Nervonic acid (NA) — a rare fatty acid crucial for brain development and fighting neurodegenerative diseases — is notoriously difficult to source. 

Aquaporins—proteins that serve as water channels across cell membranes—have long been known for their role in plant hydration and stress responses. 

Apple replant disease (ARD) can remain in orchard soil for decades, weakening newly planted apple trees and making it difficult for growers to judge whether a site is safe to reuse.

Banana breeders face a fundamental challenge: predicting which parent plants will produce the best offspring.

Wetlands are well known for filtering water, storing carbon, and supporting biodiversity. Yet much of their microbial genetic diversity remains unexplored, particularly in high-altitude ecosystems. A new study of the Napahai plateau wetland in Yunnan Province, China, has uncovered a distinctive pattern in DNA polymerase genes, suggesting that this isolated alpine wetland contains a genetic profile that differs from those found in marine, freshwater, hot spring, and agricultural environments.

Waterborne pathogens remain a major threat to public health, but many current monitoring methods are too slow or too narrowly focused to provide rapid warning of emerging biological risks. A new perspective published in Biocontaminant outlines how integrated biosensing systems could move aquatic pathogen surveillance from periodic single-target testing toward rapid, online monitoring of multiple pathogens at once.

With the growing demand for in-situ exploration of complex extreme terrains such as polar craters in lunar exploration missions, quadruped robots have demonstrated unique advantages owing to their efficient jumping and locomotion capabilities in weak gravitational fields. However, lunar gravity is only one-sixth of Earth's, which substantially prolongs the flight phase of underactuated jumping. Incorrect takeoff actions on rugged terrain generate rotational torques that cause the robot to continuously rotate in mid-air, with the angular momentum accumulating over time and leading to catastrophic consequences, thus imposing significant uncertainty on landing control. Conventional optimal control methods rely on offline preplanned trajectories and are unable to cope with the variability of unknown rugged terrains; existing deep reinforcement learning models lack effective utilization of temporal causal relationships, relying solely on current states for decision-making and struggling to predict the long-term consequences of actions. Therefore, how to leverage historical sequence information to model temporal dependencies between actions, enabling the robot to possess forward-looking prediction and adaptive adjustment capabilities during the jumping process, has become a key technical challenge for jumping control on complex lunar terrains.

With the continuous growth of global communication demands, fiber-optic networks are undergoing rapid expansion, and the most widely used silica-based optical fibers are now approaching their intrinsic loss limits. Heavy-metal fluoride ZBLAN fibers theoretically exhibit losses in the mid-infrared band that can be approximately 20 times lower than those of silica fibers. However, this theoretical advantage has long been constrained by the inevitable crystallization problem during ground-based fabrication—ZBLAN glass possesses a critical cooling rate far higher than that of silica, rendering it highly susceptible to crystallization during the fiber drawing process on Earth, which leads to a significant increase in scattering loss. Although microgravity environments may reduce crystallization rates by suppressing buoyancy-driven convection, and theoretical models support this mechanism, the lack of space-qualified automated fiber drawing equipment has previously prevented the acquisition of fiber samples of sufficient length for systematic characterization. Therefore, validating the practical feasibility and performance enhancement effects of ZBLAN fiber drawing under microgravity conditions has become a key scientific issue in overcoming the bottleneck to realizing the ultra-low-loss potential of this material.

Conventional CAR-T therapy requires collecting T cells, genetically modifying them in the laboratory, and reinfusing the engineered cells—a process that takes weeks and costs lots of money. A new review systematically examines in vivo CAR-T approaches that perform this entire reprogramming process inside the patient's body using targeted delivery systems. The article analyzes delivery platforms, evaluates clinical translation progress, and discusses strategies for overcoming key challenges, including off-target effects, immunogenicity, and T cell exhaustion.