bluuebunny/crossref_metadata_2025 huggingface dataset:
The neural determinants of abstract beauty
Authors: Rasche Samuel E. , Beyh Ahmad , Paolini Marco , Zeki Semir
Published: July 2022

We have enquired into the neural activity which correlates with the experience of beauty aroused by abstract paintings consisting of arbitrary assemblies of lines and colours. During the brain imaging experiments, subjects rated abstract paintings according to aesthetic appeal. There was low agreement on the aesthetic classification of these paintings among participants. Univariate analyses revealed higher activity with higher declared aesthetic appeal in both the visual areas and the medial frontal cortex. Additionally, representational similarity analysis (RSA) revealed that the experience of beauty correlated with decodable patterns of activity in visual areas. These results are broadly similar to those obtained in previous studies on facial beauty. With abstract art, it was the involvement of visual areas implicated in the processing of lines and colours while with faces it was of visual areas implicated in the processing of faces. Both categories of aesthetic experience correlated with increased activity in medial frontal cortex. We conclude that the sensory areas participate in the selection of stimuli according to aesthetic appeal and that it is the co-operative activity between the sensory areas and the medial frontal cortex that is the basis for the experience of abstract visual beauty. Further, this co-operation is enabled by “experience dependent” functional connections, in the sense that currently the existence and high specificity of these connections can only be demonstrated during certain experiences.
Honeycomb cell walls are plastic; initially built as curves the walls are reformed by bees during subsequent construction
Authors: Gallo Vincent , Bridges Alice , Woodgate Joseph , Chittka Lars
Published: July 2022

Honeybee comb comprises recognisable hexagons, each with straight sides. Not only are the cell side-walls flat, but so too are those that form the base of cells; base faces which are shared with cells on the opposite face of the comb. The mechanism by which bees build cells with flat sides has been the subject of speculation for centuries, but it has been conjectured by Kepler, Darwin as well as more recent researchers that bees build cylindrical cells that are transformed into flat sided prisms, without consensus as to the process by which this is achieved. By offering bees shaped wax stimuli and observing the comb that was built upon them, we have shown that under certain conditions walls will be curved and others where walls are reformed to be flat. A wall of a cell, be it a side-wall or a face of the base, with no other cell beyond it will be built as a convex curve whereas a wall with a cell to both sides will be formed flat. Furthermore, we show that these walls are plastic; walls that were initially built curved were re-shaped to be flat once a second adjacent cell had been built.
Interrelated effects of age and parenthood on whole-brain controllability: protective effects of parenthood in mothers
Authors: Jamalabadi Hamidreza , Hahn Tim , Winter Nils R. , Nozari Erfan , Ernsting Jan , Meinert Susanne , Leehr Elisabeth , Dohm Katharina , Bauer Jochen , Pfarr Julia-Katharina , Stein Frederike , Thomas-Odenthal Florian , Brosch Katharina , Mauritz Marco , Gruber Marius , Repple Jonathan , Kaufmann Tobias , Krug Axel , Nenadić Igor , Kircher Tilo , Dannlowski Udo , Derntl Birgit
Published: July 2022

Background

Controllability is a measure of the brain’s ability to orchestrate neural activity which can be quantified in terms of properties of the brain’s network connectivity. Evidence from the literature suggests that aging can exert a general effect on whole-brain controllability. Mounting evidence, on the other hand, suggests that parenthood and motherhood in particular lead to long-lasting changes in brain architecture that effectively slow down brain aging. We hypothesize that parenthood might preserve brain controllability properties from aging.

Methods

In a sample of 814 healthy individuals (aged 33.9±12.7 years, 522 females), we estimate whole-brain controllability and compare the aging effects in subjects with vs. those without children. We use diffusion tensor imaging (DTI) to estimate the brain structural connectome. The level of brain control is then calculated from the connectomic properties of the brain structure. Specifically, we measure the network control over many low-energy state transitions (average controllability) and the network control over difficult-to-reach states (modal controllability).

Results and conclusion

In nulliparous females, whole-brain average controllability increases, and modal controllability decreases with age, a trend that we do not observe in parous females. Statistical comparison of the controllability metrics shows that modal controllability is higher and average controllability is lower in parous females compared to nulliparous females. In men, we observed the same trend, but the difference between nulliparous and parous males do not reach statistical significance. Our results provide strong evidence that parenthood contradicts aging effects on brain controllability and the effect is stronger in mothers.
The Free Lunch is not over yet – Systematic Exploration of Numerical Thresholds in Phylogenetic Inference
Authors: Haag Julia , Hübner Lukas , Kozlov Alexey M. , Stamatakis Alexandros
Published: July 2022

Maximum Likelihood (ML) is a widely used phylogenetic inference model. ML implementations heavily rely on numerical optimization routines that use internal numerical thresholds to determine convergence. We systematically analyze the impact of these threshold settings on the log-likelihood and runtimes for ML tree inferences with RAxML-NG, IQ-TREE, and FastTree on empirical datasets. We provide empirical evidence that we can substantially accelerate tree inferences with RAxML-NG and IQ-TREE by changing the default values of two such numerical thresholds. At the same time, altering these settings does not significantly impact the quality of the inferred trees. We further show that increasing both thresholds accelerates the RAxML-NG bootstrap without influencing the resulting support values. For RAxML-NG, increasing the likelihood thresholdsϵLnLandϵbrlento 10 and 103respectively results in an average tree inference speedup of 1.9±0.6 onData collection 1, 1.8±1.1 onData collection 2, and 1.9±0.8 onData collection 2for the RAxML-NG bootstrap. Increasing the likelihood thresholdϵLnLto 10 in IQ-TREE results in an average tree inference speedup of 1.3±0.4 onData collection 1and 1.3±0.9 onData collection 2.
Interactive analysis of single-cell data using flexible workflows with SCTK2.0
Authors: Wang Yichen , Sarfraz Irzam , Hong Rui , Koga Yusuke , Akavoor Vidya , Cao Xinyun , Alabdullatif Salam , Pervaiz Nida , Zaib Syed Ali , Wang Zhe , Jansen Frederick , Yajima Masanao , Johnson W. Evan , Campbell Joshua D.
Published: July 2022

Analysis of single-cell RNA-seq (scRNA-seq) data can reveal novel insights into heterogeneity of complex biological systems. Many tools and workflows have been developed to perform different types of analysis. However, these tools are spread across different packages or programming environments, rely on different underlying data structures, and can only be utilized by people with knowledge of programming languages. In the Single Cell Toolkit 2.0 (SCTK2.0), we have integrated a variety of popular tools and workflows to perform various aspects of scRNA-seq analysis. All tools and workflows can be run in the R console or using an intuitive graphical user interface built with R/Shiny. HTML reports generated with Rmarkdown can be used to document and recapitulate individual steps or entire analysis workflows. We show that the toolkit offers more features when compared with existing tools and allows for a seamless analysis of scRNA-seq data for non-computational users.

Graphical Abstract

Highlights

Intuitive graphical user interface for interactive analysis of scRNA-seq data

Allows non-computational users to analyze scRNA-seq data with end-to-end workflows

Provides interoperability between tools across different programming environments

Produces HTML reports for reproducibility and easy sharing of results
High-throughput and automatic structural and developmental root phenotyping on Arabidopsis seedlings
Authors: Fernandez Romain , Crabos Amandine , Maillard Morgan , Nacry Philippe , Pradal Christophe
Published: July 2022

Background

High-throughput phenotyping is crucial for the genetic and molecular understanding of adaptive root system development. In recent years, imaging automata have been developed to acquire the root system architecture of many genotypes grown in Petri dishes to explore the Genetic x Environment (GxE) interaction. There is now an increasing interest in understanding the dynamics of the adaptive responses, such as the organ apparition or the growth rate. However, due to the increasing complexity of root architectures in development, the accurate description of the topology, geometry, and dynamics of a growing root system remains a challenge.

Results

We designed a high-throughput phenotyping method, combining an imaging device and an automatic analysis pipeline based on registration and topological tracking, capable of accurately describing the topology and geometry of observed root systems in 2D+t. The method was tested on a challenging Arabidopsis seedling dataset, including numerous root occlusions and crossovers. Static phenes are estimated with high accuracy (R2= 0.996 and 0, 923 for primary and second-order roots length, respectively). These performances are similar to state-of-the-art results obtained on root systems of equal or lower complexity. In addition, our pipeline estimates dynamic phenes accurately between two successive observations (R2= 0. 938 for lateral root growth).

Conclusions

We designed a novel method of root tracking that accurately and automatically measures both static and dynamic RSA parameters from a novel high-throughput root phenotyping platform. It has been used to characterize developing patterns of root systems grown under various environmental conditions. It provides a solid basis to explore the GxE interaction controlling the dynamics of root system architecture adaptive responses. In future work, our approach will be adapted to a wider range of imaging configurations and species.
Metformin Improves Ovarian Function and Increases Egg Production in Broiler Breeder Hens
Authors: Weaver Evelyn A. , Ramachandran Ramesh
Published: July 2022

Broiler breeder hens, the parent stock of commercial broiler chickens, have poor reproductive efficiency associated with aberrant and excessive recruitment of ovarian follicles which results in sub-optimal egg production, fertility, and hatchability. The reproductive dysfunction observed in these hens resembles polycystic ovary syndrome in women, a condition wherein metformin is prescribed as a treatment. The main objectives of this study were to determine the effect of metformin on body weight, abdominal fat pad weight, ovarian function, and plasma steroid hormone concentrations. Broiler breeder hens were treated with 0, 25, 50, or 75 mg/kg body weight of metformin mixed in the diet for 40 weeks (n= 45 hens/treatment; 25-65 weeks of age). At 65 weeks of age, hens that received the highest dose of metformin had significantly lower body and abdominal fat pad weights (p < 0.05) than the control. Metformin treatment, at all levels, normalized the preovulatory and prehierarchical ovarian follicular hierarchy. Metformin (50 or 75 mg/kg body weight) significantly increased the total number of eggs laid per hen during the entire production period and these hens had significantly greater fertility and hatchability at 65 weeks of age compared to the control (p < 0.05). Metformin treatment at all levels altered the plasma profile of reproductive hormones, with significantly lower plasma testosterone concentrations and a decreased testosterone to androstenedione ratio in hens that received metformin (p < 0.05). Future studies should focus on the mechanisms underlying the beneficial effects of metformin in improving the reproductive efficiency of broiler breeder hens.

In Brief

The pathophysiology of the ovarian dysfunction encountered in broiler breeder hens remains poorly understood but is similar to a condition in women known as PCOS. This study reveals that metformin may provide a cheap and effective method of improving ovarian function in broiler breeder hens.
Pannexin 3 channels regulate architecture, adhesion, barrier function and inflammation in the skin
Authors: O’Donnell Brooke L. , Sanchez-Pupo Rafael E. , Sayedyahossein Samar , Karimi Mehdi , Bahmani Mehrnoosh , Zhang Christopher , Johnston Danielle , Kelly John J. , Wakefield C. Brent , Barr Kevin , Dagnino Lina , Penuela Silvia
Published: July 2022

The channel-forming glycoprotein Pannexin 3 (PANX3) functions in cutaneous wound healing and keratinocyte differentiation, but its role in skin homeostasis through aging is not yet understood. We found that PANX3 is absent in newborn skin but becomes upregulated with age. We characterized the skin of globalPanx3knockout mice (KO) and found that KO dorsal skin showed sex-differences at different ages, but generally had reduced dermal and hypodermal areas compared to aged-matched controls. Transcriptomic analysis of KO epidermis revealed reduced E-cadherin stabilization and Wnt signaling compared to WT, consistent with the inability of primary KO keratinocytes to adhere in culture, and diminished epidermal barrier function in KO mice. We also observed increased inflammatory signaling in KO epidermis and higher incidence of dermatitis in aged KO mice compared to wildtype controls. These findings suggest that during skin aging, PANX3 is critical in the maintenance of dorsal skin architecture, keratinocyte cell-cell and cell-matrix adhesion and inflammatory skin responses.
Fast Local Alignment of Protein Pockets (FLAPP): A system-compiled program for large-scale binding site alignment
Authors: Sankar Santhosh , Sakthivel Naren Chandran , Chandra Nagasuma
Published: July 2022

Protein function is a direct consequence of its sequence, structure and the arrangement at the binding site. Bioinformatics using sequence analysis is typically used to gain a first insight into protein function. Protein structures, on the other hand, provide a higher resolution platform into understanding functions. As the protein structural information is increasingly becoming available through experimental structure determination and through advances in computational methods for structure prediction, the opportunity to utilize this data is also increasing. Structural analysis of small molecule ligand binding sites in particular provide a direct and more accurate window to infer protein function. However it remains a poorly utilized resource due to the huge computational cost of existing methods that make large scale structural comparisons of binding sites prohibitive. Here we present an algorithm called FLAPP that produces very rapid atomic level alignments. By combining clique matching in graphs and the power of modern CPU architectures, FLAPP aligns a typical pair of binding site binding sites at ~12.5 milliseconds using a single CPU core, ~ 1 millisecond using 12 cores on a standard desktop machine, and performs a PDB-wide scan in 1-2 minutes. We perform rigorous validation of the algorithm at multiple levels of complexity and show that FLAPP provides accurate alignments. We also present a case study involving vitamin B12 binding sites to showcase the usefulness of FLAPP for performing an exhaustive alignment based PDB-wide scan. We expect this tool will be invaluable to the scientific community to quickly align millions of site pairs on a normal desktop machine to gain insights into protein function and drug discovery for drug target and off-target identification, and polypharmacology.
Postnatal protein intake as a determinant of skeletal muscle structure and function in mice – a pilot study
Authors: Giakoumaki Ifigeneia , Pollock Natalie , Aljuaid Turki , Sanicandro Anthony J. , Alameddine Moussira , Owen Euan , Myrtziou Ioanna , Ozanne Susan E. , Kanakis Ioannis , Goljanek-Whysall Katarzyna , Vasilaki Aphrodite
Published: July 2022

Sarcopenia is characterised by an age-related decrease in the number of muscle fibres and additional weakening of the remaining fibres, resulting in a reduction in muscle mass and function. Many studies associate poor maternal nutrition during gestation and/or lactation with altered skeletal muscle homeostasis in the offspring and the development of sarcopenia. The aim of this study was to determine whether the musculoskeletal physiology in offspring born to mouse dams fed a low-protein diet during pregnancy was altered and whether any physiological changes could be modulated by the nutritional protein content in early postnatal stages. Thy1-YFP female mice were fed ad libitum on either a normal (20%) or a low-protein (5%) diet. Newborn pups were cross-fostered to different lactating dams (maintained on 20% or 5% diet) to generate 3 groups analysed at weaning (21 days): Normal-to-Normal (NN), Normal-to-Low (NL) and Low-to-Normal (LN). Further offspring were maintained ad libitum on the same diet as during lactation until 12 weeks of age creating another 3 groups (NNN, NLL, LNN). Mice on a low protein diet postnatally (NL, NLL) exhibited a significant reduction in body and muscle weight persisting up to 12 weeks, unlike mice on a low protein diet only prenatally (LN, LNN). Muscle fibre size was reduced in mice from the NL but not LN group, showing recovery at 12 weeks of age. Muscle force was reduced in NLL mice, concomitant with changes in the NMJ site and changes in atrophy-related and myosin genes. In addition, μCT scans of mouse tibiae at 12 weeks of age revealed changes in bone mass and morphology, resulting in a higher bone mass in the NLL group than the control NNN group. Finally, changes in the expression of miR-133 in the muscle of NLL mice suggest a regulatory role for this microRNA in muscle development in response to postnatal diet changes. Overall, this data shows that a low maternal protein diet and early postnatal life low-protein intake in mice can impact skeletal muscle physiology and function in early life while postnatal low protein diet favors bone integrity in adulthood.
Modular automated microfluidic cell culture platform reduces glycolytic stress in cerebral cortex organoids
Authors: Seiler Spencer T. , Mantalas Gary L. , Selberg John , Cordero Sergio , Torres-Montoya Sebastian , Baudin Pierre V. , Ly Victoria T. , Amend Finn , Tran Liam , Hoffman Ryan N. , Rolandi Marco , Green Richard E. , Haussler David , Salama Sofie R. , Teodorescu Mircea
Published: July 2022

Organ-on-a-chip systems combine microfluidics, cell biology, and tissue engineering to culture 3D organ-specific in vitro models that recapitulate the biology and physiology of their in vivo counterparts. Here, we have developed a multiplex platform that automates the culture of individual organoids in isolated microenvironments at user-defined media flow rates. Programmable workflows allow the use of multiple reagent reservoirs that may be applied to direct differentiation, study temporal variables, and grow cultures long term. Novel techniques in polydimethylsiloxane (PDMS) chip fabrication are described here that enable features on the upper and lower planes of a single PDMS substrate. RNA sequencing (RNA-seq) analysis of automated cerebral cortex organoid cultures shows benefits in reducing glycolytic and endoplasmic reticulum stress compared to conventional in vitro cell cultures.
SARS-CoV-2 causes brain inflammation via impaired neuro-immune interactions
Authors: Oka Naomi , Shimada Kazuya , Ishii Azusa , Kobayashi Nobuyuki , Kondo Kazuhiro
Published: July 2022

The brain inflammation that frequently occurs in SARS-CoV-2 is the cause of neurological complications1,2 and long COVID 3,4,5. However, many aspects of its pathogenesis mechanism remain unknown 6, 7 and no method of treatment has been established 8. By administering a non-proliferating adenovirus vector expressing SARS-CoV-2 S1 protein into the nasal cavity of mice, we developed a mouse model (S1 mouse) reproducing brain inflammation, fatigue, depressive symptoms, and lung inflammation. Having intracellular calcium elevating activity, S1 protein increased olfactory bulb apoptosis, and reduced the number of acetylcholine producing cells in the medial septal and the diagonal band of Broca as well as the amount of acetylcholine in the brain. This resulted in disrupting the cholinergic anti-inflammatory pathway (CAP) 9 and enhancing inflammation in the brain. Previously, nothing was known about anti-inflammatory factors in the CAP but we discovered that, in the inflammation occurring in the S1 mouse brain, the action of the RNA binding protein ZFP36 10 in degrading inflammatory cytokine mRNA was impaired.

The symptoms exhibited by the S1 mouse were improved by administering donepezil, a drug with a cholinergic action used in the treatment of dementia. These findings clarify the mechanism of brain inflammation in COVID-19 and indicate the possibility of applying donepezil in the treatment of neurological complications in COVID-19 and long COVID.
RAV1 mediates cytokinin signalling for regulating primary root growth in Arabidopsis
Authors: Mandal Drishti , Datta Saptarshi , Ravindra Giridhar , Mondal Pranab Kumar , Chaudhuri Ronita Nag
Published: July 2022

Root growth dynamics is an outcome of complex hormonal crosstalk. The primary root meristem size for example, is determined by antagonizing actions of cytokinin and auxin. Here we show that RAV1, a member of the AP2/ERF family of transcription factors, mediates cytokinin signalling in roots to regulate meristem size. Therav1mutants have prominently longer primary roots, with a meristem that is significantly enlarged and contain higher cell numbers, compared to wild type. The mutant phenotype could be restored on exogenous cytokinin application or by inhibiting auxin transport. At the transcript level, primary cytokinin-responsive genes likeARR1, ARR12were significantly downregulated in the mutant root, indicating impaired cytokinin signalling. In concurrence, cytokinin induced regulation ofSHY2, an Aux/IAA gene, and auxin efflux carrierPIN1was hindered inrav1, leading to altered auxin transport and distribution. This effectively altered root meristem size in the mutant. Notably, CRF1 another member of the AP2/ERF family implicated in cytokinin signalling, is transcriptionally repressed by RAV1 to promote cytokinin response in roots. Further correlating RAV1 to cytokinin signalling, our results demonstrate that cytokinin upregulateRAV1expression through ARR1, during post-embryonic root development. Regulation ofRAV1expression is a part of secondary cytokinin response that eventually repressesCRF1to augment cytokinin signalling. To conclude, in Arabidopsis, RAV1 functions in a branch pathway downstream to ARR1 that regulatesCRF1expression to enhance cytokinin action during primary root development.
Plasma Metallomics Reveals Potential Biomarkers and Insights into the Ambivalent Associations of Elements with Acute Myocardial Infarction
Authors: Lim Si Ying , Dayal Hiranya , Seah Song Jie , Woon Tan Regina Pei , Low Zhi En , Carrasco Laserna Anna Karen , Tan Sock Hwee , Chan Mark Y. , Yau Li Sam Fong
Published: July 2022

Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide. Using a validated and efficient ICP-MS/MS-based workflow, a total of 30 metallomic features were profiled in a study comprising 101 AMI patients and 66 age-matched healthy controls. The metallomic features include 12 essential elements (Ca, Co, Cu, Fe, K, Mg, Mn, Na, P, S, Se, Zn), 8 non-essential/toxic elements (Al, As, Ba, Cd, Cr, Ni, Rb, Sr, U, V), and 10 clinically relevant element-pair product/ratios (Ca/Mg, Ca×P, Cu/Se, Cu/Zn, Fe/Cu, P/Mg, Na/K, Zn/Se). Preliminary linear regression with feature selection confirmed smoking status as a predominant determinant for the non-essential/toxic elements, and revealed potential routes of action. Univariate assessments with adjustments for covariates revealed insights into the ambivalent relationships of Cu, Fe, and P with AMI, while also confirming cardioprotective associations of Se. Also, beyond their roles as risk factors, Cu and Se may be involved in the response mechanism in AMI onset/intervention, as demonstrated via longitudinal data analysis with 2 additional time-points (1-/6-month follow-up). Finally, based on both univariate tests and multivariate classification modelling, potentially more sensitive markers measured as element-pair ratios were identified (e.g., Cu/Se, Fe/Cu). Overall, metallomics-based biomarkers may have utility for AMI prediction.
Integration of Clinicopathological And Genomic Features To Predict The Risk Stratification of TCGA Lung Adenocarcinoma And Lung Squamous Cell Carcinoma Patients
Authors: Sakman Mehmet Cihan , Zengin Talip , Önal-Süzek Tuğba
Published: July 2022

Background

Predicting lung adenocarcinoma (LUAD) and Lung Squamous Cell Carcinoma (LUSC) risk cohorts is a crucial step in precision oncology. Currently, clinicians and patients are informed about the patient’s risk group via staging. Recently, several machine learning approaches are reported for the stratification of LUAD and LUSC patients, but there is no study comparatively assessing the integrated modeling of the clinicopathological and genetic data of these two lung cancer types so far.

Methods

In our study based on 1026 patients’ clinicopathological and somatically mutated gene features, a prognostic prediction model is implemented to rank the importance of features according to their impact on risk classification.

Findings

By integrating the clinicopathological features and somatically mutated genes of patients, we achieved the highest accuracy; %93 for LUAD and %89 for LUSC, respectively. Our second finding is that new prognostic genes such as KEAP1 for LUAD and CSMD3 for LUSC and new clinicopathological factors such as site of resection are significantly associated with the risk stratification and can be integrated into clinical decision making.

Conclusions

In current clinical practice, clinicians, and patients are informed about the patient’s risk group only with cancer staging. With the feature set we propose, clinicians and patients can assess the risk group of their patients according to the patient-specific clinical and molecular parameters. Using this machine learning model we are implementing a user-friendly web interface for clinicians and lung cancer patients to predict the risk stratification of individuals and to understand the underlying clinical and molecular mechanisms.
ATP-competitive and allosteric inhibitors induce differential conformational changes at the autoinhibitory interface of Akt
Authors: Shaw Alexandria L , Parson Matthew AH , Truebestein Linda , Jenkins Meredith L , Leonard Thomas A , Burke John E
Published: July 2022

The protein kinase Akt is a master regulator of pro-growth signalling in the cell. Akt is activated through its targeted recruitment to phosphoinositides, leading to disruption of the autoinhibitory interface between the kinase and pleckstrin homology (PH) domains. Hyper activation of Akt is common in oncogenic transformation, with multiple oncogenic activating mutants identified in Akt. This has led to the development of potent and selective ATP-competitive and allosteric inhibitors for Akt. Paradoxically, some ATP-competitive Akt inhibitors cause hyperphosphorylation of Akt. Here, using hydrogen deuterium exchange mass spectrometry (HDX-MS), we interrogated the conformational changes upon binding to the Akt active site inhibitor A-443654, and the Akt allosteric inhibitor MK-2206. We compared the conformational changes that occurred for each inhibitor under three different states of Akt: i-inactive monophosphorylated, ii-partially active tris-phosphorylated [T308, T450, S473], and iii-fully activated, tris-phosphorylated bound to PIP3 membranes. The allosteric MK-2206 inhibitor results in large scale allosteric conformational changes in all states, and restricts membrane binding through sequestration of the PH domain. Binding of the A-443654 inhibitor led to large scale allosteric conformational changes in both the monophosphorylated and phosphorylated states, leading to an alteration in the autoinhibitory PH-kinase interface. We also observed increased protection in the PH domain upon membrane binding in the presence of A-443654, suggesting that the PH domain is more accessible for membrane binding. This work provides unique insight into the autoinhibitory conformation of the PH and kinase domain and dynamic conformational changes induced by Akt inhibitors, and has important implications for the design of Akt targeted therapeutics.
A low-cost and open-source solution to automate imaging and analysis of cyst nematode infection assays for Arabidopsis thaliana
Authors: Kranse Olaf Prosper , Ko Itsuhiro , Healey Roberta , Sonawala Unnati , Wei Siyuan , Senatori Beatrice , De Batté Francesco , Zhou Ji , Eves-van den Akker Sebastian
Published: July 2022

Background

Cyst nematodes are one of the major groups of plant-parasitic nematode, responsible for considerable crop losses worldwide. Improving genetic resources, and therefore resistant cultivars, is an ongoing focus of many pest management strategies. One of the major bottlenecks in identifying the plant genes that impact the infection, and thus the yield, is phenotyping. The current available screening method is slow, has unidimensional quantification of infection limiting the range of scorable parameters, and does not account for phenotypic variation of the host. The ever-evolving field of computer vision may be the solution for both the above-mentioned issues. To utilise these tools, a specialised imaging platform is required to take consistent images of nematode infection in quick succession.

Results

Here, we describe an open-source, easy to adopt, imaging hardware and trait analysis software method based on a pre-existing nematode infection screening method in axenic culture. A cost-effective, easy-to-build and -use, 3D-printed imaging device was developed to acquire images of the root system of Arabidopsis thaliana infected with the cyst nematode Heterodera schachtii, replacing costly microscopy equipment. Coupling the output of this device to simple analysis scripts allowed the measurement of some key traits such as nematode number and size from collected images, in a semi-automated manner. Additionally, we used this combined solution to quantify an additional trait, root area before infection, and showed both the confounding relationship of this trait on nematode infection and a method to account for it.

Conclusion

Taken together, this manuscript provides a low-cost and open-source method for nematode phenotyping that includes the biologically relevant nematode size as a scorable parameter, and a method to account for phenotypic variation of the host. Together these tools highlight great potential in aiding our understanding of nematode parasitism.
Disentangling the genomic complexity of the Fragilariopsis cylindrus (CCMP1102) genome
Authors: Hodgkinson Kat Amy , Wright Jonathan , Accinelli Gonzalo Garcia , Heavens Darren , Hopes Amanda , Mock Thomas , van Oosterhout Cock , Clavijo Bernardo J.
Published: July 2022

Fragilariopsis cylindrus CCMP1102 is characterised by a complex genome with significant levels of heterozygosity between haplotypes, > 35% repeats, and an unknown karyotype. This complexity hindered prior assemblies, which show coverage discrepancies indicative of incompleteness. Here, we use a k-mer spectra analysis to reveal the coverage signature for a third haplotype. We applied a novel haplotype-specific assembly method to reconstruct the F. cylindrus CCMP1102 genome, producing 10 fully assembled chromosomes capped by telomeres, and a putative chromosome with a single breakpoint. Our analysis shows triploidy, two cases of aneuploidy, and several truncations. We also present evidence that F. cylindrus reproduces sexually. Taken together, our analytical approach is capable of haplotype-resolved assemblies from structurally complex, poly-ploid genomes, making it suitable for complex genomes of non-model organisms, including those with unknown karyotype.
SARS-CoV-2 BA.4 infection triggers more cross-reactive neutralizing antibodies than BA.1
Authors: Richardson Simone I. , Motlou Thopisang , van der Mescht Mieke A. , Lambson Bronwen E. , Everatt Josie , Amoako Daniel Gyamfi , Gottberg Anne von , Wolter Nicole , de Beer Zelda , de Villiers Talita Roma , Bodenstein Annie , van den Berg Gretha , Rossouw Theresa M. , Boswell Michael T. , Ueckermann Veronica , Bhiman Jinal N. , Moore Penny L.
Published: July 2022

SARS-CoV-2 variants of concern (VOCs) differentially trigger neutralizing antibodies with variable cross-neutralizing capacity. Here we show that unlike SARS-CoV-2 Omicron BA.1, which triggered neutralizing antibodies with limited cross-reactivity, BA.4/5 infection triggers highly cross-reactive neutralizing antibodies. Cross-reactivity was observed both in the absence of prior vaccination and also in breakthrough infections following vaccination. This suggests that next-generation vaccines incorporating BA.4, which is spreading globally, might result in enhanced neutralization breadth.
Systematic Bayesian Posterior Analysis Guided by Kullback-Leibler Divergence Facilitates Hypothesis Formation
Authors: Huber Holly A. , Georgia Senta K. , Finley Stacey D.
Published: July 2022

Bayesian inference produces a posterior distribution for the parameters and predictions from a mathematical model that can be used to guide the formation of hypotheses; specifically, the posterior may be searched for evidence of alternative model hypotheses, which serves as a starting point for hypothesis formation and model refinement. Previous approaches to search for this evidence are largely qualitative and unsystematic; further, demonstrations of these approaches typically stop at hypothesis formation, leaving the questions they raise unanswered. Here, we introduce a Kullback-Leibler (KL) divergence-based ranking to expedite Bayesian hypothesis formation and investigate the hypotheses it generates, ultimately generating novel, biologically significant insights. Our approach uses KL divergence to rank parameters by how much information they gain from experimental data. Subsequently, rather than searching all model parameters at random, we use this ranking to prioritize examining the posteriors of the parameters that gained the most information from the data for evidence of alternative model hypotheses. We test our approach with two examples, which showcase the ability of our approach to systematically uncover different types of alternative hypothesis evidence. First, we test our KL divergence ranking on an established example of Bayesian hypothesis formation.

Our top-ranked parameter matches the one previously identified to produce alternative hypotheses. In the second example, we apply our ranking in a novel study of a computational model of prolactin-induced JAK2-STAT5 signaling, a pathway that mediates beta cell proliferation. Here, we cluster our KL divergence rankings to select only a subset of parameters to examine for qualitative evidence of alternative hypotheses, thereby expediting hypothesis formation. Within this subset, we find a bimodal posterior revealing two possible ranges for the prolactin receptor degradation rate. We go on to refine the model, incorporating new data and determining which degradation rate is most plausible. Overall, we demonstrate that our approach offers a novel quantitative framework for Bayesian hypothesis formation and use it to produce a novel, biologically-significant insight.
Ending transmission of SARS-CoV-2: sterilizing immunity using an intranasal subunit vaccine
Authors: Leekha Ankita , Saeedi Arash , Sefat Samiur Rahman , Kumar Monish , Martinez-Paniagua Melisa , Damian Adrian , Kulkarni Rohan , Rezvan Ali , Mosoumi Shalaleh , Liu Xinli , Cooper Laurence JN , Sebastian Manu , Hurst Brett , Varadarajan Navin
Published: July 2022

Immunization programs against SARS-CoV-2 with commercial intramuscular (IM) vaccines prevent disease but not infections. The continued evolution of variants of concern (VOC) like Delta and Omicron has increased infections even in countries with high vaccination coverage. This is due to commercial vaccines being unable to prevent viral infection in the upper airways and exclusively targeting the spike (S) protein that is subject to continuous evolution facilitating immune escape. Here we report a multi-antigen, intranasal vaccine, NanoSTING-NS that yields sterilizing immunity and leads to the rapid and complete elimination of viral loads in both the lungs and the nostrils upon viral challenge with SARS-CoV-2 VOC. We formulated vaccines with the S and nucleocapsid (N) proteins individually to demonstrate that immune responses against S are sufficient to prevent disease whereas combination immune responses against both proteins prevents viral replication in the nasal compartment. Studies with the highly infectious Omicron VOC showed that even in vaccine-naïve animals, a single dose of NanoSTING-NS significantly reduced transmission. These observations have two implications: (1) mucosal multi-antigen vaccines present a pathway to preventing transmission and ending the pandemic, and (2) an explanation for why hybrid immunity in humans is superior to vaccine-mediated immunity by current IM vaccines.
TLR4/NF-κB Signaling Contributes to the Inflammation in Ovary and Inguinal Fats of Polycystic Ovary Syndrome
Authors: Sun Bo , Pan Zimeng , Kuang Hongying , Feng Xiaoling , Hou Lihui , Xu Fang , Song Feifei , Sun Miao
Published: July 2022

Background

Polycystic ovary syndrome (PCOS) is a complex reproductive endocrine disorder. It has highly heterogeneous clinical manifestations which are characterized by biochemical hyperandrogenemia, obesity, insulin resistance, dyslipidemia, anovulation, and polycystic ovaries. However, the etiologies of PCOS are still unclear. Recently, studies have found that the low-grade inflammation contributed to the occurrence of PCOS, and as a critical biomarker indicated the endocrine disruptions in PCOS.

Objective

This study is aimed to investigate the processes and mediators of inflammation in contributing to the development of PCOS.

Methods

Letrozole (LET) induced PCOS rat model was used in this study. Body weight, body temperature, inguinal fats weight, fasting glucose level, ovarian morphology, NF-κB signaling target genes in ovary, and protein expression levels of TLR4 and NF-κB in ovarian and inguinal fats were measured in rats with placebo and LET administrations for 6 and 12 weeks.

Results

PCOS rats, especially with LET intervention for 12 weeks, had higher body weight, inguinal fats weight and fasting glucose level compared to control group. The protein expression levels of TLR4 and NF-κB in cytoplasm of ovarian and inguinal fats were increased in LET-induced PCOS rats compared to control groups, while NF-κB in nucleus were reduced in PCOS rats. The expressions of ACTB, C3, CXCL3, NQO1 and SELP in ovarian were statistically different in PCOS rats induced by LET compared to control groups.

Conclusion

These findings indicated that stimulating TLR4/NF-κB pathway in inguinal fats and ovary tissues contributed to the increased inflammation in LET-induced PCOS rats, which, in turn, exacerbated the phenotype of PCOS including weight gain, adipose tissue accumulation, hyperglycemia and follicular dysplasia.
A phylogenomic approach to resolving interrelationships of polyclad flatworms, with implications for life history evolution
Authors: Goodheart Jessica A. , Collins Allen G. , Cummings Michael P. , Egger Bernhard , Rawlinson Kate A.
Published: July 2022

Platyhelminthes (flatworms) are a diverse invertebrate phylum that are useful for exploring life history evolution. Within Platyhelminthes, only two clades develop through a larval stage: free-living polyclads and parasitic neodermatans. Neodermatan larvae are considered evolutionarily derived, whereas polyclad larvae are hypothesized to be retained from the last common ancestor of Platyhelminthes – and Spiralia – due to ciliary band similarities among polyclad and other spiralian larvae. However, larval evolution has been challenging to investigate within polyclads due to low support for deeper phylogenetic relationships. To investigate polyclad life history evolution, we generated transcriptomic data for 21 species of polyclads to build a well-supported phylogeny for the group. We then used ancestral state reconstruction to investigate ancestral modes of development (direct vs indirect) within Polycladida, and flatworms in general. The resulting tree provides strong support for deeper nodes and we recover a new monophyletic clade of early branching cotyleans. Early branching clades of acotyleans and cotyleans possess diverse modes of development, suggesting a complex history of larval evolution in polyclads that likely includes multiple losses and/or multiple gains. Our ancestral state reconstructions in a previous platyhelminth phylogeny also suggests that similarities in larval morphology between flatworms and other phyla may have re-emerged secondarily or are convergently evolved.
Fast-local and slow-global neural ensembles in the mouse brain
Authors: Delaney Thomas J , O’Donnell Cian
Published: July 2022

Ensembles of neurons are thought to be co-active when participating in brain computations. However, it is unclear what principles determine whether an ensemble remains localised within a single brain region, or spans multiple brain regions. To address this, we analysed electrophysiological neural population data from hundreds of neurons recorded simultaneously across nine brain regions in awake mice. At fast sub-second timescales, spike count correlations between pairs of neurons in the same brain region were stronger than for pairs of neurons spread across different brain regions. In contrast at slower timescales, within- and between-region spike count correlations were similar. Correlations between high-firing-rate neuron pairs showed a stronger dependence on timescale than low-firing-rate neuron pairs. We applied an ensemble detection algorithm to the neural correlation data and found that at fast timescales each ensemble was mostly contained within a single brain region, whereas at slower timescales ensembles spanned multiple brain regions. These results suggest that the mouse brain may perform fast-local and slow-global computations in parallel.

AUTHOR SUMMARY

In this study we analysed publicly available neural population electrophysiology data from nine brain regions in awake mice. To discover neural ensembles, we applied community detection algorithms to the spike count correlation matrices estimated from the data. We repeated the analysis at different timescales, ranging from 10 milliseconds to 3 seconds. We found that at fast timescales<1 s, neural ensembles tended to be localised within single brain regions. In contrast at slower timescales of>1 s, ensembles tended to be include neurons spread across multiple brain regions. Most of this effect was due to high-firing-rate neurons.
A statistical censoring approach accounts for hook competition in abundance indices from longline surveys
Authors: Watson Joe , Edwards Andrew M. , Auger-Méthé Marie
Published: July 2022

Fishery-independent longline surveys provide valuable data to monitor fish populations. However, competition for bait on the finite number of hooks leads to biased estimates of relative abundance when using simple catch-per-unit-effort methods. Numerous bias-correcting instantaneous-catch-rate methods have been proposed, modelling the bait removal times as independent random variables. However, experiments have cast doubts on the many assumptions required for these to accurately infer relative abundance. We develop a new approach by treating some observations as right-censored, acknowledging that observed catch counts are lower bounds of what they would have been in the absence of hook competition. Through simulation experiments we confirm that our approach consistently outperforms previous methods. We demonstrate performance of all methods on longline survey data of eleven species. Accounting for hook competition leads to large differences in relative indices (often −50% to +100%), with effects of hook competition varying between species (unlike other methods). Our method can be applied using existing statistical packages and can include environmental influences, making it a general and reliable method for analyzing longline survey data.
Efficient 3D light-sheet imaging of very large-scale optically cleared human brain and prostate tissue samples
Authors: Schueth Anna , Hildebrand Sven , Samarska Iryna , Sengupta Shubharthi , Kiessling Annemarie , Herrler Andreas , Hausen Axel zur , Capalbo Michael , Roebroeck Alard
Published: July 2022

The ability to image human tissue samples in 3D, with both cellular resolution and a large field of view (FOVs), can improve fundamental and clinical investigations. Here, we demonstrate the feasibility of light-sheet imaging of ∼5 cm3sized formalin fixed human brain and up to ∼7 cm3sized formalin fixed paraffin embedded (FFPE) prostate cancer samples, processed with the FFPE-MASH protocol. We present a light-sheet microscopy prototype, the cleared-tissue dual view Selective Plane Illumination Microscope (ct-dSPIM), capable of fast, 3D high-resolution acquisitions, of cubic centimetre sized cleared tissue. We used Mosaic scans for fast 3D overview scans of entire tissue samples or higher resolution overviews of large ROIs with various speeds: a) Mosaic 16 (16.4 µm isotropic resolution, ∼ 1.7 hr/cm3), b) Mosaic 4 (4.1 µm isotropic resolution, ∼ 5 hr/cm3) and c) Mosaic 0.5 (0.5 µm near isotropic resolution, ∼15.8 hr/cm3). We could visualise ROIs around the border of human brain area V1/V2, and could demonstrate suitable imaging quality for Gleason score grading in prostate cancer samples. We show that ct-dSPIM imaging is an excellent technique to quantitatively assess entire MASH prepared large-scale human tissue samples in 3D, with considerable future clinical potential in prostate cancer.
Advected percolation in the actomyosin cortex drives amoeboid cell motility
Authors: García-Arcos Juan Manuel , Ziegler Johannes , Grigolon Silvia , Reymond Loïc , Shajepal Gaurav , Cattin Cédric J. , Lomakin Alexis , Müller Daniel , Ruprecht Verena , Wieser Stefan , Voituriez Raphael , Piel Matthieu
Published: July 2022

Spontaneous locomotion is a common feature of most metazoan cells, generally attributed to the fundamental properties of the actomyosin network. This force-producing machinery has been studied down to the most minute molecular details, especially in lamellipodium-driven migration. Nevertheless, how actomyosin networks work inside contraction-driven amoeboid cells still lacks unifying principles. Here, using stable motile blebs as a model amoeboid motile system, we image the dynamics of the actin cortex at the single filament level and reveal the co-existence of three phases of the actin network with distinct rheological properties. Physical modelling shows that these three phases organize spontaneously due to a rigidity percolation transition combined with an active advection of the percolated network. This spontaneous spatial organization of the mechanical properties of the actin network, which we propose to call advected percolation, constitutes a minimal and generic locomotion mechanism. It explains, down to the single actin filament level and up to the scale of the entire cell, how amoeboid cells can propel efficiently through complex 3D environments, a feature shared by immune and cancer cells.