In mice, engineered immune cells shrink pancreatic and other tumours bearing a mutant version of the KRAS protein.
Physicists at the University of Oxford have successfully simulated how light interacts with empty space – a phenomenon once thought to belong purely to the realm of science fiction. The simulations recreated a bizarre phenomenon predicted by quantum physics, where light appears to be generated from darkness. The findings pave the way for real-world laser facilities to experimentally confirm bizarre quantum phenomena. The results have been published in Communications Physics.
Using advanced computational modelling, a research team led by the University of Oxford, working in partnership with the Instituto Superior Técnico in the University of Lisbon, has achieved the first-ever real-time, three-dimensional simulations of how intense laser beams alter the ‘quantum vacuum’ – a state once assumed to be empty, but which quantum physics predicts is full of virtual electron-positron pairs.
Excitingly, these simulations recreate a bizarre phenomenon predicted by quantum physics, known as vacuum four-wave mixing. This states that the combined electromagnetic field of three focused laser pulses can polarise the virtual electron-positron pairs of a vacuum, causing photons to bounce off each other like billiard balls – generating a fourth laser beam in a ‘light from darkness’ process. These events could act as a probe of new physics at extremely high intensities.
Facial morphology is a distinctive biometric marker, offering invaluable insights into personal identity, especially in forensic science. In the context of high-throughput sequencing, the reconstruction of 3D human facial images from DNA is becoming a revolutionary approach for identifying individuals based on unknown biological specimens. Inspired by artificial intelligence techniques in text-to-image synthesis, it proposes Difface, a multi-modality model designed to reconstruct 3D facial images only from DNA. Specifically, Difface first utilizes a transformer and a spiral convolution network to map high-dimensional Single Nucleotide Polymorphisms and 3D facial images to the same low-dimensional features, respectively, while establishing the association between both modalities in the latent features in a contrastive manner; and then incorporates a diffusion model to reconstruct facial structures from the characteristics of SNPs. Applying Difface to the Han Chinese database with 9,674 paired SNP phenotypes and 3D facial images demonstrates excellent performance in DNA-to-3D image alignment and reconstruction and characterizes the individual genomics. Also, including phenotype information in Difface further improves the quality of 3D reconstruction, i.e. Difface can generate 3D facial images of individuals solely from their DNA data, projecting their appearance at various future ages. This work represents pioneer research in de novo generating human facial images from individual genomics information.
(Repost)
This study has introduced Difface, a de novo multi-modality model to reconstruct 3D facial images from DNA with remarkable precision, by a generative diffusion process and a contrastive learning scheme. Through comprehensive analysis and SNP-FACE matching tasks, Difface demonstrated superior performance in generating accurate facial reconstructions from genetic data. In particularly, Difface could generate/predict 3D facial images of individuals solely from their DNA data at various future ages. Notably, the model’s integration of transformer networks with spiral convolution and diffusion networks has set a new benchmark in the fidelity of generated images to their real images, as evidenced by its outstanding accuracy in critical facial landmarks and diverse facial feature reproduction.
Difface’s novel approach, combining advanced neural network architectures, significantly outperforms existing models in genetic-to-phenotypic facial reconstruction. This superiority is attributed to its unique contrastive learning method of aligning high-dimensional SNP data with 3D facial point clouds in a unified low-dimensional feature space, a process further enhanced by adopting diffusion networks for phenotypic characteristic generation. Such advancements contribute to the model’s exceptional precision and ability to capture the subtle genetic variations influencing facial morphology, a feat less pronounced in previous methodologies.
Despite Difface’s demonstrated strengths, there remain directions for improvement. Addressing these limitations will require a focused effort to increase the model’s robustness and adaptability to diverse datasets. Future research should aim to incorporating variables like age and BMI would allow Difface to simulate age-related changes, enabling the generation of facial images at different life stages an application that holds significant potential in both forensic science and medical diagnostics. Similarly, BMI could help the model account for variations in body composition, improving its ability to generate accurate facial reconstructions across a range of body types.
A model that includes propagating voids predicts the extent of plasma turbulence in a tokamak.
A hypothetical fifth force could be detected by its effect on the optical transition frequencies of an element’s different isotopes.
Scientists from the Natural History Museum have unraveled the geological mysteries behind jadarite, a rare lithium-bearing mineral with the potential to power Europe’s green energy transition which, so far, has only been found in one place on Earth, Serbia’s Jadar Basin.
Discovered in 2004 and described by museum scientists Chris Stanley and Mike Rumsey, jadarite made headlines for its uncanny resemblance to the chemical formula of Kryptonite, the fictional alien mineral which depletes Superman’s powers. However, today its value is more economic and environmental, offering a high lithium content and lower-energy route to extraction compared to traditional sources like spodumene.
A team of researchers at the museum have uncovered why this white, nodular mineral is so rare. Their findings show that to form, jadarite must follow an exact set of geological steps in highly specific conditions. This involves a strict interplay between alkaline-rich terminal lakes, lithium-rich volcanic glass and the transformation of clay minerals into crystalline structures which are exceptionally rare.
The Apollo astronauts didn’t know what they’d find when they explored the surface of the moon, but they certainly didn’t expect to see drifts of tiny, bright orange glass beads glistening among the otherwise monochrome piles of rocks and dust.
The beads, each less than 1 mm across, formed some 3.3 to 3.6 billion years ago during volcanic eruptions on the surface of the then-young satellite. “They’re some of the most amazing extraterrestrial samples we have,” said Ryan Ogliore, an associate professor of physics in Arts & Sciences at Washington University in St. Louis, home to a large repository of lunar samples that were returned to Earth. “The beads are tiny, pristine capsules of the lunar interior.”
Using a variety of microscopic analysis techniques not available when the Apollo astronauts first returned samples from the moon, Ogliore and a team of researchers have been able to take a close look at the microscopic mineral deposits on the outside of lunar beads. The unprecedented view of the ancient lunar artifacts was published in Icarus. The investigation was led by Thomas Williams, Stephen Parman and Alberto Saal from Brown University.
A popular 2D active material, molybdenum disulfide (MoS2), just got a platinum upgrade at an atomic level. A study led by researchers from the University of Vienna and Vienna University of Technology embedded individual platinum (Pt) atoms onto an ultrathin MoS2 monolayer and, for the first time, pinpointed their exact positions within the lattice with atomic precision.
The study, published in the journal Nano Letters, achieved this feat with an innovative approach that integrates targeted defect creation in the MoS2 monolayer, controlled platinum deposition, and a high-contrast computational microscopic imaging technique—ptychography.
The researchers believe that this new strategy for ultra-precise doping and mapping offers new pathways for understanding and engineering atomic-scale features in 2D systems.