大肠杆菌突变株高密度生长的多因素分析

[背景]pBHR68是表达聚-3-羟基丁酸酯(Poly-3-Hydroxybutyrate,PHB)合成基因簇的高拷贝质粒,大肠杆菌K-12突变菌株S17-3在携带该质粒时生长密度高,耐低pH且在低pH条件下生长时高产可拉酸(Colanic Acid,CA).[目的]系统探究与菌种(大肠杆菌S17-3)及质粒(pBHR...     

Single-cell landscape of the ecosystem in early-relapse hepatocellular carcinoma

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ITMSQ: A software tool for N‐ and C‐terminal fragment ion pairs based isobaric tandem mass spectrometry quantification

Tandem MS (MS2) quantification using the series of N‐ and C‐terminal fragment ion pairs generated from isobaric‐labelled peptides was recently considered an accurate strategy in quantitative proteomics. However, the presence of multiplexed terminal fragment ion in MS2 spectra may reduce the efficiency of peptide identification, resulting in lower identification scores or even incorrect assignments. To address this issue, we developed a quantitative software tool, denoted isobaric tandem MS quantification (ITMSQ), to improve N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantification. A spectrum splitting module was designed to separate the MS2 spectra from different samples, increasing the accuracy of both identification and quantification. ITMSQ offers a convenient interface through which parameters can be changed along with the labelling method, and the result files and all of the intermediate files can be exported. We performed an analysis of in vivo terminal amino acid labelling labelled HeLa samples and found that the numbers of quantified proteins and peptides increased by 13.64 and 27.52% after spectrum splitting, respectively. In conclusion, ITMSQ provides an accurate and reliable quantitative solutionfor N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantitative methods.     

The Volume Ratio of Ground Glass Opacity in Early Lung CT Predicts Mortality in Acute Paraquat Poisoning

Background

Pulmonary injury is the main cause of death in acute paraquat (PQ) poisoning. However, whether quantitative lung computed tomography (CT) can be useful in predicting the outcome of PQ poisoning remains unknown. We aimed to identify early findings of quantitative lung CT as predictors of outcome in acute PQ poisoning.

Methods

Lung CT scanning (64-slide) and quantitative CT lesions were prospectively measured for patients after PQ intoxication within 5 days. The study outcome was mortality during 90 days follow-up. Survival curves were derived by the Kaplan-Meier method, and mortality risk factors were analyzed by the forward stepwise Cox regression analysis.

Results

Of 97 patients, 41 (42.3%) died. Among the eight different types of lung CT findings which appeared in the first 5-day of PQ intoxication, four ones discriminated between survivors and non-survivors including ground glass opacity (GGO), consolidation, pneumomediastinum and “no obvious lesion”. With a cutoff value of 10.8%, sensitivity of 85.4% and specificity of 89.3%, GGO volume ratio is better than adopted outcome indicators in predicting mortality, such as estimated amount of PQ ingestion, plasma or urine PQ concentration, acute physiology and chronic health evaluation (APACHE) II and sequential organ failure assessment (SOFA) scores. GGO volume ratios above 10.8% were associated with increased mortality (hazard ratio, 5.82; 95% confidence interval, 4.77-7.09; P < 0.001).

Conclusions

The volume ratio of GGO exceeding 10.8% is a novel, reliable and independent predictors of outcome in acute PQ poisoning.     

Adaptive Tensor-Based Principal Component Analysis for Low-Dose CT Image Denoising

Computed tomography (CT) has a revolutionized diagnostic radiology but involves large radiation doses that directly impact image quality. In this paper, we propose adaptive tensor-based principal component analysis (AT-PCA) algorithm for low-dose CT image denoising. Pixels in the image are presented by their nearby neighbors, and are modeled as a patch. Adaptive searching windows are calculated to find similar patches as training groups for further processing. Tensor-based PCA is used to obtain transformation matrices, and coefficients are sequentially shrunk by the linear minimum mean square error. Reconstructed patches are obtained, and a denoised image is finally achieved by aggregating all of these patches. The experimental results of the standard test image show that the best results are obtained with two denoising rounds according to six quantitative measures. For the experiment on the clinical images, the proposed AT-PCA method can suppress the noise, enhance the edge, and improve the image quality more effectively than NLM and KSVD denoising methods.     

A new rhodamine‐based fluorescent chemodosimeter for mercuric ions in water media

A new rhodamine–ethylenediamine–nitrothiourea conjugate (RT) was synthesized and its sensing property as a fluorescent chemodosimeter toward metal ions was explored in water media. Analytical results from absorption and fluorescence spectra revealed that the addition of Hg²⁺ ions to the aqueous solution of the chemodosimeter RT caused a distinct fluorescence OFF–ON response with a remarkable visual color change from colorless to pink; however, no clear spectral and color changes were observed from other metal ions including: Zn²⁺, Cu²⁺, Cd²⁺, Pb²⁺, Ag⁺, Fe²⁺, Cr³⁺, Co³⁺, Ni²⁺, Ca²⁺, Mg²⁺, K⁺ and Na⁺. The sensing results and the molecular structure suggested that a Hg²⁺‐induced a desulfurization reaction and cyclic guanylation of the thiourea moiety followed by ring‐opening of the rhodamine spirolactam in RT are responsible for a distinct fluorescence turn‐on signal, indicating that RT is a remarkably sensitive and selective chemodosimeter for Hg²⁺ ions in aqueous solution. Hg²⁺ within a concentration range from 0.1 to 25 μM can be determined using RT as a chemodosimeter and a detection limit of 0.04 μM is achieved. Copyright © 2014 John Wiley & Sons, Ltd.     

Use of random forest in FTIR analysis of LDL cholesterol and tri‐glycerides for hyperlipidemia

A quantitative determination method for the diagnosis of hyperlipidemia was developed using Fourier transform infrared (FTIR) spectroscopy. Random forest (RF) was demonstrated as a potential multivariate algorithm for the FTIR analysis of low‐density lipoprotein cholesterol (LDL‐C) and tri‐glycerides (TG) in human serum samples. The informative wavebands for LDL‐C and TG were selected based on the Gini importance. The selected wavebands were mainly within the fingerprint region. The RF modeling results were better than those derived using PLS in validation process, because the chance for over‐fitting was possibly eliminated in RF algorithm. ARF also demonstrated favorable results in the test process. The prospective model exhibited a higher than 90% true prediction in negative/positive properties for male and female samples. These clinical statistical results indicated the optimization of RF algorithm performed accurately in the FTIR determination of LDL‐C and TG. RF is evaluated as a promising tool for diagnosing and controlling hyperlipidemia in populations. The parameter optimization methodology is useful in the improving model accuracy using FTIR spectroscopic technology. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:1693–1702, 2015