Hypocretin as a Hub for Arousal and Motivation

The lateral hypothalamus is comprised of a heterogeneous mix of neurons that serve to integrate and regulate sleep, feeding, stress, energy balance, reward, and motivated behavior. Within these populations, the hypocretin/orexin neurons are among the most well studied. Here, we provide an overview on how these neurons act as a central hub integrating sensory and physiological information to tune arousal and motivated behavior accordingly. We give special attention to their role in sleep-wake states and conditions of hyper-arousal, as is the case with stress-induced anxiety. We further discuss their roles in feeding, drug-seeking, and sexual behavior, which are all dependent on the motivational state of the animal. We further emphasize the application of powerful techniques, such as optogenetics, chemogenetics, and fiber photometry, to delineate the role these neurons play in lateral hypothalamic functions

The Key Role of Heavy Precipitation Events in Climate Model Disagreements of Future Annual Precipitation Changes in California

Climate model simulations disagree on whether future precipitation will increase or decrease over California, which has impeded efforts to anticipate and adapt to human-induced climate change. This disagreement is explored in terms of daily precipitation frequency and intensity. It is found that divergent model projections of changes in the incidence of rare heavy (\u3e60 mm day−1) daily precipitation events explain much of the model disagreement on annual time scales, yet represent only 0.3% of precipitating days and 9% of annual precipitation volume. Of the 25 downscaled model projections examined here, 21 agree that precipitation frequency will decrease by the 2060s, with a mean reduction of 6–14 days yr−1. This reduces California\u27s mean annual precipitation by about 5.7%. Partly offsetting this, 16 of the 25 projections agree that daily precipitation intensity will increase, which accounts for a model average 5.3% increase in annual precipitation. Between these conflicting tendencies, 12 projections show drier annual conditions by the 2060s and 13 show wetter. These results are obtained from 16 global general circulation models downscaled with different combinations of dynamical methods [Weather Research and Forecasting (WRF), Regional Spectral Model (RSM), and version 3 of the Regional Climate Model (RegCM3)] and statistical methods [bias correction with spatial disaggregation (BCSD) and bias correction with constructed analogs (BCCA)], although not all downscaling methods were applied to each global model. Model disagreements in the projected change in occurrence of the heaviest precipitation days (\u3e60 mm day−1) account for the majority of disagreement in the projected change in annual precipitation, and occur preferentially over the Sierra Nevada and Northern California. When such events are excluded, nearly twice as many projections show drier future conditions

Probabilistic estimates of future changes in California temperature and precipitation usingstatistical and dynamical downscaling

Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s. The global models were downscaled with two statistical techniques and three nested dynamical regional climate models, although not all global models were downscaled with all techniques. Both monthly and daily timescale changes in T and P are addressed, the latter being important for a range of applications in energy use, water management, and agriculture. The T changes tend to agree more across downscaling techniques than the P changes. Year-to-year natural internal climate variability is roughly of similar magnitude to the projected T changes. In the monthly average, July temperatures shift enough that that the hottest July found in any simulation over the historical period becomes a modestly cool July in the future period. Januarys as cold as any found in the historical period are still found in the 2060s, but the median and maximum monthly average temperatures increase notably. Annual and seasonal P changes are small compared to interannual or intermodel variability. However, the annual change is composed of seasonally varying changes that are themselves much larger, but tend to cancel in the annual mean. Winters show modestly wetter conditions in the North of the state, while spring and autumn show less precipitation. The dynamical downscaling techniques project increasing precipitation in the Southeastern part of the state, which is influenced by the North American monsoon, a feature that is not captured by the statistical downscaling

Robonaut Mobile Autonomy: Initial Experiments

A mobile version of the NASA/DARPA Robonaut humanoid recently completed initial autonomy trials working directly with humans in cluttered environments. This compact robot combines the upper body of the Robonaut system with a Segway Robotic Mobility Platform yielding a dexterous, maneuverable humanoid ideal for interacting with human co-workers in a range of environments. This system uses stereovision to locate human teammates and tools and a navigation system that uses laser range and vision data to follow humans while avoiding obstacles. Tactile sensors provide information to grasping algorithms for efficient tool exchanges. The autonomous architecture utilizes these pre-programmed skills to form complex behaviors. The initial behavior demonstrates a robust capability to assist a human by acquiring a tool from a remotely located individual and then following the human in a cluttered environment with the tool for future use

Wood allocation trade-offs between fiber wall, fiber lumen, and axial parenchyma drive drought resistance in neotropical trees

Functional relationships between wood density and measures of xylem hydraulic safety and efficiency are ambiguous, especially in wet tropical forests. In this meta-analysis, we move beyond wood density per se and identify relationships between xylem allocated to fibers, parenchyma, and vessels and measures of hydraulic safety and efficiency. We analyzed published data of xylem traits, hydraulic properties and measures of drought resistance from neotropical tree species retrieved from 346 sources. We found that xylem volume allocation to fiber walls increases embolism resistance, but at the expense of specific conductivity and sapwood capacitance. Xylem volume investment in fiber lumen increases capacitance, while investment in axial parenchyma is associated with higher specific conductivity. Dominant tree taxa from wet forests prioritize xylem allocation to axial parenchyma at the expense of fiber walls, resulting in a low embolism resistance for a given wood density and a high vulnerability to drought-induced mortality. We conclude that strong trade-offs between xylem allocation to fiber walls, fiber lumen, and axial parenchyma drive drought resistance in neotropical trees. Moreover, the benefits of xylem allocation to axial parenchyma in wet tropical trees might not outweigh the consequential low embolism resistance under more frequent and severe droughts in a changing climate.Peer reviewe

DEXA-Measured VAT Robustly Predicts Impaired Glucose Tolerance and Metabolic Syndrome in Obese Women

Abdominal visceral adiposity (VAT) has been shown to be an independent risk factor for metabolic and cardiovascular disease. Using enCORE analysis version 13.6 on a GE Lunar iDXA, a new fully automated analysis software to measure VAT, we determined the strength of associations between DEXA-derived VAT and other known indicators for diabetes and cardiovascular disease risk in Caucasian and African American obese women. We collected anthropometrics, vital signs, lipid profile, and DXA whole body composition scan for 229 subjects with BMI 30.0 – 49.9 kg/m2 & age 21 to 69 y. We then performed the non-parametric Spearman correlation analysis and found that in subjects overall, DEXA-VAT is positively associated with triglyceride, fasting glucose, fasting insulin, and HOMA-IR, and negatively associated with HDL. Among all anthropometric, body composition and cardiometabolic variables, DEXA-VAT was the most robust predictor of impaired glucose tolerance (IGT) and metabolic syndrome (MetSx) in binary regression analysis, even after adjusting for race. LASSO regression after adjusting for covariates that best predicted IGT and MetSx showed that HOMAIR and DEXA-VAT most significantly predicted IGT (p\u3c0.001, p\u3c0.001, respectively), and DEXA-VAT most significantly predicted MetSx (p\u3c0.001). These observations have implications for VAT associated risk in diabetes and cardiovascular disease