Science

🧠 Your Brain Is Quietly Paying a Price for Using ChatGPT We spend hours with LLMs like ChatGPT. But are we fully aware of what they’re doing to our brains? A new study from MIT delivers a clear message: The more we rely on AI to generate and structure our thoughts, the more we risk losing touch with essential cognitive processes — creativity, memory, and critical reasoning. 📊 Key insight? When students wrote essays using GPT-4o, real-time EEG data showed a significant decline in activity across brain regions tied to executive control, semantic processing, and idea generation. When those same students later had to write without AI assistance, their performance didn’t just drop — it collapsed. 🔬 What they did: 54 students wrote SAT-style essays across multiple sessions, while high-density EEG tracked information flow between 32 brain regions. Participants were split across three tools: → Solo writing (“Brain-only”) → Google Search → GPT-4o (LLM-assisted) In the final round, the groups switched: GPT users wrote unaided, and unaided writers used GPT. (LLM→Brain and Brain→LLM) ⚡ What they found: Neural dampening: Full reliance on the LLM led to the weakest fronto-parietal and temporal connectivity — signaling lighter executive function and shallower semantic engagement. Sequence effects: Writers who began solo and then layered on GPT showed increased brain-wide activity — a sign of active cognitive engagement. The reverse group (starting with GPT) showed the lowest coordination and overused LLM-preferred vocabulary. Memory failures: In their very first AI-assisted session, no GPT users could recall a single sentence they had just written — while most solo writers could. Cognitive debt: Repeated LLM use led to narrower idea generation and reduced topic diversity — making recovery without AI more difficult. 🌱 What does this mean for us? LLMs make content creation feel frictionless. But that very convenience comes at a cost: Diminished engagement. Lower memory. Narrower thinking. If we want to preserve intellectual independence and the ability to truly think, we need to use LLMs with intention. →Use them too soon, and the brain goes quiet. →Use them after thinking independently — and they amplify our output. ✨ Hybrid workflows are the way forward: Start with your own cognition, then apply LLMs to sharpen, not replace. The most irreplaceable kind of AI will always be Actual Intelligence. 👉 Full study (with TL;DR + summary table): https://zurl.co/0hnox

Today in @ScienceMagazine, together with my former colleagues at the Novartis Institutes for BioMedical Research, we report the discovery and characterization of first molecular glue degraders of the WIZ transcription factor (TF) for fetal hemoglobin derepression and therapeutic consideration in Sickle Cell Disease. Chemical Biologists may appreciate the CRBN-directed glue degrader library, here used in phenotypic screening of erythropoietic progenitors for HbF induction w/o effect on viability or differentiation. WIZ was discovered by proteomic study of hits and validated by CRISPR. Globin Biologists will enjoy the discovery of WIZ as a repressor of fetal hemoglobin (HbF). This biology has been intently studied, and here we find WIZ loss derepresses HbF by a local decrease in repressive H3K9me2, attributable to the association of WIZ and EHMT1/2. Medicinal chemists will appreciate the potent and selective activity of dWIZ-1 and dWIZ-2, the excellent drug-like properties, oral bioavailability and importantly the excellent tolerability in rodents and monkeys. For Biochemists, we show recruitment to CRBN as dependent on WIZ zinc finger 7, and biophysically characterize association by surface plasmon resonance. The CRBN:dWIZ: WIZ ternary complex buries 413 sq-A of surface area. Drug hunters like me might reflect on molecules that potently target a transcription factor with no pockets – effectively no tertiary structure predicted by @AlphaFold. This chemistry targets instead targets the ZnF secondary structure – truly marking the conceptual end of “undruggable” (if still in doubt). Hematologists will enjoy pharmacologic target validation in multiple pre-clinical models, a relatively selective impact on gene expression, the wide open therapeutic index, and the ease of end-game medicinal chemistry to produce investigational agents. Most importantly, for patients with Sickle Cell Disease. The advance of CRISPR-edited stem cells for transplantation, from our group and others, is a major advance. But patients need more accessible, safe, oral medicines especially in Sub-Saharan Africa. We welcome your feedback on this study, and hope dWIZ-1 and dWIZ-2 immediately prove valuable tools to the community and an inspiration for targeting disordered proteins. Finally, I thank all former colleagues in the NIBR TPD Initiative, and in particular this program’s true champion – Dr. Pamela Ting. Pam, working with you on this brave idea and on the collaborative assembly of the manuscript this last year are treasures I will always cherish, like our friendship. Article: https://lnkd.in/es6k87up Perspective: https://lnkd.in/ewn4eZNT

In a remote stretch of the North Atlantic, a team of marine biologists dropped a small pod into the water. Inside it wasn’t a cleanup net or machine — it was a colony of bacteria. Their mission? Find plastic. Break it down. Leave nothing behind. This isn’t science fiction. These are engineered microbes, designed to survive in salty, cold water and digest polyethylene — one of the most common and stubborn forms of plastic pollution. The bacteria don’t just stick to floating bottles. They form biofilms across microplastics — the nearly invisible shards that harm marine life. Once attached, they release enzymes that dissolve the plastic into simple carbon chains, which the bacteria then consume as food. In tests off the Canadian coast, these microbial swarms reduced plastic concentrations by up to 52% in contained zones over 30 days. No residue. No toxins. Just cleaner water. It’s not a miracle cure. It’s not instant. But it’s real, it’s replicating, and it works without disrupting ecosystems. Next, researchers plan to release the bacteria into controlled estuaries and river mouths — the places where most ocean plastic begins its journey. For the first time, the ocean has an ally that’s just as small — and just as relentless — as the problem. Science & Astronomy

Thread: Multi-omics sounds cool—until you actually try it. Here's are the nuances. 1/ You’ve got RNA-seq. Methylation. Proteomics. Time to “integrate” the data. But how? And why? Let’s break it down. 2/ Multi-omic integration sounds powerful. But it’s not magic. If you don’t ask the right question first, the answer won’t matter. 3/ Start here: Do you want shared programs across omics? Or unique signals from each modality? That choice decides your method. 4/ Unsupervised goal? Try MOFA2. Want to predict disease or treatment? DIABLO is your friend. Graph models? Great—if it performs better 5/ Real-life example: Chronic kidney disease study used both MOFA2 + DIABLO. Why? Different tools, complementary insights. Paper: https://lnkd.in/eZ_Fu83u Another New preprint for a different disease: https://lnkd.in/esXGmdqQ 6/ Here’s what makes multi-omics hard: Your matrix is incomplete. RNA-seq for 200 samples. Proteomics for 150. Methylation for 180. 7/ You can’t just “merge” them. Naive concatenation drowns real signal. Or worse—creates phantom clusters driven by batch noise. 8/ Each modality is different: scATAC-seq is sparse Proteomics is noisy RNA-seq has 20K+ features Methylation may only cover 50K regions and over 9 million CpG sites 9/ Good methods normalize each modality, learn weights, or regularize smartly. MOFA2, DIABLO, and weighted PCA all do this. 10/ Want to see how it fails? Check this post: https://lnkd.in/eMiCtVgW Spatial + gene expression integration went sideways without normalization. 11/ Math is nice. But biology matters more. If you can’t map back your result to a gene, CpG, or protein—what’s the point? 12/ These methods uncover correlations, not causes. Interpret carefully. Validate everything. 13/ Use known pathways. Run orthogonal experiments. Generalize across cohorts. Don’t trust the output blindly. 14/ Resources: Tools list: https://lnkd.in/eri4hGKR Tool review: https://lnkd.in/etcQfBm4 Overview: https://lnkd.in/esK4M-eG 15/ Key takeaways: Start with the question Pick tools based on your goal Normalize per modality Validate everything Biology > black boxes Multi-omics is messy. But it’s worth it—if you know what you’re doing. I hope you've found this post helpful. Follow me for more. Subscribe to my FREE newsletter chatomics to learn bioinformatics https://lnkd.in/erw83Svn

Oxford’s 2024 Word of the Year is brain rot—a term that once sounded like internet slang but now reflects a real, research-backed concern. The way we consume digital content is reshaping our brains. Mindless scrolling, doomscrolling, and constant notifications are rewiring our cognitive processes for distraction, instant gratification, and reduced attention spans. Studies show that excessive screen time can shrink gray matter, weaken memory, and impair executive function—making it harder to focus, think critically, and make decisions. Luckily, the brain is adaptable. Neuroplasticity means that with the right strategies, we can rewire our brains for focus, deep thinking, and resilience. Setting boundaries on screen time, curating high-quality content, prioritizing in-person interactions, and engaging in offline activities can help counteract digital overload. As technology becomes more embedded in our lives, the question isn’t whether we use it, but how we use it. Are we consuming content in a way that strengthens our minds—or weakens them? How do you manage your screen time to protect your cognitive health? 

Is climate change worsening wildfire risk? According to NASA research, the answer is unequivocally yes. --- As fossil fuel emissions accumulate in Earth’s atmosphere, more of the sun’s energy is being trapped inside, warming our planet faster than any time in the past 485 million years. 2024 was the hottest year in modern records, and these higher temperatures pull more moisture out the soil and create drier conditions that are extending fire seasons around the globe. More energy in the atmosphere also means more extreme weather, like the 100-mph Santa Ana winds that buffeted Los Angeles earlier this month. Coupled with an extraordinarily dry winter, the resulting firestorm caused more than $250 billion in economic losses and destroyed more than 12,000 structures, including the homes of more than 200 of my colleagues at NASA Jet Propulsion Laboratory — many of whom have dedicated their professional lives to readying the world for climate impacts. --- A new NASA explainer, Wildfires and Climate Change, reveals how a warming world is radically altering humanity’s relationship with wildfire. Over the last few decades: - Extreme wildfire activity has more than doubled worldwide; - Fire seasons in parts of the United States, Mexico, Brazil, and East Africa have grown by more than a month; - Earlier snowmelt, warmer nighttime temperatures, and decreasing summer rainfall have supercharged fire conditions across the planet; and - U.S. wildfires have steadily grown larger, burning wider areas of land. Many factors, of course, contribute to wildfire risk, but climate change is undeniably accelerating this risk for communities around the globe. View the full page here: https://lnkd.in/g9h3hCRi --- For more perspectives on LA’s historic fires, see powerful stories by some of my colleagues, and consider donating to the JPL Disaster Relief Fund: https://lnkd.in/gah5Sycw Benjamin Hamlington https://lnkd.in/gNU8c9xj Peter Kalmus https://lnkd.in/gDMDpN4f Whitney Haggins https://lnkd.in/gHYU576i Laurie Leshin https://lnkd.in/g9eSAZgS . . . . #LAFires #NASA #JPL #climatechange #wildfires

The first trial of creatine in Alzheimer’s disease just dropped—and the results are eye-opening. Participants took 20 grams of creatine monohydrate daily for 8 weeks. Brain creatine levels rose by 11%, and cognitive function improved across several areas: memory, reading, and attention. 19 out of 20 participants completed the protocol.  No major side effects. Over the past decade, research has shown that creatine does more than support muscle performance—it plays a critical role in brain energy metabolism and cognitive function, too. This was a small, open-label pilot study, so we need larger trials to confirm. But it’s yet another data point suggesting creatine’s potential goes far beyond the gym. https://lnkd.in/gQfUzDx5 #creatine #longevity #HealthyAging #AntiAging

Google DeepMind’s AI Co-Scientist paper was just released, and you should check it out! It represents a paradigm shift in scientific discovery, leveraging a multi-agent system built on Gemini 2.0 to autonomously generate, refine, and validate new research hypotheses. 🔹How does it work? Well the system uses a generate, debate, and evolve framework, where distinct agents called Generation, Reflection, Ranking, Evolution, Proximity, and Meta-Review, collaborate in an iterative hypothesis refinement loop. 🔹Some key innovations that pop out include an asynchronous task execution framework, which enables dynamic allocation of computational resources, and a tournament-based Elo ranking system that continuously optimizes hypothesis quality through simulated scientific debates. 🔹The agentic orchestration accelerates hypothesis validation for processes that take humans decades in some instance. For example empirical validation in biomedical applications, such as drug repurposing for acute myeloid leukemia (AML) and epigenetic target discovery for liver fibrosis, quickly helped researchers generate clinically relevant insights. What should we all get from this? 🔸Unlike traditional AI-assisted research tools, AI Co-Scientist doesn’t summarize existing knowledge but instead proposes experimentally testable, original hypotheses, fundamentally reshaping the research paradigm by acting as an intelligent collaborator that augments human scientific inquiry. Do take some time this Sunday to read! #genai #technology #artificialintelligence

👋 To all working on climate and/or urban planning: is urban design in your city's climate plan? Is decarbonization in your urban design strategy? If not, what do we need to change about how we're doing this? Last month at NYC Climate Week, Gehl - Making Cities for People and RMI debuted a piece of thinking that I'm keen to get feedback on from people in climate and urbanism. It addresses what we see as an obvious gap in the decarbonization discussion: how the shape of the city itself changes demand for energy and can be used as a powerful lever to reduce emissions. While there's much vital discussion at COP and Climate Week about supply-side energy transition, we argue that a different urban planning paradigm would make this transition *much* easier by deeply reducing demand through more efficient and effective urban form. This paradigm would allow us to reduce the need to manufacture 2x Europe’s worth of EVs, 3-4 America’s worth of solar farms, 2 Japan’s worth of wind turbines. (And so many fewer battles with infrastrcutre siting, permitting, NIMBYism, lawyers, bankers...) I know this is preaching to the choir among folks who are already advocating for compact, mixed-use, transit-oriented cities. But we suspect there are many in infrastructure finance, global development, and the general climate conversation, who could add this lever to their arsenal. Some highlights from the research: 🏙 Per capita emissions in compact, mixed-use, multi-modal cities are typically 2-3x lower than the countries in which those cities are located - regardless of whether the countries’ average per capita emissions are low or high 🚲 After controlling for wealth, urban form is the factor most responsible for the difference between per capita emissions at a country level (even more than the grid mix or nature of the economy). Countries with more compact, mixed, multi-modal cities and neighborhoods vs. countries with lower density, dispersed, car-dependent cities. 🌏 Overall, patterns of urban development are heading in the wrong direction; urban land area growing 67 percent faster than urban populations (though there are some recent glimmers of hope from the largest cities) 🌲 Business-as-usual patterns of development threaten 5-8% of remaining global carbon sinks. 🥑 Sprawl drives food waste; more infrequent bulk shopping vs. buying what you need when you need it from the neighborhood grocery. Household food waste has a strong inverse correlation to population density. 🍎 Health, equity, and economic development co-benefits come along at every stage of this paradigm shift. Thanks to our great collaborators and speakers who helped put together this research and #ClimateWeekNYC discussion including Rushad Nanavatty, Julia Meisel, Brett Merriam, Wallace Cotton, Benjamin Holland, Yuki Numata, Marissa Maze, Jackie Lombardi, Rafael Marengoni, Zack Subin, Anna Zetkulic, Robin Chase, Majora Carter and Felipe Ramírez Buitrago.

➡️ 93% of adults are no longer considered metabolically healthy. If you say “yes” to any of these, your risk of cardiovascular disease doubles (at least). ➡️ Bookmark these 7 markers to check at your next doctor appointment: 1) Waist measurement (not pants size) > 40 inches Visceral fat around your organs is associated with increased risk of nearly every disease. Track waist measurements as part of your journey as this is even more important than just losing weight. 2) Fasting glucose >100mg/dL Fasting glucose above 100 is classified as prediabetic and is a sign your metabolic health is diminishing. Stable blood sugars mean less insulin is required throughout the day. This helps to keep energy levels high and hunger in check. 3) Hemoglobin A1c >5.6% A1c is a snapshot of your blood sugar over the last 3 months. It’s more reliable than a single fasting glucose test. Higher A1c is correlated with stiffer arteries which means a higher risk for heart disease and strokes. 4) Blood pressure >120/80 High blood pressure is the “silent killer” and indicates poor metabolic health. It's a leading cause of heart disease and kidney disease and is often asymptomatic until it's not. Everyone has high blood pressure, but that doesn’t make it less lethal. 5) Triglycerides >150mg/dL Your body stores excess sugar and fat as triglycerides. But often we never use that stored energy because we continue to eat more. High triglycerides indicate poor metabolic health and are associated with increased risk of cancers and heart disease. 6) HDL levels <40mg/dL (<50 for women) HDL carries cholesterol from the rest of the body to the liver where it can be disposed of. Low HDL especially in combination with high triglycerides is correlated with increased risk of heart attacks. 7) Taking medication for any of these While medications can be beneficial to prevent the negative effects in the short term, it’s important to address the root cause. Taking meds for blood pressure, glucose or lipids is still associated with higher disease risk. Heart disease continues to be the leading cause of death by a large margin. If any of these 7 apply to you, your risk for heart disease doubles. This isn't to scare you, these can all be improved with changes to your lifestyle. But only if you take action. ---- Did you find this post helpful? Like and comment below to see more content from me on losing weight, getting off medications, and building strength.