The promoting effects of Grin2d expression in tumorigenesis and the aggressiveness of esophageal cancer

Grin2d is an ionotropic NMDA receptor, a subunit of glutamate-dependent, and a facilitator of cellular calcium influx in neuronal tissue. In this study, we found that Grin2d expression was higher in esophageal cancer than in normal mucosa at both the mRNA and protein level using RT-PCR, bioinformatics analysis, and western blotting (p<0.05). Grin2d mRNA expression was positively correlated with old age, white race, heavy weight, distal location, adenocarcinoma, cancer with Barrett’s lesion, or high-grade columnar dysplasia (p<0.05). The differential genes associated with Grin2d mRNA were involved in fat digestion and absorption, cholesterol metabolism, lipid transfer, lipoproteins, synaptic membranes, and ABC transporters (p<0.05). The Grin2d-related genes were classified into the following categories: metabolism of glycerolipids, galactose, and O-glycan, cell adhesion binding, actin binding, cadherin binding, the Hippo signaling pathway, cell-cell junctions, desmosomes, DNA-transcription activator binding, and skin development and differentiation (p<0.05). Grin2d immunoreactivity was positively correlated with distal metastasis and unfavorable overall survival in esophageal cancer (p<0.05). Grin2d overexpression promoted proliferation, migration, and invasion in esophageal cancer cells but blocked apoptosis (p<0.05) and increased the expression of PI3K, Akt and p-mTOR. Grin2d knockout caused the opposite effects. These findings indicated that upregulated Grin2d expression played an important role in esophageal carcinogenesis via the PI3K/Akt/mTOR pathway and might be a biological marker for aggressive tumor behavior and poor prognosis. Its silencing might represent a targeted therapy approach against esophageal cancer

Effect of the counterrotating-wave terms on the spontaneous emission from a multilevel atom

Journals published by the American Physical Society can be found at http://publish.aps.org/The spontaneous decay of a multilevel atom interacting with the electromagnetic field in free space is investigated with a unitary transformation method, which is introduced in order to include all rotating and counter-rotating terms in the Hamiltonian. By using the ground state of the total Hamiltonian, the evolution of the effective decay rate and the energy shift are calculated. When the atomic transition frequency is smaller than the central frequency of the spectrum, the Zeno effect dominates, and if the atomic transition frequency is larger than the central frequency, the anti-Zeno effect will dominate. The time evolution of the energy shift is obtained. The counter-rotating terms lead to a shift toward the low frequency region for the frequency distribution of the emitted photon

The histone methyltransferase Set7/9 promotes myoblast differentiation and myofibril assembly

Set7 associates with the MyoD transcription factor to enhance expression of genes required for muscle differentiation

Functional building blocks for scalable multipartite entanglement in optical lattices

Featuring excellent coherence and operated parallelly, ultracold atoms in optical lattices form a competitive candidate for quantum computation. For this, a massive number of parallel entangled atom pairs have been realized in superlattices. However, the more formidable challenge is to scale-up and detect multipartite entanglement due to the lack of manipulations over local atomic spins in retro-reflected bichromatic superlattices. Here we developed a new architecture based on a cross-angle spin-dependent superlattice for implementing layers of quantum gates over moderately-separated atoms incorporated with a quantum gas microscope for single-atom manipulation. We created and verified functional building blocks for scalable multipartite entanglement by connecting Bell pairs to one-dimensional 10-atom chains and two-dimensional plaquettes of $2\times4$ atoms. This offers a new platform towards scalable quantum computation and simulation

Baichuan 2: Open Large-scale Language Models

Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan