Gonadotropin-releasing hormone (GnRH) neurons are hypothalamic neurons that control the pulsatile release of GnRH that governs fertility and reproduction in mammals. The mechanisms underlying the pulsatile release of GnRH are not well understood. Some mathematical models have been developed previously to explain different aspects of these activities, such as the properties of burst action potential firing and their associated Ca(2+) transients. These previous studies were based on experimental recordings taken from the soma of GnRH neurons. However, some research groups have shown that the dendrites of GnRH neurons play very important roles. In particular, it is now known that the site of action potential initiation in these neurons is often in the dendrite, over 100 μm from the soma. This raises an important question. Since some of the mechanisms for controlling the burst length and interburst interval are located in the soma, how can electrical bursting be controlled when initiated at a site located some distance from these controlling mechanisms? In order to answer this question, we construct a spatio-temporal mathematical model that includes both the soma and the dendrite. Our model shows that the diffusion coefficient for the spread of electrical potentials in the dendrite is large enough to coordinate burst firing of action potentials when the initiation site is located at some distance from the soma.
Botrytis cinerea, which causes gray mold, is an important pathogen in four important economic crops, tomato, tobacco, cucumber and strawberry, in China and worldwide. Metabolic phenomics data on B. cinerea isolates from these four crops were characterized and compared for 950 phenotypes with a BIOLOG Phenotype MicroArray (PM). The results showed that the metabolic fingerprints of the four B. cinerea isolates were similar to each other with minimal differences. B. cinerea isolates all metabolized more than 17% of the tested carbon sources, 63% of the amino acid nitrogen substrates, 80% of the peptide nitrogen substrates, 93% of the phosphorus substrates, and 97% of the sulfur substrates. Carbon substrates of organic acids and carbohydrates, and nitrogen substrates of amino acids and peptides were the significant utilization patterns for B. cinerea. Each B. cinerea isolate contained 94 biosynthetic pathways. These isolates showed a large range of adaptabilities and were still able to metabolize substrates in the presence of the osmolytes, including up to 6% potassium chloride, 10% sodium chloride, 5% sodium sulfate, 6% sodium formate, 20% ethylene glycol, and 3% urea. These isolates all showed active metabolism in environments with pH values from 3.5 to 8.5 and exhibited decarboxylase activities. These characterizations provide a theoretical basis for the study of B. cinerea in biochemistry and metabolic phenomics and provide valuable clues to finding potential new ways to manage gray mold.
Myzus persicae is a serious and widespread agricultural pest, against which, imidacloprid remains an effective control measure. However, recent reports indicate that this aphid has evolved and developed resistance to imidacloprid. This study aimed to elucidate the underlying mechanisms and genetic basis of this resistance by conducting comparative transcriptomics studies on both imidacloprid-resistant (IR) and imidacloprid-susceptible (IS) M. persicae. The comparative analysis identified 252 differentially expressed genes (DEGs) among the IR and IS M. persicae transcriptomes. These candidate genes included 160 and 92 genes that were down- and up-regulated, respectively, in the imidacloprid-resistant strain. Using functional classification in the GO and KEGG databases, 187 DEGs were assigned to 303 functional subcategories and 100 DEGs were classified into 45 pathway groups. Moreover, several genes were associated with known insecticide targets, cuticle, metabolic processes, and oxidative phosphorylation. Quantitative real-time PCR of 10 DEGs confirmed the trends observed in the RNA sequencing expression profiles. These findings provide a valuable basis for further investigation into the complicated mechanisms of imidacloprid resistance in M. persicae.
Gonadotropin-releasing hormone (GnRH) neurons have two major processes that have properties of both dendrites (they receive synaptic input from other neurons) and axons (they actively propagate action potentials to the synaptic terminal). These processes have thus been termed dendrons. We construct a stochastic spatiotemporal model of the dendron of the GnRH neuron, with the goal of studying how stochastic synaptic input along the length of the dendron affects the initiation and propagation of action potentials. We show (1) that synaptic inputs closer to the soma are effective controllers of action potential initiation and electrical bursting and (2) that although the effects on the amplitude and width of propagating action potentials are critically dependent on the timing and location of synaptic input addition, the effects remain small. We conclude that although stochastic synaptic input along the length of the dendron is likely to be a major determinant of action potential initiation, it is an unlikely mechanism for controlling whether or not action potentials reach the synaptic terminal. Thus, the role of synaptic inputs situated along the dendron a long way from the site of action potential initiation remains unclear. We also show that the actions of kisspeptin can result in significant modulation of the amount of calcium released by an action potential at the synaptic terminal. Furthermore, we show that the actions of kisspeptin are greatest when multiple effects operate together and that a kisspeptin-induced increase in firing rate is, by itself, less effective at increasing Ca2+ release than is a combination of an increased firing rate, an increase in Ca2+ influx, and an increase in inositol trisphosphate (IP3) production. We conclude that the inherent synergies in the various actions of kisspeptin make it a likely candidate for the precise control of Ca2+ transients at the synaptic terminal.
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