High-Performance Gel-Free and Label-Free Size Fractionation of Extracellular Vesicles with Two-Dimensional Electrophoresis in a Microfluidic Artificial Sieve.

Extracellular vesicles (EVs) are cell-derived particles that exhibit diverse sizes, molecular contents, and clinical implications for various diseases depending on their specific subpopulations. However, fractionation of EV subpopulations with high resolution, efficiency, purity, and yield remains an elusive goal due to their diminutive sizes. In this study, we introduce a novel strategy that effectively separates EV subpopulations in a gel-free and label-free manner, using two-dimensional (2D) electrophoresis in a microfluidic artificial sieve. The microfabricated artificial sieve consists of periodically arranged micro-slit-well structures in a 2D array and generates an anisotropic electric field pattern to size fractionate EVs into discrete streams and steer the subpopulations into designated outlets for collection within a minute. Along with fractionating EV subpopulations, contaminants such as free proteins and short nucleic acids can be simultaneously directed to waste outlets, thus accomplishing both size fractionation and purification of EVs with high performance. Our platform offers a simple, rapid, and versatile solution for EV subpopulation isolation, which can potentially facilitate the discovery of biomarkers for specific EV subtypes and the development of EV-based therapeutics.

Accelerated Electrophoretic Focusing and Purification of DNA Based on Synchronous Coefficient of Drag Alteration.

Synchronous coefficient of drag alteration refers to a multidimensional transport mechanism where a net drift of molecules is achieved under a zero-time-average alternating motive force by perturbing their drag coefficient synchronously with the applied force. An electrophoretic form of the method is often applied to focus and purify nucleic acids in a gel under rotating electric fields. However, this method requires lengthy operation due to the use of limited field strengths. Here, using DNA as target molecules, we demonstrate that the operation time can be reduced from hours to minutes by replacing polymer gel with a microfabricated artificial sieve. We also describe an electrophoretic protocol that facilitates the collection of purified DNA from the sieve, which is shown to yield amplifiable DNA from crude samples including the lysates of cultured cells and whole blood. The sieve can be further equipped with nucleic acid amplification and detection functions for a point-of-care diagnostic application.

Identification of a Novel CD8+ T cell exhaustion-related gene signature for predicting survival in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a major health concern, necessitating a deeper understanding of its prognosis and underlying mechanisms. This study aimed to investigate the mechanism and prognostic value of CD8+ T Cell exhaustion (CD8+ TEX)-related genes in HCC and construct a survival prognosis prediction model for patients with HCC. METHODS: CD8+ TEX-related genes associated with HCC prognosis were analysed and identified, and a prognostic prediction model was constructed using the 'least absolute shrinkage and selection operator' Cox regression model. Immunohistochemistry was used to verify the expression of the model genes in HCC tissues. A nomogram was constructed based on risk scores and clinical features, and its predictive efficacy was verified. The expression of STAM, ANXA5, and MAD2L2 in HCC cell lines was detected by western blotting; subsequently, these genes were knocked down in HCC cell lines by small interfering RNA, and their effects on the proliferation and migration of HCC cell lines were detected by colony formation assay, cck8, wound healing, and transwell assays. RESULTS: Six genes related to CD8+ TEX were included in the risk-prediction model. The prognosis of patients with HCC in the low-risk group was significantly better than that of those in the high-risk group. Cox regression analysis revealed that the risk score was an independent risk factor for the prognosis of patients with HCC. The differentially expressed genes in patients with high-risk HCC were mainly enriched in the nucleotide-binding oligomerization domain-containing protein-like receptor, hypoxia-inducible factor-1, and tumour programmed cell death protein (PD)-1/PD-L1 immune checkpoint pathways. The CD8+ TEX-related genes STAM, ANXA5, and MAD2L2 were knocked down in HCC cell lines to significantly inhibit cell proliferation and migration. The prediction results of the nomogram based on the risk score showed a good fit and application value. CONCLUSION: The prediction model based on CD8+ TEX-related genes can predict the prognosis of HCC and provide a theoretical basis for the early identification of patients with poor HCC prognosis.

Measurement algorithm for wafer alignment based on principal component analysis.

We propose a novel measurement algorithm for wafer alignment technology based on principal component analysis (PCA) of a mark image. The waveform of the mark is extracted from the enlarged mark image, which is collected by CCD. The position of the mark center on the CCD can be calculated based on the extracted waveform. By applying PCA to the mark image, the first principal component containing position information of the mark can be obtained. Therefore PCA can be used to extract the waveform from the mark image. Compared with the typical waveform extraction method (the summed projection (SP) method), the proposed PCA method can use the position information contained in the mark image more effectively. Through simulation and experiment, it is proved that the proposed PCA method can improve the contrast of the normalized waveform, and then improve the alignment accuracy.

Sub-pixel position estimation algorithm based on Gaussian fitting and sampling theorem interpolation for wafer alignment.

Wafer alignment is the core technique of lithographic tools. Image-processing-based wafer alignment techniques are commonly used in lithographic tools. An alignment algorithm is used to analyze the alignment mark image for obtaining the mark position. The accuracy and speed of the alignment algorithm are very important for guaranteeing the overlay and throughput of lithographic tools. The most commonly used algorithm in image-processing-based alignment techniques is the self-correlation method. This method has a high accuracy, but the calculation is complex, and the calculation speed is slow. In this paper, we propose a sub-pixel position estimation algorithm based on Gaussian fitting and sampling theorem interpolation. The algorithm first reconstructs the alignment signal by sampling theorem interpolation and then obtains the sub-pixel position of the mark by Gaussian fitting. The accuracy and robustness of the algorithm are verified by testing the simulated marks and experimentally captured marks. The repeat accuracy can reach 1/100 pixels, which is in the same level with the self-correlation method. The calculation speed is highly improved compared with the self-correlation method, which needs only about 1/3 of even short calculation time.

Conductance Interplay in Ion Concentration Polarization across 1D Nanochannels: Microchannel Surface Shunt and Nanochannel Conductance.

Ion concentration polarization has received much interest in the past decade for lab-on-a-chip applications, primarily preconcentration of biomolecules and water desalination. Studying the basic phenomenon in microfluidics has also generated new knowledge, which could be pivotal in the design of novel devices. Many studies, however, have focused on designs featuring nanoslits/slots or surface-patterned ion-selective membranes whereas the characteristics of 1D nanochannels are still lacking. Here, we report on ion concentration polarization across highly ordered 1D nanochannels in isolation as well as in array formation. Intriguingly, the nanochannels in isolation exhibit a linear current-voltage characteristic at low salt concentrations despite the confirmed presence of ion-depletion zone, which is associated with the diffusion-limited transport and the consequent nonlinearity in the classical sense. The characteristic in array formation breaks away from the linearity with a peculiar dip in current for a critical salt concentration in the dilute limit. We describe these findings based on the interplay between the nanochannel conductance and the conductance of the neighboring microchannel walls (the so-called surface shunt). Also, the nanochannel transport is identified with the mobility of protons more closely than that of salt cations. We attribute fast transport to phosphorus-doped silicate glass, the nanochannel material known to have very fine pores likely to be populated with protons as a result of moisture and carbon dioxide adsorption from the air. The nanochannels possess a tubular profile 70 nm in nominal diameter and fabricated through thermal reflow of doped glass on silicon without using advanced lithography.

Oxaliplatin resistance is enhanced by saracatinib via upregulation Wnt-ABCG1 signaling in hepatocellular carcinoma.

BACKGROUND: Chemo-resistance in hepatocellular carcinoma (HCC) is a major problem, and acquired drug resistance prevents cancer therapies from achieving complete responses. Molecular targeting therapy presents an opportunity to impede tumor through combination or sequential therapy, while the accurate effect is vague. METHODS: The efficacy of combinations between oxaliplatin and anti-cancer molecular targeting drugs was screened. Strangely, the combined chemotherapy with oxaliplatin and saracatinib induced significantly antagonistic effects. Then the antitumor effects of combined treatment with saracatinib and oxaliplatin were confirmed in wide type HCC as well as in saracatinib- and oxaliplatin-resistant HCC. RNA sequencing was used to explore the resistance mechanism, and the roles of ATP-binding cassette transporter G1 (ABCG1) and Wnt signaling in oxaliplatin resistance were confirmed. RESULTS: Chemotherapy with oxaliplatin and saracatinib individually induced strong anti-HCC effects, while combined or sequential treatment of HCC cells with these two drugs exhibited reduced efficacy compared to treatment with the single drugs. And it was saracatinib treatment caused oxaliplatin resistance. RNA sequencing revealed 458 genes that were altered by treatment with saracatinib and oxaliplatin. Of these, the gene encoding ABCG1 and Wnt-associated genes were significantly upregulated. Upregulation of ABCG1 and oxaliplatin resistance were associated with activation of Wnt signaling. Interference with ABCG1 expression or inhibition of Wnt signaling resulted in reversal of the saracatinib-induced oxaliplatin resistance in HCC. CONCLUSIONS: These studies demonstrated that combined or sequential chemotherapy with oxaliplatin and saracatinib reduced antitumor efficacy, and this antagonism was attributed to the activation of Wnt signaling and upregulation of ABCG1 by saracatinib.

Micromirror array allocation algorithm based on deconvolution.

Freeform illumination is one of the necessary techniques in 28 nm technology nodes and beyond. The micromirror array (MMA) has been widely used in lithography freeform illumination systems due to its programmability and high free degree. The MMA allocation algorithm is the key to generate the target freeform illumination source. Its computational speed and precision affect the generation speed and precision of the target illumination source as well as the process window size of the generated illumination pupil directly. In this paper, an MMA allocation method based on deconvolution is proposed. The target freeform illumination source can be obtained directly with the deconvolution and quantization processes. Without the iterative optimization process, the computational speed of the proposed method is much faster than that of the traditional method. The numerical simulation results show that the difference between the target source and the MMA source generated using the proposed method is less than 0.2%. Compared with the process window loss of the target source, the process window loss of the MMA source generated by the proposed deconvolution method is less than 0.5%. Compared with the traditional allocation method, the runtime of the proposed method is less than 0.05 s and has improved by 1463 times.

Fast thermal aberration model for lithographic projection lenses.

A novel fast thermal aberration model for lithographic projection lenses is proposed. In the model, optical intensity calculation is simplified by using pupil intensity mapping, and simplified formulas for temperature calculation are derived to realize fast simulation of thermal aberration. The simulation results using the proposed model are compared with that of experiments carried out on a commercial lithography tool. The R-square of the simulation is better than 0.99 and the simulation time is about 10 minutes. Experiments and simulations show that the model is capable of predicting the thermal aberration or the variation trend of the thermal aberration of lithographic projection lenses fast and accurately. The model is applicable in projection lens design, evaluating degree of production risk posed by thermal aberration, etc.

Jones pupil metrology of lithographic projection lens and its optimal configuration in the presence of error sources.

Mueller matrix imaging polarimeter (MMIP) can be used to measure the polarization aberration (PA) of a lithographic projector in the form of the Mueller pupil, while the Jones pupil is required for lithographic imaging simulations, projection lens design and PA evaluation. In this paper, a Jones pupil measurement method of lithographic projection lens is proposed. The measurement device of the method is the same as an MMIP, but a new polarimetric measurement equation is derived to solve the Jones pupil directly from the Kronecker product of the Jones matrix and the measured intensities. Two new polarimeter configurations with the minimum condition number are designed to further improve the accuracy in the presence of error sources. The performance of the method is evaluated by measurement errors of a typical Jones pupil in the presence of error sources. Comparisons between the proposed method and the conventional method, in which the Jones pupil is converted from the Mueller pupil measured by MMIP, are given. The results validate that the measurement accuracy of the Jones pupil is significantly improved without increasing the complexity of existing measurement systems.

Remodeling of hepatic stellate cells orchestrated the stroma-derived oxaliplatin-resistance through CCN3 paracrine in hepatocellular carcinoma.

BACKGROUND: Hepatic stellate cells (HSCs) have a key role in fibrogenesis and in the filtrates of the hepatocellular carcinoma (HCC) stroma, in which they are remodeled and play a critical role in HCC progression. However, the precise role of HSCs trending, infiltration and paracrine in orchestrating the stroma-derived oxaliplatin-resistance in HCC is still vague. METHODS: The chemo-resistant models were established to explore the correlation between HSC cells and the condition of chemoresistance. The HCC clinical samples were collected to confirm this phenomenon. Then, the relationship between secretory CCN3 from oxaliplatin-resistant HCC and the infiltration of HSCs in associated HCC microenvironment was evaluated. Finally, the role and mechanism of HSCs remodeling in the orchestration of oxaliplatin-resistant HCC were explored. RESULTS: The increased infiltration of HSCs and collagen accumulation were found in the microenvironment of oxaliplatin-resistant HCC. The cDNA profiles of the oxaliplatin-resistant HCC was reanalyzed, and CCN3 was one of the significantly increased genes. In HCC clinical samples, the levels of CCN3 and α-SMA are positively correlated, and high expression of CCN3 and α-SMA are positively associated with malignant phenotype and poor prognosis. Then the enhanced abilities of migration and proliferation of HSCs, and elevation of the cytokines paracrine from HSCs relating to HCC malignancy were proved in vitro and in vivo, and which were related to CCN3-ERK signaling pathway activation. CONCLUSIONS: HSCs remodeling are positively related to CCN3 paracrine in hepatocellular carcinoma, which orchestrated the stroma-derived resistance to chemotherapy in HCC.

Paracrine effects of CCN3 from non-cancerous hepatic cells increase signaling and progression of hepatocellular carcinoma.

BACKGROUND: The liver microenvironment plays a key role in the progression and metastasis of hepatocellular carcinoma (HCC). Gene expression profiling of non-cancerous hepatic tissues obtained from patients with metastatic HCC exhibit a unique immune response signature, including upregulation of CCN3. However, the role of CCN3 secreted from non-cancerous hepatic tissues in the progression of HCC remains unclear. METHODS: Using tissue microarrays, we examined CCN3 in non-cancerous hepatic tissues of patients with HCC and correlated expression with clinical and pathological features. In addition, CCN3 localization and mechanisms of HCC progression were investigated in tissues and cell lines. Finally, correlations between CCN3 and cirrhosis were explored in patients. RESULTS: CCN3 was primarily localized to hepatic cells of non-cancerous hepatic tissues and was associated with vascular invasion and poor prognosis in patients with HCC. CCN3 expression in non-cancerous hepatic tissues also correlated with the degree of liver fibrosis. Compared with conditioned media from wild-type LO2 cells, conditioned media from hepatic cell line LO2 activated by LX2 (aLO2-CM) induced CCN3 expression and HCC cell proliferation and metastasis. Further, aLO2-CM activated MAPK signaling and epithelial-mesenchymal transition in HCC cells. Finally, CCN3 was inversely related to cirrhosis in the prognosis of HCC and negatively regulated hepatic stellate cells (HSCs) in vitro with downregulation of α-SMA, TGF-ß, and collagens. CONCLUSIONS: CCN3 was secreted from hepatic cells activated by HSCs and increased MAPK signaling, EMT, proliferation and metastasis of HCC cells. CCN3 was also inversely related to cirrhosis, regulating HSCs through a negative feedback loop.

Microfluidic device for the analysis of MDR cancerous cell-derived exosomes' response to nanotherapy.

Exosomes are membrane-enclosed extracellular vesicles which have been indicated as important biomarkers of cancerous cell functionality, such as multiple drug resistance (MDR). Nanoparticles based chemotherapy is a promising strategy to overcome MDR by interfering the production and composition of exosomes. Therefore, tumor-derived exosomes post-treatment by nanotherapy are implied to play critical roles of biomarkers on cancer MDR analysis. However, the efficient isolation of such exosomes from extracellular environment for their therapeutic response analysis remains challenging. In this study, we presented a microfluidic device featured exosome specific anti-CD63 immobilized ciliated micropillars, which were capable to isolate cancer-derived exosomes from cell culture medium. The captured exosomes can be recovered intact by dissolving the cilia on the micropillars using PBS soaking. Owing to the immobilized antibody in the microfluidic device, nearly 70% of exosome from the biofluid could be isolated. So the secreted exosomes of the MDR and ordinary human breast cancer cells pre-treated by free drug or nanotherapy could be isolated with high purity. The drug contents of the isolated exosomes were measured to analysis of the exosomal pathway response of MDR cells to different chemotherapeutic formulations. Such analyses and further definition of the biomarkers of these exosomes could benefit the future investigations of accurately and reliably determine design principle, functional activity, and mechanisms of nanotherapy for MDR overcoming.

A nanofluidic memristor based on ion concentration polarization.

This paper reports the very first nanofluidic memristor based on the principle of ion concentration polarization (ICP). ICP is induced through highly-ordered cylindrical nanochannels. These so-called nanocapillaries are formed within a glass layer on silicon through a thermal reflow process and low-resolution lithography. The current-voltage plots exhibit characteristic pinched-hysteresis loops and the concurrent tracking of fluorescent charged particles correlates the memristive behaviour to the ICP. The ICP-based nanofluidic memristor could have implications in emerging areas such as integrated fluid-based logic circuits.

Clinical Evaluation of a Blood Assay to Diagnose Paucibacillary Tuberculosis via Bacterial Antigens.

BACKGROUND: The diagnosis of active tuberculosis (TB) cases primarily relies on methods that detect Mycobacterium tuberculosis (Mtb) bacilli or their DNA in patient samples (e.g., mycobacterial culture and Xpert MTB/RIF assays), but these tests have low clinical sensitivity for patients with paucibacillary TB disease. Our goal was to evaluate the clinical performance of a newly developed assay that can rapidly diagnose active TB cases by direct detection of Mtb-derived antigens in patients' blood samples. METHODS: Nanoparticle (NanoDisk)-enriched peptides derived from the Mtb virulence factors CFP-10 (10-kDa culture factor protein) and ESAT-6 (6-kDa early secretory antigenic target) were analyzed by high-throughput mass spectrometry (MS). Serum from 294 prospectively enrolled Chinese adults were analyzed with this NanoDisk-MS method to evaluate the performance of direct serum Mtb antigen measurement as a means for rapid diagnosis of active TB cases. RESULTS: NanoDisk-MS diagnosed 174 (88.3%) of the study's TB cases, with 95.8% clinical specificity, and with 91.6% and 85.3% clinical sensitivity for culture-positive and culture-negative TB cases, respectively. NanoDisk-MS also exhibited 88% clinical sensitivity for pulmonary and 90% for extrapulmonary TB, exceeding the diagnostic performance of mycobacterial culture for these cases. CONCLUSIONS: Direct detection and quantification of serum Mtb antigens by NanoDisk-MS can rapidly and accurately diagnose active TB in adults, independent of disease site or culture status, and outperform Mycobacterium-based TB diagnostics.

Calibration method of overlay measurement error caused by asymmetric mark.

With the process nodes extending to sub-10-nm in advanced semiconductor manufacturing, the overlay requirements keep progressively scaling down, which makes it very important to measure overlay precisely for monitoring on-product performance. The overlay mark being asymmetrical when generated via the lithography process, this asymmetry will be slightly variated even in the same process or same lot, and it will bring overlay measurement error. In general, the wafer alignment data are used for correcting this overlay measurement error, utilizing its wavelengths and polarizations dependence. However, there is a residual error that cannot be removed because the structures of the wafer alignment mark and overlay mark are different and are affected by the process differently. In this paper, a new method is proposed for calibrating the overlay measurement error introduced by the asymmetric mark, which is based on the relationship between measurement data of the overlay mark and the single layer mark. The validity is verified by simulation with different types of asymmetric mark. It is very useful for improving overlay measurement accuracy and for understanding how the overlay measurement error is affected by the asymmetric mark.

Underwater Object Segmentation Based on Optical Features.

Underwater optical environments are seriously affected by various optical inputs, such as artificial light, sky light, and ambient scattered light. The latter two can block underwater object segmentation tasks, since they inhibit the emergence of objects of interest and distort image information, while artificial light can contribute to segmentation. Artificial light often focuses on the object of interest, and, therefore, we can initially identify the region of target objects if the collimation of artificial light is recognized. Based on this concept, we propose an optical feature extraction, calculation, and decision method to identify the collimated region of artificial light as a candidate object region. Then, the second phase employs a level set method to segment the objects of interest within the candidate region. This two-phase structure largely removes background noise and highlights the outline of underwater objects. We test the performance of the method with diverse underwater datasets, demonstrating that it outperforms previous methods.

Automatic spectral calibration for polarization-sensitive optical coherence tomography.

Accurate wavelength assignment is important for Fourier domain polarization-sensitive optical coherence tomography. Incorrect wavelength mapping between the orthogonal horizontal (H) and vertical (V) polarization channels leads to broadening the axial point spread function and generating polarization artifacts. To solve the problem, we propose an automatic spectral calibration method by seeking the optimal calibration coefficient between wavenumber kH and kV. The method first performs a rough calibration to get the relationship between the wavelength λ and the pixel number x of the CCD for each channel. And then a precise calibration is taken to bring both polarization interferograms in the same k range through the optimal calibration coefficient. The optimal coefficient is automatically obtained by evaluating the cross-correlation of A-line signals. Simulations and experiments are implemented to demonstrate the performance of the proposed method. The results show that, compared to the peaks method, the proposed method is suitable in both Gaussian and non-Gaussian spectrums with a higher calibration accuracy.

Depth-dependent dispersion compensation for full-depth OCT image.

A depth-dependent dispersion compensation algorithm for enhancing the image quality of the Fourier-domain optical coherence tomography (OCT) is presented. The dispersion related with depth in the sample is considered. Using the iterative method, an analytical formula for compensating the depth-dependent dispersion in the sample is obtained. We apply depth-dependent dispersion compensation algorithm to process the phantom images and in vivo images. Using sharpness metric based on variation coefficient to compare the results processed with different dispersion compensation algorithms, we find that the depth-dependent dispersion compensation algorithm can improve image quality at full depth.

Monocular Vision-Based Underwater Object Detection.

In this paper, we propose an underwater object detection method using monocular vision sensors. In addition to commonly used visual features such as color and intensity, we investigate the potential of underwater object detection using light transmission information. The global contrast of various features is used to initially identify the region of interest (ROI), which is then filtered by the image segmentation method, producing the final underwater object detection results. We test the performance of our method with diverse underwater datasets. Samples of the datasets are acquired by a monocular camera with different qualities (such as resolution and focal length) and setups (viewing distance, viewing angle, and optical environment). It is demonstrated that our ROI detection method is necessary and can largely remove the background noise and significantly increase the accuracy of our underwater object detection method.