
カビアン Hunting4MoreBioBags
4.3K posts

カビアン Hunting4MoreBioBags
@kshahi
MD/PhD-Neuroscience(with a Minor in Stonks). Try and learn something everyday! Definitely not investment advice.



Decrepit state of California's highways revealed in report ranking them worst in US trib.al/fgZ47C8



Today, in Iran, in the middle of a war, the regime executed a 19-year-old national wrestling champion for the crime of joining January protests. 💔 After signaling to the world, including President @realDonaldTrump, that they would halt executions of protesters, the regime has done the exact opposite. Three young protesters, Saleh Mohammadi, Mehdi Ghasemi, and Saeed Davoudi, were hanged in Qom after a sham trial. Reports indicate torture. Forced confessions. No access to chosen lawyers. Closed-door proceedings. No right to appeal. I call on @GlobalAthleteHQ to stand with Iranian athletes who are being silenced, imprisoned, and executed simply for raising their voices. This is not just about sports. This is about human dignity.

In 1980, a bioarchaeologist at Emory University named George Armelagos was studying ancient human bones from Sudanese Nubia, the kingdom that flourished along the Nile south of Egypt between roughly 350-550 CE, when something stopped him. Under ultraviolet light, the bones glowed. They fluoresced with a distinctive yellow-green color that Armelagos recognized immediately, because the same glow appeared in the bones of modern patients who had been treated with tetracycline. The antibiotic binds tightly to calcium and phosphorus in bone tissue as the body metabolizes it, leaving a permanent fluorescent marker. What Armelagos was seeing in bones nearly two thousand years old was chemically identical to what he saw in twentieth-century medical subjects. The archaeological community was skeptical. The received history of antibiotics began with Alexander Fleming’s discovery of penicillin in 1928, and tetracycline itself was not isolated until 1948. The idea that a pre-literate population in the Nile valley had been routinely ingesting it seemed implausible, and the initial findings were dismissed as post-mortem contamination from soil bacteria. Armelagos spent three more decades building the case. He eventually partnered with Mark Nelson, a leading tetracycline specialist at Paratek Pharmaceuticals, who agreed to perform a definitive chemical analysis. The process required dissolving the ancient bones in hydrogen fluoride, one of the most corrosive and dangerous acids in existence. What the resulting liquid-chromatography mass-spectrometry analysis found was not a trace of tetracycline. The bones were saturated with it. Multiple tetracycline variants were identified, including chlortetracycline and oxytetracycline, in concentrations indicating sustained exposure beginning in early childhood and continuing throughout life. Ninety percent of the Nubian individuals tested showed the labeling. The exposure had not been accidental or occasional. It had been lifelong and deliberate. The source was their beer. Ancient Egyptian and Nubian brewing began with grain, typically emmer wheat or barley, which in that region was naturally contaminated with Streptomyces, a soil bacterium that produces tetracycline as a metabolic byproduct. The grain was germinated, made into bread, then incompletely baked to preserve an active center, and finally fermented in vats of water. The standard practice was to seed each new batch with ten percent of the previous one, which kept the Streptomyces culture alive and active from batch to batch in a continuous chain. The resulting brew was thick, sour, low in alcohol, and highly nutritious. Everyone drank it, including children as young as two years old. The critical question Armelagos could not fully resolve was whether the Nubians understood what they were doing. The consensus among researchers is that they almost certainly did not know the mechanism. They had no concept of bacteria, no understanding of antibiotics as a drug class, and no language for what tetracycline was doing in their bodies. What they likely did know, accumulated through generations of observation and passed down as practical knowledge, was that this particular preparation of beer had medicinal effects. Ancient Egyptian and Jordanian medical texts record beer being used to treat gum disease, wounds, and other infections. The brewing method that produced tetracycline appears to have been deliberately maintained and refined over centuries, not by any understanding of the chemistry involved, but by the accumulated recognition that it worked. #archaeohistories

Yesterday, CVS-Aetna agreed to pay $117.7 million to settle whistleblower claims that they defrauded Medicare by submitting incorrect diagnosis codes to increase their Medicare Advantage payouts. Obvious question: Why are companies with documented histories of defrauding government programs still allowed to participate in them? Read more about the settlement: on.wsj.com/4lmV6LM


This is really cool (and wild): Scientists simulated a complete living cell for the first time. Every molecule, every reaction, from DNA replication to cell division. The paper (Luthey-Schulten et al., Cell 2026, doi.org/10.1016/j.cell…), just out today, used JCVI-Syn3A — a synthetic minimal bacterium with fewer than 500 genes. A 3D+time simulation of the full 105-minute cell cycle: DNA replication, protein translation, metabolism, division. Every gene, protein, RNA, and chemical reaction tracked through physical space. It took years to build. Multiple GPUs. Six days of compute time per run. And this is the simplest possible cell. A human cell has ~20,000 genes. It lives in tissue. It interacts with neighbors. It differentiates. It responds to drugs in ways that depend on context we haven't fully measured. Mechanistic simulation of the minimal cell costs 6 GPU-days for 105 minutes of biology. You cannot scale that to human cells. The complexity isn't 40x harder. It's exponentially harder. This is why the field pivoted to data-driven models. You can't hand-encode the regulatory wiring of a human hepatocyte. But you can learn it — if you have the right perturbation data collected across enough diverse biological contexts. The two approaches aren't competing. Papers like this generate the ground truth that future ML models need for validation. But the path to a clinically useful virtual cell runs through foundation models, not through scaling up mechanistic simulation. Amazing work!



I was in the middle of saying “as a born and raised New Yorker, we welcome everyone into this city” when he threw that over my head.










