Development of a Teat Bio-sealant and Evaluation of its Technological and Functional Properties

A teat bio-sealant was developed using Weissella cibaria, and the bio-sealant’s technological and functional properties were assessed. The development included four experimental phases that were analyzed using independent experimental designs. Initially, sterilized or pasteurized Aloe vera gels were used, and the effect of heat treatment was investigated. In the second phase, the effects of time, storage temperature, and addition of cryopreservatives on the viability of the probiotic were observed. The third phase consisted of evaluating the synergistic effects of the cryopreservatives. The fourth phase involved selecting a material that would provide viscosity to the teat sealant. Technological and functional properties were measured in terms of viability of W. cibaria, and antimicrobial activity against Staphylococcus aureus and Streptococcus agalactiae was also analyzed. A mixture of milk powder and glycerol preserved this antimicrobial activity. Pullulan provided greater viscosity and maintained the technological and functional properties of the bio-sealant for 29 days. This teat bio-sealant can be used as an alternative for the prevention of bovine mastitis.     

Is emotion recognition the only problem in ADHD? effects of pharmacotherapy on face and emotion recognition in children with ADHD

The objectives of this study were to evaluate both face and emotion recognition, to detect differences among attention deficit and hyperactivity disorder (ADHD) subgroups, to identify effects of the gender and to assess the effects of methylphenidate and atomoxetine treatment on both face and emotion recognition in patients with ADHD. The study sample consisted of 41 male, 29 female patients, 8–15 years of age, who were diagnosed as having combined type ADHD (N = 26), hyperactive/impulsive type ADHD (N = 21) or inattentive type ADHD (N = 23) but had not previously used any medication for ADHD and 35 male, 25 female healthy individuals. Long-acting methylphenidate (OROS-MPH) was prescribed to 38 patients, whereas atomoxetine was prescribed to 32 patients. The reading the mind in the eyes test (RMET) and Benton face recognition test (BFRT) were applied to all participants before and after treatment. The patients with ADHD had a significantly lower number of correct answers in child and adolescent RMET and in BFRT than the healthy controls. Among the ADHD subtypes, the hyperactive/impulsive subtype had a lower number of correct answers in the RMET than the inattentive subtypes, and the hyperactive/impulsive subtype had a lower number of correct answers in short and long form of BFRT than the combined and inattentive subtypes. Male and female patients with ADHD did not differ significantly with respect to the number of correct answers on the RMET and BFRT. The patients showed significant improvement in RMET and BFRT after treatment with OROS-MPH or atomoxetine. Patients with ADHD have difficulties in face recognition as well as emotion recognition. Both OROS-MPH and atomoxetine affect emotion recognition. However, further studies on the face and emotion recognition are needed in ADHD.     

Identifying indicator species for bryophyte conservation in fragmented forests

It is important to conserve bryophyte diversity in fragmented forests, due to the vulnerability of this group to environmental change. In this study, the utility of bryophyte functional groups (taxonomic classes, substrate classes, and life-forms) was examined as indicators for planning urban area conservation of bryophyte diversity. The study sites comprised 27 fragmented forests in Kyoto City, Japan. Using linear regression models, it was found that the species richness of almost all functional groups was positively correlated with patch size. Furthermore, two types of bryophyte life-form (fans and thalloid mats) were significantly correlated with environmental factors considered important for conservation planning. The species richness of fan bryophytes was positively correlated with the presence of natural forest patches and was negatively correlated with distance from mountainous areas. Similarly, the species richness of thalloid mat bryophytes was negatively correlated with maintenance practices. These results may be explained by the vulnerability of these two bryophyte groups to environmentally caused drought stress, accompanied by decreasing patch size, maintenance practices, disturbance, and/or loss of natural vegetation. Considering that drought stress represents a major threat to bryophyte diversity in fragmented forests, the species richness of hygrophilous life-forms (e.g., fans and thalloid mats) may be used as an indicator of fragmented forests that are less affected by drought stress, and these species should be preferentially conserved to maintain high levels of bryophyte diversity.     

Analytical methods for structural ensembles and dynamics of intrinsically disordered proteins

Intrinsically disordered proteins, proteins that do not have a well-defined three-dimensional structure, make up a significant proportion of our proteome and are particularly prevalent in signaling and regulation. Although their importance has been realized for two decades, there is a lack of high-resolution experimental data. Molecular dynamics simulations have been crucial in reaching our current understanding of the dynamical structural ensemble sampled by intrinsically disordered proteins. In this review, we discuss enhanced sampling simulation methods that are particularly suitable to characterize the structural ensemble, along with examples of applications and limitations. The dynamics within the ensemble can be rigorously analyzed using Markov state models. We discuss recent developments that make Markov state modeling a viable approach for studying intrinsically disordered proteins. Finally, we briefly discuss challenges and future directions when applying molecular dynamics simulations to study intrinsically disordered proteins.     

Robust frequency recognition for SSVEP-based BCI with temporally local multivariate synchronization index

Multivariate synchronization index (MSI) has been proved to be an efficient method for frequency recognition in SSVEP-BCI systems. It measures the correlation according to the entropy of the normalized eigenvalues of the covariance matrix of multichannel signals. In the MSI method, the estimation of covariance matrix omits the temporally local structure of samples. In this study, a new spatio-temporal method, termed temporally local MSI (TMSI), was presented. This new method explicitly exploits temporally local information in modelling the covariance matrix. In order to evaluate the performance of the TMSI, we performs a comparison between the two methods on the real SSVEP datasets from eleven subjects. The results show that the TMSI outperforms the standard MSI. TMSI benefits from exploiting the temporally local structure of EEG signals, and could be a potential method for robust performance of SSVEP-based BCI.     

Temporal properties of dual-peak responses of mouse retinal ganglion cells and effects of inhibitory pathways

Dual-peak responses of retinal ganglion cells (RGCs) are observed in various species, previous researches suggested that both response peaks were involved in retinal information coding. In the present study, we investigated the temporal properties of the dual-peak responses recorded in mouse RGCs elicited by spatially homogeneous light flashes and the effect of the inhibitory inputs mediated by GABAergic and/or glycinergic pathways. We found that the two peaks in the dual-peak responses exhibited distinct temporal dynamics, similar to that of short-latency and long-latency single-peak responses respectively. Pharmacological studies demonstrated that the application of exogenous GABA or glycine greatly suppressed or even eliminated the second peak of the cells’ firing activities, while little change was induced in the first peak. Co-application of glycine and GABA led to complete elimination of the second peak. Moreover, application of picrotoxin or strychnine induced dual-peak responses in some cells with transient responses by unmasking a second response phase. These results suggest that both GABAergic and glycinergic pathways are involved in the dual-peak responses of the mouse RGCs, and the two response peaks may arise from distinct pathways that would converge on the ganglion cells.     

Saliency computation via whitened frequency band selection

Many saliency computational models have been proposed to simulate bottom-up visual attention mechanism of human visual system. However, most of them only deal with certain kinds of images or aim at specific applications. In fact, human beings have the ability to correctly select attentive focuses of objects with arbitrary sizes within any scenes. This paper proposes a new bottom-up computational model from the perspective of frequency domain based on the biological discovery of non-Classical Receptive Field (nCRF) in the retina. A saliency map can be obtained according to the idea of Extended Classical Receptive Field. The model is composed of three major steps: firstly decompose the input image into several feature maps representing different frequency bands that cover the whole frequency domain by utilizing Gabor wavelet. Secondly, whiten the feature maps to highlight the embedded saliency information. Thirdly, select some optimal maps, simulating the response of receptive field especially nCRF, to generate the saliency map. Experimental results show that the proposed algorithm is able to work with stable effect and outstanding performance in a variety of situations as human beings do and is adaptive to both psychological patterns and natural images. Beyond that, biological plausibility of nCRF and Gabor wavelet transform make this approach reliable.     

Navigating abstract virtual environment: an eeg study

Perceptions of different environments are different for different people. An abstract designed environment, with a degree of freedom from any visual reference in the physical world requests a completely different perception than a fully or semi-designed environment that has some correlation with the physical world. Maximal evidence on the manner in which the human brain is involved/operates in dealing with such novel perception comes from neuropsychology. Harnessing the tools and techniques involved in the domain of neuropsychology, the paper presents nee evidence on the role of pre-central gyrus in the perception of abstract spatial environments. In order to do so, the research team developed three different categories of designed environment with different characteristics: (1) Abstract environment, (2) Semi-designed environment, (3) Fully designed environment, as experimental sample environments. Perception of Fully-designed and semi-designed environments is almost the same, [maybe] since the brain can find a correlation between designed environments and already experienced physical world. In addition to this, the response to questionnaires accompanied with a list of buzzwords that have been provided after the experiments, also describe the characteristics of the chosen sample environments. Additionally, these results confirm the suitability of continuous electroencephalography (EEG) for studying Perception from the perspective of architectural environments.     

A novel algorithm with differential evolution and coral reef optimization for extreme learning machine training

Extreme learning machine (ELM) is a novel and fast learning method to train single layer feed-forward networks. However due to the demand for larger number of hidden neurons, the prediction speed of ELM is not fast enough. An evolutionary based ELM with differential evolution (DE) has been proposed to reduce the prediction time of original ELM. But it may still get stuck at local optima. In this paper, a novel algorithm hybridizing DE and metaheuristic coral reef optimization (CRO), which is called differential evolution coral reef optimization (DECRO), is proposed to balance the explorative power and exploitive power to reach better performance. The thought and the implement of DECRO algorithm are discussed in this article with detail. DE, CRO and DECRO are applied to ELM training respectively. Experimental results show that DECRO-ELM can reduce the prediction time of original ELM, and obtain better performance for training ELM than both DE and CRO.