Objective:To explore the application effect of objectives and key results (OKR) management method in the clinical intensive training of emergency department nurses.Methods:A total of 90 nurses from the emergency department of The First Affiliated Hospital of Hebei North University who participated in clinical intensive training from September to December 2022 were selected. They were randomly divided into a control group and an observation group (45 in each group) using a random number table. The observation group was managed using OKR method, while the control group was managed using the conventional management method. The academic performance (theoretical knowledge and practical operation), clinical comprehensive ability (nurse core competency evaluation form), self-learning ability (Self-Rating Scale of Self-Directed Learning), and training satisfaction were compared between two groups of nurses at the end of each month (for a total of 3 months).Results:The observation group had significantly higher theoretical knowledge scores [(65.78±5.11), (77.89±4.22), (85.10±4.70)] and practical operation scores [(62.33±4.01), (72.45±4.29), (83.20±5.10)] than the control group [(61.99±6.09), (74.18±4.09), (82.60±5.40); (60.09±4.56), (70.24±4.11), (80.70±4.60)]. The clinical comprehensive ability (nursing ability and critical clinical thinking), self-learning ability (learning behavior, learning awareness, learning strategies, and learning evaluation), and training satisfaction (theoretical knowledge training, clinical skills training, and work plan) of nurses in the observation group were also higher than those of nurses in the control group.Conclusions:The application of OKR management method in clinical intensive training of emergency department nurses can significantly improve their clinical abilities and knowledge level, mobilize their self-learning ability, and achieve higher satisfaction.

The possibility of reusing Escherichia coli cells from the broth for succinic acid production was investigated. Using succinic acid yield and productivity as criterion, we investigated the effects of cell concentration, initial glucose concentration, different neutralizers on the bioconversion. The results revealed that E. coli could convert glucose to succinic acid in a water solution of glucose and a neutralizer. According to the results, the optimal condition was as follows: the cell concentration was 50 (OD600), glucose concentration was 40 g/L and neutralizer was MgCO3. Under the optimum conditions, we carried out the consecutive batch bioconversion in 7 L fermenter. Succinic acid yield reached 91% with the productivity of 3.22 g/(L x h) for the first conversion. For the second conversion, succinic acid yield reached 86% with productivity of 2.04 g/(L x h). Furthermore, we achieved a high mass yield above 83% with the productivity of 1.82 g/(L x h) for the third bioconversion.
Escherichia coli ; genetics ; metabolism ; Fermentation ; Genetic Engineering ; Glucose ; metabolism ; Industrial Microbiology ; Succinic Acid ; metabolism

Objective To compare the dose difference between the 12-bit and 16-bit CT images containing metallic implants calculated by different algorithms. Methods The titanium alloy rod was inserted into the phantom and subject to CT scan and then the 12-bit and 16-bit CT images were reconstructed. The CT images were online transmitted to the Monaco planning system and a 0° of single field was designed. The dose distribution was calculated by PB (Pencil Beam), CC (Collapsed Cone) and MC (Monte Carlo) algorithms, respectively. The CT-ED curve was expanded and the dose was recalculated. The depth dose curve through the center of the metallic implants along with the direction of the field was obtained by using the Matlab 8. 3 statistical software. The dose distribution curves between 12-bit and 16-bit CT images calculated by different algorithms and the dose difference of varying distances between the incident and the exit surfaces of metallic implants were statistically compared. The dose was measured by thimble chamber. Results The 16-bit CT images accurately read the CT values of the metallic implants. After the CT-ED curve was expanded, the dose on the incident surface of metallic implant was reduced by 5. 43% and that on the exit surface was increased by 25. 56% calculated by PB algorithm compared with MC algorithm. The dose on the posterior exit surface was higher than that of MC algorithm. The dose on the incident surface of metallic surface was decreased by 4. 5%, whereas that on the exit surface was reduced by 4. 31% using CC algorithm. The dose on the posterior exit surface was more significantly reduced. The calculated values by MC algorithm were the most close to the measured values. Conclusions Application of 16-bit CT image, CT-ED curve expansion of the treatment planning system combined with MC algorithm can enhance the accuracy of dose calculation for the patients containing metallic implants during radiotherapy.