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The surface modification technique is applied in microfluidic devices to modify wettability and achieve different flow velocities. Currently available methods for poly(dimethylsiloxane) (PDMS) surfaces may reliably induce wettability changes, but only one area can be altered at a time. This work introduces the controlled gradient oxygen plasma modification (CGPM) technique, which layers several resin masks with varying porosities on top of the PDMS surface. Selective wettability of the PDMS surface can be achieved by varying the oxygen plasma density above the modified material's surface by manipulation of the porosity value. Through the implementation of the COMSOL plasma module, the impact of the mask's porosity, through-hole size, distribution, and distance from the PDMS surface on wettability was studied. The suggested CGPM approach was characterized by contact angle measurements. During the 25-second CGPM procedure, the PDMS surface's contact angle continually changed from 8.77° to 76.98°. An integrated microfluidic device was created and manufactured to identify D-dimers to illustrate this method. In comparison with standard oxygen plasma treatment, the D-dimer assay was finished in 10 minutes and had a dynamic range of 1–1000 ng mL−1, with a peak fluorescence signal augmentation of 78.3% and an average fluorescence intensity enhancement of 31.1%. [ABSTRACT FROM AUTHOR]

Breath analysis may provide a convenient and non-invasive method for clinical monitoring of chronic kidney disease (CKD) progression. However, few breath volatile organic compounds (VOCs) indicating progression of CKD have been reported. In this study, we used gas chromatography-mass spectrometry (GC-MS) for untargeted detection of breath VOCs in stage 1, 3, and 5 CKD patients. The results showed that, the levels of breath 4-heptanone, n-octane, and n-dodecane gradually increased from CKD stage 1 to stage 5, and their increasing rates from CKD stage 3 to stage 5 were higher than those from CKD stage 1 to stage 3. Gender, smoking habits, age, and body mass index (BMI) had insignificant impact on the levels of the three breath VOCs. The accuracies of the polynomial support vector machine (SVM) and K-nearest neighbour (KNN) models based on 4-heptanone + n-octane + n-dodecane combination in distinguishing CKD stages 1, 3, and 5 were 76.3% and 72.8%, respectively. The combination of 4-heptanone + n-octane + n-dodecane was superior to any single component for monitoring CKD progression. These discoveries have valuable implications for long-term clinical monitoring of CKD and improving our understanding of CKD. [ABSTRACT FROM AUTHOR]