Efficient isolation of high quality nucleic acids from different tissues of <Emphasis Type="Italic">Taxus baccata</Emphasis> L.

Improved and efficient methods were developed for isolating high quality DNA and RNA from different sources of Iranian Yew (Taxus baccata L.). The methods were based on CTAB extraction buffer added with high levels of polyvinylpyrrolidone (PVP) and β-mercaptoethanol to properly remove polysaccharides and prevent oxidation of phenolics. The pellets obtained by ethanol precipitation were washed only with Chloroform: isoamyl alcohol (24:1). So, we could successfully eliminate the dangerous phenol/chloroform extraction steps from the isolation procedure. Both spectrophotometric (A₂₆₀/A₂₈₀ and A₂₆₀/A₂₃₀ ratios) and agarose electrophoresis analysis of isolated nucleic acids (DNA and RNA) indicated good results. DNA with the average yield of 100–300 μg/g leaf and stem tissue and total RNA with an average yield of 20–30 μg/g cell culture and 80–100 μg/g leaf and stem tissue of Iranian yew could be obtained. Successful amplification of pam and pds by PCR and RT-PCR, showed the integrity of isolated DNA and RNA, respectively.     

Tenascin-C as a noninvasive biomarker of coronary artery disease

Molecular Biology Reports - Coronary artery disease (CAD), is the leading cause of mortality and morbidity worldwide. Tenascin-C (TNC) with high expression levels in inflammatory and cardiovascular...     

Molecularly imprinted composite cryogels for hemoglobin depletion from human blood

A molecularly imprinted composite cryogel (MICC) was prepared for depletion of hemoglobin from human blood prior to use in proteome applications. Poly(hydroxyethyl methacrylate) based MICC was prepared with high gel fraction yields up to 90%, and characterized by Fourier transform infrared spectrophotometer, scanning electron microscopy, swelling studies, flow dynamics and surface area measurements. MICC exhibited a high binding capacity and selectivity for hemoglobin in the presence of immunoglobulin G, albumin and myoglobin. MICC column was successfully applied in fast protein liquid chromatography system for selective depletion of hemoglobin for human blood. The depletion ratio was highly increased by embedding microspheres into the cryogel (93.2%). Finally, MICC can be reused many times with no apparent decrease in hemoglobin adsorption capacity. Copyright © 2014 John Wiley & Sons, Ltd.     

The effect of replicate number and image analysis method on sweetpotato [Ipomoea batatas (L.) Lam.] cDNA microarray results

Microarray analysis makes it possible to determine the relative expression of thousands of genes simultaneously. It has gained popularity at a rapid rate, but many caveats remain. In an effort to establish reliable microarray protocols for sweetpotato [Ipomoea batatas (L.) Lam.], we compared the effect of replication number and image analysis software with results obtained by quantitative rela-time PCR (Q-RT-PCR). Sweetpotato storage root development is the most economically important process in sweetpotato. In order to identify genes that may play a role in this process, RNA for microarray analysis was extracted from sweetpotato fibrous and storage roots. Four data sets, Spot4, Spot6, Finder4 and Finder6, were created using 4 or 6 replications, and the image analysis software of UCSF Spot or TIGR Spotfinder were used for spot detection and quantification. The ability of these methods to identify significant differential expression between treatments was investigated. The data sets with 6 replications were better at identifying genes with significant differential expression than the ones of 4 replications. Furthermore when using 6 replicates, UCSF Spot was superior to TIGR Spotfinder in identifying genes differentially expressed (18 out of 19) based on Q-RT-PCR. Our study shows the importance of proper replication number and image analysis for microarray studies.     

Role ofthe IncRNA-p53 regulatory network in cancer

Advances in functional genomics have led to discovery of a large group of previous uncharacterized long non-coding RNAs （IncRNAs）. Emerging evidence indicates that IncRNAs may serve as master gene regulators through various mechanisms. Dysregulation of IncRNAs is often associated with a variety of human diseases including cancer. Of significant interest, recent studies suggest that IncRNAs participate in the p53 tumor suppressor regulatory network. In this review, we discuss how IncRNAs serve as p53 regulators or p53 effectors. Further characterization of these p53-associated IncRNAs in cancer will provide a better understanding of lncRNA- mediated gene regulation in the p53 pathway. As a result, IncRNAs may prove to be valuable biomarkers for cancer diagnosis or poten- tial targets for cancer therapy.     

The relationship between trace elements and cardiac markers in acute coronary syndromes

Previous studies have demonstrated increased serum copper and iron levels and decreased selenium and zinc levels in patients with myocardial infarction. Furthermore, the prognostic value of the levels of trace elements in myocardial infarction has been stressed. We examined serum levels of Cu, Fe, Zn and Se, as well as glutathione peroxidase (GPx), a selenoenzyme with antioxidant properties, and C-reactive protein (CRP), a marker of inflammation, in acute coronary syndromes (ACS) regarding their relationship to cardiac troponins and creatine kinase-MB mass (CK-MBm), important prognostic markers. Serum trace elements, GPx activity and CRP were determined in 70 patients with ACS who were admitted within 12 h after the onset. Differences in these parameters were evaluated in three groups of patients divided according to the levels of cardiac markers: group III consisted of patients with high increases in cTnT, cTnI and CK-MBm (> or =0.9 ng/mL, > or =1.0 ng/mL, > or =30 ng/mL, respectively), patients with milder increases in these markers were included in groups II and I consisted of patients with values just above the upper reference limits. Serum Fe levels increased significantly in group II and even more prominently in group III compared to group I (p = 0.04, 0.002, respectively). There was no significant difference between groups II and III. The increase in serum Cu was significant in group III compared to both groups II and I (p = 0.04, 0.001, respectively). There was no significant difference between groups I and II regarding Cu and Zn. The decrease in serum Se and GPx levels was significant only between groups III and I (p = 0.004 for Se and p = 0.0001 for GPx). CRP levels showed a significant increase in group III compared to groups II and I (p = 0.03 and 0.001). CRP showed a significant positive and GPx a significant negative correlation to the cardiac markers cTnT, cTnI and CK-MBm. Cu was positively correlated to all cardiac markers, while the positive correlation between Fe and cardiac markers was significant only for cTnI. Both Zn and Se were negatively correlated to cTnT, and Se was also to cTnI. In conclusion, the increase in serum levels of Cu and Fe and the decrease in serum levels of Zn and Se in patients with higher levels of troponins and CK-MBm imply that trace element levels are related to the degree of myocardial damage and thus may play a role in the pathogenesis of ischemic heart disease. The strong correlations between cardiac markers and both CRP and GPx suggest that these parameters are promising prognostic factors in acute coronary syndromes.     

Specific recognition of a multiply phosphorylated motif in the DNA repair scaffold XRCC1 by the FHA domain of human PNK

Short-patch repair of DNA single-strand breaks and gaps (SSB) is coordinated by XRCC1, a scaffold protein that recruits the DNA polymerase and DNA ligase required for filling and sealing the damaged strand. XRCC1 can also recruit end-processing enzymes, such as PNK (polynucleotide kinase 3′-phosphatase), Aprataxin and APLF (aprataxin/PNK-like factor), which ensure the availability of a free 3′-hydroxyl on one side of the gap, and a 5′-phosphate group on the other, for the polymerase and ligase reactions respectively. PNK binds to a phosphorylated segment of XRCC1 (between its two C-terminal BRCT domains) via its Forkhead-associated (FHA) domain. We show here, contrary to previous studies, that the FHA domain of PNK binds specifically, and with high affinity to a multiply phosphorylated motif in XRCC1 containing a pSer-pThr dipeptide, and forms a 2:1 PNK:XRCC1 complex. The high-resolution crystal structure of a PNK–FHA–XRCC1 phosphopeptide complex reveals the basis for this unusual bis-phosphopeptide recognition, which is probably a common feature of the known XRCC1-associating end-processing enzymes.     

Non-Invasive Separation of Alcoholic and Non-Alcoholic Liver Disease with Predictive Modeling

Background & Objective

Currently, a major clinical challenge is to distinguish between chronic liver disease caused by metabolic syndrome (non-alcoholic fatty liver disease, NAFLD) from that caused by long term or excessive alcohol consumption (ALD). The etiology of severe liver disease affects treatment options and priorities for liver transplantation and organ allocation. Thus we compared physiologically similar NAFLD and ALD patients to detect biochemical differences for improved separation of these mechanistically overlapping etiologies.

Methods

In a cohort of 31 NAFLD patients with BMI below 30 and a cohort of ALD patient with (ALDC n = 51) or without cirrhosis (ALDNC n = 51) serum transaminases, cell death markers and (adipo-)cytokines were assessed. Groups were compared with One-way ANOVA and Tukey''s correction. Predictive models were built by machine learning techniques.

Results

NAFLD, ALDNC or ALDC patients did not differ in demographic parameters. The ratio of alanine aminotransferase/aspartate aminotransferase - common serum parameters for liver damage - was significantly higher in the NAFLD group compared to both ALD groups (each p<0.0001). Adiponectin and tumor necrosis factor(TNF)-alpha were significantly lower in NAFLD than in ALDNC (p<0.05) or ALDC patients (p<0.0001). Significantly higher serum concentrations of cell death markers, hyaluronic acid, adiponectin, and TNF-alpha (each p<0.0001) were found in ALDC compared to ALDNC. Using machine learning techniques we were able to discern NAFLD and ALDNC (up to an AUC of 0.9118±0.0056) or ALDC and ALDNC (up to an AUC of 0.9846±0.0018), respectively.

Conclusions

Machine learning techniques relying on ALT/AST ratio, adipokines and cytokines distinguish NAFLD and ALD. In addition, severity of ALD may be non-invasively diagnosed via serum cytokine concentrations.