Sexually Transmitted Infections are on the rise. This drug could stop them.
Sexually transmitted infections (STIs) are surging across the U.S. to 2.5 million cases in 2021 according to preliminary data from the CDC. A new prevention and treatment strategy now in clinical trials may provide a way to get a handle on them.
It's easy to overlook the soaring rates of gonorrhea, chlamydia, and syphilis because most of those infections have few or no symptoms and can be identified only through testing. But left untreated, they can lead to serious damage to nerves and tissue, resulting in infertility, blindness, and dementia. Infants developing in utero are particularly vulnerable.
Covid-19 played havoc with regular medical treatment and preventive care for many health problems, including STIs. After formal lockdowns ended, many people gradually became more socially engaged, with increases in sexual activity, and may have prioritized these activities over getting back in touch with their doctors.
A second blow to controlling STIs is that family planning clinics are closing left and right because of the Dobbs decision and legislation in many states that curtailed access to an abortion. Discussion has focused on abortion, but those same clinics also play a vital role in the diagnosis and treatment of STIs.
Routine public health is the neglected stepchild of medicine. It is called upon in times of crisis but as that crisis resolves, funding dries up. Labs have atrophied and personnel have been redirected to Covid, “so access to routine screening for STIs has been decimated,” says Jennifer Mahn, director of sexual and clinical health with the National Coalition of STD Directors.
A preview of what we likely are facing comes from Iowa. In 2017, the state legislature restricted funding to family health clinics in four counties, which closed their doors. A year later the statewide rate of gonorrhea skyrocketed from 83 to 153.7 cases per 100,000 people. “Iowa counties with clinic closures had a significantly larger increase,” according to a study published in JAMA. That scenario likely is playing out in countless other regions where access to sexual health care is shrinking; it will be many months before we have the data to know for sure.
A decades-old antibiotic finds a new purpose
Using drugs to protect against HIV, either as post exposure prophylaxis (PEP) or pre-exposure prophylaxis (PrEP), has proven to be quite successful. Researchers wondered if the same approach might be applied to other STIs. They focused on doxycycline, or doxy for short. One of the most commonly prescribed antibiotics in the U.S., it’s a member of the tetracycline family that has been on the market since 1967. It is so safe that it’s used to treat acne.
Two small studies using doxy suggested that it could work to prevent STIs. A handful of clinical trials by different researchers and funding sources set out to generate the additional evidence needed to prove their hypothesis and change the standard of care.
Senior researcher Victor Omollo, with the Kenya Medical Research Institute, noted, “These are prevention interventions that women can control on their own without having to seek or get consent from another person,” as is the case with condom use.
The first with results is the DoxyPEP study, conducted at two sexual health clinics in San Francisco and Seattle. It drew from a mix of transgender women and men who have sex with men, who had at least one diagnosed STI over the last year. The researchers divided the participants into two groups: one with people who were already HIV-positive and engaged in care, while the other group consisted of people who were on PrEP to prevent infection with HIV. For the active part of the study, a subset of the participants received doxy, and the rest of the participants did not.
The researchers intentionally chose to do the study in a population at the highest risk of having STIs, who were very health oriented, and “who were getting screened every three months or so as part of their PrEP program or their HIV care program,” says Connie Celum, a senior researcher at the University of Washington on the study.
Each member of the active group was given a supply of doxy and asked to take two pills within 72 hours of having sex where a condom was not used. The study was supposed to run for two years but, in May, it stopped halfway through, when a safety monitoring board looked at the data and recommended that it would be unethical to continue depriving the control group of the drug’s benefits.
Celum presented these preliminary results from the DoxyPEP study in July at the International AIDS Conference in Montreal. “We saw about a 56 percent reduction in gonorrhea, about 80 percent reduction in chlamydia and syphilis, so very significant reductions, and this is on a per quarter basis,” she told a later webinar.
In Kenya, another study is following a group of cisgender women who are taking the same two-pill regimen to prevent HIV, and the data from this research should become available in 2023. Senior researcher Victor Omollo, with the Kenya Medical Research Institute, noted that “these are prevention interventions that women can control on their own without having to seek or get consent from another person,” as is the case with condom use, another effective prevention tool.
Antibiotic resistance
Antibiotic resistance is a potentially big concern. About 25 percent of gonorrhea strains circulating in the U.S. are resistant to the tetracycline class of drugs, including doxy; rates are higher elsewhere. But resistance often is a matter of degree and can be overcome with a larger or longer dose of the drug, or perhaps with a switch to another drug or a two-drug combination.
Research has shown that an established bacterial infection is more difficult to treat because it is part of a biofilm, which can leave only a small portion or perhaps none of the cell surface exposed to a drug. But a new infection, even one where the bacteria is resistant to a drug, might still be vulnerable to that drug if it's used before the bacterial biofilm can be established. Preliminary data suggests that may be the case with doxyPEP and drug resistant gonorrhea; some but not all new drug resistant infections might be thwarted if they’re treated early enough.
“There are some tradeoffs” to these interventions, Celum says, and people may disagree on the cost of increased resistance balanced against the benefits of treating the STIs and reducing their spread within the community.
Resistance does not seem to be an issue yet for chlamydia and syphilis even though doxy has been a recommended treatment for decades, but a remaining question is whether broader use of doxy will directly worsen antibiotic resistance in gonorrhea, or promote it in other STIs. And how will it affect the gut microbiome?
In addition, Celum notes that we need to understand whether doxy will generate mutations in other bacteria that might contribute to drug resistance for gonorrhea, chlamydia or syphilis. The studies underway aim to provide data to answer these questions.
“There are some tradeoffs” to these interventions, Celum says, and people may disagree on the cost of increased resistance balanced against the benefits of treating the STIs and reducing their spread within the community. That might affect doctors' willingness to prescribe the drug.
Turning research into action
The CDC makes policy recommendations for prevention services such as taking doxy, requiring some and leaving others optional. Celum says the CDC will be reviewing information from her trial at a meeting in December, but probably will wait until that study is published before making recommendations, likely in 2023. The San Francisco Department of Public Health issued its own guidance on October 20th and anecdotally, some doctors around the country are beginning to issue prescriptions for doxy to select patients.
About half of new STIs occur in young people ages 15 to 24, a group that is least likely to regularly see a doctor. And sexual health remains a great taboo for many people who don't want such information on their health record for prying parents, employers or neighbors to find out.
“People will go out of their way and travel extensive distances just to avoid that,” says Mahn, the National Coalition director. “People identify locations where they feel safe, where they feel welcome, where they don't feel judged,” Mahn explains, such as community and family planning clinics. They understand those issues and have fees that vary depending on a person’s ability to pay.
Given that these clinics already are understaffed and underfunded, they will be hard pressed to expand services covering the labor intensive testing and monitoring of a doxyPEP regimen. Sexual health clinics don't even have a separate line item in the federal budget for health. That is something the National Association of STI Directors is pushing for in D.C.
DoxyPEP isn't a panacea, and it isn't for everyone. “We really want to try to reach that population who is most likely going to have an STI in the next year,” says Celum, “Because that's where you are going to have the biggest impact.”
Researchers probe extreme gene therapy for severe alcoholism
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?
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.