Tumor infiltration with Vα24-invariant NKT cells (NKTs) associates with favorable outcome in neuroblastoma and other cancers. Although NKTs can be directly cytotoxic against CD1d + cells, the majority of human tumors are CD1d -. Therefore, the role of NKTs in cancer remains largely unknown. Here, we demonstrate that CD68 + tumor-associated monocytes/macrophages (TAMs) represented the majority of CD1d-expressing cells in primary human neuroblastomas. TAMs stimulated neuroblastoma growth in human cell lines and their xenografts in NOD/SCID mice via IL-6 production. Indeed, TAMs produced IL-6 in primary tumors and in the BM of patients with metastatic neuroblastoma. Gene expression analysis using TaqMan low-density arrays of 129 primary human neuroblastomas without MYCN amplification revealed that high-level expression of TAM-specific genes (CD14, CD16, IL6, IL6R, and TGFB1) was associated with poor 5-year event-free survival. While NKTs were not cytotoxic against neuroblastoma cells, they effectively killed monocytes pulsed with tumor cell lysate. The killing of monocytes was CD1d restricted because it was inhibited by a CD1d-specific mAb. Cotransfer of human monocytes and NKTs to tumor-bearing NOD/SCID mice decreased monocyte number at the tumor site and suppressed tumor growth compared with mice transferred with monocytes alone. Thus, killing of TAMs reveals what we believe to be a novel mechanism of NKT antitumor activity that relates to the disease outcome.

MicroRNAs (miRNAs) are a class of noncoding RNAs of lengths ranging from 18 to 23 nucleotides (nt) that play critical roles in a wide variety of biological processes. There is a growing amount of evidence that miRNAs play critical roles in intricate host-pathogen interaction networks, but the involvement of miRNAs during influenza viral infection is unknown. To determine whether the cellular miRNAs play an important role in H1N1 influenza A viral infections, 3 untranslated region (UTR) reporter analysis was used to identify putative miRNA targets in the influenza virus genome, and virus proliferation analysis was used to detect the effect of the screened miRNAs on the replication of H1N1 influenza A virus (A/WSN/33) in MDCK cells. The results showed that miRNA 323 (miR-323), miR-491, and miR-654 inhibit replication of the H1N1 influenza A virus through binding to the PB1 gene. Moreover mutational analysis of the predicted miRNA binding sites showed that the three miRNAs bind to the same conserved region of the PB1 gene. Intriguingly, despite the fact that the miRNAs and PB1 mRNA binding sequences are not a perfect match, the miRNAs downregulate PB1 expression through mRNA degradation instead of translation repression. This is the first demonstration that cellular miRNAs regulate influenza viral replication by degradation of the viral gene. Our findings support the notion that any miRNA has antiviral potential, independent of its cellular function, and that the cellular miRNAs play an important role in the host, defending against virus infection.

All measures provided similar estimates of overall adherence, although refill and electronic measures were in highest agreement. In selection of a measure, practitioners should consider population and disease characteristics, since measurement agreement could be influenced by these and other factors. The commonly used, clinically based cut-point of 80% had a reasonable balance between sensitivity and specificity in studies of adherence in patients with heart failure or hypertension.

Neuroblastoma, the second most common solid tumor in children, frequently metastasizes to the bone marrow and the bone. Neuroblastoma cells present in the bone marrow stimulate the expression of interleukin-6 (IL-6) by bone marrow stromal cells (BMSC) to activate osteoclasts. Here we have examined whether stromal-derived IL-6 also has a paracrine effect on neuroblastoma cells.

CD1d-restricted V␣24-invariant natural killer T cells (iNKTs) are important in immunoregulation. CD4 ؉ and CD4 ؊ iNKTs develop with similar frequencies in murine thymus and depend on interleukin-15 (IL-15) in periphery. However, homeostatic requirements of iNKTs have not been analyzed in humans. We evaluated thymic production, peripheral dynamics, and functional maturation of human iNKTs. CD4 ؉ subset comprises 90% of iNKTs in mature thymocytes and cord blood (CB) but only 40% in adult blood.Using T-cell receptor excision circle (TREC) analysis, we directly measured in vivo replicative history of CD4 ؉ and CD4 ؊ iNKT cells. Compared to CD4 ؉ , CD4 ؊ iNKTs contain fewer TRECs, express higher levels of IL-2R␤, and proliferate with higher rate in response to IL-15. In contrast, CD4 ؉ cells express higher levels of IL-7R␣ and better respond to IL-7. Neither thymic nor CB iNKTs are able to produce cytokines unless they are induced to proliferate. Therefore, unlike in the mouse, human CD4 ؉ iNKTs are mainly supported by thymic output and limited peripheral expansion, whereas CD4 ؊ cells undergo extensive peripheral expansion, and both subsets develop their functions in periphery. These findings reveal important differences in homeostatic requirements and functional maturation between murine and human iNKTs that are to be considered for clinical purposes. (Blood.

As an emerging biomedical image processing technology, medical image segmentation has made great contributions to sustainable medical care. Now it has become an important research direction in the field of computer vision. With the rapid development of deep learning, medical image processing based on deep convolutional neural networks has become a research hotspot. This paper focuses on the research of medical image segmentation based on deep learning. First, the basic ideas and characteristics of medical image segmentation based on deep learning are introduced. By explaining its research status and summarizing the three main methods of medical image segmentation and their own limitations, the future development direction is expanded. Based on the discussion of different pathological tissues and organs, the specificity between them and their classic segmentation algorithms are summarized. Despite the great achievements of medical image segmentation in recent years, medical image segmentation based on deep learning has still encountered difficulties in research. For example, the segmentation accuracy is not high, the number of medical images in the data set is small and the resolution is low. The inaccurate segmentation results are unable to meet the actual clinical requirements. Aiming at the above problems, a comprehensive review of current medical image segmentation methods based on deep learning is provided to help researchers solve existing problems.

Vα24-invariant NKT cells inhibit tumor growth by targeting tumor-associated macrophages (TAMs).

Background/Aims: MicroRNA (miRNA) is a small non-coding RNA molecule that functions in regulation of gene expression by targeting mRNA to affect its stability and/or translation. The aim of this study was to evaluate the miRNAs involvement in gestational diabetes mellitus (GDM), a well known risk factor for fetal overgrowth. Methods: Differential microRNA expression in placental tissues of normal controls and women with GDM were identified by miRNA micorarray analysis and further confirmed by quantitative real-time PCR (qRT-PCR) on an independent set of normal and GDM placental tissues. Target genes of microRNAs were bioinformatically predicted and verified in vitro by Western blotting. Results: Our results uncovered 9 miRNAs that were significantly deregulated in GDM samples: miR-508-3p was up-regulated and miR-27a, miR-9, miR-137, miR-92a, miR-33a, miR-30d, miR-362-5p and miR-502-5p were down-regulated. Bioinformatic approaches revealed that the microRNAs signature identifies gene targets involved in EGFR (epidermal growth factor receptor)-PI3K (phosphoinositide 3-Kinase)-Akt (also known as protein kinase B) pathway, a signal cascade which plays important roles in placental development and fetal growth. We found that the protein levels of EGFR, PI3K and phospho-Akt were up-regulated and PIKfyve (a FYVE finger-containing phosphoinositide kinase), a negative regulator of EGFR signaling, was down-regulated significantly in GDM tissues. We also confirmed PIKfyve was a direct target of miR-508-3p. Conclusion: Our data identified a miRNA signature involvement in GDM which may contribute to macrosomia through enhancing EGFR signaling.