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The gut microbiota, known as the “forgotten organ” and “human second genome,” comprises a complex microecosystem. It significantly influences the development of various tumors, including colorectal, liver, stomach, breast, and lung cancers, through both direct and indirect mechanisms. These mechanisms include the “gut-liver” axis, the “lung-intestine” axis, and interactions with the immune system. The intestinal flora exhibits dual roles in cancer, both promoting and suppressing its progression. Traditional Chinese medicine (TCM) can alter cancer progression by regulating the intestinal flora. It modifies the intestinal flora’s composition and structure, along with the levels of endogenous metabolites, thus affecting the intestinal barrier, immune system, and overall body metabolism. These actions contribute to TCM’s significant antitumor effects. Moreover, the gut microbiota metabolizes TCM components, enhancing their antitumor properties. Therefore, exploring the interaction between TCM and the intestinal flora offers a novel perspective in understanding TCM’s antitumor mechanisms. This paper succinctly reviews the association between gut flora and the development of tumors, including colorectal, liver, gastric, breast, and lung cancers. It further examines current research on the interaction between TCM and intestinal flora, with a focus on its antitumor efficacy. It identifies limitations in existing studies and suggests recommendations, providing insights into antitumor drug research and exploring TCM’s antitumor effectiveness. Additionally, this paper aims to guide future research on TCM and the gut microbiota in antitumor studies.

Hepatocellular carcinoma (HCC) is a major global cause of carcinoma-related fatality. The inhibition of tubulin polymerization holds significant potential in the development of cancer drugs. In our study, we synthesized a novel pyrrolidine-2,5-dione derivative (compound 8) that exhibited potent anti-HCC activity (IC50 value of 2.082 μM) against human HCC HepG2 cells. Moreover, compound 8 significantly suppressed the HepG2 cell multiplication, and triggered G2/M phase arrest of HepG2 cells and their apoptosis. Further mechanistic investigations revealed that compound 8 suppressed tubulin polymerization by directly binding to the colchicine binding site of β-tubulin. Additionally, compound 8 significantly inhibited tumor growth with low toxicity in nude HepG2 tumor-bearing mice, achieving an approximate inhibition rate of 45.73 %. Therefore, compound 8 represents a promising pharmaceutical candidate for HCC management.

Non-destructive phenotyping of roots and measurement of root water uptake from different soil layers in the field are vital for improving water management and facilitating the development of drought-resistant crop varieties, but difficult because of their opaqueness. As a result, indirect methods using easy-to-measure variables such as soil water content have been used as alternatives. However, the inherent measurement errors could undermine the robustness and reliability of these methods. This paper proposes a new method to bridge this knowledge gap by using soil water content profiles measured at two time points to calculate root uptake and root-length density. It is based on the Richards' equation by treating root uptake from different soil layers between the two time points as random unknown numbers; their distributions are calculated using the Bayesian framework, solved by the Markov Chain Monte Carlo method. We applied the method to 39 winter wheat lines grown in a silt-clay loam field. Soil water content profile measured at the first time point from each plot served as the initial condition, and water content measured at the second time point was the target to match the model for calculating average root water uptake and root-length density between the two time points. The results show that the measured soil water contents fall within the 95% confidence interval of the calculated soil water contents. The inherent soil water measurement errors lead to uncertainties in the calculated root water uptake for all lines, but such uncertainties decrease with soil depth. Although the soil types and agronomic management were the same for all 39 lines, their root water uptake from different soil layers varies considerably, with some lines more capable of using subsoil water than others. Generally, the calculated and measured root-length densities agree well, albeit the degree of the agreement varies with lines. While this paper focuses on methodology and applies the method to one growth stage spanning one month only, the consistent results for all 39 lines indicates the method is robust and can be applied to other crops cultivated in different conditions. Given the growing interest in improving root traits to enhance water use efficiency, the proposed method has important implications as phenotyping roots and understanding their water uptake from different soil layers in the field is a prerequisite to achieve this crucial target.