Structural and mechanistic insights into the biosynthesis of CDP-archaeol in membranes

The divergence of archaea, bacteria and eukaryotes was a fundamental step in evolution. One marker of this event is a major difference in membrane lipid chemistry between these kingdoms. Whereas the membranes of bacteria and eukaryotes primarily consist of straight fatty acids ester-bonded to glycerol-3-phosphate, archaeal phospholipids consist of isoprenoid chains ether-bonded to glycerol-1-phosphate. Notably, the mechanisms underlying the biosynthesis of these lipids remain elusive. Here, we report the structure of the CDP-archaeol synthase (CarS) of Aeropyrum pernix (ApCarS) in the CTP- and Mg(2+)-bound state at a resolution of 2.4 Å. The enzyme comprises a transmembrane domain with five helices and cytoplasmic loops that together form a large charged cavity providing a binding site for CTP. Identification of the binding location of CTP and Mg(2+) enabled modeling of the specific lipophilic substrate-binding site, which was supported by site-directed mutagenesis, substrate-binding affinity analyses, and enzyme assays. We propose that archaeol binds within two hydrophobic membrane-embedded grooves formed by the flexible transmembrane helix 5 (TM5), together with TM1 and TM4. Collectively, structural comparisons and analyses, combined with functional studies, not only elucidated the mechanism governing the biosynthesis of phospholipids with ether-bonded isoprenoid chains by CTP transferase, but also provided insights into the evolution of this enzyme superfamily from archaea to bacteria and eukaryotes.Cell Research advance online publication 29 September 2017; doi:10.1038/cr.2017.122

The Evaluation Prediction System for Urban Advanced Manufacturing Development

With the rapid development of the economy, it is important to reasonably evaluate the development status of the regional manufacturing industry. Given this, this article expands the evaluation indicators of urban advanced manufacturing (UAM) from the perspective of the push–pull-mooring (PPM). Then, it uses a machine learning (ML) method to predict the evaluation results of other cities through a small amount of sample data. The results show that: (1) From the current development status of UAM in Guangdong Province (GD), cities in the Pearl River Delta region occupy a dominant position. However, cities in eastern, western, and mountainous regions have strong development potential and lead cities. Therefore, each region has cities with high levels of development and has a demonstrative role. (2) By comparison, it was found that the overall development level of UAM in GD is not significantly different from that of the Yangtze River Economic Belt. However, due to significant differences in their extreme values, the proportion of cities above the average in the overall population is relatively small. This indirectly proves that GD’s UAM not only has a phased nature, but also has a demonstrative role. (3) The prediction effect of the perceptron model is better than other methods. Although neural network models have better prediction performance than other machine learning models, they should not overly rely on complex network structure prediction data. By comparing the results, the reliability is verified. Finally, according to the life cycle theory, we propose a targeted development path for different UAM

Significance of serum sestrin2 as a biomarker of severity and functional outcome in acute intracerebral hemorrhage: a prospective observational longitudinal study

Abstract Background Sestrin2 is a highly conserved stress-inducible protein with neuroprotective properties. Herein, we investigated the prognostic significance of serum sestrin2 in human intracerebral hemorrhage (ICH). Methods In this prospective observational longitudinal study, we enrolled 126 patients with supratentorial ICH as cases together with 126 healthy individuals as controls. Severity indicators were National Institutes of Health Stroke Scale (NIHSS) and hematoma volume. Prognostic parameters were early neurologic deterioration (END) and post-stroke 6-month poor prognosis [modified Rankin Scale (mRS) scores of 3–6]. Multivariate analysis was performed to assess relations of serum sestrin2 levels to severity and prognosis. Results Patients had statistically significantly higher serum sestrin2 levels than controls. Serum sestrin2 levels of patients were independently correlated with NIHSS scores and hematoma volume, as well as were substantially elevated in order of mRS scores from 0 to 6. Serum sestrin2 was identified as an independent predictor of END and poor prognosis. Based on the receiver operating characteristic curve, serum sestrin2 had a similar predictive ability for END and poor prognosis, as compared to NIHSS scores and hematoma volume. Prediction models of END and poor prognosis, in which serum sestrin2, NIHSS scores and hematoma volume were integrated, were visually described via nomogram, were reliable and stable under calibration curve and were of clinical benefit using decision curve analysis. Also, prediction model of poor prognosis showed dramatically higher discriminatory efficiency than any of NIHSS scores, hematoma volume and serum sestrin2. Conclusion Serum sestrin2 levels, which are obviously increased following acute ICH, are independently related to illness severity and poor clinical outcomes, substantializing serum sestrin2 as a clinically valuable prognostic biomarker of ICH

Mining Vehicles Frequently Appearing Together from Massive Passing Records

Vehicles Frequently Appearing Together, or VFATs, can be clues in solving criminal cases. Traditional sequence mining approaches help identify VFATs from passing-through records collected at monitoring sites. However, huge traffic data streams hinder fast identification of VFATs. In this paper, we present a multi-threaded approach to fast identification of VFATs based on multi-core processors, called Frequent Sequential Mining based on Multi-Cores (FSMMC). It parallels the execution of tasks, partitions large volumes of data, and obtains VFATs by merging local candidates discovered in different threads running on different processor cores. Through local parallel reduction, FSMMC eliminates the repetitive patterns and reduces computational effort. Moreover, it achieves workload balance by the dynamic distribution of tasks to a pool of threads where the thread that finishes first joins another running thread. Both theoretical analysis and case studies show that FSMMC takes full advantage of multi-core computing platforms and has higher speed-up when searching VFATs among massive passing through records, compared with other approaches without multithreading

Automatic segmentation of the central epithelium imaged with three optical coherence tomography devices

The aim of this study was to investigate the feasibility of automatic segmentation of the central corneal thickness (CCT) and epithelial thickness (ET) of the human cornea obtained with different spectral domain optical coherence tomography (OCT) instruments. Ten left eyes from 10 healthy subjects with a mean age of 22.5 ± 1.5 years participated in this study. A custom-built ultra-high resolution OCT (UHR-OCT) with a 3-μm axial resolution, ultralong scan depth OCT (UL-OCT) with a 7.5-μm resolution, and commercial RTVue OCT with a 5-μm resolution were used to image the cornea. An automated segmentation algorithm was developed to process the OCT images and yield the CCT and ET. The measurement was verified by a manual measurement. The automatic algorithm successfully processed the central thickness of the cornea and corneal epithelium for all images. The average CCT obtained by the automatic segmentation algorithm was 528.1 ± 22.4 μm, 526.1 ± 23.4 μm, and 525.2 ± 23.7 μm for UHR-OCT, UL-OCT, and RTVue, respectively. The average ET was 53.2 ± 2.0 μm, 54.1 ± 3.0 μm, and 52.1 ± 2.5 μm for UHR-OCT, UL-OCT, and RTVue, respectively. These measurements were in agreement with those of the manual method for the CCT (all r>0.997, P0.71, P<0.05). The algorithm seemed to be feasible for automatically segmenting the CCT and ET in OCT images using these tested OCT devices. The segmented results were equivalent to that obtained with the manual method

Application of Exogenous Melatonin Improves Tomato Fruit Quality by Promoting the Accumulation of Primary and Secondary Metabolites

Melatonin plays key roles in improving fruit quality and yield by regulating various aspects of plant growth. However, the effects of how melatonin regulates primary and secondary metabolites during fruit growth and development are poorly understood. In this study, the surfaces of tomato fruit were sprayed with different concentrations of melatonin (0, 50, and 100 µmol·L−1) on the 20th day after anthesis; we used high-performance liquid chromatography (HPLC) and liquid chromatography/mass spectrometry (LC/MS) to determine the changes in primary and secondary metabolite contents during fruit development and measured the activity of sucrose metabolizing enzymes during fruit development. Our results showed that 100 µmol·L−1 melatonin significantly promoted the accumulation of soluble sugar in tomato fruit by increasing the activities of sucrose synthase (SS), sucrose phosphate synthase (SPS), and acid convertase (AI). The application of 100 µmol·L−1 melatonin also increased the contents of ten amino acids in tomato fruit as well as decreased the contents of organic acids. In addition, 100 µmol·L−1 melatonin application also increased the accumulation of some secondary metabolites, such as six phenolic acids, three flavonoids, and volatile substances (including alcohols, aldehydes, and ketones). In conclusion, melatonin application improves the internal nutritional and flavor quality of tomato fruit by regulating the accumulation of primary and secondary metabolites during tomato fruit ripening. In the future, we need to further understand the molecular mechanism of melatonin in tomato fruit to lay a solid foundation for quality improvement breeding

A Comparative Study on the Nutrients, Mineral Elements, and Antioxidant Compounds in Different Types of Cruciferous Vegetables

Studies on the diversity within and among cabbage (Brassica oleracea L. var. capitata L.), cauliflower (Brassica oleracea var. botrytis), and Chinese cabbage (Brassica rapa L. ssp. pekinensis) variants are essential for the development of healthy diets. However, most studies on them have been limited to a single species, with little integrated analysis between them. In this study, the diversity within and among these species and varieties is assessed by determining the contents of 15 major characteristic nutrients, antioxidants, and minerals in 12 varieties of cabbage, 9 varieties of cauliflower, and 12 varieties of Chinese cabbage cultivated under the same conditions. The results show that there are significant differences in the compositional distributions of cabbage, cauliflower, and Chinese cabbage. Cabbage has the highest contents of soluble sugars (27.73 mg·kg−1 FW), flavonoids (5.90 mg·g−1 FW), and Fe (46.90 mg·kg−1 DW). Cauliflower is an ideal source of soluble protein (603.04 mg·kg−1 FW), polyphenols (1.53 mg·g−1 FW), glucosinolates (25.27 μmol·g−1 FW), and Cu (4.25 mg·kg−1 DW). Chinese cabbage is rich in vitamin C (0.45 mg·g−1 FW) and minerals (K, Ca, Mg, P, Mn, and Zn, at 9206.67 mg·kg−1 DW, 3297.00 mg·kg−1 DW, 3322.79 mg·kg−1 DW, 5614.78 mg·kg−1 DW, 15.36 mg·kg−1 DW, and 21.87 mg·kg−1 DW, respectively). There is a correlation between the quality, antioxidant properties, and minerals of the three species. In principal component analysis, a wide distribution of cabbage varieties and a high degree of overlap with the confidence ellipse of cauliflower are observed, indicating that certain cabbage varieties share compositional characteristics with cauliflower. These findings provide a reference for selecting varieties with higher nutritional value and antioxidant properties, as well as breeding new varieties