Continuous land cover change detection in a critically endangered shrubland ecosystem using neural networks Existing efforts to continuously land cover change using satellite image time-series have mostly focused on forested ecosystems in the tropics and northern hemisphere. The notable difference in reflectance that occurs following deforestation allows land cover change to be detected with relative accuracy. Less progress has been made in detecting change in low productivity, disturbanceprone vegetation such as grasslands and shrublands, where natural dynamics can be difficult to distinguish from habitat loss. Renosterveld is a hyperdiverse, critically endangered shrubland ecosystem in South Africa with less than 5-10% of its original extent remaining in small, highly fragmented patches. I demonstrate that direct classification of satellite image time series using neural networks can accurately detect the transformation of Renosterveld within a few days of its occurrence, and that trained models are suitable for operational continuous monitoring. A dataset of precisely dated vegetation change events between 2016 and 2021 was obtained from daily, high resolution Planet labs satellite data. This dataset was then used to train and evaluate 1D convolutional neural networks and Transformers to continuously detect land cover change events in multivariate time-series of vegetation activity of Sentinel 2 satellite data as it becomes available. The best model correctly identified 89% of land cover change events at the pixel-level, achieving a f-score of 0.93, a 79% improvement over the f-score of 0.52 achieved using a method designed for forested ecosystems based on trend analysis. Models have been deployed to operational use and are producing updated detections of habitat loss every 10 days. There is great potential for supervised approaches to continuous monitoring of habitat loss in ecosystems with complex natural dynamics. A key limiting step is the development of accurately dated datasets of land cover change events with which to train machine learning classifiers.
Modelling porcine reproductive and respiratory syndrome virus dissemination dynamics to quantifythe contribution of multiple modes of transmission: between-farm pig and vehicle movements, farmto-farm proximity, feed ingredients, and re-break Accounting for multiple modes of livestock disease dissemination in epidemiological models remains a challenge. We developed and calibrated a mathematical model for transmission of porcine reproductive and respiratory syndrome virus (PRRSV), tailored to fit nine modes of between-farm transmission pathways including: farm-to-farm proximity (local transmission), contact network of batches of pigs transferred between farms (pig movements), re-break probabilities for farms with previous PRRSV outbreaks, with the addition of four different contact networks of transportation vehicles (vehicles to transport pigs to farms, pigs to markets, feed and crew) and the amount of animal by-products within feed ingredients (e.g. animal fat or meat and bone meal). The model was calibrated on weekly PRRSV outbreaks data. We assessed the role of each transmission pathway considering the dynamics of specific types of production (i.e., sow, nursery). Although our results estimated that the networks formed by transportation vehicles were more densely connected than the network of pigs transported between-farms, pig movements and farm proximity were the main PRRSV transmission routes regardless of farm types. Among the four vehicle networks, vehicles transporting pigs to farms explained a large proportion of infections, sow = 20.9%; nursery = 15%; and finisher = 20.6%. The animal by-products showed a limited association with PRRSV outbreaks through descriptive analysis, and our model results showed that the contribution of animal fat contributed only 2.5% and meat and bone meal only 0.03% of the infected sow farms. Our work demonstrated the contribution of multiple routes of PRRSV dissemination, which has not been deeply explored before. It also provides strong evidence to support the need for cautious, measured PRRSV control strategies for transportation vehicles and further research for feed by-products modeling. Finally, this study provides valuable information and opportunities for the swine industry to focus effort on the most relevant modes of PRRSV between-farm transmission.
Suppression of sost/sclerostin and dickkopf-1 promote intervertebral disc structure in mice Intervertebral disc (IVD) degeneration is a leading cause of low back pain and characterized by accelerated extracellular matrix breakdown and IVD height loss but there is no approved pharmacological therapeutic. Deletion of Wnt signaling receptor Lrp5 induces IVD degeneration and suggests that Wnt signaling in the IVD may be responsive to inhibition of Wnt signaling inhibitors sost(gene)/sclerostin(protein) or dickkopf-1 (dkk1). Anti-sclerostin antibody (Scl-Ab) is an FDA-approved bone therapeutic that activates Wnt signaling. We (1) determined if pharmacological neutralization of sclerostin, dkk1 or their combination stimulate Wnt signaling and promote IVD structure and (2) determined the extent of the response of the IVD to global, persistent deletion of sost. Nine-week-old C57Bl/6J female mice (n=6-7/grp) were subcutaneously injected 2x/wk for 5.5 wk with scl-Ab (25 mg/kg), dkk1-Ab (25 mg/kg), 3:1 scl-Ab/dkk1-Ab (18.75:6.25 mg/kg) or vehicle (Veh). Separately, IVD of sost KO and WT (wildtype) mice (n=8, grp) were harvested at 16 weeks of age. First, compared to vehicle, scl-Ab, dkk1-Ab and 3:1 scl-Ab/dkk1-Ab similarly increased lumbar IVD height and {beta}-catenin gene expression. Despite these similarities, scl-Ab decreased cellular stress-related heat shock protein gene expressions while neither dkk1-Ab nor scl-Ab/dkk1-Ab altered the same. Genetically and compared to WT, sost KO increased MRI-determined hydration and proteoglycan staining in the IVD. Notably, persistent deletion of sost was compensated by upregulation of dkk1, which consequently reduced the cell nuclear fraction for Wnt signaling transcription factor {beta}-catenin in whole IVD. Lastly, RNA-sequencing pathway analysis confirmed the compensatory suppression of Wnt signaling and determined a reduction of cellular stress pathways. Together, suppression of sost/sclerostin or dkk1 each promote IVD structure by stimulating Wnt signaling, but sclerostin and dkk1 may differentially regulate cellular stress pathways. Ultimately, postmenopausal women prescribed scl-Ab injections to prevent vertebral fracture may also benefit from a restoration of IVD height and health.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/449486v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@db2e17org.highwire.dtl.DTLVardef@1af1bbborg.highwire.dtl.DTLVardef@145cc4corg.highwire.dtl.DTLVardef@167a19e_HPS_FORMAT_FIGEXP  M_FIG C_FIG Suppression of Wnt signaling inhibitors by genetic or pharmacological approaches promotes intervertebral disc structure and hydration by Wnt signaling. However, persistent activation of Wnt signaling induces a compensatory reduction of Wnt signaling that shifts IVD cells toward a chondrocyte-like (CLC) phenotype. AF: annulus fibrosus, NC: notochordal cell, NP: nucleus pulposus, PG: proteoglycan Computational modeling and quantitative cell physiology reveal central parameters for the brassinosteroid-regulated cell growth of the Arabidopsis root Brassinosteroids (BR) are key hormonal regulators of plant development. However, whereas the individual components of BR perception and signaling are well characterized experimentally, the question of how they can act and whether they are sufficient to carry out the critical function of cellular elongation remains open. Here, we combined computational modeling with quantitative cell physiology to understand the dynamics of the plasma membrane (PM)-localized BR response pathway during the initiation of cell elongation in the epidermis of the Arabidopsis root tip. The model, consisting of ordinary differential equations, comprises the BR induced hyperpolarization of the PM, the acidification of the apoplast and subsequent cell wall swelling. We demonstrated that the competence of the root epidermal cells for the BR response predominantly depends on the amount and activity of H+-ATPases in the PM. The model further predicted that an influx of cations is required to compensate for the shift of positive charges caused by the apoplastic acidification. A potassium channel was subsequently identified and experimentally characterized, fulfilling this function. Thus, we established the landscape of components and parameters capable of triggering and guiding cellular elongation through the fast response to BRs, a central process in plant development. MT-MAG: Accurate and interpretable machine learning for complete or partial taxonomic assignments of metagenome-assembled genomes We propose MT-MAG, a novel machine learning-based software tool for the complete or partial hierarchically-structured taxonomic classification of metagenome-assembled genomes (MAGs). MT-MAG is capable of classifying large and diverse metagenomic datasets: a total of 245.68 Gbp in the training sets, and 9.6 Gbp in the test sets analyzed in this study. MT-MAG is, to the best of our knowledge, the first machine learning method for taxonomic assignment of metagenomic data that offers a "partial classification" option. MT-MAG outputs complete or partial classification paths, and interpretable numerical classification confidences of its classifications, at all taxonomic ranks. To assess the performance of MT-MAG, we define a "weighted classification accuracy," with a weighting scheme reflecting the fact that partial classifications at different ranks are not equally informative. For the two benchmarking datasets analyzed (genomes from human gut microbiome species, and bacterial and archaeal genomes assembled from cow rumen metagenomic sequences), MT-MAG achieves an average of 80.13% in weighted classification accuracy. At the Species level, MT-MAG outperforms DeepMicrobes, the only other comparable software tool, by an average of 35.75% in weighted classification accuracy. In addition, MT-MAG is able to completely classify an average of 67.7% of the sequences at the Species level, compared with DeepMicrobes which only classifies 47.45%. Moreover, MT-MAG provides additional information for sequences that are not completely classified at the Species level, resulting in the partial or complete classification of 95.15%, of the genomes in the datasets analyzed. In particular, MT-MAG classifies, on average, 88.84% of the test sequences to the Phylum level, 88.39% to the Class level, 86.81% to the Order level, 81.17% to the Family level, and 71.13% to the Genus level. Colicin E1 opens its hinge to plug TolC The double membrane architecture of Gram-negative bacteria forms a barrier that is effectively impermeable to extracellular threats. Bacteriocin proteins evolved to exploit the accessible, surface-exposed proteins embedded in the outer membrane to deliver cytotoxic cargo. Colicin E1 is a bacteriocin produced by, and lethal to, Escherichia coli that hijacks the outer membrane proteins TolC and BtuB to enter the cell. Here we capture the colicin E1 translocation domain inside its membrane receptor, TolC, by high-resolution cryoEM, the first reported structure of a bacteriocin bound to TolC. Colicin E1 binds stably to TolC as an open hinge through the TolC pore--an architectural rearrangement from colicin E1s unbound conformation. This binding is stable in live E. coli cells as indicated by single-molecule fluorescence microscopy. Finally, colicin E1 fragments binding to TolC plugs the channel, inhibiting its native efflux function as an antibiotic efflux pump and heightening susceptibility to three antibiotic classes. In addition to demonstrating that these protein fragments are useful starting points for developing novel antibiotic potentiators, this method could be expanded to other colicins to inhibit other outer membrane protein functions. Geographical Distribution of Biomphalaria snails in East Africa There is limited information on the distribution of Biomphalaria snails, an important snail intermediate host of schistosomiasis, in East Africa. This study assessed the incidence and geographical distribution of Biomphalaria snails in Kenya, Uganda and Tanzania. Maximum Entropy modeling was used to predict the potential distribution of Biomphalaria snails, in line with habitat suitability. Malacological surveys were then conducted guided by MaxEnt predictions and information obtained from previous research papers. The surveys were conducted at a total of 156 sites including streams, rivers, lake shores, dams and irrigation canals over a 3-year period (2018 to 2020). Geographical coordinates, ecological and physicochemical information was recorded for the sites visited. Snails were identified morphologically, based on shell characters using established identification keys. Biomphalaria snails were found at 23.07% (36/156) of the sites sampled. Streams proved to be the habitats most preferred by Biomphalaria snails (50% of all of the sites where the snails were found were streams), followed by rivers (20.6%), irrigation canals (8.8%), lake shores (8.8%), springs (5.9%), and dams (5.9%) with snail abundance increasing with increase in temperature and decrease in water depth. Biomphalaria snails were found in the Lake Victoria basin, Mwea Irrigation Scheme and Eastern Province of Kenya, the Lake Albert region, Lango region, Soroti district, Lower Moshi irrigation scheme, Babati district, Iringa region, Tabora region and Kigoma region. Information on the distribution of Biomphalaria snails in East Africa will aid in developing prevention and control strategies for schistosomiasis.

AUTHOR SUMMARYFew studies have been conducted on the distribution of Biomphalaria snails in East Africa with previous studies mostly isolated projects restricted to single divisions, districts and regions. Knowledge on the distribution of snail intermediate hosts can be helpful in establishing schistosomiasis transmission surveillance systems for detecting emerging and prevailing incidences of schistosomiasis. We undertook malacological surveys of freshwater sites across Kenya, Uganda and Tanzania. A total of 156 sites were sampled and Biomphalaria snails were found at 36 of the sites. Streams yielded the highest number of snails, in comparison to the other habitats that were sampled. Temperature and water depth were established to be statistically significant ecological and physicochemical factors that influence incidences and abundance of the snails. This study provides important information on the distribution of an important snail intermediate host in East Africa and the knowledge obtained herein can be helpful in establishing appropriate schistosomiasis control initiatives. Overexpression-based detection of translatable circular RNAs is vulnerable to coexistent linear RNA byproducts In RNA field, the demarcation between coding and non-coding has been negotiated by the recent discovery of occasionally translated circular RNAs (circRNAs). Although absent of 5 cap structure, circRNAs can be translated cap-independently. Complementary intron-mediated overexpression is one of the most utilized methodologies for circRNA research but not without bearing echoing skepticism for its poorly defined mechanism and latent coexistent side products. In this study, leveraging such circRNA overexpression system, we have interrogated the protein-coding potential of 30 human circRNAs containing infinite open reading frames in HEK293T cells. Surprisingly, pervasive translation signals are detected by immunoblotting. However, intensive mutagenesis reveals that numerous translation signals are generated independently of circRNA synthesis. We have developed a dual tag strategy to isolate translation noise and directly demonstrate that the fallacious translation signals originate from cryptically spliced linear transcripts. The concomitant linear RNA byproducts, presumably concatemers, can be translated to allow pseudo rolling circle translation signals, and can involve backsplicing junction (BSJ) to disqualify the BSJ-based evidence for circRNA translation. We also find non-AUG start codons may engage in the translation initiation of circRNAs. Taken together, our systematic evaluation sheds light on heterogeneous translational outputs from circRNA overexpression vector and comes with a caveat that ectopic overexpression technique necessitates extremely rigorous control setup in circRNA translation and functional investigation. Nrf2 modulates the hybrid epithelial/mesenchymal phenotype and Notch signaling during collective cancer migration Hybrid epithelial/mesenchymal cells (E/M) are key players in aggressive cancer metastasis. It remains a challenge to understand how these cell states, which are mostly non-existent in healthy tissue, become stable phenotypes participating in collective cancer migration. The transcription factor Nrf2, which is associated with tumor progression and resistance to therapy, appears to be central to this process. Here, using a combination of single cell biosensors, immunocytochemistry, and computational modeling, we show that Nrf2 functions as a phenotypic stability factor for hybrid E/M cells by inhibiting a complete epithelial-mesenchymal transition (EMT) during collective cancer migration. We also demonstrate that Nrf2 and EMT signaling are spatially coordinated near the migrating front. In particular, computational analysis of an Nrf2-EMT-Notch network and experimental modulation of Nrf2 by pharmacological treatment or CRISPR/Cas9 gene editing reveal that Nrf2 stabilizes a hybrid E/M phenotype which is maximally observed in the interior region immediately behind the leading edge. We further demonstrate that the Nrf2-EMT-Notch network enhances Dll4 and Jagged1 expression near the leading edge, which correlates with the formation of leader cells and protruding tips. Altogether, our results provide direct evidence that Nrf2 acts as a phenotypic stability factor in restricting complete EMT and plays an important role in coordinating collective cancer migration. Citation needed?Wikipedia bibliometrics during the first waveof the COVID-19 pandemic. BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Bespoke data augmentation and network construction enable developmental morphological classification on limited microscopy datasets Deep learning is a powerful tool for image classification, yet training deep learning models often requires large datasets, which are not always available in biological research. Here we use a small dataset to train an accurate classifier by employing data augmentation regimes and Bayesian optimisation. We establish a new staging system for the Hamburger-Hamilton stage 10 chick embryo brain, based on morphology, identifying three sub-stages uncoupled from somite number, the usual metric used to stage chick embryos. Incorporating biologically informed, data-driven preprocessing, we train a deep convolutional neural network to classify our sub-stages. We find that augmenting our images with a combination of rotation, blur, shear, and cutout transformations is effective in training an accurate classifier on a small microscopy dataset. We then apply our approach to an unrelated small microscopy dataset comprising images of limb buds, finding good agreement with the results from brain classification. Through saliency analysis, we ensure that relevant features are being used by our classifier, gain insight into the efficacy of different data augmentations, and identify sub-stage specific features. In summary, we apply biological domain expertise to design effective data augmentation regimes for training a neural network-based image classifier on small, specialised datasets, classifying the developing brains and limbs with up to 90.9% and 94.4% accuracy respectively. These reliable classifiers can inform future experiments. The compound of baicalein, wogonin, and oroxylin-A inhibits EMT in A549 cell line via PI3K/AKT-TWIST1-glycolysis pathway Non-small cell lung cancer (NSCLC) is a worldwide disease with high morbidity and mortality, which is most derived from its metastasis. Some researches show that the epithelial-mesenchymal transition (EMT) process promotes lung cancer cells migration and invasion, leading to NSCLC metastasis. Total Flavonoid Aglycones Extract (TFAE) isolated from Scutellaria baicalensis was reported to inhibit tumor growth and induce apoptosis. In this study, we found that baicalein, wogonin, and oroxylin-A were the active compounds of TFAE. After reconstructing with these three compounds (baicalein (65.8%), wogonin (21.2%), and oroxylin-A (13.0%)), the reconstructed TFAE (reTFAE) present inhibitory effect on the EMT process of A549 cells. Then, bioinformatic technology was employed to elucidate the potential pharmacodynamic mechanism network of reTFAE. We identified the relationship between reTFAE and PI3K/Akt signaling pathways, with TWIST1 as the key protein. LY294002, the inhibitor of PI3K/Akt signaling pathway, and knock-down TWIST1 could significantly enhance the efficacy of reTFAE, with increasing expression of epithelial markers and decreasing expression of mesenchymal markers in A549 cells at the same time. Furthermore, stable isotope dimethyl-labeled proteomics technology was conducted to complement the follow-up mechanism that the EMT-inhibition process may be realized through glycolysis pathway. In conclusion, we claim that TWIST1-targeted flavonoids could provide a new strategy to inhibit EMT progress for the treatment of NSCLC. Spatial phylogenetics of Japanese ferns: Patterns, processes, and implications for conservation PremiseBiodiversity is often only measured with species richness. However, this ignores evolutionary history and is not sufficient for making conservation decisions. Here, we characterize multiple facets and drivers of biodiversity to understand how these relate to bioregions and conservation status in the ferns of Japan.

MethodsWe compiled a community dataset of 1,239 20 km x 20 km grid-cells including 672 taxa based on > 300,000 specimen records. We combined this with a phylogeny and functional traits to analyze taxonomic, phylogenetic, and functional diversity, and modeled biodiversity metrics in response to environmental factors and reproductive mode. Hierarchical clustering was used to delimit bioregions. Conservation status and threats were assessed by comparing the overlap of significantly diverse grid-cells with conservation zones and range maps of native Japanese deer.

ResultsTaxonomic richness was highest at mid-latitudes. Phylogenetic and functional diversity and phylogenetic endemism were highest in small southern islands. Relative phylogenetic and functional diversity were high at high and low latitudes, and low at mid-latitudes. Grid-cells were grouped into three (phylogenetic) or four (taxonomic) major bioregions. Temperature and apomixis were identified as drivers of biodiversity patterns. Conservation status was generally high for grid-cells with significantly high biodiversity, but the threat due to herbivory by deer was greater for taxonomic richness than other metrics.

ConclusionsOur integrative approach reveals previously undetected patterns and drivers of biodiversity in the ferns of Japan. Future conservation efforts should recognize that threats can vary by biodiversity metric and consider multiple multiple metrics when establishing conservation priorities. Loss of SUMO-specific protease 2 causes isolated glucocorticoid deficiency by blocking adrenal cortex zonal transdifferentiation SUMOylation is a dynamic posttranslational modification, that provides fine-tuning of protein function involved in the cellular response to stress, differentiation, and tissue development. In the adrenal cortex, an emblematic endocrine organ that mediates adaptation to physiological demands, the SUMOylation gradient is inversely correlated with the gradient of cellular differentiation raising important questions about its role in functional zonation and the response to stress. Considering that SUMO-specific protease 2 (SENP2), a deSUMOylating enzyme, is upregulated by ACTH/PKA signalling within the zona Fasciculata (zF), we generated mice with adrenal-specific Senp2 loss to address these questions. Disruption of SENP2 activity in steroidogenic cells leads to specific hypoplasia of the zF, a blunted reponses to ACTH and isolated glucocorticoid deficiency. Mechanistically, overSUMOylation resulting from SENP2 loss shifts the balance between ACTH/PKA and WNT/{beta}-catenin signalling leading to repression of PKA activity and ectopic activation of {beta}-catenin. At the cellular level, this blocks transdifferentiation of {beta}-catenin-positive zona Glomerulosa cells into zF cells and sensitises them to premature apoptosis. Our findings indicate that the SUMO pathway is critical for adrenal homeostasis and stress responsiveness. Possible Cross Reactivity of Feline and White-tailed Deer Antibodies Against the SARS-CoV-2 Receptor Binding Domain In late 2019, a novel coronavirus began circulating within humans in central China. It was designated SARS-CoV-2 because of its genetic similarities to the 2003 SARS coronavirus (SARS-CoV). Now that SARS-CoV-2 has spread worldwide, there is a risk of it establishing new animal reservoirs and recombination with native circulating coronaviruses. To screen local animal populations in the United States for exposure to SARS-like coronaviruses, we developed a serological assay using the receptor binding domain (RBD) from SARS-CoV-2. SARS-CoV-2s RBD is antigenically distinct from common human and animal coronaviruses allowing us to identify animals previously infected with SARS-CoV or SARS-CoV-2. Using an indirect ELISA for SARS-CoV-2s RBD, we screened serum from wild and domestic animals for the presence of antibodies against SARS-CoV-2s RBD. Surprisingly pre-pandemic feline serum samples submitted to the University of Tennessee Veterinary Hospital were [~]50% positive for anti-SARS RBD antibodies. Some of these samples were serologically negative for feline coronavirus (FCoV), raising the question of the etiological agent generating anti-SARS-CoV-2 RBD cross-reactivity. We also identified several white-tailed deer from South Carolina with anti-SARS-CoV-2 antibodies. These results are intriguing as cross-reactive antibodies towards SARS-CoV-2 RBD have not been reported to date. The etiological agent responsible for seropositivity was not readily apparent, but finding seropositive cats prior to the current SARS-CoV-2 pandemic highlights our lack of information about circulating coronaviruses in other species.

ImportanceWe report cross-reactive antibodies from pre-pandemic cats and post-pandemic South Carolina white-tailed deer that are specific for that SARS-CoV RBD. There are several potential explanations for this cross-reactivity, each with important implications to coronavirus disease surveillance. Perhaps the most intriguing possibility is the existence and transmission of an etiological agent (such as another coronavirus) with similarity to SARS-CoV-2s RBD region. However, we lack conclusive evidence of pre-pandemic transmission of a SARS-like virus. Our findings provide impetus for the adoption of a One Health Initiative focusing on infectious disease surveillance of multiple animal species to predict the next zoonotic transmission to humans and future pandemics. Structure Can Predict Function in the Human Brain: A Graph Neural Network Deep Learning Model of Functional Connectivity and Centrality Based on Structural Connectivity Although functional connectivity and associated graph theory measures (e.g., centrality; how centrally important to the network a region is) are widely used in brain research, the full extent to which these functional measures are related to the underlying structural connectivity is not yet fully understood. Graph neural network deep learning methods have not yet been applied for this purpose, and offer an ideal model architecture for working with connectivity data given their ability to capture and maintain inherent network structure. This model applied here to predict functional connectivity and centrality from structural connectivity accounted for 89% of the variance in mean functional connectivity, 56% of the variance in individual-level functional connectivity, 99% of the variance in mean functional centrality, and 81% of the variance in individual-level functional centrality. This model provides a new benchmark for performance and represents a novel finding that functional centrality can be robustly predicted from structural connectivity. Regions of particular importance to the models performance as determined through lesioning are discussed, whereby regions with higher centrality have a higher impact on model performance. Future research on models of patient, demographic, or behavioural data can also benefit from this graph neural network method as it is ideally-suited for capturing connectivity and centrality in brain networks. These results have set a new benchmark for prediction of functional connectivity from structural connectivity, and models like this may ultimately lead to a way to predict functional connectivity in individuals who are unable to do fMRI tasks (e.g., non-responsive patients). Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Fatal COVID-19 ARDS associated with incomplete AEC1 differentiation from the transitional state without senescence or fibrosis ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. Cryptic fertility costs of viral infection in a model social insect Declining insect populations emphasize the importance of understanding the drivers underlying reductions in insect fitness. Here, we investigated viruses as a threat to social insect reproduction, using honey bees as a model species. We report that in a sample of N = 93 honey bee (Apis mellifera) queens from nine beekeeping operations across a wide geographic range, high levels of natural viral infection are associated with decreased ovary mass. We confirmed this finding in an independent sample of N = 54 queens. Failed (poor quality) queens displayed higher levels of viral infection, reduced sperm viability, smaller ovaries, and altered ovary protein composition compared to healthy queens. We experimentally infected queens with Israeli acute paralysis virus (IAPV) and found that the ovary masses of IAPV-injected queens were significantly smaller than control queens, demonstrating a causal relationship between viral infection and ovary size. Queens injected with IAPV also had significantly lower expression of vitellogenin, the main source of nutrition deposited into developing oocytes, and higher levels of heat-shock proteins (HSPs), which are part of the honey bees antiviral response. This work together shows that viral infections occurring naturally in the field are compromising queen reproductive success. On Periodic Gene Expression in Budding Yeast Metabolic oscillation percolate throughout cellular physiology. The transcriptome oscillates between gene cohorts encoding for biosynthesis and growth, and for catabolism and stress response. However, long protein half-lives dampen effects on protein abundance, and the function of periodic transcription remains elusive. To test three prevailing hypotheses, we performed RNA-seq analysis during a dynamic state of the system, just preceding a bifurcation of system dynamics to a longer period. A few enzymes with short protein half-live and high transcript abundance amplitude could play a direct role in metabolic dynamics (hypothesis H1), e.g., carbonic anhydrase, sulfate uptake and the glyoxylate cycle. Substantial changes in the relative duration of expression of the antagonistic cohorts precede the bifurcation, supporting the idea of a function in cellular resource allocation (H2). The pulse-width modulation model, a mathematical formulation of this idea, explains the dependence of the cycle period on the culture growth rate. This pulse-like model of cell growth provides a first theoretical framework, where the phenomenon is understood as a mechanism of cellular resource allocation and protein homeostasis. The universal temporal program of transcription encodes the spatial structure of the cell, and we further suggest a function in pattern formation of the growing cell (H3). Reconstitution of 3'-processing of mammalian pre-mRNA reveals a central role of RBBP6 The 3 ends of almost all eukaryotic mRNAs are generated in an essential two-step processing reaction, endonucleolytic cleavage of an extended precursor followed by the addition of a poly(A) tail. By reconstituting the reaction from overproduced and purified proteins, we provide a minimal list of fourteen polypeptides essential and two stimulatory for RNA processing. In a reaction depending on the polyadenylation signal AAUAAA, the reconstituted system cleaves pre-mRNA at a single preferred site corresponding to the one used in vivo. Among the proteins, Cleavage Factor I stimulates cleavage but is not essential, consistent with its prominent role in alternative polyadenylation. RBBP6 is required, structural data showing it to contact and presumably activate the endonuclease CPSF73 through its DWNN domain. The C-terminal domain of RNA polymerase II is dispensable. ATP, but not its hydrolysis, supports RNA cleavage by binding to the hClp1 subunit of cleavage factor II with submicromolar affinity. Vectofusin-1 based T-cell transduction approach for generating murine chimeric antigen receptor T-cells for cancer. Gene transfer into human and murine T-cells using viral-based approaches has several promising therapeutic applications including the production of chimeric antigen receptor T-cell (CAR-T) therapy. The generation of murine CAR-T is paramount to test and validate immunocompetent mouse models for CAR-T therapy. Several viral transduction enhancers already exist for gene therapy with few limitations. In this study, we tested vectofusin-1, a short cationic peptide, as a soluble transduction enhancer for gammaretroviral transduction for the generation of anti-CD19 murine CAR-T. We found that in comparison to Retronectin, Vectofusin-1 is an equally optimal transduction enhancer for the generation of murine CAR-T cells. Trade-offs in biosensor optimization for dynamic pathway engineering Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to their ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design and calibration of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature, and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy and pharmaceutical sectors. First evidence of in vitro cytotoxic effects of marine microlitter on Merluccius merluccius and Mullus barbatus, two Mediterranean commercial fish species Marine litter is composed mainly of plastics and is recognized as a serious threats to marine ecosystems. Ecotoxicological approaches have started elucidating the potential severity of microplastics (MPs) in controlled laboratory studies with pristine materials but no information exist on marine environmental microlitter as a whole. Here, we characterized the litter in the coastal Northern Tyrrhenian sea and in the stomach of two fish species of socio-economic importance, and exposed primary cell cultures of mucosal and lymphoid organs to marine microlitter for evaluating possible cytotoxic effects. An average of 0.30 {+/-} 0.02 microlitter items m-3 was found in water samples. FT-IR analysis revealed that plastic particles, namely HDPE, polyamide and polypropylene were present in 100% and 83.3% of Merluccius merluccius and Mullus barbatus analyzed, which overall ingested 14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual, respectively. Moreover, microlitter was confirmed as a vector of microorganisms. Lastly, the apical end-point of viability was found to be significantly reduced in splenic cells exposed in vitro to two microlitter conditions. Considering the role of the spleen in the mounting of adaptive immune responses, our results warrant more in-depth investigations for clarifying the actual susceptibility of these two species to anthropogenic microlitter.

HighlightsO_LI0.30 {+/-} 0.02 microlitter items m-3 were found at the surface of coastal Northern Tyrrhenian sea
C_LIO_LI14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual were retrieved from the stomach of hakes and mullets
C_LIO_LIThe ingested microlitter contained plastic items
C_LIO_LIMicrolitter was validated as a carrier of bacteria, fungi and flagellates
C_LIO_LISplenic cells exposed to two microlitter conditions for 72 hours suffered cytotoxicity
C_LI Modular evolution of secretion systems and virulence plasmids in a bacterial species complex BackgroundMany bacterial taxa are species complexes and uncertainties regarding the organization of their genetic diversity challenge research efforts. We utilized Agrobacterium tumefaciens, a taxon known for its phytopathogenicity and applications in transformation, as a study system and devised strategies for investigating genome diversity and evolution of species complexes.

ResultsWe utilized 35 genome assemblies to achieve a comprehensive and balanced sampling of A. tumefaciens. Our confident inference of gene content and core-genome phylogeny supported a quantitative guideline for delineating 12 species and allowed for robust investigations of genes critical in fitness and ecology. For the type VI secretion system (T6SS) involved in interbacterial competition and thought to be conserved, we detected multiple losses and one horizontal gene transfer. For the tumor-inducing plasmids (pTi) and pTi-encoded type IV secretion system (T4SS) that are essential for agrobacterial phytopathogenicity, we uncovered novel diversity and hypothesized their involvement in shaping this species complex. Intriguingly, for both T6SS and T4SS, genes encoding structural components are highly conserved, whereas extensive diversity exists for genes encoding effectors and other proteins.

ConclusionsWe demonstrated that the combination of a phylogeny-guided sampling scheme and an emphasis on high-quality assemblies provides a cost-effective approach for robust analysis in evolutionary genomics. Our strategies for multi-level investigations at scales that range from whole-genomes to intragenic domains and phylogenetic depths of between- and within-species are applicable to other bacteria. Finally, modularity observed in the molecular evolution of genes and domains is useful for inferring functional constraints and informing experimental works. 3D Reconstruction of Bird Flight Trajectories Using a Single Video Camera Video cameras are finding increasing use in the study and analysis of bird flight over short ranges. However, reconstruction of flight trajectories in three dimensions typically requires the use of multiple cameras and elaborate calibration procedures. We present an alternative approach that uses a single video camera and a simple calibration procedure for the reconstruction of such trajectories. The technique combines prior knowledge of the wingspan of the bird with a camera calibration procedure that needs to be used only once in the lifetime of the system. The system delivers the exact 3D coordinates of the position of the bird at the time of every full wing extension and uses interpolated height estimates to compute the 3D positions of the bird in the video frames between successive wing extensions. The system is inexpensive, compact and portable, and can be easily deployed in the laboratory as well as the field.