Ventilatory response during CO2 inhalation after airway anesthesia with lidocaine

Airway anesthesia with inhaled aerosolized lidocaine has been associated with increases in minute ventilation (VE) and mean inspiratory flow rate (VT/TI) during CO2 inhalation. However, it is unclear whether these increases are local effects of the anesthesia or systemic effects of absorbed and circulating lidocaine. To evaluate this 20 normal subjects were treated on separate days with aerosolized lidocaine, intravenous lidocaine, aerosolized control solution, or intravenous control solution, and the effects of each treatment on VE and VT/TI were determined and compared during room-air breathing and inhalation of 5% CO2-95% O2. None of the treatments altered VE or VT/TI during room-air breathing. Aerosolized lidocaine produced small (5.9-6.0%) increases in VE and VT/TI during CO2 inhalation, but these effects were not present after intravenous lidocaine despite equivalent lidocaine blood levels. We concluded that the increases in VE and VT/TI after aerosolized lidocaine were local effects of airway anesthesia rather than systemic effects of absorbed and circulating lidocaine.     

Reliability and representational bandwidth in the auditory cortex

It is unclear why there are so many more neurons in sensory cortex than in the sensory periphery. One possibility is that these "extra" neurons are used to overcome cortical noise and faithfully represent the acoustic stimulus. Another possibility is that even after overcoming cortical noise, there is "excess representational bandwidth" available and that this bandwidth is used to represent conjunctions of auditory and nonauditory information for computation. Here, we discuss recent data about neuronal reliability in auditory cortex showing that cortical noise may not be as high as was previously believed. Although at present, the data suggest that auditory cortex neurons can be more reliable than those in the visual cortex, we speculate that the principles governing cortical computation are universal and that visual and other cortical areas can also exploit strategies based on similarly high-fidelity activity.     

Tissue biomarkers for prostate cancer radiation therapy

Prostate cancer is the most common cancer and second leading cause of cancer deaths among men in the United States. Most men have localized disease diagnosed following an elevated serum prostate specific antigen test for cancer screening purposes. Standard treatment options consist of surgery or definitive radiation therapy directed by clinical factors that are organized into risk stratification groups. Current clinical risk stratification systems are still insufficient to differentiate lethal from indolent disease. Similarly, a subset of men in poor risk groups need to be identified for more aggressive treatment and enrollment into clinical trials. Furthermore, these clinical tools are very limited in revealing information about the biologic pathways driving these different disease phenotypes and do not offer insights for novel treatments which are needed in men with poor-risk disease. We believe molecular biomarkers may serve to bridge these inadequacies of traditional clinical factors opening the door for personalized treatment approaches that would allow tailoring of treatment options to maximize therapeutic outcome. We review the current state of prognostic and predictive tissue-based molecular biomarkers which can be used to direct localized prostate cancer treatment decisions, specifically those implicated with definitive and salvage radiation therapy.     

Optimal Control of Transitions between Nonequilibrium Steady States

Biological systems fundamentally exist out of equilibrium in order to preserve organized structures and processes. Many changing cellular conditions can be represented as transitions between nonequilibrium steady states, and organisms have an interest in optimizing such transitions. Using the Hatano-Sasa Y-value, we extend a recently developed geometrical framework for determining optimal protocols so that it can be applied to systems driven from nonequilibrium steady states. We calculate and numerically verify optimal protocols for a colloidal particle dragged through solution by a translating optical trap with two controllable parameters. We offer experimental predictions, specifically that optimal protocols are significantly less costly than naive ones. Optimal protocols similar to these may ultimately point to design principles for biological energy transduction systems and guide the design of artificial molecular machines.     

Ventilatory response to high-frequency airway oscillation in humans

To investigate respiratory control during high-frequency oscillation (HFO), ventilation was monitored in conscious humans by respiratory inductive plethysmography during application at the mouth of high-frequency pressure oscillations. Studies were conducted before and after airway and pharyngeal anesthesia. During HFO, breathing became slow and deep with an increase in tidal volume (VT) of 37% (P less than 0.01) and inspiratory duration (TI) of 34% (P less than 0.01). Timing ratio (TI/TT) increased 14% (P less than 0.05) and respiratory frequency (f) decreased 12% (P less than 0.01). Mean inspiratory flow (VT/TI) did not change during HFO. Following airway anesthesia, VT increased only 26% during HFO (P less than 0.01), whereas significant changes in TI, TI/TT, and f were not observed. Pharyngeal anesthesia failed to diminish the effect of HFO on TI, TT, or f, although the increase in VT was reduced. These results indicate that 1) HFO presented in this manner alters inspiratory timing without affecting the level of inspiratory activity, and 2) receptors in the larynx and/or lower airways may in part mediate the response.     

Three centuries of fire in montane pine‐oak stands on a temperate forest landscape

Question: What was the role of fire in montane pine‐oak (Pinus‐Quercus) stands under changing human land uses on a temperate forest landscape in eastern North America? Location: Mill Mountain in the central Appalachian Mountains, Virginia, US. Methods: A dendroecological reconstruction of fire history was generated for four stands dominated by xerophytic pine and oak species. The fire chronology began under presettlement conditions following aboriginal depopulation. Subsequent land uses included European settlement, iron mining, logging, and US Forest Service acquisition and fire protection. Results: Fires occurred approximately every 5 years until 1930 without any evidence of a temporal trend in fire frequency. Burning ceased after 1930. Area‐wide fires affecting multiple pine stands were common, occurring at intervals of approximately 16 years. Most living pines became established during the late 1800s and early 1900s. Dead pines indicated that an older cohort established ca. 1730. Most hardwoods were established between the 1920s and 1940s. Conclusions: Except for fire protection, changes in land use had no discernible influence on fire frequency. Lightning ignitions and/or large fire extent may have been important for maintaining frequent burning in the 1700s, while fuel recovery may have constrained fire frequency during later periods. The disturbance regime appears to be characterized by frequent surface fires and occasional severe fires, insect outbreaks or other disturbances followed by pine recruitment episodes. Industrial disturbances appear to have had little influence on the pine stands. The greatest impact of industrial society is fire exclusion, which permitted hardwood establishment.     

A sparse coding model with synaptically local plasticity and spiking neurons can account for the diverse shapes of V1 simple cell receptive fields

Sparse coding algorithms trained on natural images can accurately predict the features that excite visual cortical neurons, but it is not known whether such codes can be learned using biologically realistic plasticity rules. We have developed a biophysically motivated spiking network, relying solely on synaptically local information, that can predict the full diversity of V1 simple cell receptive field shapes when trained on natural images. This represents the first demonstration that sparse coding principles, operating within the constraints imposed by cortical architecture, can successfully reproduce these receptive fields. We further prove, mathematically, that sparseness and decorrelation are the key ingredients that allow for synaptically local plasticity rules to optimize a cooperative, linear generative image model formed by the neural representation. Finally, we discuss several interesting emergent properties of our network, with the intent of bridging the gap between theoretical and experimental studies of visual cortex.