BackgroundStressful life events are well-established risk factors for adolescent depression; however, the psychological mechanisms underlying this association remain insufficiently understood, particularly regarding which types of stress and which dimensions of security are most closely linked to depression. This study aimed to investigate whether security and its two sub-dimensions statistically mediated the association between stressful life events and depression among clinically diagnosed adolescents, while also examining the relative strength of indirect associations across specific stress types.MethodsA cross-sectional study was conducted with 284 adolescents (70.1% female; mean age = 15.82 ± 1.86 years) diagnosed with major depressive disorder according to the DSM-5 criteria at a tertiary psychiatric hospital in Western China. Participants completed the Adolescent Self-Rating Life Events Checklist (ASLEC), Self-Rating Depression Scale (SDS), and Security Questionnaire (SQ) questionnaires. Simple mediation, parallel mediation, and dimension-specific analyses were performed using the PROCESS macro (Model 4) with 5,000 bootstrap resamples, controlling for gender and parental marital status.Resultsstressful life events were significantly positively correlated with depression (r = 0.491, p < 0.001) and negatively correlated with security (r = −0.464, p < 0.001). Simple mediation analysis revealed that security demonstrated a significant indirect association through security (indirect effect = 0.176, 95% CI [0.126, 0.232]), accounting for 53.8% of the total association. Parallel mediation analysis further indicated a dual-pathway model: both Interpersonal Security (indirect effect = 0.083, 95% CI [0.037, 0.133]) and Certainty in Control (indirect effect = 0.093, 95% CI [0.043, 0.152]) functioned as significant statistical mediators of comparable magnitude, with no significant difference between them (Contrast = −0.010, 95% CI [−0.065, 0.042]). Furthermore, dimension-specific analyses revealed that Interpersonal Stress (standardized indirect effect = 0.266) and Academic Stress (standardized indirect effect = 0.231) showed the strongest indirect associations with depression through the security pathway. Exploratory subgroup analyses revealed a gender-crossed pattern: for male adolescents (n = 85), the indirect association was significant only through Interpersonal Security (effect = 0.116, 95% CI [0.048, 0.199]); for female adolescents (n = 199), it was significant only through Certainty in Control (effect = 0.136, 95% CI [0.067, 0.212]).ConclusionSecurity functions as a significant statistical mediator in the association between stressful life events and adolescent depression. The findings are consistent with a “dual-pathway” model wherein stress is concurrently associated with lower levels of both relational security (Interpersonal Security) and personal agency (Certainty in Control). Exploratory analyses suggest that the relative importance of these two pathways may differ by gender. If confirmed by future longitudinal research, clinical interventions may benefit from an integrated approach that addresses both dimensions, with particular attention to interpersonal conflicts and academic pressure as the stressors most strongly associated with depression through security pathways.
Coming soon: 10 Things That Matter in AI Right Now
Each year we compile our 10 Breakthrough Technologies list, featuring our educated predictions for which technologies will have the biggest impact on how we live and work.
This year, however, we had a dilemma. While our final picks encompass all our core coverage areas (energy, AI, and biotech, plus a few more), our 2026 list was harder to wrangle than normal. Why? We had so many worthy AI candidates we couldn’t fit them all in! (The ones that made it were AI companions, mechanistic interpretability, generative coding, and hyperscale data centers.) Many great ideas fell by the wayside to keep the list as wide-ranging as possible.
Well, that got us thinking: What if we made an entirely new list that was all about AI? We got excited about that idea—and before we knew it we had the beginnings of what we’re calling 10 Things That Matter in AI Right Now. It’s an entirely new annual list that we’re proud to be publishing for the first time on April 21, 2026. We’ll unveil it on stage for attendees at our signature AI conference, EmTech AI, held on MIT’s campus (it’s not too late to get tickets), and then publish the list online later that day.
The process for coming up with the list was similar to the way we pick our 10 Breakthrough Technologies. We petitioned our AI team of reporters and editors to propose ideas, put them all in a document, and engaged in some robust discussion. Eventually, we voted for our favorites and whittled the long list down to a final 10.
But there’s a slight difference between this list and our 10 Breakthrough Technologies. AI is already such a big part of our lives that we didn’t want to restrict ourselves to nominating only technologies. Instead, we wanted to put together a definitive annual list that highlights what we believe are the biggest ideas, topics, and research directions in AI right now. So yes, it will include cutting-edge AI technologies, but it will also feature other trends and developments in AI that we want to bring to our subscribers’ attention.
Think of it as a sneak peek inside the collective brain of our crack AI reporting team: These are the things that our reporters will be watching this year. We intend to follow the items on this list really closely, and you will see it reflected in the news and feature stories we publish in 2026.
For us, 10 Things That Matter in AI Right Now is a guide to how we view the current AI landscape. It will be a source of discussion, debate, and maybe some arguments! We are so excited to share it with you on April 21. If you want to be among the first to see it—join us at EmTech AI or become a subscriber to livestream the announcement.
Acute aerobic exercise modulates resting-state EEG microstate dynamics in individuals with internet addiction
Internet addiction (IA) is associated with impaired cognitive control and altered large-scale brain dynamics. Electroencephalogram (EEG) microstates provide a sensitive index of rapid neural network organization; however, whether acute aerobic exercise can modulate abnormal microstate dynamics in individuals with IA remains unclear. Forty young adults [IA: n = 20; healthy controls (HC): n = 20] completed resting-state EEG recordings before and after a single 30-min bout of moderate-intensity aerobic cycling. Microstate duration, occurrence, contribution, and transition probabilities were analyzed using mixed-design repeated-measures with time (pre/post) and Microstate (A–D) as within-subject factors and group (IA/HC) as a between-subject factor. Spearman correlations examined associations between exercise-induced microstate changes and IA severity. For microstate duration, the IA group exhibited longer duration of Microstate A than HC group at baseline (t = 2.47, p = 0.018). IA group showed reduced Microstate D occurrence at baseline compared with HC (t = 4.23, p < 0.001), followed by a significant post-exercise increase (t = −4.23, p = 0.001), eliminating group differences. Microstate contribution showed a significant Time × Group interaction [F(1, 38) = 4.68, p = 0.037, η2 = 0.110], with Microstate D contribution increasing selectively in the IA group (t = −3.71, p = 0.001). Changes in Microstate D occurrence were negatively correlated with IA severity (ρ = −0.55, p = 0.012). A single session of aerobic exercise rapidly normalizes aberrant microstate dynamics in IA, particularly within Microstate D, highlighting exercise as an effective acute neuromodulatory intervention.
ASYM: multimodal depression recognition via mamba-enhanced attentive feature fusion
IntroductionDepression is a prevalent mental disorder with a severe global impact. Traditional interview-based assessments are limited by subjectivity, lengthy procedures, and unequal access to care. Although advances in AI have facilitated multimodal models for depression detection—using audiovisual data as an accessible alternative to biosignals—current approaches remain challenged by inefficient long-term temporal modeling and superficial multimodal fusion. Moreover, biosignal-based methods are constrained by high costs and narrow applicability. These challenges underscore the urgent need for optimized multimodal solutions.MethodsThis paper proposes ASYM (Attentive Synergy Mamba), a novel multimodal architecture for depression recognition, comprising three core modules: a Cross-Modal Interactive Mamba, a Multi-Scale Gated Parallel Fusion, and a Multimodal Enhanced Mamba. First, features from each modality are interactively enhanced using convolutional neural network and Bi-Mamba blocks. Cross-modal complementary information is then extracted via a cross-attention mechanism. A dual-path fusion module subsequently augments multi-scale representations and integrates cross-modal features through dynamic weighting. Finally, the feature representations are refined by a series of Bi-Mamba blocks.ResultsEvaluations on the D-Vlog and LMVD datasets using accuracy, precision, recall, and F1-score showed that ASYM achieved an accuracy of 70.91% and an F1-score of 77.13% on D-Vlog, and 74.68% accuracy with a 74.90% F1-score on LMVD. The macro-average performance across both datasets surpassed all compared mainstream methods. Ablation studies confirmed the necessity of each component, as removing any module significantly degraded performance, underscoring the efficacy and critical contribution of the proposed architecture.DiscussionWhile multimodal depression detection has improved upon single-modality approaches, issues such as computational inefficiency in long-sequence processing and inadequate fusion strategies persist. Our model addresses these limitations through multimodal interaction and multi-scale feature fusion. Future work will focus on clinical validation across diverse populations to bridge computational psychiatry and clinical practice.
Patient safety incidents in mental health residential services: a multicenter, crosssectional, survey-based study
IntroductionWhile patient safety in general hospitals is well-researched, residential mental health services have received less attention. Psychiatric patients and staff working in such facilities face unique and complex risks. This study aims to explore and describe the frequency and characteristics of patient safety incidents (PSIs) experienced by professionals working in a cohort of Italian mental health residential services.MethodsA multicenter, cross-sectional, questionnaire-based observational study was conducted involving workers from 68 psychiatric mental health services from seven different Italian provinces. A total of 159 respondents, including both healthcare and non-healthcare professionals, took part in the study. Participants reported incidents personally experienced (FHE) or reported by colleagues (CRE) over the previous 12 months, using a taxonomy adapted from the World Health Organization’s Conceptual Framework for the International Classification for Patient Safety. Data was analyzed using descriptive statistics and zero-inflated models to identify associations between respondent characteristics and reporting behaviors.ResultsA total of 4,432 FHE and 4,807 CRE were reported. The behavior-related events were the most frequently reported, followed by incidents related to organizational or infrastructure issues, and medication errors. Secondary analyses suggested that facilities with more than ten employees had significantly higher rates of both FHE and CRE. Furthermore, residential facilities showed a higher incidence rate of CRE compared to non-residential ones, and non-healthcare workers reported witnessing fewer incidents to colleagues (28%) compared to healthcare workers. Significant variability was also observed across different provinces.ConclusionResidential mental health services experience a high incidence of PSIs, suggesting a risk profile distinct from general hospital settings. The predominance of behavior-related incidents corroborates the hypothesis that primary risks are mainly driven by relational dynamics. The findings highlight that both healthcare and non-healthcare staff are exposed to significant risks, suggesting the need of inclusive and comprehensive safety interventions. Consequently, specific training programs focused on relational risk management, de-escalation, and empathic communication are essential for all workers employed in these settings.
Sovereignty: A strategic imperative the NHS cannot ignore
Digital sovereignty receives only a fraction of the attention given to AI. That needs to change, argue digital health leaders
Epigenetics at Birth Links Microbiome to Neurodevelopment, Potentially ASD and ADHD
The results of a study headed by researchers at Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, indicate that the gut microbiome and epigenetics are intertwined, and that both contribute to neurodevelopment.
The researchers showed that epigenetic changes present at birth can impact how an infant’s gut microbiome develops during their first year. They also identified specific epigenetic changes and gut microbes that were associated with signs of autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) when the children were three years old.
“Certain bacteria seem to offer protection, which is exciting because it suggests there could be ways to support a child’s development through diet or probiotics in the future,” said research lead and gastroenterologist Francis Ka Leung Chan, MD. Chan is co-senior author of the team’s published paper in Cell Press Blue, titled “Epigenome-microbiome interplay in early life associates with infants’ neurodevelopmental outcomes,” in which they stated, “We showed that epigenetic alterations at birth were associated with early-life microbiome development and that they determine the risks of neurodevelopmental consequences in children.”
The first years of life are critical for brain development and immune system maturation. Though previous studies have shown that both early epigenetic changes and gut microbiome development can impact health in later life, little is known about how these two systems interact. “Recent data suggest that epigenetic programming of gene expression profiles is sensitive to the early-life environment and can impact health outcomes in children,” the authors wrote. “One environmental cue known to trigger host epigenetic modifications is the genes of bacteria, fungi, and viruses inside the human body, collectively known as the microbiome.”
Co-senior author and public health researcher Hein Min Tun, PhD, of The Chinese University of Hong Kong, commented, “We wanted to see how the epigenome and microbiome interact in early life and if their interaction could influence a child’s risk of developing neurodevelopmental conditions like ASD and ADHD.” The authors added, “New understanding of host-microbe-epigenome interactions and mechanisms of epigenetic changes in early life can be leveraged for the prevention, early detection, and novel interventions of common childhood diseases.”
For their study the researchers characterized DNA methylation patterns from the umbilical cord blood of 571 infants. They paired this information with gut microbiome data collected from 969 infants at two, six, and 12 months of age, and from their parents during the third trimester of pregnancy. When the children reached 36 months of age, the researchers used a behavioral questionnaire to assess their neurodevelopment and investigate links between the microbiome, epigenome, and early signs of ASD and ADHD.
“This, to our knowledge, represents the first longitudinal study with multiple sample types to depict the intimate interplay between perinatal exposures, epigenetic hallmarks, and gut microbiome development and neurodevelopmental outcomes within the first three years of life,” the authors stated.
They found that an infant’s epigenome at birth was associated with birth mode, length of gestation, having older siblings, and maternal allergies, but it was not affected by their parents’ gut microbiomes. Microbiome development, on the other hand, was associated with birth mode, antibiotics, having older siblings, and breastfeeding. Infants who were born by Caesarean section (CS) showed different patterns of DNA methylation for several genes involved in immune responses and brain development. “Some of the changes in methylations of immune- and nervous-system-related genes, associated with CS delivery, are linked to neurodevelopmental outcomes,” they noted.
Their reported findings, the team suggested, “… resonate with studies linking CS to increased risks of immune-mediated and neurodevelopmental disorders, providing mechanistic plausibility through epigenomic and microbial dysbiosis.” The team also showed that an infant’s epigenome at birth impacted how their microbiome developed during their first year. Specifically, infants developed less diverse gut microbiomes at 12 months of age when they showed higher rates of DNA methylation in immune genes involved in recognizing pathogens. “We found that methylation rates in the major histocompatibility complex (MHC) region of infants at birth were linked to differences in the diversity of the infant gut microbiome at 12 months,” they commented.
The behavioral survey revealed that signs of ASD and ADHD in three-year-olds were associated with specific epigenetic patterns and the presence of certain gut microbes. “Importantly, we reported that epigenetic modifications were associated with an increased susceptibility to neurodevelopmental conditions in children, and these effects were in part mediated by microbial colonization.”
However, other microbial species seemed to mitigate these effects: infants with epigenetic patterns associated with ASD or ADHD were less likely to show signs of the disorders if they acquired Lachnospira pectinoschiza and Parabacteroides distasonis, respectively, during their first year. “We discovered a kind of conversation happening: a baby’s epigenetic setting at birth can influence their risk for neurodevelopmental disorders, but the presence of certain ‘good’ bacteria in their gut can step in and modify the risk,” Tun reported. “The foundations for brain health are laid very early, even before birth. However, we don’t want people to think this means a child’s developmental path is fixed at birth. These are complex conditions with many causes, and we’ve only uncovered a small piece of a very large puzzle.”
The researchers are continuing to follow the children who participated in the study to see how these early-life factors relate to their health as they grow. They note that laboratory experiments are needed to confirm the associations between gut microbes and neurodevelopment. In their discussion, the team wrote, “In conclusion, our findings revealed dual alterations to the neonatal epigenome and gut microbiome by perinatal factors and highlight the role of the ‘holo-epigenome’—the integrated host epigenome and microbiome—as a key mediator of neuro-immune outcomes. Interventions targeting microbial restoration or epigenetic modulation during critical developmental windows may mitigate risks of neurodevelopmental disorders.”
First author and gastroenterologist Siew Chien Ng, MD, PhD, added, “The ultimate goal is to develop safe, non-intrusive early interventions such as specific probiotics or live biotherapeutics, that could help nurture a healthy gut microbiome and potentially reduce the risk of neurodevelopmental challenges.”
The post Epigenetics at Birth Links Microbiome to Neurodevelopment, Potentially ASD and ADHD appeared first on GEN – Genetic Engineering and Biotechnology News.
A novel phase-difference transcranial alternating current stimulation system enables precise dual-site neuromodulation
Precise modulation of large-scale brain networks requires neuromodulation technologies capable of delivering frequency-locked stimulation with accurate and stable inter-regional phase control. However, conventional transcranial alternating current stimulation (tACS) systems generally lack robust dual-channel phase regulation and are rarely validated under realistic biological impedance conditions. Here, we present a novel phase-difference tACS system (PD-stim) designed to deliver programmable, high-precision phase offsets between stimulation targets. We performed a comprehensive engineering and in vivo validation of PD-stim, assessing biological impedance stability, waveform fidelity, amplitude stability, and phase-delivery accuracy. Impedance measurements obtained from the medial prefrontal cortex and hippocampus of rats demonstrated stable frequency-dependent profiles during stimulation. Benchmark comparisons against a clinically approved tACS device revealed comparable waveform fidelity and amplitude stability under both a standardised resistive load and in vivo recording conditions. Using simultaneous dual-channel oscilloscope recordings, PD-stim consistently generated stable sinusoidal waveforms with high phase-delivery accuracy across theta (8 Hz), beta (20 Hz), and gamma (40 Hz) frequency bands, under both biological and resistive conditions. Together, these results establish PD-stim as a precise, stable, and biologically robust dual-site neuromodulation platform that overcomes key technical limitations of existing tACS systems. This work provides a rigorously validated engineering framework for future mechanistic investigations of phase-specific modulation in distributed brain networks, while not addressing functional or therapeutic outcomes.
The efficacy and safety of transcranial direct current stimulation in patients with ADHD: a systematic review and meta-analysis
ObjectiveThis meta-analysis evaluated the efficacy and safety of transcranial direct current stimulation (tDCS) for treating Attention-Deficit/Hyperactivity Disorder (ADHD).MethodsFollowing PRISMA guidelines, we analyzed 28 randomized controlled trials (RCTs) involving 1,864 participants. Outcomes encompassed core ADHD symptoms, hot and cold executive functions (EFs)—including inhibitory control, working memory, and cognitive flexibility—as well as safety profiles based on adverse events. A multilevel meta-analysis was performed using a random-effects model. Subgroup analyses and meta-regressions were conducted to explore potential moderating factors.ResultsCompared to sham stimulation, tDCS did not significantly improve core ADHD symptoms (standardized mean difference (SMD) = –0.29, 95% CI [–0.59, 0.01], p= 0.05). Similarly, no significant overall effects were observed for cold EFs: inhibitory control (Hedges’ g(g)= –0.11, 95% CI [–0.26, 0.05], p=0.19), working memory (g= 0.13, 95% CI [–0.06, 0.32], p= 0.26), or cognitive flexibility (SMD = –0.42, 95% CI [–1.13, 0.29], p= 0.24). The effect on hot EFs was also non-significant (g = 0.27, 95% CI [–0.14, 0.70], p = 0.19). Exploratory analyses indicated that anode placement at Fp2 was associated with improvement in both inhibitory control (g= –0.52, 95% CI [–0.93, –0.11], p=0.01) and working memory (g = 0.72, 95% CI [0.22, 1.22], p = 0.004), although the overall test for interaction was not significant for inhibitory control (p= 0.19). The most common adverse reactions were mild and transient local skin symptoms, such as itching and redness (RR = 1.42, p=0.04).ConclusiontDCS was well-tolerated but did not demonstrate significant overall efficacy for core ADHD symptoms or executive functions. Anodal stimulation at Fp2 showed potential selective benefits warranting further investigation. tDCS is not currently recommended as a standalone treatment for ADHD. Future research should optimize stimulation protocols and explore combined interventions with behavioral or cognitive therapies.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO, identifier CRD42024612055.
AI Finds Unreported Side Effects of GLP-1 Drugs in Reddit Posts
A study of more than 400,000 posts in the social media platform Reddit has identified previously unreported side effects from the increasingly popular GLP-1 weight loss and diabetes drugs. Users reported symptoms affecting menstrual cycles and body temperature, which have not yet been described in clinical trials or included in drug labels.
Published today in Nature Health, the study covers over five years of public online posts from nearly 70,000 Reddit users discussing their personal experience taking the GLP-1 drugs semaglutide and tirzepatide.
“Some of the side effects we found, like nausea, are well known, and that shows that the method is picking up a real signal,” says Sharath Chandra Guntuku, PhD, research associate professor in computer and information science at Penn Engineering and the study’s senior author. “The underreported symptoms are leads that came from patients themselves, unprompted, and clinicians could potentially pay attention to them.”
Although the study is not representative of the broader population—Reddit users are generally younger, more likely male and based in the U.S.—the symptoms reported collectively match known side effects of semaglutide and tirzepatide. About 44% of users described at least one known side effect, most commonly symptoms of gastrointestinal distress.
“Clinical trials generally identify the most dangerous side effects of drugs, but they can fail to find what symptoms patients are most concerned about,” says Lyle H. Ungar, PhD, professor in computer and information science at Penn Engineering. “Online patient communities work a lot like a neighborhood grapevine. People who are living with these medications are swapping notes with each other in real time, sharing experiences that rarely make it into a doctor’s office visit or an official report. Even though social media is not necessarily representative, a large collection of posts may reflect additional concerns.”
The study uncovered a series of side effects that were previously unreported for these drugs. This included discussions of menstrual cycle changes, such as intermenstrual bleeding, heavy bleeding, and irregular cycles. Other users reported chills, hot flashes, fever, and other temperature-related symptoms. In addition, fatigue symptoms ranked as the second most common complaint in these online posts despite rarely being reported in clinical trials.
“We can’t say that GLP-1s are actually causing these symptoms,” says Neil K. R. Sehgal, doctoral student at the University of Pennsylvania and the study’s lead author. “But nearly 4% of the Reddit users in our sample reported menstrual irregularities, which would be even higher in a female-only sample. We think that’s a signal worth investigating.”
While efforts to scour the internet for self-reported drug side effects have been ongoing for more than a decade, screening through social media posts at scale remained challenging until the arrival of large language models such as ChatGPT or Gemini. In particular, these tools can prove instrumental in mapping the language users use to describe their symptoms to clinical terminology defined in the Medical Dictionary for Regulatory Activities (MedDRA), used to officially report symptoms in clinical trials.
“Large language models have made it possible to do this kind of analysis much faster with a level of standardization that could be difficult to achieve before,” says Sehgal.
The researchers hope these findings will encourage researchers and drug developers to investigate the side effects discussed by users online. In future work, the team plans to expand beyond Reddit and English-language discussions to confirm whether the same symptoms appear across different social media platforms and populations.
While this approach is not intended as a replacement for clinical trials, screening social media posts for clues on unreported side effects can make a significant difference in terms of speed. This can be especially relevant for drugs like semaglutide and tirzepatide, originally diabetes drugs that quickly became mainstream when the FDA granted them approval as weight loss drugs.
“Clinical trials are the gold standard, but by design, they are slow,” says Guntuku. “The whole point of this kind of approach is that it can move quickly, and that’s exactly when it’s most valuable.”
The post AI Finds Unreported Side Effects of GLP-1 Drugs in Reddit Posts appeared first on Inside Precision Medicine.