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Serial Dilution and Absorbance Measurements - Lab Report Example

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This lab report "Serial Dilution and Absorbance Measurements" discusses diluting the provided solutions and subjecting them to absorption. The test aimed to determine the characteristics of absorption of Dextrin Dye solution at various concentrations…
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Extract of sample "Serial Dilution and Absorbance Measurements"

Title: Report on Experiment Name: Student No.: Course Code Institution Name: Instructor’s Name: Date of Submission: PART A Title: Serial dilution and absorbance measurements Introduction The experiment involved diluting the provided solutions and subjecting them to absorption, after which a spectrophotometer was used to measure their wavelengths. The test aimed to determine the characteristics of absorption of Dextrin Dye solution at various concentrations. Methods and Materials During the experiment, the absorbance of Blue Dextrin Dye was tested using a series of dilutions. An absorbance spectrum was then generated using a spectrophotometer. A set of 7 doubling dilutions was performed, from ½ to 1/128, using a solution containing 1% Blue Dextrin. The tubes were labelled accordingly and the experiment was performed in triplicate. The dilutions were mixed thoroughly using vortexing. 2ml was transferred from the second dilution tube to the next and the process was continued until the series was completed. Microtitre process was then performed starting from Row A, so that 100µl of each dilution was transferred to three consecutively numbered wells on the plate. In the consecutive wells in Row B, ½ dilutions were added by transferring ¼ dilutions. This process was continued until Row H was reached. The wells of the microtitre were examined and the absorbance of the wells was also measured using a microtitre plate reader. 630nm microtitre was selected before the dilution series was read. The absorbance spectrum was performed for the purpose of determining the best wavelength at which to measure the samples. Finally, graphs showing the absorbance of the solutions were drawn. Results For the microtitre plate map experiment, the values for the solutions were A: 2.431, B: 1.916, C: 1.051, D: 0.519, E: 0.268, F: 0.134, G: 0.068 and H: 0.These results are represented as shown graphically below:- Figure 1. microtitre values for various solutions There was a gradual reduction in microtitre values across the samples. The values of the average wavelengths were obtained and were found to be A: 0.9707, B: 0.516 C: 0.2737, D: 0.1587, E: 0.0977, F: 0.061, G: 0.048 and H: 0.033. It was observed that there was a gradual reduction in wavelength values across the samples, from A to H. Discussion and Conclusion According to the graph of absorption versus wavelength, it was concluded that absorption of Blue Dextran is low at lower wavelengths and high at higher wavelengths, with the maximum value obtained at a wavelength of 630nm, beyond which the absorption rate drops. There is a limitation to this experiment, which is that the accuracy of the results might have been influenced by the lack of accuracy of the spectrophotometer, thus affecting the analysis process (Timby, 2009). PART B Title: Relationship between body composition and heart rate Abstract In this study, various body compositions are compared with heart rates in order to establish the relationship between the two. The hypothesis is as follows: there is a relationship between body characteristics and heart rate. The study involved measuring the participants’ body characteristics, including percentage fat content, Body mass Index (BMI). Body height, body weight, age and heart-rate function. The results indicated a correlation between these various characteristics and the heart rate, as hypothesized. Introduction There is a need to understand the relationship between heart rate and body composition (for example, the age of a person, fat percentage in the body and body mass index, or BMI) where these characteristics result in an alteration of the heart rate (Smith & Fernhall, 2011). Despite scholarly interest in this subject area, few studies have been conducted to establish the relationship between body characteristics and heart rate. In addition, it has been observed that people in particular age groups are more likely to have a low heart rate compared with others (Plowman & Smith, 2014). This will be relevant to the study by providing a guide on the level of exercise that a person of a particular age group needs to participate in to maintain a normal heart rate. By understanding the relationship between heart rate and body characteristics, it will be possible to suggest the recommended body characteristics that contribute to a normal heart rate (Evans & White, 2008).  Aims of the research The aim of this study was to determine the relationship between heart rate and various body characteristics such as age, body fat percentage and BMI. Method This experiment involved measuring the body characteristics of 53 participants, who were healthy students. The main characteristics that were measured were age, height, weight, percentage fat content and heart rate index. To find the BMI of each student, the formula BMI= body mass (kg) / height (m2) was used. Percentage body fat was determined via skin folds in the triceps and sub-scapular locations. For women, the formula used was body fat % = 0.55 triceps + 0.31 subscapular + 6.13 (McArdle, Katch & Katch, 2010). For men, the formula body fat % = 0.43 triceps + 0.58 subscapula + 1.47 was utilized (Macfarlane, 2011). The participants were subjected to 3 minutes’ workload of 100 Watts on a Monark ergometer. The heart rates of the participants were measured by checking the pulses in their wrists or necks at rest, at the end of the exercise and 1 minute after the exercise. The heart function index (HFI) was then calculated using the formula HFI = (resting HR + end exercise HR + recovery HR at 1 min -200) / 10 (Johansson & Chinworth, 2012). The data from the experiments was used to obtain descriptive characteristics such as mean and standard deviation (SD). The importance of descriptive characteristics is that it enables understanding of characteristics such as changes in the variable being measured. The data was also analysed using a Pearson correlation, allowing the relationship between the variables and the heart rate to be understood. Results Descriptive characteristics for the various variables were Age: M 24.7, SD 8.0; Body Weight: M 70.8, SD 12.2; Height: M 1.7, SD 0.1; BMI: M 23.4, SD 3.2; % Body Fat: M 16.8, SD 5.9. Heart Rate Function was measured at M 12.4 and SD 3.9. These results are represented graphically below:- Figure 1. Descriptive statistics of variables in the study The results of the Pearson correlation enabled positive and negative correlations between the variables as well as their relationships with the heart rate to be observed. However, the main interest was in the relationship between the variables and the heart rates. These results are summarized in the table below:- % Body Fat Heart Rate BMI Age Body Weight % Body Fat 1 0.372** 0.459** 0.004 0.213 Heart Rate 0.372** 1 -0.050 -0.251 -0.145 BMI 0.459** -0.050 1 0.155 0.837** Age 0.004 -0.251 0.155 1 0.156 Body Weight 0.213 -0.145 0.837** 0.156 1 **. Correlation is significant at the 0.01 level (2 tailed) Table 1. Pearson correlations between variables Discussion and Conclusions When percentage body fats were compared with heart rates, it was found that there was a positive correlation of 0.372. This means that those who have a high percentage of fat in their bodies are likely to have a higher heart rate than those who have a low percentage of fat. This finding accords with the theory that the heart rate increases in order to break down excess fats to provide energy (Jevon & Ewens, 2012). Thus, the hypothesis that there is a positive relationship between percentage body fat and heart rate is accepted. The results of comparing BMI and heart rate show that the relationship has a negative correlation of -0,050. This implies that those who have a high BMI have low heart rates, while those who have a low BMI have low heart rates (Bothamley & Boyle, 2009). The data follows the theory that a high BMI, which is associated with obesity, affects heart functions by slowing down the heart rate (Ingram & Lavery, 2010). This data therefore results in a rejection of the hypothesis that there is a positive relationship between BMI and heart rate. When age was compared with heart rate, it was found that there was a negative correlation of -0.251. This suggests that those who are older have a lower heart rate compared with younger people (Clarkson, 2014). This idea fits with theoretical suggestions that younger people have higher heart rates due their greater involvement in activities that involve energy expenditure, whereas older people have low heart rates because they tend to take part in activities that do not involve such high energy expenditure (Safar, 2014; O'Rourke, 2014; Frohlich, 2014). This data leads to the rejection of the hypothesis that there is a positive relationship between age and heart rate. Finally, a comparison of body weight and heart rate resulted in a negative value of -0.145. This indicates that the more a person weighs, the lower their heart rate is. This contention is supported by theoretical arguments that increased body weight is characterized by low activity, which results in a low demand for energy and in low metabolic activity (Daube & Rubin, 2009). Ultimately, such factors cause a low heart rate and the reverse is also true for lower body weights (Townend, 2012). This information results in the rejection of the hypothesis that there is a positive relationship between body weight and heart rate. References Bothamley, J., & Boyle, M. (2009). Medical conditions affecting pregnancy and childbirth. Oxford: Radcliffe Pub. Clark, M., Lucett, S., Kirkendall, D. T., & National Academy of Sports Medicine. (2010).NASM's essentials of sports performance training. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins. Clarkson, S. (2014). Fit for birth and beyond: A guide for women over 35. Wollombi, NSW: Exisle Publishing. Daube, J. R., & Rubin, D. I. (2009). Clinical neurophysiology. New York: Oxford University Press. Evans, C. H., & White, R. D. (2008). Exercise stress testing for primary care and sports medicine. New York: Springer. Jevon, P., & Ewens, B. (2012). Monitoring the critically ill patient. Chichester, West Sussex: Wiley-Blackwell. Johansson, C., & Chinworth, S. A. (2012). Mobility in context: Principles of patient care skills. Philadelphia: F.A. Davis Company. Macfarlane, P. W. (2011). Comprehensive electrocardiology. London: Springer. McArdle, W. D., Katch, F. I., & Katch, V. L. (2010). Exercise physiology: Nutrition, energy, and human performance. Baltimore, MD: Lippincott Williams & Wilkins. Plowman, S. A., & Smith, D. L. (2014). Exercise physiology for health, fitness, and performance. Philadelphia: Wolters Kluwer/Lippincott Williams & Wilkins Health. Smith, D. L., & Fernhall, B. (2011). Advanced cardiovascular exercise physiology. Champaign, IL: Human Kinetics. Timby, B. K. (2009). Fundamental nursing skills and concepts. Philadelphia: Wolters Kluwer Health/Lippincott Williams & Wilkins. Townend, J. (2012). Practical Statistics for Environmental and Biological Scientists. Hoboken: John Wiley & Sons. Read More

PART B Title: Relationship between body composition and heart rate Abstract In this study, various body compositions are compared with heart rates in order to establish the relationship between the two. The hypothesis is as follows: there is a relationship between body characteristics and heart rate. The study involved measuring the participants’ body characteristics, including percentage fat content, Body mass Index (BMI). Body height, body weight, age and heart-rate function. The results indicated a correlation between these various characteristics and the heart rate, as hypothesized.

Introduction There is a need to understand the relationship between heart rate and body composition (for example, the age of a person, fat percentage in the body and body mass index, or BMI) where these characteristics result in an alteration of the heart rate (Smith & Fernhall, 2011). Despite scholarly interest in this subject area, few studies have been conducted to establish the relationship between body characteristics and heart rate. In addition, it has been observed that people in particular age groups are more likely to have a low heart rate compared with others (Plowman & Smith, 2014).

This will be relevant to the study by providing a guide on the level of exercise that a person of a particular age group needs to participate in to maintain a normal heart rate. By understanding the relationship between heart rate and body characteristics, it will be possible to suggest the recommended body characteristics that contribute to a normal heart rate (Evans & White, 2008).  Aims of the research The aim of this study was to determine the relationship between heart rate and various body characteristics such as age, body fat percentage and BMI.

Method This experiment involved measuring the body characteristics of 53 participants, who were healthy students. The main characteristics that were measured were age, height, weight, percentage fat content and heart rate index. To find the BMI of each student, the formula BMI= body mass (kg) / height (m2) was used. Percentage body fat was determined via skin folds in the triceps and sub-scapular locations. For women, the formula used was body fat % = 0.55 triceps + 0.31 subscapular + 6.13 (McArdle, Katch & Katch, 2010).

For men, the formula body fat % = 0.43 triceps + 0.58 subscapula + 1.47 was utilized (Macfarlane, 2011). The participants were subjected to 3 minutes’ workload of 100 Watts on a Monark ergometer. The heart rates of the participants were measured by checking the pulses in their wrists or necks at rest, at the end of the exercise and 1 minute after the exercise. The heart function index (HFI) was then calculated using the formula HFI = (resting HR + end exercise HR + recovery HR at 1 min -200) / 10 (Johansson & Chinworth, 2012).

The data from the experiments was used to obtain descriptive characteristics such as mean and standard deviation (SD). The importance of descriptive characteristics is that it enables understanding of characteristics such as changes in the variable being measured. The data was also analysed using a Pearson correlation, allowing the relationship between the variables and the heart rate to be understood. Results Descriptive characteristics for the various variables were Age: M 24.7, SD 8.0; Body Weight: M 70.8, SD 12.2; Height: M 1.7, SD 0.1; BMI: M 23.4, SD 3.2; % Body Fat: M 16.8, SD 5.9.

Heart Rate Function was measured at M 12.4 and SD 3.9. These results are represented graphically below:- Figure 1. Descriptive statistics of variables in the study The results of the Pearson correlation enabled positive and negative correlations between the variables as well as their relationships with the heart rate to be observed. However, the main interest was in the relationship between the variables and the heart rates. These results are summarized in the table below:- % Body Fat Heart Rate BMI Age Body Weight % Body Fat 1 0.372** 0.459** 0.004 0.213 Heart Rate 0.

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