4D Printed Soft Microactuator for Particle Manipulation via Surrounding Medium Variation.

Soft actuators have assumed vital roles in a diverse number of research and application fields, driving innovation and transformative advancements. Using 3D molding of smart materials and combining these materials through structural design strategies, a single soft actuator can achieve multiple functions. However, it is still challenging to realize soft actuators that possess high environmental adaptability while capable of different tasks. Here, the response threshold of a soft actuator is modulated by precisely tuning the ratio of stimulus-responsive groups in hydrogels. By combining a heterogeneous bilayer membrane structure and in situ multimaterial printing, the obtained soft actuator deformed in response to changes in the surrounding medium. The response medium is suitable for both biotic and abiotic environments, and the response rate is fast. By changing the surrounding medium, the precise capture, manipulation, and release of micron-sized particles of different diameters in 3D are realized. In addition, static capture of a single red blood cell is realized using biologically responsive medium changes. Finally, the experimental results are well predicted using finite element analysis. It is believed that with further optimization of the structure size and autonomous navigation platform, the proposed soft microactuator has significant potential to function as an easy-to-manipulate multifunctional robot.

A 4D-Printing Inverse Design Strategy for Micromachines with Customized Shape-Morphing.

An active heterostructure with smart-response material used as "muscle" and inactive material as "skeleton" can deform over time to respond to external stimuli. 4D printing integrated with two-photon polymerization technology and smart material allows the material or characteristic distribution of active heterostructures to be defined directly at the microscale, providing a huge programmable space. However, the high degree of design freedom and the microscale pose a challenge to the construction of micromachines with customized shape morphing. Here, a reverse design strategy based on multi-material stepwise 4D printing is proposed to guide the structural design of biomimetic micromachines. Inspired by the piecewise constant curvature model of soft robot, a reverse design algorithm based on the Timoshenko model is developed. The algorithm can approximate 2D features to a constant-curvature model and determine an acceptable material distribution within the explored printing range. Three Chinese "Long" (Chinese dragon heralds of good fortune) designed by the strategy can deform to the customized shape. In addition, a microcrawler printed using this method can imitate a real inchworm gait. These results demonstrate that this method can be an efficient tool for the action or shape design of bionic soft microrobots or micromachines with predetermined functions.

Machine learning on ligand-residue interaction profiles to significantly improve binding affinity prediction.

Structure-based virtual screenings (SBVSs) play an important role in drug discovery projects. However, it is still a challenge to accurately predict the binding affinity of an arbitrary molecule binds to a drug target and prioritize top ligands from an SBVS. In this study, we developed a novel method, using ligand-residue interaction profiles (IPs) to construct machine learning (ML)-based prediction models, to significantly improve the screening performance in SBVSs. Such a kind of the prediction model is called an IP scoring function (IP-SF). We systematically investigated how to improve the performance of IP-SFs from many perspectives, including the sampling methods before interaction energy calculation and different ML algorithms. Using six drug targets with each having hundreds of known ligands, we conducted a critical evaluation on the developed IP-SFs. The IP-SFs employing a gradient boosting decision tree (GBDT) algorithm in conjunction with the MIN + GB simulation protocol achieved the best overall performance. Its scoring power, ranking power and screening power significantly outperformed the Glide SF. First, compared with Glide, the average values of mean absolute error and root mean square error of GBDT/MIN + GB decreased about 38 and 36%, respectively. Second, the mean values of squared correlation coefficient and predictive index increased about 225 and 73%, respectively. Third, more encouragingly, the average value of the areas under the curve of receiver operating characteristic for six targets by GBDT, 0.87, is significantly better than that by Glide, which is only 0.71. Thus, we expected IP-SFs to have broad and promising applications in SBVSs.

In silico binding profile characterization of SARS-CoV-2 spike protein and its mutants bound to human ACE2 receptor.

Severe acute respiratory syndrome coronavirus (SARS-CoV-2), a novel coronavirus, has brought an unprecedented pandemic to the world and affected over 64 million people. The virus infects human using its spike glycoprotein mediated by a crucial area, receptor-binding domain (RBD), to bind to the human ACE2 (hACE2) receptor. Mutations on RBD have been observed in different countries and classified into nine types: A435S, D364Y, G476S, N354D/D364Y, R408I, V341I, V367F, V483A and W436R. Employing molecular dynamics (MD) simulation, we investigated dynamics and structures of the complexes of the prototype and mutant types of SARS-CoV-2 spike RBDs and hACE2. We then probed binding free energies of the prototype and mutant types of RBD with hACE2 protein by using an end-point molecular mechanics Poisson Boltzmann surface area (MM-PBSA) method. According to the result of MM-PBSA binding free energy calculations, we found that V367F and N354D/D364Y mutant types showed enhanced binding affinities with hACE2 compared to the prototype. Our computational protocols were validated by the successful prediction of relative binding free energies between prototype and three mutants: N354D/D364Y, V367F and W436R. Thus, this study provides a reliable computational protocol to fast assess the existing and emerging RBD mutations. More importantly, the binding hotspots identified by using the molecular mechanics generalized Born surface area (MM-GBSA) free energy decomposition approach can guide the rational design of small molecule drugs or vaccines free of drug resistance, to interfere with or eradicate spike-hACE2 binding.

Discovery and development of small-molecule heparanase inhibitors.

Heparanase-1 (HPSE) is a promising yet challenging therapeutic target. It is the only known enzyme that is responsible for cleavage of heparan sulfate (HS) side chains from heparan sulfate proteoglycans (HSPGs), and is the key enzyme involved in the remodeling and degradation of the extracellular matrix (ECM). Overexpression of HPSE is found in various types of diseases, including cancers, inflammations, diabetes, and viral infections. Inhibiting HPSE can restore ECM functions and integrity, making the development of HPSE inhibitors a highly sought-after topic. So far, all HPSE inhibitors that have entered clinical trials belong to the category of HS mimetics, and no small-molecule or drug-like HPSE inhibitors have made similar progress. None of the HS mimetics have been approved as drugs, with some clinical trials discontinued due to poor bioavailability, side effects, and unfavorable pharmacokinetics characteristics. Small-molecule HPSE inhibitors are, therefore, particularly appealing due to their drug-like characteristics. Advances in the chemical spaces and drug design technologies, including the increasing use of in vitro and in silico screening methods, have provided new opportunities in drug discovery. This article aims to review the discovery and development of small-molecule HPSE inhibitors via screening strategies to shed light on the future endeavors in the development of novel HPSE inhibitors.

A Universal and Modular Scaffold for Heparanase Activatable Probes and Drugs.

Heparanase (HPSE) is an endo-ß-glucuronidase involved in extracellular matrix remodeling in rapidly healing tissues, most cancers and inflammation, and viral infection. Its importance as a therapeutic target warrants further study, but such is hampered by a lack of research tools. To expand the toolkits for probing HPSE enzymatic activity, we report the design of a substrate scaffold for HPSE comprised of a disaccharide substrate appended with a linker, capable of carrying cargo until being cleaved by HPSE. Here exemplified as a fluorogenic, coumarin-based imaging probe, this scaffold can potentially expand the availability of HPSE-responsive imaging or drug delivery tools using a variety of imaging moieties or other cargo. We show that electronic tuning of the scaffold provides a robust response to HPSE while simplifying the structural requirements of the attached cargo. Molecular docking and modeling suggest a productive probe/HPSE binding mode. These results further support the hypothesis that the reactivity of these HPSE-responsive probes is predominantly influenced by the electron density of the aglycone. This universal HPSE-activatable scaffold will greatly facilitate future development of HPSE-responsive probes and drugs.

Synthesis and structure-activity relationships of pyrazolo-[3,4-b]pyridine derivatives as adenosine 5'-monophosphate-activated protein kinase activators.

A series of pyrazolo[3,4-b]pyridine derivatives were designed, synthesized, and evaluated for their activation activity toward adenosine 5'-monophosphate-activated protein kinase (AMPK). According to the enzyme activity, the pyrazole N-H exposure and para substitution on the diphenyl group were proved to be essential for the activation potency. Compound 17f showed equal activation compared with A-769662. In the molecular modeling study, compound 17f exhibited important hydrogen bond interaction with Lys29, Asp88, and Arg83. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays on the NRK-49F cell line showed that potent enzyme activators could effectively inhibit cell proliferation, especially for 17f (EC50 [AMPKα1γ1ß1] = 0.42 µM, efficacy = 79%; IC50 [NRK-49F cell line] = 0.78 µM). These results might provide new insights to explore novel AMPK activators.

Elevated Expression of Kin17 in Cervical Cancer and Its Association With Cancer Cell Proliferation and Invasion.

BACKGROUND: Cervical cancer is one of the most common cancers in women worldwide. Emerging evidence suggests that kin17 is a tumor-promoting protein in some types of solid tumors. However, whether kin17 contributes to cervical cancer carcinogenesis remains unknown. METHODS: Kin17 expression in clinical samples from Guangdong Women and Children's Hospital and Health Institute was detected by immunohistochemical staining. A series of functional experiments including 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide assay, 5-bromo-2'-deoxyuridine assay, colony formation, transwell assay, flow cytometry of apoptosis, and cell cycle were performed to explore the roles of kin17 in cervical cancer cells HeLa. RESULTS: In this study, we showed for the first time that the expression of kin17 was significantly increased in clinical cervical cancer samples, and associated with tumor differentiation, lymph node metastasis, and ki-67 expression in a clinicopathologic characteristics review. Furthermore, silence of kin17 in HeLa cells inhibited cell proliferation, clone formation, cell cycle progression, migration, and invasion, and also promoted cell apoptosis. CONCLUSION: Our findings demonstrate that kin17 is closely related to the cell proliferation and invasion of cervical cancer and could be a novel diagnostic and therapeutic target for cervical cancer management. The underlying mechanisms should be elucidated in future research.

A road data assets revenue allocation model based on a modified Shapley value approach considering contribution evaluation.

This paper constructs a two-layer road data asset revenue allocation model based on a modified Shapley value approach. The first layer allocates revenue to three roles in the data value realization process: the original data collectors, the data processors, and the data product producers. It fully considers and appropriately adjusts the revenue allocation to each role based on data risk factors. The second layer determines the correction factors for different roles to distribute revenue among the participants within those roles. Finally, the revenue values of the participants within each role are synthesized to obtain a consolidated revenue distribution for each participant. Compared to the traditional Shapley value method, this model establishes a revenue allocation evaluation index system, uses entropy weighting and rough set theory to determine the weights, and adopts a fuzzy comprehensive evaluation and numerical analysis to assess the degree of contribution of participants. It fully accounts for differences in both the qualitative and quantitative contributions of participants, enabling a fairer and more reasonable distribution of revenues. This study provides new perspectives and methodologies for the benefit distribution mechanism in road data assets, which aid in promoting the market-based use of road data assets, and it serves as an important reference for the application of data assetization in the road transportation industry.

A Fluorogenic Green Merocyanine-Based Probe to Detect Heparanase-1 Activity.

Heparanase-1 (HPSE-1), an endo-ß-D-glucuronidase, is an extracellular matrix (ECM) remodeling enzyme that degrades heparan sulfate (HS) chains of heparan sulfate proteoglycans (HSPGs). HPSE-1 functions to remodel the ECM and thereby disseminate cells, liberate HS-bound bioactive molecules, and release biologically active HS fragments. Being the only known enzyme for the cleavage of HS, HPSE-1 regulates a number of fundamental cellular processes including cell migration, cytokine regulation, angiogenesis, and wound healing. Overexpression of HPSE-1 has been discovered in most cancers, inflammatory diseases, viral infections, among others. As an emerging therapeutic target, the biological role of HPSE-1 remains to be explored but is hampered by a lack of research tools. To expand the chemical tool-kit of fluorogenic probes to interrogate HPSE-1 activity, we design and synthesized a fluorogenic green disaccharide-based HPSE-1 probe using our design strategy of tuning the electronic effect of the aryl aglycon. The novel probe exhibits a highly sensitive 278-fold fluorescence turn-on response in the presence of recombinant human HPSE-1, while emitting green light at 560 nm, enabling the fluorescence imaging of HPSE-1 activity in cells.

Spontaneous redox reaction-mediated interfacial charge transfer in titanium dioxide/graphene oxide nanoanodes for rapid and durable lithium storage.

Titanium dioxide (TiO2) anodes show significant advantages in ion storage owing to their low cost, abundant sources, and small volume change during cycling. However, their intrinsic low electronic conductivity and sluggish ion diffusion coefficient restrict the application of TiO2 anodes, especially at high current densities. The construction of a covalently-bonded interface in TiO2-based composite anodes is an effective approach to solve these issues. Covalent bonds are usually formed in situ during materials synthesis processes, such as high-energy ball milling, solvothermal reactions, plasma-assisted thermal treatment, and addition of a linking agent for covalent coupling. In this study, we demonstrate that a spontaneous redox reaction between defective TiO2 powder and an oxidative graphene oxide (GO) substate can be used to form interfacial covalent bonds in composites. Different structural characterization techniques confirmed the formation of interfacial covalent bonds. Electrochemical measurements on an optimized sample showed that a specific capacity of 281.3 mA h g-1 after 200 cycles can be achieved at a current density of 1 C (1 C = 168 mA g-1). Even at a high rate of 50 C, the electrode maintained a reversible capacity of 97.0 mA h g-1. The good lithium storage performance of the electrode is a result of the uniquely designed composite electrodes with strong interfacial chemical bonds.

Skin-Inspired Capacitive Flexible Tactile Sensor with an Asymmetric Structure for Detecting Directional Shear Forces.

Flexible pressure sensors based on micro-/nanostructures can be integrated into robots to achieve sensitive tactile perception. However, conventional symmetric structures, such as pyramids or hemispheres, can sense only the magnitude of a force and not its direction. In this study, a capacitive flexible tactile sensor inspired by skin structures and based on an asymmetric microhair structure array to perceive directional shear force is designed. Asymmetric microhair structures are obtained by two-photon polymerization (TPP) and replication. Owing to the features of asymmetric microhair structures, different shear force directions result in different deformations. The designed device can determine the directions of both static and dynamic shear forces. Additionally, it exhibits large response scales ranging from 30 Pa to 300 kPa and maintains high stability even after 5000 cycles; the final relative capacitive change (ΔC/C0 ) is <2.5%. This flexible tactile sensor has the potential to improve the perception and manipulation ability of dexterous hands and enhance the intelligence of robots.

Novel PET Imaging Probe for Quantitative Detection of Senescence In Vivo.

Real-time detection of cellular senescence remains a clinical challenge. Here, we aimed to develop a positron emission tomography (PET) imaging probe targeting senescence-associated ß-galactosidase (SA-ß-Gal), the most widely used biomarker of cellular senescence, and investigate its performance for real-time in vivo quantitative detection of cellular senescence. A stable PET imaging agent [68Ga]Ga-BGal was obtained with a high labeling yield (90.0 ± 4.3%) and a radiochemical purity (>95%). [68Ga]Ga-BGal displayed high sensitivity and specificity for ß-Gal both in vitro and in vivo. The reaction and uptake of the probe correlated with the ß-Gal concentration and reaction time. In PET imaging, high ß-Gal-expressing CT26.CL25 tumors and doxorubicin-treated HeLa tumors showed high signals from [68Ga]Ga-BGal, while a low signal was observed in CT26.WT and untreated HeLa tumors. In summary, we showcased successful PET imaging of senescence in preclinical models using probe [68Ga]Ga-BGal. This finding holds the potential for translating senescence imaging into clinical applications.

Simulation of bi-directional pedestrian flow in corridor based on direction fuzzy visual field.

Bi-directional pedestrian flow in corridors is a complex dynamic system due to the diversity in pedestrian psychological characteristics. Incorporating individual differences of pedestrians is vital for improving pedestrian flow models. However, due to the inherent complexity and variability of pedestrian movement, model parameter calibration remains challenging. Controlled experiments are needed to collect empirical pedestrian movement data under different environments. This enriches the database on pedestrian movement patterns and provides necessary support for improving pedestrian flow models. To address this issue, we conducted controlled experiments to quantify pedestrian heterogeneity by defining the direction of fuzzy visual field (DFVF). The DFVF incorporates various static and dynamic pedestrian factors. We used it to modify the traditional cellular automata model. This improved model simulates bi-directional pedestrian movements in the corridors, reproduces density-speed and density-volume relationships, and reveals self-organization phenomena. Furthermore, an analysis was conducted to examine the impacts of pedestrian density and facility spatial layout on evacuation time. Pedestrian interactions were also studied to uncover fundamental bi-directional flow properties. As pedestrian density increased, the evacuation time showed an exponential upward trend. Corridor length significantly impacts evacuation time, while increasing corridor width helps control it. As crowd density increases, pedestrian flows exhibit three distinct steady states: the strolling flow at low densities, directional separated flows at medium densities, and dynamic multi-lane flows at high densities. In summary, the modified cellular automata model successfully incorporates pedestrian heterogeneity and reveals intrinsic bi-directional pedestrian flow patterns. This study provides valuable insights for pedestrian facility design and optimizing pedestrian flow organization.

Chemodynamic therapy agent optimized mesoporous TiO2 nanoparticles for Glutathione-Enhanced and Hypoxia-Tolerant synergistic Chemo-Sonodynamic therapy.

Sonodynamic therapy (SDT) can generate reactive oxygen species to kill cancer cells by activating sonosensitizers under ultrasound (US) irradiation. Nevertheless, its application is greatly limited by low quantum yield of sonosensitizers, high levels of endogenous glutathione (GSH) and tumor hypoxia. Herein, a GSH-activated sonosensitizers with synergistic therapy effect (chemodynamic therapy (CDT) and SDT) are developed by depositing Fe(III)-artemisinin infinite coordination polymers (Fe(III)-ART CPs) in pores of mesoporous TiO2 nanoparticles (NPs). The formed Fe(III)-ART-TiO2 NPs have high sono-induced electron-hole separation efficiency because the deposited Fe(III)-ART CPs can provide isolated intermediate bands to capture sono-induced electrons in TiO2 NPs. Meanwhile, Fe3+ in Fe(III)-ART-TiO2 NPs are reduced to Fe2+ by GSH with oxygen-deficient sites generated to further capture sono-induced electrons in TiO2 NPs. Based on this, the reaction efficiency between water molecules and sono-induced holes is high enough to generate numerous hydroxyl radicals (•OH) without oxygen participated for overcoming tumor hypoxia. Additionally, through consuming GSH, the generated Fe2+ can catalyze ART to produce C-centered free radicals for CDT. Owing to these characteristics, Fe(III)-ART-TiO2 NPs show significant tumor suppression ability and good biocompatibility in vivo. The strategy of using CDT agent to modify sonosensitizers offers new options to improve SDT effect without introducing harmful substances.

A Penalization Method for Estimating Heterogeneous Covariate Effects in Cancer Genomic Data.

In high-throughput profiling studies, extensive efforts have been devoted to searching for the biomarkers associated with the development and progression of complex diseases. The heterogeneity of covariate effects associated with the outcomes across subjects has been noted in the literature. In this paper, we consider a scenario where the effects of covariates change smoothly across subjects, which are ordered by a known auxiliary variable. To this end, we develop a penalization-based approach, which applies a penalization technique to simultaneously select important covariates and estimate their unique effects on the outcome variables of each subject. We demonstrate that, under the appropriate conditions, our method shows selection and estimation consistency. Additional simulations demonstrate its superiority compared to several competing methods. Furthermore, applying the proposed approach to two The Cancer Genome Atlas datasets leads to better prediction performance and higher selection stability.

In Silico Prediction of Pharmacokinetic Profile for Human Oral Drug Candidates Which Lack Clinical Pharmacokinetic Experiment Data.

BACKGROUNDS AND OBJECTIVES: In silico methods which can generate high-quality physiologically based pharmacokinetic (PBPK) models for arbitrary drug candidates are greatly needed to select developable drug candidates that escape drug attrition because of the poor pharmacokinetic profile. The purpose of this study is to develop a novel protocol to preliminarily predict the concentration profile of a target drug based on the PBPK model of a structurally similar template drug by combining two software platforms for PBPK modeling, the SimCYP simulator and ADMET Predictor. METHODS: The method was evaluated by utilizing 13 drug pairs from 18 drugs in the built-in database of the SimCYP software. All drug pairs have Tanimoto scores (TS) no less than 0.5. As each drug in a drug pair can serve as both target and template, 26 sets were studied in this work. Three versions (V1, V2 and V3) of models for the target drug were constructed by replacing the corresponding parameters of the template drug step by step with those predicted by ADMET Predictor for the target drug. V1 represents the replacement of molecular weight (MW), V2 includes the replacement of parameter MW, fraction unbound in plasma (fu), blood-to-plasma partition ratio (B/P), logarithm of the octanol-buffer partition coefficient (log Po:w) and acid dissociation constant (pKa). In V3, all above-mentioned parameters as well as human jejunum effective permeability (Peff), Vd and cytochrome P450 (CYP) metabolism parameters (Km, Vmax or CLint) are modified. Normalized root mean square error (NRMSE) was used for the evaluation of the model performance. RESULTS: We found that the performance of the three versions of the models depends on structural similarity of the drug pairs. For Group I drug pairs (TS ≤ 0.7), V2 and V3 performed better than V1 in terms of NRMSE; for Group II drug pairs (0.7 < TS ≤ 0.9), 8 out of 10 V3 models had NRMSE < 0.2, the cutoff we applied to judge whether the simulated concentration-time (C-T) curve was satisfactory or not. V3 outperformed the V1 and V2 versions. For the two drug pairs belonging to Group III (TS > 0.9), V2 outperformed V1 and V3, suggesting more unnecessary replacement can lower the performance of PBPK models. We also investigated how the prediction accuracy of ADMET Predictor as well as its collaboration with SimCYP influences the quality of PBPK models constructed using SimCYP. CONCLUSION: In conclusion, we generated practical guidance on applying two mainstream software packages, ADMET Predictor and SimCYP, to construct PBPK models for drugs or drug candidates that lack ADME parameters in model construction.

Deficiency of kin17 Facilitates Apoptosis of Cervical Cancer Cells by Modulating Caspase 3, PARP, and Bcl-2 Family Proteins.

Background: The treatment of cervical cancer in the late stage is still quite challenging, because of nonspecificity in conventional therapies and the lack of molecular targeted drugs. It is necessary to find novel biomarkers for cervical cancer treatment. Methods: In the present study, cervical cell lines HeLa and SiHa with kin17 knockdown were constructed by transfection of the recombinant lentiviral vector carrying KIN17 siRNA and screened by puromycin. The established cells with kin17 knockdown were determined by fluorescence observation and western blotting. Cell apoptosis and the mitochondrial membrane potential (MMP) were detected by flow cytometry. The activity of caspase 3 enzyme was tested by spectrophotometry. The expression profile of apoptosis-associated proteins was analyzed by western blotting. Finally, we used bioinformatics and proteomic data to analyze KIN-related genes in cervical cancer. Results: The results showed high fluorescent positive rates (>90%) and high gene silencing efficiency (>65%) in HeLa and SiHa cells transfected with gene silencing vectors. Moreover, kin17 deficiency decreased the MMP and increased the apoptosis rates in HeLa and SiHa cells, respectively. Furthermore, knockdown of kin17 enhanced the activity of caspase 3 enzyme, increased the expression of cleaved PARP and Bim, while decreasing the expression of Bcl-xL and phosphorylated BAD in HeLa and SiHa cells. Identification of KIN-related prognostic genes in cervical cancer revealed that a total of 5 genes (FZR1, IMPDH1, GPKOW, XPA, and DDX39A) were constructed for this risk score, and the results showed that CTLA4 expressions were negatively correlated with the risk score. Conclusion: Our findings demonstrated that kin17 knockdown facilitates apoptosis of cervical cancer cells by targeting caspase 3, PARP, and Bcl-2 family proteins. Besides, kin17 could regulate cancer cell apoptosis through the mitochondrial pathway and could be used as a novel therapeutic target for the regulation of cell apoptosis in cervical cancer.

Characterization of interconnectivity of gelatin methacrylate hydrogels using photoacoustic imaging.

Hydrogels can provide a three-dimensional microenvironment for cells and thus serve as an extracellular matrix in a biofabrication process. The properties of hydrogels, such as their porosity and mechanical properties, significantly influence the cell growth. However, there is still a lack of effective methods for characterizing the hydrogel structure noninvasively. Herein, a photoacoustic (PA) imaging-based method is proposed for the characterization of gelatin methacrylate (GelMA) hydrogels. Owing to their high PA contrast, red blood cells (RBCs) are included as mediators in the GelMA hydrogel to analyze its pore distribution. The interconnectivity of the pores is further analyzed through the lysis of RBCs. The diffusion of the RBC lysis buffer in the GelMA is consistent with the trend observed in simulations. The analyzed vitality of HEK293 cells in different GelMA hydrogels reveals that understanding the diffusion of solutes (i.e., nutrients) is a potential strategy to optimize the hydrogel parameters during biofabrication.

Label-free purification and characterization of optogenetically engineered cells using optically-induced dielectrophoresis.

Optogenetically engineered cell population obtained by heterogeneous gene expression plays a vital role in life science, medicine, and biohybrid robotics, and purification and characterization are essential to enhance its application performance. However, the existing cell purification methods suffer from complex sample preparation or inevitable damage and pollution. The efficient and nondestructive label-free purification and characterization of the optogenetically engineered cells, HEK293-ChR2 cells, is provided here using an optically-induced dielectrophoresis (ODEP)-based approach. The distinctive crossover frequencies of the engineered cells and the unmodified cells enable effective separation due to the opposite DEP forces on them. The ODEP-based approach can greatly improve the purity of the separated cell population and especially, the ratio of the engineered cells in the separated cell population can be enhanced by 275% at a low transfection rate. The size and the membrane capacitance of the separated cell population decreases and increases, respectively, as the ratio of the engineered cells grows in the cell population, indicating that successful expression of ChR2 in a single HEK293 cell makes its size and membrane capacitance smaller and larger, respectively. The results of biohybrid imaging with the optogenetically engineered cells demonstrated that cell purification can improve the imaging quality. This work proves that the separation and purification of engineered cells are of great significance for their application in practice.