To investigate if short-term block-structured training consisting of alternating weeks of blood flow restricted low-load resistance training (BFR-RT) and conventional free-flow heavy-load resistance training (HL-RT) leads to superior gains in mechanical muscle function, myofiber size, and satellite cell (SC) content and myonuclear number compared with HL-RT alone. Eighteen active young participants (women/men: 5/13, 23 ± 1.2 yr) were randomized to 6 wk (22 sessions) of lower limb HL-RT [70-90% one repetition maximum (1-RM)] (HRT, n = 9) or block-structured training alternating weekly between BFR-RT (20% 1-RM) and HL-RT (BFR-HRT, n = 9). Maximal isometric knee extensor strength (MVC) and muscle biopsies (VL) were obtained pre- and posttraining to examine changes in muscle strength, myofiber cross-sectional area (CSA), myonuclear (MN) number, and SC content. MVC increased in both training groups (BFR-HRT: +12%, HRT: +7%; P < 0.05). Type II myofiber CSA increased similarly (+16%) in BFR-HRT and HRT (P < 0.05), while gains in type I CSA were observed following HRT only (+12%, P < 0.05). In addition, myonuclear number remained unchanged, whereas SC content increased in type II myofibers following HRT (+59%, P < 0.05). Short-term alternating BFR-RT and HL-RT did not produce superior gains in muscle strength or myofiber size compared with HL-RT alone. Noticeably, however, conventional HL-RT could be periodically replaced by low-load BFR-RT without compromising training-induced gains in maximal muscle strength and type II myofiber size, respectively.NEW & NOTEWORTHY The present data demonstrate that periodically substituting heavy-load resistance training (HL-RT) with low-load blood flow restricted resistance training (BFR-RT) leads to similar gains in type II myofiber CSA and muscle strength as achieved by HL-RT alone. Furthermore, we have for the first time evaluated myonuclear content and myonuclear domain size before and after training intervention across separate fiber size clusters and found no within-cluster changes for these parameters with training.