bluuebunny/crossref_metadata_2025 huggingface dataset:
Alcohol-specific transcriptional dynamics of memory reconsolidation
Authors: Goltseker Koral , Garay Patricia , Iwase Shigeki , Barak Segev
Published: June 2022

Relapse, a critical issue in alcohol addiction, can be attenuated by disruption of alcohol-associated memories. Memories are thought to temporarily destabilize upon retrieval during the reconsolidation process. Here, we characterized the alcohol-specific transcriptional dynamics that regulate these memories. Using a mouse place-conditioning procedure, we found that alcohol memory retrieval increased the expression ofArcandZif268in the dorsal hippocampus (DH) and medial prefrontal cortex (mPFC). Alcohol seeking was abolished by post-retrieval non-specific inhibition of gene transcription in the DH, as well as by downregulating ARC expression in the DH using antisense-oligodeoxynucleotides. Since sucrose memory retrieval also increasedArcandZif268expression, we performed an RNA-sequencing assay, and revealed alterations in the expression ofAdcy8, Neto1, Slc8a3in the DH andFkbp5in the mPFC, caused by the retrieval of alcohol but not sucrose memories. This offers a first insight into the unique transcriptional dynamics underpinning alcohol memory reconsolidation.
Medulloblastoma Group 3 and 4 Tumors Comprise a Clinically and Biologically Significant Expression Continuum Reflecting Human Cerebellar Development
Authors: Williamson Daniel , Schwalbe Edward C , Hicks Debbie , Aldinger Kimberly A , Lindsey Janet C , Crosier Stephen , Richardson Stacey , Goddard Jack , Hill Rebecca M , Castle Jemma , Grabovska Yura , Hacking James , Pizer Barry , Wharton Stephen B , Jacques Thomas S , Joshi Abhijit , Bailey Simon , Clifford Steven C
Published: June 2022

Medulloblastoma is currently sub-classified into distinct DNA methylation subgroups/subtypes with particular clinico-molecular features. Using RNA-seq in large well annotated cohorts of medulloblastoma we show that transcriptionally Group3 and Group4 medulloblastomas exist not as discrete types but as intermediates on a bipolar continuum between archetypal Group3 and Group4 entities. Continuum position is prognostic, reflects propensity for specific DNA copy-number changes, key switches in isoform/enhancer usage and RNA-editing. Examining scRNA-seq profiles we show intra-tumoral transcriptional heterogeneity along the continuum is limited in a subtype-dependent manner. By integrating with a human scRNA-seq reference atlas we show this continuum is mirrored by an equivalent continuum of transcriptional cell types in early fetal cerebellar development. We identify unique developmental niches for all four major subgroups and link each to a common developmental antecedent. Our findings show a transcriptional continuum arising from oncogenic disruption of highly specific fetal cerebellar cell types, linked to almost every aspect of Group3/Group4 molecular biology and clinico-pathology.
Collective Evolution Learning Model for Vision-Based Collective Motion with Collision Avoidance
Authors: Krongauz David L. , Lazebnik Teddy
Published: June 2022

Collective motion (CM) takes many forms in nature; schools of fish, flocks of birds, and swarms of locusts to name a few. Commonly, during CM the individuals of the group avoid collisions. These CM and collision avoidance (CA) behaviors are based on input from the environment such as smell, air pressure, and vision, all of which are processed by the individual and defined action. In this work, a novel vision-based CM with CA model (i.e., VCMCA) simulating the collective evolution learning process is proposed. In this setting, a learning agent obtains a visual signal about its environment, and throughout trial-and-error over multiple attempts, the individual learns to perform a local CM with CA which emerges into a global CM with CA dynamics. The proposed algorithm was evaluated in the case of locusts’ swarms, showing the evolution of these behaviors in a swarm from the learning process of the individual in the swarm. Thus, this work proposes a biologically-inspired learning process to obtain multi-agent multi-objective dynamics.

Author summary

Multi-agent multi-objective tasks are common in nature with examples as collective movement in birds and economic management in humans. These problems are famous for being convoluted to efficiently solve. Nonetheless, nature has been successfully solving it for millennials using an evolution strategy. A prominent example is a task of flocking performed by multiple species, which involves both collective motion and collision avoidance. In our work, we simulate agents that are able to learn behaviors on the individual level, that in turn translate into the desired group (multi-agent) behavior. Using nature-inspired genetic algorithms and reinforcement-learning methods, the agents are successfully implementing a collective behavior similar to the one encountered in nature.
A low-cost device for cryoanesthesia of neonatal rodents
Authors: Jamieson Bradley B. , Cano-Ferrer Xavier , Konstantinou George , de Launoit Elisa , Renier Nicolas , Imbert Albane , Kohl Johannes
Published: June 2022

Studying the development of neural circuits in rodent models requires surgical access to the neonatal brain. Since commercially available stereotaxic and anesthetic equipment is designed for use in adults, reliable targeting of brain structures in such young animals can be challenging. Hypothermic cooling (cryoanesthesia) has been used as a preferred anesthesia approach in neonates. This commonly involves submerging neonates in ice, an approach that is poorly controllable. We have developed an affordable, simple to construct device – CryoPup – that allows for fast and robust cryoanesthesia of rodent pups. CryoPup consists of a microcontroller controlling a Peltier element and a heat exchanger. It is capable of both cooling and heating, thereby also functioning as a heating pad during recovery. Importantly, it has been designed for size compatibility with common stereotaxic frames. We validate CryoPup in neonatal mice, demonstrating that it allows for rapid, reliable and safe cryoanesthesia and subsequent recovery. This open-source device will facilitate future studies into the development of neural circuits in the postnatal brain.

Specifications table
A dual gene-specific mutator system installs all transition mutations at similar rates in vivo
Authors: Seo Daeje , Eom Ga-eul , Kim Hye Won , Kim Seokhee
Published: June 2022

Targeted in vivo hypermutation accelerates directed evolution of proteins through concurrent DNA diversification and selection. Among recently developed methods, the systems employing a fusion protein of a nucleobase deaminase and T7 RNA polymerase present gene-specific targeting. However, their mutational spectra have been largely limited to exclusive or dominant C:G→T:A mutations. Here we describe eMutaT7transition, a new gene-specific mutator system, that installs all the transition mutations (C:G→T:A and A:T→G:C) at comparable rates. By using two mutator proteins in which two efficient deaminases, PmCDA1 and TadA-8e, are separately fused to T7 RNA polymerase, we obtained similar numbers of C:G→T:A and A:T→G:C mutations at a sufficiently high rate (∼3.4 × 10-5 mutations per base per generation or ∼1.3 mutations per 1 kb per day). Through eMutaT7transition-mediated TEM-1 evolution for antibiotic resistance, we generated many mutations also found in clinical isolates. Overall, with a fast mutation rate and wider mutational spectrum, eMutaT7transition is a potential first-line method for gene-specific in vivo hypermutation.
Nanobody-mediated Complement Activation to Kill HIV-infected Cells
Authors: Pedersen Maria Lange , Pedersen Dennis Vestergaard , Lykkegaard Winkler Mikael Becher , Olesen Heidi Gytz , Søgaard Ole Schmeltz , Østergaard Lars , Laursen Nick Stub , Andersen Anna Halling Folkmar , Tolstrup Martin
Published: June 2022

The complement system which is part of the innate immune response against invading pathogens, represents a powerful mechanism for killing of infected cells. Utilizing direct complement recruitment for complement-mediated elimination of HIV-1-infected cells is underexplored. We developed a novel therapeutic modality to direct complement activity to the surface of HIV-1-infected cells. This bispecific complement engager (BiCE) is comprised of a nanobody recruiting the complement-initiating protein C1q, and single-chain variable fragments of broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope (Env) protein. Here, we show that two anti-HIV BiCEs targeting the V3 loop and the CD4 binding site, respectively, increase C3 deposition and mediate complement-dependent cytotoxicity (CDC) of HIV-1 Env expressing Raji cells. Furthermore, anti-HIV BiCEs trigger complement activation on primary CD4 T cells infected with laboratory-adapted HIV-1 strain and facilitates elimination of HIV-1-infected cells over time. In summary, we present a novel approach to direct complement deposition to the surface of HIV-1-infected cells leading to complement-mediated killing of these cells.
New functional vessels form after spinal cord injury in zebrafish
Authors: Ribeiro Ana , da Costa Mariana Rebocho , de Sena-Tomás Carmen , Rodrigues Elsa Charas , Quitéria Raquel , Maçarico Tiago , Rosa Santos Susana Constantino , Saúde Leonor
Published: June 2022

The vascular system is inefficiently repaired after spinal cord injury in mammals, resulting in secondary tissue damage and immune deregulation that contribute to the limited functional recovery. Unlike mammals, zebrafish can repair the spinal cord and restore motility, but the vascular response to injury has not been investigated. Here we describe the zebrafish spinal cord vasculature, from the body size-dependent vessel ingression during development to the stereotypic vessel organization and barrier specialisation in adulthood. After injury, vessels rapidly regrow into the lesion, preceding the glial bridge and regenerating axons. The initial vascularisation of the injured tissue is done by dysmorphic and leaky vessels. Dysfunctional vessels are later removed, as pericytes are recruited and the blood-spinal cord barrier is re-established. Vascular repair involves an early burst of angiogenesis, likely in response to pro-angiogenic factors detected in the injured spinal cord, including the Vegf pathway. However, the inhibition of the Vegfr2 using genetic and pharmacological methods was not able to efficiently block the formation of new blood vessels, suggesting that other signalling pathways are also involved in this process. This study demonstrates that zebrafish can successfully re-vascularise the spinal tissue, reinforcing the value of this organism as a regenerative model for spinal cord injury.
An atlas of spider development at single-cell resolution provides new insights into arthropod embryogenesis
Authors: Leite Daniel J. , Schönauer Anna , Blakeley Grace , Harper Amber , Garcia-Castro Helena , Baudouin-Gonzalez Luis , Wang Ruixun , Sarkis Naïra , Nikola Alexander Günther , Koka Venkata Sai Poojitha , Kenny Nathan J. , Turetzek Natascha , Pechmann Matthias , Solana Jordi , McGregor Alistair P.
Published: June 2022

Spiders are a diverse order of chelicerates that diverged from other arthropods over 500 million years ago. Research on spider embryogenesis, particular studies using the common house spiderParasteatoda tepidariorum, has made important contributions to understanding the evolution of animal development, including axis formation, segmentation, and patterning. However, we lack knowledge about the cells that build spider embryos, their gene expression profiles and fate. Single-cell transcriptomic analyses have been revolutionary in describing these complex landscapes of cellular genetics in a range of animals. Therefore, we carried out single-cell RNA sequencing ofP. tepidariorumembryos at stages 7, 8 and 9, which encompass the establishment and patterning of the body plan, and initial differentiation of many tissues and organs. We identified 20 cell clusters, from 18.5k cells, which were marked by many developmental toolkit genes, as well as a plethora of genes not previously investigated. There were differences in the cell cycle transcriptional signatures, suggestive of different proliferation dynamics, which related to distinctions between endodermal and some mesodermal clusters, compared with ectodermal clusters. We found many Hox genes were markers of cell clusters, and Hox gene ohnologs often were present in different clusters. This provided additional evidence of sub- and/or neo-functionalisation of these important developmental genes after the whole genome duplication in the arachnopulmonate ancestor (spiders, scorpions, and allies). We also examined the spatial expression of marker genes for each cluster to generate a comprehensive cell atlas of these embryonic stages. This revealed new insights into the cellular basis and genetic regulation of head patterning, hematopoiesis, limb development, gut development, and posterior segmentation. This atlas will serve as a platform for future analysis of spider cell specification and fate, and studying the evolution of these processes among animals at cellular resolution.
Doing what’s not wanted: conflict in incentives and misallocation of behavioural control lead to drug-seeking despite adverse outcomes
Authors: Mahajan Pranav , Baths Veeky , Gutkin Boris
Published: June 2022

Despite being aware of negative consequences and wanting to quit, long-term addicts find it difficult to quit seeking and consuming drugs. This inconsistency between the (often compulsive) behavioural patterns and the explicit knowledge of negative consequences represents a cognitive conflict which is a central characteristic of addiction. Neurobiologically, differential cue-induced activity in distinct striatal subregions, as well as the dopamine connectivity spiraling from ventral striatal regions to the dorsal regions, play critical roles in compulsive drug seeking. The focus of this work is to illustrate the mechanisms that lead to a cognitive conflict and it’s impact on actions taken i.e. addictive choices. We propose an algorithmic model that captures how the action choices that the agent makes when reinforced with drug-rewards become incongruent with the presence of negative consequences that often follow those choices. We advance the understanding of having a decision hierarchy in representing “cognitive control” and how lack of such control at higher-level in the hierarchy could potentially lead to consolidated drug-seeking habits. We further propose a cost-benefit based arbitration scheme, which mediates the allocation of control across different levels of the decision-making hierarchy. Lastly, we discuss how our work on extending a computational model to an algorithmic one, could in turn also helps us improve the understanding of how drugs hijack the dopamine-spiralling circuit at an implementation level.
A plausible identifiable model of the canonical NF-κB signaling pathway
Authors: Jaruszewicz-Błońska Joanna , Kosiuk Ilona , Prus Wiktor , Lipniacki Tomasz
Published: June 2022

An overwhelming majority of mathematical models of regulatory pathways, including intensively studied NF-κB pathway, remains non-identifiable meaning that their parameters may not be determined by existing data. The existing NF-κB models that are capable to reproduce experimental data, contain non-identifiable parameters, while simplified models with a smaller number of parameters exhibit dynamics that significantly differs from that observed in experiments. Here, we reduce an existing model of the canonical NF-κB pathway by decreasing the number of equations from 15 to 6 in a way that the resulting model exhibits dynamics closely following that of the original model, both for the nominal and the randomly selected parameters. We carried out the sensitivity-based linear analysis and Monte Carlo-based analysis to demonstrate that the resulting model is structurally and practically identifiable based on a simple TNF stimulation protocol in which 5 model variables are measured. The reduced model is capable to reproduce different types of responses characteristic to regulatory motives controlled by negative feedback loops: nearly-perfect adaptation, damped and sustained oscillations. It can serve as a building block of more comprehensive models of immune responses and cancer, where NF-κB plays a decisive role. Our approach, although may not be automatically generalized, suggests that other regulatory pathways models can be transformed to identifiable, while retaining their dynamical features.
Regulation of Aortic Morphogenesis and VE-Cadherin Dynamics by VEGF
Authors: Jadon Julian , Yelin Ronit , Arraf Alaa A. , Asleh Manar Abboud , Zaher Mira , Schultheiss Thomas M.
Published: June 2022

In amniote vertebrates, the definitive dorsal aorta is formed by the side-to-side fusion of two primordial aortic endothelial tubes. Formation of the definitive dorsal aorta requires extensive cellular migrations and rearrangements of the primordial tubes in order to generate a single fused vessel located at the embryonic ventral midline. This study examines the role of VEGF signaling in the generation of the definitive dorsal aorta. Through gain- and loss-of-function studies in vivo in the chick embryo, we document a requirement for VEGF signaling in growth and migration of the paired primordia, and identify a developmental window in which aorta development is particularly sensitive to VEGF signaling. We also find that VEGF signaling regulates the intracellular distribution between membrane and cytoplasm of the cell-cell adhesion molecule VE-Cadherin in aortic endothelial cells in vivo, suggesting a possible mechanism for how VEGF regulates aortic endothelial cell dynamics during the fusion process.
Image Downsampling Expedited Adaptive Least-squares (IDEAL) fitting improves intravoxel incoherent motion (IVIM) analysis in the human kidney
Authors: Stabinska Julia , Zöllner Helge J. , Thiel Thomas , Wittsack Hans-Jörg , Ljimani Alexandra
Published: June 2022

Purpose

To improve the reliability of intravoxel incoherent motion model (IVIM) parameter estimation for the diffusion-weighted imaging in the kidney using a novel Image Downsampling Expedited Adaptive Least-squares (IDEAL) approach.

Methods

The robustness of IDEAL was investigated using simulated diffusion-weighted MRI data corrupted with different levels of Rician noise. Subsequently, the performance of the proposed method was tested by fitting bi- and triexponential IVIM model to in vivo renal DWI data acquired on a clinical 3 Tesla MRI scanner and compared to conventional approaches (Fixed D* and Segmented fitting).

Results

The numerical simulations demonstrated that the IDEAL algorithm provides robust estimates of the IVIM parameters in the presence of noise as indicated by relatively low absolute percentage bias (sMdPB [%]) and normalized root-mean-square error (RMSE [%]). The analysis of the in vivo data showed that the IDEAL-based IVIM parameter maps were less noisy and more visually appealing than those obtained using the Fixed D* and Segmented methods. Further, the use of IDEAL for the triexponential IVIM modelling resulted in reduced cortical and medullary coefficients of variation (CVs) for all IVIM parameters when compared with Fixed D*, reflecting greater accuracy of this method.

Conclusion

The proposed fitting algorithm yields more robust IVIM parameter estimates and is less susceptible to poor SNR than the conventional fitting approaches. Thus, the IDEAL approach has the potential to improve the reliability of renal DW-MRI analysis for clinical applications.
Scale-free and oscillatory spectral measures of sleep stages in humans
Authors: Schneider Bence , Szalárdy Orsolya , Ujma Péter P. , Simor Péter , Gombos Ferenc , Kovács Ilona , Dresler Martin , Bódizs Róbert
Published: June 2022

Power spectra of sleep electroencephalograms (EEG) comprise two main components: a decaying power-law corresponding to the aperiodic neural background activity, and spectral peaks present due to neural oscillations.’Traditional’ band-based spectral methods ignore this fundamental structure of the EEG spectra and thus are susceptible to misrepresenting the underlying phenomena. A fitting method that attempts to separate and parameterize the aperiodic and periodic spectral components called ‘fitting oscillations & one over f’ (FOOOF) was applied to a set of annotated whole-night sleep EEG recordings of 251 subjects from a wide age range (4-69 years). Most of the extracted parameters exhibited sleep stage sensitivity; significant main effects and interactions of sleep stage, age, sex, and brain region were found. The spectral slope (describing the steepness of the aperiodic component) showed especially large and consistent variability between sleep stages (and low variability between subjects), making it a candidate indicator of sleep states. The limitations and arisen problems of the FOOOF method are also discussed, possible solutions for some of them are suggested.
Intraoperative Spinal Cord Stimulation Mitigates Pain after Spine Surgery in Mice
Authors: Yamamoto Satoshi , Duong Alexander , Kim Alex , Hu Chengrui , Wiemers Blaine , Wang Jigong , Chung Jin Mo , La Jun-Ho
Published: June 2022

Background

Managing postoperative pain after spine surgery is challenging, and up to 40% of operated patients develop failed back surgery syndrome (FBSS) resulting in intractable back and/or leg pain. While spinal cord stimulation (SCS) has been shown to effectively alleviate such chronic pain, it is unknown if intraoperative SCS can mitigate the development of central sensitization that potentially causes intense postoperative pain and FBSS after spine surgery.

Methods

As an experimental spine surgery, unilateral T13 laminectomy was performed in mice to expose the dorsal part of L4-5 spinal segments that receive sensory inputs from the hind limb. After the laminectomy, a group of mice received intraoperative SCS epidurally applied to the exposed side of the dorsal part of the spinal cord for an hour under anesthesia before closing the surgical wounds. Secondary mechanical hypersensitivity, a behavioral manifestation of central sensitization, was measured in hind paws using von Frey assay one day before and at predetermined times after surgery. In addition, because von Frey assay is a nocifensive reflex-based analysis that primarily assesses the sensory-discriminative domain of pain, we also performed a conflict avoidance test to capture the affective-motivational domain of pain at selected timepoints post-laminectomy.

Results

Mice that underwent unilateral T13 laminectomy developed mechanical hypersensitivity in both hind paws, which gradually resolved in 1-2 weeks. The extent of the hypersensitivity was significantly less in the contralateral hind paw (relative to the laminectomy) than in the ipsilateral hind paw only in females.

Intraoperative SCS applied to the exposed side of the dorsal -spinal cord significantly inhibited the development of hind paw mechanical hypersensitivity only in the SCS-applied side. When paws were mechanically stimulated in their preferred place to present a conflict between pain/discomfort and natural preference, mice avoided the conflict after laminectomy, spending less time in the place than before the surgery. However, mice treated with intraoperative SCS after laminectomy did not avoid the conflict.

Conclusion

These results demonstrate that spine surgery for unilateral laminectomy induces central sensitization that results in postoperative pain hypersensitivity.

Intraoperative SCS after laminectomy can mitigate the development of this hypersensitivity in the SCS-applied side.
coda4microbiome: compositional data analysis for microbiome studies
Authors: Calle M.Luz , Susin Antoni
Published: June 2022

Motivation

One of the main challenges of microbiome analysis is its compositional nature that if ig-nored can lead to spurious results. This is especially critical when dealing with microbiome variable selection since classical differential abundance tests are known to provide large false positive rates.

Results

We developed coda4microbiome, a new R package for analyzing microbiome data within the Compositional Data Analysis (CoDA) framework in both, cross-sectional and longitudinal studies. The core functions of the library are aimed at the identification of microbial signatures and involve variable selection in generalized linear models with compositional covariates. All algorithms are accompanied by meaningful graphical representations that allow a better interpretation of the results.

Availability

coda4microbiome is implemented as an R package and is available at CRANhttps://cran.r-project.org/web/packages/coda4microbiome/index.html.

Contact

malu.calle@uvic.cat

Supplementary information

coda4microbiome project website:https://malucalle.github.io/coda4mi-crobiome/.
Trait-based paleontological niche prediction demonstrates deep time parallel ecological occupation in specialized ant predators
Authors: Sosiak Christine , Janovitz Tyler , Perrichot Vincent , Timonera John Paul , Barden Phillip
Published: June 2022

Understanding the paleoecology of species is fundamental to reconstructions of paleoecological communities, analyses of changing paleoenvironments, and the evolutionary history of many lineages. One method of establishing paleoecology is through comparing the morphology of extant analogs to extinct species; this method has been applied to many vertebrate groups using predictive linear models, but has been rarely applied using invertebrate taxa or non-linear frameworks. The ant fossil record, which frequently preserves specimens in three-dimensional fidelity, chronicles putative faunal turnover during the Late Cretaceous and into Cenozoic. The earliest fossil species comprise enigmatic stem-groups that underwent extinction concomitant with crown ant diversification. Here, we apply a wide-ranging extant ecomorphological dataset to demonstrate the utility of Random Forest machine learning classification in predicting the ecology of the stem-group hell ants. We reconstruct a predicted ecomorphological assemblage of this phenotypically aberrant group of extinct ants, and compare predicted hell ant ecologies to the ecological occupations of their closest living analogs, lineages of solitary predators with highly specialized mandibular morphology. In contrast to previous hypotheses, we find that hell ants were primarily leaf litter or ground-nesting and foraging taxa, and that the ecological breadth of this unusual lineage mirrored that of living groups. Results suggest ecological coherence between the Mesozoic and modern communities, even as the earliest occupants of predatory niches were phylogenetically and morphologically distinct.
Annotation of structural variants with reported allele frequencies and related metrics from multiple datasets using SVAFotate
Authors: Nicholas Thomas J. , Cormier Michael J. , Quinlan Aaron R.
Published: June 2022

Background

Identification of impactful genetic variants from DNA sequencing data relies on increasingly detailed filtering strategies to isolate the small subset of variants that are more likely to underlie a disease phenotype. Datasets reflecting population allele frequencies of different types of variants have been demonstrated as powerful filtering tools, especially in the context of rare disease analysis. While such population-scale allele frequency datasets now exist for structural variants (SVs), it remains a challenge to match SV calls between multiple datasets and thereby correctly estimate the population allele frequency of a putative SV.

Results

We introduce SVAFotate, a software tool for SV matching that enables the annotation of SVs with variant allele frequency and related information. These annotations are derived from known SV datasets which are incorporated by SVAFotate. As a result, VCF files annotated by SVAFotate offer a variety of annotations to aid in the stratification of SVs as common or rare in the broader human population.

Conclusions

Here we demonstrate the use of SVAFotate in the classification of SVs with regards to their population frequency and illustrate how annotations provided by SVAFotate can be used to filter and prioritize SVs. Lastly, we detail how best to utilize these SV annotations in the analysis of genetic variation in studies of rare disease.
Pulsed transistor operation enables miniaturization of electrochemical aptamer–based sensors
Authors: Bidinger Sophia L. , Keene Scott T. , Han Sanggil , Plaxco Kevin W. , Malliaras George G. , Hasan Tawfique
Published: June 2022

By simultaneously transducing and amplifying, transistors offer advantages over simpler, electrode-based transducers in electrochemical biosensors. However, transistor-based biosensors typically use static (i.e., DC) operation modes that are poorly suited for sensor architectures relying on the modulation of charge transfer kinetics to signal analyte binding. Thus motivated, here we translate the AC “pulsed potential” approach typically used with electrochemical aptamer-based sensor to an organic electrochemical transistor (OECT). Specifically, by applying a linearly sweeping square-wave potential to an aptamer-functionalized gate electrode, we produce current modulation across the transistor channel two orders of magnitude larger than seen for the equivalent, electrode-based biosensor. Critically, the resulting amplification is scalable, such that there is no signal loss with OECT miniaturization. The pulsed transistor operation demonstrated here could be applied generally to sensors relying on kinetics-based signaling, expanding opportunities for non-invasive and high spatial resolution biosensing.
Nitric oxide S-nitrosylates CSF1R to augment the action of CSF1R inhibition against castration resistant prostate cancer
Authors: Kuchakulla Manish , Firdaus Fakiha , Qureshi Rehana , Soni Yash , Van Booven Derek J , Shah Khushi , Dulce Raul Ariel , Masterson Thomas , Rosete Omar Joel , Hare Joshua M. , Ramasamy Ranjith , Arora Himanshu
Published: June 2022

During progression of prostate cancer, sustained oxidative overload in cancer cells potentiates the overall tumor microenvironment (TME). Targeting the TME using colony-stimulating factor 1 receptor (CSF1R) inhibition is a promising therapy for castration-resistant prostate cancer (CRPC). However, the therapeutic response to sustained CSF1R blockade therapy (CSF1Ri) is limited as a monotherapy. We postulated that one of the causative agents for reduced efficacy of CSF1Ri and increased oxidation in CRPC is endothelial nitric oxide syntheses (eNOS). Results showed that in high grade PCa human specimens, eNOS is positively correlated with CSF1-CSF1R signaling and remains in an un-coupled state. The uncoupling disables eNOS to generate sufficient Nitric oxide (NO) that are required for inducing effective S-nitrosylation of CSF1R molecule at specific cysteine sites (Cys 224, Cys 278 and Cys 830). Importantly, we found that S-nitrosylation of CSF1R molecule at Cys 224, Cys 278 and Cys 830 sites is necessary for effective inhibition of tumor promoting cytokines (which are downstream of CSF1-CSF1R signaling) by CSF1R blockade. In this context, we studied if exogenous NO treatment could rescue the side effects of eNOS uncoupling. Results showed that exogenous NO treatment (using S-nitrosoglutathione (GSNO)) is effective in not only inducing S-Nitrosylation of CSF1R molecule, but it helps in rescuing the excess oxidation in tumor regions, reducing overall tumor burden, suppresses the tumor promoting cytokines which are ineffectively suppressed by CSF1R blockade. Together these results postulated that NO therapy could act as an effective combinatorial partner with CSF1R blockade against CRPC. In this context, results demonstrated that exogenous NO treatment successfully augment the anti-tumor ability of CSF1Ri in murine models of CRPC. Importantly, the overall tumor reduction was most effective in NO-CSF1Ri therapy compared to NO or CSF1Ri mono therapies. Moreover, Immunophenotyping of tumor grafts showed that the NO-CSF1Ri combination significantly decreased intratumoral percentage of anti-inflammatory macrophages, myeloid derived progenitor cells and increased the percentage of pro-inflammatory macrophages, cytotoxic T lymphocytes, and effector T cells respectively. Together, our study suggests that the NO-CSF1Ri combination has the potential to act as a therapeutic agent that restore control over TME and improve the outcomes of PCa patients.
Longitudinal brain studies in adult zebrafish by MRI
Authors: Hamilton Noémie , Allen Claire , Reynolds Steven
Published: June 2022

Zebrafish (Danio rerio) has been successfully used for decades in developmental studies and disease modelling. The remarkable intake of zebrafish as a model system is partly due to its transparency during the early weeks of its development, allowing in vivo imaging of cellular and molecular processes. However, this key advantage wears off when tissues become opaque as the animal reaches juvenile and adult stages, rendering access to tissues for live imaging and longitudinal studies difficult. Here we aimed to provide a novel approach to image and assess tissue integrity of adult zebrafish using Magnetic Resonance Imaging (MRI) on live zebrafish suitable for longitudinal studies. We built a 3D-printed life support chamber and designed a protocol-directed sedation regime to recover adult zebrafish post scanning in a 9.4T MRI scanner. Our life support chamber is cheap and easy to create using 3D printing, allowing other groups to copy our template for quick setup. Additionally, we optimised the delivery of contrast agent to enhance brain signals in order to refine current delivery, usually delivered by intravenous in rodents. We show here that immersion in gadolinium was a viable alternative to intraperitoneal injection to reduce T1 relaxation times. This could lead to improved image contrast in adult zebrafish disease models. In conclusion, we provide here a detailed methodology to allow longitudinal studies of brain tissue integrity of adult zebrafish, combining safe and efficient delivery of contrast agent and live MRI. This technique can be used to bridge the gap between in vivo studies and longitudinal brain analysis in adult zebrafish which can be applied to the ever-growing number of adult zebrafish models of ageing and neurodegenerative diseases.
Along-tract quantification of resting-state BOLD hemodynamic response functions in white matter
Authors: Schilling Kurt G , Li Muwei , Rheault Francois , Ding Zhaohua , Anderson Adam W , Kang Hakmook , Landman Bennett A , Gore John C
Published: June 2022

Detailed knowledge of the BOLD hemodynamic response function (HRF) is crucial for accurate analysis and interpretation of functional MRI data. Considerable efforts have been made to characterize the HRF in gray matter (GM) but much less is known about BOLD effects in white matter (WM). However, recent reports have demonstrated reliable detection and analyses of WM BOLD signals after stimulation and in a resting state. WM and GM differ in energy requirements and blood flow, so neurovascular couplings may well be different. We aimed to derive a comprehensive characterization of the HRF in WM across a population, including accurate measurements of its shape and its variation along and between WM pathways, using resting-state fMRI acquisitions. Our results show that the HRF is significantly different between WM and GM. Features of the HRF, such as a prominent initial dip, show strong relationships with features of the tissue microstructure derived from diffusion imaging, and these relationships differ between WM and GM, consistent with BOLD signal fluctuations reflecting different energy demands and differences in neurovascular coupling between tissues of different composition. We also show that the HRF varies significantly along WM pathways, and is different between different WM pathways. Thus, much like in GM, changes in flow and/or oxygenation are different for different parts of the WM. These features of the HRF in WM are especially relevant for interpretation of the biophysical basis of BOLD effects in WM.
PandoraRL: DQN and Graph Convolution based ligand pose learning for SARS-COV1 Mprotease
Authors: Jose Justin , Alam Ujjaini , Arora Pooja , Singh Divye , Jatana Nidhi
Published: June 2022

The ability to predict the correct ligand binding pose for proteinligand complex is vital for drug design. Recently several machine learning methods have suggested knowledge based scoring functions for binding energy prediction. In this study, we propose a reinforcement learning (RL) based model, PandoraRL, where the RL agent helps the ligand traverse to the optimal binding pose. The underlying representation of molecules utilizes generalized graph convolution to represent the protein ligand complex with various atomic and spatial features. The representation consists of edges formed on the basis of inter molecular interactions such as hydrogen bonds, hydrophobic interactions, etc, and nodes representing atomic features. This study presents our initial model which can train on a protein-ligand pair and predict optimal binding pose for a different ligand with the same protein. To the best of our knowledge, this is the first time an RL based approach has been put forward for predicting optimized ligand pose.

CCS CONCEPTS

Computing methodologies → Reinforcement learning.
Explainable deep graph learning accurately modeling the peptide secondary structure prediction
Authors: Jiang Yi , Wang Ruheng , Feng Jiuxin , Jin Junru , Liang Sirui , Li Zhongshen , Yu Yingying , Ma Anjun , Su Ran , Zou Quan , Ma Qin , Wei Leyi
Published: June 2022

Accurately predicting peptide secondary structures remains a challenging task due to the lack of discriminative information in short peptides. In this study, we propose PHAT, a deep graph learning framework for the prediction of peptide secondary structures. The framework includes a novel interpretable deep hypergraph multi-head attention network that uses residue-based reasoning for structure prediction. Our algorithm can incorporate sequential semantic information from large-scale biological corpus and structural semantic information from multi-scale structural segmentation, leading to better accuracy and interpretability even with extremely short peptides. Our interpretable models are able to highlight the reasoning of structural feature representations and the classification of secondary substructures. We further demonstrate the importance of secondary structures in peptide tertiary structure reconstruction and downstream functional analysis, highlighting the versatility of our models. To facilitate the use of our model, we establish an online server which is accessible via http://inner.wei-group.net/PHAT/. We expect our work to assist in the design of functional peptides and contribute to the advancement of structural biology research.
Skeletal muscle lineage is dispensable for appendage regeneration in axolotl
Authors: Hu Yan , Pan Xiangyu , Shi Yu , Qiu Yuanhui , Wang Liqun , Murawala Prayag , Liu Yanmei , Xing Wanjin , Tanaka Elly M , Fei Ji-Feng
Published: June 2022

Regeneration of a complex appendage structure such as limb requires hierarchical coordination of multiple types of tissues. Muscles, as one of the major cell masses in limbs, have been reported recently to be critical to guide other tissue regeneration in planaria, but its function and relationship to other cells in vertebrate complex regeneration have been unclear. Here, we use Pax7 mutant axolotls, in which the limb muscle is developmentally lost, to investigate limb regeneration in the absence of skeletal muscle. We find that the pattern of regenerated limbs is normal in Pax7 mutants compared to the controls. Lack of muscles do not affect the proliferation of fibroblasts, another major population in limbs. Furthermore, using single cell RNA-sequencing, we demonstrate that the cell type composition in completely regenerated limbs in Pax7 mutants is similar to that in the controls, except the lack of cell types in muscle lineage. Our study reveals skeletal muscle is not required for the guidance of complex tissue regeneration in axolotls, and provides new views of the tissue hierarchy in vertebrate appendage regeneration.
Transcriptomic analysis reveals hub genes and pathways in response to acetic acid stress in Kluyveromyces marxianus during high-temperature ethanol fermentation
Authors: Li Yumeng , Hou Shiqi , Ren Ziwei , Fu Shaojie , Wang Sunhaoyu , Chen Mingpeng , Dang Yan , Li Hongshen , Li Shizhong , Li Pengsong
Published: June 2022

The thermotolerant yeast Kluyveromyces marxianus has great potential for high-temperature ethanol fermentation, but it produces excess acetic acid during high-temperature fermentation, which inhibits ethanol production. The mechanisms of K. marxianus’s responses to acetic acid have not been fully understood. In this study, the transcriptomic changes of K. marxianus DMKU3-1042 resulted from acetic acid stress during high-temperature ethanol fermentation were investigated based on high-throughput RNA sequencing. We identified 611 differentially expressed genes (DEGs) under acetic acid stress (fold change > 2 or < 0.5, P-adjust <0.05), with 166 up-regulated and 445 down-regulated. GO terms and pathways enriched in these DEGs were identified. Protein-protein interaction (PPI) networks were constructed based on the interactions between proteins coded by the DEGs, and hub genes and key modules in the PPI networks were identified. The results in this study indicated that during high-temperature fermentation, acetic acid stress promoted protein catabolism but repressed protein synthesis, which affected the growth and metabolism of K. marxianus and led to the decrease of ethanol production. The findings in this study provide a better understanding of the response mechanism of K. marxianus to acetic acid stress, and provide a basis for subsequent increase of ethanol production by K. marxianus.
Trackable and scalable LC-MS metabolomics data processing using asari
Authors: Li Shuzhao , Siddiqa Amnah , Thapa Maheshwor , Zheng Shujian
Published: June 2022

Significant challenges still exist in the computational processing of data from LC-MS metabolomic experiments into metabolite features. In this study, we examine the issues of provenance and reproducibility in the current software tools. The inconsistency among these tools is attributed to the deficiencies of mass alignment and controls of feature quality. To address these issues, we have developed a new open-source software tool, asari, for LC-MS metabolomics data processing. Asari is designed with a set of new algorithmic framework and data structures, and all steps are explicitly trackable. Asari compares favorably to other tools in feature detection and quantification. It offers substantial improvement of computational performance over current tools, and is highly scalable.
Modelling the mechanical cross-talk between cells and fibrous extracellular matrix using hybrid cellular Potts and molecular dynamics methods
Authors: Tsingos Erika , Bakker Bente Hilde , Keijzer Koen A.E. , Hupkes Hermen Jan , Merks Roeland M.H.
Published: June 2022

The mechanical interaction between cells and the extracellular matrix (ECM) is fundamental to coordinate collective cell behavior in multicellular tissues. Relating individual cell-level mechanics to tissue-scale collective behavior is an outstanding challenge which cell-based models such as the cellular Potts model (CPM) are well-positioned to address. These models generally represent the ECM with mean-field approaches, which assume substrate homogeneity. This assumption breaks down with fibrous ECM, which has non-trivial structure and mechanics. Here, we extend the CPM with a bead-spring chain model of ECM fiber networks modelled using molecular dynamics. We model contractile cells pulling with discrete focal adhesion-like sites on the ECM fiber network, and demonstrate agreement with experimental spatiotemporal fiber densification and displacement. We show that contractile cell forces propagate over multiple cell radii scaling with power law exponent of ≈ −0.5 typical of viscoelastic ECM. Further, we use in silico atomic force microscopy to measure local cell-induced network stiffening consistent with experiments. Our model lays the foundation to investigate how local and long-ranged cell-ECM mechanobiology contributes to multicellular morphogenesis.
Graph-based pangenomics maximizes genotyping density and reveals structural impacts on fungal resistance
Authors: Vaughn Justin N. , Branham Sandra E. , Abernathy Brian L. , Hulse-Kemp Amanda M. , Rivers Adam , Levi Amnon , Wechter William P.
Published: June 2022

The genomic sequences segregating in experimental populations are often highly divergent from the community reference and from one another. Such divergence is problematic under various short-read-based genotyping strategies. In addition, large structural differences are often invisible despite being strong candidates for causal variation. These issues are exacerbated in specialty crop breeding programs with fewer, lower-quality sequence resources. We examined the benefits of complete genomic information, based on long-read assemblies, in a biparental mapping experiment segregating at numerous disease resistance loci in the non-model crop, melon (Cucumis melo). We find that a graph-based approach, which uses both parental genomes, results in 19% more variants callable across the population and raw allele calls with a 2 to 3-fold error-rate reduction, even relative to single reference approaches using a parent genome. We show that structural variation has played a substantial role in shaping twoFusariumwilt resistance loci with known causal genes. We also report on the genetics of powdery mildew resistance, where copy number variation and local recombination suppression are directly interpretable via parental genome alignments. Benefits observed, even in this low-resolution biparental experiment, will inevitably be amplified in more complex populations.
Fitness seascapes are necessary for realistic modeling of the evolutionary response to drug therapy
Authors: King Eshan S. , Maltas Jeff , Weaver Davis T. , Barker-Clarke Rowan , Pelesko Julia , Dolson Emily , Scott Jacob G.
Published: June 2022

A persistent challenge in evolutionary medicine is predicting the evolution of drug resistance, which is complicated further when the drug concentration varies in time and space within a patient. Evolutionary trade-offs, or fitness costs of resistance, cause the evolutionary landscape to change dramatically as the drug selective pressure changes. In this work, we show how fitness seascapes, or collections of genotype-specific dose-response curves, more accurately describe dose-dependent evolution and the arrival of drug resistance. We measure a novel empirical fitness seascape inE. colisubject to cefotaxime, finding substantial growth rate penalties in exchange for drug resistance. In two computational experiments we show how the fitness seascape framework may be used to model evolution in changing environments. First, we show that the probability of evolutionary escape from extinction is dependent on the rate of environmental change, aligning with priorin vitroresults. Then, we simulate patients undergoing a daily drug regimen for an infection with varying rates of nonadherence. We find that early drug regimen adherence is critical for successfully eliminating the infection, lending evidence to a “two strike” model of disease extinction. Our work integrates an empirical fitness seascape into an evolutionary model with realistic pharmacological considerations. Future work may leverage this platform to optimize dosing regimens or design adaptive therapies to avoid resistance.