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A machine learning-based approach for quantitative evaluation of cell migration in Transwell assays using deformation characteristics was developed, providing a more efficient and automated evaluation way and adapting artificial intelligence trend.

The adhesion strength of a cancer cell is a valuable biophysical marker of its metastatic potential, tightly associated with various metastatic processes; for example, cancer cells escape from a primary tumor, and circulating tumor cells (CTCs) are anchored to the vessel wall. Although constriction-based microfluidics can realize the high-throughput characterization of single-cell deformability, due to the influence of cell size heterogeneity, accurately evaluating the adhesion strength of a cancer cell at high throughputs in constriction remains difficult. In this paper, we first proposed an approach for the assessment of adhesion strength of BGC-823 and SGC-7901 cell lines at high throughputs based on a friction coefficient using the constant velocity stage of cell transit in a long-channel constriction. Cell size was proven to be independent of adhesion strength by cell detachment assay; however, it has large effects on cell transit velocity in constriction. Therefore, the linear elasticity of a completely deformed cell in constriction is simplified as a compressed spring model, effectively reducing the influence of cell size heterogeneity. Theoretically, our proposed model can well offset the influence of cell size by cell transit velocity, while our experimental results indicate that the friction coefficient has a good linear relationship with the logarithm of the adhesion strength too. Therefore, our proposed approach can realize accurate characterization of cell adhesion strength at high throughputs using long-channel constriction-based microfluidics. Hence, this work might enrich the functions of constriction-based microfluidics and bring new insights into the characterization of mechanical phenotypes.

Online diagnosis of slight interturn short-circuit fault (ISCF) has always been difficult in low-speed permanent magnet synchronous motors (PMSMs). It is found that the residual zero-sequence voltage exists in healthy PMSMs due to the inherent unbalance of a low-speed motor. This article proposes a new ISCF diagnosis method based on zero-sequence voltage vector decomposition to solve this problem. The voltage vector whose phase angle is closest to the ISCF phase angle is extracted from the zero-sequence voltage vector, which improves the sensitivity of fault phase identification. Furthermore, the method of extracting phase voltage from PWM duty-cycle control voltage is proposed, which can reduce the error caused by measuring zero-sequence voltage with three-phase balanced resistance. Experiments demonstrate that the online detection limit of ISCF is reduced from 5% to 1% (short-circuit ratio) for a low-speed PMSM.

Before there are any megascopic cancer clinical symptoms, molecular diagnosis is the main method for detecting cancer-associated gene and tumor marker. The existing detection facilities are all expensive, complicated to operate, and time-consuming, thereby making them difficult to popularize and benefit humans. In this study, we proposed a high-throughput and cost-effective approach, which enables accurate detection of extremely rare cancer cells based on molecular diagnosis of target tumor marker and a lensfree diffraction imaging platform. This approach achieves high-speed and high-quality reconstruction of huge images, which well solves the problem that precise recognition is almost impossible utilizing raw image because of significant pattern magnification and serious overlaps. Furthermore, the cells which are labeled with immune microbeads can be screened using the determined covered pixel sets, which are extracted in different focus reconstruction planes. The recognition strategy is implemented based on set intersection. With this method, the target cancer cells can be rapidly and accurately screened in a large number of benign cell samples. Besides, the detection equipment is cost-effective and easy to operate and popularize. It is expected to be widely used as a diagnostic tool for early detection of cancer.

Yeast cell viability and concentration are the crucial factors affecting product quality in food industry and bio-fuel production, as well as the evaluation basis for environmental toxic compounds. To overcome the drawbacks of existing methods, including high error, false positive and low automation, we propose a highly accurate approach based on an automatic staining and high-throughput lensfree imaging platform. A precisely controlled staining process is implemented automatically, which largely avoids the error caused by inappropriate exposure times. Based on optical simulation analysis, energy distribution characteristics are proposed. They are better with steady theoretical evidence for live yeast cell recognition. The parameters are directly extracted from raw cell fingerprints without any reconstruction. Those progresses improve robustness and increase efficiency. Availability of this approach is validated by compared the detection results with gold-standard PI counting method in a H2O2 toxicity test. So it is expected to be widely used in industrial production and environmental toxicity assessment.

Cell viability is an important indicator while screening drugs. An inaccurate evaluation of cell viability can cause large errors in anti-tumor dose experiments, and this becomes very unfavorable for cancer treatment. Generally, cell viability refers to the ratio of the number of live cells to the total number of cells. However, this evaluation method does not consider the effects of differences in metabolic abilities between different living cells. In this paper, there is a new cell viability evaluation method based on respiratory thermodynamic feature that includes the respiratory intensity, proliferation rate, and heat released by cells. These three parameters can be directly measured by a microscopic infrared thermal imaging sensor, which is fast and non-invasive and does not require consumables. The three parameters were simultaneously measured based on a micro-infrared thermal imaging sensor and fitted to the mathematical model. Finally, the method was verified by comparing it with traditional c ounting method and comparing the amount of omethoate with traditional counting method. The results indicated that omethoate is 12.36% lower than in the traditional counting method with the same level of complete cell inactivation. Therefore, this method is more accurate than the conventional cell viability assessment method, and the dosage is more precise when the uniform effect is achieved, which provides a basis for precise doses in tumor treatment and can reduce side effects in the human body. This method has a significant effect on the manufacture of cell activity detecting sensors.

The accurate equivalent circuit model contributes to the better fitting of required cell characteristics, such as cell impedance, cell adhesion area, and cell-electrode distance. However, so many theoretical models on specific modules make it difficult for new researchers to understand the whole model of electrode system physically. Besides, the accurate theoretical model and the simplified calculations obviously contradict each other; therefore, it is confusing for many researchers to choose the proper theoretical model to calculate the specific parameters required. In this review, we first discuss the problems and suggestions of electrode system design for cell adhesion-based measurement in terms of parasitic capacitance, detection range of cell number, electric field distribution, and interelectrode distance. The design of electrode system for cell nonadhesion measurement was analyzed in terms of microchannel size and electrode position. Then, we discuss the advantages and disadvantages of various equivalent circuit models according to different requirements of researchers, and simultaneously provide a corresponding theoretical model for researchers. Various factors influencing electric impedance spectroscopy (EIS) such as the parasitic capacitance between microelectrodes, the changes of cell adhesion area and cell-electrode distance, the electrode geometry, and the surface conductivity of electrode were quantitatively analyzed to contribute to better understanding of the equivalent models. Finally, we gave advice to optimize the theoretical models further and perspectives on building uniform principles of theoretical model optimization in the future.

Cell viability evaluation is significantly meaningful for cellular assays. Some cells with weak viability are easily killed in the detection of anti-cancer drugs, while others with strong viability survive and proliferate, ultimately leading to the treatment failure or the inaccuracy of biological assays. Accurately evaluating cell viability heterogeneity still remains difficult. This paper proposed a multi-physical property information fusion method for evaluating cell viability heterogeneity based on multiple linear regression (MLR) on a single-channel integrated microfluidic chip. In this method, adhesion strengths τN, that are defined as the magnitude of shear stress needed to detach (100-N) % of cell population, were extracted as the independent variables of MLR model by calculating the linear fitting of the impedance-response curves for shear stress (cell detachment assay). Besides, by calculating the non-linear fitting of the drug dose-response curves for cancer cells (IC50 assay), the half-maximal inhibitory concentration (IC50) was extracted as the dependent variables of MLR model. The results show that the mean relative error of our fusion method reduces by 17.87% and 59.66% compared with the single-parameter method and the cell counting method. Moreover, through the theoretical analysis of the drug resistance heterogeneity model, it proved that there is a qualitative relationship between the cell adhesion strength and cell viability heterogeneity, which provides a theoretical basis for our fusion method.

The regulation of cell density is an important segment in microfluidic cell culture, particularly in the repeated assays. Traditionally, consistent cell density is difficult to achieve, owing to the inaccurate regulation of cell density with manual feedback. A novel cell culture method with automatic feedback is proposed for real-time regulation of cell density based on microfluidic chip in this paper. Here, an integrated microfluidic system combining cell culture, density detection, and control of proliferation rate was developed. Interdigital electrode structures were sputtered on the microchannel automatically to provide the real-time feedback information of impedance. The most sensitive frequency was studied to improve the detection resolution of the sensing chip. Cells were cultured on the chip surface and cell density was detected by monitoring the alternation of the impedance. The feedback controller was established by the least squares support vector machines. Then, the cell proliferation rate was automatically controlled using the feedback controller to achieve the desired cell density in the repeated assays. The results show that the standard error of this method is 2.8% indicating that the method can keep a consistency of cell density in the repeated assays. This study provides a basis for improving the accuracy and repeatability in the further assays of finding the optimal drug concentration.

Impedance measurement of cells using electric cell-substrate impedance sensing (ECIS) is widely accepted as an effective method to assess cell status. However, the sensitive frequency drifts over time with the changes of culture condition according to the built circuit model and experimental results. The area-normalized impedance spectrum (ANIS) method, which uses normalized area of impedance spectrum in a certain interval to assess cell viability, was proposed in this paper to solve the problem. The certain interval is calculated due to the threshold Zth, which is determined by 2% decline of the maximum impedance. Stabilities of two methods were analyzed by normalizing the area and impedance, showing that the normalized impedance fluctuated like a wave, while the normalized area was smoother. In addition, Cell Count Kit-8 (CCK-8) assay was carried out proving that the correlation index of ANIS method increases by 2.4% compared with impedance sensing method, and the maximum error of ANIS method decreases by 4%. Comparison analysis of two methods with random measurement noise was also discussed in this paper, and the results showed that the ANIS method was less affected by measurement noise than impedance sensing method. It demonstrated that the ANIS method is a more stable and accurate method to assess cell viability.

To overcome the drawbacks such as low automation and high cost, an approach for cell viability online detection is proposed, based on the extracted lensfree cell diffraction fingerprint characteristics. The cell fingerprints are acquired by a constructed large field-of-view (FOV) diffraction imaging platform without any lenses. The approach realizes distinguishing live and dead cells online and calculating cell viability index based on the number of live cells. With theoretical analysis and simulation, diffraction fingerprints of cells with different morphology are simulated and two characteristics are discovered to be able to reflect cell viability status effectively. Two parameters, fringe intensity contrast (FIC) and fringe dispersion (FD), are defined to quantify these two characteristics. They are verified to be reliable to identify live cells. In a cytotoxicity assay of different methyl mercury concentration on BRL cells, the proposed approach is used to detect cell viability. MTT method is also employed and the results of correlational analysis and Bland-Altman analysis prove the validity of the proposed approach. By comparison, it can be revealed that the proposed approach has some advantages over other present techniques. Therefore it may be widely used as a cell viability measurement method in drug screening, nutritional investigation and cell toxicology studies.

Due to the heterogeneity of cancer cell populations, the traditional evaluation approach of cell viability based on the cell counting assay is quite inaccurate for the dose-response test of anticancer drugs, cell toxicology assays, and other biochemical stimulations. In this paper, an evaluation approach of cell viability based on the cell detachment assay in a single-channel integrated microfluidic chip is proposed to improve the accuracy of cell viability assessment. The electrodes are coated by fibronectin for specific cell adhesion, and it is biologically significant to study the cell detachment assay in vitro. The maximum number of cells that can be detected by this sensor is about 105 cells (overgrowing), while the minimum is about 100 cells. This method is calibrated with the half-maximal inhibitory concentration assay, and the results show that the cell viability calculated by adhesion strength is more accurate than that evaluated using the cell counting assay. Meanwhile, the shear rate is transformed into shear stress for the comparability among the results in other papers. The most sensitive frequency is also determined as 1 kHz according to normalized impedance. Besides, the impedance of cell adhesion affected by different shear stresses is monitored to study the optimized plan for long-term culture of cells in the integrated microfluidic chip prepared for the cell detachment assay. Adhesion strength τ25, which is the magnitude of shear stress needed to detach 75% of cell population, is introduced to describe the cell adhesion forces. It is calculated and normalized based on the cell detachment assay to evaluate cell viability. The relative errors of the cell detachment method compared with those of the cell counting method decrease by 0.637 (0% FBS), 0.586 (0.5% FBS), and 0.342 (2% FBS).

Cell viability evaluation is very meaningful for cancer treatment and cell proliferation is an effective evaluation criterion for cell viability. Traditionally, cell proliferation rate is obtained only by monitoring for several cell cycles (about 12 h) and yet there is no rapid assessment method to evaluate cell proliferation. In this paper, a rapid, real-time and online assessment approach (about 12.5 min) of cell proliferation based on electrical wound-healing impedance characteristics is proposed to evaluate the cell proliferation rate and improve cell viability assessment. The electrical wounding threshold uth is firstly studied, then an electrical signal (u1 uth) is applied to wound cells on the electrodes to death. The real-time monitoring of cell proliferation is realized by Chi660E. The results indicate that the speed of cell recovery and proliferation become slower with a higher concentration of H2O2 added. On this basis, a model of the relationship between cell recovery impedance characteristics and cell proliferation is built for cell proliferation evaluation. Finally, the effect of temperature on cell recovery is also discussed to provide theoretical support for influencing factors of the biosensor design.

This is an experimental study on the distribution of antituberculosis drugs such as rifampin, isoniazid, and pyrazinamide in pathologic vertebrae of spinal tuberculosis in order to provide the regimen of chemotherapy and surgical treatment of spinal tuberculosis. The distribution of antituberculosis drugs in pathologic vertebral tissues matters greatly to the clinical effect of spinal tuberculosis' treatment. However, few pharmacokinetic studies and clinical reports about the concentrations of antituberculosis drugs in vertebral foci have been published so far. Twenty-four patients with spinal tuberculosis were divided into sclerotic group (n = 15) or non-sclerotic group (n = 9) according to radiographic features of lesion. All patients received chemotherapy with 2HRZ/2.5H(2)R(2)Z(2) for a duration of 4.5 months. Four weeks after chemotherapy all patients underwent surgery and the specimen of serum, ilium, and pathologic vertebral tissues, including sclerotic wall, subnormal osseous tissue, and foci were obtained during operation in 120-130 and 180-190 min after oral intake in the morning, respectively. The levels of three drugs in the specimen were measured using HPLC method. The concentration levels of isoniazid, rifampin and pyrazinamide varied greatly in different tissues of spinal tuberculosis, of which the bactericidal concentration values of isoniazid and rifampin and fivefold minimal inhibitory concentration (MICs) of pyrazinamide were found in subnormal vertebral bone and self-contrast ilium, the MICs of all drugs were found in sclerotic wall outside foci, and undetected level was found in foci inside the sclerotic wall. To patients without vertebral sclerotic wall around the foci, the isoniazid in foci was of bactericidal level and rifampin and pyrazinamide in foci corresponded to the MICs respectively. The sclerotic bone of affected vertebra plays an important role in blocking the antituberculosis drug's penetration into tuberculosis focus.