Animals

The study of animal personality has gained increasing attention in recent years, as researchers recognize that non-human animals exhibit stable individual differences in behaviour. In dairy cattle, understanding personality traits holds potential for improving animal welfare, enhancing management practices, and supporting productivity outcomes. However, validating the behavioural tests used to assess these traits remains a significant challenge. The present study aimed to evaluate the consistency and validity of five commonly used behavioural tests in dairy cows: the Human Approach Test (HAT), Sudden Test (SUD), Novel Object Test (NOT), Open Field Test (OFT), and Novel Surface Test (NST). These tests were chosen for their potential to assess personality dimensions that parallel components of human personality, particularly Openness, Neuroticism, Extraversion, and Agreeableness. Repeated assessments were conducted across three time periods to evaluate both intra-test (temporal) and inter-test (contextual) consistency. Results revealed that only the SUD exhibited significant behavioural consistency across all periods, suggesting its potential as a reliable tool for personality assessment. Additionally, a moderate correlation between the HAT and SUD was observed, indicating that these tests may capture overlapping personality traits. In contrast, the remaining tests (NOT, OFT, NST) lacked consistent behavioural patterns over time and across contexts, raising questions about their reliability and the complexity of trait expression. These findings highlight the challenges of identifying stable personality traits in cattle and emphasize the need for more rigorous validation of behavioural tests. This research contributes to the growing field of animal personality by providing insights into trait stability, the limitations of current testing methods, and the potential application of personality assessment in future livestock management practices.

Background: The yak (Bos grunniens) is an essential livestock species in high-altitude alpine ecosystems, serving key roles in meat, milk, and wool production as well as ecological maintenance. However, traditional yak breeding systems face several limitations, including fragmented herd data management, inefficient phenotypic collection, missing pedigree records, and high technical barriers to applying genomic technologies. These factors constrain the widespread application of modern genetic evaluation methods in yak breeding programs. Description: We developed the Yak Genomic Evaluation Platform (YGEP, https://yakbreeding.swun.edu.cn/en/), an integrated digital system for yak genetic selection and herd management. YGEP integrates three core analytical modules: pedigree reconstruction, genotype imputation and genomic breeding value estimation. Benchmarking on 706 yaks showed that GBLUP achieved a prediction accuracy of r = 0.96 for cannon bone circumference (CCB), and KBeagle reached 84.0% imputation accuracy with the combined reference panel. Conclusion: YGEP bridges the gap between advanced genomic analytics and practical yak breeding. By integrating pedigree reconstruction, genotype imputation, and GEBV estimation into a user-friendly cloud platform, YGEP effectively eliminates technical and data bottlenecks. Overall, it provides an accessible, scalable, and standardized solution to advance digital herd management and precision genetic improvement in alpine livestock.

The Siamese fighting fish (Betta splendens) is well-known for its high levels of aggression and complex, stereotyped displays, making it an ideal model for testing deep learning-based tools for high-throughput, unbiased quantification of aggressive behaviour. A deep-learning object recognition model (BettaAI) was developed to detect the species' aggressive displays, including threat (opercula opening and fin distension), attack (bites) behaviours, as well as surface air breathing, a behaviour correlated with the frequency and intensity of aggression. Videos of males confronting their mirror image were acquired simultaneously with synchronised top and side cameras. Two separate models were trained, with some behaviours identified from top-view frames and others from side-view frames; outputs from both models were combined and post-processed for final quantification. BettaAI performed with high accuracy: F1 scores were 0.99 for the top-view model and 0.93 for the side-view model. Average Precision (AP) at 0.5 IoU exceeded 0.98 for all categories except bites, a rare behaviour in the dataset, which reached 0.865. Comparisons with a manually curated "ground-truth" dataset from videos of 10 males showed strong concordance between automated quantification and manual annotations by expert observers across all behaviours. A case study on 461 males reacting either to a mirror or to a video playback of a conspecific demonstrated the high-throughput and unbiased advantages of BettaAI, with threat displays being more frequent toward the mirror image and attack rates not differing between treatments. This work underscores the potential of BettaAI for automated, bias-free quantification of aggressive displays in B. splendens.

Zoos and public aquariums serve as essential hubs for wildlife conservation, public education, and scientific research; however, the success of these missions depends upon maintaining high animal welfare standards despite constant human presence. A primary concern is the 'visitor effect': the alteration of animal behavior due to human presence. While this phenomenon is well-documented in captive mammals and has been explored in chondrichthyes, it remains largely unexamined in teleost fish, despite evidence of their sensitivity to human stimuli in natural environments. This study addresses this knowledge gap by investigating the behavioral responses of 13 teleost species to varying levels of crowd density, direct human solicitation, and ambient noise. Our multivariate analysis reveals that visitor density and visitor-induced disturbances are significant drivers of behavioral change, with species identity acting as the primary source of variance. We observed high inter-taxonomic variability: while several species (including Euxiphipops sextriatus, Dascyllus aruanus, and Zebrasoma flavescens) showed marked sensitivity through significant alterations in stress-coping, exploration, and aggression, others remained behaviorally stable. Furthermore, acoustic analysis indicates a complex soundscape where visitor density correlates with increased sound amplitude, particularly in the 100 Hz to 400 Hz range, a critical band for teleost hearing suggesting that visitor-induced noise is distinct from the aquarium's technical background noise. These findings underscore that the 'visitor effect' is not a uniform phenomenon but a complex interaction shaped by species-specific sensitivity and distinct anthropogenic stressors. Our results highlight the necessity of incorporating species-specific behavioral data and acoustic monitoring into welfare management protocols to better mitigate the impact of human presence on captive fish populations.

Objective: Hyperthyroidism and hypothyroidism related to iodine deficiency are major public health concerns in Afghanistan. This study aimed to assess the frequency of thyroid dysfunction among male patients referred for thyroid testing and its association with age, and to examine monthly trends in thyroid dysfunction at Asia Med Laboratory in Herat, Afghanistan, from July 2021 to January 2022. Methods: A retrospective analysis was conducted on 250 male patients aged 0-69 years. We measured Serum TSH, total T4, and total T3 levels, and thyroid status was classified using age specific reference ranges. In addition, the frequency of thyroid dysfunction was analyzed across age groups with monthly trends of thyroid state. Results: Overall, the euthyroid state consisted of 69.2% of participants, 24.8% with overt hypothyroidism, 3.2% with overt hyperthyroidism, and 2.8% with subclinical hyperthyroidism. Thyroid status differed significantly by age (p = 0.0135), with hypothyroidism increasing in older age groups and reaching its highest proportion among men aged 60-69 years (55.6%). Euthyroidism predominated in patients aged 10-39 years, while hyperthyroidism across age groups remained relatively infrequent. After September 2021, a threefold increase was observed in the total number of male patients referred for thyroid testing. During this period, the proportion of hyperthyroidism increased slightly, whereas hypothyroidism cases declined. Conclusion: In conclusion, hypothyroidism was more frequent with older age. The rise in absolute case numbers after September 2021 likely reflects increased patient referrals, underscoring the need for ongoing monitoring of thyroid function. The study may assist in the early management of thyroid disorders and in reducing their complications.

The Peruvian anchovy (Engraulis ringens) is a small pelagic fish. It is the largest singlespecies fishery in the world and it is used mainly for the production of fishmeal and fish oil. The Peruvian hake (Merluccius gayi) is a predatory demersal fish that is valued for direct human consumption, mainly as frozen products. In this study, I compared the response of both species to certain fishing mortality scenarios using a climatological set-up of the multispecies model OSMOSE for the northern Humboldt Current System. I observed that hake landings benefit from a decreased fishing pressure. In addition, the resilience of the anchovy fishery may increase if a higher threshold for their minimum catch size was implemented. The results of this study provide insights into better management strategies that could be beneficial for the two species based on their life-strategies.

Objective and efficient methods for investigating animal's mental states are important for advancing animal welfare research. Behavioural observations and physiological measures provide valuable information but may not fully capture affective states. Judgment Bias Tasks (JBTs) offer a promising method to infer affective states from animals' responses to ambiguous stimuli, as distressed individuals show more pessimistic tendencies. However, the application of JBTs outside research settings may be limited due to time-consuming training and methodological or infrastructural requirements. With the present study, we aimed to test the feasibility of a simple and accessible JBT for non-human primates and to investigate its sensitivity to affective states. Eight brown capuchins (Sapajus apella) and eleven Tonkean macaques (Macaca tonkeana) were tested under positive and negative affective conditions. Individuals were trained to discriminate between never rewarded conditioned stimuli and always rewarded ones. They were then presented with ambiguous probes they had never seen before to analyse their responses to ambiguity. The discrimination training required, on average, about 12 sessions lasting a few minutes each to successfully train every individual animal. Both species significantly discriminated between conditioned stimuli and ambiguous probes. Additionally, macaques showed a greater tendency to interact with the never rewarded condition stimuli and the probes under positive conditions during early sessions. In capuchins, however, the affective conditions presented had no significant effect, although the descriptive analysis tended to show that the latency to investigate the probes was greater in the negative condition. This study also highlights key methodological considerations, such as a decrease in ambiguity across sessions. Overall, the present results suggest that, with a few improvements, this method could be effectively implemented to assess affective states of primates under human care, supporting this tool as a valuable candidate for welfare assessment.

Introduction: Thyroid diseases are major health problems and among the most common endocrine disorders worldwide, including in Ethiopia. They are characterized by alterations in hormone secretion, enlargement of the thyroid gland, or both. Fine needle aspiration cytology is an important initial screening tool, and histopathologic examination is essential for the definitive diagnosis of thyroid disease. This study aimed to compare the diagnostic accuracy of fine needle aspiration cytology with histopathology in identifying thyroid diseases. Methods: A cross-sectional study was conducted at three health facilities in Hawassa City, Ethiopia, involving 304 patients who underwent both thyroid fine needle aspiration cytology and histopathologic examination of the same site between 30th October 2024 and 29th October 2025. FNAC results were classified using the Bethesda system, with histopathology as the gold standard. Data were entered into Kobo Toolbox, exported to SPSS version 27, and analyzed using cross-tabulation and chi-square ({chi}{superscript 2}) tests to determine diagnostic accuracy. Result: 304 patient records were included in the study. The fine needle aspiration cytology was determinate/diagnostic in 81.6% of cases. The study revealed the sensitivity and specificity of fine needle aspiration cytology to be 88.2% (CI 77.6-95.1%) and 94.4% (CI 90.6-97.1%), respectively. The false negative and false positive rates in this study were 2.4% and 4.4%, respectively. The positive predictive value was 80.3% (CI 68.7-89.3%), and the negative predictive value was 96.8% (CI 93.8-98.7%). The accuracy of fine needle aspiration cytology in differentiating benign from malignant thyroid lesions was 93.1%. Conclusion: FNAC demonstrated strong agreement with histopathology and remains a reliable, cost-effective first-line diagnostic tool for thyroid disease, particularly in resource-limited settings. Strengthening sample handling, ultrasound guidance, and adherence to Bethesda criteria may further improve diagnostic precision

Environmental concerns and the need to mitigate the effects of climate change have driven the adoption of renewable energy sources, such as offshore wind farms (OWFs), making it essential to assess their overlap with seabird habitats to estimate potential impacts. This study is the first to estimate the vulnerability of coastal and seabirds to OWFs at a national scale by integrating biological trait data from the literature, spatial occurrence records from citizen science platforms, and expert knowledge (elicited from 23 specialists) into established quantitative risk frameworks. Collision risk and susceptibility scores were calculated at the family and subfamily levels, as well as disturbance and displacement indices by species and susceptibility by state. The groups with the highest collision risk and susceptibility were Fregatidae (0.354; 0.486), Sulidae (0.199; 0.419), Sterninae (0.190; 0.384) and Diomedeidae (0.190; 0.416). The extreme risk for Fregatidae is driven by their specific flight characteristics, with impacts concentrated in the highly frequented southeast and northeast regions. Regarding disturbance and displacement, Limnodromus griseus exhibited the highest national score (MMA: 0.098), while Diomedea dabbenena had the highest global score (IUCN: 0.092), highlighting the critical need to integrate both regional and global conservation statuses. Spatially, the state exhibiting the highest overall vulnerability to OWF impacts was Rio Grande do Sul (23.78; 10.69), a critical hotspot characterized by high species richness and oceanographic productivity. These findings establish an indispensable national baseline for Marine Spatial Planning, reinforcing the need for targeted pre-installation assessments, the identification of sentinel species, and spatially differentiated management during environmental licensing processes.

The fieldwork was carried out between December 2023 and June 2025, with the aim, among others, of confirming the possible presence of the North African Gerbil (Gerbillus campestris) in Melilla. To this end, 56 camera trap stations were installed, each equipped with a camera trap. Of the total number of camera trap stations installed, the presence of Gerbillus campestris was detected in six of them, representing a capture success rate of 10.71%. Following the detection of the species, a specimen was captured using cage traps. For identification purposes, samples of epithelial tissue from the ear and faeces were collected. These samples were sent to the Institute of Vertebrate Biology of the Czech Academy of Sciences, Brno, Czech Republic, for analysis. There, DNA was extracted from the samples using the Innu PREP DNA Mini Kit 2.0 (IST Innuscreen GmbH, Germany) according to the manufacturer's protocol. The results obtained confirm, for the first time through records of the species, the presence of Gerbillus campestris in Melilla and, therefore, in Spain and Europe.

International wildlife trade represents one of the major drivers of biodiversity exploitation worldwide. However, the true taxonomic diversity embedded within commercial wildlife products often remains unknown because processing removes diagnostic morphological characteristics, preventing reliable species identification. Consequently, biodiversity assessments based solely on product labels may substantially underestimate the diversity of species involved in trade networks. To investigate hidden biodiversity within wildlife trade products, we applied DNA barcoding based on the mitochondrial cytochrome c oxidase subunit I (COI) gene to 77 products commercialized as fish swim bladders and seized at Guarulhos International Airport, Brazil. Molecular analyses successfully identified all samples and revealed the presence of four species: Plagioscion auratus (n = 38), Cynoscion acoupa (n = 7), Melanosuchus niger (n = 17), and Caiman crocodilus (n = 15). Fish species accounted for 71.4% of all samples, whereas crocodilians represented 28.6%, demonstrating that products marketed under a single commercial category may conceal substantial taxonomic diversity. Notably, the occurrence of two Amazonian crocodilian species within a trade chain traditionally associated with fish products reveals a previously undocumented component of the international wildlife trade. Our findings demonstrate that DNA barcoding is an effective tool for uncovering hidden biodiversity within processed wildlife products and provide evidence that wildlife trade networks may involve a broader spectrum of species than suggested by commercial labels. These results highlight the importance of molecular surveillance for biodiversity monitoring, wildlife trade regulation, and conservation planning.

Highly pathogenic avian influenza (HPAI) is among the most significant disease threats to poultry worldwide. Modelling challenges, where independent teams address a common epidemiological scenario, can support the development of response capabilities and strengthen communication between modellers and risk managers. Despite the established benefits of these exercises, they remain uncommon in animal health, and none have previously addressed avian influenza. Here Jolly Island, an artificial landscape of 9160 poultry farms with five production types, was developed and seeded with stochastic HPAI epidemics that ran their course over a three-to-four month period. From January through April 2026, 45 registered teams across five continents investigated a selected synthetic epidemic, producing probabilistic forecasts, inferring transmission drivers, and evaluating counterfactual control policies. Here the objectives, design choices, and data generation of the HPAI Modelling Challenge are described in full, covering transmission processes, surveillance system operations, and control strategy implementation, along with the selected epidemic trajectory, the narrative situation reports supplied to the teams at each phase, and the complete phase-specific datasets released to them. As the opening paper of this special issue, here is provided the foundation upon which all subsequent contributions, where teams document their approaches and analyses, are built.

Reliable demographic data are critical for seal population assessment and management, yet remain challenging to obtain from drone surveys without automated tools. Using data from harbor seal (Phoca vitulina) haulout surveys conducted in British Columbia, Canada, in 2023-2024, we developed and tested an automated pipeline that integrates detection, morphometric extraction, and size-class classification of seals into a single system. The pipeline combines cascaded DeepLabV3+ segmentation (water removal, colony-level seal detection, and individual body-contour refinement), principal component analysis (PCA)-based extraction of body length and maximum width, and three-class size-class determination based on body length (pups, juveniles, subadults/adults). We evaluated the pipeline on 2,483 manually annotated seals across four drone platforms (DJI Mavic 3 Thermal, Mavic 2 Pro, Mini 3 Pro and Mini 2), five substrate types, and two sensor modalities (RGB, thermal infrared). Aggregate detection F1 was 0.914. Orthomosaic geometric accuracy, quantified as the RMSE of calibration-rod length on the orthomosaic, ranged from 1.0 cm to 18.0 cm depending on the platform-altitude-substrate combination, a spread that aggregate metrics would mask. Relative to manual annotation on the same orthomosaics, automated RGB body lengths showed near-zero bias (-0.6 cm; RMSE = 12.5 cm), whereas automated thermal lengths were systematically shorter (bias -19.9 cm, RMSE = 24.1 cm), establishing the unsuitability of thermal imagery for automated quantitative pinniped morphometry. For RGB imagery, threshold classification by body length reached an overall accuracy (OA) of 78.7%; for individuals outside the uncertainty zones (defined as {+/-}2 x the geometric RMSE on calibration rods around each class boundary), OA reached 90.9%. Within the RGB subset, OA was 78.9% at 20 m altitude, declining to 75.0% at 40 m where geometric error dominated. The pipeline enables automated demographic monitoring of pinniped haulouts with quantitatively characterized uncertainty across survey conditions.

1. For many animals, vision represents the primary sensory modality governing a vast diversity of behaviours. Creating 'virtual twins', or visually realistic digital reconstructions of real individuals interacting within their environments, offers a promising approach for understanding how visual information guides an animal's decisions, behaviours, and interactions. Such systems enable the creation of video scenes from any view, including the viewpoint of the animals themselves. This allows receiver information to then be analysed from the perspective of species-specific visual systems, or for the accurate reconstruction of a real animal's movement to provide social stimuli for behavioural experiments. 2. Despite advances in 3D modelling, photorealistic scene rendering, and animal tracking, efficiently creating realistic digital reconstructions of movement remains challenging for many species. In fishes, a continuously-deforming body due to the absence of discrete joints make it particularly difficult to map tracked body keypoints onto articulated digital models, often resulting in unnatural or erratic animations. 3. Here, we introduce DigiFish, an add-on for the open-source animating software Blender, that generates realistic fish animations from tracking data. By integrating anatomical keypoint tracking with spline-based body curvatures, DigiFish reconstructs biologically-realistic swimming postures and movements of fishes within customisable virtual aquatic environments. The system also supports virtual 'point-of-view' cameras that can be placed arbitrarily within a scene, or dynamically driven by eye-tracking data, enabling unlimited perspectives on how individuals, conspecifics, or landmarks appear against complex backgrounds and how these views change with realistic swimming and eye movements. 4. We provide the Blender add-on and user guide and use DigiFish to reconstruct two different contexts: staged predator-prey interactions in the laboratory and natural schooling of wild fish in the field. Using a further reconstruction of fish swimming in an arena, we also use an Elementary Motion Detector model to show that our virtual reconstructions successfully capture perceptually-realistic movements and postures of individual fish within a digitally reconstructed scene. 5. By integrating photo-realistic scenes with biologically-realistic, simulated motion, DigiFish offers a flexible and accessible platform for investigating visually guided behaviour, perception, and cognition in complex and dynamic environments.

Recent zoonotic coronavirus outbreaks have sparked an interest in understanding coronaviruses circulating in animal reservoirs. While bats are recognised as major reservoirs for these viruses, coronaviruses have also been detected in a wide range of terrestrial small mammals, particularly rodents. However, coronavirus diversity in these mammals, specifically in Europe, is still poorly characterised. In this study, we detected and characterised coronaviruses in terrestrial small mammals and bats from Belgium, France, Germany, and Ireland. We screened tissue samples from rodents and shrews and environmental bat guano using pan-coronavirus real-time and conventional PCRs, with positive results confirmed by sanger sequencing. Among 2667 bat and 1152 terrestrial mammal samples, we detected 59 positive samples, 36 from bats and 23 from rodents, from which we recovered 60 coronavirus sequences, spanning both Alphacoronavirus and Betacoronavirus lineages. Through next generation sequencing we identified one Pipistrellus pygmaeus bat guano sample carrying two distinct alphacoronaviruses, representing Nyctacovirus and Pedacovirus subgenera. Among rodents, most coronavirus-positive samples originated from a zoo in Belgium, where several CoV lineages co-circulated. The identified rodent coronaviruses clustered among previously described rodent-associated lineages, some of which also include human and other mammal-derived coronavirus sequences. Consistent with previous studies, we found sarbecoviruses in horseshoe bats (particularly Rhinolophus ferrumequinum and R. hipposideros) and merbecoviruses in Plecotus auritus bats, and these viruses are distantly related to the human coronaviruses of the respective families. Similar to bat coronaviruses, some rodent coronaviruses strains seemed to be association with specific rodent species. In conclusion, our study enhances the understanding of coronaviruses in rodents and bats, revealing potential hotspots for these viruses and their implication for human and animal health. These findings underscore the necessity for continued surveillance of coronaviruses in wildlife reservoirs to mitigate future zoonotic spillover risks.

Trail cameras have become ubiquitous tools for ecological data collection over recent decades. Despite progress in the development of automated algorithms and artificial intelligence for image classification, our ability to process large volumes of data remain limited by the need for trained human observers to make refined judgements. We provide guidance on placement of trail cameras for observing Asian elephants (Elephas maximus) and outline a protocol for training and testing naive human observers in performing image classifications (age/sex class and group composition) that cannot yet be automated. This process can be used to develop a high-throughput workflow capable of extracting useful data from large volumes of images. Our training material consisted of 14,007 images collected from 6 trail cameras around Udawalawe National Park in Sri Lanka from 2017-2019. In the first stage, expert observers (n=3) trained a group of inexperienced participants (n=4), who engaged in an iterative process to develop a protocol document. The document was then tested on a second set of subjects (n=6) each of whom classified 350 test images in four separate sequential batches using quantitative measures of precision and accuracy. The test set was sampled from 54,435 images from an additional 25 cameras. When compared to expert observers, they achieved a fair level of precision (Fleiss' kappa = 0.247) and 82.6% accuracy. Our approach can usefully be extended to other species and contexts.

Macrophages, alongside mammary epithelial cells, are major contributors to the innate immune response triggered by bacterial invasion of the mammary gland. To investigate breed-specific immune mechanisms, we stimulated monocyte-derived macrophages from Holstein and Normande cattle with Escherichia coli and Streptococcus uberis, two major mastitis pathogens. We monitored bacterial survival using [methode] and profiled gene expression via RNA-seq. E. coli exhibited significantly higher survival 6 hours post-infection compared to S. uberis (p < 0.05). Moreover, E. coli induced a robust transcriptional response, with 4403 differentially expressed genes (FDR < 0.05, |log2FC| > 1), versus only 813 for S. uberis. Qualitative differences were also observed: genes such as CCL2 and CSF1 were uniquely induced by S. uberis. Additionally, macrophages from Holstein and Normande cattle showed distinct expression profiles: 185, 45, and 174 genes were differentially expressed at steady state or after E. coli or S. uberis stimulation, respectively. These genes were enriched in immune-related pathways. Overall, our results demonstrate a stronger response to E. coli, although S. uberis specifically induces a subset of genes. The observed breed-specific differences may reflect underlying immune mechanisms that could influence disease susceptibility, warranting further functional validation.

Neoehrlichia mikurensis is widely detected in tick populations across Europe, yet its host range beyond small rodents remains poorly understood. Large wild mammals are frequently exposed to tick vectors, but their role in the transmission cycle of this bacterium is unclear. Wild boars (Sus scrofa) are among the most abundant large mammals in southern Sweden and commonly inhabit tick-infested environments, making them a potentially relevant host species. In this study, spleen samples from 87 wild boars collected between 2023 and 2025 across southern and central Sweden were analysed for the presence of N. mikurensis DNA using quantitative polymerase chain reaction. N. mikurensis DNA was not detected in any of the analysed samples, despite sampling in regions where the bacterium is known to be prevalent in ticks. These results indicate that wild boars may have a limited role in the maintenance of N. mikurensis in Sweden, although the possibility of rare or transient infection cannot be excluded. Despite being based on negative findings, this study contributes to a more comprehensive understanding of the host range of N. mikurensis and highlights the importance of continued evaluation of wildlife species in the transmission dynamics of tick-borne pathogens.

Vertical transmission of SARS-CoV-2 is controversial. Owing to the low expression of ACE2 along with TMPRSS2 in placenta, role of secondary receptors becomes significant. In our study we predicted twelve interactors of spike protein expressed in placenta through interactome analysis followed by docking and molecular dynamic simulation. Three interactors of SARS-CoV-2 spike protein were found to be CD147, EGFR and LDLR. Expression at transcriptomic and translational level by real-time PCR and immunohistochemistry respectively was observed in placenta samples obtained from women with COVID exposure risk and compared to control. Elevated protein levels of CD147 (OR=14.667), ACE2 (OR=8.25) and LDLR (OR=1.9) was associated with higher exposure risk. However, the variation in mRNA expression was not statistically significant. Computational study showed that CD147/basigin, EGFR and LDLR stably interact with spike protein outside its primary receptor binding domain. In-vitro binding assay confirmed the physical interaction between spike protein and the placental receptors. In-silico site-directed mutagenesis further identified key potential binding hotspots of spike protein- Tyr28 and Trp64 for CD147, Phe643, Val642, Thr632 for LDLR and Leu8, Phe59, Phe32, Tyr28, Trp64, Trwp152, His245, and Val213 for EGFR. Finally, concluded that CD147, EGFR and LDLR might act as secondary non-canonical cofactors for SARS-CoV-2 spike protein in placenta, thereby increasing its susceptibility and tissue tropism. The study overall gives a better insight into potential placental suscpetibility providing targeted therapeutic opportunities.

Reliable morphological criteria for sexing birds without the need for invasive procedures are scientifically and ethically valuable. Smith et al (2005) reported that iris colour assigns the genetic sex of Starlings Sturnus vulgaris with 98% accuracy, and bill base colour with 100% accuracy when birds are in breeding condition, but these figures have not been tested independently. We applied their criteria to 31 captive Starlings in breeding condition, using three observers blind to genetic sex, two of them new to Starling sexing. Bill base colour correctly predicted genetic sex for all 29 birds scored, with complete observer agreement. Mean iris score was correct for 27 of 31 (87.1%), fewer than the 94 of 96 reported by Smith et al (2005) for birds in breeding condition (Fisher exact test, P = 0.031), although with so few errors in either study this comparison is imprecise. Observer agreement was high, so these errors reflect iris colouration conflicting with genetic sex rather than inconsistent scoring; bill base colour was correct for all four misassigned birds. Body mass and tarsus length classified 77% and 58% of birds correctly, their published thresholds missing in opposite directions. We conclude that bill base colour should be the primary criterion for sexing Starlings in breeding condition; the accuracy of iris colour should not be assumed to be 98%.