Extreme salinity as a challenge to grow potatoes under Mars-like soil conditions: targeting promising genotypes.

One of the future challenges to produce food in a Mars environment will be the optimization of resources through the potential use of the Martian substratum for growing crops as a part of bioregenerative food systems. In vitro plantlets from 65 potato genotypes were rooted in peat-pellets substratum and transplanted in pots filled with Mars-like soil from La Joya desert in Southern Peru. The Mars-like soil was characterized by extreme salinity (an electric conductivity of 19.3 and 52.6 dS m−1 under 1 : 1 and saturation extract of the soil solution, respectively) and plants grown in it were under sub-optimum physiological status indicated by average maximum stomatal conductance <50 mmol H2O m−2 s−1 even after irrigation. 40% of the genotypes survived and yielded (0.3–5.2 g tuber plant−1) where CIP.397099.4, CIP.396311.1 and CIP.390478.9 were targeted as promising materials with 9.3, 8.9 and 5.8% of fresh tuber yield in relation to the control conditions. A combination of appropriate genotypes and soil management will be crucial to withstand extreme salinity, a problem also important in agriculture on Earth that requires more detailed follow-up studies

Individuals Wearing Cleats Transitioning from Sitting to Standing Demonstrate a Significant Decrease in Blood Flow to the Foot

Plantar fasciopathy is a common foot condition with 10% prevalence in the general population. Plantar fasciosis (a type of fasciopathy) is considered a degenerative condition associated with cell death due to a lack of blood flow. Narrow, tight footwear, such as cleats, have been implicated as a potential contributing factors for the development of plantar fasciopathy and their direct influence on blood flow to the foot is currently unknown. PURPOSE: To investigate blood flow change in the anterior and posterior tibial arteries between sitting and standing in a cleated foot. METHODS: Eight individuals participated in this pilot study (weight=70.5 kg±12.9, height=1.8m±0.17). The participant put cleats on both feet, with a perceived tightness of 5/10 or greater on a VAS scale. Blood flow volume measurements of the anterior and posterior tibial arteries were taken simultaneously using pulse wave ultrasound, while the participant sat on a platform. These measurements were then repeated in the standing position on the same platform. Blood flow was measured in the dominate shod foot. A paired t-test was used to compare sitting to standing conditions within participants. RESULTS: In the anterior tibial artery, average volume flow changed from 6.25 ml/min (sitting) to 2.6 ml/min (standing), a 58% drop in blood flow (p=0.09). In the posterior tibial artery, volume flow decreased from an average of 11.25 ml/min to 3.95 ml/min, a decrease of 65% (p\u3c0.05). Total reduced blood flow between the two arteries decreased from 8.75 ml/min to 3.28 ml/min, a 63% drop (p\u3c0.05). CONCLUSION: There appears to be an important alteration of blood flow to the foot in individuals wearing cleats as they transition from a sitting to standing position. If this decrease in blood flow were to persist while wearing cleats, it may help explain the development of plantar fasciopathy observed in individuals wearing narrow, tight footwear

The Feasibility of a Behavioral Group Intervention after Weight-loss Surgery: A Randomized Pilot Trial

BACKGROUND: Formal psychosocial support programs after weight-loss surgery are limited in scope and availability. OBJECTIVE: This randomized pilot study evaluated the feasibility of a postoperative behavioral intervention program. MATERIALS AND METHODS: Postoperative weight-loss surgery patients (N = 50) were recruited from February 2017-July 2017 and randomized to a four-month behavioral program or usual care wait-list. Outcomes evaluated in addition to feasibility included health-related quality of life (Short Form -36), psychosocial functioning and adherence. Secondary outcomes included within-group changes for each outcome. RESULTS: Out of eight possible sessions, intervention participants attended a mean of 4.2 sessions. Intervention group participants experienced greater improvements in the social functioning domain of health-related quality of life compared to usual care. Self-reported dietary adherence in the intervention group remained stable, while usual care group dietary adherence declined. Within the intervention group, participants also reported gains in the physical function, pain and general health aspects of quality life from baseline to post-treatment. No differences in weight, mood or other eating behaviors (e.g., loss of control, emotional eating) were evident between groups. CONCLUSION: Though participation in a postoperative behavioral intervention varied, the program helped participants to maintain aspects of quality of life and self-reported adherence to dietary recommendations. TRIAL REGISTRATION: ClinicalTrials.gov NCT03092479

A phenomenological model of the electrically stimulated auditory nerve fiber: temporal and biphasic response properties

We present a phenomenological model of electrically stimulated auditory nerve fibers (ANFs). The model reproduces the probabilistic and temporal properties of the ANF response to both monophasic and biphasic stimuli, in isolation. The main contribution of the model lies in its ability to reproduce statistics of the ANF response (mean latency, jitter, and firing probability) under both monophasic and cathodic-anodic biphasic stimulation, without changing the model's parameters. The response statistics of the model depend on stimulus level and duration of the stimulating pulse, reproducing trends observed in the ANF. In the case of biphasic stimulation, the model reproduces the effects of pseudomonophasic pulse shapes and also the dependence on the interphase gap (IPG) of the stimulus pulse, an effect that is quantitatively reproduced. The model is fitted to ANF data using a procedure that uniquely determines each model parameter. It is thus possible to rapidly parameterize a large population of neurons to reproduce a given set of response statistic distributions. Our work extends the stochastic leaky integrate and fire (SLIF) neuron, a well-studied phenomenological model of the electrically stimulated neuron. We extend the SLIF neuron so as to produce a realistic latency distribution by delaying the moment of spiking. During this delay, spiking may be abolished by anodic current. By this means, the probability of the model neuron responding to a stimulus is reduced when a trailing phase of opposite polarity is introduced. By introducing a minimum wait period that must elapse before a spike may be emitted, the model is able to reproduce the differences in the threshold level observed in the ANF for monophasic and biphasic stimuli. Thus, the ANF response to a large variety of pulse shapes are reproduced correctly by this model

NeuroGrid: recording action potentials from the surface of the brain.

Recording from neural networks at the resolution of action potentials is critical for understanding how information is processed in the brain. Here, we address this challenge by developing an organic material-based, ultraconformable, biocompatible and scalable neural interface array (the 'NeuroGrid') that can record both local field potentials(LFPs) and action potentials from superficial cortical neurons without penetrating the brain surface. Spikes with features of interneurons and pyramidal cells were simultaneously acquired by multiple neighboring electrodes of the NeuroGrid, allowing for the isolation of putative single neurons in rats. Spiking activity demonstrated consistent phase modulation by ongoing brain oscillations and was stable in recordings exceeding 1 week's duration. We also recorded LFP-modulated spiking activity intraoperatively in patients undergoing epilepsy surgery. The NeuroGrid constitutes an effective method for large-scale, stable recording of neuronal spikes in concert with local population synaptic activity, enhancing comprehension of neural processes across spatiotemporal scales and potentially facilitating diagnosis and therapy for brain disorders

Solving Navigational Uncertainty Using Grid Cells on Robots

To successfully navigate their habitats, many mammals use a combination of two mechanisms, path integration and calibration using landmarks, which together enable them to estimate their location and orientation, or pose. In large natural environments, both these mechanisms are characterized by uncertainty: the path integration process is subject to the accumulation of error, while landmark calibration is limited by perceptual ambiguity. It remains unclear how animals form coherent spatial representations in the presence of such uncertainty. Navigation research using robots has determined that uncertainty can be effectively addressed by maintaining multiple probabilistic estimates of a robot's pose. Here we show how conjunctive grid cells in dorsocaudal medial entorhinal cortex (dMEC) may maintain multiple estimates of pose using a brain-based robot navigation system known as RatSLAM. Based both on rodent spatially-responsive cells and functional engineering principles, the cells at the core of the RatSLAM computational model have similar characteristics to rodent grid cells, which we demonstrate by replicating the seminal Moser experiments. We apply the RatSLAM model to a new experimental paradigm designed to examine the responses of a robot or animal in the presence of perceptual ambiguity. Our computational approach enables us to observe short-term population coding of multiple location hypotheses, a phenomenon which would not be easily observable in rodent recordings. We present behavioral and neural evidence demonstrating that the conjunctive grid cells maintain and propagate multiple estimates of pose, enabling the correct pose estimate to be resolved over time even without uniquely identifying cues. While recent research has focused on the grid-like firing characteristics, accuracy and representational capacity of grid cells, our results identify a possible critical and unique role for conjunctive grid cells in filtering sensory uncertainty. We anticipate our study to be a starting point for animal experiments that test navigation in perceptually ambiguous environments

Dual coding with STDP in a spiking recurrent neural network model of the hippocampus.

The firing rate of single neurons in the mammalian hippocampus has been demonstrated to encode for a range of spatial and non-spatial stimuli. It has also been demonstrated that phase of firing, with respect to the theta oscillation that dominates the hippocampal EEG during stereotype learning behaviour, correlates with an animal's spatial location. These findings have led to the hypothesis that the hippocampus operates using a dual (rate and temporal) coding system. To investigate the phenomenon of dual coding in the hippocampus, we examine a spiking recurrent network model with theta coded neural dynamics and an STDP rule that mediates rate-coded Hebbian learning when pre- and post-synaptic firing is stochastic. We demonstrate that this plasticity rule can generate both symmetric and asymmetric connections between neurons that fire at concurrent or successive theta phase, respectively, and subsequently produce both pattern completion and sequence prediction from partial cues. This unifies previously disparate auto- and hetero-associative network models of hippocampal function and provides them with a firmer basis in modern neurobiology. Furthermore, the encoding and reactivation of activity in mutually exciting Hebbian cell assemblies demonstrated here is believed to represent a fundamental mechanism of cognitive processing in the brain