Efficacy of phototherapy in non-haemolytic hyperbilirubinaemia.

Clinical experience of phototherapy for non-haemolytic hyperbilirubinaemia in 3999 infants in Kandang Kerbau Hospital, Singapore, is documented. Phototherapy was most effective in extremely preterm infants with very low birth weight (gestation less than or equal to 32 weeks, birth weight less than or equal to 1500 g) and least effective in full term infants with very low birth weight (gestation greater than or equal to 37 weeks, birth weight less than or equal to 1500 g) and large preterm infants (gestation less than 37 weeks, birth weight greater than 2270 g). Overall, phototherapy was effective in almost all the infants, with a failure rate of only 2.00/1000 infants. No characteristic features common to all the failures could be detected. The bilirubin rebound was usually mild; repeat phototherapy was required in only 30 infants (7.50/1000), with the response to the second exposure comparable to that to the first. No infant required a third exposure. All the infants tolerated phototherapy well, none developing any illness that could be attributed to the treatment. This clinical experience shows that phototherapy for the treatment of nonhaemolytic hyperbilirubinaemia is effective and safe.     

Lycorine: a eukaryotic termination inhibitor?

The effect of the alkaloid lycorine on viral protein synthesis was studied in poliovirus-infected HeLa cells. The incorporation of [3H]leucine was inhibited by lycorine in a dose-dependent way, although lycorine never completely abolished translation. Using polyacrylamide gel electrophoresis, the viral proteins were identified as derived from the P1 (5' terminal), P2 (middle), or P3 (3' terminal) region of the poliovirus translation unit. The residual labeling of viral proteins in the presence of lycorine was mainly due to synthesis of P1 proteins and slightly less to P2 proteins, while virtually no P3-derived proteins were made. It is suggested that lycorine may act at the level of termination.     

Coupling of M3 Acetylcholine Receptor to Gq16 Activates a Natriuretic Peptide Receptor Guanylyl Cyclase

Muscarinic activation of tracheal smooth muscle (TSM) involves a M₃AChR/heterotrimeric-G protein/NPR-GC coupling mechanism. G protein activators Mastoparan (MAS) and Mastoparan-7 stimulated 4- and 10-fold the NPR-GC respectively, being insensitive to PTX and antibodies against Gα_i/o subfamily. Muscarinic and MAS stimulation of NPR-GC was blocked by antibodies against C-terminal of Gα_q16, whose expression was confirmed by RT-PCR. However, synthetic peptides from C-terminal of Gα_q15/16 stimulated the NPR-GC. Coupling of α_q16 to M₃AChR is supported by MAS decreased [³H]QNB binding, being abolished after M₃AChR-4-DAMP-alkylation. Anti-i₃M₃AChR antibodies blocked the muscarinic activation of NPR-GC, and synthetic peptide from i₃M₃AChR (M₃P) was more potent than MAS increasing GTPγ [³⁵S] and decreasing the [³H]QNB activities. Coupling between NPR-GC and Gα_q16 was evaluated by using trypsin-solubilized-fraction from TSM membranes, which displayed a MAS-sensitive-NPR-GC activity, being immunoprecipitated with anti-Gα_q16, also showing an immunoreactive heterotrimeric-G-β -subunit. These data support the existence of a novel transducing cascade, involving Gα_q16β γ coupling M₃AChR to NPR-GC.     

A holistic high-throughput screening framework for biofuel feedstock assessment that characterises variations in soluble sugars and cell wall composition in <Emphasis Type="Italic">Sorghum bicolor</Emphasis>

Background

A major hindrance to the development of high yielding biofuel feedstocks is the ability to rapidly assess large populations for fermentable sugar yields. Whilst recent advances have outlined methods for the rapid assessment of biomass saccharification efficiency, none take into account the total biomass, or the soluble sugar fraction of the plant. Here we present a holistic high-throughput methodology for assessing sweet Sorghum bicolor feedstocks at 10 days post-anthesis for total fermentable sugar yields including stalk biomass, soluble sugar concentrations, and cell wall saccharification efficiency.

Results

A mathematical method for assessing whole S. bicolor stalks using the fourth internode from the base of the plant proved to be an effective high-throughput strategy for assessing stalk biomass, soluble sugar concentrations, and cell wall composition and allowed calculation of total stalk fermentable sugars. A high-throughput method for measuring soluble sucrose, glucose, and fructose using partial least squares (PLS) modelling of juice Fourier transform infrared (FTIR) spectra was developed. The PLS prediction was shown to be highly accurate with each sugar attaining a coefficient of determination (R ² ) of 0.99 with a root mean squared error of prediction (RMSEP) of 11.93, 5.52, and 3.23 mM for sucrose, glucose, and fructose, respectively, which constitutes an error of <4% in each case. The sugar PLS model correlated well with gas chromatography–mass spectrometry (GC-MS) and brix measures. Similarly, a high-throughput method for predicting enzymatic cell wall digestibility using PLS modelling of FTIR spectra obtained from S. bicolor bagasse was developed. The PLS prediction was shown to be accurate with an R ² of 0.94 and RMSEP of 0.64 μg.mgDW^-1.h^-1.

Conclusions

This methodology has been demonstrated as an efficient and effective way to screen large biofuel feedstock populations for biomass, soluble sugar concentrations, and cell wall digestibility simultaneously allowing a total fermentable yield calculation. It unifies and simplifies previous screening methodologies to produce a holistic assessment of biofuel feedstock potential.

     

Impact of QTL properties on the accuracy of multi-breed genomic prediction

Background

Although simulation studies show that combining multiple breeds in one reference population increases accuracy of genomic prediction, this is not always confirmed in empirical studies. This discrepancy might be due to the assumptions on quantitative trait loci (QTL) properties applied in simulation studies, including number of QTL, spectrum of QTL allele frequencies across breeds, and distribution of allele substitution effects. We investigated the effects of QTL properties and of including a random across- and within-breed animal effect in a genomic best linear unbiased prediction (GBLUP) model on accuracy of multi-breed genomic prediction using genotypes of Holstein-Friesian and Jersey cows.

Methods

Genotypes of three classes of variants obtained from whole-genome sequence data, with moderately low, very low or extremely low average minor allele frequencies (MAF), were imputed in 3000 Holstein-Friesian and 3000 Jersey cows that had real high-density genotypes. Phenotypes of traits controlled by QTL with different properties were simulated by sampling 100 or 1000 QTL from one class of variants and their allele substitution effects either randomly from a gamma distribution, or computed such that each QTL explained the same variance, i.e. rare alleles had a large effect. Genomic breeding values for 1000 selection candidates per breed were estimated using GBLUP modelsincluding a random across- and a within-breed animal effect.

Results

For all three classes of QTL allele frequency spectra, accuracies of genomic prediction were not affected by the addition of 2000 individuals of the other breed to a reference population of the same breed as the selection candidates. Accuracies of both single- and multi-breed genomic prediction decreased as MAF of QTL decreased, especially when rare alleles had a large effect. Accuracies of genomic prediction were similar for the models with and without a random within-breed animal effect, probably because of insufficient power to separate across- and within-breed animal effects.

Conclusions

Accuracy of both single- and multi-breed genomic prediction depends on the properties of the QTL that underlie the trait. As QTL MAF decreased, accuracy decreased, especially when rare alleles had a large effect. This demonstrates that QTL properties are key parameters that determine the accuracy of genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0124-6) contains supplementary material, which is available to authorized users.     

Comparison of the adhesion and proliferation characteristics of HUVEC and two endothelial cell lines (CRL 2922 and CRL 2873) on various substrata

Endothelial cell coverage of blood-contacting devices is crucial to their eventual success in the clinic. Two established human cell lines derived from HUVEC (human umbilical vascular endothelial cells), CRL 2922 and CRL 2873, have been widely utilized to study and model endothelial cell biology. However, it is not clear if these two cell lines would be useful for modeling primary endothelial cell interaction with newly-formulated biomaterials in tissue engineering applications. Hence, this study was conducted to compare the adhesion and proliferation characteristics of HUVEC grown on seven different substrata, tissue culture polystyrene (TCPS), gelatin, chitosan, poly-L-lysine, hyaluronan, poly-L-lactic acid (PLLA), and polylactic-co-glycolic acid (PLGA). The short-term adhesive behavior (2 h) of HUVEC on the various substrata was not closely-replicated by either CRL 2873 or CRL 2922. This was likely because the 2 h timeframe is too short for identification of differences in the interaction among the three cell types grown on various substrata. There was much faster proliferation of CRL 2922 on all seven substrata when compared to HUVEC and CRL 2873. Moreover, the proliferation rates of CRL 2922 on the various substrata showed little variation. In contrast, HUVEC and CRL 2873 displayed similar trends in proliferation rates, with gelatin and TCPS yielding the highest rates, and PLLA and PLGA yielding the lowest rates. Hence, CRL 2873 is better suited for modeling primary endothelial cell interaction with newly-formulated biomaterials than CRL 2922. The advantage of using CRL 2873 over HUVEC for biomaterial screening is that it is immortalized and displays much less inter-batch variability than primary culture.     

Sensitivity of methods for estimating breeding values using genetic markers to the number of QTL and distribution of QTL variance

The objective of this simulation study was to compare the effect of the number of QTL and distribution of QTL variance on the accuracy of breeding values estimated with genomewide markers (MEBV). Three distinct methods were used to calculate MEBV: a Bayesian Method (BM), Least Angle Regression (LARS) and Partial Least Square Regression (PLSR). The accuracy of MEBV calculated with BM and LARS decreased when the number of simulated QTL increased. The accuracy decreased more when QTL had different variance values than when all QTL had an equal variance. The accuracy of MEBV calculated with PLSR was affected neither by the number of QTL nor by the distribution of QTL variance. Additional simulations and analyses showed that these conclusions were not affected by the number of individuals in the training population, by the number of markers and by the heritability of the trait. Results of this study show that the effect of the number of QTL and distribution of QTL variance on the accuracy of MEBV depends on the method that is used to calculate MEBV.