The objective of this study was to use a subcutaneous continuous glucose sensor to determine time differences in the dynamics of blood glucose and interstitial glucose. A total of 14 patients with type 1 diabetes each had two sensors (Medtronic/MiniMed CGMS) placed subcutaneously in the abdomen, acquiring data every 5 min. Blood glucose was sampled every 5 min for 8 h, and two liquid meals were given. A smoothing algorithm was applied to the blood glucose and interstitial glucose curves. The first derivatives of the glucose traces defined and quantified the timing of rises, peaks, falls, and nadirs. Altogether, 24 datasets were used for the analysis of time differences between interstitial and blood glucose and between sensors in each patient. Time differences between blood and interstitial glucose ranged from 4 to 10 min, with the interstitial glucose lagging behind blood glucose in 81% of cases (95% CIs 72.5 and 89.5%). The mean (؎SD) difference between the two sensors in each patient was 6.7 ؎ 5.1 min, representing random variation in sensor response. In conclusion, there is a time lag of interstitial glucose behind blood glucose, regardless of whether glycemia is rising or falling, but intersensor variability is considerable in this sensor system. Comparisons of interstitial and blood glucose kinetics must take statistical account of variability between sensors. Diabetes 52:2790 -2794, 2003

Diagrammatic many-body perturbation theory is formulated through third order and applied to LiH, BH, and HF with various sizes of two-center Slater orbital basis sets. The most extensive calculations use 46 orbitals to recover 94, 95, and 97% of the experimental correlation energy for the three molecules, respectively, when the perturbation expansion is carried through third order with pair restrictions and including selections of higher-order diagrams via denominator shifts. A detailed analysis of the ’’pair’’ correlation energies relative to SCF occupied orbitals is given, including both inter- and intrapair contributions for the different spin cases.

The iris loses nearly half its volume from a pupil diameter of 3 to 7 mm, probably by eliminating extracellular fluid. Smaller iris CS area change with physiologic pupil dilation is a potential risk factor for AC. Dynamic iris CS area change deserves testing as a prospective indicator of AC.

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The new equation for the pressure-volume relation derived from all the currently available ocular rigidity data on the living human eye gives a larger volume increment for a given increment of pressure than Friedenwald's equation based on measurements performed on cadaver eyes.