Identification and quantification of serum KIN17 protein based on ELISA assay and exploring its clinical diagnostic value in liver cancer.

It has been well-elaborated that KIN17 protein is closely related to the expression, development and prognosis of liver cancer; however, till date, there has been no study about detecting the KIN17 protein in serum, which is important to developing clinical applications. The objective of this work is to detect serum KIN17 protein by the ELISA method and to explore the diagnostic significance of the KIN17 protein in liver cancer. First, we verified the ELISA method for serum KIN17 measurement according to five aspects: accuracy, precision, specificity, stability and detection limit. Results illustrate that the recovery rate of the ELISA method can be controlled between 90% and 110%, the variation coefficient of intra-assay can be controlled within 16%, and the variation coefficient of inter-assay can be controlled within 10%. There is no non-specific reaction with common tumor markers, and the detection limit can reach 0.125 ng mL-1. The results show that the KIN17 protein can be detected by ELISA, and there is a significant rise in KIN17 concentration in a liver cancer group compared with a healthy group, whose average concentrations are 1.730 ng mL-1 and 0.3897 ng mL-1, respectively. On this basis, we hypothesize that the serum KIN17 protein can serve as a potential biomarker of liver cancer and be measurable with the verified ELISA system after specific ultrafiltration and centrifugation, which is of great significance for the diagnosis and treatment of liver cancer.

Anthropogenic perturbations on heavy metals transport in sediments in a river-dominated estuary (Modaomen, China) during 2003-2021.

Heavy metal pollutants in sediment greatly impact the estuarine environment and ecosystems, increasingly influenced by anthropogenic perturbations. Here, we examined the surface sediments of the Modaomen estuary in 2003, 2015, and 2021 to understand how human-induced changes influence the fate of heavy metals in the estuary's sediments. The potential ecological risk index (RI) suggests Cd should be the priority pollutant for environmental pollution control due to its high toxicity coefficient. In each sampling period, two main sources were identified through normalized heavy metals and PCA-MLR: natural and mixed anthropogenic sources (agricultural, industrial, and traffic activities), reflecting an increase in heavy metals pollution, later mitigated by successful environmental protection measures. Moreover, anthropogenic activities have not only impacted the sources discharge of heavy metals but have also influenced their spatial and temporal distribution through factors such as land reclamation, leading to sediment coarsening and reduced heavy metal content in specific areas.

Photoacoustic speckle pattern interferometry for detecting cracks of different sizes.

A system and method for non-destructive detection of cracks of different width and depths based on digital speckle interferometry coupled with pulsed laser excitation is introduced and tested. Based on photoacoustic effect, acoustic waves are induced onto the rear of the samples by pumping a pulsed laser beam on it. The generated mechanical wave propagates from the rear surface of the sample to the front while front surface is monitored by speckle interferometry. In order to acquire information about surface deformation, the front surface is illuminated by continuous wave laser and interference are imaged onto the camera as speckle images. After processing the produced fringe patterns, it indicates the presence and location of the cracks in qualitative way. In this study, the system and method mentioned above are validated by detecting medium density fiberboard with simulated cracks. The fringe patterns from areas with or without defects are compared and discussed. Besides, the system and method to distinguish and predict cracks sizes is proposed and validated.

Phase aberration adaptive compensation in digital holography based on phase imitation and metric optimization.

We proposed a numerical and accurate quadratic phase aberration compensation method in digital holography. A phase imitation method based on Gaussian 1σ-criterion is used to obtain the morphological features of the object phase using partial differential, filtering and integration successively. We also propose an adaptive compensation method based on a maximum-minimum-average- α-standard deviation (MMAαSD) evaluation metric to obtain optimal compensated coefficients by minimizing the above metric of the compensation function. The effectiveness and robustness of our method are demonstrated by simulation and experiments.

Automatic elimination of phase aberrations in digital holography based on Gaussian 1σ- criterion and histogram segmentation.

We propose a numerical and automatic quadratic phase aberration elimination method in digital holography for phase-contrast imaging. A histogram segmentation method based on Gaussian 1σ-criterion is used to obtain the accurate coefficients of quadratic aberrations using the weighted least-squares algorithm. This method needs no manual intervention for specimen-free zone or prior parameters of optical components. We also propose a maximum-minimum-average-standard deviation (MMASD) metric to quantitatively evaluate the effectiveness of quadratic aberration elimination. Simulation and experimental results are demonstrated to verify the efficacy of our proposed method over the traditional least-squares algorithm.