A Halomethane thermochemical network from iPEPICO experiments and quantum chemical calculations

Internal energy selected halomethane cations CH3Cl+, CH2Cl2+, CHCl3+, CH3F+, CH2F2+, CHClF2+ and CBrClF2+ were prepared by vacuum ultraviolet photoionization, and their lowest energy dissociation channel studied using imaging photoelectron photoion coincidence spectroscopy (iPEPICO). This channel involves hydrogen atom loss for CH3F+, CH2F2+ and CH3Cl+, chlorine atom loss for CH2Cl2+, CHCl3+ and CHClF2+, and bromine atom loss for CBrClF2+. Accurate 0 K appearance energies, in conjunction with ab initio isodesmic and halogen exchange reaction energies, establish a thermochemical network, which is optimized to update and confirm the enthalpies of formation of the sample molecules and their dissociative photoionization products. The ground electronic states of CHCl3+, CHClF2+ and CBrClF2+ do not confirm to the deep well assumption, and the experimental breakdown curve deviates from the deep well model at low energies. Breakdown curve analysis of such shallow well systems supplies a satisfactorily succinct route to the adiabatic ionization energy of the parent molecule, particularly if the threshold photoelectron spectrum is not resolved and a purely computational route is unfeasible. The ionization energies have been found to be 11.47 ± 0.01 eV, 12.30 ± 0.02 eV and 11.23 ± 0.03 eV for CHCl3, CHClF2 and CBrClF2, respectively. The updated 0 K enthalpies of formation, ∆fHo0K(g) for the ions CH2F+, CHF2+, CHCl2+, CCl3+, CCl2F+ and CClF2+ have been derived to be 844.4 ± 2.1, 601.6 ± 2.7, 890.3 ± 2.2, 849.8 ± 3.2, 701.2 ± 3.3 and 552.2 ± 3.4 kJ mol–1, respectively. The ∆fHo0K(g) values for the neutrals CCl4, CBrClF2, CClF3, CCl2F2 and CCl3F and have been determined to be –94.0 ± 3.2, –446.6 ± 2.7, –702.1 ± 3.5, –487.8 ± 3.4 and –285.2 ± 3.2 kJ mol–1, respectively

Ciguatera mini review: 21st century environmental challenges and the interdisciplinary research efforts rising to meet them

Globally, the livelihoods of over a billion people are affected by changes to marine eco-systems, both structurally and systematically. Resources and ecosystem services, provided by the marine environment, contribute nutrition, income, and health benefits for communities. One threat to these securities is ciguatera poisoning; worldwide, the most commonly reported non‐bacterial seafood‐related illness. Ciguatera is caused by the consumption of (primarily) finfish contaminated with ciguatoxins, potent neurotoxins produced by benthic single‐cell microalgae. When consumed, ciguatoxins are biotransformed and can bioaccumulate throughout the food‐web via complex path-ways. Ciguatera‐derived food insecurity is particularly extreme for small island‐nations, where fear of intoxication can lead to fishing restrictions by region, species, or size. Exacerbating these com-plexities are anthropogenic or natural changes occurring in global marine habitats, e.g., climate change, greenhouse‐gas induced physical oceanic changes, overfishing, invasive species, and even the international seafood trade. Here we provide an overview of the challenges and opportunities of the 21st century regarding the many facets of ciguatera, including the complex nature of this illness, the biological/environmental factors affecting the causative organisms, their toxins, vectors, detection methods, human‐health oriented responses, and ultimately an outlook towards the future. Ciguatera research efforts face many social and environmental challenges this century. However, several future‐oriented goals are within reach, including digital solutions for seafood supply chains, identifying novel compounds and methods with the potential for advanced diagnostics, treatments, and prediction capabilities. The advances described herein provide confidence that the tools are now available to answer many of the remaining questions surrounding ciguatera and therefore protection measures can become more accurate and routine

Research Note: Persistent Salmonella problems in slaughterhouses related to clones linked to poultry companies

Salmonellosis remains one of the main foodborne zoonoses in Europe, with poultry products as the main source of human infections. The slaughterhouse has been identified as a potential source for Salmonella contamination of poultry meat. Despite the mandatory programme of the EU, there are companies with persistent Salmonella that are unable to remove the bacteria from their processing environment, compromising the entire production line. In this context, an intensive sampling study was conducted to investigate a slaughterhouse with persistent Salmonella problems, establishing the genetic relationship among Salmonella strains isolated during the slaughter process. A total of 36 broiler flocks were sampled during processing at the slaughterhouse. Salmonella was identified based on ISO 6579-1:2017 (Annex D), serotyped by Kauffman-White-Le-Minor technique, and the genetic relationship was assessed with ERIC-PCR followed by PFGE. The outcomes showed that 69.4% of the batches sampled carried Salmonella upon arrival at the slaughterhouse and that 46.3% of the different samples from carcasses were contaminated with Salmonella. The two serovars isolated at the different steps in the slaughterhouse were Enteritidis (98.2%) and Kentucky (1.8%). Pulsed-field gel electrophoresis analysis revealed a low genetic diversity, with all S. Enteritidis isolates showing a nearly identical pulsotype (similarity >85%) and S. Kentucky strains showed the same XbaI PFGE profile (95.0% genetic similarity). The results of this study showed a high genetic relationship among isolates recovered from carcasses and environmental samples in the slaughterhouse from both Salmonella-positive and Salmonella-free flocks. Salmonella strains re-circulated across to poultry flocks and re-entered the slaughterhouse to survive on the processing line. Thus, it is necessary to implement molecular diagnosis methods in time at the field level to determine the Salmonella epidemiology of the flock, to make rapid decisions for the control of Salmonella and prevent entry into the slaughterhouse environment.info:eu-repo/semantics/publishedVersio

Whole-Genome Sequences and Classification of

In collaboration with the CDC’s Streptococcus Laboratory, we report here the whole-genome sequences of seven Streptococcus agalactiae bacteria isolated from laboratory-reared Long-Evans rats. Four of the S. agalactiae isolates were associated with morbidity accompanied by endocarditis, metritis, and fatal septicemia, providing an opportunity for comparative genomic analysis of this opportunistic pathogen.United States. National Institutes of Health (T32-OD010978)United States. National Institutes of Health (P30-ES002109

End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions

[EN] The correct assessment and characterization of heart anatomy and functionality is usually done through inspection of magnetic resonance image cine sequences. In the clinical setting it is especially important to determine the state of the left ventricle. This requires the measurement of its volume in the end-diastolic and end-systolic frames within the sequence trough segmentation methods. However, the first step required for this analysis before any segmentation is the detection of the end-systolic and end-diastolic frames within the image acquisition. In this work we present a fully convolutional neural network that makes use of dilated convolutions to encode and process the temporal information of the sequences in contrast to the more widespread use of recurrent networks that are usually employed for problems involving temporal information. We trained the network in two different settings employing different loss functions to train the network: the classical weighted cross-entropy, and the weighted Dice loss. We had access to a database comprising a total of 397 cases. Out of this dataset we used 98 cases as test set to validate our network performance. The final classification on the test set yielded a mean frame distance of 0 for the end-diastolic frame (i.e.: the selected frame was the correct one in all images of the test set) and 1.242 (relative frame distance of 0.036) for the end-systolic frame employing the optimum setting, which involved training the neural network with the Dice loss. Our neural network is capable of classifying each frame and enables the detection of the end-systolic and end-diastolic frames in short axis cine MRI sequences with high accuracy.Funding sources This work was partially supported by the Conselleria d'Innovació, Universitats, Ciència i Societat Digital, Generalitat Valenciana (grants AEST/2020/029 and AEST/2021/050) .Pérez-Pelegrí, M.; Monmeneu, JV.; López-Lereu, MP.; Maceira, AM.; Bodi, V.; Moratal, D. (2022). End-systole and end-diastole detection in short axis cine MRI using a fully convolutional neural network with dilated convolutions. Computerized Medical Imaging and Graphics. 99:1-8. https://doi.org/10.1016/j.compmedimag.2022.102085189

Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology

[EN] Background and objective: Magnetic resonance imaging is the most reliable imaging technique to assess the heart. More specifically there is great importance in the analysis of the left ventricle, as the main pathologies directly affect this region. In order to characterize the left ventricle, it is necessary to extract its volume. In this work we present a neural network architecture that is capable of directly estimating the left ventricle volume in short axis cine Magnetic Resonance Imaging in the end-diastolic frame and provide a segmentation of the region which is the basis of the volume calculation, thus offering explain-ability to the estimated value. Methods: The network was designed to directly target the volumes to estimate, not requiring any labeled segmentation on the images. The network was based on a 3D U-net with extra layers defined in a scan-ning module that learned features like the circularity of the objects and the volumes to estimate in a weakly-supervised manner. The only targets defined were the left ventricle volumes and the circularity of the object detected through the estimation of the pi value derived from its shape. We had access to 397 cases corresponding to 397 different subjects. We randomly selected 98 cases to use as test set. Results: The results show a good match between the real and estimated volumes in the test set, with a mean relative error of 8% and a mean absolute error of 9.12 ml with a Pearson correlation coefficient of 0.95. The derived segmentations obtained by the network achieved Dice coefficients with a mean value of 0.79. Conclusions: The proposed method is capable of obtaining the left ventricle volume biomarker in the end-diastole and offer an explanation of how it obtains the result in the form of a segmentation mask without the need of segmentation labels to train the algorithm, making it a potentially more trustworthy method for clinicians and a way to train neural networks more easily when segmentation labels are not readily available.The authors acknowledge financial support from the Consel-leria d'Educacio, Investigacio, Cultura i Esport, Generalitat Valenciana (grants AEST/2019/037 and AEST/2020/029) , from the Agencia Valenciana de la Innovacion, Generalitat Valenciana (ref. INNCAD00/19/085) , and from the Centro para el Desarrollo Tecnologico Industrial (Programa Eurostars2, actuacion Interempresas Internacional) , Spanish Ministerio de Ciencia, Innovacion y Universidades (ref. CIIP-20192020) .Pérez-Pelegrí, M.; Monmeneu, JV.; López-Lereu, MP.; Pérez-Pelegrí, L.; Maceira, AM.; Bodi, V.; Moratal, D. (2021). Automatic left ventricle volume calculation with explainability through a deep learning weak-supervision methodology. Computer Methods and Programs in Biomedicine. 208:1-8. https://doi.org/10.1016/j.cmpb.2021.106275S1820

Litter aeration and spread of Salmonella in broilers

Litter quality in the poultry sector is one of the main parameters of health, productivity, and animal welfare. Therefore, innovative management methods have been developed to improve the quality of litter. One of them is litter aeration (LA) by tumbling. However, there is little information related to the effect of this technique on the spreading of pathogens of public health importance such as Salmonella. In this context, the objective of this study was to determine the epidemiology of Salmonella in poultry farms, when serial LA were implemented during the rearing cycle of broilers. For this purpose, an experimental broiler farm with 3 identical rooms was used in the study. Two rooms were assigned to the LA treatment, and the other one served as the control room. Environmental samples were taken in poultry houses after LA in 4 consecutive weeks at the end of the cycle. All samples collected were analyzed according to the standards of the International Organization for Standardization (ISO 6579:2002, Annex D). The results of this study showed that in the control and treated rooms, the percentage of positive samples for Salmonella decreased in the first 3 LA sessions (LA 1, LA 2, and LA 3). However, in the last LA session of rearing (LA 4), the percentage of positive samples increased from 8.2 to 33.2% in the control room instead the treated rooms where the positive samples decreased (P = 0.017). Thus, the aeration of the litter as litter management technique in poultry broiler production does not increase the shedding or the spread of Salmonella throughout broiler houses. In addition, it could be an effective technique to reduce the infective pressure of this bacterium in several areas of the farm or in certain moments of the rearing period with more risk of multiplication and spreading of Salmonella