DNA synthesis and nuclear division during formation of infection structures by bean rust uredospore germlings

Plectonema boryanum can grow in the dark with ribose, sucrose, mannitol, maltose, glucose, or fructose. Cell doubling times with 10 mM substrate are the following: 5 days with ribose, 6 days with sucrose or mannitol, 10 days with maltose, 12 days with glucose, and 13 days with fructose; with ribose plus 0.1% casamino acids it is 2.5 days. Dark-grown cells appear morphologically similar to light-grown cells. Cells grown in the dark for several years remain pigmented and resume photoautotrophic growth when placed in the light. Dim light (85 lux) increases the growth rate with ribose and with ribose plus casamino acids to nearlytwice that of the dark rate. In moderate light, growth takes place with ribose even in the presence of 1x10^-5 M DCMU.     

The RAGE/multiligand axis: a new actor in tumor biology

The receptor for advanced glycation end-products (RAGE) is a multiligand binding and single-pass transmembrane protein which actively participates in several chronic inflammation-related diseases. RAGE, in addition to AGEs, has a wide repertoire of ligands, including several damage-associated molecular pattern molecules or alarmins such as HMGB1 and members of the S100 family proteins.Over the last years, a large and compelling body of evidence has revealed the active participation of the RAGE axis in tumor biology based on its active involvement in several crucial mechanisms involved in tumor growth, immune evasion, dissemination, as well as by sculpturing of the tumor microenvironment as a tumor-supportive niche. In the present review, we will detail the consequences of the RAGE axis activation to fuel essential mechanisms to guarantee tumor growth and spreading.     

Degradation of aromatic hydrocarbons by white-rot fungi in a historically contaminated soil

Phanerochaete chrysosporium NRRL 6361 and Pleurotus pulmonarius CBS 664.97 were tested for their ability to grow under nonsterile conditions and to degrade various aromatic hydrocarbons in an aged contaminated soil that also contained high concentrations of heavy metals. After 24 days fungal incubation, carbon-CO2 liberated, an indicator of microbial activity, reached a plateau. At the end of the incubation time (30 days), fungal colonization was clearly visible and was confirmed by ergosterol and cell organic carbon determinations. In spite of unfavorable pH (around 7.4) and the presence of heavy metals, both fungi produced Mn-peroxidase activity. In contrast, laccase and aryl-alcohol oxidase were detected only in the soil treated with P. pulmonarius CBS 664.97 and lignin-peroxidase in that with P. chrysosporium NRRL 6361. No lignin-modifying enzyme activities were present in non-inoculated soil incubated for 30 days (control microcosm). Regardless of the fungus employed, a total removal of naphtalene, tetrachlorobenzene, and dichloroaniline isomers, diphenylether and N-phenyl-1-naphtalenamine, was observed. Significant release of chloride ions was also observed in fungal-treated soil, in comparison with that recorded in the control microcosm. Both fungi led to a significant decrease in soil toxicity, as assessed using two different soil contact assays, including the Lepidium sativum L. germination test and the Collembola mortality test.     

A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer

Patients with hormone receptor(HR)-positive tumors breast cancer usually experience a relatively low pathological complete response(p CR) to neoadjuvant chemotherapy(NAC). Here, we derived a 10-micro RNA risk score(10-mi RNA RS)-based model with better performance in the prediction of p CR and validated its relation with the disease-free survival(DFS) in 755 HRpositive breast cancer patients(273, 265, and 217 in the training, internal, and external validation sets, respectively). This model,pres...     

Microbial fuel cells meet with external resistance

The influence of external load on the composition of the anodic biofilm microbial community and biomass yield was investigated in a microbial fuel cell fed with glucose and domestic wastewater was used as source of electrogens. Denaturing gradient gel electrophoresis (DGGE) of polymerase chain reaction (PCR) amplified 16S rRNA gene fragments revealed distinct differences in anodic bacterial communities formed at the anode of each MFC operated under a different external load. These results implied that in an MFC, electrogenic bacteria were enriched under higher current densities, i.e., low external load, and were able to sustain better current and effluent quality. The influence of the external resistance applied to the MFCs during formation of the bacterial communities from sewage wastewater was shown to have no significant effect on power performance of the MFCs nor to have a significant influence on their anodic activity with both glucose and brewery wastewater as fuel. As expected, current generation, COD removal and the biomass yield were all directly influenced by the external load. Significantly, when operated under lower external load, the biomass yield in the MFC was less than that in conventional anaerobic digestion (i.e., control).     

A Design Pattern for Decentralised Decision Making

The engineering of large-scale decentralised systems requires sound methodologies to guarantee the attainment of the desired macroscopic system-level behaviour given the microscopic individual-level implementation. While a general-purpose methodology is currently out of reach, specific solutions can be given to broad classes of problems by means of well-conceived design patterns. We propose a design pattern for collective decision making grounded on experimental/theoretical studies of the nest-site selection behaviour observed in honeybee swarms (Apis mellifera). The way in which honeybee swarms arrive at consensus is fairly well-understood at the macroscopic level. We provide formal guidelines for the microscopic implementation of collective decisions to quantitatively match the macroscopic predictions. We discuss implementation strategies based on both homogeneous and heterogeneous multiagent systems, and we provide means to deal with spatial and topological factors that have a bearing on the micro-macro link. Finally, we exploit the design pattern in two case studies that showcase the viability of the approach. Besides engineering, such a design pattern can prove useful for a deeper understanding of decision making in natural systems thanks to the inclusion of individual heterogeneities and spatial factors, which are often disregarded in theoretical modelling.