Long non-coding RNAs (lncRNAs) are emerging regulators of pathophysiological processes including atherosclerosis. Using RNA-seq profiling of the intima of lesions, here we identify a macrophage-specific lncRNA MAARS (Macrophage-Associated Atherosclerosis lncRNA Sequence). Aortic intima expression of MAARS increases by 270-fold with atherosclerotic progression and decreases with regression by 60%. MAARS knockdown reduces atherosclerotic lesion formation by 52% in LDLR-/- mice, largely independent of effects on lipid profile and inflammation, but rather by decreasing macrophage apoptosis and increasing efferocytosis in the vessel wall.  https://www.selleckchem.com/ALK.html  MAARS interacts with HuR/ELAVL1, an RNA-binding protein and important regulator of apoptosis. Overexpression and knockdown studies verified MAARS as a critical regulator of macrophage apoptosis and efferocytosis in vitro, in an HuR-dependent manner. Mechanistically, MAARS knockdown alters HuR cytosolic shuttling, regulating HuR targets such as p53, p27, Caspase-9, and BCL2. These findings establish a mechanism by which a macrophage-specific lncRNA interacting with HuR regulates apoptosis, with implications for a broad range of vascular disease states.Development of plasmonic biosensors combining reliability and ease of use is still a challenge. Gold nanoparticle arrays made by block copolymer micelle nanolithography (BCMN) stand out for their scalability, cost-effectiveness and tunable plasmonic properties, making them ideal substrates for fluorescence enhancement. Here, we describe a plasmon-enhanced fluorescence immunosensor for the specific and ultrasensitive detection of Plasmodium falciparum lactate dehydrogenase (PfLDH)-a malaria marker-in whole blood. Analyte recognition is realized by oriented antibodies immobilized in a close-packed configuration via the photochemical immobilization technique (PIT), with a top bioreceptor of nucleic acid aptamers recognizing a different surface of PfLDH in a sandwich conformation. The combination of BCMN and PIT enabled maximum control over the nanoparticle size and lattice constant as well as the distance of the fluorophore from the sensing surface. The device achieved a limit of detection smaller than 1 pg/mL ( less then 30 fM) with very high specificity without any sample pretreatment. This limit of detection is several orders of magnitude lower than that found in malaria rapid diagnostic tests or even commercial ELISA kits. Thanks to its overall dimensions, ease of use and high-throughput analysis, the device can be used as a substrate in automated multi-well plate readers and improve the efficiency of conventional fluorescence immunoassays.Little is known about the impact of pretreatment drug resistance (PDR) on the efficacy of second generation integrase inhibitors. We sequenced pretreatment plasma specimens from the ADVANCE trial (NCT03122262). Our primary outcome was 96-week virologic success, defined as a sustained viral load less then 1000 copies/mL from 12 weeks onwards, less then 200 copies/mL from 24 weeks onwards, and less then 50 copies/mL after 48 weeks. Here we report how this outcome was impacted by PDR, defined by the World Health Organization (WHO) mutation list. Of 1053 trial participants, 874 (83%) have successful sequencing, including 289 (33%) randomized to EFV-based therapy and 585 (67%) randomized to DTG-based therapy. Fourteen percent (122/874) have ≥1 WHO-defined mutation, of which 98% (120/122) are NNRTI mutations. Rates of virologic suppression are lower in the total cohort among those with PDR 65% (73/112) compared to those without PDR (85% [605/713], P less then 0.001), and for those on EFV-based treatment (60% [12/20] vs 86% [214/248], P = 0.002) and for those on DTG-based treatment (61/92 [66%] vs 84% [391/465] P less then 0.001, P for interaction by regimen 0.49). Results are similar in multivariable models adjusted for clinical characteristics and adherence. NNRTI resistance prior to treatment is associated with long-term failure of integrase inhibitor-containing first-line regimens, and portends high rates of first-line failure in sub Saharan Africa.This article has been retracted. Please see the Retraction Notice for more detail https//doi.org/10.1038/s41398-020-00987-z.Fulminant hepatic failure (FHF) is a clinical syndrome characterized by a sudden and severe impairment in liver function. However, the precise mechanism of immune dysregulation that is significant to FHF pathogenesis remains unclear. Enhancer of zeste homolog 2 (EZH2) has been implicated in inflammation as a regulator of immune cell function. In this study, we investigated the role of EZH2 in an animal model of human FHF induced by Propionibacterium acnes (P. acnes) and lipopolysaccharide (LPS). We demonstrated that EZH2 depletion in dendritic cells (DCs) and pharmacological inhibition of EZH2 using GSK126 both significantly ameliorated liver injury and improved the survival rates of mice with P. acnes plus LPS-induced FHF, which could be attributed to the decreased infiltration and activation of CD4+ T cells in the liver, inhibition of T helper 1 cells and induction of regulatory T cells. The expression of EZH2 in DCs was increased after P. acnes administration, and EZH2 deficiency in DCs suppressed DC maturation and prevented DCs from efficiently stimulating CD4+ T-cell proliferation. Further mechanistic analyses indicated that EZH2 deficiency directly increased the expression of the transcription factor RUNX1 and thereby suppressed the immune functions of DCs. The functional dependence of EZH2 on RUNX1 was further illustrated in DC-specific Ezh2-deficient mice. Taken together, our findings establish that EZH2 exhibits anti-inflammatory effects through inhibition of RUNX1 to regulate DC functions and that inhibition of EZH2 alleviates P. acnes plus LPS-induced FHF, probably by inhibiting DC-induced adaptive immune responses. These results highlight the effect of EZH2 on DCs, serving as a guide for the development of a promising immunotherapeutic strategy for FHF.Understanding the genetic regulatory code governing gene expression is an important challenge in molecular biology. However, how individual coding and non-coding regions of the gene regulatory structure interact and contribute to mRNA expression levels remains unclear. Here we apply deep learning on over 20,000 mRNA datasets to examine the genetic regulatory code controlling mRNA abundance in 7 model organisms ranging from bacteria to Human. In all organisms, we can predict mRNA abundance directly from DNA sequence, with up to 82% of the variation of transcript levels encoded in the gene regulatory structure. By searching for DNA regulatory motifs across the gene regulatory structure, we discover that motif interactions could explain the whole dynamic range of mRNA levels. Co-evolution across coding and non-coding regions suggests that it is not single motifs or regions, but the entire gene regulatory structure and specific combination of regulatory elements that define gene expression levels.