Interpreting Qualitative Fibrinogen Data to Design Discriminating Experiments: A proposed framework for curve interpretation molecular evidence and experimental selection

This methodological article proposes a framework for interpreting qualitative fibrinogen measurements and selecting experiments that distinguish competing explanations. It connects lysis curves, concentration measurements, post-translational modifications (PTMs), structural observations, and multimodal analysis while separating measurement validity, functional association, molecular attribution, and disease maintenance. The framework addresses how endpoint definitions, optical amplitude, normalization, time origin, and incomplete curves influence half-lysis time interpretation. It distinguishes valid censored observations from analytical failure and emphasizes donor-level independence when handling repeated measurements. Concentration standardization is treated as a defined experimental condition rather than proof of physiological independence from fibrinogen amount. Particular attention is given to the distinction between functional concentration estimates, antigenic quantity, and clottable substrate. Molecular interpretation separates PTM identification, site localization, analytical response, site occupancy, and intact-protein composition. Multimodal convergence is evaluated alongside shared technical influences, multiplicity, overfitting, and information leakage. The central contribution is a structured progression from an observed finding to surviving explanations and a discriminating experiment. The article examines purification-sensitive effects, copurified components, selective molecular interventions, and the distinction between replication and transfer into a defined recipient system. Three methodological tables provide endpoint specifications, technical alternatives and targeted checks, and a finding-to-experiment matrix. An accompanying worksheet records rival predictions, target verification, controls, uncertainty, and criteria for weakening the favored hypothesis. No original participant data or experimental outcomes are reported. Numerical examples are constructed teaching illustrations, not evidence of biological effects or analytical performance. The framework and its instruments remain proposals requiring prospective evaluation.