CharonY

1. Only the first methionine is recognized as starting codon (in bacteria, formyl-metionine is actually incorporated at the onset of translation). Further AUG are treated (for the most part) as regular methionine. A simplified way to visualize this is that the ribosome is formed at the ribosome binding area of the mRNA, the mRNA is then pulled through until the start codon is recognized. From there the elongation of the protein is processed normally, until it is terminated. In some cases (mostly viral genomes) genes can be stacked. In this cases a second ribosome binding site can be found within a larger coding area so that the initiations starts further downstream. 2. The implications can be quite deep. To understand some of them, one has to know that the genetic code is realized by the presence of tRNA that carry a specific aa with a respective anticodon, which recognizes the particular sequence on the mRNA. So mechanistically each codon requires the presence of their respective tRNA. I.e. a tRNA carrying the respective anticodon, coupled with a given amino acid (phenylalanine in this case). Some implications: - protein synthesis can be controlled by tRNA levels. One particular tRNA may be present in low concentrations, for whatever reasons, and genes carrying their codons may not become (fully) translated. - mutations within each codon can result in different amino acids (not so much an issue in this example), likewise, mutations in the genes coding for the respective tRNAs will result in different effects (as these are different genes) - on a similar note, different bases (uracil vs cytosine in this example) have different propensity to mutate in presence of different agents, so mutation rates may differ

Yes, something else is likely to be needed, but not necessarily of viral origin. I was thinking if intracellular parasites in general. Bacteria are an interesting example (think in terms of mitochondrial-nuclear gene transfer). The precise mechanisms are afaik unknown, however.

Basic text books are your friend. Either general biology (such as Campbell) or specialized genetics books (Lewin for example).

The article describes retrotransposons as a source of horizontal gene transfer, something that has e.g. also been described in Drosophila. The actual mechanism is still unknown, but hypotheses include parasites as vectors (including e.g. bacteria). Wolbachia is an example (again, with Drosophila). Retroviral transfer is a more classic route (though not the subject of the paper in question), but would not be considered terribly novel, I would think.

I am not quite sure what the question is, but hemosiderin occurrence is linked to ferritin, in fact it appears a metabolized form of ferritin. As such it is a means to reduce intracellular free iron. The source of the iron does not play a major role in this regard, i.e. neither the ferritin molecules nor the responsible regulators do not know where the rise in iron content comes from. The reason why it is being linked to Hb degradation in certain textbooks is that hemosiderins are often found in macrophages and in these cases a plausible source is the degradation of red blood cells. However, it is only one example to describe the situation where hemosiderin may be observed and is not the biochemical pathway leading to its formation per se (nor its biological role, for that matter).

Also one should be asking whether e.g. you envision an academic or private sector career. Fundamental research is mostly in the academic area. But usually there are only few pure research positions there.

Yes, most animals have reduced anabolic amino acid pathways. Apparently there was no selective pressure to maintain the respective genes and subsequently we lost the ability to synthesize them.

That is interesting. If they manage to deliver on that we may reconsider our current instrument road map. It would take some convincing, though, as some early adopters were badly disappointed.

The shotgun approach is not dependent on restriction enzymes, although they can be used. More often than not mechanical disruption is used to obtain less biased fragments. Even if you can sequence over a specific area with repeats (i.e. have sufficient read length) base calling (identification of the correct base) can be an issue as repeats tend to generate results with resolution. IIRC PacBio has pretty much abandoned strobe sequencing (in favor of the RS system with a few kb read length). I am not sure whether they go a grip on the accuracy issue, though.

The stability of a peptide also depends on its tertiary structure. If the peptide is not denatured, proteases may not be able to access the cleavage sites. Also it depends a bit on how you assess whether there was proteolysis or not (e.g. searching for fragments or indirectly via activity assays). Peptides may retain biology activity to some extent, even after cleavage. I have not read the paper but looking at the sequence there are quite a few cysteins (allowing for disulphide bonds). Moreover they generally do not ionize well and yield low signals in MS, which may limit identification of fragments. But in addition we see a number of hydrophobic residues, such as tryptophane and tyrosine, so my guess (without any close analysis) is really that tertiary structure may inhibit cleavage.

Actually no. A properly constructed study looks at relationship and does not set out to find a particular one. As such studies are not supposed to have intentions. Of course there may be researchers biased towards a particular outcome, but the idea of a good design is to prevent any influence in that regard. I think Hemenway made a good point about the overestimation of the effects, especially as they managed to reproduce the results but added a control to demonstrate that there is likely a severe flaw in it. This is a point that Hemenway specifically addressed by asking whether the assailant was wounded. The resulting numbers were a clear overestimation.

Ah, well maybe on the website. The studies (papers) themselves are a bit better and usually the conclusions are also formulated in a much more careful way. To me it does not actually mean that the authors were biased towards the outcome, but they would rather not acknowledge a faulty methodology in their study. There are a few correlation studies that looked into whether right-to-carry laws have any influence on crime rates. The consensus appears to be that the data does not support any correlation between RTC laws and crime (in some cases an inverse correlation was observed). (Aneja et al AMERICAN LAW AND ECONOMICS REVIEW Volume: 13 Issue: 2 Pages: 565-632 DOI: 10.1093/aler/ahr009 Published: FAL 2011)

I am not quite sure what you mean. I assumed you initially provided the link from the Kleck study? But as I mentioned, it appears to be a statistical error due to the low numbers problem. There are further studies that apparently look at specific relationships and also may have corrected for this error (it does not appear to be a finger pointing issue or manipulated data at this level). But I would have to read a bit more, when I got some more time (there a lot of them around, judging from abstracts the effects seems to have vanished in newer studies). I should add that many of these studies may suffer from certain issues in the estimation methodologies and models. That is also addressed in a number of studies.

I would have to read through the website (despite the hideous color scheme), but are there peer-reviewed studies supporting the assertion of that website (especially as they do not present references in a convenient format), It should be noted that the Kellerman et al. paper is based on a regional sampling, a nationwide (comparative) study could probably provide more global insights. Edit: found a paper (Armed resistance to crime: The prevalence and nature of self-defense with a gun Kleck, G; Gertz, M: JOURNAL OF CRIMINAL LAW & CRIMINOLOGY Volume: 86 Issue: 1 Pages: 150-187 DOI: 10.2307/1144004 1995) The findings are apparently somewhat controversial. Kleck and Gertz estimated a number of 2.5 million defensive gun uses per year between 1988-1993 based on a telephone survey (with n=5000). This number was faced with scepticism as estimates of crimes committed firearms were estimated to be around 1.3 million per year. Hemenway and others have looked into this, and it appears that these kind of surveys may result in an overestimation of effects. They have, for instance, conducted a similar survey which yielded slightly lower but still roughly the same results. However, with follow-up questions they also estimated how many attackers were wounded or killed during these defensive actions The surprising result was that the the number was roughly the same as the total amount of gunshots (fatal or not) reported. Yet almost all of the reported number were due to accidents, suicide or criminal assault (i.e. not a defensive gun shot). Likewise, based on the survey data the authors estimated that 322,000 of the defensive cases were to thwart rape attempts. Again, a number higher than the total number of recorded rapes and rape attempts. A reason is that the survey tries to identify a rare event (defensive gun shot) and thus even small false positives can massively distort the estimates. (see Journal of Policy Analysis and Management, Vol. 16, No. 3, 463-469 (1997))

Best bet is to look at the websites of companies related to your field (maybe biotech or analytical labs, for example) or use job websites. Job fairs are also a good way to get industrial contacts.

If you are thinking with regards to an academic career, the outlook is bleak. The only real stable position is becoming a tenured professor (there are also positions in private and national labs, but they are so few that one should not plan on getting them), meaning that between teaching, getting funding and leading a lab you will have little time for actual research. However, less than 20% of all PhD holders will eventually get tenure. How to land a job? In the end it depends on a heap of luck (you can tweak chances to your favor, but not just by being a good scientist). It depends on whether you happen to work on a project that is a hot topic. It depends on whether your PI during your PhD/postdoc has the interest and power to further your career. In other words, many factors that are not in your power contribute to it. The reason is that there is a huge surplus in capable scientists, and nowadays it is almost impossible to distinguish yourself on your own. In short, degrees do not land you a job, contacts and networks do. Just to give an idea, after PhD you are going to become a postdoc, which, depending on the lab (and country) often involves working on several projects, leading grad students, some administrative work and sometimes teaching. Generally around 4 years are expected in biological sciences then you are supposed to find a faculty position. Problem is that most will not get it (as mentioned) and if you hang around for longer it actually reduces your net worth. Depending on area your likelihood of getting interviews drop after prolonged postdocs. So you technically have a somewhat narrow (though depending on your work often flexible) window to make a transition to faculty. After that (if you are really lucky and have networked like crazy) you may become an assistant prof (or equivalent) and you are tasked to lead a lab, teach classes, doing administrative work (on faculty level) and get funding in. At this stage getting money is usually one of the main criteria of actually keeping the job (i.e. getting tenure). The funding rate of the big agencies such as NIH are somewhere between 2-10%. So if you do not get money after 5 years you may get your tenured denied. At this stage you may be around 40 and out of a job. Chances of getting a new shot at tenure are low as the new generation(s) of academics are now on the tracks. In other words, if you want a stable and secure career with clear progression, academia is not for you. It is a highly competitive field and there is no clear path towards a career here. You really have to want that life, otherwise it is really not worth the stress.

Well, teaching is not necessarily helping Also, professors are talking to you?

Usually you can start during your undergrad study as a volunteer, but it generally requires a little experience (e.g. taking a few practical courses in the area). Undergrad research often results in more work for the researchers in the lab (as they have to do hands-on teaching), and having no basics is usually a bit too much effort (unless you demonstrate some practical usefulness). Most funding is provided by agencies such as NIH, NSF and other federal or state departments. Sometimes research (usually applied) is sponsored from other sources. Depends on type of funding, research and reputation of the principle investigator. Getting personal stipends, for instance, is not super-hard. Getting research funds to actually run a lab, much more so. On average the NIH funding are dropping well below 10% (i.e. 90% of all grant applications are rejected), with the more sought-after grants being much lower (close to 1-5%). The average R01 (which is one of the oldest funding mechanisms of the NIH and is considered a bread-and-butter fund) is in his/her 40s, for example. Depends on to what purpose you join a lab. Generally you just ask. Undergrad research is generally not tied to a given degree (but can naturally lead to a bachelor/master/PhD thesis. Research is generally never completed, chances are that if the results are useful someone else will continue, if you produce crap it will be scrapped. Note that there significant differences between countries (or even type of schools within a country).

Depends on what you really want to look at. The first step is to assess sequence similarities which is mostly done via alignments of the peptides under investigation. Clustal is commonly used as well as Dialign (among others). The rest depends on the conclusions you want to draw, e.g. simply just sequence similarity, or true homology. For the latter (i.e. the identification of shared ancestry) just a comparison of two sequences is generally not enough, as you need reference sequences to really trace ancestry.

I was under the impression that English was taught at a fairly high level in Sweden. Wouldn´t it be better to have someone in-house to look over things? Usually it is easier to coordinate that way.

I do not think that we have got a neuroscientist here. My suggestion is to pick up a few good neuro books (e.g. Kandel or any of the many available). Note that in science you do not necessarily get a good mentor relationship. It depends a lot on size of the lab and the principal investigator. Also note that the right research group tends to be become relevant during the postgraduate studies, before that showing a good foundation is usually sufficient.

It depends a lot on the school and ideally you should look for one with a strong curriculum as well as active research. Generally it is not taught in the first two semesters or so, as some foundations in bio are needed. I am thinking that courses may start popping second year or so. It depends how strong and focused bio teaching is (as opposed to life-science oriented curricula).

I agree with the relevance of post grad experience, but you also need some education on cell and molecular biology. It depends a lot on the area (e.g. cancer biology, diagnostics, oncology, pharmacology, etc.). ACS for the most part are not terribly suited to learn about cancer (except for analytics). Better journals are more bio oriented (such as Cell) or medical (e.g. Cancer Research, Lancet Oncology etc). Though for starters textbooks tend to be better,supplemented with current reviews (including from review journals such as Nature Rev Cancer).

Differentiated cells could be used in cases where you want to distinguish them from pluri- or totipotent cells (pluripotent cells are not fully differentiated, but more limited in what they can become than totipoten cells). In almost all other cases you would designate the cells according to what type of cells they are (which can be more or less specific, depending on context).

There are several issue which stand out to me as someone who is not actually actively involved in securing funds. And again, I would like to separate the issue of acceptance of scientific idea and their fundability as the two are not the same (though intertwined from a career viewpoint). I only skimmed the latter part of the essay the first time and came to the conclusion but after re-reading the author pretty much confirmed that it is written from a student´s perspective (see title and the first few sentences of the essay). Another aspect that the author completely ignores is that established scientist in a field usually have a reason for their reputation (i.e. experience is a specific area). If they compete with a newcomer, they are very likely to have an advantage. Is it disproportional? Obviously, once you managed to get funding your chances of getting more increase. The big hurdle is to get your first grant in. It is less an issue of innovation, but of seniority. An established scientist has a bigger chance to push through a somewhat quirky idea (due to his track record) rather than a new one. There are different mechanisms in the NIH (not the mentioned transformative grant that the author mentioned, its goal is a completely different one) that are supposed to help junior scientists, including postdoctoral level grants, as well as a less harsh review process for first-time grants. Nonetheless, this is not about accepting new ideas at this point. Also the author is not very coherent in his argumentation as in the first part of his assay he cites reluctance of novel ideas by citing some (let´s say, controversial) ideas of very established scientists and then claim that established scientists do not have novel ideas (note that the examples were also not necessarily novel, such as. GM food toxicity).. Also he somehow equates contradiction with existing finding as novelty. How is simple contradiction a novelty? A true novelty does not contradict existing knowledge, but expands it. And finally the idea of crowdsourcing, especially for life sciences is a typical hip idea that is not very thought out. If a problem is so specific that you cannot gather sufficient support from the scientific community, how much do you have to dumb it down and sensationalize it to gather significant amount of public interest? Also the author does not appear to know the amount of money required to establish a successful research project. A R01 (the bread and butter grant from the NIH) has a volume of one million in direct costs plus overhead. How many projects of that volume could be reasonably crowdsourced? If that was the way to go we would only do high-profile rock and roll research (which, incidentally the NIH is quite keen on funding) rather than the more basic research that will open up new horizons. As a whole the essay is merely an opinion piece with little on data from a rather limited perspective. Note that the funding system (more or less worldwide) is not ideal. Not even close, but the real problems are much more in the details.