Search for light dark matter from atmosphere in PandaX-4T

We report a search for light dark matter produced through the cascading decay of $\eta$ mesons, which are created as a result of inelastic collisions between cosmic rays and Earth's atmosphere. We introduce a new and general framework, publicly accessible, designed to address boosted dark matter specifically, with which a full and dedicated simulation including both elastic and quasi-elastic processes of Earth attenuation effect on the dark matter particles arriving at the detector is performed. In the PandaX-4T commissioning data of 0.63 tonne$\cdot$year exposure, no significant excess over background is observed. The first constraints on the interaction between light dark matter generated in the atmosphere and nucleus through a light scalar mediator are obtained. The lowest excluded cross-section is set at $5.9 \times 10^{-37}{\rm cm^2}$ for dark matter mass of $0.1$ MeV$/c^2$ and mediator mass of 300 MeV$/c^2$. The lowest upper limit of $\eta$ to dark matter decay branching ratio is $1.6 \times 10^{-7}$

A Search for Light Fermionic Dark Matter Absorption on Electrons in PandaX-4T

We report a search on a sub-MeV fermionic dark matter absorbed by electrons with an outgoing active neutrino using the 0.63 tonne-year exposure collected by PandaX-4T liquid xenon experiment. No significant signals are observed over the expected background. The data are interpreted into limits to the effective couplings between such dark matter and electrons. For axial-vector or vector interactions, our sensitivity is competitive in comparison to existing astrophysical bounds on the decay of such dark matter into photon final states. In particular, we present the first direct detection limits for an axial-vector (vector) interaction which are the strongest in the mass range from 25 to 45 (35 to 50) keV/c$^2$

Phosphorylation in the regulation of muscle-specific transcription

The contents of this dissertation include studies on the mechanisms by which FGF and growth factor down-stream kinases inactivate myogenin; characterization of myogenin phosphorylation and its role in regulation of myogenin activity; analysis the C-terminal transcriptional activation domain of myogenin; studies on the nuclear localization of myogenin and characterization of proteins that interact with PKC. Activation of muscle transcription by the MyoD family requires their heterodimerization with ubiquitous bHLH proteins such as the E2A gene products E12 and E47. I have shown that dimerization with E2A products potentiates phosphorylation of myogenin at serine 43 in its amino-terminus and serine 170 in the carboxyl-terminal transcription activation domains. Mutations of these sites resulted in enhanced transcriptional activity of myogenin, suggesting that their phosphorylation diminishes myogenin\u27s transcriptional activity. Consistent with the role of phosphorylation at serine 170, analysis of the carboxyl-terminal transcriptional activation domain by deletion has revealed a stretch of residues from 157 to 170 which functions as a negative element for myogenin activity. In addition to inducing phosphorylation of myogenin, E12 also localizes myogenin to the nucleus. The DNA binding and dimerization mutants of myogenin show various deficiencies in nuclear localization. Cotransfection of E12 with the DNA binding mutants, but not a dimerization mutant, greatly enhances their nuclear binding. These data suggest that the nuclear localization signal is located in the DNA binding region and myogenin can also be nuclear localized by virtue of dimerizing with a nuclear protein. FGF is one of the most potent inhibitors of myogenesis and activates many down-stream pathways to exert its functions. One of these pathway is the MAP kinase pathway. Studies have shown that Raf-1 and Erk-1 kinase inactivate transactivation by myogenin and E proteins independent of DNA binding. The other is the PKC pathway. In transfected cells, FGF induces phosphorylation of thr-87 that maps to the previously identified PKC sites in the DNA binding domain of myogenin. Myogenin mutant T-N87 could resist the inhibition directed to the bHLH domain by FGF, suggesting that FGF inactivates myogenin by inducing phosphorylation of this site. In C2 myotubes, where FGF receptors are lost, the phosphatase inhibitor, okadaic acid, and phorbal ester PdBu, can also induce the phosphorylation of thr-87. This result supports the previous observation and suggests that in myotubes, other mechanisms, such as innervation, may inactivate myogenin through PKC induced phosphorylation. Many functions of PKC have been well documented, yet, little is known about the activators or effectors of PKC or proteins that mediate PKC nuclear localizations. Identification of PKC binding proteins will help to understand the molecular mechanism of PKC function. Two proteins that interact with the C kinase (PICKS) have been characterized, PICK-1 and PICK-2. PICK1 interacts with two conserved regions in the catalytic domain of PKC. It is localized to the perinuclear region and is phosphorylated in response to PKC activation. PICK2 is a novel protein with homology to the heat shock protein family. It interacts extensively with the catalytic domain of PKC and is localized in the cytoplasm in a punctate pattern. PICK1 and PICK2 may play important roles in mediating the actions of PKC

Autodetection of J Wave Based on Random Forest with Synchrosqueezed Wavelet Transform

J wave is the bulge generated in the descending slope of the terminal portion of the QRS complex in the electrocardiogram. The presence of J wave may lead to sudden death. However, the diagnosis of J wave variation only depends on doctor’s clinical experiences at present and missed diagnosis is easy to occur. In this paper, a new method is proposed to realize the automatic detection of J wave. First, the synchrosqueezed wavelet transform is used to obtain the precise time-frequency information of the ECG. Then, the inverse transformation of SST is computed to get the intrinsic mode function of the ECG. At last, the time-frequency features and SST-based and the entropy features based on modes are fed to Random forest to realize the automatic detection of J wave. As the experimental results shown, the proposed method has achieved the highest accuracy, sensitivity, and specificity compared with existing techniques