Construction of network entrepreneurial platform leadership characteristics model: based on the grounded theory

With the embedding of internet technology, the entrepreneurial model has been gradually developing from  traditional single linear channel into network platform with symbiotic multi-platform. Platform leadership is the most important part of the new one and has been caught greatest attention. This paper put forward a new conception of network entrepreneurial platform leadership innovatively. By the integrated use of the Classical Grounded theory, the Procedure Grounded Theory and the Construction Grounded Theory, it adopted the normative research process of open coding, axial coding and selective coding to refine 34 concept—multi-node interactive, cross-level coupling relationship, etc, and formed  11 fundamental categories which include platform leadership power, network organization entrepreneurial mode, etc. Then, we analyzed the interactions between categories, based on which, a double-level and three-type-characteristics model were ultimately built. The study was finished by both two methods of statistical software and manual operation. In order to improve the reliability and validity of the study, it invited another coder to test the category subordination collaboratively, and used matched group to test the theoretical saturation.

Quantum-inspired deep reinforcement learning for adaptive frequency control of low carbon park island microgrid considering renewable energy sources

The low carbon park islanded microgrid faces operational challenges due to the high variability and uncertainty of distributed renewable energy sources. These sources cause severe random disturbances that impair the frequency control performance and increase the regulation cost of the islanded microgrid, jeopardizing its safety and stability. This paper presents a data-driven intelligent load frequency control (DDI-LFC) method to address this problem. The method replaces the conventional LFC controller with an intelligent agent based on a deep reinforcement learning algorithm. To adapt to the complex islanded microgrid environment and achieve adaptive multi-objective optimal frequency control, this paper proposes the quantum-inspired maximum entropy actor-critic (QIS-MEAC) algorithm, which incorporates the quantum-inspired principle and the maximum entropy exploration strategy into the actor-critic algorithm. The algorithm transforms the experience into a quantum state and leverages the quantum features to improve the deep reinforcement learning’s experience replay mechanism, enhancing the data efficiency and robustness of the algorithm and thus the quality of DDI-LFC. The validation on the Yongxing Island isolated microgrid model of China Southern Grid (CSG) demonstrates that the proposed method utilizes the frequency regulation potential of distributed generation, and reduces the frequency deviation and generation cost

Rank-Aware Negative Training for Semi-Supervised Text Classification

Semi-supervised text classification-based paradigms (SSTC) typically employ the spirit of self-training. The key idea is to train a deep classifier on limited labeled texts and then iteratively predict the unlabeled texts as their pseudo-labels for further training. However, the performance is largely affected by the accuracy of pseudo-labels, which may not be significant in real-world scenarios. This paper presents a Rank-aware Negative Training (RNT) framework to address SSTC in learning with noisy label manner. To alleviate the noisy information, we adapt a reasoning with uncertainty-based approach to rank the unlabeled texts based on the evidential support received from the labeled texts. Moreover, we propose the use of negative training to train RNT based on the concept that ``the input instance does not belong to the complementary label''. A complementary label is randomly selected from all labels except the label on-target. Intuitively, the probability of a true label serving as a complementary label is low and thus provides less noisy information during the training, resulting in better performance on the test data. Finally, we evaluate the proposed solution on various text classification benchmark datasets. Our extensive experiments show that it consistently overcomes the state-of-the-art alternatives in most scenarios and achieves competitive performance in the others. The code of RNT is publicly available at:https://github.com/amurtadha/RNT.Comment: TACL 202

Rashba-splitting-induced topological flat band detected by anomalous resistance oscillations beyond the quantum limit in ZrTe5_5

Topological flat band, on which the kinetic energy of topological electrons is quenched, represents a platform for investigating the topological properties of correlated systems. Recent experimental studies on flattened electronic bands have mainly concentrated on 2-dimensional materials created by van der Waals heterostructure-based engineering. Here, we report the observation of a topological flat band formed by polar-distortion-assisted Rashba splitting in a 3-dimensional Dirac material ZrTe$_5$. The polar distortion and resulting Rashba splitting on the band are directly detected by torque magnetometry and the anomalous Hall effect, respectively. The local symmetry breaking further flattens the band, on which we observe resistance oscillations beyond the quantum limit. These oscillations follow the temperature dependence of the Lifshitz-Kosevich formula but are evenly distributed in B instead of 1/B in high magnetic fields. Furthermore, the cyclotron mass anomalously gets enhanced about 10$^2$ times at field ~20 T. These anomalous properties of oscillations originate from a topological flat band with quenched kinetic energy. The topological flat band, realized by polar-distortion-assisted Rashba splitting in the 3-dimensional Dirac system ZrTe$_5$, signifies an intrinsic platform without invoking moir\'e or order-stacking engineering, and also opens the door for studying topologically correlated phenomena beyond the dimensionality of two.Comment: 32 pages, 11 figures; Version of original submissio

Sjögren’s Syndrome Complicated by Myeloid/Natural Killer Cell Precursor Acute Leukemia: Case Report and Review of the Literature

We report a case of Sjögren’s syndrome (SS) complicated by myeloid/natural killer (NK) cell precursor acute leukemia (M/NKPAL). A 75-year-old woman with a previous SS history for 2 years was routinely treated. Peripheral blood progenitor cells were increased, and subsequent bone marrow cell morphology examination showed the presence of acute myeloid leukemia type M4. However, flow cytometry analysis revealed that CD7/CD56/CD33/CD34/HLA-DR/cCD3 were all positive and myeloperoxidase- (MPO-) specific staining, other T cells, NK cells, and myeloid markers were all negative. Clonal T-cell receptor (TCR)β/TCRγ/TCRδ gene rearrangements and Epstein-Barr virus (EBV) were negative. The diagnosis of M/NKPAL was therefore confirmed. Unfortunately, this patient did not receive chemotherapy and later died of acute left heart failure and respiratory failure. SS complication with M/NKPAL is relatively rare. Combined with the relevant literatures, our study offers new insights into the clinical characteristics, pathological features, possible pathogenesis, and differential diagnosis of this rare disease

Targeting PELP1 Attenuates Angiogenesis and Enhances Chemotherapy Efficiency in Colorectal Cancer

SIMPLE SUMMARY: Excessive angiogenesis is a distinct feature of colorectal cancer (CRC) and plays a pivotal role in tumor development and metastasis. Therefore, it is essential to clarify the underlying mechanism of angiogenesis. In this study, we found that the level of proline-, glutamic acid, and leucine-rich protein 1 (PELP1) was positively correlated with microvessel density (MVD). In vitro and in vivo assays further showed PELP1 regulated angiogenesis via the Signal transducer and activator of transcription 3 (STAT3)/Vascular endothelial growth factor (VEGFA). Notably, we found that inhibition of PELP1 enhanced the efficacy of chemotherapy due to vascular normalization. Thus, targeting of PELP1 may be a potentially therapeutic strategy for CRC. ABSTRACT: Abnormal angiogenesis is one of the important hallmarks of colorectal cancer as well as other solid tumors. Optimally, anti-angiogenesis therapy could restrain malignant angiogenesis to control tumor expansion. PELP1 is as a scaffolding oncogenic protein in a variety of cancer types, but its involvement in angiogenesis is unknown. In this study, PELP1 was found to be abnormally upregulated and highly coincidental with increased MVD in CRC. Further, treatment with conditioned medium (CM) from PELP1 knockdown CRC cells remarkably arrested the function of human umbilical vein endothelial cells (HUVECs) compared to those treated with CM from wildtype cells. Mechanistically, the STAT3/VEGFA axis was found to mediate PELP1-induced angiogenetic phenotypes of HUVECs. Moreover, suppression of PELP1 reduced tumor growth and angiogenesis in vivo accompanied by inactivation of STAT3/VEGFA pathway. Notably, in vivo, PELP1 suppression could enhance the efficacy of chemotherapy, which is caused by the normalization of vessels. Collectively, our findings provide a preclinical proof of concept that targeting PELP1 to decrease STAT3/VEGFA-mediated angiogenesis and improve responses to chemotherapy due to normalization of vessels. Given the newly defined contribution to angiogenesis of PELP1, targeting PELP1 may be a potentially ideal therapeutic strategy for CRC as well as other solid tumors

Generation and Application of Inducible Chimeric RNA ASTN2-PAPPA(as) Knockin Mouse Model

Chimeric RNAs (chiRNAs) play many previously unrecognized roles in different diseases including cancer. They can not only be used as biomarkers for diagnosis and prognosis of various diseases but also serve as potential therapeutic targets. In order to better understand the roles of chiRNAs in pathogenesis, we inserted human sequences into mouse genome and established a knockin mouse model of the tamoxifen-inducible expression of ASTN2-PAPPA antisense chimeric RNA (A-P(as)chiRNA). Mice carrying the A-P(as)chiRNA knockin gene do not display any apparent abnormalities in growth, fertility, histological, hematopoietic, and biochemical indices. Using this model, we dissected the role of A-P(as)chiRNA in chemical carcinogen 4-nitroquinoline 1-oxide (4NQO)-induced carcinogenesis of esophageal squamous cell carcinoma (ESCC). To our knowledge, we are the first to generate a chiRNA knockin mouse model using the Cre-loxP system. The model could be used to explore the roles of chiRNA in pathogenesis and potential targeted therapies

Correction:Repurposing dextromethorphan and metformin for treating nicotine-induced cancer by directly targeting CHRNA7 to inhibit JAK2/STAT3/SOX2 signaling (Oncogene, (2021), 40, 11, (1974-1987), 10.1038/s41388-021-01682-z)

Only after the article was published online did the authors notice the misspelling of the second author’s name. It should be “Liang Du” instead of “Du Liang”. The authors sincerely apologize for any inconvenience this might have caused. The original article has been corrected

Repurposing dextromethorphan and metformin for treating nicotine-induced cancer by directly targeting CHRNA7 to inhibit JAK2/STAT3/SOX2 signaling

Smoking is one of the most impactful lifestyle-related risk factors in many cancer types including esophageal squamous cell carcinoma (ESCC). As the major component of tobacco and e-cigarettes, nicotine is not only responsible for addiction to smoking but also a carcinogen. Here we report that nicotine enhances ESCC cancer malignancy and tumor-initiating capacity by interacting with cholinergic receptor nicotinic alpha 7 subunit (CHRNA7) and subsequently activating the JAK2/STAT3 signaling pathway. We found that aberrant CHRNA7 expression can serve as an independent prognostic factor for ESCC patients. In multiple ESCC mouse models, dextromethorphan and metformin synergistically repressed nicotine-enhanced cancer-initiating cells (CIC) properties and inhibited ESCC progression. Mechanistically, dextromethorphan non-competitively inhibited nicotine binding to CHRNA7 while metformin downregulated CHRNA7 expression by antagonizing nicotine-induced promoter DNA hypomethylation of CHRNA7. Since dextromethorphan and metformin are two safe FDA-approved drugs with minimal undesirable side-effects, the combination of these drugs has a high potential as either a preventive and/or a therapeutic strategy against nicotine-promoted ESCC and perhaps other nicotine-sensitive cancer types as well