Ly et al. developed a spatial in situ hybridization approach using TCR variable-gene probes to map T cell clonality and phenotype at single-cell resolution. By applying this technique to autoimmune kidney biopsies, they found that expanded T cells form localized clusters near antigen-presenting cells, consistent with local activation and proliferation.
There are certain laws of physics that heat must follow.
Take Kirchhoff’s law of thermal radiation, for example, which applies the idea of reciprocity to heat, and dictates that a surface’s ability to absorb heat at a specific angle and wavelength must also match its ability to emit heat at the same angle and wavelength.
It’s a rule that makes thermal energy difficult to control in ways we might like to, and although workarounds have been found before, they’re inefficient and volatile.
An experiment showed AI users had the most creative ideas when they used it in moderation – not too much and not too little. Columnist David Robson puts the finding to the test, and explores what we lose when we over-rely on AI
By David Robson
In the current issue of the journal Nature Methods, siibra is introduced as a software suite that integrates data from different multimodal sources into a comprehensive atlas of the human brain and makes the data easily accessible—for interactive exploration and automated, reproducible data analyses, simulations and AI applications. siibra is developed by an international team of scientists led by the Institute of Neuroscience and Medicine (INM-1) at Forschungszentrum Jülich.
To better understand the human brain, information from various levels must be integrated, from molecules and cells to their organization and entire networks. A central challenge is that these data are often scattered across sources and organized differently. They originate from methods such as microscopy, MRI and connectivity analysis; exist in formats ranging from images to tables; and rely on different spatial reference systems and conceptual taxonomies.
“Using siibra, we are now able to access and analyze brain data in a structured way from micro-to macrolevels—for more precise neuroscience studies, bio-inspired AI and clinical applications such as deep brain stimulation,” says Dr. Timo Dickscheid, working group leader for “Big Data Analytics.”
Mysterious high-speed “bullets”—clumps of possibly oxygen-rich gas traveling at up to 20 million miles per hour—have been discovered shooting out of the rarest stellar explosion in our galaxy.
They were spotted after a cloud of debris surrounding the Milky Way’s only known helium nova finally cleared after more than 20 years, revealing that an unusual stellar system was to blame for the extraordinary explosion.
But the origin of the “bullets” is an enigma that has left astronomers puzzled—nothing of their kind has ever been observed in other novae throughout the universe.
Seizures can race through the brain in seconds, making them difficult to capture in detail. To overcome this challenge, researchers have developed a new high-resolution light-sheet imaging system that is fast enough to image seizure propagation in the brain of a larval zebrafish in 3D.
“We developed a light-sheet microscope that allows rapid volumetric imaging with real-time correction of aberrations—imperfections in the way a microscope forms an image,” said research team leader Peter Kner from the University of Georgia. “Most imaging of seizure events in zebrafish has only captured 2D images, but our system allows 3D high-resolution imaging over a larger volume than was previously possible.”
In their article published in the journal Biomedical Optics Express, the researchers show that their new microscopy system can capture volumes up to 499 × 499 × 150 microns3 at a rate of four volumes per second with near-diffraction-limited resolution. They used the system to observe how seizures spread through the nervous system in zebrafish larvae, which are commonly used in neuroscience research.
