Objective:To explore the method for selecting characteristic prices of Chinese patent medicines based on informa-tion entropy theory.It involves analyzing the connotative differences among various price indicators and utilizing information entropy metrics to validate the scientific rigor of characteristic price selection so as to optimize the pricing model for Chinese patent medi-cines and improve the accuracy of price evaluation.Methods:A correlation analysis and information entropy calculation are con-ducted on the median price of the smallest preparation unit,average daily cost,and average course cost of TCM.It compares the information diversity and uncertainty of different pricing indicators.Results:The average daily cost exhibits the highest information diversity and uncertainty among all the pricing indicators examined.Conclusion:It is recommended that the average daily cost be used as the dependent variable for characteristic prices in TCM pricing research.This choice plays an important role in optimizing TCM pricing models and enhancing the accuracy of price evaluation.

Objective:To establish a scientific,systematic,and objective indicator system for the characteristic price variables of Traditional Chinese Patent Medicines(TCPM),providing a reference framework for the pricing mechanism of TCPM.Methods:The brainstorming method was initially used to screen related variable indicators.The Nominal Group Technique(NGT)and Delphi methods were applied to gather expert opinions,and SPSS 28.0 was employed for data statistical analysis.It led to the development of a TCPM characteristic price variable indicator system consisting of 6 dimensions,14 characteristic variables and 26 measurement indicators.Results:The authority coefficient of the experts exceeded 0.7,indicating the representativeness of the results.Expert opinions were generally concentrated.Based on the collected opinions and statistical analysis,the scope of selected TCPM characteristic price variables was preliminarily established.Conclusion:The TCPM characteristic price variable indicator system was initially developed.However,due to the complexity of the pricing mechanism and divergent expert opinions,further qualitative and quantitative research methods,along with a dynamic adjustment mechanism,are needed to verify and refine the system.

The central amygdala (CeA) is a crucial modulator of emotional, behavioral, and autonomic functions, including cardiovascular responses. Despite its importance, the specific circuit by which the CeA modulates blood pressure remains insufficiently explored. Our investigations demonstrate that photostimulation of GABAergic neurons in the centromedial amygdala (CeM^GABA), as opposed to those in the centrolateral amygdala (CeL), produces a depressor response in both anesthetized and freely-moving mice. In addition, activation of CeM^GABA axonal terminals projecting to the nucleus tractus solitarius (NTS) significantly reduces blood pressure. These CeM^GABA neurons form synaptic connections with NTS neurons, allowing for the modulation of cardiovascular responses by influencing the caudal or rostral ventrolateral medulla. Furthermore, CeM^GABA neurons targeting the NTS receive dense inputs from the CeL. Consequently, stimulation of CeM^GABA neurons elicits hypotension through the CeM-NTS circuit, offering deeper insights into the cardiovascular responses associated with emotions and behaviors.
Animals ; GABAergic Neurons/physiology* ; Male ; Central Amygdaloid Nucleus/physiopathology* ; Hypotension/physiopathology* ; Mice ; Blood Pressure/physiology* ; Mice, Inbred C57BL ; Solitary Nucleus/physiology* ; Photic Stimulation ; Neural Pathways/physiology*

The National Essential Medicines System could protect public health and ensure access to essential medications.Although the current selection methods for China's National Essential Medicines Lists(NEMLs)are becoming more scientific and standardized,there are still problems such as much emphasis on expert experience and the lack of transparency of decision-making basis.To address these issues,it proposes an evidence-based decision-making pathway for NEMLs selection guided by clinical value.This approach ensures a strong integration of evidence and decision-making,offering valuable insights for improving the adjustment procedures and selection criteria of the NEMLs in China.

Objective:To assess the current level of acceptance of generative artificial intelligence (GAI) among maternal and infant care providers and to explore the factors influencing their acceptance.Methods:A convenience sampling method was used to survey 164 maternal and infant care providers from Beijing Hospital and China-Japan Friendship Hospital between March and May 2024. The survey instruments included a general information questionnaire, GAI Acceptance among Maternal and Infant Care Providers Scale, and Self-assessment Scales for Digital Technology Awareness and Self-assessment Scales for Digital Competence. Multiple linear regression analysis was conducted to identify influencing factors.Results:The total acceptance score of GAI among 164 participants was [181 (158, 200) ]. Multiple linear regression analysis showed that interest in GAI, digital technology awareness, and digital competence were significant influencing factors for GAI acceptance, with statistically significant differences ( P<0.05) . Conclusions:The level of GAI acceptance among maternal and infant care providers was relatively high. It is recommended to strengthen the promotion and training on the application and precautions of GAI, improve their digital competence and professional literacy, while fostering critical and independent thinking, to enhance the integration of GAI into maternal and infant care services.

Objective:To explore the method for selecting characteristic prices of Chinese patent medicines based on informa-tion entropy theory.It involves analyzing the connotative differences among various price indicators and utilizing information entropy metrics to validate the scientific rigor of characteristic price selection so as to optimize the pricing model for Chinese patent medi-cines and improve the accuracy of price evaluation.Methods:A correlation analysis and information entropy calculation are con-ducted on the median price of the smallest preparation unit,average daily cost,and average course cost of TCM.It compares the information diversity and uncertainty of different pricing indicators.Results:The average daily cost exhibits the highest information diversity and uncertainty among all the pricing indicators examined.Conclusion:It is recommended that the average daily cost be used as the dependent variable for characteristic prices in TCM pricing research.This choice plays an important role in optimizing TCM pricing models and enhancing the accuracy of price evaluation.

Objective:To establish a scientific,systematic,and objective indicator system for the characteristic price variables of Traditional Chinese Patent Medicines(TCPM),providing a reference framework for the pricing mechanism of TCPM.Methods:The brainstorming method was initially used to screen related variable indicators.The Nominal Group Technique(NGT)and Delphi methods were applied to gather expert opinions,and SPSS 28.0 was employed for data statistical analysis.It led to the development of a TCPM characteristic price variable indicator system consisting of 6 dimensions,14 characteristic variables and 26 measurement indicators.Results:The authority coefficient of the experts exceeded 0.7,indicating the representativeness of the results.Expert opinions were generally concentrated.Based on the collected opinions and statistical analysis,the scope of selected TCPM characteristic price variables was preliminarily established.Conclusion:The TCPM characteristic price variable indicator system was initially developed.However,due to the complexity of the pricing mechanism and divergent expert opinions,further qualitative and quantitative research methods,along with a dynamic adjustment mechanism,are needed to verify and refine the system.

The National Essential Medicines System could protect public health and ensure access to essential medications.Although the current selection methods for China's National Essential Medicines Lists(NEMLs)are becoming more scientific and standardized,there are still problems such as much emphasis on expert experience and the lack of transparency of decision-making basis.To address these issues,it proposes an evidence-based decision-making pathway for NEMLs selection guided by clinical value.This approach ensures a strong integration of evidence and decision-making,offering valuable insights for improving the adjustment procedures and selection criteria of the NEMLs in China.

Objective:To assess the current level of acceptance of generative artificial intelligence (GAI) among maternal and infant care providers and to explore the factors influencing their acceptance.Methods:A convenience sampling method was used to survey 164 maternal and infant care providers from Beijing Hospital and China-Japan Friendship Hospital between March and May 2024. The survey instruments included a general information questionnaire, GAI Acceptance among Maternal and Infant Care Providers Scale, and Self-assessment Scales for Digital Technology Awareness and Self-assessment Scales for Digital Competence. Multiple linear regression analysis was conducted to identify influencing factors.Results:The total acceptance score of GAI among 164 participants was [181 (158, 200) ]. Multiple linear regression analysis showed that interest in GAI, digital technology awareness, and digital competence were significant influencing factors for GAI acceptance, with statistically significant differences ( P<0.05) . Conclusions:The level of GAI acceptance among maternal and infant care providers was relatively high. It is recommended to strengthen the promotion and training on the application and precautions of GAI, improve their digital competence and professional literacy, while fostering critical and independent thinking, to enhance the integration of GAI into maternal and infant care services.

OBJECTIVE To provide a detailed report and interpretation of the method and results for determining the weights of the technical indicators from the “multi-dimensional and multi-criteria comprehensive evaluation index system （first edition）” stated in Guideline for Multi-dimensional and Multi-criteria Comprehensive Evaluation of Chinese Patent Medicine. METHODS Normalization calculations were performed on the comprehensive weight values calculated by the analytic hierarchy process and expert weighting method to obtain the objective weights of the indicators. RESULTS The weight results of the six primary dimensions in the current comprehensive evaluation indicator system of Chinese patent medicine showed effectiveness dimension＞ safety dimension＞standard dimension＞application dimension＞scientific dimension＞economic dimension， with weight values of 0.281 0， 0.268 5， 0.195 8， 0.107 3， 0.096 1 and 0.051 3 respectively， consistent with the results of most researches currently. CONCLUSIONS The process of weight determination in this indicator system is scientifically reasonable， with clear methods and clear interpretations， and is worthy of further optimization and widespread application.