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 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.

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*

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 evaluate the risk of bias and reporting quality in randomized controlled trials(RCTs)of the Chinese medicine injection for acute cerebral infarction in the last five years.Methods RCTs literature on Chinese medicine injection in the treatment of acute cerebral infarction was systematically searched in CNKI,Wanfang Data,VIP,China Biology Medicine Database(CBM),PubMed,Embase and Cochrane Library from April 20,2018 to April 20,2023.The risk of bias and reporting quality of included RCTs were evaluated using the Cochrane Risk of Bias Tool(ROB 1.0)and CONSORT-CHM Formulas 2017,respectively.Results A total of 4 301 articles were retrieved,and 408 RCTs were included according to inclusion and exclusion criteria.The ROB evaluation results showed that the the majority of studies were rated as having an unclear risk of bias due to the lack of reporting on allocation concealment,blind method,trial registration information,and funding sources.The evaluation results of CONSORT-CHM Formulas 2017 showed that the number of reported papers of 17 items was greater than or equal to 50%,and the number of reported papers of 25 items was less than 10%,and most of the RCTs did not show the characteristics of TCM syndrome differentiation and treatment.Conclusion The quality of Chinese medicine injection in the treatment of acute cerebral infarction RCTs is generally low.It is recommended that researchers refer to the methodology design of RCTs and international reporting standards,improve the trial design,standardize the trial report,and highlight the characteristics of TCM syndrome differentiation and treatment.