On-demand activatable peroxidase-mimicking enzymatic polymer nanocomposite films.

Nanozymes continue to attract considerable attention to minimise the dependence on expensive enzymes in bioassays, particularly in medical diagnostics. While there has been considerable effort directed towards developing different nanozymes, there has been limited progress in fabricating composite materials based on such nanozymes. One of the biggest gaps in the field is the control, tuneability, and on-demand catalytic response. Herein, a nanocomposite nanozymatic film that enables precise tuning of catalytic activity through stretching is demonstrated. In a systematic study, we developed poly(styrene-stat-n-butyl acrylate)/iron oxide-embedded porous silica nanoparticle (FeSiNP) nanocomposite films with controlled, highly tuneable, and on-demand activatable peroxidase-like activity. The polymer/FeSiNP nanocomposite was designed to undergo film formation at ambient temperature yielding a highly flexible and stretchable film, responsible for enabling precise control over the peroxidase-like activity. The fabricated nanocomposite films exhibited a prolonged FeSiNP dose-dependent catalytic response. Interestingly, the optimised composite films with 10 wt% FeSiNP exhibited a drastic change in the enzymatic activity upon stretching, which provides the nanocomposite films with an on-demand performance activation characteristic. This is the first report showing control over the nanozyme activity using a nanocomposite film, which is expected to pave the way for further research in the field leading to the development of system-embedded activatable sensors for diagnostic, food spoilage, and environmental applications.

Efficientand Robust Automated Segmentation of Nanoparticles and Aggregates from Transmission Electron Microscopy Images with Highly Complex Backgrounds.

Morphologies of nanoparticles and aggregates play an important role in their properties for a range of applications. In particular, significant synthesis efforts have been directed toward controlling nanoparticle morphology and aggregation behavior in biomedical applications, as their size and shape have a significant impact on cellular uptake. Among several techniques for morphological characterization, transmission electron microscopy (TEM) can provide direct and accurate characterization of nanoparticle/aggregate morphology details. Nevertheless, manually analyzing a large number of TEM images is still a laborious process. Hence, there has been a surge of interest in employing machine learning methods to analyze nanoparticle size and shape. In order to achieve accurate nanoparticle analysis using machine learning methods, reliable and automated nanoparticle segmentation from TEM images is critical, especially when the nanoparticle image contrast is weak and the background is complex. These challenges are particularly pertinent in biomedical applications. In this work, we demonstrate an efficient, robust, and automated nanoparticle image segmentation method suitable for subsequent machine learning analysis. Our method is robust for noisy, low-electron-dose cryo-TEM images and for TEM cell images with complex, strong-contrast background features. Moreover, our method does not require any a priori training datasets, making it efficient and general. The ability to automatically, reliably, and efficiently segment nanoparticle/aggregate images is critical for advancing precise particle/aggregate control in biomedical applications.

Correlative Fluorescence and Transmission Electron Microscopy Assisted by 3D Machine Learning Reveals Thin Nanodiamonds Fluoresce Brighter.

Nitrogen vacancy (NV) centers in fluorescent nanodiamonds (FNDs) draw widespread attention as quantum sensors due to their room-temperature luminescence, exceptional photo- and chemical stability, and biocompatibility. For bioscience applications, NV centers in FNDs offer high-spatial-resolution capabilities that are unparalleled by other solid-state nanoparticle emitters. On the other hand, pursuits to further improve the optical properties of FNDs have reached a bottleneck, with intense debate in the literature over which of the many factors are most pertinent. Here, we describe how substantial progress can be achieved using a correlative transmission electron microscopy and photoluminescence (TEMPL) method that we have developed. TEMPL enables a precise correlative analysis of the fluorescence brightness, size, and shape of individual FND particles. Augmented with machine learning, TEMPL can be used to analyze a large, statistically meaningful number of particles. Our results reveal that FND fluorescence is strongly dependent on particle shape, specifically, that thin, flake-shaped particles are up to several times brighter and that fluorescence increases with decreasing particle sphericity. Our theoretical analysis shows that these observations are attributable to the constructive interference of light waves within the FNDs. Our findings have significant implications for state-of-the-art sensing applications, and they offer potential avenues for improving the sensitivity and resolution of quantum sensing devices.

Complex Dispersion of Detonation Nanodiamond Revealed by Machine Learning Assisted Cryo-TEM and Coarse-Grained Molecular Dynamics Simulations.

Understanding the polydispersity of nanoparticles is crucial for establishing the efficacy and safety of their role as drug delivery carriers in biomedical applications. Detonation nanodiamonds (DNDs), 3-5 nm diamond nanoparticles synthesized through detonation process, have attracted great interest for drug delivery due to their colloidal stability in water and their biocompatibility. More recent studies have challenged the consensus that DNDs are monodispersed after their fabrication, with their aggregate formation poorly understood. Here, we present a novel characterization method of combining machine learning with direct cryo-transmission electron microscopy imaging to characterize the unique colloidal behavior of DNDs. Together with small-angle X-ray scattering and mesoscale simulations we show and explain the clear differences in the aggregation behavior between positively and negatively charged DNDs. Our new method can be applied to other complex particle systems, which builds essential knowledge for the safe implementation of nanoparticles in drug delivery.

Regulating the Coordination Environment of Mesopore-Confined Single Atoms from Metalloprotein-MOFs for Highly Efficient Biocatalysis.

Single-atom catalysts (SACs) exhibit unparalleled atomic utilization and catalytic efficiency, yet it is challenging to modulate SACs with highly dispersed single-atoms, mesopores, and well-regulated coordination environment simultaneously and ultimately maximize their catalytic efficiency. Here, a generalized strategy to construct highly active ferric-centered SACs (Fe-SACs) is developed successfully via a biomineralization strategy that enables the homogeneous encapsulation of metalloproteins within metal-organic frameworks (MOFs) followed by pyrolysis. The results demonstrate that the constructed metalloprotein-MOF-templated Fe-SACs achieve up to 23-fold and 47-fold higher activity compared to those using metal ions as the single-atom source and those with large mesopores induced by Zn evaporation, respectively, as well as up to a 25-fold and 1900-fold higher catalytic efficiency compared to natural enzymes and natural-enzyme-immobilized MOFs. Furthermore, this strategy can be generalized to a variety of metal-containing metalloproteins and enzymes. The enhanced catalytic activity of Fe-SACs benefits from the highly dispersed atoms, mesopores, as well as the regulated coordination environment of single-atom active sites induced by metalloproteins. Furthermore, the developed Fe-SACs act as an excellent and effective therapeutic platform for suppressing tumor cell growth. This work advances the development of highly efficient SACs using metalloproteins-MOFs as a template with diverse biotechnological applications.

[Distribution Characteristics and Influencing Factors of Germanium in Soil in the Eastern Mountainous Area of the Nanyang Basin].

Based on the land quality geochemical survey results in the southwest cultivated area of Nanyang Basin, the content, spatial distribution, and enrichment characteristics of Ge in surface soil (0-20 cm) and deep soil (150-200 cm) in the eastern mountainous area of Nanyang Basin were studied, and the influencing factors of Ge in the surface soil were analyzed. The results showed that the average ω(Ge) in the surface soil and deep soil were 1.39 mg·kg-1 and 1.45 mg·kg-1, respectively. In the study area, 32.22% of surface soil and 12.77% of surface soil was rich in Ge, and the rich areas of the surface soil Ge were mainly distributed in the metamorphic rock and granite-dominant development areas. The optimal theoretical model of surface soil Ge variogram in the study area was a spherical model, and the nugget effect value was 0.434, indicating that surface soil Ge had moderate spatial correlation due to the joint influence of random factors and structural factors. The enrichment factor showed that 93.61% of Ge sites in the topsoil were mainly affected by natural factors, whereas 6.39% of Ge sites were significantly affected by human factors. The source of Ge in soil in the study area was mainly affected by the parent materials of soil formation, but the enrichment of Ge in surface soil was mainly affected by the Fe, Mn oxides, quartz, and pH in the soil.

Advances in Single-Cell Printing.

Single-cell analysis is becoming an indispensable tool in modern biological and medical research. Single-cell isolation is the key step for single-cell analysis. Single-cell printing shows several distinct advantages among the single-cell isolation techniques, such as precise deposition, high encapsulation efficiency, and easy recovery. Therefore, recent developments in single-cell printing have attracted extensive attention. We review herein the recently developed bioprinting strategies with single-cell resolution, with a special focus on inkjet-like single-cell printing. First, we discuss the common cell printing strategies and introduce several typical and advanced printing strategies. Then, we introduce several typical applications based on single-cell printing, from single-cell array screening and mass spectrometry-based single-cell analysis to three-dimensional tissue formation. In the last part, we discuss the pros and cons of the single-cell strategies and provide a brief outlook for single-cell printing.

Statistically Representative Metrology of Nanoparticles via Unsupervised Machine Learning of TEM Images.

The morphology of nanoparticles governs their properties for a range of important applications. Thus, the ability to statistically correlate this key particle performance parameter is paramount in achieving accurate control of nanoparticle properties. Among several effective techniques for morphological characterization of nanoparticles, transmission electron microscopy (TEM) can provide a direct, accurate characterization of the details of nanoparticle structures and morphology at atomic resolution. However, manually analyzing a large number of TEM images is laborious. In this work, we demonstrate an efficient, robust and highly automated unsupervised machine learning method for the metrology of nanoparticle systems based on TEM images. Our method not only can achieve statistically significant analysis, but it is also robust against variable image quality, imaging modalities, and particle dispersions. The ability to efficiently gain statistically significant particle metrology is critical in advancing precise particle synthesis and accurate property control.

Xiao-Chai-Hu-Tang ameliorates tumor growth in cancer comorbid depressive symptoms via modulating gut microbiota-mediated TLR4/MyD88/NF-κB signaling pathway.

BACKGROUND: Depressive symptoms are thought to promote cancer development and depressive remission has been reported to be effective for defeating cancer. The herbal formula Xiao-Chai-Hu-Tang (XCHT), that has an anti-depressive efficacy, has been widely utilized in China. However, its anti-cancer effect and underlying mechanisms remain unclear. PURPOSE: The present study aims to investigate the effects of XCHT on the depression-associated tumor and its potential mechanisms. METHODS: A placebo-controlled trial was conducted in cancer patients comorbid with depressive symptoms to evaluate the effects of XCHT on depressive scales, tumor-related immune indicators, and gut microbial composition. A xenografted colorectal cancer (CRC) mouse model exposure to chronic restraint stress (CRS) was established to examine XCHT effects on tumorigenesis in vivo. Further, by manipulating gut bacteria with fecal microbial transplantation (FMT) or antibiotics-induced bacterial elimination in CRS-associated xenografted model, gut microbiota-mediated anti-tumor mechanism was explored. RESULTS: In cancer patients comorbid with depressive symptoms, XCHT showed substantial effects on improvement of depressive scales, system inflammatory levels and gut dysbiosis. In vivo, XCHT inhibited tumor growth and prolonged survival time in addition to showing anti-depressive effect. Similarly, in our clinical trial, XCHT partially reversed gut dysbiosis, particularly through reducing abundances of Parabacteroides, Blautia and Ruminococcaceae bacterium. Manipulation of gut bacteria in CRS-associated xenografted model further proved that the inhibition of XCHT on tumor progression was mediated by gut microbiota and that the underlying mechanism involves in downregulation of TLR4/MyD88/NF-κB signaling. CONCLUSIONS: We demonstrated that gut microbiota mediates the anti-tumor action of the formula XCHT in cancer patients and models that were comorbid with depressive symptoms. This study implies a novel clinical significance of anti-depressive herbal medicine in the cancer treatment and clarifies the important role of gut microbiota in treating cancer accompanied by depressive symptoms.

A New Chalcone Derivative C49 Reverses Doxorubicin Resistance in MCF-7/DOX Cells by Inhibiting P-Glycoprotein Expression.

Objective: C49 is a chalcone derivative. The aim of the current study is to illuminate the efficacy of C49 in reversing multidrug resistance (MDR) in MCF-7/DOX cells and its underlying molecular mechanism. Methods: The cytotoxic effects of C49 on MCF-7/DOX cells were evaluated by MTT assay using different concentration (0-250 µmol/L) of C49. Cell proliferation was evaluated by colony formation assay. Cell death was examined by morphological analysis using Hoechst 33,258 staining. Flow cytometry and immunofluorescence were utilized to evaluate the intracellular accumulation of doxorubicin (DOX) and cell apoptosis. The differentially expressed genns between MCF-7 and MCF-7/DOX cells were analyzed by GEO database. The expression of PI3K/Akt pathway proteins were assessed by Western blot The activities of C49 combined with DOX was evaluated via xenograft tumor model in female BALB/c nude mice. Results: C49 inhibited the growth of MCF-7 cells (IC50 = 59.82 ± 2.10 µmol/L) and MCF-7/DOX cells (IC50 = 65.69 ± 8.11 µmol/L) with dosage-dependent and enhanced the cellular accumulation of DOX in MCF-7/DOX cells. The combination of C49 and DOX inhibited cell proliferation and promoted cell apoptosis. MCF-7/DOX cells regained drug sensibility with the combination treatment through inhibiting the expression of P-gp, p-PI3K and p-Akt proteins. Meanwhile, C49 significantly increased the anticancer efficacy of DOX in vivo. Conclusion: C49 combined with DOX restored DOX sensitivity in MCF-7/DOX cells through inhibiting P-gp protein.

Metrology of convex-shaped nanoparticles via soft classification machine learning of TEM images.

The shape of nanoparticles is a key performance parameter for many applications, ranging from nanophotonics to nanomedicines. However, the unavoidable shape variations, which occur even in precision-controlled laboratory synthesis, can significantly impact on the interpretation and reproducibility of nanoparticle performance. Here we have developed an unsupervised, soft classification machine learning method to perform metrology of convex-shaped nanoparticles from transmission electron microscopy images. Unlike the existing methods, which are based on hard classification, soft classification provides significantly greater flexibility in being able to classify both distinct shapes, as well as non-distinct shapes where hard classification fails to provide meaningful results. We demonstrate the robustness of our method on a range of nanoparticle systems, from laboratory-scale to mass-produced synthesis. Our results establish that the method can provide quantitative, accurate, and meaningful metrology of nanoparticle ensembles, even for ensembles entailing a continuum of (possibly irregular) shapes. Such information is critical for achieving particle synthesis control, and, more importantly, for gaining deeper understanding of shape-dependent nanoscale phenomena. Lastly, we also present a method, which we coin the "binary DoG", which achieves significant progress on the challenging problem of identifying the shapes of aggregated nanoparticles.

Total extract of Xin Jia Xuan Bai Cheng Qi decoction inhibits pulmonary fibrosis via the TGF-ß/Smad signaling pathways in vivo and in vitro.

PURPOSE: Pulmonary fibrosis (PF) is a common clinical disease, which results in serious respiratory impairment. Xin Jia Xuan Bai Cheng Qi Decoction (XJXBCQ) is a traditional prescription commonly used in treating lung diseases. We investigate the effect of XJXBCQ against PF and its mechanism via the regulation of TGF-ß1/Smad in vitro and in vivo. MATERIALS AND METHODS: XJXBCQ was first extracted and probed for chemical characterization. An PF model in vitro and in vivo was established in rats and in MRC-5 cells. In bleomycin (BLM)-induced rats model, lung function such as peak expiratory flow (PEF), minute ventilation (MV) and hydroxyproline (HYP) were measured; histopathological changes of lung tissue and TGF-ß1 in peripheral blood of rats were detected. TGF-ß receptor, Smad2 and its phosphorylation expression were tested by Western blot assay in rats model. Then the effects of XJXBCQ on TGF-ß1/Smad signal pathway were assessed by Western blot analysis in vitro, and IL-17A and IL-25 levels were evaluated by ELISA in vivo. RESULTS: Our results showed that XJXBCQ significantly enhanced the lung functions, such as PEF, MV and HYP, by reducing the expression level of lung inflammatory cytokine and the content and fibrosis of lung collagen. Moreover, XJXBCQ effectively inhibited TGF-ß1, Smad2 and its phosphorylation expression, and the activation of Smad7 in vitro and in vivo. Furthermore, XJXBCQ had an inhibitory effect on the α-smooth muscle actin (α-SMA) and fibronectin (Fn) in vitro and downregulated IL-17A and IL-25 by inhibiting the activation of TGF-ß1/Smad signaling pathway in vitro and in vivo. Further, XJXBCQ effectively inhibitied ventilation volume and peak expiratory content remodeling and hydroxyproline content through inhibition of TGF-ßRⅡ, Smad2 and its phosphorylation expression, and activation of Smad7 in vivo. CONCLUSION: XJXBCQ extract had an anti-PF effect in vitro and in vivo, which could be attributed to the inhibition of the expression of p-Smad2 and increase in the expression of Smad7 by regulating the TGF-ß1/Smad activity.

Tanshinone IIA inhibits ß-catenin/VEGF-mediated angiogenesis by targeting TGF-ß1 in normoxic and HIF-1α in hypoxic microenvironments in human colorectal cancer.

In a previous study, we demonstrated that Tanshinone IIA effectively inhibits CRC angiogenesis in vivo, but the underlying mechanisms were not elucidated. In this report, we describe experiments in which HIF-1α levels were manipulated to probe the effect of hypoxia on CRC cell angiogenesis. We studied the effects of Tan IIA on CRC pro-angiogenic factor and on human umbilical vein endothelial cell angiogenesis in normoxia and hypoxia. Our results show that Tan IIA not only lowers HIF-1α levels and inhibits secretion of VEGF and bFGF, but also efficiently suppresses the proliferation, tube formation and metastasis of HUVECs. Interruption of the HIF-1α/ß-catenin/TCF3/LEF1 signaling pathway occurs in the hypoxic microenvironment. The mechanism involves HIF-1α inhibition of TGF-ß1 secretion, which drives angiogenesis by promoting ß-catenin nuclear localization and TCF/LEF activation. To test an improved delivery system for Tan IIA, we loaded the drug into mesoporous silica nanoparticles (MSN-NH2) and found that it effectively targets HIF-1α overexpression in a mouse colon tumor model. Finally, Tan IIA sodium sulfonate exhibits anti-angiogenesis activity in CRC patients by reducing levels of angiogenin, VEGF and bFGF expression. Our research provides a new anti-angiogenesis strategy and strengthens support for the use of Tan IIA as an angiogenesis inhibitor.

Evodiamine Suppresses ABCG2 Mediated Drug Resistance by Inhibiting p50/p65 NF-κB Pathway in Colorectal Cancer.

Evodiamine (Evo), extracted from the Chinese herbal medicine Evodia rutaecarpa, has cytotoxic effects on different types of human cancer cells. However, its effects on drug resistance and their molecular mechanism and therapeutic target in colorectal cancer are not well understood. In the present study, we observed that Evo inhibited cell growth and induced apoptosis in adose-and time-dependent manner in HCT-116/L-OHP cells. Moreover, Evo treatment reduced Rhodamine 123 accumulation and ATPase activity in HCT-116/L-OHP cells, indicating that Evo decreased the efflux function in HCT-116/L-OHP cells. Interestingly, phosphorylation of NF-κB pathway, particularly p50/p65, was also inhibited by Evo treatment. Furthermore the effect of Evo in reversing drug resistance and suppressing phosphorylation of NF-κB pathway were attenuated after treatment with the NF-κB activator (LPS). Additionally, Evo inhibited the tumor growth in a colorectal MDR cancer xenograft model and down regulated p-NF-κB level in vivo. Our study provided the first direct evidence that Evo can attenuate multidrug resistance by blocking p-NF-κB signaling pathway in human colorectal cancer. Evo could be a potential candidate for cancer chemotherapy.