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The Download: making drugs in orbit and NASA’s nuclear-powered spacecraft

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 plan to make drugs in orbit is going commercial

A startup called Varda Space Industries is betting that the future of pharmaceuticals lies in orbit. The company has signed a deal with United Therapeutics to test whether drugs crystallize differently in microgravity, potentially creating improved versions with new properties.

The idea sounds futuristic, but falling launch costs and reusable rockets are making space-based manufacturing seem increasingly plausible. Varda says the partnership could mark an important step toward building products in orbit for use back on Earth.

Discover how space could become the next frontier for drug development.

—Antonio Regalado

MIT Technology Review Narrated: NASA is building the first nuclear reactor-powered interplanetary spacecraft. How will it work?

Just before Artemis II began its historic slingshot around the moon, NASA revealed an even grander space travel plan. By the end of 2028, the agency aims to fly a nuclear reactor-powered interplanetary spacecraft to Mars.

A successful mission would herald a new era in spaceflight—and might just give the US the edge in the race against China. But the project remains shrouded in mystery.

MIT Technology Review picked the brains of nuclear power and propulsion experts to find out how the nuclear-powered spacecraft might work.

—Robin George Andrews

This is our latest story to be turned into an MIT Technology Review Narrated podcast, which we publish each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released.

The must-reads

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

1 Sam Altman claims Elon Musk tried to seize control of OpenAI
Altman said Musk initially wanted 90% of the equity. (AFP)
+ And that control should go to his children when he dies. (BBC)
+ Altman also accused Musk of twice trying to end its non-profit status. (NPR)
+ Musk’s motivations for the suit are under scrutiny. (MIT Technology Review)

2 Google and SpaceX are in talks to launch data centers into orbit
SpaceX could join Suncatcher, Google’s orbital data center project. (WSJ $)
+ The project’s first launch is slated for early 2027. (Guardian)
+ Anthropic and SpaceX have also discussed orbital data centers. (Wired $)
+ But there are a few hurdles to overcome. (MIT Technology Review) 

3 Jensen Huang has joined Donald Trump’s high-stakes mission to China
Nvidia is lobbying to sell its AI chips in the country. (Bloomberg $)
+ Elon Musk and Tim Cook are also on the trip. (CNBC)
+ But a tech rivalry and distrust have sapped hopes for big deals. (Reuters $)

4 ICE agents have a list of 20 million people on their iPhones, thanks to Palantir
An ICE official said Palantir is speeding up raids and arrests. (404 Media)
+ ICE has also used facial recognition and Paragon spyware. (TechCrunch)

5 Defense tech firm Anduril just doubled its valuation to over $60 billion
In a $5 billion funding round led by Thrive Capital and a16z. (FT $)
Anduril, which makes AI-backed weapons, may go public next year. (NYT $)

6 Meta employees are protesting computer-tracking at work
Flyers posted at offices are urging staff to oppose the program. (Reuters $)
+ Meta plans to track workers’ clicks and keystrokes to train AI. (CNBC)

7 OpenAI is facing another wrongful death lawsuit over ChatGPT medical advice
The chatbot’s tips allegedly led to a teenager’s overdose. (Ars Technica)

8 The Canvas learning platform has paid hackers to delete stolen student data
It caved to ransomware demands after the biggest-ever edtech breach. (BBC)

9 Scientific researchers are thinking twice about using AI
Due to price hikes, usage limitations, and unreliable outputs. (Nature)

10 The latest AI compute solution? Putting data centers in your home
Hardware hosts get subsidized electricity and internet. (Ars Technica)

Quote of the day

“Mr Musk did try to kill it.”

—Sam Altman claims that Elon Musk tried to destroy rather than protect OpenAI’s non-profit operations, the Guardian reports.

One More Thing

ASCII image of a head with the text, "How can I help you today?"

YOSHI SODEOKA


Why does AI hallucinate?

Chatbot fails are now a familiar meme. Meta’s short-lived scientific chatbot generated wiki articles about the history of bears in space. Lawyers have submitted court documents filled with legal citations fabricated by ChatGPT. Air Canada was ordered to honor a refund policy invented by its customer service chatbot.

This tendency to make things up—known as hallucination—is one of the biggest obstacles holding chatbots back from more widespread adoption. Here’s why they do it—and why we still can’t fix it.

—Will Douglas Heaven

This story is part of MIT Technology Review Explains, our series untangling the complex, messy world of technology to help you understand what’s coming next. You can read more from the series here. 

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.)

+ A historian has unearthed the etymology of every single dinosaur name.
+ Humus on the moon is getting closer to reality after scientists grew chickpeas in lunar soil.
+ Witness the patience of a master paper artist in this gallery of intricate, handmade sculptures.
+ Want to tell the time alphabetically? Me neither, but this cursed clock is an intriguing reason to try.

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Roles of NRXN1 in neuropsychiatric disorders: from genetic lesion to molecular mechanism

Numerous neuropsychiatric disorders frequently exhibit overlapping genetic risk factors, implying the molecular basis for their comorbidity. Nevertheless, the pathogenesis of these disorders remains elusive, particularly regarding how genetic variations impair the physiological function of risk genes and contribute to disease phenotypes. Neurexin 1 protein, encoded by NRXN1 gene, belongs to the neurexin family of presynaptic adhesion molecules. And neurexin 1 is involved in synaptogenesis and the maintenance of synaptic action. Genetic variations of NRXN1 have been demonstrated to be associated with a spectrum of neuropsychiatric disorders. Herein, this review focuses on the most recent and relevant literature concerning the genetic and molecular mechanisms through which NRXN1 variants contribute to the pathogenesis of neuropsychiatric disorders, particularly schizophrenia and autism spectrum disorder. Among them, we propose the isoform-dependent excitation-inhibition imbalance hypothesis of NRXN1 in autism spectrum disorder. And this hypothesis may account for both the elevated and decreased excitation-inhibition ratios observed in diverse individuals with autism spectrum disorder. Moreover, both schizophrenia and autism spectrum disorder involve deletions and alternative splicing of NRXN1, offering molecular evidence for their comorbidity. Then, we analyzed and summarized the current research status of NRXN1 in other neuropsychiatric disorders, including attention-deficit hyperactivity disorder, insomnia, epilepsy, suicide, and depression. Additionally, available limited researches on NRXN1-targeted therapeutic strategies and associated pharmacological studies are also incorporated. Finally, we discussed existing challenges in NRXN1 research within the context of neuropsychiatric disorders and proposed potential avenues to overcome these obstacles.
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Direct modulation of human GABA-A α1β2γ2 receptors by the endocannabinoid 2-arachidonoylglycerol: implications for cannabinoid-related ligands and limitations for anxiolytic drug development

Anxiety disorders are associated with impaired inhibitory neurotransmission mediated by γ-aminobutyric acid type A (GABA-A) receptors. Although benzodiazepines remain effective anxiolytics, their clinical utility is limited by sedation, cognitive impairment, tolerance, and dependence, prompting the search for mechanistically distinct GABAergic modulators. Among cannabinoid-related molecules, the strongest evidence for direct GABA-A receptor modulation concerns the endocannabinoid 2-arachidonoylglycerol (2-AG), which potentiates recombinant human α1β2γ2 receptors through residues located in the M4 helix of the β2 subunit. Here, we review the structural architecture, biophysical properties, and pharmacological profile of the human GABA-A α1β2γ2 isoform as the relevant molecular framework for evaluating this mechanism, while discussing the broader relevance of cannabinoid-related ligands and selected phytocannabinoids without assuming mechanistic equivalence. We further assess the hypothesis that 2-AG reaches the β2-M4 site through a membrane-access route and identify five conceptual barriers that currently limit translation of this mechanism into anxiolytic drug development: supraphysiological effective concentrations, unresolved synaptic-versus-extrasynaptic actions, uncertain subtype selectivity, incomplete validation of lipid-environment effects, and lack of clinical evidence linking this mechanism to anxiolysis in humans. We conclude that direct modulation through β2-M4 defines a mechanistically intriguing allosteric pathway distinct from benzodiazepine action; however, its location on a shared β2 subunit and the micromolar concentrations required for modulation represent substantial obstacles to the rational design of anxioselective agents based on this mechanism.
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Federated training of spiking neural networks on edge hardware for audio processing

Spiking Neural Networks have caught significant attention recently for their potential for energy-efficient computation on neuromorphic hardware and their event-driven processing. Spiking Neural networks employ spike-based learning paradigms, which require specialized training procedures such as Surrogate Gradient Descent. At the same time, Federated Learning allows collaborative model training on decentralized devices with preservation of data privacy protection. However, to date, few research has examined the suitability of Federated learning with ARM-based hardware. This work primarily investigates whether Federated Spiking Neural Networks training on ARM-based hardware is feasible with the Raspberry Pi 5 as a widely available and low-cost edge computing device for audio signal processing tasks. We perform a comparative analysis of federated Spiking Neural Network and federated convolutional neural networks on ARM processors and evaluate their performance on different data partitioning strategies using Dirichlet-based splits and various federated averaging algorithms. Using Federated learning, this work investigates the impact of data heterogeneity and aggregation strategies on model convergence, communication overhead, and latency in distributed training paradigms. The results provided showcases the important insights into the trade-offs of FL-SNN implementations on Von Neumann architectures and their applications in decentralized neuromorphic computing for audio processing.
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Assessing directional connections between symptoms, cognition, insight, and real-life functioning in schizophrenia: a partial ancestor graphs analysis

IntroductionSchizophrenia is a severe chronic mental disorder causing significant global disability. Understanding the intricate relationships between symptoms, cognitive functions, and real-life outcomes is essential for developing effective interventions. Prior research, while informative, could not often determine the direction of the association between these illness-related factors. This study aimed to investigate the possible causal connections within the interrelationships of these variables. MethodsThis cross-sectional study included 215 clinically stable patients diagnosed with schizophrenia. Comprehensive assessments covered psychopathology, neurocognition, social cognition, metacognition, clinical insight, and real-life functioning. Causal relationships were explored using Partial Ancestral Graphs, a causal discovery framework that accounts for mediators and confounders. The Greedy Fast Causal Inference algorithm was employed with 1,000 bootstrap replications to assign edge orientations.ResultsA central neurocognitive–metacognitive–functional system of directed connection emerged: visual learning was linked to attention/vigilance and working memory. Working memory showed a direct relationship with metacognition, which, in turn, was connected to real-life functioning. Two partly independent contributions to real-life functioning were also identified: conceptual disorganization and experiential negative symptoms, which were directly related to expressive deficits. Positive symptoms, depressive symptoms, and social cognition occupied peripheral positions, showing no significant connection with other variables. Unawareness and misattribution of symptoms showed an indeterminate association disconnected from the main network.DiscussionThe findings show a set of directed associations that start with neurocognitive abilities, pass through working memory and metacognition, and terminate in real-life functioning. Independently, conceptual disorganization and expressive negative symptoms also exert direct influences. These directed systems of connections provide operational guidance for clinical practice, highlighting critical targets for interventions such as cognitive remediation focused on working memory, metacognitive therapies, and strategies addressing disorganization and avolition, all aimed at improving real-life outcomes in schizophrenia.
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Romanian male patients with the dual diagnosis of schizophrenia and alcohol use disorder: a prospective study of clinical, social, and treatment-related factors affecting quality of life

BackgroundSchizophrenia frequently co-occurs with alcohol use disorder (AUD), resulting in a complex clinical profile associated with poor functional outcomes and reduced quality of life (QoL). Although both conditions independently impair psychosocial functioning, few studies have examined the combined effects of clinical, social, and treatment-related factors on QoL in patients with this dual diagnosis.MethodsThis prospective observational study included 88 male inpatients diagnosed with schizophrenia and comorbid AUD and who were followed over a 6-month period. Quality of life was assessed using the World Health Organization Quality of Life–BREF (WHOQoL–BREF). The clinical variables included severity of psychotic symptoms (Positive and Negative Syndrome Scale), alcohol use severity (Michigan Alcohol Screening Test), and treatment characteristics. Social and personal factors, such as self-care capacity, social support, education, and legal problems, were also evaluated. Multivariable regression analyses were conducted to identify predictors of QoL at baseline and follow-up.ResultsAt baseline, higher QoL was significantly associated with greater self-care capacity, social support, and higher positive symptom scores, while the need for antipsychotic treatment was associated with lower QoL. At the 6-month follow-up, better QoL was predicted by greater self-care capacity, higher educational level, and receipt of anti-craving medication. By contrast, negative and general psychopathology, medico-legal problems, and the need for antidepressant treatment were associated with poorer QoL. Alcohol use severity, as measured by the MAST, was not independently associated with QoL at either timepoint.ConclusionsIn patients with schizophrenia and comorbid AUD, QoL is shaped by a complex interaction of clinical severity, functional capacity, and treatment-related factors. Beyond symptom control, interventions targeting self-care, social functioning, and integrated addiction treatment appear essential to improve long-term outcomes. These findings support the implementation of a multidimensional, recovery-oriented approach for the management of patients with the dual diagnosis.
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Internalizing and externalizing pathways to internet gaming disorder: the roles of anger and social anxiety

BackgroundInternet Gaming Disorder (IGD) represents a significant behavioral health concern, yet the roles of internalizing and externalizing psychological vulnerabilities in its development remain underexplored, particularly in Arabic-speaking populations.ObjectiveThis study examined anger and social anxiety as distinct externalizing and internalizing predictors of IGD severity in a Saudi Arabian community sample.MethodsA cross-sectional survey was administered to 303 participants (60.1% female; estimated mean age = 29.79 years, SD = 8.83) across five regions of Saudi Arabia. Participants completed the Internet Gaming Disorder Scale–Short Form (IGDS9-SF), a three-item Anger Screening Scale, and a two-item Social Anxiety screener. Hierarchical linear regression and structural equation modeling (SEM) were conducted to examine unique and incremental contributions of anger and social anxiety to IGD symptoms.ResultsAnger and social anxiety were strongly intercorrelated (r = .86, p <.001) but demonstrated divergent patterns in multivariate models. Hierarchical regression indicated that both predictors contributed unique variance when entered simultaneously, with anger positively and social anxiety negatively predicting IGD after controlling for shared variance. However, SEM clarified that only social anxiety significantly predicted latent IGD severity (β = .32, p = .027), whereas anger did not (β = .07, p = .68). The final model explained approximately 13% of variance in IGD symptoms.ConclusionsSocial anxiety was associated with IGD severity as a distinct internalizing correlate, consistent with avoidance-based coping and online social preference accounts. These preliminary, cross-sectional findings suggest that social anxiety warrants consideration in future IGD screening and research efforts in Arabic-speaking contexts.
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Perception of social support and psychological well-being among mothers of individuals with intellectual disabilities: the mediating role of self-efficacy

BackgroundThe aim of this study is to examine the mediating role of self-efficacy in the relationship between social support perception and psychological well-being among mothers of individuals with intellectual disabilities.MethodsA correlational survey model was used in this study in line with the research objectives. The study group consisted of mothers of individuals with intellectual disabilities (n=80) in two central districts of Malatya province. Convenience sampling was employed in the study. The Psychological Well-being Scale was used to measure the psychological well-being of the participating mothers, the “Perceived Support Scale for Families of Children with Disabilities” was used to measure their perceived levels of social support, and the “Parental Self-Efficacy Scale” was used to measure their self-efficacy. In addition, a personal information form was used to introduce the socio-demographic characteristics of the participants. Descriptive statistics were calculated for the variables, and the normality assumption was examined using the Kolmogorov-Smirnov and Shapiro-Wilk tests. The relationships between the variables were evaluated using Pearson’s product-moment correlation analysis. Mediation analyses were performed using the PROCESS Macro (Model 4) developed by Hayes, and the significance of indirect effects was tested using the bootstrap method (5000 samples). The internal consistency reliability of the scales used in this study sample was assessed using Cronbach’s alpha coefficient.ResultsThere are positive and significant relationships between each of the perceived social support sub-dimensions of appreciation, informational, emotional, and companionship and self-efficacy (r = 0.28–0.36; p <0.05). A positive and significant relationship was also found between the total perceived social support score and self-efficacy (r = 0.37, p <0.01). In contrast, no direct significant relationships were found between perceived social support and its sub-dimensions and psychological well-being (p> 0.05). Psychological well-being showed only a moderate, positive and significant relationship with self-efficacy (r = 0.45, p <0.01).ConclusionsIn conclusion, it can be said that the relationship between perceived social support and psychological well-being is not direct, but indirect, mediated by self-efficacy.
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From cats to cortex: T. gondii and psychosis, depression, and anxiety

This review examines whether cat ownership, via exposure to the neurotropic parasite T. gondii, contributes to vulnerability for psychotic, depressive, and anxiety symptoms. T. gondii establishes lifelong latent infection in the brain and muscle, where it can modulate dopaminergic signaling, neuroinflammation, and tryptophan–kynurenine metabolism, providing a biologically plausible pathway to altered cognition, mood, and behavior. Epidemiological and meta-analytic data indicate small-to-moderate associations between T. gondii seropositivity and schizophrenia, with more variable but suggestive links to depression and anxiety. Evidence for cat ownership as an independent risk factor is inconsistent: some cohorts and recent meta-analyses report elevated odds of schizophrenia-related outcomes in those exposed to cats, whereas rigorously controlled studies frequently find attenuated or null effects. Methodological limitations, alternative explanations, and cultural implications are discussed, and priorities for mechanism-informed, longitudinal and interventional research are outlined.