How 30 Years of Heart Surgeries Taught My Dad How to Live
![How 30 Years of Heart Surgeries Taught My Dad How to Live](https://upworthyscience.com/media-library/a-mid-1970s-photo-of-the-author-s-father-and-him-holding-a-grandchild-in-2012.jpg?id=24247469&width=1245&height=700&quality=85&coordinates=0%2C62%2C0%2C62)
A mid-1970s photo of the author's father, and him holding a grandchild in 2012.
[Editor's Note: This piece is the winner of our 2019 essay contest, which prompted readers to reflect on the question: "How has an advance in science or medicine changed your life?"]
My father did not expect to live past the age of 50. Neither of his parents had done so. And he also knew how he would die: by heart attack, just as his father did.
In July of 1976, he had his first heart attack, days before his 40th birthday.
My dad lived the first 40 years of his life with this knowledge buried in his bones. He started smoking at the age of 12, and was drinking before he was old enough to enlist in the Navy. He had a sarcastic, often cruel, sense of humor that could drive my mother, my sister and me into tears. He was not an easy man to live with, but that was okay by him - he didn't expect to live long.
In July of 1976, he had his first heart attack, days before his 40th birthday. I was 13, and my sister was 11. He needed quadruple bypass surgery. Our small town hospital was not equipped to do this type of surgery; he would have to be transported 40 miles away to a heart center. I understood this journey to mean that my father was seriously ill, and might die in the hospital, away from anyone he knew. And my father knew a lot of people - he was a popular high school English teacher, in a town with only three high schools. He knew generations of students and their parents. Our high school football team did a blood drive in his honor.
During a trip to Disney World in 1974, Dad was suffering from angina the entire time but refused to tell me (left) and my sister, Kris.
Quadruple bypass surgery in 1976 meant that my father's breastbone was cut open by a sternal saw. His ribcage was spread wide. After the bypass surgery, his bones would be pulled back together, and tied in place with wire. The wire would later be pulled out of his body when the bones knitted back together. It would take months before he was fully healed.
Dad was in the hospital for the rest of the summer and into the start of the new school year. Going to visit him was farther than I could ride my bicycle; it meant planning a trip in the car and going onto the interstate. The first time I was allowed to visit him in the ICU, he was lying in bed, and then pushed himself to sit up. The heart monitor he was attached to spiked up and down, and I fainted. I didn't know that heartbeats change when you move; television medical dramas never showed that - I honestly thought that I had driven my father into another heart attack.
Only a few short years after that, my father returned to the big hospital to have his heart checked with a new advance in heart treatment: a CT scan. This would allow doctors to check for clogged arteries and treat them before a fatal heart attack. The procedure identified a dangerous blockage, and my father was admitted immediately. This time, however, there was no need to break bones to get to the problem; my father was home within a month.
During the late 1970's, my father changed none of his habits. He was still smoking, and he continued to drink. But now, he was also taking pills - pills to manage the pain. He would pop a nitroglycerin tablet under his tongue whenever he was experiencing angina (I have a vivid memory of him doing this during my driving lessons), but he never mentioned that he was in pain. Instead, he would snap at one of us, or joke that we were killing him.
I think he finally determined that, if he was going to have these extra decades of life, he wanted to make them count.
Being the kind of guy he was, my father never wanted to talk about his health. Any admission of pain implied that he couldn't handle pain. He would try to "muscle through" his angina, as if his willpower would be stronger than his heart muscle. His efforts would inevitably fail, leaving him angry and ready to lash out at anyone or anything. He would blame one of us as a reason he "had" to take valium or pop a nitro tablet. Dinners often ended in shouts and tears, and my father stalking to the television room with a bottle of red wine.
In the 1980's while I was in college, my father had another heart attack. But now, less than 10 years after his first, medicine had changed: our hometown hospital had the technology to run dye through my father's blood stream, identify the blockages, and do preventative care that involved statins and blood thinners. In one case, the doctors would take blood vessels from my father's legs, and suture them to replace damaged arteries around his heart. New advances in cholesterol medication and treatments for angina could extend my father's life by many years.
My father decided it was time to quit smoking. It was the first significant health step I had ever seen him take. Until then, he treated his heart issues as if they were inevitable, and there was nothing that he could do to change what was happening to him. Quitting smoking was the first sign that my father was beginning to move out of his fatalistic mindset - and the accompanying fatal behaviors that all pointed to an early death.
In 1986, my father turned 50. He had now lived longer than either of his parents. The habits he had learned from them could be changed. He had stopped smoking - what else could he do?
It was a painful decade for all of us. My parents divorced. My sister quit college. I moved to the other side of the country and stopped speaking to my father for almost 10 years. My father remarried, and divorced a second time. I stopped counting the number of times he was in and out of the hospital with heart-related issues.
In the early 1990's, my father reached out to me. I think he finally determined that, if he was going to have these extra decades of life, he wanted to make them count. He traveled across the country to spend a week with me, to meet my friends, and to rebuild his relationship with me. He did the same with my sister. He stopped drinking. He was more forthcoming about his health, and admitted that he was taking an antidepressant. His humor became less cruel and sadistic. He took an active interest in the world. He became part of my life again.
The 1990's was also the decade of angioplasty. My father explained it to me like this: during his next surgery, the doctors would place balloons in his arteries, and inflate them. The balloons would then be removed (or dissolve), leaving the artery open again for blood. He had several of these surgeries over the next decade.
When my father was in his 60's, he danced at with me at my wedding. It was now 10 years past the time he had expected to live, and his life was transformed. He was living with a woman I had known since I was a child, and my wife and I would make regular visits to their home. My father retired from teaching, became an avid gardener, and always had a home project underway. He was a happy man.
Dancing with my father at my wedding in 1998.
Then, in the mid 2000's, my father faced another serious surgery. Years of arterial surgery, angioplasty, and damaged heart muscle were taking their toll. He opted to undergo a life-saving surgery at Cleveland Clinic. By this time, I was living in New York and my sister was living in Arizona. We both traveled to the Midwest to be with him. Dad was unconscious most of the time. We took turns holding his hand in the ICU, encouraging him to regain his will to live, and making outrageous threats if he didn't listen to us.
The nursing staff were wonderful. I remember telling them that my father had never expected to live this long. One of the nurses pointed out that most of the patients in their ward were in their 70's and 80's, and a few were in their 90's. She reminded me that just a decade earlier, most hospitals were unwilling to do the kind of surgery my father had received on patients his age. In the first decade of the 21st century, however, things were different: 90-year-olds could now undergo heart surgery and live another decade. My father was on the "young" side of their patients.
The Cleveland Clinic visit would be the last major heart surgery my father would have. Not that he didn't return to his local hospital a few times after that: he broke his neck -- not once, but twice! -- slipping on ice. And in the 2010's, he began to show signs of dementia, and needed more home care. His partner, who had her own health issues, was not able to provide the level of care my father needed. My sister invited him to move in with her, and in 2015, I traveled with him to Arizona to get him settled in.
After a few months, he accepted home hospice. We turned off his pacemaker when the hospice nurse explained to us that the job of a pacemaker is to literally jolt a patient's heart back into beating. The jolts were happening more and more frequently, causing my Dad additional, unwanted pain.
My father in 2015, a few months before his death.
My father died in February 2016. His body carried the scars and implants of 30 years of cardiac surgeries, from the ugly breastbone scar from the 1970's to scars on his arms and legs from borrowed blood vessels, to the tiny red circles of robotic incisions from the 21st century. The arteries and veins feeding his heart were a patchwork of transplanted leg veins and fragile arterial walls pressed thinner by balloons.
And my father died with no regrets or unfinished business. He died in my sister's home, with his long-time partner by his side. Medical advancements had given him the opportunity to live 30 years longer than he expected. But he was the one who decided how to live those extra years. He was the one who made the years matter.
Researchers probe extreme gene therapy for severe alcoholism
When all traditional therapeutic approaches fail for alcohol abuse disorder, a radical gene therapy might be something to try in the future.
Story by Freethink
A single shot — a gene therapy injected into the brain — dramatically reduced alcohol consumption in monkeys that previously drank heavily. If the therapy is safe and effective in people, it might one day be a permanent treatment for alcoholism for people with no other options.
The challenge: Alcohol use disorder (AUD) means a person has trouble controlling their alcohol consumption, even when it is negatively affecting their life, job, or health.
In the U.S., more than 10 percent of people over the age of 12 are estimated to have AUD, and while medications, counseling, or sheer willpower can help some stop drinking, staying sober can be a huge struggle — an estimated 40-60 percent of people relapse at least once.
A team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
According to the CDC, more than 140,000 Americans are dying each year from alcohol-related causes, and the rate of deaths has been rising for years, especially during the pandemic.
The idea: For occasional drinkers, alcohol causes the brain to release more dopamine, a chemical that makes you feel good. Chronic alcohol use, however, causes the brain to produce, and process, less dopamine, and this persistent dopamine deficit has been linked to alcohol relapse.
There is currently no way to reverse the changes in the brain brought about by AUD, but a team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
To find out, they tested it in heavy-drinking monkeys — and the animals’ alcohol consumption dropped by 90% over the course of a year.
How it works: The treatment centers on the protein GDNF (“glial cell line-derived neurotrophic factor”), which supports the survival of certain neurons, including ones linked to dopamine.
For the new study, a harmless virus was used to deliver the gene that codes for GDNF into the brains of four monkeys that, when they had the option, drank heavily — the amount of ethanol-infused water they consumed would be equivalent to a person having nine drinks per day.
“We targeted the cell bodies that produce dopamine with this gene to increase dopamine synthesis, thereby replenishing or restoring what chronic drinking has taken away,” said co-lead researcher Kathleen Grant.
To serve as controls, another four heavy-drinking monkeys underwent the same procedure, but with a saline solution delivered instead of the gene therapy.
The results: All of the monkeys had their access to alcohol removed for two months following the surgery. When it was then reintroduced for four weeks, the heavy drinkers consumed 50 percent less compared to the control group.
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
The researchers then took the alcohol away for another four weeks, before giving it back for four. They repeated this cycle for a year, and by the end of it, the treated monkeys’ consumption had fallen by more than 90 percent compared to the controls.
“Drinking went down to almost zero,” said Grant. “For months on end, these animals would choose to drink water and just avoid drinking alcohol altogether. They decreased their drinking to the point that it was so low we didn’t record a blood-alcohol level.”
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
Looking ahead: Dopamine is involved in a lot more than addiction, so more research is needed to not only see if the results translate to people but whether the gene therapy leads to any unwanted changes to mood or behavior.
Because the therapy requires invasive brain surgery and is likely irreversible, it’s unlikely to ever become a common treatment for alcoholism — but it could one day be the only thing standing between people with severe AUD and death.
“[The treatment] would be most appropriate for people who have already shown that all our normal therapeutic approaches do not work for them,” said Grant. “They are likely to create severe harm or kill themselves or others due to their drinking.”
This article originally appeared on Freethink, home of the brightest minds and biggest ideas of all time.
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
Generative AI has a large carbon footprint and other drawbacks. But AI can help mitigate its own harms—by plowing through mountains of data on extreme weather and human displacement.
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the book The Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
AI's accountability
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.