Category: Sciences 2502

Introduction

An identification process of protein that is accurate is required to be able to produce quantitative proteomics; this process is mostly carried out by searching automated softwares, they track the sequence of the database which contains mass spectra tandem of peptides, if these peptides do not have enough data, the software will most likely give results of peptide specifications that are not accurate. This makes manual analysis a more suitable alternative while inspecting the spectra mass. Though the disadvantages with the method are that it is time-consuming and that an experienced analyst is required to be able to make accurate results it does give an assurance that the results are accurate (Chen 2005, 1)

Sample case

Results from software are not always accurate and manual knowledge is required to be able to verify the peptide identifications, hence manual analysis of mass spectrometry data becomes vital at this point. For instance, a study done in the Department of Biochemistry and Molecular Biology at Colorado state university, whereby they used multiple protocols to make phosphopeptides rich, involving intense filtration during the flow of the work, was applied to analyze the samples that were obtained. the enriched phosphopeptides were from cultured renal that had been extracted from a rats proximal tubule (Nicholas 2011, 1)., applying three protocols that are mostly used and also a method that is dual, this method puts together separated immobile metal affinity chromatography and also TiO(2) which is titanium double oxide chromatography which is also referred to as dual IMAC or in short as(DIMAC) (Colleen 2005, 1). Phosphopeptides that were achieved from the four strategies of enrichment were put through an analysis process, by using liquid chromatography- multiple strata of mass spectrometry neutral-loss scanning, putting into use an ion trap that is of linear mass spectrometer. At first, the results from mass spectrometry (2) and mass spectrometry (3) spectra were put under an analysis by using the software peptide prophet and also making use of the search engine database thresholds which produced a false discovery rate (FDR) of less than 1.5 percent when it was put in search against a database that was reversed. Only 40 percent of the potential phosphopeptides brought positive similar results to a manual validation that was carried out, hence the combined analytical methods resulted in 110 affirmatively identified phosphopeptides (Colleen 2005, 1). Applying less rigorous initial filtering baselines, including a hundred and eleven (111) novel phosphorylation sites, were affirmed. Hence the conventional manner of data filtering in a range of widely agreed FDRs was not adequate to carry out analysis of phosphopeptides spectra that are of low resolution. Regarding this fact it is clear that having knowledge of manual analysis of mass spectrometry data is essential in order to correctly be able to use automated mass spectrometric database search programs. We can see that the combined streamline of front-ended enrichment approach and intense manual validation of spectra did allow for affirmative phosphopeptides identifications which were obtained from a sample that is complex using a low-resolution mass spectrometer ion trap (Chen 2005, 1).

Discussion

Using automated mass spectrometric database searching programs has its disadvantages due to the amount of data required to come up with accurate results it is important to look at some disadvantages associated with the use of automated mass spectrometric database searching programs (Colleen 2005, 1).

The science associated with life research has increased its focus on a systematic way of identifying and quantifying proteins that are expressed in a cell so that a comprehensive, characterized total protein at the cell level can be achieved. More focus has been put on the study of the property of the proteins that include state of modification, s protein to protein interaction, and also where the protein is located within the cell. Present technologies used for the study of proteomics are founded on the basis of various separation technologies which are then followed by the process of identifying the proteins that are separated by the use of mass spectrometry (Nicholas 2011, 1). Currently high-resolution separation technique, which is commonly used is a two-dimension (2D) gel of electrophoresis which can give proteins that are in their state obtained from samples that are complex in nature. Mass spectrometry and sequential database searching are used to identify the spots of the protein that are in the gel. Both are assisted by a matrix laser desorption or ionization period of flight mass spectrometry and also ionization electrospray of mass spectrometry is widely used for protein, there is an identification process that is of a large scale, this is done by peptide mass mapping, in this case the proteolyptic peptide mass is put into a matching process comparing them with resulting calculations from database of the proteins. For the reason of its simplicity and also the relatively high throughput of the sample, it is commonly matrix-assisted laser desorption spectrometry which is commonly applied as a method of screening. Throughput of more than a hundred separated gel from protein sample has been witnessed within a day. The short fail of these techniques is that false or else ambiguous identification of protein can occur, with gel spots that are not resolved; there are also gel interferences, modifications of proteins and mutation points of proteins. More limitations of this approach are the incapability to provide accurate analysis quantitation and transitional modifications sites. With this limitation it is important that one understands manual analysis of mass spectrometry data, it is essential to correctly use automated mass spectrometric database searching programs (Goldstrohm 2011, 1)

Significant numbers of human genome and other kinds of genomes have been put into sequences, at a level of expression of each gene in the protein, they are put into a monitoring position by use of numerous technologies in DNA chips; researchers have turned into distribution profile analysis of thousands of proteins that have been encoded by these Genomes, also known proteomes. Mass spectrometry has gained popularity as the method by which researchers use it to obtain this daunting task. Mass spectrometry-based proteomics brings into combination ionization of peptide and technologies of fragmentation together with available databases for gene sequences to be able to identify the content of the protein from complex samples in biology, for instance an entire cell. In the process of Mass spectrometry analysis which was performed by a Spectrometry Group under the leadership of Damarys.L at the Curie institute, saw hundreds of fragmented peptide spectra are produced and put through an interpretation process, making use of a software known as MASCOT(Chen 2005, 1). With this it is possible for a single spectrum to be interpreted up to ten peptide sequences that are compatible with numerous proteins (Goldstrohm 2011, 1).

Regardless of the process described above manual validation was used to achieve accurate interpretations by the Mass spectrometry specialist (Nicholas 2011, 1). Manual process of validation for Mass spectrometry identification of peptide is a crucial evaluation procedure, this calls for experts to know how to apply because of the presence of a large number of genome endeavors, the process of manual validating is an irreversible process, analyst must have this knowledge to be able to use automated mass spectrometric database search programs. A major challenge in the identification of peptides from mixtures that are complex by use of shotgun proteomics is the capacity of the programs used for searching, to accurately be able to give peptide sequences by use of fragmented spectra of Mass spectrometry. Manual validation is critical for assessing the identification of borderline (Nicholas 2011, 1). Manual validation is important in a case like that of Label-free shotgun genomics, in particular where it has been a challenge in high requirement for computational ability to carry out activities like, detection of feature and alignment resulting from the complexity of genomics systems. A lot of software has been developed in the past years to aid this procedure but it has not yet been clarified to the users of this software if this software does obtain information from raw data in the right way and whether this data is in its completeness (Colleen 2005, 1).

While not denying that analysis for Mass spectrometry of phosphorylation has become more powerful over the past ten years and has also been used in various systems that are biological, a major challenge facing the community dealing with issues of phosphoproteomics and also the proteomics sector is the accuracy and quality of data that is generated in large scale. For instance, when protein is to be identified in a sample, the solution does require numerous peptides per protein which removes the possibility of identifying a single peptide based on a single assignment (Goldstrohm 2011, 1). This has a risk of increasing false positives within the given data set. Incidentally most of the data of phosphoproteomics does fall in the latter description, as site phosphorylation which will mostly be represented by a tryptic peptide that is single in form. It does give accurate results using protocols of manual of validating to assure that accurate peptide and also site of phosphorylation assignment for individual Mass spectrometry spectra (Chen 2005, 1).

Conclusion

These facts do make it clear that technology as far biotechnology is concerned has improved tremendously but it does remain clear that the success of these software tools do require enough data and also data that is accurate so that results achieved can be credible, there is a tendency for a lot of professions to abandon the conventional methods of attaining certain required results, while in most cases the convectional methods have become obsolete due to the efficiency brought about by advancing technology, it seems not to be the case as far as mass- spectrometry analysis is concerned. Emerging experts in the field should find it important to know manual validation of peptide sequence and also tyrosine phosphorylation peptide mass-spectrometer (Colleen 2005, 1). Understanding manual analysis of mass spectrometry data is essential to correctly use automated mass spectrometric database searching programs for experts because, it is evident that results acquired from software tools cannot be entirely accredited 100% accuracy and hence expertise without the knowledge of manual analysis of mass spectrometry is most likely to result to giving inaccurate results, of which can be detrimental to research hence dire consequences.

Avoiding emerging technology as far as analysis of mass spectrometry data is concerned is not the way forward but having an understanding of manual analysis of mass spectrometry data is essential to correctly use automated mass spectrometric database searching programs this way it remains true that the results form analysis can be presented confidently

References

Chen, Y. 2005, Integrated approach for manual evaluation of peptides identified by searching protein sequence databases with tandem mass spectra,, Web.

Colleen, K, 2005, Characterization of a Fully Automated Nanoelectrospray system with Mass spectromic Detection for Proteomic Analysis. Newyork: Advion Biosciences,Inc.

Goldstrohm, D. 2011, Importance of manual validation for the identification of phosphopetides using a linear ion trap mass spectrometer, Web.

Nicholas, M. 2011, Manual validation of peptide sequence and sites of tyrosine phosphorylation from MS/MS spectra, Web.

As the name of the seventh chapter of Moral Choices suggests, Rae talks about biotechnology, genetics, and human cloning. He generally discusses the various ways professionals perform genetic testing, and, as the result, the ways they determine whether a person or a child has a predisposition to a specific genetic disorder. In addition, he analyzes the ways of treating these disorders and discovers the topic of human cloning. While highlighting the fact that the world of biotechnology is here to stay and the science will continue to advance in the future, he largely focuses on the moral dilemmas and concerns that individuals might develop and mentions that they will only become more complicated and harder to resolve. Consequently, this chapter is not only a look on the present time but also the analysis of what will happen in the future.

I found this chapter extremely interesting to read as every section was described in detail and based on examples. By including theoretical real-life examples, the author of the book gave his readers a possibility to apply the discussed information to their life and evaluate how they would react and act in these specific conditions. For this reason, the reading appeared to be relevant for the people who were reading it because they understood that, for instance, any couple can find itself in the situation when they have to decide whether they should perform and abortion or have their child no matter what genetic disease they have.

As I mentioned earlier, I really liked the reading, and this is primarily due to the fact that is valuable for the life for every individual who lives in the contemporary world. I do agree with the author that the moral concerns that arise as a result of this discussions are extremely sophisticated and require a lot of thought. What I truly believe is that everything in life is subjective and every individual has the right to act according to their personal beliefs and opinions. For example, if the parents feel that they child, who tested positive for Down syndrome, will have complications in the future and they will not be able to take care of him properly and; therefore, decide to go through an abortion, it is their personal choice and it can exist. Whatever the situation, we should prevent ourselves from judging because we never know the full story behind their decision.

One subtopic that I did not like in the chapter concerned human cloning. Despite the positive intentions that individuals, who want to perform these procedures, have, I do not think that it is even somewhat relatable to the individual values and ethical norms of the modern world. I am truly for various reproductive procedures that can help people with health complications to have children; however, I am against these procedures and human cloning for the purposes that are connected to making profit and bringing money to someones wallet. One important thing that I learned from the chapter it that every person should decide for himself whether they want to have a genetic testing or learn if their future child will have complications after birth. No one should feel obliged or pressured to do something they do not want.

Reference

Rae, S. B. (2018). Moral choices: An introduction to ethics (4th ed.). Zondervan.

It goes without saying that the functioning of the human organism is a complicated process. Cells are mainly categorized as either eukaryotic or prokaryotic. Regardless of the classification, both prokaryotic and eukaryotic cells share a lot in common. Both of them are surrounded by a semi-permeable plasma membrane that has a bilayer of phospholipids. This plasma membrane contains cytoplasm that is majorly made up of fluid and organelles. Bacteria that fall in the kingdom Monera is the most recognized member of the prokaryotes. The prokaryotes have DNA that is not enclosed in a nuclear envelope that other prokaryotic cells have. The prokaryotes, as opposed to other prokaryotic cells, do not have some other organelles like the mitochondrion that helps in the energy transduction process and the chloroplast. Apart from bacteria that are classified as prokaryotes, the other members of the four kingdoms are categorized as eukaryotes.

Eukaryotes have a true nucleus that has a true nuclear envelope that is bilayer. The nucleus is where genetic material is located. The nucleus in both eukaryotic and prokaryotic cells helps in directing cells chemical activities. The eukaryotic nucleus has a long of chromatin containing DNA and corresponding proteins. There is the lumen, a space that separates two membranes. The prolongation of the lumen is the Endoplasmic reticulum. There are types of endoplasmic reticulum: rough and smooth. The rough endoplasmic reticulum is closer to the nucleus than the smooth endoplasmic reticulum. Smooth endoplasmic reticulum forms a site where proteins are manufactured and stored before they are transported to other destinations in the cells. Vesicles, which exist as pieces of smooth endoplasmic reticulum, run from the smooth ER to other parts of the cells where they deliver their contents.

Rough endoplasmic reticula have ribosomes attached to their surfaces. These organelles help in protein synthesis. Without ribosomes, protein synthesis within the cells. Ribosomes are made up of RNA and proteins that are manufactured in the nucleus from where they are transported to the cytoplasm. The chemical composition of the prokaryotic and eukaryotic ribosomes are different hence the ability of certain antibiotics like tetracycline and streptomycin to interfere with the bacterial ribosomes capability to synthesize protein without interfering with the host cells ribosomes.

Vacuoles and vesicles are storage organelles. However, vacuoles differ from the size of the vesicles. Plant cells are synonymous with a large central vacuole that occupies the largest portion of the cell. It is basically used for storing an assortment of molecules. Contractile, found in Paramecium, helps in the secretion of water from the cell. Compared to the vacuole, vesicles have a very small size and have an important role in moving the elements within the cell. In fact, vesicles can also move to the Golgi apparatus, which is a membrane structure of the eukaryotic cells, organelle, mainly designed to remove substances that are synthesized in the endoplasmic reticulum.

Golgi bodies do a controlling function within the cell. Materials that are received like the vesicles become one entity with the Golgi body and then sent to various sections of the cell. The Golgi apparatus is the storage of some elements and materials that, in turn, participate in different reactions.

Many eukaryotic cells have mitochondrion. Mitochondrion helps in cellular respiration. They have a double membrane with an outer smoother membrane and an inner membrane that is folded into cristae. Intermembrane space is the space between the two membranes. The space that exists inside the inner membrane is known the as mitochondrion matrix.

Chloroplasts are never found in animal cells as they mainly function in plant cells helping to transform light energy to chemical energy. To facilitate this important function, Chloroplasts have chlorophyll, a green pigment that helps in energy formation. Intermembrane space divides chloroplasts from each other. Studies suggest that mitochondrion and chloroplasts may have arisen from prokaryotic invaders bearing that these two organelles have their own genetic material separate from that found in the nucleus. These organelles are capable of controlling their own protein synthesis and replication at the same time. Some other evidence that has been adduced include the fact that they are surrounded by bilayer membranes. In the process, one membrane comes from the invading cell and the other one from the plasma membrane.

Another organelle is the cytoskeleton whose building units are special proteins. Globular proteins are provided with microtubules. Cilia, flagella, and centrioles are mainly the only places it may be found in. Microtubules are arranged in a nine-plus-two formula in cilia and flagellum as opposed the to 9-sets-of-3 arrangement in centrioles. Microfilaments also comprise the cytoskeletons.

Cells do secret hormones or cytokines that communicate with the cells far away from where they are. This is a hormone signaling mechanism and is a very common means of communication among eukaryotic cells. Communication can also take place through the Juxtacrine mechanism where molecules on the surface of a target cell can be sensed by a cell closer to it. This is very important in immune cell activation and extravasations.

A hypothesis testing process consists of four consecutive steps that present a logical basis for decision-making concerning the validity of a hypothesis. In particular, the first step is stating the hypotheses, where a null hypothesis implies that there is no relationship between the variables. The alternative hypothesis implies that there is a relationship or dependence in the general population. The second step of hypothesis testing is setting the criteria for the decision. It deals with determining the significance level, which might be either alpha level or critical region. The third step includes the data collection process and sample statistics computing. During the third step, objective data analysis is performed that allows identifying the position of the sample within the set criteria. Finally, the fourth step implies making a decision based on the computed sample statistics results.

Alpha level and critical region are essential in hypothesis testing since the position of the sample in either of these levels predetermines whether the hypothesis is rejected or proven. When making a decision concerning a hypothesis, the researcher should determine how far the sample is from the null hypothesis value to prove the alternative hypothesis. However, if the sample is within the alpha level, it means that a null hypothesis cannot be rejected. On the contrary, if the sample is within a critical region, a null hypothesis is rejected.

If the difference between the sample mean and the original population mean increases, the value of the z-score increases. The increase of the population standard deviation leads to the decrease of the z-score value in hypothesis testing. The z-score value increases with the increase in sample size and the number of scores in the sample.

Null hypothesis: Studying from the screen has no effect on students quiz scores.

1. Step 1: Null hypothesis: There is no dependence between screen studying and students quiz scores.
   Alternative hypothesis: Students studying from the screen have lower quiz scores.
2. Step 2: The null hypothesis might be rejected if the samples final exam score reaches the level of 77, given that the alpha is.05.
   Thus, H0: ¼ =77; Ha: ¼ `77.
3. Step 3. To calculate the sample statistics, the following z-score formula is used Z = (M-¼)/(Ã/ n). œ stands for the sample mean, ¼ stands for the original population mean, and à stands for standard deviation. Given the values, the calculation of the z-score is as follows: Z= (72.5  77)/(8/4)=-2.25.
4. Step 4: Since the alpha level was assumed.05, the identified z-score is placed far from the alpha level, which allows for rejecting the null hypothesis. The testing shows that there is a significant relationship between screen studying and students quiz scores.

   • Hypothesis testing: H0: µ = 50; Ha: ¼ ` 50.
     To test the hypothesis, the z-score formula should be applied: Z = (M-¼)/(Ã/ n).
     Z= (53.8-50)/(15/10) = 2.53.
     The evidence is sufficient to make a conclusion that self-esteem scores for these adolescents are significantly different from those of the general population.
   • To compute the size of difference using Cohens d, one should divide the mean difference by standard deviation. Thus, 3.8/15=0.25. This value is considered a small effect size.
   • The sample provides enough evidence to prove the hypothesis based on the calculated z-score; Cohens d indicates a small size of the difference.

According to Nizet and Arnold, GAS (Group A streptococcus) is has the scientific name of Streptococcus pyogenes, the only species that exists in the beta-hemolytics group of streptococci (698). Streptococcus is a gram-positive bacterium that develops in the form of chains, predominantly in the fluid environment. In the relation to the history of the bacterium, it was first mentioned by Hippocrates who mentioned similar symptoms caused by the bacteria. In 1974, Billroth also mentioned similar symptoms in patients infected by erysipelas. In 1883 Fehleisen isolated the bacteria that were forming chains, and Rosenbach first used the name S. pyogenes in 1884. In the 1930s Lancefield was responsible for conducting further studies on the hemolytic structure of Streptococcus, which Brown and Schottmueller then divided into serotypes (Leyro 1).

Group A streptococcus usually causes acute pharyngitis (strep throat) and pyoderma in adolescents as well as children. Furthermore, the bacterium also causes a variety of other infections that affect the respiratory tract, like, for example, sinusitis, peritonsillar abscess, mastoiditis, and others (Nizet and Armold 700). The symptoms of the most common illness caused by the bacteria, strep throat, include the following: high fever, headache and rash, pain while swallowing, throat pain, red spots on the palate, as well as swollen tonsils.

The treatment of symptoms caused by the invasive Group A streptococcus infections usually involves the hemodynamic stabilizations as well as therapy targeted at the elimination of microbes. Furthermore, to treat the illness, parenteral antimicrobial therapy can be applied until the availability of the results of bacteriologic studies. In cases when bacteria is identified, the prevalent medication of choice is penicillin G, administered in doses of two hundred thousand to four hundred thousand U per kilogram a day. Clindamycin is an antibiotic which is able for inhibiting the synthesis of protein as well as the production of crucial factors of virulence, for example, SPEs or M protein. Thus, many professionals recommend the administration of clindamycin from twenty-five to forty milligrams per kilogram per day as an addition to the administered penicillin, since less than two percent of Group A streptococci can resist the effect caused by clindamycin (Nizet and Armold 702).

The prevention of illnesses caused by Streptococcus pyogenes is linked to vaccine development targeted at diversifying the M proteins. In addition, innovative approaches are used in order to explore the possibility of genetically engineered surface proteins (Nizet and Arnold 707).

Despite the fact that Streptococcus pyogenes is a bacterium that can naturally transform and form chains, there is a small number of identified indigenous cryptic plasmids. Furthermore, the majority of plasmid vectors to manipulate the bacterium stand apart from the heterologous hosts. However, according to Domingues, Cunha Aires, Mohedano, Lopez, and Arraiano, there have recently been advances in plasmid construction that allows the use the gfp-fusions vectors through the use of GFP or Green Fluorescent Protein that plays the roles as the gene expression reported (3). There has also been evidence of the newly developed vector in order to regulate the expression of genes through the use of a similar system.

Works Cited

Domingues, Susana, Andreia Cinha Aires, Mari Luz Mohedano, Paloma Lopez, and Cecilia M. Arraiano. A New Tool for Cloning and Gene Expression in Streptococcus Pneumoniae. n.d. PDF file. 2016.

Leyro, Jasmine. History of Streptococcus Pyogenes. 28 Jul. 2008. PDF file. 2016. Web.

Nizet, Victor, and John C. Arnold. Streptococcus Pyogenes (Group A Streptococcus). n.d. PDF file. 2016.

Introduction

In epidemiology, statistical precision and information exactness are extremely vital. As such, accuracy on the associations between outcomes of interest and exposure should be free from any form of distortion. However, different factors may hinder information validity resulting in distorted exposure/outcome associations. This essay discusses bias and confounding as sources of lack of statistical precision.

Discussion

Bias

Bias in medical research can be termed as any systematic error, which when not restricted may have predictable impacts on results and, therefore, hinder statistical precision by either inflating or deflating outcomes.

There are various types of bias, including selection, detection, observer, reporting/recall, response, and publication biases (Lakshminarayan, 2016; Page, et al., 2016).

The observer may favor certain variables depending on prior affiliations or knowledge of the variables. The observation bias can be avoided by adopting scientific methodologies, especially blinding techniques.

Reporting bias results from inaccuracy related to the human incapacity to recall past events. The inaccuracy in recalling oftentimes results in untrue conclusions.

Selection bias results from deliberate or involuntary omission/deletion of key information/observation leading to incorrectness in association and untrue interpretation.

Outstanding comparable characteristics among the different types of bias is that they are all caused by human errors and have significant impacts on exposure-results associations. On the other hand, bias types differ in that some biases such as observer bias happen during data collection stages while others like the reporting bias and selection bias happen at the end of the study.

Confounding

On a hypothetical ground that both variable X and variable Y can independently cause Z, confounding will occur, for instance, when variable X causes Z in the presence of Y but inaccuracy results in the distortion of the association between X and Z. The variable Y in such a case is the confounder and it distorts the association between variable X and the result Z.

For an empirical example, taking food with a high acid content, and eating sugary foods are some of the causes of dental carriers. In carrying out epidemiological studies, the effects of the two variables on dental health should be separated. Otherwise, confounding may occur when the association between dental carriers and eating food with high acid levels are distorted by a high intake of sugary foods.

Certain conditions (which constitute confounding characteristics) must hold for confounding to occur (Skelly, Dettori, & Brodt, 2012). First, the confounder variable, such as variable Y in the example above, must have an autonomous association (risk factor) with the outcome, which is the result Z in the case above (Tilaki, 2012).

Second, confounding variables should never play any role in enhancing or inhibiting the activities of the exposure variable on the disease. As such, Y in the case above should not be an intermediate between X and the result Z.

For instance, the pH levels in a mouth inhibit or enhance the activities of acids in the teeth corrosion processes. A person with high pH levels reduces the acidity in food and, therefore, reduces the effects of acids. In such a case, the pH levels in a mouth cannot be termed as a confounding factor between intake of food with high acidity levels and dental carriers.

Third, the possible effects of confounding must be evident through the extent/degree of misrepresentation of association. As such, the extent/rate at which Y distorts the association between X and Z depends on the association between Y and Z.

Conclusion

It is evident that epidemiological studies are prone to incorrectness. Bias and confounding are some of the causes of errors that can hinder statistical precisions. There are different types of bias, including selection, detection, observer, reporting/recall, response, and publication. Moreover, it is apparent that certain conditions must hold for confounding to occur.

References

Lakshminarayan, N. (2016). In How Many Ways May a Health Research Go Wrong? Journal of ICDRO, 8(1), 8-13. Web.

Page, M. J., Higgins, J. P., Clayton, G., Sterne, J. A., Hróbjartsson, A., & Savovi, J. (2016). Empirical Evidence of Study Design Biases in Randomized Trials: Systematic Review of Meta-Epidemiological Studies. PLoSE ONE, 1-26. Web.

Skelly, A. C., Dettori, J. R., & Brodt, E. D. (2012). Assessing Bias: the importance of considering confounding. Evidence-Based Spine Care-Journal, 3(1), 9-12. Web.

Tilaki, K. H. (2012). Methodological Issues of Confounding in Analytical Epidemiologic Studies. Caspian Journal Internal Medicine, 3(3), 488495.

Background

Cellular respiratory is a set of processes and reactions that occur inside the cells of a living organism. They aim at converting chemical energy from oxygen molecules to energy that can be used by body tissues (Budin 1186). Additionally, these reactions convert nutrients into adenosine triphosphate (ATP). The cellular reactions involved during the respiration process are catabolic. They break large molecules into smaller ones hence releasing energy used by the body.

The reason behind this is that weak high-energy bonds particularly in molecular oxygen are replaced by stronger bonds in the products (Budin 1186). It is through respiration that a cell produces its chemical energy that stimulates cellular activity. All the reactions generally take place in a sequence of biochemical stages where a number of the reactions are redox (Budin 1187). Even though respiration that happens in the cells is a combustion reaction, it does not seem to be one especially when it happens in a cell of a living organism (Budin 1187). The reason behind this is the decreased release of energy from the series of reactions that take place.

Examples of nutrients used by plant and animal cells during respiration comprise fatty acids, amino acids, sugars, and oxygen (O2). O2 is the most important agent that provides chemical energy to the body (Budin 1187). The energy that is stored up in ATP is then used to drive processes that depend on this energy (Budin 1187). These are processes such as the transportation of molecules across cell membranes, locomotion, and biosynthesis.

Cellular respiration occurs in the cells of all organisms; for instance, it takes place in autotrophs and heterotrophs such as plants and animals respectively. The process of respiration begins in the cells cytoplasm and ends at the mitochondria which is a membrane-enclosed organelle in the cytoplasm (Budin 1187). It is also known as the powerhouse of the cell because of the role it plays in the respiration processes (Budin 1188). Therefore, cellular respiration is a chemical reaction that takes place in a persons cells thus creating energy. When a person does exercise, muscle cells require adenosine triphosphate (ATP) to contract (Budin 1188). This energy originates from oxygen; therefore, cellular respiration depends on oxygen which is breathed in and creates carbon dioxide in response which is breathed out.

C₆H₁₂ + 6O₂ => 6CO₂ + 6H₂O + 36 ATP (energy)

Hypothesis

Cellular respiration increases as a person do exercise.

Experimental Design

During this experiment, the main focus is finding out whether cellular respiration increases as a person does exercise. Therefore, this research will examine how increased muscle activity affects the rate of cellular respiration (Calbet 101478). We gather 50 young men aged between twenty and thirty years. The young men will then be divided into two groups. Data will be taken from the first group on various respiratory indicators such as heart rate, and amount of carbon dioxide produced (Calbet 101478). Data will also be collected on the same respiratory indicators from the second group after they have performed some exercise

Measurement of the rate of breathing and heart rate is calculated per minute. The amount of carbon dioxide produced is determined by the time taken for blue bromothymol to change color (Calbet 101478). The amount of carbon dioxide produced is determined by breathing through a straw into a bromothymol solution (BTB) (Calbet 101478). BTB serves as an acid indicator; therefore, after reacting with acid its color changes from blue to yellow. Additionally, there is the formation of a weak acid after carbon dioxide reacts with water (Calbet 101478). The more carbon dioxide a person breaths through the BTB solution, the faster the solution changes color to yellow.

6CO₂ + 6H₂O => 6HCO₃ + 6H⁺

Expected Results

Discussion

Exercising affects the heart rate in that during workouts, the heart typically pumps faster so that large volumes of blood can move around the body. Additionally, the heart may increase the volume of its stroke by contracting more forcefully or enhancing the amount of blood that fills the left ventricle before pumping (Michael 301). In general, when one is exercising, the heart beats much stronger and faster thus increasing cardiac output (Michael 301). The main reason why the heart increases the rate and amount of blood it pumps is to cater for oxygen requirements by the body muscles when exercise.

During exercise, there is higher production of carbon dioxide because of increased muscles activity resulting from increased work out. In addition, the muscles need more energy to contract and relax. Various changes take place in the body so that this can be achieved (Michael 301). For instance, the rate of oxygen intake when breathing enhances to provide the body with more oxygen. CO2 generated by the body muscles during contraction also needs to be eliminated from the body (Michael 301). Therefore, the heart rate improves supplying body tissues with required oxygen and eliminating CO2 that has been generated by the body.

If the quantity of oxygen supplied to the muscles is insufficient because of forceful and longer exercising, the heart and the lungs are not capable of providing enough oxygen to the body. Therefore, body muscles start to respire anaerobically; lactic acid is generated from glucose, instead of CO2 and water causing the muscles to start contracting less efficiently (Michael 301). Where the body is involved in vigorous activity, there is increased build-up of lactic acid, and glycogen stores in the body are deprived because the respiration processes use more oxygen (Michael 301). This causes extra glucose to be moved from the liver. Increased concentration of lactic acid leads to the production of oxygen debt.

Reflection

Cellular respiration increases as a person exercises; this is because of the increased working of the muscles. This is true no matter the type of exercise that a person does (Kocher 1035). For instance, if one is lifting weight; muscles are used and will give the body fitness of the model (Kocher 1035). However, when doing cardiovascular and aerobic exercises, one uses one muscle in particular; the heart is one of those muscles (Kocher 1035). When a person engages in exercise, the body needs to generate enough energy to enable one to perform the required activity effectively. As a result, the rate of respiration in the body increases as one exercises.

References

Budin, Itay, et al. Viscous Control of Cellular Respiration by Membrane Lipid Composition. Science 362.6419 (2018): 1186-1189.

Calbet, Jose AL, et al. An Integrative Approach to the Regulation of Mitochondrial Respiration During Exercise: Focus on High-Intensity Exercise. Redox Biology 35 (2020): 101478.

Kocher, Morgan, et al. HIV Patient Systemic Mitochondrial Respiration Improves With Exercise. AIDS Research and Human Retroviruses 33.10 (2017): 1035-1037.

Michael, Scott, Kenneth S. Graham, and Glen M. Davis. Cardiac Autonomic Responses During Exercise and Post-Exercise Recovery Using Heart Rate Variability and Systolic Time IntervalsA Review. Frontiers in Physiology 8 (2017): 301.

Although Europe is often perceived as one geographic or political unit, modern society must understand and be aware of the fact that Europe is comprised of more than 44 nations. Due to the large concentration of nations in one area sometimes it is easy to wrongly perceive Europe as one, especially compared to other big countries like U.S. or Russia. However, if in other big countries there are clear differences between different nations, regions, and even local areas, then the wide range of nations and within Europe should be acknowledged and respected. Each nation within the European area has a distinct culture, traditions, mentality, and political interests. Thus, it is necessary to understand that Europe is a geographical term for the continent and could not be used for generalization purposes.

A thing that adds confusion to the term of Europe is the European Union. People generally mistake the geographical term Europe for EU, which is, in a fact, a political and economic union. For example, although several countries follow the Schengen Agreement that allows free entry and transportation within the European Union, not all countries in Europe participate in the EU. Again, although most countries from the EU use euros for currency, not all countries in Europe necessarily participate in the EU and thus, have their currency. The recent events of the United Kingdom leaving the EU left a significant mark in history and highlighted the differences between political and geographical terms for people that used to confuse them. The common confusion between the political terms of the EU and the geographical term of Europe emphasizes that most people generally focus on the political aspect. However, instead of focusing on the political side, people should focus on the differences rather than similarities and recognize the rich cultural legacy of each of the 44 nations within Europe.

Introduction

Predictive modeling is used to forecast results and outcomes for various types of situations and processes. Neural networks are the tools individuals can utilize for these purposes. This paper provides insight into the complex process of constructing predictive regression models, as well as training them and choosing appropriate input for modeling. In addition, the work offers an example of software that can be used for these purposes.

Working with Predictive Regression Models

Several factors should be considered during the construction of a predictive regression model. The process of development can be illustrated by the example of SAS software that is designed to perform this type of operation. Building regression predictive models requires identifying at least one classification or continuous variable. It is crucial to choose which variables will be inputted and the ones that will be rejected. In addition, an individual can create crossed effects by selecting at least two classifications, as well as a nested effect (SAS Enterprise Miner,). To make the predictive model work, a user should create a column for dependent variables as well.

It is necessary to mention that there are various data selection methods that can be used for a model. For example, the least angle regression method starts with no effects and adds them later; the estimated parameters are reduced and the classification variables are divided into groups (SAS Enterprise Miner,). Interpreting the data implies understanding the connection between variables and considering the p-value that suggests that the predictor and the response are not related.

A neural network is a parametric model that is flexible and can be trained according to individuals needs. For example, it is possible to use nodes that can utilize either a specific or several network configurations to identify the relationship in a data set (Analyze with a Neural Network). To train a neural network, an individual can use SAS software that enables it to have links between inputs and outputs, as well as the connection between hidden categories. It is necessary to mention that there are various training methods available, including those based on linear regression, loss function, and gradient descent. The choice of the approach should correspond to the purpose of the network and expected results.

Before choosing input for neural network predictive modeling, it may be necessary to ensure that inputs and output are normalized and the network is prepared for operations. For example, an individual may reduce the number of input variables to provide the high quality of the networks performance and results (SAS Enterprise Miner,). Moreover, the data should be divided into two parts, one of which will be utilized for training the neural network, and the other will serve as testing material. Then, it is vital to consider the link between the variables an individual is planning to select, as some of them may create the excessiveness of data, while others have no predictive value. A person should reflect on the benefits and disadvantages of each potential strategy compared to other ones. The selection should be primarily based on the problem and the expected output.

Conclusion

Constructing and interpreting regression predictive models, as well as choosing input for neural networks, can be challenging as there are many factors that should be considered. For example, it is vital to select appropriate variables to ensure that they have predictive value and can provide expected results. A correctly designed regression predictive model can be an effective tool that can be used to forecast outcomes for various types of research, as well as in daily life.

Works Cited

Analyze with a Neural Network Model. SAS, 2019. Web.

SAS Enterprise Miner: Impute, Transform, Regression & Neural Models. YouTube, uploaded by SAS Software, 2016, Web.

The principle of least action is a natural principle, according to which natural processes tend to evolve towards the most energy efficiency. Fundamental physical and chemical processes are governed by the principle of least action, seen in material formation, heat transfer and electrical currents, taking the path of least resistance (Cooperfield, 2017). The principle can also be seen in the evolution of species, the development of animal behaviors, plant growth patterns, and even human interaction. Left undisturbed, these processes gravitate towards the simplest, most efficient versions. In the 21^st century, when interest in the environment, and, therefore, efficient production, distribution, and consumption of energy, is increasing, identifying methods of optimizing these processes is particularly relevant. Applying the principle of least action to existing systems, including energy generation and distribution, can bring significant improvements in their efficiency and transparency.

Electrical systems are susceptible to power losses, causing increased and excessive production, which is, in turn, associated with negative environmental outcomes. Optimizing existing systems to minimize these losses is, therefore, beneficial for the environment. It is possible to achieve this optimization through modeling and analyzing existing electric power systems, then implementing automated control mechanisms that would align them with the principle of least action (Lezhniuk, Komar, Teptya, & Rubanenko, 2020). Furthermore, the topology of existing power grids can be similarly adjusted to facilitate efficient distribution in accordance with the principle of least action (Lezhniuk, et al., 2020). While the particular method discussed by Lezhniuk, et al. (2020) is theoretical, their research shows a significant potential for improvement if it is implemented. Thus, it demonstrates that applying the principle of least action to current processes to optimize them can achieve significant improvements.

Reference

Coopersmith, J. (2017). The lazy universe: An introduction to the principle of least action. Oxford, UK: Oxford University Press.

Lezhniuk, P., Komar, V, Teptya, V, & Rubanenko, O. (2020). Principle of the least action in models and algorithms optimization of the conditions of the electric power system. Przegld Elektrotechniczny, 1(8), 90-96. Web.