Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

Objective:To construct a "local-systemic" dual-track prediction model integrating the resistance index (RI) score of bilateral sacroiliac joints and the systemic immune-inflammation index (SII), and to evaluate its predictive efficacy for the active stage of ankylosing spondylitis (AS).Methods:A total of 205 patients with ankylosing spondylitis (AS) from the Second Hospital of Lanzhou University between April 2022 and April 2025 were retrospectively enrolled and categorized into an active group ( n=113) and a remission group ( n=92). Hematological parameters and ultrasound data were collected. The resistance index (RI) of the synovial area in bilateral sacroiliac joints was measured by Doppler ultrasound and scored as follows: RI < 0.5: 3 points; RI 0.5~0.55: 2 points; RI > 0.55: 1 point; undetectable blood flow: 0 points. A total bilateral RI score (range 0 to 6) was calculated. The systemic immune-inflammation index (SII) was derived as (neutrophils× platelets)/lymphocytes. Normality was tested for all continuous variables; normally distributed data were compared using the t-test, while non-normally distributed data were analyzed with the Mann-Whitney U test. Categorical variables were compared using the χ2 test or analysis of variance.Variable selection was performed using Lasso regression, and a multivariate logistic regression model was developed to assess predictive performance. Results:The proportion of patients with a bilateral RI total score≥5 was significantly higher in the active group compared to the remission group (50 of 113, 44.3% vs 2 of 92, 2.2%, χ2=55.63, P<0.001). Multivariate logistic regression analysis, after adjustment for confounding variables, identified the SII [ OR(95% CI)=1.01(1.00, 1.01), P<0.001], bilateral RI total score [ OR(95% CI)=1.67(1.29, 2.26), P<0.001], erythrocyte sedimentation rate [ OR(95% CI)=1.19(1.11, 1.30), P<0.001], and mean corpuscular hemoglobin concentration [ OR(95% CI)=1.09(1.03, 1.17), P<0.001] as independent risk factors for active AS. Conversely, lymphocyte count [ OR(95% CI)=0.42(0.18, 0.92), P=0.030] and globulin [ OR(95% CI)=0.89(0.80, 0.99), P=0.040] were significantly associated with protective effects. The bilateral RI total score demonstrated the strongest predictive effect, with each 1-point increase associated with a 67% elevation in the risk of active disease. ROC curve analysis indicated that the area under the curve (AUC) for predicting whether AS is in the active disease phase was 0.94 for the combined model (SII+bilateral RI total score), compared with 0.93 for the SII-alone model and 0.92 for the bilateral RI total score-alone model, demonstrating superior predictive performance of the combined model (SII+bilateral RI total score). An online prediction tool has been developed based on the combined model. Conclusion:The dual-track prediction model, which integrates local joint hemodynamic characteristics and systemic immune-inflammatory status, facilitates a multidimensional assessment of the risk of active AS and provides an objective basis for early identification.

Objective:To compare enrichment and nucleic acid detection method for hepatitis E virus (HEV) in simulated cola samples.Methods:Cola samples experimentally contaminated with HEV were enriched using positively charged filter membrane-direct lysis (Method 1), tangential flow ultrafiltration membrane-direct lysis (Method 2), and Method 3 and 4 (with the addition of a PCR inhibitor removal step on the basis of Method 1 and 2, respectively), and were assayed by real-time fluorescence quantitative RT-PCR(RT-qPCR), and the recoveries and inhibition rates were compared. Digital RT-PCR(RT-dPCR) and RT-qPCR were applied to detect the recovery of HEV in different medium and low concentrations of experimentally contaminated cola samples; and the inhibition rate and sensitivity of HEV RNA detection in different matrices.Methods 3 was selected for virus enrichment of 8 commercially available cola specimens, RT-qPCR and RT-dPCR for HEV RNA detection.Results:The HEV recoveries of method 3 and 4 (10.44% and 10.16%) were higher than those of method 1 and 2 (4.89% and 0.32%), and the differences were statistically significant ( P<0.05). The inhibition rates of method 3 and 4 were smaller than the inhibition rates of method 1 and 2. The recoveries of HEV in medium concentration artificially contaminated cola samples by RT-qPCR and RT-dPCR were 17.04% and 16.28%, respectively, and for low concentration artificially contaminated cola samples were 6.91% and 4.65%, respectively, and the differences in recoveries between the two assays at the same concentration were not statistically significant ( P=0.260, P=0.107 ); Cola matrix inhibits the detection of both RT-qPCR and RT-dPCR assays. Eight commercially available cola specimens were negative for HEV. Conclusions:Detection of HEV in cola beverages can be done by positively charged filter membrane-direct lysis + inhibitor removal (method 3) or tangential flow ultrafiltration membrane-direct lysis + inhibitor removal (method 4) enrichment, followed by RT-dPCR or RT-qPCR, with a high recovery of virus detection.

Objective:To construct a volume management program for peritoneal dialysis patients in the peridialysis period.Methods:The intervention map was used as a guiding framework to build a first draft of a volume management program for peritoneal dialysis patients during the peridialysis period based on semi-structured interviews and a literature review in conjunction with a health belief model. Between December 2023 and February 2024, the first draft of the volume management program was revised by two rounds of expert consultation to produce a final program.Results:A total of 15 peritoneal dialysis medical and nursing experts were invited to complete two rounds of Delphi expert consultation. In the two rounds of expert consultation, 15 questionnaires were issued, and 15 valid questionnaires were recovered; the effective recovery rate was 100.00%, and the expert authority coefficient was both 0.903. The final constructed volume management program for peritoneal dialysis patients during the peridialysis period consisted of four first-level items (knowledge training, volume management plan development, behavioral assessment, and belief support), 10 second-level items, and 30 third-level items.Conclusions:The volume management program for peritoneal dialysis patients in the peridialysis period constructed in this study is scientific and can provide a reference for healthcare professionals.

Objective:To establish a digital reverse transcription polymerase chain reaction（dRT-PCR）detection method for hepatitis E virus（HEV）using nanoplates，and to provide technical reference for HEV monitoring in shellfish by combining virus enrichment pretreatment methods.Methods:The annealing temperature，primer and probe concentrations of HEV dRT-PCR were optimized，and the specificity of the method was evaluated；the sensitivity of this method for detecting HEV in water samples and oyster extracts was compared. The inhibition rate and recovery rate of HEV detection in artificially contaminated oyster samples were calculated，commercially available oyster samples were tested，and compare them with real-time fluorescence quantitative RT-PCR（qRT-PCR）method.Results:The optimized annealing temperature for HEV dRT-PCR was determined to be 60 ℃，and the final concentrations of primers and probes were 0.4 μmol/L，0.4 μmol/L，and 0.2 μmol/L，respectively，indicating good specificity. The sensitivity of both methods for detecting HEV RNA in water samples was higher than that in oyster extracts. The recovery rates of HEV in oyster specimens contaminated with HEV fecal suspension by dRT-PCR and qRT-PCR were 18.76% and 18.36%，respectively，with no statistically significant difference（ P>0.05）；the inhibition rates were 17.26% and 9.58%，respectively，with statistically significant differences（ P<0.05）；55 commercially available oyster samples were tested，and both methods detected HEV RNA positivity in the same sample. Conclusion:The dRT-PCR method established in this study，combined with “proteinase K digestion，PEG/NaCl precipitation，and chloroform/n-butanol extraction” pretreatment，has a good recovery effect on HEV in shellfish food containing a large amount of PCR inhibitors，and can achieve absolute quantification. It has certain application value in monitoring and risk assessment of HEV in shellfish food.

Objective:To establish a digital reverse transcription polymerase chain reaction（dRT-PCR）detection method for hepatitis E virus（HEV）using nanoplates，and to provide technical reference for HEV monitoring in shellfish by combining virus enrichment pretreatment methods.Methods:The annealing temperature，primer and probe concentrations of HEV dRT-PCR were optimized，and the specificity of the method was evaluated；the sensitivity of this method for detecting HEV in water samples and oyster extracts was compared. The inhibition rate and recovery rate of HEV detection in artificially contaminated oyster samples were calculated，commercially available oyster samples were tested，and compare them with real-time fluorescence quantitative RT-PCR（qRT-PCR）method.Results:The optimized annealing temperature for HEV dRT-PCR was determined to be 60 ℃，and the final concentrations of primers and probes were 0.4 μmol/L，0.4 μmol/L，and 0.2 μmol/L，respectively，indicating good specificity. The sensitivity of both methods for detecting HEV RNA in water samples was higher than that in oyster extracts. The recovery rates of HEV in oyster specimens contaminated with HEV fecal suspension by dRT-PCR and qRT-PCR were 18.76% and 18.36%，respectively，with no statistically significant difference（ P>0.05）；the inhibition rates were 17.26% and 9.58%，respectively，with statistically significant differences（ P<0.05）；55 commercially available oyster samples were tested，and both methods detected HEV RNA positivity in the same sample. Conclusion:The dRT-PCR method established in this study，combined with “proteinase K digestion，PEG/NaCl precipitation，and chloroform/n-butanol extraction” pretreatment，has a good recovery effect on HEV in shellfish food containing a large amount of PCR inhibitors，and can achieve absolute quantification. It has certain application value in monitoring and risk assessment of HEV in shellfish food.

Objective:To construct a volume management program for peritoneal dialysis patients in the peridialysis period.Methods:The intervention map was used as a guiding framework to build a first draft of a volume management program for peritoneal dialysis patients during the peridialysis period based on semi-structured interviews and a literature review in conjunction with a health belief model. Between December 2023 and February 2024, the first draft of the volume management program was revised by two rounds of expert consultation to produce a final program.Results:A total of 15 peritoneal dialysis medical and nursing experts were invited to complete two rounds of Delphi expert consultation. In the two rounds of expert consultation, 15 questionnaires were issued, and 15 valid questionnaires were recovered; the effective recovery rate was 100.00%, and the expert authority coefficient was both 0.903. The final constructed volume management program for peritoneal dialysis patients during the peridialysis period consisted of four first-level items (knowledge training, volume management plan development, behavioral assessment, and belief support), 10 second-level items, and 30 third-level items.Conclusions:The volume management program for peritoneal dialysis patients in the peridialysis period constructed in this study is scientific and can provide a reference for healthcare professionals.

Objective:To compare enrichment and nucleic acid detection method for hepatitis E virus (HEV) in simulated cola samples.Methods:Cola samples experimentally contaminated with HEV were enriched using positively charged filter membrane-direct lysis (Method 1), tangential flow ultrafiltration membrane-direct lysis (Method 2), and Method 3 and 4 (with the addition of a PCR inhibitor removal step on the basis of Method 1 and 2, respectively), and were assayed by real-time fluorescence quantitative RT-PCR(RT-qPCR), and the recoveries and inhibition rates were compared. Digital RT-PCR(RT-dPCR) and RT-qPCR were applied to detect the recovery of HEV in different medium and low concentrations of experimentally contaminated cola samples; and the inhibition rate and sensitivity of HEV RNA detection in different matrices.Methods 3 was selected for virus enrichment of 8 commercially available cola specimens, RT-qPCR and RT-dPCR for HEV RNA detection.Results:The HEV recoveries of method 3 and 4 (10.44% and 10.16%) were higher than those of method 1 and 2 (4.89% and 0.32%), and the differences were statistically significant ( P<0.05). The inhibition rates of method 3 and 4 were smaller than the inhibition rates of method 1 and 2. The recoveries of HEV in medium concentration artificially contaminated cola samples by RT-qPCR and RT-dPCR were 17.04% and 16.28%, respectively, and for low concentration artificially contaminated cola samples were 6.91% and 4.65%, respectively, and the differences in recoveries between the two assays at the same concentration were not statistically significant ( P=0.260, P=0.107 ); Cola matrix inhibits the detection of both RT-qPCR and RT-dPCR assays. Eight commercially available cola specimens were negative for HEV. Conclusions:Detection of HEV in cola beverages can be done by positively charged filter membrane-direct lysis + inhibitor removal (method 3) or tangential flow ultrafiltration membrane-direct lysis + inhibitor removal (method 4) enrichment, followed by RT-dPCR or RT-qPCR, with a high recovery of virus detection.

Objective To explore the role of long non-coding RNA smad7(Linc-smad7)in invasion and migration of pancreatic cancer(PC)cells and its mechanisms.Methods The expression level of Linc-smad7 in PC tissues and cell lines was detected by qRT-PCR assays.Transwell assays were performed to observe the effect of Linc-smad7 overexpression on the migration and invasion abilities of PaCa-2 cells.Luciferase reporter analysis was made to detect the direct binding effect of Linc-smad7 on miR-125b and miR-125b on Sirtuin1(SIRT1).qRT-PCR assays were used to detect the regulatory effect of Linc-smad7 on miR-125b expression in PaCa-2 cells.qRT-PCR and Western blotting assays were used to detect the regulatory effect of miR-125b on SIRT1 expression.Results Linc-smad7 was significantly increased in PC tissues and cell lines.Paca-2 cells with overexpressed Linc-smad7 showed higher migration and invasion abilities,while miR-125b expression was decreased.After the expression of miR-125b was increased,the expression of SIRT1 was decreased significantly.Luciferase reporter assays results suggested that Linc-smad7 directly targeted with miR-125b,and miR-125b directly bound with SIRT1.Increased Linc-Smad7 or decreased miR-125b could reverse the effect of SIRT1 inhibition on invasion and migration of PaCa-2 cells.Conclusion Linc-smad7 promotes invasion and migration of PaCa-2 cells through miR-125b/SIRT1 axis.

Objective:To further study the causes of acute occupational poisoning accidents, and to provide scientific basis and decision support for the prevention of accidents in advance.Methods:From September 2022 to May 2023, the literature was searched and 232 cases of acute occupational poisoning cases occurred from 2013 to 2022 were collected. The causal nodes of the accident were determined according to the expert score, and the interpretative structural model (ISM) was used to construct the correlation model between the causal nodes to obtain the hierarchical relationship between the factors. The influence of each causal node on the occurrence of acute occupational poisoning accidents was studied by using Bayesian network (BN), and the relationship and influence among the causal nodes were analyzed by Netica 5.18 software to establish the pre-prevention model of acute occupational poisoning accidents and identify the key causal factors.Results:A total of 23, 203, and 6 cases of significant, large, and medium acute occupational poisoning accidents were included, of which 179, 29, and 24 cases were asphyxiating gas, irritating gas, and mixed gas, respectively. ISM of acute occupational poisoning accidents divided the causal factors into a 7-layer and 3-level hierarchical structure model. Among them, operation conditions, protective measures, ventilation equipment, hidden trouble investigation, emergency management, illegal operation, equipment and facilities, and blind rescue were the direct causes of the occurrence and expansion of accidents. Warning devices, inspection situation, safety education situation, safety operation procedures, and technology in the production process were indirect influences that lead to the occurrence and expansion of accidents. Safety production responsibility system, enterprise supervision and management and government supervision were the deep-rooted influences. BN reasoning showed that the maximum probability causal chain of acute occupational poisoning accidents was as follows: safety production responsibility system→enterprise supervision and management→safety education and training→protective measures→accident occurrence. The key factors leading to the occurrence of acute occupational poisoning accidents were inadequate protective measures, equipment and facility failures, operational errors, ventilation equipment not being used properly and improper emergency management.Conclusion:In the prevention of acute occupational poisoning accidents, it is necessary to correctly use protective measures, test equipment and facilities before operation, operate according to regulations, ensure the normal use of ventilation equipment, and strengthen emergency management, so as to reduce the incidence of acute occupational poisoning accidents.