Ex Vivo Modeling of Chemical Synergy in Prenatal Kidney Cystogenesis

Cyclic adenosine monophosphate (cAMP) drives genetic polycystic kidney disease (PKD) cystogenesis. Yet within certain PKD families, striking differences in disease severity exist between affected individuals, and genomic and/or environmental modifying factors have been evoked to explain these observations. We hypothesized that PKD cystogenesis is accentuated by an aberrant fetal milieu, specifically by glucocorticoids. The extent and nature of cystogenesis was assessed in explanted wild-type mouse embryonic metanephroi, using 8-Br-cAMP as a chemical to mimic genetic PKD and the glucocorticoid dexamethasone as the environmental modulator. Cysts and glomeruli were quantified by an observer blinded to culture conditions, and tubules were phenotyped using specific markers. Dexamethasone or 8-Br-cAMP applied on their own produced cysts predominantly arising in proximal tubules and descending limbs of loops of Henle. When applied together, however, dexamethasone over a wide concentration range synergized with 8-Br-cAMP to generate a more severe, glomerulocystic, phenotype; we note that prominent glomerular cysts have been reported in autosomal dominant PKD fetal kidneys. Our data support the idea that an adverse antenatal environment exacerbates renal cystogenesis

On Scene Injury Severity Prediction (OSISP) model for trauma developed using the Swedish Trauma Registry

Background: Providing optimal care for trauma, the leading cause of death for young adults, remains a challenge e.g., due to field triage limitations in assessing a patient’s condition and deciding on transport destination. Data-driven On Scene Injury Severity Prediction (OSISP) models for motor vehicle crashes have shown potential for providing real-time decision support. The objective of this study is therefore to evaluate if an Artificial Intelligence (AI) based clinical decision support system can identify severely injured trauma patients in the prehospital setting. Methods: The Swedish Trauma Registry was used to train and validate five models – Logistic Regression, Random Forest, XGBoost, Support Vector Machine and Artificial Neural Network – in a stratified 10-fold cross validation setting and hold-out analysis. The models performed binary classification of the New Injury Severity Score and were evaluated using accuracy metrics, area under the receiver operating characteristic curve (AUC) and Precision-Recall curve (AUCPR), and under- and overtriage rates. Results: There were 75,602 registrations between 2013–2020 and 47,357 (62.6%) remained after eligibility criteria were applied. Models were based on 21 predictors, including injury location. From the clinical outcome, about 40% of patients\ua0were undertriaged and 46% were overtriaged. Models demonstrated potential for improved triaging and yielded AUC between 0.80–0.89 and AUCPR between 0.43–0.62. Conclusions: AI based OSISP models have potential to provide support during assessment of injury severity. The findings may be used for developing tools to complement field triage protocols, with potential to improve prehospital trauma care and thereby reduce morbidity and mortality for a large patient population

Holistic pedestrian safety assessment for average males and females

ObjectiveAn integrated assessment framework that enables holistic safety evaluations addressing vulnerable road users (VRU) is introduced and applied in the current study. The developed method enables consideration of both active and passive safety measures and distributions of real-world crash scenario parameters.MethodsThe likelihood of a specific virtual testing scenario occurring in real life has been derived from accident databases scaled to European level. Based on pre-crash simulations, it is determined how likely it is that scenarios could be avoided by a specific Autonomous Emergency Braking (AEB) system. For the unavoidable cases, probabilities for specific collision scenarios are determined, and the injury risk for these is determined, subsequently, from in-crash simulations with the VIVA+ Human Body Models combined with the created metamodel for an average male and female model. The integrated assessment framework was applied for the holistic assessment of car-related pedestrian protection using a generic car model to assess the safety benefits of a generic AEB system combined with current passive safety structures.ResultsIn total, 61,914 virtual testing scenarios have been derived from the different car-pedestrian cases based on real-world crash scenario parameters. Considering the occurrence probability of the virtual testing scenarios, by implementing an AEB, a total crash risk reduction of 81.70% was achieved based on pre-crash simulations. It was shown that 50 in-crash simulations per load case are sufficient to create a metamodel for injury prediction. For the in-crash simulations with the generic vehicle, it was also shown that the injury risk can be reduced by implementing an AEB, as compared to the baseline scenarios. Moreover, as seen in the unavoidable cases, the injury risk for the average male and female is the same for brain injuries and femoral shaft fractures. The average male has a higher risk of skull fractures and fractures of more than three ribs compared to the average female. The average female has a higher risk of proximal femoral fractures than the average male.ConclusionsA novel methodology was developed which allows for movement away from the exclusive use of standard-load case assessments, thus helping to bridge the gap between active and passive safety evaluations

Using Drosophila behavioral assays to characterize terebrid venompeptide bioactivity

The number of newly discovered peptides from the transcriptomes and proteomes of animal venom arsenals is rapidly increasing, resulting in an abundance of uncharacterized peptides. There is a pressing need for a systematic, cost effective, and scalable approach to identify physiological effects of venom peptides. To address this discovery-to-function gap, we developed a sequence driven:activity-based hybrid approach for screening venom peptides that is amenable to large-venom peptide libraries with minimal amounts of peptide. Using this approach, we characterized the physiological and behavioral phenotypes of two peptides from the venom of predatory terebrid marine snails, teretoxins Tv1 from Terebra variegata and Tsu1.1 from Terebra subulata. Our results indicate that Tv1 and Tsu1.1 have distinct bioactivity. Tv1 (100 µM) had an antinociceptive effect in adult Drosophila using a thermal nociception assay to measure heat avoidance. Alternatively, Tsu1.1 (100 µM) increased food intake. These findings describe the first functional bioactivity of terebrid venom peptides in relation to pain and diet and indicate that Tv1 and Tsu1.1 may, respectively, act as antinociceptive and orexigenic agents. Tv1 and Tsu1.1 are distinct from previously identified venom peptides, expanding the toolkit of peptides that can potentially be used to investigate the physiological mechanisms of pain and diet

Genomic and strontium isotope variation reveal immigration patterns in a Viking Age town

The impact of human mobility on the northern European urban populations during the Viking and Early Middle Ages and its repercussions in Scandinavia itself are still largely unexplored. Our study of the demographics in the final phase of the Viking era is the first comprehensive multidisciplinary investigation that includes genetics, isotopes, archaeology, and osteology on a larger scale. This early Christian dataset is particularly important as the earlier common pagan burial tradition during the Iron Age was cremation, hindering large-scale DNA analyses. We present genome-wide sequence data from 23 individuals from the 10th to 12th century Swedish town of Sigtuna. The data revealed high genetic diversity among the early urban residents. The observed variation exceeds the genetic diversity in distinct modern-day and Iron Age groups of central and northern Europe. Strontium isotope data suggest mixed local and non-local origin of the townspeople. Our results uncover the social system underlying the urbanization process of the Viking World of which mobility was an intricate part and was comparable between males and females. The inhabitants of Sigtuna were heterogeneous in their genetic affinities, probably reflecting both close and distant connections through an established network, confirming that early urbanization processes in northern Europe were driven by migration

Dhx34 and Nbas function in the NMD pathway and are required for embryonic development in zebrafish

The nonsense-mediated mRNA decay (NMD) pathway is a highly conserved surveillance mechanism that is present in all eukaryotes. It prevents the synthesis of truncated proteins by selectively degrading mRNAs harbouring premature termination codons (PTCs). The core NMD effectors were originally identified in genetic screens in Saccharomyces cerevisae and in the nematode Caenorhabditis elegans, and subsequently by homology searches in other metazoans. A genome-wide RNAi screen in C. elegans resulted in the identification of two novel NMD genes that are essential for proper embryonic development. Their human orthologues, DHX34 and NAG/NBAS, are required for NMD in human cells. Here, we find that the zebrafish genome encodes orthologues of DHX34 and NAG/NBAS. We show that the morpholino-induced depletion of zebrafish Dhx34 and Nbas proteins results in severe developmental defects and reduced embryonic viability. We also found that Dhx34 and Nbas are required for degradation of PTC-containing mRNAs in zebrafish embryos. The phenotypes observed in both Dhx34 and Nbas morphants are similar to defects in Upf1, Smg-5- or Smg-6- depleted embryos, suggesting that these factors affect the same pathway and confirming that zebrafish embryogenesis requires an active NMD pathway