bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blockade of Interleukin Seventeen (IL-17A) with Secukinumab in Hospitalized COVID-19 patients – the BISHOP study
Authors: Resende Gustavo Gomes , da Cruz Lage Ricardo , Lobê Samara Quadros , Medeiros Amanda Fonseca , Costa e Silva Alessandra Dias , Nogueira Sá Antônio Tolentino , Oliveira Argenil José de Assis , Sousa Denise , Guimarães Henrique Cerqueira , Gomes Isabella Coelho , Souza Renan Pedra , Aguiar Renato Santana , Tunala Roberto , Forestiero Francisco , Bueno Filho Julio Silvio Souza , Teixeira Mauro Martins 
Published: July 2021

ABSTRACTBackgroundPatients with severe COVID-19 seem to have a compromised antiviral response and hyperinflammation. Neutrophils are critical players in COVID-19 pathogenesis. IL-17A plays a major role in protection against extracellular pathogens and neutrophil attraction and activation. We hypothesized that secukinumab, an anti-IL17A monoclonal antibody, could mitigate the deleterious hyperinflammation in COVID-19.MethodsBISHOP was an open-label, single-center, phase-II controlled trial. Fifty adults hospitalized Covid-19 patients, confirmed by a positive SARS-CoV-2 RT-PCR, were randomized 1:1 to receive 300mg of secukinumab subcutaneously at day-0 (group A) plus standard of care (SoC: antiviral drugs, antimicrobials, corticosteroids, and/or anticoagulants) or SoC alone (group B). A second dose of 300mg of secukinumab could be administered on day-7, according to staff judgment. The primary endpoint was ventilator-free days at day-28 (VFD-28). Secondary efficacy and safety outcomes were also explored.FindingsAn intention-to-treat analysis showed no difference in VFD-28: 23.7 (95%CI 19.6-27.8) in group A vs. 23.8 (19.9-27.6) in group B, p=0.62; There was also no difference in hospitalization time, intensive care unit demand, the incidence of circulatory shock, acute kidney injury, fungal or bacterial co-infections, and severe adverse events. Pulmonary thromboembolism was less frequent in group A (4.2% vs. 26.2% p=0.04). There was one death in each group. Viral clearance, defined by the viral load fold change (2-ΔΔCT) in upper airways, between day-0 and day-7, was also similar: 0.17 (0.05-0.56) in group A vs. 0.24 (0.10-0.57) in group B.InterpretationThe efficacy of secukinumab in the treatment of Covid19 was not demonstrated. No difference between groups in adverse events and no unexpected events were observed.FundingNovartis Brazil supported this research providing expert input in the development of the project, drug supply, data management, and monitoring.
Optical manipulations reveal strong reciprocal inhibition but limited recurrent excitation within olfactory bulb glomeruli
Authors: Zak Joseph D. , Schoppa Nathan E. 
Published: July 2021

AbstractThe local circuitry within olfactory bulb glomeruli filters, transforms, and facilitates information transfer from olfactory sensory neurons to bulb output neurons. Two key elements of this circuit are glutamatergic tufted cells (TCs) and GABAergic periglomerular (PG) cells, both of which actively shape mitral cell activity and bulb output. A subtype of TCs, the external tufted cells (eTCs), can synaptically excite PG cells, but there are unresolved questions about other aspects of the glomerular connections, including the extent of connectivity between eTCs and the precise nature of reciprocal interactions between eTCs and PG cells. We combined patch-clamp recordings in OB slices and optophysiological tools to investigate local functional connections within glomeruli. When TCs were optically suppressed, we found a large decrease in excitatory post-synaptic currents (EPSCs) in “uniglomerular” PG cells that extend dendrites to one glomerulus, indicating that TC activation was required for most excitation of these PG cells. However, TC suppression had no effect on EPSCs in eTCs, arguing that TCs make few, if any, direct excitatory synaptic connections onto eTCs. The absence of synaptic connections between eTCs was also supported by recordings in eTC pairs. Lastly, we show using similar optical suppression methods that PG cells that express GAD65, mainly uniglomerular PG cells, provide strong inhibition onto eTCs. Our results indicate that the local network of TCs form potent reciprocal synaptic connections with GAD65-expressing uniglomerular PG cells but not other TCs. This configuration favors local inhibition over recurrent excitation within a glomerulus, limiting information transfer to downstream cortical regions.
Evolutionary tuning of a key helix drove androgen selectivity
Authors: Denise Okafor C. , Colucci Jennifer K. , Cato Michael L. , Khan Sabab H. , Cottrill Kirsten , Hercules David , Eick Geeta N. , Thornton Joseph W. , Ortlund Eric A. 
Published: July 2021

AbstractThe genetic and biophysical mechanisms by which new protein functions evolve are central concerns in evolutionary biology and molecular evolution. Despite much speculation, we know little about how protein function evolves. Here, we use ancestral proteins to trace the evolutionary history of ligand recognition in a sub-class of steroid receptors (SRs), an ancient family of ligand-regulated transcription factors that enable long-range cellular communication central to multicellular life. The most ancestral members of this family display promiscuous ligand binding due to their large ligand binding pockets, while more recently evolved SRs tend to have smaller cavities. Less obvious, however, are the forces driving the selectivity of highly similar ligands. A key example is the divergence between the progesterone and androgen receptors (PR, AR), which display a high degree of sequence similarity and yet display differential ligand preferences. This work uses the ancestral steroid receptor 2 (AncSR2), the common ancestor of all 3-ketosteroids and the ancestral androgen receptor 1 (AncAR1), the seminal androgen receptor, to explore the biophysical mechanisms that drove the evolution of androgen specificity. We determine that ligand specificity in androgen receptors is driven by changes in the conformational dynamics of the receptor as well as altered binding pocket interactions, with helix 10 (H10) playing a critical role in tuning ligand specificity.
Functional similarity, not phylogenetic relatedness, predicts the relative strength of competition
Authors: Mahon Michael B. , Jennings David E. , Civitello David J. , Lajeunesse Marc J. , Rohr Jason R. 
Published: July 2021

AbstractPredicting the outcome and strength of species interactions is a central goal of community ecology. Researchers have proposed that outcomes of species interactions (competitive exclusion and coexistence) are a function of both phylogenetic relatedness and functional similarity. Studies relating phylogenetic distance to competition strength have shown conflicting results. Work investigating the role of phylogenetic relatedness and functional similarity in driving competitive outcomes has been limited in terms of the breadth of taxa and ecological contexts examined, which makes the generality of these studies unclear. Consequently, we gathered 1,748 pairwise competition effect sizes from 269 species and 424 unique species pairs with divergence times ranging from 1.14 to 1,275 million years and used meta-regression and model selection approaches to investigate the importance of phylogenetic relatedness and functional similarity to competition across ecological contexts. We revealed that functional similarity, but not phylogenetic relatedness, predicted the relative strength of interspecific competition (defined as the strength of interspecific competition relative to intraspecific competition). Further, we found that the presence of predators, certain habitats, increasing density of competitors, and decreasing spatial grain of experiments were all associated with more intense interspecific competition relative to intraspecific competition. Our results demonstrate that functional similarity, not phylogenetic relatedness, may explain patterns of competition-associated community assembly, highlighting the value of trait-based approaches in clarifying biotic assembly dynamics.
Dichloroacetate improves systemic energy balance and feeding behavior during sepsis
Authors: Oh Tae Seok , Zabalwi Manal , Jain Shalini , Long David , Stacpoole Peter W , McCall Charles E , Quinn Matthew A 
Published: July 2021

AbstractSepsis is a life-threatening organ dysfunction by dysregulated host response to an infection. The metabolic aberrations associated with sepsis underly an acute and organism wide hyper-inflammatory response and multiple organ dysfunction; however, crosstalk between systemic metabolomic alterations and metabolic reprograming at organ levels remains unknown. We analyzed substrate utilization by the respiratory exchange ratio, energy expenditure, metabolomic screening and transcriptional profiling in a cecal ligation and puncture (CLP) model, to show that sepsis increases circulating free fatty acids and acylcarnitines but decreases levels of amino acids and carbohydrates leading to a drastic shift in systemic fuel preference. Comparative analysis of previously published metabolomics from septic liver indicates a positive correlation with hepatic and plasma metabolites during sepsis. In particular, glycine deficiency was a common abnormality of both plasma and the liver during sepsis. Interrogation of the hepatic transcriptome in septic mice suggests that the septic liver may contribute to systemic glycine deficiency by downregulating genes involved in glycine synthesis. Interestingly, intraperitoneal injection of the pyruvate dehydrogenase kinase (PDK) inhibitor dichloroacetate (DCA) reverses sepsis-induced anorexia, energy imbalance, dyslipidemia, hypoglycemia, and glycine deficiency. Collectively, our data indicate that PDK inhibition rescues systemic energy imbalance and metabolic dysfunction in sepsis partly through restoration of hepatic fuel metabolism.
Automated imaging of duckweed growth and development
Authors: Cox Kevin L. , Manchego Jordan , Meyers Blake C. , Czymmek Kirk J. , Harkess Alex 
Published: July 2021

AbstractDuckweeds are some of the smallest angiosperms, possessing a simple body architecture and high rates of biomass accumulation. They can grow near-exponentially via clonal propagation. Understanding their reproductive biology, growth, and development is essential to unlock their potential for phytoremediation, carbon capture, and nutrition. However, there is a lack of non-laborious and convenient methods for spatially and temporally imaging an array of duckweed plants and growth conditions in the same experiment. We developed an automated microscopy approach to record time-lapse images of duckweed plants growing in 12-well cell culture plates. As a proof-of-concept experiment, we grew duckweed on semi-solid media with and without sucrose and monitored its effect on their growth over 3 days. Using the PlantCV toolkit, we quantified the thallus area of individual plantlets over time, and showed thatL. minorgrown on sucrose had an average growth rate four times higher than without sucrose. This method will serve as a blueprint to perform automated high-throughput growth assays for studying the development patterns of duckweeds from different species, genotypes, and conditions.
Patterns of pan-genome occupancy and gene co-expression under water-deficit in Brachypodium distachyon
Authors: Sancho Rubén , Catalán Pilar , Contreras-Moreira Bruno , Juenger Thomas E. , Des Marais David L. 
Published: July 2021

ABSTRACTNatural populations are characterized by abundant genetic diversity driven by a range of different types of mutation. The tractability of sequencing complete genomes has allowed new insights into the variable composition of genomes, summarized as a species pan-genome. These analyses demonstrate that many genes are absent from the first reference genomes, whose analysis dominated the initial years of the genomic era. Our field now turns towards understanding the functional consequence of these highly variable genomes. Here, we analyzed weighted gene co-expression networks from leaf transcriptome data for drought response in the purple false brome Brachypodium distachyon and the differential expression of genes putatively involved in adaptation to this stressor. We specifically asked whether genes with variable “occupancy” in the pan-genome – genes which are either present in all studied genotypes or missing in some genotypes – show different distributions among co-expression modules. Co-expression analysis united genes expressed in drought-stressed plants into nine modules covering 72 hub genes (87 hub isoforms), and genes expressed under controlled water conditions into 13 modules, covering 190 hub genes (251 hub isoforms). We find that low occupancy pan-genes are under-represented among several modules, while other modules are over-enriched for low-occupancy pan-genes. We also provide new insight into the regulation of drought response in B. distachyon, specifically identifying one module with an apparent role in primary metabolism that is strongly responsive to drought. Our work shows the power of integrating pan-genomic analysis with transcriptomic data using factorial experiments to understand the functional genomics of environmental response.
The Amazon River microbiome, a story of humic carbon
Authors: Sylvain François-Étienne , Bouslama Sidki , Holland Aleicia , Leroux Nicolas , Mercier Pierre-Luc , Val Adalberto Luis , Derome Nicolas 
Published: July 2021

AbstractThe Amazon River basin sustains dramatic hydrochemical gradients defined by three water types: white, clear and black waters. Black waters contain important loads of allochthonous humic dissolved organic carbon (DOC), mostly coming from bacteria-mediated lignin degradation, a process that remains understudied. Here, we identified the main bacterial taxa and functions associated with contrasting Amazonian water types, and shed light on their potential implication in the lignin degradation process. We performed an extensive field bacterioplankton sampling campaign from the three Amazonian water types, and combined our observations to a meta-analysis of 90 Amazonian basin shotgun metagenomes used to build a tailored functional inference database. We showed that the overall quality of DOC is a major driver of bacterioplankton structure, transcriptional activity and functional repertory. We also showed that among the taxa mostly associated to differences between water types, Polynucleobacter sinensis particularly stood out, as its abundance and transcriptional activity was strongly correlated to black water environments, and specially to humic DOC concentration. Screening the reference genome of this bacteria, we found genes coding for enzymes implicated in all the main lignin degradation steps, suggesting that this bacteria may play key roles in the carbon cycle processes within the Amazon basin.
ELIMINATOR: Essentiality anaLysIs using MultIsystem Networks And inTeger prOgRamming
Authors: Antoranz Asier , Ortiz María , Pey Jon 
Published: July 2021

AbstractA gene is considered as essential when it is indispensable for cells to grow and replicate under a certain environment. However, gene essentiality is not a structural property but rather a contextual one, which depends on the specific biological conditions affecting the cell. This circumstantial essentiality of genes is what brings the attention of scientist since we can identify genes essential for cancer cells but not essential for healthy cells. This same contextuality makes their identification extremely challenging. Huge experimental efforts such as Project Achilles where the essentiality of thousands of genes is measured in over one thousand cell lines together with a plethora of molecular data (transcriptomics, copy number, mutations, etc.) can shed light on the causality behind the essentiality of a gene in a given environment by associating the measured essentiality to molecular features of the cell line.Here, we present an in-silico method for the identification of patient-specific essential genes using constraint-based modelling (CBM). Our method expands the ideas behind traditional CBM to accommodate multisystem networks, that is a biological network that focuses on complex interactions within several biological systems. In essence, it first calculates the minimum number of non-expressed genes required to be active by the cell to sustain life as defined by a set of requirements; and second, it performs an exhaustive in-silico gene knockout to find those that lead to the need of activating extra non-expressed genes.We validated the proposed methodology using a set of 452 cancer cell lines derived from the Cancer Cell Line Encyclopedia where an exhaustive experimental large-scale gene knockout study using CRISPR (Achilles Project) evaluates the impact of each removal. We also show that the integration of different essentiality predictions per gene, what we called Essentiality Congruity Score, (derived from multiple pathways) reduces the number of false positives. Finally, we explored the gene essentiality predictions for a breast cancer patient dataset, and our results showed high concordance with previous publications.These findings suggest that identifying genes whose activity are fundamental to sustain cellular life in a patient-specific manner is feasible using in-silico methods. The patient-level gene essentiality predictions can pave the way for precision medicine by identifying potential drug targets whose deletion can induce death in tumour cells.
Raptor downregulation rescues neuronal phenotypes in mouse models of Tuberous Sclerosis Complex
Authors: Karalis Vasiliki , Caval-Holme Franklin , Bateup Helen S. 
Published: July 2021

AbstractTuberous Sclerosis Complex (TSC) is a neurodevelopmental disorder caused by mutations in the TSC1 or TSC2 genes, which encode proteins that negatively regulate mTOR complex 1 (mTORC1) signaling. Current treatment strategies focus on mTOR inhibition with rapamycin and its derivatives. While effective at improving some aspects of TSC, chronic rapamycin inhibits both mTORC1 and mTORC2 and is associated with systemic side-effects. It is currently unknown which mTOR complex is most relevant for TSC-related brain phenotypes. Here we used genetic strategies to selectively reduce neuronal mTORC1 or mTORC2 activity in mouse models of TSC. We find that reduction of the mTORC1 component Raptor, but not the mTORC2 component Rictor, rebalanced mTOR signaling in Tsc1 knock-out neurons. Raptor reduction was sufficient to improve several TSC-related phenotypes including neuronal hypertrophy, macrocephaly, impaired myelination, network hyperactivity, and premature mortality. Raptor downregulation represents a promising potential therapeutic intervention for the neurological manifestations of TSC.
Fully automatic segmentation of craniomaxillofacial CT scans for computer-assisted orthognathic surgery planning using the nnU-Net framework
Authors: Dot Gauthier , Schouman Thomas , Dubois Guillaume , Rouch Philippe , Gajny Laurent 
Published: July 2021

ABSTRACTObjectivesTo evaluate the performance of the nnU-Net open-source deep learning framework for automatic multi-task segmentation of craniomaxillofacial (CMF) structures in CT scans obtained for computer-assisted orthognathic surgery.MethodsFour hundred and fifty-three consecutive patients having undergone high-resolution CT scans before orthognathic surgery were randomly distributed among a training/validation cohort (n = 300) and a testing cohort (n = 153). The ground truth segmentations were generated by 2 operators following an industry-certified procedure for use in computer-assisted surgical planning and personalized implant manufacturing. Model performance was assessed by comparing model predictions with ground truth segmentations. Examination of 45 CT scans by an industry expert provided additional evaluation. The model’s generalizability was tested on a publicly available dataset of 10 CT scans with ground truth segmentations of the mandible.ResultsIn the test cohort, mean volumetric Dice Similarity Coefficient (vDSC) & surface Dice Similarity Coefficient at 1mm (sDSC) were 0.96 & 0.97 for the upper skull, 0.94 & 0.98 for the mandible, 0.95 & 0.99 for the upper teeth, 0.94 & 0.99 for the lower teeth and 0.82 & 0.98 for the mandibular canal. Industry expert segmentation approval rates were 93% for the mandible, 89% for the mandibular canal, 82% for the upper skull, 69% for the upper teeth and 58% for the lower teeth.ConclusionWhile additional efforts are required for the segmentation of dental apices, our results demonstrated the model’s reliability in terms of fully automatic segmentation of preoperative orthognathic CT scans.Key points-The nnU-Net deep learning framework can be trained out-of-the-box to provide robust fully automatic multi-task segmentation of CT scans performed for computer-assisted orthognathic surgery planning.-The clinical viability of the trained nnU-Net model is shown on a challenging test dataset of 153 CT scans randomly selected from clinical practice, showing metallic artifacts and diverse anatomical deformities.-Commonly used biomedical segmentation evaluation metrics (volumetric and surface Dice Similarity Coefficient) do not always match industry expert evaluation in the case of more demanding clinical applications.
Air travel-related outbreak of multiple SARS-CoV-2 variants
Authors: Dhanasekaran Vijaykrishna , Edwards Kimberly M , Xie Ruopeng , Gu Haogao , Adam Dillon C , Chang Lydia DJ , Cheuk Sammi SY , Gurung Shreya , Krishnan Pavithra , Ng Daisy YM , Liu Gigi YZ , Wan Carrie KC , Cheng Samuel SM , Tsang Dominic NC , Cowling Benjamin , Peiris Malik , Poon Leo LM 
Published: July 2021

ABSTRACTBackgroundA large cluster of 59 cases were linked to a single flight with 146 passengers from New Delhi to Hong Kong in April 2021. This outbreak coincided with early reports of exponential pandemic growth in New Delhi, which reached a peak of >400,000 newly confirmed cases on 7 May 2021.MethodsEpidemiological information including date of symptom onset, date of positive-sample detection, and travel and contact history for individual cases from this flight were collected. Whole genome sequencing was performed, and sequences were classified based on the dynamic Pango nomenclature system. Maximum-likelihood phylogenetic analysis compared sequences from this flight alongside other cases imported from India to Hong Kong on 26 flights between June 2020 and April 2021, as well as sequences from India or associated with India-related travel from February to April 2021, and 1,217 reference sequences.ResultsSequence analysis identified six lineages of SARS-CoV-2 belonging to two variants of concern (Alpha and Delta) and one variant of public health interest (Kappa) involved in this outbreak. Phylogenetic analysis confirmed at least three independent sub-lineages of Alpha with limited onward transmission, a superspreading event comprising 37 cases of Kappa, and transmission of Delta to only one passenger. Additional analysis of another 26 flights from India to Hong Kong confirmed widespread circulation of all three variants in India since early March 2021.ConclusionsThe broad spectrum of disease severity and long incubation period of SARS-CoV-2 pose a challenge for surveillance and control. As illustrated by this particular outbreak, opportunistic infections of SARS-CoV-2 can occur irrespective of variant lineage, and requiring a nucleic acid test within 72 hours of departure may be insufficient to prevent importation or in-flight transmission.