OBJECTIVE To investigate the effect and mechanism of picroside Ⅱ on the malignant progression of non-small cell lung cancer （NSCLC）. METHODS A549 cells were divided into the control group， picroside Ⅱ low-， medium- and high- concentration groups， K6PC-5 [sphingosine kinase 1 （SPHK1） activator] group， and picroside Ⅱ high-dose+K6PC-5 group. Cell proliferation， migration and invasion were detected. Besides， the expression of proliferating cell nuclear antigen （PCNA）， matrix metalloproteinase-2 （MMP-2）， MMP-9， SPHK1， sphingosine-1-phosphate receptor 3 （S1PR3） and extracellular signal-regulated kinase 1/2 （ERK1/2） protein in the cells were also observed. BALB/c nude mice were subcutaneously inoculated with A549 cell suspension to establish NSCLC xenograft models. Then they were assigned to the nude mouse-control group， nude mouse-picroside Ⅱ low-， medium- and high-dose groups， nude mouse-K6PC-5 group， and nude mouse-picroside Ⅱ high-dose+K6PC-5 group （with 5 mice in each group） to investigate the effect of picroside Ⅱ on their tumor mass and volume. RESULTS Compared with the control group， the OD450 values， EdU-positive cell rates， scratch healing rates， cell invasion number， and the relative expression levels of PCNA， MMP-2， MMP-9， SPHK1， S1PR3 and ERK1/2 protein in the low-， medium- and high-concentration groups of picroside Ⅱ were significantly decreased. Compared with the nude mouse-control group， the tumor mass and volume in the nude mouse-low-， medium- and high-dose groups of picroside Ⅱ were significantly decreased or shrunk. The changes of above indicators were concentration/dose-dependent （P＜0.05）. The changing trend of the corresponding indicators in the K6PC-5 ZYTS181） group and the nude mouse-K6PC-5 group was opposite （P＜0.05）. Compared with the picroside Ⅱ high-concentration group or the nude mice-picroside Ⅱ high-dose group， the above quantitative indicators in the picroside Ⅱ high- concentration+K6PC-5 group cells and the nude mouse-picroside Ⅱ high-dose+K6PC-5 group nude mice were significantly increased or enlarged （P＜0.05）. CONCLUSIONS Picroside Ⅱ may inhibit the malignant progression of NSCLC by inhibiting SPHK1/sphingosine-1-phosphate/S1PR3 signaling pathway.

Objective: To understand the status and related knowledge requirements of health emergency literacy among college students in Shaanxi Province, so as to provide the basis for improving college students health emergency literacy. Methods: A total of 2 723 students from 18 colleges and universities in Shaanxi Province were selected by multi stage random sampling and simple random sampling methods in November 2023, and the survey of health literacy in emergency and knowledge requirements of health emergency literacy was conducted. Statistical analysis was carried out by using χ 2 test, Wilcoxon rank sum test, Kruskal-Wallis H test and Logistic regression analysis. Results: About 28.98% of the surveyed college students had a high level of health emergency literacy, which varied by students whether being only one child, whether having left behind experience, with different personality types, whether being student cadres, and with different frequencies of community or social activities ( χ 2=9.15, 7.90, 32.73, 16.29 , 120.25, P <0.05). The equivalence scores of the four dimensions of health emergency literacy from high to low were poisoning and nuclear and radiation (0.84), medical rescue (0.83), infectious disease (0.82), and basic knowledge and behavior ( 0.77 ). Logistic regression analysis found that college students with left-behind experience were negatively correlated with health emergency literacy and its four dimensions ( OR =0.74, 0.72, 0.80, 0.80, 0.83), while personality type (rational type), community or social activity frequency were positively correlated with the cognitive levels of health emergency literacy and its four dimensions among college students ( OR =1.57, 1.50, 1.33, 1.27, 1.38)( P <0.05). There was a higher level of basic knowledge and behavioral cognition among only child college students ( OR =3.73), and female students had a higher level of health emergency literacy, as well as awareness of infectious disease outbreaks and medical rescue ( OR =1.21, 1.28, 1.21)( P <0.05). The radar map showed that the level of health emergency literacy was positive development radar map. About 67.68 % of the students had a high willingness to acquire health emergency literacy knowledge, and the demand for basic health emergency knowledge and behavioral knowledge was the highest (52.37%). Conclusions College students have insufficient health emergency literacy, but they have the highest demand for health emergency. Publicity and education should be strengthened for students with left behind experience, irrational type, and low frequency of community or social activities.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Objective:To develop a prognostic prediction model for patients with colorectal cancer based on a peripheral blood cell composite score (PBCS) system.Methods:This retrospective observational study included patients who had primary colorectal cancer without distant metastasis, who did not undergo radiotherapy or chemotherapy before surgery, who did not receive leukocyte or platelet-raising therapy within 1 month before surgery, and whose postoperative pathology confirmed colorectal adenocarcinoma with complete tumor resection. Patients with severe anemia, infection, or hematologic diseases before surgery, as well as those with severe heart, lung, or other important organ diseases or concurrent malignant tumors, were excluded. In total, 1021 patients with colorectal cancer who underwent surgical treatment in the Department of Gastrointestinal Surgery of the Fourth Hospital of Hebei Medical University from April 2018 to April 2020 were retrospectively included as the training set (766 patients) and the internal validation set (255 patients). Additionally, using the same criteria, 215 patients with colorectal cancer who underwent surgical treatment in another treatment group from March 2015 to December 2020 were selected as the external validation set. The "surv_cutpoint" function in R software was used to analyze the optimal cut-off values of neutrophils, lymphocytes, and platelets, and a PBCS system was established based on the optimal cut-off values. The scoring rules of the PBCS system were as follows: Neutrophils and platelets below the optimal cut-off value = 1 point, otherwise 0 points; Lymphocytes above the optimal cut-off value = 1 point, otherwise 0 points. The scores of the three cell types were added together to obtain the PBCS. Univariate and multivariate Cox regression analyses were performed to explore the correlation between patients' clinicopathological features and prognosis, and a nomogram was constructed based on the Cox regression analysis to predict patients' prognosis. The accuracy of the nomogram prediction model was validated using the C-index, calibration curve, and decision curve analysis.Results:The optimal cut-off values for neutrophils, lymphocytes, and platelets were 4.40×10 9/L, 1.41×10 9/L, and 355×10 9/L, respectively. The patients were divided into high and low groups according to the optimal cut-off values of these cells. Survival curve analysis showed that a high lymphocyte count (training set: P=0.042, internal validation: P=0.010, external validation: P=0.029), low neutrophil count (training set: P=0.035, internal validation: P=0.001, external validation: P=0.024), and low platelet count (training set: P=0.041, internal validation: P=0.030, external validation: P=0.024) were associated with prolonged overall survival (OS), with statistically significant differences in all cases. Survival analysis of different PBCS groups showed that patients with a high PBCS had longer OS than those with a low PBCS ( P<0.05). Univariate and multivariate Cox regression analysis results showed that aspirin use history, vascular thrombus, neural invasion, CA19-9, N stage, operation time, M stage, and PBCS were independent factors affecting OS (all P<0.05). The PBCS was also an independent factor affecting disease-specific survival ( P<0.05), but not progression-free survival ( P>0.05). The above independent risk or protective factors were included in R software to construct a nomogram for predicting OS. The C-index (0.873), calibration curve, and decision curve analysis (threshold probability: 0.0%–75.2%) all indicated that the nomogram prediction model had good predictive performance for OS. Conclusion:This study demonstrates that the PBCS constructed based on preoperative peripheral blood levels of neutrophils, lymphocytes, and platelets is an independent factor associated with the prognosis of patients with colorectal cancer. The nomogram model constructed based on this score system exhibits good predictive efficacy for the prognosis of these patients.

Objective:To explore the factors associated with vascular luminal dilatational remodeling (VLDR) following balloon angioplasty for intracranial atherosclerotic stenosis (ICAS).Methods:A case-control study was conducted to analyze the data of symptomatic severe ICAS patients who received either paclitaxel-coated balloon angioplasty (PCBA) or plain balloon angioplasty (POBA) at our center from January 2019 to January 2022 and completed the six-month follow-up. The patients were divided into VLDR group and non-VLDR group according to whether VLDR occurred on follow-up digital subtraction angiography (DSA). The baseline data, preoperative and postoperative lesion characteristics (DSA), and perioperative related information were collected. The definition of VLDR was a decrease in luminal stenosis rate by more than 10% at the time of follow-up compared to the immediate postoperative period. Multivariate logistic regression was performed to analyze possible factors affecting VLDR such as balloon type, balloon length, and expansion time.Results:A total of 88 patients were included in this study, with 16 in the VLDR group and 72 in the non-VLDR group. The follow-up time for all included patients was 6.00 (5.00, 7.00) months. VLDR occurred in 18.2% (16/88) of cases, with a VLDR incidence of 30.4% (14/46) after PCBA and 4.8% (2/42) after POBA. Univariate logistic regression analysis revealed that treatment balloon type, balloon length, inflated time, immediate postoperative stenosis rate, follow-up time and Mori classification may affect the occurrence of VLDR. Multivariate logistic regression analysis showed that the use of paclitaxel-coated balloon (PCB) ( OR=9.82, 95% CI 1.99-48.49, P=0.005) and postoperative immediate stenosis rate ( OR=1.07, 95% CI 1.00-1.14, P=0.042) were independently associated with VLDR. Conclusion:The occurrence of VLDR following balloon angioplasty in ICAS was associated with the use of PCB and immediate postoperative stenosis rates, which will provide guidance for the clinical application of PCB.

Objective:To determine the motion detection uncertainty of the real-time CybeRay ? imaging system and patient intrafractional motion with thermoplastic mask-based immobilization. Methods:Real-time CybeRay ? imaging system was used for irradiation and treatment for head phantom and patients with brain tumors. All patients were immobilized with thermoplastic masks. Real-time imaging was delivered using kilovoltage projection images during radiotherapy. The detected patient motion data was collected from 5 head phantom measurements and 27 treatment fractions of 9 brain tumor patients admitted to Kaifeng Cancer Hospital. The accuracy and uncertainty of the motion monitoring system were determined. Results:The mean and standard deviation (SD) of the detected motion in the X, Y, and Z directions for phantom were (-0.02±0.41) mm, (-0.05±0.22) mm and (0.01±0.35) mm, respectively. The detected motion in the X, Y and Z directions for patents were (-0.13±0.48) mm, (-0.05±0.48) mm and (0.11±0.36) mm, respectively. After removing the motion detection uncertainty, the actual intrafractional motion of patients were (-0.11±0.25) mm, (0±0.43) mm and (0.10±0.08) mm in three directions, respectively. Conclusions:The uncertainty of real-time imaging-based motion monitoring system of CybeRay ? is less than 0.5 mm. It is feasible to apply thermoplastic masks for brain tumor patients in clinical practice, which can provide steady immobilization and limit the SD of patient intrafractional motion within 0.5 mm. Real-time imaging-based motion monitoring system of CybeRay ? is accurate for patient motion monitoring during frameless stereotactic radiosurgery/radiotherapy.

Objective:To develop a prognostic prediction model for patients with colorectal cancer based on a peripheral blood cell composite score (PBCS) system.Methods:This retrospective observational study included patients who had primary colorectal cancer without distant metastasis, who did not undergo radiotherapy or chemotherapy before surgery, who did not receive leukocyte or platelet-raising therapy within 1 month before surgery, and whose postoperative pathology confirmed colorectal adenocarcinoma with complete tumor resection. Patients with severe anemia, infection, or hematologic diseases before surgery, as well as those with severe heart, lung, or other important organ diseases or concurrent malignant tumors, were excluded. In total, 1021 patients with colorectal cancer who underwent surgical treatment in the Department of Gastrointestinal Surgery of the Fourth Hospital of Hebei Medical University from April 2018 to April 2020 were retrospectively included as the training set (766 patients) and the internal validation set (255 patients). Additionally, using the same criteria, 215 patients with colorectal cancer who underwent surgical treatment in another treatment group from March 2015 to December 2020 were selected as the external validation set. The "surv_cutpoint" function in R software was used to analyze the optimal cut-off values of neutrophils, lymphocytes, and platelets, and a PBCS system was established based on the optimal cut-off values. The scoring rules of the PBCS system were as follows: Neutrophils and platelets below the optimal cut-off value = 1 point, otherwise 0 points; Lymphocytes above the optimal cut-off value = 1 point, otherwise 0 points. The scores of the three cell types were added together to obtain the PBCS. Univariate and multivariate Cox regression analyses were performed to explore the correlation between patients' clinicopathological features and prognosis, and a nomogram was constructed based on the Cox regression analysis to predict patients' prognosis. The accuracy of the nomogram prediction model was validated using the C-index, calibration curve, and decision curve analysis.Results:The optimal cut-off values for neutrophils, lymphocytes, and platelets were 4.40×10 9/L, 1.41×10 9/L, and 355×10 9/L, respectively. The patients were divided into high and low groups according to the optimal cut-off values of these cells. Survival curve analysis showed that a high lymphocyte count (training set: P=0.042, internal validation: P=0.010, external validation: P=0.029), low neutrophil count (training set: P=0.035, internal validation: P=0.001, external validation: P=0.024), and low platelet count (training set: P=0.041, internal validation: P=0.030, external validation: P=0.024) were associated with prolonged overall survival (OS), with statistically significant differences in all cases. Survival analysis of different PBCS groups showed that patients with a high PBCS had longer OS than those with a low PBCS ( P<0.05). Univariate and multivariate Cox regression analysis results showed that aspirin use history, vascular thrombus, neural invasion, CA19-9, N stage, operation time, M stage, and PBCS were independent factors affecting OS (all P<0.05). The PBCS was also an independent factor affecting disease-specific survival ( P<0.05), but not progression-free survival ( P>0.05). The above independent risk or protective factors were included in R software to construct a nomogram for predicting OS. The C-index (0.873), calibration curve, and decision curve analysis (threshold probability: 0.0%–75.2%) all indicated that the nomogram prediction model had good predictive performance for OS. Conclusion:This study demonstrates that the PBCS constructed based on preoperative peripheral blood levels of neutrophils, lymphocytes, and platelets is an independent factor associated with the prognosis of patients with colorectal cancer. The nomogram model constructed based on this score system exhibits good predictive efficacy for the prognosis of these patients.