A former tobacco industry executive has been appointed to senior leadership at the Centers for Disease Control and Prevention, alarming public health advocates and critics of industry influence on government.
Stephen Sayle, named in March as the CDC’s deputy director for legislative affairs, previously worked at Fontem Ventures, a subsidiary of the British multinational tobacco corporation Imperial Brands. Between 2017 and 2018, he was U.S. vice president of corporate affairs at Fontem, which is focused on non-combustible tobacco products like the e-cigarette brand blu and the oral nicotine pouch brand Zone.
Background: Telemedicine has become central to digital health strategies, yet the regulatory environment that shapes ethical safeguards and equitable access remains uneven and incompletely assessed across countries. Legal and normative instruments matter because they define requirements for privacy, consent, accountability, professional readiness, and barrier reduction. Objective: This study aimed to map the current global landscape of normative instruments related to telemedicine and identify which ethical and social safeguards are explicitly addressed, with particular attention to equity. Methods: We conducted a document analysis guided by the READ (ready the materials, extract data, analyze data, and distill findings) framework. From February 2024 to February 2026, we conducted a structured web-based search across all World Health Organization (WHO) member states with no language restrictions, using official government sources, statutory professional regulators, and institutional publication channels. Retrieval combined internal site searches, direct navigation, external search engine queries, and targeted snowball sampling to identify currently in-force instruments. Two researchers independently extracted and coded data using a predefined codebook. We operationalized 10 binary items covering regulatory presence and scope (questions 1 and 2), safeguards for data protection (question 3), consent and disclosure (questions 4 and 5), prior in-person prerequisites (question 6), monitoring (question 7), training requirements (question 8), and equity (questions 9 and 10). We summarized frequencies overall and stratified by WHO region and World Bank income group and conducted a qualitative thematic analysis of included normative instruments. Results: Of the 194 WHO member states, 81 (41.8%) had at least one current normative instrument related to telemedicine in force. Among these, 72.8% (59/81) defined telemedicine or telehealth. Data protection provisions were most common (73/81, 90.1%), followed by mandatory informed consent (n=71, 87.7%) and monitoring mechanisms (n=65, 80.2%). Fewer countries required disclosure of telemedicine limitations (n=36, 44.4%) or mandated telemedicine-specific training (n=26, 32.1%). Prior in-person consultation requirements were uncommon (n=8, 9.9%). Equity-related safeguards were uneven: 51.9% (n=42) referenced justice, equity, or nondiscrimination, whereas 30.9% (n=25) included concrete barrier reduction provisions (eg, digital inclusion or accommodations for people with disabilities and minors). Conclusions: Telemedicine regulation is becoming more common, but both coverage and safeguarding content remain uneven. While privacy, consent, and monitoring are frequently addressed where regulation exists, disclosure, physician competency, and operational equity measures are less consistently specified. Strengthening telemedicine governance will require translating ethical commitments into enforceable standards that address digital determinants of access and protect groups at risk of exclusion.
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Formative evaluation is widely used in implementation science to anticipate barriers and facilitators prior to the deployment of health technologies, typically relying on stakeholders’ reported beliefs collected before real-world exposure. This approach has proven informative for many digital health tools; however, its application to immersive and embodied technologies such as extended reality (XR) warrants closer scrutiny. Most XR interventions in health care are delivered through head-mounted displays, which depend on spatial perception and sensorimotor engagement. Several implementation-relevant properties, including comfort, perceived intrusiveness, safety, and workflow disruption, often become apparent only through direct interaction. At the same time, large segments of the health care workforce remain XR-naive, such that preuse judgments are frequently shaped by anticipation rather than experience. Drawing on concepts from implementation science, grounded cognition, and human-computer interaction, this Viewpoint examines a plausible interpretive problem in XR adoption and argues that perception-based formative evaluation, when applied through frameworks developed for screen-based technologies, may misclassify barriers and facilitators. Rather than questioning formative evaluation as a methodological approach, we identify a boundary condition for its interpretability in experience-dependent technologies and propose a pragmatic refinement: incorporating brief experiential familiarization before eliciting stakeholder perceptions to strengthen early-stage assessment and improve alignment with real-world implementation decisions.
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Background: Mobile health (mHealth), and specifically smartphone apps, have grown exponentially in both functionality and accessibility and are becoming an important component of health care. Research exploring the use of mHealth for managing or treating chronic diseases, such as cancer, has shown promising effects. Yet, comparatively little work has examined how such technologies can enhance exercise interventions for young people with cancer. To optimize the effectiveness of mHealth in these contexts, it is essential to build a stronger evidence base on user experience. Objective: This study aimed to investigate how healthy children and young people engaged with an augmented reality (AR) app developed specifically for children and young people undergoing cancer treatment, and to identify design features that may support engagement and behavior change in the intended clinical population. Methods: School and university students, aged 8‐21 years, were eligible to participate in the study. Practical workshops allowed participants to engage with the AR exercise app before taking part in focus groups to explore user experiences. Data were analyzed using qualitative content analysis, which also involved a critical friend approach using 2 researchers (HM and KS). Suggested improvements were mapped against the motivational affordances’ taxonomy. Results: A total of 39 participants aged 8‐21 years took part in the focus group study. Participants found the demonstrations and varied exercises useful but expressed some concerns regarding data safety and functionality of the novel AR avatar. It was proposed that additional educational components, challenges, and rewards, as well as a customizable avatar, social support features, and audio instructions for a more inclusive design would be desirable and could enhance user experience. When mapped against the motivational affordances taxonomy, the suggested improvements aligned primarily with mechanisms of user education, challenges, feedback, cooperation, and comparison. Conclusions: This study provides an understanding of how apps that prescribe exercise can be optimized to enhance motivation and user experience. By assessing feedback and suggestions for improvements, the findings highlight key design features that may support engagement. While this initial work focused on healthy, age-matched participants, further evidence specifically in children and young people with a childhood cancer diagnosis is needed. International Registered Report Identifier (IRRID): RR2-10.1177/14604582241288784
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<strong>Background:</strong> Clinicians are the interface between artificial intelligence (AI) applications and patient care. To maximize benefits and minimize risks of AI, clinicians must be “AI-ready”—that is, willing and able to understand, evaluate, and appropriately use AI tools in practice. Prior literature suggests that clinicians lack fundamental competencies in the use of AI. These gaps could be especially problematic in primary care, given its broad reach into patient care. We surveyed primary care providers (PCPs) in the United States’ largest integrated health care system, relatively early in its widespread implementation of clinical AI for frontline use, in order to identify readiness gaps that may warrant particular attention as part of a comprehensive AI implementation strategy. <strong>Objective:</strong> The aim of this study was to characterize PCPs’ use, knowledge, attitudes, and training priorities related to AI in order to inform health system AI implementation efforts. <strong>Methods:</strong> We conducted a national cross-sectional survey of United States Veterans Health Administration (VA) PCPs in October 2025, assessing AI use, self-reported knowledge, attitudes, and training experience. Descriptive analyses summarized responses with exploratory bivariate comparisons across clinician subgroups. Conventional content analysis with inductive coding was used to characterize open-ended responses providing a definition of AI. <strong>Results:</strong> Among 170 respondents (170/989, 17.2% response rate), 66.5% (113/170) reported current AI use, most commonly generative AI and decision support tools. Overall attitudes toward AI were positive, with 70.6% (120/170) mostly enthusiastic or more enthusiastic than apprehensive. Confidence in understanding sources of AI bias (62/170, 36.5%) and ethical issues (81/170, 47.6%) was limited. When asked to define AI, very few respondents provided an accurate technical definition. Key concerns about use of AI included accountability, accuracy, and transparency. Though 88.2% (150/170) identified AI training as a priority, only 26.5% (45/170) had any training. Training experiences ranged widely in source, focus, and structure. <strong>Conclusions:</strong> PCPs are eager to harness AI’s practical advantages but lack foundational competencies to do so in ways that maximize benefit and minimize risk. Our findings highlight a need for targeted education that prioritizes critical appraisal, workflow integration, and risk mitigation, supported by governance that addresses clinicians’ concerns and validated measures to evaluate progress toward an AI-ready workforce. These steps can empower PCPs to leverage AI safely and effectively and strengthen the quality and safety of primary care delivery at scale.
Background: The original counterclockwise study carried out in the late 1970s provided an extreme example of “reminiscence therapy,” reporting improvements in older adults’ cognitive and physical functioning after they had lived for 5 days in a house set up as if decades earlier (the 1950s). We tested a virtual reality (VR) analog of this approach, enhanced by embodying participants in a virtual body that looked like themselves at the corresponding younger age. Objective: This study aimed to examine whether brief VR exposures combining (1) embodiment in a virtual body as one’s younger self and (2) immersion in an iconic past event improve age-related subjective and performance outcomes compared with a current-self VR control condition. Methods: We carried out a between-groups study with 23 healthy older adults (aged 65‐85 years; mean age 71.2, SD 4.03 years). Participants were randomly allocated to either a Young Self condition (n=11; mean 72.3, SD 4.17), where they were embodied in a virtual body that looked like themselves from the 1960s, or in a Current Self control condition (n=12; mean 70.1, SD 3.75), where participants were embodied in their current body. There were 5 sessions. In Session 1, participants completed a baseline assessment. There were then 2 VR exposures, approximately 1 week apart (Sessions 2‐3), and follow-ups at 1 week (Session 4) and approximately 2 weeks (Session 5) after the final VR exposure. Outcomes included subjective age, awareness of age-related change, World Health Organization–Five Well-Being Index, Trail Making Test performance, and physical functioning (eg, grip strength). Results: A hierarchical Bayesian analysis revealed that 1 week after the final VR exposure, those in the Young Self condition demonstrated lower subjective age than those in the Current Self condition (prob=.95). They had higher awareness of positive age-related change (prob=.89) and a higher score on the World Health Organization–Five Well-Being Index (prob=.84). Moreover, with respect to performance variables, they took less time to trace a trail (prob≥.99), made fewer mistakes in doing so (prob=.89), had greater right-hand (prob=.85) and left-hand (prob≥.99) grip strength. However, 2 weeks after their final VR exposure, these differences diminished apart from positive awareness of age-related change (prob=.82), trail-making mistakes (prob=.83), and left-hand grip strength (prob≥.99). Here, “prob” refers to posterior probability. Conclusions: The results demonstrate that even 2 short VR exposures, where people were embodied in their younger body and immersed in an iconic event from more than 50 years earlier, resulted in improvement in some age-related responses. This is encouraging for further research with more extensive VR experiences over a longer time period.
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Background: Given the increasing prevalence of depression and anxiety disorders and enduring barriers to care, there is a critical need for alternative treatment options. Generative artificial intelligence (AI) chatbots show promise for increasing access to mental health care, though more direct research is needed to establish their efficacy. Objective: This pilot study aimed to test the efficacy of a generative mental health chatbot rooted in solution-focused therapy compared to the general-purpose ChatGPT and an assessment-only control (AOC) group on depression, anxiety, and well-being. Methods: A total of 185 English-speaking adults were recruited online and randomly assigned to one of three groups: AI therapy, ChatGPT, or AOC. Of these, 147 eligible participants filled out a pretreatment assessment. Over a 3-week period, the AI therapy group (n=44) was instructed to complete 3 structured, fully automated app-based sessions per week (9 total), while the ChatGPT group (n=60) was instructed to engage in 9 unstructured conversations with ChatGPT (GPT-4o–based models). The control group (n=43) received no intervention. In the AI therapy group, 39% (n=17) completed all sessions, as did 62% (n=38) of those in the ChatGPT group. Primary outcome measures, self-assessed online at baseline and postintervention, included the Patient Health Questionnaire-9 (PHQ-9), Overall Depression Severity and Impairment Scale (ODSIS) (depression), 7-item Generalized Anxiety Disorder Scale (anxiety), and World Health Organization Well-Being Index (5-item version) (well-being). Linear mixed effects models were used for data analysis. Results: Compared to AOC, both the AI therapy group (=−0.47; =.01) and the ChatGPT group (=−0.44; =.02) demonstrated significant reductions in depression scores measured by PHQ-9. The AI therapy group showed nonsignificant reductions in anxiety (=−0.37; =.11) and ODSIS depression scores (=−0.25; =.22) and an increase in well-being (=0.12; =.53) compared to AOC. Similarly, a nonsignificant reduction in anxiety (=−0.27; =.22) and ODSIS depression scores (=−0.12; =.53) and an increase in well-being (=0.20; =.29) were observed in the ChatGPT group compared to AOC. The AI therapy group did not significantly outperform the ChatGPT group on any outcomes (PHQ-9: =−0.19; =0.03; =.87; 7-item Generalized Anxiety Disorder Scale: =−0.57; =−0.11; =.62; ODSIS: =−0.59; =−0.13; =.50; and WHO: =−0.38; =−0.07; =.69). Conclusions: Both the structured generative AI chatbot and ChatGPT showed a significant reduction in depression scores compared to the control group. No significant effects were observed across other outcomes, although descriptive trends indicated improvements in anxiety. While the AI therapy group showed descriptively better outcomes for depression and anxiety, differences between groups were not significant. A larger sample and longer intervention may be needed for the emerging trends to yield clinically meaningful effect sizes. Trial Registration: OSF Registries osf.io/r76ef;
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A study in mice headed by NYU Langone Health researchers has found that cells long thought to play a secondary role in brain function build their own far-reaching connections. These pathways appear to connect distant regions in ways that had not been mapped before.
Experts usually describe the brain as a network of nerve cells (neurons) that send each other signals to pass along information. These neurons are maintained by another kind of brain cell, the star-shaped astrocyte, which ferries in nutrients and carries away waste.
The newly reported study, headed by Melissa Cooper, PhD, a postdoctoral fellow in the department of neuroscience at NYU Grossman School of Medicine, revealed that, like neurons, astrocytes form organized webs, which enable them to communicate with other specific astrocytes across the brain rather than only sending local, generalized signals. In some cases, the pathways were found to link areas that were not already joined together by neurons.
“For more than a century, neuroscientists have thought of neurons as the main actors in the brain,” said Cooper. “Yet our findings suggest that astrocytes, which are usually viewed as merely support cells, are also running their own widespread signaling pathway, adding another layer to how brain regions stay connected.” The team suggests that while their study was carried out in mice, not humans, the findings form the basis for future studies investigating how astrocyte networks might link with injury, disease, or aging and to learning and memory.”
Cooper is first and co-corresponding author of the team’s published work in Nature, titled “Astrocytes connect specific brain regions through plastic networks,” in which the researchers stated, “Astrocyte networks can directly link brain regions that are not connected by neurons, suggesting that previously unassociated brain regions communicate with one another through gap junction-coupled astrocytes.”
“Neuronal axons have traditionally been considered to be the primary mediators of functional connectivity among brain regions,” the authors wrote, and the role of communication mediated by astrocytes has been largely underappreciated. “This communication occurs through gap junctions—membrane channels that connect the cytoplasm of neighboring cells, enabling them to redistribute resources and share biochemical signals,” the team continued. “Studies using mice lacking astrocyte gap junctions have shown that these gap junctions are necessary for memory formation, synaptic plasticity, coordination of neuronal signaling, and closing the visual and motor critical periods.”
In earlier work, Cooper reported that in a mouse model of the visual neurodegenerative disease glaucoma, astrocytes can redistribute resources from astrocytes around healthy neurons to damaged neurons. Yet the team had no way to see whether this kind of support-cell network extended across the entire brain.
Cooper said the newly reported study is the first to map active, brain-wide communication networks built by astrocytes and to show that these pathways are highly specific. The research relied on a custom-built tracing tool that let the team follow the cells’ connections in far greater detail than had been possible using past methods. “Despite the importance of astrocyte gap junctional networks, studying them has been challenging,” the investigators noted. “Current methods such as slice electrophysiology disrupt network connectivity and introduce artefacts due to tissue damage.”
For their study, the researchers used a harmless virus to deliver “network tracers” into astrocytes in selected brain regions of lab mice. These tracers tagged small molecules as the molecules passed through the gap junctions linking one astrocyte to another, allowing the team to see which cells were part of the same signaling pathway.
The scientists then made the mice’s brains transparent and used a specialized microscope to capture three-dimensional images of every tagged astrocyte. By doing this across hundreds of mice, they could map astrocyte webs across brain areas. “These networks selectively connect specific regions, rather than diffusing indiscriminately, and vary in size and organization,” they reported. “We observe local networks that are confined to single brain regions and long-range networks that robustly interconnect multiple regions across hemispheres, often exhibiting patterns distinct from known neuronal networks.”
A 3D network of interconnected astrocytes imaged inside a whole, transparent mouse brain. Each astrocyte’s color shows its distance from the viewer; closer astrocytes are blue, while more distant astrocytes are red. [Cooper et al. Astrocytes connect specific brain regions through plastic networks. Nature. 2026. doi:10.1038/s41586-026-10426-6.]
The tracing tool and brain-clearing method were designed to be relatively low-cost and easy to reproduce so that other labs could use them to study the networks in many brain diseases.
In another part of the study, the team assessed mice that were genetically engineered with astrocytes that lacked gap junctions. The communication networks largely disappeared, suggesting that the pathways are active and depend on these physical bridges.
“By challenging our understanding of how the brain communicates over long distances, our results may offer fresh insight into how it develops, ages, and behaves in conditions such as Alzheimer’s and Parkinson’s diseases,” said study co-senior author Shane A. Liddelow, PhD, an associate professor in the neuroscience and ophthalmology departments at NYU Grossman School of Medicine.
Another key finding was that astrocyte networks are dynamic. When the team trimmed whiskers on one side of the mice’s faces—“this manipulation is known to induce robust structural remodeling in neurons,” the team noted—a pathway from the region that processes whisker touch got smaller and reconnected to different astrocyte partners.
“The fact that astrocyte networks shrink and reroute after a loss of sensory signals suggests they may be shaped by experience,” said study co-senior author Moses V. Chao, PhD, a professor in the cell biology, neuroscience, and psychiatry departments at NYU Grossman School of Medicine. “It also raises the possibility that each of us has a somewhat unique pattern of connections molded by what our brains have learned and lived through.”
The authors plan to investigate which molecules move through the networks and to apply their tracing tool to models of brain disorders. They also hope to examine how these webs change during development and aging, said Chao.
Liddelow emphasized that while gap junctions and astrocytes exist in humans, it remains unknown whether the networks link the same regions in the same way as in mice. Nevertheless, in their paper, the team concluded that their findings “… establish foundation for future exploration of how astrocyte network structure and function are shaped by injury, disease, development, aging and experience-dependent processes such as learning and memory.”
<![CDATA[AFSP and JED plan a 2026 merger to form the largest US suicide prevention nonprofit, uniting research, youth mental health programs, advocacy, and community support.]]>
A new study published in Nature Communications is reshaping how researchers think about metastasis, showing that the cells most likely to spread are not defined by extremes, but by a precise balance of biological states within the primary tumor.
The work, led by Raúl Jiménez Castaño, PhD, and colleagues in the Cell Plasticity in Development and Disease Laboratory headed by Ángela Nieto at the Instituto de Neurociencias in Spain, identifies a nonlinear relationship between expression of the transcription factor Prrx1 and metastatic potential in breast cancer. Tumors with intermediate levels of Prrx1—not low or high—were found to be the most metastatic.
“This is unusual,” Jiménez Castaño said. “You normally expect a linear correlation—either low or high expression being the most relevant. But here, the peak of metastasis is in the intermediate levels.”
From paradox to mechanism
The study builds on longstanding efforts to understand the epithelial-to-mesenchymal transition (EMT), a developmental program that enables cells to migrate and is co-opted by cancer cells during metastasis. While EMT has been widely linked to tumor dissemination, the new findings show that metastatic potential is not simply a function of how invasive a cell becomes. Instead, it depends on a finely tuned balance between invasion and proliferation—two processes that are often at odds.
Previous work from the group and others had produced conflicting results regarding the role of Prrx1. In some models, removing the gene reduced metastasis; in others, it appeared necessary for dissemination. To resolve this contradiction, the researchers turned to patient tumor samples, where they observed that metastatic incidence peaked in tumors with intermediate Prrx1 expression.
Modeling a metastatic “sweet spot”
To investigate, the team engineered mouse models with graded levels of Prrx1 expression, mimicking the spectrum observed in human tumors. The results closely mirrored patient data. Tumors lacking Prrx1 showed little ability to metastasize, while those with high expression were capable of invasion but produced relatively few metastases. In contrast, tumors with intermediate levels generated the highest metastatic burden.
At the invasive front of these tumors, the researchers identified a distinct population of cells capable of both migrating and adopting divergent fates—either proliferating or entering a dormant state. This balance proved to be the critical determinant of metastatic success.
To understand the underlying biology, the team applied a range of advanced techniques, including single-cell RNA sequencing, chromatin profiling, and spatial transcriptomics. These approaches allowed them to map cellular states within tumors and link Prrx1 expression levels to functional behavior.
The analyses revealed that Prrx1 plays a dual role: it promotes invasion while simultaneously activating a dormancy program that suppresses cell division.
“At the same time that Prrx1 is necessary for cancer cells to be invasive, it also activates a dormancy program,” Jiménez Castaño explained.
This creates a biological trade-off. At high Prrx1 levels, cells are highly invasive but largely non-proliferative, limiting their ability to form metastases. At low levels, cells retain proliferative capacity but cannot effectively disseminate. Only at intermediate levels do cells achieve both capabilities.
“If the cancer cell has these intermediate levels, it is both invasive and proliferative,” he said. “And therefore, these cells will create a lot of metastasis.”
Metastatic potential begins in the primary tumor
One of the study’s most significant implications is that metastatic potential is determined earlier than previously appreciated. Rather than being dictated solely by conditions at distant sites, the ability of cancer cells to form metastases appears to be encoded within specific cell states in the primary tumor.
“The big conclusion is that already in the primary tumor, the potential of the cancer cells to metastasize is defined,” Jiménez Castaño said.
This finding aligns with broader observations from the field that tumors contain heterogeneous populations of cells with distinct functional properties. In this case, a subset of cells with intermediate Prrx1 expression represents a particularly dangerous state—one that combines mobility with the capacity for sustained growth.
Implications for biomarkers and therapy
Although the study identifies Prrx1 as a potential marker of metastatic risk, translating this insight into clinical practice will require further validation. The researchers were able to stratify tumors into low, intermediate, and high expression groups using staining intensity and computational analysis, but defining precise thresholds remains a challenge.
“We cannot say at this moment it is a biomarker,” Jiménez Castaño noted.
Even so, the findings provide a conceptual framework for improving patient stratification and identifying tumors with a higher likelihood of metastasis.
They also suggest new therapeutic strategies. Rather than attempting to eliminate invasive behavior entirely, it may be possible to push tumor cells into states that are less capable of forming metastases. For example, maintaining high Prrx1 expression could promote invasion while simultaneously enforcing dormancy, preventing metastatic outgrowth.
![A 3D network of interconnected astrocytes imaged inside a whole, transparent mouse brain. Each astrocyte's color shows its distance from the viewer; closer astrocytes are blue, while more distant astrocytes are red. [Cooper et al. Astrocytes connect specific brain regions through plastic networks. Nature. 2026. doi:10.1038/s41586-026-10426-6.]](https://www.genengnews.com/wp-content/uploads/2026/04/Low-Res_Cover-Image-224x300.jpg)