2. Introduction Ion currents recorded from cells are the result of ion channel function and biological processes can be explained by their function. The best example known is signal transmission between neurons and muscle cells.

3. These currents are the result of ion channel function, proteins present on the membrane of cells. It has traditionally been accepted that to allow ions through ion channels must open (gating) and this has been assumed to be a random event.

4. Our group has been using fractal analysis to interpret ion current behavior. We have worked on the model of an immunological cell (macrophage) that gets infected by a protozoan ( Leishmania ), the 5th most prevalent parasitic disease in the world, and have compared the permeability of non infected vs. infected cells.

5. Macrophages express Inward (I KIR ) potassium currents Outward (I OUT ) potassium currents Using the whole cell configuration of the patch clamp technique, we studied these currents on non-infected as well as Leishmania infected macrophages

7. Inward currents (I KIR ) Non-infected cell Infected cell 100 pA 100 ms

8. Outward currents (I OUT ) 200 pA 200 ms

9. Non-infected Infected Outward currents (I OUT ) 200 ms 200 pA 4-AP TEA

10. Infection causes: Increase of I KIR current density Increase percentage of fast activating I OUT Altered pharmacological profile of I OUT population of infected cells differs from those of non infected cells.

11. Interval studied (white noise) 200 pA 200 ms 100 pA 100 ms

12. Voltage (mV). Hurst coefficient Inward currents (I KIR ) 0,1 0,2 0,3 0,4 -140 -120 -100 -80 -60 -40

13. Voltage (mV). Hurst coefficient Outward currents (I OUT ) 0,1 0,2 0,3 0,4 -100 -50 0 50 100

14. For inward and outward currents Hurst coefficient was different from 0.5. Therefore the time series does not follow a random pattern and that the phenomenon has memory. This result contradicts the classical assumption that channel gating is a random event.

15. The Hurst coefficient was below 0.5. This suggests an antipersistent pattern, in other words, that if channels are open at a particular time most probably will be closed in the following period of time

18. Fitting of Hurst coefficient vs. voltage curves is achieved by a fractional equation in both cases. Outward fitting was better than that for Inward currents. The m and d values are scaling parameters  associates with fractional diffusion - anomalous diffusion

19. The solution of Fick`s second order equation of diffusion has an  = 2. In our model Inward currents are the result of one to two types of ion channels whereas Outward currents are the result of at least three different types of channels. I OUT is more a complex current, more anomalous.

20. A lower  value was detected on the more complex current (Outward current). We suggest that  values below 2 describe anomalous phenomena, and the lower the  value the more anomalous the phenomenon.

21. Acknowledgments: Universidad Militar Nueva Granada The Colombian agency Colciencias- project code: 2228-05-10325 Universidad Nacional de Colombia Centro Internacional de Física Bogotá, Colombia.