Academic research - Relatix Bio

May 1, 2026

DNA-Containing Extracellular Vesicles Boost Antitumor Responses in Mice

A study led by investigators at Weill Cornell Medicine has found that activated T cells secrete extracellular vesicles (EVs) containing DNA, which can enter other immune and tumor cells to stimulate the body’s defense systems. Preclinical experiments showed that this vesicle-associated DNA could be useful therapeutically, boosting T cell attacks against tumors that otherwise evoke little or no immune response.

Studies in live mice showed that these activated T cell-derived-EVs (AT-_EVs) enhanced antigen processing and presentation (APP) in tumor cells and dendritic cells (DCs) across different immunologically cold tumors. The AT_EVs also synergized with immune checkpoint inhibitors (ICIs) to trigger antitumor immunity and hold back tumor growth.

The discovery extends the scientific understanding of the immune system, identifies a new strategy for boosting immunity against cancers, and potentially offers a new tool for delivering genetic payloads to other cells. “These findings reveal a natural mechanism for treating immunologically silent tumors and other diseases that stem from insufficient immune surveillance,” said David Lyden, MD, PhD, the Stavros S. Niarchos professor in pediatric cardiology and a member of the Gale and Ira Drukier Institute for Children’s Health and the Sandra and Edward Meyer Cancer Center at Weill Cornell Medicine.

Lyden is co-senior author of the researchers’ published paper in Cancer Cell, titled “Activated T cell extracellular vesicle DNA transfer enhances antigen presentation and anti-tumor immunity,” in which they stated, “We uncover a mechanism whereby activated T cell-derived extracellular vesicles (AT_EVs) drive a positive feedback loop that enhances antigen presentation and immune responses in normal physiology and cancer … Notably, AT_EVs hold promise as an acellular immunotherapy, restoring APP and synergizing with checkpoint blockade in immunotherapy-refractory tumors.”

Most animal cells secrete extracellular vesicles which can contain cargo including proteins, snippets of DNA, and other molecules. “Extracellular vesicles (EVs) are nanoparticles naturally released by all living cells, containing proteins, lipids, and genetic material, that facilitate intercellular communication,” the investigators wrote.

The Lyden lab in recent years has made seminal discoveries about extracellular vesicles and their functions, finding for example that vesicles secreted by tumor cells can influence the immune system’s anti-tumor response. Their findings, they noted, “… raised the possibility that EV_DNA from immune cells, such as T cells, may also have immune-related functions.” For their new study the team examined the roles of vesicles secreted by immune cells, and specifically T cells, which are the immune system’s principal tumor-fighters.

In their initial experiments, the scientists found that under physiological conditions, T cell-secreted vesicles tend to home to lymph nodes, spleen and other centers of immune activity. There the vesicles are preferentially taken up by antigen-presenting immune cells, including dendritic cells, which assist in T cell activation, a critical process in the immune response. The researchers found that the overall effect of these vesicles released by activated T cells is to boost the antigen-presenting process, thus promoting T cell priming and broader immune activation. The key payloads in these immune-boosting vesicles turned out to be snippets of T cell DNA.

“These surprisingly abundant DNA fragments are mostly on the surfaces of the vesicles, and are not just random—they are enriched for immune-related genes, including genes that help cells display antigens to the immune system,” said co-senior author Haiying Zhang, PhD, an assistant professor of cell and developmental biology in pediatrics and member of the Lyden lab. “We also found that these vesicles have, attached to their surfaces, a special enzyme that acts as a molecular drill, enabling the transfer of vesicle-carried DNA into the nucleus of the recipient cell where they can be expressed transiently,” added study co-first author Diao Liu, PhD, a postdoctoral research associate in the Lyden Lab.

Infusing DNA-carrying vesicles from activated T cells into mice with tumors, the researchers found that the vesicles were taken up not only by antigen-presenting cells but also by tumor cells themselves. The treated tumors grew more slowly and were better infiltrated by T cells and other immune cells, indicating that the vesicles induced a stronger anti-tumor response. “Our work reveals an EV-mediated mechanism through which activated T cells enhance APP across diverse recipient cells—from DCs in physiological conditions to cancer cells across tumor types,” the authors noted. Although cancers—and viruses—frequently suppress the antigen-presenting process to make malignant or infected cells “invisible” to the immune system, the main effect of the extracellular vesicular DNA was to reverse this process, restoring tumor cells’ visibility.

The team demonstrated the effectiveness of this approach, alone and in combination with existing immunotherapy, in preclinical models of three different immunologically silent cancers: glioblastoma, pancreatic and triple-negative breast cancer. “By boosting APP machinery, AT_EVs enhance tumor immunogenicity and elicit robust anti-tumor responses, particularly when combined with ICIs in otherwise resistant tumors, including pancreatic, breast, and brain cancers,” they stated. “These findings reveal the translational potential of activated T cell-derived extracellular vesicles (AT_EVs) by exploiting a naturally occurring immune-boosting process to overcome immune evasion, particularly in immunologically silent cancers.”

Co-senior author Irina Matei, PhD, an assistant professor of immunology research in pediatrics and member of the Lyden lab, stated, “There seems to be a positive-feedback loop, in which the DNA-carrying vesicles from activated T cells amplify the immune response by acting on both antigen-presenting cells, which increase expression of the machinery processing tumor antigens, and tumor cells, promoting their recognition by the immune system as well as their own production of DNA-laden vesicles.”

The researchers are now working to translate their findings into a new, vesicle-based cancer treatment, which could be used on its own or in conjunction with standard immunotherapies or other cancer treatments. “The surprising ability of these vesicles to transfer DNA from donor T cells into the nuclei of recipient cells suggests their potential as a natural, non-viral platform for transient gene delivery,” said co-first author Mengying Hu, PhD, a postdoctoral research associate in the Lyden Lab who led the research and is now an assistant professor of pharmaceutical sciences at the Ohio State University. “The results point to a broadly applicable gene-transfer strategy that may offer improved safety and efficiency compared with current gene therapy approaches.”

In their paper the authors concluded, “Overall, AT_EVs emerge as an acellular immunotherapy and delivery modality that can prime antitumor immunity, synergize with existing therapies, and serve as a vaccine adjuvant,” they concluded. “Our findings provide a foundation for the therapeutic application of AT_EVs through a deeper understanding of the biological role of AT-EV_DNA.”

The post DNA-Containing Extracellular Vesicles Boost Antitumor Responses in Mice appeared first on GEN – Genetic Engineering and Biotechnology News.

May 1, 2026

OTX-202 Smartphone App to Reduce Suicidal Ideation Among High-Risk Transition-Age Youth: Open-Label, Single-Arm, Phase 1 Clinical Trial

Background: The transition from adolescence to adulthood (18 to 25 years) is associated with an increased risk of suicidal ideation and behaviors. Suicide-focused cognitive behavioral therapies (CBTs) have been shown to significantly reduce suicidal ideation and behaviors but are not widely available to high-risk individuals. Digital therapeutics could improve access to these treatments. Objective: This study aimed to evaluate the acceptability, safety, and potential efficacy of OTX-202 among transition-age youth (18 to 25 years) receiving mental health care outside an inpatient hospital setting. Methods: In this phase 1 single-arm clinical trial, 59 transition-age youth with recent suicidal ideation or suicide attempts used OTX-202, a smartphone app designed to deliver suicide-focused CBT, concurrently with usual outpatient mental health care. After baseline, eligible patients completed 12 weekly assessments of suicidal ideation, depression, and anxiety. Results: From baseline to week 12, participants reported statistically significant, large reductions in suicidal ideation (mean difference –5.1, 95% CI –6.5 to –3.7; d=0.95). In total, 3 (5.1%; 95% CI 0%-11.2%) participants reported suicide attempts. Reductions in suicidal ideation and suicide attempt rates were consistent with results from previously published randomized clinical trials of suicide-focused CBTs. Participants rated OTX-202 in the 97th percentile of usability and completed a mean of 9.0 (SD 3.5) of 12 app modules, supporting the app’s acceptability. There were no patient deaths, device-related events, or severe adverse events, supporting the app’s safety. Conclusions: Results support the safety, acceptability, and potential efficacy of OTX-202 for reducing suicide risk among transition-age youth. Trial Registration: ClinicalTrials.gov NCT06008132; https://clinicaltrials.gov/study/NCT06008132

May 1, 2026

Restoring Protein Recycling Reverses T-Cell Exhaustion in Mice

New research published by scientists at the University of California, San Diego (UCSD), describes an unexpected factor underlying T-cell exhaustion. The details of their work in mice are published in a new Cell paper titled “Proteostasis sustains T-cell differentiation potential and tumor-infiltrating lymphocyte function.”

T cells are critical members of the immune system but there are limits to their defensive capabilities. When fighting cancer cells, T cells often burn out and become dysfunctional. A major focus of current cancer immunotherapy efforts is rescuing T cells from this state and getting them back into cancer-fighting shape. The new Cell study led by scientists in the lab of Ananda Goldrath, PhD, a professor of molecular biology at UCSD, and their collaborators elsewhere, suggests that a potential solution to T-cell exhaustion might have to do with protein recycling.

Specifically, their finding has to do with proteostasis, the network of cellular processes that orchestrates the proper construction, movement, and destruction of proteins in cells. A component of this network features a type of recycling function where healthy cells continuously dismantle old and damaged proteins to preserve energy and reuse building blocks to make new proteins. According to the paper, the scientists uncovered an impaired protein recycling function as the surprise culprit in T-cell exhaustion.

“We found that exhausted T cells’ recycling programs are falling apart, leading to damaged and misfolded proteins that pile up with nowhere to go,” said Nicole Scharping, PhD, a post-doctoral fellow in the Goldrath lab and lead author on the paper. Additionally, the scientists also uncovered a way to reverse the accumulation of misfolded proteins by fixing the broken recycling function and restoring normal proteostasis. As Scharping explained, the issue can be resolved with a “tag and sort” fix. This is accomplished using E3 ligase enzymes which act as labelers at a recycling facility, tagging worn-out proteins so the cell knows to break them down.

“In exhausted T cells, many of these enzymes get switched off, and recycling grinds to a halt,” said Scharping. After examining thousands of proteins, the scientists honed in on NEURL3, RNF149 and WSB1 as the E3 ligases responsible for rescuing T cell recycling functions. “When we restored specific E3 ligases, the buildup cleared, and the T cells regained their function and worked better at clearing tumors.” While the new study was conducted in mice, the researchers indicate that similar strategies could be employed for immunotherapy treatments in human cancer.

Importantly, the findings may have implications in other diseases as impaired protein processing is not unique to exhausted T cells. “We think this loss of proteostasis resembles what occurs in neurons in other protein aggregate diseases such as Parkinson’s and Alzheimer’s,” said Goldrath. “Rescuing these cells from exhaustion could improve the ability of T cells to respond to both chronic infection as well as tumors.”

The post Restoring Protein Recycling Reverses T-Cell Exhaustion in Mice appeared first on GEN – Genetic Engineering and Biotechnology News.

May 1, 2026

Data-Driven Tool Identifies Individuals at Highest Risk of Obesity-Related Disease

A new clinical risk model may transform how obesity is managed, by identifying which individuals are most likely to develop serious complications, regardless of their body mass index (BMI).

Developed by researchers at Queen Mary University of London and the Berlin Institute of Health, the tool, called OBSCORE, uses just 20 routinely collected clinical variables to predict the future risk of 18 obesity-related conditions, ranging from type 2 diabetes to cardiovascular disease.

Published in Nature Medicine, the study challenges the long-standing reliance on BMI as the primary metric for assessing obesity-related health risk.

Moving beyond BMI

BMI has long served as a simple proxy for obesity, but it fails to capture the biological heterogeneity of patients. Two individuals with similar BMI can have vastly different risks of developing complications.

The new model addresses this limitation directly. As described in the study, it “provides information beyond BMI” by integrating multiple dimensions of health into a unified risk score.

These include demographic data, clinical biomarkers, disease history, and lifestyle factors, variables already commonly available in healthcare settings.

The findings show that BMI alone is a poor discriminator of risk. The model consistently outperformed BMI-based approaches across all tested outcomes.

Large-scale data enables precision risk prediction

To build the model, researchers analyzed health data from nearly 200,000 individuals with overweight or obesity from the UK Biobank.

Using an interpretable machine learning framework, they screened more than 2,000 potential predictors and distilled them into a core set of 20 features that best predicted long-term health outcomes.

The resulting OBSCORE model estimates the 10-year risk of developing 18 conditions, including cardiovascular disease, kidney disease, sleep apnea, and metabolic disorders.

The model demonstrated strong predictive performance, with median concordance indices around 0.75 across outcomes, indicating robust discrimination between high- and low-risk individuals.

Hidden high-risk individuals

One of the most striking findings is that high-risk individuals are not always those with the highest BMI.

A substantial proportion of individuals classified as high risk fell into the “overweight” category (BMI 27–30 kg/m²), rather than obesity. In some outcomes, up to ~40% of those in the highest risk group had BMI below the obesity threshold.

This reveals a critical gap in current clinical practice: individuals who may benefit from intervention could be overlooked simply because they do not meet BMI-based criteria.

On the other hand, some individuals with obesity may have relatively low risk and may not require intensive intervention.

Strong risk stratification across diseases

Beyond prediction, the scientists believe that OBSCORE enables meaningful risk stratification. Individuals in the highest risk group showed dramatically higher rates of disease compared to those in the lowest group.

For example, the study reports:

Up to 89-fold higher risk for chronic kidney disease
42-fold higher risk for type 2 diabetes
47-fold higher risk for cardiovascular mortality

These differences exceed those observed when comparing individuals based solely on BMI categories, underscoring the added value of multidimensional risk assessment.

Clinical and healthcare implications

The implications of these findings are significant, particularly in the context of emerging obesity therapies.

Highly effective drugs such as GLP-1 receptor agonists and dual incretin therapies have transformed treatment options, but their high cost and limited availability make patient prioritization essential.

As the authors note, current systems lack robust frameworks to identify which patients should receive treatment.

OBSCORE offers a potential solution by enabling risk-based allocation of interventions, ensuring that treatment is directed toward those most likely to benefit.

This could improve clinical outcomes while optimizing healthcare resource use.

Toward implementation in clinical practice

One of the key strengths of OBSCORE is its practicality. Unlike many predictive models, it relies on a small number of variables that are already routinely collected, making it suitable for integration into electronic health records.

The researchers envision the model being used as a decision-support tool in clinical settings, complementing rather than replacing existing frameworks.

External validation in independent cohorts—including populations of different ancestry, demonstrated strong generalizability, further supporting its potential for real-world deployment.

Limitations and next steps

Despite its promise, the model requires further validation in broader populations, including younger individuals and more diverse healthcare settings.

Additionally, while OBSCORE effectively stratifies risk, translating these predictions into actionable treatment thresholds will require clinical consensus and cost-effectiveness analyses.

The authors also emphasize that the model identifies predictive, not necessarily causal, factors, and should be interpreted accordingly.

Taken together, the findings mark a shift toward precision medicine in obesity, moving from simplistic metrics like BMI to data-driven, individualized risk assessment.

By capturing the complex interplay of metabolic, clinical, and behavioral factors, OBSCORE could enable earlier intervention, better targeting of therapies, and improved long-term outcomes for patients living with overweight and obesity.

The post Data-Driven Tool Identifies Individuals at Highest Risk of Obesity-Related Disease appeared first on Inside Precision Medicine.

May 1, 2026

Patient-Derived Lab-on-a-Chip Improves Precision Modeling of Pancreatic Cancer

Researchers at UTHealth Houston have developed a patient-derived “tumor-on-a-chip” model designed to more precisely study pancreatic ductal adenocarcinoma (PDAC). The study, published in Advanced Science, details how the investigators designed the chip to integrate three-dimensional tumor organoids with components of the tumor microenvironment inside a microfluidic system to recreate interactions between cancer cells, stromal tissue, blood vessels, and immune cells.

“Our goal was to build a model that looks and behaves much more like a real pancreatic tumor than traditional lab models,” said Faraz Bishehsari, MD, PhD, professor and director of the Gastroenterology Research Center at McGovern Medical School at UTHealth Houston. “By recreating the tumor’s environment, we can better understand the disease and test treatments in a patient-specific way.”

Pancreatic cancer is difficult to treat because tumors exist within a dense and complex microenvironment that influences both tumor growth and drug response. Current in vitro methods to study the disease, such as two-dimensional cell cultures, as well as pancreatic cancer organoids, often fail to replicate these dynamics.

“Ex vivo models that replicate the tumor and its microenvironment can advance precision medicine in PDAC,” the researchers wrote, but noted that organoids alone “fall short in replicating the tumor microenvironment (TME), which includes various stromal and immune cells influencing tumor growth and chemoresistance.”

To address this, the UTHealth team combined patient-derived organoids with fibroblasts, endothelial cells, and immune cells in a microfluidic chip. The model was created using tumor and blood samples donated by consenting patients, which were used to grow organoids that retained the functional features of the original tumor. The organoids were then incorporated into a chip containing microfluidic channels that mimic blood flow and circulation to create a more dynamic interaction between cells types than current models.

The significance this new lab-on-a-chip lies in its ability to more closely replicate the tumor microenvironment as it would exist in humans more accurately than existing approaches. The design of the chip allows researchers to observe how tumors evolve over time, how stromal and immune components influence cancer behavior, and, perhaps most importantly, how potential drugs and therapies perform under conditions that more closely resemble human disease.

The researchers wrote that their chip “successfully recapitulated the in vivo cancer-stroma interaction of PDAC.” This included the formation of desmoplastic stroma, a dense, scar-like tissue known to limit drug effectiveness. This feature is difficult to reproduce in current PDAC models, but is known to be a major contributor to treatment resistance.

The chip allowed the team to test both chemotherapy and immunotherapies targeting PDAC. They showed that when stromal components were targeted in the model, the effectiveness of standard chemotherapy increased. For immune response, the team studied the effects of pembrolizumab to see how immune cells interacted with the tumor and showed that the drug enhanced T cell infiltration and tumor cell kill. Their observations that lower doses were less effective mirror patterns that have emerged in other clinical studies.

Based on these findings, the researchers noted that chip could serve as a tool for testing new drugs, studying mechanisms of resistance, and evaluating combination therapies tailored to individual patients. Because of its ability to closely recreate the way a tumor would react in vivo, the chip could serve as an important tool to identify the preclinical candidates most likely to effectively treat PDAC.

The implications for developing more precise PDAC therapies are significant. By incorporating organoids and tissues collected directly from individual patients, the chip could allow testing of individualized treatments to account for tumor heterogeneity. Further, it could help find ways to overcome drug resistance driven by stromal interactions and immune suppression.

Next steps for the research include improving the platform’s scalability and reproducibility to support broader use. Future work will also focus on incorporating additional immune components and refining the model to better reflect patient-specific tumor biology.

“This study shows that we can faithfully recreate key features of human pancreatic tumors, including interactions with stromal and immune cells,” Bishehsari said. “The next step is making these systems more practical so they can be widely used in research and drug development.”

The post Patient-Derived Lab-on-a-Chip Improves Precision Modeling of Pancreatic Cancer appeared first on Inside Precision Medicine.

May 1, 2026

Citraconate Enhances Antitumor Activity and Reduces Exhaustion in T Cells

Researchers have found a novel therapeutic target to enhance the effects of cancer immunotherapy. A study published today in Science Immunology reveals how a metabolite known as citraconate can reduce T cell exhaustion and enhance the ability of these immune cells to live longer, multiply, and effectively fight tumors.

Despite the widespread success of checkpoint inhibitor immunotherapies, a substantial proportion of patients still do not respond to these treatments. One contributing factor is metabolic dysregulation within the tumor microenvironment (TME), which compromises the antitumor activity of tumor-infiltrating T cells and limits their proliferation, reducing the efficacy of immunotherapy.

“Emerging evidence highlights the TME as a formidable metabolic barrier to immune cell function, attributable, in part, to the accumulation of immunosuppressive metabolites, which collectively promote T cell exhaustion and resistance to immunotherapy,” writes Lianjun Zhang, PhD, professor at the Suzhou Institute of Systems Medicine and senior author of the study. “Although tumor-derived metabolites are increasingly recognized as key modulators of T cell dysfunction and antitumor immunity, the critical metabolic circuits and specific metabolites that shape and sustain T cell phenotypes remain incompletely characterized.”

Citraconate is known to have antioxidative and antiviral properties, as well as being involved in T cell exhaustion. However, the exact signaling pathways it activates and immunological functions it plays in the context of cancer still remain poorly understood.

Zhang’s team uncovered a previously unreported role for this metabolite in antitumor immunity, by reducing T cell exhaustion and preserving their ability to replicate. In tumor tissue samples from patients, the researchers found that citraconate was depleted within exhausted T cells. In cultured human cells and mouse models, supplementation with citraconate increased the activation of tumor-infiltrating T cells, promoted their division, and reduced exhaustion, boosting their antitumor activity.

Further examination revealed that citraconate triggers these effects by increasing intracellular levels of cAMP, which in turn represses the ALOX5 enzyme involved in the oxidation of fatty acids such as arachidonic acid. This signaling cascade reduces the vulnerability of T cells to ferroptosis, a form of cell death driven by the accumulation of oxidized lipids on the cell membrane.

Genetic and pharmacologic inhibition of ALOX5 enhanced antitumor immunity mediated by T cells, confirming these findings. In mouse models of cancer, supplementation with citraconate was shown to boost the effects of immune checkpoint therapy

Taken together, these findings unveil a critical metabolic checkpoint regulating the performance of tumor-infiltrating T cells, presenting a clinically actionable target to enhance the efficacy of immune checkpoint inhibitors. Going forward, the team plans to dive deeper into the signaling pathways that citraconate employs to modulate T cell activity, its role in metabolic regulation, and the potential contributions of epigenetics to the whole process.

The post Citraconate Enhances Antitumor Activity and Reduces Exhaustion in T Cells appeared first on Inside Precision Medicine.

May 1, 2026

Cyber-Insecurity in the AI Era

Cybersecurity was already under strain before AI entered the stack. Now, as AI expands the attack surface and adds new complexity, the limits of legacy approaches are becoming harder to ignore. This session from MIT Technology Review’s EmTech AI conference explores why security must be rethought with AI at its core, not layered on after the fact.

About the speaker

Tarique Mustafa, Cofounder, CEO, and CTO, GC Cybersecurity

Tarique Mustafa is Cofounder and CEO/CTO of two AI-powered cybersecurity companies: GCCybersecurity, Inc. and its data compliance spinout, Chorology, Inc. A prolific inventor and internationally recognized authority in knowledge representation, inference calculus, and AI planning, Tarique has spent his career applying autonomously collaborative AI to solve complex, ultra-high-scale challenges across cybersecurity, data security, and compliance — with deep expertise spanning Data Classification, DLP, and DSPM industries. His groundbreaking innovations and multiple USPTO patents have earned him global recognition, including frequent invitations to deliver keynote addresses at prestigious international security conferences and forums.

At GCCybersecurity, Tarique architected the core AI algorithms powering the company’s 4th and 5th generation fully autonomous data leak protection and exfiltration platform — among the most advanced platform of its kind. Prior to founding GCCybersecurity and Chorology, he served as founding CEO/CTO of NexTier Networks, a Silicon Valley provider of award-winning Data Leak Prevention solutions. With over 20 years of technical leadership experience, Tarique has held senior roles at Symantec, DHL Airways IT, MCI WorldCom, EDS, Andes Networks, and Nevis Networks, where he served as Principal Architect and built industry-leading security products leveraging next-generation security monitoring, event correlation, IDS/IPS, and SSL/IPSec technologies.

Tarique holds multiple approved and pending patents with the USPTO and has authored numerous research publications spanning Information & Data Security, Computer & Network Security, Software Architecture, Database Technologies, and Artificial Intelligence. A recipient of the prestigious Rotary International Scholarship for doctoral studies in Computer Science at the University of Southern California (USC), Tarique also holds master’s degrees in engineering and computer science from USC, and a bachelor’s degree in mechanical engineering from NED University of Engineering & Technology.

May 1, 2026

Operationalizing AI for Scale and Sovereignty

Companies are taking control of their own data to tailor AI for their needs. The challenge lies in balancing ownership with the safe, trusted flow of high‑quality data needed to power reliable insights. This conversation from MIT Technology Review’s EmTech AI conference examines how AI factories unlock new levels of scale, sustainability, and governance—positioning data control as a strategic imperative for governments and enterprises.

About the speakers

Chris Davidson, Vice President, HPC & AI Customer Solutions, HPE

Chris Davidson is Vice President of HPC & AI Customer Solutions at Hewlett Packard Enterprise. He leads HPE’s global strategy for AI Factory solutions and Sovereign AI, working with governments, enterprises, and research institutions to build secure, scalable national- and enterprise-grade AI capabilities.

He also directs Product Management and Performance Engineering across HPE’s HPC and AI portfolio, including large-model training platforms and Cray exascale systems. His teams define product strategy, performance architecture, and deployment models that position HPE at the forefront of high-performance and AI computing.

During his nine years at HPE, Chris has led key initiatives across Performance Engineering, AI Cloud, and Professional Services, shaping how HPE delivers optimized, cloud-native, and globally deployed high-performance systems. He previously held technical and leadership roles in the biotech and medical diagnostics sectors.

Chris holds an M.B.A. in Entrepreneurship and Finance and a B.S. in Biology from Loyola University Chicago.

Arjun Shankar, Oak Ridge National Laboratory

Arjun Shankar, Division Director, National Center for Computational Science, Oak Ridge National Laboratory

Mallikarjun (Arjun) Shankar is the Division Director for the National Center for Computational Science at the Oak Ridge National Laboratory. His research focuses on the interdisciplinary bridge between computer science and large-scale scientific discovery campaigns that rely on scalable computing and data science. He is a joint faculty appointee at the University of Tennessee’s Bredesen Center, a senior member of the IEEE and a senior member of the ACM.

May 1, 2026

The Download: a new Christian phone network, and debugging LLMs

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

A new US phone network for Christians aims to block porn and gender-related content

A new US-wide cell phone network marketed to Christians is set to launch next week. It blocks porn using network-level controls that can’t be turned off—even by adult account owners.

It’s also rolling out a filter on sexual content aimed at blocking material related to gender and trans issues, optional but turned on by default across all plans.

The trouble is, many websites don’t fit neatly into one category. That leaves its maverick founder with broad, subjective control over what is allowed or banned. Read the full story.

—James O’Donnell

This startup’s new mechanistic interpretability tool lets you debug LLMs

The San Francisco–based startup Goodfire has released a new tool, Silico, that lets researchers peer inside an AI model and adjust its parameters during training. It could give users more control over how this technology is built than was once thought possible.

The goal is to make building AI models less like alchemy and more like a science. Using a technique called mechanistic interpretability, Silico maps the neurons and pathways inside a model and lets developers tweak them to reduce unwanted behaviors or steer outputs.

By exposing the “knobs and dials,” Goodfire hopes to bring AI training closer to traditional software engineering. Read the full story.

—Will Douglas Heaven

With mass firing, Trump deals a fresh blow to American science

This past week delivered another gut punch for science in the US. This time, the target was the National Science Foundation—a federal agency that funds major research projects to the tune of around $9 billion. On Friday, the 22 scientists overseeing those efforts were all fired.

Since 2025, the NSF has faced budget cuts, grant terminations, and mass firings, with staff numbers down sharply and many ambitious projects grinding to a halt. The result is a major shift in how American science is funded and governed. Discover what it means, and what’s next.

—Jessica Hamzelou

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here.

China’s open-source bet: 10 Things That Matter in AI Right Now

Silicon Valley AI companies follow a familiar playbook: keep the models behind an API and charge for access. China’s leading AI labs are playing a different game, releasing “open-weight” models that developers can download, adapt, and run on their own hardware.

That approach went mainstream after DeepSeek open-sourced its R1 model, which matched top US systems at a fraction of the cost. It also won something subtler: goodwill with developers. A growing cohort of Chinese labs is now following the same blueprint.

As AI shifts from hype to deployment, open-source models are making the future of AI more multipolar than Silicon Valley expected. Read the full story.

—Caiwei Chen

China’s open-source bet is one of the 10 Things That Matter in AI Right Now, our list of the biggest ideas, trends, and advances in AI today. We’re unpacking one item from the list each day here in The Download, so stay tuned.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Elon Musk has admitted that xAI trained Grok on OpenAI models
“Distillation” is standard practice in AI, despite being legally dubious. (Wired $)
+ The White House has accused Chinese firms using distillation of theft. (BBC)
+ American labs are widely assumed to use similar techniques. (TechCrunch)

2 A “de-extinction” startup wants to resurrect a long-lost antelope
Colossal Biosciences wants to bring back the bluebuck. (Axios)
+ The company is using genomic editing to revive the animal. (Gizmodo)
+ It previously claimed to have cloned red wolves. (MIT Technology Review)

3 An OpenAI model outperformed ER doctors at diagnosing patients
By analyzing health records data and information provided to physicians. (NPR)
+ But it still must be proven in real-world clinical trials. (Vox)

4 Scientists are trying to power AI data centers with tiny nuclear reactors
They could provide a new way to meet AI’s energy demands. (Gizmodo)
+ We did the math on AI’s energy footprint. (MIT Technology Review)

5 Spotify has started verifying human artists
A new badge will distinguish them from AI. (The Guardian)
+ Spotify has faced criticism for its handling of AI. (BBC)

6 The US is backing a Congolese railway to break China’s grip on critical minerals
The old railroad is key to the race for critical metals in Africa. (Rest of World)
+ The US is also searching for alternative sources. (MIT Technology Review)

7 Huawei is set to overtake Nvidia in China’s AI chip market
It’s expected to capture the largest market share this year. (FT $)

8 Japan is building cardboard drones for the battlefield
The flatpack designs are cheap, disposable, and built at scale. (404 Media)

9 The more young people use AI, the more they hate it
Research shows that Gen Z doesn’t trust GenAI. (The Verge)

10 A new organoid can menstruate—and show how tissue repairs itself
It’s revealing how the uterus can shed without scarring. (Nature)

Quote of the day

“I suspect that there are a number of people who do not want to put the future of humanity in Mr Musk’s hands. But we’re not going to get into that.”

—Judge Gonzalez Rogers rebukes attempts by Elon Musk’s lawyer to focus on AI’s existential risks as part of his lawsuit against OpenAI, the New York Times reports.

One More Thing

This rare earth metal shows us the future of our planet’s resources

The materials we need to power our world are shifting from fossil fuels to energy sources that don’t produce greenhouse gas emissions.

Take neodymium, a rare earth metal used in powerful magnets that power everything from smartphones to wind turbines. Its story reveals many of the challenges we’ll likely face across the supply chain in the coming century and beyond.

The question isn’t whether we’ll run out, but how we extract, process, use, and recycle these materials as technology keeps changing. Find out what it reveals about the future of our planet’s resources.

—Casey Crownhart

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line.)

+ Here’s a fascinating visual history of exploring the dark side of the Moon.
+ This interactive map lets you compare the actual dimensions of our world.
+ These five tiny homes are proof you don’t need a massive footprint to live with style.
+ Explore the history of “Control Room Green” and why it was the default choice for the Cold War’s highest-stakes environments.

Top image credit: Stephanie Arnett/MIT Technology Review | Adobe Stock

May 1, 2026

A game-theoretic framework for multimodal information utilization under heterogeneous processing environments in neuroscience and perception science

Multimodal data integration is increasingly central to neuroscience and perception science, where heterogeneous signals such as behavioral responses, sensory inputs, electrophysiological recordings, neuroimaging measurements, and computational representations must be jointly interpreted. Based on the realistic background, there is a core theoretical problem that needs further research: under what heterogeneous processing conditions does enhanced multimodal information utilization produce meaningful gains, when does it become strategically necessary, and when does it generate only limited benefits relative to its cost? To clarify this core problem, this study develops a conceptual game-theoretic framework in which information utilization is treated not as a universally beneficial technical upgrade, but as a conditional strategic choice shaped by signal heterogeneity, information asymmetry, integration cost, and differential decision influence across actors. Within this framework, we compare three endogenous strategic profiles—no enhanced information utilization, unilateral information enhancement, and bilateral information enhancement—across multiple heterogeneous environments. The analysis results show that the value of multimodal information utilization is fundamentally environment-dependent. In highly homogeneous environments, additional information processing yields little marginal benefit and is therefore not sustained in equilibrium. In moderately heterogeneous environments, however, multimodal information utilization emerges as a strategically necessary response because it reduces mismatch, improves alignment, and stabilizes decision outcomes. In more asymmetric environments, stronger decision agents capture a disproportionate share of the gains from enhanced information utilization and increasingly rely on differentiated strategic responses, whereas weaker agents adopt more defensive and uniform strategies. In highly dominated environments, the marginal value of additional information utilization declines again because structural dominance itself already secures most attainable advantages. These findings contribute to multimodal neuroscience and perception science by clarifying that the consequences of information utilization depend not only on fusion efficiency, but also on environmental structure, asymmetry, and the distribution of strategic power.