Biology
For many years, I have published across a wide range of journals and disciplines, including mathematics, physics, biology, neuroscience, medicine and philosophy. Now, having no further need to expand my scientific output or advance my academic standing, I have chosen to shift my approach. Instead of writing full-length articles for peer review, I now focus on recording and sharing original ideas, i.e., conceptual insights and hypotheses that I hope might inspire experimental work by researchers more capable than myself. I refer to these short pieces as nugae, a Latin word meaning “trifles”, “nuts” or “playful thoughts”. I invite you to use these ideas as you wish, in any way you find helpful. I ask only that you kindly cite my writings, which are accompanied by a DOI for proper referencing.
NUGAE - WAS IMMUNITY THERE FIRST? A NEW PERSPECTIVE ON LIFE’S ORIGIN
Most prevailing models of the origin of life focus on the formation of self-replicating molecular systems as the key step toward the occurrence of the first cells, emphasizing the role of either metabolism, compartmentalization or replication of RNA and other polymers. Yet most origin-of-life models overlook a fundamental property of all living systems, i.e., the ability to distinguish self from non-self, a core immunological function central to biology. We propose to integrate the immunological principle of identity maintenance to explore whether primitive forms of molecular recognition were a necessary prerequisite for the emergence of life. We hypothesize that even the earliest protocells or molecular systems required a minimal capacity to recognize and preserve their own components while excluding or neutralizing harmful elements, as this function would have been essential for achieving stability, accurate replication and long-term persistence.
To experimentally explore the theoretical immunological functions of protocells and reconstruct minimal conditions for self/non-self discrimination, we propose using lipid vesicles as model systems of protocells encapsulating well-defined “self” molecules such as RNA analogs, short peptides or labeled polymers. These protocells would be introduced into environments containing a complex mixture of “non-self” molecules, e.g., synthetic analogs of potentially parasitic or disruptive agents. By varying the chemical nature, charge and sequence specificity of both self and non-self molecules, we could assess how protocells respond in terms of stability, retention of contents and selective uptake or exclusion. Molecular crowding agents and environmental stressors (e.g., pH shifts, ionic fluctuations) would simulate potential early Earth environments. This setup would allow us to test whether physical, chemical or molecular properties (e.g., selective permeability, primitive recognition motifs, molecular competition, binding specificity or environmental noise) may enable protocells to preserve their molecular identity over time. Fluorescence tagging and microscopy would track the interaction dynamics, while leakage assays and molecular degradation measurements would quantify vesicle integrity and self-preservation. Additional experiments could incorporate engineered membrane proteins or synthetic receptors to test primitive recognition motifs and mimic early forms of selective binding.
Overall, we introduce the perspective that life may have required an early form of molecular “recognition” preceding, or occurring alongside, replication. This perspective may provide insight into how primitive identity mechanisms evolved into complex immune functions and could also guide future studies on molecular discrimination, rise of parasitism and early strategies for coping with environmental stress.
Tozzi A. 2025. Nugae -Was Immunity There First? A New Perspective On Life's Origin. DOI: 10.13140/RG.2.2.13691.22561
LACKING RESOURCES AT THE ONSET OF LIFE: USING LINEAR LOGIC TO MODEL HOW LIFE BEGAN
One of the biggest challenges in understanding how life began is figuring out which chemical reactions could have realistically occurred on early Earth. Most models assume that molecules like RNA could self-replicate, but they often don’t take into account how limited resources—like energy or building blocks—might have constrained these processes. To address this, we can use a tool from mathematical logic called Linear Logic (LL), which is designed to track how resources are used and transformed. Linear Logic is different from ordinary logic. In classical logic, you can reuse assumptions as many times as you like. But real-world chemistry doesn’t work that way. If you use up a molecule in a reaction, it’s gone—you can’t just use it again. LL reflects this principle. It treats every item as something that can be consumed, changed, or made unavailable, which is exactly what happens in chemical reactions. For example, in LL, you can’t use the same unit of energy to fuel multiple reactions at once—just like in real chemistry.
The method works by translating chemical reactions—such as the activation of nucleotides, RNA assembly, and even the transition from RNA to DNA—into logical statements within a LL system. These statements represent how many molecules are available, what is needed for a reaction, and what gets produced. By doing this, one can build a complete logical map of a possible pathway toward life, while keeping track of everything being used along the way. This LL-based framework doesn't just mimic chemistry, rather it enforces strict rules that mirror conservation laws, making sure nothing comes from nothing. You can simulate different environmental conditions (like temperature changes or radiation) and see how they affect molecular stability or replication. You can also test what happens when resources are scarce or when catalysts are added.
In short, this approach offers a formal and testable way to evaluate how life could have emerged from non-living matter. It doesn’t aim to simulate every detail but instead provides a resource-sensitive framework for checking whether a proposed sequence of reactions is even possible. Scientists can use this logic-based method to rule out impossible scenarios, highlight promising ones and ultimately guide experiments that explore the origins of life in a more structured and realistic way.
QUOTE AS: Tozzi A. 2025. Prebiotic Resource Constraints and the Origin of Life: A Linear Logic Framework. bioRxiv 2025.03.23.644802; doi: https://doi.org/10.1101/2025.03.23.644802
WHY ORDER MATTERS IN BIOLOGY: A MATHEMATICAL WAY TO UNDERSTAND SEQUENCE-DEPENDENT SYSTEMS
Many biological and evolutionary processes depend not just on what happens, but on the exact order in which things happen. For instance, the order in which transcription factors bind to DNA can decide whether a gene is turned ON or stays OFF. Similarly, in evolution, the sequence in which mutations occur can change the outcome—even if the same mutations are present. This “order sensitivity” makes biological systems non-commutative, meaning reversing steps can lead to different results. Traditional biological models often ignore or simplify this directionality. To address this, the paper applies a mathematical tool called the Wedderburn–Artin theorem. This theorem helps break down complex non-commutative structures into simpler, manageable pieces called matrix blocks. The authors treat biological events (like binding or mutations) as algebraic operations and construct a custom algebra to represent them. Then, using Wedderburn’s decomposition, they divide this algebra into smaller parts that each represent a unique “behavioral module.”
The method was applied to two scenarios:
- Gene regulation: The model simulates how the order of transcription factor binding (like A before B or B before A) affects gene expression. It showed that only one order (A → B) strongly activates the gene, while others have little or no effect.
- Evolutionary mutations: The study modeled different mutation orders (e.g., A → B → C vs. C → B → A) and their effects on trait expression. Again, only one specific order led to full trait development, highlighting how mutation history matters.
In both cases, the algebraic method successfully sorted different sequences into functional categories. It also reduced the complexity of analyzing all possible sequences by grouping them into smaller, interpretable modules.
This mathematical framework doesn’t simulate timing or continuous changes, but it’s powerful for understanding systems where the order of steps is critical. The approach could be used in fields like genetics, systems biology, and synthetic biology to uncover which event orders are essential and which are redundant. In short, this paper shows how tools from abstract algebra can help explain and simplify the logic behind real biological systems—especially when the order of events changes everything.
QUOTE AS: Tozzi, Arturo. Applications of Wedderburn's Theorem in Modelling Non-Commutative Biological and Evolutionary Systems. Preprint. Posted April 3, 2025. https://doi.org/10.1101/2025.04.03.647006.