Scientists built a robot to help explain how a tropical bat spots insects perched on leaves using echolocation, a highly sophisticated behavior that requires precise, split-second decision-making on the part of the hunting bat. In a study published today in the Journal of Experimental Biology, a bat researcher at the Smithsonian Tropical Research Institute teamed up with two robotics engineers from the University of Cincinnati and the University of Antwerp, respectively, to provide the first plausible explanation for how the common big-eared bat (Micronycteris microtis) can efficiently determine whether a leaf is occupied by a silent insect amidst the dense, cluttered understory of the tropical rainforest using only sound.

Smoking tobacco is known to worsen symptoms of periodontitis and reduce responsiveness to treatment. Using high-resolution spatial transcriptomics, researchers identified differences between smokers and non-smokers in the expression of genes that weaken gum epithelial integrity and cause bone damage through inflammation. They also identified CXCL12 secreted by endothelial cells in gums as a crucial mediator of immune-cell recruitment that drives excessive inflammation. CXCL12 is a possible target for new therapies against periodontitis aggravated by smoking.

Cilk1 deficiency disrupts normal tooth development by altering primary cilia function and weakening Hedgehog signaling. This reduction triggers extra diastemal teeth, enlarges them under further signaling loss, and can ultimately cause molar fusion. Researchers propose a progressive model linking Hedgehog signaling levels to sequential changes in tooth patterning. The study highlights a previously unknown role for Cilk1 in shaping tooth morphology and improving understanding of developmental dental disorders in humans.

A team led by Prof. Richard GU Hongri, Assistant Professor in the Division of Integrative Systems and Design of the Academy of Interdisciplinary Studies at The Hong Kong University of Science and Technology (HKUST), in collaboration with experts in mechanical engineering and biomedicine, has developed an automated robotic nanoprobe. This device can navigate within living cell, sense metabolic whispers in real time, and pluck an individual mitochondrion for analysis or—all without the need for fluorescent labeling. It is the world’s first cell-manipulation nanoprobe that integrates both sensors and actuators at its tip, enabling a micro-robot to autonomously navigate inside live cells. The breakthrough holds great promise for advancing future treatment strategies for chronic diseases and cancer.

Led by Prof. ZHAO Ruilin from the Institute of Microbiology of the Chinese Academy of Sciences, researchers showed how climate dynamics and a key gene for adaptive evolution and domestication jointly shaped the button mushroom (Agaricus bisporus) 's diversity.

“We know the genes, but not their functions.” To resolve this long-standing bottleneck in microbial research, a joint research team has proposed a cutting-edge research strategy that leverages Artificial Intelligence (AI) to drastically accelerate the discovery of microbial gene functions.

KAIST announced on Jan. 12 that a research team led by Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering, in collaboration with Professor Bernhard Palsson from the Department of Bioengineering at UCSD, has published a comprehensive review paper. The study systematically analyzes and organizes the latest AI-based research approaches aimed at revolutionizing the speed of gene function discovery.

Tokyo, Japan – Researchers from Tokyo Metropolitan University have developed a suite of algorithms to automate the counting of sister chromatid exchanges (SCE) in chromosomes under the microscope. Conventional analysis requires trained personnel and time, with variability between different people. The team’s machine-learning-based algorithm boasts an accuracy of 84% and gives a more objective measurement. This could be a game changer for diagnosing disorders tied to abnormal numbers of SCEs, like Bloom syndrome.