Abstract
This paper provides an account of the experimental conditions required for establishing whether correlating or causally relevant factors are constitutive components of a mechanism connecting input (start) and output (finish) conditions. I argue that two-variable experiments, where both the initial conditions and a component postulated by the mechanism are simultaneously manipulated on an independent basis, are usually required in order to differentiate between correlating or causally relevant factors and constitutively relevant ones. Based on a typical research project molecular biology, a flowchart model detailing typical stages in the formulation and testing of hypotheses about mechanistic components is also developed.
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Notes
Alternatively, a mechanism is “a complex system that produces that behavior by the interaction of a number of parts, where the interactions among parts can be characterized by direct, invariant, change relating generalization” (Glennan 2002), or “a structure performing a function in virtue of its component parts, component operations, and their organization […] responsible for one or more phenomena” (Bechtel and Abrahamsen 2005). Phyllis McKay Illari and Jon Williamson (2011) propose a more generally applicable characterization, according to which a “mechanism for a phenomenon consists of entities and activities organized in such a way that they are responsible for the phenomenon.”
For example, Lindley Darden (2006) characterizes the development of genetics as a gradual filling-in of mechanistic details. Mendel sketched out a possible mechanism explaining inheritance phenomena via a shuffling of pairs of alleles. Then, classical geneticists revised and elucidated some aspects of this sketch (e.g., the mechanism of allelic segregation, explained by meiosis) while relegating other aspects to ‘black-boxes’ (the ability of alleles to replicate and determine phenotypes), thus providing a first incomplete general schema of a series of mechanisms. Finally, molecular biologists filled in the remaining ‘black-boxes’ with more and more mechanistic details (the mechanisms of DNA replication and genome expression).
T-cells are a subpopulation of white blood cells, or lymphocytes, known to play a role in the regulation of immune responses and in defending the organism against intracellular pathogens, such as viruses.
Immortalized cell lines (as opposed to primary, or normal cells) are derived from cancerous cells and can grow and multiply indefinitely in a suitable growth medium (that is, outside the living body, or in vitro).
Programmed cell death; to be contrasted with necrosis, or damage-induced cell death.
An immortalized T-cell line derived from a lymphoma patient.
The correlations are semi-quantitative. Thicker bands in electrophoresis experiments mean more TRAIL mRNA or protein (Fig. 3, a and b; GAPDH/L32 are ‘house-keeping’ genes expressed at constant levels, and are used as baseline for comparison). Higher percentages in flow cytometry experiments mean more cell-surface TRAIL or a higher percentage of apoptotic cells (Fig. 3, c and d).
The second problem is a constitutive relevance issue conceptually similar to the first problem. The third problem requires a separate analysis, which I provide elsewhere (Baetu 2012b): the elucidation of a mechanism often requires the integration of findings from different cell/organism models and their extrapolation to yet another set of different models (usually models that replicate more faithfully physiologically/biologically significant conditions, or models of medical/technological interest). Note however that the two kinds of problems should not be conflated. Constitutive relevance claims apply solely to the experimental model in which experiments testing for constitutive relevance are performed (in my case, a T-cell line model in culture); whether constituency can be extrapolated to other, physiologically more relevant models (e.g., primary T-cells in blood extracts) is a separate issue, tackled by means of different experimental strategies.
This does not mean that the evidence is sufficient for demonstrating physiological/biological significance (see note 9). In my example, the second experiment does not prove that documented cases of primary T-cell activation under physiological conditions are also mediated by a mechanism involving NF-κB.
Craver (2007, 247) argues that “[m]echanistic theory building typically proceeds through the piecemeal accumulation of constraints on the space of possible mechanisms for a phenomenon.”
“[A] component is relevant to the behavior of a mechanism as a whole when one can wiggle the behavior of the whole by wiggling the behavior of the component and one can wiggle the behavior of the component by wiggling the behavior as a whole. The two are related as part to whole and they are mutually manipulable. More formally: (i) X is part of S; (ii) in the conditions relevant to the request for explanation there is some change to X’s φ-ing that changes S’s ψ-ing; and (iii) in the conditions relevant to the request for explanation there is some change to S’s ψ-ing that changes X’s φ-ing” (Craver 2007, 153).
It is interesting to note that there are ‘top-down’-like experiments designed to detect qualitative/quantitative changes in the components during the functioning of a mechanism; for example, such experiments were used to elucidate the stages in the functioning of the NF-κB regulatory mechanism (Sun et al. 1993). The goal of such high-resolution experiments is to determine how components contribute to the functioning of a mechanism once mechanistic components have been identified. By themselves, these experiments cannot and are not designed to rule out divergent causal pathways. Likewise, there are ‘bottom-up’-like two-variable experiments meant to capture fine-grained changes in the functioning of a mechanism in response to specific changes in the components of the mechanism; genetic engineering experiments, such as the production of T-cells unable to activate when exposed to inducers (Kwon et al. 1998), fit this description. Such experiments aim to artificially modify the behavior of naturally-occurring mechanisms, and rely on substantive knowledge of these mechanisms and their components.
“S’s ψ-ing can be understood as a complex input–output relationship. The inputs include all of the relevant conditions required for S to ψ. […] Between these inputs and outputs is a mechanism, an organized collection of parts and activities. X is one of those parts, and φ is one of those activities. […] In each case [i.e., top-down or bottom-up experiments], the goal is to show that X’s φ-ing is causally between the inputs and outputs that constitute S’s ψ-ing” (Craver 2007, 145–146).
Furthermore, the transitivity scenario entails that the two experiments are asymmetrical in exactly the same way causal relevance experiments (Leuridan 2011). For example, even if it were possible to artificially create false spatial memories in untrained rats by manipulating the molecular basis of long-term potentiation in hippocampal neurons or by transplanting hippocampi from trained rats, this would not change the initial conditions, but only short-circuit them; in other words, instead of starting with the initial conditions, the same causal pathway would be initiated at a subsequent intermediary stage. In contrast, Craver (2007, 153) insists that top-down and bottom-up experiments required by the mutual manipulability account are symmetrical and do not have a causal structure on the grounds that a part cannot cause the whole or vice versa.
An alternative solution would be the statistical analysis of the results of a large number of experiments. However, due to cost and time constraints, this is not a viable option.
Craver too notes that, often times, bottom-up experiments “involve putting S in the conditions for ψ-ing in order to see whether the intervention into the part changes whether S ψs or the way that S ψs” (2007, 146). What is described here is an experiment in which two variables are simultaneously manipulated (‘the conditions for ψ-ing’ and ‘the intervention into the part’) and their effects on a third variable is measured (‘S ψs’).
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Acknowledgments
I would like to thank Lindley Darden, as well as the editor and two anonymous reviewers for very useful comments on earlier drafts.
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Baetu, T.M. Filling in the mechanistic details: two-variable experiments as tests for constitutive relevance. Euro Jnl Phil Sci 2, 337–353 (2012). https://doi.org/10.1007/s13194-011-0045-3
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DOI: https://doi.org/10.1007/s13194-011-0045-3