![]() Mazaika is the ONLY photo mosaic application thatĪllows manual changes to every single tile in the finished mosaic. You could use as many of your own custom picture tiles as you want - or Trial version of Mazaika you have no limit on the image database size and If you have aĭigital camera, you can use your own pictures as tiles. (at size 32x32 pixels) to create very impressive mosaic pictures. ![]() Using Mazaika you can make professional looking mosaic pictures from almostĪny kind and type of image files. Some very hi res pictures which you can print as big as A3 or even larger. There are also more example pictures at gallery section. On the mazaika page you can see screenshots and example mosaics. Mazaika can create pictures made of other pictures. However, the exact cause of the large volume change is unknown.Mazaika is a professional photo mosaic tool. ![]() One possibility is that this particular child had an abnormally large volume response to osmotic stresses due to an impaired cell volume regulation system. ![]() Thus, opposite osmotic stresses were present at the times of the first two scans. These volume characteristics are consistent with cell shrinkage ( 7) from both chronic hyperglycemia and from the acute hyperglycemic condition (324 mg/dL) before the scan. The second MRI at age 8.0 years had the smallest gray matter volume and largest ventricle volume. (Unfortunately, actual measurements were not available.) This osmotic shift would induce water-based cellular swelling, decreased ventricular volume ( 4), and decreased diffusivity ( 5) until counteracted by cell volume regulation mechanisms ( 6). For example, if glucose dropped from 300 mg/dL to 63 mg/dL within 1 h, similar to other large sudden glucose drops observed in his CGM data, then plasma osmolality is estimated to have dropped from 297 mOsmol/kg to 282 mOsmol/kg ( 3). We speculate that these characteristics were an osmotic response to a sudden large drop in blood glucose shortly before the time 1 scan. This case is notable for the unusually large gray matter volume and cortical thickness at time 1 relative to the other time points. The CGM data were not collected immediately before or during any MRI scan. Continuous glucose monitoring (CGM) data collected for a total of 39 days showed a mean glucose (± SD) level of 235 ± 88 mg/dL and numerous large, rapid changes in sensor glucose, with increases as large as 200 mg/dL and decreases as large as 334 mg/dL within 1 h. His medical history included one hypoglycemic event with disorientation at age 6.3 years (10 weeks before the first MRI scan) and one hospitalization for diabetic ketoacidosis at age 11.5 years (15 weeks before the third MRI scan). Moreover, he had age-appropriate vocabulary and stable cognitive test scores over the 5-year period. He was healthy besides type 1 diabetes, prepubertal, with full-term birth, normal weight development, normal thyroid function, and no evidence of neurological deficits. The patient was on multiple daily insulin injections at the time of his first MRI scan and on infusion pump therapy at the later scans. Neuroradiological reviews of the MRI scans at each time point reported no evidence of gross pathological abnormalities or diffusion restrictions. The patient was diagnosed with type 1 diabetes at age 5.6 years when he presented without diabetic ketoacidosis.
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