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Data from a “living” oxygen minimum lab could help predict the oceans future

Submitted by tterrasi on Mon, 11/13/2017 - 12:25

Researchers have collected 50 years of data showing the deoxygenating cycles of a fjord on the coast of Vancouver Island, cataloging the response of the microbial communities inhabiting this environment. Marine oxygen minimum zones (OMZs) are widespread and contribute up to 7 percent of global oceans. Expansion of these OMZs has potential to bring oxygen-depleted water into new regions, affecting fish populations and nutrient cycles. Environments of low-oxygen are not well suited for most metazoans, but microbial life can flourish. As oxygen becomes limiting, microbial communities can change their metabolism to use alternative electron sources like nitrogen, carbon, and sulfur. These microbial communities can drive nutrient cycling essential for ecosystem function and diversity. The research team collected data using time-series monitoring and multi-omic sequencing (DNA, RNA, and protein) to study microbial responses to deoxygenated ocean areas. By using this data, reconstruction of microbial communities metabolism can predict future responses to ocean deoxygenating.

Data from a “living” oxygen minimum lab could help predict the oceans future

Submitted by tterrasi on Sun, 11/12/2017 - 21:02

            Researchers have collected data over a 50-year span, showing the deoxygenating cycles of a fjord on the coast of Vancouver Island, and cataloging the response of the microbial communities inhabiting this environment. Marine oxygen minimum zones (OMZs) are widespread and contribute up to 7 percent of global oceans. Expanding of these OMZs has potential to bring oxygen-depleted water into new regions, affecting fish populations and nutrient cycles. Environments of low-oxygen are not well suited for most metazoans, but microbial life can flourish. As oxygen becomes limiting, microbial communities can change their metabolism to use alternative electron sources like nitrogen, carbon, and sulfur. These microbial communities can drive nutrient cycling, essential for ecosystem function and diversity. The research team collected data using time-series monitoring and multi-omic sequencing (DNA, RNA, and protein) to study microbial responses to oxygen-depleted ocean areas. By using this data, reconstruction of microbial communities metabolism can predict future responses to ocean deoxygenating.

Seedlings change over time in monoculture

Submitted by tterrasi on Thu, 11/09/2017 - 23:00

 In a monoculture stand of plants, the number and size of seedlings can change over time. Individual plant sizes are generally extremely uneven. Usually, a few large individuals dominate an available area given, while most individuals remain very small.  This unevenness is highly unequal in size distribution, which is characterized by size hierarchies that can be attributed to asymmetric competition – larger individuals have negative effects on smaller neighboring individuals. For example, starting with a population that is relatively homogeneous, as time goes on, the distribution becomes increasingly unequal with the proportion of smaller plants increasing and smaller number of large plants. Eventually, self-thinning occurs, which is when death removes the smallest individuals from the population, in this case, so that the population is less unequal as time goes on. This shows that plant sizes vary in a cycle from having more plants of one size over the other. Also, as a population increases in size, it can reach a maximum capacity, which then individuals start dying due to reduced resources.

Seedlings change over time in monoculture

Submitted by tterrasi on Wed, 11/08/2017 - 20:22

 In a monoculture stand of plants, the number and size of seedlings can change over time. Individual plant sizes are generally extremely uneven. Usually, a few large individuals dominate an available area given, while most individuals remain very small.  This unevenness is highly unequal in size distribution, which is characterized by size hierarchies that can be attributed to asymmetric competition – larger individuals have negative effects on smaller neighboring individuals. With a starting population that is relatively homogeneous, as time goes on, the distribution becomes increasingly unequal with the proportion of smaller plants increases and smaller number of large plants. Eventually, over time, self-thinning occurs, which is when death removes the smallest individuals from the population, in this case, so that the population is less unequal as time goes on.

Cancer: causes and development

Submitted by tterrasi on Tue, 10/24/2017 - 11:11

Tumors are classified, as either benign or malignant, meaning the tumor is non-cancerous or cancerous. DNA damage is one possible way cells turn into cancer cells. This can occur due to many factors, such as exposure to toxins, radiation, diet, infection, and hormones. Cancer mutations are progressive and happen in multiple steps. Firstly, a normal functioning cell will divide into daughter cells by mitosis, but one or more of the daughter cells will have a mutation. By the time a cell divides three or even four more times, the cell is highly likely to be cancerous. The more often mutated cells divide the more likely the cell will be malignant, grow uncontrollably and have an abnormal phenotype (Kleinsmith).  When a normal cell grows, the cell goes through checkpoints to ensure that the cell is mature and function properly. But, cancer cells evade this process and divide uncontrollably, not going through an apoptotic pathway. Also, growth factors, which are proteins, stimulate cell growth and division. In cancer cells, growth receptors can be mutated so that these signals are always on to tell the cell to divide. In normal cells, these signals are turned on and off. If the cell was always on and is always dividing, then tumors will develop, and can eventually spread throughout the body by metastasis (Kleinsmith).

 

Cancer: causes and development

Submitted by tterrasi on Mon, 10/23/2017 - 21:17

               Cancer is a complex group of diseases with many possible causes. There are many different factors that cause cancer development in organisms. According to The American Cancer Society, genetic factors, tobacco use, diet and physical activity, infections and environmental exposures to different types of chemicals and radiation are only a few factors that lead to cancer. The uncontrolled proliferation of cancer cells, combined with their ability to spread throughout the body, makes cancer a potentially life-threatening disease (Kleinsmith).                 

               There are a few steps that lead to cells becoming tumors before it turns into cancer. Cancer develops when cells in a part of the body begin to grow out control. These cells arise due to damage to DNA. There are three main gene families that are major factors to cancer: Oncogenes, DNA repair genes, and tumor suppressor genes. Damaged genes can be inherited, but most often caused by environmental factors. In cancer cells, the damaged DNA is not repaired and does not undergo apoptosis. After this, the cell begins to divide rapidly and then uncontrolled cell division leads to tumor development (Keinsmith).                              

                Tumors are benign or malignant, meaning the tumor is either non-cancerous or cancerous. DNA damage is how cells can turn into cancer cells. This can occur in many ways like exposure to toxins, radiation, diet, infection, hormones, and others as listed above. Cancer mutations are progressive and happen in multiple steps. A normal cell will divide into daughter cells by mitosis, but one or more of the daughter cells will have a mutation. By the time a cell divides three or even four more times, the cell is highly likely to be cancerous. The more the mutated cell divides the more likely the cell will be malignant, grow uncontrollably and look deranged or abnormal (Kleinsmith).  When a normal cell grows, the cell goes through checkpoints to make sure that the cell is mature and ready to function. But, cancer cells ignore this process and divide uncontrollably. Also, growth factors, which are proteins, stimulate cell growth and division. In cancer cells, growth receptors can be mutated so that these signals are always on to tell the cell to divide. In normal cells, these signals are turned on and off. If the cell was always on and are always dividing, then tumors will develop all over the body (Kleinsmith).

Works Cited:

Kleinsmith, L (2006). Principles of Cancer Biology. Chapters 1-4.

The American Cancer Society. http://www.cancer.org/cancer/cancercauses/ 25 June 2014. Web, 23 October 2017.

 

           

 

Figure legend for R software data set

Submitted by tterrasi on Fri, 10/20/2017 - 15:24

Figure 1. In panel 1, the graph shows that the female GPA mode is around 3.0-3.5 and for male there is a bimodal distrubution around 1.5 and 3.5. In panel 2, there is no relationship between the amount of hours slept per week and GPA for males, and a weak positive association of hours slept per week and GPA in females. In panel 3, In both genders there is a strong positive association between hours studied per week and GPA. As the numbere of hours studied increases, so does the GPA. In panel 4, there seems to be no relationship between GPA and hours slept per week in males, and a moderate positive relationship between GPA and hours slept per week in females. In panel 5, there is both a bimodal distribution in males for hours slept per week is around 35 and 60 and females is also around 35 and 60 hours slept per week. In panel 6, the females have a positive association between hours studied per week and hours slept per week. The opposite is true for males in this panel. In panel 7, there is a positive association bewteen GPA and hours studied per week in both genders. As the GPA increases the hours studied also increases. In panel 8, there is a negative association between hours slept and hours studied per week for males, but a positive association for females. In panel 9, there is a unimodal distribution for hours studied per week in females around 7 and 10, and a bimodal distribution of hours studied per week in males around 5 and 8, and 9 and 10.

Gut microbiome may affect your risk for colorectal cancer

Submitted by tterrasi on Tue, 10/17/2017 - 10:09

The diversity and richness of bacteria in the human gastrointestinal tract, plays a significant role in our physiology. A healthy, balanced microbiome depends on a multitude of factors of exposure after birth, which includes diet and environment. A poor environment, diet, stress, or antibiotic use, can lead to dysbiosis – a microbial imbalance –, which causes intestinal barriers to breakdown, allowing for bacteria to migrate into extra-intestinal sites. Movement of bacteria to where it did not previously inhabit, can lead to inflammation and certain cancers such as colorectal cancer. By eating a diet made-up of more saturated fats and not enough fiber may also cause dysbiosis. As an aside, when the proportions of these macronutrients go from being imbalanced to being balanced, mucosal proliferation and colonic mucosal inflammation can decrease in about two weeks. This means decreasing the risks of dysbiosis that lead to physiological and psychological changes.  

Gut microbiome may affect your risk for colorectal cancer

Submitted by tterrasi on Mon, 10/16/2017 - 18:51

     The bacterium in our guts has a symbiotic relationship, which plays a big role in our physiology. A healthy microbiome depends on exposure after birth, diet, environment, etc. A poor environment, diet, stress, or antibiotics can lead to dysbiosis— a microbial imbalance— which causes intestinal barriers to break, allowing bacteria to move into the extra-intestinal sites. Movement of bacteria to where it does not belong leads to inflammation, and may lead to cancer. Eating more saturated fat and not enough fiber may also cause dysbiosis, but mucosal proliferation and colonic mucosal inflammation can decrease in two weeks when the proportions of those macronutrients are changed.

     A large study was performed on mice with cancer matches patients with colorectal cancer. The colorectal cancer patients had more Enterococcus faecalis, Bacteroids fragilis, Escherichia coli, and Fusobacterium nucleatum in their microbiome, which cause inflammation. The mice model proves humans can be affected by the bacteria’s genotype, which interacts with the human’s diet to change their microbiota diversity and function. Calorie, macronutrient, and micronutrient intake affect microbiome diversity. Studies are being done to test if fecal microbiota transfers are a safe cancer treatment. Researchers believe changing a patient’s microbial community with a fecal microbiota transplant will decrease chronic gut inflammation. The study concluded that diet is the only factor we can control; therefore, we should use it to benefit our microbiome. Researchers believe that studying our diets further can show how changing our behaviors and microbiota affect cancer risk.

Citation: Arkan, M. Canan. 2017. “The intricate connection between diet, microbiota, and cancer: A jigsaw puzzle”. http://www.sciencedirect.com/science/article/pii/S1044532317300234. http://doi.org/10.1016/j.smim.2017.08.009.

"Missing Link" explains how viruses trigger immunity

Submitted by tterrasi on Thu, 10/12/2017 - 14:55

Viruses trigger a protective immunity within the human body, but how this occurred was a mystery until now. During a viral infection, RNA is released into the environment around infected cells. The research team showed that SIDT2 allowed viral RNA to be shuffled between compartments of a cell, allowing it to reach proteins that trigger anti-viral immunity. The type of RNA that is released by the virus is double-stranded, and is not normally found in the human body. By detecting this form of RNA, it acts as a warning of a viral infection, such that double-stranded RNA acts as a trigger for cells to elicit an anti-viral immune response. Cells “take up” sample areas of their environment into compartments called endosomes. Scientists did not know how double-stranded RNA reached the cytoplasm without being taken up by the cell, where it is then detected. SIDT2 was the missing piece that is needed to transport double-stranded RNA out of the endosomes to elicit an immune response.

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