Searching Signals in Chinese Ancient Records for the 14^{14}C Increases in AD 774-775 and in AD 992-993

According to the analysis of the $^{14}$C content of two Japanese trees over a period of approximately 3000 years at high time resolution, Miyake (2012) found a rapid increase at AD 774-775 and later on at AD 992-993 (Miyake 2013). This corresponds to a high-energy event happened within one year that input $\gamma$-ray energy about 7$\times{}$10$^{24}$erg to the Earth, leaving the origin a mystery. Such strong event should have an unusual optical counterpart, and have been recorded in historical literature. We searched Chinese historical materials around AD 744-775 and AD 992-993, but no remarkable event was found except a violent thunderstorm in AD 775. However, the possibility of a thunderstorm containing so much energy is still unlikely. We conclude the event caused the $^{14}$C increase is still unclear. This event most probably has no optical counterpart, and short gamma-ray burst, giant flare of a soft gamma-ray repeater and terrestrial $\gamma$-ray flash may all be the candidates.Comment: 8 pages, 3 figure

Constraining the Mass of the Photon with Gamma-Ray Bursts

One of the cornerstones of modern physics is Einstein's special relativity, with its constant speed of light and zero photon mass assumptions. Constraint on the rest mass m_{\gamma} of photons is a fundamental way to test Einstein's theory, as well as other essential electromagnetic and particle theories. Since non-zero photon mass can give rise to frequency-(or energy-) dependent dispersions, measuring the time delay of photons with different frequencies emitted from explosive astrophysical events is an important and model-independent method to put such a constraint. The cosmological gamma-ray bursts (GRBs), with short time scales, high redshifts as well as broadband prompt and afterglow emissions, provide an ideal testbed for m_{\gamma} constraints. In this paper we calculate the upper limits of the photon mass with GRB early time radio afterglow observations as well as multi-band radio peaks, thus improve the results of Schaefer (1999) by nearly half an order of magnitude.Comment: 25 pages, 2 tables, Accepted by Journal of High Energy Astrophysic

Quantum Anomaly Detection with a Spin Processor in Diamond

In the processing of quantum computation, analyzing and learning the pattern of the quantum data are essential for many tasks. Quantum machine learning algorithms can not only deal with the quantum states generated in the preceding quantum procedures, but also the quantum registers encoding classical problems. In this work, we experimentally demonstrate the anomaly detection of quantum states encoding audio samples with a three-qubit quantum processor consisting of solid-state spins in diamond. By training the quantum machine with a few normal samples, the quantum machine can detect the anomaly samples with a minimum error rate of 15.4%. These results show the power of quantum anomaly detection in dealing with machine learning tasks and the potential to detect abnormal output of quantum devices.Comment: 10 pages, 8 figure

Resonant Quantum Principal Component Analysis

Principal component analysis has been widely adopted to reduce the dimension of data while preserving the information. The quantum version of PCA (qPCA) can be used to analyze an unknown low-rank density matrix by rapidly revealing the principal components of it, i.e. the eigenvectors of the density matrix with largest eigenvalues. However, due to the substantial resource requirement, its experimental implementation remains challenging. Here, we develop a resonant analysis algorithm with the minimal resource for ancillary qubits, in which only one frequency scanning probe qubit is required to extract the principal components. In the experiment, we demonstrate the distillation of the first principal component of a 4$\times$4 density matrix, with the efficiency of 86.0% and fidelity of 0.90. This work shows the speed-up ability of quantum algorithm in dimension reduction of data and thus could be used as part of quantum artificial intelligence algorithms in the future.Comment: 10 pages, 7 figures, have been waiting for the reviewers' responses for over 3 month

Proteasome Inhibition Augments Cigarette Smoke-Induced GM-CSF Expression in Trophoblast Cells via the Epidermal Growth Factor Receptor

Maternal cigarette smoking has adverse effects on pregnancy outcomes. The granulocyte-macrophage colony-stimulating factor (GM-CSF) is an essential cytokine for a normal pregnancy. We investigated the impact of cigarette smoke extract (CSE) on GM-CSF expression in human cytotrophoblast cells and suggested a cellular mechanism underlying the CSE-induced GM-CSF expression. An immortalized normal human trophoblast cell line (B6Tert-1) was treated with CSE. The viability and proliferation of the CSE-treated B6Tert-1 cells were evaluated, and the expression of GM-CSF in these cells was quantified at the mRNA and the protein levels by means of reverse-transcription and quantitative polymerase chain reaction (RT-qPCR); and enzyme-linked immunosorbent assay (ELISA), respectively. Human trophoblast cells treated with CSE had an increased expression of GM-CSF at both the mRNA and the protein levels. The CSE-induced GM-CSF expression was synergistically enhanced by the addition of the proteasome inhibitor MG-132, but inhibited by AG-1478, an inhibitor of the epidermal growth factor receptor (EGFR) kinase. Furthermore, CSE treatment increased the phosphorylation of the extracellular-signal regulated kinases (ERK1/2) in the trophoblast cells. The expression of other growth factors such as heparin-binding epidermal growth factor-like growth factor (HB-EGF) and vascular endothelial growth factor (VEGF) was also evaluated. Our data suggested that cigarette smoking and proteasome inhibition synergistically up-regulate GM-CSF cytokine expression by activating the EGFR signaling pathway

Application value of plasma Neurofilament light combined with magnetic resonance imaging to comprehensively evaluate multiple sclerosis activity and status

ObjectiveCompare the levels of plasma neurofilament light (NfL) in patients with multiple sclerosis (MS) at acute and remission stages and healthy individuals to explore the role of plasma NfL in monitoring the activity and severity of the disease and predicting disease prognosis.MethodsInformation on healthy individuals and patients with MS who visited the outpatient and inpatient departments of Inner Mongolia Medical University Affiliated Hospital from October 2020 to August 2022 was collected. EDSS assessment and plain scan+enhanced magnetic resonance imaging (MRI). Plasma Nfl levels were measured using Simoa. Moreover, the relationship between the level of Nlf and the disease status of patients with MS was analyzed..ResultsThrough the self-comparison of the plasma NfL levels of MS patients in the acute and remission stages, it was noted that the levels in the acute stage are higher than those in the remission stage (p < 0.001). Among the plasma NfL levels of healthy individuals and MS patients in the acute and remission stages, there were statistically significant differences (p < 0.001). Furthermore, the plasma NfL level did not correlate with age or course of disease (p = 0.614 and p = 0.058), whereas it correlated with EDSS score, the number of MRI T2 subtentorial and spinal cord lesions, and the number of MRI enhanced lesions (r = 0.789, p < 0.001; r = 0.846, p < 0.001; r = 0431, p = 0.005, respectively).ConclusionCombining the level of plasma NfL with clinical and MRI estimations will be instrumental in monitoring condition changes and optimizing treatments. The level of plasma NfL is related to the activity and severity of MS, and it is expected to become a new biomarker for assessing the activity and disease status of MS