text:
How many cells does a single blood cell generally visit in its lifespan?
Taking the point of view of a single RBC travelling through blood vessels, approximately how many cells will it affect throughout its lifetime? As blood tends to provide O2 as a whole, I am taking "affect" as being in the general oxygen transfer vicinity of a body cell.
Assuming that:

a RBC lives about ~120 days (source)
There are 60,000 miles of vessels in the avg adult human body (source)
There are ~5 trillion non-RBC type cells in the body that presumably need O2 (source)
Avg speed of 3 mph (source)
Blood cells are uniformly distributed, so any blood cell has the chance to be at any part of the body

So 120 days at 3 mph = 8640 miles travelled by a single blood cell. This represents 14.4% of the human bodies' vessels or about ~720 million cells affected by a single RBC.
Does this back of the envelope calculation make sense?

Not sure what you're trying to achieve here. Why wouldn't you take into account the probability of following the same path twice or more - and why are you concerned about a single blood cell when they act in concert? What's the objective of the calculation except to pass time.?

I have no problem with this kind of speculation; it's fun to wonder about the importance of a single tiny red blood cell, so kudos to you! My only objection is that it seems to presume to never follow the same path twice. Did you take into account that it must pass through the lungs every go round? Also, only about 80% of those miles are capillaries, where exchange is greatest. Anyway, I like this question, but it has no precise answer because of chance/randomness.

@ARogueAnt. - What's wrong with passing time wondering about a single red blood cell? It seems a decent use of time to me (given, an elderly biologist).

TL;DR: No. It's a fun little thought exercise, but unfortunately off the mark.* Most of my statements will be given, i.e. repeated numerous times in the medical literature as factual, though I can't say with certainty how they came to be so.
Assumption(?) #1 Assumption that the 60,000 miles of vasculature in the body all comprise of capillaries where exchange might take place.
Counterargument: In reality, only 80% (50,000 miles) is comprised of capillaries, where presumed "visits" take place. The rest is comprised of the heart itself, all arteries, arterioles, venules, and veins. There are (depending on how they are counted, not including the azygous system) about 30 major veins collecting blood from capillary beds; the larger they are, the more often they will be traversed by the blood cell, until they enter the superior or inferior vena cava on every return. The cell will see the same insides of the heart every go round. I don't want to do the math (I hate math) but (if) there are about 5 liters of blood in the circulatory system, and (if) the heart beats 100,000 times per day (average adult male, of course, just because), and (if) you know exactly how much of that volume is taken up by red blood cells, you can calculate how many times that one cell will visit the same heart every day (I think.)
Assumption(?) #2: Assumption that the red cell will never travel through the same vessel twice.
Counterargument: (See above for where it will travel for sure every day.) Your assumption(?) is based on equal probabilities encountered at every bifurcation in the arterial system, in other words, that every bifurcation in the vascular system is created such that the probability of going in either direction is equal. (Was that a tautology?) That isn't quite so. The probability of a red cell entering vessel A or vessle B (in the literature, described as daughter 1/d1 or daughter 2/d2) at a particular bifurcation varies with the diameters of a and b (with the larger diameter receiving more blood) and the angles of bifurcation (less important but still matters.) (This is just the mouth of one of those rabbit holes.) Randomness is not perfect at bifurcations, especially at the arteriolar level (active muscles will get more red cell visits than inactive muscles, etc.) This doesn't even take into consideration the effect of  endothelial damage (which causes drag in blood flow, thereby affecting the probabilities of entering d1 or d2) which commonly occurs with aging but can start in utero, and which is more common in youth than one normally supposes.**
All things are never really equal, so, as I said in the beginning, No. The longer answer is, "I like this question, but the calculations are off due to the human circulatory system and the lack of randomness at particular bifurcations within it.
*But I like your curiosity and tenaciousness. That you bothered to do some research and put it together here is refreshing, and though my answer is without doubt incomplete/flawed, you deserve one. So here it is (with my apologies for its quality.) I wish an anatomist was interested in answering; the quality would be so much better!
**As an intern, I once had the very sorrowful experience of admitting an healthy appearing, exuberant 4 year old child to the pediatric surgical service. The only presenting symptom was that the child started squatting during exertion (not good), and on exam, had a murmur which was caused by aortic stenosis. This was long before imaging studies were as sophisticated as they are now. The pediatric cardiac surgeon took him to the operating room (OR) to replace the valve, but there was so much atherosclerotic aortic damage that there was no healthy tissue which could hold sutures in place. The child died in the OR. I don't know what would have been done today, but had the child stayed home, they might have had a couple more years with the parents, who hoped for an uneventful procedure.  So the exercise involved in this answer was fun, but the memory it brought back is still quite sad.

I would focus on capillaries, much like anongoodnurse's answer. I'd go about thinking about the problem a bit differently, though.
From https://www.vhlab.umn.edu/atlas/physiology-tutorial/blood-vessels.shtml there are about 10 billion capillaries in the human body: capillaries being the places where vessels narrow to where only a single red blood cell can transit. These are where the "visits" happen. You can't base it on distance traveled, because most of the distance traveled is through very large vessels, where blood is really just being transported from place to place rather than "doing" anything.
On each "loop" through the circulation, a given blood cell is only going to enter one capillary. It'll be in a very small arteriole on one side, then go through a capillary, then come out in a very small venule. Before the arteriole it would have been in progressively larger vessels; after the venule it'll be in progressively larger vessels. However, the work of "visiting" other cells is mostly during that brief sojourn through the capillary.
To know how many of the 10 billion capillaries a blood cell visits in a lifetime of 120 days (=10,368,000 seconds), all we need to know is about how long a "round trip" is.
It's hard to find any solid reputable estimate for this round trip time. This very old paper:
Tarr, L., Oppenheimer, B. S., & Sager, R. V. (1933). The circulation time in various clinical conditions determined by the use of sodium dehydrocholate. American Heart Journal, 8(6), 766-786.
estimated a transit time of an average 13 seconds specifically from an arm vein, through heart and lungs, to the mouth. Travel time is going to be a lot slower to the legs, for example. I see various estimates thrown out of averages somewhere between 20 seconds and a minute. Overall it doesn't really matter for an order-of-magnitude estimate; let's just pick 30 seconds.
That would mean a blood cell has about 10,368,000 / 30 = 345,600 trips through the circulation. That number is small enough relative to the 10 billion capillaries that we can approximately assume no "repeat visits" and say 350,000/10,000,000,000 = 0.000035 = 0.0035% of capillaries are visited by one blood cell during the lifetime of that cell.
Capillary beds can be a bit complex and we've made a bunch of assumptions along the way, but I think even if you were very generous with some of those estimates you'd still stay under 0.1%.

If capillary beds make up 80% of our circulatory system (easy to believe), why do you say, most of the distance traveled is through very large vessels? Higher velocity travel is in larger vessels (travel in the aorta is - I believe - more than three orders of magnitude greater than through capillary beds), but (and it's a big but) as I stated, I hate math. If capillaries are 50K miles of vasculature, it doesn't compute if most of the time, the RBC's are actually in capillary beds, miles and miles of them, and it's there that they spend most of their time (they crawl along......slowly.)

(I purposely didn't take physical distance in account.)

@anongoodnurse Well, think about a capillary in your leg. A blood cell may travel more than a meter through the aorta, iliac, and femoral arteries before taking a relatively short trip over a mm or less through a capillary and then heading back through progressively larger veins. A huge proportion of the circulatory system is small vessels only because there are so many of them. I'd think of it the same way as roads...traveling between cities you might spend hours on a highway, and only a minute or two on a local road, though there is way more pavement dedicated to local road than highway.

In any event, it doesn't really matter for the calculation I presented. All that matters is that on one trip, a blood cell is going to go through just one capillary (or a few; it's kind of hard to define what exactly "one capillary" is in the capillary beds, just talking orders of magnitude here). Whatever % of time it spends in any kind of vessel, that's one visit per round-trip through the heart and lungs.

I believe we're mostly on the same page, just using different frames for calculating. Agree that actual distance traveled is in larger vessels, but fewer "visits" occur there.

@anongoodnurse Yes, we're definitely on the same page there; OP's calculation was based on distance. I'm saying you can't think in terms of distance, because much of the distance traveled is through vessels where nothing is being delivered, that is, there are no "visits".

In rereading the OP's question, I think your answer is the better one. Good explanation! +1.


text:
What is the size of different mouse brain cells?
I am trying to isolate microglia from the adult mouse brain. I wondered if I would get pure microglia culture if, after homogenization, I filtered cell suspension through a 70um filter. But I could not find information about the sizes of different brain cell sizes.

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In situ, cortical neurons have soma commonly in the range of 10-20 um (see for example https://en.m.wikipedia.org/wiki/Pyramidal_cell); it doesn't much matter if you talk of mice or any other mammal.
I'd recommend reading methods sections in papers that try to do something similar to what you want, rather than trying to invent a method from the bottom up.

Thank you for your answer. The problem is I got a protocol for microglia isolation in my lab, and they told me that it works fine. However, it doesn't work for me so well, so I'm trying to make slight changes to adapt this protocol to work better.

@Monika1223 It can be really frustrating when people ask about just part of their problem pertaining to their narrow solution without context. StackOverflow has called it the XY problem: https://meta.stackexchange.com/q/66377/401068

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text:
Difference between LIGR-seq and PARIS methods
I would like to reuse a dataset produced by LIGR-seq for ncRNA secondary structure prediction in the style of PARIS method.
At first glance, the methods appears to me to be very similar: use AMT for cross-linking, ligation of chimeric reads, sequencing.
Can anyone point-out the crucial differences between those methods?
Relevant papers I've found:
LIGR-seq - https://www.sciencedirect.com/science/article/pii/S109727651630106X
PARIS - https://www.cell.com/fulltext/S0092867416304226
Originally posted on Biostars (https://www.biostars.org/p/9507932/)

LIGR-seq

LIGR-seq (Figure 1A) employs in vivo crosslinking of RNA duplexes using the modified psoralen derivative 4′-aminomethyltrioxalen (AMT), which intercalates into RNA duplexes and, upon 365 nm UV irradiation, generates inter-strand adducts between juxtaposed pyrimidine bases (Calvet and Pederson, 1979). Following cell lysis and a limited single-strand S1 endonuclease digest, free RNA overhangs adjacent to duplexes are ligated using circRNA ligase. This ligase catalyzes the ATP-dependent ligation of proximal RNA ends and has optimal activity at elevated temperatures that reduce RNA hybridization. RNase R, a 3′→5′ exoribonuclease that digests linear and structured RNAs (Vincent and Deutscher, 2006), is then used to digest uncrosslinked RNA, thereby enriching AMT-crosslinked duplexes (Figures 1A and S1). Following reversal of crosslinks using 254 nm irradiation, the RNA samples are subjected to high-throughput sequencing to detect chimeras formed by ligation. To assess background ligation artifacts, uncrosslinked ("–AMT") samples are prepared in parallel, and unligated samples are used to determine the relative expression of transcripts forming chimeras for downstream normalization and analysis.

Summarized
AMT crosslinking ⟶ cell lysis ⟶ S1 endonuclease digestion ⟶ RNA-RNA ligation with circRNA ligase ⟶ RNase R digestion of uncrosslinked RNA ⟶ crosslink reversal ⟶ sequencing library preparation (adapter ligation, reverse transcription, etc.)

PARIS

HeLa, HEK293T, and mES cells were treated with or without AMT and crosslinked with 365 nm UV. Cell lysates were digested with S1 nuclease and RNA purified using TRIzol. Purified RNA was further digested with ShortCut RNase III to smaller fragments. RNA was separated by 12% native polyacrylamide gel and then the first dimension gel slices were further electrophoresed in a second dimension 20% urea-denatured gel. Crosslinked RNA above the main diagonal was eluted, proximity ligated with T4 RNA ligase I and photo-reversed with 254 nm UV. The proximity-ligated RNA molecules were then ligated to barcoded adapters and converted to libraries for Illumina sequencing.

Summarized
AMT crosslinking ⟶ cell lysis ⟶ S1 endonuclease digestion ⟶ TRIzol purificaiton ⟶ ShortCut RNase III digestion ⟶ 2D gel purification ⟶ RNA-RNA ligation with T4 RNA Ligase 1 ⟶ crosslink reversal ⟶ sequencing library preparation (adapter ligation, reverse transcription, etc.)

Concerning the capture of RNA-RNA interactions, these methods are essentially the same. Given that both papers were published in Cell Press journals in the same week, they were likely developed concurrently in competing labs. It may be the case that the editors coordinated publication so that neither group would feel they "got scooped".
From what I can tell, the major difference is in how the methods distinguish in vivo RNA interactors from transient RNA-RNA hybridization events that occur during the course of the protocols. In LIGR-seq, they include an uncrosslinked ("–AMT") control so that they can differentiate true interactions from background noise by looking for ligation chimeras that are enriched in the +AMT samples relative to –AMT. In PARIS, the second dimension of the 2D gel is 20% urea, which would serve to denature any non-crosslinked dsRNA molecules prior to ligation; see the full methods for more details:

Gel slices of each lane were embedded and polymerized into the top of the second dimension 20% urea-TBE denatured polyacrylamide gel ... The second dimension gel has higher temperature due to the high power, and the high temperature facilitates denaturation of the dsRNA fragments.

There may also be a difference in the length distributions of the chimeric RNA molecules obtained at the end each method, since LIGR-seq and PARIS use different RNase enzymes with different digestion parameters.

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text:
In enzyme kinetics, Can the Kp be greater than K1 in any way?

Enzyme reacts with substrate to produce a complex. And finally the products in a catalysis reaction.

To answer this question, we need to delve into the world of
dimensional analysis
and to consider when and how rate constants may be compared.
The OP considers the following simple kinetic mechanism, (which, after defining kinetic constants such as
$K_m$
and
$k_{cat}$
in terms of rate constants,
gives rise to the
Michaelis-Menten
equation):
$$
E + S \xrightleftharpoons[{k_{-1}}]{k_1}
ES
\xrightarrow{k_p}
E + P
\tag{1}
$$
First and Second Order Rate Constants
As written, $k_1$ is a second-order rate constant and  $k_p$ is a first-order rate constant.
Therefore $k_1$ will have units of  $concentration^{-1}\text{. }time^{-1}$, and $k_p$ will have units of $time^{-1}$ (as will $k_{-1}$).
For example, $k_1$ may be spoken of as having a value of
$10^9 \text{ M}^{-1}\text{ s}^{-1}$ (
here
and
here),
or as having a value of
$10^9 \text{ L mol}^{-1}\text{s}^{-1}$, and $k_p$ may be spoken of as having a value of $10^6 \text{ s}^{-1}$.
By the laws of
dimensional analysis,
it is meaningless to compare quantities of different units.
It is absurd, for example, it ask if pH 7 is greater than (or less than) $10^\text{o}\text{C}$,
or if 2 mol is greater than (or less than) 5 seconds.
So too with rate constants: it is meaningless to ask if a second-order rate constant is greater than or less than (or is equal to) a first-order rate constant.
The application of dimensional analysis to situations often encountered in enzyme kinetics is well described in
Fundamentals of Enzyme Kinetics
(Cornish-Bowden, 2013, 4th Ed, Section 1.3) and the relevant section seems to be freely accessible via
Google Books.
For example, we can multiply and divide quantities of different dimensions, but we
cannot add or subtract them.
Thus, inspection of the numerator of the following equation shows that it is CLEARLY WRONG:
$$
K_m
=
\frac{k_p + k_{1}}{k_{-1}}
\tag{2}
$$
The CORRECT expression for $K_m$ for the mechanism shown in Eqn (1) is
the sum of the two first-order rate constants, divided by the second-order rate constant:
$$
K_m
=
\frac{k_p + k_{-1}}{k_{1}}
\tag{3}
$$
We can also infer from Eqn (3) that ${K_m}$ has dimensions of molarity,
even if we have no idea as to what the symbol ${K_m}$ refers.
$$
  \frac{\text{s}^{-1}}{\text{M}^{-1}\text{ s}^{-1}} = \text{M}
  \tag{4}
$$
Application of the rules of dimensional analysis is often useful in 'scanning' the
equations encountered in enzyme kinetics.
$$
Y=
\frac
{1}
 {1 + \frac{[A]}{K_m^A} + \frac{[B]}{K_m^B} + X}
 \tag{5}
$$
For example, without any prior knowledge as to what $X$, $Y$, $K_m^A$ and $K_m^B$ refer to,
inspection of Eqn (5) allows the following conclusions to be drawn:

$X$ is dimensionless
The quantities $\frac{[A]}{K_m^A}$ and $\frac{[B]}{K_m^B}$ are dimensionless
$Y$ is dimensionless

Pseudo First-Order Rate Constants
Although $k_1$ and  $k_2$ have different dimensions,
$k_1 \text{[A]}$
has dimensions of a first-order rate constant $(time^{-1})$ and can be directly compared
with $k_p$ and $k_{-1}$.
The quantity
$k_1 \text{[A]}$
is often referred to as a pseudo first-order rate constant. (Personally,
I don't like the term)
Thus, to argue that $k_1 \text{[A]}$ >> $k_p$ is perfectly OK from a dimensional
analysis perspective.
Perhaps more importantly, a pseudo first-order rate constant may be added to or
subtracted from a first-order rate constant.
Thus, an equation such as the following presents no problems (again from a dimensionless
analysis point of view):
$$
Y=
\frac{k_1}
{{k_1} [A]  + k_{-1} + {k_p}}
 \tag{6}
$$
Common Confusion Concerning Rate Constants: An Example
It is surprising how often the laws of dimensional analysis are misapplied in
the world of enzyme kinetics.
For example, in a paper published in J. Chem. Educ. in 2011, it is stated "For the classic Michaelis-Menten enzyme,
$k{_1} > k_{-1} >>  k{_2}$" where "... $k_1$ is the forward rate constant for the first step, the
fast binding of substrate $(S)$ to enzyme $(E)$ to make the non-
covalent enzyme-substrate complex $(ES)$,  $k_{-1}$ is the reverse
rate constant for the dissociation of $ES$ back into $E + S$; and $k_2$
is the rate constant for the subsequent slow catalytic step converting $S$ to product".
Let's state it bluntly: $k_1$ cannot be greater than $k_{-1}$, as $k_1$ is a
second-order rate constant and $k_{-1}$ is a first-order rate constant.
Furthermore (and very surprisingly), J. Chem. Educ. has not corrected the error.
(In my opinion, the paper is otherwise good).
Reference
Cornish-Bowden, Athel (2013)
Fundamentals of Enzyme Kinetics
4th Ed,   Wiley-Blackwell
[ google books ]


text:
How do predators avoid "food poisoning"?
How do predators avoid becoming ill in cholera, diarrhoea, dysentery and similar diseases?
They aren't exactly careful when eating a kill, especially pack animals where there can be quite a fight over a catch and, I assume, should regularly get pieces of the large intestine in their mouth - which should be very unhealthy, shouldn't it?
Even house cats, when they eat mice and rats, seems to swallow them more or less whole and then cast up the skeleton = all contents of their prey's intestine remains in their stomach.

They’ve evolved and adapted to be able to eat what they do without getting ill (although they probably do get ill from eating bad food on occasions) because of natural selection. Remember, humans are quite different to other animals and what makes us ill doesn’t make most other animals ill.

Pet owners might disagree with you that their fluffy predators do indeed avoid food poisoning.

@BryanKrause - I immediately thought about my dogs when I read the title of this question. Luckily, the three I have right now have GI systems of steel, but some of my previous dogs... did not.

Not only "should [they] regularly get pieces of the large intestine in their mouth", but when I lived on my farm(ette) in the woods, where individuals were allowed to hunt, the dogs would go looking for guts to eat. We took to requiring every hunter to bury the deer's innards. The dogs would come back covered in dirt with guts to eat. We then took to requiring burial of innards with rocks stacked on the site. The end results of enjoying the contents of small and large intestines were unpleasant, to say the least.

Eating the meat freshly killed helps rather than letting it fester in the fridge for a week before eating it.

@user438383 So have humans. We clearly aren't that different from chimps, and they eat meat whenever they get the chance (gorillas and orangutans are more vegan). But what is the difference between humans and dogs? We mostly eat the same stuff. In what respect do you mean humans are quite different from dogs when it comes to infections and diseases?

@d-b - I would say that dogs are about as close to humans as a non-primate can get, with 50,000 years of co-evolution with us, eating our food, living with us, etc. They share hundreds of diseases with us, even rare ones. Dogs are the reason we have a treatment for narcolepsy. Their contribution to our knowledge is profound.

If you live in a country where things like cholera and dysentery  are endemic, how many healthy dogs do you see roaming around. How many are emaciated? When they die, who does autopsies on them to determine cause of death? My point is, you're making assumptions.


text:
Infection induced immunity vs vaccine induced immunity
I'm of course concerned about COVID here, but my question is about viruses in general and mRNA vaccines. I'm reading reports including one by the government seeming to suggest that vaccine-induced immunity is more robust than one induced by contracting a virus itself.
Doesn't a vaccine trigger the immune system in the same way that a viral infection does? I would think it would be weaker in that it is only one protein factor rather than what would be found by a true infection. The vaccine also doesn't "fight back."
What am I missing here? Thanks.

Welcome to Biology.SE. This is not simply an answer site, but instead a site that promotes self-learning with some expert help. Consequently, questions that show little or no prior research effort are off-topic on this site. Please [edit] your question and tell us where you've looked for answers (including related questions on this site), what you do know about the topic, and where exactly you still have questions. Please take the [tour] and consult the [help] starting with [ask] for details.

I'm not a biologist. I just want to be an informed proponent of vaccines. I just want to ask a question. I could go on for a paragraph about how the stack sites position themselves as places to get answers to questions but require too much from the askers. But I'll only say as an expert developer, I use stack overflow only as a last resort. It's more trouble than its worth most of the time. Thanks.

There are several factors at work here, and I don't think the relative importance has been determined with any certainty. In descending order of my own estimation of their importance, vaccine-induced immunity:

Stimulates the systemic immune system, rather than the mucosal,
Presents only antigens that will inactivate the virus when bound by
antibody,
and does not disrupt the immune system, which can result in a better response.

From a 2005 review on the mucosal immune system:

The mucous membranes covering the aerodigestive and the urogenital tracts as well as the eye conjunctiva, the inner ear and the ducts of all exocrine glands are endowed with powerful mechanical and chemical cleansing mechanisms that degrade and repel most foreign matter. In addition, a large and highly specialized innate and adaptive mucosal immune system protects these surfaces, and thereby also the body interior, against potential insults from the environment. In a healthy human adult, this local immune system contributes almost 80% of all immunocytes. These cells are accumulated in, or in transit between, various mucosa-associated lymphoid tissues (MALT), which together form the largest mammalian lymphoid organ system1.
The mucosal immune system has three main functions: (i) to protect the mucous membranes against colonization and invasion by potentially dangerous microbes that may be encountered, (ii) to prevent uptake of undegraded antigens including foreign proteins derived from ingested food, airborne matter and commensal microorganisms, and (iii) to prevent the development of potentially harmful immune responses to these antigens if they do reach the body interior. At variance with the systemic immune apparatus, which functions in a normally sterile milieu and often responds vigorously to invaders, the MALT guards organs that are replete with foreign matter. It follows that upon encountering this plethora of antigenic stimuli, the MALT must economically select appropriate effector mechanisms and regulate their intensity to avoid bystander tissue damage and immunological exhaustion.

So, by injecting a vaccine, it's expected we can provoke a more robust response than a natural infection that stays in the lungs. A few COVID cases result in high viremia (virus in the blood), but I don't know of any studies comparing viremia to duration of IgG levels, etc.
Regarding antigens; viruses have evolved ways to trick the immune system, e.g., presenting an antigen that is attractive to the immune system, but the virus can still function when it is bound by antibodies. In COVID, this is the post-fusion state of the spike protein itself. The mRNA vaccines, at least, include mutations that block the spike from transitioning to the post-fusion state.
And finally, successful viruses actively interfere with immune function. COVID has been found to induce immunodeficiency in recovered patients. This prevents the immune response to a natural infection from being as strong as you would expect, even though it is a more severe challenge to the immune system than a vaccination.

Thank you. I appreciate your answer and understood most of it.


text:
What does this jawbone belong to?
I found this specimen in a rock garden near St. Louis Mo. I believe it to be the posterior portion af a lower mandible of a mammal. The photos I am including seem to me to show;b[!broken teeth, ]2:tooth roots, blood vessel fossa. I could be seeing things but can somebody support my theory?
It measures 4cm in length,4cm in width, and 4 cm tall.

That's most likely quartz, which isn't generally found in fossils. High quality photos with the whole specimen in focus (i.e depth of field increased - use a higher f-stop) from several angles would be required for us to make any identification. We would also need a location (approximate, nearest city would probably work).

this is likely quartz,it had probably been better to ask what is this than it is to state what you think it might be.if rock id questions had been on topic over at https://earthscience.stackexchange.com/ it could have been migrated but rock id is off topic there.


text:
How do geneticists determine if a gene mutation is pathogenic?
I am analysing information about patients with neurodevelopmental disorders using the DECIPHER genomics database. I am looking for patients who have only a specific gene deleted and no other mutations and have intellectual disability.
One thing that I have noticed is that some these patients have deletions of just one gene and have intellectual disability. However the pathogenicity of the gene deletion is reported as benign.
Why is this the case? Since the patient has deletion of only one gene and no other mutations, it's most likely that the gene deletion is responsible for the patient's intellectual disability.
In general, I was wondering how do geneticists who study patients determine whether a given gene mutation is pathogenic or benign? Are there any established standards/conventions for determining this?
Any insights are appreciated.

The presence of a single variant relative to reference in a single patient is usually not considered adequate evidence to say that the variant causes a patient phenotype. It might be considered an interesting anecdotal observation, but there is plenty of room for error in genotyping, phenotyping, or the possibility that the disorder is not genetic.
Another important note is that you are looking at a specific database (DECIPHER) which has their own bespoke workflow for inferring pathogenicity. Their practice relies upon and integrates information from other data sources, but it may not be identical to any other process for determining variant pathogenicity or disease causality.
For this variant specifically in DECIPHER, it is marked as "Benign" not because of this patient, but because of prior evidence that variants in the gene don't have strong phenotypes. You can click the "?" symbol and it gives you some info:

So you can see that the benign classification is the result of a statistical model looking across patients. (Though as you can also see in the blue box, it does incorporate information from this patient; for more information about this data's lifecycle, you can see the doc here). I should be clear that I don't see documentation of what models exactly DECIPHER is using, or how they are applied, though I haven't searched exhaustively.
You can further click through the OMIM link for the gene in question, which gives more info about what is known about the gene- in this case, that it doesn't seem to have strong effects.
Also, this variant is heterozygous, which is to say that the patient has a functional copy of the gene. There is not evidence for haploinsufficiency of this gene (e.g. that one copy knocked out is bad enough to cause a phenotype). You can see this under the "ClinGen DS" entry for the gene.
If many more patients with this deletion and also similar phenotypes were observed, and there were no control individuals with this deletion, then that might change the weight of evidence towards it being pathogenic. But at present there simply isn't enough evidence to indicate that this variant is pathogenic.
Alternately, if there were evidence that the disorder were genetic from a pedigree of a family, and that this variant were co-inherited with the disorder, that would also be strong evidence.
Yet another form of evidence would be if someone made the gene deletion in e.g. a mouse or a human cell line, and showed that there were a related phenotype.
CAVEAT
Having written all that, I have to say that there are probably situations in which most people would probably accept a one-patient anecdote variant as causal. Examples might be large previously unobserved chromosomal abnormalities coupled with strong phenotypes. But that would be a gut-feeling kind of decision, not really based on rigorous scientific reasoning.

This is a bit of an off-the cuff/high-level answer, but I will leave you with a few things to think about.

The human genome, while one of the highest-quality and most thoroughly analyzed ones we have, is still "poorly" understood and "under construction".

There are large stretches of genomic material called scaffolds that we know exist but don't know where to place in the rest of the genome. Regions around chromosome centromeres are also poorly understood as centromeres are notoriously difficult to sequence though.  There are also alternate loci and other genomic phenomenon that are less understood and often overlooked when people analyze genetic data.
Why does this matter?  Just because you have sequenced someone's genome doesn't mean we have a complete set of information about it.  Maybe they have a SNP on a scaffold, maybe they have a SNP or indel in an unannotated cis- or trans-regulatory element, ect.  You are only looking at variation in "known" things but there are also a lot of known "unknowns" that you are not going to have the means to quantify.

The quality and depth of the sequencing will greatly impact your ability to call SNPs and indels (read: genetic variation).

Often in clinical settings and wide-scale studies people go for quantity over quality since the goal is often to gain statistical power through aggregating at the population level.  If your sample falls into this category you likely don't have either the depth or read length (ie sequencing quality) to call some of the more subtle genetic variation that might be present.

Everyone has genetic polymorphisms (SNPs, indels, ect.)

Estimates vary on exactly how many the average person has, but no one is ever truly genetically "normal".   The real question is, "are any of that person's variants detrimental?" and that is often a very hard question to answer. Even if polymorphisms in a gene are usually benign, you can never completely rule out the possibility that the particular polymorphism you are seeing just happened to hit a sweet spot that perturbs the gene's function enough to manifest in disease.
So it is almost certain your given patient has genetic variation in locations other than just the one gene you mentioned.  It is possible they are in unknown/unannotated regions (1) or not detectable given your sequence quality (2), but they almost certainly exist.

Phenotype = Genetics + Environment

With any phenotype there is always the possibility that some combination of genetics and environment play a role in its manifestation. Maybe its purely genetic, maybe its purely environmental, often its a mix of the two. You always need to keep these two factors in mind when studying any disease.
Putting it all together
If after sequencing you only detect a significant polymorphism in one gene, why can't you conclude that must be the root cause? The answer is a combination of 1-3 as well as a litany of other reasons.  Essentially genetic sequencing (in terms of genome-wide or other forms of high-throughput sequencing) has a lot more slop and squishyness to it than most people make it out to have.
You should never believe you have seen all there is to see, and often should be fairly critical of even what you do see.
Another point I want to make relates to point 4. The intellectual disability you see in your patient may be entirely due to environmental causes. For example, in Autism Spectrum Disorder there is a theory that severe viral infection of the mother during pregnancy may cause the maternal immune system to attack the developing fetal brain, leading to developmental deficits and eventually ASD.  It doesn't matter if this theory is actually accurate (although there is a good amount of data that seems to suggest this), but it does suggest one of many ways that a recurring phenotype in the population may be caused entirely by environmental rather than genetic factors. This possibility is always important to keep in mind.
So how do we actually figure out if genetic variation is causing disease?  The very short answer is through many complimentary methods and that it's still quite complicated.
The slightly longer answer is that we usually start with correlational data over a large population.  We gather a bunch of subjects, measure some trait (in this case presence or absence of disease), sequence their genomes, and see if we can find any recurring associations between genetic polymorphisms and the trait in question. One form of these types of studies is called a Genome Wide Association Study (GWAS) which you might want to read up on.
Another method is by looking at conserved sequences. By looking at similar genes across species, or identical genes across many samples of the same species, we can identify areas of genes that have identical or near-identical sequence (ie that are well conserved).  The theory goes that these sequences tend to get conserved because they are vital for a given gene's proper functioning, whereas less conserved sequences may be able to tolerate some change without causing significant issues.  So, if a given patient has a significant polymorphism in a highly conserved region, that's usually good evidence something might be going on and often warrants further investigation.
These types of approaches are just the start, and often lead to a list of "candidate genes" for a given disease/phenotype. At this point biochemical or other forms of experimental methods take over to physically investigate the functions of these genes. Often this involves manipulating the gene in some sort of model system (cell lines, model organisms, ect.) with the end goal usually being to a) determine the gene's functional role in disease and b)the mechanism by which the gene carries out said function.
Often the overall path looks something like this: association with gene -> deleterious variants within gene identified -> experimental modeling of variants-> biochemical investigation of models -> mechanism.  The standard can vary by field, but almost no one will say a given mutation/gene is "pathogenic" without at least some experimental evidence to back that claim up.
So, as a final thought, why is this still so complicated/why doesn't this approach work for all diseases? Rather than answer directly, I'll leave you with a (hopefully) thought-provoking example.
Let's go back to my ASD example and point 4 (P=G+E). Let's say that the theory is true and severe viral infection during pregnancy causes a significant proportion of ASD cases. If you were to do a GWAS study on ASD, you would likely turn up polymorphisms in immune system related genes (if we assume that genetic variation in certain genes could make you more susceptible to viral infection).  Now those genes aren't really the "cause" of the disease, they might just make you more likely to get infected (or more likely to become severely infected, ect.), but the viral infection itself is probably what most people would think of as the "cause".  Even more subtle still, while it is these genes in the mother that confer vulnerability to disease, they may still show up as a signal in the affected children since a decent proportion of them will inherit these genes from their mother.  So while what might show up from your study is variation in immune-related genes in the affected individuals, this actually tells you very little about what actually causes the disease. This is just one of many ways that trying to nail down a disease using genetic sequencing alone can be significantly challenging.

I think that this is overall a good answer, but it might benefit from 1) linked sources, 2) a round of revision to make it a bit shorter, 3) a tl;dr upfront, or 4) taking advantage of illustrative figures or SE formatting to make it easier to follow the argument.


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What is the creature on the cover of the fourth edition of 'Dinosaurs: A Concise Natural History'?
I have yet to receive my copy so apologies if this is explained in the book - what is the creature on the cover of the fourth edition of 'Dinosaurs: A Concise Natural History'? It looks like a bird with bat wings (picture below). Could anyone put this in context and suggest why it may have been chosen as the cover image?

It appears to be of the family Scansoriopterygidae.
This dead-end family in evolutionary terms, thrived in woodlands at some point between 153 and 165 million years ago. They ranged in size between small red-squirrels and large grey-squirrels, all having bat-like wings with no developed flight feathers as found in later species such as the well-known archaeopteryx.
They are thought to be marginal flyers or incapable of sustained flight, most likely gliding between trees as flying squirrels do now.
The most recent media sensation (such as it was) was of a discovery of the simply named Yi qi, the first dinosaur ever found with bat-like wings.

That fossil find—announced in 2015 by study co-author Xing Xu, the
IVPP's deputy director—reshaped how scientists understood the
evolution of flight.

This seems to justify its inclusion as a cover illustration.
There's a rather splendid illustration in National Geographic, but I'll not reproduce it here as per their wishes. (Link will try to sell you a subscription, no affiliation with myself), however a related species Ambopteryx longibrachium is reproduced here with attribution:

Ambopteryx longibrachium. Artwork by Chung-Tat Cheung / Min Wang / Institute of Vertebrate Paleontology and Paleoanthropology / Chinese Academy of Sciences. 2022, Smithsonian, fair usage.

Amazing - I had no idea


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Do bees use their ovipositors for egg-laying?
I'd always assumed that, since bee stings are 'modified ovipositors', queen bees couldn't sting. But apparently they can.
What is going on with bees' ovipositors? Are they capable of injecting both venom and eggs?

Hi and welcome! This is easy enough to google. Did you try, and if yes, what did you find? You might wonder what kind of Q&A site this is, being asked to show your search results; shouldn't we just answer your question? Actually, no. We're expected to help if we so choose. We're scientists or people interested in science, a lot of us teach, practice, or research some aspect of Biology. We expect some meaningful degree of research; not a ton, but not nothing, either. Consider this kind of like a classroom, not a chat room. You'll get a (better) response with a better effort on your part.

Googling didn't turn up anything useful for me, but if you know the magic phrase to google for, let me know, and I'll finish the research and answer the question myself!

Try some combination of your own words: ovipositors, stingers, queen bee, eggs.

So, from the first page of hits for "ovipositors, stingers, queen bee, eggs", I have : "However, in virtually all stinging Hymenoptera, the ovipositor is no longer used for egg-laying."  and "Queen bees can use their ovipositors to lay eggs and to sting but worker bees only use it to sting as they are infertile and don't lay eggs." That sort of thing is why I asked the damned question here, where I thought an actual biologist might answer it.

OK, so you think all Biologists know about queen bee ovipositors/stingers? An etymologist would probably know, or an apiarist. Don't know if we have either one on this site; I'd be surprised if we didn't have an apiarist or two. I have two advanced degrees in Biology, and I didn't know off the top of my head, but I did google it and found the answer. You also found the answer: your two statements are not mutually exclusive. Think about the statements and tell me why you think they don't answer your question, and I'll answer the damned question personally! ;)

So, if 'virtually all stinging hymenoptera' doesn't include the canonical example of stinging hymenoptera, then yes, clear. Queen bees lay eggs through their stingers. As implied by the unlikely conjunction of two random things on the internet. But the only reason I think that might be true now is because you've just elliptically told me this and you claim to have appropriate knowledge. I was hoping that someone might actually answer the question, maybe with a link to a trustworthy source. A man can dream. Don't worry, I won't be troubling your website with my half-wit questions again.

I'm not going to feel sorry for you for labeling your own question as "half-wit". Your feelings are what they are, and I have no control over that. It's not a bad question; hover over the downvote arrow and note that "contains no research" is a reason to DV  and to close. You were welcomed, up voted, no one down voted you, not even me. Think what you will. Btw, virtually is just shy of "all (full stop.)"

If you still want an answer, I will provide a definitive one tomorrow. It might surprise you to learn that even someone with two advanced degrees in Biology can be wrong. Maybe your question was better than your last assessment.


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Rationale for helper T cells?
If my understanding is correct, helper T cells have two main functions:

stimulating macrophages at the site of infection
activating B cells and helping them undergo somatic hypermutation

What advantages do Helper T cells in mediating this process, instead of macrophages and B cells activating on their own?
In particular, I could imagine:

macrophages always being "on duty" to swallow pathogens that do not present self-antigen.
B cells already require a first activation by free-floating antigen, so they could just have evolved to not require the second activation by helper T cells.

Would this have disadvantages I have not considered, or have had evolutionary problems?

@anongoodnurse good question! I think that is because that requires a more complex evolutionary path. But in the case of T cells, the immune system evolved a whole new type of cell instead and complex secondary activation mechanisms instead of what seems like a more straighforward strategy, which seems very mysterious to me.

@anongoodnurse I skimmed the link and still don't understand. What do you mean?

https://www.ncbi.nlm.nih.gov/books/NBK27138/ Don't skim. Read carefully. Present your findings (research into answering your own question.)

@anongoodnurse thank you. these links to more information are gems

I have edited this question by applying Occam’s razor to it, as is required in many questions here posed in terms of “why did this evolve”, which in any case generally can only be answered by subjective conjecture. By focusing on the systems in question one can answer by make objective scientific points about the mechanisms, or, if necessary, the problems in their evolution (number of events for example). But in asking this question, focus on the mechanistic question — keep other things out, allowing users to supply them in answers only if they see them as relevant.


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Why don't T-Cells that correspond to certain viruses damage our cells?
I am studying immunology, and I am facing a problem.
The antibodies that B-Cells produce attack the viruses, but won't they also attack our cells that need to use the receptors on other cells?
When I tried searching it up, Google only gave results of Autoimmune Diseases.
Any help would be appreciated.

Our cells have many, many receptors and molecular markers on their membranes. One of the ways in which the immune system does its job is by detecting infected cells which are presenting many viral molecular markers. This is a feature and not a bug, since it helps stem the infection by reducing the number of virus-producing cells.
You may have heard of NK (natural killer) immune cells. The NK decides which cells to kill by identifying which ones are exhibiting many molecular markers of stress, which gives it an important role in the body's immune response to cancerous cells, for example. So there is a balance of healthy markers and unhealthy markers that the immune system is measuring, and if it tips towards unhealthy, the distressed cell is no longer recognized as self and is eliminated by the immune system.
Auto-immune diseases are when this system is disregulated in some way, and the immune system attacks cells which would normally be deemed as healthy parts of the self.

This is a good, clear answer but it would benefit from linked sources.


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Skin tone of a new born just after birth
I have a question. My skin tone is light but the photographs of me as a baby show  that when i was just born, i was having an even lighter skin colour for about two years or probably more. As for now my skin tone is not the same as before. Why does this change of skin tone happen in the first place? Also, is it possible to get back to that same skin tone as i was, when i was a baby? Also, another follow up question, talking on the matter of skin tone, there are alot of factors that come into picture to make the tone like the location and the amount of sun rays we recieve, beside obvious genetics. So i wanted to ask can a change of location from place of birth to another completely different location, (possibly other side of the globe) can bring about a change of tone? Thanks.

Skin color in humans is mainly determined by a pigment called Melanin. Melanin is produced by cells called melanocytes present in the epidermis of the skin. Melanin production rates are determined both by genetic and environmental factors. Melanin controls the amount of ultraviolet radiation (from the sun) that penetrates the skin and while UV radiation can assist in the production of vitamin D, excessive exposure to UV can damage health. This is why the amount of sunlight a person receives can control the amount of melanin that is produced in their body. Sun tanning occurs when a person receives more sunlight than they usually do, increasing the melanin content in their skin.
As Wikipedia quotes:

[skin] start[s] out pale in infants and turn darker as the skin is exposed to more sun. All human babies are born pale, regardless of what their adult color will be. In humans, melanin production does not peak until after puberty.

This is likely why your baby photos show you as pale-skinned.
As for your last question, while a change of location can obviously affect skin color (sun tanning is an example), it is also affected by genetics. If you change location while very young, there is a big chance that your adult skin color will be different than what is expected using genetics. As noted above, melanin production peaks at around age 30, so the location you were at age 30 would most likely affect your skin color. Again, slight variations such as tanning and becoming pale will be noticeable after a location change. However, this topic is very hard to study and there is not much evidence regarding my hypotheses. It is merely an educated guess that I took after studying present evidence.
I would recommend checking out the Wikipedia article to learn more about this.

Thanks for your answer!


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Do ATP generated aerobically and anaerobically have different phosphorylation potentials?
We have recently postulated that ATP generated by substrate-level  phosphorylation may have a different phosphorylation potential to the ATP generated by oxidative phosphorylation. This  could be because ATP generated via ATP synthase is released into a more basic environment than the cytoplasm.
My question is:
Has anybody measured the phosphorylation potential of ATP during the growth of  E. coli under anaerobic conditions, and,
if so, how does it compare with the phosphorylation potential of ATP during the growth of E. coli under aerobic conditions?

Please tell us the results of your own research to try to answer this question.

@David my cynical side says this question is purely to raise the profile of the OPs paper linked in the question.

@bob1 — One has to take questions of this sort at face value, and respond by making sure they fulfil the usual prerequisites. Anyone trying to publicize their own published science on this list — especially on this type of subject — is wasting their time, in my opinion, as I think they are addressing the wrong audience. But that’s their problem.

Do you have an open-access version of your publication?

https://www.alliedacademies.org/conference-abstracts-files/switches-thresholds-and-flux-signals-in-the-control-of-central.pdf

https://www.alliedacademies.org/conference-abstracts-files/switches-thresholds-and-flux-signals-in-the-control-of-central.pdf

Welcome to Biology.SE. Please take the [tour] and then go through the [help] pages starting with [Ask] questions effectively on this site and [edit] your question accordingly. In particular, reference information should be added to the body of your question rather than being placed in a comment — comments are for discussing improvements to posts. Consequently they are ephemeral and often overlooked.

@MansiEl-Mansi You are probably the best person to answer your own question. This site is for biologists as well as general public but there are only a handful of experts who study different fields of biology. You ask a question about a very specific topic (that too asking for literature evidence for something). You have better chances of finding an answer yourself than relying on users here, because this is your research topic. Did you check out google scholar?

I thank you for the effort and time.

Based on the way this question is phrased, the answer is trivially no. No matter how you make an ATP molecule, if you measure hydrolysis in a consistent manner there will be no difference.
A fundamental axiom in chemistry is that identical molecules are indistinguishable from each other. Specifically, I mean that the entropy and enthalpy are State Functions - they only depend on the current state of the system and not how the system got there. This is best summed up with Hess' Law.
The only things that could change the free energy of hydrolysis of an ATP molecule are:

A change in the isotopic makeup of the ATP molecule
A change in the environment in which the hydrolysis is occuring

The first is very, very unlikely to be dependent on aerobic vs. anaerobic respiration. I mean I guess the isotopic makeup of the oxygen could be ever-so-slightly different or something, but I would be shocked if it was. Even then it almost certainly wouldn't make much of a difference in energy of hydrolysis.
The second, is actually very likely to occur. Changes in temperature will always affect any reaction for which the change in entropy is non-negligible (remember $ \Delta G = \Delta H - T \Delta S $). As you suggest, changes in pH would certainly effect a measured change in energy due to a change in the abundance of the various protonated forms of ATP (and keep in mind  hydronium if you're considering spontaneous hydrolysis). Indeed, almost any change in the environment could affect the measured energy.
But, importantly, these are not due to differences in the actual ATP molecule. These are due to differences in the environment that the reaction is taking place in, not the environment it was produced in. If you take two ATP molecules and place them in an identical environment they will always have the same energies (isotopic differences excluded). Any evidence contradicting this is either wrong or a suggestion of a fundamental paradigm shift upending years of basic physics and chemistry.


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How is mRNA made in a lab
I'm not a biologist, but I think I have a sound layman's understanding of how mRNA vaccines are made. At least this is how it was explained to me:

create some mRNA
get it into a cell (with the lipid nanoparticles)
the cell uses the mRNA, sort of like a blueprint, to create a protein (like spike protein from COVID-19)
the body sees these proteins, attacks them and learns for the next time

So far so good. But what I can not find anywhere, is a (layman, sorry) explanation of that first step: how we can create mRNA in a lab.
In a podcast (Stuff You Should Know) it was explained that it's fairly simple and they just enter the required sequence in a computer.
That's all well and good, but I'm interested in how we can actually create a specific mRNA sequence in a lab from scratch.

In the case of the COVID-19 mRNA vaccines, the mRNA is synthesized by in vitro transcription. The gene of interest (e.g. the SARS-CoV-2 Spike protein) is cloned into a plasmid and transcribed by RNA polymerase. The mRNA is then purified and packaged in a lipid bilayer. NHGRI has a nice infographic explaining the full process.
RNA can also be made by solid-phase synthesis, though this tends to be expensive and low-throughput.


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Is the yolk of an egg a cell?
I am a little confused, I find sites on the internet that say that the yolk of an egg is a macrocell, and another says that it is not. So... is it a macrocell or not?

Related post with no useful answer: how is chicken egg a single cell.

links to the sites themselves, with the contradictory quotes, might be helpful.

No, the yolk is not part of the egg cell in chicken and ostrich eggs. Although I found many websites claiming that the yolk is part of the egg cell, none of them were reputable. I think that it is more of a myth than a fact. Although in some animals the yolk
is enclosed within the cytoplasm of the cell, in larger species like chickens and ostriches the yolk is separate from the egg cell.
Wikipedia quotes:

The yolk is mostly extracellular to the oolemma [cell membrane], being not accumulated inside the cytoplasm of the egg cell (as occurs in frogs), contrary to the claim that the avian ovum (in strict sense) and its yolk are a single giant cell.
[...]
The yolk mass, together with the ovum proper (after fertilization, the embryo) are enclosed by the vitelline membrane, whose structure is different form a cell membrane.

This means that in the chicken egg, the egg yolk is mainly held outside of the cell membrane (of the egg cell/embryo) and hence is not considered part of the cell. However,

[in many small species] such as some fish and invertebrates, the yolk material is not in a special organ, but inside the egg cell (ovum).

So although the yolk is part of the cytoplasm of the egg cell in some species, this is not true for chickens or for ostriches.


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The role of PCA (Principal Component Analysis) in recording neurons
I am reviewing the recording methods from an experiment that tracked neuronal activity on the prefrontal cortex of a monkey.
From the method description in Nieder, Andreas, David J. Freedman, and Earl K. Miller. "Representation of the quantity of visual items in the primate prefrontal cortex." Science 297.5587 (2002): 1708-1711.:

Recordings were made from three hemispheres of the PFC [prefrontal cortex] of two adult rhesus monkeys. [...] Arrays of eight to twelve tungsten microelectrodes (FHC) were inserted using a grid (Crist Instruments) with 1-mm spacing. [...] Neurons were selected at random; no attempt was made to search for task-related activity. Waveform separation was performed off-line applying principal component analysis (Plexon Systems).

Does anyone know what PCA (Principal Component Analysis) is exactly used for here? My guess would be that it is used to cluster "significant" waveforms, i.e. to identify neurons. But I could not really find reliable resources online.
The role is unfortunately not included somewhere in the paper quoted :(

Welcome to Biology.SE. 1) Please always define abbreviations and acronyms before using them (you use two PCA and PFC). 2) When you include a quotation you must include the citation. 3) The role should be included somewhere in the paper you quote — please don't expect us to read and interpret papers for you. 4) Please don't include "thanks" and "signatures" in you posts. Please take the [tour] and consult the [help] starting with [ask] and then the section on "homework" for details about expectations for users and their questions.

PCA is the simplest way to perform spike sorting, which is necessary when the experimenter has no way of verifying that recordings are coming from single neurons.

Like vkehayas mentions in a comment, they're using it for spike sorting, as you've guessed. This involves both identifying signals from putative neurons (vs noise) and separating different source neurons, when possible.
Plexon's website mentions "Manual cluster selection in 3D feature space using principal component projections, voltage slices in time, or more than 20 other waveform features such as peak, valley, full-width at half maximum, etc." for their software.
There are many, many different ways to sort spikes, some supervised some unsupervised, some using PCA, some using the original waveforms, some using other types of decomposition.
David Redish's MClust is one example which is open source if you'd like to look at some similar software; I assume Plexon's is proprietary but they'll be using similar approaches.


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Why do plants flap their leaves?
Simple question really, I have a plant, that I'm not sure of the species. Every few days I watch its leaves droop (which scares me because I worry the plant has died), but then a few days later I find it's perked right back up. Then a few days later it does the same thing again. I don't think it's dying, in nature documentaries with time lapse I've seen plants do similar things while growing and I was curious what it's called, and why they do it?
It kind of looks like the plants are flapping their leaves, one day they're hanging down drooping, the next they're up in the air.
Photos
There's more to come, but here's a photo of what it looks like right now

Update
I've got a timelapse here I took frames once every hour, for about a week.
https://youtu.be/VE_D3E_Mioc
Two days ago the big leaves were dropping down the sides of the pot

Are you observing your plant at the same time every day? Does it receive enough water daily? How stable is it's environment (temperature, humidity, sunlight, etc.)? A plants leaves can droop and wilt when they don't have enough water, and they will perk up again when they are watered, possibly explaining the movement you described. They can also respond to environmental stimuli. These responses are known as tropisms. For example, plants that grow towards a light source exhibit phototropism.

I observe it regularly in the morning and the evening, I water it every week. But if I water when it starts wilting, then it just keeps wilting, it seems to wilt and perk up on a regular interval of every week or so.

The environment is pretty stable around 70 degrees, same with the humidity, I think. It sits in the window in my dorm room. It gets sunlight for a few hours every day, less than I think I'd like to give it, but it's the best I can do given my limitations of the dorm. Does that help @MikeyC

watch sped up footage of plants growing.

I know, that's what I'm asking about, so you've seen it then? What's it called? @John

this may be helpful https://pubmed.ncbi.nlm.nih.gov/33888615/

Welcome to Biology.SE. Can you add pictures of your plant over time (from the same position) showing the "flapping" and more detail about the pattern/timing? For example, is there any correlation with bright vs. dark days or outside temperature (might be relevant if it is right next to a poorly insulated window)? In general, these sound like "Nastic movements", but the time scale seems slower than I would expect.

@tyersome I can try to start doing that, but I haven't been taking any pictures up to this point, I will add pictures once I get them taken

@tyersome I added a photo of what my plant looks like right now

hi @iggy12345 you can take a look here https://en.wikipedia.org/wiki/Heliotropism and here https://en.wikipedia.org/wiki/Phototropism i know too little about this to make an answer.

Terms to investigate: Water pressures + wilting + water regulation

@theforestecologist I think that's what's happening, but I added a timelapse, just in case, if you add that as an answer, I'll accept it

Strongly agree with all of what @bob1 wrote. In addition, that pot looks like the type of container that is terrible for plants because it has no drainage and also doesn't breathe — this usually results in excess moisture accumulating at the bottom after watering leading to root rot. If you really like the container, I encourage you to put your Coleus into a separate pot (preferably an unglazed ceramic) with a drainage hole. You can then display your plant as you like, but pull out the inner pot to drain off the excess water.

Having looked at the time-lapse:
I suspect you might get a better answer out of gardening on this one, but I think it is entirely water related and that you are underwatering or watering poorly. It could also be that there is some problem with the pot - it may not be draining properly and the water is pooling in the bottom, which can cause root rotting.
What happens when you let a pot dry out is that when you add water, it takes some time for the soil/potting mix in the pot to hydrate. In fact, the potting mix can even become hydrophobic, so even though you see water flowing through the pot, it isn't actually soaking in.
Water won't be taken up immediately, it takes some time to soak into the potting mix, and then be taken up by the roots and transported to the leaves.
If the pot has holes in the bottom, try soaking the pot in water from the bottom once a week (I suggest about 1h - stand it in a tray), rather than adding water to the top, and/or more regular watering.
The plant you have is a Coleus, which are good pot plants. They do, however need regular watering, about every 2-3 days and good drainage to do their best. There is a good guide to growing them at TheSpruce.com.
I would say, the pale colour of the leaves is an indicator that it is suffering in some manner. There are a few possible causes - it possibly needs a bit more sun, but the few hours in your window should be enough. Having said that, the pale colour could also be from nutrient deficiency, particularly nitrogen, or caused by being too dry. The dry edges/tips on the leaves also indicate that it has been too dry at some point in the past few months.


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My bathroom connected scale pretend telling me my total body water level? How could it do that?
Along with a connected watch, I also bought a connected bathroom scale.
Both are giving me plenty of indicators, very extended ones. And sometimes, I wonder where and how they can extract or deduce them.
A simple one: my bathroom scale dares to tell me my total body water level.
The software displays (I've only had the scale for one week) this for my weight:

and this for my total body water:

These two curves don't move in the same direction nor the opposite one.
From what could the total body water be determined and is it reliable?
The scale has so few values about me and I don't see how it could measure total body water.

Welcome to Biology StackExchange! Your scale very likely uses a small electric current to measure the electrical properties of your body. It turns out that water and fat have slightly different electrical properties, which can easily be measured. This is called Bioelectrical impedance analysis and is an established method for estimating body composition. The accuracy depends on the quality of your scale, but also on various other (physiological) factors.

@Domen Thanks a lot! And just for my curiosity, when my scale displays 71.3 kg and 53.3% of total body water level, does it means that I weight "33.3 kg without water"?

Yes. Human body consists of approximately 53 % of water (by weight). Given your weight, you are composed of 38 kg of water and 33 kg of everything else.

@Domen feel free to turn that comment into an answer.

@Domen Yes, it is useful to everyone, and you deserve the answer reward for it.

Your scale exploits the difference in electrical properties of water and fat to measure the composition of your body. This method is called bioelectric impedance analysis (BIA), and it is usually used for  estimating the composition. There exists several other, more accurate methods, such as weighing a person under water (hydrostatic weighing), dual-energy X-ray absorptiometry (DXA), CT, and MRI – the last two usually regarded as the gold standard1.
The basic principle of BIA is to use a small electric current through your body and measure its electrical response. Roughly speaking, cell membranes can be regarded as electric capacitors, water as a good conductor, and fat as a bad conductor. In the simplest model, human body is therefore represented as a resistor and a capacitor in a series ($RC$ circuit), and electrical impedance (combination of electrical resistance and electrical capacitance) is measured at a single frequency (e.g. $50\;\mathrm{kHz}$).
The measurement together with your physical dimensions (height and weight), your age, and your gender – all of which you had to disclose to your bathroom scale – are then put into a BIA formula, which the manufacturer has obtained by calibrating its device with one of the more accurate methods. An example of such formula2 is
$$FFM = (0.34 \times10^4) \frac{h^2}{Z} + 15.34  h + 0.273  m - 0.127t + 4.56 S - 12.44,$$
where $FFM$ is fat-free mass, $h$ body height (in meters), $Z$ electrical impedance (in Ohms), $m$ body mass (in kilograms), $t$ age (in years), and $S=0$ (female), $S=1$ (male).
The accuracy of BIA depends on the quality of the device, but there are also other important factors, such as the environment, ethnicity, phase of menstrual cycle, and underlying medical conditions3.

https://jim.bmj.com/content/66/5/1.10
https://www.ncbi.nlm.nih.gov/labs/pmc/articles/PMC4608267/
https://www.ncbi.nlm.nih.gov/labs/pmc/articles/PMC2543039/


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Average and lowest degrees of kinship/consanguinity among humans?
I would appreciate insight into the average, median, RMS or any similar measure of relatedness among the current world population - and perhaps something about how rapidly this may be changing. A similar question is how un-related any two humans can be: i.e., what is the lowest degree of consanguinity between the two most distantly related people. The context is an exploration of how humans have evolved tendencies toward racism and other in/outgroup distinctions, when all humans share such a large fraction of DNA with each other, very nearly as much with non-human primates, and about half even with fruit flies. Might be some helpful lessons in there!
Apologies if the question is ill-formed, or answer readily available someplace - I've browsed the Web for several years on this topic, and found nothing I could understand..
Accessible material about most recent common ancestor and identical ancestor point seems to indicate a wide range of both methodologies and results, based mainly on statistical simulations since "hard" genetic structures apparently do not persist. MRCA datings based on mitochondrial and other genetics seem to line up with human behavioral modernity, ca. 200 kya. But there seem to be extreme estimates as recent as 2.3 kya, which implies a lot of mobility and high fertility by some not-so-distant forebears (like Genghis Khan). In any case, IAP may be a better starting point for this shared-anncestry question.
I'm guessing that no human is further than about a 10th~12th cousin to any other. Can't be more that 32nd, since 2^33 is more than the number of living humans!
All thoughts, including guesses more informed than mine, will be appreciated.
~ ~ ~ ~ ~
Addendum - tried to post this as an answer, but it was deleted:
MANY thanks to Zo-Bro-23 for the time, effort and creativity to create his response. I hope it is well-indexed for future explorers to find!
In case useful or interesting to anyone,or sparks further contributions, here were/are my main motivations for this inquiry:

Though having working knowledge of physical and natural sciences, and having minored in anthropology at Uni, I have never really grasped current estimations of "most recent common ancestor" and "identical ancestors point." This is probably due to my poor understanding of populations statistics, but may also reflect the huge uncertainty in and conflict between various MRCA and IAP methodologies. So I'm always seeking a simpler, if less precise, way to understand these propositions. Time-dependent mean/max degree of consanguinity seems like such a heuristic.

The ancestor cone, as mentioned in the Quartz article linked by Zo-Bro-23: I've been using the same term for decades, so I suppose it's a natural way to describe something that isn't precisely conic or biconic. For me, the description follows naturally from the notion of the light (bi-)cone in Minkowski diagrams, extending the idea of a photon's world-line to that of a genomic cluster.

I've long wondered about both genetic and memetic (e.g. religion, language, cuisine, art, toolmaking) contingency as they result from and induce changes in the topology of the ancestor cone. There are numerous groups that for geographic, religious or other reasons have been largely independent since we all left the Great Rift Valley (or wherever humanity arose). Having studied a bit of cultural diffusion, I've wondered if genetics, linguistics or anything else might give insight into how often and effectively the occasional Marco Polo or Squanto voluntarily or involuntarily acts as emissary between cultures. Many of these exchanges have apparently had significant cultural influence, and in some cases perhaps genetic as well. It might take very few such, over hundreds or thousands of generations, to lower substantially the degree of consanguinity of all humans.

This does not even count the much larger migrations, both voluntary (e.g. Bering Strait crossings that peopled the Americas), semi-voluntary (the Irish famine that so strongly influenced US culture) or entirely unwillingly (the African slave trade). Another question concerns the influence of sex-linked characteristics in Africans on the general American population, where for several centuries, the great majority of interbreeding appears to have been between White males and (usually unwilling, one imagines) Black females. Perhaps too hot a topic for research?

Pedigree collapse is a conflating factor of special interest to me, as most of my known ancestors belonged to a relatively small ethnic group that favored in-marriage, and (due to low social standing) was not attractive for outsiders to join. So other than couplings of necessity (rape, isolated populations), our cone is probably pretty narrow down to the bottom of the historic timeline. Not directly related by mechanism but probably relevant is the Galton–Watson process, the extinction of family names when a named lineage runs out of (usually male now; perhaps less so in "primitive" matriarchal societies) descendants.

Not long ago, it was popularly believed that explosive population growth since the industrial revolution resulted in the number of living humans exceeding the number deceased. Current credible estimates seem to place the latter at slightly more than 100 bn, - a dozen ghosts standing behind each living soul. Theme for an SF movie?

There is also the question of speciation. It is widely accepted that Homo sapiens and Homo neanderthalensis interbred to a considerable degree. This would, of course, violate pre-cladistic notions of what constitutes a species. (The cited Quartz article could have been titled "Everyone on Earth is actually your cousin - including some non-humans." And if all humans are at least 15th cousins, how far are we from other living families, even phyla?) I believe that barring "lost world" scenarios, we have been alone on the planet for all of historic time, hence for the lives of most H. sapiens. But if we date humanity to behavioral modernity, and plot the ancestor cone with a logarithmic or horizontal axis (or even force it into a cylinder of constant width), the influence of some of these factors on present-day consanguinity might be seen as comparable to those of posited bottlenecks like the Toba catastrophe, climate change, pandemics etc.; and on a smaller scale, founder effects like the peopling of the Pacific islands and Australia.

It's interesting that you say you've been searching/browsing the internet and haven't seen anything (I believe you.) I wasn't even looking for this when I came across an article (a scientific paper) on genetic differences between populations based on geographical distance. I wish I could remember where I saw it, I'd post a link. I don't know just how much literature there is on the subject, but there's definitely some out there.

@cTen, sorry that I took so long to answer. Although I found an article that states the final answer of "15th cousin", I didn't understand the equation that author used, so I just derived my own equation from start. I hope my answer is correct  Please feel free to edit or comment if you think that anything is wrong or if you didn't understand something I went over.

TL;DR: Most humans would be around your 13th cousin to your 15th  cousin
Please feel free to edit the formatting of my equations to make them look better.
Deriving an equation
For simplicity's sake, we are assuming that only "blood relations" count. What I mean by this is, your mother's sister's son will count as your cousin, but your father's sister-in-law's daughter will not count as your cousin. Marriage relations will not be counted, and only birth relations will be.
Let's tackle this step by step. We are trying to find the degree of kinship when the number of relatives you have in that degree exceeds 8 billion. However, let's start by simply deriving an equation to find the number of cousins you have in a certain degree. For example, your siblings would be degree 0, first cousins would be degree 1, and so on. Let's denote this by the variable n. Now, given a person in any degree of kinship with you, you would share an ancestor with them. That is the definition of kinship. Given a person in degree n with you, your closest common ancestor will be n + 1 generations from you. That means that with your siblings (degree 0), your closest common ancestor is 1 generation from you (your parents). That is simple. Now, we want to find out how many common ancestors you have in that generation. Again, this is fairly simple. That would be 2n + 1. This can be understood by the fact that you have 2 parents, each of them have 2 parents, each of them have 2 parents, etc. The number of ancestors is getting multiplied by 2 each time. However, the number of ancestral couples you have in that generation would be 2n + 1/2 or simply 2n.
Now, let's assume that everyone has x number of children. This means that each of those 2n people would have x number of children. The number of children in the next generation would then be 2n * x. Each of those children will have x children, and so the number of children in the next generation would be 2n * x * x or 2n * x2. Hence, the formula for the number of people in your generation with whom you share this common ancestor would be 2n * xn + 1 (since the original ancestors are n + 1 generations above you).
However, we are not done yet. Of these children, some of them might be duplicates. What I mean is, you have 4 grandparents. We have assumed that each of them have x children and that each of those children have x children. So the total should be x2 children in the end. However, you count as both your father's child and your mother's child. This means that there will actually be less than x2 children. However, we only care about you, so we can just subtract the places where you are duplicated. This is essentially xn duplicates. Logically, that's because each of your ancestral generation (except the last one) are having only x children instead of 2x, which is value that we get when we count the two parents. So, the final equation is as follows:
c = (2n * xn + 1) - (xn + 1)
where c is the number of cousins you would have below a certain degree, given that x is the average number of children per person, and n is the degree.
A couple of notes on the equation

We are subtracting 1 to account for you - You are not your own cousin
This will not work for siblings - You will get one less than the actual number

Testing the equation
If everyone has 3 children, you would have 14 first cousins. Your mother will have 2 siblings, and each of them will have three children. This is a total of 6 cousins from your mother's side. You will also have 6 cousins from your father's side. Added to your 2 siblings, that is a total of 14 (6 + 6 + 2). From the equation we get:
c = (2n * xn + 1) - (xn + 1)
Since everyone has 3 children, x = 3.
Since we are looking at first cousins, n = 1.
So the equation is:
c = (2n * xn + 1) - (xn + 1)
c = (21 * 31 + 1) - (31 + 1)
c = (2 * 32) - (3 + 1)
c = (2 * 9) - (4)
c = 18 - 4
c = 14
This means that we have 14 first cousins (if everyone has three children). Since this is what we arrived logically, the equation must be correct.
Although this is not a formal proof, I did go over this in my head for many hours, and it seems to work fine. Please comment if you have any revisions for the equation, and I am more than happy to make an edit.
Some caveats
Until now, we have assumed that everyone has exactly three children. However, this is not the case. Since we only need an approximate for our final answer, we will be using the average birth rate value. This means that most people will have x number of children. Some might have none, some might have many. However, using this value should give us a fairly good approximation.
Also, according to Rutgers anthropology professor Robin Fox, 80% of all marriages in history have been between second cousins or closer. This means that there you will have a lot less cousins than predicted by the equation, since even though we are assuming everyone to have x number of children, two people together are having x number of children, and so the total number of children in a generation will be much lower than predicted. Since inbreeding is so common, there's also a chance that you could be much further from someone than predicted by the equation.
Nevertheless, let's try to do some calculation. Before that, we need to think a bit more about population genetics. In India (where I am from), there is mostly only intermarriage (Indians marrying Indians). Although this is starting to change now, it was more or less like that for a long time. Because of this, there is a very low chance that I will be related to an American. We might have a common ancestor, but we might have to go as far as the first Homo Sapien for that. Because, of this, I might be much more related to a random Indian than a random human being. I have done some calculations for you below, but try experimenting on your own:
Rearranging the equation to find the degree of kinship
We will rearrange this equation to solve for n (the degree of kinship):
c = (2n * xn + 1) - (xn + 1)
c = (2n * xn * x) - (xn + 1)
c ≈ xn (2nx - 1) - We are ignoring the 1 because it is insignificant when xn is large enough
c ≈ (2x)nx - We are ignoring the 1 again because 2n is going to be very large for these problems
log c ≈ (n log 2x) + log x
log c - log x ≈ n log 2x
n ≈ $\frac{log c - log x}{log 2x}$
Since we are making some approximations in this rearrangements, we will need to do some trial-and-error work using the original equation in order to ensure that the answer is correct.
Calculation 1 - How many degrees is an Indian away from me?
Value of x: Average birth rate in India: 2.20 births per woman
Value of c: 1.38 billion
n ≈ $\frac{log c - log x}{log 2x}$
n ≈ $\frac{log (1.38 * 10^9) - log 2.20}{log 4.40}$
n ≈ $\frac{9.1398790864 - 0.34242268082}{0.64345267648}$
n ≈ $\frac{8.79745640558}{0.64345267648}$
n ≈ 13.6722663953
Verifying our answer
Value of n = 13
c = (213 * 2.2014) - (x13 + 1)
c = (8192 * 62218.2127343) - (28281.0057883 + 1)
c = (509691598.719) - (28282.0057883)
c = 509663316.713 ≈ 510 million
Value of n = 14
c = (214 * 2.2015) - (x14 + 1)
c = (16384 * 136880.068015) - (62218.2127343 + 1)
c = (2242643034.36) - (62219.2127343)
c = 2242580815.15 ≈ 2.2 billion
This means that I have roughly 510 million 13th cousins and roughly 2.2 billion 14th cousins.
Thus, the furthest an Indian can be is my 14th cousin.
Calculation 2 - How many degrees is another human being from me?
Value of x: Average birth rate across the world: 2.3 births per woman
Value of c: 7.9 billion
n ≈ $\frac{log c - log x}{log 2x}$
n ≈ $\frac{log (7.9 * 10^9) - log 2.3}{log 4.6}$
n ≈ $\frac{9.89762709129 - 0.36172783601}{0.66275783168}$
n ≈ $\frac{9.53589925528}{0.66275783168}$
n ≈ 14.3882105944
Verifying our answer
Value of n = 14
c = (214 * 2.2015) - (x14 + 1)
c = (16384 * 136880.068015) - (62218.2127343 + 1)
c = (2242643034.36) - (62219.2127343)
c = 2242580815.15 ≈ 2.2 billion
Value of n = 15
c = (215 * 2.2016) - (x15 + 1)
c = (32768 * 301136.149634) - (136880.068015 + 1)
c = (9867629351.21) - (136881.068015)
c = 9867492470.14 ≈ 9.9 billion
This means that I have roughly 2.2 billion 14th cousins and roughly 9.9 billion 15th cousins.
Thus, the furthest that any human can be is my 15th cousin.
Evaluation of results
Although these results show that we are all very close (depending on how you evaluate the results) in terms of kinship, there is another factor to consider. Through a phenomenon known as pedigree collapse, it is estimated that we share many common ancestors. That is, our great-great-grandfather from our mother's side might be the same as our great-great-grandfather from our father's side. This means that most people will be further than calculated by this equation. For example, if two cousins had a child, that child would only have six great-grandparents, not eight. Thus, that child will have less cousins than somebody else. We have also not considered marital relationships, and have only considered birth relations. Hence, the actual answer to your question might vary significantly from the values we calculated.
To learn more about this field, I would recommend checking out this article. It is very well-written in my opinion.

One useful concept that you can use to do your estimations is "genetic distance" as is commonly measured using "fixation index".
Basically what you to is that you estimate/calculate the average number of pairwise differences if you compare chromosomes from people within one population (population A).
Then you compare the number you get with the average number of pairwise differences if you take one person from population A and another person from population B.
If the average number of pairwise differences within population A is 900 and the average number of pairwise differences between a person from population A and a person from population B is 1000 you get the genetic distance as measured with fixation index as "((1000-900)/1000)" = 0.1.
You are asking:
"what is the lowest degree of consanguinity between the two most distantly related people."
Here is a "Cavalli-Sforza" diagram showing how related different people are using the fixation index method:

I think the two most different peoples are some group of African pygmies and people on Papua New Guinea. (I can't find the link right now). One reason might be that Africans have no neanderthal admixture while people on Papua New Guinea have most of all, above 4 percent according to some estimate.
Note that as humans are "diploid", we have two copies of most chromosomes. Therefore you can in principle calculate how closely related you are to yourself using the same method.
Because of for instance "migration bottlenecks" African peoples tend to have the most variation among them.


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How can a minor allele frequency be >50% (reported in GNOMAD)?
I'm receiving a data set to start an analysis. My collaborators ran GATK to find variants from sequencing data, and GNOMAD calculated the minor allele frequencies - and then I'm receiving this MAF data to start the analysis.
When I was looking at what my collaborator called the minor allele frequencies returned by GNOMAD, some of the MAF were >50% (e.g. a MAF could be 70%).
I was looking at the GNOMAD documentation and it says this: https://gnomad.broadinstitute.org/help/faf but I'm not sure I understand what it's saying. Does it make sense that a MAF can be >50%? or are the allele frequencies returned by GNOMAD just the allele frequencies of the reference variant, and extra processing is requiring to find the MAF?
p.s. I can see this question. I actually don't have the data set yet, he was just showing me it and running through what the columns were yesterday, but the column looked like this:
GNOMAD.all MAF (i.e. all ethnicities MAF from GNOMAD)
SNP1    0.75
SNP2    0.002
SNP3    0.4
SNP4    0.1

Could it be that the numbers you saw were showing the frequency as a percentage rather than a [0,1] ratio?

Minor allele critically depends on what the reference population or genome is.  And it also depends exactly how those data are sliced, it would be easier to say if we saw them.
Especially in large multipopulation consortia or aggregation efforts like gnomAD, this can be a pretty important consideration.
If your major allele is defined on something like 1000 genomes or, worse, a nation-specific population, then your "major" allele might quite often have frequency <50%.
These large data-collation efforts don't flip the major/minor allele around constantly, as that would require a significant informatics effort, and you would constantly have to track which major alleles line up with the reference genome and which don't. Probably they do update their major alleles periodically as more data gets sampled, genome builds get updated, and their curators get around to it, but it's unsurprising that at some frequency a specific population might have a minor allele at 80% or something.
It's a little more surprising when globally a minor allele is at high frequency, but it will still happen at some rate.


text:
Understanding the voltage of a living cell

Voltage, electric potential difference, electric pressure or electric tension is the difference in electric potential between two points, which (in a static electric field) is defined as the work needed per unit of charge to move a test charge between the two points. (from Wikipedia)

What exactly is a point in this definition? The voltage of a neuronal cell can be measured for example and a living cell is not exactly what I intuitively understand to be a point. Let's say I have such a cell with an electrical potential $V_m$ of $-80mV$ (is this the same as saying the cell has a voltage of $-80mV$?).
Am I right then that the voltage is a relative measure between the cell and the extracellular fluid? And is the voltage of this fluid then just the symmetric inverse, i.e. $V_{extra}=80mV$? How then can the voltage be measured between two bodies (neuron and extracellular fluid), because the concentration of charged ions might not be uniform across the fluid (or across the cell)? Could the voltage also be measured between two organelles within the cell or between the entire human body and the air surrounding it?

Voltage is always a potential difference, so you need two "points" to define one.
Technically speaking, a neuron doesn't have a voltage and the extracellular space doesn't have a voltage; there's only a voltage between the inside and outside of the cell. However, because technically speaking a neuron doesn't have a voltage, it can be reasonable shorthand to say "voltage of a cell" when you mean "potential difference between inside and outside of a cell". I wouldn't let that imprecision in terminology get you tripped up. In neuroscience we use the convention that the potential difference is with respect to the inside of the cell.
Yes, you can measure different voltages among intracellular compartments, as well. Yes, you can also have voltage gradients within cells and outside cells, though because these are aqueous solutions with dissolved ions, voltage tends to equalize in these compartments quite quickly (until confronted with the capacitance of a membrane). That is, if the concentration of charged ions is not uniform across the inside of a cell, there's going to be a net movement of charged ions inside the cell until things are effectively isopotential.
Measuring voltage with the air is going to be difficult, because air is an excellent insulator. But yes, you could define a potential difference between some place in the human body and something outside. If you've ever gotten a static "shock" you've abruptly discovered that there was a sizable voltage between the surface of your skin and whatever you just touched.
Undergraduate neuroscience textbooks typically have an extensive section on measurement and interpretation of biological voltages; two I would recommend are Purves' "Neuroscience" and Kandel's "Principles of Neural Science". The Wikipedia page "membrane potential" also seems like a good introduction.

Brilliant answer, thanks.


text:
Identity of a spider found on Cyprus
I'm trying to identify a little friendly spider seen in Cyprus. She is brown, around 0.7 inches (2cm) long with white-striped legs, and a small dotted back. This seems like a pumpkin spider, but the head is way too big.

Welcome to Biology.SE. Did you observe any behavior that could be added to your question — for example it looks like your spider might be raising its rear legs.  In addition, it would be helpful if you could add a clear photo from the front that shows the pattern of the eyes — this is an important diagnostic feature for many spiders. (Also, note I edited to (I hope) make your post clearer and correct your tag. Spiders are not insects, but instead in a separate group of arthropods that includes scorpions.)

Following the recommendations from tyersome about eye pattern and behavior I was able to identify this little spider as a Male Araneus Diadematus. They are common garden spiders and harmless, their bite is similar to a bee sting and pose no threat to human life.