Anti–miR-93-5p therapy prolongs sepsis survival by restoring the peripheral immune response

Sepsis remains a leading cause of death for humans and currently has no pathogenesis-specific therapy. Hampered progress is partly due to a lack of insight into deep mechanistic processes. In the past decade, deciphering the functions of small noncoding miRNAs in sepsis pathogenesis became a dynamic research topic. To screen for new miRNA targets for sepsis therapeutics, we used samples for miRNA array analysis of PBMCs from patients with sepsis and control individuals, blood samples from 2 cohorts of patients with sepsis, and multiple animal models: mouse cecum ligation puncture–induced (CLP-induced) sepsis, mouse viral miRNA challenge, and baboon Gram+ and Gram– sepsis models. miR-93-5p met the criteria for a therapeutic target, as it was overexpressed in baboons that died early after induction of sepsis, was downregulated in patients who survived after sepsis, and correlated with negative clinical prognosticators for sepsis. Therapeutically, inhibition of miR-93-5p prolonged the overall survival of mice with CLP-induced sepsis, with a stronger effect in older mice. Mechanistically, anti–miR-93-5p therapy reduced inflammatory monocytes and increased circulating effector memory T cells, especially the CD4+ subset. AGO2 IP in miR-93–KO T cells identified important regulatory receptors, such as CD28, as direct miR-93-5p target genes. In conclusion, miR-93-5p is a potential therapeutic target in sepsis through the regulation of both innate and adaptive immunity, with possibly a greater benefit for elderly patients than for young patients

MicroRNA Fingerprints Identify miR-150 as a Plasma Prognostic Marker in Patients with Sepsis

BACKGROUND: The physiopathology of sepsis continues to be poorly understood, and despite recent advances in its management, sepsis is still a life-threatening condition with a poor outcome. If new diagnostic markers related to sepsis pathogenesis will be identified, new specific therapies might be developed and mortality reduced. Small regulatory non-coding RNAs, microRNAs (miRNAs), were recently linked to various diseases; the aim of our prospective study was to identify miRNAs that can differentiate patients with early-stage sepsis from healthy controls and to determine if miRNA levels correlate with the severity assessed by the Sequential Organ Failure Assessment (SOFA) score. METHODOLOGY/PRINCIPAL FINDINGS: By using genome-wide miRNA profiling by microarray in peripheral blood leukocytes, we found that miR-150, miR-182, miR-342-5p, and miR-486 expression profiles differentiated sepsis patients from healthy controls. We also proved by quantitative reverse transcription-polymerase chain reaction that miR-150 levels were significantly reduced in plasma samples of sepsis patients and correlated with the level of disease severity measured by the SOFA score, but were independent of the white blood counts (WBC). We found that plasma levels of tumor necrosis factor alpha, interleukin-10, and interleukin-18, all genes with sequence complementarity to miR-150, were negatively correlated with the plasma levels of this miRNA. Furthermore, we identified that the plasma levels ratio for miR-150/interleukin-18 can be used for assessing the severity of the sepsis. CONCLUSIONS/SIGNIFICANCE: We propose that miR-150 levels in both leukocytes and plasma correlate with the aggressiveness of sepsis and can be used as a marker of early sepsis. Furthermore, we envision miR-150 restoration as a future therapeutic option in sepsis patients

The Long Noncoding RNA CCAT2 Induces Chromosomal Instability Through BOP1-AURKB Signaling

BACKGROUND & AIMS: Chromosomal instability (CIN) is a carcinogenesis event that promotes metastasis and resistance to therapy by unclear mechanisms. Expression of the colon cancer-associated transcript 2 gene (CCAT2), which encodes a long noncoding RNA (lncRNA), associates with CIN, but little is known about how CCAT2 lncRNA regulates this cancer enabling characteristic.METHODS: We performed cytogenetic analysis of colorectal cancer (CRC) cell lines (HCT116, KM12C/SM, and HT29) overexpressing CCAT2 and colon organoids from C57BL/6N mice with the CCAT2 transgene and without (controls). CRC cells were also analyzed by immunofluorescence microscopy, gamma-H2AX, and senescence assays. CCAT2 transgene and control mice were given azoxymethane and dextran sulfate sodium to induce colon tumors. We performed gene expression array and mass spectrometry to detect downstream targets of CCAT2 lncRNA. We characterized interactions between CCAT2 with downstream proteins using MS2 pull-down, RNA immunoprecipitation, and selective 2'-hydroxyl acylation analyzed by primer extension analyses. Downstream proteins were overexpressed in CRC cells and analyzed for CIN. Gene expression levels were measured in CRC and non-tumor tissues from 5 cohorts, comprising more than 900 patients.RESULTS: High expression of CCAT2 induced CIN in CRC cell lines and increased resistance to 5-fluorouracil and oxaliplatin. Mice that expressed the CCAT2 transgene developed chromosome abnormalities, and colon organoids derived from crypt cells of these mice had a higher percentage of chromosome abnormalities compared with organoids from control mice. The transgenic mice given azoxymethane and dextran sulfate sodium developed more and larger colon polyps than control mice given these agents. Microarray analysis and mass spectrometry indicated that expression of CCAT2 increased expression of genes involved in ribosome biogenesis and protein synthesis. CCAT2 lncRNA interacted directly with and stabilized BOP1 ribosomal biogenesis factor (BOP1). CCAT2 also increased expression of MYC, which activated expression of BOP1. Overexpression of BOP1 in CRC cell lines resulted in chromosomal missegregation errors, and increased colony formation, and invasiveness, whereas BOP1 knockdown reduced viability. BOP1 promoted CIN by increasing the active form of aurora kinase B, which regulates chromosomal segregation. BOP1 was overexpressed in polyp tissues from CCAT2 transgenic mice compared with healthy tissue. CCAT2 lncRNA and BOP1 mRNA or protein were all increased in microsatellite stable tumors (characterized by CIN), but not in tumors with microsatellite instability compared with nontumor tissues. Increased levels of CCAT2 lncRNA and BOP1 mRNA correlated with each other and with shorter survival times of patients.CONCLUSIONS: We found that overexpression of CCAT2 in colon cells promotes CIN and carcinogenesis by stabilizing and inducing expression of BOP1 an activator of aurora kinase B. Strategies to target this pathway might be developed for treatment of patients with microsatellite stable colorectal tumors

Preliminary ruminant digestibility evaluation of some Romanian winter barley genotypes grown on two levels of N fertilization

The aim of the study was to evaluate the effects of nitrogen N levels on ruminant digestibility of 18 different Romanian barley genotypes grown in 2013/2014 year. The experiment was designed as randomized blocks and two levels of N were tested: 46 and 92 kg ha-1 (blocks N-46 and N-92) and compared to control block N-0, without nitrogen. The grains were analyzed for chemical composition and in vitro ruminant digestibility IVOMD. The resulted grains yield (t/ha) was significantly lowered by the 92 kg ha-1 N level. The same N fertilization level had a significant effect on increasing the crude protein content. But the mean IVOMD coefficient (%) of all genotypes was significantly decreased for both the N levels (84.45 for N-46, and 83.19 for N-92 compared to 86.92 for N-0)

Safety and Efficacy of Simultaneous Resection of Gastric Carcinoma and Synchronous Liver Metastasis—A Western Center Experience

Background and objectives: Gastric cancer (GC) is often diagnosed in the metastatic stage. Palliative systemic therapy is still considered the gold standard, even for patients with resectable oligometastatic disease. The aim of the current study is to assess the potential benefit of up-front gastric and liver resection in patients with synchronous resectable liver-only metastases from GC (LMGC) in a Western population. Materials and Methods: All patients with GC and synchronous LMGC who underwent gastric resection with or without simultaneous resection of LMs between January 1997 and December 2016 were selected from the institutional records. Those with T4b primary tumors or with unresectable or more than three LMs were excluded from the analysis. All patients who underwent emergency surgery for hemorrhagic shock or gastric perforation were also excluded. Results: Out of 28 patients fulfilling the inclusion criteria, 16 underwent simultaneous gastric and liver resection (SR group), while 12 underwent palliative gastric resection (GR group). The median overall survival (OS) of the entire cohort was of 18.81 months, with 1-, 3- and 5-year OS rates of 71.4%, 17.9% and 14.3%, respectively. The 1-, 3- and 5-year OS rates in SR group (75%, 31.3% and 25%, respectively) were significantly higher than those achieved in GR group (66.7%, 0% and 0%, respectively; p = 0.004). Multivariate analysis of the entire cohort revealed that the only independent prognostic factor associated with better OS was liver resection (HR = 3.954, 95% CI: 1.542–10.139; p = 0.004). Conclusions: In a Western cohort, simultaneous resection of GC and LMGC significantly improved OS compared to patients who underwent palliative gastric resection

Specific Structural Indexes for Resonance Norway Spruce Wood Used for Violin Manufacturing

The aim of this study was to assess wood quality using diagnostic keys related to the main traits of trunk architecture in the most important resource of resonance spruce of the Romanian Carpathians. The material sampled from standing and felled trees yielded 568 individual ring series adding up to over 81,000 growth rings. The resonance xylotype was first recognized in felled trees, already designated for violin manufacture, for which a 6-class quality classification system was proposed. This system was extended to the qualitative classification of the standing trees (diameter at breast height larger than 10 cm). The width and regularity of the growth rings, the width of the sapwood and latewood, and the compression wood ratio are the variables that make recognition of trees containing resonance wood possible. Wood with resonance structural value was detected locally along the tree stem, and the best resonance structural quality was found uniformly distributed from 5 to 9 m above the ground and in the external half of the cross-section. Trees having a proper structure for violin fliches, but not yet with an appropriate size (38 cm underbark diameter), accounted for about 7% of the total tree population

Using microRNA Networks to Understand Cancer

Human cancers are characterized by deregulated expression of multiple microRNAs (miRNAs), involved in essential pathways that confer the malignant cells their tumorigenic potential. Each miRNA can regulate hundreds of messenger RNAs (mRNAs), while various miRNAs can control the same mRNA. Additionally, many miRNAs regulate and are regulated by other species of non-coding RNAs, such as circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs). For this reason, it is extremely difficult to predict, study, and analyze the precise role of a single miRNA involved in human cancer, considering the complexity of its connections. Focusing on a single miRNA molecule represents a limited approach. Additional information could come from network analysis, which has become a common tool in the biological field to better understand molecular interactions. In this review, we focus on the main types of networks (monopartite, association networks and bipartite) used for analyzing biological data related to miRNA function. We briefly present the important steps to take when generating networks, illustrating the theory with published examples and with future perspectives of how this approach can help to better select miRNAs that can be therapeutically targeted in cancer

Circulating miRNAs in sepsis—A network under attack: An <i>in-silico</i> prediction of the potential existence of miRNA sponges in sepsis - Fig 4

<p><b>The simulation of the mathematical model (panel A) and the network representation of three possible scenarios (panel B).</b> On the upper row the dynamics of the three scenarios: (S1), (S2), (S3) are represented (panel A). Legend: red = predators, green = preys, t = time, c = concentration. The horizontal axis represents time (t) and the vertical axis the concentration (c) of the predators and preys. By simulating the model for the three scenarios, we obtained the three set of data visualized in this figure: (S1) represents a connected network, where the upper red line is the concentration of the predator Y, the lower red line represents the concentration of the second predator X and the green line is the concentration of the the prey A; (S2) and (S3) represent disconnected networks. In the second scenario (S2) the initial higher concentration of Y decreases rapidly because of the low reaction rate (0.25) and the initial lower red line (the concentration of X) increases rapidly because of the high reaction rate (0.75), the lower green line represents the prey (A). In the third scenario the initial concentrations are the same: the upper red line is the concentration of Y which decreases rapidly because of the low reaction rates (0.9 and 0.1), the lower red line is the concentration of X, which will increase, because of the high reaction rates (0.9 and 0.5), the upper green line is the prey A and a new prey appears (B)–the lower green line. The concentration of A will decrease more rapidly than that of B, because of the rising concentration of the predator X, who has a high reaction rate for A and B (0.9, respectively 0.5). On the middle and lower rows three corresponding network representations are shown (panel B). The first column of the B panel represents a scenario (S1) that could reflect the mechanisms in the control group. In this case, we have two miRNAs (X and Y) competing for one common target A. The numeric value represents the reaction rates between the miRNAs and their target. In the network representation of this scenario, the two miRNAs are connected. In the second column of panel B, the scenario S2 is depicted and its network representation. In this case, the reaction rate between X and A (0.75), is different from the reaction rate between Y and A (0.25). In the corresponding network representation, the miRNAs are no longer connected. Thus, a different reaction rate between the miRNAs and a common target could be the underling mechanism that could explain the loss of edges in sepsis. The third column of panel B represents the S3 scenario. In this scenario, a new target appears (B). The two miRNAs X and Y have the same reaction rate for the first target (A), but very different reaction rates for the new target (B), 0.1 and 0.5, respectively. In the corresponding network representation, the two miRNAs are no longer connected. The S3 scenario represents, as well, a possible underling mechanism that explains the loss of connections observed in sepsis.</p