Ionizing Radiation Changes the Electronic Properties of Melanin and Enhances the Growth of Melanized Fungi

BACKGROUND: Melanin pigments are ubiquitous in nature. Melanized microorganisms are often the dominating species in certain extreme environments, such as soils contaminated with radionuclides, suggesting that the presence of melanin is beneficial in their life cycle. We hypothesized that ionizing radiation could change the electronic properties of melanin and might enhance the growth of melanized microorganisms. METHODOLOGY/PRINCIPAL FINDINGS: Ionizing irradiation changed the electron spin resonance (ESR) signal of melanin, consistent with changes in electronic structure. Irradiated melanin manifested a 4-fold increase in its capacity to reduce NADH relative to non-irradiated melanin. HPLC analysis of melanin from fungi grown on different substrates revealed chemical complexity, dependence of melanin composition on the growth substrate and possible influence of melanin composition on its interaction with ionizing radiation. XTT/MTT assays showed increased metabolic activity of melanized C. neoformans cells relative to non-melanized cells, and exposure to ionizing radiation enhanced the electron-transfer properties of melanin in melanized cells. Melanized Wangiella dermatitidis and Cryptococcus neoformans cells exposed to ionizing radiation approximately 500 times higher than background grew significantly faster as indicated by higher CFUs, more dry weight biomass and 3-fold greater incorporation of (14)C-acetate than non-irradiated melanized cells or irradiated albino mutants. In addition, radiation enhanced the growth of melanized Cladosporium sphaerospermum cells under limited nutrients conditions. CONCLUSIONS/SIGNIFICANCE: Exposure of melanin to ionizing radiation, and possibly other forms of electromagnetic radiation, changes its electronic properties. Melanized fungal cells manifested increased growth relative to non-melanized cells after exposure to ionizing radiation, raising intriguing questions about a potential role for melanin in energy capture and utilization

Genome Sequencing of the Sweetpotato Whitefly \u3cem\u3eBemisia tabaci\u3c/em\u3e MED/Q

The sweetpotato whitefly Bemisia tabaci is a highly destructive agricultural and ornamental crop pest. It damages host plants through both phloem feeding and vectoring plant pathogens. Introductions of B. tabaci are difficult to quarantine and eradicate because of its high reproductive rates, broad host plant range, and insecticide resistance. A total of 791 Gb of raw DNA sequence from whole genome shotgun sequencing, and 13 BAC pooling libraries were generated by Illumina sequencing using different combinations of mate-pair and pair-end libraries. Assembly gave a final genome with a scaffold N50 of 437 kb, and a total length of 658 Mb. Annotation of repetitive elements and coding regions resulted in 265.0 Mb TEs (40.3%) and 20 786 protein-coding genes with putative gene family expansions, respectively. Phylogenetic analysis based on orthologs across 14 arthropod taxa suggested that MED/Q is clustered into a hemipteran clade containing A. pisum and is a sister lineage to a clade containing both R. prolixus and N. lugens. Genome completeness, as estimated using the CEGMA and Benchmarking Universal Single-Copy Orthologs pipelines, reached 96% and 79%. These MED/Q genomic resources lay a foundation for future \u27pan-genomic\u27 comparisons of invasive vs. noninvasive, invasive vs. invasive, and native vs. exotic Bemisia, which, in return, will open up new avenues of investigation into whitefly biology, evolution, and management

A heterozygous moth genome provides insights into herbivory and detoxification

How an insect evolves to become a successful herbivore is of profound biological and practical importance. Herbivores are often adapted to feed on a specific group of evolutionarily and biochemically related host plants1, but the genetic and molecular bases for adaptation to plant defense compounds remain poorly understood2. We report the first whole-genome sequence of a basal lepidopteran species, Plutella xylostella, which contains 18,071 protein-coding and 1,412 unique genes with an expansion of gene families associated with perception and the detoxification of plant defense compounds. A recent expansion of retrotransposons near detoxification-related genes and a wider system used in the metabolism of plant defense compounds are shown to also be involved in the development of insecticide resistance. This work shows the genetic and molecular bases for the evolutionary success of this worldwide herbivore and offers wider insights into insect adaptation to plant feeding, as well as opening avenues for more sustainable pest management.Minsheng You … Simon W Baxter … et al

A Collision Avoidance Method for Intelligent Ship Based on the Improved Bacterial Foraging Optimization Algorithm

The bacterial foraging optimization algorithm (BFOA) is an intelligent population optimization algorithm widely used in collision avoidance problems; however, the BFOA is inappropriate for the intelligent ship collision avoidance planning with high safety requirements because BFOA converges slowly, optimizes inaccurately, and has low stability. To fix the above shortcomings of BFOA, an autonomous collision avoidance algorithm based on the improved bacterial foraging optimization algorithm (IBFOA) is demonstrated in this paper. An adaptive diminishing fractal dimension chemotactic step length is designed to replace the fixed step length to achieve the adaptive step length adjustment, an optimal swimming search method is proposed to solve the invalid searching and repeated searching problems of the traditional BFOA, and the adaptive migration probability is developed to take the place of the fixed migration probability to prevent elite individuals from being lost in BOFA. The simulation of benchmark tests shows that the IBFOA has a better convergence speed, optimized accuracy, and higher stability; according to a collision avoidance simulation of intelligent ships which applies the IBFOA, it can realize the autonomous collision avoidance of intelligent ships in dynamic obstacles environment is quick and safe. This research can also be used for intelligent collision avoidance of automatic driving ships

Study on an Implementation Scheme of Synergistic Emission Reduction of CO2 and Air Pollutants in China’s Steel Industry

China’s steel industry is an energy-intensive sector. Synergistic reduction of emissions of CO2 and air pollutants (SO2, NOx, and PM2.5) in the steel industry has an important practical significance for climate change and air pollution control. According to the CO2 emission reduction intensity targets (CERO) and air pollutant emission targets (PERO) for 2020 and 2030, 28 types of energy-saving and emission reduction technologies (20 types of carbon reduction technology and eight types of air pollution end-of-pipe technology) were selected for examination, and a two-stage dynamic optimization model with collaborative implementation of PERO and CERO was built to assess the near future (2015–2020) and long-term (2020–2030) implementation plans for synergistic emissions reduction of CO2 and air pollutants. The results show that in the near future, the implementation of PERO will have a greater synergistic effect on CO2 emission reduction. CO2 emission reduction under PERO in 2020 will be 97 million tons (Mt) higher than that of CERO, an increase of nearly 26%. However, the effects of implementing CERO are better in the long run. Under CERO, the emission reductions of SO2, NOx, and PM2.5 in 2030 are 2.44 Mt, 1.47 Mt, and 0.86 Mt, respectively, and 7%, 4%, and 5% higher than the implementation of PERO. As far as marginal abatement cost is concerned, in the near future, the marginal abatement costs of CO2 and air pollutant equivalents are 1.06 yuan/kgCO2 and 133 yuan/kg pollution equivalent (pe) under PERO, which are 23% and 11% lower than that of CERO, while in the long run, the marginal abatement costs of CO2 and pollutant equivalents under CERO are 0.025 yuan/kgCO2 and 2.73 yuan/kgpe, about 96% and 95% lower than that of PERO

Driving Factors and Growth Potential of Provincial Carbon Productivity in China

Climate change has become a global concern, and the development of a green economy has attracted wide attention. Understanding the driving factors and growth potential of provincial-level carbon productivity is crucial for China’s green economic development in the new normal phase. In this study, the logarithmic mean Divisia index (LMDI) is adopted to systematically investigate the driving factors of provincial carbon productivity and explore the growth potential of provinces’ carbon productivity based on the clustering analysis. The results show that: (1) China’s provincial carbon productivity presents an increasing trend in 2001–2017, but the differences in carbon productivity among provinces are widening. (2) Economic activity and industrial structure are key to push up regional carbon productivity in China, while energy intensity is the main factor pulling it down. (3) The potential for carbon productivity improvement varies greatly among provinces in the four groups. Specifically, in groups 1 and 2, the developed provinces have little potential for improving carbon productivity, while the developing provinces in group 4 are just the opposite. These findings can enlighten policymakers that the development of a green economy should focus on optimizing and upgrading industrial structure and reducing energy intensity, and provincial heterogeneity must be considered when formulating green economic development policies

Novel Bi-Functional 14-mer Peptides with Both Ovarian Carcinoma Cells Targeting and Magnetic Fe3O4 Nanoparticles Affinity

Fe3O4 magnetic nanoparticles (Fe3O4-MNPs) have attracted much interest for their potential medical applications due to their desirable magnetic properties. However, their potential cytotoxicity, high RES clearance in circulation, and nonspecific distribution in tissue might be the main obstacles in practice. In the present study, a novel bi-functional 14-mer peptide with both ovarian carcinoma cells targeting and magnetic Fe3O4 nanoparticles affinity was designed and synthesized, and then a facile and effective modification method was developed to bestow the Fe3O4-MNPs with tumor-targeting capability via modification, using the bi-functional peptides. First, on the basis of a tumor-targeting 7-mer peptide QQTNWSL (Q-L) and another Fe3O4-MNPs-targeting 7-mer peptide TVNFKLY (T-Y)—screened by phage-displayed peptide libraries—two bi-functional 14-mer peptides sequenced as LSWNTQQ-YLKFNVT (abbreviated as LQ-YT) and QQTNWSL-YLKFNVT (QL-YT) were synthesized through combining the Q-L peptide and T-Y peptide in predetermined configurations. Their specificity for bonding with A2780 tumor cells and affinity for Fe3O4-MNPs were verified. Then the bi-functional 14-mer peptides were applied to modify the Fe3O4-MNPs. Results showed that both bi-functional 14-mer peptides could be conjugated to the Fe3O4-MNPs surface with high affinity. Immunofluorescence and Prussian blue staining assays indicated that the LQ-YT-modified Fe3O4-MNPs could specifically bond to A2780 tumor cells. In addition to our findings suggesting that more β-turns and random coils are conducive to increasing polypeptide surface area for binding and exposing the target group and bonding sites on LQ-YT to external targets, we demonstrated that the bi-functional 14-mer peptide has affinity for Fe3O4-MNPs, and that Fe3O4-MNPs, which was modified with a 14-mer peptide, could be bestowed with a targeting affinity for ovarian carcinoma cells