Objective: To investigate the basic situation of pre-analytical quality management in blood station laboratories in North China, and to provide baseline data for promoting the homogenization and standardization of these pre-analytical processes in each blood station laboratory. Methods: A cross-sectional status survey was designed based on the quality management regulations of blood stations, ISO15189 standards and relevant quality management requirements. This survey covering various aspects including laboratory general situation, sample collection and temporary storage, transportation, reception, and quality continuous improvement situations. Data analysis was performed on the survey results of each laboratory. Results: All the 38 blood station laboratories in North China had established a pre-analytical quality management system framework and implemented basic pre-analytical quality control activities; however, there were differences in implementation. 1) Among the 12 basic quality items, 3 items were monitored by all the investigated laboratories (100%), 6 items were monitored by the vast majority of laboratories (about 90%), and 3 items were monitored by a portion of laboratories (about 60%). There were no significant differences in the monitoring index among the three regions and among different types of laboratories (P>0.05). 2) Among the total of 26 items in the three key processes before testing (sample collection and storage, transportation, reception and processing), 12 items were monitored by all laboratories (100%), 11 items were monitored by the vast majority of laboratories (about 90%), and 3 items were monitored by a portion of laboratories (about 75%). There were no significant differences in monitoring index among different regions and types of laboratories (P>0.05). Conclusion: This survey provides a reference and basis for the gap analysis of the pre-analytical process quality management in 38 blood station laboratories across North China. It facilitates laboratories in identifying pre-analytical quality problems, resolving problems, preventing errors, and ensuring that the quality of blood samples before testing meets the established requirements. It lays a foundation for the homogenization of pre-analytical quality management in regional blood stations.

Objective: To determine the frequency and main reasons of unqualified samples by analyzing the quality of pre-analytical samples in blood stations in North China, thereby providing a reference and basis for gap analysis in the implementation of pre-analytical process quality management for participating laboratories and ensuring that only high-standard and high-quality blood samples proceed to testing. Methods: Data on the quality of pre-analytical samples from blood station laboratories in North China was collected via questionnaire. Statistical analysis were performed on: 1) the basic information of samples quality monitoring in the laboratories; 2) the distribution of the overall pre-analytical unqualified rate of samples and the pre-analytical unqualified rate of samples in each laboratory; 3) the distribution of reasons for sample disqualification. Results: 1) The overall pre-analytical unqualified rate of samples in blood station laboratories in North China was 4.55, with a total sigma level of 5.39σ. The 25th, 50th and 75th percentiles (P25, P50, P75) for the total unqualified rate were 0.00, 1.10 and 5.96, respectively. The corresponding percentiles for the Sigma level were 5.34σ, 5.71σ, and 6.00σ, respectively. The pre-analytical unqualified rate of serological and nucleic acid samples (4.89 vs 4.22) showed a significant difference (χ =9.575, P<0.05). 2) The average unqualified rate of samples in region A, B and C was 1.71, 9.50 and 12.64 (χ =1 590.721, P<0.05), and the sigma level was 5.66σ, 5.21σ and 5.16σ, respectively. 3) The main reasons for unqualified serological samples were chylous blood (72.65%), hemolysis (17.39%), abnormal hematocrit (5.80%), and insufficient volume (3.50%). The main reasons for the unqualified nucleic acid samples were chylous blood (78.26%), hemolysis (8.84%), failure to centrifuge as required (5.01%), abnormal hematocrit (4.66%), and insufficient volume (1.92%). Conclusion: In North China, the quality indicators for the pre-analytical processes in blood station laboratories are generally well-managed. Laboratories in region A outperformed the national average in pre-analytical specimen quality control. However, participating laboratories exhibit gaps in implementing pre-analytical quality management. Through effective analysis of pre-analytical process quality metrics and inter-laboratory comparisons, laboratories can identify discrepancies and address shortcomings. By establishing clear quality objectives, they can achieve continuous improvement and ensure the validity of test results.

Objective: To investigate the assessment criteria and subsequent handling practices of hemolytic and lipemic blood samples before testing in blood screening laboratories in North China, and to provide data to support the standardization of their management in blood station laboratories. Methods: Data on the preanalytical management of hemolytic and lipemic samples from 38 laboratories were collected. The details of management on the criteria and verificatioon for assessment, the assessment methods, and subsequent handling procedures of hemolytic and lipemic samples in blood station laboratories were analyzed. Results: 1) All 38 blood station laboratories monitored serological and nucleic acid samples for hemolysis and lipemia in pre-analytical phase. 2) The criteria and methods for assessing hemolytic and lipemic samples varied among the laboratories of the 38 blood stations. 15 laboratories (39.47%) followed manufacturer's instructions, 9 laboratories (23.68%) formulated their own criteria, and 14 laboratories (36.84%) referred to the criteria of other laboratories. 16 laboratories (42.11%) verified the criteria for assessing hemolytic and lipemic samples, with significant variations in verification rate across laboratories from different regions (P<0.05). For the assessment methods, visual inspection was used by 28 laboratories (73.68%) for hemolytic samples and by 27 laboratories (71.05%) for lipemic samples; the colorimetric card method was used by 10 laboratories (26.32%) for assessing both hemolytic and lipemic samples; the instrumental method was used by 1 laboratory (2.63%) for assessing lipemic samples.3) The handling procedures for hemolytic and lipemic samples varied significantly and followed a gradient distribution pattern among 38 laboratories (including accepting samples for testing, accepting samples for concession testing, re-collecting samples, and rejecting samples and halting testing). With increasing severity of hemolysis and lipemia, more laboratories halted testing, and relatively fewer laboratories accepted samples for normal testing. 5 laboratories (13.16%) applied different handling procedures on serological and nucleic acid samples. Conclusion: This survey provides a reference and basis for analyzing gaps in the management of hemolytic and lipemic samples during the preanalyical phase in blood station laboratories in North China. It enables laboratories to identify the problems and deficiencies in the management of hemolytic and lipemic samples, to ensure preanalytical samples quality meets the established requirements, and to lay a foundation for promoting the homogenization and standardization of the regional sample quality management mode.

Objective The study aims to optimize the conditions for constructing orthotopic nude mouse models of liver cancer by injecting human liver tumor cell lines and to explore appropriate timings for drug administration. Methods Human hepatocellular carcinoma Hep3B and hepatoblastoma HepG2 cell lines, which stably expressing the luciferase reporter gene (LUC), were selected. The linear correlation between the luciferase luminescence intensity and the number of liver tumor cells was analyzed using a Small Animal In Vivo Imaging system to verify the luminescent efficiency of the human liver tumor cells. Different concentrations (8×10⁶, 2.4×10⁷, 7.2×10⁷ cells/mL) and resuspension media (PBS, Matrigel) of human liver tumor cell suspensions HepG2-LUC and Hep3B-LUC were orthotopically inoculated into the liver lobes of 5-week-old female BALB/c nude mice (12 groups, 7 mice each) to construct human liver tumor nude mouse orthotopic cancer models. Every 7 days, the weights of mice were recorded, and the growth of orthotopic tumors was monitored using the Small Animal In Vivo Imaging system. On day 35 post-cell inoculation, mouse livers were dissected, and pathological slices were prepared for HE staining to observe histopathological changes in liver tissues. Results The luminescence intensity of human liver tumor cell lines was positively correlated with the number of cells (R²=0.983 1, R²=0.970 5), indicating their suitability for orthotopic model construction. Successful modeling was achieved in the high-concentration groups of HepG2-LUC, the low-, medium-, and high-concentration groups of HepG2-LUC+Matrigel, the medium- and high-concentration groups of Hep3B-LUC, and the low-, medium-, and high-concentration groups of Hep3B-LUC+Matrigel. For both HepG2-LUC+Matrigel and Hep3B-LUC+Matrigel groups, mice in the high-concentration groups exhibited significantly reduced body weight compared to the low- and medium-concentration groups (both with P<0.05). The luminescence intensity of successfully modeled mice increased exponentially over time (R²>0.950 0), and reached a minimum of 1.0×10⁷ p/(s·cm²·sr) by day 14 post-transplantation. Mice in the low- and medium-concentration groups of HepG2-LUC and the low-concentration group of Hep3B-LUC showed no significant pathological changes, while the other groups exhibited evident liver tumors and hepatocyte lesions. Conclusion For the HepG2-LUC cell line, the recommended injection volume is 50 µL with a cell density of 2.4×10⁷ cells/mL, resuspended with Matrigel, followed by drug administration or prognostic measures on day 7 post-modeling. For the Hep3B-LUC cell line, the recommended injection volume is 50 µL with a cell density of 7.2×10⁷ cells/mL, not resuspended with Matrigel, with administration or prognostic measures on day 14 post-modeling.

Background: The revised Atlanta classification (RAC) and determinant-based classification (DBC) are widely used in assessing the severity of acute pancreatitis (AP). However, studies on comparison between RAC and DBC are scarce. Aims: To explore the accuracy of RAC and DBC in the assessment of AP severity. Methods: The clinical data of 481 AP patients from September 2015 to September 2019 at Taizhou People's Hospital were collected and severity were stratified according to RAC and DBC. The treatment and prognosis of each subgroup were compared. Results: On the basis of RAC, 269 (55.9%), 174 (36.2%) and 38 (7.9%) patients were classified as mild AP (MAP), moderate severe AP (MSAP) and severe AP (SAP), respectively. There were significant differences in mortality, ICU monitoring rate, ICU stay, operation rate and hospital stay among the above groups (P<0.05). On the basis of DBC, 319 (66.3%), 117 (24.3%), 34 (7.1%) and 11 (2.3%) patients were classified as MAP, MSAP, SAP and critical AP (CAP), respectively. There were significant differences in mortality, ICU monitoring rate, ICU stay, operation rate and hospital stay among the above groups (P<0.05). The ICU monitoring rate (100% vs. 63.2%, P=0.014), median ICU stay (35 days vs. 15 days, P=0.001), hospital stay [(50.36±21.54) days vs. (22.78±14.56) days, P=0.038] were significantly increased in CAP patients (classified by DBC) than those in SAP patients (classified by RAC), however, no significant differences in mortality and operation rate were found between the two groups (P=0.136; P=0.202). Conclusions: Both RAC and DBC can accurately stratify the severity of AP. SAP patients (classified by RAC) complicated with infected necrosis should be further classified into CAP.