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From cognitive abstraction to adaptive behavior: neural bases of concept learning in autistic adolescents

Learned knowledge does not consistently generalize to new contexts in autistic individuals, limiting potential for adapting to real-world demands. This challenge is hypothesized to stem from difficulties with forming abstract representations, potentially arising from perceptual processing that favors local details over the gestalt. We tested the prediction that generalization would be primarily based on exemplar-specific representations in autistic youth using computational modelling coupled with neuroimaging.

Sixty-four autistic adolescents without intellectual disability (69% males; ages 14–18 years) completed a category generalization task during functional magnetic resonance imaging at two time points. Computational models estimated abstract (prototype-based) and specific (exemplar-based) representations and underlying neural correlates. We further examined associations with adaptive functioning and moderation by autistic traits.

Contrary to predictions, we observed a consistent prototype-dominant majority, a subgroup who generalized without consistent representational reliance, and a small minority who failed to acquire category structure. Neural prototype correlates were observed in bilateral ventromedial prefrontal cortex (VMPFC), inferior parietal lobule (IPL), right frontal pole, and right lateral occipital cortex, while neural exemplar correlates were observed in bilateral cuneus. Better generalization predicted better real-world adaptive functioning. Moreover, greater prototype-related activation in left IPL predicted better adaptive functioning in participants with higher autistic traits.

This Hand-Cranked Device Can Tell You Your Blood Type And Red Cell Levels in a Minute

Medical emergencies aren’t always considerate enough to happen close to hospitals or clinics, and all the professional equipment and trained staff that go along with them.

Now researchers led by a team from the National Taiwan University have developed a hand-cranked device that can be operated by anyone, anywhere, without a power source – and which can reveal blood type and red blood cell levels in a sample within a minute.

Those are two crucial pieces of information that medics and doctors often need to know quickly about patients when an emergency happens. All that’s needed is a tiny drop of blood for analysis. Details of the device and its promising early tests have been published in Biosensors and Bioelectronics.

AI vibe coding changes a local man’s life path

CTV’s Krista Sharpe-Kilpatrick finds out how a man went from driving a forklift to a booming tech career.

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Nanoparticle properties shape protein coats that guide cell entry and immune evasion

A new study has revealed molecular rules governing how nanoparticles interact with biological systems, showing how their physicochemical properties shape protein corona (PC) formation and influence biological outcomes. The findings provide a framework for designing nanomedicines with more predictable biological identities.

The study was conducted by a research team led by professor Liu Yuan from the Hangzhou Institute of Medicine (HIM) of the Chinese Academy of Sciences (CAS). The findings were published in Proceedings of the National Academy of Sciences on Oct. 26.

Nanoparticles hold promise for precise drug delivery and modern therapeutics. Yet, how do nanoparticles interact with biological systems in vivo? For the past two decades, the PC has been regarded as a critical determinant of the fate of nanomedicines in vivo, but it has been studied largely through empirical descriptions rather than generalizable molecular rules. Therefore, a central challenge is to determine how a nanoparticle’s physicochemical properties influence its corona to drive distinct biological outcomes.

Two paths, one flux: Trapped ions simulate Aharonov–Bohm interference in a lattice gauge theory

In a new Nature Physics study, researchers demonstrated the Aharonov-Bohm effect in a quantum simulation of a lattice gauge theory using a hybrid trapped-ion quantum computer.

Gauge theories describe how matter interacts through fields called gauge fields, which carry the electromagnetic, weak and strong forces. They form the basis of the Standard Model of particle physics. In lattice gauge theories, space is modeled as a grid with matter at the vertices and gauge fields on the links connecting them.

Quantum simulators offer a way to study these theories. However, most quantum simulations of the simplest version—the Z₂ lattice gauge theory—have been limited to one spatial dimension, where effects linked to magnetic flux cannot appear.