In the macro world, building a robot is straightforward: you connect motors to joints and follow the laws of physics. But at the nanoscale—where machines are a billion times smaller—how to build a robot? Scientists are now engineering DNA to perform complex tasks at the nanoscale, building machines that move, grip, and even process information. In a new review published in SmartBot, Professor Lifeng Zhou of Peking University, along with Academician Jian S. Dai from Southern University of Science and Technology, takes us through the cutting-edge world of DNA nanorobots and explores the transition from static DNA structures to dynamic, programmable machines.

Animal studies have shown that some cartilage cells can transition to a bone-like phenotype, challenging the belief that bone cells arise solely from stem cells in the bone marrow and growth plate. However, the molecular mechanisms driving this process remain unclear. Researchers have now developed in vitro and in vivo models of bone formation that enable tracking of cartilage-to-bone transition, providing new insights into the mechanisms and signaling pathways involved in cartilage-derived bone formation.

A research team shows that future air pollution controls could significantly reshape atmospheric nitrogen deposition to the oceans, with unexpected consequences for marine productivity and climate feedbacks.

Neuroimaging analysis in brain disorders faces a persistent challenge: brain signals are complex and high-dimensional, while high-quality labeled datasets remain limited. This review article systematically examines how self-supervised learning can help address that gap by learning meaningful representations directly from unlabeled neuroimaging data. It covers major methodological families, including contrastive, generative, and hybrid generative-contrastive approaches, and discusses their applications in functional MRI, EEG, and multimodal brain network analysis.

The review argues that self-supervised learning offers more than annotation efficiency. It may enable more transferable and clinically useful representations for disease screening, diagnosis, and prognosis across heterogeneous datasets and disorders. At the same time, interpretability, data heterogeneity, missing modalities, and clinical validation remain major barriers. Future work will likely focus on stronger multimodal fusion, better cross-site generalization, and more clinically adaptable model design.

Researchers at The Hong Kong University of Science and Technology (HKUST) have developed CarGAP, a groundbreaking chemo-optogenetic tool that uses vitamin B₁₂ and green light to precisely control gap junctions, the microscopic channels enabling direct cell-to-cell communication. This innovation allows on-demand closing and opening of these intercellular bridges, providing unprecedented spatiotemporal control over vital molecules and electrical signals. Demonstrated in both mammalian cells and living fruit flies, CarGAP provides a powerful new way to study development, immunity, and neural activity, with far-reaching potential for understanding disease mechanisms and advancing regenerative medicine.

A research team conducted an extensive field investigation across the Tianshan Mountains and found that climate-driven warming and increased soil moisture could substantially reshape nitrous oxide (N₂O) emissions in arid ecosystems.

University of Phoenix announces the publication of “Harnessing AI, Virtual Landscapes, and Anthropomorphic Imaginaries to Enhance Environmental Science Education at Jökulsárlón Proglacial Lagoon, Iceland” in Glacies. The peer-reviewed study, which examines how character-driven narratives and human-centered AI can support adult learners in their understanding of complex scientific ideas, is authored by Jacquelyn Kelly, Ph.D., associate dean, College of General Studies; Dianna Gielstra, Ph.D., full‑time faculty, Environmental Science Program, College of General Studies; Tomáš J. Oberding, Ph.D., full‑time faculty, Environmental Science Program, College of General Studies; Jim Bruno, MBA, associate dean, College of Business and Information Technology; and Stephanie Cosentino, MAEd, senior instructional designer, University of Phoenix.