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Institution

Shandong Normal University

EducationJinan, Shandong, China
About: Shandong Normal University is a education organization based out in Jinan, Shandong, China. It is known for research contribution in the topics: Laser & Catalysis. The organization has 12378 authors who have published 12576 publications receiving 174572 citations.


Papers
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Journal ArticleDOI
TL;DR: Several ethyl methanesulfonate mutants of salt cress that have reduced salinity tolerance are isolated, which provide evidence that salt tolerance in this halophyte can be significantly affected by individual genetic loci.
Abstract: Salt cress (Thellungiella halophila) is a small winter annual crucifer with a short life cycle. It has a small genome (about 2 × Arabidopsis) with high sequence identity (average 92%) with Arabidopsis, and can be genetically transformed by the simple floral dip procedure. It is capable of copious seed production. Salt cress is an extremophile native to harsh environments and can reproduce after exposure to extreme salinity (500 mm NaCl) or cold to −15°C. It is a typical halophyte that accumulates NaCl at controlled rates and also dramatic levels of Pro (>150 mm) during exposure to high salinity. Stomata of salt cress are distributed on the leaf surface at higher density, but are less open than the stomata of Arabidopsis and respond to salt stress by closing more tightly. Leaves of salt cress are more succulent-like, have a second layer of palisade mesophyll cells, and are frequently shed during extreme salt stress. Roots of salt cress develop both an extra endodermis and cortex cell layer compared to Arabidopsis. Salt cress, although salt and cold tolerant, is not exceptionally tolerant of soil desiccation. We have isolated several ethyl methanesulfonate mutants of salt cress that have reduced salinity tolerance, which provide evidence that salt tolerance in this halophyte can be significantly affected by individual genetic loci. Analysis of salt cress expressed sequence tags provides evidence for the presence of paralogs, missing in the Arabidopsis genome, and for genes with abiotic stress-relevant functions. Hybridizations of salt cress RNA targets to an Arabidopsis whole-genome oligonucleotide array indicate that commonly stress-associated transcripts are expressed at a noticeably higher level in unstressed salt cress plants and are induced rapidly under stress. Efficient transformation of salt cress allows for simple gene exchange between Arabidopsis and salt cress. In addition, the generation of T-DNA-tagged mutant collections of salt cress, already in progress, will open the door to a new era of forward and reverse genetic studies of extremophile plant biology.

449 citations

Journal ArticleDOI
TL;DR: A computer-generated hologram is introduced onto SLM for performing the beam conversion and optical realization of a variety of polarization configurations confirms the reliability and flexibility of the method.
Abstract: We describe a convenient approach for generating arbitrary vector beams in a 4-f system with a spatial light modulator (SLM) and a common path interferometric arrangement. A computer-generated hologram is introduced onto SLM for performing the beam conversion. Optical realization of a variety of polarization configurations confirms the reliability and flexibility of our method.

439 citations

Journal ArticleDOI
Bo Tang1, Fabiao Yu1, Ping Li1, Lili Tong1, Xia Duan1, Ting Xie1, Xu Wang1 
TL;DR: It is shown that the probe effectively avoids the influence of autofluorescence and native cellular species in biological systems and meanwhile exhibits high sensitivity, good photostability, and excellent cell membrane permeability.
Abstract: A near-neutral pH near-infrared (NIR) fluorescent probe utilizing a fluorophore-spacer- receptor molecular framework that can modulate the fluorescence emission intensity through a fast photoinduced electron-transfer process was developed. Our strategy was to choose tricarbocyanine (Cy), a NIR fluorescent dye with high extinction coefficients, as a fluorophore, and 4′-(aminomethylphenyl)-2,2′:6′,2′′-terpyridine (Tpy) as a receptor. The pH titration indicated that Tpy-Cy can monitor the minor physiological pH fluctuations with a pKa of ∼7.10 near physiological pH, which is valuable for intracellular pH researches. The probe responds linearly and rapidly to minor pH fluctuations within the range of 6.70−7.90 and exhibits strong dependence on pH changes. As expected, the real-time imaging of cellular pH and the detection of pH in situ was achieved successfully in living HepG2 and HL-7702 cells by this probe. It is shown that the probe effectively avoids the influence of autofluorescence and native cellular s...

430 citations

Journal ArticleDOI
TL;DR: The structured deep learning model used in this study has achieved remarkable performance on a large-scale dataset, which demonstrates the strength of the method in providing an efficient tool for breast cancer multi-classification in clinical settings.
Abstract: Automated breast cancer multi-classification from histopathological images plays a key role in computer-aided breast cancer diagnosis or prognosis. Breast cancer multi-classification is to identify subordinate classes of breast cancer (Ductal carcinoma, Fibroadenoma, Lobular carcinoma, etc.). However, breast cancer multi-classification from histopathological images faces two main challenges from: (1) the great difficulties in breast cancer multi-classification methods contrasting with the classification of binary classes (benign and malignant), and (2) the subtle differences in multiple classes due to the broad variability of high-resolution image appearances, high coherency of cancerous cells, and extensive inhomogeneity of color distribution. Therefore, automated breast cancer multi-classification from histopathological images is of great clinical significance yet has never been explored. Existing works in literature only focus on the binary classification but do not support further breast cancer quantitative assessment. In this study, we propose a breast cancer multi-classification method using a newly proposed deep learning model. The structured deep learning model has achieved remarkable performance (average 93.2% accuracy) on a large-scale dataset, which demonstrates the strength of our method in providing an efficient tool for breast cancer multi-classification in clinical settings.

425 citations

Journal ArticleDOI
TL;DR: Dense coding or superdense coding in the case of high-dimension quantum states between two parties and multiparties is studied in this paper.
Abstract: Dense coding or superdense coding in the case of high-dimension quantum states between two parties and multiparties is studied in this paper. We construct explicitly the measurement basis and the forms of the single-body unitary operations corresponding to the basis chosen, and the rules for selecting the one-body unitary operations in a multiparty case.

419 citations


Authors

Showing all 12482 results

NameH-indexPapersCitations
Feng Zhang1721278181865
Jinde Cao117143057881
Wei Zhang112118993641
Miao Liu11199359811
Qian Wang108214865557
Jun Yang107209055257
Feng Li10499560692
Feng Chen95213853881
Gang Li9348668181
Jianhong Wu9372636427
Chen-Ho Tung8966230111
Shu Tao8763927304
Bernhard Hommel8547528851
Lingxin Chen8542125147
Bo Tang8370624472
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202339
2022173
20211,864
20201,710
20191,488
20181,346