A research team from the Anhui Institute of Optics and Fine Mechanics (AIOFM), the Hefei Institutes of Physical Science of the Chinese Academy of Sciences (CAS), in collaboration with the Hefei Cancer Hospital of CAS, has developed a new method to accurately measure hemoglobin levels in blood using near-infrared spectroscopy (NIRS). 

A research team led by Prof. CHU Yannan at the Hefei Institutes of Physical Science, Chinese Academy of Sciences, has uncovered a new way to detect cancer early—by analyzing the invisible chemical "scents" that the body gives off. 

Researchers from the Institute of Solid State Physics at the Hefei Institutes of Physical Science, Chinese Academy of Sciences, together with the Shenzhen International Graduate School of Tsinghua University and Suzhou University of Technology, have successfully developed a natural electron donor–assisted healing and targeted surface reconstruction strategy that enables the direct regeneration of degraded lithium iron phosphate (LiFePO₄) cathode materials from retired power batteries. 

In a paper published on aBIOTECH, the authors used a symplastic tracing approach and ultrastructural observations to elucidate the role of uninfected cells (UCs) in nutrient storage and transport within root nodules. The authors discovered an extensive network of plasmodesmata connecting infected cells (ICs) and UCs that dynamically regulates nutrient allocation. These finding provide insights into the regulatory mechanisms of symbiotic nitrogen fixation (SNF) and underscore the crucial role of UCs in optimizing nitrogen fixation efficiency.

In a recent paper published on aBIOTECH, the authors integrated epigenomic, transcriptomic, and 3D genomic data to investigate the regulatory mechanisms of plant resistance genes PRRs and NLRs in soybean. Their findings revealed a poised chromatin state of disease resistance genes (R-genes) and a co-regulation mechanism of clustered R-genes mediated by shared chromatin states within topologically associating domains (TADs)

The article examines how machine learning is revolutionizing igneous petrology and volcanology by automating tasks, enhancing models, and accelerating discoveries. At the same time, the authors warn of key challenges, including the need to understand what models actually learn and to ensure transparency, reproducibility, and interpretability. These concerns are especially critical for volcanic hazard assessment and crisis management. The study also addresses ethical risks and reviews evolving policies in the EU, US, and China.

In a paper published on aBIOTECH, so far, the authors have for the first time comprehensively analyzed the post-transcriptional modifications during peanut pod development by Direct RNA method.

In a paper published on aBIOTECH, the authors developed a lightweight open-source deep learning algorithm automates wheat Fusarium Head Blight diseased spikelet rate measurement from phone-captured images. With 93.8% AP and 7.2M parameters, this algorithm is fit for deployment on mobile devices to facilitate resistance breeding.

The polar regions of the Sun remain among the least-explored territories in solar physics, yet they play a crucial role in driving the solar magnetic cycle, generating the fast solar wind, and shaping space weather throughout the heliosphere. Limited by the Earth’s position in the ecliptic plane, past missions have only provided oblique views of the poles, leaving their behavior and evolution poorly understood. This observation gap has left three top-level scientific questions unanswered: How does the solar dynamo work and drive the solar magnetic cycle? What drives the fast solar wind? How do space weather processes globally originate from the Sun and propagate throughout the solar system? The Solar Polar-orbit Observatory (SPO), scheduled for launch in January 2029, aims to address this gap by achieving the first direct imaging observation of the Sun’s poles from high heliolatitudes. Using multiple Earth flybys and a Jupiter gravity assist, SPO will reach an orbital inclination of up to 75° (80° in an extended mission), with a 15-year lifetime (including the 8-year extended mission) covering an entire solar cycle. In order to achieve its scientific goals, SPO will carry a suite of remote-sensing and in-situ instruments to measure the vector magnetic fields and Doppler velocity fields in the photosphere, to observe the Sun in the extreme ultraviolet and X-ray wavelengths, to image the corona and the heliosphere up to 45 solar radii, and to perform in-situ detection of magnetic fields and charged particles in the solar wind. The mission’s vantage point will allow extended observation periods above ±55° latitude, including during the next solar maximum around 2035, when a polar magnetic field reversal is expected. By directly imaging the poles, SPO will provide invaluable insights, revolutionizing our understanding of the Sun and the space weather processes.

Continuous cyclohexanone production via green phenol hydrogenation using nanoparticle catalysts has suffered from catalyst-product separation challenges. To address this, a flexible, nitrogen-doped, and hierarchically porous carbon nanofiber catalytic membrane (Pd/CNFM) was developed through electrospinning, controlled co-etching, and subsequent Pd loading. This novel approach, pioneering a continuous fiber-based catalytic membrane for phenol hydrogenation in a flow-through reactor, effectively integrated catalysis and separation.