Information

Mechanisms - Biology


Kinetics of an un-catalyzed chemical reaction vs. a catalyzed chemical reaction

Gibbs Free Energy (G) is used to describe the useful energy in a reaction or the energy capable of doing work. As a result, more product will be made because more molecules will have the energy necessary for the reaction to occur and the reaction will occur at a faster rate.

Un-Catalyzed Chemical Reaction:

S↔S*↔P

Substrate is converted into product when the substrate has enough energy to overcome the activation energy and be converted into product.

Catalyzed Chemical Reaction:

S+E↔ES↔ES*↔EP ↔E+P

Once an enzyme is introduced into the reaction, the enzyme binds to the substrate forming an enzyme/substrate complex (ES). As a result this complex decreases the activation energy, allowing the reaction to occur at a faster rate and form the enzyme/product complex (EP). This complex then dissociates, into the product and the enzyme. The enzyme is then free to catalyze another reaction.

Figure 1

Quantitatively, what is the effect of reducing Ea?

For reaction A↔B, V = k[A]

k=(hT/kb)exp(-Ea/RT)

h= Plank’s constant; kb = Boltzman’s constant,

So k and thus V are inversely and exponentially related to Ea and directly related to T:

A 6 kJ/mol reduction in Ea gives ca 10x increase in k and V

∆h ~ exp(+6000/8.3*300) ~ 11 (reduction in Ea is an increase from –Ea)

V(catalyzed)/V(uncatalyzed) for various enzymes varies from 104 to 1021, meaning Ea is reduced by ca 23 to 126 kJ/mol

How do enzymes reduce Ea?

These effects raise G(ES):cage effect, orientation, steric straining of bonds (stress from H-, Vanderwaal’s, ionic bonds), dislocation of bonding electrons through +/- charges

These effects reduce G(ES*): covalent bonds, acid- base catalysis, low-barrier hydrogen bonds, and metal ion catalysis

Different classes of enzymes may use different mechanisms:

  1. Oxidoreductases (oxidation-reduction reactions)
  2. Transferases (transfer of functional groups)
  3. Hydrolases (hydrolysis reactions)
  4. Lyases (addition to double bonds)
  5. Isomerases (isomerization reactions)
  6. Ligases (formation of bonds with ATP cleavage)

Ecological succession: Important Types and 3 Mechanisms

Ecological succession mechanisms

Change is the only constant in the universe and environment is not an exception so as ecological succession. Environment has been dynamic in nature over life history of the Earth due to several factors like:

  1. Change in climatic and physiographic factors.
  2. The activities of individuals of the communities.

These factors brings out specific changes in the dominance of existing community. Which in turn sooner or later replaced by another community at the same place. This process continues and successive communities develops one after another over the period of time at the same area, until the final community again becomes more or less stable for a period of time.

This occurrence of relatively different sequence of community over a period of time in the same area is known as a ecological succession. Each phase of ecological succession is called as Sere or seral stages. The initial sere was known as Pioneer seral stage.

While due to disturbance by community from later seral stage it may acquire an earlier seral stage (Like retrograde pathway of Evolution where complex character get replaced by earlier simpler character) this is relatively rare in occurance as generally community moves towards climax.


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2.9 Mechanisms of Transport Overview

As if the basics of membrane transport weren’t complex enough, when you start to consider how organisms actually implement these strategies to maintain homeostasis and grow, the overall processes can get mind-boggling. For instance, did you know that a mushroom uses active transport, passive transport, exocytosis, and endocytosis to just to grow and reproduce? Or that a fish’s gills use ion channels, carrier proteins, and modes of active transport to help the fish regulate its water content? Even a plant, which may seem simple, uses all the different mechanisms of transport available. Understanding how these mechanisms of transport work together will definitely be on the AP Test. So, follow along with us as we cover everything you need to know about Mechanisms of Transport!

This section is all about how different mechanisms of transport work together to create living cells, tissues, organs, and organisms.

In previous sections, we covered the basics of cellular membranes and the integral membrane proteins that create the fluid mosaic model. Then, we looked into all the different types of membrane transport. We saw the uniporters, symporters, and antiporters of active transport, and we saw how diffusion, carrier proteins, and channel proteins contribute to passive transport. We even looked at some simple systems involving active and passive transport that work together to create ATP.

These complex processes are constantly active in organisms to help them react to changing environmental conditions. Let’s start with a short review of transport mechanisms and how they can work together.

This is going to be a very quick review of the different mechanisms of transport before we go into the complex processes of how these mechanisms work together to maintain homeostasis in different organisms. If any of these terms are completely unfamiliar or you are having trouble remembering these concepts, please review previous sections to get up to speed. Ready? Let’s go!

There are two basic types of transport that happen across the cell membrane.

Passive transport includes simple diffusion and facilitated diffusion – neither of which requires an input of energy. Small, uncharged molecules can move through the membrane easily via diffusion. The carrier proteins and protein channels of facilitated diffusion are needed for ions and larger molecules. Remember that passive transport always moves substances down their concentration gradient – from high to low.

By contrast, the methods of active transport require energy to move substances against their concentration gradients. Active transport can be primary when they are powered by the chemical energy stored in ATP, or they can be secondary if they are powered by the energy stored in an ion gradient. There are three types of active transport proteins: uniporters, symporters, and antiporters – all of which use energy in some form to pump a substance into an area of higher concentration.

Further, cells can import and export large amounts of substance through endocytosis and exocytosis! Endocytosis can take in very large objects via phagocytosis, large amounts of a solution via pinocytosis, or even bulk import smaller substances via receptor-mediated endocytosis. With exocytosis, the opposite process takes place by merging vesicles with the cell membrane. Large amounts of a specific chemical or large structures can be expelled from the cell through exocytosis.

Both endocytosis and exocytosis rely on complex signaling within cells and the activation of the cytoskeleton to manipulate the cell membrane into forming vesicles that can be drawn into or expelled from the cell. Together, modes of passive and active transport can form systems within cells that complete incredibly complex tasks!

One of the most ubiquitous processes in life is the generation of Adenosine Tri-phosphate molecules. ATP stores energy in the bonds between phosphate groups. When ATP is used, one of the phosphate groups breaks off and the energy from the bond can be applied to a number of other processes. This leaves a molecule of Adenosine Di-Phosphate, which can become ATP if energy is used to add another phosphate group.

In all organisms, the process of creating ATP molecules uses both active and passive transport.

ATP synthase – the enzyme that adds phosphate groups to ADP – is an integral membrane protein that harvests the energy present in the passive transport of hydrogen ions.

For this to happen, a hydrogen ion gradient must be established. This gradient is created in the intermembrane space of chloroplasts and mitochondria, and in the periplasmic space between the two membranes present in bacteria. To establish a gradient like this, cells and organelles need forms of active transport – like a proton pump.

A proton pump is the simplest form of active transport that can create a gradient. This simple system is found in many bacteria and uses the energy created by the breakdown of glucose and other molecules. The enzymes that break down glucose put the energy into a number of electron carriers such as NADH, which can then transfer that energy to the proton pump. The proton pump then uses the energy to pump hydrogen ions (or protons) into the intermembrane space.

While chloroplasts and mitochondria increase the efficiency of this process to create more ATP, each of these systems is essentially just a proton pump used to power ATP synthase. Chloroplasts simply use this ATP energy to generate more stable glucose molecules that can be stored and transferred between cells, while mitochondria break down the stored glucose molecules to create ATP on demand for the rest of the cell!

Bacterial cells use a number of different mechanisms of transport to import and export substances from their cells. Since bacterial cells are already so small, they do this mostly through the use of integral membrane proteins using both active and passive forms of transport. For instance, we’ve already seen how bacterial cells can create ATP using these types of transport. However, bacterial cells use thousands of different protein channels to carry out the functions of life.

For example, bacteria need to gather nutrients and expel waste products in order to grow and reproduce. If bacteria live in a hypotonic environment, they may need to actively transport things like glucose, amino acids, and other molecular building blocks into the cell. But, even bacterial cells use active and passive transport for more than just collecting nutrients.

Consider the flagella – even this mobility structure is driven by interactions between active and passive transport systems. On the inner membrane of the bacteria are a number of active transport proteins that are constantly pumping protons into the intermembrane space. This builds up a gradient, which stores energy. Then, some of these hydrogens are allowed to passively move through the motor proteins. As they do so, they transfer energy to these motor proteins. The motor proteins transfer this energy in order to spin the flagella, allowing the cell to move!

When you get to the level of Eukaryotic cells, the only real difference between these cells and bacteria is the presence of the endomembrane system and organelles found in eukaryotes. The endomembrane system is really like a cell within a cell. Consider a simple food vacuole.

A food vacuole is formed through endocytosis. After the process of phagocytosis, the food vacuole is moved inside the cell. A lysosome merges with the food vacuole, and the contents are digested. While we often visual food vacuoles as simple lipid bilayers, they are in fact embedded with tons of integral membrane proteins. Some of these proteins allow ions and molecules in the food vacuole to pass out of the lysosome down their concentration gradient via passive transport. Other proteins use energy via active transport to actively move substances like amino acids and glucose out of the food vacuole and into the cell.

Remember that food vacuoles are just one small example of the many different active and passive transport processes that take place in a eukaryotic cell. They are also essential for creating ATP energy, maintaining the cell’s water balance, and many other processes!

Plants and fungi, while they are very different types of organisms, use the mechanisms of transport in similar ways.

Plants and fungi both operate on the principle of turgor pressure. This internal cell pressure pushes against the cell walls, creating a rigid structure for the organism. In order to create and maintain turgor pressure, plants and fungi have to maintain their cells at a lower water potential than the surrounding environment in order for water to continuously flow into the cell. Since water potential can be lowered by adding solutes, plants and fungi pack their vacuoles with ions and solutes using active transport. Then, using a series of aquaporins and passive transport, these cells allow water to flow easily into the vacuole from outside the cell.

The turgor pressure that is created allows plant roots and fungi mycelium to push through the soil, while it also allows above-ground growth for both plants and mushrooms! Turgor pressure provides the rigidity these organisms need, while other active and passive mechanisms of transport allow the cell to utilize energy, reproduce DNA and cells, and grow larger!

When we look at the mechanisms of transport in animals, the only big difference seen in animals is the lack of a cell wall. But, the cells must use many different forms of active and passive transport to maintain the overall organism through processes that involve multiple cell types.

Animals use nerves to transfer signals. First, the nerve signal hits passive, voltage-gated ion channels in the sending nerve. This causes vesicles full of neurotransmitters to merge with the cell membrane, dumping the neurotransmitter molecules into the synaptic space via exocytosis. These neurotransmitters hit ligand-gated ion channels on the receiving proteins – causing them to open, cause an action potential, and send the signal through the receiving nerve.

An animal also needs to transport substances like oxygen and glucose to all the cells in its body. Oxygen and carbon dioxide are small, uncharged molecules that can easily diffuse through the cell membranes. But, larger, polar molecules like glucose need specific carrier proteins to carry them across the cells.

Animals also use complex patterns of active and passive transport in order to filter waste products out of their bodies. The nephrons in your kidneys are constantly manipulating water potential and ion concentrations in order to remove urea from your body and concentrate it into urine. In fact, the entire nephron is like a giant concentration gradient. Water and ions pass easily through the cell membranes in the Bowman’s capsule. As they descend into the Loop of Henle, they enter a much more concentrated region of the nephron. Cells in the downward Loop of Henle allow the passage of water, while cells in the ascending loop block the passage of water. This allows the urine to become very concentrated as it enters the collecting duct and heads toward the bladder.


MMB is a dynamic, interdisciplinary community focused on understanding biochemical, biophysical, and cellular mechanisms at the molecular level. The community seeks to enhance peer learning and faculty mentoring through a series of student work-in-progress presentations. This provides an opportunity for students to extend their breadth of knowledge and community beyond their coursework and thesis laboratories. MMB also facilitates professional development of student members through travel awards and an annual MMB symposium.

Key benefits of participating in MMB include:

  • Feedback on work-in-progress presentations
  • Peer learning with students in similar fields of study
  • Networking with students and faculty from different departments and programs
  • Opportunities for receiving mentoring from faculty and funding for travel
  • Participation in the annual MMB symposium, which attracts attendees from across HMS

Join us at the 2021 MMB Virtual Symposium on May 24, 2021, 9-11am!

Applications to join are typically accepted from interested students every December. The application deadline is always preceded by an information session held in November for prospective students to learn more about the MMB community and the research being performed by current MMB students.


Mechanisms of Behavior

Behavior faculty in the Evolution, Ecology, and Behavior (EEB) Program work on a wide range of questions related to mechanisms including hormonal, neural, genetic, immune, and developmental factors that contribute to behavioral regulation and behavioral phenotypes. Our experimental approaches range from long-term field studies to RNA interference, and include many things in between—such as neurophysiology, neuroanatomy, and behavioral genetics.

Our research is conducted within the broader contexts of evolution and ecology, and thus the highly collegial and interactive EEB group provides an excellent intellectual environment for our work, as does the interdisciplinary Center for the Integrative Studies of Animal Behavior (CISAB), which boasts more than 50 faculty affiliates from across the IU campus.

Graduate students who are interested in our Mechanisms of Behavior group typically apply to the EEB program, although some students may choose other programs in Biology.

Mechanism of Behavior Research Group Labs

Demas Lab

The primary focus of our laboratory is in the general area of “ecological physiology.” Specifically, we study of the interactions among the nervous, endocrine, and immune systems and the behavior in a variety of ecologically relevant environmental contexts.

For example, many nontropical organisms experience pronounced fluctuations in environmental conditions (e.g., day length, ambient temperature, food availability, social interactions) across the seasons of the year. Consequently, individuals of a wide range of species have evolved specific adaptive mechanisms to cope with seasonal fluctuations in the environment. These adaptations may be physiological (e.g., changes in energy balance, reproductive function, or immunity) or behavioral (e.g., changes in foraging, migration, aggression, or social behavior). 

The broad goal of our research is to identity the environmental and social factors contributing to seasonal changes in specific physiological and behavioral responses and to determine the neural, endocrine, and immune mechanisms underlying these changes. Although this research focuses primarily on rodent species (e.g., Siberian hamsters, deer mice, voles), we also address these questions in amphibian and avian species.

Hurley Lab

Sensory systems are gateways through which we receive information about the world around us. We may think that our senses indiscriminately respond to whatever happens in the environment, but sensory systems are very selective. Sensory organs themselves (and also the brain circuits that process sensory information) have an amazing ability to pick out the types of stimuli that are most important in a particular situation. Sensory neural circuits can even change the way that they process sensory cues in different behavioral states by responding to chemical signals that are released in the brain. The neuromodulator serotonin is one of these neurochemical signals.

Ketterson Lab

Our research group consists of graduate students and postdoctoral researchers who are all studying aspects of the biology of the dark-eyed junco, a songbird that is widely distributed across North America. The junco is a classic species in the study of seasonality, speciation, and mediation of phenotypic evolution by hormomes, and we have field populations under study in Virginia, South Dakota, and California and captive populations here in Indiana.

While unified by their study system, and their common interest in evolutionary biology and animal behavior, members of our group pursue research interests that are quite diverse. Examples include avian pheromones, immune function and differential migration, mechanisms of androgyny and the evolution of sexual dimorphism, song and speciation, the role of hormones in rapid evolution and phenotypic plasticity, seasonal differences in gene expression, the role of hormones in phenotypic integration, benefits of multiple mating by females, and neural correlates of female aggression.

Kingsbury-Goodson Lab

Research in our lab is focused on the evolution and function of social behavior circuits in the basal ("limbic") forebrain and midbrain. We are particularly interested in understanding how limbic circuits that are strongly conserved nonetheless give rise to massive species diversity in behavioral phenotypes, such as flocking and territoriality in birds. Neuromodulators of the vasopressin-oxytocin family are key to this diversity, and thus much of our work addresses the dynamic roles that neuromodulators play in social behavior.

Martins Lab

Our research is in the evolution of complex behavior. In particular, we are interested in the translation between processes acting on a generation time scale and the patterns seen across species. How do genetic, developmental, and evolutionary interactions among traits influence long-term change?

Moczek Lab

Our research focuses on a central question in biology: how do major phenotypic novelties originate and diversify in nature? In particular we are interested in the ecological, developmental, and genetic mechanisms, and the interactions between them, that drive evolutionary innovation and diversification. To tackle these issues from a variety of perspectives and at different levels of biological organization, we use approaches ranging from molecular developmental biology and genomics to quantitative genetics, comparative endocrinology, and behavioral ecology.

Rosvall Lab

Most behaviors are plastic traits, in that animals can modify their behavior to environmental conditions that shift over the course of minutes, hours, or seasonally. Many behaviors are nonetheless individually consistent, and behavior has long been hypothesized to be at the forefront of evolutionary change.

Research in the Rosvall Lab seeks to identify the genomic and physiological bases of behavioral adaptation and plasticity, and how these proximate mechanisms change over the course of evolutionary time. We approach these questions by combining conceptual and analytical tools from animal behavior, neuroendocrinology, evolutionary ecology, physiology, and genomics–primarily by studying free-living birds.

Smith Lab

The Smith Laboratory studies the evolution and physiology of sexually dimorphic communication behavior in South American ghost knifefishes. Ghost knifefish have electric organs that produce weak electrical signals used to detect nearby objects and to communicate. These signals provide an excellent system to study the evolution and physiology of sexual dimorphic behavior for several reasons. Electric communication signals are highly diverse both within and across species, and the magnitude of sex differences in signals varies across species.
Sex differences in electric communication behavior are regulated by gonadal steroid hormones (11-ketotestosterone and estradiol).

Finally, the neural circuits that control electric communication behavior are well-characterized and remarkably simple, which allows us to understand how hormonal and evolutionary changes in the brain and spinal cord are related to sex and species differences in behavior. We comparatively study the relationship between hormones, brain, and behavior by using a wide range of techniques including recording and playing back electric communication signals, hormone measurement and manipulation, immunohistochemistry, gene cloning and sequencing, molecular phylogenetics, and electrophysiology.


Mechanisms of Cancer Biology Program (MCBP)

The long-term goal of the Mechanisms of Cancer Biology Program (MCBP) is to identify and map the complex cellular mechanisms that drive cancer development, progression, and metastasis. To accomplish this goal, members of the MCBP are identifying factors (biochemical and physical), signaling pathways and the cellular basis for the communication between tumor and stromal cells that drives tumorigenesis. Together this approach will lay the framework for the design of specific therapeutic modalities. The MCBP is organized around two working groups termed the, (1) Cell Autonomous Cancer Drivers (CACD) and (2) Cancer Cell Nonautonomous Drivers (CCND). Recognizing the importance of the co-morbidities associated not only with the disease but the treatments deployed to fight it, MCBP is developing a third group referred to as Cancer Co-Morbidity Drivers (CCMD). Together these thematic groups include individuals working to discover how cell autonomous mutations and stromal cells, extracellular matrix structural proteins, growth factors, and cytokines interact to modulate tumorigenesis. Further, as cancer therapies become more effective at reducing mortality, cancer survivors are increasingly faced with therapy-induced co-morbidities that can significantly impact their quality of life. Thus, MCBP members also focus on the mechanisms that drive therapy-induced co-morbidities. The MCBP primarily performs basic cancer biology research and discovery, and is structured to interface with other programs within the Siteman Cancer Center (SCC) that are positioned to translate research breakthroughs into patient care, particularly in genetics, molecular and cellular cancer biology, and functional genomics. The MCBP members are currently developing a number of therapeutic drugs that were identified using this approach.

The MCBP has three specific aims.

  1. Identify the key cell autonomous changes within an incipient tumor cell that initiates tumorigenesis and drives tumor progression. To accomplish this Aim, we have developed a working group referred to as the Cell Autonomous Cancer Drivers (CACD). The MCBP members within this group focus on mutational, epigenetic and metabolomic drivers that arise within incipient cells and contribute to the transformation process, tumor progression, and development of therapy resistance.
  2. Identify key communication molecules and pathways that facilitate tumor-stromal interactions to affect tumor cell proliferation, survival, adhesion, motility, and therapy resistance. To accomplish this Aim, a second working group referred to as Cancer Cell Nonautonomous Drivers (CCND) is populated with individuals focused on understanding how the TME communicates with an incipient tumor cell to drive transformation, tumor progression, and therapy resistance. This group takes a broad view of the TME and focuses on cells and the structural (i.e., extracellular matrix) component of the TME.
  3. Translate MCBP basic science discoveries to the bedside by fostering intra-programmatic collaborations among MCBP researchers and clinician-scientists and by building an interface to foster inter-programmatic collaborations between MCBP working groups and translational investigators across all SCC research programs. Recognizing the importance of translating basic science findings to the clinic, members of MCBP are identifying putative therapeutic targets. In several instances, these targets are now moving towards clinical trials in collaboration with members of other SCC programs.

Fact and Figures:

  • MCBP has 40 members from 12 departments and three schools, and is supported by $15.1 million in funding, with $4.3 million from the NCI and $7.2 million from other peer-reviewed funding sources.
  • MCBP members published 711 peer-reviewed papers during 2014–2018, with 142 (20%) papers in journals with impact factors ≥10.
  • MCBP members also engaged in extensive collaborative interactions, with 172 (24%) inter- and 108 (15%) intra-programmatic publications.

Recorded program seminars and events are available at this link on WUSTL Box.


6. Discovery: From A-ha Moments to Discovery Strategies

6.1 Discovery via A-ha Moments

What can philosophers say about scientific discovery? Many logical empiricists had a simple answer: Nothing. According to Popper, for example, philosophers can illuminate the epistemology of testing, but they can say nothing of substance about how scientists generate the ideas to be tested (Popper 1959). Such &ldquoA-ha!&rdquo moments of creativity are in the province of psychology, not philosophy. Reichenbach distinguished the context of discovery from the context of justification (the &ldquocontext distinction&rdquo) (Reichenbach 1938 but see the entry on Hans Reichenbach for an alternate interpretation of this distinction). The process of scientific discovery was thus largely off limits to philosophers.

Not all philosophers of science agreed. Hanson, for example, articulated a logic of discovery involving abductive inferences from anomalous data to new hypotheses designed to account for them (Hanson 1958). Others focused on methodologies of discovery that could either allow one to rationally reconstruct why something was discoverable at a given time (Nickels 1985) or to explain why a new hypothesis is considered promising and worthy of further investigation (Schaffner 1993). Early contributions to the new mechanical philosophy followed this path and characterized investigative strategies scientists use to discover mechanisms (see the entry on scientific discovery).

6.2 Discovery via Strategies

Bechtel and Richardson&rsquos Discovering Complexity (2010 [1993]) is organized around a flowchart representing choice-points in the discovery of a mechanism. The process of searching for mechanisms begins with a provisional characterization of the phenomenon. Then follow strategies of localizing the mechanism within the system, and decomposing the phenomenon into distinct sub-functions. Localization of function involves determining which of these sub-functions of the system is performed by which parts. Bechtel and Richardson further characterize the use of excitatory and inhibitory experiments to obtain these kinds of information. Bechtel and Abrahamsen (2013) add a subsequent stage, in which scientists recompose what they have learned about the functional parts by putting them back together to produce the phenomenon in question (perhaps using simulations).

Darden also emphasized mechanisms as an important framework concept in scientific discovery (Darden 1980, 1982, 1986, 1991). In the discovery of protein synthesis (jointly investigated by molecular biologists and biochemists in the 1950s and 1960s), scientists didn&rsquot simply have an &ldquoA-ha&rdquo moment. Rather, they deployed strategies for revealing how a mechanism works (Darden 2006 Craver and Darden 2013). Darden characterizes the process of mechanism discovery as an &ldquoextended, piecemeal process with hypotheses undergoing iterative refinement&rdquo that process occurs via the construction, evaluation, and revision of mechanism schemas in light of observational and experimental constraints (Darden 2006: 272).

Darden&rsquos construction strategies are strategies for generating new hypotheses about a mechanism. In addition to decomposition and localization, Darden shows that scientists often borrow a schema type from another area of science, as when selection-type mechanisms were borrowed to understand how the immune system works, or assemble a mechanism from known modules of functional activity (modular sub-assembly), as is common in biochemistry and molecular biology. Sometimes, scientists know one part of the mechanism and attempt to work forward or backward through to the other parts and activities. In the discovery of the mechanism of protein synthesis, for example, molecular biologists worked forward from the structure of DNA to figure out what molecules could interact with it (forward chaining), and biochemists worked backward from proteins to figure out what chemical reactions would be necessary to create them (backward chaining). They met in the middle at RNA. Protein synthesis is now understood to involve transcribing DNA into RNA and then translating RNA into proteins. Far from being philosophically inscrutable, Darden points out that scientists used what they knew about the working entities and activities in the mechanism to infer what could come next or before in the mechanism of protein synthesis (Darden 2006 see also the entry on molecular biology).

Evaluation strategies, for Darden, involve constraint-based reasoning to limn the contours of the space of possible mechanisms for a given phenomenon. Often scientists reason about how a mechanism works by building off basic findings concerning the spatial and temporal organization of its parts. Harvey, for example, reasoned his way to the circulation of the blood by considering the locations of the valves of the veins and their orientation with respect to the heart. These organizational constraints, and many others, combined to narrow the space of possible mechanisms to a small region containing a model in which the blood completes a circuit of the body (Craver and Darden 2013).

Darden and Craver also discuss experimental strategies for learning how a mechanism works. These strategies reveal how different entities and activities in a mechanism act, interact, and are organized together. For example, one might intervene to remove a putative component to see if and how the mechanism functions in its absence (inhibitory experiments). Or one might stimulate that component to see if it can drive the mechanism or modulate its behavior. Or one might activate a mechanism by placing it in the precipitating conditions for the phenomenon and observe how the entity or activity changes as the mechanism works. Craver (2002) discusses these under the heading of &ldquointerlevel experiments&rdquo (see also Harinen forthcoming). Craver and Darden (2013) also discuss more complex kinds of experiments for learning what sort of entity or activity contributes to a process and for learning more complex features of a mechanism&rsquos organization.

Datteri (2009 Datteri and Tamburrini 2007), explores the use of robotic simulations for the purposes of testing mechanisms. They discuss both how assumptions are built into robotic models and how experiments can be designed to reveal how mechanisms work. This work extends the mechanistic framework into the area of bio-robotics and reveals a set of strategies distinct from those explored in Darden&rsquos work.

Rather than focusing on the process by which mechanism schemas are constructed, evaluated, and revised, Steele focuses on the question of how one extrapolates from a sample population or a model organism to the structure of a mechanism in the target. Will a treatment proven to suppress tumors in mice (a model organism) also suppress tumors in humans (the target population)? After developing a probabilistic account of mechanisms, Steele considers how researchers get around what he calls the extrapolator&rsquos circle: determining

how we could know that the model and the target are similar in causally relevant respects without already knowing the causal relationship in the target. (Steel 2008: 78)

Steel breaks the extrapolator&rsquos circle by developing a mechanisms-based extrapolation strategy&mdashthe strategy of comparative process tracing. Once a mechanism for some phenomenon has been elucidated in a model (such as a particular process of carcinogenesis in rats), scientists (toxicologists in this case) then compare key stages (particularly downstream stages) of the model with the stages in the target, paying particular attention to points in the process where differences are most likely to arise. The greater the similarities of the entities, activities, and organization of the mechanisms in both populations, the stronger is the basis for extrapolation the greater the differences, the weaker the basis (but see Howick et al. 2013 see also the sections on extrapolation in the entries on molecular biology and experiment in biology).

6.3 Mechanistic Evidence in Medical Discoveries

Discovery in medicine is another domain where the mechanical philosophy has been applied. Thagard draws on the case of H. pylori as a cause of ulcers to provide an account of how investigating mechanisms contributes to scientific discovery.

Thagard draws attention to both statistical evidence that suggests ulcers are somehow associated with H. pylori, as well as mechanistic evidence that can explain how the agent of infection could persist in a hostile environment long enough to cause an ulcer. More recently, philosophers interested in evidence-based medicine have probed the relationship between these two types of evidence in the health sciences. Russo and Williamson argue that both types of evidence are necessary to justify causal inference the correlational evidence establishes that there is a difference-making relation between some cause and some effect, while the mechanistic evidence establishes how exactly the cause produces its effect&mdashthe &ldquoRusso-Williamson Thesis&rdquo (Russo and Williamson 2007). Philosophers have since refined the Russo-Williamson Thesis, pointing out, for instance, that &ldquotype of evidence&rdquo could refer to different methodologies for gathering evidence or to different objects of evidence. Difference-making methodologies include observational studies and randomized controlled trials, while mechanistic methodologies include interventionist experiments such as those described above likewise, the object of evidence could be the evidence of an associated difference or it could be the evidence concerning the mechanism linking the cause and effect (Illari 2011 see also Campaner 2011). Evidence-based medicine hierarchies, which rank different kinds of evidence in terms of its epistemic strength, tend to prioritize evidence from difference-making methodologies (such as randomized controlled trials and meta-analyses) over mechanistic evidence in reply, these philosophers argue that the different types of evidence are on a par (each with its own strengths and weaknesses) and advocate for integrating difference-making and mechanistic evidence, a sentiment which aligns with the emphasis on mechanism integration discussed in Section 5.2 above (Clarke et al. 2013, 2014).

6.4 Philosophical Work to Be Done

Many mechanists have explored the strategies that scientists use in discovery. Bechtel and Richardson attended to decomposition and localization Darden and Craver highlighted forward and backward chaining Russo and Williamson emphasized drawing on both difference-making and mechanistic evidence. These strategies were found in specific, experimental sciences, such as neuroscience and molecular biology. So one task for philosophers moving forward is to assess whether or not similar strategies exist in other sciences, especially those that operate outside the traditional laboratory, both in the human sciences (such as sociology and economics) and in the physical sciences (such as cosmology).

We also expect tremendous development to come from bridging the gap between the qualitative accounts of mechanisms and mechanistic explanation developed in the new mechanism and quantitative theories of discovery from the discipline of machine learning and causal modeling (Spirtes et al. 2000 Pearl 2009). The latter offer tools to mine correlational data for causal dependencies. Such tools might escape more qualitative, historical approaches and might, in fact, go beyond the common strategies that scientists traditionally use. Such tools also offer a means to assess discovery strategies by exploring the conditions under which they succeed and fail and the efficiency with which they deliver verdicts on causal hypotheses.


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Watch the video: How Regulatory Mechanisms Control Reactions in Organisms in Biology: Biology u0026 DNA (January 2022).