Don't Panic Over Waning Antibodies. Here's Why.
![Don't Panic Over Waning Antibodies. Here's Why.](https://upworthyscience.com/media-library/a-health-care-worker-places-a-bandaid-on-the-arm-of-a-man-who-has-just-been-vaccinated.jpg?id=27377899&width=1245&height=700&quality=85&coordinates=0%2C0%2C0%2C772)
A health care worker places a bandaid on the arm of a man who has just been vaccinated.
Since the Delta variant became predominant in the United States on July 7, both scientists and the media alike have been full of mixed messages ("breakthrough infections rare"; "breakthrough infections common"; "vaccines still work"; "vaccines losing their effectiveness") but – if we remember our infectious diseases history- one thing remains clear: immunity is the only way to get through a pandemic.
What Happened in the Past
The 1918 influenza pandemic was far the deadliest respiratory virus pandemic recorded in recent human history with over 50 million deaths (maybe even 100 million deaths, or 3% of the world's population) worldwide. Although they used some of the same measures we are using now (masks, distancing, event closures, as neither testing nor a vaccine existed back then), the deaths slowed only after enough of the population had either acquired immunity through natural infection or died. Indeed, the first influenza vaccine was not developed until 1942, more than 20 years later. As judged by the amount of suffering and death from 1918 influenza (and the deadly Delta surge in India in spring 2021), natural immunity is obviously a terrible way to get through a pandemic.
Similarly, measles was a highly transmissible respiratory virus that led to high levels of immunity among adults who were invariably exposed as children. However, measles led to deaths each year among the nonimmune until a vaccine was developed in 1963, largely restricting current measles outbreaks in the U.S. now to populations who decline to vaccinate. Smallpox also led to high levels of immunity through natural infection, which was often fatal. That's why unleashing smallpox on a largely nonimmune population in the New World was so deadly. Only an effective vaccine – and its administration worldwide, including among populations who declined smallpox vaccine at first via mandates – could control and then eventually eradicate smallpox from Earth.
Fully vaccinated people are already now able to generate some antibodies against all the variants we know of to date, thanks to their bank of memory B cells.
The Delta variant is extremely transmissible, making it unlikely we will ever eliminate or eradicate SARS-CoV-2. Even Australia, which had tried to maintain a COVID-zero nation with masks, distancing, lockdowns, testing and contact tracing before and during the vaccines, ended a strategy aimed at eliminating COVID-19 this week. But, luckily, since highly effective and safe vaccines were developed for COVID-19 less than a year after its advent on a nonimmune population and since vaccines are retaining their effectiveness against severe disease, we have a safe way out of the misery of this pandemic: more and more immunity. "Defanging" SARS-CoV-2 and stripping it of its ability to cause severe disease through immunity will relegate it to the fate of the other four circulating cold-causing coronaviruses, an inconvenience but not a world-stopper.
Immunity Is More Than Antibodies
When we say immunity, we have to be clear that we are talking about cellular immunity and immune memory, not only antibodies. This is a key point. Neutralizing antibodies, which prevent the virus from entering our cells, are generated by the vaccines. But those antibodies will necessarily wane over time since we cannot keep antibodies from every infection and vaccine we have ever seen in the bloodstream (or our blood would be thick as paste!). Vaccines with shorter intervals between doses (like Pfizer vaccines given 3 weeks apart) are likely to have their antibodies wane sooner than vaccines with longer intervals between doses (like Moderna), making mild symptomatic breakthroughs less likely with the Moderna vaccine than the Pfizer during our Delta surge, as a recent Mayo Clinic study showed.
Luckily, the vaccines generate B cells that get relegated to our memory banks and these memory B cells are able to produce high levels of antibodies to fight the virus if they see it again. Amazingly, these memory B cells will actually produce antibodies adapted against the COVID variants if they see a variant in the future, rather than the original antibodies directed against the ancestral strain. This is because memory B cells serve as a blueprint to make antibodies, like the blueprint of a house. If a house needs an extra column (or antibodies need to evolve to work against variants), the blueprint will oblige just as memory B cells will!
One problem with giving a 3rd dose of our current vaccines is that those antibodies won't be adapted towards the variants. Fully vaccinated people are already now able to generate some antibodies against all the variants we know of to date, thanks to their bank of memory B cells. In other words, no variant has evolved to date that completely evades our vaccines. Memory B cells, once generated by either natural infection or vaccination, should be long-lasting.
If memory B cells are formed by a vaccine, they should be as long-lasting as those from natural infection per various human studies. A 2008 Nature study found that survivors of the 1918 influenza pandemic were able to produce antibodies from memory B cells when exposed to the same influenza strain nine decades later. Of note, mild infections (such as the common cold from the cold-causing coronaviruses called 229E, NL63, OC43, and HKU1) may not reliably produce memory B cell immunity like more severe infections caused by SARS-CoV-2.
Right about now, you may be worrying about a super-variant that might yet emerge to evade all our hard-won immune responses. But most immunologists do not think this is very realistic because of T cells. How are T cells different from B Cells? While B cells are like the memory banks to produce antibodies when needed (helped by T cells), T cells will specifically amplify in response to a piece of the virus and help recruit cells to attack the pathogen directly. We likely have T cells to thank for the vaccine's incredible durability in protecting us against severe disease. Data from La Jolla Immunology Institute and UCSF show that the T cell response from the Pfizer vaccine is strong across all the variants.
Think of your spike protein as being comprised of 100 houses with a T cell there to cover each house (to protect you against severe disease). The variants have around 13 mutations along the spike protein so 13 of those T cells won't work, but there are over 80 T cells remaining to protect your "houses" or your body against severe disease.
Although these are theoretical numbers and we don't know exactly the number of T cell antigens (or "epitopes") across the spike protein, one review showed 1400 across the whole virus, with many of those in the spike protein. Another study showed that there were 87 epitopes across the spike protein to which T cells respond, and mutations in one of the variants (beta) took those down to 75. The virus cannot mutate indefinitely in its spike protein and still retain function. This is why it is unlikely we will get a variant that will evade the in-breadth, robust response of our T cells.
Where We Go From Here
So, what does this mean for getting through this pandemic? Immunity and more immunity. For those of us who are vaccinated, if we get exposed to the Delta variant, it will boost our immune response although the memory B cells might take 3-5 days to make new antibodies, which can leave us susceptible to a mild breakthrough infection. That's part of the reason the CDC put back masks for the vaccinated in late July. For those who are unvaccinated, immunity will be gained from Delta but often through terrible ways like severe disease.
The way for the U.S. to determine the need for 3rd shots among those who are not obviously immunocompromised, given the amazing immune memory generated by the vaccines among immunocompetent individuals, is to analyze the cases of the ~6000 individuals who have had severe breakthrough infections among the 171 million Americans fully vaccinated. Define their co-morbidities and age ranges, and boost those susceptible to severe infections (examples could include older people, those with co-morbidities, health care workers, and residents of long-term care facilities). This is an approach likely to be taken by the CDC's Advisory Committee on Immunization Practices.
If immunity is the only way to get through the pandemic and if variants are caused mostly by large populations being unvaccinated, there is not only a moral and ethical imperative but a practical imperative to vaccinate the world in order to keep us all safe. Immunocompetent Americans can boost their antibodies, which may enhance their ability to avoid mild breakthrough infections, but the initial shots still work well against the most important outcomes: hospitalizations and deaths.
There has been no randomized, controlled trial to assess whether three shots vs. two shots meaningfully improve those outcomes. While we ought to trust immune memory to get the immunocompetent in the United States through, we can hasten the end of this pandemic by providing surplus vaccines to poor countries to combat severe disease. Doing so would not only revitalize the role of the U.S. as a global health leader – it would save countless lives.
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.
Here's how one doctor overcame extraordinary odds to help create the birth control pill
Dr. Percy Julian had so many personal and professional obstacles throughout his life, it’s amazing he was able to accomplish anything at all. But this hidden figure not only overcame these incredible obstacles, he also laid the foundation for the creation of the birth control pill.
Julian’s first obstacle was growing up in the Jim Crow-era south in the early part of the twentieth century, where racial segregation kept many African-Americans out of schools, libraries, parks, restaurants, and more. Despite limited opportunities and education, Julian was accepted to DePauw University in Indiana, where he majored in chemistry. But in college, Julian encountered another obstacle: he wasn’t allowed to stay in DePauw’s student housing because of segregation. Julian found lodging in an off-campus boarding house that refused to serve him meals. To pay for his room, board, and food, Julian waited tables and fired furnaces while he studied chemistry full-time. Incredibly, he graduated in 1920 as valedictorian of his class.
After graduation, Julian landed a fellowship at Harvard University to study chemistry—but here, Julian ran into yet another obstacle. Harvard thought that white students would resent being taught by Julian, an African-American man, so they withdrew his teaching assistantship. Julian instead decided to complete his PhD at the University of Vienna in Austria. When he did, he became one of the first African Americans to ever receive a PhD in chemistry.
Julian received offers for professorships, fellowships, and jobs throughout the 1930s, due to his impressive qualifications—but these offers were almost always revoked when schools or potential employers found out Julian was black. In one instance, Julian was offered a job at the Institute of Paper Chemistory in Appleton, Wisconsin—but Appleton, like many cities in the United States at the time, was known as a “sundown town,” which meant that black people weren’t allowed to be there after dark. As a result, Julian lost the job.
During this time, Julian became an expert at synthesis, which is the process of turning one substance into another through a series of planned chemical reactions. Julian synthesized a plant compound called physostigmine, which would later become a treatment for an eye disease called glaucoma.
In 1936, Julian was finally able to land—and keep—a job at Glidden, and there he found a way to extract soybean protein. This was used to produce a fire-retardant foam used in fire extinguishers to smother oil and gasoline fires aboard ships and aircraft carriers, and it ended up saving the lives of thousands of soldiers during World War II.
At Glidden, Julian found a way to synthesize human sex hormones such as progesterone, estrogen, and testosterone, from plants. This was a hugely profitable discovery for his company—but it also meant that clinicians now had huge quantities of these hormones, making hormone therapy cheaper and easier to come by. His work also laid the foundation for the creation of hormonal birth control: Without the ability to synthesize these hormones, hormonal birth control would not exist.
Julian left Glidden in the 1950s and formed his own company, called Julian Laboratories, outside of Chicago, where he manufactured steroids and conducted his own research. The company turned profitable within a year, but even so Julian’s obstacles weren’t over. In 1950 and 1951, Julian’s home was firebombed and attacked with dynamite, with his family inside. Julian often had to sit out on the front porch of his home with a shotgun to protect his family from violence.
But despite years of racism and violence, Julian’s story has a happy ending. Julian’s family was eventually welcomed into the neighborhood and protected from future attacks (Julian’s daughter lives there to this day). Julian then became one of the country’s first black millionaires when he sold his company in the 1960s.
When Julian passed away at the age of 76, he had more than 130 chemical patents to his name and left behind a body of work that benefits people to this day.