OBJECTIVE To explore the transformation of the dispensing and drug pickup process in traditional Chinese medicine pharmacy （TCM Pharmacy） in our hospital based on data-intelligence-driven， aiming to improve pharmacists’ work efficiency and patients’ drug pickup experience. METHODS Value stream mapping and journey mapping were used to systematically identify non-value-added links in pharmacists’ dispensing process and key pain points in patients’ drug pickup under the traditional process. An intelligent dispensing and drug pickup system for the TCM Pharmacy was developed based on the C# and Android television platforms， and a machine-learning model was adopted to predict patients’ drug pickup waiting time. A comprehensive evaluation was performed from three perspectives： system performance， prediction accuracy， and satisfaction of pharmacists and patients. RESULTS The system successfully streamlined non-value-added links such as “waiting for writing on the board” and “searching for drugs”， and realized multimodal dynamic prompts of dispensing status through auditory （number calling） and visual （television terminal） channels. The constructed model for predicting drug pickup waiting time exhibited good fitting degree and generalization ability （mean absolute error＝4.28 min， R 2 ＝0.882）. The comprehensive satisfaction scores of pharmacists and patients in the traditional mode were significantly increased from （70.99±1.74） and （73.58±1.98） to （90.02±1.30） and （88.61±2.08） in the new system， respectively （ P ＜0.01）. CONCLUSIONS The transformation of the intelligent drug dispensing and pickup system for TCM pharmacy based on data-intelligence-driven effectively improves the efficiency of pharmacists’ dispensing work， realizes process transparency and waiting time predictability， and significantly enhances patients’ drug pickup experience.

[Objective] To analyze the characteristics of HLA-A, HLA-B, HLA-DRB1, HLA-C, HLA-DQB1 and HLA-DPB1 allele polymorphisms among cord blood donors in Guangdong population. [Methods] According to HLA high resolution genotyping data of 32 717 samples of cord blood donors from Guangdong Cord Blood Bank from January 2009 to December 2023, the allele frequencies were calculated by direct counting and the haplotype frequencies were calculated by using Arlequin software 3.5.2.2. [Results] A total of 102 HLA-A alleles, 160 HLA-B alleles and 96 HLA-DRB1 alleles were detected in 32 717 samples. Among them, 46 HLA-DPB1 alleles were detected in 5 377 samples, and 66 HLA-C alleles and 35 HLA-DQB1 alleles were detected in 13 310 samples. The most common alleles were HLA-A^*11∶01 (28.96%), HLA-B^*40∶01 (15.23%), HLA-DRB1^*09∶01 (15.72%), HLA-C^*01∶02 (19.40%), HLA-DQB1^*03∶01 (20.85%) and HLA-DPB1^*05∶01 (40.79%). The most common 3 loci haplotype and 6 loci haplotype were HLA-A^*02∶07-B^*46∶01-DRB1^*09∶01 (1.55%), HLA-C^*07∶02-DQB1^*03∶01-DPB1^*05∶01 (1.77%), HLA-DRB1^*09∶01-DQB1^*03∶03-DPB1^*05∶01 (3.31%) and HLA-A^*02∶07-B^*46∶01-C^*01∶02-DRB1^*09∶01-DQB1^*03∶03-DPB1^*05∶01 (0.30%). [Conclusion] In this study, the allele and haplotype frequencies of HLA-A, HLA-B, HLA-DRB1, HLA-C, HLA-DQB1 and HLA-DPB1 were obtained in the cord blood donors in Guangdong, which can provide important reference data for HLA gene related research and the selection of donors for clinical application.

Superchilling is an emerging technology for meat preservation; however, the temperature changes during the process have been commonly ignored. Thus, the effects of temperature fluctuations on meat quality during superchilling are yet to be evaluated. In our study, pork loins and salmon fillets were stored for several days (0, 8, 15, 23, and 30 d) under different temperature fluctuations based on -3.5 ℃ as the target temperature. The results showed that after 15 d of superchilling storage, the values of total volatile basic nitrogen, total viable count, and lipid oxidation were significantly (P<0.05) altered in the ±2.0 ℃ fluctuation group compared with the constant temperature group. On the contrary, there was no significant difference in these parameters between the ±1.0 ℃ fluctuation group and the constant temperature group after 30 d of storage. In addition, irregular temperature changes significantly accelerated the modulation of various indicators. In brief, temperature fluctuations and irregular temperature changes accelerated the destruction of muscle structural integrity, increased the water loss, gradually widened the water loss channels, and thereby reduced the edibility by accelerating the spoilage of meat.
Animals ; Lipid Metabolism ; Pork Meat ; Red Meat ; Salmon ; Swine ; Temperature