Search for bbbˉbˉbb\bar{b}\bar{b} tetraquark decays in 4 muons, B+B−B^{+} B^{-}, B0Bˉ0B^0 \bar{B}^0 and Bs0Bˉs0B_s^0 \bar{B}_s^0 channels at LHC

We perform a quantitative analysis of the $bb\bar{b}\bar{b}$ tetraquark decays into hidden- and open-bottom mesons and calculate, for the first time, the $bb\bar{b}\bar{b}$ tetraquark total decay width. On the basis of our results, we propose the $bb\bar{b}\bar{b} \to B^{+} B^{-} (B^0 \bar{B}^0) (B_s^0 \bar{B}_s^0) \to l^{+} l^{-}+\text{X}$ decays as the most suitable channels to observe the $bb\bar{b}\bar{b}$ tetraquark states, since the calculated two-lepton cross section upper limit, $\simeq 39$ fb, is so large as to be potentially detectable with the 2018 LHCb sensitivity, paving the way to the observation of the $bb\bar{b}\bar{b}$ tetraquark in the future LHCb upgrade. The $4\mu$ signal for the ground state, $J^{PC}=0^{++}$, is likely to be too small even for the upgraded LHCb, but it may not be hopeless for the $J^{PC}=2^{++}$ fully-bottom state.Comment: 11 pages, 1 figur

Apelin-13 Increases Functional Connexin-43 through Autophagy Inhibition via AKT/mTOR Pathway in the Non-Myocytic Cell Population of the Heart

Studies have shown a link between the downregulation of connexin 43 (Cx43), the predominant isoform in cardiac gap junctions, and high susceptibility to cardiac arrhythmias and cardiomyocyte death. Non-myocytic cells (NMCs), the most abundant component of the heart, exert multiple cardiac functions and represent an important therapeutic target for diseased cardiac tissue. A few studies have investigated the effect of Apelin-13, an endogenous peptide with a key role in various cardiovascular functions, on Cx43 expression in cardiomyocytes. However, it remained unknown whether Apelin-13 influences Cx43 expression in NMCs. Here, we found that in NMCs, Cx43 protein expression increased after Apelin-13 treatment (100 nM for 48 h). Furthermore, dye transfer assays proved that Apelin-13-treated NMCs had a greater ability to communicate with surrounding cardiomyocytes, and this effect was abrogated by carbenoxolone, a gap junction inhibitor. Interestingly, we showed that Apelin-13 increased Cx43 through autophagy inhibition, as proved by the upregulation of p62 and LC3I, acting as 3-MA, a well-known autophagy inhibitor. In addition, Apelin-13-induced AKT and mTOR phosphorylation was abolished by LY294002 and rapamycin inhibitors resulting in Cx43 increased suppression. These results open the possibility of targeting gap junctions in NMCs with Apelin-13 as an exciting therapeutic approach with great potential

Targeting cancer cells overexpressing folate receptors with new terpolymer-based nanocapsules: Toward a novel targeted dna delivery system for cancer therapy

Chemotherapeutics represent the standard treatment for a wide range of cancers. However, these agents also affect healthy cells, thus leading to severe off-target effects. Given the non-selectivity of the commonly used drugs, any increase in the selective tumor tissue uptake would represent a significant improvement in cancer therapy. Recently, the use of gene therapy to completely remove the lesion and avoid the toxicity of chemotherapeutics has become a tendency in oncotherapy. Ideally, the genetic material must be safely transferred from the site of administration to the target cells, without involving healthy tissues. This can be achieved by encapsulating genes into non-viral carriers and modifying their surface with ligands with high selectivity and affinity for a relevant receptor on the target cells. Hence, in this work we evaluate the use of terpolymer-based nanocapsules for the targeted delivery of DNA toward cancer cells. The surface of the nanocapsules is decorated with folic acid to actively target the folate receptors overexpressed on a variety of cancer cells. The nanocapsules demonstrate a good ability of encapsulating and releasing DNA. Moreover, the presence of the targeting moieties on the surface of the nanocapsules favors cell uptake, opening up the possibility of more effective therapies

Bayesian Machine Learning Techniques for revealing complex interactions among genetic and clinical factors in association with extra-intestinal Manifestations in IBD patients

The objective of the study is to assess the predictive performance of three different techniques as classifiers for extra-intestinal manifestations in 152 patients with Crohn's disease. Na\uefve Bayes, Bayesian Additive Regression Trees and Bayesian Networks implemented using a Greedy Thick Thinning algorithm for learning dependencies among variables and EM algorithm for learning conditional probabilities associated to each variable are taken into account. Three sets of variables were considered: (i) disease characteristics: presentation, behavior and location (ii) risk factors: age, gender, smoke and familiarity and (iii) genetic polymorphisms of the NOD2, CD14, TNFA, IL12B, and IL1RN genes, whose involvement in Crohn's disease is known or suspected. Extra-intestinal manifestations occurred in 75 patients. Bayesian Networks achieved accuracy of 82% when considering only clinical factors and 89% when considering also genetic information, outperforming the other techniques. CD14 has a small predicting capability. Adding TNFA, IL12B to the 3020insC NOD2 variant improved the accuracy