Marco Casali

Since Darwin first articulated the theory of evolution by natural selection ([1859] 1964), chance in biology has been considered as intimately connected with the source of heritable variation. In line with Darwin’s thinking, the Modern Synthesis, developed in the 1940s and 1950s, invoked chance to characterize genetic variation via random mutations, as well as the evolutionary processes of genetic drift. In the same vein, philosophical debates on chance in biology have been mainly focused on evolutionary theory, and more generally, on the framework of evolutionary biology. But what about chance underlying evolution? Taking the analysis of explanations found in molecular and cellular biology as a starting point, my contribution to the philosophical debate on chance in biology is to give an epistemological “dignity” to chance. The intention of the account of “stochastic explanation” (SE) developed in my dissertation is for it to function as a philosophical tool which allows the central role of chance in cellular and molecular explanation to be recognized and accounted for.

With few exceptions, biological research dealing with stochasticity in molecular and cellular biology has focused on transcriptional processes (e.g., Elowitz et al. 2002; Lipniacki et al. 2006). Consequently, philosophical analyses have also centered on its role in transcription (e.g., Casali and Merlin 2020). Nonetheless, recent empirical evidence clearly shows that stochasticity is also pervasive in translation (e.g., Boersma et al. 2019). Focusing on time and a non-canonical case of translation (i.e., standard vs. alternative start codon selection), this paper aims to disentangle a way in which stochasticity can intervene in models of this intracellular process. Having provided a definition of what we mean by stochasticity, first, we introduce two models of time in order to show where and how stochasticity can make a difference in the timing of translation processes. Second, we show how this difference can be biologically relevant for cell physiology. We conclude that, from an explanatory point of view, it is thus worth dissecting stochasticity when studying translation, gene expression and, more generally, biological processes at the molecular level.

The purpose of this paper is to propose an original definition of stochasticity. It accomplishes this via a molecular case study that has rarely been analyzed in the philosophical literature: mutually exclusive alternative splicing (MEAS). The development of this definition can prove useful for rethinking the epistemological meaning of stochasticity in molecular and cellular biology. Exploring biological practice, I will show that work by Hiesinger and Hassan (Trends Neurosci 41:577–586:2018) is a good starting point for clarifying the stochastic aspect of MEAS as they provide a definition which uses the notions of causal dependence (CD) and unpredictability (U). I then emphasize that this definition is very similar to Gould’s notion of contingency which has been unpacked and clarified by the philosophers such as Beatty (J Philos 103:336–362:2006) and Turner (Biol Philos 26:65–79:2011). Taking this similarity seriously, I developed a definition of stochasticity that I call “insufficiency of causal dependence” (ICD). In ICD, the stochasticity/chanciness of a given phenomenon is characterized by the fact that certain clusters of causes X can be necessary but not sufficient to bring about a given outcome. This definition allows us to move away from defining stochasticity in terms of epistemic limitation (a phenomenon is “chancy” because we do not actually know what is happening), and/or in terms of the intrinsic properties of biological processes (something is “chancy” because we are referring to indeterministic phenomena). I will show that the main advantage of ICD is in helping to untangle the explanatory and predictive dimensions of stochasticity in the context of MEAS and, more generally, in molecular and cellular biology.

Since Darwin first articulated the theory of evolution by natural selection ([1859] 1964), chance in biology has been considered as intimately connected with the source of heritable variation. In line with Darwin’s thinking, the Modern Synthesis, developed in the 1940s and 1950s, invoked chance to characterize genetic variation via random mutations, as well as the evolutionary processes of genetic drift. In the same vein, philosophical debates on chance in biology have been mainly focused on evolutionary theory, and more generally, on the framework of evolutionary biology. But what about chance underlying evolution? Taking the analysis of explanations found in molecular and cellular biology as a starting point, my contribution to the philosophical debate on chance in biology is to give an epistemological “dignity” to chance. The intention of the account of “stochastic explanation” (SE) developed in my dissertation is for it to function as a philosophical tool which allows the central role of chance in cellular and molecular explanation to be recognized and accounted for.

Riassunto: Questo lavoro cerca di mostrare come i disordini psichiatrici non possano essere inquadrati in chiave essenzialista, cioè non possano essere individuati attraverso proprietà necessarie e sufficienti. Preliminarmente introdurremo un modello chiamato Homestatic Property Cluster, che risulterà strumentale per comprendere, in prima istanza, la natura continua o discreta delle entità “disordini psichiatrici”. Sosterremo che i disordini mentali sono entità discrete. In seguito, per quanto riguarda la nostra critica all’essenzialismo, analizzeremo il disease model, ponendo l’attenzione soprattutto sui suoi limiti, cercando di mettere in rilievo varie obiezioni rispetto alla sua applicabilità. Infine, cercheremo di illustrare come il modello HPC possa essere un buon punto di partenza per identificare e classificare i generi psichiatrici e come esso possa mediare tra una visione rigidamente discreta e una visione rigidamente continua dei generi psichiatrici, poiché il modello HPC, a nostro avviso, combina in maniera virtuosa proprietà di entrambe le concezioni. Parole chiave: Modello HPC; Generi naturali; Continuo; Discreto; Filosofia della psichiatria Psychiatric Kinds as HPC: A new Approach to the Discrete/Continuum Controversy in Psychiatry: This paper aims to show that psychiatric disorders cannot be defined within an essentialist perspective – i.e. by means of necessary and sufficient properties. We introduce the Homeostatic Property Cluster model which proves useful for addressing the question as to whether psychiatric disorders are continuous or discrete entities. From this discussion we find that psychiatric kinds are discrete. We then analyze the disease model – recognized in the medical field as an essentialist model – bringing attention to its limitations and raising objections to its applicability. Finally, we argue that the HPC model offers a good starting point for identifying and classifying psychiatric kinds, and show how it can provide a bridge between the rigidly discrete and rigidly continuous perspectives on kinds, bringing together aspects of both. Keywords: HPC Model; Natural Kinds; Continuous; Discrete; Philosophy of Psychiatry.

In this article we show that, even though the classification and diagnosis of Psychiatric Disorders are performed according to essentialist terms, the psychiatric diagnoses currently employed, do not actually meet these criteria. Diagnosis is performed operationally. In this paper, we suggest a change of perspective. We reject essentialism relating to PDs and argue for the Homeostatic Property Cluster model, which allows a greater insight into the ontology of PDs than the operational perspective. More specifically, we argue that the HPC model allows for a synthesis of continuous and discrete methods of understanding the boundaries between PDs. Finally, we specify in a more general manner, the kind of ontology we deal with when adopting the HPC model, arguing that this model can be viewed as a mirror device, reflecting the ontological features of PDs.