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.

This study investigated the level of satisfaction among consumers of special tea (Monsonia burkeana) in the Capricorn District Municipality, Limpopo Province, South Africa. It sought to identify the factors that influenced this satisfaction. A total of 225 respondents were selected using snowball sampling, and primary data were collected through structured questionnaires. Descriptive statistics were used to analyse consumer profiles and satisfaction levels, while multinomial logistic regression determined the factors influencing satisfaction across four categories: “Not satisfied at all”, “Satisfied”, “Not sure”, and “Highly satisfied”. The results revealed an average respondent age of 29.95 years and an average annual tea consumption of 4.684 uses, with over 50% of both male and female respondents expressing satisfaction. Regression analysis indicated that market access, cultural influences, income level, and the person introducing the tea significantly influenced dissatisfaction relative to high satisfaction. The income level was the only significant factor distinguishing “Satisfied” from “Highly satisfied”. Gender, age, marital status, and employment type were significant predictors for “Not sure” compared to “Highly satisfied”. These findings highlight the importance of developing the medicinal plant market, promoting cultural education, and implementing sustainable cultivation and conservation practices for Monsonia burkeana. Efforts to improve market access and address income disparities are also necessary to enhance consumer satisfaction and ensure the tea’s continued availability and cultural relevance.