Homarus Americanus Stomatogastric Nervous System Dissection

With the goal of understanding how nervous systems produce activity and respond to the environment, neuroscientists turn to model systems that exhibit the activity of interest and are accessible and amenable to experimental methods. The stomatogastric nervous system (STNS) of the American lobster (Homarus americanus; also know was the Atlantic or Maine lobster) has been established as a model system for studying rhythm generating networks and neuromodulation of networks. The STNS consists of 3 anterior ganglia (2 commissural ganglia and an oesophageal ganglion), containing modulatory neurons that project centrally to the stomatogastric ganglion (STG). The STG contains approximately 30 neurons that comprise two central pattern generating networks, the pyloric and gastric networks that underlie feeding behaviors in crustaceans^1,2. While it is possible to study this system in vivo³, the STNS continues to produce its rhythmic activity when isolated in vitro. Physical isolation of the STNS in a dish allows for easy access to the somata in the ganglia for intracellular electrophysiological recordings and to the nerves of the STNS for extracellular recordings. Isolating the STNS is a two-part process. The first part, dissecting the stomach from the animal, is described in an accompanying video article⁴. In this video article, fine dissection techniques are used to isolate the STNS from the stomach. This procedure results in a nervous system preparation that is available for electrophysiological recordings.     

Synaptic Connectivity between the Cortex and Claustrum Is Organized into Functional Modules

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Artificial neural network and response surface methodology: a comparative analysis for optimizing rice straw pretreatment and saccharification

Abstract

The present study demonstrates a comparative analysis between the artificial neural network (ANN) and response surface methodology (RSM) as optimization tools for pretreatment and enzymatic hydrolysis of lignocellulosic rice straw. The efficacy for both the processes, that is, pretreatment and enzymatic hydrolysis was evaluated using correlation coefficient (R²) & mean squared error (MSE). The values of R² obtained by ANN after training, validation, and testing were 1, 0.9005, and 0.997 for pretreatment and 0.962, 0.923, and 0.9941 for enzymatic saccharification, respectively. On the other hand, the R² values obtained with RSM were 0.9965 for cellulose recovery and 0.9994 for saccharification efficiency. Thus, ANN and RSM together successfully identify the substantial process conditions for rice straw pretreatment and enzymatic saccharification. The percentage of error for ANN and RSM were 0.009 and 0.01 for cellulose recovery and for 0.004 and 0.005 for saccharification efficiency, respectively, which showed the authority of ANN in exemplifying the non-linear behavior of the system.     

Disentangling the potential effects of land‐use and climate change on stream conditions

Land‐use and climate change are significantly affecting stream ecosystems, yet understanding of their long‐term impacts is hindered by the few studies that have simultaneously investigated their interaction and high variability among future projections. We modeled possible effects of a suite of 2030, 2060, and 2090 land‐use and climate scenarios on the condition of 70,772 small streams in the Chesapeake Bay watershed, United States. The Chesapeake Basin‐wide Index of Biotic Integrity, a benthic macroinvertebrate multimetric index, was used to represent stream condition. Land‐use scenarios included four Special Report on Emissions Scenarios (A1B, A2, B1, and B2) representing a range of potential landscape futures. Future climate scenarios included quartiles of future climate changes from downscaled Coupled Model Intercomparison Project ‐ Phase 5 (CMIP5) and a watershed‐wide uniform scenario (Lynch2016). We employed random forests analysis to model individual and combined effects of land‐use and climate change on stream conditions. Individual scenarios suggest that by 2090, watershed‐wide conditions may exhibit anywhere from large degradations (e.g., scenarios A1B, A2, and the CMIP5 25th percentile) to small degradations (e.g., scenarios B1, B2, and Lynch2016). Combined land‐use and climate change scenarios highlighted their interaction and predicted, by 2090, watershed‐wide degradation in 16.2% (A2 CMIP5 25th percentile) to 1.0% (B2 Lynch2016) of stream kilometers. A goal for the Chesapeake Bay watershed is to restore 10% of stream kilometers over a 2008 baseline; our results suggest meeting and sustaining this goal until 2090 may require improvement in 11.0%–26.2% of stream kilometers, dependent on land‐use and climate scenario. These results highlight inherent variability among scenarios and the resultant uncertainty of predicted conditions, which reinforces the need to incorporate multiple scenarios of both land‐use (e.g., development, agriculture, etc.) and climate change in future studies to encapsulate the range of potential future conditions.     

Rapid anti‐depressant‐like effects of ketamine and other candidates: Molecular and cellular mechanisms

Major depressive disorder takes at least 3 weeks for clinical anti‐depressants, such as serotonin selective reuptake inhibitors, to take effect, and only one‐third of patients remit. Ketamine, a kind of anaesthetic, can alleviate symptoms of major depressive disorder patients in a short time and is reported to be effective to treatment‐resistant depression patients. The rapid and strong anti‐depressant‐like effects of ketamine cause wide concern. In addition to ketamine, caloric restriction and sleep deprivation also elicit similar rapid anti‐depressant‐like effects. However, mechanisms about the rapid anti‐depressant‐like effects remain unclear. Elucidating the mechanisms of rapid anti‐depressant effects is the key to finding new therapeutic targets and developing therapeutic patterns. Therefore, in this review we summarize potential molecular and cellular mechanisms of rapid anti‐depressant‐like effects based on the pre‐clinical and clinical evidence, trying to provide new insight into future therapy.     

The thermodynamics of thinking: connections between neural activity,energy metabolism and blood flow

Several current functional neuroimaging methods are sensitive to cerebral metabolism and cerebral blood flow (CBF) rather than the underlying neural activity itself. Empirically, the connections between metabolism, flow and neural activity are complex and somewhat counterintuitive: CBF and glycolysis increase more than seems to be needed to provide oxygen and pyruvate for oxidative metabolism, and the oxygen extraction fraction is relatively low in the brain and decreases when oxygen metabolism increases. This work lays a foundation for the idea that this unexpected pattern of physiological changes is consistent with basic thermodynamic considerations related to metabolism. In the context of this thermodynamic framework, the apparent mismatches in metabolic rates and CBF are related to preserving the entropy change of oxidative metabolism, specifically the O₂/CO₂ ratio in the mitochondria. However, the mechanism supporting this CBF response is likely not owing to feedback from a hypothetical O₂ sensor in tissue, but rather is consistent with feed-forward control by signals from both excitatory and inhibitory neural activity. Quantitative predictions of the thermodynamic framework, based on models of O₂ and CO₂ transport and possible neural drivers of CBF control, are in good agreement with a wide range of experimental data, including responses to neural activation, hypercapnia, hypoxia and high-altitude acclimatization.This article is part of the theme issue ‘Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity’.