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BackgroundOvarian cancer is the leading cause of mortality among gynecological malignancies. Carboplatin and poly (ADP-ribose) polymerase inhibitors (PARPi) are often implemented in the treatment of ovarian cancer. Homologous recombination deficient (HRD) tumors demonstrate increased sensitivity to these treatments; however, many ovarian cancer patients are homologous recombination proficient (HRP). TTFields are non-invasive electric fields that induce an HRD-like phenotype in various cancer types. The current study aimed to investigate the impact of TTFields applied together with carboplatin or PARPi (olaparib or niraparib) in preclinical ovarian cancer models.MethodsA2780 (HRP), OVCAR3 (HRD), and A2780cis (platinum-resistant) human ovarian cancer cells were treated in vitro with TTFields (1 V/cm RMS, 200 kHz, 72 h), alone or with various drug concentrations. Treated cells were measured for cell count, colony formation, apoptosis, DNA damage, expression of DNA repair proteins, and cell cycle. In vivo, ID8-fLuc (HRP) ovarian cancer cells were inoculated intraperitoneally to C57BL/6 mice, which were then treated with either sham, TTFields (200 kHz), olaparib (50 mg/kg), or TTFields plus olaparib; over a period of four weeks. Tumor growth was analyzed using bioluminescent imaging at treatment cessation; and survival analysis was performed.ResultsThe nature of TTFields-drug interaction was dependent on the drug’s underlying mechanism of action and on the genetic background of the cells, with synergistic interactions between TTFields and carboplatin or PARPi seen in HRP and resistant cells. Treated cells demonstrated elevated levels of DNA damage, accompanied by G2/M arrest, and induction of an HRD-like phenotype. In the tumor-bearing mice, TTFields and olaparib co-treatment resulted in reduced tumor volume and a survival benefit relative to olaparib monotherapy and to control.ConclusionBy inducing an HRD-like phenotype, TTFields sensitize HRP and resistant ovarian cancer cells to treatment with carboplatin or PARPi, potentially mitigating a-priori and de novo drug resistance, a major limitation in ovarian cancer treatment.

Precision Livestock Farming (PLF) involves the real-time monitoring of images, sounds, and other biological, physiological, and environmental parameters to assess and improve animal health and welfare within intensive and extensive production systems [...]

Immune checkpoint inhibitors (ICI) have been revolutionary in the field of cancer therapy. However, their success is limited to specific indications and cancer types. Recently, the combination treatment of ICI and chemotherapy has gained more attention to overcome this limitation. Unfortunately, many clinical trials testing these combinations have provided limited success. This can partly be attributed to an inadequate choice of preclinical models and the lack of scientific rationale to select the most effective immune-oncological combination. In this review, we have analyzed the existing preclinical evidence on this topic, which is only limitedly available. Furthermore, this preclinical data indicates that besides the selection of a specific drug and dose, also the sequence or order of the combination treatment influences the study outcome. Therefore, we conclude that the success of clinical combination trials could be enhanced by improving the preclinical set up, in order to identify the optimal treatment combination and schedule to enhance the anti-tumor immunity.

A novel alpha-therapy consisting of 224Ra-labeled calcium carbonate microparticles (224Ra-CaCO3-MP) has been designed to treat micrometastatic peritoneal disease via intraperitoneal (IP) administration. This preclinical study aimed to evaluate its efficacy and tolerability when given as a single treatment or in combination with standard of care chemotherapy regimens, in a syngeneic model of ovarian cancer in immune competent mice. Female C57BL/6 mice bearing ID8-fLuc ovarian cancer were treated with 224Ra-CaCO3-MP 1 day after IP tumor cell inoculation. The activity dosages of 224Ra ranged from 14 to 39 kBq/mouse. Additionally, 224Ra-CaCO3-MP treatment was followed by either carboplatin (80 mg/kg)-pegylated liposomal doxorubicin (PLD, 1.6 mg/kg) or carboplatin (60 mg/kg)-paclitaxel (10 mg/kg) on day 14 post tumor cell inoculation. All treatments were administered via IP injections. Readouts included survival, clinical signs, and body weight development over time. There was a slight therapeutic benefit after single treatment with 224Ra-CaCO3-MP compared to the vehicle control, with median survival ratios (MSRs) ranging between 1.1 and 1.3. The sequential administration of 224Ra-CaCO3-MP with either carboplatin-paclitaxel or carboplatin-PLD indicated a synergistic effect on overall survival at certain 224Ra activities. Moreover, the combinations tested appeared well tolerated in terms of weight assessment in the first 4 weeks after treatment. Overall, this research supports the further evaluation of 224Ra-CaCO3-MP in patients with ovarian cancer. However, the most optimal chemotherapy regimen to combine with 224Ra-CaCO3-MP should be identified to fully exploit its therapeutic potential.

The lethality of patients with ovarian cancer (OC) remains high. Current treatment strategies often do not lead to the desired outcome due to the development of therapy resistance, resulting in high relapse rates. Additionally, clinical trials testing immunotherapy against OC have failed to reach significant results to date. The OC tumor microenvironment and specifically myeloid-derived suppressor cells (MDSC) are known to generate immunosuppression and inhibit the anti-tumor immune response following immunotherapy treatment. Our review aims to characterize potential candidate treatments to target MDSC in OC through drug-repurposing. A literature search identified repurposable compounds with evidence of their suppressing the effect of MDSC. A total of seventeen compounds were withheld, of which four were considered the most promising. Lurbinectedin, metformin, celecoxib, and 5-azacytidine have reported preclinical effects on MDSC and clinical evidence in OC. They have all been approved for a different indication, characterizing them as the most promising candidates for repurposing to treat patients with OC.

CAIs (canine-assisted interventions) include “canine-assisted therapy” in which a therapist sets client-oriented goals, 'canine-assisted activities' with recreational goals for clients, and 'canine-assisted education/learning' in which teachers or coaches create learning goals for students or clients. CAIs vary in nearly every way; their only common trait is the involvement of dogs to respond to human need. However, the benefits of involving dogs are highly dependent on the animal's health and behavior. A dog exhibiting negative behavior or an unwell dog might pose a risk, especially for CAI target groups, specifically individuals with immunosuppression, chronic illness, children, elderly, etc. Therefore, positive animal welfare as preventative medicine to avoid incidents or transmission of zoonosis is an attractive hypothesis, with implications for human and animal, health and well-being. This review aims to summarize the current published knowledge regarding different aspects of welfare in CAIs and to discuss their relevance in the light of health and safety in CAI participants. As method for this study, a literature search was conducted (2001–2022) using the Prisma method, describing issues of dog welfare as defined in the Welfare Quality® approach. This welfare assessment tool includes 4 categories related to behavior, health, management, and environment; it was, therefore, applicable to CAIs. Results indicate that dogs working in CAIs are required to cope with diverse variables that can jeopardize their welfare. In conclusion, we propose regular welfare assessments for dogs in CAIs, which would also protect the quality of the CAI sessions and the clients' safety and well-being.

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The aim of this paper is to develop a linear kinematic elastoplastic model for simulating the mechanical behavior of a heat-affected zone under low-cycle fatigue for welded S355J2 low-carbon steel. First, an experimental procedure is developed by means of a Gleeble machine for creating macroscopic tensile specimens with different homogeneous metallurgical compositions according to a welding continuous cooling transformation diagram. Then, cyclic tensile tests are carried out by prescribing different strain amplitudes up to 1%. By considering the stabilized behavior at mid-life, the yield stress and hardening modulus are identified as functions of the metallurgical composition by means of a linear mixture rule. Comparisons with numerical simulations are presented to show the efficiency of the multi-phase cyclic linear kinematic elastoplastic model proposed in this work.

Lameness is an important economic problem in the dairy sector, resulting in production loss and reduced welfare of dairy cows. Given the modern-day expansion of dairy herds, a tool to automatically detect lameness in real-time can therefore create added value for the farmer. The challenge in developing camera-based tools is that one system has to work for all the animals on the farm despite each animal having its own individual lameness response. Individualising these systems based on animal-level historical data is a way to achieve accurate monitoring on farm scale. The goal of this study is to optimise a lameness monitoring algorithm based on back posture values derived from a camera for individual cows by tuning the deviation thresholds and the quantity of the historical data being used. Back posture values from a sample of 209 Holstein Friesian cows in a large herd of over 2000 cows were collected during 15 months on a commercial dairy farm in Sweden. A historical data set of back posture values was generated for each cow to calculate an individual healthy reference per cow. For a gold standard reference, manual scoring of lameness based on the Sprecher scale was carried out weekly by a single skilled observer during the final 6 weeks of data collection. Using an individual threshold, deviations from the healthy reference were identified with a specificity of 82.3%, a sensitivity of 79%, an accuracy of 82%, and a precision of 36.1% when the length of the healthy reference window was not limited. When the length of the healthy reference window was varied between 30 and 250 days, it was observed that algorithm performance was maximised with a reference window of 200 days. This paper presents a high-performing lameness detection system and demonstrates the importance of the historical window length for healthy reference calculation in order to ensure the use of meaningful historical data in deviation detection algorithms.

Psychiatric illnesses are estimated to account for over 15% of the burden of disease, which is more than all kinds of cancer together. Since mental disease is often preceded by issues in emotion processing, a method to objectively measure emotions in daily life would be needed. The goal of this research is to investigate the possibilities of mental heart rate component, assessed with a real-time individualized algorithm that decomposes total heart rate in a physical, basal, and mental component, to classify discrete emotions. For this aim, twenty participants committed to wearing a wristband 24/7 for three months and to label the occurrence of fourteen emotions on their smartphones. In total, 1255 labels were added. The dynamics of the mental heart rate component responses to emotions were identified via data-based mechanistic transfer function models. For the classification, the numerator and denominator model orders and parameters, the four features that define transfer function models, were used as features in a support vector machine classifier. This resulted in an average classification accuracy of the mental heart rate responses of 51.1% over all participants, compared to a random classifier with an average accuracy of 28.5%. We concluded that the dynamics of emotions are not only highly variable between individuals, but that they are also time varying on an individual basis. To increase accuracy, more and higher quality labels are indispensable.

Abstract Background Theileria parva causes East Coast fever (ECF), one of the most economically important tick-borne diseases of cattle in sub-Saharan Africa. A live immunisation approach using the infection and treatment method (ITM) provides a strong long-term strain-restricted immunity. However, it typically induces a tick-transmissible carrier state in cattle and may lead to spread of antigenically distinct parasites. Thus, understanding the genetic composition of T. parva is needed prior to the use of the ITM vaccine in new areas. This study examined the sequence diversity and the evolutionary and biogeographical dynamics of T. parva within the African Great Lakes region to better understand the epidemiology of ECF and to assure vaccine safety. Genetic analyses were performed using sequences of two antigen-coding genes, Tp1 and Tp2, generated among 119 T. parva samples collected from cattle in four agro-ecological zones of DRC and Burundi. Results The results provided evidence of nucleotide and amino acid polymorphisms in both antigens, resulting in 11 and 10 distinct nucleotide alleles, that predicted 6 and 9 protein variants in Tp1 and Tp2, respectively. Theileria parva samples showed high variation within populations and a moderate biogeographical sub-structuring due to the widespread major genotypes. The diversity was greater in samples from lowlands and midlands areas compared to those from highlands and other African countries. The evolutionary dynamics modelling revealed a signal of selective evolution which was not preferentially detected within the epitope-coding regions, suggesting that the observed polymorphism could be more related to gene flow rather than recent host immune-based selection. Most alleles isolated in the Great Lakes region were closely related to the components of the trivalent Muguga vaccine. Conclusions Our findings suggest that the extensive sequence diversity of T. parva and its biogeographical distribution mainly depend on host migration and agro-ecological conditions driving tick population dynamics. Such patterns are likely to contribute to the epidemic and unstable endemic situations of ECF in the region. However, the fact that ubiquitous alleles are genetically similar to the components of the Muguga vaccine together with the limited geographical clustering may justify testing the existing trivalent vaccine for cross-immunity in the region.

Extracellular vesicles (EVs) are cell-derived structures surrounded by a lipid bilayer that carry RNA and DNA as potential templates for molecular diagnostics, e.g., in cancer genotyping. While it has been established that DNA templates appear on the outside of EVs, no consensus exists on which nucleic acid species inside small EVs (EGFR) gene mutation T790M as a model system for non-small cell lung cancer. We observed that mainly short genomic DNA (EGFR T790M mutation in the sEVs’ lumen with similar sensitivity using digital PCR. When applying SEC-based sEV separation prior to cell-free DNA extraction on spiked human plasma samples, we found significantly higher mutant allele frequencies as compared to standard cell-free DNA extraction, which in part was due to co-purification of circulating tumor DNA. We conclude that intravesicular genomic DNA can be exploited next to ctDNA to enhance EGFR T790M mutation detection sensitivity by adding a fast and easy-to-use sEV separation method, such as SEC, upstream of standard clinical cell-free DNA workflows.

Economic pressures continue to mount on modern-day livestock farmers, forcing them to increase herds sizes in order to be commercially viable. The natural consequence of this is to drive the farmer and the animal further apart. However, closer attention to the animal not only positively impacts animal welfare and health but can also increase the capacity of the farmer to achieve a more sustainable production. State-of-the-art precision livestock farming (PLF) technology is one such means of bringing the animals closer to the farmer in the facing of expanding systems. Contrary to some current opinions, it can offer an alternative philosophy to ‘farming by numbers’. This review addresses the key technology-oriented approaches to monitor animals and demonstrates how image and sound analyses can be used to build ‘digital representations’ of animals by giving an overview of some of the core concepts of PLF tool development and value discovery during PLF implementation. The key to developing such a representation is by measuring important behaviours and events in the livestock buildings. The application of image and sound can realise more advanced applications and has enormous potential in the industry. In the end, the importance lies in the accuracy of the developed PLF applications in the commercial farming system as this will also make the farmer embrace the technological development and ensure progress within the PLF field in favour of the livestock animals and their well-being.

Extracellular vesicles (EVs) are of interest for a wide variety of biomedical applications. A major limitation for the clinical use of EVs is the lack of standardized methods for the fast and reproducible separation and subsequent detection of EV subpopulations from biofluids, as well as their storage. To advance this application area, fluorescence-based characterization technologies with single-EV resolution, such as high-sensitivity flow cytometry (HS-FCM), are powerful to allow assessment of EV fractionation methods and storage conditions. Furthermore, the use of HS-FCM and fluorescent labeling of EV subsets is expanding due to the potential of high-throughput, multiplex analysis, but requires further method development to enhance the reproducibility of measurements. In this study, we have applied HS-FCM measurements next to standard EV characterization techniques, including nanoparticle tracking analysis, to compare the yield and purity of EV fractions obtained from lipopolysaccharide-stimulated monocytic THP-1 cells by two EV isolation methods, differential centrifugation followed by ultracentrifugation and the exoEasy membrane affinity spin column purification. We observed differences in EV yield and purity. In addition, we have investigated the influence of EV storage at 4°C or -80°C for up to one month on the EV concentration and the stability of EV-associated fluorescent labels. The concentration of the in vitro cell derived EV fractions was shown to remain stable under the tested storage conditions, however, the fluorescence intensity of labeled EV stored at 4°C started to decline within one day.

To better understand and manage climate risks in climate-sensitive sectors such as agriculture, it is essential to have access to consistent and reliable data and information products. Tailoring these products to the needs of the users they want to serve facilitate informed decision-making and downstream applications. This requires an in-depth understanding of users' needs and the context in which these users operate. Considering the diversity of the economic sectors and their actors it is extremely challenging if not outright impossible to promote the emergence of climate services without empowering a plethora of intermediate users who can act as one of the steps in a potential long knowledge brokers chain that connect the climate data providers and the end-users. In this context, Copernicus Climate Change Service (C3S) has been designed around the Climate Data Store (CDS), a unique entry point to a huge variety of quality-controlled climate data and high-level utilities to process that data to develop user-driven applications. Through the Sectoral Information System, C3S has then developed a series of sector specific applications, which show how the infrastructure can be used to address specific users’ needs. This paper presents the key elements of the CDS and selected cases of sectoral application of C3S in agriculture. Keywords: Copernicus Climate Change Services (C3S), Climate Data Store (CDS), User-driven applications, Agriculture sector

Background: In 2001, we studied the presence and coagulant properties of “microparticles” in the blood of healthy humans. Since then, multiple improvements in detection, isolation and functional characterization of the now called “extracellular vesicles” (EVs) have been made, and shortcomings were identified. Aim: To revisit the presence and function of EVs in blood from healthy humans. Methods: Blood was collected from 20 healthy donors. EV-containing plasma was prepared according to new guidelines, and plasma was diluted to prevent swarm detection. Single EVs were measured by flow cytometry with known sensitivity of fluorescence and light scatter. The haemostatic properties of EVs were measured by thrombin-, fibrin-, and plasmin generation. Plasma concentrations of thrombin-antithrombin complexes and prothrombin fragment 1 + 2 were measured to assess the coagulation status in vivo. Results: Compared to 2001, the total concentrations of detected EVs increased from 190- to 264-fold. In contrast to 2001, however, EVs are non-coagulant which we show can be attributed to improvements in blood collection and plasma preparation. No relation is present between the plasma concentrations of EVs and either TAT or F1 + 2. Finally, we show that EVs support plasmin generation. Discussion: Improvements in blood collection, plasma preparation and detection of EVs reveal that results from earlier studies have to be interpreted with care. Compared to 2001, higher concentrations of EVs are detected in blood of healthy humans which promote fibrinolysis rather than coagulation.

Abstract Background The ixodid tick Rhipicephalus appendiculatus is the main vector of Theileria parva, wich causes the highly fatal cattle disease East Coast fever (ECF) in sub-Saharan Africa. Rhipicephalus appendiculatus populations differ in their ecology, diapause behaviour and vector competence. Thus, their expansion in new areas may change the genetic structure and consequently affect the vector-pathogen system and disease outcomes. In this study we investigated the genetic distribution of R. appendiculatus across agro-ecological zones (AEZs) in the African Great Lakes region to better understand the epidemiology of ECF and elucidate R. appendiculatus evolutionary history and biogeographical colonization in Africa. Methods Sequencing was performed on two mitochondrial genes (cox1 and 12S rRNA) of 218 ticks collected from cattle across six AEZs along an altitudinal gradient in the Democratic Republic of Congo, Rwanda, Burundi and Tanzania. Phylogenetic relationships between tick populations were determined and evolutionary population dynamics models were assessed by mismach distribution. Results Population genetic analysis yielded 22 cox1 and 9 12S haplotypes in a total of 209 and 126 nucleotide sequences, respectively. Phylogenetic algorithms grouped these haplotypes for both genes into two major clades (lineages A and B). We observed significant genetic variation segregating the two lineages and low structure among populations with high degree of migration. The observed high gene flow indicates population admixture between AEZs. However, reduced number of migrants was observed between lowlands and highlands. Mismatch analysis detected a signature of rapid demographic and range expansion of lineage A. The star-like pattern of isolated and published haplotypes indicates that the two lineages evolve independently and have been subjected to expansion across Africa. Conclusions Two sympatric R. appendiculatus lineages occur in the Great Lakes region. Lineage A, the most diverse and ubiquitous, has experienced rapid population growth and range expansion in all AEZs probably through cattle movement, whereas lineage B, the less abundant, has probably established a founder population from recent colonization events and its occurrence decreases with altitude. These two lineages are sympatric in central and eastern Africa and allopatric in southern Africa. The observed colonization pattern may strongly affect the transmission system and may explain ECF endemic instability in the tick distribution fringes.

Summary: Scarce access to primary samples and lack of efficient protocols to generate oligodendrocytes (OLs) from human pluripotent stem cells (hPSCs) are hampering our understanding of OL biology and the development of novel therapies. Here, we demonstrate that overexpression of the transcription factor SOX10 is sufficient to generate surface antigen O4-positive (O4+) and myelin basic protein-positive OLs from hPSCs in only 22 days, including from patients with multiple sclerosis or amyotrophic lateral sclerosis. The SOX10-induced O4+ population resembles primary human OLs at the transcriptome level and can myelinate neurons in vivo. Using in vitro OL-neuron co-cultures, myelination of neurons by OLs can also be demonstrated, which can be adapted to a high-throughput screening format to test the response of pro-myelinating drugs. In conclusion, we provide an approach to generate OLs in a very rapid and efficient manner, which can be used for disease modeling, drug discovery efforts, and potentially for therapeutic OL transplantation. : In this article, García-León JA and colleagues demonstrate the generation of functional oligodendrocytes (OLs) from human pluripotent stem cells in a rapid and efficient manner by the single overexpression of SOX10. Generated OLs resemble primary OLs at the transcriptome level and can myelinate neurons both in vivo and in vitro. Neuron-OL co-cultures, adapted to high-throughput screening formats, responded to drugs affecting myelination. Keywords: oligodendrocyte, induced pluripotent stem cells (iPSCs), multiple sclerosis, amyotrophic lateral sclerosis, myelination, disease modeling, drug screening

This study was conducted to evaluate the effect of a 12-h light, 12-h dark (12L : 12D) photoperiod of green light during day 1 to day 18 of incubation time, on embryo growth, hormone concentration and the hatch process. In the test group, monochromatic light was provided by a total of 204 green light-emitting diodes (522 nm) mounted in a frame which was placed above the top tray of eggs to give even spread of illumination. No light–dark cycle was used in the control group. Four batches of eggs (n=300/group per batch) from fertile Ross 308 broiler breeders were used in this experiment. The beak length and crown–rump length of embryos incubated under green light were significantly longer than that of control embryos at day 10 and day 12, respectively (P

Objetivo. Se estima que hasta 18.000 niños, niñas y adolescentes están involucrados en grupos armados en Colombia. Después de desvincularse de estos grupos armados, su reinserción en la sociedad es un gran desafío. Exploramos los discursos acerca de estos jóvenes y sus procesos de reinserción. Metodología. Realizamos 64 entrevistas con profesionales de diferentes organizaciones activas en los procesos de inserción usando el enfoque de “What’s the problem represented to be?”. Resultados. Este enfoque nos permitió encontrar dos discursos explícitos. El primero, el discurso orientado a la ley, demostró ser fuertemente influenciado por las normas internacionales. Y el segundo, el discurso orientado a la alternativa, mostró resistencia al primer discurso. Conclusiones. A través de la interacción de estos discursos, las organizaciones demostraron estar limitadas en sus implementaciones prácticas, lo cual resulta peligroso para los numerosos esfuerzos dedicados a los procesos y para la inserción de los niños en la sociedad.

Dynamical downscaling in a continuous approach using initial and boundary conditions from a reanalysis or a global climate model is a common method for simulating the regional climate. The simulation potential can be improved by applying an alternative approach of reinitialising the atmosphere, combined with either a daily reinitialised or a continuous land surface. We evaluated the dependence of the simulation potential on the running mode of the regional climate model ALARO coupled to the land surface model Météo-France SURFace EXternalisée (SURFEX), and driven by the ERA-Interim reanalysis. Three types of downscaling simulations were carried out for a 10-year period from 1991 to 2000, over a western European domain at 20 km horizontal resolution: (1) a continuous simulation of both the atmosphere and the land surface, (2) a simulation with daily reinitialisations for both the atmosphere and the land surface and (3) a simulation with daily reinitialisations of the atmosphere while the land surface is kept continuous. The results showed that the daily reinitialisation of the atmosphere improved the simulation of the 2 m temperature for all seasons. It revealed a neutral impact on the daily precipitation totals during winter, but the results were improved for the summer when the land surface was kept continuous. The behaviour of the three model configurations varied among different climatic regimes. Their seasonal cycle for the 2 m temperature and daily precipitation totals was very similar for a Mediterranean climate, but more variable for temperate and continental climate regimes. Commonly, the summer climate is characterised by strong interactions between the atmosphere and the land surface. The results for summer demonstrated that the use of a daily reinitialised atmosphere improved the representation of the partitioning of the surface energy fluxes. Therefore, we recommend using the alternative approach of the daily reinitialisation of the atmosphere for the simulation of the regional climate.

Heart rate (HR) is a vital bio-signal that is relatively easy to monitor with contact sensors and is related to a living organism’s state of health, stress and well-being. The objective of this study was to develop an algorithm to extract HR (in beats per minute) of an anesthetized and a resting pig from raw video data as a first step towards continuous monitoring of health and welfare of pigs. Data were obtained from two experiments, wherein the pigs were video recorded whilst wearing an electrocardiography (ECG) monitoring system as gold standard (GS). In order to develop the algorithm, this study used a bandpass filter to remove noise. Then, a short-time Fourier transform (STFT) method was tested by evaluating different window sizes and window functions to accurately identify the HR. The resulting algorithm was first tested on videos of an anesthetized pig that maintained a relatively constant HR. The GS HR measurements for the anesthetized pig had a mean value of 71.76 bpm and standard deviation (SD) of 3.57 bpm. The developed algorithm had 2.33 bpm in mean absolute error (MAE), 3.09 bpm in root mean square error (RMSE) and 67% in HR estimation error below 3.5 bpm (PE3.5). The sensitivity of the algorithm was then tested on the video of a non-anaesthetized resting pig, as an animal in this state has more fluctuations in HR than an anaesthetized pig, while motion artefacts are still minimized due to resting. The GS HR measurements for the resting pig had a mean value of 161.43 bpm and SD of 10.11 bpm. The video-extracted HR showed a performance of 4.69 bpm in MAE, 6.43 bpm in RMSE and 57% in PE3.5. The results showed that HR monitoring using only the green channel of the video signal was better than using three color channels, which reduces computing complexity. By comparing different regions of interest (ROI), the region around the abdomen was found physiologically better than the face and front leg parts. In summary, the developed algorithm based on video data has potential to be used for contactless HR measurement and may be applied on resting pigs for real-time monitoring of their health and welfare status, which is of significant interest for veterinarians and farmers.

Using the regional climate model ALARO-0, the Royal Meteorological Institute of Belgium and Ghent University have performed two simulations of the past observed climate within the framework of the Coordinated Regional Climate Downscaling Experiment (CORDEX). The ERA-Interim reanalysis was used to drive the model for the period 1979–2010 on the EURO-CORDEX domain with two horizontal resolutions, 0.11 and 0.44°. ALARO-0 is characterised by the new microphysics scheme 3MT, which allows for a better representation of convective precipitation. In Kotlarski et al. (2014) several metrics assessing the performance in representing seasonal mean near-surface air temperature and precipitation are defined and the corresponding scores are calculated for an ensemble of models for different regions and seasons for the period 1989–2008. Of special interest within this ensemble is the ARPEGE model by the Centre National de Recherches Météorologiques (CNRM), which shares a large amount of core code with ALARO-0. Results show that ALARO-0 is capable of representing the European climate in an acceptable way as most of the ALARO-0 scores lie within the existing ensemble. However, for near-surface air temperature, some large biases, which are often also found in the ARPEGE results, persist. For precipitation, on the other hand, the ALARO-0 model produces some of the best scores within the ensemble and no clear resemblance to ARPEGE is found, which is attributed to the inclusion of 3MT. Additionally, a jackknife procedure is applied to the ALARO-0 results in order to test whether the scores are robust, meaning independent of the period used to calculate them. Periods of 20 years are sampled from the 32-year simulation and used to construct the 95 % confidence interval for each score. For most scores, these intervals are very small compared to the total ensemble spread, implying that model differences in the scores are significant.

The objective of this study was to evaluate if a multi-sensor system (milk, activity, body posture) was a better classifier for lameness than the single-sensor-based detection models. Between September 2013 and August 2014, 3629 cow observations were collected on a commercial dairy farm in Belgium. Human locomotion scoring was used as reference for the model development and evaluation. Cow behaviour and performance was measured with existing sensors that were already present at the farm. A prototype of three-dimensional-based video recording system was used to quantify automatically the back posture of a cow. For the single predictor comparisons, a receiver operating characteristics curve was made. For the multivariate detection models, logistic regression and generalized linear mixed models (GLMM) were developed. The best lameness classification model was obtained by the multi-sensor analysis (area under the receiver operating characteristics curve (AUC)=0.757±0.029), containing a combination of milk and milking variables, activity and gait and posture variables from videos. Second, the multivariate video-based system (AUC=0.732±0.011) performed better than the multivariate milk sensors (AUC=0.604±0.026) and the multivariate behaviour sensors (AUC=0.633±0.018). The video-based system performed better than the combined behaviour and performance-based detection model (AUC=0.669±0.028), indicating that it is worthwhile to consider a video-based lameness detection system, regardless the presence of other existing sensors in the farm. The results suggest that Θ2, the feature variable for the back curvature around the hip joints, with an AUC of 0.719 is the best single predictor variable for lameness detection based on locomotion scoring. In general, this study showed that the video-based back posture monitoring system is outperforming the behaviour and performance sensing techniques for locomotion scoring-based lameness detection. A GLMM with seven specific variables (walking speed, back posture measurement, daytime activity, milk yield, lactation stage, milk peak flow rate and milk peak conductivity) is the best combination of variables for lameness classification. The accuracy on four-level lameness classification was 60.3%. The accuracy improved to 79.8% for binary lameness classification. The binary GLMM obtained a sensitivity of 68.5% and a specificity of 87.6%, which both exceed the sensitivity (52.1%±4.7%) and specificity (83.2%±2.3%) of the multi-sensor logistic regression model. This shows that the repeated measures analysis in the GLMM, taking into account the individual history of the animal, outperforms the classification when thresholds based on herd level (a statistical population) are used.

Early detection of post-calving health problems is critical for dairy operations. Separating sick cows from the herd is important, especially in robotic-milking dairy farms, where searching for a sick cow can disturb the other cows’ routine. The objectives of this study were to develop and apply a behaviour- and performance-based health-detection model to post-calving cows in a robotic-milking dairy farm, with the aim of detecting sick cows based on available commercial sensors. The study was conducted in an Israeli robotic-milking dairy farm with 250 Israeli-Holstein cows. All cows were equipped with rumination- and neck-activity sensors. Milk yield, visits to the milking robot and BW were recorded in the milking robot. A decision-tree model was developed on a calibration data set (historical data of the 10 months before the study) and was validated on the new data set. The decision model generated a probability of being sick for each cow. The model was applied once a week just before the veterinarian performed the weekly routine post-calving health check. The veterinarian’s diagnosis served as a binary reference for the model (healthy–sick). The overall accuracy of the model was 78%, with a specificity of 87% and a sensitivity of 69%, suggesting its practical value.

Tools for rapid and efficient transgenesis in “safe harbor” loci in an isogenic context remain important to exploit the possibilities of human pluripotent stem cells (hPSCs). We created hPSC master cell lines suitable for FLPe recombinase-mediated cassette exchange (RMCE) in the AAVS1 locus that allow generation of transgenic lines within 15 days with 100% efficiency and without random integrations. Using RMCE, we successfully incorporated several transgenes useful for lineage identification, cell toxicity studies, and gene overexpression to study the hepatocyte lineage. However, we observed unexpected and variable transgene expression inhibition in vitro, due to DNA methylation and other unknown mechanisms, both in undifferentiated hESC and differentiating hepatocytes. Therefore, the AAVS1 locus cannot be considered a universally safe harbor locus for reliable transgene expression in vitro, and using it for transgenesis in hPSC will require careful assessment of the function of individual transgenes.

The chicken embryo is a widely used experimental animal model in many studies, including in the field of developmental biology, of the physiological responses and adaptation to altered environments, and for cancer and neurobiology research. The embryonic heart rate is an important physiological variable used as an index reflecting the embryo’s natural activity and is considered one of the most difficult parameters to measure. An acceptable measurement technique of embryonic heart rate should provide a reliable cardiac signal quality while maintaining adequate gas exchange through the eggshell during the incubation and embryonic developmental period. In this paper, we present a detailed design and methodology for a non-invasive photoplethysmography (PPG)-based prototype (Egg-PPG) for real-time and continuous monitoring of embryonic heart rate during incubation. An automatic embryonic cardiac wave detection algorithm, based on normalised spectral entropy, is described. The developed algorithm successfully estimated the embryonic heart rate with 98.7% accuracy. We believe that the system presented in this paper is a promising solution for non-invasive, real-time monitoring of the embryonic cardiac signal. The proposed system can be used in both experimental studies (e.g., developmental embryology and cardiovascular research) and in industrial incubation applications.

Animal welfare remains a very important issue in the livestock sector, but monitoring animal welfare in an objective and continuous way remains a serious challenge. Monitoring animal welfare, based upon physiological measurements instead of the audio–visual scoring of behaviour, would be a step forward. One of the obvious physiological signals related to welfare and stress is heart rate. The objective of this research was to measure heart rate (beat per minutes) in pigs with technology that soon will be affordable. Affordable heart rate monitoring is done today at large scale on humans using the Photo Plethysmography (PPG) technology. We used PPG sensors on a pig′s body to test whether it allows the retrieval of a reliable heart rate signal. A continuous wavelet transform (CWT)-based algorithm is developed to decouple the cardiac pulse waves from the pig. Three different wavelets, namely second, fourth and sixth order Derivative of Gaussian (DOG), are tested. We show the results of the developed PPG-based algorithm, against electrocardiograms (ECG) as a reference measure for heart rate, and this for an anaesthetised versus a non-anaesthetised animal. We tested three different anatomical body positions (ear, leg and tail) and give results for each body position of the sensor. In summary, it can be concluded that the agreement between the PPG-based heart rate technique and the reference sensor is between 91% and 95%. In this paper, we showed the potential of using the PPG-based technology to assess the pig′s heart rate.

For all homoeothermic living organisms, heart rate (HR) is a core variable to control the metabolic energy production in the body, which is crucial to realize essential bodily functions. Consequently, HR monitoring is becoming increasingly important in research of farm animals, not only for production efficiency, but also for animal welfare. Real-time HR monitoring for humans has become feasible though there are still shortcomings for continuously accurate measuring. This paper is an effort to estimate whether it is realistic to get a continuous HR sensor for livestock that can be used for long term monitoring. The review provides the reported techniques to monitor HR of living organisms by emphasizing their principles, advantages, and drawbacks. Various properties and capabilities of these techniques are compared to check the potential to transfer the mostly adequate sensor technology of humans to livestock in term of application. Based upon this review, we conclude that the photoplethysmographic (PPG) technique seems feasible for implementation in livestock. Therefore, we present the contributions to overcome challenges to evolve to better solutions. Our study indicates that it is realistic today to develop a PPG sensor able to be integrated into an ear tag for mid-sized and larger farm animals for continuously and accurately monitoring their HRs.

Newly hatched chicks may be held longer than 48 h and experience long periods of fasting in commercial hatcheries. Limited information is known about the physiological status of chicks in such situations, due to the difficulty of precisely recording time of hatch. This study investigated the effect of the time from hatch to pulling (holding period) on physiological measures/parameters in 109 broiler chicks. Fertile Ross 308 eggs were incubated in a custom built small-scale incubator. The individual hatching time of each focal chick was determined using eggshell temperature monitoring. At ‘pulling’ (512 h of incubation time), the quality of focal chicks was assessed using the chick scoring method and physiological parameters were measured including BW, organ (heart, liver and stomach) weights, blood values and plasma corticosterone level. The time from hatch to pulling varied from 7.58 to 44.97 h. Egg weight at setting was significantly correlated with chick BW and weight of organs at pulling, but had no effect on chick quality, blood values and plasma corticosterone. Relative BW at pulling was negatively associated with the duration of holding period (P=0.002). However, there was a positive correlation between relative stomach weight and the duration of the holding period (P

In this research, twenty-four high capacity (1360 mAh) NMC622/Si-alloy Li-ion full pouch cells with high silicon-alloy content (55%) are cycle aged under seven different cycling conditions to study the effect of different stressors on the cycle life of Si-anode full cells, among which are the effect of ambient temperature, Depth of Discharge (DoD) and the discharge current. The cells are volumetrically constrained at an optimal initial pressure to improve their cycle life, energy and power capabilities. Furthermore, the innovative test setup allows measuring the developed pressure as a result of repeated (de-)lithiation during battery cycling. This uniquely vast testing campaign on Si-anode full cells allows us to study and quantify independently the influence of different stress factors on their cycle life for the first time, as well as to develop a new capacity fade model based on an observed linear relationship between capacity retention and total discharge capacity throughput.

This study analyzed a prototype of a pouch cell containing silicon alloy anodes with the potential to significantly increase the energy density, resulting in improved autonomy for electric vehicles. An electrical characterization campaign was performed, resulting in three main observations. Firstly, measurements showed a high energy density, although a high lower cutoff voltage (3.0 V) was used due to the prototypical nature of the cells. Further optimization would allow a decrease of the lower cutoff voltage, resulting in an even higher energy density. Secondly, a large open-circuit voltage hysteresis was observed, increasing the complexity for equivalent circuit models. Thirdly, ballooning of the pouch cell was observed, most likely caused by gas formation. This leads to a loss of active surface area, significantly reducing the cell’s capacity. This third observation was more thoroughly investigated by 3D computed tomography, which showed mechanical deformation of the layers. An extensive literature review revealed that the addition of fluoroethylene carbonate (FEC) to the electrolyte enhances the cycling stability of silicon alloy batteries but leads to the production of CO 2 as a side reaction. Furthermore, the usage of external pressure was proposed and validated as a methodology to reduce the production of CO 2 while improving the cells’ performance.

Resumen: La Directiva 49/2002/CE de la UE obliga a los fabricantes de vehículos a certificar las emisiones de ruido al exterior, estableciendo importantes restricciones al respecto. Por lo tanto, resulta imperativo establecer modelos que identifiquen las fuentes de ruido en un vehículo, así como la exactitud de los mismos. En este artículo se presenta un modelo de identificación de fuentes sonoras para el estudio y caracterización del ruido del motor en vehículos. El ruido es experimentalmente caracterizado mediante la técnica de substitución de monopolos adaptado al método general de síntesis de sonido. La técnica de identificación resultante se ilustra mediante varios casos en estudio variando el número de monopolos y la posición del receptor, determinando la precisión del sistema en cada caso.Los resultados indican que el error cometido en el caso más desfavorable es inferior a 15 dB. Palabras Clave: Síntesis de sonido, Identificación, âLoudnessâ, Calidad del Sonido, ASQ

Cough is the element for monitoring and diagnosis of respiratory disease cause of mortality and loss of productivity in pig houses. In order to prevent as much as possible the outbreak of such diseases the aim of this research is to describe acoustic features of cough sounds originating from infections due to Actinobacillosis and Pasteurellosis and to compare them with healthy cough sounds provoked by inhalation of citric acid. The acoustic parameters investigated are peak frequency [Hz] and duration of cough signals. The differences resulting from the cough sound analysis confirmed a variability in acoustics parameters according to a state of health or disease in the animals. Sound analysis provides physic acoustic features that can be used as tool to label and detect cough in a automatic monitoring system applied in farms.

Small wireless trunk accelerometers have become a popular approach to unobtrusively quantify human locomotion and provide insights into both gait rehabilitation and sports performance. However, limited evidence exists as to which trunk accelerometry measures are suitable for the purpose of detecting movement compensations while running, and specifically in response to fatigue. The aim of this study was therefore to detect deviations in the dynamic center of mass (CoM) motion due to running-induced fatigue using tri-axial trunk accelerometry. Twenty runners aged 18-25 years completed an indoor treadmill running protocol to volitional exhaustion at speeds equivalent to their 3.2 km time trial performance. The following dependent measures were extracted from tri-axial trunk accelerations of 20 running steps before and after the treadmill fatigue protocol: the tri-axial ratio of acceleration root mean square (RMS) to the resultant vector RMS, step and stride regularity (autocorrelation procedure), and sample entropy. Running-induced fatigue increased mediolateral and anteroposterior ratios of acceleration RMS (p < .05), decreased the anteroposterior step regularity (p < .05), and increased the anteroposterior sample entropy (p < .05) of trunk accelerometry patterns. Our findings indicate that treadmill running-induced fatigue might reveal itself in a greater contribution of variability in horizontal plane trunk accelerations, with anteroposterior trunk accelerations that are less regular from step-to-step and are less predictable. It appears that trunk accelerometry parameters can be used to detect deviations in dynamic CoM motion induced by treadmill running fatigue, yet it is unknown how robust or generalizable these parameters are to outdoor running environments.

Pig vocalisations convey information about their current state of health and welfare. Continuously monitoring these vocalisations can provide useful information for the farmer. For instance, pig screams can indicate stressful situations. When monitoring screams, other sounds can interfere with scream detection. Therefore, identifying screams from other sounds is essential. The objective of this study was to understand which sound features define a scream. Therefore, a method to detect screams based on sound features with physical meaning and explicit rules was developed. To achieve this, 7 hours of labelled data from 24 pigs was used. The developed detection method attained 72% sensitivity, 91% specificity and 83% precision. As a result, the detection method showed that screams contain the following features discerning them from other sounds: a formant structure, adequate power, high frequency content, sufficient variability and duration.

The negative impact of the automotive industry on climate change can be tackled by changing from fossil driven vehicles towards battery electric vehicles with no tailpipe emissions. However their adoption mainly depends on the willingness to pay for the extra cost of the traction battery. The goal of this paper is to predict the cost of a battery pack in 2030 when considering two aspects: firstly a decade of research will ensure an improvement in material sciences altering a battery’s chemical composition. Secondly by considering the price erosion due to the production cost optimization, by maturing of the market and by evolving towards to a mass-manufacturing situation. The cost of a lithium Nickel Manganese Cobalt Oxide (NMC) battery (Cathode: NMC 6:2:2 ; Anode: graphite) as well as silicon based lithium-ion battery (Cathode: NMC 6:2:2 ; Anode: silicon alloy), expected to be on the market in 10 years, will be predicted to tackle the first aspect. The second aspect will be considered by combining process-based cost calculations with learning curves, which takes the increasing battery market into account. The 100 dollar/kWh sales barrier will be reached respectively between 2020-2025 for silicon based lithium-ion batteries and 2025–2030 for NMC batteries, which will give a boost to global electric vehicle adoption.