ABSTRACT
Objective:Evaluation of combined inflammatory and coagulation markers for early identification of DIC in septic patients.Methods:This study was a single-center, retrospective, observational study involving 356 patients with sepsis. Sepsis was defined by the diagnostic criteria of Sepsis version 3.0. Definition of DIC was from the International Society on Thrombosis and Hemostasis (ISTH) DIC Score. Inflammatory biomarkers, including tumor necrosis factor (TNF)-α, interleukin (IL)-1β,2R,6,8,10, etc. and biomarkers of coagulation, like platelet (PLT), international normalized ratio (INR), D-dimer, fibrinogen (Fib), etc. were included in this study.Results:Among 356 patients with sepsis, 301 patients did not develop DIC (non-DIC) during hospitalization, 32 patients had DIC on the day of admission (overt-DIC), and 23 patients developed DIC within 1 week of admission (pre-DIC). Compared to non-DIC patients, pre-DIC patients had lower platelet counts and fibrinogen ( P < 0.05), higher levels of INR and D-dimer ( P < 0.05), higher levels of cytokines (TNF-α、IL-1β、IL-2R、IL-8、IL-10) and procalcitonin ( P < 0.05), higher APACHEⅡ and SOFA scores ( P < 0.05). Using receiver operating characteristics (ROC) analysis, we found that some biomarkers of coagulation and inflammation could discriminate pre-DIC from non-DIC patients. The area under the curve (AUC) of INR in the ROC analysis was 0.773 (95% CI: 0.696-0.851), the AUC of IL-2R was 0.700 (95% CI: 0.599-0.798) which is highest among inflammation markers, the highest AUC was obtained from the combination of platelets, INR, Fib, D-dimer and IL-2R (AUC = 0.843; 95% CI: 0.758-0.928). Kaplan-Meier survival curve suggested that high level of IL-2R (> 1064.5 U/mL) was a valuable predictor of 28-day mortality in septic patients. Conclusion:Inflammatory marker, IL-2R, is related to the occurrence of DIC in septic patients and has predictive value for pre-DIC. Combination of coagulation (platelets, INR, Fib, D-dimer) and inflammatory markers (IL-2R) can help to identify pre-DIC state in septic patients.
ABSTRACT
Various genetic switches have been developed to let engineered cells perform designed functions. However, a sustained input is often needed to maintain the on/off state, which is energy-consuming and sensitive to perturbation. Therefore, we developed a set of transcriptional switches for cell states control that were constructed by the inversion effect of site-specific recombinases on terminators. Such a switch could respond to a pulse signal and maintain the new state by itself until the next input. With a bottom-up design principle, we first characterized the terminators and recombinases. Then the mutual interference was studied to select compatible pairs, which were used to achieve one-time and two-time state transitions. Finally, we constructed a biological seven-segment display as a demonstration to prove such switch's immense potential for application.
Subject(s)
Recombinases , MetabolismABSTRACT
Objective To explore the clinical value of expression levels of serum COX-2 in patients with advanced NSCLC before and after EGFR-TKI treatment. Methods The serum was collected from 58 cases. Before and after targeted therapy , the serum COX-2 level was examined by ELISA. Meanwhile , CT scan was exercised to evaluate the treatment. Follow-up interview was done. The relationship among the change in expression level of serum COX-2 , efficacy and PFS was analyzed. Results The serum COX-2 level significantly decreased in the response group (t = 11.258, P = 0.000) and increased in the PD group (t = -7.759, P =0.000) after EGFR-TKI treatment, and not significantly changed in the SD group (t = 1.424, P = 0.170). Before treatment, the baseline serum COX-2 level in the response group was significantly higher than that in the SD group and the PD group (F = 20.852, P = 0.000 ). Before the targeted therapy, the higher the level of serum COX-2 was, the longer PFS patients would enjoy. Conclusion Detection of the serum COX-2 contributes to the judgment of therapeutic effect of EGFR-TKI and can be used as a prediction of EGFR-TKI drugs outcomes for patients with advanced NSCLC.