Visible light nonlinear absorption and optical limiting of ultrathin ZrSe3 nanoflakes.

The nonlinear absorption and nonlinear refractive properties of ZrSe3 nanoflakes were studied with a 6.5 ns pulse laser at 532 nm. Open-aperture Z-scan curves reveal that ZrSe3 nanoflakes have a strong reverse saturable absorption property, and close-aperture Z-scan curves show that ZrSe3 dispersions possess a positive nonlinear refractive index caused by self-focusing. The nonlinear absorption coefficient, the nonlinear refraction coefficient, and the figures of merit (FOM) of ZrSe3 dispersed in water with linear transmittances of 0.86 at input energy of 18 µJ are 6.35 × 10-10 m W-1 15.73 × 10-17 m2 W-1, and 10.09 × 10-11 esu · cm respectively. In addition, nonlinear optical (NLO) performance of ZrSe3 nanoflakes depends on organic solvent dispersions. ZrSe3 nanoflakes in water dispersions have the largest FOM of 10.27 × 10-11 esu · cm, while the FOM in ethanol dispersions is 5.41 × 10-11 esu · cm at the same input energy of 26.5 µJ. The optical limiting threshold Fth of ZrSe3 nanosheet is 2.2 J cm-2 under picosecond laser pulse. The Results imply that ZrSe3 nanoflakes are an extraordinarily promising material for novel nanophotonic devices like optical limiters.

Physiological and symbiotic variation of a long-term evolved Rhizobium strain under alkaline condition.

Physiological variation and adaptation of the long-term evolved rhizobia to alkaline environments where no host plant existence and the stability of their symbiotic properties when they are reinoculated to legume host remain unclear. A highly effective N2-fixing Rhizobium yanglingense strain CCBAU 01603 was used as the ancestral strain and was cultured continuously with/without addition of extra alkaline reagent (KOH) in laboratory conditions for approximately 500 generations. Total 60 evolved clones obtained were checked for their adaptation to higher alkaline pH level and inoculated to their host plant Caragana microphylla to evaluate their symbiotic efficiencies. Most of the evolved clones showed increased adaptation to higher alkaline pH but all of them decreased symbiotic efficiencies, resulting in the formation of irregular root nodules with lower nitrogenase activity, production of abnormal bacteroids, and accumulation more starch grains in uninfected nodule cells. Further demonstration of lower symbiotic efficiencies came from the down-regulated expression of genes related to nitrogen fixation in the bacteroids by transcriptome comparison. In addition, genes related to transporters and other diverse functions were up- or down-regulated in the evolved clones in free-living conditions (like yjiS gene) or in symbiotic situations, demonstrating the significant variations in cellular physiology and symbiosis. Our study revealed that the enhancement of alkaline adaptation but loss of symbiotic efficiencies of the evolved clones had happened during the long-term evolution in alkaline environments where no selective pressures from host plant, offering new insight into the molecular mechanism and direction of rhizobial evolution in nature.

Deep Learning for Accurate Diagnosis of Liver Tumor Based on Magnetic Resonance Imaging and Clinical Data.

Background: Early-stage diagnosis and treatment can improve survival rates of liver cancer patients. Dynamic contrast-enhanced MRI provides the most comprehensive information for differential diagnosis of liver tumors. However, MRI diagnosis is affected by subjective experience, so deep learning may supply a new diagnostic strategy. We used convolutional neural networks (CNNs) to develop a deep learning system (DLS) to classify liver tumors based on enhanced MR images, unenhanced MR images, and clinical data including text and laboratory test results. Methods: Using data from 1,210 patients with liver tumors (N = 31,608 images), we trained CNNs to get seven-way classifiers, binary classifiers, and three-way malignancy-classifiers (Model A-Model G). Models were validated in an external independent extended cohort of 201 patients (N = 6,816 images). The area under receiver operating characteristic (ROC) curve (AUC) were compared across different models. We also compared the sensitivity and specificity of models with the performance of three experienced radiologists. Results: Deep learning achieves a performance on par with three experienced radiologists on classifying liver tumors in seven categories. Using only unenhanced images, CNN performs well in distinguishing malignant from benign liver tumors (AUC, 0.946; 95% CI 0.914-0.979 vs. 0.951; 0.919-0.982, P = 0.664). New CNN combining unenhanced images with clinical data greatly improved the performance of classifying malignancies as hepatocellular carcinoma (AUC, 0.985; 95% CI 0.960-1.000), metastatic tumors (0.998; 0.989-1.000), and other primary malignancies (0.963; 0.896-1.000), and the agreement with pathology was 91.9%.These models mined diagnostic information in unenhanced images and clinical data by deep-neural-network, which were different to previous methods that utilized enhanced images. The sensitivity and specificity of almost every category in these models reached the same high level compared to three experienced radiologists. Conclusion: Trained with data in various acquisition conditions, DLS that integrated these models could be used as an accurate and time-saving assisted-diagnostic strategy for liver tumors in clinical settings, even in the absence of contrast agents. DLS therefore has the potential to avoid contrast-related side effects and reduce economic costs associated with current standard MRI inspection practices for liver tumor patients.

Evolutionarily Conserved nodE, nodO, T1SS, and Hydrogenase System in Rhizobia of Astragalus membranaceus and Caragana intermedia.

Mesorhizobium species are the main microsymbionts associated with the medicinal or sand-fixation plants Astragalus membranaceus and Caragana intermedia (AC) in temperate regions of China, while all the Mesorhizobium strains isolated from each of these plants could nodulate both of them. However, Rhizobium yanglingense strain CCBAU01603 could nodulate AC plants and it's a high efficiency symbiotic and competitive strain with Caragana. Therefore, the common features shared by these symbiotic rhizobia in genera of Mesorhizobium and Rhizobium still remained undiscovered. In order to study the genomic background influencing the host preference of these AC symbiotic strains, the whole genomes of two (M. silamurunense CCBAU01550, M. silamurunense CCBAU45272) and five representative strains (M. septentrionale CCBAU01583, M. amorphae CCBAU01570, M. caraganae CCBAU01502, M. temperatum CCBAU01399, and R. yanglingense CCBAU01603) originally isolated from AC plants were sequenced, respectively. As results, type III secretion systems (T3SS) of AC rhizobia evolved in an irregular pattern, while an evolutionarily specific region including nodE, nodO, T1SS, and a hydrogenase system was detected to be conserved in all these AC rhizobia. Moreover, nodO was verified to be prevalently distributed in other AC rhizobia and was presumed as a factor affecting the nodule formation process. In conclusion, this research interpreted the multifactorial features of the AC rhizobia that may be associated with their host specificity at cross-nodulation group, including nodE, nodZ, T1SS as the possible main determinants; and nodO, hydrogenase system, and T3SS as factors regulating the bacteroid formation or nitrogen fixation efficiency.

Reverse saturable absorption and nonlinear refraction of ultrathin ZrS3 nanobelts.

The nonlinear optical (NLO) properties of a ZrS3 nanobelt were measured with a 6.5 ns pulse laser at 532 nm. Its optical response to the incident light exhibits good optical absorptive and refractive effects, with the nonlinear absorption coefficient ß = 4.42 × 10(-10) m W(-1) and the nonlinear refraction coefficient γ = 5.86 × 10(-17) m(2) W(-1) for the ZrS3 nanobelt in ethanol dispersions at an input energy of 34.25 µJ. In addition, the ß values and γ values have dependence on input energy. Results show that the ZrS3 nanobelts have an excellent reverse saturable absorption (RSA) performance in nanosecond pulses, demonstrating that ZrS3 nanobelts are an extraordinarily promising novel optical power limiting material. Meanwhile, compared to the pure ZrS3, graphene oxide (GO) and reduced graphene oxide (RGO), composites (ZrS3/GRO) exhibit an enhanced nonlinear absorption response at the same input energy.