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Production of “Green Hydrogen” by photosynthesis
In a popular science book from the 1970s I read about experiments to tweak some microorganisms to produce elemental hydrogen by photosynthesis.
Is this a feasible way to produce “Green hydrogen”? What kind of microorganism can be used for this task, and what is the efficiency of that process?

Photosynthesis
The aspects of photosynthesis pertinent to this question are as follows:
The overall chemical transformation in the light reactions of photosynthesis is:

2H2O + hν → 4H+ + 4e– + O2

The hydrogen ions are produced in such a way as to create a gradient that is used to generate ATP, the electrons are used to reduce NADP+ to NADPH. Together these allow the reductive synthesis of carbohydrate sugars from CO2.
This process involves two photosystems — PSII and PSI — shown below, the latter of which is most pertinent to this topic.

Coupling Photosynthesis to Hydrogen Production
The basic objective of modifying photosynthesis to generate hydrogen — biophotoloysis — involves using the electron to reduce the hydrogen ion to hydrogen gas, rather than allowing it to be used to oxidize NADP+.

2H+ + 2e– → H2

So that the overall reaction becomes:

2H2O + hν → 2H2 + O2

(Of course, this will be at the expense of energy and reducing power for carbohydrate synthesis.)
Using Hydrogenase for the Catalysis
The enzyme, hydrogenase, can catalyse the reduction of hydrogen ions shown above. This enzyme is rare in eukaryotes and absent from higher plants. It is thought to be very ancient, and may have originally been involved in energy generation from hydrogen in early evolution. One of the roles it plays in contemporary organisms is in reoxidizing NADH generated during certain fermentations in bacteria such as the Clostridium family — hydrogen is the gas produced in gas gangrene caused by Clostridium perfringens.
Certain photosynthetic organisms — notably the microalga, Chlamydomonas reinhardtii, and the photosynthetic cyanobacteria — also contain a hydrogenase in their chloroplasts. The activity of this is generally low, but appears to be coupled to photosynthesis in certain circumstances. This is through the reduced ferredoxin produced at PSI transferring its electron to the iron or iron–nickel centre of the hydrogenase:

The physiological importance of this coupling is not fully understood but its discovery offered the possibility of using it to produce hydrogen from water.
Commercial Application — Approaches and Problems
The focus of many of the attempts to exploit this coupling to produce hydrogen on a commercial scale have used Chlamydomonas reinhardtii, where is was shown that deprivation of sulphur enhanced the evolution of hydrogen significantly. From a commercial standpoint the price at which a fuel can be sold depends on the cost of its production, and to be viable this has to be competitive with alternatives. Hence it is important to maximize the production of hydrogen, and considerable effort has been directed towards this. However, we are not yet at a stage where photosynthetic hydrogen can compete with other fuels.
The two main factors limiting widespread commercial exploitation of this process have been the sensitivity of the dehydrogenase to inhibition by the oxygen produced in the process, and the low efficiencies of conversion of solar energy (<2%). The former problem is, in fact, one of the reasons for using Chlamydomonas reinhardtii, as it can perform oxidative respiration, lowering the concentration of oxygen. Attempts have been made — and are presumably still being made — to engineer the hydrogenase to reduce its sensitivity to oxygen, to control the oxygen concentration, and to improve the photosynthetic quantum yield by engineering PSII. Increasing the efficiency of photosynthesis itself is a more difficult problem in the eukaryote, Chlamydomonas, and efforts in this respected have mainly been directed at photosynthetic bacteria.
Literature
My knowledge of this field is based purely on a perusal of sources found in a literature search. I was actually surprised to discover that there is at least one journal dedicated to hydrogen as an energy source. Here are the papers I consulted:
Bolatkhan et al. (2019) Int. J. Hydrogen Energy 44, 5799–5811
Oh et al. (2013) Biohydrogen, Ch.3, pp. 45-65 Elsevier.
Ni et al. (2006) Fuel Processing Technology 87, 461–472
Hemschemeier, A. and Happe1, T. (2005) Biochem. Soc. Trans. 33, 39-41


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Why is translation so much faster in prokaryotes than eukaryotes?
Prokaryotes perform transcription and translation much faster than eukaryotes. If memory serves, a single 70S prokaryotic ribosome can incorporate around 20 amino acids per second, whereas the 80S eukaryotic counterpart is much slower, at around 2 amino acids per second. Is the reason for this known? The only possibility I can think of is that prokaryotic mRNAs are often polycistronic, whereas eukaryotic mRNAs are not and tend to involve co-translational protein folding. Slower translation may be able to improve folding accuracy. Other than that, I can't think of any reason the 80S ribosome would be physically slower than the 70S ribosome. It's not like DNA replication where accuracy is exceedingly more important in multicellular organisms than in fast-replicating unicellular prokaryotes.

I have made some minor corrections to your post. Ribosomes do not pump out amino acids, they form peptide bonds between them. (If they pump out anythng it is proteins.) Proteins cannot be polycistronic, only mRNAs or transcription units. There are poly-proteins, but mainly in eukaryotic viruses like polio. Your suggestion about folding is difficult to understand. Prokaryotic proteins are folded co-translationally just as eukaryotic ones are.

Transcription speed also varies across species. http://book.bionumbers.org/wp-content/uploads/2014/08/540-t1-ErrorRateInTranscriptionAndTranslation-1.png.

Unless the poster can cite more recent papers to support the assertion regarding a difference in rates of prokaryotic and eukaryotic protein synthesis, I would say that this is incorrect.
Lacroute and Stent (1968) reported a rate of 15 amino acids per sec for β-galactosidase in Escherichia coli, whereas Knopf and Lamfrom (1965) reported a rate of 7 amino acids per sec for globin chains in rabbit reticulocytes. This does not appear much different to me, especially as a recent study by Li et al. (2014) showed that the rate of protein synthesis varies with the complexity of the assembly (if any) into which a protein is incorporated.

My assertion mainly came from memory, and was reinforced by a quick search that showed a Quora question asking the same thing. Perhaps my memory was just mistaken!

I can imagine circumstances (growth on rich medium) where bacterial protein synthesis is faster, and I need to comb through the suplementary material in the Li paper to see if I can find an update on the 60s figures. When I've done that I'll post an addendum, also discussing what might be rate-limiting for translation.

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What is the best alignment definition for the Multiple Sequence Alignment (MSA) problem?
For simplicity, suppose that I am penalising mismatches and gaps with -1 and adding a score +100 for each match.
Does the optimum alignment of the three DNA sequences
AAATTT
AAAGGG
GGGAAC
equal to:
AAATTT---
AAAGGG---
---GGGAAC
with the total score S =  294 + 294 - 6 = 586? In this case I sum the alignment score for each of the three pairs.
Or does it equal to:
---AAATTT
---AAAGGG
GGGAAC---
with the score 200 - 7 = 193? In this case I am rewarding only the matches that occured across all three sequences at the same time.
Which of the two scores are the common Multiple Sequence Alignment algorithms trying to optimise for? Or if both are valid, then which optimal alignment (i.e. with respect to which definition) is preferred if realistic reward/penalise values were used?

Please do some reading on a topic before posting a question. This one is based on simplistic and false assumptions. A look at the WIkipedia page on MSA (https://en.wikipedia.org/wiki/Multiple_sequence_alignment) would make you aware of what a complex topic it is.

Further would you please avoid or define abbreviations in the titles of questions. This helps people searching for a topic and those who may be interested in it but are not familiar with the jargon. I am altering the title to include the full name. Please do not revert it.

A common scoring method is "sum of pairs", which is essentially the sum of scores of all pairwise alignments. The wiki page has mentioned this. You can find more discussions in Durbin's book biological sequence analysis, section 6.2.

In your case both answers are equally valid.
The scoring matrix, for example DNAFULL (http://rosalind.info/glossary/dnafull/) usually contains various penalties for wrong alignments.
Also the introduce gap score should NEVER be set at 0 as it will cause the aligned sequences to be filled with artificial gaps!
The only thing the algoritms try to optimise towards is the score, therefore you need sane values for calculating the score and those you propose does not result in usefull alignments.

The scoring matrix you mention is used (to the extent that people actually use it) for pairwise alignment. At least for Clustal, a dynamic position-specific scoring system is used as successive sequences are added. Therefore the question does not relate to actual MSA — at the most is is only a weekend newspaper puzzle.

The DNAFULL matrix can be used instead of the PAM or BLOSUM matrices for multiple alignments. The fact that it is mainly used for PAIRwise alignment doesn't exclude it from being used for MSA.

Jeppe Nielsen is right: MSA programs do use pair-wise scoring matrices. David is talking about progressive alignment, which is a heuristic to do MSA as finding the optimal solution is NP-hard.

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How do animals identify their offspring?
Recently I was watching a documentary about penguins and how a mother penguin lost its chick. Then it went looking for it, and among a horde of penguins it was able to find its chick and take it back.
What really intrigued me is that the penguins looked exactly the same. Animals don't have as many
distinctive features as we humans do, such as significally different hair color, skin color, they don't really look very different. Rather animals of the same species look very similar.
Just consider the following image:

How can one even differentiate between all these penguin chicks? Even the parents look very similar to me.
So how can parents spot their offspring among all of these penguins that look almost identical?

It varies a lot from species to species. The question How do animals know who their child is? is too broad, you probably want to ask How do penguins know who their child is? instead.

@Remi.b its not only for penguins, but for animals in general

Well the I am voting to close as the question is too broad as mechanisms vary a lot from species to species. Some would use facial recognition (e.g. sheep), others would use smell, others would not need to recognize as only their offspring stays in the neibourhood, others don't recognize their youngs, most species use some mixture of those cues, etc...

All the penguins appear (and would smell) similar to you. But not to the penguins.

nature gives them variance so that they recognize very easily what is important to recognize. to know the difference, many tests have been done, using sound proofing, visual screens, and they can probably recognize them by sight or sound, although sound is probably the main recourse because birds have very good ears and variable voices, and it's a 2 way thing, the parents call and the baby replies, it's not random sounds.

Many mammals recognize their offspring by smell, some by cry, etc. In my flock of goats, at kidding time the mothers always smelled the anuses of the infant offspring (after they had fed at least once) before allowing them to nurse. Their particular milk and the way it is digested by the offspring had a unique smell. If it was right, they nursed. If not, they were rejected. This is not unique to goats, but there are other ways as well. This is a broad subject.

@anongoodnurse You are a molecular biologist, a physician, a fan of Shakespeare, probably a parent given your activity on Parenting.SE (or maybe just a pediatrician?) and you're raising a flock of (anus smelling) goats! You sound like an interesting person to be around!

@Remi.b - Thanks for saying that; it's quite kind. Many people just think I'm crazy. ;)

You don't have to close it. I mean you can. I know its broad but its just something I wanted the answer too, and I think @anongoodnurse and the rest have given me really good answers. even remi has, thanks alot everybody

It's only a partial answer given that it's a fairly broad question, but I discussed the specific mechanism for this in sheep here: https://biology.stackexchange.com/questions/46306/why-would-a-mother-reject-her-offspring-if-it-has-been-interfered-with-by-huma/46388#46388

Penguins (and many birds) recognize their offspring and mate thanks to vocalizations.
It's called individual vocal recognition, it's like when you recognize your friend voice among a group of chatting people.
Scientific article references for penguins:
Jouventin P., Aubin, T., Lengagne, T. 1999. Finding a parent in a king penguin colony: the acoustic system of individual recognition. Animal Behaviour 57(6):1175-1183.
http://www.sciencedirect.com/science/article/pii/S0003347299910862
Aubin T., Jouventin P. and Hildebrand C. 2000. Penguins use the two–voice system to recognize each other. Proc. R. Soc. Lond. B. 267:1081–1087.
http://rspb.royalsocietypublishing.org/content/267/1448/1081.short

Animals used several ways to tell who their child is, some use sounds, yes, some use spatial cues and THEN sounds to zoom in the individual they want to find, and sometimes they even need to confirm by smell!
Here is a good reference that describes this process and the different sensory cues used in a pinniped species:
Kaja Wierucka, Benjamin J. Pitcher, Robert Harcourt, Isabelle Charrier. (2018). Multimodal mother–offspring recognition: the relative importance of sensory cues in a colonial mammal. Animal Behaviour 146: 135-142
https://www.sciencedirect.com/science/article/pii/S0003347218303208
For more information specifically on what kinds of information animals can glean or transmit use of acoustic cues, this book is really informative!
Coding Strategies in Vertebrate Acoustic Communication (Animal Signals and Communication 7) 2020 Editors Thierry Aubin and Nicolas Mathevon
https://link.springer.com/content/pdf/10.1007/978-3-030-39200-0.pdf

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Hand-washing resistant bacteria. Will they evolve one day?
I know that soap kills bacteria by dissolving their membrane. But it is not 100% effective. A small portion of bacteria which survive replicates and I have to wash my hands again.
Will this cycle lead to evolution of soap-resistant bacteria with insoluble membranes?

Different from common believe, handwashing will only reduce the number of bacteria on your hands but not eliminate them. Have a look on surgeons and their practice to wash hands and sterilize them. And this is not a problem, bacteria live normally on our skin and belong there.

soap isn't a germ killer.
soap is a germ REMOVER. it is basically made of things a lot like phospholipids, that bury their fat loving tails into germs, and their water loving heads stick into the water, making whatever is in the capsule called a "micelle" super slippery,and they wash away.
the cool thing about this is it removes even non living gunk (sometimes).

Not all soap kills bacteria, not all soaps work the same
actually, the rinsing, rubbing, and temperature of the water significantly contribute the removal and termination of bacteria even then this is not 100%.
I wouldn't want to touch blood with AIDS virus or Ebola and rely solely on soap and hand washing to save the day.
Some soaps work by raising the PH and there are already a category of organisms called Alkaliphiles which thrive in high PH environments. To my knowledge these cant really harm you as you are a low PH organism.
But yes theoretically if you use the same measure against a bacterium long enough and constantly give it a chance to succeed, eventually it will.


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Is lung size/shape a factor in long-continuous running of animals?
Apart from other factors, does lung shape/structure/size play any role in long-continuous running animals.
Is there any similarity in lung structure between different long-continuous running species?


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Why does no one get vaccinated against plague in Europe?
I've read on Wikipedia that only people who work with Y. pestis and people in 3rd world countries get vaccinated against it:

Since human plague is rare in most parts of the world, routine vaccination is not needed other than for those at particularly high risk of exposure

But I know that it is easy for plague to conquer Europe. All your need is just some fleas and half of the continent dies, as proved in history.
So why does no one in Europe get vaccinated against plague?

Because it is not necessary. Living conditions have dramatically improved since the last time the black death got over Europe.

@Chris but why did improving living conditions affecting plague and not other diseases agains which we are getting vaccinated. My friend is an anti-vaxxer and I have to convince him, yet I am not a specialist.

Also, it's arguable that the people who survived the Black Death and other plague outbreaks had a degree of natural resistance, which they passed on to their descendants.  Consider how measles &c were able to kill off a large fraction of the population of the Americas after European contact.

I'm voting to close this question as off-topic because it is of low quality. "All you need is some fleas" indeed.

Ask yourself when was the last time that you went to a friend's home and had to worry about getting flea bites? Modern cities still have lots of rats, but modern construction, pesticides, and hygiene have greatly reduced the number of encounters between fleas and people. Contrast that with the early 18th century. When the young George Washington wrote an essay on civil behavior, he felt it worth while to include this item:

13th Kill no Vermin as Fleas, lice ticks in the Sight of Others, if
  you See any filth or thick Spittle put your foot Dexteriously upon it
  if it be upon the Cloths of your Companions, Put it off privately, and
  if it be upon your own Cloths return Thanks to him who puts it off.

Plague is almost exclusively transmitted to humans by fleas (the pneumonic form of the disease can be transmitted by aerosols but is rare). Few encounters with fleas, few cases of the Plague.
Mumps and measles (for example) are transmitted by human to human contact. No fleas needed. Modern life may have done away with flea bites, but it has only increased the number of persons we come in contact with each day. If you think about it, all the diseases we commonly get vaccinations for are ones spread by direct human to human contact: smallpox, polio, diphtheria, whooping cough, mumps, measles, flu. Tetanus vaccines are an exception, but that's a bacteria that is ubiquitous in the environment, and causes a very nasty disease.

https://news.nationalgeographic.com/2018/01/rats-plague-black-death-humans-lice-health-science/

Because antibiotics are relatively cheap and effective against Y. pestis. Also our easy access to high quality healthcare ensure that diseased individuals are rapidly isolated and threated. Therefore the benefits of the vaccine does not outweigh the riscs associated with it.
You can then argue from now till the end of time of whether other vaccines are worth using. Personally I trust doctors and other scientists to analyse the available data and make the best choice in each case.

my great gran said she didnt trust doctors and she lived till 99 and 10 months. never saw one! a bit of cynicism goes a long way.

Sure, but unless you have spent 5 years of your life studying medicine, life sciences, biology or chemistry, you have no basis on which to base your decision. Therefore you will be prone to make false assumptions based on wrong, partial or non-existent knowledge.

Plague infections are extremely rare outside of the third world. For the rare occasion that isolated cases of plague make their way into the developed world, plague bacteria overall haven't had much contact with antibiotics (few opportunities to develop resistance) and therefore are generally vulnerable to a standard antibiotic course.
Modern sanitation also helps a lot.


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What species of ant is this, and is it a queen?

I found her underneath a big rock along with a bunch of much smaller Lasius niger workers, so
I suspect it might be a queen. I know Lasius niger doesn't have soldiers, so what could it have been doing there if it wasn't their queen? Also, sorry for the bad picture quality, I couldn't find a better camera, and also don't have a proper magnifying glass.
Country: Belgium
Environment: forest
Location: underneath big rock
Behaviour: calm when walking in lighted up areas
Species it was found with: Lasius niger workers running around frantically (note: this specimen was much bigger than the workers)

Wikihow > How to identify a queen ant might be a good first series of step to determine if it is queen. I suggest that you address the questions of this article into your post.

In which country and which environment (forest, prairie, ...) did you find it?

I know what a queen looks like, i've had many lasius niger and flavus colonys in the past, i've only never seached in forrests before.

I dunno what i meant, with that, i'll remove it, but it's larger than 6mm, and smaller than 1cm, she's moving around very franticly when i try to measure her legnth.

This ant looks very much like a Camponotus pennsylvanicus queen, but since it was found in a Belgian forest, I could be wrong. I am almost certain it is a Camponotus species though. I hope I could have been helpful to you!


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How can humans hear low frequency sounds using the cochlea which is tiny compared to wavelength?
Humans can reportedly hear sounds as low as 31 Hz. If we consider the speed of sound in air to be 1125 feet per second, then a sound at 31 Hz will have a wavelength of about 36 feet.
Normally, to capture a sound or other wave, we need an antenna that is at least as long as the wavelength of the signal we are attempting to receive.
But with the ear this is plainly not possible. If the cochlea of a human ear were to be unrolled, it would have a length of about 1 inch. Thus, in the sense of being an "antenna" it would seem to be far too short to be able to receive a 31 Hz signal, yet somehow it does.
How does the ear sense such low frequency sounds?

"to capture a sound or other wave we need an antenna that is at least as long as the wavelength of the signal" - this is definitely not true for sound, it doesn't have to be anything special about an ear. I am also guessing your laptop/headset/cell phone doesn't have a 15-meter long antenna.

Possible duplicate of What causes the tonotopic organization of the inner ear?

Yep, no idea where you got that quote from, but obviously we can hear low frequency sounds. Try googling "basilar membrane dynamics", which should explain how sound frequencies are separated within the ear.

Besides that misconception, I voted to close as duplicate because another question asks about tonotopic organization in the ear and how different frequencies are 'mapped' to the basilar membrane. I think that answer is sufficient to answer your question.

I don't think this question is a dupe from What causes the tonotopic organization of the inner ear?. It has overlap, but the focus is different here. Overlapping questions scopes are fine and should not be closed.

You are thinking of antennas for EM signals such as the dipole antenna. In this type of antenna, an external field (EM waves) excite the antenna (creating an electric current) which you then measure. There is thus something like a transduction step, which is more efficient if you can use the spatial scale of the wavelength.
In the case of hearing sound waves, the ear does not transduce the mechanical signal into another modality, but is directly modulated by the hair cells.


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Do we know which traits reside in which chromosome? If not, how about the next 10 years?
Assuming we develop a technology that allows us to make human gametes (sperm & eggs) combining chromosomes from different persons. Thus we take 1st chromosome from 1st person, 2nd chromosome from 2nd person, 3rd from 3rd etc. Afterward we combine them and make a gamete (sperm or egg)
Do we know which traits reside in which chromosome in order to make that technology useful? If we don't know now, how about in next 10 years.
The only thing I could find is that we know which chromosome hosts genes for certain diseases.
P.S.
This question was originally asked on world building where it was closed as off-topic.

We know the location on the chromosomes of most of the genes in the human genome. You can go to the UCSC or Ensembl genome browsers and look up the positions of most of the genes, and many other features of the human genome.
There may be some genes we haven't recognized yet, but the real issue with what you are asking is that biology typically isn't as simple as "one gene" = "one trait".
The simplified picture is that one gene is the recipe for one protein, but even that isn't strictly true. We now know that one gene may make several variations on a protein through a process called splicing. Furthermore most "traits" will arise through the interactions of dozens of proteins. On top of that there is the issue of which proteins are produced when, and in which cells. Some of this is controlled by regulatory regions, and we're still very much at the beginning of finding all the regulatory regions and how they work together.
To give you an idea of how complex this is: human height is known to be strongly heritable. We've identified about 400 regions of the human genome (genes and regulatory sequences) that have a significant effect on height. However, taken together, the variation in human height explained by these 400 regions explains only about 20% of the observed heritable variation. In other words there is a great deal about the genetics of height that we simply don't understand yet.
There have been experimental efforts to treat simple genetic diseases in humans by substituting or adding "healthy" versions of genes into people who have a non-functioning copy of some critical gene, but we're many decades away from creating whole gametes by cut and pasting multiple genes together. There is considerable ethical and political opposition to the development of such techniques.

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Is a species lifespan affected by meat consumption?
I read a review-like article about the hypothesis of Caleb E. Finch  in a science magazine. The article of interest engages with the idea of Finch

"[arguing] that immune functions and nutrition have been of major importance in the evolution of aging and longevity."

According to this, humans started to regularly consume meat. Meat itself, carrion or injuries during hunting have chances of getting infected and thereby causing death to humans. A strong defensive system against infections lets you survive and its coming into existence may be accompanied by an elongation of our lifespan.
I find myself now asking two questions:
(1) Because the whole article is only about the primate branch, I wonder, whether there are other omnivores that drifted apart concerning their eating habits and if now there is a more carnivorous, longer-living genus?
(2) Do carnivores, in general, have a long lifespan (or is their lifespan highly dependent on a healthy predator–prey equation)? I tried googling, but could not find a relevant scientific resource on this topic.

A major flaw is chimps also eat meat, often other primates, they even hunt for it.  This will put even more stress on the immune system than what we had. The invention of cooking is a more likely suspect, that basically doubled our calorie intake.

Also keep in mind chimps can live for 50 years, which is not much longer than us prior to the invention of medical technology. This sounds like an answer to a question nobody asked.

welcome to Stack Exchange. Maybe for your question it will be useful to search scholar.google.com That engine focuses on scientific literature

The title of your question is a statement. I have converted it into a question, although I doubt whether it can be answered here or anywhere else.

You are going to find too many confounding factors to get ans answer about carnivore lifespan, there are plenty of predatory carnivores that evolved from omnivores but in most cases one or the other side of the split is extinct.

You may have better results asking about Finch's hypothesis, their are plenty of competing ones, one is that humans increased ability to breakdown maillard compounds may be a factors (something we evolved for after we started cooking, or simply that higher intelligence makes longer lifespan more useful, after all evolutionarily speaking longer lifespan is not inherently better.

@John I really hope that somebody posts an example where "the other side of the split" is not extinct. But more importantly: Can you link my to an article, that focuses on the topic of how "higher intelligence makes longer lifespan more useful"?

Its simple, the real benefit of intelligence is learning and learning takes time, longer lived creatures can learn more, many tribal cultures use their elderly for as repositories of knowledge for rare events.

The stated theory is easy to prove with prevalent zoo and other statistics... its just a vague theory.

I don't think that the theory is very reasonable, because animals drink from stagnant ponds (i.e. savanna wells , forest puddles) and have lots of vectors of infection other than rotten meat: cuts and grazes, tract infections, parasites like mosquitoes and nematodes.
The olfactory sense is also very sharp in many carnivores and they can gage the decomposition state of meats. Even humans have a very strong sense of the age of meat using smell, although I can't find  research on it.
The fun thing is to see the age of other animals, i.e. birds and bears. The oldest zoo birds:
Flamingoes, seagulls, vultures, 50-70
parrots 90-120 years.
the oldest panda: 37
the oldest grizzly and polar bear: 40 and 42
Oldest reptiles:
lizards crocodiles and tortoises: 50-100 years
giant tortoise: 150-250 years.
Other herbivores with slow senescence: donkey 60, bison 50, gorilla 60...
research papers don't include any evidence to correlate carnivory and lifespan. It's mostly body mass and ecology, i.e. predation rate.
Carnivores have must stronger stomach acid also which mitigates some of the risk.

Study by Loma Linda showed that 1) a very low meat intake was associated with a significant decrease in risk of death in 4 studies, a nonsignificant decrease in risk of death in the fifth study, and virtually no association in the sixth study; 2) 2 of the studies in which a low meat intake significantly decreased mortality risk also indicated that a longer duration (>/= 2 decades) of adherence to this diet contributed to a significant decrease in mortality risk and a significant 3.6-y (95% CI: 1.4, 5.8 y) increase in life expectancy; and 3) the protective effect of a very low meat intake seems to attenuate after the ninth decade. Some of the variation in the survival advantage in vegetarians may have been due to marked differences between studies in adjustment for confounders, the definition of vegetarian, measurement error, age distribution, the healthy volunteer effect, and intake of specific plant foods by the vegetarians.
CONCLUSION:
Current prospective cohort data from adults in North America and Europe raise the possibility that a lifestyle pattern that includes a very low meat intake is associated with greater longevity.
This study can be read at https://www.ncbi.nlm.nih.gov/pubmed/12936945.

That study has way to many flaws to be useful, it does not differentiate low meat intake and no meat intake, and only compares a dichotomy, so someone who eats nothing but meat and someone who eats meat 1/week are classified together. secondly there is no linkage to the immune system shown nor does it answer any of the OP's questions.

I think this is irrelevant, because (if I understood correctly) the OP is asking about species' lifespans, not the lifespan of individuals within a species.


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Organisms that use more than the 20+2 commonly occurring amino acids?
I know scientists have created synthetic bacteria, with a genetic code containing 6 letters instead of 4, with the aim of creating more complex proteins (using amino acids outside of the standard 20+2, the +2 being selanocysteine and pyrrolysine).
Are there any examples of already-known organisms that use more than the 20+2 commonly occurring amino acids, when translating from RNA codons to amino acid sequences using the ribosome? Post-translational modifications would not count, as the ribosome would not be directly responsible for the incorporation of the amino acid into the protein through that method.
Source: 22 proteinogenic amino acids
https://en.wikipedia.org/wiki/Proteinogenic_amino_acid

Are you asking only about proteinogenic amino acids?

Yeah, I'm asking about proteinogenic amino acids. But if an amino acid is used (beyond the scope of the 22+2 common ones), that amino acid by definition should be "proteinogenic", right?

No, there are natural amino acids that are not used to build proteins. Ornithine, for example.

New contributors are welcomed to SE Biology. Good questions aim for clarity, but inadvertant ambiguity is normal. Comments can suggest ways the poster can edit to remove such ambiguity: 1. State that the +2 refers to selanocysteine and pyrrolysine. 2. Reference, e.g. the Wikipedia page on the Genetic Code. 3. State, if that is what you mean by proteinogenic, that you are refering to amino acids incorporated into protein on the ribosome, and are not talking about post-translational modifications. (The answer is that no others are yet known — as your research should have indicated.)

Thanks @David, I've edited my post to reflect your suggestions. How should I mark this question as answered?

I suggest you answer your own question and accept it. (If I do it for you I'll appear to be soliciting points.) You can just say something like "After searching for papers more recent than those quoted in the Wikipedia article, at the time of writing (Dec. 2018) I cannot find mention of any additional amino acids. For example there is an extensive review in Ann Rev Genetics 2017 which only mentions selanocysteine and pyrrololysine."

At this point in time it appears that no known organisms use amino acids beyond the standard repertoire of the 20+2 common amino acids (the +2 being selanocysteine and pyrrolysine) to construct proteins directly from the ribosome. The extensive review provided by Ann Rev Genetics 2017 mentions only selanocysteine and pyrrolysine, and no other amino acids beyond that.

Some methanogenic Archaea incorporate pyrrolysine in some of their proteins (methyltransferases).
Selenocysteine is another non-standard amino acid; proteins with selenocysteine are called selenoproteins. Both prokaryotes and eukaryotes produce selenoproteins.
Both these amino acids are incorporated at a reassigned UGA codon.

But aren't these the +2 of the question?

@David I thought the +2 are hydroxyproline and hydroxylysine but they are not considered proteinogenic because they are result due to PTM.

No. There are a host of post-translational modifications of amino acids. Those two are the ones coded by stop codons in certain contexts and — especially selenocysteine — have been well characterised, as you mention.


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Gradual slowing breath, its effect on health
I've written a computer program which beeps, then beeps after 10 sec, then beeps after 11 sec, then beeps after 12 sec, etc.
I tried the following "experiment" on myself: do only one breath between the beeps, so slowing breath until I can't do it.
After finishing this "training" and starting to breath normally again, I felt enormous "freshness".
Is this experiment safe for health? How does it influence health?

Whether or not it is safe is a discussion perhaps best to have with your doctor - personal health will determine the safety of this, and it will also depend on how far you push yourself, obviously at some point your program will be beeping once a week... As for health effects we could speculate - perhaps it is similar to some meditation techniques - but this is a very unusual small experiment.

@rg255 It would get to the "once a week" stage after more than 5,000 years.

You can try as much to slow down your breathing but the body will speed it up if it requires. What you've probably done is relaxed and just basically meditated. It's not the breathing but the relaxing yourself to slow your breathing and the focus which has refreshed you. I say conduct some experiments, like listen to calming music and relax and don't monitor your breathing and see if you feel the same.
//updating answer
Slowing your breathing builds up the carbon dioxide in your body. This is bad for the body so it forces you to breathe. In fact our breathing is seriously tightly controlled so that our body tightly controls the carbon dioxide (or more correctly the pH) in our blood. There are some groups of patients in which permanent slow breathing exists. In these people their carbon dioxide climbs and the kidneys have to compensate.


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Why does air from the nasal cavity not go into the oesophagus?
When we ingest food, the epiglottis covers the trachea and the uvula covers the nasal passage. But what happens when we breathe? Why does the air go into our trachea and not the oesophagus?

Swallowing food requires muscle strength to force the food down the oesophagus, which is a soft tube that collapses when empty, simply because the body is very crowded (space-efficient) and empty spaces collapse unless forced open. Only when you swallow, the oesophageal muscles force space to be made for food coming through.
In contrast, the trachea and bronchi are covered in almost-circular or C-shaped cartilage which holds them open and stable for air to flow through. You can see it here: http://en.wikipedia.org/wiki/Bronchi.
Concluding, air does not enter the oesophagus because it is always closed. Additionally, when the chest expands for breathing, the lungs expand and create suction down the trachea and not into the stomach (simply because this is where they connect).
The exception of course is if air is trapped in the swallowing motion with (or without) food. In this case it will enter the oesophagus and cause you to burp.


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What does probe number and segmentation mean in copy number variation (CNV) data
In TCGA Copy number variation (CNV) data there is a column with title Num_Probes. What is the meaning of probe number with respect to the sample data below?
Chromosome  Start   End Num_Probes  Segment_Mean
1   61735   62152   4   1.1973
1   62920   12777697    6514    2.2882

According to wikipedia, probes are usually 100-1000 bases long. Then does it mean in the first row above that, it took 4 probes to identify the region(61735 - 62152). In that case what would be the meaning of Segment_Mean?

The data you posted looks like it was produced by GISTIC, a program commonly used by TCGA to detect copy number changes. Assuming the data really is GISTIC-produced, my understanding is that "Segment_Mean" refers to the average Log2 Ratio of the probes in that particular segment. Looks like the copy-number of your 4-probe segment in your example is slightly less than half the copy-number of the longer segment.
You can also try using the GISTIC Google-Group to learn more.

If a a sample has a CNV gain at 12792599 - 13278863 with probe no 100 and segmentation mean 0.4 and if another sample also has a CNV gain at the same position 12792599 - 13278863 with probe no 200 and segmentation mean 0.5, does this mean 2nd CNV region is more important than 1st CNV region? I don't understand the importance of segmentation here.

Simplistic Answer: higher segment mean == higher copy number. The number for probes for each region probably doesn't matter. Also, a difference of 0.1 between each regions' segment mean probably doesn't matter much either.


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How do DNA, enzymes, hormones etc. reach their proper cellular locations?
I was trying to understand DNA transcription from this chapter, and there seems to be no explanation on how exactly the proteins, enzymes and other molecules manage to find each other inside the cell. How do they get attracted to each other in order to start reactions or transcriptions?
Same way, when the body secretes a Follicle Stimulating Hormone, how does it reach the follicle instead of losing its way in the bloodstream and ending up in a woman's feet or getting excreted out of the body? In minute 20 of this video, the person speaks of how medicines are first "sent" to the liver, but this MIT article says that medicines go all over the body.
At least for a wound it's an understandable process. An artery of vein is severed and any blood that was supposed to flow through it now can't, so there's an accumulation of white blood cells and antibodies there which can disable any intruders (though I'm sure they wouldn't be able to see an intruder and move toward it, but rather just probabilistically bump onto the intruder), and if the intruder enters the bloodstream it would probabilistically bump into other WBC's or antibodies and get killed. Else there's always fever to kill them.
Similarly, one study says sperm use heat sensors to find the egg. Another assumes it's a chemical signal.
I went through the information about cell signalling, signal transduction and allosteric regulation, but although they speak about receptors, they don't explain how the chemicals manage to find those receptors. It's like saying that I entered a huge college campus and found the secret place where my friends were meeting and they receive me when I met them, but there's no explanation on how I knew which way to travel in that huge campus to reach my friends. Given how accurately DNA transcription happens and how viruses know to shed their shell on entering a cell and make use of the cell's transcription mechanism, I believe there has to be a specific process through which these molecules "know" how to find these receptors. Is there any research that could throw light on it?

Just as I have removed "know" from your title, you should remove all anthropormorphic references from the interpretation of the sources you read — if you read popular science you will unfortunately find non-scientific expressions. So replace "finds" by "reaches", "is sent" by "is released". For the rest, the answers discuss whether after release a molecule reaches its target by diffusion or specific transport etc. But you need to trim your question which is far too widely drawn, accept your ignorance and see what answers you get before deciding that it's magic.

The answer given by Sadegh gives a general correct broad view. But one part of the puzzle is missing, which is molecular recognition.
Molecules bind to each other via physical/chemical interaction like forming hydrogen bonds, electrostatic interactions and other mechanisms. The sum of all interaction defines the strength of the binding. If molecules have enough interactions, they stick together otherwise not.
Mind that all these interactions have a range of action (a field). Like with magnets, two opposite magnetic poles attract each other at a distance, before they get in contact. Imagine a small molecule getting close to a receptor, if they are "magnetically" compatible they will be attracted toward each other.
Indeed, molecules in the bloodstream (like the Follicle Stimulating Hormone) flow all around the body. However, not all the molecules end up in all the cells. That is because cells have specific receptors on the surface that bind selectively their target. In the case of the Follicle Stimulating Hormone, some cells, like the Sertoli cells or the granulosa cells have the right receptor able to bind that specific hormone.
In the case of a drug targeting the liver, the drug gets assimilated or injected into the bloodstream, it travels all around the body but it is retained by specific molecular interactions only (mostly) in the liver. It is not that the drug knows where the liver is, it is just forced to pass through it and then it is retained by it. The drug passes also through the lungs, but it has no affinity for them so it doesn't get retained.
Inside the cells, it occurs the same. Molecules pass all around, but they do not stick to anything unless a specific protein/receptor/enzyme is found.
There is an intricate network of interactions both inside and outside the cells, molecules randomly flow throughout this network bouncing on each other until they find the binding partner and they stick to it.
Randomness is not the only factor. Brownian motion occurs, but molecules are also actively moved by different chemo/physical stimuli causing the network of interactions to be in fact extensively regulated.
For example, during the cell cycle, the cytoskeleton is actively remodeled to favor the flow of certain molecules in determinate directions (look metaphase). The cell can also alter its own permeability, actively influencing the influx/efflux of a variety of molecules.
At the body level, the circulatory system itself forces the flow in a specific direction (from the stomach to the liver for example).
The fact is, that there are mechanisms to selectively control the flow of the molecules at any level in the body, from organs to tissues, to single cells and inside subcompartments of the cells. The topic is complex but very well understood.
I suggest a big dive into this book if you really want to get a grasp on how biological systems work.
UPDATE: As suggested by @WYSIWYG, the picture would be more complete adding a very short note (the topic is way to broad to be extensively discussed here) on chemokines which are a perfect example on how cells can respond to concentration gradients. Chemokines act as a chemoattractant to guide the migration of cells. Cells can sense the concentrations of chemokines in the surrounding environment and, usually, move toward the source of the signal following the increasing concentrations of the signal molecule. In general, it cannot be overstated the importance of chemical gradients during embryogenesis, inflammation and countless other events. Gradients effectively indicate to cells the path to follow.

Perhaps you can also add a note on chemokines.

Yes, good point. I should add something about concentration and diffusion as well. I will add it as soon I have time.

It's both simple and complex. The simple answer is Brownian motion. All the particles in the cell do have mobility which is related to their mass. A small particle like a soluble enzyme undergoes random walks through the cytoplasm or nucleoplasm. Thus by having a grand number of a certain molecule you can be sure that at some point it interacts with the right target. Besides that, cells have solutions for increasing the chances of interactions by creating local concentrations of the factors in metabolic or signal transduction pathways. Look at this.
Larger Particles like vesicles are transported through cytoskeleton and motor proteins. The main reason that prokaryotes have had limitations in growing their size is lacking such a system and depending on diffusion and Brownian motion to relocate molecules.
About the complex side of the story! One might ask how some random and stochastic behaviors of molecules lead to these definitive and precise actions in the cell. You can Google up "Stochastic in cell biology" or look at this book.

Hmm...I'd take stochasticity as a theory, but maintain that there should be an alternate theory too. When I learnt of Prions, I felt there has to be another explanation to how decisions were taken to create scaffolding proteins, cytoskeleton etc. There seems to be an intelligence to it. Couldn't just be randomness.

This is definitely part of it, and indeed, I think it's an underappreciated part from the perspective of a novice, but there are also molecules that are trafficked on the cytoskeleton, which is especially important in cells like neurons that can have extremely long processes relative to the rate of diffusion.

Shortly, understanding a process called molecular recognition (as stated by @alec_djinn) under crude biological environment would answer all your questions.
Before explaining answers for your questions, to understand biochemical aspects of Transcription better, I would highly recommend to read a textbook written by Lubert Stryer.

Proteins including enzymes basically work by very specific non-covalent interactions.They do so because these interactions are reversible.(For example,  after one transcription cycle is over, same guy can work again and again). The inside situation at transcription site is complex as many biomolecules work in a complex coordinated manner and follow the rules of thermodynamics.The proteins have a 3 dimensional structure whose active site channel can only accomodate specific substrate molecule say DNA. (Think about a lock and key).This complementarity in-turn is achieved by complementarity in Shape, number/type of non-covalent interactions it can have, free energy considerations etc.
Indeed, the drug goes all over the body. However, the specific drugs contain a chemical motif which gets only recognized by specific receptors through molecular recognition.The new drug delivery systems also make use of a phenomenon called EPR effect (enhanced permeability and retention effect).The drug which is more specific towards the target and which has more retention time in the blood is more effectively acts upon the target and others eventually excreted out through renal system.

So coming back to molecular recognition, let's take the same example you have given. Think when you entered your huge college campus you specifically get attracted towards certain girls (Imagining you are a boy) but not for all. Because those girls are in a way as your mind likes. This can be compared with large class of enzymes like peptidase which break peptide bonds.Some may break between Alanine and Glycine and some may not (as you like girls).Some other may like to break between Tyrosine and Proline.That is because those enzymes have evolved in such a way that they perfectly fit in there.Continuing, now you want to find your girlfriend. This case is more specific.Its not bunch of girls. Its only one.What will you do? You will send a message/call out loud!.Similarly, biomolecules send a message through chemical signals/secretions etc.
About sperms and eggs I know they attract through chemical signals and thermal gradient.I cannot comment much about it.
Ofcourse, all these mechanisms have been proved by researches either by direct or indirect method.Modern techniques such as Fluorescence microscopy has tremendously helped us to understand the finest things of life in its native conditions.Because seeing is believing!

Thanks. This is a nice answer, but it'd have helped more if there was a mention of how these molecules learnt to locate and move toward each other. Other answers say it's just randomness (and it probably is), but when I go to a restaurant when hungry, it's not because I'm attracted to it and the restaurant has doors (receptors). It's because I know that I can get food at the restaurant. How do these molecules "know"? How do the organs that secrete these molecules "know" that the molecule could eventually reach it's target? There seems to be some kind of actual research these cells do.


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Bacteria and semi-permeable membranes
"The knowledge about semi-permeable membranes is applied for various purposes. We know that semi-permeable membrane is capable of separating substances when a driving force is applied across it. Artificially synthesized semi-permeable membranes are used for separation of bacteria from viruses, because bacteria cannot cross a semi-permeable membrane."
My Question is Why Bacteria cannot cross a semi-permeable membrane? Reason?

In my opinion, it should work by size exclusion. Bacteria are on the size of few microns, whereas the pores in semi-permeable membranes are on the size of nanometers. Therefore, bacteria will not pass through the membrane.
Viruses are usually smaller than bacteria, and so maybe more likely to pass through such a membrane. However, you have not included the pore size of the semipermeable membrane in question, and so I am unable to give a more specific answer at this point. If the pores of the membrane are very small, even viruses will not be able to pass through it.

Please add some references.

A semipermeable membrane is like a sieve. It has pores on the surfaces and tunnels that connect them. Molecules may pass through depending on their size. The pores in semipermeable membranes may be highly elliptical and the shape of molecules branched and complex rather than spherical.
However, the pore size (for example in the Polyflux 210H commonly used in hemodialysis) is 34 and 45 nm. There are spherical bacteria but often not and their size is usually greater than 0.5 micro meters. That is more than 10 times the size of pore in a Polyflux 210H semipermeable membrane.
Some viruses however are 20nm and may pass through though typically viruses are in the 100nm range.
Here is a paper on the morphology of the 210H with SEM images.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3502870/


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If fever is a natural immune defense, why do people take drugs to lower it?
If fever is a natural defense against pathogens, why do sick people take NSAIDs to reduce the fever?

Personal comfort is the primary answer. Quite a bit of research has gone into fevers, and the current consensus is that Fevers less than 105F (40.5C) shouldn't necessarily be treated.
The primary reason the body raises its temperature (via the Hypothalamus in this case) is that bacteria and viruses tend to optimally thrive at 98.6F, which is also your body's optimal operating temperature. By raising the body's temperature, the bacteria/viruses become less efficient, allowing your body to "catch up" since the body's immune response takes time to ramp up before it reaches its peak (which is a bit after peak viral/bacterial load). Here's an example for Hepatitis (HBxAg = the virus, Anti-HBx = antibodies against the virus):

Along with the Fever, joint inflammation (part of the Innate Immune system's primary response) is also a coinciding symptom. So when your body begins to fight an infection you get a fever (which can make the environment uncomfortably hot/cold) and the tissues around your joints swell (which makes movement and relaxation uncomfortable). NSAIDs like Ibuprofen reduce those symptoms, making the duration of the infection more bearable. They do not reduce the length of the infection by any measure (and might increase it, though the research is not particularly conclusive), but can make the day go by better if you've used up all your sick days or have a child to take care of.
Basically, people take NSAIDs to reduce fevers for the same reason most take any over-the-counter pain medications. To make life a little easier in the meantime.


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Length differences between physically interacting proteins
What can be said on the length differences between interacting proteins? Are they usually of similar sequence lengths or not at all?

What do you mean by length difference? Interacting proteins which are different in size? And why should this be a problem? Additionally: Proteins fold into a 3D structure, which is much more important for protein-protein interactions than the size.

Each protein has a sequence. Sequences have lengths (amount of amino acids). Some proteins interact by forming physical bonds to each other. I'm asking if something can be said about size differences between interaction proteins. E.g. - usually very small proteins would not connect with each other, but only with a bigger protein.
This is not "a problem". I'm simply wondering because I want to understand what would be a good descriptor for proteins when trying to model physical interactions.

I think that if you did an analysis of this it would be dominated by interactions involving the same protein (dimers, trimers). Apart from that I know of no bias towards similar sizes.

@Uri it seems like you mean to ask about 3D size rather than sequence length, is that correct? In other words, you are using sequence length as a proxy for some 3D size property.

No, I'm asking about sequence length.

This is just a gut feeling, but I would assume that sequence length is largely independent. In very large proteins, usually it is only one domain that interacts with a given binding partner. That domain can be a tiny fraction of the size of the protein. Eg. Nup358, a 358 kDa protein that has multiple domains that independently interact with Ran, a 25 kDa protein.

Just for reference, here's a question that actually asks about size: http://biology.stackexchange.com/questions/2965/what-role-does-a-proteins-size-have-on-protein-protein-interactions?

At least in a human protein interaction network, it appears that proteins indeed mostly bind to proteins of similar sequence length. Consider the figure below, based on analysis of a human protein interaction network from the Protein Interaction Network Analysis (PINA) platform. In the data set, the median relative protein size (the largest amino acid sequence length divided by the smallest in each interacting pair) was 1.9, the maximum value was 293.6 and the 99th percentile, which is the cutoff for the plot, was at 15.2.

Edit: As per stords comment below, you get essentially the same result for a random network:
In this case, the network was generated by picking two proteins at random from the original network, creating an interaction between them, and repeating until the random network has the same number of interactions as the original.
Immediately, it might look like the PINA PIN is dominated by random interactions. I would run some network analysis to determine its characteristics, but seeing as it's a rather large network it would take more time than I have right now. The results are similar for two additional networks with interactions in Saccharomyces cerevisiae and Caenorhabditis elegans respectively downloaded from PINA. Note that all three networks have been constructed from databases with varying levels of curation (See the original publication for PINA:  http://www.nature.com/nmeth/journal/v6/n1/full/nmeth.1282.html). As such, many of the interactions might not be biologically meaningful.
Taking into account the above, you might want to define "interacting proteins" more precisely. One might expect that a better curated network only containing interactions with a known function or effect might give a different picture. However, using a more strigently constructed human "functional interaction" network published by Wu et al. (http://genomebiology.com/content/11/5/R53, FIs_043009.txt in Additional file #3) still gave a similar result.
Method: I made a Python script to calculate the relative amino acid sequence lengths for all interactions in a human protein-protein interaction network (PIN) available from PINA ((http://cbg.garvan.unsw.edu.au/pina/interactome.stat.do). The network file is located at: http://cbg.garvan.unsw.edu.au/pina/download/Homo%20sapiens-20121210.sif. PINs for other organisms are also available at the same site and many other places. The script can be used with any PIN in SIF format using UniProt identifiers.
The script can be downloaded here: https://github.com/jarlemag/misc-bioinformatics/blob/master/ProteinInteractionNetwork.py
The most time-consuming part was downloading the sequence lengths from UniProt. To avoid having to do that, the protein sequence lengths can be saved to and loaded from a text file.  The list of protein sequence lengths is here: https://github.com/jarlemag/misc-bioinformatics/blob/master/protlengths.txt To create the figure, place all three files in the same directory and run the script using Python 2.7.
Keep in mind that the PIN data may not be entirely reliable.

Did you in any way correct for the natural distribution of protein sizes? There are many fewer large proteins than small proteins, so just by random interactions I could imagine a plot like this.

No, I took a very simple approach - suggestions for improvement are certainly appreciated. How would you do that, specifically?

I'm not very good at statistics, so take my advice with a grain of salt, but what I would do is simulate this kind of plot, but just use random interactions between proteins  in your dataset rather than using known interactions. If the random plot looks the same, then the effect is likely due to the natural length distribution. If the random plot looks different, then the effect is likely real. Its qualitative, and I'm sure that there is a better way, but its quick and would be informative, I think.

Seems like you might be right. I've updated my answer.

On the topic of PIN quality, the following articles may be of interest: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2683745/, http://www.nature.com/nmeth/journal/v6/n12/full/nmeth1209-934.html


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Do mantises stalk cicadas?
The Chinese Idiom The mantis stalks the cicada, unaware of the oriole behind (螳螂捕蝉，黄雀在后), which the story behind the idiom comes from Shuo Yuan(说苑), refers to those who are attracted by immediate interests without thinking about the possible dangerous results.
In reality, do mantises stalk cicada? Moreover, are cicadas stalked by birds?

Yes, mantises hunt cicadas...

Mantis eating cicada. Source: Dreamstime.
...and yes, orioles hunt cicadas too...

Oriole eating cicada. Source: Bird Ecology Study Group.
.., and what may be more relevant to your idiom: orioles prey on mantises.

Oriole eating mantis. Source: Sustainable Adventure.


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The biggest underground living animal
It's easy to find information about the biggest animals at land / at sea / in the air. But what was the biggest underground-living animal that ever existed?

No animals that were forced to live underground (e.g. pit ponies)
The animal should live at least 95% of its life under the earth (e.g. foxes)

There are two possible answers:

By length
By mass

My first guess was a mole

Okay, maybe not 95% of the time, but as you put ever existed, I would throw the cave bear's hat into the ring. https://en.wikipedia.org/wiki/Cave_bear.

cave bear are not primarily cave dwelling, their fossils are found there, just like "cavemen"

Graboids!   .........But seriously are you just looking at terrestrial burrowers, if not moray eels might be a contender.

Microchaetus rappi
Microchaetus rappi, the African giant earthworm, is a large earthworm in the Microchaetidae family, the largest of the segmented worms (commonly called earthworms). It averages about 1.36 m (4.5 ft) in length, but can reach a length of as much as 6.7 m (22 ft) and can weigh over 1.5 kg (3.3 lb).(https://en.wikipedia.org/wiki/Microchaetus_rappi)
Giant Gippsland earthworm
These giant earthworms average 1 metre (3.3 ft) long and 2 centimetres (0.79 in) in diameter and can reach 3 metres (9.8 ft) in length; however, their body is able to expand and contract making them appear much larger. On average they weigh about 200 grams (0.44 lb). They have a dark purple head and a blue-grey body, and about 300 to 400 body segments.(https://en.wikipedia.org/wiki/Giant_Gippsland_earthworm)

I think you got the record! +1 It'll be hard to find any bigger without going with the kind of far-fetch example I gave.

Key Words:
To aid in your search, you might want to try searching the term "Fossorial."

Fossorial animals are animals that are adapted to digging and life underground.

Though note: Lessa et al (2008) use fossorial to describe species that spend a substantial fraction of their lives outside their burrows, while they use subterranean to describe species that perform most activities underground.

You might also want to examine a list of troglobites.

Troglobites are animals that live entirely in the dark parts of caves.

Big Species
I think large specimens of @JayCkat's suggested species (Microchaetus rappi) will be tough to "beat", with large specimens reaching 6.7 m and 1.5 kg.
However, here's a list of other species anyways:
Some extant large species of fossorial animals:

Cape dune mole-rat (Bathyergus suillus): 27-35 cm (up to 39cm including tail); 570-1350 g

Supposedly, some blesmols can reach a weight of 1800 g.

Russian Desman (Desmana moschata): 18-21 cm (up to 41 cm including the tail); 400-520 g
Giant Armadillo (Priodontes maximus): up to 1.5 m; up to 50 kg

It spends all day in underground burrows though it hunts above ground at night.

Olm (Proteus anguinus): up to 40 cm long.

 Cape dune mole-rat

 Giant Armadillo

The only info I could find via a quick search for prehistoric fossorial animals:

A series of 240 million year old underground tunnels/chambers suggest some burrowing species lived there. [Source: Seeker].

"You should imagine the tracemaker as a stout, short-bodied, four-legged animal with a short tail and short neck...The trunk was about 20-25 centimeters (8-10 inches) in length.

Bonus:
How about the deepest living animal?

That award goes to the "Devil Worm" (Halicephalobus mephisto), a nematode that has been found living at 3.6 km below the surface!! ...(tied w/ Plectus aquatilis).

Though at 0.5 mm, it's definitely not winning the largest trophy :p.

 Citations:
- Lessa, E. P., Vassallo, A. I., Verzi, D. H., & Mora, M. S. (2008). Evolution of morphological adaptations for digging in living and extinct ctenomyid and octodontid rodents. Biological Journal of the Linnean Society, 95(2), 267-283.

@TheWho oops, you already listed the Russian Desman. you'd think I would have noticed the 2 year old post! :p.

I don't know if there is a bigger animal, but the biggest mole is the Russian desman with 400-520g and a length of
18-21 cm (35-41cm including the tail)

If you accept far-fetched argument, I've got an individual that weight more than a ton! But let's start with a simple example of a large troglodyte.
Blind cave eel
The blind cave eel (Ophisternon candidum) is a troglodite. It is a pure white fish growing to 40 cm, with an eel-like body, no eyes, and a thin rayless membrane around the tip of the tail. I could not find its weight but it probably does not weight much! Just like many troglodite species, its distribution range is very restricted. It only occurs in a single location in Western Australia.

Fungus
Well a fungus is not an animal (but is closely related), so it does not answer your question but I still wanted to mention it. There's an individual fungus that covers 965 hectares. See this popular article.
Ant supercolonial individual
The individual ant is of course not that big but it is not uncommon to consider a colony as a superorganism. You might want to have a look at major transitions in evolution: revisited for a discussion about the concept of individual for social species. Note also that most ant casts spend most of their time underground in the nest.
From wikipedia

Until 2000, the largest known ant supercolony was on the Ishikari coast of Hokkaidō, Japan. The colony was estimated to contain 306 million worker ants and one million queen ants living in 45,000 nests interconnected by underground passages over an area of 2.7 km2 (670 acres). In 2000, an enormous supercolony of Argentine ants was found in Southern Europe (report published in 2002). Of 33 ant populations tested along the 6,004-kilometre (3,731 mi) stretch along the Mediterranean and Atlantic coasts in Southern Europe, 30 belonged to one supercolony with estimated millions of nests and billions of workers, interspersed with three populations of another supercolony. The researchers claim that this case of unicoloniality cannot be explained by loss of their genetic diversity due to the genetic bottleneck of the imported ants.[citation needed] In 2009, it was demonstrated that the largest Japanese, Californian and European Argentine ant supercolonies were in fact part of a single global "megacolony".

Considering a weight of 3.5 mg per individual, a colony of 306 millions ant weight more than a ton (1071 kg exactly) and of course this excludes their constructed habitat which could arguably be considered as part of the individual.

"most ants spend their time underground in the nest" Do you mean they spend most of their time underground, but 95%?

@Rodrigo Depending on the cast, some ants spend a fair amount of time outside the colony. I don't know exactly what fraction of the time of foragers are spent outside and I would suspect it would varies from species to species. So I used a safe phrasing. I edited "most ants" to "most ant casts"

Can badgers qualify? They shelter underground and get a significant proportion of their food underground as well, I don't know if they stay there 95% of the time though. Wikipedia gives them as going up to 17kg and 90cm in length.
I thought a snake might get the record for length but there don't seem to be many burrowing snakes and they seem to be small. Given the sizes of other non-mammalian tetrapods and how few of them are burrowers whichever the largest underground animal is may well be a mammal.

Why probably a tetrapod?

@Rodrigo Because I didn't think worms got as long JayCkat revealed! Land invertebrates are by and large much smaller than land vertebrates, with even the biggest land invertebrates being only as large as rather small land vertebrates, so I assumed they weren't in the running.


text:
Does the new virus tree of life change their position between living and non-living things?
Viruses still do not fit the criteria of living or it's simplest form (the living cell), why would some say that the new virus tree of life makes it more closer to life? Aren't mitochondria in a point of view closer to life than viruses?

You will probably want to have a look at why-are-viruses-considered-microbes and why-isnt-a-virus-alive.

The definition of life is a question of philosophy
The definition of life is a question of philosophy and not of biology. However, because discussing it often require some knowledge of biology and because it is so common for the general public to misunderstand that the definition of life is not of biological interest, the question has already been addressed on this biology.SE. Please have a look at:
why-are-viruses-considered-microbes and why-isnt-a-virus-alive.
Why would the tree of viruses affect our definition of life?
It is impossible to say much without a link to the original claim. I will need to speculate on what the authors of this claim first meant.
A tree of viruses gives a visual representation of a feature that we tend to associate to living things only, that is they evolve and speciate. Of course, we did not need to build a tree of viruses to understand that they evolve and speciate but a visual representation can sometimes offer an emotional response that will push some to prefer considering viruses as living things. In consequences, it is possible that the vision of this tree affect the emotional aspect of what we define as "living things" and might push the community to expand their standard definition to include viruses. Again, it is important to understand that the definition of life really has absolutely no impact on Biology.


text:
How does a protein reach its substrate within the cell?
After a protein has been synthesized and its the final tertiary/quartenary adopted, how does it reach its substrate within the cell and what causes it to interact with it?
The transcription factors for a particular gene are proteins which are translated from genes on some other portion of the DNA. (That happens in the cytoplasm) But how do the transcription factors know that it has to diffuse into DNA region of the nucleus.

proteins as well as other small molecules like pharmaceuticals and steroid hormones all bind with specificity for particular targets within the cell - this specificity is what makes the protein seem like it wants to seek out its target - I'm sure there are more chemical-minded individuals that can give you a good explanation about binding energy and exergonic reactions, etc - good quesetion

A protein doesn't "know" anything, just like gravity doesn't "know" anything. There are all kinds of proteins as well; there are cell receptors, carrier proteins, cytoplasmic enzymes, structural proteins, etc. Are you specifically asking about enzymes and substrates? Or generally how do proteins "know" what to do?

As a side note, we don't know anything as per the Central Dogma.  The Central Dogma was a model, not a set of observations, not even a hypothesis; it was deliberately named to be provocative, and was overthrown pretty quickly.  It's a mere footnote to history, not an important biological concept. Unfortunately, there seem to be a group of teachers -- mainly in India -- who don't understand this, who force it onto students, and who put it on exams, leading to widespread misunderstanding.

The protein doesn't move towards anything. It just randomly diffuses (bounces around) in the cell until it sticks to something. The particular chemical structure (the shape) of the protein and whatever it hits will determine how tightly they stick together and whether or not a chemical reaction occurs.
A way to imagine this is to think of a jar filled with a lot of glass marbles (water), 1 marble shaped magnet (the protein), and 1 metal marble (the substrate). Put the magnet at the bottom, fill the jar most of the way full with glass marbles, and then put the metal marble on top. Then close the jar and shake it. Eventually, after colliding with a lot of glass marbles, the magnet and the metal marble will collide and stick to each other. That's how it works in cells also. In cells, the speed at which the molecules move is proportional to temperature.
Here's a cool video that shows how proteins with a very specific shape bouncing around randomly can assemble into a complex structure.
To get a sense of just how quickly molecules move in a cell, think of a bacterial cell. An E. coli cell is about 1 micrometer in diameter. In a cell of that size with no sub-cellular compartments, every molecule will collide with every other molecule in the cell about once every second (if we make some assumptions such as no binding to other molecules). So if the cell contains just one unit of a certain enzyme, and just one molecule of its substrate, they will still collide fairly frequently (about once every second).
This rate decreases dramatically as radius of the cell increases. For example a cell with double the diameter (2 micrometers) has a volume eight times larger, so collisions between any two molecules take 8 times ($2^3$) as long to occur (in other words, it takes molecules 8 times longer to "find" each other). This is one reason why there is a kind of upper limit on the size of an individual cell. Bigger organisms are bigger because they have more cells, not because they have larger cells.
The field of biology concerned with how likely it is for a reaction to occur is called enzyme kinetics. A related field, which deals with how frequently molecules collide is called statistical mechanics.

It just randomly diffuses in the cell until it sticks to something. This isn't entirely accurate. The secretory system can deliver proteins to specific parts of the cell and then some are embedded in the membrane whilst others have signal peptides which can be cleaved off, releasing the protein into the local vicinity. Motor proteins are even involved in the final stages of this, making it a particularly directed process. Furthermore, could you provide a reference supporting that as a reason for the upper limit of cell size?

You're right of course. I should have stipulated that this applies best to soluble, cytosolic proteins.
I would argue however, that what you're describing with secretory processes, is just a special case of diffusing around randomly until it sticks to something. In the case of secretory pathways it's just that there's a cascade, where once it interacts (sticks) to the first other protein in the cascade, it forms a complex that interacts differently than any of the two precursor proteins. And so on as the cascade hits different steps. It's just a bunch of molecules randomly bouncing around.

As far as a reference for cell size. I think I heard that in a class or read it in a text book a long time ago. Quickly looking around the Internet, I found a reference that is sort of sufficient (it doesn't account for eukaryotic cells, just bacteria). Here's that.

@SeanJohnson I understand your implications of statistical mechanics to chemical interactions inside the cell in order to reach a binding affinity that is sufficient to keep the molecules together. But as I had mentioned about transcription factors in my question, I am not able to correlate it exactly. The transcription factors' activity is within the nucleus. In that case how would it travel inside through the nuclear membrane? I am unable to understand how would it be a random interaction if it has to specifically penetrate the membrane to reach its target.

So your question is more about how proteins in eukaryotic cells enter various sub-cellular compartments? Or is it more about what distinguishes the outer membranes of different compartments?
Check out the Wikipedia article about "nuclear pores"

@James The collision propensity is proportional to concentration. And concentration decreases with increasing volume if the number of reacting molecules are constant.

Thanks both of you @SeanJohnson. I sort of get what you are trying to say. I will read about your reference for better clarity.

@Synaptic_Pik There are many more factors that affect the activity of transcription factors. There are phenomena like macromolecular crowding and chromatin organization that play a significant role. If that is your specific question then you can ask it separately along with all necessary details.


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Problems in optimisation with applications to biology?
I will soon have around 8 weeks to do a research project of my choosing  as I am finishing my undergrad in computer science.
My experience is mostly in optimisation algorithms (mostly combinatorial/discrete optimisation).
I have an interest in applying computer science to biology (mostly human biology).
I would like to ask if anyone knows optimisation problems with applications to biology which would benefit current research.
Although I have read a lot about biology in my free time, I am not too knowledgeable about the current state of the research and so it is a bit hard for me to find a good topic.
Some examples to spark the discussion are string problems in genetics (alignment problems), and community detection in graphs (to find proteins in the same functional group).
Thank you!

Optimization algorithms have lot of scope in computational biology. 'Almost' all parameter fitting requires one or another of such algorithms. I would say look into some computational biology, bioinformatics journals, you will find tons of examples.

Optimization is ubiquitous in all sciences and engineering, and biology is no exception. Many statistical models in neuroscience require optimization for example (my area).

It is probably worth picking one such algorithm and make an answer out of it.

Note that genetic algorithms are a type of optimisation algorithm that is inspired from evolutionary biology. Some people used the knowledge the computer scientist have acquired in studying these algorithms to understand evolutionary biology. For example, questions such as "What fraction of the space of possibilities is explored before reaching an optima?" can be of interest.

Depends on your area of expertise --- continuous / local optimization, or discrete, combinatorial problems? There are many discrete problems in next-generation sequencing applications and network (graph) models. Continuous optimization problems frequently arise in various statistical models (maximum likelihood fitting to data). Optimization is a large field, so would be helpful if you can be more specific as to your area of interest.

I think that either @Resonating answer is satisfying or the question is too broad.

@Roland I editted the question. Discrete/combinatorial optimisation is my focus in general

Maximum likelihood phylogenetic trees. The trees are easily scored but the tree space is so large that finding optimal phylogenetic trees is extremely difficult. There's some research but there haven't been very many actual breakthroughs, so it's probably a pretty rich field.

Well I guess this is a nice example! There's tons of papers on the subject. Here is one and another one.

Here are some examples:

Sequence (DNA, protein) alignment. With the development of next-generation sequencing methods, this is an important and active field.
Genome distance calculation by genome rearrangements
The phasing problem for single nucleotide polymorphism data (determining haplotypes)
Factor blocking problems in statistical experiment design
Network (graph) analysis. Many biological data sets can be expressed as networks, for example pairwise protein interactions, which give rise to a variety of discrete problems, like finding maximum connected subgraphs, graph flow problems, etc.
Biclustering of data matrices, notably gene expression data
Inference on phylogenetic trees was already mentioned.

I'm sure there are many more, this is just off the top of my head. Happy googling! :)


text:
Can anyone identify this tall vine that has volunteered in our back yard?
What is this 5-foot tall vine in Kentucky? It volunteered in our back yard.

The species with the dark triangular leaves is also a vine - I reckon you are aiming at the plant with the lighter rounded leaves in the middle of the image? If yes, it's a bummer the leaves in close-up are out of focus.

@AliceD the dark triangular one is hedera helix.

Or are you aiming for the heart-shaped one on the top left? Perhaps you could provide a close-up image of a leaf and add an arrow in the existing figure to point out the species in question?

@AliceD: I'm sure they mean the plant most featured in the photo (having palmate leaf veining or patterning).  The leaves towards the bottom of the image are largely in focus.

@mgkrebbs — Is that generally used in the US or is it regional? Never heard it when I lived in Chicago and it is not British usage.

The term "volunteer" is used a lot here in Indiana USA, as in "It came up volunteer" to refer to a plant that just appeared.

@David https://en.wikipedia.org/wiki/Volunteer_(botany) - I admit myself I have never heard it as a verb in this context (though the wiki page does make reference to the verb form), but rather as an adjective or noun.

I believe it is in the genus Dioscorea which is a wild yam.  There are several species native to the Eastern US.  A common species is Dioscorea villosa but you will have to look up details and compare to your specimen.


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Is there a reason for the lack of full RTK structures?
Bocharov et al. (2013) write that

As there are no structures of full-length RTKs [receptor tyrosine kinases], we do not fully understand how different domains function together to mediate signal transduction inside the cell.

True to the above quote, I've so far only found isolated domains of some RTKs in the PDB, but no complete structures (neither X-ray nor NMR). I am a chemist by training, so am hardly an expert in this area, but it does seem counterintuitive given the general importance of RTKs in cell signalling. Is there a fundamental reason for the lack of RTK structures?
In contrast, there are examples of full-length GPCRs, e.g. rhodopsin (Palczewski et al. 2000). As tsttst brought up in the comments, this seems to be an issue with RTKs being single-pass membrane proteins, whereas GPCRs are multi-pass. How does this affect the ability to obtain a structure?

Bocharov EV, Lesovoy DM, Goncharuk SA, Goncharuk MV, Hristova K, Arseniev AS. 2013. Structure of FGFR3 transmembrane domain dimer: implications for signaling and human pathologies. Structure 21(11):2087–2093. doi: 10.1016/j.str.2013.08.026.
Palczewski K, Kumasaka T, Hori T, Behnke CA, Motoshima H, Fox BA, Le Trong I,  Teller DC, Okada T, Stenkamp RE, et al. 2000. Crystal structure of rhodopsin: a G protein-coupled receptor. Science 289(5480):739–745. doi: 10.1126/science.289.5480.739.

In the meantime there are some structures, e.g.: Chen et al., J Mol Bio, 2015, or Opatowsky et al., PNAS, 2014 (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4663128/, https://www.ncbi.nlm.nih.gov/pubmed/24449920)

Thank you, I don't know why I didn't try Google... Is there still a point in asking why full structures used to be so elusive?

One trick is to check the referring papers through google scholar, and one of them highlights the difficulty to crystallize single-pass transmembrane proteins (Valley et al. BBA, 2017, https://www.sciencedirect.com/science/article/pii/S0005273617300160#bb0475 ). Asking why single-pass transmembrane sections are difficult to crystallize compared to multi-pass might be a more general and answerable question (the answer would be described in Alberts' text book).

Large proteins are challenging for NMR: the more amino acids, the more peaks one has to assign. Peak overlap is also more likely the more amino acids you have, making assignment difficult. Some NMR strategies work well for studying dynamics of large proteins, but as far as structure determination is concerned, there definitely is a critical size past which NMR is simply not the tool for the job.
Flexible proteins are challenging for crystallography: too much flexibility can simply prevent crystallization, you can spend years only trying to get crystals, and once you do manage to grow crystals they might diffract poorly or not at all. But crystallography is often very useful to solve high-resolution structures of individual, isolated domains; this is of great help down the road to interpret a lower-resolution cryoEM map of the full-length protein.
Membrane proteins are challenging for biochemistry: purifying them and getting them to remain stable in solution is difficult.
Receptor Tyrosine Kinases (RTKs) are all of that at the same time! Large, flexible membrane proteins.
Now, with tremendous technological progress of cryo-electron microscopy (cryoEM) recently, such challenging structures become more tractable. Conformational flexibility is still an issue, but unlike with crystallography it can be dealt with to some extent (i.e. it won't prevent you from collecting initial data and getting preliminary results that can guide your next attempt).

Thank you! With regard to the issue about single-pass vs multi-pass membrane proteins that was brought up in the comments - are the former simply harder to crystallise due to greater inherent flexibility (which seems logical to me)?

I am not sure about that, but that could very well be the explanation. GPCRs have flexible loops between transmembrane helices, but these 7 helices are interacting with each other and that probably makes the whole less flexible.


text:
Can the human gut work with other type of gut bacteria?
I was wondering if the human body would be capable of functioning with, say, cellulolytic bacteria in their gut (instead of or in addition of their current bacteria), like that of ruminants and if they'd be able to digest cellulose thanks to it.
Couldn't find any papers on that, only on the implantation of faecal matter from a healthy gut to a sick one, nothing interspecific.

interspecies transfer of fecal material occurs often enough, but we usually study it in terms of pathogens and parasite life cycles. Interesting question. Probably tough to get IRB approval for that one, though.

@DanHall hahaha, bet. It'd definitely be interesting though! I'd like to hear the point of view of someone who's done human-human faecal transfers and what they think would happen!


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What is meant by `individuals do not evolve, populations do`?
My university professor stated that "individuals do not evolve, populations do". But aren't populations made up of individuals? That's like saying when a compound changes in stability, none of the elements' properties change. If someone could clear this up, that would be great.

If you pick pebbles of different colours, and then throw away all the light ones, is it the pebbles or your collection that have changed colour?

Populations are made up of individuals, but you have to remember that the individuals in the population now ("after the evolution happened") are different from the individuals in the population then ("before the evolution happened").

Or in simple terms evolution is an emergent characteristic, A single individual can no more evolve than a single number by itself can undergo addition or a single car can be called gridlock traffic.

The statement individuals do not evolve, populations do is rooted in the (classical population genetic) definition of evolution. Here is this definition:

Evolution is a change of allele frequency through time in a population

Evolution is defined for a population, it is not defined for an individual. And it makes intuitive sense once you get more used to how evolution works. For example, the so-called fundamental principle of natural selection states that at any given time, the rate of increase in the population mean fitness is exactly equal to the variance in fitness.
Indeed, evolution is all about phenotypic and genetic variance (for fitness or other phenotypic traits) and without a population to observe, there is no variance. It is within this framework that people say individuals do not evolve, populations do but you are correct that as populations evolve its constituents (the individuals) changes. The sentence has the advantage to reinforce the concept that evolution happens at the level of the population.

As an ecologist I would say that evolution is a bit more than the genetic definition of changes in allele frequency. It is the natural selection that occurs on these differences, were less adapted individuals produce less offspring on average. And in that sense, evolution does happen to individuals: they die or fail to reproduce. But the effect of the adaption occurs in the next generations, at the population level.

The sentence individuals do not evolve, populations do is more of a catchy phrase that force an intuition that a fact. By definition, NS is a fitness differential in the population. While the fitness are properties of individuals, fitness variation among individuals is a property of a population. Similar notion apply to any other evolutionary forces. If you do a tiny bit of modelling in evolutionary biology, you'll realize that you will always use population-level variables (variables that vary among individuals). It is with this in mind that the quote makes sense.

Evolution itself is a term that describes populations changing over time.
As Remi.b pointed out, if you take evolution to be genetic changes in a population over time, then it doesn't make sense for an individual to evolve. Evolution can only occur as genetic changes are inherited from parents to their offspring.
A given individual in a population can be subject to natural selection, but the individual itself cannot 'evolve' in the biological sense of the word. They can only contribute to the evolution of a population by affecting the allele frequencies in that population.
As an analogy,
The evolution of a population can be thought of as a motion picture of that population.
At any given moment, the genetic structure of a population can be thought of as a screenshot, and one person (or organism) can be thought of as a pixel.
Evolution is like watching a video of a population change through time.
So you might say:
"pixels do not play, videos do".

Actually, this does answer the question. If you think it's a bad answer, you can downvote it.

Evolution is about children differing from their parents. You are not identical to your parents.

Your cells' DNA does change (a little, through new random mutations from time to time, most of it being repaired but not always correctly), but incoherently through cells, and these mutations are not transmissible if they are not happening in your gametes (sex cells).
Non-lethal changes in your gametes are transmitted. Besides, errors in chromosome duplication is a way more efficient and fast way of evolving (mixing sentences makes sense more easily than mixing letters).

Downvoters, please justify.

I don't really see how your answer specifically answers the question. You talk a little bit about the mechanical origin of mutations but it does not quite relate to the core of the question. (I was not the one down voting btw but I kinda agree with the down vote).

because all the point is about :

many cells inheriting mutation of one single parent cell vs many cells mutating incoherently
mutation transmitted vs not transmitted
change by raw mutations vs change by replication error


text:
Does protein kinase A accelerate glycolysis or slow it down?
In liver cells, the activity of PFK-1 is regulated by the PFK-2/FBP-2 complex, whose activity is in turn controlled by glucagon and insulin.
Glucagon activates protein kinase A.  Then protein kinase A phosphorylates the PFK-2/FBP-2 complex, so that the PFK-2/FBP-2 complex will make fructose-6P from fructose-2,6-bisP.  Since fructose-2,6-bisP activates PFK-1 (in liver cells), without it the process of glycolysis will slow down.
However I read from my notes that protein kinase A is dependent on cAMP (so that when the energy level is low, the increase in cAMP will cause protein kinase A to increase in activity).  It seems that protein kinase A should help increase glycolysis, so why does activating it by glucagon cause glycolysis to slow down instead?

There is a fallacy in your argument, which is the parenthetical statement:

so that when energy level is low, the increase in cAMP will cause protein kinase A to increase in activity

The activity of adenyl cyclase (the enzyme catalysing the production oc cAMP) is not controlled by energy charge, but by hormones such as glucagon. That is how glucagon has its effect on protein kinase A (better thought of as cyclic AMP-dependent protein kinase to remind you of this fact). That is why cAMP is known as a ‘second messenger’ — the hormone being ‘first messenger’ (and the enzyme that becomes phosphorylated being the recipient of the message). See, for example, Figure 21.14 from Berg et al.
Therefore the explanation in the Wikipedia article on PFK2 is quite self-consistent:

When glucose level is low, glucagon is released into the bloodstream, triggering a cAMP signal cascade. In the liver Protein kinase A inactivates the PFK-2 domain of the bifunctional enzyme via phosphorylation, however this does not occur in skeletal muscle. The F-2,6-BPase domain is then activated which lowers fructose 2,6-bisphosphate (F-2,6-BP) levels. Because F-2,6-BP normally stimulates phosphofructokinase-1(PFK1), the decrease in its concentration leads to the inhibition of glycolysis and the stimulation of gluconeogenesis.[8]

So the answer to the question posed in your title is: in liver cAMP causes the inhibition of glycolysis.