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Abstract Background 3D cell culture models have recently garnered increasing attention for replicating organ microarchitecture and eliciting in vivo-like responses, holding significant promise across various biological disciplines. Broadly, 3D cell culture encompasses organoids as well as single- and multicellular spheroids. While the latter have found successful applications in tumor research, there is a notable scarcity of standardized intestinal models for infection biology that mimic the microarchitecture of the intestine. Hence, this study aimed to develop structured multicellular intestinal spheroids (SMIS) specifically tailored for studying molecular basis of infection by intestinal pathogens. Results We have successfully engineered human SMIS comprising four relevant cell types, featuring a fibroblast core enveloped by an outer monolayer of enterocytes and goblet cells along with monocytic cells. These SMIS effectively emulate the in vivo architecture of the intestinal mucosal surface and manifest differentiated morphological characteristics, including the presence of microvilli, within a mere two days of culture. Through analysis of various differentiation factors, we have illustrated that these spheroids attain heightened levels of differentiation compared to 2D monolayers. Moreover, SMIS serve as an optimized intestinal infection model, surpassing the capabilities of traditional 2D cultures, and exhibit a regulatory pattern of immunological markers similar to in vivo infections after Campylobacter jejuni infection. Notably, our protocol extends beyond human spheroids, demonstrating adaptability to other species such as mice and pigs. Conclusion Based on the rapid attainment of enhanced differentiation states, coupled with the emergence of functional brush border features, increased cellular complexity, and replication of the intestinal mucosal microarchitecture, which allows for exposure studies via the medium, we are confident that our innovative SMIS model surpasses conventional cell culture methods as a superior model. Moreover, it offers advantages over stem cell-derived organoids due to scalability and standardization capabilities of the protocol. By showcasing differentiated morphological attributes, our model provides an optimal platform for diverse applications. Furthermore, the investigated differences of several immunological factors compared to monotypic monolayers after Campylobacter jejuni infection underline the refinement of our spheroid model, which closely mimics important features of in vivo infections.

Abstract Background We quantified SARS-CoV-2 dynamics in different community settings and the direct and indirect effect of the BNT162b2 mRNA vaccine in Monaco for different variants of concern (VOC). Methods Between July 2021 and September 2022, we prospectively investigated 20,443 contacts from 6320 index cases using data from the Monaco COVID-19 Public Health Programme. We calculated secondary attack rates (SARs) in households (n = 13,877), schools (n = 2508) and occupational (n = 6499) settings. We used binomial regression with a complementary log–log link function to measure adjusted hazard ratios (aHR) and vaccine effectiveness (aVE) for index cases to infect contacts and contacts to be infected in households. Results In households, the SAR was 55% (95% CI 54–57) and 50% (48–51) among unvaccinated and vaccinated contacts, respectively. The SAR was 32% (28–36) and 12% (10–13) in workplaces, and 7% (6–9) and 6% (3–10) in schools, among unvaccinated and vaccinated contacts respectively. In household, the aHR was lower in contacts than in index cases (aHR 0.68 [0.55–0.83] and 0.93 [0.74–1.1] for delta; aHR 0.73 [0.66–0.81] and 0.89 [0.80–0.99] for omicron BA.1&2, respectively). Vaccination had no significant effect on either direct or indirect aVE for omicron BA.4&5. The direct aVE in contacts was 32% (17, 45) and 27% (19, 34), and for index cases the indirect aVE was 7% (− 17, 26) and 11% (1, 20) for delta and omicron BA.1&2, respectively. The greatest aVE was in contacts with a previous SARS-CoV-2 infection and a single vaccine dose during the omicron BA.1&2 period (45% [27, 59]), while the lowest were found in contacts with either three vaccine doses (aVE − 24% [− 63, 6]) or one single dose and a previous SARS-CoV-2 infection (aVE − 36% [− 198, 38]) during the omicron BA.4&5 period. Conclusions Protection conferred by the BNT162b2 mRNA vaccine against transmission and infection was low for delta and omicron BA.1&2, regardless of the number of vaccine doses and previous SARS-CoV-2 infection. There was no significant vaccine effect for omicron BA.4&5. Health authorities carrying out vaccination campaigns should bear in mind that the current generation of COVID-19 vaccines may not represent an effective tool in protecting individuals from either transmitting or acquiring SARS-CoV-2 infection.

CWA Power develops, owns, and operates several CSP projects, including the largest one in the world. One of the primary objectives for companies in the Concentrated Solar Power (CSP) sector is to lower the electricity costs associated with CSP plants. This goal extends not only to existing operational plants but also to future projects. Enhancing plant performance is a key pathway to achieving this cost reduction. CSP performance models play a pivotal role in this journey by allowing us to analyse different configurations, changes, or modifications without the necessity of their physical implementation. In 2015, ACWA Power made a strategic decision to develop its own CSP performance models. This move aimed to enhance ACWA Power’s competitiveness for upcoming projects while also supporting operational plants by identifying avenues for performance improvement. The decision was made to create models for the two prevailing CSP technologies: Parabolic Trough with thermal oil as the heat transfer fluid (HTF) and molten salt storage system, as well as solar tower with molten salts.

This study investigates the prevalence of Vibrio spp. in seafood from supermarkets and fish markets in Berlin, Germany. A total of 306 seafood samples, including shrimp and mussels, were bought from supermarkets between March 2023 and January 2024. Samples were analysed using the ISO standard method and multiplex PCR to identify V. parahaemolyticus, V. alginolyticus, V. cholerae and V. vulnificus. The results indicated an overall Vibrio spp. prevalence of 56%. Among the positive samples, the most prevalent species found was V. parahaemolyticus (58%), followed by V. alginolyticus (42%), V. cholerae non-O1/non-O139 (25%), and V. vulnificus (4%). Samples obtained from supermarkets exhibited a lower prevalence (50%) than those received from fish markets (91%). Virulence genes such as ctxA, tdh, or trh were not detected in the respective Vibrio species. Nevertheless, the high prevalence underscores the need and urgency of continuous seafood surveillance.

A CSP Plant and in particular the solar field has hundreds of thousands of components and the corresponding process parameters. This needs to be monitored and evaluated every day to make sure that the plant is working efficiently. A performance assessment with a production simulation is done daily where the expected and actual power production are compared. Such evaluation is usually done with the plant performance model and the necessary data is compiled in calculation programs like Excel. The work is repetitive, time consuming and human errors may easily occur. Typically, the evaluations are done from different parties with deviating results and conclusions. ACWA Power has developed an online simulation platform to automatize the data processing to increase the data reliability and reduce the time effort. The application has been implemented in the Noor Energy 1 hybrid solar plant in Dubai and shall be presented in this paper.

Abstract Background Zoonotic microorganisms are increasingly impacting human health worldwide. Due to the development of the global population, humans and animals live in shared and progressively crowded ecosystems, which enhances the risk of zoonoses. Although Campylobacter species are among the most important bacterial zoonotic agents worldwide, the molecular mechanisms of many host and pathogen factors involved in colonisation and infection are poorly understood. Campylobacter jejuni colonises the crypts of the human colon and causes acute inflammatory processes. The mucus and associated proteins play a central host-protective role in this process. The aim of this study was to explore the regulation of specific glycosyltransferase genes relevant to differential mucin-type O-glycosylation that could influence host colonisation and infection by C. jejuni. Results Since microRNAs are known to be important regulators of the mammalian host cell response to bacterial infections, we focussed on the role of miR-125a-5p in C. jejuni infection. Combining in vitro and in vivo approaches, we show that miR-125a-5p regulates the expression of the sialyltransferase ST3GAL1 in an infection-dependent manner. The protein ST3GAL1 shows markedly increased intestinal levels in infected mice, with enhanced distribution in the mucosal epithelial layer in contrast to naïve mice. Conclusion From our previous studies and the data presented here, we conclude that miR-125a-5p and the previously reported miR-615-3p are involved in regulating the glycosylation patterns of relevant host cell response proteins during C. jejuni infection. The miRNA-dependent modulation of mucin-type O-glycosylation could be part of the mucosal immune response, but also a pathogen-driven modification that allows colonisation and infection of the mammalian host.

Abstract In plant science, the suboptimal match of growing conditions hampers the transfer of knowledge from controlled environments in glasshouses or climate chambers to field environments. Here we present the PhenoSphere, a plant cultivation infrastructure designed to simulate field-like environments in a reproducible manner. To benchmark the PhenoSphere, the effects on plant growth of weather conditions of a single maize growing season and of an averaged season over three years are compared to those of a standard glasshouse and of four years of field trials. The single season simulation proves superior to the glasshouse and the averaged season in the PhenoSphere: The simulated weather regime of the single season triggers plant growth and development progression very similar to that observed in the field. Hence, the PhenoSphere enables detailed analyses of performance-related trait expression and causal biological mechanisms in plant populations exposed to weather conditions of current and anticipated future climate scenarios.

Abstract Background Fever is a common reason to seek healthcare in Southeast Asia, and the decline of malaria has complexified how is perceived, and what actions are taken towards it. We investigated the concept of fever and the determinants influencing health-seeking behaviours among migrants on the Thai-Myanmar border, where rapid economic development collides with precarious political and socio-economic conditions. Methods We implemented a mixed-methods study between August to December 2019. Phase I used a qualitative approach, with in-depth interviews and focus group discussions. Phase II used a quantitative approach with a close-ended questionnaire based on Phase I findings. A conditional inference tree (CIT) model first identified geographic and socio-demographic determinants, which were then tested using a logistic regression model. Results Fever corresponded to a high diversity of conceptions, symptoms and believed causes. Self-medication was the commonest behaviour at fever onset. If fever persisted, migrants primarily sought care in humanitarian cost-free clinics (45.5%, 92/202), followed by private clinics (43.1%, 87/202), health posts (36.1%, 73/202), public hospitals (33.7%, 68/202) and primary care units (30, 14.9%). The qualitative analysis identified distance and legal status as key barriers for accessing health care. The quantitative analysis further investigated determinants influencing health-seeking behaviour: living near a town where a cost-free clinic operated was inversely associated with seeking care at health posts (adjusted odds ratio [aOR], 0.40, 95% confidence interval [95% CI] [0.19–0.86]), and public hospital attendance (aOR 0.31, 95% CI [0.14–0.67]). Living further away from the nearest town was associated with health posts attendance (aOR 1.05, 95% CI [1.00–1.10] per 1 km). Having legal status was inversely associated with cost-free clinics attendance (aOR 0.27, 95% CI [0.10–0.71]), and positively associated with private clinic and public hospital attendance (aOR 2.56, 95% CI [1.00–6.54] and 5.15, 95% CI [1.80–14.71], respectively). Conclusions Fever conception and believed causes are context-specific and should be investigated prior to any intervention. Distance to care and legal status were key determinants influencing health-seeking behaviour. Current economic upheavals are accelerating the unregulated flow of undocumented migrants from Myanmar to Thailand, warranting further inclusiveness and investments in the public health system.

Detection of spikes is the first important step toward image-based quantitative assessment of crop yield. However, spikes of grain plants occupy only a tiny fraction of the image area and often emerge in the middle of the mass of plant leaves that exhibit similar colors to spike regions. Consequently, accurate detection of grain spikes renders, in general, a non-trivial task even for advanced, state-of-the-art deep neural networks (DNNs). To improve pattern detection in spikes, we propose architectural changes to Faster-RCNN (FRCNN) by reducing feature extraction layers and introducing a global attention module. The performance of our extended FRCNN-A vs. conventional FRCNN was compared on images of different European wheat cultivars, including “difficult” bushy phenotypes from 2 different phenotyping facilities and optical setups. Our experimental results show that introduced architectural adaptations in FRCNN-A helped to improve spike detection accuracy in inner regions. The mean average precision (mAP) of FRCNN and FRCNN-A on inner spikes is 76.0% and 81.0%, respectively, while on the state-of-the-art detection DNNs, Swin Transformer mAP is 83.0%. As a lightweight network, FRCNN-A is faster than FRCNN and Swin Transformer on both baseline and augmented training datasets. On the FastGAN augmented dataset, FRCNN achieved a mAP of 84.24%, FRCNN-A attained a mAP of 85.0%, and the Swin Transformer achieved a mAP of 89.45%. The increase in mAP of DNNs on the augmented datasets is proportional to the amount of the IPK original and augmented images. Overall, this study indicates a superior performance of attention mechanisms-based deep learning models in detecting small and subtle features of grain spikes.

Purpose: In previous studies, it has been shown that diode laser radiation at a wavelength of 810 nm is able to kill bacteria in infected root canals. These studies were mostly in vitro studies and dealt only with selected bacterial species. The present clinical study compares the antibacterial activity of a high power diode laser with 5% sodium hypochlorite (NaOCl) solution in root canals. Materials and Methods: Thirty single-rooted nonvital teeth from thirty patients were randomly subdivided into two groups. The first group underwent laser treatment in addition to canal preparation, and the second group was instrumented and irrigated with 5% NaCCl. Before and after each treatment session, microbiological samples were taken. The teeth were treated at three appointments without intracanal dressings between appointments. Results: All 30 root canals showed cultivable flora before treatment. Endodontic treatment reduced microbes both in terms of number of infected canals and number of species. At the last treatment session, laser application resulted in 11 and NaOCl irrigation in 10 bacteria-free canals (p > 0.05 according to the Chi-square test). Conclusion: The study indicates that the use of diode laser radiation is as effective in disinfecting root canals as irrigation with 5% sodium hypochlorite. [ABSTRACT FROM AUTHOR]

Salmonella enterica subsp. enterica serovar Agona has a history of causing food-borne outbreaks and any emergence of multidrug-resistant (MDR) isolates in novel food products is of concern. Particularly, in food products frequently consumed without sufficient heating prior to consumption. Here, we report about the MDR isolate, 18-SA00377, which had been isolated from a dietary supplement in Germany in 2018 and submitted to the German National Reference Laboratory for Salmonella. WGS-based comparative genetic analyses were conducted to find a potential reservoir of the isolate itself or mobile genetic elements associated with MDR. As a phylogenetic analysis did not yield any closely related S. Agona isolates, either globally or from Germany, a detailed analysis of the largest plasmid (295,499 bp) was performed as it is the main carrier of resistances. A combined approach of long-read and short-read sequencing enabled the assembly of the isolate’s chromosome and its four plasmids. Their characterization revealed the presence of 23 different antibiotic resistance genes (ARGs), conferring resistance to 12 different antibiotic drug classes, as well as genes conferring resistance to six different heavy metals. The largest plasmid, pSE18-SA00377-1, belongs to the IncHI2 plasmid family and carries 16 ARGs, that are organized as two distinct clusters, with each ARG associated with putative composite transposons. Through a two-pronged approach, highly similar plasmids to pSE18-SA00377-1 were identified in the NCBI database and a search for Salmonella isolates with a highly similar ARG resistance profile was conducted. Mapping and structural comparisons between pSE18-SA00377-1 and these plasmids and Salmonella isolates showed that both the plasmid backbone and identical or similar ARG clusters can be found not only in Salmonella isolates, originating mostly from a wide variety of livestock, but also in a diverse range of bacterial genera of varying geographical origins and isolation sources. Thus, it can be speculated that the host range of pSE18-SA00377-1 is not restricted to Salmonella and its spread already occurred in different bacterial populations. Overall, this hints at a complex history for pSE18-SA00377-1 and highlights the importance of surveilling multidrug-resistant S. enterica isolates, especially in novel food items that are not yet heavily regulated.

In recent years, various automated methods for plant phenotyping addressing roots or shoots have been developed and corresponding platforms have been established to meet the diverse requirements of plant research and breeding. However, most platforms are only either able to phenotype shoots or roots of plants but not both simultaneously. This substantially limits the opportunities offered by a joint assessment of the growth and development dynamics of both organ systems, which are highly interdependent. In order to overcome these limitations, a root phenotyping installation was integrated into an existing automated non-invasive high-throughput shoot phenotyping platform. Thus, the amended platform is now capable of conducting high-throughput phenotyping at the whole-plant level, and it was used to assess the vegetative root and shoot growth dynamics of five maize inbred lines and four hybrids thereof, as well as the responses of five inbred lines to progressive drought stress. The results showed that hybrid vigour (heterosis) occurred simultaneously in roots and shoots and was detectable as early as 4 days after transplanting (4 DAT; i.e., 8 days after seed imbibition) for estimated plant height (EPH), total root length (TRL), and total root volume (TRV). On the other hand, growth dynamics responses to progressive drought were different in roots and shoots. While TRV was significantly reduced 10 days after the onset of the water deficit treatment, the estimated shoot biovolume was significantly reduced about 6 days later, and EPH showed a significant decrease even 2 days later (8 days later than TRV) compared with the control treatment. In contrast to TRV, TRL initially increased in the water deficit period and decreased much later (not earlier than 16 days after the start of the water deficit treatment) compared with the well-watered plants. This may indicate an initial response of the plants to water deficit by forming longer but thinner roots before growth was inhibited by the overall water deficit. The magnitude and the dynamics of the responses were genotype-dependent, as well as under the influence of the water consumption, which was related to plant size.

In recent years, the number of foodborne infections with non-O1 and non-O139 Vibrio cholerae (NOVC) has increased worldwide. These have ranged from sporadic infection cases to localized outbreaks. The majority of case reports describe self-limiting gastroenteritis. However, severe gastroenteritis and even cholera-like symptoms have also been described. All reported diarrheal cases can be traced back to the consumption of contaminated seafood. As climate change alters the habitats and distribution patterns of aquatic bacteria, there is a possibility that the number of infections and outbreaks caused by Vibrio spp. will further increase, especially in countries where raw or undercooked seafood is consumed or clean drinking water is lacking. Against this background, this review article focuses on a possible infection pathway and how NOVC can survive in the human host after oral ingestion, colonize intestinal epithelial cells, express virulence factors causing diarrhea, and is excreted by the human host to return to the environment.

C-reactive protein (CRP) point-of-care testing can reduce antibiotic prescribing in primary care patients with febrile and respiratory illness, yet little is known about its effects on treatment-seeking behavior. If patients go on to source antibiotics elsewhere, the impact of CRP testing will be limited. A randomized controlled trial assessed the impact of CRP testing on antibiotic prescriptions in Myanmar and Thai primary care patients with a febrile illness. Here we report patients’ treatmentseeking behavior before and during the twoweek study period. Self-reported antibiotic use is compared against urine antibacterial activity. Patients’ opinions towards CRP testing were evaluated. Antibiotic use before study enrolment was reported by 5.4% while antimicrobial activity was detected in 20.8% of samples tested. During the study period, 14.8% of the patients sought additional healthcare, and 4.3% sourced their own antibiotics. Neither were affected by CRP testing. Overall, patients’ satisfaction with their care and CRP testing was high. CRP testing did not affect patients’ treatment-seeking behavior during the study period whilst modestly reducing antibiotic prescriptions. CRP testing appears to be acceptable to patients and their caregivers.

Efficient and reliable desalination through seawater reverse osmosis (SWRO) mandates optimized pre-treatment strategies to minimize organic and inorganic fouling. Coagulation, the process of agglomerating colloidal particles using chemical coagulants, in combination with media filtration to reduce colloidal fouling on reverse osmosis membranes is commonly used in seawater pretreatment. Due to its inherent complexity and the absence of physical models to quantify the efficiency of coagulation, overdosing of coagulants is ubiquitously observed to maintain filtered water quality. To address this problem, we use Artificial neural networks (ANNs) to optimize coagulant dosing by predicting the SDI after chemical dosing. The model is developed by using large-scale plant data comprising of different seawater physical parameters and plant operational data including pH, SDI, turbidity, coagulant dosing rate, and flocculant dosing rate. By using feature engineering, selection, and our domain knowledge, new input parameters are derived, irrelevant parameters are eliminated, and these are used as inputs to train the model. The developed ANNs model achieved a prediction accuracy of 95% also outperforms other machine learning methods, and upon industrialization it reduced annual coagulant consumption by 11.7% when implemented in a commercial SWRO plant producing 216,000 m3/day of desalinated water.

Abstract Background Members of the genus Arcobacter are considered as emerging zoonotic food and waterborne pathogens that cause gastroenteritis and bacteremia in humans. However, the potential risk that Arcobacter species pose to public health remains unassessed in various countries, including Baltic states. Therefore, the aim of this study was to determine the prevalence, antimicrobial susceptibility and presence of putative virulence genes of Arcobacter isolates recovered from humans, food products and environmental water in Lithuania. Results A total of 1862 samples were collected and examined from 2018 to 2020 in the city of Kaunas. Overall, 11.2% (n = 208) of the samples were positive for the presence of Arcobacter spp. The highest prevalence was detected in chicken meat (36%), followed by environmental water (28.1%), raw cow milk (25%), ready-to-eat salad mixes (7.1%) and human stool (1.7%). A. butzleri was the most frequently isolated species (n = 192; 92.3%), followed by A. cryaerophilus (n = 16; 7.7%). Arcobacter spp. antimicrobial susceptibility testing revealed unimodally distributed aggregated minimal inhibitory concentrations (MICs) for gentamicin, tetracycline, ciprofloxacin, ampicillin and erythromycin. However, a bimodal distribution for azithromycin was found with 96.2% of determined MICs above the epidemiological cut-off value (ECOFF) defined for Campylobacter jejuni (0.25 µg/ml). Majority of the Arcobacter isolates (n = 187; 89.9%) showed high susceptibility to ciprofloxacin with MICs below or equal to the ECOFF value of 0.5 µg/ml. The putative virulence genes cadF (100%), ciaB (100%), cj1349 (99%), tlyA (99%), mviN (97.9%) and pldA (95.8%) were the predominant genes detected among A. butzleri isolates. In contrast, the mviN and ciaB genes were present in all, whereas cj1349 (12.5%), tlyA (25%) and hecA (12.5%) were only detected in few A. cryaerophilus isolates. Conclusions Our results demonstrate that food products and environmental water in Lithuania are frequently contaminated with Arcobacter spp. that carry multiple putative virulence genes. Furthermore, A. butzleri were isolated from 1.7% of inpatients. Fluoroquinolones and aminoglycosides were found to be more effective against Arcobacter in comparison to other antimicrobial agents. However, further studies are needed to determine the pathogenic mechanisms and factors that facilitate the spread of Arcobacter infections.

Several foodborne outbreaks associated with food of non-animal origin (FNAO) were reported within the last years. In recent years, Listeria monocytogenes has been associated with such outbreaks. For this reason, different producers of FNAO at the primary production and processing level in Bavaria, Germany, were inspected from July 2020 to June 2021. Environmental and food sampling as well as the sampling of irrigation and processing water was performed to investigate the prevalence of Listeria spp., including L. monocytogenes at facilities that produce ready-to-eat FNAO. Altogether, 39 producers of soft fruit, vegetables, ready-to-eat raw fruits, and vegetables/fresh cut were inspected. In addition to the on-spot inspections, 407 samples were taken in total, among them, 229 were swab samples from food contact material and the environment, 59 food samples (including soft fruit, vegetables and ready-to-eat vegetables), and 119 samples of irrigation and processing water. Samples were analyzed using methods according to ISO 11290-1:2017. Furthermore, the samples of irrigation and processing water were also quantitatively tested for the number of Escherichia coli (ISO 9308-2:2014-06), enterococci (ISO 7899-2:2000-11), and Pseudomonas aeruginosa (ISO 16266:2008-05). No contamination with E. coli, enterococci, and P. aeruginosa could be detected in most of the samples. Overall, in 12.53% of the samples, Listeria spp. were detected. L. monocytogenes was identified in 1.72% of the environmental and processing water samples, whereas L. monocytogenes was not detected in food samples.In addition to water sources and quality, this study demonstrates that irrigation regime, cultivation, hygienic handling, and maintenance protocols are highly important to reduce the potential contamination of ready-to-eat soft fruits and vegetables with Listeria spp.

Non-O1 and non-O139 Vibrio cholerae (NOVC) can cause gastrointestinal infections in humans. Contaminated food, especially seafood, is an important source of human infections. In this study, the virulence potential of 63 NOVC strains isolated from retail seafood were characterized at the genotypic and phenotypic levels. Although no strain encoded the cholera toxin (CTX) and the toxin-coregulated pilus (TCP), several virulence factors, including the HlyA hemolysin, the cholix toxin ChxA, the heat-stable enterotoxin Stn, and genes coding for the type 3 and type 6 secretion systems, were detected. All strains showed hemolytic activity against human and sheep erythrocytes: 90% (n = 57) formed a strong biofilm, 52% (n = 33) were highly motile at 37 °C, and only 8% (n = 5) and 14% (n = 9) could resist ≥60% and ≥40% human serum, respectively. Biofilm formation and toxin regulation genes were also detected. cgMLST analysis demonstrated that NOVC strains from seafood cluster with clinical NOVC strains. Antimicrobial susceptibility testing (AST) results in the identification of five strains that developed non-wildtype phenotypes (medium and resistant) against the substances of the classes of beta-lactams (including penicillin, carbapenem, and cephalosporin), polymyxins, and sulphonamides. The phenotypic resistance pattern could be partially attributed to the acquired resistance determinants identified via in silico analysis. Our results showed differences in the virulence potential of the analyzed NOVC isolated from retail seafood products, which may be considered for further pathogenicity evaluation and the risk assessment of NOVC isolates in future seafood monitoring.

ABSTRACT: The aim of this work was to evaluate whether there is any influence of temporary soil flooding on the agronomic performance and yield of wheat varieties. The experimental design was completely random blocks, in an 11x2 factorial scheme (eleven varieties and two soil water conditions), with four replications. Stress was imposed in the stage prior to plant anthesis. The assessments were made in two seasons (2016/2017) in relation to the number of spikelets in the main ear, number of seeds in the main ear, mass of seeds in the main ear, number of seeds in the tiller ear, mass of seeds in the tiller ear and yield in the useful area. The physical attributes number of seeds, seed mass and wheat seed yield, according to variety and agricultural year, are negatively affected by the temporary flooding (12 days) of the soil. There is influence of temporary soil flooding on the agronomic performance and yield of wheat varieties. The varieties TBio Toruk, TBio Sinuelo, TBio Sintonia, and CD151 are superior in soil flooding condition for the number of spikelets, number of seeds end for the seed mass attribute. In the soil at field capacity, the seeds produced have higher yield compared to those produced under flooding period, reaching about 309.2 Kg more for the variety TBio Sinuelo, 262 Kg for TBio Toruk and 114 Kg in CD1303.

Abstract High-throughput root phenotyping in the soil became an indispensable quantitative tool for the assessment of effects of climatic factors and molecular perturbation on plant root morphology, development and function. To efficiently analyse a large amount of structurally complex soil-root images advanced methods for automated image segmentation are required. Due to often unavoidable overlap between the intensity of fore- and background regions simple thresholding methods are, generally, not suitable for the segmentation of root regions. Higher-level cognitive models such as convolutional neural networks (CNN) provide capabilities for segmenting roots from heterogeneous and noisy background structures, however, they require a representative set of manually segmented (ground truth) images. Here, we present a GUI-based tool for fully automated quantitative analysis of root images using a pre-trained CNN model, which relies on an extension of the U-Net architecture. The developed CNN framework was designed to efficiently segment root structures of different size, shape and optical contrast using low budget hardware systems. The CNN model was trained on a set of 6465 masks derived from 182 manually segmented near-infrared (NIR) maize root images. Our experimental results show that the proposed approach achieves a Dice coefficient of 0.87 and outperforms existing tools (e.g., SegRoot) with Dice coefficient of 0.67 by application not only to NIR but also to other imaging modalities and plant species such as barley and arabidopsis soil-root images from LED-rhizotron and UV imaging systems, respectively. In summary, the developed software framework enables users to efficiently analyse soil-root images in an automated manner (i.e. without manual interaction with data and/or parameter tuning) providing quantitative plant scientists with a powerful analytical tool.

Abstract Background Campylobacter jejuni (C. jejuni) infections are of increasing importance worldwide. As a typical mucosal pathogen, the interaction of C. jejuni with mucins is a prominent step in the colonisation of mucosal surfaces. Despite recent advances in understanding the interaction between bacterial pathogens and host mucins, the mechanisms of mucin glycosylation during intestinal C. jejuni infection remain largely unclear. This prompted us to identify relevant regulatory networks that are concerted by miRNAs and could play a role in the mucin modification and interaction. Results We firstly used a human intestinal in vitro model, in which we observed altered transcription of MUC2 and TFF3 upon C. jejuni NCTC 11168 infection. Using a combined approach consisting of in silico analysis together with in vitro expression analysis, we identified the conserved miRNAs miR-125a-5p and miR-615-3p associated with MUC2 and TFF3. Further pathway analyses showed that both miRNAs appear to regulate glycosyltransferases, which are related to the KEGG pathway ‘Mucin type O-glycan biosynthesis’. To validate the proposed interactions, we applied an in vivo approach utilising a well-established secondary abiotic IL-10−/− mouse model for infection with C. jejuni 81-176. In colonic tissue samples, we confirmed infection-dependent aberrant transcription of MUC2 and TFF3. Moreover, two predicted glycosyltransferases, the sialyltransferases ST3GAL1 and ST3GAL2, exhibited inversely correlated transcriptional levels compared to the expression of the identified miRNAs miR-125a-5p and miR-615-3p, respectively. In this study, we mainly focused on the interaction between miR-615-3p and ST3GAL2 and were able to demonstrate their molecular interaction using luciferase reporter assays and RNAi. Detection of ST3GAL2 in murine colonic tissue by immunofluorescence demonstrated reduced intensity after C. jejuni 81-176 infection and was thus consistent with the observations made above. Conclusions We report here for the first time the regulation of glycosyltransferases by miRNAs during murine infection with C. jejuni 81-176. Our data suggest that mucin type O-glycan biosynthesis is concerted by the interplay of miRNAs and glycosyltransferases, which could determine the shape of intestinal glycosylated proteins during infection.

3D real-space analysis of thick nanoparticle crystals is non-trivial. Here, the authors demonstrate the structural analysis of a bulk-like Laves phase by imaging an off-stoichiometric binary mixture of hard-sphere-like nanoparticles in spherical confinement by electron tomography, enabling defect analysis on the single-particle level.

The increasing relevance of improved therapeutic monoclonal antibodies (mAbs) to treat neurodegenerative diseases has strengthened the need to reliably measure their brain pharmacokinetic (PK) profiles. The aim of this study was, therefore, to absolutely quantify the therapeutic antibody ocrelizumab (OCR) as a model antibody in mouse brain interstitial fluid (ISF), and to record its PK profile by using cerebral open flow microperfusion (cOFM). Further, to monitor the blood–brain barrier (BBB) integrity using an endogenous antibody with a similar molecular size as OCR. The study was conducted on 13 male mice. Direct and absolute OCR quantification was performed with cOFM in combination with zero flow rate, and subsequent bioanalysis of the obtained cerebral ISF samples. For PK profile recording, cerebral ISF samples were collected bi-hourly, and brain tissue and plasma were collected once at the end of the sampling period. The BBB integrity was monitored during the entire PK profile recording by using endogenous mouse immunoglobulin G1. We directly and absolutely quantified OCR and recorded its brain PK profile over 96 h. The BBB remained intact during the PK profile recording. The resulting data provide the basis for reliable PK assessment of therapeutic antibodies in the brain thus favoring the further development of therapeutic monoclonal antibodies.

Global ocean warming results in an increase of infectious diseases including an elevated emergence of Vibrio spp. in Northern Europe. The European Centre for Disease Prevention and Control reported annual periods of high to very high risks of infection with Vibrio spp. during summer months along the North Sea and Baltic Sea coasts. Based on those facts, the risk of Vibrio infections associated with recreational bathing in European coastal waters increases. To obtain an overview of the seasonal and spatial distribution of potentially human pathogenic Vibrio spp. at German coasts, this study monitored V. cholerae, V. parahaemolyticus, and V. vulnificus at seven recreational bathing areas from 2017 to 2018, including the heat wave event in summer 2018. The study shows that all three Vibrio species occurred in water and sediment samples at all sampling sites. Temperature was shown to be the main driving factor of Vibrio abundance, whereas Vibrio community composition was mainly modulated by salinity. A species-specific rapid increase was observed at water temperatures above 10°C, reaching the highest detection numbers during the heat wave event with abundances of 4.5 log10 CFU+1/100 ml of seawater and 6.5 log10 CFU+1/100 g of sediment. Due to salinity, the dominant Vibrio species found in North Sea samples was V. parahaemolyticus, whereas V. vulnificus was predominantly detected in Baltic Sea samples. Most detections of V. cholerae were associated with estuarine samples from both seas. Vibrio spp. concentrations in sediments were up to three log higher compared to water samples, indicating that sediments are an important habitat for Vibrio spp. to persist in the environment. Antibiotic resistances were found against beta-lactam antibiotics (ampicillin 31%, cefazolin 36%, and oxacillin and penicillin 100%) and trimethoprim-sulfamethoxazole (45%). Moreover, isolates harboring pathogenicity-associated genes such as trh for V. parahaemolyticus as well as vcg, cap/wcv, and the 16S rRNA-type B variant for V. vulnificus were detected. All sampled V. cholerae isolates were identified as non-toxigenic non-O1/non-O139 serotypes. To sum up, increasing water temperatures at German North Sea and Baltic Sea coasts provoke elevated Vibrio numbers and encourage human recreational water activities, resulting in increased exposure rates. Owing to a moderate Baltic Sea salinity, the risk of V. vulnificus infections is of particular concern.

The use of wild plant species or their halophytic relatives has been considered in plant breeding programs to improve salt and drought tolerance in crop plants. Aeluropus littoralis serves as halophyte model for identification and isolation of novel stress adaptation genes. A. littoralis, a perennial monocot grass, grows in damp or arid areas, often salt-impregnated places and wasteland in cultivated areas, can survive periodically high water salinity, and tolerate high salt concentrations in the soil up to 1,100 mM sodium chloride. Therefore, it serves as valuable genetic resource to understand molecular mechanisms of stress-responses in monocots. The knowledge can potentially be used for improving tolerance to abiotic stresses in economically important crops. Several morphological, anatomical, ecological, and physiological traits of A. littoralis have been investigated so far. After watering with salt water the grass is able to excrete salt via its salt glands. Meanwhile, a number of ESTs (expressed sequence tag), genes and promoters induced by the salt and drought stresses were isolated, sequenced and annotated at a molecular level. Transfer of stress related genes to other species resulted in enhanced stress resistance. Here we describe the genome sequence and structure of A. littoralis analyzed by whole genome sequencing and histological analysis. The chromosome number was determined to be 20 (2n = 2x = 20). The genome size was calculated to be 354 Mb. This genomic information provided here, will support the functional investigation and application of novel genes improving salt stress resistance in crop plants. The utility of the sequence information is exemplified by the analysis of the DREB-transcription factor family.

BackgroundAutomated analysis of large image data is highly demanded in high-throughput plant phenotyping. Due to large variability in optical plant appearance and experimental setups, advanced machine and deep learning techniques are required for automated detection and segmentation of plant structures in complex optical scenes.MethodsHere, we present a GUI-based software tool (DeepShoot) for efficient, fully automated segmentation and quantitative analysis of greenhouse-grown shoots which is based on pre-trained U-net deep learning models of arabidopsis, maize, and wheat plant appearance in different rotational side- and top-views.ResultsOur experimental results show that the developed algorithmic framework performs automated segmentation of side- and top-view images of different shoots acquired at different developmental stages using different phenotyping facilities with an average accuracy of more than 90% and outperforms shallow as well as conventional and encoder backbone networks in cross-validation tests with respect to both precision and performance time.ConclusionThe DeepShoot tool presented in this study provides an efficient solution for automated segmentation and phenotypic characterization of greenhouse-grown plant shoots suitable also for end-users without advanced IT skills. Primarily trained on images of three selected plants, this tool can be applied to images of other plant species exhibiting similar optical properties.

Arcobacter (A.) butzleri is an emerging zoonotic pathogen associated with gastrointestinal diseases, such as abdominal cramps and diarrhea, and is widely detected in animals, showing a high prevalence in poultry and seafood. The survival and adaptation of A. butzleri to cold temperatures remains poorly studied, although it might be of interest for food safety considerations. To address this, growth patterns of eight A. butzleri isolates were determined at 8 °C for 28 days. A. butzleri isolates showed strain‐dependent behavior: six isolates were unculturable after day 18, one exhibited declining but detectable cell counts until day 28 and one grew to the stationary phase level. Out of 13 A. butzleri cold shock‐related genes homologous to Escherichia coli, 10 were up‐regulated in response to a temperature downshift to 8 °C, as demonstrated by reverse transcription‐quantitative PCR. Additionally, we compared these data with the cold‐shock response in E. coli. Overall, we provide a deeper insight into the environmental adaptation capacities of A. butzleri, which we find shares similarities with the E. coli cold‐shock response.

Objectives: This study investigated causes of fever in the primary levels of care in Southeast Asia, and evaluated whether C-reactive protein (CRP) could distinguish bacterial from viral pathogens. Methods: Blood and nasopharyngeal swab specimens were taken from children and adults with fever (>37.5 °C) or history of fever (

Abstract Background Automated segmentation of large amount of image data is one of the major bottlenecks in high-throughput plant phenotyping. Dynamic optical appearance of developing plants, inhomogeneous scene illumination, shadows and reflections in plant and background regions complicate automated segmentation of unimodal plant images. To overcome the problem of ambiguous color information in unimodal data, images of different modalities can be combined to a virtual multispectral cube. However, due to motion artefacts caused by the relocation of plants between photochambers the alignment of multimodal images is often compromised by blurring artifacts. Results Here, we present an approach to automated segmentation of greenhouse plant images which is based on co-registration of fluorescence (FLU) and of visible light (VIS) camera images followed by subsequent separation of plant and marginal background regions using different species- and camera view-tailored classification models. Our experimental results including a direct comparison with manually segmented ground truth data show that images of different plant types acquired at different developmental stages from different camera views can be automatically segmented with the average accuracy of $$93\%$$ 93 % ( $$SD=5\%$$ S D = 5 % ) using our two-step registration-classification approach. Conclusion Automated segmentation of arbitrary greenhouse images exhibiting highly variable optical plant and background appearance represents a challenging task to data classification techniques that rely on detection of invariances. To overcome the limitation of unimodal image analysis, a two-step registration-classification approach to combined analysis of fluorescent and visible light images was developed. Our experimental results show that this algorithmic approach enables accurate segmentation of different FLU/VIS plant images suitable for application in fully automated high-throughput manner.

Abstract Background Arcobacter species, particularly A. butzleri, but also A. cryaerophilus constitute emerging pathogens causing gastroenteritis in humans. However, isolation of Arcobacter may often fail during routine diagnostic procedures due to the lack of standard protocols. Furthermore, defined breakpoints for the interpretation of antimicrobial susceptibilities of Arcobacter are missing. Hence, reliable epidemiological data of human Arcobacter infections are scarce and lacking for Germany. We therefore performed a 13-month prospective Arcobacter prevalence study in German patients. Results A total of 4636 human stool samples was included and Arcobacter spp. were identified from 0.85% of specimens in 3884 outpatients and from 0.40% of specimens in 752 hospitalized patients. Overall, A. butzleri was the most prevalent species (n = 24; 67%), followed by A. cryaerophilus (n = 10; 28%) and A. lanthieri (n = 2; 6%). Whereas A. butzleri, A. cryaerophilus and A. lanthieri were identified in outpatients, only A. butzleri could be isolated from samples of hospitalized patients. Antimicrobial susceptibility testing of Arcobacter isolates revealed high susceptibilities to ciprofloxacin, whereas bimodal distributions of MICs were observed for azithromycin and ampicillin. Conclusions In summary, Arcobacter including A. butzleri, A. cryaerophilus and A. lanthieri could be isolated in 0.85% of German outpatients and ciprofloxacin rather than other antibiotics might be appropriate for antibiotic treatment of infections. Further epidemiological studies are needed, however, to provide a sufficient risk assessment of Arcobacter infections in humans.

Men’s Sheds are a community-based health promotion concept which brings men together to engage in joint activities. Prior research reported beneficial effects on health and well-being of the participants; however, evidence is limited. The main objective of this systematic review is to provide an extensive overview of current research on the effectiveness of Men’s Sheds on self-rated health, social isolation, and well-being by applying a mixed-methods approach. In addition, this review aims to identify how to successfully transfer and implement the concept. Eligible for inclusion were all studies published in English, German, or French that specifically referred to the concept of Men’s Sheds. Four databases were searched for eligible studies, followed by a hand search on websites and reference lists. Methodological quality of included studies was assessed using checklists developed by the Joanna Briggs Institute. Following the convergent integrated approach, quantitative data were transformed and merged with qualitative data to conduct a thematic analysis. Overall, 35 qualitative, nine quantitative, and eight mixed-methods studies were included. We found evidence regarding benefits of shed participation on self-rated health, social isolation, and well-being. We identified three key characteristics of a successful Men’s Shed, including appropriate shed facilities, sufficient funding as well as a participant-driven management and organization of the shed. This mixed-methods systematic review provides a comprehensive overview of the evidence base concerning Men’s Sheds and highlights the need for longitudinal studies investigating causal relationships and gathering sufficient information on how to successfully transfer and implement the concept of Men’s Sheds in other countries.

Arcobacter (A.) butzleri, the most widespread species within the genus Arcobacter, is considered as an emerging pathogen causing gastroenteritis in humans. Here, we performed a comparative genome-wide analysis of 40 A. butzleri strains from Lithuania to determine the genetic relationship, pangenome structure, putative virulence, and potential antimicrobial- and heavy-metal-resistance genes. Core genome single nucleotide polymorphism (cgSNP) analysis revealed low within-group variability (≤4 SNPs) between three milk strains (RCM42, RCM65, RCM80) and one human strain (H19). Regardless of the type of input (i.e., cgSNPs, accessory genome, virulome, resistome), these strains showed a recurrent phylogenetic and hierarchical grouping pattern. A. butzleri demonstrated a relatively large and highly variable accessory genome (comprising of 6284 genes with around 50% of them identified as singletons) that only partially correlated to the isolation source. Downstream analysis of the genomes resulted in the detection of 115 putative antimicrobial- and heavy-metal-resistance genes and 136 potential virulence factors that are associated with the induction of infection in host (e.g., cadF, degP, iamA), survival and environmental adaptation (e.g., flagellar genes, CheA-CheY chemotaxis system, urease cluster). This study provides additional knowledge for a better A. butzleri-related risk assessment and highlights the need for further genomic epidemiology studies in Lithuania and other countries.

Reported cases of listeriosis from food of non-animal origin (FNAO) are increasing. In order to assess the risk of exposure to Listeria monocytogenes from FNAO, the genetic characterization of the pathogen in FNAO products and in primary production and processing plants needs to be investigated. For this, 123 samples of fresh and frozen soft fruit and 407 samples of 39 plants in Bavaria, Germany that produce and process FNAO were investigated for Listeria contamination. As a result, 64 Listeria spp. isolates were detected using ISO 11290-1:2017. Environmental swabs and water and food samples were investigated. L. seeligeri (36/64, 56.25%) was the most frequently identified species, followed by L. monocytogenes (8/64, 12.50%), L. innocua (8/64, 12.50%), L. ivanovii (6/64, 9.38%), L. newyorkensis (5/64, 7.81%), and L. grayi (1/64, 1.56%). Those isolates were subsequently sequenced by whole-genome sequencing and subjected to pangenome analysis to retrieve data on the genotype, serotype, antimicrobial resistance (AMR), and virulence markers. Eight out of sixty-four Listeria spp. isolates were identified as L. monocytogenes. The serogroup analysis detected that 62.5% of the L. monocytogenes isolates belonged to serogroup IIa (1/2a and 3a) and 37.5% to serogroup IVb (4b, 4d, and 4e). Furthermore, the MLST (multilocus sequence typing) analysis of the eight detected L. monocytogenes isolates identified seven different sequence types (STs) and clonal complexes (CCs), i.e., ST1/CC1, ST2/CC2, ST6/CC6, ST7/CC7, ST21/CC21, ST504/CC475, and ST1413/CC739. The core genome MLST analysis also showed high allelic differences and suggests plant-specific isolates. Regarding the AMR, we detected phenotypic resistance against benzylpenicillin, fosfomycin, and moxifloxacin in all eight L. monocytogenes isolates. Moreover, virulence factors, such as prfA, hly, plcA, plcB, hpt, actA, inlA, inlB, and mpl, were identified in pathogenic and nonpathogenic Listeria species. The significance of L. monocytogenes in FNAO is growing and should receive increasing levels of attention.