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This work investigates the preparation of a catalytic complex of palladium nanoparticles supported on novel Schiff base modified chitosan-Unye bentonite microcapsules (Pd NPs@CS-UN). The complex has been characterized by FT-IR, EDS, XRD, TEM, HRTEM, Raman, ICP-OES and elemental mapping analyses. Pd NPs@CS-UN was used as a catalyst for Sonogashira coupling reactions between aryl halides and acetylenes, employing K2CO3 as the base and EtOH as a green solvent under aerobic conditions in which it showed high efficacy. Pd NPs@CS-UN was regenerated by filtration after the completion of the reaction. This catalytic process has many advantages including simple methodology, high yields, and easy work-up. The catalytic performance does not notably change even after five consecutive runs.

Abstract Crystal-violet staining, microscopy with image analysis, and quantitative PCR (qPCR) were compared to examine biofilm dynamics. Biofilms of 30 polycultures comprising 15 bacterial species were monitored for 14 days. Collectively, qPCR (representing population) revealed a different growth pattern compared to staining (biomass) and microscopy (colonization): biomass and colonization gradually increased over time, whereas population increased rapidly for the first seven days and leveled off. Temporal forms were categorized into two growth patterns: continuous increase (CI) and non-continuous increase. Staining and microscopy showed similar odds of detecting the CI pattern (27 and 23 polycultures, respectively) across polycultures, greater than that of qPCR (14 polycultures) (P < 0.05). All three methods revealed the identical patterns for 13 polycultures. Staining with microscopy, staining with qPCR, and microscopy with qPCR found the same patterns in 22, 15, and 19 polycultures, respectively. Additionally, staining was quantitatively agreed with microscopy (P < 0.05; R2 > 0.50), whereas neither staining nor microscopy strongly agreed with qPCR (P < 0.05; R2 ≤ 0.22). Collectively, staining was more compatible with microscopy than qPCR in characterizing biofilm dynamics and quantifying biofilms owing to the difference between population growth and biofilm expansion. The concurrent use of qPCR with biomass estimations allows for accurate and comprehensive biofilm quantification.