Eli Lilly has told about 50 hospitals participating in a federal drug discount program to submit comprehensive claims data over the next five days or they will no longer receive the mandated price breaks.
The move comes after the company announced a policy last January demanding such data in a bid to reduce what it calls duplicate discounts paid to participating hospitals. The issue has riled the pharmaceutical industry and contributed to a long-standing clash with hospitals over the 340B drug discount program.
For the past few years, more than 2,300 hospitals have complied with the demand, but some of the larger hospitals systems around the U.S. have refused to do so, despite recent follow-up letters regarding the policy that went into effect on Feb. 1, according to Derek Asay, senior vice president for government strategy and federal accounts at Lilly. Up to 1,000 have so far not complied.
With no licensed vaccines available to protect against the Ebola virus currently spreading in Democratic Republic of Congo, efforts are underway to fast-track development of at least three vaccines. But even with infusions of cash to help fund the work, it is likely to be months before clinical trials of vaccines that specifically target the Bundibugyo ebolavirus can begin.
The Coalition for Epidemic Preparedness Innovations (CEPI) announced Monday that it is providing three entities with roughly $62 million in funding to help manufacture and test Bundibugyo vaccines. The only licensed Ebola vaccine, Merck’s Ervebo, targets the Zaire ebolavirus.
Bundibugyo virus has rarely caused outbreaks in the past; only two previous epidemics, in 2007 and 2012, have been recorded. Because it has been so infrequently seen, work to develop vaccines and therapeutics to use against this particular form of Ebola has trailed development of tools to combat other filoviruses — the family to which Ebola belongs — such as Sudan ebolavirus or Marburg, a separate virus that triggers disease similar to that caused by Ebola viruses.
Abivax said Monday that its experimental treatment for ulcerative colitis showed significant efficacy in a closely watched maintenance trial, but shares of the company tanked in post-market trading as it reported a few cases of cancer among treated patients.
The Phase 3 trial enrolled 580 patients who had responded in a pair of earlier, shorter trials. The participants were then followed for 44 weeks, and 50.8% of those taking the 25-milligram dose of the daily pill, called obefazimod, experienced clinical remission, while 51.3% of those taking the 50-mg dose did, compared with 10.4% of those on placebo.
The study appears to have posted the highest placebo-adjusted clinical remission rates observed in a long-term ulcerative colitis trial, Leerink analyst Thomas Smith wrote.
We asked Brian Wolpin, the presenter for yesterday’s plenary on the daraxonrasib pancreatic cancer study, about the sustained standing ovation that interrupted his remarks.
“Honestly, it was tough to hold it together in that moment and then keep going. It felt like 20 years of work all rolled into 12 minutes,” he told us.
It was a truly memorable ASCO meeting. With this newsletter, we say goodbye from Chicago. Thanks again for spending time with us. You can still join our virtual recap on Wednesday!
High-resolution extracellular electrophysiology is typically used to record from neurons in order to understand brain function. Combining electrophysiology with optogenetics allows researchers to test the causal role of specific neurons by activating or inactivating those populations while recording the effects of neural activity.
Now, a new technology, co-developed by UCL scientists, simultaneously records and manipulates neuronal activity deep within the brain. The device, known as Neuropixels Opto and researched in mice, integrates electrophysiology and optogenetics in a single probe, enabling unprecedented insight into how individual neurons in the brain function and interact. By packing around 1,000 closely spaced recording sites onto an ultra-thin probe, it is possible to capture high-resolution signals from individual brain cells while monitoring large neural networks at the same time. The device could transform our understanding of neural circuits and neurological conditions, such as Alzheimer’s disease and schizophrenia.
“This makes it possible, for the first time, to directly test how specific neurons influence the activity of surrounding circuits—revealing causal relationships between neuronal activity and brain function,” notes Matteo Carandini, PhD, a professor at the UCL Institute of Ophthalmology. “The ability to both record and control neuronal activity in the same experiment represents a significant advance for neuroscience.”
This work is published in Nature Methods in the paper, “Neuropixels Opto: combining high-resolution electrophysiology and optogenetics.” The device, which packs 960 electrical recording sites and two sets of 14 light emitters onto a 70-μm-wide, 1-cm-long shank, allows spatially addressable optogenetic stimulation with blue and red light. The device allows researchers to monitor the electrical activity of hundreds of neurons while also selectively activating or silencing specific cells using light.
“The brain processes information through complex patterns of electrical activity, with billions of neurons communicating via rapid electrical signals,” explains Carandini. “Understanding how these signals give rise to behavior, thought and disease requires tools that can both observe and influence neuronal activity.”
“Until now, scientists have typically relied on separate approaches: electrophysiological probes to record neural activity, and optogenetics to control it,” Carandini adds. “Combining the two has proved challenging, particularly in deeper brain regions, where delivering light without disrupting sensitive recordings is technically difficult. Neuropixels Opto overcomes these limitations by integrating both capabilities into a single device, enabling simultaneous measurement and manipulation of neural circuits.”
Karolina Socha, PhD, research fellow at UCL Institute of Ophthalmology, has used the probes to investigate the function of the cerebral cortex. “We were surprised to discover that the activity of neurons in the cortex can be remarkably localized. Up to now, we thought that neurons are so interconnected that there would be no way to activate some of them without activating many others,” she said. “The new Neuropixels Opto probes revealed that these neurons can operate not only in concert but also rather independently.”
The technology may also have important implications for understanding neurological and psychiatric conditions. Many disorders, including schizophrenia, Alzheimer’s Disease and Parkinson’s Disease, are associated with disruptions in how neurons communicate. By providing a clearer picture of how neural circuits function in both healthy and diseased states, Neuropixels Opto could support the development of more targeted treatments.
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.
China has approved the world’s first invasive brain-computer chip—here’s what’s next
Sitting in the courtyard of his house in China’s Henan province last October, Dong Hui decided to try holding a pen. Six years after a car accident left him paralyzed from the neck down, he slowly wrote his name, “Thank you,” and the date.
The breakthrough was made possible by a brain implant called NEO. In March, it became the world’s first invasive brain-computer interface approved for use beyond clinical trials. The approval is expected to accelerate China’s push to become a global leader in brain implants.
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Nvidia is launching its first AI chip for personal computers The RTX Spark will power laptops from Dell, HP, Microsoft, and others. (BBC) + They’re being designed specifically to run AI agents. (WSJ $) + The first devices are set to launch on Windows PCs in the fall. (CNBC) + The move marks a challenge to Apple and Intel. (FT $)
2 The US is stopping exports of AI chips to Chinese firms abroad It’s closed a loophole allowing exports to Chinese subsidiaries. (Reuters $) + Which may have enabled unlicensed access to Nvidia chips. (Al Jazeera) + Export curbs have led China to redesign its chip industry. (MIT Technology Review)
3 Surgeons have transplanted pig liver and kidneys into a living person The clinically dead recipient’s organs worked for almost five days. (Nature) + Pig organs could ease transplant shortages. (Guardian) + Putin says organ transplants could grant immortality. (MIT Technology Review)
4 The US, Australia, and UK will defend seabed cables with underwater drones They’re developing the vehicles via the trilateral AUKUS defense pact. (CNN) + Undersea internet cables face growing threats. (BBC)
5 A new study has revealed chatbots’ manipulative ‘dark patterns’ It found they prey on emotions to encourage harmful behavior. (404 Media) + They can also sway voters better than political ads. (MIT Technology Review)
6 Apple plans to disrupt the traditional glasses market Its smart glasses target the broader spectacles industry. (Bloomberg $) + Smart glasses are also gaining traction in warfare. (MIT Technology Review)
7 AI super PACs are dueling over the midterms Split between Anthropic and OpenAI, they’re fighting to shape AI regulation. (NYT $)
8 SoftBank has overtaken Toyota as Japan’s most valuable company The AI boom pushed SoftBank’s market value above $305 billion. (Bloomberg $)
9 A botnet of more than 17 million devices has been dismantled in Europe Dutch authorities linked the network to a Russian proxy service. (Ars Technica)
10 Tech leaders are uniting around a transhuman vision for AI They’re working toward a post-human agenda. (Guardian)
Quote of the day
“It’s just been shoved down their throats in secrecy. And that makes them upset.”
—Legendary environmental activist Erin Brockovich tells “The Jim Acosta Show” why citizens are angry about data centers expanding into their communities.
One More Thing
MIKE BELLEME
What happens when you donate your body to science
Rebecca George doesn’t mind the vultures. At Western Carolina University’s body farm, forensic anthropologists monitor donors—sometimes for years—as they become nothing but bones.
Around 20,000 people donate their cadavers to scientific research and education each year. At anatomy labs and body farms, they help train doctors, advance research, and teach scientists more about the human body long after death.
IntroductionThree-dimensional assessment of fetal cortical morphology from MRI is essential for understanding early brain neurodevelopment. However, measurement can be affected by fetal imaging quality, number and selection of available stacks, and reconstruction methods.MethodsWe evaluated the within-session reliability of an automated cortical morphometry pipeline in 30 typically developing fetuses [22–36 weeks gestational age (GA)]. For each subject, two disjoint subsets of 2D T2-weighted stacks (no shared stacks) were independently reconstructed into 3D volumes using the Neural Slice-to-Volume Reconstruction (NeSVoR) and the Slice-to-Volume Reconstruction Toolkit (SVRTK). Cortical plate volume, surface area, mean sulcal depth, and absolute mean curvature were extracted, and measurement reliability was assessed using absolute percent difference (APD) and intraclass correlation coefficients (ICC). Multiple linear regression evaluated the effects of mean stack quality, quality difference between subsets, stack count, and GA on measurement reliability.ResultsNeSVoR-derived metrics showed high reliability for all measures (mean APD < 3%, ICC > 0.99). SVRTK-derived metrics were also robust (mean APD < 5%, ICC > 0.97). Reliability increased with greater stack count and older GA in NeSVoR, and with higher mean stack quality in SVRTK.DiscussionThese results demonstrate that automated cortical morphometry from fetal MRI yields highly consistent measurements of volumetric and surface metrics within the proposed within-session design, once minimum levels of image quality and stack count are met. This study proposes a within-session benchmark for automated fetal cortical measurements and underscores that systematic reliability assessment is essential for confident application of automated pipelines in fetal neuroimaging.
IntroductionMotor imagery (MI) is one of the most widely used paradigms in electroencephalogram (EEG)-based brain–computer interfaces (BCIs). In recent years, deep learning and transfer learning techniques have been increasingly adopted to further improve MI-EEG decoding performance, thereby facilitating the practical deployment of BCIs. In transfer learning, the similarity between the source and target domains is a critical factor influencing its effectiveness. Given the analogous cortical activation patterns observed in MI and motor execution (ME) tasks, cross-task transfer learning from ME to MI presents a promising yet underexplored direction.MethodsTo tackle the underexplored problem of cross-task transfer learning from ME to MI, we propose a domain-aware domain–class adaptation network (DDCA Net), which consists of a domain-shared feature extractor, two classifiers, and two domain-specific feature re-weighting blocks. Domain-level alignment is achieved by minimizing the maximum mean discrepancy between source and target feature distributions, while domain-specific feature re-weighting preserves discriminative characteristics unique to each task. In addition, a bi-classifier adversarial learning framework is employed to encourage consistency of decision boundaries across domains, thereby enabling implicit class-level alignment.ResultsExtensive experiments were conducted on a public dataset with over 100 subjects under varying proportions of target-domain training samples. When 80% of target-domain samples are used for training, the proposed DDCA Net significantly outperforms the within-task baseline, achieving a 7.71% improvement in classification accuracy and converting approximately 80% of previously BCI-illiterate subjects into BCI-literate users.DiscussionTo the best of our knowledge, this is the first work to verify the feasibility of applying domain adaptation for cross-task transfer learning in MI-EEG classification. The findings of this study provide new insights for integrating ME and MI in advanced BCIs.
BackgroundPatients with glioma are at high risk of postoperative venous thromboembolism (VTE) and postoperative neurological deterioration (PND). Conventional clinical scoring systems have limited accuracy in predicting these perioperative risks. This study aimed to develop and validate machine-learning models for individualized preoperative prediction of postoperative VTE and PND in patients with glioma.MethodsA retrospective cohort of 427 patients with glioma was included. Patients were randomly divided into training and test sets at an 8:2 ratio using stratified random sampling. Multiple machine-learning algorithms were trained and evaluated. Model performance was assessed using the area under the curve (AUC), accuracy, sensitivity, specificity, calibration curves, and decision curve analysis. An online prediction platform was developed to facilitate individualized risk assessment.ResultsAmong 427 patients, postoperative VTE and PND occurred in 34 and 35%, respectively. For VTE prediction, the final Top-10 random forest model outperformed the Caprini score alone and achieved an AUC of 0.815 (95% CI, 0.720–0.910) in the held-out test set. Performance remained strong in the clinically significant VTE sensitivity analysis (AUC, 0.923; 95% CI, 0.847–0.998). SHAP analysis indicated that older age, elevated D-dimer and fibrin degradation products (FDP), as well as lower hemoglobin levels, were associated with increased predicted VTE risk. For PND prediction, the final Top-10 logistic regression model achieved an AUC of 0.741 (95% CI, 0.627–0.854). Older age, recurrent glioma, higher Caprini score, higher neutrophil percentage, and hypertension history tended to increase predicted PND risk. Models were deployed in the GLOBE web platform (https://gliomas.shinyapps.io/GLOBE/) for real-time preoperative risk prediction.ConclusionWe developed accurate, interpretable, and clinically meaningful preoperative prediction models for postoperative VTE and PND in patients with glioma. The GLOBE online prediction system translates these models into a practical tool for individualized perioperative risk stratification.
ObjectiveInsomnia Disorder (ID) is associated with significant health burdens. First-line treatments are limited by accessibility or side effects, necessitating alternative approaches. rTMS, a noninvasive neuromodulation technique, has shown promise in treating various neuropsychiatric disorders by modulating cortical excitability. This comprehensive meta-analysis explores the effect of rTMS on ID and identifies possible factors that influence it.MethodsA comprehensive search of the Cochrane Library, Embase, Web of Science, PubMed, CNKI, and Wanfang databases identified RCTs evaluating the effects of rTMS on insomnia disorder. Data synthesis and subgroup analysis were performed via SMD, WMD, relative risk (RR), and 95% CI to evaluate the effects of rTMS and its influencing factors. The review protocol was prospectively registered in PROSPERO (CRD42024626833).ResultsNineteen studies contributed 23 trials involving 1,690 adult participants. The rTMS group demonstrated markedly improved sleep quality compared with sham rTMS recipients in individuals with insomnia disorder. (PSQI total scores; ISI; p < 0.001); (PSG (SE); p = 0.003). Combined rTMS and medication were more effective than medication alone. (PSQI total scores; p = 0.003). In the subgroup analysis, after excluding a study with high heterogeneity, the rTMS cohort showed greater improvement in sleep quality than the other treatment groups. (PSQI total scores; p = 0.03).ConclusionIndependent rTMS and rTMS-medication combinations significantly improve sleep patterns and rest quality in patients with Insomnia Disorder. The safety and efficacy of LF-rTMS are also significant. The duration of the disease, treatment duration, and stimulation site may influence the sleep quality of patients with ID.
