A surgical technique for catheter implantation for sequential blood sampling in the pig is described. This methodology minimizes stress to the animal and chances of catheter dislodgement, both of which are detrimental to accurate long-term metabolic assessment of the animal model. The technique involves implantation of a vinyl catheter via the external jugular vein into the vena cava. To ensure catheter retention, the method uses a silicone plug fitted to the catheter and located cranial to its entry to the vein, double ligation at the venous insertion, subsequent passage of the catheter to exit 10 cm cranial to the scapula on the dorsal midline, and a denim vest fitted to the thorax. With this technique seven out of nine catheters have functioned more than 50 days, two functioned for approximately 100 days, and one for over 150 days.

DFT calculations show how the kinetics and thermodynamics of thiol additions to enones are affected by incorporation of the enone into a cross-conjugated divinyl ketone moiety.

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Machine learning can extract complex structure/property relationships but is often insufficient to explain how to control or tune the properties of materials, particularly when they are multi-functional. This study demonstrates the value of combining multi-target regression and multi-target causal graphs to address the need to simultaneously control multiple properties of nanomaterials, and the need to translate these relationships into actionable insights. Using nanodiamonds as an exemplar, recursive feature elimination is first used to identify nine structural features that allow simultaneous prediction of their electron charge transfer properties and thermochemical stability to high accuracy by an interpretable random forest regressor. A multi-target Bayesian network with domain knowledge incorporated via interactive learning using a hill-climbing algorithm then determines how these important structural features of nanodiamonds relate to their functional properties, proposing causal paths that can be used to inform experimental design.