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Hill, J. K.

Publications and source records attributed to Hill, J. K..

2 recordsLinked to original sources

Brain-derived neurotrophic factor contributes to activity-induced muscle pain in male but not female mice

Activity-induced muscle pain increases release of interleukin-1{beta} (IL-1{beta}) in muscle macrophages and the development of pain is prevented by blockade of IL-1{beta}. Brain derived neurotrophic factor (BDNF) is released from sensory neurons in response to IL-1{beta} and mediates both inflammatory and neuropathic pain. Thus, we hypothesized that metabolites released during fatiguing muscle contractions activate macrophages to release IL-1{beta}, which subsequently activate sensory neurons to secrete BDNF. To test this hypothesis, we used an animal model of activity-induced pain induced by repeated intramuscular acidic saline injections combined with fatiguing muscle contractions. Intrathecal or intramuscular injection of inhibitors of BDNF-Tropomyosin receptor kinase B (TrkB) signaling, ANA-12 or TrkB-Fc, reduced the decrease in muscle withdrawal thresholds in male, but not in female, mice when given before or 24hr after, but not 1 week after induction of the model. BDNF messenger ribonucleic acid (mRNA) was significantly increased in L4-L6 dorsal root ganglion (DRG), but not the spinal dorsal horn or gastrocnemius muscle, 24hr after induction of the model in either male or female mice. No changes in TrkB mRNA or p75 neurotrophin receptor mRNA were observed. BDNF protein expression via immunohistochemistry was significantly increased in L4-L6 spinal dorsal horn and retrogradely labelled muscle afferent DRG neurons, at 24hr after induction of the model in both sexes. In cultured DRG, fatigue metabolites combined with IL-1{beta} significantly increased BDNF expression in both sexes. In summary, fatigue metabolites release, combined with IL-1{beta}, BDNF from primary DRG neurons and contribute to activity-induced muscle pain only in males, while there were no sex differences in the changes in expression observed in BDNF.

neuroscience↗

Unlocking the potential of historical abundance datasets to study biomass change in flying insects

O_LITrends in insect abundance are well-established in some datasets, but far less is known about how abundance measures translate into biomass trends. Moths (Lepidoptera) provide particularly good opportunities to study trends and drivers of biomass change at large spatial and temporal scales, given the existence of long-term abundance datasets. However, data on the body masses of moths are required for these analyses, but such data do not currently exist. C_LIO_LITo address this data gap, we collected empirical data in 2018 on the forewing length and dry mass of field-sampled moths, and used these to train and test a statistical model that predicts the body mass of moth species from their forewing lengths (with refined parameters for Crambidae, Erebidae, Geometridae and Noctuidae). C_LIO_LIModelled biomass was positively correlated, with high explanatory power, with measured biomass of moth species (R2 = 0.886 {+/-} 0.0006, across 10,000 bootstrapped replicates) and of mixed-species samples of moths (R2 = 0.873 {+/-} 0.0003), showing that it is possible to predict biomass to an informative level of accuracy, and prediction error was smaller with larger sample sizes. C_LIO_LIOur model allows biomass to be estimated for historical moth abundance datasets, and so our approach will create opportunities to investigate trends and drivers of insect biomass change over long timescales and broad geographic regions. C_LI

ecology↗