Biomimetic Metal-Organic Nanoparticles Prepared with a 3D-Printed Microfluidic Device as a Novel Formulation for Disulfiram-Based Therapy Against Breast Cancer

Disulfiram (DSF) is currently tested in several clinical trials for cancer treatment in combination with cop-per (Cu) ions. Usually, DSF and Cu are administered in two separate formulations. In the body, DSF andCu ions form diethyldithiocarbamate copper complex [Cu(DDC)2] which has potent antitumor activities.However, the “two formulation” approach often achieved low Cu(DDC)2 concentration at tumor regions and resulted in compromised anticancer efficacy. Therefore, preformed Cu(DDC)2 complex administered in a single formulation will have better anticancer efficacy. However, the poor aqueous solubility of Cu(DDC)2 is a significant challenge for its clinical use. In this work, a biomimetic nanoparticle formulation of Cu(DDC)2 was produced with a novel SMILE (Stabilized Metal Ion Ligand complex) method developed in our laboratory to address the drug delivery challenges. The Metal-organic Nanoparticle (MON) is composed of Cu(DDC)2 metal-organic complex core and surface decorated bovine serum albumin (BSA). Importantly, we designed a 3D-printed microfluidic device to further improve the fabrication of BSA/Cu(DDC)2 MONs. This method could precisely control the MON preparation process and also has great potential for large scale production of Cu(DDC)2 MON formulations. We also used a computational modeling approach to simulate the MON formation process in the microfluidic device. The optimized BSA/Cu(DDC)2 MONs demonstrated good physicochemical properties. The MONs also showed potent antitumor activities in the breast cancer cell monolayers as well as the 3D-cultured tumor spheroids. The BSA/Cu(DDC)2 MONs also effectively inhibited the growth of tumors in an orthotopic 4T1 breast tumor model. This current study provided a novel method to prepare a biomimetic MON formulation for DSF/Cu cancer therapy .© 2019 Elsevier Ltd. All rights reserved

Chinese Cerebrovascular Neurosurgery Society and Chinese Interventional & Hybrid Operation Society, of Chinese Stroke Association Clinical Practice Guidelines for Management of Brain Arteriovenous Malformations in Eloquent Areas

Aim: The aim of this guideline is to present current and comprehensive recommendations for the management of brain arteriovenous malformations (bAVMs) located in eloquent areas.Methods: An extended literature search on MEDLINE was performed between Jan 1970 and May 2020. Eloquence-related literature was further screened and interpreted in different subcategories of this guideline. The writing group discussed narrative text and recommendations through group meetings and online video conferences. Recommendations followed the Applying Classification of Recommendations and Level of Evidence proposed by the American Heart Association/American Stroke Association. Prerelease review of the draft guideline was performed by four expert peer reviewers and by the members of Chinese Stroke Association.Results: In total, 809 out of 2,493 publications were identified to be related to eloquent structure or neurological functions of bAVMs. Three-hundred and forty-one publications were comprehensively interpreted and cited by this guideline. Evidence-based guidelines were presented for the clinical evaluation and treatment of bAVMs with eloquence involved. Topics focused on neuroanatomy of activated eloquent structure, functional neuroimaging, neurological assessment, indication, and recommendations of different therapeutic managements. Fifty-nine recommendations were summarized, including 20 in Class I, 30 in Class IIa, 9 in Class IIb, and 2 in Class III.Conclusions: The management of eloquent bAVMs remains challenging. With the evolutionary understanding of eloquent areas, the guideline highlights the assessment of eloquent bAVMs, and a strategy for decision-making in the management of eloquent bAVMs

microRNA-153 Targets mTORC2 Component Rictor to Inhibit Glioma Cells.

Rictor upregulation and mTORC complex 2 (mTORC2) over-activation participate in glioma cell progression, yet the underling mechanisms are not known. We here identified microRNA-153 (miR-153) as a potential anti-Rictor miRNA, which was downregulated in multiple human glioma tissues and glioma cell lines (U87MG, T98G, U373MG and U251MG). miR-153 downregulation was correlated with Rictor (mRNA and protein) upregulation and p-Akt Ser473 (the mTORC2 indicator) over-activation in the glioma tissues and cells. Our in vitro evidences suggested that Rictor could be one primary target of miR-153 in glioma cells. Exogenous overexpression of miR-153 downregulated Rictor (mRNA and protein) and decreased p-Akt Ser473 in U87MG cells, leading to significant growth inhibition and apoptosis activation. Notably, U87MG cells with Rictor shRNA knockdown showed similar phenotypes of cells with miR-153 overexpression. More importantly, in Rictor-silenced U87MG cells, miR-153 expression failed to further affect cell growth nor apoptosis. In vivo, we showed that miR-153 overexpression dramatically inhibited U87MG tumor growth in nude mice. Together, these results suggest that miR-153 downregulation could be one important reason of Rictor upregulation and mTORC2 over-activation in glioma cells. Further, miR-153-induced anti-glioma cell activity is possibly via downregulating Rictor

Analysis of microRNAs Expression Profiles in Madin-Darby Bovine Kidney Cells Infected With Caprine Parainfluenza Virus Type 3

Caprine parainfluenza virus type 3 (CPIV3) is a newly emerging pathogenic respiratory agent infecting both young and adult goats, and it was identified in eastern China in 2013. Cellular microRNAs (miRNAs) have been reported to be important modulators of the intricate virus-host interactions. In order to elucidate the role of miRNAs in madin-darby bovine kidney (MDBK) cells during CPIV3 infection. In this study, we performed high-throughput sequencing technology to analyze small RNA libraries in CPIV3-infected and mock-infected MDBK cells. The results showed that a total of 249 known and 152 novel candidate miRNAs were differentially expressed in MDBK cells after CPIV3 infection, and 22,981 and 22,572 target genes were predicted, respectively. In addition, RT-qPCR assay was used to further confirm the expression patterns of 13 of these differentially expressed miRNAs and their mRNA targets. Functional annotation analysis showed these up- and downregulated target genes were mainly involved in MAPK signaling pathway, Jak-STAT signaling pathway, Toll-like receptor signaling pathway, p53 signaling pathway, focal adhesion, NF-kappa B signaling pathway, and apoptosis, et al. To our knowledge, this is the first report of the comparative expression of miRNAs in MDBK cells after CPIV3 infection. Our finding provides information concerning miRNAs expression profile in response to CPIV3 infection, and offers clues for identifying potential candidates for antiviral therapies against CPIV3

miR-153 downregulation correlates with Rictor upregulation in multiple human glioma tissues and cell lines.

<p>miR-153 (-3p) and its putative binding sequence in the 3’-UTR of Rictor mRNA (A). Expressions of miR-153 (B), Rictor mRNA (C) as well as Rictor protein (D, vs. Tubulin) and p-Akt (D, vs. Akt1) in human glioma tissues (“Glioma”) and their surrounding normal brain tissues (“Normal”) were shown. Expressions of miR-153 (E), Rictor mRNA (F) as well as Rictor protein (G) and p-Akt (G) in primary human astrocytes (“Astrocytes”) and established glioma cell lines (T98G,U373MG, U251MG and U87MG) were shown. Rictor protein expression (vs. Tubulin) and p-Akt Ser473 (vs. Akt1) were quantified (D and G). Experiments in this figure were repeated three times, with similar results obtained. Bars stand for mean ± SD. * <i>p</i> < 0.05 vs. “Normal” group (B-D, n = 9). * <i>p</i> < 0.05 vs. “Astrocytes” group (E-F, n = 3).</p

Assessing the Impacts of Fertilization Regimes on Soil Aggregate Dynamics in Northeast China

Determining the effects of fertilization regimes on soil aggregates, carbon (C) and nitrogen (N) distribution, and pH is essential for improving soil structure and soil organic carbon (SOC) accumulation to help in proper soil fertility management. Based on a 41-year field fertilization experiment conducted on dark brown soil in northeast China, we examined the soil aggregate size distribution and associated C, N, and pH to provide a scientific basis for elucidation of the mechanisms underlying the effects of fertilization treatments on soil structure and fertility. Six different fertilization treatments included no fertilizer (CK), low-dose chemical fertilizer (NP), moderate-dose chemical fertilizer (2NP), high-dose chemical fertilizer (4NP), normal-dose organic fertilizer (M), and normal-dose organic fertilizer plus moderate-dose chemical fertilizer (M+2NP). Our findings showed that compared to CK, M and M+2NP significantly increased the proportion of macroaggregates by 40% and 28%, respectively, whereas 4NP significantly decreased it by 19%. The mean weight diameter (MWD) and geometric mean diameter (GMD) under M and M+2NP were significantly higher than that under CK, at 12–21% and 24–36%, respectively. The fractal dimension (D) value of M+2NP was significantly lower than those of 2NP and 4NP by 4% and 5%, respectively. Soil pH under the M treatment was highest, followed by M+2NP. Soil pH under 2NP and 4NP more significantly decreased, by 0.1 and 0.2 units, than under M treatment. Soil pH values were correlated with the proportion of soil macroaggregates, MWD, and GWD, respectively (p 2NP > 4NP. Overall, the long-term application of organic fertilization regimes (M and M+2NP) effectively improved soil aggregation as well as SOC accumulation and decreased soil acidification in dark brown soil in northeast China

Rictor is a target of miR-153 in glioma cells.

<p>Stable U87MG cells expressing miR-153, microRNA-control (“miR-C”) or empty vector (“pSuper-puro”) were subjected to real-time PCR assay of miR-153 (A) and Rictor mRNA (B). Expressions of listed proteins in these cells were also tested (C). Rictor protein expression (vs. Tubulin) and p-Akt Ser473 (vs. Akt1) were quantified (C). Bars stand for mean ± SD. * <i>p</i> < 0.05 vs. “Vector” group (A and B, n = 5).</p

miR-153 overexpression inhibits glioma cell growth, and activates cell apoptosis.

<p>Exact same number of stable glioma cells (U87MG or U373MG lines) expressing miR-153, microRNA-control (“miR-C”) or empty vector (“pSuper-puro”) were subjected to MTT assay (A and B) or clonogenicity assay (C and D) to analyze of cell growth; Apoptosis level in these cells was also tested by Histone DNA ELISA assay (E and F). Bars stand for mean ± SD. * <i>p</i> < 0.05 vs. “miR-C” group (n = 6).</p

The anti-glioma activity by miR-153 <i>in vivo</i>.

<p>miR-153-expressing U87MG cells (“miR-153”) or miR-C-expressing U87MG cells (“miR-C”) were inoculated into the nude mice (13 mice per group), tumor volumes (A) and mice body weights (D) were recorded weekly; Estimated daily tumor growth was calculated (B); Mice survival at week-7 was also presented (C, summarizing of three-set repeats). At week-5, three xenografted U87MG tumors per group were isolated, miR-153 (E) and Rictor mRNA (F) expressions in the fresh tissues were tested by real-time PCR assay; Bars stand for mean ± SD. * <i>p</i> < 0.05 vs. “miR-C” tumor group (A-F).</p

miR-153-induced anti-glioma cell activity is mediated via downregulating Rictor.

<p>Relative Rictor mRNA (A) and miRNA-153 (C) expression in stable U87MG cells with scramble control shRNA (“shRNA-C”) or Rictor shRNA (“shRNA-Rictor”) was tested by Real-time PCR assay. Expressions of listed proteins in these cells were also shown (B). Same number of U87MG cells with “shRNA-C” or “shRNA-Rictor” were subjected to MTT assay (D) and clonogenicity assay (E) to test cell growth; Cell apoptosis was also tested (Histone DNA ELISA assay, F). Rictor shRNA-expressing stable U87MG cells were transfected with miR-153 or microRNA-control (“miR-C”), miR-153 expression (G, Real-time PCR assay), cell growth (E, MTT assay) and apoptosis (F, Histone DNA ELISA assay) in these cells were tested. Rictor expression (vs. Tubulin) and p-Akt Ser473 (vs. Akt1) were quantified (B). Bars stand for mean ± SD. * <i>p</i> < 0.05 vs. “shRNA-C” group (A, C, D-F, n = 5). * <i>p</i> < 0.05 vs. “miR-C” group (G, n = 5).</p