This is a non-issue with Polars dataframes to_pandas() method. You get all the performance of Polars for cleaning large datasets, and to_pandas() gives you backwards compatibility with other libraries. However, plotnine is completely compatible with Polars dataframe objects.
> Life's two most fundamental properties are homeostasis and reproduction.
> The loss of these two combined with its parasitic nature makes this cell a form on non-life.
This is a decidedly Eukaryote-centric take. Homeostasis in higher mammals is a complex network of genes -> RNA -> proteins -> metabolic pathways
Reproduction is also far more simple in organisms with binary fission cellular division.
A more appropriate scientific term would be obligate commensalism vs. "parasitic". That actually encapsulates their need for metabolic precursors from the host, but allows for tRNA, rRNA, origin of replication, etc...present in the organism's genome.
For all the folks saying, "Isn't this just a virus?"
The actual paper states that the genome encodes transfer RNA's and ribosomal RNA's. I think that's a really important biological distinction missing from the popular press junket. The primary source material is well written and elucidates a lot more than the Quanta article. https://www.biorxiv.org/content/10.1101/2025.05.02.651781v1
Yeah I think this is definitely the future. Recently, I too have spent considerable time on probabilistic hyper-graph models in certain domains of science. Maybe it _is_ the next big thing.
Countable is a relative term in microbiology. I like that the author stuck to the phrase "countable colonies", since colony forming units are not really "countable as cells".
Ah, brings me back to the countless nights I spent counting plate after plate of HEK293 cells using a Haemocytometer [0], a light microscope, and a mechanical counter [1].
At least with HEK293 cells you could mostly tell if they were dead through the microscope (dead cells are darker).
I've made the same transition and feel the same way. I miss the bench, but I don't miss the late hours, vending machine dinners, and Christmas day cell culture maintenance.
> Meet MemMachine, an open-source memory layer for advanced AI agents. It enables AI-powered applications to learn, store, and recall data and preferences from past sessions to enrich future interactions. MemMachine's memory layer persists across multiple sessions, agents, and large language models, building a sophisticated, evolving user profile. It transforms AI chatbots into personalized, context-aware AI assistants designed to understand and respond with better precision and depth.
This seems really interesting for local LLM experimentation.
This! The amount of clinicians I know who simply read the abstract of a case study, with no real statistical interpretation of results, is a non-zero number.
Whenever I see some hyped up popular press article about a scientific study, my immediate reaction is to go to the primary literature. First, I read the study design and analysis methods, then I determine if its even worth continuing to read the rest. Study pre-registration should be a must and papers need to be more explicit about being exploratory when the sample size dictates it.
