ABSTRACT
Wound age estimation is the core content in the practice of forensic medicine. Accurate estimation of wound age is a scientific question that needs to be urgently solved by forensic scientists at home and abroad. Metabolomics techniques can effectively detect endogenous metabolites produced by internal or external stimulating factors and describe the dynamic changes of metabolites in vivo. It has the advantages of strong operability, high detection efficiency and accurate quantitative results. Machine learning algorithm has special advantages in processing high-dimensional data sets, which can effectively mine biological information and truly reflect the physiological, disease or injury state of the body. It is a new technical means for efficiently processing high-throughput big data. This paper reviews the status and advantages of metabolomic techniques combined with machine learning algorithm in the research of wound age estimation, and provides new ideas for this research.
Subject(s)
Algorithms , Machine Learning , Forensic Medicine , Metabolomics , Big DataABSTRACT
In this paper, we report an interesting bubble melt electrospinning (e-spinning) to produce polymer microfibers. Usually, melt e-spinning for fabricating ultrafine fibers needs "Taylor cone", which is formed on the tip of the spinneret. The spinneret is also the bottleneck for mass production in melt e-spinning. In this work, a metal needle-free method was tried in the melt e-spinning process. The "Taylor cone" was formed on the surface of the broken polymer melt bubble, which was produced by an airflow. With the applied voltage ranging from 18 to 25 kV, the heating temperature was about 210â»250 °C, and polyurethane (TPU) and polylactic acid (PLA) microfibers were successfully fabricated by this new melt e-spinning technique. During the melt e-spinning process, polymer melt jets ejected from the burst bubbles could be observed with a high-speed camera. Then, polymer microfibers could be obtained on the grounded collector. The fiber diameter ranged from 45 down to 5 µm. The results indicate that bubble melt e-spinning may be a promising method for needleless production in melt e-spinning.
ABSTRACT
Electrospinning has been widely used as a nanofiber fabrication technique. Its simple process, cost effectiveness and versatility have appealed to materials scientists globally. Pristine polymeric nanofibers or composite nanofibers with dissimilar morphologies and multidimensional assemblies ranging from one dimension (1D) to three dimensions (3D) can be obtained from electrospinning. Critically, these as-prepared nanofibers possessing high surface area to volume ratio, tunable porosity and facile surface functionalization present numerous possibilities for applications, particularly in biomedical field. This review gives us an overview of some recent advances of electrospinning-based nanomaterials in biomedical applications such as antibacterial mats, patches for rapid hemostasis, wound dressings, drug delivery systems, as well as tissue engineering. We further highlight the current challenges and future perspectives of electrospinning-based nanomaterials in the field of biomedicine.