The content and distribution of 18 phenolic compounds in 462 batches of edible flowers from 73 species commercially available in China

Development of an ic-CLEIA for precise detection of 3-CQA in herbs and patent medicines: ensuring quality control and therapeutic efficacy

Background

3-caffeoylquinic acid (3-CQA), a member of the chlorogenic acid family, possesses diverse pharmacological properties, such as scavenging, antioxidant, and antiapoptotic activity, rendering substantial value to alimentary consumables and therapeutic substances. However, the pervasiveness of non-standard practices, notably the misuse and abuse of indigenous botanicals, coupled with the inherent susceptibility of 3-CQA to degradation under light and heat exposure, engenders discernible disparateness in the quality profiles of the same kinds of herbs. Consequently, precise quantification of 3-CQA becomes imperative.

Methods

In this context, an artificial antigen was synthesized as a specific conjugate of 3-CQA and bovine serum albumin (3-CQA-BSA), followed by the generation of a monoclonal antibody (mAb) against the conjugate. Through optimization, a mAb-based indirect competitive chemiluminescence enzyme immunoassay (ic-CLEIA) was developed.

Results

It demonstrated an IC50 and the calibration range of 2.97 ng/mL and 0.64-13.75 ng/mL, respectively, outperforming the conventional enzyme-linked immunosorbent assay (ELISA). Notably, the ic-CLEIA displayed 10.71% cross-reactivity with 3,5-dicaffeoylquinic acid, alongside minimal cross-reactivity toward other isomeric counterparts and analogs. Validation experiments on herbs and Chinese patent medicines using ic-CLEIA, confirmed by high-performance liquid chromatography (HPLC) analysis, revealed a robust correlation coefficient of 0.9667 between the two modalities.

Conclusion

These findings unequivocally demonstrated that the proposed ic-CLEIA represents a viable and reliable analytical method for 3-CQA determination. This method holds significant potential for ensuring the quality control and therapeutic efficacy germane to herbs and patent medicines, spanning diverse therapeutic milieus and applications.

Intelligent chemical profiling of 73 edible flowers by liquid chromatography-high resolution mass spectrometry combined with HRMS database and their authentication based on large-scale fingerprints

A commercial high-resolution MS database "TCM-PCDL" was innovatively introduced to automatically identify multi-components in 73 edible flowers rapidly and accurately by liquid chromatography-high resolution mass spectrometry, which can be time-consuming and labor-intensive in traditional manual method. The database encompasses over 2565 natural products with various energy levels. Unknown compounds can be identified through direct matching and scoring MS2 spectra with database. A total of 870 compounds were identified from 73 flowers, with polyphenols constituting up to 75%. Focusing on polyphenols, a high performance liquid chromatography (HPLC) method was developed to generate fingerprints from 510 batches, establishing an "HPLC database" that enabled accurate authentication using similarity scores and rankings. This method demonstrated an accuracy rate of 100% when applied to 30 unknown samples. For flowers prone to confusion, additional statistical analysis methods could be employed as aids in authentication. This study provides valuable insights for large-scale sample chemical profiling and authentication.

ASAP-MS combined with mass spectrum similarity and binary code for rapid and intelligent authentication of 78 edible flowers

This is the first report to use Atmospheric Pressure Solids Analysis Probe (ASAP) for rapid and intelligent authentication of 78 edible flowers. Mass spectra of 451 batches were collected, with each run for 1-2 min. Experimental raw data was automatically extracted and aligned to create a MS database, based on which flowers were identified by MS similarity scores and rankings. To avoid background interference, top 25 ions of each flower were screened and gathered into an m/z pool containing 292 ions (+) and 399 ions (-). Binary sequence IDs were then generated by automatically assigning "1″ for presence and "0″ for absence, resulting in 78 binary codes. Binary code similarity with 78 IDs was used for authentication. Above two approaches were automatically performed by MATLAB, and compared to k-nearest neighbor model, and samples were all successfully identified (100 %). The proposed method provides a high-throughput authentication approach for large-scale food samples.