• Can I include lithium ion batteries (nobel prize 2023)? It's on the edge of the chosen timeframe. They hit the market after 1991, but the tech developments were earlier. This is an important one because it made the world look more "futuristic" in a wide variety of ways, because of all the portable electronic devices.
• LED lighting (nobel prize 2014). The main development was efficient blue LEDs, since it's easy to redshift with a stokes shift and get a mixture that looks white. This one is special, not just because it lowered our electric bills and saved us much of the time we used to spend replacing bulbs, but because it changed the "look" of the world. Now if you time travelled back to when I was a kid, it would look like the past, the quality of the light would be different.
• The "sequencing by synthesis" methods used, with variations, by Illumina and other companies. We used to call it "next-generation sequencing" in contrast to the gel electrophoresis methods, but idk what to call it 20 years later. The Illumina method involves "polonies" of identical DNA fragments on a glass slide, large enough to see under a microscope. This required a clever method of like, spatially localized DNA amplification. Then one base at a time is added, with a fluorescent tag, so which of the four bases was added can be determined by the color of the polony. There's a digital camera in the machine, you get images of all these little dots. Sequencing got very cheap very fast, people started sequencing everything. Important to the application of "targeted therapy" which is the next bullet point. Also led to huge sequence databases that clarified the evolutionary history of life. And also, in these sequence databses you could see correaltion in the evolution of different sites in the same gene, which sometimes corresponds to physical contacts in the protein product (site A mutated to a larger amino acid so site B mutated to a smaller one, etc). This coevolutionary information then began driving progress in the protein folding problem, culminating in AlphaFold.
• "Targeted therapy" for cancer. Maybe I should just say imatinib, and the paradigm it established. That is, identifying mutant genes in cancer, and making drugs targeted to their protein products. Some people prematurely predicted victory in the war on cancer, but in patients with stage IV disease, resistance to targeted therapies tends to develop quickly, since there's always some subpopulation of cancer cells with a mutated target that the drug doesn't bind to, or with the ability to remove the drug from the cell, or just aren't reliant on the targeted protein. But the original success holds up: patients with chronic myelogenous leukemia are treated with imatinib, and then other drugs as resistance develops, and it's slow enough that they can often chase resistance your whole life until you die of something else. And targeted therapies can be lifesaving for earlier stage cancer, for example adjuvant trastuzumab in Her2 positive breast cancer, which in a few percent of patients prevents relapse after surgery.
• Immunotherapy for caner (nobel prize 2018). The first success was a CTLA4 inhibitor used for melanoma. CTLA4 is not a protein mutated in cancer, rather it's a protein found in immune cells. It's part of a feedback loop that puts the brakes on immune responses, and inhibiting it is like cutting the brakes, to use the same metaphor as Jim Allison. In a small fraction (maybe 10%?) of stage IV melanoma patients, the immune response cleared the melanoma, and it stayed gone for years. Maybe forever in some cases? Hard to find really long term followup in clinical trials. This kind of lasting response in stage IV, when the cancer is spread throughout the body, is what was missing from targeted therapy. Hard to say why it happens; maybe as the cancer adapts, the immune system adapts too? But the success in melanoma proved hard to replicate in other cancer types. Melanomas originate from cells that have taken heavy genetic damage from sunlight, and already appear "foreign" to the immune system to some degree before they even become cancerous. This kind of thing may be the mechanism behind vitiligo, and in fact patients treated with immunotherapy sometimes get vitiligo. You can live without melanocytes, so some long term responses could be essentially induced vitiligo that also kills off the cancerous melanocytes, I guess. Based on this reasoning, if you had to guess another cancer where immunotherapies have worked well, maybe you'd guess lung cancer, and you'd be right.
• The Vertex cystic fibrosis drugs, which I wrote about before. Not paradigm-setters like imatinib or the CTLA-4 inhibitors, but I suspect they will be. Treating a genetic disease with a drug that restores function to the protein product of the mutated gene. What the fuck.
• Gene therapy! I tend to talk about the gene therapy for sickle cell anemia, but that's just for storytelling reasons: sickle-cell anemia was the first genetic disease to be understood on the level of a defective protein, so the time from that discovery (1949) to FDA approval of a gene therapy to insert a hemoglobin gene (2019) is a good way to frame the story of the development of gene therapy. But there's a handful of approved gene therapies now, mostly from the last ten years.
• mRNA vaccines, of course. I feel like this could have been an even bigger deal than it was. After imatinib, "chasing resistance" required repeating the drug development process: identify a mutated version of the target protein, find a drug that will bind to it, and the changes you made could affect bioavailabiltiy, pharmacokinetics, toxicity, it's a whole new drug development process. mRNA vaccines, if the virus mutates, just make a corresponding change to the sequence in the vaccine. I think we were denied the full potential of this innovation by a regulatory process that was adapted for drugs. Anyway, we'll see where this technology goes. An important underlying scientific discovery was the effect of mRNA made with modified nucleotides (Nobel prize 2023)
• Deep learning. Including AlphaFold, which i already mentioned. And large language models, I love github copilot code autocomplete. Game playing, image recognition, one classic AI problem after another.

• don't call what you create "content". regardless of what it is. that's the devil talking. call it art, call it writing, call it music, call it analysis, call it editing, literally just call it what it is
• I was going to put other things but oh my god please just don't call yourself a "content creator". you are a person you are making art / writing / music / etc you are an artist an author a musician
• you are not an Image Generator For Clicks And Views. please. allow yourself to connect with your work by naming it properly and acknowledging yourself in kind

• Shitposting? You're a comedian, a satirist.
• Long posts about other people's art? You're a critic (positive), a scholar.
• Long posts exploring ideas, society, and the world around you? You're an essayist, a philosopher.
• Can't get enough of sharing information about X topic? You're a scholar, an educator, a columnist.
• Just love collecting and sharing other people's stuff on your blog? Archivist, curator, collector.
• Just not sure where you fit? Babe, you're a blogger.

Frodo and Sam's journey