Detecting spatial chirp signals by Luneburg lens based transformation medium.

Gradient refractive index (GRIN) lens-based chirp signal chirpiness detection usually relies on the fractional Fourier transform (FRFT) functionality of a quadratic GRIN lens and is limited by paraxial conditions. In this paper, a non-FRFT mechanism-based chirpiness detection GRIN lens is proposed that converts the Luneburg lens' focus capacity of input plane waves to the designed lens' focusing of input chirp waves using transformation optics, and the source chirpiness can be obtained by sweeping the illumination wavelength rather than locating the focusing pulse, consequently greatly increasing the upper limit of the chirpiness detection range. The feasibility and robustness of the method are verified through numerical simulations.

A New Laccase of Lac 2 from the White Rot Fungus Cerrena unicolor 6884 and Lac 2-Mediated Degradation of Aflatoxin B1.

Aflatoxin B1 (AFB1) is a known toxic human carcinogen and can be detoxified by laccases, which are multicopper oxidases that convert several environmental pollutants and toxins. In this study, a new laccase that could catalyze AFB1 degradation was purified and identified from the white-rot fungus Cerrena unicolor 6884. The laccase was purified using (NH4)2SO4 precipitation and anion exchange chromatography, and then identified as Lac 2 through zymogram and UHPLC-MS/MS based on the Illumina transcriptome analysis of C. unicolor 6884. Six putative laccase protein sequences were obtained via functional annotation. The lac 2 cDNA encoding a full-length protein of 512 amino acids was cloned and sequenced to expand the fungus laccase gene library for AFB1 detoxification. AFB1 degradation by Lac 2 was conducted in vitro at pH 7.0 and 45 °C for 24 h. The half-life of AFB1 degradation catalyzed by Lac 2 was 5.16 h. Acetosyringone (AS), Syrinagaldehyde (SA) and [2,2' -azino-bis-(3-ethylbenzothiazoline-6-sulfonic acid)] (ABTS) at 1 mM concentration seemed to be similar mediators for strongly enhancing AFB1 degradation by Lac 2. The product of AFB1 degradation catalyzed by Lac 2 was traced and identified to be Aflatoxin Q1 (AFQ1) based on mass spectrometry data. These findings are promising for a possible application of Lac 2 as a new aflatoxin oxidase in degrading AFB1 present in food and feeds.

Variations in Oral Microbiota Composition Are Associated With a Risk of Throat Cancer.

In this study, a next-generation sequencing strategy on 16S ribosomal RNA (16S rRNA) gene was employed to analyze 70 oral samples from 32 patients with throat cancer, nine patients with vocal cord polyp, and 29 healthy individuals (normal controls). Using this strategy, we demonstrated, for the first time, that the salivary microbiota of cancer patients were significantly different from those of patients with a polyp and healthy individuals. We observed that the beta diversity of the cancer group was divergent from both the normal and polyp groups, while alpha-diversity indices such as the Chao1 estimator (P = 8.1e-05), Simpson (P = 0.0045), and Shannon (P = 0.0071) were significantly reduced in cancer patients compared with patients containing a polyp and normal healthy individuals. Linear discriminant analysis (LDA) and Kruskal-Wallis test analyses and real-time quantitative polymerase chain reaction (qPCR) verification test revealed that the genera Aggregatibacter, Pseudomonas, Bacteroides, and Ruminiclostridium were significantly enriched in the throat cancer group compared with the vocal cord polyp and normal control groups (score value >2). Finally, diagnostic models based on putatively important constituent bacteria were constructed with 87.5% accuracy [area under the curve (AUC) = 0.875, 95% confidence interval (CI): 0.695-1]. In summary, in this study we characterized, for the first time, the oral microbiota of throat cancer patients without smoking history. We speculate that these results will help in the pathogenic mechanism and early diagnosis of throat cancer.

Elevational patterns of the percentages of plant genera with tropical and temperate affinities in Nepal.

BACKGROUND: Geographical patterns of species diversity are one of the key topics in biogeography and ecology. The effects of biogeographical affinities on the elevational patterns of species diversity have attracted much attention recently, but the factors driving elevational patterns of the percentages of plants with tropical and temperate biogeographical affinities have not been adequately explored. METHODS: We first used univariate least squares regressions to evaluate the effects of each predictor on the elevational patterns of the percentages of plant genera with tropical and temperate affinities in Nepal. Then, the lowest corrected Akaike information criterion value was used to find the best-fit models for all possible combinations of the aforementioned predictors. We also conducted partial regression analysis to investigate the relative influences of each predictor in the best-fit model of the percentages of plant genera with tropical and temperate affinities. RESULTS: With the increase of elevation, the percentage of plant genera with tropical affinity significantly decreased, while that of plant genera with temperate affinity increased. The strongest predictor of the percentages of plant genera with tropical affinity in the examined area was the minimum temperature of the coldest month. For the elevational patterns of the percentages of plant genera with temperate affinity, the strongest predictor was the maximum temperature of the warmest month. Compared with mid-domain effects (MDE), climatic factors explained much more of the elevational variation of the percentages of plant genera with tropical and temperate affinities. DISCUSSION: The elevational patterns of the percentages of plant genera with tropical affinities and the factors driving them supported the revision of the freezing-tolerance hypothesis. That is, freezing may filter out plant genera with tropical affinity, resulting in the decrease of their percentages, with winter coldness playing a predominant role. Winter coldness may not only exert filtering effects on plant genera with tropical affinity, but may also regulate the interactions between plant genera with tropical and temperate affinities. The elevational patterns of tropical and temperate plant diversities, and those of their percentages, might be controlled by different factors or mechanisms. Freezing-tolerance and the interactions between plant genera with tropical and temperate affinities regulated by climatic factors played stronger roles than MDE in shaping the elevational patterns of the percentages of plant genera with tropical and temperate affinities in Nepal.

Investigation of glucose fluctuations by approaches of multi-scale analysis.

Glucose variability provides detailed information on glucose control and fluctuation. The aim of this study is to investigate the glucose variability by multi-scale analysis approach on 72-h glucose series captured by continuous glucose monitoring system (CGMS), gaining insights into the variability and complexity of the glucose time series data. Ninety-eight type 2 DM patients participated in this study, and 72-h glucose series from each subject were recorded by CGMS. Subjects were divided into two subgroups according to the mean amplitude of glycemic excursions (MAGE) value threshold at 3.9 based on Chinese standard. In this study, we applied two types of multiple scales analysis methods on glucose time series: ensemble empirical mode decomposition (EEMD) and refined composite multi-scale entropy (RCMSE). With EEMD, glucose series was decomposed into several intrinsic mode function (IMF), and glucose variability was examined on multiple time scales with periods ranging from 0.5 to 12 h. With RCMSE, complexity of the structure of glucose series was quantified at each time scale ranging from 5 to 30 min. Subgroup with higher MAGE value (>3.9) presented higher glycemic baseline and variability. There were significant differences in glycemic variability on IMFs3-5 between subgroups with MAGE>3.9 and MAGE < = 3.9 (p<0.001), but no significant differences in variability on IMFs1-2. The complexity of glucose series quantified by RCMSE showed statistically difference on each time scale from 5 to 30 min between subgroups (p<0.05). Glucose series from subjects with higher MAGE value represented higher variability but lower complexity on multiple time scales. Compared with traditional matrices measuring the glucose variability, approaches of EEMD and RCMSE can quantify the dynamic glycemic fluctuation in multiple time scales and provide us more detailed information on glycemic variability and complexity.

[Investigation of the glucose dynamics with an approach of refined composite multi-scale entropy analysis].

The study on complexity of glucose fluctuation not only helps us understand the regulation of the glucose homeostasis system but also brings us a new insight of the research methodology on glucose regulation. In the experiments, we analyzed the complexity of the temporal structure of the 72 hours continuous glucose time series from a group of 93 subjects with type Ⅱ diabetes mellitus using the multi-scale entropy method. We adapted the most recently improved refined composite multi-scale entropy(RCMSE) algorithm which could overcome the shortcomings on the 72 hours short time series analysis. We then quantified and compared the complexity of continuous glucose time series between groups with type Ⅱ diabetes mellitus with different mean absolute glycemic excursion(MAGE) and glycated hemoglobin(Hb A1c). The results implied that the complexity of glucose time series decreased on lower MAGE group compared to high MAGE group, and the entropy on scale 1 to 6 which corresponded to 5 to 30 min had significant differences between these two groups; the complexity of glucose time series decreased with the increasing Hb A1 c level but the entropy had no statistical difference among groups at different scales. Therefore, RCMSE provided us with a new prospect to analyze the glucose time series and it was proved that less complexity of glucose dynamics could indicate the impaired gluco-regulation function from the MAGE point of view or Hb A1 c for patients, and the glucose complexity had the potential to become a new biomarker to reflect the fluctuation of the glucose time series.