Comparison of Giardia duodenalis point-of-care antigen faecal tests to reference laboratory assays in non-symptomatic dogs

Giardia duodenalis is one of the most prevalent enteric parasites of dogs. Point-of-care antigen tests (POC) are rapid and do not require additional equipment, or a specialised diagnostic laboratory. The aim of this study was to compare diagnostic tests available in veterinary practices and in a diagnostic laboratory for the detection of G. duodenalis on a cohort of group-housed dogs from New South Wales, Australia. Two different POC tests were used for the detection of G. duodenalis. Laboratory tests used were the multiplexed-tandem PCR panel (MT-PCR) that includes detection of G. duodenalis DNA, and two reference tests (an in-house TaqMan real-time PCR and a direct immunofluorescence assay, DFA). Canine faecal samples (n = 40) were tested simultaneously for the detection of G. duodenalis. Using either DFA or TaqMan real-time PCR as reference tests, 77.5% (31/40) and 82.5% (33/40) of dogs tested positive, respectively. Agreement (Kappa) between the DFA and TaqMan real-time PCR was 0.84 (95% CI 0.64 to 1.00). There was substantial G. duodenalis test outcome agreement between the two POC tests, Kappa = 0.75. Combining the two POC tests yielded 77% sensitivity and 100% specificity with DFA as reference, and for TaqMan real-time PCR it was 73% sensitivity and 100% specificity. The MT-PCR was in excellent agreement with each reference test, DFA or TaqMan real-time PCR. Due to the high specificity of both POC tests, they can be confidently used as rule-in diagnostics. Confirmatory testing that detects different biological parameters such as DNA, e.g. PCR (inc. MT-PCR), should be implemented before concluding that a dog is negative for the presence of G. duodenalis.

Multifractality in stride-to-stride variations reveals that walking involves more movement tuning and adjusting than running

Introduction: The seemingly periodic human gait exhibits stride-to-stride variations as it adapts to the changing task constraints. The optimal movement variability hypothesis (OMVH) states that healthy stride-to-stride variations exhibit "fractality"-a specific temporal structure in consecutive strides that are ordered, stable but also variable, and adaptable. Previous research has primarily focused on a single fractality measure, "monofractality." However, this measure can vary across time; strideto-stride variations can show "multifractality." Greater multifractality in stride-tostride variations would highlight the ability to tune and adjust movements more. Methods: We investigated monofractality and multifractality in a cohort of eight healthy adults during self-paced walking and running trials, both on a treadmill and overground. Footfall data were collected through force-sensitive sensors positioned on their heels and feet. We examined the effects of self-paced walking vs. running and treadmill vs. overground locomotion on the measure of monofractality, α-DFA, in addition to the multifractal spectrum width, W, and the asymmetry in the multifractal spectrum, WAsym, of stride interval time series. Results: While the α-DFA was larger than 0.50 for almost all conditions, α-DFA was higher in running and locomoting overground than walking and locomoting on a treadmill. Similarly, W was greater while locomoting overground than on a treadmill, but an opposite trend indicated that W was greater in walking than running. Larger WAsym values in the negative direction suggest that walking exhibits more variation in the persistence of shorter stride intervals than running. However, the ability to tune and adjust movements does not differ between treadmill and overground, although both exhibit more variation in the persistence of shorter stride intervals. Discussion: Hence, greater heterogeneity in shorter than longer stride intervals contributed to greater multifractality in walking compared to running, indicated by larger negative WAsym values. Our results highlight the need to incorporate multifractal methods to test the predictions of the OMVH.

Entropy-Based Multifractal Testing of Heart Rate Variability during Cognitive-Autonomic Interplay

Entropy-based and fractal-based metrics derived from heart rate variability (HRV) have enriched the way cardiovascular dynamics can be described in terms of complexity. The most commonly used multifractal testing, a method using q moments to explore a range of fractal scaling in small-sized and large-sized fluctuations, is based on detrended fluctuation analysis, which examines the power-law relationship of standard deviation with the timescale in the measured signal. A more direct testing of a multifractal structure exists based on the Shannon entropy of bin (signal subparts) proportion. This work aims to reanalyze HRV during cognitive tasks to obtain new markers of HRV complexity provided by entropy-based multifractal spectra using the method proposed by Chhabra and Jensen in 1989. Inter-beat interval durations (RR) time series were obtained in 28 students comparatively in baseline (viewing a video) and during three cognitive tasks: Stroop color and word task, stop-signal, and go/no-go. The new HRV estimators were extracted from the f/α singularity spectrum of the RR magnitude increment series, established from q-weighted stable (log-log linear) power laws, namely: (i) the whole spectrum width (MF) calculated as αmax - αmin; the specific width representing large-sized fluctuations (MFlarge) calculated as α0 - αq+; and small-sized fluctuations (MFsmall) calculated as αq- - α0. As the main results, cardiovascular dynamics during Stroop had a specific MF signature while MFlarge was rather specific to go/no-go. The way these new HRV markers could represent different aspects of a complete picture of the cognitive-autonomic interplay is discussed, based on previously used entropy- and fractal-based markers, and the introduction of distribution entropy (DistEn), as a marker recently associated specifically with complexity in the cardiovascular control.

Effects of Motor Task Difficulty on Postural Control Complexity during Dual Tasks in Young Adults: A Nonlinear Approach

Few studies have evaluated the effect of a secondary motor task on the standing posture based on nonlinear analysis. However, it is helpful to extract information related to the complexity, stability, and adaptability to the environment of the human postural system. This study aimed to analyze the effect of two motor tasks with different difficulty levels in motor performance complexity on the static standing posture in healthy young adults. Thirty-five healthy participants (23.08 ± 3.92 years) performed a postural single task (ST: keep a quiet standing posture) and two motor dual tasks (DT). i.e., mot-DT(A)—perform the ST while performing simultaneously an easy motor task (taking a smartphone out of a bag, bringing it to the ear, and putting it back in the bag)—and mot-DT(T)—perform the ST while performing a concurrent difficult motor task (typing on the smartphone keyboard). The approximate entropy (ApEn), Lyapunov exponent (LyE), correlation dimension (CoDim), and fractal dimension (detrending fluctuation analysis, DFA) for the mediolateral (ML) and anterior-posterior (AP) center-of-pressure (CoP) displacement were measured with a force plate while performing the tasks. A significant difference was found between the two motor dual tasks in ApEn, DFA, and CoDim-AP (p < 0.05). For the ML CoP direction, all nonlinear variables in the study were significantly different (p < 0.05) between ST and mot-DT(T), showing impairment in postural control during mot-DT(T) compared to ST. Differences were found across ST and mot-DT(A) in ApEn-AP and DFA (p < 0.05). The mot-DT(T) was associated with less effectiveness in postural control, a lower number of degrees of freedom, less complexity and adaptability of the dynamic system than the postural single task and the mot-DT(A).

Exposure, but not timing of exposure, to a sulfonylurea herbicide alters larval development and behaviour in an amphibian species

Environmental contamination is one of the major causes of biodiversity loss. Wetlands are particularly susceptible to contamination and species inhabiting these habitats are subjected to pollutants during sensitive phases of their development. In this study, tadpoles of a widespread amphibian, the spined toad (Bufo spinosus), were exposed to environmental concentrations of nicosulfuron (0 μg/L; 0.15 ± 0.05 μg/L and 0.83 ± 0.04 μg/L), a sulfonylurea herbicide, during different phases of development. Tadpoles were exposed during embryonic (12.98 ± 0.90 days) or larval development (93.74± 0.85 days), or throughout both phases, and we quantified development duration, morphological traits and behavioural features as responses to exposure. Developing tadpoles exposed to nicosulfuron were larger, but with smaller body, and had shorter but wider tail muscles. They were also more active and swam faster than control tadpoles and showed diverging patterns of behavioural complexity. We showed that higher concentrations had greater effects on individuals than lower concentrations, but the timing of nicosulfuron exposure did not influence the metrics studied: Exposure to nicosulfuron triggered similar effects irrespective of the developmental stages at which exposure occurred. These results further indicate that transient exposure (e.g., during embryonic development) can induce long-lasting effects throughout larval development to metamorphosis. Our study confirms that contaminants at environmental concentrations can have strong consequences on non-target organisms. Our results emphasize the need for regulation agencies and policy makers to consider sublethal concentrations of sulfonulyrea herbicides, such as nicosulfuron, as a minimum threshold in their recommendations.

Long-range correlations and stride pattern variability in recreational and elite distance runners during a prolonged run

BACKGROUND

Although movement variability and long-range correlations (LRCs) have been assessed in relation to neuropathology and aging during walking, to date only a few studies have investigated these aspects in subjects of different skill levels during prolonged overground running.

RESEARCH QUESTION

What effect does skill level and run duration have on different stride parameters, measures of variability and long-range correlations?

METHODS

Using a between-subject repeated measures design, we assessed stride mechanics, variability and LRCs in recreational and elite runners over the course of a continuous exhaustive run. All subjects ran at a fixed, pre-determined running speed relative to their maximal performance. Stride parameters were continually recorded using a single foot-mounted inertial measurement unit. It was hypothesized that a significant reduction in the strength of the LRCs would occur over the course of the run and that the observed changes would be more pronounced in the group of recreational runners.

RESULTS

Runners maintained a consistent stride length (SL), stride time (ST) and contact time (CT) during the run, while peak impact acceleration increased. Across groups, long-range correlations significantly decreased over the course of the run, while the magnitude of the variability remained constant. LRCs did not differ significantly between groups.

SIGNIFICANCE

This is the first study to simultaneously investigate the effects of prolonged running and skill level on a range of stride parameters as well as stride-to-stride variability. Generally, long-range correlations were shown to be sensitive to run duration, while the magnitude of the variability did not differ between earlier and later stages of the run. The lack of a group effect on LRCs supports the idea that the mechanisms responsible for the emergence of temporal patterns in the stride pattern are not influenced by skill level.

A Comprehensive Diagnosis Method of Rolling Bearing Fault Based on CEEMDAN-DFA-Improved Wavelet Threshold Function and QPSO-MPE-SVM

A comprehensive fault diagnosis method of rolling bearing about noise interference, fault feature extraction, and identification was proposed. Based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), detrended fluctuation analysis (DFA), and improved wavelet thresholding, a denoising method of CEEMDAN-DFA-improved wavelet threshold function was presented to reduce the distortion of the noised signal. Based on quantum-behaved particle swarm optimization (QPSO), multiscale permutation entropy (MPE), and support vector machine (SVM), the QPSO-MPE-SVM method was presented to construct the fault-features sets and realize fault identification. Simulation and experimental platform verification showed that the proposed comprehensive diagnosis method not only can better remove the noise interference and maintain the original characteristics of the signal by CEEMDAN-DFA-improved wavelet threshold function, but also overcome overlapping MPE values by the QPSO-optimizing MPE parameters to separate the features of different fault types. The experimental results showed that the fault identification accuracy of the fault diagnosis can reach 95%, which is a great improvement compared with the existing methods.

Breaking Trivium Stream Cipher Implemented in ASIC Using Experimental Attacks and DFA

One of the best methods to improve the security of cryptographic systems used to exchange sensitive information is to attack them to find their vulnerabilities and to strengthen them in subsequent designs. Trivium stream cipher is one of the lightweight ciphers designed for security applications in the Internet of things (IoT). In this paper, we present a complete setup to attack ASIC implementations of Trivium which allows recovering the secret keys using the active non-invasive technique attack of clock manipulation, combined with Differential Fault Analysis (DFA) cryptanalysis. The attack system is able to inject effective transient faults into the Trivium in a clock cycle and sample the faulty output. Then, the internal state of the Trivium is recovered using the DFA cryptanalysis through the comparison between the correct and the faulty outputs. Finally, a backward version of Trivium was also designed to go back and get the secret keys from the initial internal states. The key recovery has been verified with numerous simulations data attacks and used with the experimental data obtained from the Application Specific Integrated Circuit (ASIC) Trivium. The secret key of the Trivium were recovered experimentally in 100% of the attempts, considering a real scenario and minimum assumptions.

Treadmill-belt width, but not feedback from the lower visual field, influences the noise characteristics of step width time series

Step kinematic variability, which has been associated with gait-related fall risk, is thought to be attributed to neuromotor noise. Altered neuromotor control of step kinematics would be expected to manifest as changes in the noise-related characteristics of the step kinematic time series. This study determined the effects of eliminating feedback from the lower visual field and reducing treadmill-belt width on the noise characteristics of step width time series and statistical measures of step width variability during treadmill walking. We hypothesized that eliminating feedback from the lower visual field and reducing treadmill-belt width would both alter the noise characteristics of step width time series, reflected by decreased fractal scaling, and increase statistical measures of step width variability. Eighteen young adults performed four randomly ordered walking trials during which we manipulated visual feedback from the lower visual field (normal and obstructed) and treadmill-belt width (wide and narrow). Reducing treadmill-belt width, but not eliminating feedback from the lower visual field, significantly reduced the fractal scaling of step width time series, indicating a shift towards white, uncorrelated noise. These results suggest that accounting for the influence of treadmill-belt width on step width time series may be an important consideration in both laboratory and clinical settings. Further work is needed to clarify the effects of vision on measures of step width, identify the mechanism(s) underlying the observed shift towards white, uncorrelated noise associated with reduced treadmill-belt width, and to assess the potential relationship between the noise characteristics of step width time series and fall risk.

On the Face of It: No Differential Sensitivity to Internal Facial Features in the Dog Brain

Dogs are looking at and gaining information from human faces in a variety of contexts. Next to behavioral studies investigating the topic, recent fMRI studies reported face sensitive brain areas in dogs' temporal cortex. However, these studies used whole heads as stimuli which contain both internal (eyes, nose, mouth) and external facial features (hair, chin, face-outline). Behavioral studies reported that (1) recognition of human faces by dogs requires visibility of head contour and that (2) dogs are less successful in recognizing their owners from 2D pictures than from real human heads. In contrast, face perception in humans heavily depends on internal features and generalizes to 2D images. Whether putative face sensitive regions in dogs have comparable properties to those of humans has not been tested so far. In two fMRI experiments, we investigated (1) the location of putative face sensitive areas presenting only internal features of a real human face vs. a mono-colored control surface and (2) whether these regions show higher activity toward live human faces and/or static images of those faces compared to scrambled face images, all with the same outline. In Study 1 (n = 13) we found strong activity for faces in multiple regions, including the previously described temporo-parietal and occipital regions when the control was a mono-colored, homogeneous surface. These differences disappeared in Study 2 (n = 11) when we compared faces to scrambled faces, controlling for low-level visual cues. Our results do not support the assumption that dogs rely on a specialized brain region for processing internal facial characteristics, which is in line with the behavioral findings regarding dogs inability to recognize human faces based on these features.

Influence of Glutathione and Ascorbic Acid Treatments during Vinification of Feteasca Regala Variety and Their Antioxidant Effect on Volatile Profile

Volatile profiles were determined for white wines of Feteasca regala variety produced from musts in which the antioxidants glutathione and ascorbic acid were added in different proportions before inception of alcoholic fermentation. Treatments with these antioxidants affect some volatile compound evolution and positively influence the wine volatile profile. After one year of storage in bottles with and without carbon dioxide protection the volatile profiles of the wines were assessed by using a Fast GC Alpha MOS Heracles e-Nose by applying a DFA multivariate statistical method and AroChemBase database for compound identification. The analyses showed that some higher alcohols, such as 2-phenylethanol and 2-methyl-1-butanol were in lower concentrations in wines treated with reduced glutathione, while the main ethyl fatty acid esters, such as ethyl butanoate, ethyl hexanoate, ethyl octanoate, and ethyl decanoate were better preserved when higher concentrations of any of the antioxidants were added in must. On the other hand, it was observed that some other volatile compounds were not affected by these applied treatments.

Host factors associated with Giardia duodenalis infection in dogs across multiple diagnostic tests

Background

The aim of this study was to assess potential associations between Giardia duodenalis infection in dogs, as determined by three diagnostic tests, and dog’s group of origin, fecal consistency, age, sex, neuter status, and co-infections with other gastrointestinal parasites.

Methods

Fecal samples from 1291 dogs from four groups (household, shelter, hunting and clinical dogs) were tested with qPCR, rapid enzyme immunochromatographic assay (IDEXX SNAP^®Giardia), and direct immunofluorescence (DFA, Merifluor) for presence of G. duodenalis. Moreover, fecal samples were tested with centrifugation sedimentation flotation (CSF) coproscopical analysis for presence of gastrointestinal parasites. Associations were expressed as odds ratios (ORs).

Results

Several significant associations were found, of which a few were consistent for all three tests and Giardia positivity in general (positive with at least one of these tests). Dogs older than one year were significantly less likely to test positive for Giardia than younger dogs. Group-housed dogs, especially hunting dogs, were significantly more likely to test positive for Giardia compared to household and clinical dogs. A consistently significant association with Trichuris appeared to be driven by the high prevalence in hunting dogs. Although there was no significant association between loose stool and Giardia infection in the overall population, household dogs were significantly more likely to test Giardia-positive when having loose stool. Overall, Giardia-positive dogs with loose stool shed significantly more cysts, both determined semi-quantitatively with CSF and quantitatively by qPCR, than positive dogs with no loose stool. When other gastrointestinal parasites were present, significantly fewer cysts were detected with CSF, but this was not confirmed with qPCR.

Conclusion

Giardia is the most common gastrointestinal parasite in Dutch dogs, except for hunting dogs, in which Trichuris and strongyle-type eggs (hookworms) prevailed. Giardia infection was not significantly associated with loose stool, except for household dogs. Young dogs and group-housed dogs were significantly more often Giardia-positive. These associations were consistent across diagnostic tests. Young dogs, clinical dogs and dogs with loose stool shed Giardia cysts in the highest numbers. If another gastrointestinal parasite was present lower numbers of cysts were observed by microscope (CSF), but not with a molecular method (qPCR).

Characterization of statistical persistence in joint angle variation during walking

The objective of this study was to characterize joint angle variation across strides. Specifically, the statistical persistence of variations were quantified using the Hurst exponent. If a time series exhibits statistical persistence, then a parameter which is smaller (or larger) than average will tend to be followed by additional values that are also smaller (or larger) than average. Human walking has statistical persistence between stride durations. Variation in stride duration must arise from variation in the motion of the leg segments during walking. It is unclear, however, if the joint angle variation also exhibits statistical persistence. This study examined kinematic data collected from nine healthy adults walking for 10 min at a self-selected comfortable speed on a treadmill. The joint angle variation in the lower limbs was parameterized using first-order Fourier series which in turn were described by frequency and magnitude coefficients for each stride. To determine if the joint angle variation exhibited statistical persistence, the Hurst exponent was found for each coefficient at each joint. The mean Hurst exponents were 0.54 for the frequency coefficients and 0.61 for the magnitude coefficients. Neither the frequency or magnitude coefficients exhibited statistically significant persistence, although some of the magnitude coefficients were close to reaching statistical significance. This suggests that joint angle variability in healthy adults does not directly produce the statistical persistence observed in stride duration fluctuations.

High sensitivity LC-MS profiling of antibody-drug conjugates with difluoroacetic acid ion pairing

Reversed-phase liquid chromatography (RPLC) separations of proteins using optical detection generally use trifluoroacetic acid (TFA) because it is a strong, hydrophobic acid and a very effective ion-pairing agent for minimizing chromatographic secondary interactions. Conversely and in order to avoid ion suppression, analyses entailing mass spectrometry (MS) detection is often performed with a weaker ion-pairing modifier, like formic acid (FA), but resolution quality may be reduced. To gain both the chromatographic advantages of TFA and the enhanced MS sensitivity of FA, we explored the use of an alternative acid, difluoroacetic acid (DFA). This acid modifier is less acidic and less hydrophobic than TFA and is believed to advantageously affect the surface tension of electrospray droplets. Thus, it is possible to increase MS sensitivity threefold by replacing TFA with DFA. Moreover, we have observed DFA ion pairing to concomitantly produce higher chromatographic resolution than FA and even TFA. For this reason, we prepared and used MS-quality DFA in place of FA and TFA in separations involving IdeS digested, reduced NIST mAb and a proprietary antibody-drug conjugate (ADC), aiming to increase sensitivity, resolution and protein recovery. The resulting method using DFA was qualified and applied to two other ADCs and gave heightened sensitivity, resolution and protein recovery versus analyses using TFA. This new method, based on a purified, trace metal free DFA, can potentially become a state-of-the-art liquid chromatography-MS technique for the deep characterization of ADCs.

Fatigue-Mediated Loss of Complexity is Contraction-Type Dependent in Vastus Lateralis Electromyographic Signals

The purpose of this study was to investigate the effect of fatigue status and contraction type on complexity of the surface electromyographic (sEMG) signal. Twelve females (mean age ± SD = 21.1 ± 1.4 years) performed three fatigue-inducing protocols that involved maximal concentric, eccentric, or isometric knee-extensor contractions over three non-consecutive sessions. Pre- and post-fatigue assessments were also completed each session and consisted of three maximal efforts for each type of contraction. Complexity of sEMG signals from the vastus lateralis was assessed using Sample Entropy (SampEn) and Detrended Fluctuation Analysis (DFA) as expressed using the scaling exponent α. The results showed that fatigue decreased (p < 0.05) sEMG complexity as indicated by decreased SampEn (non-fatigued: 1.57 ± 0.22 > fatigued: 1.46 ± 0.25) and increased DFA α (non-fatigued: 1.27 ± 0.26 < fatigued: 1.32 ± 0.23). In addition, sEMG complexity was different among contraction types as indicated by SampEn (concentric: 1.58 ± 0.22 > eccentric: 1.47 ± 0.27 and isometric: 1.50 ± 0.21) and DFA α (concentric: 1.27 ± 0.18 < isometric: 1.32 ± 0.18). Thus, these findings suggested sEMG complexity is affected by fatigue status and contraction type, with the degree of fatigue-mediated loss of complexity dependent on the type of contraction used to elicit fatigue.

Evidence for the Formation of Difluoroacetic Acid in Chlorofluorocarbon-Contaminated Ground Water

The concentrations of difluoroacetic acid (DFA) and trifluoroacetic acid (TFA) in rainwater and surface water from Berlin, Germany resembled those reported for similar urban areas, and the TFA/DFA ratio in rainwater of 10:1 was in accordance with the literature. In contrast, nearby ground water historically contaminated with 1,1,2-trichloro-1,2,2-trifluoroethane (R113) displayed a TFA/DFA ratio of 1:3. This observation is discussed versus the inventory of microbial degradation products present in this ground water along with the parent R113 itself. A microbial transformation of chlorotrifluoroethylene (R1113) to DFA so far has not been reported for environmental media, and is suggested based on well-established mammalian metabolic pathways.

Variation in the skull morphometry of four taxonomic units of Thrichomys (Rodentia: Echimyidae), from different Neotropical biomes

The echimyid rodents of the genus Thrichomys vary considerably in their behavior and feeding ecology, reflecting their occurrence in environments as different as the Caatinga, Cerrado, Pantanal, and Chaco biomes. While the genus was originally classified as monospecific, a number of Thrichomys species have been recognized in recent decades, based on morphometric, cytogenetic, and molecular analyses. While Thrichomys is well studied, the variation found in its cranial morphology is poorly understood, given the taxonomic and ecological complexities of the genus. Using a geometric morphometric approach, we characterized the differences found in the cranial morphology of four Thrichomys taxonomic units, including three established species, Thrichomys apereoides, Thrichomys fosteri, and Thrichomys laurentius, and one operational taxonomic unit (OTU), Thrichomys aff. laurentius. No significant differences were found among these units in cranium size, but significant variation was found in skull shape. The Procrustes distances provided a quantification of the differences in the shape of the skull, with the largest distances being found between T. aff. laurentius and T. fosteri in the dorsal view, and between T. aff. laurentius and T. apereoides in the ventral view. A Discriminant Function Analysis (DFA) with cross-validation determined that the pairings with the highest correct classification were T. aff. laurentius vs. T. apereoides and T. aff. laurentius vs. T. fosteri, in both views. The principal variation in skull shape was found in the posterior region and the zygomatic arch, which may be related to differences in diet.

Effects of a Short-Term Cycling Interval Session and Active Recovery on Non-Linear Dynamics of Cardiac Autonomic Activity in Endurance Trained Cyclists

Measurement of the non-linear dynamics of physiologic variability in a heart rate time series (HRV) provides new opportunities to monitor cardiac autonomic activity during exercise and recovery periods. Using the Detrended Fluctuation Analysis (DFA) technique to assess correlation properties, the present study examines the influence of exercise intensity and recovery on total variability and complexity in the non-linear dynamics of HRV. Sixteen well-trained cyclists performed interval sessions with active recovery periods. During exercise, heart rate (HR) and beat-to-beat (RR)-intervals were recorded continuously. HRV time domain measurements and fractal correlation properties were analyzed using the short-term scaling exponent alpha1 of DFA. Lactate (La) levels and the rate of perceived exertion (RPE) were also recorded at regular time intervals. HR, La, and RPE showed increased values during the interval blocks (p < 0.05). In contrast, meanRR and DFA-alpha1 showed decreased values during the interval blocks (p < 0.05). Also, DFA-alpha1 increased to the level in the warm-up periods during active recovery (p < 0.05) and remained unchanged until the end of active recovery (p = 1.000). The present data verify a decrease in the overall variability, as well as a reduction in the complexity of the RR-interval-fluctuations, owing to increased organismic demands. The acute increase in DFA-alpha1 following intensity-based training stimuli in active recovery may be interpreted as a systematic reorganization of the organism with increased correlation properties in cardiac autonomic activity in endurance trained cyclists.

Detection of lyssavirus antigen and antibody levels among apparently healthy and suspected rabid dogs in South-Eastern Nigeria

OBJECTIVES

Domestic dogs are the main reservoir of rabies virus (RABV) infection in Nigeria, thus surveillance of rabies in dog populations is crucial in order to understand the patterns of spread of infection and ultimately devise an appropriate rabies control strategy. This study determined the presence of lyssavirus antigen in brain tissues and anti-rabies antibodies in sera of apparently healthy and suspected-rabid dogs slaughtered for human consumption at local markets in South-Eastern Nigeria.

RESULTS

Our findings demonstrated that 8.3% (n = 23) of brain tissues were lyssavirus positive and 2.5% (n = 25) of sera had rabies antibody levels as percentage blocking of 70% and above correlating with a cut-off value ≥ 0.5 IU/mL in the fluorescent antibody neutralization test. There was an inverse correlation between lyssavirus positivity and rabies antibody levels confirming that infected individuals most often do not develop virus neutralizing antibodies to the disease. The low percentage of rabies antibodies in this dog population suggests a susceptible population at high risk to RABV infection. These findings highlight a huge challenge to national rabies programs and subsequent elimination of the disease from Nigeria, considering that majority of dogs are confined to rural communal areas, where parenteral dog vaccination is not routinely undertaken.

Strong long-range temporal correlations of beta/gamma oscillations are associated with poor sustained visual attention performance

Neuronal oscillations exhibit complex amplitude fluctuations with autocorrelations that persist over thousands of oscillatory cycles. Such long-range temporal correlations (LRTC) are thought to reflect neuronal systems poised near a critical state, which would render them capable of quick reorganization and responsive to changing processing demands. When we concentrate, however, the influence of internal and external sources of distraction is better reduced, suggesting that neuronal systems involved with sustained attention could benefit from a shift toward the less volatile sub-critical state. To test these ideas, we recorded electroencephalography (EEG) from healthy volunteers during eyes-closed rest and during a sustained attention task requiring a speeded response to images deviating in their presentation duration. We show that for oscillations recorded during rest, high levels of alpha-band LRTC in the sensorimotor region predicted good reaction-time performance in the attention task. During task execution, however, fast reaction times were associated with high-amplitude beta and gamma oscillations with low LRTC. Finally, we show that reduced LRTC during the attention task compared to the rest condition correlates with better performance, while increased LRTC of oscillations from rest to attention is associated with reduced performance. To our knowledge, this is the first empirical evidence that 'resting-state criticality' of neuronal networks predicts swift behavioral responses in a sensorimotor task, and that steady attentive processing of visual stimuli requires brain dynamics with suppressed temporal complexity.

Sign and magnitude scaling properties of heart rate fluctuations following vagus nerve stimulation in a patient with drug-resistant epilepsy

Vagus nerve stimulation (VNS) therapy has been recently incorporated in Latin America as a treatment for drug-resistant epilepsy. In particular, it is known that linear analysis and fractal parameters of heart rate variability (HRV) are able to indirectly measure cardiac autonomic activity. This case report presents a 17-year-old female with drug-resistant epilepsy implanted with a VNS device. In order to explore cardiac autonomic changes due to VNS, linear and fractal HRV indices were calculated in the presence and absence of neurostimulation. Novel fractal scaling exponents from HRV analysis were obtained from this patient and from a healthy control subject. Our results indicate that fractal indices of HRV, such as short-term scaling parameters from magnitude and sign analyses seem to be sensitive to the presence or absence of VNS, being confirmed by linear classical methods. This study shows that VNS therapy increases the complexity of cardiac fluctuations in a patient with drug-resistant epilepsy, reflecting an augmented HRV non-linearity and a diminished anticorrelated pattern in heart rate fluctuations. A potential clinical use of these parameters includes the early identification of bradycardia, sudden unexpected death (SUDEP) risk and preoperative VNS approaches. Thus, the scaling and magnitude properties of HRV have potential importance as a non-invasive and easy method for adequate diagnostic/prognostic implications in epilepsy treatment.

The Color of Noise and Weak Stationarity at the NREM to REM Sleep Transition in Mild Cognitive Impaired Subjects

In Older Adults (OAs), Electroencephalogram (EEG) slowing in frontal lobes and a diminished muscle atonia during Rapid Eye Movement sleep (REM) have each been effective tracers of Mild Cognitive Impairment (MCI), but this relationship remains to be explored by non-linear analysis. Likewise, data provided by EEG, EMG (Electromyogram) and EOG (Electrooculogram)—the three required sleep indicators—during the transition from REM to Non-REM (NREM) sleep have not been related jointly to MCI. Therefore, the main aim of the study was to explore, with results for Detrended Fluctuation Analysis (DFA) and multichannel DFA (mDFA), the Color of Noise (CN) at the NREM to REM transition in OAs with MCI vs. subjects with good performances. The comparisons for the transition from NREM to REM were made for each group at each cerebral area, taking bilateral derivations to evaluate interhemispheric coupling and anteroposterior and posterior networks. In addition, stationarity analysis was carried out to explore if the three markers distinguished between the groups. Neuropsi and the Mini-Mental State Examination (MMSE) were administered, as well as other geriatric tests. One night polysomnography was applied to 6 OAs with MCI (68.1 ± 3) and to 7 subjects without it (CTRL) (64.5 ± 9), and pre-REM and REM epochs were analyzed for each subject. Lower scores for attention, memory and executive funcions and a greater index of arousals during sleep were found for the MCI group. Results confirmed that EOGs constituted significant markers of MCI, increasing the CN for the MCI group in REM sleep. The CN of the EEG from the pre-REM to REM was higher for the MCI group vs. the opposite for the CTRL group at frontotemporal areas. Frontopolar interhemispheric scaling values also followed this trend as well as right anteroposterior networks. EMG Hurst values for both groups were lower than those for EEG and EOG. Stationarity analyses showed differences between stages in frontal areas and right and left EOGs for both groups. These results may demonstrate the breakdown of fractality of areas especially involved in executive functioning and the way weak stationarity analyses may help to distinguish between sleep stages in OAs.

Frequency-Specific Fractal Analysis of Postural Control Accounts for Control Strategies

Diverse indicators of postural control in Humans have been explored for decades, mostly based on the trajectory of the center-of-pressure. Classical approaches focus on variability, based on the notion that if a posture is too variable, the subject is not stable. Going deeper, an improved understanding of underlying physiology has been gained from studying variability in different frequency ranges, pointing to specific short-loops (proprioception), and long-loops (visuo-vestibular) in neural control. More recently, fractal analyses have proliferated and become useful additional metrics of postural control. They allowed identifying two scaling phenomena, respectively in short and long timescales. Here, we show that one of the most widely used methods for fractal analysis, Detrended Fluctuation Analysis, could be enhanced to account for scalings on specific frequency ranges. By computing and filtering a bank of synthetic fractal signals, we established how scaling analysis can be focused on specific frequency components. We called the obtained method Frequency-specific Fractal Analysis (FsFA) and used it to associate the two scaling phenomena of postural control to proprioceptive-based control loop and visuo-vestibular based control loop. After that, convincing arguments of method validity came from an application on the study of unaltered vs. altered postural control in athletes. Overall, the analysis suggests that at least two timescales contribute to postural control: a velocity-based control in short timescales relying on proprioceptive sensors, and a position-based control in longer timescales with visuo-vestibular sensors, which is a brand-new vision of postural control. Frequency-specific scaling exponents are promising markers of control strategies in Humans.

Introducing Statistical Persistence Decay: A Quantification of Stride-to-Stride Time Interval Dependency in Human Gait

Stride-to-stride time intervals during human walking are characterised by predictability and statistical persistence quantified by sample entropy (SaEn) and detrended fluctuation analysis (DFA) which indicates a time dependency in the gait pattern. However, neither analyses quantify time dependency in a physical or physiological interpretable time scale. Recently, entropic half-life (ENT½) has been introduced as a measure of the time dependency on an interpretable time scale. A novel measure of time dependency, based on DFA, statistical persistence decay (SPD), was introduced. The present study applied SaEn, DFA, ENT½, and SPD in known theoretical signals (periodic, chaotic, and random) and stride-to-stride time intervals during overground and treadmill walking in healthy subjects. The analyses confirmed known properties of the theoretical signals. There was a significant lower predictability (p = 0.033) and lower statistical persistence (p = 0.012) during treadmill walking compared to overground walking. No significant difference was observed for ENT½ and SPD between walking condition, and they exhibited a low correlation. ENT½ showed that predictability in stride time intervals was halved after 11-14 strides and SPD indicated that the statistical persistency was deteriorated to uncorrelated noise after ~50 strides. This indicated a substantial time memory, where information from previous strides affected the future strides.

Cortical Contribution to Linear, Non-linear and Frequency Components of Motor Variability Control during Standing

Motor variability is an inherent feature of all human movements and reflects the quality of functional task performance. Depending on the requirements of the motor task, the human sensory-motor system is thought to be able to flexibly govern the appropriate level of variability. However, it remains unclear which neurophysiological structures are responsible for the control of motor variability. In this study, we tested the contribution of cortical cognitive resources on the control of motor variability (in this case postural sway) using a dual-task paradigm and furthermore observed potential changes in control strategy by evaluating Ia-afferent integration (H-reflex). Twenty healthy subjects were instructed to stand relaxed on a force plate with eyes open and closed, as well as while trying to minimize sway magnitude and performing a "subtracting-sevens" cognitive task. In total 25 linear and non-linear parameters were used to evaluate postural sway, which were combined using a Principal Components procedure. Neurophysiological response of Ia-afferent reflex loop was quantified using the Hoffman reflex. In order to assess the contribution of the H-reflex on the sway outcome in the different standing conditions multiple mixed-model ANCOVAs were performed. The results suggest that subjects were unable to further minimize their sway, despite actively focusing to do so. The dual-task had a destabilizing effect on PS, which could partly (by 4%) be counter-balanced by increasing reliance on Ia-afferent information. The effect of the dual-task was larger than the protective mechanism of increasing Ia-afferent information. We, therefore, conclude that cortical structures, as compared to peripheral reflex loops, play a dominant role in the control of motor variability.

What Is the Contribution of Ia-Afference for Regulating Motor Output Variability during Standing?

Motor variability is an inherent feature of all human movements, and describes the system's stability and rigidity during the performance of functional motor tasks such as balancing. In order to ensure successful task execution, the nervous system is thought to be able to flexibly select the appropriate level of variability. However, it remains unknown which neurophysiological pathways are utilized for the control of motor output variability. In responding to natural variability (in this example sway), it is plausible that the neuro-physiological response to muscular elongation contributes to restoring a balanced upright posture. In this study, the postural sway of 18 healthy subjects was observed while their visual and mechano-sensory system was perturbed. Simultaneously, the contribution of Ia-afferent information for controlling the motor task was assessed by means of H-reflex. There was no association between postural sway and Ia-afference in the eyes open condition, however up to 4% of the effects of eye closure on the magnitude of sway can be compensated by increased reliance on Ia-afference. Increasing the biomechanical demands by adding up to 40% bodyweight around the trunk induced a specific sway response, such that the magnitude of sway remained unchanged but its dynamic structure became more regular and stable (by up to 18%). Such regular sway patterns have been associated with enhanced cognitive involvement in controlling motor tasks. It therefore appears that the nervous system applies different control strategies in response to the perturbations: The loss of visual information is compensated by increased reliance on other receptors; while the specific regular sway pattern associated with additional weight-bearing was independent of Ia-afferent information, suggesting the fundamental involvement of supraspinal centers for the control of motor output variability.

Real time QRS complex detection using DFA and regular grammar

Background

The sequence of Q, R, and S peaks (QRS) complex detection is a crucial procedure in electrocardiogram (ECG) processing and analysis. We propose a novel approach for QRS complex detection based on the deterministic finite automata with the addition of some constraints. This paper confirms that regular grammar is useful for extracting QRS complexes and interpreting normalized ECG signals. A QRS is assimilated to a pair of adjacent peaks which meet certain criteria of standard deviation and duration.

Results

The proposed method was applied on several kinds of ECG signals issued from the standard MIT-BIH arrhythmia database. A total of 48 signals were used. For an input signal, several parameters were determined, such as QRS durations, RR distances, and the peaks’ amplitudes. σRR and σQRS parameters were added to quantify the regularity of RR distances and QRS durations, respectively. The sensitivity rate of the suggested method was 99.74% and the specificity rate was 99.86%. Moreover, the sensitivity and the specificity rates variations according to the Signal-to-Noise Ratio were performed.

Conclusions

Regular grammar with the addition of some constraints and deterministic automata proved functional for ECG signals diagnosis. Compared to statistical methods, the use of grammar provides satisfactory and competitive results and indices that are comparable to or even better than those cited in the literature.

Best hits of 11110110111: model-free selection and parameter-free sensitivity calculation of spaced seeds

Background

Spaced seeds, also named gapped q-grams, gapped k-mers, spaced q-grams, have been proven to be more sensitive than contiguous seeds (contiguous q-grams, contiguous k-mers) in nucleic and amino-acid sequences analysis. Initially proposed to detect sequence similarities and to anchor sequence alignments, spaced seeds have more recently been applied in several alignment-free related methods. Unfortunately, spaced seeds need to be initially designed. This task is known to be time-consuming due to the number of spaced seed candidates. Moreover, it can be altered by a set of arbitrary chosen parameters from the probabilistic alignment models used. In this general context, Dominant seeds have been introduced by Mak and Benson (Bioinformatics 25:302–308, 2009) on the Bernoulli model, in order to reduce the number of spaced seed candidates that are further processed in a parameter-free calculation of the sensitivity.

Results

We expand the scope of work of Mak and Benson on single and multiple seeds by considering the Hit Integration model of Chung and Park (BMC Bioinform 11:31, 2010), demonstrate that the same dominance definition can be applied, and that a parameter-free study can be performed without any significant additional cost. We also consider two new discrete models, namely the Heaviside and the Dirac models, where lossless seeds can be integrated. From a theoretical standpoint, we establish a generic framework on all the proposed models, by applying a counting semi-ring to quickly compute large polynomial coefficients needed by the dominance filter. From a practical standpoint, we confirm that dominant seeds reduce the set of, either single seeds to thoroughly analyse, or multiple seeds to store. Moreover, in http://bioinfo.cristal.univ-lille.fr/yass/iedera_dominance, we provide a full list of spaced seeds computed on the four aforementioned models, with one (continuous) parameter left free for each model, and with several (discrete) alignment lengths.

Performance evaluation of a rapid molecular diagnostic, MultiCode based, sample-to-answer assay for the simultaneous detection of Influenza A, B and respiratory syncytial viruses

BACKGROUND

Clinical signs and symptoms of different airway pathogens are generally indistinguishable, making laboratory tests essential for clinical decisions regarding isolation and antiviral therapy. Immunochromatographic tests (ICT) and direct immunofluorescence assays (DFA) have lower sensitivities and specificities than molecular assays, but have the advantage of quick turnaround times and ease-of-use.

OBJECTIVE

To evaluate the performance of a rapid molecular assay, ARIES FluA/B & RSV, using laboratory developed RT-PCR assays (LDA), ICT (BinaxNOW) and DFA.

METHODS

Analytical and clinical performance were evaluated in a retrospective study arm (stored respiratory samples obtained between 2006-2015) and a prospective study arm (unselected fresh clinical samples obtained between December 2015 and March 2016 tested in parallel with LDAs).

RESULTS

Genotype inclusivity and analytical specificity was 100%. However, ARIES was 0.5 log, 1-2logs and 2.5logs less sensitive for fluA, RSV and fluB respectively, compared to LDA. In total, 447 clinical samples were included, of which 15.4% tested positive for fluA, 9.2% for fluB and 26.0% for RSV, in both LDA and ARIES. ARIES clinical sensitivity compared to LDA was 98.6% (fluA), 93.3% (fluB) and 95.1% (RSV). Clinical specificity was 100% for all targets. ARIES detected 10.6% (4 fluA, 8 fluB, 11 RSV) and 26.9% (7 fluA, 3 fluB, 22 RSV) more samples compared to DFA and ICT, all confirmed by LDA.

CONCLUSION

Although analytically ARIES is less sensitive than LDA, the clinical performance of the assay in our tertiary care setting was comparable, and significantly better than that of the established rapid assays.

NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics

BACKGROUND

To address the shortcomings of digital rectal examinations (DRE), serum prostate-specific antigen (PSA), and trans-rectal ultrasound (TRUS) for precise determination of prostate cancer (PC) and differentiation from benign prostatic hyperplasia (BPH), we applied (1) H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate tactic for probing and prediction of PC and BPH.

METHODS

The study comprises 210 filtered sera from suspected PC, BPH, and a healthy subjects' cohort (HC). The filtered serum approach delineates to identify and quantify 52 metabolites using (1) H NMR spectroscopy. All subjects had undergone clinical evaluations (DRE, PSA, and TRUS) followed by biopsy for Gleason score, if needed. NMR-measured metabolites and clinical evaluation data were examined separately using linear multivariate discriminant function analysis (DFA) to probe the signature descriptors for each cohort.

RESULTS

DFA indicated that glycine, sarcosine, alanine, creatine, xanthine, and hypoxanthine were able to determine abnormal prostate (BPH + PC). DFA-based classification presented high precision (86.2% by NMR and 68.1% by clinical laboratory method) in discriminating HC from BPH + PC. DFA reveals that alanine, sarcosine, creatinine, glycine, and citrate were able to discriminate PC from BPH. DFA-based categorization exhibited high accuracy (88.3% by NMR and 75.2% by clinical laboratory method) to differentiate PC from BPH.

CONCLUSIONS

(1) H NMR-based metabolic profiling of filtered-serum sample appears to be assuring, swift, and least-invasive for probing and prediction of PC and BPH with its signature metabolic profile. This novel technique is not only on a par with histopathological evaluation of PC determination but is also comparable to liquid chromatography-based mass spectrometry to identify the metabolites. Prostate 76:1106-1119, 2016. © 2016 Wiley Periodicals, Inc.

The effect of footwear and footfall pattern on running stride interval long-range correlations and distributional variability

The presence of long-range correlations (self-similarity) in the stride-to-stride fluctuations in running stride interval has been used as an indicator of a healthy adaptable system. Changes to footfall patterns when running with minimalist shoes could cause a less adaptable running gait. The purpose of this study was to investigate stride interval variability and the degree of self-similarity of stride interval in runners wearing minimalist and conventional footwear. Twenty-six trained habitual rearfoot footfall runners, unaccustomed to running in minimalist footwear, performed 6-min sub-maximal treadmill running bouts at 11, 13 and 15 km·h(-1) in minimalist and conventional shoes. Force sensitive resistors were placed in the shoes to quantify stride interval (time between successive foot contacts). Footfall position, stride interval mean and coefficient of variation (CV), were used to assess performance as a function of shoe type. Long-range correlations of stride interval were assessed using detrended fluctuation analysis (α). Mean stride interval was 1-1.3% shorter (P=0.02) and 27% of runners adopted a midfoot footfall (MFF) in the minimalist shoe. There was a significant shoe effect on α and shoe*speed*footfall interaction effect on CV (P<0.05). Runners that adopted a MFF in minimalist shoes, displayed reduced long-range correlations (P<0.05) and CV (P<0.06) in their running stride interval at the 15 km·h(-1) speed. The reduced variability and self-similarity observed for runners that changed to a MFF in the minimalist shoe may be suggestive of a system that is less flexible and more prone to injury.

Model selection for identifying power-law scaling

Long-range temporal and spatial correlations have been reported in a remarkable number of studies. In particular power-law scaling in neural activity raised considerable interest. We here provide a straightforward algorithm not only to quantify power-law scaling but to test it against alternatives using (Bayesian) model comparison. Our algorithm builds on the well-established detrended fluctuation analysis (DFA). After removing trends of a signal, we determine its mean squared fluctuations in consecutive intervals. In contrast to DFA we use the values per interval to approximate the distribution of these mean squared fluctuations. This allows for estimating the corresponding log-likelihood as a function of interval size without presuming the fluctuations to be normally distributed, as is the case in conventional DFA. We demonstrate the validity and robustness of our algorithm using a variety of simulated signals, ranging from scale-free fluctuations with known Hurst exponents, via more conventional dynamical systems resembling exponentially correlated fluctuations, to a toy model of neural mass activity. We also illustrate its use for encephalographic signals. We further discuss confounding factors like the finite signal size. Our model comparison provides a proper means to identify power-law scaling including the range over which it is present.

Using Continuous Glucose Monitoring Data and Detrended Fluctuation Analysis to Determine Patient Condition: A Review

Patients admitted to critical care often experience dysglycemia and high levels of insulin resistance, various intensive insulin therapy protocols and methods have attempted to safely normalize blood glucose (BG) levels. Continuous glucose monitoring (CGM) devices allow glycemic dynamics to be captured much more frequently (every 2-5 minutes) than traditional measures of blood glucose and have begun to be used in critical care patients and neonates to help monitor dysglycemia. In an attempt to obtain a better insight relating biomedical signals and patient status, some researchers have turned toward advanced time series analysis methods. In particular, Detrended Fluctuation Analysis (DFA) has been a topic of many recent studies in to glycemic dynamics. DFA investigates the "complexity" of a signal, how one point in time changes relative to its neighboring points, and DFA has been applied to signals like the inter-beat-interval of human heartbeat to differentiate healthy and pathological conditions. Analyzing the glucose metabolic system with such signal processing tools as DFA has been enabled by the emergence of high quality CGM devices. However, there are several inconsistencies within the published work applying DFA to CGM signals. Therefore, this article presents a review and a "how-to" tutorial of DFA, and in particular its application to CGM signals to ensure the methods used to determine complexity are used correctly and so that any relationship between complexity and patient outcome is robust.

Assessment of taste attributes of peanut meal enzymatic-hydrolysis hydrolysates using an electronic tongue

Peanut meal is the byproduct of high-temperature peanut oil extraction; it is mainly composed of proteins, which have complex tastes after enzymatic hydrolysis to free amino acids and small peptides. The enzymatic hydrolysis method was adopted by using two compound proteases of trypsin and flavorzyme to hydrolyze peanut meal aiming to provide a flavor base. Hence, it is necessary to assess the taste attributes and assign definite taste scores of peanut meal double enzymatic hydrolysis hydrolysates (DEH). Conventionally, sensory analysis is used to assess taste intensity in DEH. However, it has disadvantages because it is expensive and laborious. Hence, in this study, both taste attributes and taste scores of peanut meal DEH were evaluated using an electronic tongue. In this regard, the response characteristics of the electronic tongue to the DEH samples and standard five taste samples were researched to qualitatively assess the taste attributes using PCA and DFA. PLS and RBF neural network (RBFNN) quantitative prediction models were employed to compare predictive abilities and to correlate results obtained from the electronic tongue and sensory analysis, respectively. The results showed that all prediction models had good correlations between the predicted scores from electronic tongue and those obtained from sensory analysis. The PLS and RBFNN prediction models constructed using the voltage response values from the sensors exhibited higher correlation and prediction ability than that of principal components. As compared with the taste performance by PLS model, that of RBFNN models was better. This study exhibits potential advantages and a concise objective taste assessment tool using the electronic tongue in the assessment of DEH taste attributes in the food industry.

Quantification of the acute effect of a low dose of red wine by nonlinear measures of RR and QT interval series in healthy subjects

The measures of nonlinear properties of RR interval and QT interval time series are sensitive to physiologically- or pathologically-induced complexity/regularity changes, but were not used to estimate the effect of alcohol intake. We wanted to examine the potential of these measures to quantify the acute effect of a low dose of red wine in healthy subjects. In separate experiments, fourteen young volunteers drank 200ml of red wine and a control drink with equal concentration of ethanol. ECG in supine position was recorded 20min before and 60min after drink intake. RR interval and QT interval series were extracted from ECG and we calculated variability, scaling exponents (α1 and α2) and sample entropy (SampEn) for both series. Systolic and diastolic blood pressures (BP) were measured every 10min. The immediate effect of both the drinks was equal: HR, BP and QT variability exhibited a sudden increase and then a decrease. However, the prolonged effect of wine and the control drink was different. Wine decreased both BP (p<0.05) and reduced complexity of RR and QT series (increased scaling exponents and decreased SampEn). The control drink prolonged QT and RR intervals (p<0.05). These results point out that the nonlinear properties of RR and QT interval series could be used to differentiate the effect of wine and ethanol. Changes in RR and QT interval series induced by a low dose of red wine are more detectable by methods that quantify the structure of the series than by methods that quantify their variability.

A case-control study evaluating RT-PCR/ESI-MS technology compared to direct fluorescent antibody and xTAG RVP PCR

Waste nasopharyngeal swabs (N = 244) were evaluated by the reverse-transcriptase polymerase chain reaction/electrospray ionization mass spectrometry PLEX-ID Broad Respiratory Virus Surveillance Kit version 2.5 compared to direct fluorescent antibody and xTAG Respiratory Virus Panel for percent agreement, sensitivity, and specificity. Sensitivity and specificity were 91% (111/122) and 95.1% (116/122), respectively. Sensitivity by virus, except parainfluenza, was 92.9-100%, and specificity was 99-100%.

Patterns of optimization in single- and inter-leg gait dynamics

INTRODUCTION

We examined the influence of walking speed on the fluctuation and synchronization dynamics of stride intervals and ground reaction force (GRF) profiles. Our aim was to identify patterns of optimization in the single-leg and inter-leg dynamics at preferred walking speed (PWS). PWS is thought to bring about the most stable walking pattern in terms of the attractor dynamics of the locomotion system.

METHODS

Twenty healthy subjects (29.1 ± 1.8 years; 10 women) walked on a treadmill for 5-min periods at their PWS and at 20, 40, 70, and 80% of maximal walking speed. The coefficient of variation (CV) and long-range correlations α of GRF profile and stride time fluctuations as well as the phase synchronization ρ of inter-leg stride timing were analyzed.

RESULTS

GRF profile α increased with increasing walking speed (p < 0.001). In contrast, stride time CV and α showed a U-shaped speed-dependency with lowest values at PWS (p < 0.05). The speed-dependency of single-leg stride time fluctuations was mirror-inverted in the speed-dependency of inter-leg stride timing ρ; its highest values occurred at PWS (p < 0.001).

CONCLUSIONS

Fluctuations in GRF profiles become more consistent with increasing walking speed. In contrast, the dynamics of single-leg and inter-leg timing show a collective pattern of optimization at PWS. Less correlated noise in single-leg timing at PWS, imposed on the two coupled oscillating legs, increases the phase synchronization of bilateral timing, thereby enhancing gait stability at the attractor of self-paced walking. Thus, the attractor dynamics of locomotion appear to rely on the interaction of single- and inter-leg timing.

Munc18-1 haploinsufficiency results in enhanced anxiety-like behavior as determined by heart rate responses in mice

Heterozygous (HZ) missense mutations in the gene encoding syntaxin binding protein 1 (Stxbp1 or Munc18-1), a presynaptic protein essential for neurotransmitter release, causes early infantile epileptic encephalopathy, abnormal brain structure and mental retardation in humans. Here we investigated whether the mouse model mimics symptoms of the human phenotype. The effects of the deletion of munc18-1 were studied in HZ and wild-type (WT) mice based on heart rate (HR) and its variability (HRV) as independent measures to expand previous behavioral results of enhanced anxiety and impaired emotional learning suggesting mild cognitive impairments. HR responses were assessed during novelty exposure, during the expression and extinction of conditioned tone-dependent fear and during the diurnal phase. Novelty exposure yielded no differences in activity patterns between the two genotypes, while maximum HR differed significantly (WT: 770 bpm; HZ: 790 bpm). Retention tests after both auditory delay and trace fear conditioning showed a delayed extinction of the conditioned HR response in HZ mice compared to WT mice. Since the HR versus HRV correlation and HR dynamics assessed by nonlinear methods revealed similar function in HZ and WT mice, the higher HR responses of munc18-1 HZ mice to different emotional challenges cannot be attributed to differences in autonomic nervous system function. Thus, in contrast to the adverse consequences of deletion of a single allele of munc18-1 in humans, C57BL/6J mice show enhanced anxiety responses based on HR adjustments that extend previous results on the behavioral level without support of cognitive impairment, epileptic seizures and autonomic dysregulation.

On-line monitoring of food fermentation processes using electronic noses and electronic tongues: a review

Fermentation processes are often sensitive to even slight changes of conditions that may result in unacceptable end-product quality. Thus, close follow-up of this type of processes is critical for detecting unfavorable deviations as early as possible in order to save downtime, materials and resources. Nevertheless the use of traditional analytical techniques is often hindered by the need for expensive instrumentation and experienced operators and complex sample preparation. In this sense, one of the most promising ways of developing rapid and relatively inexpensive methods for quality control in fermentation processes is the use of chemical multisensor systems. In this work we present an overview of the most important contributions dealing with the monitoring of fermentation processes using electronic noses and electronic tongues. After a brief description of the fundamentals of both types of devices, the different approaches are critically commented, their strengths and weaknesses being highlighted. Finally, future trends in this field are also mentioned in the last section of the article.

Nonlinear variability of body sway in patients with phobic postural vertigo

Background: Subjective postural imbalance is a key symptom in the somatoform phobic postural vertigo (PPV). It has been assumed that more attentional control of body posture and / or co-contraction of leg muscles during standing is used to minimize the physiological body sway in PPV. Here we analyze nonlinear variability of body sway in patients with PPV in order to disclose changes in postural control strategy associated with PPV.

Methods: Twenty patients with PPV and 20 age-matched healthy subjects (HS) were recorded on a stabilometer platform with eyes open (EO), eyes closed (EC), and while standing on a foam rubber with eyes closed (ECF). Spatio-temporal changes of the center of pressure (CoP) displacement were analyzed to assess the structure of postural variability by computing the scaling exponent α and the sample entropy (SEn) of the time series.

Results: With EO on firm ground α and SEn of CoP displacement were significantly lower in patients (p < 0.001). For more difficult conditions (EC, ECF) postural variability in PPV assimilated to that of HS.

Conclusion: Postural control in PPV patients differs from HS under normal stance condition. It is characterized by a reduced scaling behavior and higher regularity. These changes in the structure of postural variability might suggest an inappropriate attentional involvement with stabilizing strategies, which are used by HS only for more demanding balance tasks.

Predicting function from sequence in a large multifunctional toxin family

Venoms contain active substances with highly specific physiological effects and are increasingly being used as sources of novel diagnostic, research and treatment tools for human disease. Experimental characterisation of individual toxin activities is a severe rate-limiting step in the discovery process, and in-silico tools which allow function to be predicted from sequence information are essential. Toxins are typically members of large multifunctional families of structurally similar proteins that can have different biological activities, and minor sequence divergence can have significant consequences. Thus, existing predictive tools tend to have low accuracy. We investigated a classification model based on physico-chemical attributes that can easily be calculated from amino-acid sequences, using over 250 (mostly novel) viperid phospholipase A₂ toxins. We also clustered proteins by sequence profiles, and carried out in-vitro tests for four major activities on a selection of isolated novel toxins, or crude venoms known to contain them. The majority of detected activities were consistent with predictions, in contrast to poor performance of a number of tested existing predictive methods. Our results provide a framework for comparison of active sites among different functional sub-groups of toxins that will allow a more targeted approach for identification of potential drug leads in the future.

Automated identification of normal and diabetes heart rate signals using nonlinear measures

Diabetes mellitus (DM) affects considerable number of people in the world and the number of cases is increasing every year. Due to a strong link to the genetic basis of the disease, it is extremely difficult to cure. However, it can be controlled to prevent severe consequences, such as organ damage. Therefore, diabetes diagnosis and monitoring of its treatment is very important. In this paper, we have proposed a non-invasive diagnosis support system for DM. The system determines whether or not diabetes is present by determining the cardiac health of a patient using heart rate variability (HRV) analysis. This analysis was based on nine nonlinear features namely: Approximate Entropy (ApEn), largest Lyapunov exponet (LLE), detrended fluctuation analysis (DFA) and recurrence quantification analysis (RQA). Clinically significant measures were used as input to classification algorithms, namely AdaBoost, decision tree (DT), fuzzy Sugeno classifier (FSC), k-nearest neighbor algorithm (k-NN), probabilistic neural network (PNN) and support vector machine (SVM). Ten-fold stratified cross-validation was used to select the best classifier. AdaBoost, with least squares (LS) as weak learner, performed better than the other classifiers, yielding an average accuracy of 90%, sensitivity of 92.5% and specificity of 88.7%.

Effect of endotoxin on heart rate dynamics in rats with cirrhosis

Reduced heart rate variability (HRV) is a hallmark of systemic inflammation which carries negative prognostic information in sepsis. Decreased HRV is associated with partial uncoupling of cardiac pacemaker from cholinergic neural control during systemic inflammation. Sepsis is a common complication in liver cirrhosis with high mortality. The present study was aimed to explore the hypothesis that endotoxin uncouples cardiac pacemaker from autonomic neural control and reduces HRV in an experimental model of cirrhosis. Cirrhosis was induced by surgical ligation of the bile duct in rats. Cirrhotic rats were given intraperitoneal injection of either saline or lipopolysaccharide (endotoxin, 1mg/kg). Changes in HRV indices were studied in conscious rats using implanted telemetric probes. The atria were isolated and chronotropic responsiveness to cholinergic stimulation was assessed in vitro. Endotoxin injection induced a significant tachycardia and decreased short-term and long-term HRV indices in control rats. However, endotoxin was unable to increase heart rate in cirrhotic animals. In contrast with control rats, endotoxin induced biphasic changes in short-term HRV in cirrhotic rats. Acute endotoxin challenge reduced long-term HRV with 60-min delay in comparison with control animals. Endotoxin injection was associated with a significant hypo-responsiveness to cholinergic stimulation in control rats in vitro. Endotoxin did not change atrial chronotropic responsiveness to cholinergic stimulation in cirrhotic rats. Our data shows that cirrhosis is associated with development of tolerance to cardiac chronotropic effect of endotoxin in rats.

Effects of autonomic ganglion blockade on fractal and spectral components of blood pressure and heart rate variability in free-moving rats

Fractal analysis is a promising tool for assessing autonomic influences on heart rate (HR) and blood pressure (BP) variability. The temporal spectrum of scale coefficients, α(t), was recently proposed to describe the cardiovascular fractal dynamics. Aim of our work is to evaluate sympathetic influences on cardiovascular variability analyzing α(t) and spectral powers of HR and BP after ganglionic blockade. BP was recorded in 11 rats before and after autonomic blockade by hexamethonium infusion (HEX). Systolic and diastolic BP, pulse pressure and pulse interval were derived beat-by-beat. Segments longer than 5 min were selected at baseline and HEX to estimate power spectra and α(t). Comparisons were made by paired t-test. HEX reduced all spectral components of systolic and diastolic BP, the reduction being particularly significant around the frequency of Mayer waves; it induced a reduction on α(t) coefficients at t<2s and an increase on coefficients at t>8s. HEX reduced only slower components of pulse interval power spectrum, but decreased significantly faster scale coefficients (t<8s). HEX only marginally affected pulse pressure variability. Results indicate that the sympathetic outflow contributes to BP fractal dynamics with fractional Gaussian noise (α<1) at longer scales and fractional Brownian motion (α>1) at shorter scales. Ganglionic blockade also removes a fractional Brownian motion component at shorter scales from HR dynamics. Results may be explained by the characteristic time constants between sympathetic efferent activity and cardiovascular effectors. Therefore fractal analysis may complete spectral analysis with information on the correlation structure of the data.

Volatile fingerprints of cancer specific genetic mutations

We report on a new concept for profiling genetic mutations of (lung) cancer cells, based on the detection of patterns of volatile organic compounds (VOCs) emitted from cell membranes, using an array of nanomaterial-based sensors. In this in-vitro pilot study we have derived a volatile fingerprint assay for representative genetic mutations in cancer cells that are known to be associated with targeted cancer therapy. Five VOCs were associated with the studied oncogenes, using complementary chemical analysis, and were discussed in terms of possible metabolic pathways. The reported approach could lead to the development of novel methods for guiding treatments, so that patients could benefit from safer, more timely and effective interventions that improve survival and quality of life while avoiding unnecessary invasive procedures. Studying clinical samples (tissue/blood/breath) will be required as next step in order to determine whether this cell-line study can be translated into a clinically useful tool.

FROM THE CLINICAL EDITOR

In this novel study, a new concept for profiling genetic mutations of (lung) cancer cells is described, based on the detection of patterns of volatile organic compounds emitted from cell membranes, using an array of nano-gold based sensors.