text:
"Other" classification for epitopes in the Immune Epitope Database (IEDB)
I used the immune epitope database (IEDB) to search for epitopes. I found some epitopes derived from antigens called " other" by IEDB.  When I asked about it,  the answer was "We use the "other" category to group epitopes from the same species that only BLAST match to GenBank entries that are nonhomologous to the reference proteome".
Could someone explain this?

Welcome to BiologySE @Shad... you've got some abbreviations and technical language that may make it a bit hard for some individuals to follow... you may want to edit it a big (explain some more things) and visit the help center for additional pointers - thanks for your efforts and contribution http://biology.stackexchange.com/help/how-to-ask

I've done what @VanceLAlbaugh suggested for you as I have edit privileges. Good titles make questions more useful to other uses and increase your chances of getting an appropriate answer.

I presume that these epitopes represent peptides that have been eluted from MHC molecules and then sequenced by mass spec.  You can then compare these peptide sequences to a reference genome (more specifically to the proteins predicted to arise from the reference genome).  If the peptide matches perfectly to a predicted protein, then you assign it that identify.
But many peptides will not align to the predicted proteins, and so they can't be unambiguously assigned a gene of origin.
There are many reasons why MHC-derived peptides may not match the proteome.  Most obviously, the reference genomes are typically from a single individual, so if the sequenced peptide has a SNP, or other allelic variation, it won't line up.  As well, a significant number of peptides undergo some form of modification during antigen processing, such as deglycosylation changing Asn to Asp, proteasome-mediated cleavage and re-annealing, and so on.  These modified peptides also won't line up to the predicted proteome.


text:
Identification of a spider from my basement
It's a little over 1" long including legs, and I found it in my basement in Pennsylvania. My guess is a funnel weaver, which would be nice since then I can free it (right?) from the tin can it's currently sitting in.

Thanks!

It is not a Brown Recluse, but it doesn't look like any of the other spiders in that document either. This isn't an ID, but it might at least help you feel a little better about it.

I've changed the title so that it uses the verb "identify" instead of the noun abbreviation, "ID". There was also no need for a question mark as your title was not a question.

I think it's a common wolf spider, which closely resemble funnel weavers. It's almost a toss-up. I can't tell from the resolution of your photograph, but funnel weavers have spiny legs whereas the wolf spider has smooth legs and has a bit more of a difference in the comparative size of the abdomen to thorax.
Wolf spider (coloration varies) vs. funnel weaver (in this case, a barn dweller)

Another distinctive feature of the wolf spider are the two especially large eyes (The Tenegra domestica's eye arrangement is different) which gives the wolf spider such great eyesight. If the legs are smooth, and you shine a light on your spider and see two eyes shine back at you (called eyeshine), I think you have your answer.

Wolf spiders can be found in a wide range of habitats both coastal and inland. These include shrublands, woodland, wet coastal forest, alpine meadows, suburban gardens, and homes.

I let it out of the tin can after user137 ID'd it as not a Brown Recluse, but thanks for the details, especially the bit about eyeshine.

Based on abdominal coloration I'd go with funnel weaver, but it's not really my area.

@arboviral - It's not my area either. :) I agree that the abdominal coloration (and thoracic) is a dead ringer, but the wolf spider coloration is highly variable, and the abdomen shape/size is no help. Unfortunately the specimen is free now, so we'll never know for sure.

I agree with @arboviral . The abdomen pattern is classic barn funnel weaver, and the striped/banded legs are extra confirmation.

Yes, it's Tegenaria domestica, the common funnelweaver House Spider.  It's not a wolf spider; the color patterns on both abdomen and cephalothorax are completely consistent with Tegenaria, but not terribly like the wolf spiders common in our area.  I also find the Tegenaria cephalothorax shape to be more blocky in the front than the normal Wolf Spider shape, but that's a sort of subjective call.  You should be able to find more of them in your basement, especially if you have a furnace or laundry area with bare blocks for walls.  When you find another one, look for the two tailpipe spinnerets sticking out the back end - while not as long as on the outdoor Agelenids, the spinnerets on these indoor ones are still noticeable.  Wolf Spiders don't have that.
Source - any of the spider guides, but let's go with Bug Guide on this one: https://bugguide.net/node/view/31445

Thanks for the answer. Species ID answers need to be accompanied by a proper source, and preferably an image of the species you think it is.

Ah - well, for sources, try Kaston, BJ 1972 How to Know the Spiders (which I realize is more of a lab manual, and which is somewhat outdated, but which is useful also for field work) and perhaps also Cushing and Ubick 2009, Spiders of North America: An Identification Manual and the very attractive (the book, not the author, although I'm sure Mr. Bradley is also lovely) Bradley 2012, Common Spiders of North America.  Also, approximately 40 years of personal experience, although naturally that is a somewhat subjective qualification.

For images of Tegenaria domestica, I could hardly do better than the photo which appears in the original post, but let me add a few to it (from this link):  https://bugguide.net/node/view/31445    Edit:  I seem unable to post images, but when I figure out how to do it, I shall return and toss them in.

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text:
Partial pressure of gases in the alveoli
The atmosphere has a partial pressure of oxygen of 160mm Hg, but in the alveoli it is 105mm Hg. The partial pressure of carbon dioxide in the atmosphere is 0.3mm Hg, but 40mm Hg in the alveoli.
How are these difference maintained, and what is the mechanism behind it?

Many different factors contribute to this difference being maintained. These include long, thin airways, big lungs, and homeostatic mechanisms.
The alveolar air in the lungs is connected to the outside air by long, thin tubes (the trachea is about 11 cm long). Because of this, there is almost no diffusion between the outside air and the alveolar air. To fill our lungs with fresh atmospheric air and get rid of stale alveolar air, we need a more efficient way to transport air.
Breathing creates pressure gradients between the alveoli and the atmosphere, causing a bulk airflow. Inhalation reduces the pressure inside the lungs, which "pulls" atmospheric air into the lungs. Exhalation increases the pressure inside the lungs, which pushes alveolar air out of the lungs. Normally, each breath pumps only a small amount of air in and out of the lungs. The average volume of a breath (inhalation or exhalation) is about 500 milliliters. 150 milliliters of this atmospheric air remain in the airways after inhalation and are exhaled back into the atmosphere without reaching the alveoli. Only 350 milliliters of fresh air are inhaled into the alveoli and only 350 milliliters of stale air are exhaled into the atmosphere in each breath. Since the lungs are big (about 2.5 liters), pumping 350 milliliters of fresh air in and 350 milliliters of stale air out doesn't make much of a difference to the overall composition of the alveolar air.*
Homeostatic mechanisms in the body try to keep the partial pressure of carbon dioxide in the blood at about 5% of atmospheric pressure. If our carbon dioxide levels change and chemoreceptors detect the change, the respiratory center in the brain alters our breathing rate and depth to bring carbon dioxide levels back to normal.  For example, we usually generate about 250 ml of carbon dioxide every minute, which corresponds to 17 ml every four seconds (the duration of a breath.) The homeostatic mechanisms make us breathe about 500 ml of air in every breath so that every exhalation contains 17 ml of carbon dioxide from 350 ml of alveolar air. This keeps the ratio at 5%. Homeostatic mechanisms also increase respiratory rate and volume during exercise.
*During exercise, however, the alveolar air composition changes rapidly due to large and fast breaths.

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text:
What is the energy produced by the mitochondria?
I know that the mitochondria is basically the power house of the body,
it consumes amino acids, fatty acids, glucose, etc and oxygen.
When these molecules meet up in a enzyme, a series of reactions happen (Krebs
cicle) which end up in CO2, H20 and energy.
Then the enzyme and later mitochondria will release its energy which will be stored in ATP molecules.
My question is what is this energy?

The use of the energy in ATP is quite complex. Since my college days our knowledge of how ATP is used has broadened considerably.
Let's look first at the role of ATP in the sodium-potassium pump. This pump uses roughly 20% of the ATP your body produces, even more if you are a couch potato. ATP powers this process by attaching its terminal phosphate group to the pump. The phosphate group is highly charged. Its attachment pulls and tugs on some regions of the pump and repels other regions due to the fact that many of the amino acids comprising the pump are polar or charged. These electrical, magnetic-like, interactions change the shape of the pump. This causes sodium ions to be pumped outside the cell even though they are more plentiful there. When the phosphate is released, the pump returns to its original shape bringing in potassium ions and reloading sodium. It is this pumping action that, among other things, provides the energy for messages in nerve and muscle cells (action potentials).
Probably the important energy use of ATP is this. Many of the reactions your body needs are uphill battles. That is, there is more energy in the substances we wish to produce (products) than in the substances which we must use for raw materials (reactants). So, the ATP attaches its phosphate to the reactant. This raises the energy in the reactant making it now have more energy (more unstable) than the product we wish to produce. The reaction now becomes "downhill" and can proceed naturally ("spontaneously") without holding a bunsen burner under your bottom. This concept is termed "coupled reactions" where we take the "downhill" breaking down of ATP and use it to power the "uphill" production of a requires substance.
There are two principal reasons a molecule becomes more energetic when a phosphate is attached. It is now more complex. Complexity increases instability, a consequence of the laws of thermodynamics. Another reason is that the highly charged phosphate creates stress in the molecule due to electrical interactions with other parts of the molecule.
Here's an image (mine) to show the concept of coupled reactions:

@AlwaysConfused Thanks! We've come a long way since textbooks likened the energy in ATP as beling like a loaded spring that could somehow do work.

ATP is a form of chemical energy. Hydrolysis of the third phosphate group produces quite a bit of energy:
ΔG° = −30.5 kJ/mol (−7.3 kcal/mol)

ATP is used in a variety of cellular processes, from signal transduction to biosynthetic reactions, motility, and cell division.
An interesting bonus fact: an adult human body only contains about 250 grams of ATP at any one time, but turns over its entire body weight in ATP during the course of a single day.

nice fact, we basically run on 250 gram "battery"
but my question is "what is energy?"

@aurelius I don't understand your question, then. The energy is stored in the phosphate bonds of ATP - it's chemical energy. It can then be converted to mechanical energy, heat, electrical energy (neuron impulses), etc.

my question was this  but I couldn't express it right so I tried it again here if you are curious: http://skeptics.stackexchange.com/questions/35461/what-is-energy

You seem to have misunderstood energy as some sort of substance which is produced as a product of cellular respiration like CO2 or H2O then released into the bonds of ATP molecules. Remembering that it is not a substance and that it is transferred(and not made) by the breaking and formation of bonds in the process of respiration should help clear that out.

Do correct me if I'm wrong.

it is not that I thought of energy as a substance, I know what energy is not, but I don't know what it is, except that it is the driving force of the universe and that it can take many forms. It is just that I cannot picture it in my mind. Even I consume, store, produce, waste, transform energy and still I can't get it right.

@aurelius Have a look at this Physics SE question: http://physics.stackexchange.com/questions/3014/what-is-energy-where-did-it-come-from .

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text:
What are the distinct neurochemical components of sexual pleasure?
Sexual activity is usually described as pleasurable.
What neurochemical systems does sex activate? Does the presence or absence of a partner make a difference -- say, in the activation of the oxytocin system?
Undoubtedly, sexual activity is salient, and so it surely involves dopamine. (Salient activities, whether painful or pleasurable, activate the dopaminergic system.)
What about these systems:

adrenergic
gabaergic
cannabinoid
nicotinic
opioid
serotonergic
cholinergic
glycinergic
histaminergic
glutaminergic

The post contains multiple questions, you will obtain better answers if you split the post.

Sexual response is primarily related to nitric oxide and its products. All of the systems you mentioned play a role, however the core pathway is from touch stimuli, to oxytocin release, to nitric oxide and dopamine accumulation, to motor response (orgasm) followed by prolactin to counteract said neurochemicals and temporarily suppress sexual response.

Supporting references please.

Sex gives you dopamine, oxytocin, adrenaline, and endorphins.

Please add some references


text:
Is there any biological basis for the emphasis on the value of the firstborn son?
Is the firstborn son biologically different in any way from the sons that follow?
Perhaps his epigenome is different? I have heard that a man's testosterone levels decrease when he becomes a father -- could this then have implications for the epigenetics of subsequent sons?

King Joeffrey was a monster. His younger brother, King Tommen, was a sweetie. Jamie is a heartthrob. Tywin somewhat less so (as a dwarf.) So yes, of course sons are different, but not in any predictable way. (Sorry to use fiction to answer, but it's as accurate as anything else on this matter.)

This report from 1 million babies finds a negative effect on health at birth for lower parity offspring: https://cinch.uni-due.de/fileadmin/content/research/workingpaper/1513_CINCH-Series_ardilamolitor.pdf. Whether that is due to biological characteristics of the babies themselves or the mother is not clear.

The firstborn son has equal chances of birth asphyixiation, being born blue, and having negative traits like autism, as the other children, based on the egg-sperm combination. The quality of the gametes of a traditional female mother from age 16 to 30 let's say, does not vary that much.

There are lots of cases reported now that suggest that overall the firstborn child is usually more intelligent. The articles supporting this are based on behavioural and economic study though, so the biological basis is a little lacking.
It's also not clear if this is nature or nurture. The firstborn may benefit from their parents undivided attention disproportionately.
Here's the press release for it. And the coverage from the Independent
and Forbes
I read somewhere that the firstborn is more likely to be overweight too, but I can't find the article now. Other people may know other traits that are supposed to differ between children.

There are apparently downvotes on this. I realise there are non-scientific links but I only provided them for completion. If anyone has a problem with the answer they should provide a constructuve comment with their vote.

It would be more representative of the literature to also report the magnitude of the detected IQ effect, which was roughly 1.5 units in this larger study: http://www.pnas.org/content/112/46/14224.

I expect that 1.5 units probably derives from the cultural effect of competition and favouritism, and the higher likelihood of the the other children to have depression.

I remember reading/hearing something about the effect of older brothers on the chances of people becoming certain types of people.
It went something like the oldest was most likely to be a pilot/doctor/CEO etc.
The second was most likely to be a teacher/middle management etc.
There's plenty of blogs that suggest the more older brothers a man has, the more likely they are to be homosexual. But this obviously doesn't look at whether or not Biological influences lead to this "birth order effect", or cultural influences.
I remember a suggestion that it was to do with antibodies (or some other substance) that builds up in the mother's womb after having son's. But again I can't find any evidence for that, so it might be pure speculation.
NB. I don't subscribe to this theory, but if you're really interested, it might be worth looking at the science behind it.


text:
Do we know that PrEP actually prevents infection, rather than masking it?
Pre-exposure prophylactic treatment (PrEP) for HIV is commonly said to reduce infection rates by more than 75%.
Similar treatments for already-infected patient treatments do not cure HIV, but reduce viral load to undetectable levels. If treatment of these patients is stopped, viral load will eventually rise.
Do we know that PrEP actually prevents infection, rather than masking it? Are there no cases of someone engaging in no risk behaviors, then going on PrEP and engaging in risk behaviors, then coming off it, not engaging in any further risk behaviors, and nevertheless testing positive for HIV?

"Are there no cases of someone being on PrEP, coming off it, and then testing positive for HIV?" is absolutely the wrong question to ask and is not how scientific study works, but everything else here is a good question.

Edited to improve last section

Still bad. Asking "are there no cases" implies that if you saw one case, you would conclude it's a masking effect. That's wrong, especially in light of the previous claim which is a 75% reduction: clearly there are still cases that PrEP does not prevent. Furthermore, not "engaging in any further risk behaviors" is an impossible thing to ask for in a clinical trial. You would have absolutely know way to know if there is a masking effect or if people are just lying about not engaging in further risk behaviors.


text:
Is tolerance unavoidable?
Do all psychoactive substances induce tolerance eventually?
For that matter, do all receptor-binding substances induce tolerance eventually?
It seems certain that different substances take different amounts of time to produce tolerance. Is there a pattern here? Do all receptor antagonists take similar amounts of time, or does it vary by receptor type?
(How do we know medications are not a zero-sum game?)

It also depends on concentration. If you're not over-stimulating the cell, tolerance won't be induced. Many patients do quite well on the same dosage of psychoactive drugs for years. Remember, the goal with drug therapy is to make up for the brain's imbalance in neurotransmitters, not to flood the system with them. That's what addicts do.

In general receptor-binding substances cause an "overflow" of your own already produced neurotransmitter. Your brain reacts by reducing the receptors. Also your own neurotransmitter production may be down-regulated by negative feedback. When you take away the "medication" afterwards, there are less receptors together with less neurotransmitter, causing withdrawal symptoms.
When you put in more substance in a control loop, there will always be some sort of "adaption" in order to reinstate a new balance (1). If you take in just enough drugs to balance the neurotransmitter-receptor system in a way, that the signal transduction in terms of nerve pulses remain the same, you have reached a tolerance stage, but not an effect stage. Still, medication is not "useless", since not all receptors will be dissipated. It is a matter of dose rate to increase the nerve pulses; once there is relatively more neurotransmitter (2) available than before medication, one should obtain a constant effect or an effectively altered control loop balance.
(1) https://books.google.at/books?id=z9TUch7m144C&pg=PA34&lpg=PA34&dq=receptor+regulation+up+down+neurotransmitter+drugs&source=bl&ots=2-4GRChqBi&sig=6e0YM-UrfgnMlw6e-rXR2Or7Qxc&hl=de&sa=X&ved=0ahUKEwixr_D25ZDMAhWB7RQKHcF9DqYQ6AEIHzAA#v=onepage&q=receptor%20regulation%20up%20down%20neurotransmitter%20drugs&f=false
(2) http://www.merckmanuals.com/professional/clinical-pharmacology/pharmacodynamics/drug-receptor-interactions

Please add some references to support your claims. Unsourced answers may be challenged and removed.

So, in other words:
"No, medications are not a zero-sum game, as long as the dosage is such than an effect stage is reached, rather than a tolerance stage."


text:
Is receptor antagonism just long-term binding?
By my understanding, a substance that binds to a receptor and activates it is called an agonist, while a substance that binds to a receptor without activating it is called an antagonist. (Wiki) What is the fundamental difference between binding to a receptor and activating it?
EDIT: I guess the receptor is a complex enough beast that fitting into it and staying there can be accomplished by some sections of the interface being completed, without necessarily completing the "usual" interfacing process between the receptor and its agonist -- thereby blocking the receptor geometrically without imparting the proper energy to it chemically.

This is similar to competitive inhibition of enzymes.

The details of activation vary by receptor of course, but talking in the popular key-lock picture:

An agonist is a key, that fits the lock and opens ("activates") it.
An antagonist is a key that you can put into the keyhole, but it does not open the lock. What this means is: while the "wrong" key is in the keyhole, you won't be able to open the door, even if you have the correct key, as long as the wrong key is in the keyhole.

As far as Wikipedia goes, the articles for Agonist (and the links contained therein) might be more informative than the one you quoted.
https://en.wikipedia.org/wiki/Agonist


text:
Different Effects of Detection Probability Between Presence and Count Data at the Same Location
I'm modeling habitat suitability for a large, mobile animal using occurrence data (presence only - I have no true absence data in this case) collected from camera traps (stations with automatic motion/heat sensing cameras). At each camera trap location I have 0 to several occurrences recorded.
Typically, when such data is modeled, they are modeled as count data, and detection probability is included in order to mitigate for covariates that affect detection, which otherwise may be identified as covariates that affect suitability. For example, an area where detection is less likely due to, say, dense vegetation, may be mistaken as less suitable due to that vegetation structure when in fact that may not be the case (or even the opposite may be true).
My question is, if the count variable were to instead be used as a detection/no-detection variable (so, a binary) would the probability of detection have less of an effect on the model (*when modeling relative suitability, not probability of occurrence)? i.e. if you didn't account detection probability, would using a binary response variable give you a less biased estimate of habitat suitability than if you were to use count data? And if so, why? It doesn't seem like probability of detection would change, or would be more homogeneous across the study area with this change, but it seems like the effects would be smaller in magnitude by not reinforcing differences in detection probability with multiple occurrences.
Also, I understand that it's not desirable to toss out all the other occurrences assuming you can calculate detection probability. I'm asking this in an attempt to better understand the possible differences in outcome between these two modeling approaches when using such data, as I've seen both methods in the literature, but have not seen this question specifically addressed. If you could reference any publications that may shed light on this, I'd be very appreciative.

Do you in any way have the option of estimating the detection probability over a season, e.g. from being able to identify the individuals in the pictures? Do you have data for several years or only a single year?

yes, that actually has already been done. the data i'm talking about was used to model occupancy with a capture/recapture model. capture probability was 0.05.

Disclaimed: Not really an answer, but too long for a comment

If I understand you correctly, this must depend entirely on the accumulated probablity of detection over the entire detection period (the time the cameras were out). If the accumulated probability of detection across all habitat types is high (approaching 1, given that the animal is present), then the detection probability shouldn't be a problem for the binary occurrence variable. An indication of this would be if you have sites (cameras) with either zero or a very high number of occurrences, which should indicate that the binary occurrence is rather robust. On the other hand, if sites have 0-4 occurrences in total it will be extremely difficult to separate non-occurrence from random factors or detectability. I assume that the detection probability across habitats is unknown though (as well as the accumulated probability of detection), but you might be able to make an educated guess. Also, by using a binary response, you will completely exclude the possibility to estimate e.g. an effect of habitat quality (for instance a difference in abundance between habitats), since counts of 1 or 13 will both be represented by 1 in the binary detection variable. In the Q, you talk about "modeling relative suitability" which indicates that you are indeed interested in something similar to this (relative habitat quality). In that case, I think that a binary response will be too coarse to provide useful information.
One possible toy scenario could be that you have two habitat types A and B (10 camera locations/sites of each) with a binary detection variable as:
A: 1 1 1 0 1 0 1 1 0 1  (species found in 7 sites)
B: 0 1 0 0 1 0 1 1 0 0  (species found in 4 sites)
In that case, the species can obviously exist in both habitat types (as you have categorized them), so the higher amount if zeros in B can represent (among other things) 1) lower occupancy of this habitat (in a metapop perspective), 2) that the quality of B is heterogeneous which is not captured by your habitat categorization (so parts of B is just as suitable as A), 3) lower population abundance in B compared to A (but the same detectability), or 4) lower detectability in B compared to A (but the same abundance). I don't really see how you can separate between these cases with only the binary variable, and I don't believe that using a binary detection variable will solve any specific problems compared to using the count data.
This is all very hand-wavy, but can hopefully give you some useful ideas/perspectives.

thanks for the thorough reply. i was thinking along the same lines as your first point - that cumulative detection probability over the detection period might be high enough to not cause any major issues using binary data. detection period was 20 days, using 300+ traps, and generated 100+ occurrence locations (~180 detections). counts range from 0-5. the only specific problem using binary data would solve is the problem of time, and user expertise. the question was raised as to whether a more user friendly method (e.g. maxent) could be used with this data to make meaningful inferences.

To be able to separate abundance from probability of detection, you need to have marked animal. If this is the case, you can then build a history of capture for each animal and model the probability of detection.
Have a look at this article : http://www.sciencedirect.com/science/article/pii/S0006320712005071. For some recommendations on the use of spatially explicit model when using camera traps to estimate population parameters (abundance...).
To answer your question, theoretically if there is independence between the detection at one site, using binary data will underestimate the probability of detection but if your detection are dependent let say animal moving in a group so each times you detect an animal you have a strong chance of detecting more than one then using binary data would make sense.
Hope it helps !
Cheers

Nico - I understand the relationship between detection probability and abundance, mark-recapture, and why it needs to be accounted for.
My question however, is if you didn't account detection probability, would using a binary response variable give you a less biased estimate of habitat suitability than if you were to use count data? And if so, why?

It all depend if your detection are dependent or independent ? What is the animal you are studying ?

Assume they are independent, and it's a large felid.

and in your model you ''y'' variable is the occurence of the felid you are studying ? And your question is : Is there more probability of detecting an felid in a specific habitat ?

not really, i guess you could frame it as a question of "probability of detection". but let's frame it as a very basic habitat modeling question: given this set of occurrence locations, what is suitable habitat for this species? i know probability of detection can bias that estimate. my question is whether the bias would decrease if using binary data.

Ok, then in this case I would say using binary data vs count data would underestimate the probability of detection since you assume independence between your detection. But the only way you could affirm that is if you had marked animal. When you get ''station'' with more than 1 detection are they close in time ? Like do you detection two felid in the same hour or in 12 hours ?

Nico - I'm not talking about estimating the probability of detection, i'm talking about estimating habitat suitability, and how these two data types effect that estimate given imperfect detection.


text:
Is there a way to identify a species of tree?
My family has been passing down  seeds from a lemon tree for about 3 generations now, There is some controversy about its origin or species. The lemons look like tangerines and when cut the pulp is very orange but are sour just like lemons. People always think we dye the lemonade. We have asked family members where our family got the original seed from and some say it was from Vera Cruz, Mexico but other family members say it might have came from Hawaii. Regardless it appears to have been from a tropical region. Is there a way a seed or part of a tree can be tested? If so, how much can I expect it to cost and where could I get it done?

Images would be helpful. We can try to identify it here, asking where to get it tested is not really on topic here.

True, true...but I don't have the tree physically with me and I ate all then lemons, lol. Sending a seed to a lab maybe?

I don't think OP is asking us to identify the species. He is asking for a test that will confirm the species of the plant. @MrHons Genetic tests should tell you the species. You can do a 16S rRNA sequencing. The cost shouldn't be very high but if you have a friend working in a bio-lab then you can ask for a little favour.

@WYSIWYG You could make an answer out of your comment if you want especially if you extend it to add a link to who the OP could send the tissue sample to for sequencing and analysis


text:
Online multiple sequence alignment with constraints
This is probably a naive question.
I have accesssed the Clustal Omega online multiple sequence alignment tool at http://www.ebi.ac.uk/Tools/msa/clustalo/ for the first time, but I think I need to provide more input to get it to do what I want, by specifying more constraints.
Edited to clarify constraints:
The original sequence P sequence has four symbols, say A,B,C,D.
The algorithm has access to 4 derived sequences.
P1: all occurrences of A,B deleted, no other change
P2: all occurrences of A,D deleted, no other change
P3: all occurrences of C,D deleted, no other change
P4: all occurrences of B,C deleted, no other change
Goal: given P1,P2,P3,P4, recover P
Example
P:
ABACCADDACBBC
P1
CCDDCC
P2
BCCCBBC
P3
ABAAABB
P4
AAADDA
Note that I have removed the under bars by which I had tried to indicate deleted symbols but since the deletion processes for the Pi are deterministic they can be supplied to Clustal or whichever tool is appropriate.
End of edit
Toy madeup example illustrating my input, the output, and the problem.
The actual sequence from which these sequences came after deletions, followed by the resulting sequences is as below:
p  ABACBAC
p1 A_AC_A_
p2 _BA__AC
p3 __ACBA_
so I input
>p1
AACA
>p2
BAAC
>p3
ACBA

and got the output
p1 _AACA_
p2 BAAC__
p3 __ACBA
      **

Which is entirely reasonable, but I have constraints.
I want to align with the constraints that

for certain symbols matches between certain sequence pairs should be maximized, and
for certain symbols mismatches between certain sequence pairs are allowed

In fact given p1,p2,p3,p4, which all arose from p after deletions, there are the pairwise constraints

A should be a match between p3 and p4 (it never appears in p1 or p2)
B should be a match between p2 and p3 (it never appears in p1 or p4)
C should be a match between p1 and p2 (it never appears in p3 or p4)
D should be a match between p1 and p4 (it never appears in p2 or p3)

This means that p1 has only C,D; p2 has only B,C; p3 has only A,B; and p4 has only A,D characters after deletion.
I want to obtain the most likely alignment or a few most likely alignments of p1,p2,p3,p4 under these constraints.
I have looked to see if I could figure out how to input the constraints but no luck.
Should I have used another tool? In general I will have much longer sequences, typically 4 of them, with pairwise agree/disagree constraints, as stated above.

This question is unclear. What do you mean by A,B, C and D? Are these residues, or points in a list. I think you should expand on your toy sequences.Assuming you can't post your actual sequences, perhaps use another real peptide and make up similar constraints to the ones in your own problem (although I still don't understand what your constraints are).

I also don't understand your constraints. Also, why do you need constraints? Usually when you do MSA, you don't pose any constraints since you presumably don't know how the query sequences can be aligned. Also, I bet that if you include sequence "p" in your MSA, the alignment will be different and will include your constraints.

@James, thanks for your comments, I will re-edit the question to clarify.

@GerganaVandova, thanks, will rephrase the question.

Answer
You can't. Clustal doesn't provide the options of setting the sort of restraints you would like. Multiple Sequence Alignment (MSA) is difficult to program and the authors of Clustal have been refining their algorithm for years. If it were perfect and completely robust they might be in a position to add more user tweaking, but at the moment you're stuck with those provided.
Comparison matrices and forcing alignments
It may be worth while to mention how one can force particular correspondences in simpler pairwise alignments. This involves manipulation of the comparison matrix used to score the comparison. DNA comparison matrices may be very simple, scoring, say, 1 for a perfect AA, TT, GG, CC match and 0 for any mismatch. Protein comparison matrices are more complex, with the values for perfect matches dependent on rarity and unique function (e.g. In the PAM250 substitution matrix WW scores 17, whereas GG scores only 5) and the values for mismatches also varying markedly (e.g. ED scores 4, compared with 5 for EE; but EW scores –7). There are various matrices available, so implementations of the Smith Waterman and Needleman and Wunsch pairwise comparison algorithms generally allow you to specify your own.
Suppose you have biological information (not intrinsic in the algorithm) that makes you wish to force an alignment. For example, AAATAA sequences near the polyA tail of two mRNA 3'UTRs should align, but sometimes do not because other stretches of As give better scores. What you can do is replace the AAATAA by AAAZAA in each case, and then modify the scoring matrix so that ZZ scores very highly (e.g. 20) compared with AA. This will force the alignment, after which you can change the Zs back to Ts.
Multiple Sequence Alignments tend to to use position-specific dynamic scoring matrices. As the overall sequences align, the original scoring system is adjusted to reflect the frequency found at a particular position. (For example if a position is skewed to E in 90% if cases, EE will score more than at a position in which E is found only in 20% of cases).
I'm not saying it would not be possible to change the initial Clustal matrix with Zs at a particular position, but I don't think this possibility is provided. (Anyway your situation is more complex.) Glancing at the Clustal Omega paper, I see that they allow, indeed encourage, you to build up alignments from previous profiles. If you managed to force the alignments of a few sequences and input the profile derived from that, you might get what you want. But I imagine that requires the command-line program from Dublin, rather than the EBI online version.


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How do viral vaccines work?
I have read that a vaccine against a pathogen typically works by using a dead or weakened version of that pathogen and then inciting an immune response against the pathogen so that the immune system then recognizes that pathogen in the future and attacks it immediately.
However, suppose that a person gets vaccinated against a virus. Why couldn't the virus infect a few cells before it runs into immune system cells and starts replicating as normal? Does the immune system somehow recognize virus-infected cells?
Also, how would a vaccine against a virus that attacks immune system cells work (like HIV, for instance)? In this scenario, wouldn't any immune cell that tries to destroy the virus get infected itself?

Look at the normal reaction of your body during infection by a new virus, how (the steps are : detection of the infection, inflammation, processing and presentation of antigens, replication, mutation and selection of the B-cell-antibody pool) it needs 2 weeks to create potent B-cells-antibodies, how it is much faster when enough of the viral proteins contain "antigens" already seen for which your body previously made long-term memory B-cells.

Vaccines containing these weakened or killed viruses or bacteria are introduced into your body, usually by injection. Your immune system reacts to the vaccine in a similar way that it would if it were being invaded by the pathogen — by making antibodies. The antibodies react to the vaccine (virus/bacteria) just as they would the live pathogen — like a training exercise against an antigen. Then they stay as amemory in your body, giving you immunity. If you are ever exposed to the real disease, the memory is activated and antibodies are there to protect you.
Moreover if a cell gets infected virally, infected cells produce and release small proteins called interferons, which play a role in immune protection against viruses. Interferons prevent replication of viruses, by directly interfering with their ability to replicate within an infected cell.

It is better to use the term "pathogens" instead of "germs" especially when the OP is very well aware of the former. Also, it would be great if you could provide some references

Edited your answer for terminology. If not acceptable, please feel free to roll back.

It depends on the particular vaccine.  Generally we can divide vaccines into two groups: live and "dead".
Live vaccine contains weakened (attenuated) pathogen, which (in case of a virus) theoretically can infect our cells.  However, as it is attenuated, it is not doing it very efficiently, thus even naive immune system has no problem with defeating it.
"Dead" vaccines contain either inactivated ("killed") pathogen or only some of its parts (antigens).  As it is not active virus, it can not infect your cells.  It is just presented to your white blood cells as a "dummy" for "target practice".  And by "target practice" I mean things like activation and proliferation of competent lymphocytes, followed by formation of immunological memory - exactly as if the organisms was infected by a virus.
Our body is "blindly" creating a variety of lymphocytes, and each of them is able to fight with pathogens with certain antigens.  As the lymphocytes has been created "blindly", most of them seems to be useless.  However, if there happens to be a lymphocyte able to recognize a virus antigen, the lymphocyte is indeed useful.  It proliferates, "learns" to recognize the antigen even better, fights the virus (or its antigens) and is preserved as memory cells, just in case of reinfection.
Of course I am oversimplifying here, but I hope I managed to grasp the big picture. ;)


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Preserving a sample for mtDNA and nuclear DNA analysis
Imagine a person in the early half of the 20th century (1900 to 1950) took some kind of sample(s) from a living human body using any technology of the era.  They then stored it using any technology available, but could not use prolonged (70+ years) refrigeration.
We want to be able to do useful analysis of that sample in the year 2024.  We particularly might want to be able to sequence mtDNA and nucleus DNA, look at telomeres and methylation.  Furthermore, we especially want to be able to try to determine the age of the individual, and even better, from what approximate generation they were (i.e. plus/minus a hundred years).
Is such sample storage even possible?
Using my "just enough knowledge to ask stupid questions":

Could a sample be preserved in formalin and then immersed in alcohol, all in an air-free sealed container, and preserve the needed DNA strands and/or other biochemistry?
Could ethanol precipitation of DNA be used on the sample
contemporaneously, and that precipitate instead be stored safely for
70+ years?

Maybe these other questions apply?

DIY extraction and long term storage of human DNA sample?
How realistic is to use DNA for long term storage?
Isopropanol precipitation of DNA - duration and magnitude of cold storage

(I'm an old hand at Stack Overflow / Stack Exchange sites, but this is my first post to Biology.  Gentle feedback appreciated.)

If you're wanting to store DNA long-term at room temperature, you'll probably want to dry it. DNA extraction methods have been known since 1869. You can then use ethanol to precipitate the DNA, centrifuge it, and dry off the ethanol. The dried DNA pellet is surprisingly stable (though still maybe not great at this time scale, depending on what you want to do with it). Adsorbing the DNA onto a matrix, including silk, can increase preservation.
You could also try preserving the tissue itself. Two good options would be freeze drying the tissue, or preserving it in 95% ethanol. You would not want to store in formalin, as that creates DNA fragmentation and cross-linkages.

Thank you so much!  That's exactly the kind of knowledge I was looking for!

For anyone curious, @Darlingtonia's answer is what I needed.  It also gave me the search terms that Google could use to finally find further useful information.  In particular, a paper published at the National Center for Biotechnology Information, linked here.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3910151/
First paragraph of the abstract:

The globalization of DNA barcoding will require core analytical facilities to develop cost-effective, efficient protocols for the shipment and archival storage of DNA extracts and PCR products. We evaluated three dry-state DNA stabilization systems: commercial Biomatrica® DNAstable® plates, home-made trehalose and polyvinyl alcohol (PVA) plates on 96-well panels of insect DNA stored at 56 °C and at room temperature. Controls included unprotected samples that were stored dry at room temperature and at 56 °C, and diluted samples held at 4 °C and at −20 °C. PCR and selective sequencing were performed over a 4-year interval to test the condition of DNA extracts. Biomatrica® provided better protection of DNA at 56 °C and at room temperature than trehalose and PVA, especially for diluted samples.


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With CRISPR-mediated gene editing, can the PAM for the guide RNA also be site of the desired edit?
I'm hoping to use CRISPR-Cas9 in yeast to change a single nucleotide in a gene of interest. While there are a couple potential guide RNA sequences I could use, the best option's PAM sequence (TGG) it contains the site of my desired edit (TGG > TTG). Would there be any issue with this?


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Calculating Possible Combinations of Bases in a DNA Strand of a Given Length
In my Biology class we were asked this question:

This DNA strand consists of eight pairs of nitrogenous bases. How many different sequences of eight bases can you make? Explain how you found your answer.
I guessed either 28 or 8!. Apparently, the answer is 8! ÷ 24. I asked my teacher, but she did not know the answer. Does anyone know why this would be?

The answer your teacher gave you might be the answer to the question of how many sequences of 8 bases can be formed using only the bases shown in the diagram, each one can be used once. The factorial comes from the fact that once you pick a base there are n-1 options left and so on. 2^4 is 222*2 which accounts for there being four duplicate bases so that count only unique sequences.

Don't guess! You need to learn to approach this sort of simple statistics logically as laid out by @Remi.b. The relevence of this sort of problem to biology is more in relation to the frequency of restriction sites, which are smaller and a better place to start. You can find lots of practice questions and an explanation of how to answer them on a self-teaching resource I put up for students at my own university. Give it a try.

At each base, you can have 4 different bases (A,T,C or G). Therefore for the first base there are 4 possibilities, namely

A
T
C
G

For the first two base pairs there are $4^2 = 16$ possible combinations
(I'm no good with math but the premise below is in error. If there is an A then it can only be paired with a T if there is a T it can only pair with an A C with G and G with C. So many of the below listed options will not occur - changed to italics)

AA
AT
*AC
AG*
TA
*TT
TC
TG*
*CA
CT
CC*
CG
*GA
GT*
GC
GG

For the first three bases, there are $4^3$ possible combinations. For 8 base pairs, there are $4^8 = 65536$ possible combinations. $2^8$, $8!$ and $8! + 2^4$ are all wrong.

I think the problem asks combinations with bases in the given sequence. There is 2 of each of A, T, G, and C. So the combinations come out to 8!/(222*2) which is the answer their teacher provided.

Unfortunately @Remi.B is wrong. His answer allows the choice of any base for each position. This includes arrangements such as AAAAAAAA which is not possible as there are only two A bases. User40950 is correct in his comment. Here is a little more expanded version of his comment.
If we label the bases as A1 A2 C1 C2 G1 G2 T1 T2 then there are 8! possible arrangements. Notice however that interchanging A1 and A2 while leaving everything else unchanged yields the same arrangement, hence we divide the answer by 2. This same argument applies to each of the other duplicate pairs, so we divide the answer by $2^4$. Thus the final answer is
$8!/2^4$


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Does mechanotransduction of cells play a role in the biocompatibility of titanium?
What exactly is mechanotransduction as the information varies between sources. Some sources indicate that mechanotransduction is the underlying principle where cells pull on the surface they grow on to test their stiffness, so they can stretch and facilitate cell growth and differentiation. Other sources indicate that mechanotransduction is how cells detect mechanical stimuli and turn them into chemical signals.
Is this the main reason titanium is biocompatible to replace bones because it has a low surface resistance and cells on stretch on it?

Welcome to BiologySE... since this is a homework question you should see the site's help section...http://biology.stackexchange.com/help/homework

You have 2 questions, one in each paragraphe, and it would have been better to ask separately. For the 1st one, the two statements are not antagonistic: the second is the general definition of mechanotransduction. The 1st one is one of the phenomena that arise via mechanotransduction: a mechanical stimulus (resistance of substrate when exerting force on it = its stifness) is turned into signals that lead to a specific behaviour (spreading, differentiation)

First off, AOZ has a wonderful page about titanium alloy uses in medical applications you should read and that most of my info is coming from:

Suitability of Titanium for Implant Purposes

I think you're having a couple of easy to correct misconceptions. First, titanium alloys are used for medical implants and replacements because they're lightweight, stronger by tensile strength than steel and judged to be completely inert and immune to corrosion by all body fluids and tissue, and is thus wholly biocompatible. It's also non-magnetic, meaning you can even go through an MRI machine with it! The range of alloys that we're able to produce is also key to the widespread use of titanium in medical applications as different alloys can serve their purpose as anything from hip joints to jaw reconstruction bases to spinal fusion devices based on their composition.
But cells don't exactly "stretch on it" and in fact in many operations additional material is used to ensure that the host body is able to function with the implant. This includes the use of polymethyl methacrylate bone cement to ensure that implant joints stay in place, and the use of roughened bioactive surfaces (hydroxyapatite) to stimulate the integration of the bone and surrounding tissue onto the implant.
As far as mechanotransduction goes, the problem is that it covers an extremely wide range of topics so ascribing it only one definition can quickly cause issues between studies. I usually go off of Nature's definitions for these kinds of things, which in this case says that "Mechanotransduction refers to the processes through which cells sense and respond to mechanical stimuli by converting them to biochemical signals that elicit specific cellular responses" (1). If you peek at the studies highlighted on google scholar for mechanotransduction you can see that the range of work is extreme and that's why ascribing the term one specific meaning at this point is unrealistic.


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Do "virgin" ant queens ever shed their wings?
In species that reproduce sexually, if an ant queen goes on a nuptial flight and does not successfully mate, will she still shed her wings and try to found a colony (although she probably won't succeed because unfertilized eggs will result in drones only)?

Good question. I tried to find a few articles to validate my answer, but it would appear that very few professional studies have been done on the matter. One of my hobbies a few years back was ant keeping and I have had several colonies started from queens over the years, so I can share some of my personal experiences.
Anyway, back to your question. For the most part, no. An infertile queen will keep her wings and either find a safe place to lay eggs like a fertile queen or just walk aimlessly until she dies/is eaten. However, there are some rare instances where an infertile queen will shed her wings after the nuptial flight and find a safe place to nest and even in some occasions will lay eggs that are, of course, unfertilized and will therefore die or become male drones.
On the subject, the same is true vice versa. In rare instances, a fertile queen will NOT shed her wings, find a nesting place and even raise a colony all with wings on. Most of the time, however, her first workers to emerge promptly remove them.
I hope this answers your question.
CDB

Actually, the thought just occurred to me that, just because a species can reproduce sexually, it doesn't mean it must reproduce sexually: what if in some species, the virgin queen can still lay eggs that are just clones of herself? She would still get her army or workers. I think I have read about one species in Japan where there is no queen and all workers just lay their own eggs that are clones of themselves. So it doesn't seem like a total impossibility for queens in other species to do the same. In fact, are we even sure that queens always have enough sperm reserve for her lifetime?

The queenless species in question seems to be Pristomyrmex punctatus (a.k.a. Pristomyrmex pungens):
http://www.researchgate.net/publication/247154220_Japanese_Queenless_Ants_Pristomyrmex_punctatus_Prefer_the_Traces_of_Both_Nestmates_and_Strangers_in_Nest_Selection
http://ant.edb.miyakyo-u.ac.jp/BE/Kingdom/2425/2425e.html


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Do GPCRs have 7TMHs?
I've screened a non-redundant set of GPCRs acquired from UniProt. I found a handful of examples of record IDs that contain more than the 7 TMHs. For example Q89609 and P20905, both of which have been manually reviewed to some extent.
For an idea of the variability in the GPCR family, below is a screenshot from a Clustal Omega alignment comparing P2095 to a bonafide human GPCR. There are ~16 indels of varying length.

Also, when blasting against SwissProt, the 2 hits that appear are also GPCRs with the same function from mammals but they have the expected 7 TMHs.

Is it possible for GPCRs to contain more than 7 TMHs, or is it a case that the annotation is incorrect?

How big is the sequence homology to the GPCR that definitely have 7 tm-domains?

This is from the reference given in the SwissProt entry:  The predicted structure of the 5HT-dro receptor reveals... eight putative transmembrane domains instead of the expected seven I don't have journal access right now, but the paper may be insightful.

@Chris I've compared one to a bona fide GPCR, however, the sequence variation in the GPCR family makes this a tricky question to answer. Also, sequence homology is rife with errors when examining TM proteins.

@canadianer Thanks for this. Evidently, my question is long standing from the 1990s! Originally I suspected SignalP had made an error and the first TMH would be cleaved, but that paper suggests it's the second TMH that is not found in other GPCRs. I'll give this a thorough read.


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Single copy housekeeping genes
I am working on a tool for SNP calling in polyploid plants. To test my method, I need a list of housekeeping genes common in almost all plants. For my case, these genes must be single copy (ie each HK gene should have no paralogs).
Briefly I need a list of genes that are:

House keeping
Single copy
Common in almost all genomes, or genomes of a taxa

Any help is appreciated.

If you talk about animals, globin might fit in all criteria...

I found this to be relevant https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1203353/

Just flying from the waist: filter approach:
If there is a data source that has the expression data for cells in multiple tissues for any organism i would use that to find the housekeeping genes by sorting which genes are expressed in the greatest number of cells (think excel or XML). Next, I would check which of those genes are also found in/similar to the respective gene (homolog I thin its called) in the plants (using genome browser, e.g., ensembl and blast or just look it and click on the button to bring you to the plant genome). If your model organism does not have sequenced genome... get primers and see if you can sequence it for yourself to see if its there. Then check to see if its a single copy. Hardest part is finding an expressome database spanning multiple tissues in an organism to find housekeeping genes - then hoping they are conserved to the plant. Alternatively, you can consult literature to find housekeeping genes.
You probly just wanted a listing of the genes... sorry.

There is no single answer for a gene. The most correct thing to do is to use a set of genes across many locus and measure the correlation of copy number across them first, and only use the ones which co-segregate as single copy number as the measure of 'one copy'.
This is the same approach used for qPCR and is the basis of the widely used geNorm algorithm (11k citations). While in qRT-PCR the 'stability' of a gene expression is compared across mRNA which are at different stoichiometry, in your case you just further restrict that the genes should have stable stoichiometry.
If I was designing this, I would use the same set of genes which are 'housekeepers' defined in the two publications above and avoid sex chromosomes.

The following is probably a good set, it's for Arabidopsis you need to check if it fits with your need.
CBP20 Gene
Gene Locus: At5g44200
Actin-2 Gene
Gene Locus: At3g18780
UBC Gene
Gene Locus: At5g25760
SIGMA sells primers set for these: http://www.sigmaaldrich.com/life-science/molecular-biology/plant-biotechnology/plant-molecular-biology/control-primers-for-arabidopsis.html


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Do you know of ways that help a plant to produce more flowers?

In Crocus sativus, or saffron crocus, the most commercially important part is the stigma of flowers. Each plant produces one flower (so there is more than one plant in this picture) and each flower has three stigmas (stigmas are red in this picture). What are the possible mechanisms to produce more stigma in a plant for commercial cultivation?

There are few hormones that may help you.

This question might be a better fit on Gardening.SE

Each species of flowering plant produces a set number of floral parts, more or less. Having three styles and three stigmas per flower is a trait that is determined genetically. Mutations can cause floral parts to be duplicated. Heirloom tomatoes have mutations in the fascicated and locule-number genes, resulting in more locules being produced per fruit. Mutations in the fascicated gene also cause increases in other floral parts, such as petals, sepals, and stamens. If you compare a regular tomato to an heirloom, you'll notice that heirlooms tend to have around 10 petals and sepals compared to a regular tomato's 5.
Now the question is, do such mutations exist for Crocus sativus? A quick Google search didn't turn up anything other than the normal three-stigma flowers, so it doesn't look like such a mutation is common, if it exists at all. My answer to your question is: there is no easy way to get a saffron flower to produce more stigmas, for if such a method existed, everyone would be using it. I don't doubt that a dedicated botanist could come up with something (crossing with a related species, perhaps), but it's not something you can likely accomplish in your home garden.
Edit:
User Sleepses found an article where a high-yielding mutant with 5 stigmas was obtained through gamma radiation mutagenesis. I'm not sure whether or not this mutant is for sale commercially, though.

What about multiple flowers per plant, as asked in the title?

Found an article documenting C.sativa with five stigma obtained with gamma ray random mutagenesis.

@Sleepses Very interesting! I'll go ahead and append that to my answer

One way getting most attention is re-deriving Crocus sativus again.
Crocus sativus (with autotriploid chromosomes) is derived from Crocus cartwrightianus (diploid). ref for this is https://www.sciencedirect.com/science/article/pii/S1055790319300879
This article talks about resynthesizing the triploid https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4549961/
You could breed crocus relatives to have abundant and tasty flower parts. Possible ways without genetic modification could be:

grow a genetically variable population of Crocus cartwrightianus, and do mass tasting to find an suitable plant.
do a genetic comparison to find the genes that are responsible for the taste, then search through the variable population for plants with that combination of the genes needed.

Ya I was going to suggest polyploidy using colchicine or something. Colchicine is a powerful poison coming from a spring-time bulb in europe. It mutates chromosomes by preventing meiosis, and results in plants with extra chromosomes, which give profusive branching and double flowers. Generally, you can be sure that very adept botanists are trying to make saffron a bigger crop, and you can write a thesis on it. Biotechnology is very difficult to engineer.


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What is the genome size of Saffron (Crocus sativus)?
I searched the web but cannot find an answer for my question. Has the genome size of Crocus sativus been determined?

Neither NCBI nor Ensembl have a genome project listed for any crocus species, although individual ethidium bromide stained nuclei have been analyzed by flow cytometry, revealing approximately 11.4 pg of DNA per nucleus (warning, pay wall).
C. sativus is triploid, giving it a C-value of 3.8 pg which works out to a haploid genetic content of about 3.45 Gbp.
(full credit to canadianer for finding the Brandizzi paper)

Here's a paper that actually measures C. sativus: http://link.springer.com/article/10.1007%2FBF00985356 They got around 11.3 pg and 3.45 Gb

3.45 Gb is apparently for the haploid genome, by the way.

Yep, you nailed this question. Why not put it as an actual answer instead of commenting on my, less awesome, answer? I feel like I should actually delete mine now.

Haha well when I first read it the numbers were so close that I thought it was just confirming your estimate. I can post an answer later if I get time, but feel free to edit yours.


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Can yeast survive without mitochondria?
Some yeast cells have very low mitochondria copy number (see number of mitochondria in non budding cell, you can count mtDNA). This makes them susceptible to fluctuations, and one can conceive that some yeast cells might arise entirely without mitochondria. Would they survive? Could they reproduce?
Please, assume they have all the nutrients required, in particular excess glucose to ferment, so mitochondrial energy output is dispensable.
If you could point me to some references that would be awesome.

Basic answer: Yes, they can survive, but only if they do not need to undergo cellular respiration.  I quote from Microbiological Research, Volume 169, Issue 2-3, p. 185-195:

Mitochondrial DNA (mtDNA) is a compulsory genetic component for encoding essential respiratory enzymes in all eukaryotic cells.

In other words, for cellular respiration to occur, the yeast must have the mtDNA.  However, the article goes on to explain,

However, some yeast species (called rho positive) could survive without mtDNA under conditions of fermentation (a metabolic pathway alternative to respiration). In these species, partial or complete losses of mtDNA (spontaneous or induced by mutagenic factors) is associated with the formation of respiratory deficient mutants (rho− type or rho0 type) characterised by slow growth on fermentable carbon sources (e.g. glucose) and inability to grow on non-fermentable sources, such as glycerol or ethanol.

In other words, yeast can survive in the presence of correct conditions for fermentation to occur.  In the absence of those conditions, the yeast must have the mitochondrial DNA, because in order for it to survive, it must perform cellular respiration.

No, yeast cannot survive without mitochondria.  Petite positive yeast can survive on fermentable carbon sources without mitochondrial DNA, but they must have a mitochondrial compartment.  Mitochondrial respiration can even be lost in human tissue culture cells, but they too must have mitochondrial compartments.  Mitochondrial compartments are where Fe-S cluster assembly and other essential biochemical pathways occur, thus they are required for eucaryotic cells to either live for a long time or reproduce.

Can you add a reference?


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Effect of HIV on T-cells
When HIV infects macrophages, it doesn't kill or destroy them immediately, but once it infects T-cells, they're destroyed. Why is that? As in why does it destroy T-cells and not macrophages or other cells.

This process does not destroy the macrophages.
  Unlike macrophages, helper T cells are destroyed.

I think HIV can destroy macrophages, since just by virtue of the infected cell accumulating the virons and the cell lysing due to so much accumulation no? Is this not one of the ways the virus spreads throughout the body?

No, it doesn't destroy macrophages, or so my book says. It does destroy T-cells though ; @RoSiv

Can you provide a quotation from (or better, photo of) the book so we can understand the context? As written, this question is rather unclear.

PLEASE DO NOT POST TEXT AS IMAGES. Copy and paste the text into your question. Images are not searchable, and can not be interpreted by screen readers for those with visual impairments. Use the [edit] link to modify your question.

From this article:

Researchers found that when the virus productively infects the few permissive CD4 T cells present, death occurs through apoptosis mediated by an enzyme called caspase-3. But when HIV abortively infects nonpermissive CD4 T cells, death occurs by pyroptosis, which depends on the activation of caspase-1. It turns out that the vast majority—roughly 95 percent—of CD4 T cell death in lymphoid tissues is driven by caspase-1-mediated pyroptosis.

When it comes to macrophages, however:

macrophages are much more resistant to cytopathic effects of lentiviral replication than for example activated CD4+ T cells [23, 24, 25], and HIV-1 has evolved sophisticated mechanisms to prolong the life span of infected macrophages [24, 26]. Especially long-lived macrophages may therefore harbor the virus for long time periods, thus constituting HIV-1 reservoirs and posing a major obstacle to virus eradication from infected individuals.

Source


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Comparison between Transmission Electron Microscope (TEM) to Scanning Electron Microscope (SEM)
Can someone state the advantages of Transmission Electron Microscope (TEM) over Scanning Electron Microscope (SEM) and vice versa?

Well, the main difference between them is that with SEM you get information about the surface using scattered electrons whereas with TEM you get information about the inner structure with transmitted electrons. TEM has higher resolution, but SEM is simpler because you do not need a thin sample.
I recommend these videos about SEM and TEM. Short description of both can be also found at this webpage and in the material for students by ThermoFisher Scientific.


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How can dehydrogenation steps in some biochemical pathways produce ATP?
Dehydrogenation reaction of alkanes is inherently endothermic as one removes two thermodynamically more stable C-H bonds and replaces it with one less stable C=C. Although the product is conjugated with the carbonyl group, this stabilization should be negligible, shouldn't it?
How comes then according to the scheme below, the result of this reaction are two high-potential electrons capable of forming ATP from ADP? Is the reaction concerted with some other not shown here? Or is the enzyme regenerated afterwards with some input of energy?

cross-post https://chemistry.stackexchange.com/questions/86929/how-can-dehydrogenation-steps-in-some-biochemical-pathways-produce-atp

You have to consider the full redox reaction to determine if the reaction is favourable or not. It's not correct to think of enoyl-CoA alone as "higher energy" than acyl-CoA, because of the free energy difference $\Delta G$ of the half-reaction:
acyl-CoA  $\leftrightarrow$  enoyl-CoA + 2 $e^-$
cannot be determined without knowing what the electron acceptor is. You might be thinking of the enoyl group as "higher energy" because it is reactive towards H$_2$ (as in hydrogenation reactions), but that's not the relevant redox couple here.
In this case, we should consider the energetics of the entire process of electron transport, as shown in your diagram. Since the intermediates (FAD, ETF, quinones) all cancel out, the overall reaction without ATP synthesis is:
acyl-CoA + 1/2 O$_2$ $\leftrightarrow$  enoyl-CoA + H$_2$O
This reaction is highly favourable, with a $\Delta G$ of about -150 kJ/mol, because O$_2$ is a very good electron acceptor. (See this site for free energy calculations.) This is more than enough to drive ATP synthesis (about 45 kJ/mol).

The reason is that the reaction is not solely a dehydrogenation, but more properly, oxidation of the two central atoms.
In the C-H bond, the C is more electronegative, which means the electrons they share will be more on their side - the carbon is in a reduced state. In the reaction you pointed, it's not only the H+ that leaves, but also one electron per H+ (so that makes one H atom leaving, but since electron was more of the C than the H, it's actually the C that is losing an electron - being oxidated). Those electrons are then stored on an electron carrier (FAD --> FADH2), which goes on to provide those electrons to the electron transport chain in the mitochondria, enabling the production of ATP. (know more about this process: https://en.wikipedia.org/wiki/Oxidative_phosphorylation)

But where do you take the energy to remove those hydrogen atoms (protons with electron)? From what you wrote it seems that you 'magically' remove electrons from more electronegative element producing intermediate higher in energy (Enoyl-CoA), and then you use those same electrons to produce even more energy stored in bond energy of ATP?! From this it seems, that it must be there some kind of concerted exergonic reaction that drives the reaction.


text:
Relationship between the ambiguity (wobble) at codon position 3 in elongation and codon position 1 in initiation
In prokaryotes the usual observed start codon frequency is AUG > GUG > UUG.
An explanation for this is that

AUG is the most common initiator codon because it forms the most stable interaction with the CAU anticodon in fMet-tRNA

But does this have anything to do with the more general wobble rules?

Codon-anticodon pairing takes place according
  to the wobble rules (Crick 1966). During translation,
  base-pairing occurs in the usual way (A with U, and
  G with C) between the first and second nucleotides
  and the second and third anticodon nucleotides. The
  wobble rules state that in the pairing between the
  third codon nucleotide and the first anticodon nucleotide,
  there is a certain amount of play, or "wobble."
  This enables G in first anticodon positions to
  pair with U or C in codons, U with A or G, and I
  (inosine) with U, C, or A. In first anticodon positions,
  C pairs only with G, and A (very rare) only
  with U. These rules are fundamental to all discussions
  of codon capture. Table 1 shows anticodons
  in the universal genetic code as predicted by the
  wobble rules (Crick 1966).

I'm confused because that seems the exact opposite of what happens in the start codons' case, i.e. the "play" is in the first (not third) codon nucleotide in the start codon case. And the table in this last paper only gives CAU Met as the only pairing for CAU, so no wobble.
Am I interpreting this correctly and there's no "Crick" wobble in the AUG > GUG > UUG start codon, but rather another wobble-like mechanism that explains the start codons' first nucleotide wobble-like behavior?

I have changed the title, retaining the sense while not prejudging the nature of any "rules".

Summary
The difference in the nature of codon–anticodon ambiguity seen between bacterial initiation and elongation lies not only in the position of the codon at which it occurs (5′ v 3′, respectively), but in the partial or absolute nature of the interactions (only some AUG and GUG etc. codons initiate and insert fMet, whereas all AUU and AUC codons will recognize the Phe-tRNA with anticodon, 3′-UAG-5′. It can be accounted for by the quite different molecular interactions occurring at the ribosomal P-site (for initiation) and the A-site (for elongation) and the importance of the base-pairing between the Shine & Dalgarno (RBS) region of the mRNA for initiation.
Wobble in context
Wobble was the term applied by Crick in 1966 to the non-standard base-pairing between the 3′ position of mRNA codons and the 5′ position of anticodons of certain tRNAs. To avoid violating the genetic code Crick assumed strict base pairing at the first two codon positions and asked the question “If one sRNA [old term for tRNA] codes both XYU and XYC [because of experimental evidence that this might be the case for Phe codons], how is it done?”. And then, given the many ways bases might be paired added the constraint “How many base pairs are there in which glycosidic bonds occur in a position close to the standard one?”.
On the basis of geometry Crick predicted that anticodon 5′-U might be able to pair with a codon 3′-G (in addition to the standard A), and anticodon 5′-G with codon 3′-U (in addition to the standard C). He — unwisely in my opinion — referred to these predictions (and his prediction for inosine, I) as ‘rules’. The predictions are summarized below, together with the actual pattern that has since emerged.

It should be noted that although the two predictions involving G=U base pairs would appear reciprocal, that involving an anticodon 5′-U does not occur except in mitochondria, were it is incorrect in that the interactions are not restricted to Crick’s ‘rules’.
The subsequent elucidation of the structure of phe-tRNA by Quigley and Rich in 1976 suggested why the wobble occurred at the 5′ position of the anticodon. This position (G34 in my modification of their figure, below) lacks the base-stacking that would be expected to constrain the interactions at the other two positions of the anticodon, and which was aided by a modified base (yW37) 3′ to the anticodon.

As the amino acid, methionine, has only a single codon (AUG) in the genetic code, one would expect it to have a tRNA that does not allow wobble at the 5′-codon position. This turns out to be the case:

Both the tRNAmet for elongation and initiation have
  the anticodon 3′-UAC-5′.

In summary: 5′-codon wobble allows mRNA to be decoded accurately by fewer than the 61 amino acid codons, and one can speculate that its emergence involved evolution of both the structures of tRNAs and the ribosomal A-site.
Initiation and decoding ambiguity
In bacteria (eubacteria) there are two main differences in codon recognition during translation from that in elongation.

There is a single specific tRNA species involved which, uniquely, can interact with initiation factors and be bound to the P-site of the ribosome.
Interaction is required between the 16S rRNA of the 30S ribosomal subunit and a polypurine sequence 5′ of the initiation codon (the Shine & Dalgarno sequence or ribosome-binding site) in addition to the codon–anticodon interaction.

To adopt an extreme position, the situation in initiation may almost be thought of as one in which the fMet-tRNA is bound at the P-site of the small ribosomal subunit waiting for mRNA to bind, in contrast to elongator Met-tRNA binding to an A-site with the elongation codon AUG. The energy provided by the Shine–Dalgarno interactions may thus be enough to allow initiation if one of the initiation codon bases is incorrect. This raises at least two questions:

What advantage would allowing such ambiguous recognition have?
Why is the ambiguity in the first codon position and how does it operate in molecular terms?

I have no answer to the first question. Perhaps it has none, but is tolerated because it has no disadvantages either. The second question is the crux of the poster’s concerns.
First, ambiguity at the 3′-position of the codon would not be expected on grounds of structure or precedent: the table above shows anticodon 5′-C only base-pairs with codon 3′-G.
Second, the anticodon loop of initiator tRNAmet differs from that of elongator tRNAmet in having an internal-facing rather than an external-facing disposition (Woo et al., 1980). Furthermore it lacks a modified base 3′ to the anticodon.
Third, the interactions between initiator and elongator tRNAs with the rRNA at the A- and P-sites, respectively are quite different (Berk et al. 2006), conceivably allowing more flexibility at the 3′-anticodon position.
Despite the fact that the predicted anticodon-U/codon-G wobble never occurs at the A-site, it is reasonable to suppose that structural differences allow it at the P-site, explaining the second bacterial initiation codon, GUG. As regards UUG, U=U base-pairs were considered by Crick but regarded as “rather close together”. Presumably in certain contexts this is not too energetically unfavourable to be prevented.
Finally…
The poster asked:

Am I interpreting this correctly and there's no "Crick" wobble in the AUG > GUG > UUG start codon, but rather another wobble-like mechanism that explains the start codons' first nucleotide wobble-like behavior?

To which I would reply that:

There is not and cannot be any wobble at the 3′-position of either initiation or elongation AUG codons of bacteria because it would involve non-standard base-pairing of the anticodon C. To the extent that the ambiguity at the 5′-position of the alternative initiation codons used (GUG>UUG) follows a pattern consistent with the most likely non-standard base-pairing predicted by Crick, it would seem to involve base-pairing achieved by movement (wobble) of the 3′-anticodon residue U of initiator fMet-tRNA.

Also, did look at a paper comparing the initiation and elongator myself (has nice diagrams on both eukaryotes and prokaryotes (Rassmusen et al.), but  they didn't hint to anything about function with respect to wobble-like behavior from the structural difference. So I do wonder how speculative the mechanisms are.


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Deducing amino acid sequence from a DNA sequence
The suggested answer to the question is the following: "M L S C D K S D Stop". I do not understand how they get that result.
The question is as follows:
An RNA polymerase transcribes the following DNA sequence, in the direction of the arrow. Which amino acid sequence will be generated?

Thanks in advance!

I get that, and the first ATG is at 5' CCA CC ATG TTA. I thought it always reads the code in triplets? Thats why that option doesn't make any sense to me.

@OLi4 The polymerase certainly does NOT search for a start codon to start transcription. The polymerase produces a mRNA with a 5' untranslated region before the start codon. However this question is not about RNA polymerase, its a theoretical question about the genetic code.

This is a deceptively and badly worded trick question. Your confusion is because it starts with a mention of RNA polymerase, which transcribes DNA into mRNA, but asks about the protein, which is produced by the translation of the mRNA on ribosomes.
The first step in solving the problem is asking what is the sequence of the mRNA produced by the transcription. The question doesn't actually say which strand is copied, but the 5'-end of the mRNA is synthesized first, so you can assume the mRNA is the complement of the bottom strand, which is copied. (The convention of direction presumably tells you the same thing). Thus, the mRNA has the sequence:

CCACCAUGUUA...

Now you need to go along the sequence (as a ribosome) looking for where to start translating. However the question doesn’t tell you whether this is a prokaryote or a eukaryote (unless you omitted to tell us). In order to solve the problem we have to assume it is a eukaryote where the ribosome normally scans along from the cap to the first AUG to initiate translation (the region italicized above):

AUG (ATG) = M
UUA (TTA) = L
etc

(If it were a prokaryote you’d need to look for a Shine and Dalgarno ribosome-binding site.)
You might wish to raise my criticisms with your instructor (although I doubt that he will thank you for doing so).


text:
What is the difference between cytosol and cytoplasm?
I've generally seen cytosol defined as the solution inside cells minus  the organelles, cytoskeleton, etc and cytoplasm as the cytosol plus the organelles, cytoskeleton, etc. This naturally leads to the impression that cytosol is the cytoplasm minus all the solids. The problem here is that there are all sorts of other large molecules in the cells which could be thought of as solid. Are they also part of the cytosol or are they suspended in it? (I.e. are they part of the cytosol or are they non-cytosol components of the cytoplasm?)
Basically, I'm asking if the precise definition of cytosol is just anything in the cell that's not behind an endomembrane (save the exoskeleton) or if the dividing line is something else.
Subquestion: things can get even more terminologically confused because the cytosol is sometimes called the matrix. What the heck is the preferred terminology with this stuff?

'The problem here is that there are all sorts of other large molecules in the cells which could be thought of as solid.' Can you give some examples so that we understand how you are using the term 'solid'?

IMO, the definitive answer to this question is given in a paper by J. S Clegg.  He traced the origin of the term cytosol to a book chapter by H. A. Lardy, and confirmed by email that Lardy had indeed coined the term. Their definition of cytosol is as follows:

... that portion of the cell which is found in the supernatant fraction after centrifuging the homogenate at 105 000 x g for 1 hour.

Thus cytosol is a centrifugation term, (ie a fraction obtained by centrifugation)  and  ' should not be applied, in any context, to the intact cell' (Clegg, 1983).
The cytosol  may roughly be though of as the 'soluble' portion of the cellular extract obtained after everything else, including the microsomes, have been sedimented. (For those not familiar with subcellular frationation, centrifugation at 100 000 g for 1 hr is the 'standard' method of sedimenting microsomes. If your enzyme is found in the 100 000 g supernatant fraction, you can be  pretty sure it is soluble).
When we are referring to the cellular aqueous fluid  that 'holds'   the organelles and other  components we should use the term cytoplasm.
At the bottom of Clegg's article, the editors of TIBS have supplied the following quote, attributed to F.H.C Crick & A. F. W Hughes (1950):

If we were compelled to suggest a model for the structure of cytoplasm we would propose Mother's Work Basket -a jumble of threads, beads and buttons of all shapes and sizes, with pins and threads for good measure, all jostling about and held together by "colloidal forces".'

In being a  centrifugation fraction,  the term  'cytosol' is very like  microsome: the intact cell contains neither cytosol or microsome.
Ref
Clegg, J. S. (1983) What is the cytosol? Trends in Biochemical Sciences 8, (Dec, issue 12), pp 436-437

Per my bio textbook, they have cytoplasm as "the region contained within the plasma membrane" and cytosol as described as "site of many metabolic pathways" and "the region of a eukaryotic cell that is inside the plasma membrane and outside the organelles."
Ref
Brooker, R. J.; Widmaier, E. P.; Graham, L. E.; Stiling, P. D. Biology; McGraw-Hill Education: New York, NY, 2017.


text:
Are PVC&PET bacteria found inside homes?
I am interested in weather PVC and PET eating bacteria can be found inside people's homes. The PET consuming ones were found in or near plastic waste dumps or in the ocean, but would they also have adequate conditions in people's domiciles or they require specific things like the plastic being constantly in contact with water or earth?
I am mainly interested in the probability/possibility of PET eating bacteria being found in domestic spaces.

Sorry, i was away for a while and didn't see it ^^: I am more interested in PVC, and yeah, i have plastics that are 15+ years old and don't have any visible holes or abrasions, i was a bit perplexed about weather a lifeform so proliferous (and with ample ''food'' available) would only be found in dirt/water, if that, and could consume PVC only while there.

Only thing i found that addressed the issue tangentially was a wikipedia article about a strain that eats PET and was found in Japan, and an article about PET degrading bacteria in cold seas, no mention of PVC or household conditions. I guess that i'd do best to find some microbiologist or bacteriologist and ask them directly, but chances of that are low.

I see (X-ray specs you get after a certain time here) that you tried to thank me in an answer (deleted) You haven't enough "reputation" (points) to comment yet, where this would normally go. You are welcome. Although I don't share your particular concerns, it was interesting to me from a biochemical point of view to read about the bacterial metabolism.

If you read the Wikipedia article carefully, and the recent article in PNAS on improving the enzymes responsible for TET degradation, it is evident that Ideonella sakaiensis is the only example so far known of a bacterium that can use PET as an energy source. As it is a Japanese marine bacterium it will not be found in “domestic spaces”.
The requirement for an aqueous environment is presumably related to the need for the enzymes the bacterium secretes to gain access to the plastic and the products of the digestion to be reabsorbed, and perhaps also for access to essential nitrogen, not present in the plastics. The rarity of bacteria that have evolved this facility presumably relates to the ‘difficulty’ of the chemistry — or its difference from that involved in degrading other carbon sources — although there is some similarity to cutinase, the enzyme in certain fungi that can digest the cuticle of plants.

I also found something other of interest, apparently a certain Daniel Burd isolated some microorganisms from a landfill, full info here:
https://oxsci.org/2018/11/27/daniel-burd-17-year-old-eco-expert/
The organisms that he found degrading PET were genus Sphingomonas and Pseudomonas. I couldn't find weather they had PVC degrading capabilities though. As for these being found in ''domestic'' conditions, well, they were found in a landfill, so a level of moisture and soil contact seem to be of some necessity to them.


text:
What are the differences between different strains/types of Cre?
Reading from Hedgehog signaling reprograms hair follicle niche fibroblasts to a hyper-activated state:

Lineage-specific genetic tools are necessary to precisely study HF
fibroblasts; however, their repertoire remains limited. Embryonic
dermal condensate progenitors can be targeted with Tbx18-Cre (Clavel
et al., 2012), whereas adult DS fibroblasts, with
Sma-CreERT2 (Rahmani et al., 2014) and Acan- CreER (Heitman
et al., 2020). DP fibroblasts activate Sox18- CreERT2 at
birth (Legrand et al., 2016), Corin-Cre soon after birth
(Enshell-Seijffers et al., 2010a), and CD133-CreERT2 in
adult skin, albeit only with low efficiency (Zhou et al., 2016). Here,
we confirm that in mouse skin, Leptin receptor (Lepr) is a faithful DP
marker gene (Greco et al., 2009; Rezza et al., 2016) and show that
isoform B-specific LeprB-Cre (DeFalco et al., 2001) and LeprB-CreER
can be used to efficiently target postnatal DP fibroblasts. Using
these genetic tools, we uncover how DP fibroblast lineage and
signaling niche are regulated by the Hedgehog pathway.

I watched this video as a refresher on Cre recombinase. I attempted to Google the question with no luck. I also glanced back at one of the papers referenced. It seems it would take considerable effort for me to teach myself this answer and I'm sure there are members here who know off-hand. My understanding of Cre is that we will put it under the expression of tissue-specific promoters, as is stated in the video. I covered this technique in a paper I read last semester. I assume ER stands for endoplasmic reticulum, possibly? Where additional confusion is arising for me is that in the sentences describing "at birth" and "soon after birth" it seems in the way it's presented that these Cre could be native to the organism but we add Cre to the genome in all these cases, right?

FWIW, to find a reference to include in my answer I searched "CreER cre recombinase" (to avoid false positives with "creer") in Google and found an example paper to cite immediately. Perhaps it helped that I'm familiar with the system and knew what I was looking for.

Your answer is absolutely helpful, thank you for typing it up and for the quick reply. I definitely am in a much better position to complete the investigation myself if need be. Instead of accepting your answer, I am going to leave the question open as while your answer is a start there is quite a bit going on in that paragraph I quoted from the paper.

CreER is Cre coupled with a binding site for the estrogen receptor ("ER") to make an inducible version of the Cre system triggered by tamoxifen. CreERT2 is just a particular variety of this system with some mutations that improve the function.
Feil, S., Valtcheva, N., & Feil, R. (2009). Inducible cre mice. In Gene knockout protocols (pp. 343-363). Humana Press.
Some quotes from this paper:

To add inducibility to the Cre/lox system, ligand-dependent chimeric Cre recombinases, so-called CreER recombinases, have been developed (3–6). They consist of Cre fused to mutated hormone-binding domains of the estrogen receptor. The CreER recombinases are inactive, but can be activated by the synthetic estrogen receptor ligand 4-hydroxytamoxifen (OHT), therefore allowing for external temporal control of Cre activity.

The properties of CreER recombinases were continuously improved to decrease the background activity in the absence of inducer and to increase the sensitivity and efficiency of tamoxifen-induced recombination in mice. The CreERT2 recombinase, which contains the human estrogen receptor ligand-binding domain with a G400V/M543A/L544A triple mutation, is currently the sharpest tool in the CreER box and its use is highly recommended for inducible mutagenesis in the mouse (4 , 9 , 10).

Briefly, the two common ways to use the Cre-Lox system these days are either 1) You have a gene you want to knock out in only certain cells; you've modified this gene to be surrounded by LoxP sites (often referred to as 'floxed' as a shortening of 'flanked by LoxP sites'), or 2) You have some genetic construct you want to express in only certain cells (for example a reporter like green fluorescent protein/GFP), so you start with an inserted gene with a 'floxed' stop codon that comes before the GFP.
You then express Cre under a desired promoter (let's call it YourFavoritePromoter), Cre cuts out the floxed section: either the gene to conditionally knock-out (1), or the stop codon so your GFP is produced (2), but only in cells that have YourFavoritePromoter expression.
However, this is a permanent change in a lineage. If Cre is ever expressed at any time during a cell's lineage, all subsequent daughter cells will have had the floxed part removed. That means the cells you mark with GFP are not necessarily those expressing YourFavoritePromoter now, but cells that sometime in the past expressed YourFavoritePromoter.
You can use CreER to get around this, as Cre will only be expressed with tamoxifen present. That allows you to control the time window in which Cre is expressed, and therefore the time window in which you are identifying cells with YourFavoritePromoter.
You'd want to follow up with all the individual references in your paragraph to see what they are doing specifically. For example, in the "Legrand et al 2016" paper:

Sox18 is expressed specifically in the DP in all dorsal hair follicle types; however, at birth its expression is restricted to zigzag hairs lacking Sox2 expression in the DP (Driskell et al., 2009, Pennisi et al., 2000)

So, if you want to tag "zigzag hairs" (I really have no idea what these are, but it doesn't matter for understanding the system), you use Sox18-CreER and give tamoxifen at birth. If you used ordinary Sox18-Cre, you'd label "all dorsal hair follicles" instead.
All of these are artificially introduced constructs. A frequent method for efficiency is to have some homozygous mouse strain that expresses the gene you want to see (say, floxed GFP in our example), and a different mouse strain that has the Cre construct you want (say, Sox18-CreER). Each are created using standard transgenic techniques; many researchers don't need to bother with those details because you can just buy the mice, but if you want a particular unique line you have to make them. You then breed them together to get mice that have Cre and the floxed gene.
Here's what they did (quotes from Legrand et al):
Make mice with floxed version of gene they want to control expression of (STAT5A/B; note here they're actually doing a conditional knockout, so rather than have Cre remove a stop codon it's removing the entire gene):

STAT5A/Blox/lox mice (Cui et al., 2004) were first crossed with Flash/+ reporter mice to generate mice homozygous for the STAT5 floxed allele containing the previously described Flash Wnt-reporter transgene (Hodgson et al., 2014)

Breed these with the Sox18-CreERT2 mice so they have tamoxifen-controllable cre expression under the Sox18 promoter (extra complication here that these mice also express a reporter gene; that one works with the stop codon method I described above):

These mice were then crossed with B6;129S-Sox18tm1(GFP/cre/ERT2)Pzg/J (Sox18GCE/+) mice to generate Sox18GCE/+ mice homozygous for the STAT5A and STAT5B floxed alleles, although also containing the Flash reporter transgene

Give tamoxifen at birth to express cre in a specific population of cells which will knockout STAT5A/B and express the GFP reporter.

Recombination in these mice and their appropriate control groups was induced at birth using a single dose of 1mg tamoxifen.

Thank you, Bryan, for your well-thought-out answer. My only suggestion would be to define acronyms before you use them (I think I also made this mistake in some of my earlier content). I know what GFP is but it's about making it easier for the next guy. Anyhow, I definitely feel up to my neck with this paper and am going to pause, step back, and read the chapter you referenced.  Where I struggle is with visualization of the crossing of mice, and like anything needs practice. I am open to any specific literature (or exercises) you feel may be helpful before I continue reading this paper.

@neurosciencecalc I think it'll come with experience. Crossing mice is just like Mendel's experiments with pea plants, I'd go re-read those sections of a biology textbook for a refresher.

Sounds good. Thank you, Bryan.

I feel kind of silly for my question now that I am understanding more, but that's all part of the learning process. I see now that the notation is 'tissue_specific_promotor-CreERT2' and you did such a great job explaining the CreERT2 and that chapter you linked to is great as well. Thanks again for your help.


text:
CD45 as a microglial marker in Fluorescence-Activated Cell Sorting (FACS)
I am reading this article: Microglial cannabinoid receptor type 1 mediates social memory deficits in mice produced by adolescent THC exposure and 16p11.2 duplication.
In Figure 1a, the authors are using Fluorescence-Activated Cell Sorting (FACS) and are identifying different cell types as follows: microglia (CD45$^+$CD11b$^+$TMEM119$^+$), astrocyte (ACSA-2$^+$), and neuron (NeuN$^+$).

My understanding is that the upper and lower panels indicate two different batches of cells. The upper panel shows neurons identified by the NeuN marker. At first I was thinking that because of this "microglia (CD45$^+$CD11b$^+$TMEM119$^+$)," that cells were selected from Q2 in the left lower panel and were further examined in the context of expressing TMEM119 and ACSA-2 to differentiate between microglia and astrocytes.
The problem I am running into with my interpretation is two-fold. Reading from abcam: "A combination of CD11b and CD45 labeling can be used to distinguish microglia from macrophages. Resting microglia are CD11b$^{hi}$, CD45$^{low}$, whereas macrophages are CD11b$^{hi}$, CD45$^{hi}$." This would seem to indicate that Q1 is the pool of microglia. As far as Q2, if it represents macrophages, why would there be a larger presence than the resident immune cell microglia?
The second issue with my interpretation is that I do not see any literature suggesting that astrocytes express CD11b or CD45. Any help here is greatly appreciated!
Edit: Regarding the abcam source, they also provide this with references.
Edit2: "In order to confirm Cnr1 expression at the protein level, we used magnetic activated cell sorting (MACS) to isolate microglia-enriched CD11b$^+$ cells, ACSA-2$^+$ astrocytes, and remaining cells including neurons from the cerebral cortex of Cx3cr1$^{CreER/+}$;Cnr1$^{flox/flox}$ mice and littermate controls (Cx3cr1$^{CreER/+}$;Cnr1$^{+/+}$). We used this approach as it produces a higher cell yield than FACS with over 95% of collected CD11b$^{+}$ cells being microglia." I feel like this excerpt from the paper should help to provide some clarification to whoever answers this question.