💊 A once-daily pill that slashes “bad” cholesterol by ~58%

High LDL (“bad”) cholesterol is a slow-motion killer: it silently damages arteries and drives heart attacks and strokes. For people with familial hypercholesterolemia (roughly 1 in 250 adults), LDL is dangerously high from birth.

A new clinical trial just tested an experimental pill called enlicitide decanoate, an oral PCSK9 inhibitor:
• 293 adults with inherited high cholesterol
• all already on statins, but still with elevated LDL
• randomized to enlicitide once a day vs placebo for 24 weeks

📉 Result:
Those on the pill saw LDL drop by 58.2% on average, while the placebo group actually had a slight increase in LDL. The effect stayed strong over a full year, and side effects were similar to placebo.

PCSK9 inhibitors already exist as injections; this one is a tablet that basically lets the liver vacuum more LDL out of the blood. If longer-term studies confirm it reduces heart attacks and strokes, millions of high-risk patients could swap some injections for a daily pill.

Question:
If you had very high LDL, would you take a daily PCSK9 pill on top of statins?

#medicine #cholesterol #cardiology #pharma

Imagine your liver biopsy being scored not by a panel of pathologists, but by an AI that regulators officially treat as a “lab tool” for drug trials. That just became real.

PathAI has announced that its AIM-MASH AI Assist system is the first AI-powered pathology tool ever qualified by the US FDA (and already by the European Medicines Agency) for use in clinical trials of MASH — a common, fatty liver disease that can progress to cirrhosis and cancer. Instead of three experts arguing over how bad the damage looks on a slide, the model helps a single pathologist assign consistent scores.

Why this matters: drug trials for liver disease live and die on tiny changes in biopsy scores. Human reads are slow, expensive and notoriously variable. An AI that gives the same answer every time for the same slide can make trials faster, cheaper and statistically cleaner — which may mean more liver drugs actually making it to market.

Important caveat: this AI is cleared only as a biomarker tool for trials, not for diagnosing individual patients. But if regulators are starting to trust models as part of the evidence pipeline, how long until similar systems sit inside routine hospital workflows?

Would you be comfortable knowing an AI scored your tissue sample in a drug trial? Should this kind of model stay in research, or gradually move into everyday diagnostics?

Full story from PathAI’s press release: https://www.pathai.com/news/pathais-aim-mash-ai-assist-becomes-first-ai-powered-pathology-tool-to-receive-fda-qualification-for-mash-clinical-trials

#AI #medicine #pathology #liverdisease #clinicaltrials #FDA #biotech

Scientists may have accidentally discovered a dementia prevention tool that's been available for years.

A shingles vaccine — originally designed to prevent that painful rash you might get from a dormant childhood virus — appears to cut dementia risk by 20%. And in people already diagnosed with dementia, it seems to slow the disease's progression.

The discovery came from a quirk in Welsh health policy. In 2013, Wales offered the vaccine only to people who were exactly 79 — anyone who had already turned 80 was ineligible. This created a near-perfect natural experiment: two groups of people, virtually identical except for a few weeks of age difference, one vaccinated and one not.

When Stanford Medicine researchers tracked these groups for nine years, the results were striking. Among those vaccinated, dementia diagnoses dropped significantly. Even more surprising: people who already had dementia and got the vaccine were far less likely to die from it.

The effect was strongest in women. Whether this comes from stronger immune responses or something else entirely remains unclear. Scientists don't yet know if the vaccine works by suppressing the virus itself or by generally boosting the immune system.

Would you consider getting the shingles vaccine earlier if these findings hold up in clinical trials? Does it change how you think about the connection between viruses and brain health?

For more details, see the full article from Stanford Medicine: https://med.stanford.edu/news/all-news/2025/03/shingles-vaccination-dementia.html

#dementia #vaccines #neuroscience #aging #medicine #science

2026 is the year AI stops playing — and starts becoming infrastructure

This isn’t hype. It’s a structural shift.

IEEE Computer Society has consolidated its outlook into 26 key technology trends for 2026, and almost all of them point to the same idea:
AI is no longer a feature or a tool — it’s becoming a new economic layer, comparable to electricity, the internet, or cloud computing.

⸻

What we’ll see in the real world (not just demos)

AI & the Future of Work
AI agents become standard “team members” across most office jobs.
Competitive advantage shifts from headcount to intelligence leverage: one human + multiple agents > a large department.

Wearable AI devices
New “always-on” form factors push AI into everyday life — and sharply raise privacy and surveillance concerns.

AI-generated content
The most mature and widely deployed area: video, music, presentations, documents.
The concept of authenticity takes a direct hit.

Social AI
Assistants learn soft skills:
reading emotions, adjusting tone, negotiating, de-escalating conflict.

Embodied / Physical AI
Robots, drones, and autonomous systems scale across manufacturing, logistics, and urban infrastructure.

Autonomous driving & robotaxis
Autonomy shifts toward capital-intensive, dense urban services, powered by heavy compute and training via digital twins.

⸻

How work and the economy transform

The firm is no longer “a group of people”
It becomes people + agents.
This is stated explicitly in the AI & Future of Work forecast: agents as standard members of teams.

Jobs dissolve into functions
The labor market moves away from professions toward tasks and outcomes.
“Future of coding” and “vibe coding” mean software is produced by non-developers — code becomes a byproduct of intent.

The real bottlenecks: energy and trust
AI scaling hits two hard limits:
• power generation and data-center energy consumption
• identity, data provenance, and control

IEEE puts it bluntly: adoption bottlenecks = Trust + Power.

Skills that matter
Reskilling isn’t just technical.
Critical thinking, adaptability, communication, collaboration, and change management rise in value.

⸻

The most important directions for science & deep tech

AI-driven scientific discovery & robot scientists
High risk–high reward: accelerated science, paired with risks of false optimization and misplaced trust.

In-memory computing & new processors
The real enemy of AI isn’t compute — it’s data movement and energy loss.
Radical gains must come from performance-per-watt, not raw FLOPS.

Quantum-safe cryptography & trust infrastructure
Preparing for post-quantum threats while building scalable digital trust layers.

AI-enabled digital twins
Savings via simulation instead of replication: predictive maintenance, system optimization —
with new vulnerabilities and accountability challenges.

Future of medicine & engineered therapeutics
According to the authors, medicine carries the largest potential impact on humanity, with bioengineered therapies entering the core technology stack.

⸻

The key takeaway

AI is no longer “about the future.”

It is becoming infrastructure of the present —
with its own power requirements, trust layers, governance, and social consequences.

The real question is no longer “Will AI happen?”
It’s “Who controls energy, data, and trust in an AI-driven world?”

Source: IEEE Technology Predictions 2026


#AI #Science #FutureOfWork #Robotics #DigitalTwins #Infrastructure #Medicine

🩻 The Company Behind Midjourney Just Revealed a Machine That Could Scan Your Entire Body in 60 Seconds

Most people know Midjourney as one of the world’s leading AI image generators.

Now the company is attempting something far more ambitious: reinventing medical imaging itself.

Midjourney has unveiled Midjourney Scanner, an experimental full-body imaging system that uses thousands of ultrasound transducers arranged around a person immersed in a water-filled scanning chamber. The goal is to create a detailed 3D map of the human body in about one minute — without radiation and without the massive magnets used in MRI machines.

The concept is surprisingly simple: instead of moving a single ultrasound probe across the body, surround the entire body with ultrasound sensors and capture everything at once.

According to Midjourney founder David Holz, the long-term vision is not just medical diagnosis, but something much bigger:

🔹 Regular full-body scans available to ordinary people

🔹 Tracking changes in muscles, fat, organs, and tissues over time

🔹 Building a continuously updated digital model of your body

🔹 Detecting health changes long before symptoms appear

If the technology succeeds, it could fundamentally change preventive medicine. Today, most people only receive detailed internal imaging after something goes wrong. Midjourney’s vision is a future where full-body imaging becomes as routine as stepping on a scale.

There are important caveats.

The current system is an early prototype. Only a small number of people have been scanned so far, and the device is not yet approved for medical diagnosis. Whether it can eventually match the capabilities of MRI or CT remains unknown.

Still, the announcement raises a fascinating question:

What if the next major breakthrough in medicine doesn’t come from a hospital, pharmaceutical company, or medical device giant — but from an AI company best known for generating artwork?

The company that helped computers imagine images is now trying to help humans see inside themselves.

📄 Source: Midjourney Medical announcement

https://www.midjourney.com/medical/blogpost

#Medicine #HealthTech #AI #MedicalImaging #Ultrasound #FutureOfMedicine #Midjourney
#science

🧬 A Personalized mRNA Cancer Vaccine Has Passed Its Biggest Test Yet

For the first time, a personalized mRNA cancer therapy has succeeded in a Phase 3 clinical trial — the final major testing stage before regulators can consider approval.

The treatment, called intismeran autogene, is not an off-the-shelf vaccine. Doctors sequence each patient’s tumour, identify mutations unique to their cancer, and manufacture an individual mRNA therapy encoding up to 34 of those tumour-specific targets. The goal is essentially to give the immune system a personalized wanted poster for the cancer.

In the trial, 1,137 people with stage IIB–IV melanoma whose tumours had been completely removed received either the personalized mRNA therapy plus the immunotherapy drug pembrolizumab (Keytruda), or pembrolizumab alone. The combination produced statistically significant and clinically meaningful improvements in both recurrence-free survival and distant-metastasis-free survival. No new safety signal was reported.

There is an important caveat: the companies have so far announced only top-line Phase 3 results. They have not yet released the detailed numbers, and it is not yet known whether the treatment ultimately extends overall survival. The therapy also remains investigational and has not been approved.

But the principle is now much harder to dismiss. Instead of finding one cancer vaccine that works for everyone, medicine may be able to manufacture a different vaccine for each individual tumour.

Cancer is personal.

The vaccine might have to be too.

#Cancer #mRNA #Melanoma #Immunotherapy #Biotechnology #Medicine #Science

🤖 AI Found 15 Cancers That Radiologists Had Missed

A new clinical study offers a glimpse of what medical AI may actually be best at: not replacing doctors, but quietly checking their work.

Researchers deployed an AI system called LiON alongside radiologists reading contrast-enhanced CT scans in routine hospital practice. In a prospective trial involving 10,333 patients, the system flagged 51 liver lesions that had initially been overlooked. Fifteen of them turned out to be malignant.

The alerts were not merely theoretical. They led doctors to amend 37 radiology reports, send 22 cases for multidisciplinary review, and change clinical management for some patients. Before the live trial, LiON had been trained on 6,443 patients and validated retrospectively on another 22,251.

The important nuance is that this was not a randomized trial comparing AI-assisted doctors against doctors alone, and the study did not show that the system improves survival. The researchers themselves say larger prospective comparative studies across different healthcare systems are still needed.

But this is a meaningful step beyond “AI beats doctors on a test set.”

Here, the algorithm sat inside an actual clinical workflow — and found cancers that humans had missed.

Perhaps the most useful medical AI will not be the doctor in the room.

It will be the second pair of eyes that never gets tired.

#AI #Medicine #Cancer #Radiology #MedicalAI #Science

https://www.nature.com/articles/s41591-026-04589-y⁠