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.

Non-small cell lung cancer(NSCLC)is one of the malignant tumors with high morbidity and mortality worldwide.Ferroptosis is a new type of programmed cell death caused by abnormal accumulation of iron-dependent reactive oxygen species(ROS)leading to lipid peroxidation.It involves the balance between iron metabolism,lipid metabolism,oxy-gen free radical reaction and lipid peroxidation.Recent studies have found that ferroptosis is closely related to the occurrence and development of NSCLC.Due to the emergence of chemotherapy resistance and radiotherapy resistance in the treatment of NSCLC,there is an urgent need to develop new effective drugs and treatment strategies.Traditional Chinese medicine has unique advantages in the prevention and treatment of NSCLC due to its multi-targets and minimal side effects.In this review,we summarize the mechanism of ferroptosis in NSCLC,and discuss the research status of active ingredients of traditional Chinese medicine,single-herb traditional Chinese medicine and Chinese herbal compounds in the intervention of NSCLC through ferroptosis,in order to provide a new theoretical basis for the research of ferroptosis pathway and the prevention and treatment of NSCLC by targeted ferroptosis of traditional Chinese medicine.

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 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 summarize the best evidence for non-pharmacological interventions for anxiety and depression in patients receiving maintenance hemodialysis (MHD) .Methods:According to the "6S" evidence hierarchy model, evidence on non-pharmacological interventions for anxiety and depression in patients receiving MHD was systematically searched from top to bottom across databases and websites, including BMJ Best Practice, UpToDate, International Guideline Network, National Institute for Health and Care Excellence (NICE), International Society of Nephrology, Medlive, Cochrane Library, PubMed, Web of Science, China National Knowledge Infrastructure, and China Biology Medicine disc. The search timeframe was from September 1, 2013, to September 1, 2023. Two researchers independently evaluated the quality of the literature, extracted evidence, and summarized recommendations in collaboration with an evidence evaluation group.Results:A total of 18 articles were included, comprising one guideline, two expert consensuses, one clinical decision, one evidence summary, and 13 systematic reviews. A total of 22 best evidence points were summarized in six aspects: screening and assessment, exercise interventions, lifestyle improvements, psychological interventions, other forms of interventions, and personnel and information support.Conclusions:Evidence-based non-pharmacological interventions for anxiety and depression in patients receiving MHD are diverse. The application of evidence should adhere to the principle of individualization, and the combined use of different evidence-based interventions may yield better outcomes.