Single-Cell Microgels for Diagnostics and Therapeutics

Cell encapsulation within hydrogel droplets is transforming what is feasible in multiple fields of biomedical science such as tissue engineering and regenerative medicine, in vitro modeling, and cell-based therapies. Recent advances have allowed researchers to miniaturize material encapsulation complexes down to single-cell scales, where each complex, termed a single-cell microgel, contains only one cell surrounded by a hydrogel matrix while remaining <100 μm in size. With this achievement, studies requiring single-cell resolution are now possible, similar to those done using liquid droplet encapsulation. Of particular note, applications involving long-term in vitro cultures, modular bioinks, high-throughput screenings, and formation of 3D cellular microenvironments can be tuned independently to suit the needs of individual cells and experimental goals. In this progress report, an overview of established materials and techniques used to fabricate single-cell microgels, as well as insight into potential alternatives is provided. This focused review is concluded by discussing applications that have already benefited from single-cell microgel technologies, as well as prospective applications on the cusp of achieving important new capabilities.     

Resveratrol as Chemosensitizer Agent: State of Art and Future Perspectives

Resistance to chemotherapy still remains a major challenge in the clinic, impairing the quality of life and survival rate of patients. The identification of unconventional chemosensitizing agents is therefore an interesting aspect of cancer research. Resveratrol has emerged in the last decades as a fascinating molecule, able to modulate several cancer-related molecular mechanisms, suggesting a possible application as an adjuvant in cancer management. This review goes deep into the existing literature concerning the possible chemosensitizing effect of resveratrol associated with the most conventional chemotherapeutic drugs. Despite the promising effects observed in different cancer types in in vitro studies, the clinical translation still presents strong limitations due to the low bioavailability of resveratrol. Recently, efforts have been moved in the field of drug delivery to identifying possible strategies/formulations useful for a more effective administration. Despite the necessity of a huge implementation in this research area, resveratrol appears as a promising molecule able to sensitize resistant tumors to drugs, suggesting its potential use in therapy-refractory cancer patients.     

Antibacterial and photocatalytic behaviour of green synthesis of Zn0.95Ag0.05O nanoparticles using herbal medicine extract

The present work aimed to synthesize Zn_0.95Ag_0.05O (ZnAgO) nanoparticles using rosemary leaf extracts as a green chemistry method. The characterization of Ag-doped ZnO nanoparticles was performed by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and ultraviolet–visible spectrophotometry (UV–visible). The XRD, FTIR, and UV–visible spectra confirmed the formation of the presence of hexagonal ZnAgO nanoparticles. FESEM micrograph shows that the nanoparticles have been distributed homogeneously and uniformly. The morphology of ZnAgO nanoparticles is quasi-spherical configuration. Also, the mean particle size is in the range of 22–40 nm. The photocatalytic degradation of methylene blue in the presence of Ag-doped ZnO nanoparticles is nearly 98.5% after exposing 100 min. The ultraviolet lamp was used as the light source for photocatalyst degradation. The disc diffusion method was chosen to study the antibacterial activity of as-synthesized ZnAgO nanoparticles. Antibacterial activity of Zn_0.95Ag_0.05O nanoparticles against Staphylococcus aureus and Escherichia coli revealed that the as-synthesized ZnAgO nanoparticles were efficient in inhibition of bacterial growth.     

Weighted regularized extreme learning machine to model the discharge coefficient of side slots

In the current research, a modern learning machine algorithm named “Weighted Regularized Extreme Learning Machine (WRELM)" is implemented for the first time for the simulation of the coefficient of discharge of side slots. For this purpose, an effective variable on the coefficient of discharge of side slots is firstly introduced, then five distinctive WRELM models are produced by it for the estimation of the coefficient. In the next stage, a database is created for verification of WRELM results. it should be mentioned that 70% of the data are utilized for training the WRELM models, while the rest (i.e. 30%) for testing them. After that, the optimal number of hidden layer neurons as well as the best activation function of the WRELM algorithm are chosen. In addition, the best regularization parameter and also the weight function of the WRELM are achieved. By conducting a sensitivity analysis, the most effective variable for the simulation of the coefficient of discharge along with the WRELM superior model is introduced. The WRELM superior model estimates values of the coefficient of discharge with the maximum exactness and the highest correlation. For instance, the estimations of the correlation coefficient and scatter index for this model are computed to be 0.930 and 0.051, respectively. The sensitivity analysis shows that the ratio of the side slot crest height to its length and the Froude number should be considered as the most important input variables. A comparison between the WRELM with the ELM displays that the former works much better. Furthermore, an uncertainty analysis is executed for both models. Eventually, an equation is suggested for the estimation of the coefficient of discharge and a partial derivative sensitivity analysis is performed on it.     

Characterization of Dog Glutathione Transferase P1-1, an Enzyme Relevant to Veterinary Medicine

Glutathione transferases (GSTs) form a family of detoxication enzymes instrumental in the inactivation and elimination of electrophilic mutagenic and carcinogenic compounds. The Pi class GST P1-1 is present in most tissues and is commonly overexpressed in neoplastic cells. GST P1-1 in the dog, Canis lupus familiaris, has merits as a marker for tumors and as a target for enzyme-activated prodrugs. We produced the canine enzyme CluGST P1-1 by heterologous bacterial expression and verified its cross-reactivity with antihuman-GST P1-1 antibodies. The catalytic activity with alternative substrates of biological significance was determined, and the most active substrate found was benzyl isothiocyanate. Among established GST inhibitors, Cibacron Blue showed positive cooperativity with an IC₅₀ value of 43 nM. Dog GST P1-1 catalyzes activation of the prodrug Telcyta, but the activity is significantly lower than that of the human homolog.     

Numerical modeling of effect of slot on bubble motion in aluminum electrolytic process

A transient three-dimensional (3D) model was established to understand the bubble motion in an industrial electrolytic process. An anode with a new design was tested. It incorporates two slots that allow an efficient removal of gas bubbles. The electromagnetic fields were described by solving Maxwell's equations. The bubble movement was studied with two-way coupling Euler–Lagrange approach. The interplay of current density and bubble nucleation rate was included. The collision and coalescence of bubbles were considered. Random walk module was invoked for involving the chaotic effect of the turbulence. The numerical results were validated by experimental measurements. The results indicate that the current distribution and the bubble nucleation periodically change. Due to the slot, the bubble elimination heavily increases. The contribution of the slot to the bubble removal exceeds 50% in the case of three currents, and the promotion of the slot decays with increasing the current.     

Cell-free Stem Cell-Derived Extract Formulation for Regenerative Medicine Applications

Stem cells for regenerative medicine purposes offer therapeutic benefits, but disadvantages are still ill defined. The benefit of stem cells may be attributed to their secretion of growth factors (GFs), cytokines (CKs), and extracellular vesicles (EVs), including exosomes. We present a novel cell-free stem cell-derived extract (CCM), formulated from human progenitor endothelial stem cells (hPESCs), characterized for biologically active factors using ELISA, nanoparticle tracking analysis and single particle interferometric reflectance imaging sensing. The effect on fibroblast proliferation and ability to induce stem cell migration was analyzed using Alamar Blue proliferation and Transwell migration assays, respectively. GFs including IGFBP 1, 2, 3, and 6, insulin, growth hormone, PDGF-AA, TGF-α, TGF-β1, VEGF, and the anti-inflammatory cytokine, IL-1RA were detected. Membrane enclosed particles within exosome size range and expressing exosome tetraspanins CD81 and CD9 were identified. CCM significantly increased cell proliferation and induced stem cell migration. Analysis of CCM revealed presence of GFs, CKs, and EVs, including exosomes. The presence of multiple factors including exosomes within one formulation, the ability to promote cell proliferation and induce stem cell migration may reduce inflammation and pain, and augment tissue repair.     

狭缝节流空气静压轴承局部气膜流场的直接数值模拟

采用3阶精度的迎风格式及2阶精度的中心差分格式,直接求解二维非定常N-S方程组,研究狭缝节流空气静压轴承压降恢复之后区域的流场特性。使用雷诺方程计算相同位置气膜中心处的流场状态,并与直接数值模拟方法的计算结果进行对比。结果表明:雷诺方程与N-S方程在计算域内计算结果基本一致,两者压力偏差为0.173%,速度偏差为1.217%;流场压力、密度沿气流方向逐渐减小,但在气膜方向几乎不变;流场速度、压力梯度沿气流方向逐渐增加,速度在流场出口处达到最大值;直接数值模拟方法得到了流场的温度变化,即整个流场的温度变化很小,温度整体呈上下高、中心低的分布,而雷诺方程无法计算得出整个流场的温度变化情况;采用雷诺方程计算轴承压降恢复之后区域的流场是合理的。