Single-cell Model Research Articles

Three-Dimensional Modeling of the Optical Switch Based on Guided-Mode Resonances in Photonic Crystals.

Optical switching is an essential part of photonic integrated circuits and the focus of research at the moment. In this research, an optical switch design working on the phenomenon of guided-mode resonances in a 3D photonic-crystal-based structure is reported. The optical-switching mechanism is studied in a dielectric slab-waveguide-based structure operating in the near-infrared range in a telecom window of 1.55 µm. The mechanism is investigated via the interference of two signals, i.e., the data signal and the control signal. The data signal is coupled into the optical structure and filtered utilizing guided-mode resonance, whereas the control signal is index-guided in the optical structure. The amplification or de-amplification of the data signal is controlled by tuning the spectral properties of the optical sources and structural parameters of the device. The parameters are optimized first using a single-cell model with periodic boundary conditions and later in a finite 3D-FDTD model of the device. The numerical design is computed in an open-source Finite Difference Time Domain simulation platform. Optical amplification in the range of 13.75% is achieved in the data signal with a decrease in the linewidth up to 0.0079 µm, achieving a quality factor of 114.58. The proposed device presents great potential in the field of photonic integrated circuits, biomedical technology, and programmable photonics.

3D printing to construct in vitro multicellular models of melanoma.

Currently, there is a lack of suitable models for in-vitro studies of malignant melanoma and traditional single cell culture models no longer reproduce tumor structure and physiological complexity well. The tumor microenvironment is closely related to carcinogenesis and it is particularly important to understand how tumor cells interact and communicate with surrounding nonmalignant cells. Three-dimensional (3D) in vitro multicellular culture models can better simulate the tumor microenvironment due to their excellent physicochemical properties. In this study, 3D composite hydrogel scaffolds were prepared fromgelatin methacrylate and polyethylene glycol diacrylate hydrogels by 3D printing and light curing techniques, and 3D multicellular in vitro tumor culture models were established by inoculating human melanoma cells (A375) and human fibroblasts cells on them. The cell proliferation, migration, invasion, and drug resistance of the 3D multicellular in vitro model was evaluated. Compared with the single-cell model, the cells in the multicellular model had higher proliferation activity and migration ability, and were easy to form dense structures. Several tumor cell markers, such as matrix metalloproteinase-9 (MMP-9), MMP-2, and vascular endothelial growth factor, were highly expressed in the multicellular culture model, which were more favorable for tumor development. In addition, higher cell survival rate was observed after exposure to luteolin. The anticancer drug resistance result of the malignant melanoma cells in the 3D bioprinted construct demonstrated physiological properties, suggesting the promising potential of current 3D printed tumor model in the development of personalized therapy, especially for discovery of more conducive targeted drugs.

Establishment of a novel co-cultured liver cancer model based on tumor microenvironment

Objective: To construct a new co-cultured liver cancer research model composed of activated hepatic stellate cells (aHSC) and liver cancer cells, explore the efficacy difference between it and traditional model, so as to establish a liver cancer research model in vitro and in vivo that can reflect the real clinical efficacy. Methods: A new co-culture model of liver cancer consisting of aHSC and liver cancer cells was constructed. The differences in efficacy between the new co-culture model and the traditional single cell model were compared by cytotoxicity test, cell migration test, drug retention test and in vivo tumor inhibition test. Western blot was used to detect the drug-resistant protein P-gp and epithelial-mesenchymal transition-related proteins. Masson staining was used to observe the deposition of collagen fibers in tumor tissues of tumor-bearing mice. CD31 immunohistochemical staining was used to observe the microvessel density in tumor tissues of tumor-bearing mice. Results: The cytotoxicity of single cell model and co-culture model was dose-dependent. With the increase of curcumin (CUR) concentration, the cell viability decreased, but the cell viability of single cell model decreased faster than that of co-culture model. When the concentration of CUR was 10 μg/ml, the cell viability of the co-culture model was 62.3% and the migration rate was (28.05±3.68)%, which were higher than those of the single cell model [38.5% and (14.91±5.92)%, both P<0.05]. Western blot analysis showed that the expressions of P-gp and vimentin were up-regulated in the co-culture model, which were 1.55 and 2.04 fold changes of the single cell model, respectively. The expression of E-cadherin was down-regulated, and the expression level of E-cadherin in the single cell model was 1.17 fold changes of the co-culture model. Drug retention experiment showed that the co-culture model could promote drug efflux and reduce drug retention. In vivo tumor inhibition experiment showed that the m-HSC+ H22 co-transplantation model had faster tumor growth and larger tumor volume than those of the H22 single cell transplantation model. After CUR treatment, the tumor growths of m-HSC+ H22 co-transplantation model and H22 single cell transplantation model were inhibited. Masson staining showed that the deposition of collagen fibers in tumor tissues of m-HSC+ H22 co-transplantation model mice was more than that of H22 single cell transplantation model. CD31 immunohistochemical staining showed that the microvessel density in tumor tissue of m-HSC+ H22 co-transplantation model was higher than that of H22 single cell transplantation model. Conclusions: The aHSC+ liver cancer cell co-culture model has strong proliferation and metastasis ability and is easy to be resistant to drugs. It is a new type of liver cancer treatment research model superior to the traditional single cell model.

SC-AIR-BERT: a pre-trained single-cell model for predicting the antigen-binding specificity of the adaptive immune receptor.

Accurately predicting the antigen-binding specificity of adaptive immune receptors (AIRs), such as T-cell receptors (TCRs) and B-cell receptors (BCRs), is essential for discovering new immune therapies. However, the diversity of AIR chain sequences limits the accuracy of current prediction methods. This study introduces SC-AIR-BERT, a pre-trained model that learns comprehensive sequence representations of paired AIR chains to improve binding specificity prediction. SC-AIR-BERT first learns the 'language' of AIR sequences through self-supervised pre-training on a large cohort of paired AIR chains from multiple single-cell resources. The model is then fine-tuned with a multilayer perceptron head for binding specificity prediction, employing the K-mer strategy to enhance sequence representation learning. Extensive experiments demonstrate the superior AUC performance of SC-AIR-BERT compared with current methods for TCR- and BCR-binding specificity prediction.

A bivariate zero-inflated negative binomial model and its applications to biomedical settings.

The zero-inflated negative binomial distribution has been widely used for count data analyses in various biomedical settings due to its capacity of modeling excess zeros and overdispersion. When there are correlated count variables, a bivariate model is essential for understanding their full distributional features. Examples include measuring correlation of two genes in sparse single-cell RNA sequencing data and modeling dental caries count indices on two different tooth surface types. For these purposes, we develop a richly parametrized bivariate zero-inflated negative binomial model that has a simple latent variable framework and eight free parameters with intuitive interpretations. In the scRNA-seq data example, the correlation is estimated after adjusting for the effects of dropout events represented by excess zeros. In the dental caries data, we analyze how the treatment with Xylitol lozenges affects the marginal mean and other patterns of response manifested in the two dental caries traits. An R package "bzinb" is available on Comprehensive R Archive Network.

ScDesign3 generates realistic in silico data for multimodal single-cell and spatial omics.

We present a statistical simulator, scDesign3, to generate realistic single-cell and spatial omics data, including various cell states, experimental designs and feature modalities, by learning interpretable parameters from real data. Using a unified probabilistic model for single-cell and spatial omics data, scDesign3 infers biologically meaningful parameters; assesses the goodness-of-fit of inferred cell clusters, trajectories and spatial locations; and generates in silico negative and positive controls for benchmarking computational tools.

Human atrial fibrillation and genetic defects in transient outward currents: mechanistic insights from multi-scale computational models.

Previous studies have linked dysfunctional Ito arising from mutations to KCND3-encoded Kv4.3 and KCND2-encoded Kv4.2 to atrial fibrillation. Using computational models, this study aimed to investigate the mechanisms underlying pro-arrhythmic effects of the gain-of-function Kv4.3 (T361S, A545P) and Kv4.2 (S447R) mutations. Wild-type and mutant Ito formulations were developed from and validated against experimental data and incorporated into the Colman et al. model of human atrial cells. Single-cell models were incorporated into one- (1D) and two-dimensional (2D) models of atrial tissue, and a three-dimensional (3D) realistic model of the human atria. The three gain-of-function mutations had similar, albeit quantitatively different, effects: shortening of the action potential duration; lowering the plateau membrane potential, abbreviating the effective refractory period (ERP) and the wavelength (WL) of atrial excitation at the tissue level. Restitution curves for the WL, the ERP and the conduction velocity were leftward shifted, facilitating the conduction of atrial excitation waves at high excitation rates. The mutations also increased lifespan and stationarity of re-entry in both 2D and 3D simulations, which further highlighted a mutation-induced increase in spatial dispersion of repolarization. Collectively, these changes account for pro-arrhythmic effects of these Kv4.3 and Kv4.2 mutations in facilitating AF. This article is part of the theme issue 'The heartbeat: its molecular basis and physiological mechanisms'.

Comparing the effects of chemical Ca2+ dyes and R-GECO on contractility and Ca2+ transients in adult and human iPSC cardiomyocytes

We compared commonly used BAPTA-derived chemical Ca2+ dyes (fura2, Fluo-4, and Rhod-2) with a newer genetically encoded indicator (R-GECO) in single cell models of the heart. We assessed their performance and effects on cardiomyocyte contractility, determining fluorescent signal-to-noise ratios and sarcomere shortening in primary ventricular myocytes from adult mouse and guinea pig, and in human iPSC-derived cardiomyocytes. Chemical Ca2+ dyes displayed dose-dependent contractile impairment in all cell types, and we observed a negative correlation between contraction and fluorescence signal-to-noise ratio, particularly for fura2 and Fluo-4. R-GECO had no effect on sarcomere shortening. BAPTA-based dyes, but not R-GECO, inhibited in vitro acto-myosin ATPase activity. The presence of fura2 accentuated or diminished changes in contractility and Ca2+ handling caused by small molecule modulators of contractility and intracellular ionic homeostasis (mavacamten, levosimendan, and flecainide), but this was not observed when using R-GECO in adult guinea pig left ventricular cardiomyocytes. Ca2+ handling studies are necessary for cardiotoxicity assessments of small molecules intended for clinical use. Caution should be exercised when interpreting small molecule studies assessing contractile effects and Ca2+ transients derived from BAPTA-like chemical Ca2+ dyes in cellular assays, a common platform for cardiac toxicology testing and mechanistic investigation of cardiac disease physiology and treatment.

Label-Free Cytometric Evaluation of Mitosis via Stimulated Raman Scattering Microscopy and Spectral Phasor Analysis.

Hyperspectral stimulated Raman scattering (SRS) microscopy is a robust imaging tool for the analysis of biological systems. Here, we present a unique perspective, a label-free spatiotemporal map of mitosis, by integrating hyperspectral SRS microscopy with advanced chemometrics to assess the intrinsic biomolecular properties of an essential process of mammalian life. The application of spectral phasor analysis to multiwavelength SRS images in the high-wavenumber (HWN) region of the Raman spectrum enabled the segmentation of subcellular organelles based on innate SRS spectra. Traditional imaging of DNA is primarily reliant on using fluorescent probes or stains which can affect the biophysical properties of the cell. Here, we demonstrate the label-free visualization of nuclear dynamics during mitosis coupled with an evaluation of its spectral profile in a rapid and reproducible manner. These results provide a snapshot of the cell division cycle and chemical variability between intracellular compartments in single-cell models, which is central to understanding the molecular foundations of these fundamental biological processes. The evaluation of HWN images by phasor analysis also facilitated the differentiation between cells in separate phases of the cell cycle based solely on their nuclear SRS spectral signal, which offers an interesting label-free approach in combination with flow cytometry. Therefore, this study demonstrates that SRS microscopy combined with spectral phasor analysis is a valuable method for detailed optical fingerprinting at the subcellular level.

A comparative study of data-driven electro-thermal models for reconfigurable lithium-ion batteries in real-time applications

Reconfigurable battery systems can change the cell topology, which allows novel applications that are not possible with conventional battery systems. However, reconfiguration complicates monitoring of the individual cell state since greater variances in temperature and SOC are introduced. Especially critical for a safe operation and adequate performance is the thermal behavior, which needs to be determined for every single cell in real-time. In this work, four different reduced-order lumped models and four artificial neural network models are compared in a surrogate modeling approach for the practical application in a reconfigurable battery system. The comparison includes the representation of serial and serial–parallel topologies. Furthermore, different coupling variants of single cell models are investigated in order to find the best representation of the physical model of a reconfigurable battery systems in an automotive application. While a separate observation of individual cells in switching systems is shown to be no longer sufficient, good results are already evident with simple models and adequate coupling approaches. The data-driven surrogate approaches achieved errors as low as 0.1 K while at the same time reducing the computational effort drastically compared to a physics-based model.

SC-AIR-BERT: A pre-trained single-cell model for predicting the antigen binding specificity of the adaptive immune receptor

SC-AIR-BERT: A pre-trained single-cell model for predicting the antigen binding specificity of the adaptive immune receptor

Mathematical Modeling of Microbial Electrolysis Cells for Enhanced Urban Wastewater Treatment and Hydrogen Generation

Conventional wastewater treatment plants (CWTPs) are intensive energy consumers. New technologies are emerging for wastewater treatment such as microbial electrolysis cells (MECs) that can simultaneously treat wastewater and generate hydrogen as a renewable energy source. Mathematical modeling of single and dual-chamber microbial electrolysis cells (SMEC and DMEC) has been developed based on microbial population growth in this study. The model outputs were validated successfully with previous works, and are then used for comparisons between the SMEC and DMEC regarding the hydrogen production rate (HPR). The results reveal that the daily HPR in DMEC is higher than in SMEC, with about 0.86 l H2 and 0.52 l H2, respectively, per 1 L of wastewater. Moreover, the results have been used to compare the HPR in water electrolysis (WE) processes and MECs. WE consume 51 kWh to generate 1 kg of hydrogen, while SMEC and DMEC require only 30 kWh and 24.5 kWh, respectively.

Super-exponential growth and stochastic size dynamics in rod-like bacteria

Proliferating bacterial cells exhibit stochastic growth and size dynamics, but the regulation of noise in bacterial growth and morphogenesis remains poorly understood. A quantitative understanding of morphogenetic noise control, and how it changes under different growth conditions, would provide better insights into cell-to-cell variability and intergenerational fluctuations in cell physiology. Using multigenerational growth and width data of single Escherichia coli and Caulobacter crescentus cells, we deduce the equations governing growth and size dynamics of rod-like bacterial cells. Interestingly, we find that both E. coli and C. crescentus cells deviate from exponential growth within the cell cycle. In particular, the exponential growth rate increases during the cell cycle irrespective of nutrient or temperature conditions. We propose a mechanistic model that explains the emergence of super-exponential growth from autocatalytic production of ribosomes coupled to the rate of cell elongation and surface area synthesis. Using this new model and statistical inference on large datasets, we construct the Langevin equations governing cell growth and size dynamics of E. coli cells in different nutrient conditions. The single-cell level model predicts how noise in intragenerational and intergenerational processes regulate variability in cell morphology and generation times, revealing quantitative strategies for cellular resource allocation and morphogenetic noise control in different growth conditions.

Enhanced Drug Uptake on Application of Electroporation in a Single-Cell Model.

Electroporation method is a useful tool for delivering drugs into various diseased tissues in the human body. As a result of an applied electric field, drug particles enter the intracellular compartment through the temporarily permeabilized cell membrane. Consequently, electroporation method allows better penetration of the drug into the diseased tissue and improves treatment clinically. In this study, a more generalized model of drug transport in a single cell is proposed. The model is able to capture non-homogeneous drug transport in the cell due to non-uniform cell membrane permeabilization. Several numerical experiments are conducted to understand the effects of electric field and drug permeability on drug uptake into the cell. Through investigation, the appropriate electric field and drug permeability are identified, which lead to sufficient drug uptake into the cell. This model can be used by experimentalists to get information prior to conduct any experiment, and it may help reduce the number of actual experiments that might be conducted otherwise.

Single-cell genetic models to evaluate orphan gene function: The case of QQS regulating carbon and nitrogen allocation.

We demonstrate two synthetic single-cell systems that can be used to better understand how the acquisition of an orphan gene can affect complex phenotypes. The Arabidopsisorphan gene, Qua-Quine Starch (QQS) has been identified as a regulator of carbon (C) and nitrogen (N) partitioning across multiple plant species. QQS modulates this important biotechnological trait by replacing NF-YB (Nuclear Factor Y, subunit B) in its interaction with NF-YC. In this study, we expand on these prior findings by developing Chlamydomonas reinhardtii and Saccharomyces cerevisiae strains, to refactor the functional interactions between QQS and NF-Y subunits to affect modulations in C and N allocation. Expression of QQS in C. reinhardtii modulates C (i.e., starch) and N (i.e., protein) allocation by affecting interactions between NF-YC and NF-YB subunits. Studies in S. cerevisiae revealed similar functional interactions between QQS and the NF-YC homolog (HAP5), modulating C (i.e., glycogen) and N (i.e., protein) allocation. However, in S. cerevisiae both the NF-YA (HAP2) and NF-YB (HAP3) homologs appear to have redundant functions to enable QQS and HAP5 to affect C and N allocation. The genetically tractable systems that developed herein exhibit the plasticity to modulate highly complex phenotypes.

Single-Cell Kinetic Modeling of β-Lapachone Metabolism in Head and Neck Squamous Cell Carcinoma.

Head and neck squamous cell carcinoma (HNSCC) cells are highly heterogeneous in their metabolism and typically experience elevated reactive oxygen species (ROS) levels such as superoxide and hydrogen peroxide (H2O2) in the tumor microenvironment. Tumor cells survive under these chronic oxidative conditions by upregulating antioxidant systems. To investigate the heterogeneity of cellular responses to chemotherapeutic H2O2 generation in tumor and healthy tissue, we leveraged single-cell RNA-sequencing (scRNA-seq) data to perform redox systems-level simulations of quinone-cycling β-lapachone treatment as a source of NQO1-dependent rapid superoxide and hydrogen peroxide (H2O2) production. Transcriptomic data from 10 HNSCC patient tumors was used to populate over 4000 single-cell antioxidant enzymatic network models of drug metabolism. The simulations reflected significant systems-level differences between the redox states of healthy and cancer cells, demonstrating in some patient samples a targetable cancer cell population or in others statistically indistinguishable effects between non-malignant and malignant cells. Subsequent multivariate analyses between healthy and malignant cellular models pointed to distinct contributors of redox responses between these phenotypes. This model framework provides a mechanistic basis for explaining mixed outcomes of NAD(P)H:quinone oxidoreductase 1 (NQO1)-bioactivatable therapeutics despite the tumor specificity of these drugs as defined by NQO1/catalase expression and highlights the role of alternate antioxidant components in dictating drug-induced oxidative stress.

Enhancement of Power Conversion Efficiency of Non-Fullerene Organic Solar Cells Using Green Synthesized Au-Ag Nanoparticles.

Organic-based photovoltaics are excellent candidates for renewable energy alternatives to fossil fuels due to their low weight, low manufacturing cost, and, in recent years, high efficiency, which is now above 18%. However, one cannot ignore the environmental price of the fabrication procedure due to the usage of toxic solvents and high-energy input equipment. In this work, we report on the enhancement of the power conversion efficiency non-fullerene organic solar cells by incorporating green synthesised Au-Ag nanoparticles, using onion bulb extract, into the hole transport layer poly (3,4-ethylene dioxythiophene)-poly (styrene sulfonate) (PEDOT: PSS) of Poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b;4,5-b']dithiophene-2,6-diyl-alt-(4-(2-ethylhexyl)-3 fluorothieno[3,4-b]thiophene-)-2-carboxylate-2-6-diyl)]: 3,9-bis(2-methylene-(3-(1,1-dicyanomethylene)-indanone))-5,5,11,11-tetrakis(4-hexylphenyl)-dithieno[2,3-d:2',3'-d']-s-indaceno[1,2-b:5,6-b']dithiophene (PTB7-Th: ITIC) bulk-heterojunction organic solar cells. Red onion has been reported to contain quercetin, which serves as a capping agent that covers bare metal nanoparticles, thus reducing exciton quenching. We found that the optimized volume ratio of NPs to PEDOT: PSS is 0.06:1. At this ratio, a 24.7% enhancement in power conversion efficiency of the cell is observed, corresponding to a 9.11% power conversion efficiency (PCE). This enhancement is due to an increase in the generated photocurrent and a decrease in the serial resistance and recombination, as extracted from the fitting of the experimental data to a non-ideal single diode solar cell model. It is expected that the same procedure can be applied to other non-fullerene acceptor-based organic solar cells, leading to an even higher efficiency with minimal effect on the environment.

Numerical and experimental analysis of the effects of tar components on single planar SOFC under high fuel utilization

One of the main challenges and obstacles for the application of SOFCs with wood gas is the degradation of Nickel anode caused by heavier hydrocarbons from the gasification process. The unclear conversion process on the anode and the fluctuant content of tars in wood gas will cause problems like the excess of critical fuel cell utilization and thus the oxidation of Nickel anode. This work focuses on the experimental and numerical analysis of tar conversion on the single SOFC under different conditions. A three-dimensional Computational Fluid Dynamics (CFD) model for an electrolyte-supported single cell was developed using the commercial CFD code FLUENT. The conversion kinetics of tar is validated by experimental results and implemented into the model. With this model, local distributions of Nernst voltage across the anode area are demonstrated. Areas, where an oxidation of Nickel is to be feared, are identified. Both experimental and simulative results have proved the positive effect of toluene reforming on preventing Ni from re-oxidation.

Shiga Toxin (Stx) Type 1a and Stx2a Translocate through a Three-Layer Intestinal Model.

Shiga toxins (Stxs) produced by ingested E. coli can induce hemolytic uremic syndrome after crossing the intact intestinal barrier, entering the bloodstream, and targeting endothelial cells in the kidney. The method(s) by which the toxins reach the bloodstream are not fully defined. Here, we used two polarized cell models to evaluate Stx translocation: (i) a single-layer primary colonic epithelial cell model and (ii) a three-cell-layer model with colonic epithelial cells, myofibroblasts, and colonic endothelial cells. We traced the movement of Stx types 1a and 2a across the barrier models by measuring the toxicity of apical and basolateral media on Vero cells. We found that Stx1a and Stx2a crossed both models in either direction. However, approximately 10-fold more Stx translocated in the three-layer model as compared to the single-layer model. Overall, the percentage of toxin that translocated was about 0.01% in the epithelial-cell-only model but up to 0.09% in the three-cell-layer model. In both models, approximately 3- to 4-fold more Stx2a translocated than Stx1a. Infection of the three-cell-layer model with Stx-producing Escherichia coli (STEC) strains showed that serotype O157:H7 STEC reduced barrier function in the model and that the damage was not dependent on the presence of the eae gene. Infection of the three-layer model with O26:H11 STEC strain TW08571 (Stx1a+ and Stx2a+), however, allowed translocation of modest amounts of Stx without reducing barrier function. Deletion of stx2a from TW08571 or the use of anti-Stx1 antibody prevented translocation of toxin. Our results suggest that single-cell models may underestimate the amount of Stx translocation and that the more biomimetic three-layer model is suited for Stx translocation inhibitor studies.

Brassinosteroids regulate cotton fiber elongation by modulating very-long-chain fatty acid biosynthesis.

Brassinosteroid (BR), a growth-promoting phytohormone, regulates many plant growth processes including cell development. However, the mechanism by which BR regulates fiber growth is poorly understood. Cotton (Gossypium hirsutum) fibers are an ideal single-cell model in which to study cell elongation due to their length. Here we report that BR controls cotton fiber elongation by modulating very-long-chain fatty acid (VLCFA) biosynthesis. BR deficiency reduces the expression of 3-ketoacyl-CoA synthases (GhKCSs), the rate-limiting enzymes involved in VLCFA biosynthesis, leading to lower saturated VLCFA contents in pagoda1 (pag1) mutant fibers. In vitro ovule culture experiments show that BR acts upstream of VLCFAs. Silencing of BRI1-EMS-SUPPRESOR 1.4 (GhBES1.4), encoding a master transcription factor of the BR signaling pathway, significantly reduces fiber length, whereas GhBES1.4 overexpression produces longer fibers. GhBES1.4 regulates endogenous VLCFA contents and directly binds to BR RESPONSE ELEMENTS (BRREs) in the GhKCS10_At promoter region, which in turn regulates GhKCS10_At expression to increase endogenous VLCFA contents. GhKCS10_At overexpression promotes cotton fiber elongation, whereas GhKCS10_At silencing inhibits cotton fiber growth, supporting a positive regulatory role for GhKCS10_At in fiber elongation. Overall, these results uncover a mechanism of fiber elongation through crosstalk between BR and VLCFAs at the single-cell level.