Anxiety disorders are associated with impaired inhibitory neurotransmission mediated by γ-aminobutyric acid type A (GABA-A) receptors. Although benzodiazepines remain effective anxiolytics, their clinical utility is limited by sedation, cognitive impairment, tolerance, and dependence, prompting the search for mechanistically distinct GABAergic modulators. Among cannabinoid-related molecules, the strongest evidence for direct GABA-A receptor modulation concerns the endocannabinoid 2-arachidonoylglycerol (2-AG), which potentiates recombinant human α1β2γ2 receptors through residues located in the M4 helix of the β2 subunit. Here, we review the structural architecture, biophysical properties, and pharmacological profile of the human GABA-A α1β2γ2 isoform as the relevant molecular framework for evaluating this mechanism, while discussing the broader relevance of cannabinoid-related ligands and selected phytocannabinoids without assuming mechanistic equivalence. We further assess the hypothesis that 2-AG reaches the β2-M4 site through a membrane-access route and identify five conceptual barriers that currently limit translation of this mechanism into anxiolytic drug development: supraphysiological effective concentrations, unresolved synaptic-versus-extrasynaptic actions, uncertain subtype selectivity, incomplete validation of lipid-environment effects, and lack of clinical evidence linking this mechanism to anxiolysis in humans. We conclude that direct modulation through β2-M4 defines a mechanistically intriguing allosteric pathway distinct from benzodiazepine action; however, its location on a shared β2 subunit and the micromolar concentrations required for modulation represent substantial obstacles to the rational design of anxioselective agents based on this mechanism.
The Download: a Nobel winner on AI, and the case for fixing everything
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
Three things in AI to watch, according to a Nobel-winning economist
A few months before he won the Nobel Prize in economics in 2024, Daron Acemoglu published a paper that earned him few fans in Silicon Valley. He argued that AI would give only a small boost to US productivity and would not eliminate the need for human work.
Two years later, Acemoglu’s measured take has not caught on. The technology has advanced quite a bit since his cautious predictions, but the data is still largely on his side.
MIT Technology Review spoke with him to understand if any of the latest developments have changed his thesis. Here are the three things Acemoglu is paying closest attention to in AI right now.
—James O’Donnell
This story is from The Algorithm, our weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday.
The case for fixing everything
Stewart Brand, the counterculture icon and tech industry legend, considers maintenance a “civilizational” act. His new book argues that taking responsibility for maintaining something, whether a motorcycle, a monument, or the planet, can be radical.
Brand argues that maintainers haven’t gotten the laurels they deserve—and he’s right. Yet his vision of maintenance often feels solitary: profound, but more about personal fulfillment than tending to a shared world or making it better.
Read the full review of his handsome new book, Maintenance: Of Everything, Part One.
—Lee Vinsel
Lee Vinsel is an associate professor of science, technology, and society at Virginia Tech, a cofounder of The Maintainers, and the host of Peoples & Things, a podcast about human life with technology.
This story is from the latest edition of our print magazine, which is all about nature. Subscribe now to read the full issue and receive future print copies once they land.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 The first zero-day exploit built by AI has been discovered
Google spotted and stopped the attempted “mass exploitation event.” (CNBC)
+ The hackers used AI to discover an unknown bug. (NYT $)
+ AI-powered hacking has exploded into an industrial-scale threat. (Guardian)
+ New tools are simplifying online crime. (MIT Technology Review)
2 OpenAI just launched its answer to Claude Mythos
Daybreak patches vulnerabilities before attackers find them. (The Verge)
+ Sam Altman said it will “continuously secure software.” (Gizmodo)
+ It will rival Anthropic’s Claude Mythos, which arrived a month ago. (BBC)
+ OpenAI is allowing wider access to its cyber models than Anthropic. (CNBC)
3 Trump is heading to China to spread the gospel of American tech
While taking cues from Beijing’s more stringent approach. (Guardian)
+ But investors want Trump and Xi to stay out of AI’s way. (Reuters $)
+ Elon Musk and Tim Cook are joining him on the trip this week. (BBC)
4 Ilya Sutskever has testified on Sam Altman’s “pattern of lying”
OpenAI co-founder Sutskever took the stand in the Altman v. Musk trial. (BI)
+ He said he spent a year gathering proof of Altman’s dishonesty. (Reuters $)
+ But he also added to OpenAI’s defense. (Wired $)
+ While Satya Nadella called attempts to remove Altman “amateur city.” (FT $)
+ Here’s what happened last week in the trial. (MIT Technology Review)
5 A new hantavirus vaccine is in the works
Moderna and Korea University are developing an mRNA vaccine. (Wired $)
+ Here’s what you need to know about the cruise ship outbreak. (MIT Technology Review)
6 Texas has sued Netflix over alleged data harvesting and “addictive” design
AG Ken Paxton accuses Netflix of secretly collecting and selling user data. (Quartz)
+ And spying on children while deliberately fostering addiction. (Guardian)
7 A data center guzzled 30 million gallons of water—and no one noticed
The curious case serves as a warning for other data center projects. (Ars Technica)
8 Europe is reportedly selling spyware to human rights abusers
EU states allegedly sold the tech to countries violating rights. (Bloomberg $)
9 The US government’s AI vetting announcement has mysteriously vanished
It had detailed a security test agreement with Google, xAI, and Microsoft. (Gizmodo)
10 Amazon staff are using AI for pointless tasks just to inflate usage scores
In a bid to impress managers. (FT $)
+ An AI expert says we should stop using AI so much. (MIT Technology Review)
Quote of the day
“This is like the cheating husband complaining about the cheating wife.”
—Anupam Chander, a professor of law and technology at Georgetown Law School, tells the New York Times that Elon Musk’s hypocrisy over OpenAI becoming a for-profit company will undermine his courtroom battle with Sam Altman.
One More Thing
STUART BRADFORD
How sounds can turn us on to the wonders of the universe
For decades, astronomy has relied on visual information to make sense of the cosmos: images, charts, and graphs. Now, some researchers are trying something different: listening to the universe.
Using sonification, the process of turning information into sound, they’re helping blind and visually impaired researchers explore the cosmos—and even uncover patterns that might otherwise go unnoticed. The approach is spreading beyond astronomy into fields like climate science, navigation, and education.
Discover how sound could make science more accessible—and even more revealing.
—Corey S. Powell
We can still have nice things
A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.)
+ This musical mashup beautifully blends LCD Soundsystem with Twin Peaks.
+ Match your speculative ideas to sci-fi stories with the Extrapolated Futures Archive.
+ A live-action animation Coyote vs. ACME is coming soon—and the first trailer just dropped.
+ Want to surf elsewhere in the galaxy? Here’s what it would be like to catch waves on distant planets.
Therapeutic Interventions Targeted at Problematic Use of Digital Technology: Systematic Review and Meta-Analysis of Evidence
Background: Problematic use of digital technology has increased across the world. Despite growing research, evidence on treatment effectiveness across digital behaviors remains fragmented. Objective: This study aimed to systematically evaluate and compare the effectiveness of therapeutic interventions targeted at problematic use of digital technology across various behavioral domains. Methods: A systematic review and meta-analysis was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines (PROSPERO: CRD420251052442). Electronic searches of PubMed, Scopus, and Embase (up to April 2025) were conducted. It identified 125 eligible studies, including 73 randomized controlled trials (RCTs), 32 non-RCTs, 14 pre-post studies, and 6 pilot studies. The interventions that were assessed in these studies included psychological therapies, digital or web-based programs, exercise-based interventions, pharmacological treatments, neuromodulation, parent-focused programs, virtual reality–based interventions, educational programs, and multicomponent approaches. Random-effects meta-analyses using standardized mean differences (SMDs) were performed. Results: For problematic internet use, psychological treatments showed a strong effect (effect size=−2.68; <.001). Digital interventions also showed significant benefit (effect size=−1.16; <.001). For smartphone addiction, psychological treatments (effect size=−1.49; <.001) and exercise-based programs (effect size=−3.07; =.001) showed significant improvement. For gaming disorder, psychological treatments showed improvement (effect size=−1.01; =.02), but results were mixed. There were limited studies to calculate pooled results for social media addiction, pornography use, gambling, screen time, and over-the-top content watching. No treatment studies were found for problematic over-the-top content watching. High heterogeneity and evidence of small-study effects were observed in several studies. Conclusions: Overall, structured psychological therapies showed the most consistent benefit. These findings support structured interventions that aim for control of use and reduce cues linked to high use. Evidence remains limited for several emerging digital behaviors. More high-quality studies are needed in clinical settings and for less-studied forms of digital addiction.
Supreme Court extends mifepristone deadline
Get your daily dose of health and medicine every weekday with STAT’s free newsletter Morning Rounds. Sign up here.
Good morning. My co-workers and pals Isabella Cueto and Lev Facher have been talking about alcohol for years. As STAT’s reporters on chronic disease and addiction, respectively, it’s right at the intersection of their beats, yet rarely covered as a public health issue. I’m happy to share that all their talking turned to reporting, and now an incredible series. The first parts are up now. Scroll down or skip ahead to start reading.
Integrating dual-process decision making and social dynamics: A formal modeling framework for addiction.
Psychological Review, Vol 133(4), Jul 2026, 864-891; doi:10.1037/rev0000584
Currently, formal models of addiction focus either on the complex individual decision-making processes involved in addiction or on the social dynamics of addiction. They do not integrate these two levels, which has been identified as a key shortcoming of current formal models of addiction. To address this, we propose a nonlinear dynamical modeling framework of addiction integrating both the individual level and social level of addictive behavior. The individual level of our modeling framework is a formalization of a dual-process theory, where one type of process increases the consumption of addictive goods, and another type of process limits consumption. For our formalization, we build on a well-studied model from ecology, originally used to model periodic outbreaks of the spruce budworm population. To this model, we add the process of incentive sensitization at the individual level and at the social level, we incorporate the critical processes of selection homophily and peer influence. We show that our integrated modeling framework can be used to explain key phenomena identified in addiction literature: a gradual transition to heavy use, sudden relapse and sudden quitting, relatively stable use states over time (i.e., abstinence moderate use, and heavy use), social contagion and sudden outbreaks, clustering of users, and social aid in recovery. In addition, we demonstrate how our modeling framework can be extended to include mutualistic, competitive, and more complex interactions between different addictive behaviors. Finally, we show how our framework can lead to new insights and predictions and suggest avenues for future research. (PsycInfo Database Record (c) 2026 APA, all rights reserved)
STAT+: Trump pivots on kratom derivative 7-OH, floating approval for some forms
President Trump on Monday suggested the federal government could move to approve some forms of 7-OH, an opioid derived from the naturally occurring kratom plant.
“We’re looking very seriously at natural 7-OH and getting that approved,” Trump said.
It was not clear what Trump meant by “natural 7-OH.” Small amounts of the compound, shorthand for 7-hydroxymitragynine, occur naturally in kratom, which is increasingly used as a recreational drug and an unapproved pain treatment. While kratom is significantly less dangerous than potent synthetic opioids like fentanyl or prescription pain pills, it can still cause addiction and overdose.
<![CDATA[Psilocybin therapy shows fast, lasting relief for depression; clinicians discuss trial hurdles and emerging promise for PTSD and addiction in this podcast.]]>
Digital Therapeutic Content for Substance Use Disorder Treatment: Development and Evaluation Study
Background: Substance use disorders (SUDs) are a major public health concern, contributing to significant individual and societal costs. Despite this, the uptake of evidence-based pharmacologic and behavioral interventions remains limited. The digital delivery of SUD treatment has emerged as a potentially scalable way to reduce access barriers and increase treatment use. Existing digital therapeutic interventions are often created without clinician involvement, evidence-based materials, interdisciplinary input, or content review. The implementation of a structured and methodologically rigorous development process is needed across digital health interventions to help ensure patient-facing materials are validated, understandable, and actionable for the end user. Objective: This early report seeks to describe and evaluate an iterative, interdisciplinary, platform-agnostic process for adapting and refining existing print materials for digital therapeutic modules in SUD treatment. The a priori goal was to evaluate if a structured, human-centered approach would generate digital modules that were rated as understandable and actionable based on a validated assessment for written materials. Methods: Fourteen therapeutic modules were adapted from existing Mayo Clinic–written, patient-facing education materials originally developed by a board-certified addiction psychiatrist and a doctoral-level education specialist for clinical use. A team of 4 purposively recruited licensed alcohol and drug counselors with lived experience with a SUD, all in recovery, and a doctoral-level therapeutic specialist met weekly for one hour over a 6-month period to iteratively adapt this existing content for smartphone delivery (2‐3 hours per module). The process flow included selecting source material, restructuring content for viewing on a phone screen, simplifying language, improving organization and flow to promote understanding, and including specific actions users could take based on the content. The counselors then independently evaluated the modules using the Patient Education Materials Assessment Tool for printable materials (PEMAT-P). PEMAT-P scores for understandability and actionability were calculated as percentages, and descriptive statistics were used to summarize scores in aggregate and across modules. A target of >70% was set for each PEMAT-P domain, consistent with accepted benchmarking standards. Results: Mean understandability and actionability for all modules were 87.2% (SD 4.8%; range 81.4%‐96.9%) and 75.1% (SD 12.3%; range 57.1%‐95.0%), respectively, exceeding the recommended threshold. While all modules were adequately understandable, 35.7% (5/14) scored below the actionability threshold. Conclusions: This early report highlights the value of a human-centered, iterative process for adapting therapeutic materials for digital delivery in SUD treatment. Although the modules performed well overall on PEMAT-P benchmarks, actionability was less consistent than understandability, and aggregate scores masked weaknesses in several individual modules. This indicates that a standardized process does not guarantee actionable material across all content types. Involving current patients in this process may improve the end product by incorporating a perspective that was previously missed.
Trends of incident stimulant use disorder diagnoses before and after the COVID-19 pandemic in British Columbia (2013-2024): a population-based study
BackgroundThere is rising detection of unregulated stimulants (e.g. cocaine and methamphetamine) in toxicology results among people who died of unregulated drug poisoning. Nevertheless, little research describes the population-level trends of incident (new) stimulant use disorder (StUD) diagnoses. This study reports on trends of incident StUD diagnoses pre- and post-Covid-19 public health emergency in British Columbia (BC), Canada.MethodsInterrupted time series analyses were conducted with BC’s COVID-19 public health emergency declaration on March 16, 2020 as the interruption point. Descriptive statistics on demographic and health service contact were conducted for the population diagnosed before (January 1, 2013 – March 16, 2020) and after (March 17, 2020 – December 31, 2024) the COVID-19 pandemic emergency declaration. Seasonal autoregressive integrated moving average (sARIMA) models were used to .estimate changes to incident StuD diagnoses rates before and after the COVID-19 pandemic declaration.Results38, 217 people were identified with incident StUD diagnoses between January 1, 2013 and March 31, 2024. The average diagnosis rate of incident StUD was 5.18 per 100, 000 in the pre-pandemic period and increased by 19.9% to 6.21 per 100, 000 in the post-pandemic period. The estimated increase in slope (ramp) of incident StUD was 0.0315 cases per 100, 000 population per month (95% CI: -0.00182, 0.06482).ConclusionsWe identified a rate of increase in incident StUD diagnoses since the COVID-19 pandemic declaration in BC that was not statistically significant. Our study highlights the need for more comprehensive linked data -including, administrative health data, surveys, and other services/program data (e.g., community services, private sector) to better disentangle StUD incidence and prevalence to inform services to meet the needs of people with StUD. Stimulant use, Stimulant use disorder, pandemic, Covid-19, methamphetamines, cocaine, interrupted time series.
Trump administration’s drug strategy is at odds with recent actions on funding, policy
The White House’s new strategy for addressing the nation’s drug crisis calls for a number of consensus public health measures: the overdose-reversal medication naloxone, medication-assisted treatment, and test strips used to detect fentanyl or other drug supply adulterants.
But the May 4 document appears to run counter to many of the Trump administration’s latest drug policy actions. In particular, it comes just days after the administration issued new restrictions on using federal dollars to distribute test strips and warned against the use of medication-assisted treatment unless accompanied by other services, like counseling.