Fang Zhou

X-ray Micro Computed Tomography (Micro-CT) is a non-destructive 3D imaging technique that plays a vital role in medical and biological research by enabling high resolution visualization and quantitative analysis of internal sample structures. This paper first elaborates on the structural composition, imaging principle, and experimental workflow of micro-CT, including key steps like sample pretreatment, parameter setting, data reconstruction, and data analysis. Secondly, it systematically reviews the application progress of micro-CT technology in fish research, covering multiple aspects such as whole-body tissue structure modeling of zebrafish, structure and evolution of bones (vertebrae, skull, pharyngeal jaw, teeth, etc.), lung evolution, otolith characteristics, cardiovascular development, skin and adipose tissue analysis, reproductive development tracking, and distribution of heavy metal accumulation. These applications demonstrate the unique advantages of micro-CT in qualitative and quantitative study of fish tissues. Finally, the paper points out existing issues in current micro-CT applications for fish soft tissue imaging, such as insufficient staining specificity, and provides an outlook on future technological development directions and application prospects. This review aims to offer references for promoting the in-depth application of micro-CT technology in ichthyological research.

To address the challenges posed by extensive sample pretreatment and significant matrix interference in conventional metal quantification methods for cyanobacterial culture media, an automated online metal capture and enrichment system was developed and integrated with inductively coupled plasma mass spectrometry (ICP-MS). This system enabled the simultaneous determination of nine metal elements—Cd, Pb, V, Mn, Fe, Co, Ni, Cu, and Zn—within the culture medium. Through systematic optimization and validation, the method demonstrated exceptional analytical performance: calibration curves for all analytes exhibited correlation coefficients (r) exceeding 0.999; repeatability tests yielded relative standard deviations (RSD) below 3% (n = 6); and recoveries at low, medium, and high spike levels ranged from 93.98% to 108.70%. The procedure is characterized by simplicity, high automation, low detection limits, and robust accuracy, making it an effective platform for multi-element contamination monitoring and metal metabolic studies in cyanobacterial cultivation. This approach holds significant potential for applications in algal resource utilization and environmental restoration.

With the increasing use and release of plastic products, microplastics have rapidly accumulated in ecological environments. When microplastics enter the food chain, they cause serious harm to organisms and humans. Microplastics pollution has become a growing concern worldwide; however, there is still no standardized method for rapidly and accurately detecting microplastics. In this work, we used fluorescence lifetime imaging technology to detect four kinds of Nile red-stained and unstained microplastics, and the unique phasor fingerprints of different microplastics were obtained by phasor analysis. Tracing the corresponding pixels of the “fingerprint” in the fluorescence lifetime image allowed for the quick and intuitive identification of different microplastics and their location distributions in a mixed sample. In our work, compared with staining the four microplastics with a fluorescent dye, using the phasor “fingerprint library” formed by the autofluorescence lifetimes of the microplastics was more easily distinguished than microplastics in the mixed samples. The feasibility of this method was further tested by adding three single substances—SiO₂, chitin and decabromodiphenyl ethane (DBDPE), and surface sediments to simulate interferent in the environment, and the results providing potential applications for the identification and analysis of microplastics in complex environments.

Due to problems such as unbalanced intake of nutrients or excessive intake of energy, cultured fish accumulate fat in places such as the abdominal cavity, liver, and muscle, resulting in fatty liver, reducing the quality of fish meat, and even causing many fish deaths, resulting in losses to aquaculture production. Therefore, research on lipid metabolism in fish is important and has attracted increasing attention. The detection of fish body fat distribution and content is a key to such research. The existing methods for detecting fat distribution and content in fish have limitations, such as cumbersome procedures and damage to fish tissues, and thus, is imperative to develop a simple, fast, nondestructive fat detection technology. Taking zebrafish as the research material, this study established an imaging technology for the rapid and nondestructive detection of the fat distribution and content of fish by micro-computed tomography (micro-CT), optimized the fat CT-scanning method, determined the steps of fat quantitation in the CTAn data processing software, and constructed a three-dimensional (3D) model of zebrafish adipose tissue. This technology reveals the distribution of fish adipose tissue in an all-round way, and thus, it will play an important role in the study of lipid metabolism in fish.