Table_1_Biomarkers for Macrosomia Prediction in Pregnancies Affected by Diabetes.PDF

<p>Large birthweight, or macrosomia, is one of the commonest complications for pregnancies affected by diabetes. As macrosomia is associated with an increased risk of a number of adverse outcomes for both the mother and offspring, accurate antenatal prediction of fetal macrosomia could be beneficial in guiding appropriate models of care and interventions that may avoid or reduce these associated risks. However, current prediction strategies which include physical examination and ultrasound assessment, are imprecise. Biomarkers are proving useful in various specialties and may offer a new avenue for improved prediction of macrosomia. Prime biomarker candidates in pregnancies with diabetes include maternal glycaemic markers (glucose, 1,5-anhydroglucitol, glycosylated hemoglobin) and hormones proposed implicated in placental nutrient transfer (adiponectin and insulin-like growth factor-1). There is some support for an association of these biomarkers with birthweight and/or macrosomia, although current evidence in this emerging field is still limited. Thus, although biomarkers hold promise, further investigation is needed to elucidate the potential clinical utility of biomarkers for macrosomia prediction for pregnancies affected by diabetes.</p

Protocols for obtaining immobilized cells for SEM.

<p>(A) Add cell suspension into the PDMS chamber. (B) Apply electric field and immobilize cells between the microelectrodes. Immobilized cell density can be adjusted by varying the electric field application period. (C) Dry the suspension with a lint-free cotton wipe. (D) Add media containing chemicals into the PDMS chamber for cell treatment. (E) Dry the medium with a lint-free cotton wipe. (F) Add dehydration solutions to the PDMS chamber. (G) Dry the dehydration solutions with a lint-free cotton wipe. Turn off the electric field and leave the sample for 10 minutes at room temperature to let the remained medium evaporate. (H) The sample is ready for SEM when all liquid is evaporated. Scale bar is 100 µm.</p

Optical density and protoplast conversion efficiency <i>vs</i> time plot for Lyticase treated non-budding and budding yeast cells after adding 5% SDS solution.

<p>The two insets show the non-budding and budding yeast suspensions following a 30 min treatment with 2 U/mL Lyticase and 5% SDS.</p

SEM images for both non-budding and budding yeast cells before and after Lyticase treatment at the magnifications of 10000× and 40000×.

<p>SEM images for both non-budding and budding yeast cells before and after Lyticase treatment at the magnifications of 10000× and 40000×.</p

Specifications of the applied DEP systems:

<p>(A) an open-top PDMS block was assembled onto a DEP platform equipped with one microelectrode array, the inset shows the magnified image of one pair of the curved microelectrodes, the minimum gap of the electrode is 40 µm and the width of the electrod tip is 50 µm. (B) Contours of electric field at the levitation height of z = 10 µm. (C) The formation of vortices due to the electro-thermal effects, obtained under the medium conductivity of 0.03 S/m. The streamlines are colored according to the local temperature of the liquid. A maximum velocity of 54 µm/s was achieved along the tip of microelectrodes.</p

Possibilities and limits of photon correlation spectroscopy in determining polymer molecular weight distributions

The effect of concentration and polydispersity on the collective diffusion coefficient Dc, evaluated using Photon Correlation Spectroscopy (PCS), has been investigated on poly(methyl methacrylate) (PMMA) in acetone solutions. The concentration dependence of the collective diffusion coefficient follows a linear regression law, the slope being fairly independent of polydispersity, molecular weight and temperature. The diffusion coefficient at infinite dilution D0 obeys the scaling law D0 = AMw\u2013\u3bd in the range from Mw = 10 000 to Mw = 800 000; the value of the scaling exponent, \u3bd = 0.57, proves the good solvent quality of acetone. The inversion of the scattered intensity autocorrelation data by the regularization method CONTIN allowed the evaluation of the molecular weight distribution function of the polymeric samples. Although this algorithm gives valuable information on average quantities or on the width of the distribution, it has limited resolution power; therefore a comparison with the results obtained by Size Exclusion Chromatography (SEC) was carried out for a set of samples having monomodal and bimodal distribution functions