders, interstitial edema and hemorrhage, presence of a large number of vacuoles, elevated levels of myocardial injury markers, myocardial apoptosis, ROS, and malondialdehyde(MDA), lowered superoxide dismutase(SOD) level, and up-regulated protein and mRNA le-vels of PKCßⅡ, NOX2, cysteinyl aspartate specific proteinase-3(caspase-3), and acyl-CoA synthetase long-chain family member 4(ACSL4) in the myocardial tissue. Compared with the model group, Chaihu Sanshen Capsules reduced the area of myocardial infarction, alleviated the pathological changes in the myocardial tissue, lowered the levels of myocardial injury and oxidative stress indicators and apoptosis, and down-regulated the mRNA and protein levels of PKCßⅡ, NOX2, caspase-3, and ACSL4 in the myocardial tissue. Chaihu Sanshen Capsules can inhibit oxidative stress and programmed cell death(apoptosis, ferroptosis) by regulating the PKCßⅡ/NOX2/ROS signaling pathway, thus mitigating myocardial ischemia reperfusion injury.

Patient-derived organoids of lung cancer based on organoids-on-a-chip: enhancing clinical and translational applications.

Lung cancer is one of the most common malignant tumors worldwide, with high morbidity and mortality due to significant individual characteristics and genetic heterogeneity. Personalized treatment is necessary to improve the overall survival rate of the patients. In recent years, the development of patient-derived organoids (PDOs) enables lung cancer diseases to be simulated in the real world, and closely reflects the pathophysiological characteristics of natural tumor occurrence and metastasis, highlighting their great potential in biomedical applications, translational medicine, and personalized treatment. However, the inherent defects of traditional organoids, such as poor stability, the tumor microenvironment with simple components and low throughput, limit their further clinical transformation and applications. In this review, we summarized the developments and applications of lung cancer PDOs and discussed the limitations of traditional PDOs in clinical transformation. Herein, we looked into the future and proposed that organoids-on-a-chip based on microfluidic technology are advantageous for personalized drug screening. In addition, combined with recent advances in lung cancer research, we explored the translational value and future development direction of organoids-on-a-chip in the precision treatment of lung cancer.

Predictive modeling the probability of suffering from metabolic syndrome using machine learning: A population-based study.

Background: There is an increasing trend of Metabolic syndrome (MetS) prevalence, which has been considered as an important contributor for cardiovascular disease (CVD), cancers and diabetes. However, there is often a long asymptomatic phase of MetS, resulting in not diagnosed and intervened so timely as needed. It would be very helpful to explore tools to predict the probability of suffering from MetS in daily life or routinely clinical practice. Objective: To develop models that predict individuals' probability of suffering from MetS timely with high efficacy in general population. Methods: The present study enrolled 8964 individuals aged 40-75 years without severe diseases, which was a part of the REACTION study from October 2011 to February 2012. We developed three prediction models for different scenarios in hospital (Model 1, 2) or at home (Model 3) based on LightGBM (LGBM) technique and corresponding logistic regression (LR) models were also constructed for comparison. Model 1 included variables of laboratory tests, lifestyles and anthropometric measurements while model 2 was built with components of MetS excluded based on model 1, and model 3 was constructed with blood biochemical indexes removed based on model 2. Additionally, we also investigated the strength of association between the predictive factors and MetS, as well as that between the predictors and each component of MetS. Results: In this study, 2714 (30.3%) participants suffer from MetS accordingly. The performances of the LGBM models in predicting the probability of suffering from MetS produced good results and were presented as follows: model 1 had an area under the curve (AUC) value of 0.993 while model 2 indicated an AUC value of 0.885. Model 3 had an AUC value of 0.859, which is close to that of model 2. The AUC values of LR model 1 and 2 for the scenario in hospital and model 3 at home were 0.938, 0.839 and 0.820 respectively, which seemed lower than that of their corresponding machine learning models, respectively. In both LGBM and logistic models, gender, height and resting pulse rate (RPR) were predictors for MetS. Women had higher risk of MetS than men (OR 8.84, CI: 6.70-11.66), and each 1-cm increase in height indicated 3.8% higher risk of suffering from MetS in people over 58 years, whereas each 1- Beat Per Minute (bpm) increase in RPR showed 1.0% higher risk in individuals younger than 62 years. Conclusion: The present study showed that the prediction models developed by machine learning demonstrated effective in evaluating the probability of suffering from MetS, and presented prominent predicting efficacies and accuracies. Additionally, we found that women showed a higher risk of MetS than men, and height in individuals over 58 years was important factor in predicting the probability of suffering from MetS while RPR was of vital importance in people aged 40-62 years.

Regulation of opticin on bioactivity of retinal vascular endothelial cells cultured in collagen.

AIM: To investigate the effects of collagen and opticin on the bioactivity of human retinal vascular endothelial cells (hRVECs), and explore its regulations by integrins and RhoA/ROCK1 signal pathway. METHODS: hRVECs were cultured in collagen and treated by opticin, and cell-based bioactivity assays of cell proliferation, migration, and adhesion were performed. The expression of integrin α2, integrin ß1, RhoA and ROCK1 were examined with real-time PCR and Western blotting. RESULTS: Collagen could promote cell viability of proliferation and migration (all P<0.05), and enhance the mRNA expression of integrin α2, integrin ß1, RhoA and ROCK1 (all P<0.05). Opticin could inhibit proliferation and migration ability of hRVECs cultured in collagen, and reduce the mRNA expression of integrin α2, integrin ß1, RhoA and ROCK1 (all P<0.05). CONCLUSION: Collagen and opticin can affect bioactivity of hRVECs, which may be regulated by α2-, ß1-integrins and RhoA/ROCK1 signal pathway.

Effect of dietary phosphorus levels on meat quality and lipid metabolism in broiler chickens.

To analyze the influence of dietary phosphorus (P) levels on meat quality and lipid metabolism, a 42-day feeding experiment (P deficient group; normal group; high P level groups of H1 and H2, respectively) using 100 one-day-old broilers was conducted. Results demonstrated that the quality of broiler chicken meat in deficient or high P groups decreased relative to the normal group. High P diets resulted in increased lightness, redness values, shear forces and decreased fatty acid contents and intramuscular fat content in breast meat (p<0.01). Compared with normal group, lower malic enzyme activity, higher fatty acid synthase and AMP-activated protein kinase activities were observed in the treatment groups (p<0.05). Chickens fed with normal diets had the lowest serum total cholesterol and triglyceride levels which differed from that of other treatments (p<0.05). High-P diets significantly decreased the lipid accumulation in the liver (p<0.01), whereas phosphorus levels in breast meat increased significantly (p<0.01). It can be concluded that deficient or higher P levels could affect meat quality and expression of indicators on lipid metabolism of broiler chickens.

[Research on Accuracy and Stability of Inversing Vegetation Chlorophyll Content by Spectral Index Method].

Spectral index method was widely applied to the inversion of crop chlorophyll content. In the present study, PSR3500 spectrometer and SPAD-502 chlorophyll fluorometer were used to acquire the spectrum and relative chlorophyll content (SPAD value) of winter wheat leaves on May 2nd 2013 when it was at the jointing stage of winter wheat. Then the measured spectra were resampled to simulate TM multispectral data and Hyperion hyperspectral data respectively, using the Gaussian spectral response function. We chose four typical spectral indices including normalized difference vegetation index (NDVD, triangle vegetation index (TVI), the ratio of modified transformed chlorophyll absorption ratio index (MCARI) to optimized soil adjusted vegetation index (OSAVI) (MCARI/OSAVI) and vegetation index based on universal pattern decomposition (VIUPD), which were constructed with the feature bands sensitive to the vegetation chlorophyll. After calculating these spectral indices based on the resampling TM and Hyperion data, the regression equation between spectral indices and chlorophyll content was established. For TM, the result indicates that VIUPD has the best correlation with chlorophyll (R2 = 0.819 7) followed by NDVI (R2 = 0.791 8), while MCARI/OSAVI and TVI also show a good correlation with R2 higher than 0.5. For the simulated Hyperion data, VIUPD again ranks first with R2 = 0.817 1, followed by MCARI/OSAVI (R2 = 0.658 6), while NDVI and TVI show very low values with R2 less than 0.2. It was demonstrated that VIUPD has the best accuracy and stability to estimate chlorophyll of winter wheat whether using simulated TM data or Hyperion data, which reaffirms that VIUPD is comparatively sensor independent. The chlorophyll estimation accuracy and stability of MCARI/OSAVI also works well, partly because OSAVI could reduce the influence of backgrounds. Two broadband spectral indices NDVI and TVI are weak for the chlorophyll estimation of simulated Hyperion data mainly because of their dependence on few bands and the strong influence of atmosphere, solar altitude, viewing angle of sensor, background and so on. In conclusion, the stability and consistency of chlorophyll estimation is equally important to the estimation accuracy by spectral index method. VIUPD introduced in the study has the best performance to estimate winter wheat chlorophyll, which illustrates its potential ability in the area of estimating vegetation biochemical parameters.