High glucose induces vascular endothelial growth factor production in human synovial fibroblasts through reactive oxygen species generation

Background

Diabetes is an independent risk factor of osteoarthritis (OA). Angiogenesis is essential for the progression of OA. Here, we investigated the intracellular signaling pathways involved in high glucose (HG)-induced vascular endothelial growth factor (VEGF) expression in human synovial fibroblast cells.

Methods

HG-mediated VEGF expression was assessed with qPCR and ELISA. The mechanisms of action of HG in different signaling pathways were studied using Western blotting. Knockdown of proteins was achieved by transfection with siRNA. Chromatin immunoprecipitation assays were used to study in vivo binding of c-Jun to the VEGF promoter.

Results

Stimulation of OA synovial fibroblasts (OASF) with HG induced concentration- and time-dependent increases in VEGF expression. Treatment of OASF with HG increased reactive oxygen species (ROS) generation. Pretreatment with NADPH oxidase inhibitor (APO or DPI), ROS scavenger (NAC), PI3K inhibitor (Ly294002 or wortmannin), Akt inhibitor, or AP-1 inhibitor (curcumin or tanshinone IIA) blocked the HG-induced VEGF production. HG also increased PI3K and Akt activation. Treatment of OASF with HG increased the accumulation of phosphorylated c-Jun in the nucleus, AP-1-luciferase activity, and c-Jun binding to the AP-1 element on the VEGF promoter.

Conclusions

Our results suggest that the HG increases VEGF expression in human synovial fibroblasts via the ROS, PI3K, Akt, c-Jun and AP-1 signaling pathway.

General significance

We link high glucose on VEGF expression in osteoarthritis.     

TGF-β1 Regulation of Estrogen Production in Mature Rat Leydig Cells

Background

Besides androgens, estrogens produced in Leydig cells are also crucial for mammalian germ cell differentiation. Transforming growth factor-β1 (TGF-β1) is now known to have multiple effects on regulation of Leydig cell function. The objective of the present study is to determine whether TGF-β1 regulates estradiol (E₂) synthesis in adult rat Leydig cells and then to assess the impact of TGF-β1 on Cx43-based gap junctional intercellular communication (GJIC) between Leydig cells.

Methodology/Principal Findings

Primary cultured Leydig cells were incubated in the presence of recombinant TGF-β1 and the production of E₂ as well as testosterone (T) were measured by RIA. The activity of P450arom was addressed by the tritiated water release assay and the expression of Cyp19 gene was evaluated by Western blotting and real time RT-PCR. The expression of Cx43 and GJIC were investigated with immunofluorescence and fluorescence recovery after photo-bleaching (FRAP), respectively. Results from this study show that TGF-β1 down-regulates the level of E₂ secretion and the activity of P450arom in a dose-dependent manner in adult Leydig cells. In addition, the expression of Cx43 and GJIC was closely related to the regulation of E₂ and TGF-β1, and E₂ treatment in turn restored the inhibition of TGF-β1 on GJIC.

Conclusions

Our results indicate, for the first time in adult rat Leydig cells, that TGF-β1 suppresses P450arom activity, as well as the expression of the Cyp19 gene, and that depression of E₂ secretion leads to down-regulation of Cx43-based GJIC between Leydig cells.     

Diversity of the Photoreceptors and Spectral Opponency in the Compound Eye of the Golden Birdwing,Troides aeacus formosanus

The compound eye of the Golden Birdwing, Troides aeacus formosanus (Papilionidae, Lepidoptera), is furnished with three types of ommatidia, which are clearly different in pigmentation around the rhabdom. Each ommatidium contains nine photoreceptors, whose spectral sensitivities were analyzed electrophysiologically. We identified nine spectral types of photoreceptor with sensitivities peaking at 360 nm (UV), 390 nm (V), 440 nm (B), 510 nm (BG), 540 nm (sG), 550 nm (dG), 580 nm (O), 610 nm (R), and 630 nm (dR) respectively. The spectral sensitivities of the V, O, R and dR receptors did not match the predicted spectra of any visual pigments, but with the filtering effects of the pigments around the rhabdom, they can be reasonably explained. In some of the receptors, negative-going responses were observed when they were stimulated at certain wavelengths, indicating antagonistic interactions between photoreceptors.     

Protein Phosphatase 2A Catalytic Subunit α Plays a MyD88-Dependent,Central Role in the Gene-Specific Regulation of Endotoxin Tolerance

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Highlights? PP2Ac is constitutively activated and targets MyD88 in LPS-tolerized macrophages ? Constitutively active PP2Ac shifts a proinflammatory MyD88 to its prosurvival mode ? Constitutively active PP2Ac reprograms gene-specific chromatin modification landscape ? Constitutively active PP2Ac broadly defines ET at both signaling and epigenetic levels     

Recent progresses in the application of machine learning approach for predicting protein functional class independent of sequence similarity

Protein sequence contains clues to its function. Functional prediction from sequence presents a challenge particularly for proteins that have low or no sequence similarity to proteins of known function. Recently, machine learning methods have been explored for predicting functional class of proteins from sequence-derived properties independent of sequence similarity, which showed promising potential for low- and non-homologous proteins. These methods can thus be explored as potential tools to complement alignment- and clustering-based methods for predicting protein function. This article reviews the strategies, current progresses, and underlying difficulties in using machine learning methods for predicting the functional class of proteins. The relevant software and web-servers are described. The reported prediction performances in the application of these methods are also presented, which need to be interpreted with caution as they are dependent on such factors as datasets used and choice of parameters.     

Antifungal Susceptibility Testing of <Emphasis Type="Italic">Candida</Emphasis> and <Emphasis Type="Italic">Cryptococcus</Emphasis> Species and Mechanisms of Resistance: Implications for Clinical Laboratories

Purpose of Review

Resistance to antifungal drugs amongst Candida species is a growing concern, and azole resistance may be emerging in Cryptococcus species. This review provides a contemporary perspective, relevant to the clinical mycology laboratory, of antifungal susceptibility testing of these fungi, focussing on the challenges of phenotypic and genotypic methodologies to detect drug resistance.

Recent Findings

Standardised CLSI and EUCAST broth microdilution (BMD) susceptibility testing methods are the benchmark to determine clinical breakpoints (CBPs) and/or epidemiological cut-off values (ECVs) MICs for Candida and Cryptococcus spp. Commercial methods may be used but caution is required when employing BMD CBPs/ECVs to interpret results. Species-specific CBPs/ECVs for Candida spp. generally correlate well with predicting likelihood of therapeutic failure or of presence of a drug resistance mechanism with the exception of the echinocandins where the presence of specific FKS gene mutations and not the MIC correlates most accurately with clinical outcome. The relationship of presence of one or more mechanisms of azole resistance and drug MICs is uncertain. Next generation sequencing technology is offering insights into the relationships between susceptibility results obtained by phenotypic and genotypic methods. For Cryptococcus spp., CBPs are not established but species- and genetic type-specific EVCs are useful for guiding therapy where clinically indicated. Isolates of genotype VGII appear to exhibit the highest MICs.

Summary

Antifungal susceptibility testing of yeasts is important to detect drug resistance. For Candida spp., MICs have clinical utility for the azoles but detecting echinocandin resistance by genotypic methods is preferred. For Cryptococcus spp., ECVs are useful in guiding therapy.

     

Predictive power of splenic thickness for post-hepatectomy liver failure in HBV-associated hepatocellular carcinoma patients

Background

The purpose of this case series is to investigate the relationship between splenic thickness (ST) and postoperative outcomes after hepatic resection in hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC) patients.

Methods

The clinical data of 320 patients with HBV-associated HCC who had undergone liver resection were retrospectively analyzed. The value of ST in predicting postoperative outcomes was evaluated.

Results

A total of 320 patients were enrolled in the study. An increase in ST was significantly associated with an increase in portal vein diameter (PVD), indocyanine green retention rate 15 min (ICG R15), and total bilirubin (TBIL); however, it was negatively correlated with platelet count (PLT). Post-hepatectomy liver failure (PHLF) occurred in 35 (10.9%) patients. Multivariate logistic regression analysis showed that ST was an independent predictor of morbidity and mortality after hepatectomy. Meanwhile, ST was associated with an almost sixfold increased risk for developing perioperative complications (OR 5.678; 95% CI 2.873 to 11.224; P?<?0.001) and almost 13-fold increased risk for mortality after hepatectomy (OR 13.007; 95% CI 1.238 to 136.627; P?=?0.033).The area under the receiver operating characteristic (ROC) curve (AUC) of ST for predicting the incidence of PHLF was 0.754 (95% confidence interval (CI) 0.667 to 0.841; P?<?0.001), with a sensitivity of 57.1% and a specificity of 82.5%, which were significantly greater than those of the ICG R15 level (AUC 0.670; 95% CI 0.560 to 0.779; P?<?0.001). The critical value of ST was 43.5 mm.

Conclusions

ST, which is an easy, inexpensive, and routinely available perioperative marker, showed a favorable predictive value for postoperative outcomes in HBV-associated HCC patients.

     

CT Permeability Imaging Predicts Clinical Outcomes in Acute Ischemic Stroke Patients Treated with Intra-arterial Thrombolytic Therapy

In this study, we determined whether a prediction of final infarct volume (FIV) and clinical outcomes in patients with an acute stroke is improved by using a contrast transfer coefficient (K ^trans) as a biomarker for blood–brain barrier (BBB) dysfunction. Here, consecutive patients admitted with signs and symptoms suggesting acute hemispheric stroke were included in this study. Ninety-eight participants with intra-arterial therapy were assessed (46 female). Definition of predicted FIV was performed using conventional perfusion CT (PCT-PIV) parameters alone and in combination with K ^trans (K ^trans-PIV). Multiple logistic regression analyses and linear regression modeling were conducted to determine independent predictors of the 90-day modified Rankin score (mRS) and FIV, respectively. We found that patients with favorable outcomes were younger and had lower National Institutes of Health Stroke Scale (NIHSS) score, smaller PCT-PIV, K ^trans-PIV, and smaller FIV (P?<?0.001). K ^trans-PIV showed good correlation with FIV (P?<?00.001, R ²?=?0.6997). In the regression analyses, K ^trans-PIV was the best predictor of clinical outcomes (P?=?0.009, odds ratio (OR)?=?1.960) and also the best predictor for FIV (F?=?75.590, P?<?0.0001). In conclusion, combining PCT and K ^trans maps derived from first-pass PCT can identify at-risk cerebral ischemic tissue more precisely than perfusion parameters alone. This provides improved accuracy in predicting FIV and clinical outcomes.