Conductance Ratios and Cellular Identity

Recent experimental evidence suggests that coordinated expression of ion channels plays a role in constraining neuronal electrical activity. In particular, each neuronal cell type of the crustacean stomatogastric ganglion exhibits a unique set of positive linear correlations between ionic membrane conductances. These data suggest a causal relationship between expressed conductance correlations and features of cellular identity, namely electrical activity type. To test this idea, we used an existing database of conductance-based model neurons. We partitioned this database based on various measures of intrinsic activity, to approximate distinctions between biological cell types. We then tested individual conductance pairs for linear dependence to identify correlations. Contrary to experimental evidence, in which all conductance correlations are positive, 32% of correlations seen in this database were negative relationships. In addition, 80% of correlations seen here involved at least one calcium conductance, which have been difficult to measure experimentally. Similar to experimental results, each activity type investigated had a unique combination of correlated conductances. Finally, we found that populations of models that conform to a specific conductance correlation have a higher likelihood of exhibiting a particular feature of electrical activity. We conclude that regulating conductance ratios can support proper electrical activity of a wide range of cell types, particularly when the identity of the cell is well-defined by one or two features of its activity. Furthermore, we predict that previously unseen negative correlations and correlations involving calcium conductances are biologically plausible

Monitoring of microbial hydrocarbon remediation in the soil

Bioremediation of hydrocarbon pollutants is advantageous owing to the cost-effectiveness of the technology and the ubiquity of hydrocarbon-degrading microorganisms in the soil. Soil microbial diversity is affected by hydrocarbon perturbation, thus selective enrichment of hydrocarbon utilizers occurs. Hydrocarbons interact with the soil matrix and soil microorganisms determining the fate of the contaminants relative to their chemical nature and microbial degradative capabilities, respectively. Provided the polluted soil has requisite values for environmental factors that influence microbial activities and there are no inhibitors of microbial metabolism, there is a good chance that there will be a viable and active population of hydrocarbon-utilizing microorganisms in the soil. Microbial methods for monitoring bioremediation of hydrocarbons include chemical, biochemical and microbiological molecular indices that measure rates of microbial activities to show that in the end the target goal of pollutant reduction to a safe and permissible level has been achieved. Enumeration and characterization of hydrocarbon degraders, use of micro titer plate-based most probable number technique, community level physiological profiling, phospholipid fatty acid analysis, 16S rRNA- and other nucleic acid-based molecular fingerprinting techniques, metagenomics, microarray analysis, respirometry and gas chromatography are some of the methods employed in bio-monitoring of hydrocarbon remediation as presented in this review

Search for gravitational waves associated with gamma-ray bursts detected by Fermi and Swift during the LIGO–Virgo run O3b

We search for gravitational-wave signals associated with gamma-ray bursts (GRBs) detected by the Fermi and Swift satellites during the second half of the third observing run of Advanced LIGO and Advanced Virgo (2019 November 1 15:00 UTC–2020 March 27 17:00 UTC). We conduct two independent searches: a generic gravitational-wave transients search to analyze 86 GRBs and an analysis to target binary mergers with at least one neutron star as short GRB progenitors for 17 events. We find no significant evidence for gravitational-wave signals associated with any of these GRBs. A weighted binomial test of the combined results finds no evidence for subthreshold gravitational-wave signals associated with this GRB ensemble either. We use several source types and signal morphologies during the searches, resulting in lower bounds on the estimated distance to each GRB. Finally, we constrain the population of low-luminosity short GRBs using results from the first to the third observing runs of Advanced LIGO and Advanced Virgo. The resulting population is in accordance with the local binary neutron star merger rate