An algorithm-driven intelligent mining and identification strategy for natural product mass spectrometry.

Efficiently mining and identification of new compounds from the extensive MS/MS datasets of plant extracts poses a significant challenge due to the structural diversity and compositional complexity inherent in natural products (NPs). Various data post-processing techniques have been developed to simplify the interpretation of MS/MS data; however, they often suffer from limited specificity and precision. Meanwhile, structure annotation following data post-processing is particularly time-consuming.

Species diversity and seasonal dynamics of filamentous cyanobacteria in urban reservoirs for drinking water supply in tropical China.

Filamentous cyanobacteria have been observed to become the dominant species in reservoirs, especially in small reservoirs for drinking water supply in southern China. The occurrences of filamentous cyanobacteria blooms in such reservoirs add additional costs for water plants by decreasing the filtration efficiency and the potential of toxin production. To serve the purpose of drinking water supply, the effective risk assessment requires the dynamic pattern of filamentous cyanobacteria.