Fast Chromatographic Determination of Free Amino Acids in Bee Pollen.

The consumption of bee pollen has increased in the last few years due to its nutritional and health-promoting properties, which are directly related to its bioactive constituents, such as amino acids. Currently, there is great interest in understanding the role of these in bee products as it provides relevant information, e.g., regarding nutritional value or geographical and botanical origins. In the present study, two fast chromatographic methods were adapted based on commercial EZ:faast™ kits for gas chromatography-mass spectrometry and liquid chromatography−mass spectrometry for determining free amino acids in bee pollen. Both methods involved the extraction of amino acids with water, followed by a solid phase extraction to eliminate interfering compounds, and a derivatization of the amino acids prior to their chromatographic separation. The best results in terms of run time (<7 min), matrix effect, and limits of quantification (3−75 mg/kg) were obtained when gas chromatography−mass spectrometry was employed. This latter methodology was applied to analyze several bee pollen samples obtained from local markets and experimental apiaries. The findings obtained from a statistical examination based on principal component analysis showed that bee pollen samples from commercial or experimental apiaries were different in their amino acid composition.

Differentiation of bee pollen samples according to the betaines and other quaternary ammonium related compounds content by using a canonical discriminant analysis.

In the last years, an increase has been observed in the adulteration of bee pollen. Consequently, different tools are required to authenticate the origin of this product, such as a study of the profile and composition of a specific family of compounds. The present study investigates the potential of betaines and related compounds as markers of the apiary of origin and harvest period of 71 bee pollen samples. These were collected from four apiaries (Pistacho, Tío Natalio, Monte and Fuentelahiguera), located in the same geographical area (Guadalajara, Spain) and sampled during three consecutive harvest periods in the same year (April-May, June, July-August). They were analyzed by means of a previously developed methodology, which involved solvent extraction, hydrophilic interaction liquid chromatography coupled to mass spectrometry, and a statistical analysis of the data (canonical discriminant analysis). Variable amounts of betaines and related compounds were found in the samples, with four of these being identified in all of them (betonicine, betaine, trigonelline and choline); betonicine was the predominant compound in a concentration range of 264 to 52384 mg/kg. It was possible to statistically assign over 50 % of the samples to the corresponding apiary of origin, the best results being obtained for the Tío Natalio apiary (75 %); this classification was even better in the case of the harvest period, as more than 75 % of the samples were correctly assigned, and in two periods (April-May and June) a 90 % rate was obtained.

Glucosinolates as Markers of the Origin and Harvesting Period for Discrimination of Bee Pollen by UPLC-MS/MS.

Bee pollen is currently one of the most commonly consumed food supplements, as it is considered to be a good source of bioactive substances and energy. It contains various health-promoting compounds, such as proteins, amino acids, lipids, as well as glucosinolates. In the present study, the glucosinolate content was determined, by means of ultra-performance liquid chromatography coupled to a quadrupole time-of-flight mass detector, in 72 bee pollen samples from four different apiaries in Guadalajara (Spain), harvested in three different periods. In addition, 11 commercial multifloral samples from different Spanish regions were also analyzed. The aim was to verify the suitability of these compounds as biomarkers of their geographical origin, and to test their potential for distinguishing the harvesting period. By means of a canonical discriminant analysis, it was possible to differentiate the apiary of origin of most of the samples, and these could also be clearly differentiated from the commercial ones, simply as a result of the glucosinolate content. In addition, it was also demonstrated for the first time that bee pollen samples were capable of being differentiated according to the time of harvesting and their glucosinolate content.

Data envelopment analysis efficiency in the public sector using provider and customer opinion: An application to the Spanish health system.

Measuring the relative efficiency of a finite fixed set of service-producing units (hospitals, state services, libraries, banks,...) is an important purpose of Data Envelopment Analysis (DEA). We illustrate an innovative way to measure this efficiency using stochastic indexes of the quality from these services. The indexes obtained from the opinion-satisfaction of the customers are estimators, from the statistical view point, of the quality of the service received (outputs); while, the quality of the offered service is estimated with opinion-satisfaction indexes of service providers (inputs). The estimation of these indicators is only possible by asking a customer and provider sample, in each service, through surveys. The technical efficiency score, obtained using the classic DEA models and estimated quality indicators, is an estimator of the unknown population efficiency that would be obtained if in each one of the services, interviews from all their customers and all their providers were available. With the object of achieving the best precision in the estimate, we propose results to determine the sample size of customers and providers needed so that with their answers can achieve a fixed accuracy in the estimation of the population efficiency of these service-producing units through the use of a novel one bootstrap confidence interval. Using this bootstrap methodology and quality opinion indexes obtained from two surveys, one of doctors and another of patients, we analyze the efficiency in the health care system of Spain.

The Existence of the StartReact Effect Implies Reticulospinal, Not Corticospinal, Inputs Dominate Drive to Motoneurons during Voluntary Movement.

Reaction time is accelerated if a loud (startling) sound accompanies the cue-the "StartReact" effect. Animal studies revealed a reticulospinal substrate for the startle reflex; StartReact may similarly involve the reticulospinal tract, but this is currently uncertain. Here we trained two female macaque monkeys to perform elbow flexion/extension movements following a visual cue. The cue was sometimes accompanied by a loud sound, generating a StartReact effect in electromyogram response latency, as seen in humans. Extracellular recordings were made from antidromically identified corticospinal neurons in primary motor cortex (M1), from the reticular formation (RF), and from the spinal cord (SC; C5-C8 segments). After loud sound, task-related activity was suppressed in M1 (latency, 70-200 ms after cue), but was initially enhanced (70-80 ms) and then suppressed (140-210 ms) in RF. SC activity was unchanged. In a computational model, we simulated a motoneuron pool receiving input from different proportions of the average M1 and RF activity recorded experimentally. Motoneuron firing generated simulated electromyogram, allowing reaction time measurements. Only if ≥60% of motoneuron drive came from RF (≤40% from M1) did loud sound shorten reaction time. The extent of shortening increased as more drive came from RF. If RF provided <60% of drive, loud sound lengthened the reaction time-the opposite of experimental findings. The majority of the drive for voluntary movements is thus likely to originate from the brainstem, not the cortex; changes in the magnitude of the StartReact effect can measure a shift in the relative importance of descending systems.SIGNIFICANCE STATEMENT Our results reveal that a loud sound has opposite effects on neural spiking in corticospinal cells from primary motor cortex, and in the reticular formation. We show that this fortuitously allows changes in reaction time produced by a loud sound to be used to assess the relative importance of reticulospinal versus corticospinal control of movement, validating previous noninvasive measurements in humans. Our findings suggest that the majority of the descending drive to motoneurons producing voluntary movement in primates comes from the reticulospinal tract, not the corticospinal tract.

Modeling Post-Scratching Locomotion with Two Rhythm Generators and a Shared Pattern Formation.

This study aimed to present a model of post-scratching locomotion with two intermixed central pattern generator (CPG) networks, one for scratching and another for locomotion. We hypothesized that the rhythm generator layers for each CPG are different, with the condition that both CPGs share their supraspinal circuits and their motor outputs at the level of their pattern formation networks. We show that the model reproduces the post-scratching locomotion latency of 6.2 ± 3.5 s, and the mean cycle durations for scratching and post-scratching locomotion of 0.3 ± 0.09 s and 1.7 ± 0.6 s, respectively, which were observed in a previous experimental study. Our findings show how the transition of two rhythmic movements could be mediated by information exchanged between their CPG circuits through routes converging in a common pattern formation layer. This integrated organization may provide flexible and effective connectivity despite the rigidity of the anatomical connections in the spinal cord circuitry.

Effects of Short-Term Random Noise Electrical Stimulation on Dissociated Pyramidal Neurons from the Cerebral Cortex.

Transcranial random noise electrical stimulation (tRNS) of the human brain is a non-invasive technique that can be employed to increase the excitability of the cerebral cortex; however, the physiological mechanisms remain unclear. Here we report for the first time the effects of short-term (250 ms) random noise electrical stimulation (RNS) on in-vitro acutely-isolated brain pyramidal neurons from the somatosensory and auditory cerebral cortex. We analyzed the correlation between the peak amplitude of the Na+ current and its latency for different levels of RNS. We found three groups of neurons. The first group exhibited a positive correlation, the second, a negative correlation, and the third group of neurons did not exhibit correlation. In the first group, both the peak amplitude of a TTX-sensitive Na+ current and its inverse of latency followed similar inverted U-like functions relative to the electrical RNS level. In this group, the RNS levels in which the maximal values of the inverted U-like functions occurred were the same. In the second group, the maximal values of the inverted U-like functions occurred at different levels. In the third group, only the peak amplitude of the Na+ current exhibited a clear inverted U-like function, but the inverse of the latency versus the electrical RNS, did not exhibit a clear inverted U-like function. A Hodgkin-Huxley neuron model reproduces our experimental results and shows that the observed behavior in the Na+ current could be due to the impact of RNS on the kinetics of activation and inactivation of the Na+ channels.

Differential frequency-dependent antidromic resonance of the Schaffer collaterals and mossy fibers.

To better understand information transfer along the hippocampal pathways and its plasticity, here we studied the antidromic responses of the dentate gyrus (DG) and CA3 to activation of the mossy fibers and Schaffer collaterals, respectively, in hippocampal slices from naïve and epileptic rats. We applied trains of 600 electrical stimuli at functionally meaningful frequencies (θ, ß/γ and γ). The responses of the DG to θ frequency trains underwent rapid potentiation that lasted about 400 stimuli, after which they progressively returned to control value. At ß/γ and γ frequencies, however, the initial potentiation was followed by a strong frequency-dependent depression within the first 50 stimuli. In kindled animals, the initial potentiation was stronger than in control preparations and the resonant phase at θ frequency lasted longer. In contrast, CA3 responses were exponentially depressed at all frequencies, but depression was significantly less intense at θ frequency in epileptic preparations. Failure of fibers to fire action potentials could account for some of the aforementioned characteristics, but waveforms of the intracellular action potentials also changed as the field responses did, i.e., half-duration and time-to-peak increased in both structures along the stimulation trains. Noteworthy, block of glutamate and GABA ionotropic receptors prevented resonance and reduced the depression of antidromic responses to ß/γ and γ stimulation recorded in the DG, but not in CA3. We show that the different behavior in the information transfer along these pathways depends on the frequency at which action potentials are generated, excitability history and anatomical features, including myelination and tortuosity. In addition, the mossy fibers are endowed with ionotropic receptors and terminal active properties conferring them their sui generis non-passive antidromic responses.

Improved detection of magnetic signals by a MEMS sensor using stochastic resonance.

We introduce the behavior of the electrical output response of a magnetic field sensor based on microelectromechanical systems (MEMS) technology under different levels of controlled magnetic noise. We explored whether a particular level of magnetic noise applied on the vicinity of the MEMS sensor can improve the detection of subthreshold magnetic fields. We examined the increase in the signal-to-noise ratio (SNR) of such detected magnetic fields as a function of the magnetic noise intensity. The data disclosed an inverted U-like graph between the SNR and the applied magnetic noise. This finding shows that the application of an intermediate level of noise in the environment of a MEMS magnetic field sensor improves its detection capability of subthreshold signals via the stochastic resonance phenomenon.

Reticular activating system of a central pattern generator: premovement electrical potentials.

For the first time, here we characterize a bulbar reticular activating system (RAS) of neurons in decerebrate, deafferented and decerebellated cats producing a premovement electrical potential that we named obex slow potential (OSP). The OSP occurs about 0.8 ± 0.4 sec prior to the onset of a fictive-scratching-episode. Here, we describe two classes of bulbar neurons, off-on, which are silent but exhibit a 80 ± 56 Hz firing discharge at the beginning of (and during) the OSP, and on-off interneurons, with a 27 ± 14 Hz firing activity that stops at the beginning of (and during) the OSP. We suggest that these OSP-associated neurons belong to a descending RAS, which contributes to the activation of the spinal central pattern generators.

Digital signal processing by virtual instrumentation of a MEMS magnetic field sensor for biomedical applications.

We present a signal processing system with virtual instrumentation of a MEMS sensor to detect magnetic flux density for biomedical applications. This system consists of a magnetic field sensor, electronic components implemented on a printed circuit board (PCB), a data acquisition (DAQ) card, and a virtual instrument. It allows the development of a semi-portable prototype with the capacity to filter small electromagnetic interference signals through digital signal processing. The virtual instrument includes an algorithm to implement different configurations of infinite impulse response (IIR) filters. The PCB contains a precision instrumentation amplifier, a demodulator, a low-pass filter (LPF) and a buffer with operational amplifier. The proposed prototype is used for real-time non-invasive monitoring of magnetic flux density in the thoracic cage of rats. The response of the rat respiratory magnetogram displays a similar behavior as the rat electromyogram (EMG).

Respiratory magnetogram detected with a MEMS device.

Magnetic fields generated by the brain or the heart are very useful in clinical diagnostics. Therefore, magnetic signals produced by other organs are also of considerable interest. Here we show first evidence that thoracic muscles can produce a strong magnetic flux density during respiratory activity, that we name respiratory magnetogram. We used a small magnetometer based on microelectromechanical systems (MEMS), which was positioned inside the open thoracic cage of anaesthetized and ventilated rats. With this new MEMS sensor of about 20 nT resolution, we recorded a strong and rhythmic respiratory magnetogram of about 600 nT.

Improved sensorimotor performance via stochastic resonance.

Several studies about noise-enhanced balance control in humans support the hypothesis that stochastic resonance can enhance the detection and transmission in sensorimotor system during a motor task. The purpose of the present study was to extend these findings in a simpler and controlled task. We explored whether a particular level of a mechanical Gaussian noise (0-15 Hz) applied on the index finger can improve the performance during compensation for a static force generated by a manipulandum. The finger position was displayed on a monitor as a small white point in the center of a gray circle. We considered a good performance when the subjects exhibited a low deviation from the center of this circle and when the performance had less variation over time. Several levels of mechanical noise were applied on the manipulandum. We compared the performance between zero noise (ZN), optimal noise (ON), and high noise (HN). In all subjects (8 of 8) the data disclosed an inverted U-like graph between the inverse of the mean variation in position and the input noise level. In other words, the mean variation was significantly smaller during ON than during ZN or HN. The findings suggest that the application of a tactile-proprioceptive noise can improve the stability in sensorimotor performance via stochastic resonance. Possible explanations for this improvement in motor precision are an increase of the peripheral receptors sensitivity and of the internal stochastic resonance, causing a better sensorimotor integration and an increase in corticomuscular synchronization.

Sensing magnetic flux density of artificial neurons with a MEMS device.

We describe a simple procedure to characterize a magnetic field sensor based on microelectromechanical systems (MEMS) technology, which exploits the Lorentz force principle. This sensor is designed to detect, in future applications, the spiking activity of neurons or muscle cells. This procedure is based on the well-known capability that a magnetic MEMS device can be used to sense a small magnetic flux density. In this work, an electronic neuron (FitzHugh-Nagumo) is used to generate controlled spike-like magnetic fields. We show that the magnetic flux density generated by the hardware of this neuron can be detected with a new MEMS magnetic field sensor. This microdevice has a compact resonant structure (700 × 600 × 5 µm) integrated by an array of silicon beams and p-type piezoresistive sensing elements, which need an easy fabrication process. The proposed microsensor has a resolution of 80 nT, a sensitivity of 1.2 V.T(-1), a resonant frequency of 13.87 kHz, low power consumption (2.05 mW), quality factor of 93 at atmospheric pressure, and requires a simple signal processing circuit. The importance of our study is twofold. First, because the artificial neuron can generate well-controlled magnetic flux density, we suggest it could be used to analyze the resolution and performance of different magnetic field sensors intended for neurobiological applications. Second, the introduced MEMS magnetic field sensor may be used as a prototype to develop new high-resolution biomedical microdevices to sense magnetic fields from cardiac tissue, nerves, spinal cord, or the brain.

An intersegmental neuronal architecture for spinal wave propagation under deletions.

Recent studies have established and characterized the propagation of traveling electrical waves along the cat spinal cord during scratching, but the neuronal architecture that allows for the persistence of such waves even during periods of absence of bursts of motoneuron activity (deletions) is still unclear. Here we address this problem both theoretically and experimentally. Specifically, we monitored during long lasting periods of time the global electrical activity of spinal neurons during scratching. We found clear deletions of unaltered cycle in extensor activity without associated deletions of the traveling spinal wave. Furthermore, we also found deletions with a perturbed cycle associated with a concomitant absence of the traveling spinal wave. Numerical simulations of an asymmetric two-layer model of a central-pattern generator distributed longitudinally along the spinal cord qualitatively reproduce the sinusoidal traveling waves, and are able to replicate both classes of deletions. We believe these findings shed light into the longitudinal organization of the central-pattern generator networks in the spinal cord.

Propagation of sinusoidal electrical waves along the spinal cord during a fictive motor task.

We present for the first time direct electrophysiological evidence of the phenomenon of traveling electrical waves produced by populations of interneurons within the spinal cord. We show that, during a fictive rhythmic motor task, scratching, an electrical field potential of spinal interneurons takes the shape of a sinuous wave, "sweeping" the lumbosacral spinal cord rostrocaudally with a mean speed of approximately 0.3 m/s. We observed that traveling waves and scratching have the same cycle duration and that duration of the flexor phase, but not of the extensor phase, is highly correlated with the cycle duration of the traveling waves. Furthermore, we found that the interneurons from the deep dorsal horn and the intermediate nucleus can generate the spinal traveling waves, even in the absence of motoneuronal activity. These findings show that the sinusoidal field potentials generated during fictive scratching could be a powerful tool to disclose the organization of central pattern generator networks.