The global photobiomodulation (PBM) on an organism was studied in terms of function-specific homeostasis (FSH) and scale-free functional network in this paper. A function can be classified into a normal function in its FSH and a dysfunctional function far from its FSH. An FSH-specific stress (FSS) disrupting an FSH can also be classified into a successful stress in its FSS-specific homeostasis (FSSH) and a chronic stress far from its FSSH. The internal functions of an organism can be divided into essential, special nonessential, and general nonessential functions. Health may be defined as a state of an organism in which all the essential and special nonessential functions are normal or their stresses are successful. Suboptimal health may be defined as a state of a disease-free organism in which only some special nonessential functions are dysfunctional in comparison with its healthy state. Disease may be defined as a state of an organism which is not in both health and suboptimal health. The global PBM of health, suboptimal health, or disease suggested that the PBM may depend on the organism action.

Objective A signal transduction pathway is always signal-specific, but it becomes special in exercise physiology, especially for habitual exercise training. In this paper, the normal signal transduction pathways (NPs) of habitual endurance exercise of Sprague-Dawly (SD) rats at different intensities were studied in terms of self-similar algorithm . Methods  1. SD rats were randomly divided into a control group with no exercise (Cont), a low-intensity exercise group (LI) at 15 m/min for 60 min, a medium-intensity exercise group (MI) at 25 m/min for 40 min, and a high-intensity exercise group (HI) 35 m/min for 30 min. The the treadmill exercise began at 10 m/min for 10 min. The speed and time increased by 5 m/min and by 5 min respectively after every two days until the intensity was OK for LI, MI and HI groups. All rats in the exercise groups were trained for eight weeks. The muscle was collected two hours after the last training. The 20 parameters, the expression of PGC-1α, PI3K, AMPK, p38MAPK, SIRT1, IGF-1, Akt, mTOR, TFAM, NRF1 and NRF2 and the level of T, CS, SDH, β-HAD, MDH, HK, PK, LDH and HSL, were assessed. 2. The 20 dimension data sets were integratedly analyzed with self-similar algorithm. Results 1. The first-order self-similarity held for the 20 dimension data sets between MI and HI groups. 2. There was one biomarker, PGC-1α, between Cont and LI groups with respect to HI group which parameters were used to be dimensionless for Cont and LI groups. 3. There were two biomarkers, PGC-1α and PI3K, between LI and MI or HI groups with respect cont group. Conclusions The NP of LI group may be PGC-1α pathway, and the NPs of MI or HI group may be PGC-1α and PI3K pathways.