ObjectiveTo clarify the neuroprotective effect of black Panacis Quinquefolii Radix（PQR） and explore its active ingredients， with the aim of establishing an activity-oriented quality evaluation method. MethodsTransgenic Tg（HuC∶EGFP） zebrafish was used to establish a neuronal injury model by aluminum chloride immersion. Different doses（10， 20 mg·L^-1） of PQR and black PQR ethanol extracts were administered. The neuroprotective effects of PQR and black PQR were compared by analyzing the fluorescent area and intensity of zebrafish neurons. Based on ultra-performance liquid chromatography（UPLC）， a fingerprint profile of black PQR was established， followed by principal component analysis（PCA） and orthogonal partial least squares-discriminant analysis（OPLS-DA）. Differential components were screened using the criteria of variable importance in the projection（VIP） value>1 and P<0.05. The neuroprotective activity of 14 batches of black PQR was assessed， and Spearman correlation analysis was used to identify saponins related to neuroprotective activity， which were then validated. Based on the above results， active marker components were determined， and an UPLC method was established for their quantitation with clear content limits. ResultsPharmacological efficacy results showed that both PQR and black PQR at different doses could significantly improved neuronal damage in zebrafish. At a dose of 20 mg·L^-1， black PQR demonstrated superior efficacy（P<0.05）. The fingerprint similarities of 14 batches of black PQR were>0.94， with 26 common peaks identified. Through comparison with the reference standards， 8 components were confirmed， including peak 1（ginsenoside Rg₁）， peak 2（ginsenoside Re）， peak 5（ginsenoside Rb₁）， peak 9（ginsenoside Rd）， peak 16［ginsenoside 20（S）-Rg₃］， peak 17［ginsenoside 20（R）-Rg₃］， peak 18（ginsenoside Rk₁）， and peak 19（ginsenoside Rg₅）. The results of PCA and OPLS-DA indicated that there were differences in saponins among black PQR samples from different origins， and 12 differential components were screened. All 14 batches of black PQR exhibited good protective effects on zebrafish neurons， with Shaanxi-produced black PQR showing superior protective effects compared to the other three production regions. Spearman correlation analysis revealed that a total of 11 components， including ginsenosides 20（S）-Rg₃， 20（R）-Rg₃， Rk₁ and Rg₅， showed a significant positive correlation with the neuroprotective effect in zebrafish（P<0.05）. The activity validation results indicated that ginsenosides 20（S）-Rg₃， 20（R）-Rg₃， Rk₁ and Rg₅ were the primary components responsible for the neuroprotective effects of black PQR. Quantitative analysis showed that the content of ginsenoside 20（S）-Rg₃ in 14 batches of black PQR ranged from 0.17% to 0.52%， and the repair rate of neuronal damage ranged from 42.77% to 97.83%. ConclusionBased on the fingerprint and neuronal protective activity， the spectrum-effect related quality control model of black PQR was established， with ginsenoside 20（S）-Rg₃ as the quality control index， and the neuronal damage repair rate≥60% as the evaluation standard， the minimum limit of ginsenoside 20（S）-Rg₃ in black PQR should be≥0.20%.

ObjectiveTo assess the quality consistency of black Panacis Quinquefolii Radix（bPQR） decoction pieces prepared by atmospheric and pressurized steaming processes based on chromaticity-chemical composition-vasoactive inhibition. The ultimate goal was to screen the pressurized steaming process yielding quality equivalent to atmospheric steaming， and optimize the processing technology of bPQR. MethodsThe bPQR decoction pieces were prepared using both atmospheric and pressurized steaming processes， and the chromaticity values［lightness value（L^*）， red/green chromaticity value（a^*）， yellow/blue chromaticity value（b^*）， total chromaticity value（E^*ab）］ were measured. High performance liquid chromatography（HPLC） was employed to establish fingerprint profiles for the decoction pieces， and cluster analysis was conducted on chromaticity values and the common peak areas in fingerprint profiles to elucidate the quality relationships between the decoction pieces processed by different methods. The optimal atmospheric steaming of bPQR decoction pieces was determined through zebrafish angiogenesis inhibition experiments. The contents of ginsenosides Rg₁， Re， Rb₁， 20（S）-Rg₃， Rk₁ and Rg₅ in the decoction pieces were quantified， and Spearman correlation analysis was employed to investigate the relationship between saponin content， chromaticity， and angiogenesis inhibition activity during the steaming process. By integrating the consistency of chromaticity， saponin components and angiogenesis inhibition activity， pressurized steaming conditions with quality equivalent to the atmospheric pressure method were selected. ResultsCompared with the atmospheric steaming method， pressurized steaming resulted in faster color darkening and higher conversion rates of ginsenosides in bPQR decoction pieces. Moreover， the neovascularization inhibitory activity of bPQR decoction pieces continued to increase with the deepening of processing. Based on the effectiveness and safety， the optimal process for preparing bPQR decoction pieces with neovascularization inhibitory activity was determined to be atmospheric steaming for 21 h. All six ginsenosides tested exhibited strong to extremely strong correlations with both the chromaticity values of the decoction pieces and their neovascularization inhibitory activities. Among them， ginsenosides Rg₁， Re and Rb₁ exhibited positive correlations with chromaticity values and negative correlations with zebrafish angiogenesis inhibition activity. Conversely， ginsenosides 20（S）-Rg₃， Rk₁ and Rg₅ showed negative correlations with chromaticity values and positive correlations with zebrafish angiogenesis inhibition activity. By integrating chromaticity values， cluster analysis results， as well as the results of activity， it was determined that the quality of bPQR decoction pieces steamed under pressurized conditions of 110 ℃（0.045 MPa） for 5 h and 115 ℃（0.07 MPa） for 3 h was highly consistent with that obtained by atmospheric steaming for 21 h. ConclusionThe preparation of bPQR decoction pieces by pressurized steaming has the advantages of short preparation time， low energy consumption， and rapid saponin conversion rate， making it a viable alternative to atmospheric steaming for preparing bPQR decoction pieces. Meanwhile， the evaluation method based on chromaticity-chemical composition-activity can provide a more scientific and effective explanation of change rules in the quality during traditional Chinese medicine processing， and offer a new model for optimizing processing technology and enhancing quality control.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.

Objective To evaluate the quality of prediction model on healthcare-associated infections in China,so as to standardize research process and reporting methods.Methods It performed a literature search for healthcare-associated infections prediction model studies published using the following databases by the end of 2022.After independently screening the literature and cross-checking the extracted data according to the inclusion and exclusion criteria,the research team applied the prediction model risk of bias assessment tool(PROBAST)to evaluate the methodological quality,and the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis(TRIPOD)statement to evaluate the quality of study reporting.Results A total of 81 healthcare-associated infections prediction studies were identified.Their median PROBAST overall adherence were 58.11%±13.88%,median TRIPOD adherence were 56.11%±16.35%.The main methodological flaws involved participants defined,ignored complexities in data,and omitted missing data.The reporting flaws lay in the items of risk groups,sample size,and supplementary information.Conclusion There are methodological deficiencies and incomplete reporting of domestic hospital infection prediction modelling studies,which limit the reliability and applicability of the results and leave much room for improvement.