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What backbone to use for Helper dependent adenovirus (HDAd)
I have been trying to design a plasmid for a helper dependent adenovirus but while looking i wasn't able to see a backbone specifically for HDAds so I was wondering if a general adenovirus backbone would work or if there is an available backbone for helper dependent adenoviruses. A helper dependent adenovirus is considered a next generation adenovirus and has advantages like less immune response and longer effect, there are other considerations like attachment sites and wondered if there was already a commercially availible backbone that took the considerations into effect
I plan on making it consumed orally and to express a therapeutic protein

Can you say more about what your application is for the adenovirus? What are you going to do with it?

to add production of a protein by being consumed orally but so far just as a design project

So, I'm not at all sure that this is what you are doing, but your ultimate goal may be to make some sort of vector for therapeutic protein expression. You are interested in using a helper-dependent adenovirus (don't know what that is without any references, but maybe someone does). I think that what you want is to just dump some kind of constitutive expression cassette into that virus backbone, which will turn on full power when it is ingested. It looks like maybe this is a vehicle sometimes for vaccines. Can you look at what people have used in the past? If not, why haven't you?

I am pretty sure it would be considered a vector for therapeutic protein expression, And a helper-dependent adenovirus is also considered a gutless adenovirus or a next generation adenovirus with less immune response and longer expression. The backbone as far as I can tell has some of the same things as an adenovirus but some specific concerns like attachment sites to get into the adenovirus and I was wondering if there was a backbone that had these pre integrated

Having a lot of this detail directly in the question would make it a lot easier to answer. Consider editing the question and providing this and additional information (citations, some maps of some vectors that you are considering, examples). That will likely lead to a more helpful answer than I can give you here.


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What makes something an organism?
Someone asked me this, and I didn't know how to respond. I think I know an adult human is an organism, or an embryo in-utero, but it doesn't seem right to say my somatic cells are also human organisms.
I saw self-sufficiency as an answer once, as somatic cells cannot obtain nutrients on their own, they are naturally part of and rely on a larger biological system, but this would exclude foetuses (and maybe parasites), as they rely on the mother.
What makes something an organism? This is an answer from another posting on here:

An organism is any system of components which depend on each other for survival and cooperate in proliferating potentially unboundedly.

However the person who proposed this admitted that this does not apply to organisms who are sterile.

source: Stack Exchange

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

sort: votes


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Undesired Histidine Residue Introduced by NdeI Cleavage Site: Seeking Optimization Strategies
I'm currently working on a genetic engineering project where I aim to insert my gene of interest into a vector downstream of a TEV cleavage site. The vector is designed to be cut with the NdeI restriction enzyme, but unfortunately, the NdeI recognition site also encodes an additional histidine amino acid. I'm concerned that this extra histidine residue might interfere with the function of my protein.
I'm seeking advice on how to address this issue. I would greatly appreciate any suggestions or recommendations.

Is the His residue really an issue? Do you expect it to affect the protein any more than the TEV site and whatever other tag you have upstream of it, and what appears to be a T7 tag downstream of it?
If there absolutely cannot be a His, the easiest and cheapest solution would probably just be ordering a synthetic gene with the exact sequence that you want. When you can get a gene cloned into an expression vector, sequence verified, and shipped to you for $150 USD, is fiddling around with restriction digests and ligation reactions really worth the effort?

I'm not concerned about the residues before the TEV site, as they will be cleaved off after the TEV protease cuts, leaving only the terminal amino acid. I'm also using overlapping oligos for the synthetic gene. Given my current resources, I'm looking to develop a vector system where the gene is placed immediately after the TEV site, thus avoiding any additional amino acids between the TEV site and the gene

Oh yeah, of course the TEV site is cleaved, how stupid of me. Would a scarless cloning method like Gibson assembly work? Alternatively, if your gene always starts with the T7 tag (Met-Ala-Ser…), can you include this sequence in the vector and use NheI for cloning? This assumes you have some control over the vector sequence. Your vector would be …TCCATGG|CTAGC…

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


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Genomics vendors with publicly available pricing
Are there vendors for genomics with publicly available pricing?
Motivation:

I'm curious why the reagents needed for gene cloning using bacterial plasmid costs 100-150 USD, and why this can't be made cheaper. If the reagents can be purchased in bulk for  cheap and the research labour can be automated, so that a gene cloning costs 1 USD instead of 100 USD, then the entire field of research will be able to iterate very quickly.
If I google each of these steps I can find the required amount of each reagent, but the prices of the reagents are not available. For example for DNA ligation, how much does T4 DNA ligase cost?

What do you want to clone? And most important: Why? What do you hope from this?

@Chris I want to clone using bacterial plasmid, on species for example ecoli, I've added it to the post. I could provide lot more specifics like which species and which plasmid etc if it'll affect the cost a lot

@Chris Goal is I'm wondering if there's a way to really cheaply and quickly test if a certain genetic modification produces a certain protein or not. Being able to run this type of test millions of times seems like it'll move the field forward quickly.

There are ways to test this: You can do mutation screens on expressed proteins, but first you need to clone this. And as far as I know, this has to be done by hand. The process is relatively easy, but I don't see you can automate everything. You will in most cases get a protein, if this expresses in E.coli or is functional, is another thing.

@Chris Yes I understand automation is a difficult problem. Might need microfluidic system, and might need AI. (I'd love to read more on how one will actually try to automate it, but it's a separate question) For automation to even be worth attempting though, cost of reagents has to be much lower than $100. Hence wondering what the actual cost of reagents in bulk is, for gene cloning.

Ok, turn out, I was wrong: There are already automated services that you can buy: https://www.nzytech.com/en/hs0070-high-throughput-gene-synthesis/ Still leaves you with the problem of testing these proteins and optimize conditions for overexpression. Both are no simple tasks.

I’m voting to close this question because it is not about biology.

This is not a question of biology - it is a question for market economics. Reagents cost because that's what the market has set them at. Note that it isn't like you can just pull T4 ligase of the shelf or make it from scratch by just chcking amino acids into a tube, it is a whole manufacturing set up with fermenters expressing the right plasmids under the right conditions, batch processing, multiple purification steps, quality control, validation, testing etc. All require a LOT of equipment, reagents, time, people and it simply costs money to do so.

And - yes, simply go to company websites, they do tell you how much it costs to get a certain amount. e.g. ThermoFisher T4, 1000U, 5U/ul, 5000 U, 30 U/ul,  or NEB's selection among many.

I think that https://www.inscripta.com/ has a business model something like this, not that it seems to be going particularly well. (I got laid off after working there, I have no financial stake.) It is also similar to Ginkgo, they are also not doing particularly well.

@bob1 I figured out the problem, I had to to set VPN location to USA to view prices. Thanks!

@MaximilianPress Thanks for this. I couldn't find any information about inscripta's research though.

They haven't done a good job of publishing. This article talks about several applications they worked on at one point. But like I said they're not doing very well business wise- they had issues with low demand for their product. So I'm not sure that you'll find much. Look at Ginkgo or Willow though, or Amyris. They have similar goals.

@MaximilianPress Thanks, I will check!

Set your VPN location to USA then visit ThermoFisher 1 2 or NEB 3 website.
Credits to @bob1 for making me realise the websites view differently depending on country.

Prices often vary by location, so viewing prices with a VPN may not show you the price you will actually pay in your location.

@BryanKrause Fair point! P.S. Do you know why I'm being downvoted?


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Why isn't all genetics work published on GitHub?
Update: When hackernews is ruthlessly critical of a new software project, the implicit assumption is that software projects are dime-at-dozen, attention of HN users is worth millions of dollars, hence criticism protects this attention from being wasted. Genetics doesn't yet seem to have the same problems or same solutions. I should have more empathy for that.
I don't mean to attack any person specifically, just ideas and processes of how to do things.

I'm coming more from a software background than a genetics one so forgive my ignorance but:
Why isn't GitHub the default place to publish work in genetics?
Just to give an example, I was looking at pairwise alignment between genomes: https://asia.ensembl.org/info/genome/compara/analyses.html
Here's a list of stats that's been obtained. https://asia.ensembl.org/info/genome/compara/mlss.html?mlss=1098
Why isn't there a list of commands (presumably lastz called with some options) to generate these stats?
Why does lastz release source code but not compiled releases? https://github.com/lastz/lastz/releases
Why does clicking on details open an online GUI browser for the entire genome instead of ... some actual commands I could run on my machine? https://asia.ensembl.org/Pan_troglodytes/Location/Compara_Alignments/Image?align=1098;r=14:80237279-80308917
And if something as important as aligning genomes is like this, I'm assuming more niche work requires even more hassle if you want replicate results or play around with it.
Publishing work to GitHub has lot of obvious benefits:

replication of results is trivial - just clone repo and run command
high signal-to-noise ratio - related to previous point, you can't hide behind bad results when replicating results is trivial
code quality - you can identify who is actually a good developer by looking at their code, and which repos and tools are good quality, so it is safe to build on top of them
docs and activity - relatedly, you can also instantly identify which tools have good docs and which tools have active developers, so you can avoid the tools that are poorly documented or inactive
no gatekeeping - anybody can push code to GitHub, you don't need a degree. more people can contribute (while still keeping signal-to-noise ratio high)
high-level abstraction - you can build high-level abstractions, break down a problem into multiple pieces and different research fields work on them in parallel. (People writing OS and hardware stuff, network engineers, web developers, sysadmins can all build on top of each other's work without having expertise in each others' fields)

Some blockers I can imagine are:

Not all genetics experts are trained to code well - Sure, but like, doesn't getting good at coding help you become a genetics expert in the first place? How do you generate results quickly or verify others results if you can't code well yourself? And how do you become an expert in genetics if you can't do either of those things fast?
Lack of data standards - I don't know enough about this to comment. FASTA, BLAST6, etc seem standardised but there is a lot of metadata about various genes written in plain English, I'm not sure if there's a standardised format for that yet.
Some steps are subjective or matter of taste - Data cleaning and preprocessing seems quite involved for genetic data. More so than say, most NLP work in ML. I understand this makes it more work, but I'm unsure why that means it isn't worth doing. I understand some decisions in data cleaning or labelling can be subjective and a matter of research taste.

(Although I'm vaguely suspicious of this reasoning too, research taste just means we don't have proper reasoning for the best way of doing something yet. Being able to run code means we can develop benchmarks on all such steps and get hard empirical data)

I don't mean to rant here btw. I'm not a particular good software developer either. (Guess how I know? Because I've seen what actually good looks like, and hence I can benchmark my own abilities against others better. That's what open source allows you to do.)
I'm just curious why open source culture of pushing everything to github rather than arxiv, hasn't penetrated genetics research yet.

Update: Looks like lack of data standards is a major problem in the field.

Update: I just started going through biopython documentation and ... why does it read like a novel? :/ :/ :/ Why are the docs teaching me python indexes from zero? Why is there a random anecdote in the middle of the docs about how previous software version had a bug?  Why are the docs full of exclamation marks and "this is not too scary" comments (presumably for people who are scared of writing software?)

scikit-bio docs are so much better. But not enough algorithms implemented I think? Are they hoping other people will build on top of scikit-bio in future?

This doesn't really address most of your points, but GitHub is not an archive tool (it requires using a secondary tool to properly archive)

@Darlingtonia I mean fair but like, why does this matter? In machine learning, people know the real work happens on GitHub but publish papers just for namesake. I would be surprised if anyone is rejecting actually useful papers because their citation is not in Zenodo or whatever.

Why should it be on Github? You will not work on a genome or fork it. There are repositories for the genome data (Ensembl and NCBI) where you can get the data to work with it.

@Chris Yeah it's fine for the data to be on Ensembl or NCBI and the code to be on GitHub.

Certainly getting buy-in for researchers to post their code and data is an ongoing push, so I'm not speaking to the generalized question, but have you not been able to find what you need in the Ensembl GitHub organization or using their API?

@Darlingtonia They have linked to lastz which requires me to compile it from source, figure out what arguments they have called lastz with, and that will probably still only give some of the stats. Maybe there is some repo they've published it in (I don't know), but they've not linked it from the comparative genomics page that generates the results.

I don't actually need this specific result, I'm just curious why isn't it as simple as git clone somelink.git; run app

@Darlingtonia Their API mentions comparative genomics, but this link has class definitions and nothing human-readable. The API you've linked mention doxygen, which they've deprecated in favour of ensembl-hive, and again, not sure where I'm supposed to start.

There's a manual for hive, if that's the tool you want. However, I'd recommend surveying the many tools and FAQ for what might best fit your needs. To my eye, Ensembl has gone to great lengths to embody open source culture, and not only made raw code available, but produced several complex tools catering to technical users who aren't necessarily software engineers (or are just tired of trying to compile lastz on their bespoke computing cluster).

@Darlingtonia Sorry if this comes across as arrogant but like, I will literally pay non-trivial sum of money if someone can use Ensembl API and no outside help (such as contacting Ensembl team members) to replicate all the stats on this page within a week. Ideal world would allow you to replicate it within an hour.

I know I'm coming across the wrong way on this, maybe I should log off and return tomorrow, I'm sorry.

As to why Lastz and many others provide source code rather than compiled is that lots of people use *nix variants of some sort (including Mac) so they would need to provide compiled packages for all the variants and the source code for the variants they don't want to compile for.  In addition not everyone runs the most up to date software, many groups will be using a particular version of software with a particular set of programs for their own purposes, so you would need to provide all those too... Source is easier.

@bob1 This makes sense but like, popular tools can release pre-compiled for multiple *nix variants. (Atleast in the software world) Or they provide the compiled release for 2-3 popular OSes and some lengthy instructions for how to compile it yourself for other OS. Maybe these programs are not as popular?

@ghosts_in_the_code Sure, they could, but the reality is that often these tools are maintained by a research group that maybe has only one or two programmers on it and little time/money to do so, so it just doesn't happen.

To amplify what @bob1 has already written: most of the work in genomics is done by grad students and post-docs. Having those folks spend time on building anything like multi-platform installers is doing them a grave disservice. They are supposed to be working on extending our knowledge of science and/or coming up with novel algorithms. Doing commercial style software engineering is not what they signed up for. Funding agencies generally don't give two figs for providing niceties like installers and will look at you funny if you ask for funding for it*.

*They will sometimes in special cases fund for improved usability, but not often. Frankly the largest problem in bioinformatics is not the lack of binary distributions, it's the prevalence of  'ghost software'. Some grad student writes a useful program with a novel algorithm, it develops a small user base, the grad student graduates and moves on to a different topic, bit rot sets in, and after 2-3 years the software stops working.

I've edited out the personal commentary as it's not allowed network-wide, but the sentiment of the OP's update is appreciated and understood.

In addition to not being peer-reviewed, GitHub is commercial and not archival: see for example Zenodo: https://zenodo.org/search?q=genetics&l=list&p=1&s=10&sort=bestmatch

A trivial answer for much (most?) genetics work: it is not computationally reproducible, no code was written, and no CLI commands were run. Data analysis is restricted to excel spreadsheets and raw digital imaging. In some cases, no computers at all are involved.
Consider Lee Hartwell's beautiful classic work elucidating cell cycle control that won him the Nobel Prize. His tools were yeast culture equipment, a microscope, and a camera.

Thanks for taking time to reply! I just read the paper.

P.S. I have understood the problem in genetics completely wrong. I thought the main problem in genetics is that there's a ton of data available and what's needed is for people to find insights from it more quickly. For this, being good at software will help. But now I'm realising that even though the raw data can be obtained cheaply (DNA sequencing, protein sequencing, measuring protein expression level, digital imaging of cell phenotype, etc.), it takes lot of research labour to go from DNA to protein to phenotype. So automating this research labour may be the best way to accelerate the field

I would love to get any comment from your side. And I apologise again for how I behaved earlier.

I'd say that the problem of having a well-developed research question (e.g. "why are some cats grey and other cats orange?" vs. "i want to sequence a cat genome!") is the big hurdle for highly automated science. In the absence of such a question you can spend a ton of money and effort on something rather uninteresting. That's probably the biggest factor in your research labor- people actually planning out experiments that will answer those specific questions. There's a middle ground for big resource projects like databases or methods development, but those still need compelling applications.

Oh yes! What you're saying makes sense. Maybe I'll try asking this. Suppose you were made in charge of all biotech research on Earth. Suppose right now you can ask researchers to run 1,000 bacterial gene cloning experiments per month. Suppose automation made it possible to run 1,000,000 bacterial gene cloning experiments per month instead of 1,000. When picking which 1,000,000 to run, would you be particular about running certain types of experiments (based on the hypothesis you want to investigate) or would you rather just randomly pick lots of species and lots of genes and mutations?

The potential mutational space of biodiversity is astronomically large. 1,000,000 is a very small number if randomly distributed across biodiversity and mutation types. The mutational space with a meaningful effect is a pretty small subsample of that, though still astronomically large. You'd be wasting your effort if you didn't focus on interesting well-posed questions.

Thank you your answer is super helpful

Github isn't a publishing site for any science at all that I am aware of, it lacks the key component of peer-review. ArXiv isn't either, it's for preprints and also lacks peer review.
For many geneticists they use a collection of tools from various coders to do their work, not develop whole new tools each time. It's incredibly inefficient to write whole new tools when someone else already has the tool that does the job you want it to do. I'm aware that this isn't the case in most software development because of commercial sensitivity and copyright issues, but science is all about sharing data openly so the most popular tools are FOSS (Free Open Source Software).
So, geneticists generally gather the tools into a pipeline of sorts and use that to process the data. Many of these tools ARE on Github (e.g. here's TopHat among many others). Details of the pipeline are published in the papers written or hosted on Github (e.g. this one) or some other location like a locally hosted webpage for the lab as specified in the publication.
A popular tool for geneticists is the programming language Python - particularly Bioconda (note where that link takes you..). Have a look at the repository of packages within Bioconda, then choose a random one and look at where its homepage is...

Thanks for replying. 1. Yup Tophat/Hisat2 seems good, I haven't run it but just from reading. 2. Thanks for the bioconda link. Okay you're right there's more code being written than I thought at first. After seeing all the repos I think I'm better understanding what the problem actually is. I guess I'll spend more time on it myself. 3. I'm comparing to FOSS work in software in general, most commercial work builds on top of FOSS too. As far as I can see there is way more tools-building-on-top-of-each-other in software world compared to genetics.

Is peer review that important? I'm honestly unsure. Status and reputation in open source tech circles depends on other people building on top of your work. Which is in a way similar to paper citations. Ultimately though you want to solve some real problem for a real person (maybe detect cancer or something) and that person will provide you feedback as to whether your solution works for them or not. Status/reputation/etc are just incentives to get people to do the intermediate steps of work before you're solving the real problem. (Atleast that's my understanding of it)

@ghosts_in_the_code People publishing in genetics are not "in open source tech circles", they're in genetics. You're not stumbling on something new, biologists are quite aware of issues with reproducibility and code availability in the field. However, you're coming across as extremely rude about it. Like someone from "fork culture" showing up in a country where people use chopsticks and blasting them for not using forks.

@ghosts_in_the_code Maybe you learn something about the field first, before you try to re-invent the wheel and understand how things work. This includes things like peer review. Also: A lot of biology research is not about solving problems, it is about understanding things. That is how science works. When you understand how things work or how they are connected, you can start solving problems. However, this is often a complicated task.

@ghosts_in_the_code Peer review is the foundation of science. It provides a critical check and balance system, where the work must hold up to independent scrutiny before being published. During the Covid pandemic, much of this process was suspended due to the need to disseminate information as fast as possible and resulted in a lot of misinformation being spread. e.g. the use of ivermectin as treatment (it doesn't work...), which would have been pulled up by peer review. Publishing quality work in high quality journals is how your research reputation grows - none of that without peer review!

@bob1 Oh this makes sense actually. (the ivermectin example) Usually the worst that happens with bad software is wasting other people's time before they eventually realise it. But here one of the bad outcomes is people consume the wrong medicines and suffer health effects. So you can't wait till the bad outcome actually happens, for people to realise the solution is wrong. I really wish there was like a fully automated genetic engineering lab for bacteria or something, so people could iterate quickly without the downsides.

@Chris Yes fair, I could spend more time trying to understand stuff

@BryanKrause You are right. Apologies for coming across as rude. I don't mean to attack anyone specific. It's more of "Santa Claus is not real" type of frustration for me. But I'm sorry I should learn to express myself better.


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Identification of bone?tooth? found on beach
Need help identifying what I think is a tooth. We found it on the beach near Galveston, Tx. I took it to a natural science museum for help with ID and they agreed it appeared to be a tooth but not sure what from. They thought possibly marine mammal? Anyways I'm posting here with pictures in hopes someone can identify it's origins. Thank you

Yep, I found it myself. Boliver peninsula

that doesn't look like a tooth, teeth have roots and are no hollow. more likely a fish bone, and there are a lot of weird fish bones. you may want to change the title so you get people who are more familiar with fish.

I don't believe it is hollow except for that small area at the top. It seemed like maybe that's where the roots were. But that is interesting. Thanks for the insight

Its very likely a hyperostotic fish bone - or swollen bones which occurs in around 80 species.

Here's the location against the vertebrae

Here's its location against the silver bream skeleton

Here's a brief description of the skeletal phenomena

Oh wow interesting! So it's actually an abnormality. That makes since as it's so strange lol. Thank you for solving this mystery for us!!

Please cut the sources of your images (ideally beneath each image.  caption  works well


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can anyone help me with this question?
During exercise, a capillary of radius =500m
and length =0.1cm.
L=0.1 cm supplies oxygen to surrounding muscle tissue. Blood flows through the capillary with a volumetric flow rate =1L/s. The partial pressure of oxygen in the blood entering the capillary is 2,=100mmHg, and oxygen diffuses from the capillary into the tissue. The diffusion coefficient of oxygen in blood is =2×10^−5cm^2/s, and the oxygen solubility in blood is =0.003mL O2/mL blood/mmHg. The muscle tissue consumes oxygen at a rate of =0.1 mol/m^3/s.
İ FOUND THİS The calculated oxygen transport rate is approximately 1.884×10^−4 mLO2/s, which indicates the amount of oxygen diffusing out of the capillary into the tissue per second.

Welcome Yagmur. Please be aware of our homework policy. You will need to show what you've tried and where you got stuck else risk closure and deletion of your question - oh, and you would need to ask an actual question.

That's a slight improvement, but ideally you'd need to add a source or description of how you calculated it. - You've still not asked a question.


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What causes genetic drift?
I read that it occurs by chance, however since it's an important effect, is it really so random? are there any factors that enhance it or hinder it? Thank you
Also how do studbooks in zoos prevent genetic drift?

Its worth reading up on Ernst Myer's work on population genetics and his theory of speciation

homework questions are expected to show effort to answer the question on your own.

@john this is not a homework question, i'm not in school

@upquark homework questions is shorthand for a question at the level of basic homework. either way you are expected to show some effort to research the topic on your own first.

There are a lot of non-random processes in evolution.
"Genetic drift" is just the name/label applied to the remaining random part. If it were non-random, it wouldn't be genetic drift, it would be something else.
Randomness is more important in a small sample, which is why there's a bigger effect of genetic drift when a population shrinks (bottleneck) or a new population is established (founder effect).
Zoos and other artificial breeding programs act to mitigate bottlenecks and founder effects by keeping track of lineages and preserving genetic diversity by breeding more distant lineages. That doesn't do anything to eliminate genetic drift besides increasing the population, it acts against the non-random way that the surviving population is sampled (for example, if only individuals in a small geographical area survive in the wild).

thank you! why is genetic diversity preserved by breeding more distant lineages?

@upquark Because they are more genetically diverse by virtue of being more distantly related. At the other extreme would be inbreeding within just one family.


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What is the mechanism by which seeds stay alive while in storage?
I know folks who store seeds for months and sometimes a year before planting them. What is the mechanism by which they stay alive?
Also some associated questions:
How do the cells in the seed stay alive without resources for so long?
How long can the seeds stay alive in storage?
Does storing them long affect their growth?

What resources have you checked on seed dormancy? You’ll likely have to narrow the scope of your question for it to receive a good answer.

I suggest a little preliminary research.  But a year is really nothing for seeds: there's a date palm in Israel that was grown from a 2000 year old seed.  With a little assistance, plants were grown from 31,000 year old Silene stenophylla seeds.  It's also perfectly normal for seeds in the environment to grow after many years, wen conditions are right, e.g. a rainstorm for desert ephemerals, a fire for seeds that require smoke exposure to germinate, or just being exposed to light when I till my garden :-(

Seeds are made from cells in an amorphous metastable superviscous state because the cell's cytoplasm becomes a solid matrix of hydrogenated oil and sugar. The fats also contain a lot of anti-oxidants, so that ambient oxygen that can affect the dormant cells is absorbed by buffer chemicals.
The sugars and oils in the cell cytoplasm (the inside of the cell) become hydrogenated, and change into margarine and then become solidified fat and solidified sugar. Then the consistency of the cell at that stage becomes glassy because it's so solid, which is what you can see if you try to crack a peanut or a lentil, it has a glassy surface. The cell fats can rapidly become liquid again if they absorb water and change their chemistry.
references and images
It's not very different from microbe dormancy, so it's like an ancient biological trick that cells have been doing for billions of years.
The cotyledon is the future baby leaves of the seedling, the radicle is the root and the plumule is the leaf shoots, they are all made of cells that are in a solidified dehydrated form made of fats and sugars and special chemicals that resist ambient water and oxygenation in a controlled way.


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Did Dinosaurs have a neocortex?
Did dinosaurs have a neocortex in their brains? If not, when did it come into existence?

Dinosaurs did not have a neocortex - but many of them might have had something neocortex-like.
The neocortex does, in fact, appear to be a uniquely mammalian brain structure.  However, birds are dinosaurs, and although birds do not have a neocortex they do have complex brain structures that appear to be fairly similar in function.
The neocortex and analogous bird brain structures do appear to have derived from the same base, which means that somewhere after the amniota split, at least some fraction of dinosaurs did in fact possess those neocortex-like structures that we still observe in birds today.
Since information about brains does not fossilize well, we still know very little about dinosaur brains. As such, it's not currently possible to know whether all dinosaurs had such brain structures, or if it only emerged in the group that we now know as birds.

There is some evidence for the bird structure in at least maniraptorans, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4262302/ but the issue with definition does make it weak at best.

Interesting! Thank you for your time


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Is the Lucy fossil really what scientists claim it is?
The New Scientist has an article talking about how a baboon bone was found in the Lucy skeleton.
Creationist sites like this, https://christiannews.net/2015/04/23/evolutionary-embarrassment-part-of-famous-ape-man-skeleton-actually-came-from-baboon/, and Dr. David Menton are claiming that the Lucy fossil is another hoax like Nebraska man.
Are we sure that the Lucy fossil is not a hoax? (I am not trolling, I really want to know the truth, and when I search, I get mostly creationist sites).

Creationist websites are not a source of information. You can read the paper which the news article is referring to, or at least its abstract, and see that none of the scientists involved are claiming that Lucy is a "hoax".

Although evolution concerns biology, your question is one of palaeontology requiring expert knowledge and familiarity with the particular fossil. It is not on topic here, and you are unlikely to find anyone here more knowledgeable than the professional experts who have analysed it. If someone here with a doctorate told you it was true or untrue, why would you believe them? You have to make your own choice whether to trust the published work of generations of scientists or believe the conspiracy theorists. We can’t make it for you.

I'm voting to close this question as off-topic because it is about palaeontology not biology in terms of SE Biology.

There's dozens of other australopithecus in better condition that Lucy's bones, so there are literally 100's of times more heavy evidence than Lucy. If you want very interesting reading, check out the Homo Naledi discovery. You can read about the circumstances of Lucy's discovery on Wiki, and there are 100'ds of references where scientists have argued the finer points of the discovery.

@David paleontology is completely withing acceptable biological topics.

Per the comments, the actual paper seems pretty like a pretty straightforward operation of normal science:

Somebody noticed something that looked off about one of the bones and decided they'd look into it more carefully.
They found that yes, that bone appears to have been an accidental inclusion, and in fact the rest of the skeleton makes more sense without it.
The original conclusions are not weakened in any way, but are in fact strengthened by cleaning up a minor mistake.

It might have come out otherwise, but in this case, as in most cases, careful criticism and examination of scientific work ends up making the whole enterprise more coherent.
It's frankly not even very interesting, scientifically, which is probably why you're finding discussion of it mostly on creationist sites.  Note also that the creationist article linked uses sloppy language like "proof" and "part ape, part human" that tend to indicate a massive lack of understanding of both science in general and evolution in particular.

It is also worth mentioning the historic hoax anthropoids were discovered by scientists basically as soon as scientists were allowed to see the specimens. They are what happens when people try to circumvent the scientific process and go dirrectly to the media instead.


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Is there a maximum testosterone limit, or is it more accurate to say use?
I am constantly amazed at how we cannot differentiate between male and female.
The International Olympic committee sets the target testosterone at 5 nmol per deciliter with active androgen receptors.
What are active androgen receptors? Do they count sex hormone binding globulin (SHBG) bound Testosterone, especially in the brain? If I was serious about asking someone who would I ask ?

Whatever is the exact definition of the threshold that the Olympic committee sets, it's going to be relatively arbitrary and unfair to some people.
When it comes down to it, biology is generally messy and blurry, and that includes matters of sex and gender.  Thus, even if most people cluster in a fairly straightforward manner into male and female, there are all sorts of things like androgen insensitivity syndrome that can end up causing a person's normal body state to be judged as too extreme for their gender.
In the end, there is no simple line that can be drawn simply because the biology of gender permits many different ways for naturally occurring variations to form a continuum across any given metric that one might wish to establish.


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Common ancestry of our cells to the first unicellular cell
If we start the chapter of life with low fidelity self replicating RNAs forming exactly identical copies of themselves,  which then later evolved to form the first primordial basic cells which further reproduced, and formed identical daughter cells and so on ... besides mutation and other factors that might affect gene expression, our genome must still be derived from the very first RNA strand.
So is it too far fetched to say that in our bodies, our cells are the primordial cells themselves, as reproduction happens either by mitosis and meiosis (which keep the integrity of the first cell genome besides factors like mutation, etc.)?

I think it is too far-fetched to say so. It bounds a bit on philosophy: in what sense the modern sense are primordial cells? It do not consist of the very same molecules, and they do not resemble the primordial cells in terms of their RNA/DNA sequence, protein sequences, etc.

What it seems you're struggling with here is a lack of clear definitions.
Yes, the unity of core cellular mechanisms implies an unbroken line of descent back to the origins of life. But that does not in any way mean the cells are actually the same. I think that you would find it instructive to learn about the puzzle of the Ship of Theseus, which is the essence of the issue you are dealing with. In short, once changes can happen (e.g., mutation, as you note), it's possible to have both continuity and a fundamentally different item.
Beyond this, it's also worth noting that at every step we are dealing not with individuals but populations, even likely back into the murk of abiogenesis (when the populations would be various chemicals and protocells of some sort), and that genomes are also modified in a much wilder variety of ways, e.g., all the various forms of horizontal gene transfer.


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How many different DNA molecule classes does a person have?
Books always refer to human DNA as a unique molecule, and two different humans generally have different DNA molecules. But how many different types of DNA molecule does a person have?
In order to make this more understandable, let's give a physical/mathematical definition of molecule equivalence classes. Two molecules are in the same equivalence class if they have the same atoms in the same relative position to each other. And we say these two molecules are equivalent. In other word they are chemical clones of each other, like two $H_2O$ molecules are equivalent.
My question is this: how many equivalence classes of DNA does one human have (before being damaged or mutated)? 1, 23, 46, 92 or another number? Does a human have 46 or 92 different kinds of DNA molecules or just one that wraps differently to give different chromosomes? The same question could be given for a whole person or a single human cell.
Yes, I have looked on the internet and even asked a biologist. It seems the answers are always confusing to me because of the definition of the terms. What biologists seem to call "the DNA molecule" seems to be an ensemble of different equivalence classes of molecules, and I am finding this confusing.

It's worth doing some research before posting here. A fine start might be to look up "chromosome" or "human chromosomes".

Despite your interchange with @jakebeal perhaps persuading you that you are "right", you should try to appreciate why your question has been so badly received. We don't understand you. Not because we have no mathematics, but because you are talking in terms that do not relate to what we know and how we think about chromosomes. So even with your explanation, equivalence class means little to me. If we are talking about molecules of DNA, presumably one molecule is one chromosome. So, to us, your question becomes "how many chromosomes?" which you can find from the Internet. So what do you mean?

@David  one same molecule could wrap differently to produce the different chromosomes. I talked with biologists who believed this was the correct answer, admitting it was confusing. I don't believe it is the correct answer, it seems unrealistic. So far I believe the correct answer is that humans have 23 or 46 or 92 different DNA molecules. I don't care about being downvoted. I don't care about points. I just want an answer and help others if I can. Thank you

And I was trying to help you, not by telling you how to get points, but how to get an answer. And no, different chromosomes are not formed by different conformations of the same DNA. This has been known for ever because of their different sizes and appearances, but they have all been sequenced now. And if you are talking in multiples of 23, I assume you are entering the semantic wilderness of whether one strand or two strands of DNA constitutes a molecule. You can find that fruitless question has already been asked and the answer is yes.

It seems to me that you are becoming confused because you are thinking of DNA in the same way that one things about small molecules.
When molecules are enormous, however, they act more like a material than a simple molecule and have no single structure.  A good starting place for learning how to think about DNA as a large molecule is to learn about polymer chemistry.
Furthermore, a critical difference between these molecules and prototypical small molecules like water or glucose is that the small molecules are largely rigid in their structure. Biopolymers like DNA, RNA, and proteins (not to mention complex carbohydrates and lipid structures), on the other hand, are flexible. This means that the number of geometric configurations of such molecules is infinite.
This flexibility is critical for life, since it allows the molecules to retain their integrity even while interacting with other molecules to perform biological processes. That extends even to modification of the molecule itself, e.g., via epigenetic modification. In biology, we often talk about this as though the molecule is the same (again, treating it more like a material rather than a small molecule), even though technically its chemical species has indeed changed. With such an unbounded number of potential variant species, however, this sort of shorthand makes pragmatic sense for discussion, even if it does not match the definitions from Chemistry 101.

sorry to think of molecules as ... molecules. Thank you so much for your wisdom pointing out exactly my problem.

@ceillac It's an easy mistake to make, since early chemistry classes generally focus on either small molecules or crystalline ionic solids, both of which are far more well-behaved and easy to understand than the weirdness of enormous wibbly-wobbly biopolymers.

I was being ironic. This site has become a parody. I am out

@ceillac Would you care to point out what I am misunderstanding in your question? I'm happy to attempt to amend or clarify.


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How did so many types of larvae become known as worms?
How did it come to be that so many types of creatures typically known as worms are actually insect larvae? Silkworms are not actually worms at all, but larvae of a type of moth. Another example being the Maguey worm, which is supposedly the worm in some types of tequila and also not a worm, actually also a type of moth-larvae?
I find it curious that Wikipedia would have a creature with the word worm in its title, and then the first thing they tell you about it is that it is actually an insect. These are just the two examples I came across, there are probably more.

I’m voting to close this question because it is a language usage question rather than one about a biological concept or mechanism.

Discussion on meta: https://biology.meta.stackexchange.com/q/4178/52598

An addition to tsttst answer:
"Worm" can go to very abstract realms, in Neuroethology "Worm" can be a stimulus attribute:
horizontal movement implied:
▄▄▄▄▄▄   would be considered "Worm configuration"

▅
█
█
▀
would be considered "antiworm" (ignore the white stripes)
at this level of abstraction underlying taxa would not matter at all, could be an eel, a snake or a branch , or a piece of cardboard. As long as it triggers the "worm " synapse

Excellent question. My zoology professor during biology undergrads explained this by clarifying that "worm" is a term that relates to one type of shape of animals. As such it does not carry any additional information on the relatedness of animals or their developmental stage.
This view also seems to align with wikipedia.

but worms are not insects though, worms have no exoskeleton, breathe trough there skin and dont molt. They are both Invertebrates though. I'm trying to get my head around this.

"worm" is not a word with an exact scientific meaning (like the word insect). It's use colloquially to name any animal that have an elongated cylindrical shape. (Maybe snakes escape from this use today, but not in the 13th century, as you can read in https://en.wikipedia.org/wiki/Worm)

@NeilMeyer It's not too unusual for colloquial terms to not match the scientific counterparts. In some cases the colloquial terms have shifted with science, in other cases not. For example, "fish" once referred to all sorts of non-(biological fish) animals that lived in water, including marine mammals. We still see it used this way in jellyfish, starfish, the more generic "shellfish", etc.

@Bryan Krause: And then there's the silverfish, which doesn't live in water. https://en.wikipedia.org/wiki/Silverfish

This isn't really a matter of biology so much as etymology.
The English word for "worm" was applied to any sort of slithering distasteful creature for centuries before we actually started get our taxonomies properly sorted out. Thus, the word "worm" ended up in the common names for lots of organisms without any real relationship to one another besides their generally cylindrical shape. It's also unsurprising that there are so many different things that have ended up with that shape, because it's a really simple one to grow and thus an easy case for convergent evolution.
In short: "worm" just describes a common shape and isn't really a biological term of art.

In common English, worm is not a precise biological term, and long predates even the idea of precise biological names.  It's a generic descriptor for creatures that are long & skinny, without much in the way of legs.  So we have earthworms, silkworms, tapeworms, &c.  Even dragons can be called worms - or wurms, wyrms, &c, depending on your spelling preferences.  For instance, Old English epic Beowulf https://en.wikipedia.org/wiki/Beowulf ends with Beowulf fighting & being slain by a wyrm or dragon.
PS: Worm is also applied to non-biological things, for instance the worm gear: https://en.wikipedia.org/wiki/Worm_drive


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Can a cell receive multiple copies of an insert when using different MOIs?
I want to transduce a cell line with virus that carries a specific insert.
When using different Multiplicity of Infection (MOI), I expect to get different percentage of transduced cells, but is it possible to get more than one insert integrated in the cell genome?
I use high MOI and I always get 1 copy per cell, so I am not sure if increasing it a lot may also affect the number of in integrated inserts.

Yes, if you use a high enough MOI, you'll start to get double infections. Usually, anything >1 MOI will guarantee a high chance of double infections. If you're using a high MOI and only seeing single inserts, it might be due to your cells being difficult to transfect. If you look at this site: https://manuals.cellecta.com/lentiviral-construct-packaging-and-transduction/v10a/en/topic/lentiviral-titer-calculation it should give you a general reference for what % double transfected cells you should see. The difference between transfected cells and MOI % should estimate double infections assuming 100% efficiency.
Some cells are less efficient at being transfected, and it's a good idea to get a functional titer on your target cell line which is very easy if you have a fluorophore in the plasmid you're trying to insert.
I reread what you're getting at, and it's generally accepted that MOI under 0.4 won't give you double transfections.


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What would an organism be like if its entire genome "worked"?
It is known that a large fraction of the genome of almost any organism "does not work", that is, it does not encode any proteins and does not participate in gene expression, in protein synthesis, and in changes in the properties of the organism during mutations (e.g., estimates of functional DNA fraction in humans).
If you imagine an organism, for example a human, whose genome consists of completely "working" parts, what will be the consequence? For example, if all 3 billion base pairs of the human genome formed fully working genes, each of which would code for some proteins or combinations of proteins.
What would a human be like if their entire genome of 3 billion sequences consisted of coding genes?

Not really since the number of genes doesn't correlated with organismal complexity. Water daphnia have ~30% more genes than humans do. Going by your last couple of posts, this article may clear up some things and be of interested to you https://metode.org/issues/monographs/the-size-of-the-genome-and-the-complexity-of-living-beings.html

@user438383 And what correlates? And yet, what would a person be like if their entire genome (all 3 billion base pairs) were working?

@user438383 That is, what would a human be like if his entire genome of 3 billion sequences consisted of coding genes?

That's impossible to answer - it's much too hypothetical, so the answer could never be known. Humans are humans because of the genes we have. It might be fun to speculate, but it' doesn't really make sense as a scientific question.

@user438383 I actually think this is quite answerable, based on the work that's been done in minimal organisms.

I think it's very important to stress that your statement It is known that most of the genome of almost any organism "does not work" is completely incorrect, as @jakebeal describes in his answer. Just because a sequence or region doesn't code for a protein gene product doesn't mean it's useless. This is a common misconception we see here, and it deserves to be vigorously refuted.

As a new contributor I would encourage you to read the guidelines on what sort of questions one should avoid asking here. If you do so I think you will realize why I think that this is one of them.

@MattDMo Your assertion is also not correct, depending on the metric. I've attempted to clean up the question without changing its sense too much.

@jakebeal in what way? I wasn't trying to say that every single base has a function, just that the notion of "majority junk DNA" is not correct.

@MattDMo The paper that I link to discusses a variety of different metrics that come up with highly divergent estimates depending on the sense in which "junk" is meant, a number of which are indeed the majority of the genome of humans and many other large eukaryotes. While the OP's phrasing was not precise, I find their question quite intelligible and reasonable.

@jakebeal ok, I'll check it out

Your question is closely related to the concept of minimal genomes, in which researchers attempt to understand the significance of genes by removing everything that isn't strictly necessary, which includes "broken" genes, redundant genes, intergenic regions, etc.
The typical result is a much more fragile and less functional organism. Much of this is due to the fact that "not strictly necessary" is not the same as "not useful."  However, there is also a lot of regulatory function outside of coding sequences, as well as implicit and unknown functionality in apparently "non-functional" DNA.
Examples of this include spacing between genes that interacts with histone positioning, decouples methylation, or other epigenetic factors, spacing that couples or decouples genes, sequences with functions that haven't been discovered yet.
So what would happen if you had a human with either all of the "excess" material removed or with the "empty" material filled in with extra genes with some intended function?  In either case, you'd probably never actually end up with a human, because the resulting organism would be so fragile and impaired by undesirable interactions due to the loss of genetic separation, that it would never even be able to make it past the embryo stage to become a fetus.

Very likely the all genes active is going to be a mass of stem cells. So more of a cancer than human.

@jakebeal Why will it be fragile? Additional genes implies coding for new forms of proteins, about which we know nothing (after all, the space of proteins is huge and grows with the number of amino acids). Maybe there will be proteins that make the body not fragile, but quite the opposite?

@RoniSaiba .
Why do you think so?

@ArmanArmenpress A genome is more than just proteins. The regulation of those proteins is critical as well, and "empty space" is part of that regulation. Break the regulation and break the organism.

@ArmanArmenpress Embryonic stem cells have the highest euchromatin to heterochromatin ratios. As cell become more specialized i.e. differentiate, they start shutting down unnecessary (for them) regions of the genome. I think Gilbert's Developmental Biology will be a book that will satisfy your curiosity.


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Safety of Covid-19 vaccine for pregnant women
Is there any possibility that the protein produced by COVID-19 mRNA vaccine taken into body could cause negative effect for unborn babies?
In particular, isn't it possible the protein could be used as part of the baby of the pregnant woman?
In addition, mRNA can be broken by thermal fluctuation, so I worry that this broken mRNA might produce unexpectedly harmful protein for the body. Is this risk possibly realized?

Why do you think the protein would 'be used to become part of the pregnant woman' or 'produce unexpectedly harmful protein for the body'?

In a very recent case, an unvaccinated mother gave birth to her baby, held her once, and she died 10 days later of Covid-19. How, when the vaccine is so new, can we determine all of its effects on intrauterine offspring? However, the lack of a mother has definite known negative side effects.

The CDC has evaluated COVID-19 vaccines for pregnant people, and has determined that they are safe.
The main worry that they were addressing, however, was not either of your concerns (which do not make sense biologically). Instead, they were looking at whether the reaction of the body to the vaccine would be a potential cause of miscarriage.  The answer is: no, it's not.
Instead, we should be encouraging pregnant people to get vaccinated so that they will be less likely to die or become seriously ill, which will definitely have a bad effect on their unborn baby.

Thank you for your prompt answer. ok, I am totally new to biology and my concern might be off the point, but I am sincerely trying to understand why scientifically this mRNA vaccine is believed to be safe. Could you kindly answer SPECIFICALLY what does not make sense biologically?

How can you prove that the protein made by the mRNA does not affect unborn baby?
How can you rule out the possibility that the proteins made by broken mRNA is not toxic to human?

I would suggest studying some of the basics on how cells, proteins, and pregnancies work. mRNA is being degraded continually unless it's stabilized, so when mRNA gets broken, it gets rapidly recycled and you get no product, not a toxic product. As for impact on unborn babies, big proteins won't pass the placental barrier at all, so they simply cannot get to the baby in the first place.

As for "how do we prove ... ?", "how do we rule out ...?"  The only way to prove that the vaccines are safe for pregnant women, or more precisely to evaluate their risk (since nothing is 100% safe), is to run a randomized clinical trial. This is (1) slow, (2) expensive, (3) unethical because we don't have any reason to believe that they're unsafe (so it wouldn't be fair to the pregnant women we left in the control group who got COVID). "Prove it" is a bit like "prove I won't be eaten by a crocodile on my front porch" (even if I live in New Jersey).

@jakebeal, you could add the second and third sentence of your comment to your answer ...

Some immunoglobulins (IgG) are known to cross the placenta. They usually help the infant, not harm them, making a potential case for the safety of the vaccine. (Also, sorry that I repeated one of your points to the OP. I had not read your answer at that point.)

@anongoodnurse True, though the transfer of IgG is mediated by a specific targeted mechanism, so the basic point about proteins not passing through remains, and I hope the (inevitable) exception doesn't confuse the OP.

Thank you all for kindly answering question from layman. My knowledge on biology is from what I've read the textbook of essential cell biology, so not enough to understand papers on mRNA vaccines, but thanks for explaining in easy words.
@BenBolker I get your point, maybe my words were too strong, the proof of safety is like devil's proof.

@jakebeal OK, so there is enough reason to believe harmful proteins will not enter placenta generally. I will believe it.

@jakebeal What about the first question? it will take a while (~hours to days?) for mRNA to be broken by brownian motion, so if the broken mRNA is still able to produce corresponding protein, aren't there any possibilities that one of those proteins might be harmful to human?

@HQMA Cells regulate mRNA quite aggressively for many reasons, including preventing production of harmful proteins by RNA-based viruses. Those same mechanisms will generally prevent what you are worrying about. See, for example, this survey: https://www.nature.com/articles/nrm2104

@jakebeal Thank you for your comment, it's good to know there are such arguments to suggest the safety


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DNA mutations in humans are generally bad, but why to they make viruses stronger?
When I read about DNA mutations in humans, the mutations are generally bad.
When I read about mutations in viruses such as the recent emerging strains of COVID-19, however, it seems to be good for the virus and make it stronger.
Why do mutations seem to be good for viruses, and can we apply that technique to the human body too?

https://en.wikipedia.org/wiki/Survivorship_bias

So has my understanding been wrong? please enlighten me

Your title implies that most mutations in a viral genome are beneficial for the virus.  Is that the case? Can you better explain the logic that led to your conclusion that mutations "make [viral] bodies stronger"?

Viruses are said to always mutate so that they need antibodies that always change according to the type of virus. Corona viruses, for example, have several types because they mutate so that vaccines are always being developed. that according to my understanding, please correct

in fact you can and the human immune system is one good example of doing that; processes such junctional diversity on t-cell's that due to frame-shift mutations the v(d)j process can happen and create the tcr, are extremely important for our survival. furthermore, remember that the survival of the fittest law is always being applied in biology (or in life and everything..)

Thank you so much

Why do you claim that mutations in human DNA were generally bad? Mutations in general can be disadvantageous, beneficial or without immediate effect to the organism in question, afaik.

Yes thank you so much. now I know because of some hopeful  answer

The effects of mutations
As have been already pointed out, mutations are neither good nor bad - they are simply changes in the DNA sequence. The effects of mutations on humans and viruses are rather different, since humans are multicellular organisms - mutations in one cell do not affect the whole organism, but only this cell (except for the germline mutations in sperm and ovum, before these cells start to divide and become an organism with trillions of cells).
A mutation in a human cell may have different effects:

if it occurs in a coding region of a protein, this protein may start working better or its functioning may be disrupted (the latter is more statistically probable), leading to cell death.
if it occurs in a regulatory region, it may dirupt normal functioning of the cell, e.g., making it divide uncontrollably, and thus creating a cancer tumor.
it may also happen in a unimportant region, conferring no special changes.
Note also that severe disruptions, such as thsoe leading to cancer, are usually not a result of a single mutation, but an accumulation of many of them.

A mutation in virus may equally have different effects. Most mutations have either negative effect - producing a non-functional virus, or a neutral effect - resulting in no special changes (particularly the so-called synonymous mutations, which do not change the identity of the encoded amino-acid). Some mutations change the proteins in the virus capsid, resulting in viruses which either have different properties vis-à-vis antibodies or can better attach to cellular receptors - these are beneficial for virus survival.
The important difference with the hma, where mutations affect only one cell, is that a single infected cell produces multiple new viruses (from dozens to millions of them,d epending on the virus) - some of them will be disfunctional, some as good as their parents, and some more fit.
Classification of mutations
As could be already conjecture from the discussion above, depending on the effect of the mutation on the new viral particles, they can be classified in deleterious, neutral and beneficial.
Mutations and fitness
A single viral particle being more fit would not pose much problems. However this particle may infect another cell, producing new generation of fit particles, which will replicate again and so on. In other words, what makes a mutation good for a virus is the natural selection among the millions of viral particles.
On the other hand, when we speak about a mutatuion being bad for a huma, we speak about the effect of the mutation on a single individual. In otehr words, we are comparing here appels and oranges. If we were to make an equivalent comparison, we should consider a human population over the course of thousands or even millions of generations. We would see in this case mutations can have similarly different effects: the Neanderthal "human strain" turned out to be less fit and disappeared, whereas the homo sapiens "strain" has survived and populated the whole Earth.
References:

Population genetics
Viral ecology
Principles of virology

Thank you so much for the clear explanation really helps me.

Mutations of the genome are neither bad nor good. They alter. If the product of this alteration is advantagious to the virus or any organism, they may gain some advantage to reproduce better. If the alteration is deleterious, it may be bad for the virus and any organism.
With humans you see bad results with viruses not (they are too small).

Thank you so much for the answer


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What is this tiny, transparent creature found in my home?

Found these in my bathroom, everything was literally crawling with them - there were thousands of those on walls, sink, bathtub... I have all surfaces were sprayed with chlorine spray and with bug repellent afterwards. Still these creatures came back same day, although in smaller numbers.
There's not many features I can use to describe this creature aside from:

Size: very tiny, below 1mm; (black strands are beard hair)
They are pale-yellowish and semi-transparent as it's seen on photos provided
Rather slow and they walk aimlessly on all kinds of surfaces
They seem to be coming from cupboard under the sink, where it's warm, moist, dark and there's access to sewage piping shaft

I'm aware photos could be much better, but they were taken with smartphone combined with a lens from a flashlight to enable macrophotography. Not a best tool for that purpose though.
EDIT: Added circles around creature. Please ignore zoom cursor on first image.


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Non-nucleated cell-like population with RNA
We're working on invertebrate hemolymph (blood) and we have found with flow cytometry (staining with DRAQ5) a cell-like population without nucleus but it has RNA production.
Does anyone any experience with something similar? May anyone recommend any publication with something like that?
More information:
1) We don't know the real population size because we have identified it by flow cytometry, future experiments we wish to use TEM to characterize it better.
2) We know that this "population" produces RNA because we have extracted total RNA using low input RNA kit and run the result in Bioanalyzer.
3) We "know"/suspected this population doesn't have cell-nucleus because DRAQ5 is a DNA staining and this population is DRAQ5-. We wish study that by confocal microscopy ASAP.

Welcome to Biology.SE!  Will you please edit your question to include more information – including: 1) size of these putative "cells", 2) how you know they produce RNA, and 3) how you know they don't have a nucleus?

My first inclination is to suspect some sort of prokaryote — can you rule that out?

Hi! Thanks so much for your contribution but I might not be a prokaryotic population because it's producing 18S and 28S rRNA, instead of 16S and 23S.

This is a bit outside my wheelhouse so forgive me if I am ignorant of something, but does (2) actually mean RNA is being produced? Or could it just be that some RNA is still present? For example immature RBCs have RNA and make proteins despite lacking a nucleus.

Maybe you are seeing extracellular vesicles1?
At least might be worth checking out since extracellular vesicles containing RNA have been reported within the hemolymph of mosquitos2.
References:
1: Van der Pol, E., Böing, A. N., Harrison, P., Sturk, A., & Nieuwland, R. (2012). Classification, functions, and clinical relevance of extracellular vesicles. Pharmacological reviews, 64(3), 676-705.
2: Severo, M. S., Landry, J. J., Lindquist, R. L., Goosmann, C., Brinkmann, V., Collier, P., ... & Levashina, E. A. (2018). Unbiased classification of mosquito blood cells by single-cell genomics and high-content imaging. Proceedings of the National Academy of Sciences, 115(32), E7568-E7577.


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What separates humans from other animals?
It is clear that humans are distinguished from the other species on Earth, but what specific features are the cause? Other animals like chimpanzees have been shown to have consciousness and some self-awareness, dolphins likewise have a form of structured communication. What features of human biology (physical and/or mental) are unique to the human race as far as we know?
I would also appreciate any books or articles on these aspects of human biology if possible.
Thanks in advance!

"It is clear that humans are distinguished" - clear in what way? There are lots of species that are much more unusual compared to their relatives than humans are to theirs.

In the sense that we have subordinated the natural world to our control to a degree unmatched by any other animal. I’m asking what the biological preconditions of this are.

Humans are distunguished from other species by humans, due to chauvinism.

Unmatched by any other animal? There are only some 7 billion humans. There are 10,000 trillion ants. In our own bodies, there are as many bacterial cells as actual human cells.

To an extent I’m sure, but it isn’t purely that we ascribe exceptional qualities to humans simply because we are humans. No other animal species can manipulate its environment for specific ends in the same way humans can, which is what enabled us to develop our modern society. We must have some unique biological features that allow us to do this.

https://en.wikipedia.org/wiki/Lateral_prefrontal_cortex

When we take other similar species (or sub-species) into account, like neanderthals, we see that the difference is in the level of some capabilities like problem solving and memory.
And because of the level of these capabilities, modern humans can be distinguished as an animal which isn't bounded to a specific habitat on Earth.
If one looks to the animal species that live today and want to "distinguish" human, then she/he can think that there's a massive difference between human's and other amimals' communication and problem solving capabilities. But, rather than a difference, we need to look this as a kind of gap which isn't actually exist.
So, if needed, we can distinguish modern humans as a species from others on the basis of the results of their capabilities, not on the basis of the biological properties that cause these results.
Of course, this kind of questioning (trying to distinguish human) doesn't affect biological classification and identification of species at all, but it can affect people's general attitude and opinion on this issue.

Welcome to Biology.SE! Your answer reads like an opinion rather than being based on facts.  What evidence can you supply for differences in problem solving and memory between Neanderthals and modern humans?  Answers are much more likely to receive a favorable response if they include supporting references.  ——— You may wish to consult the help pages for additional advice on how to provide effective answers: biology.stackexchange.com/help/how-to-answer. Thanks!

I mentioned Neanderthals just to bring to attention that modern humans/humans aren't "unique" in any way when we take all the species/sub-species that lived on Earth into account.


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How does the dopamine spike from drugs compare quantitatively to pleasurable non-drug activities?
I did find this popular press article that quotes a researcher offering the following quantification: "in lab experiments done on animals, sex causes dopamine levels to jump from 100 to 200 units, and cocaine causes them to spike to 350 units. '[With] methamphetamine you get a release from the base level to about 1,250 units...'" [1]
However, I haven't found any research study supporting this claim or providing any details?
[1] http://www.pbs.org/wgbh/pages/frontline/meth/body/

This review article [1] gives dopamine responses for rats (similar to the BBC article above) and includes references to the underlying studies:

Sex/Food:  150% - 300%
Alcohol/Ethanol:  190%  (1g/kg) *
Morphine: 200% (1mg/kg) *
Nicotine:  220%   (0.6mg/kg) *
Cocaine:  350%  (5mg/kg)
Methamphetamine:  1000%  (1mg/kg)

These are percentages of the baseline dopamine level (not percentage increases), so 100% would be no effect.  They correspond to dopamine levels in the Nucleus Accumbens, which is a brain region involved in processing reward.
Also, the drug effects are dose dependent, so the above values show the dosage with the largest effect among the dosages tested in this study [2], which was referenced from the review article.  The values marked with asterisks were estimated visually from the graphs.
[1] Allerton M, Blake W. The "Party Drug" Crystal Methamphetamine: Risk Factor for the Acquisition of HIV. Perm J. 2008;12(1):56–58.
 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3042341/
[2] Di Chiara G, Imperato A. Drugs abused by humans preferentially increase synaptic dopamine concentrations in the mesolimbic system of freely moving rats. Proc Natl Acad Sci U S A. 1988;85(14):5274–5278.
 https://www.ncbi.nlm.nih.gov/pubmed/2899326

Hi Andy, nice answer. We like answers to be able to stand on their own, however. A link to a source is good but please also provide a full citation. And if the articles provide more info like dosages it would also be better to include those directly.

I added a more detailed citation.  However, the review article I cited does not include dosages, though results for various dosages are included in some of the studies that they reference.  If I find time, I may track them down.


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What is the probability of an offspring sharing identical HLA typing as one of their parents?
DISCLAIMER: I have yet to thoroughly study HLA 100% to the bone, and hence I won't know everything about it at the back of the hand.
Recently I came across this information on a San Francisco hospital website claiming the chance of a full HLA match between 2 randomly selected people is 1/1,000,000 and the chance of a full HLA match between a child and one of their parents is 1/200.$^{[1]}$
What struck me as odd is the 1/200 chance of a parent matching their offspring's HLA, which seemed too high of an estimate. The immediate intuition is for a child to have identical HLA typing as one of their parents, their parents need to share some HLA haplotypes, which on its own should be a rare occurrence. Hence I decided to attempt verification of this number to confirm if it was within the realm of possibility
According to Stanford$^{[2]}$, the HLA cell surface receptors that mix during inheritance are HLA-A, HLA-B in MHC I, and HLA-DR in MHC II. A set of these 3 forms a haplotype. [HLA-C and HLA-DQ are probably involved too, but we'll omit them for simplicity's sake.]
For our estimation, we use data from the same Stanford source$^{[2]}$ and find there are 59 HLA-A serotypes, 118 HLA-B serotypes, and 124 HLA-DR serotypes. This gives us $59\times118\times124=863288$ different possible haplotypes.
To get the probability of 2 parents sharing at least 1 common haplotype, we do some math: $\frac{1}{863288} \times \frac{863287}{863288} + \frac{1}{863288} \times \frac{863287}{863288} + 2 \times \frac{1}{863288} \times \frac{1}{863288} = 1/431644$
The above is assuming the parents have met randomly in the world and no inbreeding has taken place. Inbreeding will pretty much ensure 2 parents share common HLA haplotypes.
This means the chance of an offspring to even possibly have the same HLA typing as one of their parents is 1 in 431,644, which is already way lower than the 1 in 200 chance stated on the hospital's website.
Just for calculation sake, the precise chance of an offspring sharing the same HLA typing with either one of their parents after accounting for different possible haplotype combinations produced by the parents would be: $100\% \times \frac{1}{863288}^2 \times 2 + 25\% \times \frac{1}{863288} \times \frac{863286}{863288} \times 2 + 50\% \times 2 \times \frac{1}{863288}^2 = 5.792 \times 10^{-7}$
An exceedingly small chance.
Issues with my estimation:
There were 2 assumptions made during this estimatey computation. I didn't take into account the weighted and uneven distribution of the haplotypes, and just assumed they are all statistically evenly distributed. Some haplotypes are more common than others, and this factor was not considered during the estimation. If existing data on haplotype occurrence is used, it will likely affect the estimation quite a bit, however, this is highly difficult as the data varies by region and ancestry.
I also did not take Genetic matchmaking into account, which is a factor that will lower the chance of 2 parents sharing common HLA haplotypes.
If exact computation for the probability proves to be difficult, what would be a reasonable estimation on the order of magnitude of said probability? Is 1/200 within the realm of possibility once you take into account the uneven distribution of haplotypes caused by certain more common ones?
Sources:
$^{[1]}$https://www.ucsfbenioffchildrens.org/education/types_of_bmt_donors/#2
$^{[2]}$http://web.stanford.edu/dept/HPST/transplant/html/hla.html

If you follow your math, you will definitely not find a 1/1,000,000 chance of two random people being an HLA match, so it seems clear that the independence and equal weighting of types is not a great assumption.
We can make a different set of back-of-envelope assumptions, and just say that the 1/1000000 number comes from having 6 combined matches. In that case, you would interpret 1/1000000 as due to 6 independent matchings of probability 1/10. In that case, with a parent you only have to randomly match the other three. 1/10^3 = 1/1000, much closer to the 1/200. Further non-independence, unequal frequencies, and homozygosity makes 1/200 seem reasonable in a whole population (though individuals with more rare HLA would be less likely to match a parent or a random individual), and I presume the 1/200 number comes from actual observed frequencies rather than theoretical calculations.
Perhaps someone with more HLA expertise (I have basically none) will provide a better answer based on more specifics, but I just meant this as a quick napkin calculation for whether the numbers given are plausible, and I think that they are.

After googling around, I'm not too sure about the accuracy of the 1/1,000,000 chance claim of HLA matching between random individuals either, as there are rarely any sources making direct claims of the estimation chance.


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Why do my tomatoes start to rot on the same fruit part?
I observe a phenomenon for many years now. I observe it on a wide diversity of tomatoes produced all over Europe and Northern Africa that are sold at my local supermarket.
When I keep my tomatoes at ambient temperature around 20 to 25 degrees celsius, they deteriorate after a variable time, usually starting a five to fifteen days after I bought them. Nothing abnormal so far.
However, I observed that the mold pattern of virtually all these tomatoes is the same. It almost always starts a few millimeters from the junction where the tomato was attached to its branch, forming a ring on the top of the fruit.
I have thought why this could happen and my main hypothesis is that when they are grown the sun hits the top of the tomatoes (except where it is attached to the branch, obviously) and some ultraviolet radiation might weaken the tomato resistance in some way. The other reasonable hypothesis, although I cannot think of a definite mechanism, is that gravity would favor this polarized degradation. I have other hypotheses but they are too far a stretch, I believe.
So what is really happening?
I am a biologist, just not into botany or agriculture, so feel free to go technical and not just oversimplify.

Mold spores float around everywhere in the air, in your home and on farms. They are also likely found on the surfaces of farm equipment used for harvesting (shears, knives, etc.). Grey mold can infect tomato leaves and stems where there are lesions, such as those introduced when harvesting fruit, when cutting the fruit off at the stem. This could happen wherever such spores can find ingress between the farm, produce distributors, the market, and your home.
Cite: https://content.ces.ncsu.edu/botrytis-gray-mold-of-tomato

But there is no apparent lesion there, and the flesh is as firm there as the rest of the fruit until a week passed, then it gets softer, darker, and cracks open, allowing mold to take place. Are you saying that harvesting damages the tomatoes around the stem location although it is invisible?

When you cut fruit off the vine, that cut is a lesion. In handling the cut tomato, the stem can be pushed and separated to allow spores entry.


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Best fundamental literature about genetics
I'm seeking for good genetics literature. I'm not afraid of it's complexity, because I want to have relevant knowledges about molecular genetics. After Wikipedia articles and basic molecular-biology books I need something, that can explain some aspects more detailed. I need something fundamental, but not abstract or scientifically popular. I understand, that question probably will be closed, but I don't know any other place to ask.

Finding something more fundamental and more detailed than Wikipedia might be a challenge.

For textbooks, I think Gene X is very detailed, very comprehensive.

"genetics" is extremely broad. Could you identify a specific discipline? e.g. molecular genetics/molecular biology, human population genetics, evolutionary genetics, genomics, plant genetics, developmental genetics, biotechnology...? The obvious answer would be "a genetics textbook" but I suspect you want something more specific.

@Maximilian Press Probably, molecular genetics is what i need.

I can think of a few different sources that might be interesting to you, focusing specifically on so-called "Central Dogma" ideas.
My personal bias is I think that knowing a bit of the history is invaluable for understanding the concepts, because a lot of the concepts turn out to be tied up in how they were discovered. Most of the big-picture stuff in molecular biology was figured out by 1980 or so, and molecular genetics followed closely behind.
Matthew Cobb has written a number of good books about how famous discoveries were made- I've read Life's Greatest Secret, which I found very readable and also informative about the discovery of the genetic code.
Sean Carroll wrote a good book about molecular mechanisms in developmental biology.
Both of these are "pop science" books but they are written by PhD biologists with a lot of technical details.
I am very fond of Erwin Chargaff's books as well but he is not to everyone's taste; he missed a few things early on in the history of molecular biology by being over-cautious, and was rather bitter about it later, which bled through in his writing. Most relevant probably are "Essays on Nucleic Acids" and "That Heraclitean Fire".
You could also read Jim Watson's book Molecular Biology of the Gene, which is rather old (though updated) but is a lot better on the technical aspects than most textbooks by my understanding. (He's a bad person but the book is good.)
And of course MIT has online molecular genetics courses.


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Viral RNA to DNA
I have a question concerning reverse transcriptase.
Why is it that when the viral rna is converted to viral dna( as in the case for hiv), the virus develops resistance to medicine?
Under what circumstances does reverse transcriptase causes a viral mutation?

Welcome to Biology.SE! We encourage you to do some research on your own and then ask questions informed by what you have learned (ideally with references to reliable sources). For example, the top hit I found searching with "mutation-rate reverse-transcription" was: https://www.ncbi.nlm.nih.gov/pubmed/12456349 ——— Please also take the time to go through the [tour] and the help pages starting with [Ask] questions effectively on this site. Thanks!

Via: https://en.wikipedia.org/wiki/Reverse_transcriptase#Replication_fidelity

There are three different replication systems during the life cycle of a retrovirus. First of all, the reverse transcriptase synthesizes viral DNA from viral RNA, and then from newly made complementary DNA strand. The second replication process occurs when host cellular DNA polymerase replicates the integrated viral DNA. Lastly, RNA polymerase II transcribes the proviral DNA into RNA, which will be packed into virions. Therefore, mutation can occur during one or all of these replication steps.[17]
Reverse transcriptase has a high error rate when transcribing RNA into DNA since, unlike most other DNA polymerases, it has no proofreading ability. This high error rate allows mutations to accumulate at an accelerated rate relative to proofread forms of replication. The commercially available reverse transcriptases produced by Promega are quoted by their manuals as having error rates in the range of 1 in 17,000 bases for AMV and 1 in 30,000 bases for M-MLV.[18]  (Emphasis added.)

Polymerases are proteins (enzymes) that make copies of genetic material: DNA or RNA. https://en.m.wikipedia.org/wiki/Polymerase
These enzymes have different fidelity or error rates. This means that different polymerases can make fewer or more mistakes when copying genetic information.
To accommodate errors, DNA polymerases have proofreading mechanisms that go back and fix errors. Most of the time, this works as expected.  https://en.m.wikipedia.org/wiki/Proofreading_(biology)
However, the reverse transcriptase that copies RNA into DNA does not do any proofreading, so there will be various mutations in some fraction of copies, depending on the transcriptase's fidelity rate. https://en.m.wikipedia.org/wiki/Reverse_transcriptase
For viruses, it is a pure numbers game. All they are programmed to do is make copies of themselves, and as many copies as possible, when they are in infectious, non-dormant state. https://en.wikipedia.org/wiki/Lysogenic_cycle and https://en.wikipedia.org/wiki/Lytic_cycle
Most mutations will be deleterious and the virus won't infect, integrate, and replicate successfully. A random mutation will often break a needed protein involved in the viral reproductive cycle.
Some mutations are "neutral" or "silent" and won't change how the virus copies itself. Consider that the genetic code is redundant — substitute a base here or there and you can still get the same amino acid sequence. https://en.wikipedia.org/wiki/Silent_mutation
But if you have enough virus particles copying themselves, all you need are mutations in the parts of the virus genome that allow it to keep replicating and also change the proteins it makes, just enough to evade the host's immune system.
If a mutated virus can still replicate and also change the proteins it gets the infected cell to make on its behalf, it can be more successful at copying itself. Immune cells will have to "relearn" whatever changes were made in order to trigger the usual immune response and fight back.
In the case of HIV, it also attacks the immune system directly, which is another complication.
Medications try to interfere with the different ways in which HIV works to infect immune cells and to make copies of themselves.
For example, one class of medication tries to "compete" with the part of HIV that binds to the surface of T cells. It's like a night club, where the bouncers at the doors are more likely to keep HIV from getting into the cell/club and partying.
Other classes of medication interfere with a protein called integrase that HIV makes to integrate its viral DNA into the host DNA. Integration of the HIV DNA into the host cell's DNA is a critical step for infection, so that's one way to target the virus. https://en.wikipedia.org/wiki/Integrase
Still other drugs try to inhibit the reverse transcriptase that turns HIV RNA into DNA. If the virus RNA is inhibited from being made into DNA, then that can help keep further infection in check. PrEP is a combination of two drugs (tenofovir and emtricitabine) which are RT inhibitors. https://www.cdc.gov/hiv/basics/prep.html
An overview of some of these medications is available here: https://www.webmd.com/hiv-aids/aids-hiv-medication
These medications all try to target the proteins involved in how HIV infects and replicates inside immune cells.
In turn, reverse transcriptase is sloppy enough in turning HIV RNA into DNA that it can get lucky and mutate enough to make one or another medication less effective.
Treatments are sometimes put into so-called "cocktails" of multiple drugs. A multi-drug regimen that attacks the virus by different means will give HIV a harder time in getting lucky enough to mutate in ways that it can get past a multi-pronged attack in those who are HIV+. Another good summary of such medications — many of which target reverse transcriptase activity — is available here: http://www.aidsinfonet.org/fact_sheets/view/403


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What is this very tiny (3mm) centipede-like insect?

My kid found this little guy in his bedroom. It’s about 2-3mm long. Lots of legs, and white rings around its abdomen.
Any idea what it is?
Edit: Location in San Jose, CA.

Welcome to Biology.SE! For identification questions please edit your post to include the location (e.g. country and region — the more specific the better) where you observed this creature. The location can be an essential clue for identifications. ——— If possible clear, closeup photos of the creature from multiple angles would also be helpful. ——— Please take the time to take the [tour] and then go through the help pages starting with [Ask] questions effectively on this site. Thanks!

Related: What kind of insect can this be?..., Can anyone help confirm this tiny insect larvae?, Bug Identification: Is this small tubular, black bug...,
How to protect my mounted insects..., What is the name of the critter depicted..., What small insect is this?, What bug is this...

That is a dermestid larva. A beetle from the family Dermestidae https://en.wikipedia.org/wiki/Dermestidae, common name, skin beetle. They eat dried skin, or flesh, and are generally the last insect to feed on a carcass. They are the bane of insect collectors, because they eat dried insects right off the pin.


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Cell communication
In some organism we observe that different individual cells organize and form structures. How are these individual cells attaining the information for the grouping? How does these cells communicate?

Welchome to Stack exchange! While this question may seem basic / simple, it is actually a super broad question: Cell communication & organisation encompasses large parts of developmental biology and cell signalling - both of which are very large & active fields of research. You can check the Tour and Help center, which may help you to narrow your question down to a point where we can reasonably answer it.


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How can we say that a gene is spacio-temporally regulated?
Gene expression is depending on the space and time of the cell. How can we distinguish the function of a gene without a chance of changing its expression? And also how is it possible to find the exact position where the gene is expressed?

The title doesn't seem to fit with the body of the question, which includes two almost completely unrelated subquestions. Can you edit to clarify and reduce your question to one question? It would also help to describe your attempts to answer the question on your own. A typical basic biology textbook would have examples of both testing function and measuring location while teaching other concepts.

Some clarifying questions:  "How can we distinguish the function of a gene without a chance of changing its expression." -- are you asking what the effects of measurement are on transcriptional dynamics? "And also how is it possible to find the exact position where the gene is expressed?" -- by position, are you referring to position in the nucleus / cell?  position along the gene body?