D Roovers

@chrisklomp Ik heb een keer een PSA test geweigerd die me bij de uroloog werd aangeboden, zag er toen het nut niet van in. Paar jaar later wel gedaan toen ik een plekje op mijn staartbeen had (het schijnt dat prostaatkanker soms uitzaait naar bot). Gelukkig was het niks bijzonders

Ik had bedacht om binnenkort een Space te doen over mijn advies aan mannen (50plus) om een PSA-test te laten doen. Er wordt nogal verschillend over gedacht en misschien is het aardig om deskundigen aan het woord te laten. Dus dat.

@JaapStalenburg Ter Apel heeft ongeveer 35% van de bevolking van de gemeente Westerwolde (9000/26000). Maar een klein percentage van de bevolking heeft last van het azc

Opmerkelijk inderdaad. In Ter Apel is maar 1 partij tegen het AZC. En die haalt nog geen zetel ook. Hoe zit dan met de door radicaal rechts opgedrongen frames dat ‘het volk’ in Ter Apel veel overlast ervaart van de asielzoekers daar. Het begint op factfree ophitsen te lijken.

uitstekende vraag dit

@maximilianbladt Op 20 maart in Nederland:

Vrijdag hebben we een testrit gemaakt in een Tesla met Full Self-Driving. We hebben de auto gepusht door hem over de dam te laten rijden tijdens de spits, waar zelfs verkeersregelaars stonden. Fascinerend om te zien hoe als AI expert/ondernemer hoe AI systemen steeds meer taken overnemen in de fysieke wereld, zelfs autorijden. Het mooiste moment was toen een wegwerker ons eerst stopte en toen doorwuifde. De auto begreep de handgebaren en luisterde. Benieuwd wanneer men dit legaal kan gebruiken in NL 🇳🇱

@J41963735 “Goudse kaas” is geen beschermde naam, dus kan overal gemaakt worden. Blijkbaar is het in Spanje goedkoper om te maken

We worden bestolen #NieuwsInPerspectief

This pattern will blow your mind

A non-hyped explainer of the “cell simulation” paper. The recent study about the “4D” simulation of a minimal cell has been getting a lot of attention on social media. Unfortunately, most posts about it have serious errors. I’ve seen people claim that the model simulates every chemical reaction in the cell, for example, which is not true. Some biomolecules and reactions *are* tracked individually in the simulation, including proteins and RNA (and ribosomes), and the chromosome. But the simulation does not track individual metabolites (like ATP or glucose), water, nucleotide precursors, lipds, and so on. These "other" molecules are represented, instead, as concentrations (using ordinary differential equations). But anyway, here goes my quick explanation: Researchers built a computational model that simulates roughly 100 minutes of biological time, or one cell division, for a single bacterial cell. Each simulation takes 4–6 days to run on two NVIDIA A100 GPUs, and the authors ran it 50 times in replicate. The cell simulation includes some elements of randomness, so each replication attempt leads to a slightly different outcome. When they plotted out these replicates and averaged results, they found that the model could predict a few things without being fitted to experimental data: The simulated cells “divided” every 105 minutes, on average, which matches experimental results; and the mRNA molecules had an average half-life of 3.63 minutes, which is roughly what we’d expect from experiments, too. The cell they are modeling is called JCVI-syn3A, and it is not a naturally-occurring organism. It’s a bacterium that has been engineered, over many years, to have a small genome. It only has 493 genes (compared to 4,000+ for E. coli), all of which are housed on a single chromosome. The Syn3A cell was made by taking a natural organism, called Mycoplasma mycoides, and then slashing out non-essential genes. Its entire proteome, transcriptome, and metabolism have been studied in depth, which is why it’s being used to build these whole-cell simulations. The actual *simulation*, though, is not a single thing! Instead, the authors wrote down all the “stuff” that happens inside a cell (transcription! translation! metabolism! lipid biosynthesis!) and decided which type of mathematical model would be best-suited to describe each thing. Some cell processes were modelled deterministically, others had “spatial” elements, and other parts were relatively random. More specifically, they used four different types of models to build this simulation: 1. A Reaction-Diffusion Master Equation, which was used to model the individual proteins, RNAs, and ribosomes. 2. A Chemical Master Equation, which was used to model things where spatial location doesn’t matter as much (it basically treats the whole cell as one mixed entity); including tRNA charging. 3. Ordinary Differential Equations, which you may be familiar with from Calculus class, were used to model changes in ATP concentration, lipids, and so on. 4. Brownian Dynamics, which simulated the chromosome as a physical chain of beads, where each bead represents 10 base pairs of DNA. The Reaction-Diffusion Equation works like this: Basically, they chopped up the entire digital cell into a 3D grid of cubes. Each cube measures 10 nanometers on each side. The whole cell is about 500 nanometers across, so there are tens of thousands of cubes in the cell's interior. (This is a useful way to coarse grain the simulation; if the cubes were smaller, the simulation would take much longer to run.) Each cube is a little box that contains some number of molecules. At every “step” in the simulation, only one of two things can happen to the molecules in each box: Either they react with a molecule in the same box, or they diffuse (“hop”) to an adjacent box. That’s it; the model is just rolling a die for each molecule at each time step in each box, and using those results to decide how each molecule changes over time. (The reason this spatial model is important is because biology only works if molecules physically bump into each other. And so this spatial grid means that, unlike simpler models, a protein actually has to “diffuse” across boxes in the cell to encounter its reaction partner; only then can it react and do something useful.) So anyway, each of these models is used to represent a different type of molecule. It’s not like there is a single, all-powerful simulation that they are running here; instead, they’re running these four models together, using a script that synchronizes their results with each other. The Reaction-Diffusion equation is the main part of the simulation. It takes time steps of 50 microseconds of biological time. Every 12.5 milliseconds of biological time — meaning every 250 RDME steps — the simulation pauses so that the other models can synchronize based on the latest state of the simulation. The Brownian Dynamics part runs on a completely separate GPU, and only updates every four seconds of biological time. So that's the gist here. But let's also be honest about what this simulation does NOT do: - It does not include polysomes, which are a cluster of ribosomes that all latch onto a single mRNA and translate at the same time. Polysomes are really common inside of cells, but this simulation assumes that each mRNA can only be translated by one ribosome at a time. - It does not include polycistronic transcription. In bacteria, genes are often grouped next to each other on the chromosome and thus “transcribed” (or turned into mRNA) all at once, together. The majority of genes in E. coli, for example, are arranged in these operons, and the authors of this paper acknowledge that many Syn3A genes are likely co-transcribed the same way. But the simulation doesn't capture it. - The authors manually tuned many parameters to get the model to make predictions that more closely resemble experiments. Earlier simulations were waaaayyyyy off from experimental results. For example, they adjusted the ratio of mRNA binding rates to ribosomes versus degradosomes because, in earlier simulations, mRNA was being degraded too quickly, before ribosomes could translate it, causing most proteins to be severely underproduced. - In the Brownian Dynamics model, the authors added a “fake” 12 pN physical force to push the two daughter chromosomes apart during division, because the real biological mechanism for chromosome partitioning in Syn3A is not known. - And some other things. That being said: This model is really cool! I love papers like this! I'm enamored by scientists who choose really difficult problems (like simulating an entire cell) and actually go after it and make progress! This paper is amazing because it shows us what we are able to simulate well, and what we don't yet understand, and to figure out which experiments we ought to perform to reconcile the two. So instead of framing this paper as "OH MY GOSH SCIENTISTS FIGURED OUT HOW TO SIMULATE AN ENTIRE CELL!" we should frame it as proof that there is still plenty of room at the bottom, many measurements to be made, and many avenues to explore as we seek to understand biology better.

@arselaayundita Its a magic transfer system :-) lol

Don’t throw away your kids drawings🥹

@Boldyboy1975 The egg looks fake, prepared earlier

Brilliant hack, and afterwards you get to buy yourself a new toaster, cos the old ones now knackered 🥴🤣🤣🤣🤣

@weg_met Waarschijnlijk iemand die snel hulp wilde halen om de andere mensen uit te graven

Op sommige collega's kun je bouwen, andere daarentegen zijn vooral goed in hard wegrennen... (Vijayapura, Karnataka, India)

@cooltechtipz He doesn’t like glass: it breaks and is therefore dangerous for barefoot people :-)

Superbly done 👏

@TheEdgyVeggie1 @vivscontent Ik vind dat at5.nl altijd netjes en objectief verslag geeft van deze ongeregeldheden

Frustratie bij omwonenden van islamitisch Haga Lyceum in Amsterdam: "15-jarigen maken hier de dienst uit"👇🏻 at5.nl/artikelen/2369…

@ReinBijlsma Indrukwekkend, beweging geeft de sfeer goed weer

Voor mijn nieuwe #VR-experience "The Golden Age of Dutch #AI Painting" heb ik tussendoor even voor de gein een schilderij van "Rembrandt" tot leven gewekt:

@researchUSAI @stemexplor Coke contains phosphoric acid (pH 2,3-2,7), the same happens with milk in your stomach (acid environment, pH 1.0-3.0)

@stemexplor Coke + milk = gut nuking curdled hellfire? Straight poison combo science warned us about who's tempting fate next? 💥🥛🩸

You should never drink coca cola and milk together in your entire life

@Josyanne Geen automatische spellingcontrole?

Abbonoment? Abbonement? Abbonnement? Abonement? Abonnement. ~ Josan (36), vier keer per dag.

@rkemp59 Ministers betalen dus meer, maar een lager percentage van hun inkomen. Nepnieuws dus

Zo ontzettend klaar met dat tuig. Wat een aso's 😒 #vrijheidsbijdrage

@RTLZ Doet me denken aan hachchi: trouw.nl/nieuws/ex-kame…

Van Berkel nét lang genoeg Kamerlid geweest om 2 jaar wachtgeld te kunnen krijgen rtl.nl/nieuws/economi…

@Luitzen300 @Gaia_Universe Dit heb ik een keer nazocht, een zwaan kan niet direct met een klap van je vleugels je been breken maar wel zorgen dat je valt en daardoor je been breekt of iets anders

@Gaia_Universe Een zwaan meestal niet weerloos, misschien verzwakt door de winter, maar als een zwaan aanvalt en je krijgt een klap van de vleugels, kan ze je de benen breken. Blijf dierenmishandeling en hoort straf bij. Geen foeigesprek

Volgens medewerkers van de dierenambulance is de zwaan bekogeld met stenen door een groep jongeren. Het dier raakte daarbij ernstig gewond aan zijn hoofd. Omstanders zagen bloed langs de witte veren lopen terwijl de zwaan zich wanhopig probeerde te verschuilen aan de waterkant.🤬 dehavenloods.nl/nieuws/algemee…

@HowThingsWork_ Its not the amount of light but the frequency of the light

How a camera's capture rate changes due to the amount of light being let into the camera 📷