Gap Junctions: The complex bridge of the body
Gap junctions are a crucial component of cell to cell communication that connects cells and can transport a multitude of products. They can be found in all different types of body cells and assist with a variety of functions
Gap junctions have been found to be present in a variety of bone cells (Doty, 1981). Gap junctions, as intercellular bridges, connected adjacent bone cells and suggest they help in the control/coordination of bone cell activity. In most cells, gap junctions connect the cytoplasm of two cells and can transfer hydrophilic molecules. However, if an immune system response surfaces, rat cells can shut off these gap junctions in order to minimize the spread of a foreign substance (Fraser, 1987).
Gap junctions are even used in cells related to hormone distribution. Thyroid cells were found to reconstruct gap junctions in response to the hormone TSH. However, when the protein Kinase-C was activated, the functional activity of the gap junctions reacted negatively (Munari-Silem, 2009). Showing how different aspects of cell communication can intertwine, gap junctions can be affected by hormones. In fact, gap junctions can have different selectivity because the connexins subunits that form gap junctions can be mixed and matched, leading to a whole realm of complexity on what passes through the junctions (Kumar, 1996).
(Kumar,1996) Model of a pore in a gap junction. The pore is constructed by the different connexin sub units.
Sources
Doty, Stephen B. “Morphological Evidence of Gap Junctions between Bone Cells.” Calcified Tissue International 33.1 (1981): 509-12.
Fraser, S., C. Green, H. Bode, and N. Gilula. “Selective Disruption of Gap Junctional Communication Interferes with a Patterning Process in Hydra.” Science 237.4810 (1987): 49-55.
Munari-Silem, Yvonne, Christine Audebet, and Bernard Rousset. “Hormonal Control of Cell to Cell Communication: Regulation by Thyrotropin of the Gap Junction-Mediated Dye Transfer between Thyroid Cells.” Endocrinology 128.6 (1991): 3299-309.
Kumar, Nalin M., and Norton B. Gilula. “The Gap Junction Communication Channel.” Cell84.3 (1996): 381-88.
Analyzing and Interpreting Genome Sequences
Finding mutations for genetic disorders involves not only the study of genes and their modes of inheritance but the cooperation of the scientific community and the way genomic data is collected and sequenced. Communication between scientific communities is crucial to the propelling understanding of genetic disorders. The genome is universal so gene expressions and mutations in a few individuals can give information about certain genes that are found in all humans.
Figure 1- Timeline of genomic sequencing in non-vertebrates
Source: Lander, ES. Initial sequencing and analyzing of the human genome. Nature 2001.
Genomic sequencing of non-vertebrates such as humans and mice, as shown in Figure 1, has been paramount in learning more about genes. Since the human genome sequencing was completed, researchers have worked to sequence exons, which are DNA sequences that code for proteins (Lyon 2012). This is called exome sequencing, short for “a set of exons in a genome” (Ng 2008). Sequencing genomes were very expensive initially. Work in that field was tied down by costs. As technology improved, a way to sequence genomes cheaply was found in 2007, making the field exome sequencing easier to research (Albert 2007). In 2008, the causes for syndromes such as Bartter syndrome were found through exome sequencing (Choi 2009). Genome and exome sequencing became more available through companies founded with the goals of sequencing them at low costs. Genome or exome sequencing are used to find genetic causes of disorders such as diabetes and autism, to diagnose patients, and to study pedigrees (Bonnefond 2010, Hedges 2009).
Unfortunately, exome sequencing cannot be used to learn about all genetic disorders. Some disorders are caused by mutations in the non-coding regions of DNA (Cartault 2012). It is estimated that genetic causes are found in only 10% to 50% of cases by exome sequencing, but it is difficult to tell because most researchers that fail to find a genetic cause through exome sequencing do not publish that they failed (Lyon 2012).
Genome sequencing is more readily available, but there is a tremendous amount of data that needs to be analyzed and interpreted. The field of bioinformatics deals with analyzing and interpreting genomic data. Current technology such as software tools should be improved to aid in sequencing these data. Software tools have limited ability because they can only analyze one type of data that came from one type of experiment for sequencing (Lyon 2012). However, there is not enough support to improve these tools. As a result, a genome sequence that costs $1,000 is in reality much more expensive (Lyon 2012). Analyzing the sequence will cost $20,000 to $100,000 (McPherson 2009). The astronomical cost caused those working in genomics to seek better technology so newer software programs were released (Lyon 2012). The problem still remains, however, that larger amounts of data need to be analyzed more quickly and accurately with practical costs.
There is a more practical way of analyzing and interpreting genomic data. Instead of each individual or team analyzing an entire genome, several groups can analyze one genome and share data with each other. In addition, genomic data and its analyses can be made available to the entire scientific community to spread knowledge. Collaboration in the scientific community has produced amazing results in the past in sequencing the human genome for the first time. It can work again to analyze the genome. There may be privacy concerns because there are several ways to thinking about who “owns” a genomic sequence from an individual (Lyon 2012). Companies that store, analyze and interpret the sequence may own it or the individual that the sequence came from may own it. Currently, the consensus is that the individual the genomic sequence came from owns the sequence (Lyon 2012). There may also be other concerns between data sharing among scientists. However, it is undeniable that collaborating to tackle the problem of analyzing and interpreting genomic sequences to find the genetic basis for genetic disorders is a smart idea.
Works Cited
Albert TJ, Molla MN, Muzny DM, Nazareth L, Wheeler D, Song X, Richmond TA, Middle CM, Rodesch MJ, Packard CJ, Weinstock GM, Gibbs RA: Direct selection of human genomic loci by microarray hybridization. Nat Methods. 2007, 4: 903-905. 10.1038/nmeth1111.
Bonnefond A, Durand E, Sand O, De Graeve F, Gallina S, Busiah K, Lobbens S, Simon A, Bellanné-Chantelot C, Létourneau L, Scharfmann R, Delplanque J, Sladek R, Polak M, Vaxillaire M, Froguel P: Molecular diagnosis of neonatal diabetes mellitus using next-generation sequencing of the whole exome. PLoS One. 2010, 5: e13630-10.1371/journal.pone.0013630.
Cartault F, Munier P, Benko E, Desguerre I, Hanein S, Boddaert N, Bandiera S, Vellayoudom J, Krejbich-Trotot P, Bintner M, Hoarau JJ, Girard M, Génin E, de Lonlay P, Fourmaintraux A, Naville M, Rodriguez D, Feingold J, Renouil M, Munnich A, Westhof E, Fähling M, Lyonnet S, Henrion-Caude A: Mutation in a primate-conserved retrotransposon reveals a noncoding RNA as a mediator of infantile encephalopathy. Proc Natl Acad Sci USA. 2012, 109: 4980-4985. 10.1073/pnas.1111596109.
Choi M, Scholl UI, Ji W, Liu T, Tikhonova IR, Zumbo P, Nayir A, Bakkaloglu A, Ozen S, Sanjad S: Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. Proc Natl Acad Sci USA. 2009, 106: 19096-19101. 10.1073/pnas.0910672106.
Hedges DJ, Burges D, Powell E, Almonte C, Huang J, Young S, Boese B, Schmidt M, Pericak-Vance MA, Martin E, Zhang X, Harkins TT, Züchner S: Exome sequencing of a multigenerational human pedigree. PLoS One. 2009, 4: e8232-10.1371/journal.pone.0008232.
Lander ES, Linton LM, Birren B, Nusbaum C, Zody MC, Baldwin J, Devon K, Dewar K, Doyle M, FitzHugh W, Funke R, Gage D, Harris K, Heaford A, Howland J, Kann L, Lehoczky J, LeVine R, McEwan P, McKernan K, Meldrim J, Mesirov JP, Miranda C, Morris W, Naylor J, Raymond C, Rosetti M, Santos R, Sheridan A, Sougnez C, et al: Initial sequencing and analysis of the human genome. Nature. 2001, 409: 860-921. 10.1038/35057062.
Lyon GJ, Wang K: Identifying disease mutations in genomic medicine settings: current challenges and how to accelerate progress. Genome Medicine. 2012, 4: 58. 10.1186/gm359.
McPherson JD: Next-generation gap. Nat Methods. 2009, 6: S2-5. 10.1038/nmeth.f.268.
Ng PC, Levy S, Huang J, Stockwell TB, Walenz BP, Li K, Axelrod N, Busam DA, Strausberg RL, Venter JC: Genetic variation in an individual human exome. PLoS Genet. 2008, 4: e1000160-10.1371/journal.pgen.1000160.
Different Theories That Attempt To Describe and Explain The Universe
Many scientists have attempted to explain the universe we reside in through many different theories. None of them are absolute of course, but some tend to be more believable than others. While there is no definite evidence that fully supports any single theory, based on what we see so far, we can only assume that one is correct depending on how the theory’s intricacies match up to and are in accordance with mathematical equations that describe the governing laws of physics. Many theories and models can be explored, with the prevalent ones being the multiverse theory, Quantum Field Theory, the Anisotropic model, and the currently accepted, Big Bang Theory.
One of these theories consists of an anisotropic model of the universe. This model explores a role “in the study of cosmic highly excited strings in the early universe” (Sepehri et al., 2015). These strings mentioned became an important part to this theory because they were supposedly created during the phase transition after the Big Bang explosion, with the temperature lowering, with them “then decay[ing] to standard model particles at the Hagedorn temperature” (Sepeheri et al., 2015). Essentially the theory shows that vector string tachyons, a big rip singularity, control the expansion of the anisotropic universe, whilst shifting from the non-phantom phase to the phantom phase with the phantom-dominated era of the universe accelerating and ending up in a big rip singularity (Sepehri et al., 2015).
Another theory, Quantum Field Theory, asserts that quantum fields propagate on a classical background, defining quantum phenomena “in a regime where the quantum effects of gravity do not play a dominant role, but the effects of curved spacetime may be significant” (Tavakoli and Fabris, 2015). This theory of quantum fields becomes invalid in classical curved spacetime, with regimes arbitrarily close to the classical singularities. Here the spacetime curvatures become extremely small, relative on Planckian scales and so the quantum effects of gravity are no longer negligible (Tavakoli and Fabris, 2015). This theory is explained through many complex mathematical equations and finds some foothold as a plausible theory explaining the creation of particles in a cyclic universe.
A microgravity environment for the central nervous system allows us to explore the beginnings of mankind, in a purely theoretical sense. While this article doesn’t primarily discuss the origins of the universe, it relates to the beginnings of mankind and draws a connection to the universe. The connection is made with simply the limbic system, with connections between the brainwaves, oscillations and our soul, with the soul being our origin and the greater limbic system being the seat of the soul. The article asserts that everything moves in a wave-like pattern, where everything is oscillating, and this idea is related to parts of the human bodies that create wave-like oscillations, such as “brain waves, heart rate, blood pulsation, and pressure, respiration, peristalsis for most living creatures and oscillations or waves for the whole of the universes contents” (Idris, 2014). These relations highlight the basis of this theory, which has more to do with similarities as opposed to mathematical logic and proofs.
One of the better-known theories proposed is the theory of the multiple universes, in which an infinite number of universes exist that accommodate all possible scenario of events, called the multiverse theory. The theory presents a “many-worlds view, in which all possible outcomes of a quantum measurement are always actualized, in the different parallel worlds, and a one-world view, in which a quantum measurement can only give rise to a single outcome” (Aerts & Bianchi, 2014). This is made possible by many quantum measurements happening frequently, thus allowing for multiple pictures. This theory draws some basis from the equations from quantum theory that describe waves, however the multiverse theory assumes an illusion of just one image being created by the results of quantum theory (Vaidman, 2015).
Currently there are many theories and attempts being made to describe the universe, but they are immensely difficult to explain and involve many intricacies. Even with all the specificities of each theory, most fall short in some aspect and due to the lack of complete knowledge, we cannot fully accept a theory. The Big Bang Theory explains many of the phenomena we have come to known and understand and explains them well according to our knowledge thus far, but we cannot fully accept it yet. For the time being however, it is the currently accepted theory.
Figure 1. Numerical solution for the scale factor of the universe represented as a graph. Oscillatory behavior is shown for the scale factor in the whole evolution of the universe (Tavakoli & Fabris, 2015).
Works Cited
Aerts, Diederik, and Massimiliano Sassoli de Bianchi. “Many-Measurements Or Many-Worlds? A Dialogue.” Foundations Of Science 20.4 (2015): 399-427.
Idris, Zamzuri. “Searching For The Origin Through Central Nervous System: A Review And Thought Which Related To Microgravity, Evolution, Big Bang Theory And Universes, Soul And Brainwaves, Greater Limbic System And Seat Of The Soul.” Malaysian Journal Of Medical Sciences 21.4 (2014): 4-11.
Sepehri, Alireza, Anirudh Pradhan, and Hassan Amirhashchi. “Removing The Big Rip Singularity From Anisotropic Universe In Super String Theory.” Canadian Journal Of Physics 93.11 (2015): 1324-1329.
Tavakoli, Yaser, and Júlio C. Fabris. “Creation Of Particles In A Cyclic Universe Driven By Loop Quantum Cosmology.” International Journal Of Modern Physics D: Gravitation, Astrophysics & Cosmology 24.8 (2015): -1.
Vaidman, Lev. “The Emergent Multiverse: Quantum Theory According To The Everett Interpretation.” British Journal For The Philosophy Of Science 66.2 (2015): 465-468.
Finding their way home: Different ways that cell messengers reach their destination
Cell communication contains various methods in order for its messengers to reach their target cells for both eukaryotic and prokaryotic organisms.
In bacterial cells, we know that they use quorum sensing (QS) as a form of cell communication. This method of communication mirrors how hormones are used in eukaryotic cells. A strand of E. Coli that uses QS was actually found to be able to communicate with eukaryotic cells (Sperandio, 2003). The fact that it can replicate the shapes of our hormones in order to infiltrate our cells shows how advanced bacteria can adapt in order to survive.
However, hormones in some species have been found to work around the specificity for a certain cell. In certain rat ovarian granulosa cells and mouse myocardial cells, it was discovered that hormones for a certain cell were able to reach their target through an unrelated cell and their intercellular communication (Lawrence, 1978). The non-target cell and target cell communicated through a mediator that brought the hormones to the target cell.
In long distance cell communication, it was found that exosomes are a mediator that assist different messengers (Bang, 2012). Exosomes are vesicles that can carry a variety of objects. It was found they could also carry proteins, messenger RNAs and microRNAs. And since exosomes are secreted by a variety of cell types, they can be mediators for all different kinds of pathways and communications between the many cells of the body.
Plant cells also have its own way of long distance communication. Similar to the human body and its circulatory system, plants have phloem transport tubes that connect the most distant organs of plants (Kehr, 2007). The messengers that plants use include RNAs that correspond with physiological processes that are crucial to the plant. The RNA can be translated to important proteins that help the plant function and protect itself.
An example of the phloem tubes in plants. This representation shows how sugar molecules and water travel through the plant cells. (Boundless)
References
Sperandio, V., A. G. Torres, B. Jarvis, J. P. Nataro, and J. B. Kaper. “Bacteria-host Communication: The Language of Hormones.” Proceedings of the National Academy of Sciences 100.15 (2003): 8951-956.
Lawrence, Theodore S., William H. Beers, and Norton B. Gilula. “Transmission of Hormonal Stimulation by Cell-to-cell Communication.” Nature 272.5653 (1978): 501-06.
Bang, Claudia, and Thomas Thum. “Exosomes: New Players in Cellâcell Communication.” The International Journal of Biochemistry & Cell Biology 44.11 (2012): 2060-064.
Kehr, J., and A. Buhtz. “Long Distance Transport and Movement of RNA through the Phloem.” Journal of Experimental Botany 59.1 (2007): 85-92.
“Transportation of Photosynthates in the Phloem.” Image: Translocation to the Sink. Boundless, n.d.
Trusted Traveler Programs
Current aviation security procedures screen all passengers uniformly. Changing the amount of screening some individuals receive has the potential to relieve the burden of frequent travelers while making the screening process more efficient. Trusted traveler programs exist so that some travelers pre identified as “low risk” undergo expedited screening (Caulkins). This allows security resources to be shifted from low risk passenger to the unknown risk population. However, fears arise that terrorists may exploit these programs to harm the community around us.
Trusted traveler programs are one of the many attempts the United States Customs and Border Protection is using to make the international arrivals process faster and more convenient for travelers (Chow, Dreyer). They simplify traveling by eliminating paper forms, expanding the use of Automated Passport Control kiosks, and incorporating mobile apps for travelers. Mobile Passport Control allows travelers to fill out customs declaration forms and biographic information before the passenger even lands (Drury, Ghylin).
NEXUS is a program offered by both the United States and Canadian Border Protection agencies that allows registered users accelerated clearance when entering the US or Canada. The SENTRI program is also similar to the NEXUS program except it offers expedited clearance within the southern US land port of entries and Mexico. FAST is another program that caters to low risk truck shipments between the US from Canada and Mexico (Perisco, Todd).
All of these programs require applicants to undergo an intensive background check with government databases and intelligence as well as in person interview with a customs officer.
These new programs are growing in popularity with over 350,000 people now belonging to NEXUS and are receiving anywhere from 10,000 to 12,000 applicants a month. The SENTRI program is also very successful with over 200,000 people enrolled. By pre screening travelers beforehand, these programs are able to reduce wait times for travelers anywhere from 10 minutes to 2 hours (Richardson, Cave).
Figure 1: Comparison of Trusted Traveler Programs offered to US citizens.
Figure 2: Graph of Automated Kiosks Usage in US Airports
References:
Caulkins JP (2004) CAPPS II: A risky choice concerning an untested risk detection
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