I am quite sure that there is this blood-placental barrier between the mother and the baby so that nothing (except a type of antibody) can pass through it.
But I remember reading somewhere that when a pregnant woman suffers an organ damage, fetus would send stem cells to the damage organ to help repair it.
Anything to support that?
The equations of motion are just second order ordinary differential equations. They can be solved numerically by any of the usual methods, However, for two bodies an exact solution can be found, that solution was known to Kepler. To model the trajectory you need to know the orbital period and the eccentricty (e) of the orbit.
If you know the period of orbit of a body, then the "Mean anomaly (M)" is the angle time/period *2*pi radians (it increases uniformly from zero to 2pi in one orbital period.
The find the Eccentric anomaly ("E", the angle made by the body, the center of the elliptical orbit and the point of periapsis when the body is closest to the sun) you solve $M=E-esin(E)$ (it can be solved by newton's method quickly, though convergence is fastest for roughly circular orbits.
You then know the body is on a ellipse, with the sun at one focus and you have calculated the ray on which the body is found at a given time. This gives you the position of the body.
There is a rough implementation of this in a python gist
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.
Looking at the articles referenced in the Wikipedia article, there's probably no direct physiological link between senescence and beta-galactosides. Lee et al (2006) and others before them have shown that the "hypothetical" protein is just regular lysosomal beta-galactosidase, which is present in higher concentrations in aging and stressed cells because the number of lysosomes increase under those conditions. There's a collection of references in the Discussion section of the Lee paper that delves deeper into the aging-lysosome connection.
I'm well out of my depth by this point, but if I were going to take a wild guess I'd suggest that lysosomal upregulation could be part of a stress response involving autophagy (i.e. the cell breaking down and recycling intracellular materials to meet critical demands), though I don't know the specific connection to aging. As far as beta-galactosides go: if you have any hanging around, you get to eat them, is all, I bet. I bet the references in Lee would tell you if I'm on track or not.
The simple answer is (as with so much in astronomy):
We Don't Know
Parallel universes may or may not exist. There is no definitive way to prove that these universes do or don't exist.
A parallel universe is a separate existence to ours. The Theories that suggest that there may be parallel universes are classified as theories of multiverses. There are many theories of multiverse, all of which propose different ideas about what could exist beyond the limits of our universe. There are also theories that suggest that the multiverse doesn't exist, although the theories with most support are by far the multiverse theories.
For a nice reference in book form, see Steinhardt and Turok's "Endless Universe: Beyond the Big Bang". Also, see Max Tegmark's work on multiverses levels I-IV (Max Tegmark -> See his Scientific American article entitled Parallel Universes).
Antibodies are simply proteins and like any other protein have a relatively short "life", so after clearing out an infection, they are not retained for long (most of them anyway). What the body keeps is memory cells which can produce a much more rapid response if they come in contact with the same pathogen again.
You could see it as a selective process: the body produces immune cells, one or more specific cells for nearly every potential antigen that might exist in the world (there are more steps involved of course but they are of little relevance here). Only those which are used at some point mature into memory cells.
Unfortunately, I just realised that I can't explain why the immune system goes through this selective process; producing cells equivalent to memory cells in the first place would make the immune response much stronger. One explanation I can think of for why the body produces naive cells first is that either a) their production or b) their maintenance is less costly.
The other explanation I could think of is that even immune cells in the periphery which have undergone the proofing mechanisms of immune cell development already, may not be perfect and target body cells every now and then - in that case it would be devastating if they would go all-out like a memory cell.
From my three explanations, only alternative b) would mean there could be a limitation to how many vaccinations our immune system can bear (if memory cells take more effort to maintain than naive cells, having too many of them may overstrain whatever systems maintain them). Otherwise I don't see any limiting factor for how many memory cells you can retain; except if their numbers become so large that your lymph nodes swell and that causes problems.
Edit note: I'm not aware of any research about that question and couldn't find anything either.
I just bought a new telescope with these specifications:
I usually use a 28 mm eyepiece, giving me about 42.5x magnification, but I also have a 20 mm and a 10 mm eyepiece.
I was trying to find Messier objects, but I only found the Orion Nebula, and even then it wasn't very impressive. I was wondering, what types of objects are see-able in my telescope? I read that Charles Messier found the Messier objects using a four-inch refractor, and I have an 8 inch reflecting telescope.
When I tried to find things like the pinwheel galaxy, or the crab nebula, I only saw points of light. So basically, how do I see things like nebula and galaxies?
For reference, I live in the midwestern United States.