Lab Instructions_ Physiology Act I Mission Memo (Spring A 2024 Onward) 2

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Apr 27, 2024

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Lab Instructions: Physiology Act I Mission Memo Greetings Fellow Explorer: Despite your efforts to treat Xor, she remains weak and disoriented. To make matters worse, the herd will not leave Xor to continue on its journey. If we cannot help Xor recover quickly, the other megaraffe's will soon be in danger. Having ruled out dehydration as a cause of Xor's symptoms, three potential causes remain: (1) a low concentration of oxygen in the blood, (2) a low concentration of carbohydrates in the blood, and (3) a high blood pressure in the arteries. You must investigate the homeostatic systems that regulate these three variables in a megaraffe. Use the following questions to guide your work. ● How does a megaraffe regulate variables in the body that affect the reactions needed to survive? (Appendix 1) ● How should we treat Xor if one of her homeostatic systems has failed? (Appendix 2) The appendices to this mission memo will guide you in answering these questions. Once you have completed your analyses, report your conclusions via Canvas before returning to the Sanctuary. Do not underestimate the urgency of your work. Universally in your debt,

The AI Appendix 1 How does a megaraffe regulate variables in the body that affect the reactions needed to survive? To survive, an organism must regulate many variables in the body that affect the chemical reactions of life. For example, a megaraffe must ensure that its blood carries suﬃcient resources to all cells of the body. These resources include carbohydrates and oxygen (O 2 ), which are needed to fuel critical reactions in cells. If an organism cannot deliver enough of these resources, illness, or even death could occur. Xor's disorientation might have resulted from a failure to regulate the concentration of O 2 [O 2 ], or carbohydrates in her blood, or a failure to maintain a blood pressure needed for the blood to carry these resources to cells. The regulation of blood O 2 concentration, blood carbohydrate concentration, and blood pressure is critical to the survival of a megaraffe. On earth, systems of cells, tissues, and organs in every large, multicellular organism collaborate to maintain these variables within a narrow range needed to sustain life. The process of regulation, called homeostasis , is how organisms such as megaraffes keep their internal conditions within limits necessary for survival. To diagnose whether Xor's symptoms stem from a failure to regulate the concentration of [O 2 ], concentration of carbohydrates, or blood pressure, we must use a path model of a homeostatic system. Let's start by making sure that we’re interpreting a path model correctly. We’ll practice interpreting a path model of a homeostatic system that regulates the concentration of O 2 in the blood of megaraffes. We need to complete the following step to understand how megaraffes regulate the O 2 concentration in their blood. Step 1: Interpret a path model: Interpret a path model of a homeostatic system that regulates O 2 concentration in the blood of megaraffes. This step will prepare us to diagnose potential causes of Xor's condition and determine the appropriate treatment.

Step 1: Interpret a path model All organisms, from the smallest bacteria to the largest species in the universe, need to maintain a relatively constant internal environment despite a changing external environment. The process by which organisms maintain a consistent internal environment is called homeostasis. What is homeostasis? Homeostasis is the process by which organisms maintain a relatively stable internal environment in an ever-changing external environment. Like any system, homeostatic systems involve a set of components that interact to achieve a desired outcome. In this case, the outcome is the regulation of a variable within a range required to sustain life; the mean value of a regulated variable is called a set point , reﬂecting the idea that the organism attempts to set the value of the variable at that point. Examples of regulated variables in humans include blood O 2 concentration, blood glucose concentration, blood pressure, and body temperature. How does an organism detect when the value of a variable deviates from the set point and return the variable to the set point? First, the system must have a component called a sensor , which measures the magnitude of the regulated variable. A sensor relays information about the magnitude of a variable to a component called the integrator . The integrator sums the information from all sensors and responds by activating a component that can return the regulated variable to the set point. How does the integrator cause the variable to return to the set point? Depending on the information that the integrator receives from the sensors, it sends its own signals to cells called effectors . These signals cause the effectors to function in a way that returns the variable to the set point. To summarize, a homeostatic system with a sensor, integrator, and effector detects a change in the value of a variable and counteracts that change, restoring the initial value. Because the change caused by a homeostatic system opposes the direction of the initial change, a homeostatic system is also called a negative feedback loop . Figure 1 shows a generic path model of a homeostatic system as a set of boxes and arrows. The regulated variable is represented with a dashed black box containing black

text. Each component of the system is represented by a black box containing black text. These boxes state the action of the component and include the name of the component within the box - e.g., sensor, integrator, effector 1 and effector 2. In practice, the activity of each component would be measured by a specific variable; for example, a sensor's activity might be measured by the rate of electrical impulses fired by a nerve cell. Additionally, that sensor would not be labeled as a “sensor” but rather would be labeled as the name of the cell or tissues. In this example, we would call the sensor a nerve cell. An arrow connecting one box to another indicates a relationship between two components. The direction of the arrow tells us about cause and effect; for example, the arrow pointing from the sensor's box to the integrator's box tells us that the activity of the sensor directly affects the activity of the integrator. When modeling this relationship, we can think of the activity of the sensor as an independent variable and the activity of the integrator as a dependent variable.

Figure 1. Path model of a generic homeostatic system. The variable being regulated is represented by a dashed black box containing black text. Each variable and the physical component associated with that variable in the model is represented by a black box containing black text. There are four components in the model: a sensor, an integrator, and two effectors (effector 1 and effector 2). An arrow connecting one box to another indicates a relationship between two variables. There is an arrow pointing from the regulated variable to the activity of the sensor, from the activity of the sensor to the activity of the integrator, from the activity of the integrator to the activity of effector 1, from the activity of the integrator to the activity of effector 2, and from the activity of each effector to the regulated variable. However, Figure 1 is incomplete. Recall that in Figure 1, the activity of the sensor affects the activity of the integrator. But how? Does the activity of the integrator increase or decrease as the activity of the sensor increases? In Figure 2, you’ll notice that each arrow now has a symbol indicating whether the relationship between the variables is positive (+) or negative (-).

Figure 2. Path model of a generic homeostatic system. The variable being regulated is represented by a dashed black box containing black text. Each variable and the physical component associated with that variable in the model is represented by a black box containing black text. There are four components in the model: a sensor, an integrator, and two effectors (effector 1 and effector 2). An arrow connecting one box to another indicates a relationship between two variables. A “+” or “-” symbol over each arrow indicates whether the relationship between two variables is a positive relationship or a negative relationship, respectively. There is an arrow pointing from the regulated variable to the activity of the sensor with a “+” symbol over it, from the activity of the sensor to the activity of the integrator with a “+” symbol over it, from the activity of the integrator to the activity of effector 1 with a “+” symbol over it, from the activity of the integrator to the activity of effector 2 with a “-” symbol over it, and from the activity of each effector to the regulated variable. The arrow pointing from the activity of effector 1 to the regulated variable has a “+” symbol over it. The arrow pointing from the activity of effector 2 to the regulated variable has a “-” symbol over it. For a positive relationship (“+” symbol), the activity of the dependent component increases as the activity of the independent component increases . Remember, a positive relationship also means that the activity of the dependent component decreases as the activity of the independent component decreases (Figure 3a). For a negative relationship, the activity of the dependent component decreases as the activity of the independent component increases . Remember, a negative relationship also means that the activity of the dependent component increases as the activity of the independent component decreases (Figure 3b).

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