Category: Methodology

The Dutch Give Citizen Scientists Property Rights to the Fossils They Find

Holland has significant claim, along with England, to being a strong and early bastion of freedom. So it is fitting that today Holland’s institutions provide a sanctuary for the practice of citizen science. The article below notes that Dutch law gives citizen scientists property rights in the fossils they find. This gives them an incentive to seek fossils AND it gives them an incentive to share information about what they find. (If they did not have such property rights, they would have an incentive to hide the fossils so they would not be seized.)

Dick Moll is an entrepreneur, using some of his fossils as part of a Historyland theme park. His doing good through creative funding, reminds me of Martin Couney, who financed baby incubators for poor families, by displaying the incubators at theme park exhibits.

If academic scientists, instead of hiding behind their credentials, sought clever ways to recruit the eyes of curious citizen scientists, we could learn much more and learn it much more quickly. This would be easier if the values and methods of science were more empirical, more true to Galileo. Let everyone have a look in the telescope.

(p. C1) After scouring a beach in the harbor all morning in Rotterdam, the Netherlands, a retired Dutch engineer, Cock van den Berg, had finally found something interesting: a polished black stone about the size of an acorn with two punctures, like finger holes in a bowling ball.

He held it out in the palm of his hand to show Dick Mol, an expert on ice age fossils.

“What do you think?” he asked. “Is it a mammoth tooth?”

Mol examined it for about 30 seconds and decided it was not. It was a molar from a prehistoric rhinoceros, he said.

. . .

(p. C6) Under Dutch law, beach combers who find fossils on Maasvlakte 2 are not required to report or submit them. They can take their finds home if they like, but they are encouraged to promote scientific research by voluntarily registering them with the Naturalis Biodiversity Center, a national natural history museum and research center in the city of Leiden.

Using a website built by the port of Rotterdam authority and managed by Naturalis, amateur paleontologists can submit a photo and the GPS location of the find so that experts can help them identify it.

“In other countries, like Germany, fossils or anything related to paleontology are protected by the state, but that’s not the case in the Netherlands,” explained Isaak Eijkelboom, a Ph.D. student in paleontology at Naturalis who studies fossils found at Maasvlakte 2 and other locations.

But since trophy hunters don’t have to worry about losing their finds, he thinks they’re more likely to share their discoveries with the museum and collaborate with scientists.

“It allows us to practice citizen science,” Eijkelboom said.

For more than a decade, Naturalis has been using volunteers to gather information for its fossil database, which now lists more than 23,000 finds, he said.

“This is only possible because it’s so open, and so free,” Eijkelboom said. “In other places, when people find fossils, they end up in their closets and the knowledge is hidden away.”

Van den Berg, who discovered the rhinoceros molar, said he was excited to share it with Naturalis. A few years ago, he found a jaw part from a macaque monkey at Maasvlakte 2 and donated it to the Natural History Museum in Rotterdam. The rare specimen, which scientists dated to 125,000 years ago, was described in three scientific papers, Mol said.

. . .

Mol joked that the “biggest mistake of van den Berg’s life” was donating the monkey jaw to the museum and not to Mol’s “Mammoth Lab” at Historyland, a museum and theme park that he helped establish in the town of Hellevoetsluis, about a 15-minute drive from the beach.

There, Mol, a retired airport customs official, has his own impressive collection of 55,000 ice age fossils. An autodidact who never attended university, Mol is nonetheless widely recognized as an international expert; in 2000, he was knighted in the Netherlands for his significant contributions to paleontology, and he was featured in Discovery Channel documentaries such as “Raising the Mammoth” and “Land of the Mammoth.”

. . .

In spite of a steady stream of beachcombers, Eijkelboom said there will still be plenty more fossils to find for a long time to come.

“In general, in paleontology, a lot of people say we’ve only discovered the tip of the iceberg,” he said. Rising sea levels will require continued fortifications of the Dutch coastline, using North Sea sand deposits for quite some time to come, he added.

Although it is unfortunate that such action is needed to prevent humans from going extinct like the mammoth, he said, “at least there will be more and more beaches where we can hunt for ice age fossils.”

For the full story see:

Nina Siegal and Ilvy Njiokiktjien. “On the Hunt for Mammoths.” The New York Times (Weds., November 19, 2025): C1 & C6.

(Note: ellipses added.)

(Note: the online version of the story has the date Nov. 17, 2025, and has the title “A Day at the Beach Hunting Mammoths.”)

FDA Worked Better and Much Cheaper Before 1962 Expansion

Before 1962, the FDA regulated for drug safety, but not for drug efficacy. If the FDA returned to regulating only for safety, that would imply that Phase 3 randomized clinical trials would no longer be mandated. Phase 3 trials are usually more expensive than the Phase 1 and Phase 2 trials combined. They cost a lot more, and usually take a lot longer. If the FDA no longer mandate Phase 3 trials we will have more drug innovation, more quickly, and have much lower costs. And we will have more freedom.

(p. A13) From 1938 through 1962, the Food and Drug Administration required proof of safety before drug approval but not proof of efficacy. The approach was abandoned due to a significant misunderstanding of the thalidomide tragedy—when thousands of babies outside the U.S. were born with severe birth defects.

The issue with thalidomide was a failure of safety, not efficacy. But under pressure to react, Congress required, through the Kefauver-Harris Amendments of 1962, proof of efficacy before granting marketing approval. The new rule addressed a problem that didn’t exist and, in doing so, imposed a substantial new cost burden.

Before 1962, developing a drug took about two years. Now it takes 12 to 14 years. Since 1975 real development costs have risen about 7.5% a year, roughly doubling every decade. Today, we estimate that bringing one successful drug to market costs about $9 billion on average.

For the full commentary, see:

Charles L. Hooper and Solomon S. Steiner. “Deregulation Can Make Medications Cheaper.” The Wall Street Journal (Sat., Oct. 18, 2025): A13.

(Note: the online version of the commentary has the date Oct. 17, 2025, and has the same title as the print version.)

Adjuvants Did Not Arise from Theory, but from Open-Eyed Trial-And-Error Experimentation

Sometimes you see journalists, commentators, or politicians saying that ordinary people should not use trial-and-error experiments with health treatments, but instead listen to the advice of certified scientists. Listen to the “science” we hear. But many of the most common practices in medicine originated with ordinary trial-and-error experiments of the sort that can be conducted with little if any certified expertise.

Consider adjuvants. An adjuvant “helps” the primary therapy; aluminum can be an adjuvant to a vaccine or, with cancer, radiation can be an adjuvant to a surgery. As the passages quoted below show, the first vaccine adjuvants were not discovered through the theorizing of a certified genius. A motivated alert and practical veterinarian wanted to protect horses from disease. He noticed that a horse vaccine worked better when, by chance, the horse also had an infection at the vaccination site. He speculated that the inflammation from the infection aroused the immune system. So why not try deliberately causing inflammation? He tried different substances, landing on tapioca as the best of what he tried. Others later found aluminum to be more reliable.

Maybe what often matters most for medical progress is a sense of open-eyed urgency and a persistent willingness to engage in trial-and-error experimentation. The uncertified can have those traits. When they do, we should not ridicule, ban, or cancel them.

(p. A14) The origins of added aluminum in vaccines can be traced back nearly a century. In a stable on the outskirts of Paris, a young veterinarian had made a peculiar discovery: mixing tapioca into his horses’ diphtheria vaccines made them more effective.

The doctor, Gaston Ramon, had noticed that the horses who developed a minor infection at the injection site had much more robust immunity against diphtheria. He theorized that adding something to his shots that caused inflammation — ingredients he later named adjuvants, derived from the Latin root “to help” — helped induce a stronger immune response.

After testing several candidates — including bread crumbs, petroleum jelly and rubber latex — he found success with a tapioca-laced injection, which produced slight swelling and far more antibodies.

Tapioca never caught on as an adjuvant. But in 1932, a few years after Dr. Ramon’s studies were published, the United States began including aluminum salts in diphtheria immunizations, as they were found to invoke a similar but more reliable effect.

Today, aluminum adjuvants are found in 27 routine vaccines, and nearly half of those recommended for children under 5.

This extra boost of immunity is not needed in all types of vaccines. Shots that contain a weakened form of a virus, like the measles mumps and rubella shot, or created with mRNA technology, like the Pfizer and Moderna Covid-19 vaccines, generate strong enough immune responses on their own.

But in vaccines that contain only small fragments of the pathogen, which would garner little attention from the immune system, adjuvants help stimulate a stronger response, allowing vaccines to be given in fewer doses.

Scientists believe that aluminum salts work in two ways. First, aluminum binds to the core component of the vaccine and causes it to diffuse into the bloodstream more slowly, giving immune cells more time to build a response.

It’s also thought that aluminum operates more directly, enhancing the activity of certain immune cells, though this mechanism is not fully understood.

For the full story see:

Teddy Rosenbluth. “Aluminum in Vaccines Is a Good Thing, Scientists Say.” The New York Times (Sat., January 25, 2025): A14.

(Note: ellipsis, and bracketed date, added.)

(Note: the online version of the story has the date Jan. 24, 2025, and has the title “Yes, Some Vaccines Contain Aluminum. That’s a Good Thing.”)

“Nothing Is Incontrovertible in Science”

Somewhere we should start a Hall of Fame for those who had the courage to take the ill will from the enforcers of the “new religion” of global warming. Among its honorees would be Michael Crichton, Freeman Dyson, and (see below) Ivar Giaever. Science is not a body of doctrine; science is a process of inquiry.

(p. B12) Ivar Giaever might not have won the Nobel Prize in Physics if a job recruiter at General Electric had known the difference between the educational grading systems of the United States and Norway.

It was 1956, and he was applying for a position at the General Electric Research Laboratory in Schenectady, N.Y. The interviewer looked at his grades, from the Norwegian Institute of Technology in Trondheim, where Dr. Giaever had studied mechanical engineering, and was impressed: The young applicant had scored 4.0 marks in math and physics. The recruiter congratulated him.

But what the recruiter didn’t know was that in Norway, the best grade was a 1.0, not a 4.0, the top grade in American schools. In fact, a 4.0 in Norway was barely passing — something like a D on American report cards. In reality, his academic record in Norway had been anything but impressive.

He did not want to be dishonest, Dr. Giaever (pronounced JAY-ver) would say in recounting the episode with some amusement over the years, but he also did not correct the interviewer. He got the job.

He proceeded to spend the next 32 years at the laboratory, along the way developing an experiment that provided proof of a central idea in quantum physics — that subatomic particles can behave like powerful waves.

. . .

Though Dr. Giaever later earned a doctorate in theoretical physics, in 1964, from Rensselaer Polytechnic Institute in Troy, N.Y., he had not yet completed that degree when he came up with the experiment that would earn him his share of the Nobel. Indeed, as he admitted in his Nobel lecture, he did not fully understand the ideas behind the experiment when he first started working on it. He was, after all, a mechanical engineer, steeped in how things work in classical physics, which deals with real-world objects. Quantum physics, on the other hand, predicts what happens in the weird subatomic world.

. . .

Dr. Giaever prided himself on his common-sense approach to science, but not all his ideas were welcomed by his peers. He became a prominent denier of climate change, referring to the science around it as a “new religion.” (“I would say that, basically, global warming is a nonproblem,” he said in a 2015 speech.) He based his opposition, in part, on his belief that it is impossible to track changes in the Earth’s temperature and that, even if it could be done, the temperature changes would be insignificant.

When the American Physical Society announced in 2011 that the evidence for climate change and global warming was incontrovertible, he resigned from the society in disgust, saying: “‘Incontrovertible’ is not a scientific word. Nothing is incontrovertible in science.”

For the full obituary, see:

Dylan Loeb McClain. “Ivar Giaever, 96, ‘D’ Student Who Won Nobel Prize.” The New York Times (Thursday, July 10, 2025): B12.

(Note: ellipses added.)

(Note: the online version of the obituary was updated July 9, 2025, and has the title “Ivar Giaever, Nobel Winner in Quantum Physics, Dies at 96.”)

Latest “So-Called Reasoning Systems” Hallucinate MORE Than Earlier A.I. Systems

Since more sophisticated “reasoning” A.I. systems are increasingly inaccurate on the facts, it is unlikely that such systems will threaten any job where job performance depends on getting the facts right. Wouldn’t that include most jobs? The article quoted below suggests it would most clearly include jobs working with “court documents, medical information or sensitive business data.”

(p. B1) The newest and most powerful technologies — so-called reasoning systems from companies like OpenAI, Google and the Chinese start-up DeepSeek — are generating more errors, not fewer. As their math skills have notably improved, their handle on facts has gotten shakier. It is not entirely clear why.

Today’s A.I. bots are based on complex mathematical systems that learn their skills by analyzing enormous amounts of digital data. They do not — and cannot — decide what (p. B6) is true and what is false. Sometimes, they just make stuff up, a phenomenon some A.I. researchers call hallucinations. On one test, the hallucination rates of newer A.I. systems were as high as 79 percent.

. . .

The A.I. bots tied to search engines like Google and Bing sometimes generate search results that are laughably wrong. If you ask them for a good marathon on the West Coast, they might suggest a race in Philadelphia. If they tell you the number of households in Illinois, they might cite a source that does not include that information.

Those hallucinations may not be a big problem for many people, but it is a serious issue for anyone using the technology with court documents, medical information or sensitive business data.

“You spend a lot of time trying to figure out which responses are factual and which aren’t,” said Pratik Verma, co-founder and chief executive of Okahu, a company that helps businesses navigate the hallucination problem. “Not dealing with these errors properly basically eliminates the value of A.I. systems, which are supposed to automate tasks for you.”

. . .

For more than two years, companies like OpenAI and Google steadily improved their A.I. systems and reduced the frequency of these errors. But with the use of new reasoning systems, errors are rising. The latest OpenAI systems hallucinate at a higher rate than the company’s previous system, according to the company’s own tests.

The company found that o3 — its most powerful system — hallucinated 33 percent of the time when running its PersonQA benchmark test, which involves answering questions about public figures. That is more than twice the hallucination rate of OpenAI’s previous reasoning system, called o1. The new o4-mini hallucinated at an even higher rate: 48 percent.

When running another test called SimpleQA, which asks more general questions, the hallucination rates for o3 and o4-mini were 51 percent and 79 percent. The previous system, o1, hallucinated 44 percent of the time.

. . .

For years, companies like OpenAI relied on a simple concept: The more internet data they fed into their A.I. systems, the better those systems would perform. But they used up just about all the English text on the internet, which meant they needed a new way of improving their chatbots.

So these companies are leaning more heavily on a technique that scientists call reinforcement learning. With this process, a system can learn behavior through trial and error. It is working well in certain areas, like math and computer programming. But it is falling short in other areas.

For the full story see:

Cade Metz and Karen Weise. “A.I. Hallucinations Are Getting Worse.” The New York Times (Fri., May 9, 2025): B1 & B6.

(Note: ellipses added.)

(Note: the online version of the story was updated May 6, 2025, and has the title “A.I. Is Getting More Powerful, but Its Hallucinations Are Getting Worse.”)

A.I. Only “Knows” What Has Been Published or Posted

A.I. “learns” by scouring language that has been published or posted. If outdated or never-true “facts” are posted on the web, A.I. may regurgitate them. It takes human eyes to check whether there really is a picnic table in a park.

(p. B1) Last week, I asked Google to help me plan my daughter’s birthday party by finding a park in Oakland, Calif., with picnic tables. The site generated a list of parks nearby, so I went to scout two of them out — only to find there were, in fact, no tables.

“I was just there,” I typed to Google. “I didn’t see wooden tables.”

Google acknowledged the mistake and produced another list, which again included one of the parks with no tables.

I repeated this experiment by asking Google to find an affordable carwash nearby. Google listed a service for $25, but when I arrived, a carwash cost $65.

I also asked Google to find a grocery store where I could buy an exotic pepper paste. Its list included a nearby Whole Foods, which didn’t carry the item.

For the full commentary see:

Brian X. Chen. “Underneath a New Way to Search, A Web of Wins and Imperfections.” The New York Times (Tues., June 3, 2025): B1 & B4.

(Note: the online version of the commentary has the date May 29, 2024, and has the title “Google Introduced a New Way to Use Search. Proceed With Caution.”)

A.I. Hastens Search for Antibiotic Peptides in Extinct Species

In an earlier entry I commented on the use of A.I. to seek antibodies by George Church’s startup Lila. Now it appears that César de la Fuente is employing a similar approach. In both cases A.I. is being used to more efficiently do repetitive well-structured tasks. This is not the highest creative level of human intelligence, but it can free time for humans to exercise the highest level of human intelligence.

(p. A3) Buried in the DNA of the long extinct woolly mammoth is a compound that scientists hope will one day yield a lifesaving antibiotic.

In experiments, mammuthusin, as the compound is called, has eradicated superbugs—bacteria that are resistant to today’s antibiotics and cause infections that are hard to treat—says César de la Fuente, the bioengineer who helped discover the molecule.

. . .

To help combat superbugs, doctors say we need new antibiotics with novel chemical structures or mechanisms of action. But only a handful of such drugs has entered the market over the past several decades.

De la Fuente is banking on artificial intelligence to help end this dry spell. He and his collaborators have built deep-learning algorithms to comb through enormous genetic databases to find peptides, or protein fragments, that have antibacterial properties. They have used this method to analyze animal venoms, the human microbiome and archaea, an underexplored group of microorganisms. They have also mined the genetic codes from fossils of long-extinct animals and humans, including Neanderthals and Denisovans. “This deep-learning model has opened a window into the past,” de la Fuente says.

. . .

When the algorithms identify a new peptide with antibiotic potential, de la Fuente and his team use robots to manufacture the compound in their lab and then test it in mice infected with bacteria. So far, a few hundred peptides made in de la Fuente’s lab have safely and effectively cured sick mice.

One of them was mammuthusin, identified in the genetic code of Mammuthus primigenius, a species of mammoth that last roamed the Earth about 4,000 years ago. The researchers discovered the peptide after mining a National Center for Biotechnology Information database of DNA sequencing data obtained from the fossils of extinct animals. In experiments, mammuthusin was as potent as polymyxin B, an antibiotic often used as a last resort for serious infections, according to a paper published in the journal Nature in June [2024]. The mammoth peptide effectively eradicated a type of bacterium that the World Health Organization has designated a critical pathogen because of its resistance to many common antibiotics.

For the full story, see:

Dominique Mosbergen. “Search for New Antibiotics Turns Back Time.” The Wall Street Journal (Weds., May 28, 2025): A3.

(Note: ellipses, and bracketed year, added.)

(Note: the online version of the story has the date May 24, 2025, and has the title “A Search for New Antibiotics in Ancient DNA.” In the original of both the online and print versions, Mammuthus primigenius appeared in italics.)

The academic article published in Nature Biomedical Engineering in June 2024, and mentioned above, is:

Wan, Fangping, Marcelo D. T. Torres, Jacqueline Peng, and Cesar de la Fuente-Nunez. “Deep-Learning-Enabled Antibiotic Discovery through Molecular De-Extinction.” Nature Biomedical Engineering 8, no. 7 (July 2024): 854-71.

My Email Response to George Church on A.I. and Longevity

On May 17 I ran an entry commenting on George Church’s over-optimism about the use of A.I. to replicate the scientific method, and expressed wistful disappointment that Church’s longevity project had not advanced as quickly as 60 Minutes implied it would in 2019.

On May 20, Church sent me a cordial email disputing some of what I wrote in my entry. I responded to him on May 22, and asked him if he would mind if I ran his email and my response on my blog. He never responded to that request, so I will not reproduce his email here. But I see no harm in my including below the links he sent me. And then I will follow with my email response to him.

Here are the links that Church thought I should ponder:

2024 pmc.ncbi.nlm.nih.gov/articles/PMC10909732 (see Fig 1b)
2022 rejuvenatebio.com/animal-health-pipeline
2022 rejuvenatebio.com/pipeline
2023 biorxiv.org/content/10.1101/2023.11.13.566787v1.full

Here is my email response to Church:

Dear Prof. Church,

Thank you for taking the time to read and respond to my blog post. I appreciate the links you sent. The first link gives us the good news of progress toward increasing the lifespan of mice and in reducing their frailty, which could be interpreted as one part of reversing their aging. The fourth link also gives good news of the proof-of-concept of a new factor at the cell level that may be able to rejuvenate cells without the cancer of the Yamanaka factors.

But on 60 Minutes in 2019 you said age reversal was already “available to mice.” And you said the “veterinary product might be a couple years away and then that takes another 10 years to get through the human clinical trials.” That is not exactly a promise, but it does sound like a hopeful prediction. And I will admit that the timing matters to me. If your 60 Minutes prediction was right there’s a good chance I might live to see it; if it takes twice that long, I almost certainly will not.

In re-reading my post, I see a couple of revisions I would make. I would add that I wish you well in what you are trying to do, and strongly and sincerely hope that you succeed (whether through A.I or by other means). And I would add that I believe Elon Musk said that being overly optimistic is one way that great innovators push themselves toward great goals.

I appreciate your “fact checking” offer. I have a comment apropos that. You say that “The Lohr article doesn’t say “feeding” or “literature”. “ Here is the relevant exact quote from the Lohr article:

Lila has taken a science-focused approach to training its generative A.I., feeding it research papers, documented experiments and data from its fast-growing life science and materials science lab. That, the Lila team believes, will give the technology both depth in science and wide-ranging abilities, mirroring the way chatbots can write poetry and computer code.

So the Lohr article does say “feeding.” It doesn’t say “literature,” but does say “research papers” which I take to be the same thing. I appreciate that Lila also is collecting new data. But is it some generative intelligence in Lila that is identifying the new data to seek or is it George Church and his team?

I agree that A.I. can help crank through possibilities that have already been defined. I am dubious that A.I. can come up with the possibilities as well as George Church and his team can. It may seem harmless that A.I. is being over-hyped. But as an economist it is my job to notice that funding is scarce, so funding spent on A.I. is funding not spent on other inputs to science.

I fear that I may come across as a privileged spectator complaining about the bloodied combatant in the arena. But a big part of my research is aimed at reducing the regulations that burden medical entrepreneurs. For instance, I am working on a paper supporting Milton Friedman’s suggestion that the F.D.A. should just regulate for safety and stop regulating for efficacy. Without Phase 3, more can be tried, more quickly and more cheaply.

If you are willing, I would like to paste your response (or an edited version if you prefer) at the end of my original post. Let me know if that is OK.

Thanks!

Art

One Third of Near-Death Multiple Myeloma Patients Are Cured by a New CAR-T Immunotherapy

Many consider immunotherapy to be the most promising current approach to curing cancer. One way to implement immunotherapy is to develop CAR-T cells. But there apparently are many ways to develop a CAR-T cell and which, if any, will work is a matter of trial-and-error.

It seems overly-cautious for regulators to require that the most innovative and promising therapies must first be tried on the patients nearest to death, and so least likely to respond. Why not allow patients at earlier stages to volunteer to try the new therapies earlier? They would be taking a bigger risk, but also would have the possibility of a bigger benefit. They would avoid the suffering from current treatments that are known to have major side-effects, and also are known to only extend life for short periods of time; and they would gain a shot at a real long-term cure.

(p. A18) A group of 97 patients had longstanding multiple myeloma, a common blood cancer that doctors consider incurable, and faced a certain, and extremely painful, death within about a year.

They had gone through a series of treatments, each of which controlled their disease for a while. But then it came back, as it always does. They reached the stage where they had no more options and were facing hospice.

They all got immunotherapy, in a study that was a last-ditch effort.

A third responded so well that they got what seems to be an astonishing reprieve. The immunotherapy developed by Legend Biotech, a company founded in China, seems to have made their cancer disappear. And after five years, it still has not returned in those patients — a result never before seen in this disease.

These results, in patients whose situation had seemed hopeless, has led some battle-worn American oncologists to dare to say the words “potential cure.”

. . .

The new study, reported Tuesday [June 3, 2025] at the annual conference of the American Society of Clinical Oncology and published in The Journal of Clinical Oncology, was funded by Johnson & Johnson, which has an exclusive licensing agreement with Legend Biotech.

. . .

The Legend immunotherapy is a type known as CAR-T. It is delivered as an infusion of the patient’s own white blood cells that have been removed and engineered to attack the cancer. The treatment has revolutionized prospects for patients with other types of blood cancer, like leukemia.

Making CAR-T cells, though, is an art, with so many possible variables that it can be hard to hit on one that works.

. . .

The . . . study took on a . . . challenge — helping patients at the end of the line after years of treatments. Their immune systems were worn down. They were, as oncologists said, “heavily pretreated.” So even though CAR-T is designed to spur their immune systems to fight their cancer, it was not clear their immune systems were up to it.

Oncologists say that even though most patients did not clear their cancer, having a third who did was remarkable.

To see what the expected life span would be for these patients without the immunotherapy, Johnson & Johnson looked at data from patients in a registry who were like the ones in its study — they had failed every treatment. They lived about a year.

. . .

. . ., the hope is that perhaps by giving it earlier in the course of the disease, it could cure patients early on.

Johnson & Johnson is now testing that idea.

Dr. Kenneth Anderson, a myeloma expert at Dana-Farber Cancer Institute who was not involved with the study, said that if the treatment is used as a first-line treatment, “cure is now our realistic expectation.”

For the full story, see:

Gina Kolata. “From No Hope to Potential Cure for Deadly Blood Cancer, Study Shows.” The New York Times (Thurs., June 5, 2025): A18.

(Note: ellipses, and bracketed date, added.)

(Note: the online version of the story was updated June 5, 2025, and has the title “From No Hope to a Potential Cure for a Deadly Blood Cancer.”)

The academic article on the new cure is:

Jagannath, Sundar, Thomas G. Martin, Yi Lin, Adam D. Cohen, Noopur Raje, Myo Htut, Abhinav Deol, Mounzer Agha, Jesus G. Berdeja, Alexander M. Lesokhin, Jessica J. Liegel, Adriana Rossi, Alex Lieberman-Cribbin, Saad Z. Usmani, Binod Dhakal, Samir Parekh, Hui Li, Feng Wang, Rocio Montes de Oca, Vicki Plaks, Huabin Sun, Arnob Banerjee, Jordan M. Schecter, Nikoletta Lendvai, Deepu Madduri, Tamar Lengil, Jieqing Zhu, Mythili Koneru, Muhammad Akram, Nitin Patel, Octavio Costa Filho, Andrzej J. Jakubowiak, and Peter M. Voorhees. “Long-Term (≥5-Year) Remission and Survival after Treatment with Ciltacabtagene Autoleucel in Cartitude-1 Patients with Relapsed/Refractory Multiple Myeloma.” Journal of Clinical Oncology https://doi.org/10.1200/JCO-25-0076.

Electricity May Be a Pellet in the “Magic Buckshot” Against Cancer

In a recent entry I claimed that the cure for many diseases may not be Paul Ehrlich’s one “magic bullet” but may instead be “magic buckshot.” A recent article in The Wall Street Journal suggests that one pellet in the magic buckshot against cancer is electricity. As proof of concept, the article claims that after surgery, radiation, and chemotherapy for a glioblastoma brain cancer, adding electrodes to the skull that deliver low-intensity electricity to the brain, will add a median of 4.9 months to the patient’s lifespan.

The Wall Street Journal article mentioned above is:

Brianna Abbott. “Next Hope in Treating Cancer: Electricity.” The Wall Street Journal (Tues., May 20, 2025): A10.

(Note: the online version of the article has the date May 16, 2025, and has the title “The Next Frontier to Treat Cancer: Electricity.”)

The Wall Street Journal article links to the following article in JAMA:

Stupp, Roger, Sophie Taillibert, Andrew Kanner, William Read, David M. Steinberg, Benoit Lhermitte, Steven Toms, Ahmed Idbaih, Manmeet S. Ahluwalia, Karen Fink, Francesco Di Meco, Frank Lieberman, Jay-Jiguang Zhu, Giuseppe Stragliotto, David D. Tran, Steven Brem, Andreas F. Hottinger, Eilon D. Kirson, Gitit Lavy-Shahaf, Uri Weinberg, Chae-Yong Kim, Sun-Ha Paek, Garth Nicholas, Jordi Bruna, Hal Hirte, Michael Weller, Yoram Palti, Monika E. Hegi, and Zvi Ram. “Effect of Tumor-Treating Fields Plus Maintenance Temozolomide Vs Maintenance Temozolomide Alone on Survival in Patients with Glioblastoma: A Randomized Clinical Trial.” JAMA 318, no. 23 (Dec. 19, 2017): 2306-16.

During Covid-19 “Bureaucratic Authorities Erred in Pretending . . . Certainty”

(p. A13) Adam Kucharski, a professor of epidemiology at the London School of Hygiene & Tropical Medicine, takes the reader on a fascinating tour of the history of what has counted as proof.

. . .

What should we do, . . ., when a mathematical proof of truth is unavailable, but we must nonetheless act?

This leads us to a discussion of probability and statistics, and of pioneers such as William Gosset, a brewer at Guinness who figured out how to quantify random errors in experiments, and Janet Lane-Claypon, an English scientist who first thought to investigate confounding factors while analyzing children’s health. Some innovations, though, have hardened into unhelpful dogma. The scientific notion of “statistical significance” relies, Mr. Kucharski explains, on a wholly arbitrary cutoff, which incentivizes researchers to massage their data. Such issues, he says, can be hard for scientists, let alone the laity, to understand.

Mr. Kucharski speaks from experience, since he was one of the experts first called upon by the British government for advice on the Covid-19 pandemic. He explains brilliantly the fragmentary and confusing nature of the data then available, and the provisional conclusions they led to. As a public face of this effort, Mr. Kucharski was bombarded daily with abusive and threatening messages from angry citizens who simply didn’t believe what they were being told.

The lesson Mr. Kucharski draws isn’t that he and his colleagues were right (though they largely were), but that bureaucratic authorities erred in pretending there was certainty when all that was possible at the time was messy and provisional. Notoriously, in March 2020 the World Health Organization tweeted “FACT: #COVID19 is NOT airbone.” (As it turns out, it was, and it is.) The author regrets, too, that politicians claimed to be “following the science,” because science can never tell you what you should do.

For the full review see:

Steven Poole. “Bookshelf; Finding Truth In Numbers.” The Wall Street Journal (Friday, June 6, 2025): A13.

(Note: ellipses added.)

(Note: the online version of the review has the date June 5, 2025, and has the title “Bookshelf; ‘Proof’: Finding Truth in Numbers.”)

The book under review is:

Kucharski, Adam. Proof: The Art and Science of Certainty. New York: Basic Books, 2025.