<![CDATA[Explore how circadian gene rhythms differ in schizophrenia, depression, and bipolar disorder—and why stable sleep timing may curb addiction risk.]]>
Tracking the longitudinal course of physiologic and mental health functioning among individuals in substance use disorder treatment
IntroductionMental health monitoring is crucial to long-term recovery in substance use disorder (SUD) treatment; however, little is known about how changes in physiological indicators align with changes in self-reported mental health over time.MethodsWe examined longitudinal associations of resting heart rate (RHR) and heart rate variability (HRV) collected via a WHOOP® photoplethysmography device with self-reported stress, anxiety, and depressive symptoms among individuals in SUD treatment. Participants (N = 59) continuously wore the device and completed at least two mental health and stress assessments during the first month of residential treatment. ResultsLinear regression results indicated favorable changes in mental health and/or physiologic metrics, with notable heterogeneity in concurrent subject-level trends. Among participants with decreased RHR (better physiological functioning), 39% (N=23) also endorsed decreased stress, 42% (N=25) decreased anxiety, and 39% (N=23) improved depressive symptoms. Of those with increased HRV (greater stress adaptability), 39% (N=23) endorsed decreased stress, 39% (N=23) improved anxiety, and 41% (N=24) reduced depressive symptoms.DiscussionConcurrent changes in physiologic and mental health metrics during the first month of treatment varied across participants. These findings highlight the importance of integrating subjective mental health measures with physiological indicators to capture clinically relevant change during early SUD treatment.
Association between plasma proBDNF levels and cognitive impairment in patients with alcohol dependence: a case–control and longitudinal study
BackgroundAlcohol dependence is frequently accompanied by cognitive impairment. Brain-derived neurotrophic factor (BDNF) signaling plays a critical role in synaptic plasticity, while the precursor form, proBDNF, has been increasingly implicated in neurodegenerative and psychiatric disorders. However, the association between plasma proBDNF levels and cognitive impairment in alcohol dependence remains unclear.MethodsEighty male patients with alcohol dependence and forty-two matched healthy controls were enrolled. Plasma proBDNF levels were measured via enzyme-linked immunosorbent assay (ELISA). Cognitive function was assessed using the Mini-Mental State Examination (MMSE), the Modified Wisconsin Card Sorting Test (M-WCST), and the Verbal Fluency Test (VFT). Forty-one patients were reassessed after four weeks of abstinence. Group comparisons and correlation analyses were performed.ResultsPatients with alcohol dependence exhibited significantly elevated plasma proBDNF levels and impaired cognitive performance compared with controls. Plasma proBDNF levels were positively correlated with alcohol consumption severity, and linked to global cognitive deficits alongside nuanced executive performance variations. After four weeks of abstinence, plasma proBDNF levels decreased and cognitive performance improved; however, changes in proBDNF were weakly associated with cognitive recovery.ConclusionsElevated plasma proBDNF levels are associated with alcohol dependence severity and cognitive impairment, suggesting that proBDNF may serve as a peripheral biomarker reflecting the dynamic neurocognitive status in alcohol dependence.
Are Republicans turning against medications for treating opioid addiction?
When Robert F. Kennedy Jr. took office in February 2025, he broke new ground as the first health secretary openly in recovery from addiction to drugs and alcohol.
At a public appearance soon after, he delivered precisely the message that many substance use experts had hoped to hear: that evidence-based medications for treating opioid addiction, in particular, would remain essential components of the country’s response to its drug overdose crisis.
Testing STAR and TextSTAR: A Randomized Controlled Trial
Conditions: Sexual Violence; Posttraumatic Stress Disorder (PTSD); Opioid Misuse
Interventions: Behavioral: Skills Training in Active Recovery (STAR) Video; Behavioral: Text Skills Training in Active Recovery (TextSTAR) program
Sponsors: University of Wisconsin, Madison; National Institute on Drug Abuse (NIDA)
Enrolling by invitation
Interventions: Behavioral: Skills Training in Active Recovery (STAR) Video; Behavioral: Text Skills Training in Active Recovery (TextSTAR) program
Sponsors: University of Wisconsin, Madison; National Institute on Drug Abuse (NIDA)
Enrolling by invitation
Neurocognitive function among individuals with problematic social media use
BackgroundWith the development of technology and the internet, social networks gained momentum quickly and play a central role in daily activities. Despite this, there is a public health concern over excessive or problematic social media use. There is also a debate whether excessive social media use should be considered as a behavioral addiction characterized by impulsivity or an impulse control disorder characterized by compulsivity. The goal of this study is to use neurocognitive tasks to investigate impulsivity and compulsivity among excessive social media users compared with non-excessive users.MethodThe study included 79 participants (age range 18 to 37), divided into two groups: 34 participants who excessively use social media (Mean Age = 23.03, SD = 2.71) and 45 participants who do not excessively use social media (Mean Age = 25.47, SD = 4.3). Participants filled out a demographic questionnaire, questionnaires on social media use, impulsivity, compulsivity, anxiety, and depression. They performed computerized cognitive tasks: GO/NO-GO (with Facebook and traffic sign pictures), Experimental Delay Discounting (EDT), and the Wisconsin Card Sorting Test (WCST).ResultsExcessive users of social media exhibited a lower ability to delay gratification on the EDT, indicating impulsivity. They made fewer non-perseverative errors on the WCST, which indicated high flexibility and test shifting, which is a contradicting evidence for compulsivity. Furthermore, on the GO/NO-GO task, individuals who excessively use social media made more omission errors in response to the “Facebook” sign compared to traffic signs (GO condition), indicating impaired selective attention. Finally, they also showed higher subjective ratings of anxiety, depression, impulsivity, and compulsivity.DiscussionThe results of this study provide evidence for impulsivity indicated by delay discounting tendency, which supports the behavioral addiction model, impaired selection attention and lack of evidence for compulsivity in excessive social media users. Further research on neurocognitive function in excessive social media users is required in order to determine whether it should be considered a behavioral addiction or an impulse control disorder.
Context-dependent interaction between oxytocin gene polymorphisms and alcohol dependence in modulating negative emotions during acute alcohol withdrawal in adult males
ObjectiveThe importance of multiple gene-environment interaction (G × E) has been highlighted in understanding the etiology of negative emotions. This study examines the impact of oxytocin (OXT) polymorphisms (rs2740210, rs6133010, and rs2740209) in combination with alcohol dependence on anxiety and depression symptoms during acute alcohol withdrawal under different social and environmental contexts.MethodA total of 414 Chinese Han male adults undergoing acute alcohol withdrawal were recruited. Participants provided blood samples for genotyping, self-reported measures of depression and anxiety, assessments of alcohol dependence severity, and demographic information regarding social and environmental contexts.ResultsResults revealed a positive correlation between severity of alcohol dependence and symptoms of depression and anxiety, while oxytocin polymorphism did not have a direct effect on depressive and anxiety symptoms. A significant interaction between OXT polymorphism (rs2740210 and rs2740209) and alcohol dependence in relation to anxiety symptoms solely among adults living with family and/or those who were married was observed. Further analyses indicate that the GG and CC genotypes are risk genotypes, while the T allele (rs2740210) and G allele (rs2740209) are non-risk alleles in the interaction between OXT genotypes (rs2740210, rs2740209) and alcohol dependence on anxiety among the aforementioned participants.ConclusionsThese findings provide evidence for distinct G × E interaction effects on anxiety and depression symptoms during acute alcohol withdrawal, supporting the weak diathesis-stress model. Furthermore, the study highlights the importance of considering environmental factors when investigating the role of oxytocin as a biological substrate underlying social bonding and the regulation of negative emotions.
Why isn’t alcohol seen as a public health emergency?
Alcohol kills more Americans than any other drug by a wide margin. But discussions about substance use epidemics in the U.S. are usually centered around drugs like fentanyl or meth. In fact, most people in the U.S. do not see alcohol is as much of a public health problem at all.
My STAT colleagues, reporters Isabella Cueto and Lev Facher, spent months examining this contradiction — how can such a dangerous substance be treated with such ambivalence? Earlier this week they launched a new STAT series “The Deadliest Drug” that aims to answer that question.
Establishing AI and data sovereignty in the age of autonomous systems
When generative AI first moved from research labs into real-world business applications, enterprises made a tacit bargain: “Capability now, control later.” Feed your proprietary data into third-party AI models, and you will get powerful results. But your data passes through systems you do not own, under governance you do not set. The protections you rely on are only as durable as the provider’s next policy update.
Now, with generative AI established in everyday business operations and sophisticated new agentic AI systems advancing every day, companies are reevaluating the terms of that deal.
“Data is really a new currency; it’s the IP for many companies,” says Kevin Dallas, CEO of EDB, echoing a recurrent anxiety from customers. “The big concern is, if you’re deploying an AI-infused application with a cloud-based large language model, are you losing your IP? Are you losing your competitive position?”
That question is now fueling a movement toward reclaiming both the data and AI systems that have rapidly become part of core business infrastructure. AI and data sovereignty, which refers to breaking dependence on centralized providers and establishing genuine control over models and data estates, it is an urgent priority for many companies, says Dallas, citing internal EDB data: “70% of global executives believe they need a sovereign data and AI platform to be successful.”
The idea of AI sovereignty is becoming a global policy conversation. NVIDIA CEO Jensen Huang recently spoke about the need for such a shift at the World Economic Forum’s annual meeting at Davos in January 2026: “I really believe that every country should get involved to build AI infrastructure, build your own AI, take advantage of your fundamental natural resource—which is your language and culture—develop your AI, continue to refine it, and have your national intelligence be part of your ecosystem.”
This report explores how enterprises are pursuing sovereignty over their models and data estates in an era of rapid AI adoption. Drawing on a survey conducted by EDB of more than 2,050 senior executives and a series of interviews with industry experts, the research confirms that the sovereignty movement on the enterprise level is already well underway.
This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.
STAT+: Three years of declining overdose deaths begets cautious optimism and some concerns
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The Trump admin’s wish list for its next FDA leader
The Trump administration is working to identify the next FDA commissioner after Marty Makary resigned on Tuesday. The dream candidate is someone who can rebuild trust with agency staff, focus on the agency’s food policy, and continue to drive drug-approval reforms, STAT’s Daniel Payne and Lizzy Lawrence report.