Tag: News Approved

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The Download: an organ transplant breakthrough, and homegrown Chinese chips

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.

Supercooled kidneys have been transplanted into pigs in a “landmark achievement” 

When it comes to organ donation, time is everything. As soon as an organ has been removed from a donor’s body, it starts to deteriorate. Surgeons have only a matter of hours to get it into a recipient.

In most cases, organs will be kept on ice during that time, at around 4 °C (39 °F). They cannot be frozen—in previous attempts, ice has formed, causing all kinds of damage.

But now, scientists have come up with a device that allows organs to be cooled to -4 °C (25 °F) without forming any ice. They’ve tested it with pig organs and shown that kidneys, at least, can be preserved in the device for days then successfully transplanted. 

Read our story about their breakthrough, and why it raises hopes for longer-term storage of donated human organs.

—Jessica Hamzelou

If you want to read more about this story and its implications for organ preservation and transplantation, sign up to receive The Checkup, our weekly biotech newsletter, later today.

The must-reads

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

1 Inside China’s epic push to replace US chips 
The gap between their chips’ capabilities remains large—for now. (WSJ $)
+ How China is using open source AI as a new form of soft power around the globe. (NYT $)
+ A new bill in the US takes aim at Chinese AI companies’ training practices. (NBC)
+ US lawmakers are also mulling banning the military from using Chinese humanoid robots. (SCMP)

2 Space data centers don’t exist yet, but people already oppose them
Environmental experts warn it’ll further pollute the stratosphere. (Guardian)
+ Four things we’d need to put data centers in space. (MIT Technology Review)
+ What it’s like inside the data centers powering AI down here on Earth. (Axios)
+ The left and right are finding common cause with data center protests in the US. (The Verge)

3 US lawmakers are pushing for an AI ‘kill switch’
After OpenAI’s models went rogue and hacked Hugging Face. (BBC)

4 Peptides seem on the cusp of going mainstream in the US
A lack of scientific evidence didn’t stop the FDA just voting to let some pharmacies to legally dispense them. (Wired $)
+ How does Make America Healthy Again hold up to scientific scrutiny? (Nature)
+ US measles cases are reaching levels not seen for three decades. (Wired $)
+ Peptides are everywhere. Here’s what you need to know. (MIT Technology Review)

5 The EU just fined Google almost $1 billion
For competition breaches over apps and search. (FT $)
+ It came just a day before Trump renewed tariffs on 60 trading partners, including the EU. (BBC)

6 Electric vehicles are selling well in Europe
And the share made by Chinese firms has doubled in the last year. (The Next Web)
+ Hybrids are hot property in the US this summer. (Wired $)

7 There’s a worsening shortage of computer science professors
You can blame AI companies—they keep snapping them up, to our general detriment. (The Atlantic $)

8 A judge caught a stenographer allowing AI errors into their transcript 
It’s apparently the first time this has happened, but it certainly won’t be the last. (404 Media)
+ Even judges themselves are falling for AI. (MIT Technology Review)

9 Here’s what new tech millionaires will do with their IPO wealth ?
What a nice problem to have to grapple with! (Quartz $)

10 Dating apps’ latest wheeze? In-person events 
Well well well, it seems we’ve come full circle. (Bloomberg $)

Quote of the day

“Call us optimists, call us dreamers. Just as we’ve always done, we’re betting on people.” 

—The voiceover from a new advert from Meta, which exhorts us to be more optimistic about AI.

One More Thing

bird on a branch

BELL HUTLEY


AI is changing how we study bird migration

In a warming world increasingly full of human infrastructure that can be deadly to them, like glass skyscrapers and power lines, migratory birds are facing many existential threats. 

Scientists rely on a combination of methods to track the timing and location of their migrations, though each has shortcomings. But now, machine-learning tools are unlocking a treasure trove of acoustic data for ecologists. 

Read our story about the technology that’s making it easier to detect and identify birds and their movements.

—Christian Elliott

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.)

+ It’s never too late to live your dreams. Here’s how these late bloomers did it.
+ Limbs feeling a bit tight? Try these stretches!
+ These English football fans went to the 1986 World Cup—and loved it so much they never came home.
+ How the invention of the humble paint tube revolutionized the world of art.

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Machine learning methods evaluation for identification of cognitive phenotypes in multiple sclerosis and their MRI correlates

BackgroundCognitive impairment (CI) is common in multiple sclerosis (MS) yet poorly captured by conventional disability scales. Although neuropsychological assessment and magnetic resonance imaging (MRI) are routinely used separately, there is no simple clinically applicable framework integrating cognitive performance with structural brain changes to identify patients at increased risk of cognitive decline. Integrating neuropsychological testing with MRI-based atrophy metrics may yield clinically useful cognitive phenotypes with differential patterns of brain atrophy measures.MethodsData were collected from 79 patients with multiple sclerosis (PwMS) who underwent comprehensive neuropsychological assessment and brain MRI. Neuropsychological variables were subjected to a feature selection procedure based on variance and quartile coefficient of dispersion filtering, followed by Pearson correlation and mutual information (MI) analyses to generate reduced feature sets. These feature sets were used as input for unsupervised clustering with the Partitioning Around Medoids (PAM) algorithm to identify cognitive phenotypes. Differences between the resulting groups in the degree of brain atrophy measures were subsequently evaluated using appropriate statistical tests—one-way ANOVA or the Kruskal–Wallis test. Post hoc analysis was performed using a pairwise t-test, Welch’s t-test, or Wilcoxon test with the Holm-Bonferroni correction, depending on the data distribution and variance.ResultsThe feature selection procedure based on variance and mutual information identified neuropsychological features that were subsequently used for clustering. Based on these features, the PAM algorithm identified three distinct groups of PwMS that differed in their clinical characteristics, degree of brain atrophy measures, and cognitive phenotype, ranging from preserved cognition to global cognitive impairment.ConclusionThree cognitive phenotypes with differential patterns of brain atrophy measures integrate neuropsychological testing with MRI measures into a clinically applicable framework that may help bridge the gap between structural imaging findings and everyday cognitive assessment in PwMS. This approach may improve screening, enable earlier detection of CI, improve monitoring, and provide valuable information for rehabilitation planning.
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Identification and validation of mitophagy and astrocyte-related molecular signature in the pathogenesis of Alzheimer’s disease: evidence from ensemble learning-driven multi-omics and clinical validation

BackgroundAlzheimer’s disease (AD) is a progressive neurodegenerative disorder with limited diagnostic tools and therapeutic options. Dysregulated mitophagy in astrocytes plays a pivotal role in AD pathogenesis. This study aims to identify a mitophagy and astrocyte (MA)-associated molecular signature for AD diagnosis and therapeutic targeting.MethodsLimma, WGCNA, xCell, PPI network and integrated machine learning pipeline coupled with SHAP were deployed on AD patient hippocampal bulk profiles (GSE28146, GSE36980, GSE29378, GSE48350) for identification of MA-associated predictive model and hub gene. Next, astrocyte patten and MA-associated hub gene molecular performance were estimated in hippocampal single-cell profile of AD patients (GSE163577) via advanced analytical frameworks. In addition, active learning framework and molecular docking was deployed in GSE29378 for identification of therapeutic candidate for AD patients by targeting MA-associated hub gene. Furthermore, AD hippocampal tissues were collected, and then MA-associated hub gene expression was estimated.ResultsA core 8-gene MA signature (ITSN1, VLDLR, CYP7A1, SREBF2, RASL12, TPMT, CYP4X1, ARHGEF) was identified, which can guide the molecular subgroup identification and predictive model construction for AD patients. ITSN1 can be considered as the MA-associated hub gene in AD pathogenesis, which was up-regulated and predominantly expressed in astrocytes. Drug repositioning identified BRD-K10008415 as the potential compound predicted to reverse the AD signature by targeting ITSN1.ConclusionsThis study identified ITSN1 as a MA-associated critical hub potential connecting mitophagy dysregulation and astrocyte dysfunction in AD. We also identified MA-associated molecular signatures that can potentially elaborate predictive effects on AD pathogenesis. BRD-K10008415 can be considered as potential candidate for AD treatment by targeting ITSN1.
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Identifying and investigating emergent behaviour in neural systems

The concept of emergence is key to understanding much of neurophysiology, neurodevelopment, and neurodegeneration. Many brain functions are underpinned by behaviour that emerges from interactions of components such as neurons, synapses, and glia. Perturbations such as ion channel mutations or trauma can lead to new types of, often detrimental, emergent behaviour. Typical approaches to neuroscience involve studying neural behaviour in a range of in vitro, in vivo, and in silico models designed to capture the key components of the brain region under investigation. Translating from these models back to the brain requires that the component interactions within the models can be mapped onto interactions in the brain. However, in many cases, this may not hold, leading to emergent behaviour that is not derivable from knowledge of the brain components in relative isolation. We thus need a framework that respects the prospective system-dependent differences in interactions. In this manuscript, we distil theoretical approaches to emergence into a practical framework for assessing system behaviour focussed on “novelty” as a necessary condition for emergence and identify a range of ways in which novelty can arise. We consider how different approaches for investigating system behaviour can be applied in different contexts and when these might fail. We provide examples of different forms of novelty in neuroscience contexts and then apply the framework to understanding the specific case of epilepsy. We end by outlining a set of guiding principles for designing experiments and models for understanding emergent behaviour in neural systems.
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Effects of music interventions on disorders of consciousness: a systematic review and meta-analysis

ObjectiveThe study aimed to systematically evaluate the effects of music intervention on outcomes related to the recovery of consciousness in patients with disorders of consciousness (DOC).MethodsDatabases including PubMed, Web of Science, Embase, the Cochrane Library, China National Knowledge Infrastructure (CNKI), and ProQuest were systematically searched from January 1970 to December 2025 to identify relevant randomized controlled trials (RCTs). The literature was screened based on pre-established inclusion and exclusion criteria, and the review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The methodological quality of the included studies was assessed using the Cochrane Risk of Bias tool (RoB 1).ResultsA total of 12 randomized controlled trials (RCTs) involving 926 patients with disorders of consciousness (DOC) were included. As the types of outcome indicators reported in the included studies varied, the number of studies included for each outcome also differed. Specifically, five studies were included in the analyses of Glasgow Coma Scale (GCS) scores and the GCS-based awakening rate, whereas two studies were included in the analyses of GCS scores of > 8, the Coma Recovery Scale-Revised (CRS-R), and the National Institutes of Health Stroke Scale (NIHSS). A meta-analysis showed that GCS scores were significantly higher in the music intervention group than in the control group (mean difference (MD) = 2.32). The analyses of GCS scores of > 8 showed that a higher proportion of patients in the music intervention group achieved a GCS score of > 8 (odds ratio (OR) = 5.98). The awakening rate also indicated that the music intervention group was significantly superior to the control group (OR = 3.76). For secondary outcomes, the music intervention group showed higher CRS-R scores (MD = 2.86) and lower NIHSS scores (MD = −1.24).ConclusionMusic intervention may help improve consciousness levels and awakening-related outcomes in patients with disorders of consciousness and may serve as a safe and non-invasive adjunctive measure in rehabilitation nursing care. However, more high-quality randomized controlled trials are needed to further verify its effects and mechanisms.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD420261354569, Identifier: CRD420261354569.
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The associations between emotional neglect and positive mental health: the mediating role of stress-is-enhancing mindset and the moderating role of stress-is-debilitating mindset

ObjectiveThis study aimed to investigate the associations among emotional neglect (EN), stress-is-enhancing mindset (SIEM), stress-is-debilitating mindset (SIDM), and positive mental health (PMH).MethodsThe cross-sectional survey was employed in this study. A sample of 2150 college students (826 males) completed the emotional neglect subscale of the Childhood Trauma Questionnaire Short Form, the Stress Mindset Measure and the Positive Mental Health Scale. The PROCESS macro version 4.2 for SPSS was used to examine the moderated mediation model.ResultsEN negatively predicted PMH (p < 0.001). SIEM mediated the association between EN and PMH. Moreover, SIDM (β = 0.04, p < 0.001) not merely moderated the relationship between EN and PMH, but also moderated the link between EN and SIEM (β = 0.04, p < 0.001).ConclusionEN has a direct negative link to PMH and an indirect negative link to PMH through SIEM. Importantly, high SIDM mitigates the direct negative relation between EN and PMH. Moreover, the indirect negative effects of EN on PMH via SIEM diminish as SIDM increases, and the mediation pathway of SIEM is neutralized under high SIDM. These findings preliminary reveal the interplay between SIEM and SIDM in post-traumatic cognitive processing, offering new insights into the non-linear processes of psychological adaptation following early adversity.
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Cross-national comparisons of adolescent mental health and suicidality in the Middle East: a cross-sectional secondary analysis of the global school-based student health survey

BackgroundAdolescent mental health and suicidality represent growing global public health concerns, yet comparative evidence from the Middle East remains limited. This study examined the prevalence and correlates of psychological distress and suicidal behaviors among adolescents across Middle Eastern countries using the Global School-based Student Health Survey (GSHS).MethodsA cross-sectional analysis of nationally representative GSHS datasets from 12 Middle Eastern countries collected between 2004 and 2017. The pooled sample included 90,573 school-attending adolescents aged 11–18 years. Multivariable logistic regression models assessed associations between psychosocial factors and suicidal behaviors while adjusting for age, sex, and country.ResultsSubstantial cross-country variation in mental health indicators and suicidality was observed. Loneliness ranged from 11.5% in Bahrain to over 50.0% among female adolescents in Tunisia and Morocco. Suicidal ideation affected 16.3% of adolescents overall, while suicide planning was reported by 13.4%. Suicide attempts were reported by 9.1% of adolescents at least once. Female adolescents consistently reported higher levels of loneliness and anxiety, whereas males showed slightly higher adjusted odds of suicidal ideation and attempts (OR = 1.2). Lack of parental support, low school connectedness, and fewer friendships were significantly associated with higher odds of suicidal ideation, planning, and attempts. Emotional symptoms such as loneliness (OR = 1.7) and anxiety (OR = 1.8) were also strongly associated with suicide attempts.ConclusionsPsychological distress and suicidality are prevalent among adolescents across the Middle East, with notable gender and cross-country differences. Strengthening family support, peer relationships, and school connectedness should be central to regional adolescent mental health and suicide prevention strategies.
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From emotion regulation to suicide-specific coping: a qualitative study of self-regulatory processes in suicidal crises

IntroductionNegative affect is strongly associated with suicidal thoughts and behaviors (STBs). Accordingly, the ability to regulate intense negative affective states may be central to understanding the emergence and maintenance of STBs. However, very little is known about how individuals with lived experience regulate negative affect and cope with suicidal thoughts and urges. This study aimed to explore emotion-regulation strategies (ERS) and suicide-specific coping strategies (SCS) used during suicidal crises, their perceived effectiveness, and the situational and contextual factors influencing their selection.MethodsSemi-structured interviews were conducted with 12 individuals admitted to a psychiatric hospital due to an acute suicidal crisis. Data were analyzed using qualitative content analysis.ResultsBefore and during suicidal crises, participants predominantly used avoidance-oriented ERS that contributed to the maintenance of negative affect. With increasing distress, suicidal thoughts emerged as an additional ERS, providing short-term relief while contributing to the intensification of the suicidal crisis over time. A broad range of SCS was identified, differing in their motivational orientation toward suicidal behavior. Suicide-approach strategies (e.g., suppression, substance use, preparatory behaviors) often facilitated the escalation of the suicidal crisis, whereas suicide-avoidant strategies (e.g., seeking support, safety strategies) were context-dependent and not consistently effective. Strategy selection and effectiveness were shaped by situational and contextual factors.ConclusionSuicidal crises can be understood as dynamic, context-dependent self-regulatory processes characterized by escalating emotional distress, changes in strategy use, and dynamic regulatory resources. Interventions should focus on strengthening flexible coping repertoires and preserving self-regulatory capacity. Future research should further investigate these processes to improve prevention and intervention efforts.
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Big Five personality profiles, self-reported distress, and resilience resources among adults in Italy after the acute COVID-19 emergency: a cross-sectional cluster-analytic study

IntroductionPsychological recovery after the acute COVID-19 emergency has been uneven, and brief non-diagnostic markers that stratify vulnerability may support public mental health monitoring. We examined whether person-centered Big Five profiles differentiated self-reported distress and resilience resources among adults living in Italy after the end of the World Health Organization-declared COVID-19 public health emergency.MethodsThis cross-sectional anonymous online survey included 2,169 adults assessed between 22 May 2023 and 23 December 2024. Participants completed the Big Five Inventory-10 (BFI-10), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), Perceived Stress Scale-10 (PSS-10), and Resilience Scale for Adults-11 (RSA-11). Standardized Big Five scores were clustered using k-means, and the number of profiles was evaluated using elbow, silhouette, and hierarchical-clustering methods.ResultsA two-profile solution was retained, although separation was modest (average silhouette width = 0.185). Compared with the resourceful trait profile (n = 1,113), the vulnerable trait profile (n = 1,056), characterized especially by lower emotional stability and conscientiousness, reported higher anxiety symptoms (g = 0.74), depressive symptoms (g = 0.76), and perceived stress (g = 0.86), and lower resilience resources (g = −1.02; all p < 0.001).DiscussionBrief person-centered Big Five profiling differentiated adults with greater self-reported symptom burden and fewer resilience resources in a prolonged post-emergency context. These findings are non-diagnostic and do not establish COVID-specific causal mechanisms, but may inform vulnerability stratification during future prolonged crises.