Science, Volume 392, Issue 6798, Page 584-584, May 2026.
Short RNA chaperones promote aggregation-resistant TDP-43 conformers to mitigate neurodegeneration
Science, Volume 392, Issue 6798, May 2026.
Ferrimagnetism of ultracold fermions in a multiband Hubbard system
Science, Volume 392, Issue 6798, Page 612-616, May 2026.
ChatGPT Health triage advice falls short in key cases
Nature Medicine, Published online: 07 May 2026; doi:10.1038/s41591-026-04427-1
ChatGPT Health showed high accuracy for moderately urgent conditions but frequently overtriaged mild cases and undertriaged emergencies. These findings highlight safety risks at clinical extremes, raising concerns about the reliability of AI tools for urgent care decision-making.
Macrophages Use Cell Volume Changes to Sense Danger and Amplify Inflammation
Macrophages are often described as the immune system’s first responders, but new work suggests they are also remarkably attuned to the physical state of their environment. A study published in the Journal of Cell Biology titled “Disruption of macrophage cell volume drives inflammatory responses and type I interferon signaling” reveals that shifts in cell volume act as a previously underappreciated danger signal—one that can rewire macrophage gene expression, heighten antiviral defenses, and intensify inflammatory responses.
The research, led by Jack Green, PhD, and colleagues at the University of Manchester, centers on the Volume‑Regulated Anion Channel (VRAC), a protein complex that helps cells maintain osmotic balance. When VRAC is missing, macrophages lose the ability to correct swelling under hypo‑osmotic stress. “Cell volume disruption induced type I interferon signaling through a DNA- and TBK1-dependent mechanism, but independent of cGAS and 2′3′-cGAMP transport,” the authors wrote. That loss of control, the team found, is far more consequential than a simple biophysical hiccup. It fundamentally alters how macrophages interpret threats.
Green noted that although earlier studies hinted at a connection between cell volume and inflammatory signaling, the underlying biology remained murky. “Despite the reported indications that cell volume and VRAC are involved in inflammatory signaling, the basic biological mechanisms of how the regulation of cell volume shapes inflammation were unknown,” he said. To probe that gap, the team examined VRAC‑deficient macrophages exposed to mild osmotic stress.
The swelling triggered broad reprogramming of gene expression, including the induction of antiviral and proinflammatory pathways. Many of the most strongly upregulated genes belonged to type I interferon signaling cascades or nucleic acid–sensing systems. First author James Cook frames the finding succinctly: “Together, these findings suggest that cell volume acts as an additional layer of danger sensing in macrophages that shapes and tunes the nature of immune responses to pathogens.”
That prediction held up in functional assays. When challenged with Influenza A virus, VRAC‑deficient macrophages mounted a more potent antiviral response than their wild‑type counterparts. The heightened sensitivity extended beyond viral infection. In mouse models of systemic hyperinflammation, animals lacking VRAC showed elevated levels of a key inflammatory mediator, indicating that dysregulated cell volume can exacerbate cytokine‑driven pathology in vivo.
Rather than responding solely to biochemical cues, these cells appear to fold physical perturbations—such as osmotic imbalance—into their danger‑sensing logic. Green argued that this perspective may help explain why inflammatory diseases can escalate unpredictably when tissue conditions shift. “Understanding disruptions in the tissue microenvironment leading to alterations in cell volume is therefore an important consideration in our understanding of inflammation and disease pathogenesis,” he concluded, adding that “future studies will reveal the potential for regulating VRAC‑dependent cell volume changes in macrophages in disease.”
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Fraudulent citations, blamed on AI hallucinations, are becoming more common in research papers
Citations in academic papers are intended to ground research in the work that preceded it, over time creating something of a family tree explaining the roots of ideas, protocols, and studies.
But a growing number of these citations lead to dead ends. “Fabricated” citations that do not reference real papers are spreading in the literature, polluting the public record of science, a new study published Thursday in the Lancet shows. Tools using generative AI are likely to blame, say the Columbia University researchers who authored the paper.
Barriers and Facilitators in the Implementation of the Systematic Medical Appraisal, Referral, and Treatment (SMART) Mental Health Digital Intervention in Rural India: Mixed Methods Process Evaluation Study
<strong>Background:</strong> An estimated 150 million people have mental health care needs in India, but only 15% are able to access care. Depression and anxiety contribute to a large proportion of mental morbidity. The Systematic Medical Appraisal, Referral, and Treatment (SMART) Mental Health trial used a mobile-based clinical decision support system for primary care doctors and community health workers (CHWs) to identify and treat people at risk of depression, anxiety disorders, and self-harm. A community-based antistigma campaign was also delivered. The intervention led to improved remission rates for depression and anxiety and lower stigma scores. <strong>Objective:</strong> A process evaluation assessed (1) implementation fidelity, barriers, and facilitators; (2) perceptions of doctors and CHWs on the use of SMART Mental Health; and (3) the causal pathways that led to trial outcomes. <strong>Methods:</strong> A mixed methods evaluation combining backend program data and qualitative data was conducted. A total of 38 focus group discussions and 37 key informant interviews were conducted with primary doctors, CHWs, government officials, local community leaders, and research project staff. The data were coded and analyzed using a framework analysis approach based on the UK Medical Research Council guidance on process evaluations and the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework. <strong>Results:</strong> The intervention had high implementation fidelity. Across clusters, the median proportion of participants with at least 1 CHW follow-up was 98% (IQR 96.6%-100%). The referral rate for a psychiatrist was low (224/1697, 13.2%), and only 23.6% (53/224) of those referred visited the psychiatrist. The median exposure to antistigma audiovisual content was 84% (IQR 65.7%-95.9%). At the community level, key implementation barriers included cultural inhibitions in seeking mental health care and the unavailability of patients due to competing demands. Proximity and tight social connections between CHWs and their communities were important facilitators in seeking medical help. Doctor and CHW training, mentoring, and feedback provided by program staff were important facilitators to support the use of the digital health components by the health workforce. <strong>Conclusions:</strong> A complex intervention that included both community-based antistigma and clinical digital health interventions achieved high implementation fidelity. Key areas to consider for maintenance of such interventions include (1) the need for sustained community-based strategies to address stigma and other cultural barriers; (2) health workforce strengthening policies, including supportive supervision for CHWs and doctors to increase capability in the use of mental health digital health tools; and (3) strategies to improve access to specialist care for those with more complex care needs. <strong>Trial Registration:</strong> Clinical Trial Registry India CTRI/2018/08/015355; https://tinyurl.com/5r63suxp
From Sequence to Patient in Under 12 Months: A Case Study in Advancing Complex Cancer Immunotherapies
Joseph Shultz
Vice President of Technical Development and Manufacturing
Ottimo Pharma
Panelist
Joseph Shultz
Joseph Shultz is the vice president of technical development and manufacturing at Ottimo Pharma. His more than 30 years in the industry span development, manufacturing, quality, and technology development. He has held influential positions at Amgen, Novartis Pharma, the Battelle Memorial Institute, Evelo Biosciences, and Resilience. He initiated the technologies and led the strategies that resulted in next-generation biomanufacturing plants at both Amgen and Novartis.
Imroz Ghangas
Vice President of Commercial Sales
Asimov
Panelist
Imroz Ghangas
Imroz Ghangas and his team drive partnerships to advance Asimov’s genetic design platform and AI capabilities. With over 25 years in biotech, Imroz has evolved from process development scientist to commercial leader, bridging technical innovation with scalable solutions. His expertise spans bioprocess development and platform integration, with deep knowledge of biomanufacturing workflows from gene to drug product. He leverages his technical foundation to accelerate the adoption of next-generation bioprocessing technologies.
Broadcast Date:
- Time:
Complex biologics such as bifunctional antibodies are opening new therapeutic possibilities in oncology, but these molecules present significant challenges for manufacturing teams. Non-standard architectures can often translate to low expression and difficult developability, making cell line development a critical bottleneck between a promising sequence and a viable clinical candidate.
In this GEN webinar, Joseph Shultz (vice president of technical development and manufacturing, Ottimo Pharma) and Imroz Ghangas (vice president of commercial sales, Asimov) discuss strategies for achieving high-performing clonal titers and advancing a dual-paratopic cancer immunotherapy from sequence to dosed patient in under a year. Attendees will learn about the unique attributes of Ottimo’s molecule and how a specialist partnership with Asimov accelerated the program. The presenters will also introduce the CHO Edge System, which combines Asimov’s proprietary GS knock-out CHO host, hyperactive transposase, library of characterized genetic elements, and AI-driven genetic design tools to routinely deliver clonal titers of 8-12 g/L.
A live Q&A session will follow the presentation offering you a chance to pose questions to our expert panelists.
Produced with support from:
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Impact of a Prototype Combining Recommender Functionality With Structured Documentation on Operator Performance in Calls to Medical Communication Centers: Quasi-Experimental Feasibility Study
<strong>Background:</strong> Management of contacts to medical communication centers relies heavily on clinical judgment, contextual understanding, and communication skills. Decision support systems, intended to complement medical expertise, may, due to their rigidity, impede effective caller interaction and may, together with the obligatory documentation of calls, contribute to a workflow that draws attention away from the communication. Recommender systems have demonstrated potential in supporting decision-making across various domains by nudging individuals toward better choices without undermining autonomy. We built a prototype that combined artificial intelligence–based question recommendations with structured documentation (hereafter: the prototype) and conducted a feasibility study to test its influence on operators’ performance. <strong>Objective:</strong> This study aimed to examine whether the prototype influenced the operators’ performance during telephone triage. We hypothesized that the prototype would affect medical quality without affecting communication quality. <strong>Methods:</strong> A quasi-experimental pre- and posttest feasibility study was conducted in a simulated setting. Twenty-five operators were voluntarily recruited from 5 Norwegian medical communication centers, in which 22 operators contributed to both the pretest (before the prototype) and the posttest (with the prototype). The operators handled the same 15 medical cases presented by simulated callers, with a 5-month interval between the 2 sessions. The question recommender was trained on other data and then fine-tuned on the 15 scenarios used. Audio recordings of the calls were rated using the tool Assessment of Quality in Telephone Triage. Pre- and posttest values were compared, with overall medical and communication quality as the primary outcomes. Secondary outcomes included specific items related to medical content and communication, accuracy of triage, patient safety, call duration, and efficiency. <strong>Results:</strong> A total of 320 paired calls were analyzed. Overall medical quality improved significantly with use of the prototype, from a mean of 6.83 points pretest to 7.16 points posttest rated on a 10-point scale (difference 0.34, 95% CI 0.11-0.57; <i>P</i>=.004). The effect size was small (Cohen <i>dz</i>=0.16). No significant change was observed in overall communication quality, with a mean of 7.06 points pretest and 6.97 points posttest (difference –0.09 points, 95% CI –0.28 to 0.10; <i>P</i>=.35). A significant decrease from pre‑ to posttest was observed in the specific items “Collects information about the patient’s location” (<i>P</i><.001) and “Ensures that the triage decision is understandable and feasible” (<i>P</i>=.002). None of the remaining secondary outcomes showed significant changes. <strong>Conclusions:</strong> The prototype yielded a modest improvement in medical quality within the scenario‑based test environment. Although overall communication quality remained unchanged, aspects of the interaction were negatively affected. Artificial intelligence–based question recommendations combined with structured documentation may serve as useful functionalities within a decision support system, but each functionality requires further testing and development before such technology can be implemented in the triage of unselected, real‑world calls. <strong>Trial Registration:</strong>
Fully Anonymized Digital Health Data Acquisition in a Research Partnership Using a Blinded Deidentification Proxy in the HerzFit App: Implementation Study
Background: The European General Data Protection Regulation (GDPR) strictly regulates the processing of personal and health-related data, posing challenges for digital health research, especially when data are collected using participants’ own devices. Although scientific data can theoretically be anonymized, standard internet communication protocols inevitably expose transmission metadata, preventing true anonymization. Existing solutions, including virtual private networks, reverse proxies, and trust centers, improve confidentiality but do not technically or legally enable fully anonymized data collection. Consequently, large-scale digital health research often requires extensive organizational measures, complex consent procedures, and high regulatory overhead. Objective: This study aimed to develop a GDPR-compliant concept for fully anonymized scientific data collection, ensuring that no entity has simultaneous access to identifying information and donated data. We also implemented and evaluated this concept in a real-world public-private partnership. Methods: We designed a data donation architecture based on a blinded deidentification proxy that decouples identifying transmission metadata from encrypted user data at the time of donation. The concept combines symmetric (Advanced Encryption Standard-128 in Cipher Block Chaining) and asymmetric (Rivest-Shamir-Adleman with Optimal Asymmetric Encryption Padding) encryption, enabling end-to-end encrypted and anonymized data transfer without persistent identifiers. The system was integrated into the HerzFit app, a mobile lifestyle coach for cardiovascular disease prevention available in German-speaking countries, and evaluated for adoption, technical feasibility, and performance. Performance overhead was assessed using round-trip time benchmarks. Duplicate donations were identified and merged to estimate unique data donors. Results: The solution was integrated and tested in the HerzFit app with more than 200,000 downloads between April 2022 and December 2025. Since the introduction of the data donation feature, more than 13,000 donations have been received, translating to more than 9000 individual users contributing anonymized datasets. Proxy-based transmission resulted in an average round-trip time of 143 ms, compared to 58 ms for direct transfer, representing a modest overhead while maintaining usability. The operator of the donation database did not gain access to identifying information at any stage, demonstrating full technical anonymization. The approach can be operated reliably at scale with minimal server resources due to the stateless proxy design. Conclusions: This work introduces a novel system architecture enabling fully anonymized, GDPR-compliant data donation directly from participants’ devices. By decoupling identifying metadata from encrypted health data, the concept minimizes regulatory effort, strengthens privacy protection, and provides a practical framework for large-scale digital health research in research partnerships, for example, between a private company and a research institution. The real-world deployment in HerzFit demonstrates the feasibility, scalability, and scientific utility of this approach. The concept is broadly transferable to other mobile health apps and has the potential to substantially expand ethically and legally compliant data acquisition.
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