Category: Sciences 2502

Venezuela is located in the northern end of South America, with an area spanning approximately 354 thousand square miles. It has a 1,700-mile coastline bordering the Caribbean Sea and the Atlantic Ocean, administering a number of islands and archipelagos in those bodies of water. Venezuela is divided into three elevations of topography. These include the coastal sea level, the interior forested uplands, and the mountains reaching up to 16,400 feet. Within these divisions, there are 7 physiographic regions. These include the islands and coastal plains, with the Orinoco delta; the Maracaibo lowlands; the northern Andes mountain ranges; the coastal mountain system, the northwestern valley and hill ranges; the wide Llanos plains, and the Guiana Highlands (Heckel et al., 2020).

Despite being the smallest part of the national territory, the coastal mountain system containing two parallel ranges  Coastal and Interior ranges have the highest concentration of Venezuelas population. The intermountain valleys contain the largest cities of Valencia, Maracay, and the capital of Caracas. The country has over a thousand rivers, with largest being the Orinoco River flowing from the Guiana highlands into the Atlantic as well as the Caroni, which stems from the Orinoco and flows into the Caribbean. The country also has Lake Maracaibo located in the Maracaibo lowlands, considered the largest lake in South America. The majority of Venezuelas major cities are located along the coastline or nearby the major watersheds described. Meanwhile, vast areas such as the Llanos and the Guiana highlands remain vastly empty and unsettled, with rich natural wildlife and tropical rainforests (Heckel et al., 2020).

The development of Venezuela has been dependent on the geography. As mentioned early, all major cities and settlements are located along the major bodies of water and river basins. These are critical to the infrastructure and economy. For example, the Caroni is one of the most rapid flowing rivers on the continent, providing opportunities for hydroelectric power generation. The most significant geographical areas for Venezuela are the Orinoco Belt, in the southern strip of the river basin which has the worlds largest known deposits of petroleum. The Maracaibo Basin of Lake Maracaibo is also a hydrocarbon region which has produced over 30 billion barrels of oil (Heckel et al., 2020). Caracas and other major cities are established in the intermountain valleys due to the protections of physical geography and easily accessible access to the coastline, which was crucial for early Spanish settlers. Later on, when city became the unofficial capital of the country, the central location allowed it to govern well. The majority of other regions such as the llanos and Guiana highlands remain sparse with secondary cities, primarily supporting agriculture and oil exploration (Minkel & Medina, 2019). Significant elements of the Venezuelan culture are influenced by the Spanish roots of its origins combined with Caribbean influences with which it has close contact with both politically and culturally.

Unique Issue

Venezuela is undoubtedly one of the most influential and powerful countries in South America. Its rich deposits of petroleum and other natural resources has allowed it to become a major player on the world market. During the oil price boom in the late 2000s, Venezuela reached an economic peak of 334,069 billion USD, becoming one of the wealthiest on the continent and maintaining high quality of living. Venezuelas economy was fully dependent on its oil production and export. However, in the decade after, a series of internal political factors, economic mismanagement which have been in the making, and the declining price of oil on the global market resulted in a catastrophic economic default for the country, plunging it into a continuous recession which also impacted social factors such as quality of life and crime.

In the mid-20th century, Venezuela was experiencing an economic boom due its newly discovered oil resource. However, the decline of the country and its supporting oil industry can be traced back to 1976, when then President Pérez sought to nationalize the industry using it to fund development. A state-run monopoly was created named Petróleous de Venezuela (PDVSA). Initially, PDVSA had a lean efficient structure with competent management. Despite reform efforts, Venezuela never diversified its economy, which was felt strongly in the oil collapse price of the 1990s when production dipped. Foreign companies returned to the country at this time as well. In 1998, Chávez was elected president, running on a strongly authoritarian and socialist agenda. It is under Chávez that the PDVSA saw its top management stripped due to political reasons, and the government exerted full control over the organization, with hopes to maximize revenue which would fund the socialist agenda. However, PDVSA went into decline as new management appointed by Chávez had little knowledge of the industry and company assets were continuously mismanaged or used for political gains. Furthermore, by 2001, an energy law was passed that pushed out foreign firms by mandating that PDVSA lead all new oil exploration and they could only hold minority stakes in any developments (Johnson, 2018).

By 2002, Chávez was facing significant public pressure with protests and strikes, but managed to survive a coup. By 2005 and after, mismanagement of PDVSA became evident as accidents became frequent, efficiency dropped, and all specialists began to leave the company or the country. Meanwhile, Chávez was illegally siphoning billions in revenue from PDVSA as well as placing extremely unfair and high taxes on foreign firms to fund social programs to appease the growing frustration among the population. The majority of foreign firms left the country, but despite a drop in production the national oil industry continued to survive due to surging oil prices reaching almost $150 per barrel. Suddenly, Chávez died in 2014, replaced by President Maduro. At the same time, by 2015, oil collapsed to less than $30 per barrel. Therefore, with 95% of Venezuelas export earnings based on oil, the GDP shrunk by 6% and the economy went into crisis (Johnson, 2018).

The issue was exacerbated by Maduro, also a socialist, whose administration virtually established a dystopian cartel-style of dictatorship in the country. Maduro and his following established a grip on power (opposition is virtually non-existent or quickly removed), have been involved in multiple corruption allegations (Venezuela is the 9th most corrupted country in the world), and continue to disregard any form of competent political and economic management of the country. Desperate measures such as printing more money were undertaken, deepening inflation. Maduros political stance and violation of human rights have resulted in the U.S. placing sanctions, which strongly limits Venezuelas capacity to produce and sell oil, even more drastically crashing the economy and the currency losing 99% of its value (OBrien, 2016).

At this point, Venezuelas economy and society are in ruin. The oil-exporting business which used to subsidize everything is at an all time low, due to the mismanagement, sanctions, and global situation combined. The countrys stores are empty and hospitals lacking not only medications but even electricity. In order to survive, many in Venezuela turned to crime, but the police often prosecute protesters and petty criminals for political showmanship. Venezuelans do not use the national currency anymore, reverting back to bartering since the value keeps on declining (OBrian, 2016). Unfortunately, despite strong foreign pressure and leading opposition figures emerging, Maduro maintains an iron grip on power in the country, and it is unlikely that the status quo will change anytime soon while the once prospering and democratic Venezuela is being run into the ground.

References

Heckel, H.D., Martz, J. D., McCoy, J. L., & Lieuwen, E. (2020). Venezuela. Web.

Johnson, K. (2018). How Venezuela struck it poor. Foreign Policy. Web.

Minkel, C.W., & Medina, J. R. (2019). Caracas. Web.

OBrien, M. (2016). Venezuela: The country that should have been so rich but ended up this poor. The Independent. Web.

Introduction

A citys statistics can tell much information about it, especially if done in comparison. A chronological contrast reveals various changes or potential stagnations while comparing two metropolises can assist in choosing where to move in. Boston and Memphis are the cities with a similar population but different histories and geographical positions, which could have affected other aspects of life. This essay will focus on discovering similar and different features of the two municipalities in the 1950s and 2010s.

Main body

A citys population is an important statistic that shows its people and suggests their circumstances. As of 2010, 617,000 people lived in Boston, while Memphis had approximately 647,000 citizens (Quickfacts, 2019). In 1950, Boston had a population of 801,000 people, and Memphis had 396,000 residents (Census of population and housing, 2018). Older people comprised 11% of Bostons population and 12% of Memphiss in 2010, while teenagers below 18 were 16% and 25%, respectively (Quickfacts, 2019). As of 1950, the numbers were lower, with older people constituting 6% of Memphiss population and 10% of Bostons (Census of population and housing, 2018). Meanwhile, the median age was about 30 years in both cities (Census of population and housing, 2018). Boston had a predominantly White population in 2010, with the Black, Hispanic, and Asian populace also being prominent, while Memphis had a mainly Black population (Quickfacts, 2019). In 1950, 37% of Memphiss population was non-white, while Boston had about 2% (Census of population and housing, 2018). Thus, Boston seems to be more racially diverse than Memphis nowadays.

The racial composition may impact other aspects of a citys statistics. Memphiss poverty rate in 2010 was about 27%, while Bostons was 20% (Quickfacts, 2019). For 1950, it was 43% in Memphis and 30% in Boston (Census of population and housing, 2018). The 2010s median rental was $884 for Memphis and $1,539 for Boston; the housing cost was $97,000 and $487,300, respectively (Quickfacts, 2019). In 1950, the rent was $33 in Memphis and $52 in Boston, with housing being about $8,000 and $10,000 (Census of population and housing, 2018). As of the 2010s, Memphis was more racially segregated than Boston, while both could have a high segregation rate in 1950 (Williams & Emamdjomeh, 2018). The average education level in both cities was elevated in 2010, although Boston had more bachelor degree holders (Quickfacts, 2019). The appropriate statistic from 1950 was the median school years completed, 9.5 for Memphis and 12 for Boston (Census of population and housing, 2018). Generally, Memphiss historical significance of the Black population could explain other demographical factors.

A citys industry plays a vital role in its economy, infrastructure, and employment. As of 2010, Boston and Memphis had business as the main sphere, and their respective websites focus on providing jobs there (Doing business with the city, 2020; Starting a business, 2019). In 1950, about one-third of Bostons working population was involved in manufacturing, 10% in retail, and construction, together with finance, comprised 6% both (Census of population and housing, 2018). Memphis had a similar distribution, with 20% being employed in manufacturing, 12,5% in retail, and 7% in construction (Census of population and housing, 2018). Overall, both cities have similar major industries in the past and the present.

Conclusion

In conclusion, Boston and Memphis have many similarities in both periods, particularly in their economy and demographics, but they also possess several differences, including racial distribution. Bostons population declined while Memphiss kept increasing, potentially due to its attractiveness to the Black citizens. The abolishment of the segregation laws following the 1960s Civil Rights Act also could have contributed to the citys prosperity. Meanwhile, Boston probably had other competitors with better conditions and lower cost of living, which led to its decline in population. Altogether, both cities have something to offer to various demographic groups.

References

Census of population and housing. (2018). Web.

Doing business with the city. (2020). Web.

QuickFacts. (2019). 

Starting a business. (2019). 

Williams, A., & Emamdjomeh, A. (2018). America is more diverse than ever  but still segregated. Web.

Introduction

Trichoderma Reesei is a mesophilic fungus which is usually known for its high ability to secrete cellulotytic enzymes (Hi138, 2006). It is majorly used in many industrial processes especially in the conversion of cellulose to glucose, large scale fermentation, down strain process engineering and the process of developing genetically modified strains. Cellulase which is also a resultant product of the genetic transformation of Trichoderma Reesei is the most common by-product and Hi138 (2006) identifies that: Cellulase is widely used in starch processing, grain alcohol, fermentation, preparation and brewing malt, animal breeding, as well as silage beverage processing, fruit juice and vegetable juice extraction and many other areas. Recent scientific developments have increased the commercial value of Trichoderma Reesei for cellulose hydrolysis.

Genetic Transformation Techniques

Trichoderma Reesei in its natural form does not have high components of protein (which is the most important element of its use). This has led to the massive genetic transformation of the spontaneous strain. Genetic modification is done through molecular transformation techniques and fungal gene transfer (Kinghorn, 1992, p. 184). Genetic transformation systems have also been developed over the past few years to incorporate ascomycetous and basidiomycetous fungi which have eased the process of producing proteins for industrial purposes. This process is also used in food and biological control processes. The same transformation has also been carried out in gilled basidiomycetes (Goldman, Van-Montagu and Herrera-Estrella, 1990).

There have been many methods of universal genetic transformation and common among them is the polyethylene glycol mediated DNA uptake by protoplasts (Goldman, Van-Montagu and Herrera-Estrella, 1990). Other methods such as the electroporation of protoplasts and incubation of germinating conidia in a lithium salt have also existed in the past. The revolution still goes on because recent techniques such as microprojectile bombardment of intact conidia with gold or tungsten particles coated with DNA have been introduced in the recent past; together with the biolistic method which has been practiced more with uninucleate haploid conidia (Goldman, Van-Montagu and Herrera-Estrella, 1990).

These techniques have been proved to have a high rate of success especially in relation to the time required in doing repetitive purification. In addition, these methods have a high record of providing highly stable transformants (Goldman, Van-Montagu and Herrera-Estrella, 1990). Genetic transformation has even had a higher success rate in the recent past with the introduction of Agrobacterium T-DNA which has the highest rate of fungal transformation in relation to fungal conidia.

These methods have been especially developed with a high success rate because of Trichoderma reeseis high protein synthesis ability. The eukaryotic synthesis mechanism is almost similar to the mammalian protein synthesis system. With high success rates of genetic transformation on Trichoderma reesei, studies have been done to probe its safety. Results have established that the system is very safe (Hi138, 2006).

Conclusion

Among the existing methods of genetic transformation of Trichoderma reesei, a modification of the initial processes has especially increased protein production. The use of genes is especially noteworthy. The presence of Trichoderma reesei in a number of molecular systems and adoption of different strategies for the homologous and heterologous protein production forms can significantly improve production. With the nature of Trichoderma Reesei, while carrying out genetic engineering modification, the commercial viability of making a variety of commercially viable strains is highly likely. The mass production of genetically transformed strains of Trichoderma reesei will improve and even be more efficient in the near future.

References

Goldman, G.H., Van Montagu, M., & Herrera-Estrella, A. (1990). Transformation of Trichoderma harzianum by high-voltage electric pulse. Curr. Genet, 17, 169-174.

Hi138. (2006). Filamentous Fungus Trichoderma Reesei the Production Of Recombinant Proteins in Molecular Biology Research. Web.

Kinghorn, J. (1992). Applied Molecular Genetics Of Filamentous Fungi. New York: Springer.

Organic substances and compounds are chemical compounds that include carbon atoms. This includes proteins, carbohydrates, fats, nucleic acids, and other compounds that are not found in inanimate nature. Different types of cells may consist of various amounts of organic compounds. For example, plant cells contain more carbohydrates, and animal cells contain more proteins. As I can remember, a functional group is an active, easily changing atomic group with specific chemical properties, necessarily containing atoms of oxygen, nitrogen, sulfur, or other elements capable of forming polar bonds. Another characteristic of this class of organic compounds that determines its chemical properties is a structural fragment of a molecule. Examples of functional groups are hydroxyl, carbonyl, carboxyl, or amino groups (Brown & Poon, 2015). An organic substance molecule may contain not one, but several functional groups. If a molecule contains one or more identical functional groups, then these are compounds with homogeneous chemical functions. If a molecule has several different functional groups, such a substance is a compound with mixed chemical functions. The functional groups determine the overall property of a molecule, which plays a critical role in building such more complex molecules as proteins.

In my opinion, the most important difference between prokaryotes and eukaryotes is the presence of a nucleus in the latter, which is reflected in the name of these groups. Hence, prokaryotes are pre-nuclear organisms, and eukaryotes are nuclear. However, this is far from the only difference between prokaryotic organisms and eukaryotes. There is no membrane organelles in the cells of prokaryotes, such as mitochondria, chloroplasts, Golgi complex, endoplasmic reticulum, and lysosomes. Their functions are performed by outgrowths or invaginations of the cell membrane, on which various pigments and enzymes are located, which ensure vital processes. Prokaryotes have no chromosomes characteristic of eukaryotes, and their main genetic material is a nucleoid, usually in the form of a ring. In eukaryotic cells, chromosomes are complexes of DNA and histone proteins that play an important role in DNA packaging. These chemical complexes are called chromatin, while the prokaryote nucleoid does not contain histones, and the RNA molecules associated with it give the form.

Plant and animal cells are both eukaryotic life forms with key differences. As I recall, plant cells possess cell walls made from cellulose, whereas animal cells outer layer is a plasma membrane. Plant cells also have plastids, which capture the light energy and convert it into an organic one. Therefore, animal cells feeding metabolism is heterotrophic, but it is autotrophic in plants. The latter usually contains one large vacuole without any specialization, whereas animal cells have different variations of the given structure.

As far as I know, mitochondria, similarly to plastids, are double-layered organelles, which most likely originated in ancient prokaryotic life forms. Mitochondria are covered by two layers, such as a smooth outer membrane and a folded inner one, where the latter has a large surface. The folds of the inner membrane deeply penetrate the matrix of mitochondria, forming a transverse septum called crista. The area between the outer and inner layers is usually called the intermembrane space. According to endosymbiosis theory, both mitochondria and plastids were separate prokaryotic organisms, which were engulfed and became a part of the endosymbiosis relationship with a larger host cell (Archibald, 2015). The given hypothesis is supported by the fact that mitochondria possess its own DNA and ribosomes. The organelle allows a cell to extract energy from molecules in a more efficient manner. Plastids allow plant cells to use light energy sources in order to build carbohydrates.

References

Archibald, J. M. (2015). Endosymbiosis and eukaryotic cell evolution. Current Biology, 25(19), R911-R921.

Brown, W. H., & Poon, T. (2015). Introduction to organic chemistry. Wiley.

Introduction

Not all types of data analysis help determine how one variable impact the other. In some cases, the researchers use methods suitable for showing that there is a correlation between variables or that there is none. However, this does not provide insight into understanding how one issue may be connected to the other. This paper will discuss the types of research methods, which help determine the cause and effect.

Main body

To explore how researchers can study the cause and effect, one can use a hypothetical experiment, where the goal is to determine if the consumption of carbs leads to obesity. There are multiple research methods one can use to collect data to answer this question. For example, through a questionnaire were respondents with and without obesity answer questions about their eating habits. Although the researchers will receive some data, and in the case of quantitative studies, statistical data, there is a high possibility that the participants were biased or did not accurately account for the number of carbs they eat. Hence, such research may show a negative correlation between the two variables, meaning that the more carbs a person eats, the slimmer they become. Considering the selected research method, potential bias, and the inability of an independent researcher to verify the words of the participants, this study produces results that are questionable because the cause and effect of the negative correlation are unclear. This relationship can be explained by a plethora of factors. For example, the participants may favor carbs and do sports regularly, which allows them to stay fit. Without being able to see the daily routines of the participants and account for all the factors that can modify the results, one cannot be sure if a phenomenon is caused by a specific event.

In a controlled experiment, the researchers get to manipulate the different aspects that may affect the results. The conditions in which the participants are placed are continuously controlled by the scientists. Therefore, using the previous example, scientists can control what food the participants eat, how much they exercise to see if the assumption about the carbohydrates is valid. All of the potential participant bias and the effect of other variables are examined in the study, therefore one can conclude the cause and effect.

This type of research implies that one uses a hypothesis with two variables  independent and dependant. The former is the cause, while the latter is the effect, which helps establish how the two variables are connected. For instance, if an individual consumes 400 grams of carbs per day, then they will become obese is an example of a hypothesis for an experiment where the cause and effect are examined. Here, the anticipated cause is a high amount of carbs in the diet, and the result is obesity. To account for all other factors that may cause obesity, the researchers have to observe the participants constantly to verify how many carbs they are eating, which can only be done in a controlled experiment.

One major drawback of the controlled experiments is that the findings cannot be generalized. This is because the conditions in a laboratory where these experiments occur differ from those of the real world. This is because these types of studies do not rely on external validity as an essential procedure. This validity measure is an application of the findings outside of research or checking if the experiments results are the same in the real world.

The nature of a controlled experiment does not imply that external validity should be measured. In practice, this means that although the participants who ate more carbs during this experiment were slimmer, in real-life conditions, people may become obese on such a diet. For example, because during the investigation, the researchers controlled the number of calories the subjects consume while in real life, most people do not do this. Therefore, this research method usually has lower validity when compared to other research strategies. Despite this drawback, this type of design is beneficial when establishing the cause and effect relationships. However, it is not used in all studies, mainly to answer all research questions because the nature of the research question may require examining participants in real-life conditions. For example, a study aiming to assess the participants view of carbohydrates can be performed as a survey or an interview, since it will allow one to collect the necessary data.

Conclusion

Overall, this essay explores the controlled experiment method as a method for determining the cause and effect relationships. Although other methods can be used to collect data, this type of experiment is the only approach that can be relied on when discussing the cause and effect. Although the design of controlled research allows a conclusion about the impact of one variable on the other, they cannot be generalized for the entire population.

Reference

Today I found out. (2019). The appalling Tuskegee Syphilis experiment [Video]. Web.

Conducting qualitative research requires observing some essential conditions that are the key to successful work and obtaining credible results. One of these principles is methodological coherence which, as Mayan (2009) argues, makes it possible to ensure congruence between your epistemological and ontological viewpoint (p. 13). However, this principle is not the only technique that may be applied when planning research and developing a target problem. The topic for analysis is the acculturation of former Latin American military personnel serving in the United States in the civilian world. As a theoretical framework that may contribute to describing the experience of the given social group, a phenomenological approach can be utilized rationally. According to Daniels (2017), in terms of acculturation, this method involves a comprehensive evaluation of the opinions of individuals with a specific background and transiting to an unfamiliar cultural environment. Based on this evaluative principle, the research question for the upcoming study may be as follows: what is the lived experience of first-gen Latinos in transition from the military to civilian life?

The research built on the basis of this issue implies a complete rejection of biases or personal judgments regarding the stated topic. Since a qualitative study is planned, an interview is the best method for collecting primary data. The accuracy of this information may be high because, as Daniels (2017) remarks, the phenomenological approach involves a small sample (five or a few more participants). In addition, the experience of the former military will be analyzed based on a specific topic, in this case, acculturation in civilian life, which will allow the research participants to formulate their positions as accurately as possible. Therefore, the phenomenological method is a valuable technique to ensure a coherent and credible research process.

References

Daniels, W. C. (2017). A phenomenological study of the process of transitioning out of the military and into civilian life from the acculturation perspective. Web.

Mayan, M. J. (2009). Essentials of qualitative inquiry. New York, NY: Routledge.

Comparison between tachyzoites and bradyzoites

During the various stages of a lifecycle, a parasite goes through various cellular stages that are characterized by different morphology, behavior, function, and biochemistry. Tachyzoites and bradyzoites are stages in the lifecycle of T. gondii. In each of the stages, the parasite differs in shape, size, function, and location. The main function of tachyzoites is to expand the population of the parasite in the host through rapid multiplication (Hill & Dubey 2002). Their motility and ability to multiply rapidly aid in fulfilling their role. With regard to their morphology, tachyzoites are crescent-shaped and possess a pointed front (Dubey & Jones 2008). In addition, they are 2 by 6 micrometers with a rounded back end. They contain numerous organelles and inclusion bodies. Examples of these structural bodies and organelles include pellicle, micronemes, endoplasmic reticulum, apical rings, Golgi complex, ribosomes, microtubules, amylopectin granules, micropores, mitochondria, and dense granules (Dubey 1998). They lack motility structures even though they have the ability to flex, glide, undulate, and rotate. After multiplication, they are transported to various parts of the body through bloodstreams. As the lifecycle progresses, tachyzoites convert to bradyzoites in order to form tissue cysts that are critical in the development of the parasite (Eaton 2014). Unlike tachyzoites which have a central nucleus, bradyzoites have a nucleus that is located toward the cells posterior end (Dubey 1998). They are crescent-shaped and are larger than tachyzoites. They are about 7 by 1.5 micrometers in size. The rhoptries of bradyzoites contain numerous electrons while those of tachyzoites are labyrinthine (Offenberg 2015). The main function of bradyzoites is to form tissue cysts when they enter a hosts cells and aid in the progression of the parasites life cycle. They are orally infectious and therefore, play an important role in the transmission of T. gondii in the hosts body (Tenter et al. 2001).

Hosts immune response to Toxoplasma gondii

The host responds to infection by initiating innate and adaptive immune responses. After the ingestion of T. gondii, the hosts immune system activates macrophages to fight the parasite (Flegr 2013). The main purpose of the innate immune response is to prevent the multiplication of T. gondii (Tenter et al. 2001). In addition, it initiates the activation of the adaptive immune response after the ingestion of the parasite (Flegr 2007). The adaptive immune response triggers the release of certain antibodies and effector cells whose role is to eliminate the invader (Flegr 2013). The response causes the specialization of dendritic cells, B cells, and macrophages in order to present specific antigens for the elimination of T. gondii. The presentation of the antigen to T cells commences the differentiation process that leads to the development of immunological memory that protects the host from re-infection (Blanchard et al. 2015).

Localization of the cysts on the brain

One of the mechanisms through which T. gondii manipulates the hosts behavior is through localization on certain parts of the brain. In infected hosts, cysts of the parasite are usually distributed in several brain regions (Carruthers & Suzuki 2007). A study conducted to study the distribution of T. gondii cysts in the brains of CD1 mice found out that cysts were localized on all brain regions including the olfactory bulb, the hippocampus, amygdala, the entorhinal, and the frontal association and visual cortices (Berenreiterova et al. 2011). Low distribution of cysts was observed in regions that include the cerebellum, myelinated axons, the pontine nuclei, and the caudate-putamen. The study conducted by Berenreiterova et al (2011) found out that 54 brain regions contained the parasites cysts. Research has shown that during the chronic stages of T. gondii infection, cysts are found throughout the brain (Blanchard et al. 2015). However, the localization of the cysts has not yet been studied in detail. Certain studies have shown that there is a high density of T. gondii cysts in two main brain regions namely the frontal cortex and the amygdala (Carruthers & Suzuki 2007). Brains infected by T. gondii have high volumes of dopamine (Lafferty 2006). These findings have been used to explain why infected hosts exhibit changes in behavior. According to McConkey et al (2013), T. gondii manipulates host behavior by localizing in brain regions that process fear including the amygdala (Wiser 2010). It can be concluded from several research studies that T. gondii cysts are highly localized in brain regions that include the amygdala, frontal cortex, olfactory bulbs, hippocampus, and diencephalon (McConkey et al. 2013).

Effect on neuromodulator levels

Studies have proposed histopathological, immunological, and neuromodulatory hypotheses for the manipulation of host behavior by T. gondii. According to the neuromodulatory hypothesis, the local immune response that is elicited to inactivate T. gondii alters the levels of cytokines, which influence neuromodulator levels (Lafferty 2006). The neurological basis of anxiety has been studied in several studies to determine how T. gondii alters neuromodulator levels. Fearless reactions in rats have been shown to emanate from the blocking of anxiogenic N-methyl-D-aspartic acid receptors in the amygdala (plays an important role in emotional behavior). Homovanillic and norepinephrine alter the mood, locomotor activity, and cerebral blood flow of hosts. Homovanillic acid is a degradation product of dopamine that has been associated with behavior change of infected hosts. One of the proposed mechanisms of neuromodulation involves alterations in the levels of neurotransmitters in the host (Wiser 2010). Brain cells of acutely-infected hosts show an HVA elevation of 140% while the levels of dopamine in chronically-infected hosts elevate by 114% (McConkey et al. 2013). Several studies have found that the levels of dopamine increase in brain cells that contain cysts. T. gondii directly increases the quantities of dopamine in infected cells by synthesizing tyrosine hydroxylase, which plays an important role in the production of dopamine. Studies have identified two tyrosine hydroxylase genes that are responsible for the production of excess dopamine in the brain. For example, overregulation of the TgAaaH2 gene during the differentiation of T. gondii to bradyzoites results in stimulation that increases the production of dopamine (McConkey et al. 2013). The accumulation of dopamine in various brain regions is responsible for the behavioral changes that are observed in animals and humans infected by T. gondii (Lafferty 2006).

References

Berenreiterova, M, Flegr, J, Kubena, A & Nemec, P 2011, The Distribution of Toxoplasma gondii Cysts in the Brain of a Mouse with Latent Toxoplasmosis: Implications for the Behavioural Manipulation Hypothesis, PLoS One, vol. 6, no. 12, 41-53.

Blanchard, N, Dunay IR & Schulter, D 2015, Persistence of Toxoplasma gondii in the Central Nervous System: A Fine-Tuned Balance between the Parasite, the Brain and the Immune System, Parasite Immunology, vol. 37, no. 3, 150-158.

Carruthers, V & Suzuki, Y 2007, Effects of Toxoplasma gondii Infection on the Brain, Schizophrenia Bulletin, vol. 33, no. 3, 745-751.

Dubey, JP & Jones, JL 2008, Toxoplasma gondii Infection in Humans and Animals in the United States, International Journal of Parasitology, vol. 38, no. 11, 1257-1278.

Dubey, JP 1998, Advances in the Life Cycle of Toxoplasma gondii, International Journal of Parasitology, vol. 28, 1019-1024.

Eaton J 2014, What Does it Mean when 2 Billion people Share Their Brain with a Parasite. Web.

Flegr, J 2007, Effects of Toxoplasma on Human Behavior, Schizophrenia Bulletin, vol. 33, no, 3, 757-760.

Flegr, J 2013, Influence of Latent Toxoplasma Infection on Human Personality, Physiology and Morphology: Pros and Cons of the Toxoplasma-Human Model in Studying the Manipulation Hypothesis, Journal of Experimental Biology, vol. 216, no. 1, 127-216.

Hill, D & Dubey, JP 2002, Toxoplasma gondii: Transmission, Diagnosis and Prevention, Clinical Microbiology and Infection, vol. 8, no. 10, 634-640.

Hunter, C & Sibley, D 2012, Modulation of Innate Immunity by Toxoplasma gondii Virulence Effectors, Nature Reviews Microbiology, vol. 10, no. 1, 766-778.

Lafferty, KD 2006, Can the Common Brain Parasite, Toxoplasma gondii, Influence Human Culture?, Proceedings of the Royal Society, vol. 273, no. 1602, 111-126.

McConkey, GA, Martin, HL, Bristow, GC & Webster, JP 2013, Toxoplasma gondii Infection and Behavior: Location, Location, Location, The Journal of Experimental Biology, vol. 216, 113-119.

Offenberg, K 2015, Toxoplasma gondii, Agenda Verlag GmbH & Company, New York.

Tenter, A. M, Heckeroth, A. R & Weiss, LM 2001, Toxoplasma gondii: from Animals to humans, International Journal of Parasitology, vol. 31, no. 2, 217-220.

Wiser, M 2010, Protozoa and Human Disease, Garland Science, New York.

Confidence interval (IC) is a type of interval estimate of a population constant. lt is used to ascertain the reliability of a statistical estimate. Rather than estimating a constant using a single value, a range is determined that includes the constant. The interval between the constants is measured by the confidence coefficient.

The confidence coefficient is normally denoted as a percentage of the confidence level, for instance, a 90 percent confidence interval. It is examined that the higher the confidence level, the larger the confidence coefficient and thus the more reliable the parameters are. The extremes of the confidence interval of the variables are known as confidence limits.

Interval estimates can be distinguished from point estimates. While a point estimate represents a single value of the sample population constant such as the mean of a given quantity, an interval estimate gives two extreme limits where the constant is likely to be found.

Confidence intervals can be used in the significance testing of variables. For example in the case given, taking a point estimate of distance from the is 200, with a confidence interval (200, 300) at the confidence coefficient, 90 percent, then any housing units number outside the interval (200, 300) will be said to be significantly from, Distance From City, at a significance level of 10% (100%  90%), considering the spread assumptions made in ascertaining the confidence interval.

Significance testing will involve two hypotheses, that is, a null and alternative hypothesis. If the value of the distance from the city is less than or greater than the housing units number, the null hypothesis will be rejected since the value of the constant equaled the distance from the city.

Since confidence intervals do not deal with multiple quantities, in cases with multiple quantities, confidence regions can be estimated to generalize the confidence interval of the population. Confidence regions show the estimation errors and also highlight the value of the reliable and estimates estimate.

Confidence intervals can be reported in tables, charts, or graphs, along with point estimates of the conceding constants, to illustrate the reliability of the estimates.

Alongside the confidence intervals method, there are other methods of interval estimation such as credible intervals and prediction intervals. Confidence intervals are a probability representation and adhere to normal probability rules and assumptions. When calculating confidence intervals, the principle of independence of variables must apply. If confidence intervals are calculated to do statistical tests, the several statistics are calculated separately holding that they are independent. Also, the data given should be normally distributed.

The general way to come up with confidence intervals is presupposing the practical applicability of a reliable significance test. That is, to define a 100%  100±% confidence interval consisting of all values, ¸0, for that a hypothesis test ¸=¸0 is accepted at a significance level of 100±%.

A reliable confidence interval should be valid, optimal, and invariant.

References

Smithson, Michael. Confidence intervals (Quantitative Applications in the Social Sciences Series). Belmont, CA: SAGE Publications. 2003. Print.

Is the Data Suitable for Analysis?

Although the structure of the data appears normal (observations are stored in one record each; replications have separate records; each variable has its own field, which is always in the same column, etc.), not all the variables from the file Data 02 (1).sav are suitable for analysis. The data in several variables missing or appears corrupted. For example, the values 7777 and 9999 in the variable HEIGHT3 cannot be explained without further clarification. The variable ORACE2 only has 58 valid values; the rest, 7631 values, are missing. The data in the variable IDATE is corrupt because the last number of the year is missing, although this can be mitigated because there is the IYEAR variable. The variable HEIGHT3 is very difficult to use, and should be treated as categorical; it should be recorded into a continuous variable (this is done below).

The variable CHILDREN, which is supposed to reflect the number of children in a household, often has the value of 88 (5728 out of 7689 values). For certain variables, it might be possible to address the problem; for instance, the value 88 in CHILDREN might mean that the household has no children; the missing values in the variable PREGNANT may denote the value not pregnant, although it is impossible to differentiate these from simply missing data.

On the whole, some of the data is usable, at least for certain purposes; some is corrupt, but can be mitigated; some is corrupt, and cannot be mitigated without additional information.

Converting and Combining Variables

Converting

Table 1 below is a frequencies table for height in feet and inches (file Data 02 (1).sav), whereas Table 2 displays frequencies for a new variable cat_height, obtained via Transform ’ Recode into different variables (Field, 2013), which reflects the categories into which the participants were sorted according to their height: 1 is d4 feet 11 inches; 2 is 5 feet  5 feet 11 inches; 3 is 6 feet  7 feet 8 inches; 0 is e 7 feet 9 inches. The last category (0) contains original values 7777 and 9999 which make no sense and should be excluded from the analysis (e.g., via Filter Data procedure).

Table 1. Height in feet and inches  frequencies (file Data 02 (1).sav).

Table 2. Height categories  frequencies (file Data 02 (1).sav).

Combining

Tables 3 and 4 below provide the frequencies for the numbers of men and women in households, respectively (file Data 02 (1).sav).

Table 5 provides frequencies for the total number of men and women in a household; this new variable, males_plus_females, was gained via the Transform ’ Compute variable (Warner, 2013).

Table 3. Frequencies for men (file Data 02 (1).sav).

Table 4. Frequencies for women (file Data 02 (1).sav).

Table 5. Frequencies for men and women (file Data 02 (1).sav).

Further Data Manipulations

Merging

To combine the files Data 02 (1).sav and Data 03 (1).sav, which contain the same variables, a variable id_merge was created to enumerate the cases and keep track of them. Cases were enumerated 1 through 7689, and 7690 through 12466 for the named files, respectively.

For the file Data 02 (1).sav, the descriptives for the variable WEIGHT2 are shown in Table 6 below. The descriptives for the same variable from the file Data 03 (1).sav are shown in Table 7. The descriptives for the same variable from the merged file 02_03_merged.sav are shown in Table 8.

Merging these two files allows for combining the data from these files with respect to the sample. In other words, because both files have the same variables, merging the files simply permits to add cases from the second data set to the first data set.

Table 6. Descriptives for WEIGHT2 in Data 02 (1).sav.

Table 7. Descriptives for WEIGHT2 in Data 03 (1).sav.

Table 8. Descriptives for WEIGHT2 in 02_03_merged.sav.

Manipulating the Data to Create a New Variable

A new variable in the merged file 02_03_merged.sav will be created by using the command Transform ’ Compute variable to multiply the existing variable WEIGHT2 by the number 0.453592 (George & Mallery, 2016). This will allow for creating a new variable weight_kg denoting the weight of the participants in kilograms. Such a variable will be useful if it is needed to calculate the body mass index of the participants (BMI = weight / height², where weight is in kilograms, and height is in meters), which will permit for assessing whether the participants are underweight, of normal weight, overweight, or obese.

The descriptives for WEIGHT2 in this data set can be found in Table 8 above. The descriptives for weight_kg can be found in Table 9 below.

Table 9. Descriptives for weight_kg in 02_03_merged.sav.

Manipulating the Data Structure

Manipulating the data structure means changing variables so that they would be measured in different units (DeCoster, 2001). On the whole, this was done in the previous subsection, when weight in pounds was transformed into weight in kilograms. The same can be done with the variable HEIGHT3 to make it usable in the analysis (file Data 02 (1).sav). First, it is possible to create a new variable in which the height would be measured in inches only. It is possible to do that by using the command via Transform ’ Recode into different variables and manually setting the values for each value of height (from 400 to 708), or by using the syntax from Appendix. The resulting variable is height_inches.

There is no point in creating the descriptives for HEIGHT3 because the data is categorical. However, the frequencies are given in Table 1 above. For the data in inches only (height_inches), descriptives are provided in Table 10 below.

It should be noted that the syntax in Appendix does not contain transformation instructions for the values from 700 through 707 because there are no such values in the data, as can be seen from Table 1 with frequencies for HEIGHT3. Also, the values 7777 and 9999 (outliers that make no sense in this variable) were left as they were during the transformation. They can be filtered out by using the command Data ’ Select cases, for example.

Table 9. Descriptives for height_inches in Data 02 (1).sav.

References

DeCoster, J. (2001). Transforming and restructuring data. Web.

Field, A. (2013). Discovering statistics using IBM SPSS Statistics (4th ed.). Thousand Oaks, CA: SAGE Publications.

George, D., & Mallery, P. (2016). IBM SPSS Statistics 23 step by step: A simple guide and reference (14th ed.). New York, NY: Routledge.

Warner, R. M. (2013). Applied statistics: From bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: SAGE Publications.

Appendix

DATASET ACTIVATE DataSet1.

RECODE HEIGHT3 (400=48) (401=49) (402=50) (403=51) (404=52) (405=53) (406=54) (407=55) (408=56)

(409=57) (410=58) (411=59) (500=60) (501=61) (502=62) (503=63) (504=64) (505=65) (506=66) (507=67)

(508=68) (509=69) (510=70) (511=71) (600=72) (601=73) (602=74) (603=75) (604=76) (605=77) (606=78)

(607=79) (608=80) (609=81) (610=82) (611=83) (708=92) (7777=7777) (9999=9999) INTO height_inches.

VARIABLE LABELS height_inches height in inches.

EXECUTE.

Summary

The following paper is a profile of the Magnolia tree, and it addresses its background, origin, and biological attributes. It will examine the life cycle of the tree in addition to its reproductive system, and carry out a study on the plants evolutional history. Under evolution, it will focus on the various adaptive traits the plant has developed over the years and their importance. It will also mention a few unique attributes that make the plant different from other angiosperms.

Introduction

The Magnolia tree is also called the Southern magnolia or bull bay, its scientific name is Magnolia Grandiflora, and it is classified under the Kingdom Plantae, Order Magnoliales, the Magnoliaceae family, and Genus Magnolia. It is native to the southern parts of the USA and grows in Virginia, Florida, Texas and Oklahoma States. It also does well in other warm parts of the world, where it is commercially planted because the hard timber makes it ideal for making furniture and pallets.

Life Cycle

The life Cycle of the Magnolias starts with the seeds, which are grown either through cuttings of grafts, they are dispersed by birds or mammals and due to their hard outer cover, they go through the digestive tracts unharmed (Halls, 1977). The next stage is the sapling or pole stage when they are about 3 to 7 inches in diameter and they develop an extensive root system from the single taproot in the seedlings. The Juvenile stage is when they appear mature, but cannot produce flowers or seeds, this can last as few as 10, or as many as 25 years. The flowering stage is when they are mature and produce flowers, which have both male and female parts. Their lifespan is between 80 to 120 years depending on where they are growing.

Reproductive System

Their reproductive system is usually bisexual (perfect), and the flower consists of 3 sepals and between 6 and 12 petals. These are however not very distinct from each other and they are referred to as tepals. The stamen is spiral, and the flowers have many simple ovaries that are centrally placed (Halls, 1977). Insects pollinate the plant, which makes it possible for the differentiation of species through cross-pollination. Double red seeds in each follicle then connect the fruits, which are dispersed by birds and mammals over large distances.

Evolution and adaptation

The Magnolias are some of the oldest angiosperms with some of their fossils estimated to be over 90 million years old (Soltis, Soltis & Edwards, 2005). While the plant is generally bisexual, there are fossil records that suggest some early species might have reverted to unisexuality. The same has been experienced in other primitive plant families such as the Winteraceae, whose flowers are unisex. Botanists claim that the floral structure evolved to facilitate pollination by beetles since the plant existed before bees did. In addition to beetles, other animals such as primitive moths and even some caterpillar species also facilitated pollination.

Molecular analysis of the Magnolias reveals that the group comprises of six families namely, Myristicaceae, Degeneriaceae, Himantandraceae, Magnoliaceae, Eupomatiaceae, and Annonaceae (Soltis, Soltis & Edwards, 2005). The relationships among members of this family are visible in their shared minimal pit borders, stratification of their phloem and the presence of a progressive tectum within their pollen. In addition, there is a testa capable of multiplication of the seeds, among other distinct similarities.

Additional Information

Magnolia trees have fascinated botanists for centuries owing to their singular features such as the fact that, despite evolving for millions of years, their flower structure has remained almost unchanged. In addition, contrary to popular expectations that evergreens are neat trees, especially for domestication, the Magnolia is particularly messy and it shed leaves and fruits all year round.

References

Halls, L. K. (1977). Southern magnolia/Magnolia grandiflora L. Southern fruit-producing woody plants used by wildlife, 196-197.

Soltis, P., Soltis, D., & Edwards, C. (2005). Magnoliids. Web.