Toward embryo cryopreservation-on-a-chip: A standalone microfluidic platform for gradual loading of cryoprotectants to minimize cryoinjuries.

Embryo vitrification is a fundamental practice in assisted reproduction and fertility preservation. A key step of this process is replacing the internal water with cryoprotectants (CPAs) by transferring embryos from an isotonic to a hypertonic solution of CPAs. However, this applies an abrupt osmotic shock to embryos, resulting in molecular damages that have long been a source of concern. In this study, we introduce a standalone microfluidic system to automate the manual process and minimize the osmotic shock applied to embryos. This device provides the same final CPA concentrations as the manual method but with a gradual increase over time instead of sudden increases. Our system allows the introduction of the dehydrating non-permeating CPA, sucrose, from the onset of CPA-water exchange, which in turn reduced the required time of CPA loading for successful vitrification without compromising its outcomes. We compared the efficacy of our device and the conventional manual procedure by studying vitrified-warmed mouse blastocysts based on their re-expansion and hatching rates and transcription pattern of selected genes involved in endoplasmic reticulum stress, oxidative stress, heat shock, and apoptosis. While both groups of embryos showed comparable re-expansion and hatching rates, on-chip loading reduced the detrimental gene expression of cryopreservation. The device developed here allowed us to automate the CPA loading process and push the boundaries of cryopreservation by minimizing its osmotic stress, shortening the overall process, and reducing its molecular footprint.

Optimization of modified carbon paste electrode with multiwalled carbon nanotube/ionic liquid/cauliflower-like gold nanostructures for simultaneous determination of ascorbic acid, dopamine and uric acid.

We describe the modification of a carbon paste electrode (CPE) with multiwalled carbon nanotubes (MWCNTs) and an ionic liquid (IL). Electrochemical studies by using a D-optimal mixture design in Design-Expert software revealed an optimized composition of 60% graphite, 14.2% paraffin, 10.8% MWCNT and 15% IL. The optimal modified CPE shows good electrochemical properties that are well matched with model prediction parameters. In the next step, the optimized CPE was modified with gold nanostructures by applying a double-pulse electrochemical technique. The resulting electrode was characterized by scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, and electrochemical impedance spectroscopy. It gives three sharp and well-separated oxidation peaks for ascorbic acid (AA), dopamine (DA), and uric acid (UA). The sensor enables simultaneous determination of AA, DA and UA with linear responses from 0.3 to 285, 0.08 to 200, and 0.1 to 450 µM, respectively, and with 120, 30 and 30 nM detection limits (at an S/N of 3). The method was successfully applied to the determination of AA, DA, and UA in spiked samples of human serum and urine.

Application of the UNIFAC model for prediction of surface tension and thickness of the surface layer in the binary mixtures.

Surface properties of binary mixtures of (alkanol with acetonitrile) have been measured by surface tension method at T=298.15 K and atmospheric pressure. The UNIFAC method is used for calculation activity coefficients of surface and bulk phases. Also, the surface tension has been predicted based on the Suarez method. This method combines a model for the description of surface tension of liquid mixtures with a UNIFAC group contribution method for the calculation of activity coefficient. Two techniques for calculation of molar surface areas, based on Paquette areas and Rasmussen areas are tested. On comparing the computed values of surface tension by the present approaches with experimental data, satisfactory results have been observed. In addition, the relative Gibbs adsorption and the surface mole fraction have been evaluated using this model. It is possible to calculate the thickness of liquid-vapor interfaces starting from surface tension data. A novel procedure is developed to obtain the thickness of liquid-vapor interfaces as a function of composition in binary systems.