miTarget: microRNA target gene prediction using a support vector machine

BACKGROUND: MicroRNAs (miRNAs) are small noncoding RNAs, which play significant roles as posttranscriptional regulators. The functions of animal miRNAs are generally based on complementarity for their 5' components. Although several computational miRNA target-gene prediction methods have been proposed, they still have limitations in revealing actual target genes. RESULTS: We implemented miTarget, a support vector machine (SVM) classifier for miRNA target gene prediction. It uses a radial basis function kernel as a similarity measure for SVM features, categorized by structural, thermodynamic, and position-based features. The latter features are introduced in this study for the first time and reflect the mechanism of miRNA binding. The SVM classifier produces high performance with a biologically relevant data set obtained from the literature, compared with previous tools. We predicted significant functions for human miR-1, miR-124a, and miR-373 using Gene Ontology (GO) analysis and revealed the importance of pairing at positions 4, 5, and 6 in the 5' region of a miRNA from a feature selection experiment. We also provide a web interface for the program. CONCLUSION: miTarget is a reliable miRNA target gene prediction tool and is a successful application of an SVM classifier. Compared with previous tools, its predictions are meaningful by GO analysis and its performance can be improved given more training examples

Renormalization group theory for percolation in time-varying networks

Motivated by multi-hop communication in unreliable wireless networks, we present a percolation theory for time-varying networks. We develop a renormalization group theory for a prototypical network on a regular grid, where individual links switch stochastically between active and inactive states. The question whether a given source node can communicate with a destination node along paths of active links is equivalent to a percolation problem. Our theory maps the temporal existence of multi-hop paths on an effective two-state Markov process. We show analytically how this Markov process converges towards a memory-less Bernoulli process as the hop distance between source and destination node increases. Our work extends classical percolation theory to the dynamic case and elucidates temporal correlations of message losses. Quantification of temporal correlations has implications for the design of wireless communication and control protocols, e.g. in cyber-physical systems such as self-organized swarms of drones or smart traffic networks.Comment: 8 pages, 3 figure

The use of gold nanoparticle aggregation for DNA computing and logic-based biomolecular detection

The use of DNA molecules as a physical computational material has attracted much interest, especially in the area of DNA computing. DNAs are also useful for logical control and analysis of biological systems if efficient visualization methods are available. Here we present a quick and simple visualization technique that displays the results of the DNA computing process based on a colorimetric change induced by gold nanoparticle aggregation, and we apply it to the logic-based detection of biomolecules. Our results demonstrate its effectiveness in both DNA-based logical computation and logic-based biomolecular detection.the Ministry of Commerce, Industry and Energy through the Molecular Evolutionary Computing (MEC) Project the Ministry of Education and Human Resources Development (MOEHRD) under the BK21-IT Program The ICT at Seoul National University provided research facilities a Korea Research Foundation Grant funded by the Korean Government (MOEHRD, Basic Research Promotion) (KRF-2006-351-C00045

Predictors of Success of Repeated Injections of Single-dose Methotrexate Regimen for Tubal Ectopic Pregnancy

The purpose of this study is to evaluate predictors of success of repeated injections of methotrexate in the single-dose regimen for the treatment of tubal ectopic pregnancy. All patients who had ectopic tubal pregnancy and were treated with a single dose regimen were retrospectively identified. 126 patients were treated with methotrexate. Among them, 39 patients were adequate for this study. 33 were treated with the 2nd dose and 27 were successfully cured. Additionally, 6 who were injected with the 3rd dose were all cured as well. Therefore, in our study, the success rate for the repeated injections of methotrexate was found to be 84.6% (33/39). The mean initial β-hCG level was significantly lower in patients who were successfully treated than in patients who failed (3915.3±3281.3 vs. 8379.7±2604.4 IU/mL, p<0.05). The success rate is 96% when the β-hCG level is less than 6,000 IU/mL and is 58% when β-hCG is greater than 6,000 IU/mL (OR=18.57, 95% CI 1.86-185.89). The initial β-hCG level is the only factor that has significant meaning as predictor of success of repeated injections of methotrexate in the single-dose regimen. Repeated injections of methotrexate may be particularly effective when the initial β-hCG level is below 6,000 IU/mL

Good Glycemic Control Is Associated with Better Survival in Diabetic Patients on Peritoneal Dialysis: A Prospective Observational Study

BACKGROUND: The effect of glycemic control after starting peritoneal dialysis (PD) on the survival of diabetic PD patients has largely been unexplored, especially in Asian population. METHODS: We conducted a prospective observational study, in which 140 incident PD patients with diabetes were recruited. Patients were divided into tertiles according to the means of quarterly HbA1C levels measured during the first year after starting PD. We examined the association between HbA1C and all-cause mortality using Cox proportional hazards models. RESULTS: The mean age was 58.7 years, 59.3% were male, and the mean follow-up duration was 3.5 years (range 0.4-9.5 years). The mean HbA1C levels were 6.3%, 7.1%, and 8.5% in the 1(st), 2(nd), and 3(rd) tertiles, respectively. Compared to the 1(st) tertile, the all-cause mortality rates were higher in the 2(nd) [hazard ratio (HR), 4.16; 95% confidence interval (CI), 0.91-18.94; p = 0.065] and significantly higher in the 3(rd) (HR, 13.16; 95% CI, 2.67-64.92; p = 0.002) tertiles (p for trend = 0.005), after adjusting for confounding factors. Cardiovascular mortality, however, did not differ significantly among the tertiles (p for trend = 0.682). In contrast, non-cardiovascular deaths, most of which were caused by infection, were more frequent in the 2(nd) (HR, 7.67; 95% CI, 0.68-86.37; p = 0.099) and the 3(rd) (HR, 51.24; 95% CI, 3.85-681.35; p = 0.003) tertiles than the 1(st) tertile (p for trend = 0.007). CONCLUSIONS: Poor glycemic control is associated with high mortality rates in diabetic PD patients, suggesting that better glycemic control may improve the outcomes of these patients

Effect of Fermented Sauropus Androgynus Leaves on Blood Lipid Fraction and Haematological Profile in Broiler Chickens

This study was conducted to evaluate effect of fermented Sauropus androgynus leaves on blood lipid fractions and haematological profiles in broilers. One hundred and twelve broilers were distributed to 7 treatment groups. One group was fed diets without Sauropus androgynus leaves as the control, and other six groups were fed Sauropus androgynus leaves fermented by Neurospora crassa, Lactobacillus sp. or Saccharomyces cerevisiae at level of 25 g or 50 g/kg diet. Experimental results showed that the treatments had no effect on cholesterol, high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c) and atherogenic index, very low-density lipoprotein cholesterol (VLDL-c) and triglyceride concentration (P>0.05). It was shown that fermented Sauropus androgynus leaves significantly affected red blood count (RBC), white blood count (WBC), packed cell volume (PCV), trombosit dan erythrocyte sedimentation rate (ESR) (

A More Appropriate Cardiac Troponin T Level That Can Predict Outcomes in End-Stage Renal Disease Patients with Acute Coronary Syndrome

Purpose: Cardiac troponin T (cTnT), a useful marker for diagnosing acute myocardial infarction (AMI) in the general population, is significantly higher than the usual cut-off value in many end-stage renal disease (ESRD) patients without clinically apparent evidence of AMI. The aim of this study was to evaluate the clinical usefulness of cTnT in ESRD patients with acute coronary syndrome (ACS). Materials and methods: Two hundred eighty-four ESRD patients with ACS were enrolled between March 2002 and February 2008. These patients were followed until death or June 2009. Medical records were reviewed retrospectively. The cut-off value of cTnT for AMI was evaluated using a receiver operating characteristic (ROC) curve. We calculated Kaplan-Meier survival curves, and potential outcome predictors were determined by Cox proportional hazard analysis. Results: AMIs were diagnosed in 40 patients (14.1%). The area under the curve was 0.98 in the ROC curve (p<0.001; 95% CI, 0.95-1.00). The summation of sensitivity and specificity was highest at the initial cTnT value of 0.35 ng/mL (sensitivity, 0.95; specificity, 0.97). Survival analysis showed a statistically significant difference in all-cause and cardiovascular mortalities for the group with an initial cTnT ≥0.35 ng/mL compared to the other groups. Initial serum cTnT concentration was an independent predictor for mortality. Conclusion: Because ESRD patients with an initial cTnT concentration ≥0.35 ng/mL have a poor prognosis, it is suggested that urgent diagnosis and treatment be indicated in dialysis patients with ACS when the initial cTnT levels are ≥0.35 ng/mL.ope