Long non-coding RNA ATB promotes malignancy of esophageal squamous cell carcinoma by regulating miR-200b/Kindlin-2 axis

Esophageal squamous cell carcinoma (ESCC) is one of the leading causes of cancer-related death, especially in China. In addition, the prognosis of late stage patients is extremely poor. However, the biological significance of the long non-coding RNA lnc-ATB and its potential role in ESCC remain to be documented. In this study, we investigated the role of lnc-ATB and the underlying mechanism promoting its oncogenic activity in ESCC. Expression of lnc-ATB was higher in ESCC tissues and cell lines than that in normal counterparts. Upregulated lnc-ATB served as an independent prognosis predictor of ESCC patients. Moreover, loss-of-function assays in ESCC cells showed that knockdown of lnc-ATB inhibited cell proliferation and migration both in vitroand in vivo. Mechanistic investigation indicated that lnc-ATB exerted oncogenic activities via regulating Kindlin-2, as the anti-migration role of lnc-ATB silence was attenuated by ectopic expression of Kindlin-2. Further analysis showed that lnc-ATB functions as a molecular sponge for miR-200b and Kindlin-2. Dysregulated miR-200b/Kindlin-2 signaling mediated the oncogenic activity of lnc-ATB in ESCC. Our results suggest that lnc-ATB predicts poor prognosis and may serve as a potential therapeutic target for ESCC patients

Organelle-specific anchored delivery system stretching a reversal of tumor hypoxia microenvironment to a combinational chemo-photothermal therapy

Direct delivery to an organelle-specific point can boost the efficacy of therapy procedures to new heights. Among other subcellular organelles, mitochondria generate ATP as intracellular powerhouse, and are associated with multiple aspects of tumorigenesis and tumor development. Here, a mitochondrial anchored biomimetic nanoplatform (CZACN) is designed and its reversal of tumor hypoxia microenvironment underlying the mitochondria-located chemo-photothermal therapy is studied. After shuttling into cancer cells, therapeutic payloads including cisplatin (CDDP) and Au nanozymes are controllably released in the ATP-overexpressed mitochondria. CDDP generates O2â ¢â , forms H2O2 for a chemical fuel in the next reaction, and damages mitochondrial DNA. Meanwhile, the catalase-like Au nanozymes catalyze the produced hydrogen peroxide for oxygen supply to relieve hypoxic tumor microenvironment, offering cytotoxic singlet oxygen against cancer cells under NIR treatment. As a result of cancer-cell self-recognition, mitochondria-targeted therapy, and photothermal conversion ability, the fabricated CZACNs obtained 89.2 ± 3.70% of tumor growth inhibition under NIR irradiation and constrained the dose-limiting toxicity of CDDP, as well. These findings reinforce the synergistic effect of organelle-specific navigation and in situ oxygen self-sufficiency for combinational chemo-photothermal therapy.X.C., X.Y., and L.Z. contributed equally to this work. This work has been supported by the National Natural Science Foundation of China (22003038, 81922037, and 11575107), the Shanghai University-Universal Medical Imaging Diagnostic Research Foundation (19H00100), Shanghai Biomedical Science and Technology Support Project (19441903600), the Program for Changjiang Scholars and Innovative Research Team in University (IRT13078). The authors would like to thank the workers from Shiyanjia Lab (www.shiyanjia.com) for the ICP-OES analysis

Identifying Disease-Gene Associations With Graph-Regularized Manifold Learning

Complex diseases are known to be associated with disease genes. Uncovering disease-gene associations is critical for diagnosis, treatment, and prevention of diseases. Computational algorithms which effectively predict candidate disease-gene associations prior to experimental proof can greatly reduce the associated cost and time. Most existing methods are disease-specific which can only predict genes associated with a specific disease at a time. Similarities among diseases are not used during the prediction. Meanwhile, most methods predict new disease genes based on known associations, making them unable to predict disease genes for diseases without known associated genes.In this study, a manifold learning-based method is proposed for predicting disease-gene associations by assuming that the geodesic distance between any disease and its associated genes should be shorter than that of other non-associated disease-gene pairs. The model maps the diseases and genes into a lower dimensional manifold based on the known disease-gene associations, disease similarity and gene similarity to predict new associations in terms of the geodesic distance between disease-gene pairs. In the 3-fold cross-validation experiments, our method achieves scores of 0.882 and 0.854 in terms of the area under of the receiver operating characteristic (ROC) curve (AUC) for diseases with more than one known associated genes and diseases with only one known associated gene, respectively. Further de novo studies on Lung Cancer and Bladder Cancer also show that our model is capable of identifying new disease-gene associations

Population genomics of an icefish reveals mechanisms of glacier-driven adaptive radiation in Antarctic notothenioids

Background Antarctica harbors the bulk of the species diversity of the dominant teleost fish suborder—Notothenioidei. However, the forces that shape their evolution are still under debate. Results We sequenced the genome of an icefish, Chionodraco hamatus, and used population genomics and demographic modelling of sequenced genomes of 52 C. hamatus individuals collected mainly from two East Antarctic regions to investigate the factors driving speciation. Results revealed four icefish populations with clear reproduction separation were established 15 to 50 kya (kilo years ago) during the last glacial maxima (LGM). Selection sweeps in genes involving immune responses, cardiovascular development, and photoperception occurred differentially among the populations and were correlated with population-specific microbial communities and acquisition of distinct morphological features in the icefish taxa. Population and species-specific antifreeze glycoprotein gene expansion and glacial cycle-paced duplication/degeneration of the zona pellucida protein gene families indicated fluctuating thermal environments and periodic influence of glacial cycles on notothenioid divergence. Conclusions We revealed a series of genomic evidence indicating differential adaptation of C. hamatus populations and notothenioid species divergence in the extreme and unique marine environment. We conclude that geographic separation and adaptation to heterogeneous pathogen, oxygen, and light conditions of local habitats, periodically shaped by the glacial cycles, were the key drivers propelling species diversity in Antarctica.info:eu-repo/semantics/publishedVersio

Revisit to the yield ratio of triton and 3^3He as an indicator of neutron-rich neck emission

The neutron rich neck zone created in heavy ion reaction is experimentally probed by the production of the $A=3$ isobars. The energy spectra and angular distributions of triton and $^3$He are measured with the CSHINE detector in $^{86}$Kr +$^{208}$Pb reactions at 25 MeV/u. While the energy spectrum of $^{3}$He is harder than that of triton, known as "$^{3}$He-puzzle", the yield ratio $R({\rm t/^3He})$ presents a robust rising trend with the polar angle in laboratory. Using the fission fragments to reconstruct the fission plane, the enhancement of out-plane $R({\rm t/^3He})$ is confirmed in comparison to the in-plane ratios. Transport model simulations reproduce qualitatively the experimental trends, but the quantitative agreement is not achieved. The results demonstrate that a neutron rich neck zone is formed in the reactions. Further studies are called for to understand the clustering and the isospin dynamics related to neck formation

Scale Development-Related Genes Identified by Transcriptome Analysis

Scales, as key structures of fish skin, play an important role in physiological function. The study of fish scale development mechanisms provides a basis for exploring the molecular-level developmental differences between scaled and non-scaled fishes. In this study, alizarin red staining was used to divide the different stages of zebrafish (Danio rerio) scale development. Four developmental stages, namely stage I (~17 dpf, scales have not started to grow), stage II (~33 dpf, the point at which scales start to grow), stage III (~41 dpf, the period in which the scales almost cover the whole body), and stage IV (~3 mpf, scales cover the whole body), were determined and used for subsequent transcriptome analysis. WGCNA (weighted correlation network analysis) and DEG (differentially expressed gene) analysis were used for screening the key genes. Based on the comparison between stage II and stage I, 54 hub-genes were identified by WGCNA analysis. Key genes including the Scpp family (Scpp7, Scpp6, Scpp5, and Scpp8), the Fgf family (Fgfr1b and Fgfr3), Tcf7, Wnt10b, Runx2b, and Il2rb were identified by DEG analysis, which indicated that these genes played important roles in the key nodes of scale development signal pathways. Combined with this analysis, the TGF-β, Wnt/β-catenin, and FGF signaling pathways were suggested to be the most important signal pathways for scales starting to grow. This study laid a foundation for exploring the scale development mechanism of other fishes. The scale development candidate genes identified in the current study will facilitate functional gene identifications in the future