TABLE 1.

Potential reasons for divergent experimental results and interpretations

Item	Variability	References
Animal models
Species	Results might vary depending on species studied, i.e., RyR2 phosphorylation level at baseline or in heart failure	^{10, 14, 15, 38}
Genetic background	Mouse strain might contribute to variable responses to β-adrenergic or pathological stress	^{15, 18, 20, 21, 40, 94, 95}
Environmental conditions	Diet (chow) and lifestyle can affect SR Ca²⁺ handling	^96–98
Circadian rhythm	Circadian rhythm can modulate pathological phenotypes as well as RyR2 properties itself	^{99, 100}
Experimental models
Animal model of disease	Involvement of specific RyR2 phosphorylation sites might depend on the type of experimental heart failure (i.e., LAD ligation vs. transverse aortic banding) and the time points at which phenotypes are evaluated	^{15, 18, 20, 21, 27, 28, 40, 54, 94, 95, 101, 102}
Anesthesia / surgical techniques	Anesthesia type and surgical techniques might alter study outcomes	^{103, 104}
Sample analysis methods	Results may dependent on analysis methods, i.e., Western Blotting vs. back-phosphorylation might reveal different results, and SR Ca²⁺ leak (tetracaine) protocol vs. Ca²⁺ spark measurements	^{10, 25, 105}
Scale	Results might vary at the whole animal (in vivo vs. ex vivo), isolated cell (intact vs. permeabilized), and single channel level	^{74, 81, 86, 91, 106}
Reagents
Antibodies	Results might vary depending on antibody (i.e., epitope, purification, species). Antibodies are often not well characterized.	^{25, 27, 28, 32, 38, 74}
Buffers, detergents, fluorophores	Buffer conditions, detergents (for solubilization of RyR2), fluorophores (for Ca²⁺ imaging) could affects results	^{107, 108}
Redox levels	S- and Cys-nitrosylation, oxidation, tyrosine nitration levels can alter RyR phosphorylation or Ca²⁺ handling	^{24, 109}
Data processing
Data analysis procedures	Results might vary depending on data analysis procedures (i.e., quantification of western blot signals, processing of confocal Ca²⁺ imaging data)	¹¹⁰
Data quality	Proper use of positive and negative controls, etc.
Fitting of data within conceptual models	Different groups might interpret the same data differentially based on the null hypothesis	^{15, 18}