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NYC Rapper Drew Empire @DrewEmpire718 wears N95s and organizes mask-required shows to stay healthy and to show solidarity to marginalized people with disabilities, compromised immune systems and #LongCOVID. Support #MaskTogetherAmerica#CleanAir
For myself, this is one of the most important pieces written about taking covid precautions when most people don’t. It resonated so deeply with me. I think it will resonate with many of the folks that I interact with here.
@drseanmullen
https://t.co/CFvjftw6Ik
Long COVID is defined as an symptomatic condition. However, COVID-19 can also cause organ damage without symptoms.
New Paper:
Spectrum of COVID-19: From Asymptomatic Organ Damage to Long COVID Syndrome
#LongCovidAwarenessDay
https://t.co/L3o8WOLA27
The research behind this is wild. Your sperm carries a set of instructions that tell your genes when to turn on and off. A Duke University study found that THC rewrites those instructions. The more weed in your system, the bigger the changes. It goes straight for the genes your future embryo needs in its first week of life.
I had to read the "day 3 crash" part twice. For the first three days after fertilization, an embryo runs entirely on the mother's DNA. Day 3, the father's genes switch on. If those genes carry cannabis damage, the embryo just stops growing. Fertility doctors see this happen in their labs: embryos that fertilized fine and looked healthy on day 2 go completely still by day 5.
Boston University tracked 1,535 couples trying to have a baby. Men who smoked weed once a week or more doubled their partner's miscarriage risk. That number held up even when the woman herself never touched cannabis. And the miscarriages clustered in the first 8 weeks, right when the father's damaged DNA would be doing the most harm.
Duke also found that the specific genes THC alters in sperm overlap with genes linked to autism. One of those genes, called DLGAP2, helps brain cells communicate with each other. It was changed in cannabis users' sperm. When researchers bred THC-exposed male rats and checked their offspring, the same altered gene pattern showed up in the pups' brains. The damage crossed a generation.
Weed has gotten way stronger over the last 30 years. THC content was about 4% in the 1990s but nearly quadrupled to 15% by 2018, and modern dispensary strains regularly sit at 20-30%. Concentrates go up to 95%.
Quitting for about 11 weeks (one full cycle of sperm production) reverses some of the DNA changes. Not all of them. Duke's lead researcher says men should stop at least 6 months before trying for a baby. Half of your kid's genetic blueprint comes from you, and right now, THC is editing that blueprint before conception even happens.
Microplastics have been found in human brains, blood, placentas, and testes across 1,300 species. An 18-year-old in Virginia just built a filter in her garage that removes 95.5% of them. The physics of how it works is worth understanding.
Traditional water filters use solid membranes. Water passes through, particles get caught. The problem: microplastics range from 5mm down to 1 micrometer. Filters fine enough to catch the smallest particles clog constantly and need replacing. The maintenance cost makes them impractical for household use.
Mia Heller built exactly this, over and over, after water tests in Warrenton, Virginia showed PFAS and microplastic contamination. Government agencies said no public funds were coming. Residents were on their own.
Heller took a completely different approach. Her system uses ferrofluid, a liquid containing magnetic nanoparticles suspended in oil. The key insight is polarity. Microplastics and water have different polarities. Microplastics are more attracted to the oily ferrofluid than they are to water. So when ferrofluid enters contaminated water, the microplastics migrate toward it on their own.
Then you apply a magnetic field. The ferrofluid is magnetic. The magnet pulls the ferrofluid out of the water, and all the attached microplastics come with it. The ferrofluid is recovered and reused at an 87.15% recycling rate.
No membrane. No clogging. No constant filter replacements.
She went through five prototypes before getting it working. The system filters about a liter at a time and fits under a kitchen sink. She also built her own turbidity sensor to verify the removal rate, rather than relying on visual inspection.
Municipal drinking water plants achieve 70 to 97% microplastic removal depending on technology. Her garage prototype hits 95.52%. She won a $500 prize at the Regeneron International Science and Engineering Fair for it.
The constraint she already sees: ferrofluid is expensive to produce at scale. She designed the system for individual households, not treatment plants. But the mechanism, polarity and magnetism replacing physical filtration, is the kind of first-principles reasoning that makes the best engineering.
Five prototypes. One garage. $500.
Your brain runs an authenticity detector, and AI just broke it.
There's an fMRI study from Oxford where researchers showed people Rembrandt paintings. Same paintings, same canvas, same brushstrokes. The only variable: whether subjects were told "this is genuine" or "this is a copy." When told "copy," the frontopolar cortex lit up. That's the region your brain activates for complex evaluative judgments and prediction errors. When told "authentic," the orbitofrontal cortex activated instead. That's the reward center. Same painting. Completely different neurological experience.
Your brain has two separate circuits for processing the same content depending on whether it believes a human made it.
Now layer in what neuroscientists call the predictive coding framework. Your brain is constantly generating predictions about incoming sensory information. When the prediction matches reality, you process smoothly. When it doesn't, your brain fires a prediction error signal, which triggers heightened attention and cognitive load. That signal is the same mechanism behind the uncanny valley. Your visual cortex detects something 95% right, the prefrontal cortex flags a mismatch, and the result is unease.
AI content has pushed this system into permanent overdrive. Every piece of writing, every image, every video now generates a low-grade prediction error because your brain can't confidently categorize it as human or machine. The cognitive load of constant authenticity assessment is real and measurable. Anxious hypervigilance research shows the brain amplifies these prediction error signals under uncertainty, which burns through attentional resources and impairs higher-order thinking.
The comic nails the cultural observation. The neuroscience is darker. We trained an entire species to run threat detection on every piece of content they consume. The metabolic cost of never trusting what you see is not zero.
@EVRYTHNGFATIGUE@Sean_Doc_16 Plus, one way to fund a movie is to pre-sell distribution territories, and these presales are often determined by attaching actors to those movies who draw audiences in those territories. I'm not sure how much weight is given to actors in animated movies, but it's likely not zero
@EVRYTHNGFATIGUE@Sean_Doc_16 It's also the publicity opportunities. A bigger name actor might go on a talk show or something similar as a guest and promote the movie. Voice actors SHOULD get invited to talk shows, but they don't as often. So hiring a lesser known actor can mean less soft advertising.
Your brain at 2 AM writing a paper you started at 10 PM is operating in a neurochemical state that most productivity systems spend thousands of dollars trying to replicate.
Sleep deprivation suppresses your prefrontal cortex. That's the region responsible for self-criticism, second-guessing, and the voice that says "this paragraph isn't good enough." At 2 AM, that voice goes quiet. Not because you've achieved some zen state. Because the hardware running it is shutting down for the night and you won't let it.
Meanwhile the deadline is dumping norepinephrine and cortisol into your system, which narrows your attention to a single point. Your brain physically cannot multitask in that state. No checking your phone. No opening a new tab. The stress response has commandeered every available resource and pointed it at the Google Doc.
Lowered inhibition plus chemically forced single-task focus. That combination is almost identical to what Csikszentmihalyi documented across 30 years of flow state research. Clear goal, immediate feedback, challenge matched to skill. A 12-page paper due in 8 hours hits all three criteria by accident.
The lo-fi beats matter more than people think. Repetitive audio at 60-70 BPM synchronizes with resting heart rate and suppresses novelty-seeking circuits. You stop hearing it within minutes. It becomes an auditory wall that blocks interruption without costing you any cognitive load. It's the cheapest sensory deprivation chamber ever built.
And the black coffee at midnight is pharmacologically different from your morning cup. Your adenosine levels have been building all day, so the caffeine is fighting a much stronger sleep signal. The subjective experience of "wired but calm" at 1 AM is a different drug interaction than alert-at-9-AM. Same molecule, completely different neurochemical environment.
Every semester, twice a semester, four years straight. That's 40 sessions of accidental deep work before anyone had a name for it.
The grade was an A- because the conditions were perfect. Not despite the chaos. Because of it.
🚨 Stanford researchers just exposed a weird side effect of AI that almost nobody is talking about.
The paper is called “Artificial Hivemind.” And the core finding is unsettling.
As language models get better, they also start sounding more and more the same.
Not just within a single model. Across different models.
Researchers built a dataset called INFINITY-CHAT with 26,000 real open-ended questions things like creative writing, brainstorming, opinions, and advice. Questions where there isn’t a single correct answer.
In theory, these prompts should produce huge diversity.
But the opposite happened.
Two patterns showed up:
1) Intra-model repetition
The same model keeps producing very similar answers across runs.
2) Inter-model homogeneity
Completely different models generate strikingly similar responses.
In other words:
Instead of thousands of unique perspectives…
We’re getting the same few ideas recycled over and over.
The authors call this the “Artificial Hivemind.”
It happens because most frontier models are trained on similar data, optimized with similar reward models, and aligned using similar human feedback.
So even when you ask something open-ended like:
• “Write a poem about time”
• “Suggest creative startup ideas”
• “Give life advice”
Many models converge toward the same phrasing, metaphors, and reasoning patterns.
The scary implication isn’t about AI quality.
It’s about culture.
If billions of people rely on the same systems for ideas, writing, brainstorming, and thinking…
AI might slowly compress the diversity of human thought.
Not because it’s trying to.
But because the models themselves are drifting toward the same answers.
That’s the real risk the paper highlights.
Not that AI becomes smarter than humans.
But that everyone starts thinking like the same machine.
A both funny and educational meme. Let me explain:
In the first panel, Joey is excited because the hotel’s “free Wi-Fi” is extremely fast. Anyone who has stayed in hotels knows their Wi-Fi is usually slow, overloaded, and frustrating. So when a connection suddenly feels blazing fast, it feels like you got lucky.
In the second panel, Joey checks his device and notices his IP address starts with 172.16.42.x. His expression instantly changes to shock — because that number means something very specific in cybersecurity.
That IP range is the well-known default network configuration used by a device called a WiFi Pineapple.
A WiFi Pineapple is a portable penetration-testing tool that attackers can use to create rogue Wi-Fi access points. It can imitate legitimate networks … like a hotel’s Wi-Fi and trick nearby devices into connecting to it instead of the real network.
Once your device connects, the attacker effectively becomes the network in the middle, allowing them to observe or manipulate traffic passing through it. This is a classic Man in the Middle (MitM) attack.
The reason the connection feels “fast” is simple: you’re probably one of the few people connected to it, and the attacker is letting your traffic pass through so they can monitor it.
So if you ever connect to public Wi-Fi and notice an IP address like 172.16.42.x, there’s a good chance you’re not actually on the hotel’s network…. you might be connected to a rogue hotspot controlled by someone else.
Today is day four of sitting bedside with my father.
He’s stable. He’s going to be OK. But the truth is, had I not made the call to EMS and gotten him out of the rehab facility he was in, he may not still be with us.
He fell and broke both his arm and ankle and needed rehab due to limited mobility. His arm surgery was major. Fifty-two stitches from shoulder to elbow. Because of that, proper wound care was critical.
It wasn’t happening.
While he was there, he developed an infection. When I visited Monday, his arm was bandaged, so I had no idea how bad it truly was. Then I learned he had a fever and wasn’t eating or drinking.
I went back Tuesday. This time I asked to see the wound.
What I saw is the gnarliest infection I’ve ever seen in my life. I took pictures.
He told me they weren’t changing the bandages often enough, and some days they weren’t changing them at all.
His bed linens and gown were dirty. I kept telling staff that with an open infection like that, he cannot be lying on dirty sheets. I took more pictures.
That’s when I made the decision to call EMS and get him out of there and into the ER.
Thankfully, the ER doctor acted immediately. Two IV antibiotics. A full round of tests. He’s having surgery today to reopen the arm, clean out the infection, and remove the hardware. In six weeks, he’ll need another surgery to reconstruct the bone, because the infection prevented proper healing.
By some miracle, he wasn’t septic yet.
If I showed you the deformity that infection caused to his arm, you’d lose your lunch.
Moral of the story:
Be an advocate for your loved ones.
In hospitals.
In nursing homes.
In rehab facilities.
Ask questions. Look closely. Speak up. Trust your gut.
We are also filing a formal complaint with the state.
I’m beyond grateful I listened to that inner voice. It might have saved my dad’s life.
“My husband and I were dressed and ready to go out for a lovely evening of dinner and theater.
Having been burgled in the past, we turned on a 'night light' and the answering machine, then put the cat in the backyard. When our cab arrived, we walked out our front door and our rather tubby cat scooted between our legs inside, then ran up the stairs. Because our cat likes to chase our budgie we really didn't want to leave them un-chaperoned so my husband ran inside to retrieve her and put her in the back yard again.
Because I didn't want the taxi driver to know our house was going to be empty all evening, I explained to him that my husband would be out momentarily as he was just bidding goodnight to my mother. A few minutes later he got into the cab all hot and bothered, and said (to my growing horror and amusement) as the cab pulled away.
"Sorry it took so long but the stupid bitch was hiding under the bed and i had to poke her ass with a coat hanger to get her to come out! She tried to take off so i grabbed her by the neck and wrapped her in a blanket so she wouldn't scratch me like she did last time. But it worked! I hauled her fat arse down the stairs and threw her into the backyard....she had better not shit in the vegetable garden again."
The silence in the taxi was deafening....”
~ Robyn Markham
This is one of the most important studies in sleep science.
Van Dongen et al. ran the experiment that changed how we understand chronic sleep restriction. They had subjects sleep 4h, 6h, or 8h nightly for 14 days, testing cognitive performance every 2 hours.
The 6h group’s reaction time deficits by day 14 matched subjects who had been awake for 24 hours straight. The 4h group? They performed like someone awake 48 hours.
But here’s what makes this study terrifying.
The Stanford Sleepiness Scale ratings in Panel B plateau after day 3-4. Subjects stopped feeling more tired even as their cognitive performance continued deteriorating through day 14. Your subjective experience of fatigue is a lagging indicator that eventually just… stops updating.
This explains why chronic undersleeping feels sustainable. You’ve adapted to feeling tired. Your prefrontal cortex hasn’t adapted to being impaired.
The PVT (Psychomotor Vigilance Task) in Panel A measures lapses in attention. These are the moments where you’re staring at a screen and your brain simply checks out for 500ms. Every additional day of 6h sleep adds more lapses. The curve never flattens.
Panel C and D show working memory and processing speed. Same pattern: continuous degradation with no subjective awareness.
The practical implications:
If you’re sleeping 6h and think you’re functioning fine, you’ve lost the internal calibration to know you’re not. The subjects in this study would have told you they felt “okay” while performing like they’d pulled an all-nighter.
For anyone doing cognitively demanding work, this means you cannot trust how you feel. You need to track objective markers: error rates, decision latency, problem-solving throughput.
Sleep need is biological, not negotiable. Most adults require 7-9 hours, and the research shows no population-level adaptation to chronic restriction. “I only need 6 hours” is almost always “I’ve forgotten what baseline cognition feels like.“
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Taekwondoin @TinaSugandh and her black belt kids, who always compete in their masks, warn about #LongCOVID — why they support #MaskTogetherAmerica & @pubhealthaction. “This is for all that say you can't compete to your fullest potential at athletic events with a mask on.”
The 8-hour sleep obsession may be focusing on the wrong variable entirely.
This UK Biobank study tracked 88,975 participants using wrist accelerometers for 7 days, then followed them for 7.1 years to see who died. The findings flip conventional sleep advice.
The most irregular sleepers (bottom 5%) had 53% higher mortality. The most regular sleepers (top 5%) had only 10% lower mortality. The asymmetry here matters. You’re not getting bonus years from perfect regularity. You’re hemorrhaging years from chaotic sleep timing.
And when researchers ran the models head-to-head? Sleep regularity was a stronger predictor of all-cause mortality than sleep duration. Getting 7 hours on a wildly shifting schedule does worse than getting 6.5 hours at the same time every night.
The mechanism is circadian disruption. Higher sleep regularity was associated with a 20%-48% lower risk of all-cause mortality and a 22%-57% lower risk of cardiometabolic mortality across the top four regularity quintiles. Your heart doesn’t just care when you sleep. It cares whether you can predict when you’ll sleep.
The practical implication: stop optimizing for duration and start treating your sleep-wake times as a fixed appointment with your biology.