bluuebunny/crossref_metadata_2025_split huggingface dataset:
Compartmental models and defining a model with a differential equation
Authors: Motulsky Harvey , Christopoulos Arthur 
Published: November 2023

Abstract
Let’s create a pharmacokinetic model that explains how the concentration of a drug in blood plasma declines over time. You inject a bolus of drug, and measure plasma drug levels at various times thereafter. The drug is metabolized by a liver enzyme that is far from fully saturated. In this situation, the rate of drug metabolism is proportional to the concentration of drug in the plasma. This is called.first-order kinetics. When the plasma concentration is cut in half, so is the rate of drug metabolism.
Generating confidence intervals by Monte Carlo simulations
Authors: Motulsky Harvey , Christopoulos Arthur 
Published: November 2023

Abstract
As discussed in the previous chapter, the asymptotic method built in to most nonlinear regression programs is only an approximate method to determine the confidence interval of a best-fit parameter. This chapter presents one alternative method, and the next chapter presents still another alternative method. The idea here is to simulate a bunch of data sets, each with different random scatter. Then fit each simulated data set to determine the best-fit values of the parameters. Finally, we’ll use the distribution of best-fit parameters among the simulated data sets to create confidence intervals.
Examples of comparing the fit of two models to one data set
Authors: Motulsky Harvey , Christopoulos Arthur 
Published: November 2023

Abstract
Look at the graph of the one site fit model (dashed curve). It seems to deviate systematically from the data points, but not so badly that we will reject the model completely. The graph of the two-site fit looks better. Do the best-fit values of the two-site model make sense? The best-fit two-site curve has a high affinity site with a logEC50 of-7.5 comprising 31% of the sites, and a low affinity site with a logEC50 of-6.1. These results are certainly scientifically plausible. Next we look at the confidence intervals, which are reasonably narrow (given so few data points). Because the results are sensible, it makes sense to compare the sum-of-squares statistically.
Using an unpaired t test to test for a treatment effect in a series of unmatched experiments
Authors: Motulsky Harvey , Christopoulos Arthur 
Published: November 2023

Abstract
We measured enzyme velocity as a function of substrate concentration in the presence and absence of a treatment. We had three control animals and three treated. We obtained tissue from each, and measured enzyme activity at various concentrations of substrate. All six curves were obtained at one time, with no pairing or matching between particular control and treated animals.
The law of mass action
Authors: Motulsky Harvey , Christopoulos Arthur 
Published: November 2023

Abstract
Analyses of radioligand binding experiments and enzyme kinetics are based on a simple molecular model called the law of mass action. This “law” states that the velocity of a chemical reaction is proportional to the product of the concentrations (or mass) of the reactants. In the simplest case, one kind of molecule is transformed into a different kind of molecule. The rate at which the reaction occurs is proportional to the concentration of the starting material.
The operational model of agonist action
Authors: Motulsky Harvey , Christopoulos Arthur 
Published: November 2023

Abstract
Fitting a standard sigmoidal (logistic) equation to a dose-response curve to determine EC50 (and perhaps slope factor) doesn’t tell you everything you want to know about an agonist. The problem is that the EC50 is determined by two properties of the agonist: A single dose-response experiment cannot untangle affinity from efficacy. Two very different drugs could have identical dose-response curves, with the same EC50 values and maximal responses (in the same tissue). One drug binds tightly with high affinity but has low efficacy, while the other binds with low affinity but has very high efficacy. Since the two dose-response curves are identical, there is no data analysis technique that can tell them apart. You need to analyze afamily of curves, not an individual curve, to determine the affinity and efficacy. The rest of this chapter explains how.
Linear regression with Prism
Authors: Motulsky Harvey , Christopoulos Arthur 
Published: November 2023

Abstract
You may force the regression line to go through a particular point such as the origin. In this case, Prism will determine only the best-fit slope, as the intercept will be fixed. Use this option when scientific theory tells you that the line must go through a particular point (usually the origin, X=o, Y=o) and you only want to know the slope. This situation arises rarely, and you should use common sense when making your decision. For example, consider a protein assay. You measure optical density (Y) for several known concentrations of protein in order to create a standard curve. You then want to interpolate unknown protein concentrations from that standard curve. When performing the assay, you adjusted the spectrophotometer so that it reads zero with zero protein. Therefore you might be tempted to force the regression line through the origin. But this constraint may result in a line that doesn’t fit the data well. Since you really care that the line fits the standards very well near the unknowns, you will probably get a better fit by not constraining the line.
Graphing a family of theoretical curves
Authors: Motulsky Harvey , Christopoulos Arthur 
Published: November 2023

Abstract
You’ll often find it useful to graph a theoretical curve, or a family of theoretical curves, as a way to understand the properties of the model. This is sometimes called “plotting a function”. This is different from fitting a curve with nonlinear regression. With nonlinear regression, you choose the equation and Prism finds the values of the parameters that make that equation fit your data the best. When plotting theoretical curves, you choose both the equation and the values of the parameters, and Prism graphs the function. You don’t need to enter any data, and there is no curve fitting involved.
Prognosis
Authors: Ahlskog J Eric 
Published: November 2023

Abstract
Initially being told that you have Parkinson’s disease (PD) can be devastating. Often the first thing that comes to mind is an image of a relative or an acquaintance with terrible, end-stage problems. We tend to remember worst- case scenarios. Hearing Parkinson’s disease may evoke a mental image of Uncle Frank with PD, who was in a wheelchair and died in a nursing home. However, someone in the workplace, still leading a full life after ten years of PD, may be forgotten. Furthermore, Uncle Frank may not have had PD but a disorder that only looks like PD, or possibly his course was complicated by a stroke. Also, Uncle Frank may have developed PD before effective medications became available.
The Causes of PD: What We Know and Where This is Leading Us
Authors: Ahlskog J Eric 
Published: November 2023

Abstract
As we have already seen, Parkinson’s disease (PD) is a neurodegenerative disorder, one of a variety of such conditions. To date, we have not identified the cause for any of them, despite major research efforts in laboratories and clinics around the world. For decades, theories have been proposed for the cause of PD, but with little support from hard facts. Blame has been placed on everything from viruses and bacteria to the food we eat. Each hypothesis has had enough supporting evidence to stimulate research, mostly leading to dead ends. We need credible clues to point us in the right direction. Clues are slowly accumulating, although some may be red herrings. However, the answer is probably buried in what we already know. The trick is to figure out which of the many pieces of evidence will lead us to the cause of PD. Let’s first review two areas of investigation that have been a central focus in the past ten to twenty years—the MPTP story and the oxidative stress hypothesis.
Medications for Movement Problems (Gait, Tremor, Slowness)
Authors: Ahlskog J Eric 
Published: November 2023

Abstract
Although we do not have drugs that affect the underlying cause or progression of Parkinson’s disease (PD), we have very good drugs for controlling many of the symptoms. The progression of PD is slow, and hence the symptomatic treatment is often gratifying for many years. Although the treatment of the symptoms is not always smooth or perfect, optimal adjustment of medications can typically keep people in the mainstream of their lives and turn back the clock on this disorder. This symptomatic treatment capitalizes on our understanding of brain chemistry. Thus there is a rational basis for the drugs, based on scientific principles. To appreciate the treatment principles and understand the role for the medications, we will first need to review some basics about relevant brain chemistry.
Starting Treatment of Movement Problems: Which Drug and When?
Authors: Ahlskog J Eric 
Published: November 2023

Abstract
Now we are ready to address practical issues. If you have read the previous chapters, you should have a good background for the subject of this chapter. Having Parkinson’s disease (PD) does not mean you must start on a medication. If we had drugs that slowed the progression of PD, then beginning them at the first sign of parkinsonism would obviously be important. Although some drugs have been touted to slow PD progression (such as pramipexole and ropinirole), compelling proof is lacking. Your symptoms determine when to start a medication for PD. If the symptoms don’t bother you, medications can be deferred. Sooner or later a medication will become necessary, but this can be put off until the symptoms get in the way.
Starting Dopamine Agonist Treatment
Authors: Ahlskog J Eric 
Published: November 2023

Abstract
In chapter 12, we considered principles and guidelines for starting carbidopa/ levodopa. Now we examine the use of dopamine agonist medications. As you read this chapter, you will recognize that many of the same principles that were discussed in this previous chapter also apply to dopamine agonist therapy. Dopamine agonists are used to treat Parkinson’s disease (PD) in two situations: • as the initial medication and (2) added to carbidopa/levodopa later in the course to help counter motor fluctuations. We will address both uses in this chapter, since the dosage guidelines are similar. In subsequent chapters we will look at levodopa-related motor fluctuations in more detail; when they demand dopamine agonist treatment, we will refer back to the guidelines in this chapter.
Movement Problems That Develop Later: Dyskinesias, Motor Fluctuations, and Treatment with Levodopa Adjustments
Authors: Ahlskog J Eric 
Published: November 2023

Abstract
More complex movement problems often surface after several years of carbidopa/levodopa treatment. This includes excessive movements (dyskinesias) as well as fluctuations in control of parkinsonism. These may be treated by adding one of several medications, and we will cover their use later in this book; however, the quickest and most expedient solution is often adjustment of the carbidopa/levodopa dosage, which will be our focus now. This will be easiest if you are taking the immediate-release form of carbidopa/ levodopa, but the same principles apply if you are using the sustained-release (Sinemet CR) formulation. The guidelines in this chapter are appropriate if you are taking carbidopa/ levodopa alone or with a dopamine agonist. If you are experiencing no substantial side effects from the agonist medication, we won’t change the dose. In this chapter, we will focus on carbidopa/levodopa adjustments and ignore the agonist.
Urinary Symptoms
Authors: Ahlskog J Eric 
Published: November 2023

Abstract
PD may cause problems with urination. Typically, this is not an early symptom and may never be a problem. However, when such symptoms develop, there are appropriate tests, consultations, treatments, and caveats to consider. When urinary symptoms develop in PD, they reflect problems in the bladder and structures connected to the bladder. Although the kidneys make the urine, kidney problems do not cause difficulties passing urine. The kidneys essentially filter the blood, extracting water and other products that need to be excreted. As the kidneys produce urine drop by drop, it passes down tubes to the reservoir that stores the urine. That reservoir is the bladder. The conduits from kidneys to bladder are called the ureters. When urine is released, it passes from the bladder through another conduit, the urethra. This anatomy is illustrated in figure 27.1. Normally urine is stored in the bladder until the brain is signaled that it is time to urinate.
Support and Advocacy Groups, and the Internet
Authors: Ahlskog J Eric 
Published: November 2023

Abstract
Many communities have well-organized Parkinson’s disease (PD) support groups that meet regularly. These meetings allow people with PD and their families to exchange information and share ideas for dealing with common problems. Frequently guest speakers (doctors, nurses, therapists, etc.) are invited to discuss topics of interest. These groups additionally provide a social outlet and a chance to meet people in similar circumstances. If you are un- aware of a PD support group in your community, check with your doctor’s office, clinic, or hospital for information.
Using Structural Equation Models to Validate Measures of Positive Emotions
Authors: Lucas Richard E 
Published: November 2023

Abstract
Positive emotions play an important role in a comprehensive positive psychology. First and foremost, positive emotions serve as an indicator that one’s life is on the right track. Diener and Lucas (2000) reviewed evidence that positive emotions are strongly related to individuals’ overall evaluations of their lives. By measuring positive emotions and correlating this outcome with various predictor variables, researchers can identify the characteristics that are necessary for a good life. In addition, by measuring positive emotions following interventions, researchers can determine the best ways to increase wellbeing. Thus, positive emotional experiences serve as a useful outcome variable in investigations of the good life.
Dolce Far Niente: The Positive Psychology of Personality Stability and Invariance
Authors: McCrae Robert R , Terracciano, Antonio , Khoury Brigitte 
Published: November 2023

Abstract
When Costa and McCrae first published their findings on the stability of personality in adulthood (Costa & McCrae, 1978, 1980b; Costa, McCrae, & Arenberg, 1980) the results were met not only with skepticism, but also with hostility and scorn. Developmentalist Orville Brim, in an interview in Psychology Today (Rubin, 1981), was quoted as saying “When you focus on stability ... you’re looking at the dregs-the people who have gotten stuck. You want to look at how a person grows and changes, not at how a person stays the same” (p. 24). Costa and McCrae were once half-jokingly introduced at a symposium as “the Antichrists of adult development.” Years later, when McCrae and Costa (1997b) showed constancy of personality trait factor structures across cultures, a similar reaction was evident in some quarters. As Bond (2000) wrote, “among many cross-cultural psychologists there is concern about importing tests developed out of a Western cultural logic ... into alien cultural systems. Berry (1969) labeled this an imposed etic strategy-it was imposed presumably because the test measuring the construct was pressed on the host culture, distorting and dominating its own voice; it was etic because it innocently presumed that the construct being measured was coherent and functioned similarly in all cultures” (p. 64).
Wisdom as a Classical Human Strength: Psychological Conceptualizations and Empirical Inquiry
Authors: Kunzmann Ute , Stange Antje 
Published: November 2023

Abstract
Positive psychologists value the investigation of positive traits and subjective experiences, including happiness, self-efficacy, and optimism (e.g., Aspinwall & Staudinger, 2003; Seligman & Csikszentmihalyi, 2000). The field of positive psychology would be incomplete, however, if it failed to incorporate human strengths such as empathy, altruism, or morality-even if these characteristics do not necessarily guarantee a constant experiencing of positive feelings, but rather require the ability to tolerate and make use of mixed and negative experiences, at least occasionally.
Hardiness as a Dispositional Resource: Methods of Conceptualizing the Construct
Authors: Wallace K A , Bergeman C S 
Published: November 2023

Abstract
Broadly defined, positive psychology encompasses the scientific examination of human strengths and virtues (Sheldon & King, 2001) at either a subjective, individual, or institutional level (Seligman & Csikszentmihalyi, 2000). Particularly relevant to the present chapter, the individual level concerns positive individual traits (i.e., positive personality traits), including, for example, forgiveness, spirituality, wisdom, and hardiness. In conjunction with researchers’ growing interest in the area of positive psychology and human strengths (Aspinwall & Staudinger, 2003a), there has been an increase in substantive work on various positive personality traits such as these (e.g., Baltes, Glueck, Kunzmann, 2002; Lightsey, 1996; McCullough, Pargament, & Thoresen, 2001; Pargament & Mahoney, 2002). Despite recent growth in the field of positive psychology (e.g., Keyes & Haidt, 2003), however, considerable research is needed concerning the conceptualization and measurement of positive psychological traits.
Exploring Cyclic Change in Emotion Using Item Response Models and Frequency Domain Analysis
Authors: Chow Sy-Miin , Grimm Kevin]. , Fujita, Frank , Ram Nilam 
Published: November 2023

Abstract
Effective mood regulation presupposes that affect and mood are dynamic and capable of change. Researchers have begun to conceptualize affect as dynamic processes (e.g., Carver & Scheier, 1990; Larsen, 2000). However, most of the analytic tools used in affect research are predominantly static. In other words, they do not account for any interdependencies in emotions that may exist over time. Very often, single-occasion factor analytic or correlational techniques are used to capture the relationships among different emotions at one point in time (e.g., Feldman Barrett, 1998; Tellegen, Watson, & Clark, 1999; Watson & Tellegen, 1985). Furthermore, even when such techniques are extended to examine how emotions unfold over time (e.g., Diener, Fujita, & Smith, 1995; Eid & Diener, 1999), they are limited in that they usually only capture linear change. Evidence is building that emotions exhibit nonlinear rather than linear patterns of change over time (e.g., diurnal and weekly cycles; Chow, Ram, Boker, Fujita, & Clore, 2005; Murray, Allen, Trinder, & Burgess, 2002; Larsen & Kasimatis, 1990; Rusting & Larsen, 1998). Taken together, these shortcomings suggest that researchers should expand the study of emotion to incorporate tools for capturing nonlinear (e.g., cyclic) change.
Multilevel Models of Change: Fundamental Concepts and Relationships to Mixed Models and Latent Growth-Curve Models
Authors: Maxwell Scott E , Tiberio Stacey S 
Published: November 2023

Abstract
In their classic article, Cronbach and Furby (1970) recommended that psychologists interested in studying change “frame their questions other ways” (p. 80). Fortunately, in the intervening years methodologists have taken up the challenge to develop better methods of understanding change. In the last two decades, new methods have appeared that offer not just new ways of analyzing data but, more important, fundamentally different conceptualizations of change itself.
Application of Latent Growth Analyses to Health Outcomes of Adolescent Girls
Authors: Ghisletta Paolo , Trickett Penelope K 
Published: November 2023

Abstract
This chapter accompanies the reader through three applications of latent growth analysis. The data utilized come from a longitudinal study on the interrelationships between puberty and sexual abuse in a sample of young women. First, we discuss a general modeling strategy when applying latent growth models (LGMs). We posit that the LGMs should not be tested immediately in their most complex specification, but as a series of increasingly complex models. Like any other structural equation model, this strategy allows examining a series of educated research hypotheses. We then proceed to demonstrate the most popular application of LGMs in psychological research: The examination of change in one variable measured directly. Two body appearance scales were analyzed independently to conclude that one was more sensitive to longitudinal change than the other. The second application concerned the simultaneous analyses of change in two variables. The two body appearance scales were this time analyzed simultaneously to conclude that much, but not all, of the information in the scales is shared between them. We further analyzed the two subscales to inquire about differences between the sexually abused and the nonabused subgroup.
Understanding Journeys: Growth- Curve Analysis as a Tool for Studying Individual Differences in Change Over Time
Authors: Norem Julie K , Andreas Jasmina Burdzovic 
Published: November 2023

Abstract
Imagine a race with three runners. Runner A crosses the finish line first, followed fairly closely by Runner B. Runner C finishes last. Studying how the winner of the race trained prior to the race, and the strategies she used while running, may reveal techniques that can improve results for other runners. If one is interested in running a good race, it makes good sense to study winners, and focusing on Runner A would seem the way to go.
Using Experience Sampling and Multilevel Modeling to Study Person-Situation lnteractionist Approaches to Positive Psychology
Authors: Fleeson William 
Published: November 2023

Abstract
The purpose of this chapter is to describe a method to study interactionism; this method may help rejuvenate interactionist approaches in psychology and may highlight the value of interactionism in positive psychology. Most broadly, interactionism is the view that both environmental and person factors are required for a complete understanding of psychological functioning and that the two factors often interact in producing behavior (Bowers, 1973; Lewin, 1935; Magnusson, 1999; Magnusson & Endler, 1977). Interactionism is valuable to developmental and to social psychology when those fields are interested in how environmental impacts depend on the characteristics and history of the individuals (Magnusson, 1999). Interactionism is valuable to personality psychology as a way to characterize personality in terms of unique responses to situations and as a potential solution to the problems for pure trait or pure situation approaches (Magnusson, 1999). Finally, interactionism is valuable to positive psychology because one of the ways people attain the good life is through flexibly adapting their behavior in situations to accomplish their goals (Magnusson & Mahoney, 2003; Seligman, 2003).