Cellulose nanocrystal, known as CNCs, is a form of material that can be produced by synthesizing carbon from naturally occurring substances, such as plants. Due to the unique properties it possesses, including a large surface area, impressive mechanical strength, and the ability to biodegrade, it draws significant attention from researchers nowadays. Several methods are available to prepare CNC, such as acid hydrolysis, enzymatic hydrolysis, and mechanical procedures. The characteristics of CNC include X-ray diffraction, transmission electron microscopy, dynamic light scattering, etc. In this article, the recent development of CNC preparation and its characterizations are thoroughly discussed. Significant breakthroughs are listed accordingly. Furthermore, a variety of CNC applications, such as paper and packaging, biological applications, energy storage, etc., are illustrated. This study demonstrates the insights gained from using CNC as a potential environmentally friendly material with remarkable properties.

In recent years, the pathological diagnosis of glomerular diseases typically involves the study of glomerular his-to pathology by specialized pathologists, who analyze tissue sections stained with Periodic Acid-Schiff (PAS) to assess tissue and cellular abnormalities. In recent years, the rapid development of generative adversarial networks composed of generators and discriminators has led to further developments in image colorization tasks. In this paper, we present a generative adversarial network by Spectral Normalization colorization designed for color restoration of grayscale images depicting glomerular cell tissue elements. The network consists of two structures: the generator and the discriminator. The generator incorporates a U-shaped decoder and encoder network to extract feature information from input images, extract features from Lab color space images, and predict color distribution. The discriminator network is responsible for optimizing the generated colorized images by comparing them with real stained images. On the Human Biomolecular Atlas Program (HubMAP)—Hacking the Kidney FTU segmentation challenge dataset, we achieved a peak signal-to-noise ratio of 29.802 dB, along with high structural similarity results as other colorization methods. This colorization method offers an approach to add color to grayscale images of glomerular cell tissue units. It facilitates the observation of physiological information in pathological images by doctors and patients, enabling better pathological-assisted diagnosis of certain kidney diseases.