Nature Medicine, Published online: 19 May 2026; doi:10.1038/d41591-026-00026-2
The portable, low-resource MiniDock MTB test, evaluated across multiple countries, shows promise for detecting pulmonary tuberculosis using sputum and tongue swabs.
STAT+: Marc Tessier-Lavigne addresses new book’s allegations about his conduct in Stanford misconduct case
SAN FRANCISCO — Former Stanford President Marc Tessier-Lavigne responded publicly for the first time Tuesday to allegations in a new book that he was forced to resign from the university not only because of flaws in his oversight of scientists but over how he handled the controversy.
At the STAT Breakthrough Summit West, STAT reporter Matthew Herper read aloud three paragraphs from Theo Baker’s book, “How to Rule the World.’’ Tessier-Lavigne sat with hands clasped in his lap as he listened to Baker’s description of the board meeting that led to his ouster.
According to Baker, the board concluded “that Tessier-Lavigne’s admit-nothing, deny-everything approach ‘did not reflect well on him and, by extension, the institution.’” The Stanford investigation, according to unnamed sources in the book, omitted yet another incident that contributed to the university turning on Tessier-Lavigne — a younger, female colleague challenging the conclusions of his work, and him dismissing her. By the end of the meeting, “there was no pro-MTL camp” and the board voted unanimously to replace him, Baker wrote.
Trump’s cuts to foreign aid are undermining the Ebola response, insiders say
WASHINGTON — For years, the United States has poured hundreds of millions of dollars into programs to prevent and control infectious diseases in the Democratic Republic of the Congo.
But in the months leading up to a fast-moving Ebola outbreak, the Trump administration slashed aid to the country, leading to a cascade of consequences that probably hampered the detection of the outbreak and the response to it, six people involved in or familiar with the efforts in the region said.
COVID-19 Knowledge, Attitudes, and Practices and Perceived Risk: Cross-Sectional Mixed Methods Study
Background: The COVID-19 pandemic was marked by rapidly evolving and inconsistent public health messaging, contributing to confusion regarding recommended preventive behaviors. Knowledge, attitudes, and practices (KAP) and perceived risk frameworks offer a structured approach to examine how education, personal beliefs, and contextual factors influence health behaviors during public health emergencies. Vulnerable populations, such as patients with multiple sclerosis (MS), experience heightened risk perception compared with the general population, which may further shape behavioral responses. Objective: This study aimed to examine COVID-19–related KAP and perceived risk among patients with MS, health care providers, and laypeople during the first 6 months of the pandemic. The aim of mixed methods was to explore quantitative factors associated with KAP and perceived risk and to qualitatively describe participants’ perceptions and emotional responses to the pandemic. Methods: A descriptive, cross-sectional, partially mixed methods explanatory sequential design was used. Participants were recruited using convenience sampling and completed an online demographic questionnaire and a COVID-19 KAP instrument that included perceived risk items. Quantitative data were analyzed using descriptive statistics and inferential analyses to examine group differences and associations between perceived risk and preventive behaviors. Chi-square testing was applied to compare perceived risk across groups, and correlational analyses were used to examine the relationships between perceived risk and behavioral practices. Qualitative comments provided by participants were analyzed using thematic analysis to further contextualize quantitative findings and to explore perceived risk experiences. Results: A total of 148 participants were included, comprising 43 (29%) individuals with MS, 50 (33.8%) health care providers, and 55 (37.2%) laypeople. Overall, 90% (n=133) of participants demonstrated basic knowledge of COVID-19 transmission and prevention. Attitudes toward public health guidance and self-reported preventive behaviors varied across groups. Lay participants most frequently reported a moderate perceived risk of COVID-19 infection, whereas participants with MS and health care providers more commonly reported high perceived risk (²=12.65, =.049). Neither immunosuppressive treatment status nor vaccine hesitancy significantly predicted perceived risk. However, higher perceived risk was significantly associated with greater avoidance of crowded and public places. Qualitative analysis yielded 5 interrelated themes describing participants’ perceived risk experiences: uncertainty related to evolving scientific information; anxiety regarding personal and family safety; fear of infection and long-term consequences; vulnerability, particularly among individuals with chronic illness and frontline exposure; and accountability toward protecting others through adherence to preventive measures. These themes provided contextual insight into the emotional and cognitive processes underlying reported attitudes and behaviors. Conclusions: Knowledge of COVID-19 is associated with favorable attitudes and engagement in preventive practices across populations. Differences in perceived risk highlight the importance of tailoring risk communication and educational strategies to specific populations. KAP-focused educational interventions that explicitly address uncertainty, emotional responses, and behavioral translation may strengthen preparedness and promote sustained protective behaviors during future public health emergencies. Trial Registration: ClinicalTrials.gov NCT07021716; https://clinicaltrials.gov/ct2/show/NCT07021716
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/5eef2f4db696516c49b8f739973d5ff1" />
Effects of an Eye-Tracking Digital Serious Game on Cognitive Function in Mild Cognitive Impairment: Pilot Intervention Study
<strong>Background:</strong> Cognitive decline in aging populations underscores the need for early interventions in mild cognitive impairment (MCI), where pharmacological treatments show limited benefit. Eye-movement metrics serve as sensitive markers of cognitive deficits in MCI, and digital programs integrating these tasks offer scalable, data-driven training approaches. <strong>Objective:</strong> This study aimed to evaluate the effectiveness of a digital cognitive training program incorporating eye-movement tasks in individuals with MCI, and to determine whether eye-movement indicators can serve as objective markers of cognitive improvement. <strong>Methods:</strong> A total of 12 participants aged 60-85 years with MCI (Korean version of the Montreal Cognitive Assessment [K-MoCA] score of ≤22) completed baseline and postintervention assessments using the K-MoCA and Mini-Mental State Examination-Korean version (MMSE-K). Longitudinal changes in visuospatial attention and oculomotor performance were examined using Spearman correlations across sessions, and pre-post comparisons of eye-tracking metrics were conducted to assess training-related improvements. <strong>Results:</strong> Cognitive scores improved significantly, with K-MoCA increasing by 1.5 points (from mean 20.3, SD 1.1 to mean 21.8, SD 1.7; <i>P</i>=<i>.</i>004; Cohen <i>d</i>=1.38) and MMSE-K by 1.3 points (from mean 21.9, SD 2.0 to mean 23.2, SD 2.2; <i>P</i>=<i>.</i>002; Cohen <i>d</i>=1.29). Fixation duration decreased (<i>r</i>=0.248; <i>P</i>=<i>.</i>003), and saccade velocity increased (<i>r</i>=0.258; <i>P</i>=<i>.</i>002), indicating enhanced visual processing efficiency and faster attentional shifts, whereas fixation count and saccade amplitude showed no consistent changes. In addition, saccade duration decreased by 21.72 ms, and saccade velocity increased by 114.54 °/s. <strong>Conclusions:</strong> Digital cognitive training yielded measurable gains in visuospatial attention and oculomotor efficiency in MCI, with optimized fixation and saccade patterns indicating enhanced attentional control and information processing. These findings support eye-movement metrics as sensitive indicators of cognitive change and highlight digital interventions as scalable, noninvasive tools for cognitive support in aging populations.
Automated Safety Testing and Reporting Application for Conversational Safety Monitoring of Generative AI Tools for Mental Health: Development and Validation Study
<strong>Background:</strong> Artificial intelligence (AI)–based conversational tools are rapidly expanding within mental health care as a means of increasing access and scalability. At the same time, these systems introduce distinct safety risks arising from both user disclosures (eg, self-harm ideation) and inappropriate or inadequate AI responses. <strong>Objective:</strong> This study aimed to develop and evaluate the Automated Safety Testing and Reporting Application (ASTRA), an external system intended to identify clinically relevant risk behaviors across entire AI-mediated mental health conversations. <strong>Methods:</strong> ASTRA was tested on a dataset of 100 synthetic therapeutic conversations written by licensed clinicians to reflect risk behaviors and harmful responses between users and AI tools. Conversations varied in length and included both subtle and overt risk behavior examples across 8 predefined categories. Human coder consensus ratings served as the reference standard. ASTRA’s classifications were evaluated across 2 prompt iterations using standard diagnostic performance metrics and agreement statistics. <strong>Results:</strong> ASTRA demonstrated consistently high concordance with expert human ratings across all categories. Accuracy exceeded 0.90 for all risk behavior categories examined, with specificity uniformly high and sensitivity varying by category (range 0.55-1.00). Agreement beyond chance was substantial to almost perfect between ASTRA and human raters (κ=0.65-1.00). Detection of user self-harm indicators was particularly accurate, even in conversations where risk was expressed subtly. <strong>Conclusions:</strong> In this initial validation study, ASTRA reliably identified multiple forms of mental health–related risk behaviors at the conversation level. These findings support the feasibility of independent safety monitoring systems as a complement to AI tools used in mental health contexts and underscore the need for further evaluation using larger and real-world datasets.
STAT+: Virginia governor vetoes legislation to create an advisory panel to lower the cost of prescription drugs
Virginia Gov. Abigail Spanberger has vetoed closely watched legislation to create an advisory panel to lower prescription drug costs, a setback to attempts by lawmakers across the United States to address the rising cost of medicines.
Unlike affordability boards in other states, the Virginia panel would have used Medicare as a benchmark. Rather than start from scratch to identify drugs considered expensive, each year the panel would have targeted the same drugs chosen by Medicare for price negotiations. The board would have also set upper payment limits to create a ceiling on what would be paid.
By doing so, Virginia would have leapfrogged plans by other states that are at varying stages of establishing affordability boards. Of the other nine states that have boards, none is eyeing all of the same drugs chosen annually by Medicare and only four have the authority to set upper payment limits.
STAT+: This spine surgery usually costs $1,400. Under No Surprises Act arbitration? $34,000
When health insurers contract with providers, they agree on prices for all kinds of procedures. For a lumbar laminectomy, a common spine surgery for ailments like herniated discs or arthritis, the median price is $1,400.
Out-of-network providers, those that don’t contract with health insurers, are getting 24 times that amount for the same surgery at the median — nearly $34,000 — through the No Surprises Act’s arbitration process. Some are even getting north of $100,000.
The lumbar laminectomy is just one example of the extraordinarily high awards being doled out under the flawed system created by the 2020 law. The law has successfully protected patients from unexpected bills, but it’s also been a major boon for providers. They’re not only securing massive sums when they win, but they’re also prevailing in over 80% of disputes.
How AI helped treat a newborn’s ultra rare disease. ‘It was almost like a light switch.’
In the first, tenuous weeks of her life, Jorie Kraus and her parents faced her possible death repeatedly. Muscles throughout her tiny body simply didn’t work properly. Her heart. Her legs. Her larynx. Even the involuntary action of breathing was labored, and constantly faltering.
In those panicked days, through a haze of terrible news and incomprehensible instructions, something incredible happened: A long-shot attempt to discover the root cause of her problems identified a widely available, yet previously unknown, treatment.
Roundtables: Inside the Musk v. Altman Trial
Listen to the session or watch below
Elon Musk lost his suit against OpenAI, in which he alleged CEO Sam Altman and President Greg Brockman had deceived him over the company’s non-profit status.
Watch as AI reporter and attorney Michelle Kim, who covered the trial for MIT Technology Review, joins in conversation with editor in chief Mat Honan to go behind the scenes of the trial and the implications for the AI race.
Speakers: Mat Honan, Editor in Chief, and Michelle Kim, AI Reporter
Recorded on May 19, 2026
Related Stories:
- Elon Musk and Sam Altman are going to court over OpenAI’s future
- Musk v. Altman week 1: Elon Musk says he was duped, warns AI could kill us all, and admits that xAI distills OpenAI’s models
- Musk v. Altman week 2: OpenAI fires back, and Shivon Zilis reveals that Musk tried to poach Sam Altman
- Musk v. Altman week 3: Musk and Altman traded blows over each other’s credibility. Now the jury will pick a side.
- Here’s why Elon Musk lost his suit against OpenAI