Determination of neutrino mass ordering from Supernova neutrinos with T2HK and DUNE

In this paper we study the possibility of determining the neutrino mass ordering from the future supernova neutrino events at the DUNE and T2HK detectors. We estimate the expected number of neutrino event rates from a future supernova explosion assuming GKVM flux model corresponding to different processes that are responsible for detecting the supernova neutrinos at these detectors. We present our results in the form of $\chi^2$, as a function of supernova distance. For a systematic uncertainty of 5\%, our results show that, the neutrino mass ordering can be determined at $5 ~\sigma$ C.L. if the supernova explosion occurs at a distance of 44 kpc for T2HK and at a distance of 6.5 kpc for DUNE. Our results also show that the sensitivity of T2HK gets affected by the systematic uncertainties for the smaller supernova distances. Further, we show that in both DUNE and T2HK, the sensitivity gets deteriorated to some extent due to presence of energy smearing of the neutrino events. This occurs because of the reconstruction of the neutrino energy from the energy-momentum measurement of the outgoing leptons at the detector.Comment: 19 pages, 7 figure

Exploring models with modular symmetry in neutrino oscillation experiments

Abstract Our study aims to investigate the viability of neutrino mass models that arise from discrete non-Abelian modular symmetry groups, i.e., Γ N with (N = 1, 2, 3, . . . ) in the future neutrino experiments T2HK, DUNE, and JUNO. Modular symmetry reduces the usage of flavon fields compared to the conventional discrete flavor symmetry models. Theories based on modular symmetries predict the values of leptonic mixing parameters, and therefore, these models can be tested in future neutrino experiments. In this study, we consider three models based on the A 4 modular symmetry, i.e., Model-A, B, and C such a way that they predict different values of the oscillation parameters but still allowed with respect to the current data. In the future, it is expected that T2HK, DUNE, and JUNO will measure the neutrino oscillation parameters very precisely, and therefore, some of these models can be excluded in the future by these experiments. We have estimated the prediction of these models numerically and then used them as input to scrutinize these models in the neutrino experiments. Assuming the future best-fit values of θ 23 and δ CP remain the same as the current one, our results show that at 5σ C.L, Model-A can be excluded by T2HK whereas Model-B can be excluded by both T2HK and DUNE. Model-C cannot be excluded by T2HK and DUNE at 5σ C.L. Further; our results show that JUNO alone can exclude Model-B at an extremely high confidence level if the future best-fit of θ 12 remains at the current-one. We have also identified the region in the θ 23 - δ CP parameter space, for which Model-A cannot be separated from Model-B in T2HK and DUNE

Virtual screening of truncated single stranded DNA aptamers for Staphylococcal enterotoxin type A

Single stranded DNA (ssDNA)/RNA aptamers, are screened through the labor intensive, iterative Systematic Evolution of Ligand by Exponential Enrichment process (SELEX) method. Complete sequence of screened aptamers never interacts with target or participates in final structure. Hence, in silico tools can be used to redesign a short length aptamer from previously reported aptamers which can have high affinity and specificity to the target. This approach is fast, cost effective, and less laborious than in vitro SELEX towards finding an aptamer sequence with better affinity with the target. Here, Staphylococcal enterotoxin type A (SEA) was used as target. A total of nine aptamers reported for different Staphylococcal food poisoning (SFP) enterotoxins were used as a starting pool. The aptamers were variously truncations and thoroughly analyzed through in silico methods. Three truncated aptamers namely AptSEA1.4, AptSEA2.4 and AptSEA8.4 were found to show higher affinity with target SEA. The computational data was also validated with DOT BLOT assay complemented with image analysis. These results also confirmed that the % specific binding and the dissociation constant (Kd) of truncated aptamers AptSEA1.4, AptSEA2.4 and AptSEA8.4 was better than their original counterparts. The truncated aptamers showed great promise to be used as a capture reagent in developing a sensitive assay for detection of SEA. Communicated by Ramaswamy H. Sarma</p

The tumor suppressor HINT1 regulates MITF and \u3b2-catenin transcriptional activity in melanoma cells

Histidine triad nucleotide-binding protein 1 (HINT1) is a haploinsufficient tumor suppressor gene that inhibits the Wnt/\u3b2-catenin pathway in colon cancer cells and Microphthalmia-associated transcription factor (MITF) activity in human mast cells. MITF and \u3b2-catenin play a central role in melanocyte and melanoma cell survival, and this study aimed to investigate the effects of HINT1 on the MITF and \u3b2-catenin pathways in malignant melanoma cells. We found that HINT1 inhibits MITF and \u3b2-catenin transcriptional activity, and both proteins can be co-immunoprecipitated with an anti-HINT1-specific antibody in melanoma cell lines. Stable, constitutive overexpression of the HINT1 protein in human melanoma cells significantly impaired cell proliferation in vitro and tumorigenesis in vivo. These effects were associated with a decreased expression of cyclin D1 and BCL2, well known MITF and \u3b2-catenin transcription targets, respectively. We also demonstrated that BCL2 and cyclin D1 can partially rescue the HINT1-driven phenotype. Moreover, we found in ChIP assays that HINT1 binds the chromatin at MITF and \u3b2-catenin sites in BCL2 and cyclin D1 promoters, respectively, and that mSIN3a and HDAC1, well known transcriptional repressors, can be co-immunoprecipitated with an anti-HINT1-specific antibody. These findings support the tumor suppressor activity of HINT1 gene in melanoma cells by promoting the formation of non-functional complexes with oncogenic transcription factors like MITF and \u3b2-catenin

Synthetic vulnerabilities of mesenchymal subpopulations in pancreatic cancer

Malignant neoplasms evolve in response to changes in oncogenic signalling. Cancer cell plasticity in response to evolutionary pressures is fundamental to tumour progression and the development of therapeutic resistance. Here we determine the molecular and cellular mechanisms of cancer cell plasticity in a conditional oncogenic Kras mouse model of pancreatic ductal adenocarcinoma (PDAC), a malignancy that displays considerable phenotypic diversity and morphological heterogeneity. In this model, stochastic extinction of oncogenic Kras signalling and emergence of Kras-independent escaper populations (cells that acquire oncogenic properties) are associated with de-differentiation and aggressive biological behaviour. Transcriptomic and functional analyses of Kras-independent escapers reveal the presence of Smarcb1-Myc-network-driven mesenchymal reprogramming and independence from MAPK signalling. A somatic mosaic model of PDAC, which allows time-restricted perturbation of cell fate, shows that depletion of Smarcb1 activates the Myc network, driving an anabolic switch that increases protein metabolism and adaptive activation of endoplasmic-reticulum-stress-induced survival pathways. Increased protein turnover renders mesenchymal sub-populations highly susceptible to pharmacological and genetic perturbation of the cellular proteostatic machinery and the IRE1-\u3b1-MKK4 arm of the endoplasmic-reticulum-stress-response pathway. Specifically, combination regimens that impair the unfolded protein responses block the emergence of aggressive mesenchymal subpopulations in mouse and patient-derived PDAC models. These molecular and biological insights inform a potential therapeutic strategy for targeting aggressive mesenchymal features of PDAC