I've read that unlike humans, octopuses have eyes "designed" the "right way", i.e. with the nerve fibers behind the retina, thus getting rid of the blind spot we humans have as well as theoretically improving eyesight.
Have there been tests to compare octopus sight with that of humans, and do they indeed have better vision than us?
Also, this question is going to be slightly gross, just a warning, but I promise it comes to a point.
I have read that the adenoids have a texture to them but, unlike say the palatine tonsils, they don't have crypts.
Last year my palatine tonsils became fairly badly infected and had to be removed over the summer. Before the surgery, I discovered I could reach back to the tonsils with my tongue, enabling me to remove the tonsil stones that built up. Gross, I know, but I believe it actually did make the infection noticeably better. After the surgery, and after the area had healed, I resumed discovering the back of my throat and, eventually, up the nasal cavity, all the way to the back of the nasal septum, which means I can reach the Eustachian tubes, adenoids, and posterior nares. If that sounds impossible, I assure you, it is perfectly achievable, and only mildly uncomfortable. With my tongue I can feel the texture of the adenoids but, more toward the posterior nares, this texture changes and resembles folds or crypts like I remember the texture of the palatine tonsils. Three times, always in the morning after waking up, I have discovered debris in this region strongly resembling tonsil stones but green instead of off white. The mucus, however, is always clear.
My question has several parts:
- What are these crypts? Are they even crypts at all? Are they part of the adenoids?
- Why can I not find mention to these structures in any diagrams or medical articles?
- Why can I not find mention to tonsil stone like debris except in the palatine tonsils? I am quite convinced that, if these are not tonsil stones of a sort, they are closely related.
The proportions of diagrams and cross sections of the nasal cavity all seem wildly different. Some of them are just blatantly wrong, depicting, for example, the Eustachian tubes coming from the roof of the nasal cavity instead of the sides. It has been very difficult to find good information on any of this. I am not even sure if I am referring to the region correctly. By nasal cavity, I mean everything between the back of the throat and the posterior nares, although I am aware the nasal cavity includes the region all the way up to the anterior nares as well.
This is the only picture I can find that shows the nasal septum.
This is a better diagram of the rest of the structures. The pharyngeal tonsils are the adenoids.
In a 1987 article "Nonenteric Infections Acquired through Contact with Water", the author mentioned that "Infection of the ears, throat, respiratory tract, and cornea are also encountered" by virulent strains of Acanthamoeba and Naegleria fowleri. The only reference that implicates Naegleria fowleri is this one, but it doesn't mention modes of infection.
The long and the short of it is that Acanthamoeba infections can be acquired through contact with the cornea, but it's not clear whether Naegleria infections can also be acquired in this way.
n.b. The first link takes you to the JSTOR page. In the event you do not have access, here is the PubMed page.
Well, there are a number of problems. First, the discovery of noncoding RNAs is relatively new and they are difficult to detect, so their number is unknown. In addition, it is unknown how many of them are functional. This has also made it very difficult to define what a gene is and thus made it difficult to count how many genes there are.
Protein coding genes, however, are much easier to deal with, and if you like you can enter any public protein database (at NCBI, for example) and easily query the number of distinct proteins.
Finally, the last problem is that with an organism like human, experimental methods are generally limited by sensitivity (might not detect proteins/RNA at very low concentrations) and the fact that you can't measure all possible cell types/conditions (many gene products will be cell type/condition specific).
Who said life is easy? Somehow things are always complicated in biology...
There are so many techniques/methodologies in the life sciences that we can use to interrogate interesting questions. The thing is, most of us are completely unaware of the available methods we can employ. Rather, we go with the techniques we are familiar with or that are popular in our subdomains at the time. But that's pretty limiting.
So I'm wondering... we have databases for everything else... is there one for life sciences techniques/methods? Something like this could be immensely helpful in experimental planning. In particular, I think a comprehensive database would help scientists break outside of their spheres of familiarity and to employ less known (but potentially illuminating) methods to their questions.
I know there are journals that publish protocols and methods, but they are fragmented and don't encompass everything.
Does what I'm looking for exist? If not, how might one go about creating such a tool?
There seems to be a lot of redundancy in PDB files. These files can of course be compressed with general-purpose compression programs like gzip, but I can't help but imagine that these tools are overlooking a significant amount of redundancy in PDB files. Are there compressors that specifically target PDB files? If not, what are some aspects of PDB files that are ripe for compression?
Looking at a typical PDB file, some redundancies are immediately apparent. Other redundancies are less obvious. Consider this excerpt of two residues from 1MOB (myoglobin):
ATOM 332 N LYS A 42 16.481 27.122 -10.033 1.00 11.15 N
ATOM 333 CA LYS A 42 15.926 28.134 -9.159 1.00 8.64 C
ATOM 334 C LYS A 42 16.970 29.081 -8.512 1.00 16.74 C
ATOM 335 O LYS A 42 16.687 30.075 -7.799 1.00 11.84 O
ATOM 336 CB LYS A 42 15.093 27.489 -8.043 1.00 18.03 C
ATOM 337 CG LYS A 42 13.731 26.888 -8.502 1.00 19.65 C
ATOM 338 CD LYS A 42 12.679 27.912 -8.953 1.00 17.94 C
ATOM 339 CE LYS A 42 11.438 27.406 -9.703 1.00 24.82 C
ATOM 340 NZ LYS A 42 10.474 28.567 -9.803 1.00 19.81 N
ATOM 341 N PHE A 43 18.218 28.599 -8.544 1.00 12.28 N
ATOM 342 CA PHE A 43 19.311 29.318 -7.919 1.00 11.81 C
ATOM 343 C PHE A 43 20.223 30.024 -8.949 1.00 10.95 C
ATOM 344 O PHE A 43 21.201 29.462 -9.450 1.00 10.08 O
ATOM 345 CB PHE A 43 20.138 28.301 -7.137 1.00 9.30 C
ATOM 346 CG PHE A 43 19.494 27.689 -5.877 1.00 9.53 C
ATOM 347 CD1 PHE A 43 19.572 28.376 -4.679 1.00 12.01 C
ATOM 348 CD2 PHE A 43 18.837 26.465 -5.923 1.00 10.54 C
ATOM 349 CE1 PHE A 43 18.993 27.861 -3.536 1.00 9.59 C
ATOM 350 CE2 PHE A 43 18.261 25.959 -4.775 1.00 8.62 C
ATOM 351 CZ PHE A 43 18.341 26.666 -3.597 1.00 7.89 C
These two residues occupy 1,638 bytes as plain text; when compressed with gzip, they occupy 467 bytes. For reference, the format of ATOM records in PDB files is defined at wwpdb.org/documentation/format33/sect9.html#ATOM.
Almost all of the data in the above excerpt seems redundant. The first field (ATOM), second field (atom index, e.g. 332 in the first row), sixth field (residue index, e.g. 42), tenth field (occupancy, e.g. 1.00) and last field (element name, e.g. N) seem clearly extraneous. The fourth field (residue name) could be shortened from three characters to 1 character, or simply an integer. I'm not a data compression expert, but I imagine gzip picks up most of this redundancy.
Slightly less obviously, the atom names for each residue also seem unnecessary. To my understanding, the atomic composition of all residues' backbones will always be the same, and represented in PDB files as "N", "CA", "C", "O". The same for the atomic composition of the residues' respective sidechains: a lysine sidechain will always be "CB", "CG", "CD", "CE", "NZ" and a phenylalanine sidechain will always be "CB", "CG", "CD1", "CD2", "CE1", "CE2", "CZ".
A subtler redundancy, but one that might increase compressibility a lot, seems like it could be in the atomic coordinates themselves. For example, in the backbone, would it be possible to deduce each residue atom's X, Y and Z coordinates (12 data points: 4 atoms * 3 coordinates) given only their phi, psi and omega dihedral angles (3 data points)? Could applying dihedral angles to atoms within sidechains similarly remove the need to explicitly list the 3D coordinates there?
Could "temperature factor" (the second to last field in the excerpt) be losslessly removed, or compressed in some non-obvious way? What are some other possible optimizations that could be used to more efficiently compress PDB files? Are there any obvious grave performance implications of these various compression techniques on the speed of a hypothetical decompressor to convert back to the official PDB format? Have these questions been answered in the literature or an existing PDB-specific compression program?
Thanks in advance for any answers or feedback.
Edit:
Given that no PDB-specific file compressors seem to be available, I suppose my specific goal is to develop one. One potential application I see for this is in significantly decreasing fresh times-to-render in certain use cases of browser-based molecular visualization programs, e.g. Jmol, ChemDoodle Web Components or GLmol. Another application could be decreasing the time and size of data needed to download archives of PDB files like those described here.
This would of course require a way to efficiently decompress the packed PDB files, but this trade-off between decompression time and download time seems like it could be useful in at least some niche applications.
Edit 2:
In a comment, nico asks "How would compressing the file decrease render time?". Decreasing gzipped PDB file size (e.g. by half or more) and thus decreasing time needed to download the file would decrease the time between when the PDB file was requested from a remote server and when the structure was rendered by a molecular visualization program running on a client machine. Apologies if that use of "fresh time-to-render" in that context was unclear.
A lossless compression could also involve encoding the PDB file to an object (e.g. JSON) that is faster to parse for the visualization program, and decrease render times that way. Looking around further, if the application only required displaying the 3D structure and not also retaining data about specific atoms and residues, then using a binary mesh compression (e.g. webgl-loader) seems like it would probably decrease time-to-render even more.
I want to ask what is the reason that T315I type CML leukemia is currently untreatable. I have read quite a few papers in this subject. Why the current genetic oriented engineering drugs failed to stop the leukemia stem cell's expansion but can only slow the secondary leukemia stem cell's expansion? I found it to be utterly hopeless for a patient to be in such a position, as chemical therapy does not work well and radiation therapy can only target specific area. There are experimental drugs in the developmental stage but from what I know they are mostly unreliable.
There is nothing special about the use of rhodopsin when compared to making a cell express any transgene. This question can then be read as:
What is the process in which a cell population is targeted and implanted with a gene of interest?
There are many ways, which depend on the specific cell type and on whether you want to do it in vitro, in vivo and in which species, and it would be very complex to explain them all in detail here, so I will limit myself to two approaches that are popular when doing optogenetics in rodents: viral infection and transgenesis.
Viral infection uses an inactivated virus to deliver the transgene. Essentially you engineer a piece of DNA with the gene for the bacterial opsin of interest and you put it in a viral envelope, that is a series of proteins that form the "body" of the virus and that contain its genetic material.
You then inject the virus in the desired zone (e.g. in a specific brain nucleus) and wait for it to infect the cells around the injection site. A week later those cells will express the transgene.
For (at least, I think) historical reasons the first type of viruses used for this approach were lentiviruses. These, however, are a tad more complex to handle (especially as they require specialised rooms where they can be handled safely) so adeno-associated viruses (AAV) are becoming more and more popular.
Note that the virus is inactivated, that is, it cannot replicate, just infect the cells around the infection site, but it will not be able to spread around. This is both for safety reasons and because you want the infection to be confined to the specific region where you injected the virus.
As I was saying before, instead of putting a bacterial opsin you can put whatever gene of interest, the procedure is the same. As for the opsins, the first two that were used were the channelrhodopsin-2 (ChR2), a channel sensitive to blue light and that can be used to depolarize (=excite) the cells and the halorhodopsin (NpHR), a chloride pump sensitive to yellow light that will, conversely, hyperpolarize (=inhibit) the cells.
There are nowadays tens of variants of these and other opsins that can be used to drive cell activity with lights. Many of these are described in this (beware! Quite technical) review:
Optogenetics in neural systems - Yizhar et al., Neuron 2011
Transgenesis works instead by generating an animal that carries the opsin (or any other gene) in its DNA. This can be done in various way, such as by microinjection of embryonic stem cells carrying the transgene.
You can find a fairly detailed explanation of the process here: Transgenic Cells and Gene Knock-outs, well summed up by this figure (taken by the same page):
But how do you get cell-type selectivity?
In front of the gene for the opsin you also will have to put another sequence, called promoter. The promoter is a sequence that is specific to each gene and that is used to determine which genes a cell will or will not transcribe. For instance, the promoter for the gene coding for a protein only present in muscles will be used by muscle cells but not by neurons. You can even get more specific, for instance by using promoters that are typical of a subset of cells and not other (e.g. glutamatergic neurons use a different set of promoters than GABAergic neurons, although these two sets will -at least in part- overlap). However, this means that if you want to change the cell type you are working on you will have to change the DNA vector you are using.
A commonly used approach to avoid this is that of using Cre-dependent vectors (note that this can be used both for viral infections or for transgenic animals).
Essentially you will have a mouse line which expresses a protein derived from the P1 phage, called Cre recombinase, only in the cell type of interest (again, using a specific promoter). Cre has the property of cutting DNA next to specific 34 base-pair-long sequences called loxP (with sequence ATAACTTCGTATAGCATACATTATACGAAGTTAT). Essentially, if you have loxP-[some sequence in the middle]-loxP and Cre recombinase is around, it will cut away the sequence in the middle, leaving only a loxP sequence.
Hundreds of different Cre-expressing mouse lines are commercially available nowadays, to target many different cell types in different organs.
Now, you just need a construct that allows you to express the opsin in a Cre-dependent manner. This is what was done by the group of Hongkui Zeng, and reported in this paper:
A toolbox of Cre-dependent optogenetic transgenic mice for light-induced activation and silencing. - Madisen et al., Nat. Neurosci. 2012
Without going into too much details, the idea is to flank a STOP sequence with two loxP sites. This will block transcription (that is what a STOP sequence does) unless Cre-recombinase is present.
Essentially:
Source: myself, CC-by-sa licensed, feel free to reuse it
Note that in the scheme, ROSA26 is an ubiquitous promoter, that is, a promoter used by all cells, so in this case the specificity is given by expression of Cre recombinase and not by the promoter of this construct. Also, a fluorescent reporter (e.g. GFP) is inserted to be able to visualize where the opsin is expressed.
By breeding these mice with the Cre-line(s) of your choice you can then express the opsins in the cell type of your interest.
Dogs have a genomic structure that allows breeding with high variation in size, shape, coat quality, color and other qualities particular to each breed as well.
Other domesticated animals can be bred for as many qualities, but dogs in particular show a wide level of morphological traits - varying in size from just over a pound to the size of a wolf, from which dogs are derived and genetically are still compatible. But more interesting than just size or coat color/texture and even their intelligence and personalities, the proportions of their bodies, of their skull length and breadth, are remarkable.
There are over 160 registered breeds of dogs, but this is only a measure of how much time people have put into them. I think its possible to get nearly anything you want with animals, if you are patient enough - its not clear what is and is not possible with enough genetic manipulating. For instance, horses can be bred over nearly as great a size range for instance (the miniature horse the size of a large dog, the Shire is 3,300 pounds), but it would not be as easy to get both the size and muscularity and shape of a bulldog in a horse. Breeding a mouse of various colors can be done, and so can interesting behaviors, but body shape seems to be harder a Weimaraner mouse could take a tremendous amount of time and animals.
Not an answer, but just a suggestion:
If you are in a position where you must read off of a computer monitor without ample ambient light, I'd suggest you try setting your monitor/reader/whatever to have a dark background and light/wight text so it doesn't feel like you're staring into the sun.
I think any discussion of this question can benefit from a historical perspective. For a long time, it was in fact believed that proteins was the hereditary material. The Nature Scitable page on the discovery of DNA (1) starts with the following passage:
In the first half of the twentieth century, Gregor Mendel's principles
of genetic inheritance became widely accepted, but the chemical nature
of the hereditary material remained unknown. Scientists did know that
genes were located on chromosomes and that chromosomes consisted of
DNA and proteins. At the time, however, proteins seemed to be a better
choice for the genetic material, because chemical analyses had shown
that proteins are more varied than DNA in their chemical composition,
as well as in their physical properties.
While perhaps easy to dismiss in hindsight, it is possible to understand the reasoning of the day. The "central dogma" of molecular biology, that genetic information flows from DNA to RNA to proteins was only described later, and explained how the production of complex proteins consisting of 20-odd amino acids can be directed by a polymer consisting of only four nucleotides. This allows great complexity and variety in phenotypes while maintaining simplicity of the genetic material. The central dogma also facilitates the seperation of the use (through protein expression) and storage (as DNA) of genetic material.
As Watson and Crick noted in their famous paper, the double helix of DNA, when discovered, immediately suggested how the genetic material could be elegantly copied. While the more complex structure of proteins would likely require a more complex copying mechanism, the specification of amino acids through three-nucleotide codons in DNA allows the regularity of the DNA material to be retained for easy replication while allowing complex proteins to be produced.
However, even though DNA is the primary genetic material today, the situation may have been different at the time life first appeared. According to the RNA world hypothesis, RNA may have been the original genetic material and that DNA is a variation of RNA, not the other way around as it is commonly seen.
For a fuller historical perspective, I recommend the book "What is Life?" by Erwin Schrödinger, which was written before the discovery of DNA as the genetic material.
According to Psychoanalysis101.org, it is quite rare to be able to control dreams, though apparently it can happen 9according to the article. Lucid dreaming is the term to describe when the person is aware that they are dreaming, further research and scepticism of lucid dreaming are outlined in this section of the article.
I'm not sure that all phytoplankton perform the same type of photosynthesis.
Originally, people thought that they all performed C4, on the basis of genome sequencing, which revealed the presence of genes important for C4 photosynthesis. However, experiments on individual species seemed to indicate that the phytoplankton were performing multiple types of photosynthesis (source).
EDIT: CAM is unlikely, as that is an adaptation for dry environments.
EDIT 2: and of course, some phytoplankton appear to have both C3 and C4 pathways. In short, you can't generalize.
This is not really a biological answer, but a psychological one:
One important fact to consider is that the perception of time is essentially a recollection of past experience, rather than perception of the present.
Researchers who study autobiographical memory have suggested that part of this effect may be explained by the number of recallable memories during a particular time period. During one's adolescence, one typically has a large number of salient memories, due to the distinctness of events. People often make new friends, move frequently, attend different schools, and have several jobs. As each of these memories is unique, recollection of these (many) memories gives the impression that the time span was large.
In contrast, older adults have fewer unique experiences. They tend to work a single job, and live in a single place, and have set routines which they may follow for years. For this reason, memories are less distinct, and are often blurred together or consolidated. Upon recollection, it seems like time went by quickly because we can't remember what actually happened.
In other words, it can be considered a special case of the availability heuristic: people judge a time span to be longer in which there are more salient/unique events.
Incidentally, (and to at least mention biology), episodic memory has been shown to be neurally distinct from semantic memory in the brain. In particular, a double dissociation has been shown for amnesics who suffer from semantic or episodic memory, but not both.
My apologies for the lack of citations, but a good bit about autobiographical memories can be found in:
Eysenck, M.W., & Keane, M.T. (2010). Cognitive Psychology: A
Student's Handbook.
You may also be interested in some responses or references to a related question on the Cognitive Science StackExchange:
Alan has covered some of it, but to add an illustration of the malabsorption piece of it, below left you can see a "normal" slice of small intestine, where the villi (finger like projections) are covered in enterocytes (the purple "bricks" along the border of the finger), which are responsible for the uptake of lipids (and their eventual "packaging") after they have been emulsified with bile salts in the intestinal lumen.
The offending gluten causes an autoimmune reaction over time that damages these villi as well as the enterocytes (as seen on the right side of the diagram), leaving a flattened area (hence far less surface area for absorption), and disrupted lipid packaging, so the unabsorbed lipids continue through the intestine into the stool.
from Cell Biology at Yale
Microorganisms constitute the bulk of all the biomass on Earth. I weighed myself yesterday, and wondered how much less I would weigh if I were completely free of bacteria and microbes, inside and out.
Approximately how much weight and volume do microbes occupy within the average human body? How were these values obtained?
it is highly variable even in a single cell type.
Dont know for a human cell but this is the range for ecoli: 1500-11400
check this site out. got this number from there (its quite useful for questions like these):
http://bionumbers.hms.harvard.edu/bionumber.aspx?&id=101440&ver=3&trm=RNA%20polymerase
You can estimate protein copy numbers and there are techniques available for doing so. One of such techniques:
http://www.mcponline.org/content/11/3/O111.009613.long
You can also calculate concentration using traditional techniques like western blot and elisa and calculate approximate copy-numbers (you have to also calculate average cell volume and number of cells for protein extraction.
I'm no thermodynamics expert, but Ill have a go at this.
The energy comes from the original set up, in which you have created a low entropy state. As the diffusion of water molecules equalises their concentration across the membrane so the entropy of the system will increase. This translates to a negative free energy change. That manifests as potential energy stored in the hydrostatic pressure resulting from the changes in volume, which in turn is available to turn the turbine.
So in the case of an experiment of the type described, the energy is derived from the experimenter who sets up the experimental situation in the first place.
It's less a problem of speed and more of raw photon count. Assuming a brightly lit day, the bullet will move so fast that it doesn't reflect enough photons to register against the background. High speed images of bullets usually involve a very bright flash (and other controlled settings) for the camera to pick it up. (Also, a very short flash helps the bullet to appear stationary in the image.
On the other hand, seeing where your bullets are going is pretty useful. Therefore tracer bullets were created, which are essentially a pyrotechnic flare that you substitute in every 5th bullet, typically in machine gun ammunition. Proof that if you make a bullet bright enough, you can register it just fine.
