Opioid use disorder is a chronic, relapsing condition that continues to rise worldwide. Naloxone (Narcan®), an opioid antagonist, reverses overdose but triggers strong negative affect. The neuronal circuits underlying these aversive effects remain unclear. We previously identified mu opioid receptor–expressing habenular neurons (Hb-MOR) as key encoders of negative emotional states and hypothesized that they also mediate naloxone aversion.
Major Depressive Disorder from a Brain-Body Perspective: Reproducible Central Cardiac Interoception Deficits and Peripheral Autonomic Dysfunctions Dissociate
Brain-heart interaction (BHI) offers a systems-level framework for understanding major depressive disorder (MDD), yet reproducible cross-system markers remain unclear. We aimed to identify reproducible BHI impairments in MDD and clarify their physiological and clinical correlates.
Focused ultrasound ablation for psychiatric disorders
Modern circuit-based neurosurgical interventions address a critical unmet need for patients with treatment-resistant psychiatric illness. Magnetic resonance–guided high-intensity focused ultrasound (HIFU) enables incisionless, millimeter-precision thermoablation via staged sonications with real-time monitoring, reshaping the risk–benefit profile of traditional neurosurgical interventions for psychiatric disorders.Here, we review the clinical evidence for HIFU ablation and contrast it with alternative platforms, including radiofrequency ablation, radiosurgery, laser interstitial thermal therapy, and deep brain stimulation.
An obesity drug deep-dive, and peptides move mainstream
Can any of the new obesity medications in development stand out from the pack? Which company just broke records with its IPO? And will the Food and Drug Administration allow greater access to experimental peptides?
We discuss all that and more on this week’s episode of “The Readout LOUD,” STAT’s biotech podcast.
Digital Health Monitoring and Intervention Suite for Stress in Frontline Nurses: Prospective Cohort Trial
Background: Stress among health care workers (HCWs) contributes to burnout, workforce attrition, and adverse patient outcomes. Although virtual reality (VR), psychoeducation, ecological momentary assessments (EMAs), and wearables have independently shown promise in stress research, no integrated digital suite has combined controlled stress induction, intervention delivery, and longitudinal real-world monitoring in HCWs. Objective: This study aimed to evaluate the feasibility, engagement, and preliminary effectiveness of a multimodal Digital Health Monitoring and Intervention suite for Stress framework integrating VR simulation, psychoeducation, EMAs, and wearable biometrics. We examined (1) the impact of VR simulation and psychoeducation on stress outcomes and (2) associations between physiological and self-reported mental health outcomes. Methods: Ninety-nine nurses (mean age 33.7, SD 8.9 yr, 87% female) were enrolled in 2023. We conducted a single-arm prospective cohort study (NCT05923398). Using convenience sampling, participants were recruited from social media advertisements, flyers, and email notices distributed through professional listservs. Participants completed ≥2-week baseline monitoring, a single VR session (2 runs separated by a brief psychoeducation intervention), and 12-week follow-up. In-VR stress was assessed using the Subjective Units of Distress Scale (SUDS) and 4-item Moral Injury Outcome Scale (MIOS-4), with synchronous heart rate variability. Longitudinal outcomes included weekly and biweekly EMAs alongside 70 wearable-derived features. Paired tests, aligned rank transform ANOVA, and Pearson correlations informed study objectives, with P values adjusted for multiple comparisons. Qualitative content analysis classified emotional responses during and after VR. Results: VR significantly increased subjective stress across checkpoints in both runs, with attenuation in Run B relative to Run A (all <.001). No significant heart rate variability differences were observed between runs (.15). During VR, 92% (91/99) of participants felt stressed, 36% (36/99) reported anxiety or nervousness, and 51% (50/99)‐78% (77/99) endorsed anger, guilt, shame, and/or betrayal. Most (59/99, 60%) HCWs returned to an emotional baseline post-VR, although 12% (12/99) reported lingering distress. Immediate reliable improvements in anger, guilt, shame, and/or betrayal occurred for 50% (50/99)‐75% (74/99) of participants post intervention. Anxiety (mean −0.53, SD 2.34; .03) and stress (mean −3.05, SD 11.35; .01) decreased 2 weeks post intervention, but were not sustained at 12 weeks. Increased sleep restlessness was the only wearable feature showing significant changes (mean 2.46%, SD 5.43; <.001). In-VR stress correlated with 12-week real-world stress (SUDS: =0.57‐0.58; MIOS-4: =0.58‐0.61; all .01). Data completion exceeded 90%, with 71% achieving full compliance. Conclusions: This study moves beyond single-tool interventions to demonstrate the feasibility and preliminary effectiveness of an integrated, multimodal stress platform within a single coordinated framework. This trial demonstrates high engagement, short-term symptom responsiveness, ecological validity, and emotional safety. The framework provides a scalable model for proactive stress identification, skills training, and implementation in high-risk occupational settings. Randomized controlled trials are needed to establish sustained efficacy and optimize deployment for real-world implementation. Trial Registration: ClinicalTrials.gov NCT05923398; https://clinicaltrials.gov/study/NCT05923398 International Registered Report Identifier (IRRID): RR2-10.2196/54180
RFK Jr. claims his calendar is publicly available. We’ve been trying to get it for a year
WASHINGTON — Health secretary Robert F. Kennedy Jr. on Wednesday pointed to his “publicly available calendar” as an example of his commitment to transparency and to beat back unfavorable reporting.
But no such calendar, detailing who Kennedy meets with or how he spends his time, has been released by the administration. STAT has been asking the Department of Health and Human Services for Kennedy’s calendar for more than a year, via Freedom of Information Act requests and emails to the press office.
Drinking during pregnancy rose after 2020, new CDC data suggest
New data released Thursday suggest the prevalence of drinking during pregnancy increased in recent years.
National survey data published in a Centers for Disease Control and Prevention report show about 15% of adult pregnant women reported current drinking (use in the prior 30 days) between 2021 and 2024. About 13.5% of women reported the same between 2018 and 2020.
STAT+: AMA and lawmakers push back on AI care denials
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Pioneering Innovation in Transplant Diagnostics
Sara Barrington is CEO of Verici Dx, a precision diagnostics company redefining how transplant clinicians understand and predict graft health. By combining multi-omic analysis with proprietary artificial intelligence (AI) models, Verici Dx delivers predictive, actionable intelligence that helps clinicians optimize therapy, inform biopsy decisions, and stratify risk for complex transplant patients.
In this edition of Asked & Answered, Barrington speaks with Inside Precision Medicine Editor in Chief Damian Doherty about pioneering innovation in transplant diagnostics to better reflect biological and patient complexity, and ultimately, improve health outcomes.
Q: Tell me about Verici Dx, its founding, mission, and products.
Sara Barrington: Verici Dx was founded with a very clear purpose: to fundamentally improve how transplant clinicians are informed and manage graft health. Transplant medicine requires high-stakes, time-sensitive decision-making to promote longevity of the graft, minimize the risk of complications, and improve the patient’s quality of life.
Kidney transplantation has long struggled with one fundamental challenge: accurately identifying rejection early and distinguishing it from other causes of injury and graft dysfunction. Clinicians often rely on conventional blood markers such as serum creatinine or, more recently, donor-derived cell-free DNA. While these tools are useful for signaling that “something is wrong,” they are injury markers and lack a level of precision important in rejection biology.
Creatinine levels, for example, increase only after functional damage has already occurred and cannot differentiate rejection from non-immune causes of injury such as ischemic reperfusion injury, drug toxicity, or viral infections like BK virus–associated nephropathy. Biomarkers can generate false positives, triggering biopsies or treatment escalation that may not be necessary and can expose patients to avoidable risk.
This lack of specificity has made rejection difficult to manage proactively. By the time rejection is clearly identified, tissue injury may already be established. At the same time, clinicians are understandably cautious about intensifying immunosuppression without clear evidence, given the associated risks of infection, malignancy, and toxicity.
Our mission is to close this information gap by delivering precision diagnostics that reflect the true complexity of transplant biology and translate that complexity into insights clinicians can proactively and confidently apply to patient care.
We operate at the intersection of multi-omic science, advanced analytics, and clinical reality. We know that transplant rejection and graft injury are not single-signal events, but are multifactorial, dynamic biological processes. We design our diagnostics to capture that complex biology in a way that mirrors how clinicians think about their patients, rather than forcing clinical decision-making to fit the limitations of older technologies.
Our lead product, Tutivia
, is a blood-based test that assesses the immune and broader, relevant biological status of kidney transplant patients to identify the risk of all forms of acute rejection, including T cell (TCMR) and antibody-mediated rejection (ABMR). Tutivia combines transcriptomics with proprietary AI models to address this precise unmet need: biologically accurate insight into what is actually happening within the graft.
The test delivers a risk score that enables more precise immunosuppression management by distinguishing rejection from other causes of graft injury, such as BK virus–associated nephropathy and ischemia-reperfusion injury, which can confound conventional blood tests like serum creatinine and donor-derived cell-free DNA.
By focusing on the immune and other pathways associated with rejection, Tutivia moves beyond damage markers and toward a direct assessment of rejection biology itself. That shift, from injury detection to biological interpretation, is what makes the test such a valuable tool for transplant clinicians.
Thermo Fisher Scientific recently launched its One Lambda Pre-Transplant Risk Assessment (PTRA) assay, using pre-transplant prognostic technology licensed from Verici Dx. The assay provides a risk score for early acute rejection based on a patient’s unique gene profile, helping clinicians better balance the risk of rejection against the potential side effects of over-immunosuppression. Using a 29-gene mRNA signature, the PTRA assay stratifies patients into high- and low-risk categories, with clinical validation showing high-risk patients are seven times more likely to experience early acute rejection.
Q: Tutivia is built on RNA sequencing. Why is precision transcriptomic analysis well-suited for identifying rejection biology?
Barrington: The need for reliable biomarkers is crucial for individualizing therapy that offers the potential to extend allograft survival.
Early research underpinning the science leading to the development of Tutivia was led by principal investigators at The Mount Sinai Hospital in New York, one of the world’s leading transplant research centers, combining decades of clinical expertise with rigorous science. The underlying science reflects the fact that rejection in kidney transplant patients is not driven by a single molecule or pathway, it results from coordinated immune and other biologic pathways across multiple cell types, signaling cascades, and regulatory mechanisms. Injury-driven biomarkers capture only a narrow slice of this biology and can be influenced by non-rejection factors, limiting their specificity and reliability.
Precision transcriptomic analysis, on the other hand, measures gene expression patterns across thousands of genes simultaneously. In developing specific tests, this analysis is the basis for gene selection using unsupervised deep learning mathematical modeling, allowing the most impactful and reproducible gene expression signals and interactions to be included in the final signature.
Tutivia uses a peripheral blood next-generation sequencing assay to evaluate a 17-gene mRNA signature in combination with a proprietary artificial intelligence algorithm to categorize kidney transplant patients as at low risk or high risk of acute rejection.
This provides a comprehensive view of immune activation, regulation, and injury responses within the transplanted organ, allowing the identification of signature changes that are truly characteristic of rejection biology.
In short, RNA sequencing lets us ask better biological questions: not just whether the kidney is injured, but whether immune-mediated rejection is driving that injury. That distinction is critical for precision medicine in transplantation.
Q: What does earlier and more precise identification of rejection biology mean for patient management and outcomes?
Barrington: Earlier identification of rejection biology can create an opportunity to intervene before irreversible damage occurs. When clinicians have confidence in what the biology is telling them, they can make timely, targeted decisions that may preserve graft function.
This precision also supports more individualized care. Rather than applying broad treatment strategies, clinicians can tailor immunosuppression based on biological risk, potentially reducing over-treatment and its associated complications.
For patients, this can translate into fewer unnecessary biopsies, fewer adverse events related to immunosuppression, and a greater likelihood of long-term graft survival. Ultimately, better information leads to better decisions, and better decisions lead to better outcomes.
Our vision is that precision diagnostics like Tutivia become a standard component of transplant management, providing earlier insight into rejection biology, supporting more informed clinical decisions, and helping clinicians intervene at the right time for the right patient.
Q: AI is central to your platform. How does Verici Dx apply AI differently from others in diagnostics?
Barrington: We apply AI with rigor and restraint. We use advanced machine learning and mathematical modeling to analyze highly complex biological data, but always within a disciplined scientific framework. Our models are developed using unsupervised approaches and validated extensively on inclusive patient populations. Once validated, they are locked and reproducible; they are not evolving over time. That distinction matters because clinicians are making life-altering decisions based on these results, and trust, consistency, and validation are essential.
Q: Validation and standards are recurring themes for Verici Dx. How was Tutivia validated?
Barrington: Tutivia was validated through a rigorous clinical study that included a broad and diverse transplant patient population, rather than narrowly curated cohorts. We deliberately chose a more difficult validation path because clinical reality is complex, and diagnostics must perform under those conditions. While this approach requires more time and effort, it ensures the test is reliable, reproducible, and clinically relevant across the full spectrum of patients that clinicians see every day.
Q: What’s in the future for the company?
Barrington: Verici Dx is focused on deepening the clinical adoption of Tutivia as well as expanding the studies demonstrating the utility of an earlier and more precise biomarker in improving patient outcomes. Long-term outcomes for transplant patients involve more biological pathways, and significant complexity is involved in managing care. We are focused on developing and validating tests using both transcriptomic and proteomic precision tools to assist clinicians and their patients in this journey.
Damian Doherty has been in media and publishing for over 30 years, beginning at News Corporation. Damian has managed, edited, and launched life science titles in drug discovery and precision medicine. He was features editor of Drug Discovery World and founded the Precision Medicine Leaders Summit and the Journal of Precision Medicine. He edited AIMed magazine before launching Photo51Media, a platform for illuminating untold, compelling stories in precision healthcare. Damian joined Mary Ann Liebert in 2021 to help steer the new rebrand and relaunch of Clinical OMICS to Inside Precision Medicine.
The post Pioneering Innovation in Transplant Diagnostics appeared first on Inside Precision Medicine.
Examining the Social and Mental Health Benefits of Virtual and In-Person Physical Activity Intervention Among Postsecondary Students: Quasi-Experimental Study
Background: Physical activity (PA) is a promising prevention approach for supporting mental health and enhancing social inclusion among postsecondary students. However, it is unclear whether similar outcomes are realized when PA programming is delivered in-person versus virtually. Objective: Using data from a multiphase research project, the purpose of the study was to examine the influence of on-campus PA programming (virtual and in-person delivery) on mental ill health symptoms (ie, anxiety and depression), social inclusion indices (ie, social connectedness, emotional ties, and social relationship quality), and well-being. Three objectives were addressed: (1) to assess pre-post change in symptoms, social inclusion indices, and well-being for virtual and in-person delivery; (2) to evaluate whether outcome change over time differed by delivery mode; and (3) to examine whether change in symptoms and social inclusion indices predicted change in well-being for both delivery modes. Methods: Physically inactive postsecondary students experiencing mental ill health participated in a 6-week structured and supervised PA program. Pre-post intervention data were collected across 3 phases, and the analytical samples included: 1. In-person delivery (n=87; 82%, 69/84 young adults; 86%, 74/86 women; 38%, 33/86 White; 20%, 17/86 Chinese; 86%, 75/87 with mental illness; 2. Virtual delivery (n=62; 69%, 42/61 young adults; 95%, 59/62 women; 34%, 21/62 White; 21%, 13/62 South Asian; 55%, 34/62 with mental illness), and 3. Data from students who received in-person or virtual delivery: (n=92; 67%, 61/91 young adults; 90%, 83/92 women; 32%, 29/92 White; 20%, 18/92 South Asian; 59%, 54/92 with mental illness). Data were analyzed using 2-tailed paired samples tests to address objective 1, a 2 (delivery mode) × 2 (time: pre-post) repeated-measures ANOVA to address objective 2, and hierarchical regression analyses to address objective 3. Results: Both virtual and in-person PA delivery were effective for symptom reduction and social inclusion improvements across all outcomes (<.001), with moderate-to-large effects. There was no significant time × delivery mode (=0.72, ²=0.04, =.60) interaction effect. Change in social inclusion indices explained unique variance in well-being, beyond covariates (gender, mental illness, and ethno-racial identity), and symptom reduction for virtual ( = 0.75, 008001) and in-person ( = 0.72, =0.16, <.001) PA delivery. Conclusions: Online distance learning is increasing across postsecondary settings worldwide, underscoring the need for accessible, technology-enabled mental health prevention interventions. The results provide support for the effectiveness of virtual and in-person PA programming for reducing symptoms of anxiety and depression, while also enhancing social inclusion indices and overall well-being. Social inclusion indices were also a key contributor to improved well-being, emphasizing the relevance of social factors in both virtual and in-person PA-based mental health prevention strategies for postsecondary students.
