Classification between Normal and Cancerous Human Urothelial Cells by Using Micro-Dimensional Electrochemical Impedance Spectroscopy Combined with Machine Learning

Although the high incidence and recurrence rates of urothelial cancer of the bladder (UCB) are heavy burdens, a noninvasive tool for effectively detecting UCB as an alternative to voided urine cytology, which has low sensitivity, is yet to be reported. Herein, we propose an intelligent discrimination method between normal (SV-HUC-1) and cancerous (TCCSUP) urothelial cells by using a combination of micro-dimensional electrochemical impedance spectroscopy (µEIS) with machine learning (ML) for a noninvasive and high-accuracy UCB diagnostic tool. We developed a unique valved flow cytometry, equipped with a pneumatic valve to increase sensitivity without cell clogging. Since contact between a cell and electrodes is tight with a high volume fraction, the electric field can be effectively confined to the cell. This enables the proposed sensor to highly discriminate different cell types at frequencies of 10, 50, 100, 500 kHz, and 1 MHz. A total of 236 impedance spectra were applied to six ML models, and systematic comparisons of the ML models were carried out. The hyperparameters were estimated by conducting a grid search or Bayesian optimization. Among the ML models, random forest strongly discriminated between SV-HUC-1 and TCCSUP, with an accuracy of 91.7%, sensitivity of 92.9%, precision of 92.9%, specificity of 90%, and F1-score of 93.8%

Input Shaping Based on an Experimental Transfer Function for an Electrostatic Microscanner in a Quasistatic Mode

This paper describes an input shaping method based on an experimental transfer function to effectively obtain a desired scan output for an electrostatic microscanner driven in a quasistatic mode. This method features possible driving extended to a higher frequency, whereas the conventional control needs dynamic modeling and is still ineffective in mitigating harmonics, sub-resonances, and/or higher modes. The performance of the input shaping was experimentally evaluated in terms of the usable scan range (USR), and its application limits were examined with respect to the optical scan angle and frequency. The experimental results showed that the usable scan range is as wide as 96% for a total optical scan angle (total OSA) of up to 9° when the criterion for scan line error is 1.5%. The usable scan ranges were degraded for larger total optical scan angles because of the nonlinear electrostatic torque with respect to the driving voltage. The usable scan range was 90% or higher for most frequencies up to 160 Hz and was drastically decreased for the higher driving frequency because fewer harmonics are included in the input shaping process. Conclusively, the proposed method was experimentally confirmed to show good performance in view of its simplicity and its operable range, quantitatively compared with that of the conventional control

Enhanced nanoplasmonic heating in standoff sensing of explosive residues with infrared reflection-absorption spectroscopy

Various standoff sensing techniques employing optical spectroscopy have been developed to address challenges in safely identifying trace amounts of explosives at a distance. A flexible anodic aluminum oxide (AAO) microcantilever and a high-power quantum cascade laser utilized as the infrared (IR) source are used for standoff IR reflection-absorption spectroscopy to detect explosive residues on a metal surface. Standoff sensing of trinitrotoluene (TNT) is demonstrated by exploiting the high thermomechanical sensitivity of a bimetallic AAO microcantilever. Moreover, sputtering gold onto the fabricated AAO nanowells generates a strong scattering and absorption of IR light in the wavelength range of 5.18 μm to 5.85 μm resulting in enhanced nanoplasmonic heating. Utilizing the IR absorption enhancement in this wavelength range, the plasmonic AAO cantilever could detect TNT molecules 7 times better than the bimetallic AAO cantilever.Natural Sciences and Engineering Research Council (NSERC

multiplexing molecular spectroscopy via metasurface using plasmonic resonance energy transfer

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metasurface-driven hyperspectral imaging with plasmonic resonance energy transfer

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Microelectrical Impedance Spectroscopy for the Differentiation between Normal and Cancerous Human Urothelial Cell Lines: Real-Time Electrical Impedance Measurement at an Optimal Frequency

Purpose. To distinguish between normal (SV-HUC-1) and cancerous (TCCSUP) human urothelial cell lines using microelectrical impedance spectroscopy (μEIS). Materials and Methods. Two types of μEIS devices were designed and used in combination to measure the impedance of SV-HUC-1 and TCCSUP cells flowing through the channels of the devices. The first device (μEIS-OF) was designed to determine the optimal frequency at which the impedance of two cell lines is most distinguishable. The μEIS-OF trapped the flowing cells and measured their impedance at a frequency ranging from 5 kHz to 1 MHz. The second device (μEIS-RT) was designed for real-time impedance measurement of the cells at the optimal frequency. The impedance was measured instantaneously as the cells passed the sensing electrodes of μEIS-RT. Results. The optimal frequency, which maximized the average difference of the amplitude and phase angle between the two cell lines (p<0.001), was determined to be 119 kHz. The real-time impedance of the cell lines was measured at 119 kHz; the two cell lines differed significantly in terms of amplitude and phase angle (p<0.001). Conclusion. The μEIS-RT can discriminate SV-HUC-1 and TCCSUP cells by measuring the impedance at the optimal frequency determined by the μEIS-OF

The Clinicopathological and Prognostic Significance of Nrf2 and Keap1 Expression in Hepatocellular Carcinoma

Nuclear factor E2-related factor2 (Nrf2) activation is associated with both cytoprotective effects and malignant behavior of cancer cells. This study aimed to evaluate the clinicopathological implications of the expression of Nrf2, pNrf2, and its regulator Keap1 in human hepatocellular carcinomas (HCCs). Tissue microarrays consisting of 285 surgically resected HCCs were immunohistochemically stained with pNrf2, Nrf2, Keap1, stemness-related markers (keratin 19 (K19), epithelial cell adhesion molecule (EpCAM)), carbonic anhydrase IX (CAIX), epithelial&ndash;mesenchymal transition (EMT)-related markers (ezrin, uPAR, E-cadherin), and p53, and the results were correlated with the clinicopathological features. pNrf2 expression was significantly associated with increased proliferative activity, as well as EpCAM, ezrin, p53, and CAIX expression and E-cadherin loss (p &lt; 0.05, all). Strong cytoplasmic Nrf2 expression was associated with CAIX and ezrin expression (p &lt; 0.05, both). Keap1 was associated with increased proliferative activity, portal vein invasion, EMT-related markers, and p53 expression in CAIX-negative HCCs (p &lt; 0.05, all). Both pNrf2 and cytoplasmic Nrf2 expression were associated with decreased overall survival (p &lt; 0.05, both), and cytoplasmic Nrf2 expression was an independent predictor of decreased overall survival on multivariate analysis (hazard ratio 4.15, p &lt; 0.001). Both pNrf2 and cytoplasmic Nrf2 expression were associated with poor survival and aggressive behavior of HCC. In addition, Keap1 expression was also associated with aggressive HCC behavior in CAIX-negative HCCs, suggesting that Keap1 expression should be interpreted in the context of hypoxia status

A comparison of Ki-67 counting methods in luminal Breast Cancer: The Average Method vs. the Hot Spot Method

<div><p>In spite of the usefulness of the Ki-67 labeling index (LI) as a prognostic and predictive marker in breast cancer, its clinical application remains limited due to variability in its measurement and the absence of a standard method of interpretation. This study was designed to compare the two methods of assessing Ki-67 LI: the average method vs. the hot spot method and thus to determine which method is more appropriate in predicting prognosis of luminal/HER2-negative breast cancers. Ki-67 LIs were calculated by direct counting of three representative areas of 493 luminal/HER2-negative breast cancers using the two methods. We calculated the differences in the Ki-67 LIs (ΔKi-67) between the two methods and the ratio of the Ki-67 LIs (H/A ratio) of the two methods. In addition, we compared the performance of the Ki-67 LIs obtained by the two methods as prognostic markers. ΔKi-67 ranged from 0.01% to 33.3% and the H/A ratio ranged from 1.0 to 2.6. Based on the receiver operating characteristic curve method, the predictive powers of the KI-67 LI measured by the two methods were similar (Area under curve: hot spot method, 0.711; average method, 0.700). In multivariate analysis, high Ki-67 LI based on either method was an independent poor prognostic factor, along with high T stage and node metastasis. However, in repeated counts, the hot spot method did not consistently classify tumors into high vs. low Ki-67 LI groups. In conclusion, both the average and hot spot method of evaluating Ki-67 LI have good predictive performances for tumor recurrence in luminal/HER2-negative breast cancers. However, we recommend using the average method for the present because of its greater reproducibility.</p></div

The distribution of Ki-67 labeling indices in 493 luminal breast cancers.

<p>The X-axis represents the individual cases, arranged in ascending order based on their Ki-67 labeling index (LI) measured by the average method. The Y-axis represents the individual Ki-67 LIs measured by the hot spot method (the edge of the light gray area) and the average method (dotted line), and the values measured at the “cold spot”, the area with the lowest Ki-67 LI (the edge of the dark gray area). The extent of the light gray colored area represents the difference between the Ki-67 LI measured at the hot spot and the cold spot (Δ Ki-67).</p