bluuebunny/crossref_metadata_2025_split huggingface dataset:
When should bees be flower constant? An agent-based model highlights the importance of social information and foraging conditions
Authors: Hayes Lucy , Grüter Christoph 
Published: August 2022

AbstractMany bee species show flower constancy,i.e. a tendency to visit flowers of one type during a foraging trip. Flower constancy is important for plant reproduction, but whether bees also benefit from flower constancy remains unclear. Social bees, which often use communication about food sources, show particularly strong flower constancy.We hypothesised that the sharing of social information increases the benefits of flower constancy because foragers share information selectively about high-quality food sources, thereby reducing the need to sample alternatives. We also asked if foraging landscapes affect flower constancy. We developed an agent-based model that allowed us to simulate bee colonies with and without communication and flower constancy in different foraging environments.Flower constancy alone performed poorly in all environments, while indiscriminate flower choice was often the most successful strategy. However, communication improved the performance of flower constant colonies in nearly all tested environments. This combination was particularly successful when high-quality food sources were abundant and competition was weak.Our findings help explain why social bees tend to be more flower constant than solitary bees and suggest that flower constancy can be an adaptive strategy in social bees. Simulations suggest that anthropogenic changes of foraging landscapes will have different effects on the foraging performance of bees that vary in flower constancy.
An antibody-drug conjugate targeting GPR56 demonstrates efficacy in preclinical models of colorectal cancer
Authors: Jacob Joan , Francisco Liezl E. , Chatterjee Treena , Liang Zhengdong , Subramanian Shraddha , Liu Qingyun J. , Rowe Julie H. , Carmon Kendra S. 
Published: August 2022

AbstractAntibody-drug conjugates (ADCs) have become an increasingly successful class of anticancer therapy, particularly within the past few years. Though ADCs are in clinical trials for colorectal cancer (CRC), a candidate has yet to be approved. CRC continues to be a leading cause of cancer-related death, emphasizing the need to identify novel target antigens for ADC development. GPR56, a member of the 7TM receptor family, is upregulated in colorectal tumors compared to normal tissues and located on the surface of CRC cells, making it a promising ADC target. Furthermore, high GPR56 expression occurs in tumors that are microsatellite stable, negative for the CpG methylator phenotype, and show chromosomal instability. We previously reported the generation of a high affinity GPR56-specific monoclonal antibody, 10C7, and we have now mapped the epitope to the C-terminal end of the extracellular domain, proximal to the GPCR proteolysis site. Here, we describe the development of a duocarmycin-conjugated 10C7 ADC. 10C7 co-internalized with GPR56 and trafficked to the lysosomes of CRC cells, which is critical for efficient ADC payload release. Evaluation of the ADC in a panel of CRC cell lines and tumor organoids with different levels of GPR56 expression showed the ADC selectively induced cytotoxicity at low nanomolar concentrations in a GPR56-dependent manner. A nontargeting control ADC showed minimal to no activity. Furthermore, GPR56 ADC exhibited significant antitumor efficacy against GPR56-expressing patient-derived xenograft models of CRC. This study provides rationale for the development of a GPR56-targeted ADC approach to potentially treat a large fraction of CRC patients.
Spike desensitisation as a mechanism for high-contrast selectivity in retinal ganglion cells
Authors: Chang Le , Ran Yanli , Auferkorte Olivia , Butz Elisabeth , Hüser Laura , Haverkamp Silke , Euler Thomas , Schubert Timm 
Published: August 2022

ABSTRACTIn the vertebrate retina, several dozens of parallel channels relay information about the visual world to the brain. These channels are represented by the different types of retinal ganglion cells (RGCs), whose responses are rendered selective for distinct sets of visual features by various mechanisms. These mechanisms can be roughly grouped into synaptic interactions and cell-intrinsic mechanisms, with the latter including dendritic morphology as well as ion channel complement and distribution. Here, we investigate how strongly ion channel complement can shape RGC output by comparing two mouse RGC types, the well-described ON alpha cell and a little-studied ON cell that is EGFP-labelled in the Igfbp5 mouse line and displays an unusual selectivity for high-contrast stimuli. Using patch-clamp recordings and computational modelling we show that in ON Igfbp5 cells – but not in the ON alpha cells – a higher activation threshold and a pronounced slow inactivation of the voltage-gated Na+ channels are responsible for the distinct contrast tuning and transient responses of ON Igfbp5 RGCs, respectively. This study provides an example for the powerful role that the last stage of retinal processing can play in shaping RGC responses.SIGNIFICANCE STATEMENTHere, we investigated, how voltage-gated sodium channels contribute to shaping the light responses of mouse retinal ganglion cells. Using single-cell electrophysiology and computational modelling, we studied a ganglion cell type that displays highly transient responses and an unusual selectivity for visual high-contrast stimuli. We found that the cell’s characteristic responses were largely determined by intrinsic mechanisms, notably, a high activation threshold and a pronounced slow inactivation of its voltage-gated sodium channels. Therefore, our study demonstrates how sodium channels at the last stage of retinal signal processing can contribute to shape retinal output to higher visual areas the brain; it also adds a rare example for how channel complement can be directly linked to feature selectivity.
Spectral brain signatures of aesthetic natural perception in the alpha and beta frequency bands
Authors: Kaiser Daniel 
Published: August 2022

AbstractDuring our everyday lives, visual beauty is often conveyed by sustained and dynamic visual stimulation, such as when we walk through an enchanting forest or watch our pets playing. Here, I devised an MEG experiment that mimics such situations: Participants viewed 8s videos of everyday situations and rated their beauty. Using multivariate analysis, I linked aesthetic ratings to (1) sustained MEG broadband responses and (2) spectral MEG responses in the alpha and beta frequency bands. These effects were not accounted for by a set of high- and low-level visual descriptors of the videos, suggesting that they are genuinely related to aesthetic perception. My findings provide a first characterization of spectral brain signatures linked to aesthetic experiences in the real world.
Impact of population size on early adaptation in rugged fitness landscapes
Authors: Servajean Richard , Bitbol Anne-Florence 
Published: August 2022

AbstractDue to stochastic fluctuations arising from finite population size, known as genetic drift, the ability of a population to explore a rugged fitness landscape depends on its size. In the weak mutation regime, while the mean steady-state fitness increases with population size, we find that the height of the first fitness peak encountered when starting from a random genotype displays various behaviors versus population size, even among small and simple rugged landscapes. We show that the accessibility of the different fitness peaks is key to determining whether this height overall increases or decreases with population size. Furthermore, there is often a finite population size that maximizes the height of the first fitness peak encountered when starting from a random genotype. This holds across various classes of model rugged landscapes with sparse peaks, and in some experimental and experimentally-inspired ones. Thus, early adaptation in rugged fitness landscapes can be more efficient and predictable for relatively small population sizes than in the large-size limit.
Through the Random Forest: Ontogeny as a study system to connect prediction to explanation
Authors: Simon Sophia , Glaum Paul , Valdovinos Fernanda S. 
Published: August 2022

AbstractAs modeling tools and approaches become more advanced, ecological models are becoming more complex and must be investigated with novel methods of analysis. Machine learning approaches are a powerful toolset for exploring such complexity. While these approaches are powerful, results may suffer from well-known trade-offs between predictive and explanatory power. We employ an empirically rooted ontogenetically stage-structured consumer-resource model to investigate how machine learning can be used as a tool to root model analysis in mechanistic ecological principles. Applying random forest models to model output using simulation parameters as feature inputs, we extended established feature analysis into a simple graphical analysis. We used this graphical analysis to reduce model behavior to a linear function of three ecologically based mechanisms. From this model, we find that stability depends on the interaction between internal plant demographics that control the distribution of plant density across ontogenetic stages and the distribution of consumer pressure across ontogenetic stages. Predicted outcomes from these linear models rival accuracy achieved by our random forests, while explaining results as a function of ecological interactions.
TRIAC disrupts cerebral thyroid hormone action via a negative feedback loop and heterogenous distribution among organs
Authors: Yamauchi Ichiro , Hakata Takuro , Ueda Yohei , Sugawa Taku , Omagari Ryo , Teramoto Yasuo , Nakayama Shoji F , Nakajima Daisuke , Kubo Takuya , Inagaki Nobuya 
Published: August 2022

Abstract3,3’,5-triiodothyroacetic acid (TRIAC) is a metabolite of endogenous thyroid hormones (THs) that can bind to and activate TH receptors. As TRIAC was previously detected in sewage effluent, we aimed to investigate exogenous TRIAC’s potential for endocrine disruption. We administered either TRIAC or 3,3’,5-triiodo-L-thyronine (LT3) to both euthyroid mice and 6-propyl-2-thiouracil-induced hypothyroid mice. In hypothyroid mice, TRIAC alleviated growth retardation, suppressed the hypothalamus-pituitary-thyroid (HPT) axis, and upregulated TH-responsive genes in the pituitary gland, liver, and heart. We observed that, unlike LT3, TRIAC does not upregulate the expression of TH-responsive genes in the cerebrum. Measurement of organ-specific TRIAC levels suggested that TRIAC was not efficiently trafficked into the cerebrum. Furthermore, by analyzing euthyroid mice, we found that cerebral TRIAC levels did not increase despite TRIAC administration at higher concentrations, whereas serum and cerebral TH levels were substantially decreased. Hence, TH-responsive genes in the cerebrum appear to be downregulated by TRIAC. In summary, TRIAC administration decreases circulating TH levels by suppressing the HPT axis, while the consequent attenuation of TH actions was compensated by TRIAC in peripheral tissues but not in the cerebrum due to the relative impermeability of the blood–brain barrier towards TRIAC. We verified that exogenous TRIAC disrupts TH actions in the cerebrum. This disruption is apparently due to the additive effects of circulating endogenous THs being depleted via a negative feedback loop involving the HPT axis and heterogenous distribution of TRIAC among different organs. Our findings indicate that environmental TRIAC poses a potential neurodevelopmental risk.
Unsupervised learning reveals interpretable latent representations for translucency perception
Authors: Liao Chenxi , Sawayama Masataka , Xiao Bei 
Published: August 2022

ABSTRACTHumans constantly assess the appearance of materials to plan actions, such as stepping on icy roads without slipping. Visual inference of materials is challenging because a given material can appear dramatically different in various scenes. This problem especially stands out for translucent materials (e.g., skin, soap), whose appearance strongly depends on lighting, geometry, and viewpoint. Despite this, humans can still distinguish between different materials, and it remains unsolved how to systematically discover visual features pertinent to material inference. Here, we developed an unsupervised style-based image generation model to identify perceptually relevant dimensions for material appearances from natural photographs. We find the model can synthesize images of convincing material appearances. Importantly, without supervision, human-understandable scene attributes, including object’s shape, material, and body color, spontaneously emerge in the model’s layer-wise latent space in a scale-specific manner. Crucially, the middle-layers of the latent space selectively encode translucency features correlated with perception, suggesting that translucent impressions are established in mid-to-low spatial scale features. Our findings indicate that humans may use the scale-specific statistical structure of natural images to efficiently represent material properties across contexts, and our approach is widely applicable in discovering perceptually relevant features from complex stimuli for many visual inference tasks.
The Arabidopsis INNER NO OUTER (INO) gene acts exclusively and quantitatively in regulation of ovule outer integument development
Authors: Skinner Debra J. , Dang Trang , Gasser Charles S. 
Published: August 2022

ABSTRACTThe INNER NO OUTER (INO) gene is essential for formation of the outer integument of ovules in Arabidopsis thaliana. Initially described lesions in INO were missense mutations resulting in aberrant mRNA splicing. To determine the null mutant phenotype we used CRISPR to induce frame-shift mutations and found, in confirmation of results on another recently identified frame-shift mutation (Vijayan et al., 2021), that such mutants have a phenotype identical to the most severe splicing mutant (ino-1), with effects specific to outer integument development. We show that the altered protein of an ino mRNA splicing mutant with a less severe phenotype (ino-4) does not have INO activity, and the mutant is partial because it produces a small amount of correctly spliced INO mRNA. Screening for suppressors of ino-4 in a fast-neutron mutagenized population identified a genetic duplication of the ino-4 gene leading to an increase in the amount of this mRNA. The increased expression led to a decrease in the severity of the mutant effects, indicating that the amount of INO activity quantitatively regulates outer integument growth. The results further confirm that the role of INO in Arabidopsis development is specific to the outer integument of ovules where it quantitatively affects the growth of this structure.
Evolutionary dynamics of genome size and content during the adaptive radiation of Heliconiini butterflies
Authors: Cicconardi Francesco , Milanetti Edoardo , de Castro Erika C. Pinheiro , Mazo-Vargas Anyi , Van Belleghem Steven M. , Ruggieri Angelo Alberto , Rastas Pasi , Hanly Joseph , Evans Elizabeth , Jiggins Chris D , McMillan W Owen , Papa Riccardo , Di Marino Daniele , Martin Arnaud , Montgomery Stephen H 
Published: August 2022

AbstractHeliconiusbutterflies, a speciose genus of Müllerian mimics, represent a classic example of an adaptive radiation that includes a range of derived dietary, life history, physiological and neural traits. However, key lineages within the genus, and across the broader Heliconiini tribe, lack genomic resources, limiting our understanding of how adaptive and neutral processes shaped genome evolution during their radiation. We have generated highly contiguous genome assemblies for nine new Heliconiini, 29 additional reference-assembled genomes, and improve 10 existing assemblies. Altogether, we provide a major new dataset of annotated genomes for a total of 63 species, including 58 species within the Heliconiini tribe. We use this extensive dataset to generate a robust and dated heliconiine phylogeny, describe major patterns of introgression, explore the evolution of genome architecture, and the genomic basis of key innovations in this enigmatic group, including an assessment of the evolution of putative regulatory regions at theHeliconiusstem. Our work illustrates how the increased resolution provided by such dense genomic sampling improves our power to generate and test gene-phenotype hypotheses, and precisely characterize how genomes evolve.
The K-mer Antibiotic Resistance Gene Variant Analyzer (KARGVA)
Authors: Marini Simone , Boucher Christina , Noyes Noelle , Prosperi Mattia 
Published: August 2022

AbstractCharacterization of antibiotic resistance genes (ARGs) from high-throughput sequencing data of metagenomics and cultured bacterial samples is a challenging task, with the need to account for both computational (e.g., string algorithms) and biological (e.g., gene transfers, rearrangements) aspects. Curated ARG databases exist together with assorted ARG classification approaches (e.g., database alignment, machine learning). Besides ARGs that naturally occur in bacterial strains or are acquired through mobile elements, there are chromosomal genes that can render a bacterium resistant to antibiotics through point mutations, i.e., ARG variants (ARGVs). While ARG repositories also collect ARGVs, there are only a few tools that are able to identify ARGVs from metagenomics and high throughput sequencing data, with a number of limitations (e.g., pre-assembly, a posteriori verification of mutations, or specification of species). In this work we present the k-mer, i.e., strings of fixed length k, ARGV analyzer –KARGVA– an open-source, multi-platform tool that provides: (i) an ad hoc, large ARGV database derived from multiple sources; (ii) input capability for various types of high-throughput sequencing data; (iii) a three-way, hash-based, k-mer search setup to process data efficiently, linking k-mers to ARGVs, k-mers to point mutations, and ARGVs to k-mers, respectively; (iv) a statistical filter on sequence classification to reduce type I and II errors. On semi-synthetic data, KARGVA provides very high accuracy even in presence of high sequencing errors or mutations (99.2% and 86.6% accuracy within 1% and 5% base change rates, respectively), and genome rearrangements (98.2% accuracy), with robust performance on ad hoc false positive sets. On data from the worldwide MetaSUB consortium, comprising 3,700+ metagenomics experiments, KARGVA identifies more ARGVs than Resistance Gene Identifier (4.8x) and PointFinder (6.8x), yet all predictions are below the expected false positive estimates. The prevalence of ARGVs is correlated to ARGs but ecological characteristics do not explain well ARGV variance. KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.
Development and validation of PainFace, a software platform that simplifies and standardizes mouse grimace analyses
Authors: McCoy Eric S. , Park Sang Kyoon , Patel Rahul P. , Ryan Dan F. , Mullen Zachary J. , Nesbitt Jacob J. , Lopez Josh E. , Taylor-Blake Bonnie , Krantz James L. , Hu Wenxin , Garris Rosanna L. , Lima Lucas V. , Sotocinal Susana G. , Austin Jean-Sebastien , Kashlan Adam D. , Jimenez Jessica A. , Shah Sanya , Trocinski Abigail K. , Vanden Kelly A. , Major Rami M. , Bazick Hannah O. , Klein Morgan R. , Mogil Jeffrey S. , Wu Guorong , Zylka Mark J. 
Published: August 2022

AbstractFacial grimaces are now commonly used to quantify spontaneous pain in mice and other mammalian species, but scoring remains subjective and relies on humans with very different levels of proficiency. Here, we developed a Mouse Grimace Scale (MGS) for black-coated (C57BL/6) mice consisting of four facial action units (orbitals, nose, ears, whiskers). We used this scale to generate ground truth data from over 70,000 images of black mice in different settings. With this large data set, we developed a deep neural network and cloud-based software platform called PainFace (http://painface.net) that accurately scores facial grimaces of black mice on a 0–8 scale. PainFace generates over two orders of magnitude more MGS data than humans can realistically achieve, and at superhuman speed. By analyzing the frequency distribution of grimace scores, we found that mice spent >7x more time in a high grimace state following laparotomy surgery relative to sham surgery controls. The analgesic carprofen reduced the amount of time animals spent in this high grimace state after surgery. Specific facial action unit score combinations were overrepresented following laparotomy surgery, suggesting that characteristic facial expressions are associated with a high grimace state. We performed validation experiments in two labs located in different countries to demonstrate reproducibility of the PainFace platform. To further enhance rigor and reproducibility, we will invite pain researchers to beta test PainFace and then incorporate their feedback into the software and manuscript prior to peer review. While this study is focused on mice, PainFace was designed to simplify, standardize, and scale up grimace analyses with many other mammalian species, including humans.
Parasitoid pressures and silence evolution
Authors: Suswaram Megha R. , Yeakel Justin D. , Gokhale Chaitanya S. 
Published: August 2022

AbstractAcoustic signals used by organisms to attract mates are known to attract parasitoid flies. The parasitoid flies lay their eggs inside the host signaler, eventually killing the host. We build a host-parasitoid acoustic model to investigate the effect of parasitoid flies on the signalling host’s eco-evolutionary dynamics. We used field crickets as a system to build the framework of the model. We explore how the sex ratio and the female parasitoid fecundity impact the evolution of the acoustic signal and population density of the signalling hosts. We also explore the stability of the host populations with an increase in parasitoid load. We find that up to a threshold value, an increase in parasitoid load leads to a thriving yet silent host population. Consistent with field observations, we show how this emergence of silence as an evolutionary strategy is immediate. Our results show that a drastic increase in the parasitoid load can rapidly push the signalling host population towards instability and extinction.