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Ecosystem reliance on groundwater, defined here as water stored in the saturated zone deeper than one meter beneath the surface, has been documented in many semi-arid, arid, and seasonally-dry regions around the world. In California, groundwater sustains ecosystems and mitigates mortality during drought. However, the effect of groundwater on carbon cycling still remains largely unresolved. Here we use 20 years of eddy covariance, groundwater, and tree growth measurements to isolate the impact of groundwater on carbon cycling in a semi-arid Mediterranean system in California during the summer dry season. We show that daily ecosystem groundwater use increases under positive groundwater anomalies and is associated with increased carbon assimilation and evapotranspiration rates. Negative groundwater anomalies result in significantly reduced ecosystem groundwater uptake, gross primary productivity, and evapotranspiration, with a simultaneous increase in water use efficiency. Three machine learning algorithms better predict gross primary productivity and tree growth anomalies when trained using groundwater data. These models suggest that groundwater has a unique effect on carbon assimilation and allocation to woody growth. After controlling for the effect of soil moisture, which is often decoupled from groundwater dynamics at the site, wet groundwater anomalies increase canopy carbon assimilation by 179.4 ± 25.7 g C m−2 (17 % of annual gross primary productivity) over the course of the summer season relative to dry groundwater anomalies. Similarly, annual tree growth increases by 0.175 ± 0.035 mm (17.7 % of annual growth) between dry and wet groundwater anomalies, independent of soil moisture dynamics. Our results demonstrate the importance of deep subsurface water resources to carbon assimilation and woody growth in dryland systems, as well as the benefits of collocated, long-term eddy covariance and ancillary datasets to improve understanding of complex ecosystem dynamics.

Case summary A 2-year-old spayed female domestic shorthair cat presented with tetraparesis after being involved in a road traffic accident. Survey spine radiographs revealed a C2–C3 cervical subluxation, which was confirmed by a CT scan. Surgical stabilisation was performed using screws and polymethyl methacrylate (PMMA) via a ventral approach. A postoperative CT scan demonstrated correct implant positioning and good reduction of the subluxation. After surgery, the cat rapidly recovered to a neurologically normal status. Relevance and novel information Trauma-induced cervical subluxation is an uncommon occurrence in cats but should be considered in the differential diagnosis. This report describes the surgical management of a C2–C3 cervical subluxation in a cat using screws and PMMA. This is the first case report of a surgically treated subaxial cervical subluxation in a cat.

Abstract Selective binding of TCR-like antibodies that target a single tumour-specific peptide antigen presented by human leukocyte antigens (HLA) is the absolute prerequisite for their therapeutic suitability and patient safety. To date, selectivity assessment has been limited to peptide library screening and predictive modeling. We developed an experimental platform to de novo identify interactomes of TCR-like antibodies directly in human tissues using mass spectrometry. As proof of concept, we confirm the target epitope of a MAGE-A4-specific TCR-like antibody. We further determine cross-reactive peptide sequences for ESK1, a TCR-like antibody with known off-target activity, in human liver tissue. We confirm off-target-induced T cell activation and ESK1-mediated liver spheroid killing. Off-target sequences feature an amino acid motif that allows a structural groove-coordination mimicking that of the target peptide, therefore allowing the interaction with the engager molecule. We conclude that our strategy offers an accurate, scalable route for evaluating the non-clinical safety profile of TCR-like antibody therapeutics prior to first-in-human clinical application.

Abstract Background Electronic health records (EHRs) contain valuable information for clinical research; however, the sensitive nature of healthcare data presents security and confidentiality challenges. De-identification is therefore essential to protect personal data in EHRs and comply with government regulations. Named entity recognition (NER) methods have been proposed to remove personal identifiers, with deep learning-based models achieving better performance. However, manual annotation of training data is time-consuming and expensive. The aim of this study was to develop an automatic de-identification pipeline for all kinds of clinical documents based on a distant supervised method to significantly reduce the cost of manual annotations and to facilitate the transfer of the de-identification pipeline to other clinical centers. Methods We proposed an automated annotation process for French clinical de-identification, exploiting data from the eHOP clinical data warehouse (CDW) of the CHU de Rennes and national knowledge bases, as well as other features. In addition, this paper proposes an assisted data annotation solution using the Prodigy annotation tool. This approach aims to reduce the cost required to create a reference corpus for the evaluation of state-of-the-art NER models. Finally, we evaluated and compared the effectiveness of different NER methods. Results A French de-identification dataset was developed in this work, based on EHRs provided by the eHOP CDW at Rennes University Hospital, France. The dataset was rich in terms of personal information, and the distribution of entities was quite similar in the training and test datasets. We evaluated a Bi-LSTM + CRF sequence labeling architecture, combined with Flair + FastText word embeddings, on a test set of manually annotated clinical reports. The model outperformed the other tested models with a significant F1 score of 96,96%, demonstrating the effectiveness of our automatic approach for deidentifying sensitive information. Conclusions This study provides an automatic de-identification pipeline for clinical notes, which can facilitate the reuse of EHRs for secondary purposes such as clinical research. Our study highlights the importance of using advanced NLP techniques for effective de-identification, as well as the need for innovative solutions such as distant supervision to overcome the challenge of limited annotated data in the medical domain.

Urbanization profoundly alters environmental conditions for organisms, particularly through the urban heat island (UHI) effect, which elevates temperatures in city centers. This study examines the influence of urban environmental variables on rove and ground beetle communities. We sampled 36 grasslands in Rennes (northwestern France), yielding 3317 and 505 staphylinid and carabid adult individuals, respectively, belonging to 121 and 60 species, respectively. Staphylinid and carabid communities are not primarily affected by temperature-related variables. Staphylinids, often overlooked in urban ecology, showed species composition variation to be influenced by habitat and temperature, whereas their functional diversity was positively correlated with herbaceous vegetation height only. In contrast, carabid communities exhibited no significant relationship with the tested environmental variables. This study underscores the taxon-dependent nature of ectotherm’s responses to thermal environments. Although a further investigation into species-specific traits, and particularly dispersal capacities in staphylinids, is needed to advance our understanding of urbanization’s impact, our results indicate that functional diversity in staphylinid assemblages can be favored by locally reducing the mowing frequency or increasing the cutting height within urban green spaces.

Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity, which requires moving away from broadly defined functional types. Different approaches have been adopted in the last years to incorporate a trait-based perspective into modeling exercises. A common parametrization strategy involves using trait data to represent functional variation between individuals while discarding taxonomic identity. However, this strategy ignores the phylogenetic signal of trait variation and cannot be employed when predictions for specific taxa are needed, such as in applications to inform forest management planning. An alternative strategy involves adapting the taxonomic resolution of model entities to that of the data source employed for large-scale initialization and estimating functional parameters from available plant trait databases, adopting diverse solutions for missing data and non-observable parameters. Here we report the advantages and limitations of this second strategy according to our experience in the development of MEDFATE (version 2.9.3), a novel cohort-based and trait-enabled model of forest dynamics, for its application over a region in the western Mediterranean Basin. First, 217 taxonomic entities were defined according to woody species codes of the Spanish National Forest Inventory. While forest inventory records were used to obtain some empirical parameter estimates, a large proportion of physiological, morphological, and anatomical parameters were matched to measured plant traits, with estimates extracted from multiple databases and averaged at the required taxonomic level. Estimates for non-observable key parameters were obtained using meta-modeling and calibration exercises. Missing values were addressed using imputation procedures based on trait covariation, taxonomic averages or both. The model properly simulated observed historical changes in basal area, with a performance similar to an empirical model trained for the same region. While strong efforts are still required to parameterize trait-enabled models for multiple taxa, and to incorporate intra-specific trait variability, estimation procedures such as those presented here can be progressively refined, transferred to other regions or models and iterated following data source changes by employing automated workflows. We advocate for the adoption of trait-enabled and population-structured models for regional-level projections of forest function and dynamics.

All projects require a structure to meet project requirements and achieve established goals. This framework is called project management. Therefore, project management plays an important role in national development and economic growth. Project management includes various knowledge areas such as project integration management, project scope management, project schedule management, etc. The article focuses on the resource-constrained project scheduling known as problem so- called the resource-constrained project scheduling problem (RCPSP). The RCPSP is a part of schedule management. The standard RCPSP has two important constraints, resource constraints and precedence relationships of activities during project scheduling. The objective of the problem is to optimize and minimize the project duration, subject to the above constraints. In this paper, we develop a convolutional neural network approach to solve the standard single mode RCPSP. The advantage of this algorithm over conventional methods such as metaheuristics is that it does not need to generate many solutions or populations. In this paper, the serial schedule generation scheme (SSGS) is used to schedule the project activities using an evolved convolutional neural network (CNN) as a tool to select an appropriate priority rule to filter out a candidate activity. The evolved CNN learns according to the eight project parameters, namely network complexity, resource factor, resource strength, average work per activity, etc. The above parameters are the inputs of the network and are recalculated at each step of the project planning. Moreover, the developed network has priority rules which are the outputs of the developed neural network. Therefore, after the learning process, the network can automatically select an appropriate priority rule to filter an activity from the eligible activities. In this way, the algorithm is able to schedule all project activities according to the given project constraints. Finally, the performance of the Convolutional Neural Network (CNN) approach is investigated using standard benchmark problems from PSPLIB in comparison to the MLFNN approach and standard metaheuristics.

Abstract Wild boar is increasingly establishing populations in the outskirts of European cities, with the largest German urban population occurring in Berlin. Related soil disturbance in grasslands is common and often considered as damage to biodiversity. However, it is unknown how animal and plant species in urban grasslands respond to wild boar activity - an important limitation for conservation management. We sampled plants, grasshoppers and sand lizards in 22 dry grasslands and measured wild boar activity. We show that plant diversity decreased with rooting intensity, but not species richness, endangered or specialist species. Relationships with animals were mostly positive. Grasshopper diversity, total richness and richness of endangered and specialist species were positively related to rooting, as was sand lizard abundance. These relationships contrast to mostly negative effects in the wild boar’s non-native range. This first multi-taxa study in a large city suggests that soil disturbance by wild boars is not necessarily a threat to biodiversity. An implication for conservation is to consider the context-dependence of biodiversity responses to wild boar activity. For dry grasslands, disturbed patches should be accepted in management plans rather than re-vegetated by seeding.

Abstract Mitochondrial metabolism varies significantly between individuals of the same species and can influence animal performance, such as growth. However, growth rate is usually determined before the mitochondrial assay. The hypothesis that natural variation in mitochondrial metabolic traits is linked to differences in both previous and upcoming growth remains untested. Using biopsies to collect tissue in a non-lethal manner, we tested this hypothesis in a fish model (Dicentrarchus labrax) by monitoring individual growth rate, measuring mitochondrial metabolic traits in the red muscle, and monitoring the growth of the same individuals after the mitochondrial assay. Individual variation in growth rate was consistent before and after the mitochondrial assay; however, the mitochondrial traits that explained growth variation differed between the growth rates determined before and after the mitochondrial assay. While past growth was correlated with the activity of the cytochrome c oxidase, a measure of mitochondrial density, future growth was linked to mitochondrial proton leak respiration. This is the first report of temporal shift in the relationship between growth rate and mitochondrial metabolic traits, suggesting an among-individual variation in temporal changes in mitochondrial traits. Our results emphasize the need to evaluate whether mitochondrial metabolic traits of individuals can change over time.

Along with worldwide urbanization, upheavals in habitat and temperature are major threats for biodiversity. However, due to their interdependence, their relative roles as drivers of animal community composition remain entangled. Here, we investigated how taxonomic and functional compositions of arthropod communities were related to uncorrelated habitat and temperature gradients, and compared landscape (i.e., urbanization, Urban Heat Island (UHI)) to local variables (i.e., vegetation height and cover, near-ground temperature). We sampled 20,499 spiders (137 species) on 36 grasslands in Rennes (northwestern France). Unlike rural areas, urban sites were characterized by short vegetation and intense UHI, hosted species-poor communities, and were composed of small thermophilic species. UHI intensification and local loss of habitat complexity (short and dense vegetation) were associated with declining large and heat-sensitive species. These results highlight the prevalent role of urban warming, rather than land cover change, as an urban filter. Further, we show that landscape-scale UHI, not local temperature, filters species according to their functional attributes. UHI can therefore be considered as a thermal barrier, filtering species according to their physiological capacity to cope with urban thermal conditions. Finally, to counterbalance biotic homogenization, we argue for the importance of implementing complex habitat structures at the local scale within urban green infrastructure.

The European sea bass Dicentrarchus labrax is the main species reared in Mediterranean aquaculture. Its larval stage, which is very sensitive and highly affected by sanitary and environmental conditions, is particularly scrutinized in hatcheries. Recently, a Mediterranean sea bass farm had to deal with an abnormal increase in mortality, especially between 20 and 35 days post-hatching (dph). Biological investigations led to the observation of cytopathic effects on three different fish cell lines after almost 3 weeks of culture at 14 °C in contact with homogenized affected larvae, suggesting the presence of a viral agent. High-throughput sequencing revealed a 6818-nucleotide-long RNA genome with six putative ORFs, corresponding to the organization of viruses belonging to the Totiviridae family. This genome clustered with the newly described and suggested Pistolvirus genus, sharing 45.5% to 37.2% nucleotide identity with other piscine toti-like viruses such as Cyclopterus lumpus toti-like virus (CLuTLV) or piscine myocarditis virus (PMCV), respectively. Therefore, we propose to name this new viral agent sea bass toti-like virus (SBTLV). Specific real-time RT-PCR confirmed the presence of the viral genome in the affected larval homogenate from different production batches and the corresponding cell culture supernatant. Experimental infections performed on sea bass fingerlings did not induce mortality, although the virus could be detected in various organs and a specific immune response was developed. Additional studies are needed to understand the exact involvement of this virus in the mortality observed in hatcheries and the potential associated cofactors.

Abstract Background Progressive CO2-induced ocean acidification (OA) impacts marine life in ways that are difficult to predict but are likely to become exacerbated over generations. Although marine fishes can balance acid–base homeostasis efficiently, indirect ionic regulation that alter neurosensory systems can result in behavioural abnormalities. In marine invertebrates, OA can also affect immune system function, but whether this is the case in marine fishes is not fully understood. Farmed fish are highly susceptible to disease outbreak, yet strategies for overcoming such threats in the wake of OA are wanting. Here, we exposed two generations of the European sea bass (Dicentrarchus labrax) to end-of-century predicted pH levels (IPCC RCP8.5), with parents (F1) being exposed for four years and their offspring (F2) for 18 months. Our design included a transcriptomic analysis of the olfactory rosette (collected from the F2) and a viral challenge (exposing F2 to betanodavirus) where we assessed survival rates. Results We discovered transcriptomic trade-offs in both sensory and immune systems after long-term transgenerational exposure to OA. Specifically, RNA-Seq analysis of the olfactory rosette, the peripheral olfactory organ, from 18-months-old F2 revealed extensive regulation in genes involved in ion transport and neuronal signalling, including GABAergic signalling. We also detected OA-induced up-regulation of genes associated with odour transduction, synaptic plasticity, neuron excitability and wiring and down-regulation of genes involved in energy metabolism. Furthermore, OA-exposure induced up-regulation of genes involved in innate antiviral immunity (pathogen recognition receptors and interferon-stimulated genes) in combination with down-regulation of the protein biosynthetic machinery. Consistently, OA-exposed F2 challenged with betanodavirus, which causes damage to the nervous system of marine fish, had acquired improved resistance. Conclusion F2 exposed to long-term transgenerational OA acclimation showed superior viral resistance, though as their metabolic and odour transduction programs were altered, odour-mediated behaviours might be consequently impacted. Although it is difficult to unveil how long-term OA impacts propagated between generations, our results reveal that, across generations, trade-offs in plastic responses is a core feature of the olfactory epithelium transcriptome in OA-exposed F2 offspring, and will have important consequences for how cultured and wild fish interacts with its environment.

Instroduction: Diabetes, including its numerous complications, is one of fundamental challenges of modern medicine. Over the years, many types of this disease have been appointed, differing in both etiological background and method of treatment. Dentists, when providing dental care to a patient burdened with diabetes, should pay special attention to the first symptoms reported by the patient as well as manifested in the oral cavity and surrounding tissues, e.g. in the form of xerostomia, hypertrophy of the salivary glands, changes on mucous membranes, impeded healing, or difficulties in combating local inflammation and infections, as well as in the form of physiological microflora disorders. Aim of the study: The aim of the study is to emphasize the need for controlling diabetes for the sake of general and oral health. Materials and methods: Our work is mainly based on the articles published in PubMed, websites or medical books. We were looking for keywords such as ‘diabetes’, ‘dental treatment’, ‘symptoms of diabetes’ or ‘oral cavity diseases’. Results: Diabetes is often manifested by changes in the oral cavity, as evidenced by numerous scientific studies presented in the bibliography. Controlling the disease helps to eliminate lowering quality-of-life general symptoms and oral lesions. Conclusions: Faced with the challenges of modern medicine, the dentist is obliged to inform the patient about the diagnostic and therapeutic possibilities of both diabetes itself and its symptoms occurring in the oral cavity and then take all steps to ensure that the patient's condition is stabilised.