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There have been 14 items by Ubiquitous (Search limited from 21-September 19)
One thing I don't seem to understand is the design of the 3' end primer. In the paper, Qt=Qo+Qi+TTTTTTTTTTTTTTT
I understand that Qi contains the restriction sites for Hind III, Sst I and Xho I. Q outer (Qo) is 5'–ccagtgagcagagtgacg–3'. I simply don't understand what Qo is used for and why Qo has this sequence. The protocol says "The end is amplified using a primer that contains part of thissequence (Qouter, QO) and that binds to these cDNAs at their 3' ends ends, and a primer that matches the gene of interest (gene-specific primer 1; GSP1).
Can someone please help clarify why Qo has the sequence is does, and what it is exactly used for? I'm still not clear on why it is in the primer. Thanks!
I need to add drug to my 6 well plate with cells ( each well can hold up to 3.2 ml). the molecular weight of the drug is 357 and i am given 5 mg of the drug that needs to be dissolved in DMSO. plate 1 is control, plate 2 needs to have .001 micromolar of the drug, plate 3 .01 micromolar, plate 4 .1 micromolar of the drug, plate 5 1 micromolar and, plate 6 5 micromolar of the drug. I know that i need to come up with a reasonable volume of DMSO to dissolve the drug in and that i need to start with the highest concentration (plate 6) and from there i need to make serial dilutions to obtain correct drug conc. that needs to be added to the corresponding well. And the volume of DMSO that will be added to each well has to be equal. I need to have a step by step tutorial on how to solve this problem. Thanks for help in advance!!!!
One thing you could do is a pilot study where you just test for the toxicity effect of your vehicle (DMSO). Just take your cells and add different volumes of DMSO and then count them after incubating for 2 days to get an idea of toxicity. It should give you an idea of what types of volume of DMSO you can add to your cells and avoid significant toxicity from the DMSO. DMSO is definitely toxic. When we have an extremely lipophilic molecule that needs DMSO, it is typical for us to create 100 mM stock solutions and add the volume needed to reach the desired drug concentration.
You're working on the nM range so take into consideration the fact that you want to add a volume that won't be too small (i.e. the volumes require aren't say 0.01 uL). There's simply too much error and uncertainty when working with small volumes when using a typical hand pipette.
What I don't understand is that the authors seem to say that increasing sialylation might be a good thing to prevent cancer progression since it inhibits EGFR dimerization. However, wouldn't this go against almost 50 or 60 years of research that suggest that increased levels of sialic acid are one of the well known hallmarks of cancer that aid in its progression and metastasis? What could explain this apparent discrepancy?
If adding serum to culture media causes cancer cells to terminally differentiate into lines that are completely different from their in vivo human counterparts, why do we still add serum then to media to grow cancer cells? This has been known since 2006, so why do we still continue to do it if the accuracy of such models is completely off from what would be expected to occur in vivo?
Are there more studies out there that have looked at whole transcriptomes of other commonly used cell lines that are purchased from vendors that also compared those transcriptomes to cells from a primary tumor? Just curious to see how much cell culture changes the in vivo pheno/genotypes, and if it is a reason why so much science fails when it comes time to translating research into the clinic.
I guess for some proteins it's really difficult to obtain a positive control (or even a negative control)... I use AB's in other applications than WB though (flow cytometry, immunofluorescence etc.) and I really had and have trouble finding cells etc. that do express the proteins I work with for sure !
Do you have trouble because of the ABs? Or because of the protein? How do you make sure your ABs really work and really do bind to the protein of interest? Just take the vendor's word for it? What should one do to validate their Abs? SiRNA experiments if one can not purchase the protein outright to do a positive control on a gel?
Also, is there a link you have describes these new "linear" antibodies? I'm curious. AFIK, if one is going to do densiometry readings, then a standard curve is needed on your gel. Do the new ABs no longer require this?
You make some excellent points, Ubiquitous, however I doubt that many of us on here will appreciate your condescending tone.
In the same way that many biologists may be under skilled in statistics, most statisticians would not make good biologists either.
Instead of adversary and derision (from both sides), would it not be better to have cooperation, so that those who have the appropriate skill set do what they do best, and have others help with the rest?
I know at least at my university has statisticians available to help with design and analysis of experiments- which plenty of biologists take advantage of (probably not as many as should, though). And you sure as heck won't get animal ethics approval to do your in vivo work without demonstrating that your experiments are statistically sound (i.e. have been looked over by a statistician, have had power analyses performed etc).
Sorry didn't mean to offend anyone, my apologies. It's just that this topic non-reproducibility gets me going. We dump billions of dollars every year into bio and biomedically related research, and there's probably a good chance that much of it should simply be thrown in the trash because it was never done right in the first place. A. Complete. Waste. Of. Money. How much time, effort, and money do people waste trying to repeat "statistically significant data" that simply can't be repeated because the statistics were handled wrongly?
There's a significant threat to the scientific community from the hordes of published data that come from statistically underpowered studies. Everyone knows about the type II errors that can be made from underpowered studies, and once those findings are published, the error just keeps propagating and propagating. Then when someone tries a properly designed experiment and the data goes against what has been supposedly been " well established" in the scientific community, they're outcast like they're some sort of leper.
Next time anyone reads a journal article, look at how many samples were tested to create the data. Shockingly, a large amount of journal articles don't even tell you. Even in articles that do tell you sample size, they never give justification for the amount of samples being tested. This may be less prevalent in studies involving animals, since yes, many organizations required power of analysis in animal studies, but what about the huge amount of other research being done on the molecular or cellular level?
By rtPCR you mean real time- or reverse transcription- PCR? If the former, to avoid confusion it is better to use quantitative PCR (qPCR).
As far as I know primers do not contain sybr green, the sybr agent is much like ethidium bromide in that it relies on intercalation between the DNA strands at a particular density per bp, and as such sybr is added as part of the PCR mastermix. It is possible however to get primers that are fluorescently (fl) tagged such as Taqman assay primers.
In practice it shouldn't matter whether the primers are tagged for use in sequencing, though I have never tried it. I can imagine that a Fl tagged primer may obscure the signal from some of the initial base calls if used though.
For sequencing, yes the company does require primers, you need to set up a tube that contains the target DNA and ONE primer only - if you have both primers in the same tube you will get mixed signal as the forward and reverse regions get sequenced simultaneously (think about how DNA is replicated and the orientation of the two strands).
The universal primers are only for sequencing off plasmids (and even then, only for some plasmids) if your product is not contained in a plasmid you need to supply the correct primer.
Thanks for clearing this up for me. Yes I meant qPCR. And no the primers don't contain SYBR green, which is part of the master mix, you're right. Made some errors describing what I want to do because this is the first time I've ever tried PCR.
WHen will biologists learn to do proper statistics? I don't doubt at all that many published findings are not repeatable, and it's simply the fact that many biologists don't know how to properly do statistics. I don't think it is out of anything nefarious (data manipulation etc.)
Ask yourself, what does statistical significance mean? If you can't answer that properly, go back and look back at a basic biostats book. Statistical significance does NOT mean the following:
-that your results are reproducible (in fact statistically significant findings may only be reproducible 50% of the time)
-that your research hypothesis is indeed valid. This one is a biggie. Suppose a researcher has a hypothesis that A affects X which causes Y. The researcher manipulates X and sees Y change. Therefore the researcher concludes that theory A is supported since the null hypothesis is rejected due to "statistically significant data". The researcher is in fact wrong, and falling into a fallacy noted by Aristotle 2000 years ago. Statistically significant findings don't automatically mean A is true, since theories B, C, D, E, F.....could all say X affects Y as well, and may even be better at it than A. A good scientist would therefore pit theory A against theories B, C, D, E, F.... but that in most cases is impossible. Statisical significance ONLY describes the probability of observing your data under the assumption that your null hypothesis is true.
-that the probability that your hypothesis is true given your data D is answered by statistically significant data.
-that your findings are even important, it has nothing to do with the magnitude of effect one observes.
Power of analysis should always be done to design an experiment to properly determine sample sizes needed. Statisticians secretly laugh their asses off at much of the bio related literature from the poor handling of data and experimental design. Underpowered experiments run the danger of not only type II statistical errors, but also type I. It's laughable that hardly any biology studies outside of the clinic do not do power of analyses. Journals need to start rejecting manuscripts without proper a priori experimental design.
Here's a great article on the topic why most published findings are wrong:
If you want to do much higher quality research than the 90% of scrubs out there properly design your experiments using POA. Analyze your statistics for not only significance BUT ALSO MAGNITUDE OF EFFECT. Use confidence intervals (SEMs should be banned from literature) and look at things like Cohen's d, eta^2, etc. Maybe even try Bayesian techniques.
So I have a validated set of primers for rtPCR from Biorad that contains SYBR green. If I do rtPCR, can I use the rtPCR product after purifying it with a Qiagen PCR purification kit? Also, I'm under the impression that the sequencing company needs primers to do sequencing, do I just use the PCR primer or one of the "universal" primers the company has?
However, how do cell biologists conduct POA? The sample sizes needed that are mentioned in a POA are often huge (say 50-200 samples for an experiment designed for ANOVA w/ a power of 0.8 and moderate effect size). What am I doing wrong? Obviously it is impossible for the cell biologist to collect that many biologically independent samples, how do you calculate POA then? I know the "triplicate biological w/ triplicate technical" is quite standard, but what is so magical about 3x3? POA should be done to address proper sample size, I'm just not sure how I go about doing it relative to cell biology work.