Characterization of vestibular schwannoma tissues using liquid chromatography-tandem mass spectrometry analysis of specific peptide fragments separated by in-sample tryptic protein digestion followed by mathematical analysis.

Vestibular schwannoma is the most common benign neoplasm of the cerebellopontine angle. Its first symptoms include hearing loss, tinnitus, and vestibular symptoms, followed by cerebellar and brainstem symptoms, along with palsy of the adjacent cranial nerves. However, the clinical picture has unpredictable dynamics and currently, there are no reliable predictors of tumor behavior. Hence, it is desirable to have a fast routine method for analysis of vestibular schwannoma tissues at the molecular level. The major objective of this study was to verify whether a technique using in-sample specific protein digestion with trypsin would have the potential to provide a proteomic characterization of these pathological tissues. The achieved results showed that the use of this approach with subsequent liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of released peptides allowed a fast identification of a considerable number of proteins in two differential parts of vestibular schwannoma tissue as well as in tissues of control healthy samples. Furthermore, mathematical analysis of MS data was able to discriminate between pathological vestibular schwannoma tissues and healthy tissues. Thus, in-sample protein digestion combined with LC-MS/MS separation and identification of released specific peptides followed by mathematical analysis appears to have the potential for routine characterization of vestibular schwannomas at the molecular level. Data are available via ProteomeXchange with identifier PXD045261.

Cannabidiol nanoemulsion for eye treatment - Anti-inflammatory, wound healing activity and its bioavailability using in vitro human corneal substitute.

Cannabidiol (CBD) is the non-psychoactive component of the plant Cannabis sativa (L.) that has great anti-inflammatory benefits and wound healing effects. However, its high lipophilicity, chemical instability, and extensive metabolism impair its bioavailability and clinical use. Here, we report on the preparation of a human cornea substitute in vitro and validate this substitute for the evaluation of drug penetration. CBD nanoemulsion was developed and evaluated for stability and biological activity. The physicochemical properties of CBD nanoemulsion were maintained during storage for 90 days under room conditions. In the scratch assay, nanoformulation showed significantly ameliorated wound closure rates compared to the control and pure CBD. Due to the lower cytotoxicity of nanoformulated CBD, a higher anti-inflammatory activity was demonstrated. Neither nanoemulsion nor pure CBD can penetrate the cornea after the four-hour apical treatment. For nanoemulsion, 94 % of the initial amount of CBD remained in the apical compartment while only 54 % of the original amount of pure CBD was detected in the apical medium, and 7 % in the cornea, the rest was most likely metabolized. In summary, the nanoemulsion developed in this study enhanced the stability and biological activity of CBD.

Proteotypic peptides of hairs for the identification of common European domestic and wild animal species revealed by in-sample protein digestion and mass spectrometry analysis.

The aim of this work is to offer an alternative or complementary analytical tool to the time-consuming and expensive methods commonly used for the recognition of animal species according to their hair. The paper introduces a simple and fast way for species differentiation of animal hairs called in-sample digestion. A total of 10 European animal species, including cat, cow, common degu, dog, fallow deer, goat, horse, sika deer, rabbit, roe deer, and 17 different breeds of dogs were examined using specific tryptic cleavage directly in hair followed by matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography-electrospray ionization quadrupole time of flight. Principal component analysis was used for the subsequent mass spectrometric data evaluation. This novel approach demonstrates the ability to distinguish among individual animal species, which is supported by finding characteristic m/z values obtained by the mass spectrometry for each animal species. The approach was successfully tested on two "blind" samples. On the other hand, the attempt to distinguish among hairs of different dog breeds has not been successful due to the very similar protein composition and their amino acid sequences.

Acute and chronic blood serum proteome changes in patients with methanol poisoning.

Twenty-four blood serum samples from patients with acute methanol poisoning (M) from the mass methanol poisoning outbreak in the Czech Republic in 2012 were compared with 46 patient samples taken four years after poisoning (S) (overlap of 10 people with group M) and with a control group (C) of 24 samples of patients with a similar proportion of chronic alcohol abuse. When comparing any two groups, tens to hundreds of proteins with a significant change in concentration were identified. Fifteen proteins showed significant changes when compared between any two groups. The group with acute methanol poisoning showed significant changes in protein concentrations for at least 64 proteins compared to the other groups. Among the most important identified proteins closely related to intoxication are mainly those involved in blood coagulation, metabolism of vitamin A (increased retinol-binding protein), immune response (e.g., increased complement factor I, complement factors C3 and C5), and lipid transport (increased apolipoprotein A I, apolipoprotein A II, adiponectin). For blood coagulation, the most affected proteins with significant changes in the methanol poisoning group were von Willebrand factor, carboxypeptidase N, alpha-2-antiplasmin (all increased), inter-alpha-trypsin inhibitor heavy chain H4, kininogen-1, plasma serine protease inhibitor, plasminogen (all decreased). However, heparin administration used for the methanol poisoning group could have interfered with some of the changes in their concentrations. Data are available via ProteomeXchange with the identifier PXD035726.

Liquid chromatography-tandem mass spectrometry analysis of peptides separated from the insoluble matrix by in-sample tryptic protein digestion for rapid discrimination of various induced pathological states of human bone models in oral surgery.

For the understanding of pathological states of bone tissues in oral surgery, it would be desirable to have the possibility to simulate these processes on bone cell models in vitro. These cultures, similarly to bone tissues, contain numerous proteins entrapped in the insoluble matrix. The major goal of this study was to verify whether a method based on direct in-matrix protein digestion could be suitable for the discrimination between different induced pathological states of bone cell models cultivated in vitro. Using in-sample specific protein digestion with trypsin followed by liquid chromatography-tandem mass spectrometry analysis of released peptides, 446 proteins (in average per sample) were identified in a bone cell in vitro model with induced cancer, 440 proteins were found in a model with induced inflammation, 451 proteins were detected in control in vitro culture, and 491 proteins were distinguished in samples of vestibular laminas of maxillary bone tissues originating from six different patients. Subsequent partial least squares - discrimination analysis of obtained liquid chromatography-tandem mass spectrometry data was able to discriminate among in vitro cultures with induced cancer, with induced inflammation, and control cultivation. Thus, the direct in-sample protein digestion by trypsin followed by liquid chromatography-tandem mass spectrometry analysis of released specific peptide fragments from the insoluble matrix and mathematical analysis of the mass spectrometry data seems to be a promising tool for the routine proteomic characterization of in vitro human bone models with induced different pathological states.

Comparison of proteomic approaches used for the detection of potential biomarkers of Alzheimer's disease in blood plasma.

At present, Alzheimer's disease is detected mainly using psychological tests, which can only confirm the disease in its more advanced phases. Therefore, bioanalytical possibilities for detecting this disease earlier are being investigated. To date, the results of analyses, which focus mainly on the study of lipids and proteins either in cerebrospinal fluid or much less often in blood plasma, do not provide satisfactory results. In addition, cerebrospinal fluid sampling is uncomfortable for the patients and involves many health risks. In this work, we deal with proteomic analysis using Matrix-Assisted Laser Desorption/Ionisation-Time of Flight and Liquid Chromatography coupled to tandem Mass Spectrometry of blood plasma with a focus on various ways of preanalytical sample treatments. This should lead to results improvement and facilitate the subsequent evaluation using principal component analysis and partial least squares discriminant analysis. The obtained results indicate the direction of further research, namely the study of interactions between proteins and lipids contained in blood plasma. These substances may be regarded as potential biomarkers allowing for the diagnosis of Alzheimer´s disease even in its early stages.

Classification of Ataxic Gait.

Gait disorders accompany a number of neurological and musculoskeletal disorders that significantly reduce the quality of life. Motion sensors enable high-quality modelling of gait stereotypes. However, they produce large volumes of data, the evaluation of which is a challenge. In this publication, we compare different data reduction methods and classification of reduced data for use in clinical practice. The best accuracy achieved between a group of healthy individuals and patients with ataxic gait extracted from the records of 43 participants (23 ataxic, 20 healthy), forming 418 segments of straight gait pattern, is 98% by random forest classifier preprocessed by t-distributed stochastic neighbour embedding.

In-bone protein digestion followed by LC-MS/MS peptide analysis as a new way towards the routine proteomic characterization of human maxillary and mandibular bone tissue in oral surgery.

Proteomic characterization of alveolar bones in oral surgery represents an analytical challenge due to their insoluble character. The implementation of a straightforward technique could lead to the routine use of proteomics in this field. This work thus developed a simple technique for the characterization of bone tissue for human maxillary and mandibular bones. It is based on the direct in-bone tryptic digestion of proteins in both healthy and pathological human maxillary and mandibular bone samples. The released peptides were then identified by the LC-MS/MS. Using this approach, a total of 1120 proteins were identified in the maxillary bone and 1151 proteins in the mandibular bone. The subsequent partial least squares-discrimination analysis (PLS-DA) of protein data made it possible to reach 100% discrimination between the samples of healthy alveolar bones and those of the bone tissue surrounding the inflammatory focus. These results indicate that the in-bone protein digestion followed by the LC-MS/MS and subsequent statistical analysis can provide a deeper insight into the field of oral surgery at the molecular level. Furthermore, it could also have a diagnostic potential in the differentiation between the proteomic patterns of healthy and pathological alveolar bone tissue. Data are available via ProteomeXchange with the identifier PXD026775.

Deep Learning for Accelerometric Data Assessment and Ataxic Gait Monitoring.

Ataxic gait monitoring and assessment of neurological disorders belong to important multidisciplinary areas that are supported by digital signal processing methods and machine learning tools. This paper presents the possibility of using accelerometric data to optimise deep learning convolutional neural network systems to distinguish between ataxic and normal gait. The experimental dataset includes 860 signal segments of 16 ataxic patients and 19 individuals from the control set with the mean age of 38.6 and 39.6 years, respectively. The proposed methodology is based upon the analysis of frequency components of accelerometric signals simultaneously recorded at specific body positions with a sampling frequency of 60 Hz. The deep learning system uses all of the frequency components in a range of 〈0,30 〉 Hz. Our classification results are compared with those obtained by standard methods, which include the support vector machine, Bayesian methods, and the two-layer neural network with features estimated as the relative power in selected frequency bands. Our results show that the appropriate selection of sensor positions can increase the accuracy from 81.2% for the foot position to 91.7% for the spine position. Combining the input data and the deep learning methodology with five layers increased the accuracy to 95.8%. Our methodology suggests that artificial intelligence methods and deep learning are efficient methods in the assessment of motion disorders and they have a wide range of further applications.

Efficient Confirmation of Plant Viral Proteins and Identification of Specific Viral Strains by nanoLC-ESI-Q-TOF Using Single-Leaf-Tissue Samples.

Plant viruses are important pathogens that cause significant crop losses. A plant protein extraction protocol that combines crushing the tissue by a pestle in liquid nitrogen with subsequent crushing by a roller-ball crusher in urea solution, followed by RuBisCO depletion, reduction, alkylation, protein digestion, and ZipTip purification allowed us to substantially simplify the sample preparation by removing any other precipitation steps and to detect viral proteins from samples, even with less than 0.2 g of leaf tissue, by a medium resolution nanoLC-ESI-Q-TOF. The presence of capsid proteins or polyproteins of fourteen important viruses from seven different families (Geminiviridae, Luteoviridae, Bromoviridae, Caulimoviridae, Virgaviridae, Potyviridae, and Secoviridae) isolated from ten different economically important plant hosts was confirmed through many identified pathogen-specific peptides from a protein database of host proteins and potential pathogen proteins assembled separately for each host and based on existing online plant virus pathogen databases. The presented extraction protocol, combined with a medium resolution LC-MS/MS, represents a cost-efficient virus protein confirmation method that proved to be effective at identifying virus strains (as demonstrated for PPV, WDV) and distinct disease species of BYDV, as well as putative new viral protein sequences from single-plant-leaf tissue samples. Data are available via ProteomeXchange with identifier PXD022456.

Capillary electrophoretic profiling of in-bone tryptic digests of proteins as a potential tool for the detection of inflammatory states in oral surgery.

The commonly used histological assessment of pathological states of alveolar bone tissues in oral surgery needs laborious and time-consuming processing by an experienced histologist. Therefore, a simpler and faster methodology is required in this field. Following this demand, this paper reports a straightforward approach using the tryptic cleavage of proteins directly in bone without its demineralization, followed by the capillary electrophoresis-ultraviolet detection profiling of the yielded protein digest. Cleavage-derived peptides were separated by capillary electrophoresis in acidic background electrolytes, pH 2.01-2.54. The best resolution of peptide fragments with the highest peak capacity was achieved in the background electrolyte composed of 55 mM H3 PO4 , 14 mM tris(hydroxymethyl)aminomethan, pH 2.01. The differences in the obtained capillary electrophoresis-ultraviolet detection profiles with characteristic patterns for particular bone samples were subsequently discriminated by linear discriminant analysis over principal components. This approach was first verified on porcine bone tissues as model samples; jawbone and calf bone tissues could be discriminated with an accuracy of 100%. Subsequently, the method was capable of differentiating unequivocally between human healthy and inflammatory alveolar bone tissues obtained from oral surgery. This procedure seems to be promising as complement or even an alternative to the traditional histological discrimination between healthy and inflammatory bone tissues in oral surgery.

Complex Density of Continuum States in Resonant Quantum Tunneling.

We introduce a complex-extended continuum level density and apply it to one-dimensional scattering problems involving tunneling through finite-range potentials. We show that the real part of the density is proportional to a real "time shift" of the transmitted particle, while the imaginary part reflects the imaginary time of an instantonlike tunneling trajectory. We confirm these assumptions for several potentials using the complex scaling method. In particular, we show that stationary points of the potentials give rise to specific singularities of both real and imaginary densities which represent close analogues of excited-state quantum phase transitions in bound systems.

Simple capacitor-switch model of excitatory and inhibitory neuron with all parts biologically explained allows input fire pattern dependent chaotic oscillations.

Due to known information processing capabilities of the brain, neurons are modeled at many different levels. Circuit theory is also often used to describe the function of neurons, especially in complex multi-compartment models, but when used for simple models, there is no subsequent biological justification of used parts. We propose a new single-compartment model of excitatory and inhibitory neuron, the capacitor-switch model of excitatory and inhibitory neuron, as an extension of the existing integrate-and-fire model, preserving the signal properties of more complex multi-compartment models. The correspondence to existing structures in the neuronal cell is then discussed for each part of the model. We demonstrate that a few such inter-connected model units are capable of acting as a chaotic oscillator dependent on fire patterns of the input signal providing a complex deterministic and specific response through the output signal. The well-known necessary conditions for constructing a chaotic oscillator are met for our presented model. The capacitor-switch model provides a biologically-plausible concept of chaotic oscillator based on neuronal cells.

Superradiance in finite quantum systems randomly coupled to continuum.

We study the effect of superradiance in open quantum systems, i.e., the separation of short- and long-living eigenstates when a certain subspace of states in the Hilbert space acquires an increasing decay width. We use several Hamiltonian forms of the initial closed system and generate their coupling to continuum by means of the random matrix theory. We average the results over a large number of statistical realizations of an effective non-Hermitian Hamiltonian and relate robust features of the superradiance process to the distribution of its exceptional points. We show that the superradiance effect is enhanced if the initial system is at the point of quantum criticality.

Collective performance of a finite-time quantum Otto cycle.

We study the finite-time effects in a quantum Otto cycle where a collective spin system is used as the working fluid. Starting from a simple one-qubit system we analyze the transition to the limit cycle in the case of a finite-time thermalization. If the system consists of a large sample of independent qubits interacting coherently with the heat bath, then the super-radiant equilibration is observed. We show that this phenomenon can boost the power of the engine. Mutual interaction of qubits in the working fluid is modeled by the Lipkin-Meshkov-Glick Hamiltonian. We demonstrate that in this case the quantum phase transitions for the ground and excited states may have a strong negative effect on the performance of the machine. Conversely, by analyzing the work output we can distinguish between the operational regimes with and without a phase transition.

Recombinant expression of osmotin in barley improves stress resistance and food safety during adverse growing conditions.

BACKGROUND: Although many genetic manipulations of crops providing biofortified or safer food have been done, the acceptance of biotechnology crops still remains limited. We report on a transgenic barley expressing the multi-functional protein osmotin that improves plant defense under stress conditions. METHODS: An Agrobacterium-mediated technique was used to transform immature embryos of the spring barley cultivar Golden Promise. Transgenic barley plants of the T0 and T1 generation were evaluated by molecular methods. Transgenic barley tolerance to stress was determined by chlorophyll, total protein, malondialdehyde and ascorbate peroxidase content. Methanol extracts of i) Fusarium oxysporum infected or ii) salt-stressed plants, were characterized by their acute toxicity effect on human dermal fibroblasts (HDF), genotoxicity and affection of biodiversity interactions, which was tested through monitoring barley natural virus pathogen-host interactions-the BYDV and WDV viruses transmitted to the plants by aphids and leafhoppers. RESULTS: Transgenic plants maintained the same level of chlorophyll and protein, which significantly declined in wild-type barley under the same stressful conditions. Salt stress evoked higher ascorbate peroxidase level and correspondingly less malondialdehyde. Osmotin expressing barley extracts exhibited a lower cytotoxicity effect of statistical significance than that of wild-type plants under both types of stress tested on human dermal fibroblasts. Extract of Fusarium oxysporum infected transgenic barley was not able to damage DNA in the Comet assay, which is in opposite to control plants. Moreover, this particular barley did not affect the local biodiversity. CONCLUSION: Our findings provide a new perspective that could help to evaluate the safety of products from genetically modified crops.

The Complex Behaviour of a Simple Neural Oscillator Model in the Human Cortex.

The brain is a complex organ responsible for memory storage and reasoning; however, the mechanisms underlying these processes remain unknown. This paper forms a contribution to a lot of theoretical studies devoted to regular or chaotic oscillations of interconnected neurons assuming that the smallest information unit in the brain is not a neuron but, instead, a coupling of inhibitory and excitatory neurons forming a simple oscillator. Several coefficients of variation for peak intervals and correlation coefficients for peak interval histograms are evaluated and the sensitivity of such oscillator units is tested to changes in initial membrane potentials, interconnection signal delays, and changes in synaptic weights based on known histologically verified neuron couplings. Results present only a low dependence of oscillation patterns to changes in initial membrane potentials or interconnection signal delays in comparison to a strong sensitivity to changes in synaptic weights showing the stability and robustness of encoded oscillating patterns to signal outages or remoteness of interconnected neurons. Presented simulations prove that the selected neuronal couplings are able to produce a variety of different behavioural patterns, with periodicity ranging from milliseconds to thousands of milliseconds between the spikes. Many detected different intrinsic frequencies then support the idea of possibly large informational capacity of such memory units.

Data on low-molecular weight proteins of Escherichia coli treated by essential oils components, tetracycline, chlorine and peroxide by MALDI-TOF MS.

In this dataset we provide MALDI-TOF MS spectra of Escherichia coli. The data presented in this article are related to the article entitled "Stress response of Escherichia coli to essential oil components - insights on low-molecular-weight proteins from MALDI-TOF" (Bozik et al., 2018) [1]. Essential oils and their components are known for their antibacterial effect. Many studies evaluated the effect of essential oil components (EOCs) on the cell wall, bacterial membranes, and energetic metabolism. But data about low molecular weight proteins (<20 kDa) are limited. Provided data are focused on bacterial response to EOCs; tetracycline, peroxide and chlorine was used as control as common antibiotic and disinfectant agents used against bacteria. These data describe the effect of tested substances to bacterial protein synthesis.

Stress response of Escherichia coli to essential oil components - insights on low-molecular-weight proteins from MALDI-TOF.

The antibacterial effects of essential oils and their components (EOCs) are usually attributed to effects on membranes and metabolism. Studies of the effects of EOCs on protein expression have primarily analysed proteins larger than 10 kDa using gel electrophoresis. In the present study, we used MALDI-TOF-MS to investigate the effects of EOCs on low-molecular-weight proteins. From 297 m/z features, we identified 94 proteins with important differences in expression among untreated samples, samples treated with EOCs, and samples treated with antibiotics, peroxide, or chlorine. The targets of these treatments obviously differ, even among EOCs. In addition to ribosomal proteins, stress-, membrane- and biofilm-related proteins were affected. These findings may provide a basis for identifying new targets of essential oils and synergies with other antibiotics.

Principal component analysis of normalized full spectrum mass spectrometry data in multiMS-toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains.

RATIONALE: Explorative statistical analysis of mass spectrometry data is still a time-consuming step. We analyzed critical factors for application of principal component analysis (PCA) in mass spectrometry and focused on two whole spectrum based normalization techniques and their application in the analysis of registered peak data and, in comparison, in full spectrum data analysis. We used this technique to identify different metabolic patterns in the bacterial culture of Cronobacter sakazakii, an important foodborne pathogen. METHODS: Two software utilities, the ms-alone, a python-based utility for mass spectrometry data preprocessing and peak extraction, and the multiMS-toolbox, an R software tool for advanced peak registration and detailed explorative statistical analysis, were implemented. The bacterial culture of Cronobacter sakazakii was cultivated on Enterobacter sakazakii Isolation Agar, Blood Agar Base and Tryptone Soya Agar for 24 h and 48 h and applied by the smear method on an Autoflex speed MALDI-TOF mass spectrometer. RESULTS: For three tested cultivation media only two different metabolic patterns of Cronobacter sakazakii were identified using PCA applied on data normalized by two different normalization techniques. Results from matched peak data and subsequent detailed full spectrum analysis identified only two different metabolic patterns - a cultivation on Enterobacter sakazakii Isolation Agar showed significant differences to the cultivation on the other two tested media. The metabolic patterns for all tested cultivation media also proved the dependence on cultivation time. CONCLUSIONS: Both whole spectrum based normalization techniques together with the full spectrum PCA allow identification of important discriminative factors in experiments with several variable condition factors avoiding any problems with improper identification of peaks or emphasis on bellow threshold peak data. The amounts of processed data remain still manageable. Both implemented software utilities are available free of charge from http://uprt.vscht.cz/ms.