Norway-based Circio and Tcelltech, based in Germany, will collaborate using the double-stranded, non-integrating nanoSMAR vector platform for the development of next generation engineered T-cell therapies.
Engineered T-cell therapies such as CAR-T have transformed the treatment of certain cancers. However, ex vivo manufacturing remains complex, and the shift towards in vivo approaches currently relies on viral vectors that have significant safety concerns, according to Richard Harbottle, PhD, head of vector technology and manufacturing at Tcelltech. By integrating the technologies developed by Circio and Tcelltech, the parties aim to engineer T-cells with enhanced and sustained CAR/TCR expression, without the need for viral vectors, he adds.
“The combination of Tcelltech’s non-viral, episomal nanoSMAR DNA vector platform with Circio’s circVec expression technology holds great promise for the development of in vivo gene delivery systems that are non-disruptive to target cells, maintain high expression levels, and enable straightforward, cost-effective manufacturing,” says Harbottle. “Furthermore, the exceptionally large cargo capacity of nanoSMAR vectors—beyond what is achievable with viral approaches—enables the design of complex, and sophisticated constructs incorporating multiple payload genes and regulatory elements.”
Circio and Tcelltech will combine Circio’s circVec circular RNA expression technology with Tcelltech’s non-viral, high-cargo capacity nanoSMAR vector platform and evaluate the combination in engineered T cells through a staged research program. An initial proof-of-concept phase will compare how strongly and how durably the different technology combinations drive gene expression in primary human T cells, followed by a functional phase in which CD19-directed CAR T cells are generated and tested for their ability to kill tumor cells.
“In vivo T-cell therapy is one of the most exciting frontiers for our circVec technology and is a rapidly advancing approach that could make these therapies more scalable and accessible,” adds Victor Levitsky, PhD, CSO of Circio. “Tcelltech´s universal nanoSMAR platform is a promising and differentiated delivery technology for T-cells, which we expect will act synergistically with circVec-enhanced payload expression.
“This collaboration fits into Circio’s broad business development strategy of testing circVec across multiple modalities and delivery systems to identify the optimal technology combination and identify the most promising therapeutic avenues.”
By Florencia Assaneo, PhD, Research Fellow, Stavros Niarchos Foundation (SNF) Global Center for Child and Adolescent Mental Health at the Child Mind Institute
Educational challenges for Latin American children
Primary education in Latin America has faced a steady decline over recent decades, contributing to what many organizations now describe as an educational crisis. International institutions such as the Economic Commission for Latin America and the Caribbean (ECLAC), the United Nations Educational, Scientific and Cultural Organization (UNESCO), as well as the World Bank Group have all called for urgent action to address worsening learning outcomes across the region. The situation is particularly concerning in Mexico. Results from the 2022 Programme for International Student Assessment showed that Mexico scored well below the Organization for Economic Co-operation and Development (OECD) average in reading, mathematics, and science — placing the country among the lower-performing educational systems evaluated globally.
The consequences of this crisis extend far beyond the classroom. Educational difficulties during childhood are closely linked to long-term social and mental health outcomes. Research has shown that additional years of basic education are associated with lower rates of depression and anxiety (Kondirolli & Sunder, 2022), as well as higher levels of resilience and perceived control over one’s life (Niemeyer et al. 2019). In this sense, poor academic performance in primary school can have lasting effects that continue into adulthood, limiting employment opportunities, increasing vulnerability, and negatively affecting overall well-being.
Can rhythm-based video games improve learning?
Open-access interventions that strengthen children’s cognitive and academic abilities could have enormous value in low- and middle-income countries, where educational resources are often limited. Our work explores whether the ability to coordinate movements with rhythmic sounds — such as clapping, tapping, or dancing to music — can be leveraged to support children’s learning and cognitive development through engaging digital tools.
Over the last decade, multiple studies have shown that children who are better at synchronizing their movements to rhythm also tend to perform better on a wide range of cognitive and language-related tasks. These include reading, phonological awareness, processing speed, rapid naming, and other foundational abilities linked to academic success. Researchers have assessed these rhythmic coordination skills in multiple ways, from walking to the beat of music to tapping along with a steady rhythm or coordinating movements while playing musical instruments. Across these different approaches, one result consistently emerges: children who are better at aligning movement with sound also tend to show stronger cognitive performance.
Building on these study findings, my current fellowship project, supported by the Stavros Niarchos Foundation (SNF) Global Center for Child and Adolescent Mental Health at the Child Mind Institute, seeks to better understand how these rhythm synchronization abilities develop during childhood and whether they could eventually be strengthened through interactive digital interventions. Specifically, we are studying the developmental stage at which these abilities become established in children, and whether individuals with stronger rhythmic coordination also show advantages in attention and language-related skills. Understanding when these abilities emerge is particularly important because it may help identify the developmental window during which they are most malleable and therefore most responsive to training or intervention.
From left to right: Rebeca Hernández Soto, associated researcher at the lab; M. Florencia Assaneo; principal of the public primary school; and Moramay Ramos Flores, a PhD student working on the project. At the public school “Américas Unidas” in Querétaro, Mexico.
In parallel, we are using functional magnetic resonance imaging (fMRI) — a non-invasive brain imaging technique that allows us to observe which brain regions become active during different tasks — to explore the relationship between rhythmic synchronization and the brain’s reward system. Importantly, these same reward-related regions are also strongly engaged during video game play. If the pathways within this reward system are similarly activated during rhythmic coordination, this could mean that children who initially struggle to synchronize movements with sound may be able to strengthen these abilities through a carefully designed video game experience. One possible future application could involve an open-access mobile game in which children synchronize taps or hand movements to musical rhythms while progressing through increasingly challenging levels and unlocking rewards or visual customizations.
Overall, the current project seeks to generate the scientific evidence necessary to determine whether rhythm-based digital interventions could become a viable tool for supporting children’s cognitive development. This work has the potential to contribute to the future development of accessible and scalable tools that can strengthen foundational cognitive skills linked to academic performance in children. These tools can be applied to children in Mexico and, more broadly, across low- and middle-income countries (LMICs), expanding access to education resources and interventions.
The power of collaboration between the SNF Global Center and UNAM
Our laboratory at Universidad Nacional Autónoma de México (UNAM) is primarily dedicated to basic neuroscience research. Based at UNAM’s campus in Querétaro, our team brings together researchers and students from different disciplines — including neuroscience, psychology, physics, engineering, and data analysis — united by a shared interest in understanding how rhythm and brain dynamics shape human cognition and behavior. Here, we have access to excellent infrastructure for fundamental research, including neuroimaging facilities and high-performance computational resources. However, translating basic scientific discoveries into interventions capable of improving people’s daily lives is often much more challenging and requires strong cross-sector collaboration.
Members of the research team at the laboratory facilities on UNAM’s Querétaro campus.
The work I’m conducting as part of the SNF Global Center Research Fellowship has encouraged us to begin thinking beyond the laboratory. This current fellowship has given us the opportunity to test the core scientific assumptions behind our proposed open-access intervention. If the pilot project proves successful, the next stages of the work will become considerably more ambitious, involving both the technological development of the intervention and its large-scale implementation and evaluation in school settings. Advancing toward those goals will likely require the support of larger international organizations and cross-sector collaborations. In this context, the opportunities provided by the SNF Global Center at the Child Mind Institute to share, disseminate, and give visibility to our work are extremely valuable, helping create the connections and momentum necessary to move from foundational research toward real-world impact.
More broadly, this kind of collaboration highlights the importance of building bridges between global institutions and local research communities. By combining international support with local expertise and close engagement with schools and communities, it becomes possible to develop solutions that are both scientifically rigorous and genuinely connected to the realities of the populations they aim to serve.
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.
Heat waves mess with your brain. Scientists are trying to figure out why.
—Jessica Hamzelou
It’s been hot in London this week. Really hot. A dangerous heat wave has hit Western Europe. On Wednesday, the UK recorded its highest ever June temperature at 36.1 °C (about 97 °F). But as the weather app on my phone confirmed, it felt like 39 °C.
Much of Western Europe is suffering, bringing awful consequences for agriculture, infrastructure, and the health system. But heat can also affect the brain.
Studies have confirmed that as temperatures rise, people seem to get more irritable and more violent. And they have shown that firefighters find it harder to focus immediately after heat exposure. Rising temperatures can also have particularly disastrous outcomes for children and people with mental health disorders.
Research on lab animals suggests that excessive heat can alter the function of chemical signals in our brains. But we still need a better understanding of the mechanisms behind these effects.
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 The Trump administration has asked OpenAI to limit its next model release It wants to vet the first GPT 5.6 users before a wider launch. (Bloomberg $) + OpenAI said each of the initial partners will be government-approved. (FT $) + It’s the first US firm to be told to restrict an AI model before release. (Axios) + Anthropic is also still feuding with Washington. (MIT Technology Review)
2 Apple and Xbox have hiked prices, blaming AI-driven chip costs Some MacBooks, iPads, and Xboxes are going up in price by over 20%. (BBC) + Apple’s shares plummeted after the announcement. (NBC) + AI data center demand has pushed up memory and storage prices. (WSJ $) + The shortages have been dubbed “RAMaggedon.” (The Verge)
3 Colossal and the US are building an endangered species “biovault” It aims to cryptopreserve over 2,300 plant and animal samples. (Wired $) + It comes amid growing threats to endangered species protections. (NYT $) + Colossal is also growing chickens in artificial eggshells. (MIT Technology Review)
4 The US has banned Polestar from selling its EVs due to anti-China rules The Sweden-based company is majority-owned by China’s Geely. (CNN) + The ban is because its connected-vehicle tech is linked to China. (Reuters $) + What happened to China’s overseas EV factory boom? (Rest of World)
5 China is betting on humanoids to beat its demographic decline It wants the robots to narrow the labour gap. (FT $) + Gig workers are training humanoids at home. (MIT Technology Review)
6 The “fingerprints” of a black hole’s event horizon have been detected The discovery was made by studying ripples in space-time. (AFP)
7 OpenAI is now expected to delay its IPO until next year It’s been spooked by choppy global markets and SpaceX’s slump. (NYT $)
8 Data centers have moved to the forefront of environmental lawsuits The litigation is linked to energy sources, water consumption, and air pollution. (Guardian)
9 A master gene that turns on human development has been uncovered It results in cells forming a human body. (New Scientist $)
10 Grok’s most popular feature? Smut It accounts for “well over half” of the chatbot’s traffic. (The Information $)
Quote of the day
“The most advanced AI is built by a handful of American companies, on American soil, under American law, and what the rest of us are permitted to do with it can change on a Friday afternoon.”
—Nathan Benaich, AI investor at London-based venture firm Air Street Capital, tells the Financial Times about the geopolitical reality of US AI dominance.
One More Thing
MAX-O-MATIC
How technology helped archaeologists dig deeper
In 1991, construction workers in Manhattan unearthed hundreds of coffins. Further investigation revealed that the remains were between 200 and 300 years old, and they were all African and African American.
This discovery came at an inflection point in scientific history. Breakthroughs in chemical and genetic analysis allowed researchers to figure out where many of these people were born, the physical challenges they faced, and even the routes they took from Africa to North America.
Today, archaeologists are using techniques they could only dream of then: lasers, 3D photography, lidar, satellite imagery, and more. These tools are revealing where people came from, how ancient cities were built, and the lives of those who built them.
Auricular vagus nerve stimulation (aVNS) is a neuromodulation technology that establishes balance in the autonomic nervous system and, in turn, provides therapy for numerous chronic ailments. Personalized aVNS adapts the stimulation parameters in accordance with the time-varying physiological state of the body, and is suggested to improve the therapeutic outcomes and reduce side effects. The physiological state is estimated via recorded biomarkers such as the electrocardiogram (ECG). aVNS can be delivered in synchrony with any phase of the cardiac cycle before and after the R-peak. This paper proposes the prediction of the duration of the next cardiac cycle after the detected R-peak for the realization of the personalized cardiac-gated closed-loop aVNS applied at any time point during the predicted cardiac cycle. We propose and explore the feasibility of four different prediction methods for predicting the duration of the next cardiac cycle. Two methods are respiration-insensitive, last value and averaging, and the other two are respiration-sensitive, extrapolation and interpolation. Offline recorded ECG waveforms were used to evaluate the different methods. Subsequently, three of the four methods (last value, averaging, and extrapolation) were implemented in real-time on a proprietary aVNS hardware setup, with the data acquisition performed across normal and paced deep breathing. Offline evaluation of the methods revealed that extrapolation and interpolation achieved lower prediction errors during deep breathing with the median absolute error (MdAE) of 32.09 ms (interquartile range 16.07–56.61 ms) and 31.71 ms (15.5–54.06 ms), respectively, as compared with the averaging and last-value methods with 88.75 ms (58.73–124.15 ms) and 40.85 ms (19.7–68.4 ms), respectively. During normal breathing, all evaluated methods yielded lower prediction errors relative to the averaging method 28.5 ms (15.2–43.7 ms). Real-time implementation validated these methods for closed-loop cardiac-gated aVNS, with the best performance achieved by the extrapolation method with 31.4 ms (15.17–55.9 ms) during paced deep breathing. During normal breathing, comparable performance across prediction methods favors the computationally simple last-value approach (MdAE: 31.6 ms). Proposed methods establish the potential of ECG-based R-peak prediction in real-time as a reliable and individual biomarker for the personalized cardiac-gated aVNS, creating a foundation for future clinical applications of aVNS.
Amblyopia is a neurodevelopmental disorder of the visual cortex which leads to issues in visual acuity, contrast sensitivity and eye movement patterns, all characteristics which, along with other deficits may negatively influence reading skills. Individuals with reduced reading capabilities due to amblyopia or other binocular vision disorders may have difficulties navigating various social aspects of daily life including employment and academics. Reading is an active viewing task which involves multiple oculomotor and cognitive processes. In this review, we introduce how a lack of binocular vision or other low vision issues such as blur, low illumination or altered contrast sensitivity may contribute to impaired reading performance. These impairments, particularly in amblyopia, include changes to reading speed, eye movements and crowding. Though reading is such an important daily skill, and is known to be impacted in amblyopia, there are no known treatments for this condition which are specifically designed to improve reading. Binocular therapies may be leveraged to address these issues. This narrative review provides available evidence on alterations to reading ability in amblyopia and why this may be relevant for developing novel amblyopia therapies.
IntroductionElectroencephalogram (EEG)-based biometric recognition for brain–computer interfaces faces challenges from domain shifts, temporal nonstationarity, and limited scalability.MethodsTo address these issues, we present DyAMNet, a framework that combines EEG microstate analysis with a hybrid attention mechanism. DyAMNet employs dynamic loss balancing to improve generalization and constructs a domain-invariant feature space that supports user expansion without catastrophic forgetting. We evaluated the model on three benchmark datasets (DEAP, THU-EP, and SEED).ResultsThe framework attains 87.2% accuracy in cross-dataset recognition and retains 84.0% accuracy when incrementally scaling to 60 users. The system also tolerates physiological artifacts and intersession signal drift, outperforming state-of-the-art models.DiscussionThese findings show that dynamic adversarial training coupled with contrastive feature learning reduces brain-signal variability and preserves scalability. The work establishes a robust basis for feasible identity authentication and supports deploying brain–computer interfaces in clinical and everyday settings. The code is available at: https://github.com/cangtianhaoxue/DyAMNet.git.
BackgroundThe Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), is widely used in the diagnostic evaluation of autism spectrum disorder (ASD); however, its diagnostic performance in real-world clinical referral populations remains heterogeneous, particularly across modules and clinical contexts. This systematic review and meta-analysis evaluated the module-specific diagnostic accuracy of ADOS-2 using hierarchical meta-analytic modeling and examined sources of heterogeneity in updated evidence clinical studies.MethodsA systematic search of PubMed/MEDLINE, Scopus, and Web of Science was conducted from January 2021 to February 2026, with additional screening of reference lists. Studies were included if they evaluated ADOS-2 diagnostic accuracy in real-world clinical referral populations, used DSM- or ICD-based clinical best-estimate diagnosis as the reference standard, and reported extractable 2×2 data. Diagnostic accuracy was pooled using a hierarchical summary receiver operating characteristic (HSROC) model with a bivariate random-effects approach. Module-specific analyses (Toddler Module, Modules 1–2, Module 3, Module 4) and meta-regression were performed to examine heterogeneity.ResultsTen studies were included in the qualitative synthesis, and six provided extractable 2×2 data for quantitative pooling. Overall pooled sensitivity was 0.88 (95% CI: 0.83–0.92) and pooled specificity was 0.74 (95% CI: 0.68–0.80), with an HSROC AUC of 0.86. The Toddler Module showed the highest diagnostic performance (sensitivity 0.92; specificity 0.88; AUC 0.94), whereas specificity decreased in Modules 3 and 4. Meta-regression identified module level, psychiatric referral setting, and adult samples as significant contributors to reduced specificity. No significant publication bias was detected.ConclusionsADOS-2 demonstrates high overall sensitivity but variable specificity across modules in real-world clinical referral populations. Reduced specificity was more commonly observed in higher ADOS-2 modules, which are typically administered to verbally fluent adolescents and adults with greater psychiatric complexity.
BackgroundElevated post-stroke depressive symptoms are common among acute ischemic stroke (AIS) survivors and are associated with poor functional recovery. However, readily available biomarkers reflecting lipid–inflammation status remain limited. The ratio of non–high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (NHHR) may integrate atherogenic burden and inflammatory status and thus be associated with depressive symptom burden after stroke.MethodsWe retrospectively analyzed a cohort of 518 Chinese AIS patients. Admission NHHR was calculated from routine lipid panels. Depressive symptoms at 90 days were assessed using the Hamilton Depression Rating Scale (HAMD), and elevated post-stroke depressive symptoms were defined according to the prespecified HAMD threshold. Multivariable logistic regression, restricted cubic spline (RCS) analysis, and subgroup analyses were conducted to examine the association between NHHR and elevated depressive symptoms.ResultsAmong the 518 patients, 179 exhibited elevated post-stroke depressive symptoms at 90 days. Higher NHHR levels were independently associated with increased odds of elevated depressive symptoms after adjustment for demographics, stroke severity, cognitive function, inflammatory markers, and coagulation parameters (OR = 1.35, P = 0.029). Dose–response trends were observed, and RCS analysis suggested a linear relationship without significant nonlinearity. No significant interactions were found across sex, smoking, alcohol use, hypertension, or diabetes subgroups.ConclusionsElevated NHHR at admission was independently associated with elevated post-stroke depressive symptoms at 90 days in Chinese AIS patients. As a simple, cost-effective, and readily obtainable biomarker, NHHR may facilitate early risk stratification and guide individualized interventions.
IntroductionAlzheimer’s disease (AD) is associated with progressive cognitive decline, functional impairment, and reduced quality of life. Although pharmacological treatments such as cholinesterase inhibitors and memantine are commonly used, their clinical benefits remain limited and heterogeneous. Cognitive stimulation therapy (CST) may provide additional benefits when combined with standard pharmacotherapy. This randomized controlled trial (RCT) aimed to evaluate the clinical efficacy of modified CST combined with standard drug therapy on cognitive function, activities of daily living, and quality of life in patients with mild-to-moderate AD and to explore key predictors of CST efficacy using a multivariate regression model.MethodsThis evaluator-blinded randomized controlled trial enrolled 80 patients with mild-to-moderate Alzheimer’s disease (AD), who were randomly assigned in a 1:1 ratio to either the modified CST plus standard pharmacotherapy group (study group, n = 40) or the standard pharmacotherapy-alone group (control group, n = 40).The modified CST program comprised 14 weekly 45-minute sessions. The primary endpoint was the change in the Alzheimer’s Disease Assessment Scale–Cognitive Subscale (ADAS-Cog) score from baseline to post-intervention. Secondary measures included the Activities of Daily Living (ADL) scale and the Quality of Life in Alzheimer’s disease (QOL-AD) questionnaire. Data were analyzed using an intention-to-treat (ITT) approach. Independent predictors of treatment efficacy were identified using a two-stage screening strategy (univariate screening and stepwise regression).ResultsA total of 75 patients completed the study, and 80 were included in the ITT analysis. After 14 weeks of intervention, baseline-adjusted ANCOVA showed that the study group had significantly better post-intervention ADAS-Cog scores than the control group. The adjusted mean difference in ADAS-Cog score was -3.28 points (95% CI: -3.72 to -2.83; P < 0.001), favoring the study group. Significant baseline-adjusted between-group differences were also observed for ADL (adjusted mean difference = -4.93, 95% CI: -8.39 to -1.47; P = 0.006) and QOL-AD (adjusted mean difference = 2.69, 95% CI: 1.01 to 4.37; P = 0.002), both favoring the study group. Higher years of education (β = -0.54, P < 0.001), regular physical activity (β = -0.28, P = 0.003), higher baseline Mini-Mental State Examination (MMSE) scores (β = -0.22, P = 0.001), and active hobbies (β = -0.20, P = 0.002) were significant independent predictors of CST efficacy.DiscussionModified CST combined with medication significantly delays cognitive decline and improves QOL-AD in patients with mild-to-moderate AD. Educational attainment, lifestyle factors, and cognitive reserve are key determinants of CST efficacy. Relevant institutions should develop targeted enhancement protocols for patients with lower educational levels or insufficient cognitive reserves when implementing CST.Trial RegistrationChinese Clinical Trial Registry, identifier ChiCTR2600118654, https://www.chictr.org.cn.
