Comprehensive reference genomes have now been assembled for six ape species: siamang (a Southeast Asian gibbon), Sumatran orangutan, Bornean orangutan, gorilla, bonobo and chimpanzee. Areas of their genomes previously inaccessible because of structural complexity have now mostly been resolved.  The resource is already lending itself to comparative studies that offer new insights into human and ape evolution, and into what underlies the functional differences among these species.  

By mapping the subcellular architecture and protein interactions within cells, researchers can better understand how mutations contribute to pediatric cancers and other conditions.

Utilizing numerical simulations, researchers have succeeded in recreating the fluid dynamics of flowing cells like blood or immune cells in the circulatory system. The team recreated the cells by programing them as deformable ‘capsules’ and placed them in a tube with a pulsating ‘flow.’ This in-silico model revealed that capsules will move to a specific position depending on two factors: the deformation of the capsule and the pulsation frequency.

Milky seas are a rare bioluminescent phenomenon where vast areas of the ocean glow at night, sometimes for months. This glow, likely caused by Vibrio harveyi bacteria, has been reported by sailors for centuries but remains poorly understood due to its rarity and remote locations, mainly in the Indian Ocean. Researchers at Colorado State University have compiled a 400-year database of sightings, using historical records and satellite data, revealing that milky seas are linked to climatic patterns like the Indian Ocean Dipole and El Niño.

A recent paper published in National Science Review presents a multi-space alignment approach for cross-species and cross-modality electroencephalogram (EEG) based epileptic seizure detection. By employing deep learning techniques, including domain adaptation and knowledge distillation, it aligns cross-species and cross-modality EEG signals to enhance the detection capability beyond traditional within-species and within-modality models. Experiments on multiple scalp and intracranial EEG datasets of humans and canines demonstrated substantial improvements in the detection accuracy, achieving over 90% AUC scores for cross-species and cross-modality seizure detection with extremely limited labeled data from the target species/modality. This is the first study that demonstrates the effectiveness of integrating heterogeneous data from different species and modalities to improve EEG-based seizure detection performance.