The potential of acetylsalicylic acid and vitamin E in modulating inflammatory cascades in chickens under lipopolysaccharide-induced inflammation

International audienceAbstractDistinct enzymes, including cyclooxygenase 1 and 2 (COX-1 and COX-2), lipoxygenase (LOXs), and cytochrome P450 monooxygenase (CYP450), produce different stress mediators and mediate inflammation in birds. Bioactive agents such as acetylsalicylic acid (ASA) and vitamin E (vE) may affect enzyme activities and could be used in poultry production to control the magnitude of acute phase inflammation. Here, we characterized COX, LOX, and CYP450 mRNA expression levels in chicken immune tissues in response to Escherichia coli lipopolysaccharide (LPS) challenge and investigated whether ASA and vE could alter gene expression. Additionally, for the first time in chickens, we evaluated oxygen consumption by platelet mitochondria as a biomarker of mitochondria function in response to ASA- and vE. LPS challenge compromised bird growth rates, but neither dietary ASA nor vE significantly ameliorated this effect; however, gradually increasing dietary vE levels were more effective than basal levels. ASA regulated arachidonic acid metabolism, providing an eicosanoid synthesis substrate, whereas gradually increasing vE levels evoked aspirin resistance during challenge. Gene expression in immune tissues was highly variable, indicating a complex regulatory network controlling inflammatory pathways. However, unlike COX-1, COX-2 and CYP450 exhibited increased mRNA expression in some cases, suggesting an initiation of novel anti-inflammatory and pro-resolving signals during challenge. Measuring oxygen consumption rate, we revealed that neither the ASA nor vE levels applied here exerted toxic effects on platelet mitochondria

Parallel implementation of the k-connectivity test algorithm

There exists a large number of theoretical results concerning fast parallel algorithms for graph problems, however, scarcely one finds reports of their practical implementation. In an attempt at partial filling this gap we discuss implementation of an algorithm performing the pretest for k-connectivity. This test is based, first, on the Scan-First Search algorithm introduced in [1]. Utilizing this procedure we decrease the size of the input graph by removing selected edges so that the resulting graph (certificate of k-connectivity) has only 0(kn) left. During this part of computations we can answer the question about k-connectivity negatively if a certificate cannot be generated. Afterwards, we can apply the test described in [2] to establish ^-connectivity in the remaining cases

Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum

Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Since the price of Arabica is much higher than that of Robusta, this lack of information is not only an economical issue but a possible fraud to consumers, besides the potential allergic reaction that these mixtures may trigger in some individuals. In this paper, two sample preparation techniques were compared before the analysis of the total volatile organic compounds (VOCs) found in Robusta, Arabica, and in the mixture from both coffee types. The comparison of the signals obtained from the analyses showed that the VOCs concentration levels obtained from the headspace (HS) analyses were clearly higher than those obtained from the pre-concentration step where an adsorbent, an active charcoal strip (ACS + HS), was used. In the second part of this study, the possibility of using the headspace gas-chromatography ion mobility spectrometry (HS-GC-IMS) for the discrimination between Arabica, Robusta, and mixed coffee samples (n = 30) was evaluated. The ion mobility sum spectrum (IMSS) obtained from the analysis of the HS was used in combination with pattern recognition techniques, namely linear discrimination analysis (LDA), as an electronic nose. The identification of individual compounds was not carried out since chromatographic information was not used. This novel approach allowed the correct discrimination (100%) of all of the samples. A characteristic fingerprint for each type of coffee for a fast and easy identification was also developed. In addition, the developed method is ecofriendly, so it is a good alternative to traditional approaches

Gut microbiota activity in chickens from two genetic lines and with outdoor-preferring, moderate-preferring, and indoor-preferring ranging profiles

Despite the existing research into the gut microbiome of meat chickens, the associations between gut microbiome composition, its activity and chicken outdoor ranging frequency remain unexplored. The aim of this study was to determine the gut microbiota composition, activity and metabolic products in chickens of 2 different lines and 3 ranging profiles. Sixty non-beak trimmed birds, either Sasso or Green-legged Partridge were housed with access to outdoor ranges from wk. 5 to 10 of age. Outdoor ranges were video recorded to obtain frequencies of the birds’ range use. The information about relative abundance of selected bacterial groups in the ceca including Lactobacillus spp., E. coli, Bifidobacterium spp., and Clostridium spp. was obtained with the PCR method. Gut microbiota activity was assessed based on the glycolytic activity of bacterial enzymes including, α-glucosidase, β-glucosidase, α-galactosidase, β-galactosidase, and β-glucuronidase as well as based on the concentration of short-chain fatty acids (SCFA) in the caecal digesta. Statistical analysis was conducted by generalized linear mixed models, applying the breed and ranging profile as fixed effects and pen as a random factor. The lowest relative abundance of Bifidobacterium spp. was found in the cecal content of indoor-preferring Sasso birds (0.01 ± 0.001), as compared to all other birds in the experiment (ranging from 0.03 ± 0.01 to 0.11 ± 0.07; P = 0.0002). The lowest relative abundance of E. coli was identified for all outdoor-preferring birds and indoor- preferring Sasso birds (0.01 ± 0.001; P = 0.0087). Cecal activity of: α-glucosidase, β-glucuronidase and β-galactosidase was higher in Green-legged Partridges, as compared to Sasso (P = 0.013; P = 0.008; P = 0.004). Valeric acid concentrations were higher in moderate Green-legged Partridges than in Sasso of the same ranging profile (2.03 ± 0.16 vs. 1.5 ± 0.17; 0.016). The majority of the current results confirmed an effect of genotype and ranging profile on the various analyzed parameters. In outdoor-preferring birds, the consumption of pasture originating feed sources as a supplement to the indoor accessible cereal-based diet likely caused the positive effects on the birds’ microbial profile

ProTheRaMon : a GATE simulation framework for proton therapy range monitoring using PET imaging

Objective. This paper reports on the implementation and shows examples of the use of the ProTheRaMon framework for simulating the delivery of proton therapy treatment plans and range monitoring using positron emission tomography (PET). ProTheRaMon offers complete processing of proton therapy treatment plans, patient CT geometries, and intra-treatment PET imaging, taking into account therapy and imaging coordinate systems and activity decay during the PET imaging protocol specific to a given proton therapy facility. We present the ProTheRaMon framework and illustrate its potential use case and data processing steps for a patient treated at the Cyclotron Centre Bronowice (CCB) proton therapy center in Krakow, Poland. Approach. The ProTheRaMon framework is based on GATE Monte Carlo software, the CASToR reconstruction package and in-house developed Python and bash scripts. The framework consists of five separated simulation and data processing steps, that can be further optimized according to the user’s needs and specific settings of a given proton therapy facility and PET scanner design. Main results. ProTheRaMon is presented using example data from a patient treated at CCB and the J-PET scanner to demonstrate the application of the framework for proton therapy range monitoring. The output of each simulation and data processing stage is described and visualized. Significance. We demonstrate that the ProTheRaMon simulation platform is a high-performance tool, capable of running on a computational cluster and suitable for multi-parameter studies, with databases consisting of large number of patients, as well as different PET scanner geometries and settings for range monitoring in a clinical environment. Due to its modular structure, the ProTheRaMon framework can be adjusted for different proton therapy centers and/or different PET detector geometries. It is available to the community via github (Borys et al 2022)

From tests of discrete symmetries to medical imaging with J-PET detector

We present results on CPT symmetry tests in decays of positronium performed with the precision at the level of 10$^{-4}$, and positronium images determined with the prototype of the J-PET tomograph. The first full-scale prototype apparatus consists of 192 plastic scintillator strips readout from both ends with vacuum tube photomultipliers. Signals produced by photomultipliers are probed in the amplitude domain and are digitized by FPGA-based readout boards in triggerless mode. In this contribution we report on the first two- and three-photon positronium images and tests of CPT symmetry in positronium decays

Transformation of PET raw data into images for event classification using convolutional neural networks

In positron emission tomography (PET) studies, convolutional neural networks (CNNs) may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, unprocessed PET coincidence data exist in tabular format. This paper develops the transformation of tabular data into -dimensional matrices, as a preparation stage for classification based on CNNs. This method explicitly introduces a nonlinear transformation at the feature engineering stage and then uses principal component analysis to create the images. We apply the proposed methodology to the classification of simulated PET coincidence events originating from NEMA IEC and anthropomorphic XCAT phantom. Comparative studies of neural network architectures, including multilayer perceptron and convolutional networks, were conducted. The developed method increased the initial number of features from 6 to 209 and gave the best precision results (79.8) for all tested neural network architectures; it also showed the smallest decrease when changing the test data to another phantom

Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum

Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Since the price of Arabica is much higher than that of Robusta, this lack of information is not only an economical issue but a possible fraud to consumers, besides the potential allergic reaction that these mixtures may trigger in some individuals. In this paper, two sample preparation techniques were compared before the analysis of the total volatile organic compounds (VOCs) found in Robusta, Arabica, and in the mixture from both coffee types. The comparison of the signals obtained from the analyses showed that the VOCs concentration levels obtained from the headspace (HS) analyses were clearly higher than those obtained from the pre-concentration step where an adsorbent, an active charcoal strip (ACS + HS), was used. In the second part of this study, the possibility of using the headspace gas-chromatography ion mobility spectrometry (HS-GC-IMS) for the discrimination between Arabica, Robusta, and mixed coffee samples (n = 30) was evaluated. The ion mobility sum spectrum (IMSS) obtained from the analysis of the HS was used in combination with pattern recognition techniques, namely linear discrimination analysis (LDA), as an electronic nose. The identification of individual compounds was not carried out since chromatographic information was not used. This novel approach allowed the correct discrimination (100%) of all of the samples. A characteristic fingerprint for each type of coffee for a fast and easy identification was also developed. In addition, the developed method is ecofriendly, so it is a good alternative to traditional approaches

Impact of Automatic Aircraft Control on Flight Safety.

The work presents the phenomenon of automatic flight control of an aircraft. This is a great convenience used daily in thousands of aircraft every day. For the implementation of aviation tasks, small private and large passenger aircraft, such as Boeing and ATR. However, is it safe? The following analysis of accident and aviation accident reports will try to answer the key question whether automatic flight control systems are safe?Praca przedstawia zjawisko automatycznego sterowania lotem statku powietrznego. Jest to wielkie ułatwienie wykorzystywane codziennie w tysiącach samolotów każdego dnia. Do realizacji zadań lotniczych, małych samolotów prywatnych oraz wielkich pasażerskich, jak Boeing czy ATR. Jednak, czy jest ono bezpieczne? Poniższa analiza raportów wypadków oraz zdarzeń lotniczych postara się odpowiedzieć na kluczowe pytanie czy system automatycznego sterowania lotem są bezpieczne