text:
Chance for a Female to Inherit an X-Linked Dominant disorder
A few days ago I had an MCQ on a test that read:-

Females have _____ % more probability of inheriting an X-Linked
Dominant disorder.
A) 50
B) 25
C) 17
D) 1

The answer in the key was C: 17%.
I think they solved the question like this:-
Females could have three genotypes,i.e. $X^D$$X^D$, $X^D$$X^d$, $X^d$$X^d$
Each genotype has a 1/3 probability. Diseased females have a 2/3 probability (66.6666% chance).
Similary males have two genotypes, i.e. $X^D$Y,$X^d$Y. Each has 1/2 probability and therefore 50% chance.
And therefore 66.666%-50%= 16.666% , which is approx. 17%.
But that shouldn't be how it works. I mean, how did they assume that females have an equal chance of inheriting the three genotypes mentioned above.
So what I did was that I took all the possible combinations of parents and found out their offsprings. There were six different combinations of parents.e.g. $X^D$$X^D$x$X^D$Y ; $X^D$$X^d$x$X^D$Y ,etc.
There were a total of 24 offsprings(4 from each pair of parents). 12 were males and 12 were females.
Half of the males(6) had the disease and half didn't.
And therefore males had a 50% chance of the inheriting the disease.
9/12 of the females had the disease and 3/12 were normal.
Therefore females have a 75% chance of getting the disease.
That means females have 25% more chance of inheriting the disease.
But what should be the correct answer to this question? Am I missing something?

This seems like a crappy question if you were given no more information.  Men have a 0% chance of inheriting an X-linked allele from their fathers.  Women have a 50/50.  Both sexes have a 50/50 chance of inheriting a particular allele from their mother.  Yes, you are right, you generally do not do a probability problem by listing all the possibilities and presuming they are all equally likely, since that often is not true.

I think that the error you're making is that you're assuming that your 12 hypothetical sets of parents are an accurate representation of the population.
You are however correct that the genotypes are not all equally likely, so I don't agree that 17% is right either.
If you assume that that particular set of parents is true, then you've changed the problem such that you can compute a different probability. But you're asking a different question than the prompt you've been given (assuming that no additional information is given, e.g. the parental genotypes or allele frequencies).
If we instead take the actual pool of alleles and sample from them a la Hardy-Weinberg to make up the genotypes, then you instead have a differently posed question. You can't assume that the dominant and recessive alleles are in equal frequency.
I can't claim to understand the question, and I don't agree with the answer you've indicated (17%) for this same reason. XX people have two opportunities to get the dominant allele, vs. only one for males.
Let's call the frequency of the allele in the population $p$. XY people sample one X chromosome, so their probability is simply $p$.
XX people sample two X chromosomes, so their probability of receiving a dominant allele is $p$ for the first X, plus $(1-p) * p$ for the probability of receiving the allele on the second X (conditioning on not receiving it in the first X, thus the $1-p$).
This yields the ratio
$\frac{(1-p)*p + p}{p}$
for the answer to your question.
For high values of $p$ (1), XX people converge to the same probability as XY people, because there are no recessive alleles:
$\frac{(1-1)*1 + 1}{1} = 1$
For low values of $p$, say 0.01, this ratio is close to 2:1 (100% higher).
In your example, where I think implicitly $p=0.5$, we do indeed observe
$\frac{(1-0.5)*0.5 + 0.5}{0.5} = \frac{0.75}{0.5} = 1.5$,
or a 50% higher odds ratio for XX over XY (or alternately $75\%-50\% = 25\%$ higher, as you write). But that is only true for this specific case of $p=0.5$.
There is a value of $p$ in there where 17% will be the excess probability of women vs. men, but it is actually assuming a different $p$. This would be, similar to what you say:
$\frac{(1-p)*p + p}{p} = \frac{2/3}{1/2} \approx \frac{0.67 + 0.67 * (1-0.67)}{.67}$,
so they seem to be assuming $p=0.67$ (two in three alleles are the dominant allele in the population).
Maybe I've made a basic math error somewhere here, but I think that the difference between XX and XY probability of inheriting the dominant allele has to depend on $p$ (dominant allele frequency).

Yes, you are right about the problem in the solution I proposed. I also noticed that just after I had written it down. I think that since we are at a lack of information we have to assume the most ideal conditions. If we assume that the ratio of the dominant to recessive allele in the population is 1, and that the ratio of no. of males to females in the population is 1 too. And that the ratio of homozygous females to heterozygous females is one too.

Since females carry two X chromosomes while males carry one,  it becomes evident that the 2/3 of the dominant alleles and 2/3 of the recessive alleles are carried by females, and the rest, i.e. 1/3 of each by males. Now since homozygous to heterozygous ratio for females is one, 2/4 females are heterozygous, 1/4 are homozygous dominant and 1/4 are homozygous recessive. Therefore 3/4 (75%)have the disease. While in males, the chance is obv. 50%. Now, females have a 50% higher chance than that of males. Conversely males a have a 33.333% lower chance than that of females.

@MuhammadFahadIqbalKhan yes, this case agrees with both the result for $p=0.5$ that I give and your result given in the original question (if we ignore issues like whether we take the difference or the ratio between XX and XY). What I think I disagree with is whether the $p=0.5$ case is relevant on its own (or as you put it "most ideal").


text:
Cedar-like conifer near Kaladar, Ontario
What species of conifer is this?

Cedar-like leaves
Rocky terrain near Kaladar, Ontario
Sept 29, 2022
Approx 15 feet tall; approx 6 inches DBH

Certainly looks like the Eastern Red Cedar, Juniperus virginiana.  They are very fond of disturbed areas and can be any where from a scrubby bush to a decent tree.  Wikipedia has more info.  Your location is a little north of the distribution maps, but not much, and it is warmer these days...

source: Stack Exchange

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

sort: votes


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What is the function of ocreae on a mile-a-minute vine?
There is a plant called the "mile-a-minute" vine.  (See link below)
https://mam.uconn.edu/species-identification/#trait3
I noticed the plant has ocreae surrounding each branch point but I cannot find any description about the function of ocreae online.
Does anyone have any idea what the function of the ocreae are on this vine?  The only thing I could think of is that it helps collect water and distribute it down the vine towards the root assuming that the plants' roots are below the ocreae.

From an article on Wikipedia (linked to from Persicaria perfoliata).

An ochrea (Latin ocrea, greave or protective legging), also spelled ocrea, is a plant structure formed of stipules fused into a sheath surrounding the stem, and is typically found in the Polygonaceae.

There are no citations, but if correct then the name suggests it's for protection.

I'm going to take the unusual route of explaining my down vote because I realize that, as a new user trying to be helpful, it seems unkind not to. It's a mistake to think that taxonomic nomenclature does anything more than label taxonomic groups. At its best, it does explain function, but often it is simply based on the appearance of a thing. The ochrea resembles what was a familiar enough object: a greave, or today, a shinguard. So the person who named this plant basically named it "like a peach with a greave". The heck if I know why it's like a peach (or a red shank, the other possibility)

... As stated, I gave this a DV, and did so because it's wrong. I apologize for not explaining the DV. I hope you see this, and also hope to express that I appreciate your willingness to help (so please, do so again!), and again, I'm sorry. (A well known example of silly nomenclature is Pieza rhea (2002), meant to sound like "pizzaria", Pieza pi, and Pieza kake. See what I mean? Nomenclature explains when it's well done, but it's all over the place.

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


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Is there an abbreviation for palisade cells?
I want to know if there are any abbreviation for palisade cells and spongy cells?
Just like there is an abbrevation for macrophages (MP).

The more common abbreviation for macrophage is actually MΦ, using the Greek letter phi.

MP isn't really an abbreviation specific for macrophages. In a paper about leucocytes, authors might use MP, but usually only after initially defining that (e.g. ...yada yada macrophage (MP) activity...). So, no. Commonly discussed things have abbreviations (EEG, EKG, EMG, CBC, HR, RR, VT, ASHD, etc.) and very specific things (e.g. CYP51A1) that are too long to repeatedly write out. MP can be "middle phalynx" and a number of other things.


text:
Will eating candy with a lower ph than the stomach increase stomach acidity in the short term?
The average stomach ph is 2.5.
Some candies have a ph that is lower (more acidic) than that.
Will eating candy with a lower ph than the stomach increase stomach acidity in the short term?

Do you have a specific concern about this (your link was about the effect of acidic candy on teeth.) Note that the candy on that list that I'm familiar with is sour (likely due to high citric acid content). Have you researched how sour candy might affect the stomach (you might get an answer right there)? Some background research is a requirement on this site. Thanks.

Well, it works for antacids so...

@DKNguyen - It works with antacids partly because antacids don't ellicit a response that counters the substance increasing the pH (well, Ca++ does cause a slight increase in acid secretion, but it's not clinically significant; it still neutralizes more acid than it stimulates secretion of.) I'm surprised at how limited this view is.

@anongoodnurse And on my end I am surprised why you choose to continue to going around pointing out why others are wrong but then choose not to also simply provide a full answer if you know what's going on.

@DKNguyen - We aren't supposed to answer questions which lack research. I am happy to provide answers to anyone demonstrating even a bit of research, and have always been. We are also "not supposed to answer in comments". That doesn't stop people from comment, posting the wrong answer. Which is worse? Posting the wrong answer in a comment/answer or steering readers to the more correct scenario? This is what I try to do. Way too often, people guess at an answer in comments which is completely wrong.

Ah, I see. So that's why you are witholding an answer. Understood.

@DKNguyen - Do you? Or are you being sarcastic, because I can't tell from those written words.

@anongoodnurse Not being sarcastic.

@DKNguyen - OK, thanks for clarifying.

That's a simple closed chemical system, none of the fluid and reactant escapes, so yes, it will lower the pH of the stomach fluid, to add fluid with a lower pH.

No source? "...to add fluid with a lower pH." The candy isn't a fluid, it dissolves in saliva. Please note that sour candy causes copious salivary secretions, with a pH of around 6.7. Does that affect your answer? It should. As with other organs, the stomach has a degree of homeostatic mechanisms.

realize that with a mouth on one end and an anus on the other, and many, many glands throughout, that the GI tract is not "a simple closed chemical system"


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Is there a non-directed way to probe proteins in a given sample?
I'm familiar with various ways to probe for specific proteins in a given sample(antibody/antigen, aptamers, etc). But these techniques seem to require an understanding of what protein you're looking to probe.
Is there a way to probe for unknown proteins? Some sort of molecule that enables proteins to bind, and through many interrogation reactions would allow us to know what that protein is?

If you have no idea: Proteomics using Mass spectrometry
Mass spectrometry is a powerful
method that (in theory) identifies every proteins in a given solution. However, I don‘t know how robust this method is in terms of sensitivity in the presence of large background signals. Usually, people pre-process the sample, e.g. they separate the raw protein extract in a 2D PAGE (polyacrylamid gel electrophoresis), separating the proteins by size and isoelectric point in a gel. Then they cut the gel into pieces, extract specific proteins and then identify protein fractions using mass spectrometry.
Advanced mass spectrometry methods seem to be able to identify proteomes from imaged tissue samples Ryan et al. 2019
A pulldown assay is also powerful method to pre-isolate unknown components of a protein complex. But for that you need one component or an antibody that binds to a component of the protein complex.


text:
Where do the 2 hydrogen ions in glycolysis come from?
In the reaction for glycolysis, two hydrogen ions are produced as one of the end products. In all the ten steps, I am not able to figure out where exactly these two hydrogen ions are formed. Please elucidate
Glycolysis reaction:
Glucose + 2ADP+ 2NAD+ + 2Pi ----> 2Pyruvate + 2ATP + 2NADH + 2H2O + H+

Welcome to Biology StackExchange. Write the equation of glyolysis with glucose and pyruvate in molecular form. Then count the hydrogens, and they should match. Also, it should be $\ce{2H^+}$ in the products. You may help yourself also with Wikipedia page.


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How does embryology provide evidence for evolution?
I am not a biology student, I just have a profound fascination and appreciation for biology, and from time to time I like to read and watch videos about it.
I was reading about evolution when I came across different evidence in favor of it, like genealogy, fossil records and embryology. However, it isn't quite clear to me as how embryology provides evidence for evolution.
The way I understand is this - and please correct me, if I am wrong here, - when we observe fetuses of different species, we observe some similarities in the development of those fetuses. But what I am not clear about is how exactly these similarities tell us that through the process of genetic mutation, we obtain new species. What am I missing here? I understand how genetic similarities tell us that we have a common ancestor, and how fossil records show the same.
If you can explain this to me, in words that a layman would understand, then I would be very very thankful. I would also like to know other lines of evidences for evolution in somewhat detail then that would be amazing.

I think you're forgetting that evolution means common ancestors in addition to mutation and natural selection.

Similarities of development between species can be interpreted in a roughly similar fashion as similarities of nucleotide sequence. I am confused why you think that a similarity of development could tell you "that through the process of genetic mutation, we obtain new species". Speciation and evolution are rather more than that! I would suggest reading about the field a bit, here is one review paper.

There's an old and mostly discarded notion that “ontogeny recapitulates phylogeny”, and I think that's what you're expressing here. Just forget about it.

This might interest you

See phylotypic stage.

Srinidhi, the video in the above link explains the idea of embryo development and evolution, Did you find it helpful? It's expressed in layman's terms.

When observing fetuses of different species, some similarities in the development of those fetuses are observed.
These similarities suggest that they may share common genes.
Conversely, differences suggest that they may have become a new species through a process of mutation.
Of course, they need to be investigated in detail genetically to see if they are not the result of convergent evolution or adaptive divergence.


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Is TTGATATAT a gene?

Biologists use the sequence of letters A, C, T and G to model genomes. A gene is a substring of a genome that begins after the three-character ATG and ends before the three-character TAG, TAA, and TGA. Therefore, the length of the genome string is a multiple of 3, and the gene does not include three characters such as ATG, TAG, TAA and TGA.

I'm a little confused by the last sentence. Take a genome as an example, ATGTTGATATATTAG. Is TTGATATAT a gene? When the definition says the gene doesn't include ATG, TAG, TAA or TGA, does this requirement apply for every three characters TTG ATA TAT or for any character TTGATATAT?
ps: I don't have too much biology background. I'm currently doing a programming assignment on gene. The definition is all that is given to me. So excuse me if my question sounds really dumb...

Welcome to Stack Exchange Biology. Please finish reading the [Tour] to find out how this site works. It is primarily for "biology researchers, academics, and students", so if you "don't have too much biology background" you should play by the rules to justify posting here. This involves reading the Help on asking questions where you will see that posters are required to research their topic. The quotation you present (citation?) is unadulterated nonsense, as reading the Wikipedia entry for "Gene" would inform you. Please do so. (PS the answer is NO.)

I'd suggest reading more about genome annotation and gene finding for perspectives about these as computational problems. For your specific question, Bryan's answer should sort you out with regard to how codons can translate into protein outputs. This seems like a weird definition of either gene or genome, possibly there is more context in your instructor's questions that is missing.

The premise of the question should be accepted or the question closed. The existing answers don't even attempt to answer the question (the answer is "every three characters").

As a programmer, I'm irked by the fact that ATGATGA follows the "definition" of gene as indicated, yet its length is not a multiple of three.

This is a very lazy (biologically) "programmer's definition" of a gene. It would be like if you found a biology textbook that said "a program in C is everything between main( and )" - maybe for some purpose this definition is useful, but it would be clear to a programmer that it is incomplete and misses too much.
You can read about "start codon", "stop codon" and "genetic code" to understand the concepts they are using for your programming assignment. Using these concepts, there is a specific 3-letter code that says start and codes one amino acid, and every 3 letters after that codes another amino acid, until you reach a 3-letter code that indicates "stop". So, if you want to simply write a program to get an amino acid sequence from DNA/RNA this is sufficient.
For your assignment, you probably want to find what your instructor wants you to define as a gene, not what a biologist would.

This isn't the definition of a gene.  In many organisms, genes include introns, and the regions upstream and downstream of the starts and stops (untranslated regions, usually called 5' and 3' UTRs), as well as promoters upstream of the 5' UTR, are counted as part of the "gene".  And of course, not all organisms always use ATG as the start codon, I'm pretty sure that some organisms have different stop codons.
But most importantly, if you looked up just the coding region of a gene, you'd definitely include the starting codon, because that's usually included in the final protein, and you'd want to include the final stop so you know you aren't looking at a truncated sequence.
That paragraph has nothing to do with how any real computational biologist would work with gene sequences.  It's just pretend.

According to the cringe-worthy biology from your assignment, yes the example that you gave - i.e. TTGATATAT - is a gene. The TGA that's out of phase (TTGATATAT) isn't relevant.
As for what makes the text that you quoted text so painful? I think it boils down to the line:

Therefore, the length of the genome string is a multiple of 3

If you're interested, a small amount of reading about the genomes of humans (or any other organism) should quickly reveal why it's nonsense.

note that a) that conclusion (in the given question) doesn't even follow from the rest of it, and b) i'm pretty sure they mean the gene string, not the genome string

true, my intent was to try to answer the question as posed (while also lending some color to the tone of the answers so far - mine included)


text:
Why can't protein pumps reuse phosphate groups?
I am currently in AP Bio, and our textbook has a diagram of a sodium-potassium pump:

If I am understanding correctly, every time this cycle occurs, an ATP is hydrolyzed in step 2 to produce a new phosphate group. Why can't the pump reuse the phosphate group it released in step 4 from the previous cycle?

The phosphate group must be detached from the protein to cause a change in conformation. The lost phosphate group is drifting in the cytoplasm and cannot be reused without reattachment to ADP (creating ATP), since attachment of phosphate to the protein requires energy.


text:
How can Monstera plant know which leaves to split?
The monstera plant splits some leaves when they put shadow on other leaves behind it, if I understand correctly. But how can the plant know which leave is responsible for the shadowing and therefore which leave to split? Are there other phaenomena similar to this in other plants?

Are you sure it's not just a case of mature leaves always splitting and younger leaves always growing from the bottom? Because you may be mistaking why it splits for how it splits. Many photos show leaves that are split with no obvious shadowing; Just that larger moire mature leaves split automatically.

Plants don't "know" (that I know of) anything, but they do react to many things: hormones, light, temperature, day length, injury, and myriad other factors , many of which I know nothing about. Whatever the case is with Monstera, it's a physiological reaction to some stimulus, not an intellectual one. If I had a few hours, I could give you a layperson answer based on this paper, but I have fewer hours left than you probably do, so have at it!

Thanks for the hint. Obviously, I am looking for a mechanism, yes.


text:
Taxonomy of viruses
There is a distinction drawn in the ICTV code between  "valid names" and "accepted names".
Valid names are those that are published and comply with the rules outlined in the code, while accepted names are those valid names that have been added to the Index.
My question is what is the correct way of introducing new names in a publication for them to be considered valid. Should they be introduced e.g. as simply new genus Xxxxxvirus or should they be supplied with an explicit "tax.nov.": Xxxxxvirus gen. nov.. Are quotation marks needed around names indicating that they are not yet accepted? Should there be any other indication that they are not yet accepted?


text:
Primers spaning exon-exon junctions
I am trying to choose which of two primers is most appropriate to use in qPCR, based on if the primer spans an exon-exon junction or not, where the primer that does span an exon-exon junction is considered the most appropriate.
What exactly is an exon-exon junction? When searching online I still am not sure if there is supposed to be an intron between the exons or not. I believed it to be two exons without an intron between them, however a classmate said "primer one spans over an intron, so it is the most appropriate to use".
Can someone please make this clearer for me. Thank you!

See similar questions elsewhere.
Looking into this paper on primer design, they write this:

It is often necessary to choose the primers from the exon—exon junctions (E-E-jns), the regions of mRNA which include nucleotide sequences from the 5’ border of one exon and 3’ border of the neighboring exon. Selecting at least one primer that represents one such E-E-jn of a particular transcript is important for expression profiling of alternatively spliced variants. The E-E-jn specific oligonucleotides could also be used as probes in microarray experiments addressing alternative splicing and the follow up confirmations by reverse transcription—polymerase chain reaction (RT—PCR) (e.g. Johnson et al., 2003). This type of ‘junction primers’ could be used to overcome the problem of genomic DNA in mRNA samples used in RT—PCR reactions.

In other words, a "junction primer" will be able to work off of cDNA (made from mRNA) but not genomic DNA. Thus you can be confident, if your primer works, that you are measuring expressed mRNA.
Presumably you are actually doing qRT-PCR off of mRNA of a eukaryotic organism, not just qPCR off of genomic DNA. That is why you want the exon-exon junctions, as explained above.
For a step by step guide to qRT-PCR primer design, you can see this.
See also their figure from the paper linked above:


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What are the W and DSM codes for the following bacteria referring to?
In this paper the following bacteria are listed:

Bifidobacterium bifidum W23 (DSM 26331)
Lactobacillus salivarius W24 (DSM 26403)
Lactobacillus acidophilus W37 (DSM 26412)
Lactobacillus casei W56 (DSM 26388)
Lactococcus lactis W58 (DSM 26390)
Lactobacillus plantarum W21 (DSM 26401)
Lactobacillus rhamnosus W71 (DSM 26396)

However, I can't find anything under the NCBI's taxonomy browser or the German DSM system for either the Wxx or DSMxxxxx codes.
Where are the identifying central definitions of these strains?
Thanks in advance.

I only took a look into the DSM numbers and obviously these are not correct. Have you tried contacting the corresponding author?

No, I'll try though. Thanks for the second look.

Update: I've asked the authors.
However, in the paper they say they identifed the strains by matching 16S data in this database:
http://rdp.cme.msu.edu/hierarchy/hb_intro.jsp
But I can't find the referenced Wxx or DSMxxxxx codes in that database under the stated species (you have to open up all the filters to the max and use the ORG:searchterm to search for named organisms).

*they identified the closest species by matching 16S data

After speaking to someone at Winclove Probiotics, who developed these strains (hence the Wxx code), I've found out that they are registered with DSMZ but they're "private" (hence why looking for the DSM codes doesn't work).
The names of the species listed are based on nearest matches of 16S data to species in the RDP database.


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Genes on the reverse strand of DNA indicated by (-) in GFF
In the transcription process, RNA is produced from the template strand of DNA (that is 3'-5') so the RNA molecule produced has the direction 5'-3'.
When working with genes in bioinformatics, there are many genes that we indicate with a (-) sign meaning they are from the reverse (coding strand).
I am really confused here. If RNA is only transcribed from the template strand, shouldn't all genes have the same direction?
I'd appreciate your input a lot!

There is a difference between the forward / reverse (also top / bottom) strand of DNA, and the template / coding strand during transcription. The designation of forward / reverse is rather arbitrary, one of the strands has to be forward (left (5') to right (3')), the other reverse, but it makes no practical difference which goes into which direction. DNA is double stranded and both strands go from 5' -> 3' in opposite directions.
The template and coding strand during transcription are a specific feature of transcribed DNA sequences, and typically relate to features of the 5' -> 3' sequence of the DNA, such as promoters and coding sequences.
For example this short double stranded DNA sequence:
 5' ATTTACGTATGTACAT 3'
 3' TAAATGCATACATGTA 5'

There is an ATG start codon in 5' -> 3' direction on the bottom strand, and this could serve as the start codon of a coding strand after RNA transcription of a protein coding sequence. In this case, the template strand would be the top strand, the bottom strand is the coding strand. Transcription would happen on the top strand from right to left, so in reverse (-).

Thank you! Wouldn't transcription occur on the top strand from 3' to 5', so from right to left? That is transcribing TAC....?

The new stand would be complementary to the top stand, so identical to the bottom stand (with the exception that in RNA T is replaced by U)


text:
How does one prove that a particular bacterium causes a disease if we've found it in the blood of all infected people?
Let's say we have a new disease and are trying to identify the cause. We isolate, though culture, a new microbe from the blood of all infected people. Is it enough to say that it isn't present in healthy people, but in all our infected people, to come to the conclusion that this microbe is the cause of the disease? Why, or why not?
I feel intuitively that using Koch's way of introducing these microbes into a healthy individual to see if they cause the same disease, is a fool-proof way of proving that it causes this disease.
However, some of my students have said that they would like to test the blood of healthy individuals to see if they can find that microbe in it. If not, then the microbe can be said to cause that disease. This seems all right too, except that it only proves correlation, not causation. Does it suffice?

As you're new to this site, you might not be aware that some research is required on your part in order not to get a close vote or a down vote. Providing evidence of a search (not typing that you've searched but found nothing) and editing what you've found into your question is much more likely to get you an answer.

https://pdfs.semanticscholar.org/0361/58a9ea43125e9802bb5e2b5db2118f51d81a.pdf


text:
Location of Kozak Sequences
Are Kozak sequences always found within the first exon? I know that the first exon must be right next to the promoter so that RNA polymerase can start transcription, but just wondering how that would work if kozak sequences aren't always found in the first exon.

Welcome to the site. Please take a [tour] and visit the [help] for more information on this site. Please also note that one of the requirements for this site is some prior research by you into what might be the answer to your question. On that note - what comprises a Kozak sequence (in bases) and how does this answer your question...?


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Molecular Signaling: Why is it more difficult to study membrane-bound signaling molecules compared to soluble ones?
I am reading the textbook Neuroscience (6th ed.) by Dale Purves and colleagues. In one of the chapters (Chapter 7, Molecular Signaling within Neurons), I am reading about the different types of signaling molecules.
The book states that signaling molecules can be grouped into 3 classes: cell-impermeant, cell-permeant and cell-associated signaling molecules. Unlike the first 2 classes, cell-associated signaling molecules are membrane-found, found on the extracellular surface of the plasma mmebrane. Examples of such molecules are cell adhesion molecules such as the integrins and neural cell adhesion molecules (NCAMs).
There is something that the book says which I am unclear about. They say that "Membrane-bound signaling molecules are more difficult to study, but are clearly important in neuronal development and other circumstances where physical contact between cells provides information about cellular identities".
Why is it the case that membrane-bound molecules are more difficult to study compared to secreted/soluble molecules? Any advice is appreciated.

Secreted/soluble/extracellular signaling molecules you can synthesize/purify externally and dump them on some tissue or cells to see what they do.
You can't really do the same with signals that are membrane-bound - you'd need to manipulate their synthesis/trafficking/degradation.


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What percentage of HIV cases are caused by each of the following pathways?
Most studies of STI focuses on sexual intercourses.  For example one study shows that approximately 70% of HIV is caused by male-male intercourse, and 20% is caused by heterosexual sexes.
However, I cannot find reliable data of the percentage of each of the possible pathways. For a list:

injection of addictive drugs
injection of drugs or blood for medical reasons
Sexual intercourse
non-penetrative sexual conducts (such as kissing)
Mother-child transmission
etc.

How do I find the data for the approximate percentage of cases that are caused by each the reasons above?
Note: the percentage data is calculated by the number of cases of one cause divided by the total cases. It can be an estimation, but it is different from the risk per exposure

It'll strongly depend on where you are in the world and which publications you are looking at as a consequence.

World data is the best but any data from the major countries (like G8, G20) would help!

Here's a start, from WHO/European Centre for Disease Control. From the report, for new infections in Europe not including the Russian Federation (or Belgium) in 2019:

50% heterosexual contact (not subdivided by penetrative/non-penetrative contact, but the latter will be a tiny fraction)
21% sex between men (ditto)
13% injecting drug use
0.7% mother-to-child transmission
0.2% "other" (nosocomial, transfusion or use of other blood products)
UNKNOWN 15%

See Table 8 in the full report for a country-by-country breakdown.
Note: these numbers (which are reported on p. 38 of the full report) are for the "WHO European Region", which includes lots of eastern European/former Soviet (including Central Asian) countries, where reporting (not necessarily actually infections!) is heavily skewed to heterosexual transmission (10 to 1). The figure below is for EU/EEA countries only.

Great to see an answer to this difficult question, so kudos! How does this answer square with the EU/EEA average pie chart puting sex between men at ~50% with heterosexual sex trailing by 6-7(?)%. I haven't read anything but the conclusion, but am curious from where your breakdown is obtained and if it's accurate. Is it based on sheer numbers? Is the pie chart not based on numbers?

I'm just quoting values from page 28 of the report. I didn't try to match up numbers between the report and the figure ... Conceivably the pie chart made a mistake in the legend/colour assignment?? Seems unlikely.  With more time, could look at Table 8 and see how the various country-level pie charts match up with the table ...

(Table 8 lists 9525 from sex between men, 8164 from heterosex, 955 from drug users, 167 from IVDU, so maybe I misunderstood the numbers on p. 28 ???)

@BenBolker I'm not finding the numbers you mention on page 28.

Oops, p. 38 ...

oops, discrepancies may be between "EU/EEA" and "WHO Western Region"

Ah, thanks. Yeah, that does seem to be the case.

There it is. Thanks!

Yes EU $\neq$ Europe


text:
How do you calculate the time until the steady-state of a drug?
I encountered a mathematically intriguing conundrum, in that it's related to medicine but is centered around mathematics.
Suppose drug A has a half-life in the body of 30 hours. The patient takes 40mg once per day. How long is it then until the patient then reaches steady-state dosage in the body (within some tolerance interval)?
The answer should be about one week, but I'm trying to understand the math behind "why".

Here's a short simulation that show the process. You can find more about how to simulate a half decay process here
You can notice that the first dose of 40 mg should decay to 20 mg in 30 hours, but the process is cut by the new dose.
The daily oscillation reaches a steady state around the seventh day (you can find small changes in the data, but not appreciable at the naked eye)

import matplotlib.pylab as plt
import numpy as np

ndays = 12
ttot = 24*ndays
dt = 0.25

time = np.arange(0, ttot, dt)
Concentration = np.zeros(len(time))

conc = 0
tau = 30./np.log(2)  ## exponential decay time constant from half-life value
dosis = 40

for k, t in enumerate(time):
    if t%24 == 0:   ## If the time is multiple of 24 hours, the dosis is given
        conc += dosis
    Concentration[k] = conc
    ### update concentration decay
    conc = conc*(1 - dt/tau)

ax = plt.subplot(111)
ax.plot(time, Concentration)
ax.set_xticks(np.arange(0, ndays * 24, 24 ))
ax.set_xticklabels(['%d'%d for d in np.arange(ndays)])
ax.set_xlabel('Days')
ax.set_ylabel('Dosis remaining (AU)')
plt.savefig('Steady_state.png', dpi = 300)

Can you explain where the 0.693 in the calculation of tau comes from?

0.693 = ln 2. Assumed exponential kinetics for half-life

you could use np.log(2) to make that clearer ...

Thanks for the nice plot. Is there a way you could simulate what the effect would be if the daily dosage was instead an "average" over a 24 hour period? That should give you a nice differential equation you can solve explicitly.

Glad you like it. The differential equation you propose is the one in #thegreatemu answer. In that case D = dose/24 (mg/hour). If you simulate it, the dynamic is the same he found analytically. The Euler step can go like this "conc = conc*(1 - dt/tau) + dt*dosis/24"

heracho's answer does a good job showing the realistic timing. However you can do a pretty good approximation with a simple differential equation, where you approximate the daily dose as a continuous input. If $C(t)$ is the concentration of the drug at time $t$, then
$$ \frac{dC}{dt} = D - \frac{\ln{2}}{t_{1/s}} C$$
where $D$ is the dose rate, 40 mg/day. The steady-state condition is reached when $\frac{dC}{dt} \to 0$, which tells you that the (average) steady state concentration is $$C_{ss} = D\frac{t_{1/2}}{\ln{2}} \approx 72.13\mathrm{mg}$$ which agrees pretty well with heracho's plot.
The full solution to the differential equation, assuming $C(0)=0$ is
$$ C(t) = C_{ss}\cdot(1-\mathrm{e}^{-t\ln{2}/t_{1/2}})$$
From here you can see clearly the answer to the "when do we reach steady state?" question is driven by the exponential term, which is negligible by ~5 half-lives.
Having stolen @heracho's plotting script and added the following lines:
conc_ss = dosis*(tau/24)
concavg = conc_ss*(1-np.exp(-time/tau))
...
ax.plot(time, concavg, label='continuous dose approximation')

you can see that this approximation follows the mean of the true concentration pretty well after just a few half-lives.

Very nice, I appreciate the simpler differential equation that matches closely, it's a bit easier to analyze than something that oscillates up and down so much.

Let's take a moment to think about what it means for a drug dosed multiple times to reach "steady-state": "steady-state" would mean that it doesn't matter much if you've been taking the drug for N or N-1 days, if you've reached "steady-state" the concentration of drug is steady from day to day (of course, with a 30-hour half-life, it's not going to be particularly stable within a day, assuming relatively rapid uptake).
It's also important to recognize that simple exponential decay is a scenario that occurs when the fates of particles are independent of each other. Therefore, one way we can think about comparing day N to day N-1 would be to consider how much drug is still around on day N from the first dose, because that's the only difference in the history of doses.
For a drug with a 30-hour half-life, after 7 days you could say 7 days * 24 hours/day * 1 half-life/30 hours = 5.6 half-lives have passed.
After 5.6 half-lives, you could say 0.5^5.6 = about 0.02 or 2% of a drug is remaining relative to the original concentration.
Another way to say that is that the difference at the end of the 7th day between having had the drug for 7 days vs. having had it for 6 days would be that 2% remaining from day 1. That seems roughly reasonable to consider a "steady-state".
This is all assuming simple exponential kinetics, other assumptions will change the nature of the problem. It's also important to recognize that for a drug with a 30-hour half-life given once daily, the concentration will never really be "steady" but will still have a clear oscillation after each dosage, depending on the kinetics of release/uptake.

This seems like a good start, but it could be more clearly framed in terms of build-up of concentration over time. The time scales are the same for loss from steady-state vs. build-up of a monomolecular/saturating curve starting from zero (basic dynamics are $1-\exp(-kt)$), so a half-life describes the time taken to decrease the distance from the current concentration to the steady-state concentration (i.e. after 5.6 half-lives we are within 2% of the steady state).

@BenBolker I was trying to go from a simpler intuitive approach to exponential decay, which is to recognize that every molecule is independent of the others. That means that on the 7th day you can know how much of the first dose is still present, which tells you whether you should care that you're on the 6th versus 7th versus 8th day of dosing. Once it doesn't matter, you can effectively consider that "steady-state", though of course there is still some accumulation forever, we just have to decide at what point we don't care anymore.

This is a very clever approach. To just check how much of the first dose is still in the body at day N, and compare the difference of having taking it or not (N v/s N-1 days).

The first two paragraphs had me thinking this answer had missed the point of multiple dosing, but now I see it's a very elegant solution to the problem (avoiding the work of simulating an ODE with a series of impulses).

@electronpusher I think I probably could have done a better job of setting up the conceptual approach. I'll try to improve it.

I like @thegreatmu's answer, but I think we can get closer to the original
problem.
During the day, the concentration decays according to
$$
\frac{\partial C}{\partial t} = - \frac{\log(2)}{t_{1/2}} C
$$
pretty much like @thegreatmu's equation, but without the term $D$, because
during the day, no medicine is added.
At a fixed point during every day, say at breakfast, the medicine is ingested,
and the concentration instantly increases by the dose $D$. At such moments,
whe have both the low concentration $C_-$ and the high concentration $C_+ = C_- + D$.
Let us measure time in days (the half-time is 1.25 days), and let us take breakfast-time to be the moments $t=0$, $t=1$, $t=2$, etcetera.
The concentration at any time $n-1\leq t < n$ in the $n$-th day is given by
$$
C(t) = \exp\left(- \frac{\log(2) }{t_{1/2}}  (t-n+1)\right) C_+(n),
$$
so just before taking the medicine again, we have the low concentration
$$
C_-(n+1) = \exp\left(- \frac{\log(2) }{t_{1/2}} \right) C_+(n).
$$
and the high concentration is given by
$$
C_+(n+1) = D + \exp\left(- \frac{\log(2) }{t_{1/2}} \right) C_+(n).
$$
From here it is pssible to calculate the high concentration for any day $n$:
\begin{eqnarray}
C_+(0) = D &,&
C_+(1) = D\left(1 + \exp\left(- \frac{\log(2) }{t_{1/2}} \right)\right), \cdots
\nonumber
\end{eqnarray}
leading to
\begin{eqnarray}
C_+(n) &=& D\sum_{j=0}^{n} \exp\left(- \frac{\log(2) }{t_{1/2}} \right)^j
=
    D\frac{1-\exp\left(- \frac{\log(2) }{t_{1/2}} \right)^{n+1}}
          {1-\exp\left(- \frac{\log(2) }{t_{1/2}} \right)}
\nonumber
\end{eqnarray}
and at $n-1\leq t < n$, any moment in the $n$-th day, the concentration is given by
\begin{eqnarray}
C(t) &=&
    D\frac{1-\exp\left(- \frac{\log(2) }{t_{1/2}} \right)^{n}}
          {1-\exp\left(- \frac{\log(2) }{t_{1/2}} \right)}
\exp\left(- \frac{\log(2) }{t_{1/2}} (t-n+1)\right)
\nonumber
\end{eqnarray}
we can compare the current concentration $C(t)$ to the concentration
$C(t+m)$, the same time of day, but $m$ days later:
\begin{eqnarray}
C(t) =
    \frac{1-\exp\left(- \frac{\log(2) }{t_{1/2}} \right)^{n}}
         {1-\exp\left(- \frac{\log(2) }{t_{1/2}} \right)^{n+m}} C(t+m)
=
    \left(1-\exp\left(- \frac{\log(2) }{t_{1/2}} \right)^{n}\right)C(t+\infty),
\nonumber
\end{eqnarray}
where $C(t+\infty)$ means 'at this time of day, in steady state'.
Therefore, we can say that the concentration is in steady state when
\begin{eqnarray}
    \exp\left(- \frac{\log(2) }{t_{1/2}} \right)^{n} < \epsilon,
\nonumber
\end{eqnarray}
where $\epsilon$ is small, for instance $\epsilon = 0.01$ when
you consider 'in steady state' to mean 'less that one percent away from steady state'. This will be after $n$ days, where $n$ is given by
\begin{eqnarray}
    n >  {}^2\log(1/\epsilon)~t_{1/2}.
\nonumber
\end{eqnarray}
In the case where the half-time is $1.25$ days, and $\epsilon=0.01$, we get
$n > 8.3$: just over a week. After 7 days, steady stage is approached up to
2%.


text:
My boyfriend and I found this Object on the beach wondering if anyone could help

My boyfriend and I found this object on the beach and need help Identifying it. It looks like a Shark Tooth not for sure. Found in Gulfshore Alabama on the beach. It looked rusty when we found it but after cleaning it up this is what we ended up with. It is 5 1/2" it feels hollow inside.

it could a shark tooth but to get a better guess of what it may be could you post the size and where you found it.
Judging on how it looks it may not be a shark tooth as usually they keep there shape throughout being in the sea.

My best guess is that it is fairly heavily oxidized iron - probably not a tooth, but I can't be sure.

5 1/2" is massive - would have to be Charcharodon megalodon for that size, which would be fossil. Great whites up to 3" apparently.

Looks non biological to me. Definitely not shark tooth

I ran a Metal Detector over it and it Doesn't show up any Metal


text:
How does red light change the cellular mechanism in cells?
As winter approaches and the amount of sunlight decreases in the northern hemisphere, I have been reading about red light therapy and its supposed beneficial clinical effects.
Yet there is no much explanation for how red light impacts the metabolism and inflammation related to the mitochondria, which is the supposed benefit of this therapy.
Is there any in depth explanation of the impact in the molecular machinery in the body? Does red light impacts/effects change when red light is exposed to different cells/organs?

We ask questions to demonstrate prior research. An example in this case might be to show evidence that red light therapy is effective for something, such that it's appropriate to ask a follow up question about the mechanism.

The claim is that red light therapy decreases inflammation and increases ATP production; my question is the pathway that allows this + the supplementary question.

Okay, but whose claim? What is the source? Demonstrate the research you've done so far.

Sorry for entering the conversation from the side.
I am a little interested in the topic and found this paper.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4126803/
This paper explains here;
The photons are absorbed by mitochondrial chromophores in skin cells. Consequently electron transport, adenosine triphosphate (ATP) nitric oxide release, blood flow, reactive oxygen species increase and diverse signaling pathways get activated.
As my thought, Mitochondria were independent bacteria until they were incorporated into cells, so I don't think it is strange that their activity is activated in response to light.
I believe that the mitochondria had chromophores that absorb red light well out of the wavelengths of light.


text:
How to list coding/noncoding genomic regions linked to significant SNPs?
For QTL analysis in mice GEMMA was used to get P values ("p_lrt" column) for SNPs. GEMMA output (...assoc.txt) file excerpt:
chr  rs           ps       n_miss  allele1  allele0  af     logl_H1        l_mle         p_lrt
1    UNC6         3010274  45      T        C        0.753  -1.871575e+03  9.092954e+00  4.497885e-01
1    JAX00240613  3323400  12      T        C        0.766  -1.871777e+03  9.096464e+00  6.822045e-01
...

Then, drawing a Manhattan plot with qqman R package applies default suggestive/genomewide cutoffs. But if I get it right, P < 5×10^(−8) is a commonly used genomewide threshold Ref1, Ref2.
Then I have to list the relevant coding/noncoding regions linked to these significant SNP (with P < 5×10^(−8)).
How can I do this?
I found a fantastic tool called FUMA
but it seems for GWAS in humans not for QTL analysis.
Update:
In Karl Browman's presentations: pdf (p. 13); pdf (p. 23(=28), 29(=34), 30(=35)).

GEMMA should give you confidence/credible intervals no? Also please expand on what you mean by ‘gene candidates’, that’s a bit of a vague term.

thanks for the comment. I've edited the question.

I would suggest seeing what others have done when using GEMMA. For example, you can see this paper's methods:

We converted p-values to LOD scores and used a 1.5-LOD support interval to approximate a critical region around each associated region, which enabled us to systematically identify overlap with eQTLs.

They further discuss this approach in the supplementary note:

Instead we converted p-values
to LOD scores and used a 1.5-LOD support interval to approximate a critical region around each
association. The LOD drop approach provides a quick, straightforward way to gauge mapping precision
and systematically identify overlap between eQTL genes and candidate QTGs; however, it does not
correspond to a specific confidence interval (e.g. 95% confidence interval).

I would suggest trying something like this to estimate such a "critical region". For a discussion of the relationship between LOD and p-values, a quick search yielded this paper.


text:
What are these mushrooms growing in my garden?
I live in Southern California. Over the last couple weeks, these two different kinds of mushroom have manifested in my garden. They seem to grow rapidly overnight, only to wither and show up somewhere else a couple days later. For reference, in these images they are about 2-3 inches tall. I'm concerned my neighbor's cat may try to eat them.

The second image is a type of coprinoid https://www.mushroomexpert.com/coprinoid.html There are specialiized mushroom ID groups on FB and Reddit.


text:
What are monocytes with vacoules called?
I've heard that monocytes sometimes appear with vacuoles. Do monocytes with a vacuole have a name? If so, do monocytes without a vacuole have a name as well?

Well, if you’re sure that you’re looking at a monocyte, then I don’t think there is a difference in nomenclature here. But normally monocytes aren’t very phagocytic, they leave most of that to when they differentiate into macrophages.
This is further seen in blood smears. A monocyte’s cytoplasm isn’t quite vacuolated, implying that there isn’t very much phagocytosis going on; but is granular due to the presence of lysosomes awaiting fusion with phagosomes, and the lysosomes in this case are actually called “azurophilic granules”.

I think this is a helpful answer, but it would be good to include citations, linked sources, or illustrations.


text:
What is the best estimate of RGB color sensitivity of human eye?
Web has a lot of references for human eye color sensitivity curves. Examples are

This article:
J.J.Vos, Colorimetric and Photometric Properties of a 2° Fundamental Observer (1978) [3]
has a very different dataset that has maximum of the blue channel sensitivity at about 33 times lower compared to the maximum of the green channel sensitivity. This paper also has the red channel maximum higher than the blue channel maximum, and the second graph above has them all the way around.
What is the current best state of knowledge about spectral curves of RGB channels of human eye?
Are there numerical tables that approximate these spectral curves?

What do you mean by "sensitivity"? I think you'll find these charts are all using different measures rather than conflicting in any substantial way. And what is your ultimate goal: what do you want to do with this information?

By sensitivity I mean the amount of perceived brightness per photon of light.
The purpose is research is color perception. I have some ideas about how to improve computer cameras' color perception and would like to have an accurate information on how human vision perceives light.
Corresponding sensitivity curves for cameras are called "quantum efficiency" and are typically published in camera specifications.

If you want to know about perception, then you will want to study perception, not the sensitivity of individual cones, and you don't need to know about different receptor types at all but rather about perceptual sensitivity itself. There's also a big difference between sensitivity in terms of "can you detect a brief, dim flash" versus discrimination: can I tell this color from that color. Both are going to be complicated by conditions in ways that a physical camera is not.

My research focuses on numerical values and numerical processing.
I also don't think that this question is meaningless. One can have a blue light with a fixed intensity and a red light with a fixed intensity and it is possible to compare how bright does a human perceive it.

I'm not saying the question is meaningless, I'm saying it needs to be made precise, and that if you want to know about perception it's wrong to base your measurements on photoreceptor cells in the retina. The perceived brightness of a blue light of fixed intensity and a red light with fixed intensity will depend on a lot: how bright is the room, and what color light illuminates it, or is it completely dark? If completely dark, for how long before the stimulus? Is it a flash or constant light? etc... Perception isn't a camera.

I understand this. For flash vs. permanent light there should be two different spectral graphs. For low vs. high intensity there again should be two different spectral graphs. When the light hits the retina it creates some effect that depends on the wavelength. I am interested in the intensity of that effect depending on wavelength and type of sensing cell (RGB).

"I am interested in the intensity of that effect depending on wavelength and type of sensing cell" - again, do you want perception or retinal physiology? If the former, "type of sensing cell" doesn't make any sense.

@Bryan Krause, isn't the perception adjusted to compensate using 3 different channels which can be amplified or attenuated for accuracy?

@jenniferM.  They use spectral photometry of isolated cells to measure the responses... https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=photoreceptor+spectral+photometry&btnG=

The graph of same amplitudes is called a normalized view, the peak of the three graphs is multiplied to 1.0... It doesn't really matter about the individual cone/rod efficiency because there are different counts and ratios of them as necessary.
The relative spectral sensitivities of the five photoreceptors in human retina, including S-, M-, L-cones, rods, and ipRGCs (A), LED spectral distributions (B), and LED chromaticities in CIE color space. (ref 2015)

Scientists use spectral photometry of cells and measure their response, so that's the field you can study to know the spectral sensitivity.
The brain/ganglions can adjust for differences to give a balanced/optimized mix, and there can be 2 times more of a specific receptor cell type if it 0.5 times as receptive, so the perceived view is more or less psycho-normalized to see white accurately.
Current understanding is that the 6 to 7 million cones can be divided into

"red" cones (64%),
"green" cones (32%),
"blue" cones (2%)

based on measured response curves. They provide the eye's color sensitivity. The green and red cones are concentrated in the fovea centralis . The "blue" cones have the highest sensitivity and are mostly found outside the fovea, leading to some distinctions in the eye's blue perception.
The cones are less sensitive to light than the rods, as shown a typical day-night comparison. The daylight vision (cone vision) adapts much more rapidly to changing light levels, adjusting to a change like coming indoors out of sunlight in a few seconds. Like all neurons, the cones fire to produce an electrical impulse on the nerve fiber and then must reset to fire again. The light adaption is thought to occur by adjusting this reset time.
The cones are responsible for all high resolution vision. The eye moves continually to keep the light from the object of interest falling on the fovea centralis where the bulk of the cones reside.


text:
Biological investigations or Biochemical investigations
I am working on phytochemicals and their antimicrobial and antioxidant activities.
Are these activities investigations called Biological investigations or Biochemical investigations?
What is the difference between them?

For what purpose do you want to use one of these labels?

As the name implies, biochemical relates to the chemical reactions in biological processes. If that is your focus, fine, if you are only interested in the events, inappropriate. But you don’t say, and if you check the meaning of these terms, you don’t need to post here.


text:
What were fed to the rodents in Calhoun's experiments?
From, (https://en.wikipedia.org/wiki/Behavioral_sink) (https://en.wikipedia.org/wiki/John_B._Calhoun) (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1644264/)(https://www.gwern.net/docs/sociology/1962-calhoun.pdf)
As I see, Calhoun does not say what they fed to the rodents. I suspect that they might be foods without all the essential nutrients in enough amounts.
I suspect that answer to this question is not published, but may be found by staff in the institutes where Calhoun worked.
There is a nutrient that can deсrease slowly over generations, omega-3 fatty acids: see google's translation from https://znatok-ne.livejournal.com/86130.html :

During the period of intensive brain formation during fetal development, the human fetus receives DHA from the mother's body. In this case, the placenta selectively absorbs maternal DHA and transfers this PUFA to the fetus. For example, the transfer rate of DHA across the placenta is three times higher than that of ARA (Lauritzen et al., 2001). Due to the intensive and selective transfer through the placenta, the content of DHA in the mother's blood plasma is reduced by half (Broadhurst et al., 2002). We found a similar phenomenon in fish: during the gestation of eggs, which have an extremely high level of DHA accumulation, the content of this acid in the muscles of the fish almost halved (Sushchik et al., 2007). During the period of breastfeeding, the mother's stores of DHA also continue to be depleted, as this PUFA passes into breast milk (Lauritzen et al., 2001). DHA from the blood is selectively absorbed precisely by the cells of the brain, as well as the nervous system and organs of vision (Bazan,. The cells of these organs are able to retain the "captured" DHA for an extremely long time, ensuring its constant concentration. For example, in order to reduce the content of DHA in the brain and retina in rodents need to be kept on a DHA-free diet for two generations (Bazan, 2009).It is believed that the same effective conservation of DHA is characteristic of the human brain (Lauritzen et al., 2001).However, according to some estimates, in the human brain as a result metabolism consumes 2-8% of DHA daily, and these losses must be replenished by the body (McNamara, Carlson, 2006).

What leads you to suspect that?

@JiminyCricket. it is not published together with the 2 linked articles. i have searched https://eprints.lse.ac.uk/22514/1/2308Ramadams.pdf for "criti" and "food" and i have not seen anything about critiquing about the food.

I don't see any reason to think they were fed anything other than the standard rodent chow used in the labs at the time; the second link notes "hard pellets of food" which is the typical form of this feed.
If this food were short of essential nutrients you would expect that all lab rodents, regardless of housing condition, have the same deficiencies. It seems very unlikely to me that this would be overlooked across all studies of lab rodents. In any event, as all animals in the experiment were fed the same food, it's unclear how the results of population density could be explained by some sort of nutritional deficiency, since those results are about different behaviors at different densities while the same food is used for all.

"it's unclear how the results of population density could be explained by some sort of nutritional deficiency, since those results are about different behaviors at different densities while the same food is used for all" - i have added explanation about it to the question.

@qdinar Okay, except your argument has nothing to do with population density.


text:
drug-dna concentration
I want to understand how you calculate the final concentration of a Drug-DNA complex. I tried to mix equal concentration and volume of drug and DNA to form a complex and tried to see the absorbance spectra using UV-VIS but saw very little peak for drug. I think I am doing something wrong to calculate the concentration.
Here is what I did.
I mixed 500uL of 20uM of DNA to 500ul of 20uM of drug. I expect to see a large absorbance peak but I see very small peak at the wavelength of that drug. My aim is to have a drug-DNA complex of 20 uM. Could anybody please explain to me how to calculate the final concentration. Any reference articles so that I can understand are greatly appreciated. Also, I want to understand the job plot where we can find the binding of the drug to DNA.

Hi, this isn't the right place for wet-lab trouble shooting. Biology SE is probably better

Your ratios assume 1:1 DNA:drug stoichiometry. Is that correct? What is the drug, and how is it expected to interact with DNA? Is it an intercalating agent? Is the DNA a single sequence of a fixed length or is it a mix of sequences of different lengths?

Thank you for your comment. I want to check the number of base pair ligand is interacting with. DNA is double sequence and of fixed length. The ligand intercalates with DNA. I want to know what the feasible way is to do it.


text:
Why are homologous chromosomes similar?
I was recently studying gametogenesis (I'm a medical student), and I was thinking about meiosis and fertilization. So on the surface it sounds simple, 23 s-chromosomes from the father and 23 from the mother, and together we have 46 chromosomes and 23 "homologous pairs" of autosomes. I already knew beforehand that each chromosome has 2 copies, but today was the first time that I asked "but why are they similar"? The father and mother should be genetically non-identical, but somehow the maternal and paternal copies of chromosome 1 for example are similar actually, enough to warrant them being called homologs of each other. So why is that? I have some sneaking suspicion it involves evolutionary genetics, but I might be wrong.
Any response is appreciated!

related: https://biology.stackexchange.com/questions/98047/in-our-23-chromosome-pairs-do-the-2-members-of-the-pair-have-distinct-or-virtua

They are similar because, on average, your genome is 99.9% identical to other humans. So, while there are traceable differences on each chromosome that can be mostly mapped back to each parent, the sequence of the chromosomal pairs is nearly the same.
Each chromosome has a specific length and set of genes. Except in rare cases of intra-chomosomal recombination (and the special case of the X/Y chromosomes), each chromosome in the pair will encode the same genes, which will be nearly identical except for the parent-specific differences, and (rare) mutations that may arise alter which are unique to the progeny.

karyotype image from NHGRI
These two questions give more background about homologous chromosomes:

What are homologous chromosomes?
In our 23 chromosome pairs, do the 2 members of the pair have distinct or virtually identical sequences?


text:
Why do catabolic reactions release heat despite that breaking bonds absorbs heat?
According to Campbell, the definition of a catabolic reaction is:

Some metabolic pathways release energy by breaking down complex
molecules to simpler compounds. these degradative processes are called
catabolic pathways, or breakdown pathways. ... Energy released from
downhill reactions of catabolic pathways can be stored and then used
to drive uphill reactions of anabolic pathways.

The book also mentions that:

It is important to realize that the breaking of bonds does not release
energy; on the contrary, as you will soon see, it requires energy. The
phrase "energy stored in bonds" is short-hand for the potential energy
that can be released when new bonds are formed after the original
bonds breaking, as long as the products are of lower free energy than
the reactants.

Can someone help me link these two ideas considering the apparent "contradiction"? How is it that catabolic pathways, which release energy, work on breaking bonds, which require energy? Are catabolic pathways energy-releasing because of the "net" energy difference because the heat required to break bonds exceeds the energy required to break them? And how are those bonds broken? I think the book was attempting to answer my question in that second excerpt, but I could not fully grasp it from their wording. Thank you!

What do you mean by "breaking bonds absorbs heat"?

I mean that energy is required to break bonds, so how is it that catabolic reactions release energy?

Please define “catabolic reaction”. As far as I am aware the term “catabolic” only applies to metabolic pathways, not individual reactions. And if you read something please quote it verbatim and provide a source.

If it takes energy to push a boulder off a cliff, does the boulder have more or less potential energy at the bottom of the cliff than when it started?

I completely understand your confusion, because this is – in my opinion – a concept in biology/biochemistry that is often not well communicated, and explained without properly involving chemistry. It is true that breaking a bond is always an endothermic reaction, and creating a bond is exothermic. But be careful, this is true for all types of bonds! See, when ATP is hydrolyzed, this is not simply "breaking one bond in ATP", because there is also formation of new bonds between $\ce{P_i}$ and water. This "energy" is also called hydration energy/enthalpy. So, why is ATP hydrolysis ...

... exothermic? Because formation of bonds between $\ce{P_i}$ and water releases more energy than it is required to break the bond in ATP, therefore the net enthalpy change is negative. (Actually, you can make this story more precise: Two covalent bonds are broken ($\ce{O-P}$ and $\ce{O-H}$), one covalent is formed ($\ce{O-H}$), and bonds between water and $\ce{P_i}$ are formed ... But the main idea is the same: Bond formation releases more energy than bond breaking spends.)

You can read more about this concept here.

I see now, thank you so much for your explanation!

Once again you ignore my point about the term catabolic being applied to pathways. Your quotation from Campbell purporting to define "catabolic reaction" does no such thing. It refers to "catabolic pathways". A pathway is a series of reactions. The two statements refer to different processes — in the first to pathways, in the second to individual reactions. Therefore your question is invalid as it stands and should be closed. Please pay attention.

I had simply forgotten to rename the title of my question... I was not aware of the difference between catabolic reaction and pathway in the beginning. I didn't notice the usage of different terms and just put everything collectively as "some catabolic stuff" in my thought process.

The book is right, but you are missing quite a big chunk of information inbetween. In a sentence, catabolism is fairly complex and it cannot be seen reaction by reaction but as whole. Because, in order to produce ATP from glucose so that it can be used to drive reactions in anabolic processes, the metabolism of glucose undergoes multiple processes (or phases) with distinct goals: glycolysis, krebs cycle and oxidative phosphorylation (OP).

Glycolysis, or the lysis (as in breaking down) of glucose is a preparation phase. In this phase, glucose is metabolized in a way of preparing it to eventually generate energy. This phase barely generates any energy (net +2 ATP per glucose molecule), but the initial molecule (glucose) undergoes quite a transformation before being converted into pyruvate.

Krebs cycle is a continuation of the preparation phase where, essentially, carbon is converted into electrons. In other words, one full cycle in the Krebs cycle entails Acetyl-CoA (2 carbons) entering the cycle and the full oxidation of 2 carbons into CO2. With this cycle, several molecules of FAD and NAD+ are reduced into FADH2 and NADH, respectively, using the electrons of the oxidative reactions. Per glucose molecule, only 2 GTP molecules are produced as well.

OP is where energy is effectively generated. O2 is reduced into H2O, NADH/FADH2 are oxidized into NAD+/FAD and ADP is converted into ATP by harnessing energy from a proton gradient inside the mitochondria. Per molecule of glucose, and depending on efficiency, 30-36 molecules of ATP are produced in this phase.

Of course, multiple reactions in these processes release energy (-ΔG'o), while others actually take energy (+ΔG'o). The only way the cells can make up for this is by adjusting the concentrations of products and reagents to drive the reactions in the direct reaction and not the other way around by resulting in a negative ΔG, according to the following equation:
ΔG = ΔG’o + RT * ln([products]/[reagents])
By doing this, metabolic reactions flow in a way that the overall process of glucose metabolism will ultimately result in energy generation, despite some of the reactions barely generating any energy, while some others actually take up energy.


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Where can I find the exact base pairs for a specific gene, e.g. SRY (sex determining region Y)?
Per a quora answer, the Sex-determining Region Y (SRY) gene contains 14 bp. I searched the gene on NIH and genenames and get just the info about the gene itself.
Where can I find those exact 14 base pairs for the gene?

First of all, the information on Quora is wrong: The SRY gene transcript is 828 nucleotides long and encodes for a protein of 204 amino acids. 14 base pairs would only code for 4 amino acids which is not really a functional protein.
You can download sequence information from Ensembl (or also the NCBI if you like, the datasets behind it are the same). Go to the Ensembl Website choose human and type in the gene you are looking for.
You will get back a page which looks like the following:

On the left side you can now either click on "exons" or "cDNA" to get a closer look on the sequence:

This is what you get when you choose cDNA. It shows the complete transcript in the first line, the processed, protein coding sequence in the middle and the protein sequence below each triplett. You also have a download button for the sequences, if you press it, you can decide which information you want to have (full transcript, mRNA...) and the format (simple text or annotated rtf file):

Choose the information you are looking for and then save it to your computer.


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What type of bug is this? Found under a blanket
I'm a bit worried as we found a few of these bugs under a blanket in a spare bedroom. It was very small (3-3.5 mm) and rust/brown in color with a tubular/long shape. There seemed to be a nymph next to it (looked like a small worm). I live in France and autumn is approaching. I could only decipher shape when zoomed in with a photo. Looks really small with the naked eye. I really hope this isn't a bed bug as I have been doing LOTS of global travel in the last 6 months.
Thanks for your expertise. I also found one crawling on the ceiling in the same room. Thank you for your expertise.

@ commenters. Comments are not for answers. They cannot be downvoted if incorrect, which is especially problematic on species ID posts and even more so when most of the above comments are wrong. This is not a black beetle, is not a weevil, and is not a Cardinal beetle. It's more likely a pest (likely some type of grain beetle or related) that I would recommend the OP worry about.

Also, FYI: See Insect identification - Is this a bedbug? for some images of bed bugs.

Comments are not for extended discussion; this conversation has been moved to chat.


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How does evolution work at the level of a caterpillar mimicking a snake?
I am referencing this video, where a caterpillar turns into what looks like a snake when it gets frightened, presumably to ward off predators.
Now how can this evolve?
I majored in Molecular Neurobiology and studied evolution, and random molecular evolution makes sense to some degree. Every now and then there are random mutations, sometimes which affect gene / cell-signaling pathways, which could cause reproductive advantages, leading to evolutionary adaptations. But to go so far as to be able to mimic an external structure like a snake, how is that possible? I don't see how that can randomly evolve.
It is as if as a species we have a plan on what we want to become, and we slowly realize that plan by somehow tuning the genes to, say, look like a snake. But that is just me trying to fill in the gaps with imaginative thinking, how something like this can evolve. There are many other examples of incredible things evolving, but this one demonstrates the question perfectly.
Briefly, can you explain how this sort of thing could evolve?

Because vision is not perfect, a predator could confuse a caterpillar for a snake under different conditions at different distances. is it cloudy out, is the caterpillar in shadow, partially obscured. At every step of looking more like a snake the caterpillar is less likely to be eaten in more and more situations. this is fairly easy to see because there are a variety of caterpillars that resemble snakes to varying degrees. Many are just simple spots that look like eyes. Even if it only fools only a few predators under only a few conditions it is still an advantage.  This is why mimicry in general is so common.

Consider the certainty of a predator, if the predatory is just confused about whether something is or is not a snake, it can still be a big advantage. That might be a snake but that other thing is definitely a caterpillar. Which one is the predator going to investigate the possible threat or the easy meal? Then the caterpillar that does not resemble a snake gets eaten and the poor mimic gets spared. Prey selection is a risk assessment and a certainty assessment at the same time, thus is exploitable.

Mutations are random; natural selection is not.
Caterpillars are eaten by animals like birds. If you get eaten as a caterpillar you don't get to reproduce, so there's a strong selection for anything that makes you less likely to get eaten.
Even a very basic snake-like appearance (maybe just a color) might cause some survival benefit - maybe not every caterpillar with that gene survives, but over generations more snake-like caterpillars survive than non-snake-like, so the population looks more snake-like.
I don't see the snake-like behavior part as any different evolutionarily from the appearance part, or distinct from any other defensive behaviors that animals make, such as posturing to look larger, etc. It's just a behavior that's unlikely to be beneficial until after the other appearance changes. No planning is necessary at any stage, just selection on characteristics that appear.
Be wary, too, of selection bias when thinking about the evolutionary likelihood of any one thing: you observe the things that did evolve, not all the things that are possible.


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Why do highland/alpine plants require a drop in night temperatures to thrive?
There are mountain plants which require a drop in nightly temperature (many Nepenthes, Heliamphora and orchids for example). A non-specialist explanation is that the plants die of "starvation" if you do not provide cold nights, that During warm nights they metabolize their stored energy reserves much faster than they're adapted to do in natural environments, leading to overexpenditure and eventual death.
Is that plausible and if so can it be expressed in scientific terms?
Would extending the photo period be a simple way of counteracting this?

What research have you conducted to try to find an answer? As you have credit from another SE community you will be aware that this is requirement for posts.

There's a possibility this might fit on [gardening.se] if it doesn't work here. Nonetheless, interesting question, perhaps show your attempt to answer  - anything you found on the subject and where it lead you.

There's this paper (https://www.pnas.org/doi/10.1073/pnas.0914299107) that finds starch accumulation during the daytime is basically linear and more importantly, the plant then proceeds to use up those stores until dawn when they're basically depleted. I had already assumed that because it makes sense for an equilibrium state to evolve. This seems to support the logic behind the starvation hypothesis, I haven't found anything looking at the starch degradation in alpine plants however. I really want to know if there are metabolic processes that can't happen at all without a temperature drop.

At first, I also thought that it might be an equilibrium problem for metabolites and revcheckd the Michaelis-Menten equation.
However, the metabolic reaction stops (or appears to stop) because
-All enzymes are lost or inactivated.
-All substrates are lost.
-The enzymatic reaction reaches an equilibrium
All of the substrates are lost.
If the temperature is around 10°C, the enzymes are not completely deactivated. Nor is the enzymatic reaction in equilibrium, since the starch will continue to be broken down until dawn.
So I thought there is not enough CO2 in the material.

That's an interesting explanation.
I don't know of a definitive paper, so I write here only a guess.
Perhaps in alpine plants that are stressed by high temperatures at night, abscisic acid is produced and the stomata close, preventing CO2 uptake and photosynthesis.
CO2, the material for photosynthesis, is taken up by the leaves by opening the stomata at night.
Abscisic acid, a plant hormone that closes these stomata, appears to be synthesized in response well to stress responses.
https://www.frontiersin.org/articles/10.3389/fpls.2016.00571/full
In common plants, it seems to be synthesized in response to dryness, high salt concentrations, and low temperatures, but alpine plants may have a mechanism to recognize high temperatures at night as stress.
About abscisic acid, it is still under research, especially its receptors and signals.


text:
How does the body avoid making an immune response to self-antigens?
The body contains antigen-detecting and presenting cells (APCs) including leukocytes and cytokines each having their characteristic HLA genes consisting of different recognition sites that detect the foreign molecules. Although the immune system can respond to a huge amount of different proteins or other antigens, self-antigens are not attacked by the immune system. Why not?

Check the terminology you're using, like "antigen", and see that you are using it properly. As-is, I think someone can guess at what you are writing here but the way it's actually written is nonsensical. For example, do antigens "attack"?

related, but not quite duplicate: https://biology.stackexchange.com/questions/64897/autoimmunity-negative-selection-of-t-cells-apc. https://biology.stackexchange.com/questions/14067/autoimmunity-and-central-tolerance. Not sure if there's a good duplicate on self-tolerance that I missed though

@hali--the phenomenon you're asking about is "immune tolerance", or more specifically, "self immune tolerance". Those are helpful terms to google

Cytokines are not cells, they are proteins.

short answer, because your thymus tests every antigen binding protein against all your bodies antigens , helpful video, https://www.youtube.com/watch?v=LmpuerlbJu0


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What type of brown mushroom is this?
What mushroom is this? Maybe some type of Armillaria?

Welcome to the site, where in the world is this photo located?

Hello, it's in Austria, close to Kufstein.

The ID is incomplete because we can't see the profile of the gills and the stalk.

I added another image


text:
Understanding the names of microorganisms of the normal body flora
I'm taking an introductory course to microbiology and immunology, and i have been required to memorise the following microorganisms of the normal flora.
I'm trying to understand before I memorise, and I need your kind help because no textbook or any resource on google had helped me. I am trying to link the etymology and/or characteristics of the microorganism to its anatomical locale, for example: Heliobacter pylori --> helical bacteria, pylorus region of the stomach, or enterococci --> Entero = small intestine, cocci = circular. Some can be found out via a simple google search but the others cannot, can you help me link/understand it? It doesn't have to be anything so jargonic, just clever ways to facilitate memorisation, for example: lactobacilli --> lacto --> lactic acid --> acidic environment of the vagina and bacillus = rod shaped.
Many many many thanks in advance!

While the name of a microorganism sometimes reflects its shape, that is not always true. Additionally, the name doesn't necessarily reflect its location in the body.

There isn't any clever way to memorize where (everything/whatever) lives, e.g the ubiquitous Candida albicans which basically means white white. Sometimes it's just the hard work of memorizing that gets you through, if that's what you're required to do.

As mentioned in the comments to the question, binomial names for species are odd ones and don't necessarily relate to anything to do with either common location or a function of the species. However, a lot of the common bacteria were named fairly early on in the process of classifying species at a time when it was fashionable to name them based on a function or a characteristic of the species, much in the manner that Carl Linne did, when he set up the binomial system.
Here's my table of the meanings of the names for the in the list above:

First part
definition
second part
definition

Strepto
twisted chain
coccus
ball

Haemo
blood
philus
loving

Neisseria
after Albert Neisser

Candida
white

Actino
ray (of light)
myces
fungus

Staphylo
bunch of grapes
coccus
ball

Coryne
club shaped
bacterium
bacterium

Propioni
synthesizes propionic acid
bacterium
bacterium

Entero
relating to the intestine
bacteriaceae
family of bacteria

Entero
as above
cocci
ball

Bacter
representing bacterium
oides
like

Bifido
divided in two
bacterium
bacteria

Clostrid
spindle shaped
ium
suffix

Pepto
cook
streptococcus
see strepto...

Lacto
milk
bacilli
rod shaped

Myco
related to fungi
bacterium
bacteria

As you can see the names sometimes make sense in an immediate manner (e.g. Streptococcus = "twisted chain of balls" and Staphylococcus = "balls in a shape like a bunch of grapes"), but don't always - for example Bacteroides means "bacterium that is representative of bacteria" - which only makes sense if you know that this is probably the most abundant species found in the gut. Also note that for  Actinomyces; at the time it was named it was thought to be a fungus - hence the "myces" part. The colonies are fuzzy, like a fungus and form corrugations that, with a bit of imagination, look like rays/beams - hence the "Actino" part; so you kind of need to also know a little of the history to understand some of the names.
As far as I know there is no system from the names to work out the location of the organisms in terms of their names, the closest you might come is to know whether they are anaerobes or aerobes, and that will give you at least a hint of their location(s). However, this won't work for all species, and some are not bacteria, but yeasts, which are eukaryotic rather than prokaryotic.

this is so beautiful, I can't thank you enough! highly appreciated!


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Origin of holes at 800 m depth in the Mediterranean
From 8 to 12 small 2-3 cm holes in the bottom mud are forming rounds with a diameter of 20-40 cm. No tentacles or other body parts have been observed. Mediterranean sea, 600-1000 m.
What are they?

Where's the picture from? What makes you think you're looking at biology?

-The picture is from subsea remote operated vehicle. It doesn't look like an occasional structure in mud. There are many of them with the same pattern.

Is it your picture, or someone else's?

I've made it, yes

I take it the 20-40 cm is the diameter between the green lines and the 2-3 cm holes are each of the 9 shapes?, or is it that the 9 shapes are 20-40 cm across each? I'd suspect a moving mollusc or something similar, or perhaps a fish hunting for sub-surface feed.

50 cm between the lines

Can you comment on when these formed (that is, did you observe this ground without the holes last year, but this year they appear? Or is this the first time you see them and they could have formed many years ago?) Can you comment on how solid or soft this ground is (does it leave footprints like sand, or is it harder like dirt?) Have you seen several of these rings, or just this one?

1)Have no idea wether it's appeared this year, but I think it should be something usual. Something, that should be known by zoologists. That's the first time I see such structures. 2) Ground is very soft. It's a mud or dust. It's lifting up with ROV propellers. 3) There are many of rings. Sometimes there are two of them (like 8) or even three. –


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Unbounded synaptic weight in Hebb’s rule
I am new to neuroscience and apologies in advance if this is a very trivial question. I want to model the synaptic weights of neurons and using the discrete Hebb’s update rule
$$w_{n+1}=w_n(1+c)$$
That is whenever two neurons fire in succession the synaptic weight is increased by a factor c. But here the synaptic weights are unbounded and grow to infinity. Is there any other simple discrete update rule which takes care of this. I came across Oja’s rule but it seems to depend on postsynaptic and presynaptic activity

Are you looking for a rule based on a biological mechanism, or simply one suitable for simulating biologically-motivated network activity? Oja's rule certainly seems like it would be an answer, but it's not clear to me why you suggest it depends on "postsynaptic and presynaptic activity", or why that would be a problem, per se.

Actually, in my model there are only two states of the neuron. Either it fires or it doesn't.  So I don't have a measure of the post or presynaptic activity. Do you think I can use Ojas rule in this setting?

My understanding is the only difference between Oja and Hebb is Oja scales the weight vector to have length 1.

Do you have a reference for this?

https://en.wikipedia.org/wiki/Oja%27s_rule perhaps as a start? Or go right to the source: https://link.springer.com/content/pdf/10.1007/BF00275687.pdf


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In the female reproductive system, is the labia minora / labia majora / labia as a whole the female counterpart of the scrotum in male?
I am confused about which labia is the counterpart of the male scrotum. Any help would be appreciated. My first question so pls try being more lenient with downvotes.

We have an expectation here, as is common across StackExchange, that questions contain evidence of prior research. An example here might be quoting from (and citing) a textbook or other source like Wikipedia that states this homology but is unclear about the details you request. We also ask that questions be free from "meta" information like that it's your "first question": we're building a repository of Q&A here, so ultimately who asks a question isn't supposed to matter, just the content itself; other text is just noise for the next person who finds this Q&A via Google or elsewhere.

https://www.kenhub.com/en/library/anatomy/homology-of-the-male-and-female-genitalia


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Is there a way to relate the OD to cells/mL without doing a standard growth curve?
I am helping out with an experiment with multiple bacterial cultures (>20 species). I need to a very specific concentration (cells/mL or CFUs*/mL) for this purpose. Unfortunately it appears that standard growth curves (OD** vs. CFU/mL) are not available for these cultures. I am not in a position to generate them afresh either given the sheer number of cultures I have to work with and how laborious the growth curve experiments are.
Given these constraints, are there other reliable (and needless to say fast and accurate) ways through which I can find out how many cells/mL (or CFUs/mL) I have in a given bacterial culture at a given OD? All the more better if the method is parallelizable.
I came across this study (Robust estimation of bacterial cell count from optical density.) where they suggest using silicon microspheres with dimensions similar to E. coli to reliably estimate ODs, but I don't know what the cell sizes for the bacteria I am working with are. In this case, what are some easy and accurate ways in which I can estimate the average size of these bacterial species?
* - CFU - colony forming unit
** - OD - optical density

Do you have access to a flow cytometer? That would be one way of making direct counts of a culture. And, of course, there's always the good ol' hemocytometer.

You really need something tangible to tie back to the OD, whether it's CFU, MPN, or direct cell counts. Without some kind of standard curve, you're basically just guessing. If you have a plate reader, you could do your OD dilution series on that, and follow up with a quick drop plate assay (basically a spot titer for CFU) to get you in the ball park (probably within half a log or so). Should be easy to blow through 20 bugs in a day or so (three or four days if you want a few replicate measurements). Just realize your plate reader OD will not be identical to your cuvette OD.

I would argue that performing a full growth curve isn't strictly necessary to obtain a standard curve to convert between OD and CFU. As long as you're collecting cells in a standardized way, a standard curve generated from a simple dilution series of cultured cells can prove quite reliable.
For example, you can harvest cells from your culture in early stationary phase and generate a 2-fold dilution series, collecting OD measurements for each dilution until you get below the threshold for which your OD reader can generate accurate OD measurements. Then switch to 10-fold dilutions and plate those for CFU counts. You can then back-calculate the CFU/mL present at each of the OD measurements for your standard curve.
The same concept can be applied to overnight colonies suspended in normal saline or PBS. Pick colonies from an overnight streak plate and suspend them in saline until it's turbid, with an OD reading >1.0. Do the 2-fold dilutions to get multiple OD readings until you bottom out, and plate for CFU. This is generally how innocula are standardized for determining MIC values in broth dilution methods, and the range of acceptable CFU concentrations for those methods is often quite narrow.
Whatever method you use, replicate it several times to make sure you're getting consistent conversions, stick with that method for your experiment, and always verify your experimental CFU.

You can estimate cell size through a microscope. However cell size can vary significantly in different stages of growth, or growth under different conditions.

@markur I actually did ask about this also.

ah I see, I deleted my comment


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How to avoid mutations when performing Gibson Assembly (or generating amplicons during PCR)
More often than desired (about 75 % of the time), when building plasmids via Gibson Assembly (~ 5 kb plasmids; from a maximum of 2 fragments) we obtain clones with several random point mutations all along the plasmid (from 1–3 point mutations to 6+ depending on the day, without specific region targetted).
Since we use the NEBuilder HiFi DNA Assembly kit and since there doesn't seem to be any specificity as of where those mutation are found, I suspect that they arise during the PCR reaction when producing the amplicons.
We use the Phusion High-Fidelity polymerase to generate the amplicons from ~1 pmol of template in 50 µL of PCR reaction (or split in 5 x 10 µL since working with reduced volumes seems to improve the efficiency of amplification) and 30 cycles.

Is this a normal/common issue or does this result indicate that something wrong is happening in our experiments?

And more importantly, any idea of how to prevent such problems?

I have in mind:

Reducing the number of cycles (how low can one go?) and/or increasing the concentration of template (related).
Changing polymerase (but for which one and shouldn't Phusion High-Fidelity be one of the best suited?).
Changing other parameters or conditions (but which ones?)

Any bullet-proof experience on that? Thanks
EDIT:
Changing the DNA polymerase from a Phusion HF to the Q5 suggested in the NEBuilder kit manual (suggestion that I had overlooked) completely solved the problem.
Rem 1: Mind that the elongation time must be slightly increased to amplify "long" fragments with Q5—probably a side effect of its higher proofreading ability. Whereas 20–30 s/kb is recommended, 120 s where not enough to amplify a fragment of 3.5 kb; an elongation time of 240 s—i.e. 60 s/kb—did work though.
Rem 2: In the past, amplification with the Phusion HF DNA polymerase did result in correct sequences in most of the cases, so I was surprised to have issues here. A possible factor that came to my mind afterwards and that could explain the apparition of mutations could be a low purification quality of the DNA preparation used as the template (leftover chemical contaminants). Although I have not (yet) tested and confirmed this possible explanation in my case.
I marked the answer from @markur below as accepted, as his/her suggestions (along with the accompanying discussion underneath) prompted me to go and read the original articles and then to read again more carefully the manual of the NEBuilder kit where the solution was.

Polymerases are never perfect. Mistakes can happen and are usually the reason why one always picks several clones and sends them off to sequencing. Phusion polymerase is advertised to contain 1 error in 6% of all PCR products (5000 bp, 30 cycles, HF buffer;  thermofisher error calculator). Companies always underestimate their errors, but in your case, having 6 point mutations in each clone is reason enough to optimize your protocol.
Changing the Enzyme will definitely have the greatest impact on your problem. Especially if it also includes changing the buffer system.
Phusion has been around quite a while, I'm sure that some companies did apply some optimizations trying to beat the competition (Kapa).
Another thing that came to my mind is that high magnesium concentrations increase the amplification rate, hence reducing corrective activity (aatbio). You might want to review your plasmid purification protocol to see if there might be salt contaminants (e.g. after EtOH precipitation).
Decreasing cycles also makes sense, and is definitely worth a shot.
Other aspects to try, if you're desperate:

Get a longer primer (~30 bp) and use a higher melting temperature to enforce strict and correct primer binding.
Getting fresh primers is also a good idea to avoid freeze/thaw damages
Use a fresh dNTP solution
Adding BSA is always worth a shot with PCR Farell 2012. Not just during the reaction, but also during storage to protect nucleic acids from freeze/thaw cycles Svec et al. 2013!
Check out thermofishers troubleshooting guide, there are some more ideas that might help!

Important: Please verify that it's indeed the PCR reaction that's causing point mutations, and not the bacterial clones! Check that by re-amplifying the same plasmid with PCR without prior Gibson Assembly and sequencing the product like any other clone!

Thank you very much for your answer + the tips + the links. A question: do you have experience in Gibson Assembly? I am asking because I am also wondering how my experience compares with others (1st point in my question) regardless of theoretical error rates as advertised by companies.

I've done a lot of Gibson Assembly with a home made kit (preparation identical to the original publication), and although I don't have numbers, I can't recall random mutations being particularly common. Do you see any pattern to where the mutations most often appear? Is it anywhere in the PCR amplified fragments, or are they more common in the repair regions (fragment overlaps)?

@TheQuark - I did it a few times but I will ask some technical assistants if 1-6 random point mutations per 5 kb for each clone is common (I don't think it is). One clone should be "perfect".

Following these exchanges, see the edit in my original post.