Elevated Plasma SPARC Levels Are Associated with Insulin Resistance,Dyslipidemia, and Inflammation in Gestational Diabetes Mellitus

Objective

Recent studies suggested that secreted protein acidic and rich in cysteine (SPARC), a novel adipokine, is a key player in the pathology of obesity and type 2 diabetes. We aimed to determine whether concentrations of SPARC were altered in patients with gestational diabetes mellitus (GDM) compared to normal glucose tolerance (NGT) controls and to investigate the relationships between SPARC and metabolic parameters in pregnant women.

Design/Methods

Cross-sectional study of 120 pregnant women with GDM and 60 controls with NGT, in a university hospital setting. Plasma levels of SPARC, adiponectin, fibroblast growth factor 21 (FGF21), insulin and proinsulin were determined by ELISA.

Results

GDM women had higher SPARC and lower adiponectin than NGT subjects; no difference was found in FGF21. SPARC levels were the lowest in subjects in the third tertile of insulin sensitivity index (ISI_OGTT) and correlated positively with pre-pregnant BMI, insulin and 3 h glucose during 100-g OGTT, HOMA-IR, fasting proinsulin, hsCRP and white blood cells count, and negatively with ISI_OGTT, when adjusting for gestational age. Triglyceride (TG), Apolipoprotein A1, apolipoprotein B and lipoprotein (a) correlated with SPARC in partial Pearson correlation. Correlations between SPARC with adiponectin, systolic blood pressure and TG were marginally significant in partial Spearman correlation analysis. In multivariate regression analysis, SPARC was an independent negative indicator of ISI_OGTT.

Conclusions

SPARC levels are correlated significantly with inflammation and may also be correlated with dyslipidemia and represent an independent determinant of insulin resistance in late pregnancy, indicating a potential role of SPARC in the pathophysiology of GDM.     

Determination of an Optimal Standardized Uptake Value of Fluorodeoxyglucose for Positron Emission Tomography Imaging to Assess Pathological Volumes of Cervical Cancer: A Prospective Study

Purpose

To determine the optimal standardized uptake value (SUV) of ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) for positron emission tomography (PET) imaging, at which the PET-defined gross tumor volume (GTV_PET) best matches with the pathological volume (GTV_PATH) in the cervical cancer.

Materials and Methods

Ten patients with the cervical cancer who underwent surgery were enrolled in this study. The excised specimens were processed for whole-mount serial sections and H-E staining. The tumor borders were outlined in sections under a microscope, histopathological images were scanned and the GTV_PATH calculated. The GTV_PET was delineated automatically by using various percentages relative to the maximal SUV and absolute SUV. The optimal threshold SUV was further obtained as the value at which the GTV_PET best matched with the GTV_PATH.

Results

An average of 85±10% shrinkage of tissue was observed after the formalin fixation. The GTV_PATH was 13.38±2.80 cm³ on average. The optimal threshold on percentile SUV and absolute SUV were 40.50%±3.16% and 7.45±1.10, respectively. The correlation analysis showed that the optimal percentile SUV threshold was inversely correlated with GTV_PATH (p<0.05) and tumor diameter (p<0.05). The absolute SUV was also positively correlated with SUV_max (p<0.05).

Conclusion

The pathological volume could provide the more accurate tumor volume. The optimal SUV of FDG for PET imaging by use of GTV_PATH as standard for cervical cancer target volume delineation was thus determined in this study, and more cases are being evaluated to substantiate this conclusion.     

Targeting the Non-structural Protein 1 from Dengue Virus to a Dendritic Cell Population Confers Protective Immunity to Lethal Virus Challenge

Dengue is the most prevalent arboviral infection, affecting millions of people every year. Attempts to control such infection are being made, and the development of a vaccine is a World Health Organization priority. Among the proteins being tested as vaccine candidates in preclinical settings is the non-structural protein 1 (NS1). In the present study, we tested the immune responses generated by targeting the NS1 protein to two different dendritic cell populations. Dendritic cells (DCs) are important antigen presenting cells, and targeting proteins to maturing DCs has proved to be an efficient means of immunization. Antigen targeting is accomplished by the use of a monoclonal antibody (mAb) directed against a DC cell surface receptor fused to the protein of interest. We used two mAbs (αDEC205 and αDCIR2) to target two distinct DC populations, expressing either DEC205 or DCIR2 endocytic receptors, respectively, in mice. The fusion mAbs were successfully produced, bound to their respective receptors, and were used to immunize BALB/c mice in the presence of polyriboinosinic: polyribocytidylic acid (poly (I:C)), as a DC maturation stimulus. We observed induction of strong anti-NS1 antibody responses and similar antigen binding affinity irrespectively of the DC population targeted. Nevertheless, the IgG1/IgG2a ratios were different between mouse groups immunized with αDEC-NS1 and αDCIR2-NS1 mAbs. When we tested the induction of cellular immune responses, the number of IFN-γ producing cells was higher in αDEC-NS1 immunized animals. In addition, mice immunized with the αDEC-NS1 mAb were significantly protected from a lethal intracranial challenge with the DENV2 NGC strain when compared to mice immunized with αDCIR2-NS1 mAb. Protection was partially mediated by CD4⁺ and CD8⁺ T cells as depletion of these populations reduced both survival and morbidity signs. We conclude that targeting the NS1 protein to the DEC205⁺ DC population with poly (I:C) opens perspectives for dengue vaccine development.     

Serum Metabolome and Lipidome Changes in Adult Patients with Primary Dengue Infection

Background

Dengue virus (DENV) is the most widespread arbovirus with an estimated 100 million infections occurring every year. Endemic in the tropical and subtropical areas of the world, dengue fever/dengue hemorrhagic fever (DF/DHF) is emerging as a major public health concern. The complex array of concurrent host physiologic changes has hampered a complete understanding of underlying molecular mechanisms of dengue pathogenesis.

Methodology/Principle Findings

Systems level characterization of serum metabolome and lipidome of adult DF patients at early febrile, defervescence, and convalescent stages of DENV infection was performed using liquid chromatography- and gas chromatography-mass spectrometry. The tractability of following metabolite and lipid changes in a relatively large sample size (n = 44) across three prominent infection stages allowed the identification of critical physiologic changes that coincided with the different stages. Sixty differential metabolites were identified in our metabolomics analysis and the main metabolite classes were free fatty acids, acylcarnitines, phospholipids, and amino acids. Major perturbed metabolic pathways included fatty acid biosynthesis and β-oxidation, phospholipid catabolism, steroid hormone pathway, etc., suggesting the multifactorial nature of human host responses. Analysis of phospholipids and sphingolipids verified the temporal trends and revealed association with lymphocytes and platelets numbers. These metabolites were significantly perturbed during the early stages, and normalized to control levels at convalescent stage, suggesting their potential utility as prognostic markers.

Conclusions/Significance

DENV infection causes temporally distinct serum metabolome and lipidome changes, and many of the differential metabolites are involved in acute inflammatory responses. Our global analyses revealed early anti-inflammatory responses working in concert to modulate early pro-inflammatory processes, thus preventing the host from development of pathologies by excessive or prolonged inflammation. This study is the first example of how an omic- approach can divulge the extensive, concurrent, and dynamic host responses elicited by DENV and offers plausible physiological insights to why DF is self limiting.     

Uremic Pruritus,Dialysis Adequacy,and Metabolic Profiles in Hemodialysis Patients: A Prospective 5-Year Cohort Study

Background

Uremic pruritus is a common and intractable symptom in patients on chronic hemodialysis, but factors associated with the severity of pruritus remain unclear. This study aimed to explore the associations of metabolic factors and dialysis adequacy with the aggravation of pruritus.

Methods

We conducted a 5-year prospective cohort study on patients with maintenance hemodialysis. A visual analogue scale (VAS) was used to assess the intensity of pruritus. Patient demographic and clinical characteristics, laboratory parameters, dialysis adequacy (assessed by Kt/V), and pruritus intensity were recorded at baseline and follow-up. Change score analysis of the difference score of VAS between baseline and follow-up was performed using multiple linear regression models. The optimal threshold of Kt/V, which is associated with the aggravation of uremic pruritus, was determined by generalized additive models and receiver operating characteristic analysis.

Results

A total of 111 patients completed the study. Linear regression analysis showed that lower Kt/V and use of low-flux dialyzer were significantly associated with the aggravation of pruritus after adjusting for the baseline pruritus intensity and a variety of confounding factors. The optimal threshold value of Kt/V for pruritus was 1.5 suggested by both generalized additive models and receiver operating characteristic analysis.

Conclusions

Hemodialysis with the target of Kt/V ≥1.5 and use of high-flux dialyzer may reduce the intensity of pruritus in patients on chronic hemodialysis. Further clinical trials are required to determine the optimal dialysis dose and regimen for uremic pruritus.     

Model-Based Assessment of Estuary Ecosystem Health Using the Latent Health Factor Index,with Application to the Richibucto Estuary

The ability to quantitatively assess ecological health is of great interest to those tasked with monitoring and conserving ecosystems. For decades, biomonitoring research and policies have relied on multimetric health indices of various forms. Although indices are numbers, many are constructed based on qualitative procedures, thus limiting the quantitative rigor of the practical interpretations of such indices. The statistical modeling approach to construct the latent health factor index (LHFI) was recently developed. With ecological data that otherwise are used to construct conventional multimetric indices, the LHFI framework expresses such data in a rigorous quantitative model, integrating qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modeling approach allows unified statistical inference of health for observed sites (along with prediction of health for partially observed sites, if desired) and of the relevance of ecological drivers, all accompanied by formal uncertainty statements from a single, integrated analysis. Thus far, the LHFI approach has been demonstrated and validated in a freshwater context. We adapt this approach to modeling estuarine health, and illustrate it on the previously unassessed system in Richibucto in New Brunswick, Canada, where active oyster farming is a potential stressor through its effects on sediment properties. Field data correspond to health metrics that constitute the popular AZTI marine biotic index and the infaunal trophic index, as well as abiotic predictors preconceived to influence biota. Our paper is the first to construct a scientifically sensible model that rigorously identifies the collective explanatory capacity of salinity, distance downstream, channel depth, and silt–clay content–all regarded a priori as qualitatively important abiotic drivers–towards site health in the Richibucto ecosystem. This suggests the potential effectiveness of the LHFI approach for assessing not only freshwater systems but aquatic ecosystems in general.     

Barcoding Poplars (Populus L.) from Western China

Background

Populus is an ecologically and economically important genus of trees, but distinguishing between wild species is relatively difficult due to extensive interspecific hybridization and introgression, and the high level of intraspecific morphological variation. The DNA barcoding approach is a potential solution to this problem.

Methodology/Principal Findings

Here, we tested the discrimination power of five chloroplast barcodes and one nuclear barcode (ITS) among 95 trees that represent 21 Populus species from western China. Among all single barcode candidates, the discrimination power is highest for the nuclear ITS, progressively lower for chloroplast barcodes matK (M), trnG-psbK (G) and psbK-psbI (P), and trnH-psbA (H) and rbcL (R); the discrimination efficiency of the nuclear ITS (I) is also higher than any two-, three-, or even the five-locus combination of chloroplast barcodes. Among the five combinations of a single chloroplast barcode plus the nuclear ITS, H+I and P+I differentiated the highest and lowest portion of species, respectively. The highest discrimination rate for the barcodes or barcode combinations examined here is 55.0% (H+I), and usually discrimination failures occurred among species from sympatric or parapatric areas.

Conclusions/Significance

In this case study, we showed that when discriminating Populus species from western China, the nuclear ITS region represents a more promising barcode than any maternally inherited chloroplast region or combination of chloroplast regions. Meanwhile, combining the ITS region with chloroplast regions may improve the barcoding success rate and assist in detecting recent interspecific hybridizations. Failure to discriminate among several groups of Populus species from sympatric or parapatric areas may have been the result of incomplete lineage sorting, frequent interspecific hybridizations and introgressions. We agree with a previous proposal for constructing a tiered barcoding system in plants, especially for taxonomic groups that have complex evolutionary histories (e.g. Populus).     

13-Methyltetradecanoic Acid Exhibits Anti-Tumor Activity on T-Cell Lymphomas In Vitro and In Vivo by Down-Regulating p-AKT and Activating Caspase-3

13-Methyltetradecanoic acid (13-MTD), a saturated branched-chain fatty acid purified from soy fermentation products, induces apoptosis in human cancer cells. We investigated the inhibitory effects and mechanism of action of 13-MTD on T-cell non-Hodgkin’s lymphoma (T-NHL) cell lines both in vitro and in vivo. Growth inhibition in response to 13-MTD was evaluated by the cell counting kit-8 (CCK-8) assay in three T-NHL cell lines (Jurkat, Hut78, EL4 cells). Flow cytometry analyses were used to monitor the cell cycle and apoptosis. Proteins involved in 13-MTD-induced apoptosis were examined in Jurkat cells by western blotting. We found that 13-MTD inhibited proliferation and induced the apoptosis of T-NHL cell lines. 13-MTD treatment also induced a concentration-dependent arrest of Jurkat cells in the G₁-phase. During 13-MTD-induced apoptosis in Jurkat cells, the cleavage of caspase-3 and poly ADP-ribose polymerase (PARP, a caspase enzymolysis product) were detected after incubation for 2 h, and increased after extending the incubation time. However, there was no change in the expression of Bcl-2 or c-myc proteins. The appearance of apoptotic Jurkat cells was accompanied by the inhibition of AKT and nuclear factor-kappa B (NF-κB) phosphorylation. In addition, 13-MTD could also effectively inhibit the growth of T-NHL tumors in vivo in a xenograft model. The tumor inhibition rate in the experimental group was 40%. These data indicate that 13-MTD inhibits proliferation and induces apoptosis through the down-regulation of AKT phosphorylation followed by caspase activation, which may provide a new approach for treating T-cell lymphomas.     

Serum Uric Acid and Non-Alcoholic Fatty Liver Disease in Non-Diabetic Chinese Men

Increased serum uric acid (SUA) levels may be involved in the development of non-alcoholic fatty liver disease (NAFLD) in men presenting with metabolic syndrome (MetS) and/or insulin resistance. We aimed to determine the independent relationship between SUA and NAFLD in non-diabetic Chinese male population, and to explore the determinants of SUA levels among indexes of adiposity, lipid, and genotypes pertaining to triglycerides metabolism, inflammation, oxidative stress, and SUA concentrations. A total of 1440 men, classified depending on the presence of ultrasonographically detected NAFLD, underwent a complete healthy checkup program. Genotypes were extracted from our previously established genome-wide association study database. After adjusting for age, smoking, drinking, body mass index, homeostasis model assessment of insulin resistance, C-reactive protein, creatinine, alanine aminotransferase (ALT) and components of metabolic syndrome, the odds ratio for NAFLD, comparing the highest with the lowest SUA quartile, was 2.81 (95% confidence interval 1.66–4.76). A stepwise multivariate linear regression analysis (R² = 0.238, P<0.001) retained age, waist circumference, serum creatinine, triglycerides, the Q141K variant in ABCG2 (rs2231142) and NAFLD as significant predictors of SUA levels (all P<0.001). Besides, ALT and Met196Arg variant in TNFRSF1B (rs1061622) additionally associated with SUA among individuls with NAFLD. Our data suggest that in Chinese men, elevated SUA is significantly associated with NAFLD, independent of insulin resistance and other metabolic disorders, such as central obesity or hypertriglyceridemia. Meanwhile, among subjects with NAFLD, index of liver damage, such as elevated ALT combined with genetic susceptibility to inflammation associated with increased SUA levels.