Israel is committing what some experts are calling a genocide. In any case, they killed a lot of civilians. It can probably be debated whether this is noble or "striving to be better". But either way, the political beliefs and hobbies of the laureates aren't interesting to me, and I can't imagine the Nobel committee seriously taking this into account.
I am really surprised they fired him for a really relatively mild series of tweets. I know some of the Israeli scientists leading the campaign against him also pointed out he tweeted "Fuck Israel" in 2018 [0]. Due to the date, May 15 2018, he is probably referring to IDF slayings the preceding day during Palestinian border protests [1]. Nature also did a factual write up of this guy's firing [2].
Writing Basel as Bâle would be silly and non-standard too, yes. Maybe "wrong" is too strong of a classification. But for example, I wouldn't immediately recognize it as Basel in a headline. FWIW Leuven refers to itself in English as Leuven on their own website: https://www.leuven.be/en
Also somewhat interesting to me is that for some reason people think Belgium is mainly a French speaking country, but in fact there are actually more Dutch speakers than French speakers (56% vs 38% native speakers according to Eurostat in 2015) - I have the sense referring to Flemish cities by their French name reflects that
Interesting history, but people in Leuven call this city Leuven and not Louvain. No need to use the french term in a flemish city where almost no one speaks french as their first language. In fact, french language was the subject of some amount of political struggle in the 1960s, resulting in the founding of the french speaking university in "Louvain-la-Neuve", a planned city that was built in (french speaking) Wallonia for this purpose. You can read more about the politically important language discussion that occured in the 1960s here: https://en.wikipedia.org/wiki/Split_of_the_Catholic_Universi...
They use a random forest classifier, which is an ensemble model that gives a consensus result of several decision trees. One way to achieve this consensus is voting. Random forest models are commonly used in building chemical models like this (and in QSAR), because they are quite robust. Due to the typically small size of chemical data sets (dozens to thousands, typically), more sophisticated methods are not usable and do not perform better.
High-throughput screening (HTS), i.e. testing a large amount of compounds in simple biochemical assays can't be compared with testing 10 compounds in monkeys. The point of HTS is finding active substances in a large collection of compounds (finding needles in the haystack), and then using this as the initial step of a whole chemical optimization research program that may lead to a new drug candidate down the line.
Conversely, the 10 compounds tested in monkeys will usually be advanced drug candidates just before phase 1 trials in humans. If you would give monkeys 10 compounds from a HTS collection you would learn nothing about what works in human disease because most compounds are inactive at a given target.
Every large pharma company has HTS infrastructure and uses this for early discovery (in addition to animal experiments at later stages of drug discovery campaign) - and these companies are interested in making profit by discovering new drugs that meet the requirements to get approved, not in generating publications or boasting about their fancy HTS robot.
Agreed the process is very simple. The innovation that makes the resolution worth it is (as Derek also mentioned in the blog post) an efficient way to re-racemize the L-meth to DL-meth, which can then be resolved again. With steady state production and pooling this means it can be done using just one batch size (and not ever smaller "brsm" style bathces). If these steps are efficient enough you definitely get much more bang for your buck. Here is one such method[0] which probably inspired these drug manufacturers (as they use thioglycol and AIBN, which has been found in clandestine lab seizures).
I was wondering the same thing. I found this in a guardian article
> The military’s firefighters use aqueous film-forming foam, or AFFF, which contains extremely high levels of PFAS, in training exercises and emergencies. Though AFFF is effective, it has led to widespread contamination around bases and airports, and Congress just mandated the military check for PFAS pollution at 700 facilities while earmarking $571m for cleanup, though observers say the cost will likely be much higher.
I may be misreading it, but doesn't the GoL as commonly understood also depend on diagonal neighbors (i.e. 8 direct neighbors)? In that case the rule space would explode beyond the 32 bit integer one. (to a 256 bit one)
BOL-148 is not like the others. All others are N1-acyl analogs of LSD, so unlike bol148 they rapidly metabolize to LSD proper. This also means until they make a prodrug or analog law, it will be easy to keep on thinking of new LSD prodrugs. Here are a few free ones that will certainly work, no payment to me required: isovaleroyl, cyclobutanecarbonyl, oxetanecarbonyl(both isomers), cyclopropylacetyl.
They definitely will, this is after all the intended purpose of these firms, and some of the more professional among them are producing cGMP APIs at scale in a completely legitimate context. Although if you have a need for ACE2 inhibitors (not sure which kind of binders you need for which purpose ...) that are marketed and formulated it may be more convenient to just source a large amount of the pharmaceutical product, though I can't comment on the legality of doing that.
Fluorine on an aromatic ring is not labile: other examples of substances with fluorinated aromatic rings are fluoxetine(prozac), citalopram (celexa) and paroxetine (paxil), which are antidepressants many people are taking daily without fluorine-related toxicity
With all due respect for the forensic chemists and their good work on identifying an unknown substance, it is fairly common for forensic groups to once in a while detect new chemical analogs of known drugs. A few years back, lots of new cannabinoids and cathinones were getting released constantly as older analogs were getting banned. Often, these novel analogs are pharmacological low hanging fruit. The drug in this article is also such low-hanging fruit: it is well known an N-methyl to N-ethyl substitution does not lead to reduced activity in this category of arylcyclohexylamine dissociative anesthetics (this was actually one of the SAR considerations taken by the designers of methoxetamine!). And indeed, this very same substitution was used here on 2-Fluorodeschloroketamine, leading to the drug from the article.
PS the Chinese abbreviation for "CanKet", 2F-NENDCK, most likely stands for 2-fluoro-N-ethyl-nordeschloroketamine. It is almost certain this drug was synthesized by a Chinese custom synthesis group (the most typical source for these type of substances at scale) and not by Australian clandestine chemists.
Pretty unlikely. The F would be already in place at an early stage, the precursor is probably 2-F-benzonitrile, alternatively 2-f-phenylmagnesium bromide.
(I have a background in organic chemistry as well)
I somewhat disagree with this. Measuring chemical similarity is notoriously difficult, see these two interesting blog posts from a cheminformatic angle [0][1]. The molecules are not only pharmacologically similar but even chemically at least somewhat similar, perhaps in the same way a dog has much more similarities with a flying squirrel than with, let's say a church. I would argue the main active molecule [2] is relatively similar to LSD (compared to other well known psychedelics) due the presence of the tetrahydropyridine unit, which is also present in LSD, albeit connected to the 3 position of the indole in a different way. Also, there is a pharmaco*phor*ic similarity: positively charged N and 5-6 fused aromatic ring oriented in the same way with some degree of rigidity (though you could argue this is just a roundabout way to bin it in a category of 5ht2a binders). So in this way, I feel that it has something like an LSD-based design philosophy to it.
Quantitatively, making use of one of the most common similarity metrics, the Tanimoto similarity of ECFP4 fingerprints, the similarities to LSD, psilocin, DMT and mescaline are respectively 0.17,0.15,0.18 and 0.07. In other words, the similarity is low to all compounds and the indole derivatives are about equally far removed from the compound from TFA, although a bit closer than mescaline. The numbers probably rather follow your line of reasoning.
Finally, I'd also like to remark that I consider the fact they generated quite novel chemical matter a plus: most of the people working on generating new 5HT2A agonists are currently using quite conservative classic SAR approaches, for example creating constrained (e.g. Lophora's azetidines) or deconstructed versions (e.g. Delix's ring opened LSD variants and ibogaine analogs) of better known compounds, or even just prodrugs of known compounds (Field trip's FT104 is a 4-HO-DIPT prodrug). This will also make it easier for them to fight patent challenges if this series of compounds will lead to a clinical candidate.